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1.
利用黄土高原地区加强观测期探空资料和大气红外探测器(Atmospheric Infrared Sounder,AIRS)反演的温度、相对湿度廓线资料,评估了AIRS反演产品在黄土高原的适用性,以及利用AIRS温度廓线计算边界层高度的可行性。结果表明,各种边界层高度计算方法相关性显著,平均高度差异一般不超过200 m;Richardson数临界值的选取对确定边界层高度的影响不大。AIRS反演的大气温度和相对湿度均能很好地反映环境温湿的变化;温度平均偏差在±1 K以内,均方根误差一般不超过2 K;AIRS反演的地面气温误差相对较大,平均偏差和均方根误差分别为-1.68 K和3.32 K,并且会影响边界层高度的确定;AIRS相对湿度平均偏差在±10%以内,均方根误差不超过20%。利用Parcel法估计的边界层高度结果显示,根据AIRS反演的温度廓线确定的AIRS边界层高度低于利用探空观测资料确定的边界层高度,但能较好地再现边界层高度的变化,在没有探空数据时,可以用AIRS反演的温度廓线确定边界层高度。 相似文献
2.
目前云对卫星相对湿度廓线反演精度的影响研究大多是针对云量,对其他云属性的影响研究尚少,云高也是影响卫星相对湿度廓线反演精度的重要因素。利用上海宝山站L波段(1型)加密探空资料,分析了上海地区7—9月不同质量控制标识、云量和云顶高度条件下大气红外探测器AIRS/Aqua (Atmospheric Infrared Sounder) 相对湿度廓线的反演精度,以期为今后开展AIRS等卫星资料的同化研究提供科学依据。结果表明:(1)AIRS相对湿度廓线反演误差随着云量的增加而逐渐增大,并且随着气压值的升高,少云与多云时的均方根误差(Root Mean Squared Error, RMSE)之差有逐渐增大的趋势;(2)云顶高度越高,AIRS相对湿度廓线反演精度越差,云顶以上湿度廓线反演精度更高,而云顶以下高度的反演误差较大;(3)高云且多云时,AIRS相对湿度廓线的反演精度最差,850 hPa处,AIRS相对湿度反演数据与探空资料绝对误差的下限达到了[-63.51%];(4)虽然质量控制标识为0时,AIRS湿度廓线在对流层范围内的反演精度仍达不到无线电探空的水平,但是相对于质量控制标识1时,反演精度明显提高。 相似文献
3.
上对流层水汽分布对于全球能量和水循环具有非常重要的影响。利用美国Aqua卫星红外高光谱仪器（AIRS）反演的湿度廓线资料对中国上对流层水汽时空分布特征进行了分析。为了保证卫星反演湿度廓线产品精度可以满足气候特征分析的需求,首先利用JICA野外加密探空试验观测数据对卫星反演湿度廓线进行了真实性检验,分析表明,Aqua卫星搭载的AIRS反演的湿度廓线与探空加密观测数据总体具有较好的相关性,在200 hPa高度相对湿度偏差在5%以内,其精度可以用于上对流层水汽气候特征的分析。通过趋势分析以及EOF分解等方法,分析了2003年1月-2013年12月的中国区域上对流层水汽时空分布特征,结果表明,受夏季风影响,中国区域上对流层水汽具有明显的季节变化规律和年周期特征,中国大部分地区上对流层冬季偏干、夏季偏湿,夏季高湿区可以北移到35°N以北。而在新疆地区冬季偏湿、夏季偏干。总体来说,全年夏季水汽含量最高,秋季次之,冬季最小。2003年以来新疆地区及南部海域上对流层水汽呈显著增加趋势,华南、华北、内蒙古中西部水汽也有所增加,在高原地区及东北区域上对流层水汽稍有减少,但变化均不显著。上对流层水汽的增加,将有可能放大温室效应,在气候变化研究中应给予重视。 相似文献
4.
利用AIRS卫星资料反演大气廓线Ⅰ.特征向量统计反演法 总被引：2，自引：0，他引：2
官莉 《南京气象学院学报》2006,29(6):756-761
引进美国威斯康星大学的IMAPP（International MODIS／AIRS Preprocessing Package）软件包，介绍了利用高光谱分辨率大气红外探测器AIRS（Atmospheric Infrared Sounder）观测辐射值，用特征向量统计法反演大气温度、湿度等垂直廓线的算法，采用亮度温度分类和扫描角分类回归后，减小了反演误差。并将其应用到中国地区，通过与无线电探空值及欧洲中期天气预报中心ECMWF（European Center of Medium-range Weather Forecasts）客观分析场的比较，结果表明：该方法所获得的温度、水汽反演结果与探空观测及ECMWF大气廓线分布一致，且AIRS因其高光谱分辨率（即高垂直空间分辨率）显示了精细的大气结构。 相似文献
5.
利用中国气象局大气探测试验基地的L波段探空数据和微波辐射计观测数据,采用MonoRTM辐射传输模型作为正演亮温模型,BP (back propagation) 神经网络作为反演工具,在由亮温反演大气湿度廓线的过程中,添加与样本匹配的云底高度和云厚度信息,建立新的反演模型,使新反演模型得到的反演湿度廓线和未添加云信息的反演湿度廓线分别与探空数据进行对比,获取两种反演方法各高度层的均方根误差,分析云信息对反演大气湿度廓线的影响。对比结果表明:未添加云信息时,测试样本的反演湿度廓线与探空廓线的相关系数平均值为0.685,而添加云信息后,相关系数平均值为0.805。相比未添加云信息的反演廓线,添加云信息之后多数高度层的均方根误差均有不同程度减小,而在有云以上高度层表现尤为明显。 相似文献
6.
在地基高光谱遥感中,特征向量法获取的温湿廓线以初值的方式对物理反演进行约束,其反演精度对物理反演结果有着重要的影响。利用AERI的观测辐射资料和同站点的探空数据,基于特征向量法分析了温度廓线与湿度廓线反演的异同点;研究了主成分个数的选择问题,综合考虑反演精度和特征向量中包含的信息将反演温度廓线和湿度廓线的最优主成分个数定为7。为提高反演精度,引入地面温度、湿度、气压作为影响因子,试验结果表明,考虑反演精度和稳定性,地面气压的引入相比于其他2种单一气象要素以及3种气象要素组成的因子集表现更好,尤其是对边界层中下部的温湿廓线有着明显的提升,并随着高度的降低提升作用更明显,温度廓线RMSE降低最高达到1.5K,湿度廓线RMSE降低最高达到0.42g/kg。同时,分析了对数反演形式对湿度廓线的影响,结果表明,以水汽混合比的形式反演时取自然对数对反演精度的影响较小;将反演得到的水汽混合比转化为相对湿度后,取自然对数对反演精度有12%以上的提升。 相似文献
7.
DRP-4DVar方法同化AIRS反演资料在一次江淮流域暴雨中的应用 总被引：2，自引：1，他引：1
利用经济省时的降维投影四维变分同化方法(DRP-4DVar),在2009年7月22～23日江淮流域的一次大暴雨过程中同化晴空条件下高光谱大气红外探测仪(AIRS)反演温度、湿度廓线,改进此次强降水过程的模拟。试验结果分析显示,同化AIRS反演的温度及湿度场后,基于四维变分同化系统的模式约束,能够改进湿度场、高度场、高低层散度场。从累积降水量偏差图及同化试验增量图可以看到,正降水量偏差对应于正湿度增量、负位势高度增量及低层负散度高层正散度增量,负降水量偏差则与之相反。同化试验较参照试验可更好地模拟出暴雨的天气形势、对暴雨的落区及强度有更好的反映。此外,从单次同化与连续同化的试验对比结果看出,连续同化试验结果较单次同化结果有进一步的改进,说明不断加入新的观测资料可以更好地模拟强降水过程。 相似文献
8.
应用FY-3A/MWHS资料反演太平洋海域晴空大气湿度廓线 总被引：1，自引：0，他引：1
发展Smith迭代算法,建立适用于微波波段的物理迭代算法。采用搭载于FY-3A卫星之上的微波湿度计亮温数据及矢量辐射传输模式,对我国西北太平洋海域晴空区域的大气水汽廓线进行反演计算。反演得到的水汽廓线与MODIS水汽廓线产品比较,单点结果表明,反演混合比廓线与MODIS水汽廓线趋势一致,下层水汽反演能力较中上层强;500 hPa水汽场反演结果表明,可基本反映水汽干湿中心分布情况,反演水汽混合比值与MODIS产品相比偏低。经统计所有气压层反演结果与MOD07水汽廓线产品相比偏差均控制在5.76 g/kg以内。 相似文献
9.
基于一维变分算法的地基微波辐射计遥感大气温湿廓线研究 总被引：3，自引：1，他引：2
为研究地基微波辐射计遥感温、湿度廓线的一维变分算法的反演能力,用北京地区2010—2011年00和12时(世界时)的多通道地基微波辐射计亮温资料进行试验。首先,利用同时次的地面观测资料、红外亮温(由地基微波辐射计自带红外传感器测得)及探空观测数据,给出提取无云样本的方案,得到432个无云样本;再以辐射传输模式计算得到的模拟亮温为参考,对无云条件下的观测亮温进行质量控制;然后利用探空数据进行模拟试验,结果发现,一维变分算法对3 km以下的温度廓线有较大调整。使反演结果更加接近探空,而对湿度廓线在0—10 km都有不同程度的优化;最后利用一维变分算法对地基微波辐射计观测亮温进行大气温湿廓线反演,将结果与探空对比可以看出,温度廓线的均方根误差小于2.9 K,绝对湿度的均方根误差小于0.47 g/m~3;进一步与地基微波辐射计自带神经网络的反演结果比较表明,一维变分的反演结果更接近实际大气。 相似文献
10.
利用人工神经网络方法反演大气温度廓线 总被引：5，自引：0，他引：5
高光谱大气红外探测仪AIRS(Atmospheric Infrared Sounder)资料能够显示小尺度的大气温度垂直结构,为数值预报和天气诊断提供了更加准确精细的初始场.目前处理数据主要使用晴空大气业务反演国际MODIS/AIRS处理软件包IMAPP (International MODIS/AIRS Preprocessing Package)中的特征向量统计回归算法,由于统计法算法简单,反演精度受到较大限制.现提出一种利用人工神经网络的算法来对晴空状况下AIRS模拟辐射值进行大气温度廓线反演的方法,并与特征向量统计法结果相比较.结果表明,神经网络方法与特征向量统计法反演所耗时间相当,减小了反演误差,各高度层温度反演精度均有不同程度的改进,获得了较好的反演结果. 相似文献
11.
Validation of the Atmospheric Infrared Sounder Retrieval Products over China and Their Application in Numerical Mode 
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下载免费PDF全文 The atmospheric infrared sounder (AIRS) instrument onboard Aqua Satellite is a high spectral resolution infrared sounder. In recent years, AIRS has gradually become the primary method of atmospheric vertical observations. To examine the validation of AIRS retrieval products (V3.0) over China, the AIRS surface air temperature retrievals were compared with the ground observations obtained from 540 meteorological stations in July 2004 and January 2005, respectively. The sources of errors were considerably discussed. Based on the error analysis, the AIRS retrieved surface air temperature products were systemically corrected. Moreover, the AIRS temperature and humidity profile retrievals were compared with T213 numerical forecasting products. Because T213 forecasting products are not the actual atmospheric states,to further verify the validation, the AIRS temperature and humidity profile products were assimilated into the MM5 model through the analysis nudging. In this paper, the case on February 14, 2005 in North China was simulated in detail. Then, we investigated the effects of AIRS retrievals on snowfall, humidity field,vertical velocity field, divergence field, and cloud microphysical processes. The major results are: (1) the errors of AIRS retrieved surface air temperature products are largely systematic deviations, for which the influences of terrain altitude and surface types are the major reasons; (2) the differences between the AIRS atmospheric profile retrievals and T213 numerical prediction products in temperature are generally less than
2 K, the differences in relative humidity are generally less than 25%; and (3) the AIRS temperature and humidity retrieval products can adjust the model initial field, and thus can improve the capacity of snowfall simulation to some extent. 相似文献
12.
The atmospheric infrared sounder (AIRS) instrument onboard Aqua Satellite is a high spectral resolution infrared sounder. In recent years, AIRS has gradually become the primary method of atmospheric vertical observations. To examine the validation of AIRS retrieval products (V3.0) over China, the AIRS surface air temperature retrievals were compared with the ground observations obtained from 540 meteorological stations in July 2004 and January 2005, respectively. The sources of errors were considerably discussed. Based on the error analysis, the AIRS retrieved surface air temperature products were systemi-cally corrected. Moreover, the AIRS temperature and humidity profile retrievals were compared with T213 numerical forecasting products. Because T213 forecasting products are not the actual atmospheric states, to further verify the validation, the AIRS temperature and humidity profile products were assimilated into the MM5 model through the analysis nudging. In this paper, the case on February 14, 2005 in North China was simulated in detail. Then, we investigated the effects of AIRS retrievals on snowfall, humidity field, vertical velocity field, divergence field, and cloud microphysical processes. The major results are: (1) the errors of AIRS retrieved surface air temperature products are largely systematic deviations, for which the influences of terrain altitude and surface types are the major reasons; (2) the differences between the AIRS atmospheric profile retrievals and T213 numerical prediction products in temperature are generally less than 2 K, the differences in relative humidity are generally less than 25%; and (3) the AIRS temperature and humidity retrieval products can adjust the model initial field, and thus can improve the capacity of snowfall simulation to some extent. 相似文献
13.
The physical retrieval algorithm of atmospheric temperature and moisture distribution from the Atmospheric InfraRed Sounder （AIRS） radiances is presented. The retrieval algorithm is applied to AIRS clear-sky radiance measurements. The algorithm employs a statistical retrieval followed by a subsequent nonlinear physical retrieval. The regression coefficients for the statistical retrieval are derived from a dataset of global radiosonde observations （RAOBs） comprising atmospheric temperature, moisture, and ozone profiles. Evaluation of the retrieved profiles is performed by a comparison with RAOBs from the Atmospheric Radiation Measurement （ARM） Program Cloud And Radiation Testbed （CART） in Oklahoma, U. S. A.. Comparisons show that the physically-based AIRS retrievals agree with the RAOBs from the ARM CART site with a Root Mean Square Error （RMSE） of 1K on average for temperature profiles above 850 hPa, and approximately 10% on average for relative humidity profiles. With its improved spectral resolution, AIRS depicts more detailed structure than the current Geostationary Operational Environmental Satellite （GOES） sounder when comparing AIRS sounding retrievals with the operational GOES sounding products. 相似文献
14.
A Neural Network Based Single Footprint Temperature Retrieval for AtmosphericInfrared Sounder Measurements and Its Application to Study onStratospheric Gravity Wave 下载免费PDF全文
下载免费PDF全文 Satellite hyperspectral infrared sounder measurements have better horizontal resolution than other sounding techniques as it boasts the stratospheric gravity wave (GW) analysis. To accurately and efficiently derive the three- dimensional structure of the stratospheric GWs from the single-field-of-view (SFOV) Atmospheric InfraRed Sounder (AIRS) observations, this paper firstly focuses on the retrieval of the atmospheric temperature profiles in the altitude range of 20-60 km with an artificial neural network approach (ANN). The simulation experiments show that the retrieval bias is less than 0.5 K, and the root mean square error (RMSE) ranges from 1.8 to 4 K. Moreover, the retrieval results from 20 granules of the AIRS observations with the trained neural network (AIRS_SFOV) and the corresponding operational AIRS products (AIRS_L2) as well as the dual-regression results from the Cooperative Institute for Meteorological Satellite Studies (CIMSS) (AIRS_DR) are compared respectively with ECMWF T799 data. The comparison indicates that the standard deviation of the ANN retrieval errors is significantly less than that of the AIRS_DR. Furthermore, the analysis of the typical GW events induced by the mountain Andes and the typhoon "Soulik" using different data indicates that the AIRS_SFOV results capture more details of the stratospheric gravity waves in the perturbation amplitude and pattern than the operational AIRS products do. 相似文献
15.
人工神经网络法反演晴空大气湿度廓线的研究 总被引：4，自引：0，他引：4
高光谱分辨率大气红外探测器AIRS(Atmospheric Infrared Sounder)作为第一个超高光谱大气红外探测仪,开辟了卫星大气探测的新时代.以无线电探空值与SARTA(Stand-Alone Radiative Transfer Algorithm辐射传输模式)v1.05版的前向模式模拟出的AIRS辐射... 相似文献
16.
This study investigates the use of dynamic a priori error information according to atmospheric moistness and the use of quality controls in temperature and water vapor profile retrievals from hyperspectral infrared (IR) sounders. Temperature and water vapor profiles are retrieved from Atmospheric InfraRed Sounder (AIRS) radiance measurements by applying a physical iterative method using regression retrieval as the first guess. Based on the dependency of first-guess errors on the degree of atmospheric moistness, the a priori first-guess errors classified by total precipitable water (TPW) are applied in the AIRS physical retrieval procedure. Compared to the retrieval results from a fixed a priori error, boundary layer moisture retrievals appear to be improved via TPW classification of a priori first-guess errors. Six quality control (QC) tests, which check non-converged or bad retrievals, large residuals, high terrain and desert areas, and large temperature and moisture deviations from the first guess regression retrieval, are also applied in the AIRS physical retrievals. Significantly large errors are found for the retrievals rejected by these six QCs, and the retrieval errors are substantially reduced via QC over land, which suggest the usefulness and high impact of the QCs, especially over land. In conclusion, the use of dynamic a priori error information according to atmospheric moistness, and the use of appropriate QCs dealing with the geographical information and the deviation from the first-guess as well as the conventional inverse performance are suggested to improve temperature and moisture retrievals and their applications. 相似文献
17.
北京秋季一次降雪前污染天气的激光雷达观测研究 总被引：1，自引：0，他引：1
以2009年11月5~8日北京地区发生的一次特殊天气形势下的重污染天气过程为例,研究分析本次污染特点和大气边界层结构特征以及此天气过程的大气温度和相对湿度结构特点。激光雷达是探测大气边界层及气溶胶的一个高效工具,利用ALS300激光雷达系统测量信号,应用Fernald方法反演大气消光系数,根据反演的气溶胶消光系数的最大突变,即最大递减率的高度来确定大气边界层的高度。利用其观测的退偏比分析大气污染物特性。利用微波辐射计数据,确定大气温度和湿度时空特征。研究结果表明:在本次污染天气下,大气具有很强的逆温结构,逆温最大可达近1 K(100 m)-1,500 m以上的大气相对湿度很低,在这种天气特征下的大气边界层高度在400 m左右,非常稳定。污染结束降雪开始前,大气逆温结构消失,大气湿度大幅度增加,接近饱和。根据lidar(light detection and ranging)退偏比的分析,本次污染天气是一次典型的烟尘类颗粒物的污染,污染具有区域性特点。PM2.5(空气动力学当量直径小于等于2.5μm的颗粒物)与AOT(Aerosol Optical Thickness)之间有明显的线性关系,相关系数达到0.72。该lidar系统能够反演出秋季降雪前本次污染天气背景下北京城区上空的大气污染特性和大气边界层高度。 相似文献
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一次大范围暴雪天气的大气环境形成机理研究 总被引：3，自引：1，他引：2
通过分析2009年11月9—12日的一次大范围暴雪天气事件,探讨其发生前期和过程中的大气环境条件及形成机理。通过研究分析环流特征、星载雷达有关能数、物理量场诊断等表明:此次天气过程中暴雪区域上空对流层中低层一直存在着一层具有增温增湿特征的层状云,暴雪前大气低层高温高湿的环境为暴雪的发生提供了一个有利的温湿能量蓄积场;东北回流冷空气的入侵是层状云开始形成的触发机制;大气低层因水汽凝结产生的大量凝结潜热促进了垂直上升运动,大气中低层在水汽条件具备时,通过垂直上升运动的作用使水汽大量凝结增长,形成层状云。 相似文献
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1. IntroductionThe development of global climate and weathermodels requires accurate monitoring of atmospherictemperature and moisture profiles, as well as the con-tents of trace gases and aerosols. It is quite difficultto monitor continuously these parameters on a globalscale.Until recently. AIRS (Atmospheric InfraredSounder) offers a new opportunity to improve globalmonitoring of temperature, moisture, and ozone distri-butions and changes therein. The high spectral resolu-tion (v/Δv ? 12… 相似文献