Focus Area:
Regional Scale Climate Models

To provide sound science for policy-making recommendations, it is imperative to have atmospheric models that include correct descriptions of physical and chemical processes.   Currently, the AIRMAP Regional Climate Modeling System (RCMS) is our principal tool for seasonal to decadal simulations of regional climate.   The RCMS is a fully coupled soil-biosphere-atmosphere modeling system tuned to study the interactions between climate and biogenic emissions, a critical component for understanding New England air quality.   In addition to model applications, modifications in the RCMS with initial efforts in the planetary boundary layer and radiation schemes are being implemented to improve the model's capability to correctly simulate surface processes and long-term effects of increased greenhouse gases.

The planetary boundary layer scheme that is currently in use in the RCMS needs to be improved to better simulate wind fields.   To depict the vertical mixing processes of pollutants accurately, it is critical to capture the diurnal cycles of surface and PBL winds.   This requires realistic parameterization of sub-grid scale physical processes, especially the processes that transfer turbulent heat, moisture, and momentum fluxes. Most PBL schemes focus on the diurnal variation in surface temperature.   Spatial winds are treated as a dynamical response to a thermal gradient, which leads to unrealistic and variable simulations of wind speed and direction in the PBL, particularly near the surface. Following Noh et al ., [2003], we will modify the calculation of the velocity scale to make it height-dependent within the PBL.

The current radiation scheme needs to be updated to better simulate the greenhouse effect and to maintain physical consistency in the model.   Solar radiation is the driver of photochemical processes and the energy budget.   The CCM2 radiation scheme is used to describe the flow of radiation energy through the climate system.   This radiation scheme has great limitations in cloud simulations, which have proven to induce large bias in cloud radiative forcing. Due to overestimation of cloud water in CCM2, solar radiation is greatly underestimated in the RCMS over the U.S. east coast in summer.   Subsequently, this affects the simulations of temperature, precipitation, and circulation patterns through thermal-dynamical feedbacks within the entire climate system.   We propose to replace the CCM2 radiation scheme currently used in the RCMS with CCM3 which accounts for the effects of trace greenhouse gases, has improved cloud radiative properties, and is consistent with the large-scale forcing for our RCMS.