Evaluation of Humidity Correction Methods for Vaisala RS92 Tropical Sounding Data

This study examines the DigiCORA andGlobal Climate Observing SystemReferenceUpper-Air Network (GRUAN) humidity corrections of Vaisala RS92 radiosondes at three sites over the tropical Indian Ocean and surrounding areas during theDynamics of theMadden–Julian Oscillation (DYNAMO) field campaign in 2011. The proprietary DigiCORA correction algorithm is built into the ground station software provided by Vaisala, whereas the GRUAN correction is an open source algorithm. Included in the GRUAN data product are uncertainty estimates for their corrections. This information is used to examine the statistical consistency of the various corrections. In general, the algorithms produce a positive relative humidity (RH) correction that increases with altitude related primarily to a solar radiation dry bias adjustment. For example, in daytime soundings the relative RH correction increases from a few percent for temperatures .08C to 20%–40% between 100 and 200 hPa. Comparison of corrected RH vertical profiles show only small differences (on the order of a few percent or less at any given level) between the DigiCORA and GRUAN algorithms, such that these corrections are considered to be statistically consistent at most levels. In evaluating corrected humidity data with independent estimates of total precipitable water (TPW), good agreement was found at all sites between corrected sounding and ground-basedmicrowave radiometer (MWR) estimates of TPW with mean differences #0.9mm (or ,2%), which is well within the uncertainty of these measurements. Overall, the correction algorithms examined herein perform well over a wide range of tropical moisture conditions.