32 research outputs found

    Estimating Watershed Evapotranspiration with PASS. Part I: Inferring Root-Zone Moisture Conditions Using Satellite Dat

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    A model framework for parameterized subgrid-scale surface fluxes (PASS) has been modified and applied as PASS1 to use satellite data, models, and limited surface observations to infer root-zone available moisture (RAM) content with high spatial resolution over large terrestrial areas. Data collected during the 1997 Cooperative Atmosphere–Surface Exchange Study field campaign at the Atmospheric Boundary Layer Experiments site in the Walnut River watershed in Kansas were used to evaluate applications of the PASS1 approach to infer soil moisture content at times of satellite overpasses during cloudless conditions. Data from Advanced Very High Resolution Radiometers on the NOAA-14 satellite were collected and then adjusted for atmospheric effects by using LOWTRAN7 and local atmospheric profile data from radiosondes. The input variables for PASS1 consisted of normalized difference vegetation index and surface radiant temperature, together with representative observations of downwelling solar irradiance, air temperature, relative humidity, and wind speed. Surface parameters, including roughness length, albedo, surface conductance for water vapor, and the ratio of soil heat flux to net radiation, were estimated with parameterizations suitable for the area using satellite data and land-use information; pixel-specific near-surface meteorological conditions such as air temperature, vapor pressure, and wind speed were adjusted according to local surface forcing; and RAM content was estimated using surface energy balance and aerodynamic methods. Comparisons with radar cumulative precipitation observations and in situ soil moisture estimates indicated that the spatial and temporal variations of RAM at the times of satellite overpasses were simulated reasonably well by PASS1

    An eddy-correlation measurement of NO2 flux to vegetation and comparison to O3 flux

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    Eddy-correlation measurements with a newly developed fast-response NOx sensor indicate that the deposition velocity at a height of about 6m above a soybean field has a maximum value near 0.6cms-1 for NOx and is usually about 2/3 ofthat found for ozone. In these studies, over 90% of the NOx is NO2. The corresponding minimum surface resistance for NOx calculated as the quantity remaining after atmospheric resistances are subtracted is about 1.3 s cm-1, which is larger than expected on the basis of leaf stomatal resistance alone. Emission of NO from sites in the plant canopy and soil where NO2 is deposited and reduced to NO or release of NOx as a result of biological activity may have lessened the downward fluxes of NOx as measured. During windy conditions at night, surface resistances are found to have values of about 15scm-1 for NOx (again, greater than 90% NO2) and 1.8scm-1 for O3, corresponding to deposition velocities of 0.05cms-1 and 0.3cms-1, respectively.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24138/1/0000395.pd

    Estimating the Long-Term Hydrological Budget over Heterogeneous Surfaces

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    Estimates of the hydrological budget in the Walnut River Watershed (WRW; 5000 km2) of southern Kansas were made with a parameterized subgrid-scale surface (PASS) model for the period 1996–2002. With its subgrid-scale distribution scheme, the PASS model couples surface meteorological observations with satellite remote sensing data to update root-zone available moisture and to simulate surface evapotranspiration rates at high resolution over extended areas. The PASS model is observationally driven, making use of extensive parameterizations of surface properties and processes. Heterogeneities in surface conditions are spatially resolved to an extent determined primarily by the satellite data pixel size. The purpose of modeling the spatial and interannual variability of water budget components at the regional scale is to evaluate the PASS model’s ability to bridge a large grid cell of a climate model with its subgrid-scale variation. Modeled results indicate that annual total evapotranspiration at the WRW is about 66%–88% of annual precipitation—reasonable values for southeastern Kansas—and that it varies spatially and temporally. Seasonal distribution of precipitation plays an important role in evapotranspiration estimates. Comparison of modeled runoff with stream gauge measurements demonstrated close agreement and verified the accuracy of modeled evapotranspiration at the regional scale. In situ measurements of energy fluxes compare favorably with the modeled values for corresponding grid cells, and measured surface soil moisture corresponds with modeled root-zone available moisture in terms of temporal variability despite very heterogeneous surface conditions. With its ability to couple remote sensing data with surface meteorology data and its computational efficiency, PASS is easily used for modeling surface hydrological components over an extended region and in real time. Thus, it can fill a gap in evaluations of climate model output using limited field observations
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