Lab 2: Cell thermal mass#
Aim: To gain an understanding of how a sensor’s sampling approach can affect the measurement.
Learning outcomes: After the session, you will be able to explain the cell thermal mass effect and how it may affect salinity measurements in the ocean, depending on temperature gradients and sampling strategy.
Background: The typical instruments that we use to measure salinity in the ocean are based on a conductivity cell design, where seawater flows past a thermistor (temperature sensor) and into the conductivity cell (roughly 11 cm long and 1 cm diameter) where the conductivity is measured. Conductivity depends more strongly on temperature than it does on salinity, so in order to calculate the salinity of the water, the temperature effect must first be removed.
Two temperature effects are corrected for using standard processing:
timing offset between when a parcel of water passes the thermistor and when it is in the conductivity cell, and
a heating or cooling effect by the conductivity cell on the parcel of water that is being measured.
Without these corrections, artefacts may appear in the derived salinity profile. These appear as e.g. ‘salinity spikes’ where salinity can spike negative or positive around a large temperature gradient, and offsets in T-S space between downcasts and upcasts. In this experiment, you will create an extreme example of a cell thermal mass anomaly by dipping a microCAT (SBE37) in a bucket of ice wa- ter for a specified amount of time, and then dipping it in a bucket of saltwater with specified salinity.
Design an experiment#
Come up with a hypothesis and experimental design for the cell thermal mass effect on measurements of salinity. An experimental design should have: a testable hypothesis, a detailed methodology/procedure that someone else could follow (i.e., could repeat and ideally get the same results that you have), identified independent and dependent variables, and a plan for a data table or figure to demonstrate your results and based on which the results could be analysed to test the hypothesis.
In plain language, what are you testing and what do you expect to see? In other words, why are we carrying out this test?
Come up with a couple sample hypotheses to design an experiment around.
What are your possible independent variables? Recall, your independent variable is the cause. Its value is independent of the other variables in your study (you can control it).
What is your dependent variable? The dependent variable is the effect. Its value depends on changes in the independent variable.
Get to know your instrumentation
Check out your CTD. What are the stated valid ranges for temperature?
What are the stated valid ranges for salinity? Make sure that in your experimental design, you do not violate the manufacturers stated valid ranges.
What is your information source?
How quickly can the instrument sample?
Will the instrument be damaged if it is set up to sample in air?
Outline the methodology
How will you set up the experiment, in broad terms. What water temperatures will you use? What salinities? How and when will you set up your sampling device (CTD) and in what order, and for how long, will you put it in a bucket of water with specified properties?
Calculation: For your chosen salinities, how will you make the water? How much water and how much salt?
What are the materials required for your experiment? You have access to water, salt, ice, buckets, a CTD and necessary software. If you have more requirements, check with instructors.
Revise and finalise
Go back and check your hypothesis. Did you use words like “influence” or “impact” or “affect”? These are not acceptable. You need to make a hypothesis about what you expect to see. Your hypothesis should describe the effect you expect to see, and indicate the sign of the effect that is anticipated.
Based on your revised hypothesis, revise your experiment design. You want an experiment that is as simple as possible but still capable of testing your hypothesis. Make notes about how to simplify it.
Double check the instrument manual. Make notes for the instructions to include on how to set up the instrument for sampling, as well as how to make measurements and download data. Assume the users are students at a gymnasium with a fair degree of common sense but no experience handling oceanographic measurements. They will only do what you tell them to do. If you don’t warn them about not sampling in air, they may leave the device sampling on a table. If you tell them swap from one bucket to another, tell them how long the swap should take.
Design the results table/figure. Based on your planned experiment, what form will the results take? Is it a table of discrete values? Is it a graph or a time series plot?
Sketch an example of a results figure, graph or plot that will allow someone looking at the figure to say ’yes’ or ’no’ to the hypothesis. Is there any further information that could or should be determined from the figure?
Should the experiment be repeated multiple times, or is one time through sufficient? (What about user error?)