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Abstract To better understand the dynamics and impacts of blocking events, their 3D structure needs to be further investigated. We present a comprehensive composite analysis of the 3D structure of blocks and its response to future climate change over North Pacific, North Atlantic, and Russia in summers and winters using reanalysis and two large-ensemble datasets from CESM1 and GFDLCM3. In reanalysis, over both ocean and land, the anomalous winds are equivalent-barotropic in the troposphere and stratosphere, and temperature anomalies are positive throughout the troposphere and negative in the lower stratosphere. The main seasonal and regional differences are that blocks are larger/stronger in winters; over oceans, the temperature anomaly is shifted westward due to latent heating. Analyzing the temperature tendency equation shows that in all three sectors, adiabatic warming due to subsidence is the main driver of the positive temperature anomaly; however, depending on season and region, meridional thermal advection and latent heating might have leading-order contributions too. Both GCMs are found to reproduce the climatological 3D structure remarkably well, but sometimes disagree on future changes. Overall, the future summertime response is weakening of all fields (except for specific humidity), although the impact on near-surface temperature is not necessarily weakened; e.g.,more »the blocking-driven near-surface warming over Russia intensifies. The wintertime response is strengthening of all fields, except for temperature in some cases. Responses of geopotential height and temperature are shifted westward in winters, most likely due to latent heating. Results highlight the importance of process-level analyses of blocks’ 3D structure for improved understanding of the resulting temperature extremes and their future changes.« less

The forecast skill of numerical weather prediction (NWP) models and the intrinsic predictability can be different among weather regimes. Here, we examine the predictability of distinct Pacific‐North American weather regimes during extended boreal summer. The four identified weather regimes include Pacific trough, Arctic low, Arctic high, and Alaskan ridge. The medium range forecast skill of these regimes is quantified in the ECMWF and the National Centers for Environmental Prediction models from the TIGGE project. Based on anomaly correlation coefficient, persistence, and transition frequency, the highest forecast skill is consistently found for the Arctic high regime. Based on the instantaneous local dimension and persistence from a dynamical systems analysis, the Arctic high regime has the highest intrinsic predictability. The analysis also suggests that overall, the Pacific trough regime has the lowest intrinsic predictability. These findings are consistent with the forecast skills of the NWP models, and highlight the link between prediction skill and intrinsic predictability.

The movement of tropical cyclones (TCs), particularly around the time of landfall, can substantially affect the resulting damage. Recently, trends in TC translation speed and the likelihood of stalled TCs such as Harvey have received significant attention, but findings have remained inconclusive. Here, we examine how the June-September steering wind and translation speed of landfalling Texas TCs change in the future under anthropogenic climate change. Using several large-ensemble/multi-model datasets, we find pronounced regional variations in the meridional steering wind response over North America, but―consistently across models―stronger June-September-averaged northward steering winds over Texas. A cluster analysis of daily wind patterns shows more frequent circulation regimes that steer landfalling TCs northward in the future. Downscaling experiments show a 10-percentage-point shift from the slow-moving to the fast-moving end of the translation-speed distribution in the future. Together, these analyses indicate increases in the likelihood of faster-moving landfalling Texas TCs in the late 21^stcentury.

Understanding the response of atmospheric blocking events to climate change has been of great interest in recent years. However, potential changes in the blocking area (size), which can affect the spatiotemporal characteristics of the resulting extreme events, have not received much attention. Using two large‐ensemble, fully coupled general circulation model (GCM) simulations, we show that the size of blocking events increases with climate change, particularly in the Northern Hemisphere (by as much as 17%). Using a two‐layer quasi‐geostrophic model and a dimensional analysis technique, we derive a scaling law for the size of blocking events, which shows that area mostly scales with width of the jet times the Kuo scale (i.e., the length of stationary Rossby waves). The scaling law is validated in a range of idealized GCM simulations. Predictions of this scaling law agree well with changes in blocking events' size under climate change in fully coupled GCMs in winters but not in summers.