Andreas F. Prein


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Dryline characteristics in North America’s historical and future climates
Lucia Scaff, Andreas F. Prein, Yanping Li, Adam J. Clark, Sebastian A. Krogh, Neil Taylor, Changhai Liu, Roy Rasmussen, Kyoko Ikeda, Zhenhua Li
Climate Dynamics, Volume 57, Issue 7-8

Drylines are atmospheric boundaries separating dry from moist air that can initiate convection. Potential changes in the location, frequency, and characteristics of drylines in future climates are unknown. This study applies a multi-parametric algorithm to objectively identify and characterize the dryline in North America using convection-permitting regional climate model simulations with 4-km horizontal grid spacing for 13-years under a historical and a pseudo-global warming climate projection by the end of the century. The dryline identification is successfully achieved with a set of standardized algorithm parameters across the lee side of the Rocky Mountains from the Canadian Rockies to the Sierra Madres in Mexico. The dryline is present 27% of the days at 00 UTC between April and September in the current climate, with a mean humidity gradient magnitude of 0.16 g−1 kg−1 km−1. The seasonal cycle of drylines peak around April and May in the southern Plains, and in June and July in the northern Plains. In the future climate, the magnitude and frequency of drylines increase 5% and 13%, correspondingly, with a stronger intensification southward. Future drylines strengthen during their peak intensity in the afternoon in the Southern U.S. and Northeast Mexico. Drylines also show increasing intensities in the morning with future magnitudes that are comparable to peak intensities found in the afternoon in the historical climate. Furthermore, an extension of the seasonality of intense drylines could produce end-of-summer drylines that are as strong as mid-summer drylines in the current climate. This might affect the seasonality and the diurnal cycle of convective activity in future climates, challenging weather forecasting and agricultural planning.


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Simulating the convective precipitation diurnal cycle in North America’s current and future climate
Lucia Scaff, Andreas F. Prein, Yanping Li, Changhai Liu, Roy Rasmussen, Kyoko Ikeda
Climate Dynamics, Volume 55, Issue 1-2

Convection-permitting models (CPM) with at least 4 km horizontal grid spacing enable the cumulus parameterization to be switched off and thus simulate convective processes more realistically than coarse resolution models. This study investigates if a North American scale CPM can reproduce the observed warm season precipitation diurnal cycle on a climate scale. Potential changes in the precipitation diurnal cycle characteristics at the end of the twenty first century are also investigated using the pseudo global warming approach under a high-end anthropogenic emission scenario (RCP8.5). Simulations are performed with the Advanced Research Weather Research and Forecasting (ARW-WRF) model with 4-km horizontal grid spacing. Results from the WRF historical run (2001–2013) are evaluated against hourly precipitation from 2903 weather stations and a gridded hourly precipitation product in the U.S. The magnitude and timing of the diurnal cycle peak are realistically simulated in most of the U.S. and southern Canada. The model also captures the transition from afternoon precipitation peaks eastward of the Rocky Mountains to night peaks in the central U.S., which is related to propagating mesoscale convective systems. However, the historical climate simulation does not capture the observed early morning peaks in the central U.S. and overestimates the magnitude of the diurnal precipitation peak in the southeast region. In the simulation of the future climate, both the precipitation amount of the diurnal cycle and precipitation intensity increase throughout the domain, along with an increase in precipitation frequency in the northern region of the domain in May. These increases indicate a clear intensification of the hydrologic cycle during the warm season with potential impacts on future water resources, agriculture, and flooding.