Performance of the Vaisala RS80A/H and RS90 Humicap Sensors and the Meteolabor “Snow White” Chilled-Mirror Hygrometer in Paramaribo, Suriname
Performance of the Vaisala RS80A/H and RS90 Humicap Sensors and the Meteolabor “Snow White” Chilled-Mirror Hygrometer in Paramaribo, Suriname
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DOI：
10.1175/jtech1941.1
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发表时间：
2006-11
影响因子：
2.2
通讯作者：
Gé Fujiwara;Masatomo Dolmans;G. Verver;M. Fujiwara;Pier Dolmans;P. Fortuin;L. Miloshevich
中科院分区：
文献类型：
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作者：
Gé Fujiwara;Masatomo Dolmans;G. Verver;M. Fujiwara;Pier Dolmans;P. Fortuin;L. Miloshevich
在气候研究中，强烈需要准确观测高层大气中的水蒸气。无线电探测提供了相对湿度剖面，但许多常规仪器的精度在寒冷的对流层上层是众所周知的不足。本研究介绍了在苏里南帕拉马里博（北纬 5.8°，西经 55.2°）执行的探测计划的结果。该计划的目的是比较热带对流层上层不同湿度传感器的性能，并测试文献中建议的不同偏差校正。每次探测的有效载荷包括用作参考的 Meteolabor AG 的冷镜“Snow White”传感器，以及维萨拉的两个附加传感器，即 RS80A、RS80H 或 RS90。总共进行了 37 次单独的探测。与白雪公主观测相比，RS80A 在对流层低层发现了 4% 至 8% RH 的明显干燥偏差，证实了之前研究的结果。在对流层上层发现了平均干偏差，可以有效纠正。 RS80H传感器在对流层中上层的相对湿度中显示出2%~5%的显着湿偏差，这是以前没有报道过的。与不同使用年限的 RS80H 传感器进行比较观察结果，没有发现传感器老化或传感器污染的迹象。因此得出的结论是，维萨拉为避免传感器污染而引入的塑料盖是有效的。最后，RS90 传感器在 7 公里海拔以下会产生 2%–3% 的小但显着的湿偏差。 Miloshevich 等人的时滞误差修正。将其应用于维萨拉数据，导致分别在 9 公里 (RS80A)、8 公里 (RS80H) 和 11 公里 (RS90) 高度以上的相对湿度剖面变化性增加，这与白雪公主数据更加一致。将白雪公主的平均剖面与欧洲中期天气预报中心 (ECMWF) 的平均相对湿度剖面进行比较。分析或预测均未发现重大偏差。白雪公主和 ECMWF 数据在 200 至 800 hPa 之间的相关系数，36 小时预报为 0.66，分析为 0.77。
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.