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

2. Overview
1. Introduction
2. The data
3. Results

3. 1. Introduction

4. 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

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

6. 1. How?
Graphs
Animations!

7. 2. The data

8. 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

9. 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

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

11. 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

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

13. 3. Results

14. 3. Results

15. 3. Results
Temperature profile: La Niña

16. 3. Results
Temperature profile: Normal conditions

17. 3. Results
Temperature profile: El Niño

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

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

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

21. Questions?