High Resolution Climate Analysis and Prediction

The Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) has concluded that global warming is "unequivocal", with discernible changes in ocean temperatures, continental–average temperatures, temperature extremes, and wind patterns, all of which have far reaching socioeconomic and ecologic impacts. Now, more than ever, there is a compelling need for accurate information about the local, regional, and global climate, how it has evolved in the past, how it is likely to change in the future, and how it has and will impact human activities. These impacted activities include agriculture and energy production and consumption (especially renewable energy sources such as solar, wind, and hydropower). Ecological impacts that directly affect humanity include the spread of disease, the reliability of water resources, and the effects on plant and animal life. But before the impacts of future climate change can be understood and assessed, we must understand the climate of the recent past, say within the past 20–40 years.

Many long–term, global gridded reconstructions of observations exist to fill this need, but because of the sheer computational expense associated with creating these datasets, they are typically done on a coarse grid (grid cells that are ∼250 km on a side) with output available only every 6 h. These analyses fail to account for the local influences on weather and climate of small to modest–sized land–surface features and water bodies, and they only marginally represent the effects of the daily heating cycle.

To meet this ever–growing need, NCAR's RAL has developed the Climate Four Dimensional Data Assimilation System (ClimoFDDA), originally based upon the Penn State/NCAR MM5 model, and now the NCAR WRF Model. ClimoFDDA uses global–scale data from a long term analysis (such as the NCEP/NCAR Reanalysis, or the European Center for Medium Range Weather Forecasting Reanalysis); standard surface and upper observations; and satellite–derived estimates of winds, temperature, and humidity to map the global climate information to the local region, while fully accounting for topographic variations and surface characteristics (e.g., crop lands, lakes, dense urban areas, etc.).

Primary Contacts