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Showing posts with label Environmental Modelling. Show all posts
Showing posts with label Environmental Modelling. Show all posts

Friday, 27 May 2011

C++ Example 1: Reading GCM output data (IPCC Data Distribution Centre).

Ejemlo 1 para C++: Lectura de salidas de modelos de circulación global (Datos del IPCC)

Do you know how do climate change studies are carried?

From an engineering perspective, a fundamental element for climate change studies is provided by the outputs from Global Circulation Models, GCM, whose numerical experiments are run for several "climate change scenarios".

Why is it important to learn some programming language? Practitioners (especially young ones) may tend to think that commercial software packages have "the solution". Unfortunately, that is not true, and most of the time we will need to build our own tools. Then, postgraduate students will see the advantages, because those obstacles will enrich their experiences throughout a process where the aim is to understand the basis behind a phenomena.

I am posting a practical example where are described the elements in a C++ program that can be used when dealing with matrices. Why matrices?, because from my perspective, those elements are perhaps the most useful resource in problems where environmental models are involved. You will notice that my programs are not as elaborated as a program written by an IT expert, but they work. Details on the language may be found elsewhere.

At the same time the example shows how to read data obtained from the IPCC Data Distribution Centre.

Glossary:
GCM: Global Circulation Model.
IPCC: Intergovernmental Panel on Climate Change.

Thursday, 26 May 2011

Neural Networks: A practical application to hydrological modelling.

Redes neuronales: Una aplicación práctica a la modelación hidrológica.

This material is part of a series of informal meetings that some friends of mine used to record when we were pursuing our postgraduate studies. It shows a practical approach on neural networks and hydrological modelling. The material is kindly provided by Dr. Nam, from Vietnam. The link to that material is this one.

Thanks.

Monte Carlo and sensitivity analysis: A practical example.

Monte Carlo y análisis de sensibilidad: Ejemplo práctico

Monte Carlo experiments are stochastic techniques that can be used to analyze the response of a system. It is commonly viewed as the alternative when all other analysis techniques have failed. Me and my friends recorded the following presentation during an informal meeting we had back in 2010. The link to that meeting is this one. Links to similar resources are appreciated.

Geographical Information Systems GIS: Intro to Arcview GIS

Arcview GIS is the old version (yet useful) of the ArcGIS software. Last year (2010), me and a group of postgrads recorded our meeting, where the basics of GIS was introduced by using the Arcview GIS software.

The contents of the meeting is posted here.


It would be interesting if you can provide some more information on similar recources. I think that would help to all.

Thanks,
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