Jupyter Book
GitHub repo
Regional Cabled Array Learning Site
Ryan Abernathy’s Introduction to Physical Oceanography
Abernathy’s ItPO source repo
Ocean Science#
But I now leave my cetological System standing thus unfinished, even as the great Cathedral of Cologne was left, with the crane still standing upon the top of the uncompleted tower. For small monuments may be finished by their first architects; grand ones, true ones, ever leave the copestone to posterity. God keep me from ever completing anything. This whole book is but a draught—nay, but the draught of a draught. Oh, Time, Strength, Cash, and Patience!
-Herman Melville
Construction note: See nexus on inlining images.
Science basis#
This book explores research ideas in oceanography based upon observational data from sensors. The underlying agenda is to document how, the methods of the exploration.
There is a lot of detail in this method that can overwhelm the science. I take two approaches
to try and keep the primary focus on data interpretation. First the the book is segmented in
two parts. The first half starting with the present chapter includes very minimal technical
detail, focusing on the science narrative using black box methods, primarily Python
code placed in module files like charts.py
. The second half of the book, starting with
the chapter on data
, goes into the technical methods and means.
The second approach to not overwhelming the science is to “farm out” some documentation to the nexus documentation website.
One more remark on contet: This book follows in the footsteps of Ryan Abernathy’s Introduction to Physical Oceanography textbook.
To begin with a task: Characterize the nature and stability of the epipelagic ocean… somewhere.
Epipelagic ocean defined#
Pelagic refers to the ocean water column, surface to sea floor, and the term usually implies some distance away from the shore. Epipelagic is then the upper water column coinciding with the sun illuminated or photic part of the ocean. The most common terms for the upper ocean are ‘epipelagic zone’ and/or ‘photic zone’.
To be specific, the upper 200-or-so meters of the water column is subject to downwelling sunlight. Below that depth very little light penetrates even at noon on a clear day. Sunlight is the energy source of primary production, by which is meant photosynthesis by phytoplankton. Hence epipelagic and photic zones are roughly synonymous for the upper ocean ecosystem, a biological engine powered by sunlight.
need map here
Our observational starting point is three observing sites located in the northeastern Pacific Ocean.
Site name Latitude Longitude Depth (m) D-offshore (km)
----------------- -------- --------- --------- ---------------
Oregon Offshore 44.37 -124.96 577 67
Oregon Slope Base 44.53 -125.39 2910 101
Axial Base 45.83 -129.75 2620 453
Our initial focus is a shallow profiler maintained and by the Regional Cabled Array program at the Oregon Slope Base site. The shallow profiler generates a record of the state of the upper ocean at fine scale both in time and in depth. Once we have a handle on shallow profiler observations we can proceed to add other sensor resources such as ARGO drifters, satellites, and NOAA buoys.
# offhore distances (from Oregon coast) of three shallow profiler sites in the Regional Cabled Array
from math import cos, pi
re=6378.
d_oof = .95648 - .10448
d_osb = 1.38966 - .09422
d_axb = 5.75326 # using shore lon = -124
d2r = pi/180
km_per_rad = (cos(pi/4)*(2*pi*re))/(2*pi)
s_oof = d_oof*d2r*km_per_rad
s_osb = d_osb*d2r*km_per_rad
s_axb = d_axb*d2r*km_per_rad
print('Oregon offshore: ' + str(round(s_oof,0)) + 'km')
print('Oregon slope base: ' + str(round(s_osb,0)) + 'km')
print('Axial base: ' + str(round(s_axb,0)) + 'km')
Oregon offshore: 67.0km
Oregon slope base: 102.0km
Axial base: 453.0km
Interpreting stability.#
We want to consider stability in terms of definite measurable phenomena.
depth: A measurable dimension; of interest on scales of centimeters to tens of meters to kilometers
physical characteristics: temperature, density of water, available light, current, turbulence, opacity
chemistry: salinity, dissolved oxygen, concentration of inorganic carbon
biology: nutrient concentration particularly nitrates, particulate distribution, protein fluorescence
ocean-atmosphere boundary: wind, wave action, episodic events (storms); meters to hundreds of kilometers
time: minutes to days to seasonal to annual to multi-year (climatological)
See note below on thermohaline circulation
large scale perturbation: sea state, upwelling, eddies, terrigenous influence (runoff)
structure and stratification
mixed layer depth, clines
asymptotes in the lower epipelagic
inversion layers, lensing
These observables can often be related to stability through deviation with time. The narrative consequently moves towards two ideas: What is observed? And how frequently?
Thermohaline circulation#
Surface currents in the ocean are driven by prevailing winds. The ocean below the epipelagic, in contrast, is increasingly indifferent to the ocean-atmosphere interface: Wind has less influence. Rather, circulation in the deep ocean is driven by gradients in temperature and salinity (’thermohaline’), the two important factors determining water density. In this regime the important time scale is a range from centuries to millenia. The observational record for the regional cabled array, in contrast, is approaching one decade.
The utility of coincidence and persistence#
Figure: Temperature versus depth (from 200 meters to near surface): Observed by a shallow profiler both ascending (red) and descending (green) directly thereafter. The low temperature excursion feature seen from 65 to 85 meters is persistent between the two observations separated in time by about 30 minutes. From 100 meters down the profile structures are similar but exhibit a relative offset.
Coincidence refers to ocean structure that persists across multiple sensor streams. Persistence refers to structures that persist in time, i.e. for multiple consecutive observations as shown above.
Suppose a smooth data curve concerned with temperature has a noticeable ‘jag’ or anomaly in measurement at a depth of 100 meters. Perhaps this reflects actual water temperature or it may be due to a temporary sensor issue. We can turn to another sensor – say salinity or chlorophyll – and look for a matching anomaly at a comparable depth. If present: We have evidence that the anomaly is in fact due to the water via coincidence.
Continuing onward from this point: Temperature data is collected on both ascent and descent over the course of more than an hour. Seeing the above anomaly in both profiler phases is an example of persistence of a signal of interest. Even stronger evidence: The anomaly appears over the course of multiple profiles (of which there are nine per day).
To take this one step further: We will find that the shallow profiler also measures water velocity as a function of depth. Suppose an anomaly persists for two days and the upper water column has a consistent velocity of 2 kilometers per hour southward. This suggests a water mass 100 kilometers across has drifted past the profiler site; an estimate that could be compared with satellite data, both spectral and sea level anomaly.
How stable is the epipelagic ocean?#
The water column is well understood as stratified. The upper layer is the mixed layer, below that is a transitional layer called the pycnocline, and below this is the lower epipelagic layer. (’Pelagic’ covers the entirety of the open ocean water column.)
Our starting points is a profile: A chart with depth as the vertical axis in meters and observation values on the horizontal axis. Profiles tend to have a consistent shape with occasional anomalies. Repeated profiles comprise a profile time series.
Ocean chemistry#
Let’s motivate a very simple table of atoms and molecules distributed in the ocean. We have on the one hand the physical ocean with tides and currents and sunlight; we have ocean chemistry including pH and salinity (salt concentration); and we have biology: Life in the ocean from plankton to apex predators. These topics are interconnected and the umbrella term invented for all of it – with a particular eye to how carbon is transported and stored – is biogeochemistry. (For a great deal more on the topic visit this ocean carbon and biogeochemistry website.)
The following table is sorted in terms of molecular mass in Daltons. (One Dalton is effectively the mass of a single hydrogen atom.) The last three entries are life-based or organic compounds. Chlorophyll is of particular interest as the central agent in photosynthesis: Absorbing and transferring light energy within a structure called a photosystem.
Mass (Daltons) |
Substance |
Comment on measurement |
---|---|---|
1 |
Hydrogen cation H+ |
pH sensor |
17 |
Hydroxide ion OH- |
-no direct observation- |
18 |
Water H2O |
temperature, salinity, light sensors |
? |
Calcium |
-no direct observation- |
? |
Silica |
-no direct observation- |
46 |
carbon dioxide CO2 |
‘partial pressure’ pCO2 sensor |
62 |
carbonic acid H2CO3 |
by inference |
61 |
bicarbonate anion HCO3- |
by inference |
60 |
carbonate CO32- |
by inference |
62 |
nitrate NO3- |
nitrate sensor |
180 |
glucose C6H12O6 |
-no direct observation- |
240 |
Cystine (amino acid) C6H12N2O4S2 |
-no direct observation- |
894 |
chlorophyll C55H72MgN4O5 |
fluorescence sensor |
Ocean structure#
In addition to chemical composition here are some further attributes of the ocean.
Locations in the ocean are given precisely in terms of latitude and longitude
Informally we discuss location using historical terminology
Example: The Coral and Tasman Seas are regions of the southwestern Pacific Ocean
The ocean is 3700 meters deep on average, covering 70% of the earth’s surface
Coastal ocean water (shelf water) is six times as productive as the deep ocean
The photic zone is the upper 200 meters of the ocean
Consequently 90% of the ocean is in perpetual darkness
Remark on the heat capacity of seawater relative to that of the atmosphere, to land
Water temperature decreases with depth and is fairly constant below the thermocline
Geothermal heat emanates from the earth’s interior: At the sea floor
Ocean spreading centers feature hydrothermal vents
Salinity increases with depth, typically stable below the halocline
Ocean water has the capacity to hold oxygen: A dissolved gas
This holding capacity increases with lower water temperature
Dissolved oxygen is depleted by biological respiration
Carbon dioxide is an atmospheric gas that dissolves in the ocean
Within the ocean: Carbon dioxide is converted to carbonic acid
Carbonic acid in turn dissociates to bicarbonate and hydrogen ions
Collectively this is called carbonate chemistry
Productivity primarily refers to photosynthesis by phytoplankton
Photosynthesis is bounded on the low side by availability of nutrients and sunlight
Photosynthesis is bounded on the high side by saturation (availability of chlorophyll)
Nutrients: Nitrate
Questions on method#
Is shallow profiler data reliably interpretable?
Sensor by sensor: Can 30-day-span mean signals be used to flag anomalies?
Supposing yes: Characterize anomaly signals in three dimensions { sensor, depth, time }
Can the mixed layer depth be measured as a synthetic time series dataset
Microbial ecology and global carbon#
DOM is dissolved organic matter
small organic molecules not functional within organisms
CDOM is an older term for color-DOM (has some spectral signature)
FDOM indicates fluorescent, hence measurable by fluorometry in some degree
metabolites are products of metabolic processes
energy consumption dependent on iron, nitrates, phosphorous; temperature mediation
Carbon pools measured in Gigatons (one billion x one thousand kilograms)
or equivalently in Petagrams of Carbon PgC
Distinct from the mass of greenhouse gases: 44/12 times larger
CO2 has a molecular weight of 44 whereas Carbon usually has an atomic weight of 12
Earth system science considers cycling of matter and energy
Exchange of carbon between reservoirs is expressed in terms of rates of transfer
for exmple PgC per year
Earth carbon pools include ocean, atmosphere, lithosphere, soil, peat, living creatures…
Carbon transfer mechanisms include
primary production
greenhoues gas (GHG) emission by humans
carbon dioxide moving from the atmosphere into the ocean.
GHG transfer to the atmosphere from the lithosphere is about 9 PgC / year
combining fuel burning with land-use changes such as slash-and-burn clearcutting
The ocean biological pump and solubility pump combine
to move about 11 PgC into the ocean’s interior per year
…a few pieces of a more complex picture.
Below I calculate the mass of dissolved organic matter in the ocean
The approximate value is given as 1,000 PgC
The calculation arrives at 645 PgC
Inorganic carbon: Simplest carbon compounds
the ocean-atmosphere interface facilitates dissolving of atmospheric carbon dioxide in the ocean
However carbon dioxide molecules dissolved in the ocean are subject to modification (’carbonate chemistry’)
Atmospheric CO2 has a half-life of 60 years…
whereas dissolved CO2 in the ocean has a half-life of minutes
\(CO_2\) carbon dioxide from the atmosphere, dissolved in the ocean transforms into
\(H_2CO_3\) carbonic acid which dissociates into
\(HCO_3^-\) bicarbonate ions and
\(H^+\) hydrogen ions
which lower the pH of the ocean
historically from 8.15 in 1950 to 8.05 in 2020
Carbon pools#
Ocean 38,000 PgC
Dissolved organic carbon (size 0.22 to 0,70 microns): 1000 PgC
Inorganic carbon (dissolved CO2 and related carbonates): 37,000 PgC
Earth biomass: 600 PgC
Atmosphere: 800 PgC
Soil + peat: 1500 PgC (1000 PgC organic)
Carbon transport#
Marine autotrophs: 50 PgC/a
Terrestrial primary production 50 PgC/a
Lithosphere to atmosphere (human activity) 10 PgC/a
Atmosphere to ocean interior (Biological and Solubility Pumps): 11 PgC/a
Noting that the biological pump operates at about the same scale as the marine carbon pump; and these numbers are about one fifth of marine primary production we can make the case that biological activity is an important component of the global carbon cycle.
Carbon is 1, 1, 4, 50 respectively life, atmosphere, soil, ocean. 1 = 600 Gton.
Where the edge is
System models are vague. For example what drives coastal productivity?
How is decreasing ocean pH impacting ecologies?
What is the data trying to tell us (deluge problem)
What you bring: Imagination, enthusiasm, perseverence
Even as an aware person you can advocate for science education
What you can develop: Math, computing skills (domain context of course!)
Other programs
ARGO
Estuary modeling
Currents and ecosystems
Metagenomics
Caption: Shallow profiler platform (lower half of image) gradually spooling out a winch (bright green cable) permitting the Science Pod to ascend through the upper water column.
Profiler stage times in minutes
Ascent: 67
Descent: 45 (exception: local noon and midnight descents are about an hour longer)
Rest: 45
Ascent data are considered more pristine; although pH and pCO2 are unique in that they are recorded on descent.
A DOC Calculation#
The Ocean Carbon and Biogeochemistry (OCB) organization is concerned with the science of the ocean carbon cycle. This includes carbon in various chemical forms considered as distributed reservoirs. By far the largest of these is dissolved inorganic carbon (DIC) associated with carbonate chemistry. A second important carbon reservoir is Dissolved Organic Carbon, referring to biologically important carbon compounds. The following cell – in part to illustrate Python utility – gives an estimate of the total mass of the ocean’s dissolved organic carbon reservoir. More on DOC can be found at this OCB web resource.
import oceanscience
oceanscience.OceanScienceCalculations()
Mass of earth's oceans: 1.34e+09 GTons
Organic carbon (kg) dissolved per kg of seawater: 4.8e-07
Dissolved organic carbon mass, earth's oceans: 644.6 GTons
Agenda#
Getting our feet wet
Ocean Science (this chapter): Establish a heirarchy of research questions and terminology
Data: Structure, necessity of profile metadata, sensors-to-measurements
Epipelargosy: A sense of the structure of the epipelagic water column
Anomaly and Coincidence: We recognize the ‘normal’ signal so let’s characterize instability
Annotation: An interpretive narrative
Other observation systems
ARGO: A massive drifter program
GLODAP: A compilation of ocean characteristics
MODIS: Satellite remote sensing of sea surface color
ROMS: A circulation model
Bio-optics
Spectrophotometer
PAR and spectral irradiance
Digging in to the stability question
Temperature:
Appendices: Technical background
shallow profiler technical
documentation
issues
Additional themes of GeoSMART#
Workflows
Reproducibility
Troubleshooting