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Introduction

A correct representation of the soil water buffering in land surface schemes used for weather and climate prediction is essential to accurately simulate surface water fluxes both towards the atmosphere and rivers (van den Hurk et al., 2005; Hirschi et al., 2006a). Moreover the energy repartition at the surface is largely driven by the soil moisture which influences directly the Bowen ratio.

The coupling between the land surface and the atmosphere is an essential step, since Koster et al. (2004) indicated a strong inter-model variability in coupling between soil moisture and precipitation over large continental areas, generalizing the studies of Beljaars et al. (1996).

HTESSEL

The Tiled ECMWF Scheme for Surface Exchanges over Land (TESSEL) is used operationally in the Integrated Forecast System (IFS) for describing the evolution of soil, vegetation and snow over the continents at diverse spatial resolutions.

A revised land surface hydrology (HTESSEL) was introduced in the ECMWF operational model in 2007, to address shortcomings of the land surface scheme, specifically the lack of surface runoff and the choice of a global uniform soil texture.

Figure 1: Schematic representation of the structure of (a) TESSEL land-surface scheme and (b) spatial structure added in HTESSEL (for a given precipitation P1=P2 the scheme distributes the water as surface runoff and drainage with functional dependencies on orography and soil texture respectively).

The TESSEL scheme (Tiled ECMWF Scheme for Surface Exchanges over Land) is shown schematically in Figure 1a. Up to six tiles are present over land (bare ground, low and high vegetation, intercepted water, shaded and exposed snow) and 2 over water (open and frozen water) with separate energy and water balances.

The vertical discretization considers a four-layer soil that can be covered by a single layer of snow. The depths of the soil layers are in an approximate geometric relation, as suggested in Deardorff (1978). Warrilow et al. (1986) have shown that four layers provide a reasonable compromise between computational cost and the ability to represent all timescales between one day and a year. The soil heat budget follows a Fourier diffusion law, modified to take into account soil water freezing/melting according to Viterbo et al. (1999). The energy equation is solved with a net ground heat flux as the top boundary condition and a zero-flux at the bottom. An interception layer accumulates precipitation until it is saturated, and the remaining precipitation (throughfall) is partitioned between surface runoff and infiltration. Subsurface water fluxes are determined by Darcy’s law, used in a soil water equation solved with a four-layer discretization shared with the heat budget equation. The top boundary condition is infiltration plus surface evaporation, free drainage is assumed at the bottom and each layer has an additional sink of water in the form of root extraction over vegetated areas.

In each grid box two vegetation types are present: a high and a low vegetation type. An external climate database is used to obtain the vegetation characteristics. The data provides for each pixel a biome classification based on the Biosphere-Atmosphere Transfer Scheme (BATS) model (Dickinson et al., 1993), and four parameters have been derived for each grid box: dominant vegetation type, TH and TL, and the area fraction, AH and AL, for each of the high- and low-vegetation components, respectively.

The HTESSEL scheme includes the following revisions to the soil hydrology: (i) a spatially varying soil type replacing the single loamy soil, (ii) the Van Genuchten (VG) formulation of soil hydraulic properties replacing the Clapp and Hornberger (CH) scheme, and (iii) the surface runoff generation changing according to a variable infiltration capacity based on soil type and local topography.

In Figure 1b the HTESSEL changes are illustrated: in two adjacent model grid-points with the same land surface conditions and receiving an equal amount of precipitation the surface runoff will be different and proportional to the terrain complexity while the soil water drainage will depend on the soil texture class.

References

G.Balsamo, P.Viterbo, A.Beljaars, B.van den Hurk, M.Hirschi, A.K.Betts, K.Scipal, 2009, A revised hydrology for the ECMWF model, J. Hydro.Met., https://doi.org/10.1175/2008JHM1068.1.

(and references therein)

 


 

 

 


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