RESEARCH HIGHLIGHT

Detailed Temperature Forecasting With Topoclimate Modeling

June 5, 2007

In order to forecast the weather, meteorologists look at two types of data – observational data from balloons and weather stations and data coming from numerical models of the atmosphere that are run on computers. Steady growth in computer capabilities has allowed numerical models to play an increasingly important role in weather forecasting. They cannot, however, account for all processes and details in areas of complex topography. This means that the small-scale processes that occur due to topography are not accounted for, leaving temperature estimates often in error when compared to measured temperatures. In other words, the impact of mountain ranges, rivers, and other geological formations located far between weather stations are not taken into account.

Given that the weather station network can never be dense enough for detailed coverage of a large area with a low population density such as Alaska or northern Canada, accurate estimates of surface temperatures at fine spatial resolution over large areas are currently unavailable.

To examine how a little used method could be used to construct a better representation of temperature for Alaska, François Gourand, a graduate student from Ecole Nationale de la Météorologie/Météo-France, has been working at IARC to examine this problem with David Atkinson of IARC and the Atmospheric Sciences Program (UAF College of Natural Sciences and Mathematics). Atkinson’s Ph.D. thesis (2000) considered similar problems in the Canadian Archipelago. Called “topoclimatic” modeling, the basic method combines numerical weather model data with information about topography to improve the representation of temperature at fine scales.

Using a high-resolution US Geological Survey global digital elevation model (DEM), detailed terrain and elevation information was obtained for two major study domains: Alaska/Yukon and France. Meteorological data were obtained from the Global Forecast System (GFS), developed and operated by NOAA’s National Weather Service (US). By combining these two models and looking at site-specific parameters, a more complete and detailed representation of surface air temperature is achieved.

Some examples of site-specific conditions are: How elevation, solar radiation and coastal proximity affects the temperature of a region; the way obstacles such as mountain ranges affect wind flow, e.g, causing some areas to be exposed and others to be sheltered; and how the drainage of cold, dense air down slopes and valleys affects nighttime or wintertime thermal inversions.

Once the conditions are defined, a temperature map is produced and evaluated for errors using weather station observational data. The model is run every six hours. A more detailed description and the model results can be found at: http://research.iarc.uaf.edu/TCM/

Gourand’s model results may not only help to refine the weather forecast systems already in place but could be of use for many applied efforts. Many research disciplines require detailed air temperature data: hydrologists, glacioligists, paleoclimatologist, and animal/plant physiology and ecology groups. Examples of studies include glacier melt and energy use by hibernating animals.

This Friday, Gourand returns to the Ecole Nationale de la Météorologie in Toulouse, France to finish his studies and then will work for Meteo-France in the future.