SF
Member Since 2006
Steve J. Fletcher
Senior Research Scientist, Cooperative Institute for Research in the Atmosphere
AGU Research
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Extending and Reprocessing the NASA NVAP-M Water Vapour Dataset
ADVANCES IN DATA ASSIMILATION, DATA FUSION, MACHINE LEARNING, PREDICTABILITY, AND UNCERTAINTY QUANTIFICATION IN THE GEOSCIENCES III POSTER
nonlinear geophysics | 09 december 2024
Steven J. Fletcher, John M. Forsythe, Thomas H. Vo...
The existing NASA Water Vapor Project Making Earth System Data Records for Use in Research Environments (NVAP-M) dataset spans 1988-2009. It consists ...
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Thank You to Our 2023 Reviewers
EARTH AND SPACE SCIENCE
05 april 2024
Graziella Caprarelli, David Baratoux, Cinzia Cerva...
The Editors and Staff of Earth and Space Science thank the reviewers whose selfless work has significantly contributed to the publication process o...
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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