Contributions from TU Dresden / GLUES

Fakultät Forst, Geo- und Hydrowissenschaften, Fachrichtung Geowissenschaften, Professur Geoinformationssysteme

Matthias Mueller, Christin Henzen

Overview

Data sets related to climate change. The access will be provided by OGC specified Web Services.

A time-aware visualization client (Time4Maps) for geodata which includes functions for data exploration and comparison.

Processing services for climate classification and spatio-temporal data aggregation.

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Data sets

PIK limited WCRP CMIP3 multi-model dataset Based on WCRP CMIP3 multi-model dataset (

http://www-pcmdi.llnl.gov/ipcc/about_ipcc.php) Multiple models and multiple SRES scenarios Harmonized to common spatial resolution (0.5 x 0.5 deg) Harmonized to common temporal resolution (1 month) Spatial extent: World Temporal extent: 2006–2100 Variables: Temperature, Precipitation, Cloudiness [%] WMS / WCS / OPeNDAP (Thredds Server) URL: http://

glues.pik-potsdam.de:8080/thredds/catalog/pik_wcrp_cmip3/catalog.html

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Data sets

Extented metadata (including ISO Lineage) coming soon

http://catalog.glues.geo.tu-dresden.de:8080/terraCatalog/OpenSearch.do?search=PIK+limited+WCRP+CMIP3+multi-model+dataset&type=/Query/OpenSearch.do

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Data sets

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Temperature

Data sets

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Precipitation

Data sets

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Cloudiness (Cloud cover fraction)

Time4Maps

Visual exploration of time-enabled OGC Web Map Services Interactive map view Animations Parameterized calls

http://geoportal.glues.geo.tu-dresden.de:8080/Time4Maps/index.jsp?

&url=<WMS Endpoint>&version=<WMS version>&layer=<layer names>

Query map values (GetFeatureInfo)

Comparative exploration Linked map views for two different layers / services

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Time4Maps

Single view

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Feature Info

Legend

Timeslider

Animation

Interactive map view

Time4Maps

Compare 2 Maps Two linked views (same extent, same date)

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Processing services

Climate classifications Convenient means to support screening of climate projections Subsequent visualization allows to see climate zones moving

(e.g. arid climate zones are moving northward) Implementation should be finished by July 2012

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This image is not our work – but it has inspired us.

We want to put the classification logic as a WPS process for ad-hoc execution.

Processing services

Zonal statistics / spatio-temporal aggregation Computes Min, Max, Mean, Stddev for given zones (polygons /

multipart) Suitable for BigData Supports raster data (values) and Shape-Geometries (zones) Also available for spatio-temporal data (NetCDF) and time-

enabled Shape-Geometries (Start and end date) Implementation should be finished by June 2012

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Value Raster (Temperature, Pollution, …)

Statistical units

Zonal statisticsAggregation

Processing services – Example: Zonal statistics

Summary

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Contribution SBA Standards Performance Availability

Data sets on climate projections

Disaster preparedness and mitigation (Atmospheric properties, precipitation)

Climate

HTTP/OpenDAP, NetCDF, WMS

> 10.000 hits per hour

> 2015

Köppen climate classification service

Disaster preparedness and mitigation (Atmospheric properties, precipitation)

Climate

OGC WPS, NetCDF

depends on data volume; > 12 classifications per hour

> 2015

Spatio-temporal data aggregation service

Cross-cutting OGC WPS depends on data volume; > 12 aggregations per hour

> 2015

Time4Maps Cross-cutting, visualization of global change

WMS Client depends on response times of invoked WMS services, Web server can handle > 10.000 hits per hour

> 2015

Point of contact

Visualization / Time4Maps Christin Henzen, christin.henzen@tu-dresden.de

Data Services and Processing Matthias Mueller, matthias_mueller@tu-dresden.de

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