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Hindcast attribution simulations suggest that anthropogenic climate change increased the likelihood of Hurricane Dorian's extreme 3-hourly rainfall amounts and total accumulated rainfall by 8%-18% and 5%-10%, respectively. Hurricane Dorian formed [...]

The exigencies of the global community toward Earth system science will increase in the future as the human population, economies, and the human footprint on the planet continue to grow. [...]

Dynamical downscaling is a crucial process for providing regional climate information for broad uses, using coarser-resolution global models to drive higher-resolution regional climate simulations. The pool of global climate models (GCMs) providing the fields needed for dynamical downscaling has increased from the previous generations of the Coupled Model Intercomparison Project (CMIP). However, with limited computational resources, the need for prioritizing the GCMs for subsequent downscaling studies remains. GCM selection for dynamical downscaling should focus on evaluating processes relevant for providing boundary conditions to the regional models and be inspired by regional uses such as the response of extremes to changes in the boundary conditions. This leads to the need for metrics representing processes of relevance to diverse stakeholders and subregions of a domain. Procedures to account for metric redundancy and the statistical distinguishability of GCM rankings are required. Further, procedures for selecting realizations from ensembles of top-performing GCM simulations can be used to span the range of climate change signals in multiple ways. As a result, distinct weighting of metrics and prioritization of particular realizations may depend on user needs. We provide high-level guidelines for such region-specific evaluations and address how CMIP7 might enable dynamical downscaling of a representative sample of high-quality models across representative shared socioeconomic pathways (SSPs). [ABSTRACT FROM AUTHOR]

While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and to understand the relationship [...]

The frequency of atmospheric blocking has been largely underestimated by general circulation models (GCMs) participating in the Coupled Model Intercomparison Project (CMIP). Errors in the onset, persistence, barotropicity, geographical preference, seasonality, intensity, and moving speed of global blocking were diagnosed in 10 Geophysical Fluid Dynamics Laboratory (GFDL) GCMs for recent CMIP5 and CMIP6 using a detection approach that combines zonal eddies and the reversal of zonal winds. The blocking frequency, similar at 500 and 250 hPa, is underestimated by 50% in the Atlantic–Europe region during December–February but is overestimated by 60% in the Pacific–North America region during that season and by 70% in the southwest Pacific during July–August. These blocking biases at 500 hPa were investigated in the five CMIP6 models that showed improvements over the CMIP5 versions. The Atlantic–Europe underestimate corresponds to lower instantaneous blocking rates, lower persistent blocking rates, and higher persistent stationary ridge rates; the number of blocks with a duration of 4–5 days is only 40%–65% of that in observations. In contrast, the overestimate consists of excessive blocks with a duration longer than 12 days in the Pacific–North America and up to twice as many 4–6-day events in the southwest Pacific. Simulated December–February blocks up to 12 days in the Pacific–North America region tend to be stronger and to move more slowly than those in observations. Diagnostic sensitivity tests indicated that the zonal mean and zonal eddy components of the mean state play a key role, as replacing each with that of observations substantially reduced many of the outstanding biases in these GCMs. [ABSTRACT FROM AUTHOR]

The prevailing conceptual model for the production of severe local storm (SLS) environments over North America asserts that upstream elevated terrain and the Gulf of Mexico are both essential to their formation. This work tests this hypothesis using two prescribed-ocean climate model experiments with North American topography removed or the Gulf of Mexico converted to land and analyzes how SLS environments and associated synoptic-scale drivers (southerly Great Plains low-level jets, drylines, elevated mixed layers, and extratropical cyclones) change relative to a control historical run. Overall, SLS environments depend strongly on upstream elevated terrain but more weakly on the Gulf of Mexico. Removing elevated terrain substantially reduces SLS environments especially over the continental interior due to broad reductions in both thermodynamic instability and vertical wind shear, leaving a more zonally uniform residual distribution that is maximized near the Gulf coast and decays toward the continental interior. This response is associated with a strong reduction in synoptic-scale drivers and a cooler and drier mean-state atmosphere. Replacing the Gulf of Mexico with land modestly reduces SLS environments over the Great Plains (driven primarily thermodynamically) and increases them over the eastern United States (driven primarily kinematically), shifting the primary local maximum eastward into Illinois; it also eliminates the secondary, smaller local maximum over southern Texas. This response is associated with modest changes in synoptic-scale drivers and a warmer and drier lower troposphere. These experiments provide insight into the role of elevated terrain and the Gulf of Mexico in modifying the spatial distribution and seasonality of SLS environments. [ABSTRACT FROM AUTHOR]

The four idealized configurations of the U.S. CLIVAR Hurricane Working Group are integrated using the global Community Atmospheric Model version 5.1 at two different horizontal resolutions, approximately 100 and 25 km. The publicly released 0.9° × 1.3° configuration is a poor predictor of the sign of the 0.23° × 0.31° model configuration's change in the total number of tropical storms in a warmer climate. However, it does predict the sign of the higher-resolution configuration's change in the number of intense tropical cyclones in a warmer climate. In the 0.23° × 0.31° model configuration, both increased CO2 concentrations and elevated sea surface temperature (SST) independently lower the number of weak tropical storms and shorten their average duration. Conversely, increased SST causes more intense tropical cyclones and lengthens their average duration, resulting in a greater number of intense tropical cyclone days globally. Increased SST also increased maximum tropical storm instantaneous precipitation rates across all storm intensities. It was found that while a measure of maximum potential intensity based on climatological mean quantities adequately predicts the 0.23° × 0.31° model's forced response in its most intense simulated tropical cyclones, a related measure of cyclogenesis potential fails to predict the model's actual cyclogenesis response to warmer SSTs. These analyses lead to two broader conclusions: 1) Projections of future tropical storm activity obtained by a direct tracking of tropical storms simulated by coarse-resolution climate models must be interpreted with caution. 2) Projections of future tropical cyclogenesis obtained from metrics of model behavior that are based solely on changes in long-term climatological fields and tuned to historical records must also be interpreted with caution. [ABSTRACT FROM AUTHOR]