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。     

人工神经网络法反演晴空大气湿度廓线的研究

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...     

利用人工神经网络方法反演大气温度廓线

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.     

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.     

一种新的TOVS大气湿度反演方法及试验

利用国家气象中心的数值天气预报（NWP）6 h预报场。作为同步物理反演模式初估场，由气象卫星垂直探测（TOVS）资料推导出大气湿度，并给出了试验结果。结果表明，TOVS湿度反演的相对误差（RMS）约为20%。其中，夏季反演结果略优于冬季，而且低层（1000 hPa）和高层（500 hPa以上）与初估场相比有较大的改进，中层（850，700 hPa）二者大致相当。与统计回归反演结果相比其精度约提高10%。该研究为在我国建立“卫星反演/数据同化/数值预报”相互影响的循环系统奠定了基础     

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

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.     

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.     

A New Temperature Channel Selection Method Based on Singular Spectrum Analysis for Retrieving Atmospheric Temperature Profiles from FY-4A/GIIRS

Hyperspectral data have important research and application value in the fields of meteorology and remote sensing.With the goal of improving retrievals of atmospheric temperature profiles, this paper outlines a novel temperature channel selection method based on singular spectrum analysis(SSA) for the Geostationary Interferometric Infrared Sounder(GIIRS), which is the first infrared sounder operating in geostationary orbit. The method possesses not only the simplicity and rapidity of the principa...     

高原地区基于微波辐射计反演大气廓线的神经网络算法研究

以2007~2018年西宁二十里铺气象站探空资料为模拟样本,利用MonoRTM模式模拟中心频率21.985~58.759GHz的35通道亮温,应用BP神经网络对模拟数据进行反复训练,构建最优反演模型,并以2019年探空资料为测试样本,对比分析了不同季节和不同天气条件下BP神经网络与微波辐射计的反演效果。结果表明：晴空条件下,BP神经网络与微波辐射计在温度反演上效果最佳,水汽密度次之,相对湿度最差,其中冬春季BP神经网络反演效果优于微波辐射计,夏秋季反之;有云条件下,BP神经网络温度反演效果在冬、春和夏季均优于微波辐射计,其水汽密度反演效果在四季均较微波辐射计有明显提升,其相对湿度反演效果在冬、春和夏季均较微波辐射计更佳。晴空和有云条件下,BP神经网络在不同季节反演温度、水汽密度和相对湿度的平均绝对误差和标准偏差均小于微波辐射计,尤其是相对湿度的反演精度提升最为明显。晴空条件下,BP神经网络反演温度廓线在春、夏和秋季效果最佳,反演水汽密度廓线在中低层精度较高,反演相对湿度廓线的精度较差,但基本和探空资料趋势一致;有云条件下,BP神经网络反演温度廓线与晴空时基本一致,较微波辐射计精度更高,反演水汽密度和相对湿度廓线在8km以上效果较好。     

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。     

一次层积云发展过程对黑潮延伸体海洋锋强迫的响应研究——观测与机制分析

由于缺乏海上现场观测,对天气尺度扰动下,海表面温度锋 (海洋锋) 对海洋大气边界层 (MABL) 垂直结构和MABL内海洋性低云 (marine stratus) 的影响研究较少。2014年4月12日,中国海洋大学东方红2号科学考察船在黑潮延伸体海区的海洋锋附近捕捉到一次层积云的迅速发展。在比较稳定的天气形势下,由暖水侧向北穿越海洋锋时,云底和云顶高度升高,云区范围迅速扩大。本文利用多种大气-海洋联合观测数据,结合卫星观测和再分析资料,对此次层积云迅速发展的机理进行了综合分析。结果表明,在海上低压后部西北风控制下,在海洋锋的暖水侧 (下风方) 形成热通量大值中心和低压槽,有助于高空西风动量下传,进而又使得海气界面热通量增加,这种正反馈效应为MABL内混合层厚度加大和云底/顶高度在海洋锋的下风方升高提供有利背景条件。4月12日09:00~12:00(协调世界时),来自日本本州岛陆地的低空暖平流到达该热通量中心上空,暖平流与热通量中心的共同作用,导致该时段近海面暖中心强度异常增加,MABL中静力不稳定层加深和低压槽发展,综合作用的结果使得混合层厚度明显加深,云底高度升高,云区迅速发展。本研究有助于理解在复杂大气背景扰动下MABL对海洋强迫的响应机理。     

基于卷积神经网络的逐时降水预报订正方法研究

应用2017—2018年5—9月福建省观测资料对华南区域中尺度模式(GTRAMS-3 km-RUC)预报进行站点检验,建立和训练基于卷积神经网络的逐时降水分级订正模型,并与频率匹配法进行2017—2018年测试集的对比试验和2019年数据集的模拟业务检验,探讨了试验过程中遇到的样本不均衡、特征变量选取以及模型过拟合问题。结果表明:模式对于15 mm·h^-1以上降水的预报能力弱,各订正方法对原始预报均有不同程度的改进作用。从评估指标来看,基于卷积神经网络的订正方法比频率匹配法表现出优势,其中相关系数判别方案下的网络模型对强降水预报的订正效果显著优于其他方法;在输入特征变量选取方面,应用主成分分析方案的模型训练收敛速度比相关系数判别方案更快,最佳训练期有所提前,但也更早进入严重的过拟合状态,而相关系数判别方案能够使网络模型的训练拥有更长的提升期以达到更具"潜力"的状态;基于卷积神经网络的订正方法对减少分类降水预报的漏报率、晴雨和弱降水预报的空报率具有显著作用,其优化程度明显超过频率匹配法。     

Microphysical Properties of Convective Clouds in Summer over the Tibetan Plateau from SNPP/VIIRS Satellite Data

The Tibetan Plateau (TP) plays an important role in formation and development of the East Asian atmospheric circulation, climate variability, and disastrous weathers in China. Among the many topics on TP meteorology, it is critical to understand the microphysical characteristics of clouds over the TP;however, observations of the cloud microphysics in this area are insufficient mainly due to sparse stations and limited cloud physical data. The Visible Infrared Imaging Radiometer Suite (VⅡRS), onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite, has an improved imaging spectroradiometer with 17 channels of 750-m moderate resolution and 5 channels of 375-m image resolution. The high-resolution instrument has an advantage for observing the small or initial convective clouds. Based on the methodologies that we proposed before for retrieving cloud microphysical properties from SNPP, an automated mapping software package named Automatic Mapping of Convective Clouds (AMCC) has been developed at the scale of satellite swath. The properties of convective clouds are retrieved by AMCC and their values are averaged over 0.33°×0.33° grids based on the SNPP/VⅡRS satellite data over the TP during the summers of 2013-17. The results show that:(1) the temperature of lifting condensation level (TLCL) at Naqu meteorological station and the cloud base temperature (Tb) retrieved from VⅡRS are linearly correlated, with a correlation coefficient of 0.87 and standard deviation (STD) of 3.0℃;(2) convective clouds over the TP have the following macro-and microphysical properties. First, the cloud base temperature (Tb) is about -5℃, the cloud base height above the ground (Hb) ranges between 1800 and 2200 m, and the cloud water content is low. Second, the cloud condensation nuclei concentration (NCCN) is between 200 and 400 mg-1 with 0.7% in maximum supersaturation (Smax);consequently, the condensation growth of water cloud droplet with less NCCN and higher Smax is fast. Third, because the precipitation initiation depth (D14) varies within 1500-2000 m and 500-1000 m at the Yarlung Zangbo River basin and southern Tibet, respectively, the clouds over these areas are more prone to precipitation. Fourth, mean height of the cloud top above sea level (Htop) is between 10 and 13 km, but the cloud depth (Dcld) is rather small, which is about 5000 m in southern TP and gradually reduces to 2500 m in northern TP. Fifth, the glaciation temperature (Tg) ranges from -30℃ in central and southern TP to -25℃ in northern TP, which, combined with the warmer Tg and the Tb less than 0℃, leads to the domination of ice process in the clouds;(3) the macro-and microphysical properties of convective clouds over the TP explain why rainfall there is frequent and lasts over a short time with small amount and large rain drops.     

基于卫星观测的我国北方地区紫外吸收性气溶胶的时空分布研究

利用气溶胶指数(Aerosol Index,AI)资料研究了东亚地区紫外吸收性气溶胶的时空分布特征,主要得出以下结论:1)雨云七号卫星(Nimbus 7,N7)和地球探测卫星(Earth Probe,EP)搭载的臭氧总量测绘光谱仪(Total Ozone Mapping Spectrometer,TOMS)以及臭氧监测仪(Ozone Monitoring Instrument,OMI)反演的AI数据在东亚大陆具有较好的一致性,但EP/TOMS-OMI AI的连续性较好,而N7/TOMS-EP/TOMS AI的连续性较差;2)东亚地区紫外吸收性气溶胶主要位于塔克拉玛干沙漠及其东部周边的库姆塔格、柴达木盆地沙漠、古尔班通古特沙漠、内蒙古中西部、蒙古国南部以及我国东北、华北地区;3)紫外吸收性气溶胶具有明显的月际变化特征;4)旋转正交经验函数分析不仅能分离紫外吸收性气溶胶的源区范围,还能给出源强相对大小的定性信息。     

基于无人机垂直观测的南京PM2.5污染个例研究

为了深入理解边界层内气温、相对湿度对PM2.5垂直分布和近地面污染的影响,本文使用搭载了多参数大气环境探测传感器的无人机对南京2017年12月3～4日和12月23～24日的PM2.5浓度、气温和相对湿度进行垂直观测,结合对气象数据的分析及HYSPLIT4（Hybrid Single Particle Lagrangian Integrated Trajectory version 4）轨迹计算模式的应用,对这两次PM2.5的垂直分布特征及污染过程的成因进行了分析。结果表明,PM2.5浓度和相对湿度呈明显的正相关关系,在12月23～24日的6次观测中相关系数均值达到0.96。逆温层下部,PM2.5浓度和相对湿度高且垂直差异较小;逆温层以上,PM2.5浓度和相对湿度随高度升高而迅速降低。由于大气扩散条件较差,导致PM2.5在华北平原南部不断累积,之后受到高压系统的影响分别向南和东南转移。这两次PM2.5污染过程都明显受到外部输送的影响,大气逆温对PM2.5和水汽的向上输送有明显的抑制作用,外部输送和局部逆温是导致这两次PM2.5污染的主要原因。