Flux Interpolation on Cloudy Days

As noted above, ALEXI cannot be applied on a given day at grid cells within the modeling domain where it was cloudy at, or between, the times of the two radiometric temperature measurements which primarily drive the model. This leads to spatially patchy model output, where the unmodeled patches move about in the domain from day to day. Typical daily model coverage is about 10-40% for the continental U.S. Such patchy output is not conducive to analyses of long-term flux patterns and climatologies.

To provide spatially and temporally continuous flux estimates across the entire modeling domain, a flux interpolation algorithm is employed to predict fluxes under cloudy conditions. This algorithm compares ALEXI-derived estimates of soil and canopy latent heat fluxes to potential fluxes given by the Priestley-Taylor approximation partitioned between the soil (using methods of Jury & Tanner, 1976) and canopy (Norman et al., 1995) components of the system. Campbell and Norman (1998) relate the fraction of potential plant uptake rate to the available water fraction in the root zone. A similar functional is applied to predict the available water fraction in the soil surface layer from the ratio of "actual" to potential soil evaporation.

In this way, the soil moisture content in the surface (0-5cm) and root zone (5cm-2m) moisture pools is updated each day ALEXI can be executed at a given grid cell. Between updates, these pools are depleted each day by the day- integrated soil and canopy latent heat flux assigned to that grid cell by the interpolation procedure.

On cloudy days, the procedure is reversed. The relation of Campbell and Norman (1998) is inverted to estimate the actual/potential latent heat flux ratio from the current estimates of available water fraction. Computing potential fluxes from satellite-based estimates of net radiation, "actual" soil and canopy evaporative fluxes are backed out, and sensible heat fluxes solved as the residuals to the component energy budgets.

While somewhat simplistic, this methodology has the advantage of imposing day-to-day continuity in flux partitioning during cloudy intervals while still responding to largescale climatic controls on evaporation such as radiation load and atmospheric demand. Tests with ground-based flux measurements indicates this method does a reasonable job of interpolating cloudy day flux components.

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ALEXI TUTORIAL

  1. Structure of the ALEXI model
  2. Partitioning the energy budget
  3. Inputs to the ALEXI model
  4. Outputs from the ALEXI model
  5. Cloudy-day interpolation algorithm [YOU ARE HERE]
  6. ALEXI as an agent for soil moisture assimilation
  7. The ALEX suite of landsurface models

 
 

 

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