Sources and Citations

forcingkit produces no data of its own: every value in a store comes from a model or network run by the institutions below. If you publish work that uses a forcingkit store, cite the source models and acknowledge the providers named in the store’s source attribute, as you would if you had fetched the data yourself. Terms of use are the providers’; check their pages for the current wording.

Providers

Source

Institutions

Cite or acknowledge

HRRR

NOAA Global Systems Laboratory (development) and NOAA NCEP (operations); distributed by NOAA Open Data Dissemination

Dowell et al. (2022); James et al. (2022). NOAA asks for attribution and that modified products not be presented as NOAA’s.

NECOFS

UMass Dartmouth SMAST and Woods Hole Oceanographic Institution; operation supported by NERACOOS

Chen, Liu and Beardsley (2003) for FVCOM; acknowledge NECOFS and SMAST.

NYOFS, DBOFS

NOAA CO-OPS; archived by NOAA NCEI and on AWS through NOAA Open Data Dissemination

Blumberg and Mellor (1987) for POM (NYOFS); Shchepetkin and McWilliams (2005) for ROMS (DBOFS); NOAA attribution as for HRRR.

HYCOM

The HYCOM consortium (US Navy, NOAA and academic partners); from 2024-09-05 the US Navy’s ESPC-D-V02 analysis, served by the consortium

Bleck (2002) for the model; Chassignet et al. (2007) for the data-assimilative system.

ERA5 (used through NumericalEarth, not served here)

ECMWF for the Copernicus Climate Change Service

Hersbach et al. (2020). The Copernicus licence requires the statement “Contains modified Copernicus Climate Change Service information [year]”.

CO-OPS water level

NOAA CO-OPS

NOAA attribution.

NDBC buoys

NOAA National Data Buoy Center

NOAA attribution.

River discharge

US Geological Survey stream gauges, through the USGS Water Data APIs; drainage areas from the USGS NLDI and NHDPlus

Cite the gauges as “U.S. Geological Survey, USGS Water Data for the Nation”, with the site numbers in the store’s provenance. USGS data are in the public domain; provisional values are subject to revision.

Satellite surface fields

NOAA NESDIS CoastWatch ERDDAP servers: VIIRS chlorophyll-a and Kd490 (S-NPP, NOAA-20, NOAA-21), Sentinel-3 OLCI chlorophyll-a, and the gap-filled DINEOF products; MUR sea surface temperature from NASA JPL (PO.DAAC), served through CoastWatch

Acknowledge NOAA NESDIS CoastWatch and the datasets named in the store’s products attribute. MUR: JPL MUR MEaSUREs Project (2015) and Chin et al. (2017). OLCI and DINEOF products require “Contains modified Copernicus Sentinel data [year]”.

Water-column profiles

University of Connecticut Department of Marine Sciences (ERDDAP)

Acknowledge the station operator named in each dataset’s ERDDAP metadata.

Related systems not served by forcingkit: NYHOPS from the Davidson Laboratory at Stevens Institute of Technology (see NYOFS: NOAA New York/New Jersey Operational Forecast System), and the atmospheric datasets compared in Atmospheric Forcing Datasets.

Software

References

  • Beardsley, R. C., C. Chen and Q. Xu (2013). Coastal flooding in Scituate (MA): A FVCOM study of the 27 December 2010 nor’easter. Journal of Geophysical Research: Oceans, 118(11), 6030-6045. doi:10.1002/2013JC008862

  • Bleck, R. (2002). An oceanic general circulation model framed in hybrid isopycnic-Cartesian coordinates. Ocean Modelling, 4(1), 55-88. doi:10.1016/S1463-5003(01)00012-9

  • Blumberg, A. F. and G. L. Mellor (1987). A description of a three-dimensional coastal ocean circulation model. In N. S. Heaps (ed.), Three-Dimensional Coastal Ocean Models, Coastal and Estuarine Sciences 4, American Geophysical Union, 1-16. doi:10.1029/CO004p0001

  • Chassignet, E. P., H. E. Hurlburt, O. M. Smedstad, et al. (2007). The HYCOM (HYbrid Coordinate Ocean Model) data assimilative system. Journal of Marine Systems, 65(1-4), 60-83. doi:10.1016/j.jmarsys.2005.09.016

  • Chen, C., H. Liu and R. C. Beardsley (2003). An unstructured grid, finite-volume, three-dimensional, primitive equations ocean model: application to coastal ocean and estuaries. Journal of Atmospheric and Oceanic Technology, 20(1), 159-186. doi:10.1175/1520-0426(2003)020<0159:AUGFVT>2.0.CO;2

  • Chin, T. M., J. Vazquez-Cuervo and E. M. Armstrong (2017). A multi-scale high-resolution analysis of global sea surface temperature. Remote Sensing of Environment, 200, 154-169. doi:10.1016/j.rse.2017.07.029

  • Dowell, D. C., C. R. Alexander, E. P. James, et al. (2022). The High-Resolution Rapid Refresh (HRRR): An hourly updating convection-allowing forecast model. Part I: Motivation and system description. Weather and Forecasting, 37(8), 1371-1395. doi:10.1175/WAF-D-21-0151.1

  • Hersbach, H., B. Bell, P. Berrisford, et al. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), 1999-2049. doi:10.1002/qj.3803

  • James, E. P., C. R. Alexander, D. C. Dowell, et al. (2022). The High-Resolution Rapid Refresh (HRRR): An hourly updating convection-allowing forecast model. Part II: Forecast performance. Weather and Forecasting, 37(8), 1397-1417. doi:10.1175/WAF-D-21-0130.1

  • JPL MUR MEaSUREs Project (2015). GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). PO.DAAC, CA, USA. doi:10.5067/GHGMR-4FJ04

  • NOAA (2002). Implementation Plan, Port of New York and New Jersey Operational Forecast System (NYOFS). NOAA Technical Report NOS CO-OPS 37, Silver Spring, MD. PDF

  • Ramadhan, A., G. L. Wagner, C. Hill, et al. (2020). Oceananigans.jl: Fast and friendly geophysical fluid dynamics on GPUs. Journal of Open Source Software, 5(53), 2018. doi:10.21105/joss.02018

  • Shchepetkin, A. F. and J. C. McWilliams (2005). The regional oceanic modeling system (ROMS): a split-explicit, free-surface, topography-following-coordinate oceanic model. Ocean Modelling, 9(4), 347-404. doi:10.1016/j.ocemod.2004.08.002

  • Tsujino, H., S. Urakawa, H. Nakano, et al. (2018). JRA-55 based surface dataset for driving ocean-sea-ice models (JRA55-do). Ocean Modelling, 130, 79-139. doi:10.1016/j.ocemod.2018.07.002