Copyright © 2009, Open Geospatial Consortium, Inc. Modelling Meteorological Observations and...

Copyright © 2009, Open Geospatial Consortium, Inc.

Modelling Meteorological Observations and Forecast Data as Discrete Coverages

for exchange using WFS

Meteorology DWG

Debbie Wilson – Snowflake Software

30 September 2009

Helping the World to CommunicateGeographically

Copyright © 2009 Open Geospatial Consortium

Rationale• Met Office provide ~650 products and services to a wide range of customers:

• Government• Research• Business• Media• Public

• Until recently many of these products were exchanged with customers using traditional FTP push services for integration into their own information systems

• Met Office is moving away from data supply towards providing services and decision-support applications where users access highly detailed weather information directly



Rationale• Met Office have developed several decision support systems to support

transport sector:– OpenRoad– Open Runway– OpenRailway– SafeSee

• These applications provide access to highly detailed forecast and observation data relating to real-world objects they manage and operate

• To ensure that these can remain operational and increase efficiency



Example: OpenRoad



Example: OpenRoad



Example: OpenRoad



Example: OpenRoad



Design Brief• To develop an efficient and compact schema for encoding forecast and

observation data for exchange using WFS based upon:– ISO 19123 coverages specification– GML 3.2.1 coverage profile

• Reusable across a wide range of Met Office projects – i.e. schema should be flexible to allow it to be easily integrated into project specific application schema

• We were not required to develop a full information model but demonstrated how the schema could be incorporated into a more comprehensive information models:– O&M (OGC)– WXXM (Aviation)– Route-Based Forecast Model (Internal)

• Compatible with GO Publisher’s WFS on-the-fly data translation capabilities



Design Issues and Constraints• Need to understand the types of queries to be performed by WFS

client:– Identity Queries:

• Select the 36 hour forecast for Heathrow Airport• Select the latest observation for Telegraph Hill Weather Station

– Spatio-temporal Queries:• Select the latest observations within a user-defined bounding box

– Parameter Queries:• Select road surface temperature from the 36 hour forecast for A360• Select observed air temperature at Telegraph Hill over period:

2009-09-29T00:00:00 – 2009-09-30T11:00:00

• To support ability to process these queries the data must be defined within an XML element



Modelling Met Office Data as Discrete Coverages



Modelling Issues faced• Took a similar approach to CSML separating the spatio-temporal domain into

two parts:– Feature of Interest: i.e. Road, railway, region, postcode, sporting venue, latest– Coverage Domain: i.e. Time-series (list or temporal grid) or MultiPoint, MultiCurve or

MultiSurface • For many Met Office use cases the most common discrete coverage type is the

Time-Series coverage• Unfortunately – ISO 19123 and GML 3.2.1 only support spatial coverages• Although-O&M does illustrate how ISO 19123 could be extended to incorporate

temporal coverages and provided a O&M best practice schema provides a literal implementation schema time-series – as a geometry-value pair – not compact enough or defined within GML 3.2.1 spec.



Modelling Parameter values• For encoding parameter values within the gml:rangeSet 2 options:

– ValueArray– AbstractScalarValueList

• Of these AbstractScalarValueList provides the most compact encoding for listing the values for each parameter type.

• Also provides ability to hard type the parameter type by specialising AbstractScalarValueList types within the application schema



Next Steps• To test the schemas to see whether the compact encodings can

support the various query types identified• Evaluate the performance of GO Publisher to translate the data from

RDBMS into discrete coverage schema on-the-fly• Refine schemas where required

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