No abstract

Flash droughts refer to a type of droughts that have rapid intensification without sufficient early warning. To date, how will the flash drought risk change in a warming future climate remains unknown due to a diversity of flash drought definition, unclear role of anthropogenic fingerprints, and uncertain socioeconomic development. Here we propose a new method for explicitly characterizing flash drought events, and find that the exposure risk over China will increase by about 23% ± 11% during the middle of this century under a socioeconomic scenario with medium challenge. Optimal fingerprinting shows that anthropogenic climate change induced by the increased greenhouse gas concentrations accounts for 77% ± 26% of the upward trend of flash drought frequency, and population increase is also an important factor for enhancing the exposure risk of flash drought over southernmost humid regions. Our results suggest that the traditional drought-prone regions would expand given the human-induced intensification of flash drought risk.

[1] NOAA's National Centers for Environmental Prediction (NCEP) has transitioned to operationally use the second generation of their coupled ocean-atmosphere-land model, the Climate Forecast System version 2 (CFSv2), with advanced physics, increased resolution and refined initialization to improve the seasonal climate forecasts. We present a first look at the capability of CFSv2 on surface air temperature and precipitation predictions based on analyzing the 28-year (1982-2009) reforecasts. These variables are primary inputs to hydrological seasonal forecast procedures. Averaged globally, the CFSv2 increases the predictive skill for month-1 land surface air temperature and precipitation from the CFSv1 by 37% and 29%, respectively. The CFSv2 has comparable performance to the latest ECMWF model, the best among the current European seasonal forecast models. The soil moisture produced by CFSv2 also provides useful information in identifying several major drought events, especially over tropical regions. Though there is limited skill beyond month-1, the CFSv2 does show promising features for advancing hydrological forecast and application studies.