Improving Boundary Layer and Near-Surface Temperatures Forecasts over Arid Mountainous Regions: Results from the MATERHORN Field Campaign

Near-surface temperature (NST) forecasts are critical for the protection of life and property, economic and operational activities, and routine day-to-day planning, but remain an Achilles heal for numerical weather prediction. Modeling systems in many regions of the world have trouble simulating NSTs and typically underpredict the diurnal NST cycle. Indeed, Weather Research and Forecasting Model (WRF) forecasts for Dugway Proving Ground (DPG), a rugged, arid region of complex terrain in Northwest Utah, show an underprediction of the diurnal NST cycle. In particular, nocturnal cooling over the sparsely vegetated silt loam soil area of DPG is underpredicted with a mean positive bias error of 3.4°C in the early morning [1200 UTC (0500 LST)]. In addition, daytime heating is under-predicted with a mean negative bias error of 1.0°C in the late afternoon [0000 UTC (1700 LST)]. Using surface and upper level observations collected during the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) field campaigns we show that the early morning warm bias is related to the improper initialization of soil moisture and parameterization of the soil thermal conductivity in silt loam and sandy loam soils. This bias can be reduced significantly by initializing the WRF with observed soil moisture and by replacing the Johansen (1975) parameterization of soil thermal conductivity in the Noah land-surface model with that proposed by McCumber and Pielke (1981) for silt loam and sandy loam soils. A case study demonstrates how these changes can reduce a nighttime 2-m temperature warm bias of 4.9°C over silt loam soil textures to 0.8°C and also improve predicted ground heat flux and soil thermal conductivity values. The mean late afternoon cool bias extends vertically beyond the top of the planetary boundary layer and ongoing research aims to better understand and improve this bias. We anticipate these results to be applicable in other arid regions of complex terrain.