Increased spatial extent and likelihood of compound long-duration dry and hot events in China, 1961–2014

Abstract

Abstract. Compound dry and hot events can cause aggregated damage compared with isolated hazards. Although increasing attention has been paid to compound dry and hot events, the persistence of such hazards is rarely investigated. Moreover, little attention has been paid to the simultaneous evolution process of such hazards in space and time. Based on observations during 1961–2014, the spatiotemporal characteristics of compound long-duration dry and hot (LDDH) events in China during the summer season are investigated on both a grid basis and a 3D event basis. Grid-scale LDDH events mainly occur in eastern China, especially over northeastern areas. Most regions have experienced a pronounced increase in the likelihood of LDDH events, which is dominated by increasing temperatures. From a 3D perspective, 146 spatiotemporal LDDH (SLDDH) events are detected and grouped into 9 spatial patterns. Over time, there is a significant increase in the frequency and spatial extent of SLDDH events. Consistent with the grid-scale LDDH events, hotspots of SLDDH events mainly occur in northern China, such as the Northeast China, North China and Qinghai clusters, which are accompanied by a high occurrence frequency and large affected areas greater than 300 000 km2.

Changes in apparent temperature and PM2.5 around the Beijing–Tianjin megalopolis under greenhouse gas and stratospheric aerosol intervention scenarios

“…To validate the downscaled AP from model results, we use the daily temperature, humidity, and wind speed during 2008-2017 from the gridded observational dataset CN05.1 with the resolution of 0.25 • × 0.25 • based on the observational data from more than 2400 surface meteorological stations in China, which are interpolated using the "anomaly approach" (Wu and Gao, 2013). This dataset is widely used and has good performance relative to other reanalysis datasets over China (Zhou et al, 2016;Y. Yang et al, , 2023Yang and Tang, 2023).…”

“…This dataset is widely used and has good performance relative to other reanalysis datasets over China (Zhou et al, 2016;Y. Yang et al, , 2023Yang and Tang, 2023). Dynamical downscaling for the four ESM datasets was done with WRFv.3.9.1 with a parameter set used for urban China studies (Wang et al, 2012) in two nested domains at 30 and 10 km resolution over two time slices (2008-2017 and 2060-2069).…”

Large-Scale Climate Factors of Compound Agrometeorological Disasters of Spring Maize in Liaoning, Northeast China

“…In addition, this study presents the effect of large-scale climate factors on CADs on an interannual timescale. Although under the background of climate warming, the main factors affecting the production of spring maize have shifted from heat limited to water limited [30,43], and there is a significant increase in the frequency and spatial extent [44,45]. Therefore, the interdecadal shift of CADs needs further research.…”

Assessment of Changes in Agroclimatic Resources of the Republic of Bashkortostan (Russia) under the Context of Global Warming

“…The combined effect of arid and hot phenomena leads to a large cumulative damage compared to individual dangerous natural phenomena [13]. Also, Hao et al [14] concluded that combined droughts and hot weather events can lead to more serious consequences than individual droughts of the past.…”