Characteristics of Fengyun-4A Satellite Atmospheric Motion Vectors and Their Impacts on Data Assimilation

The high observation efficiency, scanning speed and observation frequency of the Fengyun-4A(FY-4A) satellite indicates the progress of Chinese geostationary meteorological satellites. The characteristics of FY-4A atmospheric motion vectors(AMVs) derived from the high-level water vapor(WV-High) channel, mid-level water vapor(WV-Mid) channel,and infrared(IR) channel of FY-4A are analyzed, and their corresponding observation errors estimated. Then, the impacts of single-channel and multi-channel FY...     

气象卫星风矢量BUFR编码

为了与国际接轨且满足气象卫星风矢量产品国际交流需求的不断增长,开发了WMO新模板的风矢量产品BUFR编码软件。编码过程中通过附加字段提供了质量控制信息,描述符由早期风矢量产品BUFR编码的18个激增至254个,BUFR报文提供的信息更加丰富。编码结果表明非压缩编码BUFR报文的长度是压缩编码BUFR报文的9倍;为了便于GTS传输,宜采用压缩格式BUFR编码。压缩格式的BUFR编码有较高的数据压缩率（约53%）,非常利于数据传输。     

Evaluation of Total Precipitable Water over East Asia from FY-3A/VIRR Infrared Radiances

Satellite retrieval of atmospheric water vapor is intended to further understand the role played by the energy and water cycle to determine the Earth's weather and climate. The algorithm for operational retrieval of total precipitable water (TPW) from the visible and infrared radiometer (VIRR) onboard Fengyun 3A (FY-3A) employs a split window technique for clear sky radiances over land and oceans during both day and night. The retrieved TPW is compared with that from the moderate resolution imaging spectroradiometer (MODIS) onboard the Terra satellite and data from radiosonde observations (RAOB). During the study period, comparisons show that the FY-3A TPW is in general agreement with the gradients and distributions from the Terra TPW. Their zonal mean difference over East Asia is smaller in the daytime than at night, and the main difference occurs in the complex terrain at mid latitude near 30°N. Compared with RAOB, the zonal FY-3A and the Terra TPW have a moist bias at low latitudes and a dry-bias at mid and high latitudes; in addition, the FY-3A TPW performs slightly better in zonal mean biases and the diurnal cycle. The temporal variation of the FY-3A and the Terra TPW generally fits the RAOB TPW with the FY-3A TPW. The FY-3A TPW is more accurate at night, while the Terra TPW is more accurate during the daytime. Comparisons of correlations, root mean square differences and standard deviations indicate that the FY-3A TPW series is more consistent with the RAOB TPW at selected stations. As a result, the FY-3A TPW has some advantages over East Asia in both spatial and temporal dimensions.     

Water vapor motion signal extraction from FY-2E longwave infrared window images for cloud-free regions: The temporal difference technique

The aim of this study is to calculate the low-level atmospheric motion vectors （AMVs） in clear areas with FY-2E IR2 window （11.59-12.79 μm） channel imagery,where the traditional cloud motion wind technique fails.A new tracer selection procedure,which we call the temporal difference technique,is demonstrated in this paper.This technique makes it possible to infer low-level wind by tracking features in the moisture pattern that appear as brightness temperature （TB） differences between consecutive sequences of 30-min-interval FY-2E IR2 images over cloud-free regions.The TB difference corresponding to a 10％ change in water vapor density is computed with the Moderate Resolution Atmospheric Transmission （MODTRAN4） radiative transfer model.The total contribution from each of the 10 layers is analyzed under four typical atmospheric conditions：tropical,midlatitude summer,U.S.standard,and midlatitude winter.The peak level of the water vapor weighting function for the four typical atmospheres is assigned as a specific height to the TB ＂wind＂.This technique is valid over cloudfree ocean areas.The proposed algorithm exhibits encouraging statistical results in terms of vector difference （VD）,speed bias （BIAS）,mean vector difference （MVD）,standard deviation （SD）,and root-mean-square error （RMSE）,when compared with the wind field of NCEP reanalysis data and rawinsonde observations.     

FY-2E卫星云导风定高误差及在同化中的应用

FY-2E气象卫星云导风产品观测误差较大的主要原因是高度指定存在较大误差。针对该问题,采用一维变分方法对云导风高度进行调整。统计分析表明:经高度调整后的FY-2E气象卫星云导风产品质量得到很大改善;采用新息向量法,选取零阶Bessel函数模型,在观测空间分离背景误差和观测误差方差得到云导风的观测误差。运用GRAPES全球模式进行数值模拟,结果表明:采用新的观测误差方案和经过高度调整后的云导风产品能提高数值模式在北半球的短期预报能力,高层的改进效果明显好于中低层。并根据云导风反演原理及算法,讨论了FY-2E气象卫星云导风高度指定系统性偏高的主要原因,以求进一步改善云导风产品的质量。     

FY-4A卫星云导风观测误差优化及同化效果影响研究

为了推进FY-4A卫星资料在数值模式中的实际应用,本研究选择云导风产品作为研究对象,首先统计了FY-4A高层水汽通道和红外通道云导风的观测误差,进一步基于WRFDA(Weather Research and Forecasting model Data Assimilation system)系统,利用默认观测误差和新...     

FY-2E卫星资料在基于LAPS的台风三维云分析中的应用

LAPS(Local Analysis and Prediction System)采用物理初值化与三维变分约束相结合的方法,通过融合多源观测资料,发挥各种资料的优势,分析得到较为客观的三维云场,并可改善数值模式初始场。将FY-2E卫星可见光反照率和红外亮温资料引入LAPS,针对2014年6月登陆我国的台风"海贝思",设计不同水平分辨率的同化试验,研究台风三维云结构和初始场的改善情况。结果表明:1)LAPS云分析中引入卫星可见光反照率资料之后,总云量有显著的调整,能够较清晰地分辨出台风眼区、云墙和螺旋云带,卫星红外亮温资料在云顶高度的调整中发挥了重要作用,而且高分辨率的云分析结果有助于更好地分析出台风结构和强对流区域。2)LAPS物理初值化技术将卫星资料中的云结构和微物理信息添加到初始场中,一定程度上调整了数值模式初始场中垂直速度、云水、云冰和水汽场等变量的分布,提高了模式初值质量,对模拟和预报台风系统将会产生一定的影响。     

基于CloudSat、FY-2E资料的中国海域及周边地区深对流和穿透性对流特征

深对流在地-气系统的物质和能量交换中起着至关重要的作用,伴随而来的暴雨、雷电、冰雹等天气会对人类社会产生影响。利用CloudSat/CALIPSO和FY-2E卫星观测数据,研究了中国海域及周边地区非穿透性对流（DCwo）及穿透性对流（CO）的海-陆分布、云顶红外亮温和云团特征（包括对流系统（CS）和对流单体（CC）的面积、活跃性对流比、偏心率、最低亮温、平均亮温梯度）。结果发现:穿透性对流比非穿透性对流的云顶红外亮温更低,垂直高度上的雷达反射率更高;从发生次数来看,非穿透性对流/穿透性对流在海洋比陆地多,低纬度比高纬度多,夏季比其他季节多,冬季海陆差异最大;从云顶亮温的分布来看,海洋比陆地、穿透性对流比非穿透性对流集中分布区间的亮温值更低,穿透性对流的分布区间比非穿透性对流集中;从云团特征来看,对流系统/对流单体的发生频率随面积的增大而降低,穿透性对流比非穿透性对流、海洋比陆地更容易出现较大面积的对流系统/对流单体,海洋穿透性对流的活跃性对流比相对较高;偏心率在0.5以上的发生频率较高,对流系统形状更偏向于圆形,在海洋上更加明显;穿透性对流在海陆上的最低亮温集中分布区间为190-195 K,比非穿透性对流的分布更集中,平均亮温梯度在0.1 K/km以下的发生频率较高。      

利用FY-2E红外和水汽波段对强对流云团的识别和演变研究

使用FY-2E静止气象卫星的红外1(10.3~11.3μm)和水汽波段(6.3~7.6μm)时序图像,对强对流云进行识别和短时预测。亮温阈值法是将强对流云和其他高云区分开的常用方法,但是合适的亮温阈值是随着时间和空间而变化的,过高的阈值会将许多卷云包括进来,太低的阈值会排除掉云顶发展还不是很高的强对流云。水汽波段所在的位置是水汽的一个强吸收带,而高度在400 h Pa上下的大气层是水汽波段的一个强吸收层,大气在垂直方向上的对水汽波段辐射吸收的分布模式使得卫星接收到的水汽波段辐射主要来自于400 h Pa以上的大气中高层,而卫星接收到的红外波段辐射主要来自于大气中低层,两个波段间辐射来源的差异使得不同光学厚度的高云的辐射观测值在红外—水汽光谱空间中的分布具有明显差别,并且这种差异具有时空的稳定性。本文将一定范围内的云团的象元测值在红外—水汽光谱空间中的分布的拟合直线斜率作为强对流云识别的依据,结果表明相对于亮温阈值法,本文的识别方法不仅能够较好地区别卷云和强对流云,同时也能更有效地识别未达到旺盛阶段的对流云。在对强对流云进行识别后,根据相邻时间段的卫星图像,利用交叉相关法反演得到强对流云团顶部的位移矢量场,并根据后向轨迹法对强对流云团位置形状进行短时预测,预报结果在短时间内(0~1 h)较好,并且对面积较大的云团的预报效果要优于较小的对流云团。此外文中还利用逐半小时的云顶黑体温度(Temperature of Black Body,TBB)资料分析了云顶亮温的分布变化,得到了整个强对流过程的演变特征。     

FY-2C云迹风资料同化应用对台风预报的影响试验研究

针对0505号台风“海棠”, 采用WRF区域中尺度模式进行控制试验和两个同化试验, 利用WRF-3DVAR同化系统同化FY-2C红外和水汽两个通道云迹风反演产品, 同化分云迹风经质量控制和未经质量控制两组同化试验。通过三组试验分析云迹风资料对降水和风场等的预报结果的影响, 并进行24小时降水量分级Ts评分检验以及风场点对点检验。结果表明: 同化经质量控制云迹风资料可以提高降水落区和强度预报的准确度, 不同等级的Ts评分较其它试验都有较明显改进; 风场预报模拟也有所改善。增加两例台风, 使用与“海棠” 相似的处理方法进行模拟试验, 并对模拟结果24小时降水分析与检验, 得到与“海棠”类似结论。因此, 经过合理性选择的云迹风资料的加入, 有利于补充初始场中可能未包含的中尺度信息, 从而提高试验中对于降水、风场等的模拟效果, 提高WRF模式的模拟预报能力。     

Influence of HITRAN Database Updates on Retrievals of Atmospheric CO2 from Near-Infrared Spectra

The line-transition parameters of the High Resolution Transmission (HITRAN) 2008 database have been updated relative to previous editions. The transmission spectra and sensitivity to changes in CO2 concentrations using line parameters from the HITRAN 2004 and HITRAN 2008 databases are compared to evaluate the effect of the database updates on retrievals of carbon dioxide vertical columns from nearinfrared reflected sunlight. This comparison is done in three spectral regions covering the 2.06-, 1.61-, and 1.58-μm CO2bands used by the Greenhouse Gases Observatory Satellite (GOSAT) instrument and the planned successor to the Orbiting Carbon Observatory (OCO). The updates to the HITRAN database have the largest effects on the transmittance and the off-line to on-line transmittance ratio in the 2.06-μm region and the smallest effects on these parameters in the 1.58-μm region. The influence of the updates to the HITRAN database on the off-line to on-line ratio calculation in the narrow spectral region 4855-4880 cm-1 could be equivalent to a change in CO2 of more than 50 ppmv. Use of the HITRAN 2004 database will lead to an underestimate of the column CO2abundance in the 2.06- and 1.61-μm spectral regions, whereas it will lead to an overestimate of the column CO2abundance in the 1.58-μm spectral region.