全球地面降水月值历史数据集研制

全球降水历史数据是开展气候、水循环等研究的基础。收集整理全球12个数据源降水历史月值资料,通过站号、站名甄别不同数据源中相同台站,对344个通过相关系数、一致率、均值t检验、方差F检验的台站多源资料进行拼接,尽可能多地融合各套数据产品优势,最终形成全球降水历史月值数据集(CMA Global PrecipitationV1.0, CGP)。数据集重点解决当前国际数据产品在东亚地区站点稀少、同时应用多套数据应用门槛较高等问题。数据集收录3.1万个台站共计1.87×107组月降水记录, 4152个台站序列长度达百年。与美国大气海洋局(NOAA)的全球降水数据集(GHCN-M V2.0)对比,CGP新增1万个站点、0.5×107组有效观测记录和1030条百年序列,其中141条百年序列通过多源整合技术获取。CGP的站点和数据量优势主要体现在东亚、东欧、西伯利亚等站点稀疏地区。基于CGP分析的全球降水时空特征与国际同类产品的结果较一致。新增的数据虽然没有改变全球降水分布的总体特征,但对区域性的百年降水变化检测有一定影响。基于CGP的全球降水百年序列结果显示,20世纪前半叶全球降水量偏小,近20年是1900年以来全球降水量最大的时期,各纬度带、各个国家或地区的降水长期变化趋势呈现显著的差异。      

GPCC's new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle

In 1989, the need for reliable gridded land surface precipitation data sets, in view of the large uncertainties in the assessment of the global energy and water cycle, has led to the establishment of the Global Precipitation Climatology Centre (GPCC) at Deutscher Wetterdienst on invitation of the WMO. The GPCC has calculated a precipitation climatology for the global land areas for the target period 1951–2000 by objective analysis of climatological normals of about 67,200 rain gauge stations from its data base. GPCC's new precipitation climatology is compared to several other station-based precipitation climatologies as well as to precipitation climatologies derived from the GPCP V2.2 data set and from ECMWF's model reanalyses ERA-40 and ERA-Interim. Finally, how GPCC's best estimate for terrestrial mean precipitation derived from the precipitation climatology of 786 mm per year (equivalent to a water transport of 117,000 km³) is fitting into the global water cycle context is discussed.     

1901~2013年GPCC和CRU降水资料在中国大陆的适用性评估

利用1901~2013年中国大陆地区的气象台站实测降水资料,对东英吉利（East Anglia）大学气候研究中心（Climatic Research Unit,CRU）和全球降水气候中心（Global Precipitation Climatology Centre,GPCC）的降水资料分别从季节、年际和年代际尺度上进行了评估。结果表明：1961~2013年CRU与GPCC降水资料均能较准确地描述中国大陆地区的降水特征,且在东部较西部地区、夏季较冬季与站点实测降水情况更为一致。将中国大陆划分为不同区域并在其季节、年际和年代际时间尺度上通过比较降水偏差绝对值的百分比、均方根误差和相关系数等统计量后发现：CRU在青藏高原和其它较大的山脉附近与站点实测降水的差别较大,且年均降水趋势在西北一带的阿尔金山脉、黄土高原、东南地区和长江下游地区,比实测降水的年均趋势小、甚至出现趋势相反的情况。此外,CRU降水的年代际变化趋势也偏小。而GPCC数据不论是降水量还是降水趋势都更接近实际情况。在1901~1961年,通过与65个长期气象观测站点的降水时间序列比较发现,CRU在110°E以西地区与站点观测的降水资料间的差别较大,而GPCC与站点观测资料的吻合较好。最后,利用1961~2013年两套降水资料和站点实测资料分别计算了标准化降水指数（SPI）,简单分析了中国大陆地区的干旱变化,发现GPCC对旱涝的时空变化特征的描述比CRU更接近站点实际观测;并且CRU也没有反映出1997年夏季中国地区出现的严重干旱情况,而GPCC较为准确地反映出了这一干旱事件特征。因此,本文的研究结果认为,就中国大陆地区长时期降水资料而言,GPCC的适用性优于CRU。     

Mapping average annual precipitation in Serbia (1961–1990) by using regression kriging

The appearence of geostatistics and geographical information systems has made it possible to analyze complex spatial patterns of meteorological elements over large areas in the applied climatology. The objective of this study is to use geostatistics to characterize the spatial structure and map the spatial variation of average values of precipitation for a 30-year period in Serbia. New, recently introduced, geostatistical algorithms facilitate utilization of auxiliary variables especially remote sensing data or freely available global datasets. The data from Advanced Spaceborn Thermal Emission and Reflection Radiometer global digital elevation model are incorporated as ancillary variables into spatial prediction of average annual precipitation using geostatistical method known as regression kriging. The R ² value of 0.842 proves high performance result of the prediction of the proposed method.     

Effects of climate change on annual streamflow using climate elasticity in Poyang Lake Basin, China

Hydrological processes depend directly on climate conditions [e.g., precipitation, potential evapotranspiration (PE)] based on the water balance. This paper examines streamflow datasets at four hydrological stations and meteorological observations at 79 weather stations to reveal the streamflow changes and underlying drivers in four typical watersheds (Meigang, Saitang, Gaosha, and Xiashan) within Poyang Lake Basin from 1961 to 2000. Most of the less than 90th percentile of daily streamflow in each watershed increases significantly at different rates. As an important indicator of the seasonal changes in the streamflow, CT (the timing of the mass center of the streamflow) in each watershed shows a negligible change. The annual streamflow in each watershed increases at different rates, with a statistically significant trend (at the 5 % level) of 9.87 and 7.72 mm year^?1, respectively, in Meigang and Gaosha watersheds. Given the existence of interactions between precipitation and PE, the original climate elasticity of streamflow can not reflect the relationship of streamflow with precipitation and PE effectively. We modify this method and find the modified climate elasticity to be more accurate and reasonable using the correlation analysis. The analyses from the modified climate elasticity in the four watersheds show that a 10 % increase (decrease) in precipitation will increase (decrease) the annual streamflow by 14.1–16.3 %, while a 10 % increase (decrease) in PE will decrease (increase) the annual streamflow by ?10.2 to ?2.1 %. In addition, the modified climate elasticity is applied to estimate the contribution of annual precipitation and PE to the increasing annual streamflow in each watershed over the past 40 years. Our result suggests that the percentage attribution of the increasing precipitation is more than 59 % and the decreasing in PE is less than 41 %, indicating that the increasing precipitation is the major driving factor for the annual streamflow increase for each watershed.     

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。     

Possible Impact of Spatial and Temporal Non-Uniformity in Land Surface Temperature Data on Trend Estimation

The present work investigates possible impact of the non-uniformity in observed land surface temperature on trend estimation, based on Climatic Research Unit (CRU) Temperature Version 4 (CRUTEM4) monthly temperature datasets from 1900 to 2012. The CRU land temperature data exhibit remarkable non-uniformity in spatial and temporal features. The data are characterized by an uneven spatial distribution of missing records and station density, and display a significant increase of available sites around 1950. Considering the impact of missing data, the trends seem to be more stable and reliable when estimated based on data with < 40% missing percent, compared to the data with above 40% missing percent. Mean absolute error (MAE) between data with < 40% missing percent and global data is only 0.011°C (0.014°C) for 1900–50 (1951–2012). The associated trend estimated by reliable data is 0.087°C decade^–1 (0.186°C decade^–1) for 1900–50 (1951–2012), almost the same as the trend of the global data. However, due to non-uniform spatial distribution of missing data, the global signal seems mainly coming from the regions with good data coverage, especially for the period 1900–50. This is also confirmed by an extreme test conducted with the records in the United States and Africa. In addition, the influences of spatial and temporal non-uniform features in observation data on trend estimation are significant for the areas with poor data coverage, such as Africa, while insignificant for the countries with good data coverage, such as the United States.     

A daily temperature dataset over China and its application in validating a RCM simulation

This paper describes the construction of a 0.5°×0.5°daily temperature dataset for the period of 1961- 2005 over mainland China for the purpose of climate model validation. The dataset is based on the in- terpolation from 751 observing stations in China and comprises 3 variables: daily mean,minimum,and maximum temperature.The"anomaly approach"is applied in the interpolation.The gridded climatology of 1971-2000 is first calculated and then a gridded daily anomaly for 1961-2005 is added to the climatologY to o...     

Regional climate modelling over complex terrain: an evaluation study of COSMO-CLM hindcast model runs for the Greater Alpine Region

In this study the results of the regional climate model COSMO-CLM (CCLM) covering the Greater Alpine Region (GAR, 4°–19°W and 43°–49°N) were evaluated against observational data. The simulation was carried out as a hindcast run driven by ERA-40 reanalysis data for the period 1961–2000. The spatial resolution of the model data presented is approx. 10 km per grid point. For the evaluation purposes a variety of observational datasets were used: CRU TS 2.1, E-OBS, GPCC4 and HISTALP. Simple statistics such as mean biases, correlations, trends and annual cycles of temperature and precipitation for different sub-regions were applied to verify the model performance. Furthermore, the altitude dependence of these statistical measures has been taken into account. Compared to the CRU and E-OBS datasets CCLM shows an annual mean cold bias of ?0.6 and ?0.7 °C, respectively. Seasonal precipitation sums are generally overestimated by +8 to +23 % depending on the observational dataset with large variations in space and season. Bias and correlation show a dependency on altitude especially in the winter and summer seasons. Temperature trends in CCLM contradict the signals from observations, showing negative trends in summer and autumn which are in contrast to CRU and E-OBS.     

Evaluation of the antarctic surface wind climate from ERA reanalyses and RACMO2/ANT simulations based on automatic weather stations

A continental scale evaluation of Antarctic surface winds is presented from global ERA-40 and ERA-Interim reanalyses and RACMO2/ANT regional climate model at 55 and 27 km horizontal resolution, based on a comparison with observational data from 115 automatic weather stations (AWS). The Antarctic surface wind climate can be classified based on the Weibull shape factor k _w . Very high values (k _w  > 3) are found in the interior plateaus, typical of very uniform katabatic-dominated winds with high directional constancy. In the coast and all over the Antarctic Peninsula the shape factors are similar to the ones found in mid-latitudes (k _w  < 3) typical of synoptically dominated wind climates. The Weibull shape parameter is systematically overpredicted by ERA reanalyses. This is partly corrected by RACMO2/ANT simulations which introduce more wind speed variability in complex terrain areas. A significant improvement is observed in the performance of ERA-Interim over ERA-40, with an overall decrease of 14 % in normalized mean absolute error. In escarpment and coastal areas, where the terrain gets rugged and katabatic winds are further intensified in confluence zones, ERA-Interim bias can be as high as 10 m s^?1. These large deviations are partly corrected by the regional climate model. Given that RACMO2/ANT is an independent simulation of the near-surface wind speed climate, as it is not driven by observations, it compares very well to the ERA-Interim and AWS-115 datasets.     

Summertime inter-annual temperature variability in an ensemble of regional model simulations: analysis of the surface energy budget

The inter-annual variability in monthly mean summer temperatures derived from nine different regional climate model (RCM) integrations is investigated for both the control climate (1961–1990) and a future climate (2071–2100) based on A2 emissions. All regional model integrations, carried out in the PRUDENCE project, use the same boundaries of the HadAM3H global atmospheric model. Compared to the CRU TS 2.0 observational data set most RCMs (but not all) overpredict the temperature variability significantly in their control simulation. The behaviour of the different regional climate models is analysed in terms of the surface energy budget, and the contributions of the different terms in the surface energy budget to the temperature variability are estimated. This analysis shows a clear relation in the model ensemble between temperature variability and the combined effects of downward long wave, net short wave radiation and evaporation (defined as F). However, it appears that the overestimation of the temperature variability has no unique cause. The effect of short-wave radiation dominates in some RCMs, whereas in others the effect of evaporation dominates. In all models the temperature variability and F increase when imposing future climate boundary conditions, with particularly high values in central Europe.     

格点降水资料在中国东部夏季降水变率研究中的适用性

本文使用1951~2010年PREC、CRU、APHRO和GPCC 4种格点降水资料,通过比较其与中国756站点观测降水资料在中国东部(105°E以东)夏季降水变率中的差异,检验和评估了它们的可靠性和适用性。结果表明:中国东部夏季降水变率的前3个主要模态分别是以江淮流域、长江流域和华北与东北南部为核心的经向多中心分布,有明显的年际和年代际变率特征,且干旱特征较洪涝更明显;长江流域夏季降水异常的主周期为3~7 a和20~50 a,而江淮流域和华北地区夏季降水异常的主周期则为准2 a和准10 a。另外,长江与江淮流域和华南地区分别在1970s末和1990s初发生了显著的年代际转变;4种格点降水资料都能很好地再现中国东部夏季降水的时空变率特征,但由于GPCC格点降水资料是基于更多的基站观测和更精细复杂的质量控制方案得到的,因此它具有更高的可靠性。     

A 1951–80 global land precipitation climatology for the evaluation of general circulation models

Previous evaluations of model precipitation fields have suffered from two weaknesses; they have used only mean observed climatologies which have prevented an explicit evaluation of interannual variability, and they have generally failed to quantify the significance of differences between model and observed fields. To rectify these weaknesses, a global precipitation climatology is required which is designed with model evaluation in mind. This paper describes such a climatology representative of the period 1951–80. The climatology is based on historical gauge-precipitation measurements from over 2500 land-based station time series representing over 28% of the Earth's surface. It is necessarily biased towards terrestrial areas. The climatology (CRU5180) is derived from month-by-month gridbox precipitation estimates at 5° resolution. Although other global precipitation climatologies exist, this is the first one to have used a consistent reference period for each station, and to include the details of interannual variability. Fields of mean seasonal and annual precipitation and mean temporal variability are presented, and the variability of global-mean precipitation over 1951–80 assessed. The resulting mean monthly global precipitation fields are compared briefly with two other observed climatologies used for model evaluation, those prepared by Jaeger and Legates and Willmott. The global and hemispheric means, mean seasonal cycles, and spatial patterns of the three cimatologies are compared. Although based on a smaller set of stations than Legates and Willmott, the CRU5180 precipitation estimates agree closely with their uncorrected climatology.     

Characterization of precipitation δ 18O variation in Nagqu, central Tibetan Plateau and its climatic controls

The stable isotopic composition of precipitation in different regions reflects climatic factors such as temperature, precipitation, moisture sources, and transport process. However, the isotopic variation in the region is usually much complicated due to the combined influences of these factors. A good understanding of climatic controls on the isotopic composition of precipitation can contribute to the study on isotopic tracer for climate and hydrology. To investigate the isotopic variation of precipitation and its climatic controls in the middle of the Tibetan Plateau, a monitoring station for stable isotope in precipitation has been established in Nagqu region, central Tibetan Plateau. We obtained 79 daily samples at Nagqu Meteorological Station in 2000. The observed δ ¹⁸O in precipitation showed a distinctly seasonal pattern with higher values in spring and winter and lower values in summer, despite of individually low values in winter due to extremely low temperature. To further understand this pattern, we evaluated the influence of temperature, precipitation, moisture sources, and moisture transport process on precipitation δ ¹⁸O. A multiple linear regression model represents quantitatively the dependence of precipitation δ ¹⁸O on precipitation and temperature: δ ¹⁸O_ppt?=??0.30P???0.11T???14.8 (R ²?=?0.13, n?=?79, P?=?0.005), which indicates δ ¹⁸O values in precipitation are more dependent on precipitation amount than on temperature. In contrast, when the temperature is low enough (<2°C), δ ¹⁸O values in precipitation are mainly dependent on temperature: δ ¹⁸O_ppt?=?0.53T???10.2 (R ²?=?0.44, n?=?19, P?=?0.002). The variation of δ ¹⁸O in precipitation is also closely related to moisture origins and transport trajectories. A model is set up to trace the trajectories for air masses arriving in the observed region, and the results demonstrated that humid marine air masses from the Indian Ocean generally have significantly lower δ ¹⁸O values than dry continental air masses from the north or local re-evaporation. During monsoon precipitation, the distance and depth of moisture transport as well as convective precipitation all lead to the large variability of δ ¹⁸O in precipitation.     

Dominant east-west pattern of diurnal temperature range observed across Zambia

Diurnal temperature range (DTR) is an important index for climate because of its statistical relationships to greenhouse gases, urban heat, cloud cover, land use change, and aerosol haze layers. This study examines DTR trends across Zambia for the period 1930–2016 using the latest version of high-resolution monthly data (CRU TS v4.01) from the Climatic Research Unit. Non-parametric trend analyses were extensively employed at different spatial and temporal scales to quantify DTR changes. Taken together, results show a dominant east-west pattern with higher DTR values being observed in the western half of the country. Although there are noticeable differences in the magnitude from one month to the other, this east-west pattern is persistent throughout all the months. It is also found that mean annual DTR is negatively correlated with mean annual cloud cover with a strong and statistically significant coefficient of -0.8 but its correlation with precipitation weakens to -0.5 at the α 0.05. Results from the Mann-Kendall trend test shows marginal increments in DTR during all the seasons and they are all statistically significant at the α 0.05. The observed increments can be attributed to a general decrease in cloud cover over Zambia.     

Variations of δ^18 O in Precipitation along Vapor Transport Paths

Three sampling cross sections along the south path starting from the Tropics through the vapor passage in the Yunnan-Guizhou Plateau to the middle-low reaches of the Yangtze River, the north path from West China, via North China, to Japan under the westerlies, and the plateau path from South Asia over the Himalayas to the northern Tibetan Plateau, are set up, based on the IAEA (International Atomic Energy Agency)/WMO global survey network and sampling sites on the Tibetan Plateau. The variations, and the relationship with precipitation and temperature, of the δ^18 O in precipitation along the three cross sections are analyzed and compared. Along the south path, the seasonal differences of mean δ^18 O in precipitation are small at the stations located in the Tropics, but increase markedly from Bangkok towards the north, with the 51so in the rainy season smaller than inthe dry season. The δ^18 O sovalues in precipitation fluctuate on the whole, which shows that there are different vapor sources. Along the north path, the seasonal differences of the mean δ^18 O in precipitation for the stations in the west of Zhengzhou are all greater than in the east of Zhengzhou. During the cold half of the year, the mean δ^18 O in precipitation reaches its minimum at Uriimqi with the lowest temperature due to the wide, cold high pressure over Mongolia, then increases gradually with longitude, and remains at roughly the same level at the stations eastward from Zhengzhou. During the warm half of the year, the δ^18 O values in precipitation are lower in the east than in the west, markedly influenced by the summer monsoon over East Asia. Along the plateau path, the mean δ^18 O values in precipitation in the rainy season are correspondingly high in the southern parts of the Indian subcontinent, and then decrease gradually with latitude. A sharp depletion of the stable isotopic compositions in precipitation takes place due to the very strong rainout of the stable isotopic compositions in vapor in the process of lifting over the southern slope of the Himalayas. The low level of the δ^18 O in precipitation is from Nyalam to the Tanggula Mountains during the rainy season,but δ^18 O increases persistently with increasing latitude from the Tanggula Mountains to the northern Tibetan Plateau because of the replenishment of vapor with relatively heavy stable isotopic compositions originating from the inner plateau. During the dry season, the mean δ^18 O values in precipitation basically decrease along the path from the south to the north. Generally, the mean δ^18 O in precipitation during the rainy season is lower than in the dry season for the regions controlled by the monsoons over South Asia or the plateau, and opposite for the regions without a monsoon or with a weak monsoon.     

Bulgarian mountains air temperatures and precipitation—statistical downscaling of global climate models and some projections

Measured air temperature and precipitation data from three high mountainous Bulgarian stations were used along with data from 18 global climate models (GCMs). Air temperature and precipitation outputs of preindustrial control experiment were compared with actually observed values. GCM with the best overall performance is BCCR BCM 2.0 for air temperatures (period 1941?C2009) and CGCM 3.1/T47 for precipitation (period 1947?C2009). Statistical methods were used in this research??nonparametric Spearman correlation, Mann?CWhitney test, multiple linear regression, etc. Projections were made for the following future decades: 2015?C2024, 2045?C2054 and 2075?C2084. The best months, described by multiple linear regression (MLR) model of air temperatures, are November, January, March, and May. The worst described are summer months. There is not any pattern in the relationship between constructed MLR models and measured precipitation. Models that perform the best in different months at the three investigated stations are MIUB ECHO-G, GISS AOM, CGCM 3.1/T63, and CNRM CM3 for air temperatures and GFDL CM 2.1, GISS AOM, and MIUB ECHO-G for precipitation. The fit between statistical models' outputs and values observed at stations is different, better in cold part of the year. There will be mixed future changes of air temperatures at all the three high mountainous stations. An increase of temperatures is expected in April, November, and December. A decrease will happen in February, July, and October. Mean annual temperatures are expected to rise by 0.1?°C (Botev) to 0.2?°C (Musala and Cherni vrah) in the decade 2075?C2084, but mean annual temperatures at the end of the period with measurements (2009) has already exceeded by far projected values. Trends in precipitation are mixed both in spatial and in temporal directions. Observed decrease of precipitation, especially in the warm half of the year, is not described well in MLR models. The same is valid for annual amounts, which are projected to be higher than those measured in the end of instrumental period (2009). This is opposite to observed trends in recent decades, especially at stations Cherni vrah and Botev, where a significant decrease of precipitation amounts has happened.     

北半球环状模和东北冷涡与我国东北夏季降水关系分析

利用国家气象信息中心提供的1951～2004年全国160个测站月平均降水资料和欧洲中心提供的ERA-40再分析资料,对近50多年东北地区夏季降水、东北冷涡与前期北半球环状模和海温的关系进行了统计分析,定义了一个夏季(6～8月)东北冷涡强度指数(NECVI)。结果表明:NECVI能够较好表征东北低涡的气候效应;夏季东北冷涡强度与降水存在显著的正相关,东北冷涡强年,降水偏多,前期2月北半球环状模(NAM)偏弱;东北冷涡偏弱年,降水偏少,前期2月NAM偏强。此外,夏季东北冷涡与前期的中国近海海温存在显著的负相关,前期NAM和中国近海海温的异常可以作为夏季东北冷涡异常的一个前兆信号,进而为东北地区夏季降水异常的预测提供参考依据。     

4种再分析月降水数据在内蒙古地区的适用性分析

利用1981—2020年气象台站的实测降水数据,对CRA40、ERA5、JRA55和MERRA2这4种再分析月降水数据在内蒙古地区的降水分布特征,与实测降水的相关性和误差进行分析。结果表明：（1）内蒙古地区4种再分析降水数据的空间分布与台站降水基本一致,误差分析表明CRA40与MERRA2的数据质量较高,ERA5次之,而JRA55数据质量相对较差。（2）CRA40和MERRA2在1983—1986年存在明显的降水低估,ERA5在2005年之后的内蒙古中东部出现明显的降水低估,JRA55在115°E以东存在明显降水高估,在115°E以西则以降水低估为主。（3）4种再分析月降水数据的年内最大均方根误差和绝对误差均集中在6—8月,与台站降水相关系数的年内最小值均出现在7月,内蒙古夏季汛期是再分析降水误差产生的主要时段。