Quality-Controlled Upper-Air Sounding Dataset for TiMREX/SoWMEX: Development and Corrections

Abstract

Abstract During the Terrain-Influenced Monsoon Rainfall Experiment (TiMREX), which coincided with Taiwan’s Southwesterly Monsoon Experiment—2008 (SoWMEX-08), the upper-air sounding network over the Taiwan region was enhanced by increasing the radiosonde (“sonde”) frequency at its operational sites and by adding several additional sites (three that were land based and two that were ship based) and aircraft dropsondes. During the special observing period of TiMREX (from 15 May to 25 June 2008), 2330 radiosonde observations were successfully taken from the enhanced network. Part of the challenge of processing the data from the 13 upsonde sites is that four different sonde types (Vaisala RS80, Vaisala RS92, Meisei, and Graw) were used. Post–field phase analyses of the sonde data revealed a significant dry bias in many of the sondes—in particular, in the data from the Vaisala RS80 sondes that were used at four sites. In addition, contamination of the sonde data by the ship’s structure resulted in poor-quality low-level thermodynamic data at a key oceanic site. This article examines the methods used to quality control the sonde data and, when possible, to correct them. Particular attention is given to the correction of the humidity field and its impact on various convective measures. Comparison of the corrected sonde humidity data with independent estimates shows good agreement, suggesting that the corrections were effective in removing many of the sonde humidity errors. Examining various measures of convection shows that use of the humidity-corrected sondes gives a much different perspective on the characteristics of convection during TiMREX. For example, at the RS80 sites, use of the corrected humidity data increases the mean CAPE by ∼500 J kg−1, decreases mean convective inhibition (CIN) by 80 J kg−1, and increases the midlevel convective mass flux by greater than 70%. Ultimately, these corrections will provide more accurate moisture fields for diagnostic analyses and modeling studies.