Dr. Steven Fletcher

Research Scientist/Scholar III
Fort Collins, Colorado


Steven Fletcher received his B.Sc.(HONS) in Mathematics and Statistics from the University of Reading in the United Kingdom (1998), his M.Sc. in Numerical Solutions to Differential Equations again from the University of Reading (1999), (Advisor: Prof. Nancy Nichols) and his Ph.D. in Data Assimilation also from the Mathematics department at the University of Reading (2004), (Advisors: Prof. Nancy Nichols and Prof. Ian Roulstone, Met Office/U. Surrey). His areas of interest are numerical weather prediction and modeling, data assimilation, control theory, calculus of variation, control variable transforms and preconditioning for large scale nonlinear inverse problems and non-Gaussian probability models for data assimilation. 
From 2004 to 2006, he worked as a post doctoral fellow at the Cooperative Institute for Research in the Atmosphere (CIRA) under a National Science Foundation grant into the use of control theory in Numerical weather prediction. During this time he published the first non-Gaussian three-dimensional variational data assimilation system for lognormally distributed observational errors. Besides this he also published the first paper to combine Gaussian and lognormal errors together to allow for the simultaneous assimilation of different observational error types. He has also worked with the Maximum Likelihood Ensemble Filter (MLEF) with Dr. Milija Zupanski and Prof. Mike Navon of Florida State University exploring the size of the ensemble and the dynamics in the shallow water equations. 
From 2006 to 2010 Dr. Fletcher was a research scientist at the Center for Geosciences/Atmospheric Research (CG/AR) in CIRA. During this time he developed a Bayesian based probability model for 4DVAR to enable any distribution to be used. In particular he derived the 4DVAR equivalent for the mixed lognormal-Gaussian distribution.  As part of the review process for the Fletcher (2010) Tellus paper Dr. Fletcher derived and coded into the Lorenz 1963 model, the equations for a mixed distribution constant model error term.  Also during this time Dr. Fletcher worked on detecting important dynamical properties of the MLEF with respect to Lyapunov and Bred vectors. He has also worked with the DA group at the National Center for Atmospheric Research on their preconditioner for the Weather, Research and Forecasting model’s 4D VAR system for the US Air Force.
During 2008 to 2011,  Dr. Fletcher worked on techniques associated with how to assimilate both binary MODIS 500m snow cover observations with coarse AMSR-E 25km snow water equivalence into the snow evolution model SnowModel.  There were four different schemes developed from simple nudging to a rule based iterative direct insertion technique as well as combination of the two to optimize the data available.  This work was tested over two different spacial domains; the first in south-eastern Colorado and the second over a region of the tri-state are of Colorado, Wyoming and Nebraska, during the winter season of 2006-2007.  This was work done in collaboration with Drs. Glen Liston, Christopher Hiemstra and Steven Miller.
Between 2012 and 2014 Dr. Fletcher worked with the data assimilation scientist at the Naval Research Laboratory in Monterey, CA, on the Navy's numerical weather prediction system investigating updating the background error covariance model as well as non-Gaussian possibilities inside of the observation space based DA system.  Also during this period Dr. Fletcher was awarded an NSF grant to investigate the non-Gaussian effects inside of Gaussian data assimilation systems.  Part of this research lead to the first ever non-additive incremental based 3D and 4D VAR systems.
Fletcher, S. J. and A. S. Jones, 2014: Multiplicative and Additive Incremental Variational Data Assimilation for Mixed Lognormal-Gaussian Errors. Mon. Wea. Rev., 142, 2521--2544.
Dr. Fletcher has organized a session at the Annual Fall Meeting of the American Geophysical Union (AGU) since 2010 on different aspects of DA, data fusion, predictability and uncertainty quantification in the Nonlinear Geophysics (NG) Focus Group of AGU.  Since 2013 Dr. Fletcher has been part of the program committee of the AGU Annual Fall Meeting representing Nonlinear Geophysics where he oversees the scientific program for NG for the meeting in San Francisco.
Currently Dr. Fletcher is still working on the NSF project supervising the postdoctoral fellow - Dr. Anton Kliewer.  He is also working on a new project with NRL in Monterey with NAVGEM as well as teaching as part of the data assimilation internship program at CIRA - Variational DA theory.

Recent Work

March 24, 2014

Dr. Fletcher's newest project is an NSF grant to investigate the impacts of using Gaussian and logarithmic transform approaches compared to a lognormal based Bayesian approach firstly in the CIRA 1-Dimensional Optimal Estimator (C1DOE) but eventually this work will be ...

March 12, 2014
Dr. Fletcher is investigating different approaches to improve the background error covariance matrix in the NAVDAS-AR system as well as investigating possible new choices for moisture representation in the same system.  He is also investigating the differences in both the ...