Vitae for Steven J. Fletcher
Cooperative Institute for Research in the Atmosphere
Colorado State University, Fort Collins, CO 80523-1375
Telephone: (970) 491-8376, Fax (970) 491-8241, Email: Steven.Fletcher@colostate.edu
a. Professional Preparation
2004 Ph.D. in Mathematics, University of Reading, United Kingdom. Thesis title:
Higher Order Balance Conditions Using Hamiltonian Dynamics for Numerical
Weather Prediction.
1999 M.Sc. in Mathematics, Numerical Solutions to Differential Equations,
University of Reading, United Kingdom. Dissertation title: Numerical
Approximations to Bouyancy Advection in the Eady Model.
1998 B.Sc.(HONS) in Mathematics and Statistics, University of Reading,
United Kingdom
b. Appointments
20112006-2011
2004-2006
2002-2003
Research Scientist III, CIRA/CSU
Research Scientist II, CIRA/CSU
Postdoctoral Fellow, CIRA/CSU
Sessional Lecturer, Department of Mathematics, University of
Reading, UK. Courses taught and examined: Introduction to
matrices (Freshman), Introduction to Control Theory (Second and
Finalists).
Tutor, Department of Mathematics, University of Reading, UK.
Tutored Calculus of several variables, linear algebra, introduction
to matrices, vectors and complex numbers, introduction to
calculus, numerical analysis I (computer practicals in MATLAB
for numerical linear algebra and splines), numerical analysis III
(Computer practicals in MATLAB for numerical solutions to
Initial and boundary value problems).
Private Tutor. Helping G.C.S.E and A. Level students with their
mathematics exams, specifically students who had dyslexia,
teaching them techniques to overcome this in mathematic exams.
1998-2003
1998-2002
c. Research Projects
i.
Considerations of a mixed Gaussian-lognormal retrieval system and the
effects of incorrect distributions for WRF-VAR. This project involved the
CIRA 1-Dimensional Optimal Estimation (C1DOE) microwave retrieval
system. This is a Newton-Rhapson based solver for a Bayesian based
maximum likelihood problem. The work involved investigating where in the
large set of Fortran90, C codes and the IMSL library changes would be
needed to convert this Gaussian based system to allow for a mixed probability
distribution as the basis in the underlying Bayesian conditional probability
framework. These changes were derived through the Newton-Rhapson
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ii.
iii.
iv.
v.
equation for the mixed lognormal-Gaussian based Bayesian problem. This
work will also change the Weather, Research and Forecasting 3D VAR
system to allow for different combinations of mixed and Gaussian errors, as
well as quantifying the impact of the assumed distribution for both
observations and background terms.
Assimilation of MODIS and AMSR-E snow parameter observations. This
project involved the manipulation of large Fortran77 set of codes that make up
SnowModel, a high spatial and temporal resolution numerical model of snow
evolution. In this project a new Fortran90 module was introduced and the
namelist of the code changed to allow for the many different versions of the
assimilation systems to be used by the larger program. All this work was
performed using a LINUX based operating system and graphics produced
using MATLAB. Also involved was the re-projecting of the MODIS and
AMSR-E satellite products into the same projection and truncating them to the
domains of the model. Also these new smaller files were converted from
HDF format into ASCII files to be read into the model through a MATLAB
code I wrote using the intrinsic readers in MATLAB. Due to the illposedness of the problem, the difference in the spatial resolution of the
numerical model (500m) and that of the AMSR-E observation resolution
(25km), an iterative algorithm was derived to distribute SWE in the AMSR-E
equivalent area in the model.
Non-Gaussian Data Assimilation. This project involved the derivation from
first principles of a mixed Gaussian-lognormal based 3 and 4 dimensional
variational system in both a calculus of variation and Bayesian framework. It
was also identified through statistical properties that the transform approach,
when the lognormal variable is transformed into a Gaussian random variable,
resulted in the median as the analysis state in lognormal space and not the
mode. As part of the project the 3D and 4D cost functions and solvers were
programmed in MATLAB with adjoint consideration of the product of the
geometric errors in MATLAB. A mixed distribution model error component
for 4D was also derived and coded in a toy Lorenz’63 chaotic model for a
constant bias case.
ARWA-WRF preconditioning. This project involved the investigation of the
WRF-VAR system and the RAMDAS 4D VAR system to see if it was
possible to use the preconditioner from RAMDAS in the WRF-VAR system.
This involved two large sets of Fortran90 data assimilation codes.
Maximum Likelihood Ensemble Filter (MLEF) Data Assimilation. This
project involved changing parts of the Fortran90 MLEF code to be able to
assimilate in a Gaussian framework observations with different size errors as
well as different frequency with a global spherical shallow water equations
model. The large set of code for the shallow water model were manipulated to
introduce the Rossby-Haurwitz wave as a set of initial conditions. This work
was all ran on NCAR’s supercomputers. Also as part of this work it was
discovered that the mathematical structure of the MLEF enabled the ensemble
members to be initialized by both Lyapunov and bred vectors.
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d. Publications
(i) Peer reviewed publications
Fletcher, S. J., Nichols, N. K. and Roulstone, I., 2013: Flow-Dependent Balance
Conditions and Data Assimilation, To be resubmitted to Q. J. Roy. Meteor. Soc.
Fletcher, S. J., Liston, G. E., Hiemstra, C. A. and Miller, S. D., 2012: Assimilation of
MODIS and AMSR-E Snow Parameter Observations into a Physical Snow Model. J.
Hydrometeorology. 13, 1475-1492.
Guillot, E. M, Vonder Haar, T. H., Forsythe, J. M. and Fletcher, S. J., 2012: Evaluating
Satellite-Based Cloud Persistence and Displacement Nowcasting Techniques over
Complex Terrain, Weather and Forecasting. 27, 502—514.
Fletcher, S. J. 2010: Mixed lognormal-Gaussian four-dimensional data assimilation.
Tellus, 62A, 266—287.
Fletcher, S. J. and Zupanski, M. 2008: A study of ensemble size and shallow water dynamics
with the Maximum Likelihood Ensemble Filter. Tellus, 60A, 348—360.
Uzunoglu, B., Fletcher, S. J., Zupanski, M. and Navon, I. M. 2007: Adaptive ensemble
reduction and inflation. Q. J. R. Meteor. Soc. 133, 1281-1294.
Fletcher, S. J. and Zupanski, M., 2007: Implications and impacts of transforming lognormal
variables into Normal variables in VAR. Meteorologische Zeitschrift, 16, 348—360,
Zupanski, M., Fletcher, S.J., Navon, I.M., Uzunoglu, B., Heikes, R.P., Randall, D.A.,
Ringler, T.D. and Daescu, D. 2006: Initiation of ensemble data assimilation. Tellus, 58A,
159—170.
Fletcher, S. J., and Zupanski, M., 2006: A data assimilation method for lognormal
distributed observational errors. Q. J. Roy. Meteor. Soc., 132, 2505—2519.
Fletcher, S. J., and Zupanski, M., 2006: A Hybrid Multivariate Normal and lognormal
distribution for Data assimilation. Atmos. Sci. Lett., 7, 43—46.
(ii) Book Chapters
Jones, A. S., and Fletcher, S. J., 2013: Solar Forecasting: Chapter 13: Data Assimilation
into NWP and Sample Applications, Elsevier Publishing, Ed. J. Kleissi, in preparation.
(iii) Proceedings Papers
Fletcher, S. J., Zupanski, M. and Vonder Haar, T. H. 2007: Lognormal Data Assimilation:
Theory and Applications. BACIMO 2007, 6 - 8 November, Boston College, Chestnut Hill,
Boston, MA.
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Fletcher, S.J. and Zupanski, M., 2007: An Alternative to bias correction in retrievals and
direct radiance assimilation. Extended Abstract from the 11th Symposium on Integrated
Observing and Assimilation Systems for Atmosphere, Oceans and Land Surfaces, 87th
American Meteorological Society Annual Meeting, 14 – 18 January, San Antonio, Texas.
Fletcher, S.J. and Zupanski, M, 2006: An ensemble data assimilation scheme that has mixed
Gaussian and non-Gaussian errors. Extended Abstract from the 18th Conference on
Probability and Statistics in the Atmospheric Sciences, 86th American Meteorological Society
Annual Meeting 29 January – 2 February, Atlanta, Georgia.
Fletcher, S.J., Zupanski, M., Navon, I.M., Uzunoglu, B., Heikes, R. and Randall, D.A., 2005:
A maximum likelihood ensemble filter with a shallow water model. Proceedings of the
fourth WMO International Symposium on Assimilation of Observations in Meteorology and
Oceanography. 18 – 22 April, Prague, Czech Republic.
Fletcher, S.J. and Zupanski, M., 2005: Numerical Studies of the Maximum Likelihood
Ensemble Filter with a 2D shallow water model, Geophysical Research Abstracts, 7.
Fletcher, S. J., Roulstone, I. and Nichols, N. K., 2003: Imposing Higher Order Balance
Conditions in Variational Data Assimilation, Geophysical Research Abstracts, 5.
(iv) Technical Reports
Fletcher, S.J. and Jones, A.S. 2012: A review of Verification Statistic Selection to
Determine Air Force Weather Agency (AFWA) Coupled Assimilation and Prediction
System (ACAPS) Performance using the Model Evaluation Toolkit (MET). February
2012, Technical Report, Fort Collins, 11pp.
Jones, A. S. and Fletcher, S. J., 2010: AFWA Couples Assimilation and Prediction System
(ACAPS): Recommendations for Future Activities. 15 January, Technical Report, Fort
Collins, CO, 17 pp.
Jones, A. S. and Fletcher, S. J., 2010: Final Technical Report: AFWA Couples Assimilation
and Prediction System (ACAPS) developments at CIRA, 1 February 2009 – 31 January
2010, 16 January, 3pp.
Jones, A. S., Fletcher, S. J. and Longmore, S. 2008: Final Technical Report: CIRANCAR/MMM WRF-Var Collaboration Work Plan, 19 April 2007 – 31 January 2008,
March 21, 15 pp.
e. Oral Presentations
Fletcher, S. J., Liston, G. E., Hiemstra, C. A. and Miller, S. D, 2011: Assimilation of
MODIS and AMSR-E Snow Parameter Observations into a Physical Snow Model. The
9th Workshop on Adjoint Applications in Dynamic Meteorology, 10 – 14 October,
Cefalu, Sicily. Italy.
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Fletcher, S. J., 2011: Non-Gaussian and Non-Linear Data Assimilation Research at the
Cooperative Institute for Research in the Atmosphere (Invited), Naval Research
Laboratory: Monterey, 23 August, Monterey, CA.
Fletcher, S. J., 2011: Non-Gaussian Data Assimilation: CGAR Annual Review, 8 March,
Fort Collins.
Auligne, T., Jones, A. S. and Fletcher, S. J., 2010: Development of a Cloud Analysis
System, Battlefield Atmospheric and Cloud Impacts on Military Operations (BACIMO)
Conference, 13-15 April, Omaha, NE.
Fletcher, S. J. 2010: Development of a mixed Gaussian-lognormal weak constraint 4D
VAR system. CG/AR Annual Review, Fort Collins, CO, 30-31 March.
Fletcher, S.J. 2009: Non-Gaussian 4D VAR, AFWA Cloud Analysis Workshop.
Boulder, CO, 1-3 September.
Fletcher, S.J. 2009: Non-Gaussian 4D VAR, 8th International workshop on Adjoint
Model Applications in Dynamic Meteorology, Tannersville, PA, 18 – 22 May.
Fletcher, S.J. and Sengupta, M., 2009: Non-Gaussian 4D VAR, JCSDA Seminar Series,
(Invited), NOAA Camp Springs, MD, 21 April.
Fletcher, S. J. 2009: 4-Dimensional non-Gaussian Data Assimilation. CG/AR Annual
Review, Fort Collins, CO, 11-12 March.
Fletcher, S. J. 2008: Advances in Data Assimilation, CIRA CG/AR VTC Seminar Series,
CIRA, Colorado State University, Fort Collins, CO, 16 September.
Fletcher, S. J, 2008: Hybrid Lognormal – Normal Data Assimilation theory and
applications. R.A.L, Boulder, CO, 4 August.
Fletcher, S. J., Zupanski, M. and Vonder Haar, T. H. 2007: Lognormal Data Assimilation:
Theory and Applications. BACIMO 2007, Boston College, Chestnut Hill, Boston, MA, 6-8
November.
Fletcher, S.J. and Zupanski, M. 2007: Implications and impacts of transforming
lognormal variables into normal variables in VAR, 7th International Workshop on adjoint
applications in dynamic meteorology, Obergurgl, Austria, 9-13 October.
Fletcher, S. J., 2007: Data assimilation research at CIRA/CSU, Data Assimilation
Research Centre Seminar Series (Invited), University of Reading, UK, 9 May.
Fletcher, S. J. and Zupanski, M. 2006: Lognormal Data Assimilation: Theory and
Applications. Annual Meeting of the American Geophysical Union, San Francisco, CA,
11-15 December.
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Fletcher, S. J. 2006: Lognormal Data Assimilation: Motivation, Theory and Application
to Satellite Data Assimilation. CIRA Seminar, CIRA, Colorado State University, Fort
Collins, CO, 26 July.
Fletcher, S. J., Zupanski, M. and Sengupta, M. 2006: Impacts and Implications from
transforming between lognormal variables and normal variables. Workshop on
Predictability, Observations and Uncertainties in the Geosciences, The Florida State
University, Tallahassee, FL, 13-15 March.
Fletcher, S. J. and Zupanski, M., 2006: An ensemble data assimilation scheme that has
mixed Gaussian and non-Gaussian errors. 86th Annual Meeting of the American
Meteorological Society, Atlanta, GA, January 29 – February 2.
Fletcher, S. J., Nichols, N. K. and Roulstone, I. 2003: Hamiltonian and SemiGeostrophic Theory. Data Assimilation Research Centre Seminar, University of Reading,
UK.
f. Posters Presentations
Fletcher, S. J. and S. A. Boukabara, 2012: Impact assessment and data assimilation of
NOAA NPP/JPSS sounding products and quality control parameters. Annual Fall
Meeting of the American Geophysical Union, San Francisco, 3-7 December.
Jones, A. S., S. J. Fletcher, S. Q. Kidder and J. M. Forsythe, 2012: The use of Parallel
Data Processing and Error Analysis System (DPEAS) for the observational exploration of
complex Multi-Satellite Non-Gaussian data assimilation algorithms. Annual Fall Meeting
of the American Geophysical Union, San Francisco, 3-7 December.
Fletcher, S.J., Liston, G.E., Hiemstra, C.A. and Miller, S.D. 2011:Assimilation of
MODIS and AMSR-E snow parameter observations into a physical snow model. Annual
Fall Meeting of the American Geophysical Union, San Francisco, 5-9 December.
Jones, A. S., Fletcher, S. J., Cogan, J., Mason, G., and McWilliams, G., 2011: Initial test
results using a temporal variational data assimilation method to retrieve deep soil
moisture, 7th Annual Symposium on Future National Operational Environmental Satellite
System-JPSS and GOES-R, , Seattle, Washington, 25-26 January.
Kashawlic, E. A., Fletcher, S. J., Forsythe, J. M., Jones, A. S., and Vonder Haar, T. H.,
2010: A comparison between mixed and transform data assimilation schemes on short-,
medium- and long-term forecasts, Ninth Center for Multiple Scale Modeling of
Atmospheric Processes’s (CMMAP) Team Meeting, Fort Collins, CO, 3-5 August.
Fletcher, S. J., Jones, A. S. and Vonder Haar, T. H., 2010: Mixed Gaussian-lognormal
four dimensional variational data assimilation: Strong and weak constraint formulations,
Battlefield Atmospheric and Cloud Impacts on Military Operations (BACIMO)
Conference, Omaha, NE, 13-15 April.
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Fletcher, S. J. and Vonder Haar, T. H., 2010: Development of a mixed Gaussianlognormal weak constraint 4D VAR system. CG/AR Annual Review, Fort Collins, CO,
30-31 March.
Seaman, C., Sengupta, M., Fletcher, S. J., Jones, A. S. and Vonder Haar, T. H., 2010:
Impact of Cloud-Affected Infrared Satellite Observations on a Cloud-Free Initial Model
State, CG/AR Annual Review, Fort Collins, CO, March 30-31.
Fletcher, S. J., Liston, G. E., Hiemstra C. A. and Miller, S. D., 2009: Assimilation of
MODIS snow cover data and AMSR-E snow water equivalent data into SnowModel. The
5th WMO Symposium on Data Assimilation, Melbourne, Australia, 5-9 October.
Fletcher, S. J., Zupanski, M, Jones, A. S., Sengputa, M. and Vonder Haar, T. H., 2009:
Non-Gaussian Data Assimilation, Cooperative Institute Director’s Meeting, Fort Collins,
CO, 16-17 June.
Jones, A. S., Fletcher, S. J., Longmore, S., Sengupta, M., Vonder Haar, T. H. and
Augline, T., 2009: Advanced WRF-4DVAR Cloud Data Assimilation using Satellite
Data, Cooperative Institute Director’s Meeting, Fort Collins, CO, 16-17 June.
Fletcher, S. J., Liston, G. E., Hiemstra, C. A. and Miller, S. D. 2009: Assimilation of
MODIS snow cover data into SnowModel. 8th International workshop on Adjoint Model
Applications in Dynamic Meteorology, Tannersville, PA, 18-22, May.
Fletcher, S. J., Sengupta, M. and Vonder Haar, T. H. 2009: 4-Dimensional non-Gaussian
Data Assimilation. CG/AR Annual Review, Fort Collins, CO, 11-12 March.
Fletcher, S.J., Zupanski, M., Navon, I.M., Uzunoglu, B., Heikes, R. and Randall, D.A., 2005:
A maximum likelihood ensemble filter with a shallow water model. Proceedings of the
fourth World Meteorological Organization’s International Symposium on Assimilation of
Observations in Meteorology and Oceanography. Prague, Czech Republic, 18-22 April.
Zupanski, M., Fletcher, S. J., Navon, I. M. and Uzunoglu, B. 2005: Maximum Likelihood
Ensemble Filter: Exploiting dynamic localization of Lyapunov vectors. 85th Annual
Meeting of the American Meteorological Society, San Diego, CA, 9-13 January.
g. Proposals PI/CoPI
Impact Assessment and Data Assimilation of NOAA NPP/JPSS Sounding products and
Quality Control Parameters, April 1, 2012 – March 31, 2014. (PI)
Improvements to background error covariances and moisture representation in the Navy's
Data Assimilation System, Jan 9, 2012 – Jan 8, 2014. (PI)
AFWA Coupled Assimilation and Prediction System Development at CIRA, Jan. 1, 2011
– Dec. 31, 2011, (CoPI)
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CIRA-NCAR/MMM WRF-Var Collaboration Work Plan, 19 April 2007 – 31 January 2008,
Leading the preconditioning work at CIRA/CSU. (CoPI)
h. Conference Convened/organizing committee
Annual Fall meeting of the American Geophysical Union, 3rd – 7th December, 2012,
San Francisco, CA: Convene and chaired the session in Non-Linear Geophysics Section
with Profs. Brian Ancell (TTU) and Derek Posselt (U. Michigan) titled ‘Non-Gaussian
and Non-Linear Aspects of Data Assimilation/Fusion and Predictability in the
Geosciences’
Annual Fall meeting of the American Geophysical Union, 5th – 9th December, 2011,
San Francisco, CA: Convene and chaired the session in Non-Linear Geophysics Section
with Profs. Brian Ancell (TTU) and Derek Posselt (U. Michigan) titled ‘Non-Gaussian
and Non-Linear Aspects of Data Assimilation and Predictability in the Geosciences’
Annual Fall meeting of the American Geophysical Union, 13th – 17th December,
2010, San Francisco, CA: Convened and Chaired the session in the Non-linear
Geophysics Section with Prof. Brian Ancell (TTU) titled ‘Non-Gaussian and NonLinear Aspects of Data Assimilation and Predictability in the Geosciences’
AFWA Cloud Analysis Workshop, 1st – 3rd September, 2009, NCAR Foothills
Laboratory, Boulder, CO: Organizing Committee, timetabling, chairing session on
Cloud prediction skills and verification.
i. Synergistic Activities
Co-Convener ATS 786: Topics in Data Assimilation, Spring 2011, Colorado State
University. Taught 2 lectures on non-Gaussian and then non-linear data assimilation.
Advised students and convened some of the lectures in this course.
Invited Lecturer for the Joint Center for Satellite Data Assimilation and the
University of Maryland’s workshop on Applications of Remotely Sensed Observations
in Data Assimilation, July 23rd – August 10th 2007: Non-Gaussian Data assimilation,
Minimization Algorithms and Preconditioning.
Associated Member of the Institute for Mathematics and its Applications, 2003Member of the American Meteorological Society, 2005Associate Fellow of the Royal Meteorological Society, 2005Student Member of the Royal Meteorological Society, 2002-2004,
Member of the European Geosciences Union, 2005Member of the American Geophysical Union (Nonlinear Geophysics), 2006Reviewer for the Journal of Geophysical Research: Atmospheres, Tellus A, Monthly
Weather Review, Quarterly Journal of the Royal Meteorological Society,
Hydrometeorology, Journal of Atmospheric Sciences, JAMES, Applied
Mathematics and Computation, Meteorology and Atmospheric Physics
Reviewer for the National Science Foundation.
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Part of the ACAPS 4D VAR development team for the WRF model.
CIRA Seminar Committee 2010 Teaching assistant at The Oxford/RAL Spring School in Quantitative Earth
Observations, March 12 – 23, 2001. The University of Oxford, United Kingdom.
i. Collaborators and Other Affiliations
(i) Collaborators
David Randall
Nancy Nichols
Ian Roulstone
Milija Zupanski
Dusanka Zupanski
I. Mike Navon
Dale Barker
Thomas Auligne
Andrew Jones
Glen Liston
Chris Hiemstra
Steven Miller
Nancy Baker
Colorado State University
University of Reading, UK
University of Surrey, UK
CIRA/Colorado State University
CIRA/Colorado State University
The Florida State University
NCAR/MMM
NCAR/MMM
CIRA/Colorado State University
CIRA/Colorado State University
CIRA/Colorado State University
CIRA/Colorado State University
NRL-Monterey
(ii) Conference organizing collaborators
Brian Ancell
Derek Posselt
Thomas Auligne
Texas Technical University
U. Michigan
MMM/NCAR
(iii) Masters Students Committee:
James Ruppert (CSU/ATS) 2011.
(iv) Interns Supervised
Erin Kashawlic – summer 2010, CMMAP intern working on non-Gaussian Data
assimilation.
(v) Students Mentored
Kevin Donofrio (MS, 2007), Curtis Seaman (Ph.D., 2009), Eric Guillot (MS, 2010).
(vi) Thesis Advisors
Nancy K. Nichols
Ian Roulstone
University of Reading, UK
Met Office, UK
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