PPT-Joint Center for Satellite Data Assimilation (JCSDA)
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Architects Yannick Trémolet Thomas Auligne Presenter Guillaume Vernieres The Joint Effort for Data assimilation Integration JEDI as a Framework for Interdisciplinary
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Joint Center for Satellite Data Assimilation (JCSDA): Transcript
Architects Yannick Trémolet Thomas Auligne Presenter Guillaume Vernieres The Joint Effort for Data assimilation Integration JEDI as a Framework for Interdisciplinary Application Joint Center for Satellite Data Assimilation. 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. 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. 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”?. Benjamin Ruston. Steve Swadley, Nancy Baker, . Rolf . Langland. NRL, . Monterey, . CA. Outline. Gather information about instrument: . What are previous sensors or instruments, how have they been used?. 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.. Lecture 1: Theory. Steven J. Fletcher. Cooperative Institute for Research in the Atmosphere. Colorado State University. Overview of Lecture. Motivation. Evidence for non-Gaussian . Behaviour. Distributions and Descriptive Statistics . Gregory Carmichael(1), . Pablo . E. . Saide. (NCAR), . Meng. . Gao. (1), Maryam . Abdioskouei. (1), . Arlindo da Silva (NASA GSFC), R. Brad Pierce (NOAA NESDIS-STAR), David G. Streets (ANL), . Jhoon. 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 . Lecture . 2: Applications. Steven J. Fletcher. Cooperative Institute for Research in the Atmosphere. Colorado State University. Overview of Lecture. Do we linearize the Bayesian problem or do we find the Bayesian Problem for the linear increment?. Lecture . 2: Applications. Steven J. Fletcher. Cooperative Institute for Research in the Atmosphere. Colorado State University. Overview of Lecture. Do we linearize the Bayesian problem or do we find the Bayesian Problem for the linear increment?. June 5-7, 2013, NCWCP, College Park, MD. Utility of . GOES. -R . ABI . and GLM instruments in . regional . data assimilation . for . high-. impact weather. Milija Zupanski. Cooperative . Institute for Research in the Atmosphere. . VIIRS Snow . and . Ice Product Provisional Maturity Review November 14, 2013. Mike . Ek. , . Jiarui. Dong . and EMC Land Team. NOAA/NCEP/EMC. •. Unified Noah LSM in all NCEP NWP and climate systems, plus in NLDAS/GLDAS.. Polly Smith, Alison . Fowler & Amos . Lawless. School of Mathematical and Physical . Sciences, . University of . Reading, UK.. Introduction (1). Typically, . initial conditions for coupled atmosphere-ocean model forecasts . 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.
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