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Wikimpacts — A global climate impact database based on automated information extraction from Wikipedia

Ni Li, Wim Thiery, Shorouq Zahra, Mariana Madruga de Brito, Koffi Worou, Murathan Kurfali, Seppe Lampe, Paul Munoz, Clare Flynn, Camila Trigoso, Joakim Nivre, Jakob Zscheischler, Gabriele Messori

We introduce Wikimpacts 1.0, a global database on climate impacts developed using natural language processing techniques. Impact data for each event is recorded at three levels: event, national, and sub-national. Categories include the number of deaths, injuries, homelessness, displacements, affected individuals, damaged buildings, and insured or total economic damages.

Extreme climate events like storms, heatwaves, wildfires, floods, and droughts pose serious threats to human society and ecosystems. Impact database can be used in impact forecasting, early warning, and disaster risk management.

This database utilizes the GPT4o large language model for extracting information, following document selection, post-processing, and data consolidation. In this release, we have processed 3,173 Wikipedia articles. This dataset encompasses 2,726 events from 1034 to 2024, featuring 17,912 national and 32,343 sub-national data entries.

TerrestrialClimate ImpactsImpact databaseClimate extremesGPT4oLLM

Download data

Name

li-2025-wikimpacts

Version

1.0.final

Citation

Ni Li, Wim Thiery, Shorouq Zahra, Mariana Madruga de Brito, Koffi Worou, Murathan Kurfali, Seppe Lampe, Paul Munoz, Clare Flynn, Camila Trigoso, Joakim Nivre, Jakob Zscheischler, Gabriele Messori (2026) Wikimpacts — A global climate impact database based on automated information extraction from Wikipedia. Dataset version 1.0.final. Bolin Centre Database. https://doi.org/10.17043/li-2025-wikimpacts-1.0.final

Data description

The database is available in SQL format and provided as a db file. The SQL format comprises four components.

Total_Summary

Impact information at the event level and includes 2,726 events. Impact information includes

  • Event_ID which is internal to the database
  • Event_Names
  • Sources which provides a URL to the relevant Wikipedia article
  • Main_Event e.g. wildfire, tornado, flood and the like
  • Hazards resulting from the event, e.g. wind or lightning
  • Administrative_Areas_Norm
  • Administrative_Areas_GID the administrative area in Global Impact Database format
  • Administrative_Areas_Type e.g. country, state, town, etc.
  • Administrative_Areas_GeoJson the administrative area in GeoJSON format
  • Start_Date_Day as the date of a month
  • Start_Date_Month as the number of the month
  • Start_Date_Year
  • End_Date_Day as above
  • End_Date_Month as above
  • End_Date_Year
  • Total_Deaths_Min the minimum estimated number of fatalities
  • Total_Deaths_Max the maximum estimated number of fatalities
  • Total_Deaths_Approx 1 if the number of fatalities is approximate, 0 if not
  • Minimum, maximum and approximate values for
    • Total_Injuries_*
    • Total_Affected_*
    • Total_Displaced_*
    • Total_Homeless_*
    • Total_Buildings_Damaged_*
    • Total_Insured_Damage_*
    • Total_Damage_*

Values for Total_Insured_Damage_* and Total_Damage_* have information on unit (e.g. USD), adjustment for inflation, and the year of inflation adjustment

Instance_*

8 tables that provide impact information at the national level, with a total of 17,912 entries.

Tables

  • Instance_Per_Administrative_Areas_Affected
  • Instance_Per_Administrative_Areas_Buildings_Damaged
  • Instance_Per_Administrative_Areas_Damage
  • Instance_Per_Administrative_Areas_Deaths
  • Instance_Per_Administrative_Areas_Displaced
  • Instance_Per_Administrative_Areas_Homeless
  • Instance_Per_Administrative_Areas_Injuries
  • Instance_Per_Administrative_Areas_Insured_Damage

Each of these tables provide data for

  • Event_ID
  • Administrative_Areas_Norm
  • Administrative_Areas_GID
  • Administrative_Areas_Type
  • Start_Date_Day
  • Start_Date_Month
  • Start_Date_Year
  • End_Date_Day
  • End_Date_Month
  • End_Date_Year
  • Num_Min
  • Num_Max
  • Num_Approx
Specific_Instance_Per_Administrative_Area_*

8 tables that detail impact information at the sub-national level, with a total of 32,343 entries. The tables are structured as those for the national level.

Geo_Json_Obj

All GeoJSON objects for geolocation information within the database.

Comments

Gabriele Messori is also affiliated with

  • Swedish centre for impacts of climate extremes (climes), Uppsala University, Uppsala, Sweden
  • Department of Meteorology and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden

This dataset is published under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).

Version history

Version 1.0.final

In this final version of the Wikimpacts 1.0 database, 195 multi-event articles from the initial release have been removed, along with 7 events that lacked mandatory information. The database is now published under a license aligned with Wikipedia, which differs from the license used in the initial release.

Version 1.0

Initial release.

Publisher

Bolin Centre Database

License

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)

First name

Gabriele

Last name or organisation

Messori

Email address

gabriele.messori@geo.uu.se

Address

Department of Earth Sciences; Uppsala University

Postal code

SE-752 36

City

Uppsala

Country

Sweden

GCMD science keyword

Earth science > Human dimensions > Natural hazards

GCMD location

Continent

Dataset language

English

DOI

10.17043/li-2025-wikimpacts-1.0.final

Time

2026-04-05T12:14:05.048+00:00

Versions

  • 1.0.final 2026-04-05T12:14:05.048+00:00
  • 1.0 2025-06-11T09:37:23.288+00:00