Javascript is not activated in your browser. This website needs javascript activated to work properly.
You are here

Advanced statistics for model evaluation, simulation set-up and analysis (RA4)

The focus of RA4 is provide and develop statistical models and methods that improve the analysis and evaluation of climate data and output from climate and earthsystem models on a global, regional, and local scale. The work includes both development of new statistical methodology that is widely applicable to spatial and spatio-temporal datasets and the use of modern statistical methods to analys environmental data.

Environmental modelling and monitoring produces very large datasets of past, present and potential future climate and vegetation. The data, obtained from historic records and present day monitoring equipment as well as from earth system models (link to RA1) include such diverse things as ordinary weather data (e.g. temperature and precipitation), atmospheric concentrations of greenhouse gases (e.g. CO2 and methane), land use, vegetation health, and many other measurements of important processes.


Land reconstructions by using historic pollen records

A recent example is ongoing work with RA2 to analys historic pollen records. Since earth system models are developed and evaluated based, partially, on historic data our ability to accurately describe past land-cover and human land use (i.e. farming) is important. Based on pollen records from lake sediments we can reconstruct the amount of land that, 200 years ago, was covered by coniferous forest, broadleaved forest or left unforested. However, these reconstructions are only possible around suitable lakes and the resulting maps provide only, as illustrated, a fragmented record of past land cover.


Reconstructions of forest covered land 200 years ago
Pollen based reconstructions of forest coverd land 200 years ago.


Using statistical methods for spatial interpolation developed by Behnaz Pirzamanbein we are able to expand on these patchy measurements. The result is a coherent estimate of past land cover over all of North West Europe. An estimate that can be used both in the development and validation of regional earth system models, and to help us understand how past humans, through agriculture, may have affected regional climate.


Models can help us understand how past humans, through agriculture, may have affected regional climate.
Statistical models expand the pollen based data to provide forest covered land over the entire area. The resulting information helps us understand how past humans, through agriculture, may have affected regional climate


Read more

Page Manager:


RA4 leader
Johan Lindström

Mathematical Statistics,
LTH/Lund University
johan [dot] lindstrom [at] matstat [dot] lu [dot] se