Atmospheric Chemistry and Data Science – The Final Frontier?
LOCATION
Convenors: Paul Griffiths, University of Cambridge and Ryan Hossaini, Lancaster University
Atmospheric science is being transformed by the growing use of innovative data science and machine learning methods. In this ACSG meeting we explore how such methods have been successfully applied in atmospheric chemistry research to provide new insights into processes affecting air quality and climate. Focussed on application as well as method, our national and international speakers will cover topics that include (1) downscaling of atmospheric models with machine learning for improved air quality exposure studies, (2) how causal discovery algorithms offer a novel approach for climate model evaluation, and (3) how the development of ‘digital twins’ might operationally be used to improve air quality.
Agenda
8th Dec 2022 11:00 - 16:00
Session schedule
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Registration
REGISTRATION IS NOW OPEN.
Registration for this event is available virtually.
As part of the registration process you will be asked to provide personal information (name and contact email address). Any information you provide to us will only be used by The Royal Meteorological Society and appointed representatives.
Multiple registrations made with the same email address are no longer accepted online. Every registration must have a different name AND a unique email address.
This meeting is part of the Royal Meteorological Society Meetings programme, open to all, from expert to enthusiast, for topical discussions on the latest advances in weather and climate. Free to attend. Non-members are welcome.
A copy of our terms and conditions can be found here
If you have any queries with regards to this event or require any further information please contact us at meetings@rmets.org
Convenors: Paul Griffiths, University of Cambridge and Ryan Hossaini, Lancaster University
Atmospheric science is being transformed by the growing use of innovative data science and machine learning methods. In this ACSG meeting we explore how such methods have been successfully applied in atmospheric chemistry research to provide new insights into processes affecting air quality and climate. Focussed on application as well as method, our national and international speakers will cover topics that include (1) downscaling of atmospheric models with machine learning for improved air quality exposure studies, (2) how causal discovery algorithms offer a novel approach for climate model evaluation, and (3) how the development of ‘digital twins’ might operationally be used to improve air quality.
Agenda
8th Dec 2022 11:00 - 16:00
Session schedule
Hide
Registration
REGISTRATION IS NOW OPEN.
Registration for this event is available virtually.
As part of the registration process you will be asked to provide personal information (name and contact email address). Any information you provide to us will only be used by The Royal Meteorological Society and appointed representatives.
Multiple registrations made with the same email address are no longer accepted online. Every registration must have a different name AND a unique email address.
This meeting is part of the Royal Meteorological Society Meetings programme, open to all, from expert to enthusiast, for topical discussions on the latest advances in weather and climate. Free to attend. Non-members are welcome.
A copy of our terms and conditions can be found here
If you have any queries with regards to this event or require any further information please contact us at meetings@rmets.org
