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Retrieval of water vapor profiles from GPS/MET radio occultations

机译:从GPS / MET无线电掩星中检索水汽剖面

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摘要

Present Global Positioning System Meteorology (GPS/MET) refractivity profiles cannot distinguish between refractivity effects due to water vapor and those due to air density. Current methods of resolving the ambiguity rely heavily on ancillary upper-air data, such as National Centers for Environmental Prediction and European Centre for Medium Range Weather Forecasts (ECMWF) analyses. However, the accuracy of these ancillary sources suffers in regions where upper-air data are sparse. A method of separating the water vapor and temperature effects in GPS/MET-derived refractivity profiles with the addition of only ancillary surface pressure and temperature data and the hydrostatic assumption is discussed. Water vapor and temperature data derived fromthis method are presented and compared with accepted values. This method allows for the construction of temperature profiles with a mean bias of 0.33 K and a mean standard deviation of 1.86 K when compared with ECMWF data from 30 to 1000 mb. Height fields can also be corrected to within an average bias of 6 m and a standard deviation of 31 m. These corrected profiles result in retrieved water vapor pressure profiles with an average bias of 0.19 mb and a standard deviation of 0.53 mb.
机译:当前的全球定位系统气象(GPS / MET)折射率概况无法区分由于水蒸气引起的折射率影响和由于空气密度引起的折射率影响。解决歧义性的当前方法在很大程度上依赖于辅助的空中数据,例如国家环境预测中心和欧洲中程天气预报中心(ECMWF)分析。但是,这些辅助源的准确性在高空数据稀疏的区域中受到影响。讨论了一种方法,该方法仅添加辅助表面压力和温度数据以及静水压力假设,即可分离GPS / MET衍生的折射率剖面中的水汽和温度影响。给出了从该方法获得的水蒸气和温度数据,并将其与可接受的值进行比较。与从30到1000 mb的ECMWF数据相比,该方法可以构建平均温度偏差为0.33 K,平均标准偏差为1.86 K的温度曲线。高度场也可以校正到6 m的平均偏差和31 m的标准偏差之内。这些校正后的轮廓导致检索到的水蒸气压力轮廓具有0.19 mb的平均偏差和0.53 mb的标准偏差。

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