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dc.contributor.authorCurtis, David Carletonen_US
dc.contributor.authorEagleson, Peter S.en_US
dc.date.accessioned2022-06-13T13:10:44Z
dc.date.available2022-06-13T13:10:44Z
dc.date.issued1982-05
dc.identifier274
dc.identifier.urihttps://hdl.handle.net/1721.1/143027
dc.descriptionPrepared with the Support of the National Oceanic and Atmospheric Administration, the National Weather Service, and the National Science Foundation.en_US
dc.description.abstractA stochastic, multivariate, hydrometeorological data generation algorithm is presented. Hourly values of precipitation, cloud cover, shortwave radiation, longwave radiation, temperature, dewpoint, wind speed, and wind direction are jointly generated for the two-meter level. The procedure is designed to provide coherent sets of input data for models of various land surface processes. The model's flexibility and economy allow the study of land surface responses to different atmospheric forcings. Generated data plots, model output statistics, and generated mean diurnal curves are compared to observations for the months of January and July at two sites, Boston, Massachusetts and Dodge City, Kansas. Data representing three "climates", normal, wet, and temperature-biased were generated and applied to a detailed model of the land surface. The resulting energy fluxes across the land-atmosphere interface are reviewed and the differences are noted.en_US
dc.publisherCambridge, Mass. : Ralph M. Parsons Laboratory, Hydrology and Water Resource Systems, Massachusetts Institute of Technology, Dept. of Civil Engineering
dc.relation.ispartofseriesR (Massachusetts Institute of Technology. Department of Civil Engineering) ; 82-25.
dc.relation.ispartofseriesReport (Ralph M. Parsons Laboratory for Water Resources and Hydrodynamics) ; 274.
dc.titleConstrained Stochastic Climate Simulationen_US
dc.identifier.oclc10691587
dc.identifier.aleph241185


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