CLIMADA features

Main characteristics

CLIMADA is a framework and not a data model. The focus lies on its broad application and flexibility instead of data fine tuning.
Any geographical scales: Worldwide, Country, Region, City, ...
Event basis: probabilistic sets, single events, time series, ...
Any event time scales: annual extremes, isolate events, seasonal or monthly extremes, hourly forecasts, ...
Impact and risk: current, past, future impacts and adaptation option risk reduction
Any exposures: People, Ecosystems, Assets, Economic supply chains, Critical infrastructures, Heritage sites, Coral reefs, Wind turbines, ...
Any hazards: Tropical cyclones, Winter storms, Wildfires, Floods, Drought, Heatwaves, ...
Various output metrics: impact at location, return period curves, risk transfer metrics, average impact, risk maps, forecast probabilities, warning levels, ...
Applications: risk assessment, adaptation option appraisal, storylines, forecasting, insurance pricing, impact attribution, ...
The code is devided into core modules (very high stability) and petals modules (advanced optional features and data models)

Major modules and features

UNSEQUA (uncertainty and sensitivity quantification module)

The UNSEQUA module allows to run global uncertainties and sensitivites analysis on the CLIMADA impact and adaptation option appraisal outputs using state-of-the art algorithms for quasi Monte-Carlo sampling and sensivity index calculation using the SALib package.
Kropf, C. M., et al. Geosci. Model Dev., 1–32, https://doi.org/10.5194/gmd-2021-437 (2022).

Impact function calibration module

Calibrate impact functions for each impact assessment to truly have model truly in line with your data. Seamlessly connect the optained ensembles of tragedy or average ensembles to the unsequa module for uncertainty quantification. Riedel, L. et al. JOSS 9, 6755 https://joss.theoj.org/papers/10.21105/joss.06755(2024).

Lines and polygon handler

The lines and polygons handler allows for the seamless disaggregation and aggregation of exposures and impact data to lines and polygons. Mühlhofer, E. et al, Environ. Res. Commun. 6, 015005 https://dx.doi.org/10.1088/2515-7620/ad15ab

Open Street Map integration

Integrate seamlessly any element from open street map as an exposure layer into CLIMADA with the OSMflex package.
Mühlhofer, E. et al. Environ. Res. Commun. 6, 015005 https://dx.doi.org/10.1088/2515-7620/ad15ab(2024).

LitPop

The LitPop module allows to generate globally consistent physical assets exposure layer estimates based on population estimates, nightlight satellite imagery and GDP estimates.
Eberenz, S., et al.. Earth Syst. Sci. Data 12, 817–833 https://doi.org/10.5194/essd-12-817-2020(2020).

Various modules to support the creation of hazard datasets

Tropical cyclone wind intensities can be computed with several parametric models based on tracks generated from various sources (direct support for tracks from IBTrACS, STORM, CHAZ, Kerry Emanuel).
River flood maps can be derived based on GloFAS discharge data with the dedicate module: Riedel, L. et al., Geosci. Model Dev., 17, 5291, https://gmd.copernicus.org/articles/17/5291/2024/.
Hazard data in a large variety of formats, either rasters (e.g., netcdf, geotiff) or vector data (shapefiles, .csv, excell) are supported. Thus, data from known sources such as ISIMIP, ERA5/6 or CMIP5/6 can be used. Certain datasets are directly available through the data API.

Cascading critical infrastructure risks

The cascading infrastructure module allows the computation of the indirect impacts of extreme events to critical infrastructure service povision by modelling cascading failures
Mühlhofer E. et al., Reliability Engineering & System Safety 234, 109194 https://doi.org/10.1016/j.ress.2023.109194

Multi-hazard risk and recovery

In a publication by Stalhandske Z. et al. (2024) code to integrate multi-hazard impact and recovery was developed and made available.
Stalhandske, Z. et al. Sci. Rep. 14, 5875 https://www.nature.com/articles/s41598-024-55775-2