Extract and download data from the World Ocean Database
The WOD data is available from various sources. In this tutorial, you’ll use the WODselect retrieval system, which allows you to extract data based on geographic area, date, and variables. You’re interested in studying the start of the 2022 hurricane season in the Gulf of Mexico, so you’ll limit your search accordingly.
- Go to the World Ocean Database Select and Search page.
Note:
If the WOD website is unavailable, you can download a copy of the data. Continue reading through the tutorial and begin following the steps again at the next section.
First, you’ll set the criteria that you’ll use to search for data. You want to define your search based on a specific area (the Gulf of Mexico), specific dates (June 2022), and a specific variable (temperature).
- Under Search Criteria, check the boxes for Geographic Coordinates, Observation Dates, and Measured Variables.
- Click the Build a query button.
The next page allows you to build a query to search for data based on your selected criteria.
- For Geographic Coordinates, enter the following:
- Northern edge: 31
- Western edge: -99
- Eastern edge: -80
- Southern edge: 17
These coordinates correspond to the Gulf of Mexico.
Note:
Alternatively, click Draw Map. Press and hold the Shift key. Click and drag on the map to draw a box around the Gulf of Mexico. Click Submit Coordinates.
- For Observation Dates, type the following values:
Year [YYYY] Month [1-12] Day [1-31] From:
2022
6
1
To:
2022
6
30
June 1 is the start of hurricane season in the Atlantic basin. The peak of the season is not until September, but this data will give you a sense of how the early season developed in 2022.
- For Measured Variables, check both check boxes next to Temperature.
Column 1 allows you to select variables that you're interested in but which don’t need to appear in every cast. Column 2 allows you to select variables that are crucial for your analysis, guaranteeing that they will be present in every cast. A cast is a single deployment of an instrument package into the ocean to collect data.
- Scroll to the bottom of the page and click the Get an Inventory button.
The inventory report may take a few minutes to generate.
Note:
If the inventory report takes too long to generate, you can download a copy of the data. Continue reading through the tutorial and begin following the steps again at the next section.
The inventory report displays the number of casts for each type of oceanographic instrument, the estimated file size, and the approximate extraction time.
- Click the Download Data button.
- On the next page, in the Choose Format section, for netCDF, choose ragged array.
The tools in ArcGIS Pro expect the data to be in this format. NetCDF is a file format for storing multidimensional scientific data. You can read more about the netCDF ragged array format on the NCEI website.
- Leave all other options at their default values.
- In the Extract Data section, type your email address and click Extract Data.
Within a few minutes, you will receive an email with two links to download two files.
- In the email, click each of the File name links to download the data.
- Unzip both of the downloaded .gz files to a location you can remember.
Note:
You may need to install the 7-zip application to unzip the .gz files. Alternatively, download a copy of the data with the .zip file extension.
The unzipped data consists of two netCDF files: ocldb1712848812.21990_APB.nc and ocldb1712848812.21990_PFL.nc. Depending on how they were unzipped, they may be inside two folders with the same names.
The files are named based on the type of measurement instrument: the observations in the APB file were collected by Autonomous Pinniped Bathythermographs (sensors attached to seals), and the PFL data was collected by profiling floats. You can find the acronyms and descriptions of all of the WOD instrument types in the WOD Introduction document.
Make a map in ArcGIS Pro
Next, you’ll make a new project and map in ArcGIS Pro to view the WOD data.
- Start ArcGIS Pro. If prompted, sign in with your ArcGIS account.
Note:
If you don't have access to ArcGIS Pro or an ArcGIS organizational account, see options for software access.
- Under New Project, click Map.
- In the New Project window, for Name, type Gulf of Mexico, June 2022. Optionally, choose a different location.
- Click OK.
A map appears.
Run the NetCDF Profiles To Feature Class tool
Next, you need to add the downloaded netCDF data to the map. Because it is multidimensional data, it can’t be added to ArcGIS Pro directly. You’ll use a geoprocessing tool to convert the two netCDF files into feature classes.
- On the ribbon, click the Analysis tab. In the Geoprocessing group, click Tools.
The Geoprocessing pane appears.
- In the search bar, type netcdf.
A list of tools that use or create the netCDF data format appear.
- In the list of search results, click NetCDF Profiles To Feature Class (Discreete Sampling Geometry).
This is one of several tools in ArcGIS Pro that read data formatted as discrete sampling geometries. You’ll choose this specific tool because the WOD data that you downloaded is structured as profiles. Profiles are a series of connected observations along a vertical line, in this case, temperature measurements at different depths.
- For Input NetCDF Files or Folders, click the Browse button.
- Browse to the location where you unzipped the data from the World Ocean Database. Select one of the .nc files.
- Click the next Browse button and select the other .nc file.
Note:
If you have a folder with many netCDF files, you can point to it instead of adding the files individually.
The tool updates to list three observation variables:
- Temperature_WODflag (sea_water_temperature status_flag) records the results of a quality check. A value of zero indicates that there are no concerns with the observation. Other values indicate there might be a problem.
- Temperature_sigfigs (sea_water_temperature significant_figures) records the number of significant digits in the data. ArcGIS Pro handles this automatically, so you don’t need this variable.
- Temperature (sea_water_temperature, degree_C) contains the temperature measurement.
- For Observation Variables, check the boxes for Temperature_WODflag (sea_water_temperature status_flag) and Temperature (sea_water_temperature, degree_C).
- For Instance Variables, check the box for date (date).
- For Output Schema, ensure that Instance and Observation is chosen.
In this example, the instances are the casts. They contain the spatial information and the date. The observations are the measurements from each cast. They contain the temperature measurements at different depths.
The Instance and Observation schema will result in a feature class of 2D points (the instances) with an associated table containing the temperature variables (the observations).
Next, you’ll define names for the layers that the tool will create.
- For Output Point or Polyline Name, type gulf_instances.
- For Output Join or Event Table Name, type gulf_observations.
- For Output Join Layer, type gulf_join.
The Output Join Layer is an optional parameter and is only available when Output Schema is set to Instance and Observation. It combines the instances and observations into a single layer. You’ll use it later in the tutorial.
- Click Run.
Explore the data
Three layers are added to the Contents pane: gulf_join, gulf_instances, and gulf_observations. The data appears on the map as a number of points scattered about the Gulf of Mexico.

Next, you’ll explore how this data is structured and where it is stored.
- In the Contents pane, right-click the gulf_instances layer and click Attribute Table.
The table appears below the map and contains the date and time of each cast.
This layer also contains the location of each cast, visible on the map.
- In the Contents pane, right-click gulf_observations and click Open.
Another table appears. This layer is a stand-alone table, which means it contains no spatial information. It contains the temperature and depth measurements for each observation.
These two layers can be joined together using their common field (InstanceID) and the Add Join geoprocessing tool. However, this isn’t necessary because the NetCDF Profiles To Feature Class tool has already created a joined layer: gulf_join.
- Close the two open tables. In the Contents pane, right-click gulf_join and click Attribute Table.
This layer is more useful to you than the other two. It contains many features with the same InstanceID value and the same location, but different ObservationID, depth, and temperature values.
Below the table, a Duplicate rows warning appears. This is an expected result of the one-to-many join and can be ignored.
- Close the attribute table.
Export the joined layer
The gulf_join layer is temporary. It was created by the NetCDF Profiles To Feature Class tool to allow you to quickly explore the output without creating a potentially large file on disk. To use this layer in other geoprocessing tools, you must copy it to a permanent feature class.
- At the top of the Geoprocessing pane, click the Back button.
- Search for and open the Copy Features tool.
- For Input Features, choose gulf_join. For Output Feature Class, type Temperature_June2022.
- Click Run.
A new layer appears in the Contents pane. The new layer, Temperature_June2022, is stored on disk, in your project’s geodatabase. The old layer (gulf_join) was only stored in memory. The new layer can be used as an input in other geoprocessing tools.
Note:
To view your project’s geodatabase, on the ribbon, click the View tab. In the Windows group, click Catalog Pane. In the Catalog pane, click the Project tab and expand Databases.
- In the Contents pane, right-click gulf_join and click Remove.
- Also remove the gulf_instances and gulf_observations layers.
- Right-click anywhere on the map and click Select Features.
- On the map, drag a box around any isolated point to select it.
Below the map, the Zoom to selected features button records the number of selected features. It is a large number because each observation is now recorded as a separate feature, and there are many observations recorded for each cast.
- Click anywhere on the map to deselect the feature.
Filter the layer
Next, you’ll filter the data to show only reliable observations and those that are within 5 meters of the ocean’s surface.
- In the Catalog pane, right-click Temperature_June2022 and click Properties.
- In the Layer Properties window, click the Definition Query tab and click New definition query.
- Click the Select a field menu and choose sea_water_temperature status_flag (Temperature_WODflag).
This field was created as part of a quality control process, and flags observations that are potentially unreliable.
- In the second menu, choose is equal to. In the third menu, type 0.
- Click Add Clause.
- Construct the second clause so it reads And Z is less than 5.
This query will filter the layer to only reliable near-sea surface observations.
- Click Apply and click OK.
The resulting dataset contains only analysis-ready near-surface observations.
Change the layer’s symbology
Next, you’ll symbolize the data on the map to better depict the temperature measurements and look for any spatial patterns.
- In the Contents pane, right-click Temperature_June2022 and click Symbology.
The Symbology pane appears.
- In the Symbology pane, for Primary symbology, choose Unclassed Colors.
This method will apply a range of colors to the points based on a numeric field.
- For Field, choose sea_water_temperature (Temperature).
In the Contents pane, the legend shows that the temperatures range from 25 to 31 degrees Celsius (77 to 88 degrees Fahrenheit).
According to the National Oceanic and Atmospheric Administration (NOAA), sea surface temperatures must be more than 26 degrees Celsius for hurricanes to form. According to this map, there were still some locations in June 2022 where hurricanes might weaken, but for the most part, the Gulf of Mexico was warm enough to support them.
Since all of the observations in your layer are warm, you’ll choose a color scheme with only warm colors.
- In the Symbology pane, for Color scheme, choose Yellow to Red. (Point to color schemes to read their names.)
You’ll make the symbols a little smaller so it’s easier to read the map where they are clustered together.
- In the Symbology pane, click the gray circle next to Template.
- If necessary, click the Properties tab and the Symbol tab.
- Set the Size to 6 pt.
- At the bottom of the pane, ensure Auto Apply is turned on or click the Apply button.
On the map, the red features represent the warmest temperatures and the yellow features represent the coolest.
The coolest temperatures are along the east coast of Florida, outside of the Gulf of Mexico. Otherwise, no clear spatial pattern is visible.
- Close the Symbology pane and the Geoprocessing pane.
Create a chart
So far, you’ve found the gulf waters were sufficiently warm in June 2022 to sustain a hurricane, but the map does not show any clear patterns. This is because you are viewing the entire month’s data at the same time. Sea surface temperature can change daily—it is influenced by the amount of solar radiation, wind, and changing ocean currents. Next, to explore sea surface temperature over time, you’ll create a chart.
- In the Contents pane, right-click Temperature_June2022, point to Create Chart and click Line Chart.
An empty chart view and the Chart Properties pane both appear.
- In the Chart Properties pane, for Date or Number, choose Time (UTC).
- For Aggregation, choose Mean.
- For Numeric field(s), click Select and choose sea_water_temperature (Temperature).
- Click Apply or click outside of the menu.
The chart view populates with a line.
- Check the Smooth line check box. Leave the remaining parameters set to their default values.
The chart shows a steady increase in the mean surface temperature across the Gulf of Mexico in the month of June.
The data from the World Ocean Database can help inform solutions to our climate, ecosystem, and blue economy challenges. In this tutorial, you downloaded observations and mapped them in ArcGIS Pro. You learned how to find and run geoprocessing tools, explore spatial data, filter and export layers, symbolize a map, and create a chart.
This is just the start of how this data can be explored and analyzed. The following are suggestions for what you can try next:
- Explore a different study area. The World Ocean Database is a global dataset. Find an area that interests you or where you know the ocean is facing a challenge.
- Explore a different variable. The World Ocean Database contains many variables. Is coastal development impacting oxygen levels? Are desalination plants impacting ocean salinity?
- Explore the water column. In this tutorial, you used near-surface observations only. In the NetCDF Profiles To Feature Class tool, change the Output Schema parameter to Point 3D. Then use the IDW 3D geoprocessing tool to create voxels of the water column. (This tool requires a Geostatistical Analyst extension license.)
You can find more tutorials in the tutorial gallery.