1 . FY12-13 GIMPAP Project Proposal Title Page date: 7 August 2012 - PowerPoint PPT Presentation

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1 . FY12-13 GIMPAP Project Proposal Title Page date: 7 August 2012

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  1. 1. FY12-13 GIMPAP Project Proposal Title Pagedate: 7 August 2012 15 Title: GOES SST Assimilation for Nowcasts and Forecasts of Coastal Ocean Conditions Status: Progress Report Project Leads: Alexander Kurapov /CIOSS, Oregon State U. /kurapov@coas.oregonstate.edu P. Ted Strub / CIOSS/ tstrub@coas.oregonstate.edu L. Miller / NOAA/NESDIS/STAR / Laury.Miller@noaa.gov E. Maturi / NOAA/NESDIS/STAR/SOCD / Eileen.Maturi@noaa.gov D. Foley / NOAA/NESDIS/CoastWatch / dave.foley@noaa.gov Other Participants: P. Yu / CIOSS, Oregon State University

  2. 2. Project Summary • Hourly GOES SST are assimilated in the real-time forecast model that predicts coastal ocean circulation off Oregon • These data are assimilated in combination with HF radar surface currents and along-track SSH • We have developed, and will continue testing, a tool that provides: • cloud-free maps of SST within 500 km of the coast; • accurate near-surface velocity fields, dynamically consistent with observed SST; • synthesis of SST and other near-real time observations (land-based HF radar and along-track altimetry) • reliable 3-day dynamical forecasts of temperature, currents, and other conditions in the coastal zone(popular among fishermen) • The surface velocity fields are provided to the NOAA ORR lab (Watabayashi, MacFadyen) via the OpenDAP server, where our fields are currently used to track large marine debris originated from the Japan Tsunami

  3. Our model forecasts are currently used by NOAA ORR to track marine debris objects like this, sighted recently by the Coast Guard. [Photo courtesy CG and G. Watabayashi] • Risks: • navigation safety • bio-fouling (invasive species) 30ft x 10ft object “As along as the object is within the OSU ROMS grid, we will continue to make the model one of the key data sources we tap into so feel free to mention this when it comes time to justify funding. Sorry but we have no $$ to throw your way.” Glen (Bushy) Watabayashi(NOAA ORR, Seattle)

  4. A dock from Japan settled on the Oregon coast (Agate Beach) (photo courtesy J. Stork, KVAL.com)

  5. 3. Motivation / Justification • Fishermen, to plan their trips, want to know the SST front location for tomorrow, or 2 days from now, not two days ago. • We can assimilate SST in the coastal ocean model to improve accuracy of the initial conditions for the SST forecasts • SST is dynamically coupled with surface currents. Assimilation of SST can help to improve currents (esp. in frontal regions where SST contrasts are large • Supporting NOAA Mission Goal(s): • Model Observational Infrastructure (MOBI) • Weather and Water • Commerce & Transportation

  6. SST and surface velocities are coupled (geostrophy, advection) Model surface velocities (vectors, largest are near 1 m/s) and SST (color, C), Aug 23, 2011

  7. Forecast model estimates obtained on Jul-30-2012: substantial temporal variability in near-coast SST on scales of several days +2 d forecast

  8. GOES SST: very sparse coverage, given our scales of interest Variational Data Assimilation: The dynamical model is used as a time- and space- interpolator of the sparse data sets (also combining SST with other data)

  9. 4. Methodology • Our forecast model is ROMS, at 3 km horizontal resolution • Our data assimilation system is based on the variational approach (4DVAR, representer-based) and utilizes the tangent linear model AVRORA and its adjoint, developed at Oregon State U. • Observations are assimilated in a series of 3-day time windows. Initial conditions are corrected at the beginning of each window, to improve fit of the nonlinear model to assimilated observations • The correction is multivariate, with dominant balances between temperature, SSH, and currents maintained • Nonlinear model starts from the corrected initial conditions and runs until the end of the next time window, providing nowcast and forecast. assim (Tangent linear &Adjoint) forecast (nonlinear ROMS) 5/20 5/23 5/26 5/29 6/1 6/4 6/7

  10. 4. Methodology (Cont.) 4DVAR = dynamically based time- and space- interpolation of data HF radar daily ave maps GOES hourly data forecast analysis time present - 3 days → min

  11. 4. Methodology (Cont.) Forecast products: http://www-hce.coas.oregonstate.edu/~orcoss/ACTZ/SSCforecast.html www.nanoos.org + OpenDAP server for automatic and rapid delivery of surface fields to NOAA ORR

  12. Forecast product improvement: • (1) QC (pre-assimilation data evaluation / rejection) • (2) Development of a new model • (so far tested without data assimilation) • larger domain (OR+WA) • 2-km horizontal resolution • Columbia R., tides • Tests and model-data comparisons: Columbia R. influences SST (e.g., colder in winter) ROMS ave SST, Jan 2009 Monthly GOES Monthly ROMS (1/09)

  13. Velocity differences in the river plume (winter): (color is SSS, < 32 psu) w/out CR w/ CR h=50 m Low-pass filterted and daily ave currents on Jan 13 2009 (low winds)

  14. 5. Expected Outcomes • Accurate SST maps (a product of synthesis of data from different platforms) – combine GOES SST, AVHRR, VIIRS NPP (esp. microwave) • 3-day forecasts of SST and surface currents: help track marine debris • Assimilation in a larger domain, with Columbia R. • Include assimilation of T and S vertical sections from autonomous underwater vehicles - gliders (Barth, NSF OOI)

  15. 6. First Year - Preliminary Results • Coastal ocean forecasts have been delivered to NOAA ORR via the OpenDAP server and general public (via www.nanoos.org) • The new model has been developed (including OR and WA coasts, Columbia R. discharge, higher resolution, global NAVY/NOAA forecasts are used for boundary conditions) • The effect of the CR on SST in winter (downwelling) and summer (upwelling) has been studied - winter: colder signal along the WA coast - summer: upwelling and frontal current enhancement along OR coast • The study of the effect of HF radar surface current assimilation on SST is completed (Yu et al., Oc. Mod., 2012)

  16. 7. Possible Path to Operations • Maintain the year-around assimilation and forecasts off Oregon • Provide forecasts for display at www.nanoos.org, maintain the OpenDAP server for NOAA ORR • Make users aware of this product: fishermen, environmental hazard response, search&rescue • Coordinate activities with the NOAA ocean modelers (NCEP, NOS), e.g., via the Ocean Working Group

  17. 8. FY13 Milestones • Set-up assimilation in the larger domain: testing (hindcasts), transition to real-time operation • Maintain daily updates of 3-day forecasts • Include assimilation of new data streams: AVHRR, VIIRS, glider, Cryosat altimeter • QC: pre-assimilation review of the data, comparing to unassimilated data • Work with NOAA ORR personnel to assess quality of forecasts, tracking marine debris

  18. 9. Funding Request (K)

  19. 10. Spending Plan FY13 • FY13 $89,465 Total Project Budget • Grant to CI -89,465 • CIOSS labor: 47,368 (AK/PTS: 1 mo/year, P.Yu: 3mo/year) • Travel - 3,000 • Publication charge - 2,000 • Federal Travel – none • Federal Publication Charges – none • Federal Equipment - none • Transfers to other agencies – none • Other • Equipment (disk storage) - $ 6,000 • Material/supplies - $ 2,300 • Overhead @ 46.2% $ 26,297