A high-resolution, one-dimensional, moist planetary boundary layer (PBL) model is developed following Blackadar, and verified using the 10 April 1979 SESAME data set. The model consists of two modules to predict the time-dependent behavior of the PBL under various surface characteristics. Under stable conditions, turbulent fluxes are related to a local Richardson number. In contrast, under conditions of free convection, the exchange of heat, moisture and momentum occurs through mixing between convective elements originating at the surface and environmental air in the PBL. Sensitivity tests showed that the daytime PBL structure is most sensitive to moisture availability, roughness length, albedo and thermal capacity, in that order. It is less sensitive in the nighttime to the above parameters. The wind profile is extremely sensitive to the specified geostrophic wind profile at all times. Simulations over both dry and moist terrain indicate that both the free convection (daytime) and the stable (no... Abstract A high-resolution, one-dimensional, moist planetary boundary layer (PBL) model is developed following Blackadar, and verified using the 10 April 1979 SESAME data set. The model consists of two modules to predict the time-dependent behavior of the PBL under various surface characteristics. Under stable conditions, turbulent fluxes are related to a local Richardson number. In contrast, under conditions of free convection, the exchange of heat, moisture and momentum occurs through mixing between convective elements originating at the surface and environmental air in the PBL. Sensitivity tests showed that the daytime PBL structure is most sensitive to moisture availability, roughness length, albedo and thermal capacity, in that order. It is less sensitive in the nighttime to the above parameters. The wind profile is extremely sensitive to the specified geostrophic wind profile at all times. Simulations over both dry and moist terrain indicate that both the free convection (daytime) and the stable (no...

One mechanism for climate change is the collected impact of changes in land cover or land use. Such changes are especially significant in urban areas where much of the world’s population lives. Satellite observations provide a basis for characterizing the physical modifications that result from urbanization. In particular, the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the National Aeronautics and Space Administration (NASA) Terra satellite measures surface spectral albedos, thermal emissivities, and radiative temperatures. A better understanding of these measurements should improve our knowledge of the climate impact of urbanization as well as our ability to specify the parameters needed by climate models to compute the impacts of urbanization. For this purpose, it is useful to contrast urban areas with neighboring nonurban surfaces with regard to their radiative surface temperatures, emissivities, and albedos. Among these properties, surface temperatures have been most extensively studied previously in the context of the “urban heat island” (UHI). Nevertheless, except for a few detailed studies, the UHI has mostly been characterized in terms of surface air temperatures. To provide a global analysis, the zonal average of these properties are presented here measured over urban areas versus neighboring nonurban areas. Furthermore, individual cities are examined to illustrate the variations of these variables with land cover under different climate conditions [e.g., in Beijing, New York, and Phoenix (a desert city of the United States)]. Satellite-measured skin temperatures are related to the surface air temperatures but do not necessarily have the same seasonal and diurnal variations, since they are more coupled to surface energy exchange processes and less to the overlying atmospheric column. Consequently, the UHI effects from skin temperature are shown to be pronounced at both daytime and nighttime, rather than at night as previously suggested from surface air temperature measurements. In addition, urban areas are characterized by albedos much lower than those of croplands and deciduous forests in summer but similar to those of forests in winter. Thus, urban surfaces can be distinguished from nonurban surfaces through use of a proposed index formed by multiplying skin temperature by albedo.

Urban heat island (UHI) effects can strengthen heat waves and air pollution episodes. In this study, the dampening impact of urban trees on the UHI during an extreme heat wave in the Washington, D.C., and Baltimore, Maryland, metropolitan area is examined by incorporating trees, soil, and grass into the coupled Weather Research and Forecasting model and an urban canopy model (WRF-UCM). By parameterizing the effects of these natural surfaces alongside roadways and buildings, the modified WRF-UCM is used to investigate how urban trees, soil, and grass dampen the UHI. The modified model was run with 50% tree cover over urban roads and a 10% decrease in the width of urban streets to make space for soil and grass alongside the roads and buildings. Results show that, averaged over all urban areas, the added vegetation decreases surface air temperature in urban street canyons by 4.1 K and road-surface and building-wall temperatures by 15.4 and 8.9 K, respectively, as a result of tree shading and evapotranspiration. These temperature changes propagate downwind and alter the temperature gradient associated with the Chesapeake Bay breeze and, therefore, alter the strength of the bay breeze. The impact of building height on the UHI shows that decreasing commercial building heights by 8 m and residential building heights by 2.5 m results in up to 0.4-K higher daytime surface and near-surface air temperatures because of less building shading and up to 1.2-K lower nighttime temperatures because of less longwave radiative trapping in urban street canyons.

In this study, the inner-core structures of Hurricane Andrew (1992) are explicitly simulated using an improved version of the Penn State–NCAR nonhydrostatic, two-way interactive, movable, triply nested grid mesoscale model (MM5). A modified Betts–Miller cumulus parameterization scheme and an explicit microphysics scheme were used simultaneously to simulate the evolution of the larger-scale flows over the coarser-mesh domains. The intense storm itself is explicitly resolved over the finest-mesh domain using a grid size of 6 km and an explicit microphysics package containing prognostic equations for cloud water, ice, rainwater, snow, and graupel. The model is initialized with the National Centers for Environmental Prediction analysis enhanced by a modified moisture field. A model-generated tropical-storm-like vortex was also incorporated. A 72-h integration was made, which covers the stages from the storm’s initial deepening to a near–category 5 hurricane intensity and the landfall over Florida. As... Abstract In this study, the inner-core structures of Hurricane Andrew (1992) are explicitly simulated using an improved version of the Penn State–NCAR nonhydrostatic, two-way interactive, movable, triply nested grid mesoscale model (MM5). A modified Betts–Miller cumulus parameterization scheme and an explicit microphysics scheme were used simultaneously to simulate the evolution of the larger-scale flows over the coarser-mesh domains. The intense storm itself is explicitly resolved over the finest-mesh domain using a grid size of 6 km and an explicit microphysics package containing prognostic equations for cloud water, ice, rainwater, snow, and graupel. The model is initialized with the National Centers for Environmental Prediction analysis enhanced by a modified moisture field. A model-generated tropical-storm-like vortex was also incorporated. A 72-h integration was made, which covers the stages from the storm’s initial deepening to a near–category 5 hurricane intensity and the landfall over Florida. As...

Previous studies have focused mostly on the roles of environmental factors in the rapid intensification (RI) of tropical cyclones (TCs) because of the lack of high-resolution data in inner-core regions. In this study, the RI of TCs is examined by analyzing the relationship between an upper-level warm core, convective bursts (CBs), sea surface temperature (SST), and surface pressure falls from 72-h cloud-permitting predictions of Hurricane Wilma (2005) with the finest grid size of 1 km. Results show that both the upper-level inertial stability increases and static stability decreases sharply 2–3 h prior to RI, and that the formation of an upper-level warm core, from the subsidence of stratospheric air associated with the detrainment of CBs, coincides with the onset of RI. It is found that the development of CBs precedes RI, but most subsidence warming radiates away by gravity waves and storm-relative flows. In contrast, many fewer CBs occur during RI, but more subsidence warming contributes to the balanced upper-level cyclonic circulation in the warm-core (as intense as 20°C) region. Furthermore, considerable CB activity can still take place in the outer eyewall as the storm weakens during its eyewall replacement. A sensitivity simulation, in which SSTs are reduced by 1°C, shows pronounced reductions in the upper-level warm-core intensity and CB activity. It is concluded that significant CB activity in the inner-core regions is an important ingredient in generating the upper-level warm core that is hydrostatically more efficient for the RI of TCs, given all of the other favorable environmental conditions.

The heaviest rainfall in 6 decades fell in Beijing on 21 July 2012 with a record‐breaking amount of 460 mm in 18 h and hourly rainfall rates exceeding 85 mm. This extreme rainfall event appeared to be reasonably well predicted by current operational models, albeit with notable timing and location errors. However, our analysis reveals that the model‐predicted rainfall results mainly from topographical lifting and the passage of a cold front, whereas the observed rainfall was mostly generated by convective cells that were triggered by local topography and then propagated along a quasi‐stationary linear convective system into Beijing. In particular, most of the extreme rainfall occurred in the warm sector far ahead of the cold front. Evidence from a cloud‐permitting simulation indicates the importance of using high‐resolution cloud‐permitting models to reproduce the above‐mentioned rainfall‐production mechanisms in order to more accurately predict the timing, distribution, and intensity of such an extreme event.