PPT-Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean

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Polly Smith Alison Fowler amp Amos Lawless School of Mathematical and Physical Sciences University of Reading UK Introduction 1 Typically initial conditions

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Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean: Transcript

Polly Smith Alison Fowler amp Amos Lawless School of Mathematical and Physical Sciences University of Reading UK Introduction 1 Typically initial conditions for coupled atmosphereocean model forecasts . strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean model. Polly Smith, Alison . Fowler & Amos . Lawless. School of Mathematical and Physical . Sciences, . University of . Building an idealised coupled system. Polly Smith, Amos . Lawless, Alison Fowler*. School of Mathematical and Physical Sciences, University of Reading, UK. * funded by NERC. Outline. Recap. objectives. Michele . Rienecker. Global Modeling and Assimilation Office. NASA/GSFC. WMO CAS Workshop. Sub-seasonal to Seasonal Prediction. Met Office, Exeter. 1 to 3 December 2010 . 2. What do we mean by “coupled data assimilation”?. Coupled Atmosphere-Ocean . Data . Assimilation. Strategies with an . EnKF. and a Low-Order Analogue of the . Climate System. Robert Tardif . Gregory J. Hakim . Chris Snyder. University of Washington. isopycnic. grids. Rainer Bleck, Shan Sun, . Haiqin. Li, Stan Benjamin. NOAA Earth System Research Laboratory. Boulder, Colorado. April 2016. Design . goals. :. (some reached, some pending). Global domain. calls. CW2015. Kristian. S. . Mogensen. Marine Prediction . Section. k.mogensen@ecmwf.int. Overview of talk:. Baseline:. The focus of this talk is going to be on coupling of IFS and WAM to NEMO. Motivation. 1. Saha-UMAC-09Aug2016. Atmosphere. , Land, Ocean, . Seaice. , Wave, . Chemistry, . Ionosphere. Data Assimilation cycle. Analysis frequency H. ourly. Forecast length . 9 . hours. Resolution . 10 . Presented By Suru . Saha. (EMC/NCEP). Contributors: . Jack Woollen, Daryl Kleist, Dave . Behringer. , Steve Penny, . Xingren . Wu, Bob . Grumbine. , Mike . Ek. , . Jiarui. Dong, . Shrinivas. . Moorthi. NON - VERTICAL CAVITY LASER ARRAYS BY ZIHE GAO DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Electrical and Computer Engineering in the NON-VERTICAL CAVITY LASER ARRAYSBYZIHE GAODISSERTATIONSubmitted in partial fulfillment of the requirementsfor the degree of Doctor of Philosophy in Electrical and Computer Engineeringin the Graduate C and Prospects for the Future. Michele Rienecker. Global Modeling and Assimilation Office. NASA/GSFC. With many . contributions borrowed . from the Ocean Data Assimilation . Community. e. specially. Co-authors of Rienecker et al. OceanObs’09. Spring 2012. Jose E. Schutt-Aine. Electrical & Computer Engineering. University of Illinois. jesa@illinois.edu. Signal Integrity. Crosstalk Dispersion Attenuation. Reflection Distortion Loss. 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. the 2018 Hurricane Season. Maria . Aristizabal. Scott Glen. Travis Miles . Avichal. . Mehra. Hyun-Sook Kim . Pat Hogan . Gregg Jacobs. Sue Chen. Assess the impact of glider data assimilation on the operational hurricane models .

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