© crown copyright met office re using gis for re climate impacts analysis 2nd acre workshop (1 st...

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Using GIS for ReRe Climate Impacts Analysis 2nd ACRE Workshop (1st to 3rd April 2009)Neil Kaye

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Introduction

• Not Just Pretty Maps (but that’s part of it)

• GIS data structures and storage

• Using GIS to solve problems

• A technique for visualising ensemble forecasts

• A funky map to finish

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Not just Pretty Maps!

HOME

MET OFFICE

The West CountryMet Office HQ

London

Up North

Scotland

50o

60o

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What is GIS?

• A GIS is a computer system capable of capturing, storing, analyzing, and displaying geographically referenced information; that is, data identified according to location.

• A GIS allows multiple layers to be combined in one dataset

Social FactorsSocial Factors

BiodiversityBiodiversity

EngineeringEngineering

Land UseLand Use

Environmental Environmental ConsiderationsConsiderations

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Data Structures

Raster vs Vector

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Data Storage

Spatial databases

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Problem:

Identify a location for 4 new climate stations that occur in an in area of low climate station density and high population density.

Solution:

Create a map to identify the appropriate areas.

High population density, high station density

Low population density, low station density

Low population density, high station density

High population density, low station density

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Selecting station based on climatology

Max Temp +/- 0.5oC

Min Temp +/- 0.5oC

Precipitation +/- 10%

Elevation +/- 100m

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Vineyard Suitability GIS Example

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It matters what it looks like!!!

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Koppen Classification

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Change in classification by 2050 (HADCM3)

Equatorial to aridWarm temperate to equatorial Warm temperate to arid

Hotter Summers

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Tundra to snow fully humid with a cool summer

Change from cool to warm summer

Change from warm to hot summer

Change from warm temperate to arid

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Change from warm temperate to arid

Change from steppe to desert

Change from equatorial summer dry to arid steppe

Change from warm temperate fully humid to equatorial summer dry

Hotter summers

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Visualizing ensemble model data Neil Kaye

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Standard HADCM3 Model Run

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QUMP Atmospheric Ensemble – Global Mean Temperature Anomaly

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Runoff 2100 – 2000 Atmospheric QUMP (HADCM3)

Little Agreement between Ensemble Members

Transition between strong agreement on decreased runoff and strong agreement of increased runoff

Little Agreement between Ensemble Members

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QUMP Atmospheric Ensemble – Global Mean Temperature Anomaly

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Low Mean R2 Value

Low Mean R2 Value

High Mean R2 Value

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Cartogram showing global CO2 emissions

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It matters what it looks like

• It is about presentation