1. a. FY12-13 GIMPAP Project Proposal Title Page version 27 October 2011 Title:GOES SST Assimilation for Nowcasts and Forecasts of Coastal Ocean Conditions Status: Renewal Duration: 2 years 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 1

2. b. Project Summary 2 We study the impact of GOES SST assimilation on outputs of the real-time coastal ocean forecast model off Oregon These data can be 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; -reliable 3-day dynamical forecasts of temperature, currents, and other conditions in the coastal zone.

3. c. Motivation / Justification 3 Supports NOAA Mission Goal(s): –Model Observational Infrastructure (MOBI) –Weather and Water –Commerce & Transportation GOES SST will be utilized to improve the accuracy of ocean state estimates and 3-day forecasts of ocean conditions over the shelf and in the eddy dominated coastal transition zone. Accurate forecasts of near-surface ocean conditions are important for fishing (and other shipping) vessel routing, homeland security, search and rescue, recreational activities, & environmental hazard response Our coastal ocean forecasts have been used by fishermen to guide their daily operations (they are looking for surface temperature fronts) Our velocity estimates will be tested with the oil spill prediction software, developed by NOAA Hazmat Tested off Oregon, our methods can be applied to other regions.

4. d. 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. 4 assim (Tangent linear &Adjoint) forecast (nonlinear ROMS)

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

6. Forecast products: http://www-hce.coas.oregonstate.edu/~orcoss/ACTZ/SSCforecast.html www.nanoos.org

7. 4. Methodology (Cont.) 12UTC 5pm (loc) 1am (loc) 9am (loc) 6pm (loc) 2am (loc) 10am (loc) 4DVAR: filter noise, fill in gaps in data  smooth, time- and space continuous SST map (+ velocity estimates, + 3-day forecast) ROMS before / after SST assimilation For verification: Multisatellite blended SST (D. Foley, CoastWatch) SST (color), SSH (contours, every 2.5 cm)

8. 8 4. Methodology (Cont.) Assimilation of GOES SST helped to improve the slope of SSH, when it was not assimilated improved geostrophic component of surface velocities SSH along J2 track 247: Free-run Analysis Monthly averaged SST (color), SSH (contours) – January 2011 GOES SST assimilation impacts patterns connecting interior and coastal ocean areas

9. e. Expected Outcomes 9 Accurate SST maps (a product of synthesis of data from different platforms) – combine GOES SST and AMSR-E assimilation 3-day forecasts of SST and surface currents Assimilation in a larger domain Understand the dynamical significance of SST in winter Understand the effect of surface data assimilation on subsurface flows Understand the effect of the Columbia River on SST in early spring Monitor diurnal variability in GOES SST (correlate with winds) [Merchant, Le Borgne et al., 2008]

10. e. Expected Outcomes (illustrations) 10 Assimilation in a larger domain (image courtesy P. Fayman, OSU) The effect of the Columbia River on SST in early spring (image courtesy E. Simmons III, OSU) HYCOM, 1/12 th degr., 18 Sep., 2008 GOES SST monthly composite, June 2011

11. e. Possible Path to Operations Maintain the year-around assimilation and forecasts off Oregon Provide forecasts for display at www.nanoos.org Create a more interactive display Coordinate with NOAA Hazmat (A. MacFayden) to use our velocity fields with the GNOME oil spill software Make users aware: fishermen, recreation (surfers), environmental hazard response, search&rescue 11

12. f. Milestones Test the utility of our forecast products driving the GNOME oil spill software (with A. MacFayden, NOAA) Evaluate accuracy/bias in AMSR-E compared to GOES SST and our model and make decision about adding AMSR-E to the set of assimilated data Evaluate the impact of SST, SSH, and HF radar surface current assimilation on subsurface oceanic fields Analyze the effect of GOES SST assimilation in winter, compared to other sources Evaluate the model with the Columbia R. and understand the impact of the river discharge on SST assimilation Set-up assimilation in the larger domain (extend the forecast capability to Northern California, Oregon, and Washington coasts) 12

13. g. Funding Request (K) Funding SourcesProcurement Office Purchase Items FY12FY13 GIMPAPStAR Total Project Funding 88,50093,524 StAR Grant to CI StAR Federal Travel StAR Federal Publication StAR Federal Equipment StAR Transfers to other agencies Other Sources 13

14. g. Spending Plan FY12 FY12 $88,500 Total Project Budget 1.Grant to CIOSS: - 88,500 –CIOSS labor: 50,658 (AK/PTS: 1 mo/year, P.Yu: 3mo/year) –Travel: 3,000 –Publication charge: 0 –Equipment (disk storage): 6,000 –Materials and supplies:1,200 –Computer services:1,500 –Communications:71 –Overhead @46.2%:26,071 2.Federal Travel – none 3.Federal Publication Charges – none 4.Federal Equipment - none 5.Transfers to other agencies – none 14

15. g. Spending Plan FY13 FY13 $93,524 Total Project Budget 1.Grant to CI -93,524 –CIOSS labor: 50,066 (AK/PTS: 1 mo/year, P.Yu: 3mo/year) –Travel - 3,000 –Publication charge - 2,000 2.Federal Travel – none 3.Federal Publication Charges – none 4.Federal Equipment - none 5.Transfers to other agencies – none –Other Equipment (disk storage) - $ 6,000 Material/supplies - $ 2,300 Overhead @ 46% $ 27,658 15