Radiation Dry Bias Correction of Vaisala RS92 Humidity Data and Its Impacts on Historical Radiosonde Data

Author:

Wang Junhong1,Zhang Liangying2,Dai Aiguo3,Immler Franz4,Sommer Michael5,Vömel Holger5

Affiliation:

1. National Center for Atmospheric Research,* Boulder, Colorado, and Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York

2. National Center for Atmospheric Research,* Boulder, Colorado

3. Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York, and National Center for Atmospheric Research,* Boulder, Colorado

4. European Commission, Brussels, Belgium

5. GRUAN Lead Centre, Deutscher Wetterdienst, Lindenberg, Germany

Abstract

Abstract The Vaisala RS92 radiosonde is the most widely used type of sonde in the current global radiosonde network. One of the largest biases in the RS92 humidity data is its daytime solar radiation dry bias (SRDB). An algorithm [referred to as NCAR radiation bias correction (NRBC)] was developed to correct the SRDB based on a more complicated algorithm developed by the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN). The NRBC to relative humidity (RH) is a function of the measured RH and temperature, and the temperature solar radiation correction. The latter varies with pressure, season, and time of the day. The RH correction has a mean magnitude of about 2%–4% and 6%–8% in the lower–midtroposphere and upper troposphere, respectively. The NRBC is evaluated against the GRUAN-corrected RS92 data and the ground-based GPS-estimated precipitable water (PW). The corrected RH agrees with the GRUAN data within ±0.5% on average, with standard deviations of about 1%–2% and 2%–6% in the lower–midtroposphere and upper troposphere, respectively. The NRBC leads to reduced mean biases, and better agreement with the GPS PW and its diurnal cycle. The NRBC has been applied to historical radiosonde data at 65 stations. The radiosonde humidity data, both with and without the NRBC, are homogenized using the method of Dai et al. (2011). The NRBC results in consistently elevated RHs throughout the whole record in the homogenized data. This could have a significant impact on global reanalysis products when they are assimilated into the reanalysis models. However, the NRBC has insignificant effects on the long-term trends as the correction is primarily for mean biases.

Publisher

American Meteorological Society

Subject

Atmospheric Science,Ocean Engineering

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