@article { liu2003,
     Journal = {Geophysical Research Letters},
     Year = {2003},
     Title = {Use of a two-mode soil pore size distribution to estimate soil water transport in a land surface model},
     Author = {Liu, Q and Dickinson, RE},
     Keywords = {Hydraulic Conductivity; },
     Abstract = {Hydraulic properties determine the soil water content and its transport in the soil. They are provided in most current climate models as empirical formulas by functions of the soil texture. Such is not realistic if the soil contains a substantial amount of macropores. A two-mode soil pore size distribution is incorporated into a land surface model to provide more accurate estimation of hydraulic properties of well-aggregated soils. The pore-size distribution for soils with heterogeneous pore systems is regarded as a linear combination of two simple (uni-mode) distributions, thus the macropores can be isolated as an component of the size distribution. The matric potential and the unsaturated hydraulic conductivity are derived from this distribution. Using an observational dataset at a tropical forest site with aggregated soils, the treatment is found to significantly improve the simulation of its soil moisture and surface water fluxes.},
     Volume = {30},
     Issue = {6},
     Month = {Mar}
}

@article { wu2002,
     Journal = {Journal Of Geophysical Research-Atmospheres},
     Year = {2002},
     Title = {A case study for land model evaluation: Simulation of soil moisture amplitude damping and phase shift},
     Author = {Wu, WR and Geller, MA and Dickinson, RE},
     Keywords = {ATMOSPHERE TRANSFER SCHEME; SPATIALLY-VARIABLE WATER; ENERGY-BALANCE PROCESSES; STOMATAL-RESISTANCE; SURFACE PROCESSES; FIELD EXPERIMENT; FIFE DATA; PART II; CLIMATE; RAINFALL; soil moisture, phase shift, amplitude damping, land surface model, First International Satellite Land Surface Climatological Project Field Experiment (FIFE), model validation},
     Abstract = {[1] Observations have described soil moisture profile variability in terms of phase shift, fluctuation damping, and persistence increasing with soil depth [Wu et al., 2002]. This variability as a function of soil depth couples to climate variability. Whether or not land models can reproduce this variability should be a good test of their parameterizations in soil hydrology both physically and numerically. A widely used multilayer land surface model was applied to simulate the soil moisture profile variability documented from observations to explore the sensitivity to various parameters and to evaluate the model performances through the detailed analysis of a case study. Sensitivity experiments assumed changes of (1) the initial soil moisture field; (2) the root sink term; (3) the soil texture; and (4) the atmospheric forcing at upper boundary. Their impacts on the soil moisture profile phase shift, amplitude damping, and corresponding evapotranspiration were examined. The key land surface prognostic variables, i.e., soil moisture and evapotranspiration, were evaluated against observations prior to the sensitivity integrations. All the factors that affected the soil moisture profile variability of amplitude damping and phase shift also influenced the amplitude and phase of evapotranspiration, suggesting that the simulation of soil moisture profile variability might be more important in the context of timescales than the soil wetness field itself.},
     Volume = {107},
     Issue = {D24},
     Month = {Dec}
}

@article { bonan2002,
     Journal = {Journal Of Climate},
     Year = {2002},
     Title = {The land surface climatology of the community land model coupled to the NCAR community climate model},
     Author = {Bonan, GB and Oleson, KW and Vertenstein, M and Levis, S and Zeng, XB and Dai, YJ and Dickinson, RE and Yang, ZL},
     Keywords = {Boreal Forest Ecosystems; Leaf-Area Index; Km Avhrr Data; Air-Temperature; Spatial Variability; United-States; Carbon-Dioxide; Energy Budget; Arctic Tundra; Snow Cover; },
     Abstract = {The land surface parameterization used with the community climate model (CCM3) and the climate system model (CSM1), the National Center for Atmospheric Research land surface model (NCAR LSM1), has been modified as part of the development of the next version of these climate models. This new model is known as the community land model (CLM2). In CLM2, the surface is represented by five primary subgrid land cover types (glacier, lake, wetland, urban, vegetated) in each grid cell. The vegetated portion of a grid cell is further divided into patches of up to 4 of 16 plant functional types, each with its own leaf and stem area index and canopy height. The relative area of each subgrid unit, the plant functional type, and leaf area index are obtained from 1-km satellite data. The soil texture dataset allows vertical profiles of sand and clay. Most of the physical parameterizations in the model were also updated. Major model differences include: 10 layers for soil temperature and soil water with explicit treatment of liquid water and ice; a multilayer snowpack; runoff based on the TOPMODEL concept; new formulation of ground and vegetation fluxes; and vertical root profiles from a global synthesis of ecological studies. Simulations with CCM3 show significant improvements in surface air temperature, snow cover, and runoff for CLM2 compared to LSM1. CLM2 generally warms surface air temperature in all seasons compared to LSM1, reducing or eliminating many cold biases. Annual precipitation over land is reduced from 2.35 mm day(-1) in LSM1 to 2.14 mm day(-1) in CLM2. The hydrologic cycle is also different. Transpiration and ground evaporation are reduced. Leaves and stems evaporate more intercepted water annually in CLM2 than LSM1. Global runoff from land increases from 0.75 mm day(-1) in LSM1 to 0.84 mm day(-1) in CLM2. The annual cycle of runoff is greatly improved in CLM2, especially in arctic and boreal regions where the model has low runoff in cold seasons when the soil is frozen and high runoff during the snowmelt season. Most of the differences between CLM2 and LSM1 are attributed to particular parameterizations rather than to different surface datasets. Important processes include: multilayer snow, frozen water, interception, soil water limitation to latent heat, and higher aerodynamic resistances to heat exchange from ground.},
     Pages = {3123--3149},
     Volume = {15},
     Issue = {22},
     Month = {Nov}
}

@article { beringer2001,
     Journal = {Journal Of Climate},
     Year = {2001},
     Title = {The representation of arctic soils in the land surface model: The importance of mosses},
     Author = {Beringer, J and Lynch, AH and Chapin, FS and Mack, M and Bonan, GB},
     Keywords = {Atmospheric Co2; Tundra Ecosystems; Carbon-Dioxide; Boreal Forests; Climate-Change; Energy Budget; Active Layer; Alaska; Sink; Temperature; },
     Abstract = {Mosses dominate the surface cover in high northern latitudes and have the potential to play a key role in modifying the thermal and hydrologic regime of Arctic soils. These modifications in turn feed back to influence surface energy exchanges and hence may affect regional climate. However, mosses are poorly represented in models of the land surface. In this study the NCAR Land Surface Model (LSM) was modified in two ways. First, additional soil texture types including mosses and lichens were added to more realistically represent northern soils. Second, the LSM was also modified so that a different soil texture type could be specified for each layer. Several experiments were performed using climate data from an Arctic tundra site in 1995. The model was run for a homogeneous loam soil column and then also for columns that included moss, lichen, peat, and sand. The addition of a surface layer of moss underlain by peat and loam had a substantial impact on modeled surface processes. First, moss acted as an insulative layer producing cooler summer temperatures (6.9 degreesC lower at 0.5 m) and warmer winter temperatures (2.3 degreesC higher at 0.5 m) when compared with a homogenous loam soil column. Second, a soil column with a moss surface had a greater surface infiltration, leading to greater storage of soil moisture in lower layers when compared with a homogeneous loam column. Last, moss modulated the surface energy exchanges by decreasing soil heat flux (57% in July) and increasing turbulent fluxes of heat (67% in July) and moisture (15% in July). Mosses were also more effective contributors to total latent heating than was a bare loam surface. These results suggest that the addition of moss and the ability to prescribe different soil textures for different soil layers result in a more plausible distribution of heat and water within the column and that these modifications should be incorporated into regional and global climate models.},
     Pages = {3324--3335},
     Volume = {14},
     Issue = {15}
}

@article { chen2001,
     Journal = {Monthly Weather Review},
     Year = {2001},
     Title = {Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity},
     Author = {Chen, F and Dudhia, J},
     Keywords = {General-Circulation Models; Numerical Weather Prediction; Atmospheric Boundary-Layer; Soil-Moisture; Parameterization Schemes; United-States; Mesoscale Circulations; River Basin; Heat-Flux; Climate; },
     Abstract = {This paper addresses and documents a number of issues related to the implementation of an advanced land surface-hydrology model in the Penn State-NCAR fifth-generation Mesoscale Model (MM5). The concept adopted here is that the land surface model should be able to provide not only reasonable diurnal variations of surface heat fluxes as surface boundary conditions for coupled models, but also correct seasonal evolutions of soil moisture in the context of a long-term data assimilation system. In a similar way to that in which the modified Oregon State University land surface model (LSM) has been used in the NCEP global and regional forecast models, it is implemented in MM5 to facilitate the initialization of soil moisture. Also, 1-km resolution vegetation and soil texture maps are introduced in the coupled MM5-LSM system to help identify vegetation/water/ soil characteristics at fine scales and capture the feedback of these land surface forcings. A monthly varying climatological 0.15 degrees x 0.15 degrees green vegetation fraction is utilized to represent the annual control of vegetation on the surface evaporation. Specification of various vegetation and soil parameters is discussed, and the available water capacity in the LSM is extended to account for subgrid-scale heterogeneity. The coupling of the LSM to MM5 is also sensitive to the treatment of the surface layer, especially the calculation of the roughness length for heat/moisture. Including the effect of the molecular sublayer can improve the simulation of surface heat flux. It is shown that the soil thermal and hydraulic conductivities and the surface energy balance are very sensitive to soil moisture changes. Hence, it is necessary to establish an appropriate soil moisture data assimilation system to improve the soil moisture initialization at fine scales.},
     Pages = {569--585},
     Volume = {129},
     Issue = {4}
}

@article { delage1999,
     Journal = {Atmosphere-Ocean},
     Year = {1999},
     Title = {Aggregation of parameters for the land surface model CLASS},
     Author = {Delage, Y and Wen, L and Belanger, JM},
     Keywords = {Effective Roughness Lengths; General-Circulation Models; Atmospheric Models; Meteorological Models; Heat-Transfer; Scale; Heterogeneity; Stability; Scheme; Fluxes; },
     Abstract = {Land surface schemes are used in climate and weather forecasting models at various resolutions requiring the use of effective or aggregated parameters to adequately represent each grid square. In this study we investigate the rules for aggregating the surface parameters for the Canadian Land Surface Scheme (CLASS). The method consists of running a one-dimensional version of CLASS over a period of 105 days in summer using meteorological data observed at an agricultural site near Quebec City. The aggregation of parameters is tested by successively running the model with two homogeneous values (usually a small one and a large one) of a chosen parameter and then with a mean or aggregated value of that parameter; the results of the latter run are then compared with the area-averaged results of the two homogeneous runs. Vegetation coverage, rooting depth, soil texture and roughness lengths are the input parameters thus tested. Heterogeneity of soil moisture content due to uneven distribution of precipitation is also discussed. The results indicate that the sub-areas of CLASS must have their own soil variables, that roots must occcupy full soil layers and not part of a layer and that the aggregating rule for the roughness lengths (z(o) for momentum and z(ot) for heat and moisture) should be changed from the current logarithmic averages to the blending height method for z(o) and to a new formula involving both roughness lengths for z(ot).(.) The surface-layer scheme in CLASS was found inadequate and replaced. Results for soil texture aggregation are not as clear; it seems difficult to obtain simultaneously a good averaging of atmospheric energy fluxes and a good averaging of soil moisture contents, runoff and drainage. Horizontal variability of soil moisture due to uneven distribution of rainfall generates an overestimate of evapotranspiration and an underestimate of runoff in an aggregated model lacking this effect. Preliminary results indicate that, in order to effectively parametrize this effect in CLASS, both surface pending capacity and ground infiltration rate must be reduced over the grid square when convective precipitation occurs.},
     Pages = {157--178},
     Volume = {37},
     Issue = {2},
     Month = {Jun}
}

@article { bosilovich1995,
     Journal = {Boundary-Layer Meteorology},
     Year = {1995},
     Title = {Formulation And Verification Of A Land-Surface Parameterization For Atmospheric Models},
     Author = {Bosilovich, MG and Sun, WY},
     Keywords = {Bare-Soil Surfaces; Biosphere Model; Prairie Grassland; Diurnal-Variation; Covered Surfaces; Moisture Fluxes; Evaporation; Fife; Layer; Scale; },
     Abstract = {The need for a well-defined lower boundary condition for atmospheric numerical models is well documented. This paper describes the formulation of a land surface parameterization, which will be used in atmospheric boundary-layer and mesoscale numerical models. The land surface model has three soil layers for the prediction of soil moisture and soil temperature. Model soil properties depend on soil texture and moisture content. A homogeneous distribution of vegetation is also included, so that transpiration may be included, as well as the interception of precipitation by vegetation elements. The simulated vegetation also affects the mean surface albedo and roughness characteristics.First ISLSCP Field Experiment (FIFE) data are used to verify the model. Three cases during the growing season were chosen, each case having different amounts of vegetation cover. ''Stand alone'' simulations, where observations of atmospheric and radiation variables are input to the land surface model, were performed. These simulations show that the model is able to reproduce observed surface energy budgets and surface temperatures reasonably well. The RMS differences between modeled and obsered turbulent fluxes of heat and moisture are quite comparable to those reported by more detailed land surface models.},
     Pages = {321--341},
     Volume = {73},
     Issue = {4},
     Month = {Mar}
}

