Thesis icon

Thesis

Improving subseasonal to seasonal rainfall forecasts in Central America using dynamic model ensembles

Abstract:

Hydrometeorological hazards such as droughts and floods can have devastating consequences. Central America is one region at risk of hydrometeorological extremes impacts, which will likely increase under human-induced climate change. Physically-based subseasonal to seasonal (S2S) rainfall forecasts from Atmospheric Oceanic General Circulation Models (AOGCMs) can be used to inform anticipatory actions from multiple weeks to several months ahead. Multiple AOGCMs can be combined into multi-mod...

Expand abstract

Actions


Access Document


Files:

Authors


More by this author
Institution:
University of Oxford
Division:
SSD
Department:
SOGE
Role:
Author

Contributors

Institution:
University of Costa Rica
Research group:
Department of Geography
Role:
Contributor
Institution:
Columbia University
Research group:
Department of Earth and Environmental Sciences
Role:
Contributor
Institution:
Sheffield University
Research group:
Department of Geography
Role:
Contributor
Institution:
Climate Adaptation Services
Role:
Contributor
Institution:
NOAA Physical Sciences Laboratory
Research group:
Modelling and Data Assimilation
Role:
Contributor


More from this funder
Funder identifier:
https://ror.org/04v48nr57
Funding agency for:
Kowal, K
More from this funder
Funding agency for:
Kowal, K


DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

Terms of use



Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP