# CLIMADA ### Description CLIMADA (Aznar-Siguan and Bresch, 2019) is an open-source probabilistic natural catastrophe and climate change adaptation model which can also calculate the potentially averted damages due to implemented adaptation measures (including infrastructural and behavioural changes). It integrates hazard, exposure and vulnerability data, providing multi-hazard assessments across flexible geographical and temporal scales. ### Model Specifications | Model Specifications | Description | | ----------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Model Type | Integrates hazard, exposure and vulnerability data to provide information about climate and disaster risks as well as impacts, and the effects of adaptation measures. | | Associated Probability Method | Event-based approach to risk assessments, utilizing probabilistic (obtained ideally from bespoke models) or historical hazard sets to model the occurrence and impacts of climate-related events . Provides comprehensive uncertainty and sensitivity analysis, vulnerability Bayesian calibration methods, critical infrastructure cascading failures propagation, multi-hazard and recovery modelling, adaptation option appraisal and multi-criteria analysis | | Spatial Resolution | Depends on the data. Coverages for global major climate-related hazards are provided at 4km and above, but it can support localised application with a resolution down to 100m (thus enabling risk assessments at all levels). | | Intensity Parameters | Hazard-specific and exposure specific. CLIMADA is agnostic to the units of the inputsFor example, for tropical cyclones one could use maximum wind-gust (m/s), for floods the maximum flood depth, for heat the number of days about a WBGT threshold, or for storm surges the maximum water level rise. | | Other Inputs | Historical impact data, OSM Data, high-resolution climate data (such as CHELSA), socio-economic datasets, infrastructure distribution, data regarding adaptation measures. Can be expanded with additional datasets and modules, such as topography datasets, external elevation, etc. | | Calibration and Validation | Calibration focuses on the refinement of various hazard impact functions (describing the relationship between intensity and impacts). Requires historical hazard, exposure and impact data. Validated via comparing outputs against independent datasets, historical events, and the correspondence between predicted and observed impacts. | | Effects of Climate Change | CLIMADA can process both hazard and climate data and related datasets (including EM-DAT, or Copernicus Climate Data Store). | *** --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://directed-eu.gitbook.io/data-fabric-manual/model-documentation/climada.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.