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GOES-R Risk Reduction – Ocean Dynamics

Research Topic: Data Fusion and Algorithm Development
Task Leader: Andy Harris
CICS Scientist: Andy Harris
Sponsor: NESDIS GOESPO & STAR
Published Date: 7/25/2014
AHAH_GOES_1-1

FY13 REPORT

BACKGROUND

The goal of this task is to develop and evaluate alternative algorithms to satisfy the requirement for ABI Ocean Surface Currents (OSC) product generation.  Although there is an Ocean Dynamics (OD) component to the GOES-R Algorithm Working Group (AWG), there have been some concerns expressed by end-user that the final product will not correctly represent the required current vectors.  While the 80% AWG targets for OD accuracy were largely being met after the application of quality control measures based on a gradient strength metric, there is potential scope for improvement (see Figure 1).

AHAH_MDCB_3

Figure 1.  Locations and magnitudes of current U&V Component biases w.r.t. Navy Global NCOM data.  As can be seen, while the V-component shows relatively little bias, the U-component displays a significant geographical preference.

During this project, collaborators at Oregon State University (OSU) have implemented and evaluated two approaches to estimate ocean surface currents, using satellite-derived sea surface temperature (SST) fields:  “Feature Tracking;” and “Data Assimilation” into coastal circulation models.

Results from the first approach, use of feature tracking methods, are consistent with previous evaluations – the methods recover velocity fields with directions of the velocities that are qualitatively reasonable but with speeds that are greatly underestimated.  We are working to understand why this happens in an attempt to develop a methodology that would find only a small number of good velocities, for assimilation into ocean circulation models. Results from the second approach, data assimilation of the GOES SST fields into the dynamical ocean circulation model, are very positive, especially when multiple fields are assimilated (SST, altimeter SSH, coastal HF Radar surface velocities, etc.). The assimilation of the SST fields increases the realism of the model nowcast and forecast velocity and water property fields.

ACHIEVEMENTS

While significant results were obtained during the first two years of the project, most of these were accomplished by our partners at OSU (who received the vast majority of funding).  During Year-3, residual project funds have been used to support a PhD graduate student at the University of Maryland.  The student, Jeehye Han, completed her comprehensive exams and took the Data Assimilation class at UMD, in preparation for this research project.  Another researcher, Dr Daniel Comarazamy (NOAA-CREST), has recently joined NOAA/STAR and has been instrumental in transferring technology from OSU to the NOAA S4 supercomputer.

Since the project is entering a enter a new educational and research phase, the goals are now more directed towards coupled modeling and data assimilation rather than the specific one of ocean currents.  This has effectively been mandated by insufficient resource to enable the work to be done on the feasibility of a research-to-operations transition.  To this end, substantial progress has been made on all of the intended goals:

·         Familiarization with work accomplished by OSU

·         Setting up student with access to modeling capability

·         Procuring sample datasets for initial assimilation runs

·         Results of initial tests for coupled modeling with different assimilation methods (3-d VAR, 4-d VAR, Ensemble Kalman Filter).  This is only in the initial phase

PUBLICATIONS

None

DELIVERABLES

  • Report on GAASP AMSR-2 SST product accuracy;
  • Contribution of materials to NOAA design reviews.

PRESENTATIONS

None

OTHER

N/A

 

PERFORMANCE METRICS

 

FY13

# of new or improved products developed following NOAA guidance

0

# of products or techniques transitioned from research to ops following NOAA guidance

0

# of new or improved products developed without NOAA guidance

0

# of products or techniques transitioned from research to ops without NOAA guidance

0

# of peer reviewed papers

0

# of non-peered reviewed papers

0

# of invited presentations

0

# of graduate students supported by a CICS task

1

# of graduate students formally advised

1

# of undergraduate students mentored during the year

0

 

PERFORMANCE METRICS EXPLANATION

The entire budget for this project (residual funding originally intended for Year 2 but deferred to Year 3) is devoted to the support of the graduate student.

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