Extensive research sponsored by the DOD has been conducted to determine the feasibility of using a limited-area high-resolution numerical model as an alternative to generate local climate statistics around the globe. Many planning applications and simulations that are impacted by the environment require values for statistical parameters describing the local climate in great detail. The most obvious and direct way to obtain local climate statistics is to calculate them from long-term point observations. This method is being developed because of the limitations imposed on the use of long-term observational datasets. Long-term point observations are not available for large areas of the world and the representativeness and quality of observations change in time as observing sites are relocated, the land use around a site is changed or new instrumentation is used. In this research the numerical model approach involves determining local climate from a set of long period of mesoscale simulations.
The goal is to simulate the actual climate statistics for a particular period of time over a specified region. The objective is addressed by executing the model for a long period of time in a data assimilation mode and allowing the model to fuse the available data into a 3-D climatological dataset. In this mode the model continuously or periodically ingests the available observed data through one of several possible data assimilation techniques (Newtonian relaxation periodic reanalysis, etc.). The model then dynamically fuses the available observations with its knowledge of the surface characteristics of the earth and the basic principles of physics to generate estimates of local climate statistics at locations for which no observational data is available. This technique has been given the name CLImate statistics by a dynamical MODel (CLIMOD). The research has shown that the quality of the simulated climate statistics are significantly impacted several modeling factors to include the method of data assimilation, specific model configuration, model resolution and subgrid parameterization schemes.
The research has now been conducted for several different climate regimes around the world at a model resolution of 10 and 40 km. The focus of this presentation will be on the research issues involving the sensitivity of the simulated climate statistics to data assimilation techniques, model configuration, model resolution and subgrid parameterization schemes. The Air Force Climatology Center plans to modify a companion presentation to this presentation that will focus on the quality of the climate statistics produced in the various climate regimes.