Document Type


Publication Date

January 1993


Executive Summary: Introduction: This report summarizes work conducted during the funding period (December 1, 1991 through September 30, 1992) of a Research Joint Venture Agreement between the Intermountain Research Station, Forest Service, U. S. Department of Agriculture and the Utah Water Research Laboratory (UWRL), Utah State University (USU). The purpose of the agreement is to develop a Western Mountain Cilmate Generator (MCLIGEN) similar in function to the existing (non-orographic area) Climate Generator (CLIGEN), which is part of the Water Erosion Prediciton Project (WEPP) procedure. Aso, we are developing a Western U.S. Snowpack Simulation Model for includsion in WEPP. In the western U.S., topographic influences on climate make the climate too variable to be captured by one representatbie station per 100 km, as is done in CLIGEN. Also, few meteorological observations exist in high-elevation areas where Forest Service properties are located. Therefore, a procedure for estimating climatological variables in mountainous areas is needed to apply WEPP in these regions. A physically based approach, using an expanded and improved orographic precipitation model, is being utilized. It will use radiosonde lightning data to estimate historical weather sequences. Climatological sequences estimated at ungaged locations will be represented using stochastic models, similar to the approach used in the existing CLIGEN. By using these stochastic models, WEPP users will be able to synthesize climate sequences for input to WEPP. MCLIGEN will depend on historically based, physically interpolated weather sequences from a mesoscale-climate modeling system which is comprised of four nested layers: 1. an existing synoptic scale forecast model (200 x 300 km) 2. a regional scale slimate model (60 x60 km) 3. a local scale climate model (10 x 10 km); and 4. a specific point climate predictor, referred to as "ZOOM." Two additional MCLIGEN components are: 5. a local scalses stochastic climate generator; and 6. a point energy balance snowmelt model Progress made during the reporting period in developing the physically based interpolation climate modeling system stochastic models, and snowpack models is summareized below.