Absolute accuracy of water vapor measurements from six operational radiosonde types launched during AWEX‐G and implications for AIRS validation

Abstract

A detailed assessment of radiosonde water vapor measurement accuracy throughout the tropospheric column is needed for assessing the impact of observational error on applications that use the radiosonde data as input, such as forecast modeling, radiative transfer calculations, remote sensor retrieval validation, climate trend studies, and development of climatologies and cloud and radiation parameterizations. Six operational radiosonde types were flown together in various combinations with a reference‐quality hygrometer during the Atmospheric Infrared Sounder (AIRS) Water Vapor Experiment‐Ground (AWEX‐G), while simultaneous measurements were acquired from Raman lidar and microwave radiometers. This study determines the mean accuracy and variability of the radiosonde water vapor measurements relative to simultaneous measurements from the University of Colorado (CU) Cryogenic Frostpoint Hygrometer (CFH), a reference‐quality standard of known absolute accuracy. The accuracy and performance characteristics of the following radiosonde types are evaluated: Vaisala RS80‐H, RS90, and RS92; Sippican Mark IIa; Modem GL98; and the Meteolabor Snow White hygrometer. A validated correction for sensor time lag error is found to improve the accuracy and reduce the variability of upper tropospheric water vapor measurements from the Vaisala radiosondes. The AWEX data set is also used to derive and validate a new empirical correction that improves the mean calibration accuracy of Vaisala measurements by an amount that depends on the temperature, relative humidity, and sensor type. Fully corrected Vaisala radiosonde measurements are found to be suitably accurate for AIRS validation throughout the troposphere, whereas the other radiosonde types are suitably accurate under only a subset of tropospheric conditions. Although this study focuses on the accuracy of nighttime radiosonde measurements, comparison of Vaisala RS90 measurements to water vapor retrievals from a microwave radiometer reveals a 6–8% dry bias in daytime RS90 measurements that is caused by solar heating of the sensor. An AWEX‐like data set of daytime measurements is highly desirable to complete the accuracy assessment, ideally from a tropical location where the full range of tropospheric temperatures can be sampled.