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- Author or Editor: Yongkang Xue x
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Abstract
A general circulation model sensitivity study was carried out to investigate the influence of global sea surface temperature (SST) on Sahel rainfall. This study was inspired by the impressive model simulations of Sahel rainfall reported by Folland et al. and Rowell et al. The model was integrated from June through September with three different atmospheric initial conditions and four years (1950, 1958, 1983, and 1984) of SST. In three out of four cases (1950, 1983, 1984), the area-averaged simulated rainfall anomaly was consistent with the observations. However, the model’s internal variability was rather large. The simulated anomalies had relatively larger sensitivity to the initial conditions in this study than those in a desertification study performed previously by the authors. This model failed to simulate the rainfall anomaly for 1958. Additional model experiments are needed to establish the role of SST variation in determining the Sahel rainfall variation.
Abstract
A general circulation model sensitivity study was carried out to investigate the influence of global sea surface temperature (SST) on Sahel rainfall. This study was inspired by the impressive model simulations of Sahel rainfall reported by Folland et al. and Rowell et al. The model was integrated from June through September with three different atmospheric initial conditions and four years (1950, 1958, 1983, and 1984) of SST. In three out of four cases (1950, 1983, 1984), the area-averaged simulated rainfall anomaly was consistent with the observations. However, the model’s internal variability was rather large. The simulated anomalies had relatively larger sensitivity to the initial conditions in this study than those in a desertification study performed previously by the authors. This model failed to simulate the rainfall anomaly for 1958. Additional model experiments are needed to establish the role of SST variation in determining the Sahel rainfall variation.
Abstract
The Pennsylvania State University–NCAR Mesoscale Model (MM5) and a simplified simple biosphere (SSiB) scheme are modified and then coupled to study various regional climate and weather problems. These modifications include correcting the moisture and cloud hydrometeor fields to ensure the mass conservation; incorporating the effects of dissipative heating to ensure total energy conservation; decoupling soil and vegetation types in specifying various surface parameters; and eliminating the shortwave radiation reaching the surface at points where deep convection occurs.
A 30-day integration of June 1998 over the Midwest states was used to examine the model's capability in capturing the observed wet regional climate and the passage of several mesoscale weather events. It is found that the coupled model reproduces the distribution and magnitude of monthly accumulated precipitation, the time series of area-integrated precipitation, surface pressures, and diurnal changes in surface temperatures, low-level winds and precipitation, as well as the evolution of precipitation systems across the central United States. In particular, the model reproduces well many daily weather events, including the distribution and intensity of low-level temperature and pressure perturbations and precipitation, even up to a month. The results suggest that the daily temperature, clouds, and precipitation events from the weekly to monthly scales, as well as their associated regional climate phenomena, could be reasonably simulated if the surface, boundary layer, radiation, and convective processes are realistically parameterized, and the large-scale forcing could be reasonably provided by general circulation models.
Abstract
The Pennsylvania State University–NCAR Mesoscale Model (MM5) and a simplified simple biosphere (SSiB) scheme are modified and then coupled to study various regional climate and weather problems. These modifications include correcting the moisture and cloud hydrometeor fields to ensure the mass conservation; incorporating the effects of dissipative heating to ensure total energy conservation; decoupling soil and vegetation types in specifying various surface parameters; and eliminating the shortwave radiation reaching the surface at points where deep convection occurs.
A 30-day integration of June 1998 over the Midwest states was used to examine the model's capability in capturing the observed wet regional climate and the passage of several mesoscale weather events. It is found that the coupled model reproduces the distribution and magnitude of monthly accumulated precipitation, the time series of area-integrated precipitation, surface pressures, and diurnal changes in surface temperatures, low-level winds and precipitation, as well as the evolution of precipitation systems across the central United States. In particular, the model reproduces well many daily weather events, including the distribution and intensity of low-level temperature and pressure perturbations and precipitation, even up to a month. The results suggest that the daily temperature, clouds, and precipitation events from the weekly to monthly scales, as well as their associated regional climate phenomena, could be reasonably simulated if the surface, boundary layer, radiation, and convective processes are realistically parameterized, and the large-scale forcing could be reasonably provided by general circulation models.
Abstract
Off-line simulations of improved bucket hydrology and Simplified Simple Biosphere (SSiB) models are performed for a grassland vegetation catchment region, located at the Valdai water-balance research station in Russia, forced by observed meteorological and simulated actinometric data for 1966–83. Evaluation of the model simulations is performed using observations of total soil moisture in the top 1 m, runoff, evaporation, snow depth, and water-table depth made within the catchment. The Valdai study demonstrates that using only routine meteorological measurements, long-term simulations of land-surface schemes suitable for model evaluation can be made. The Valdai dataset is available for use in the evaluation of other land-surface schemes.
Both the SSiB and the bucket models reproduce the observed hydrology averaged over the simulation period (1967–83) and its interannual variability reasonably well. However, the models’ soil moisture interannual variability is too low during the fall and winter when compared to observations. In addition, some discrepancies in the models’ seasonal behavior with respect to observations are seen. The models are able to reproduce extreme hydrological events to some degree, but some inconsistencies in the model mechanisms are seen. The bucket model’s soil-moisture variability is limited by its inability to rise above its prescribed field capacity for the case where the observed water table rises into the top 1-m layer of soil, which can lead to erroneous simulations of evaporation and runoff. SSiB’s snow depth simulations are generally too low due to high evaporation from the snow surface. SSiB typically produces drainage out of its bottom layer during the summer, which appears inconsistent to the runoff observations of the catchment.
Abstract
Off-line simulations of improved bucket hydrology and Simplified Simple Biosphere (SSiB) models are performed for a grassland vegetation catchment region, located at the Valdai water-balance research station in Russia, forced by observed meteorological and simulated actinometric data for 1966–83. Evaluation of the model simulations is performed using observations of total soil moisture in the top 1 m, runoff, evaporation, snow depth, and water-table depth made within the catchment. The Valdai study demonstrates that using only routine meteorological measurements, long-term simulations of land-surface schemes suitable for model evaluation can be made. The Valdai dataset is available for use in the evaluation of other land-surface schemes.
Both the SSiB and the bucket models reproduce the observed hydrology averaged over the simulation period (1967–83) and its interannual variability reasonably well. However, the models’ soil moisture interannual variability is too low during the fall and winter when compared to observations. In addition, some discrepancies in the models’ seasonal behavior with respect to observations are seen. The models are able to reproduce extreme hydrological events to some degree, but some inconsistencies in the model mechanisms are seen. The bucket model’s soil-moisture variability is limited by its inability to rise above its prescribed field capacity for the case where the observed water table rises into the top 1-m layer of soil, which can lead to erroneous simulations of evaporation and runoff. SSiB’s snow depth simulations are generally too low due to high evaporation from the snow surface. SSiB typically produces drainage out of its bottom layer during the summer, which appears inconsistent to the runoff observations of the catchment.
