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Preliminary Estimation of Specific Humidity Profiles with Wind Profile Radar
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摘要: 基于湍流散射理论，运用边界层风廓线雷达 (WPR) 联合RASS (Radio Acoustic Sounding System), GPS/PWV (Global Position System/Precipitable Water Vapor) 进行全遥感系统的大气比湿廓线反演试验，并对影响因子进行分析。利用2011年8—9月云南大理综合探测试验数据的反演结果与探空数据进行比较分析，结果表明：WPR联合探空的温度廓线和起始边界比湿 (q0) 反演大气比湿廓线，与探空大气比湿廓线相比具有相同的变化趋势，标准差为0.84 g·kg-1，误差随高度增加呈递增趋势；WPR联合RASS, GPS/PWV数据反演大气比湿廓线，与探空大气比湿廓线的标准差为0.85 g·kg-1。参加反演的数据中，折射指数结构常数Cn2与谱宽σturb2对反演影响最大，反演算法中大气折射指数梯度M符号的判断对反演精度也有较大影响。Abstract: As a new type of detection instrument, wind profile radar (WPR) can detect meteorological factors such as wind profiles, spectral width, and refractive index structure constant and so on. The special detecting ability of WPR decides its broad application in atmospheric science research, meteorological operation application, climate research, aviation security and many other areas. With the advances of detection, a new specific humidity profiles retrieving method with WPR is proposed.Based on the turbulent backscattering theory, the method of estimating specific humidity profiles using boundary layer wind profile radar characteristics of clear-air echoes is devised. A retrieving test of specific humidity profiles are carried out with the data of observational campaign conducted from 15 Aug to 10 Sep in 2011 at a meteorological station of Dali, Yunnan Province, analyzing the main factors of retrieving accuracy. In the low atmosphere the refractive index gradient (M) is mainly influenced by three factors: dq/dz by 80.39%, the atmospheric temperature (T) by 12.75%, and the specific humidity q by 6.86% on average, respectively. Obviously, the dq/dz item is the most important factor, namely, there is a close relationship between the refractive index gradient and specific humidity.It is the measurement of refractive index gradient that turns out to retrieve specific humidity profiles with the help of WPR. The volume reflectivity (η) of turbulence echoes can indicate the fluctuation of atmosphere specific humidity due to the good correlation with M. Another factor that matters is the atmospheric turbulence dissipation rate which is under the influence of the signal spectral width observed by WPR. Radio Acoustic Sounding System (RASS) provides virtual temperature in retrieving of specific humidity profiles with the measurement of acoustic speed; PWV from GPS provides a method to obtain the initial boundary specific humidity; estimation of specific humidity profiles comparing with radiosonde data at the same time is conducted with WPR, RASS and GPS data.Results show that WPR can successfully retrieve specific humidity profiles with a certain degree of error. Among many factors that affect the retrieving accuracy, the determining of the sign of M, the refractive index structure constant and turbulence spectral width plays the key role, while the temperature and pressure are not so important. This new method can retrieve specific humidity profiles simply with the remote sensing instruments. The specific humidity retrieving from WPR, temperature profilers and initial boundary specific humidity from radiosonde shows the same trend comparing with which observed by radiosonde. The mean deviation and standard deviation turns out to be 0.75 g·kg-1 and 0.8 g·kg-1 respectively, both showing an increasing trend with height. With the assistance of WPR, GPS/PWV and RASS data, the retrieving mean deviation and standard deviation of specific humidity is 0.64 g·kg-1 and 0.85 g·kg-1 comparing with the observation of radiosonde.
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图 1 2011年9月2日20:00折射指数梯度M (a)、比湿q (b) 随高度分布
Fig. 1 The height distribution of refractive index gradient M (a) and specific humidity q (b) at 2000 BT 2 Sep 2011
图 4 WPR反演比湿与探空比湿廓线比对
(a) WPR反演与探空散点图, (b) 平均偏差随高度变化, (c) 标准差随高度变化
Fig. 4 The comparison of specific humidity between the retrieved from WPR and RS
(a) the scatter diagram of humidity from WPR and RS，(b) the mean deviation between WPR and RS，(c) the standard deviation between WPR and RS
图 5 折射指数结构常数Cn2与谱宽σturb2对反演比湿精度的影响
Fig. 5 The specific humidity retrieving accuracy effect of refractive index structure constant Cn2 and spectral width σturb2
图 6 WPR联合探空反演比湿与探空比湿比对
(a) 探空与WPR确定M符号反演比湿廓线, (b) 探空M与WPR确定M符号, (c) 探空与探空确定M符号反演比湿廓线
Fig. 6 The comparison of specific humidity between the retrieved from WPR and RS
(a) specific humidity profiles retrieved by sign of M from WPR and RS, (b) the sign of M from WPR and RS, (c) specific humidity profiles retrieved by sign of M from RS and observed
图 7 WPR, RASS和GPS反演比湿与探空比湿廓线比对
(a) WPR，RASS和GPS反演与探空比湿散点图，(b) 平均偏差随高度变化，(c) 标准差随高度变化
Fig. 7 The comparison of specific humidity between the retrieved and RS
(a) the scatter diagram of specific humidity from WPR，RASS，GPS and RS，(b) the mean deviation between WPR，RASS，GPS and RS，(c) the standard deviation between WPR，RASS，GPS and RS
图 8 WPR, RASS, GPS反演与探空比湿廓线比对
(a) 2011年8月16日08:00, (b) 2011年8月21日08:00, (c) 2011年8月21日20:00
Fig. 8 The comparison of specific humidity profilers among the retrieved from WPR, RASS, GPS and RS, respectively
(a) 0800 BT 16 Aug 2011, (b) 0800 BT 21 Aug 2011, (c) 2000 BT 21 Aug 2011
表 1 不同高度水汽含量占全程水汽总量比例
Table 1 The ratio of vapor accounting for the total below different height
距离地面的高度/m 距地高度单位气柱
平均水汽总量/mm距地高度占全程
水汽总量比例/%距地高度占全程
水汽总量比例离差/%300 3.55 12.46 1.34 1000 10.62 36.17 3.53 1500 14.70 50.08 4.78 2000 18.09 61.63 5.40 3000 23.11 78.67 5.48 4000 26.23 89.20 3.91 5000 28.03 95.25 2.39 6000 28.89 98.10 1.30 7000 29.25 99.29 0.61 
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表 2 引入RASS数据与GPS数据的误差影响
Table 2 The effect of taking RASS data and GPS data into account on errors
引入数据 平均偏差/(g·kg-1) 标准差/(g·kg-1) RASS 0.06 0.32 GPS -0.06 0.85
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