Surface temperature lapse rates over complex terrain: Lessons from the Cascade M

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Title:
Surface temperature lapse rates over complex terrain: Lessons from the Cascade Mountains Authors:
Minder, Justin R.; Mote, Philip W.; Lundquist, Jessica D. Affiliation:
AA(Department of Atmospheric Science, University of Washington, Seattle, Washington, USA), AB(Oregon Climate Change Research Institute, College of Oceanic and Atmospheric Sciences, Oregon State University, Corvallis, Oregon, USA), AC(Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, USA) Publication:
Journal of Geophysical Research: Atmospheres, Volume 115, Issue D14, CiteID D14122 (JGRD Homepage) Publication Date:
07/2010 Origin:
AGU; WILEY Keywords:
Atmospheric Processes: Climatology (1616, 1620, 3305, 4215, 8408), Hydrology: Instruments and techniques: modeling, Hydrology: Instruments and techniques: monitoring, Atmospheric Processes: Regional modeling, Atmospheric Processes: Mesoscale meteorology, mountain hydrology, snowpack, mountain meteorology Abstract Copyright:
Copyright 2010 by the American Geophysical Union. DOI:
10.1029/2009JD013493 Bibliographic Code:
2010JGRD..11514122M

Abstract

The typically sparse distribution of weather stations in mountainous terrain inadequately resolves temperature variability. Accordingly, high-resolution gridding of climate data (for applications such as hydrological modeling) often relies on assumptions such as a constant surface temperature lapse rate (i.e., decrease of surface temperature with altitude) of 6.5°C km-1. Using an example of the Cascade Mountains, we describe the temporal and spatial variability of the surface temperature lapse rate, combining data from: (1) COOP stations, (2) nearby radiosonde launches, (3) a temporary dense network of sensors, (4) forecasts from the MM5 regional model, and (5) PRISM geo-statistical analyses. On the windward side of the range, the various data sources reveal annual mean lapse rates of 3.9-5.2°C km-1, substantially smaller than the often-assumed 6.5°C km-1. The data sets show similar seasonal and diurnal variability, with lapse rates smallest (2.5-3.5°C km-1) in late-summer minimum temperatures, and largest (6.5-7.5°C km-1) in spring maximum temperatures. Geographic (windward versus lee side) differences in lapse rates are found to be substantial. Using a simple runoff model, we show the appreciable implications of these results for hydrological modeling.
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