Using Radiance Closure Experiments to Evaluate Vaisala RS92 Radiosonde Solar Radiation Dry Bias Correction Algorithms

Vaisala RS92 radiosondes are among the most widely used upper-air instruments in the world. The RS92 radiosonde has a well-documented history of relative humidity (RH) dry-biased measurements induced by solar radiation. Several correction algorithms have been developed to correct for this dry bias. This study evaluates two of these correction algorithms: Miloshevich et al. (JGR 2009) and Wang et al. (JTECH 2013). A radiative closure approach is used to evaluate these two corrections, using both space-borne and ground-based radiance observations. In this former, AIRS radiance data is extracted over a number of the U.S. Department of Energy (DOE) Atmospheric Radiance Measurements (ARM) sites. Corrected RS92 RH data taken from these same sites is used as input for an upwelling radiance calculation in the Line-by-Line Radiation Transfer Model (LBLRTM). Radiance measurements from the LBLRTM output are convolved with the AIRS instrument function to allow for a direct comparison of radiances. Since the LBLRTM does not explicitly include clouds, the comparisons were done in clear-sky scenes and hence a cloud-screening algorithm over the AIRS footprint was implemented. The ground-based closure exercise used a 15-channel 183 GHz microwave radiometer and RS92 data during the 2009 RHUBC-II campaign, where a large dataset was collected in a desert climate located in the Atacama at 5320 m MSL. The Monochromatic Radiance Transfer Model (MonoRTM) is used to calculate downwelling radiances every 10 MHz from 170-183.31 GHz for the respective RH corrected radiosondes. These calculations are then convolved to match the radiometer channels. Results from the two radiance closure experiments are used to characterize the accuracy and skill of the two correction algorithms in a variety of conditions, and the implications are discussed.