Kai A. Parker
Li H. Erikson
Jennifer A. Thomas
Kees Nederhoff
Tim Leijnse
20230315
Nearshore water level, tide, and non-tidal residual hindcasts (1979-2016) for the U.S. Atlantic coast
comma-delimited text
data release
DOI:10.5066/P9BQQTCI
Pacific Coastal and Marine Science Center, Santa Cruz, California
U.S. Geological Survey
https://doi.org/10.5066/P9BQQTCI
Patrick L. Barnard
Kevin Befus
Jeffrey J. Danielson
Anita C. Engelstad
Li H. Erikson
Amy C. Foxgrover
Maya K. Hayden
Daniel J. Hoover
Tim Leijnse
Chris Massey
Robert McCall
Norberto C. Nadal-Caraballo
Kees Nederhoff
Leonard O. Ohenhen
Andrea C. O’Neill
Kai A. Parker
Manoocher Shirzaei
Xin Su
Jennifer A. Thomas
Maarten van Ormondt
Sean F. Vitousek
Kilian Vos
Madison C. Yawn
2023
Future coastal hazards along the U.S. Atlantic coast
data release
DOI:10.5066/P9BQQTCI
Pacific Coastal and Marine Science Center, Santa Cruz, CA
U.S. Geological Survey
https://doi.org/10.5066/P9BQQTCI
A dataset of modeled nearshore water levels (WLs) was developed for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Water levels, defined for this dataset as the linear sum of tides and non-tidal residuals (NTR), were produced by Muis and others (2016) using a global tide and surge model (GTSM) forced by global atmospheric fields -. Water level outputs were extracted from the global grid at approximately 20 km resolution along the coastlines. These data were then statistically downscaled using a signal-specific set of corrections to improve skill in comparison to tide gauge observations (Parker and others, 2023). Hindcast water levels were forced by ERA5 atmospheric forcing provided by the dataset of Hersbach and others (2020). ERA5 is a reanalysis product, incorporating observations and data assimilation to best represent the experienced climate. Therefore, data from this version of the dataset are comparable to observed WLs along the study region. Similar modeled data for North Carolina and South Carolina are available from Barnard and others, 2023, at https://doi.org/10.5066/P9W91314)
These data are intended for policy makers, resource managers, science researchers, students, and the general public. These data can be used with geographic information systems or other software to identify and assess possible areas of vulnerability. These data are not intended to be used for navigation.
This data release was funded by the USGS Coastal and Marine Hazards and Resources Program. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
2020
2023
year of project start through publication date
None planned
-81.4600
-75.9814
36.958
25.0049
USGS Metadata Identifier
USGS:d3de898b-78c4-435a-ba91-72fc014ca696
ISO 19115 Topic Category
Oceans
Data Categories for Marine Planning
Physical Habitats and Geomorphology
predictions
USGS Thesaurus
Climate Change
Storms
Floods
Sea-level Change
mathematical modeling
effects of climate change
earth sciences
coastal processes
hazards
Marine Realms Information Bank (MRIB) keywords
sea level change
floods
numerical modeling
None
U.S. Geological Survey
USGS
Coastal and Marine Hazards and Resources Program
CMHRP
Pacific Coastal and Marine Science Center
PCMSC
tides
Global Change Master Directory (GCMD)
Hazards Planning
Sea Level Rise
Storm Surge
Floods
Water Depth
Geographic Names Information System (GNIS)
State of Florida
State of Georgia
State of Virginia
None
USGS-authored or produced data and information are in the public domain from the U.S. Government and are freely redistributable with proper metadata and source attribution. Please recognize and acknowledge the U.S. Geological Survey as the originator(s) of the dataset and in products derived from these data.
U.S. Geological Survey, Pacific Coastal and Marine Science Center
PCMSC Science Data Coordinator
mailing and physical
2885 Mission Street
Santa Cruz
CA
95060
831-427-4747
pcmsc_data@usgs.gov
WL_Tide_NTR_ERA5_ StationLocations _FL_GA_VA.jpg
Map showing output station locations for water levels, tides, and non-tidal residuals during the ERA5 hindcast period.
JPEG
All processing performed using MATLAB on a Personal Desktop Computer (PC) equipped with the Windows 10 operating system.
Patrick L. Barnard
Kevin Befus
Jeffrey J. Danielson
Anita C. Engelstad
Li H. Erikson
Amy C. Foxgrover
Matthew W. Hardy
Daniel J. Hoover
Tim Leijnse
Chris Massey
Robert McCall
Norberto C. Nadal-Caraballo
Kees Nederhoff
Leonard Ohenhen
Andrea C. O’Neill
Kai A. Parker
Manoocher Shirzaei
Xin Su
Jennifer A. Thomas
Maarten van Ormondt
Sean F. Vitousek
Kilian Vos
Madison C. Yawn
2023
Future coastal hazards along the U.S. North and South Carolina coasts
Barnard, P.L., Befus, K., Danielson, J.J., Engelstad, A.C., Erikson, L.H., Foxgrover, A.C., Hardy, M.W., Hoover, D.J., Leijnse, T., Massey, C., McCall, R., Nadal-Caraballo, N.C., Nederhoff, K., Ohenhen, L., O’Neill, A.C., Parker, K.A., Shirzaei, M., Su, X., Thomas, J.A., van Ormondt, M., Vitousek, S.F., Vos, K., and Yawn, M.C., 2023, Future coastal hazards along the U.S. North and South Carolina coasts: U.S. Geological Survey data release, https://doi.org/10.5066/P9W91314
Michael Déqué
2007
Frequency of precipitation and temperature extremes over France in an anthropogenic scenario: Model results and statistical correction according to observed values
Déqué, M.,2007, Frequency of precipitation and temperature extremes over France in an anthropogenic scenario: Model results and statistical correction according to observed values: Global and Planetary Change, vol. 57, p. 16–26, doi: 10.1016/j.gloplacha.2006.11.030
https://doi.org/10.1016/j.gloplacha.2006.11.030
Hans Hersbach
Bill Bell
Paul Berrisford
Shoji Hirahara
András Horányi
Joaquín Muñoz-Sabater
Julien Nicolas
Carole Peubey
Raluca Radu
Dinand Schepers
Adrian Simmons
Cornel Soci
Saleh Abdalla
Xavier Abellan
Gianpaolo Balsamo
Peter Bechtold
Gionata Biavati
Jean Bidlot
Massimo Bonavita
Giovanna De Chiara
Per Dahlgren
Dick Dee
Michail Diamantakis
Rossana Dragani
Johannes Flemming
Richard Forbes
Manuel Fuentes
Alan Geer
Leo Haimberger
Sean Healy
Robin J. Hogan
Elías Hólm
Marta Janisková
Sarah Keely
Patrick Laloyaux
Philippe Lopez
Cristina Lupu
Gabor Radnoti
Patricia de Rosnay
Iryna Rozum
Freja Vamborg
Sebastien Villaume
Jean-Noël Thépaut
2020
The ERA5 global reanalysis
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G.D., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keely, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J-N., 2020, The ERA5 global reanalysis: Quarterly Journal of the Royal Meteorological Society, vol. 146, no. 730, p. 1999-2049, doi: 10.1002/qj.3803.
https://doi.org/10.1002/qj.3803
Sanne Muis
Martin Verlann
Hessel C. Winsemuis
Jeroen C. J. H. Aerts
Phillip J. Ward
2016
A global reanalysis of storm surges and extreme sea levels
Muis, S., Verlaan, M., Winsemius, H.C., Aerts, J.C.J.H., and Ward, P.J., 2016, A global reanalysis of storm surges and extreme sea levels: Natural Communications vol. 7, p. 1–11, doi: 10.1038/ncomms11969.
https://doi.org/10.1038/ncomms11969
Kai A. Parker
Li H. Erikson
Jennifer A. Thomas
Kees Nederhoff
Patrick Barnard
Sanne Muis
2023
Relative contributions of water-level components to extreme water levels along the US Southeast Atlantic Coast from a regional-scale water level hindcast
Parker, K.A., Erikson, L.H., Thomas, J.A., Nederhoff, K., Barnard, P.L., and Muis, S., 2023, Relative contributions of water-level components to extreme water levels along the US Southeast Atlantic Coast from a regional-scale water level hindcast: Natural Hazards, https://doi.org/10.1007/s11069-023-05939-6.
https://doi.org/10.1007/s11069-023-05939-6
Accuracy of modeled water level data is dependent on a variety of factors including resolution, quality of forcing inputs, numerics, and included physical processes. Validation of modeled hindcast data compared to observations from tide gauges across the study region suggests that model root mean square error is around 13 cm for water levels, 7 cm for Non-Tidal Residuals, and 9 cm for Tides
All data fall within expected ranges. Missing data have been filled with -9999 values. Missing data values were assigned for data that failed QA/QC checks, primarily due to numerical artifacts, such as instabilities.
Dataset is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details.
The reported horizontal location of data output points is approximate. Horizontal accuracy is within a kilometer, with the error depending on local mesh resolution and how close the output stations happen to be to a model grid node.
A comprehensive determination of vertical positional accuracy is impossible due to a lack of observations across the full study region. A comparison of observations at tide gauges across the study region produced a model root mean square error of around 13 cm for water levels, 7 cm for Non-Tidal Residuals, and 9 cm for Tides.
Sanne Muis
Maialen Irazoqui Apecechea
José Antonio Álvarez
Martin Verlaan
Kun Yan
Job Dullaart
Jeroen Aerts
Trang Duong
Rosh Ranasinghe
Li Erikson
Andrea O’Neill
Dewi le Bars
Rein Haarsma
Malcolm Roberts
2021
Global water level change indicators from 1950 to 2050 derived from HighResMIP climate projections
netCDF files
online
Copernicus Climate Change Service (C3S) Climate Data Store (CDS)
https://cds-dev.copernicus-climate.eu/cdsapp#!/dataset/sis-water-level-change-cmip6-indicators?tab=overview
online database
19500101
20491231
time range for which data are available
GTSM
Hindcast and forecast datasets of water levels
National Oceanic and Atmospheric Administration
2022
NOAA Tides and Currents
database
online
NOAA
https://tidesandcurrents.noaa.gov/stations.html?type=Water+Levels
online database
20200301
time data were downloaded
NOAA
Water level and tidal data
Water levels were obtained from the Global Tide and Surge Model (GTSM) hindcast/forecast dataset for the Atlantic region. See Muis and others (2016) for information on GTSM setup.
GTSM
20200301
NOAA Tide Gauge data were obtained at all available stations along the Atlantic coast. All available water level and tidal prediction data were download for NOAA stations: 8632200, 8638610, 8638901, 8651370, 8652587, 8654467, 8656483, 8658163, 8661070, 8662245, 8665530, 8670870, 8720030, 8720218, 8721604, 8722670, 8722956, 8723214.
NOAA tide gauge
20200301
GTSM water level data were separated into contributing signals: Non-tidal Residual, Tides, Seasonality, and Monthly Mean Sea Levels. This was accomplished using tidal analysis and band-pass filtering (see Parker and others, 2023).
20200401
Non-tidal residuals were correcting using quantile matching (Déqué, 2007) with the target being the average error across all tide gauge observations (see Parker and others, 2023).
Quantile matching
20201001
Seasonality (defined here as the annual and semi-annual harmonics) was corrected using linear regression to remove locational bias as compared to tide gauges. The amplitude and phase of the seasonal cycles were shift with latitude as a predictor variable (see Parker and others, 2023).
20201001
Tides were corrected using an ensemble-based method. Phase and Amplitude of tidal harmonics were determined based on a weighted average of available tide information in the region with weighting determined by the average model performance in comparison to tide gauges. See Parker and others (2023) for more details.
20201001
Monthly Mean Sea Level was corrected using a single linear shift to eliminate bias in modeled values (see Parker and others, 2023).
20201001
Corrected water level signals were recombined and validated against all tide gauges in the region (see Parker and others, 2023).
20201101
Edits were made correct spelling of an author name and to include final citation information for a Cross_Reference. No data were changed. The metadata available from a harvester may supersede metadata bundled within a download file. Users are advised to compare the metadata date of this file to any similar file to ensure they are using the most recent version. (scochran@usgs.gov)
20230516
point
point
81947520
0.0001
0.0001
Decimal degrees
North American Datum of 1983
Geodetic Reference System 80
6378137.000000
298.257222
Mean Sea Level
0.001
meters
Explicit elevation coordinate included with horizontal coordinates
WL_Tide_NTR_ERA5hindc_NUM.csv
Combined in one csv file are water levels (WL), tides (Tide) and non-tidal residuals (NTR), where NUM in the file name refers to the station ID along the coast (see browse graphic for more details).
Producer defined
Year
Year of hindcasted data (UTC)
Producer defined
1979
2016
Year
1
Month
Month of hindcasted data (UTC), where 1=January and 12=December
Producer defined
1
12
Month
1
Day
Day of hindcasted data (UTC)
Producer defined
1
31
Day
1
Hour
Hour of hindcasted data (UTC)
Producer defined
0
23
Hour in 24-hour format
1
Minute
Minute of hindcasted data (UTC)
Producer defined
0
50
Minute
1
WL_[m]
water levels for ERA5 hindcast
Producer defined
-2.644
2.367
meters
0.001
Tide_[m]
tides for ERA5 hindcast
Producer defined
-1.572
1.726
meters
0.001
NTR_[m]
non-tidal residuals for ERA5 hindcast
Producer defined
-1.606
1.889
meters
0.001
Lat_[Nad83]
Latitude coordinate
Producer defined
25.0049
36.958
decimal degrees
0.0001
Lon_[Nad83]
Longitude coordinate
Producer defined
-81.46
-75.9814
decimal degrees
0.001
WL_Tide_NTR_ERA5_Ref_StationIdsLocs_FL.csv (Florida), WL_Tide_NTR_ERA5_Ref_StationIdsLocs_GA.csv (Georgia), and WL_Tide_NTR_ERA5_Ref_StationIdsLocs_VA.csv (Virginia)
Files contain the station IDs and their locations in Latitude and Longitude coordinates.
Producer defined
Station_ID
station identification number
Producer defined
1
89
NA
1
Lat_[Nad83]
Latitude coordinate
Producer defined
25.0049
36.9580
decimal degrees
0.0001
Lon_[Nad83]
Longitude coordinate
Producer defined
-81.46
-75.9814
decimal degrees
0.001
The first line of the csv file is a header line.
U.S. Geological Survey
U.S. Geological Survey - CMGDS
mailing and physical
2885 Mission Street
Santa Cruz
CA
95060
831-427-4747
pcmsc_data@usgs.gov
These data are available in csv format in three zip files. The state for which the data is available is reflected in the file name [WL_Tide_NTR_ERA5hindc_STATE.zip], where STATE can be either FL (Florida), GA (Georgia) or VA (Virginia). Additionally, two reference files (WL_Tide_NTR_ERA5_Ref_StationIdsLocs_FL.csv, WL_Tide_NTR_ERA5_Ref_StationIdsLocs_GA.csv and WL_Tide_NTR_ERA5_Ref_StationIdsLocs_VA.csv) are provided which contain the station IDs and the corresponding transect locations.
Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty.
comma-delimited text
csv files were zipped for Florida
WinZip or archive utility
667.3
https://doi.org/10.5066/P9BQQTCI
Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section.
comma-delimited text
csv files were zipped for Georgia
WinZip or archive utility
138.1
https://doi.org/10.5066/P9BQQTCI
Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section.
comma-delimited text
csv files were zipped for Virginia
WinZip or archive utility
92.2
https://doi.org/10.5066/P9BQQTCI
Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section.
comma-delimited text
csv files contain station IDs and locations for Florida
WinZip or archive utility
0.8
https://doi.org/10.5066/P9BQQTCI
Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section.
comma-delimited text
csv files contain station IDs and locations for Georgia
WinZip or archive utility
0.2
https://doi.org/10.5066/P9BQQTCI
Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section.
comma-delimited text
csv files contain station IDs and locations for Virginia
WinZip or archive utility
0.2
https://doi.org/10.5066/P9BQQTCI
Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section.
None.
These data can be viewed with any text reading software.
20230516
U.S. Geological Survey, Pacific Coastal and Marine Science Center
PCMSC Science Data Coordinator
mailing and physical
2885 Mission Street
Santa Cruz
CA
95060
831-427-4747
pcmsc_data@usgs.gov
Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998