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Abstract
This study investigates the capability of the dynamic downscaling method (DDM) in a North American regional climate study using the Eta/Simplified Simple Biosphere (SSiB) Regional Climate Model (RCM). The main objective is to understand whether the Eta/SSiB RCM is capable of simulating North American regional climate features, mainly precipitation, at different scales under imposed boundary conditions. The summer of 1998 was selected for this study and the summers of 1993 and 1995 were used to confirm the 1998 results. The observed precipitation, NCEP–NCAR Global Reanalysis (NNGR), and North American Regional Reanalysis (NARR) were used for evaluation of the model’s simulations and/or as lateral boundary conditions (LBCs). A spectral analysis was applied to quantitatively examine the RCM’s downscaling ability at different scales.
The simulations indicated that choice of domain size, LBCs, and grid spacing were crucial for the DDM. Several tests with different domain sizes indicated that the model in the North American climate simulation was particularly sensitive to its southern boundary position because of the importance of moisture transport by the southerly low-level jet (LLJ) in summer precipitation. Among these tests, only the RCM with 32-km resolution and NNGR LBC or with 80-km resolution and NARR LBC, in conjunction with appropriate domain sizes, was able to properly simulate precipitation and other atmospheric variables—especially humidity over the southeastern United States—during all three summer months—and produce a better spectral power distribution than that associated with the imposed LBC (for the 32-km case) and retain spectral power for large wavelengths (for the 80-km case). The analysis suggests that there might be strong atmospheric components of high-frequency variability over the Gulf of Mexico and the southeastern United States.
Abstract
This study investigates the capability of the dynamic downscaling method (DDM) in a North American regional climate study using the Eta/Simplified Simple Biosphere (SSiB) Regional Climate Model (RCM). The main objective is to understand whether the Eta/SSiB RCM is capable of simulating North American regional climate features, mainly precipitation, at different scales under imposed boundary conditions. The summer of 1998 was selected for this study and the summers of 1993 and 1995 were used to confirm the 1998 results. The observed precipitation, NCEP–NCAR Global Reanalysis (NNGR), and North American Regional Reanalysis (NARR) were used for evaluation of the model’s simulations and/or as lateral boundary conditions (LBCs). A spectral analysis was applied to quantitatively examine the RCM’s downscaling ability at different scales.
The simulations indicated that choice of domain size, LBCs, and grid spacing were crucial for the DDM. Several tests with different domain sizes indicated that the model in the North American climate simulation was particularly sensitive to its southern boundary position because of the importance of moisture transport by the southerly low-level jet (LLJ) in summer precipitation. Among these tests, only the RCM with 32-km resolution and NNGR LBC or with 80-km resolution and NARR LBC, in conjunction with appropriate domain sizes, was able to properly simulate precipitation and other atmospheric variables—especially humidity over the southeastern United States—during all three summer months—and produce a better spectral power distribution than that associated with the imposed LBC (for the 32-km case) and retain spectral power for large wavelengths (for the 80-km case). The analysis suggests that there might be strong atmospheric components of high-frequency variability over the Gulf of Mexico and the southeastern United States.
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.
Abstract
When compared with differences in snow accumulation predicted by widely used hydrological models, there is a much greater divergence among otherwise “good” models in their simulation of the snow ablation process. Here, we explore differences in the performance of the Variable Infiltration Capacity model (VIC), Noah land surface model with multiparameterization options (Noah-MP), the Catchment model, and the third-generation Simplified Simple Biosphere model (SiB3) in their ability to reproduce observed snow water equivalent (SWE) during the ablation season at 10 Snowpack Telemetry (SNOTEL) stations over 1992–2012. During the ablation period, net radiation generally has stronger correlations with observed melt rates than does air temperature. Average ablation rates tend to be higher (in both model predictions and observations) at stations with a large accumulation of SWE. The differences in the dates of last snow between models and observations range from several days to approximately a month (on average 5.1 days earlier than in observations). If the surface cover in the models is changed from observed vegetation to bare soil in all of the models, only the melt rate of the VIC model increases. The differences in responses of models to canopy removal are directly related to snowpack energy inputs, which are further affected by different algorithms for surface albedo and energy allocation across the models. We also find that the melt rates become higher in VIC and lower in Noah-MP if the shrub/grass present at the observation sites is switched to trees.
Abstract
When compared with differences in snow accumulation predicted by widely used hydrological models, there is a much greater divergence among otherwise “good” models in their simulation of the snow ablation process. Here, we explore differences in the performance of the Variable Infiltration Capacity model (VIC), Noah land surface model with multiparameterization options (Noah-MP), the Catchment model, and the third-generation Simplified Simple Biosphere model (SiB3) in their ability to reproduce observed snow water equivalent (SWE) during the ablation season at 10 Snowpack Telemetry (SNOTEL) stations over 1992–2012. During the ablation period, net radiation generally has stronger correlations with observed melt rates than does air temperature. Average ablation rates tend to be higher (in both model predictions and observations) at stations with a large accumulation of SWE. The differences in the dates of last snow between models and observations range from several days to approximately a month (on average 5.1 days earlier than in observations). If the surface cover in the models is changed from observed vegetation to bare soil in all of the models, only the melt rate of the VIC model increases. The differences in responses of models to canopy removal are directly related to snowpack energy inputs, which are further affected by different algorithms for surface albedo and energy allocation across the models. We also find that the melt rates become higher in VIC and lower in Noah-MP if the shrub/grass present at the observation sites is switched to trees.
Abstract
The simplified Simple Biosphere model (SSiB) has been validated using observed meteorological, turbulent flux, and vegetation property data from the Anglo-Brazilian Amazonian Climate Observation Study (ABRACOS) over a forest clearing site. The results show that SSiB is able to simulate the observed fluxes realistically. The differences between the simulated and observed latent and sensible heat fluxes are less than 10 W m−2. Compared to previous deforestation experiments, the new vegetation dataset produces significantly different latent heat fluxes and surface temperatures in off-line and general circulation model (GCM) simulation. Using the new dataset the GCM simulated surface temperature is about 2 K higher, and the simulated latent heat flux is about 25 W m−2 lower than that generated using a previous dataset. These differences can be expected to result in substantially different responses in rainfall and atmosphere circulation. The parameters that are most significant in producing such large differences are leaf area index and soil properties. This study again demonstrates that to realistically assess the climatic impact of land surface degradation a realistic specification of the land surface conditions within GCMs is crucial.
Abstract
The simplified Simple Biosphere model (SSiB) has been validated using observed meteorological, turbulent flux, and vegetation property data from the Anglo-Brazilian Amazonian Climate Observation Study (ABRACOS) over a forest clearing site. The results show that SSiB is able to simulate the observed fluxes realistically. The differences between the simulated and observed latent and sensible heat fluxes are less than 10 W m−2. Compared to previous deforestation experiments, the new vegetation dataset produces significantly different latent heat fluxes and surface temperatures in off-line and general circulation model (GCM) simulation. Using the new dataset the GCM simulated surface temperature is about 2 K higher, and the simulated latent heat flux is about 25 W m−2 lower than that generated using a previous dataset. These differences can be expected to result in substantially different responses in rainfall and atmosphere circulation. The parameters that are most significant in producing such large differences are leaf area index and soil properties. This study again demonstrates that to realistically assess the climatic impact of land surface degradation a realistic specification of the land surface conditions within GCMs is crucial.
Abstract
Land-use and land-cover change (LULCC) is one of the most important forcings affecting climate in the past century. This study evaluates the global and regional LULCC impacts in 1950–2015 by employing an annually updated LULCC map in a coupled land–atmosphere–ocean model. The difference between LULCC and control experiments shows an overall land surface temperature (LST) increase by 0.48 K in the LULCC regions and a widespread LST decrease by 0.18 K outside the LULCC regions. A decomposed temperature metric (DTM) is applied to quantify the relative contribution of surface processes to temperature changes. Furthermore, while precipitation in the LULCC areas is reduced in agreement with declined evaporation, LULCC causes a southward displacement of the intertropical convergence zone (ITCZ) with a narrowing by 0.5°, leading to a tripole anomalous precipitation pattern over the warm pool. The DTM shows that the temperature response in LULCC regions results from the competing effect between increased albedo (cooling) and reduced evaporation (warming). The reduced evaporation indicates less atmospheric latent heat release in convective processes and thus a drier and cooler troposphere, resulting in a reduction in surface cooling outside the LULCC regions. The southward shift of the ITCZ implies a northward cross-equatorial energy transport anomaly in response to reduced latent/sensible heat of the atmosphere in the Northern Hemisphere, where LULCC is more intensive. Tropospheric cooling results in the equatorward shift of the upper-tropospheric westerly jet in both hemispheres, which, in turn, leads to an equatorward narrowing of the Hadley circulation and ITCZ.
Abstract
Land-use and land-cover change (LULCC) is one of the most important forcings affecting climate in the past century. This study evaluates the global and regional LULCC impacts in 1950–2015 by employing an annually updated LULCC map in a coupled land–atmosphere–ocean model. The difference between LULCC and control experiments shows an overall land surface temperature (LST) increase by 0.48 K in the LULCC regions and a widespread LST decrease by 0.18 K outside the LULCC regions. A decomposed temperature metric (DTM) is applied to quantify the relative contribution of surface processes to temperature changes. Furthermore, while precipitation in the LULCC areas is reduced in agreement with declined evaporation, LULCC causes a southward displacement of the intertropical convergence zone (ITCZ) with a narrowing by 0.5°, leading to a tripole anomalous precipitation pattern over the warm pool. The DTM shows that the temperature response in LULCC regions results from the competing effect between increased albedo (cooling) and reduced evaporation (warming). The reduced evaporation indicates less atmospheric latent heat release in convective processes and thus a drier and cooler troposphere, resulting in a reduction in surface cooling outside the LULCC regions. The southward shift of the ITCZ implies a northward cross-equatorial energy transport anomaly in response to reduced latent/sensible heat of the atmosphere in the Northern Hemisphere, where LULCC is more intensive. Tropospheric cooling results in the equatorward shift of the upper-tropospheric westerly jet in both hemispheres, which, in turn, leads to an equatorward narrowing of the Hadley circulation and ITCZ.
Abstract
Soil moisture observations in sites with natural vegetation were made for several decades in the former Soviet Union at hundreds of stations. In this paper, the authors use data from six of these stations from different climatic regimes, along with ancillary meteorological and actinometric data, to demonstrate a method to validate soil moisture simulations with biosphere and bucket models. Some early and current general circulation models (GCMS) use bucket models for soil hydrology calculations. More recently, the Simple Biosphere Model (SiB) was developed to incorporate the effects of vegetation on fluxes of moisture, momentum, and energy at the earth's surface into soil hydrology models. Until now, the bucket and SiB have been verified by comparison with actual soil moisture data only on a limited basis. In this study, a Simplified SiB (SSIB) soil hydrology model and a 15-cm bucket model are forced by observed meteorological and actinometric data every 3 h for 6-yr simulations at the six stations. The model calculations of soil moisture are compared to observations of soil moisture, literally “ground truth,” snow cover, surface albedo, and net radiation” and with each other.
For three of the stations, the SSIB and 15-cm bucket models produce good simulations of seasonal cycles and interannual variations of soil moisture. For the other three stations, there are large errors in the simulations by both models. Inconsistencies in specification of field capacity may be partly responsible. There is no evidence that the SSiB simulations are superior in simulating soil moisture variations. In fact, the models are quite similar since SSiB implicitly has a bucket embedded in it. One of the main differences between the models is in the treatment of runoff due to melting snow in the spring-SSiB incorrectly puts all the snowmelt into runoff. While producing similar soil moisture simulations, the models produce very different surface latent and sensible beat fluxes, which would have large effects on GCM simulations.
Abstract
Soil moisture observations in sites with natural vegetation were made for several decades in the former Soviet Union at hundreds of stations. In this paper, the authors use data from six of these stations from different climatic regimes, along with ancillary meteorological and actinometric data, to demonstrate a method to validate soil moisture simulations with biosphere and bucket models. Some early and current general circulation models (GCMS) use bucket models for soil hydrology calculations. More recently, the Simple Biosphere Model (SiB) was developed to incorporate the effects of vegetation on fluxes of moisture, momentum, and energy at the earth's surface into soil hydrology models. Until now, the bucket and SiB have been verified by comparison with actual soil moisture data only on a limited basis. In this study, a Simplified SiB (SSIB) soil hydrology model and a 15-cm bucket model are forced by observed meteorological and actinometric data every 3 h for 6-yr simulations at the six stations. The model calculations of soil moisture are compared to observations of soil moisture, literally “ground truth,” snow cover, surface albedo, and net radiation” and with each other.
For three of the stations, the SSIB and 15-cm bucket models produce good simulations of seasonal cycles and interannual variations of soil moisture. For the other three stations, there are large errors in the simulations by both models. Inconsistencies in specification of field capacity may be partly responsible. There is no evidence that the SSiB simulations are superior in simulating soil moisture variations. In fact, the models are quite similar since SSiB implicitly has a bucket embedded in it. One of the main differences between the models is in the treatment of runoff due to melting snow in the spring-SSiB incorrectly puts all the snowmelt into runoff. While producing similar soil moisture simulations, the models produce very different surface latent and sensible beat fluxes, which would have large effects on GCM simulations.
Abstract
A global and seasonal assessment of regions of the earth with strong climate–vegetation biophysical process (VBP) interactions is provided. The presence of VBP and degree of VBP effects on climate were assessed based on the skill of simulations of observed global precipitation by two general circulation models of the atmosphere coupled to three land models with varying degrees of complexity in VBP representation. The simulated VBP effects on precipitation were estimated to be about 10% of observed precipitation globally and 40% over land; the strongest impacts were in the monsoon regions. Among these, VBP impacts were highest on the West African, South Asian, East Asian, and South American monsoons. The specific characteristics of vegetation–precipitation interactions in northern high latitudes were identified. Different regions had different primary impact season(s) depending on regional climate characteristics and geographical features. The characteristics of VBP effects on surface energy and water balance as well as their interactions were also analyzed. The VBP-induced change in evaporation was the dominant factor in modulating the surface energy and water balance. The land–cloud interaction had substantial effects in the feedback. Meanwhile, the monsoon regions, midlatitudes lands, and high-latitude lands each exhibited quite different characteristics in circulation response to surface heating changes. This study is the first to compare simulations with observations to identify and assess global seasonal mean VBP feedback effects. It is concluded that VBPs are a major component of the global water cycle.
Abstract
A global and seasonal assessment of regions of the earth with strong climate–vegetation biophysical process (VBP) interactions is provided. The presence of VBP and degree of VBP effects on climate were assessed based on the skill of simulations of observed global precipitation by two general circulation models of the atmosphere coupled to three land models with varying degrees of complexity in VBP representation. The simulated VBP effects on precipitation were estimated to be about 10% of observed precipitation globally and 40% over land; the strongest impacts were in the monsoon regions. Among these, VBP impacts were highest on the West African, South Asian, East Asian, and South American monsoons. The specific characteristics of vegetation–precipitation interactions in northern high latitudes were identified. Different regions had different primary impact season(s) depending on regional climate characteristics and geographical features. The characteristics of VBP effects on surface energy and water balance as well as their interactions were also analyzed. The VBP-induced change in evaporation was the dominant factor in modulating the surface energy and water balance. The land–cloud interaction had substantial effects in the feedback. Meanwhile, the monsoon regions, midlatitudes lands, and high-latitude lands each exhibited quite different characteristics in circulation response to surface heating changes. This study is the first to compare simulations with observations to identify and assess global seasonal mean VBP feedback effects. It is concluded that VBPs are a major component of the global water cycle.
Abstract
Degradation of the land surface has been suggested as a cause of persistent drought in tropical north Africa. A general circulation model is used to assess the impact of degradation of five regions within tropical north Africa. Idealized degradation scenarios are used since existing observations are inadequate to determine the extent and severity of historical degradation. It is found that the impact of degradation varies between the regions. The greatest effects are found from degradation of the Sahel or West Africa, which result in substantial reduction of precipitation over the degraded area. Both surface evaporation and atmospheric moisture convergence are reduced. In the Sahelian case the precipitation reduction extends well to the south of the area of changed land surface. The occurrence of easterly wave disturbances is not altered by degradation, but the mean rainfall from each event is reduced. Degradation of an area in eastern north Africa results in smaller reductions of precipitation and moisture convergence. Finally, degradation of a southern area next to the Gulf of Guinea has little effect on precipitation because of a compensatory increase of moisture convergence. The simulated rainfall reduction following degradation of the Sahel is comparable to observed changes in recent decades, suggesting that degradation may have contributed to that change.
Abstract
Degradation of the land surface has been suggested as a cause of persistent drought in tropical north Africa. A general circulation model is used to assess the impact of degradation of five regions within tropical north Africa. Idealized degradation scenarios are used since existing observations are inadequate to determine the extent and severity of historical degradation. It is found that the impact of degradation varies between the regions. The greatest effects are found from degradation of the Sahel or West Africa, which result in substantial reduction of precipitation over the degraded area. Both surface evaporation and atmospheric moisture convergence are reduced. In the Sahelian case the precipitation reduction extends well to the south of the area of changed land surface. The occurrence of easterly wave disturbances is not altered by degradation, but the mean rainfall from each event is reduced. Degradation of an area in eastern north Africa results in smaller reductions of precipitation and moisture convergence. Finally, degradation of a southern area next to the Gulf of Guinea has little effect on precipitation because of a compensatory increase of moisture convergence. The simulated rainfall reduction following degradation of the Sahel is comparable to observed changes in recent decades, suggesting that degradation may have contributed to that change.