The DOI matches its Crossref record; 67 of the 67 references it cites were found in a registry or an index; 19 of the 61 sources its claims cite were checked for support.
Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records
Open accessPublished version of a preprint
Abstract
We introduce the OSI-450, the SICCI-25km and the SICCI-50km climate data records of gridded global sea-ice concentration. These three records are derived from passive microwave satellite data and offer three distinct advantages compared to existing records: first, all three records provide quantitative information on uncertainty and possibly applied filtering at every grid point and every time step. Second, they are based on dynamic tie points, which capture the time evolution of surface characteristics of the ice cover and accommodate potential calibration differences between satellite missions. Third, they are produced in the context of sustained services offering committed extension, documentation, traceability, and user support. The three records differ in the underlying satellite data (SMMR & SSM/I & SSMIS or AMSR-E & AMSR2), in the imaging frequency channels (37 GHz and either 6 or 19 GHz), in their horizontal resolution (25 or 50 km), and in the time period they cover. We introduce the underlying algorithms and provide an evaluation. We find that all three records compare well with independent estimates of sea-ice concentration both in regions with very high sea-ice concentration and in regions with very low sea-ice concentration. We hence trust that these records will prove helpful for a better understanding of the evolution of the Earth's sea-ice cover.
Overview
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Written from the paper’s full text.
TL;DR
The paper introduces three new gridded global sea-ice concentration climate data records—OSI-450, SICCI-25km, and SICCI-50km—derived from passive microwave satellite data with dynamic tie points, per-pixel uncertainty estimates, and filtering information. Evaluation against independent 0 % and 100 % sea-ice concentration estimates shows good agreement, with SICCI-50km generally most accurate but at coarser spatial resolution.
Key findings
- The three CDRs differ in sensors, frequencies, resolution, and period: OSI-450 uses SMMR/SSM/I/SSMIS at 19/37 GHz on 25 km grids from January 1979 to December 2015; SICCI-25km uses AMSR-E/AMSR2 at 19/37 GHz on 25 km grids from June 2002 to October 2011 and July 2012 to May 2017; SICCI-50km uses AMSR-E/AMSR2 at 6/37 GHz on 50 km grids over the same AMSR periods.
- At open water (0 % SIC), OSI-450 and SICCI-25km have mean SIC of 0 % or −0.2 % in summer and ∼0.5 % in winter, with precision (1 standard deviation) of 1 %–2 %; SICCI-50km has summer ∼−0.5 % and winter 0.2 %–0.5 %, with the best precision.
- At closed ice (100 % SIC), SICCI-50km has the smallest bias, with mean SIC 99.5 % in the Arctic and 99.3 % in the Antarctic and standard deviation of the mean ∼2 % and ∼3 %; OSI-450 and SICCI-25km have mean SIC ∼98 % in the Arctic and ∼98.5 % in the Antarctic, with standard deviation of the mean 3.5 %–4.0 %.
- Algorithm uncertainty σ_algo is typically 2 %–3 % SIC, smearing uncertainty σ_smear reaches up to 40 % SIC at the ice edge, and total uncertainty is dominated by σ_smear; mean total uncertainty at 0 % SIC is ∼2 % in summer and ∼2.5 % in winter for OSI-450/SICCI-25km, and ∼1.5 % in summer and ∼2 % in winter for SICCI-50km.
Methods
- Input data are passive microwave brightness temperatures from SMMR, SSM/I, SSMIS, AMSR-E, and AMSR2, plus ERA-Interim 10 m wind speed, 2 m air temperature, and total column water vapour for atmospheric correction.
- The SIC algorithm is a hybrid, self-optimizing combination of a best-open-water algorithm and a best-closed-ice algorithm, with dynamic tie points trained separately per instrument and hemisphere using a [−7; +7 day] sliding window; processing includes RTM-based atmospheric correction, open-water filtering, a consolidated-ice-curve correction, land-spillover correction, and Level 2/3/4 gridding and gap filling.
- Evaluation uses the Round Robin Data Package v2 ground-truth locations for 0 % SIC (2002–2015) and 100 % SIC (2007–2016), plus time-series monitoring of algorithm tuning statistics and open-water-filter stability; uncertainties are evaluated against retrieval errors at 0 % and 100 % SIC.
Limitations
- The paper states that the open-water filter removes some true low-concentration ice, especially in the marginal ice zone, and this effect is not included in the uncertainty variables; melt-pond water is misinterpreted as open water, thin sea ice (<30 cm) is underestimated, and neither effect is included in the uncertainty fields.
- The paper states that interpolated values where satellite data were missing should be used with caution, especially spatial interpolation; uncertainty variables are not interpolated, and days with no satellite data are missing from the records. Land-spillover correction is imperfect, leaving some false coastal sea ice, especially for OSI-450 and SICCI-50km, and may remove some true coastal ice; fresh and brackish water ice is not handled with dedicated tie points.
- The paper states that evaluation covers only 0 % and 100 % SIC, not the intermediate marginal-ice-zone range, due to lack of high-quality validation data; uncertainties are slightly underestimated at 100 % SIC for OSI-450 and slightly overestimated at 0 % SIC. The text also makes evident that SICCI-50km’s open-water-filter temporal consistency is poorer because its SIC channels (6/37 GHz) differ from the 19/37 GHz channels used for the filter, and that atmospheric correction is less effective in the SMMR era.
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Claims the paper makes
93 Own interpretation · 76 No basis given · 57 Own result · 22 Own method · 12 Sources not found · 12 No full text of the sources · 8 Partly supported · 6 Supported · 5 Not checked yet · 3 Supported so far · 2 Couldn’t confirm · accuracy not yet measured
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“In many cases, these algorithms are evolutions of those already applied in the previous version of the EUMETSAT OSI SAF CDR (OSI-409, Tonboe et al., 2016).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3 Algorithms and processing details
What the sources say
- Partly supportedcites Tonboe et al., 2016 sourceExperimental — accuracy not yet measured
Section 2.3 describes the EUMETSAT record’s hybrid Bristol–Bootstrap algorithm, supporting the claim that the record uses established sea-ice concentration algorithms. The References name OSI-409 and OSI-409a, but the paper does not say which algorithms OSI-409 used or establish that the algorithms in later SIC CDRs evolved from it. (LLM, conf=0.80)
hedged- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Niederdrenk and Notz (2018) found that observational uncertainty is the main source of uncertainty for estimating at which level of global warming the Arctic will lose its summer sea-ice cover.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 1 Introduction
What the sources say
- Supportedcites Niederdrenk and Notz (2018) source
Section 3.1 finds that the warming level for an ice-free summer Arctic differs more between observational estimates (about 1.7°C versus 2.3°C) than within the ensemble uncertainty range for the high-sensitivity estimate (1.5°C–1.9°C). The Summary also says observational uncertainty dominates additional uncertainty from internal variability. (LLM, conf=0.93)
plaindirect- Asserted: passes — The authors put it forward as true.
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- Supported
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In the paper
“This is, for example, reflected by substantial differences between existing estimates of sea-ice concentration from various algorithms (e.g.Ivanova et al., 2015;Comiso et al., 2017b).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 1 Introduction
What the sources say
- Supportedcites Ivanova et al., 2015 source
Section 5.1 describes variability in sea-ice concentration produced by different algorithms and compares their sensitivity to error sources. The abstract also reports a systematic evaluation of 30 algorithms, supporting the claim that their estimates differ substantially. (LLM, conf=0.88)
- Not matchedcites Comiso et al., 2017b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
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- Supported
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In the paper
“Satellite-retrieved records of Arctic and Antarctic sea-ice concentration differ widely in their estimates of a specific sea-ice concentration on a given day in a given region (e.g.Ivanova et al., 2015;Comiso et al., 2017a).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 1 Introduction
What the sources say
- Supportedcites Ivanova et al., 2015 source
The Introduction reports differences among sea-ice concentration algorithms of 5–12% at intermediate concentrations and up to 12% in a particular Arctic region. Section 4.1 also reports differing retrieval biases in both hemispheres. These passages support the broad point that satellite-derived records can give substantially different concentration estimates, though the size of the difference depends on conditions. (LLM, conf=0.86)
- Not matchedcites Comiso et al., 2017a
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Supported
The cited sources that could be checked couldn’t confirm or dispute this claim.
In the paper
“As in Tonboe et al. (2016), the CI training sample is based on the results of the NASA Team (NT) algorithm (Cavalieri et al., 1984): locations for which the NT value is greater than 95 % are used as a representation of 100 % ice (Kwok, 2002).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.3 Dynamical tuning of the SIC algorithm
What the sources say
- Not checked — no full text of the sourcecites Cavalieri et al., 1984 source
- Could not verifycites Kwok, 2002 sourceExperimental — accuracy not yet measured
The Data Sets and Approach section identifies the NASA Team algorithm, but does not describe a >95% threshold or closed-ice training samples. The Results and Discussion and Conclusions discuss uncertainty in winter-pack ice concentrations, without assessing whether NT values above 95% can represent 100% ice. Searches for the threshold and training-sample criterion found no such passage in our copy. (LLM, conf=0.76)
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“Values of K were tuned using a footprint simulator and selected cloud-free scenes of the marginal ice zone imaged by the Moderate-Resolution Imaging Spectroradiometer (MODIS) as described in Tonboe et al. (2016).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.5 Uncertainties
What the sources say
- Partly supportedcites Tonboe et al. (2016) sourceExperimental — accuracy not yet measured
Section 1.4 describes selecting cloud-free MODIS scenes with different ice concentrations, and Section 2.4.2 describes using them in a satellite-footprint simulation. Those sections use the simulation to estimate smearing uncertainty; they do not say that values of K were tuned with it. (LLM, conf=0.86)
plaindirect- Asserted: passes — The authors put it forward as true.
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- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“A complete, 100 % cover of thin sea ice will be retrieved with a lower concentration, depending on the thickness (Ivanova et al., 2015).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.3 Caveats and known limitations
What the sources say
- Supportedcites Ivanova et al., 2015 source
Section 3.4 describes testing the algorithms on areas of approximately 100% thin-ice cover. Section 5.4 reports that the algorithms underestimated sea ice concentration for ice up to 35 cm thick and that their sensitivity varied with thickness. (LLM, conf=0.93)
hedgeddirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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- Supported
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In the paper
“All SIC algorithms based on the passive microwave data are very sensitive to melt-pond water on top of the ice (Kern et al., 2016).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.3 Caveats and known limitations
What the sources say
- Partly supportedcites Kern et al., 2016 sourceExperimental — accuracy not yet measured
The Conclusions report that all eight algorithms investigated underestimated sea-ice concentration when melt ponds covered 40% of the ice. But the paper does not establish that all passive-microwave SIC algorithms are *very* sensitive: Section 4.3.3 says Near90_lin is sensitive only to some degree, and the Conclusions identify Bootstrap_p and NASA Team as having the lowest sensitivity. Page numbers were not supplied. (LLM, conf=0.88)
plaindirect- Asserted: passes — The authors put it forward as true.
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- Partly supported
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Our algorithms do not rely on such a channel (Sect.3.4.2).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 2.1 Input satellite data
plain- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although not identical, the spatial resolution of the channels needed for the SIC algorithms is similar for the three coarse-resolution sensor series (SMMR, SSM/I, and SSMIS) with about 70×45 km instantaneous field-of-view (iFoV) diameters for the 19 GHz frequency channels, and 38 × 30 km for the 37 GHz ones (Table 2).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 2.1 Input satellite data
hedged- Asserted: passes — The authors put it forward as true.
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- Probably not a substantial claim. 51
- It may state two separate claims as one. 99
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“The L2 chain holds an iteration (marked by the”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.1 Overview of the processing chain
What the sources say
- Supportedcites Tonboe et al., 2016 source
Section 2.2 (page not provided) says sea ice concentration is solved by iteration and that Andersen et al. (2006b) describes the correction procedure in detail. This supports the claim that the cited workflow includes an iteration rooted in those developments. (LLM, conf=0.91)
- Not checked — no full text of the sourcecites Andersen et al., 2006 source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“In the Arctic the latter has been found to be linearly related to global-mean temperature (e.g.Gregory et al., 2002;Niederdrenk and Notz, 2018), atmospheric CO 2 concentration (e.g.Johannessen, 2008;Notz and Marotzke, 2012) and anthropogenic CO 2 emissions (Zickfeld et al., 2012;Herrington and Zickfeld, 2014;Notz and Stroeve, 2016).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 1 Introduction
What the sources say
- Not checked — no full text of the sourcecites Gregory et al., 2002 source
- Partly supportedcites Niederdrenk and Notz, 2018 sourceExperimental — accuracy not yet measured
Section 2.2 reports a linear relationship between global-mean temperature and Arctic sea-ice area in observations and simulations. The citing sentence refers to sea-ice extent, whereas the paper explicitly uses area rather than extent (Section 2.1). This citation is attached to the temperature relationship, not the separate claims about CO₂ concentration or emissions. (LLM, conf=0.86)
- Not checked — no full text of the sourcecites Johannessen, 2008 source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The cited sources that could be checked couldn’t confirm or dispute this claim.
In the paper
“OSI-450 has been released by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF, http://www.osi-saf.org/,last access: 15 June 2018) and is a fully revised version of its predecessor OSI-409 (Tonboe et al., 2016).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 1 Introduction
What the sources say
- Could not verifycites Tonboe et al., 2016 sourceExperimental — accuracy not yet measured
The Data availability section says the OSI SAF sea ice concentration record was available for download, and the References identify OSI-409a. The Future work section describes a later update as planned, but our copy does not mention OSI-450 or say that it was released as a fully revised version of OSI-409 (searched: OSI-450, OSI-409, revised version). (LLM, conf=0.74)
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Could not verify
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“While WFs are effective at removing false sea ice in openwater regions, they will always falsely remove (detect as open water) some amount of low-concentration (and/or thin) sea ice, especially along the ice edge (Ivanova et al., 2015).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.2 Open-water filtering
What the sources say
- Partly supportedcites Ivanova et al., 2015 sourceExperimental — accuracy not yet measured
Section 4.4 (page unavailable) says open-water/weather filters efficiently remove weather-related noise over open water, but also set some low-concentration ice pixels to 0% SIC. The paper does not establish that filters will always remove ice or that they specifically remove thin ice. The Introduction links low-concentration retrieval uncertainty to the marginal ice zone, but does not show that false removal is especially frequent at the ice edge. (LLM, conf=0.86)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Indeed, GR2219v is mostly effective at detecting water vapour effects, while GR3719v is effective at screening cloud liquid water and wind-roughening effects (Cavalieri et al., 1995).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.2 Open-water filtering
What the sources say
- Supportedcites Cavalieri et al., 1995 source
The Discussion of Results (Fig. 6) says the GR(22/19) threshold is effective only for water vapor. It also reports that the GR(37/19) threshold filters cloud liquid water and wind effects, among others. The claim accurately summarizes those distinct roles. (LLM, conf=0.92)
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Note that, although this swath-based correction step is quite efficient at reducing land spillover contamination, a statistical method similar to that of Cavalieri et al. (1999) still had to be applied at Level 3; this is further discussed in Sect.5.2.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.6 Other relevant algorithms and processing steps
What the sources say
- Supportedcites Cavalieri et al. (1999) source
Section 3.3 describes an automated land-to-ocean spillover correction using a grid of coastal pixels and a matrix of minimum ice concentrations derived from monthly averages. That supports citing Cavalieri et al. (1999) as the model for a similar statistical correction. The swath-based step and its efficiency are the citing authors’ own description, not a finding attributed to this source. (LLM, conf=0.90)
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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It may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“However, there is no unique way to derive nor to present uncertainties in EO data (Merchant et al., 2017).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.5 Uncertainties
What the sources say
- Supportedcites Merchant et al., 2017 source
The Conclusion says methods of quantifying uncertainty vary across essential climate variables and that the form of uncertainty information must differ with the variable. Section 8 adds that no single strategy for providing uncertainty information is optimal for every variable. Together, these support the claim about deriving and presenting uncertainty in EO data. (LLM, conf=0.91)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“All three share the same algorithm baseline, which is both a continuation of the EUMETSAT OSI SAF SIC approach (Andersen et al., 2006;Tonboe et al., 2016) and a series of innovations contributed to mostly by the ESA CCI activities.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.1 Discussion
What the sources say
- Not checked — no full text of the sourcecites Andersen et al., 2006 source
- Supportedcites Tonboe et al., 2016 source
The citation is attached to the claim that the algorithm baseline continues the EUMETSAT OSI SAF SIC approach. In Future work (page unavailable), Tonboe et al. state that the near-real-time OSISAF product and their climate data record use the same algorithms and similar methodologies. The later clause about ESA CCI innovations is not attributed to this citation. (LLM, conf=0.90)
plainn = 3- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Among other data sets, the RRDP v2 holds ground-truth locations for openwater cases (OW, 0 % SIC) for the period 2002-2015, as well as ground-truth locations for closed ice (CI, 100 % SIC) for the period 2007-2016.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.2 Evaluation against ground truth
What the sources say
- Partly supportedcites Ivanova et al. (2015) sourceExperimental — accuracy not yet measured
Section 3.2 (page not provided) confirms that the RRDP contains open-water (0% SIC) and closed-ice (100% SIC) validation locations. It gives different coverage periods: open-water AMSR-E data cover 2002–2011, closed-ice AMSR-E data cover 2007–2011, and the full data set extends only through 2011. The paper does not establish the claimed RRDP v2 coverage through 2015 and 2016. (LLM, conf=0.88)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Mixing the two types of sensors (coarse resolution with medium resolution) into a single CDR would require careful consideration of the mismatch in spatial resolution and possibly advanced enhanced resolution methods (e.g.Long and Daum, 1998;Long and Brodzik, 2016), which are not used here.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.1 Discussion
What the sources say
- Not checked — no full text of the sourcecites Long and Daum, 1998 source
- Supportedcites Long and Brodzik, 2016 source
Section IV (Gridding and Reconstruction) identifies enhanced-resolution image reconstruction methods and explains that the high-resolution product optimizes resolution separately for each channel rather than forcing channels to match. This supports the citation’s role as an example of enhanced-resolution methods; the statement that those methods are not used in the citing study is the citing authors’ own description. (LLM, conf=0.90)
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
Every source the paper cites for this claim was checked and supports it.
In the paper
“Therefore, a very similar algorithm performance in both hemispheres is not a surprise and agrees with earlier findings (e.g.Ivanova et al., 2015).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.1 Discussion
What the sources say
- Supportedcites Ivanova et al., 2015 source
Section 4.1 reports closely matching standard deviations for the same algorithms in the Northern and Southern Hemispheres: 3.8% versus 3.5% for CV at 15% sea-ice concentration, and 3.1% versus 2.9% for BR at 75%. This supports the cited point about similar algorithm performance; “not a surprise” is the citing authors’ interpretation. (LLM, conf=0.88)
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The ERA-Interim reanalysis starts in January 1979 and is available throughout the time period of our CDRs.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 2.2 ERA-Interim data
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“It is noteworthy that the AMSR2 data are not from an FCDR, but rather from an archive of an operational data stream.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 2.1 Input satellite data
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“All three sea-ice concentration (SIC) CDRs share the same algorithms, processing chains, and data format.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 1 Introduction
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“first, all three records provide quantitative information on uncertainty and possibly applied filtering at every grid point and every time step.”
- Also stated in: § 1 Introduction · plain
“First, all our three records provide quantitative information on uncertainty and access to filtered as well a raw values at every grid point and every time step.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > Abstract
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“The two medium-resolution radiometers AMSR-E and AMSR2 have finer resolutions at these channels (27 × 16 km and 14 × 9 km), accompanied by increased sampling (10 × 10 km instead of 25 × 25 km for SSM/I).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 2.1 Input satellite data
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In the paper
“The first of our three climate data records (CDRs) is referred to as OSI-450.It is based on coarse-resolution (30-60 km) passive microwave (PMW) satellite data that are available from October 1978 onwards.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 1 Introduction
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In the paper
“Vector u is computed by principal component analysis (PCA) and is the direction with highest variance in the CI T B samples.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.2 A hybrid, self-tuning, self-optimizing sea-ice concentration algorithm
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In the paper
“A new sea-ice concentration algorithm was developed during the ESA CCI Sea Ice projects and is used for the three CDRs.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.2 A hybrid, self-tuning, self-optimizing sea-ice concentration algorithm
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In the paper
“Conversely to BRI, we do not impose H on the projection plane.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.2 A hybrid, self-tuning, self-optimizing sea-ice concentration algorithm
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“This iteration implements two key correction schemes: the atmospheric correction algorithm at low-concentration range (Sect.3.4.1)and a novel correction for systematic errors at high-concentration range (Sect.3.4.3).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.1 Overview of the processing chain
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In the paper
“Both T B spaces feature two higher-frequency channels with same wavelength but alternate polarization (37 GHz in both cases), and a lower-frequency vertically polarized channel (19V or 6V ).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.2 A hybrid, self-tuning, self-optimizing sea-ice concentration algorithm
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In the paper
“We call the SIC algorithm a hybrid algorithm because it combines two other SIC algorithms: one that is tuned to perform better over open-water and low-concentration conditions (named B OW for best open water), and one that is tuned to perform better over closed-ice and high-concentration conditions (named B CI for best closed ice).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.2 A hybrid, self-tuning, self-optimizing sea-ice concentration algorithm
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In the paper
“In winter Arctic conditions, it is typical to observe that B CI (T ) values are consistently lower than 100 % (down to 85 %-90 %) for old ice (low values of DAL) and consistently higher than 100 % (up to 105 %-110 %) for new and first-year ice (high values of DAL).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.3 Reducing systematic errors at high-concentration range
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In the paper
“In that particular example, the improvement is mostly for OW conditions and limited for CI conditions.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.2 A hybrid, self-tuning, self-optimizing sea-ice concentration algorithm
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In the paper
“The combination equation is quite simply a linear weighted average of B OW and B CI results, where w ow is the open-water weight and SIC is expressed as sea-ice fraction [0; 1]:”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.2 A hybrid, self-tuning, self-optimizing sea-ice concentration algorithm
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In the paper
“We rather rotate the plane around u and seek the optimum rotation an- gle θ that yields best SIC accuracy.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.2 A hybrid, self-tuning, self-optimizing sea-ice concentration algorithm
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In the paper
“Like in BRI we seek an optimum”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.2 A hybrid, self-tuning, self-optimizing sea-ice concentration algorithm
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In the paper
“However, careful analysis of the spread of consolidated ice samples along the ice line reveals that systematic deviations exist and are stable with time.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.3 Reducing systematic errors at high-concentration range
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In the paper
“The smearing uncertainty is largest, up to 40 % SIC, at the ice edge and low, near 0 % SIC, in areas where all contributing satellite footprints cover the same SIC (e.g.open water).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.1 The data records and selected examples
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In the paper
“The same effect is observed for the standard deviations resulting from uncorrected SMMR T B data (purple thin line), which is consistent with a central frequency of 18.0 GHz (Table 2).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
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In the paper
“These regions generally present negative SICs before correction and are brought closer to 0 % SIC by the process of atmospheric correction.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.3 Reducing systematic errors at high-concentration range
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In the paper
“The SICCI-50km SIC has increased granularity due to the lower resolution of the 6 GHz channels compared to the 19 GHz channels.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.1 The data records and selected examples
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In the paper
“The two SIC fields on the top row are rather similar except in the marginal ice zone, where the higher resolution of the AMSR2 instrument (SICCI-25km) with respect to that of the SSMIS (OSI-450) leads to resolving finer details.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.1 The data records and selected examples
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In the paper
“This difference in frequency yields better accuracy for SICCI-25km than OSI-450 when using uncorrected T B data (not shown) but this effect is mostly cancelled after atmospheric correction (though not fully in SH, bottom panel).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
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In the paper
“During summer, σ algo is larger by a few percent, and the increased variability inside the ice pack yields higher σ smear , leading to larger σ tot .”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.1 The data records and selected examples
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In the paper
“It is lower for sea ice than for open water because the global variability of closed sea ice is lower than the SIC variability over open water.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.1 The data records and selected examples
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In the paper
“The time series in Fig. 8 illustrate that the algorithms behave as expected across instruments and are effectively tuned to achieve zero bias and a small retrieval noise for each instrument in the time series.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
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In the paper
“Over closed-ice conditions (inside the 70 % SIC isoline), the regional patterns of the correction are clearly visible and seem to match variations in sea-ice age”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.3 Reducing systematic errors at high-concentration range
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In the paper
“SICCI-50km (green) is more accurate than both SICCI-25km and OSI-450, by nearly 1 % in NH and 0.5 % in SH.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
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In the paper
“OSI-450 and SICCI-25km provide a slightly larger bias with a mean SIC of ∼ 98 % in the Arctic and ∼ 98.5 % in the Antarctic, which also comes with a higher SIC standard deviation of the mean: 3.5 % to 4.0 %.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.2 Evaluation against ground truth
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In the paper
“Distributions for SICCI-50km are considerably narrower (Fig. 11c, f) and, in comparison to OSI-450 and SICCI-25km, have a modal value closer to 100 %.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.2 Evaluation against ground truth
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In the paper
“For SICCI-50km, the accuracy varies more than for the other two CDRs: summer is ∼ -0.5 % and winter is 0.2 % to 0.5 %.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.2 Evaluation against ground truth
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In the paper
“Figure 12c, d further illustrate that SICCI-50km provides the smallest bias (best accuracy) in both hemispheres with mean SICs of 99.5 % and 99.3 % for the Arctic and Antarctic.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.2 Evaluation against ground truth
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In the paper
“For open water, SIC = 0 % (Fig. 12a, b), we find that mean SIC total uncertainties differ by less than 0.3 % between OSI-450 and SICCI-25km and take values of ∼ 2 % during summer and of ∼ 2.5 % during winter.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.3 Evaluation of the uncertainties
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In the paper
“However, coastal correction procedures are not perfect, and some false sea-ice remains along some coastlines, especially for OSI-450 and SICCI-50km because of the larger footprint of the instruments.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.3 Caveats and known limitations
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In the paper
“Although the filter is efficient at detecting and removing weather-induced noise (false ice) over open water, it also has the effect of removing some amount of true low-concentration ice, especially in the marginal ice zone.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.3 Caveats and known limitations
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In the paper
“For SICCI-50km, the mean SIC total uncertainty is smaller than for the other two CDRs -particularly during summer in the Northern Hemisphere, with ∼ 1.5 % compared to ∼ 2 % in winter.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.3 Evaluation of the uncertainties
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In the paper
“The SICCI-25km curves are close to the OSI-450 ones, but at a slightly larger value of 11 %, with a seasonal variation range of about 2 %.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
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In the paper
“For both hemispheres, we find that the precision of OSI-450 and SICCI-25km SIC CDRs are similar to each other and poorer than for SICCI-50km, which is in line with the findings in Fig. 8.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.2 Evaluation against ground truth
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In the paper
“They are in any case well below the 15 % threshold throughout the data record and very little change is observed when transitioning between sensors.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
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In the paper
“The footprint of the AMSR-E and AMSR2 channels used in the ESA CCI CDRs (SICCI-25km and SICCI-50km) are much more compatible with the 25 × 25 km (SICCI-25km) and 50×50 km (SICCI-50km) target grids, so that their grid spacing is closer to the true resolution.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.3 Caveats and known limitations
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- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“During winter (blue curves) OSI-450 and SICCI-25km are skewed a bit towards negative SIC in the Arctic but not in the Antarctic.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.2 Evaluation against ground truth
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The OSI-450 curves are very stable with time and increase only slightly from around 9 % SIC at the beginning of the period to around 10.5 % SIC at the end.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Although there was always at least one satellite mission carrying a relevant passive microwave instrument after October 1978, a few data gaps exist in the satellite data record that are too short to appear in Fig. 1.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.3 Conclusions
What the sources say
- Not matchedcites Fig. 1
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“These regions generally present negative SICs before correction and are brought closer to 0 % SIC by the process of atmospheric correction.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.3 Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Based on similar frequency channels at 19 and 37 GHz, the OSI-450 and SICCI-25km CDRs achieve similar accuracies, both in the time-series plots of internal tuning parameters (Sect.4.2.1) and when validated against ground-truth (Sect.4.2.2).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.1 Discussion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Over consolidated sea ice, the retrieval accuracy is somewhat poorer (3.5 % to 4 % SIC) and has limited low bias (2 % SIC in NH, 1 % in SH).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.1 Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Over open water, the retrieval accuracy of these two CDRs is as good as 1.5 % to 2 % SIC (1 standard deviation) and without biases.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.1 Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Time-series plots document that the dynamic tuning of the SIC algorithms and of the OWF perform as expected, and that temporal consistency is mostly achieved despite the changes of channel frequencies and calibration between sensors.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.1 Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Uncertainties are systematically documented in the final products and have carefully been evaluated.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.3 Conclusions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Over consolidated sea ice, the accuracy is better than 2.5 % SIC and the bias is limited to below 1 %.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.1 Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Overlap of satellite missions and the 9-month data gap between AMSR-E and AMSR2 operations are clearly visible from Fig. 1.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.3 Conclusions
What the sources say
- Not matchedcites Fig. 1
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
In the paper
“In their most recent update (GCOS-IP, 2016), they request that reliable observational records of sea-ice concentration are made available to the climate research community.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 1 Introduction
What the sources say
- Not matchedcites GCOS-IP, 2016
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Slight changes in incidence angle or wavelengths between the sensor series can be compensated for by the algorithms, but it is harder or even impossible to achieve temporal consistency in the event of sudden loss of channels.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 2.1 Input satellite data
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“which hinders a robust evaluation and bias correction of climate models, and in particular hinders a robust estimate of the future evolution of the Arctic sea-ice cover.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 1 Introduction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“These data are also at the heart of the two currently most widely used seaice concentration algorithms, namely the NASA Team algorithm (Cavalieri et al., 1984) and the bootstrap algorithm (Comiso et al., 2017b).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 1 Introduction
What the sources say
- Not checked — no full text of the sourcecites Cavalieri et al., 1984 source
- Not matchedcites Comiso et al., 2017b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For any of these applications, the reliability of the underlying sea-ice concentration record is crucial.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 1 Introduction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Scattering, reflection, and emission in the atmosphere add or subtract contributions to the radiated signal, and challenge our ability to accurately quantify seaice concentration.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 2.2 ERA-Interim data
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
In the paper
“the 23.0 GHz channels of the SMMR instrument have been highly unstable since their launch, and eventually ceased to function on 11 March 1985 (Njoku et al., 1998).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 2.1 Input satellite data
What the sources say
- Not matchedcites Njoku et al., 1998
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Third, they are produced in the context of sustained services offering committed extension, documentation, traceability, and user support.”
- Also stated in: § 1 Introduction · plain
“Third, they are produced in the context of sustained services offering committed extension, documentation, traceability, and user support.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Also stated in: § 1 Introduction · plain
In the paper
“Such a wavelength is typically used in filtering weather effects in other SIC CDRs (e.g.Meier et al., 2017).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 2.1 Input satellite data
What the sources say
- Not checked — no full text of the sourcecites Meier et al., 2017 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“These two SICCI CDRs are released by the European Space Agency (ESA) Climate Change Initiative (CCI, http://cci.esa.int/, last access: 15 June 2018) programme.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 1 Introduction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Second, they are based on dynamic tie points, which capture the time evolution of surface characteristics of the ice cover and accommodate potential calibration differences between satellite missions.”
- Also stated in: § 1 Introduction · plain
“Second, they are based on dynamic tie points, which capture the time evolution of surface characteristics of the ice cover and help to minimize the impact of sensor drift and change in satellite sensor.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Also stated in: § 1 Introduction · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Building a consistent data record requires methodologies that carefully intercalibrate and tune the algorithms to yield similar results when using all these sensors.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 2.1 Input satellite data
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“as is much of the heat and moisture transfer between the ocean and the atmosphere (e.g.Maykut, 1978).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 1 Introduction
What the sources say
- Not checked — no full text of the sourcecites Maykut, 1978 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The effective field-ofview (eFoV) diameter includes the two effects and is a better measure of the true footprint of the instrument.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 2.1 Input satellite data
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The values of θ OW and θ CI will vary with the exact frequencies, calibration, or viewing angle of the instrument (Table 2), as well as with the OW and CI signatures that exhibit regional, seasonal, and interannual variations.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.2 A hybrid, self-tuning, self-optimizing sea-ice concentration algorithm
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The varying signature of sea-ice and ocean emissivity with time and hemisphere, the different frequencies of the 19 and 37 GHz channels for different instruments, and the varying effects of atmospheric correction all prevent the adoption of fixed thresholds.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.2 Open-water filtering
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The new hybrid, self-optimizing algorithms described in this section can always be tuned to available training data (see Sect. 3.3) and deliver optimum and time-consistent performance.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.2 A hybrid, self-tuning, self-optimizing sea-ice concentration algorithm
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These fields can and will typically exhibit data gaps, e.g. in case of missing satellite data.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.1 Overview of the processing chain
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“The NOAA/NSIDC sea ice concentration CDR uses the Cavalieri et al. (1992) thresholds, with the exception of Southern Hemisphere processing for SSMIS F17, where the GR3719v threshold is set to 0.053 (Algorithm Theoretical Basis Document for Meier et al., 2017).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.2 Open-water filtering
What the sources say
- Not matchedcites Cavalieri et al. (1992)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Meier et al., 2017 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“(e) compensate for trends potentially arising from the use of NWP reanalysed data to correct the T B (see Sect. 3.4.1).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.3 Dynamical tuning of the SIC algorithm
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“For example, Spreen et al. (2008) adapted the GR3719v threshold to 0.045 and GR2219v to 0.040 when processing seaice concentration with AMSR-E data.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.2 Open-water filtering
What the sources say
- Not checked — no full text of the sourcecites Spreen et al. (2008) source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This, however, fails to recognize that the scatter of the closed-ice points around the line and that of open-water T B samples around the point H are anisotropic in the (19V , 37V , 37H ) T B space.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.2 A hybrid, self-tuning, self-optimizing sea-ice concentration algorithm
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“All T B data falling below the GR3719v isoline will result in GR3719v > T and will thus be flagged as OW (SIC = 0 %) by the GR3719v test.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.2 Open-water filtering
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This is a better approach than computing WFs from daily averaged gridded T B data, which will smooth and smear the sea-ice edge region, as well as rapidly changing weather effects such as cloud liquid water content or wind roughening.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.2 Open-water filtering
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This is an illustration of how WFs based on this gradient ratio will not only successfully detect false sea ice as open water, but also wrongly result in ice-free conditions where some true sea ice should have been observed.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.2 Open-water filtering
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“indicating that a combination of DAL (right panel) and ice curve correction (left panel) could be used for sea-ice type (if not age) classification studies.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.3 Reducing systematic errors at high-concentration range
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Spatially and temporally varying uncertainty estimates for each and every SIC value are required of state-of-the-art CDRs (GCOS-IP, 2016).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.5 Uncertainties
What the sources say
- Not matchedcites GCOS-IP, 2016
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- Not matched
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“It is noteworthy that full advantage of the overlap of satellite missions (see Fig. 1 and Table 2) was taken in order to reduce the occurrence of missing data areas as much as possible in the daily composited fields.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.6 Other relevant algorithms and processing steps
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“This consolidated ice curve defines the SIC 100 % isoline during the second iteration of Level 2, and -conversely to the atmospheric correction described in Sect.3.4.1 -has the greatest effect on consolidated ice regions.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.3 Reducing systematic errors at high-concentration range
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Several other proxies for the local variability of the SIC field (among others the 3×3 standard deviation, the Laplacian, and power-tomean-ratio) were tested and this one was selected for its simplicity and robustness.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.5 Uncertainties
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Prior to further describing Fig. 8, it is important to note that the biases and standard deviations discussed here are internal to the processing chains, not an evaluation of the CDRs against independent observations of SICs.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The emissivity of land is comparable to sea-ice emissivity and much higher than water emissivity.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.6 Other relevant algorithms and processing steps
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The parameterizations implemented in the SMMR RTM are probably less developed than in the SSM/I and SSMIS RTM, which might explain why the impact on our standard deviation is more limited for SMMR.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“We note that clear-sky radiances from SSM/I and SSMIS were directly assimilated in ERA-Interim over the ocean (Dee et al., 2011) but not SMMR radiances (P. Poli, personal communication, 2018).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
What the sources say
- Not checked — no full text of the sourcecites Dee et al., 2011 source
- Not matchedcites P. Poli, personal communication, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Intuitively, both effects should have no or limited impact where the sea-ice cover is homogeneous (fully consolidated sea ice or open water).It should be at a maximum where sharp spatial gradients occur, typically at the sea-ice edge.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.5 Uncertainties
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Since SICCI-25km uses very similar frequency channels to those of OSI-450 (Table 1), it is not surprising that they achieve similar accuracy.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Still in Fig. 5 (centre panel), the increased variability (red tones) between the 15 % and 70 % isolines follows logically from the two above-mentioned reductions: the corrections enable more accurate retrievals of SICs; thus the ice edge is more sharply defined in the daily SIC fields, and this results in higher variability on a monthly basis.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.3 Reducing systematic errors at high-concentration range
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Another plausible explanation is that the reanalysed fields for wind speed and water vapour from ERA-Interim are less accurate in the SMMR era than in the SSM/I and SSMIS era.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“As noted at the end of Sect.3.4.1,OSI-450 uses the Wentz (1983) RTM for SMMR, and the Wentz (1997) RTM for SSM/I and SSMIS.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
What the sources say
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Effect (b) is that the footprint of the 37 GHz channels is smaller than that of the 19 GHz ones, so that the two frequencies entering the SIC algorithms do not cover the same area of the Earth's surface.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.5 Uncertainties
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The consolidated sea-ice samples we extract dynamically for [-7; +7 days] sliding windows (Sect.3.3) will typically exhibit more variability due to shorter-term changes in sea-ice signatures.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.3 Reducing systematic errors at high-concentration range
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“In addition, the ice curve in Fig. 3 is fitted through the consolidated ice points from the ESA CCI Sea Ice RRDP (Pedersen et al., 2018) that spans several years and winter months and thus illustrates an average sea-ice curve.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 3.4.3 Reducing systematic errors at high-concentration range
What the sources say
- Not checked — no full text of the sourcecites Pedersen et al., 2018 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A key asset of the algorithms we adopted is that they are selftuning and self-optimizing to the data, which greatly helps temporal consistency to be achieved between different satellite missions, both in the past and future (discussed later in Outlook, Sect.5.2).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.1 Discussion
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Using the status_flag variable, any SIC contaminated by land spillover effects or with high air temperatures were discarded.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.2 Evaluation against ground truth
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The true resolution of the SICCI-25km CDR might be slightly better than 25 × 25 km, but this grid spacing was retained to ease uptake by users and comparison with OSI-450.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.3 Caveats and known limitations
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“The retrieval of ice area fraction in these conditions would call for dedicated tie points (e.g.Ghaffari et al., 2011), which we did not implement here.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.3 Caveats and known limitations
What the sources say
- Not matchedcites Ghaffari et al., 2011
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The mismatch of grid spacing to the true resolution of the instrument footprint is taken into account in the uncertainty model of the OSI SAF CDR and is a key contribution to the smearing uncertainty (Sect.3.5).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.3 Caveats and known limitations
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Because the locations for ground-truth estimates are generally not at the ice edge, the smearing uncertainty term is close to zero and σ algo dominates the evaluation results summarized in Fig. 12.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.3 Evaluation of the uncertainties
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We note in addition that both the OSI-450 and SICCI-25km CDRs dynamically tune their optimal data planes for low-concentration range θ OW in the (19V , 37V , 37H ) 3-D T B space, while the OWF is only tuned in the (19V , 37V ) T B plane.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The CI locations are selected in areas of high sea-ice concentration and after 24 h of convergent sea-ice motion, as computed from a highly accurate SAR-based sea-ice drift product from the Copernicus Marine Environment Monitoring Service (CMEMS, http://marine.copernicus.eu,last access: 15 June 2018).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.2 Evaluation against ground truth
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For SIC = 100 % cases, the dynamically selected training samples are spread mostly all over the high sea-ice concentration regions, and there are thus good odds that the training samples are representative of the geophysical conditions in the ground-truth data set, and that in turn the reported uncertainties are in agreement with the retrieval errors for SIC = 100 % cases.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.3 Evaluation of the uncertainties
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These results are in agreement with those introduced in Sect.4.2.1 and are mainly explained by the frequency channels used in the three CDRs: 18.7 GHz for SICCI-25km, instead of 19.3 GHz for OSI-450 (less noise contribution from atmospheric water vapour content), and 6.9 GHz for SICCI-50km (lower sensitivity to atmosphere and surface snow and seaice property variations).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.3 Evaluation of the uncertainties
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The OSI-450 data set currently covers 1979 to 2015 with a consistent set of frequencies at 19 and 37 GHz.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.1 Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The OW locations are situated just outside the climatological mask delineating maximum sea-ice extent but well inside the buffer zone added to it in Sect.3.6.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.2 Evaluation against ground truth
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“For the evaluation at 100 % SIC conditions, we collocated the SIC CDRs with the SAR-based CI locations in the RRDP v2 for months November to March (Arctic) and May to September (Antarctic) in the same way as we did for open water; no spatial or temporal interpolations are performed.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.2 Evaluation against ground truth
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The departure of the optimal SIC plane from the OWF plane (by convention at θ = 0 • ; see right-hand panel in Fig. 4) could be the cause for the slight increase of the 1 % percentile curves of OSI-450 during the time period (via an improvement of the reanalysis data entering the atmosphere correction step over time), and the different value obtained with SICCI-25km.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, the results summarized in Fig. 12 indicate that the uncertainty σ tot provided with the three CDRs are slightly underestimated, especially for OSI-450 for the high sea-ice concentration range (SIC = 100 %), and are slightly overestimated for the low sea-ice concentration range (SIC = 0 %).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.3 Evaluation of the uncertainties
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The temporal stability of the time series in Fig. 9 documents that the tuning of the OWFs at values close to 10 % SIC is successful for the two data records that rely on the 19 and 37 GHz for computing their SICs (OSI-450 and SICCI-25km) and is not as good for SICCI-50km, which uses the 6 and 37 GHz channels to compute the SIC values.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.2.1 Monitoring stability and internal consistency
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In addition to the difficulty of computing dynamic tie points over such small areas, it is unclear if such dedicated tie points would make a large difference in the end, because of the combination of many error sources in these closed water bodies (land spillover, thin sea-ice, larger atmospheric influence, etc.).”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.3 Caveats and known limitations
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The 23.0 GHz channels of the SMMR instrument have been highly unstable since their launch and eventually ceased to function in March 1985.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.1 Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Ice resulting from freezing of fresh and brackish waters does not have the same emissivity as that from seawater.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 4.3 Caveats and known limitations
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The SICCI-50km is thus the most accurate of our three new CDRs but also has the coarsest spatial resolution due to the large footprint of the 6 GHz channels.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.1 Discussion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and is potentially linked to the age of sea ice.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.3 Conclusions
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, because our algorithms self-adapt to the data and their calibration, the implementation with MWI should be possible.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.2 Outlook
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The almost 15-year record of brightness temperature observations from these two instruments is a key complement to OSI-450.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.1 Discussion
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Theoretically 6 GHz is a better channel for estimating sea-ice concentration since the atmosphere is more transparent, the influence of error sources like seaice age or snow processes have less influence, and the contrast between ocean and ice is larger.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.1 Discussion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This guarantees ease of a long-term maintenance of these products”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.3 Conclusions
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
The authors state this as an assumption.
The total uncertainty σ_tot is given by two uncertainty components, σ_algo and σ_smear.
“we make the assumption that the total uncertainty σ tot is given by two uncertainty components.”
The paper relies on this without support.
The temporal consistency of the minimum detected SIC has not been documented for other available CDRs, although all use OWFs.
“To the best of our knowledge the temporal consistency of the minimum detected SIC has not been documented for other available CDRs, although all use OWFs.”
The paper relies on this without support.
Such 3-D-based filters do not exist at present.
“Such 3-D-based filters do not exist at present and this is addressed as future work in Sect.5.2.”
The paper relies on this without support.
All the aspects listed below apply generally to the other existing SIC data records based on PMW satellite data.
“All the aspects listed below apply generally to the other existing SIC data records based on PMW satellite data.”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated major: it would touch a result — a value a result rests on, reported and recomputed p-values on opposite sides of the significance level, two passages that conflict with no sign which is right, or a cited work retracted before this paper was published.
In the paper
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 2.1 Input satellite data
“The AMSR-E data we use are the NSIDC FCDR AE_L2A V003 FCDR by Ashcroft and Wentz (2013), covering the full lifetime of the mission from 1 June 2002 to 4 October 2011.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.3 Conclusions
“| EOS Aqua | 1 June 2002 | 3 October 2010 | 6.9 (75 × 43), 18.7 (27 × 16), | 89.5 • | 55 • | |”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 2.1 Input satellite data
“covering 23 July 2012 until 15 May 2017, that is the end of the SICCI-25km and SICCI-50km CDRs.”
§ Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records > 5.3 Conclusions
“| GCOM W1 | 23 July 2012 | 31 May 2017 | 6.9 (62 × 35), 18.7 (22 × 14), | 89.5 • | 55 • | AMSR2 operated |”
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InfluentialA well‐calibrated ocean algorithm for special sensor microwave / imager
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“The tie points for applying the NT algorithm to SMMR, SSM/I, and SSMIS are taken from Appendix A in Ivanova et al. (2015).”
MethodInfluentialLarge Decadal Decline of the Arctic Multiyear Ice Cover
Comiso, J. C. (2011) · Journal of Climate · doi:10.1175/jcli-d-11-00113.1 · Cited by 811 · cited 4×
“For easing later discussion, we note here that in winter Arctic conditions, the typical multiyear sea-ice signature is to the “left” of the ice line -close to A- while first-year sea ice and young sea ice is to the right -closer to D- (Comiso et al. 2012). 5 The left-hand panel of Figure 4 is originally adapted from S…”
BackgroundMethodInfluentialDetermination of sea ice parameters with the NIMBUS 7 SMMR
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BackgroundMethodObserved Arctic sea-ice loss directly follows anthropogenic CO 2 emission
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BackgroundSelf-citationTrends in the sea ice cover using enhanced and compatible AMSR‐E, SSM/I, and SMMR data
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“BFM and BPM are widely used for sea-ice monitoring in what is commonly known as the bootstrap algorithm (Comiso and Nishio, 2008).”
MethodInfluential
Cited by
Sorted by citations
Items 401–468 of 468
Intercomparison of Long-Term Sea Ice Concentration Remote Sensing Products in the Southern Ocean
李, 佳. (2023) · Climate Change Research Letters · doi:10.12677/ccrl.2023.124085
Comment on egusphere-2023-1411
Selivanova, J., Iovino, D., & Cocetta, F. (2023) · doi:10.5194/egusphere-2023-1411-rc1
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Self-citationComment on egusphere-2023-1411
Selivanova, J., Iovino, D., & Cocetta, F. (2023) · doi:10.5194/egusphere-2023-1411-rc2
Selivanova, J. (2023) · doi:10.5194/egusphere-2023-1411-ac2
Selivanova, J. (2023) · doi:10.5194/egusphere-2023-1411-ac1
Maliuha, Е., & Gavriluk, R. V. (2023) · Ukrainian hydrometeorological journal · doi:10.31481/uhmj.32.2023.06
Liang, H., & Zhou, W. (2024) · doi:10.5194/tc-2023-134-rc1
Liang, H., & Zhou, W. (2024) · doi:10.5194/tc-2023-134-rc2
Comment on egusphere-2022-1189
Wernecke, A., Notz, D., Kern, S., et al. (2024) · doi:10.5194/egusphere-2022-1189-rc1
Self-citationLiang, H. (2024) · doi:10.5194/tc-2023-134-ac2
Liang, H. (2024) · doi:10.5194/tc-2023-134-ac1
Comment on egusphere-2022-1189
Wernecke, A., Notz, D., Kern, S., et al. (2024) · doi:10.5194/egusphere-2022-1189-rc2
Self-citationWernecke, A. (2024) · doi:10.5194/egusphere-2022-1189-ac1
Wernecke, A. (2024) · doi:10.5194/egusphere-2022-1189-ac2
Global Ocean Forecast Accuracy Improvement Due to Optimal Sensor Placement
Turko, N. A., Lobashev, A., Ushakov, K. V., et al. (2023) · Rossijskij žurnal nauk o zemle/Russian journal of earth sciences · doi:10.2205/2023es000883
Thermodynamics Drive Changes in the Antarctic Sea Ice Seasonal Cycle Following 2016Preprint
Himmich, K., Vancoppenolle, M., Stammerjohn, S. E., et al. (2024) · doi:10.22541/au.171387368.89541964/v1
Allende, S., Tréguier, A., Lique, C., et al. (2024) · doi:10.5194/gmd-2024-49-rc1
Allende, S., Tréguier, A., Lique, C., et al. (2024) · doi:10.5194/gmd-2024-49-rc2
A New Near Real Time Sea Ice Concentration Algorithm for OSI SAF
Baordo, F., Shi, H., & Singha, S. (2024) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss53475.2024.10642767
“The accurate estimation of sea ice concentration (SIC) is crucial for understanding the dynamics of polar regions and monitoring long-term climate change [1, 2].”
BackgroundMethodInfluentialSeki, M., Hori, M., Naoki, K., et al. (2024) · Remote Sensing · doi:10.3390/rs16193549
“The long-term sea ice datasets from the SMMR and SSM/I series are available through the NASA Team (NT1) [1], Bootstrap Version 2 [2], and European Meteorological Satellite Program (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI-SAF Version 2) [3].”
Comment on egusphere-2024-3490
Landrum, L., DuVivier, A. K., Holland, M. M., et al. (2024) · doi:10.5194/egusphere-2024-3490-rc2
Comment on egusphere-2024-3687
Servettaz, A. P. M., Isaji, Y., Yoshikawa, C., et al. (2025) · doi:10.5194/egusphere-2024-3687-rc1
The Nimbus 6 Electrically Scanning Microwave Radiometer: Data rescue
Tellefsen, E. H., Tonboe, R. T., Kolbe, W. M., et al. (2025) · Remote Sensing Applications Society and Environment · doi:10.1016/j.rsase.2025.101504
Self-citationPark, K., Woo, H., Saux-Picart, S., O’Carroll, A. G., Sohn, E.-H., Joo, H., Lee, J., & Yang, J.-Y. (2025) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2025.3557003
“…interpolation SST (OISST) analysis [17], multiscale ultrahigh resolution SST (MURSST) [18], ESA climate change initiative (CCI) SST [5], [15], [19], Canadian Meteorological Centre (CMC) analysis, remote sensing system (REMSS) analysis, merged satellite and in situ data global daily SST…”
Bhattacharjee, S., & Garg, R. D. (2025) · Remote Sensing in Earth Systems Sciences · doi:10.1007/s41976-025-00224-5
“Prior research on sea ice concentration estimation using optical sensors and passive microwave data usually reports RMSE values between 0.3 and 0.5, with lower accuracy in areas with mixed ice-water conditions and melt ponds [13, 29].”
InfluentialVichi, M., Seyboth, E., Mazomba, T., Vermeulen, E., Findlay, K., Meynecke, J., de Bie, J., Secchi, E. R., Rosa, L. D., & Roychoudhury, A. N. (2025) · Environmental Research Climate · doi:10.1088/2752-5295/add614
Chen, Z., Li, D., Liu, J., et al. (2025) · Journal of Geophysical Research Oceans · doi:10.1029/2024jc022206
Seasonal and Regional Antarctic Sea Ice Biases: A Closer Look at CMIP6
Schroeter, S. (2025) · ATMOSPHERE-OCEAN · doi:10.1080/07055900.2025.2507880
Impact of stratospheric polar vortex variability on Antarctic sea ice in CMIP6 models
Mezzina, B., Palmeiro, F. M., Goosse, H., et al. (2025) · Climate Dynamics · doi:10.1007/s00382-025-07765-x
Chowdhury, M. N. S., Capuano, T. A., & Rahman, M. S. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5377711
A review of emergent vulnerabilities indices in the Alaska Arctic
Bushnell, E. J., Miner, K. R., Sousa, D. J., et al. (2025) · Frontiers in Environmental Science · doi:10.3389/fenvs.2025.1619823
Methods of satellite remote sensing of sea ice
Spreen, G., Itkin, P., & Kern, S. (2025) · Wiley eBooks · doi:10.1002/9781394213764.ch05 · Cited by 2
Self-citation王, 庆., 邹, 建., Feng, X., Dou, R., 董, 智., Zhu, A., 刘, 焱., & 石, 学. (2025) · SCIENTIA SINICA Terrae · doi:10.1360/sste-2024-0341
Eayrs, C., & Labe, Z. M. (2025) · Elsevier eBooks · doi:10.1016/b978-0-323-85242-5.00050-6
A Fair Assessment of Sea Ice Age Reduces Bias and Gives New Insight to Arctic Sea Ice Dynamics
Davy, R., Regan, H., Korosov, A. A., et al. (2025) · Geophysical Research Letters · doi:10.1029/2025gl117765
Spatial and temporal patterns of SST uncertainty
Cobb, A., & Green, P. (2025) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.5062
“1 (Good et al. , 2020a; Lavergne et al. , 2019; Merchant et al. , 2019), ESA CCI v3 (Embury et al. , 2024), and DOISST v2 (Huang et al. , 2021; Reynolds et al. , 2007).”
InfluentialThe climate science, engineering and finance landscape
Chong, B., & Yip, E. (2025) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-80592-084-720251002
Wang, Q., Zou, J., Feng, X., Dou, R., Zhi, D., Zhu, A., Liu, Y., & Shi, X. (2025) · Science China Earth Sciences · doi:10.1007/s11430-024-1700-y
Towards importance of periodicity estimation in long-term spatio-temporal data prediction
Borisova, J., & Nikitin, N. O. (2025) · doi:10.1109/ijcnn64981.2025.11228079
“…from benchmarks adopted for the task of video prediction [32]: KTH [10], Moving MNIST [12], a 5-degree resolution Weather-Bench [23], and supplemented them with the Arctic sea ice concentration dataset collected from the OSISAF provider [11] and synthetic data with cycled video in GIF format.”
Zhang, F., Lei, R., Qu, M., et al. (2025) · The cryosphere · doi:10.5194/tc-19-3065-2025
Global Sea Surface Temperature
Merchant, C. J., & Harris, A. R. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-13220-9.00074-3
Sahoo, S. K., Momin, I. M., Gera, A., et al. (2026) · Theoretical and Applied Climatology · doi:10.1007/s00704-025-06017-6
“For assimilation, the daily SIC data were derived from passive microwave sensor data, specifically the Special Sen - sor Microwave Imager/Sounder (SSMIS), obtained from the Ocean and Sea Ice Satellite Application Facility (OSI SAF; Lavergne et al. 2019).”
Brief communication: Evaluation of the ESA CCI+ ESMR v1.1 sea-ice concentration product
Kern, S. (2026) · The cryosphere · doi:10.5194/tc-20-527-2026
Self-citationFrequency-Enhanced Hilbert Scanning Mamba for Short-Term Arctic Sea Ice Concentration Prediction
Gao, F., Gong, Z., Liu, W., Gan, Y., Zheng, Z., Dong, J., & Du, Q. (2026) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2026.3665141
“As an updated version of the OSI-450a1 dataset [42], OSI-450a1 is sourced from the OSI-SAF website and represents a full reprocessing of SIC data from 1978 to 2020 with optimized data processing.”
Wang, Q., Li, W., Shan, L., & Liu, X. (2026) · Climate Dynamics · doi:10.1007/s00382-026-08088-1
Kilic, L. (2019) · theses.fr (ABES) · doi:10.70675/2f303297z425fz4b6cz9630z98fa98f23bc5
“Des algorithmes plus récents utilisent des combinaisons de ces méthodes, avec quelques ajustements, comme l’algorithme OSISAF (Ocean Sea Ice - Satellite Application Facilities) soutenu par EUMETSAT [Tonboe et al., 2016, Lavergne et al., 2019].”
BackgroundCaractérisation de la banquise Arctique à partir d'observations micro-ondes multi-satellites
Soriot, C. (2022) · theses.fr (ABES) · doi:10.70675/018b7abazea7fz48c1zb660zf39870cff1ab
Consistent passive microwave sea ice concentration biases in AntarcticaPreprint
Horvat, C., Tavri, A., & Mohammadnezhad, K. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6553998
Malysheva, A. S., & Lobanova, P. V. (2025) · Izvestiya Atmospheric and Oceanic Physics · doi:10.1134/s0001433826700192
“…ESA SST CCI and C3S reprocessed sea surface temperature analyzes database (DOI (product): https://doi.org/10.48670/moi-00169) (Good et al., 2020; Lavergne et al., 2019; Merchant et al., 2019) with a spatial resolution of 0.05 × 0.05 ° and a temporal resolution of 8 days for the period under…”
InfluentialStudy on improved DPR sea ice concentration retrieval algorithm
Wang, X., Wang, Y., Sun, Z., Li, Z., & Liu, X. (2026) · International Journal of Remote Sensing · doi:10.1080/01431161.2026.2687819
“…strengths of different algorithms and provide more reliable data products, institutions such as the European Space Agency (ESA) had initiated algorithm intercom-parison and validation projects, generating consensus SIC datasets that merge the results of multiple algorithms (Lavergne et al. 2019).”
InfluentialShabanov, P. A. (2026) · Oceanology · doi:10.1134/s0001437026700049
“Satellite ice concentration measurements may be misinterpreted near the coastal zone [14, 30, 35, 39].”
Uncertainty of the satellite-retrieved sea-ice area record and its trend
Wernecke, A., Lavergne, T., Kern, S., et al. (2026) · The cryosphere · doi:10.5194/tc-20-3783-2026
“…of measurements with different footprints The OSI SAF SIC uncertainty includes the smearing_uncertainty variable which is based on the local gradients in SIC because measurements within fields of large gradients are more sensitive to the exact location of the measurements (Lavergne et al., 2019).”
Self-citationEnhanced prediction skill of Antarctic sea ice through sea ice thickness assimilation
Williams, N., Wang, Y., & Counillon, F. (2026) · The cryosphere · doi:10.5194/tc-20-3795-2026
Li, R., Guo, F., Yang, W., et al. (2026) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2026.105502
Stentella, M., Picard, G., Heil, P., Boutin, J., Dinnat, E. P., & Corney, S. P. (2026) · The Cryosphere · doi:10.5194/tc-20-4465-2026
“…to address only a sensitivity analysis of the geophysical noise, represented by the variability of brightness temperatures around the open-ocean and 100 % SIC tie points and does not address additional sources of uncertainty related to spatial smearing (Lavergne et al., 2019) described in Sect.2”
Changes in the Ice-Free Period in the Chukchi Sea Based on Remote Sensing and Coastal Observations
Shabanov, P. A. (2026) · Oceanology · doi:10.1134/s0001437026700165
“Satellite ice concentration measurements may be misinterpreted near the coastal zone [15, 32, 39, 54].”
Liu, J., Zhang, G., Xing, S., et al. (2026) · Acta Oceanologica Sinica · doi:10.1007/s13131-026-2744-9
“The Global SIC Climate Data Record (GSICCDR) was initially developed under Phase 2 of the European (Ivanova et al., 2015), ensuring climate-scale consistency (Lavergne et al., 2019), and have undergone extensive validation through independent ground-based observations (Horvat et al., 2025).”
Choo, M., Kim, Y. J., Lee, G., et al. (2026) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2026.09.021
OSISAF-to-MASAM2: Deep Learning for Sea Ice Concentration Super-Resolution Product
Borisova, J., Morozov, D., Gilemkhanov, D., et al. (2026) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2026.3735399
“Satellite-based passive microwave observations have provided continuous SIC estimates since 1978, forming the backbone of climate data records [1].”
Global, regional and UK climate in 2025
Sandford, C., Dunn, R., Kendon, M., Rayner, N. A., Morice, C., & Blannin, J. (2026) · Weather · doi:10.1002/wea.70137
Paul, D., Caus, D., Keil, P., et al. (2026) · The cryosphere · doi:10.5194/tc-20-5491-2026
Assessment of warm bias in ERA5 surface skin temperature over Arctic landfast sea ice
Diaz, A., Papakyriakou, T., & Ehn, J. K. (2026) · Elementa Science of the Anthropocene · doi:10.1525/elementa.2026.00016
Song, Z., Li, J., Dian, J., Ye, H., Dai, X., & Li, J. (2026) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2026.09.039
Zhang, Y., Li, B., Zuo, G., et al. (2026) · Journal of Marine Science and Engineering · doi:10.3390/jmse14201909
Horvat, C., Tavri, A., & Mohammadnezhad, K. (2026) · Remote Sensing of Environment · doi:10.1016/j.rse.2026.115723
Metadata
- Authors
- Lavergne, T., Sørensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjær, G., Eastwood, S., Gabarro, C., Heygster, G., Killie, M. A., Brandt Kreiner, M., Lavelle, J., Saldo, R., Sandven, S., & Pedersen, L. T.
- ORCID
- Venue
- The Cryosphere
- Publisher
- Copernicus GmbH
- Published
- 2019-01-09
- Volume
- 13
- Issue
- 1
- Pages
- 49-78
- ISSN
- 1994-0416 (ISSN-L)
- 1994-0424
- OpenAlex
- W2883803127
- Cited by
- 469
- References
- 65
- Citations by year
- 2026: 33 · 2025: 56 · 2024: 59 · 2023: 72 · 2022: 78 · 2021: 113 · 2020: 38 · 2019: 16
- FWCI
- 24.13
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- The cryosphere (publishedVersion, cc-by)
- DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion, cc-by)
- Funders
- European Organization for the Exploitation of Meteorological Satellites
- Japan Aerospace Exploration Agency
- Topics
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Arctic and Antarctic ice dynamics
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Cryospheric studies and observations
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Oceanographic and Atmospheric Processes
- Keywords
- sea ice concentration, climate data record, passive microwave remote sensing, satellite calibration, uncertainty estimation, SMMR, SSM/I, SSMIS, AMSR-E, AMSR2, 37 GHz, 6 GHz band, 19 GHz, horizontal resolution, Arctic sea ice, Antarctic sea ice
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