Modelling Waves & Swerves
30th Nov - 1st Dec / 2019
On this pad, are notes that we took from the last workgroup. Not all of the sessions were documented.
The weekend ran as follows:
Friday Eve - Intro of ourselves
We were: Michela, Marta, Chris, Martino, Kym, Ed, Anna, Yen, Fi
Screenings possible bodies or other moving image
Saturday - 10 which means 10.30
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Katherine Sammler -
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The rising politics of sea level: demarcating territory in a vertically relative world
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12.30
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lunch
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14.00
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FVCOM
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15.30-16.00
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Evelyn Fox Keller - Models, Simulations and 'Computer Experiments'
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18.00
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cooking dinner?
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Sunday
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10.30
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Refractor investigation plus:
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Barad - maybe technoscientific practices or how material-discursive practices matter, from meeting the universe halfway
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pg. 118 - 121
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pg 139: The primary ontological unit is not object, but phenomena
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till 145-or 146?
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(N.B. 77 > wave forms)
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theroretical models -
discovery and
https://stuff2233.club/padlife/p/MW&S
Saturday afternoon: Modelling :)
http://fvcom.smast.umassd.edu/wp-content/uploads/GB/images/integrated_model.image.jpg
Military and BP, etc - the data sets that are not sensitive is not released
sound undersea is very sensitive (submarines going past)
Depending on funding source, is whether you can use data or not
during election capagins (60 days before election) one is not allowed to release content that favours one politician or another?
if management goes full-on commercial, then this would change a lot. ( dependencies, funding, data access etc )
glider that thought that it should be in the 1970s. in the 90s when they programmed the glider software they didnt think that
-- FVCOM
an ocean model is solving some euqations but you need material coming from other sources ( models, data )
you need first snapshot, what is known to be going on, then through equations that represent processes , you move to other point son time.
assimilation
snapshot = initial conditions (measurements/data frmo another model)
of the content that you have ( measurement, data or zero ) some coherency / consistency..
have a rough idea of what youre gonna find in oceans
educated guess.
number can also be zero to run the element
initial conditions and boundary conditions
atmosphere is a boundary of the ocean
boundary condition for example physical boundary
this conditions translate int
o
an equation. li
k
e how velocity changes in space and time.
some of the many assumptions result in removing whole aspects ( salinity or maybe atmospheric )
salinity model of marta doesnt account for winds
the model per se is imperfect so will never reproduce the reality in
an
y point. it is not the point..
1:1 is not the point
1:1 is not possible
a model has always a level of abstraction from reality..
simulat
io
n is perfect representation of reality?
fvcom simulation or model?
using a model, running a simulation..
data is biased - marta
jo - we dont even have the data nor intstruments for that
diminishing returns is it enough to get out of it
if you know very well what your model cannot do - what is left out and
there is a peak in salinity that has a correlation with strong winds..
happy there is not peak in salinity when taking out strong winds
(if there is no two elements that have a correlation between them..)
all the parameters in the model
david hockney - painters using mirrors or lenses to do portraits
working within models is similar to acting from inside the camera obscura.
the model is not knowing
input data needed to use the model
fresh water input!
one point in which you put a river in for example, like the rain from the region..
modelling the dry season, don't consider rains..
filtering atmospheric properties (rain, pressure evaporation...)
global model
take elevation of boundaries from tidal model? Astronomy
Tidal Model gives for every point of the boundary ... waves or tides?
TPXO = tidal model
data sets ripple over each other
if it doesn't reproduce reality it's kind of good.
Looking at modeling typhoons
wasnt getting the wind velocity in atmospheric model
not reproducing what michela knew was happening
thought and care given to acknowledgeing the imperfection - chris
very educated guess.
where models misfunction, it's good it makes that transparent.
not "black art" i.e: gut instinct or familiartiy with the model
using some eqiuations in creating the wind velocity field limited to the typhoon track all background was lost
interested in imapct on currents and sea level
that was ok for her
a more simple specific model, small scale ( the typhoon model ) makes much more sense than a global atmospheric model.
grid striation..
build the model, and check against measurements
to validate, you have to use old measurings from macau ( before coming china, that does not share data )
project to ask china and asia their data.
will we have metadata? thank you.
maybe you get all data about salinity, but no metadata you don't know if its at the surface or at the bottom
salinity at the bottom took her a year and a half to figure it out
difficulties arise f
rom
political decisoin in china?
not bc scientists are dumb, where does the instruction come from?
Googlemaps is shifted 100m from reality in chinese landmass
different flows, chain of favors between scientists
to get data..
and then you have
to
give the favour back
this has implications for modelling obv
ERA5 atmostpheric model, with observations asismilated into it.
typhoon - 25km grid cell in
era - a software we use a the time has underestimated a typhoon massively
runs in one hour steps
time delay of 2-3 months
"boundary forcing" data has to be available or you can
'
t run the model
forecast might be too rough a resolution in space and time
hindtesting is the way of improving the model
do that with ships data and
data assimilation is a whole science in itself
if you put too much into the model then you risk it becoming just noise
sea-level rise and surge - plotted and visualised
Michela seperated out the surge to represent that
you can fly through barthymetry data and topology data in 4D
that is possible, and is sometimes used for scientific purposes
if you want to be a particle and flow through you can do that!
takes 3 days to ptroduce the gif of pearl delta river
is there likely to be another iteration of the model which includes winds? ( Stephen - Marta)
running for a month and a half, but cluster keeps on breaking
> depends on the time
--
computation running now for 4 days, still 14 days to go.
might have you have to repeat it, or that the cluster crashes.
--
txtfile
inputs: start/end date
initial conditions
coldstart? statrts from an inital value that doesnt pick form a previous model
.dat = text file > initatl conditions
.nc = netcdf format
grid.dat = mesh
node = vertex of each one of the triangles
geographical locatin of each corner of the triangle
node number of each of the triangle corner
then cells, with their latitude longitude and depth
model needs to know which triangles connected to which
ncdump to read content of ncdf files..
we are inputtnig fresh water, need to tell to the grid at which point you put in the fresh water
describing the rivers' locations and then their values
river flux
temp(10) & salinity(0)
physics decide what is wet and what is dry.
you decide in advance what can be wet and what not.
and the model goes in only few kms, but will increasingly need more..
in mangroves for example where do you define the limit of your grid
text file - how the water column is divided
sigma is the layering (at the coast each of the 10 layers is 20cm, deeper every layer = 200m)
Tornado:
fvcom counts the time in days since this moment
17 of november 1858
Astronomers have long measured the passage of time using Julian dates, defined by Joseph Scaliger in 1853 as the number of days that have passed since noon on January 1, 4713 BC. In 1957, the Smithsonian Astrophysical Union wanted to track Sputnik using a 36-bit IBM 704 computer. They needed 18 bits to store the time down to 100 nanoseconds. The day had to fit in the remaining 18 bits, so they tracked a Modified Julian Date, defined as the days since midnight of November 17, 1858 (Julian day 2,400,000.5).
1st jan 1740 = matlab
file which tells each one of the files is one day of data
grid metrix -
heating on = F
Airpresssure = true
waves are false
here where we don't know about the turbolence there is some parametrization. put some numbers.!!
another one is the roughness of the bottom ofmarta: the sea. ( rocks, mud.. )
suspect noone knows this parameter, because the whole industry its
uniform in the whole domain - cant tell the roughness so put 0.001
fvcom press -
intro long
4tran
global attributes
groundwater Forcing
Surface_heat Forcing =
http://fvcom.smast.umassd.edu/FVCOM/Source/code.htm
http://fvcom.smast.umassd.edu/FVCOM/Source/agreement.htm
fax it! :D
Community participation..
The user agrees to openly participate in the FVCOM community through three primary mechanisms. These are (a) reporting code bugs and problems, (b) sharing major modifications made to the code, and (c) contributing to an open and ongoing discussion of model deficiencies, needed improvements and additions, and major successes. (Contact Drs. C. Chen, G. Cowles, or R. Beardsley). These mechanisms are intended to benefit the entire FVCOM user community through quick notification of code problems, possible solutions, major code improvements, and, in general, the further development of the FVCOM source code and the associated software tools needed to process, visualize and interpret FVCOM model output.
thursday., meeting of all the user of FVCOM in the uk
20 people
how to keep the repository of the code and the scripts
NEMO merging party
--
Models are theoretical or physical experiments..
not theoretical == deterministic
theroretical models -
theoretical measurement? kind of a contradiction
mix of discovery and experimentation
theory taken to be provisional until they are proved true?
new science until its proven, then just becomes science - old science becomes quackery
kuhn's principle of falsification
all matter has waves and particles
matter and energy are somehow the same thing
a cannon ball has its particle aspects that overshadow its wave aspects..
in a camera, one could take the glass as the cut between observed object and capturing apparatus, but looking closely there are a lot of cuts at the sensor level, depending on what is the apparatus, what is measured..
marta: the models used are objects of observation?
it is the model itsel which
where you set the cut in models?
the model is the instrument of observing something
the models produces the measure
we determine the interaction in setting up the model.. keep the indeterminacy of knowing it is not in the water..
lots of different sources of error
uncertainty
how fine your ruler is known aslo as error
attempt to quantify them all
including their own ensemble measurement
dont know what starting confdition was as well as we thought
try to understand the contribution to the systematice errors
science deals with all the sources of error..
takes longer than the rest of the physics
1190s is the morphology of thte coastline
drift of calibration
what are we doing when we caibrate? pushing the slide
myrtle
someone making on in the workshop
john huthenance
metal fram 3 pressure sensor
send through short wave radio measurements to 11 pods on it
storage device radio, gps and more powerful radio
on the sea floor.
takes 6 months for the sensors to figure out where they are
send a boat with an acoustic signal, picks it up, and releases one pod, and it floats to the top, and you try to catch it - thats how you get the data
the myrtle goes 2km down sometimes so no radio connection, you retrieve data physically..
everyone is going to see different measurements..
focus makes it less precise
17
20
16.5
30
almost 30
27
rhs ppt (parts per trillion)
lhs sg (specific gravity)
refractoin we are measuring photons?
relative salt to water
saturation is 100% salt in the water, itd oesnt dissolve anymore
salt water is more dense than not salt water
mass/volume = density
mass = you cant find mass w/o gravitation
what you are doing with the intetument is measuring density
tree rings as a proxy for climate change
this is measuring a proxy for salinity
this is only a salinity refrator if you put salinity on it
--
model as apparatus
with measurements going in through apparatuses..
models are ways of measuring.observing something you can't measure/observe
calibrating is put inside some real measurements in the model/instrument..
are you observing the model when you are changing it?
experimenting with the model and altering it..
that object and observer are inseperable, btwn instrument & model you go
once scle higher -
although model includes 1000s of instruments & collected "data"
with the example of wave-particle are two phenomena, if earth system is the object, than ocean can be broke in different phenomena to measure with the modell
model is an object?
model is a phenomana
and part of apparatus
which keeps producing its object phenomena
.war.
oceanography is being pushed by world wars too..
how sound propogates under the ocean whats happening under the ocean - military necessary knowledge
who does oceanography for military reasons dont publish anything..
nato oceanographers don't publish anything.
phd student working on something finds bombs - absolutely cant publish on that and would havea job for life inthe navy
--
questions..
* What is the model? / as an apparatus/phenomena
* What can you describe as being imaginative? - given material-computation constraint
* When you know something about the ethic
not just the model itself but the project as a whole? it really feels like colonialism
* how much any model colonizes the imagination
* and how much visualizations colonize the model and imagination..
the model produces a bunch of files which we decide to visualise one or another way
* affective way of moving from the model to audience? (i.e. scary red)
* visualizations that are meaningful for everyone?
* models are the main tools for exploitation? i.e. how much data collection you have from oil companies partnerships with cloud
* different formations of "truth" that includes uncertainty within it (attack that you can expect from leaving out of the data some data points, political levarage and competition prevents uncertainty from being allowed)
* qualitative spectrum of truth or untruth
80s - knew about climate change and global warming, and they decided to hide the
Exxon scientists in the 80s made their own climate models and accurately depicted the current situation.. then worked on how to hide it for as long as possible.
https://www.scientificamerican.com/article/exxon-knew-about-climate-change-almost-40-years-ago/
https://www.theguardian.com/environment/climate-consensus-97-per-cent/2018/sep/19/shell-and-exxons-secret-1980s-climate-change-warnings
much more abstract more parametrics - produces less data
oil companies have less data, less processes can do in the cloud
time/speculation/limited resources..
Calvino - Palomar
Post Worksession Notes:
So yes it seems that not every nation ratified the UNCLOS after all..
Turkish propaganda doesn't seem to use the fractal argument, though. :^)
https://www.dailysabah.com/politics/2019/12/01/experts-eastern-mediterranean-deal-with-libya-signals-turkeys-future-deeds-in-region
This deal brings a new perspective to Turkey's shoreline. With a three-dimensional viewpoint, it maximizes the country's maritime boundaries and shows that Turkey's border districts of Marmaris, Fethiye and Kaş are actually neighbors with Libya's Derna, Tobruk and Bardiya districts.
https://www.keeptalkinggreece.com/2019/12/05/turkey-libya-agreement-mou-text-english/