地理科学进展 ›› 2023, Vol. 42 ›› Issue (1): 161-172.doi: 10.18306/dlkxjz.2023.01.013
收稿日期:
2022-06-17
修回日期:
2022-09-19
出版日期:
2023-01-28
发布日期:
2023-03-28
作者简介:
李双双(1988— ),男,陕西潼关人,副教授,硕士生导师,研究方向为气候变化与区域灾害防治。E-mail: lss1988@snnu.edu.cn
基金资助:
LI Shuangshuang(), HE Jinping, DUAN Keqin, REN Taotao, YAN Junping
Received:
2022-06-17
Revised:
2022-09-19
Online:
2023-01-28
Published:
2023-03-28
Supported by:
摘要:
识别降雪异常空间模态,明晰降雪异常的影响因素,对理解中国南北过渡带气候变化规律具有重要的实践意义。论文基于1970—2020年逐日气象数据,辅以湿球温度动态阈值法、经验正交分解法等气候诊断方法,对秦岭南北冷季(11月—次年5月)降雪异常空间模态进行识别,探讨了不同主导模态与海气异常的相关关系。结果表明:① 秦岭南北冷季降雪异常存在2个主导模态。第1模态为“全区一致型”,降雪异常偏强区分布于关中平原、秦岭山地、汉江谷地和大巴山区东段;第2模态为“山地主导下降型”,反映山地降雪异常对气候变化的敏感性;② 在时间变化上,第1模态以年际波动为主,20世纪90年代中期后,空间模态多处于负相位,即全区一致降雪偏少;第2模态以年代转折为主,近期空间模态多处于正相位,即山地降雪异常偏少;③ 在影响因素上,第1模态降雪异常与1月中高纬度500 hPa欧亚遥相关波列相关,第2模态降雪异常与冬季赤道中东太平洋海温异常密切相关。研究将降雪异常格局与环流异常机制组合研究,可为理解中国南北过渡带降雪异常预警信号提供理论基础。
李双双, 何锦屏, 段克勤, 任涛涛, 延军平. 秦岭南北降雪异常空间模态识别及其影响因素分析[J]. 地理科学进展, 2023, 42(1): 161-172.
LI Shuangshuang, HE Jinping, DUAN Keqin, REN Taotao, YAN Junping. Identifying the spatiotemporal pattern of snowfall and influencing factors in the south and north of the Qinling Mountains[J]. PROGRESS IN GEOGRAPHY, 2023, 42(1): 161-172.
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