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.     

Assimilation of Global Navigation Satellite Radio Occultation Observations in GRAPES: Operational Implementation

This paper presents the design of an observation operator for assimilation of global navigation satellite system (GNSS) radio occultation (RO) refractivity and the related operational implementation strategy in the global GRAPES variational data assimilation system. A preliminary assessment of the RO data assimilation effect is performed. The results show that the RO data are one of the most important observation types in GRAPES, as they have a significant positive impact on the analysis and forecast at all ranges, especially in the Southern Hemisphere and the global stratosphere where in-situ measurements are lacking. The GRAPES model error cannot be controlled in the Southern Hemisphere without RO data being assimilated. In addition, it is found that the RO data play a key role in the stable running of the GRAPES global assimilation and forecast system. Even in a relatively simple global data assimilation experiment, in which only the conventional and RO data are assimilated, the system is able to run for more than nine months without drift compared with NCEP analyses. The analysis skills in both the Northern and Southern Hemispheres are still relatively comparable even after nine-month integration, especially in the stratosphere where the number of conventional observations decreases and RO observations with a uniform global coverage dominate gradually.     

Assimilation of Global Navigation Satellite Radio Occultation Observations in GRAPES:Operational Implementation

This paper presents the design of an observation operator for assimilation of global navigation satellite system(GNSS) radio occultation(RO) refractivity and the related operational implementation strategy in the global GRAPES variational data assimilation system.A preliminary assessment of the RO data assimilation effect is performed.The results show that the RO data are one of the most important observation types in GRAPES,as they have a significant positive impact on the analysis and forecast at all ranges,especially in the Southern Hemisphere and the global stratosphere where in-situ measurements are lacking.The GRAPES model error cannot be controlled in the Southern Hemisphere without RO data being assimilated.In addition,it is found that the RO data play a key role in the stable running of the GRAPES global assimilation and forecast system.Even in a relatively simple global data assimilation experiment,in which only the conventional and RO data are assimilated,the system is able to run for more than nine months without drift compared with NCEP analyses.The analysis skills in both the Northern and Southern Hemispheres are still relatively comparable even after nine-month integration,especially in the stratosphere where the number of conventional observations decreases and RO observations with a uniform global coverage dominate gradually.     

The impact of observation systems on medium-range weather forecasting in a global forecast system

To investigate the impact of various types of data on medium-range forecasts, observing system experiments are performed using an assimilation algorithm based on the National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) reanalysis system. Data-denial experiments for radiosonde, satellite, aircraft, and sea surface observations, and selected data experiments for radiosonde and surface data, are conducted for the boreal summer of 1997 and the boreal winter of 1997/1998. The data assimilation system used in this study is remarkably dependent on radiosonde data, which provides information about the three-dimensional structure of the atmosphere. As expected, the impact of radiosonde observations on medium-range forecasts is strongly positive over the Northern Hemisphere and tropics, whereas the satellite system is most beneficial over the Southern Hemisphere. These results are also found in experiments simulating historical changes in observation systems. Over the tropics, assimilation without radiosonde observations generates unbalanced analyses resulting in unrealistic forecasts that must be corrected by the forecast model. Forecasts based on analysis from the observation data before the era of radiosonde observation are found to be less meaningful. In addition, the impacts on forecasts are closely related to the geographical distribution of observation data. The memory of observation data embedded in the analysis tends to persist throughout forecasts. However, cases exist where the effect of forecast error growth is more dominant than that of analysis error, e.g., over East Asia in summer, and where the deficiency in observations is supplemented or the imbalance in analysis is adjusted by the forecast model during the period of forecasts. Forecast error growth may be related to the synoptic correction performed by the data assimilation system. Over data-rich areas, analysis fields are corrected to a greater extent by the data assimilation system than are those over data-poor areas, which can cause the forecast model to produce more forecast errors in medium-range forecasts. It is found that even one month per season is sufficient for forecast skill verification in data impact experiments. Additionally, the use of upper-air observations is found to benefit areas that are downstream of observation data-rich areas.     

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.     

硫酸盐气溶胶对全球水循环因子的影响

  利用卫星资料进一步检验了CAM3.0模式对云的模拟能力,该模式可以较好地再现全球云的分布和季节变化的主要特征。在硫循环过程与辐射和动力过程之间双向耦合的情况下,探讨了硫酸盐气溶胶直接气候效应对水循环过程的影响。模式较好地模拟了硫酸盐气溶胶的浓度和分布变化。硫酸盐气溶胶对水循环因子的影响在不同季节和区域是不同的,其中,北半球夏季的影响最大,这是因为北半球夏季硫酸盐浓度最高。纬向平均的云量、降水和水汽的变化形势大部分相似,存在比较密切的联系。     

基于集合的观测资料影响性评价——简单AGCM的理想试验

在Liu and Kalnay (2008) 的研究基础上, 将基于集合的观测资料影响性评价方法(简称LK08法)运用到一个简单的大气环流模式中, 对模拟探空资料的预报影响性进行了综合评价, 考察了LK08法在真实大气环流模式上的适用性。研究结果表明, 应用基于集合的评价方法可以一次性计算出同化系统中每个观测的影响性, 然后按观测手段、观测区域等进行影响性数值的简单累加, 以此可以比较不同类型观测的相对影响性。比较结果显示, 不同半球的模拟探空观测对预报的总影响性相差不大, 但由于南半球资料个数要远远少于北半球, 因此, 南半球单个观测的影响性要大于北半球的单个观测。不同观测类型对预报的总影响性也不相同。有效性验证分析表明, 按LK08法计算得到的总体观测影响性能解释实际影响性的70%～80%, 且很好地抓住了其变化和走势。     

Two warm frontal passages at Ottawa,Canada

The numerical simulations of Baumhefner (1971, 1972) and Miyakoda and Umscheid (1973) have shown that a “wall” placed at or near the equator has a serious effect on Northern Hemisphere forecasts after 10–14 days.

In practice, however, numerical models have available some information from the Southern Hemisphere. The question is posed, “How much information from the Southern Hemisphere is necessary to yield a forecast for the Northern Hemisphere which is more accurate than that obtained by integrating over the Northern Hemisphere alone?”

A simple numerical experiment demonstrates that a global model in which only the largest scales of the Southern Hemisphere are known at initial time yields a more accurate forecast for the Northern Hemisphere than a hemispheric model.     

Cross‐equatorial error propagation: Research note

Abstract

Numerical simulation experiments published in 1974 by Daley have been repeated with a much higher resolution, spectral, shallow water model. With a forecast period extending toll d, it is shown that a global model in which only the largest scales are used at initial time in the Southern Hemisphere yields a more accurate forecast for the Northern Hemisphere than a hemispheric model does. Compared with a uniform high‐resolution, global model, the error in the Northern Hemisphere forecast is high in the ultra‐long waves but decreases rather rapidly while the resolution of the initial Southern Hemispheric data is increased.     

基于往返式平漂探空的FY-3D卫星反演温度检验

往返式平漂探空观测（以下简称平漂探空）可实现对流层至平流层低层大气温度廓线垂直探测以及平流层低层内持续4 h的水平温度分布探测。该文介绍利用平漂探空试验数据对风云3号气象卫星D星（FY-3D）反演温度数据的检验评估算法,基于该算法和2021年3—9月长江中下游平漂探空试验数据完成对卫星反演大气温度数据的检验。结果显示:FY-3D卫星反演的温度数据准确度总体较高,与平漂探空上升段数据平均绝对偏差约为1.34℃,与下降段数据平均绝对偏差约为1.93℃;卫星反演的100 hPa以上和850 hPa以下温度误差分别偏大0.59℃和0.33℃;卫星反演平流层温度准确度低于温度廓线,平均绝对偏差约为3.92℃;与平漂探空数据相比,卫星大气温度廓线分辨率较低、趋势较平滑,无法显示大气温度垂直分布和平流层温度水平分布的细节特征。     

全球大气温度廓线的统计特性分析

利用欧洲数值预报中心发布的第三代ERA-Interim月平均再分析资料对1979—2016年全球大气温度廓线进行统计,分别探讨了南、北半球大气温度廓线平均值和标准差随季节、纬度和海陆的时空分布特征,并与国内外常用的AFGL标准大气廓线进行了对比。研究结果表明:南、北半球各高度层温度的平均值、频数最大温度区间和最大值垂直分布均随高度先减小后增加;在大气低层,多年的温度波动较大,200 hPa处波动达到最小;不论是北半球还是南半球,大气温度平均值廓线均具有典型的纬度差异,其中低纬度季节性差异较小,中纬度次之,高纬季节性差异最大;各季节大气温度廓线的海陆差异不同,且南半球海陆差异比北半球大。大气温度标准差廓线同样存在纬度、海陆和季节分布差异。根据ECMWF再分析资料构建的温度廓线较AFGL标准大气廓线而言具有更加丰富的时空分布等细节特征,并且代表了气候变化后最新的大气温度状况。有关结果可作为现有标准大气廓线的更新和完善,为新型卫星仪器应用性能评估、辐射传输算法和大气反演方法评价和对比分析提供支持。      

A SPATIAL-TEMPORAL DISTRIBUTION CHARACTERISTICS STUDY ON THE ATMOSPHERIC CARBON DIOXIDE OBSERVED BY GOSAT SATELLITE REMOTE SENSING

The variation of the atmospheric Carbon Dioxide (CO2) concentration plays an important role in global climate and agriculture. We analyzed the spatial-temporal characteristics of CO2 in the China region and around the globe with the CO2 column mixing ratios observed by the Japanese GOSAT satellite (Greenhouse Gases Observing Satellite). In order to make sure that the accuracy of the CO2 data retrieved by the satellite meets the needs of the climate characteristics analyses, we ran a validation on the CO2 column mixing ratios retrieved by the satellite against the ground-based TCCON (Total Carbon Column Observing Network) observation data. The result shows that the two sets of data have a correlation coefficient of higher than 0.7, and a bias of within 2.2 ppmv. Therefore, the GOSAT CO2 data can be used for the climate characteristics analysis of global CO2. Our analysis on the spatial-temporal characteristics of the CO2 column mixing ratios observed during the period of June 2009 through January 2014 proved that, with the impact of the natural emission of near ground CO2 and human activities, the global CO2 concentration has a significant latitudinal characteristics with its highest level averaging 390 ppmv in the 0-40oN latitudinal zone in the Northern Hemisphere, and 387 ppmv in the Southern Hemisphere. China has a relatively higher CO2 concentration with the highest level exceeding 398 ppmv, and the eastern area higher than the western area. The variation of global CO2 concentration shows a seasonal pattern, i.e. the CO2 concentration reaches its highest in spring in the Northern Hemisphere averaging more than 392 ppmv, second highest in winter, and lowest in summer averaging less than 387 ppmv. It fluctuates the most in the Northern Hemisphere with an average concentration of 392.5 ppmv in April, and 385.5 ppmv in July. While in the Southern Hemisphere, the seasonal fluctuation is smaller with the highest concentration occurring in July. Over the recent years, the global CO2 concentration has shown an elevating trend with an average annual increase rate of 1.58 ppmv per year. It is a challenge that the human kind has to face to slow down the increase of the CO2 concentration.     

Assimilation of ERS‐2 scatterometer winds using the Canadian 3D‐var

Abstract

The goal of this study is to evaluate the impact of incorporating the marine surface winds retrieved from the ERS‐2 scatterometer in the Canadian three‐dimensional variational analysis system, (3D‐var). The aspects of the 3D‐var most relevant to the assimilation of surface ‐wind observations and a general method for resolving the directional ambiguity of the retrieved scatterometer ‐winds are first described. A comparison ‐with 6‐h forecasted winds is then made to demonstrate that these data are of high quality, but exhibit a speed bias that can be removed by increasing their amplitudes by about 5%. The analysis increment from a single scatterometer wind observation is calculated to illustrate the response of the 3D‐var to surface wind observations. As a consequence of the forecast error covariance model, the assimilation of surface wind observations produces meteorologically consistent increments for both the rotational and divergent wind components and the mass field. The results from a series of cross‐validation experiments using ship‐based wind data demonstrate a positive impact of assimilating scatterometer winds and the effectiveness of a simple method for estimating and removing the speed bias. The impact of assimilating scatterometer data within a short assimilation cycle is also evaluated. Overall, the results show that including scatterometer data in the analysis decreases the 6‐h forecast error of surface wind by 13%. Over the northern extra‐tropics the improvement is only 4% and for the southern extra‐tropics it is 16%. Results from a series of two‐day forecasts produced using the analyses from the assimilation cycles with and without retrieved scatterometer winds included are also presented. Using radiosonde observations at 850 hPa, 500 hPa, 250 hPa and 100 hPafor verification, the impact on the forecasts is nearly neutral in the northern hemisphere and the tropics. Conversely, a significant positive impact is found on both wind and mass fields in the southern hemisphere over the entire two‐day forecast.     

GNSS反演资料在GRAPES_Meso三维变分中的应用

为了进一步提高GRAPES_Meso的分析和预报效果,该文在GRAPES_Meso三维变分同化系统中建立了同化GNSS/RO反演的大气资料的观测算子,实现了对GNSS/RO反演的大气资料的同化应用,并通过2013年7月1个月的同化和预报试验分析了GNSS/RO反演大气资料对GRAPES_Meso模式系统分析和预报的影响。结果表明:增加了GNSS/RO反演大气资料的同化后,GRAPES_Meso位势高度场的分析误差明显减小,平均分析误差减小约8%,预报误差略有减小,平均预报误差减小约1%;湿度场的分析误差和预报误差变化不明显,常规观测资料稀少的青藏高原地区的降水预报技巧有所提高,小雨到大雨的ETS (equitable threat score) 评分提高约0.01,对全国及其他分区的降水预报技巧总体上有正效果。     

先进技术微波探测仪(ATMS)云液态水路径算法评估

云液态水路径是气候和天气系统分析的重要参数,可以从卫星观测资料反演获得.目前,基于卫星微波探测仪器观测资料的云水算法可由23.8和31.4 GHz两个通道产生.本研究使用先进技术微波探测仪(ATMS)观测数据,对物理和经验两种算法反演出的云液态水路径进行验证评估.结果表明,经验算法和物理算法都可以描述云液态水在全球洋面...     

Preliminary Study on Direct Assimilation of Cloud-affected Satellite Microwave Brightness Temperatures

Direct assimilation of cloud-affected microwave brightness temperatures from AMSU-A into the GSI three-dimensional variational(3D-Var) assimilation system is preliminarily studied in this paper. A combination of cloud microphysics parameters retrieved by the 1D-Var algorithm(including vertical profiles of cloud liquid water content, ice water content, and rain water content) and atmospheric state parameters from objective analysis fields of an NWP model are used as background fields. Three cloud microphysics parameters(cloud liquid water content, ice water content, and rain water content) are applied to the control variable. Typhoon Halong(2014) is selected as an example. The results show that direct assimilation of cloud-affected AMSU-A observations can effectively adjust the structure of large-scale temperature, humidity and wind analysis fields due to the assimilation of more AMSU-A observations in typhoon cloudy areas, especially typhoon spiral cloud belts. These adjustments, with temperatures increasing and humidities decreasing in the movement direction of the typhoon,bring the forecasted typhoon moving direction closer to its real path. The assimilation of cloud-affected satellite microwave brightness temperatures can provide better analysis fields that are more similar to the actual situation. Furthermore, typhoon prediction accuracy is improved using these assimilation analysis fields as the initial forecast fields in NWP models.     

Construction of vertical wind profile from satellite-derived winds for objective analysis of wind field

During summer Monex-79, a variety of observing systems viz. research ships, research aircrafts, constant pres-sure balloons and geostationary satellite etc. were deployed, besides the regular conventional observations The pur-pose of these additional systems was to make the best possible data for the studies on various aspects of monsoon cir-culation. The present study is aimed at the construction of vertical wind profile using cloud motion vectors obtained from GOES (I-O) satellite and to examine whether the constructed wind profiles improves the representation of the monsoon system, flow pattern etc. in the objective analysis. For this purpose, climatological normals of the wind field are considered as the initial guess and the objective analyses of the wind field are made with, first using only data from conventional observations over land areas, subsequently including the constructed winds from cloud motion vectors. These analyses are then compared with the standard analyses of wind field obtained from Quick Look Atlas by T. N. Krishnamurti et al. (1979).It is inferred that satellite estimated mean wind profiles show good agreement with the mean wind profiles of the research ships with RMS errors less than 5 mps below 500 hPa and less than 8 mps above 500 hPa. It is further infer-red that the inclusion of constructed winds shows a positive impact on the objective analysis and improvement is seen to be more marked in the data-sparse region of the Arabian sea. Analyses which include the constructed winds show better agreement with the standard analysis, than the analyses obtained using only conventional winds. Thus, results of our study suggest that the wind profiles constructed using cloud motion vectors are of potential use in objective analysis to depict the major circulation features over the Indian region.     

基于WACCM+DART的临近空间SABER和MLS臭氧观测同化试验研究

本研究在WACCM+DART（Whole Atmosphere Community Climate Model,Data Assimilation Research Test-Bed）临近空间资料同化预报系统中加入SABER（Sounding of the Atmosphere using Broadband Emission Radiometry）和MLS（Microwave Limb Sounder）臭氧观测同化接口,并以2016年2月一次平流层爆发性增温（SSW）过程为模拟个例进行了SABER和MLS臭氧观测同化试验,得出以下结论:同化SABER和MLS臭氧体积浓度观测得出的WACCM+DART臭氧分析场能够较真实反映SSW期间北极上空平流层臭氧廓线随时间的演变特征,且与ERA5（Fifth Generation of ECMWF Reanalyses）再分析资料描述的臭氧变化特征具有很好的一致性;基于SABER和MLS臭氧观测的WACCM臭氧6 h预报检验表明同化臭氧观测对臭氧分析和预报误差的改善效果主要体现在南半球高纬平流层和北半球中高纬平流层中上层-中间层底部;基于ERA5再分析资料的WACCM+DART分析场检验表明同化SABER和MLS臭氧体积浓度资料可在提高北半球高纬地区上平流层-中间层底部臭氧场分析质量的同时减小该地区上平流层-中间层底部温度场和中间层底部纬向风场的分析误差;基于MLS臭氧资料的臭氧中期预报检验表明相对控制试验同化SABER和MLS臭氧体积浓度资料能更好改善0~5 d下平流层和中间层底部臭氧的预报效果。     

水物质对云雨区卫星微波观测模拟影响

受云和降水影响卫星资料在数值天气预报中的同化应用对于进一步改善数值预报效果具有重要作用, 这部分工作的开展要求快速辐射传输模式中能够较好地考虑各种水物质的辐射效应。使用美国卫星资料同化联合中心新近开发的快速辐射传输模式CRTM, 通过中尺度数值模式WRF的预报输出提供水物质输入, 分析水物质辐射效应对云雨区卫星微波观测模拟计算的影响。在WRF模式预报水物质的分布和天气系统配置合理并符合云物理基本特征的前提下, 水物质辐射效应的考虑极大改善了卫星观测模拟的效果。结合卫星各通道探测特性, 进一步分析各种水物质粒子对NOAA-16 AMSU A/B各通道卫星亮温模拟的影响和物理机理, 定量统计各类水物质对各卫星观测通道亮温计算偏差和偏差贡献的权重大小。分析结果表明:快速辐射传输模式中, 考虑水物质辐射效应为数值天气预报中云雨区卫星资料的同化应用提供了必需的基础条件。     

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。