SalishSeaCast ERDDAP

ERDDAP is a data server that gives you a simple, consistent way to download subsets of scientific datasets in common file formats and make graphs and maps.

This particular ERDDAP installation has model product datasets from the SalishSeaCast system run by the Mesoscale Ocean and Atmospheric Dynamics (MOAD) group in the Department of Earth, Ocean, and Atmospheric Sciences (EOAS) at the University of British Columbia (UBC). Available datasets include surface and 3D fields of currents, temperature, salinity, sea surface height, biological and chemical tracers from NEMO and FVCOM, and wave fields WaveWatch III®, as well as the Environment and Climate Change Canada (ECCC) High Resolution Deterministic Prediction System (HRDPS) atmospheric model fields used to force the models. Also available are aggregated datasets from selected Ocean Networks Canada (ONC) real-time sensors, and a real-time current dataset from a Vancouver Fraser Port Authority (VFPA) sensor at the 2nd Narrows railway bridge in Vancouver Harbour.

Please see https://salishsea.eos.ubc.ca/ for more information about the model and the SalishSeaCast system.

V21-11 NEMO Model is Live!

A new, improved version of the SalishSeaCast NEMO model has been running in near-real-time since 1-Jan-2024. A hindcast from 1-Jan-2007 using that model configuration was completed in late 2023. New NEMO datasets from that model configuration were added to this ERDDAP starting in December 2023. They are identified with a V21-11 version string in their dataset ids, titles, summaries, etc.

The hindcast was spun up for 5 years with best available forcing and boundary conditions for 2002-2006. The spin-up years are not included in the V21-11 datasets.

Time series datasets like hourly physics, biology, and chemistry variables will have co-existing V19-05 and V21-11 versions until at least 31-Dec-2024, after which time the V19-05 datasets will be removed.

The rolling forecast datasets are from the V21-11 model configuration. The version part of the rolling forecast dataset ids was dropped on 2-Jul-2019 to reflect the fact that those datasets transition smoothly from one model version to the next. Please see the summary metadata item to learn what model version is producing the most recent fields in the rolling forecast datasets.

Changes Between V19-05 and V21-11

Physics

From Stang and Allen, 2024:

• Daily river flows are calculated using continuous gauge records fitted to monthly watersheds from Morrison et al. (2012), which allows for inter-annual variability like winter storms and summer droughts.
• The bathymetry was improved by adjusting the coastline to the 2-m isobath (previously set to the mean sea level isobath) and then deepening the minimum water depth to 4 m. These changes align the extent of the Fraser River plume more closely with observations. The bathymetry is available in the ubcSSnBathymetryV21-08 dataset.
• Coastal wave characterization was improved using WaveWatch III® model results, addressing the small fetch and waves in the Salish Sea (Moore-Maley, 2022). The new parameterization reduces mixing by adjusting the turbulence parameterization surface boundary condition, partially correcting the too salty surface salinities in the Fraser River plume.

Biology

From Suchy, et al, in preparation:

• Mesodinium rubrum removed as evaluation showed the model was not reproducing the small number of observations available.
• Functional light dependence was switched to a PE-curve style, but tuned to closely match the V19-05 response
• Sinking for biological tracers was switched from upstream advection to being incorporated in the NEMO Flux-Corrected Transport scheme
• River tracer inputs were updated
• The N:O coupling for various processes was updated and a parameter for sediment oxygen demand was added that effectively allows an oxygen flux into the sediments not coupled to an outgoing nitrate flux. It is proportional to the amount of organic matter sinking out of the domain. Further improvements to oxygen in the model are ongoing.

References

Stang C. and Allen S.E., 2024. Seasonably variable estuarine exchange through inter-connected channels in the Salish Sea. ESS Open Archive, November 11, 2024. DOI: https://doi.org/10.22541/essoar.173134323.35470755/v1

Morrison, J., Foreman, M. G. G., & Masson, D., 2012. A Method for Estimating Monthly Freshwater Discharge Affecting British Columbia Coastal Waters. Atmosphere-Ocean, 50(1), 1–8. https://doi.org/10.1080/07055900.2011.637667

Moore-Maley, B. L., 2022. Wind-driven upwelling and nutrient supply in a productive estuarine sea. University of British Columbia. https://open.library.ubc.ca/collections/ubctheses/24/items/1.0418447

Citing SalishSeaCast Datasets

If you use datasets from this ERDDAP server in your research, please reference it with wording similar to these examples, and include citations of the publications below.

Example reference for physics-only datasets:

Velocity, temperature, and salinity fields from the SalishSeaCast model (Soontiens et al, 2016; Soontiens and Allen, 2017) were downloaded from their ERDDAP server (https://salishsea.eos.ubc.ca/erddap/) on DATE from datasets: DATASETID, DATASETID, ...

Example reference for biological and dissolved oxygen datasets:

Nitrate, silicon, and diatom fields from the SalishSeaCast model (Soontiens et al, 2016; Moore-Maley et al, 2016; Soontiens and Allen, 2017; Olson et al, 2020) were downloaded from their ERDDAP server (https://salishsea.eos.ubc.ca/erddap/) on DATE from datasets: DATASETID, DATASETID, ...

Example reference for carbon chemistry datasets:

Dissolved inorganic carbon, total alkalinity, and surface CO2 flux fields from the SalishSeaCast model (Soontiens et al, 2016; Moore-Maley et al, 2016; Soontiens and Allen, 2017; Olson et al, 2020; Jarníková et al, 2022) were downloaded from their ERDDAP server (https://salishsea.eos.ubc.ca/erddap/) on DATE from datasets: DATASETID, DATASETID, ...

In any of those cases, you substitute in the DATE(s) on which you downloaded the fields, and the DATASETID(s) you downloaded from. The DATE(s) and DATASETID(s) help to ensure reproducibility of your work. DATASETID(s) look like ubcSSg3DTracerFields1hV21-11 and are listed in the rightmost column of the table at https://salishsea.eos.ubc.ca/erddap/info/index.html

Publications to Cite

Jarníková T., Ianson D., Allen S.E., Shao A.E., Olson E.M., 2022. Anthropogenic carbon increase has caused critical shifts in aragonite saturation across a sensitive coastal system. Global Biogeochemical Cycles, 36(7). https://doi.org/10.1029/2021GB007024

Olson, E. M., Allen, S. E., Do, Vy, Dunphy, M., and Ianson, D., 2020. Assessment of Nutrient Supply by a Tidal Jet in the Northern Strait of Georgia Based on a Biogeochemical Model. J. Geophys. Res. Oceans 125(8). https://doi.org/10.1029/2019JC015766

Soontiens, N. and Allen, S., 2017. Modelling sensitivities to mixing and advection in a sill-basin estuarine system. Ocean Modelling, 112, 17-32. https://dx.doi.org/10.1016/j.ocemod.2017.02.008

Soontiens, N., Allen, S., Latornell, D., Le Souef, K., Machuca, I., Paquin, J.-P., Lu, Y., Thompson, K., Korabel, V., 2016. Storm surges in the Strait of Georgia simulated with a regional model. Atmosphere-Ocean, 54, 1-21. https://dx.doi.org/10.1080/07055900.2015.1108899

Moore-Maley, B. L., Allen, S. E., and Ianson, D., 2016. Locally-driven interannual variability of near-surface pH and ΩA in the Strait of Georgia. J. Geophys. Res. Oceans, 121(3), 1600–1625. https://dx.doi.org/10.1002/2015JC011118

Easier Access to Scientific Data

Different scientific communities have developed different types of data servers.

For example, OPeNDAP, WCS, SOS, OBIS, and countless custom web pages with forms. Each is great on its own. But without ERDDAP, it is difficult to get data from different types of servers:

• Different data servers make you format your data request in different ways.
• Different data servers return data in different formats, usually not the common file format that you want.
• Different datasets use different formats for time data, so the results are hard to compare.

ERDDAP unifies the different types of data servers so you have a consistent way to get the data you want, in the format you want.

• ERDDAP acts as a middleman between you and various remote data servers. When you request data from ERDDAP, ERDDAP reformats the request into the format required by the remote server, sends the request to the remote server, gets the data, reformats the data into the format that you requested, and sends the data to you. You no longer have to go to different data servers to get data from different datasets.
   
• ERDDAP offers an easy-to-use, consistent way to request data: via the OPeNDAP standard. Many datasets can also be accessed via ERDDAP's Web Map Service (WMS).
   
• ERDDAP returns data in the common file format of your choice. ERDDAP offers all data as .html table, ESRI .asc and .csv, Google Earth .kml, OPeNDAP binary, .mat, .nc, ODV .txt, .csv, .tsv, .json, and .xhtml. So you no longer have to waste time and effort reformatting data.
   
• ERDDAP can also return a .png or .pdf image with a customized graph or map.
   
• ERDDAP standardizes the dates+times in the results. Data from other data servers is hard to compare because the dates+times often are expressed in different formats (for example, "Jan 2, 1985", 2 Jan 85, 02-JAN-1985, 1/2/85, 2/1/85, 1985-01-02, "days since Jan 1, 1900"). For string times, ERDDAP always uses the ISO 8601:2004(E) standard format, for example, 1985-01-02T00:00:00Z. For numeric times, ERDDAP always uses "seconds since 1970-01-01T00:00:00Z". ERDDAP always uses the Zulu (UTC, GMT) time zone to remove the difficulties of working with different time zones and standard time vs. daylight saving time. ERDDAP has a service to convert a string time to/from a numeric time.
   
• ERDDAP has web pages (for humans with browsers) and RESTful web services (for computer programs). You can bypass ERDDAP's web pages and use ERDDAP's RESTful web services (for example, for searching for datasets, for downloading data, for making maps) directly from any computer program (for example, Matlab, R, or a program that you write) and even from web pages (via HTML image tags or JavaScript).

For a quick introduction to ERDDAP, watch the first half of this video. (5 minutes) In it, a scientist downloads ocean currents forecast data from ERDDAP to model a toxic spill in the ocean using NOAA's GNOME software (in 5 minutes!). Thanks to Rich Signell. (One tiny error in the video: when searching for datasets, don't use AND between search terms. It is implicit.)

Find out more about ERDDAP.

Data Providers: You can set up your own ERDDAP server and serve your own data. ERDDAP is free and open source. It uses Apache-like licenses, so you can do anything you want with it. ERDDAP's appearance is customizable, so your ERDDAP will reflect your institution, not NOAA. The small effort to set up ERDDAP brings many benefits. If you already have a web service for distributing your data, you can set up ERDDAP to access your data via the existing service or via the source files or database. Then, people will have another way to access your data and will be able to download the data in additional file formats or as graphs or maps. ERDDAP has been installed by over 60 organizations worldwide. NOAA's Data Access Procedural Directive includes ERDDAP in its list of recommended data servers for use by groups within NOAA.

Start Using ERDDAP:
    Search for Interesting Datasets

• View a List of All 69 Datasets

• Do a Full Text Search for Datasets

  Search

• Search for Datasets by Category

  Datasets can be categorized in different ways by the values of various metadata attributes. Click on an attribute (cdm_data_type, institution, ioos_category, keywords, long_name, standard_name, variableName) to see a list of categories (values) for that attribute. Then, you can click on a category to see a list of relevant datasets.

• Search for Datasets with Advanced Search 

• Search for Datasets by Protocol

  Protocols are the standards which specify how to request data. Different protocols are appropriate for different types of data and for different client applications.
   

  Protocol	Description
  griddap datasets	Griddap lets you use the OPeNDAP hyperslab protocol to request data subsets, graphs, and maps from gridded datasets (for example, satellite data and climate model data). griddap documentation
  tabledap datasets	Tabledap lets you use the OPeNDAP constraint/selection protocol to request data subsets, graphs, and maps from tabular datasets (for example, buoy data). tabledap documentation
  "files" datasets	ERDDAP's "files" system lets you browse a virtual file system and download source data files. WARNING! The dataset's metadata and variable names in these source files may be different than elsewhere in ERDDAP! You might prefer using the dataset's Data Access Form instead. "files" documentation
  WMS datasets	The Web Map Service (WMS) lets you request an image with data plotted on a map. WMS documentation

   

• Developers of computer programs and JavaScripted web pages can search for datasets via

  • ERDDAP's RESTful search services
  • ERDDAP's allDatasets tabular dataset that has a row of information for each dataset
  • ERDDAP's OpenSearch 1.1 Service

Converters
In addition to serving data, ERDDAP has some handy converters:

Metadata
ERDDAP has an
FGDC Web Accessible Folder (WAF) with FGDC‑STD‑001‑1998 metadata files and an
ISO 19115 Web Accessible Folder (WAF) with ISO 19115‑2/19139 metadata files for all of the geospatial datasets in this ERDDAP.

RESTful Web Services
You can bypass ERDDAP's web pages and use ERDDAP's RESTful web services (for example, for searching for datasets, for downloading data, for making maps) directly from any computer program (for example, Matlab, R, or a program that you write) and even from web pages (via HTML image tags or JavaScript). REST documentation

And