Data displayed on the NOAA Great Lakes Environmental Research Laboratory (GLERL) website is considered experimental.
GLERL is located within NOAA Research. NOAA GLERL is providing these data "as is". Timely
delivery of data and products through the Internet is not guaranteed. Before using information obtained from this website, special
attention should be given to the date and time frame of the data and products being displayed. (see
GLERL Disclaimer and Intellectual Property Notice)
GLERL collects environmental and physical observations through a variety of techniques. These techniques include: direct
biological sampling, satellite remote sensing, in situ sensors and observing systems, and mobile platforms,
such as vessels and autonomous vehicles. Observations of the physical, chemical, and
biological components of the Great Lakes and coastal ecosystems supports studies and assessments,
inform experiments and models, and ultimately predictions and forecasts.
Citing GLERL Data
How do I cite GLERL data located at NCEI?
The National Centers for Environmental Information (NCEI) is
NOAA’s data archiving center. Many of the NOAA GLERL datasets are archived on the NCEI website. Please review the tabs on
this page to find links to specific GLERL datasets located in the NCEI archives.
To cite GLERL data at NCEI, please use the “Data Citation” text located in the right menu on a dataset’s landing page at NCEI.
How do I cite data located only on the GLERL website?
Please use the following format:
NOAA. webpage name, optional: dataset subset. Great Lakes Environmental Research Laboratory, website URL.
Accessed MM/DD/YYYY.
For example, the citation for a subset of the Great Lakes Coastal Forecasting System (GLCFS)
data would look like this:
NOAA. Great Lakes Coastal Forecasting System (GLCFS), Lake Huron waves and currents from 2018-2020. Great Lakes Environmental Research Laboratory,
website, https://www.glerl.noaa.gov/res/glcfs/. Accessed: 4/12/2022.
Great Lakes Depth and Shoreline Data
Lake Depths Data
NOAA was engaged in a program to compile Great Lakes bathymetric (lake depth) data and make them readily available to the public,
especially to the communities concerned with Great Lakes science, pollution, coastal erosion, response to climate changes, threats to lake ecosystems,
and health of the fishing industry. Compilation of new bathymetry for the Great Lakes was an important part of this program, carried out cooperatively between NOAA
(NCEI and GLERL), and the Canadian Hydrographic Service. This new bathymetry provided a more detailed portrayal of lakefloor topography, and revealed
some lakefloor features seen for the first time
Bathymetry (Lake Depths)
Shoreline & Navigation
Data from Historical Field Experiments
Climate
NOAA-GLERL is working to improve and expand the capacity to forecast effects of climate change on the Great Lakes and its ecosystem to
reduce risk and improve resilience.
Water Temperature & Ice Data
GLERL collects water temperature data from buoys and people deploying instruments from research vessels. GLERL also predicts Great Lakes water temperatures
using NOAA scientific models.
- In situ observations
- Modeled water temperatures & ice
- The NOAA Great Lakes Coastal Forecasting System (GLCFS) is a set of experimental 3-D models that predict currents,
water temperatures, waves, ice, and more in the Great Lakes. This experimental data can be found here:
Great Lakes Coastal Forecasting System (GLCFS)/
- Satellite-derived water temperatures
- Ice Cover Observations
GLERL has been monitoring and documenting Great Lakes ice cover since the early 1970's using the ice products developed by the
U.S. National Ice Center and the Canadian Ice Service.
Ice cover data specific to the Great Lakes can be found here:
- Great Lakes Ice Cover Observations
- Water Temperature Observations Data at NCEI
Currents Data
GLERL collects surface current observations data from drifters and models and predicts Great Lakes currents
using NOAA scientific models.
- In situ observations
- Modeled currents
- The NOAA Great Lakes Coastal Forecasting System (GLCFS) is a set of experimental 3-D models that predict currents,
water temperatures, waves, ice, and more in the Great Lakes. This experimental data can be found here:
Great Lakes Coastal Forecasting System (GLCFS)/
Harmful Algal Blooms & Hypoxia Data
NOAA GLERL harmful algal blooms (HABs) and hypoxia research program uses an integrated approach
to understand the environmental drivers of HABs and hypoxia to predict events. This approach includes using satellite
images, remote sensing, buoys, a comprehensive monitoring program in Lake Erie, and Saginaw Bay, Lake Huron, and advanced genetic
techniques to understand the long and short-term seasonal dynamics of HABs and hypoxia. The data collected are used to inform forecast
models used by key Great Lakes stakeholder groups, such as drinking water managers.
Lake Erie
Saginaw Bay, Lake Huron
Biological and Water Quality Data
NOAA GLERL makes long-term ecological observations, conducts targeted
fundamental research on ecological processes, and provides data to develop models critical to understanding
ecosystem structure and function. GLERL also develops models to forecast impacts of multiple stressors e.g., invasive species,
climate, and nutrients on water
quality, food webs and fisheries. GLERL observations, laboratory, and field experiments support the development of new concepts,
models, forecasting tools and
applications to evaluate and forecast impacts of, and mitigation strategies for, present and future ecosystem stressors
- Benthos & Invasive Species
- Biological Identification
- Long-Term Ecological Research - Muskegon Transect
- UV & PAR
- Water Quality
- Zooplankton
Remote Sensing Data
NOAA GLERL develops and uses remote sensing technology and products to record and observe the Great Lakes environment through the collection of data.
Remote sensing technology enables observing, measuring, and monitoring of detailed and symoptic events on the eartlh's surface (land and water) and atmposphere through
the use of satellite-based, airborne, and ship-based sensors that are remote from the objects or events being observed. These observations directly benefit a wide range
of research and operational constituents such as commercial shippers, modelers, recreational users, and regional drinking water managers.
How to Access GLERL Data at NCEI
Datasets archived at NCEI are either a specific record or part of a collection1. To access data follow the instructions below.
- Click on an NCEI link from one of the tabs above to access data of interest located at NCEI.
- The dataset landing page at NCEI provides a title, brief abstract, suggested dataset citation and
other helpful information about the dataset.
- To access the data at NCEI, first go to the Access tab.
In the Download Data row of the table you will see either HTTPS or Granule Search.
To access the data for specific record, click on the HTTPS.
To access the data for a collection, click on the Granule Search, select the granule2 (record) of interest, and
then click on the HTTPS
under the individual granules Access tab.
- The Downloads page allows the user to download individual files. Or, clicking the link that ends in “.tar.gz” will download all the
files associated with the dataset as a compressed .tar.gz file. If you download the compressed file, you now have the files locally and can decompress
them using 7-Zip or other file archiving utility software. If you choose to download the files individually, proceed to the next step.
- Click on the Download individual files for accession link, which will take you to an archive index navigation.
The first level of the index shows all the available versions of the data organized by folder. Select the most recent version (highest number) to download.
- You may browse through the dataset and download individual files by right-clicking on them and selecting Save link as…. Note that only individual
files, and not folders, can be downloaded using Save link as... On a Mac,
press and hold the Control key while clicking an item.
- Please cite using the "Data Citation" text located in the right menu on a dataset's landing page.
Definitions
1A collection is a grouping of environmental data or products that share common characteristics, is represented by a
single metadata record, and consists of one or more granules.
2A granule is the smallest aggregation of data that can be independently described and retrieved.
