In the first of several series I hope to start on this blog, let start off with our first installment of Better Know a Dataset. Given that New Jersey is currently in the midst of a sweltering heat wave (record highs around 103 °F were set it many places today), it seems only appropriate that we should start with temperature.
Sea Surface Temperature, or SST for short, is the most common ocean data measurement you will run across. Temperature is the easiest variable to measure in the ocean (and anywhere else for that matter), and as a result you can easily find oodles of temperature data online, often spanning back several decades.
Surface actually is a relative term, as it depends on how the temperature is measured. Surface buoys typically include a temperature probe underneath the surface, about 3 feet down. This insures the temperature measurement reflects the water temperature only, and does not bob in and out of the water.
But perhaps the most popular SST datasets are those measured from satellites, like the AVHRR sensors on NOAA’s POES satellites. The advantage of satellite SST data is that it can map out entire regions of the ocean’s surface, rather than just one point. The disadvantages are that satellites may not pass over a region every day, they have a lower spatial resolution (typically 1km^2) whereas a buoy can measures small scale changes in temperature, and if clouds are present most satellite sensors can not see through them.
Satellites are able to record the temperature of the ocean’s surface by measuring the emitted infrared radiation from the ocean. In theory, this measurement is from the top few micrometers of the surface. In actual practice, given that the ocean is a very dynamic place with a lot of wind, waves and mixing, the top few micrometers are often essentially the same as the top few feet or more. However, on a calm sunny day the skin temperature may be several degrees higher than the true surface layer. In oceanography, nothing is ever easy.
The image above, from the Rutgers Coastal Ocean Observation Lab, is a quintessential example of a SST image. It shows snapshot of sea surface temperature that was recorded by the satellite NOAA-15 as it flew over the Mid Atlantic earlier today. The white area on the left is the East Coast of the United States. You can see Cape Cod near the top right and Cape Hatteras in the bottom left. The recognizable coastlines of New Jersey, Long Island and the Chesapeake Bay are also clearly visible.
The temperature data in this image is colored using the typical scientist’s palette, that is, the color scaling uses the full rainbow of colors to show a full range in temperatures. While this is not a very intuitive color scale (a topic we’ll delve into in future posts), it is one that is commonly used by scientists to extract as much detail from the data as possible.
Red and orange areas depict the warmest areas while blue and purple areas are the coolest. Many web sites use a static color map throughout the year. However, due to the extreme range in ocean temperatures over the course of a year in the Mid-Atlantic and the desire of scientists, fisherman and others, to be able to extract all the features possible out of these images, Rutgers constantly changes the scales on their color map to keep up with the changing temperatures. This means you need to constantly check the color scale, as red areas on one image may not be the same temperature as red areas on another image.
There are several notable features in this image.
- The white and purple patchy areas on the right are actually clouds that are obscuring the ocean surface and somewhat corrupting the data. (Scientists would flag this data as questionable and not use it in their research.)
- The red ribbon of warm water toward the bottom of the image is the Gulf Stream.
- Above the Gulf Stream and in the midst of the clouds, you can see a warm core eddy, that shows up as a red circle. This eddy was originally part of the Gulf Stream before it split off and started heading back towards the coast. The eddy itself rotates in a clockwise direction.
- Off the coasts of Delaware, New Jersey and Long Island the temperatures are somewhat cooler than further offshore. This is due to coastal upwelling. Over the past week, winds in the area have been from the Southwest, which when combined with the forcing from the Earth’s rotation, drives surface waters offshore and allows cooler waters to come to the surface. Upwelling also brings nutrient-laden bottom waters to the sunny surface where phytoplankton can have a feeding frenzy.
As you can see, sea surface temperature maps provide a rich dataset to analyze ocean currents and features that impact the biology and chemistry in the ocean.
Of course, they can also help you find a cool beach on a hot day.
Sage, this is a well written introduction about SST. I want to point out a couple things for those who wants to explore SST images of the Mid-Atlantic region further. SST in the ocean can vary on the different time scales. It is an informative exercise to compare the SST for the same region of the ocean at different times of the day and different times of the year. For the students, can you figure out what meteorological and oceanographic processes can cause the observed differences in SST?
Thanks Donglai for the suggesting a great exercise. I’m always amazed by the dynamic range of temperature we observe in the Mid Atlantic, both spatially and temporally. There is certainly a lot to explore, and plenty of challenges in interpreting and also visualizing the data.