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。     

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。     

土壤侵蚀模型中植被管理因子的遥感估算

在大区域土壤侵蚀评价中,由于缺乏详细的降雨记录和侵蚀观测实验,USLE模型中植物管理因子的参数化非常困难。该研究提议采用多时相Landsat TM/ETM遥感图像和天气模拟相结合的方法来估算植物管理因子值。其中,采用线性光谱分解算法计算各类地面覆盖物的盖度,用以估算潜在土壤流失率;采用CLIGEN模型模拟历史降雨事件并计算降雨侵蚀指数的时间分布;最后使用正则化的降雨侵蚀指数加权平均潜在土壤流失率,获得植物管理因子的估算值。该研究方法在潮河上游流域进行了应用验证,计算各土地利用类型的植物管理因子值并对比分析,结果表明:其数值变化与土地利用分类定义的植被盖度非常一致,利用上述因子值进行土壤侵蚀评估的结果和其他研究成果很接近。      

Responses of crop yield and water use efficiency to climate change in the North China Plain

Based on future climate change projections offered by IPCC, the responses of yields and water use efficiencies of wheat and maize to climate change scenarios are explored over the North China Plain. The climate change projections of 21st century under A2A, B2A and A1B are from HadCM3 global climate model.A climate generator (CLIGEN) is applied to generate daily weather data of selected stations and then the data is used to drive CERES-Wheat and Maize models. The impacts of increased temperature and CO₂ on wheat and maize yields are inconsistent. Under the same scenario, wheat yield ascended due to climatic warming, but the maize yield descended. As a more probable scenario, climate change under B2A is moderate relative to A2A and A1B. Under B2A in 2090s, average wheat yield and maize yield will respectively increase 9.8% and 3.2% without CO₂ fertilization in this region. High temperature not only affects crop yields, but also has positive effect on water use efficiencies, mainly ascribing to the evapotranspiration intensification. There is a positive effect of CO₂ enrichment on yield and water use efficiency. If atmospheric CO₂ concentration reaches nearly 600 ppm, wheat and maize yields will increase 38% and 12% and water use efficiencies will improve 40% and 25% respectively, in comparison to those without CO₂ fertilization. However, the uncertainty of crop yield is considerable under future climate change scenarios and whether the CO₂ fertilization may be realized is still needed further research.     

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CLIGEN和GCM模型预测未来40年黄土丘陵沟壑区的气候变化——以安塞为例

为预测3种温室气体排放情景（A2、B2和GGa1）下未来40年黄土丘陵沟壑区的气候变化,利用安塞试验站1986—2003年的气候观测资料以及1986—2049年GCM（HadCM3）栅格数据,通过空间转换和时间转换,利用CLIGEN和GCM模型,预测未来40年以安塞为代表的黄土高原丘陵沟壑区的气候变化。结果表明：与当前条件相比,到2049年,A2、B2和GGa1 3种情景下预测的降雨量分别增加37%、22%和12%;3种情景下预测的最大月均降雨量出现在夏季;到2049年,A2、B2和GGa1 3种情景下预测的月均最低气温和月均最高气温皆增加,但差异不明显,年均最低气温和年均最高气温分别增加1.41-1.56℃和0.92-1.57℃。     

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。     

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.