Climatographies: Helping Users Grasp Local Weather, Day by Day and Season to Season

Typical weather behavior—prevailing wind patterns, wind strength, annual precipitation, and more—is critical information for planners in government and industry. Whether identifying the perfect location for wind turbines, assessing the effect of coal plant emissions on downwind communities, or creating a disaster preparedness plan in case of terrorist threat, planners benefit from knowledge of long-term weather conditions. Climatographies—thorough, quantitative descriptions of climate—provide exactly this information.

Planners can identify or eliminate potential airport locations if they know when and how wind shear might affect proposed airport sitesMerging the power of weather forecasting models with observations gathered from weather gauging stations, satellite and airborne instruments, and other means, scientists in NCAR’s Research Applications Lab (RAL) have generated regional climatographies with horizontal grid increments as small as 3 kilometers (1.86 miles) and global climatographies with grid spacings of 40 km (24 miles). These descriptions of diurnal and seasonal atmospheric processes and events help planners better understand how weather conditions at a given time—for example, a summer afternoon at 4 p.m. —might affect the direction that a plume from a chemical plant is likely to travel.

In addition to their use in calculating possible transport direction of particulatesat different times of day, these mesoscale analyses of current climates can be used in other ways. For example, planners can identify or eliminate potential airport locations if they know when and how wind shear might affect proposed airport sites. Additionally, climatographies benefit those desiring to select the ideal time and season for an event, such as a sailing regatta on the Great Lakes or a fall marathon.

An additional benefit of RAL’s climatographies is that they can be constructed for areas with sparse observational data. By using, for example, NCAR’s Weather Research and Forecasting (WRF) model, which has a built-in data assimilation capability, meteorological conditions in the model can be “nudged” toward available observational data until model output closely matches observed regional conditions. If the model accurately replicates weather conditions defined by the sparse observations, planners can then use the “tuned” model to interpolate climatic conditions in nearby areas that have only sparse data. The result is a 4-dimensional (the three spatial dimensions and time), gridded realization of the current climate that is consistent with model dynamics and available observations.

Virtually any location can benefit from climatographies, but one domain where this information will soon be used to a greater degree is for the development of alternative energy farms and facilities. For example, climatographies are helping industry experts find favorable locations for potential solar and wind farms. Both solar and wind power depend on very specific meteorological conditions; before placement, companies need to identify locales that have enough sun or wind to make creating the required infrastructure cost effective. Using climatographies increases the chances of identifying these ideal locations, says RAL scientist Tom Warner. With few companies equipped to handle this sort of task efficiently, many utility companies are turning to NCAR to find viable solutions.