FY-3B/VIRR海表温度算法改进及精度评估

该文介绍了卫星观测海表温度 (SST) 算法的发展历程,给出了所用SST算法的回归模型,并在FY-3B/VIRR业务SST算法的基础上进行了改进。基于NOAA-19/AVHRR匹配数据集,进行多算法建模分析及精度评估,白天最优算法为非线性SST (NL) 算法,夜间最优算法为三通道SST (TC) 算法,最优算法的确定与NESDIS/STAR一致。建立2012年8月—2013年3月FY-3B/VIRR匹配数据集,并在此基础上进行多算法回归建模及精度评估,白天和夜间的最优均为NL算法,分析发现夜间TC算法采用匹配数据集版本2(MDB_V2) 时,3.7 μm通道存在类似百叶窗的条带现象。以2012年10—12月FY-3B/VIRR匹配数据集计算回归系数,以2013年1—3月独立样本进行精度评估,与浮标SST相比,NL算法白天和夜间的均方根误差分别为0.41℃和0.43℃。与日平均最优插值海温 (OISST) 相比,NL算法白天和夜间的均方根误差分别为1.45℃和1.5℃; 选择与OISST偏差在2℃以内的样本,NL算法白天和夜间均方根误差分别为0.82℃和0.84℃。     

基于非线性算法的FY 3A/VIRR SST反演

利用非线性算法实现了FY-3A/VIRR数据的海洋表面温度SST产品的反演.对2010年的全球船舶站观测数据和FY-3A/VIRR数据建立匹配数据集,选择单月的匹配数据采用多元回归模型计算得到了适用于FY-3A/VIRR数据的非线性海表温度反演算法NLSST的系数,能够实现FY-3A/VIRR数据的高精度SST产品反演.并利用独立于反演算法的双月匹配数据采用最小绝对偏差方法通过线性模型对SST算法的精度进行检验,结果显示白天和夜间的偏差分别为0.05℃和-0.05℃,绝对偏差在0.50℃以下,标准偏差在0.65℃以下.通过文中实现的算法反演了VIRR数据的SST产品,并和MODIS的官方产品进行比较,结果显示两种SST产品具有很高的一致性.     

基于FY-3C微波辐射成像仪海表温度产品的偏差订正方法研究

提出一种针对FY-3C搭载的微波辐射成像仪（MWRI）海表温度产品的分段回归偏差订正方法,该方法通过引进气候态海表温度数据,建立与关联实测海表温度相匹配的回归模型,并通过对模型中关联变量的误差分析,选择最优样本进行分段回归,以实现对海表温度数据的重新估计。通过对MWRI海表温度数据的偏差订正试验表明,采用分段回归方法获得的订正结果无论在误差指标的空间分布还是时间序列上,都要明显优于采用传统概率密度函数偏差订正方法的结果。其中,采用概率密度函数方法订正后的海表温度产品误差标准差和均方根误差从订正前的0.9—1.0℃,减小到0.8℃左右,而采用分段回归方法获得相应的订正误差仅为0.6℃左右,订正效果有明显改善。      

FY3A/VIRR海面温度业务产品算法改进与质量检验

针对FY3A/VIRR海面温度(SST)业务产品温度偏低的现状,进行误差原因分析,并对SST产品算法进行了如下改进:采用精度优先原则,以尽可能大的SST覆盖度提高SST反演精度;针对业务SST云污染的现状,构建3×3数据块,并在此基础上进行了SST空间一致性检验;引入气候阈值检验,以进一步剔除异常值。改进后的SST产品,全球日平均SST的覆盖度有所降低,但SST的一致性提高了;算法改进前后全球月平均SST覆盖度基本一致,但改进后云污染的现象得到了抑制。利用分析场日平均OISST对改进后的FY3ASST进行了质量检验,在南北纬70°之间的海域,FY3ASST的全局精度为-0.23±1.74℃,负的偏差说明云和气溶胶的影响仍然存在。改进后的FY3ASST 1.74℃的均方根误差与FY3A VIRR 11μm通道1.6K的定标精度量级相当。     

从GTS获得的海洋温、盐资料在BCC海洋同化系统中的质量控制及同化结果初步分析

介绍了从全球电信系统(GTS)上获得的海洋温度、盐度观测资料在中国国家气候中心(BCC)新一代海洋同化系统中的应用情况。通过资料的质量控制判断温、盐观测的重复记录、观测深度、地形、极端值、气候变率、层结、空间差异,有效地过滤了错误的或不可靠的观测信息。质量控制后,将温、盐观测资料加入同化系统,有效地改进了模块化全球海洋环流模式MOM4中的全球热带、副热带海洋,尤其是太平洋地区的多年平均海表温度、盐度场分布特征;此外,同化温、盐资料对南北半球中纬度地区的海表温度分布特征也有明显的改进。对比同化前后的均方根误差(RMSE)发现,同化后大部分海区,尤其是热带海洋的海表温度/盐度的均方根误差明显降低,降幅通常在0.1—1.0℃/psu,模拟与观测的海表温、盐分布特征也更为接近。进一步分析指出,同化明显地改善了模式对Nino3、Nino4区海温时间演变特征的模拟,同化后的Nino3海温与最优插值海表温度的差异减小,但其通常在上半年改进较多(差值绝对值多在0.5℃左右),而在下半年则改进较少(差值绝对值常达1℃左右);Nino4区的海温特征则改进明显,其与最优插值海表温度的差值绝对值通常都控制在0.5℃以下。     

FGOALS耦合模式对赤道太平洋海温和降水年循环的模拟评估

本文评估了中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室（LASG/IAP）研发的全球气候系统模式（FGOALS）的4个版本（FGOALS-g2、s2、g3、f3-L）对赤道太平洋地区的海温、降水气候态和季节循环的模拟能力。本文从海气耦合机制和热量收支的角度对耦合模式结果和相应的大气模式比较计划试验（AMIP）进行了对比分析,探讨了造成这一地区海温和降水模拟偏差的原因。结果显示,上一代模式g2和s2的海表温度均方根误差大于2°C,新一代模式g3和f3-L模拟的均方根误差降低50%,为1°C左右。因为新版本中赤道太平洋地区的净短波辐射平均态误差的减小,海洋上层热量动力输送过程的改善和净短波辐射与海温回归关系改进,赤道太平洋地区海温的平均态,南北温度和降水的不对称性都更加接近观测。f3-L比g3在上述方面改进更多,海温也更加合理。但是新一代版本模拟的降水均没有显著改进,赤道北侧ITCZ的降水偏大4 mm d?1。对流降水带来的凝结潜热释放加强了南北非绝热加热梯度,越赤道南风偏差抵消了一部分因为短波辐射偏大带来的海温偏暖,这说明海温平均态的改善是模拟误差相互抵消的结果。在季节循环的模拟方面也存在类似的现象,f3-L和g3中的海温年循环有所改进但较观测振幅仍旧偏弱。这是因为f3-L和g3模拟的经向风和潜热的年循环振幅比前版本要偏强,误差加大的同时也更大地抵消短波辐射的年循环偏差。g2和s2模拟的海温在赤道东太平洋则存在一个虚假半年循环分量,这主要是由潜热通量半年循环偏差所引起的。     

国家自然科学基金委员会地球科学部南京信息工程大学大气资料服务中心资料通讯

第10卷第2期（总第34期）2011年8月全球海表温度（SST）数据集简介本期介绍大气资料服务中心目前存放的3套全球海表温度（sea surface tem perature,简称SST）资料,分别是NOAA最优差值海表温度数据集、NOAA延长重建的海表温度数据集以及MODIS海表温度温度数据集。     

北太平洋海温与次年盛夏副热带高压的遥相关响应

选取1952-2005年北太平洋月平均海表温度（SST）资料，经过奇异值分解分析表明：6月份日界线附近西风漂流区的海温集中了北太平洋海温场的主要信息，西风漂流区与赤道冷水区的海温存在遥相关震荡，并且在6月份达到全年的最高值，11月份其振幅出现次高值。6月西风漂流区的海温（SST）可视为来年盛夏（7-8月）西太平洋副热带高压的强弱变化的信号：当6月份西风漂流区的海温（SST）偏低，则来年盛夏西太平洋副热带高压偏强；反之，则来年盛夏西太平洋副热带高压偏弱。     

GPS探测与FY-2反演大气可降水量对比分析

为深入了解FY-2卫星大气可降水量(PW)的反演质量,文章选取2012和2015年地基GPS水汽观测数据,与FY-2的PW反演产品进行了对比分析。结果表明:(1)北京、武汉和海口三站GPS/PW(PW_(GPS))与FY-2/PW(PW_(FY-2))在夏季存在显著正相关,三站的相关系数都达到0.67以上,夏季PW的均方根误差值、月平均偏差绝对值均小于冬季。北京与武汉站PW平均偏差和均方根误差在四季均具有明显日变化特征;(2)当PW_(GPS)20 mm时,北京、武汉、海口和拉萨站FY-2/PW与GPS/PW比较一致,PW偏差均值的绝对值和均方根误差较小,当PW_(GPS)20 mm时,PW偏差均值绝对值和均方根误差随PW_(GPS)值减小而迅速变大。FY-2的PW产品在夏季可以为大部分区域提供高时空分辨率、高精度的大气可降水量,在大气湿度非常低、冬季和夜间条件,反演结果精度有待提高。     

参数化次表层上卷海温改进ENSO模拟

通过参数化次表层上卷海温改进了一个热带太平海洋模式的SSTA模拟.这种参数化方案通过经验方法将海洋上混合层底部海温变化与海表面起伏联系起来,从而可以方便地利用模式模拟的海表起伏描述温跃层的变化情况及其对混合层海温变化的影响.三组数值试验表明通过上述方法显著改善了SST年际变化的模拟,与观测相比,在赤道东太平洋及南美沿岸,距平相关系数由原来的0.7左右提高到0.8以上,均方根误差在赤道东太平洋由原来0.8℃降到0.6℃,在南美沿岸由1.3℃以上降为0.9℃.这表明在赤道东太平洋及南美沿岸,温跃层的变化通过夹卷过程及垂直扩散过程可以显著影响混合层的温度,OGCM对这些过程描述不足是导致SST年际变化模拟偏弱的一个重要原因,通过强调这些过程可以改善模拟效果.同时在热带西太平洋的改进也是显著的.     

Characteristics of sea surface temperature retrieved from MTSAT-1R and in-situ data

Multi-channel sea surface temperature (MCSST) data were retrieved from the Japanese geostationary satellite, MTSAT-1R, for East Asia in western North Pacific. The coefficients used to calculate the MCSST data were estimated by assuming a linear relationship between the brightness temperatures obtained from the satellite and the in-situ buoy SST. It is important to remove cloud contamination pixels to retrieve meaningful information from infrared data. Therefore, the cloud detection algorithm was improved by using a 10-day maximum or minimum composite map for infrared and visible channels. The RMSE of the MCSST in comparison with the two-year buoy SST was about 0.89oC. The error was the largest at mid-latitudes in summer. Additionally, the error between the two SSTs showed that diurnal variation had a positive bias during daytime and a negative bias during nighttime. Furthermore, in 2007, both SSTs showed seasonal and spatial diurnal variation. The magnitude of the daily variation in the MCSST was two times larger than that in the buoy SST, and this was attributed to diurnal heating with a weak surface wind speed.     

Derivation of Regression Coefficients for Sea Surface Temperature Retrieval over East Asia

Among the regression-based algorithms for deriving SST from satellite measurements, regionally optimized algorithms normally perform better than the corresponding global algorithm. In this paper,three algorithms are considered for SST retrieval over the East Asia region (15°-55°N, 105°-170°E),including the multi-channel algorithm (MCSST), the quadratic algorithm (QSST), and the Pathfinder algorithm (PFSST). All algorithms are derived and validated using collocated buoy and Geostationary Meteorological Satellite (GMS-5) observations from 1997 to 2001. An important part of the derivation and validation of the algorithms is the quality control procedure for the buoy SST data and an improved cloud screening method for the satellite brightness temperature measurements. The regionally optimized MCSST algorithm shows an overall improvement over the global algorithm, removing the bias of about -0.13℃ and reducing the root-mean-square difference (rmsd) from 1.36℃ to 1.26℃. The QSST is only slightly better than the MCSST. For both algorithms, a seasonal dependence of the remaining error statistics is still evident. The Pathfinder approach for deriving a season-specific set of coefficients, one for August to October and one for the rest of the year, provides the smallest rmsd overall that is also stable over time.     

FY-3A陆表温度反演及高温天气过程动态监测

采用FY-3A/VIRR数据,利用Becker局地分裂窗改进算法反演得到逐日陆表温度 (LST), 对2009年一次高温天气过程进行动态监测, 并分析不同下垫面的热环境变化。结果显示:此过程中可见光红外扫描辐射计 (VIRR) 陆表温度产品在敦煌辐射校正场地两次验证的误差为-0.17 K和1.77 K,与同时间过境的MODIS产品均方根误差为2.64 K,直方图对比陆表温度的频数分布基本一致;对高温天气过程监测发现,此次出现以华北的石家庄、郑州、北京等地和西北地区东部的西安等地为中心的两个陆表温度高值区, 部分地区达到了320.2 K以上;城市剖面资料证实城市热岛现象存在,并发现工矿用地的热岛效应不容忽视,主要是大面积的工矿用地周围植被破坏严重,地表增温更为显著。     

Evaluation and Preprocess of Chinese Fengyun-3A Sea Surface Temperature Experimental Product for Data Assimilation

Validated satellite-derived sea surface temperatures (SSTs) are widely used for climate monitoring and ocean data assimilation systems. In this study, the Fengyun-3A (FY-3A) SST experimental product is evaluated using Advanced Very High Resolution Radiometer (AVHRR)-merged and in situ SSTs. A comparison of AVHRR-merged SSTs reveals a negative bias of more than 2K in FY-3A SSTs in most of the tropical Pacific and low-latitude Indian and Atlantic Oceans. The error variance of FY-3A SSTs is estimated using three-way error analysis. FY-3A SSTs show regional error variance in global oceans with a maximum error variance of 2.2 K in the Pacific Ocean. In addition, a significant seasonal variation of error variance is present in FY-3A SSTs, which indicates that the quality of FY-3A SST could be improved by adjusting the parameters in the SST retrieval algorithm and by applying regional and seasonal algorithms, particularly in key areas such as the tropical Pacific Ocean. An objective analysis method is used to merge FY-3A SSTs with the drifter buoy data. The errors of FY-3A SSTs are decreased to-0.45K comparing with SST observations from GTSPP.     

风云三号气象卫星数据传输体制分析

风云三号气象卫星 (FY-3) 是我国的新一代太阳同步轨道气象卫星, 其星-地数据传输体制采用了国际空间数据系统咨询委员会 (CCSDS) 推荐使用的先进在轨系统 (AOS) 规约和数据结构, 采用R-S编码和卷积编码级联的编码方式, 使用了L波段和X波段同时广播的方式。该文分析了FY-3星地数据传输体制, 将FY-3的传输体制与国外同类卫星传输体制进行了比较分析, 给出了FY-3的传输体制与风云一号 (FY-1) 的差别, 在此基础上提出了我国下一代气象卫星地面站建设的基本策略。     

An Operational Precipitable Water Vapor Retrieval Algorithm for Fengyun-2F/VISSR Using a Modified Three-Band Physical Split-Window Method

The Visible and Infrared Spin-Scan Radiometer(VISSR) onboard the Fengyun-2(FY-2) satellite can provide valuable thermal infrared observations to help create a precipitable water vapor(PWV) product with high spatial and temporal resolutions. The current FY-2/VISSR PWV product in operation is produced by using a traditional two-band physical split-window(PSW) method, which produces low quality results under dry atmospheric conditions. Based on the sensitivity characteristics of FY-2 F/VISSR water vapor channel and two split-window channels to atmospheric water vapor, this study developed a new, robust operational PWV retrieval algorithm for FY-2 F to improve the operational precision of the current PWV product. The algorithm uses a modified three-band PSW method, which adds a scale for the water vapor channel in the improved three-band PSW method. Integrated PWV products from the radiosonde data in 2016 are used here to validate the precision of the PWV retrieved by the modified three-band and traditional two-band PSW methods. The mean bias, root mean square error(RMSE), and correlation coefficient of the PWV retrieved by the modified three-band PSW method are 0.28 mm, 4.53 mm, and 0.969, respectively. The accuracy is much better than the PWV retrieved by the two-band method, whose mean bias, RMSE, and correlation coefficient are 12.67 mm, 29.35 mm, and 0.23. Especially, in mid-or high-latitude regions, the RMSE of the PWV is improved from 10 to 2 mm by changing the inversion in the two-band method to the modified three-band PSW method. Furthermore, the modified three-band PSW results show a better consistency with the radiosonde PWV at any zonal belt and season than the two-band PSW results. This new algorithm could significantly improve the quality of the current FY-2 F/VISSR PWV product, especially at sites where the actual PWV are lower than 15 mm.     

Impact of assimilating FY-3C MWHS2 data in the RMAPS-ST forecast system on its rainfall forecasts

中层水汽初值的误差是数值预报,尤其是短期预报不确定性的重要来源.星载微波湿度计资料能很好地弥补常规资料的不足,同化微波湿度计资料对改善对流层中高层的水汽初始场精度有着重要意义.本研究基于新一代快速更新多尺度资料分析和预报系统短期数值预报系统(RMAPS-ST),选取2019年6月4-6日中国华中地区降水过程开展了 FY-3C MWHS2资料同化对于此次降水预报的影响评估.研究开展了4组试验:冷启动试验,控制试验,同化FY-3C MWHS试验,同时同化常规观测和FY-3C MWHS试验.结果表明:经质量控制及偏差订正之后FY-3C MWHS2各通道O-B明显趋于正态分布,同化FY-3C MWHS资料后,对此次降水过程降水落区和强度的预报均优于控制试验和冷启动试验,同时对于环境场的预报也有改善.     

A Precipitation Detection Method for MWTS-Ⅱ Radiance Assimilation in Typhoon Simulation

FY-3C Microwave Temperature Sounder Ⅱ(MWTS-Ⅱ) lacks observations at 23.8 GHz, 31 GHz and 89 GHz,making it difficult to remove the data contaminated by precipitation in assimilation. In this paper, a fast forward operator based on the Community Radiative Transfer Model(CRTM) was used to analyze the relationship between the observation minus background simulation(O-B) and the cloud fractions in different MWTS-Ⅱ channels. In addition,based on the community Gridpoint Statistical Interpolation(GSI) system, the radiation brightness temperature of the MWTS-Ⅱ was assimilated in the regional Numerical Weather Prediction(NWP) model. In the process of assimilation,Visible and Infrared Radiometer(VIRR) cloud detection products were matched to MWTS-Ⅱ pixels for precipitation detection. For typhoon No. 18 in 2014, impact tests of MWTS-Ⅱ data assimilation was carried out. The results show that,though the bias observation minus analysis(O-A) of assimilated data can be reduced by quality control only with | O-B| 3 K; however, the O-A becomes much smaller while the precipitation detection is performed with F_(virr) 0.9(VIRR cloud fraction threshold of 0.9). Besides, the change of the environmental field around the typhoon is more conducive to make the simulated track closer to the observation. The 72-hour typhoon track simulation error also shows that, after the precipitation detection, the error of simulated typhoon track is significantly reduced, which reflects the validity of a precipitation detection method based on a double criterion of | O-B | 3 K and F_(virr) 0.9.