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Infusion of Data into Models

Infusion of Data into Models. Zhang Lin. Vogelmann Miller Jensen Wagener. Colle. Chang. Liu Daum Guo. NY Blue Center. Riemer. McGraw Schwartz Lewis Chang. Wang. Reisman Bhatt. Infusion of Data into Models Radar and Satellite Strategies (BNL) Ensemble Modeling (Colle)

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Infusion of Data into Models

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  1. Infusion of Data into Models Zhang Lin Vogelmann Miller Jensen Wagener Colle Chang Liu Daum Guo NY Blue Center Riemer McGraw Schwartz Lewis Chang Wang Reisman Bhatt

  2. Infusion of Data into Models • Radar and Satellite Strategies (BNL) • Ensemble Modeling (Colle) • Data Assimilation (Zhang)

  3. GPM BNL Model-Data Infusion Radar and Satellite Strategies for Blue Gene Model Development, Validation & Improvement

  4. SCM MMF (Quasi-2D) CSRM (Quasi-3D) Global Modeling Resolution Progression • BNL Model-Data Efforts • Active Remote Sensing of Cloud Layers (ARSCL) • Microbase cloud property retrievals • Broadband Heating Rate Profile Project • Doppler Spectrum Processing

  5. Cloud & Storm Tracking Using geostationary satellite data Provides an underutilized validation method for high-resolution Blue Gene model simulations

  6. CloudSat & CALIPSO • Space-borne Radar & Lidar • Launched 2006 • Profiles Clouds & Aerosols

  7. Cloud-Aerosol-Transport Science A Collaborative BNL-SBU Research Team A Pending LDRD Proposal Compelling question example: What are the Southeast Asian pollution-cloud interactions & impacts on the current and future climate? BNL Atmospheric Sciences Division (ASD) Vogelmann, McGraw* Luke, Benkovitz, Jensen, Lewis, Liu Scientific Information Systems Group (SISG) Wagener, Cialella Computational Science Center (CSC) Davenport SBU/ITPA Faculty Zhang (ITPA Director), Marat Khairoutdinov (SBU supercomputer hire), Colle, & Riemer

  8. Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) An National Science Foundation Engineering Center • Contribution from Kollias (McGill) & Wiscombe (DOE-ARM/BNL) • DOE/ARM-CASA partnership • 3-D Scanning precipitation radars • Distributed Collaborative Adaptive Sensing networks http://www.casa.umass.edu/

  9. Recent DOE/ARM-CASA Partnership Common objective  the fill observational “gaps” CASA – Observe lowest 3 km of the atmosphere Poorly sampled by the NEXRAD radars (esp. at long ranges) ARM – Provide long-term quality measurements of clouds & precipitation to test and validate MMF results. Synergistic capabilities CASA – Emerging, robust, low-cost technologies for observation of precipitation, winds at low-levels ARM – Extensive experience in quality measurements of cloud & radiation

  10. 15-Member MM5 and WRF Ensemble at Stony Brook

  11. 6h forecast (July 6 2003) 12h forecast Radar observation at 0600 UTC at 1200 UTC • Without high-resolution initialization: • A model can take a • number of hours to • spin up. • Convection with weak • synoptic-scale forcing • can be missed. Example of model spin-up problem Graphic source: http://www.joss.ucar.edu

  12. Dual-Doppler (WSR-88D and TDWR) Analysis Single-Doppler (KOUN) Assimilation 8 May 2003 Oklahoma City Storm:Single-Radar Assimilation Vs. Independent Dual-Doppler Analysis Reflectivity and Wind at 300 m Above Ground Level Images provided by F. Zhang, Texas A&M

  13. Ensemble Storm-Scale Forecasting WRF 4km NMM 4.5km WRF 2km Observed Morris Weisman - NCAR

  14. Assimilation of Data To Improve Initial Conditions (Zhang) Plan: From Single Column to Gridded Fields

  15. Reducing Systematic Model Biases & Assimilation of Data for El Nino Forecasts (Zhang) Plan: POP + CAM or CCSM Resolution and Sensitivity Experiment

  16. Initial Condition (IC) Dependence (IPCC 2007)

  17. 2006/07 Dec-Jan-Feb Precipitation Anomaly Outlook Climate Forecast System (CFS) Observations Outlook (IPCC 2007)

  18. Zhang Zhang Marat K. Vogelmann Vogelmann Lin Lin Miller Miller Colle Colle Jensen Jensen Wagener Wagener Liu Liu Daum Daum Chang Chang NY Blue NY Blue NY Blue NY Blue Guo Guo Center Center Center Center McGraw McGraw Schwartz Schwartz Riemer Riemer Lewis Lewis Chang Chang Reisman Reisman Wang Wang Bhatt Bhatt • Data Infusion Summary • SBU-BNL team enables opportunities to: • Exploit underutilized and/or emerging radar & satellite • technologies in model development & improvement • Ensemble modeling benefits significantly from • Blue Gene capabilities • Enhances ability to estimate the variance & the • initial condition treatments of the input fields

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