Changes of compound hot and dry extremes on different land surface conditions in China during 1957–2018

Abstract

The co-occurrence of hot and dry extremes (compound hot and dry extreme, CHDE) has attracted much attention due to the amplified impact on wildfire occurrence, agriculture production and human health. Most existing studies have reported the spatiotemporal variations of CHDE, changes in CHDE on different land surface conditions are barely discussed. The study investigated the spatial and temporal differences of CHDE over different regions and land covers in China during 1957-2018. On average over China, both day-and night-time CHDEs have increased with a more rapid (2.6 times faster) and significant (p < .05) increasing trend in night-time ones. Increasing trends are mainly distributed in north China with decreasing trends in central China. Moreover, increasing trends in night-time mildly dry (0.07 per decade) and moderately hot (0.06 per decade) CHDEs are the largest among all dry and hot CHDEs. Regionally, the frequency of CHDE is the highest over the humid and sub-humid regions for night-and daytime CHDEs, but the lowest for both over the arid region. Meanwhile, CHDE has increased over the humid and sub-humid regions in the recent decade but decreased over the arid region since 1957. For different land covers, the frequency of CHDE is the highest over forest but the lowest over grassland. Daytime CHDEs of different hot magnitudes indicate the largest increasing trends over grassland caused by the largest increasing trends of daytime heatwave. Significant (p < 0.05) increasing trends of day-and night-time CHDEs over forest may increase the risks of tree mortality or forest fires after 2010 and larger increasing trends in nighttime CHDEs over urban may negatively impact human health.

Population exposure to compound dry and hot events in China under 1.5 and 2°C global warming

“…Of course, some other factors, such as the resolution of the data, and the uncertainties in the projected population and climate variables may also matter for uncertainties in this assessment. In addition, we only base our investigation on the monthly data, while some valuable sub‐monthly information of hot events may be ignored (Russo et al ., 2019; Feng et al ., 2020; Weber et al ., 2020). Thus, further analysis based on the daily data would improve our understanding on the population exposure to compound events under the two warming levels.…”

Comparative study of multiple heat indices in revisiting summer heat across China based on meteorological observations

“…The raw meteorological and radiation data have been improved through a preliminary quality check. We also interpolate those missing daily observations caused by station relocation or senor replacement with the average of daily observations on the neighboring 4 days (Feng et al, 2020). All the above data are used to calculate multiple heat indices of interest.…”

“…Examples of individual indices include summer days (SD) proposed by the Expert Team on Climate Change Detection and Indices (ETCCDI), hot days (HD) built upon daily maximum temperature (Collins et al, 2000), and the excess heat factor (EHF) describing heat-wave–like conditions based on daily average temperature (Nairn et al, 2009). Both absolute or relative thresholds are applied to describe different hot conditions (Bradfield et al, 2019; Feng et al, 2020; Li et al, 2019). Apart from temperature, higher air humidity brings a stronger heat feeling at the same degree of temperature (Teodoreanu, 2016).…”

“…Both absolute or relative thresholds are applied to describe different hot conditions (Bradfield et al, 2019;Feng et al, 2020;Li et al, 2019). Apart from temperature, higher air humidity brings a stronger heat feeling at the same degree of temperature (Teodoreanu, 2016).…”

Changes in compound hot and dry day and population exposure across China under climate change

“…China has been reported with significant increases in compound hot and dry extreme events (Feng et al ., 2020; Yu and Zhai, 2020). In this study, changes in compound hot and dry day (CHDD) and population exposure ( E pop ) are analysed based on observations and 11 GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under climate change.…”