Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms

Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bi...

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Published in:Atmospheric Measurement Techniques
Main Authors: Dzambo, Andrew M., Turner, David D., Mlawer, Eli J.
Language:unknown
Published: 2021
Subjects:
Online Access:http://www.osti.gov/servlets/purl/1258743
https://www.osti.gov/biblio/1258743
https://doi.org/10.5194/amt-9-1613-2016
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spelling ftosti:oai:osti.gov:1258743 2023-07-30T04:02:06+02:00 Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms Dzambo, Andrew M. Turner, David D. Mlawer, Eli J. 2021-07-20 application/pdf http://www.osti.gov/servlets/purl/1258743 https://www.osti.gov/biblio/1258743 https://doi.org/10.5194/amt-9-1613-2016 unknown http://www.osti.gov/servlets/purl/1258743 https://www.osti.gov/biblio/1258743 https://doi.org/10.5194/amt-9-1613-2016 doi:10.5194/amt-9-1613-2016 97 MATHEMATICS AND COMPUTING 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY 2021 ftosti https://doi.org/10.5194/amt-9-1613-2016 2023-07-11T09:06:52Z Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bias (SRDB). These corrections are markedly different with MILO adding up to 40 % more moisture to the original radiosonde profile than WANG; however, the impact of the two algorithms varies with height. The accuracy of these two algorithms is evaluated using three different approaches: a comparison of precipitable water vapor (PWV), downwelling radiative closure with a surface-based microwave radiometer at a high-altitude site (5.3 km m.s.l.), and upwelling radiative closure with the space-based Atmospheric Infrared Sounder (AIRS). The PWV computed from the uncorrected and corrected RH data is compared against PWV retrieved from ground-based microwave radiometers at tropical, midlatitude, and arctic sites. Although MILO generally adds more moisture to the original radiosonde profile in the upper troposphere compared to WANG, both corrections yield similar changes to the PWV, and the corrected data agree well with the ground-based retrievals. The two closure activities – done for clear-sky scenes – use the radiative transfer models MonoRTM and LBLRTM to compute radiance from the radiosonde profiles to compare against spectral observations. Both WANG- and MILO-corrected RHs are statistically better than original RH in all cases except for the driest 30 % of cases in the downwelling experiment, where both algorithms add too much water vapor to the original profile. In the upwelling experiment, the RH correction applied by the WANG vs. MILO algorithm is statistically different above 10 km for the driest 30 % of cases and above 8 km for the moistest 30 % of cases, suggesting that the MILO correction performs better than the WANG in clear-sky scenes. Lastly, the cause of this statistical significance is likely explained by ... Other/Unknown Material Arctic SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Arctic Atmospheric Measurement Techniques 9 4 1613 1626
institution Open Polar
collection SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy)
op_collection_id ftosti
language unknown
topic 97 MATHEMATICS AND COMPUTING
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
spellingShingle 97 MATHEMATICS AND COMPUTING
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
Dzambo, Andrew M.
Turner, David D.
Mlawer, Eli J.
Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms
topic_facet 97 MATHEMATICS AND COMPUTING
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
description Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bias (SRDB). These corrections are markedly different with MILO adding up to 40 % more moisture to the original radiosonde profile than WANG; however, the impact of the two algorithms varies with height. The accuracy of these two algorithms is evaluated using three different approaches: a comparison of precipitable water vapor (PWV), downwelling radiative closure with a surface-based microwave radiometer at a high-altitude site (5.3 km m.s.l.), and upwelling radiative closure with the space-based Atmospheric Infrared Sounder (AIRS). The PWV computed from the uncorrected and corrected RH data is compared against PWV retrieved from ground-based microwave radiometers at tropical, midlatitude, and arctic sites. Although MILO generally adds more moisture to the original radiosonde profile in the upper troposphere compared to WANG, both corrections yield similar changes to the PWV, and the corrected data agree well with the ground-based retrievals. The two closure activities – done for clear-sky scenes – use the radiative transfer models MonoRTM and LBLRTM to compute radiance from the radiosonde profiles to compare against spectral observations. Both WANG- and MILO-corrected RHs are statistically better than original RH in all cases except for the driest 30 % of cases in the downwelling experiment, where both algorithms add too much water vapor to the original profile. In the upwelling experiment, the RH correction applied by the WANG vs. MILO algorithm is statistically different above 10 km for the driest 30 % of cases and above 8 km for the moistest 30 % of cases, suggesting that the MILO correction performs better than the WANG in clear-sky scenes. Lastly, the cause of this statistical significance is likely explained by ...
author Dzambo, Andrew M.
Turner, David D.
Mlawer, Eli J.
author_facet Dzambo, Andrew M.
Turner, David D.
Mlawer, Eli J.
author_sort Dzambo, Andrew M.
title Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms
title_short Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms
title_full Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms
title_fullStr Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms
title_full_unstemmed Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms
title_sort evaluation of two vaisala rs92 radiosonde solar radiative dry bias correction algorithms
publishDate 2021
url http://www.osti.gov/servlets/purl/1258743
https://www.osti.gov/biblio/1258743
https://doi.org/10.5194/amt-9-1613-2016
geographic Arctic
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genre Arctic
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op_relation http://www.osti.gov/servlets/purl/1258743
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container_title Atmospheric Measurement Techniques
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container_issue 4
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