近50a中国降水格点数据集的建立及质量评估

基于2012年6月更新的高质量2 400个台站降水资料,采用薄盘样条法,制定了采用3个自变量(经度、纬度、海拔高度)、降水量开平方预处理、3次样条的插值方案,并引入数字高程资料,以减弱中国独特地形条件下高程对降水空间插值精度的影响,并对1961—2010年中国区域地面降水站点资料进行了空间内插,得到了中国地面降水0.5°×0.5°格点数据集。经数据集的质量评估结果表明:分析值与站点观测值均方根误差平均为0.49 mm,相关系数平均达0.93(通过0.01的显著性检验),夏季插值误差高于冬季,东南地区误差普遍高于其他地区。冬、春、夏、秋季绝大多数台站绝对误差在±10 mm/月以内。冬、春、夏、秋季分别有60%、82%、54%、77%的台站相对误差在±10%之间。插值后的格点化降水资料能够比较细致、准确地描述中国大陆年平均降水场的东南多、西北少的主要空间特征,但也平滑掉了范围很小的降水极值中心。台站分布越密集的地方,插值效果越好,并且最近距离小于40 km的台站插值精度较高,大于40 km插值精度衰减较快。     

基于西南地区台站降雨资料空间插值方法的比较

以西南地区1996～2000年93个气象台站观测的月均降雨量为基础,对各月降雨量进行空间自相关性,变异特征等空间分析后,采用反距离加权法(IDW)和以不同变异函数模型(指数模型、球面模型、高斯模型)为基础的普通克里金(O-Kriging)两种方法进行空间插值,通过交叉验证结果对两种方法进行分析比对。结果表明:(1)西南地区月均降雨量存在明显的空间集聚现象,并具有显著的空间自相关性和变异特征,可对该研究区域降雨量进行空间插值研究。(2)在O-Kriging插值时,变异函数选用指数模型的效果最好,球面模型次之,高斯模型最差。(3)两种方法对月均降雨量及其极大值和极小值插值时,O-Kriging的插值误差均小于IDW,插值误差整体上与降雨量呈正相关关系。在剔除各月降雨量极大值较为集中的两个站点后进行插值,插值结果的误差均明显降低。(4)对研究区域整体来说,O-Kriging的插值效果优于IDW,但就单个站点来看,结果并非如此。在降雨量的空间插值中,由于研究区域和时间尺度的不同,并不存在绝对的最优方法,应根据实际应用效果选择最适方法。     

Monthly precipitation mapping of the Iberian Peninsula using spatial interpolation tools implemented in a Geographic Information System

Summary In this study, spatial interpolation techniques have been applied to develop an objective climatic cartography of precipitation in the Iberian Peninsula (583,551 km²). The resulting maps have a 200 m spatial resolution and a monthly temporal resolution. Multiple regression, combined with a residual correction method, has been used to interpolate the observed data collected from the meteorological stations. This method is attractive as it takes into account geographic information (independent variables) to interpolate the climatic data (dependent variable). Several models have been developed using different independent variables, applying several interpolation techniques and grouping the observed data into different subsets (drainage basin models) or into a single set (global model). Each map is provided with its associated accuracy, which is obtained through a simple regression between independent observed data and predicted values. This validation has shown that the most accurate results are obtained when using the global model with multiple regression mixed with the splines interpolation of the residuals. In this optimum case, the average R ² (mean of all the months) is 0.85. The entire process has been implemented in a GIS (Geographic Information System) which has greatly facilitated the filtering, querying, mapping and distributing of the final cartography.     

Observed monthly precipitation trends in China 1951–2002

Summary Monthly precipitation trends of 160 stations in China from 1951–2002 have been analysed and interpolated. The Mann-Kendall trend test was applied to examine the monthly precipitation data. Significant positive and negative trends at the 90, 95, and 99 percent confidence levels were detected for numerous stations. The number, distribution, and direction of the trends varied from month to month.The detected trends were spatially interpolated by applying the Inverse Distance Weighted (IDW) interpolation method. The spatial presentation of the detected precipitation trends gives a better understanding of climatic changes or variations in China during the last 50 years. This is especially the case for highlighting the spatial structure of precipitation trends.A clustering of trends is observed in certain months, including distinct trend belts especially in east and north-east China. Nevertheless, positive as well as negative monthly trends can be noted simultaneously in different areas. The spatial interpolation of precipitation trend analysis results is a useful approach to give further understanding of the regional pattern of precipitation trends in China.     

A Model to Interpolate Monthly Mean Climatological Data at Bavarian Forest Climate Stations

Summary  Six methods were used to interpolate the monthly mean climatological data from German climate stations to three Bavarian forest climate stations. The observed forest climatological data at the Bavarian forest climate stations were used as the reference data to which the interpolated data were compared. The results show that, for monthly mean daily maximum temperature at valley and plain forest climate stations, each of the six interpolation methods can give accurate estimates. For monthly mean daily maximum temperature, minimum temperature, air temperature and water vapor pressure at mountain forest climate stations, topographically aided interpolation can give the most accurate estimates. Barnes interpolation combined with empirical transfer functions can give accurate estimates forall climate variables at the plain and valley forest climate stations, and it can also give accurate estimates for monthly mean wind speed and monthly precipitation at the mountain forest climate station. The empirical transfer functions are very important for estimating the forest climatological data. These transfer functions will be used for reconstruction of long-term forest climatological data in Bavaria. Received September 9, 1998 Revised May 21, 1999     

基于Shepard和OI方法对雨量计逐时资料的分析

引入地形影响效应的日降水量气候分析场,分别运用Shepard和最优插值(OI)两种插值方法对广东和广西2007年5月20日—8月30日汛期小时雨量计降水量进行插值,得到0.125°×0.125°分辨率的规范化网格资料。结果表明:无论是直接插值还是用降水比率(地形影响效应的日降水量气候分析场)插值,两种方法均能很好地体现广东和广西雨量计站点观测降水的季内变化和日变化特征。虽然用直接插值方法比用降水比率插值方法得到的降水空间分布更为平滑,但估值精度没有用降水比率插值方法高。通过交叉检验进一步表明,总体上OI方法优于Shepard方法,而考虑地形影响效应的降水比率OI方法为最优,能有效提高相关性,并减少均方根误差和系统误差。     

中国区域高分辨率多源降水观测产品的融合方法试验

高质量、高分辨率降水产品研制对于数值天气模式检验、水文陆面模拟、山洪地质灾害监测有着重要意义。利用中国近4万自动气象站逐时降水资料、中国雷达定量降水估计和CMORPH卫星反演降水产品,开展0.05°×0.05°和0.01°×0.01°两种高分辨率下的三源降水融合方法研究试验,探讨如何有效引入雷达高分辨率信息来提高降水产品质量。一方面,在0.05°分辨率上,先以自动气象站观测降水数据为基准,采用概率密度函数（PDF）匹配法订正雷达和卫星估测降水产品的系统偏差,将雷达降水产品的偏差从-0.05 mm/h降至-0.008 mm/h;再采用贝叶斯模型平均（BMA）方法融合雷达和卫星降水产品,形成0.05°分辨率的中国区域覆盖完整且最优的联合降水背景场。此外,在0.01°分辨率上,以0.05°分辨率的卫星-雷达贝叶斯模型平均联合降水产品为背景,采用1 km雷达估测降水的空间结构信息进行降尺度,亦能有效提高0.01°分辨率背景场的质量。然后,分别以不同分辨率的卫星-雷达联合降水产品为背景,采用统计方法量化误差估计,再采用最优插值方法融入地面观测。通过2419个中国国家级气象台站的独立样本检验,评估了多种类型的降水资料及融合试验产品在中国地区的质量。结果表明,两种分辨率的三源融合试验产品的精度均优于任何单一来源的降水产品,特别是在站点稀疏地区,降水精度均较融合前有显著提高,达到了较好的融合效果,其中在0.05°分辨率上采用“概率密度函数+贝叶斯模型平均+最优插值”方法的三源融合降水产品整体质量最好,而0.01°分辨率上基于“概率密度函数+贝叶斯模型平均+降尺度+最优插值”方法的三源融合降水产品在强降水监测上更有优势。      

Spatial distributions of heating, cooling, and industrial degree-days in Turkey

Summary The degree-day method is commonly used to estimate energy consumption for heating and cooling in residential, commercial and industrial buildings, as well as in greenhouses, livestock facilities, storage facilities and warehouses. This article presents monthly and yearly averages and spatial distributions of heating, cooling, and industrial degree-days at the base temperatures of 18 °C and 20 °C, 18 °C and 24 °C, and 7 °C and 13 °C, respectively; as well as the corresponding number of days in Turkey. The findings presented here will facilitate the estimation of heating and cooling energy consumption for any residential, commercial and industrial buildings in Turkey, for any period of time (monthly, seasonal, etc.). From this analysis it will also be possible to compare and design alternative building systems in terms of energy efficiencies. If one prefers to use set point temperatures to indicate the resumption of the heating season would also be possible using the provided information in this article. In addition, utility companies and manufacturing/marketing companies of HVAC systems would be able to easily determine the demand, marketing strategies and policies based on the findings in this study.     

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。     

重庆山地区域气象要素空间插值方法对比

利用重庆地区1999年和2018年气象数据, 分别采用薄盘光滑样条、协同克里金、普通克里金、反距离加权4种方法, 从年和月两种尺度对气温、降水、太阳总辐射三个要素进行空间插值; 采取交叉验证方法, 用MAE、MRE、RMSE评估插值精度, 确定各要素最优插值方法。结果表明: 气温和太阳总辐射最优插值方法为薄盘光滑样条, 降水为反距离加权; 插值精度上气温、太阳总辐射高值月份优于低值月份, 降水则相反, 但三个要素均表现出年尺度优于月尺度。MRE检验表明, 插值精度为气温>太阳总辐射>降水, 1999年年尺度插值精度分别为1.86%、4.60%、6.87%, 月尺度插值精度分别为2.79%、5.82%、17.42%;2018年太阳总辐射年、月尺度插值精度分别为3.03%、4.88%, 区域站加密后气温、降水年尺度插值精度分别为2.03%、11.20%, 月尺度对应插值精度分别为3.20%、23.14%。     

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。     

Spatial Heating Monthly Degree-Day Features and ClimatologicPatterns in Turkey

Summary  Degree-days as a measure of accumulated temperature deviations from a base temperature have many practical applications in various human related activities such as home cooling, heating, plant growth in agriculture and power generation in addition to energy requirement. Long temperature records are necessary for their reliable estimations at given stations. In this paper, degree-day measure has been applied to monthly temperature records for systematically changed base temperature values from − 25 °C to + 35 °C with 5 °C increments at 255 meteorology stations in Turkey. The results are represented in the form of spatial degree-day distribution maps, which are then related to various climatic, meteorological and topographic features of Turkey. For instance, free surface water bodies in forms of surrounding seas, lakes and rivers insert retardation in the expansion of heating degree-days over large regions. On the other hand, cold air penetration from polar regions in the northeastern Turkey originating from Siberia appears at moderate base temperature heating degree-days. Received August 20, 1998 Revised June 21, 1999     

我国单站旱涝指标确定和区域旱涝级别划分的研究

根据1951～1995年各月降水资料，在全国选取8个代表站，测试了3种单站旱涝指标，并作了相互比较，认为Z指数方法最优。在此基础上，以华北地区为例，选取80个站点，探讨了能反映区域旱涝时空分布和强度的区域旱涝指标以及旱涝等级。     

面雨量空间扩展估算法

以温州地区1991～2001年90个观测站的月平均降雨为例,在GIS支持下,对样条函数法、克立格内插法及距离平方反比法这3种插值方法进行了对比研究;并在90个观测站中筛选出最少量的、能达到稳定结果的站点数;还考虑了插值的空间分辨率对结果的影响。对上述3点进行大量的计算、统计分析的结果表明:①在选择距离平方反比法及样条函数法对月平均降雨量插值效果均较好;②利用这两种插值方法对不同站点密度选取不同空间分辨率插值后得出,选取50站误差趋于稳定,利用距离平方反比法插值结果误差较小,而空间分辨率对结果几乎没有影响。利用距离平方反比法,选择50个站得到了温州地区1km×1km面雨量空间扩展结果,为水文预报工作提供一种较精确的面雨量估算和输入方法。     

中国中东部区域TRMM降水产品降尺度研究及其时空特征分析

该研究以中国中东部区域(17°～50°N,98°～135°E)为研究范围,在前人研究基础上,根据水汽与降水之间的关系,基于MOD05水汽产品,采用偏最小二乘法,对中国中东部区域2001—2010年10 a平均TRMM3B43_V 7月降水产品进行降尺度,旨在得到空间分辨率为1 km×1 km的月降水空间分布。通过比较分析,发现该降尺度模型能大幅提高TRMM产品空间分辨率,估算结果平均相对误差为15.35%,与地面观测较接近,能体现中国中东部区域降水宏观分布趋势,且估算结果精度高于前人基于归一化植被指数(NDVI)的降尺度模型,能满足降水产品的精细化需求。     

The influence of interpolation and station network density on the distributions and trends of climate variables in gridded daily data

We study the influence of station network density on the distributions and trends in indices of area-average daily precipitation and temperature in the E-OBS high resolution gridded dataset of daily climate over Europe, which was produced with the primary purpose of Regional Climate Model evaluation. Area averages can only be determined with reasonable accuracy from a sufficiently large number of stations within a grid-box. However, the station network on which E-OBS is based comprises only 2,316 stations, spread unevenly across approximately 18,000 0.22° grid-boxes. Consequently, grid-box data in E-OBS are derived through interpolation of stations up to 500 km distant, with the distance of stations that contribute significantly to any grid-box value increasing in areas with lower station density. Since more dispersed stations have less shared variance, the resultant interpolated values are likely to be over-smoothed, and extreme daily values even more so. We perform an experiment over five E-OBS grid boxes for precipitation and temperature that have a sufficiently dense local station network to enable a reasonable estimate of the area-average. We then create a series of randomly selected station sub-networks ranging in size from four to all stations within the E-OBS interpolation search radii. For each sub-network realisation, we estimate the grid-box average applying the same interpolation methodology as used for E-OBS, and then evaluate the effect of network density on the distribution of daily values, as well as trends in extremes indices. The results show that when fewer stations have been used for the interpolation, both precipitation and temperature are over-smoothed, leading to a strong tendency for interpolated daily values to be reduced relative to the “true” area-average. The smoothing is greatest for higher percentiles, and therefore has a disproportionate effect on extremes and any derived extremes indices. For many regions of the E-OBS dataset, the station density is sufficiently low to expect this smoothing effect to be significant and this should be borne in mind by any users of the E-OBS dataset.     

North Sea – Caspian Pattern (NCP) – an upper level atmospheric teleconnection affecting the eastern Mediterranean – implications on the regional climate

Summary ?A calendar of the negative and positive phases of the North Sea – Caspian Pattern (NCP) for the period 1958–1998 was used to analyse the implication of the NCP upper level teleconnections on the regional climate of the eastern Mediterranean basin. Series of monthly mean air temperature and monthly total rainfall from 33 stations across Greece, Turkey and Israel, for the same period, were used. For each month, from October to April, averages of the monthly mean temperatures and the monthly rainfall totals as well as the standardized values of both parameters were calculated separately for the negative (NCP (−)) and the positive (NCP (+)) phases of the NCP. At all stations and in all months, temperature values were significantly higher during the NCP (−) as compared with the NCP (+). Furthermore, apart from very few exceptions, the absolute monthly mean maximum and monthly mean minimum values were obtained during the NCP (−) and the NCP (+) phases, respectively. The maximum impact of the NCP on mean air temperature was detected in the continental Anatolian Plateau, where the mean seasonal differences are around 3.5 °C. This influence decreases westwards and southwards. The influence on the rainfall regime is more complex. Regions exposed to the southern maritime trajectories, in Greece and in Turkey, receive more rainfall during the NCP (−) phase, whereas in the regions exposed to the northern maritime trajectories, such as Crete in Greece, the Black Sea region in Turkey, and in all regions of Israel, there is more rainfall during the NCP (+) phase. The accumulated rainfall differences between the two phases are over 50% of the seasonal average for some stations. A comparison of the capabilities of the NCP, the North Atlantic Oscillation (NAO) and the Southern Oscillation (SO) indices to differentiate between below and above normal temperatures was made. The results have placed the NCP, as the best by far of all three teleconnections in its ability to differentiate between below or above normal temperatures and as the main teleconnection affecting the climate of the Balkans, the Anatolian Peninsula and the Middle East. These results may serve to downscale General Circulation Model (GCM) scenarios to a regional scale and provide forecasts regarding eventual temperature and/or precipitation changes. Received June 25, 2001; revised February 25, 2002; accepted March 3, 2002     

Monthly and daily precipitation trends in the Mediterranean (1950–2000)

Summary The aim of the paper lies in the identification of possible significant linear trends at monthly, seasonal and annual timescales in the Mediterranean during the second half of the 20th century. Monthly and daily records of 63 stations have been used to elaborate several precipitation indices: sum of daily precipitation (SDP) for rainfall >0.1 mm, >10 mm and >95^th percentile, of number of rainy days (RD) >0.1 mm and >10 mm and of mean daily precipitation (MDP) >0.1 mm and >10 mm. For each index the stations have been gathered together by Rotated Principal Component Analyses to determine 8 sub-areas which can be considered as identical for all the timescales at the spatial scale of the research. Trends have been estimated from the scores of each eigenvector retained in all RPCAs. They are mainly non existant or non significant decreasing, even if a few monthly trends appear to be significantly diminishing, primarily during winter months, March in the Atlantic region, October in the Mediterranean Spain, December in the Lions and Genoa Gulfs, January, winter and the year in Greece, winter and the year in Italy and winter in the Near East and increasing in April in the two gulfs. Correlation coefficients between SDP>0.1 mm and other indices have been computed: the significant trends seem mainly related to RD>10 mm, which represents a high percentage of the total rainfall amount. Greece is remarkable: SDP>0.1 mm and >10 mm decrease significantly during January, winter, the rainy season and the entire year whereas SDP>95^th percentile increases significantly, in accordance with the climatic change scenarios for the end of this century as does the decreasing of the total monthly and seasonal rainfall.