我国华北地区人口密集，气候条件受到东亚季风的影响。在全球变暖背景下，华北地区频繁遭受高温热浪事件的影响，给国家和人们带来了严重的损失（Ding et al., 2010; Sun et al., 2014; Li et al., 2017; Johnson et al., 2018）。前人的研究指出华北地区高温热浪事件在近几十年呈现增长趋势（Li et al., 2017; Chen et al., 2018; Zhang et al., 2020）。因此，如何提高对华北地区夏季高温热浪的季节预测水平是重要的科学问题。
杨凯, 冯信贤, 黄刚. 2023. 海陆气协同作用对华北地区夏季高温热浪的影响 [J]. 气候与环境研究, 28(6): 665−675. doi: 10.3878/j.issn.1006-9585.2023.23035
摘要：
通过统计分析并利用WRF（Weather Research and Forecasting）模式进行多组敏感性试验研究发现，华北地区前期土壤湿度异常与夏季高温热浪的关系受到西太平洋副热带高压（西太副高）强度的影响。当西太副高异常偏强时，其西侧南风携带来自热带海洋的大量水汽至华北地区南部并增加该区域降水，不利于前期土壤湿度干异常的维持，从而限制了前期土壤湿度异常对高温热浪的贡献。相反，当西太副高偏弱时，华北地区前期土壤湿度干异常持续能力较强，有利于局地高温热浪的发展。西太副高强度与热带中东太平洋地区海温有关。当夏季热带太平洋海温异常处于暖位相时，西太副高强度相对较弱且华北地区南部降水偏少，有利于前期较干土壤条件的维持。此类情况下前期土壤湿度异常可以作为高温热浪的预测信号。
图3 1981～2020年（a、b）ERA5数据、（c、d）控制试验5月次表层（第二层）土壤湿度与夏季高温日数相关系数空间分布（左列）和华北地区（红框区域为本文定义的华北地区范围）区域平均的6月次表层土壤湿度与7月高温日数之间的关系（右列）。在40年的控制试验中，有两年的土壤湿度异常明显偏离其他年份，导致整体6月次表层土壤湿度与7月高温日数存在较强相关（蓝色拟合线及参数）。如果不考虑这两个年份，则两者的相关系数不再显著（红色拟合线及参数）。图3c不包含图3d中两个蓝色点年份数据
Fig. 3 Spatial distributions of the correlation between subsurface (second layer) soil moisture in May and the number of hot days in summer (left panel) and the relationship between Jun subsurface soil moisture and the number of hot days in Jul averaged over North China (red boxed shows the North China region defined in this study) (right panel) from (a, b) ERA5 data and (c, d) control experiment during 1981−2020. In two of the 40 years of the control experiment, the soil moisture anomaly deviates significantly from the other years, resulting in a strong correlation between the Jun subsurface soil moisture and the number of hot days in Jul (blue fitted line and parameters). If these two years are not considered, the correlation coefficient is no longer significant (red fitted line and parameters). The data of the two blue years in Fig. 3d are not included in Fig. 3c
图7 （a）控制试验、（c）ERA5资料高异常年和低异常年7月850 hPa位势高度场和风场差异的空间分布；（b）ERA5资料中高异常年和低异常年7月海温差异的空间分布；（d）控制试验和ERA5资料中高异常年和低异常年华北地区区域平均的7月降水量差值及根据Niño3.4指数判定的热带中东太平洋海温暖异常年和冷异常年华北地区区域平均的7月降水量差值
Fig. 7 Spatial distributions of the difference between the 850-hPa geopotential height field and wind field in Jul in the high and low anomaly years from (a) the control experiment and (c) the ERA5 data; (b) Spatial distribution of the difference between the SST anomalies in Jul in the high and low anomaly years in the ERA5 data; (d) Regional averaged North China July precipitation differences between the high and low anomaly years in the control experiment and ERA5 data, and differences of the regional averaged Jul precipitation in North China between tropical east-central Pacific SST warm anomaly years and cold anomaly years defined based on Niño3.4 index
http://www.iapjournals.ac.cn/qhhj/cn/article/doi/10.3878/j.issn.1006-9585.2023.23035
