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。     

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。     

有云时大气红外遥感及其反演问题 I. 理论研究

我们已经研究了晴空情况下的大气红外遥感及其反演问题。本文对有云情况下的大气红外遥感及其反演问题进行了研究，首先指出国际上通用的处理有云反演的晴空订正法存在误差放大问题，然后提出了3×3相邻视场同步反演法，在该方法中，假定3×3相邻视场具有共同的大气温度廓线和大气水汽廓线，从而使求解方程数增加到9倍，而反演参数只增加有限的几个，大大提高了有云情况下反演的稳定性。     

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。      

A practical approach for the assimilation of cloudy infrared radiances and its evaluation using airs simulated observations

Abstract

A variational estimation procedure for the simultaneous retrieval of cloud parameters and thermodynamic profiles from infrared radiances is proposed. The method is based on a cloud emissivity model which accounts for the frequency dependence of cloud absorption and scattering and possible mixed phase situations. An effective cloud top height and emissivity are assumed. Monte Carlo experiments performed in a 1D‐var assimilation context using simulated Atmospheric Infrared Radiance Sounder (AIRS) observations from 100 channels demonstrate the substantial added value, in theory, of cloudy radiance assimilation as opposed to clear‐channel assimilation. Improved temperature and humidity retrievals are obtained for a broad layer above the cloud as well as below cloud level under partial cloud cover conditions. The impact is most pronounced in broken to overcast situations involving mid‐level clouds. In these situations, the effective cloud top height and emissivity are retrieved with estimated rms errors typically lower than 30 hPa and 3%, respectively. Expected relative errors on the retrieved effective particle size are of the order of 30–50%. The methodology is directly applicable to real hyperspectral infrared data upon inclusion, for local estimation, of the cloud parameters in the Canadian 4D‐var assimilation system.     

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.     

高光谱红外云检测方案阈值的客观判定方法

GRAPES3Dvar大气红外高光谱云检测采用McNally andWatts(2003)的晴空通道方案,该方案基于模拟观测与实际观测偏差(B-O)进行检测,其中阈值的选取与预报模式有关。传统对云检测阈值的选取多采用主观判定方法,如图像对比分析等。文章在主观判定的基础上提出两种新的较为客观的阈值判定方法:(1)视场偏差分析:通过分析模拟观测与实际观测之间偏差的垂直分布,观察不同阈值下的云顶高度来评估阈值选取的合理性;(2)云检测指标评分:通过建立一系列云检测指标,对其进行评分来选取最优的阂值。并结合上述三种方法,将其应用于IASI辐射率资料的云检测阈值判定,其中梯度阈值对最后的云检测效果影响不大,保持与欧洲中心相同的值;偏差阈值则采用综合的分析方法进行判定,从而克服了单纯利用云图对比而带来的视觉误差。分析结果表明,偏差阈值取2.0 K、窗区通道梯度阈值取0.4 K,非窗区通道梯度阈值取0.02 K时云检测的效果最好。最后进行的为期1个月的试验显示:通过对比不同云检测偏差阈值的同化效果,选取的云检测闾值是有效的。     

Cloud mapping from the earth's surface using infrared radiance contrasts*

Abstract

Radiance criteria for distinguishing low, middle, and high clouds in the 9.5–11.5 μm band of the infrared are developed and used to produce local cloud maps. The performance of this radiance contrast method for mapping clouds from the earth's surface is evaluated with a view to using the technique for objective observation of cloud amount and distribution in the sky hemisphere.

Discrimination radiance formulas are developed using a multilayer, wavenumber‐specific infrared radiative transfer model including cloud parameters measured by other workers and atmospheric conditions measured by radiosonde. The clear sky radiance (N₀) is the dominant independent variable in the discrimination formulas. The variation of N₀ with time (primarily due to changes in atmospheric water vapour content) and zenith angle are found to be important in distinguishing cirriform clouds from clear sky and other clouds.

The local cloud maps are produced by applying the discrimination radiances (in voltage form) to the output from a narrow‐view infrared radiometer pointed at a sky‐scanning mirror. It is necessary to assume that the radiance from a cloud observed at the surface decreases unambiguously with an increase in cloud base height. Cloud maps for five days in July 1978 indicate the mapping technique shows promise under a wide range of sky conditions. Cloud motions rapidly degrade the maps’ quality over time‐scales that are much less than the current manual cloud sampling period of 1 h.     

红外高光谱资料模拟大气廓线反演对云的敏感性

用不同云顶高度和不同有效云量时的星载红外高光谱观测值,模拟大气温湿垂直廓线反演对云参数的敏感性。用特征向量统计反演法按照云顶高度和有效云量分类反演了大气温湿廓线,统计了不同云高（200,300,500,700和850hPa）及云高有50hPa误差时温度、水汽混合比反演的均方根误差随有效云量的变化。结果表明,随着有效云量的增大,云顶以下各高度层上的温度、水汽混合比反演误差都明显增大。云高有50hPa误差较准确已知而言,温度和水汽混合比的反演误差增大,但温度反演对云高误差的敏感性比水汽反演要高。     

Validation of Forecast Cloud Parameters from Multispectral AIRS Radiances

The well-known CO₂ slicing technique which provides retrievals of cloud parameters (effective height and amount) is adapted in light of model validation using multispectral infrared sounders. The technique is applied to both real Atmospheric Infrared Sounder (AIRS) radiances and to corresponding radiances simulated from global 6 h and 12 h forecasts for the 31 days of July 2008. The forecast model is the one used operationally at the Canadian Meteorological Centre. Radiances are simulated from the Radiative Transfer for the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (RTTOV) model. When compared to model output of cloud parameters, simulated retrievals help us understand systematic biases linked to the retrieval technique. Systematic errors of interest, attributed to forecast cloud parameters, are then more clearly assessed from real retrievals. This is the central idea of this paper. The proposed definition of model cloud top, based on cloud transmittance, corresponds well to the height derived from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) instrument. These lidar-derived cloud heights, in turn, confirm the nature of the biases produced by the CO₂ slicing technique (e.g., a negative bias increasing with height to about 2 km (approximately 50 hPa) for the highest clouds at 16 km (approximately 100 hPa)). Results suggest that the model has a tendency to produce an excess of low-level clouds below 2 km, compensated for by a deficit from 3 to 6 km. No significant differences are found between 6 h and 12 h forecast monthly fields, an indication that the model has sufficiently spun-up after a few hours. Retrieved global monthly cloud parameter fields are compared to independently derived products available from the Moderate Resolution Imaging Spectrometer (MODIS) and AIRS standard processing. Significant differences are noted, linked to the different retrieval approaches, input data and resolution. This is further evidence that, for validation purposes, definitions of observed and model parameters must be consistent.     

A validation of the multivariate and minimum residual method for cloud retrieval using radiance from multiple satellites

The Multivariate and Minimum Residual(MMR) cloud detection and retrieval algorithm, previously developed and tested on simulated observations and Advanced Infrared Sounder radiance, was explored and validated using various radiances from multiple sensors. For validation, the cloud retrievals were compared to independent cloud products from Cloud Sat, MODIS(Moderate Resolution Imaging Spectroradiometer), and GOES(Geostationary Operational Environmental Satellites). We found good spatial agreement within a single instrument, although the cloud fraction on each pixel was estimated independently. The retrieved cloud properties showed good agreement using radiances from multiple satellites, especially for the vertically integrated cloud mask. The accuracy of the MMR scheme in detecting mid-level clouds was found to be higher than for higher and lower clouds. The accuracy in retrieving cloud top pressures and cloud profiles increased with more channels from observations. For observations with fewer channels, the MMR solution was an "overly smoothed" estimation of the true vertical profile, starting from a uniform clear guess. Additionally, the retrieval algorithm showed some meaningful skill in simulating the cloudy radiance as a linear observation operator, discriminating between numerical weather prediction(NWP) error and cloud effects. The retrieval scheme was also found to be robust when different radiative transfer models were used. The potential application of the MMR algorithm in NWP with multiple radiances is also discussed.     

Assimilating All-sky Infrared Radiances from Himawari-8 Using the 3DVar Method for the Prediction of a Severe Storm over North China

Although radar observations capture storm structures with high spatiotemporal resolutions, they are limited within the storm region after the precipitation formed. Geostationary satellites data cover the gaps in the radar network prior to the formation of the precipitation for the storms and their environment. The study explores the effects of assimilating the water vapor channel radiances from Himawari-8 data with Weather Research and Forecasting model data assimilation system(WRFDA) for a severe storm case over north China. A fast cloud detection scheme for Advanced Himawari imager(AHI)radiance is enhanced in the framework of the WRFDA system initially in this study. The bias corrections, the cloud detection for the clear-sky AHI radiance, and the observation error modeling for cloudy radiance are conducted before the data assimilation. All AHI radiance observations are fully applied without any quality control for all-sky AHI radiance data assimilation. Results show that the simulated all-sky AHI radiance fits the observations better by using the cloud dependent observation error model, further improving the cloud heights. The all-sky AHI radiance assimilation adjusts all types of hydrometeor variables, especially cloud water and precipitation snow. It is proven that assimilating all-sky AHI data improves hydrometeor specifications when verified against the radar reflectivity. Consequently, the assimilation of AHI observations under the all-sky condition has an overall improved impact on both the precipitation locations and intensity compared to the experiment with only conventional and AHI clear-sky radiance data.     

红外高光谱观测值反演云参数

最小局部比辐射率变化MLEV算法根据在红外长波10～15 μm 区, 云的吸收、发射和散射具有相对有限的局部谱变化的特征, 利用对云敏感的长波红外辐射观测值来同时反演单层云的云顶高度和有效云比辐射率谱。先给定一些假想的云高初始猜测, 最佳的云高和比辐射率谱解使得用这些不同云高计算得到的比辐射率谱的局部变化最小, 该算法适用于高光谱(光谱分辨率从0.25～1 cm-1) 的大气红外探测器。通过用两种不同方案的内部比较及与激光雷达观测和MODIS业务云高产品的对比验证, 说明对卫星红外高光谱观测资料采用MLEV算法同时反演单层云的云顶高度和云有效比辐射率谱是非常有效的, 尤其是对中高云。     

The effect of cirrus clouds on microwave limb radiances

This study presents and analyses the first simulations of microwave limb radiances with clouds. They are computed using the 1D unpolarized version of the Atmospheric Radiative Transfer System (ARTS). The study is meant to set a theoretical foundation for using microwave limb measurements for cloud monitoring. Information about clouds is required for the validation of climate models.Limb spectra are generated for the frequency bands of the Millimeter wave Acquisitions for Stratosphere/Troposphere Exchange Research (MASTER) instrument. For these simulations, the radiative transfer equation is solved using the Discrete Ordinate ITerative (DOIT) method, which is briefly described. Single scattering properties for the cloud particles are calculated using the T-matrix method.The impact of various cloud parameters is investigated. Simulated brightness temperatures most strongly depend on particle size, ice mass content and cloud altitude. The impact of particle shape is much smaller, but still significant. Increasing the ice mass content has a similar effect as increasing the particle size; this complicates the prediction of the impact of clouds on microwave radiances without exact knowledge of these cloud parameters.     

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...     

基于红外实时阈值的全天空云量观测

红外测温传感器在旋转平台控制下定时对全天空进行扫描,拼接全天空红外辐射亮温图像。利用天空中的云点与非云点在红外波段中表现出的不同特性,考虑不同仰角方向天空中云点与非云点的温度差异,结合地面环境参数,实时拟合天顶到水平区间内晴空时刻的温度阈值函数,利用阈值分割方式得出全天空云分布及云量信息。该方法可以有效减少地面环境参数及太阳光照对云图的影响,能够全天实时运行。将利用该方法获取的数据分别与人工观测数据及典型天气条件下可见光测云结果进行对比,结果表明该系统在云量观测方面具有一定的先进性和准确性。     

Remote sensing of cloud liquid water

Summary A method is presented to infer cloud liquid water path (LWP in kg/m²) over the ocean from passive microwave measurements of SSM/I. The algorithm to retrieve LWP is based on simulated satellite observations. They are calculated with a radiative transfer model applied to about 3000 radiosonde ascents over the Atlantic Ocean. Since radiosonde observations do not contain direct information about cloud water and ice, these parameters are parameterized based on relative humidity and temperature using modified adiabatic liquid water density profiles. A multiple linear regression is applied to the simulated radiances and the calculated LWP to derive the algorithm. The retrieval accuracy based on the regression analysis including instrumental noise is 0.03 kg/m². Validation of the LWP-algorithm was pursued through a comparison with measurements of a ground-based 33 GHzmicrowave radiometer on board of R.V. Poseidon during the International Cirrus Experiment 1989 at the North Sea (ICE'89). The LWP values agree within the range of uncertainty caused by the different sampling characteristics of the observing systems. The retrieval accuracy for clear-sky cases determined using colocated METEOSAT data over the North Sea is 0.037 kg/m² and confirms the accuracy estimated from regression analysis for the low liquid water cases.The algorithm was used to derive maps of monthly mean LWP over the Atlantic Ocean. As an example the Octobers of the 5 years 1987–1991 were selected to demonstrate the interannual variability of LWP. The results were compared with the cloud water content produced by the climate model ECHAM-T2 from the Max-Planck-Institut Hamburg.Observations during ICE'89 were used to check the accuracy of the applied radiative transfer model. Brightness temperatures were calculated from radiosonde ascents launched during the overpass of DMSP-F8 in cloud-free situations. The channel-dependent differences range from about –2 to 3 K.The possibility to identify different cloud types using microwave and infrared observations was examined. The main conclusion is that simultaneous microwave and infrared measurements enable the separation of dense cirrus and cirrus with underlying water clouds. A classification of clouds with respect to their top heights and LWP was carried out using a combination of SSM/I derived LWP and simultaneously recorded Meteosat IR-data during ICE'89.With 11 Figures     

Quality Assessment and Forecast Sensitivity of Global Remote Sensing Observations

The satellite-derived wind from cloud and moisture features of geostationary satellites is an important data source for numerical weather prediction(NWP) models. These datasets and global positioning system radio occultation(GPSRO)satellite radiances are assimilated in the four-dimensional variational atmospheric data assimilation system of the UKMO Unified Model in India. This study focuses on the importance of these data in the NWP system and their impact on short-term24-h forecasts. The quality of the wind observations is compared to the short-range forecast from the model background. The observation increments(observation minus background) are computed as the satellite-derived wind minus the model forecast with a 6-h lead time. The results show the model background has a large easterly wind component compared to satellite observations. The importance of each observation in the analysis is studied using an adjoint-based forecast sensitivity to observation method. The results show that at least around 50% of all types of satellite observations are beneficial. In terms of individual contribution, METEOSAT-7 shows a higher percentage of impact(nearly 50%), as compared to GEOS, MTSAT-2and METEOSAT-10, all of which have a less than 25% impact. In addition, the impact of GPSRO, infrared atmospheric sounding interferometer(IASI) and atmospheric infrared sounder(AIRS) data is calculated. The GPSRO observations have beneficial impacts up to 50 km. Over the Southern Hemisphere, the high spectral radiances from IASI and AIRS show a greater impact than over the Northern Hemisphere. The results in this study can be used for further improvements in the use of new and existing satellite observations.     

地基双波段测云系统及其对比试验

针对地基测云系统中云在可见光波段与红外波段中表现出的不同特性,用双站数字式云高仪所测云高进行标校,结合地面实时观测天顶红外辐射亮温及地面环境参数,分析地面到云层底大气对红外辐射亮温的影响,从中发现利用天空红外辐射亮温来遥感云底高度的可行性,研发地基双波段测云系统。该系统以对流层大气的垂直温度递减率为理论基础,建立云层底到地面的温度递减梯度参数K,根据递减梯度参数反演天顶方向的云高。该算法不依赖于探空数据,通过实时定标形式得出符合仪器所在地的云底高反演公式。通过与维萨拉激光云高仪CL31进行数据对比分析得出,地基双波段测云系统反演结果具有较高的准确性。