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Cited by 54Precipitation Measurement and AnalysisEnvironmental Monitoring and Data ManagementMeteorological Phenomena and Simulations

The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.

TITAN automatic spatial quality control of meteorological in-situ observations

Open access
Båserud, Line, Lussana, Cristian, Nipen, Thomas N., Seierstad, Ivar A., Oram, Louise, Aspelien, Trygve·2020·Advances in Science and Research
DOI 10.5194/asr-17-153-2020
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Abstract

Abstract. In science, poor quality input data will invariably lead to faulty conclusions, as in the spirit of the saying “garbage in, garbage out”. Atmospheric sciences make no exception and correct data is crucial to obtain a useful representation of the real world in meteorological, climatological and hydrological applications. Titan is a computer program for the automatic quality control of meteorological data that has been designed to serve real-time operational applications that process massive amounts of observations measured by networks of automatic weather stations. The need to quality control third-party data, such as citizen observations, within a station network that is constantly changing was an important motivation that led to the development of Titan. The quality control strategy adopted is a sequence of tests, where several of them utilize the expected spatial consistency between nearby observations. The spatial continuity can also be evaluated against independent data sources, such as numerical model output and remote sensing measurements. Examples of applications of Titan for the quality control of near-surface hourly temperature and precipitation over Scandinavia are presented. In the case of temperature, this specific application has been integrated into the operational production chain of automatic weather forecasts at the Norwegian Meteorological Institute (MET Norway). Titan is an open source project and it is made freely available for public download. One of the objectives of the Titan project is to establish a community working on common tools for automatic quality control, and the Titan program represents a first step in that direction for MET Norway. Further developments are necessary to achieve a solution that satisfies more users, for this reason we are currently working on transforming Titan into a more flexible library of functions.

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Cites

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Figures

Figure 1 Spatial domain, in the geographical coordinate system, used for the example application. The sea, large bodies of water and rivers are shown in blue. The altitude above the mean sea level (in m) is shown through shaded colors. The red circle marks Oslo. The purple square marks Lillehammer.
Figure 1 Spatial domain, in the geographical coordinate system, used for the example application. The sea, large bodies of water and rivers are shown in blue. The altitude above the mean sea level (in m) is shown through shaded colors. The red circle marks Oslo. The purple square marks Lillehammer.CC-BY · From the PDF
Figure 2 The result of the quality control by Titan for observations in Lillehammer for 06:00 UTC on 5 November 2019, showing the temperature observations (a) with the corresponding SCT scores (b) . The observations passing the quality control are shown in grey, whereas those failing the plausibility check, the DEM check, or the SCT are shown in light purple, dark purple, and red, respectively. Background image source: ESRI World Imagery.
Figure 2 The result of the quality control by Titan for observations in Lillehammer for 06:00 UTC on 5 November 2019, showing the temperature observations (a) with the corresponding SCT scores (b) . The observations passing the quality control are shown in grey, whereas those failing the plausibility check, the DEM check, or the SCT are shown in light purple, dark purple, and red, respectively. Background image source: ESRI World Imagery.CC-BY · From the PDF
Figure 3 The result of the quality control by Titan for observations in Oslo for 12:00 UTC on 28 July 2019, showing the temperature observations (a) with the corresponding SCT scores (b) . The observations passing the quality control are shown in grey, whereas those failing the plausibility check, the DEM check, or the SCT are shown in light purple, dark purple, and red, respectively. Background image source: ESRI World Imagery.
Figure 3 The result of the quality control by Titan for observations in Oslo for 12:00 UTC on 28 July 2019, showing the temperature observations (a) with the corresponding SCT scores (b) . The observations passing the quality control are shown in grey, whereas those failing the plausibility check, the DEM check, or the SCT are shown in light purple, dark purple, and red, respectively. Background image source: ESRI World Imagery.CC-BY · From the PDF
Figure 4 The result of the quality control by Titan for precipitation observations in Oslo for 00:00 UTC on 4 August 2019. The values are total accumulated precipitation over the last hour. The observations (circles) passing the quality control are shown in grey, whereas those failing the buddy check or the first-guess check (radar) are shown in orange and blue, respectively. The radar data are shown as a grid of grey squares. Background image source: ESRI World Imagery.
Figure 4 The result of the quality control by Titan for precipitation observations in Oslo for 00:00 UTC on 4 August 2019. The values are total accumulated precipitation over the last hour. The observations (circles) passing the quality control are shown in grey, whereas those failing the buddy check or the first-guess check (radar) are shown in orange and blue, respectively. The radar data are shown as a grid of grey squares. Background image source: ESRI World Imagery.CC-BY · From the PDF

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Citations

Cites

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Research works printed but not linked: 1

  1. Gandin, L. S. and Hardin, R.: Objective analysis of meteorologi- cal fields, in: vol. 242, Israel program for scientific translations, Jerusalem, 1965.

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Metadata

Authors
Båserud, L., Lussana, C., Nipen, T. N., Seierstad, I. A., Oram, L., & Aspelien, T.
Affiliations
Norwegian Meteorological Institute (NO)
Corresponding author
  • Båserud, Line
  • Lussana, Cristian
  • Nipen, Thomas N.
  • Seierstad, Ivar A.
  • Oram, Louise
  • Aspelien, Trygve
ORCID
Venue
Advances in Science and Research
Publisher
Copernicus GmbH
Published
2020-07-22
Volume
17
Pages
153-163
ISSN
  • 1992-0628 (ISSN-L)
  • 1992-0636
DOI
10.5194/asr-17-153-2020
OpenAlex
W3044689994
Cited by
54
References
20
Citations by year
2026: 7 · 2025: 11 · 2024: 13 · 2023: 3 · 2022: 13 · 2021: 7
FWCI
1.88
Type
journal article
Language
en
Open access
Licence
Locations
  • Advances in science and research (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Precipitation Measurement and Analysis
  • Physical Sciences › Environmental Science › Management, Monitoring, Policy and Law › Environmental Monitoring and Data Management
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
Keywords
automated quality control, automatic weather station, spatial consistency, near-surface temperature, precipitation, numerical model output, remote sensing validation, open source software, Scandinavia

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