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contributor authorParding, Kajsa M.
contributor authorBenestad, Rasmus
contributor authorMezghani, Abdelkader
contributor authorErlandsen, Helene B.
date accessioned2019-10-05T06:48:48Z
date available2019-10-05T06:48:48Z
date copyright4/5/2019 12:00:00 AM
date issued2019
identifier otherJAMC-D-17-0348.1.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4263495
description abstractAbstractA method for empirical?statistical downscaling was adapted to project seasonal cyclone density over the North Atlantic Ocean. To this aim, the seasonal mean cyclone density was derived from instantaneous values of the 6-h mean sea level pressure (SLP) reanalysis fields. The cyclone density was then combined with seasonal mean reanalysis and global climate model projections of SLP or 500-hPa geopotential height to obtain future projections of the North Atlantic storm tracks. The empirical?statistical approach is computationally efficient because it makes use of seasonally aggregated cyclone statistics and allows the future cyclone density to be estimated from the full ensemble of available CMIP5 models rather than from a smaller subset. However, the projected cyclone density in the future differs considerably depending on the choice of predictor, SLP, or 500-hPa geopotential height. This discrepancy suggests that the relationship between the cyclone density and SLP, 500-hPa geopotential height, or both is nonstationary; that is, that the statistical model depends on the calibration period. A stationarity test based on 6-hourly HadGEM2-ES data indicated that the 500-hPa geopotential height was not a robust predictor of cyclone density.
publisherAmerican Meteorological Society
titleStatistical Projection of the North Atlantic Storm Tracks
typeJournal Paper
journal volume58
journal issue7
journal titleJournal of Applied Meteorology and Climatology
identifier doi10.1175/JAMC-D-17-0348.1
journal fristpage1509
journal lastpage1522
treeJournal of Applied Meteorology and Climatology:;2019:;volume 058:;issue 007
contenttypeFulltext


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