The Earth System Data Lab: A light-weight data cube approach to empower the study of land-surface processes and interactions

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iDiv Leipzig

tba

12 / 0.25 CP

Contents

Scientists today are confronted with a plethora of Earth observations (EO) that are available through a multitude of data platforms, monitoring initiatives, and model-data integration approaches. To tap into the full potential of joint exploitations of these datasets, the scientist has to deal with different data formats, retrieval methods, data usage policies, inconsistent resolutions and formatting as well as getting access to suitable computation and data storage facilities. This can be time consuming and impede scientific progress.

The “Earth System Data Lab” is a novel infrastructure for scientists. It not only provides a set of harmonized data cubes, but also developed a strong data analytics toolkit in tandem with access to computational facilities to jointly analyze the datasets. The data cube consists on a selection of diverse Earth observation datasets including multiple atmospheric variables, Land-Atmosphere fluxes, biophysical parameters and is currently extended to ocean variables. These datasets are analysis-ready, harmonized on different temporal and spatial resolutions to allow rapid exploitation. The core data analytics toolkit allows users, proficient in a language of scientific computing like Python or Julia, to apply their own analysis methods on the multivariate data cube. Examples implemented include nonlinear time series analytic tools, dimensionality reduction approaches, or anomaly detectors, among others.

During the workshop we will introduce the Earth System Data Lab in a hands-on session. Participants will learn how to access the data cube, how to apply user-defined functions on the data cube and how to visualize the results.


Lecturers

Lecturer in charge:

Dr. Miguel D. Mahecha, Miguel leads the research group Empirical Inference of the Earth System at the Max Planck Institute for Biogeochemistry

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Further lecturer:

Fabian Gans, Max-Planck-Institute for Biogeochemistry

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