The driving processes of concurrent hot and 2 dry extreme events in ChinaTian, F., Klingaman, N. P. ORCID: https://orcid.org/0000-0002-2927-9303 and Dong, B. ORCID: https://orcid.org/0000-0003-0809-7911 (2021) The driving processes of concurrent hot and 2 dry extreme events in China. Journal of Climate, 34 (5). pp. 1809-1824. ISSN 1520-0442
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1175/JCLI-D-19-0760.1 Abstract/SummarySubseasonal heatwave-driven concurrent hot and dry extreme events (HDEs) can cause substantial damage to crops, and hence to lives and livelihoods. However, the physical processes that lead to these devastating events are not well understood. Based on observations and reanalysis data for 1979–2016 over China, we show that HDEs occur preferentially over central and eastern China (CEC) and southern China (SC), with a maximum of three events per year along the Yangtze Valley. The probability of longer-lived and potentially more damaging HDEs is larger in SC than in CEC. Over SC the key factors of HDEs—positive anomalies of surface air temperature and evapotranspiration, and negative anomalies of soil moisture—begin two pentads before maximizing at the peak of the HDEs. These anomalies occur south of a positive height anomaly at 200 hPa, associated with a large-scale subsidence anomaly. The processes over CEC are similar to those for SC, but the anomalies begin one pentad before the peak. HDE frequency is strongly related to the Silk Road pattern and the boreal summer intraseasonal oscillation. Positive phases of the Silk Road pattern and suppressed phases of the boreal summer intraseasonal oscillation are associated with positive height anomalies over CEC and SC, increasing HDE frequency by about 35%–54% relative to the climatological mean. Understanding the effects of subseasonal and seasonal atmospheric circulation variability, such as the Silk Road pattern and boreal summer intraseasonal oscillation, on HDEs is important to improve HDE predictions over China.
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