Use pH with depth data to determine if there are relationships over time across different regions of the ocean.
Make a prediction about what kind of changes or patterns in pH with depth you may observe between two different parts of the ocean.
Compare patterns in the data below to determine what and if there are relationships over time and/or space.
When the site loads, you are able to see pH data data from all of January 2016 from the Coastal Endurance (Oregon Offshore) and Cabled (Oregon Shallow Slope) Arrays both off of Oregon. You can interact with the data by:
Selecting a different amount of time to look at by choosing between, "1 week," "2 weeks," or "1 month."
Selecting a different part of the year to explore the data in ways that interest you by moving the highlighted section of the bottom graph to the right or left.
Zooming in and out of the data to look at different time scales that interest you by changing the width of the highlighted section of the bottom graph to be more or less than a month.
As a note, the color denotes the time of year the pH data are from (light purple/pink are from January through blue/dark purple from December).
Questions for Thought
Across what time periods are you able to observe pH data in these graphs?
What is the first month and year there are data for each graph?
What is the last month and year there are data for each graph?
What is the overall range of pH data you are able to observe in these graph?
What similarities and differences did you find in patterns of pH with depth over time between Coastal Offshore and Shallow Slope locations in temperate North Pacific Ocean locations?
What other questions do you have about variations in patterns of pH with depth over time and space from these data?
Click on the images below to learn more about where and how the dataset above was collected.
The data for this activity was obtained from the following profiling pH instruments:
The above datasets were downloaded from the OOI data portal. Complete profiles of the instrument were identified and the profile closest to midnight (GMT) each day was saved. This reduced the overall temporal resolution (and size) of the final dataset but it preserved the raw variability exhibited in individual profiles and measurements.