Please find the first annoucement of the Science Workshop of the project, which will be held at IFREMER (Brest) at the end of the project.
Tuesday, May 22, 2012
Final workshop announcement
Please find the first annoucement of the Science Workshop of the project, which will be held at IFREMER (Brest) at the end of the project.
Monday, May 14, 2012
The NOC team have finished quality controlling the next set of
open ocean whitecapping (wavebreaking) in-situ measurements. These data will be
used within OceanFlux GHG to help validate the model and Earth Observation
derived estimates of whitecapping.
The figure shows the percentage Whitecap coverage (W) versus wind speed (U10n) standardized to a height of 10 meters above the sea surface and neutral atmospheric stability. The red circles show W averaged as a function of wind speed and the dashed
line
shows an older empirical relationship (Monahan and Muircheataigh, 1980). All
of
these in situ data have been collected using digital camera systems mounted on a
number of different research ships.
Measurements were collected during the following projects:
Deep Ocean Gas Exchange Experiment (DOGEE)
High Wind Air-Sea Exchanges (HiWASE)
Sea Spray, Gas Fluxes and Whitecaps (SEASAW)
Waves, Aerosols and Gas Exchange Study (WAGES)
Tuesday, May 8, 2012
whitecapping in situ data quality control processing underway
Monday, May 7, 2012
From surf to satellite
Oceanic whitecaps play a role in the
uptake of carbon dioxide from the atmosphere, and hence in the
Earth’s carbon cycle. Lonneke Goddijn-Murphy writes about
monitoring their coverage on a global scale.
As a keen surfer I like to see
whitewater, the white foam on the sea surface. From my desk at the
Environmental Research Institute (ERI) in Thurso I can keep an eye on
Dunnet Head, the most northerly tip of mainland Scotland, and the
presence of whitewater where the cliffs meet the ocean is a good
indicator for the possibility of a surf session later. As one can
imagine, observing whitecaps from space is a more challenging
business. But why would we want to use space technology to view
whitecaps (other than for chasing surfing waves around the globe)?
My post-doc at the ERI is part of
NCEO’s global carbon cycle research. It is well known that burning
fossil fuels releases atmospheric carbon dioxide (CO2), a
greenhouse gas, and that planting trees helps remove CO2
from the atmosphere. It might be less well-known that the oceans play
an important role in the carbon cycle as well. The sea surface can
emit or absorb CO2 gas depending on the region and
conditions, but on the whole the world’s oceans take up more CO2
than they produce. Here at the ERI we study the physical controls on
air-sea gas exchange, an area of expertise for Senior Research
Fellow, David Woolf. This includes whitecaps because they enhance the
absorption of CO2. We are interested in whitecap
observations from satellites because, if we want to compute total CO2
fluxes, we need long term data on a global scale.
Whitecaps play an important role in
various other physical processes, for example whitecaps are highly
reflective, providing a cooling influence on the Earth’s climate.
Whitecaps can also affect the colour of the sea surface, so that
whitecap removal algorithms need to be applied to the remote sensing
of ocean colour. A better understanding of whitecapping is avidly
sought after by wave modellers, because whitecaps relate to energy
dissipation of waves, the least known process of wave evolution.
Whitecaps are presently used as a ‘tuning knob’ of any wave
model, but what exactly are whitecaps made of ?
Whitecaps essentially consist of
bubbles and foam, a product of breaking waves that generate
turbulence and capture air at the sea surface. A common
quantification of whitecaps is the fractional area coverage by
whitecaps, W. Although whitecaps are known to distort remote
sensing observations, it has appeared to be difficult to monitor W
from satellites. A way around is to parameterize W using more
assessable parameters. Because whitecaps are mainly wind driven and
wind speed data are common in Earth Observation (EO), most W
parameterizations are a function of wind speed. Unfortunately, the
uncertainties in wind speed parameterizations are too big. This may
not be surprising, as one can imagine many factors other than wind
speed that affect whitecapping, such as wave height, the stage of
wave development, the length of time the wind has been blowing and
the interaction between waves. A range of different W
parameterizations that take sea state factors into account have been
proposed over the years, we tested several.
One of our problems was finding high
quality field measurements. W can be derived from the fraction
of white area in an image of the sea surface taken from a ship or a
stationary platform. In the pre-digital era these photos were printed
and the whitecaps were cut out by hand to weigh on a scale. The
weight of these paper cut-outs, divided by the weight of the initial
paper, gave W. The drawback of this method is that you really
need to average hundreds of images to achieve one useful W
value, a bit too much to ask of the person holding the scissors! In
present days this process is automated, so that hundreds of frames of
digital video recordings can be easily analyzed and averaged in an
objective manner. Our colleague Adrian Callaghan from the National
University of Ireland, Galway (now at Scripps in San Diego, CA), who
developed the Automated Whitecap Extraction technique, kindly gave us
his shipboard W measurements.
The W retrievals were state of
the art, but the dataset set did not contain information about the
sea state. Also, because the wind speed was measured on a moving
ship, its accuracy was questionable. EO data were needed to fill in
the gaps. We obtained observations from the SeaWinds microwave
scatterometer aboard NASA’s QuikSCAT (Quick Scatterometer)
satellite. This scatterometer uses radar to measure near-surface wind
speed and direction over the ocean under almost all weather and cloud
conditions. For detailed information about the sea surface we went to
the European Centre for Medium-Range Weather Forecasts (ECMWF). The
ECMWF offers global meteorological data, produced by an assimilation
of a coupled atmosphere–wave model with reliable observational
datasets. The dataset we acquired contained 30 wind and wave
variables, we used seven to describe sea surface conditions.
Combining all the field, satellite and
re-analysis data, we found that accounting for the state of the sea
surface improved W surprisingly little. This was
disappointing, but not totally unexpected. An explanation could be
that the assessed W parameterizations were just too simple.
One of our conclusions was that developed waves relate to increased
whitecapping, supporting the assumptions that W increases with
wave age and height, and hence with swell. On the other hand
cross-swell conditions, i.e. when the directions of wind and waves
intersect, appeared to reduce whitecapping. These two counter-acting
effects may explain the ongoing debate between wave modellers about
whether the presence of swell does, or does not, dampen whitecapping.
Interestingly, I have experienced both
effects in the water while surfing; a bigger swell definitely means
bigger whitewater to deal with and I have seen cross-winds blow out
lovely waves. Our study might not have resulted in practically
improved whitecap measurements from space, but it might have opened
doors to a better understanding of wave breaking and wind-wave
interaction. Currently we are re-examining alternative ways to
measure whitecaps, or air-sea gas exchange, from space directly. But
if you will excuse me now, I think I can see whitewater at the
headland !
Lonneke Goddijn-Murphy
Pictures about QuikSCAT :
Example of ocean surface winds by QuikSCAT
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