Variation characteristics of clouds and their relationship with precipitation over China in El Niño decaying summers
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摘要: 基于1961—2010年中国地面台站和卫星观测等多种数据,对不同类型厄尔尼诺事件次年夏季中国地区云的变化特征和不同类型降水的变化特征进行了分析,探讨云的变化特征与总降水异常的复杂联系。结果表明:站点数据中,厄尔尼诺事件次年夏季总云量和低云量的异常与降水异常分布形势大致相同;积雨云、雨层云和层积云等低云的出现频率有所增加。云量与降水异常在全国范围内表现出显著的正相关;通过显著性检验的正相关站点,云量与降水异常的线性关系也通过了显著性检验,总云量和低云量与降水的增加比例分别接近1:3和1:1。卫星观测数据中,厄尔尼诺事件次年夏季高云量、深对流云量、光学厚度和云水路径的变化与站点降水异常基本呈正相关;黄河以南地区总降水的变化主要来源于对流降水的异常,其贡献比例高达80%。中国东部地区低云对降水具有很好的指示作用;厄尔尼诺事件次年夏季南方地区总降水的异常主要来自对流降水的变化;对流降水异常增加与深对流云的异常增多有关。厄尔尼诺事件的发生使得次年夏季中国季风区对流活动增强,对流云云量增多,云层增厚,云顶向上发展,故而对流降水增加,异常雨带形成。Abstract: Based on various datasets, including observations of ground stations and satellites in China from 1961 to 2010, the variation characteristics of clouds and different types of precipitation over China were analysed in the decaying summers of two types of El Niño events (eastern Pacific El Niño and central Pacific El Niño), and the complex relationship between the variation characteristics of clouds and total precipitation anomalies was discussed. The results demonstrate that the anomalies of total cloud amount and low cloud amount in El Niño decaying summers are about the same as those of precipitation based on station observations. Low cloud forms such as cumulonimbus, nimbostratus, and stratocumulus have become more common. A significant positive correlation exists between cloud amount anomalies and precipitation anomalies over China. At stations where the positive correlation passes the significance test, the linear relationship between cloud amount anomalies and precipitation anomalies is clear and also passes the significance test. In the meantime, the growing ratios of total cloud amount and low cloud amount to precipitation are close to 1:3 and 1:1, respectively. Variations in cloud amounts of high cloud and deep convective cloud, cloud optical thickness and cloud water path are positively correlated with precipitation anomalies based on station records. Convective precipitation anomalies, which account for up to 80% of total precipitation in the regions south of the Yellow River, are the major cause of fluctuation in total precipitation. Low clouds are a good predictor of precipitation in eastern China. The fluctuation of convective precipitation is primarily responsible for the anomalies of total precipitation in southern China in El Niño decaying summers, and the abnormal increases in convective precipitation are directly associated with anomalous increases in deep convective clouds. An El Niño event can boost convective activities in China's monsoon zone in the subsequent summer. Specifically, it leads to increases in deep convective cloud amount and thickness of cloud layer and promotes upward development of cloud top. These effects eventually increase convective precipitation and result in the formation of abnormal rain band.
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Key words:
- El Niño /
- Summer precipitation /
- Cloud /
- Correlation /
- Linear relationship
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图 2 厄尔尼诺 (a. 东部型,b. 中部型) 事件次年夏季累计降水相对于气候平均值的距平百分率 (单位:%,站点数据;通过置信度为95%显著性检验的站点以*标注)
Figure 2. Percentage anomalies (unit:%,station dataset) of cumulative precipitation in the El Niño (a. EP El Niño,b. CP El Niño) decaying summers relative to the climatic average (stations with values passing significance test at the 95% confidence level are marked with *)
图 3 厄尔尼诺 (a、c、e. 东部型,b、d、f. 中部型) 事件次年夏季日平均云量 (a、b. 白天总云量,c、d. 白天低云量,e、f. 夜间低云量) 的距平百分率 (单位:%,站点数据)
Figure 3. Percentage anomalies (unit:%,station dataset) of daily average cloud amount in the El Niño decaying summers (a,c,e. EP El Niño,b,d,f. CP El Niño;a,b. total cloud amount at daytime,c,d. low cloud amount at daytime,e,f. low cloud amount at nighttime)
图 4 厄尔尼诺 (a、c、e、g. 东部型,b、d、f、h. 中部型) 事件次年夏季云量 (a、b. 总云量,c、d. 高云量,e、f. 卷层云云量,g、h. 深对流云云量) 的距平百分率 (单位:%,ISCCP数据)
Figure 4. Percentage anomalies (unit:%,ISCCP dataset) of cloud amount in the El Niño decaying summers (a,c,e,g. EP El Niño,b,d,f,h. CP El Niño;a,b. total cloud amount,c,d. high cloud amount,e,f. cirrostratus cloud amount,g,h. deep convective cloud amount)
图 5 厄尔尼诺 (a、c、e. 东部型,b、d、f. 中部型) 事件次年夏季云量 (a、b. 总云量, c、d. 高云量,e、f. 卷云云量) 的距平百分率 (单位:%,MODIS数据)
Figure 5. Percentage anomalies (unit:%,MODIS dataset) of cloud amount in the El Niño decaying summers (a,c,e. EP El Niño,b,d,f. CP El Niño;a,b. total cloud amount,c,d. high cloud amount,e,f. cirrus cloud amount)
图 6 厄尔尼诺 (a、c、e. 东部型,b、d、f. 中部型) 事件次年夏季与总云相关的物理量 (a、b. 云顶气压,c、d. 云顶温度,e、f. 光学厚度) 距平百分率 (单位:%,MODIS数据)
Figure 6. Percentage anomalies (unit:%,MODIS dataset) of physical quantities of total cloud in the El Niño decaying summers (a,c,e. EP El Niño,b,d,f. CP El Niño;a,b. pressure in cloud top,c,d. temperature in cloud top,e,f. optical thickness)
图 7 厄尔尼诺 (a、c、e. 东部型,b、d、f. 中部型) 事件次年夏季白天降水(a、b)和云量 (c、d. 总云量,e、f. 低云量) 距平百分率 (单位:%,MICAPS数据)
Figure 7. Percentage anomalies (unit:%,MICAPS dataset) of precipitation and cloud amount in the El Niño decaying summers at daytime (a,c,e. EP El Niño,b,d,f. CP El Niño;a,b. precipitation,c,d. total cloud amount,e,f. low cloud amount)
图 8 厄尔尼诺 (a、c、e. 东部型,b、d、f. 中部型) 事件次年夏季白天低云 (a、b. 普通层积云,c、d. 碎雨云,e、f. 鬃状/砧状积雨云) 出现频率的距平 (单位:%,MICAPS数据)
Figure 8. Anomalies (unit:%,MICAPS dataset) of frequency of low cloud forms in the El Niño decaying summers at daytime(a,c,e. EP El Niño,b,d,f. CP El Niño;a,b. stratocumulus,c,d. fractonimbus,e,f. cumulonimbus capillatus and incus)
图 9 厄尔尼诺 (a、c、e. 东部型,b、d、f. 中部型) 事件次年夏季降水与云量距平百分率的相关系数(站点数据;a、b. 白天降水与总云量,c、d. 白天降水与低云量,e、f. 夜间降水与低云量)
Figure 9. Correlation between percentage anomalies of precipitation and cloud amount in the El Niño decaying summers (station dataset;a,c,e. EP El Niño,b,d,f. CP El Niño;a,b. precipitation and total cloud amount at daytime,c,d. precipitation and low cloud amount at daytime,e,f. precipitation and low cloud amount at nighttime)
图 10 厄尔尼诺 (a、c、e. 东部型,b、d、f. 中部型) 事件次年夏季降水与云量距平百分率的线性回归 (站点数据,公式为回归方程,Num表示拟合站点数,p为回归方程F显著性检验的p值;a、b. 白天降水与总云量,c、d. 白天降水与低云量,e、f. 夜间降水与低云量)
Figure 10. Linear regression between percentage anomalies of precipitation and cloud amount in the El Niño decaying summers (station dataset,the formula on the figure is the regression equation,"Num" represents the number of fitting stations,and "p" is the p-value of F test of regression equation;a,c,e. EP El Niño,b,d,f. CP El Niño;a,b. precipitation and total cloud amount at daytime,c,d. precipitation and low cloud amount at daytime,e,f. precipitation and low cloud amount at nighttime)
图 11 厄尔尼诺 (a、c、e、g. 东部型, b、d、f、h. 中部型) 事件次年夏季站点降水与ISCCP云量距平百分率的相关系数 (a、b. 总降水与总云量,c、d. 总降水与高云量,e、f. 总降水与卷层云云量,g、h. 总降水与深对流云云量;通过0.05水平显著性检验的区域打点标注)
Figure 11. Correlation between percentage anomalies of precipitation of station dataset and cloud amount in the ISCCP dataset in the El Niño decaying summers (a,c,e,g. EP El Niño,b,d,f,h. CP El Niño;a,b. total precipitation and total cloud amount,c,d. total precipitation and high cloud amount,e,f. total precipitation and cirrostratus cloud amount,g,h. total precipitation and deep convective cloud amount;dots denote passing the test of 0.05 significance level)
图 12 厄尔尼诺 (a、c. 东部型,b、d. 中部型) 事件次年夏季站点降水与ISCCP总云相关物理量距平百分率的相关系数 (a、b. 总降水与总云光学厚度,c、d. 总降水与云水路径)
Figure 12. Correlation between percentage anomalies of precipitation from station dataset and total cloud related physical quantities from the ISCCP dataset in the El Niño decaying summer (a,c. EP El Niño,b,d. CP El Niño;total precipitation and total cloud (a,b) optical thickness and (c,d) cloud water path)
图 13 厄尔尼诺 (a、c、e. 东部型, b、d、f. 中部型) 事件次年夏季近地表总降水的距平百分率 (a、b) 以及对流降水 (c、d) 和层云降水 (e、f) 异常占总降水异常的百分数 (单位:%,TRMM数据)
Figure 13. Percentage anomalies (unit:%,TRMM dataset) of total precipitation (a,b) and the ratios accounted for by convective (c,d) and stratus (e,f) precipitation anomalies in the El Niño decaying summers (a,c,e. EP El Niño,b,d,f. CP El Niño)
表 1 各数据集的选用说明
Table 1. Instruction for the selection of datasets
数据集 东部型厄尔尼诺 中部型厄尔尼诺 气候平均态 数据信息/筛选 地面站点数据
(2400站) 1961—2010年1963/1964年
1965/1966年
1972/1973年
1976/1977年
1982/1983年
1986/1988年
1991/1992年
1997/1998年
2006/2007年1968/1970年
1994/1995年
2002/2003年
2004/2005年
2009/2010年1981—2010年 站点筛选条件:缺测率(同时考虑降水和云量)小于5% 且连续缺测不超过1个月;水平距离变化小于20 km;海拔高度变化小于150 m。
选取站点:1678站
北京时间02时的低云量、02和20时的总云量由于缺测率过高,未选用。MICAPS 数据
2000—2013年2006/2007年 2002/2003年
2004/2005年
2009/2010年2000—2013年 将2000—2013年都有记录的站点选取出来,未对缺测率和站点迁址范围进行控制。
选取:白天905站,夜间879站ISCCP D2数据
1984—2009年1986/1988年
1991/1992年
1997/1998年
2006/2007年1994/1995年
2002/2003年
2004/2005年1984—2009年 水平分辨率:2.5°×2.5°
选取范围:13.85°—56.25°N,71°—137°EMOD08_3M数据
2000—2017年2006/2007年
2014/2016年2002/2003年
2004/2005年
2009/2010年2000—2017年 水平分辨率:1°×1°
选取范围:15.5°—55.5°N,69.5°—137.5°ETRMM 3A25数据
1998—2014年1997/1998年
2006/2007年2002/2003年
2004/2005年
2009/2010年1998—2014年 水平分辨率:0.5°×0.5°
选取范围:15.25°—36.75°N,70.25°—137.25°E表 2 MICAPS数据低云状的类别及其伴随天气现象
Table 2. Low cloud forms and accompanied weather phenomena in the MICAPS dataset
编码 低云状 天气现象 31 淡积云 淡积云在晴天常见 32 浓积云 浓积云有时可产生阵性降水 33 秃积雨云 积雨云常产生雷暴、降雨(雪) 34 积云性层积云 层积云有时可降雨、雪,通常量较小 35 普通层积云 层积云有时可降雨、雪,通常量较小 36 层云或碎层云 层云可降毛毛雨或米雪 37 碎雨云 雨层云常有连续性降水,碎雨云常出现在雨层云、积雨云等降水云层之下 38 不同高度的积云和层积云 积云和层积云有时可产生降水 39 鬃状/砧状积雨云 积雨云常产生雷暴、降雨(雪) -
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