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- Author or Editor: A. J. Dolman x
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Abstract
A dual-source model that solves the energy balance over vegetation and soil separately can be inverted to obtain the roughness length for heat z 0h of a single-source model. Model parameters for the dual-source model were taken from previous analysis of data from a sparse canopy in semiarid terrain. In these circumstances, the value of z 0h , is shown to be dependent on the humidity deficit, the available energy, the vegetation fraction, and the surface resistance of the soil and the vegetation.
Abstract
A dual-source model that solves the energy balance over vegetation and soil separately can be inverted to obtain the roughness length for heat z 0h of a single-source model. Model parameters for the dual-source model were taken from previous analysis of data from a sparse canopy in semiarid terrain. In these circumstances, the value of z 0h , is shown to be dependent on the humidity deficit, the available energy, the vegetation fraction, and the surface resistance of the soil and the vegetation.
Abstract
Atmospheric moisture within a region is supplied by both local evaporation and advected from external sources. The contribution of local evaporation in a region to the precipitation in the same region is defined as “precipitation recycling.” Precipitation recycling helps in defining the role of land–atmosphere interactions in regional climate. A dynamic precipitation recycling model, which includes the moisture storage term, has been applied to calculate summer variability of the precipitation recycling over Europe based on 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) data. Time series for three subregions in Europe (central Europe, the Balkans, and Spain) are obtained to analyze the variability in recycling and to compare the potential in the subregions for interactions between land surface and atmospheric processes. In addition, the recycled precipitation and recycling ratios are linked to several components of the water vapor balance equation [precipitation, evaporation, precipitation minus evaporation (P − E), and moisture transport]. It is found that precipitation recycling is large in dry summers for central Europe, while the opposite is true for the Balkans. Large precipitation recycling is determined in relation with weak moisture transport and high evaporation rates in central Europe. This occurs for dry summers. For the Balkans, precipitation recycling is large in wet summers when moisture transport is weak, and P − E and evaporation are large. Here, the recycling process intensifies the hydrological cycle due to a positive feedback via convective precipitation and therefore the amount of recycled precipitation is larger. For Spain, recycling is also larger when moisture transport is weak, but other correlations are not found. For regions such as central Europe in dry summers and the Balkans in wet summers, which are susceptible to land–atmosphere interactions, future climate and/or land use can have an impact on the regional climate conditions due to changes in evaporation.
Abstract
Atmospheric moisture within a region is supplied by both local evaporation and advected from external sources. The contribution of local evaporation in a region to the precipitation in the same region is defined as “precipitation recycling.” Precipitation recycling helps in defining the role of land–atmosphere interactions in regional climate. A dynamic precipitation recycling model, which includes the moisture storage term, has been applied to calculate summer variability of the precipitation recycling over Europe based on 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) data. Time series for three subregions in Europe (central Europe, the Balkans, and Spain) are obtained to analyze the variability in recycling and to compare the potential in the subregions for interactions between land surface and atmospheric processes. In addition, the recycled precipitation and recycling ratios are linked to several components of the water vapor balance equation [precipitation, evaporation, precipitation minus evaporation (P − E), and moisture transport]. It is found that precipitation recycling is large in dry summers for central Europe, while the opposite is true for the Balkans. Large precipitation recycling is determined in relation with weak moisture transport and high evaporation rates in central Europe. This occurs for dry summers. For the Balkans, precipitation recycling is large in wet summers when moisture transport is weak, and P − E and evaporation are large. Here, the recycling process intensifies the hydrological cycle due to a positive feedback via convective precipitation and therefore the amount of recycled precipitation is larger. For Spain, recycling is also larger when moisture transport is weak, but other correlations are not found. For regions such as central Europe in dry summers and the Balkans in wet summers, which are susceptible to land–atmosphere interactions, future climate and/or land use can have an impact on the regional climate conditions due to changes in evaporation.
The Global Soil Wetness Project (GSWP) is an ongoing land surface modeling activity of the International Satellite Land-Surface Climatology Project (ISLSCP), a part of the Global Energy and Water Cycle Experiment. The pilot phase of GSWP deals with the production of a two-year global dataset of soil moisture, temperature, runoff, and surface fluxes by integrating uncoupled land surface schemes (LSSs) using externally specified surface forcings from observations and standardized soil and vegetation distributions. Approximately one dozen participating LSS groups in five nations have taken the common ISLSCP forcing data to drive their state-of-the-art models over the 1987–88 period to generate global datasets. Many of the LSS groups have performed specific sensitivity studies, which are intended to evaluate the impact of uncertainties in model parameters and forcing fields on simulation of the surface water and energy balances. A validation effort exists to compare the global products to other forms of estimation and measurement, either directly (by comparison to field studies or soil moisture measuring networks) or indirectly (e.g., use of modeled runoff to drive river routing schemes for comparison to streamflow data). The soil wetness data produced are also being tested within general circulation models to evaluate their quality and their impact on seasonal to interannual climate simulations. An Inter-Comparison Center has also been established for evaluating and comparing data from the different LSSs. Comparison among the model results is used to assess the uncertainty in estimates of surface components of the moisture and energy balances at large scales and as a quality check on the model products themselves.
The Global Soil Wetness Project (GSWP) is an ongoing land surface modeling activity of the International Satellite Land-Surface Climatology Project (ISLSCP), a part of the Global Energy and Water Cycle Experiment. The pilot phase of GSWP deals with the production of a two-year global dataset of soil moisture, temperature, runoff, and surface fluxes by integrating uncoupled land surface schemes (LSSs) using externally specified surface forcings from observations and standardized soil and vegetation distributions. Approximately one dozen participating LSS groups in five nations have taken the common ISLSCP forcing data to drive their state-of-the-art models over the 1987–88 period to generate global datasets. Many of the LSS groups have performed specific sensitivity studies, which are intended to evaluate the impact of uncertainties in model parameters and forcing fields on simulation of the surface water and energy balances. A validation effort exists to compare the global products to other forms of estimation and measurement, either directly (by comparison to field studies or soil moisture measuring networks) or indirectly (e.g., use of modeled runoff to drive river routing schemes for comparison to streamflow data). The soil wetness data produced are also being tested within general circulation models to evaluate their quality and their impact on seasonal to interannual climate simulations. An Inter-Comparison Center has also been established for evaluating and comparing data from the different LSSs. Comparison among the model results is used to assess the uncertainty in estimates of surface components of the moisture and energy balances at large scales and as a quality check on the model products themselves.
Abstract
A meso-β-scale model is used to model a frontal intrusion in southwest France during HAPEX-MOBILHY. The skill of the model to reproduce the observed variation in temperature, humidity, and wind speed over the domain is reasonable within the limitations of the model parameterizations and initialization procedure, although there were errors in the timing and positioning of the front. A stable boundary layer was both observed and modeled over the forested area. The associated negative sensible heat flux provided the energy to sustain evaporation from the wet forest canopy under conditions of low radiation. A large wind shear over the stably stratified boundary layer provided the required turbulent kinetic energy to maintain the downward transport of sensible heat. Sensitivity experiments showed that local rainfall with a full forest cover changed from 2.9 to 3.8 mm, which represents a 30% increase when compared with a bare-soil domain. Half of this increase is from positive feedback of the intercepted water that reevaporates. The high roughness length of the forest, with its associated physical and dynamical effects, accounts for the rest of the increase in rainfall and for the accompanying increase in soil moisture.
Abstract
A meso-β-scale model is used to model a frontal intrusion in southwest France during HAPEX-MOBILHY. The skill of the model to reproduce the observed variation in temperature, humidity, and wind speed over the domain is reasonable within the limitations of the model parameterizations and initialization procedure, although there were errors in the timing and positioning of the front. A stable boundary layer was both observed and modeled over the forested area. The associated negative sensible heat flux provided the energy to sustain evaporation from the wet forest canopy under conditions of low radiation. A large wind shear over the stably stratified boundary layer provided the required turbulent kinetic energy to maintain the downward transport of sensible heat. Sensitivity experiments showed that local rainfall with a full forest cover changed from 2.9 to 3.8 mm, which represents a 30% increase when compared with a bare-soil domain. Half of this increase is from positive feedback of the intercepted water that reevaporates. The high roughness length of the forest, with its associated physical and dynamical effects, accounts for the rest of the increase in rainfall and for the accompanying increase in soil moisture.
Abstract
The relative contribution of topography and land use on precipitation is analyzed in this paper for a forested area in the Netherlands. This area has an average yearly precipitation sum that can be 75–100 mm higher than the rest of the country. To analyze this contribution, different configurations of land use and topography are fed into a mesoscale model. The authors use the Regional Atmospheric Modeling System (RAMS) coupled with a land surface scheme simulating water vapor, heat, and momentum fluxes [Soil–Water–Atmosphere Plant System–Carbon (SWAPS-C)]. The model simulations are executed for two periods that cover varying large-scale synoptic conditions of summer and winter periods. The output of the experiments leads to the conclusion that the precipitation maximum at the Veluwe is forced by topography and land use. The effect of the forested area on the processes that influence precipitation is smaller in summertime conditions when the precipitation has a convective character. In frontal conditions, the forest has a more pronounced effect on local precipitation through the convergence of moisture. The effect of topography on monthly domain-averaged precipitation around the Veluwe is a 17% increase in the winter and a 10% increase in the summer, which is quite remarkable for topography with a maximum elevation of just above 100 m and moderate steepness. From this study, it appears that the version of RAMS using Mellor–Yamada turbulence parameterization simulates precipitation better in wintertime, but the configuration with the medium-range forecast (MRF) turbulence parameterization improves the simulation of precipitation in convective circumstances.
Abstract
The relative contribution of topography and land use on precipitation is analyzed in this paper for a forested area in the Netherlands. This area has an average yearly precipitation sum that can be 75–100 mm higher than the rest of the country. To analyze this contribution, different configurations of land use and topography are fed into a mesoscale model. The authors use the Regional Atmospheric Modeling System (RAMS) coupled with a land surface scheme simulating water vapor, heat, and momentum fluxes [Soil–Water–Atmosphere Plant System–Carbon (SWAPS-C)]. The model simulations are executed for two periods that cover varying large-scale synoptic conditions of summer and winter periods. The output of the experiments leads to the conclusion that the precipitation maximum at the Veluwe is forced by topography and land use. The effect of the forested area on the processes that influence precipitation is smaller in summertime conditions when the precipitation has a convective character. In frontal conditions, the forest has a more pronounced effect on local precipitation through the convergence of moisture. The effect of topography on monthly domain-averaged precipitation around the Veluwe is a 17% increase in the winter and a 10% increase in the summer, which is quite remarkable for topography with a maximum elevation of just above 100 m and moderate steepness. From this study, it appears that the version of RAMS using Mellor–Yamada turbulence parameterization simulates precipitation better in wintertime, but the configuration with the medium-range forecast (MRF) turbulence parameterization improves the simulation of precipitation in convective circumstances.
Abstract
The interaction between the land surface and the atmosphere is of significant importance in the climate system because it is a key driver of the exchanges of energy and water. Several important relations to heat waves, floods, and droughts exist that are based on the interaction of soil moisture and, for instance, air temperature and humidity. Our ability to separate the elements of this coupling, identify the exact locations where they are strongest, and quantify their strengths is, therefore, of paramount importance to their predictability. A recent rigorous causality formalism based on the Liang–Kleeman (LK) information flow theory has been shown, both theoretically and in real-world applications, to have the necessary asymmetry to infer the directionality and magnitude within geophysical interactions. However, the formalism assumes stationarity in time, whereas the interactions within the land surface and atmosphere are generally nonstationary; furthermore, it requires a sufficiently long time series to ensure statistical sufficiency. In this study, we remedy this difficulty by using the square root Kalman filter to estimate the causality based on the LK formalism to derive a time-varying form. Results show that the new formalism has similar properties compared to its time-invariant form. It is shown that it is also able to capture the time-varying causality structure within soil moisture–air temperature coupling. An advantage is that it does not require very long time series to make an accurate estimation. Applying a wavelet transform to the results also reveals the full range of temporal scales of the interactions.
Abstract
The interaction between the land surface and the atmosphere is of significant importance in the climate system because it is a key driver of the exchanges of energy and water. Several important relations to heat waves, floods, and droughts exist that are based on the interaction of soil moisture and, for instance, air temperature and humidity. Our ability to separate the elements of this coupling, identify the exact locations where they are strongest, and quantify their strengths is, therefore, of paramount importance to their predictability. A recent rigorous causality formalism based on the Liang–Kleeman (LK) information flow theory has been shown, both theoretically and in real-world applications, to have the necessary asymmetry to infer the directionality and magnitude within geophysical interactions. However, the formalism assumes stationarity in time, whereas the interactions within the land surface and atmosphere are generally nonstationary; furthermore, it requires a sufficiently long time series to ensure statistical sufficiency. In this study, we remedy this difficulty by using the square root Kalman filter to estimate the causality based on the LK formalism to derive a time-varying form. Results show that the new formalism has similar properties compared to its time-invariant form. It is shown that it is also able to capture the time-varying causality structure within soil moisture–air temperature coupling. An advantage is that it does not require very long time series to make an accurate estimation. Applying a wavelet transform to the results also reveals the full range of temporal scales of the interactions.
The Second Global Soil Wetness Project (GSWP-2) is an initiative to compare and evaluate 10-year simulations by a broad range of land surface models under controlled conditions. A major product of GSWP-2 is the first global gridded multimodel analysis of land surface state variables and fluxes for use by meteorologists, hydrologists, engineers, biogeochemists, agronomists, botanists, ecologists, geographers, climatologists, and educators. Simulations by 13 land models from five nations have gone into production of the analysis. The models are driven by forcing data derived from a combination of gridded atmospheric reanalyses and observations. The resulting analysis consists of multimodel means and standard deviations on the monthly time scale, including profiles of soil moisture and temperature at six levels, as well as daily and climatological (mean annual cycle) fields for over 50 land surface variables. The monthly standard deviations provide a measure of model agreement that may be used as a quality metric. An overview of key characteristics of the analysis is presented here, along with information on obtaining the data.
The Second Global Soil Wetness Project (GSWP-2) is an initiative to compare and evaluate 10-year simulations by a broad range of land surface models under controlled conditions. A major product of GSWP-2 is the first global gridded multimodel analysis of land surface state variables and fluxes for use by meteorologists, hydrologists, engineers, biogeochemists, agronomists, botanists, ecologists, geographers, climatologists, and educators. Simulations by 13 land models from five nations have gone into production of the analysis. The models are driven by forcing data derived from a combination of gridded atmospheric reanalyses and observations. The resulting analysis consists of multimodel means and standard deviations on the monthly time scale, including profiles of soil moisture and temperature at six levels, as well as daily and climatological (mean annual cycle) fields for over 50 land surface variables. The monthly standard deviations provide a measure of model agreement that may be used as a quality metric. An overview of key characteristics of the analysis is presented here, along with information on obtaining the data.
