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Project Goals 2009-2011


Hurricane model transition to operations at NCEP/EMC: R. Tuleya (Old Dominion Univ.)

 

  • Obtain the most realistic hurricane initial condition possible.
  • Develop a more physically consistent landfall prediction, using an advanced land surface model and verifying both rainfall and winds.
  • Analysis and resolution of day-to-day problems in the HWRF system.

 

Improving the Hurricane WRF-Ocean Coupled System for Transition to Operations: I. Ginis (Univ. of Rhode Island) and M. Bender (NOAA/GFDL)

 

  • GFDN model improvement:
    1. Increase horizontal grid spacing from 1/12th to1/18th degree in the inner mesh.
    2. Couple with the WAVEWATCH III (WW3) wave model.
    3. Improve physics of the air-sea fluxes, including sea spray effects (implement the new URI air-sea interface model (ASIM) coupled with the ESRL sea-spray model).
    4. Implement Navy's NCODA real-time ocean analysis in the Atlantic basin.
  • HWRF model improvements
  • Improve physics of the air-sea fluxes, including sea spray effects (implement the new URI air-sea interface model (ASIM) coupled with the ESRL sea-spray model).
  • Assist in testing and evaluating the improved HWRF-Wave-Ocean coupled system.

 

Evaluation and Improvements of Cloud and Precipitation Physics in the Operational Hurricane WRF Model at NOAA/EMC: Y. Wang and V. Phillips (Univ. of Hawai.i)

 

  • Evaluate and identify possible discrepancies in current cloud and precipitation physics used in the HWRF model and understand how these discrepancies may affect hurricane structure and intensity.
  • Diagnose discrepancies of the current cloud and precipitation physics and the interaction between grid-scale moist processes and subgrid-scale convection in the HWRF model and to understand how they affect hurricane intensity and structure, including size.
  • Improve the representation of the cloud and precipitation physics in the HWRF model based on the PI and co-I.s previously results and evaluate the performance of the modified schemes through model inter-comparison between the HWRF model and TCM4.
  • Test and tune the modified schemes in the experimental prediction mode and to evaluate their overall improvements in predicting hurricane structure and intensity using the HWRF model hindcasts for the cases in the 2010 hurricane season.
  • Document the modified schemes with both technical and scientific details and to provide training to the members of the HWRF model development team at NCEP/EMC.

 

Evaluation and Improvement of Ocean Model Parameterizations for NCEP Operations: N. Shay (Univ. of Miami/RSMAS) and G. Halliwell (NOAA/AOML)

 

  • Determine lowest horizontal and vertical resolution that resolves the ocean response structure
  • Evaluate different vertical mixing schemes, including one proposed by Kantha and Clayson that is now being added to HYCOM
  • Improve ocean model initialization by evaluating ocean hindcasts available from operational centers (particularly NCEP and NRL) and provide feedback for improving these products, including the identification of deficiencies in observational coverage
  • Determine optimum parameterizations of surface flux drag coefficients, using results from tank experiments, GPS sonde analysis, and the Coupled Boundary Layer Air-Sea Transfer (CBLAST) program
  • Devise strategies to improve model efficiency (decrease run time)
  • Continue interaction with NOAA-NCEP-EMC that we established during summer 2008 help evaluate the ongoing HWRF tests.

 

Improving Predictability of the Atlantic Warm Pool (AWP) in Ocean Model for Assistance to Operational Hurricane Forecast: C. Wang and S.-K. Lee (NOAA/AOML)

 

  • Evaluate and improve HYCOM.s predictability of the AWP and associated mesoscale ocean features for NCEP/EMC transition to operational hurricane forecast
  • Deliver an improved Real Time Ocean Forecasting System for Atlantic that will be equipped with flux bias correction scheme (with an option to couple with an atmospheric mixed layer model), an optimized vertical coordinate scheme and on-line heat budget diagnosis routine.

 

Advanced Applications of the Monte Carlo Wind Probability Model: S. Kidder (Colo. Sate Univ.) and M. DeMaria (NOAA/NESDIS)

 

  • Develop four new applications and provide four code modifications to address model limitations.
    1. The calculation of the probability distributions of the storm intensity just before landfall and timing of landfall to supplement the wind probability table information, which provides the intensity distributions at fixed times
    2. Creation and evaluation of 5-year database of incremental probabilities for U.S. landfall storms at coastal breakpoints
    3. Development of a .line-integral. option that estimates the probabilities for any portion of a specified set of line segments for aid in interpretation and issuance of watches and warnings
    4. Development of an automated method for using the text probability product to provide guidance on watch/warning locations and timing.

 

ATCF Requirements, Intensity Consensus and Sea Heights Consistent w/ NHC Forecasts: B. Sampson (Naval Research Lab.)

 

  • Address NHC requirements.
  • Evaluate and improve Atlantic and eastern Pacific intensity consensus.
  • Implement WAVEWATCH III analysis and forecast consistent with advisories

 

In-Flight Data Processing for the Wind Swath Radar Altimeter (WSRA) for Real-Time Reporting of Directional Ocean Wave Spectra from the NOAA WP-3D Hurricane Reconnaissance Aircraft: I. PopStefanjia (ProSensing Inc.)

 

  • Develop processing algorithms and real-time software to perform in-flight data processing for newly developed Wide Swath Radar Altimeter (WSRA.
  • Optimize the WSRA digital beamforming and range centroid tracking algorithms, conversion of the processing algorithms into a multi-threaded C application, and deployment of a multi-core PC processor to execute in-flight processing.
  • Provide continuous real-time reporting of directional ocean wave spectra, significant wave height and the radius of 12. seas from the NOAA P-3 aircraft to the National Hurricane Center through a satellite data link.

 

Improvement in the Rapid Intensity Index Incorporation of Inner Core Information: J. Kaplan, J. Cione, J. Dunion (NOAA/AOML), J. Dostalek (CIRA/CSU), M. DeMaria, J. Knaff (NOAA/NESDIS) and T. Lee (NRL)

 

  • Improve the operational RII by including predictors derived from three new sources of inner core.
    1. Time evolution of inner-core structure as deduced from GOES IR imagery.
    2. Microwave-derived total precipitable water
    3. Inner-core fluxes of heat and moisture obtained from the sea-surface temperature computed from the SHIPS inner-core sea-surface temperature cooling algorithm as well as the operational GFS surface temperature and relative humidity forecast fields.

 

Improved Real-Time Hurricane Ocean Vector Winds from QuikSCAT: L. Jones (Univ. Central FL), E. Uhlhorn (NOAA/AOML), P. Chang and Z. Jelenak (NOAA/NESDIS)

 

  • Provide a new QuikSCAT hurricane wind product for forecast guidance.
  • Process, in near real-time, all QuikSCAT hurricane passes routinely captured by NOAA/NESDIS/ORA using the improved Q-Winds algorithm.
  • Develop appropriate training materials to facilitate proper operational utilization of new QuikSCAT product.

 

A New Secondary Eyewall Formation Index: Transition to Operations and Quantification of Associated Intensity Changes: J. Kossin (Univ. of Wisconsin/CIMSS)

 

  • Implement a new empirical/statistical model that provides real-time probability estimate forecast of secondary hurricane eyewall formation.
  • Transfer this new model onto the existing SHIPS platform.
  • Combine with the Annular Hurricane Index described by Knaff et al. (2003; 2008) to form a general objective tool that diagnoses imminent structure changes in hurricanes

 

Development of a Unified Dropsonde Quality Assurance and Visualization Capability: M. Black (NOAA/AOML) and C. Martin (NCAR/EOL)

 

  • Development of a single dropsonde QA software package that includes requirements definition, designing and implementing the software, testing and evaluation
  • Implement final software package along with the appropriate documentation and training.