Lessons and recommendations for modellers

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Lessons and recommendations for modellers

Model builders

Model based analyses

Things Earth Systems modellers need to know: online sources or books

Open-source (or at least free) software recommendations

I'm picky about reasonable learning curves, logical syntax, and simple scripts. These packages are my favourites:

1D (timeseries,..) plots: gnuplot
scriptable, logical syntax
2D area map graphics and netcdf access/regridding...: Ferret
Ferret has a short learning curve and is script based (with optional GUI interface for those so inclined). It is also backed by a very helpful user/developer community
matrix/numerical analysis: Octave
Octave is an open-source partial clone of Matlab
data management/scripting: Python
Python is much more numerically oriented than Perl and as far as I'm concerned, has a more logical syntax
vector graphics: xfig
xfig is easy to use and can import many types of graphic files
GIS: GRASS
Powerful, scriptable, relatively easy learning curve, diverse set of toolboxes
Statistical Computing: R
Similar to the proprietary S language and environment but open-sourced and with loads of tool-boxes.
general scripting: awk
awk, csh, sed, join, cut are all easy to use and powerful tools for managing large datasets, automating data processing,...
Artificial Neural Networks
Netlab is a freely available Neural Toolbox for Matlab (that unfortunately doesn't work on Octave). It's biggest plus is the associated text: Netlab: Algorithms for Pattern Recognition. All the algorithms are developed in detail in the textbook and for me this was a great learning aid. Phil Goodman's Nevprop is the easiest package that I've found to use. It is a good starting point for someone who wants to get quick results even though it is limited to standard feedforward multilayer perceptron networks. For Bayesian neural networks and Markov chain sampling I recommend Radford Neal's software for flexible Bayesian modelling which is being used in our calibration project.

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