Relationship between the clouds and precipitation over southern China based on ISCCP and CMORPH-AWS data

doi:10.11755/j.issn.1006-7639(2022)-04-0613

Abstract

Abstract:

This paper addresses the spatial and temporal variation of cloud cover at different heights over southern China and its relationship with precipitation, which is useful for understanding the role of clouds in precipitation and feedback mechanisms as well as provides a basis and foundation for the development of cloud water resources. Based on 12 years (1998-2009) data from the D dataset of International Satellite Cloud Climatology Project (ISCCP), the temporal and spatial distribution characteristics of total cloud cover, low cloud cover, medium cloud cover and high cloud cover were analyzed over Southern China. And based on the CMORPH-AWS merged gridded precipitation product which combined National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) morphing technique (CMORPH) with precipitation observations from automatic weather stations, the relationships between the cloud cover and precipitation intensity, precipitation frequency were analyzed over southern China. The results are as follows: (1) The spatial distribution of total cloud cover and medium cloud cover over southern China was similar. The high-value center was located over the junction of Sichuan Basin, Guizhou and Chongqing, while the low-value center was located in Yunnan. High clouds were distributed in the western part of southern China, and decreased from west to east. Low clouds were mainly distributed over the southeastern part of southern China. Overall, low cloud cover decreased from coastal area to inland area. (2) The seasonal variation of total cloud cover and high cloud cover was similar, with cloud cover more in summer and less in winter. Moreover, the high value center of total cloud cover shifted with the seasons. The high cloud cover changed seasonally. The moderate cloud cover and low cloud cover were more in winter and less in summer, with small seasonal changes. (3) With the increase of total cloud cover and high cloud cover, the precipitation intensity increased but the monthly precipitation frequency decreased. With the increase of medium cloud cover, the frequency of monthly precipitation increased, while effect on precipitation intensity varied little. (4) With the increase of cloud cover of stratocumulus and stratus clouds, precipitation intensity and monthly precipitation frequency decreased. With the increase of cloud cover of altocumulus, altostratus and deep convection clouds, precipitation intensity increased while monthly precipitation frequency decreased. In general, cloud cover and precipitation were closely related over southern China, especially total cloud cover and high cloud cover had a greater influence on precipitation intensity and precipitation frequency, while medium cloud cover only had a greater impact on precipitation frequency. The cloud cover of stratocumulus, stratus, altocumulus, altostratus, deep convection clouds had a greater influence on precipitation intensity and precipitation frequency, while cloud cover of cirrus and cirrostratus only had a greater impact on precipitation intensity.

Key words: cloud and precipitation, ISCCP cloud data, CMORPH-AWS merged precipitation product, temporal and spatial distribution characteristics

摘要：

探究中国南方地区不同高度云量的时空变化及其与降水的关系，可了解云在降水中的作用和反馈机制并为空中云水资源开发提供基础和依据。利用国际卫星云气候计划(International Satellite Cloud Climatology Project， ISCCP)中D系列卫星观测云数据集12 a(1998—2009年)资料，详细分析了中国南方地区总云量、低云量、中云量、高云量的时空分布特征，并结合中国自动站(automatic weather station， AWS)降水数据与美国国家海洋和大气管理局(National Oceanic and Atmospheric Administration， NOAA)气候预测中心(Climate Prediction Center， CPC) MORPHing technique(CMORPH)卫星反演降水产品融合的格点降水产品(CMORPH-AWS)分析了云量与降水强度、降水次数的关系。结果表明：(1)在空间分布上，中国南方地区总云量和中云量空间分布类似，高值中心位于四川盆地、贵州、重庆交接处，低值中心位于云南地区;高云主要分布在南方地区的西部，表现为由西向东逐渐减少的分布特征;低云主要分布在南方地区的东南部，表现为沿海地区向内陆地区逐渐减少的空间分布特征。(2)在季节变化上，总云量和高云量为夏季多、冬季少，总云量高值中心随季节位移，高云量随季节变化，中云量和低云量为冬季多夏季少，季节性变化小。(3)随着总云量和高云量的增多，降水强度增大、月降水次数减小;随着中云量增多，月降水次数增加、降水强度无明显变化。(4)随着层积云、层云云量的增加，降水强度和月降水次数减小;随着高积云、高层云、深对流云云量的增加，降水强度增加但月降水次数减小。总体而言，中国南方地区云量和降水关系密切，特别是总云量和高云量对降水强度和降水次数影响较大，中云量仅对降水次数影响较大，层积云、层云、高积云、高层云、深对流云云量对降水强度和降水次数影响较大，卷云、卷层云云量仅对降水强度影响较大。

关键词: 云和降水, ISCCP云资料, CMORPH-AWS融合降水产品, 时空分布特征

CLC Number:

FAN Sirui, WANG Weijia, CHEN Yonghang. Relationship between the clouds and precipitation over southern China based on ISCCP and CMORPH-AWS data[J]. Journal of Arid Meteorology, 2022, 40(4): 613-623.

范思睿, 王维佳, 陈勇航. 基于ISCCP和CMORPH-AWS资料的中国南方地区云与降水关系分析[J]. 干旱气象, 2022, 40(4): 613-623.

Figures/Tables 10

Fig.1 Sketch map of study region

Fig.2 Spatial distribution of annual mean cloud cover during 1998-2009 over southern China (Unit：%) (a)total cloud cover， (b)low cloud cover， (c)medium cloud cover， (d)high cloud cover

Fig.3 Spatial distribution of annual mean precipitation during 1998-2009 over southern China (Unit：mm)

Fig.4 The spatial distribution of the total cloud cover in four seasons during 1998-2009 over southern China (Unit：%) (a) spring， (b) summer， (c) autumn， (d) winter

Fig.5 The spatial distribution of the medium cloud cover in four seasons during 1998-2009 over southern China (Unit：%) (a) spring， (b) summer， (c) autumn， (d) winter

Fig.6 The spatial distribution of the high cloud cover in four seasons during 1998-2009 over southern China(Unit：%) (a) spring， (b) summer， (c) autumn， (d) winter

Fig.7 Monthly variation of cloud cover at different heights over southern China during 1998-2009

Fig.8 The scatter plots between precipitation intensity (a，b，c，d) ， monthly precipitation frequency (e，f，g，h) and cloud cover over southern China during 1998-2009 (a，e) total cloud cover， (b，f) low cloud cover， (c，g) medium cloud cover， (d，h) high cloud cover

Fig.9 The scatter plots between precipitation intensity and cloud cover with different type over southern China during 1998-2009(a)cumulus， (b) stratocumulus， (c) stratus， (d) altocumulus， (e) altostratus， (f) nimbostratus， (g) cirrus， (h) cirrostratus， (i) deep convective

Fig.10 The scatter plots between monthly precipitation frequency and cloud cover with different type over southern China during 1998-2009 (a)cumulus， (b) stratocumulus， (c) stratus， (d) altocumulus， (e) altostratus， (f) nimbostratus， (g) cirrus， (h) cirrostratus， (i) deep convective

References 37

[1]	WILD M, FOLINI D, HAKUBA M Z, et al. The energy balance over land and oceans: an assessment based on direct observations and CMIP5 climate models[J]. Climate Dynamics, 2014, 44 (11/12): 3393-3429.
[2]	钱永甫, 黄媛媛. 臭氧、云和气溶胶对纬带平均气候的影响[J]. 地理学报, 1994, 49 (3): 266-274.
[3]	汪宏七, 赵高祥. 云和辐射-(I)云气侯学和云的辐射作用[J]. 大气科学, 1994, 18(增刊):910-921.
[4]	DAI A, TRENBERTH K E, KARL T R. Effects of clouds, soil moisture, precipitation, and water vapor on diurnal temperature range[J]. Journal of Climate, 1999, 12:2451-2473.
[5]	符传博, 丹利, 冯锦明, 等. 1960—2012年中国地区总云量时空变化及其与气温和水汽的关系[J]. 大气科学, 2019, 43(1):87-98.
[6]	丁守国, 石广玉, 赵春生. 利用ISCCP D2资料分析近20年全球不同云类云量的变化及其对气候可能的影响[J]. 科学通报, 2004, 49(11):1105-1111.
[7]	汪宏七, 赵高祥. 云微物理特性对云光学和云辐射性质的影响[J]. 应用气象学报, 1996, 7(1):36-44.
[8]	曹越前, 张武, 药静宇, 等. 半干旱区云量变化特征及其与太阳辐射关系的研究[J]. 干旱气象, 2015, 33(4):684-693.
[9]	向华, 张峰, 江静, 等. 利用CFSR资料分析近30年全球云量分布及变化[J]. 气象, 2014, 40(5):555-561.
[10]	丁守国, 赵春生, 石广玉, 等. 近20年全球总云量变化趋势分析[J]. 应用气象学报, 2005, 16(5):670-677.
[11]	郑建宇, 刘东, 王志恩, 等. CloudSat/CALIPSO卫星资料分析云的全球分布及其季节变化特征[J]. 气象学报, 2018, 76(3):420-433.
[12]	徐兴奎. 中国区域总云量和低云量分布变化[J]. 气象, 2012, 38(1):90-95.
[13]	马茜蓉, 游庆龙, 蔡淼, 等. 基于CERES卫星资料分析中国近15 a云量变化[J]. 干旱气象, 2018, 36(6):911-920.
[14]	范思睿, 王维佳, 林丹. 基于ISCCP云资料的中国地区不同类型云的时空分布[J]. 干旱气象, 2020, 38(2):213-225.
[15]	陈勇航, 黄建平, 王天河, 等. 西北地区不同类型云的时空分布及其与降水的关系[J]. 应用气象学报, 2005, 16(6):717-727.
[16]	陈勇航, 黄建平, 陈长和, 等. 西北地区空中云水资源的时空分布特征[J]. 高原气象, 2005, 24(6):905-912.
[17]	李跃清, 张琪. 西南地区夏季云量与降水的关系特征分析[J]. 自然资源学报, 2014, 29(3):441-453.
[18]	李昀英, 寇雄伟, 方乐锌, 等. 中国东部云-降水对应关系的分析与模式评估[J]. 气象学报, 2015, 73(4):766-777.
[19]	孙丽, 张晋广, 杨磊, 等. 基于Aqua/CERES数据的辽宁省云宏微观特征及其与降水的相关性研究[J]. 干旱气象, 2020, 38(4):612-618.
[20]	ROSSOW W B, SCHIFFER R A. ISCCP cloud data products[J]. Bulletin of American Meteorological Society, 1991, 72:2-20.
[21]	ROSSOW W B, WALKER A W, GARDER L C. Comparison of ISCCP and other cloud amounts[J]. Journal of Climate, 1993, 6(12) :2394-2418.
[22]	ROSSOW W B, SCHIFFER R A. Advances in understanding clouds from ISCCP[J]. Bulletin of American Meteorological Society, 1999, 80(11):2261-2287.
[23]	HAHN C J, ROSSOW W B, WARREN S G. ISCCP cloud properties associated with standard cloud types identified in individual surface observations[J]. Journal of Climate, 2001, 14(1): 11-27.
[24]	刘洪利, 朱文琴, 宜树华, 等. 中国地区云的气候特征分析[J]. 气象学报, 2003, 61(4):466-473.
[25]	李昀英, 宇如聪, 徐幼平, 等. 中国南方地区层状云的形成和日变化特征分析[J]. 气象学报, 2003, 61(6):723-743.
[26]	LI Y Q, LIU X D, CHEN B D. Cloud type climatology over the Tibetan Plateau: a comparison of ISCCP and MODIS/TERRA measurements with surface observations[J]. Geophysical Research Letters, 2006, 33(17),L17716. DOI: 10.1029/2006GL026890.
[27]	潘旸, 沈艳, 宇婧婧, 等. 基于最优插值方法分析的中国区域地面观测与卫星反演逐时降水融合试验[J]. 气象学报, 2012, 70(6):1381-1389.
[28]	宇婧婧, 沈艳, 潘旸, 等. 概率密度匹配法对中国区域卫星降水资料的改进[J]. 应用气象学报, 2013, 24(5):544-553.
[29]	周璇, 罗亚丽, 郭学良. CMORPH卫星-地面自动站融合降水数据在中国南方短时强降水分析中的应用[J]. 热带气象学报, 2015, 31(3):333-344.
[30]	江志红, 卢尧, 丁裕国. 基于时空结构指标的中国融合降水资料质量评估[J]. 气象学报, 2013, 71(5):891-900.
[31]	李兴宇, 郭学良, 朱江. 中国地区空中云水资源气候分布特征及变化趋势[J]. 大气科学, 2008, 32(5):1094-1106.
[32]	LI Y Y, GU H. Relationship between middle stratiform clouds and large scale circulation over eastern China[J]. Geophysical Research Letters, 2006, 33(9), 9706.DOI:10.1029/2005GL025615.
[33]	张琪, 李跃清, 陈权亮, 等. 近46年西南地区云量的时空变化特征[J]. 高原气象, 2011, 30(2):339-348.
[34]	徐祥德, 陶诗言, 王继志, 等. 青藏高原季风水汽输送“大三角扇型”影响域特征与中国区域旱涝异常的关系[J]. 气象学报, 2002, 60(3):257-266.
[35]	WEARE B C. Near-global observations of low clouds[J]. Journal of Climate, 2000, 13: 1255-1268.
[36]	刘奇, 傅云飞. 热带地区云量日变化的气候特征[J]. 热带气象学报, 2009, 25(6):717-723.
[37]	寇雄伟, 李昀英, 方乐锌, 等. 东亚夏季风活动与不同类型云的相关性研究[J]. 大气科学, 2016, 40 (3): 463-475.