COAPS Climate Variability

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Climate Variability

Climate Versus Weather - In general, climate is defined by the long-term (monthly or longer) pattern of weather conditions in a given region. Climate is not the same as weather, as weather deals with short-term variations tied to them movement and development of individual weather systems (fronts, cyclones, air masses). The earth's climate is now recognized as a dynamic system, with regional variations on many different time scales from seasonal, to year-to-year, up to decades and even longer.

Heat Island Effect for Atlanta, GA An example of our climate variability studies is a look at variations in daily maximum and minimum temperatures across the United States. This study examines the trends in temperature at both automated national weather service sites and cooperative observing stations.

Additional climate variability activities at the Center for Ocean-Atmospheric Prediction Studies (COAPS) include: (1) dynamical forecasting/hindcasting of Northern Hemisphere tropical Atlantic basin hurricane activity; (2) examination of crop yields as determined by a dynamical downscaled atmospheric model; and (3) comparison between statistically downscaled climate data and data generated by dynamical models.

The key scientific questions regarding seasonal hurricane prediction we hope to answer are: (1) can a high resolution dynamical model provide useful forecast for overall seasonal hurricane activity and how do these forecast compare with other forecasts including statistically based methods? and (2) how sensitive is the tropical cyclogenesis to cumulus parameterization and surface flux parameterizations.

To help answer these questions, we are presently using the FSU/COAPS climate global atmospheric model (T126L27) and the FSU/COAPS atmospheric model coupled to the newly developed Max Planck global ocean model with orthogonal curvilinear coordinates. One advantage of using this ocean model is that it allows us to rotate the poles and place them over Africa and North America, thus allowing us to have very high spatial resolution in the Atlantic basin.

Seasonal climate and climate variability has been shown to be a significant factor in yield variability in agricultural crops. Shifts in seasonal climate due to ENSO phase in the Southeastern U.S. significantly influence maize, wheat, cotton, tomato, rice and hay production. We are exploring the use of the FSU/COAPS global and regional models in hindcasting/forecasting crop yields over the Southeastern U.S.

Finally, the studies above are all conducted using dynamical models (both global and regional). We are currently working on comparison studies using statistical downscaling techniques compared against dynamical methods. The advantage of statistical methods is that they are relatively inexpensive computationally and can be performed at any spatial resolution. Seasonal characteristics and higher moment statistics are some of the comparisons being conducted.

Contact Tim LaRow at or Jim O'Brien at for more information.