The need in oceanography for direct broadcast, why, and what type are discussed. Four reasons for support exist: need for real-time observations in support of field studies; need to back up point failures; need for experimentation with onboard processing and selection of data for direct broadcasting; and the need to develop future operational NOAA systems. Each of these areas is examined

Esaias, W. E.

English

NASA Technical Reports Server

 90-27156
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APPLICATIONS OF ISES FOR THE OCEANS*
W. E. Esaias
NASA Goddard Space Flight Center
Greenbelt, MD
I will discuss my interests in oceanography and acquaint you with how some oceanographers feel
concerning the need for direct broadcast, why, and what type.
I am particularly interested in the role of the ocean in carbon storage in sequestering. Through fos-
sil fuel burning, approximately 5 to 6 gigatons of carbon are emitted into the atmosphere each year. Half
of that amount stays in the atmosphere, and it is thought that about half of the remaining carbon goes
into the oceans. The ocean biota represent a small pool, but they overturn very rapidly. In fact, this
very small pool of carbon represents a mechanism that has sequestered over geological time 99.99 per-
cent of the carbon on Earth. If you have read any of the Earth Observing System (Eos) literature, you
have seen a figure of the carbon cycle. Most of the carbon reservoir is in sediments of marine origin, and
our main interest is the ocean phytoplankton that is typically studied through ocean color. Phytoplank-
ton represent a small biomass, but through eons of fixing carbon particles and sinking in the deep ocean,
most of the carbon on Earth has ended up in marine sediments. Although the annual input is very large
because of such processes as dissolution of carbon and deep water formation, the signal that represents
this deep carbon storage is very small. We are looking at a very small signal difference between very
large signals. To determine this difference really requires time series and comprehensive observation, as
well as a great deal of in situ work understanding these processes; this entails ships out in the ocean and
moored instruments. Many magnifiers of global processes exist, such as enhanced production in deep
ocean due to aerosols (i.e., continental aerosols, Asian dust, and Saharan dust, which has a lot of iron).
These magnifiers fulfill some nutrient limitations. A particular species or a group of species of phyto-
plankton called coccolithophores produce dimethyl sulfide, and it is thought this parameter might play
a role in cloud formation. Due to eutrophication of estuaries and rivers, we are seeing enhanced produc-
tion in coastal regions, which again affects or magnifies anthropogenic effects and carbon cycling. This
observation is especially interesting because ocean colors are flow visualizers and signify mixing changes.
We have been processing Coastal Zone Color Scanner (CZCS) data and were able to generate a
composite representation of 32 months of observations. We can see upwelling at the equatorial region,
high productivity in the Northern latitudes, large production in the Southern oceans due to mixing,
upwelling along the coasts of Africa, Peru, and the Western U.S., Amazon river outflows, and monsoonal
areas. This composite basically represents the general picture that we had before satellite data. Things
become interesting when we look at interannual variability. By transforming data like these, we can
estimate the total zonal production and howmuch carbon is fixed (as a function of latitude). From
this we calculate how much carbon is going into the ocean biomass, with time. The data set contains
32 months of data beginning when Nimbus 7 was launched; from this we can estimate a total carbon fix
per day, which is equivalent to approximately 60 gigatons of carbon per year. The anthropogenic output
is one-tenth of that amount. If one-tenth of this gets fixed by phytoplankton and ends up in the deep
ocean, then all the fossil fuel CO 2 is used up and there is nothing to worry about. But it is unlikely that
the number is that high; it is probably closer to 1 percent. Notice that there is a hint of a secular trend.
What we measure with the satellite is radiance in four spectral bands, and from that we look at
color shift in an empirical relationship between the water-leaving radiance and the amount of chlorophyll
pigment. Chlorophyll pigment is used as a measure of biomass. It is also the primary photosynthetic
pigment, and these chlorophyll concentrations are a good indication of how fast the plants are growing.
Plants in the ocean are not like plants on land. If you look at plants in the forest, you see only carbon
trunks. The carbon stays around for a long time. But, the plants in the ocean are unicellular; they have
no support structure. They divide once a day so the biomass is a good measure of how strong they are
*Paper taken from workshop recordings.
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https://ntrs.nasa.gov/search.jsp?R=19900017840 2020-03-19T21:15:22+00:00Z
growing.If theyarenot growing,they aresinkingto the bottomor theyarebeingeaten.Thereis a very
simplerelationshipthereforebetweenthe chlorophyllconcentrationandthe total carbonfix.
Wecanseetrends,andfor thefirst time, wecanlookat interannualvariability. For example,we
seethe differencein CZCSdatabetweenwinterandspring. In springyougetmoresunlight,plants
growfaster,the watercolumnstabilizes,and the nutrients are fixed. Between winter and spring there
is a tremendous increase in biomass and phytoplankton in the ocean, and a substantial fraction of:that
will sink in the deep ocean, be removed from contact with the atmosphere, and represent a short-term
repository for carbon. One-tenth to one percent will get incorporated into the sediments and then
enter a pool that is on a geological time scale. It is apparent from 1979 data that there is a spring
bloom and a fall bloom (we see a much smaller spring bloom in 1980, a much larger fall bloom in 1981,
and a spring bloom in 1981). This delineates some of the interannual variability that we see, which
represents anthropogenic carbon input. So the variability in the ocean is large with respect to how much
anthropogenic carbon is going in. The southern oceans receive outflow froth-rivers, where the windsare
more constant and show very little interannual variability. The name of the game is how variable is the
ocean, and for the first time, with satellite data sets, we can look at interannual variability. We have
never been able to do that on these scales before from ship data.
In summary, our ocean estimate is 61 gigatons of carbon; compare that to 6 gigatons of carbon
output by fossil fuel. The new production, which is the production that is due to nutrients coming up
from underneath the ocean due to upwelling, is approximately 23 gigatons. We would expect that an
equivalent amount of carbon gets sunk with residence times on the order of decades to centuries, and
if 10 percent of that gets buried, then we have essentially solved the missing cartoon problem, i don't
believe any of the carbon budgets, but understanding the process of what you see in the Satellite image
and relating it to what happens to the carbon inside the ocean are the subjects of a major international
effort called the Global Ocean Flux Program. Currently, there are field pilot studies occupying a transect
from Iceland down past the Azores. If you understand the onset of the spring bloom and how much
carbon goes deep into the ocean, you understand that the winter nitrate concentration is the primary
limiting nutrient of phytoplankton production. Another issue is how deep the water mixes, because this
is a prime forcing function. We are interested in wind stress and mixed layer calculations and running
physical models in order to set up a physical regime with which to determine the biology. To give you
an idea of the scale of this, consider the area that is occupied by this field experiment. The bloom starts
first in the south. The U.S. was there in April, and now as time goes on, the bloom progresses north so
the activity shifts toward the north. The Germans are there, our P3 aircraft is there, along with one
Canadian vessel and the British who come and go. A Netherlands ship was also involved. My point is
that this occupies a very large area of the world, and right now we have no way of determining what
is happening on a regional basis. To look at some of the historical data, we need to kilow where to put
stations. These stations were chosen because they were close to the European support and because :they
had past moorings there. One might move those stations if real-time information were available.
Since I was first asked to consider direct broadcasting, we have had follow-on studies for oce_
color sensors to look at, some of which include direct broadcast and some not. i Can see four reasons
for support. 1) We need to back up single point failures, such as the Tracking and Data_elay Satellite
(TDRSS), EosDIS, and a central data handling facility. 2) Obviously, we need real-time observations in
support of field studies. The ocean does not stay fixed, and the name of the game is to get a ship to one
of the bloom areas or plumes. We need data within a day. It is not obvious that the EosDIS will be able
to deliver that. 3) We would like to experiment with onboard processing and selection of data for direct
broadcast. 4) We need to develop future operational NOAA systems.
i'm concerned about all these areas. It seems we have a choice of three data rates. High data rate,
X-band (I call high data rate anything above 20 megabits per second) will require a large ground station
(there are going to be a few of them), lots of dollars, and some screening of data, b_canse you still
can't handle all of Eos and therefore must select which data and what day you put it out. it is going to
require on-site processing at the ground station, and this will be a major effort. You still have a problem
of how to get it out to the ships at sea. Oceanographic Principal Investigators (PI's) tend to go to
sea: they take their act with them. For medium data rate (such as the L-band for the High'Resolution
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Picture Transmission (HRPT) or S-band), there are lots of ground stations. Screening or selection of
data (that is, which bands from which sensors) is needed. Many of these HRPT stations are within the
PI domain, but you still have the problem of distribution to the field sites. There is also low data rate, in
which you experiment with onboard data processing and produce a geophysical product.
There are potentially a large number of ground stations, and it is very foreseeable to have a station
on every major or even minor oceanographic research ship with a PC to do processing. It really requires
a selection of data. Which data do you send? For the most part, the PI would rather have the raw
data, not a geophysical unit. The field party gets the data directly (that is, there are no problems in up-
linking again to a satellite to get it out to a ship).
Concern about research for operational use is based on my own point of view, which is mostly
for research needs. Does a scientist have a VAX or access to a supercomputer or does he just want
information to show where to take a dory? We have considered the high- and low-data rate reception
capability, but we should not forget the regional "value added" processing and routing. I mention this
because commercially there is a great deal of interest in fisheries' broadcasting, in which a number of
businesses have been set up to take ocean color and sea surface temperature data, process it (based on
their previous knowledge of ocean conditions and topography), and forecast where the mackerel, squid, oJ
other fish will be. That procedure requires that you get data to the fisheries and that they distribute a
product to the ultimate user.
Another topic is cruise activity and planing for algorithm development. We hope to have more
sophisticated algorithms making use of the multi-bands than were possible with CZCS. When you are
at sea trying to validate a model, it is nice to know what the ocean is doing rather than use pigment as
a predictor of some other species or pollution event and make your correlative measurements. It is nice
to have that data in hand to find where the hot spot is. A hot spot in a general pigment measurement
is not necessarily the hot spot of a coccolithophore bloom; they have different spectral signatures. This
area is intended for tailored algorithm development and validation studies. The instrument scientists
have a real need to get the data down to look at it to find out if their sensor is working right, i.e., sensor
performance.
We use an ozone product to atmospherically correct our data in the final processing. Currently
we have the Total Ozone Measurement Satellite (TOMS) data because we are doing it retrospectively
now. With TOMS, we get approximately a 25-percent improvement in the results. With the present
scenario we are going to have to wait approximately 5 days in order to get an ozone product unless it
is from MODIS itself. You can read in wind speed because there will be glint corrections. The point
is, there is a need for ancillary data. If it were possible to get that data on the ground quickly, to a
first approximation (even though the people studying the ozone might not be satisfied, it could be a
preliminary product for them), then all we need is a 90-percent-accurate ozone number to form a crude
correction because it doesn't affect the CZCS data by more than one-third count. You will never see
it using a correction term. I think there are other analogies in which quick data could be very useful in
routine data processing.
Concerning timeliness, for research cruise planning, approximately a 12-hour response will be
needed to be useful. The ocean community has been over this time and time again with no justifying
need for real-time data distribution, and they have settled on 12 hours as a satisfactory number. We
would like it sooner, but 12 hours is enough time to set up next day activities on the vessel.
It is certainly possible to consider doing the sea surface temperature (SST) processing onboard the
satellite even though that method would have pluses and minuses. Currently it is done in a hands-off
mode; it takes a bit of "number crunching," approximately 2 minutes on a micro-VAX 3 size instrument.
Doing the CZCS pigment type algorithm onboard Eos might be feasible. It is not trivial; it takes on the
order of 20 minutes on a micro-VAX 2 to process a 2-minute scene. It is an intensive task even with
nearly optimized code. You have to know the ephemeris, calculate the Sun sensor geometry, store large
look-up tables for the Rayleigh correction, make some assumptions concerning an ozone field, use a red
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colorpixel to estimateaerosols and assume a default aerosol type, and use one of the channels to identify
clouds, land, and glint.
One scene is approximately one-fourth of a megabit. The look-up tables for the atmosphere cor-
rection, where you have already solved the multi-scatter radiative transfer model, are typically done on
every 32 pixels. You then interpolate within the look-up table. All of the data we have generated was
essentially done in a hands-off mode. A number of us looked at the output to determine if it worked or
didn't, and threw out what didn't work. It is not interactive in the sense that we are refining a coeffi-
cient. We know there are errors when you change from a marine to a continental aerosol model around
Africa. Some of the errors can be estimated, and that is what we do. We don't have the information
within the CZCS to make decisions as to what their corrections should be; therefore, MODIS final prod-
ucts certainly would be much better for quick results. People who are in favor of onboard processes
would be delighted with something like that.
What I'm suggesting is that the way we process CZCS data today requires none of those correc-
tions. There will be an ozone channel on MODIS. As for the research algorithms that people expect to
have developed and ready to do MODIS ocean color, they are at the same stage that ISES is right now.
We must answer these questions: what can we correct for, where do we get the data, and how do we
code an algorithm? I think it is unrealistic to expect to come up with a consensus in time to help with
the present algorithms and processing methodology that can be done. It's going to take a good deal of
onboard storage and encoding software. There is no way that I would recommend that you get into the
next-generation algorithm development for onboard processing. There are applications that haven't even
used real-time wind speeds to do a good glint correction, for example. Atmospheric pressure is needed to
recompute and solve the Rayleigh scattering model on a regional basis each time, because with the ex-
pected precision of MODIS, which we presently just ignore with CZCS, the atmospheric effect will be
very evident in the research data product. Even the sea surface temperature, the multi-channel SST
that NOAA does routinely, is not perfect. Many people find it has problems, but it is extremely useful
for fishermen or setting up regional field studies. If it were available in real-time over a simple data link,
that would be good. To me, one of the real challenges would be to control the selection of data from the
various instrument types and output that through several channels of the HRPT.
out a product of known performance. People are used to it and it is available in real-time. You don't
have to go through Goddard and wait 3 days. You don't have to wait for the NOAA satellite. Suppose
the NOAA satellite fails, we still have the data.
I see a couple of ways to handle the process for chlorophyll. You Could have the ability to select
MODIS visible channels. You could select up to 8 or 10 Channe]sl maybe have a switch to select........... which
ones are useful for oceanographers and land scientists, put them into a HRPT format, and direct broad-
cast to any current NOAA HRPT station. The Navy and universities will then have that data. It won't
be all the data they will ultimately want, but it will be enough to tell them what to do tomorrow.
one 0fthe main problems I see is that you stiii have to do onboard selection to choose what:data
to put into the data stream unit; you may be sending down the wrong data. Who gets to decide what
and when would be a key issue. If I'm planning an experiment, how much lead time will I have to get
a commitment from NASA that my data will be there when needed? It would not be good if I planned
a multi-national effort and found that SAR data was scheduled to be taken that week; that does me
no good at all. So the important thing is who controls the sensor outputs. If we have several selectable
channels, such as an ocean channel, a land channel, a vegetation channel, a desert channel, and an
atmospheric channel, which could be relied on, then it would make planning for field efforts much easier.
The SST is a lot simpler than ocean color because it is just a simple difference or ratio between
two channels; you multiply it by some coefficient_ _0 get approximately a degree and 0he-half accuracy.
The atmospheric correction is extremely simple. You don't require people to use look-up tables or make -
extensive calculations. It can be done with a microprocessor by using a couple of channels and putting
In conclusion, it would certainly be desirable to have a direct broadcast capability to support
research ships at sea, as well as other activities. The format may include a selected number of raw
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datachannelsfrom someof the instruments, or it may contain fully processed geophysical parameters.
The selection would be dependent upon the application, however, and a guarantee of availability when
needed would be essential. Because the algorithm development for the MODIS data products is still an
active issue, it is perhaps too early to state exactly what real-time products are needed and what mix of
onboard and ground data processing is desirable.
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Applications of ISES for the oceans

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