The Regularized WSM6 Microphysical Scheme and Its Validation in WRF 4D-Var

A cold cloud assimilation scheme was developed that fully considers the water substances, i.e., water vapor, cloud water, rain, ice, snow, and graupel, based on the single-moment WSM6 microphysical scheme and four-dimensional variational(4D-Var) data assimilation in the Weather Research and Forecasting data assimilation(WRFDA) system. The verification of the regularized WSM6 and its tangent linearity model(TLM) and adjoint mode model(ADM) was proven successful. Two groups of single observation a...     

Development and initial assessment of a new land index for microwave humidity sounder cloud detection

This paper describes a new quality control (QC) scheme for microwave humidity sounder (MHS) data assimilation. It consists of a cloud detection step and an O–B (i.e., differences of brightness temperatures between observations and model simulations) check. Over ocean, cloud detection can be carried out based on two MHS window channels and two Advanced Microwave Sounding Unit-A (AMSU-A) window channels, which can be used for obtaining cloud ice water path (IWP) and liquid water path (LWP), respectively. Over land, cloud detection of microwave data becomes much more challenging due to a much larger emission contribution from land surface than that from cloud. The current MHS cloud detection over land employs an O–B based method, which could fail to identify cloudy radiances when there is mismatch between actual clouds and model clouds. In this study, a new MHS observation based index is developed for identifying MHS cloudy radiances over land. The new land index for cloud detection exploits the large variability of brightness temperature observations among MHS channels over different clouds. It is shown that those MHS cloudy radiances that were otherwise missed by the current O–B based QC method can be successfully identified by the new land index. An O–B check can then be employed to the remaining data after cloud detection to remove additional outliers with model simulations deviated greatly from observations. It is shown that MHS channel correlations are significantly reduced by the newly proposed QC scheme.     

有云环境下MODIS亮温资料的变分同化Ⅰ——方案设计与理想试验

云对红外辐射传输过程有十分重要的影响,在资料同化过程中考虑云的作用,不仅可以改进大气参数的同化效果,还可以利用红外资料调整部分云参数,减小云参数的初始误差。在GRAPES-3DVAR（Global and Regional Assimilation and Prediction Enhanced System,全球/区域同化预报系统）基础上,增加云水含量、云冰水含量和云量作为同化系统控制变量,针对晴空、部分有云和完全有云等环境对MODIS（Moderate Resolution Imaging Spectroradiometer,即中分辨成像光谱仪）的16个气象通道亮温进行了同化理想试验,结果表明当背景场模拟的亮温低于观测亮温时,分析场通过增温、减湿、减少云水含量、云冰水含量、云量可以达到升高模拟亮温的目的;反之可以降低模拟亮温;晴空环境下对温度、比湿的调整符合MODIS仪器的设计特点;有云环境下对云层以下的影响减弱。理想试验证实了在红外辐射资料同化过程中将云参数和大气参数同时作为同化系统控制变量,可以利用红外资料调整云参数和常规气象要素场,提高资料的利用率。     

Physical retrievals of over-ocean rain rate from multichannel microwave imagery. Part I: Theoretical characteristics of normalized polarization and scattering indices

Summary Microwave rain rate retrieval algorithms have most often been formulated in terms of the raw brightness temperatures observed by one or more channels of a satellite radiometer. Taken individually, single-channel brightness temperatures generally represent a near-arbitrary combination of positive contributions due to liquid water emission and negative contributions due to scattering by ice and/or visibility of the radiometrically cold ocean surface. Unfortunately, for a given rain rate, emission by liquid water below the freezing level and scattering by ice particles above the freezing level are rather loosely coupled in both a physical and statistical sense. Furthermore, microwave brightness temperatures may vary significantly (30–70 K) in response to geophysical parameters other than liquid water and precipitation. Because of these complications, physical algorithms which attempt to directly invert observed brightness temperatures have typically relied on the iterative adjustment of detailed microphysical profiles or cloud models, guided by explicit forward microwave radiative transfer calculations.In support of an effort to develop a significantly simpler and more efficient inversion-type rain rate algorithm, the physical information content of two linear transformations of single-frequency, dual-polarization brightness temperatures is studied: thenormalized polarization difference P of Petty and Katsaros (1990, 1992), which is intended as a measure of footprint-averaged rain cloud transmittance for a given frequency; and ascattering index S (similar to the polarization corrected temperature of Spencer et al., 1989) which is sensitive almost exclusively to ice. A reverse Monte Carlo radiative transfer model is used to elucidate the qualitative response of these physically distinct single-frequency indices to idealized 3-dimensional rain clouds and to demonstrate their advantages over raw brightness temperatures both as stand-alone indices of precipitation activity and as primary variables in physical, multichannel rain rate retrieval schemes.As a byproduct of the present analysis, it is shown that conventional plane-parallel analyses of the well-known footprint-filling problem for emission-based algorithms may in some cases give seriously misleading results.With 11 Figures     

Uncertainty of AMSU-A derived temperature trends in relationship with clouds and precipitation over ocean

Microwave Sounding Unit (MSU) and Advanced Microwave Sounding Unit-A (AMSU-A) observations from a series of National Oceanic and Atmospheric Administration satellites have been extensively utilized for estimating the atmospheric temperature trend. For a given atmospheric temperature condition, the emission and scattering of clouds and precipitation modulate MSU and AMSU-A brightness temperatures. In this study, the effects of the radiation from clouds and precipitation on AMSU-A derived atmospheric temperature trend are assessed using the information from AMSU-A window channels. It is shown that the global mean temperature in the low and middle troposphere has a larger warming rate (about 20–30 % higher) when the cloud-affected radiances are removed from AMSU-A data. It is also shown that the inclusion of cloud-affected radiances in the trend analysis can significantly offset the stratospheric cooling represented by AMSU-A channel 9 over the middle and high latitudes of Northern Hemisphere.     

基于亮温通道变率的FY-3C微波湿度计陆地云检测新方法

云检测是卫星资料同化的重要前处理步骤,无论是晴空资料同化还是有云资料同化,都需要准确地区分有云和晴空资料。由于陆地地表发射率的多变性和微波能穿透部分云类的特点,微波湿度计资料在陆地上空的云检测研究一直是难点。利用快速辐射传输模式（CRTM）分析了不同云类条件下FY-3C微波湿度计（MWHS-Ⅱ）各通道亮温的通道间变率特征,根据MWHS-Ⅱ亮温通道间变率随云高以及云中液态水含量的增大而减小的特点,提出了一个基于亮温通道变率的MWHS-Ⅱ陆地资料云检测方法。与已有的云产品比较结果表明:新的云检测算法能有效地剔除大部分受云影响的资料,剔除后的晴空资料观测和模拟偏差更好地符合高斯分布。新方法对过冷水云、冰云、重叠云的检测能力较强,正确检测率可以达到80%,对卷云以及高度较低的水云的检测能力相对较弱。新方法能有效利用MWHS-Ⅱ观测资料自身完成云检测,在MWHS-Ⅱ资料同化中有很好的应用前景。      

基于TMI产品资料对数值模式水凝物模拟能力的检验分析

本文利用热带测雨卫星(Tropical Rainfall Measuring Mission,TRMM)搭载微波成像仪(TRMM Microwave Imager,TMI)的探测及反演结果,结合微波辐射传输模式,就2004年17号台风暹芭(Chaba)过程,对AREM(Advanced Regional Eta-coo...     

云参数对微波亮温模拟计算的影响试验

利用CRTM (Community Radiative Transfer Model) 快速辐射传输模式对NOAA-K系列卫星的AMSU-A通道亮温进行正演模拟,重点研究云粒子类型、云高、云厚度等云参数对微波亮温模拟的影响。结果表明:改变云粒子类型时,云水和雨水对模拟亮温影响较大,模拟亮温值比晴空高1 K;霰、雪、冰、雹等固态粒子对模拟亮温的影响较小,模拟亮温值略低于晴空无云情况;云层光学厚度较大时,各通道亮温受云层影响的情况取决于权重函数峰值高度和云顶高度的配置;多个高度存在云时,若最上层云较厚 (2 km),光学厚度大,相应通道亮温取决于最上层云,较低层云对亮温不产生影响;云层变薄,光学厚度减小,高度低于云层或略高于云顶的通道亮温随云层厚度的变化明显,若通道高度远高于云顶,云层厚度的变化对于其亮温模拟的影响很小。     

ATOVS辐射率资料的直接变分同化试验研究

文中采用增量三维变分 ( 3D Var)同化方法 ,对先进的微波探测装置 (AMSU A)探测的辐射亮温资料与常规探空资料在MM5中尺度数值预报模式中的直接同化和预报进行对比试验研究。结果表明 ,同化AMSU A辐射亮温资料对中高层温度分析场的影响最明显 ,对MM5模式的温度和水汽混合比预报有总体上的正效应 ,但对降水预报的改善作用不大     

三维变分和物理初始化方法相结合同化多普勒雷达资料的试验研究

以美国新近研发的天气研究预报模式(WRF)配置的三维变分(3D-Var)同化系统WRF 3D-Var为平台,结合物理初始化方法(Physical Initialization,简称PI)来同化多普勒雷达径向风和回波强度观测资料.其基本做法是首先用物理初始化方法由雷达回波资料估计出比湿、云水混合比和垂直速度,然后用估计的比湿和云水混合比对模式的相应变量进行调整,最后再将估计出的垂直速度作为一种新的观测类型添加到现有的WRF 3D-Var目标函数中,同时以WRF 3D-Var提供的方法直接同化径向风.针对2002年6月19日的一次强对流性降水过程和2003年7月5日的一次梅雨锋暴雨过程进行了一组同化多普勒雷达径向风和回波资料的试验研究.同化结果表明:分析变量的增量场和观测的雷达回波有很好的对应关系.在雷达回波区,有正的比湿增量、云水含量增量和垂直速度增量,并且水平风增量在此辐合;在没有雷达回波的地方有负的垂直速度增量.预报结果表明,调整云水含量对降水预报改善不明显,调整比湿对降水预报改进明显,直接用物理初始化估计出的垂直速度替代模式的初始垂直速度,对降水预报改进不明显,但以新的方案同化雷达资料能有效地缩短模式的起转时间(spin-up time),明显改进短时降水预报.     

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。     

不同卫星微波遥感资料同化对台风路径模拟的影响

本文以2015年13号超强台风“苏迪罗”为个例,利用WRF模式及其3DVar同化系统对NOAA15、NOAA18和NOAA19的AMSU-A微波遥感资料分别同化及组合同化,探究同化不同卫星的同一种微波遥感资料对于台风路径模拟效果的影响。结果表明:同化不同卫星的同一种微波遥感资料对于台风路径模拟具有不同的调整,本文中NOAA15的同化效果最好,其次是NOAA18,最后是NOAA19;同时同化NOAA15、NOAA18和NOAA19的AMSU-A资料并没有取得最好的同化效果,而组合NOAA15和NOAA18则取得了最好的同化效果,即不是同化的卫星数量越多,同化效果越好;同化试验3个时刻的增量场表明同化不同卫星的同一种微波遥感资料对物理场具有不同的调整,这与其对台风模拟路径的调整有着较好的对应,相对于温度场、海平面气压场、位势高度场和风场的增量结构与模拟台风路径的调整更为密切。     

有云环境下MODIS亮温资料的变分同化Ⅱ——对暴雨预报的影响

卫星资料提供了大量关于云和雨的观测信息,在暴雨预报中可发挥巨大的作用,然而在数值模式资料同化中的应用水平仍然不高,特别是红外辐射资料的应用。由于有云环境下辐射传输过程的模拟难度很大,因此通常只同化晴空环境下的红外辐射资料。基于GRAPES-3DVAR(Global and Regional Assimilation and Prediction Enhanced System,全球/区域同化预报系统),根据RTTOV辐射传输模式(fast radiative transfer model for TOVS,快速辐射传输模式)的特点,增加云水含量、云冰水含量和云量作为同化系统控制变量,在改进辐射传输模式对红外资料模拟的同时,利用红外资料调整初始云参数和大气参数。针对2007年5月26日南海季风爆发后广东地区的一次暴雨过程,选取MODIS(Moderate Resolution Imaging Spectroradiometer,中分辨成像光谱仪)传感器水汽(第27)和云顶观测(第36)通道进行了同化试验,利用WRF(Weather Research and Forecasting Model,天气研究和预报模式)进行了数值模拟,结果表明同化MODIS资料,可以改进初始场水汽和温度分布,间接调整高空风场,调整趋势符合卫星观测,对短时降水预报有正面影响。     

利用卫星遥感资料分析台风“烟花”(202106)的影响过程

2021年第6号台风“烟花”于7月18日生成,7月30日变性为温带气旋,生命史长达13 d,先后对中国东部14个省市造成影响,其主要特点是移动速度慢、陆上滞留时间长和累积雨量大。基于静止气象卫星、极轨气象卫星和全球降水测量卫星的多通道观测和产品,对“烟花”的影响过程进行分析。结果表明：“烟花”空间尺度较大（最大半径约为350 km）,登陆前对流深厚、云系螺旋特征显著,登陆后云系结构遭到破坏、中等对流分布密集但没有组织性;“烟花”在洋面上时液态水和冰态水含量丰富并表现出非对称分布,登陆后液态水和冰态水主要集中在台风前进方向的右侧。基于微波成像仪的降水反演结果显示：降水主要分布在台风外围螺旋雨带位置,且在位置和形态上与实况较吻合;虽然雨量估计值与实况存在一定偏差,但对降水预报,特别是常规资料稀少区域的降水预报仍具有参考意义。     

AMSU资料变分同化及在暴雨数值模拟中的应用研究

在中尺度数值模拟中,利用中国气象科学研究院数值天气预报创新基地开发的GRAPES三维变分同化系统,对AMSU-A/B微波遥感资料进行了同化试验,研究了这种资料在我国夏季暴雨数值预报中的作用。以2003年7月4日的一次暴雨过程为例,分析了同化结果及模拟结果,结果表明:(1)单独同化AMSU-A资料主要改进了初始温度场,而单独同化AMSU-B资料主要改进了初始湿度场;(2)无论是同化AMSU-A资料还是同化AMSU-B资料,对暴雨预报都有一定的改进作用,但是同化AMSU-B资料的改进作用更明显;(3)同时同化AMSU-A/B资料比只使用其中一种资料的模拟效果好,可以更好地改进模拟的暴雨落区及强度,使结果与实况更加接近。使用AMSU资料,对我国夏季暴雨数值预报有改进作用。     

Subpixel fractional cloud cover and inhomogeneity effects on microwave beam-filling error

Using synthetic geometrical clouds and radiative microwave model, we examine the possibility to correct the estimations of liquid water path (LWP) or rain rate with cloud cover measurement. This information may be gotten by co-localized measurements of microwave and infrared/visible measurements on new satellites (TRMM, ADEOS 2, …). In a first step, the effects of fractional cloud cover on microwave brightness temperatures (TB) are investigated in three typical cases of nonprecipitating and precipitating (stratiform and convective) clouds. The beam-filling error (BFE) on brightness temperatures may be analyzed with the known spatial variability using 1D or 3D radiative transfer model. Relationships between BFE and subpixel cloud fraction (CF) are discussed according to the cloud type. We tested several parameters that characterize the horizontal cloud inhomogeneity within a radiometer field of view. BFE was found very sensitive to cloud type and inhomogeneity and is maximum for raining cloud with open spatial structure. In order to account for the uncertainty introduced by the spatial distribution, dependence of BFE on textural-based parameters is also discussed using homogeneity, entropy and an indicator of CF horizontal gradient.     

30-Year atmospheric temperature record derived by one-dimensional variational data assimilation of MSU/AMSU-A observations

In the past, satellite observations of the microwave radiation emitted from the atmosphere have been directly utilized for deriving the climate tends of vertical-layer-averaged atmospheric temperatures. This study presents the 30-year atmospheric temperature trend derived by one-dimensional variational (1D-Var) data assimilation of Microwave Sounding Unit/Advanced Microwave Sounding Unit-A (MSU/AMSU-A) observations. Firstly, the radiance measurements from MSU on board the early National Oceanic and Atmospheric Administration (NOAA)-6 to NOAA-14 and AMSU-A on board NOAA-15 to -19 have been inter-calibrated to form a fundamental climate data record. A 1D-Var method is then employed to establish the thematic climate data record of atmospheric temperature profiles that are appropriate for climate change study. Verification of the MSU/AMSU-A derived temperature profiles with collocated Global Positioning System radio occultation data confirms a reasonable good accuracy of the derived atmospheric temperature profiles in the troposphere and low stratosphere. Finally, the global climate trend of the atmospheric temperature in clear-sky conditions is deduced, showing not only a global warming in the troposphere and a cooling in the stratosphere, but also a stronger warming in the upper troposphere than in the low troposphere.     

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.     

基于CloudSat卫星分析西太平洋台风云系的垂直结构及其微物理特征

基于2012—2014年CloudSat卫星数据,按照热带气旋强度分类的6个等级以及沿台风中心的径向距离,分析西太平洋台风云系的垂直结构及其微物理特征。研究表明:(1)不同强度的台风云系中均是单层云占主导,多层云中双层云出现比例最高;随着台风强度的增强,距离台风中心250km之内,单层云分布位置更加集中且垂直厚度较厚,而450km之外的单层云一直集中在7~15km,厚度较薄;随着台风强度的增强,距离台风中心250km之内的双层云中的底层云和顶层云均增厚且分布位置更加趋于集中,云间距变窄,而450km之外顶层云和底层云较薄,云间距一直较大。(2)台风云系中,深对流云、高层云、卷云与其他云类型相比,分布的垂直范围较广,出现频率较高,分布的位置会随着台风强度变化和沿台风中心径向距离的增加有明显的变化。(3)随着台风强度的增强,近台风中心5km以上的回波有明显增强,除此高值区外,发展较为成熟的台风,距台风中心450km之外也会出现多个明显的柱状回波高值区。(4)近台风中心液水含量的值和冰水含量的值随强度变化均有明显增加,但外围云系中也有分散的冰水含量高值中心但分布高度相对较低,在10km附近;液水粒子数浓度的高值区域与液水含量的高值区非常对应,而冰水含量的高值区位于冰粒子数浓度的高值区下方,表明小的冰粒子被较强的对流活动带到了高处,而大的冰粒子集中在云系较低处。     

AMSU-A全空辐射率资料同化对台风“天鸽”的预报影响研究

利用美国NCEP(National Centers for Environmental Prediction)发展的GSI(Gridpoint Statistical Interpolation)同化系统和GSM(Global Spectral Model)全球频谱预报模式作为循环同化系统,选用2017年第13号台风为研究个例,采用全空和晴空两种同化方案对AMSU-A(The Advanced Microwave Sounding Unit-A)辐射率观测开展同化对比试验,并对台风"天鸽"个例进行5 d预报,研究AMSU-A全空辐射率同化对台风天鸽发展过程预报的影响。结果表明,全空同化方案相比晴空同化方案预报的台风路径、台风中心气压以及台风最大风速预报误差更小;全空同化方案对台风"天鸽"生命周期的模拟更加准确,更接近中国气象局发布的台风天鸽最佳路径的最低气压,而晴空同化方案预报的台风发展较弱,无法预报出成熟期的台风强度;全空同化方案能够增加低层通道海上厚云覆盖区域辐射率资料同化量,增幅占AMSUA同化观测总量10%,从而改进海洋区域天气系统的热力场结构。