The Clausius–Clapeyron (C–C) relationship is a thermodynamic relationship between saturation vapor pressure and temperature. Based on the C–C relationship, the scaling of extreme precipitation with respect to surface air temperature (i.e., extreme precipitation scaling) has been widely believed to quantify the sensitivity of these extremes to global surface warming under climate change. However, the extreme precipitation scaling rate in the observations produces counter-intuitive results, particularly in the tropics (i.e., strong negative scaling in the tropical land) possibly associated with limitations in moisture availability under the high-temperature bands. The trends in extreme precipitation based on station data are mixed with decreases in most of the tropics and subtropics and increases in most of the USA, western Europe, Australia, and a large portion of Asia. To try to reconcile these results, we examine the extreme precipitation scaling using dew point temperature and extreme precipitation and compare these results with those obtained from surface air temperature and extreme precipitation using station-based data, reanalysis data, and climate model simulations. We find that this mix of increases and decreases in the trends of extreme precipitation across the planet is more similar to the changes in surface dew point temperature rather than the actual temperature across the station-based data, reanalysis data, and the historical experiments with the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 5 (CAM5). These findings suggest that dew point temperature is a better and more realistic metric for the responses of extreme precipitation to temperature increases. Therefore, the risk of having extreme precipitation is higher than what was obtained using surface air temperature, particularly in the tropics and subtropics (e.g., South Asia), areas of the world characterized by extremely high population density and severe poverty.

Heavy rainfall and flooding associated with tropical cyclones (TCs) are responsible for a large number of fatalities and economic damage worldwide. Despite their large socioeconomic impacts, research into heavy rainfall and flooding associated with TCs has received limited attention to date and still represents a major challenge. The capability to adapt to future changes in heavy rainfall and flooding associated with TCs is inextricably linked to and informed by understanding of the sensitivity of TC rainfall to likely future forcing mechanisms. Here a set of idealized high-resolution atmospheric model experiments produced as part of the U.S. Climate Variability and Predictability (CLIVAR) Hurricane Working Group activity is used to examine TC response to idealized global-scale perturbations: the doubling of CO2, uniform 2-K increases in global sea surface temperature (SST), and their combined impact. As a preliminary but key step, daily rainfall patterns of composite TCs within climate model outputs are first compared and contrasted to the observational records. To assess similarities and differences across different regions in response to the warming scenarios, analyses are performed at the global and hemispheric scales and in six global TC ocean basins. The results indicate a reduction in TC daily precipitation rates in the doubling CO2 scenario (on the order of 5% globally) and an increase in TC rainfall rates associated with a uniform increase of 2K in SST (both alone and in combination with CO2 doubling; on the order of 10%-20% globally). © 2014 American Meteorological Society.

Some of the long-term changes in weather and climate extremes across the US have occurred as expected in the warming climate, but the trends vary throughout the country and easily detected due to multiyear and decadal variations. The US National Climate Assessment has to address extremes, as these are changing and anthropogenic climate change has a role in altering the probabilities of some of the extreme events. Extreme events also drive changes in natural and human systems more than average climatic conditions. Four workshops have been held to provide technical input to the US National Climate Assessment writing team where leading scientists in the field worked jointly to determine how best to assess the state of the science in understanding the decadal- to century-scale variability and changes in various types of extreme events.

Although a theory of the climatology of tropical cyclone formation remains elusive, high-resolution climate models can now simulate many aspects of tropical cyclone climate.

Responses of tropical cyclones (TCs) to CO2 doubling are explored using coupled global climate models (GCMs) with increasingly refined atmospheric/land horizontal grids (~ 200 km, ~ 50 km and ~ 25 km). The three models exhibit similar changes in background climate fields thought to regulate TC activity, such as relative sea surface temperature (SST), potential intensity, and wind shear. However, global TC frequency decreases substantially in the 50 km model, while the 25 km model shows no significant change. The ~ 25 km model also has a substantial and spatially-ubiquitous increase of Category 3–4–5 hurricanes. Idealized perturbation experiments are performed to understand the TC response. Each model’s transient fully-coupled 2 × CO2 TC activity response is largely recovered by “time-slice” experiments using time-invariant SST perturbations added to each model’s own SST climatology. The TC response to SST forcing depends on each model’s background climatological SST biases: removing these biases leads to a global TC intensity increase in the ~ 50 km model, and a global TC frequency increase in the ~ 25 km model, in response to CO2-induced warming patterns and CO2 doubling. Isolated CO2 doubling leads to a significant TC frequency decrease, while isolated uniform SST warming leads to a significant global TC frequency increase; the ~ 25 km model has a greater tendency for frequency increase. Global TC frequency responds to both (1) changes in TC “seeds”, which increase due to warming (more so in the ~ 25 km model) and decrease due to higher CO2 concentrations, and (2) less efficient development of these“seeds” into TCs, largely due to the nonlinear relation between temperature and saturation specific humidity.