Abstract
The intensification of climate extremes is one of the most immediate effects of global climate change. Heatwaves and droughts have uneven impacts on ecosystems that can be exacerbated in case of compound events. To comprehensively study these events, e.g. with local high-resolution remote sensing or in-situ data, a global catalogue of such events is essential. Here, we propose a workflow to build a database of large-scale dry and hot extreme events based on data from ERA5 reanalysis. Drought indicators are constructed based on evapotranspiration and precipitation data averaged over 30, 90 and 180 days. Extreme events are detected with the peak-over-threshold approach for the 1950–2022 period. Extremes and non-extremes are defined for daily maximum temperature at 2 m in combination with three drought indicators. In the last step, the spatiotemporal extent of the events is computed by a connected component analysis. The identified events are validated against extreme events reported in the literature.
Chaonan Ji
Postdoctoral fellow / Earth System Data Science
My research interests include the classification of hyperspectral images from air and space, gradient analysis, and its application in urban areas. My current research interest is in the study and analysis of environmental responses to climate extremes.
