极点对称模态分解下陕西气候变化特征及影响因素

doi:10.12118/j.issn.1000–6060.2021.01.04

摘要/Abstract

摘要：

全球变暖背景下,受人类活动和气候系统波动共同影响,气候要素响应具有非线性、非平稳特征,如何识别气候变化多时间尺度信息,是当前研究的热点话题。基于1970—2017年气温和降水逐日数据,辅以滑动平均、趋势分析和极点对称模态分解（ESMD）等方法,对陕西3大地理单元气候时空特征进行分析,进而探讨不同海区厄尔尼诺指数与气温、降水变化的响应关系。结果表明：1970—2017年,陕北气候变化经历“暖干-冷湿-暖湿”的变化过程;关中和陕南气候在20世纪80—90年代末呈现暖干化,随后增温停滞,降水增多,近期再次呈现暖干化;利用ESMD对陕西气温和降水变化信号进行分解,发现区域气温响应变暖停滞,是受年代波动影响,周期为9.2~11.5 a左右;从趋势项分析,除陕北气温平稳波动之外,关中和陕南气温增速并未减缓;在影响因素上,不同海区海温异常与陕西气温、降水变化相关性存在差异。其中,气温影响主要在中国东部海区,且与NINO A区、黑潮区海温显著正相关;影响降水变化的关键海区在赤道太平洋,即赤道太平洋中部海温异常偏高时,关中和陕南降水呈现下降,而赤道太平洋东部海温异常偏高,陕北降水减少更为明显。

关键词: 极点对称模态分解, 气候变化, 时空分析, 陕西省

Abstract:

Against the background of global warming affected by human activities and climate system fluctuations, climate response is non-linear and nonsmoothed. A hot topic is how to identify multiple-time scale information about climatic change. The spatiotemporal characteristics of climate change were analyzed for three geographical sub-regions of Shaanxi Province by sliding average, trend analysis, and extreme-point symmetric mode decomposition (ESMD) methods, using daily temperature and precipitation data between 1970 and 2017 and then discussing the tele-correlation between sea surface temperature (SST) in 17 different sea areas and the regional temperature and precipitation changes. The main SST indexes included El Niño-Southern Oscillation, Pacific Decadal Oscillation, Atlantic Multi-decadal Oscillation, Quasi-Biennial Oscillation (QBO), and Kuroshio Current SST (KCSST). The results showed that from 1970 to 2017, the mean annual temperature in Shaanxi rose significantly, with step-change points in 1984, 1999, and 2012. In detail, climate change in northern Shaanxi involved warming-drying, cooling-wetting, and warming-wetting, whereas in Guanzhong Plain and southern Shaanxi, there was warming-drying from 1970 to 1999. Since 1999, the regional climate of these two regions exhibited a warming hiatus, and it was not until 2012 that intensified warming and decreasing precipitation have become more obvious. The ESMD of temperature and precipitation signals showed a non-linear upward trend, which implied changes on decadal scales (9.2-11.5 a) in response to the warming hiatus. The temperature increased in Guanzhong Plain and southern Shaanxi, except for a slight decline in northern Shaanxi in 1999—2017. Spatial differences exist in the influencing factors of temperature and precipitation in Shaanxi Province. The SST of eastern China is the dominant influencing factor for annual and decadal temperature variability. Temperatures generally increase in Shaanxi with positive SST anomaly for both NINO A and KCSST. Additionally, positive SST anomalies in the central equatorial Pacific cause decreasing precipitation in both Guanzhong Plain and southern Shaanxi. Less precipitation was expected in northern Shaanxi with increasing positive SST anomalies centered in the eastern equatorial Pacific, commonly known as the East Pacific type of El Niño. The above results could provide insights for the regional response and risk management of extreme precipitation resulting from global climate change. However, it should be noted that the connections between the SST and climate anomalies in Shaanxi Province are not clear. Hence, future work should determine the SST-forced heat and moisture stress anomalies to explain rainfall variations.

Key words: extreme-point symmetric mode decomposition (ESMD), climate change, spatiotemporal analysis, Shaanxi Province

申雨晨,李双双,延军平,武亚群,汪成博. 极点对称模态分解下陕西气候变化特征及影响因素[J]. 干旱区地理, 2021, 44(1): 36-46.

SHEN Yuchen,LI Shuangshuang,YAN Junping,WU Yaqun,WANG Chengbo. Spatiotemporal climate variation and its influencing factors in Shaanxi Province based on extreme-point symmetric mode decomposition[J]. Arid Land Geography, 2021, 44(1): 36-46.

图/表 7

图1

表1

不同海区海气环流指数"

序号	海气环流	定义
1	NINO 1+2区	0°~10°S、80°~90°W区域内,海表温度距平的区域平均值
2	NINO 3区	5°S~5°N、90°~150°W区域内,海表温度距平的区域平均值
3	NINO 4区	5°S~5°N、150°W~160°E区域内,海表温度距平的区域平均值
4	NINO 3.4区	5°S~5°N、120°~170°W区域内,海表温度距平的区域平均值
5	NINO W区	0°~10°N、140°~180°E区域内,海表温度距平的区域平均值
6	NINO C区	10°S~0°、90°~180°W区域内,海表温度距平的区域平均值
7	NINO A区	25°~35°N、130°~150°E区域内,海表温度距平的区域平均值
8	NINO B区	0°~10°N、50°~90°E区域内,海表温度距平的区域平均值
9	PDO	北太平洋年代际振荡指数,20°N以北的北太平洋地区,海表温度距平经验正交函数分解（EOF）第1模态的时间系数
10	AMO	大西洋经向模海温指数,21°S~32°N、74°W~15°E区域内,海表温度(左场)和经、纬向10 m风场(右场)最大协方差分析结果中海表温度场(左场)的时间系数
11	QBO	准两年振荡指数,赤道地区30 hPa纬向风平均值
12	NAT	大西洋海温三极子指数,0°~60°N、0°~80°W区域内,海表温度距平（去除线性趋势）经验正交函数分解（EOF）第一模态作为投影模态,月海温距平场在去除全球海温增暖影响后对该模态投影系数的标准化序列
13	SOI	南方涛动指数,指标准化塔希提与达尔文站月平均海平面气压之差的序列的标准化值
14	NCP	中部型厄尔尼诺-南方涛动（ENSO）指数
15	NEP	东部型厄尔尼诺-南方涛动（ENSO）指数
16	KCSST	黑潮区海温指数,指35°N、140°~150°E及25°~30°N、125°~150°E区域内,海表温度距平的区域平均值
17	WPWP	西太平洋暖池强度指数,指30°S~30°N、120°~180°E范围,海表温度超过28.0 °C的区域内,格点海表温度与28.0 °C之差乘以格点面积的累积值.

表1

图2

图3

表2

图4

图5

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分区	气候因子	指标	IMF1	IMF2	IMF3	R
陕北地区	气温	周期	4.0 a	9.6 a/8.0 a	-	-
		贡献率	34.1%	26.4%	-	39.5%
		F值	9.6	6.2/5.7	-	-
	降水	周期	2.5 a/2.2 a	6.9 a-6.0 a-4.8 a-4.4 a	12.0 a/9.6 a	-
		贡献率	40.7%	20.8%	11.9%	26.6%
		F值	10.0/3.6	4.5/4.6/4.2/4.3	10.5/14.6	-
关中地区	气温	周期	4.0 a	6.9 a	24.0 a-16.0 a	-
		贡献率	26.1%	18.9%	12.8%	42.1%
		F值	9.8	28.1	14.1-6.1	-
	降水	周期	3.7 a	9.6 a/6.9 a	24.0 a/16.0 a	-
		贡献率	49.6%	24.2%	14.9%	11.3%
		F值	3.5	27.6/6.6	32.3/12.0	-
陕南地区	气温	周期	4.0 a/3.7 a	6.9 a/9.6 a	24.0 a/48 a	-
		贡献率	26.7%	20.1%	19.7%	33.5%
		F值	6.4/3.7	18.0/7.2	32.2/6.8	-
	降水	周期	2.2 a	12.0 a-9.6 a-6.9 a	-	-
		贡献率	44.2%	29.2%	-	26.6%
		F值	4.1	4.5/23.6/4.4	-	-