Abstract

The tracks, intensities, and other properties of tropical cyclones downscaled from three models’ simulations of the Last Glacial Maximum (LGM) are analyzed and compared to those of storms downscaled from simulations of the present climate. Globally, the mean maximum intensity of storms generated from each model is lower at LGM, as is the fraction of all storms that reach intensities of category 4 or higher on the Saffir–Simpson hurricane wind scale. The median day of the storm season shifts earlier by an average of one week in all three models in both hemispheres. Two of the three models’ LGM simulations feature a reduction in storm count and global power dissipation index compared to the current climate, but a third shows no significant difference between the two climates. Although each model is forced by the same global changes, differences in the way sea surface temperatures and other large-scale environmental conditions respond in the North Atlantic impart significant differences in the climatology at LGM between models. Our results from the cold LGM provide a novel opportunity to assess how tropical cyclones respond to climate changes.

Abstract

The spatial and temporal distribution of stable and convectively neutral air masses is examined in climate simulations with carbon dioxide levels spanning from modern-day values to very high levels that produce surface temperatures relevant to the hottest climate of the past 65 million years. To investigate how stability with respect to slantwise and upright moist convection changes across a wide range of climate states, the condition of moist convective neutrality in climate experiments is assessed using metrics based upon the saturation of potential vorticity, which is zero when temperature profiles are moist adiabatic profiles along vortex lines. The modern climate experiment reproduces previously reported properties from reanalysis data, in which convectively neutral air masses are common in the tropics and locally at higher latitudes, especially over midlatitude continents in summer and ocean storm tracks in winter. The frequency and coverage of air masses with higher stabilities declines in all seasons at higher latitudes with warming; the hottest case features convectively neutral air masses in the Arctic a majority of the time in January and nearly universally in July. The contribution from slantwise convective motions (as distinct from upright convection) is generally small outside of midlatitude storm tracks, and it declines in the warmer climate experiments, especially during summer. These findings support the conjecture that moist adiabatic lapse rates become more widespread in warmer climates, providing a physical basis for using this assumption in estimating paleoaltimetry during warm intervals such as the early Eocene.

Abstract

A method to simulate thousands of tropical cyclones using output from a global climate model is applied to simulations that span very high surface temperatures forced with high levels of carbon dioxide (CO₂). The climatology of the storms downscaled from a simulation with modern-day conditions is compared to that of events downscaled from two other simulations featuring 8 and 32 times preindustrial-era levels of CO₂. Storms shift poleward with warming: genesis locations and track densities increase in subtropical and higher latitudes, and power dissipation increases poleward of 20°S and 30°N. The average latitude at which storms reach their maximum intensity shifts poleward by more than 1.5° latitude in the 8 × CO₂ experiment and by more than 7° latitude in the 32 × CO₂ case. Storms live longer and are more numerous in both of the warmer climates. These increases come largely from an expansion of the area featuring favorable conditions into subtropics and midlatitudes, with some regions of the Arctic having the thermodynamic conditions necessary to sustain systems in the hottest case. Storms of category 5 intensity are 52% more frequent in the 8 × CO₂ experiment but 40% less so in the 32 × CO₂ case, largely owing to a substantial decline in low-latitude activity associated with increases in a normalized measure of wind shear called the ventilation index. Changes in genesis and track densities align well with differences in the ventilation index, and environmental conditions become substantially more favorable poleward of about 20° latitude in the warmer climates.

Abstract

Research in meteorological prediction on subseasonal to seasonal (S2S) time scales has seen growth in recent years. Concurrent with this growth, demand for seasonal drought forecasting has risen. While there is obvious synergy between these fields, S2S meteorological forecasting has typically focused on low-resolution global models, whereas the development of drought can be sensitive to the local expression of weather anomalies and their interaction with local surface properties and processes. This suggests that downscaling might play an important role in the application of meteorological S2S forecasts to skillful forecasting of drought. Here, we apply the generalized analog regression downscaling (GARD) algorithm to downscale meteorological hindcasts from the NASA Goddard Earth Observing System global S2S forecast system. Downscaled meteorological fields are then applied to drive offline simulations with the Catchment Land Surface Model to forecast U.S. Drought Monitor–style drought indicators derived from simulated surface hydrology variables. We compare the representation of drought in these downscaled hindcasts with hindcasts that are not downscaled, using the North American Land Data Assimilation System Phase 2 (NLDAS-2) dataset as an observational reference. We find that downscaling using GARD improves hindcasts of temperature and temperature anomalies but that the results for precipitation are mixed and generally small. Overall, GARD downscaling led to improved hindcast skill for total drought across the contiguous United States, and improvements were greatest for extreme (D3) and exceptional (D4) drought categories.

Abstract

Forecasts by mid-2015 for a strong El Niño during winter 2015/16 presented an exceptional scientific opportunity to accelerate advances in understanding and predictions of an extreme climate event and its impacts while the event was ongoing. Seizing this opportunity, the National Oceanic and Atmospheric Administration (NOAA) initiated an El Niño Rapid Response (ENRR), conducting the first field campaign to obtain intensive atmospheric observations over the tropical Pacific during El Niño.

The overarching ENRR goal was to determine the atmospheric response to El Niño and the implications for predicting extratropical storms and U.S. West Coast rainfall. The field campaign observations extended from the central tropical Pacific to the West Coast, with a primary focus on the initial tropical atmospheric response that links El Niño to its global impacts. NOAA deployed its Gulfstream-IV (G-IV) aircraft to obtain observations around organized tropical convection and poleward convective outflow near the heart of El Niño. Additional tropical Pacific observations were obtained by radiosondes launched from Kiritimati , Kiribati, and the NOAA ship Ronald H. Brown, and in the eastern North Pacific by the National Aeronautics and Space Administration (NASA) Global Hawk unmanned aerial system. These observations were all transmitted in real time for use in operational prediction models. An X-band radar installed in Santa Clara, California, helped characterize precipitation distributions. This suite supported an end-to-end capability extending from tropical Pacific processes to West Coast impacts. The ENRR observations were used during the event in operational predictions. They now provide an unprecedented dataset for further research to improve understanding and predictions of El Niño and its impacts.