What Drives the Spatial and Temporal Variability of Potential Evaporation Across CONUS and the Colorado River Basin?
Location
ECC 307/309
Event Website
http://water.usu.edu/
Start Date
4-4-2012 1:50 PM
End Date
4-4-2012 2:10 PM
Description
Because the distribution of soil and vegetative moisture is essentially unknowable at operationally useful temporal and spatial scales, hydrologists interested in quantifying actual evapotranspiration (ET) use potential evaporation (E0) to quantify ET’s upper limit. ET is then estimated by scaling down from E0 using simple vegetation-related coefficients or land-surface models. This paradigm underpins much of operational hydrology, including streamflow prediction, water management in municipalities and agriculture, and other decision-making enterprises that rely on real-time quantification of surface water availability. This widespread use of E0 motivates a need for measures that rely on physically appropriate forcings, that yield accurate results at time and space scales relevant to operational goals, and that avoid extraneous modeling uncertainty or the omission of key sources of variability. The primary goal of our study is to meet this need To understand the sources of variability of E0, a mean-value, second-moment uncertainty analysis is applied to a 30-year, CONUS-distributed dataset of daily synthetic pan evaporation derived from the “PenPan” model, a combination equation that mimics observations from US Class A evaporation pans. For drivers, we use six North American Land Data Assimilation System variables: temperature, specific humidity, station pressure, wind speed, and downwelling shortwave and longwave radiation. The variability of E0 is decomposed across various time scales into contributions from these drivers. We find that, contrary to popular expectation and much hydrologic practice, temperature is not always the most significant driver of temporal variability in E0, particularly at sub-annual time scales. Instead, depending on the region and the season, one of four drivers (temperature, specific humidity, downwelling shortwave radiation, and wind speed) dominates across different regions of CONUS. Temperature, specific humidity, downwelling shortwave radiation, and wind speed must together be examined, with downwelling longwave radiation as a secondary input. If any variable may be ignored, it is atmospheric pressure. While temperature generally dominates in the northern continental interior, parameterizations based solely on temperature should be avoided over large areas and at sub-annual time scales. Our results have clear implications for modeling E0 in operational hydrology or as a metric of climate change and variability; not least in assisting land surface modelers find a balance between parameter parsimony and physical representativeness. In our presentation, we will describe the analysis concept across CONUS and then concentrate on the implications of our results across the Colorado River basin.
What Drives the Spatial and Temporal Variability of Potential Evaporation Across CONUS and the Colorado River Basin?
ECC 307/309
Because the distribution of soil and vegetative moisture is essentially unknowable at operationally useful temporal and spatial scales, hydrologists interested in quantifying actual evapotranspiration (ET) use potential evaporation (E0) to quantify ET’s upper limit. ET is then estimated by scaling down from E0 using simple vegetation-related coefficients or land-surface models. This paradigm underpins much of operational hydrology, including streamflow prediction, water management in municipalities and agriculture, and other decision-making enterprises that rely on real-time quantification of surface water availability. This widespread use of E0 motivates a need for measures that rely on physically appropriate forcings, that yield accurate results at time and space scales relevant to operational goals, and that avoid extraneous modeling uncertainty or the omission of key sources of variability. The primary goal of our study is to meet this need To understand the sources of variability of E0, a mean-value, second-moment uncertainty analysis is applied to a 30-year, CONUS-distributed dataset of daily synthetic pan evaporation derived from the “PenPan” model, a combination equation that mimics observations from US Class A evaporation pans. For drivers, we use six North American Land Data Assimilation System variables: temperature, specific humidity, station pressure, wind speed, and downwelling shortwave and longwave radiation. The variability of E0 is decomposed across various time scales into contributions from these drivers. We find that, contrary to popular expectation and much hydrologic practice, temperature is not always the most significant driver of temporal variability in E0, particularly at sub-annual time scales. Instead, depending on the region and the season, one of four drivers (temperature, specific humidity, downwelling shortwave radiation, and wind speed) dominates across different regions of CONUS. Temperature, specific humidity, downwelling shortwave radiation, and wind speed must together be examined, with downwelling longwave radiation as a secondary input. If any variable may be ignored, it is atmospheric pressure. While temperature generally dominates in the northern continental interior, parameterizations based solely on temperature should be avoided over large areas and at sub-annual time scales. Our results have clear implications for modeling E0 in operational hydrology or as a metric of climate change and variability; not least in assisting land surface modelers find a balance between parameter parsimony and physical representativeness. In our presentation, we will describe the analysis concept across CONUS and then concentrate on the implications of our results across the Colorado River basin.
https://digitalcommons.usu.edu/runoff/2012/AllAbstracts/47