Using machine learning to constrain the atmospheric dynamics contribution to regional climate change
Lead Research Organisation:
Imperial College London
Department Name: Physics
Abstract
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Organisations
People |
ORCID iD |
Apostolos Voulgarakis (Primary Supervisor) | |
Carl Thomas (Student) |
Publications

Thomas C
(2021)
An unsupervised learning approach to identifying blocking events: the case of European summer
in Weather and Climate Dynamics
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
NE/R011613/1 | 30/09/2017 | 30/09/2023 | |||
2123640 | Studentship | NE/R011613/1 | 30/09/2018 | 29/06/2022 | Carl Thomas |
Description | In my research I have studied atmospheric blocking patterns. These are complex large-scale weather patterns which block the path of the jet stream. They are associated with heat waves in summer and cold snaps in winter. Blocking is poorly understood, and the effect of climate change is not clear. In my research I have developed a new method to study blocking using unsupervised machine learning. I have shown that this method performs better than previous methods used. I have also developed a new data set which has classified these blocking patterns over European summer. These results show the potential for unsupervised learning in atmospheric science. |
Exploitation Route | The new blocking index identification and accompanying data set can be used by others. A recent reviewer of the current article has stated that the work "provides a quite "revolutionary" and unique dataset to work with", and this can be used to develop understanding of the long-standing problem of objective blocking identification. This can work towards understanding blocking patterns better, and help solve the long-standing problem in climate science of how climate change is impacting the dynamics of the atmosphere. This long-standing issue is a key source of uncertainty in future projections of extreme events, and solving this issue will lead to better information for climate policy, particularly with regard to adaptation. |
Sectors | Environment |
URL | https://wcd.copernicus.org/preprints/wcd-2021-1/ |
Title | 100 summers of blocking classification over Europe for UKESM1-0-LL pre-industrial control |
Description | A unique classification of regional blocking events in a modern climate model. This has been used to develop and verify a new blocking index that has improved skill at classifying blocking events, particularly in climate models. This can help answer the outstanding question of how blocking events respond to climate change. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | This dataset can help answer the outstanding question of how blocking events respond to climate change, and could be used to study the occurrence of blocking events with other methods. |
URL | https://doi.org/10.5281/zenodo.4436225 |
Title | ERA5 JJA European blocking classification 1979-2019 |
Description | A unique classification of regional blocking events created from the ERA5 reanalysis for the period 1979-2019, covering European summer. This has been used to develop and verify a new blocking index that has improved skill at classifying blocking events, particularly in climate models. This can help answer the outstanding question of how blocking events respond to climate change. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | This dataset can help answer the outstanding question of how blocking events respond to climate change, and could be used to study the occurrence of blocking events with other methods. |
URL | https://doi.org/10.5281/zenodo.4436206 |