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Abstract
An experimental study of the dynamics within artificial thermal plumes rising in the boundary layer is presented.
In this third part, measurements just above the heat source and aircraft investigations in the plume aloft are used to reveal the internal structure of the airflow within the buoyant column. Analysis of the pressure perturbation obtained both by direct measurements and as a residual in the mean vertical motion equation for a plume, shows that the vertical pressure gradient accelerates the airflow near the heat source and then reduces the buoyancy in the upper levels. The pressure deficits, attaining maximum values of 1 mb in the core of the lower portion of the plume, are well correlated with large vertical velocities. During light ambient wind conditions, the reduced pressure near the heat source produces a large converging inflow sufficient to cause the lower portion of the plume to go into rotation as a whole. An analysis of the components of the velocity field and momentum fluxes within the column underscores the convergent and divergent characters of the flow, respectively, at the lower and upper portions of the plume. Strong vorticity concentration (∼4 10−2 s−1) is associated with a reduction of entrainment into the column.
Abstract
An experimental study of the dynamics within artificial thermal plumes rising in the boundary layer is presented.
In this third part, measurements just above the heat source and aircraft investigations in the plume aloft are used to reveal the internal structure of the airflow within the buoyant column. Analysis of the pressure perturbation obtained both by direct measurements and as a residual in the mean vertical motion equation for a plume, shows that the vertical pressure gradient accelerates the airflow near the heat source and then reduces the buoyancy in the upper levels. The pressure deficits, attaining maximum values of 1 mb in the core of the lower portion of the plume, are well correlated with large vertical velocities. During light ambient wind conditions, the reduced pressure near the heat source produces a large converging inflow sufficient to cause the lower portion of the plume to go into rotation as a whole. An analysis of the components of the velocity field and momentum fluxes within the column underscores the convergent and divergent characters of the flow, respectively, at the lower and upper portions of the plume. Strong vorticity concentration (∼4 10−2 s−1) is associated with a reduction of entrainment into the column.
Abstract
This paper investigates the problem of aggregation of land surface properties in a large area comparable in size with a model grid box of a GCM. The study is based on 3D numerical results obtained for atmospheric situations encountered during HAPEX-MOBILHY 1986-that is, moderate plant water stress at the beginning of summer. Estimating effective surface properties describing the spatial distribution of the vegetation and the soil texture within the large area under study is proposed as a first guess for accounting for spatial variability. Despite the nonlinear dependence of surface fluxes on both vegetation and soil water content, it is found that the effective surface fluxes computed from effective parameters with a ID column model match the areal-averaged fluxes estimated from 3D mesoscale model results with a relative error less than 10%. On the other hand, fluxes computed with prescribed surface properties associated with the dominant land use of the large domain depart significantly from the averaged fluxes. For the cases examined, the effects of nonlinearity are found to be smaller for the vegetation behavior than for the soil water transfers.
The parameter aggregation method has been tested successfully for a long lime period within the context of a ID GCM grid cell representing the HAPEX-MOBILHY 1986 instrumented area. Given precipitation and solar radiation fluxes, predictions of soil water content and total evaporation for 25 days compare well with aggregated observations within the large area.
Abstract
This paper investigates the problem of aggregation of land surface properties in a large area comparable in size with a model grid box of a GCM. The study is based on 3D numerical results obtained for atmospheric situations encountered during HAPEX-MOBILHY 1986-that is, moderate plant water stress at the beginning of summer. Estimating effective surface properties describing the spatial distribution of the vegetation and the soil texture within the large area under study is proposed as a first guess for accounting for spatial variability. Despite the nonlinear dependence of surface fluxes on both vegetation and soil water content, it is found that the effective surface fluxes computed from effective parameters with a ID column model match the areal-averaged fluxes estimated from 3D mesoscale model results with a relative error less than 10%. On the other hand, fluxes computed with prescribed surface properties associated with the dominant land use of the large domain depart significantly from the averaged fluxes. For the cases examined, the effects of nonlinearity are found to be smaller for the vegetation behavior than for the soil water transfers.
The parameter aggregation method has been tested successfully for a long lime period within the context of a ID GCM grid cell representing the HAPEX-MOBILHY 1986 instrumented area. Given precipitation and solar radiation fluxes, predictions of soil water content and total evaporation for 25 days compare well with aggregated observations within the large area.
Abstract
A parameterization of land surface processes to be included in mesoscale and large-scale meteorological models is presented. The number of parameters has been reduced as much as possible, while attempting to preserve the representation of the physics which controls the energy and water budgets. We distinguish two main classes of parameters. The spatial distribution of primary parameters, i.e., the dominant types of soil and vegetation within each grid cell, can be specified from existing global datasets. The secondary parameters, describing the physical properties of each type of soil and vegetation, can be inferred from measurements or derived from numerical experiments. A single surface temperature is used to represent the surface energy balance of the land/cover system. The soil heat flux is linearly interpolated between its value over bare ground and a value of zero for complete shielding by the vegetation. The ground surface moisture equation includes the effect of gravity and the thermo-hydric coefficients of the equations have been either calculated or calibrated using textural dependent formulations. The calibration has been made using the results of a detailed soil model forced by prescribed atmospheric mean conditions. The results show that the coefficients of the surface soil moisture equation are greatly dependent upon the textural class of the soil, as well as upon its moisture content. The new scheme has been included in a one-dimensional model which allows a complete interaction between the surface and the atmosphere. Several simulations have been performed using data collected during HAPEX-MOBILHY. These first results show the ability of the parameterization to reproduce the components of the surface energy balance over a wide variety of surface conditions.
Abstract
A parameterization of land surface processes to be included in mesoscale and large-scale meteorological models is presented. The number of parameters has been reduced as much as possible, while attempting to preserve the representation of the physics which controls the energy and water budgets. We distinguish two main classes of parameters. The spatial distribution of primary parameters, i.e., the dominant types of soil and vegetation within each grid cell, can be specified from existing global datasets. The secondary parameters, describing the physical properties of each type of soil and vegetation, can be inferred from measurements or derived from numerical experiments. A single surface temperature is used to represent the surface energy balance of the land/cover system. The soil heat flux is linearly interpolated between its value over bare ground and a value of zero for complete shielding by the vegetation. The ground surface moisture equation includes the effect of gravity and the thermo-hydric coefficients of the equations have been either calculated or calibrated using textural dependent formulations. The calibration has been made using the results of a detailed soil model forced by prescribed atmospheric mean conditions. The results show that the coefficients of the surface soil moisture equation are greatly dependent upon the textural class of the soil, as well as upon its moisture content. The new scheme has been included in a one-dimensional model which allows a complete interaction between the surface and the atmosphere. Several simulations have been performed using data collected during HAPEX-MOBILHY. These first results show the ability of the parameterization to reproduce the components of the surface energy balance over a wide variety of surface conditions.
Abstract
Vajious formulations of surface evaporation are tested against in situ data collected over a plot of loamy bare ground. Numerical simulations lasting seven days are compared with observations of near-surface water content and cumulative evaporation.
A comparison of classical bulk aerodynamic formulations shows similar predictions of daytime evaporation while significant differences are exhibited during the night. The so-called “surface moisture availability method” seems to overestimate the nocturnal evaporation flux.
In the context of this dataset, threshold methods strongly underestimate surface evaporation during the whole period of observations. A sensitivity analysis reveals that threshold evaporation (maximum sustainable water flux) is highly sensitive upon the depth of the top soil layer.
Abstract
Vajious formulations of surface evaporation are tested against in situ data collected over a plot of loamy bare ground. Numerical simulations lasting seven days are compared with observations of near-surface water content and cumulative evaporation.
A comparison of classical bulk aerodynamic formulations shows similar predictions of daytime evaporation while significant differences are exhibited during the night. The so-called “surface moisture availability method” seems to overestimate the nocturnal evaporation flux.
In the context of this dataset, threshold methods strongly underestimate surface evaporation during the whole period of observations. A sensitivity analysis reveals that threshold evaporation (maximum sustainable water flux) is highly sensitive upon the depth of the top soil layer.
Abstract
This paper presents a simple parameterization of gravitational drainage for land surface schemes describing soil water transfers according to the force-restore method of Deardorff. A one-year time series of observed soil moisture period from HAPEX-MOBILHY (Hydrological Atmospheric Pilot Experiment-Mobilisation du Bilan Hydrique) 1986 revealed the importance of subsurface drainage during the wintertime period. This physical process is accounted for through a Newtonian restore to field capacity when soil moisture is above it. Simulation of the annual cycle of soil moisture by the land surface scheme ISBA (interactions soil biosphere atmosphere) is in this way greatly improved.
Abstract
This paper presents a simple parameterization of gravitational drainage for land surface schemes describing soil water transfers according to the force-restore method of Deardorff. A one-year time series of observed soil moisture period from HAPEX-MOBILHY (Hydrological Atmospheric Pilot Experiment-Mobilisation du Bilan Hydrique) 1986 revealed the importance of subsurface drainage during the wintertime period. This physical process is accounted for through a Newtonian restore to field capacity when soil moisture is above it. Simulation of the annual cycle of soil moisture by the land surface scheme ISBA (interactions soil biosphere atmosphere) is in this way greatly improved.
Abstract
In this last part, a detailed comparison of the model predictions with all the HAPEX-MOBILHY dataset available within a mesoscale subdomain is carried out. The simulation subdomain encompasses a fraction of a pine forest and of a nearby agricultural area. The predicted surface fields at noon are strongly related to the horizontal inhomogeneities of the vegetation. By comparing the predicted surface energy fluxes with local observations, it is found that the model reproduces a realistic partitioning of energy over the forest and the crops. This results in a good prediction of the deep daytime boundary layer over the forest where sensible heat flux and friction velocity are stronger. The problem of area-averaged fluxes is addressed from a comparison between predicted turbulent quantities and aircraft estimates at three levels within the boundary layer.
Abstract
In this last part, a detailed comparison of the model predictions with all the HAPEX-MOBILHY dataset available within a mesoscale subdomain is carried out. The simulation subdomain encompasses a fraction of a pine forest and of a nearby agricultural area. The predicted surface fields at noon are strongly related to the horizontal inhomogeneities of the vegetation. By comparing the predicted surface energy fluxes with local observations, it is found that the model reproduces a realistic partitioning of energy over the forest and the crops. This results in a good prediction of the deep daytime boundary layer over the forest where sensible heat flux and friction velocity are stronger. The problem of area-averaged fluxes is addressed from a comparison between predicted turbulent quantities and aircraft estimates at three levels within the boundary layer.
Abstract
The bulk soil water content must be estimated accurately for short- and medium-term meteorological modeling. A method is proposed to retrieve the total soil moisture content as well as the field capacity from observed surface parameters such as surface soil moisture or surface temperature. A continuous series of micrometeorological and soil water content measurements was obtained in southwestern France over a fallow site in 1995. In addition, the database includes measurements of the surface temperature and soil moisture profiles within the top 5-cm soil layer. The surface soil moisture measurements are available twice a day during two 30-day intensive observing periods in spring and autumn 1995. Once calibrated, the ISBA (Interactions between Soil, Biosphere, and Atmosphere) surface scheme is able to properly simulate the measured surface variables and the bulk soil moisture. Then an assimilation technique is applied to analyze the field capacity and the total soil water content from the surface data. In particular, it is shown that knowing the atmospheric forcing and the precipitation, four or five estimations of the surface soil moisture spread out over a 15-day period are enough to retrieve the total soil water content by inverting ISBA. The use of the surface temperature seems more problematic because its sensitivity to the value of the total water content is meaningful in relatively dry conditions only.
Abstract
The bulk soil water content must be estimated accurately for short- and medium-term meteorological modeling. A method is proposed to retrieve the total soil moisture content as well as the field capacity from observed surface parameters such as surface soil moisture or surface temperature. A continuous series of micrometeorological and soil water content measurements was obtained in southwestern France over a fallow site in 1995. In addition, the database includes measurements of the surface temperature and soil moisture profiles within the top 5-cm soil layer. The surface soil moisture measurements are available twice a day during two 30-day intensive observing periods in spring and autumn 1995. Once calibrated, the ISBA (Interactions between Soil, Biosphere, and Atmosphere) surface scheme is able to properly simulate the measured surface variables and the bulk soil moisture. Then an assimilation technique is applied to analyze the field capacity and the total soil water content from the surface data. In particular, it is shown that knowing the atmospheric forcing and the precipitation, four or five estimations of the surface soil moisture spread out over a 15-day period are enough to retrieve the total soil water content by inverting ISBA. The use of the surface temperature seems more problematic because its sensitivity to the value of the total water content is meaningful in relatively dry conditions only.
Abstract
This paper and its companion report on the development of a sequential assimilation technique based upon optimum interpolation in order to initialize soil moisture in atmospheric models. A previous study by Mahfouf has demonstrated that it is possible to estimate soil moisture from the evolution of atmospheric temperature and relative humidity near the surface. The main purpose of this paper is to examine more precisely the dependence of atmospheric low-level parameters upon soil moisture and how this dependence is affected by various factors (soil characteristics, vegetation type, low-level wind). The sensitivity of atmospheric parameters to soil moisture is expressed as the statistical quantities of the optimal interpolation. The importance of observation errors, which define the relevance of the atmospheric parameters for the assimilation procedure, is also investigated. An analytical formulation of the optimal interpolation coefficients is proposed. Finally, the usefulness and limitations of this work for soil moisture analysis in three-dimensional models are discussed.
Abstract
This paper and its companion report on the development of a sequential assimilation technique based upon optimum interpolation in order to initialize soil moisture in atmospheric models. A previous study by Mahfouf has demonstrated that it is possible to estimate soil moisture from the evolution of atmospheric temperature and relative humidity near the surface. The main purpose of this paper is to examine more precisely the dependence of atmospheric low-level parameters upon soil moisture and how this dependence is affected by various factors (soil characteristics, vegetation type, low-level wind). The sensitivity of atmospheric parameters to soil moisture is expressed as the statistical quantities of the optimal interpolation. The importance of observation errors, which define the relevance of the atmospheric parameters for the assimilation procedure, is also investigated. An analytical formulation of the optimal interpolation coefficients is proposed. Finally, the usefulness and limitations of this work for soil moisture analysis in three-dimensional models are discussed.
Abstract
A sequential assimilation technique based upon optimum interpolation is developed to initialize soil moisture in atmospheric models. Soil moisture increments are linearly related to forecast errors of near-surface atmospheric temperature and relative humidity. Part I has shown that soil moisture can be estimated from surface characteristics (vegetation coverage, soil texture). In this part, the behavior of the method is examined within a three-dimensional mesoscale model. The model includes a realistic land surface parameterization that relates soil moisture to atmospheric variables. Results reveal that after 48-h assimilations soil moisture has converged near reference values by blending atmospheric quantities in the algorithm. The convergence rate is almost independent of the first guess. Sensitivity studies show that the observational errors modulate the efficiency of the process and that results with an analytic formulation of the optimum coefficients are close to those obtained with a Monte Carlo method. These conclusions are of practical interest for an implementation in operational models.
Abstract
A sequential assimilation technique based upon optimum interpolation is developed to initialize soil moisture in atmospheric models. Soil moisture increments are linearly related to forecast errors of near-surface atmospheric temperature and relative humidity. Part I has shown that soil moisture can be estimated from surface characteristics (vegetation coverage, soil texture). In this part, the behavior of the method is examined within a three-dimensional mesoscale model. The model includes a realistic land surface parameterization that relates soil moisture to atmospheric variables. Results reveal that after 48-h assimilations soil moisture has converged near reference values by blending atmospheric quantities in the algorithm. The convergence rate is almost independent of the first guess. Sensitivity studies show that the observational errors modulate the efficiency of the process and that results with an analytic formulation of the optimum coefficients are close to those obtained with a Monte Carlo method. These conclusions are of practical interest for an implementation in operational models.
Abstract
The interactions between the soil, biosphere, and atmosphere (ISBA) land surface parameterization scheme has been modified to include soil ice. The liquid water equivalent volumetric ice content is modeled using two reservoirs within the soil: a thin surface layer that directly affects the surface energy balance, and a deep soil layer. The freezing/drying, wetting/thawing analogy is used, and a description of the modifications to the ISBA force–restore scheme, in particular to the hydrological and thermal transfer coefficients, is presented. In addition, the ISBA surface/vegetation scheme is coupled to a multilayer explicit diffusion soil heat and mass transfer model in order to investigate the accuracy of the force–restore formalism soil freezing parameterization as compared with a higher-order scheme.
An example of the influence of the inclusion of soil freezing in ISBA on predicted surface and soil temperatures and surface fluxes is examined using prescribed atmospheric forcing from a micrometeorological case study that includes freeze–thaw cycles. Surface temperature prediction is improved in comparison with the observed values, especially at night, primarily from the release of latent heat as the soil freezes. There is an improvement in the overall surface flux prediction, although for some specific periods there is increased error in the prediction of various components of the surface energy budget. Last, the simplified force–restore approach is found to produce surface flux and temperature predictions consistent with the higher-resolution model on typical numerical weather prediction model timescales (on the order of several days to two weeks) for this particular site.
Abstract
The interactions between the soil, biosphere, and atmosphere (ISBA) land surface parameterization scheme has been modified to include soil ice. The liquid water equivalent volumetric ice content is modeled using two reservoirs within the soil: a thin surface layer that directly affects the surface energy balance, and a deep soil layer. The freezing/drying, wetting/thawing analogy is used, and a description of the modifications to the ISBA force–restore scheme, in particular to the hydrological and thermal transfer coefficients, is presented. In addition, the ISBA surface/vegetation scheme is coupled to a multilayer explicit diffusion soil heat and mass transfer model in order to investigate the accuracy of the force–restore formalism soil freezing parameterization as compared with a higher-order scheme.
An example of the influence of the inclusion of soil freezing in ISBA on predicted surface and soil temperatures and surface fluxes is examined using prescribed atmospheric forcing from a micrometeorological case study that includes freeze–thaw cycles. Surface temperature prediction is improved in comparison with the observed values, especially at night, primarily from the release of latent heat as the soil freezes. There is an improvement in the overall surface flux prediction, although for some specific periods there is increased error in the prediction of various components of the surface energy budget. Last, the simplified force–restore approach is found to produce surface flux and temperature predictions consistent with the higher-resolution model on typical numerical weather prediction model timescales (on the order of several days to two weeks) for this particular site.
