Modeling Soil Moisture and Surface Flux Variability with an Untuned Land Surface Scheme: A Case Study from the Southern Great Plains 1997 Hydrology Experiment

Karen I Mohr,Aaron Boone,James S Famiglietti,Patrick J Starks

doi:10.1175/1525-7541(2000)001<0154:msmasf>2.0.co;2

Abstract

The Parameterization for Land‐Atmosphere‐Cloud Exchange (PLACE), a typical surface‐vegetation‐atmosphere transfer (SVAT) parameterization, was used in a case study of a 2500 km 2 area in southwestern Oklahoma for 9‐16 July 1997. The research objective was to assess PLACE’s simulation of the spatial variability and temporal evolution of soil moisture and heat fluxes without optimization for this case study. Understanding PLACE’s performance under these conditions may provide perspective on results from more complex coupled land‐atmosphere simulations involving similar land surface schemes in data-poor environments. Model simulations were initialized with simple initial soil moisture and temperature profiles tied to soil type and forced by standard meteorological observations. The model equations and parameters were not adjusted or tuned to improve results. For surface soil moisture, 5- and 10-cm soil temperature, and surface fluxes, the most accurate simulation (5% error for soil moisture and 2 K for 5- and 10-cm soil temperature) occurred during the 48 h following heavy rainfall on 11 and 15 July. The spatial pattern of simulated soil moisture was controlled more strongly by soil texture than was observed soil moisture, and the error was correlated with rainfall. The simplifications of the subsurface soil moisture, soil texture, and vegetation cover initialization schemes and the uncertainty in the rainfall data (.10%) could account for differences between modeled and observed surface fluxes that are on the order of 100 W m22 and differences in soil moisture that are greater than 5%. It also is likely that the soil thermal conductivity scheme in PLACE damped PLACE’s response to atmospheric demand after 13 July, resulting in reduced evapotranspiration and warmer but slower-drying soils. Under dry conditions, the authors expect that SVATs such as PLACE that use a similar simple initialization also would demonstrate a strong soil texture control on soil moisture and surface fluxes and limited spatial variability.

Highlights

Recognition of the importance of land surface processes in the prediction of weather and climate has lead to efforts to incorporate improved land surface parameterizations into atmospheric models to represent land– atmosphere interaction (e.g., Avissar and Pielke 1989; Noilhan and Planton 1989; Dickinson et al 1993; Fa-᭧ 2000 American Meteorological Society MOHR ET AL.al. 1987), Groves (1989), Mahfouf (1991), and Capehart and Carlson (1994) have proposed the technique of using the water and energy budget of a surface–vegetation–atmosphere transfer model (SVAT), driven by standard meteorological observations, to predict soil moisture
A simple simulation initialization scheme is used, advantage is taken of the wealth of remotely sensed soil moisture imagery and supporting data from the Southern Great Plains 1997 (SGP97) Hydrology Experiment (Jackson 1997) for validation of simulation results
The soil textures are plotted over the soil moisture maps for 14 July. These overlays reveal a noticeable control of soil texture over soil moisture in both the model-derived and Electronically Scanned Thinned Array Radiometer (ESTAR) maps, the soil texture control is stronger in the modelderived map

Summary

Introduction

Recognition of the importance of land surface processes in the prediction of weather and climate has lead to efforts to incorporate improved land surface parameterizations into atmospheric models to represent land– atmosphere interaction (e.g., Avissar and Pielke 1989; Noilhan and Planton 1989; Dickinson et al 1993; Fa-᭧ 2000 American Meteorological Society MOHR ET AL.al. 1987), Groves (1989), Mahfouf (1991), and Capehart and Carlson (1994) have proposed the technique of using the water and energy budget of a surface–vegetation–atmosphere transfer model (SVAT), driven by standard meteorological observations, to predict soil moisture. Four-dimensional data assimilation of surface meteorological data into land surface models has been suggested as a method to retrieve soil moisture by simulation (McNider et al 1994; Houser et al 1998). It is worth exploring in detail how a currently available and typical SVAT scheme might perform ‘‘as is’’ (i.e., untuned) in a data-poor environment. We seek to understand how well PLACE, a typical SVAT, can simulate the spatial variability and temporal evolution of soil moisture and surface fluxes under conditions for which it has not been optimized. The current case study takes place 9–16 July (192 h) and encompasses several wetting and drying cycles to observe the performance of PLACE under both conditions and its ability to make a transition from one to the other

Results

Discussion

Conclusion