It’s the wee hours of the morning and most of the scientists and ship personnel are fast asleep.  Dr. Peter Gaube and I, however, are nursing our first cups of coffee and helping with the overboard deployment of a sampling package that collects seawater from specific depths and makes continuous measurements of optical properties through the water column.  It’s all part of a NASA Earth Venture Suborbital mission called the North Atlantic Aerosol and Marine Ecosystem Study (NAAMES).  We are part of the seagoing team for NAAMES and currently our research vessel, the Atlantis, is at a sampling station south of Greenland.  The seas get pretty ‘bumpy’ out here.  The other half of the NAAMES team is stationed out of Saint John’s, Newfoundland, and they’ll be joining us later in the day on the NASA C-130 Hercules airplane to make measurements of aerosols, clouds, and marine ecosystems.  But for now it’s just us, bouncing around on the ocean, watching the monitor as data streams up from below, and trying to stay awake.

Figure: Overboard deployment of a Conductivity, Temperature, and Depth (CTD) profiling package with sampling bottles and optical sensors

The density of seawater changes with depth and these changes can make it difficult for water at one depth to be mixed with water below or above it.  However, at the very surface of the ocean, density is essentially uniform with depth and mixes freely.  What this means is that biological, chemical, and optical properties are homogeneous in the upper active mixing layer.  So on this particular morning, we were not surprised when our sampling package showed on its descent a uniform concentration of phytoplankton (i.e., the microscopic photosynthetic cells that support nearly all marine food webs) in this mixed layer.  What surprised us when the package came back up through the layer about an hour later was that a big ‘wedge’ of phytoplankton in the mixed layer had disappeared.  The culprit?  Vertically migrating zooplankton.  Pete had been collecting acoustics measurements from the ship during the overboard deployment and, where the phytoplankton had disappeared, a clear acoustic layer had developed that documented the newly arrived zooplankton.  I had known about these vertical migrations for decades, but never really paid much attention to them (not really my field!).  However, this first-hand experience of their impact caught my attention.  “Hmmm, something to keep in mind”, I thought.

Fast forward a year.

Big science conferences have never been my forté, but they do present a chance to catch-up with colleague, soak up some new science, and meet new scientists.  Ocean Sciences is one of the larger meetings for biological oceanographers and at this particular meeting a young scientist I had recently been working with, Dr. William Burt, found me and asked if I’d have a moment to look at his poster.  “With pleasure, of course, Will.”  What Will showed me from a recent field campaign in the subarctic Pacific was a high temporal resolution record of an optical property called the ‘particulate backscatter coefficient’ or ‘bbp’.  The intensity of optical backscatter varies with the number of particles suspended in the water and specific properties of those particles.  Accordingly, measurements of bbp have been used to quantify phytoplankton carbon biomass and the biomass of total particulates in the water.  However, what Will had found in his field data from the surface mixed layer was that there was a very clear difference between bbp measured during the day and bbp measured at night.  Specifically, the nighttime data was punctuated by bright spikes in backscatter that were entirely absent during the day.  These spikes correspond to those vertically migrating zooplankton that we observed during NAAMES.  Compared to phytoplankton, migrating zooplankton are very rare, but whenever one of these individuals passes in front of the measurement window of a field bbp sensor it ‘lights up’.  The other thing that ‘lit up’ when I saw Will’s poster was an idea on how I could link these migrators to something we can measure from space.

Figure:Example of the day-night changes in bbp observed by Dr. William Burt during a field campaign in the subarctic Pacific showing the nighttime appearance of large spikes from DVM animals.

Now let’s take a step back.  Who are these migrators and why are they important?

Every night across the global ocean, untold numbers of small marine animals (zooplankton) migrate from depth to the ocean’s surface to feed upon the day’s plankton production.  And when these small animals migrate, their predators follow (e.g., larger crustaceans, squid, and fish).  For some of these animals, the daily migration may be hundreds of meters through the water column, which is a really long distance for a small animal.  But all the effort is well worth it. The reason for the migration is that it is safer to spend the day in the darker reaches of the ocean where visual predators are less effective.  The problem with the deep sea, though, is that there really isn’t much food down there.  Most of the food is nearer the surface, so the animals move up at sunset and then hide again at sunrise.  This remarkable daily phenomenon is referred to as Diel Vertical Migration (DVM) and, numerically, it is the largest animal migration on Earth.  Oceanographers have known about the DVM for nearly 200 years, but its significance is only now becoming fully appreciated. 

Figure: Copepods are only one of a huge assortment of different animal types that ascend to the ocean’s surface at night.

The fact is that the deep sea could not support nearly the animal biomass it does if it relied solely on the slow sinking of organic matter from the surface.  As this material sinks, it is rapidly degraded by near-surface animals and bacteria, causing food availability to decrease exponentially with depth.  But DVM animals change all of this.  Consuming surface biomass by night and retiring to the ‘deep dark’ by day effectively creates a biological conveyor belt that greatly enhances the sustainable biomass of resident animals of the deep sea.  It also creates an efficient pathway for moving photosynthetically-captured carbon dioxide from the surface to the longer-term carbon storage pools at depth.  Because of these important ecological and biogeochemical functions, scientists have recently been incorporating DVM parameterizations in global ocean ecosystem models.  The problem is how to validate the models.  Research ships cost tens of thousands of dollars a day to operate, they are slow, and they are few in number.  Despite making acoustic measurements of DVMs for decades, ship-based measurements simply cannot provide the spatial and temporal data coverage needed as input to global models.  Here is where satellite observations really ‘shine’.  The question is, “how can we measure the DVM from space?”

Marine animals from space

Satellites have been globally monitoring ocean ecosystems from space for decades using a technique called ‘passive ocean color’.  In essence, this approach measures the spectral intensity of sunlight reflected from within the ocean and transmitted back to space.  This reflected light carries the signature ocean plankton because the abundance of these organisms increases the intensity of backscattered light and because the pigments inside the cells change the color of the ocean color signal compared to the color of pure seawater.  Mathematical algorithms have been developed over time that can now be applied to satellite ocean color data to quantitatively retrieve the backscattering coefficient, bbp – which is the property I mentioned above that can register DVM animals.  The problem is that ocean color measurements are only collected during the day and the DVM animals show up in the ocean surface at night.  To observe the DVM signal, we needed satellite measurements both day and night and this required new technology.  To put a fine point on it, we needed an ‘active satellite sensor’.

In 2013, my colleagues and I published the first global maps of plankton biomass using an active satellite lidar (which stands for ‘light detection and ranging).  The data were from an instrument called CALIOP, which was designed for measuring cloud and aerosol properties in the atmosphere.  What we showed in that first paper was that it also provided a signal from the first 20 meters in the ocean.  In 2017, we published another CALIOP-based study where the lidar data were used to study decadal changes in polar plankton population.  As this paper came out while NAAMES was underway, lidar were naturally on my mind when I was trying to figure out how to detect DVMs from space.  The pieces fell in place: DVM animals impact nighttime bbp and the lidar measures bbp globally during the day and the night.  However, the actual quantification of the DVM signal was not as simple as just calculating the difference between CALIOP day and night bbp data because phytoplankton also have a diel cycle in bbp.  To tackle this problem, we first parameterized a model of the phytoplankton cycle based on laboratory measurement and satellite-derived estimates of phytoplankton growth rates (which influence the magnitude of the diel cycle) and then applied the model solutions to CALIOP’s global day-night bbp difference data.  The outcome was the first satellite-observed global data set on the ocean DVM.  The results showed that the relative strength of the DVM signal is greatest in the clearest ocean regions (which makes sense because in these areas visual predators have a particular advantage), while the absolute strength of the signal was greatest in more productive ocean regions (which also makes sense because food availability is greater here).  The decade-long CALIOP record also allowed us to evaluate how the DVM signals are changing over time and what we found is that in some region temporal changes correlate with parallel changes in phytoplankton productivity, while in other regions these two properties are inversely correlated.

Figure: CALIOP has provided the first global observations of ocean ecosystems from a space-based lidar

Our new publication on the ocean’s DVM represents a first step.  There is still much to do.  A standard practice in satellite oceanography is to validate retrieved geophysical variables with highest quality field data available.  For our DVM paper, we did this using historical ship acoustics data and field zooplankton net collections.  While our analysis demonstrated agreement two data sets, the field data are sparse and, more often than not, predated CALIOP, so additional validation efforts are needed in the future.  In addition, there were some regions where the field data and CALIOP data disagreed and we still do not understand why trends in the DVM covaries with phytoplankton productivity in some regions and not in others.  Finally, CALIOP has now provided for multiple lines of inquiry a proof-of-concept demonstration of the rich information on ocean ecosystems that can be gained from a satellite lidar, but it’s technology was not designed for such applications.  Advanced High Spectral Resolution Lidar (HSRL) instruments have now been extensively shown from aircraft platforms to provide more accurate and information-rich data on ecosystems properties and at meter-scale resolution through the water column.  It is time to think about how such new technology can be implemented as a future ocean-focused satellite mission.