GPS折射率资料在梅雨锋暴雨数值模拟中的应用

运用WRF三维变分同化系统同化GPS掩星折射率资料,并应用到2007年7月4—6日梅雨锋暴雨个例中进行数值模拟试验,以此考察GPS掩星折射率资料在梅雨锋暴雨数值模拟中的应用。同化结果表明：GPS掩星折射率资料对初始资料的调整主要是中低层湿度场,对于温度场和高度场的调整都是从底层到高层逐渐增大;加入GPS掩星折射率资料对降水预报有所改进,这与中低层湿度场的初始调整有关系;从对模拟结果进行诊断和结构分析中可以发现负散度增量和正涡度增量与降水中心和区域有很好的对应,同化资料之后对于各降水中心地区增强了产生降水的动力条件。     

一次降水过程的GPS可降水量资料同化试验

选取2005年7月23—24日北京、天津、河北地区的一次强降水过程,利用MM5模式进行数值模拟试验和GPS可降水量资料的伴随同化试验。为了检验GPS可降水量资料对模式湿度场的改善程度和伴随同化效果,采用24h降水TS评分、模拟湿度场与真实场的均方差和实况降水等检验方法,通过温度场、高度场和风场的均方差试验,结果证明加入GPS可降水量资料在改善初始湿度场的同时对初始温度场、高度场和风场也有不同程度的改善。     

大气红外探测器(AIRS)温、湿度反演产品的有效性检验及在数值模式中的应用研究

利用中国540个地面气象观测站点资料,对1和7月大气红外探测器(AIRS)的反演中国区域地面气温精度做了详细评估,分析了产生误差的原因。同时把AIRS的反演温、湿度廓线产品与T213数值预报产品进行比较,分析了它们之间的差异。为进一步考察AIRS温、湿度产品的有效性,我们把经过订正的AIRS地面气温以及温、湿度廓线产品分析同化到中尺度模式MM5中,用于华北降雪天气过程的对比模拟试验,分析AIRS反演产品对降雪量、水汽场、垂直速度场、散度场以及云物理过程等的影响。     

可降水量同化对初始湿度场调整的应用研究

设计了一个三维变分同化方案,利用非静力中尺度模式MM5和由实况观测反演得到的可降水量资料,运用该变分同化方法改善初始湿度场,并对2003年7月9～10日的暴雨过程进行数值模拟对比试验.结果表明,①可降水量资料的变分同化对初始湿度场具有较强的调整能力;②同化可降水量后,可以明显地改善模式初始湿度场,能够有效地提高降水模拟的准确率.     

降水量的直接同化对初始场的影响

四维变分法用严格的数学方法、合乎逻辑的物理过程根据观测资料和模式本身来获得一个最优的初始场,是当前最先进的四维资料同化方法之一.作者用四维变分法对自动站降水量作直接同化,对初始场增量进行了分析.结果表明降水量的同化对初始场中热力性质的量影响相对较大,对低层的影响大于高层,大部分增量在925 hPa至850 hPa层间达最大.通过同化,北京地区对流不稳定性明显增加.对风场的增量分析表明,同化增加了一些中尺度信息.对于散度场和水汽通量散度场,同化有使低层辐合加强的趋势.通过同化,在MM5初始场上增加了原先没有     

数值天气预报业务模式现状与展望

基于新疆区域同化预报系统（简称“DOGRAFS”）,选取新疆伊犁河谷地区2016年7月31日—8月1日的强降水过程,利用常规观测资料和卫星微波辐射资料进行同化敏感试验,其中控制试验仅同化常规地面和探空资料,敏感试验在常规观测基础上分别增加微波温度（AMSU-A）、湿度（MHS）和温、湿度（AMSU-A、MHS）资料,并对2016年7月进行连续试验,以初步探究卫星微波温、湿度资料同化对新疆降水预报的影响。从关键要素增量的垂直和水平分布来看,仅同化AMSU-A资料与同时同化AMSU-A和MHS资料对初始场温度、位势高度和湿度的调整均比较显著,其低层温度和位势高度为正增量,中、高层为负增量,湿度场增量中心集中在800—600 hPa。而仅同化MHS资料对温度和位势高度的影响较小,对湿度场有所“微调”,但可更好地修正补充降水过程中的水汽信息。从降水预报和客观检验结果来看,同化AMSU-A资料总体为负效果;而同化MHS资料对于整个降水落区和大阈值降水的预报均有明显优势。

     

青藏高原新增探空资料同化对南疆夏季降水预报的影响

利用第三次青藏高原大气科学试验中青藏高原西部新增3个探空站(狮泉河、申扎、改则)的探空资料,基于中尺度数值(WRF)模式和GSI同化系统,选取2015年夏季南疆两次不同类型(南亚高压双体型和单体型)的强降水过程进行同化敏感试验,以初步评估新增3个站探空资料同化对南疆夏季降水预报的影响。从初始场物理量的增量场来看,同化高原3个站探空资料对两次过程的初始场均有一定改进,对南亚双体型过程的改进较显著,这可能与其偏南气流及上下游效应较强有关。中、高层物理量的增量中心均出现在高原中、西部,分别对应申扎和狮泉河两站,并向周边地区逐渐减小,南疆地区表现为弱的正或负增量。虽然高原探空资料均在600 h Pa以上,通过动力调整对低层物理量也有一定影响。同化后低层的散度和湿度增量中心出现在高原西南侧,南疆地区变化较小。随着模式时间积分,各高度上的物理量和降水影响系统调整效果逐渐显著,总体使得200 h Pa副热带长波槽有所加深、南疆上空的偏南急流得到加强,500 h Pa低值系统强度有所减弱,850 h Pa的散度和湿度在南疆地区均有显著调整,但低层散度和湿度在南疆西部强降水中心调整相对较小。从降水预报结果来看,同化高原3个站探空资料后,对两次过程的小量级降水评分显著提高,即对降水落区预报能力有所提高;但对强降水中心结果影响不大,即对局地性强降水的预报能力仍有所欠缺。     

两种背景场同化雷达资料对辽宁省一次暴雨预报的影响

针对2013年8月15—16日先后在辽宁省锦州和抚顺地区发生的特大暴雨,分别以T639和NCEP预报场作为背景场,利用中尺度数值模式WRF(Weather Research and Forecasting Model)和ADAS(ARPS Data Analysis System)同化系统进行了同化多普勒雷达观测资料的试验,检验同化雷达资料和采用不同背景场对暴雨预报的影响。结果表明:(1)同化雷达资料前,使用两种背景场的预报结果对锦州的强降水均出现漏报,同化雷达资料后,均预报出了锦州黑山一带的强降水,而12~24 h预报结果中对位于抚顺地区强降水预报的改善不大,采用T639较NCEP预报作为背景场对抚顺地区强降水的预报更好;(2)ADAS同化雷达资料后对模式初始湿度场的改善较大,700 h Pa和850 h Pa比湿有明显的增量。同时,同化雷达资料后更新了模式初始场中的水物质,水物质增量位置和强降水发生位置有较好的对应关系;(3)通过分析模式预报的风场,回波和水汽通量散度发现,同化试验预报初期在锦州和阜新一带预报出了强度较强且深厚的水汽场,低层西南暖湿气流和高层西北干冷气流的配置在锦州地区水汽区域的左侧激发了强烈的上升辐合运动,而其右侧伴有强烈的辐散是导致锦州黑山强降水爆发的主要原因。     

可降水量资料反演及在暴雨数值模拟中的初步应用

通过同化可降水资料改善模式初始湿度场从而提高暴雨模拟与预报效果。首先应用适时回归方法反演大气可降水量资料，然后以1998年6月18—19日暴雨模拟为例，采用变分同化方法研究了可降水量资料在暴雨数值模拟中的作用。数值模拟结果表明：1)MM5模式中同化可降水量资料后，对于雨带位置的模拟效果起到很大的改善；亦可改进暴雨降水强度的模拟效果，改进程度与降水参数化方案有关。2)同化可降水量资料后，明显改善初始湿度场，在一定程度上缓解旋转加强(spin up)问题，从而有效地提高降水模拟效果。3)降水模拟对参数化方案的选取同样敏感，改进初始湿度场的同时应该选择相应的降水参数化方案。     

多普勒天气雷达资料同化对冬季暴雨模拟的影响研究

采用基于本征正交分解的四维集合变分同化（POD-4DEnVar）方法,利用梅州站的多普勒天气雷达资料和NCEP资料,对2015年12月9日一次华南冬季暴雨过程进行同化试验,探讨了同化不同的雷达观测要素对暴雨模拟的影响。结果表明:同化多普勒天气雷达资料有利于削弱控制试验偏强降水的模拟结果,改善降水分布结构;同化不同的雷达观测要素得到的模拟结果不同,同时同化径向风和反射率的降水模拟结果最好。同化试验对降水模拟结果的改善主要通过调整初始时刻的风场和水汽条件来实现,一方面减弱偏南风和偏东风在暴雨区的辐合,阻碍海上暖湿气流对暴雨区的水汽输送,另一方面直接削弱暴雨区的水汽条件,大幅降低水汽混合比。同化试验相对于控制试验的同化增量远大于不同雷达观测要素的同化试验之间的分析场差异,这表明同化不同的雷达观测要素对初始风场和水汽条件的调整呈现类似的特征。虽然同化试验的初始场存在较小的差异,但随着模式积分,16 h后模拟降水出现了明显差异。分析同化试验之间的初始偏差演变发现,850~700 hPa的平均垂直速度偏差和雨水混合比偏差在模式积分至16 h开始急剧增长,这种变量偏差的急剧增长与逐时降水偏差的迅速增加一致,是降水偏差增长的直接原因。另外,这两个变量偏差的增大,也伴随着偏差能量的增大,变量偏差增长最明显的时段为偏差能量增幅最大的时段,且偏差能量迅速增长早于变量偏差和降水偏差的迅速增长,变量偏差增长最明显的区域为偏差能量梯度较大的区域。     

The impact of AIRS atmospheric temperature and moisture profiles on hurricane forecasts: Ike (2008) and Irene (2011)

Atmospheric Infra Red Sounder(AIRS) measurements are a valuable supplement to current observational data, especially over the oceans where conventional data are sparse. In this study, two types of AIRS-retrieved temperature and moisture profiles, the AIRS Science Team product(Sci Sup) and the single field-of-view(SFOV) research product, were evaluated with European Centre for Medium-Range Weather Forecasts(ECMWF) analysis data over the Atlantic Ocean during Hurricane Ike(2008) and Hurricane Irene(2011). The evaluation results showed that both types of AIRS profiles agreed well with the ECMWF analysis, especially between 200 h Pa and 700 h Pa. The average standard deviation of both temperature profiles was approximately 1 K under 200 h Pa, where the mean AIRS temperature profile from the AIRS Sci Sup retrievals was slightly colder than that from the AIRS SFOV retrievals. The mean Sci Sup moisture profile was slightly drier than that from the SFOV in the mid troposphere. A series of data assimilation and forecast experiments was then conducted with the Advanced Research version of the Weather Research and Forecasting(WRF) model and its three-dimensional variational(3DVAR) data assimilation system for hurricanes Ike and Irene. The results showed an improvement in the hurricane track due to the assimilation of AIRS clear-sky temperature profiles in the hurricane environment. In terms of total precipitable water and rainfall forecasts, the hurricane moisture environment was found to be affected by the AIRS sounding assimilation.Meanwhile, improving hurricane intensity forecasts through assimilating AIRS profiles remains a challenge for further study.     

Atmospheric profile retrieval with AIRS data and validation at the ARM CART site

The physical retrieval algorithm of atmospheric temperature and moisture distribution from the Atmospheric InfraRed Sounder （AIRS） radiances is presented. The retrieval algorithm is applied to AIRS clear-sky radiance measurements. The algorithm employs a statistical retrieval followed by a subsequent nonlinear physical retrieval. The regression coefficients for the statistical retrieval are derived from a dataset of global radiosonde observations （RAOBs） comprising atmospheric temperature, moisture, and ozone profiles. Evaluation of the retrieved profiles is performed by a comparison with RAOBs from the Atmospheric Radiation Measurement （ARM） Program Cloud And Radiation Testbed （CART） in Oklahoma, U. S. A.. Comparisons show that the physically-based AIRS retrievals agree with the RAOBs from the ARM CART site with a Root Mean Square Error （RMSE） of 1K on average for temperature profiles above 850 hPa, and approximately 10% on average for relative humidity profiles. With its improved spectral resolution, AIRS depicts more detailed structure than the current Geostationary Operational Environmental Satellite （GOES） sounder when comparing AIRS sounding retrievals with the operational GOES sounding products.     

ATOVS资料同化方案对暴雨模拟效果的影响

本文利用WRF 模式及其3DVar 同化系统,以2009 年6 月29 日00 时到30 日00 时的湖北鹤峰暴雨为研究个例,对ATOVS 探测器的AMSU-A、AMSU-B 和HIRS 三类资料进行了不同的同化方案试验。结果表明:同化ATOVS 三类资料对暴雨模拟的影响不同,HIRS 资料对暴雨模拟效果改进最大,AMSU-B 次之,AMSU-A 最小。同时同化ATOVS 三类资料时,AMSU-A 资料起主要作用,其同化效果与同时同化ATOVS 三类资料相近,优化组合同化AMSU-B 和HIRS 资料的效果最好。同化ATOVS 不同资料对初始要素场的影响不同,AMSU-A 资料主要影响大气温度场,AMSU-B 资料对中高空要素场的影响较大,HIRS 资料对低空湿度场及风场的协同改变最有利于降水模拟的改善。同时ATOVS 资料的稀疏分辨率也是影响同化效果的一个因子,在模式分辨率不变时,同化资料稀疏分辨率可能存在最佳选择。     

Improved Analyses and Forecasts With AIRS Temperature Retrievals Using the Local Ensemble Transform Kalman Filter

In this paper we investigate the impact of the Atmospheric Infra-Red Sounder (AIRS) temperature retrievals on data assimilation and the resulting forecasts using the four-dimensional Local Ensemble Transform Kalman Filter (LETKF) data assimilation scheme and a reduced resolution version of the NCEP Global Forecast System (GFS). Our results indicate that the AIRS temperature retrievals have a significant and consistent positive impact in the Southern Hemispheric extratropics on both analyses and forecasts, which is found not only in the temperature field but also in other variables. In tropics and the Northern Hemispheric extratropics these impacts are smaller, but are still generally positive or neutral.     

Simulation of heavy precipitation over Santacruz, Mumbai on 26 July 2005, using Mesoscale model

Summary An attempt has been made to simulate the unprecedented heavy precipitation of 94.4 cm in a day over Santacruz, Mumbai during 0300 UTC 26 July to 0300 UTC 27 July 2005. Three experiments have been conducted using Advanced Regional Prediction System model developed by Center for Analysis and Prediction of Storms of Oklahoma University, USA. In first experiment the model input at large domain size has been obtained using NCEP/NCAR reanalysis data at 2.5° × 2.5° lat.–lon. resolution. In other two experiments model input at large as well as at small domain sizes, have been obtained from NCEP/NCAR FNL data of 1° × 1° lat.–lon. resolution. In all three experiments model’s horizontal resolution is 40 km and integration period is 30 hours from 0000 UTC 26 July 2005. Based on the temporal distribution of observed rainfall rates it is considered that the rainfall of 38.1 cm during 0900–1200 UTC on 26 July could be due to cloud burst phenomenon and 56.3 cm from 1200 UTC of 26 July to 0300 UTC of 27 July has been due to continuous regeneration of thunderstorm activity under influence of mesoscale cloud complex. It is found that model forecast of rainfall in first experiment was qualitatively as well as quantitatively very poor. Among other two, experiment with large domain size has predicted better rainfall values and location compared to the experiment with small domain size. The larger domain has produced rainfall of 41 cm as against observed rain rate of 56.3 cm. during 1200 UTC of 26 July to 0300 UTC of 27 July. Divergence, vorticity, vertical velocity and moisture parameters are examined in relation with the various stages of the event. The maximum values of convergence, vorticity and moisture fluxes precede the initial phase of mature stage, however vertical velocity follows the later phase of mature stage. Vorticity budget over the location of maximum rainfall, revealed the significant role of tilting term in maintenance and dissipation of the cloud complex responsible for the event. The model has simulated mixing ratios of ice, snow and hail up to height of 15 km which matches with the observations that clouds reaching up to 15 km were present at the time of event of heavy precipitation.     

全球大气环流模式BCC_AGCM2.0.1对1998年夏季江淮流域强降水过程的回报试验研究

利用中国气象局北京气候中心全球大气环流模式(BCC_AGCM2.0.1) 对1998年6月24日～7月3日发生在我国江淮流域的强降水天气过程进行了回报试验。模式起报时间为1998年6月24日00时, 使用前10天NCEP-II再分析逐时温度、涡度和散度场进行预报前初始协调 (spin-up) 积分, 产生模式初值, 预报时段为1998年6月24日～7月10日, 回报试验结果表明: 模式对全球500 hPa位势高度的天气尺度演变过程具有4～7天的可预报性; BCC_AGCM2.0.1模式对中国区域的降水以及大气环流场具有3～4天的可预报性, 6月24日起报后3天内的预报降水区域位置与实况一致, 但中心强度有所差异。对起报后未来2天的5 mm和10 mm以上的降水预报能力相对较强, ETS评分值达到了0.25以上, HK评分超过了0.4, 降水区域范围预报较为准确, BIA评分趋于1.0。模式对20 mm以上的降水也具有一定的可预报性, 但模式对大于30 mm以上强降水的预报能力较差。     

Application of ATOVS microwave radiance assimilation to rainfall prediction in Summer 2004

Experiments are performed in this paper to understand the influence of satellite radiance data on the initial field of a numerical prediction system and rainfall prediction. First, Advanced Microwave Sounder Unit A （AMSU-A） and Unit B （AMSU-B） radiance data are directly used by three-dimensional variational data assimilation to improve the background field of the numerical model. Then, the detailed effect of the radiance data on the background field is analyzed. Secondly, the background field, which is formed by application of Advanced Television and Infrared Observation Satellite Operational Vertical Sounder （ATOVS） microwave radiance assimilation, is employed to simulate some heavy rainfall cases. The experiment results show that the assimilation of AMSU-A （B） microwave radiance data has a certain impact on the geopotential height, temperature, relative humidity and flow fields. And the impacts on the background field are mostly similar in the different months in summer. The heavy rainfall experiments reveal that the application of AMSU-A （B） microwave radiance data can improve the rainfall prediction significantly. In particular, the AMSU-A radiance data can significantly enhance the prediction of rainfall above 10 mm within 48 h, and the AMSU-B radiance data can improve the prediction of rainfall above 50 mm within 24 h. The present study confirms that the direct assimilation of satellite radiance data is an effective way to improve the prediction of heavy rainfall in the summer in China.     

Validation of the Atmospheric Infrared Sounder Retrieval Products over China and Their Application in Numerical Model

The atmospheric infrared sounder (AIRS) instrument onboard Aqua Satellite is a high spectral resolution infrared sounder. In recent years, AIRS has gradually become the primary method of atmospheric vertical observations. To examine the validation of AIRS retrieval products (V3.0) over China, the AIRS surface air temperature retrievals were compared with the ground observations obtained from 540 meteorological stations in July 2004 and January 2005, respectively. The sources of errors were considerably discussed. Based on the error analysis, the AIRS retrieved surface air temperature products were systemi-cally corrected. Moreover, the AIRS temperature and humidity profile retrievals were compared with T213 numerical forecasting products. Because T213 forecasting products are not the actual atmospheric states, to further verify the validation, the AIRS temperature and humidity profile products were assimilated into the MM5 model through the analysis nudging. In this paper, the case on February 14, 2005 in North China was simulated in detail. Then, we investigated the effects of AIRS retrievals on snowfall, humidity field, vertical velocity field, divergence field, and cloud microphysical processes. The major results are: (1) the errors of AIRS retrieved surface air temperature products are largely systematic deviations, for which the influences of terrain altitude and surface types are the major reasons; (2) the differences between the AIRS atmospheric profile retrievals and T213 numerical prediction products in temperature are generally less than 2 K, the differences in relative humidity are generally less than 25%; and (3) the AIRS temperature and humidity retrieval products can adjust the model initial field, and thus can improve the capacity of snowfall simulation to some extent.