Dynamic sea surface height prediction hindcasts and reconstructions with residual damped persistence, 1994-2016

Description:This dataset contains time series of dynamic sea surface height (SSH) anomaly reconstructions and hindcasts, for the Western and Eastern U.S. Gulf Coast regions during the years 1994-2016. The SSH anomalies are relative to the time mean for each month (i.e., seasonal cycle removed). Where coupled model results (SEAS5) are used, the mean surface flux or SSH at each prediction lead time is also removed to adjust for model prediction drift. For validation purposes, SSH from MEaSUREs altimetry (Fournier et al. 2022) are also included, as are tide gauge data from select stations within the regions, from the Permanent Service for Mean Sea Level (https://psmsl.org). The observational time series have been corrected to remove non-dynamic effects (global mean SSH, inverted barometer pressure response). The dynamic SSH time series were computed using the ECCO adjoint convolution method (Delman et al., 2026; Wang et al., 2026), with adjoint sensitivities for lead times up to 12 months. The ECCO adjoint sensitivities were convolved with different ocean surface flux products:- reconstr_ecco: ECCO version 4 release 4 (ECCOv4r4)- reconstr_era5: ERA5 reanalysis (Hersbach et al. 2020)- pred_ecco_only: ECCOv4r4 pre-initialization time, zero anomaly post-initialization (dynamic persistence)- pred_era5: ERA5 pre-initialization time, zero anomaly post-initialization (dynamic persistence)- pred_era5_seas5: ERA5 pre-initialization time, ECMWF SEAS5 (Johnson et al. 2019) post-initialization time, up to 7 months lead timeNonseasonal river discharge from JRA55-do (Tsujino et al. 2018) was also added to the pre-initialization freshwater fluxes along the coasts. The predictions above were also repeated with a damped persistence component added based on the "residual" SSH anomaly unaccounted for in the adjoint sea level reconstructions, to better anticipate effects that would not be resolved correctly in the ECCO state estimate.- pred_ecco_only_damp_resid: pred_ecco_only with residual damped persistence added- pred_era5_damp_resid: pred_era5 with residual damped persistence added- pred_era5_seas5: pred_era5_seas5 with residual damped persistence added Additional time series included:- damp_pers: Damped persistence forecast, based on the prior month's anomaly and the lag-1 month autocorrelation in the altimetry time series- pred_coupled_ensmean: ensemble mean forecast from ECMWF seasonal prediction system, up to 7 months lead time Region Definitions: Western Gulf Coast: Average over model grid cells nearest to land grid cells west of the Mississippi River. Eastern Gulf Coast: Average over model grid cells nearest to land grid cells east of the Mississippi River. Files: README.txt README file. Pred_hindcasts_EasternGulfCoast_1994_2016_with_damp_pers_resid.nc Hindcast dynamic sea level predictions for the Eastern Gulf Coast region at lead times up to 12 months, 1994–2016.Pred_hindcasts_WesternGulfCoast_1994_2016_with_damp_pers_resid.nc Hindcast dynamic sea level predictions for the Western Gulf Coast region at lead times up to 12 months, 1994–2016. Software: Codes used to generate these reconstructions and predictions can be found in the ECCOv4-adj-reconstr repository on GitHub (https://github.com/andrewdelman/ECCOv4-adj-reconstr). References: Delman, A., Wang, O., & Lee, T. (2026). Forcing of subannual-to-decadal sea level variability and the recent rapid rise along the U.S. Gulf Coast. Journal of Geophysical Research: Oceans, 131, e2025JC023189. https://doi.org/10.1029/2025JC023189 Fournier, S., Willis, J., Killet, E., Qu, Z., & Zlotnicki, V. (2022). MEaSUREs gridded sea surface height anomalies version 2205 [Dataset]. NASA Physical Oceanography Distributed Active Archive Center. https://doi.org/10.5067/SLREF‐CDRV3 Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., et al. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), 1999–2049. https://doi.org/10.1002/qj.3803 Johnson, S. J. et al. (2019). SEAS5: the new ECMWF seasonal forecast system. Geoscientific Model Development, 12, 1087-1117. https://doi.org/10.5194/gmd-12-1087-2019 Tsujino, H., Urakawa, S., Nakano, H., Small, R. J., Kim, W. M., Yeager, S. G., et al. (2018). JRA‐55 based surface dataset for driving ocean–sea ice models (JRA55‐do). Ocean Modelling, 130, 79–139. https://doi.org/10.1016/j.ocemod.2018.07.002 Wang, O., Lee, T., Frederikse, T., Fukumori, I., & Fenty, I. (2026). Subpolar North Atlantic heat flux drives projected U.S. East Coast sea-level trend in a climate model. Communications Earth & Environment. https://doi.org/10.1038/s43247-026-03632-7 Acknowledgments: We gratefully acknowledge support from the Gulf Research Program (2000013300), administered by the National Academies of Science, Engineering, and Medicine. Ou Wang and Tong Lee were also supported by the NASA Physical Oceanography Program. Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004).