PPT-Impact of Glider Data Assimilation on the Global Ocean Forecasting System During

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. While written to incorporate computer technology the lesson can be easily adapted to paper and pen Lesson Objective Students will compose a series of slides based on the exhibits at OC The teacher may select one type of exhibit such as those that co 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”?. Yudong. Gao. 1 observational data analysis. Pictures are from P. W. Chan et al. (2014). Left figure is the reconnaissance data from 9:06 to 9:59 UTC, which is thinning at 3km. . data from 12:00 to 12:12 UTC. The direction of wind was changing as the flight direction.. 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. Kevin Garrett. 1,2,3. , Sid Boukabara. 1,2. , . and Erin Jones. 1,2,3. 1. NOAA/NESDIS/STAR. 2. Joint Center for Satellite Data Assimilation. 3.. Riverside Technology, Inc.. Preparation for GPM GMI . © 2011 Project Lead The Way, Inc.. Aerospace Engineering. Balsa Glider Construction. Balsa Wood. Very high . strength-to-weight ratio. Easy to cut and sand. Grainy. Available in strips, sheets, or blocks. in the . NOAA GDAS. Erin Jones. 1. , Kevin Garrett. 1. , Eric Maddy. 1. , Sid Boukabara. 2. 1. 1: . RTi. @ NOAA/NESDIS/STAR/JCSDA, 2: NOAA/NESDIS/STAR/JCSDA. Outline. Objectives. Passive microwave assimilation:.  . Cesaroni C.. 1. , . Spogli L.. 1,2. , . Aragon. -Angel A.. 3. , Fiocca M.. 4. , . Dear. V.. 5. , De Franceschi G.. 1. , Romano V.. 1,2. 1. Istituto . Nazionale di Geofisica e Vulcanologia, . Italy. 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. a flood forecasting system. . A tempered particle filter for combatting . degeneracy and sample impoverishment. .. Authors:. Concetta Di Mauro, Renaud Hostache, Patrick Matgen, Ramona Pelich, . Marco Chini, Peter Jan van Leeuwen, Nancy Nichols, and Günter Blöschl. 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. 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. 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 .