RS92和CFH对青藏高原大气湿度廓线观测比较分析

Comparative analysis of atmospheric humidity profiles observed by RS92 radiosonde and CFH in the Tibetan Plateau

中文关键词:  湿度(RH和χv)廓线,RS92气象探空仪,CFH霜点湿度计,上对流层-下平流层(UTLS),青藏高原

英文关键词:Humidity(RH, χv) profile,RS92 radiosonde, Cryogenic Frost-point Hygrometer (CFH), Upper troposphere-lower stratosphere (UTLS), Tibetan Plateau

中文摘要:

      [目的]为了解青藏高原大气湿度廓线准确测值分布，[资料和方法]本文对在西藏拉萨（白天）和林芝（夜间）应用Vaisala RS92气象探空仪（简称:RS92）和与iMet气象探空仪（简称:iMet）所搭配的霜点湿度计（CFH）在线观测的湿度廓线进行比较分析。[结果]结果表明，相比与测量性能最优的RS92气压（P）和气温（T）数据，iMet气压对CFH的水汽体积混合比（χV）影响在对流层未超过~100μL/L（?2%）、10km高度以上平均未超过1%；而iMet因T测值偏高使得拉萨和林芝的（液面）相对湿度（RH）在16－18km高度分别偏低3.2%和4.1%；iMet的值偏低又使得CFH在6－8 km云层高度的测值偏高约10%且RH过饱和次数增加近50%。以RS92的P、T和CFH的露（霜）点温度测值离线计算的大气湿度（RH和 χV ）廓线为准，在林芝10km高度以下，RS92经湿度传感器响应时间滞后订正的RH和χV值分别平均偏低0.4±2.8%（0.7±6.3%）和172±332μL/L（1.8±5.2%）；在拉萨未经订正RS92的RH和χV值则分别平均偏低4±7.4%（5.3±10.4%）和539±866μL/L（2.7±15.6%）；RS92的χV值在林芝和拉萨在10－16km分别偏低13±21μL/L（16±25%）和19±88μL/L（5±33%）；16 km高度以上RS92测值出现伪增湿的现象、不能反映真实大气湿度廓线垂直精细结构变化。研究建议，大气湿度廓线观测应选、测量准确的气象探空仪为平台且应避免受太阳辐射加热的影响；10km高度以下的RS92湿度数据精确度与CFH测值相当，10－16 km的RS92湿度数据,无论是订正或未被订正的均显著偏低CFH测值而不适于做长期趋势分析。

英文摘要:

      The atmospheric humidity profiles simultaneously observed by the Vaisala RS92 radiosonde (RS92) and the Cryogenic frost-point hygrometer (CFH) online operated by the iMet radiosonde (iMet) in Lhasa (daytime) and Nyingchi (nighttime), Tibet are comparatively analyzed for a better understanding of the accurate vertical distribution of water vapor over the Tibetan Plateau. With the high precision of atmospheric pressure (P) and temperature (T) measurements, RS92 indicates that CFH online water vapor volume mixing ratio (χV ) would be lower of 100μL/L(~2%) in troposphere and generally less than 1% higher above 10km while the CFH relative humidity (,on the liquid surface) would be lower of 3.2% in Lhasa and of 4.1% in Nyingchi at the altitudes of 16-18 km, and cloud may result in ~10% higher of CFH online RH values and of about 50% higher numbers of water vapor supersaturation occurrence at 6-8 km as iMet T is used. The reference of the humidity profile presented by andare offline recalculated on the basis of the RS92"s P, T and CFH"s dew (frost) point temperature for assessing the RS92 humidity data. In Nyingchi, the corrected RS92andwith the consideration of the radiosonde humidity sensor time lagging and solar heating effect, were respectively 0.4±2.8% (0.7±6.3% ) and 172±332(1.8±5.2%) lower than the reference below 10 km, in Lhasa, the uncorrected RS92 and were respectively 4±7.4%(-5.3±10.4%) and 539±866μL/L(?2.7±15.6%) lower, the corrected and uncorrected χV values respectively in Nyingchi and Lhasa were 13±21(16±25%) and 19±88(5±33%) lower from 10 to 16 km,and spurious moistening above 16 km, failing to display the fine vertical structure of the humidity profile RS92 and χV data . It is suggested that the atmospheric humidity profile observation should be conducted through the radiosonde platform with highly precision of and T measurements and be from the influence of solar heating effects on the radiosonde sensors; RS92 humidity profile below 10 km is sufficiently accurate as that of CFH, however, either the corrected or uncorrected RS92 humidity data from 10 to 16 km is significantly lower and should not be suitable for long-term trend analysis.