Robust increases in severe thunderstorm environments in response to greenhouse forcing

Although severe thunderstorms are one of the primary causes of catastrophic loss in the United States, their response to elevated greenhouse forcing has remained a prominent source of uncertainty for climate change impacts assessment. We find that the Coupled Model Intercomparison Project, Phase 5, global climate model ensemble indicates robust increases in the occurrence of severe thunderstorm environments over the eastern United States in response to further global warming. For spring and autumn, these robust increases emerge before mean global warming of 2 °C above the preindustrial baseline. We also find that days with high convective available potential energy (CAPE) and strong low-level wind shear increase in occurrence, suggesting an increasing likelihood of atmospheric conditions that contribute to the most severe events, including tornadoes. In contrast, whereas expected decreases in mean wind shear have been used to argue for a negative influence of global warming on severe thunderstorms, we find that decreases in shear are in fact concentrated in days with low CAPE and therefore do not decrease the total occurrence of severe environments. Further, we find that the shift toward high CAPE is most concentrated in days with low convective inhibition, increasing the occurrence of high-CAPE/low-convective inhibition days. The fact that the projected increases in severe environments are robust across a suite of climate models, emerge in response to relatively moderate global warming, and result from robust physical changes suggests that continued increases in greenhouse forcing are likely to increase severe thunderstorm occurrence, thereby increasing the risk of thunderstorm-related damage.

Congo Basin rainfall climatology: can we believe the climate models?

The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models.