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Eric F. Wood and Venkataraman Lakshmi

Abstract

The effects of small-scale heterogeneity in land-surface characteristics on the large-scale fluxes of water and energy in the land-atmosphere system have become a central focus of many of the climatology research experiments. The acquisition of high-resolution land-surface data through remote sensing and intensive land-climatology field experiments (like HAPEX and EIFE) has provided data to investigate the interactions between microscale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small-scale heterogeneities and whether “effective” parameters can be used in the macroscale models. To address this question of scaling, three modeling experiments were performed and are reviewed in the paper. The first is concerned with the land-surface hydrology during rain events and between rain events. The second experiment applies the Simple Biosphere Model (SiB) to a heterogeneous domain and the spatial and temporal latent beat flux is analyzed. The third experiment uses thermatic mapper (TM) data to look at the scaling of the normalized vegetation index (NDVI), latent heat flux, and sensible heat flux through either scaling of the TM-derived fields using the TM data or the fields derived from aggregated TM data.

In all three experiments it was found that the surface fluxes and land characteristics can be sealed, and that macroscale models based on elective parameters are sufficient to account for the small-scale heterogeneities investigated. The paper also suggests that the scale at which a macroscale model becomes valid, the representative elementary scale (REA), is on the order 1.5–3 correlation lengths, which for land processes investigated appears to be about 1000–1500 m. At scales less than the REA scale, exact patterns of subgrid heterogeneities are needed for accurate small-scale modeling.

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Toshihisa Matsui, Venkataraman Lakshmi, and Eric E. Small

Abstract

Substantial evolution of Normalized Difference Vegetation Index (NVDI)-derived vegetation cover (Fg) exists in the southwestern United States and Mexico. The intraseasonal and wet-/dry-year fluctuations of Fg are linked to observed precipitation in the North American monsoon system (NAMS). The manner in which the spatial and temporal variability of Fg influences the land–atmosphere energy and moisture fluxes, and associated likelihood of moist convection in the NAMS regions, is examined. For this, the regional climate model (RCM) is employed, with three different Fg boundary conditions to examine the influence of intraseasonal and wet-/dry-year vegetation variability. Results show that a strong link exists between evaporative fraction (EF), surface temperature, and relative humidity in the boundary layer (BL), which is consistent with a positive soil moisture feedback. However, contrary to expectations, higher Fg does not consistently enhance EF across the NAMS region. This is because the low soil moisture values simulated by the land surface model (LSM) yield high canopy resistance values throughout the monsoon season. As a result, the experiment with the lowest Fg yields the greatest EF and precipitation in the NAMS region, and also modulates regional atmospheric circulation that steers the track of tropical cyclones. In conclusion, the simulated influence of vegetation on land–atmosphere exchanges depends strongly on the canopy stress index parameterized in the LSM. Therefore, a reliable dataset, at appropriate scales, is needed to calibrate transpiration schemes and to assess simulated and realistic vegetation–atmosphere interactions in the NAMS region.

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Venkataraman Lakshmi, Eric F. Wood, and Bhaskar J. Choudhury

Abstract

Regional-scale estimation of soil moisture using in situ field observations is not possible due to problems with the representativeness of the sampling and costs. Remotely sensed satellite data are helpful in this regard. Here, the simulations of 19- and 37-GHz vertical and horizontal polarization brightness temperatures and estimation of soil moistures using data from the Special Sensor Microwave/Imager (SSM/I) for 798 0.25° × 0.25° boxes in the southwestern plains region of the United States for the time period between 1 August 1987 and 31 July 1988 are presented. A coupled land-canopy–atmosphere model is used for simulating the brightness temperatures. The land-surface hydrology is modeled using a thin-layer hydrologic model. The canopy scattering is modeled using a radiative transfer model, and the atmospheric attenuation is characterized using an empirical model. The simulated brightness temperatures are compared with those observed by the SSM/I sensor aboard the Defense Metereological Satellite Program satellite. The observed brightness temperatures are used to derive the soil moistures using the canopy radiative transfer and atmospheric attenuation model. The discrepancies between the SSM/I-based estimates and the simulated soil moisture are discussed. The mean monthly soil moistures estimated using the 19-GHz SSM/I brightness temperature data are interpreted along with the mean monthly leaf area index and accumulated rainfall. The soil moistures estimated using the 19-GHz SSM/I data are used in conjunction with the hydrologic model to estimate cumulative monthly evaporation. The results of the simulations hold promise for the utilization of microwave brightness temperatures in hydrologic modeling for soil moisture estimation.

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Enrique R. Vivoni, Hugo A. Gutiérrez-Jurado, Carlos A. Aragón, Luis A. Méndez-Barroso, Alex J. Rinehart, Robert L. Wyckoff, Julio C. Rodríguez, Christopher J. Watts, John D. Bolten, Venkataraman Lakshmi, and Thomas J. Jackson

Abstract

Relatively little is currently known about the spatiotemporal variability of land surface conditions during the North American monsoon, in particular for regions of complex topography. As a result, the role played by land–atmosphere interactions in generating convective rainfall over steep terrain and sustaining monsoon conditions is still poorly understood. In this study, the variation of hydrometeorological conditions along a large-scale topographic transect in northwestern Mexico is described. The transect field experiment consisted of daily sampling at 30 sites selected to represent variations in elevation and ecosystem distribution. Simultaneous soil and atmospheric variables were measured during a 2-week period in early August 2004. Transect observations were supplemented by a network of continuous sampling sites used to analyze the regional hydrometeorological conditions prior to and during the field experiment. Results reveal the strong control exerted by topography on the spatial and temporal variability in soil moisture, with distinct landscape regions experiencing different hydrologic regimes. Reduced variations at the plot and transect scale during a drydown period indicate that homogenization of hydrologic conditions occurred over the landscape. Furthermore, atmospheric variables are clearly linked to surface conditions, indicating that heating and moistening of the boundary layer closely follow spatial and temporal changes in hydrologic properties. Land–atmosphere interactions at the basin scale (∼100 km2), obtained via a technique accounting for topographic variability, further reveal the role played by the land surface in sustaining high atmospheric moisture conditions, with implications toward rainfall generation during the North American monsoon.

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