Ocean wave time-series data along the Alaska coast simulated with a global-scale numerical wave model under the influence of CMIP6 wind and sea ice fields (ver. 2.0, October 2024)

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Frequently anticipated questions:

What does this data set describe?

Title:
Ocean wave time-series data along the Alaska coast simulated with a global-scale numerical wave model under the influence of CMIP6 wind and sea ice fields (ver. 2.0, October 2024)
Abstract:
This dataset presents historical (1979-2014) and projected (2020-2050) hourly time-series of wave heights, wave periods, incident wave directions and directional spreading at distinct points along the open coast of Alaska. The time-series were developed by running the National Oceanic and Atmospheric Administration’s (NOAA’s) WAVEWATCHIII model. Wind and sea ice fields from seven different Global Climate or General Circulation Models from the CMIP6 High-Resolution Model Intercomparison Project were used to simulate waves across the globe at a 0.5-degree resolution (approximately 50 kms, depending on latitude) and further downscaled to 10- (approximately 18 kilometer) and 4-arc-minute (approximately 7 kilometer) model grids. Point model output data extracted from NOAA’s 4-arc-minute grid for Alaska (ak_4m) are provided herein.
Supplemental_Information:
Coupled atmosphere-ocean global climate models (or general circulation models, GCMs) are the current standard tool for improving understanding and predictability of climate behavior on seasonal to centennial time-scales. However, GCMs do not currently include ocean wave conditions caused by the exchange of momentum, heat, and mass across the air-sea interface (Hemer and others, 2012). To fulfill this need, projections of wave conditions have been done by independent researchers using statistical and numerical modeling methods driven by atmospheric forcing derived from the 5th generation Coupled Model Intercomparison Project (CMIP5) GCMs (Morim and others, 2019, 2020). This work follows a well-established method of applying GCM-derived wind and sea-ice fields as boundary conditions to the WaveWatchIII model to generate projections of wave climatologies (Hemer and others 2013; Erikson and others, 2015; Mentaschi and others 2017). But in contrast to earlier works, this data set was produced by applying wind and sea-ice fields from the High Resolution Model Intercomparison Project (HighResMIP v1.0), which is part of the CMIP6 framework (Haarsma and others, 2016). With a spatial resolution up to 25-50 km (compared to 150 km for CMIP5), the HighResMIP models are capable of resolving localized climate extremes, such as tropical cyclones (Roberts and others., 2020). Additional information about WAVEWATCHIII and the Production Multigrid model from which these data were derived is available online at https://polar.ncep.noaa.gov/waves/validation/. Computing was performed at the USGS Advanced Research Computing Facility, USGS Denali Supercomputer https://doi.org/10.5066/P9PSW367 and Intel Corporation. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
  1. How might this data set be cited?
    Erikson, Li H., Herdman, Liv, Flanary, Chris, Engelstad, Anita C., Pusuluri, Prasad, Barnard, Patrick L., Storlazzi, Curt D., Beck, Michael, Reguero, Borja G., and Parker, Kai A., 20241026, Ocean wave time-series data along the Alaska coast simulated with a global-scale numerical wave model under the influence of CMIP6 wind and sea ice fields (ver. 2.0, October 2024): data release DOI:10.5066/P9KR0RFM, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, California.

    Online Links:

    This is part of the following larger work.

    Erikson, Li H., Herdman, Liv, Flanary, Chris, Engelstad, Anita C., Pusuluri, Prasad, Barnard, Patrick L., Storlazzi, Curt D., Beck, Michael, Reguero, Borja G., and Parker, Kai A., 2022, Ocean wave time-series data simulated with a global-scale numerical wave model under the influence of historical and projected CMIP6 wind and sea ice fields (ver. 2.0, October 2024): data release 10.5066/P9KR0RFM, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, CA.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -178.7300
    East_Bounding_Coordinate: -134.3300
    North_Bounding_Coordinate: 72.0670
    South_Bounding_Coordinate: 50.0670
  3. What does it look like?
    WavePnts_ak_4m_Fut_Preview.png (png)
    Water depth at model savepoints (meters)
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 01-Jan-1979
    Ending_Date: 31-Dec-2050
    Currentness_Reference:
    time period for which the data were modeled
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: netCDF files
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      Indirect_Spatial_Reference:
      Data were generated within a numerical model scheme. Refer to self-contained netCDF files for location information.
    2. What coordinate system is used to represent geographic features?
      Horizontal positions are specified in geographic coordinates, that is, latitude and longitude. Latitudes are given to the nearest 0.0167. Longitudes are given to the nearest 0.0167. Latitude and longitude values are specified in Decimal degrees. The horizontal datum used is WGS_1984.
      The ellipsoid used is WGS_1984.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257223563.
  7. How does the data set describe geographic features?
    Entity_and_Attribute_Overview:
    netCDF files are self-contained and attribute information may be found in the header of the file itself. The netCDF attributes for the file WavePnts_CMCC_ak_4m_Fut.nc are provided below as a sample. All attributes are the same for each file with the exception of reference to the filename, forcing file names, and max/min values. 
    Format:
           netcdf4
Global Attributes:
           product_name    = 'CMIP6 WW3 Extracted Station Wave Parameters'
           area            = 'Alaskan 4 min wave grid'
           data_type       = 'OCO spectra 2D'
           format_version  = '1.1'
           CMIP6_Mod       = 'CMCC'
           start_date      = '2020-01-01'
           stop_date       = '2050-12-31'
           Temporal_Res    = 'hourly'
           Extracted_Dir   = '/caldera/projects/usgs/water/nywsc/lherdman/WW4/WW3-             6.07.1'
           Extracted_Files = 'cmcc.pnts.ak_4m*_tab.nc'
           author          = 'USGS, lerikson@usgs.gov'
           CMIP6_Winds     = 'CMCC-CM2-VHR4-r1i1p1f1_gn, 6-hourly, 25 km resolution'
           CMIP6_SeaIce    = ' CMCC-CM2-VHR4-r1i1p1f1_gn, daily, 25 km resolution '
Dimensions:
           time    = 271752
           station = 1139
Variables:
    time
           Size:       271752x1
           Dimensions: time
           Datatype:   single
           Attributes:
                       _FillValue    = -9999
                       long_name     = 'julian day (UT)'
                       standard_name = 'time'
                       conventions   = 'Relative julian days with decimal part (as parts of the day)'
                       axis          = 'T'
                       units         = 'hours since 2020-01-01 00:00:00'
                       calendar      = 'proleptic_gregorian'
    station
           Size:       1139x1
           Dimensions: station
           Datatype:   single
           Attributes:
                       _FillValue = -9999
                       long_name  = 'station id'
                       axis       = 'X'
    longitude
           Size:       1139x1
           Dimensions: station
           Datatype:   single
           Attributes:
                       _FillValue    = -9999
                       long_name     = 'longitude'
                       standard_name = 'longitude'
                       globwave_name = 'longitude'
                       units         = 'degree_east'
                       valid_min     = -178.73
                       valid_max     = -134.33
                       content       = 'TX'
                       associates    = 'time station'
    latitude
           Size:       1139x1
           Dimensions: station
           Datatype:   single
           Attributes:
                       _FillValue    = -9999
                       long_name     = 'latitude'
                       standard_name = 'latitude'
                       globwave_name = 'latitude'
                       units         = 'degree_north'
                       valid_min     = 50.067
                       valid_max     = 72.067
                       content       = 'TX'
                       associates    = 'time station'
    depth
           Size:       1139x1
           Dimensions: station
           Datatype:   single
           Attributes:
_FillValue    = -9999
    long_name = 'Station Depth Below MSL' standard_name = 'station_depth' units = 'm' Convention = 'Positive Downward' valid_min = 5.1 valid_max = 7070.6 associates = 'station' 
        hs
           Size:       1139x271752
           Dimensions: station,time
           Datatype:   single
           Attributes:
                       _FillValue    = -9999
                       long_name     = 'spectral estimate of significant wave height'
                       standard_name = 'sea_surface_wave_significant_height'
                       globwave_name = 'significant_wave_height'
                       units         = 'm'
                       valid_min     = 0
                       valid_max     = 21.0576
                       content       = 'TX'
                       associates    = 'time station'
    fp
           Size:       1139x271752
           Dimensions: station,time
           Datatype:   single
           Attributes:
                       _FillValue    = -9999
                       long_name     = 'peak frequency (Fp=1/Tp)'
                       standard_name = 'dominant_wave_frequency'
                       globwave_name = 'dominant_wave_frequency'
                       units         = 's-1'
                       valid_min     = 0
                       valid_max     = 0.52997
                       content       = 'TX'
                       associates    = 'time station'
    tr
           Size:       1139x271752
           Dimensions: station,time
           Datatype:   single
           Attributes:
                       _FillValue    = -9999
                       long_name     = 'mean period normalised by the relative frequency'
                       standard_name = 'mean_period_normalised_by_the_relative_frequency'
                       globwave_name = 'mean period normalised by the relative frequency'
                       units         = 's'
                       valid_min     = 0
                       valid_max     = 22.6691
                       content       = 'TX'
                       associates    = 'time station'
    th1m
           Size:       1139x271752
           Dimensions: station,time
           Datatype:   single
           Attributes:
                       _FillValue    = -9999
                       standard_name = 'mean_wave_direction'
                       globwave_name = 'mean_wave_direction'
                       units         = 'degree'
                       valid_min     = 0
                       valid_max     = 359.9999
                       content       = 'TX'
                       associates    = 'time station'
    th1p
           Size:       1139x271752
           Dimensions: station,time
           Datatype:   single
           Attributes:
                       _FillValue    = -9999
                       long_name     = 'mean wave direction from spectral moments at spectral peak'
                       standard_name = 'dominant_wave_direction'
                       globwave_name = 'dominant_wave_direction'
                       units         = 'degree'
                       valid_min     = 0
                       valid_max     = 359.9999
                       content       = 'TX'
                       associates    = 'time station'
    sth1m
           Size:       1139x271752
           Dimensions: station,time
           Datatype:   single
           Attributes:
                       _FillValue    = -9999
                       long_name     = 'directional spread from spectral moments'
                       standard_name = 'mean_wave_spreading'
                       globwave_name = 'mean_wave_spreading'
                       units         = 'degree'
                       valid_min     = 0
                       valid_max     = 81.0263
                       content       = 'TX'
                       associates    = 'time station'
    sth1p
           Size:       1139x271752
           Dimensions: station,time
           Datatype:   single
           Attributes:
                       _FillValue    = -9999
                       long_name     = 'directional spread at spectral peak'
                       standard_name = 'dominant_wave_spreading'
                       globwave_name = 'dominant_wave_spreading'
                       units         = 'degree'
                       valid_min     = 0
                       valid_max     = 81.0158
                       content       = 'TX'
                       associates    = 'time station'
    Entity_and_Attribute_Detail_Citation: none

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Li H. Erikson
    • Liv Herdman
    • Chris Flanary
    • Anita C. Engelstad
    • Prasad Pusuluri
    • Patrick L. Barnard
    • Curt D. Storlazzi
    • Michael Beck
    • Borja G. Reguero
    • Kai A. Parker
  2. Who also contributed to the data set?
    We thank Dr. Babak Tehranirad (Stantec Inc.), Dr. Sean Vitousek (USGS), and Reyce Bogardus (UAF) for review of the wave data. For the wind and sea-ice fields we thank and acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF.
  3. To whom should users address questions about the data?
    U.S. Geological Survey, Pacific Coastal and Marine Science Center
    Attn: PCMSC Science Data Coordinator
    2885 Mission Street
    Santa Cruz, CA

    831-427-4747 (voice)
    pcmsc_data@usgs.gov

Why was the data set created?

These wave data were produced as part of a larger investigation into assessing future coastal hazards along the United States open coastlines.

How was the data set created?

  1. From what previous works were the data drawn?
    CMCC (source 1 of 8)
    Scoccimarro, Enrico, Bellucci, Alessinio, and Peano, Daniele, 2017, CMCC CMCC-CM2-VHR4 model output prepared for CMIP6 HighResMIP: Earth System Grid Federation, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution:
    East-west and north-south wind components and sea-ice concentrations were used as boundary conditions for the WAVEWATCHIII® model.
    CNRM projected (source 2 of 8)
    Voldoire, Aurore, 2019, CNRM-CERFACS CNRM-CM6-1-HR model output prepared for CMIP6 ScenarioMIP ssp585: Earth System Grid Federation, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution:
    East-west and north-south wind components and sea-ice concentrations were used as boundary conditions for the WAVEWATCHIII® model.
    CNRM historical (source 3 of 8)
    Voldoire, Aurore, 2019, CNRM-CERFACS CNRM-CM6-1-HR model output prepared for CMIP6 CMIP historical: Earth System Grid Federation, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution:
    East-west and north-south wind components and sea-ice concentrations were used as boundary conditions for the WAVEWATCHIII® model.
    EC-Earth (source 4 of 8)
    (EC-Earth), EC-Earth Consortium, 2018, EC-Earth-Consortium EC-Earth3P-HR model output prepared for CMIP6 HighResMIP Geospatial_Data_Presentation_Form: netCDF files: Earth System Grid Federation, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution:
    East-west and north-south wind components and sea-ice concentrations were used as boundary conditions for the WAVEWATCHIII® model.
    GFDL wind and projected sea-ice concentrations (source 5 of 8)
    Guo, Huan, John, Jasmin G., Blanton, Chris, McHugh, Colleen, Nikonov, Serguei, Radhakrishnan, Aparna, Rand, Kristopher, Zadeh, Niki T., Balaji, V., Durachta, Jeff, Dupuis, Christopher, Menzel, Raymond, Robinson, Thomas, Underwood, Seth, Vahlenkamp, Hans, Dunne, Krista A., Gauthier, Paul P.G., Ginoux, Paul, Griffies, Stephen M., Hallberg, Robert, Harrison, Matthew, Hurlin, William, Lin, Pu, Malyshev, Sergey, Naik, Vaishali, Paulot, Fabien, Paynter, David J., Ploshay, Jeffrey, Schwarzkopf, Daniel M., Seman, Charles J., Shao, Andrew, Silvers, Levi, Wyman, Bruce, Yan, Xiaoqin, Zeng, Yujin, Adcroft, Alistair, Dunne, John P., Held, Isaac M., Krasting, John P., Horowitz, Larry W., Milly, Chris, Shevliakova, Elena, Winton, Michael, Zhao, Ming, and Zhang, Rong, 2018, NOAA-GFDL GFDL-CM4 model output prepared for CMIP6 ScenarioMIP: Earth System Grid Federation, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution:
    East-west and north-south wind components and sea-ice concentrations were used as boundary conditions for the WAVEWATCHIII® model.
    GFDL historical sea-ice concentrations (source 6 of 8)
    Kennedy, John, Titchner, Holly, Rayer, Nick, and Roberts, Malcom, 2017, input4MIPs.MOHC.SSTsAndSeaIce.HighResMIP.MOHC-HadISST-2-2-0-0-0: Earth System Grid Federation, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution:
    sea-ice concentrations were used as boundary conditions for the WAVEWATCHIII® model.
    HadgemHH (source 7 of 8)
    Roberts, Malcolm, 2018, MOHC HadGEM3-GC31-HH model output prepared for CMIP6 HighResMIP: Earth System Grid Federation, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution:
    East-west and north-south wind components and sea-ice concentrations were used as boundary conditions for the WAVEWATCHIII® model.
    HadgemHM, HadgemSST (source 8 of 8)
    Roberts, Malcolm, 2018, MOHC HadGEM3-GC31-HM model output prepared for CMIP6 HighResMIP: Earth System Grid Federation, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution:
    East-west and north-south wind components and sea-ice concentrations were used as boundary conditions for the WAVEWATCHIII® model.
  2. How were the data generated, processed, and modified?
    Date: 31-Mar-2021 (process 1 of 4)
    The data are presented by geographic areas bounded by model grids which were nested within a common global grid. All process steps apply to all data and geographic areas. Download and rewriting of General Circulation Model (GCM)wind (near-surface 10-m height) and sea-ice fields. Specific GCM variants used were as follows: CMCC winds: CMCC-CM2-VHR4_hist-1950_r1i1p1f1_gn (historical time-period) and CMCC-CM2-VHR4_highres-future_r1i1p1f1_gn (projected time-period), 6-hourly, 25 km resolution, CMCC sea-ice: CMCC-CM2-VHR4_hist-1950_r1i1p1f1_gn (historical time-period) and CMCC-CM2-VHR4_highres-future_r1i1p1f1_gn (projected time-period), daily, 25 km resolution, CNRM winds: CNRM-CM6-1-HR_historical_r1i1p1f2_gr (historical time-period)and CNRM-CM6-1-HR_ssp585_r1i1p1f2_gr (projected time-period), 3-hourly, 25 km resolution, CNRM sea-ice: CNRM-CM6-1-HR_historical_r1i1p1f2_gn (historical time-period) and CNRM-CM6-1-HR_ssp585_r1i1p1f2_gn (projected time-period), daily, 25 km resolution, ECEARTH winds: EC-Earth3P-HR_hist1950_r1i1p2f1_gr (historical time-period) and EC-Earth3P-HR_highres-future_r1i1p2f1_gr (projected time-period) 3-hourly, 50 km resolution, ECEARTH sea-ice: EC-Earth3P-HR_hist1950_r1i1p2f1_gn (historical time-period) and EC-Earth3P-HR_highres-future_r1i1p2f1_gn (projected time-period), daily, 25 km resolution, GFDL winds: GFDL-CM4C192_highresSST-present_r1i1p1f1_gr3 (historical time-period) and GFDL-CM4C192_highresSST-future_r1i1p1f1_gr3 (projected time-period), 3-hourly, 50 km resolution, GFDL sea-ice: input4MIPs_SSTsAndSeaIce_HighResMIP_MOHC-HadISST-2-2-0-0-0_gn (historical time-period), GFDL-CM4_ssp585_r1i1p1f1_gr2 (projected time-period), daily, 25 km resolution, HadgemHH winds: HadGEM3-GC31-HH_hist-1950_r1i1p1f1_gn (historical time-period) and HadGEM3-GC31-HH_highres-future_r1i1p1f1_gn (projected time-period), 3-hourly, 50 km resolution. HadgemHH sea-ice: HadGEM3-GC31-HM_hist-1950_r1i1p1f1_gn (historical time-period) and HadGEM3-GC31-HM_highres-future_r1i1p1f1_gn (projected time-period), daily, 25 km resolution, HadgemHM winds: HadGEM3-GC31-HM_hist-1950_r1i1p1f1_gn (historical time-period) and HadGEM3-GC31-HM_highres-future_r1i1p1f1_gn (projected time-period), 3-hourly, 50 km resolution, HadgemHM sea-ice: HadGEM3-GC31-HM_hist-1950-r1i1p1f1_gn (historical time-period) and HadGEM3-GC31-HM_highres-future_r1i1p1f1_gn(projected time-period), daily, 25 km resolution, HadgemSST winds: HadGEM3-GC31-HM_highresSST-present_r1i1p1f1_gn (historical time-period) and HadGEM3-GC31-HM_highresSST-future_r1i1p1f1_gn (projected time-period), forced atmosphere experiment using SST/sea ice derived from CMIP5 RCP8.5, 3-hourly, 50 km resolution. HadgemSST sea-ice: HadGEM3-GC31-HM_highresSST-present_r1i1p1f1_gn (historical time-period) and HadGEM3-GC31-HM_highresSST-future_r1i1p1f1_gn (projected time-period), daily, 25 km resolution native grid. The near-surface wind fields and sea-ice cover were downloaded from ESGF CMIP6 Data Holdings (pcmdi.llnl.gov/CMIP6) in March 2021 (June 2021 for CMCC), and they were interpolated to common 3-hourly time-points and grid resolutions of 0.5 degrees for GFDL and CNRM, 0.35 degrees for Hadgem and ECEARTH, and 0.3125 degrees for CMCC. All data were written to netCDF format files ingestible by the wave model. The GCM wind and ice fields are part of the High-Resolution Model Intercomparison Project (HighResMIP, Haarsma and others, 2016). The primary goal of HighResMIP is to assess the robustness of improvements in the representation of important climate processes with weather-resolving global model resolutions, using the physical climate system only with constrained aerosol forcing (Eyring and others, 2016). The higher resolution and inclusion of more forcings and detailed physics is expected to reduce bias compared to the standard CMIP6 and CMIP5 predecessor. Data sources used in this process:
    • CMCC, CNRM projected, CNRM historical, EC-Earth, GFDL wind and projected sea-ice concentrations, GFDL historical sea-ice concentrations, HadgemHH, HadgemHM, HadgemSST
    Date: 25-Jan-2021 (process 2 of 4)
    Wave model setup. The third-generation, spectral wave model WAVEWATCHIII (WW3; version 6.07.1; WAVEWATCHIII® Development Group (WW3DG), 2019) was downloaded from GitHub at https://github.com/NOAA-EMC/WW3/releases). WW3 is a ‘phase-averaged model’ that solves the random phase spectral action density balance equation for wavenumber-direction spectra based on the assumption that water depths, currents, and wave fields vary on time and spatial scales much larger than that of a single wave. This version of the model includes transitional- and shallow-water equations. Source terms for physical processes include parameterizations for wind-driven wave growth, parametrized forms for nonlinear resonant wave-wave interactions, scattering due to wave-bottom interactions, triad interactions, and dissipation due to whitecapping, bottom friction, surf-breaking, and interactions with ice. Model switches used in this study were as follows (see WW3DG, 2019 for further explanations): F90 DIST MPI OMPG OMPH PR3 UQ FLX0 LN1 ST4 STAB0 NL1 BT1 IC4 IS0 REF0 DB0 TR1 MLIM BS0 XX0 WNT1 WNX1 CRT1 CRX1 NOGRB O0 O1 O2 O3 O4 O5 O6 O7 O11 NC4. Model grids consist of one 0.5 x 0.5 degree global grid, 4 nested 10 arc-minute resolution (approximately 18 km) ‘child’ grids, and 3 nested 4 arc-minute resolution (approximately 7 km) ‘grand-child’ grids (grid, geographic coverage, resolution in arc-minutes and approximate km). The finer resolution nested grids each take inputs along their open boundaries from the increasingly coarse grids. The finest resolution wave grids (approximately 7 km) align the outer coast of Alaska, including the Aleutian Islands, and the U.S. East and West coasts, including the Gulf of Mexico, Hawai’i, and Puerto Rico. U.S. territories in the Pacific Ocean are represented by a 10 arc-minute (approximately 18 km) grid. Please see the overview image provided as part of this data release for a visual representation of the spatial grid coverage. Bathymetry and landmasks for all grids were obtained from the 1-arc-minute ETOPO1 global relief model (Amante and Eakins, 2009). In an effort to optimize model output data storage needs, more than 5000 model output points (‘savepoints’) were placed along the approximate 20m, 50m, and 100m isobaths (as derived from the ETOPO1 bathymetry), spaced approximately 10 km in the alongshore direction of all U.S. coastlines or co-located with buoys or other points of interest. Output point locations were snapped to grid points and thus are not necessarily precisely coincident with long-term buoy observation locations.
    Date: 30-Nov-2023 (process 3 of 4)
    Wave model implementation and post-processing. The WW3 model was compiled and run on two separate high-performance computing systems: the USGS Advanced Research Computing Facility, USGS Denali Supercomputer https://doi.org/10.5066/P9PSW367 and Intel Corporation for part of the projection GCMs. Computing efficiency was optimized resulting in approximately 80 hours of computation (wall-clock) time per 10-year simulation. The WW3 model was run with the spatiotemporally varying wind and ice fields, described in the first process step, applied across all model domains. Each year was run individually, with restart files from the previous year. Data from the years 1979 and 2020 are cold-start runs and hence model ‘spin-up’ is included in the approximate first week of data outputs for that year; users are cautioned on using the first weeks of data in years 1979 and 2020. Hourly time-series of bulk wave statistics were saved at each global model grid point (0.5-degree resolution) and coastal ‘savepoint’ from the nested grids (see second process_step) in the form of binary files. A post-processor script included with the WAVEWATCHIII® 6.07.01 release was used to write out select bulk parameters from the binary data files to netCDF format. The annual data files were subsequently re-written to produce netCDF files with continuous time-series spanning all years from 2020 through 2050; model depths at each of the savepoint locations were extracted from the grids and added to the final netCDF files. The data are presented for U.S. coastlines within nested model domains (grids) which correspond to the U.S. West Coast and Hawai’i (wc_4m), East Coast and Gulf of Mexico and Puerto Rico (at_4m), Alaska (ak_4m), and U.S. territories in the Pacific Ocean (ep_10m). This dataset is for the coast of Alaska.
    Date: 20-Aug-2024 (process 4 of 4)
    Wave time-series for the hindcast period were added to the existing data release of wave time-series for the projected period. Corrections were made to the metadata to fix the erroneous version description of EC-Earth projections (EC-Earth3P-HR_highres-future_r1i1p1f1_gr for wind was changed to EC-Earth3P-HR_highres-future_r1i1p2f1_gr, and EC-Earth3P-HR_highres-future_r1i1p2f1_gr was changed to and EC-Earth3P-HR_highres-future_r1i1p2f1_gn). In the previously released data files for the projection period, the global attribute description was also corrected to EC-Earth3P-HR_highres-future_r1i1p2f1_gn. Additionally, erroneous non-zero wave data in the data files for the projection period in the Arctic regions, at times when the Arctic Ocean is usually ice-covered and waves in this region are not expected, were fixed. Erroneous variable datatypes were corrected.
  3. What similar or related data should the user be aware of?
    Amante, C., and Eakins, B.W., 2009, ETOPO1 Arc-minute global relief model: procedures, data sources and analysis.

    Online Links:

    Other_Citation_Details:
    Amante, C. and Eakins, B.W., 2009, ETOPO1 Arc-minute global relief model: procedures, data sources and analysis: NOAA Technical Memorandum NESDIS NGDC-24, p. 25, https://www.ngdc.noaa.gov/mgg/global/
    Erikson, Li, Hegermiller, Christie, Barnard, Patrick L., Ruggiero, Peter, and Ormondt, Maarten van, 2015, Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios.

    Online Links:

    Other_Citation_Details:
    Erikson, L.H., Hegermiller, C.A., Barnard, P.L., Ruggiero, P., and van Ormondt, M., 2015, Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios: Ocean Modelling, v. 96 no. 1, pp. 171–185, doi: 10.1016/j.ocemod.2015.07.004.
    Eyring, V., Bony, S., Meehl, G.A., Senior, C.A., Stevens, B., Stouffer, R.J., and Taylor, K.E., 2016, Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization..

    Online Links:

    Other_Citation_Details:
    Eyring, V., Bony, S., Meehl, G.A., Senior, C.A., Stevens, B., Stouffer, R.J., and Taylor, K.E., 2016, Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization: Geoscientific Model Development, v. 9, p. 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016
    Falgout, J.T., Gordon, J., Williams, B., and Davis, M.J., 2024, USGS Advanced Research Computing, USGS Denali Supercomputer..

    Online Links:

    Other_Citation_Details:
    Falgout, J.T., Gordon J., Williams B., Davis M. J., USGS Advanced Research Computing, USGS Denali Supercomputer: U.S. Geological Survey, https://doi.org/10.5066/P9PSW367
    Haarsma, R.J., Roberts, M.J., Vidale, P.L., Senior, C.A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fučkar, N.S., Guemas, V., Hardenberg, J. von, Hazeleger, W., Kodama, C., Koenigk, T., Leung, L.R., Lu, J., Luo, J.-J., Mao, J., Mizielinski, M.S., Mizuta, R., Nobre, P., Satoh, M., Scoccimarro, E., Semmler, T., and, J. Small, and Storch, J.-S. von, 2016, High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6.

    Online Links:

    Other_Citation_Details:
    Haarsma, R.J., Roberts, M.J., Vidale, P. L., Senior, C.A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fučkar, N. S., Guemas, V., von Hardenberg, J., Hazeleger, W., Kodama, C., Koenigk, T., Leung, L.R., Lu, J., Luo, J.-J., Mao, J., Mizielinski, M. S., Mizuta, R., Nobre, P., Satoh, M., Scoccimarro, E., Semmler, T., Small, J., and von Storch, J.-S., 2016, High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6: Geoscientific Model Development, v. 9, p. 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016
    Hemer, Mark, Wang, Xiaolan, Weisse, Ralf, and Swail, Val, 2012, Advancing wind-waves climate science: The COWCLIP project.

    Online Links:

    Other_Citation_Details:
    Hemer, M., Wang, X., Weisse, R., Swail, V., 2012, Advancing wind-waves climate science: The COWCLIP project: Bulletin of the American Meteorological Society, v. 93, p. 791-796, https://doi.org/10.1175/BAMS-D-11-00184.1
    Hemer, Mark A., Fan, Yalin, Mori, Nobuhito, Semedo, Alvaro, and Wang, Xiaolan L., 2013, Projected changes in wave climate from a multi-model ensemble.

    Online Links:

    Other_Citation_Details:
    Hemer, M.A., Fan, Y., Mori, N., Semedo A., and Wang, X.L., 2013, Projected changes in wave climate from a multi-model ensemble: Nature Climate Change v. 3, p. 471–476, https://doi.org/10.1038/nclimate1791
    Mentaschi, Lorenzo, Vousdoukas, Michalis I., Voukouvalas, Evangelos, Dosio, Alessandro, and Feyen, Luc, 2017, Global changes of extreme coastal wave energy fluxes triggered by intensified teleconnection patterns.

    Online Links:

    Other_Citation_Details:
    Mentaschi, L., Vousdoukas, M. I., Voukouvalas, E., Dosio, A., and Feyen, L., 2017, Global changes of extreme coastal wave energy fluxes triggered by intensified teleconnection patterns: Geophysical Research Letters, v. 44, p. 2416–2426, doi:10.1002/2016GL072488.
    Morim, Joao, Hemer, Mark, Wang, Xiaolan L., Cartwright, Nick, Trenham, Claire, Semedo, Alvaro, Young, Ian, Bricheno, Lucy, Camus, Paula, Casas-Prat, Mercè, Erikson, Li, Mentaschi, Lorenzo, Mori, Nobuhito, Shimura, Tomoya, Timmermans, Ben, Aarnes, Ole, Breivik, Øyvind, Behrens, Arno, Dobrynin, Mikhail, Menendez, Melisa, Staneva, Joanna, Wehner, Michael, Wolf, Judith, Kamranzad, Bahareh, Webb, Adrean, Stopa, Justin, and Andutta, Fernando, 2019, Robustness and uncertainties in global multivariate wind-wave climate projections.

    Online Links:

    Other_Citation_Details:
    Morim, J., Hemer, M., Wang, X.L., Cartwright, N., Trenham, C., Semedo, A., Young, I., Bricheno, L., Camus, P., Casas-Prat, M., Erikson, L., Mentaschi, L., Mori, M. Shimura, T., Timmermans, B., Aarnes, O., Breivik, O., Behrens, A., Dobrynin, M., Menendez, M., Staneva, J., Wehner, M., Wolf, J., Kamranzad, B., Webb, A., Stopa, J., and Andutta, F., 2019, Robustness and uncertainties in global multivariate wind-wave climate projections: Nature Climate Change, v. 9,p. 711–718, https://doi.org/10.1038/s41558-019-0542-5
    Morim, Joao, Trenham, Claire, Hemer, Mark, Wang, Xiaolan L., Mori, Nobuhito, Casas-Prat, Mercè, Semedo, Alvaro, Shimura, Tomoya, Timmermans, Ben, Camus, Paula, Bricheno, Lucy, Mentaschi, Lorenzo, Dobrynin, Mikhail, Feng, Yang, and Erikson, Li, 2020, A global ensemble of ocean wave climate projections from CMIP5-driven models.

    Online Links:

    Other_Citation_Details:
    Morim, J., Trenham, C., Hemer, M. et al. A global ensemble of ocean wave climate projections from CMIP5-driven models: Scientific Data, v. 7, no. 105, https://doi.org/10.1038/s41597-020-0446-2
    Roberts, Malcolm J., Camp, Joanne, Seddon, Jon, Vidale, Pier L., Hodges, Kevin, Vannière, Benoît, Mecking, Jenny, Haarsma, Rein, Bellucci, Alessio, Scoccimarro, Enrico, Caron, Louis-Philippe, Chauvin, Fabrice, Terray, Laurent, Valcke, Sophie, Moine, Marie-Pierre, Putrasahan, Dian, D.Roberts, Christopher, Senan, Retish, Zarzycki, Colin, Ullrich, Paul, Yamada, Yohei, Mizuta, Ryo, Kodama, Chihiro, Fu, Dan, Zhang, Qiuying, Danabasoglu, Gokhan, Rosenbloom, Nan, Wang, Hong, and Wu, Lixin, 2020, Projected future changes in tropical cyclones using the CMIP6 HighResMIP multimodel ensemble.

    Online Links:

    Other_Citation_Details:
    Roberts, M.J., Camp, J., Seddon, J., Vidale, P.L., Hodges, K., Vannière, B., Mecking, J., Haarsma, R., Bellucci, A., Scoccimarro, E., Caron, L.-P., Chauvin, F., Terray, L., Valcke, S., Moine, M.-P., Putrasahan, D., Roberts, C.D., Senan, R., Zarzycki, C., Ullrich, P., Yamada, Y., Mizuta, R., Kodama, C., Fu, D., Zhang, Q., Danabasoglu, G., Rosenbloom, N., Wang, H. and Wu, L., 2020, Projected future changes in tropical cyclones using the CMIP6 HighResMIP multimodel ensemble: Geophysical Research Letters, v. 47, https://doi.org/10.1029/2020GL088662
    WAVEWATCHIII R Development Group (WW3DG), 2019, User manual and system documentation of WAVEWATCHIII R version 6.07..

    Online Links:

    Other_Citation_Details:
    WAVEWATCHIII R Development Group (WW3DG), 2019, Tech. Note 333, NOAA/NWS/NCEP/MMAB, College Park, MD, USA, p. 465 + Appendices, https://github.com/NOAA-EMC/WW3/wiki/files/manual.pdf

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
    This study does not include model hindcast runs and comparisons to buoy or altimeter observations, but comparisons to various measurements have been done by previous studies (for example, https://polar.ncep.noaa.gov/waves/validation/prod/).
  2. How accurate are the geographic locations?
    The horizontal accuracy is inherited from the source model grid (NOAA’s WAVEWATCHIII model). Because the overall horizontal accuracy depends on the underlying bathymetry, forcing values used, and the accuracy of the model, the spatial accuracy of this data layer cannot be meaningfully quantified.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    Spatial and attribute properties are believed to be complete. The geospatial data were checked for integrity. Possible data duplicates have been checked and eliminated.
  5. How consistent are the relationships among the observations, including topology?
    The data provided matches the wave source information and falls within the expected ranges for wave parameters. An exception is the GFDL wave outputs for years 2020-2050 which did not account for the sea ice cover in the Beaufort Sea area. Other regions including the Chukchi and Bering Seas do not appear to have been affected. The underlying reason for this lack of sea ice representation in only the Beaufort Sea region and for only this GCM is unclear. The affected data files are noted by a modification to the filename: ‘LimitedUse’.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints No access constraints
Use_Constraints 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, University of California Santa Cruz (UCSC), and Intel Corporation as the originator(s) of the dataset and in products derived from these data.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey - CMGDS
    2885 Mission Street
    Santa Cruz, CA

    1-831-427-4747 (voice)
    pcmsc_data@usgs.gov
  2. What's the catalog number I need to order this data set? The dataset consists of 14 netCDF files, seven of which contain hourly wave parameters for the years 1979 through 2014 and seven of which contain hourly wave projections for the years 2020 through 2050 at 1139 output points extracted from the 4-minute nested “Alaskan 4 min” grid (ak_4m; see https://polar.ncep.noaa.gov/waves/validation/). Wave parameters provided are as follows: significant wave heights (swell and seas combined), mean and peak wave periods, and mean and peak wave directions and associated spread. The motivation for providing high temporal resolution values of these variables is driven by the notion that storm impacts on coastal processes, including wave runup and erosion, are often investigated with these parameters. Each netCDF file represents results from model runs using wind forcing and sea ice boundary conditions from one Global Climate Model / General Circulation Model (GCM). Filenames follow the format: WavePnts_<GCM>_<grid>_<period>.nc where <GCM> is the abbreviated name of one of the GCMs listed above, <grid> refers to the NOAA-named model grid from which data were extracted. The common field ‘WavePnts’ is meant to indicate wave time-series at select model output points (as opposed to gridded data). <period> refers to the time-period for which data is provided where ‘His’ represents the historical time-period (1979 through 2014) and ‘Fut’ represents the projected time-period (2020 through 2050). The filename for the GFDL data includes the addition of ‘LimitedUse’ (full filename: WavePnts_GFLD_ak_4m_Fut_LimitedUse.nc) for the historical time-period to emphasize the limitations of the GFDL model results outlined in the Data Quality Information Section.
  3. What legal disclaimers am I supposed to read?
    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.
  4. How can I download or order the data?
    • Availability in digital form:
      Data format: files contain time-series of modeled (CMCC) wave parameters for the historical time-period in standard netCDF version 4 format. in format netCDF (version Python 3.7) CF4 Size: 8900
      Network links: https://doi.org/10.5066/P9KR0RFM
      Data format: files contain time-series of modeled (CMCC) wave parameters for the projected time-period in standard netCDF version 4 format. in format netCDF (version Python 3.7) CF4 Size: 7700
      Network links: https://doi.org/10.5066/P9KR0RFM
      Data format: files contain time-series of modeled (CNRM) wave parameters for the historical time-period in standard netCDF version 4 format. in format netCDF (version Python 3.7) CF4 Size: 8800
      Network links: https://doi.org/10.5066/P9KR0RFM
      Data format: files contain time-series of modeled (CNRM) wave parameters for the projected time-period in standard netCDF version 4 format. in format netCDF (version Python 3.7) CF4 Size: 7700
      Network links: https://doi.org/10.5066/P9KR0RFM
      Data format: files contain time-series of modeled (ECEARTH) wave parameters for the historical time-period in standard netCDF version 4 format. in format netCDF (version Python 3.7) CF4 Size: 8900
      Network links: https://doi.org/10.5066/P9KR0RFM
      Data format: files contain time-series of modeled (ECEARTH) wave parameters for the projected time-period in standard netCDF version 4 format. in format netCDF (version Python 3.7) CF4 Size: 7700
      Network links: https://doi.org/10.5066/P9KR0RFM
      Data format: files contain time-series of modeled (GFDL) for the historical time-period wave parameters in standard netCDF version 4 format. in format netCDF (version Python 3.7) CF4 Size: 8800
      Network links: https://doi.org/10.5066/P9KR0RFM
      Data format: files contain time-series of modeled (GFDL) for the projected time-period wave parameters in standard netCDF version 4 format. in format netCDF (version Python 3.7) CF4 Size: 7600
      Network links: https://doi.org/10.5066/P9KR0RFM
      Data format: files contain time-series of modeled (HadgemHH) wave parameters for the historical time-period in standard netCDF version 4 format. in format netCDF (version Python 3.7) CF4 Size: 8900
      Network links: https://doi.org/10.5066/P9KR0RFM
      Data format: files contain time-series of modeled (HadgemHH) wave parameters for the projected time-period in standard netCDF version 4 format. in format netCDF (version Python 3.7) CF4 Size: 7800
      Network links: https://doi.org/10.5066/P9KR0RFM
      Data format: files contain time-series of modeled (HadgemHM) wave parameters for the historical time-period in standard netCDF version 4 format. in format netCDF (version Python 3.7) CF4 Size: 8900
      Network links: https://doi.org/10.5066/P9KR0RFM
      Data format: files contain time-series of modeled (HadgemHM) wave parameters for the projected time-period in standard netCDF version 4 format. in format netCDF (version Python 3.7) CF4 Size: 7700
      Network links: https://doi.org/10.5066/P9KR0RFM
      Data format: files contain time-series of modeled (HadgemSST) wave parameters for the historical time-period in standard netCDF version 4 format. in format netCDF (version Python 3.7) CF4 Size: 8900
      Network links: https://doi.org/10.5066/P9KR0RFM
      Data format: files contain time-series of modeled (HadgemSST) wave parameters for the projected time-period in standard netCDF version 4 format. in format netCDF (version Python 3.7) CF4 Size: 7800
      Network links: https://doi.org/10.5066/P9KR0RFM
    • Cost to order the data: None.

  5. What hardware or software do I need in order to use the data set?
    These data can be viewed with any software that reads netCDF files (such as Mathworks MATLAB™, Python, Panoply).

Who wrote the metadata?

Dates:
Last modified: 26-Oct-2024
Metadata author:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Attn: PCMSC Science Data Coordinator
2885 Mission Street
Santa Cruz, CA

831-427-4747 (voice)
pcmsc_data@usgs.gov
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/pcmsc/DataReleases/CMGDS_DR_tool/DR_P9KR0RFM/WavePnts_metadata_ak_4m.faq.html>
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