Climate Science for Service Partnership (WCSSP) South Africa - Calls- tender-UNIVERSITY OF SOUTHAMPTON
Project disclaimer
Description
Collaborative project between meteorological services in South Africa and UK focusing on capacity building for improved weather and climate services, enabling mitigation of risk from extreme weather events. Research into improving representation of Climate Variability and change over Africa by using Machine Learning as a tool for Data Rescue.
Objectives
The observational record of weather and climate is severely limited – there are many times and places where we have few or no observations, and these limitations restrict both science and predictions, particularly for extreme, high-impact events. This restriction is particularly severe over Africa. The aim of this project is to improve the observational record by taking archived observations – currently only on paper – and making them available to science by converting them into computer-readable form. Doing this by hand is unacceptably slow and expensive, but recent developments in Machine Learning offer the potential of a fast, automatic data rescue process. This project should combine state-of-the-art Machine Learning methods, and pre-existing work on data rescue, to produce a recommended method for automatic observation transcription. The work should apply that method to some undigitized records from South Africa, Africa or the surrounding oceans, to demonstrate its effectiveness and scalability. The work should also elaborate how the method can be shared and used more widely. Where appropriate, research should be done in collaboration with WCSSP South Africa partners and help explore opportunities to build capacity in use of the method.
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Download IATI Data for GB-GOV-26-ISPF-MO-AUXD8VC-TH7V62F-Y9D3QXT