Alison Fowler

In preparation

• Skakal, J. et al: How uncertain and observable are marine ecosystem indicators in shelf seas? In preparation.

• Fowler, A. M.: On the robustness of methods to correct background bias in data assimilation to the uncertainties in the bias estimates. In preparation.

• Hu, G., et al.: On methods for assessment of the value of observations in convection-permitting numerical weather prediction. In preparation for QJRMS.

Peer Reviewed

2023

• Dong, B., Bannister, r. Chen, Y. Fowler, A. and Haines, K: Simplified Kalman smoother and ensemble Kalman smoother for improving reanalyses. Geoscientific Model Development

• Francis, D., Fowler, A. M., Lawless, A., Eyre, J. and Migliorini, S.: 'The Effective Use of Anchor Observations in Variational Bias Correction in the Presence of Model Bias. QJRMS DOI:10.1002/qj.4482

2022

• Fowler, A. M., Skákala, J., Ford, D.: Validating and improving the uncertainty assumptions for the assimilation of ocean colour derived chlorophyll a into a marine biogeochemistry model of the North-West European Shelf Seas. QJRMS DOI:10.1002/qj.4408

2020

• Geir Evensen, Javier Amezcua, Marc Bocquet, Alberto Carrassi, Alban Farchi, Alison Fowler, Peter Houtekamer, Christopher K. R. T. Jones, Rafael de Moraes, Manuel Pulido, Christian Sampson, Femke Vossepoel: An international assessment of the SARS-CoV-2 pandemic using ensemble data assimilation, Foundations of Data Science. DOI: 10.3934/fods.2021001.

• Fowler, A. M., Simonin, D. and Waller, J.: Measuring theoretical and actual observation influence in the Met Office UKV: application to Doppler radial winds, GRL, DOI: doi/10.1029/2020GL091110

2019

• Fowler, A. M.: Data compression in the presence of observational error correlations, Tellus A: Dynamic Meteorology and Oceanography, 71:1, 1-16, DOI: 10.1080/16000870.2019.1634937

2018

• Fowler, A. M., Dance, S. and Waller, J.: On the interaction of observation and a-priori error correlations in data assimilation. Q.J.R.Met.Soc.144: 48–62. doi:10.1002/qj.3183

2017

• Fowler, A. M.: A sampling method for the objective selection of IASI channels. Mon. Wea. Rev., 145, 709–725, https://doi.org/10.1175/MWR-D-16-0069.1
• Howes, K. E., Fowler, A. M. and Lawless, A. S.: Accounting for model error in strong-constraint 4DVar data assimilation. Q.J.R.Met.Soc.143: 1227–1240. doi:10.1002/qj.2996

2016

• Fowler, A. M. and Lawless, A.S.: Coupled atmosphere-ocean data assimilation in the presence of model error. Mon. Wea. Rev., 144, 4007–4030

2015

• Smith, P.J., Fowler, A.M. and Lawless, A.S.: Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean model. Tellus A , 67, 27025.

2013

• Fowler, A., van Leeuwen, P. J.: Measures of observation impact in data assimilation: the effect of non-Gaussian measurement error.Tellus A, 65, 20035.

2012

• Fowler, A., van Leeuwen, P. J.: Measures of observation impact in non-Gaussian data assimilation. Tellus A, 64, 17192.
• Fowler, A., Bannister, R., Eyre, J.: A new floating model level scheme for the assimilation of boundary layer top inversions: The univariate assimilation of temperature. Q. J. R. Met. Soc., 138, 682-698.

2011

• Brooks, I., Fowler, A., 2011: An evaluation of Boundary-Layer Depth, Inversion and Entrainment Parameters by Large-Eddy Simulation. Boundary-Layer Meteorol., doi:10.1007/s10546-011-9668-3.

2010

• Fowler, A., Bannister, R., Eyre, J., 2010: Characterising the background errors for the boundary layer capping inversion. Austral. Meteorol. Ocean. J., 59 , 17-24.

2007

• Brooks, I., Fowler, A., 2007: A new measure of entrainment zone structure. GEOPHYSICAL RESEARCH LETTERS, VOL. 34, L16808, doi:10.1029/2007GL030958

Conference Proceedings

2014

• van Leeuwen, P. J., Ades, M., Fowler, A., Nichols, N., Waller, J., and Stott, Z. Advanced methods in data assimilation: Addressing the big data problem. Proceedings of the 2014 conference on Big Data from Space (BiDS'14)