MADIS web services in support of NextGen

NOAA is investing in the transition of MADIS (Meteorological

Assimilation Data Ingest System) into NWS operations to help improve

performance for a wide-variety of service applications including the

reduction of the nation's losses of life, property, and commerce

caused by severe storms, drought, local high-impact weather, and toxic

atmospheric plumes. MADIS supports these services areas by 1)

improving the density, usability, reliability, timeliness, and

accuracy of integrated surface and upper air observations used in

local weather warning, model predictions, and hazardous situations,

and 2) providing products in more easily accessible and usable formats

that the federal government, industry, and society can better use to

reduce risk and uncertainty, lower costs, and improve public safety

and security. MADIS is also included in NOAA and FAA plans to provide

observation capabilities for the Initial Operating Capability of the

NextGen 4-D Weather Information Database (WIDB).

Existing MADIS system capabilities include:

- Flexible web-enabled data access methodologies

- Integrated observational data with uniform formats and time stamps

- Continuous database updates triggered by arriving observations

- Increased observation data density and temporal resolution

- Seamless access to real-time and saved datasets

- Tiered observation quality control processing

- Web-enabled push/pull distribution capabilities, with server-side

subsetting capabilities

- Secure authentication for proprietary data

- On-the-fly, flexible, variable transformations and data reformatting

The advantage of using MADIS to implement advanced web services for

NextGen is the opportunity for a direct path into NWS operations,

providing efficient, cost-effective, access to a broad cross-section

of mission-critical information with core expertise in sub-orbital in

situ and remotely sensed environmental observations.

This paper will report on the recent addition of a Joint METOC Broker

Language (JMBL) service for surface observations to the set of web

services offered by MADIS, and present a gap analysis comparing the

pre-existing MADIS web service subsetting capabilities with those

offered by JBML services. Future work will focus in the near-term on

implementing an Open Geospatial Consortium (OGC) Web Feature Service

(WFS) for surface observations, and will include an analysis comparing

JMBL and WFS capabilities. Longer term plans include providing

additional observation datasets in the primary data transfer language

selected for the WIDB.