基于一维变分算法的红外高光谱(IASI)卫星遥感大气温湿廓线研究

大气温湿度廓线是大气重要参数,在数值天气预报及天气预警中具有重要的应用价值。为获得高精度的大气温度与水汽混合比廓线数据,研究了基于Metop-A/IASI红外高光谱资料的大气温度与水汽混合比廓线变分反演方法。利用IASI高光谱传感器温度和水汽探测通道资料,结合CRTM模式和WRF模式预报技术,使用一维变分方法,研究了卫星资料质量控制、背景误差协方差本地化、观测误差协方差计算等方法,构建了大气温度及水汽混合比廓线变分反演系统,并在北京、青岛、沈阳3个地区开展了反演试验。以探空为标准的反演结果对比显示,使用WRF模式预报值作为背景场,温度的平均误差绝对值小于0.6 K,均方根误差为0.89 K;水汽混合比的平均误差绝对值小于0.021 g/kg,均方根误差为0.02 g/kg。试验结果表明:基于一维变分方法,可以利用Metop-A/IASI红外高光谱资料进行大气温度与水汽混合比廓线高精度探测。     

GNSS/PWV与风云四号A星GIIRS水汽廓线融合应用研究

中国新一代地球静止气象卫星风云四号A星（FY-4A）搭载的干涉式大气垂直探测仪（Geostationary Interferometric Infrared Sounder, GIIRS）以红外高光谱干涉分光方式探测三维大气温湿结构,取得了在静止轨道上探测大气的突破性进展。地基全球导航卫星系统（Global Navigation Satellite System,GNSS）是一种连续监测大气可降水量（Precipitable Water Vapor,PWV）的有效手段,基于2018年6—8月中国地基GNSS站监测的PWV和FY-4A/GIIRS水汽廓线的业务产品以及常规无线电探空资料,开展GNSS/PWV与FY-4A/GIIRS水汽廓线快速融合应用,以提高卫星资料反演大气水汽廓线的精度。结果表明:与常规无线电探空相比,FY-4A/GIIRS水汽廓线产品在大气低层均方根误差（Root Mean Square Error,RMSE）为4.5 g/kg,700 hPa为2.4 g/kg,500 hPa以上因水汽含量较低RSME小于1.5 g/kg。GNSS/PWV与FY-4A/GIIRS水汽廓线融合后,FY-4A/GIIRS水汽廓线误差整层RMSE减小20%,从近地层到600 hPa RMSE平均减小20%—25%,尤其是850—700 hPa改善最明显,极大改善了卫星水汽反演资料的可用性。对一次多系统影响的暴雨天气过程应用分析表明,GNSS/PWV和FY-4A/GIIRS融合产品可获得高时、空密度的大气水汽廓线,对强降水的临近预报有非常重要的支撑作用。      

Comparison of atmospheric water vapor profiles obtained by GPS, MWR, and radiosonde

In studies of weather changes and, especially, in enhancing the performance of rainfall prediction, it is important to measure the water vapor distribution in the atmosphere. We estimated atmospheric water vapor profiles for fourteen days, including periods of severe weather conditions, by processing ground-based Global Positioning System (GPS) measurements and compared our results with microwave radiometer (MWR) and radiosonde (RAOB) observations. As a result, we found that the standard deviation (STD) of wet refractivity profiles between GPS with MWR was smaller than the STD between RAOB and MWR refractivities; the average STD was 9.3 mm km^?1. In particular, we found that GPS-based wet refractivities detected inversion layers close to those from MWR when the observed GPS satellites were well distributed in the azimuth and elevation angle directions. When the satellite geometry was better, the mean error of GPS wet refractivities with respect to MWR was reduced to 0.4 from 3.2 mm km^?1 for altitudes lower than 3 km. In some cases, however, the precision of GPS refractivities are lower than that of RAOB ones relative to MWR results.     

Evaluation of Total Precipitable Water over East Asia from FY-3A/VIRR Infrared Radiances

Satellite retrieval of atmospheric water vapor is intended to further understand the role played by the energy and water cycle to determine the Earth's weather and climate. The algorithm for operational retrieval of total precipitable water (TPW) from the visible and infrared radiometer (VIRR) onboard Fengyun 3A (FY-3A) employs a split window technique for clear sky radiances over land and oceans during both day and night. The retrieved TPW is compared with that from the moderate resolution imaging spectroradiometer (MODIS) onboard the Terra satellite and data from radiosonde observations (RAOB). During the study period, comparisons show that the FY-3A TPW is in general agreement with the gradients and distributions from the Terra TPW. Their zonal mean difference over East Asia is smaller in the daytime than at night, and the main difference occurs in the complex terrain at mid latitude near 30°N. Compared with RAOB, the zonal FY-3A and the Terra TPW have a moist bias at low latitudes and a dry-bias at mid and high latitudes; in addition, the FY-3A TPW performs slightly better in zonal mean biases and the diurnal cycle. The temporal variation of the FY-3A and the Terra TPW generally fits the RAOB TPW with the FY-3A TPW. The FY-3A TPW is more accurate at night, while the Terra TPW is more accurate during the daytime. Comparisons of correlations, root mean square differences and standard deviations indicate that the FY-3A TPW series is more consistent with the RAOB TPW at selected stations. As a result, the FY-3A TPW has some advantages over East Asia in both spatial and temporal dimensions.     

Use of total precipitable water classification of a priori error and quality control in atmospheric temperature and water vapor sounding retrieval

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.     

The Capability of Atmospheric Profile Retrieval from Satellite High Resolution Infrared Sounder Radiances

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METOP星载干涉式超高光谱分辨率红外大气探测仪(IASI)及其产品

为了深入了解国际卫星红外大气探测仪器的新特点,以欧洲METOP卫星装载的超高光谱红外大气探测仪(IASI:Infrared Atmospheric Sounding Interferometer)为例,介绍卫星红外探测仪研发背景、仪器特征和数据产品处理,并与第1个高光谱大气红外探测仪(AIRS:Atmosphenic Inftared Sounder)作了比较分析.采用干涉分光技术的IASI为地球大气遥感提供了丰富的研究资料,可用于反演大气、海洋、云和大气成分,对我国风云卫星的高光谱红外大气垂直探测仪器的研发具有重要参考价值.     

青藏高原大气总水汽量的反演研究

利用2001年青藏高原89个气象站资料、NCEP格点再分析资料以及2001—2003年7月3个地基GPS站的大气总水汽量观测资料,对GPS遥感的大气总水汽量与探空观测结果做了比较,研究了大气总水汽量变化对降雨形成的影响,大气总水汽量与地面水汽压的关系,分析了青藏高原大气总水汽量的时空变化特征及其成因。结果表明:GPS遥感的大气总水汽量与探空观测结果吻合得较好,2001年那曲站两种结果相比均方根误差仅0.15 cm;大气总水汽量与地面水汽压之间有良好的相关关系;不同季节高原上基本都存在3个明显的大气总水汽量高值中心:即东南部、西南部和西北部;高原大气总水汽量分布的季节变化与500 hPa风场及整层大气水汽通量的变化关系密切。     

A simplified interpretation of the radiances from the SSM/T-2

Summary A microwave radiometer with channels near the 18 GHz water vapor line and in nearby windows, the Special Sensor Microwave/Temperature-2 (SSM/T-2) was launched on a Defense Meteorological Satellite Program (DMSP) satellite in November of 1991. The instrument is intended to provide data for the retrieval of atmospheric water vapor profiles. Because the relationship between the radiances observed by the instrument and the water vapor profile are both non-linear and non-local and because of the influence of clouds, the interpretation of the radiances is inherently complex. Here we develop a simplified, albeit approximate, algorithm for the profile retrievals and test it with simulation studies. Specifically it is shown that for each channel of the instrument near the 183 GHz line there is a nearly constant overburden of water vapor above the height at which the atmospheric temperature equals the observed brightness temperature. This relationship, in turn, provides the basis for a simple analytic algorithm for the relative humidity immediately above that height.The simplified algorithm is useful as a first guess for iterative solutions to the non-linear equations and for a variety of analyses such as estimating the impact of uncertainty in the radiances or the temperature profile on the retrieved water vapor profile. It is also useful as a conceptual tool to aid in the understanding of the more complex algorithms.With 7 Figures     

用MODIS反演北京城市地区地表反照率精度以及算法改进

MODIS(MODerate-resolution Imaging Spectroradiometer)地表反照率的精度在乡村地区已经得到了检验,但是至今没有在城市地区的有关研究。地表反照率的精度在很大程度上取决于大气订正的精度,作者利用2002年以来的北京AERONET(国际气溶胶检测网络)站点Cimel气溶胶观测资料对反射率进行大气订正,通过对比来评价MODIS地表反照率算法中大气订正的精度。结果发现,MODIS大气订正在蓝光波段具有明显的过度订正现象,MODIS大气订正后地表反射率平均偏低0.03。MODIS地表反照率在冬季有约75%的缺测,这是因为冬季严重的空气污染使得MODIS云检测得到晴空观测较少。MODIS使用三参数双向反射率函数（BRDF）要求16天以内至少有3次以上的晴空观测（MODIS算法中要求7次）。通过分析MODIS反演得到的三参数,发现虽然它们的绝对值具有明显的季节变化,但是它们的比值是十分稳定的,这样使BRDF函数降低到只需要一个参数,有效降低了对晴空观测次数的要求,这一思想可以应用到热带等晴空日数较少的地区。     

利用多种再分析资料对比分析青藏高原夏季大气水汽含量变化情况

利用ERA-Interim、MERRA和NCEP/NCAR三套再分析资料,分析1979~2014年夏季青藏高原大气水汽含量的时空变化特征,同时对比了各套资料异同点,结果表明:(1) ERA-Interim和MERRA资料均显示出夏季青藏高原大气水汽含量呈现显著的上升趋势,在1994~1995年前后发生明显突变,大气水汽含量由偏低时期向偏高时期转变;而NCEP/NCAR资料并没有出现类似的显著上升趋势和突变年份;ERA-Interim资料与MERRA资料的夏季青藏高原湿池指数之间的相关性明显强于NCEP/NCAR资料与它们任何一个之间的相关性。(2)夏季青藏高原大气水汽含量呈现出自高原东南边缘地区向西北部递减的分布形式。其中,MERRA与ERA-Interim资料显示的水汽含量分布更为相似,而NCEP/NCAR资料反映的水汽含量在高原中部往北递减不明显,湿度中心较为分散。(3)从空间分布上,MERRA与ERA-Interim资料显示青藏高原大部分地区夏季水汽含量均呈显著的增加趋势,而NCEP/NCAR资料仅在高原东北部小部分区域存在显著的增加趋势。(4)从夏季青藏高原大气水汽含量的年际变化特征分析来看,ERA-Interim和MERRA资料相对于NCEP/NCAR资料也更为接近。      

区域海气耦合模式对华北夏季大气水汽输送模拟结果的检验及其与单独气候模式的比较分析

将区域海气耦合模式RegCM3-POM和区域气候模式RegCM3 40年(1963-2002年)的模拟结果与NCEP/NCAR再分析资料进行对比,检验区域海气耦合模式对中国华北地区夏季大气水汽含量和水汽输送特征的模拟能力,比较耦合模式与单独区域气候模式的差异.结果表明,区域海气耦合模式RegCM3-POM的模拟性能相对于单独区域气候模式RegCM3,大气水汽输送特征的模拟能力有了较大的改进.分析显示两种模式都能够较好地再现东哑地区气候平均夏季大气水汽储量浅红和水汽输送的空间分布特征,而耦合模式对大气水汽输送的模拟更为合理.在对流层中低层更接近观测;耦合模式对中国华北地区夏季平均大气水汽输送通量在垂直方向卜的分布型及水平4个边界水汽输送收支的模拟,相对于单独大气模式有了一定的改进;耦合模式对伴随华北地区夏季早涝的大气水汽异常输送也具有较好的模拟能力,其模拟的水汽输送异常的来源与观测基本一致,尤其是在20°N以北地区,耦合模式结果相对于单独区域气候模式有了很大的改进.但同时耦合模式在低纬度海洋上对气候平均夏季大气水汽含量模拟的偏差比区域气候模式显著;与观测相比,耦合模式对来自孟加拉湾地区的大气水汽输送模拟偏弱,而对西太平洋副热带高压西侧水汽输送模拟偏强,与华北夏季旱涝相联系的水汽输送异常的模拟在低纬度海洋上也存在明显偏差.     

A New Infrared Atmospheric Sounding Interferometer Channel Selection and Assessment of Its Impact on Met Office NWP Forecasts

A new set of Infrared Atmospheric Sounding Interferometer(IASI) channels was re-selected from 314 EUMETSAT channels.In selecting channels,we calculated the impact of the individually added channel on the improvement in the analysis outputs from a one-dimensional variational analysis(1D-Var) for the Unified Model(UM) data assimilation system at the Met Office,using the channel score index(CSI) as a figure of merit.Then,200 channels were selected in order by counting each individual channel's CSI contribution.Compared with the operationally used 183 channels for the UM at the Met Office,the new set shares 149 channels,while the other 51 channels are new.Also examined is the selection from the entropy reduction method with the same 1D-Var approach.Results suggest that channel selection can be made in a more objective fashion using the proposed CSI method.This is because the most important channels can be selected across the whole IASI observation spectrum.In the experimental trial runs using the UM global assimilation system,the new channels had an overall neutral impact in terms of improvement in forecasts,as compared with results from the operational channels.However,upper-tropospheric moist biases shown in the control run with operational channels were significantly reduced in the experimental trial with the newly selected channels.The reduction of moist biases was mainly due to the additional water vapor channels,which are sensitive to the upper-tropospheric water vapor.     

Derivation of Cloud-Free-Region Atmospheric Motion Vectors from FY-2E Thermal Infrared Imagery

The operational cloud-motion tracking technique fails to retrieve atmospheric motion vectors(AMVs) in areas lacking cloud; and while water vapor shown in water vapor imagery can be used, the heights assigned to the retrieved AMVs are mostly in the upper troposphere. As the noise-equivalent temperature difference(NEd T) performance of FY-2E split window(10.3–11.5 μm, 11.6–12.8 μm) channels has been improved, the weak signals representing the spatial texture of water vapor and aerosols in cloud-free areas can be strengthened with algorithms based on the difference principle, and applied in calculating AMVs in the lower troposphere. This paper is a preliminary summary for this purpose, in which the principles and algorithm schemes for the temporal difference, split window difference and second-order difference(SD) methods are introduced. Results from simulation and cases experiments are reported in order to verify and evaluate the methods, based on comparison among retrievals and the "truth". The results show that all three algorithms, though not perfect in some cases,generally work well. Moreover, the SD method appears to be the best in suppressing the surface temperature influence and clarifying the spatial texture of water vapor and aerosols. The accuracy with respect to NCEP 800 h Pa reanalysis data was found to be acceptable, as compared with the accuracy of the cloud motion vectors.     

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 principal component analysis method, but also the interpretability of the conventional channel selection method. The novel SSA method is used to decompose the GIIRS observed infrared brightness temperature spectrum(700-1130 cm~(-1)), and the reconstructed grouped components can be obtained to reflect the energy variations in the temperature-sensitive waveband of the respective sequence. At 700-780 cm~(-1), the channels selected using our method perform better than IASI(Infrared Atmospheric Sounding Interferometer) and Cr IS(Cross-track Infrared Sounder)temperature channels when used as inputs to the neural network retrieval model.     

西南地区夏季大气水汽含量及其与南亚高压关系

利用欧洲中期天气预报中心 (ECMWF) 提供的ERA-interim高分辨率资料,借助经验正交函数 (EOF) 分解、距平合成和相关分析等方法,讨论1979—2014年我国西南地区夏季大气水汽含量的时空变化特征及其与南亚高压的关系。研究结果表明:我国西南地区夏季大气水汽含量空间分布形态主要有全区一致型、南北振荡型和东西振荡型。全区一致型 (EOF1) 能够反映西南地区夏季水汽含量的主要特征,西南地区夏季大气水汽含量具有明显的年际变化特征;西南地区夏季大气水汽含量与南亚高压强度指数、面积指数及东伸指数均存在非常显著的正相关关系;南亚高压的异常偏强,有利于南海地区水汽向西南地区输送,且在西南地区气流由低层向高层的上升运动显著增强,引起西南地区大气水汽含量的异常偏多。     

利用FY-3A近红外资料反演水汽总量

该文介绍了利用搭载在FY-3A卫星上的中分辨率光谱成像仪 (MERSI) 的近红外 (NIR) 通道反演大气水汽总量 (PWV) 的方法。根据预先建立的查找表,大气水汽总量可以通过水汽通道与窗区通道的卫星测值相比反演得到。对MERSI近红外水汽通道灵敏度进行估算,结果表明:处于吸收带两翼的905 nm和980 nm通道对不同水汽量的敏感性表现比较接近,对较大水汽含量最为敏感;当水汽较弱时,强吸收的940 nm通道非常敏感。基于这3个通道对水汽含量敏感性的不同表现,采用3个通道水汽总量的加权平均值作为PWV产品的最终反演值。文中设计了水汽总量业务算法反演流程,并基于FY-3A/MERSI最新观测资料进行晴空大气水汽总量的业务处理生成试验,顺利生成MERSI单轨道水汽总量产品及日拼图中国区域产品和全球产品,同时生成多天合成产品,产品反映出MERSI具有较好的近红外水汽探测能力。将卫星反演结果与探空数据进行初步比对检验,显示卫星反演值有20%~30%系统性偏低,需要进一步改进反演查找表。     

卫星(IASI 探测仪)观测云顶高与地基云雷达观测的对比验证

IASI（Infrared Atmospheric Sounding Interferometer）是搭载在欧洲METOP-A 卫星上,采用干涉分光技术的新一代超高光谱红外大气探测仪器,其光谱测量范围涵盖了多个吸收带,可用于反演大气、海洋、云和大气成分,为地球大气遥感、气象业务和科学研究提供了丰富的遥感资料,是各国学者关注的又一热点。为深入了解IASI 在国内的云产品情况,本文利用2008 年10 月15 日～12 月15 日期间IASI 在安徽寿县地区的云参数观测资料和中美 [美国能源部大气辐射测量（ARM）计划] 联合在安徽省寿县进行大气辐射综合观测试验期间,相同时段云雷达[ARM W-band（95 GHz）Cloud Radar,WACR]的观测资料进行了对比分析和验证。在以寿县ARM 移动观测设施（AMF）为中心,半径为20 km 的范围内,IASI（2 次/d）共有有效观测129 次,其中与WACR（1 次/2 s）匹配的IASI 有效观测共80 时次。结果表明:对于单层云,二者云高相关系数为0.8312,标准差为1.8423 km;对于双层及多层云,IASI 反演云顶高结果绝大多数在WACR 的最上和最下层云之间,且靠近较厚的云层。对比结果显示,一般情况下,IASI 反演云顶高结果明显低于WACR;IASI 反演云顶高结果受到视场中云量、云层厚度及云层中粒子浓度大小的影响:视场中云量越大,云层越厚,云层中粒子浓度越大,IASI 反演云高的结果越接近真实云高。     

南亚高压对亚洲季风区夏季对流层上层水汽异常分布的动力效应

正确认识对流层上层水汽以及其他大气痕量成分的分布和形成机理对于正确认识全球气候变化具有重要的意义.已有的研究说明亚洲季风区为全球的一个特殊的区域.基于最新的卫星微波临边探测仪(EOS-MLS)资料,首先定性地分析了亚洲季风区对流层上层水汽分布异常特征,然后,利用2005年夏季NCEP/NCAR的GFS资料和大气拉格朗日...     

基于GPS技术的大气可降水反演方法

根据全球定位系统遥感水汽的原理,利用2004年6月哈尔滨GPS跟踪站的观测资料和气象资料,对哈尔滨地区的大气综合水汽含量进行了反演,得到了误差(与控探空资料计算的水汽含量相比)为2.7 mm的反演结果。同时对影响水汽反演的误差进行了分析,给出了各项误差对水汽结果的影响程度,并对反演结果与探空资料结果和实际降水进行了比较,得出了其间变化一致性的结论。