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  • 1
    Publication Date: 2016-11-01
    Description: Some real-time radiosonde reports are now available with higher vertical resolution and higher precision than the alphanumeric TEMP code. There are also extra metadata; for example, the software version may indicate whether humidity corrections have been applied at the station. Numerical weather prediction (NWP) centers and other users need to start using the new Binary Universal Form for Representation of Meteorological Data (BUFR) reports because the alphanumeric codes are being withdrawn. TEMP code has various restrictions and complexities introduced when telecommunication speed and costs were overriding concerns; one consequence is minor temperature rounding errors. In some ways BUFR reports are simpler: the whole ascent should be contained in a single report. BUFR reports can also include the time and location of each level; an ascent takes about 2 h and the balloon can drift 100 km or more laterally. This modernization is the largest and most complex change to the worldwide reporting of radiosonde observations for many years; international implementation is taking longer than planned and is very uneven. The change brings both opportunities and challenges. The biggest challenge is that the number and quality of the data from radiosonde ascents may suffer if the assessment of the BUFR reports and two-way communication between data producers and data users are not given the priority they require. It is possible that some countries will only attempt to replicate the old reports in the new format, not taking advantage of the benefits, which include easier treatment of radiosonde drift and a better understanding of instrument and processing details, as well as higher resolution.
    Print ISSN: 0003-0007
    Electronic ISSN: 1520-0477
    Topics: Geography , Physics
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  • 2
    Publication Date: 2017-11-06
    Description: There are numerous networks and initiatives concerned with the non-satellite-observing segment of Earth observation. These are owned and operated by various entities and organisations often with different practices, norms, data policies, etc. The Horizon 2020 project GAIA–CLIM is working to improve our collective ability to use an appropriate subset of these observations to rigorously characterise satellite observations. The first fundamental question is which observations from the mosaic of non-satellite observational capabilities are appropriate for such an application. This requires an assessment of the relevant, quantifiable aspects of the measurement series which are available. While fundamentally poor or incorrect measurements can be relatively easily identified, it is metrologically impossible to be sure that a measurement series is correct. Certain assessable aspects of the measurement series can, however, build confidence in their scientific maturity and appropriateness for given applications. These are aspects such as that it is well documented, well understood, representative, updated, publicly available and maintains rich metadata. Entities such as the Global Climate Observing System have suggested a hierarchy of networks whereby different subsets of the observational capabilities are assigned to different layers based on such assessable aspects. Herein, we make a first attempt to formalise both such a system-of-systems networks concept and a means by which to, as objectively as possible, assess where in this framework different networks may reside. In this study, we concentrate on networks measuring primarily a subset of the atmospheric Essential Climate Variables of interest to GAIA–CLIM activities. We show assessment results from our application of the guidance and how we plan to use this in downstream example applications of the GAIA–CLIM project. However, the approach laid out should be more widely applicable across a broad range of application areas. If broadly adopted, the system-of-systems approach will have potential benefits in guiding users to the most appropriate set of observations for their needs and in highlighting to network owners and operators areas for potential improvement.
    Print ISSN: 2193-0856
    Electronic ISSN: 2193-0864
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 3
    Publication Date: 2019-01-07
    Description: The characterisation of errors and uncertainties in numerical weather prediction (NWP) model fields is a major challenge that is addressed as part of the Horizon 2020 Gap Analysis for Integrated Atmospheric ECV CLImate Monitoring (GAIA-CLIM) project. In that regard, observations from the GCOS (Global Climate Observing System) Reference Upper-Air Network (GRUAN) radiosondes are being used at the Met Office and European Centre for Medium-Range Weather Forecasts (ECMWF) to assess errors and uncertainties associated with model data. The software introduced in this study and referred to as the GRUAN processor has been developed to collocate GRUAN radiosonde profiles and NWP model fields, simulate top-of-atmosphere brightness temperature at frequencies used by space-borne instruments, and propagate GRUAN uncertainties in that simulation. A mathematical framework used to estimate and assess the uncertainty budget of the comparison of simulated brightness temperature is also proposed. A total of 1 year of GRUAN radiosondes and matching NWP fields from the Met Office and ECMWF have been processed and analysed for the purposes of demonstration of capability. We present preliminary results confirming the presence of known biases in the temperature and humidity profiles of both NWP centres. The night-time difference between GRUAN and Met Office (ECMWF) simulated brightness temperature at microwave frequencies predominantly sensitive to temperature is on average smaller than 0.1 K (0.4 K). Similarly, this difference is on average smaller than 0.5 K (0.4 K) at microwave frequencies predominantly sensitive to humidity. The uncertainty estimated for the Met Office–GRUAN difference ranges from 0.08 to 0.13 K for temperature-sensitive frequencies and from 1.6 to 2.5 K for humidity-sensitive frequencies. From the analysed sampling, 90 % of the comparisons are found to be in statistical agreement. This initial study has the potential to be extended to a larger collection of GRUAN profiles, covering multiple sites and years, with the aim of providing a robust estimation of both errors and uncertainties of NWP model fields in radiance space for a selection of key microwave and infrared frequencies.
    Print ISSN: 1867-1381
    Electronic ISSN: 1867-8548
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 4
    Publication Date: 2018-06-01
    Print ISSN: 1530-261X
    Electronic ISSN: 1530-261X
    Topics: Geosciences , Physics
    Published by Wiley
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  • 5
    Publication Date: 2018-07-18
    Description: The characterisation of errors and uncertainties in numerical weather prediction (NWP) model fields is a major challenge that is addressed as part of the Horizon 2020 Gap Analysis for Integrated Atmospheric ECV CLImate Monitoring (GAIA-CLIM) project. In that regard, observations from the GCOS (Global Climate Observing System) Reference Upper-Air Network (GRUAN) radiosondes are being used at the Met Office and European Centre for Medium-range Weather Forecasts (ECMWF) to assess errors and uncertainties associated with model data. The software introduced in this study and referred to as the GRUAN Processor has been developed to collocate GRUAN radiosonde profiles and NWP model fields, simulate top-of-atmosphere brightness temperature at frequencies used by space-borne instruments, and propagate GRUAN uncertainties in that simulation. A mathematical framework used to estimate and assess the uncertainty budget of the comparison of simulated brightness temperature is also proposed. One year of GRUAN radiosondes and matching NWP fields from the Met Office and ECMWF have been processed and analysed for the purposes of demonstration of capability. We present preliminary results confirming the presence of known biases in the temperature and humidity profiles of both NWP centres. The night-time difference between GRUAN and Met Office (ECMWF) simulated brightness temperature at microwave frequencies predominantly sensitive to temperature is on average smaller than 0.1K (0.4K). Similarly, this difference is on average smaller than 0.5K (0.4K) at microwave frequencies predominantly sensitive to humidity. The uncertainty estimated for the Met Office – GRUAN difference ranges from 0.08 to 0.13K for temperature sensitive frequencies and from 1.6 to 2.5K for humidity sensitive frequencies. From the analysed sampling, 90% of the comparisons are found to be in statistical agreement. This initial study has the potential to be extended to a larger collection of GRUAN profiles, covering multiple sites and years, with the aim of providing a robust estimation of both errors and uncertainties of NWP model fields in radiance space for a selection of key microwave and infrared frequencies.
    Electronic ISSN: 1867-8610
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 6
  • 7
    Publication Date: 2017-04-11
    Description: There are numerous networks and initiatives concerned with the non-satellite observing segment of Earth Observation. These are owned and operated by various entities and organisations often with different practices, norms, data policies etc. The Horizon 2020 project GAIA-CLIM is working to improve our collective ability to use an appropriate subset of these observations to rigorously characterise satellite observations. The first fundamental question is which observations from the mosaic of non-satellite observational capabilities are appropriate for such an application. This requires an assessment of the relevant, quantifiable aspects of the measurement series which are available. While fundamentally poor or incorrect measurements can be relatively easily identified, it is metrologically impossible to be sure that a measurement series is correct. Certain assessable aspects of the measurement series can, however, build confidence in their scientific maturity and appropriateness for given applications. These are aspects such as that it is well documented, well understood, representative, updated, publicly available, maintains rich metadata etc. Entities such as the Global Climate Observing System have suggested a hierarchy of networks whereby different subsets of the observational capabilities are assigned to different layers based upon such assessable aspects. Herein, we make a first attempt to formalise both such a system-of-systems networks concept and a means by which to, as objectively as possible, assess where in this framework different networks may reside. In this study, we concentrate upon networks measuring primarily a sub-set of the atmospheric Essential Climate Variables of interest to GAIA-CLIM activities. We show assessment results from our application of the guidance and how we plan to use this in downstream exemplary applications of the GAIA-CLIM project. However, the approach laid out could be more widely applicable. If broadly adopted, the system-of-systems approach will have potential benefits in guiding users to the most appropriate set of observations for their needs, and in highlighting to network owners and operators areas for potential improvement.
    Electronic ISSN: 2193-0872
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 8
    Publication Date: 2022-01-31
    Description: The air–sea interface is a key gateway in the Earth system. It is where the atmosphere sets the ocean in motion, climate/weather-relevant air–sea processes occur, and pollutants (i.e., plastic, anthropogenic carbon dioxide, radioactive/chemical waste) enter the sea. Hence, accurate estimates and forecasts of physical and biogeochemical processes at this interface are critical for sustainable blue economy planning, growth, and disaster mitigation. Such estimates and forecasts rely on accurate and integrated in situ and satellite surface observations. High-impact uses of ocean surface observations of essential ocean/climate variables (EOVs/ECVs) include (1) assimilation into/validation of weather, ocean, and climate forecast models to improve their skill, impact, and value; (2) ocean physics studies (i.e., heat, momentum, freshwater, and biogeochemical air–sea fluxes) to further our understanding and parameterization of air–sea processes; and (3) calibration and validation of satellite ocean products (i.e., currents, temperature, salinity, sea level, ocean color, wind, and waves). We review strengths and limitations, impacts, and sustainability of in situ ocean surface observations of several ECVs and EOVs. We draw a 10-year vision of the global ocean surface observing network for improved synergy and integration with other observing systems (e.g., satellites), for modeling/forecast efforts, and for a better ocean observing governance. The context is both the applications listed above and the guidelines of frameworks such as the Global Ocean Observing System (GOOS) and Global Climate Observing System (GCOS) (both co-sponsored by the Intergovernmental Oceanographic Commission of UNESCO, IOC–UNESCO; the World Meteorological Organization, WMO; the United Nations Environment Programme, UNEP; and the International Science Council, ISC). Networks of multiparametric platforms, such as the global drifter array, offer opportunities for new and improved in situ observations. Advances in sensor technology (e.g., low-cost wave sensors), high-throughput communications, evolving cyberinfrastructures, and data information systems with potential to improve the scope, efficiency, integration, and sustainability of the ocean surface observing system are explored.
    Type: Article , PeerReviewed
    Format: text
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  • 9
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Centurioni, L. R., Turton, J., Lumpkin, R., Braasch, L., Brassington, G., Chao, Y., Charpentier, E., Chen, Z., Corlett, G., Dohan, K., Donlon, C., Gallage, C., Hormann, V., Ignatov, A., Ingleby, B., Jensen, R., Kelly-Gerreyn, B. A., Koszalka, I. M., Lin, X., Lindstrom, E., Maximenko, N., Merchant, C. J., Minnett, P., O'Carroll, A., Paluszkiewicz, T., Poli, P., Poulain, P., Reverdin, G., Sun, X., Swail, V., Thurston, S., Wu, L., Yu, L., Wang, B., & Zhang, D. Global in situ observations of essential climate and ocean variables at the air-sea interface. Frontiers in Marine Science, 6, (2019): 419, doi: 10.3389/fmars.2019.00419.
    Description: The air–sea interface is a key gateway in the Earth system. It is where the atmosphere sets the ocean in motion, climate/weather-relevant air–sea processes occur, and pollutants (i.e., plastic, anthropogenic carbon dioxide, radioactive/chemical waste) enter the sea. Hence, accurate estimates and forecasts of physical and biogeochemical processes at this interface are critical for sustainable blue economy planning, growth, and disaster mitigation. Such estimates and forecasts rely on accurate and integrated in situ and satellite surface observations. High-impact uses of ocean surface observations of essential ocean/climate variables (EOVs/ECVs) include (1) assimilation into/validation of weather, ocean, and climate forecast models to improve their skill, impact, and value; (2) ocean physics studies (i.e., heat, momentum, freshwater, and biogeochemical air–sea fluxes) to further our understanding and parameterization of air–sea processes; and (3) calibration and validation of satellite ocean products (i.e., currents, temperature, salinity, sea level, ocean color, wind, and waves). We review strengths and limitations, impacts, and sustainability of in situ ocean surface observations of several ECVs and EOVs. We draw a 10-year vision of the global ocean surface observing network for improved synergy and integration with other observing systems (e.g., satellites), for modeling/forecast efforts, and for a better ocean observing governance. The context is both the applications listed above and the guidelines of frameworks such as the Global Ocean Observing System (GOOS) and Global Climate Observing System (GCOS) (both co-sponsored by the Intergovernmental Oceanographic Commission of UNESCO, IOC–UNESCO; the World Meteorological Organization, WMO; the United Nations Environment Programme, UNEP; and the International Science Council, ISC). Networks of multiparametric platforms, such as the global drifter array, offer opportunities for new and improved in situ observations. Advances in sensor technology (e.g., low-cost wave sensors), high-throughput communications, evolving cyberinfrastructures, and data information systems with potential to improve the scope, efficiency, integration, and sustainability of the ocean surface observing system are explored.
    Description: LC, LB, and VH were supported by NOAA grant NA15OAR4320071 and ONR grant N00014-17-1-2517. RL was supported by NOAA/AOML and NOAA’s Ocean Observation and Monitoring Division. NM was partly supported by NASA grant NNX17AH43G. IK was supported by the Nordic Seas Eddy Exchanges (NorSEE) funded by the Norwegian Research Council (Grant 221780). DZ was partly funded by the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement NA15OAR4320063. RJ was supported by the USACE’s Civil Works 096×3123.
    Keywords: Global in situ observations ; Air-sea interface ; Essential climate and ocean variables ; Climate variability and change ; Weather forecasting ; SVP drifters
    Repository Name: Woods Hole Open Access Server
    Type: Article
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