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Bangladesh - Tropical Cyclone Historical Catalogue - Met Office

Gridded data for major historical tropical cyclones over Bangladesh.

Each tropical cyclone has a 9 member ensemble, and comprises of timeseries and footprints at resolutions of 4.4km and 1.5km based on the Met Office Unified Model dynamically downscaling ECMWF ERA5 data.

There are 12 available variables, including: air temperature, maximum wind gust speed, minimum air pressure at sea level and precipitation amounts, available at a range of temporal scales, including model instantaneous values, and hourly and daily aggregations.

The catalogue contains the following tropical cyclones (landfall date): BOB01 (30/04/1991 00:00) BOB07 (25/11/1995 09:00) TC01B (19/05/1997 15:00) Akash (14/05/2007 18:00) Sidr (15/11/2007 18:00) Rashmi (26/10/2008 21:00) Aila (25/05/2009 06:00) Viyaru (16/05/2013 09:00) Roanu (21/05/2016 12:00) Mora (30/05/2017 03:00) Fani (04/05/2019 06:00) Bulbul (09/11/2019 18:00).

See the technical documentation for further details, including a full list of variables, and the data domains.

Note that this data is currently a pre-release version 0.2, and subject to change following integration testing.

This data is part of the Oasis Platform for Climate and Catastrophe Risk Assessment – Asia (, a project funded by the International Climate Initiative (IKI), supported by the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety, based on a decision of the Germany Bundestag

Data Download

netCDF files are packaged into gzip compressed tar archives. To un-compress and un-tar data, use tar -xvzf file.tar.gz. Alternatively, 7-zip can handle tar.gz archives.

Oasis format files are zip archives.

Data and Resources

Download documentation

Additional Info

Field Value
Author Hamish Steptoe
Maintainer Met Office
Version 0.2
Last Updated December 4, 2020, 11:16 (Etc/UTC)
Created October 3, 2019, 15:37 (Etc/UTC)
Time range From: 04/30/1991 To: 11/12/2019
Origin Places South-eastern Asia, Bangladesh
Price, £ -

Customer reviews

Cyclone bulbul

Thanks for the data availability. Apparently, cyclone bulbul 2019 timeseries archive is corrupted.

Geospatial Accuracy:
Temporal Length:
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