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- Author or Editor: K. W. Oleson x
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Abstract
The characteristics of satellite-derived land-cover data for climate models vary depending on sensor properties and processing options. To better understand the first-order effects of differences in land-cover data on a land surface parameterization scheme (VBATS), stand-alone model runs were performed for two adjacent 2.8° × 2.8° GCM grid cells in Wyoming using land cover from two satellite-derived maps (AVHRR, TM) and a global land-cover dataset commonly used in GCMs.
The dominant cover type by area differed among the datasets for both grid cells. In the western grid cell, these differences resulted in substantially different surface fluxes simulated by VBATS. At spatial resolutions of 0.2° and 0.4°, the two satellite-derived datasets agreed on only 54%–62% of the land-cover types in both grid cells. Despite this disagreement, the VBATS simulated surface fluxes averaged over the grid cell were similar in the eastern grid cell for the two satellite-derived datasets. In the western grid cell, the partitioning of net radiation into sensible and latent heat fluxes was influenced by the dataset prescriptions of land-cover heterogeneity. In particular, the relative proportions of wet cover types (i.e., inland water and irrigated crop) had an effect on this partitioning, emphasizing the importance of accounting for the presence of wet cover types within a GCM grid cell in arid regions.
Spatial aggregation of the satellite-derived datasets reduced the number of land-cover types prescribed for each GCM grid cell. In the western grid cell, the reduction in the number of cover types from 11 to 2 resulted in differences in annual averages of sensible and latent heat fluxes of about 10%. Other simulations involving these datasets suggest that these differences could be reduced if one accounted for the wet cover types. In this respect, fine spatial resolution is required for some cover types, whereas coarser resolution may be adequate for other types. Land-cover classifications for land surface modeling need to be based more on model sensitivities than on traditional vegetation-type schemes.
Abstract
The characteristics of satellite-derived land-cover data for climate models vary depending on sensor properties and processing options. To better understand the first-order effects of differences in land-cover data on a land surface parameterization scheme (VBATS), stand-alone model runs were performed for two adjacent 2.8° × 2.8° GCM grid cells in Wyoming using land cover from two satellite-derived maps (AVHRR, TM) and a global land-cover dataset commonly used in GCMs.
The dominant cover type by area differed among the datasets for both grid cells. In the western grid cell, these differences resulted in substantially different surface fluxes simulated by VBATS. At spatial resolutions of 0.2° and 0.4°, the two satellite-derived datasets agreed on only 54%–62% of the land-cover types in both grid cells. Despite this disagreement, the VBATS simulated surface fluxes averaged over the grid cell were similar in the eastern grid cell for the two satellite-derived datasets. In the western grid cell, the partitioning of net radiation into sensible and latent heat fluxes was influenced by the dataset prescriptions of land-cover heterogeneity. In particular, the relative proportions of wet cover types (i.e., inland water and irrigated crop) had an effect on this partitioning, emphasizing the importance of accounting for the presence of wet cover types within a GCM grid cell in arid regions.
Spatial aggregation of the satellite-derived datasets reduced the number of land-cover types prescribed for each GCM grid cell. In the western grid cell, the reduction in the number of cover types from 11 to 2 resulted in differences in annual averages of sensible and latent heat fluxes of about 10%. Other simulations involving these datasets suggest that these differences could be reduced if one accounted for the wet cover types. In this respect, fine spatial resolution is required for some cover types, whereas coarser resolution may be adequate for other types. Land-cover classifications for land surface modeling need to be based more on model sensitivities than on traditional vegetation-type schemes.
Abstract
In a companion paper, the authors presented a formulation and evaluation of an urban parameterization designed to represent the urban energy balance in the Community Land Model. Here the robustness of the model is tested through sensitivity studies and the model’s ability to simulate urban heat islands in different environments is evaluated. Findings show that heat storage and sensible heat flux are most sensitive to uncertainties in the input parameters within the atmospheric and surface conditions considered here. The sensitivity studies suggest that attention should be paid not only to characterizing accurately the structure of the urban area (e.g., height-to-width ratio) but also to ensuring that the input data reflect the thermal admittance properties of each of the city surfaces. Simulations of the urban heat island show that the urban model is able to capture typical observed characteristics of urban climates qualitatively. In particular, the model produces a significant heat island that increases with height-to-width ratio. In urban areas, daily minimum temperatures increase more than daily maximum temperatures, resulting in a reduced diurnal temperature range relative to equivalent rural environments. The magnitude and timing of the heat island vary tremendously depending on the prevailing meteorological conditions and the characteristics of surrounding rural environments. The model also correctly increases the Bowen ratio and canopy air temperatures of urban systems as impervious fraction increases. In general, these findings are in agreement with those observed for real urban ecosystems. Thus, the model appears to be a useful tool for examining the nature of the urban climate within the framework of global climate models.
Abstract
In a companion paper, the authors presented a formulation and evaluation of an urban parameterization designed to represent the urban energy balance in the Community Land Model. Here the robustness of the model is tested through sensitivity studies and the model’s ability to simulate urban heat islands in different environments is evaluated. Findings show that heat storage and sensible heat flux are most sensitive to uncertainties in the input parameters within the atmospheric and surface conditions considered here. The sensitivity studies suggest that attention should be paid not only to characterizing accurately the structure of the urban area (e.g., height-to-width ratio) but also to ensuring that the input data reflect the thermal admittance properties of each of the city surfaces. Simulations of the urban heat island show that the urban model is able to capture typical observed characteristics of urban climates qualitatively. In particular, the model produces a significant heat island that increases with height-to-width ratio. In urban areas, daily minimum temperatures increase more than daily maximum temperatures, resulting in a reduced diurnal temperature range relative to equivalent rural environments. The magnitude and timing of the heat island vary tremendously depending on the prevailing meteorological conditions and the characteristics of surrounding rural environments. The model also correctly increases the Bowen ratio and canopy air temperatures of urban systems as impervious fraction increases. In general, these findings are in agreement with those observed for real urban ecosystems. Thus, the model appears to be a useful tool for examining the nature of the urban climate within the framework of global climate models.
Abstract
Urbanization, the expansion of built-up areas, is an important yet less-studied aspect of land use/land cover change in climate science. To date, most global climate models used to evaluate effects of land use/land cover change on climate do not include an urban parameterization. Here, the authors describe the formulation and evaluation of a parameterization of urban areas that is incorporated into the Community Land Model, the land surface component of the Community Climate System Model. The model is designed to be simple enough to be compatible with structural and computational constraints of a land surface model coupled to a global climate model yet complex enough to explore physically based processes known to be important in determining urban climatology. The city representation is based upon the “urban canyon” concept, which consists of roofs, sunlit and shaded walls, and canyon floor. The canyon floor is divided into pervious (e.g., residential lawns, parks) and impervious (e.g., roads, parking lots, sidewalks) fractions. Trapping of longwave radiation by canyon surfaces and solar radiation absorption and reflection is determined by accounting for multiple reflections. Separate energy balances and surface temperatures are determined for each canyon facet. A one-dimensional heat conduction equation is solved numerically for a 10-layer column to determine conduction fluxes into and out of canyon surfaces. Model performance is evaluated against measured fluxes and temperatures from two urban sites. Results indicate the model does a reasonable job of simulating the energy balance of cities.
Abstract
Urbanization, the expansion of built-up areas, is an important yet less-studied aspect of land use/land cover change in climate science. To date, most global climate models used to evaluate effects of land use/land cover change on climate do not include an urban parameterization. Here, the authors describe the formulation and evaluation of a parameterization of urban areas that is incorporated into the Community Land Model, the land surface component of the Community Climate System Model. The model is designed to be simple enough to be compatible with structural and computational constraints of a land surface model coupled to a global climate model yet complex enough to explore physically based processes known to be important in determining urban climatology. The city representation is based upon the “urban canyon” concept, which consists of roofs, sunlit and shaded walls, and canyon floor. The canyon floor is divided into pervious (e.g., residential lawns, parks) and impervious (e.g., roads, parking lots, sidewalks) fractions. Trapping of longwave radiation by canyon surfaces and solar radiation absorption and reflection is determined by accounting for multiple reflections. Separate energy balances and surface temperatures are determined for each canyon facet. A one-dimensional heat conduction equation is solved numerically for a 10-layer column to determine conduction fluxes into and out of canyon surfaces. Model performance is evaluated against measured fluxes and temperatures from two urban sites. Results indicate the model does a reasonable job of simulating the energy balance of cities.
