应用风云气象卫星及融合降水资料改进地表参数模拟

气象卫星资料不仅对天气、气候研究非常重要, 对于地表参数模拟和预报也具有重要意义。本文首次将全国自动站观测、卫星降水估计和地面观测融合降水资料(CMORPH)以及风云二号D星(FY-2D)积雪覆盖率数据应用到了高分辨率陆面资料同化系统(u-HRLDAS)。融合降水资料用于驱动u-HRLDAS, 同时用于计算雪水当量;积雪覆盖率资料作为u-HRLDAS强迫变量。区域模拟结果表明, 积雪覆盖率对于地表反照率、地表温度以及地气交换通量模拟有极其重要的影响。密云站土壤湿度模拟结果表明, 融合降水资料准确度优于全球陆面资料同化系统(GLDAS)再分析资料。小汤山站单点验证结果表明, 应用融合降水资料及卫星积雪覆盖率资料可以改进地表温度及地气交换通量的模拟。     

卫星资料循环同化应用对区域数值预报效果影响分析

为提高卫星资料在同化系统中的利用率及验证卫星微波资料对区域数值预报效果的影响,本文以2008年8月1-31日为研究时段,利用WRF模式及其WRF-3DVAR同化模块,设计并构建了卫星微波资料的快速循环同化方案,分析循环同化方案对数值预报的改进效果.结果表明,相比于单时次同化,循环同化方案使各预报要素的相关系数在一定程度上得到改善,均方差也呈现减小的趋势.此外,对研究时段内暴雨和台风个例的具体分析显示,循环同化方案能够有效改善降水和台风路径的预报.     

在NCEPGDAS中同化MSG和GOES资料

首次将MSG-2（Meteosat Second Generation-2）卫星上的旋转增强可见光及红外成像仪（Spin—ning Enhanced Visibleand Infrared Imager,SEVIRI）的观测资料同化到美国国家环境预报中心（Na—tional Centers for Environmental Prediction,NCEP）全球资料同化系统（globaldataassimilationsys—tern,GDAS）中。对当前的地球静止业务环境卫星（Geostationary Operational Environmental Satel—lite,GOES）成像仪资料的同化问题也进行了进一步探讨。利用CRTM（The Community Radiative Transfer Model）模式,对SEVIRI辐射率观测资料进行了模拟。为了对红外辐射率资料进行模拟,CRTM模式中的几个关键部分得到改进,例如：动态更新地面发射率资料以及采用了快速精确的气体吸收模块。为了改进对SEVIRI和GOES成像仪辐射率资料的模拟效果,采用了GSICS（The Global Space—Based Inter—Calibration System）标定订正。初步研究结果表明,包含对SEVIRI辐射率资料的水汽通道（6．25和7．35μm）和二氧化碳通道（13．40μm）的同化对GFS（Global Forecast System）6d预报具有显著的正影响;而对其他5个SEVIRI红外窗口通道资料的同化则减小了这种正影响。通过应用GSICS标定算法,订正了SEVIRI和GOES-12成像仪观测资料的偏差,提高了对GFS预报的影响。此外,还需作进一步研究来提高对SEVIRI红外窗口通道辐射率资料同化的有效性。     

卫星辐射率资料EnSRF同化及暴雨模拟应用

基于自主构建的WRF—EnSRF（Weather Researchand Forecasting—Ensemble Square—Root Filter）同化系统,同化了ATOVS（Advanced TIROS Operational Vertical Sounder）辐射率资料,以检验该系统同化卫星资料的能力及其在暴雨过程模拟中的效能。对2008年6月6—7日广东地区一次大暴雨过程进行了同化及数值模拟试验,结果表明,同化ATOVS辐射率资料得到的分析场,丰富了对流层高层的大气温度和对流层中低层的大气湿度信息,对风场也有一定的改进。控制试验和同化试验都较好地模拟出了降水的主要落区和发生时段,但控制试验对暴雨、大暴雨的雨区和雨强的模拟效果欠佳;相比而言,同化试验对强降水中心的位置、范围的模拟均有更好的反映,模拟的暴雨强度也与实际降水量级基本一致,同化改进效果明显。     

Assimilation of FY-3D MWTS-Ⅱ Radiance with 3D Precipitation Detection and the Impacts on Typhoon Forecasts

Precipitation detection is an essential step in radiance assimilation because the uncertainties in precipitation would affect the radiative transfer calculation and observation errors. The traditional precipitation detection method for microwave only detects clouds and precipitation horizontally, without considering the three-dimensional distribution of clouds.Extending precipitation detection from 2D to 3D is expected to bring more useful information to the data assimilation without using the a...     

利用NOAA/AMSU资料和GRAPES同化系统对陆面比辐射率计算的改进研究

地表比辐射率计算的不确定性,直接影响到卫星资料在数值预报中同化应用的效果。本文采用美国NOAA/NESDIS的Weng等[1,2]提出的复杂陆面比辐射率模式,同时用NOAA卫星AMSU-ACh1或Ch2反演的地表比辐射率来调整该模式所需的地表参数,从而在缺少详细地表参数的情况下,改进AMSU-A Ch3和Ch15的地表比辐射率计算精度。在积雪地表情况下,用NOAA卫星AMSU-A资料直接反演各通道的比辐射率,在GRAPES同化系统中的应用表明,结果有明显的改进。     

卫星资料变分同化在一次中尺度强暴雨模拟中的应用

利用ATOVS资料和常规观测资料, 采用GRAPES 3D-Var同化系统和中尺度数值模式MM5设计了仅同化常规观测资料的NOATOVS试验和同化常规观测资料及ATOVS辐射率资料的ATOVS试验, 对2004年6月22—24日长江中下游和西南地区东部的特大暴雨进行了分析和模拟。结果表明:直接同化ATOVS辐射率资料获得的分析场可以有效改进对流层温、湿场分布, 对风场也有一定的影响。对比试验结果表明:ATOVS试验可以较好地模拟出暴雨天气形势、主要影响系统, 对降雨的落区、强度也有较好的反映, 模拟的局地暴雨强度与实际降雨量基本一致, 同化卫星资料的改善效果较为明显。即同化ATOVS资料对于改进中尺度局地暴雨过程模拟效果是可行的。     

Assimilation of the FY-4A AGRI Clear-Sky Radiance Data in a Regional Numerical Model and Its Impact on the Forecast of the “21·7” Henan Extremely Persistent Heavy Rainfall

Assimilation of the Advanced Geostationary Radiance Imager(AGRI) clear-sky radiance in a regional model is performed. The forecasting effectiveness of the assimilation of two water vapor(WV) channels with conventional observations for the “21·7” Henan extremely heavy rainfall is analyzed and compared with a baseline test that assimilates only conventional observations in this study. The results show that the 24-h cumulative precipitation forecast by the assimilation experiment with the addition ...     

WRF-EnSRF卫星资料同化模块的构建研究

为加强国内卫星资料在同化系统中的应用,在自主构建的新一代WRF-EnSRF同化系统中,采用RTTOV辐射传输模式作为观测算子,并建立卫星资料读取、偏差订正及质量控制等子模块,构建出WRF-EnSRF卫星资料同化系统.运用该同化系统,同时同化NOAA-16的AMSU-A和AMSU-B的辐射率资料,进行华南暴雨过程的卫星资料同化数值模拟试验.试验结果表明:偏差订正后亮温资料拟合结果基本位于主对角线上,偏差有所降低.从TS评分看,同化试验对中雨及大雨部分的降水落区以及暴雨级别以上的降水强度的模拟效果有改善.试验证明,建立的卫星同化系统是可运行的.     

基于AMSR-E土壤湿度产品的LIS同化试验

由陆面信息系统 (Land Information System, 简称LIS) 通过NOAH陆面过程模型使用集合卡尔曼滤波开展AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System) 土壤湿度同化试验,得到2003年中国区域垂直深度为4层、水平空间分辨率为0.25°×0.25°的土壤湿度试验数据。使用农业气象观测站土壤相对湿度和国家生态系统野外科学观测研究站土壤体积含水量对试验结果进行检验,结果表明:同化过程整体上提高了陆面模型的模拟精度,草地生态系统模拟精度高于作物和森林生态系统;有效的同化过程依赖于AMSR-E土壤湿度的准确性;模拟出的土壤湿度空间分布特征与实际相符。同化试验得到的时空相对连续且精度相对准确的土壤湿度数据是气候变化和干旱监测的重要数据基础。     

Influence of Surface Temperature and Emissivity on AMSU-A Assimilation over Land

AMSU-A (Advanced Microwave Sounding Unit-A) measurements for channels that are sensitive to the surface over land have not been widely assimilated into numerical weather prediction (NWP) models due to complicated land surface features. In this paper, the impact of AMSU-A assimilation over land in Southwest Asia is investigated with the Weather Research and Forecasting (WRF) model. Four radiance assimilation experiments with different land-surface schemes are designed, then compared and verified against radiosonde observations and global analyses. Besides the surface emissivity calculated from the emissivity model and surface temperature from the background field in current WRF variational data assimilation (WRF-VAR) system, the surface parameters from the operational Microwave Surface and Precipitation Products System (MSPPS) are introduced to understand the influence of surface parameters on AMSU-A assimilation over land. The sensitivity of simulated brightness temperatures to different surface configurations shows that using MSPPS surface alternatives significantly improves the simulation with reduced root mean square error (RMSE) and allows more observations to be assimilated. Verifications of 24-h temperature forecasts from experiments against radiosonde observations and National Centers for Environmental Prediction (NCEP) global analyses show that the experiments using MSPPS surface alternatives generate positive impact on forecast temperatures at lower atmospheric layers, especially at 850 hPa. The spatial distribution of RMSE for forecast temperature validation indicates that the experiments using MSPPS surface temperature obviously improve forecast temperatures in the mountain areas. The preliminary study indicates that using proper surface temperature is important when assimilating lower sounding channels of AMSU-A over land.     

中尺度区域模式层顶高度对高空风场数值模拟的影响分析

本文基于中尺度区域模式WRF,开展模式层顶高度变化对高空气象要素,特别是高空风场数值模拟影响的研究。通过设计模式顶高45、5 hPa两个试验,同化来源于NOAA-15、NOAA-18、NOAA-19和METOP-2的AMSU-A辐射计高通道数据,表明提高模式层顶能够使卫星更多的高通道样本数量进入同化系统,达到减小背景场误差,同时减小高于层顶通道辐射能量对低层通道影响的目的,一定程度上改进了同化效果,从而改善高空气象要素,特别是风场的模拟效果,与观测值的均方根误差减小了约0.4~0.5 m·s^-1。     

Numerical simulation of the impact of vegetation index on the interannual variation of summer precipitation in the Yellow River Basin

Two sets of numerical experiments using the coupled National Center for Environmental Prediction General Circulation Model （NCEP/GCM T42L18） and the Simplified Simple Biosphere land surface scheme （SSiB） were carried out to investigate the climate impacts of fractional vegetation cover （FVC） and leaf area index （LAI） on East Asia summer precipitation, especially in the Yellow River Basin （YRB）. One set employed prescribed FVC and LAI which have no interannual variations based on the climatology of vegetation distribution; the other with FVC and LAI derived from satellite observations of the International Satellite Land Surface Climate Project （ISLSCP） for 1987 and 1988. The simulations of the two experiments were compared to study the influence of FVC, LAI on summer precipitation interannual variation in the YRB. Compared with observations and the NCEP reanalysis data, the experiment that included both the effects of satellite-derived vegetation indexes and sea surface temperature （SST） produced better seasonal and interannual precipitation variations than the experiment with SST but no interannual variations in FVC and LAI, indicating that better representations of the vegetation index and its interannual variation may be important for climate prediction. The difference between 1987 and 1988 indicated that with the increase of FVC and LAI, especially around the YRB, surface albedo decreased, net surface radiation increased, and consequently local evaporation and precipitation intensified. Further more, surface sensible heat flux, surface temperature and its diurnal variation decreased around the YRB in response to more vegetation. The decrease of surface-emitting longwave radiation due to the cooler surface outweighed the decrease of surface solar radiation income with more cloud coverage, thus maintaining the positive anomaly of net surface radiation. Further study indicated that moisture flux variations associated with changes in the general circulation also contributed to the precipitation interannual variation.     

台风数值预报中受云影响微波卫星资料的同化试验

目前, 数值预报中卫星资料的应用主要只是针对晴空条件, 大量受云和降水影响的卫星资料被丢弃不加以使用。但是, 云雨区观测往往包含有大量与天气系统发生发展密切相关的大气信息, 对这部分资料的同化应用由此成为当前研究的一个重要问题。在快速辐射传输模式中云雨粒子辐射效应的考虑还有待于进一步完善情况下, 云雨区卫星资料的应用通常是采用云检测方案对观测受云影响的严重程度进行判识并决定使用的取舍。以0604号热带气旋Bilis作为研究个例, 该文设计了一组受云影响微波卫星资料不同云检测方案和通道选择的应用试验。对AMSU-A资料, 云检测方案包括散射因子、降水概率和小雨检测3种, AMSU-B卫星资料的云检测方法选用了通道2亮温模拟观测误差和Bennartz散射因子。在对进入分析系统卫星资料与天气系统的配置关系、卫星模拟与实际观测偏差特征的统计以及对初始分析影响研究的基础上, 探讨了它们对台风不同阶段数值预报效果的影响。     

GCOM-W AMSR2资料在CMA_GFS 四维变分中的同化应用

卫星微波仪器的辐射率资料,由于兼具卫星观测的全天空优势和微波观测的全天候特性,成为数值天气预报系统同化的日益重要的角色。微波成像仪作为被动微波辐射计的重要一类,其在数值预报中的应用潜力亟待进一步的检验和更充分的挖掘。针对全球水循环变化观测卫星GCOM-W上搭载的第2代先进微波扫描辐射计AMSR2的10个通道,建立了半径200 km的稀疏化方案;研发了包含9项检验的质量控制方案,对于污染低频通道观测的太阳耀光现象和无线电信号干扰等因素进行屏蔽;设计基于经典预报因子的偏差订正方案,对仪器系统偏差进行有效的校正;采用基于变分同化后验估计的观测误差统计,克服了观测误差难以准确估计的问题。通过以上方法,GCOM-W AMSR2共有10个通道辐射率资料在中国自主研发的全球/区域同化预报系统（CMA_GFS,原名为GRAPES_GFS）3.0版的四维变分同化系统（4DVar）中实现了直接同化应用。1个月的批量试验证明,同化GCOM-W AMSR2后,CMA_GFS湿度分析场得到了一定的改进,各量级定量降水中期预报评分有所提高,同时,GCOM-W AMSR2辐射率直接同化对CMA_GFS南半球和赤道地区预报有明显正贡献。研究证实AMSR2能够很好地弥补常规观测资料稀疏区的资料匮乏,发挥水汽敏感特性,改进湿度分析和降水预报的技巧。      

ATOVS 不同卫星资料在台风模拟中的同化试验研究

利用美国国家大气研究中心(NCAR)开发的中尺度模式WRF(ARW)V3.2 及其三维变分同化系统WRF-3DVAR,以1011 号超强台风“ 凡亚比” 为个例,采用连续循环同化的方法对ATOVS 卫星资料进行同化试验,探讨了同化ATOVS 不同卫星资料对“ 凡亚比” 模拟的影响。结果表明,强度影响方面:同化ATOVS不同资料均可有效改善台风强度,台风中心海平面气压平均偏差从42 hPa 下降到18 hPa,但不同资料间的差异并不显著,平均在6 hPa 以内,这表明仅同化ATOVS 资料对台风强度的改善相对有限。路径影响方面:(1)不同卫星的同一种传感器资料效果略有不同,同化NOAA-18 和NOAA-15 的AMSU-A 资料效果较好,NOAA-16 的AMSU-A 效果较差;同化NOAA-15 和NOAA-16 的AMSU-B 资料效果相当,且均优于AMSU-A 资料。(2) 同一颗卫星不同传感器资料的差异较大,同化AMSU-B 资料的改善较为明显,HIRS-3 次之,AMSU-A较差,而同时同化不同资料并没有带来更为明显的改善。(3) 同时同化多颗卫星ATOVS 资料的试验表明,将多种资料引入到同化系统的同时,也带来相应的累积误差,因而仅同化一颗卫星可能比同时同化两颗或三颗卫星ATOVS 资料的效果要好。      

The Impact of Satellite Radiance Data Assimilation within a Frequently Updated Regional Forecast System Using a GSI-based Ensemble Kalman Filter

A regional ensemble Kalman filter (EnKF) data assimilation (DA) and forecast system was recently established based on the Gridpoint Statistical Interpolation (GSI) analysis system. The EnKF DA system was tested with continuous threehourly updated cycles followed by 18-h deterministic forecasts from every three-hourly ensemble mean analysis. Initial tests showed negative to neutral impacts of assimilating satellite radiance data due to the improper bias correction procedure. In this study, two bias correction schemes within the established EnKF DA system are investigated and the impact of assimilating additional polar-orbiting satellite radiance is also investigated. Two group experiments are conducted. The purpose of the first group is to evaluate the bias correction procedure. Two online bias correction methods based on GSI 3DVar and EnKF algorithms are used to assimilate AMSU-A radiance data. Results show that both variational and EnKF-based bias correction procedures effectively reduce the observation and background radiance differences, achieving positive impacts on forecasts. With proper bias correction, we assimilate full radiance observations including AMSU-A, AMSU-B, AIRS, HIRS3/4, and MHS in the second group. The relative percentage improvements(RPIs) for all forecast variables compared to those without radiance data assimilation are mostly positive, with the RPI of upper-air relative humidity being the largest. Additionally, precipitation forecasts on a downscaled 13-km grid from 40-km EnKF analyses are also improved by radiance assimilation for almost all forecast hours.     

AMSU微波探测资料同化的质量控制方法概述

微波相比红外、可见光等卫星探测方式有能够穿透薄云的优点,同化微波探测资料能明显改进数值预报模式初始场。由于观测算子在云、降水粒子及性质复杂下垫面等因素影响下模拟辐射传输过程不准确,以及资料的观测误差较大等原因,实际同化应用时必须对微波探测资料加以认真筛选。为充分发挥探测资料作用并保证同化分析效果,在同化AMSU微波探测的研究中,很多机构和学者建立了散射指数、降水检测等质量控制方法,用来剔除观测算子不能准确模拟的观测。研究表明,资料同化过程中引入质量控制能起到改善同化效果,提高数值天气预报准确率的作用。但是,对于各种质量控制方法的原理和使用条件目前尚无完整的分析,使得各业务研究单位使用的质量控制方案差别较大。文章针对AMSU微波探测资料同化,在分析同化误差来源的基础上,总结了散射指数、降水概率、下垫面类型检测等质量控制方法,并简单讨论了质量控制的发展方向。     

RTTOV散射模块在FY-3 MWHS资料同化中的应用

一直以来,受同化系统中观测算子的限制,云区的卫星微波观测资料在使用时都常会做晴空假设,只考虑大气的吸收作用而忽略散射作用,从而会造成对大气中水汽含量的高估。为了克服这一缺点,文中设计了RTTOV微波散射模块在WRF 3DVAR系统中的应用方案,使得计算辐射能衰减的同时考虑大气的散射作用,并在此基础上通过4组试验进行了风云3 A星微波湿度计亮温以及多普勒雷达反射率因子的同化研究对比。结果表明：RTTOV微波散射模块的引入,能有效抑制晴空辐射模块对大气水汽含量的高估。若先同化雷达反射率因子后再继续同化卫星资料,会发现同化雷达后,同化区域内大气水凝物含量明显增加,受此影响同化卫星资料时大气的散射作用也会随之增大。并且雷达同化区域覆盖率越大,对降水预报的改善效果也愈明显。     

Assimilation of Feng-Yun-3B Satellite Microwave Humidity Sounder Data over Land

The ECMWF has been assimilating Feng-Yun-3B(FY-3B) satellite microwave humidity sounder(MWHS) data over ocean in an operational forecasting system since 24 September 2014. It is more difficult, however, to assimilate microwave observations over land and sea ice than over the open ocean due to higher uncertainties in land surface temperature, surface emissivity and less effective cloud screening. We compare approaches in which the emissivity is retrieved dynamically from MWHS channel 1 [150 GHz(vertical polarization)] with the use of an evolving emissivity atlas from 89 GHz observations from the MWHS onboard NOAA and EUMETSAT satellites. The assimilation of the additional data over land improves the fit of short-range forecasts to other observations, notably ATMS(Advanced Technology Microwave Sounder) humidity channels, and the forecast impacts are mainly neutral to slightly positive over the first five days. The forecast impacts are better in boreal summer and the Southern Hemisphere. These results suggest that the techniques tested allow for effective assimilation of MWHS/FY-3B data over land.