SF
Member Since 2006
Steve J. Fletcher
Senior Research Scientist, Cooperative Institute for Research in the Atmosphere
AGU Research
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Non-Gaussian based Maximum Likelihood Ensemble Smoothers
ADVANCES IN DATA ASSIMILATION, PREDICTABILITY, AND UNCERTAINTY QUANTIFICATION III POSTER
nonlinear geophysics | 13 december 2023
Steven J. Fletcher, Senne Van Loon, Milija Zupansk...
Recently the Maximum Likelihood Ensemble Filter (MLEF) has been extended to allow for lognormal as well as reverse lognormal errors that is based upon...
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Multisatellite Water Vapor Products at the Weather / Climate Interface
BRIDGING THE GAP FROM CLIMATE TO EXTREME WEATHER: OBSERVATIONS, THEORY, AND MODELING I POSTER
atmospheric sciences | 12 december 2023
John M. Forsythe, Thomas H. Vonder Haar, Jack Dost...
Water vapor is the fuel for much of what we perceive as weather, including the formation of clouds and precipitation. Since the primary source of wate...
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Foundations for Universal Non-Gaussian Data Assimilation
ADVANCES IN DATA ASSIMILATION, PREDICTABILITY, AND UNCERTAINTY QUANTIFICATION I ORAL
nonlinear geophysics | 12 december 2023
Senne Van Loon, Steven J. Fletcher
In almost all applications of data assimilation, a substantial assumption is made: all variables are well-described by Gaussian error statistics. This...
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Foundations for Universal Non‐Gaussian Data Assimilation
GEOPHYSICAL RESEARCH LETTERS
02 december 2023
Senne Van Loon, Steven J. Fletcher
In many applications of data assimilation, especially when the size of the problem is large, a substantial assumption is made: all variables are we...
Non‐Gaussian Hybrid Variational Data Assimilation
ADVANCES IN DATA ASSIMILATION, PREDICTABILITY, AND UNCERTAINTY QUANTIFICATION IV POSTER
nonlinear geophysics | 14 december 2022
Steven J. Fletcher, Senne Van Loon, Jakir Hossen, ...
With the advancement of nonGaussian based variational techniques the need to extend this to hybrid ensemblevariational techniques is the next step tow...
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Machine Learning for Distribution Selection in Non-Gaussian Variational Data Assimilation
ADVANCES IN DATA ASSIMILATION, PREDICTABILITY, AND UNCERTAINTY QUANTIFICATION IV POSTER
nonlinear geophysics | 14 december 2022
Senne Van Loon, Steven J. Fletcher, Jakir Hossen, ...
Recent advances have made it possible to relax the Gaussian assumption in variational data assimilation, and allow for lognormal or mixed Gaussian-log...
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Non‐Gaussian Detection Using Machine Learning With Data Assimilation Applications
EARTH AND SPACE SCIENCE
22 april 2022
Michael Goodliff, Steven J. Fletcher, Anton Kliewe...
In most data assimilation and numerical weather prediction systems, the Gaussian assumption is prevalent for the behavior of the random variables/e...
Non-Gaussian Hybrid Variational Data Assimilation
ADVANCES IN DATA ASSIMILATION, PREDICTABILITY, AND UNCERTAINTY QUANTIFICATION III POSTER
nonlinear geophysics | 14 december 2021
Steven J. Fletcher, Michael Goodliff, Jakir Hossen...
With the advancement of non-Gaussian based variational techniques the need to extend this to hybrid techniques is the next step towards operational vi...
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