CLIGEN降水要素在黄土塬区的适应性评估

 CLIGEN是目前较全面产生降水要素(降水量、历时、达到最大降水强度的时间与降水总历时的比率、最大降水强度与平均降水强度的比率)的天气发生器,其生成降水要素的质量直接影响水文和农业响应模型的输出结果。利用黄土高原长武1957—2001年的日气象观测数据、王东沟流域1988—2001年的降水要素数据和CLIGEN生成的100年日气象数据,对CLIGEN模型产生日、月、年降水量的均值和方差、概率分布、降水极端值和降水历时、强度进行评估。结果表明:CLIGEN对日、月和年降水量均值的模拟效果较好,相对误差都不大于1.0%;对标准差的模拟结果偏低,相对误差的绝对值小于6.6%;没有模拟出日降水量的概率分布,但是较好地模拟出了月和年降水量的概率分布;对日、月和年最大降水量的模拟误差较大,表明CLIGEN对极值的模拟精度有待提高。CLIGEN很好地模拟出连续降水的频率,但是连续干旱天数在20d以内的累积频率的平均相对误差为8.9%;CLIGEN产生的最大降水强度与平均降水强度的比率高于实测数据;相对于实测数据,CLIGEN模拟的降水历时和降水量具有相同的趋势,对小降水量或短历时的模拟结果偏高,对大降水量或长历时的模拟结果偏低。     

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。     

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。     

长武黄土高塬沟壑区降水及侵蚀性降雨特征

利用长武县气象局1957—2006年的日降水量资料,分析该地区降水的年内、年际变化、概率分布特征等。结果表明：该区降水量季节分布不均,主要集中在7—9月;降水量的年际变化幅度较大,多年变化呈明显的丰水、平水、枯水年交替发生现象;降水量的年际变化大于年降水时间的年际变化。对侵蚀性降雨研究发现,其主要发生在7、8月,以降雨量小于30 mm的降雨次数较多;降雨强度随降雨量增加而减小;同时,以短历时降雨为主,历时在30min以内的降雨次数较多,其他时段相对较少。     

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.     

基于密度参数K-均值算法的RBF网络及其在降水量预测中的应用

径向基函数（Radial Basis Funtion,简称RBF）神经网络是一种收敛速度快、逼近能力强的前馈型神经网络。为提高网络的训练速度,采用基于密度参数的K-均值算法,消除传统K-均值算法对初始聚类中心的敏感性,构建了基于K-均值算法的RBF降水预报模型,并应用于挠力河流域的友谊农场汛期月降水量预报中,以检验所建模型的有效性。结果表明,与标准的K-均值算法RBF网络模型和BP（Back Propagation）网络模型相比,所构建的RBF降水预报模型对2008年,2009年,2010年各年间汛期（6—9月）降水量的预测平均相对误差为9.270 7％;确定性系数为0.96。预报精度均有所提高,且满足水文预报要求。     

华北地区气候资源的空间分布特征

应用国家气象局整编的华北地区155个气象站点48a(1961-2008年)的气象资料和中国数字高程模型,对华北地区48a日照时数、年均气温、≥10℃积温、年降水量和春、夏、秋、冬四季降水量等气象资料的空间分布进行分析,得到了华北地区气候资源分布图。结果表明:华北地区年日照时数总体分布为北高南低,气温及≥10℃积温分布为南部高于北部,东部高于西部,降水总体是从南向北递减,四季降水不均匀,主要降水集中在夏季。总体来说,华北南部地区热量及降水资源丰富,而光照资源相对较少;华北北部地区光照和热量资源充足,降水资源相对短缺。     

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个百分点,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个百分点,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。     

黑龙江省近50年降水变化趋势及空间分布特征

依据黑龙江省呼玛、孙吴、齐齐哈尔、富锦、安达、哈尔滨、鸡西和牡丹江8个气象站1960—2012年的降水资料,运用线性回归、Mann-Kendall秩相关检验法和GIS空间插值等方法,分析该区近50多年来降水变化趋势和空间分布特征。结果表明:1)黑龙江省年代际降水表现为2降1升或2升1降30 a左右的周期,且从2012年开始转为多水期;2)除齐齐哈尔、呼玛站和安达站外,多年平均降水量在500 mm以上,降水集中在夏季,约占全年的64%,所有站点多年平均月降水量均呈现单峰曲线变化;3)仅孙吴和鸡西站年降水量呈显著减少趋势;4)多年降水空间分布以孙吴站和牡丹江为中心向周围递减,春季空间分布与多年降水空间分布较为一致;5)黑龙江省南部和北部年降水量均发生2次突变,分别为20世纪80年代初中期和21世纪初期,东、西部不存在明显的突变。研究结果可为该区的降水研究、水资源配置和生产实践等提供参考。     

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.     

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.     

华北平原近45年农业气候资源变化特征分析

利用华北平原53个气象站1961—2005年逐日气温、降水资料,运用最小二乘法进行线性倾向估计,分析华北平原主要农业气候资源时间、空间变化趋势及其差异。结果表明：华北平原年≥0℃活动积温、5-10月≥10℃活动积温以及〈0℃负积温绝对值的变化与年平均气温的变化密切相关,20世纪60年代-70年代中期是热量贫乏阶段,70年代中期-90年代末是热量增加阶段,90年代末-2005年热量最丰富,但趋势表现为减少;华北北部和东部沿海热量增加趋势明显,中南部≥10℃活动积温呈减少趋势;华北平原全年、夏季降水量减少趋势不显著,但年际间变化增大,多年来降水偏少,2003—2005年的降水量增加;华北平原降水量分配在南北之间、沿海与内陆之间趋于平均,夏季表现尤为明显。     

增暖背景下华北平原极端降水事件时空变化特征

利用1961-2010年华北平原53个气象站的逐日降水资料,采用百分位值法定义极端降水事件的阈值,统计极端降水事件的降水量、频次和强度,重点分析华北平原近50 a极端降水事件时空变化特征.结果表明:(1)在气候暖化背景下,近50 a华北平原极端降水事件整体呈现下降趋势;(2)在空间格局上,极端总降水量、发生频率和强度空间格局具有一致性;(3)华北平原极端降水呈现下降趋势的区域主要分布于河北省及山东省东南沿海一带,而河南省大部呈上升趋势;(4)从时间上看各指标均呈波动变化,20世纪60年代表现出明显的减少趋势,且90年代中后期波动变化剧烈,并开始呈现上升趋势.除极端降水强度外,极端总降水量及频次均发生了突变,时间在1965年左右.     

LARS-WG天气发生器在黄土高原的适应性研究

 利用黄土高原地区西安、兰州、太原、银川、呼和浩特和延安6个气象站1951—1990年的日序列的降雨量、最高温度、最低温度及日照时间,用LARS-WG天气发生器模拟1991—2000年的日气象资料,并用1991—2000年的实际观测值与之比较,对LARS-WG天气发生器适应性进行了检验。通过线性回归、平方根误差和平均偏差评价表明:通过长序列日气象资料,LARS-WG天气发生器能准确地模拟黄土高原6个站点的日最高温度、日最低温度的月分布和年辐射总量。年降水及其月分布值普遍高于实际降水值。