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Adriaan J. Teuling, Remko Uijlenhoet, Bart van den Hurk, and Sonia I. Seneviratne

1. Introduction The dynamic role of the land surface in the climate system is nowadays widely recognized. Fluxes of latent heat from the land surface into the atmosphere transport large amounts of energy and water and limit direct heating of the lower atmosphere. Their magnitude, however, strongly depends on the soil moisture content of the soil. Model studies have shown that without soil moisture interacting freely with the atmosphere, warm season precipitation and temperature variability over

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Dongryeol Ryu, Wade T. Crow, Xiwu Zhan, and Thomas J. Jackson

mean of the perturbed state variables are compared with unperturbed state variables. However, owing to nonlinear processes imbedded in land surface models, it is unavoidable that ensemble perturbation using Gaussian noise will lead to biased model forecasts ( De Lannoy et al. 2006 ). As a consequence, the mere ensembling of the model during implementation of the EnKF can introduce systematic error into its flux and state predictions. Examples of nonlinear model processes potentially responsible for

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Damian J. Barrett and Luigi J. Renzullo

approaches to hydrometeorological problems include better estimation of initial soil moisture and temperature in mesoscale climatological models ( Jones et al. 2004 ; Huang et al. 2008 ), improved energy partitioning between latent and sensible heat fluxes ( Pipunic et al. 2008 ), and a concomitant higher skill in quantitative precipitation forecasts ( Koster et al. 2000 ). For example, it has been shown that updating soil moisture in a numerical weather model using passive microwave observations at

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Yongqiang Zhang, Francis H. S. Chiew, Lu Zhang, and Hongxia Li

capacity of air, R n is the net radiation, G is the soil heat flux (assumed to be zero here), G a is the aerodynamic conductance, and G s is the surface conductance. Leuning et al. (2008) developed an algebraic, biophysical six-parameter surface conductance model: and where ɛ is Δ/ γ , G i = γ ( R n − G )/( ρ a C p D ) is the isothermal conductance ( Monteith and Unsworth 1990 ), G c is canopy conductance, τ = exp(− k A LAI) is the fraction of available energy

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Gabriëlle J. M. De Lannoy, Paul R. Houser, Niko E. C. Verhoest, and Valentijn R. N. Pauwels

moisture profiles are estimated with the CLM2.0 ( Dai et al. 2003 ) at 36 locations ( Fig. 1 ) in a 21-ha corn field in Beltsville, Maryland, where the OPE 3 experiment is conducted ( Gish et al. 2002 ; De Lannoy et al. 2006b ). The model simulates land surface processes by calculating hourly vertical water and heat fluxes and states for each profile without interaction between profiles—that is, the linearized system matrix is block diagonal. To limit the computational costs, only the 10-layer soil

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Dingchen Hou, Kenneth Mitchell, Zoltan Toth, Dag Lohmann, and Helin Wei

-1694(02)00106-3 Lohmann, D. , and Coauthors , 2004 : Streamflow and water balance intercomparisons of four land surface models in the North American Land Data Assimilation System project. J. Geophys. Res. , 109 , D07S91 . doi:10.1029/2003JD003517 . Milly, P. C. D. , and Dunne K. A. , 2002a : Macroscale water fluxes. 1. Quantifying errors in the estimation of basin mean precipitation. Water Resour. Res. , 38 , 1205 . doi:10.1029/2001WR000759 . Milly, P. C. D. , and Dunne K. A. , 2002b

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Vahid Naeimi, Zoltan Bartalis, and Wolfgang Wagner

. , 28 , 404 – 412 . 10.5589/m02-035 Fontaine, B. , Louvet S. , and Roucou P. , 2007 : Fluctuations in annual cycles and inter-seasonal memory in West Africa: Rainfall, soil moisture and heat fluxes. Theor. Appl. Climatol. , 88 , 57 – 70 . 10.1007/s00704-006-0246-4 Gelsthorpe, A. R. , Schied E. , and Wilson J. J. W. , 2000 : ASCAT—Metop’s advanced scatterometer. ESA Bull. , 102 , 19 – 27 . Naeimi, V. , Kuenzer C. , Hasenauer S. , Bartalis Z. , and Wagner W. , 2007

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J. M. Schuurmans and M. F. P. Bierkens

100 × 100 m outside the study area, within the model boundaries ( Fig. 1a ). The groundwater model is schematized into seven layers. A flux that is of importance for soil moisture and is influenced by the soil moisture conditions is evapotranspiration. Our model uses Makkink ( Bruin 1987 ; Makkink 1957 ; Winter et al. 1995 ) reference evapotranspiration (ET ref ) as input (spatially uniform). The measured ET ref in this study comes from De Bilt. The potential evapotranspiration (ET pot ) is

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