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- Author or Editor: Mark A. Friedl x
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Abstract
Diurnal variation in soil heat flux is a key constraint on the amount of energy available for sensible and latent heating of the lower troposphere. Many studies have demonstrated that soil heat flux G is strongly correlated with net radiation R n . However, methods to parameterize G based on this relationship typically do not account for the dependency of G on soil properties and ignore asymmetry in the diurnal variation of G relative to R n . In this paper, the diurnal behavior of G as a function of R n is examined for sparse cover and bare soil conditions, focusing on patterns of diurnal variation as well as on the effects of soil moisture and soil type. To this end, information from field data is combined with simulations from a multilayer, diffusion-based soil model over a range of soil conditions and vegetation densities. The results show that a relatively simple function can be used to capture the first-order diurnal covariation between G and R n . Within this framework, soil moisture exerts an important control on this relationship. When soils make the transition from stage-1 (atmosphere limited) to stage-2 (soil limited) evaporation, the ratio of G to R n tends to increase. Further, soils in stage-2 evaporation exhibit positive G later in the day relative to moist soils. Data from several field experiments show that the amplitude of diurnal surface temperature can be used to predict the magnitude and behavior of G/R n by integrating the effects of soil type and moisture. Based on these results, a method to estimate G/R n is proposed that provides a robust representation of G/R n on hourly timescales for varying soil conditions. This method provides improvement over previous semiempirical treatments for G for which diurnal energy balance closure is required.
Abstract
Diurnal variation in soil heat flux is a key constraint on the amount of energy available for sensible and latent heating of the lower troposphere. Many studies have demonstrated that soil heat flux G is strongly correlated with net radiation R n . However, methods to parameterize G based on this relationship typically do not account for the dependency of G on soil properties and ignore asymmetry in the diurnal variation of G relative to R n . In this paper, the diurnal behavior of G as a function of R n is examined for sparse cover and bare soil conditions, focusing on patterns of diurnal variation as well as on the effects of soil moisture and soil type. To this end, information from field data is combined with simulations from a multilayer, diffusion-based soil model over a range of soil conditions and vegetation densities. The results show that a relatively simple function can be used to capture the first-order diurnal covariation between G and R n . Within this framework, soil moisture exerts an important control on this relationship. When soils make the transition from stage-1 (atmosphere limited) to stage-2 (soil limited) evaporation, the ratio of G to R n tends to increase. Further, soils in stage-2 evaporation exhibit positive G later in the day relative to moist soils. Data from several field experiments show that the amplitude of diurnal surface temperature can be used to predict the magnitude and behavior of G/R n by integrating the effects of soil type and moisture. Based on these results, a method to estimate G/R n is proposed that provides a robust representation of G/R n on hourly timescales for varying soil conditions. This method provides improvement over previous semiempirical treatments for G for which diurnal energy balance closure is required.
Abstract
The convective planetary boundary layer (PBL) integrates surface fluxes and conditions over regional and diurnal scales. As a result, the structure and evolution of the PBL contains information directly related to land surface states. To examine the nature and magnitude of land–atmosphere coupling and the interactions and feedbacks controlling PBL development, the authors used a large sample of radiosonde observations collected at the southern Atmospheric Research Measurement Program–Great Plains Cloud and Radiation Testbed (ARM-CART) site in association with simulations of mixed-layer growth from a single-column PBL/land surface model. The model accurately predicts PBL evolution and realistically simulates thermodynamics associated with two key controls on PBL growth: atmospheric stability and soil moisture. The information content of these variables and their influence on PBL height and screen-level temperature can be characterized using statistical methods to describe PBL–land surface coupling over a wide range of conditions. Results also show that the first-order effects of land–atmosphere coupling are manifested in the control of soil moisture and stability on atmospheric demand for evapotranspiration and on the surface energy balance. Two principal land–atmosphere feedback regimes observed during soil moisture drydown periods are identified that complicate direct relationships between PBL and land surface properties, and, as a result, limit the accuracy of uncoupled land surface and traditional PBL growth models. In particular, treatments for entrainment and the role of the residual mixed layer are critical to quantifying diurnal land–atmosphere interactions.
Abstract
The convective planetary boundary layer (PBL) integrates surface fluxes and conditions over regional and diurnal scales. As a result, the structure and evolution of the PBL contains information directly related to land surface states. To examine the nature and magnitude of land–atmosphere coupling and the interactions and feedbacks controlling PBL development, the authors used a large sample of radiosonde observations collected at the southern Atmospheric Research Measurement Program–Great Plains Cloud and Radiation Testbed (ARM-CART) site in association with simulations of mixed-layer growth from a single-column PBL/land surface model. The model accurately predicts PBL evolution and realistically simulates thermodynamics associated with two key controls on PBL growth: atmospheric stability and soil moisture. The information content of these variables and their influence on PBL height and screen-level temperature can be characterized using statistical methods to describe PBL–land surface coupling over a wide range of conditions. Results also show that the first-order effects of land–atmosphere coupling are manifested in the control of soil moisture and stability on atmospheric demand for evapotranspiration and on the surface energy balance. Two principal land–atmosphere feedback regimes observed during soil moisture drydown periods are identified that complicate direct relationships between PBL and land surface properties, and, as a result, limit the accuracy of uncoupled land surface and traditional PBL growth models. In particular, treatments for entrainment and the role of the residual mixed layer are critical to quantifying diurnal land–atmosphere interactions.
Abstract
Relationships among convective planetary boundary layer (PBL) evolution and land surface properties are explored using data from the Atmospheric Radiation Measurement Program Cloud and Radiation Test Bed in the southern Great Plains. Previous attempts to infer surface fluxes from observations of the PBL have been constrained by difficulties in accurately estimating and parameterizing the conservation equation and have been limited to multiday averages or small samples of daily case studies. Using radiosonde and surface flux data for June, July, and August of 1997, 1999, and 2001, a conservation approach was applied to 132 sets of daily observations. Results highlight the limitations of using this method on daily time scales caused by the diurnal variability and complexity of entrainment. A statistical investigation of the relationship among PBL and both land surface and near-surface properties that are not explicitly included in conservation methods indicates that atmospheric stability in the layer of PBL growth is the most influential variable controlling PBL development. Significant relationships between PBL height and soil moisture, 2-m potential temperature, and 2-m specific humidity are also identified through this analysis, and it is found that 76% of the variance in PBL height can be explained by observations of stability and soil water content. Using this approach, it is also possible to use limited observations of the PBL to estimate soil moisture on daily time scales without the need for detailed land surface parameterizations. In the future, the general framework that is presented may provide a means for robust estimation of near-surface soil moisture and land surface energy balance over regional scales.
Abstract
Relationships among convective planetary boundary layer (PBL) evolution and land surface properties are explored using data from the Atmospheric Radiation Measurement Program Cloud and Radiation Test Bed in the southern Great Plains. Previous attempts to infer surface fluxes from observations of the PBL have been constrained by difficulties in accurately estimating and parameterizing the conservation equation and have been limited to multiday averages or small samples of daily case studies. Using radiosonde and surface flux data for June, July, and August of 1997, 1999, and 2001, a conservation approach was applied to 132 sets of daily observations. Results highlight the limitations of using this method on daily time scales caused by the diurnal variability and complexity of entrainment. A statistical investigation of the relationship among PBL and both land surface and near-surface properties that are not explicitly included in conservation methods indicates that atmospheric stability in the layer of PBL growth is the most influential variable controlling PBL development. Significant relationships between PBL height and soil moisture, 2-m potential temperature, and 2-m specific humidity are also identified through this analysis, and it is found that 76% of the variance in PBL height can be explained by observations of stability and soil water content. Using this approach, it is also possible to use limited observations of the PBL to estimate soil moisture on daily time scales without the need for detailed land surface parameterizations. In the future, the general framework that is presented may provide a means for robust estimation of near-surface soil moisture and land surface energy balance over regional scales.
Abstract
Large-scale changes in the state of the land surface affect the circulation of the atmosphere and the structure and function of ecosystems alike. As global temperatures increase and regional climates change, the timing of key plant phenophase changes are likely to shift as well. Here we evaluate a suite of phenometrics designed to facilitate an “apples to apples” comparison between remote sensing products and climate model output. Specifically, we derive day-of-year (DOY) thresholds of leaf area index (LAI) from both remote sensing and the Community Land Model (CLM) over the Northern Hemisphere. This systematic approach to comparing phenologically relevant variables reveals appreciable differences in both LAI seasonal cycle and spring onset timing between model simulated phenology and satellite records. For example, phenological spring onset in the model occurs on average 30 days later than observed, especially for evergreen plant functional types. The disagreement in phenology can result in a mean bias of approximately 5% of the total estimated Northern Hemisphere NPP. Further, while the more recent version of CLM (v5.0) exhibits seasonal mean LAI values that are in closer agreement with satellite data than its predecessor (CLM4.5), LAI seasonal cycles in CLM5.0 exhibit poorer agreement. Therefore, despite broad improvements for a range of states and fluxes from CLM4.5 to CLM5.0, degradation of plant phenology occurs in CLM5.0. Therefore, any coupling between the land surface and the atmosphere that depends on vegetation state might not be fully captured by the existing generation of the model. We also discuss several avenues for improving the fidelity between observations and model simulations.
Abstract
Large-scale changes in the state of the land surface affect the circulation of the atmosphere and the structure and function of ecosystems alike. As global temperatures increase and regional climates change, the timing of key plant phenophase changes are likely to shift as well. Here we evaluate a suite of phenometrics designed to facilitate an “apples to apples” comparison between remote sensing products and climate model output. Specifically, we derive day-of-year (DOY) thresholds of leaf area index (LAI) from both remote sensing and the Community Land Model (CLM) over the Northern Hemisphere. This systematic approach to comparing phenologically relevant variables reveals appreciable differences in both LAI seasonal cycle and spring onset timing between model simulated phenology and satellite records. For example, phenological spring onset in the model occurs on average 30 days later than observed, especially for evergreen plant functional types. The disagreement in phenology can result in a mean bias of approximately 5% of the total estimated Northern Hemisphere NPP. Further, while the more recent version of CLM (v5.0) exhibits seasonal mean LAI values that are in closer agreement with satellite data than its predecessor (CLM4.5), LAI seasonal cycles in CLM5.0 exhibit poorer agreement. Therefore, despite broad improvements for a range of states and fluxes from CLM4.5 to CLM5.0, degradation of plant phenology occurs in CLM5.0. Therefore, any coupling between the land surface and the atmosphere that depends on vegetation state might not be fully captured by the existing generation of the model. We also discuss several avenues for improving the fidelity between observations and model simulations.
