A11C-3035:
Applying GOES-derived fog frequency indices to water balance modeling for the Russian River Watershed, California

Monday, 15 December 2014
Alicia Torregrosa1, Lorraine E Flint2, Alan L Flint2, Jeff Peters1 and Cindy Combs3, (1)USGS California Water Science Center Menlo Park, Menlo Park, CA, United States, (2)USGS California Water Science Center Sacramento, Sacramento, CA, United States, (3)Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States
Abstract:
Coastal fog modifies the hydrodynamic and thermodynamic properties of California watersheds with the greatest impact to ecosystem functioning during arid summer months. Lowered maximum temperatures resulting from inland penetration of marine fog are probably adequate to capture fog effects on thermal land surface characteristics however the hydrologic impact from lowered rates of evapotranspiration due to shade, fog drip, increased relative humidity, and other factors associated with fog events are more difficult to gauge. Fog products, such as those derived from National Weather Service Geostationary Operational Environmental Satellite (GOES) imagery, provide high frequency (up to 15 min) views of fog and low cloud cover and can potentially improve water balance models. Even slight improvements in water balance calculations can benefit urban water managers and agricultural irrigation. The high frequency of GOES output provides the opportunity to explore options for integrating fog frequency data into water balance models. This pilot project compares GOES-derived fog frequency intervals (6, 12 and 24 hour) to explore the most useful for water balance models and to develop model-relevant relationships between climatic and water balance variables. Seasonal diurnal thermal differences, plant ecophysiological processes, and phenology suggest that a day/night differentiation on a monthly basis may be adequate. To explore this hypothesis, we examined discharge data from stream gages and outputs from the USGS Basin Characterization Model for runoff, recharge, potential evapotranspiration, and actual evapotranspiration for the Russian River Watershed under low, medium, and high fog event conditions derived from hourly GOES imagery (1999-2009). We also differentiated fog events into daytime and nighttime versus a 24-hour compilation on a daily, monthly, and seasonal basis. Our data suggest that a daily time-step is required to adequately incorporate the hydrologic effect of fog.