Performance of the Vaisala RS80A/H and RS90 Humicap Sensors and the Meteolabor “Snow White” Chilled-Mirror Hygrometer in Paramaribo, Suriname

Author:

Verver Gé1,Fujiwara Masatomo2,Dolmans Pier3,Becker Cor4,Fortuin Paul1,Miloshevich Larry5

Affiliation:

1. Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands

2. Hokkaido University, Sapporo, Japan

3. Eindhoven University of Technology, Eindhoven, Netherlands

4. Meteorological Service Suriname, Paramaribo, Suriname

5. National Center for Atmospheric Research, Boulder, Colorado

Abstract

Abstract In climate research there is a strong need for accurate observations of water vapor in the upper atmosphere. Radiosoundings provide relative humidity profiles but the accuracy of many routine instruments is notoriously inadequate in the cold upper troposphere. In this study results from a soundings program executed in Paramaribo, Suriname (5.8°N, 55.2°W), are presented. The aim of this program was to compare the performance of different humidity sensors in the upper troposphere in the Tropics and to test different bias corrections suggested in the literature. The payload of each sounding consisted of a chilled-mirror “Snow White” sensor from Meteolabor AG, which was used as a reference, and two additional sensors from Vaisala, that is, either the RS80A, the RS80H, or the RS90. In total 37 separate soundings were made. For the RS80A a clear, dry bias of between −4% and −8% RH is found in the lower troposphere compared to the Snow White observation, confirming the findings in previous studies. A mean dry bias was found in the upper troposphere, which could be effectively corrected. The RS80H sensor shows a significant wet bias of 2%–5% in RH in the middle and upper troposphere, which has not been reported before. Comparing observations with RS80H sensors of different ages gives no indication of sensor aging or sensor contamination. It is therefore concluded that the plastic cover introduced by Vaisala to avoid sensor contamination is effective. Finally, the RS90 sensor yields a small but significant wet bias of 2%–3% below 7-km altitude. The time-lag error correction from Miloshevich et al. was applied to the Vaisala data, which resulted in an increased variability in the relative humidity profile above 9- (RS80A), 8- (RS80H), and 11-km (RS90) altitude, respectively, which is in better agreement with the Snow White data. The averaged Snow White profile is compared with the average profiles of relative humidity from the European Centre for Medium-Range Weather Forecasts (ECMWF). No significant bias is found in either the analyses or the forecasts. The correlation coefficient for the Snow White and ECMWF data between 200 and 800 hPa was 0.66 for the 36-h forecast and 0.77 for the analysis.

Publisher

American Meteorological Society

Subject

Atmospheric Science,Ocean Engineering

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