GIS Meteorology

META Model grid converted to point shapefile, with surface temperature attribute contours. Projection is Orthographic true at 0N, 60W.

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Weather folks have a tradition of using any technology available to track, understand and forecast the weather. New software and hardware are exploited to the limits of performance, and the weather technologist can never be satisfied with the limitations which are inevitably encountered. Developers of weather technology have therefore found themselves on the "bleeding edge", and are accustomed with the need to invent tools which cannot be affordably purchased as Commercial-Off-The-Shelf (COTS) products. This situation has lead to a robust and self-reliant weather industry with active participation by industry, government, military, academia and the public (volunteers and hobbyists), resulting in a wide and varied array of meteorological software and hardware products, including shareware and freeware.
The "self reliance" of the weather community, however, has also lead to isolation from other disciplines. This isolation has fostered an environment in which decisions are made for the benefit of weather experts, generally without regard for other users of weather data who are not current participants or cognoscent. Thus, the World Meteorological Organization (WMO) has established "international standards" such as GRIB (Gridded Binary) for the compression and exchange of weather model gridfields, leading to specialized software and procedures which are well-known to weather insiders, but making access to these data more difficult for "weather outsiders". I would also like to point out that WMO GRIB formats are not followed universally, and that more efficient methods for array compression are available (and more affordable from a Life Cycle point of view). Looking from the outside in, the weather business appears to be dominated by specialized codes and decoders (METAR, SHEF, SYNOP, et al.), discipline-centric jargon (Rossby waves, baroclinic instability, positive vorticity advection, et al.), and "Black Magic" (objective [sic.] analysis, areal forecast probability, sub-grid scale parameterization, et al.). Understanding all this requires a "Black Belt" in meteorology.
Geographic Information Systems (GIS) may change the balance of power between weather "providers" and traditional "users" of weather data and related services. There are over 100,000 known installations of leading desktop GIS systems such as ESRI ArcView 3 and MapInfo. Several groups are currently exploring desktop GIS to uncover data formats and processing capabilities which are valuable to weather data processing. We have discovered that most GIS users do not (yet) realize that they may already have a sophisticated weather processing system at their disposal. The primary block to using GIS as a weather processing system still appears to be access to weather data in compatible (geographic spatial) formats.
In addition to using GIS for traditional weather processing functions, we also see an enormous impact and potential market value for weather data and services when integrated into "non-weather" applications. Today's weather outsiders may be current users of GIS who acquire weather information and services separately, using totally independent systems. These users typically have not (yet) integrated the weather services with the business enterprise applications being developed around GIS. Compare the current estimate of a $2 billion annual weather industry to the $200 billion (plus) "other" industry that can use and benefit from readily available weather information. This estimate for "outside" community applications excludes the $2 trillion agribusiness industry, which is not a stranger to either GIS or weather data.

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