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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ftdoajarticles:oai:doaj.org/article:f13b866b3d904bca895c9a567d317822 2023-05-15T15:16:25+02:00 Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms A. M. Dzambo D. D. Turner E. J. Mlawer 2016-04-01T00:00:00Z https://doi.org/10.5194/amt-9-1613-2016 https://doaj.org/article/f13b866b3d904bca895c9a567d317822 EN eng Copernicus Publications http://www.atmos-meas-tech.net/9/1613/2016/amt-9-1613-2016.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548 1867-1381 1867-8548 doi:10.5194/amt-9-1613-2016 https://doaj.org/article/f13b866b3d904bca895c9a567d317822 Atmospheric Measurement Techniques, Vol 9, Iss 4, Pp 1613-1626 (2016) Environmental engineering TA170-171 Earthwork. Foundations TA715-787 article 2016 ftdoajarticles https://doi.org/10.5194/amt-9-1613-2016 2022-12-31T13:30:36Z 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. The cause of this statistical significance is likely explained by the fact ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Atmospheric Measurement Techniques 9 4 1613 1626 |
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ftdoajarticles |
language |
English |
topic |
Environmental engineering TA170-171 Earthwork. Foundations TA715-787 |
spellingShingle |
Environmental engineering TA170-171 Earthwork. Foundations TA715-787 A. M. Dzambo D. D. Turner E. J. Mlawer Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms |
topic_facet |
Environmental engineering TA170-171 Earthwork. Foundations TA715-787 |
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. The cause of this statistical significance is likely explained by the fact ... |
format |
Article in Journal/Newspaper |
author |
A. M. Dzambo D. D. Turner E. J. Mlawer |
author_facet |
A. M. Dzambo D. D. Turner E. J. Mlawer |
author_sort |
A. M. Dzambo |
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 |
publisher |
Copernicus Publications |
publishDate |
2016 |
url |
https://doi.org/10.5194/amt-9-1613-2016 https://doaj.org/article/f13b866b3d904bca895c9a567d317822 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Atmospheric Measurement Techniques, Vol 9, Iss 4, Pp 1613-1626 (2016) |
op_relation |
http://www.atmos-meas-tech.net/9/1613/2016/amt-9-1613-2016.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548 1867-1381 1867-8548 doi:10.5194/amt-9-1613-2016 https://doaj.org/article/f13b866b3d904bca895c9a567d317822 |
op_doi |
https://doi.org/10.5194/amt-9-1613-2016 |
container_title |
Atmospheric Measurement Techniques |
container_volume |
9 |
container_issue |
4 |
container_start_page |
1613 |
op_container_end_page |
1626 |
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1766346705819664384 |