Observing System Simulation Experiments (OSSEs)

North Atlantic Hurricane Region Hybrid Coordinate Ocean Model (ATL-HYCOM) Observing System Simulation Experiments (OSSEs)

Observing System Simulation Experiments (OSSEs) enable the impact of ocean observing systems to be determined entirely from ocean models without the need to actually deploy the instruments. The joint AOML/CIMAS/UM-RSMAS Ocean Modeling and OSSE Center (OMOC) has developed a fraternal twin ocean OSSE syste based on two different configurations of the HYCOM.

The full OSSE system was successfully validated in the open Gulf of Mexico (Halliwell et al., 2014) by documenting the positive impact of airborne ocean profilinf surveys conducted during the 2010 Deepwater Horizon oil spill to improve ocean analyses and forecast.

The OSSE system has been expanded into a larger Atlantic Ocean domain to primarily determine the impact of existing and planned operational ocean observing systems on improving hurricane intensity forecasts. The OSSE sustem will also be demonstrated for other apllications, including monitoring and forecasting seasonal evolution of the Atlantic Warm Pool that provides thermal energy to hurricanes, the spreading of freshwater from the Amazon River basic, and other specific regional and coastal applications within the larger domain.

Halliwell. G.R., A. Shrinivasan, V.H. Kourafalou, H. Yang, D. Willey, M. Le Henaff and R. Atlas, 2014. Rigorous Evaluation of a Fraternal Twin Ocean OSSE System for the Open Gulf of Mexico. J. Atm. Ocean. Techn. 31(1):105-130, doi:10.1175/JTECH-D-13-00011.1.
Example results from multiple glider experiment

(a) Initial Syntheric Glider Experiment:
     During the 2009 hurricane season, eleven syntheric gliders were deployed, which sampled T,S profiles to 1000m several times per day along their tracks (red gliders roughly correspond to two gliders released for AOML/PHOD glider project).

(b) H20 Error Reduction due to Gliders:
  Figure shows percent change in mean error (ME) in depth of 20oC isotherm compared to control run due to adding synthetic glider assimilation - blue regions near gliders highlight mean error reduction due to glider data assimilation.

(c) SSS Error Reduction due to Gliders:
    Figure shows percent change in mean SSS error compared to control run due to adding syntheric gloder assimilation-blue regions near gliders reveal error reduction due to glider data assimilation.

Villy Kourafalou — vkourafalou@rsmas.miami.edu
George Halliwell — George.Halliwell@noaa.gov