Sentences with phrase «dynamical downscaling»
"Dynamical downscaling" refers to a method used in climate research to provide more detailed and localized information about weather patterns. It involves taking global climate model data and using it to create more specific predictions for smaller regions or areas. This helps scientists better understand and analyze the impacts of climate change on a smaller scale. Full definition
Operational use of dynamical downscaling with the RSM and WRF models for seasonal forecasting over GHA.
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«To explore the long - term effects of a global GHG mitigation strategy, we used dynamical downscaling from global simulations to predict the changes in air quality and related premature deaths.»
Knutson, T. R., J. J. Sirutis, G. A. Vecchi, S. Garner, M. Zhao, H. - S. Kim, M. Bender, R. E. Tuleya, I. M. Held, and G. Villarini, 2013: Dynamical downscaling projections of twenty - first - century Atlantic hurricane activity: CMIP3 and CMIP5 model - based scenarios.
GFDL researchers have developed a regional dynamical downscaling model for Atlantic hurricanes and tested it by comparing with observed hurricane activity since 1980.
We have developed a regional dynamical downscaling model for Atlantic hurricanes and tested it by comparing with observed hurricane activity since 1980.
This study explores whether dynamical downscaling can reduce EETC frequency biases, and whether this affects future projections of storms along North America's Atlantic coast.
The limited effect of dynamical downscaling on EETC frequency projections is consistent with the lack of impact on the maximum Eady growth rate.
In a series of Atlantic basin - specific dynamical downscaling studies (Bender et al. 2010; Knutson et al. 2013), we attempted to address both of these limitations by letting the Atlantic basin regional model of Knutson et al. (2008) provide the overall storm frequency information, and then downscaling each individual storm from the regional model study into the GFDL hurricane prediction system.
Rockel, B., C.L. Castro, R.A. Pielke Sr., H. von Storch, and G. Leoncini, 2008: Dynamical downscaling: Assessment of model system dependent retained and added variability for two different regional climate models.
As with the dynamical downscaling of RCMs, the methods described in this section rely on the concept that regional climates are largely a function of the large - scale atmospheric state.
Dynamical downscaling uses high - resolution climate models to represent global or regional sub-domains, and uses either observed or lower - resolution AOGCM data as their boundary conditions.
Dynamical downscaling has the potential for capturing mesoscale nonlinear effects and providing coherent information among multiple climate variables.
Hughes M., J. D. Lundquist and B. Henn (April 2017): Dynamical downscaling improves upon gridded precipitation products in the Sierra Nevada, California.
Spak, S., T. Holloway, B. Lynn, and R. Goldberg, 2007: A comparison of statistical and dynamical downscaling for surface temperature in North America.
See Christensen et al. (2007a) for a complete discussion of the strengths and weaknesses of both statistical and dynamical downscaling.