, 张明军, 王圣杰, 王杰, 赵培培, 周盼盼西北师范大学地理与环境科学学院,兰州 730070
Diurnal variation of summer precipitation and its influencing factors of the Qilian Mountains during 2008-2014
LIUXuemei, ZHANGMingjun, WANGShengjie, WANGJie, ZHAOPeipei, ZHOUPanpan通讯作者:
收稿日期:2015-11-20
修回日期:2016-01-23
网络出版日期:2016-05-25
版权声明:2016《地理学报》编辑部本文是开放获取期刊文献，在以下情况下可以自由使用：学术研究、学术交流、科研教学等，但不允许用于商业目的.
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1 引言
随着全球气候变暖,北半球中纬度地区增温显著,促使水循环加速[1-2]。降水作为水循环的重要环节,在大气热力和动力过程的综合影响下往往表现出日变化特征[3],是世界气候研究计划（WCRP）重点关注的科学问题之一[4]。降水日变化是地球自转对太阳辐射强迫的反映,对地表和大气中的能量流动、水文变化和人类生产生活有重要影响[5-6]。通过研究降水日变化特征可以揭示与之相关的环流和其他参数的日变化规律[7],有助于解释降水的形成机制及评估区域气候模型[8],从而进行合理的水资源调配。因此,对日尺度降水特征的研究有着重要的科学意义和现实意义[9-10]。目前,国内外****对全球不同区域的降水日变化特征展开了大量的研究工作[11-12]。受海陆分布、地形、海拔、纬度等因素影响,降水日变化区域差异显著：其中处于寒带的瑞典内陆,暖季日降水峰值为午后,而处于瑞典东海岸的降水则没有明显的昼夜差 异[13-14];在温带,除青藏高原地区外,一些****得出降水日变化位相有明显向东传播的特征,在西风带的影响下北美的传播速度比东亚快[15-16]。卫星遥感技术的发展为研究热带降水的日变化提供了更为有效的手段,利用TRMM卫星降水资料和地面观测资料融合发现,各大洋热带气旋降水的昼夜循环是相似的[17];但在北大西洋,受到西风带的影响,降水日变化强度明显弱于其他大洋[18];东亚季风区的研究发现,降水高度影响着降水强度的日变化,并且一些地区的降水日变化峰值相位存在着明显的经向传播特征[15, 19]。除了大区域的降水日变化研究外,也有****针对特定小区域的降水日变化进行了研究,相关结论完善了对当地降水机制的认识[20-23]。
祁连山区地处青藏高原东北部,降水表现出了明显的空间差异,总体而言山区降水多于平原,东部降水多于西部,其降水量变化对于毗邻区域尤其是河西走廊水资源具有至关重要的影响,其降水的日变化特征值得深入研究[24]。地面观测资料是降水日变化研究的基础,但已有气象监测网络对祁连山区的覆盖十分有限,尤其是高海拔山区缺乏足够的实测气象站点,不利于降水日变化的深入研究;卫星反演资料可以在空间分布上弥补上述缺陷,但是没有经过地面资料订正的卫星降水数据集往往具有不同程度的不确定性,尤其是在中国西部的山区,影响研究结果的可信性[25-29]。在这样的基础上,中国气象局国家气象信息中心利用中国境内的自动气象站降水数据与CMORPH数据[27]融合,发布了全国范围的逐时降水量0.1°网格数据集。Shen等[28-29]介绍了该产品的生成方法,并从误差时空分布、不同降水量级差异、强降水刻画能力等方面评估了降水产品的质量,发现该产品弥补了中国西部地区自动站分布较少和易受到寒冷天气影响的不足。近年来,该款数据也越来越多地运用于不同区域降水研究,表现出了较好的效果[30-33]。本文选取该降水融合数据,利用逐时平均降水量、降水频率、降水强度和降水变率等指标对祁连山近年来降水的日变化特征进行分析,并利用ERA-Interim再分析数据对日变化的影响因素进行探讨,旨在增进对这一区域水文循环特征的认识,理解降水形成的机理。
2 数据与方法
2.1 研究区概况
祁连山处于亚欧大陆中部,山峰海拔在4000~5000 m之间,是青藏高原东北部最大的边缘山系,北为河西走廊,南为柴达木盆地,祁连山区具有典型的大陆性气候和高原气候的特征（图1）。山区终年积雪并有现代冰川的分布,根据第二次中国冰川编目数据,现有冰川面积1597.81±70.30 km2,储量约84.48 km3 [34],在全球气候变暖的背景下冰川呈现出加速退缩的趋势[35-36]。祁连山区降水的时空分布特征复杂,季节性和区域性特征较为显著,为了便于分析,本文将101°E和98°E分别作为祁连山区东段、中段和西段的分界线[37]。
显示原图|下载原图ZIP|生成PPT图1祁连山区逐时降水量0.1°×0.1°网格空间分布
-->Fig. 1Spatial distribution of grid boxes for hourly precipitation at 0.1°×0.1° resolutions in the Qilian Mountains
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2.2 数据来源
本文使用中国气象局国家气象信息中心发布的中国自动站与CMORPH降水产品融合的逐时降水量0.1°网格数据集（1.0版）（http://cdc.cma.gov.cn）,该数据集覆盖时段为2008-2014年。该数据集以地面逐时降水格点数据为基础,使用最优插值（Optimal Interpolation, OI）的方法与卫星降水资料进行有效的结合[38]。在西风带、南亚季风和高原季风的共同影响下,夏季祁连山区几乎为一个“水汽汇”,在全年降水中占到很大的比例[39-40],故本文重点关注2008-2014年夏季（6-8月）降水的日变化特征。此外,本文还使用了欧洲中期天气预报中心提供的ERA-Interim再分析数据集[41]分析祁连山区日降水的影响因素,主要选取2008-2014年研究区内的相对湿度和气温数据,空间分辨率为0.125°×0.125°,时间分辨率为6 h。2.3 研究方法
为描述祁连山区降水日变化特征,选取了逐时平均降水量、降水频率、降水强度、白天（北京时间08:00-20:00）和夜间（北京时间20:00-08:00）降水量和降水变率等6个指标用于表征祁连山区夏季降水日变化特征。一般来说,降水变率的大小反映了降水的稳定性,某区域的降水丰富、变率小,表明该区域水资源利用价值高,不易发生旱涝灾害。本文利用降水平均相对变率来表征不同分区不同时刻的降水稳定性,计算公式如下：
式中：P表示降水平均相对变率;xi指某小时的降水量（mm/h）;
月尺度下的逐时平均降水量为：
式中：P表示逐时平均降水量（mm/月）;pi是表示逐时降水量（mm/h）。
使用Pearson相关系数r来分析逐时平均降水量、降水频率和降水强度之间的相关关系,用T检验法来检验线性趋势的显著性,并利用ArcGIS软件绘制相关的空间分布图。
相关系数计算公式如下：
式中：当r>0时,表明要素之间为正相关;当r<0时,表明要素之间为负相关。r的绝对值越接近1,则表明相关性越好,反之越差。
3 结果与分析
3.1 不同分区逐时降水量的时空变化特征
2008-2014年祁连山区夏季逐时平均降水量的变化（图2）,东中段的逐时平均降水量明显大于西段,这与以往基于格点降水数据[40]和地面监测资料[42]的祁连山区降水空间分布研究结果相一致。祁连山区大部分地区的逐时降水量呈现出7月最大,6月次之,8月最小的趋势;在祁连山区中段,7月和整个夏季的逐时平均降水量峰值出现时间是18:00（北京时间,下同）,而6月和8月的峰值出现时间分别是17:00和20:00。总体而言,祁连山区的逐时平均降水量的峰值时间出现在17:00-20:00,这与以往研究的认识[43]也是大致相符的,即山地型降水的峰值时间主要集中于傍晚和前半夜。
显示原图|下载原图ZIP|生成PPT图22008-2014年祁连山区不同分区夏季逐时平均降水量变化(mm/月)
-->Fig. 2Variation of mean hourly precipitation amount in different zones in the Qilian Mountains during the summer of 2008-2014 (mm/month)
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就祁连山区的全区而言,降水主要集中在东中段,西段的降水较为稀少（图3）。从逐时降水量的空间分布（图3）来看,自08:00之后呈逐渐较少的趋势,直至12:00逐时降水量最少,此后开始增加,尤其是16:00之后逐时降水量显著增加且北坡的降水量比南坡的降水量更大,22:00至翌日07:00则表现为减少趋势且南坡的降水量逐渐大于北坡的。在17:00-21:00之间具有降水较为集中的特点,祁连山区东中段大部分地区的逐时降水量超过了4 mm/月。
3.2 不同分区逐时降水频率的时空变化特征
研究时段内祁连山区降水频率的日变化特征（图4）可以看出,逐时降水频率的变化特征与逐时平均降水量的较为一致。祁连山东中段的逐时降水频率大于西段,尤其是中段的降水频率最大,西段在夏季发生降水的概率最小。从月份上看,东中段在7月的降水频率最大,6月次之,8月最小;在祁连山西段,6月的逐时降水频率最大,7月次之,8月最小。在祁连山中段,6月和整个夏季的逐时降水频率峰值时间均为17:00,7月的峰值时间是21:00,8月的峰值时间是18:00。综上所述,祁连山区逐时降水频率的峰值时间为17:00-21:00,与逐时平均降水量的峰值时间大致吻合,即集中于傍晚和前半夜。从祁连山区夏季逐时平均降水频率的空间分布（图5）来看,山区的降水频率一般大于周围地区,且东中段的逐时降水频率均较西段大,在东中段的大部分地区降水频率均超过了0.15。
显示原图|下载原图ZIP|生成PPT图32008-2014年祁连山区夏季逐时平均降水量的空间分布
-->Fig. 3Spatial distribution of mean hourly precipitation in the Qilian Mountains during the summer of 2008-2014
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显示原图|下载原图ZIP|生成PPT图42008-2014年祁连山区不同分区夏季逐时平均降水频率变化
-->Fig. 4Variation of mean hourly precipitation frequency in different zones in the Qilian Mountains during the summer of 2008-2014
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显示原图|下载原图ZIP|生成PPT图52008-2014年祁连山区夏季逐时平均降水频率的空间分布
-->Fig. 5Spatial distribution of mean hourly precipitation frequency in the Qilian Mountains during the summer of 2008-2014
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显示原图|下载原图ZIP|生成PPT图62008-2014年祁连山区不同分区夏季逐时平均降水强度变化(mm/h)
-->Fig. 6Variation of mean hourly precipitation intensity in different zones in the Qilian Mountains during the summer of 2008-2014 (mm/h)
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显示原图|下载原图ZIP|生成PPT图72008-2014年祁连山区夏季逐时平均降水强度的空间分布
-->Fig. 7Spatial distribution of mean hourly precipitation intensity in the Qilian Mountains during the summer of 2008-2014
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3.3 不同分区逐时降水强度的时空变化特征
图6反映了2008-2014年祁连山区夏季逐时平均降水强度的变化。降水强度的日变化特征与上文中降水量和降水频率的日变化特征存在明显差异,祁连山大部分地区的降水强度相似,即东段、中段和西段没有明显的递变规律。从月份上看,东段和中段的降水强度7月最强,而西段的降水强度6月最强,7月次之,但是月份间没有太大的差异。中段的降水强度比较稳定,没有明显的峰值时间;东段6月、7月和8月份降水强度的峰值时间分别是05:00、20:00和07:00;西段6月的降水强度峰值时间在23:00-00:00,7月为12:00和07:00,8月则为06:00-07:00。祁连山区降水强度的高值区并非与逐时降水量和降水频率一样分布在降水丰富的山区（图7）,与海拔并未表现出较好的一致性,东段、中段和西段的降水强度无明显差异。3.4 昼夜降水量时空变化的比较
2008-2014年祁连山区以及东段、中段和西段的白天降水量均呈上升趋势（图8）,且中段白天降水量的增加趋势最为显著（r2 = 0.5251)。东段白天降水量在2008-2011年波动相对较小,维持在较低水平,2012-2014年降水量则比前一时段偏高,尤其是2012年出现明显高值;中段和西段白天降水量的变化趋势与东段的类似,但2013年降水量更为偏大。全区和各分区夜间降水量呈上升趋势（图9）,其中东段夜间降水量的增加趋势最为显著（r2 = 0.5588）。东段夜间降水量自2010年出现小波谷后逐渐上升,在2013年达峰值后逐渐降低;中段和西段夜间降水量与东段类似,但最大值出现在2012年。
显示原图|下载原图ZIP|生成PPT图82008-2014年夏季祁连山区白天降水量的年际变化
-->Fig. 8Inter-annual variation of daytime precipitation in the Qilian Mountains during the summer of 2008-2014
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显示原图|下载原图ZIP|生成PPT图92008-2014年夏季祁连山区夜间降水量的年际变化特征
-->Fig. 9Inter-annual variation of nighttime precipitation in the Qilian Mountains during the summer of 2008-2014
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显示原图|下载原图ZIP|生成PPT图102008-2014年夏季祁连山区白天(a)和夜间(b)降水量及其差值(c)的空间分布
-->Fig. 10Spatial distribution of precipitation in daytime (a), nighttime (b) and their difference (c) in the Qilian Mountains during the summer of 2008-2014
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图10反映了祁连山区夏季白天和夜间平均降水量及其差值的空间分布情况。白天和夜间降水量的空间特征基本一致,无论白天还是夜间东段和中段降水量都明显大于西段,且降水主要集中于山区（图10a、图10b）;在祁连山区大部分地区夜间降水量大于白天,有明显的夜雨现象（图10c）。这种夜雨现象在其他地区也有报道,尤其是在四川盆地[44-45]。
3.5 降水变率及各指标间的相关性分析
2008-2014年祁连山区夏季逐时降水相对变率（图11）可以看出,所有分区不同时刻的逐时降水相对变率介于5%~38%之间。中段和西段夏季降水相对变率的最大值均出现在20:00,而东段的最大值则出现在19:00。在降水变率的高值区更易发生极端的天气事件,气象灾害频发[46];全区相对变率的最低值普遍出现在12:00,此时降水的稳定性较好。从祁连山区逐时平均降水量、降水频率和降水强度的相关性（表1）来看,逐时平均降水量和降水频率的相关性最好,各分区均通过了0.01信度的显著性水平检验,尤其是东段和中段。
Tab. 1
表1
表12008-2014年祁连山区夏季逐时平均降水量、降水频率和降水强度的相关系数
Tab. 1Correlation coefficients among mean hourly precipitation, frequency and intensity in the Qilian Mountains during the summer of 2008-2014
| 祁连山区东段 | 祁连山区中段 | 祁连山区西段 | 祁连山区 | |
|---|---|---|---|---|
| r (降水量—降水强度) | 0.366 | 0.887** | -0.062 | 0.194 |
| r (降水量—降水频率) | 0.834** | 0.963** | 0.598** | 0.931** |
| r (降水强度—降水频率) | -0.036 | 0.806** | -0.483* | -0.071 |
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显示原图|下载原图ZIP|生成PPT图112008-2014年祁连山区逐时降水平均相对变率变化
-->Fig. 11Hourly variation of mean relative variation of precipitation in the Qilian Mountains during the summer of 2008-2014
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3.6 降水日变化的影响因素
影响降水日变化的因素极为复杂,即使是临近区域受地形等因素影响也会产生不同的日变化特征。本文得出的逐时降水量的峰值时间为17:00-21:00,为傍晚和前半夜型。从ERA-Interim再分析资料（图12）来看,祁连山区东段和中段为相对湿度和地面温度的高值区域,这与逐时平均降水量的分布规律基本一致。祁连山区午后太阳辐射强度大,山地温度升高,从而使山区地面蒸发和植被蒸腾作用加强,20:00左右相对湿度达到峰值,近地面形成高温高湿的气团;该气团迫使地面与高空的对流加强,且傍晚地面温度开始下降,空气冷却,易形成降水;至翌日凌晨,相对湿度减少,温度继续下降,故山地的逐时降水量峰值集中于傍晚和前半夜。当然,进一步的机理分析还有待继续开展,从而加深对祁连山降水日变化的认识。
显示原图|下载原图ZIP|生成PPT图122008-2014年夏季祁连山区500 hPa相对湿度和地面气温的空间分布
-->Fig. 12Spatial distribution of relative humidity at 500 hPa and surface air temperature in the Qilian Mountains during the summer of 2008-2014
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4 结论
本文选用中国自动站与CMORPH降水产品融合的逐时降水量0.1°×0.1°网格数据集分析了2008-2014年祁连山区夏季逐时平均降水量、降水频率、降水强度等指标的变化特征,并结合ERA-Interim再分析资料分析了降水日变化的影响因素,得到以下几点结论：（1）祁连山区逐时平均降水量和降水频率的日变化特征基本一致,即东中段的降水量和降水频率较西段的大;降水强度的高值区位置与逐时降水量和降水频率的不同,与海拔没有明显的联系;逐时平均降水量和降水频率均是7月最大,6月次之,8月最小;东中段的降水强度是7月最大,8月最小,但是西段的为6月最大,8月最小。
（2）2008-2014年祁连山区白天和夜间降水量的年际变化大体呈增加趋势,峰值多出现在2012年;白天和夜间降水量的空间特征基本一致,即中东段的降水量大于西段,且集中于山区;祁连山区夜间降水量大于白天,有明显的夜雨现象。
（3）祁连山区不同时刻降水相对变率介于5%~38%之间,全区在20:00时相对变率最大,更易发生极端降水事件;逐时平均降水量和降水频率之间普遍存在较好的相关性,有其是在祁连山东中段。
（4）结合ERA-Interim再分析资料分析发现,祁连山区降水日变化与相对湿度和地面温度等气象要素的日变化存在联系。
The authors have declared that no competing interests exist.
参考文献 原文顺序
文献年度倒序
文中引用次数倒序
被引期刊影响因子
| [1] | |
| [2] | IPCC第五次评估报告（AR5）第一工作组（WGI）报告的亮点结论，是过去7年全世界气候变化科学研究成果凝练出来的精华。20世纪50年代以来全球气候变暖的一半以上是人类活动造成的。1971年以来人为排放温室气体产生热量的93%进入了海洋，海洋还吸收了大约30%人为排放的CO<sub>2</sub>，导致海表水pH值下降了0.1，等等。采用全球耦合模式比较计划第五阶段（CMIP5）的模式，预估未来全球气候变暖仍将持续，21世纪末全球平均地表温度在1986—2005年的基础上将升高0.3～4.8℃。限制气候变化需要大幅度持续减少温室气体排放。如果将1861—1880年以来人为CO<sub>2</sub>累积排放控制在1000 GtC，那么人类有超过66%的可能性把未来升温幅度控制在2℃以内（相对1861—1880年）。 . IPCC第五次评估报告（AR5）第一工作组（WGI）报告的亮点结论，是过去7年全世界气候变化科学研究成果凝练出来的精华。20世纪50年代以来全球气候变暖的一半以上是人类活动造成的。1971年以来人为排放温室气体产生热量的93%进入了海洋，海洋还吸收了大约30%人为排放的CO<sub>2</sub>，导致海表水pH值下降了0.1，等等。采用全球耦合模式比较计划第五阶段（CMIP5）的模式，预估未来全球气候变暖仍将持续，21世纪末全球平均地表温度在1986—2005年的基础上将升高0.3～4.8℃。限制气候变化需要大幅度持续减少温室气体排放。如果将1861—1880年以来人为CO<sub>2</sub>累积排放控制在1000 GtC，那么人类有超过66%的可能性把未来升温幅度控制在2℃以内（相对1861—1880年）。 |
| [3] | This paper summarizes the recent progress in studies of the diurnal variation of precipitation over contiguous China. The main results are as follows. (1) The rainfall diurnal variation over contiguous China presents distinct regional features. In summer, precipitation peaks in the late afternoon over the southern inland China and northeastern China, while it peaks around midnight over southwestern China. In the upper and middle reaches of Yangtze River valley, precipitation occurs mostly in the early morning. Summer precipitation over the central eastern China (most regions of the Tibetan Plateau) has two diurnal peaks, i.e., one in the early morning (midnight) and the other in the late afternoon. (2) The rainfall diurnal variation experiences obvious seasonal and sub-seasonal evolutions. In cold seasons, the regional contrast of rainfall diurnal peaks decreases, with an early morning maximum over most of the southern China. Over the central eastern China, diurnal monsoon rainfall shows sub-seasonal variations with the movement of summer monsoon systems. The rainfall peak mainly occurs in the early morning (late afternoon) during the active (break) monsoon period. (3) Cloud properties and occurrence time of rainfall diurnal peaks are different for longand short-duration rainfall events. Long-duration rainfall events are dominated by stratiform precipitation, with the maximum surface rain rate and the highest profile occurring in the late night to early morning, while short-duration rainfall events are more related to convective precipitation, with the maximum surface rain rate and the highest profile occurring between the late afternoon and early night. (4) The rainfall diurnal variation is influenced by multi-scale mountain-valley and land-sea breezes as well as large-scale atmospheric circulation, and involves complicated formation and evolution of cloud and rainfall systems. The diurnal cycle of winds in the lower troposphere also contributes to the regional differences in the rainfall diurnal variation. (5) Evaluation of the model performance shows that the present numerical models are weak in simulating the rainfall diurnal variation over contiguous China. The simulations are not significantly improved by increasing the model horizontal resolution alone. The key is to reduce the uncertainty in physical parameterizations related to the rainfall processes. |
| [4] | Not Available |
| [5] | <FONT face=Verdana>本文在对比了TRMM多卫星降水分析TMPA(TRMM Multi-satellite Precipitation Analysis)资料和中国643个气象站观测降水量时空分布的基础上，采用2002~2006年夏季TMPA每小时降水量资料，用合成分析和谐波分析的方法研究了青藏高原及其周边地区夏季降水量和降水频率的日变化特征.分析结果表明，平均降水量和降水频率日变化谐波分析的标准振幅显示出青藏高原地区夏季降水具有显著的日变化特征，高原中部地区对流活动日变化最强，其次是高原西南方向的印度半岛地区.谐波分析的位相表明降水量和降水频率最大值出现的时间具有选择性，高原中部降水量最大值多集中在傍晚前后，高原以东的四川盆地通常在夜晚，尤其是在后半夜达到最大值，而长江上游和中下游地区对流活动则分别在上午和下午最为活跃.青藏高原以东地区降水量日变化的位相明显不同于其他陆地地区，也不同于高原中部，具有自西向东传播的信号，四川盆地的夜雨现象可能是高原地区对流活动日变化自西向东传播的结果.</FONT> . <FONT face=Verdana>本文在对比了TRMM多卫星降水分析TMPA(TRMM Multi-satellite Precipitation Analysis)资料和中国643个气象站观测降水量时空分布的基础上，采用2002~2006年夏季TMPA每小时降水量资料，用合成分析和谐波分析的方法研究了青藏高原及其周边地区夏季降水量和降水频率的日变化特征.分析结果表明，平均降水量和降水频率日变化谐波分析的标准振幅显示出青藏高原地区夏季降水具有显著的日变化特征，高原中部地区对流活动日变化最强，其次是高原西南方向的印度半岛地区.谐波分析的位相表明降水量和降水频率最大值出现的时间具有选择性，高原中部降水量最大值多集中在傍晚前后，高原以东的四川盆地通常在夜晚，尤其是在后半夜达到最大值，而长江上游和中下游地区对流活动则分别在上午和下午最为活跃.青藏高原以东地区降水量日变化的位相明显不同于其他陆地地区，也不同于高原中部，具有自西向东传播的信号，四川盆地的夜雨现象可能是高原地区对流活动日变化自西向东传播的结果.</FONT> |
| [6] | |
| [7] | Abstract Hourly or 3-hourly precipitation data from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Tropical Rainfall Measuring Mission (TRMM) 3B42 satellite products and rain gauge records are used to characterize East Asian summer monsoon rainfall, including spatial patterns in June鈥揂ugust (JJA) mean precipitation amount, frequency, and intensity, as well as the diurnal and semidiurnal cycles. The results show that the satellite products are comparable to rain gauge data in revealing the spatial patterns of JJA precipitation amount, frequency, and intensity, with pattern correlation coefficients for five subregions ranging from 0.66 to 0.94. The pattern correlation of rainfall amount is higher than that of frequency and intensity. Relative to PERSIANN, the TRMM product has a better resemblance with rain gauge observations in terms of both the pattern correlation and root-mean-square error. The satellite products overestimate rainfall frequency but underestimate its intensity. The diurnal (24 h) harmonic dominates subdaily variations of precipitation over most of eastern China. A late-afternoon maximum over southeastern and northeastern China and a near-midnight maximum over the eastern periphery of the Tibetan Plateau are seen in the rain gauge data. The diurnal phases of precipitation frequency and intensity are similar to those of rainfall amount in most regions, except for the middle Yangtze River valley. Both frequency and intensity contribute to the diurnal variation of rainfall amount over most of eastern China. The contribution of frequency to the diurnal cycle of rainfall amount is generally overestimated in both satellite products. Both satellite products capture well the nocturnal peak over the eastern periphery of the Tibetan Plateau and the late-afternoon peak in southern and northeastern China. Rain gauge data over the region between the Yangtze and Yellow Rivers show two peaks, with one in the early morning and the other later in the afternoon. The satellite products only capture the major late-afternoon peak. |
| [8] | |
| [9] | |
| [10] | paper uses hourly observations from 1953 to 2011 of temperature, relative humidity, and opaque cloud cover from 14 climate stations across the Canadian Prairies to analyze the impact of agricultural land use change on the diurnal cycle climate, represented by the mean temperature and relative humidity and their diurnal ranges. We show the difference between the years 1953-1991 and 1992-2011. The land use changes have been largest in Saskatchewan where 15-20% of the land area has been converted in the past four decades from summer fallow (where the land was left bare for 1 year) to annual cropping. During the growing season from 20 May to 28 August, relative humidity has increased by about 7%. During the first 2 months, 20 May to 19 July, maximum temperatures and the diurnal range of temperature have fallen by 1.2掳C and 0.6掳C, respectively, cloud cover has increased by about 4%, reducing surface net radiation by 6 W m, and precipitation has increased. We use the dry-downs after precipitation to separate the impact of cloud cover and show the coupling between evapotranspiration and relative humidity. We estimate, using reanalysis data from ERA-Interim, that increased transpiration from the larger area of cropland has reduced the surface Bowen ratio by 0.14-0.2. For the month on either side of the growing season, cloud cover has fallen slightly; maximum temperatures have increased, increasing the diurnal temperature range and the diurnal range of humidity. |
| [11] | |
| [12] | 通过对1961—2010年中国540个气象站逐日降水观测数据和高精度区域气候模式CCLM（COSMO model in climate mode）3839个格点模拟值的对比，检验CCLM模式对中国日降水的模拟能力，揭示了1961—2010年日降水分布格局的变化特征；同时利用CCLM模式对中国地区2011—2050年的日降水预估值（SRES-A1B情景），运用概率统计和极值理论方法，分析了2011—2050年日降水序列及其极值的可能变化趋势。结果表明：除华南和青藏高原西部存在着较大的偏差以外，模式和观测日降水序列的峰度和偏度的分布格局较一致，空间相关系数达到0.75以上，CCLM能够很好地模拟中国日降水的分布特征。2011—2050年，峰度和偏度在江淮部分地区、东北与内蒙中东部等地区呈显著增加趋势，降水极端事件将会增多；最大日降水量和汛期最多无降水日数在上述地区的增加，进一步反映干旱和洪涝出现概率将升高。 . 通过对1961—2010年中国540个气象站逐日降水观测数据和高精度区域气候模式CCLM（COSMO model in climate mode）3839个格点模拟值的对比，检验CCLM模式对中国日降水的模拟能力，揭示了1961—2010年日降水分布格局的变化特征；同时利用CCLM模式对中国地区2011—2050年的日降水预估值（SRES-A1B情景），运用概率统计和极值理论方法，分析了2011—2050年日降水序列及其极值的可能变化趋势。结果表明：除华南和青藏高原西部存在着较大的偏差以外，模式和观测日降水序列的峰度和偏度的分布格局较一致，空间相关系数达到0.75以上，CCLM能够很好地模拟中国日降水的分布特征。2011—2050年，峰度和偏度在江淮部分地区、东北与内蒙中东部等地区呈显著增加趋势，降水极端事件将会增多；最大日降水量和汛期最多无降水日数在上述地区的增加，进一步反映干旱和洪涝出现概率将升高。 |
| [13] | This study investigated the diurnal cycle of precipitation in Sweden using hourly ground observations for 1996-2008. General characteristics of phase and amplitude for the diurnal cycle of precipitation, both in amount and frequency, were identified. In the warm season (April-September), the 'typical' afternoon (14-16 LST) peaks are dominant over inland Sweden, whereas late night to early morning (04-06 LST) peaks with relatively weak amplitude are discernable in the east coast along the Baltic Sea. The diurnal variation is almost negligible in the cold season (October-March), due to the weak solar radiation at high latitudes. The variations of convective activity forced by solar heating and modulated by geographical characteristics were suggested as primarily factors to invoke the cycles and spatial variation identified. The observed cycle was compared with the cycle simulated by a regional climate model. The model fairly well captures the spatial pattern of the phase of the diurnal cycle. However, the warm season afternoon peak is simulated too early and too uniformly across the stations, associated with too frequent occurrences of convective rainfall events with relatively light intensity. These discrepancies point to the need to improve the convection parametrization and geographic representation of the model. |
| [14] | This study examines the diurnal cycle of precipitation over Sweden for the warm season (April to September) both in hourly observational data and in simulations from the Rossby Centre regional climate model (RCA3). A series of parallel long-term simulations of RCA3 with different horizontal resolutions - 50, 25, 12, and 6 km - were analyzed to investigate the sensitivity of the model's horizontal resolution to the simulated diurnal cycle of precipitation. Overall, a clear distinction between an afternoon peak for inland stations and an early morning peak for stations along the Eastern coast is commonly found both in observation and model results. However, the diurnal cycle estimated from the model simulations show too early afternoon peaks with too large amplitude compared to the observation. Increasing horizontal model resolution tends to reduce this bias both in peak timing and amplitude, but this resolution effect seems not to be monotonic; this is clearly seen only when comparing coarser resolution results with the 6 km resolution result. As the resolution increases, the peak timing and amplitude of the diurnal cycle of resolved large-scale precipitation become more similar to the observed cycle of total precipitation while the contribution of subgrid scale convective precipitation to the total precipitation decreases. An increase in resolution also tends to reduce too much precipitation of relatively light intensity over inland compared to the observation, which may also contribute to the more realistic simulation of the afternoon peak in convective precipitation. (C) 2011 Elsevier B.V. All rights reserved. |
| [15] | A wave-number-frequency spectral decomposition technique is used to analyze the high-resolution NOAA/Climate Prediction Center morphing technique (CMORPH) precipitation data set and to explore the differences and similarities of the diurnal variation of warm-season precipitation in the East Asia and North America downstream of big topography. The predominant phase speed of precipitation at different time scales for North America, averaged over all warm-season months (May-August) for 2003-2010, is ~20 ms, which is faster than the speed of ~14 mscalculated for East Asia. Consistent with the recent studies of the precipitation diurnal cycles for these two regions, the difference in the diurnal phase propagation is likely due to the difference in the mean steering level wind speed for these two regions. The wave-number-frequency spectral analysis further reveals the complex, multi-scale, multi-modal nature of the warm-season precipitation variation embedded within the diurnal cycle over both continents, with phase speeds varying from 10 to 30 msand wave periods varying from diurnal to a few hours. At the diurnal frequency regulated by the thermodynamically driven mountains-plains solenoids (MPSs), increased precipitation for both continents first originates in the afternoon from the eastern edge of big topography and subsequently moves downslope in the evening and reaches the broad plains area at night. More complex diurnal evolutions are observed in East Asia due to the more complex, multistep terrains east of the Tibetan Plateau and the associated localized MPS circulations. Nevertheless, increased variation of precipitation at smaller spatial and temporal scales is evident in the active phase of the dominant diurnal cycle for both continents. |
| [16] | Some new features concerning the diurnal variation of precipitation over the Tibetan Plateau (TP) are revealed from rainfall data acquired by a network of rain gauge stations and estimated by the Climate Precipitation Center Morphing (CMORPH) technique collected during the summer of 2010 and 2011. Maxima in precipitation amount and frequency are associated with the afternoon‐to‐evening precipitation regime at approximately 60% of the stations in the network. CMORPH data also capture this pattern, but miss the late morning peak that occurs at some stations. The timing of maximum occurrence agrees well with the diurnal cycle of synoptic conditions favouring the development of precipitation over this area. There is no distinct west‐to‐east propagation of the diurnal cycle, implying that the diurnal cycle is more driven by local effects than by large‐scale circulation. It turns out that the diurnal cycle in precipitation frequency depends largely on topography and landscape. The geographical transition in precipitation peak time is distinct from hilly regions (daytime peak) towards lakes and valleys (evening‐to‐nocturnal peaks). Stations located in mountainous regions (valleys) tend to experience more precipitation in either late morning or early afternoon (late afternoon or evening). Overall, precipitation amount shows a similar topographic dependence, as does the precipitation frequency, suggesting that local‐scale effects, such as the mountain valley circulation effect, has a great impact on the diurnal variation in precipitation when large‐scale dynamical processes are weak. A possible mechanism for the non‐uniform diurnal cycle of precipitation over the TP is proposed. The major conclusion is that plateau‐scale synoptic systems, as well as local circulation systems caused by the complex topography, should be taken into account when determining the diurnal variation in precipitation over the TP. |
| [17] | Not Available |
| [18] | 15 years (1998-2012) of satellite-measured precipitation data and tropical cyclone (TC) information, this study estimates the diurnal variations of TC precipitation in its inner core and outer rainbands. It is found that for both weak (tropical storms to category 1 TCs) and strong (categories 2-5 TCs) storms over all six TC basins, the TC precipitation reaches its daily maximum in the morning, but the mean rain rate and diurnal variations are larger in the inner core than in the outer rainbands. With increasing radial distance from the TC center, the diurnal amplitude of precipitation decreases, and the peak time appears progressively later. The outward propagation of diurnal signals from the TC center dominates as an internal structure of the TC convective systems. For all basins examined, the diurnal precipitation maximum within the inner core of a strong storm occurs earlier than the maximum observed in non-TC precipitation; the same result is not found for the outer rainbands. In the North Atlantic, the diurnal variations of TC precipitation in weak storms are much weaker than those in other basins, and the TC precipitation in strong storms shows a semidiurnal cycle in the inner core while exhibiting a clear diurnal cycle with a peak around noon in the outer rainbands. |
| [19] | Climatological characteristics of diurnal variations in summer precipitation over the Asian monsoon region are comprehensively investigated based on the Tropical Rainfall Measuring Mission (TRMM) satellite data during 1998鈥2008. The topographic influence on the diurnal variations and phase propagations of maximum precipitation are identified according to spatiotemporal distributions of the amplitude and peak time of the diurnal precipitation. The amplitude and phase of diurnal precipitation show a distinct geographical pattern. Significant diurnal variations occur over most of continental and coastal areas including the Maritime Continent, with the relative amplitude exceeding 40%, indicating that the precipitation peak is 1.4 times the 24-h mean. Over the landside coasts such as southeastern China and Indochina Peninsula, the relative amplitude is even greater than 100%. Although the diurnal variations of summer precipitation over the continental areas are characterized by an afternoon peak (1500鈥1800 Local Solar Time (LST)), over the central Indochina Peninsula and central and southern Indian Peninsula the diurnal phase is delayed to after 2100 LST, suggesting the diurnal behaviors over these areas different from the general continental areas. The weak diurnal variations with relative amplitudes less than 40% exist mainly over oceanic areas in the western Pacific and most of Indian Ocean, with the rainfall peak mainly occurring from midnight to early morning (0000鈥0600 LST), indicating a typical oceanic regime characterized by an early morning peak. However, apparent exceptions occur over the South China Sea (SCS), Bay of Bengal (BOB), and eastern Arabian Sea, with the rainfall peak occurring in daytime (0900鈥1500 LST). Prominent meridional propagations of the diurnal phase exist in South Asia and East Asia. Along the eastern Indian Peninsula, there is not only the southward phase propagation with the peak occurring around 25掳N but also the northward phase propagation with the peak beginning with the southernmost continent, and both reach the central Indian continent to finish. Along the same longitudes where southern China and Kalimantan are located, the diurnal phase of the former propagates from the oceanic area (northern SCS) toward the inland continent, while the phase of the latter propagates from the land area toward the outside sea, showing a landward or seaward coastal diurnal regime. A distinct zonal propagation of the diurnal phase is observed over the BOB oceanic area. The maximum precipitation zone originates from the land-sea boundary of the eastern coast of the Indian peninsula at around 0300 LST, and then propagates eastward with increasing time to reach the eastern coast of the BOB on 1800 LST, finally migrates into the Indochina continent on about 2100 LST. |
| [20] | |
| [21] | 基于1994—2008年逐年5—9月辽宁省52个气象台站的逐时降水数据，应用逐时降水量、逐时降水频次、逐时降水强度和不同持续时间降水4个指标对辽宁省降水日变化特征进行了研究。结果表明：辽宁省5—9月降水量和降水频次都呈现双峰型的日变化特征，峰值区为14:00—17:00和2:00—8:00；降水强度日变化呈现单峰型，峰值区位于14:00—17:00；各时次降水量与降水强度平均相关系数为0.8，与降水频次相关系数为0.5，降水量变化与降水强度关系密切，受降水频次影响较小；短时降水降水量和频次对总降水量和总降水次数的贡献较长持续时间降水的大，且短时降水多发于14:00—19:00，长持续时间降水主要出现于2:00—9:00。 . 基于1994—2008年逐年5—9月辽宁省52个气象台站的逐时降水数据，应用逐时降水量、逐时降水频次、逐时降水强度和不同持续时间降水4个指标对辽宁省降水日变化特征进行了研究。结果表明：辽宁省5—9月降水量和降水频次都呈现双峰型的日变化特征，峰值区为14:00—17:00和2:00—8:00；降水强度日变化呈现单峰型，峰值区位于14:00—17:00；各时次降水量与降水强度平均相关系数为0.8，与降水频次相关系数为0.5，降水量变化与降水强度关系密切，受降水频次影响较小；短时降水降水量和频次对总降水量和总降水次数的贡献较长持续时间降水的大，且短时降水多发于14:00—19:00，长持续时间降水主要出现于2:00—9:00。 |
| [22] | <p>利用山东地区16 个气象站1961~2012 年逐月降水资料以及同期大气环流指数资料，采用Mann-Kendall 非参数检验法、累积距平法、有序聚类分析法以及Mann-Whitney-Pettitt（MWP）法等方法，对最近50 a 来山东地区夏季降水及其占全年降水比例的时空变化及影响因素进行了研究。结果表明，最近50 a 来，山东地区夏季降水呈现总体下降趋势，但有显著的阶段性。其中，沿海地区变化幅度小于内陆，其阶段转换和突变也早于内陆，内陆中山区又早于平原。沿海地区夏季降水占年降水比例呈现总体上升趋势，但无明显的阶段性和突变现象；而内陆地区呈现总体下降趋势，但存在阶段性和突变现象，其中山地与平原间又有差异。分析表明，山东地区夏季降水变化与同期东亚夏季风、南方涛动和北极涛动之间有显著的响应关系，但在沿海与内陆、山地与平原之间存在差异。</p> . <p>利用山东地区16 个气象站1961~2012 年逐月降水资料以及同期大气环流指数资料，采用Mann-Kendall 非参数检验法、累积距平法、有序聚类分析法以及Mann-Whitney-Pettitt（MWP）法等方法，对最近50 a 来山东地区夏季降水及其占全年降水比例的时空变化及影响因素进行了研究。结果表明，最近50 a 来，山东地区夏季降水呈现总体下降趋势，但有显著的阶段性。其中，沿海地区变化幅度小于内陆，其阶段转换和突变也早于内陆，内陆中山区又早于平原。沿海地区夏季降水占年降水比例呈现总体上升趋势，但无明显的阶段性和突变现象；而内陆地区呈现总体下降趋势，但存在阶段性和突变现象，其中山地与平原间又有差异。分析表明，山东地区夏季降水变化与同期东亚夏季风、南方涛动和北极涛动之间有显著的响应关系，但在沿海与内陆、山地与平原之间存在差异。</p> |
| [23] | Abstract Top of page Abstract 1.Introduction 2.Satellite Precipitation Products and Reanalysis Data 3.Diurnal Cycle of Rainfall Along the YRV in Spring, Presummer, and Midsummer 4.Statistical Analysis of the Space Scale and Propagation of Prevailing Rain Events 5.Lower Tropospheric Conditions Related to Morning Rainfall Over YRV 6.Summary AppendixA::Statistics of the Space Scale and Movement of Rain Events Using TRMM Data Acknowledgments References Supporting Information [1] A 12 year archive of the Tropical Rainfall Measuring Mission (TRMM) rain rate is used to document the regionality of diurnal rainfall cycle in the Yangtze River Valley (YRV). The regional rain peaks, local phase shifts, rain event's behavior, and related seasonal change from March to August are examined. In the middle reach of YRV, rainfall appears mainly in early morning and displays a distinct local shift of diurnal phase. Such features are well established at each presummer (from May to June) and result from the eastward migrating events with a late night growth in size. They are supported by the low-level convergence that moves from the east slope of the Tibetan Plateau to the middle reach of YRV, as the deviated wind vector rotates clockwise to enhance southerlies at late night and southwesterlies in the morning. In the lower reach of YRV, however, one observes an eruption of morning rainfall with less local difference in diurnal phase. Morning rainfall is active in presummers of some years but suppressed in some others, contributing greatly to the variance of rainfall budget and resulting in anomalous wet/dry seasons. It is found to arise from a local growth of rain events rather than the migrating events from the middle reach. A majority of these organized convections prefer to form and develop in a belt-shaped zone where the nocturnal southwesterlies of warm/moist air impinge on the Meiyu front in the lower troposphere. |
| [24] | <FONT face=Verdana>利用祁连山区及河西走廊20个气象站的气温和降水资料,运用一元回归分析、5 a趋势滑动、Spline插值法,进行气候变化的时空分布特征分析。结果表明：祁连山及河西走廊的气温在20世纪60—80年代偏低,90年代以后偏高;气温的年际变化率为0.0298 ℃·a<SUP>-1</SUP>,并且升温趋势显著;大部分地区的增温幅度在0.02~0.04 ℃·a<SUP>-1</SUP>之间,其中祁连山区的增温幅度大于走廊平原;气温的年际变化幅度在空间上呈现出南北分异,大致以黑河干流为界,中东部地区的增温幅度从南到北呈增大趋势,而中西部地区从南到北呈减小趋势;降水在60年代偏少,其他年代偏多,其中2000年以后明显增多;降水的年际变化率为0.6571 mm·a<SUP>-1</SUP>,不过增加趋势不太明显;大部分地区降水的增加幅度在0~2 mm·a<SUP>-1</SUP>之间,其中祁连山区的增加幅度大于走廊平原;降水的年际变化幅度在空间上呈现出南北分异,其增加幅度从南到北呈减小趋势。<BR></FONT> . <FONT face=Verdana>利用祁连山区及河西走廊20个气象站的气温和降水资料,运用一元回归分析、5 a趋势滑动、Spline插值法,进行气候变化的时空分布特征分析。结果表明：祁连山及河西走廊的气温在20世纪60—80年代偏低,90年代以后偏高;气温的年际变化率为0.0298 ℃·a<SUP>-1</SUP>,并且升温趋势显著;大部分地区的增温幅度在0.02~0.04 ℃·a<SUP>-1</SUP>之间,其中祁连山区的增温幅度大于走廊平原;气温的年际变化幅度在空间上呈现出南北分异,大致以黑河干流为界,中东部地区的增温幅度从南到北呈增大趋势,而中西部地区从南到北呈减小趋势;降水在60年代偏少,其他年代偏多,其中2000年以后明显增多;降水的年际变化率为0.6571 mm·a<SUP>-1</SUP>,不过增加趋势不太明显;大部分地区降水的增加幅度在0~2 mm·a<SUP>-1</SUP>之间,其中祁连山区的增加幅度大于走廊平原;降水的年际变化幅度在空间上呈现出南北分异,其增加幅度从南到北呈减小趋势。<BR></FONT> |
| [25] | |
| [26] | 利用国家气象信息中心研制的全国30000多个地面自动站降 水与 CMORPH (Climate Prediction Center Morphing technique)卫星反演降水融合而成的融合降水产品，分析了融合降水平均偏差和均方根误差的时空分布特征，探讨了不同降水量级以及站点稀疏区和密集 区的融合效果，结果表明：融合降水的平均偏差和均方根误差量值均较卫星反演降水有显著减小，随时间的变化幅度不大且误差的区域性差异减弱；融合降水不同量 级降水日数分布接近于地面观测降水，虽高估了雨强小于等于4 mm/d的降水，低估了大于4 mm/d高值降水，但同一量级下的误差比卫星反演降水大幅减小，且随着降水强度的增加改善效果明显；站点密集区的融合降水值主要是取决于地面观测降水；站 点稀疏区在没有站点分布时，融合降水值主要取决于卫星反演降水，但随着站点个数增加，地面观测降水在融合降水中所占比重逐渐增大，且超过了卫星反演降水的 作用。可见融合降水充分有效利用了地面观测降水和卫星反演降水各自的优势，融合效果明显。 . 利用国家气象信息中心研制的全国30000多个地面自动站降 水与 CMORPH (Climate Prediction Center Morphing technique)卫星反演降水融合而成的融合降水产品，分析了融合降水平均偏差和均方根误差的时空分布特征，探讨了不同降水量级以及站点稀疏区和密集 区的融合效果，结果表明：融合降水的平均偏差和均方根误差量值均较卫星反演降水有显著减小，随时间的变化幅度不大且误差的区域性差异减弱；融合降水不同量 级降水日数分布接近于地面观测降水，虽高估了雨强小于等于4 mm/d的降水，低估了大于4 mm/d高值降水，但同一量级下的误差比卫星反演降水大幅减小，且随着降水强度的增加改善效果明显；站点密集区的融合降水值主要是取决于地面观测降水；站 点稀疏区在没有站点分布时，融合降水值主要取决于卫星反演降水，但随着站点个数增加，地面观测降水在融合降水中所占比重逐渐增大，且超过了卫星反演降水的 作用。可见融合降水充分有效利用了地面观测降水和卫星反演降水各自的优势，融合效果明显。 |
| [27] | |
| [28] | 基于全国自动站观测降水量和CMORPH（CPCMORPHingtechnique）卫星反演降水资料，采用PDF（probabilitydensityfunction）和OI（optimalinterpolation）两步融合方法生成了中国区域1h、0．1°×0．1°分辨率的降水量融合产品。本文分别从产品误差的时空分布特征、不同降水量级和不同累积时间下的产品质量、三种站网密度下的融合效果以及对强降水过程监测能力等方面对比评估了融合降水产品质量。结果表明，融合降水产品有效利用了地面观测和卫星反演降水各自的优势，在降水量值和空间分布上均更为合理；融合产品平均偏差和均方根误差均减小，随时间的变化幅度不大且区域性分布特征减弱；融合产品与融合前的卫星反演降水产品相比在中雨（1．0～2．5mm／h）、中到大雨（1．0～8．0mm／h）、暴雨及以上（≥8．0mm／h）的相对误差分别为一1．675％、小于15．0％、30．0％左右，且随着累积时间的增加，产品质量进一步提高；该产品能准确抓住强降水过程．在定量监测强降水中具有优势。 . 基于全国自动站观测降水量和CMORPH（CPCMORPHingtechnique）卫星反演降水资料，采用PDF（probabilitydensityfunction）和OI（optimalinterpolation）两步融合方法生成了中国区域1h、0．1°×0．1°分辨率的降水量融合产品。本文分别从产品误差的时空分布特征、不同降水量级和不同累积时间下的产品质量、三种站网密度下的融合效果以及对强降水过程监测能力等方面对比评估了融合降水产品质量。结果表明，融合降水产品有效利用了地面观测和卫星反演降水各自的优势，在降水量值和空间分布上均更为合理；融合产品平均偏差和均方根误差均减小，随时间的变化幅度不大且区域性分布特征减弱；融合产品与融合前的卫星反演降水产品相比在中雨（1．0～2．5mm／h）、中到大雨（1．0～8．0mm／h）、暴雨及以上（≥8．0mm／h）的相对误差分别为一1．675％、小于15．0％、30．0％左右，且随着累积时间的增加，产品质量进一步提高；该产品能准确抓住强降水过程．在定量监测强降水中具有优势。 |
| [29] | <p>Using hourly rain gauge data at more than 30,000 automatic weather stations in China, in conjunction with the Climate Precipitation Center Morphing (CMORPH) precipitation product for the 2008–2010 warm seasons (from May through September), we assess the capability of the probability density function–optimal interpolation (PDF-OI) methods in generating the daily, 0.25° × 0.25° and hourly, 0.1° × 0.1° merged precipitation products between gauge observations and the CMORPH product. We find that error correlation, error variances of gauge and satellite data, and matching strategy in the PDF-OI method are dependent on the spatial and temporal resolutions of the used data. Efforts to improve the parameters and matching strategy for the hourly and 0.1° × 0.1° product have been conducted. These improvements are not only suitable to a high-frequency depiction of no-rain events, but accurately describe the error structures of hourly gauge and satellite fields. The successive merged precipitation algorithm or product is called the original PDF-OI (Orig_PDF-OI) and the improved PDF-OI, respectively. The cross-validation results show that the improved method reduces systematic bias and random errors effectively compared with both the CMORPH precipitation and the Orig_PDF-OI. The improved merged precipitation product over China at hourly, 0.1° resolution is generated from 2008 to 2010. Compared with the Orig_PDF-OI, the improved product reduces the underestimation greatly and has smaller bias and root-mean-square error, and higher spatial correlation. The improved product can better capture some varying features of hourly precipitation in heavy weather events.</p> |
| [30] | . |
| [31] | 基于CMORPH融合降水产品 与地面观测雨量资料,分别采用网格算术平均法与泰森多边形法估算淮河流域15个子单元2008—2011年汛期(6—9月)逐日面雨量,并对2种面雨量估 算结果进行对比统计分析。结果表明:15个子单元2种面雨量估算结果具有系统性差异,两者之间存在显著线性关系;逐日面雨量估算结果也存在系统性差异,利 用地面观测雨量资料估算的面雨量普遍大于利用CMORPH融合降水产品的估算结果;2种面雨量估算结果在降水量级上有很好的对应关系,各降水量级完全对应 的总体比例为78.8%,相差1个量级的比例为20.5%,其中小雨量级完全对应的比例高达91.4%。 . 基于CMORPH融合降水产品 与地面观测雨量资料,分别采用网格算术平均法与泰森多边形法估算淮河流域15个子单元2008—2011年汛期(6—9月)逐日面雨量,并对2种面雨量估 算结果进行对比统计分析。结果表明:15个子单元2种面雨量估算结果具有系统性差异,两者之间存在显著线性关系;逐日面雨量估算结果也存在系统性差异,利 用地面观测雨量资料估算的面雨量普遍大于利用CMORPH融合降水产品的估算结果;2种面雨量估算结果在降水量级上有很好的对应关系,各降水量级完全对应 的总体比例为78.8%,相差1个量级的比例为20.5%,其中小雨量级完全对应的比例高达91.4%。 |
| [32] | <p>库姆塔格沙漠极端干旱,而其南部阿尔金山比较湿润.研究库姆塔格沙漠及南部阿尔金山的降水特征,对揭示库姆塔格沙漠水源补给机制和地貌形成原因具有重要作用.本文利用中国自动气象站与CMORPH融合逐时降水量0.1°网格数据集,分析了库姆塔格沙漠及阿尔金山的降水特征.结果表明:(1)库姆塔格沙漠降水主要集中在夏季,其他季节降水较少;而阿尔金山降水主要集中在春、秋两季,并存在一条降水量大值带,3月范围最大而夏季消失;(2)阿尔金山对库姆塔格沙漠的水源补给作用主要体现在春、秋两季,夏季降水基本与库姆塔格沙漠持平,春季降水超出库姆塔格沙漠最多;(3)阿尔金山各月平均逐小时降水量演变特征有很大不同,冬季12、1月及夏季6、7月每月逐时降水演变特征以"凌晨型"为主,可能与凌晨云顶辐射冷却引起的大气层结不稳定有关;春、秋两季每月逐时降水演变特征以"午后-黄昏型"为主, 可能与午后太阳辐射地面加热引起的大气层结不稳定有关;2、8月是两种类型的过渡时期.本文研究结果可为探索库姆塔格沙漠水源补给机制以及"羽毛状沙丘"独特的沙漠景观形成原因提供一定的参考依据.</p> . <p>库姆塔格沙漠极端干旱,而其南部阿尔金山比较湿润.研究库姆塔格沙漠及南部阿尔金山的降水特征,对揭示库姆塔格沙漠水源补给机制和地貌形成原因具有重要作用.本文利用中国自动气象站与CMORPH融合逐时降水量0.1°网格数据集,分析了库姆塔格沙漠及阿尔金山的降水特征.结果表明:(1)库姆塔格沙漠降水主要集中在夏季,其他季节降水较少;而阿尔金山降水主要集中在春、秋两季,并存在一条降水量大值带,3月范围最大而夏季消失;(2)阿尔金山对库姆塔格沙漠的水源补给作用主要体现在春、秋两季,夏季降水基本与库姆塔格沙漠持平,春季降水超出库姆塔格沙漠最多;(3)阿尔金山各月平均逐小时降水量演变特征有很大不同,冬季12、1月及夏季6、7月每月逐时降水演变特征以"凌晨型"为主,可能与凌晨云顶辐射冷却引起的大气层结不稳定有关;春、秋两季每月逐时降水演变特征以"午后-黄昏型"为主, 可能与午后太阳辐射地面加热引起的大气层结不稳定有关;2、8月是两种类型的过渡时期.本文研究结果可为探索库姆塔格沙漠水源补给机制以及"羽毛状沙丘"独特的沙漠景观形成原因提供一定的参考依据.</p> |
| [33] | 2012年7月21—22日，61年以来最强降水袭击北京，北京大部分地区出现大暴雨，局部特大暴雨，过程雨量大、雨势强、范围广，造成了严重影响。此次强降水配置较为典型，业务预报提前指示出了此次过程，但预报结果存在强度偏弱，峰值偏晚等偏差。在对此次大暴雨进行综合分析的基础上，利用中国自动气象站与NOAA气候预测中心卫星反演降水资料CMORPH（Climate Prediction Center Morphing Technique）产品融合的逐时降水量网格数据资料作为观测，着重对北京市气象局新的快速更新循环同化和预报系统（BJ-RUC v2.0）的3 km高分辨率模式分析场和预报场进行了检验与分析，以期通过对中尺度模式预报性能的了解，为暴雨可预报性问题提供进一步的参考。研究结果表明，此次特大暴雨过程水汽条件极佳，降水区域较为集中，呈现西南—东北走向的中尺度雨带特征。利用常规检验评分对预报降水的时间序列进行检验发现，预报降水在时间上滞后，降水强度偏弱，存在偏西南的位置误差，并且未能反映降水系统的线状特征。进一步利用检验连续降水区域定量降水预报的CRA（contiguous rain area）方法，对预报误差进行分解表明，整体降水（>5 mm/h）的主要误差来自于位置和形状误差；而在暴雨（>20 mm/h）的预报中，降水强度的偏差占误差的主要部分。最后结合对预报场大尺度环流和物理量的诊断（水汽条件和不稳定条件），分析探讨了此次极端暴雨预报不佳的原因。 . 2012年7月21—22日，61年以来最强降水袭击北京，北京大部分地区出现大暴雨，局部特大暴雨，过程雨量大、雨势强、范围广，造成了严重影响。此次强降水配置较为典型，业务预报提前指示出了此次过程，但预报结果存在强度偏弱，峰值偏晚等偏差。在对此次大暴雨进行综合分析的基础上，利用中国自动气象站与NOAA气候预测中心卫星反演降水资料CMORPH（Climate Prediction Center Morphing Technique）产品融合的逐时降水量网格数据资料作为观测，着重对北京市气象局新的快速更新循环同化和预报系统（BJ-RUC v2.0）的3 km高分辨率模式分析场和预报场进行了检验与分析，以期通过对中尺度模式预报性能的了解，为暴雨可预报性问题提供进一步的参考。研究结果表明，此次特大暴雨过程水汽条件极佳，降水区域较为集中，呈现西南—东北走向的中尺度雨带特征。利用常规检验评分对预报降水的时间序列进行检验发现，预报降水在时间上滞后，降水强度偏弱，存在偏西南的位置误差，并且未能反映降水系统的线状特征。进一步利用检验连续降水区域定量降水预报的CRA（contiguous rain area）方法，对预报误差进行分解表明，整体降水（>5 mm/h）的主要误差来自于位置和形状误差；而在暴雨（>20 mm/h）的预报中，降水强度的偏差占误差的主要部分。最后结合对预报场大尺度环流和物理量的诊断（水汽条件和不稳定条件），分析探讨了此次极端暴雨预报不佳的原因。 |
| [34] | . |
| [35] | During the past five decades, fluctuations of glaciers were reconstructed from historical documents, aerial photographs, and remote sensing data. From 1956 to 2003, 910 glaciers investigated had reduced in area by 21.7% of the 1956 value, with a mean reduction for the individual glacier of 0.10 km(2). The relative area reductions of small glaciers were usually higher than those of large ones, which exhibited larger absolute loss, indicating that the small glaciers were more sensitive to climate change than large ones. Over the past similar to 50 years, glacier area decreased by 29.6% in the Heihe (sic) River basin and 18.7% in the Beidahe (sic) River basin, which were the two regions investigated in the Middle Qilian (sic) Mountain region. Compared with other areas of the Qilian Mountain region, the most dramatic glacier shrinkage had occurred in the Middle Qilian Mountain region, mainly resulting from rapid rising temperatures. Regional differences in glacier area changes are related to local climate conditions, the relative proportion of glaciers in different size classes, and other factors. |
| [36] | Glaciers in the Qilian mountains, located in the northeastern part of the Tibetan Plateau, constitute an important freshwater resource for downstream populations and natural systems. To enhance our understanding of the variability of the glaciers, temporally and spatially comprehensive information on them is needed. In this study, the glacier outlines of ~1990, ~2000 and ~2010 for the whole area were delineated in a semi-automated manner using band TM3/TM5 ratio images of Landsat ETM+ or TM scenes with the help of a merged ASTER GDEM/SRTM v4.1 digital elevation model. Combining our own results with those of previously published studies that span the period back to 1956, we found that the glacier area shrank by 30脗卤8% from 1956 to 2010 and the shrinkage accelerated remarkably in the past two decades. The linear trends of annual air temperature and precipitation measured at weather stations within the glacierized areas were 0.03-0.058C a-1 (significant only after 2000) and 0.37-1.58mm a-1 (not significant) respectively from 1961 to 2010. Glaciers shrank mainly due to the increasing temperature. Glaciers in the Qilian mountains are very unlikely to have experienced positive mass balance over the past decade. Moreover, given the trend toward higher temperatures, the glaciers in this region will continue to shrink. |
| [37] | 利用祁连山区的逐时、逐日降水资料和山丹军马场大黄沟的云杉树轮宽度资料，研究祁连山区的降水时空变化和分布特征。研究发现：海拔高度对该地区降水有较大影响，并且降水主要发生在午后和夜间；近40 a来，该地区极端降水频次出现了增加趋势，增加幅度达1.25 d/10 a。利用一元二次回归模型重建这一区域200 a以来的降水历史序列。分析表明：整体上19世纪降水比20世纪更加丰富，20世纪初降水出现了突变特征，并逐渐趋于干旱，在20世纪20、30年代曾有严重的旱灾发生，这与该时期在我国北方大范围的干旱事件相一致。 . 利用祁连山区的逐时、逐日降水资料和山丹军马场大黄沟的云杉树轮宽度资料，研究祁连山区的降水时空变化和分布特征。研究发现：海拔高度对该地区降水有较大影响，并且降水主要发生在午后和夜间；近40 a来，该地区极端降水频次出现了增加趋势，增加幅度达1.25 d/10 a。利用一元二次回归模型重建这一区域200 a以来的降水历史序列。分析表明：整体上19世纪降水比20世纪更加丰富，20世纪初降水出现了突变特征，并逐渐趋于干旱，在20世纪20、30年代曾有严重的旱灾发生，这与该时期在我国北方大范围的干旱事件相一致。 |
| [38] | 为了发展一套适用于中国区域的高分辨率（0.1°×0.1°）逐时降水产品，以CMORPH卫星反演降水为背景场，以基于3万个自动气象站观测的逐时降水量分析的中国降水格点分析产品（Chinese Precipitation Analyses，CPA）作为地面观测场，采用最优插值方法对二者进行了融合试验。用2009年6—8月的样本统计分析了卫星反演与地面观测降水的误差及其协相关形式，按照误差结构来分配权重。融合试验的个例检验表明，该方案在有站点的地区能较好地引入地面观测信息，在没有站点观测的地区则保留CMORPH的原始信息，最终形成一套覆盖中国区域的高时空分辨率的降水场。2009年6—8月独立样本检验的统计结果也表明，该融合产品的平均偏差、均方根误差、相对误差分别为-0.004 mm/h、1.271 mm/h和15.964%，平均空间相关系数达到0.778，与融合前CMORPH的各统计值相比，改进幅度基本都超过了50%，且与风云系列卫星的同类型产品相比精度也有一定程度的提高。 . 为了发展一套适用于中国区域的高分辨率（0.1°×0.1°）逐时降水产品，以CMORPH卫星反演降水为背景场，以基于3万个自动气象站观测的逐时降水量分析的中国降水格点分析产品（Chinese Precipitation Analyses，CPA）作为地面观测场，采用最优插值方法对二者进行了融合试验。用2009年6—8月的样本统计分析了卫星反演与地面观测降水的误差及其协相关形式，按照误差结构来分配权重。融合试验的个例检验表明，该方案在有站点的地区能较好地引入地面观测信息，在没有站点观测的地区则保留CMORPH的原始信息，最终形成一套覆盖中国区域的高时空分辨率的降水场。2009年6—8月独立样本检验的统计结果也表明，该融合产品的平均偏差、均方根误差、相对误差分别为-0.004 mm/h、1.271 mm/h和15.964%，平均空间相关系数达到0.778，与融合前CMORPH的各统计值相比，改进幅度基本都超过了50%，且与风云系列卫星的同类型产品相比精度也有一定程度的提高。 |
| [39] | <FONT face=Verdana>根据祁连山区海拔2800 m以上的5个气象站点的气温及降水资料， 分析了近50年的气候变化、研究表明, 50年来祁连山区年平均气温呈上升趋势， 突变出现在1980年代中期， 1980年代中期以前增温缓慢， 以后增温明显加快。冬季变暖的趋势远大于夏季， 夜间升温幅度远大于白天， 祁连山区气温以东西两段增温幅度最大； 祁连山区降水量呈增加趋势， 少雨年在1960年代和1970年代， 多雨年在近20年, 春季和夏季有明显上升趋势， 祁连山西段降水量增加幅度明显。</FONT> . <FONT face=Verdana>根据祁连山区海拔2800 m以上的5个气象站点的气温及降水资料， 分析了近50年的气候变化、研究表明, 50年来祁连山区年平均气温呈上升趋势， 突变出现在1980年代中期， 1980年代中期以前增温缓慢， 以后增温明显加快。冬季变暖的趋势远大于夏季， 夜间升温幅度远大于白天， 祁连山区气温以东西两段增温幅度最大； 祁连山区降水量呈增加趋势， 少雨年在1960年代和1970年代， 多雨年在近20年, 春季和夏季有明显上升趋势， 祁连山西段降水量增加幅度明显。</FONT> |
| [40] | Based on a 0.5°×0.5° daily gridded precipitation dataset and observations in meteorological stations released by the National Meteorological Information Center, the interannual variation of areal precipitation in the Qilian Mountains during 1961–2012 is investigated using principal component analysis (PCA) and regression analysis, and the relationship between areal precipitation and drought accumulation intensity is also analyzed. The results indicate that the spatial distribution of precipitation in the Qilian Mountains can be well reflected by the gridded dataset. The gridded data-based precipitation in mountainous region is generally larger than that in plain region, and the eastern section of the mountain range usually has more precipitation than the western section. The annual mean areal precipitation in the Qilian Mountains is 724.9×10 8 m 3 , and the seasonal means in spring, summer, autumn and winter are 118.9×10 8 m 3 , 469.4×10 8 m 3 , 122.5×10 8 m 3 and 14.1×10 8 m 3 , respectively. Summer is a season with the largest areal precipitation among the four seasons, and the proportion in summer is approximately 64.76%. The areal precipitation in summer, autumn and winter shows increasing trends, but a decreasing trend is seen in spring. Among the four seasons, summer have the largest trend magnitude of 1.7×10 8 m 3 61a –1 . The correlation between areal precipitation in the mountainous region and dry-wet conditions in the mountains and the surroundings can be well exhibited. There is a negative correlation between drought accumulation intensity and the larger areal precipitation is consistent with the weaker drought intensity for this region. |
| [41] | ERA-Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim project was conducted in part to prepare for a new atmospheric reanalysis to replace ERA-40, which will extend back to the early part of the twentieth century. This article describes the forecast model, data assimilation method, and input datasets used to produce ERA-Interim, and discusses the performance of the system. Special emphasis is placed on various difficulties encountered in the production of ERA-40, including the representation of the hydrological cycle, the quality of the stratospheric circulation, and the consistency in time of the reanalysed fields. We provide evidence for substantial improvements in each of these aspects. We also identify areas where further work is needed and describe opportunities and objectives for future reanalysis projects at ECMWF. Copyright (C) 2011 Royal Meteorological Society |
| [42] | 利用1960-2009 年的日降水量资料,采用线性趋势、5 年趋势滑动、IDW 空间插值、Morlet 小波分析、Mann-Kendall 突变检验等方法,对祁连山及河西走廊地区不同等级降水日数和降水强度的时空变化特征进行了研究。结果表明:不同等级降水日数和降水强度的多年平均在空间上既表现出东西分异,也表现出南北分异;不同等级降水日数的年际变化在绝大部分区域呈增多趋势,且自东向西增幅减小,大雨强度的年际变化在绝大部分区域呈增大趋势,其它等级降水强度为部分区域呈增大趋势,部分区域呈减小趋势;小雨、中雨日数的年际变化呈显著增多趋势,大雨日数呈明显增多趋势,暴雨日数呈不明显增多趋势,小雨、大雨强度的年际变化呈不明显减小趋势,中雨、暴雨强度呈不明显增大趋势;不同等级降水日数变化的周期集中在2a、5a、8a、11a、19a,不同等级降水强度变化的周期集中在2a、5a、11a、15a、25a;除小雨强度突变减小外,其它等级降水日数均突变增多,降水强度均突变增大,降水量的增加主要是降水日数的增多造成的,其中小雨、中雨日数的增多贡献最大。 . 利用1960-2009 年的日降水量资料,采用线性趋势、5 年趋势滑动、IDW 空间插值、Morlet 小波分析、Mann-Kendall 突变检验等方法,对祁连山及河西走廊地区不同等级降水日数和降水强度的时空变化特征进行了研究。结果表明:不同等级降水日数和降水强度的多年平均在空间上既表现出东西分异,也表现出南北分异;不同等级降水日数的年际变化在绝大部分区域呈增多趋势,且自东向西增幅减小,大雨强度的年际变化在绝大部分区域呈增大趋势,其它等级降水强度为部分区域呈增大趋势,部分区域呈减小趋势;小雨、中雨日数的年际变化呈显著增多趋势,大雨日数呈明显增多趋势,暴雨日数呈不明显增多趋势,小雨、大雨强度的年际变化呈不明显减小趋势,中雨、暴雨强度呈不明显增大趋势;不同等级降水日数变化的周期集中在2a、5a、8a、11a、19a,不同等级降水强度变化的周期集中在2a、5a、11a、15a、25a;除小雨强度突变减小外,其它等级降水日数均突变增多,降水强度均突变增大,降水量的增加主要是降水日数的增多造成的,其中小雨、中雨日数的增多贡献最大。 |
| [43] | <FONT face=Verdana>基于祁连山区2007年7～8月地基GPS遥感的大气可降水量（Precipitable Water,PW）资料、 探空资料和自动气象站资料， 采用谐波分析等方法， 分析了祁连山区夏季PW的日变化特征, 并初步探讨其成因。结果表明： 祁连山区夏季PW具有明显的日变化特征。PW日变化特征在无降水日比有降水日更显著。日循环（24 h）与半日循环（12 h）是PW日变化的主要信号。在无降水日， PW日变化以日循环为主， 振幅为0.8～1.6 mm， 峰值出现的时间在18:00～21:00（北京时， 下同）。半日循环的振幅为0.6～0.7 mm， 峰值出现的时间在05:00～06:00和17:00～18:00。在有降水日， 不同站点PW日变化特征有所不同， 有的以日循环为主导， 有的以半日循环为主导。PW日变化与逐时累积降水频次日变化具有明显的先后关系， 两者日变化的位相差为2.5 h。PW日变化与气温和比湿等要素的日变化以及山谷风演变有关。</FONT><P> </P> . <FONT face=Verdana>基于祁连山区2007年7～8月地基GPS遥感的大气可降水量（Precipitable Water,PW）资料、 探空资料和自动气象站资料， 采用谐波分析等方法， 分析了祁连山区夏季PW的日变化特征, 并初步探讨其成因。结果表明： 祁连山区夏季PW具有明显的日变化特征。PW日变化特征在无降水日比有降水日更显著。日循环（24 h）与半日循环（12 h）是PW日变化的主要信号。在无降水日， PW日变化以日循环为主， 振幅为0.8～1.6 mm， 峰值出现的时间在18:00～21:00（北京时， 下同）。半日循环的振幅为0.6～0.7 mm， 峰值出现的时间在05:00～06:00和17:00～18:00。在有降水日， 不同站点PW日变化特征有所不同， 有的以日循环为主导， 有的以半日循环为主导。PW日变化与逐时累积降水频次日变化具有明显的先后关系， 两者日变化的位相差为2.5 h。PW日变化与气温和比湿等要素的日变化以及山谷风演变有关。</FONT><P> </P> |
| [44] | Abstract<br/><p class="a-plus-plus">The nocturnal precipitation in the Sichuan Basin in summer has been studied in many previous works. This paper expands the study on the diurnal cycle of precipitation in the Sichuan Basin to the whole year. Results show that the nocturnal precipitation has a specific quasi-stationary feature in the basin. It occurs not only in summer but also in other three seasons, even more remarkable in spring and autumn than in summer. There is a prominent eastward timing delay in the nocturnal precipitation, that is, the diurnal peak of precipitation occurs at early-night in the western basin whereas at late-night in the center and east of the basin. The Tibetan Plateau plays an essential role in the formation of this quasi-stationary nocturnal precipitation. The early-night peak of precipitation in the western basin is largely due to strong ascending over the plateau and its eastern lee side. In the central and eastern basin, three coexisting factors contribute to the late-night peak of precipitation. One is the lower-tropospheric southwesterly flow around the southeastern edge of the Tibetan Plateau, which creates a strong cyclonic rotation and ascendance in the basin at late-night, as well as brings abundant water vapor. The second is the descending motion downslope along the eastern lee side of the plateau, together with an air mass accumulation caused by the warmer air mass transport from the southeast of the Yunnan-Guizhou Plateau, creating a diabatic warming at low level of the troposphere in the central basin. The third is a cold advection from the plateau to the basin at late-night, which leads to a cooling in the middle troposphere over the central basin. All these factors are responsible for precipitation to occur at late-night in the central to eastern basin.</p><br/> |
| [45] | 本文利用四川地区1971～2012年29个气象站逐小时降水资料,计算四川地区雨季(5～9月)夜雨比例、夜雨强度和夜雨频次,并通过区域平均与趋势分析等统计方法,分析了其空间差异与时间变化特征,结果表明:(1)四川地区雨季夜雨占日降水量的比例较大,且具有显著的区域性差异,盆地西南部的夜雨占日降水量的比例最大,川西高原东北与川东北则为明显的两个低值区;(2)川东北地区雨季具有夜雨占日降水量的比例较小、夜雨发生概率也较低、但其夜雨强度却较大的特征,川西高原则与之相反,而盆地西南部的夜雨发生频次虽然不是很高,但夜雨强度和夜雨比例都较大;(3)42年平均四川地区雨季逐日变化,夜雨占日降水量的比例表现为先下降、后上升的特征,夜雨强度与夜雨比例相反,呈先上升、后下降的波动趋势,而夜雨频次的逐日变化呈现出明显的双峰特征;(4)四川地区夜雨比例、夜雨强度和夜雨频次的年变化具有一定差异。20世纪70、80年代,其夜雨频次和夜雨比例均较大,但呈减少趋势,而夜雨强度20世纪70年代较小,80年代较大,呈增大趋势。20世纪90年代,夜雨强度、频次和比例都处于较低状态;21世纪,夜雨强度和夜雨比例都开始明显增大,而夜雨频次增大相对滞后,其中,21世纪夜雨频次和夜雨比例波动明显。 . 本文利用四川地区1971～2012年29个气象站逐小时降水资料,计算四川地区雨季(5～9月)夜雨比例、夜雨强度和夜雨频次,并通过区域平均与趋势分析等统计方法,分析了其空间差异与时间变化特征,结果表明:(1)四川地区雨季夜雨占日降水量的比例较大,且具有显著的区域性差异,盆地西南部的夜雨占日降水量的比例最大,川西高原东北与川东北则为明显的两个低值区;(2)川东北地区雨季具有夜雨占日降水量的比例较小、夜雨发生概率也较低、但其夜雨强度却较大的特征,川西高原则与之相反,而盆地西南部的夜雨发生频次虽然不是很高,但夜雨强度和夜雨比例都较大;(3)42年平均四川地区雨季逐日变化,夜雨占日降水量的比例表现为先下降、后上升的特征,夜雨强度与夜雨比例相反,呈先上升、后下降的波动趋势,而夜雨频次的逐日变化呈现出明显的双峰特征;(4)四川地区夜雨比例、夜雨强度和夜雨频次的年变化具有一定差异。20世纪70、80年代,其夜雨频次和夜雨比例均较大,但呈减少趋势,而夜雨强度20世纪70年代较小,80年代较大,呈增大趋势。20世纪90年代,夜雨强度、频次和比例都处于较低状态;21世纪,夜雨强度和夜雨比例都开始明显增大,而夜雨频次增大相对滞后,其中,21世纪夜雨频次和夜雨比例波动明显。 |
| [46] | The projected temporal evolution in the interannual variability of East Asian summer rainfall in the 21st century is investigated here, by analyzing the simulated results of 18 coupled models under the 20th century climate experiment and scenario A1B. The multi-model ensemble (MME) mean projects two prominent changes in the interannual variability of East Asian summer rainfall in the 21st century under scenario A1B. The first change occurs around the 2030s, with a small change before and a large increase afterward. The intensity of the interannual variability increases up to approximately 0.53 mm/d in the 2070s, representing an increase of approximately 30% relative to the early 21st century. The second change happens around the 2070s, with a decrease afterward. By the end of the 21st century, the increase is approximately 12% relative to the early 21st century. The interannual variability of two circulation factors, the western North Pacific subtropical high (WNPSH) and the East Asian upper-tropospheric jet (EAJ), are also projected to exhibit two prominent changes around the 2030s and 2070 under scenario A1B, with consistent increases and decreases afterward, respectively. The MME result also projects two prominent changes in the interannual variability of water vapor transported to East Asia at 850 hPa, which occurs separately around the 2040s and 2070s, with a persistent increase and decrease afterward. Meanwhile, the precipitable water interannual variability over East Asia and the western North Pacific is projected to exhibit two prominent enhancements around the 2030s and 2060s and an increase from 0.1 kg/m 2 in the early 21st century to 0.5 kg/m 2 at the end of the 21st century, implying a continuous intensification in the interannual variability of the potential precipitation. Otherwise, the intensities of the three factors鈥 (except EAJ) interannual variability are all projected to be stronger at the end of the 21st century than that in the early period. These studies indicate that the change of interannual variability of the East Asian summer rainfall is caused by the variability of both the dynamic and thermodynamic variables under scenario A1B. In the early and middle 21st century, both factors lead to an intensified interannual variability of rainfall, whereas the dynamic factors weaken the interannual variability, and the thermodynamic factor intensifies the interannual variability in the late period. |
| [47] | 利用TRMM(Tropical Rainfall Measuring Mission)3B42RT和3G68 PR 1998-2005年8 a的观测资料,研究了中南半岛地区夏季(6-8月)降水日变化特征.结果表明:整个夏季,中南半岛西侧沿海和长山山脉西侧迎风坡为降水大值区和降水日方差 大值区.陆地上平原地区和远海海面降水主要出现在16-19LST(local standard time);沿海海面在07-10LST达到降水最大值.降水在白天由沿海分别向内陆和远海海面传播;夜间,降水从远海海面向沿海地区回传,但没有发现内 陆向沿海地区回传.长山山脉西侧迎风坡的一南一北两个区域,表现出明显不同的降水日变化特征,其原因与降水的传播有关.01-04LST,降水大值区出现 在泰国湾东部沿海,并向中南半岛岛内传播,16-19LST在长山山脉西南侧形成降水大值区,之后降水进一步沿山脉向西北传播,并于次日01-04LST 传到长山山脉西北侧区域,通过降水的这种传播特征从而导致长山山脉迎风坡一侧不同的降水日变化特征. . 利用TRMM(Tropical Rainfall Measuring Mission)3B42RT和3G68 PR 1998-2005年8 a的观测资料,研究了中南半岛地区夏季(6-8月)降水日变化特征.结果表明:整个夏季,中南半岛西侧沿海和长山山脉西侧迎风坡为降水大值区和降水日方差 大值区.陆地上平原地区和远海海面降水主要出现在16-19LST(local standard time);沿海海面在07-10LST达到降水最大值.降水在白天由沿海分别向内陆和远海海面传播;夜间,降水从远海海面向沿海地区回传,但没有发现内 陆向沿海地区回传.长山山脉西侧迎风坡的一南一北两个区域,表现出明显不同的降水日变化特征,其原因与降水的传播有关.01-04LST,降水大值区出现 在泰国湾东部沿海,并向中南半岛岛内传播,16-19LST在长山山脉西南侧形成降水大值区,之后降水进一步沿山脉向西北传播,并于次日01-04LST 传到长山山脉西北侧区域,通过降水的这种传播特征从而导致长山山脉迎风坡一侧不同的降水日变化特征. |
