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Comparison of Aura MLS Water Vapor Measurements with GFS and NAM Analyses in the Upper Troposphere–Lower Stratosphere

机译:高层地流层中GFS和NAM分析的Aura MLS水蒸气测量的比较

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摘要

Water vapor mixing ratios in the upper troposphere and lower stratospheremeasured by the AuraMicrowave Limb Sounder (MLS) version 2.2 instrument have been compared with Global Forecast System(GFS) analyses at five levels within the 300–100-hPa layer and North AmericanMesoscale (NAM) model analyses at six levels within the 300–50-hPa layer over the two years of 2005 and 2006 at four analysis times (e.g., 0000, 0600, 1200, and 1800UTC). Probability density functions of the vapormixing ratios suggest that both analyses are oftenmoister than Aura MLS values, but NAM model analyses agree somewhat better with Aura MLS measurements than GFS model analyses over the same North American domain at the five common levels. Examining five subsets of the global GFS domain, the GFS model analysis is moister than Aura MLS estimates everywhere but at 150 and 100 hPa in all regions outside of the tropics. NAM model analysis water vapor mixing ratios exceeded the AuraMLS values at all levels from 250 to 150 hPa in all four seasons of both years and some seasons at 100 and 50 hPa. Moist biases in winter and spring of both years were similar at all levels, but these moist biases in summer and fallwere smaller in 2005 than in 2006 at all levels. These differences may be due to the change in the NAM from using the Eta Model to using the Weather Research and Forecasting model (WRF) in June 2006.
机译:上层对流层中的水蒸气混合比和通过AuramicroWave Lemb Soulder(MLS)版本2.2仪器的速度较低,与全球预测系统(GFS)进行了比较了300-100-HPA层和北美尺度(NAM)的五个层次分析在2005年和2006年的300-50 -50-HPA层内的模型分析在2005年和2006年的四个分析时间(例如,0000,0600,1200和1800UTC)。 Vapormixing比率的概率密度函数表明,两种分析都是比Aura MLS值的常时,但是NAM模型分析与Aura MLS测量比GFS模型在五个共同级别的同一北美领域的模型分析比较更好。检查全球GFS域的五个子集,GFS模型分析是烟雾,而不是Aura MLS估计,但在热带地区外的所有地区的150和100 HPA。 NAM模型分析水蒸气混合比率在两年内的所有四季和1000多个HPA的所有四季中的所有级别超过250至150 HPA的AurAmL值。冬季和春季的潮湿偏见在各级相似,但夏季的这些潮湿的偏见和2005年的跌倒小于各级的2006年。这些差异可能是由于NAM在2006年6月使用ETA模型使用ETA模型的变化来使用天气研究和预测模型(WRF)。

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