COSMIC掩星资料反演青藏高原大气廓线与探空观测的对比分析

利用青藏高原地区COSMIC掩星资料反演的大气湿廓线Wet Prf数据和8个站点的探空数据,分析了COSMIC反演大气廓线和可降水量与探空观测的偏差,并考查了偏差随高度的变化特征。结果显示:(1)COSMIC反演的温度、压强和水汽压廓线与探空观测具有很好的正相关;与探空观测相比,COSMIC的温度、压强和水汽压的偏差为-0.2℃、1.7 h Pa和0 h Pa,均方差为1.8℃、1.6 h Pa和0.4 h Pa;COSMIC反演大气廓线与探空观测的偏差基本上在大气低层较大,然后随高度增加而减小。(2)COSMIC反演的可降水量与探空观测正相关较好;COSMIC反演的可降水量低于探空观测,两者的偏差为-5.0 mm,均方差为5.7 mm;两者的负偏差在大气低层最明显。(3)探空观测在近地层的不稳定性和COSMIC反演方法中背景模式在青藏高原地区描述大气状态的能力有限,是造成COSMIC反演大气廓线和探空观测的偏差在近地层较大的主要原因;COSMIC观测的折射率偏小导致其反演的可降水量偏低。     

中国区域高空三种气温、湿度资料交叉对比

本文对比分析了2011—2013年中国区域L波段探空气温、湿度廓线,COSMIC掩星气温、湿度廓线和ERA-Interim再分析资料的气温、湿度廓线之间的差异。对比显示,从时间变化来看,三者之间有很好的正线性相关关系。除10 hPa以上的少数层次外,三种气温资料之间互相吻合较好,彼此偏差范围在±0.4℃之间,偏差标准差在1~2℃,对流层中高层,L波段探空气温受太阳辐射影响较大,气温偏高,与COSMIC相比,L波段探空偏高最高可达到0.64℃。而对于相对湿度,三种数据存在明显差异。对流层中低层到对流层顶L波段探空存在不同程度的偏干,且有较明显的昼夜、季节和区域差异:白天、春夏季和南方潮湿气候区域偏干更明显。一般来说,在对流层顶附近区域,L波段探空相对湿度偏干较明显,200 hPa附近及以上L波段探空相对湿度转为偏湿。在对流层顶以下,L波段探空与COSMIC掩星、ERA-Interim再分析相对湿度具有明显的正相关,对流层顶以上表现为负相关。     

COSMIC掩星数据与L波段探空数据的对比分析

COSMIC(Constellation Observation System for Meteorology,Ionosphere and Climate)每天可以提供全球2000～3000条从40 km高空到近地面的大气温、压、湿的廓线资料,有效地弥补了常规探空资料在时间和空间上分辨率的不足。通过对2008年5月20日至2008年11月26日COSMIC资料与L波段探空秒数据进行比对,结果表明,在10 km高度以下,COSMIC反演的湿廓线资料与L波段探空数据偏差较小,温度偏差为-0.5℃,均方根误差为1.5℃;折射率偏差为1.4N,均方根误差为5.9N;气压偏差为2.0 hPa,均方根误差为4.7 hPa;水汽压偏差为0.1 hPa,均方根误差为1.1 hPa。COSMIC干廓线资料与L波段探空相比,在10～30 km高度内,温度偏差为-0.3℃,均方根误差为1.9℃;折射率偏差为0.4N,均方根误差为0.9N;气压偏差为1.4 hPa,均方根误差为2.6 hPa。表明COSMIC资料既具有较高的时空分辨率,又具有较好的精度,在数值模式中具有重要的潜在应用。     

AIRS反演中国区域上对流层水汽分布特征研究

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。     

利用AIRS卫星资料反演大气廓线Ⅰ.特征向量统计反演法

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。     

ERA5再分析数据在微波辐射计数据反演中的初步应用

为了研究ERA5再分析资料在微波辐射计数据反演中的应用效果,利用探空和ERA5作为训练样本分别训练得到两个神经网络,对微波辐射计观测数据进行反演。并以探空资料作为参考分别统计基于探空和ERA5再分析资料反演得到的数据的相关系数、绝对偏差和均方根误差,用于评估ERA5再分析资料在微波辐射计数据反演中的应用效果。结果表明：基于ERA5和探空反演的温度廓线与探空的相关系数分别为0.988、0.99,绝对偏差分别为2.402 ℃、2.607 ℃。反演水汽与探空的相关系数分别为0.975、0.979,绝对偏差分别为0.412 g/m3、0.369 g/m3。反演的相对湿度相关系数分别为0.663、0.696,绝对偏差分别为15.587%、13.976%。反演的积分水汽总量相关系数分别为0.959、0.968,绝对偏差分别为0.258 cm、0.227 cm。从结果来看,基于ERA5资料反演的温度、水汽资料与利用探空反演的结果相差较小,温度廓线反演效果优于相对湿度廓线。     

基于不同背景场的云内COSMIC掩星资料的偏差分析

利用2007-2009年Cloud Sat卫星云廓线雷达(nadir-pointing cloud profiling radar,CPR)资料,气象、电离层和气候卫星联合观测系统(Global Constellation Observing System for Meteorology,Ionosphere,and Climate,COSMIC)掩星资料,分析了不同类型云内COSMIC掩星资料与欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)和美国国家环境预报中心(National Centers for Environmental Prediction,NCEP)分析场之间的折射率偏差特征。COSMIC与ECMWF和NCEP之间的折射率偏差分别用Nbias^ECMWF和Nbias^NCEP表示。研究发现,Nbias^ECMWF在积云、层积云、高积云和高层云中的最大值分别为1.2%、0.2%、0.5%和0.2%,而Nbias^NC...     

基于往返式平漂探空的FY-3D卫星反演温度检验

往返式平漂探空观测（以下简称平漂探空）可实现对流层至平流层低层大气温度廓线垂直探测以及平流层低层内持续4 h的水平温度分布探测。该文介绍利用平漂探空试验数据对风云3号气象卫星D星（FY-3D）反演温度数据的检验评估算法,基于该算法和2021年3—9月长江中下游平漂探空试验数据完成对卫星反演大气温度数据的检验。结果显示:FY-3D卫星反演的温度数据准确度总体较高,与平漂探空上升段数据平均绝对偏差约为1.34℃,与下降段数据平均绝对偏差约为1.93℃;卫星反演的100 hPa以上和850 hPa以下温度误差分别偏大0.59℃和0.33℃;卫星反演平流层温度准确度低于温度廓线,平均绝对偏差约为3.92℃;与平漂探空数据相比,卫星大气温度廓线分辨率较低、趋势较平滑,无法显示大气温度垂直分布和平流层温度水平分布的细节特征。     

NCEP再分析资料在强对流环境分析中的应用

为考察NCEP再分析资料在我国强对流天气产生环境分析中的适用性,选取2002—2009年多普勒天气雷达识别的60例超级单体风暴个例,对比分析常规探空资料和NCEP再分析资料提取的温、湿、风垂直廓线,结果表明:NCEP再分析资料计算的对流有效位能因对抬升气团湿度敏感而与观测间差异较大,宜用K指数、温度直减率分析大气层结稳定度;因对流层中高层风与探空差异不大,其中500~700 hPa的风与探空近乎一致,因此NCEP再分析资料计算的深层、中层风垂直切变参量可靠性较高;NCEP再分析资料水汽参数与探空资料差异大,特别是在大气边界层,需用观测资料订正;边界层物理量,特别是风向与探空差异显著,因此不宜用NCEP再分析资料讨论雷暴触发问题;平均而言,NCEP再分析资料湿度廓线低层偏干而中层偏湿,925 hPa以上风速偏小,降低了强对流发生概率。     

利用COSMIC掩星资料分析青藏高原地区对流层顶季节变化特征

根据WMO(1957)对流层高度的判别方法,利用2007—2013年COSMIC掩星资料计算了对流层高度,并用无线电探空资料对结果进行检验,分析了青藏高原地区对流层顶季节变化特征.结果表明,COSMIC掩星资料和无线电探空资料判定的对流层高度具有很高的线性相关关系,相关系数高达0.976,平均值偏差为0.448 km,...     

COSMIC反演精度和有关特性的检验

COSMIC是一个由6颗低轨卫星组成的用于天气、气候和电离层观测的空基GPS星座观测系统, 从2006年9月开始每天可提供覆盖全球的约2000~3000个掩星点, 掩星过程可提供从40 km高空到近地面的大气温、压、湿的廓线资料。为了有效利用这些资料, 以探空资料为基准, 对2007年1-10月我国及邻近区域的COSMIC掩星资料进行精度、可用性和全天候性的检验。结果表明: COSMIC反演的温度和折射率的精度很高, 水汽压的精度相对较差。与NCEP/NCAR再分析资料相比, 折射率和湿度廓线有更高精度。     

Comparison of COSMIC radio occultation refractivity profiles with radiosonde measurements

In recent years, radio occultation (RO) technology making use of global positioning system (GPS) signals has been exploited to obtain profiles of atmospheric parameters in the neutral atmosphere. In this paper, the RO refractivity profiles obtained from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) mission are statistically compared with the observations of 38 radiosonde stations provided by the Australian Bureau of Meteorology during the period from 15 July 2006 through 15 July 2007. Different collocation criteria are compared at first, and COSMIC RO soundings that occur within 3 hours and 300 km of radiosonde measurements are used for the final statistical comparison. The overall results show that the agreements between the COSMIC refractivity profiles and the radiosonde soundings from the 38 stations are very good at 0--30 km altitude, with mean absolute relative refractivity deviations of less than 0.5%. Latitudinal comparisons indicate that there are negative refractivity deviations in the lower troposphere over the low latitude and middle latitude regions and large standard deviations exist in the lower troposphere of low latitude regions, which can reach up to ~6%. The comparisons of COSMIC RO refractivity profiles and radiosonde observations for 3 polar stations in four different seasons indicate that the accuracy of GPS RO profiles is better in the Austral summer and autumn than in the Austral spring and winter during the year from September 2006 to August 2007.     

A Study on Retrieving Atmospheric Profiles from EOS/AIRS Observations

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…     

One-Dimensional Variational Retrieval of Temperature and Humidity Profiles from the FY4A GIIRS

A physical retrieval approach based on the one-dimensional variational(1 D-Var) algorithm is applied in this paper to simultaneously retrieve atmospheric temperature and humidity profiles under both clear-sky and partly cloudy conditions from FY-4 A GIIRS(geostationary interferometric infrared sounder) observations. Radiosonde observations from upper-air stations in China and level-2 operational products from the Chinese National Satellite Meteorological Center(NSMC)during the periods from December 2019 to January 2020(winter) and from July 2020 to August 2020(summer) are used to validate the accuracies of the retrieved temperature and humidity profiles. Comparing the 1 D-Var-retrieved profiles to radiosonde data, the accuracy of the temperature retrievals at each vertical level of the troposphere is characterized by a root mean square error(RMSE) within 2 K, except for at the bottom level of the atmosphere under clear conditions. The RMSE increases slightly for the higher atmospheric layers, owing to the lack of temperature sounding channels there.Under partly cloudy conditions, the temperature at each vertical level can be obtained, while the level-2 operational products obtain values only at altitudes above the cloud top. In addition, the accuracy of the retrieved temperature profiles is greatly improved compared with the accuracies of the operational products. For the humidity retrievals, the mean RMSEs in the troposphere in winter and summer are both within 2 g kg^–1. Moreover, the retrievals performed better compared with the ERA5 reanalysis data between 800 h Pa and 300 h Pa both in summer and winter in terms of RMSE.     

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

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。     

地基微波辐射计探测大气边界层高度方法

采用2013年中国科学院大气物理研究所香河大气综合观测试验站的地基微波辐射计和激光雷达观测数据,以激光雷达探测的大气边界层高度为参考,分别利用非线性神经网络和多元线性回归方法建立微波亮温直接反演大气边界层高度的算法,并对比两种方法的反演能力, 同时分析非线性神经网络算法在不同时段及不同天气状况下反演结果的差异。结果表明:非线性神经网络算法的反演能力优于多元线性回归算法,其反演结果与激光雷达探测的大气边界层高度有较好一致性,冬、春季的相关系数达到0.83,反演精度比线性回归算法约高26%;对于不同时段和不同天气条件,春季的反演结果最好,晴空的反演结果好于云天; 四季和不同天气状况的划分也有利于提高反演精度。     

Atmospheric profile retrieval with AIRS data and validation at the ARM CART site

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.     

COSMIC掩星反演大气温湿资料的质量特征分析

针对COSMIC(Constellation Observation System of Meteorology Ionosphere and Climate)掩星反演的大气温度和水汽压二级资料,利用常规探空观测和NCEP(National Centers for Environmental Prediction)分析资料分别进行质量检验分析,以揭示反演资料质量的海陆差异、随纬度和高度变化等三维空间特征。结果显示:我国区域反演资料的温度略低于探空观测与NCEP分析资料,温度与水汽压相对于检验资料的均方根误差较小;全球范围内,反演大气温湿资料的质量随高度和纬度的不同而存在明显差异,而且海洋和陆地上质量的水平和垂直分布特征也存在显著不同。总体上看,COSMIC反演大气温湿资料具有良好的可靠性与精确度,可作为我国数值预报资料同化的新资料,反演温湿资料的质量特征也可为COSMIC资料同化的质量控制和垂直稀疏化方案的设计提供科学依据。     

Validation of the Atmospheric Infrared Sounder Retrieval Products over China and Their Application in Numerical Model

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.