How does moveout correction work in seismic reflection profiling?

The offset is measured in meters, but the depth is still measured in time. The extra distance the wave have traveled to a longer offset is therefor also seen as an increased time in the CMP-gather (Common Mid Point) and the extra time depends on the seismic velocity of the layers.

If the velocities are high, the moveouts are short. The longer offset, the longer distance the wave have traveled through the layer and the larger moveout correction is needed before stacking. Sometimes we mute long moveouts as they tend to be distorted and noisy.

When we stack the traces in the CMP-gather, we need the reflectors to be at the same time and to do that, we perform NMO-correction (Normal MoveOut).

To find the right velocities to use for the NMO-correction, we can do a semblance analysis to get the NMO-velocity. That is to simply try possible velocities and see at what velocity the reflector in the CMP-gather is aligned horizontally and gives the highest peak when summed for all traces.

The figure shows a synthetic CMP-gather to the left. A semblance velocity scan is performed and the peaks are shown in the middle plot. The velocities are picked as shown in the graph and are used to NMO correct the CMP-gather as seen in the seismogram to the right. When this is stacked, the reflectors will add up and the noise will be suppressed. So in theory, we don't need the velocity beforehand to perform NMO-correction. The moveout can be used to calculate a NMO-velocity model.

The figure is from Madagascar development blog.

However, if we know the velocities, eg from borehole data or refraction studies, we don't need to rely on computing heavy semblance velocity scans and uncertain velocity picking. Data are rarely so neat as this synthetic example shown here. Also, it's impossible to derive the gradually increasing velocity in a formation without internal reflectors.

The velocity we use to do NMO-correction is not the same as the velocity of the layer, but rather the additional velocity to the average needed to correct the moveout. To finally estimate the actual velocity of the layer, we can use e.g. Dix equation to correct the velocities, but more accurate methods are usually used nowadays.

This is the basic application for stacking, but there is much more to it, you can read more e.g. here.


Which mountains (or hills) are visible from both Boston and Rhode Island?

As Boston and Rhode Island are whole areas more than points, the question is easier to answer the other way around: From which mountain you can see Boston and Rhode Island?

To answer the question I'll use the SRTM Digital Elevation Model at 30 meters resolution, and pick the following five mountains or hills that seem good candidates:

Shown elevations are the ones derived from STRM data. From each of these points I've made a view shed analysis. And for easier comparison I've put them together in the following animation:

In these view shed analysis, the areas in read represent the one that would be visible from the corresponding mountain or hill. As you can see, Blue Hill and Moose hill are visible from some parts of Boston and Rhode Island. So that chain of hills (including Tower Hill) is definitely visible from many parts of both areas.

For the mountains further inland as Wachusett Mt. and Monadnock Mt., they don't seem to be visible from the coastal areas of Rhode Island.


Does El Niño increase the amount of heat that escapes into space, or does it increase the amount of heat trapped on Earth?

During El Niño heat is transferred from ocean to atmosphere. If atmosphere gets warmer, yes, it generates more radiation and more heat escapes into space. The same about land surface - if it's warmer, it radiates more heat.

Of course that's all with assumption that there are no other factors influencing it - like e.g. greenhouse gases.


Why does every tsunami travel differently?

The answer to some parts of your question lie mainly in basic physics, there are a number of factors that will affect how a Tsunami will travel after the initial water displacement.

For example, is the initial displacement a point event (such as Tsunami caused by landslides), or an event occurring along a long line, such as the massive fault movement that caused the "Boxing Day" Tsunami of 2004.

A point event allows the water to spread out in all directions from that point, similar to ripples in a pond after a raindrop or pebble falls in, the energy is dissipated equally in all directions and therefore the water displacement - and thus the height of the breaking Tsunami wave - decreases rapidly.

Conversely, a linear event such as the "Boxing Day" tsunami doesn't allow the energy to dissipate equally in all directions, because at any given point along the wave-front, there is more "wave" to the 'left' and 'right' that prevent that dissipation. This allows the energy to be transferred over much greater distances, and allowing the water displacement to be preserved.

As for why some land gets passed by, this is usually an effect of the local topography, going back to the Boxing Day Tsunami example, the Maldives were less effected than they could have been because there was no continental shelf for the waves to encounter and build up on. Bangladesh and other countries north of the fault-line also suffered less than they could have done because the northern and southern ends of the fault acted like point-events, and the waves to the north and south dissipated much more rapidly than those to the east and west.


Physically there is no difference. A thunderstorm is defined by occurrence of lightning, no matter how much lightning there is, if it's cloud-to-ground or intercloud.
Usually if meteorologists talk about thundershowers in weather reports they want to point out that there will be weaker thunderstorms (e.g. without hail, storm, heavy rainfall or the danger of flash floods).


Amount of Earths water with consideration to space travel?

Everyone always says that there has always been, and always will be, the same amount of water on planet Earth.

Your premise is wrong. The surface and atmosphere of the Earth keeps gaining and losing water all the time. I have no idea where is that coming from, but no scientists say the amount of water is constant.

The Earth's atmosphere is leaking gas to space. This includes mostly hydrogen gas, which is a major component of water, and also some minor amounts of molecular water.
Earth is gaining water (and a bunch of other stuff) from meteorites and dust hitting the Earth. Dust accounts for the majority of the mass flux to the Earth.
The Earth's surface and atmosphere are getting huge amount of water from volcanic eruptions. H2O is the major component of volcanic gas in most volcanic eruptions.
Earth is losing water to the mantle in subduction zones and in lithified sediments.

All of these water mass fluxes are orders of magnitude larger than the amount of water carried to the international space station. It's like asking whether you can deplete a beach from sand by taking single sand grains out of it, when you're gaining and lose huge amounts of sand by ocean wave action.


Is the continent with Australia in it Oceania or Australia?

Partly, it depends on where you got educated. In many countries of Europe, Oceania is the continent. Calling the continent Australia is pretty much considered "English-centric". The reasoning for calling it Oceania is that Australia is only part of the continent. The extend of the mainland during the ice ages included part of today's Indonesia and Papua-New Guinea. While calling it Australia makes some sense and it is the largest part of the continent, in a sense it is like if we were to call Asia, Russia.

Source: Wikipedia (Maximilian Dörrbecker (Chumwa) - Self made, using this map for the background, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=7382691)


How can I find weather data for greenland sea during the 4 seasons?

An interactive website called earth has detailed weather data for the entire globe. Using this is similar to using Google Earth. You can adjust it for almost any weather data you need by clicking the "earth" icon and adjusting the date under each section. You can see the numerical data for a specific area by clicking the area on the globe with your mouse.


If the earth's core is made up of copper/other metals other than iron-nickel alloy, how our magnetosphere will be?

On a quick approach:

Magnetism. The copper itself have a weak magnetism, so a copper core will not create a magnetosphere. Chek here or here.
Gravity. The Iron density is 7.874 g/cm³ and the nickel density is 8.908 g/cm³. Copper density is 8.96 g/cm³. So with those density data, the core will be heavier. (The actual core is supposed to have a 9.9-12 g/cm³ density) It is supposed that this additional mass will increase the gravity. What it is not well determine is the % of iron and nickel at the core, so, we can talk on probably a raising on between 5-15% the actual gravity force.

Regarding some other metals, it will depends on magnetism and density.

Hope it helps!


Is it possible for an active volcano to become less violent over time?

The ultimate fate of all active volcanos is to become extinct volcanos, and eventually, objects that are barely recognizable (or not recognizable at all) as extinct volcanos.
This process from pre-volcano to active volcano to extinct volcano to barely recognizable extinct volcano takes a long time, even by geological standards of "a long time". The oldest elements of the Hawaiian–Emperor seamount chain predate the Chicxulub crater, and even those oldest elements are easily recognizable as extinct volcanos. Active volcanos are active for only short periods of time (short by geological standards), a few hundred thousand years at most. That of course is a very, very long period of time by human standards.

Alternatively, would it be possible to terraform the volcano to make its eruptions less dangerous?

Consider the follow hypothetical doctor-patient conversation: "Doctor, it hurts when I do this!" (The patient then bonk himself on the head.) The doctor's response is simple: "Don't do that then." The easiest way to do this with regard to active volcanos is to stop having humans live near active volcanos. What is feasible is to vastly improve the ability to predict when volcanos will erupt. The state of the art in this regard is rather lousy (the state of the practice is lousier still),
That is not feasible; there are too many humans who already live near active volcanos. Terraforming also is not feasible. While the amount of energy released by volcanos per year is a lot less (orders of magnitude less) than the amount of energy the Earth receives from the Sun, it is still orders of magnitude higher than the amount of energy consumed by humanity. To make matters worse, that human consumption is widely dispersed while volcanic energy is concentrated in a few places.


Confusion about grid registration concepts and their relevance in modelling

Yes, it makes a difference. In this case the grid-registered dataset is higher fidelity. However, the cell-registered is easier to handle.

As you see, both types of data are available on the dataset's page. The page states:

  The grid-registered is the authoritative registration.

The page also points out:

  The cell-registered is derived from the grid-registered,
  and the conversion produces slightly flattened relief.

So what's the difference? The grid-registered version puts the data points at the grid corners (the red lines, not the grey squares, define the grid boundaries. You have to imagine the grid cells in the left-hand image). So if there are $n \times m$ grid cells, there are $(n+1) \times (m+1)$ data points in the grid-registered data.

Since there are fewer data points in the cell-registered version, making it involves some smoothing (averaging) of the values in the grid-registered version. There's an illustration of this effect on the other page you linked to; notice how the centre cell of value 90 ends up being smoothed away:

So if accuracy is paramount, you should use the grid-registered version.

But...

You might find cell-registered data more convenient to work with (for me at least it's more intuitively analogous to an image).

The catch is that if you have grid-registered but accidentally treat it as cell-registered, then the data will shift by half a cell. So you should keep careful track of what kind of data you have. As the NOAA page states:

  Most grid applications recognize both types and avoid [the grid shift]
  problem but care should be taken.

Indeed, one popular open source GIS tool, GRASS, apparently only handles cell-registered data, as explained in the GRASS wiki. So after loading (to wherever) you should check where the pixels of the raster actually end up.


Earthquake prediction really is a contentious issue, especially after the l'Aqula trials. However, let me try to elaborate how predictions might be possible in the future and what is inhibiting this development.

We do have some understanding of earthquakes and rupture mechanisms. However, for prediction in a scale of hours (sufficient for evacuation), we have to take the following into account. The stress fields in the crust are basically applying the pressure necessary for earthquakes. However, these are difficult to measure and different stresses may apply to the same region (local, regional, global stress fields). Just look at the world stress map below, how chaotic the different influences are.

Stress

These stresses are also pretty difficult to measure. These methods include (Source World Stress Map):

Earthquake focal mechanisms
Well bore breakouts and drilling-induced fractures
In-situ stress measurements (overcoring, hydraulic fracturing, borehole slotter)
Young geologic data (from fault-slip analysis and volcanic vent alignments)

These may sometimes give contradictory stress tensors. One of these reasons is that in-situ measurements are often more localized than focal mechanisms (as an example). But when we look at the map, we do have a lot of data (27.000 data points). Here another big problem comes into play:

Material

While geophysicists like to assume that the ground is homogeneous, it really isn't. A rupture may occur when the material at a fault fails under pressure. Yet the material is highly diverse and includes cracks and fractures that make it virtually impossible to make an accurate assessment. The material may act elastic, ductile or brittle and that may be location-dependent. From this you cannot say if a small rupture triggers a larger earthquake due to stress transfer or if it stays a small earthquake.

What would be to improve

This would make a simulation highly chaotic and the prediction would have a high probability to be false positive or false negative, therefore, decreasing the reliability significantly.

In the end we would have to improve our understanding of:

Stress fields
Stress-Strain relations
Rupture mechanisms
Material science and location

Early Warning in California

Nevertheless, an earthquake early warning (EEW) system is being implemented in California (and tested). It's called CISN ShakeAlert. They can use the trick that so-called P-waves of earthquakes are faster (and less destructive) than surface waves. This can give valuable time to safety-relevant systems like nuclear plants or high speed trains. But this is in a very early stage, when an earthquake already happened and is bound to arrive somewhere.

(I would have loved to put down more links, but my rep is too low, so see Wikipedia for Rupture Mechanics, Stress-Strain relations, the World Stress Map website and the CISN ShakeAlert website.)


What type of cloud formation are these dark low-hanging clouds?

Based on your video, it does appear to be a non-rotating wall cloud - but admittedly, it is hard to definitively determine, mainly as it is hard to see any updraft.

Another example of a non rotating wall cloud is from NOAA's Cloud Classification and Characteristics page (image below):

and their description:

  The lowering denotes a storm's updraft where rapidly rising air causes lower pressure just below the main updraft, which enhances condensation and cloud formation just under the primary cloud base. Wall clouds take on many shapes and sizes. Some exhibit strong upward motion and cyclonic rotation, leading to tornado formation, while others do not rotate and essentially are harmless.

Alternatively and given the possible absence of the characteristic updraft of a wall cloud, it could be a scud cloud, similar to the one shown below

Image source

A scud cloud is defined by Accuweather as being:

  ow, ragged and wind-torn cloud fragments, usually not attached to the thunderstorm base. They are often seen in association with, and behind, gust fronts.
  Scud clouds DO NOT produce severe weather. Scud clouds are often mistaken for wall clouds and tornadoes, especially when attached to the thunderstorm base.

A handy tip to tell the difference between a wall cloud and a scud cloud is (according to Accuweather):

  to watch their relative position with respect to the rain area: scud
  clouds move away from the rain area while wall clouds maintain the
  same relative distance.

A video tutorial is included in the Accuweather site


Why is cold air fast in an occluded front, but slow in an anti-cyclone?

I do not think that there is a general relation between the temperature of an airflow and its velocity in meteorology.

There are several physical processes that need to be considered when thinking about the surface winds in occluding cyclones or fronts. A possible mechanism that I could think of explaining the stronger winds in the cold air compared to the warm air is the difference in vertical stability. The colder air is often characterized by steeper lapse rates (a stronger decrease in temperature with height). This leads to more exchange of momentum between the near-surface air layer and the so-called free troposphere air aloft. This exchange accelerates the surface winds compared to a situation where there is less exchange (as is the case for the warm air in an occluding front).

In a (wintertime) anti-cyclone, the cold air establishes itself mainly close to the surface due to radiative cooling. This leads to a very stable vertical profile, meaning that there is not much exchange of momentum between the near-surface layer and the air aloft. In such a situation, one can say that the surface layer is decoupled from the free troposphere. When a front moves in, it will simply move over the cold layer at the surface without disturbing it too much initially. The cold air indeed moves only slowly in this case.

Hope this explains at least a part of your question.


How thin is our atmosphere relative to the size of Earth?

The answer to your question depends on where one defines the edge of the atmosphere.
The Earth's atmosphere is layered. The thickness, density of composition of each layer varies. The five layers are:

Exosphere: 700 to 10,000 km (440 to 6,200 miles)
Thermosphere: 80 to 700 km (50 to 440 miles)
Mesosphere: 50 to 80 km (31 to 50 miles)
Stratosphere: 12 to 50 km (7 to 31 miles)
Troposphere: 0 to 12 km (0 to 7 miles)

Being the outermost layer, the exosphere is the layer with the most nebulous upper boundary. It is also the layer with the lowest density and it is primarily composed of very low density hydrogen and helium, particularly in the outer/upper reaches.
Because of the low density of the exosphere and also because the Karman Line, which is 100 km above the Earth, which the line designated where Earth ends and outer space begins, the exosphere is sometimes ignored.
So if one accepts the top of the Thermosphere as being the effective upper boundary of the atmosphere the effective thickness of the atmosphere is only 700 km compared the radius of the Earth, which is 6370 km.


Predicting earthquakes using disturbances in DTH TV transmission

Earthquake prediction have been discussed before in this forum and is rather dispiriting. Distortion in transmitted signals could be an early indication of earthquake, but seismometers (geophones) are still a far better instrument to detect vibrations. In future satellites could be an option in remote areas.

However, damage from an earthquake can be mitigated if warning signals can be transmitted to reach people before the actual arrival of the most devastating surface waves. It helps, in this context, that the surface waves that are  relatively slow.

Early warning systems are used in e.g Japan to slow down trains and automatically alert people through radio and internet. Similar systems are used and developed in other earthquake affected regions.

The challenge is that such systems are expensive and moreover, people with limited access to radio and other sources of information might not be able to receive the warnings. The problem is similar to the Tsunami warnings, that the most vulnerable people are the those receiving least help.


How averaging works in GFS model from NOAA?

The GFS is a model, and the model have a given time-step equal or smaller than the time-step of the output, that in this case is 3 hours. Different processes can be computed using different or even multiple time-steps.

Some of the reported variables are instantaneous, others are cumulative, and others are time averaged.

According to the documentation for the GFS radiation driver module in the GFS Operational Physics Documentation, the Downwards shortwave radiation flux correspond to a time averaged output quantity, meaning that for each model grid cell, its value is stored every internal time step (deltim) to then report the time-weighted average of all stored values, which is what you get in the 3-hour output.
However, I don't know what is the exact value used for deltim or how the time weights are computed.

Therefore, what you said seem to be pretty much the case. This is that the value reported for timestamp hour is the average of all the intermediate values computed between hour-3+deltim and hour using some time weights schema that is unclear to me.

In the link above, you can find all the source code for GFS, so it seem that to figure our the details of the time averaging you might need to search in the code where the values of the array fluxr (that store the intermediate time-step radiation flux values) is averaged and see there how it is done.


What is the meaning of seismic spectral blueing?

It is a kind of spectral shaping, intended to increase the vertical resolution of seismic reflection data.

The logic goes like this:

Seismic data is band-limited and lacks high frequencies. This limits its vertical (travel time, and thus thickness) resolution. This is annoying because we often care about thin beds.
The spectral peak of seismic data tends to be at a fairly low frequency compared to its total band. That is, the longer wavelengths are disproportionately strong compared to the short ones. Thinking of an analogy with the electromagnetic spectrum, we could say that the spectrum is reddish.
We assume that geology is whitish, or scale free, so all 'frequencies' are represented (when we're in the time domain, they are frequencies; when in depth they are wavenumbers).
So maybe we can reshape the seismic spectrum to more closely match the geological spectrum, as derived from logs, by boosting the higher seismic frequencies a bit.
One way to do this is to design an operator, a sort of wavelet, with which to convolve the seismic data. The result would be the seismic with the boosted frequencies.

Here's one example of the application of the method [PDF] from Yadav et al. (2010).

It's just my opinion, but I'd treat the idea and the method with the same skepticism as any method claiming to enhance seismic resolution. That said, I'm sure there's a champion of blueing for every detractor. Caveat interpretor.


Using the Born approximation in seismic inversion

The best reference on this is:

J.A. Hudson and J.R. Heritage, 1981, The use of the Born approximation in seismic scattering problems, Geophys. J. R. Astr. Soc., v.66, 221-240.

Basically, the Born approximation is a governing principle of the standard imaging condition that treats seismic wavefields from a single point scatterer. This is the justification for simplifying the full elastic wave equation into the scalar and vector potential wavefields and just working with the scalar wave equation for the purposes of building seismic images.

There is a very nice derivation of this in Aki & Richards (Quantitative Seismology, 1980).


How deep is the permafrost in the Antarctic?

According to "Permafrost, active-layer dynamics and periglacial environments of continental Antarctica" South African Journal of Science 98. pages 82-90:

Only 25% of Antarctica has permafrost, as the material beneath thick ice sheets is not permafrost.

The deepest permafrost occurs where there is no ice sheet.

The deepest permafrost in the Antarctic is about 1000m.


Which clouds can produce lighting and thunder?

Why are cumulus the only basic cloud type to favor lightning?
Because the speed of rising in the updraft is fundamental to lightning formation, as shown by this example plot from Total lightning activity as an indicator of updraft characteristics by Deierling and Petersen:

The faster the air rises, the more lightning in makes.  Only rapid updrafts can separate charges fast enough to overcome dissipation and build up the hundreds of millions of Volts (related ESE question) needed for lightning.  Out of the three standard cloud categories, only cumulus involves significant vertical motion.

Other cloud types?
First off, nearby clouds of other types can mask the cumulus structure responsible for the lightning.  Very commonly in strong storm environments, the broad widespread rising motion, especially near the warm front, can cause a thick low-level stratus deck to form.  And sometimes, in situations where dynamic forcing is dominant (such as with upper-level storm systems), or where storms move into a new environments (such as lake effect snow storms), fog can be thick, such that basically nothing can be seen!  So in those situations, its hard to truly attribute the lightning to the cumulonimbus, despite that being the cause.

Plus, full storm cells often develop fairly complex structures:

(Wikipedia, credit Kelvinsong)

Due to their shape and motions, some parts of storms might reasonably be categorized as stratus or altostratus, though they stem from a larger (past or present) cumulonimbus structure. These stratus-like components include arcus, incus, and velum.  And mammatus clouds that can occur as part of strong storms are actually a unique example of clouds with sinking air.  Even though air in these regions isn't rising much, leftover charge from nearby (or past) updrafts can still bring about lightning.  Anvil crawlers are a common lightning seen in the fairly flat upper regions of storms.

Also, while more precise cloud classifications do now set the stages of growing thunderstorms clouds into the cumulonimbus genus, the nimbus prefix classically meant precipitating (raining/hailing/snowing).  Precipitation reaching the ground is not an absolute requirement for a storm cloud to produce lightning.  So in a loose sense, a cloud doesn't truly have to be a cumulonimbus, at least historically.

And of course, as it can do with just about any non-insulating material, lightning can pass through inactive clouds on the journey to the ground.

But while these situations may technically satisfy your search for lightning in other clouds types, you're fundamentally right, standard lightning generally derives from cumuloform cloud origins.


Does natural plant decomposition release more greenhouse gases than burning

Another way of looking at the question:

I take 2 standard wheelbarrows of bits of plants from my garden. One wheelbarrow is used to fill the compost bin. The other goes to the bonfire.
How much ash do I have from burning compared to how much compost from the compost bin. Any gardener will know that the amount of compost will be much larger than the amount of ash. So now we need to compare the chemical composition of the ash with that of the compost. For Wood Ash there are quite a few research articles. Most of the carbon atoms in wood ash will be in the form of Calcium Carbonate (CaCO3). Percentage in the ash will vary widely but lets take a median of 50%. Ash as a percentage of original organic matter will be maybe of the order of 8% by weight.

For an original 100kg of organic matter (yes, its a big wheelbarrow) we would have 8kg of ash. In this ash would be 4kg of CaCO3. The carbon atoms would be 12% of that (relative atomic masses). So 100kg of organic bits gives you 0.48kg of carbon atoms left in the ash when you burn it.

There seems to be fewer research articles on composting but we found the following approximations. For 100kg of organic matter there will be about 9% organic carbon  (9kg). Composting will turn 100kg of raw material into around 30kg of compost in which the organic carbon content will be around 25% ( 7.5kg of carbon). These figures are median "pot luck selection" as results can vary widely. We can however see that composting retains massively more (7.5kg) of carbon atoms compared with burning (0.48kg). The difference will be in the atmosphere.


Is an underground mine collapse or a tunnel collapse called a sinkhole?

This is probably more of an English language question than a science question.
The answer to it depends on the extent of a person's vocabulary & knowledge of a particular field of engineering.

Over a period of time, in the media I have read & heard mine "tunnels" incorrectly being called shafts. Mine shafts are vertical or near vertical. What most people call mine "tunnels", people in the industry call drifts or drives - these are horizontal or near horizontal. The word tunnel is better applied to civil items of infrastructure rather than mines: such as rail or vehicular tunnels or tunnels to access underground bunkers or storage facilities.

Similarly, a tunnel or mine collapse could be termed a sinkhole and people not familiar with either the civil engineering or mining fields might do that - particularly journalists. People in the civil or mining fields would use terms such as tunnel collapse or mine subsidence hole.


Why are parts of the Atlas Mountains in Morocco flat?

Once the sediments (mainly silt and sand) have been deposited as layers in an ocean, when the sea level was much higher. Thus, each layer is very homogeneous in its texture, hardness and stability against weathering and erosion. Therefore vertical forces of erosion have a uniform effect on the entire surface and the ridge remains flat when there is no deformation due to tectonic strain. But lateral erosion has different effects on the different hard layers and so you see ribs on the mountains flanks. So it is mainly due to the layer homogenity and due to the absence of tectonic deformation that you see in the background.


Resources to determine temperature probability for a given location on a given date

The most basic way to measure probability is to look at historical
records. There are several sources for this data, including:

http://wunderground.com
ftp://ftp3.ncdc.noaa.gov/pub/data/noaa/isd-lite/

This assumes no climate change. If you believe in climate change, you
will need to factor that in.


Required temperature difference between land and sea for sea breeze

So wind is caused by differences in atmospheric pressure which in turn is a result of temperature induced density differences.

1. Required temperature diference:

A quick search brought up this paper:
Miller et al. 2003 SEA BREEZE: STRUCTURE, FORECASTING, AND IMPACTS https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2003RG000124

They calculate that a 10 degree difference between land and sea over 20km results in an accelaration of 7.2*10E-3 m/s. Now, this is an estimate. There are many more variables that will affect the complex fluid dynamics of the system.

2. Wind Intensity vs dT.

Absolutely if you increase the temperature gradient (difference) the wind speed will be higher.

from the paper they mention the sea breeze of Alcoa Bay, South Africa, where the strongest sea breeze occurs in areas with nearby dune fields:

  "During the daytime the sand dunes create a region of superheated air immediately overhead, setting up a very strong land-sea temperature difference."

3. Wind Intensity vs dT/dt

Now this is where it gets complicated. So thinking of this in a mathematical sense, the rate of increase in temperature is not going to matter that much because when calculating the wind speed at a given time what matters most is the absolute temperature difference between land and sea.
  For a temperature difference to occur the rate of temp change has to be fairly rapid as the system is always trying to reach equilibrium (i.e. remove the temp difference). So naturally if you have a parcel of air, it will reach a higher temperature if the heating is fast vs slow. If it reaches a higher temperature then it will result in a greater wind velocity. But if you wanted to make a more complex model of the system then you would need to look into the rate of change of change in Temp.


EnergyNumbers suggestion is good, but you can only go so far in reading about it second hand. I suggest that you pick a grid cell of interest, then go to the World Bank's climate change knowledge portal.

Climate Change Knowledge Portal

This gives a good cross section of 16 CMIP-5 AOGCM outputs. Check out the variation, and accuracy of the hindcasts vs evidence-based field instrumental data for the same location. Then you will get a good feel for the strengths and weaknesses of the modelling. Also, remember that water-related parameters are much less accurate to forecast than temperature-related parameters.


How do upper-level cyclones and anticyclones affect surface level winds?

High pressures and low pressures at any height do not exist in isolation.  Had to remind myself a lot of this (so anyone feel free to correct), but the first thing worth highlighting is that the Bermuda High is a warm core high pressure and so extends a great depth through the atmosphere.
This image is a fairly typical cross section of the atmosphere at 35 North in June:

Source: NCEP/NCAR Reanalysis Monthly Means
The left of the two dashed lines is the center of the Bermuda High\Ridge.  Note how it it is very upright and strong through a large height... so the winds at low levels tend to be aligned to the winds at higher levels.  The high at each level has the same cause... being a favored area for the consistent sinking air caused by the Hadley Circulation [i.e. the necessity of poleward moving air to return to the Equator once it reaches certain velocities]
On the other hand the blue trough\low (the dashed line further to the right) is tilted.  This is the typical structure of midlatitude cyclones (i.e. cold core lows).  The starting upper level feature causes the surface low to develop ahead of it (downstream) because the air moving out of the upper trough sparks rising motion below it due to divergence\positive vorticity advection increasing with height.
The result (in the NH) is there will tend to be northwesterly winds at the ground locations near where the axis of the trough is passing over (and so southwest of the surface low\northeast of the surface high).  Such northwesterly winds will tend to bring cooler air and lower relative humidities in most places, but it just how cold or dry the air will be depends upon the source region of the airmass the northwest winds are blowing in (which itself relates in large part back to the strength and larger history of the trough itself).
Overall, fundamental cause of connections between motion\pressures at different atmospheric heights is the fact mass continuity must occur (if air rises, it must be replaced, and it must eventually sink somewhere else to maintain the weight-density to prevent continuing mass buildup/loss), and works out to clearer relationships such as thermal wind (the reality that different winds at different height levels is a direct consequence\identity of temperature advection in the layer between the levels) and the fact the two main terms that cause vertical motion in the quasigeostrophic approximation are differential vorticity advection with height (i.e. different spin changes at different levels causes vertical movement) and maxima of temperature advection below (plus two other terms on friction and external heat).
In a sense, the fact pressure at one elevation induces changes\motion in another elevation maybe shouldn't seem any less weird than the fact that a low-level low pressure system can affect the wind and weather hundreds of miles away from it horizontally.  This isn't spooky action at a distance, this is a continuous fluid where changes to one part of it causes impacts on another part.


Should Modis & LandSAT NDVI composites agree and why not?

I can't comment yet, but I want to share this thought:

One challenge of the comparison is the co-registration of the data, so that really the same area on Earth's surface is compared.

In this article about the difference of MODIS and Landsat 7 NDVI, the authours put much effort in the co-registration to really compare the same area on the ground (but still there was a difference between the two sensors)


In meteorology, are satellite data "better" than reanalysis data?

Unfortunately, your question has no answer. Both have errors. Both can be unreliable. Your choice really depends on how you plan on using them.
Satellites instrument contain sources of error, such as bad observations (wildfires in the NIR), mapping problems (especially near the poles), and representation error. Don't underestimate those sources of error- Geer and Bauer found that representation error can result in errors in brightness temperature larger than 20 K. Reanalysis combines both observation errors and model errors. A good reanalysis will reduce the influence of both errors, but it is still ingrained into the product. Satellites still report back observations.
Reanalyses can be unreliable. For example, this paper shows that TRMM and PERSIANN‐CDR were more reliable than CFSR or ERA-interim.
Maybe more significantly, they both actually report entirely different things. Satellites measure radiances which can be converted into more sensible variables, while reanalyses use a mathematical representation of the atmosphere and observations. So comparing these are a lot like comparing apples and oranges.
Some other thoughts you may want to consider:

Is balance more important than truth? Reanalyses tend to be more meteorologically complete, therefore balanced. Satellites actually observe the earth system, so they will be more grounded in reality.
What temporal resolution do you want? Reanalysis outputs are usually once every few hours, while the temporal resolution of satellites vary a large amount, in both number of observations per hour and when observations are taken (such as geostationary vs polar orbiting).
What horizontal resolution do you want? Satellites may have a horizontal resolution modelers can only dream of (metaphorically speaking), but at the cost of the number of regions (for polar orbiting satellites) or consistency (for geostationary satellites).
For what amount of time do you want data? The ERA-20C dataset can go back to 1900 and the NOAA/CIRES dataset goes back to 1850, while the first meteorological satellite was put up in 1959.


The first coal deposits were laid during the Carboniferous period, between 358.9 million years ago and 298.9 million years ago.
Within this period, the early Mississippian period from 358.9 to 346.7 Mya, was when the first coal deposits were being laid. During this period, coal was being laid in what is now eastern North America, specifically the Kentucky region.


The UTM coordinate system, is a kind of Transverse Mercator projection separated in longitude bands and restricted in latitud extent such that the distortions associated with the projection remain small. Also, the UTM coordinate system is conformal projection. Therefore, it preserves the angles. That means that within the UTM zones, a straight line in UTM projection is a good approximation great circle over the relatively short distances that could be found in a UTM zone. If you don't need great accuracy, you can just trace the straight line between P1 and P2.

The following plot shows the maximum deviation that a straight line have from a great circle. In this case P1 the red dot at the Equator and Longitude 3°E, and the maximum deviation is calculated for all points in the displayed box of 6°x6°.

While the differences remain small within distances of few hundred kilometers, bigger differences can be found over larger distances, specially if P1 and P2 are in different UTM zones.

If your application requires larger distances, you shouldn't use UTM projection. Alternatively, if you your application require greater accuracy over distances suitable for UTM projection, you can calculate the great circle trajectory, but I don't know any direct formulas.

What I have used, which I know is not what you are asking for, are some Matlab functions to convert to and from UTM coordinates and another that computes great circle tracks in geographic coordinates:

function [lat, lon] = greatCircle(P1,P2,N)
%GREATCIRCLE compute points along the great circle arc connecting points P1
%and P2
%   P1, P2 format: [lat,lon]
%   N: Number of points along the great circle arc

        lat1=P1(1);
        lon1=P1(2);

        lat2=P2(1);
        lon2=P2(2);

        lon12=lon2-lon1;

        a1=atan2d(cosd(lat2).*sind(lon12),(cosd(lat1)*sind(lat2)-sind(lat1)*cosd(lat1).*cosd(lon12)));
        %a2=atan2d(cosd(lat1).*sind(lon12),(-cosd(lat2)*sind(lat1)+sind(lat2)*cosd(lat1).*cosd(lon12)));

        a0=atand(sind(a1).*cosd(lat1)./sqrt((cosd(a1).^2)+(sind(a1).^2).*(sind(lat1).^2)));

        sigma01=atan2d(tand(lat1),cosd(a1));
        sigma12=atan2d(sqrt((cosd(lat1)*sind(lat2)-sind(lat1)*cosd(lat2)*cosd(lon12))^2+(cosd(lat2)*sind(lon12))^2),(sind(lat1)*sind(lat2)+cosd(lat1)*cosd(lat2)*cosd(lon12)));
        sigma02=sigma01+sigma12;

        lon01=atan2d(sind(a0)*sind(sigma01),cosd(sigma01));
        lon0=lon1-lon01;

        sigma=linspace(sigma01,sigma02,N);

        lat=atan2d(cosd(a0)*sind(sigma),sqrt(cosd(sigma).^2+sind(a0)^2*sind(sigma).^2));
        lon=wrapTo360(atan2d(sind(a0)*sind(sigma),cosd(sigma))+lon0);
end

And for the conversions:

function  [x,y,utmzone] = deg2utm(Lat,Lon,Huso)
% -------------------------------------------------------------------------
% [x,y,utmzone] = deg2utm(Lat,Lon)
%
% Description: Function to convert lat/lon vectors into UTM coordinates (WGS84).
% Some code has been extracted from UTM.m function by Gabriel Ruiz Martinez.
%
% Inputs:
%    Lat: Latitude vector.   Degrees.  +ddd.ddddd  WGS84
%    Lon: Longitude vector.  Degrees.  +ddd.ddddd  WGS84
%
% Outputs:
%    x, y , utmzone.   See example
%
% Example 1:
%    Lat=[40.3154333; 46.283900; 37.577833; 28.645650; 38.855550; 25.061783];
%    Lon=[-3.4857166; 7.8012333; -119.95525; -17.759533; -94.7990166; 121.640266];
%    [x,y,utmzone] = deg2utm(Lat,Lon);
%    fprintf('%7.0f ',x)
%       458731  407653  239027  230253  343898  362850
%    fprintf('%7.0f ',y)
%      4462881 5126290 4163083 3171843 4302285 2772478
%    utmzone =
%       30 T
%       32 T
%       11 S
%       28 R
%       15 S
%       51 R
%
% Example 2: If you have Lat/Lon coordinates in Degrees, Minutes and Seconds
%    LatDMS=[40 18 55.56; 46 17 2.04];
%    LonDMS=[-3 29  8.58;  7 48 4.44];
%    Lat=dms2deg(mat2dms(LatDMS)); %convert into degrees
%    Lon=dms2deg(mat2dms(LonDMS)); %convert into degrees
%    [x,y,utmzone] = deg2utm(Lat,Lon)
%
% Author:
%   Rafael Palacios
%   Universidad Pontificia Comillas
%   Madrid, Spain
% Version: Apr/06, Jun/06, Aug/06, Aug/06
% Aug/06: fixed a problem (found by Rodolphe Dewarrat) related to southern
%    hemisphere coordinates.
% Aug/06: corrected m-Lint warnings
%-------------------------------------------------------------------------

% Argument checking
%
error(nargchk(2, 3, nargin));  %2 arguments required
CHuso=true;
if nargin==3
    CHuso=false;
end
n1=length(Lat);
n2=length(Lon);
if (n1~=n2)
   error('Lat and Lon vectors should have the same length');
end

% Memory pre-allocation
%
x=zeros(n1,1);
y=zeros(n1,1);
utmzone(n1,:)='60 X';

% Main Loop
%
for i=1:n1
   la=Lat(i);
   lo=Lon(i);

   sa = 6378137.000000 ; sb = 6356752.314245;

   %e = ( ( ( sa ^ 2 ) - ( sb ^ 2 ) ) ^ 0.5 ) / sa;
   e2 = ( ( ( sa ^ 2 ) - ( sb ^ 2 ) ) ^ 0.5 ) / sb;
   e2cuadrada = e2 ^ 2;
   c = ( sa ^ 2 ) / sb;
   %alpha = ( sa - sb ) / sa;             %f
   %ablandamiento = 1 / alpha;   % 1/f

   lat = la * ( pi / 180 );
   lon = lo * ( pi / 180 );
    if CHuso
        Huso = fix( ( lo / 6 ) + 31);
    end
   S = ( ( Huso * 6 ) - 183 );
   deltaS = lon - ( S * ( pi / 180 ) );

   if (la<-72), Letra='C';
   elseif (la<-64), Letra='D';
   elseif (la<-56), Letra='E';
   elseif (la<-48), Letra='F';
   elseif (la<-40), Letra='G';
   elseif (la<-32), Letra='H';
   elseif (la<-24), Letra='J';
   elseif (la<-16), Letra='K';
   elseif (la<-8), Letra='L';
   elseif (la<0), Letra='M';
   elseif (la<8), Letra='N';
   elseif (la<16), Letra='P';
   elseif (la<24), Letra='Q';
   elseif (la<32), Letra='R';
   elseif (la<40), Letra='S';
   elseif (la<48), Letra='T';
   elseif (la<56), Letra='U';
   elseif (la<64), Letra='V';
   elseif (la<72), Letra='W';
   else Letra='X';
   end

   a = cos(lat) * sin(deltaS);
   epsilon = 0.5 * log( ( 1 +  a) / ( 1 - a ) );
   nu = atan( tan(lat) / cos(deltaS) ) - lat;
   v = ( c / ( ( 1 + ( e2cuadrada * ( cos(lat) ) ^ 2 ) ) ) ^ 0.5 ) * 0.9996;
   ta = ( e2cuadrada / 2 ) * epsilon ^ 2 * ( cos(lat) ) ^ 2;
   a1 = sin( 2 * lat );
   a2 = a1 * ( cos(lat) ) ^ 2;
   j2 = lat + ( a1 / 2 );
   j4 = ( ( 3 * j2 ) + a2 ) / 4;
   j6 = ( ( 5 * j4 ) + ( a2 * ( cos(lat) ) ^ 2) ) / 3;
   alfa = ( 3 / 4 ) * e2cuadrada;
   beta = ( 5 / 3 ) * alfa ^ 2;
   gama = ( 35 / 27 ) * alfa ^ 3;
   Bm = 0.9996 * c * ( lat - alfa * j2 + beta * j4 - gama * j6 );
   xx = epsilon * v * ( 1 + ( ta / 3 ) ) + 500000;
   yy = nu * v * ( 1 + ta ) + Bm;

   if (yy<0)
       yy=9999999+yy;
   end

   x(i)=xx;
   y(i)=yy;
   utmzone(i,:)=sprintf('%02d %c',Huso,Letra);
end

and

function  [Lat,Lon] = utm2deg(xx,yy,utmzone)
% -------------------------------------------------------------------------
% [Lat,Lon] = utm2deg(x,y,utmzone)
%
% Description: Function to convert vectors of UTM coordinates into Lat/Lon vectors (WGS84).
% Some code has been extracted from UTMIP.m function by Gabriel Ruiz Martinez.
%
% Inputs:
%    x, y , utmzone.
%
% Outputs:
%    Lat: Latitude vector.   Degrees.  +ddd.ddddd  WGS84
%    Lon: Longitude vector.  Degrees.  +ddd.ddddd  WGS84
%
% Example 1:
% x=[ 458731;  407653;  239027;  230253;  343898;  362850];
% y=[4462881; 5126290; 4163083; 3171843; 4302285; 2772478];
% utmzone=['30 T'; '32 T'; '11 S'; '28 R'; '15 S'; '51 R'];
% [Lat, Lon]=utm2deg(x,y,utmzone);
% fprintf('%11.6f ',lat)
%    40.315430   46.283902   37.577834   28.645647   38.855552   25.061780
% fprintf('%11.6f ',lon)
%    -3.485713    7.801235 -119.955246  -17.759537  -94.799019  121.640266
%
% Example 2: If you need Lat/Lon coordinates in Degrees, Minutes and Seconds
% [Lat, Lon]=utm2deg(x,y,utmzone);
% LatDMS=dms2mat(deg2dms(Lat))
%LatDMS =
%    40.00         18.00         55.55
%    46.00         17.00          2.01
%    37.00         34.00         40.17
%    28.00         38.00         44.33
%    38.00         51.00         19.96
%    25.00          3.00         42.41
% LonDMS=dms2mat(deg2dms(Lon))
%LonDMS =
%    -3.00         29.00          8.61
%     7.00         48.00          4.40
%  -119.00         57.00         18.93
%   -17.00         45.00         34.33
%   -94.00         47.00         56.47
%   121.00         38.00         24.96
%
% Author:
%   Rafael Palacios
%   Universidad Pontificia Comillas
%   Madrid, Spain
% Version: Apr/06, Jun/06, Aug/06
% Aug/06: corrected m-Lint warnings
%-------------------------------------------------------------------------

% Argument checking
%
error(nargchk(3, 3, nargin)); %3 arguments required
n1=length(xx);
n2=length(yy);
n3=size(utmzone,1);
if (n1~=n2 || n1~=n3)
   error('x,y and utmzone vectors should have the same number or rows');
end
c=size(utmzone,2);
if (c~=4)
   error('utmzone should be a vector of strings like "30 T"');
end

% Memory pre-allocation
%
Lat=zeros(n1,1);
Lon=zeros(n1,1);

% Main Loop
%
for i=1:n1
   if (utmzone(i,4)>'X' || utmzone(i,4)<'C')
      fprintf('utm2deg: Warning utmzone should be a vector of strings like "30 T", not "30 t"\n');
   end
   if (utmzone(i,4)>'M')
      hemis='N';   % Northern hemisphere
   else
      hemis='S';
   end

   x=xx(i);
   y=yy(i);
   zone=str2double(utmzone(i,1:2));

   sa = 6378137.000000 ; sb = 6356752.314245;

%   e = ( ( ( sa ^ 2 ) - ( sb ^ 2 ) ) ^ 0.5 ) / sa;
   e2 = ( ( ( sa ^ 2 ) - ( sb ^ 2 ) ) ^ 0.5 ) / sb;
   e2cuadrada = e2 ^ 2;
   c = ( sa ^ 2 ) / sb;
%   alpha = ( sa - sb ) / sa;             %f
%   ablandamiento = 1 / alpha;   % 1/f

   X = x - 500000;

   if hemis == 'S' || hemis == 's'
       Y = y - 10000000;
   else
       Y = y;
   end

   S = ( ( zone * 6 ) - 183 );
   lat =  Y / ( 6366197.724 * 0.9996 );
   v = ( c / ( ( 1 + ( e2cuadrada * ( cos(lat) ) ^ 2 ) ) ) ^ 0.5 ) * 0.9996;
   a = X / v;
   a1 = sin( 2 * lat );
   a2 = a1 * ( cos(lat) ) ^ 2;
   j2 = lat + ( a1 / 2 );
   j4 = ( ( 3 * j2 ) + a2 ) / 4;
   j6 = ( ( 5 * j4 ) + ( a2 * ( cos(lat) ) ^ 2) ) / 3;
   alfa = ( 3 / 4 ) * e2cuadrada;
   beta = ( 5 / 3 ) * alfa ^ 2;
   gama = ( 35 / 27 ) * alfa ^ 3;
   Bm = 0.9996 * c * ( lat - alfa * j2 + beta * j4 - gama * j6 );
   b = ( Y - Bm ) / v;
   Epsi = ( ( e2cuadrada * a^ 2 ) / 2 ) * ( cos(lat) )^ 2;
   Eps = a * ( 1 - ( Epsi / 3 ) );
   nab = ( b * ( 1 - Epsi ) ) + lat;
   senoheps = ( exp(Eps) - exp(-Eps) ) / 2;
   Delt = atan(senoheps / (cos(nab) ) );
   TaO = atan(cos(Delt) * tan(nab));
   longitude = (Delt *(180 / pi ) ) + S;
   latitude = ( lat + ( 1 + e2cuadrada* (cos(lat)^ 2) - ( 3 / 2 ) * e2cuadrada * sin(lat) * cos(lat) * ( TaO - lat ) ) * ( TaO - lat ) ) * ...
                    (180 / pi);

   Lat(i)=latitude;
   Lon(i)=longitude;

end

I hope that helps.


Estimating fracture pressure (looking for literature to support)

fracture formula What is the method of injection and fluid you are using? Apply a leak off test to the formation after drilling out casing shoe and your 5-10m into open hole. I’ve attached two links that may be helpful.                           formation fracture pressure
                         a list of methods
There are also plenty of apps for you’re phone that you may find useful. Search “drilling formulas”

Basic frac graduent is 18kpa per meter there fore at 1000m it would take 18000kpa pressure  more or less to fracture a zone.
In psi it is .8 psi per ft of vertical depth.
Usually it takes a higher pressure to frac a formation but feed rates are much lower.

Kind regards
Jeff B.


What are the relative contributions of planets to the Milankovitch Cycles?

The tidal effect over time tends to circularize orbits.    It's well known that Moon is being tidally pushed away from the Earth over time (about 1.5 inches a year).  This effect is stronger when the moon is closer and weaker when the moon is farther, so there is a very gradual tidal circularizing of orbits over time, unless the orbit is highly eccentric, then you can get the reverse effect, if, when the orbiting object accelerates ahead of the tidal bulge during Perihelion that can draw it closer to the sun during that part of the orbit and that tidal effect tends to increase eccentricity.

This tidal "circularizing" only works in 2 body systems though.  3 body systems and n-body systems are more complicated.  I can't explain the effect of Jupiter and Saturn because 3 body gravitation is too complex, but I can tell you that Trojan asteroids and the asteroid belt are not factors or, very very tiny factors because they don't have enough mass.  orbital cycles are all about the strength of the gravitational fields any synchronization of orbits.  The gravitational fields on Earth by the asteroid belt or Jupiter trojans is too tiny.

The temperature change on earth can be observed by the ice ages.   The net effect of the Milankovich cycles, if the earth was consistent would be quite small, maybe 1 degree C peak to trough.  Most of the 10 degree change globally that we see, ice age to warm period between ice ages is due to feedback mechanisms on the earth, glacier formation and ice cover increases albedo which reflects more sunlight directly back into space and colder oceans absorb more CO2 which lowers the greenhouse effect and as glaciers grow high the air over high altitude gets colder.   Changes in ocean currents may be factors too, but that's not as well understood.

Locally, the effect can be much greater than 1 degree C though, even without the feedback mechanisms.   Precession has much more significant local effects because 3.4% closer at Perihelion means 6.8% more energy, and that's significant, even if it varies,  3.4% above normal peak summer to 3.4% below normal, low winter, but that's enough to cause a significant change.   It's thought that precession is behind the Sahara desert cycle between forest and desert every 13,000 years or so.   Precession may be (speculation on my part), a factor in ending ice ages as well, but it doesn't seem to be a factor in starting them, as ice ages appear to begin on roughly 100,000 year cycles and before that, 40,000 year cycles.   Source.   There's not any good evidence that I know of for ice ages operating on 26,000 year cycles.


What does global weirding mean regarding temperature extremes?

First things first.   Global "Weirding" is very difficult to quantify.  That doesn't mean it's not happening, but it's inexact.  The idea came from climate models, which produced a lot of unexpected variations as opposed to more smooth and consistent warming and weather patterns are so complicated that there's still a lot of unknowns in this area.

  Warmer waters mean typhoons can form more often, so in locations where
  extreme weather is also caused by typhoons they will see this more
  often

Typhoons/Hurricanes are formed not just by warm water but by warm air and wind direction.   If the wind is too strong, the hurricane doesn't form, it needs to build and as it builds, begin to spin.    That's a dummies explanation, more details here

Warmer water can make hurricanes grow larger (unclear if it makes the wind blow faster too, it might).  One of the fun little jokes made about global warming is that in the IPCC's 4th assessment report (4AR) they predicted fewer hurricanes and in the 5th (5AR) they predicted more, though both were stated with some uncertainty and in the 4AR they predicted fewer with a chance of larger so those predictions aren't nearly as contradictory as this cartoon writers tries to make it sound.

I personally trust 5AR over 4AR cause it's had 7 more years of research behind it, but whatever ends up being true, predicting hurricanes is complicated.   Short article on the debate of cause of the apparent recent increase here

  Warmer air can transport more water and since steam pressure rises
  greater than linear with temperature, the same temp. swing around a
  high mean means that more water can precipitate.

I'm not sure about stream pressure, though warmer air can hold significantly more water vapor, so that I agree with.

Every 1 ° warmer, the atmosphere can hold in saturation about 6% more water.   So warmer air can hold quite significantly more water and as a result, lead to larger rain storms, though it's not just air temperature, but temperature variation as the warm air rises, etc.   But more precipitation per storm is a very likely consequence of man made climate change.   Source.

Also, while the Earth has warmed less than 1 ° C so far, most of the surface temperature over land has warmed over 1 ° C (1.53 ° C on average - see here) and it's the rainfall over land that affects us.   This means that the atmosphere over the land can hold as much as 10% more water on average than it did at pre-climate change levels.   Now, the temperature increase is lower in the upper atmosphere, so it's not really 10%.  but we've seen a few percent increase in how much water our atmosphere can store over land over just the last few decades and that's expected to continue to increase.

Water evaporation and atmospheric water-vapor replenishment is trickier and depends on a few factors, river flow rate is based on rainfall and snow-melt upstream, wind speed and plant transpiration are also important.   Some people say CO2 is plant food but it's not that simple.  Plants need to take in oxygen to capture CO2 which they use to grow.   Sunlight and soil neutralists are the actually the "food" for plants, CO2 is what they use to grow and with higher levels of CO2 in the air, they need to take in less atmosphere to get what they need and as a result, they lose less water, so less water is returned to the atmosphere from forests and trees, as CO2 increases.

So, in a nutshell, the global warmed atmosphere on average can hold more water, it can also take more time for the atmosphere "fill up again" after a rainfall or after passing over high mountains and dropping a lot of water-vapor.  That's why you get more floods and more droughts.  That much is simple physics.

If snow melt is high, that can lead to greater river flow and more flooding, and snow tends to fall in greater amounts with more water-vapor in the air.   There's a number of factors.

That strange 5 feet of snow event on Buffalo in 2014 happened when cold air blew over warm great lakes and the temperature difference caused the wind to draw a lot of water off the lakes.  Which, as it blew inland a mile or two, it quickly turned to snow and not the houses on the lake, but the houses a mile away from the lake got covered in snow.  The lake effect isn't unique to climate change.  It happened in the 1940s and 1970s, but warm lakes and a cold blast of air are the 2 drivers.  2014 was perfect for that with the polar vortex and the warm temperature colliding.  It was (I think) the largest lake effect Buffalo has on record.

Cool video here,

  I often hear a statement to the effect that more energy in a weather
  system means it has more extreme 'swings' in its behaviour. I find
  this rather opaque and unconvincing.

I think I agree with you here.  More "energy" is at best, vague, and it explains nothing.

Water vapor condensation is one way that air temperature can rapidly change.   Condensation/cloud formation releases heat so more water vapor can play a role in faster temperature change, but I'm not sure how big a factor that is.

Changes in ocean currents, perhaps caused by salinization changes and glacier melt can have significant effects.  Europe's moderate winters relative to high latitude are in large part caused by the gulf-stream and the gulf-stream may be slowing, article here.  There's still some uncertainty on the extent of this effect, but there appears to be a connection.

The Polar Vortex may also be growing as a result of climate change, based on some complicated models.   Despite the earth being warmer, harsh winters in some northern locations are still possible based on weather patterns.   Key point from article here:

  As strange as it sounds, Kim believes the intense cold air outbreaks
  in recent winters across Europe, Asia, and North America are, in his
  words, “a side effect of global warming.”

  In 2100, we'll see more extreme heat events relative to 2015 mean
  temperatures or

  In 2100 we'll see more extreme heat events relative to 2100 mean
  temperatures

This is a tough one.

First point is that there really is no 2015 mean in terms of temperature.  We can generate a global average temperature for 2015, but local temperature fluctuates too much to have a 2015 standard.   Temperature variation vs a standard is generally measured against a baseline over a few decades.   For example, see chart below.  (I couldn't get it to embed), but it compares 2014 local temperature to a baseline of 30 years, 1981-2010.

https://www.ncdc.noaa.gov/sotc/service/global/map-blended-mntp/201401.gif

If your question is rewritten as, will 2015, 2016, 2017, 2018, 2019, etc, compared to a 1981-2010 baseline have fewer extremes and look less "weird" than 2100, 2101, 2102, 2103, 2104, etc compared to a 2066-2095 baseline, then that's an interesting question but very hard to answer.   Individual years will be hit or miss, but on average, …hard to say.

As ice melt increases and as oceans continue to store heat and slowly grow warmer the weird weather variation could increase, but as CO2 levels begin to perhaps at some point, stop rising and reach a leveling off, we might see a decrease in "weirdness" compared to previous years, though the planet would still be warmer, but the rate of change might drop, so the best answer I can give you is that it could go either way.

The IPCC models suggest a gradual increase in the rate of warming for surface temperatures between now and 2100, as well as an expected increase in sea level rise but that corresponds to a steady increase in CO2.  The future CO2 growth rate could be a factor.

Guesses aside, when the experts say that weather will continue to get stranger, they are talking about compared to a consistent baseline, not a moving baseline cause that's a safer prediction, so your first sentence is the prediction that's usually put forth, but your 2nd sentence has a ballparkish 50% chance of being true too.

At some point the degree of weirdness has to level off simply because nothing builds indefinitely and for now global "weirding" appears to be gradually increasing, though as far as I know, precise measurements don't really exist.   It's too hard to quantify.


Don't think of the Coriolis force as deflecting motion clockwise/counter clockwise, but to the right (NH) or left (SH), when looking in the direction of the motion.

So this is sort of 'by definition'. A cyclone is a low pressure system, and air will move from a location with high pressure towards a location with low pressure. The Coriolis force will deflect this air to the right in the Northern Hemisphere, creating a counter-clockwise motion around the low pressure.
Around high pressure systems the direction of the motion is opposite, anti-cyclonic.

A very simple sketch, with a low pressure in the centre, and higher pressure around it:

Another way of looking at this is through the equation for geostrophic motion. The wind around a cyclone is (nearly) geostrophic, so the equation of motion can be simplified to

$$
f\mathbf{k}\times\mathbf{v} = -\frac{1}{\rho}\nabla p
$$

where $f$ is the Coriolis parameter, $\mathbf{k}$ is the vertical unit vector, $\mathbf{v}$ is the wind speed vector, $\rho$ is density and $\nabla p$ is the pressure gradient.

So, looking at a sketch of a low pressure system on the northern hemisphere, the pressure gradient force will look like

The gradient itself goes from low to high pressure, but the force has the opposite direction. To achieve a balance between this and the Coriolis term, we need this situation:

(Note the negative sign for the Coriolis term here. In the above equation we have equality, so with the negative sign the direction is opposite that of the pressure gradient force.)

As $f$ is positive on the northern hemisphere, when we use the right-hand rule for cross-products, this means that $\mathbf{v}$ must be directed as

i.e., giving a counter-clockwise motion around the low pressure.


Math needed for Hydrology, specifically surface water hydrology

Math is very important for hydrology. Especially for surface water problems, you require understanding of differential equations while open-water hydraulics like backwater calculations are complex. If you need a great deal of detail, these problems cannot be solved analytical, only numerical.

So I recommend a good mathematical basis to study surface water hydrology and hydraulics.


What is the deepest we have ever gone into the Earth?

Probably a bit over 4 km, in this South African mine: https://en.wikipedia.org/wiki/Mponeng_Gold_Mine  But as the link mentions, the mine operators go to considerable lengths to reduce the mine temperature to endurable levels from the  66°C/151°F of the surrounding rock.

Note: This answer is for the original question, where the OP asked for the deepest depth below the surface.  It's since been changed to ask for depth below sea level.

http://cracked.tumblr.com/post/162183647834/the-mponeng-gold-mine-in-south-africa-is-the


Natural spiral pattern of grass - what could cause this?

I came across this photo from Mount Calavera, San Diego County, California.  It is described as rock art and is also found in the floor of a quarry.  The spiral pattern, including the vegetation, is very similar to your photo.  In your photo it looks like the rocks have just been removed.

Rocks appear to affect the soil moisture available for vegetation by shading. From a study in Southwest China investigating the influence of bare rocks on soil moisture:

•We found that bare rocks influenced the surrounding soil moisture by shading.

•The effect degree of rocks to surrounding soil moisture correlated with its shape.

•Soil moisture on the north side of the rocks was significantly higher than others.

•The location at 15 cm north of the rocks was ideal site for plantation restoration.

Source: http://www.sciencedirect.com/science/article/pii/S0341816213003123

Is it possible that rocks used to be placed in a spiral pattern in your photo that allowed the vegetation to take hold?


The Role of the Antarctic Circumpolar Vortex & Ocean Current in Keeping Antarctica Frozen

The Antarctic Circumpolar Current keeps the warm waters away from the higher latitudes because Antarctica is disconnected from other land masses. This in turn amplifies the westerlies and therefore, polar front Antarctic Circumpolar Current prevent any warmer air/water to enter the high latitudes of Antarctica.[more on this: wikipedia]

During the Oligoncene/Eocene boundary about 32 million years ago, the Tasman Passage opened which gave rise to the onset of Antarctic glaciation [more on this wikipedia]


where can I download ECHAM climate model data?

Where to find the data

The German Climate Research Center (DKRZ, Deutsches Klimarechenzentrum) hosts the Word Data Center for Climate (WDCC). You can search the WDCC via the CERA Database (cera-www.dkrz.de).

Looking for ECHAM provides you with several sets of ECHAM model results: here. You get at least the ECHAM data for the second to fourth IPCC assessment reports and some more data sets.

You need to have a login. It can be easily created.

Information on the structure of the data at CERA

You have projects, experiments, and data (sets).

Projects contain overall information on the model setup, on the data producers, and on the validation.

One experiment can summarize several data sets. For a coupled climate model this could mean, that the physical ocean, the biogeochemical ocean, the meteorology, and the atmospheric chemistry are saved as individual data sets, which are than summarized as one experiment.

Experiments can have a doi (digital object identifier). Thus, they are easily citeable in scientific publications and long-term available.

Access data at the WDCC

You can directly download data via the web-interface. As an alternative, you can use jblob, which is a command line utility for downloading data from the WDCC. Jblob also has some options to pre-process data on the DKRZ servers prior to download it -- which might reduce your file size. For both access pathways you need to have a valid login.


How to calculate the temperature of Earth's surface

An easy calculation is to start with the solar constant, the power (energy per unit time) produced by solar radiation at a distance of one astronomical unit. This is 1.361 kilowatts per square meter. The surface area of the Earth is $4\pi R^2$, where $R$ is the radius of the Earth, while the cross section of the Earth to solar radiation is $\pi R^2$. Thus the Earth as a whole receives 1/4 of that solar constant.

Assume a planet with an atmosphere that is transparent in the thermal infrared, with the same albedo as that of the Earth (0.306), rotating rapidly like the Earth, and orbiting at the same distance from the Sun as the Earth. The effective temperature of this planet is given by the Stefan Boltzmann law:
$$T = \left(\frac{(1-\alpha)\,I_\text{sc}}{4\sigma}\right)^{1/4}$$
where

$\alpha$ is the albedo (0.306),
$I_\text{sc}$ is the solar constant (1.361 kW/m2),
$\sigma$ is the Stefan Boltzmann constant (5.6704×10−8 W/m2/K4), and
the factor of 1/4 arises from the the fact that the Earth is a rapidly rotating spherical object.

The result is -19 °C.


This article in Fox News points to this paper and asserts that the fastest deep current measured is the Antarctic.

Rintoul, of the Antarctic Climate and Ecosystems Cooperative Research
Center in Hobart, said it proved to be the fastest deep ocean current
yet found, with an average speed of 7.9 inches a second (0.20 m/s).

I have no access to the paper, I can only read the abstract. I guess Fox News didn't lie this time as they are sourcing a scientifical paper of Nature Geoscience.
Fukamachi, Y., Rintoul, S., Church, J. et al. Strong export of Antarctic Bottom Water east of the Kerguelen plateau. Nature Geosci 3, 327–331 (2010). https://doi.org/10.1038/ngeo842


I'm not sure I entirely understand your questions but I'll have a go.

  Does grade of metamorphism apply to igneous and sedimentary rocks?

Yes. Both igneous and sedimentary rocks can be metamorphosed. For example, a high grade metamorphic rock of the amphibolite facies could have been originally either a sedimentary rock or an igneous rock. It's not always straightforward to figure out if it was one or the other. Note that because igneous rocks already consist of "high-grade" minerals such as pyroxenes, amphiboles, feldspars, etc., and their grain size is already occasionally coarse, it may not be obvious than an igneous rock have been metamorphosed. Sometimes it takes a closer look to distinguish a metamorphic igneous rock and just an igneous rock. Sedimentary rocks, on the other hand, are originally composed of clays and other "low-grade" minerals so it's obvious when one is metamorphosed. A metamorphic fabric (foliation and the likes) is also much easier to develop in originally sedimentary rocks than in igneous rocks.

  I know that grade of metamorphism applies to the scale in which a rock becomes crystallized. Or is it?

I'm not sure what the question is. Usually higher grade metamorphic rocks have larger grain size. For example, greenschist facies rocks are commonly fine grained (for example phyllites or schists) whereas eclogite facies rocks are usually composed of big beautiful crystals, sometimes in the cm scale.

  Please also define grade of metamorphism as a clarification.

Start here:

Metamorphic grades


Can up-welling water at oceanic fronts be physically felt?

There is a sea-surface thermal front at the northwest tip of Scotland. On the western side is water from the Gulf Stream Drift - cool, but sufficiently comfortable to swim in. On the north side is Arctic water which is horribly cold and which nobody in their right mind would swim in. I write from personal experience!


What is "sheltered site" (as opposed to "exposed site")?

Depends on the context. Examples can be: In depressions instead of lonely on the plain, inside of the forest instead of at the edge, along a river bank or lakeside instead of on dry ground.

Or, in short: exposed to wind & weather instead of sheltered from the rigour.

Also depends on the tree. Some pioneer trees can grow individually in adverse conditions, others like it in groups and warm and wet.


Australia's Institute of Marine Science webpage How the Great Barrier Reef was formed is the result of the flooding of the former coastal plain when sea levels were lower.  A further explanation from the website states:

  The coastal plain included river valleys and small and large hills. Corals tended to grow best on hills because they were where waves broke and the water was most turbulent. Thus, although corals probably grew on any available hard shallow surface on the flooding coastal plain, reefs tended to form where there were hills.

A diagram of the formation is shown below:

Image source

So, not the result of volcanoes, but rather the after effects of coastal plain inundation.


Is it hotter in different places with the same air temperature?

While perceptions about the climate can have an effect on how we react to our environment, Guangdong and Minnesota are fundamentally different climates altogether. Using the Koppen-Geiger climate classification system, Minnesota is mostly a Temperate Continental (Dfb/Dwb) climate, meaning that is has warm summers and long cold winters, while Guangdong is a Humid Subtropical (Cfa/Cwa) climate with hot and wet summers and a short dry winter. The classification is largely based on monthly average temperatures and precipitations based on climate normals (~30-year periods).

It might be the case that temperatures match up at some points, but based on the classifications/geography of both areas, it would seem that Guangdong experiences more humidity and much longer warm periods, which combined would raise the Humidex (https://en.wikipedia.org/wiki/Humidex) above that of Minnesota.

For more information on the Koppen-Geiger classification, https://en.wikipedia.org/wiki/K%C3%B6ppen_climate_classification


What is a good definition of the word "rock" for teaching?

I usually tend to think that the shorter a definition is the more it introduces ambiguity and errors. So I would just think about your audience and choose an appropriate length (You  didn't mention the level you are teaching for).

Similar to the definition of life you can offer to your audience characteristics, which some rocks will conform more or less. This is just a list I thought out:

Rocks are solids at the Earth's surface

I would definitely include solid ice, which is the primary lithology of Greenland and Antarctica
How solid? Most of them are incompressible to high pressures(Exception porous sediments)
With lower temperatures more things become rocks (even our Sun).
Density varies greatly (bring a lead-ore and a floating tuff)

Rocks are consolidated

To differentiate them from sediments rocks have underwent a certain amount of compaction and cementation

Rocks form through purely anorganic, organic, or a mixture of those processes

This category probably needs the most explanation on how diverse the pathways to a rocks are

Rocks form through natural processes

Human-made rocks exist so instead of tossing that aside, talk about the interesting differences and similarities. Natural rocks fulfill the requirments of chemistry, physics, thermodynamics. Human-made rocks additionally fulfill requirements of pragmatism: a brick needs to be square in order to build a wall; holes make it light and insulate better; etc...

Anorganic rocks fall into natural categories which obey the conditions set by their chemistry and the resulting eutectic points, reduce chemical oversaturations, and minimalization of the Gibbs free energy (There is a reason why granites in all their diversity, are actually pretty similar)
Organic rocks obey the requirements by organisms of which nutrients exist in excess and can be used to synthesize a skeleton or shell.
Rocks don't fulfill the requirements of life

Talk about what makes living matter special. Talk about, that on planets devoid of life everything is a rock or sediment.

Rocks have a scale

One atom or chemical compound is not enough to make a rock. At what scale does language speak of a rock. What scale is so big that other words are introduced. Talk about how words are also just concepts defined by other words which are concepts themselves (This is what makes science fun)


Is it possible to see Auroras from the equatorial region?

Quoting from the Wikipedia article on the Solar Storm of 1859;

  On September 1–2, 1859, the largest recorded geomagnetic storm occurred. Aurorae were seen around the world, those in the northern hemisphere even as far south as the Caribbean; those over the Rocky Mountains were so bright that their glow awoke gold miners, who began preparing breakfast because they thought it was morning.[2] People who happened to be awake in the northeastern US could read a newspaper by the aurora's light.[4] The aurora was visible as far from the poles as Cuba and Hawaii.

So, it didn't quite make it to the equator, but it came very close.  There is no physical reason why you can't get aurora at the equator, but it takes a lot of very energetic particles being ejected by the sun over a brief period.

However, as I mentioned in my comment, a solar storm of that magnitude would wipe out most of the Earth's electric grids.  Even the telegraph systems of the 1800's couldn't survive.  Another quote from the Wikipedia article;

  Telegraph systems all over Europe and North America failed, in some cases giving telegraph operators electric shocks.[6] Telegraph pylons threw sparks.[7] Some telegraph systems continued to send and receive messages despite having been disconnected from their power supplies.[8]


The true reflected colour of a cloud doesn't change from white unless there is serious pollution, such as Saharan dust, wildfire soot or industrial emissions. None of these produce a blue colour, so the question really becomes 'what reflected light looks blue', and that is a function of the direction of view (towards or away from the sun), the subject's perception of colour (which can be surprisingly deceptive), and how much atmospheric blue back-scatter the cloud is reflecting. The latter accounts for most of the 'blue cloud' that we see.


You need to be very wary of anything written in the non-scientific media about science. The media loves woo and controversy because those are the things that garners readers, and that in turn garners advertising revenue.

By way of analogy, suppose as near-adult in gym class someone said "My gym shoes smell bad. Bad! Awfully bad!" Someone else would inevitably take a sniff. If it was bad, really, really bad, he would say so, while gagging. Someone else would say "That bad? Are you sure? Pass it over." That shoe would have quickly been passed around the locker room if it truly did smell worse than death. (Apologies if you are female; females don't do stupid stuff like this.)

The non-scientific media love scientific articles that smell, particularly those articles that smell extremely bad. The media falls under the compulsion of passing these articles around. Good, solid journalism is sorely lacking nowadays. It's much easier to copy someone else's writing than it is to investigate. It's not plagiarism if the original source receives acknowledgement and a fee. You can typically trace those dubious reports that are all over the internet to a single source.

So what's the source of this 27 million year recurring extinction event figure? It's two men who keep peddling this conjecture every other year or so. Here's the article that caused this imbroglio:

A. Melott and R. Bambach, "Nemesis reconsidered," Monthly Notices of the Royal Astronomical Society: Letters, 407:1 99,102 (2010).

Rather than looking to the non-scientific media, it is much better to look to the scientific community and see how much credence they have given to this conjecture. The answer is essentially none. That article has received a grand total of seven (CrossRef), maybe nine (Web of Science) citations in the four years it has been in print. The vast majority of those are either self citations or citations by other fringe scientists who are pushing their own brand of woo. This hypothesis is viewed rather lightly by the scientific community.

Moral of the story: Don't believe everything you read on the internet.

Let's suppose your conjecture is true. What signs would we see of a prior civilization? If the civilization was sufficiently advanced we would see a depletion of resources. If that prior civilization had advanced to the stage of sending stuff into space, we wouldn't see iron where we see it now. We see iron in very, very old banded iron deposits. We don't see any anomalous iron deposits in what would have been cities millions and millions of years ago.

The same goes for coal and oil. Our first discoveries of oil and coil was stuff easily accessible from the surface. Easy pickings. Those easy pickings would not exist if some prior civilization had advanced to the Elizabethan stage, perhaps even Roman level.

What if some calamity had wiped out humanity 2000 years ago? 10,000 years ago? What would a future civilization see millions of years from now? That's a better question. The answer is not much. That future civilization might well not see anything at all. Archaeologists have found fossil records of our ancestors, but that's because we humans are driven to look for those ancestors. A future civilization might not find any fossil humanoids that exhibited a tripling in brain size in just a few million years.

That of course is assuming that intelligent life arose before humanity. That too is dubious. Evolution shows a more or less steady progression in brain size. Dinosaurs might not have been as dumb as people thought 50 years ago, but they were still pretty dumb. Their brains were reptilian. Science fiction writers love the idea of intelligent dinosaurs. That's a rather non-standard view amongst scientists.


How much pollution would it take to stop global warming?

I found a decent review article by Zhang et al. (2015) covering various geo-engineering proposals that is worth reading. As for atmospheric pollution, they report that pollution should be injected at controlled altitudes into the stratosphere, where it is longer-lived. Using $\text{SO}_2$, apparently around $2-7 \text{Tg}$ of stratospheric injection would be needed, which is substantially lower than the global $\text{SO}_2$ emissions (e.g. Lee et al. (2011) report annual emissions around $50\text{Tg}$ $\text{S}$, probably the figure has decreased a bit since then).
So, as for your question, it is not about simply polluting more but about controlledly injecting pollutants into the correct atmospheric layers.
References
Lee et al., SO2 emissions and lifetimes: Estimates from inverse modeling using in situ and global, space‐based (SCIAMACHY and OMI) observations, Journal of Geophysical Research Atmospheres 116 (2011), https://doi.org/10.1029/2010JD014758
Zhang et al., Review of geoengineering approaches to mitigating climate change, Journal of Cleaner Production 103 (2015), pp. 898-907, https://doi.org/10.1016/j.jclepro.2014.09.076, available at http://www.homepages.ed.ac.uk/shs/Climatechange/Geo-politics/Comparisons.pdf


What percent of volcanoes are glaciated?

21.7%, by my calculations (338 / 1556 holocene-active volcanoes). I calculated perennial snow by combining 6 weeks of MOD10A2 data from winter and summer weeks in 2014 to figure out which pixels had snow both in the summer and the winter. My source code for that is available as a gist (an older version accidentally classified cloud as snow; that's been fixed). Then I checked if these pixels fell within 10km of the volcanoes in the Smithsonian Institution's Global Volcanism Database. I also plotted the woefully incomplete Global Land Ice Measurements from Space glacier polygons.

There are clearly a few false-positives on ocean islands... I think this is due to MOD10A2 marking choppy surf as snow. Looking into that. I intend to publish this and will put a reference here if it is published.

Here's what the map looks like for part of Alaska:

And the whole world:


how high was mount vesuvius (mount somma?) before it erupted in AD 79?

The AD 79 eruption is the last of four caldera forming events which reduced the heigth of Monte Somma. Their approximate timing is: ca. 18000 BP, ca. 8000 BP, ca. 3400 BP and AD 79.

Between 3400 BP and AD 79 it was about 1300 m high and height of the intact stratovulcano before the beginning of the caldera collapse was about 1900 m.
Note that while the original height can be extrapolated from the shape of the cone, the remaining height after individual events is not well constrained.

Reference: Cioni, R., Santacroce, R., & Sbrana, A. (1999). Pyroclastic deposits as a guide for reconstructing the multi-stage evolution of the Somma-Vesuvius Caldera. Bulletin of Volcanology, 61(4), 207-222.


Rainfall units conversion from depth to rate/intensity

Your 6-hour rainfall data represent the depth of water fallen in 6 hours. In order to have the average rainfall intensity in m/s corresponding to that interval of time, you have to divide the rainfall depth for the number of seconds in the time interval or for mm/s you multiply for 1000/21600. If you want the intensity in m/h you divide for 6 hours.
You have only the cumulative rainfall in 6 hours so you can estimate the intensity dividing equally the volume of rainfall over the 6 hours. The information remains the same. The real intensity was not constant over the 6 hours, obviously. You cannot, therefore, obtain the real 1-hour rainfall depth for each hours from 6-hours rainfall depth but only an average value that assumes it constant in each hour. If you have the measured 1-hour rainfall depth data in meter and you calculate the intensity in m/s from that data the results will be different.
I hope to have correctly understood your doubts and that this made things clearer.


The readme file for all the datasets has a section on units.  In this section, they describe how to interpret the numbers (which exclude decimal points in the data files).

For the "number of days" data it says:

  [units are] "tenths of days" for the number of days per [time] above or below certain threshold, such as days above 90F. e.g., "256" is 25.6 days.

So, you need to divide all those numbers by 10 to get the actual values.  Also, take note in the readme file of these pieces that correspond to the data file in question:

S = standard (no more than 5 years missing and no more than 3 consecutive
    years missing among the sufficiently complete years)

P = provisional (at least 10 years used, but not sufficiently complete to be
    labeled as standard or representative). Also used for parameter values on
    February 29 as well as for interpolated daily precipitation, snowfall, and
    snow depth percentiles.

-9999: missing or insufficient data; values cannot be computed
-7777: a non-zero value that would round to zero, for variables bound by zero.


How does one create petroleum/crude oil for future generations?

Geological processes are just too slow. Although, given how quickly we are pumping greenhouse gases into the atmosphere, humanity may well (in a generation or two) be growing biological material as fast as possible and throwing it into deep holes in the ground, which will give another fossil-fuel resource in a few million years. But we'll be doing that just to sequester carbon dioxide from out of the atmosphere, not to invest in future hydrocarbon supplies.

Hydrocarbons are useful because they have very high energy density: the energy stored per unit weight and unit volume is extremely high. Furthermore, that energy can be harnessed with very primitive technology - just burn it. Because we've been relying on them for nearly two centuries now, we've got very good at safely transporting them globally, and safely storing them in a form ready for immediate use.

So, hydrocarbons have two uses: one, they act as storage, as a time-buffer for time-sensitive energy demands such as electricity consumption. And two, their energy density makes them very suitable for powering transport on irregular or changeable routes.

However, as a means of energy storage, they're not very efficient: even the best CCGT gas-powered electricity generators are only 60% efficient; and internal combustion engines tend to give an efficiency of about 20-25%, tank-to-wheel. And that's without the losses involved in creating the hydrocarbons in the first place

So whether hydrocarbons have a future as a source of energy is very dubious, because for almost all applications, we now have superior options.

And the future for fossil hydrocarbons must, for the sake of human civilisation, be short and quickly-tapering, because of the risk of catastrophic global warming.

For some transport applications, the energy density is still a winning attribute of hydrocarbons: most notably, powered flight for freight and travel.

We already have two routes to non-fossil hydrocarbons: biological sources, and direct chemical synthesis. Each involves capturing atmospheric CO2, and combining with water, to generate a blend of hydrocarbons.

Now, we already have means of creating hydrocarbons suitable for flight (e.g. Jet-A and Jet-A1 fuels). And there are already demonstration plants that have closed-loop generation of synthetic hydrocarbons, for use in electricity-grid-balancing, by using surplus electricity to synthesise methane, which is then burnt in gas turbines when required. Similarly, Tony Marmont's team have been synthesising petrol (gasoline) from air, water, and electricity.

However, none of those things mean that hydrocarbons necessarily have much of a future, beyond plastics production. Because hydrocarbon-powered aviation has a lot of environmental problems beyond just CO2 emissions, in particular it makes other contributions to exacerbating global warming. And there are lots of options for energy storage within the electricity supply chain.


Can the formation of gypsum evaporites (sand roses) be simulated in the lab?

Yes, it has.

Cody & Cody (1998), Journal of Sedimentary Research.

http://archives.datapages.com/data/sepm/journals/v55-58/data/058/058002/0247.htm

Abstract:

  Gypsum crystals were grown in experimental conditions analogous to
  saline terrestrial environments within bentonite clay gels by
  diffusion control at three different temperatures, four brine
  salinities, and four tannic acid (a model terrestrial humic substance)
  concentrations. The resulting crystals correspond to natural gypsum
  formed in terrestrial environments. Prismatic gypsum typically grew at
  both high and low temperatures in the absence of the organic additive.
  With increasing organic acid concentrations, the prismatic crystals
  progressively became flattened perpendicular to [001], and two
  temperature-dependent trends developed. At low temperatures, a
  hemi-bipyramidal habit dominated by 1111 faces developed, whereas the
  lenticular e103 dominated habit forme at higher temperatures. With
  progressively greater concentrations of organic material a(100)
  penetration twinning developed, secondary complex nucleation occurred
  near the twin interfaces, and finally, rosette and rosette-like
  aggregates formed. Higher temperatures generally favored better-formed
  and larger rosettes. The presence of 5% and 15% NaCl greatly decreased
  nucleation density and resulted in larger single crystals and crystal
  aggregates. The a(100) penetation twins appear to be diagnostic of
  gypsum growth in natural terrestrial sediments at a pH greater than
  7.5.

Relevant bit about gypsum roses is in bold.


Why are South African mountains short and flat?

I suspect you are referring to the mesas and buttes dotted around the Karoo - the large semi-arid plateau that makes up much of South Africa's interior. These are a product of the glacial and geological history of the region. The flat hills are capped by hard, resistant dolerite. This is solidified lava that was forced between the horizontal strata of the sedimentary rocks (which make up most of the Karoos geology) through high pressure. The dolerite erodes much slower than the surrounding rock and forms a flat cap above the underlying rock.

Most South African mountains are actually not like this - Google "Drakensberg" and you will see that the country's most prominent and highest mountain range is far from flat and short!


A better way to prevent ice shelf from melting and raising ocean levels?

The problem is that "inland" is uphill from the sea. If you can cause gravity to make water flow uphill, you can solve many more problems than just sea-level rise.


How is it possible for rocks to be trapped within another type of rock?

There are three major types of geological formations that contain or are composed of various rocks:

breccia
conglomerate
xenoliths

Breccia
The word breccia comes from the Italian word for rubble. There are various forms of breccia:

sedimentary
tectonic
igneous
impact
hydrothermal

The clast (rock fragments) within breccia are angular in shape and generally randomly orientated, a opposed to a conglomerate which is composed of rounded fragments.
Sedimentary beccia generally formed in ancient stream beds. Igneous breccia forms as a result of rocks being torn away during volcanic eruptions. Impact beccia results from the impact of meteorites. Hydrothermal breccia results from fissure opening up due to seismic or volcanic activity & hydrothermal fluids (hot water) entering the fissure causing the sides of the fissure to collapse inwards.
Conglomerate
Conglomerates contain rounded rocks bound within a sedimentary unit. They form either within ancient stream systems or in marine environments. They can also form as a result of glacial activity.
Xenolith
Xenoliths are fragments of rock contained with igneous rocks. Their spacing with the host rock is much greater than that of beccia or conglomerate - they are more isolated. They generally result from volcanic eruptions.


Interdisciplinary sciences which combine earth sciences with computer science

Pretty much all Earth Sciences combine deeply with computer sciences. In many areas where the underlying physical phenomena are not well understood, machine learning is often used, and numerical models are a very common tool in pretty much all fields in Earth Sciences.

I think some notable examples where Earth Science is working side by side with leading edge computer sciences are large scale numerical models. A large fraction of the work done by today's larger supercomputers is running atmospheric models for weather forecasting. Similar models are often run also for reanalysis of historic climate, long term climate evolution, oceanic currents, models of Earth's core and its magnetic field, mantle convection, and the list could go on and on.

Inverse modelling and tomography are also areas were leading edge computer sciences are applied to Earth Science problems. Such as reconstructing the structure of earth interior from seismic tomography, inverting for the basal conditions of glaciers, or in a more applied field; electric, seismic and magnetic tomograhies to find minerals and oil.

It terms of formally mixed fields, you can think of many, starting from my own field: Geophysics, where physics is used to understand the Earth system. Although, many geophysicist work in Planetary Sciences, where the same methods are applied to other bodies beside the Earth, of course they work shoulder to shoulder with astronomers and space scientists. And like that, there are many others, like Geochemistry, Biogeochemistry, Geomicrobiology, Biogeography, Chemical oceanography, and many others.


The phosphorous sinks are the ocean and ocean sediments.

The ocean holds $3 \times 10^{15}$ moles of phosphorous.

The annual amount of phosphorous input into the ocean, as well as the amount of burial of phosphorous as sediment is on the order of $10^{10}$ moles.

The sediment is of three categories:

Phosphorous associated with calcium carbonate
Organic phosphorous (associated with organic carbon)
Apatite

See Phosphorous Accumulation in Marine Sediments and the Oceanic Phosphorous Cycle for a detailed analysis.


It's confusing to measure liquid in units of length instead of volume, isn't it? Here's how it works.

"One millimeter of rain" is actually one cubic millimeter per square millimeter. On average, over the area you're talking about, each square millimeter has received one cubic millimeter of rain. If you divide n mm3 by 1 mm2, you get -- n mm!

The field of Dimensional Analysis deals with questions like this.

If there was "1 mm of rain", how much rain did a square meter receive? 1000 mm * 1000 mm * 1 mm = 1 000 000 mm3 = 1 liter. Pour one liter of water into a square container one meter on a side, and it forms a layer one millimeter deep.

To calculate "how much rain fell on Hong Kong" (expressed as total volume), you'd take the area of Hong Kong, and multiply it by 1 mm. That's usually not what people want to know, though -- they want to know how wet things got, and the volume-per-area number is most convenient for that.


https://www.engineeringtoolbox.com/evaporation-water-surface-d_690.html

The amount of evaporated water can be expressed as:

gs = Θ A (xs - x) / 3600                                 (1)

or

gh = Θ A (xs - x)

where

gs = amount of evaporated water per second (kg/s)

gh = amount of evaporated water per hour (kg/h)

Θ = (25 + 19 v) = evaporation coefficient (kg/m2h)

v = velocity of air above the water surface (m/s)

A = water surface area (m2)

xs = maximum humidity ratio of saturated air at the same temperature as the water surface (kg/kg)  (kg H2O in kg Dry Air)

x = humidity ratio air (kg/kg) (kg H2O in kg Dry Air)

Note! The units for Θ don't match since the this is an empirical equation - a result of experience and experiments.

Found the answer to my question.


Projecting rectangular stereography centred on 42°N, 10°E

The product (H-SAF 05) manual stated the datasets are in the projection mentioned in the title. EUMETSAT user support answered me the datasets use a polar stereographic projection with 25-75°N lat, 25°W- 45°E long.