Winter daily precipitation variability over the South West Peninsula of England

Summary Daily precipitation totals for five consecutive winters (1995–99) were obtained for 127 stations in Devon and Cornwall to explore spatial variations in rainfall. This dataset was assembled with the explicit aim of assessing the appropriateness of current arrangements for daily rainfall forecasts in the SW Peninsula of England. Firstly, the extent to which fundamental geographic variables determine precipitation was investigated by correlating each station’s mean wet day amount (WDA) and percentage of wet days (PERWET) with altitude, latitude, longitude and distance from the coast. Altitude emerged as the most important control on precipitation, with a two-variable multiple linear regression model containing altitude and latitude being able to explain 39.3% (29.8%) of the variance in WDA (PERWET) values. The main spatial modes of variability in the region’s precipitation field were identified by using S mode principal components analysis (PCA). Six PCs were statistically significant and explained 83.4% of the geographic variance in precipitation over Devon and Cornwall. The components were interpreted physically by examining the synoptic flow environment (pressure and wind anomalies) on days with high positive and negative PC scores. Explaining 25.1% of the variance, the most important pattern (PC1) depicts a location’s degree of exposure or shelter in a moist, unstable W–NW airflow. The higher PCs describe modes of variability that accentuate rainfall in East Devon (PC2), Cornwall (PC3), Dartmoor and Bodmin Moor (PC4), South Devon (PC5), and North Cornwall and NW Devon (PC6) relative to other areas of the Peninsula. Finally, a winter precipitation regionalisation was derived by applying agglomerative hierarchical cluster analysis to the PC loadings of the significant components. In most cases, the six coherent precipitation regions do not reflect the familiar administrative or topographic areas used for forecasting, suggesting that forecasts issued on such a basis are likely to be insufficiently detailed and misleading.     

Recent trends in seasonal and annual precipitation indices in Tuscany (Italy)

Global warming alters the hydrological cycle since a rise in temperature leads to an increase in the moisture-holding capacity of the atmosphere at a rate of about 7 %/°C. This fact can influence the global, but also local characteristics of precipitation, such as total amount and intensity. Therefore, it is important to study changes in rainfall regime in regions with complex orography, like Tuscany, where there are strong spatial gradients in precipitation amounts. The aim of this study is to look for temporal change in precipitation from 1955 to 2007 searching for spatial differences. Daily data of 21 meteorological stations were analyzed to identify trends in seasonal and annual precipitation indices. Cluster analysis applied to principal components was applied to identify homogeneous groups of stations. A decrease in precipitation was observed at annual time scale, during winter and spring, especially in northwestern areas. Wet days highlighted a decrease in all of Tuscany, due to the same seasons. In northern Tuscany, the decrease in rainfall amount was mainly determined by a lower frequency of rainy events which in turn caused a decrease in the occurrence of extreme daily precipitation events (75th, 90th, and 95th percentile). In central-southern Tuscany, no significant changes were observed except for an increase in precipitation fraction, due to extreme events and in mean daily total amount for wet days. These results are consistent with recent findings for the Mediterranean area and confirm the usefulness of cluster analysis for the analysis of the spatial distribution of precipitation.     

柴达木盆地降水的时空分布特征

利用柴达木盆地11个国家气象站(2017年3月—2018年2月)及28个区域气象站(2017年6—8月)月降水量资料,运用线性回归订正法和比值订正法推算柴达木盆地的年降水量,进一步分析柴达木盆地降水量季节变化及空间分布特征。结果表明:(1)柴达木盆地降水量年内分配极不均匀,呈单峰性,峰值出现在7月,5—9月(汛期)降水量占全年的87.4%。季节差异非常明显,降水主要集中在夏季;(2)年降水量空间分布特征:柴达木盆地年降水量各地差异极为显著,降水量整体表现为从东向西逐渐减少。最大值出现在天峻,最小值出现在冷湖。用2种方法推算的年降水量最大值出现在柴达木盆地东北部祁连山南麓的木里镇,其次在格尔木市南部出现了两个相对的大值中心,中间区域(93°～97°E)由四周山区向盆地中心逐渐减少的形势表现得更加清晰。夏季降水量的空间分布与年降水量的空间分布完全一致。(3)国家气象站模型中降水量分布只受经度和海拔高度的影响,而线性回归法和比值订正法模型中降水量的分布不仅受经度和海拔高度的影响,还受纬度的影响,三者的贡献率由大到小的排序是经度海拔高度纬度。     

Uncertainty analysis of statistical downscaling models using Hadley Centre Coupled Model

Regression-based statistical downscaling is a method broadly used to resolve the coarse spatial resolution of general circulation models. Nevertheless, the assessment of uncertainties linked with climatic variables is essential to climate impact studies. This study presents a procedure to characterize the uncertainty in regression-based statistical downscaling of daily precipitation and temperature over a highly vulnerable area (semiarid catchment) in the west of Iran, based on two downscaling models: a statistical downscaling model (SDSM) and an artificial neural network (ANN) model. Biases in mean, variance, and wet/dry spells are estimated for downscaled data using vigorous statistical tests for 30 years of observed and downscaled daily precipitation and temperature data taken from the National Center for Environmental Prediction reanalysis predictors for the years of 1961 to 1990. In the case of daily temperature, uncertainty is estimated by comparing monthly mean and variance of downscaled and observed daily data at a 95 % confidence level. In daily precipitation, downscaling uncertainties were evaluated from comparing monthly mean dry and wet spell lengths and their confidence intervals, cumulative frequency distributions of monthly mean of daily precipitation, and the distributions of monthly wet and dry days for observed and modeled daily precipitation. Results showed that uncertainty in downscaled precipitation is high, but simulation of daily temperature can reproduce extreme events accurately. Finally, this study shows that the SDSM is the most proficient model at reproducing various statistical characteristics of observed data at a 95 % confidence level, while the ANN model is the least capable in this respect. This study attempts to test uncertainties of regression-based statistical downscaling techniques in a semiarid area and therefore contributes to an improvement of the quality of predictions of climate change impact assessment in regions of this type.     

乌鲁木齐市地理地形因素对降水空间分布的影响

提供了一个描述乌鲁木齐市年、季降水空间分布的估算模型.利用中国气象局整编的气象站点信息资料和位于研究区域的3个站点(乌鲁木齐、达坂城、蔡家湖)从建站到2000年的多年降水资料,采用多元逐步回归方法,分析和估算了3个地理、地形影响因子(即经度、纬度、海拔高度)对乌鲁木齐市降水空间分布的影响,并对回归方程和影响因子进行了显著性检验,得出了一些定性、定量的结果.本文模型估算的降水能够较好地再现该区的实际降水分布,具有一定的适用价值.     

湖北省主要山系高影响天气指标空间特征分析与建模

为了揭示湖北省主要山系高影响天气指标空间分布特征,利用湖北省内1716个气象站点2016-2018年逐日气温、降水资料,定义6个高影响天气指标,利用GIS空间插值方法,绘制了湖北省高影响天气指标的空间分布图。选取7个湖北主要山系坡面,分析各个坡面上高影响天气指标的海拔梯度变化特征。根据湖北主要山系分布将湖北分为8个区,利用DEM数据,采用多元回归分析方法,建立各个区域内高影响天气指标和经度、纬度、海拔高度和坡度这4个地理因子之间的关系模型。结果表明,模型相关性显著,对估算模型进行F检验,大部分通过置信度为0.95的相关性检验。研究结果可为湖北山区风电建设、旅游开发、风险区划等提供参考依据。     

Accuracy of TRMM precipitation data in the southwest monsoon region of China

Accurate, high-resolution precipitation data is important for hydrological applications and water resource management, particularly within mountainous areas about which data is presently scarce. The goal of the this study was to assess the accuracy of TRMM 3B43 precipitation data from the southwest monsoon region of China between 1998 and 2011 based on the correlation coefficients, regression, and geostatistical methods. We found a strong correlation between TRMM 3B43 data and observational data obtained from meteorological stations, but the TRMM 3B43 precipitation data was consistently lower than that obtained from the weather stations. The TRMM 3B43 data was significantly different from the data obtained by weather stations located in the northwest and northeast regions of the Hengduan Mountains. The spatial distribution of precipitation obtained from TRMM 3B43 was also different from meteorological data, but the deviation was predominantly distributed along the northern longitude and southern latitude. In addition, the TRMM data more accurately reflected the regional precipitation patterns. Our results indicate that the TRMM 3B43 data should be used for hydrological applications and water resource management at meteorological stations that have a sparse and uneven distribution of observation stations in the southwest monsoon region.

     

东北地区逐日气象要素的空间插值方法应用研究

针对作物生长动力模型区域应用时对高精度格点逐日气象要素输入值的需要，以东北地区为例，选用克立格法 (Kriging)、以经纬度分布方向为权重的距离权重反比法（IDW）及带高度梯度订正的距离权重反比法（GIDW）3种插值方法进行有限气象站点4~10月逐日气象要素空间插值方法研究，并进行插值的统计量分析和估值的交叉验证。结果表明，对温度而言，GIDW方法估值精度较高，插值结果的平滑程度适中，插值结果分布趋势也较为接近实际站点的分布。对降水而言，IDW估值精度高于Kriging, 而且插值结果的平滑程度较小，更适合于日降水量的空间插值。GIDW、IDW估值精度较高的原因是研究中考虑到日最高温度、最低温度和降水量的经向、纬向梯度、海拔高度梯度存在明显的季节性变化，采用了根据气象要素经纬度方向确定权重，以及根据气象要素高度梯度年内变化进行高度订正的结果。     

1980-2020年山西省极端降水的研究

基于1980-2020年山西省109个气象观测站点的逐日降水资料,选取10个极端降水指数,采用气候倾向率、相关分析、因子分析、R/S预测方法等方法,对山西省极端降水进行了时空分布的研究,以期为山西省的气候变化、生态环境保护、防灾减灾、气象服务工作提供参考依据,结果表明：(1)从时间尺度来看,1980-2020年期间,山西省极端降水的强度和极值都有明显增加,连续干旱日数和连续湿日日数呈下降趋势,其余均表现出不同程度的增加,其中年总降水量增加幅度最明显;从空间尺度来看,年总降水量、降水强度、降水频率、极值均为从西北向东南逐渐增多,空间差异较明显;从各站点的空间分布来看,北部和中部地区的极端事件增加最显著,北部地区的干旱日数仍以增加趋势为主,连续湿日日数气候倾向率的空间差异较大,中部地区站点显著增加,南北部以减少趋势为主;(2)基于相关分析方法表明各极端降水指数(除干旱日数外)与年总降水量都有很好的相关关系,强降水量和极强降水量对年总降水量的贡献值呈现出增加趋势;采用因子分析方法提取了3个公共因子,方差贡献率累计达到了87％,可以看出极端降水强度和降水量指数在对极端降水方面影响较大;利用R/S分析法可以得到年总降水量、中雨日数、大雨日数、最大5日降水量这几个指数未来呈现弱减少趋势,而干旱日数仍为减少趋势,连续湿日日数为持续弱增加趋势。总体看来,山西省极端降水近年来呈现出增加趋势,在空间分布有明显差异。     

Multisite statistical downscaling model for daily precipitation combined by multivariate multiple linear regression and stochastic weather generator

This study provides a multi-site hybrid statistical downscaling procedure combining regression-based and stochastic weather generation approaches for multisite simulation of daily precipitation. In the hybrid model, the multivariate multiple linear regression (MMLR) is employed for simultaneous downscaling of deterministic series of daily precipitation occurrence and amount using large-scale reanalysis predictors over nine different observed stations in southern Québec (Canada). The multivariate normal distribution, the first-order Markov chain model, and the probability distribution mapping technique are employed for reproducing temporal variability and spatial dependency on the multisite observations of precipitation series. The regression-based MMLR model explained 16?%?~?22?% of total variance in daily precipitation occurrence series and 13?%?~?25?% of total variance in daily precipitation amount series of the nine observation sites. Moreover, it constantly over-represented the spatial dependency of daily precipitation occurrence and amount. In generating daily precipitation, the hybrid model showed good temporal reproduction ability for number of wet days, cross-site correlation, and probabilities of consecutive wet days, and maximum 3-days precipitation total amount for all observation sites. However, the reproducing ability of the hybrid model for spatio-temporal variations can be improved, i.e. to further increase the explained variance of the observed precipitation series, as for example by using regional-scale predictors in the MMLR model. However, in all downscaling precipitation results, the hybrid model benefits from the stochastic weather generator procedure with respect to the single use of deterministic component in the MMLR model.     

1961-2010 年东北地区降水事件时空均匀性研究

利用1961-2010年东北三省和内蒙古四盟90个气象站逐日降水资料,分析了中国东北地区降水事件的气候特征及时空分布均匀性变化。结果表明：近50 a来,东北地区年降水量略有减少,但冬、春季降水量显著增加;考虑降水日数,冬、春季降水量增加主要是由于降水强度的增加,夏、秋季降水量减少主要是由于降水频次的减少。气候变暖的大背景下,虽然年降水量线性变化趋势并不明显,但是降水量年际间分布不均匀性增加,降水有向极端化发展的趋势,夏、秋季表现更为明显,各等级降水事件尤其是降雪在近20 a时间分布明显不均匀。降水量空间均匀性在1993年发生转折突变,突变后空间不均匀性增加,降水日数空间均匀性在1986年发生变率突变,突变后振荡加剧。降水事件时空不均匀性的增加一定程度上造成了东北地区旱涝事件发生可能性增加,不同地域旱涝事件同发现象加剧。     

引入低纬高原复杂地形因子的气象要素精细化估算模型

低纬高原地区的气象要素变化除了受大气环流因子的影响外,高程、坡度、坡向等地理因子的作用不可忽视.以云南省为例,应用云南省125个气象站的降水、温度、露点温度等气象资料,与各站点的经度、纬度、高程、坡向、坡度等地理因子建立关系模型,运用多元回归方法,求得回归系数,代入随机抽取的检验站点的地理因子回归方程式中,得出拟合量,...     

Intraseasonal variability in subtropical South America as depicted by precipitation data

Daily precipitation data from three stations in subtropical Argentina are used to describe intraseasonal variability (20–90 days) during the austral summer. This variability is compared locally and regionally with that present in outgoing longwave radiation (OLR) data, in order to evaluate the performance of this variable as a proxy for convection in the region. The influence of the intraseasonal activity of the South American Seesaw (SASS) leading convection pattern on precipitation is also explored. Results show that intraseasonal variability explains a significant portion of summer precipitation variance, with a clear maximum in the vicinity of the SASS subtropical center. Correlation analysis reveals that OLR can explain only a small portion of daily precipitation variability, implying that it does not constitute a proper proxy for precipitation on daily timescales. On intraseasonal timescales, though, OLR is able to reproduce the main features of precipitation variability. The dynamical conditions that promote the development of intraseasonal variability in the region are further analyzed for selected summers. Seasons associated with a strong intraseasonal signal in precipitation variability show distinctive wet/dry intraseasonal periods in daily raw data, and are associated with a well defined SASS-like spatial pattern of convection. During these summers, strong large-scale forcing (such as warm El Niño/Southern Oscillation (ENSO) events and/or tropical intraseasonal convective activity), and Rossby-wave-like circulation anomalies extending across the Pacific Ocean, are also observed.     

空间分辨率对中国夏季降水时空演变特征的影响

本文使用1979—2021年国家气候中心160站(R₁₆₀)和国家级地面气象观测站2 314站(R₂₃₁₄)逐月降水观测资料,利用EOF (Empirical Orthogonal Function)分解和相关分析等方法,研究两类资料夏季降水时空变化特征及其与海气因素之间物理联系的表征水平差异,并分析了差异的可能原因。结果表明,R₁₆₀在我国西北、青藏高原等地区站点极为稀疏,导致其各EOF模态对上述地区降水的时空变化特征描述失真,中东部地区偏低的空间分辨率会使局地强降水的变化特征信号损失,造成降水的年际变率降低。而R₂₃₁₄主模态能够更为真实地反映我国降水的时空演变特征,特别是在极端降水频发的江淮地区以及降水受局地地形影响较大的山区,其EOF主模态的空间分布和时间系数演变与ENSO (El Niño-Southern Oscillation)、西太平洋副热带高压、青藏高原雪盖等气候强迫信号之间的相关性更为显著。     

Uncertainty analysis of statistical downscaling models using general circulation model over an international wetland

Regression-based statistical downscaling model (SDSM) is an appropriate method which broadly uses to resolve the coarse spatial resolution of general circulation models (GCMs). Nevertheless, the assessment of uncertainty propagation linked with climatic variables is essential to any climate change impact study. This study presents a procedure to characterize uncertainty analysis of two GCM models link with Long Ashton Research Station Weather Generator (LARS-WG) and SDSM in one of the most vulnerable international wetland, namely “Shadegan” in an arid region of Southwest Iran. In the case of daily temperature, uncertainty is estimated by comparing monthly mean and variance of downscaled and observed daily data at a 95 % confidence level. Uncertainties were then evaluated from comparing monthly mean dry and wet spell lengths and their 95 % CI in daily precipitation downscaling using 1987–2005 interval. The uncertainty results indicated that the LARS-WG is the most proficient model at reproducing various statistical characteristics of observed data at a 95 % uncertainty bounds while the SDSM model is the least capable in this respect. The results indicated a sequences uncertainty analysis at three different climate stations and produce significantly different climate change responses at 95 % CI. Finally the range of plausible climate change projections suggested a need for the decision makers to augment their long-term wetland management plans to reduce its vulnerability to climate change impacts.     

1961-2012年夏季南亚高压与云南地区降水的关系

基于1961-2012年NCEP/NCAR月平均再分析资料和云南地区124个观测站月降水资料,利用相关分析法分析夏季南亚高压与云南地区降水的关系。结果表明：1961-2012年夏季滇西南地区降水与南亚高压主中心经度呈较显著负相关,滇南地区降水与南亚高压面积呈较显著负相关;6月滇西北和滇南地区降水与南亚高压脊线位置、高压主中心纬度呈显著正相关,滇西南地区降水与南亚高压主中心强度呈显著正相关,而与南亚高压主中心经度呈显著负相关,滇中地区降水与南亚高压主中心纬度呈显著正相关;7月滇西南、滇西北的西南部和滇西的北部地区降水与南亚高压脊线位置呈较显著正相关,滇西地区降水与南亚高压主中心强度呈较显著负相关,滇中和滇东地区降水与南亚高压主中心经度呈较显著负相关;8月滇西南、滇中、滇南和滇东地区降水与南亚高压面积呈显著负相关。     

Spatiotemporal variations in climate moisture indices in Georgia under global warming

Using observational data from 50 weather stations in Georgia for the period of 1936-2013, the following climate indices of moisture regime are studied: maximum 1-day precipitation, maximum 5-day precipitation, the simple daily intensity index, the number of days with precipitation equal to not less than 10, 20, and 50 mm, number of consecutive wet and dry days. Geoinformation maps of the spatial structure are plotted, and the dynamics of these indices is studied for the period of global warming. Expected changes in the moisture regime in different physiographic regions in Georgia are assessed.     

秦岭山区近50 年降水差异及可能局地成因探讨

利用秦岭山区54个气象站50年以上日降水资料,分析了复杂地形下小区域降水变化差异,探讨了可能的局地成因,结果表明:(1)年均降水量总体为南高北低、西高东低,反映出秦岭阻挡作用和山谷东风回流影响;(2)近50年来区域年降水以减为主,9个增加站位于东部,夏季降水以增加为主,减少站集中在秦岭山上和区域西部,降水向夏季集中倾向明显;(3)日雨量小于5 mm的年雨量和雨日数减少趋势明显,雨量≥50 mm的年雨量和雨日数增加趋势明显,即小雨减少大雨增多;(4)降水变化的多个方面及其与海拔高度和经度对应关系的分析结果,反映出气溶胶抑制地形降水以及成冰作用恢复被抑制降水的作用,说明局地成因中气溶胶起了不可忽视作用;(5)地形作用和区域能量平衡也是重要局地成因.     

Climatology and trends of wet spells in China

Summary Climatological features and variations of wet spells, especially their trends over China, are investigated using a dataset of 594 meteorological stations across China from 1951 to 2003. The results show that the lower the latitude is, the longer the annual duration of wet spells is. The mean annual precipitation from wet spells is higher in southeastern coastal areas and much lower in western and northern China. The longest wet spells are found in Southwest China and the eastern Tibetan Plateau. The maximum daily precipitation of wet spells decreases from the southeast to the northwest, with the highest in southeastern coastal areas and the lowest in western China. The trends of wet spells exhibit striking regional differences. In most areas of western China, the annual number of days in wet spells has slightly increased, but significantly decreased over North China, Central China and Southwest China. The annual precipitation amount from wet spells displays significant downward trends in North China, eastern Northeast China and the eastern part of Southwest China, but upward trends in the eastern Tibetan Plateau and some southeastern coastal areas. Two clearly-contrasting regions in climatic changes of wet spells are the mid-lower reaches of the Yellow River and the eastern Tibetan Plateau, characterized by a decrease of about 24 days and an increase of about 6 days in annual wet spell days from 1953 to 2003, respectively.     

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。