Freva for ClimXtreme: an aid to get the bigger picture in analysis of extremes

 

The number of damaging events caused by natural disasters is increasing because of climate change. Projects of public interest such as ClimXtreme (Climate Change and Extreme Events [1, 2]), aim to improve our knowledge of extreme events, the influence of environmental changes and their societal impacts.

ClimXtreme focuses on an integral evaluation through a three-pronged approach, namely: the physical processes behind the extremes, the statistical assessment of them, and their impact. The success of such a project depends on a coordinate effort from many interdisciplinary groups down to the management of computational and data storage resources. The ever-growing amount of available data at the researcher’s disposal is a two-sided blade that craves for greater resources to host, access, and evaluate them efficiently through High Performance Computing (HPC) infrastructures. Additionally, these last years the community is demanding an easier reproducibility of evaluation workflows and data FAIRness [3]. Frameworks like Freva (Free Evaluation System Framework [4, 5]) offer an efficient solution to handle customizable evaluation systems of large research projects, institutes or universities in the Earth system community [6-8] over the HPC environment and in a centralized manner. Mainly written on python, Freva offers:

• A centralized access. Freva can be accessed via command line interface, via web, and via python module (e.g. for jupyter notebooks) offering similar features.
• A standardized data search. Freva allows for a quick and intuitive incorporation and search of several datasets stored centrally.
• Flexible analysis. Freva provides a common interface for user defined data evaluation routines to plug them in to the system irrespective of the programming language. These plugins are able to search from and integrate own results back to Freva. This environment enables an ecosystem of plugins that fosters the interchange of results and ideas between researchers, and facilitates the portability to any other research project that uses a Freva instance.
• Transparent and reproducible results. Every analysis run through Freva (including parameter configuration and plugin version information) is stored in a central database and can be consulted, shared, modified and re-run by anyone within the project. Freva optimizes the usage of computational and storage resources and paves the way of traceability in line with FAIR data principles.

Hosted at the DKRZ, ClimXtreme’s Freva instance (XCES [7]) offers quick access to more than 9 million datafiles of models (e.g. CMIP, CORDEX), observations (stations, gridded) and evaluation outputs. The ClimXtreme community has been actively contributing with plugins to XCES, its biggest asset, with close to 20 plugins of different disciplines at the disposal of everyone within the project, and more than 20,000 analysis run through the system. At present, any researcher can focus on a past, present or future period and a geographical region and run a series of evaluations ranging from coocurrence probabilities of extreme events, their impact on crops to wind tracking algorithms among many others. Freva facilitates comprehensive and exhaustive analysis of extreme events in an easy way.

 

References:

[1] https://www.fona.de/de/massnahmen/foerdermassnahmen/climxtreme.php

[2] https://www.climxtreme.net/index.php/en/

[3] https://www.go-fair.org/fair-principles/

[4] http://doi.org/10.5334/jors.253

[5] https://github.com/FREVA-CLINT/freva-deployment

[6] freva.met.fu-berlin.de

[7] https://www.xces.dkrz.de/

[8] www-regiklim.dkrz.de