Visualizing 4D Weather Data
Chris Little, UK Met Office, FOSS4G, Nottingham,20 Sept 2013
© Crown copyright Met Office
Contents
• Who, What, When, Why?
• Meteorological Background
• Current Forecasting Capability
• How
• Way Forward
• Questions and answers
© Crown copyright Met Office
Who, What, When, Why?
© Crown copyright Met Office
Who?
Chris Little, UK Met Office
IT Fellow, Co-Chair OGC Met Ocean Domain WG
chris.little@metoffice.gov.uk
Christine Perey, Perey Research & Consulting
Augmented Reality, Spime Wrangling
cperey@perey.com
Mike Reynolds, Augmented Technologies Ltd
Founder & CEO, merging AR & geospatial
AWILA: Augment What I Look At
mike.reynolds@aug-tech.co.uk
© Crown copyright Met Office
Mont Blanc
Geneva
Thonon-les-Bains
Lake Geneva
What?
Arriving in
Montreux in
15 min
camera, GPS, compass,
accelerometer, micropho
3/14/2016
Now… can the invisible,
such as forces of nature,
be made more visible?
3/14/2016
From Maps & Wind Radar to Wind AR
When?
• 2012-10 Idea & quick plan in 30mins after long day
at OGC TC Seoul
• 2013-01 Proof of concept, canned demo
Shown at OGC TC Redlands under NDA
• 2013-02 Live Demo
Mobile World Congress, Barcelona
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Why?
Current Users of AR
• Well over 100M consumer-grade mobile devices are
capable of supporting AR
• Many mobile Web browsers have all necessary components
for basic AR
• Consumer applications continue to evolve
• Many are “gimmicks” for product promotion
• Industrial users are keen to begin using AR
• Positive ROI has been demonstrated in many domains
• Internal use cases permit use of controlled environments and
well-defined devices
Three challenging points
From geospatial data to the service platform
• Business data
• Emergency data
• Environmental data to service platform
From service platform to end users
• Professional and consumer
• How do you do things locally (applies to this proximity)?
• How do you serve this through a remote service provider
• Real location versus Point of Interest POI
Temporal adjustment of (geospatial) data
• Time-indexed data to be viewed from/aa specific place, in real time
• 4th dimension
Existing practice
Meteorology uses:
• Point & Line data (BUFR)
• Gridded data (GRIB)
• In specialized standardized
WMO formats to minimize
bandwidth
Augmented Reality uses:
• Batch orientated
• No levels or orography
• No specific data formats
• Streamed by location
• Point/feature orientated
• No time dimension other
• Data is usually ‘all or nothing’
than ‘now’
fire-hose for large area of Earth
• Interoperability just
starting
• 4D is natural
• Interoperability for >100 years
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Meteorological Background
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Wilhem Bjerknes
Lewis Fry Richardson
Jules Charney
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Alan Turing
John von Neumann
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Scales and Predictability
Increasing scale
Increasing lifetime
Increasing predictability
Model resolution
Tornado
1km
10 minutes
30 minutes
200m
Thunderstorm
10 km
1 hour
3 hours
2 km
…but if we know what the planetary wave
characteristics will be in 9 days, we can give
an accurate probabilistic tornado forecast
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Front
100 km
12 hours
36 hours
20 km
Planetary Wave
10000 km
3 days
9 days
2000 km
Influence of grid length on forecasts
Forecast rainfall
accumulations for
1200-1800UTC
16/8/2004
60km forecast
from 00UTC
12km forecast from 00UTC
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5km
radar
actual
4km forecast from 00UTC
1km forecast from 00UTC
Current Forecasting Capability
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Current NWP Vertical resolution
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NWP State of the Art 2013
15 Centres forecast Globally
• 15-20Km resolution, 70-90 levels, 1-4 times/day
• ~1MW electricity per supercomputer
70 Centres Regional/National/Local forecasts
• <40 Centres have 1Km to 5Km resolution
• 4-8 times/day
191 National Met Services: “authoritative voice”
• Timeliness, expiry
Ensembles: 12-24 simultaneous forecasts
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How?
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3. Publication
4. Check availability
2. Transmission
1. Preparation
6. Response
5. Query
Meteorological Services
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1.
Data prepared internally (creation of forecast dataset)
2.
Data transmitted to external facing server, chopped into tiles
3.
Tiled data made 'visible' to client application's on-line content store
4.
When client application queries on-line content store, it knows where and
how to retrieve the wind dataset
5.
Client queries tile-cache on Met Office data server for tiles covering the
client's location
6.
Necessary data is returned to the client app
7.
Data processed on client application to 'AR friendly‘
8.
Wind AR information finally presented to user with options for navigating
to more data via the UI
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Proof of Concept details - 1
Amazon EC2 store (password protected)
•
•
•
•
Agreement already in place
Escalation
Redundancy
Authentication & Authorization
Meteo data in WMO GRIB or NetCDF
• 971 x 597 grid points
• 4 / day ( fresh data every 6 hour) batch feeds
• T-48 hours to T+36 hours in rolling buffer
Convert to CSV grid in Lat/Long with IRIS & CartoPy
AWILA converts CSV to Slippy Map tileset, Level 11
URL not Request/Response
• 1 tile per level or time, 7.4MB
• 1 tile for several parameters
• 9 tiles around location
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Wavefront OBJ model for the arrows
Proof of Concept details - 2
AWILA: Augment What I Look At
• Augmented Reality + Geospatial, written in Java
• SQLServer for data Service Catalogue
• Uses OGC Simple Features GeoAPI
• Can change altitude of viewpoint
• Can switch video on / off
• Switch between real location and POI
• Has time scroll
• Ingest various data-streams (WFS, WMS, ESRI,
pipe-work, weather data)
• Can store data for canned replays along a route
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Way Forward?
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Future NWP
2015
• Global Models at 15 Km, 100 levels
• National Models at 1 Km
2020
• Global models at 8 Km, ~150 levels
• National models at 0.3 Km
No global provider at <1 Km resolution, so
interoperability essential
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• UK Met Office wants to develop a system that is
universal
– Data from any source (including but not limited to UK)
would work
– As long as it is formatted in accordance with open
data and our specifications
– No interpolation – safety critical
– Deterministic wind values unlikely ever to be finer than
100m and more frequent than 10 mins.
• Benefits to using Amazon
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Goal: Expand OGC Standards
From Map Tiles to Data Tiles
Web Map Services
Web Coverage Services
• Problem
• Problem
• Not sufficiently fast
• Not sufficiently fast
• Solution
• Solution
• Create Map Tiles
• Create Data Tiles
• Web Map Tile Service
Ows-10?• Create Web Data Tile Service
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Immediate Experiments
Easy
• Windsocks not arrows
• Multiple levels, vertical data set at specific place
• Other providers
• Standard WMO format before tiling
• Flexible CartoPy, IRIS
Slighter more work
• Other parameters (how to visualise?)
• Combine with orography
• Combine with severe weather warning areas
• Alternative to Amazon EC2 cloud
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Way forward
AWILA
– More exposure of the AWILA browser
– Increase usefulness, visibility
PEREY
– To make the invisible visible
– To make AR useful
– Explore 3D AR
Meteorology
– OGC standard for data tiling
– OGC 4D and time mainstream
– Common interface for real time & archived data
Questions & answers
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Questions & Answers
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Meteorological Satellites
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Choose Data Sets
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Initial Requirements
Technical Requirements
• Make 3D objects interact
with things that don’t
move
• Data presentation in
vertical plane
• Temporal plane (time
varying)
• Real time
• Play back (time series)
Business Requirements
• Location and data
accuracy
• Location and data
precision
• One data set, many
services
• One device, many data
sets
• Any network, any device
and all data sets
Relevant OGC Standards
Established
• CityGML
Emerging
• GeoSMS
• WMS
• Indoor GML
• Web Map Tiling Service
• ARML 2.0
• SLD/SE
• Sensor Web for IoT
• WFS/T
• WCS
• Open LS
• GeoPackage
• Sites for Mobile
Other Standards
W3C
• Many relevant standards
Khronos Group
• WebGL
• OpenGL ES
United Nations ITU/ISO/WMO
• H.264
• TC-211
• Meteorological: GRIB, BUFR,…
• OpenSL
• COLLADA
• StreamInput
• MPEG ARAF
OASIS
• MPEG-V
• Common Alerting Protocol
(CAP)
Potential Impacts of the Work
• Increase real time access to geospatial data
• Increase temporal element in geospatial
• Increase use of 3D
• Greater cooperation with other SDOs
• Relevance of OGC standards
• Professional
• Government
• Consumer
are all Lat Long
Managed services require
the policies are observed
• Data on device will erase itself after time interval
• Authentication and safe guards
• Must be a real time service
• Classic example is Meteoalarm
• Weather alarms for Europe
• Green / Yellow / Red
• White (outdated information)
• Gray (where there is no information) 3D data void?
• Need something similar safeguard in the service in the
roadmap for commercial/managed service
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© Crown copyright Met Office