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81.
分析了河西走廊1980~2010年一日大风持续时间的气候特征。结果表明:河西走廊一日大风平均和最长持续时间的空间分布特征与大风日数基本一致,总体上自东向西、自南向北增多,且随海拔高度的升高而增多。全区年大风平均持续时间在7~207 min之间,平均为65 min。大风一日最长持续时间是1 390 min。酒泉市大部、永昌、民勤和乌鞘岭年大风平均和最长持续时间偏长,其余地方偏短。各季大风平均和最长持续时间,春季最长、冬季次长、夏季最短、秋季次短。年一日大风持续时间的频率为偏态分布,在0~2 h的累积频率为0.67。风速偏小站大风的持续时间基本为0~12 h,风速偏大站大风的持续时间在12~24 h,这说明风速越大,大风的持续时间越长。 相似文献
82.
In model-based sensitivity studies, the growth of model error over long-term integrations may lead to serious deviations between the simulated and actual states. To reduce these errors, we have developed a new modeling approach with application of the Newtonian relaxation technique, or nudging. In this approach, an identical artificial Newtonian relaxation term that reflects the difference between the model reference state and its analysis (available in many sensitivity studies) is added to the prognostic equations of the two simulated states, the reference state and the perturbed state (for which observations are nonexistent). We have conducted idealized sensitivity experiments with a shallow-water model to evaluate the benefits and viability of this approach and to test its sensitivity to changes in the nudging period and error in the analysis data. The experimental results confirm that this approach lead to more credible atmospheric responses to modified external forcing if the data error is within a reasonable range. The results also indicate that a 12-hour period is more favorable for nudging than a 24-hour period. 相似文献
83.
Evapotranspiration (ET) is a critical component in the hydrological cycle. However, its actual values appear to be difficult to obtain, especially in areas in which precipitation has high inter‐annual variability. Here, we evaluated eight commonly used ET models in semi‐arid and semi‐humid areas of China. The order of overall performance from best to worst is as follows: the revised Priestley–Taylor model (PT‐JPL, 0.71, 1.65 [18.37%], 4.72 [49.19%]) a a Statistics (model abbreviation, coefficient of determination, bias [relative value], standard deviation [relative value]).
, the modified PT‐JPL model (M1‐PT‐JPL, 0.67, ?0.68 [7.56%], 3.87 [40.31%]), the Community Land Model (CLM, 0.68, ?2.52 [28.01%], 5.10 [53.17%]), the modified PT‐JPL model (M2‐PT‐JPL, 0.63, 0.57 [6.27%], 5.04 [52.52%]), the revised Penman–Monteith model (RS‐PM, 0.62, 3.56 [37.40%], 6.11 [63.68%]), an empirical model (Wang, 0.59, ?1.04 [11.57%], 5.61 [58.43%]), the advection‐aridity model (AA, 0.55, 5.56 [61.78%], 7.45 [77.60%]), and the energy balance model (SEBS, 0.35, 5.11 [56.72%], 9.43 [98.18%]). The performance of all of the models is comparably poor in winter and summer, except for the PT‐JPL model, and relatively good in spring and autumn. Because of the vegetation control on ET, the Wang, RS‐PM, PT‐JPL, M1‐PT‐JPL, and M2‐PT‐JPL models perform better for cropland, whereas the AA model, SEBS model and CLM perform better for grassland. The CLM, PT‐JPL, and Wang models perform better in semi‐arid region than in semi‐humid region, whereas the opposite is true for SEBS and RS‐PM. The AA, M1‐PT‐JPL, and M2‐PT‐JPL models perform similarly in semi‐arid and semi‐humid regions. When considering the inter‐annual variability in precipitation, the Wang model has relatively good performance under only some annual precipitation conditions; the performance of the PT‐JPL and AA models is reduced under conditions of high precipitation; the two modified PT‐JPL models inherited the steady performance of the PT‐JPL model and improved the performance under conditions of high annual precipitation by the modification of the soil moisture constraint. RS‐PM is more appropriate for humid conditions. CLM and PT‐JPL models could be effectively applied to all precipitation conditions because of their good performance across a wide annual precipitation range. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
, the modified PT‐JPL model (M1‐PT‐JPL, 0.67, ?0.68 [7.56%], 3.87 [40.31%]), the Community Land Model (CLM, 0.68, ?2.52 [28.01%], 5.10 [53.17%]), the modified PT‐JPL model (M2‐PT‐JPL, 0.63, 0.57 [6.27%], 5.04 [52.52%]), the revised Penman–Monteith model (RS‐PM, 0.62, 3.56 [37.40%], 6.11 [63.68%]), an empirical model (Wang, 0.59, ?1.04 [11.57%], 5.61 [58.43%]), the advection‐aridity model (AA, 0.55, 5.56 [61.78%], 7.45 [77.60%]), and the energy balance model (SEBS, 0.35, 5.11 [56.72%], 9.43 [98.18%]). The performance of all of the models is comparably poor in winter and summer, except for the PT‐JPL model, and relatively good in spring and autumn. Because of the vegetation control on ET, the Wang, RS‐PM, PT‐JPL, M1‐PT‐JPL, and M2‐PT‐JPL models perform better for cropland, whereas the AA model, SEBS model and CLM perform better for grassland. The CLM, PT‐JPL, and Wang models perform better in semi‐arid region than in semi‐humid region, whereas the opposite is true for SEBS and RS‐PM. The AA, M1‐PT‐JPL, and M2‐PT‐JPL models perform similarly in semi‐arid and semi‐humid regions. When considering the inter‐annual variability in precipitation, the Wang model has relatively good performance under only some annual precipitation conditions; the performance of the PT‐JPL and AA models is reduced under conditions of high precipitation; the two modified PT‐JPL models inherited the steady performance of the PT‐JPL model and improved the performance under conditions of high annual precipitation by the modification of the soil moisture constraint. RS‐PM is more appropriate for humid conditions. CLM and PT‐JPL models could be effectively applied to all precipitation conditions because of their good performance across a wide annual precipitation range. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
84.
气候变暖背景下祁连山区春季积雨云变化特征 总被引：1，自引：0，他引：1
利用祁连山区及其周边26个气象观测站1961-2005年春季云形状和气温观测资料,采用线性趋势分析、小波分析等方法,分析了祁连山区春季积雨云出现频率的空间分布与时间变化特征,探讨了与气候变暖的关系,并选用同期NCEP/NCAR全球再分析资料,对祁连山区春季积雨云的环流特征进行分析。结果表明:① 祁连山区春季积雨云出现频率在20%～24%,为河西走廊和柴达木盆地的3～6倍,山区东、南侧多于西、北侧,与该区大气水汽含量分布呈现相一致。② 近45年来,祁连山区春季平均气温增温0.9 ℃,气温变化经历了低—高—低—高的4个变化阶段,气温变化的倾向率为0.18 ℃/10a。③ 近45年来,祁连山区春季积雨云出现频率与同期气温变化反相,经历了多—少—多—少4个变化阶段,总体呈弱的减少趋势,倾向率为0.2%/10a。④ 在25a时间尺度上,祁连山区春季气温和积雨云出现频率为反相位变化结构为主,表明在长期气候变化上,气温偏低时期对应积雨云出现偏多时期,气温偏高时期对应积雨云出现偏少时期。⑤ 祁连山区春季积雨云偏多与偏少年在欧亚500 hPa环流场上存在明显的差异,积雨云出现频次的多少是对欧亚500 hPa环流异常的响应。 相似文献
85.
近60年来西南地区旱涝变化及极端和持续性特征认识 总被引：3，自引：1，他引：2
利用1953~2012年中国西南地区44个气象台站的逐日降水、温度资料,通过降水和潜在蒸发均一化旱涝指数,从旱涝的年代际、年际、季节内变化以及极端和持续性特征等方面进行了分析,结果表明：从旱涝的空间趋势变化来看,西南近60 a来秋季和年变化呈显著的一致变旱趋势,而春、夏、冬3季旱涝变化趋势表现出一定的区域性特征;从旱涝的时间演变来看,在温度与降水双重因子驱动下春、夏、秋、冬均表现为干旱化趋势,相比较秋季的干旱化程度最强,而春季的最弱,夏、冬两季相当,而全年的干旱程度比四季的程度更强;从极端旱涝的多时间尺度来看,在年代际和年际尺度上,极端洪涝发生频次逐渐减少,而极端干旱发生频次逐渐增多,从季节尺度看,春、冬两季极端干旱发生频次较多,而夏季最少,极端洪涝发生频次夏季最多,春季次之,秋季最少。从旱涝的持续性特征来看,持续性干旱事件的持续时间有增长趋势,发生频率有增多趋势,发生强度有增强趋势,并且主要发生在冬春两季,而持续性洪涝事件的持续时间、发生强度没明显变化趋势,发生频率有减少趋势,发生的季节也没明显差异。 相似文献
86.
利用1953-2012年中国西南地区44个气象台站的逐日降水、温度以及NCAR/NCEP月平均高度场、风场、地面气压、比湿、垂直速度和NOAA月平均海表温度资料,分析了西南地区4～5月持续性干旱的大气环流特征,并对前期印度洋海表温度对西南地区4～5月持续性干旱的影响进行了初步探讨,结果表明：在西南4～5月持续性干旱年,同期4、5月乌拉尔山脊偏弱,东亚大槽南段偏弱,南支槽也偏弱,中高纬西风带偏强,这样北方冷空气和西南暖湿气流均偏弱;对应西南地区表现为异常的下沉运动,同时水汽输送通量表现为异常的辐散中心,从而使得西南地区发生干旱。另外,在西南4～5月持续性干旱年,从前期2月中印度洋异常偏暖的海表温度区逐渐向东移动,在4～5月到达东印度洋,东印度洋异常偏暖的海表温度加热该地区的大气,使得该地区表现出异常的上升运动,导致哈德莱环流增强,而我国西南地区对应异常的下沉气流,从而使得西南地4～5月发生干旱。 相似文献
87.
干旱是影响甘肃省河东地区农业生产的主要气象灾害之一。如何在众多的干旱遥感监测指数中选择适宜的指数是干旱遥感监测工作面临的主要问题。利用研究区30个农业气象站观测的不同深度土壤相对湿度和对应的MODIS数据,分析了7种典型干旱遥感监测指数(AVI、NDWI、VCI、PDI、MPDI、VSWI和MEI)的构建原理和模拟结果,并选择适宜的干旱遥感监测指数对2006年甘肃省河东地区干旱情况的时空分布做了动态监测。结果表明:7种干旱遥感监测指数均能反映研究区土壤湿度的时空变化特征;各干旱遥感监测指数对土壤水分监测的最佳深度为20 cm,其次为10 cm。从相关系数来看,PDI、MPDI指数对春季,VSWI、NDWI指数对夏季的土壤相对湿度有较好的监测结果;MEI指数对秋季土壤相对湿度模拟效果较差,其余指数对秋季模拟效果均较好;根据各指数与20 cm处土壤相对湿度的相关系数,结合各指数的构成原理,春季选择PDI和MEI,夏季选择VSWI和NDWI,秋季选择PDI和MPDI,分别对2006年甘肃省河东地区干旱情况进行监测。通过考虑各等级出现的频率,同时兼顾土壤相对湿度,评定各指数干旱等级。监测结果显示,庆阳市北部连续出现春旱、春末夏初旱、伏旱和秋旱,陇中北部和庆阳市北部旱情严重。 相似文献
88.
1901-2012年中国西北地区东部多时间尺度干旱特征 总被引：1，自引：0，他引：1
以干旱的多时间尺度特征出发,利用CRU最新数据,计算了考虑降水和气温双因子影响的标准化降水蒸散指数(SPEI),并与标准化降水指数(SPI)进行对比,分析中国西北地区东部1901-2012年不同时间尺度的干旱特征。本文不仅对百年来CRU资料的可靠性进行检验,而且对SPEI在西北地区东部的适应性进行讨论。结果表明:CRU资料可靠性较好,但由于CRU资料本身的属性,1920年以前资料的可靠性不确定。从干旱事件的发生强度及干旱范围分析,SPEI在西北地区东部具有较好的适用性。SPEI与SPI在不同时间尺度下的波动变化一致,短时间尺度主要表现年内或季节特征,长时间尺度则侧重表现年际、年代际特征。将研究区分为高原东北区和陕南区进行分析,1901-2012年高原东北区有4个干期,陕南区有5个干期。针对温度变化对西北地区东部干旱的影响及与SPI对比表明,高温对干旱的贡献不容忽视。 相似文献
89.
西北地区气候变化新动态及对干旱环境的影响——总体暖干化,局部出现暖湿迹象 总被引：12，自引：1，他引：11
近50 a来,西北地区气温呈显著的上升趋势,降水变化空间差异突出,西北地区整体暖干化趋势明显,局部出现暖湿现象。气候变暖使冰川退缩,雪线上升,冻土消融,湿地退化,湖泊萎缩,河流流量减少,水资源越来越短缺,出现生态环境恶化问题。根据IPCC预测结果分析,未来西北地区气候变暖趋势会更加明显。从保护西北地区生态环境、完善气候变化综合监测系统以及开展重点区域气候变化过程专项研究等方面提出了对策建议。 相似文献
90.
A Study of the Atmospheric Boundary Layer Structure During a Clear Day in the Arid Region of Northwest China 
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下载免费PDF全文 The local climate and atmospheric circulation pattern exert a clear influence on the atmospheric boundary layer （ABL） formation and development in Northwest China. In this paper, we use field observational data to analyze the distribution and characteristics of the ABL in the extremely arid desert in Dunhuang, Northwest China. These data show that the daytime convective boundary layer and night time stable boundary layer in this area extend to higher altitudes than in other areas. In the night time, the stable boundary layer exceeds 900 m in altitude and can sometimes peak at 1750 m, above which the residual layer may reach up to about 4000 m. The daytime convective boundary layer develops rapidly after entering the residual layer, and exceeds 4000 m in thickness. The results show that the deep convective boundary layer in the daytime is a pre-requisite for maintaining the deep residual mixed layer in the night time. Meanwhile, the deep residual mixed layer in the night time provides favorable thermal conditions for the development of the convective boundary layer in the daytime. The prolonged periods of clear weather that often occurs in this area allow the cumulative effect of the atmospheric residual layer to develop fully, which creates thermal conditions beneficial for the growth of the daytime convective boundary layer. At the same time, the land surface process and atmospheric motion within the surface layer in this area also provide helpful support for forming the particular structure of the thermal ABL. High surface temperature is clearly the powerful external thermal forcing for the deep convective boundary layer. Strong sensible heat flux in the surface layer provides the required energy. Highly convective atmosphere and strong turbulence provide the necessary dynamic conditions, and the accumulative effect of the residual layer provides a favorable thermal environment. 相似文献