CLIGEN在华北地区生成降水的效能评估

为了检验天气发生器CLIGEN在华北地区生成降水的有效性,应用该区15个气象站1951-2008年的日气象观测资料和CLIGEN生成的150a日气象数据,对CLIGEN再现该区降水的效能进行了评估。结果表明:CLIGEN很好地再现了年和日降水量的均值和降水日数,但对降水极值的模拟精度不高,年和日最大降水量的平均相对偏差均大于均值的平均相对偏差。非参数检验的结果表明,CLIGEN能很好地生成年降水量的概率分布,且对日降水的概率分布也有较高的生成精度。总体来看,CLIGEN模型在华北地区能很好地再现年、日降水量平均值统计特征,并较好地再现了降水的变率。     

CLIGEN气候生成器模型在紫色土地区的适应性研究

随机气候生成器CLIGEN模型可以为当前一些综合模型所需要的气象资料提供必要的数据支持,为检验CLIGEN在四川紫色土地区的适用性,以CLIGEN模型为研究平台,根据四川省遂宁水土保持实验站1987～2002年降水和气温的月平均资料及在全美范围内选择参照站点得到的其他气象因子,利用CLIGEN模型分别模拟出遂宁市的月平均降水量、月平均最高温度和月平均最低温度。结果证明用所选的3个参证站点,利用CLIEGN模拟出来的降水、气温在数值上和年内的分布上均与实测值较为符合,选择模型有效系数E和平均绝对百分比误差（MAPE）为评价指标,作为3个站点最优选择的指标,最终选择CENTERVILLE站点为最优参证站,CEN-TERVILLE站点的模拟月平均降雨量、月平均最高温度和月平均最低温度的相对平均绝对值（MAPE）分别为7.15%,7.03%和6.17%,而有效系数分别为0.996 2,0.926 6和0.995 7,从而确定了CLIGEN模型在遂宁紫色土地区的适用性。     

CLIGEN天气发生器在长江上游地区的适用性评价

CLIGEN天气发生器是WEPP土壤侵蚀模型的组成模块之一,用于模型预测预报以及天气数据缺测时生成模拟天气数据;但是CLIGEN天气发生器是基于美国的天气条件研发的,在其他地区模拟的精度具有不确定性.以长江上游沱沱河站、马尔康站、丽江站、都江堰站和沙坪坝站5个典型国家气象站40年的日观测数据为基础,分析评价CLIGEN天气发生器在该地区模拟的日和月天气数据的精度.结果表明：CLIGEN天气发生器天气参数的输入对于模拟结果具有较大的影响;模拟结果在长江上游5个不同地貌区气象站的精度基本相当;模拟的日天气数据误差较大,模拟的月天气数据效果好于日天气数据;模拟的各月最高气温和最低气温平均值较实际值偏低,部分参数模拟值的绝对误差和相对误差存在一定的月际差异.     

丽水市短历时降水特征

利用1981～2010年丽水市国家气象观测站分钟降水强度资料,分析10个降水历时(5、10、15、20、30、45、60、90、120、180 min)分布特征并计算其气候倾向率,采用广义极值分布和线性参数估计方法,拟合年最大降水量概率分布,采用柯尔莫哥洛夫检验进行拟合优度检验。经检验得出如下结论:1)丽水市短历时年最大降水量极值均出现在6～8月,各历时年最大降水量呈增加的趋势;2)10个短历时年最大降水量采用广义极值分布拟合,效果较好,均通过信度0.05显著性检验。随历时增加,降水强度和变化幅度逐渐增大;形状参数随历时增加呈现先增后减的趋势。     

GPM与TRMM降雨数据在黄河流域适用性分析

GPM(Global Precipitation Measurement)是继TRMM(Tropical Rainfall Measuring Mission)之后的新一代全球卫星降水测量计划。GPM扩展了TRMM传感载荷,提升了降水观测能力。以GPM和TRMM重合期(2014年3月—2015年4月)数据为对象,利用黄河流域内76个气象站点的降雨实测数据,探讨了两种卫星降水数据在黄河流域的适用性,并分析了流域内两种卫星降水数据误差的时空分布。结果表明:年尺度上,GPM与TRMM卫星数据与实测降水量的决定系数分别为0.78,0.86,总体一致性较好,但分别存在2.46%与2.19%的相对高估。季节尺度上,春、秋两季数据精度高,夏季卫星降水数据相对于实测降水量存在较大的绝对误差,冬季则相对误差较大。月尺度上,除7月、8月外卫星降水数据均大于实测降水量,相对误差最大值出现在12月,绝对误差最大值出现在9月。单站点验证结果表明GPM与TRMM卫星降水数据在流域北部的陶乐、惠农、临河等区域数据精度偏低,而在广大的流域中南部区域卫星降水数据与实测降水量有较高的一致性。     

CLIGEN非降水参数在黄土高原的适应性评估

 天气生成器(CLIGEN)可以产生以日为时间单元的天气数据,从而广泛应用于土壤侵蚀和作物生长模拟模型,其模拟结果的优劣直接影响这些模型的输出结果。利用散布黄土高原的12个标准气象站点长时间序列的气候数据评估CLIGEN模拟非降水参数(温度、太阳辐射、风速)的能力。结果表明:CLIGEN能较好的模拟日最高温度;对日最低温度与露点温度的模拟次之;模型对太阳辐射和风速的模拟较差,特别是对风速的模拟,模拟值要显著的高于实测值。CLIGEN模拟的温度日较差、第1天最高温度与第2天最低温度之差、第2天最高温度与第1天最低温度之差的均值和标准差普遍偏高,但均值的误差较小,而标准差被过高模拟;模型在产生气候数据时,没有保持逐日渐变性和连续性。CLIGEN能够较好的模拟最高温度与最低温度的季节连续性与相关性;而过高的模拟了太阳辐射的季节相关性以及温度与太阳辐射的季节互相关性;同时,模型没有模拟出各气象要素自身及其之间的逐日相关性。     

不同订正方法下CFSR再分析数据在天山西部山区径流模拟中的应用

以天山西部山区喀什河流域为典型研究区,基于1990-2000年的水文气象站点实测资料、2005年喀什河流域遥测降水数据及各时间段对应的CFSR(Climate Forecast System Reanalysis)再分析数据,通过实测站与其最近CFSR站多年月平均降水的比值,CFSR站点处2005年的年降水量与同期遥测年降水量的比值,以及基于实测站点降水数据和各CFSR站点与实测站点最近的CFSR站点的空间关系3种方法对CFSR降水数据进行订正。借助VIC模型,分析不同订正方法下研究区径流的模拟效果。降水时间序列分析结果表明,CFSR降水数据能够较好地在时间和空间上反应喀什河流域内月降水的变化情况。径流模拟结果表明,(1)CFSR降水数据的不同订正方法对径流结果影响较为明显;(2)基于实测站点降水数据以及各CFSR站点与实测站点最近的CFSR站点的空间关系订正的所有CFSR降水,在径流模拟中表现最好,模型率定期和验证期的模型效率系数均在0.80以上,多年径流相对误差在15.0%以内。该订正方法不仅考虑了降水在时间维度上的变化,还考虑其在地理空间维度的变化,较其它两种方法在径流模拟中具有更好的应用前景。     

TRMM卫星降水产品降尺度及其在湘江流域水文模拟中的应用

高时空分辨率降水数据对准确刻画区域降水时空变化特征、精准模拟区域生态和水文过程具有重要的现实意义。以湘江流域为例,在考虑地理、地形和植被等多重要素的基础上,建立了基于地理加权回归法（Geographic Weighted Regression,GWR）的热带降雨测量卫星（Tropical Rainfall Measuring Mission,TRMM）降水降尺度模型,并采用比例指数法反演得到星地融合日降水Ⅰ、Ⅱ、Ⅲ三种产品,用来驱动土壤和水评估模型（Soil and Water Assessment Tool,SWAT）,分析评估其在水文模拟中的应用潜力。结果表明：1）GWR降尺度后,在TRMM降水空间分辨率由0.25°提升至0.05°的同时,同气象站点观测月降水之间的决定系数（R2）平均提升了0.33,均方根误差（RMSE）平均降低了43.30 mm,平均相对偏差（Average Relative Error,ARE）平均降低了38.71%,表明该降尺度模型在湘江流域TRMM月降水降尺度研究中具有良好的适用性;2）与TRMM日降水量相比,星地融合日降水Ⅲ产品同气象站点观测日降水量的R2提高了0.81,RMSE降低了10.27 mm,ARE降低了0.11%,表明以气象站点观测日降水量作比例指数展布星地融合月降水是可行有效的;3）星地融合日降水Ⅲ产品在SWAT模型日、月径流模拟中的纳什效率系数最大,分别为0.79、0.93,相对误差最小,分别为0.12%、1.10%,水文模拟效果最优,可替代气象站点和TRMM卫星降水进行水文模拟。研究结果可为气象站点稀缺区域的高精度降水资料获取和高效水文模拟提供数据支撑和方法借鉴。     

鄱阳湖流域降水量变化对水沙演变影响研究

利用鄱阳湖流域"五大"入湖河流控制水文站实测水沙资料,探讨了鄱阳湖流域1961—2006年水沙变化特征及其演变趋势,在此基础上应用线性回归分析方法揭示了鄱阳湖流域水沙演变过程对流域降水的响应。研究结果表明,1961—2006年鄱阳湖流域降水量和入湖径流量总体略呈上升趋势,降水日数呈下降趋势,表明降水强度增加、降水时间分布不均匀更加明显。鄱阳湖流域降水和径流基本符合幂函数关系。相关分析结果显示,鄱阳湖入湖泥沙总量和径流量、降水量、降水强度均具有很好的正相关关系,水体中的泥沙含量和径流系数具有很好的负相关性,说明流域降水量和降水强度均对流域产沙量和输沙量有促进作用;流域月降水量与月输沙量基本符合幂函数关系,进一步说明了流域产沙量是降水量和降水强度综合作用的结果。     

CLIGEN天气发生器在黄河流域的适应性研究

根据年降水及其年内分布特征在全美范围内选择参照站的基础上,用黄河流域3个气象站30年降水和气温的月平均资料,对CLIGEN天气发生器在黄河流域的适应性进行了检验。结果表明利用参证站、通过月资料的输入,CLIGEN可以较好地模拟年降水、降水的月分布、最高温度和最低温度,模拟值的标准差普遍低于实际值的标准差,参照站的气候特征对模拟结果有显著影响,因此,在参证站选择时应综合考虑多个气象参数。     

Evaluation of CLIGEN for storm generation on the semiarid Loess Plateau in China

The Stochastic generation of storm patterns is often necessary for driving process-based hydrological and ecological models. CLIGEN is the only weather generator being able to generate internal storm patterns. Its goodness needs to be evaluated for its proper application. This paper aims to find the advantages and limitations of CLIGEN on semiarid areas and provide references for custom-built weather generators for the Loess Plateau. The daily rainfall time series (1957–2002) and breakpoint rainfall data (more than 20 years) on six stations on the Loess Plateau were used to estimate input parameters for CLIGEN and to compare with CLIGEN-generated 50 years of storm data. Precipitation occurrence (wet day and dry day sequence) is well-simulated without significant difference across months and sites. Errors of monthly average number of wet days range from − 0.67 to 1.08 days, standard deviations range from − 1.19 to 0.76 days, and the distributions of continuous number of wet and dry days on the semiarid Loess Plateau are adequately simulated. Daily rainfall amount is not simulated as well as precipitation occurrence. The relative errors of average daily rainfall range from − 12.93% to 8.64% and those of standard deviations range from − 21.35% to 27.46%. During the rain seasons (May–September), among 30 month–location combinations, all the Mann–Whitney tests for the means passed, 47% for squared ranks tests rejected the null hypothesis of equality of standard deviations, and 73% for K–S test suggested that the generated and measured distributions of daily rainfall were different at 0.01 level of significance Three variables to describe internal storm patterns in CLIGEN are storm duration, relative peak intensity, and time to peak. Storm duration was not well-reproduced because none of squared ranks tests and K–S test passed at the significance level of 0.01. The frequency of short duration storms (< 300 min) was over-predicted while frequency of long duration storms (400–1200 min) was significantly under-predicted. The distribution of maximum 5 min rainfall intensity (ip₅) was well-simulated for four sites out of the six because all tests passed. However, generated maximum ip₅ for all six sites are around 190 mm/h, which are much larger than the measured (70 to 150 mm/h). Ip₃₀ is simulated better than ip₅, suggesting that CLIGEN can reliably generate rainfall erosivity. Time to peak was well-simulated because all the tests passed with P values significantly greater than the significance level of P = 0.01. Improvement for CLIGEN has to be made in terms of the daily rainfall simulation in rainfall-concentrated seasons and storm pattern generation in order to generate reliable rainfall time series on the Loess plateau.     

WGDWS天气发生器在中国五大气候区的适用性

为了检验基于干湿期的天气发生器(Weather Generator based on Dry and Wet Spells,WGDWS)在中国不同气候区的应用效果,该研究利用中国五大主要气候区16个站点57 a的逐日天气数据,通过对比生成与实测气象要素统计值,及比较WGDWS与随机天气模拟器(Daily Weather...     

Simulating site-specific impacts of climate change on soil erosion and surface hydrology in southern Loess Plateau of China

Proper spatial and temporal treatments of climate change scenarios projected by General Circulation Models (GCMs) are critical to accurate assessment of climatic impacts on natural resources and ecosystems. The objective of this study was to evaluate the site-specific impacts of climate change on soil erosion and surface hydrology at the Changwu station of Shaanxi, China using a new spatiotemporal downscaling method. The Water Erosion Prediction Project (WEPP) model and climate change scenarios projected by the U.K. Hadley Centre's GCM (HadCM3) under the A2, B2, and GGa emissions scenarios were used in this study. The monthly precipitation and temperature projections were downloaded for the periods of 1900–1999 and 2010–2039 for the grid box containing the Changwu station. Univariate transfer functions were derived by matching probability distributions between station-measured and GCM-projected monthly precipitation and temperature for the 1950–1999 period. The derived functions were used to spatially downscale the GCM monthly projections of 2010–2039 in the grid box to the Changwu station. The downscaled monthly data were further disaggregated to daily weather series using a stochastic weather generator (CLIGEN). The HadCM3 projected that average annual precipitation during 2010–2039 would increase by 4 to 18% at Changwu and that frequency and intensity of large storms would also increase. Under the conventional tillage, simulated percent increases during 2010–2039, compared with the present climate, would be 49–112% for runoff and 31–167% for soil loss. However, simulated soil losses under the conservation tillage during 2010–2039 would be reduced by 39–51% compared with those under the conventional tillage in the present climate. The considerable reduction in soil loss in the conservation tillage indicates the importance of adopting conservation tillage in the region to control soil erosion under climate change.     

Adjustment of CLIGEN parameters to generate precipitation change scenarios in southeastern Australia

Global climate model predictions are often downscaled with stochastic weather generators to produce suitable climate change scenarios for impact analysis. Proportional adjustment to generated daily precipitation and direct adjustment to parameter values for weather generators have been used for assessing the impact of climate change on runoff and soil loss. Little is known of how these parameter values should be realistically adjusted, the amount of adjustment, and whether the adjustments are correlated among different parameters. Rainfall in southeastern Australia has significantly increased since the late 1940s. Rainfall records in Sydney show a similar trend. Long term daily and 6-min intensity data from Sydney have made it possible to examine how CLIGEN parameter values have changed in relation to the underlying significant increase in rainfall. This study shows that for Sydney, most of the increase in rainfall is a result of the increase in wet day precipitation. The increase in the standard deviation of wet-day precipitation is greater than that in the mean, implying a greater rainfall variability during wetter periods. The wet-following-wet transition probability, and maximum 30-min rainfall intensity are all positively and significantly correlated with the change in wet-day precipitation. The change in peak intensity is about half the change in rainfall. No significant relationship can be established between the changes in mean monthly rainfall and those in the skewness coefficient for wet day precipitation and wet following dry transition probability for the site. Simultaneous adjustment of all these parameters is needed for generation of precipitation change scenarios for the region. Using simple proportional adjustment to generated precipitation sequences would lead to maximum impacts on runoff and soil loss predicted with WEPP, while attributing precipitation change equally to the change in wet day precipitation and the number of wet days would under-estimate the magnitude of the impacts considerably for the site.     

Simulating site-specific impacts of climate change on soil erosion and surface hydrology in southern Loess Plateau of China

Proper spatial and temporal treatments of climate change scenarios projected by General Circulation Models (GCMs) are critical to accurate assessment of climatic impacts on natural resources and ecosystems. The objective of this study was to evaluate the site-specific impacts of climate change on soil erosion and surface hydrology at the Changwu station of Shaanxi, China using a new spatiotemporal downscaling method. The Water Erosion Prediction Project (WEPP) model and climate change scenarios projected by the U.K. Hadley Centre's GCM (HadCM3) under the A2, B2, and GGa emissions scenarios were used in this study. The monthly precipitation and temperature projections were downloaded for the periods of 1900–1999 and 2010–2039 for the grid box containing the Changwu station. Univariate transfer functions were derived by matching probability distributions between station-measured and GCM-projected monthly precipitation and temperature for the 1950–1999 period. The derived functions were used to spatially downscale the GCM monthly projections of 2010–2039 in the grid box to the Changwu station. The downscaled monthly data were further disaggregated to daily weather series using a stochastic weather generator (CLIGEN). The HadCM3 projected that average annual precipitation during 2010–2039 would increase by 4 to 18% at Changwu and that frequency and intensity of large storms would also increase. Under the conventional tillage, simulated percent increases during 2010–2039, compared with the present climate, would be 49–112% for runoff and 31–167% for soil loss. However, simulated soil losses under the conservation tillage during 2010–2039 would be reduced by 39–51% compared with those under the conventional tillage in the present climate. The considerable reduction in soil loss in the conservation tillage indicates the importance of adopting conservation tillage in the region to control soil erosion under climate change.     

Rainfall erosivity in Cape Verde

This paper presents rainfall erosivity values derived from a 7-year rainfall recording in the Cape Verde islands, Central East Atlantic. The data set consisted of 63 storm events, continuously registered in 15-min intervals. Kinetic energy of storm rainfall corresponded to established values in other tropical locations. Two algorithms to estimate erosivity, expressed as energy times intensity, using daily rainfall or storm depth and duration as predictor variables are derived. Erosivity of design storms for various return frequencies is calculated for some locations in Santiago island. An indicative range for the annual rainfall erosion R-index is given. Data analysis further showed the extreme seasonal concentration of precipitation and erosivity at this location, with a very high fraction of total annual erosivity contained in the annual maximum 24-h rainfall.     

随机气候生成器在黄土高原的适用性检验

 为进一步检验水蚀预报模型WEPP在黄土高原的适用性,并提供必要的数据准备,根据安塞水土保持综合试验站1986—2003年的日序列的降雨量、最高温度、最低温度和平均风速的实测值及全美范围内选择参照站得到的其他气象因子,对随机气候生成器在黄土高原的适用性进行了检验。结果表明:随机气候生成器能够较好地模拟单个气象因子,并未考虑各个气象因子之间的相互关系;同时,能准确地模拟年降水及其月分布,日最高温度、日最低温度的月分布,而风速模拟值的月均值、标准差普遍高于实测值的月均值、标准差。为此,选择参考站点时应综合考虑各个气象因子。按月计算的降水降水的概率和不降水降水的概率的模拟月均值比实测值偏低。