Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature

We tested four land surface parameterization schemes against long-term (5 months) area-averaged observations over the 15 km × 15 km First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) area. This approach proved to be very beneficial to understanding the performance and limitations of different land surface models. These four surface models, embodying different complexities of the evaporation/hydrology treatment, included the traditional simple bucket model, the simple water balance (SWB) model, the Oregon State University (OSU) model, and the simplified Simple Biosphere (SSiB) model. The bucket model overestimated the evaporation during wet periods, and this resulted in unrealistically large negative sensible heat fluxes. The SWB model, despite its simple evaporation formulation, simulated well the evaporation during wet periods, but it tended to underestimate the evaporation during dry periods. Overall, the OSU model ably simulated the observed seasonal and diurnal variation in evaporation, soil moisture, sensible heat flux, and surface skin temperature. The more complex SSiB model performed similarly to the OSU model. A range of sensitivity experiments showed that some complexity in the canopy resistance scheme is important in reducing both the overestimation of evaporation during wet periods and underestimation during dry periods. Properly parameterizing not only the effect of soil moisture stress but also other canopy resistance factors, such as the vapor pressure deficit stress, is critical for canopy resistance evaluation. An overly simple canopy resistance that includes only soil moisture stress is unable to simulate observed surface evaporation during dry periods. Given a modestly comprehensive time-dependent canopy resistance treatment, a rather simple surface model such as the OSU model can provide good area-averaged surface heat fluxes for mesoscale atmospheric models.

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Modeling of land surface evaporation by four schemes and comparison with FIFE observations

Large-scale conversion of tropical forests into pastures or annual crops could lead to changes in the climate. We have used a coupled numerical model of the global atmosphere and biosphere (Center for Ocean-Land- Atmosphere GCM) to assess the effects of Amazonian deforestation on the regional and global climate. We found that when the Amazonian tropical forests were replaced by degraded grass (pasture) in the model, there was a significant increase in the mean surface temperature (about 2.5°C) and a decrease in the annual evapo-transpiration (30% reduction), precipitation (25% reduction), and runoff (20% reduction) in the region. The differences between the two simulations were greatest during the dry season. The deforested case was associated with larger diurnal fluctuations of surface temperature and vapor pressure deficit; such effects have been observed in existing deforested arms in Amazonia. The calculated reduction in precipitation was larger than the calculated decrease in evapotranspirat...

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Amazonian Deforestation and Regional Climate Change

An overview of the commonly applied evapotranspiration (ET) models using remotely sensed data is given to provide insight into the estimation of ET on a regional scale from satellite data. Generally, these models vary greatly in inputs, main assumptions and accuracy of results, etc. Besides the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance models, must rely to a certain degree on ground-based auxiliary measurements in order to derive the turbulent heat fluxes on a regional scale. We discuss the main inputs, assumptions, theories, advantages and drawbacks of each model. Moreover, approaches to the extrapolation of instantaneous ET to the daily values are also briefly presented. In the final part, both associated problems and future trends regarding these remotely sensed ET models were analyzed to objectively show the limitations and promising aspects of the estimation of regional ET based on remotely sensed data and ground-based measurements.

https://www.mdpi.com/1424-8220/9/5/3801/pdf

A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data

Components of the Simple Biosphere Model (SiB) of Sellers et al. (1986) were used to generate global monthly fields of surface albedo (0.4-4.0 microns), roughness length and minimum surface (stomatal) resistance. SiB consists of three submodels which describe the roles of radiative transfer, turbulent transfer and surface resistance in determining the energy balance of the vegetated land surface. These three submodels were detached from SiB and used on the SiB parameter set (total and green leaf area index, leaf angle orientation, canopy dimensions, etc.) to calculate global monthly fields of albedo, roughness length and minimum stomatal resistance at 1 x 1 deg resolution. Time series of various parameters are also displayed for each vegetation type for specified grid points. The SiB results compare reasonably well with appropriate measurements obtained from the literature and have the additional merit of being mutually consistent; the three submodels use many common parameters, which ensures that, for each grid area, the calculated surface properties are closely interrelated as is the case in nature. The derived fields provide a check on the operation of the submodels and the correctness of the parameter set. They can also be used as prescribed fields for GCMs that do not have biophysically based land surface parameterizations.

A Global Climatology of Albedo, Roughness Length and Stomatal Resistance for Atmospheric General Circulation Models as Represented by the Simple Biosphere Model (SiB)

One-dimensional, sparse-crop interaction theory is reformulated to allow calculation of the canopy resistance from measurements of foliage temperature. A submodel is introduced to describe eddy diffusion within the canopy which provides a simple, empirical simulation of the reported behavior obtained from a second-order closure model. The sensitivity of the calculated canopy resistance to the parameters and formulas assumed in the model is investigated. The calculation is shown to exhibit a significant but acceptable sensitivity to extreme changes in canopy aerodynamics, and to changes in the surface resistance of the substrate beneath the canopy at high and intermediate values of leaf area index. In very sparse crops changes in the surface resistance of the substrate are shown to contaminate the calculated canopy resistance, tending to amplify the apparent response to changes in water availability. The theory is developed to allow the use of a measurement of substrate temperature as an option to mitigate this contamination.

The theoretical relationship between foliage temperature and canopy resistance in sparse crops

A bare-soil surface resistance parameter significantly improved the fit of a numerical model of heat and moisture flow in soils to 3 days of field measurements. The resistance removed a positive bias from the model estimates of daily cumulative evaporation on days with minimum surface soil moisture

A resistance parameter for bare-soil evaporation models

Useful quantitative information about soil properties may be obtained by calibrating energy and moisture balance models with remotely sensed data. In this study, a soil physics model solves heat and moisture flux equations in the soil profile and is driven by the surface energy balance. Model-generated surface temperature and soil moisture and temperature profiles are then used in a microwave emission model to predict the soil brightness temperature. The model hydraulic parameters are varied until the predicted temperatures agree with the remotely sensed measurements. Using this method, values were estimated for hydraulic conductivity, matric potential and soil moisture at saturation, and a soil texture parameter. The conductivity agreed with values measured with an infiltration ring and the other parameters agreed with values in the literature.

Estimating Soil Hydraulic Parameters Using Passive Microwave Data

A two-dimensional model of water flow in a hillslope which has been implemented on the massively parallel processor is described. Flow in the soil both in the saturated and unsaturated zones, evaporation and overland flow are modeled, and the rainfall rates are allowed to vary spatially. Previous models of this type have always been very limited computationally. This model takes less than a minute to model all the components of the hillslope water flow for a day. The model can be used in sensitivity studies to specify which measurements should be taken and how accurate they should be to describe such flows for environmental studies. >

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Estimating water flow through a hillslope using the massively parallel processor

One important part of the global hydrological system is a catchment, which separates rainfall into evaporation, overland flow, and infiltration. For a heavy rain, infiltration excess reaches the stream first as overland flow. Part of the infiltrated water may then flow rapidly below the surface to reemerge downslope or enter the stream. This is usually referred to as saturated subsurface flow. The rest reaches the unsaturated zone. The flow there is vertical and horizontal, and the latter component may eventually contribute to the stream flow. Another component that can contribute to the stream flow is horizontal flow in a perched water table above the bedrock. These processes are depicted schematically in Figure 6.1.

Robert J. Gurney

Papers

The theoretical relationship between foliage temperature and canopy resistance in sparse crops

A resistance parameter for bare-soil evaporation models

Estimating Soil Hydraulic Parameters Using Passive Microwave Data

Estimating water flow through a hillslope using the massively parallel processor

A Two-Dimensional Model of the Hydrological Response of a Hillslope