2023-03-06, 09:45–10:15, Auditorium
This talk will introduce CLIMADA [1], an open-source and -access modeling platform for climate risk assessments. Using state-of-the-art probabilistic modelling, CLIMADA allows to estimate multi-hazard socio-economic impacts as a measure of risk today, the incremental increase from socio-economic development and the further incremental increase due to climate change.
This talk will introduce CLIMADA [1], an open-source and -access modeling platform for climate risk assessments. Using state-of-the-art probabilistic modelling, CLIMADA allows to estimate multi-hazard socio-economic impacts as a measure of risk today, the incremental increase from socio-economic development and the further incremental increase due to climate change.
As a risk calculation tool, CLIMADA requires substantial (geospatial) input data for hazards, exposures and vulnerabilities. CLIMADA’s core functionalities are hence written in a way that provides default hazards, exposures and vulnerabilities data layers. These layers are either seamlessly available from open-source providers (for instance population data from the WorldPop project [2], infrastructure data from OpenStreetMap [3], tropical cyclone data from IBTrACS [4]) or through a CLIMADA database created specifically for this purpose, available via a public API [5]. This enables risk assessments without extensive data collection and creates transparent, auditable and reproducible analyses.
CLIMADA is spatially explicit and globally consistent and, as of today, it provides global coverage of major climate-related extreme-weather hazards at high resolution, namely (i) tropical cyclones, (ii) river flood, (iii) agro drought, (iv) European winter storms, and (v) wildfire, all at 4km spatial resolution globally. For all hazards, historic and probabilistic event sets exist, for some also under select climate forcing scenarios (RCPs) at distinct time horizons (e.g. 2040). All directly available via the CLIMADA data API.
CLIMADA is freely available on GitHub under GNU GPL3 code [6] and CC BY 4.0 data licences, it is readily installable with a package manager (pip) and its functionalities are documented with a comprehensive manual and tutorials [7]. It is used and maintained by the Weather and Climate Risks (WCR) group at ETH Zurich and partner organisations with an active developer community of about 30 researchers.
[1] https://github.com/CLIMADA-project
[2] Tatem, A. J.: WorldPop, open data for spatial demography, Sci Data, 4, 170004, https://doi.org/10.1038/sdata.2017.4, 2017
[3] Haklay, M. and Weber, P.: OpenStreetMap: User-Generated Street Maps, IEEE Pervasive Computing, 7, 12–18, https://doi.org/10.1109/MPRV.2008.80, 2008.
[4] Knapp, K. R., Kruk, M. C., Levinson, D. H., Diamond, H. J., and Neumann, C. J.: The International Best Track Archive for Climate Stewardship (IBTrACS): Unifying Tropical Cyclone Data, Bulletin of the American Meteorological Society, 91, 363–376, https://doi.org/10.1175/2009BAMS2755.1, 2010.
[5] https://climada.ethz.ch/rest/docs#/
[6] https://github.com/CLIMADA-project/climada_python/blob/main/LICENSE
[7] https://climada-python.readthedocs.io