Short answer:    Nobody knows.   Estimates of post-cambrian water levels are done by studying geology and where shorelines were in the past and what land was under water and working out from that how high the sea level probably was.   There are no pre-cambrian sea level estimates that I know of.

Working out how much water was on the surface of the Earth, especially during the pre-Cambrian era is a difficult subject with much uncertainty.   While the total amount of water on Earth may not have changed too much too much over the last 3 billion years, ground water vs surface water, and the shape of the ocean basin and the role of volcanoes and tectonics add to the uncertainty.   There's still some uncertainty on snowball Earth and if it went all the way down to the equator over the oceans.   Sea level over the pre-cambrian requires working out the specifics of snowball earth.   It's a tricky subject full of uncertainty.

Long answer that also says we basically don't know:

  From what reference point/level are prehistorical (e.g., Precambrian
  era) sea levels estimated?

I've never seen a pre-cambrian era estimate on sea level so I don't know how they are estimated.   This is the oldest I could find.

As the article explains, historic sea level is estimated by finding where the shorelines were at geologically historic time periods and looking at what was under water.   There's probably a pretty significant margin of error in those estimates I would think.

The article also says

  The main factors affecting sea level are the amount and volume of
  available water and the shape and volume of the ocean basins. The
  primary influences on water volume are the temperature of the
  seawater, which affects density, and the amounts of water retained in
  other reservoirs like rivers, aquifers, lakes, glaciers, polar ice
  caps and sea ice. Over geological timescales, changes in the shape of
  the oceanic basins and in land/sea distribution affect sea level. In
  addition to eustatic changes, local changes in sea level are caused by
  tectonic uplift and subsidence.

  Over geologic time sea level has fluctuated by hundreds of meters.
  Today's interglacial level is near historic highs and is 130 meters
  above the low level reached during the Last Glacial Maximum
  19,000–20,000 years ago.

So, key factors are obviously ice ages and glaciers, as well as the shape of the ocean basin.   The movement of continents affects the shape and depth of the ocean basin, so continental movement likely has an effect.

As a somewhat small but fun example, the Mediterranean Sea has about 3.75 million cubic km of water in it and the sea is thought to have been a dry valley some 5.33 million years ago that, once the straight of Gibraltar gave way, was quickly filled by the Atlantic ocean.   That's just a theory.  It may have filled much more slowly, and over 5 million years ago, it might have been a significantly different size too, but if we use the 3.75 million cubic km number over today's 361.9 million square km of ocean surface, that works out to a 10 meter drop in sea level to fill up the Mediterranean valley.    10 meters isn't a big change in the grand scheme of things, but if it happened over as little as a year, as one hypotheses suggests, that would have been quite something to observe a 10 meter drop in sea level over a single year or so.   However long the Mediterranean took to fill, it's a nice example of how shifting land can affect sea level.

Historic estimates are made (as noted above) by studying where the shorelines were and studying what was under water and trying to piece together an estimate from that.   Formation of glaciers like the Antarctic Glacier, which would raise sea level 58 meters if it melted, affect sea level too.  The antarctic glacier began to grow in earnest about 34 million years ago.   Greenland is another 6 meters and that formed much later, over the last million years or so.

Geological history of ice ages is fairly well understood, though the total amount of water in those glaciers might have some uncertainty.   The shape of the ocean basin is (I think) less well understood over the last 600 million years or so.

The ice age periods, 260 to 360 and 420 to 450 million years ago should correspond to drops in the chart, below.  The recent ice age period is just 2.5 million years long, and too short to be well represented but the 34 million years when the antarctic ice formed is apparent.

  Since the formation of continents, land elevations everywhere have
  been continually changing due to plate tectonics, weathering,
  sedimentation, etc.

The continents formed quite early, between 2.5 and 3 billion years ago.  The silicate rock that form most of the granite that makes up both the continents and the continental plates was present at the formation of the Earth.   Heat and plate tectonics likely helped form the continents.   Life and photosynthesis may have added to them over time, but most of the continental material was present at Earth's formation.

Precisely how sea levels change, other than by formation of glaciers or the forming of filling of valleys on land is (to my knowledge) not well understood though the shape of the ocean basin (noted above) plays a key role.   The continents are roughly some 35 miles thick in silicate rock, but that far below the Earth's surface, silicate rock can melt and mix with basalt in the upper mantle.   We know this because lava can be either basalt rich or silicate rich.

Wikipedia mentions sediment and groundwater likely also play roles.  Over long enough periods of time, the rock cycle likely returns sediment that erodes of land into the ocean, back to the land.   Likewise, life can lead to the formation of limestone and other carbonate rock, but that's probably a small percentage of total land and a small factor, not a major factor.

The internal heat of the Earth (I would guess) play a bigger role.  A hotter earth, the upper mantle is a little closer to the surface and the granite continents and continental plates are less thick, so they float less high on the basalt, leading to a corresponding higher sea level, but that's just speculation on my part.   As Earth cools over hundreds of millions of years, the granite may become thicker and the sea level could drop in relation to the rising land.  This fits with the studies that sea level was generally higher in the past, but, again, this is speculation on my part.

  The total volume of ocean water has been essentially the same since
  formation in the early Hadean.

You probably shouldn't make that assumption.  The Hadean was the first epoch all the way back to the formation of the Earth.   For consistent amounts of water, the earliest I would consider starting would be the end of the late heavy bombardment, about 3.8 billion years ago.   That would be enough time for the magnetic field to form (about 4 billion years ago) and time for the sun to settle down, because UV rays from the young sun can strip water form Earth by photo-chemical dissociation.

Throughout the history of Earth, UV rays from the sun have stripped hydrogen from atmospheric water vapor, effectively taking water away from Earth and replacing it with hydroxide, which is fairly reactive.   Likewise, comets and asteroids that hit the Earth bring water with them.   The current rate is quite small and insignificant, but 3.8 billion years ago, even after the late heavy bombardment, there might still have been frequent enough comet impacts to affect sea level over different eras.

Precise numbers aren't known - question on that here.   But if Earth loses 50,000 tons of mass per year, most of that hydrogen stripped from water, that's as much as 900,000 tons of water photo-disintegrated per year.   Over a billion years, that's 900 trillion tons of water, which sounds like a lot, but it's less than 1/10th of 1% of our ocean's mass of about 1.5 million trillion tons.

That said, when the Earth was hotter when it was young, it could have had more water in it's upper atmosphere and lost more water than 0.1% per billion years.   This estimate suggests that the Earth lost as much as 25% of it's water over the last 3.8 billion years based on studying deuterium ratio in 3.8 million year old rocks to water on Earth today.

There's also the problem of water emerging from inside the Earth.   It was recently discovered that the lower mantle is wet and there's as much water deep inside the Earth as there is in the oceans, maybe more.   How much mantle water made it's way to the surface of the Earth during the pre-cambrian era is unknown.  Some of Earth's water today likely came from inside, even though the heat of formation of the planet probably lost most of it, some (at least an ocean's worth) is still deep inside the Earth but much (most?) is thought to have come from comets and meteors during the late heavy bombardment.

  So is the rise and fall of sea level derived from the geological
  record measured relative to the adjacent land, or the center of the
  earth, or what?

Speaking strictly for the geological record, it's not directly measured, but estimated by the methods discussed above, looking at geological records of old shorelines and land that was once under water and working out an estimate.

Sea level from the center of the Earth is mostly done for modern measurements.   You can measure sea level against the land, but land can rise and fall, or it can be measured from the center of the Earth, independent of land shifting.   I don't think that's particularly relevant to your question on geological estimates of sea level.

That probably needs some cleaning up, but it's a fun subject.   I thought I'd give it a shot.


How accurate are climate proxies in giving us a clear picture of global average temperatures throughout Earth history?

Overall, any individual proxy is not a reliable indicator.  It's the combination of multiple proxies that provides a clearer picture.

For example, tree ring growth has been correlated with temperatures.  However, it's not without it's anomalies:

  ...from the middle of the 20th century tree ring growth was less than might have been expected from the temperature record... ([source]

(http://www.climatedata.info/Proxy/Proxy/treerings_introduction.html))

If we were to only look at tree-rings, we could not possibly trust on them as a reliable source, since they have known problems.

We can also use coral as a indicator of past climate.  However, it's also somewhat questionable:

  However, long (multi-centure) records are rare, and the possible influence of non-climatic influences has not yet been confidently established.
  source

Ice-cores are not immune to skepticism:

  An indisputable interpretation of ice-core oxygen isotopes in terms of
  atmospheric temperature variability, moreover, remains elusive, and
  precise annual dating can be difficult.

However, if we can combine these three indicates along with other indicators (pollen, earth bores, etc), we can increase the reliability of our understanding.  For example, if most indicators show a cold year, we can more reliability say it was a cold year.

Combining these proxies together helps us to gain a clearer picture of the past environment.

Overall Reliability

However, with that said, the amount of uncertainty with the multi-proxy method is not small.

At the Workshop on Mathematics in the Geosciences, Blake McShane presented a new algorithm for estimating paleoclimate.  This algorithm provided a more reliable estimate by increasing the uncertainty of the predictions.  That's an important point that I will restate:

Through his talk, he showed that his method was more reliable because it was less certain.

Even that wide uncertainty level, he questioned:

  Indeed, this should make us increase our level of uncertainty (indeed perhaps
  our wide intervals are in fact optimistically too narrow)!

  source

In the end, we can look at proxies for guidelines and trends, but they cannot be used for reliable readings.


What can I use as a heatproof, non-magnetic glue for samples?

Oxford Instruments used to sell a VSM (vibrating sample magnetometer) with an oven option up to 1000K. Mounting samples was made using a "non-magnetic" paste/cement. You may want to look into that.


What place on Earth is closest to the Sun?

This is an interesting question, but it lacks a key factor that is crucial to the answer: TIME.

The point on Earth closest to the Sun varies through time, so the question can be asked about any moment in time, or over periods of time. Let's analyze the factors involved.

At any given moment in time, the point on Earth's surface that is closest to the Sun is what is called the “subsolar point”. This point corresponds to the point on the surface that intersects the imaginary line that connects the center of the Earth to the center of the Sun. In other words, the subsolar point correspond to the point on Earth surface where the sunlight hits the Earth perpendicular to the ground, therefore, a vertical object would project no shadow.

(image from Wikipedia: subsolar point)

The longitude of the subsolar point corresponds to that of the meridian experiencing solar noon. Over Greenwich (longitude 0°) that happens at the actual noon, and as the Earth rotates 15° every hour, that will happen one our later (at 13:00 h UTC) at longitude 15° W, two hours later (at 14:00 h UTC) at longitude 30° W, and so on. In general terms, you can use the following formula for the subsolar point longitude ($\text{SSP}_{\text{long}}$).

$\text{SSP}_{\text{long}} = \left(\text{UTC} -12\right)*15°$

This is a simplified formula, but accurate enough for our purpose. Let's take as an example the following date

July 20, 1969, at 20:17 UTC

In that moment, the longitude of the subsolar point was 124° 15' West:

$(20+(17/60)-12)*15°=124.25°=124°15'$

Finding the latitude of the subsolar point is a bit more complicated, we need to know the declination of the Sun. Declination is the equivalent of latitude for celestial coordinates. For that, use a formula, a table, or a online calculator like the NOAA Solar Position Calculator.

Just enter the date, and even that the location doesn't matter here, we need to select “Enter Lat/Long -->” to be allowed to enter the offset to UTC as 0, otherwise the time won't be interpreted as UTC time.

From there we can find that the solar declination for our example date is 20.58° (20° 34') which corresponds to the latitude of the subsolar point: 20° 34' North.

Therefore, on July 20, 1969, at 20:17 UTC, the subsolar point was at 20° 34' N, 124° 15' W, which is somewhere between Mexico and Hawaii. That was the point on Earth closest to the Sun at that moment.

Now, what would happen if there were a very tall mountain close to the subsolar point? Would that mountain be closer to the Sun?

The answer is: probably. It depends on how far and how much higher it is relative to the subsolar point.

We can do a quick calculation based on the following diagram (in this approximation we assume that Earth is spherical, that the sun is infinitely far away and other simplifications)

From there we have

$r-r'=\Delta H$

$D = r ~ \theta$ ($\theta$ in radians)

$\frac{r'}{r}=\cos(\theta)$

After some algebra you can write that the extra height $\Delta H$ needed to be as close to the Sun as the subsolar point is

$\Delta H = r \left(1-\cos\left(\frac{D}{r}\right)\right)$

Where $D$ is the distance and $r$ is Earth's radius (in this case makes sense to use the equatorial radius of 6378.1 km)

If we plot this equation we get the following

(the vertical axis is logarithmic)

We can see that around 10 km away from the subsolar point, ~10 meters are enough to be closer than it to the Sun. ~30 meters at 20 km, ~800 meters at 100 km, ~3,000 m at 200 km, and if you go further than 340 km, not even Mount Everest will get you closer to the Sun.

So, the closest point to the Sun will be whatever geographical feature that maximizes the value $\text{Altitude}-\Delta H$, where $\text{Altitude}$ is the altitude of the geographical feature. Let's call that point “proxisolar” point. I just made up that name, but it will be handy for the following discussion.

Now that we understand the basis to establish what is the closest point to the Sun at a given moment, we can tackle the question that probably most people meant when asking this question:

What is the point on Earth that gets closest to the Sun over a year?

The most important fact to keep in mind, is that the variations of the distance between the Earth and the Sun over the year dwarf any topographical feature and even the diameter of the Earth itself. Earth’s distance from the Sun (center-to-center) varies from 147,098,074 km at perihelion (closest) to 152,097,701 km at aphelion (most distant). Therefore, the difference is 5 million kilometers!.

The perihelion happens around January 4th, when the solar declination is about -23°, therefore, the latitude of the subsolar point is around 23° South. That rules out Chimborazo, Cayambe and Everest, because they are too far to be the “proxisolar” point. In contrast, Sairecabur (5,971 m at 22.72° S) and Licancabur (5,916m at 22.83° S) are reasonable contestants.

The problem is that the perihelion happens on different days of the year and at different times of the day every year, so the point that gets closest to the Sun on a given year is just the one that happen to be the “proxisolar point” at the time of the Perihelion.

People who argues that Sairecabur or Licancabur are the points that get closer to the Sun, are implicitly assuming that the distance Earth-Sun doesn't vary much during the day of the perihelion. Therefore, the extra elevation of these mountains allows them to get closer to the Sun during that day. Unfortunately, that assumption is completely wrong. Let's see why:

An approximation of the distance Earth-Sun can be obtained from the following formula

$d = \frac{a(1-e^2)}{1+e \cos\left(\text{days}\frac{360}{365.25}\right)}$

Where $a$ is the semi-major axis of Earth's orbit, $e$ is the eccentricity, and $\text{days}$ is the number of days elapsed since the perihelion. To see the simplifications behind this equation look here (note that the conversion factor 360/365.25 is erroneously inverted in that link, thanks @PM2Ring for spotting that).

If you solve the above equation for the perihelion and for one day before/after it, you will get that the difference is 358 km, and for half a day you get 89 km. Therefore, if the subsolar point happens to be on the opposite side of the Earth than, let's say, Licancabur volcano, this volcano would need to be 89 km higher that the subsolar point to get closer than it to the Sun that year. 89 kilometers!

Therefore, we can discard the idea that a given mountain could be the point that gets closer to the Sun on EVERY year.

If we plot the above equation with distances relative to the perihelion we get the following (using $a$ and $e$ from here)

Here we can see, that if the perihelion happens a bit more than 3 hours before or after the solar noon at Licancabur, the ~6,000 m of elevation advantage would not be enough to get closer to the Sun than the subsolar point at the perihelion, even if such point is at sea level.

Note that three hours corresponds to 45° in Longitude, which at that approximate latitude corresponds to approximately 4,600 km.

Therefore, it can be argued that Licancabur is the point on Earth that has more chances to be the closest to the Sun in an arbitrary year. But in a given year, it might or might not be the closest depending on where the subsolar point is at the moment of the perihelion.

Finally, it is important to note that the distance Earth-Sun at the perihelion varies widely from year to year. If you look at this table of perihelions between years 2001 and 2100, you will see that perihelions often vary by several thousand of kilometers.

Therefore, for example between years 2001 and 2100, the closest perihelion by far is the perihelion of next year (2020), and it will happen when the subsolar point is in the middle of the Indian ocean, about 12,700 km away from Licancabur and Sairecabur volcanoes. Therefore, the point that will be closest to the Sun this century will be one in the middle of the Indian ocean about 320 km south of Rodrigues Island.

Said this, the question of which point on Earth will get closest to the Sun depends on the period of time on which it is considered. For each year, each century and any other arbitrary period of time, the answer will be different.


How to install ESMF and ESMFPy in Ubuntu using gfortran, gcc, python?

First download the esmf tar file from http://www.earthsystemmodeling.org/esmf_releases/public/ESMF_7_1_0r/reg/ESMF_Framework_Down.html

Then install netcdf library and gfortran compiler using

sudo apt-get install git tcsh pkg-config
sudo apt-get install gfortran
sudo apt-get install netcdf-bin libnetcdf-dev libnetcdff-dev
sudo apt-get install openmpi-bin libopenmpi-dev
sudo apt-get install libnetcdff-dev

Once you have the netcdf library and gfortran compiler in your /usr/local/lib and /usr/local/include You can check this also, login as root using

sudo -i

Then define the following environment variables

cd path_of_esmf_dir
export ESMF_DIR=path_of_esmf_dir
export ESMF_INSTALL_PREFIX=/usr/local/esmf
export ESMF_OS=Linux
export ESMF_NETCDF="local"
export ESMF_COMM=mpiuni
export ESMF_F90COMPILER=gfortran
export ESMF_CXXCOMPILER=g++
export ESMF_TESTEXHAUSTIVE=on
export ESMF_TESTSHAREDOBJ=on
export ESMF_NETCDF_INCLUDE=/usr/local/include
export ESMF_NETCDF_LIBS="-lnetcdf -lnetcdff"
export ESMF_NETCDF_LIBPATH=/usr/local/lib
export ESMF_BOPT=O3

Then run the following syntax to make the library ESMF

make all
make install
make installcheck

Now to install the ESMF python library

cd path_to_esmf_dir/addon/ESMpy/
python setup.py build --ESMFMKFILE=/usr/local/esmf/lib/libO3/Linux.gfortran.64.mpiuni.default/esmf.mk
python setup.py install

You can check the installation by

$ python
>>> import ESMF

ESMF python library has got limited features as compared to the ESMF library. Hence it is better to use ESMF directly.


Barnes & Hillenbrand (2010) argue that there is faunal evidence for a late-Quaternary trans-Antarctic seaway. From the abstract:

  We investigated biological evidence for past connectivity between different regions of Antarctica by comparing the composition of modern bryozoan assemblages from the continental margin around Antarctica. Surprisingly, we found most similarity between two areas which are not currently connected – the shelves of the Weddell Sea (WS) and Ross Sea (RS). We evaluated three hypotheses to explain this and conclude that bryozoans most likely dispersed through a trans-Antarctic seaway that opened in response to a WAIS collapse and connected the WS and RS shelves. These bryozoans must have survived glaciations(s) during subsequent ice ages in refuges, whereas they were wiped out in most other regions of the Antarctic shelf. After the last glacial period, bryozoan assemblages could freely disperse between many of the regions we examined (e.g. Antarctic Peninsula and South Shetland Islands), which has allowed recolonization of areas in which bryozoans had been eradicated during the last ice age. For the bryozoans on the WS and RS shelves to be more similar than those which are in close proximity means the trans-Antarctic seaway may have been as late as the last few interglacials.

There are some other folk in agreement, in particular Strugnell et al. (2012) on the topic of genetics of an Antarctic octopus (yes, really); and Vaughan et al. (2011) review available data and find strong biogeographical evidence for the existence of such a trans-Antarctic seaway, with four possible candidates and extensive discussion of when it might most recently have been open:

  The methods currently at our disposal do not allow us to constrain, with confidence, which recent interglacial saw the last open West Antarctic seaways. However, given that during the last interglacial (MIS 5e), air temperature in Antarctica was substantially warmer than present for several thousand years [Sime et al., 2009] and at the same time, ice-loss from Antarctica almost certainly contributed to higher global sea levels [Kopp et al., 2009], it would appear that MIS 5e is a strong candidate.

In summary: biogeography and octopuses say yes.


There are two main approaches to measuring sea level (and thus its change): local and satellite-based.

To measure local sea level we can set up gauges on the coast that record the water level every so often - hourly is common. These use various methods, which have evolved over time, all aimed at having a very precise (sometimes down to millimetres) long-term record at that location. In the UK, the UK Tide Gauge network has records going back (in some locations) to 1915.

The mechanisms of tide gauges vary, and have improved over time. Early ones used floats inside a "stilling well" (a column of water that protects the gauge from waves). Some modern gauges work by sensing water pressure. If we have good measurements of temperature and salinity we can calculate density, and if we know density and the pressure at a location, we can calculate the amount of water above that location. Other modern gauges use ultrasound or radar transceivers located at a known vertical position above the water, and thus measure the distance to the water surface with very high accuracy.

These records of water level include the tides, of course, as well as other influences such as the effects of changing air pressure, wind driven currents, and so forth. They are also affected by the rising and falling of land over time. These effects can all be accounted for, and removed from the signal, and effort goes into doing this. You might some interesting reading on the topic from the National Tidal and Sea Level Facility.

However, no matter how good the record from fixed tide gauges, they can only tell us what is happening on the coast. While that's arguably the most important for mankind, it's hardly a global picture.

The other approach that we can take is satellite observations. Radar altimeters on satellites can, and do, measure sea level worldwide to a precision of a few centimetres or better. This is a recent mission for this purpose (there may have been others since - I'm not an expert). The level of accuracy here is not as good, but it can be improved statistically through a large number of measurements.

The greater difficulty with satellite altimetry is removing the tides, because the satellites are always moving over the earth's surface and so can only measure any one location at relatively infrequent intervals. Consequently, some sophisticated global tidal models are used with data provided by the satellites to (a) improve the models, for people who want to predict tides, and (b) use the tides from the models to remove the tides from the satellite measurements, leaving just longer-term changes in sea level.

I think part of the intent of your question is "people quote changes in sea level of millimetres or centimetres per year, yet surely the measurements are not this accurate?". Well, satellite measurements aren't, though local ones might be, but remember that we're measuring for more than just one year. One approach might be to look at a ten- or twenty-year trend, and work out the average change per year from that.


When I visit that link, the first option at the top ("Data Product") defaults to inst3_3d_asm_Np, which is atmospheric variables in pressure levels.  I suspect you need to change that dropdown option to inst1_2d_asm_Nx, which is surface and near-surface variables.  The list is shows me for that option is,

DISPH = zero plane displacement height
PS = surface pressure
QV10M = 10-meter specific humidity
QV2M = 2-meter specific humidity
SLP = sea level pressure
T10M = 10-meter air temperature
T2M = 2-meter air temperature    <---- Here it is!
TO3 = total column ozone
TOX = total column odd oxygen
TQI = total precipitable ice water
TQL = total precipitable liquid water
TQV = total precipitable water vapor
TROPPB = tropopause pressure based on blended estimate
TROPPT = tropopause pressure based on thermal estimate
TROPPV = tropopause pressure based on epv estimate
TROPQ = tropopause specific humidity using blended tropp estimate
TROPT = tropopause temperature using blended tropp estimate
TS = surface skin temperature
U10M = 10-meter eastward wind
U2M = 2-meter eastward wind
U50M = eastward wind at 50 meters
V10M = 10-meter northward wind
V2M = 2-meter northward wind
V50M = northward wind at 50 meters


The geology of Lithuania is pretty complex - ice ages could have brought  nearly anything. The fossil belongs to Rugose corals - an extinct order of solitary and colonial corals that were abundant in Middle Ordovician to Late Permian seas.

For precise identification try Baltoscandia fossil database: http://fossiilid.info/46


What is the difference between Water Holding Capacity, Field Capacity and TAWC?

Okay Water Holding Capacity(WHC) is how much water the soil has in it at total saturation, if you filled every soil pore space completely with water.

Field Capacity(FC), if I remember correctly from first year, is shorthand for the water that stays in the soil after surface runoff and groundflow has ceased; the sub-saturation "ground state" of the moist soil if you will.

Soil Water(SW) would appear based on the excerpt provided to be referring to the percentage of WHC present at time of measurement.

You've also asked about Total Available Water Capacity(TAWC) which is the water that can be accessed by plants, this is the water stored in macro, as opposed to micro, pores in the soil (it's more complex than that but we always worked it as a two grade problem; pores big enough for plant roots and pores too small for them). Usually to quantify this figure WHC, or FC depending on what's of interest, is multipled by the percentage of plant accessible pore spaces in the soil, this gives the volume of water plants can access before they start to wilt.

Please note I'm mostly working from my memory of an entry level class I took nearly a decade ago so this may not be perfect, but it it does check against the research material I quickly skimmed while writing.


Is the sunlight on the GOES-16 Imagery reaching from the east?

Yes. The time stamp says that the image is taken at 13:45Z, which means the sun is overhead in the Eastern Atlantic (12:45 PM local time in Cabo Verde and the Azores). In Winnepeg, near the upper arrow, it is 7:45 AM and still in darkness.

Being winter in the NH, places that are more southerly like Louisiana and east Texas in the US have light while places at the same longitude further north do not.

You can tell that the image is taken in winter from the south-west to north-east slope of the terminator (i.e. the line separating the light and dark areas, see discussion here).


There are crickets species living in Wales (Reference)

Field Grasshopper

Green Grasshopper

Meadow Grasshopper

Roesel's Bush-cricket

Oak Bush-cricket

Speckled Bush-cricket

Mottled Grasshopper
and even if a species is not common in this part of the UK it might be brought there e.g. as a secret passanger in a car.


Seismic Reflectivity and Fractal (Random) Behavior

The assumption that the earth's reflectivity is random (i.e. has a white spectrum) is only necessary for the statistical extraction of a wavelet from the data itself via the amplitude spectrum of the autocorrelation function. The convolutional model still works regardless of the reflectivity pattern, although getting a wavelet may be more difficult if the "white reflectivity" assumption does not hold.

On the other hand, in most sedimentary basins, earth's reflectivity pattern tends to not be random. Sedimentary deposition happens in nested cycles forming smaller cyclic layers within large cycle layers. This fractal nature is observed in the amplitude spectrum of real (i.e. measured) reflectivity series. Instead of a having a flat (i.e. white) amplitude spectrum, real reflectivity series tend to have low amplitudes in the lower frequencies and high amplitudes in the high frequencies (i.e. blue) while generally conforming to a consistent positive slope line when ploted in octave vs dB. The slope of this line is a characteristic of the local geology and contains information about the fractal nature of the layering.

This concept is used in a technique called spectral blueing (and also similarily in coloured inversion), where seismic data is forced to match the characteristic reflectivity amplitude spectrum line causing an increase in apparent bandwidth.


Is there a special name for along-course elevation profiles of rivers, and where you can you find them?

I guess there are multiple names, but I know it as the river's "long profile", and it is used in academic papers (one example here and a search in google scholar here). But you can find similar diagrams under names like the river's height profile, longitudinal profile, longitudinal map or geographic profile. These last two are the ones used in an Australian government web page that have many of those profiles for all major rivers in Australia, with the cities along the river and other information. I'm not aware of a global repository of long profiles.

The following picture is from the same link pointed above (from Geography AS Notes)

A quick search for "Danube long profile" put the following image in the second position of the results

Taken from here


Pangaea - Why did all the land mass form in one area?

The formation and break up of supercontinents have happened throughout Earth's history in almost a cyclical manner. There may have been many others supercontinents before Pangaea and the total number of such is uncertain. The 4 last supercontinents are: Nuna (some other people call it Columbia) that was present in the period 2.0–1.8 Ga (billion years ago or 1000 million years ago, if you use the long notation); Rodinia that formed around 1.1 Ga and lasted until about 750 Ma; Pannotia that lasted 650-560 Ma; and finally, Pangaea.

The location of the supercontinents seems to have varied throughout Earth's history and it doesn't seem likely that there was something special about the location of Pangaea, except the underlying forces of plate tectonics.

Here is good animation of the evolution in time of the different supercontinents.


How do subsurface oceans form under a rocky crust?

As Jean-Marie Prival comments, Ceres doesn't have a rocky crust.  It has an icy crust in which rocky matter is embedded from asteroid impacts.  I'd rather see this comment turned into an answer than reinvent the wheel on that dwarf planet.  In case they "die", the relevant comments are quoted below the main body of the answer..
Instead, here I consider a celestial body closer at hand.  Earth does not have a subterranean ocean but it can produce water deep in the mantle, extracted from rock.  As described in this answer from Space Exploration Stack Exchange, a high-pressure solid phase of water, Ice VII, has been identified as inclusions in diamonds; the presence of these inclusions implies that water exists in the molecular state ($\text{H}_2\text{O}$) as distinct from hydroxyl groups in minerals.  The water is first trapped as a supercritical fluid as the diamonds form deep in the mantle, then condenses to Ice VII as the diamonds cool at the surface but retain mantle-level pressures internally.
Water in Earth's mantle likely does not come directly from surface oceans, but from hydroxide-bearing minerals in the rock.  When the rock is cycled downwards by plate tectonics, it becomes hot enough to decompose the hydroxides (hydroxides of silicon, aluminum, iron, calcium, and magnesium, the elements to which hydroxyl groups are most likely to be bound in crustal rocks, all decompose well below 1000°C), thus generating the subterranean water.

Previous comments
There seems to be a whole bunch of publications on the matter: nature.com/articles/s41550-020-1146-8, nature.com/articles/s41550-020-1019-1, nature.com/articles/s41561-020-0581-6. I don't have access to all of them (too expensive ...). Maybe there's some useful information on the matter. – user20217 Aug 12 at 12:59
Interesting! The first one states that "the interior of Ceres consists of (1) a thin lag deposit (regolith) layer, (2) an icy crust that contains the bulk of an origin ocean [...]". That would explain a lot, the rocky layer being created on top of the icy surface by impacts. What got me was this passage in doi.org/10.1038/s41467-020-15973-8 : "Ceres [...] is partially differentiated into a rocky interior and a comparatively more volatile-rich crust, which is composed of rock, salts, clathrates, and ≤ 40% water ice." Looks like the crust might not be so "rocky" after all... – Jean-Marie Prival Aug 12 at 14:10


Why is WRF most often configured at 3:1 nesting ratio?

To understand why the nesting ratio of 3 is preferred to the nesting ratio of 2, it is important to understand the following two features of WRF:

1) Grids are Arakawa C-staggered: mass points are at cell centers,
 u-velocities are at east-west cell edges, v-velocities are at
 north-south cell edges. See Mesinger and Arakawa 1976, Chapter 4
 for a good description and explanation of Arakawa staggering. WRF's
 grid in computer memory looks like this:

   +-------+-------+-------+
   |     v |     v |     v |
j=3|       |       |       |
   | u   p | u   p | u   p |
   +-------+-------+-------+
   |     v |     v |     v |
j=2|       |       |       |
   | u   p | u   p | u   p |
   +-------+-------+-------+
   |     v |     v |     v |
j=1|       |       |       |
   | u   p | u   p | u   p |
   +-------+-------+-------+
      i=1     i=2     i=3

Thus, p(1,1) is geographically located $\Delta x /2$ East of u(1,1) and  $\Delta x /2$ south of v(1,1).

2) For computational efficiency and accuracy, the data from the child (nested) domain is copied to the parent domain. This is opposite from the data going from parent to child, which is interpolated. For more specifics, see the WRF Registry documentation by Michalakes and Schaffer.

As a consequence of the above two, it is more computationally efficient and accurate to use a nesting ratio of 3, rather than 2. In the example below, for 2:1 nesting ratio and 1-d case for simplicity, u values are simply copied from child to parent array because these points are guaranteed to overlap between two grids. Notice that the p points do not overlap and child p values must be interpolated to the parent. This induces computational overhead and numerical damping of the $2\Delta x$ wavelength in mass:

child  u   p   u   p   u   p   u
       +-------+-------+-------+
       |    \     /    |
       |     \   /     |
       |      \ /      |
       v       v       v

parent U       P       U
       +---------------+

In a 3:1 nesting ratio however, both the velocity and mass points overlap, and a simple copy is feasible:

child  u   p   u   p   u   p   u
       +-------+-------+-------+
       |           |           |
       |           |           |
       v           v           v

parent U           P           U
       +-----------------------+


Why is Earth's density gradient a step-function, rather than smooth?

Roughly put, it's the same thing that makes a density step function when you try to combine oil and water:
Source
The components do not mix with or dissolve into each other, so gravity makes the denser material -- water -- settle to the bottom.  The density as a function of height jumps up from the oil density to the water density when you go below the interface.
In the case of Earth, there are several progressively denser phases that do not mix.  The biggest step in the density gradient is when the rock phases (olivine, spinel, perovskites, and ferropericlase which is not shown in the illustration below) give way to the much denser core.  In the illustration below, this boundary is where the bottom part of the rocky mantle, the D" layer, meets the predominantly iron core.
Source
One major difference between the interior of Earth and the oil-water combination in the first picture is that much of Earth's interior is solid, so it takes a lot of heat and pressure -- both generated by gravity -- to make the materials yield and flow to their equilibrium positions.  The same is true of other predominantly solid celestial bodies, so only relatively large and massive ones have enough gravitational power to enable separation of different density phases.  Planetary scientists call this process differentiation.


Why are atmospheric BrO and ClO important to measure by satellite?

BrO and ClO significantly deplete ozone from the atmosphere.

Researchers at Harvard University state:

  It is a remarkable fact that perhaps the most important observation coupling climate forcing to UV dosage levels at the surface at mid-latitudes is the observation of high (e.g. > 10 ppmv) water vapor and low temperatures (< 210 K) with the simultaneous determination of BrO and ClO in the lower stratosphere at mid-latitudes.

Similarly, Science magazine states:

  Halogen-radical chemistry was responsible for approximately one-third of the photochemical removal of O3; reactions involving BrO account for one-half of this loss.

Additonally,

  ... where the chlorine and bromine thus released participate in the catalytic destruction of ozone.

Kinetic studies of the BrO plus ClO cross-reaction over the range T=246-314 K


The question is requesting an answer that has no practical application. So rather than improving on some hypothetical calculation, I will describe the problem and hopefully make the difficulty providing a real answer to a time frame clear.

First: "polar ice" Antarctica is located in a polar position and consists of a multi-km thick ice sheet. The Arctic is covered by sea ice except for smaller glaciers and Greenland, which is not located in a polar position equal to Antarctica. One has to remember that Antarctica is circulation-wise isolated from the rest of the planet by circumpolar circulation, both in th esea and atmosphere, a situation not met in the Arctic. Hence the term polar ice is very fuzzy and should be avoided. It is better to speak about the objects directly.

Second: an ice sheet such as Greenland and Antarctica is not a stagnant sheet of ice, it has its own dynamics and which can change over time depending on forcing and change in forcing.. Greenland is largely land based but with outlet glaciers that terminate in the sea. Although mass loss through these have seen an increase in loss, much of the Greenland mass gain and loss is through surface mass balance (snow accumulation minus ablation, melt). Antarctica is a different beast since East Antarctica is largely land based while West Antarctica is to a large extent sitting on ground below (in places several km) below sea level. Te latter situation is more unstable since the ice could disintegrate by calving (loss through ice berg formation), a process which is potentially much quicker than surface melt (of which there is currently very little in Antarctica). So one part of Antarctica is much more unstable than the other.

Now, several other processes are at play. Ocean currents are sen to produce massive amounts of submarine melt on both Greenland outlet glaciers as well as on the sea-terminating edges of Antarctica. In places, circulation models estimate up to equal loses by calving an submarine melt. This occurs at the same time as there is hardly any surface melt to speak of. So calculating mass loss by surface melt is clearly a lost cause when calving and submarine melt dominate.

Finally, in this still simplified picture, the dynamic response of the ice sheets to changes in forcing is not well understood. This means we do not know how unstable East Antarctica really is. That Antarctica will totally disappear seems very unlikely any time soon and time frames of 10^3-10^4 years is a minimum. Greenland, not being a polar ice sheet is more sensitive in that as it loses mass it is also on average lower in altitude, experiencing more melt. There appears to be a point of no return for Greenland, under which elevation the ice sheet would not be able to recuperate unless the climate cooled significantly. Again the time to melt off the ice is long.

despite the seemingly slow increase in sea level, much infra structure  in the coastal environments is threatened by only dm to m changes in ea level so the 66.1 m quoted from IPCC is not something that will happen in a life time but that does not mean the rates are not already problematic.

As a PS, I will add some relevant references once I am back home in case someone misses them at the moment.


Would more or less land be usable if global temperatures rose?

Yes. current climate change will most likely increase the amount of cultivable lands on Earth. However, it will at a high social cost and at the expense of biodiversity, and I can't emphasize enough the paramount importance of biodiversity for the heath of ecosystems and human food safety.

Consider also that similarly to mining, where the value of a deposit is related not only to the total amount of mineral but also to its concentration, we have to consider also how intensive is the food production allowed by a piece of land. In this regard, climate change can lead to the loss of highly productive areas, compensated only by the gain of large expanses of nutrient poor soils in the tundra.

You should also consider the social impacts of the degradation of current cultivation lands and the economic costs of moving food production pole-wards.

To answer this question with some degree of certainty is extraordinarily complex, because we don't know how exactly climate will change, but several studies have addressed this problem. A good example is The global distribution of cultivable lands: current patterns and sensitivity to possible climate change. There they point that:

  We estimate that climate change, as simulated by global climate
  models, will expand cropland suitability by an additional 16%, mainly
  in the Northern Hemisphere high latitudes. However, the tropics
  (mainly Africa, northern South America, Mexico and Central America and
  Oceania) will experience a small decrease in suitability due to
  climate change.

Figure 4 of the paper shows the current "land suitability index" worldwide.

You can see how the north of America and Eurasia show large expanses (although quite exaggerated by the map projection) of land not suitable for cultivation due to the cold temperatures.
This data can be downloaded here, and I've used it to plot the following figure that shows the mean cultivation suitability index as a function of latitude. It is also plotted the land area as a function of latitude as derived from ETOPO:

As you can see, pole-wards of 56° there is a significant amount of land of which none is suitable for cultivation. However, it is clear that temperature is not the whole picture, and aridity around 25° of latitude can significantly drop cultivation suitability.

I found interesting to see that the left (equator-wards) side of the main peak in cultivation suitability currently at 37° lies at a latitude with a lot of land, so if that end is lost to aridity, the gain of land on its (right) pole-wards end will be smaller due to the downwards trends of land area towards the pole. Nevertheless, as I mentioned, models suggest climate change will increase the overall land surface suitable for agriculture.

Another study: Northward shift of the agricultural climate zone under 21st-century global climate change. Focus on temperature and shows in Fig. 1 how the line that divides temperature regime suitable from cultivation of cereals will migrate northwards under the projected climate change:

However, they highlight the challenges for cultivation in high latitudes, which present a much more dramatic seasonal contrast that traditional crop lands:

  By 2099, roughly 76% of the boreal region might reach
  crop feasible conditions, compared to the current 32%. The leading
  edge of the feasible conditions will shift northwards. However, most of the
  newly gained areas are associated with highly seasonal and monthly
  variations in climatic water balances, a critical component of any
  future land-use and management decisions.

[the cite above was edited for simplification and context]


Get atmospheric pressure values through JavaScript

There are some problems with your request, and maybe some misunderstandings.

Misunderstanding: You actually need more than pressure to get wind vectors. Wind speed is nonlinear, and is dependent on more than just wind. Even if you had observations of pressure, that will only tell you how the wind is changing due to the pressure gradient force, and not due to things like transport, diffusion, or Coriolis force, especially at the resolution you are requesting. Fortunately, wind observations are much easier to get than pressure observations, so that lies in your favor. You could use satellite data to get wind data, or near the surface.

Problem: Observations aren't really on a structured grid (unless you are working with satellite data, which has quality problems), nor are they available at the resolution you want. You may be able to use model data or reanalysis data, but even the resolutions you request may not be sufficient.

You can interpolate down to whatever resolution you want.

If you want near realtime model data for Europe, try the GFS model from the WPC. You can try to get data from the ECMWF (perhaps they have data sources I am unaware of), but their data is proprietary. You may also want to use a grib reader to access the data. If you are familiar with Python, you can use pygrib. Or you can refer to the ECMWF recommendations on reading grib files. I'm a little unfamiliar with satellite-derived products, so I can't really help you there.


I agree with the comments; some upfront research would be good here, even at a basic level.  A good place to start is this Wikipedia article, which gives not only atmospheric heights but also other characteristics such as composition and the behavior of molecules.
In terms of heights the Wikipedia article suggests 700 km for the lower boundary of the exosphere, versus 1600 km in the question. Neither figure is really wrong because, of course, when you're dealing with atmospheres there is no hard and fast boundary between layers.
Similarly, the 10,000 km altitude given for the top of the exosphere, where it merges with the solar wind, is not hard and fast either; it depends on how you decide where the solar wind becomes dominant over the molecules bound by Earth's gravity.
Moreover, the outer boundary of the exosphere, however you define it, should not really be considered spherical.  The solar wind moves outwards from the Sun, so the exosphere is compressed on the side facing the Sun and pulled out like the tail of a comet on the opposite side.  The same effect is seen with our (and other planets') magnetosphere, because the solar wind also contains electrically charged particles.
I hope I've whetted your appetite for more in-depth exploration.  Good luck!


Why would India have so much thorium on its beaches?

why would India have so much thorium on it's beaches...?

Because monazite. Monazite is a rare earth element phosphate, with the formula CePO4 (where Ce stands not only for cerium, but all of the are earth elements and yttrium as well). It is one of the main ore minerals for the rare earths. It's a very common mineral in granites and similar rocks, and it's very resistant to erosion.

Therefore, it commonly accumulates in placer deposits, together with other resistant minerals such as quartz, magnetite, zircon, rutile, etc. Essentially, nature breaks down the rocks and concentrates those minerals in mineral sands (sometimes known as black sands). These sands are not unique to India, and many examples can be found across the world. Essentially you find them where ever you have sandy beaches developed in areas of granite mountains (in the case of monazite).

Why thorium? Because monazite shares the same crystal structure with a mineral called cheralite: CaTh(PO4)2, and the two components (monazite and cheralite) can exist in the same mineral via solid solution. Some monazites can contain 20 and 30% thorium! Granite-derived monazite is particularly rich in Th, unlike carbonatite-derived monazite which usually has little Th. The Th is usually an unwanted by-product, with monazite mined primarily for the rare earths. But, if you're looking for the Th - this is something that you actually want.


Doesn't increased human activity add to heating the atmosphere directly?

It does, but globally it's negligible compared to other heat flux densities.

Simply do the math:

World wide primary energy consumption: 162,494 TWh (2018)
Hours/year (2018): 8760 h
Earth surface: 510,100,000,000,000 m²

Assuming all this energy is transformed to atmospheric heating, this is an average heat flux (q=E/t*A) of 0.036 W/m². Locally this varies widely depending on climate (and the necessity to heat or cool buidlings), the degree of industrialisation, the population density etc. One figure I've found in Wikipedia for Germany: 1.2 W/m², Antarctica obviously: more or less 0.0 W/m², Hongkong (2018) 40.2 W/m² (calculated myself). BTW the average geothermal heat flux is 0.087 W/m².

Compare this to the solar contant: 1361 W/m². Considering albedo, day & night etc. the average (solar short wave) flux density on Earth's surface is ~ 175 W/m². The atmospheric back radiation is ~ 300 W/m².

So the average solar short wave flux density on Earth's surface alone is ~ 4,850 larger than the heat flux density directly induced by human energy consumption.

The heat flux density indirectly induced by human energy consumption (CO₂-, CH₄-, N₂O- etc. accumulation in the atmosphere) currently adds up to netto ~ 2.3 W/m² additional back radiation, which is roughly 60 times larger than the directly induced heat flux density.

Conclusion: direct heating of the atmosphere caused by energy consumption is almost insignificant compared to other effects.


What usually happens is that moisture laden air is blown toward mountains and forced to climb higher. As it rises, it tends to  become colder and less dense, so can hold less moisture. The surplus moisture is often precipitated in the hills or mountains, so when the air passes beyond the mountains there is much less rainfall. This is known as rain shadow. Here in Hereford UK we have plenty of rain, but not nearly as much as some places in the Welsh hills which lie 20 miles to the west of us, so I think we benefit a little from rain shadow. It was my experience in Borneo that there was more rain in the hills than at lower altitudes, but whether this holds true for the summit if Mount Kinabalu, which is over 12,000 feet high, I am not so sure. Probably not. More likely the rain is precipitated on the lower slopes.


Is Mount Everest currently becoming taller or shorter every year?

According to one survey using GPS mounted on a plateau below the summit, Mount Everest is increasing its height approximately 4mm each year.

As for plate techtonics, this site describes it pretty simply:

  Much like a car crashing head-on with a truck, crumpling occurred when the two continents met and the result was the creation of the Himalayan Mountains. Although the northward drift of India slowed dramatically with initial collision, the two continents have continued to converge as India slides under Asia.


Is there a way to approximate the density of air during rain?

Air without rain has a mass of about $\ce{1200 g/m^3}$ at 20°C.

You can figure out the amount of water in falling rain if you know the rate of accumulation (how much rain falls through a given volume in a given time, landing on the ground) and the velocity of the falling rain.

Here's a link to a post elsewhere on this same question. In that discussion, they assume a rainfall rate of 1 inch (2.54cm) per hour, and estimate a raindrop's terminal velocity (from observation) at about 9 m/s. They divide that rate by that velocity (converting units), and come up with about $\ce{3/4 cm^3}$ of water per $\ce{m^3}$ of rain.

So, given those assumptions, the density of (rain + air) is about .06% higher than the density of air without rain. Interestingly, that's much less than the difference in density between dry and humidity-saturated air (about 1% at 20°C). In other words, air at 100% relative humidity with heavy rain falling through it is still less dense than dry air.


What are the benefits of using conservative temperature in oceanography?

The TEOS-10 manual, page 26, says that the potential temperature is the temperature that a parcel of fluid conserving its Gibbs energy and absolute salinity would have if brought to the surface, or from an integral of the adiabatic lapse rate. The conservative temperature is not a true temperature, but a multiple of the enthalpy. It's really an energy that's been scaled to have units of temperature. The scale factor is the heat capacity of water in a standard state, since it's taken to be constant. In the potential temperature, the heat capacity is allowed to vary during ascent.

This distinction crops up a lot in meteorology, where the moist static enthalpy is conserved under adiabatic ascent, whereas other measures of temperature aren't conserved. I think the reason for the change is similar to why we would use enthalpy in meteorology, too. Suppose that the adiabatic changes in pressure and temperature also change the equilibrium coefficients of some reaction, say $\ce{CO2 + H2O -> H+ + HCO3-}$. This would change the absolute salinity, since it's splitting apart a water molecule into ions. The actual ascent can be adiabatic - there's no mixing with the surrounding water - but it's no longer isohaline. The enthalpy will still be conserved, though. This is why I think your questions (here's the other one) are related: using a mass-based salinity fits in much better with a thermodynamically-consistent formulation of the Equation of State, and using the enthalpy over the potential temperature is part of this complex salinity-temperature-entropy relationship.

The manual mentions that near the surface, the differences between potential and conserved temperature should be really small. The heat capacity chosen to scale the enthalpy is similar to that for surface water. You'd get the largest differences at depth and where the composition of seawater is much different (like with absolute salinity). The difference here is whether that composition is expected to change with temperature and pressure.


What would change if our earth lacks mountains?

Well, mountains are not a cause. Mountains are an effect. It's not that we have earthquakes because we have mountains. We have mountains because we have earthquakes.

  Earth as we know but without mountains (mountains have never been formed or don't exist at all)

So by saying that mountains never existed at all, you are implying there are no tectonics. That would be a sad thing - one of the things that make Earth so alive and interesting is the fact that we have plate tectonics. Go and have a look on Mars, the Moon, etc. There are no active tectonics there are those are dead places.

  What will happen if the Mountains would just been taken away?

They would just form again. First of all, there would be the effect of isostatic rebound. When you take away a certain mass from an elastic thing, that thing bounces back up. When you're sleeping on your bed, there is a dent in it. When you get up, it springs right up. This will happen also in the Earth. It is happening actually as we speak - certain places in the world (Scandinavia is one example) that are slowly rising because the huge ice sheets that existed during the last ice age melted. That said, India is still colliding into Asia and the Mediterranean is still closing so you would get more Himalayas and Alps. Plates are still subducting so you you will get volcanic arcs such as the Andes or Japan. It will take some time, but the mountains will come back.


How much energy released by the Theia-Gaia impact?

Here's a quick-and-dirty estimate.
The gravitational self-energy of a uniform-density sphere is
$$
U = \frac35 \frac{GM^2}R
$$
Let's assume Theia had the same mass and density as Mars, and that Gaia contained the rest of the mass of the Earth-Moon system.
The binding energies for the four bodies are then

theia/mars 4.82e+30 joules
gaia       1.90e+32 joules
earth      2.24e+32 joules
moon       1.24e+29 joules

You can see that Theia and the Moon contribute to the binding energy starting the third significant figure: moving the 90% of Theia's mass to Gaia, leaving us with the Earth and the Moon, must have released something like $0.3\times10^{32}\rm\,J$ of gravitational binding energy as heat.

Kinetic energies due to Earth's rotation and the Moon's orbit are irrelevant compared to Earth's binding energy --- the biggest contributor there is $0.25\times10^{30}\rm\,J$ associated with Earth's daily rotation.
It's probably safe to assume the same about the progenitors.

Apparently a teraton of TNT is $4\times10^{21}\rm\,J$, if you insist on that comparison.

Note that I've assumed nothing about the geometry of the collision, whether it was head-on or glancing. I'm only making assumptions about the (well-known) final state and the (poorly constrained) initial state.


Would the subsurface event leading to tree death at West Tern Lake in Yellowstone be visible in thermal imaging?

If it’s hot enough to alter the groundwater chemistry that is killing the trees, then you would see it in satellite thermal imaging. Remember, tree roots only go down about 20 to 30 feet at the most, so this is all pretty shallow stuff. This is actually quite a strong thermal anomaly. Like you said, the heat alone may have killed the tree/tree roots.the white areas of the photos are likely salt deposits from the thermal water left behind after evaporation. So again, the thermal water is shallow, indeed, it’s right at the surface. Pretty cool.


Are Argo probe data used for numerical weather prediction (NWP)?

One of the issues with ARGO data is that in most cases it does not provide data from the real surface of the ocean. When they ascend from their drifting depth (usually at 1000 or 2000 meters) to the surface, most of them stop recording at a depth of around 5 meters from the surface. From SeaBird (the company that provides the CTD sensors in most ARGO floats, SSalOceanSciencesMar08-5Pages.pdf): "...to avoid degrading the salinity accuracy by ingesting sea surface contaminants, the pump is turned off at approximately 5 decibars beneath the surface as the Argo float ascends." This creates problems when assimilating into atmospheric models because of inconsistencies between the satellite-derived sea surface temperature and the ARGO temperature at 5 meters. To address this issue and provide better surface flux information, some ARGO floats are equipped with a second temperature and salinity sensor (STS) that only measures in the proximity of the surface.


Aren't fresh water deposits renewed by the water cycle?

Rain water is still one of the most cleanest water sources available. There may be some ancient underground aquifers that have clean uncontaminated water.

One issue with rain water is that atmospheric moisture - part of the water cycle - needs to condense on aerosols in the atmosphere before it can develop into rain. With the amount of pollution humans are dumping into the atmosphere some of that can form the aerosols that eventually develops into rain thus making rain water dirtier than it used to be - such as acid rain being formed when sulfur dioxides are dumped into the atmosphere when high sulfur coal is burned in power stations. Other aerosols include salt from the oceans.

The other issue with rain water is that the soil in water catchments can be contaminated by pollution. Rain falling on the catchments can absorb some of the contaminants thus making the rain water in the resultant catchment dirtier that it might have been in the past.

Regarding the rate of urine production of animals, it depends on the type of animal. A mouse will process water at a different rate to an elephant or domestic live stock. It is also influenced by circadian rhythms for each type of animal.


How accurate are the resistivity values from the electrical resistivity tomography (ERT)?

Inaccuracies are inherent based on a wide range of variables. In particular, the array type, as well as the inversion will affect the resistivity of any layer or body.

Interpreting data based purely on apparent resistivity isn't a good idea at all! You should always try to invert the data to produce realistic conductivity distributions.

The inaccuracies are caused by the path of the current through the Subsurface. This is why the array will affect the final result (different configurations drive current in different ways). Something unusually conductive will divert current towards the body, while resistive bodies will divertv away.

To better estimate the Subsurface resistivity, you can constrain the inversion with prior knowledge. For example, sharp high contrast boundaries, which can affect the recovered values quite significantly, can be incorporated into most inversion algorithms to (usually) enhance the accuracy of the result.

To answer your question, the inaccuracy is a product of the physics - instrumentation can only do so much before the physics kicks in.

Hope this helps! (Please correct me if/where I'm wrong too!)


Three methods spring to mind:

1) If you can really estimate both the width in degrees and distance to the cloud, you can draw a triangle and use trigonometry to calculate the width.

2) The distance to the cloud you may estiamte from the cloud type. But both height and width in degrees are uncertain numbers. Instead you can estimate cloud sizes by looking at planes passing through them. If you time how long it takes a plane to pass through a cloud, you can multiply that with its cruising speed to get the width of the cloud. The cruising speed (typically 500km/h) can be found via say, the Flightradar24 app.

3) Using that app, you can also track the plane in real-time to map out not only the length of the cloud, but what land it is covering. No need to time the plane or know its speed.

By following a plane on the app until it goes under the horizon at your location, you get a feel for "how far away the horizon is", for clouds at that plane's altitude. high-altitude clouds and aurora at the horizon will be much farther away than low-altitude clouds.


What causes the counter-intuitive presence of CO2 in the atmosphere during spring and summer months?

From Scripps:

  [The] latitudinal differences in fluctuation are the result of photosynthetic activity by plants. As plants begin to photosynthesize in the spring and summer, they consume CO2 from the atmosphere and eventually use it as a carbon source for growth and reproduction. This causes the decrease in CO2 levels that begins every year in May. Once winter arrives, plants save energy by decreasing photosynthesis. Without photosynthesis, the dominant process is the exhalation of CO2 by the total ecosystem, including bacteria, plants, and animals.  Two regions of Earth contain the majority of land plants: Northern Hemisphere continents and the tropics that encompass ... the vast rain forests of the Amazon basin. Near the equator, however, the seasonal variations in temperature are less pronounced. Seasonal swings in CO2 are therefore most pronounced in the Northern Hemisphere, where the seasonal changes in temperature result in very large differences in plant photosynthesis from summer to winter.

My interpretation of the slide-graphic confirms the idea that more CO2 exists earlier in the springtime, especially in the Northern Hemisphere.  There are darker reds (~403 ppb) over most of the northern latitudes in March/April

and more of an orange-yellow color in June (~400 ppb).

In general, I would caution you in putting too much meaning into graphics that NASA develops such as these.  These graphics are made by concatenating a couple weeks of satellite overpass data (generally one to two retrievals per pixel).  These are not an "average" like you might think.  This is because the swath of the instrument detection is very thin, thus requiring weeks to get "global coverage".  Furthermore, the OCO CO2 algorithms are still being refined, and will go through several more revisions before the data is "finalized".


Oh boy, a thorough understanding will be difficult, because reading these things to their full potential can take 10+ years of experience... If you really want to dive into it, read a book on seismic (exploration) geophysics -- this is the main reference book in the field: https://wiki.seg.org/wiki/Seismic_Data_Analysis .

The best way to understand the picture is to understand how the data came to be:

The subsurface consists of layers (and other shapes) of varying density and compressibility, leading to different wave speeds. For example, mechanical vibrations (=seismic waves) move with a different speed through sand than through granite, ...
Take a famous model, the Marmousi model:

This model has variations in the velocity (low velocities at the top, faster towards the bottom), with all kinds of geological features: faults, folds, uncomformities, ...
The seismic company creates an explosion to create a seismic wave that propagates through the model, and at every interface where the seismic properties change (called the 'acoustic impedance'), a reflection is created. However, the company only records the signal at the top, the same level where it created the seismic wave:
https://www.youtube.com/watch?v=U0hT9vO_oHA ; on the left you see the wave move into the Marmousi model, reflecting off every impedance change; on the right you see the data that is recorded at the receivers, with the color specifying a contraction or an extension (any wave creates both extension and contraction, never just one: https://www.youtube.com/watch?v=2rYjlVPU9U4 )
Actually, the recording consists of individual receivers which record individual traces, it's just interpolated and turned into a black-and-white image in the video:

Eventually, through careful and computationally intense algorithms, the recorded data is turned into a stack and is 'migrated', such that the recorded data is 'imaged' at the approximate location of the reflections in the subsurface. When still using the individual traces you get:

The traces are now SO close together that it almost becomes a black and white image. And this is where the colors come in, the same section may be displayed as:

where the positive (right-ward, black) trace has been replaced with RED, and the negative (left-ward, white) move of the trace has been replaced with BLUE, and white as the intermediate color.
So, for the Marmousi model, people can make these type of images:

you see how it looks similar to the true model -- but is still generally much noisier, particularly for deeper reflections further down the image? In principal, the red/blue color corresponds to an increase or a decrease in acoustic impedance, but it's sometimes tough to see these things clearly...

Hence, the image that you have is probably a migrated stack, varying from extremely light blue to dark blue to grey to red to yellow. The z axis corresponds to (approximate) depth, the x axis corresponds to receiver positions/offsets. All the lines are contrasts between rock types that have been geologically deformed, either a positive or negative impedance contrast. Features of interest to geologists are too numerous to mention, but of basic interest are (1) tracking a whole line over the entire image to see the continuity of a single reflecting unit, (2) seeing a fault -- where a reflector breaks and picks up a bit below, (3) finding really intense ('bright') spots in the data, (4) finding salt, e.g., as done here https://www.kaggle.com/c/tgs-salt-identification-challenge/ ...

But yeah, demand more information from whoever wants you to do this work about what features are of interest because there's too much in the image to just blindly start learning things...


Why is my ♦ hammer (i.e. diamond) so durable, but it can burn?

It is bond strength, not hardness, that determines how easily oxygen
  can attack and burn a material, allowing me to burn a diamond in a
  pool of liquid oxygen resting in a block of graphite.

Diamond is hard because its bonds form an inflexible, three-dimensional lattice. However, the strength of these bonds themselves is not even as strong as graphite, for example. Graphite has much stronger bonds, but they create "sheets," which can slide around, making graphite softer but harder to burn.

(source)

Indeed, people have burned diamonds before by putting them in tubes of pure oxygen.


I've never heard of the 'Mulligan river', and neither, apparently has Google Earth, (apart from the Australian Mulligan). However, there are some obvious features of the Sebaskatchu River on Google Earth that one might note. As background, 11,000 years ago the Earth was just beginning to emerge from the last ice age, so ice cover was very much greater, and sea level was very much lower, so I assume that the +135 metre lake level to which you refer is relative to today's sea level, consisting of a temporary glacially dammed lake level. These ancient lake shore lines are a common feature of glaciated terrain, as may be seen in Alaska, Scotland, Norway and New Zealand.

All lakes are relatively short-lived in geological terms, being effectively sediment traps. Sediment accumulation in the lower Sebaskatchu river basin has been intense, and has all but filled the entire lower basin. This is most obvious from the extreme river meandering, which occurs only wherever there is a high sediment load combined with a low hydraulic gradient.  There are two phases of sediment fill - a general fill over a large area, and a specific small lake fill which you can see about 6 km (as the crow flies) from the river mouth, and for about 8 km further upstream.

You may note that none of the lower basin drainage is guided by the bedrock, whereas the upper basin, presumably above your threshold of +135m, is of a different style, This upper drainage is partly guided by the underlying rock structure, i.e. along strike, and partly by a cross-cutting component. The latter is most likely 'superimposed drainage', which has cut down through ice and glacial drift into the bedrock.


Present earthquakes create new mountains, former earthquakes created old mountains.
Hence, the Alps are older than the Appenines. In the past surely the Alps had more earthquakes than now.


What is the difference between N-MORB, E-MORB and OIB?

The nomenclature is confusing and recent studies have shown that among mid-ocean ridge basalts (generally called MORBs) that  normal mid-ocean ridge basalts (NMORB) should reflect the statistically usual composition while enhanced MORB (EMORB) and depleted MORB (DMORB) should reflect end-members of the MORB population.  Gale et. al 2013 proposes the use of the term NMORB to refer to the most likely basalt composition encountered along the global ridge system distant from hotspots. The NMORB is given by the lognormal mean of the compositions of ridge segments more than 500 km away from plumes excluding back-arcs.  Contrary to some literature discussion,  NMORBs are NOT depleted in trace elements according to this Gale's work and so linkage between the idea of depletion and NMORBs should be broken.

Gale et.al propose the term DMORB to recognize trace element depleted basalts. DMORBs would not be considered representative of the upper mantle or ocean crust nor would they be commonly found in ridge systems.  Finally, EMORB would refers to incompatible trace element enriched NMORBS via a statistical definition found in Gale et. al.  This statistical definition is due to the fact that current data does not allow clear spatial linkage of EMORBs to any particular form of ridge or plume system or island located near to both.

A good example of an EMORB system is given by Iceland where the rate of magma production has caused volcanism to build the oceanic ridge above sea level.  In this environment, the predominant basalts are also tholeiitic basalts, but there are higher concentrations of incompatible trace elements. EMORBs are enriched in incompatible trace elements such as K, Ba, La, Rb compared to NMORBs.  By incompatible, one means elements that do not fit easily into the crystal structure of mineral elements in the mantle and are usually not found in upper mantle derived rocks because they are preferentially ejected into the melt.

See this paper The mean composition of ocean ridge basalts - Gale - 2013 for a detailed discussion.

Generally, all MORBs are tholeiitic basalts occurring in oceanic spreading centers, such as an ocean ridge away from hot spots and back-arc basins. At these spreading centers, a relatively small range of chemical compositions of basalts are erupted to form the basaltic layer of the oceanic crust.  The main melting mechanism is likely decompression melting due to rising convection cells moving upward through the mantle beneath the ridges. The composition of these basalts typically ranges from olivine to quartz tholeiites. Tholeiitic magmas are sub-alkaline, meaning they contain less sodium and potassium than other basalts and can be distinguished from other basalts by the redox state of the magma from which they crystallized—- tholeiitic parent magmas are reduced whereas calc-alkaline parent magmas are oxidized.  All three NMORBS, DMORBS, and EMORBS share common chemical compositions (ordered by decreasing wt%) of SiO2, Al2O3, MgO, FeO, CaO.  They also share a common mineralogy of plagioclase, pyroxene and olivine. The plutonic equivalents to a tholeiitic basalt are diorite, gabbro, and anorthosite.

For the next section, this is a great reference!

Oceanic Island Basalts –basalts associated with islands in the ocean basins that generally occur away from plate boundaries, and are often associated with hot spots.  Most oceanic islands appear to be related to ascending plumes of hot mantle which operate independent of the main convection cells that ascend beneath ocean ridges and descend at subduction zones.  A wide variety of rocks occur in these islands, not all are basaltic, but all appear to be related to upper mantle melts.  One may find tholeiites, alkaline basalts, Hawaiites, trachytes and rhyolites in an OIB environment which span the compositional spectrum of magnesium, iron and the alkaline elements. From a melting perspective, low pressure environments tend to produce the tholeiitic magmas and high pressures are required to derive alkali basalts.  OIB mantle sources are enriched in incompatible elements and demonstrate a wider variety fractionization than MORBs. How does this occur?  a recent theory for OIB sources posits that subducted lithosphere sinks to the core/mantle boundary and mixes with the mantle to produce an enriched mantle which heats and rises in narrow plumes which channel this enriched mantle melt upward producing hotspots which produce the compositional variety of OIBs observed.


Where is the hot air for Australia's record spring heatwave coming from?

There are 2 causes of record high daytime temperatures: insolation and subsidence. As air is forced to subside, heat of compression adds to insolation. This happens at the poleward margins of the tropical Hadley cells, at or near the latitude where the deserts of Australia are located. Cloud cover (or dustiness in deserts) contributes to record high nighttime temperatures by trapping infrared radiation from the Earth.


NOAA has climate division files in netcdf and shapefile format, though they may be just CONUS:

http://www.esrl.noaa.gov/psd/data/usclimdivs/boundaries.html

The most promising link looks like this source with paper citation below.  They have lots of freely available data in a variety of formats:

http://koeppen-geiger.vu-wien.ac.at/shifts.htm

Rubel, F., and M. Kottek, 2010: Observed and projected climate shifts 1901-2100 depicted by world maps of the Köppen-Geiger climate classification. Meteorol. Z., 19, 135-141. DOI: 10.1127/0941-2948/2010/0430.

There's also the ArcGIS Online map service that has Koppen-Geiger Observed and Predicted Climate Shifts:

http://www.arcgis.com/home/item.html?id=0b9f1f90f4f745daacbc35599609b59a

To answer your question about the types of temperature in a classification,  I suggest you refer to the paper above and the ranges of expected temperatures for each Koppen climate type which can be found here: https://en.wikipedia.org/wiki/K%C3%B6ppen_climate_classification

For modeled and observed temperature, precipitation, etc. you might find the following resources helpful:

http://iridl.ldeo.columbia.edu/

http://gisclimatechange.ucar.edu/

http://www.worldclim.org/


What (if anything) can be learned from accurately recording tilt motion during seismic events?

The intent with this (very, very cool) device seems to simply be to improve hazard assessment and mitigation by providing higher resolution motion data.

It reminds me of tiltmeters used on volcanoes. These devices measure changes in the flank slope of a volcano in order to assess volatility and risk (how the magma chamber is developing, etc.).

This kind of technology isn't new, but it's only been available in a precious few places. The ROMY will be able to cover a wide area, but the real holy grail is to have many mobile stations that can record local movements worldwide (as they mention in the video).


Is there a way to guess if its going to rain based on pressure temperature humidity and cloud cover

If you live in a part of the world where the rainfall is dominated by frontal systems, and mainly by cold fronts, then there is a rough inverse correlation between pressure and rain. Otherwise, no. As Gerrit pointed out, rainfall is a whole lot more complicated than that. If you are looking for something to correlate with rain then I suggest you look into satellite-based cloud-top temperatures. The supercooled temperatures at the top of cumulus towers does correlate tolerably well with rainfall.


Is there any correlation between Australia's uranium deposits and the unique animals?

No. The reason for Australia’s unique evolution is that it was relatively isolated from the rest of the world.

Australia isn’t too radioactive either. The fact that it has more uranium deposits than other countries is that it’s huge.


Calculating Solar Noon from Sunrise and Sunset

Received an answer on the astronomy stack. https://astronomy.stackexchange.com/questions/22239/getting-solar-noon-from-sunset-and-sunrise/22241#22241

The short of it is that yes, this is reasonably accurate for most geographies, but can vary significantly in polar regions. For most cases, middling the difference of sunrise and sunset is sufficient.


You can compare verification scores using this application from ECMWF made from guidelines by the WMO. The example below fits nicely with what is widely known, namely that IFS (the ECMFWF global model) scores generally best. In recent year the UK Met Office global model have also scored better than GFS. The figure shows the root mean square error of MSLP.
The example below of course only covers verification for one month, so you should examine longer periods and focus on the fields you are most interested in.


Here is a thermal profile of the borehole:

(Source: Fig 5 in Yuri A. Popov, Sergei L. Pevzner, Vyacheslav P. Pimenov, Raisa A. Romushkevich,
New geothermal data from the Kola superdeep well SG-3,
Tectonophysics,
Volume 306, Issues 3–4,
1999,
Pages 345-366,
ISSN 0040-1951,
https://doi.org/10.1016/S0040-1951(99)00065-7.)

This borehole is (almost) vertical and not an angle, so its depth is true (11662 m) and it is quite warm down there, around 180 degrees Celsius as shown in the above figure. I assume temperatures were similar in other shafts drilled at maximum depth at 12262 m.

The equipment they used initially for the 1982 borehole down to 11662 m was made to be able to work in thermal stability up to 200 degrees Celsius (Source: Kozlovsky, Yevgeny A., and N. I. Adrianov, eds. The superdeep well of the Kola Peninsula. Springer Berlin Heidelberg, 1987.) Consequently I assume the equipment used for the later shaft that reached 12262 m was of similar or better make than the original.

The problem is not the temperature against the barrel only: there is heat due to the shear (rotation) and let's not forget the weight of the shaft down the base. This is why the thermal stability of the system is to be considered in addition to the resistance of single parts of the drill system. So while hotter than they expected, it was within the operating range conform to the specifications of the make - but yet very near the thresholds and thus problematic.

The problem lied also with the rock being more and more plastic deep down in the borehole, due to pressure, porosity and water, making it a very difficult challenge to keep the borehole open each time the shaft need to be replaced or removed, adding difficulties to this already never-been-done-before project.

So this sum of challenges are probable reason why the project was interrupted before reaching the initial goal of 15 km.


What is the geochemical source for the helium detected in deep Arctic explosive eruptions?

Helium is formed through the radioactive decay of uranium 238, uranium 235  and Thorium 232. A helium atom is an alpha particle that has collected electrons. The only way that helium is produced on Earth is by such radioactive decay deep underground.

Generally, the helium travels along cracks until it reaches a subterranean cavern where it accumulates.

Yellowstone National Park in the US is leaking helium.

Quoting from the website http://www.yellowstonepark.com/2014/02/helium/

  the gas is gurgling up from a store that’s been trapped in the Earth’s core for up to 2 billion years. Scientists believe that the
  helium began its exodus up from the depths roughly 2 million years
  ago.

  The helium was initially released when a “hotspot” of collected magma
  fought its way to the Earth’s surface and caused a series of volcanic
  eruptions, the most recent of which occurred 640,000 years ago.

The helium being release at Gakkel Ridge would be of a similar origin and it appears to be released in a manner similar to what is happening at Yellowstone NP. The article you provided a link for also states that carbon dioxide is being release at Gakkel Ridge, which is not inconsistent with the volcanic activity of the ridge.

From the website http://www.helium-corp.com/facts/heliumfound.html

  Carbon Dioxide is also found in some helium-bearing formations but the
  presence of this gas is primarily due to its proximity to ancient
  volcanic activity.

Other website that may be of interest are:
http://www.pa.msu.edu/sciencet/ask_st/051095.html

http://www.anl.gov/articles/underground-helium-travels-earth-s-surface-aquifers-new-study-says


Before the artificial changes of the Aral Sea, what was its average depth and salinity?

From the link provided by Keith McClary, the Aral had a salinity of about 1% and a max depth of 69 m. (Could not find average depth in the article.)

The Caspian Sea, on the other hand, has a salinity of about 1.2%, max depth of 1,025 m, and average depth of 211 m. I think this is enough information to say that the Aral was not just a smaller version of the Caspian, unless your main criteria is salinity.


What is a source of worldwide temperature data that also includes extreme weather?

CLIMDEX, the "Datasets for Indices of Climate Extremes" is probably the closest you are going to get, for any pre-computed indices. The 27 indices it includes are listed on the indices page of that site.

Unfortunately, it doesn't include anything like "coldest 3-day average per year", let alone "coldest 3-day average over the last 5 years". I doubt there would be any pre-built dataset with exactly that index, and there is unlikely to be online tool that would calculate unusual indices, because the data sets are huge (HadCRUt4 is 20MB for monthly data over the last 150 years), and unusual indices would have to be calculated on the fly - something that's just not feasible on the 'web.

I would guess that you'd have to calculate that yourself, from a raw daily temperature dataset. Unfortunately, I don't think such a thing exists on a global scale. However, a reanalysis product like the NCEP/NCAR Reanalysis is probably good enough for your purposes. However, you'll need to be familiar with large data analysis - the daily surface temperature dataset is over 450MB.

Depending on your exact usage requirements, you might be better off just looking up some of the historical records for neighbouring meteorological stations and using those.


What fraction of Earth's crustal material survives the supercontinent cycle?

There is two parts to this answer, first continental crust tends to persist and oceanic tends to be recycled. This is largely due to density, continental crust is less dense and tends to "float" compared to the mantle and is very difficult to push back into the mantle for remelting. Only a tiny fraction of continental crust ever gets subducted mostly as sediment on oceanic crust, so basically by piggybacking on subducting oceanic crust. This is why continent to continent convergent boundaries form mountains with no subduction, they can only push down by pushing even more material up, in effect packing together like wads of compressing clay.

Second continental crust is reworked by other processes, erosion, faulting, rifting, mountain building, metamorphic processes, etc. These are regional effects and thus more random, so how much they alter can vary quite a bit from continent to continent. Exposed un-reworked continental crust is rare but this is due to the accumulation of events reworking smaller regions and the tendency of sediment covering it up. There is much more unexposed old continental crust buried under the sediment, often referred to as the shield portion of the craton, Shield is the portion of the continental crust that is not sediment and is not tectonically active (even some shield is partially metaphorically altered, but this is where you find unaltered material) There is quite of bit of ancient shield (brown in this picture) although it still makes up a small percentage of the overall continental crust. Even then only a fraction of it has survived all the continental cycles and is completely unaltered since the first continents formed.

This image illustrates how much of the oldest continental crust is still around(purple).

Basically oceanic crust is guaranteed to be reworked eventually, check the age of oceanic crust, while continental crust has a more random factor involved meaning some in the more stable regions of some continents has not been reworked. That is why they are only small scattered areas.


Does depletion of Planck radiation intensity in the upper atmosphere mean that "CO2 has no impact on climate change"?

Talk of Schwarzschild radiation integrations negating the effect of CO2 in atmospheric warming is just mumbo jumbo on a par with creationism, but there is a danger of going too far in the other direction. Carbon dioxide forms 0.0325 percent of the atmosphere, and although a slight increase has been recorded in the past 100 years and attributed to human activity, this increase is infinitesimally small. Whenever I say that climate warming began 12,000 years ago it is always very unpopular, but it nevertheless happens to be a fact. There is unanimous agreement among scientists that the small amount of CO2 in the atmosphere helps to warm the Earth, but where there is less agreement is on the question of whether the minute increase since the industrial revolution has measurably accelerated the climate warming which had already been underway for 12,000 years. Another unpopular idea which also happens to be a fact is that increased atmospheric CO2 causes plants to grow more vigorously, so to some extent increased CO2 content is self-correcting, but only up to a point. It could easily be overwhelmed if the CO2 increase is too rapid.


Some of the IPCC AR5 reports were written in LaTeX, some in MS Word. You will not be able to get the .bib files for those reports written using MS Word because Word does not use BibTeX.
Working Group I did use LaTeX, and you can get the .bib files for their report, on a chapter by chapter basis, here.
Working Group II apparently used Word, but they have released a set of bibliographies in both .csv and .xml format. I used "apparently" because I am getting errors galore for any page under ipcc-wg2.org. Apparently IPCC Working Group II has not updated their subscription, and some expletive deleted online gambling company has bought rights to that domain.


Cool, didn't realize that the GFS was on Github.
Looking on down the wiki, it seems like the "free-forecast" is associated with the deterministic model, while the "cycled" is associated with the Ensemble Kalman Filter. That is, the free-forecast is not constrained by data assimilation algorithms- it can just start from a restart file and go. A cycled run, however, needs multiple runs, as well as data.
This is all speculation based on naming conventions. If you really want an answer, perhaps asking the code developer?


Identification of rock formation along Wales coast

This is Marloes Sand Beach, a classical fossil site. The nicely colored rocks are sandstones of the Silurian age (around 425 million years old). The different dipping angles of the sandstone layers are a result of tectonic processes, which were folding the rocks.

Further information about Marloes Sand can be found here


What conditions could produce 50 km long lava tubes?

In Hawaii, the Mauna Loa lava tube from the 1859 lava flow

  enters the ocean about 50 kilometers (31 mi) from its eruption point

And in the Undara Volcanic National Park in Queensland, Australia

  Bayliss Cave is the remains of a lava tube that was once over 100 kilometres (62 mi) in length.

So a lava tube, 50 km long on the Moon, may not be that remarkable.

Additionally, The Undara field has feature call the Wall, which is a continuous ridge 40 km long and 20 m high.

  The Wall is believed to be the closest terrestrial analogue to the basaltic ridges seen on the moon. The longest lava flows in the Solar System are on Venus.


The climatological variance of albedo, soil moisture in weather models

WRF model development is done in such a way that users can run the model independently before you start adding more complex options to ingest observations.  There is even an "ideal" mode that new users can take advantage of to learn how the system works (not for simulating real Earth situations).  In "real" mode, there are typically two types of simulations done: a forecast or a retrospective (historical) simulation.  It's important to have real observations ingested into a retrospective simulation, since the intent is to model the event as best you can.  However, this is not possible in forecast mode, since the observations do not yet exist.  So, it is important to have default lookup tables that characterize your unknowns.

Regarding the values in the LANDUSE.tbl, there are many groups that use the monthly MODIS-derived values to ingest into their simulations that replace some of these values.  A "summer" and "winter" lookup table is provided for users in WRF, but those defaults are not appropriate for the best retrospective weather simulations. Forecasting, on the other hand, can use old satellite data (MODIS land-surface data is several days if not weeks old by the time it is processed) but that has error just as a seasonal average would.  The values in the LANDUSE.tbl (except surface roughness) will get overwritten with the VEGPARM.TBL values if you use Noah or the RUC Land Surface Model (LSM). Noah uses monthly values as far as I know. RUC might write values on its own... not really sure if it uses the VEGPARM.TBL or not. I'm sure there are experienced WRF modelers out there that can give you more detailed information, e.g. on the WRF modelers forum.


Perhaps the Global Significant Earthquake Database request form from NOAA would help?


They form due to strong convective forces, coriolis effects, local wind and weather, and local topography.  The fire effectively creates an intense localized low pressure cell due to the heating of the air which can behave similar to any low pressure system.  I haven't seen one on flat terrain like your picture shows but when performing slash burns for silviculture purposes you can have very large tornados form along ridges as the fire burns uphill.  These tornados can extend outside the fire zone under the right conditions but generally die out soon once removed from the source of heat.


Since CO2 concentration is responsible of temperature, that trend is related to the little ice age, where Earth cooled a little. Wikipedia article describes several possible causes for that, one of the is the answer of Keith, but others might be orbital cycles, solar activity, volcanic activity and ocean circulation.
Also is possible that is just a cycle that repeats itself each 1000 or 1500 years.