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- Author or Editor: W. James Shuttleworth x
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Abstract
In this study, a climate version of the Regional Atmospheric Modeling System (ClimRAMS) was used to investigate the sensitivity of regional climate simulations to changes in vegetation distribution in the Great Plains and Rocky Mountain regions of the United States. The evolution of vegetation phenology was assimilated into the ClimRAMS in the form of estimates of the leaf area index (LAI) derived from the normalized difference vegetation index (NDVI). Initially, two model integrations were made. In the first, the NDVI-derived vegetation distribution was used, while the second integration used the model's “default” description of vegetation. The simulated near-surface climate was drastically altered by the introduction of NDVI-derived LAI, especially in the growing season, with the run in which observed LAI was assimilated producing, in general, a wetter and colder near-surface climate than the default run. A third model experiment was then carried out in which the (comparatively more homogeneous) spatial distribution of the LAI remained the same as in the “default” run, but the overall, domain-averaged magnitude of the LAI was reduced to be consistent with that of NDVI-derived LAI. This third run simulated a drier and warmer near-surface climate compared to the default run. Taken together, these results indicate that regional climates are indeed sensitive to seasonal changes in vegetation phenology, and that they are especially sensitive to the land surface heterogeneity associated with vegetation cover. The need to realistically represent both the spatial and temporal distribution of vegetation in regional climate models is thus highlighted, and the value of assimilating remotely sensed measures of vegetation vigor in Four-Dimensional Data Assimilation (4DDA) systems is demonstrated.
Abstract
In this study, a climate version of the Regional Atmospheric Modeling System (ClimRAMS) was used to investigate the sensitivity of regional climate simulations to changes in vegetation distribution in the Great Plains and Rocky Mountain regions of the United States. The evolution of vegetation phenology was assimilated into the ClimRAMS in the form of estimates of the leaf area index (LAI) derived from the normalized difference vegetation index (NDVI). Initially, two model integrations were made. In the first, the NDVI-derived vegetation distribution was used, while the second integration used the model's “default” description of vegetation. The simulated near-surface climate was drastically altered by the introduction of NDVI-derived LAI, especially in the growing season, with the run in which observed LAI was assimilated producing, in general, a wetter and colder near-surface climate than the default run. A third model experiment was then carried out in which the (comparatively more homogeneous) spatial distribution of the LAI remained the same as in the “default” run, but the overall, domain-averaged magnitude of the LAI was reduced to be consistent with that of NDVI-derived LAI. This third run simulated a drier and warmer near-surface climate compared to the default run. Taken together, these results indicate that regional climates are indeed sensitive to seasonal changes in vegetation phenology, and that they are especially sensitive to the land surface heterogeneity associated with vegetation cover. The need to realistically represent both the spatial and temporal distribution of vegetation in regional climate models is thus highlighted, and the value of assimilating remotely sensed measures of vegetation vigor in Four-Dimensional Data Assimilation (4DDA) systems is demonstrated.
Abstract
MICRO-SWEAT, a soil–vegetation–atmosphere transfer scheme (SWEAT) coupled with a microwave emission model, was used to predict the microwave brightness temperatures (T B ) measured at El Reno, Oklahoma, during the Southern Great Plains 1997 (SGP97) field experiment. Comparison with soil-moisture time series measured at four intensively monitored sites revealed the need for a substantially greater soil-saturated hydraulic conductivity than that estimated from soil maps. After revision of the hydraulic conductivity, the modeled and measured time series of soil moisture and surface energy fluxes showed excellent agreement with observations at these 4 sites and with the measurements of the surface soil moisture and T B at the remaining 11 measurement sites. A two-dimensional array of calibrated MICRO-SWEAT models was implemented at 200-m resolution for the El Reno area. There were noticeable differences between the spatial distributions of modeled and measured T B . These differences likely result from imperfect knowledge of the spatial distributions of soil properties, precipitation, and the estimated optical depth of the vegetation used in MICRO-SWEAT. A statistical measure of the usefulness of assimilating the observed soil moisture was explored by assuming the estimation of the optical depth provided the main source of error in the relationship between soil moisture and microwave brightness temperature. Analyses indicated that there is merit in assimilating T B observations for significant portions of the modeled domain, but it is suggested that this would be enhanced if the optical depth of the vegetation were also directly remotely sensed, as proposed in the Soil Moisture and Ocean Salinity (SMOS) mission.
Abstract
MICRO-SWEAT, a soil–vegetation–atmosphere transfer scheme (SWEAT) coupled with a microwave emission model, was used to predict the microwave brightness temperatures (T B ) measured at El Reno, Oklahoma, during the Southern Great Plains 1997 (SGP97) field experiment. Comparison with soil-moisture time series measured at four intensively monitored sites revealed the need for a substantially greater soil-saturated hydraulic conductivity than that estimated from soil maps. After revision of the hydraulic conductivity, the modeled and measured time series of soil moisture and surface energy fluxes showed excellent agreement with observations at these 4 sites and with the measurements of the surface soil moisture and T B at the remaining 11 measurement sites. A two-dimensional array of calibrated MICRO-SWEAT models was implemented at 200-m resolution for the El Reno area. There were noticeable differences between the spatial distributions of modeled and measured T B . These differences likely result from imperfect knowledge of the spatial distributions of soil properties, precipitation, and the estimated optical depth of the vegetation used in MICRO-SWEAT. A statistical measure of the usefulness of assimilating the observed soil moisture was explored by assuming the estimation of the optical depth provided the main source of error in the relationship between soil moisture and microwave brightness temperature. Analyses indicated that there is merit in assimilating T B observations for significant portions of the modeled domain, but it is suggested that this would be enhanced if the optical depth of the vegetation were also directly remotely sensed, as proposed in the Soil Moisture and Ocean Salinity (SMOS) mission.
Abstract
This paper describes the second part of a study to document the sensitivity of the modeled regional moisture flux patterns and hydrometeorological response of the North American monsoon system (NAMS) to convective parameterization. Use of the convective parameterization schemes of Betts–Miller–Janjic, Kain–Fritsch, and Grell was investigated during the initial phase of the 1999 NAMS using version 3.4 of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) running in a pseudoclimate mode. Substantial differences in both the stationary and transient components of the moisture flux fields were found between the simulations, resulting in differences in moisture convergence patterns, precipitation, and surface evapotranspiration. Basin-average calculations of hydrologic variables indicate that, in most of the basins for which calculations were made, the magnitude of the evaporation-minus-precipitation moisture source/sink differs substantially between simulations and, in some cases, even the sign of the source/sink changed. There are substantial differences in rainfall–runoff processes because the basin-average rainfall intensities, proportion of rainfall from convective origin, and the runoff coefficients differ between simulations. The results indicate that, in regions of sustained, deep convection, the selection of the subgrid convective parameterization in a high-resolution atmospheric model can potentially have a hydrometeorological impact in regional analyses, which is at least as important as the effect of land surface forcing.
Abstract
This paper describes the second part of a study to document the sensitivity of the modeled regional moisture flux patterns and hydrometeorological response of the North American monsoon system (NAMS) to convective parameterization. Use of the convective parameterization schemes of Betts–Miller–Janjic, Kain–Fritsch, and Grell was investigated during the initial phase of the 1999 NAMS using version 3.4 of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) running in a pseudoclimate mode. Substantial differences in both the stationary and transient components of the moisture flux fields were found between the simulations, resulting in differences in moisture convergence patterns, precipitation, and surface evapotranspiration. Basin-average calculations of hydrologic variables indicate that, in most of the basins for which calculations were made, the magnitude of the evaporation-minus-precipitation moisture source/sink differs substantially between simulations and, in some cases, even the sign of the source/sink changed. There are substantial differences in rainfall–runoff processes because the basin-average rainfall intensities, proportion of rainfall from convective origin, and the runoff coefficients differ between simulations. The results indicate that, in regions of sustained, deep convection, the selection of the subgrid convective parameterization in a high-resolution atmospheric model can potentially have a hydrometeorological impact in regional analyses, which is at least as important as the effect of land surface forcing.
Abstract
Over the last decade, improved understanding of plant physiological processes has generated a significant change in the way stomatal functioning is described in advanced land surface schemes. New versions of two advanced and widely used land surface schemes, the Biosphere–Atmosphere Transfer Scheme (BATS) and the Simple Biosphere Model (SiB), reflect this change in understanding, although these two models make different assumptions regarding the response of stomata to atmospheric humidity deficit. The goal of this study was to evaluate the new, second version of BATS, here called BATS2, using Amazon field data from the Anglo–Brazilian Amazonian Climate Observational Study (ABRACOS) project, with an emphasis on comparison with the original version of BATS and the new, second version of SiB (SiB2). Evaluation of SiB2 using a 3-yr time series of ABRACOS data revealed that there is an unrealistic simulation of the yearly cycle in soil moisture status, with a resulting poor simulation of evaporation. Improved long-term simulation by SiB2 requires specification of a deeper rooting depth, and this requirement is general for all three models. In general, the original version of BATS with a revised root distribution and rooting depth gave good agreement with observations of the surface energy balance but occasionally showed excessive sensitivity to large atmospheric vapor pressure deficit. Evaluation of BATS2 revealed that changes are required in the parameters that determine stomatal behavior in the model for realistic simulation of transpiration, time-averaged respiration, and net carbon dioxide (CO2) uptake. When initiated with default values for carbon stores, BATS2 takes several hundred years to reach an equilibrium carbon balance. Aspects of the model’s representation of instantaneous carbon allocation and respiration processes indicate that BATS2 cannot be expected to provide a realistic simulation of hourly variations in CO2 exchanges. In general, all three models have weaknesses when describing the field data with default values of model parameters. If a few model parameters are modified in a plausible way, however, all three models can be made to give a good time-averaged simulation of measured exchanges. There is little evidence of sensitivity to the different forms assumed for the stomatal response to atmospheric humidity deficit, although this study suggests that assuming that leaf stress is related linearly to relative humidity is marginally preferred.
Abstract
Over the last decade, improved understanding of plant physiological processes has generated a significant change in the way stomatal functioning is described in advanced land surface schemes. New versions of two advanced and widely used land surface schemes, the Biosphere–Atmosphere Transfer Scheme (BATS) and the Simple Biosphere Model (SiB), reflect this change in understanding, although these two models make different assumptions regarding the response of stomata to atmospheric humidity deficit. The goal of this study was to evaluate the new, second version of BATS, here called BATS2, using Amazon field data from the Anglo–Brazilian Amazonian Climate Observational Study (ABRACOS) project, with an emphasis on comparison with the original version of BATS and the new, second version of SiB (SiB2). Evaluation of SiB2 using a 3-yr time series of ABRACOS data revealed that there is an unrealistic simulation of the yearly cycle in soil moisture status, with a resulting poor simulation of evaporation. Improved long-term simulation by SiB2 requires specification of a deeper rooting depth, and this requirement is general for all three models. In general, the original version of BATS with a revised root distribution and rooting depth gave good agreement with observations of the surface energy balance but occasionally showed excessive sensitivity to large atmospheric vapor pressure deficit. Evaluation of BATS2 revealed that changes are required in the parameters that determine stomatal behavior in the model for realistic simulation of transpiration, time-averaged respiration, and net carbon dioxide (CO2) uptake. When initiated with default values for carbon stores, BATS2 takes several hundred years to reach an equilibrium carbon balance. Aspects of the model’s representation of instantaneous carbon allocation and respiration processes indicate that BATS2 cannot be expected to provide a realistic simulation of hourly variations in CO2 exchanges. In general, all three models have weaknesses when describing the field data with default values of model parameters. If a few model parameters are modified in a plausible way, however, all three models can be made to give a good time-averaged simulation of measured exchanges. There is little evidence of sensitivity to the different forms assumed for the stomatal response to atmospheric humidity deficit, although this study suggests that assuming that leaf stress is related linearly to relative humidity is marginally preferred.
Abstract
The purpose of this note is to present preliminary findings from a new event-based surface rain gauge network in the region of northwest Mexico. This region is characterized as semiarid, owing the largest percentage of its annual rainfall to summer convective systems, which are diurnal in nature. Although the existing surface network and satellite-derived precipitation products have clarified some features of convective activity over the core region of the North American monsoon (NAM), a detailed examination of the spatial and temporal structure of such activity has been prohibited by the lack of a surface observation network with adequate temporal and spatial resolution. Specifically, the current network of sparsely spaced climate stations has inhibited a detailed diagnosis of the timing, intensity, and duration of convective rainfall in general, and of the topography–rainfall relationship in particular. In this note, a brief overview of the network and present preliminary analyses from the first monitoring season, summer 2002, is provided. It is shown that the diurnal cycle of precipitation varies with elevation in a way that is consistent with a hypothesis that convective events organize and, occasionally, propagate from high terrain onto lower-elevation plains, but more conclusive statements will require expansion of the network and increased record length. It is also emphasized from these studies that it is essential to evaluate wet-day statistics or rainfall intensities from precipitating periods in parallel, with comparable all-day statistics, when conducting hydrometeorological analyses in semiarid convective regimes where precipitation is infrequent and highly localized.
Abstract
The purpose of this note is to present preliminary findings from a new event-based surface rain gauge network in the region of northwest Mexico. This region is characterized as semiarid, owing the largest percentage of its annual rainfall to summer convective systems, which are diurnal in nature. Although the existing surface network and satellite-derived precipitation products have clarified some features of convective activity over the core region of the North American monsoon (NAM), a detailed examination of the spatial and temporal structure of such activity has been prohibited by the lack of a surface observation network with adequate temporal and spatial resolution. Specifically, the current network of sparsely spaced climate stations has inhibited a detailed diagnosis of the timing, intensity, and duration of convective rainfall in general, and of the topography–rainfall relationship in particular. In this note, a brief overview of the network and present preliminary analyses from the first monitoring season, summer 2002, is provided. It is shown that the diurnal cycle of precipitation varies with elevation in a way that is consistent with a hypothesis that convective events organize and, occasionally, propagate from high terrain onto lower-elevation plains, but more conclusive statements will require expansion of the network and increased record length. It is also emphasized from these studies that it is essential to evaluate wet-day statistics or rainfall intensities from precipitating periods in parallel, with comparable all-day statistics, when conducting hydrometeorological analyses in semiarid convective regimes where precipitation is infrequent and highly localized.
