GIS in Water Resources Term Project Cedric DAVID

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Presentation transcript:

GIS in Water Resources Term Project Cedric DAVID The El Niño Phenomenon GIS in Water Resources Term Project Cedric DAVID

Overview 1. Introduction 2. The data 3. Results

1. Introduction

What? Weak trade wind  El Niño Strong wind  La Niña ENSO Pacific Ocean Wind Higher water level Higher Temperature Weak trade wind  El Niño Strong wind  La Niña ENSO

1. Why? Drastic changes Needs to be understood (and predicted) Weather (Droughts & Rains) Ecosystem Impacts on Economy Needs to be understood (and predicted)

1. How? Graphs Animations!

2. The data

2. The data National Virtual Ocean Data System JAVA Based Lot of Dataset (Ocean, atm, land) Different Formats Shaded Plot Tab Separated ArcView FORTRAN netCDF

288 Files 2. The data I had access to: 1 year of monthly average 24 depths btw surface and 1500m One ArcView file each 288 Files

2. The data netCDF often used in ENSO related studies Developed by Self Describing Architecture Independent Easily sharable  ONE FILE FOR THE WHOLE DATA!

2. The data Best Files cannot be directly opened with ArcGIS® Find a way using ArcGIS®? Use 288 files and link them? Use another software

2. The data IDV Software Java-based software framework for analyzing and visualizing geoscience data

3. Results

3. Results

3. Results Temperature profile: La Niña

3. Results Temperature profile: Normal conditions

3. Results Temperature profile: El Niño

3. Results Prepare for the best part: animations Salinity Temperature

3. Results Good Points in IDV Built-in link to download data Satellite images Radar DEM Calculations and formulas Good graphic interface FREE

Conclusions El Niño, La Niña , ENSO Power of netCDF files One way to improve ArcGIS® IDV

Questions?

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