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Review and assessment of latent and sensible heat flux accuracy over the global oceans.
Open accessAbstract
For over a decade, several research groups have been developing air-sea heat flux information over the global ocean, including latent (LHF) and sensible (SHF) heat fluxes over the global ocean. This paper aims to provide new insight into the quality and error characteristics of turbulent heat flux estimates at various spatial and temporal scales (from daily upwards). The study is performed within the European Space Agency (ESA) Ocean Heat Flux (OHF) project. One of the main objectives of the OHF project is to meet the recommendations and requirements expressed by various international programs such as the World Research Climate Program (WCRP) and Climate and Ocean Variability, Predictability, and Change (CLIVAR), recognizing the need for better characterization of existing flux errors with respect to the input bulk variables (e.g. surface wind, air and sea surface temperatures , air and surface specific humidities), and to the atmospheric and oceanic conditions (e.g. wind conditions and sea state). The analysis is based on the use of daily averaged LHF and SHF and the associated bulk variables derived from major satellite-based and atmospheric reanalysis products. Inter-comparisons of heat flux products indicate that all of them exhibit similar space and time patterns. However, they also reveal significant differences in magnitude in some specific regions such as the western ocean boundaries during the Northern Hemisphere winter season, and the high southern latitudes. The differences tend to be closely related to large differences in surface wind speed and/or specific air humidity (for LHF) and to air and sea temperature differences (for SHF). Further quality investigations are performed through comprehensive comparisons with daily-averaged LHF and SHF estimated from moorings. The resulting statistics are used to assess the error of each OHF product. Consideration of error correlation between products and observations (e.g., by their assimilation) is also given. This reveals generally high noise variance in all products and a weak signal in common with in situ observations, with some products only slightly better than others. The OHF LHF and SHF products, and their associated error characteristics, are used to compute daily OHF multiproduct-ensemble (OHF/MPE) estimates of LHF and SHF over the ice-free global ocean on a 0.25° × 0.25° grid. The accuracy of this heat multiproduct, determined from comparisons with mooring data, is greater than for any individual product. It is used as a reference for the anomaly characterization of each individual OHF product.
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“The estimation contains uncertainty, which hampers our ability to accurately quantify air-sea thermodynamic interactions and heat budgets in the tropical Atlantic (Frankignoul and Kestenare, 2005;Pinker et al., 2014;Bentamy et al., 2017).”
From The tropical atlantic observing system (2019) · cites this paper as Bentamy et al., 2017
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Cites
The ERA‐Interim reanalysis: configuration and performance of the data assimilation system
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., et al. (2011) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.828 · Cited by 24,480
Summarizing multiple aspects of model performance in a single diagram
Taylor, K. E. (2001) · Journal of Geophysical Research Atmospheres · doi:10.1029/2000jd900719 · Cited by 8,927
The NCEP Climate Forecast System Reanalysis
Saha, S., Moorthi, S., Pan, H., Wu, X., Wang, J., Nadiga, S., Tripp, P., Kistler, R. E., Woollen, J. S., Behringer, D. W., et al. (2010) · Bulletin of the American Meteorological Society · doi:10.1175/2010bams3001.1 · Cited by 5,251
MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications
Rienecker, M. M., Suárez, M. J., Gelaro, R., Todling, R., Bacmeister, J. T., Liu, E., Bosilovich, M. G., Schubert, S. D., Takacs, L. L., Kim, G.-K., et al. (2011) · Journal of Climate · doi:10.1175/jcli-d-11-00015.1 · Cited by 4,856
Daily High-Resolution-Blended Analyses for Sea Surface Temperature
Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K. S., & Schlax, M. G. (2007) · Journal of Climate · doi:10.1175/2007jcli1824.1 · Cited by 4,435
A New Method of Interpolation and Smooth Curve Fitting Based on Local Procedures
Akima, H. (1970) · Journal of the ACM · doi:10.1145/321607.321609 · Cited by 2,135
Trenberth, K. E., Fasullo, J., & Kiehl, J. T. (2008) · Bulletin of the American Meteorological Society · doi:10.1175/2008bams2634.1 · Cited by 2,068
Wind stress on a water surface
Charnock, H. (1955) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.49708135027 · Cited by 1,961
Atlas, R. M., Hoffman, R. N., Ardizzone, J. V., Leidner, S. M., Jusem, J. C., Smith, D. K., & Gombos, D. (2010) · Bulletin of the American Meteorological Society · doi:10.1175/2010bams2946.1 · Cited by 973
Toward the true near‐surface wind speed: Error modeling and calibration using triple collocation
Stoffelen, A. (1998) · Journal of Geophysical Research Atmospheres · doi:10.1029/97jc03180 · Cited by 895
A well‐calibrated ocean algorithm for special sensor microwave / imager
Wentz, F. J. (1997) · Journal of Geophysical Research: Oceans · doi:10.1029/96jc01751 · Cited by 837
Yu, L., Jin, X., & Weller, R. A. (2008) · Cited by 538
The parametrization of surface fluxes in large‐scale models under free convection
Beljaars, A. C. M. (1995) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.49712152203 · Cited by 518
ICOADS Release 2.5: extensions and enhancements to the surface marine meteorological archive
Woodruff, S. D., Worley, S. J., Lubker, S. J., Ji, Z., Freeman, E., Berry, D. I., Brohan, P., Kent, E. C., Reynolds, R. W., Smith, S. R., et al. (2010) · International Journal of Climatology · doi:10.1002/joc.2103 · Cited by 462
Self-citationAn imperative to monitor Earth's energy imbalance
von Schuckmann, K., Palmer, M. D., Trenberth, K. E., Cazenave, A., Chambers, D. P., Champollion, N., Hansen, J. E., Josey, S. A., Loeb, N. G., Mathieu, P. ‐., et al. (2016) · Nature Climate Change · doi:10.1038/nclimate2876 · Cited by 445
Self-citationMcColl, K. A., Vogelzang, J., Konings, A. G., Entekhabi, D., Piles, M., & Stoffelen, A. (2014) · Geophysical Research Letters · doi:10.1002/2014gl061322 · Cited by 438
ICOADS Release 3.0: a major update to the historical marine climate record
Freeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E., Berry, D. I., Brohan, P., Eastman, R. M., Gates, L., et al. (2016) · International Journal of Climatology · doi:10.1002/joc.4775 · Cited by 416
Self-citationRecent advances in (soil moisture) triple collocation analysis
Gruber, A., Su, C., Zwieback, S., Crow, W. T., Dorigo, W. A., & Wagner, W. (2015) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2015.09.002 · Cited by 370
The Past, Present, and Future of the AVHRR Pathfinder SST Program
Casey, K. S., Brandon, T. B., Cornillon, P., & Evans, R. H. (2010) · Springer eBooks · doi:10.1007/978-90-481-8681-5_16 · Cited by 360
North Atlantic Ocean control on surface heat flux on multidecadal timescales
Gulev, S., Latif, M., Keenlyside, N. S., Park, W., & Koltermann, K. P. (2013) · Nature · doi:10.1038/nature12268 · Cited by 314
Self-citationGridded surface wind fields from metop/ASCAT measurements.
Bentamy, A., & Fillon, D. C. (2012) · International Journal of Remote Sensing · doi:10.1080/01431161.2011.600348 · Cited by 241
Self-citationThe Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data – HOAPS-3
Andersson, A., Fennig, K., Klepp, C., Bakan, S., Graßl, H., & Schulz, J. (2010) · Earth system science data · doi:10.5194/essd-2-215-2010 · Cited by 220
Anderson, E., & Järvinen, H. J. (1999) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.49712555416 · Cited by 208
A New Air–Sea Interaction Gridded Dataset from ICOADS With Uncertainty Estimates
Berry, D. I., & Kent, E. C. (2008) · Bulletin of the American Meteorological Society · doi:10.1175/2008bams2639.1 · Cited by 176
Brodeau, L., Barnier, B., Gulev, S., & Woods, C. (2016) · Journal of Physical Oceanography · doi:10.1175/jpo-d-16-0169.1 · Cited by 149
Self-citationA Deterministic Algorithm for Robust Location and Scatter
Mia Hubert, B., Rousseeuw, P. J., & Verdonck, T. (2012) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.2012.672100 · Cited by 140
Beyond triple collocation: Applications to soil moisture monitoring
Su, C., Ryu, D., Crow, W. T., & Western, A. W. (2014) · Journal of Geophysical Research Atmospheres · doi:10.1002/2013jd021043 · Cited by 131
Roberts, J. B., Clayson, C. A., Robertson, F. R., & Jackson, D. L. (2010) · Journal of Geophysical Research Atmospheres · doi:10.1029/2009jd013099 · Cited by 84
Self-citationSchlüssel, P., Schanz, L., & Englisch, G. (1995) · Advances in Space Research · doi:10.1016/0273-1177(95)00389-v · Cited by 78
A comparison of nine monthly air–sea flux products
Smith, S. R., Hughes, P. J., & Bourassa, M. A. (2010) · International Journal of Climatology · doi:10.1002/joc.2225 · Cited by 74
Self-citationIntercomparison and Validation of Ocean-Atmosphere Energy Flux fields,
Taylor, P. (2000) · Cited by 73
Evaluation of HOAPS-3 Ocean Surface Freshwater Flux Components
Andersson, A., Klepp, C., Fennig, K., Bakan, S., Graßl, H., & Schulz, J. (2010) · Journal of Applied Meteorology and Climatology · doi:10.1175/2010jamc2341.1 · Cited by 69
Gulev, S., Jung, T. J., & Ruprecht, E. (2007) · Journal of Climate · doi:10.1175/jcli4010.1 · Cited by 62
Self-citationToward an Intercalibrated Fundamental Climate Data Record of the SSM/I Sensors
Sapiano, M. R. P., Berg, W. K., McKague, D. S., & Kummerow, C. D. (2012) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2012.2206601 · Cited by 62
Improvement in air–sea flux estimates derived from satellite observations
Bentamy, A., Grodsky, S. A., Katsaros, K. B., Mestas‐Nuñez, A. M., Blanke, B., & Desbiolles, F. (2013) · International Journal of Remote Sensing · doi:10.1080/01431161.2013.787502 · Cited by 61
Self-citationGulev, S., & Belyaev, K. P. (2011) · Journal of Climate · doi:10.1175/2011jcli4211.1 · Cited by 59
Self-citationIntraseasonal Latent Heat Flux Based on Satellite Observations
Grodsky, S. A., Bentamy, A., Carton, J. A., & Pinker, R. T. (2009) · Journal of Climate · doi:10.1175/2009jcli2901.1 · Cited by 50
Self-citationHomogenization of scatterometer wind retrievals
Bentamy, A., Grodsky, S. A., Elyouncha, A., Chapron, B., & Desbiolles, F. (2016) · International Journal of Climatology · doi:10.1002/joc.4746 · Cited by 43
Self-citationGulev, S., Jung, T. J., & Ruprecht, E. (2007) · Journal of Climate · doi:10.1175/jcli4008.1 · Cited by 43
Self-citationA Guide to Making Climate Quality Meteorological and Flux Measurements at Sea.
Bradley, E. F., & Farall, C. (2021) · IOC of UNESCO (Intergovernmental Oceanographic Commission) · doi:10.25607/obp-1353 · Cited by 42
Unexpected impacts of the Tropical Pacific array on reanalysis surface meteorology and heat fluxes
Josey, S. A., Yu, L., Gulev, S., Jin, X., Tilinina, N. D., Barnier, B., & Brodeau, L. (2014) · Geophysical Research Letters · doi:10.1002/2014gl061302 · Cited by 40
Self-citationImpact of Synoptic Atmospheric Forcing on the Mean Ocean Circulation
Wu, Y. S., Zhai, X., & Wang, Z. (2016) · Journal of Climate · doi:10.1175/jcli-d-15-0819.1 · Cited by 31
Tomita, H., & Kubota, M. (2006) · Journal of Geophysical Research Atmospheres · doi:10.1029/2005jc003013 · Cited by 27
Ayina, L.-H., Bentamy, A., Mestas‐Nuñez, A. M., & Madec, G. (2006) · Journal of Climate · doi:10.1175/jcli3939.1 · Cited by 23
Self-citationNew Approaches for Air-Sea Fluxes in the Southern Ocean
Gille, S. T., Josey, S. A., & Swart, S. (2016) · Eos · doi:10.1029/2016eo052243 · Cited by 16
Self-citationExploitation of error correlation in a large analysis validation: GlobCurrent case study
Danielson, R. E., Johannessen, J. A., Quartly, G. D., Rio, M., Chapron, B., Collard, F., & Donlon, C. J. (2018) · Remote Sensing of Environment · doi:10.1016/j.rse.2018.07.016 · Cited by 15
Self-citationMestas‐Nuñez, A. M., Bentamy, A., & Katsaros, K. B. (2006) · Journal of Climate · doi:10.1175/jcli3721.1 · Cited by 10
Self-citationThe ENSO footprint in monthly satellite evaporation over the global ocean during 1993–2007
Mestas‐Nuñez, A. M., Kelly, F. J., Bentamy, A., & Katsaros, K. B. (2013) · Remote Sensing Letters · doi:10.1080/2150704x.2013.788259 · Cited by 4
Self-citationCarlin (2002) · doi:10.1175/1520-0442(2002)015
Shay (2000) · doi:10.1175/1520-0493(2000)128
Latif, M. (1999) · doi:10.1175/1520-0442(1999)012
Self-citationMcHugh, M. (2004) · doi:10.1175/1520-0442(2004)017
- Self-citation
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2 of the 56 references couldn’t be matched to a known paper.
Research works printed but not linked: 5
- Chou, 2003, Surface turbulent heat and momentum fluxes over global oceans based on the Goddard satellite retrieval, version 2 (GSSTF2), J. Clim., 16, 3256, 10.1175/1520-0442(2003)016<3256:STHAMF>2.0.CO;2 · DOI
- Clayson, 2013, SEAFLUX Version 1: a new satellite-based ocean-atmosphere turbulent flux dataset, Int. J. Climatol.
- Fairall, 2003, Bulk parameterization of air–sea fluxes: updates and verification for the COARE algorithm, J. Clim., 16, 571, 10.1175/1520-0442(2003)016<0571:BPOASF>2.0.CO;2 · DOI
- Kurihara, 2006, Global daily sea surface temperature analysis using data from satellite microwave radiometer, satellite infrared radio meter and in-situ observations (in Japanese), Weather Bull., 73, s1
- Simmons, 2006, 110, 26
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Metadata
- Authors
- Bentamy, A., Piollé, J. F., Grouazel, A., Danielson, R., Gulev, S., Paul, F., Azelmat, H., Mathieu, P. P., von Schuckmann, K., Sathyendranath, S., Evers-King, H., Esau, I., Johannessen, J. A., Clayson, C. A., Pinker, R. T., Grodsky, S. A., Bourassa, M., Smith, S. R., Haines, K., Valdivieso, M., Merchant, C. J., Chapron, B., Anderson, A., Hollmann, R., & Josey, S. A.
- Affiliations
- Ifremer (FR)
- Nansen Environmental and Remote Sensing Center (NO)
- Institute of Oceanology. PP Shirshov Russian Academy of Sciences (RU)
- European Space Research Institute (IT)
- Institut Méditerranéen d’Océanologie (FR)
- Plymouth Marine Laboratory (GB)
- Woods Hole Oceanographic Institution (US)
- University of Maryland, College Park (US)
- Florida State University (US)
- National Centre for Earth Observation (GB)
- University of Reading (GB)
- European Organisation for the Exploitation of Meteorological Satellites (DE)
- Corresponding author
- Bentamy, A.
- ORCID
- Venue
- Remote Sensing of Environment
- Publisher
- Elsevier BV
- Published
- 2017-11
- Volume
- 201
- Pages
- 196-218
- ISSN
- 0034-4257 (ISSN-L)
- OpenAlex
- W2756493409
- Cited by
- 116
- References
- 56
- Citations by year
- 2026: 8 · 2025: 8 · 2024: 16 · 2023: 15 · 2022: 21 · 2021: 9 · 2020: 12 · 2019: 17 · 2018: 10
- FWCI
- 7.09
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Remote Sensing of Environment (publishedVersion, other-oa)
- Marine Biological Association (acceptedVersion)
- CentAUR (University of Reading) (submittedVersion)
- HAL (submittedVersion, other-oa)
- Institutional Archive of Ifremer (French Research Institute for Exploitation of the Sea) (submittedVersion)
- ePrints Soton (University of Southampton) (submittedVersion)
- Funders
- ESA (4000111424/14/I-AM)
- Russian Science Foundation (14-17-00697-II)
- Topics
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Oceanographic and Atmospheric Processes
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Ocean Waves and Remote Sensing
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Keywords
- latent heat flux, sensible heat flux, air-sea heat flux, ocean heat flux, surface wind speed, specific humidity, sea surface temperature, global ocean
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