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

Journal Article · Tue Apr 12 00:00:00 EDT 2016 · Atmospheric Measurement Techniques (Online)

DOI:https://doi.org/10.5194/amt-9-1613-2016· OSTI ID:1247003

Dzambo, Andrew M. ; Turner, David D. ; Mlawer, Eli J.

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 the fact the WANG correction also accounts for cloud cover – a condition not accounted for in the radiance closure experiments.

• Research Organization: Univ. of Oklahoma, Norman, OK (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER)
• Grant/Contract Number: SC0008830
• OSTI ID: 1247003
• Alternate ID(s): OSTI ID: 1258743
• Journal Information: Atmospheric Measurement Techniques (Online), Journal Name: Atmospheric Measurement Techniques (Online) Vol. 9 Journal Issue: 4; ISSN 1867-8548
• Publisher: Copernicus Publications, EGU
• Country of Publication: Germany
• Language: English

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97 MATHEMATICS AND COMPUTING
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