中国降水量序列均一性分析方法及数据集更新完善

基于中国气象局国家气象信息中心2012年发布的《中国国家级地面气象站基本气象要素日值数据集（V3.0）》,选取一定空间范围内相关性、数据完整性均较好的邻近站降水资料,构建参考序列,结合标准正态检验和台站历史沿革信息对我国2342个台站年、月降水资料进行均一性检验。采用相关系数权重平均方法和一阶差分方法相结合得到参考序列,以降低因计算方法和邻近站序列长度不一致等引起的参考序列不确定性。最终结果显示：98个台站降水序列存在断点,仅占总站数的4.2%。采用比值法订正上述非均一性的降水序列,订正后的序列在一定程度上消除了人为因素的干扰,部分台站降水量变化趋势（1960-2009年）异常的问题得到改善。     

我国逐日降水量格点化方法

国家气象信息中心(NMIC)和美国大气海洋局气候预测中心合作开发了"中国逐日格点降水量实时分析系统(V1.0)",并已在NMIC投入业务试运行。该系统基于我国2419个国家级地面气象站日降水量观测(08:00—08:00,北京时)数据,采用"基于气候背景场"的最优插值方法,实时生成空间分辨率为0.5°×0.5°的格点化日降水量资料。通过对汛期典型区域和单站降水过程的对比分析表明:该格点化产品的精度较高,能准确捕捉并再现每一次降水过程。误差分析表明:约91%的数据绝对误差小于1.0 mm/d。该产品在定量分析天气实况、检验天气气候模式精度、检验卫星产品精度等方面有应用前景。     

Latest update of the climatology and changes in the seasonal distribution of precipitation over China

Based on daily precipitation data from 524 meteorological stations in China during the period 1960–2009, the climatology and the temporal changes (trends, interannual, and decadal variations) in the proportion of seasonal precipitation to the total annual precipitation were analyzed on both national and regional scales. Results indicated that (1) for the whole country, the climatology in the seasonal distribution of precipitation showed that the proportion accounted for 55 % in summer (June–August), for around 20 % in both spring (March–May) and autumn (September–November), and around 5 % in winter (December–February). But the spatial features were region-dependent. The primary precipitation regime, “summer–autumn–spring–winter”, was located in central and eastern regions which were north of the Huaihe River, in eastern Tibet, and in western Southwest China. The secondary regime, “summer–spring–autumn–winter”, appeared in the regions south of the Huaihe River, except Jiangnan where spring precipitation dominated, and the southeastern Hainan Island where autumn precipitation prevailed. (2) For the temporal changes on the national scale, first, where the trends were concerned, the proportion of winter precipitation showed a significantly increasing trend, while that of the other three seasons did not show any significant trends. Second, for the interannual variation, the variability in summer was the largest among the four seasons and that in winter was the smallest. Then, on the decadal scale, China experienced a sharp decrease only in the proportion of summer precipitation in 2000. (3) For the temporal changes on the regional scale, all the concerned 11 geographic regions of China underwent increasing trends in the proportion of winter precipitation. For spring, it decreased over the regions south of the Yellow River but increased elsewhere. The trend in the proportion of summer precipitation was generally opposite to that of spring. For autumn, it decreased over the other ten regions except Inner Mongolia with no trend. It is noted that the interannual variability of precipitation seasonality is large over North China, Huanghuai, and Jianghuai; its decadal variability is large over the other regions, especially over those regions south of the Yangtze River.     

Stochastic Post-Processing of CFSR Daily Precipitation across Canada

Reanalyses, based on numerical weather prediction methods assimilating past observations, provide continuous precipitation datasets and represent interesting options for assessing the climatology of regions with sparse station networks (e.g., northern Canada). However, reanalysis series cannot be used directly because of possible biases and mismatch between their spatial and temporal resolutions with that needed for local applications. To address these issues, a Stochastic Model Output Statistics (SMOS) approach was selected to post-process precipitation series simulated by the Climate Forecast System Reanalysis (CFSR) across Canada. This approach uses CFSR precipitation as a covariate and is based on two regression models: the first one is a logistic regression that deals with precipitation occurrence, and the second is a vector generalized linear model for precipitation intensity. At-site post-processed daily precipitation series are randomly generated using the SMOS approach, and selected climate indicators from the Expert Team on Climate Change Detection and Indices, which is jointly sponsored by the Commission for Climatology of the World Meteorological Organization's (WMO) World Climate Data and Monitoring Programme, the Climate Variability and Predictability Programme of the World Climate Research Programme, and the Joint WMO-IOC Technical Commission for Oceanography and Marine Meteorology (CCI/CLIVAR/JCOMM) are estimated and compared with corresponding observed and CFSR values. The two models in the SMOS approach, in addition to adequately correcting systematic biases, produced better predictions than the climatology of the wet and dry and intensity sequences. Additionally, the SMOS generally yields consistent climate indices when compared with those from CFSR without post-processing, though there is still room for improvement for specific indices (e.g., annual maximum of cumulative wet days).     

热带气旋对1975-2018年暖季中国极端降水气候态、变化趋势及其与温度关系的影响研究

全球变暖背景下我国极端小时降水和极端日降水(EXHP、EXDP)气候态及变化趋势的区域差异明显, 其中热带气旋(TC)的影响尚不明确。利用1975-2018年暖季台站小时降水(P)和热带气旋最佳路径等资料, 采用百分位法定义极端小时降水与极端日降水, 并将总降水(All)客观分为热带气旋降水与非热带气旋(nonTC)降水, 分析热带气旋对中国东部All-P、All-EXHP、All-EXDP的气候态和变化趋势以及极端小时降水随温度变化的影响。主要结论如下: (1) TC-P、TC-EXDP、TC-EXHP占其对应总降水之比均从东南和华南沿海向西北内陆递减, 区域平均而言, TC-P占All-P之比与TC-EXHP占All-EXHP之比均约为11%, 而TC-EXDP占AllEXDP之比为15.8%;(2) 热带气旋和非热带气旋降水变化趋势的空间分布差别较大, 热带气旋对长江流域东部总降水增多的贡献高达49%, 并一定程度上改变了降水趋势的空间分布; (3) TC-EXHP强度与温度的关系在约21℃发生改变, 且截然不同于nonTC-EXHP, 华南、东南沿海TC-EXHP强度随温度的变化率明显低于nonTCEXHP, 造成nonTC-EXHP和All-EXHP随温度变化率不同, 且在东南沿海差异显著。      

近38年中国气温和降水的1 km网格数据集

对中国38年的气温和降水进行了空间插值分析,选取最优模型去生成1km网格数据集,为中国大陆的植被分布、气候变化和环境生态等研究提供支持。基于国家气象中心839个气象站的逐日气温和降水数据,用经度、纬度和海拔作为ANUSPLIN软件插值的3个变量,对降水进行开平方预处理,采用3次样条的薄盘光滑样条法,得到了1980—2017年中国大陆月平均气温和月累计降水1km网格插值数据集。数据集的广义交叉验证均方根(RTGCV)和均方根误差(RMSE)具有年周期性和明显的季节变化特征;各站点的平均误差(MBE)的频率分布近似正态分布,绝对误差(MAE)的空间分布也符合中国大陆气候的变化特征。数据集在精准度和时间序列上较新,且提供公共下载服务,可为全国陆地生态系统的研究提供信息支持。     

1951～2009年东亚地区日降水趋势特征分析

研究大陆或次大陆尺度日降水长期趋势变化规律,对于检测、理解区域气候和陆地水循环对全球气候变暖的响应特征十分重要。利用美国国家气候资料中心(NCDC)和中国基准气候站、基本气象站网降水观测资料,在对该站点资料进行基本质量控制基础上,选取东亚地区619个站1951～2009年日降水数据,按照百分位阈值对降水进行分级,共分为弱、中、强、极强4个级别,用经纬度网格面积加权平均方法构建区域平均的时间序列,分析了各类降水事件长期变化趋势的时空特征。结果表明:东亚地区近59年平均总降水量表现出不显著下降趋势,降水日数没有出现趋势性变化,平均日降水强度略有减小;区域平均的年降水量、降水日数和日降水强度在中国北方大部、蒙古东部、俄罗斯远东地区南部和日本列岛多呈减少趋势,而在俄罗斯中西伯利亚南部、朝鲜半岛南部和中国长江中下游流域一般表现为增加。从季节上看,近59年东亚区域平均的冬、春季降水量、降水日数和日降水强度均呈增加趋势,而夏、秋季一般呈减少趋势,仅夏季日降水强度略有增加。降水的年内分配出现均匀化趋势。从不同级别降水事件看,近59年来东亚区域平均的各级别降水量均为下降趋势,中降水、强降水和极强降水日数也呈现下降趋势,弱降水日数表现出较明显增加;仅有全区秋季强降水量、日数减少趋势和冬季中降水量、日数增加趋势通过了显著性水平检验。分析还发现,近30年(1980～2009年)东亚地区日降水趋势变化出现了新的特征,主要表现为大部分地区降水日数呈现增加,日降水强度减少,45°N以南多数台站降水量也增加,全区降水有向非极端化方向发展趋势。     

三套再分析降水资料在中国区域的对比评估

利用实测资料对NCEP-1、ERA-40和20CR再分析降水资料在中国范围内均值、年际变化、相关性和长期趋势等方面进行比较评估。结果表明,平均而言ERA-40年降水量和实测值最为接近,而20CR和NCEP-1年降水量明显偏多,三者差值百分比分别为-1.3%,55.0%和36.9%;三种再分析降水偏差最大区均出现在西南地区,最大偏差值都在600 mm以上;年际变化上,ERA-40和NCEP-1自20世纪70年代中期开始年降水差值百分比出现一定波动性,而20CR在整个研究时段年降水差值百分比基本稳定;三套资料和实测资料的相关性具有明显的区域性特征,东部相关系数明显高于西部,值得一提的是ERA-40在大部地区的相关性好于其他两套资料;ERA-40和20CR则对大部分区域降水变化趋势的描述好于NCEP-1资料。     

融合降水实况分析产品在四川地区的适用性评估

利用四川省地面自动站2018年6月—2019年5月的逐小时降水观测资料,在邻近插值和双线性插值对比分析的基础上,从晴雨准确率、降水时空特征、降水分量级检验等多个方面,对国家气象信息中心研制的融合降水实况分析产品在四川地区的适用性进行评估分析。评估结果表明:(1)邻近插值和双线性插值对评估结果影响小。(2)融合降水实况分析产品的完整性好,其平均晴雨准确率为92.6%,对探测降水有无存在较大可能。(3)融合降水实况分析产品的数据质量较高,能反映四川区域年内小时降水的时空变化特征,且随着降水量级的增大,误差相应增大,TS评分相应减小,说明在弱降水量级,融合降水实况分析产品与观测降水更接近。(4)非独立检验的效果好于独立检验,盆地的检验效果好于高原、山区等复杂地区,说明参与评估的站点分布、数据质量对评估结果存在一定影响。     

近60年中国日降水量分区及气候特征

根据中国国家级地面气象站均一化降水数据集,使用1956~2015年512个台站的日降水量资料,通过旋转经验正交函数（REOF）得到七个分区。比较了各分区平均日降水量的年内变化和多年倾向率差异:我国偏南分区的小雨日数减少,大雨、暴雨日数、日降水量的区域年均值增加;偏北分区的小雨、大雨、暴雨日数、降水量年均值为递减;长江中下游区（东北区）日降水量、小雨日数、暴雨日数的年均值的近60年倾向率分别是0.0071 mm a-1（-0.0010 mm a-1）、-0.0729 d a-1（-0.0615 d a-1）、0.0132 d a-1（-0.0007 d a-1）。100°E以西地区:小雨、中雨日数在增加,无雨日数显著减少,日降水量的年均值呈递增特点。通过自相关函数和小波功率谱估计,揭示了七个分区的日降水量年均值普遍存在2~4 a周期震荡。使用NCEP/NCAR月均再分析资料,以区域日降水量年均值为指数得到500 hPa、700 hPa、850 hPa回归风系数场、旱涝年整场水汽通量和水汽通量散度差异场相结合分析,结果表明:"东高西低,南高北低"环流型和区域降水有密切关系,水汽差异场是上述环流特点的反映。     

2019年西北太平洋和南海台风活动概述

应用中央气象台业务实时资料和中国气象局台风最佳路径资料对2019年发生在西北太平洋和南海的台风活动主要特征以及主要影响我国的台风路径、强度及风雨情况进行了统计分析和论述。2019年西北太平洋和南海共有29个台风生成,较多年平均值偏多2个;秋季台风异常活跃,生成数较常年明显偏多;台风整体强度偏弱,超强台风数与常年持平;有5个台风登陆我国,较多年平均值略偏少;登陆台风平均强度较多年平均值明显偏弱,但台风“利奇马”登陆强度强、风雨影响重。     

中国年和季各等级日降水量的变化趋势分析

通过对中国554个测站1961—2003年的日降水量数据进行线性回归,对我国全年和各个季节的总降水量和各级降水的线性趋势进行分析,并对两种不同的极端降水定义方法所得的变化趋势进行了比较。结果显示,全年总降水量在西北、长江中下游和华南地区具有明显的增加趋势,而在华北和四川盆地地区具有明显的减少趋势。分析各类降水的季节变化趋势可以发现,西北地区各个季节的日降水都是增加的,长江中下游地区的各类降水的增加趋势主要集中在夏季和冬季,而华北地区的各类降水在各个季节基本都呈减少趋势。极端降水趋势方面,西北、长江中下游、西南部分地区和华南沿海地区具有明显的增加趋势,而华北、四川盆地和东北部分地区则有明显的减少趋势。     

基于数据挖掘CART算法的区域夏季降水日数分类与预测模型研究

夏季降水日数的准确预测,对于保障农业、运输业、电力等行业的有序进行具有重要现实意义.利用连云港市气象局提供的1951—2012年夏季降水数据对连云港地区的降水日数特征进行分析,难以直观地发现夏季降水日数随时间分布的规律.为进一步探索降水日数的发生规律,结合国家气候中心网站提供的多种气候因子数据,基于CART决策树算法构建了连云港地区夏季降水日数是否偏多与是否偏少的分类与预测模型.该模型可以发现在多种气候因子不同条件下,夏季降水日数是否偏多（偏少）的规律,模型的分类与预测都具有良好的效果.利用52 a的数据样本训练模型,模型的训练准确率为90.38%（86.54%）,再用剩余10 a数据样本检验模型,测试准确率为80%（80%）,并且得到规则集,方便气象业务人员使用以及决策服务人员参考.同时,为降水日数的预测提供了数据挖掘的新思路.     

我国高分辨率降水融合资料的适用性评估

利用国家气象信息中心研制的全国30000多个地面自动站降水与 CMORPH (Climate Prediction Center Morphing technique)卫星反演降水融合而成的融合降水产品,分析了融合降水平均偏差和均方根误差的时空分布特征,探讨了不同降水量级以及站点稀疏区和密集区的融合效果,结果表明：融合降水的平均偏差和均方根误差量值均较卫星反演降水有显著减小,随时间的变化幅度不大且误差的区域性差异减弱;融合降水不同量级降水日数分布接近于地面观测降水,虽高估了雨强小于等于4 mm/d的降水,低估了大于4 mm/d高值降水,但同一量级下的误差比卫星反演降水大幅减小,且随着降水强度的增加改善效果明显;站点密集区的融合降水值主要是取决于地面观测降水;站点稀疏区在没有站点分布时,融合降水值主要取决于卫星反演降水,但随着站点个数增加,地面观测降水在融合降水中所占比重逐渐增大,且超过了卫星反演降水的作用。可见融合降水充分有效利用了地面观测降水和卫星反演降水各自的优势,融合效果明显。     

1957-1996台风对中国降水的影响

台风活动中国气候的重要特点之一，它能带来大量降水并造成严重的财产损失。在一些地区，台风降水甚至可以在总降水量中占很大比例。本文目的是研究那些对中国产生影响的台风并重点关注台风对中国降水的影响。文中涉及四个方面的工作。首先，研究了影响中国台风的频率，结果表明台风影响的主要季节为5－11月，尤其以7－9月频繁；在过去40年中影响台风的频率没有明显的变化趋势。第二，对台站台风降水的气候特征分析结果显示，海南和东南沿海地区受台风的影响最大，而且长江以南大部地区每年都受到台风的影响；另外，影响区域大部分地区的台风降水在过去40年中表现出下降的趋势，但是只有东北地区南部这种趋势是显著的。第三，对台风个例的分析表明，个例降水总量和影响面积之间存在着显著的线性关系。最后，对台风造成的中国范围降水总量进行了分析，初步结果显示台风降水总量在1957－1996年间显著减少。     

近40a中国不同量级降水对年降水量变化的影响性分析

采用1968-2007年全国595个气象台站的日降水资料,将降水量分为0．1～9．9mm、10～24．9mm、25～49．9mm和≥50mm共4个不同量级降水,通过趋势系数等统计诊断方法,分析了年雨日与年降水量相关性、年雨日与日平均降水强度的变化趋势、不同量级降水的日数和强度的变化趋势以及它们分别对年降水量变化的影响。...     

An Overview of Surface-Based Precipitation Observations at Environment and Climate Change Canada

The objective of this paper is to provide an overview of the present status and procedures related to surface precipitation observations at Environment and Climate Change Canada (ECCC). This work was done to support the ongoing renewal of observation systems and networks at the Meteorological Service of Canada. The paper focusses on selected parameters, namely, accumulated precipitation, precipitation intensity, precipitation type, rainfall, snowfall, and radar reflectivity. Application-specific user needs and requirements are defined and captured by World Meteorological Organization (WMO) Expert Teams at the international level by Observing Systems Capability Analysis and Review (OSCAR) and WMO Integrated Global Observing System (WIGOS), and by ECCC user engagement initiatives within the Canadian context. The precipitation-related networks of ECCC are separated into those containing automatic instruments, those with human (manual) observers, and the radar network. The unique characteristics and data flow for each of these networks, the instrument and installation characteristics, processing steps, and limitations from observation to data distribution and storage are provided. A summary of precipitation instrument-dependent algorithms that are used in ECCC's Data Management System is provided. One outcome of the analysis is the identification of gaps in spatial coverage and data quality that are required to meet user needs. Increased availability of data, including from long-serving manual sites, and an increase in the availability of precipitation type and snowfall amount are identified as improvements that would benefit many users. Other recognized improvements for in situ networks include standardized network procedures, instrument performance adjustments, and improved and sustained access to data and metadata from internal and external networks. Specific to radar, a number of items are recognized that can improve quantitative precipitation estimates. Increased coverage for the radar network and improved methods for assessing and portraying radar data quality would benefit precipitation users.     

Recent Progress in Studies of Climate Change in China

An overview of basic research on climate change in recent years in China is presented. In the past 100 years in China, average annual mean surface air temperature (SAT) has increased at a rate ranging from 0.03℃ (10 yr)-1 to 0.12℃ (10 yr)-1 . This warming is more evident in northern China and is more significant in winter and spring. In the past 50 years in China, at least 27% of the average annual warming has been caused by urbanization. Overall, no significant trends have been detected in annual and/or summer precipitation in China on a whole for the past 100 years or 50 years. Both increases and decreases in frequencies of major extreme climate events have been observed for the past 50 years. The frequencies of extreme temperature events have generally displayed a consistent pattern of change across the country, while the frequencies of extreme precipitation events have shown only regionally and seasonally significant trends. The frequency of tropical cyclone landfall decreased slightly, but the frequency of sand/dust storms decreased significantly. Proxy records indicate that the annual mean SAT in the past a few decades is the highest in the past 400-500 years in China, but it may not have exceeded the highest level of the Medieval Warm Period (1000-1300 AD). Proxy records also indicate that droughts and floods in eastern China have been characterized by continuously abnormal rainfall periods, with the frequencies of extreme droughts and floods in the 20th century most likely being near the average levels of the past 2000 years. The attribution studies suggest that increasing greenhouse gas (GHG) concentrations in the atmosphere are likely to be a main factor for the observed surface warming nationwide. The Yangtze River and Huaihe River basins underwent a cooling trend in summer over the past 50 years, which might have been caused by increased aerosol concentrations and cloud cover. However, natural climate variability might have been a main driver for the mean and extreme precipitation variations observed over the past century. Climate models generally perform well in simulating the variations of annual mean SAT in China. They have also been used to project future changes in SAT under varied GHG emission scenarios. Large uncertainties have remained in these model-based projections, however, especially for the projected trends of regional precipitation and extreme climate events.     

概率密度匹配法对中国区域卫星降水资料的改进

为考察概率密度匹配法 (PDF方法) 对中国区域卫星反演降水产品系统误差订正的适用性,基于逐日和逐时我国地面观测降水量资料,引入PDF方法,分别对逐日0.25°×0.25°水平分辨率和逐时0.1°×0.1°水平分辨率的CMORPH (Climate Prediction Center Morphing Technique) 卫星降水产品的系统误差进行订正。在分析CMORPH卫星降水产品误差特征的基础上,根据两种资料不同的时空分辨率和误差特点,调整概率密度匹配时选取样本的时间和空间范围,设计相应的订正方案。评估结果表明: PDF方法订正后, 两种分辨率卫星降水资料在中国区域系统误差均显著减小,达到了理想的订正效果。在我国站点稀疏的西部地区,订正后的CMORPH卫星降水产品仍保持卫星观测的降水空间分布,降水量也明显接近于地面观测降水量。可见,PDF方法是中国区域卫星反演降水产品系统误差订正的一种有效方法。     

Global monsoon: Dominant mode of annual variation in the tropics

This paper discusses the concept of global monsoon. We demonstrate that the primary climatological features of the tropical precipitation and low-level circulation can be represented by a three-parameter metrics: the annual mean and two major modes of annual variation, namely, a solstitial mode and an equinoctial asymmetric mode. Together, the two major modes of annual cycle account for 84% of the annual variance and they represent the global monsoon. The global monsoon precipitation domain can be delineated by a simple monsoon precipitation index (MPI), which is the local annual range of precipitation (MJJAS minus NDJFM in the Northern Hemisphere and NDJFM minus MJJAS in the Southern Hemisphere) normalized by the annual mean precipitation. The monsoon domain can be defined by annual range exceeding 300 mm and the MPI exceeding 50%.The three-parameter precipitation climatology metrics and global monsoon domain proposed in the present paper provides a valuable objective tool for gauging the climate models’ performance on simulation and prediction of the mean climate and annual cycle. The metrics are used to evaluate the precipitation climatology in three global reanalysis products (ERA40, NCEP2, and JRA25) in terms of their pattern correlation coefficients and root mean square errors with reference to observations. The ensemble mean of the three analysis datasets is considerably superior to any of the individual reanalysis data in representing annual mean, annual cycle, and the global monsoon domain. A major common deficiency is found over the Southeast Asia-Philippine Sea and southeast North America-Caribbean Sea where the east–west land–ocean thermal contrast and meridional hemispheric thermal contrast coexist. It is speculated that the weakness is caused by models’ unrealistic representation of Subtropical High and under-represented tropical storm activity, as well as by neglecting atmosphere–ocean interaction in the reanalysis. It is recommended that ensemble mean of reanalysis datasets be used for improving global precipitation climatology and water cycle budget. This paper also explains why the latitudinal asymmetry in the tropical circulation decreases with altitude.