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- Author or Editor: Mukul Tewari x
- Journal of Hydrometeorology x
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Abstract
To enhance the capability of models in better characterizing the urban water cycle, physical parameterizations of urban hydrological processes have been implemented into the single-layer urban canopy model in the widely used Weather Research and Forecasting (WRF) Model. While the new model has been evaluated offline against field measurements at various cities, its performance in online settings via coupling to atmospheric dynamics requires further examination. In this study, the impact of urban hydrological processes on regional hydrometeorology of the fully integrated WRF–urban modeling system for two major cities in the United States, namely, Phoenix and Houston, is assessed. Results show that including hydrological processes improves prediction of the 2-m dewpoint temperature, an indicative measure of coupled thermal and hydrological processes. The implementation of green roof systems as an urban mitigation strategy is then tested at the annual scale. The reduction of environmental temperature and increase of humidity by green roofs indicate strong diurnal and seasonal variations and are significantly affected by geographical and climatic conditions. Comparison with offline studies reveals that land–atmosphere interactions play a crucial role in determining the effect of green roofs.
Abstract
To enhance the capability of models in better characterizing the urban water cycle, physical parameterizations of urban hydrological processes have been implemented into the single-layer urban canopy model in the widely used Weather Research and Forecasting (WRF) Model. While the new model has been evaluated offline against field measurements at various cities, its performance in online settings via coupling to atmospheric dynamics requires further examination. In this study, the impact of urban hydrological processes on regional hydrometeorology of the fully integrated WRF–urban modeling system for two major cities in the United States, namely, Phoenix and Houston, is assessed. Results show that including hydrological processes improves prediction of the 2-m dewpoint temperature, an indicative measure of coupled thermal and hydrological processes. The implementation of green roof systems as an urban mitigation strategy is then tested at the annual scale. The reduction of environmental temperature and increase of humidity by green roofs indicate strong diurnal and seasonal variations and are significantly affected by geographical and climatic conditions. Comparison with offline studies reveals that land–atmosphere interactions play a crucial role in determining the effect of green roofs.
Abstract
Analyses of daytime fair-weather aircraft and surface-flux tower data from the May–June 2002 International H2O Project (IHOP_2002) and the April–May 1997 Cooperative Atmosphere Surface Exchange Study (CASES-97) are used to document the role of vegetation, soil moisture, and terrain in determining the horizontal variability of latent heat LE and sensible heat H along a 46-km flight track in southeast Kansas. Combining the two field experiments clearly reveals the strong influence of vegetation cover, with H maxima over sparse/dormant vegetation, and H minima over green vegetation; and, to a lesser extent, LE maxima over green vegetation, and LE minima over sparse/dormant vegetation. If the small number of cases is producing the correct trend, other effects of vegetation and the impact of soil moisture emerge through examining the slope ΔxyLE/Δxy H for the best-fit straight line for plots of time-averaged LE as a function of time-averaged H over the area. Based on the surface energy balance, H + LE = R net − G sfc, where R net is the net radiation and G sfc is the flux into the soil; R net − G sfc ∼ constant over the area implies an approximately −1 slope. Right after rainfall, H and LE vary too little horizontally to define a slope. After sufficient drying to produce enough horizontal variation to define a slope, a steep (∼−2) slope emerges. The slope becomes shallower and better defined with time as H and LE horizontal variability increases. Similarly, the slope becomes more negative with moister soils. In addition, the slope can change with time of day due to phase differences in H and LE. These trends are based on land surface model (LSM) runs and observations collected under nearly clear skies; the vegetation is unstressed for the days examined. LSM runs suggest terrain may also play a role, but observational support is weak.
Abstract
Analyses of daytime fair-weather aircraft and surface-flux tower data from the May–June 2002 International H2O Project (IHOP_2002) and the April–May 1997 Cooperative Atmosphere Surface Exchange Study (CASES-97) are used to document the role of vegetation, soil moisture, and terrain in determining the horizontal variability of latent heat LE and sensible heat H along a 46-km flight track in southeast Kansas. Combining the two field experiments clearly reveals the strong influence of vegetation cover, with H maxima over sparse/dormant vegetation, and H minima over green vegetation; and, to a lesser extent, LE maxima over green vegetation, and LE minima over sparse/dormant vegetation. If the small number of cases is producing the correct trend, other effects of vegetation and the impact of soil moisture emerge through examining the slope ΔxyLE/Δxy H for the best-fit straight line for plots of time-averaged LE as a function of time-averaged H over the area. Based on the surface energy balance, H + LE = R net − G sfc, where R net is the net radiation and G sfc is the flux into the soil; R net − G sfc ∼ constant over the area implies an approximately −1 slope. Right after rainfall, H and LE vary too little horizontally to define a slope. After sufficient drying to produce enough horizontal variation to define a slope, a steep (∼−2) slope emerges. The slope becomes shallower and better defined with time as H and LE horizontal variability increases. Similarly, the slope becomes more negative with moister soils. In addition, the slope can change with time of day due to phase differences in H and LE. These trends are based on land surface model (LSM) runs and observations collected under nearly clear skies; the vegetation is unstressed for the days examined. LSM runs suggest terrain may also play a role, but observational support is weak.
