气候业务中全球台站逐日气候资料集的建立

通过对全球逐日气温和降水观测资料集（GDCN1．0）的改进，建立了适用于开展气候业务的全球台站逐日气候资料集。新建资料集保留了GDCN1．0资料集中有较好代表性的资料，基本保持了原资料的空间分布，同时中国范围（含台湾岛）的资料内容更加丰富。对气温进行了严格的质量控制，最大限度地减少了错误值的影响。新建资料集在时间和空间分布上以及质量上都基本满足业务需求。     

多套格点降水资料在云南及周边地区的对比

利用1979—2006年云南及周边地区148个测站月降水资料 (简称为STN) 与APHRO (日本APHRODITE高分辨率逐日亚洲陆地降水数据集)、GPCC (全球降水气候中心的月降水合成数据)、CRU (英国East Anglia大学提供的月降水要素数据集)、CMAP (雨量资料与卫星估计及NCEP/NCAR再分析降水场合并分析月数据)、GPCP (全球降水气候中心研制的全球陆地雨量计观测分析月数据) 5套格点降水资料,分析了云南及周边地区气候特征。结果表明:5套格点降水资料空间分布与STN基本一致。EOF第1模态空间场分布也表明:这5套格点降水资料与STN空间分布特征较为一致,但5套格点降水资料在滇南、滇西北、滇川黔交界的3个区域的分布与STN有较大不同,各套资料的EOF第1模态时间序列、与STN的相关系数及均方根误差均随时间不同呈较为一致的波动性;在降水空间分布、相关系数及均方根误差3个方面,APHRO适用性最好,GPCC次之,CMAP与GPCP无明显差别,CRU最差,其中APHRO,GPCC在对降水估计偏低,CRU对降水估计总体略高,CMAP略低,GPCP对降水估计则明显偏高。     

GPCP与中国台站观测降水的气候特征比较

文中利用GPCP降水资料和中国大陆740个台站雨量计降水观测结果,分析研究了1980—2000年中国大陆范围内两者的异同。平均降水率分布结果表明:在中国台站雨量计分布密集地区(100°E以东)两者的多年年平均、季平均和月平均降水率分布具有很好的一致性,即均能表现自春季至冬季中国大陆降水分布自东南向西北伸展,然后向东南后退的气候变化特点。对长江中下游、华北、东北、西南的降水距平随时间的变化分析表明,两者的月距平随时间变化也具有很好的相似性,相关系数均超过0.8。差异分析还表明,由于中国降水季节性变化和台站雨量计密度不均匀,造成春秋冬三季节GPCP和台站雨量计之间的差异较小,而夏季差异较大。总体上GPCP有过高估计降水率的趋势。在GPCP逐月降水资料既能很好地反映出100°E以东中国大陆降水的气候分布,又能很好地表示出上述地区降水量异常变化的基础上,我们利用GPCP降水资料对青藏高原和中国大陆西北地区西部降水分布及变化进行了分析。结果表明20世纪80年代前期青藏高原西部降水偏多,而90年代后降水量减少;中国西北地区降水总体偏少,但没有明显的变化趋势。     

中国区域逐日融合降水数据集与国际降水产品的对比评估

中国国家气象信息中心基于2400多个国家级台站观测日降水量和CMORPH卫星反演降水产品,采用概率密度匹配和最优插值相结合的两步数据融合方法,研制了中国区域1998年以来的0.25°×0.25°分辨率的逐日融合降水产品(CMPA_Daily)。通过该数据集与广泛应用于中国天气气候领域的两种国际上降水融合产品TRMM 3B42(Tropical Rainfall Measuring Mission, 3B42)和GPCP(Global Precipitation Climatology Project, 1 degree daily)的对比评估,考察CMPA_Daily产品的质量,评价其能否合理体现中国降水的天气气候特征。首先利用2008—2010年5—9月独立检验数据定量对比了CMPA_Daily、TRMM 3B42和GPCP 三种降水产品的误差,结果表明,在误差的时间变化和空间分布上,CMPA_Daily均具有最高的相关系数和最小的平均偏差及均方根误差,TRMM 3B42其次,GPCP的误差相对较大。CMPA_Daily只低估了大暴雨,TRMM 3B42低估了大雨以上量级的降水,而GPCP低估了除小雨以外的所有降水。CMPA_Daily产品因融入了更多的站点观测信息,不论在中国东部沿海,还是中西部地形复杂区,其精度均优于TRMM 3B42和GPCP产品,即使在站点稀疏的青藏高原地区,CMPA_Daily降水量也更加接近站点观测,呈现明显的高相关。CMPA_Daily与独立检验数据的高相关在地形起伏时效果也较稳定,TRMM和GPCP的相关系数则随着地形变化幅度陡变而非常明显地降低。进一步通过对比分析各降水产品1998—2012年的气候平均降水特征表明,3种资料对中国区域气候平均降水量、降水强度、频率分布以及年际变化的总体描述基本一致,因有效融入了更多的中国站点观测信息,不论降水空间分布还是降水量,CMPA_Daily与地面观测均最为接近,在中国的中东部大部分地区对降水的估计精度明显更高,而在站点分布较稀疏的青藏高原地区,CMPA_Daily的降水分布型与TRMM、GPCP卫星融合资料类似,较地面站点插值产品更能体现出合理的降水分布。对中国强降水事件监测对比表明,CMPA_Daily产品可以更加准确地描述降水的强度变化,细致刻画降水空间分布,在把握降水小尺度特征上具有明显的优势,体现出高分辨率、高精度降水产品的特点。     

GPCP全球降水资料数据集介绍

南京大气资料服务中心最近收到GPCP全球降水资料,包括1°×1°的逐月、逐日全球降水资料和2．5°×2．5°逐月全球降水资料。逐月的资料数据集延伸时段从1979年1月到2008年4月;逐日资料数据集延伸时段从1996年10月到2008年4月。区域范围覆盖全球（0．5°E-359．5°E,89．5°S～89．5°N）;为地面一层,一个变量。统计内容见表1：     

华南地区几种降水产品的对比分析

对华南地区3种比较常用的降水产品（CMAP、GPCP、TRMM）进行了比较和分析。结果表明,在华南地区,这3种降水产品测出的降雨量在空间上具有一致的大尺度分布特征,在时间演变上具有一致的演变趋势,都能很好地反映雨带的季节性迁移特征和华南汛期的降雨特征;但是在不同的具体区域,三者的细节特征差异还是比较显著的,相比较而言,GPCP和TRMM具有更为一致的空间分布特征;在地形复杂的区域,TRMM具有更良好的表现能力。     

地面站点观测降水资料与CMORPH卫星反演降水产品融合的试验效果评估

选取2008年9月—2010年2月的中国2 400个国家级地面观测站降水资料和美国NOAA研发的CMORPH卫星反演降水产品,利用最优插值方法开展了两类降水资料的融合试验,并对试验效果进行评估。结果表明,利用OI方法形成的融合降水产品和地面观测降水分布特征基本一致,能反映西部台站稀疏地区的降水特征以及陆地与海洋之间降水系统的空间连续性。此外,该融合产品保留了高分辨率的卫星观测信息,在台站稀疏地区,一些通过地面观测无法反映出来的中尺度对流系统在融合产品中得到体现。交叉检验结果显示,融合结果和地面观测降水量、台站密度高度相关。样本网格分析结果显示,融合结果和地面降水的逐日时间序列具有较强的一致性。总的来说,OI方法在降水资料融合研究中具有较好的应用效果。      

RHtest方法对我国降水资料的均一性检验试验

应用RHtest方法结合台站元数据信息对我国1725个气象台站1961-2009年月降水资料进行了均一性检验试验和订正,并以波密站、元阳站和巢湖站为例介绍了检验过程.结果表明:该方法能够适用于对我国降水资料均一性检验且具有较高的应用前景.2400台站高密度月降水资料的使用更加有益于参考序列的选取,采用数理统计分析和结合元数据主观判断的方式来对序列进行均一性检验更加合理.检验出存在非均一性断点的台站仅占2.1％,表明我国降水资料序列均一性情况良好,台站较大距离的迁移是造成部分降水序列非均一的重要原因之一.对检验出存在断点的降水序列采用RHtest提供的订正方法进行了订正和趋势分析,发现订正后降水序列的年变化趋势具有明显的改变,均一性也有很大改善.     

月相对全球逐日温度的影响

从卫星逐日蝗对流层下部全球温度距平最新资料集使评估月球位相对全球温度的影响成为可能。其结果揭示了全球在新月和满月之间有统计上显著的０．０２Ｋ的涨落在一个朔 望月周期中，全球日平均最高温度与满月出现的时间对应在。对全球逐日温度记录的谱分析上实其存在的周期性与月球的朔望周期相吻合。由于卫星观测到的全逐日菜足够的精度，可以产月球对短期内的全球温度有可辨识的影响。     

基于低频振荡的西北地区中西部延伸期降水预报研究

对1980—2014年的NCEP/NCAR 3个层次(200 h Pa、500 h Pa和700 h Pa)多个要素场逐日格点资料进行Butterworth带通滤波,保留周期为30~60 d的低频信号,通过周期分析、双评分标准筛选和最优子集回归方法对2011—2014年全球6—8月各要素场预报日前150 d的低频数据进行逐日外延(至未来30 d)。在此基础上,通过逐步相似过滤方法对西北地区中西部44个台站2011—2012年夏季降水进行10~30 d的预报及效果检验。结果表明:(1)对低频要素场的拟合准确度随预报时效增长逐步降低,后期趋于稳定;且各层次各低频要素相应的大部分关键区通过0.05显著性水平检验;(2)当相似个例中降水个例数≥3时预报当日有降水,其对应的Cs评分最高,44个台站的Cs评分均值为0.585,且Cs评分整体高于气候概率值。因此,利用该预报方法进行降水预报是可行的,可用于实际业务中。     

Uncertainties in the GSWP-2 precipitation forcing and their impacts on regional and global hydrological simulations

The Global Soil Wetness Project (GSWP) is an international initiative aimed at producing global data sets of soil wetness and energy and water fluxes by driving land surface models with state-of-the-art 1° by 1° atmospheric forcing and land surface parameters. It also provides a unique opportunity to develop and test land surface parameterizations at the global scale, using multi-year off-line simulations that are not affected by the systematic errors found in atmospheric models. Nevertheless, the accuracy and reliability of the 10?year GSWP-2 atmospheric forcing remain questionable. A first comparison using the high-resolution Rhône-AGGregation (Rhône-AGG) database reveals that the baseline GSWP-2 precipitation forcing is drastically overestimated over the Rhône river basin. Hydrological simulations driven with each dataset and using the ISBA land surface model and the MODCOU river routing model are also compared. The simulated river discharges are validated against a dense network of river gauges and are generally less realistic when using the GSWP-2 instead of the Rhône-AGG precipitation forcing. Secondly, the GSWP-2 precipitation forcing is compared with three alternative data sets (GPCP-2, CRU-2, CMAP) at the global scale. Moreover, the results of a global sensitivity study to the precipitation forcing conducted with six land surface models are shown. The TRIP river routing model is used to convert daily runoff from all models into river discharges, which are compared at 80 gauging stations distributed over the globe. In agreement with the regional evaluation, the results reveal that the baseline GSWP-2 precipitation forcing is generally overestimated over the mid and high latitudes, which implies systematic errors in the simulated discharges. This study reveals that the empirical wind corrections applied to the GSWP-2 precipitation forcing are exaggerated, whereas the GPCP satellite adjustments seem to be useful for simulating realistic annual mean river discharges over the East Siberian river basins.     

Tropical Precipitation Estimated by GPCP and TRMM PR Observations

In this study, tropical monthly mean precipitation estimated by the latest Global Precipitation Climatology Project （GPCP） version 2 dataset and Tropical Rainfall Measurement Mission Precipitation Radar （TRMM PR） are compared in temporal and spatial scales in order to comprehend tropical rainfall climatologically. Reasons for the rainfall differences derived from both datasets are discussed. Results show that GPCP and TRMM PR datasets present similar distribution patterns over the Tropics but with some differences in amplitude and location. Generally, the average difference over the ocean of about 0.5 mm d^-1 is larger than that of about 0.1 mm d^-1 over land. Results also show that GPCP tends to underestimate the monthly precipitation over the land region with sparse rain gauges in contrast to regions with a higher density of rain gauge stations. A Probability Distribution Function （PDF） analysis indicates that the GPCP rain rate at its maximum PDF is generally consistent with the TRMM PR rain rate as the latter is less than 8 mm d^-1. When the TRMM PR rain rate is greater than 8 mm d^-1, the GPCP rain rate at its maximum PDF is less by at least 1 mm d^-1 compared to TRMM PR estimates. Results also show an absolute bias of less than 1 mm d^-1 between the two datasets when the rain rate is less than 10 mm d^-1. A large relative bias of the two datasets occurs at weak and heavy rain rates.     

Climatology Comparison Studies of Precipitations Between GPCP and Rain Gauges in China

The Global Precipitation Climatology Project (GPCP) monthly rainfall data and the rainfall records observed by 740 rain gauges in the mainland of China are used to analyze similarities and differences of the precipitation in China in the period from January 1980 to December 2000. Results expose significantly consistent rainfall distributions between the both data in multi-year mean, multi-year seasonal mean, and multi-year monthly mean. Departures of monthly rainfall for each dataset also show a high correlation with an over 0.8 correlation coefficient. Analysis indicates small differences of both datasets during autumn, winter, and spring, but relative large ones in summer. Generally, the GPCP has trend of overestimating the rainfall rate. Based on above good relationship of both datasets, the GPCP data are used to represent distributions and variations of precipitation in the Tibetan Plateau and Northwest China. Results indicate positive departures of precipitation in summer in the west part of Tibetan Plateau in the 1980s and negative departures after the 1980s. For the west part of Northwest China, analysis illustrates precipitation decreases a little, but no clear variation tendency.     

基于本征微观态方法探究全球地表气压变化特征及其与降水的联系

利用ERA5和GPCP再分析资料及NOAA提供的气候指数,基于本征微观态和传统气象学方法,探讨了全球1950—2022年地表气压变化特征及其与全球降水和环流变化之间的关系。结果表明:全球地表气压的第一大本征微观态主要以南极一致性变化为主,与南极涛动显著相关;第二大本征微观态以北极一致性变化为主,与北极涛动和北大西洋涛动显著相关;第三大本征微观态在热带太平洋呈现纬向偶极子结构,与厄尔尼诺—南方涛动(EI Niño-Southern Oscillation,ENSO)联系紧密。不同本征微观态对全球降水的影响存在显著的区域性差异。第一大本征微观态处于正位相时,南极绕极环流增强,南半球高纬度地区降水增多,中纬度地区降水减少。第二大本征微观态处于正位相时对应北极降水增多,北大西洋及其周边地区降水减少。第三大本征微观态影响范围较广,主要表现为西太平洋降水减少和中东太平洋降水增多。     

Validation of satellite rainfall products over Greece

Six widely available satellite precipitation products were extensively validated and intercompared on monthly-to-seasonal timescales and various spatial scales, for the period 1998–2006, using a dense station network over Greece. Satellite products were divided into three groups according to their spatial resolution. The first group had high spatial (0.5°) resolution and consists only of Tropical Rainfall Measuring Mission (TRMM) products: the TRMM Microwave Imager (TMI) precipitation product (3A12) and the TRMM multisatellite precipitation analysis products (3B42 and 3B43). The second group comprised products with medium spatial (1°) resolution. These products included the TRMM 3B42 and 3B43 estimates (remapped to 1° resolution) and the Global Precipitation Climatology Project one-degree daily (GPCP-1DD) analysis. The third group consisted of low spatial (2.5°) resolution products and included the 3B43 product (remapped to 2.5° resolution), the GPCP Satellite and Gauge (GPCP-SG) product, and the National Oceanographic and Atmospheric Administration Climate Prediction Center (NOAA-CPC) Merged Analysis (CMAP). Rain gauge data were first gridded and then compared with monthly and seasonal precipitation totals as well as with long-term averages of the six satellite products at different spatial resolutions (2.5°, 1°, and 0.5°). The results demonstrated the excellent performance of the 3B43 product over Greece in all three spatial scales. 3B42 from the first and second group and CMAP from the third exhibited a reasonable skill.     

NCEP/NCAR再分析资料所揭示的全球季风降水变化

大气模式是研究气候变化的重要工具,当前的大气模式在模拟季风降水时均存在较大偏差,目前尚不清楚该偏差是来自模式环流场还是模式物理过程.再分析资料由于同化了各类观测和卫星资料,其大气环流近似可被视作是“真实”的.再分析资料中的降水场是在基本真实的环流场强迫下,由当前最先进的数值预报模式计算输出的.因此,再分析资料的降水场能...     

A strategy for merging objective estimates of global daily precipitation from gauge observations,satellite estimates,and numerical predictions

This paper describes a strategy for merging daily precipitation information from gauge observations, satellite estimates(SEs), and numerical predictions at the global scale. The strategy is designed to remove systemic bias and random error from each individual daily precipitation source to produce a better gridded global daily precipitation product through three steps.First, a cumulative distribution function matching procedure is performed to remove systemic bias over gauge-located land areas. Then, the overall biases in SEs and model predictions(MPs) over ocean areas are corrected using a rescaled strategy based on monthly precipitation. Third, an optimal interpolation(OI)–based merging scheme(referred as the HL-OI scheme)is used to combine unbiased gauge observations, SEs, and MPs to reduce random error from each source and to produce a gauge—satellite–model merged daily precipitation analysis, called BMEP-d(Beijing Climate Center Merged Estimation of Precipitation with daily resolution), with complete global coverage. The BMEP-d data from a four-year period(2011–14) demonstrate the ability of the merging strategy to provide global daily precipitation of substantially improved quality.Benefiting from the advantages of the HL-OI scheme for quantitative error estimates, the better source data can obtain more weights during the merging processes. The BMEP-d data exhibit higher consistency with satellite and gauge source data at middle and low latitudes, and with model source data at high latitudes. Overall, independent validations against GPCP-1DD(GPCP one-degree daily) show that the consistencies between BMEP-d and GPCP-1DD are higher than those of each source dataset in terms of spatial pattern, temporal variability, probability distribution, and statistical precipitation events.     

GPCP和TRMM PR热带月平均降水的差异分析

文中利用GPCP(Global Precipitation Climatology Project)和TRMM(Tropical Rainfall Measuring Missio) PR(Precipitation Radar)资料,分析了1998～2002年热带地区月平均降水的差异及其主要原因.结果表明,GPCP和TRMM PR资料能一致地反映热带降水的主要分布特征,但降水的强度和范围存在着差异;两种资料的差异与雨强有密切关系;平均而言,洋面上的降水差异(0.5 mm/d)大于陆地上的差异(0.1 mm/d).微波发射信号(SSM/I E)的反演结果对洋面降水的高估和地面雨量计的缺乏,是造成两种资料间差异的主要原因.分析结果还表明,洋面上GPCP降水相对于PR降水的最大概率差异随雨强增大呈线性增大;陆地上这种差异则呈非线性关系.文中最后还利用最大概率函数对1979～1997年GPCP气候平均降水的误差进行了分析.