2006
DOI: 10.1175/jhm486.1
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A Meteorological Distribution System for High-Resolution Terrestrial Modeling (MicroMet)

Abstract: An intermediate-complexity, quasi-physically based, meteorological model (MicroMet) has been developed to produce high-resolution (e.g., 30-m to 1-km horizontal grid increment) atmospheric forcings required to run spatially distributed terrestrial models over a wide variety of landscapes. The following eight variables, required to run most terrestrial models, are distributed: air temperature, relative humidity, wind speed, wind direction, incoming solar radiation, incoming longwave radiation, surface pressure,… Show more

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Cited by 514 publications
(585 citation statements)
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“…This has been observed in many other mountain regions. For example Liston and Elder [72] use a seasonally variable linear gradient, where precipitation increases with altitude, according to work in the western US by Thornton et al [73]. Closer to the Pyrenees, in the Alps Lehning et al [74] have noted the problems of deriving a reliable precipitation gradient, either because of lack of measurements at high altitude [75,76], or because the difficulty of measuring solid precipitation at high elevation and with strong winds [77].…”
Section: Discussionmentioning
confidence: 99%
“…This has been observed in many other mountain regions. For example Liston and Elder [72] use a seasonally variable linear gradient, where precipitation increases with altitude, according to work in the western US by Thornton et al [73]. Closer to the Pyrenees, in the Alps Lehning et al [74] have noted the problems of deriving a reliable precipitation gradient, either because of lack of measurements at high altitude [75,76], or because the difficulty of measuring solid precipitation at high elevation and with strong winds [77].…”
Section: Discussionmentioning
confidence: 99%
“…The observed meteorological data was interpolated into 10 km × 10 km grids based on the meteorological distribution system for high-resolution terrestrial modeling (MicroMet) [37]. The potential evaporation was estimated using the Penman-Monteith equation [38] for each grid cell.…”
Section: Datamentioning
confidence: 99%
“…One potential source of these errors would be errors in estimation of meteorologic inputs. Interpolation of both temperature and precipitation in mountain environments is a well-documented source of error in hydrologic models (Liston and Elder, 2006). Here we use a relatively simple approach where point meteorologic measurements of temperature are scaled using a constant environmental lapse rate of temperature with elevation, and precipitation is scaled based on long-term mean patterns derived from PRISM (Daly et al, 1994).…”
Section: Discussionmentioning
confidence: 99%