Wenguang Zhao

Modeling of long‐wave and net radiation energy distribution within a homogeneous plant canopy via multiple scattering processes

Received 13 September 2005; revised 20 April 2006; accepted 28 April 2006; published 30 August 2006. [1] This paper presents a newly developed multiple-layer, long-wave radiation scattering model for use in homogeneous vegetation canopies. The model is able to simulate the radiation distribution within and the outgoing radiation above the canopy. This model differs from the shortwave model developed earlier by the authors owing to the complexity introduced by the fact that leaves within and soil below the canopy emit long-wave radiation in accordance with their surface temperature. Combined, the short- and long-wave models are able to simulate net radiation distribution above and within the canopy sublayers and at the soil surface. The model represents multiple scatterings of radiation reflected, transmitted, and emitted from leaf surfaces and penetrating through gaps as infinite series equations, which are reduced analytically to simple forms. In stand-alone mode this model has the limitation that it requires canopy temperature profile data as input in order to simulate outgoing long-wave radiation and net radiation. However, once we or other users couple this model to a turbulent transfer model, canopy temperature profiles will be produced as model output, making this a useful tool for remote sensing data assimilation. The model was tested against measurements collected in a wheat field in 2002. Satisfactory agreement was obtained between the modeled outgoing long-wave radiation above a wheat canopy and observed long-wave radiation measured with an Eppley precision infrared radiometer (PIR), both for daily total values and diurnal variation of 20-min averages. The root-mean-square error (RMSE) of daily total values of outgoing long-wave radiation, with respect to measurements, was only 1.1% of the mean of the measurements. Comparison of the modeled net radiation with two independent measurements produced RMSE values equal to 3.7% of the mean measured daily total net radiation.

Modeling of the short wave radiation distribution in an agroforestry system

In an agroforestry system, short wave radiation distribution under the canopy of the trees is important to the activity of the annual crops growing beneath. A three-dimensional model is proposed to describe the short wave radiation distribution under the tree canopy in an agroforestry system. In the model, the agroforestry system is assumed to be planted in regular arrays and have spherical crowns. The short wave radiation that reaches a prescribed point on the ground is computed as the integration of radiation from all the differential directions of the whole hemisphere. The canopy depth in each differential direction is computed, and the extinction coefficient of the tree canopy is estimated by computer analysis of photograph images of the tree crowns taken by a conventional camera. A major advantage of this method is that the laborious leaf area index (LAI) and leaf inclination measurement can be eliminated. The model is able to predict both the short wave radiation distributions below the canopy of an agroforestry system at a prescribed time and the diurnal variation of the total hemispherical short wave radiation at a prescribed point below the canopy. Comparison of the modeled results with the measured values showed that the proposed model describes the daily patterns of the short wave radiation under the tree canopy quite well for both discontinuous canopy and overlapping canopy and for different shading conditions. The difference between the modeled daily total values of the short wave radiation under the canopy and the measured daily total values is usually less than 5% of the global radiation. Results from sensitivity analyses of the model to crown radius and canopy gap fraction are reported.

A comprehensive analysis of interseasonal and interannual energy and water balance dynamics in semiarid shrubland and forest ecosystems

Accurate estimation of ecosystem-scale land surface energy and water balance has great importance in weather and climate studies. This paper summarizes seasonal and interannual fluctuations of energy and water balance components in two distinctive semiarid ecosystems, sagebrush (SB) and lodgepole pine (LP) in the Snake River basin of Idaho. This study includes 6 years (2011-2016) of eddy covariance (EC) along with modeled estimates. An analysis of the energy balance indicated a higher energy balance ratio (0.88) for SB than for LP (0.86). The inclusion of canopy storage (CS) increased the association between turbulent fluxes and available energy in LP. Green vegetation fraction (GVF) significantly controlled evapotranspiration (ET) and surface energy partitioning when available energy and soil moisture were not limited. Seasonal water balance in the Budyko framework showed severe water-limited conditions in SB (6-9 months) compared to LP (6-7 months). Based on the validated Noah land surface model estimates, direct soil evaporation (ESoil) is the main component of ET (62 to 79%) in SB due to a large proportion of bare soil (60%), whereas at the lodgepole pine site, it was transpiration (ETran, 42-52%). A complementary ratio (CR) analysis on ET and potential ET (PET) showed a strong asymmetric CR in SB, indicating significant advection. Both SG and LP showed strong coupling between soil moisture (SM) and air temperature (Ta). However, a weak coupling was observed in SB when the soil was dry and Ta was high. This weak coupling was due to the presence of net advection. The results presented here have a wider application: to help us understand and predict the survival, productivity, and hydroclimatology of water-limited ecosystems.

Aerodynamic Roughness Length Estimation with Lidar and Imaging Spectroscopy in a Shrub-Dominated Dryland

The aerodynamic roughness length (Z0m) serves an important role in the flux exchange between the land surface and atmosphere. In this study, airborne lidar (ALS), terrestrial lidar (TLS), and imaging spectroscopy data were integrated to develop and test two approaches to estimate Z0m over a shrub dominated dryland study area in south-central Idaho, USA. Sensitivity of the two parameterization methods to estimate Zom was analyzed. The comparison of eddy covariancederived Z0m and remote sensing-derived Z 0m sho1iVed that the accuracy of the estimated Z0m heavily depends on the estimation model and the representation of shrub (e.g., Artemisia tridentata subsp. lryomingensis) height in the models. The geometrical method (RA1994) led to 9 percent (-0.5 cm) and 25% (1.1 cm) errors at site 1 and site 2, respectively, which performed better than the height variability-based method (MR1994) with bias error of 20 percent and 48 percent at site 1 and site 2, respectively. The RA1994 model resulted in a larger range of Zom than the MR1994 method. We also found that the mean, median and 75th percentiles of heights (H75) from ALS provides the best Z 0m estimates in the MR1994 model, while the mean, median, and MAD (Median Absolute Deviation from Median Height), as well as AAD (Mean Absolute Deviation from Mean Height) heights from ALS provides the best Z0m estimates in the RA1994 model. In addition, the fractional cover of shrub and grass, distinguished with ALS and imaging spectroscopy data, provided the opportunity to estimate the frontal area index at the pixel-level to assess the influence of grass and shrub on Z0m estimates in the RA1994 method. Results indicate that grass had little effect on Z 0m in the RA1994 method. The Z0m estimations were tightly coupled with vegetation height and its local variance for the shrubs. Overall, the results demonstrate that the use of height and fractional cover from remote sensing data are promising for estimating Zom• and thus refining land surface models at regional scales in semiarid shrublands. Aihua Li and Nancy F. Glenn are with the Department of Geoscience, Boise State University, 1920 University Drive, Boise ID 83725 (nancyglenn@bosiestate.edu). Jessica J. Mitchell is with the Depa1tment of Geography and Planning, Appalachian State University, Boone NC. Ivlatthew J. Germino is with the US Geological Survey, Forest and Rangeland Ecosystem Science Center, Boise, ID. Joel B. Sankey is with the US Geological Survey, Grand Canyon Monitoring and Research Center, Flagstaff, AZ. Wenguang Zhao and Richard Allen are with Biological Engineering, University of Idaho, Kimberly, ID. PHOTOGRAMMETRk: ENGINEERING & REMOTE SENSING Introduction The roughness of the land surface plays an important role in the flux exchange between the land surface and atmosphere (Sud et aL, 1988; Prueger et al., 2004). Land surface roughness can be characterized by the aerodynamic roughness length (Z0m), which is the height of roughness elements at which the mean wind speed approaches zero given the extrapolation of the logarithmic wind profile (Garratt, 1992; Kaimal and Finnigan, 1994). In dryland ecosystems, such as semiarid shrublands, the spatial distribution of roughness elements and specifically Z0m are key parameters for physical models of aeolian transport and for estimating dust emissions from wind erosion (Prigent et al., 2005; Sankey et al., 2010; Sankey et al., 2013; Nield et al., 2013; Pelletier and Field, 2016) and for land surface models (Dickinson and Henderson-Sellers, 1988; Jasinski and Crago, 1999). Traditionally, Zom is calculated using the Ivlonin-Obukhov similarity theory (MOST) applied to measurements of horizontal V\rind speed profiles (Garratt, 1994; Kustas et al., 1994). Therefore, Z0m can be obtained through observations by an eddy covariance (EC) system which provides meteorological measurements; however, estimating Zom from EC is restricted to a single value in the source area of the EC tower, and thus EC estimates are limited for regional land surface models (Paul-Limoges et al., 2013). To address this issue, studies have used remotely sensed information, such as scatterometer (Prigent et al., 2005) and bi-directional reflectance (Marticorena et al., 2004) data, along with laser altimeter measurements (Menenti and Ritchie, 1994; De Vries et al., 2003, Colin and Faivre, 2010, Weligepolage et al., 2012) for parameterizing Zom over a local or regional scale. Aerodynamic roughness is influenced by the height, geometry, density and pattern of roughness elements which include vegetation and microand macro-topographic features (Garratt, 1992; Lettau, 1969; Raupach, 1992 and 1994; Shaw and Pereira, 1982). Empirical relationships between Zom and measurable characteristics of roughness elements (e.g., vegetation height, normalized difference vegetation index (NDVI), leaf area index (LAI), frontal area index (FAI, A.1)) have been used to parameterize Z0m over a large sale. For example, NDVI and LAI derived from optical remote sensing have been correlated with Zom (Choudhury and Monteith, 1988; Bastiaanssen, 1995; Jia et al., 2003). In some previous studies, Z0m was assumed as a proportion of roughness element height (i.e., Kustas et al., 1989; Garratt, 1992). The three-dimensional (3D) structure of the lands surface and vegetation, as captured by laser altimetry (or light detection and ranging (lidar)) provides a straightforward measure of Photogrammetric Engineering & Remote Sensing Vol. 83, No. 6, June 2017, pp. 415-427. 0099-1112/17/415-427