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a. FY12-13 GIMPAP Project Proposal Title Page version 04 August 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. /[email protected]

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a fy12 13 gimpap project proposal title page version 04 august 2011
a. FY12-13 GIMPAP Project Proposal Title Pageversion 04 August 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. /[email protected]

P. Ted Strub/ CIOSS/ [email protected]

L. Miller / NOAA/NESDIS/STAR / [email protected]

E. Maturi / NOAA/NESDIS/STAR/SOCD / [email protected]

D. Foley / NOAA/NESDIS/CoastWatch/ [email protected]

Other Participants:

P. Yu / CIOSS, Oregon State University

b project summary
b. Project Summary
  • 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.
c motivation justification
c. Motivation / Justification
  • 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.
d methodology
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.

assim (Tangent linear &Adjoint)

forecast (nonlinear ROMS)

slide5

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

slide6

4. Methodology (Cont.)

Forecast products:

http://www-hce.coas.oregonstate.edu/~orcoss/ACTZ/SSCforecast.html

www.nanoos.org

slide7

4. Methodology (Cont.)

  • 4DVAR: filter noise, fill in gaps in data
  • smooth, time- and space continuous SST map
  • (+ velocity estimates, + 3-day forecast)

12UTC

5pm (loc)

6pm (loc)

ROMS before / after SST assimilation

2am (loc)

1am (loc)

10am (loc)

9am (loc)

For verification:

Multisatellite blended SST (D. Foley, CoastWatch)

SST (color),

SSH (contours, every 2.5 cm)

slide8

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:

Monthly averaged SST (color), SSH (contours) – January 2011

Free-run Analysis

GOES SST assimilation impacts patterns connecting interior and coastal ocean areas

e expected outcomes
e. Expected Outcomes
  • 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]
e expected outcomes illustrations
e. Expected Outcomes (illustrations)

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)

GOES SST monthly composite,

June 2011

HYCOM, 1/12thdegr.,

18 Sep., 2008

e possible path to operations
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
f milestones
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)
g spending plan fy12
g. Spending Plan FY12
  • FY12 $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
g spending plan fy13
g. Spending Plan FY13
  • FY13 $93,524 Total Project Budget
    • 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
    • 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% $ 27,658
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