Our People
Alison Fowler
Research Fellow
Data Assimilation
Research interests
My work focuses on the development of data assimilation theory and its application to meteorology and oceanography. I am particularly interested in bias correction and observation uncertainty, as well as the development of observing networks to extract the most information from available observations.
Recent publications
On the robustness of methods to account for background bias in data assimilation to uncertainties in the bias estimates. 2024-07-04
DOI: https://doi.org/10.1002/qj.4790
Simplified Kalman smoother and ensemble Kalman smoother for improving reanalyses. 2023-07-27
DOI: http://dx.doi.org/10.5194/gmd-16-4233-2023
The effective use of anchor observations in variational bias correction in the presence of model bias. 2023-07
DOI: https://doi.org/10.1002/qj.4482
Validating and improving the uncertainty assumptions for the assimilation of ocean‐colour‐derived chlorophyll a into a marine biogeochemistry model of the Northwest European Shelf Seas. 2023-01
DOI: https://doi.org/10.1002/qj.4408
An international initiative of predicting the SARS-CoV-2 pandemic using ensemble data assimilation. 2021
DOI: http://dx.doi.org/10.3934/fods.2021001
Measuring Theoretical and Actual Observation Influence in the Met Office UKV: Application to Doppler Radial Winds. 2020-12-28
DOI: https://doi.org/10.1029/2020GL091110
Data compression in the presence of observational error correlations. 2019-01-01
DOI: http://dx.doi.org/10.1080/16000870.2019.1634937
On the interaction of observation and prior error correlations in data assimilation. 2018
A Sampling Method for Quantifying the Information Content of IASI Channels. 2017-02
DOI: http://dx.doi.org/10.1175/mwr-d-16-0069.1
Accounting formodel error in strong-constraint 4D-Var data assimilation. 2017
An Idealized Study of Coupled Atmosphere-Ocean 4D-Var in the Presence of Model Error. 2016
Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean model. 2015
Observation impact in data assimilation: the effect of non-Gaussian observation error. 2013
A new floating model level scheme for the assimilation of boundary-layer top inversions: the univariate assimilation of temperature. 2012
An Evaluation of Boundary-Layer Depth, Inversion and Entrainment Parameters by Large-Eddy Simulation. 2012
Measures of observation impact in non-Gaussian data assimilation. 2012
Characterising the background errors for the boundary-layer capping inversion. 2010
New measure of entrainment zone structure. 2007
On the robustness of methods to account for background bias in data assimilation to uncertainties in the bias estimates. 2024-07-04
DOI: https://doi.org/10.1002/qj.4790
Simplified Kalman smoother and ensemble Kalman smoother for improving reanalyses. 2023-07-27
DOI: http://dx.doi.org/10.5194/gmd-16-4233-2023
The effective use of anchor observations in variational bias correction in the presence of model bias. 2023-07
DOI: https://doi.org/10.1002/qj.4482
Validating and improving the uncertainty assumptions for the assimilation of ocean‐colour‐derived chlorophyll a into a marine biogeochemistry model of the Northwest European Shelf Seas. 2023-01
DOI: https://doi.org/10.1002/qj.4408
An international initiative of predicting the SARS-CoV-2 pandemic using ensemble data assimilation. 2021
DOI: http://dx.doi.org/10.3934/fods.2021001
Measuring Theoretical and Actual Observation Influence in the Met Office UKV: Application to Doppler Radial Winds. 2020-12-28
DOI: https://doi.org/10.1029/2020GL091110
Data compression in the presence of observational error correlations. 2019-01-01
DOI: http://dx.doi.org/10.1080/16000870.2019.1634937
On the interaction of observation and prior error correlations in data assimilation. 2018
A Sampling Method for Quantifying the Information Content of IASI Channels. 2017-02
DOI: http://dx.doi.org/10.1175/mwr-d-16-0069.1
Accounting formodel error in strong-constraint 4D-Var data assimilation. 2017
An Idealized Study of Coupled Atmosphere-Ocean 4D-Var in the Presence of Model Error. 2016
Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean model. 2015
Observation impact in data assimilation: the effect of non-Gaussian observation error. 2013
A new floating model level scheme for the assimilation of boundary-layer top inversions: the univariate assimilation of temperature. 2012
An Evaluation of Boundary-Layer Depth, Inversion and Entrainment Parameters by Large-Eddy Simulation. 2012
Measures of observation impact in non-Gaussian data assimilation. 2012
Characterising the background errors for the boundary-layer capping inversion. 2010
New measure of entrainment zone structure. 2007
