The Effect of Soil and Vegetation Parameters in the ECMWF Land Surface Scheme

Abstract

Numerical Weather Prediction (NWP) and climate models are sensitive to evapotranspiration at the land surface. This sensitivity requires the prediction of realistic surface moisture and heat fluxes by land surface models that provide the lower boundary condition for the atmospheric models. This paper compares simulations of a stand-alone version of the European Centre for Medium-Range Weather Forecasts (ECMWF) land surface scheme, or the Viterbo and Beljaars scheme (VB95), with various soil and vegetation parameter sets against soil moisture observations across the Murrumbidgee River catchment in southeast Australia. The study is, in part, motivated by the adoption of VB95 as the operational land surface scheme by the Australian Bureau of Meteorology in 1999.VB95 can model the temporal fluctuations in soil moisture, and therefore the moisture fluxes, fairly realistically. The monthly model latent heat flux is also fairly insensitive to soil or vegetation parameters. The VB95 soil moisture is sensitive to the soil and, to a lesser degree, the vegetation parameters. The model exhibits a significant (generally wet) bias in the absolute soil moisture that varies spatially. The use of the best Australia-wide available soils and vegetation information did not improve VB95 simulations consistently, compared with the original model parameters. Comparisons of model and observed soil moistures revealed that more realistic soil parameters are needed to reduce the model soil moisture bias. Given currently available continent-wide soils parameters, any initialization of soil moisture with observed values would likely result in significant flux errors. The soil moisture bias could be largely eliminated by using soil parameters that were derived directly from the actual soil moisture observations. Such parameters, however, are only available at very few point locations.

The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements

“…The OzNet network is managed by the University of Melbourne. Datasets from the OzNet have been extensively used for satellite product validation (Draper et al, 2009;Liu et al, 2011;Parinussa et al, 2011) and the evaluation of land surface models (Richter et al, 2004).…”

Retrieval of an Available Water-Based Soil Moisture Proxy from Thermal Infrared Remote Sensing. Part I: Methodology and Validation

“…Although NWP has improved since the implementation of LSMs, the overall performance of a forecast is still highly dependent on the initialization of soil and vegetation variables, such as soil moisture, fraction of green vegetation cover ( f c ), and leaf area index (LAI; Wetzel and Chang 1987;van den Hurk et al 1997;Crawford et al 2001;Kurkowski et al 2003;Richter et al 2004). These variables are not readily or easily observed on the scales needed to initialize NWP models, and therefore such models often rely on parameterized routines to provide a representation of the current land surface state.…”

Parameter Sensitivity in LSMs: An Analysis Using Stochastic Soil Moisture Models and ELDAS Soil Parameters

“…Also, the exact magnitude of this effect is uncertain. Some studies report a high sensitivity of both soil moisture and evapotranspiration to soil characteristics, such as the water-holding capacity or other soil hydraulic properties (e.g., Soet et al 2000;Seneviratne et al 2006b), while others reported mainly an effect on soil moisture (Richter et al 2004;Braun and Schä dler 2005;Kato et al 2007). The sensitivity of a LSM to its parameters also depends on the climate conditions (e.g., Pitman 1994;Bastidas et al 1999;Soet et al 2000;Liang and Guo 2003;Kahan et al 2006).…”