Comparison of 4DVAR and EnKF state estimates and forecasts in the Gulf of Mexico
KAUST DepartmentEarth Fluid Modeling and Prediction Group
Earth Science and Engineering Program
Physical Science and Engineering (PSE) Division
Permanent link to this recordhttp://hdl.handle.net/10754/631839
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AbstractAn experiment is conducted to compare four-dimensional variational (4DVAR) and ensemble Kalman filter (EnKF) assimilation systems and their predictability in the Gulf of Mexico (GoM) using the Massachusetts Institute of Technology general circulation model (MITgcm). The quality of the ocean-state estimates, forecasts, and the contribution of ensemble prediction are evaluated. The MITgcm–Estimating the Circulation and Climate of the Ocean (ECCO) 4DVAR (MITgcm–ECCO) and the MITgcm–Data Assimilation Research Testbed (DART) EnKF (MITgcm–DART) systems were used to compute two-month hindcasts (March–April, 2010) by assimilating satellite-derived along-track sea-surface height (SSH) and gridded sea-surface temperature (SST) observations. The estimates from both methods at the end of the hindcast period were then used to initialize forecasts for two months (May–June, 2010). This period was selected because a loop current (LC) eddy (Eddy Franklin: Eddy-F) detachment event occurred at the end of May 2010, immediately after the Deepwater Horizon (DwH) oil spill. Despite some differences between the setups, both systems produce analyses and forecasts of comparable quality and both solutions significantly outperformed model persistence. A reference forecast initialized from the 1/12° Hybrid Coordinate Ocean Model (HYCOM)/NCODA global analysis also performed well. The EnKF experiments for sensitivity to filter parameters showed enhanced predictability when using more ensemble members and stronger covariance localization, but not for larger inflation. The EnKF experiments varying the number of assimilation cycles showed enhanced short-term (long-term) predictability with fewer (more) assimilation cycles. Additional hindcast and forecast experiments at other times of significant LC evolution showed mixed performance of both systems, which depends strongly on the background state of the GoM circulation. The present work demonstrates a practical application of both assimilation methods for the GoM and compares them in a limited number of realizations. The overall conclusion showing improved short-term (long-term) predictability for EnKF (4DVAR) carries an important caveat that the results from this study are specific to a few 4DVAR and EnKF LC eddy separation experiments in the GoM and cannot be generalized to conclude the relative performance of both methods, especially in other applications. However, some of the concepts and methods should carry over to other applications.
CitationGopalakrishnan G, Hoteit I, Cornuelle BD, Rudnick DL (2019) Comparison of 4DVAR and EnKF state estimates and forecasts in the Gulf of Mexico. Quarterly Journal of the Royal Meteorological Society. Available: http://dx.doi.org/10.1002/qj.3493.
SponsorsWe gratefully acknowledge the ECCO consortium, including MIT, JPL, and the University of Hamburg, and the NCAR Data Assimilation Research Section (DAReS). The MITgcm code used in this study is checkpoint 64Y, and was obtained from http://mitgcm.org/. The Ssalto/Duacs altimeter product AVISO is produced and distributed by the Copernicus Marine and Environment Monitoring Service (CMEMS: http://marine.copernicus.eu/). The HYCOM/NCODA 1/12° global analysis data were obtained from the HYCOM consortium (http://hycom.org/dataserver/). The along-track altimetry data were obtained from the Radar Altimeter Database System (RADS: http://rads.tudelft.nl/rads/index.shtml). The SST data were obtained from Remote Sensing Systems Inc. (http://www.remss.com/). The NCEP/NCAR-Reanalysis-1 atmospheric forcings were obtained from http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.html. The MITgcm–DART EnKF and MITgcm–ECCO 4DVAR state estimates, input files including observations and error fields, are available from the authors upon request (email:firstname.lastname@example.org). BDC gratefully acknowledges support from the Office of Naval Research grants N000141512285 and N000141512598. Research reported in this publication was supported by the Gulf Research Program of the National Academy of Sciences under award number 2000006422. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Gulf Research Program or the National Academy of Sciences.