PPT-A comparison of hybrid variational data assimilation methods in the Met Office

A comparison of hybrid variational data assimilation methods in the Met Office global NWP system Andrew Lorenc 11 th Adjoint Workshop Aveiro Portugal July 2018 wwwmetofficegovuk Crown Copyright 2018 Met Office. 1. Min-Jeong Kim. JCSDA 9th Workshop on Satellite Data Assimilation, May 24-25, 2011, M-J. Kim. 2. Fuzhong Weng, . 3. Emily Liu, . 4. Will McCarty, . 3. Yanqiu Zhu, . 3. John Derber, and . 3. Andrew Collard. . Radar Data Assimilation for 0-12 hour severe weather forecasting. Juanzhen. Sun . National Center for Atmospheric Research. Boulder, Colorado. sunj@ucar.edu. Outline. . Background. - . Motivation . for the NCEP GFS. Tom Hamill, for . Jeff . Whitaker. NOAA Earth System Research Lab, Boulder, CO, USA. jeffrey.s.whitaker@noaa.gov. Daryl Kleist, Dave Parrish and John . Derber. National Centers for Environmental Prediction, Camp Springs, MD, USA. P. Lewis. What is Data Assimilation?. Optimal merging of models and data. Models. Expression of current understanding about process. E.g. terrestrial C model. Data. Observations. E.g. EO. . Some basic stats. data assimilation. and forecast error statistics. Ross Bannister, 11. th. July 2011. University of Reading, r.n.bannister@reading.ac.uk. “All models are wrong …” . (George Box). “All models are wrong and all observations are inaccurate”. the Upper Troposphere - Lower Stratosphere. K. . Wargan, . S. . Pawson. , . M. . Olsen, . J. . Witte, . A. . Douglass. Global Modeling and Assimilation Office (GMAO). Chemistry and Dynamics Branch. NASA GSFC. EGU 2012, Vienna. Michail Vrettas. 1. , Dan Cornford. 1. , Manfred Opper. 2. 1. NCRG, Computer Science, Aston University, UK. 2. Technical University of Berlin, Germany. Why do data assimilation?. Aim of data assimilation is to estimate the posterior distribution of the state of a dynamical model (X) given observations (Y). When one cultural group adapts to another cultural group’s way of life. Language, religion, way of life is abandoned. Cultural differences then disappear. Cultural “uniformity” is created. Can be done voluntarily. Inference. Dave Moore, UC Berkeley. Advances in Approximate Bayesian Inference, NIPS 2016. Parameter Symmetries. . Model. Symmetry. Matrix factorization. Orthogonal. transforms. Variational. . a. Henning Lange, Mario . Bergés. , Zico Kolter. Variational Filtering. Statistical Inference. (Expectation Maximization, Variational Inference). Deep Learning. Dynamical Systems. Variational Filtering. in the NCEP Global Forecast System. 1. Ting-Chi Wu. 1. , Lewis Grasso. 1. , . Milija. Zupanski. 1. , Heather Cronk. 1. , . James Fluke. 1. , Richard Schulte. 2. , Wesley Berg. 2. , Anton Kliewer. 1. Mihail. Codrescu. 1. , Stefan Codrescu. 1,2. , . Mariangel. Fedrizzi. 1,2. , and Claudia Borries. 3. 1. Space Weather Prediction Center, Boulder, United States of America (. mihail.codrescu@noaa.gov. Jeremy Berman. University at Albany. Thursday 03 May 2018. ATM 419/563. Outline. Data Assimilation (DA). At the end, you should know:. What is it?. How it works?. Why is it important?. Basic DA techniques. the 2018 Hurricane Season. Maria . Aristizabal. Scott Glenn. Travis Miles . Benjamin . LaCour. Pat Hogan . MTS Oceans Meeting . 2019. Roy Watlington. Doug Wilson (OCOVI). Improve the intensity forecast of the operational hurricane models.