Abstract
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Environmental Informatics uses a panoply of tools from the statistics, mathematics,
computing, and visualization disciplines. It uses these tools to reveal, quantify, and
validate scientific hypotheses in the environmental sciences, with the quantification of
uncertainty central to its approach. There is nowa strong recognition that scientificmodels
need to incorporate stochastic components throughout: While it has always been recognized
that data have a component of measurement error, attention is now being given
to the quantification of model error, and it is becoming accepted by environmental scientists
that probability models for the latter allow for a coherent way to make scientific
inference. In Environmental Informatics, uncertaintymay be assigned not only to data sets
of measurements but also to computer-generated climate-model output.Methodological
advances, in the form of hierarchical statistical models and the accompanying computational
developments, have expanded the scope of statistical analyses into very large
spatial domains. This has led to studies of the dynamical evolution of entire spatial fields
of geophysical variables, where results are given in terms of predictive distributions. Environmental
Informatics is not only involved in characterizing the environment, it can also
be used to make decisions about mitigation and adaptation strategies. The steps taken by
environmental scientists, from data to information, from information to knowledge, and
from knowledge to decisions, are all taken in the presence of uncertainty. Environmental
Informatics encompasses all these aspects.