[1] The common methodology in dynamical regional climate downscaling employs a continuous integration of a limited-area model with a single initialization of the atmospheric fields and frequent updates of lateral boundary conditions based on general circulation model outputs or reanalysis data sets. This study suggests alternative methods that can be more skillful than the traditional one in obtaining high-resolution climate information. We use the Weather Research and Forecasting (WRF) model with a grid spacing at 36 km over the conterminous U.S. to dynamically downscale the 1-degree NCEP Global Final Analysis (FNL). We perform three types of experiments for the entire year of 2000: (1) continuous integrations with a single initialization as usually done, (2) consecutive integrations with frequent re-initializations, and (3) as (1) but with a 3-D nudging being applied. The simulations are evaluated in a high temporal scale (6-hourly) by comparison with the 32-km NCEP North American Regional Reanalysis (NARR). Compared to NARR, the downscaling simulation using the 3-D nudging shows the highest skill, and the continuous run produces the lowest skill. While the re-initialization runs give an intermediate skill, a run with a more frequent (e.g., weekly) re-initialization outperforms that with the less frequent re-initialization (e.g., monthly). Dynamical downscaling outperforms bi-linear interpolation, especially for meteorological fields near the surface over the mountainous regions. The 3-D nudging generates realistic regional-scale patterns that are not resolved by simply updating the lateral boundary conditions as done traditionally, therefore significantly improving the accuracy of generating regional climate information.

The Pearl River Delta (PRD) region, located in the southern part of Guangdong Province in China, is one of the most rapidly developing regions in the world. The evolution of local and regional sea-breeze circulation (SBC) is believed to be responsible for forming meteorological conditions for high air-pollution episodes in the PRD. To understand better the impacts of urbanization and its associated urban heat island (UHI) on the local- and regional-scale atmospheric circulations over PRD, a number of high-resolution numerical experiments, with different approaches to treat the land surface and urban processes, have been conducted using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). The results show that an accurate urban land-use dataset and a proper urban land-use parameterization are critical for the mesoscale model to capture the major features of the observed UHI effect and land–sea-breeze circulations in the PRD. Stronger UHI in the PRD increases the differential temperature gradient between urbanized areas and nearby ocean surface and hence enhances the mesoscale SBC. The SBC front consequently penetrates farther inland to overcome the prevailing easterly flow in the western part of inland Hong Kong. Additional sensitivity studies indicate that further industrial development and urbanization will strengthen the daytime SBC as well as increase the air temperature in the lowest 2 km of the atmosphere.

[1] This paper studies the effects of climate change under future A1B scenario and land use change on surface ozone (O 3 ) in the greater Houston, Texas, area. We applied the Weather Research and Forecasting Model with Chemistry (WRF/Chem) to the Houston area for August of current (2001)(2002)(2003) and future (2051-2053) years. The model was forced by downscaled 6-hourly Community Climate System Model (CCSM) version 3 outputs. High-resolution current year land use data from National Land Cover Database (NLCDF) and future year land use distribution based on projected population density for the Houston area were used in the WRF/Chem model coupled with an Urban Canopy Model (UCM). Our simulations show that there is generally a 2°C increase in near-surface temperature over much of the modeling domain due to future climate and land use changes. In the urban area, the effect of climate change alone accounts for an increase of 2.6 ppb in daily maximum 8-h O 3 concentrations, and a 62% increase of urban land use area exerts more influence than does climate change. The combined effect of the two factors on O 3 concentrations can be up to 6.2 ppb. The impacts of climate and land use change on O 3 concentrations differ across the various areas of the domain. The increase in extreme O 3 days can be up to 4-5 days in August, in which land use contributes to 2-3 days' increase. Additional sensitivity experiments show that the effect of future anthropogenic emissions change is on the same order of those induced by climate and land use change on extreme O 3 days.

[1] Recent satellite observations show that a layer of haze perpetually hangs over the Pearl River Delta (PRD) region and surface observations show numerous violations of the Hong Kong Air Quality Objective. This layer of haze mostly concentrates in the Pearl River Estuary and a narrow (20 km wide) band along the shoreline, in particular during weak wind situations. Although researchers suspect the land-sea breeze (LSB) circulations ''concentrate'' or ''trap'' various pollutants in this region, the physical mechanism of the phenomenon has never been fully explained or quantified. In this paper, a mesoscale atmospheric model (MM5) coupled with the Noah land surface model (LSM), which has bulk urban land use treatments along with a detailed Pearl River Delta land use map, is used to investigate the unique feature and mechanism of this land-sea breeze effect and the temporal evolution. A three-dimensional particle trajectory model is used to understand its associated pollutant transport, trapping and accumulation. A conceptual model is then developed for the perpetual air pollution phenomenon in the region. Further sensitivity experiments are used to illustrate the impact of urbanization and large-scale winds on the pollution processes. Results show that urbanization enhances the pollutant trapping and therefore contributes to the overall poor air quality in the region.