'Adjoint model' presentation slideshows

Accomplishments:

ROMS data assimilation for ESPreSSO. Accomplishments:. * Nested ROMS in larger domain forward simulation (MABGOM-ROMS) with configuration suitable for IS4DVAR experimentation. Considerations: boundary conditions, resolution, computational cost

683 views • 51 slides

Data Assimilation and Predictability Studies for Improving Tropical Cyclone Intensity Forecasts

March 2012, NOPP TC Topic Review, Miami. Data Assimilation and Predictability Studies for Improving Tropical Cyclone Intensity Forecasts. PI: Takemasa Miyoshi University of Maryland, College Park miyoshi@atmos.umd.edu Co-PIs : E. Kalnay , K. Ide (UMD), and C . H. Bishop (NRL).

642 views • 50 slides

Data Assimilation by the Adjoint Method in Coastal and River Models

588 views • 47 slides

Performance Characteristics of a Pseudo-operational Ensemble Kalman Filter

Performance Characteristics of a Pseudo-operational Ensemble Kalman Filter. Greg Hakim & Ryan Torn University of Washington http://www.atmos.washington.edu/~hakim. April 2006, EnKF Wildflower Meeting. Outline. Issues for limited-area EnKFs. Boundary conditions. Nesting.

632 views • 46 slides

Optimization for inverse modelling

564 views • 40 slides

Daily Operation and Validation of a Global Assimilative Ionosphere Model

Daily Operation and Validation of a Global Assimilative Ionosphere Model. USC/JPL GAIM. Brian Wilson, JPL George Hajj, JPL, USC Lukas Mandrake, JPL Xiaoqing Pi, JPL, USC Chunming Wang, USC Gary Rosen, USC. Beacon Satellite Symposium, Trieste, Italy, Oct. 18-22, 2004. Outline.

521 views • 40 slides

ROMS User Meeting Grenoble, 6-8 October 2008

508 views • 40 slides

Application and interpretation of adjoint-derived sensitivities in synoptic-case studies

Application and interpretation of adjoint-derived sensitivities in synoptic-case studies. Michael C. Morgan University of Wisconsin-Madison. Acknowledgements. Linda Keller Kate La Casse Dr. Hyun Mee Kim (KMA) Daryl T. Kleist (NCEP/NOAA). Goals. Describe what an adjoint model is

512 views • 39 slides

471 views • 39 slides

Dr. Ronald M. Errico Goddard Earth Sciences and Technology Center (UMBC)

Introduction to Adjoint Models. Dr. Ronald M. Errico Goddard Earth Sciences and Technology Center (UMBC) Global Modeling and Assimilation Office (NASA). Outline. 1. Sensitivity analysis 2. Examples of adjoint-derived sensitivity 3. Development of adjoint model software

477 views • 36 slides

Integrated boundary current observations in the global climate system

385 views • 28 slides

Interpretation of station data with an adjoint Model

Interpretation of station data with an adjoint Model. Maarten Krol (IMAU) Peter Bergamaschi (ISPRA) Jan Fokke Meierink, Henk Eskes (KNMI) Sander Houweling (SRON/IMAU). What is TM5?. Global model with zoom option Two-way nesting Mass-conserving / Positive

391 views • 27 slides

How Predictable Is Tropical Cyclone Intensity Change?

How Predictable Is Tropical Cyclone Intensity Change?. Mark DeMaria NOAA/NESDIS/RAMMB NCAR Collaborative Tropical Cyclone Meeting 16 January 2008. NHC Official Intensity Forecast Errors 2001-2006 Atlantic Sample. Hurricane Intensity Research Working Group (HIRWG) Forecast Goal.

369 views • 23 slides

A Simplified Dynamical System for Tropical Cyclone Intensity Evolution

A Simplified Dynamical System for Tropical Cyclone Intensity Evolution. Mark DeMaria, NESDIS/StAR Fort Collins, CO 80523 Presented at The 28 th AMS Conference on Hurricanes and Tropical Meteorology, April 28-May 2, 2008. Outline. The logistic growth equation model

300 views • 20 slides

Setup of 4D VAR inverse modelling system for atmospheric CH 4 using the TM5 adjoint model

Setup of 4D VAR inverse modelling system for atmospheric CH 4 using the TM5 adjoint model. Peter Bergamaschi Climate Change Unit Institute for Environment and Sustainability(IES) Joint Research Center Ispra, Italy. Maarten Krol Institute for Marine and Atmospheric Research

333 views • 19 slides

Kumaresh Singh Department of Computer Science, Virginia Tech

Assimilating Tropospheric Emission Spectrometer profiles into GEOS-Chem. Kumaresh Singh Department of Computer Science, Virginia Tech Paul Eller, Adrian Sandu, Mohamed Jardak , Kevin Bowmann, Daven Henze, Dylan Jones, Meemong Lee. Motivation.

381 views • 18 slides

Monika Kopacz 1 , Daniel J. Jacob 1 , Daven Henze 2 ,

Comparison of adjoint and analytical approaches for solving atmospheric chemistry inverse problems. Monika Kopacz 1 , Daniel J. Jacob 1 , Daven Henze 2 , Colette Heald 3 , David G. Streets 4 , Qiang Zhang 5 October 11, 2006.

324 views • 17 slides

Adjoint model of the GYRE configuration of NEMO by using the YAO software

230 views • 13 slides

Sensitivity Analysis of SST along NJ coast with ADROMS

Sensitivity Analysis of SST along NJ coast with ADROMS. Weifeng (Gordon) Zhang John Wilkin Julia Levin Hernan Arango Institute of Marine and Coastal Sciences, Rutgers University Oct. 2005. Background. Plenty of measurement in New Jersey shore area;

198 views • 11 slides

Derivative-based uncertainty quantification in climate modeling

Derivative-based uncertainty quantification in climate modeling. P. Heimbach 1 , D. Goldberg 2 , C. Hill 1 , C. Jackson 3 , N. Petra 3 , S. Price 4 , G. Stadler 5 , J. Utke 6 MIT, EAPS, Cambridge, MA U. Edinburgh, UK UT Austin, TX LANL, Los Alamos, NM ANL, Chicago, IL.

241 views • 10 slides