At the same time and mostly independent of GIS, the meteorological community has been exploiting latest technologies to solve a different problem: the visualization of non-linear processes associated with atmospheric movements and changes in state. Early systems such as McIDAS made quick approximations for geography in order to support rapid animation of graphics on satellite images. The meteorological community currently supports a wide array of independently developed and mutually exclusive software systems, as evidenced by the Extended Abstracts for Interactive Information and Processing Systems (IIPS) (Shipley and Beddoe, 1996), now in its twelfth year. WPS development appears to focus on two key factors: 1) speed and throughput of near-real-time information, particularly under animation and now 3-D, and 2) data compaction with impacts to communication and storage. These factors have contributed to the current wide array of encoded meteorological data formats which are protected and sanctioned by International Agreements.
1) Maintain lists of contacts, observers, and equipment, their positions and contact methods,
2) Address and forward time-critical information to/from contact points (collect and disseminate information),
3) Quality control critical information (usually done last or on a time-available basis),
4) Compare current observations/forecasts to thresholds and climatology, and
5) Watch the weather.
Current COTS GIS technology provides the means to automate such weather support functions without major changes to existing data formats. To prove this point, a prototype GIS/WPS should demonstrate, at a minimum, the following functionality:
a) Display Meteorological Data, including station plots, model grids, radar and satellite images,
b) Use Intrinsic GIS Functionality to support traditional WPS functions, including contouring, cross sections, and superposition,
c) Incorporate User-Supplied Algorithms and software through calls to subroutines (e.g. C or C++) and clients,
d) Support an Interactive GUI Builder, and
e) Animation.
3.1 Display Meteorological Data: GIS manages meteorological data as points, lines and polygons. Images (including raster datasets such as DEM) are usually referenced "as is" and are often displayed as backdrops to geographic overlays. Examples for point data include lightning strikes and surface station observations. Lines are collections of connected arcs with node points. Examples for line data include rivers and streams, with gage or river forecast point positions associated with selected nodes. Polygons are collections of topologically connected lines, including shared lines for adjacent polygons. A sample polygon approach to NEXRAD polar data is shown in Figure 1, where polygon shading is used to present radar reflectivity.
![Figure 1 [28k gif]](P2921.GIF)
Figure 1. Polar coordinate radar reflectivity (1 km) for the Dover, DE NEXRAD, plotted as adjacent polygons on a Lambert Conformal projection. Intrinsic GIS functions are also shown for user selection of county polygons and marking of the selected county records in an attached relational database (RDBMS).
3.2 Intrinsic GIS Functionality: ArcInfo currently provides over 3400 callable functions supporting a wide range of spatial database, analysis, display and user interaction operations. The contouring function is demonstrated in Figure 2, where intrinsic GIS macros were used to ingest, smooth and display surface station measurements onto a 60 km rectangular gridfield.
![Figure 2 [11k gif]](P2922.GIF)
Figure 2. Contours for wind speed [knots] computed at 60 km resolution over CONUS and Alaska based on surface station observations. Intrinsic GIS interpolation methods were employed, but calls to user supplied algorithms are also supported.
3.3 User-Supplied Algorithms: Significant coding productivity can be realized through use of the Esri ARC Macro Language (AML) and Avenue, an object oriented programming environment. Current GIS and related technologies are realizing lower costs and risks for implementation of applications compared to implementation in C or C++ (Strand, 1995; Zhuang and Engel, 1995). For example, the GIS/WPS prototype for a Pilot Briefing application shown in Figure 3 was accomplished in 440 LOC (including comments) using Esri AML.
![Figure 3 [16k gif]](P2923.GIF)
Click picture for full image, 1200x825 (84k).
Figure 3. A prototype application for the Pilot Briefing function. User marks flight plan waypoints on a shadefile (upper panel). Stations within 25 km of the flight path are selected and plotted at the surface of a vertical cross section using a Digital Elevation Model or DEM (lower panel). Weather data is available by station ID or symbol through an attached RDBMS.
3.4 Interactive GUI Builder: User programmable Visual Graphical User Interface (GUI) toolkits are standard COTS components in ArcInfo and ArcView.
3.5 Animation: Intrinsic prototype animation was too slow in comparison to current WPS technology, but can be provided using third party software. Is the GIS industry working on this capability?
![Figure 4 [65k gif]](P2924.GIF)
Figure 4. Within seconds of an atmospheric release, an EIS/Win user predicts plume dispersion using the ALOHA model and locates the release point on an EIS/Map image. The model results are then plotted on a detailed ArcInfo map using ArcView 2.
4.1 http://geog.gmu.edu/gess/wxproject/: Concepts for manipulating weather data are demonstrated on the Internet using ArcView 1 by the GIS Weather Project at George Mason University. Sample weather data including the lightning and radar data referenced in this paper are currently provided at this location (subject to change), including all themes required to construct Figure 5. This figure demonstrates the use of ArcView GIS to merge meteorological data as points (lightning), lines (river levels) and polygons (radar reflectivity), correctly positioned over a satellite image.
![Figure 5 [85k gif]](P2925.GIF)
Figure 5. Weather Project sample window from ArcView 2, showing lightning, radar and geography on a georeferenced Landsat image (data samples from various dates). Intrinsic GIS function also shown for NWS office identification and marking from an attached relational database.
4.2 http://iwin.nws.noaa.gov/: Live weather data are now available to the public at no charge by Internet distribution, and radio broadcasts courtesy of the US Government. We have explored the experimental radio broadcast in the metropolitan Washington, DC area on VHF at 163.350 MHz, using ArcView to display surface station observations in near "real time". As shown in Figure 6, the Emergency Managers Weather Information Network (EMWIN) packet radio broadcast can be captured, decoded and adapted for tactical displays of meteorological data. The EMWIN broadcast includes all NWS Watches and Warnings, river gage reports, and other information of interest to existing and future users of GIS. At the time of this writing, the EMWIN broadcast is available in Norman and Tulsa, OK, as well as from a satellite transponder.
![Figure 6 [16k gif]](P2926.GIF)
Click picture for full image, 1069x706 (93k).
Figure 6. Emergency Managers' Weather Information Network (EMWIN) sample window from ArcView 2, showing live surface station reports displayed over the Susquehanna River Basin. Surface Airways Observations (SAOs) are decoded on the fly (sa2.dbf) and linked to a point event theme (Stations.dbf).
The GIS industry continues to innovate in areas currently unaddressed within the WPS community. WPS development efforts typically exploit new technologies as they become affordable. For example, Esri announced in 1995 the acquisition of a Spatial Database Engine (SDE) capable of supporting 100+ users with simultaneous access to very large and continuous spatial databases. Oracle and Esri subsequently announced technology which bundles SDE with the Oracle 7 Spatial Data Option. Using AML and Avenue, the authors have experienced applications coding productivity increases over traditional methods by factors of 5 to 10. Emerging methodologies including Open GeoData Interoperability (Tcl/Tk et al.) are therefore expected to overtake such traditional development methods on grounds for reduced cost and lower project risk.
ACKNOWLEDGMENTS
This abstract first appeared in the Extended Abstracts of the AMS 12th IIPS (Shipley and Beddoe, 1996), and has been updated. Prototype designs include contributions by Roger Shriver (NOAA SAO) and Mike Heathfield (NWS). Mark Smith and Elizabeth Falkenberg (Esri) produced the prototype in two weeks and at Esri expense. Grid and surface station observations courtesy of the Air Resources Laboratory (ARL). Lightning data courtesy of Global Atmospherics Inc. NEXRAD base reflectivity courtesy of Alden Electronics. Figure 4 courtesy of EIS International.
DISCLAIMER
The first two authors are currently on assignment to NOAA NWS, where they support the Advanced Weather Interactive Processing System (AWIPS). This paper does not represent official positions nor endorsement by NOAA, the National Weather Service, or the AWIPS Prime Contractor.
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Ira A. Graffman, Hughes STX Corporation
4400 Forbes Blvd, Lanham, MD 20706-4392
irgraffman@delphi.com
David P. Beddoe, Esri Federal Systems
2070 Chain Bridge Road, Vienna, VA 22182-2536
dbeddoe@Esri.com