DOI: 10.5281/zenodo.14915031
title: US-CoastEX: Observation-based probabilistic reanalysis of storm surge and sea level extremes for United States (1950-2020)

description: NOTE: all data and associated articles (listed below) require proper acknowlement, citation and referencing of all data when directly or indirectly using any archived file listed below.

US-CoastEX provides:

Extreme storm surge PREDICTIONS (ungauged sites):

1) BAYESL-TG (standard version): skew surge distributions from BAYEX model informed with annual maxima skew surge (m) from standard hourly tide gauge data only between 1950-2020.

Filename #1: BAYEX-TG_GEV_PRED (name in data descriptor  'BAYESL-TG_GEV_PRED-TG')

and

2) BAYESL-TG/EXT (extended): skew surge distributions from BAYEX model informed with annual maxima skew surge (m) from standard hourly tide gauge data only between 1950-2020 complemented with updated annual maxima extracted from additional complementary data sources (e.g., inferred extremes, last recorded extreme water levels, high water marks and other data).

Filename #2: BAYEX-TG-EXT_GEV_PRED (name in data descriptor  'BAYESL-TG-EXT_GEV_PRED ')

In each file, we provide:






BAYEX GEV parameters at U.S. ungauged locations



Indicator name



Dimensions for GEV parameters (samples x sites x years - for μ)



Units





Latitude



BAYEX_LAT_PRED



1712 (ungauged sites)



Degrees





Longitude



BAYEX_LON_PRED



1712 (ungauged sites)



Degrees





Predicted Shape (ξ)



BAYEX_GEV_SHAPE_PRED



6000 x 1712



-





Predicted Scale (σ)



BAYEX_GEV_SCALE_PRED



6000 x 1712



m





Predicted Location (μ)



BAYEX_GEV_LOC_PRED



6000 x 1712 x 71 (years)



m





 

Extreme sea level PREDICTIONS (ungauged sites):

1) BAYESL-TG (standard version): ESL data obtained by combining BAYEX-TG data with tidal peaks from TPXO9v5. 

Filename #3: BAYEX-TG_ESL_PRED (name in data descriptor  'BAYESL-TG_ESL_PRED ')

Note: newer tidal products can be combined with BAYESL-TG data

and

2) BAYESL-TG/EXT (extended): ESL data obtained by combining BAYEX-TG/EXT data with tidal peaks from TPXO9v5

Filename #4: BAYEX-TG-EXT_ESL_PRED (name in data descriptor  'BAYESL-TG_EXT_ESL_PRED ')

Datum: ESL estimates are relative to mean sea level (MSL) as tidal elevations from TPXO are referenced to MSL.

In each file, we provide:






ESL return periods (up to 1000 years) at U.S. ungauged sites



Indicator name



Dimensions for ESL estimates (sites x return periods x percentile statistics: 50th, 5th and 95th)



Units





Latitude coordinates



BAYEX_LAT_PRED



1712 (ungauged sites)



Degrees





Longitude coordinates



BAYEX_LON_PRED



1712 (ungauged sites)



Degrees





Estimated return levels using Method  1 (Convolution)*



BAYEX_RL_ESL_CONV_TPXO



1712 x 999 x 3



m





Estimated return levels using Method 2 (MHW)*



BAYEX_RL_ESL_MHW_TPXO



1712 x 999 x 3



m





Estimated return levels using Method 2 (MHHW)*



BAYEX_RL_ESL_MHHW_TPXO



1712 x 999 x 3



m





Estimated return levels using Method 2 (HAT)*



BAYEX_RL_ESL_HAT_TPXO



1712 x 999 x 3



m





*represent different methods of combining extreme storm surge data with tidal peak data (see complementary articlesfor further details). The tidal data from TPXO can be found here (https://www.tpxo.net/global/tpxo10-atlas).

Note: other tidal products can be combined with BAYESL-TG/TX data to obtain extreme sea level predictions from BAYEX data.

Data limitations are discussed in its data descriptor listed below.

NOTE: all data and associated articles (listed below) require proper acknowlement, citation and referencing of all data when directly or indirectly using any archived file listed above.

Associated data descriptor:

Morim, J., Rasmussen, D.J., Wahl, T. et al. US-CoastEX: Observation-based probabilistic reanalysis of storm surge and sea level extremes for United States (1950-2020). Scientific Data (2025).

Associated research publications:

Morim, J., Wahl, T., Rasmussen, D.J. et al. Observations reveal changing coastal storm extremes around the United States. Nature Climate Change (2025). https://doi.org/10.1038/s41558-025-02315-z

Associated data:

1. Morim, J. (2024). National estimates of U.S. storm surge extremes and underlying long-term trends (1950-2020) using spatiotemporal non-stationary Bayesian Hierarchical Modeling [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10944076

BAYEX model:

Calafat, F. M. (2024). BAYEX: Spatiotemporal Bayesian hierarchical modeling of extremes with max-stable processes (v3.0). Zenodo. https://doi.org/10.5281/zenodo.10967174

Media:

https://cpree.princeton.edu/news/2025/researchers-uncover-clearer-patterns-extreme-storm-surge-trends-amid-rising-sea-levels