Masterclass | The Role of Data Assimilation in Forecasting and Reanalysis
LOCATION
Virtual - Hosted on Zoom
Data assimilation provides Earth system models a route to incorporate information from the extensive network of observation instruments. In this way, data assimilation is crucial to the skill of modern-day numerical weather prediction and is also essential for reconstructing historical weather systems in the form of reanalyses.
The theory of data assimilation is based on applying Bayes' theorem to the Earth system. To efficiently solve Bayes' theorem, various data assimilation algorithms have been proposed, each making different assumptions about the error characteristics of the model and observations.
In this lecture, I will provide a brief introduction to the main data assimilation algorithms. We will discuss their advantages and limitations within the context of the challenges in the advancing field of numerical weather prediction and reanalysis. These challenges include the increasing resolution of models, the growing number of components of the Earth system being modelled, and the greater variety of instruments being used.
Speaker
Dr Alison Fowler
Alison is a National Centre for Earth Observation Research Fellow based at the University of Reading. She has over 15 years of experience in the development of data assimilation theory and its application to a variety of environmental challenges. In close collaboration with the Met Office, her recent work includes the development of metrics to help establish new observation networks and the quantification of observation uncertainty to improve the assimilation of existing observations.
Before joining the University of Reading to study for a PhD in Meteorology, Alison obtained a BSc in Mathematics and an MRes in Physics of the Earth and Atmosphere from the University of Leeds.
Responder
Erik Andersson
Erik Andersson has a PhD in Atmospheric Sciences (dynamic meteorology) from Stockholm University. He worked a long and varied career at the European Centre for Medium-Range Weather Forecasts (ECMWF) located in Reading, UK.
He was the Head of the ECMWF Data Assimilation Section for a period of 8 years, and for a time thereafter he was responsible for ECMWF's operational forecasting systems.
Erik started his career as weather forecaster in Sweden, then transitioned to meteorological research and development by taking up a scientist position at ECMWF in 1987, in charge of the development of ECMWF's data assimilation system from 2000-2008. He now retains a keen interest in the various observing systems required for numerical weather prediction (NWP), both satellite instruments and surface-based networks. He has been deeply involved in establishing ECMWF as the operator of the Copernicus Climate Change Service and the Copernicus Atmosphere Monitoring Service on behalf of the European Commission. In his current role as part-retired consultant he contributes to the WMO activities to promote global exchange of key observational data e.g. for NWP and climate reanalysis.
Daniel Lea
Daniel has a DPhil in ocean data assimilation from the University of Oxford. Subsequently he has worked on data assimilation in the ocean for over 20 years first at Johns Hopkins University in the US, followed by the university of Reading and then for the past 17 years at the Met Office.
Daniel works in the Marine Data Assimilation group at the Met Office primarily focussed on improving the performance of global ocean data assimilation. He has worked on using data assimilation for observation bias correction. He led the project to develop the initial Met Office coupled data assimilation system. He is currently working on hybrid ensemble-variational assimilation.
Registration
REGISTRATION IS NOW CLOSED
Registration for this event is closed.
If you have any queries with regards to this event or require any further information please contact us at meetings@rmets.org.
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Masterclass Series Abstract
Continuing its online Meteorological Masterclasses in partnership with the University of Reading, the Society is pleased to announce a new series for Autumn 2024.
During this series, three leading experts from the University of Reading will discuss the latest scientific advances for understanding and predicting weather, climate, and its impacts.
These masterclasses are intended to provide support for professionals working in Meteorology and Climate Science, and its operational applications who wish to remain up to date on recent scientific developments in the field.
Data assimilation provides Earth system models a route to incorporate information from the extensive network of observation instruments. In this way, data assimilation is crucial to the skill of modern-day numerical weather prediction and is also essential for reconstructing historical weather systems in the form of reanalyses.
The theory of data assimilation is based on applying Bayes' theorem to the Earth system. To efficiently solve Bayes' theorem, various data assimilation algorithms have been proposed, each making different assumptions about the error characteristics of the model and observations.
In this lecture, I will provide a brief introduction to the main data assimilation algorithms. We will discuss their advantages and limitations within the context of the challenges in the advancing field of numerical weather prediction and reanalysis. These challenges include the increasing resolution of models, the growing number of components of the Earth system being modelled, and the greater variety of instruments being used.
Speaker
Dr Alison Fowler
Alison is a National Centre for Earth Observation Research Fellow based at the University of Reading. She has over 15 years of experience in the development of data assimilation theory and its application to a variety of environmental challenges. In close collaboration with the Met Office, her recent work includes the development of metrics to help establish new observation networks and the quantification of observation uncertainty to improve the assimilation of existing observations.
Before joining the University of Reading to study for a PhD in Meteorology, Alison obtained a BSc in Mathematics and an MRes in Physics of the Earth and Atmosphere from the University of Leeds.
Responder
Erik Andersson
Erik Andersson has a PhD in Atmospheric Sciences (dynamic meteorology) from Stockholm University. He worked a long and varied career at the European Centre for Medium-Range Weather Forecasts (ECMWF) located in Reading, UK.
He was the Head of the ECMWF Data Assimilation Section for a period of 8 years, and for a time thereafter he was responsible for ECMWF's operational forecasting systems.
Erik started his career as weather forecaster in Sweden, then transitioned to meteorological research and development by taking up a scientist position at ECMWF in 1987, in charge of the development of ECMWF's data assimilation system from 2000-2008. He now retains a keen interest in the various observing systems required for numerical weather prediction (NWP), both satellite instruments and surface-based networks. He has been deeply involved in establishing ECMWF as the operator of the Copernicus Climate Change Service and the Copernicus Atmosphere Monitoring Service on behalf of the European Commission. In his current role as part-retired consultant he contributes to the WMO activities to promote global exchange of key observational data e.g. for NWP and climate reanalysis.
Daniel Lea
Daniel has a DPhil in ocean data assimilation from the University of Oxford. Subsequently he has worked on data assimilation in the ocean for over 20 years first at Johns Hopkins University in the US, followed by the university of Reading and then for the past 17 years at the Met Office.
Daniel works in the Marine Data Assimilation group at the Met Office primarily focussed on improving the performance of global ocean data assimilation. He has worked on using data assimilation for observation bias correction. He led the project to develop the initial Met Office coupled data assimilation system. He is currently working on hybrid ensemble-variational assimilation.
Registration
REGISTRATION IS NOW CLOSED
Registration for this event is closed.
If you have any queries with regards to this event or require any further information please contact us at meetings@rmets.org.
We take data privacy seriously. Please read the RMetS privacy policy to find out more.
Masterclass Series Abstract
Continuing its online Meteorological Masterclasses in partnership with the University of Reading, the Society is pleased to announce a new series for Autumn 2024.
During this series, three leading experts from the University of Reading will discuss the latest scientific advances for understanding and predicting weather, climate, and its impacts.
These masterclasses are intended to provide support for professionals working in Meteorology and Climate Science, and its operational applications who wish to remain up to date on recent scientific developments in the field.
