Coriolis effect discrepancy. How to deduce the direction of the effect?

That means from the perspective of the equator to the north pole, it is rotating clockwise

That's the part you got wrong.
As seen from the Equator (as any other point on the Earth), the North pole is not rotating. The rotation only shows up in an external frame of reference. And is actually using an internal frame of reference (like an observer on the equator) what gives rise to the Coriolis force, that is not a real force but just the inertia seen from a rotating frame of reference.

From the Equator, the North pole is in a fix position, as well as the celestial north pole, that is fix to the Equatorial horizon due north. But the starts and the Sun moves around it from East to West, which is COUNTERCLOCKWISE. That's is because the observer is moving Eastwards.

Coriolis is easier to understood if you imagine that any point on the Earth's surface (or the atmosphere) north of the Equator, have to complete a smaller circle around the Earth axis every 24 hours. Therefore, those points are moving Eastwards at a slower speed than the ones at the equator. Hence, if you shoot a projectile to the North, it will have an excess Eastwards velocity relative to the ground under it, so it will tend to go Eastwards. Which will apear like it is turning rightwards.
If the projectile is flying south from the Equator, Eastwards will mean leftwards.

This schematics from Facts About All will help in an example:

Let's imagine you are at at the monument "La Mitad del Mundo" right on the Equatorial line on Ecuador. And you shoot a projectile straight North to Raleigh, North Carolina, 3,960 km North of "La Mitad  del Mundo".

Let's say your canon shoots a frictionless projectile at speed of 1,000 km/h. Then the projectile had a Northwards speed of 1,000 km/h, and an Eastward speed of 1,666 km/h which is the speed the canon at Ecuador have in order to go around the earth center every 24 hours.

Now, in 3.96 hours, the projectile would have reached the latitude of Raleigh, but in the same amount of time the eastward component of its speed took it 6,600 km to the East. However, the eastward velocity of Raleigh is only 1356 km/h

That is because at latitude 35.7° the distance to the Earth rotation axis is only 5,179 km (in contrast with 6,378 km at the equator), therefore, the distance it have to travel around it every 24 hours is only 32,540 km (in contrast to 40,000) requiring a speed of just 1356 km/h.

That means that, while the projectile wast traveling, Raleigh only moved 5,369 km eastwards, 1,231 km less than the projectile, with the consequence that the projectile ended up, 1,231 km to the East of Raleigh (The right as seen from "La Mitad del Mundo"), catastrophically missing the target, and falling in the Atlantic ocean somewhere north of Bermuda.

This excess eastward velocity visualization of Coriolis, seemingly falls apart when considering a projectile shoot due East or West. But it would still be deflected to the right (in the northern hemisphere). An explanation in such case can be found in this answer, however that answer is not as clear as I would like, as it just ignores the vertical effect, also known as Eötvös effect, which is important to make sense of the deflection of a projectile traveling East/West. In short, the increased/decreased velocity of a projectile moving East/West, increase/decrease the centrifugal force, so it moves away/towards from Earth's axis of rotation. This means "moves up" at the equator, and move south/north and up (in different proportions) north of the equator. The rightwards deflection is considered part of the Coriolis effect, while the upwards deflection is the Eötvös effect.


Could an icy/extremely-cold asteroid/comet ever strike and cool the Earth?

No.
The smallest possible velocity is about 11 km/s velocity, and that would require a near miracle. For that to happen, the object would have to enter the vicinity of the Earth through a very small keyhole near the Sun-Earth L1 or L2 point with a very small velocity (a comet will not have that very small velocity), then be nearly ballistically captured by the Moon, and then fall to Earth. A comet would be more likely to hit the Earth at 40 km/s, or larger.
And that means that it does not matter how cold or how hot the object was prior to impact. The kinetic energy of the impact will dwarf whatever thermal energy the object had prior to the impact.


formula to convert precipitation in mm/h to runoff in m³/s

When we say there was 1 mm (or 0.001 m) of rain, it is assumed that it is on a 1 square meter area, so it is equivalent to a volume of water of 0.001 $\small\mathsf{m^3}$ (or one liter). So first you have to divide your data by 1000.

Then you have time, which is easy: there are 3600 seconds in one hour. So to convert L/h in m$\small\mathsf{^3}$/s, you have to divide your data by 3,600,000:
1 L/h = 2.7778 x 10$\small\mathsf{^{-7}}$ m$\small\mathsf{^3}$/s.

You can ask this sort of things in WolframAlpha; the trick here is to "convert" mm/h, assumed by the engine to be a speed, in L/h, the volume flow rate hidden by the mm/h unit.


The Karstic aquifer is vertically divided in several zones. These zones host caves that are typical for them and are also named after them. The zone closest to the surface is called epikarst that is commonly riddeled with karren and also most efected by outer conditions. Below it lies vadose zone that is from hydrological aspect unsaturated and hosts mostly shafts and vertical caves. Epiphreatic zone is flooded occasionally and caves in this part are mostly horizontal, some have water some do not. The lowest is the phreatic zone that is flooded all the time. Passages of caves here are jumping up and down in vertical profile along fissures and bedding planes.

This is only a general explanation to find out more i would suggest this book:

http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0470849967.html


How do we know the asteroids formed at the same time as earth?

what evidence do we have that the asteroids indeed formed at the same time as earth?

It depends on what is your definition as "the same time". The formation of the solar system and Earth did not happen at a particular second in time but was rather a continuous process. It also depends on what you define as "asteroids".

I'll try to put some things in order.

The oldest known material from Earth is a zircon from the Jack Hills in Australia. Its age has been recently refined to be 4382 million years. We know that because we measured it.(1)
The moon forming event occurred sometime between 4348 and 4413 million years ago.(2) Now, that zircon should be younger than the moon (because the moon forming event would destroy any already-existing minerals on Earth). Yet, there is a slight overlap between the ages. This is due to the fact that analytical capabilities have their uncertainties and error.

This means that the Earth has been here at least ~4.4 billion years ago, because you need the Earth to have a moon. The Earth didn't just pop into existence, but it formed over a period of time, in which small planetesimals collided with each other and accreted to form a larger body.

The question now is, what is the age of the planetesimals? We can't know for sure because they are all integrated into Earth, but we can look at asteroids and see their age. We do that by dating the meteorites that fall on the Earth, which in some cases are blasted off asteroids by (even more) collisions and impacts.

When you look inside a specific type of meteorites called chondrites, you can see objects that are called CAIs (calcium-aluminum inclusions). These things are solids condensed from vapourised gas that existed in the solar nebula before any planets and planetesimals formed. These are basically the first solid to form in the solar system, and they define the birth of the solar system. We know that they formed 4568(3,4) or 4569.5(5) million years ago.

Planetary bodies (which for this discussion will be considered as km-sized chucks or rock with the ability to melt and differentiate to mantle and crust, and accrete to form proper planets) began forming around 4566.2 to 4567 million years ago(5,6,7). We know that because we can date meteorites that we know originated in asteroids. This is just 2 million years after the formation of the first solid droplets in the solar system. Now, while 2 million may seem like a long time for your daily commute, it is not too long for planetary processes (considering Earth is 4.5-4.4 billion years old).

Now there is a time gap - what happened between 4566 (formation of planetesimals and asteroids) and 4413 (formation of the moon)? There are about 150 million years that I haven't talked about yet. Was the Earth gradually growing in a linear fashion during that time or did it form rather quickly? Luckily, there are answers to that as well. Based on some measured geochemical data it was shown that most of Earth's mass actually accreted ~10 million years after the formation of the solar system(8). That's rather quick! So the Earth has been sitting there, all by itself, around 100 million years until the moon formed. As to how the Earth itself formed, it could be just amalgamation of small planetisimals, collision of larger bodies, or something completely else. Chemical evidence and physical models do not always agree, and it's all highly debated.

This is a field which is rapidly evolving and discoveries are made all the time due to better analytical capabilities and better models. Just look at the years of the papers below. This is all cutting edge and a highly exciting field of study. Everything that I wrote here can be inaccurate or even plain wrong, but that's the fun in science.

  Is there any physical evidence, or is it a conclusion reached mostly through simulation?

So it is a combination of both. You find physical evidence: rocks from Earth and parts of meteorites and their minerals. You measure their isotopic composition to find their age and other characteristics. Then you make a model (or a simulation) that tries to see what has to happen in order for the physical properties to agree.

Further reading:

An introduction to Meteorites and the origin of the Solar System - a very accessible and interesting read.

Chronometry of Meteorites and the Formation of the Earth and Moon - a more technical review, may be paywalled.

Refs:

1 Valley, J. W., Cavosie, A. J., Ushikubo, T., Reinhard, D. A., Lawrence, D. F., Larson, D. J., … Spicuzza, M. J. (2014). Hadean age for a post-magma-ocean zircon confirmed by atom-probe tomography. Nature Geoscience, 7(3), 219–223. doi:10.1038/ngeo2075

2 Carlson, R. W., Borg, L. E., Gaffney, A. M., & Boyet, M. (2014). Rb-Sr, Sm-Nd and Lu-Hf isotope systematics of the lunar Mg-suite: the age of the lunar crust and its relation to the time of Moon formation. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 372(2024), 20130246. doi:10.1098/rsta.2013.0246

3 Bouvier, A., & Wadhwa, M. (2010). The age of the Solar System redefined by the oldest Pb–Pb age of a meteoritic inclusion. Nature Geoscience, 3(9), 637–641. doi:10.1038/ngeo941

4 Burkhardt, C., Kleine, T., Bourdon, B., Palme, H., Zipfel, J., Friedrich, J. M., & Ebel, D. S. (2008). Hf–W mineral isochron for Ca,Al-rich inclusions: Age of the solar system and the timing of core formation in planetesimals. Geochimica et Cosmochimica Acta, 72(24), 6177–6197. doi:10.1016/j.gca.2008.10.023

5 Baker, J., Bizzarro, M., Wittig, N., Connelly, J., & Haack, H. (2005). Early planetesimal melting from an age of 4.5662 Gyr for differentiated meteorites. Nature, 436(7054), 1127–31. doi:10.1038/nature038825

6 Greenwood, R. C., Franchi, I. A., Jambon, A., & Buchanan, P. C. (2005). Widespread magma oceans on asteroidal bodies in the early Solar System. Nature, 435(7044), 916–8. doi:10.1038/nature03612

7 Amelin, Y., Kaltenbach, A., Iizuka, T., Stirling, C. H., Ireland, T. R., Petaev, M., & Jacobsen, S. B. (2010). U–Pb chronology of the Solar System’s oldest solids with variable 238U/235U. Earth and Planetary Science Letters, 300(3-4), 343–350. doi:10.1016/j.epsl.2010.10.015

8 Rudge, J. F., Kleine, T., & Bourdon, B. (2010). Broad bounds on Earth’s accretion and core formation constrained by geochemical models. Nature Geoscience, 3(6), 439–443. doi:10.1038/ngeo872


Are El Niños stronger when there is a longer gap from the last El Niño?

One issue here is whether El Niño (ENSO) is chaotic in nature. There is a fair amount of literature on the chaotic and deterministic nature of ENSO (e.g., https://www.sciencemag.org/content/264/5155/72.abstract, http://onlinelibrary.wiley.com/doi/10.1029/97GL53639/full). Under the chaotic assumption, the posted question might not have a clear answer.

Then there is the fact that ENSO affects the atmospheric-oceanic energy budget. If too much energy is available, then El Niño might happen, but whether it is stronger is unclear.


What tools allow a quick comparison of NetCDF output from ocean models?

For very quick visual comparison I would use Cube Browser or ncview together with a command line tool like the Climate Data Operators. For quick production of nice looking graphics (and animations) Panoply really makes good job. For further analysis or special graphics keep following your approach and script with things like MATLAB, Python (e.g. with Iris), IDL, R, ncl or whatever people around you are using.


I must admit that I was not well informed on the matter of offshore aquifers before reading this thread. Usually when I think about the hydrologic models I think of the water as a dynamic component of a system (snow, streams, moisture, glaciers) and not necessarily old water pockets somewhat trapped deep (and at the moment with no know perceptible input/ouput in the system). In line with those classical hydrologic cycle model.

I searched a bit and found this paper on physorg.org which led me to other reads on the matter.

Apparently there is substantial offshore freshwater aquifers, trapped undersea. Water from Pleistocene, which probably got trapped during the glaciations, while the mean sea level was much lower. When the ice sheet (ex: Laurentidian) receded, sea level rose and freshwater in charged aquifers would be somewhat trapped and sealed. Multiple glaciation during the Pleistocene would have enabled the process to cycle multiple time during the last 2.5 M year.

And yes - the related paper in Nature specify that some of those 30 inventoried undersea aquifers have an onshore connection (Perth among others is listed there).

This is pretty interesting but in my opinion there is not a ton of paper on the question. Yet I will keep this part of this (paleo!) hydrologic cycle in mind when such questions and discussions arise in the future.


What causes jagged appearance of mountains in SE Asia?

David Hammen has already answered with the correct term in his comment.

Karsts are formed as water dissolve rocks, typically carbonates (as limestone or dolomite) or evaporites.

Karst landscapes can originate from karst caves, formed by groundwater flowing through the rocks. When the caves eventually collapse (see image here) a rugged landscape is left behind. Karsts are also formed on the surface as limestone dissolves and forms spectacular landscapes, as the Tsingy in Madagascar or from sea erosion, e.g. calanques (karstic valleys).

The landscape is also known as Pepino Hills sometimes mogotes, if they are surrounded by flat landscape.

Another interesting feature is that as karst caves collapse, the cavity fills up with material from the ceiling and the cavity can continue to migrate upwards through the stratigraphy. Those karsts can be important channels for groundwater or petroleum. Sometimes the collapse material is more resistant to erosion than the surrounding rocks, and we get pinnacles of karst breccia left behind.


A historic yet well observed landslide in the East Kootenays of British Columbia took approximately 100 seconds to settle, Frank Slide.  The slides at Sierra Leone and the Philippines that you mentioned are a different type of slide made of mud and other unconsolidated materials.  I cannot find any information on them but I have witness a few slides in my previous forestry work.  From my observations a slide can occur in 10s of seconds, quick slump flowing fast enough that one cannot escape if you were to be in the path, the one I witnessed took a truck off the road and about 150 meters down a shallow bank the people in the truck escaped but we lost the truck.  They also can occur very slowly, we had an area that due to changes in the drainage up slope started slumping.  The slumping started in March but didn't stop until September.  In the case of the slow slide/slump it took a hectare of forest and slowly moved it down slope and across a road very slowly.  Often the speed of the slide seems to be affected by the amount of water in the soil.  The fastest being the closest to be categorized as a debris flow rather than a slide, the other factor is the steepness of the slope, the steeper falling faster.


Is the Great Artesian Basin a closed basin?

In the far north of the Great Artesian Basin, there is groundwater outflow to the Gulf of Carpentaria. Everywhere else the aquifer behaves as a closed basin with outflow in the form of vertical seepage (e.g. to the Mound Springs of South Australia), artesian overflowing boreholes, and pumped boreholes. There may once have been hydraulic connection to the Southern Ocean, but that ceased several millions of years ago - not such a long time when one considers that the longest through-flow time of groundwater, from east to west, is about two million years.


Firstly, Mars is farther away from the sun than Venus or Earth, so it gets less heat from the sun. Secondly, Venus & Earth are volcanically active, whereas Mars is volcanically inert. Thirdly, the atmosphere on Mars is much thinner than those on Venus and Earth.

The density of the atmosphere on Venus is approximately $65\ \mathrm{kg/m}^3$, whereas, the density of Earth's atmosphere is $1.217\ \mathrm{kg/m}^3$ and the density of Mars's atmosphere is $0.02\ \mathrm{kg/m}^3$. Earth's atmosphere is 60 times denser than that of Mars; Venus's atmosphere is over 3000 times denser.

With such a thin atmosphere on Mars, there is little atmospheric mass to retain heat, despite the atmosphere being composed of 95.3 percent carbon dioxide.


What Happens When India Stops Hitting Asia

You are correct in that, sooner or later (and nobody can say just when) the Indian plate will stop crashing into the Eurasian plate, and the the two plates will effectively fuse into a single plate. The underlying mantle convection is likely to continue for a few million years, tending to displace the combined plate further northward, probably with a component of anti-clockwise rotation, which might result in a few micro-continental fragments breaking off. The Yakutsk peninsular is one such possible candidate.

Probably the single most important result will be the fate of the Himalayan chain. Again, the underlying mantle is likely to take a few million years to gain litho-static equilibrium, so seismic rumblings will continue, but probably with much less intense earthquakes than we have seen recently. Fluvial erosion is probably faster than you think. Within 20 million years, and possibly even in 10 million years, all of the great mountains will be worn down to a pale shadow of their former state. More and more rivers will break through from Tibet, and drain southwards. The Himalayas will become much less of a climatic barrier than they are now, such that the monsoonal air flow, and much of the moisture than it carries, will spill over into Central Asia. The main rivers that feed into the Ganges will carry less water. The climate of Central Asia will change dramatically, but it's difficult to predict exactly how. Currently the air flow from southern Europe is deflected southeasterly across Iran and the Gulf, being effectively blocked by the Central Asian mountains. As these mountains are eroded this airflow will become progressively less hindered, making west central Asia wetter, and the Arabian Gulf even drier than it is already.

Glaciers and snow topped mountains are already in rapid decline because of global warming. The ice will certainly be long-gone by the time the tectonic conveyor belt grinds to a halt.

The eroded debris will drain into the Bay of Bengal. The current effects of rising sea level will flood most of Bangladesh in the short term, but it will ultimately be reformed as erosion overtakes rising sea level.

As for Tibet, one would expect a long period of erosion, mainly by deeply incised rivers dissecting the plateau, much as the Colorado River is cutting away at the Colorado plateau in North America; a process greatly aided by much increased rainfall.


Southern Hemisphere: What is the most Northern latitude where the sun can be seen for more than 24 hours?

The situation in the southern hemisphere is identical to the northern hemisphere, but they occur at different times of the year.

In the northern hemisphere the arctic circle is situated at 66.5 degrees North. Likewise in the southern hemisphere, the antarctic circle is situated at 66.5 degrees South. Between each circle and its respective pole 24 hours of daylight will occur for about a month or more from the onset of the summer solstice for each hemisphere.

The southernmost settlement in South America is Puerto Williams which is located at 56 degrees 56 minutes South. This is a lot further north than the antarctic circle.

To experience 24 hour days in the southern hemisphere you will have to be in Antarctica, as is evident from this picture, acquired from Wikipedia.

The Australian base at Casey is just outside of the antarctic circle having a latitude of 66 degrees 17 minutes South. However, the Chilean base at Carvajal is just inside the antarctic circle with a latitude of 67 degrees 45 minutes South.


Anyone sucessfully installed pywafo for Python 3 under windows OS?

this is probably a little late in the day to answer. I have a wafo "superficially working" on windows 10 with python 3.7.1: however, so far I have only accessed the wave spectrum models. The recipe I used was

clone the repo
pip install 2to3
navigate to the cloned folder
2to3 . -w
copy folder to src/wafo folder to site-packages/wafo
Open cmd.exe or something better e.g. ConEmu
Assuming your python.exe is in your PATH. type ... python -c "import wafo"
Then address each problem in turn...

There aren't many problems to address if all you need are the wave spectrum models. It took me an hour to hack the source code to access these. If you need to access the whole suite of functionality, continue the approach. You may need to recompile the c-libraries if they are needed.

Sorry I can't provide a comprehensive list of the changes I made to get wafo to import. Here are the ones I remember

It will complain about "import scipy.lib.six". Change to "import six" (install it)
It will complain about scipy's piecewisepolynomial. Change to PPoly
It will complain some version checks ... set to True as your module versions are no-doubt much newer than the versions 5 years ago.


NOTE: This is not the solution to the question in the title but it solves the problem described in the question's text.

Alternative solution

I would download the netCDF files from the grd directory instead of the srtm files from the data directory on the FTP server. The netCDF files can directly be plotted by GMT.

Example

Based on this file: e020n40.nc

#!/bin/bash

outfile=pic.ps
infile=e020n40.nc
invar=z
colorfile=colors.cpt

gmt makecpt -Cviridis -D -T-5200/2400/400 > ${colorfile}

gmt psbasemap -R20/60/-10/40 -JM18 -B4/4"NSEW" -X+1.5c -P -K > ${outfile}
gmt grdimage ${infile}?${invar} -R -J -C${colorfile} -O -K >> ${outfile}
gmt pscoast -J -R -Di -W1,black -O >> ${outfile}

output (pic.ps imported into GIMP v2.8.22 in 60 dpi resolution and with strong antialiasing):


Convert NO2 concentration in Sentinel-5P data from mol/m2 to μg/m3 on the ground level

...measured in mol/m² within the total or tropospheric column. Is it possible to deduce concentrations for a specific slice of the troposphere?

Not really, since you have a crucial bit of information missing: the vertical distribution.

Your alternatives are:

Combine satellite data with a model to estimate near-surface NO₂.  The model may be able to estimate what surface conditions may be associated with what total column conditions, depending on other factors.
Stick with total column data.
Use a different data source, preferably ground-based measurements.  Although a limb sounder does a much better job at getting a high vertical resolution (at expense of horizontal resolution), below 50 metre is too close to the surface.

Measuring the vertical distribution with a down-looking sensor is difficult.  You can get some information with vertical sounding by having many closely-spaced channels along a spectral line, but the vertical resolution is going to be very poor, in particular from space.  Vertical sounding is common practice for temperature and water vapour, but if you search for NO₂ vertical sounding, you will find mostly, probably exclusively, ground-based measurements.  I've tried to do CH₄ sounding and you're lucky if you can get 2 degrees of freedom of signal (DOFS), meaning a rough split in "lower half" or "upper half", but usually you get much less than that:

Source: Holl et al., (2016)

TANSO-FTS is a spectrometer carried on a satellite, PEARL-FTS is a ground-based instrument looking up.  Now this was for CH₄ (not NO₂) and for a station in the Arctic at night.  Hopefully you're not trying to do this in the Arctic and not at night, so if you try to retrieve profiles from a spectrometer (AIRS, IASI, CrIS) you can do a better job, but near-surface, probably not.  Looking up, such as PEARL-FTS does, tends to be easier than looking down because you don't have a background surface to deal with.

There are plenty of  instruments that can retrieve NO₂ total column:

Source: WMO Oscar

However, to get a good quality profile from space you need a limb sounder, such as these:

Source: WMO Oscar

A limb sounder gets a much better vertical resolution, but a much worse horizontal and temporal resolution (there are no geostationary limb sounders, and the concept wouldn't make much sense).  You can find a limb viewing geometry illustration here:

Source: Riese et al. (2014)

The best signal to noise ratio are from solar occultation limb sounders such as ACE-FTS, but those can only measure at sunrise and sunset.  And close to the surface is difficult with any limb sounder, solar occultation or not, so it is unlikely that a limb sounder would even work in your case of measurements within 50 metre from the surface.

Depending on your scientific background, I would either look for model data or use ground-based measurements.

Holl, G., Walker, K. A., Conway, S., Saitoh, N., Boone, C. D., Strong, K., & Drummond, J. R. (2016). Methane cross-validation between three Fourier transform spectrometers: SCISAT ACE-FTS, GOSAT TANSO-FTS, and ground-based FTS measurements in the Canadian high Arctic. Atmospheric Measurement Techniques, 9(5), 1961-1980.
Riese, M. & Oelhaf, H. & Preusse, P. & Blank, Joerg & Ern, M. & Friedl-Vallon, Felix & Fischer, H. & Guggenmoser, Tobias & Höpfner, Michael & Hoor, Peter & Kaufmann, M. & Orphal, Johannes & Ploeger, Felix & Spang, Reinhold & Suminska-Ebersoldt, O. & Ungermann, Jörn & Vogel, B. & Woiwode, W.. (2014). Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) scientific objectives. Atmospheric Measurement Techniques. 7. 1915-1928. 10.5194/amt-7-1915-2014.


When did/will peak conventional oil happen?

The answer depends a lot on what you mean by "excluding shale oil".  Tight oil production, commonly referred to as "shale oil" is about 4 million barrels per day currently (2014), compare to almost none in 2005.

Canadian oil sands production is at 2 millon barrels per day, compare to about 700,000 per day in 2005.

So compare to 2005, tight oil (shale oil) and oil sands production is up about 5 million barrels per day.

Now look at total world oil production:

From the graph it can been seen that subtracting out the 5 million barrels/day of unconventional production, world production is somewhat below the 2005 level. (Quantitative values were 73.9 M bbl/day in 2005; 76.9 M bbl/day in first 8 months of 2014)

With the expectation that tight oil and oil sands production will increase in share of the production, it is entirely possible that the peak in conventional production has already occurred.


How things feel is partly psychological and often doesn't have a purely physical explanation. If you run a hot bath and the water from the tap starts to feel tepid, plunge your hand into the very hot water with which the bath is filled. Hold it there for a minute or two, then put it under the tepid tap. The water will feel stone cold, though when tested with the other hand it still feels tepid.

If 85F at 7,500 ft feels hotter to you than 85F at sea level, it could be due to a number of things. On a sunny day you will get more solar radiation at high altitude, especially around mid day, and that will be in addition to the shade temperature which weather forecasters use. When walking from A to B in the mountains, we usually exert ourselves more than we would at sea level, and therefore we feel hotter.

The day you have in mind might have been especially humid in your mountain location, so that would make it feel warmer as well. Maybe your walk was when the sun was at its highest and you are comparing it to walks in the lowlands where, although the shade temperature was the same, the sun was lower in the sky or maybe there was even some cloud. And always there is the psychological aspect to consider. Our minds like to play tricks on us.


The mantle viscosity is likely to be non-linear, e.g., it could be as low as $10^{18} \textrm{Pa}\cdot\rm s$ (over shorter time scales) or as high as $10^{21} \textrm{Pa}\cdot\rm s$ (over longer time scales). In any case the values reported in the literature are somewhere between $10^{18}-10^{21} \textrm{Pa}\cdot\rm s$ and these are based on studies from earthquakes, glacial rebound etc. So you can calculate the relaxation time(s) using these two end member values.

E.g., if you assume the average i.e., $10^{19.5} \textrm{Pa}\cdot\rm s$ then we get a relaxation time of $10^{19.5}/150\cdot10^9$ (viscosity/mu) which is $2.1082\cdot10^8$ seconds or ~$6.6$ years.


How big is the influence of tree leaves on global windsystems?

Wind is largely driven by differences in atmospheric pressure.

The effect of trees and forests is to force the winds to flow over the forests. The loss of leaves in forests would result in winds having a larger impact at ground level. Also, due to the change in the surface roughness to air flow because of the loss of leaves the wind would lose less of its energy.

It has been suggested in this paper, though not yet fully accepted by many, that water vapour in the atmosphere due to evaporation and transpiration can contain sufficient latent heat to accelerate air and drive winds.


I would say the most relevant factor involved would be Radiative cooling, with ground areas closer to the buildings not losing as much heat energy as the buildings act to reflect some of the radiation back keeping those areas frost free, while open exposed areas lose more energy and experience frost.


Need different temperature change data sets explained

There are several climate datasets around the world, two in America - NASA's GISTEMP, and NOAA's MLOST, and one in the UK - HadCRUT. These are the main datasets but there are others around the world, China, Japan etc.

The datasets differ slightly in the starting date, number of met stations included, degree of interpolation, and the way they get round the problem of lack of met stations in oceanic areas.

As to being 'tampered with', this is a subtle malicious implication that the data has been fudged. It is also an insult to the scientific integrity of the thousands of climate scientists involved, whose aim, as in all of science, is to get at the truth. Of course, the data have been 'processed'. This is an essential part of data quality control to interpolate missing data, and to ensure consistency of the data set. But no data has been 'tampered with' in the sense of trying to lead to false conclusions.
One of the striking features of all the global datasets is that, despite minor differences, they all show the same basic characteristics of an accelerating global temperature - the 'hockey stick graph'.

There is much dishonesty about, but not with the climate scientists. It is the climate skeptics who are being dishonest (not to mention scientifically incompetent).


Decomposition of variables in horizontal and vertical modes

Multiplicative decomposition as defined in the post is often called factorization. It is not always possible to achieve an exact factorization. There would be some residual difference that we could denote as eps(x, y, z, t).

U(x, y, z, t) = uv(z) * uh(x,  y,  t) + eps(x, y, z, t)

Such a decomposition is not unique, however you may choose a pair of functions that minimizes the value of eps(x, y, z, t) according to some metric.

For further reading consider the description of sklearn Non-negative matrix factorization function.


How to quickly or easily prove the world is spherical?

To answer my own question based on the useful comments here, my favorite methods were:

The earth's shadow cast on the moon during an eclipse. It is easy to observe and the flat earth counter argument is so insane that if it is offered you should just walk away.
Shadows differ from place to place. The same experiment as Eratosthenes but you can carry this out locally with a piece of large card, 2 obelisks and a light source casting a shadow. Now bend the card and observe the change in shadows. The same effect could then be observed on the earth's surface. The counter argument of curved rays of light is weakened by the fact you can reproduce it locally.
triple-right triangle:
You move in a straight line for a long enough distance Turn right
90° degrees, walk in that same direction for the same distance Turn
again to the right 90° degrees and walk again the same distance
After this you'll end up at the starting point. This is not possible
on a flat surface since you'd just be "drawing" a half-finished
square. Not sure how practical this is as you'd have to walk a long way!
Although not technically about the earth being flat, in a flat earth theory the sun orbits, or at least moves over the earth. A simple way to discount this is observing parallax with surrounding stars.
It is not too difficult to prove the earth curves at least, such as by observing more objects over the horizon the further you go up. And even measuring the curvature is not difficult. Thus I believe a person could drive the length of the African continent, observing the curvature and measuring the straight line distance, and modelling that alone would show the earth curves beyond what could be acceptable on a flat earth, without all the water running off the edge!
One I haven't seen mentioned yet is showing that the flat earth map cannot work. In a flat earth, apparently, the north pole is at the centre and south pole is a ring around the outside. Pick a land mass close to the south pole, and another on the opposite side of the map. The distance you would need to travel to reach one from the other by e.g. flying east around the map would be enormous and not congruent with the flight times or shipping times in real life.
Earth is warmer near the equator, for obvious reasons in a non-flat world but the counter argument would have to be pretty imaginative.
Sunrise and sunset do not happen at the same time for everyone on earth. The difference in timezones, which can be observed by taking a trip to different countries, cannot reasonably be explained by a curved but nearly flat earth.
Experiments with gravity, but flat-earthers reject the complication of gravity (things drop just because). So I avoided this one, but it would be a compelling way to demonstrate why people on the other side of a spherical earth are not on their heads.


You were most likely seeing lightning (to be sure, a date/time and your location would be necessary).  Lightning can be visible from quite a distance and storms can be incredibly active with lightning within the clouds and from cloud-to-cloud.  Given a large distance and being inside a (relatively) loud airplane cabin it is no surprise that you couldn't hear the thunder associated with the lightning flashes.


At what altitude stalagmite/stalactite caves are located? What kind of rocks are needed to form them?

The classic text has long been "Karst Hydrology and Physical Speleology" by Alfred Bogli, - which I highly recommend.

Karstic dissolution and precipitation (to form stalactites, helictites, etc.) are basically hydrologic processes in which groundwater seeks to attain thermodynamic equilibrium with the carbonate rocks with which it is in contact. Water flows downhill towards the base-level of erosion - generally sea level. But bear in mind that during the last glaciation sea level was about -120 metres compared to modern sea level. To get very high mountain karst the system has to develop and then be lofted by other tectonic processes of uplift. In the Jebel Akhdar of Oman there are caves up to about 2 km elevation, but I guess that some limestone massifs have been elevated higher than that.


How can I create multi model ensemble from output of 3 CMIP5 models?

What is an ensemble?

An ensemble is a set of several model simulations. One simulation of an ensemble is denoted as ensemble member.

A multi-model ensemble is an ensemble created by simulations with several models (e.g. each model is run twice).

Alternatively, one might create an ensemble by performing several simulations performed with one model. Each simulation is disturbed by some noise so that the model produces slightly different result for each model run. We denote each run as a realization. The generation of the appropriate noise is model dependent (the results should cover the natural variability) and a scientific topic itself. Additionally, we might use other initial conditions or different physical parameterizations.

The individual simulations of a CMIP5 model are identified according to the rip nomenclature: rXiYpZ (r: realization; i: initialisation; p: physics; X, Y, and Z are integers), e.g. r12i1p1 or r1i1p1.

It is also explained here: https://portal.enes.org/data/enes-model-data/cmip5/datastructure

Summarizing ensemble simulations

If you calculate the mean of your models runs, you call it the "ensemble mean". If you calculate the standard deviations, you call it "ensemble standard deviation". The "ensemble" prefix just means that you calculated the mean/std.dev./etc. from an ensemble of simulations.

Example: This plot of the 5th Assessment Report of the IPCC (synthesis report of Topic 2 - Future Climate Changes, Risks and Impacts, online version) shows the ensemble mean (solid thick colored lines) and the space covered by the 5% to 95% percentiles (shaded area).

Please have a look here for the caption and more details: http://ar5-syr.ipcc.ch/topic_futurechanges.php#figure_2_1


In the USA, are pesticides regulated differently for animal vs human consumption?

I'm not familiar with pesticide legislation in the United States, but I do know that all oats are grown with human consumption in mind. Only the lower grades are used for animal feed. In the rare event that high grade oats become contaminated with insect pests, they would also be consigned to animal feed. Animals are less fastidious than humans, and don't mind a few beetles in their oats. It is highly improbable that your animal feed would be contaminated with pesticides, except to the extent that all non-organic farm produce has minute traces of it.

Most mushroom growers in UK use horse manure or stable muck as a substrate for growing their crop. The manure has to be suitably matured and not fresh. I would imagine it is cheaper than animal grade oats.


Is Iceland an example of a hot-spot overlying a mantle plume?

Yes, Iceland is an example of a hotspot overlying a plume. The plume has been imaged seismically, e.g., see the Science paper (Figure 3) by Montelli et al. (2004). It is available at http://www.sciencemag.org/content/303/5656/338

The 2015 paper you referred doesn't dispute that claim. All is says is that "The plume split off a sliver of continent from Greenland in the Early Eocene. This sliver is now located beneath southeast Iceland where it locally contaminates some of the plume-derived magmas".


Star dunes, caused by the prevailing winds coming from multiple directions.

Take a look at these different dune types.


What kinds of remote sensing required to observe methanogenic life on Titan?

Note: As I discovered after writing most of this answer, this question on Space Stack Exchange is closely related, and called2voyage’s answer uses some of the same early points that I do, as it discusses the paper you referenced.
It’s worth noting that the results of McKay & Smith were purely theoretical, and their paper was originally received by the journal on the exact day the Huygens lander reached Titan: January 14, 2005. The paper was revised that April, but data from the spacecraft does not appear to have been published prior to that date. In other words, the authors had no idea what Cassini-Huygens would find on Titan. The empirical results confirmed their calculations; the “anomaly” you speak of had not yet been observed.
Later that year, Niemann et al. published results from the Gas Chromatograph Mass Spectrometer (GCMS). The results agreed with predictions of what Titan would look like with methanogenic life. Specifically, McKay & Smith stated that there would be three main observable effects:

No acetylene (C2H2) on the surface
Very low levels of ethane (C2H6) compared to the expected amounts from photolysis. Photolysis on Titan has been studied by, among others, Romanzin et al. (2005), who include graphs of levels of ethane (and acetylene) at different altitudes.
A “sink” of molecular hydrogen at the surface, leading to a non-zero change in concentration per change in altitude
Niemann et al. found only trace amounts of acetylene, low levels of ethane. They provide a description of the GCMS (better summaries are in this presentation and Niemann et al. (1999)); I’ll give a quick overview here.

Gas from the atmosphere enters the gas sampling system, where it is first moved through a gas chromatographer (the carrier gas is hydrogen, chosen for storage efficiency), which separates gases using capillary columns. Gas is then sent through the ion source, which utilizes something called electron impact ionization, involving electron beams of 25 eV or 75 eV. A quadrupole switching lens can deflect the beams through mass filters; electron multipliers enhance detection in the low-mass regime.
The GCMS also found slightly lower levels of H2 on the surface than higher in the atmosphere; however, this difference was within the limits of uncertainty and so is not at all conclusive. That said, the Ion and Neutral Mass Spectrometer (INMS) onboard the Cassini orbiter did observe a gradient in the H2 mixing ratio. Strobel (2010) viewed this in the interpretation of the gradient supporting the methanogenic predictions of McKay & Smith. The INMS, like the GCMS, uses an ion source and then directs the ions to a quadrupole mass analyzer; the two instruments are quite distinct, but they are still quite similar, so I’ll omit a description. A good overview can be found here.
The predictions contained in the paper you cited contained three predictions, all of which have been verified. It is true that they can be explained through abiotic phenomena, as the authors have pointed out. However, the Cassini-Huygens results mean that in order to conclusively prove that methanogenic life does not exist on Titan, other predictions would need to be falsified.
One prediction involves an azotosome, a hypothetical analogue of a cell membrane composed of acrylonitrile (created by Stevenson et al. (2015)). It is considered one of the best hopes for the construction of cells in a world based around methane and ethane, like Titan. Assuming the stability of azotosomes - which Stevenson et al. consider over about 100 years - one barrier for this type of methanogenic life on Titan would be a lack of atmospheric acrylonitrile. However, the INMS confirmed previous detections of acrylonitrile (see Nixon et al. (2010)). That said, concentrations would need to be high enough for life to be possible. More detailed mass spectroscopy on the surface, including samples from liquids, could answer this question.
Another potential piece of evidence which McKay & Smith mentioned in passing is different levels of isotopes of carbon. Schulze-Makuch and Grinspoon (2005) note 12C/13C ratios of 95.6 found by the INMS, which would be caused by lifeforms processing carbon-based compounds, but Atreya et al. (2006) notes that this is only in the upper atmosphere; lower ratios (82.3, which is not drastically low but still too low) were found in the lower atmosphere. This would seem to be another strike against methanogenic life.
Finally, as McKay wrote in an article in 2010, there are abiotic explanations for the discrepancy in molecular hydrogen:

The Cassini-Huygens measurements are incorrect.
H2 particles are being physically moved down in the atmosphere.
There is a catalyst mediating a hydrogenation reaction. McKay writes that (referring to the existence of a catalyst operating at the low temperature of 95 Kelvin)

That would be quite interesting and a startling find although not as startling as the presence of life.

In summary, there are quite a few different factors that could influence whether or not methanogenic life can exist on Titan:

A lack of acetylene would indicate the presence of methanogenic life.
Low ethane levels could also be consistent.
A vertical gradient of molecular hydrogen would indicate a “sink”, possible biotic in origin.
The presence of high enough concentrations of acrylonitrile would indicate that life based on azotosomes is possible.
High carbon isotopes ratios could be positive indicators of methanogenic life.

Cassini-Huygens covered all of these to some extent using the Gas Chromatograph Mass Spectrometer and the Ion and Neutral Mass Spectrometer. Follow-up measurements to confirm these results, likely using mass spectroscopy, would shed more light on the possibility for methanogenic life, while new instruments designed to detect McKay’s alternative hypothetical catalyst could show that there is no need for life to explain the Cassini-Huygens measurements.


How were we able to measure carbon dioxide levels in earlier climates?

One method is through ice cores from the worlds ice caps.

Each year, as small amounts of snow accumulate on ice caps such as on Antarctica and Greenland, bubbled of air gets trapped.  As we drill through the ice, we can identify the air samples in those trapped bubbles, and measure directly the composition of the air in those bubbled.  It tells us much more than the level of CO₂.  For example, the ratio of isotopes of oxygen is a pretty good thermometer.  We can also see pollen, volcanic ash, and other things.

Other methods are listed at the Wikipedia article on climate proxies.  Most famous are ice cores and tree rings, but other methods are lake and ocean sediments, corals, and others.  Those methods are somewhat independent so if they confirm each other, that is good.  Errors on timing may get larger if one gets further back, and sometimes a new analysis leads too a change in timing estimates.  But for the period where we have comparable records (for example, the period for which written historical records exist), results compare pretty well!


Any stone quartz rich and smooth not porous (no visible holes) like agates, quartzite or cherts are you best bet for getting a nice tumbled stone.

A great book is:

Gems and Minerals of America: A Guide to Rock Collecting (1st Edition)
by Jay Ellis Ransom
Hardcover, 705 Pages, Published 1975

ISBN-10: 0-06-013512-3        / 0060135123
ISBN-13: 978-0-06-013512-6 / 9780060135126

Your local library might have a copy of it.
See to find on sale on Internet also: used ~$5.00

http://www.gettextbooks.com/isbn/9780060135126

BTW, tumbling stones and rock collecting led me to a career as a geologist.


What is the difference between mineral groups and series?

Yes, there is a difference.

A mineral series represents mineral which have a well defined solid solution. One of the most known examples is olivine: olivine is not a strictly defined chemical composition for a mineral, but rather a series between the forsterite end-member (Mg2SiO4) and fayalite end-member (Fe2SiO4). Note that if you find a pure end-member in nature, then you have a mineral species. Quite rare for olivine though. There's also the olivine group, which consists of other minerals that do not form a solid solution with the forsterite-fayalite series (for example monticellite CaMgSiO4) or minerals that do form a solid solution, except that it's extremely rare in nature (for example tephroite Mn2SiO4). Here's a comprehensive list of the minerals in the olivine group: http://www.mindat.org/min-29264.html

Another example is the pyroxene group. So for simple Ca-Mg-Fe pyroxenes, you have the clinopyroxene and orthopyroxene series, which consist of the end-members (species, if you find them pure) diopside (CaMgSiO6) - hedenbergite (CaFeSiO6) and enstatite (MgSiO3) - ferrosilite (FeSiO3), respectively. Intermediate clinopyroxenes are also called augite.

The distinction is not always clear. For example, the feldspar group traditionally has the plagioclase series (albite-anorthite, NaAlSi3O8-CaAl2Si2O8) and the K-feldspar species (KAlSi3O8, either microcline, orthoclase or sanidine, depending on structure). But in some cases there is a solid solution between albite and K-feldspar, forming the alkali-feldspar series. Nature doesn't always behave according to our rules, and it's important to remember that our classification systems work well with ideal systems but break down often.

Further reading


At what point is the atmospheric pressure considered to be high or low?

Usually when you hear someone say "high" or "low" pressure, it is an abbreviated way of saying "local maxima" or "local minima." And usually that pressure is the Mean Sea Level Pressure. By that definition, it is a singular point. But if you want to cover an area, you can probably reference a gridded dataset and plot the isobars. Then you can categorize the isobars as cyclonic (low pressure in Northern Hemisphere) or anticyclonic (high pressure in Northern Hemisphere). Then you can say if the location is enclosed in either, then it is in the respective area. You can make it however complex you want.
But if you want to create your own "pressure climatology" then you can probably do what you want to do.


Divergent boundary and trenches between oceanic plates

The elevation of oceanic crust is controlled by Pratt isostasy, whereby hotter crust is elevated because it is less dense. Oceanic crust is produced at mid-ocean ridges and cools as it moves away from the ridge. Mid-ocean ridges are hot and therefore they are elevated above the colder, more dense adjacent crust.

In continental rifts, the dominant process controlling the topography is normal faulting, which leads to subsidence of the rift valley floor and uplift of the sides, leading to the formation of mountains either side of the active rift. Continental rifts form valleys because they have not yet reached isostatic equilbrium and their topography is controlled by extensional faulting.


Not able to open .f000 file formats in pygrib

Figured out my error: I was assuming that I needed to alter the filename endings / type in order to save as a genuine .grb or .grib2 file. The files are already in grib2 format despite the ending in .f000 so you should be able to leave them as that.

My other error was not double checking the exact filename and path when dealing with multiple grib files across the GFS datasets. Some have slight differences in the naming convention, and when loading on pygrib it will throw the same generic "import error" as if the file couldn't be read.


Can soil color give accurate data about properties which affect it?

Unfortunately, the color itself won't give you much more information than the amount of organic matter and oxides/hydroxides. The amount of carbonate and some silicates might also be detected, but those values would be very vague without further examination of the soil.

If you want to get more information you would need some more data. The grain sizes for example (sand, clay, silt), pH-measurements, the amount of water and air, what other minerals and the salinity. You also need information about the soil biota, and so on. To collect all these data you need further research methods.
So your project idea is nice, but a picture alone won't bring you much information since the soil's properties are too complex.

Also writing such a program (I guess a mobile app?) will be hard since all cameras take different pictures under different lighting.. furthermore they all have a different processing of the pictures.
I'm not sure how computer vision could help since you'd need a special camera. So if you want to make an app you're going to have a hard time. I don't think you want to design a special device just for this.

Another aspect is that whenever you work with soil, you're going to get dirty. That's no good environment for such technology, that's why the munsell charts are used. It's no problem when they get dirty.

I really like the idea, but I don't think it'll get you far, but that's just my opinion!


What disciplines of science are used in the locating and extraction of mineral resources?

The locating and extraction of mineral resources is essentially a three step process - find, extract and process.

The first step of finding the mineral resources requires the use of geophysics, geochemistry, sometimes geobiology and geology.

Geophysics uses techniques such as magnetic studies, geological resistivity and seismic analysis to find geological anomalies. Which techniques are used depends on the minerals sought (metal sulphides or oxides), the overall host geology of the region, the remoteness of a region and proximity to infrastructure.

Geochemistry generally involves taking multiple surface samples for chemical analysis over an area of interest to ascertain if there are any geochemical anomalies. One that comes to mind is following gold samples up a river to locate the hard rock source of the gold.

Geobiology is the use of plants to locate, or discover, a mineral deposit. One example that comes to mind was the discovery of the Viscaria copper deposit in Sweden due to a particular flower that grew over the deposit and not anywhere else in the region. The deposit was named after the flower that lead to its discover - Viscaria alpina (Lychnis alpina, "copper flower"). Geobiology is not widely used.

Geologists follow up any interesting anomalies discovered by these techniques with field mapping and drilling and the analysis of drill hole sampling.

The extraction of minerals from the ground is the domain of mining engineers. They take the models produced by geologists and determine where the mine should be located - because mineral deposits are not uniform and vary widely. They also determine which parts of the mineral deposit should be mined and how it is to be mined - open pit, underground, small or large scale stoping. They also determine the equipment to be used and with help from geotechnical/geomechanical engineers they determine the maximum size of openings that the ground can support during mining operations.

Once mineral bearing rocks (ore) have been mined, the minerals must be removed and concentrated. This is done by metallurgists in a processing plant. Depending on the minerals being processed, this can involved froth flotation (copper, zinc, lead, nickel), gravity techniques such as shaking tables (tin) or spirals, carbon in pulp processing (gold), magnetic separation (mineral sands), heavy media separation (iron ore). Most mineral processing methods require the use of water. Further refining is done by another group of metallurgists during smelting, if smelting is required.


Does human body temperature impact climate change? Directly? It's not even a blip. The Earth's population is 7.6 billion. With each person radiating about 80 watts (basal metabolism), that's about 600 gigawatts, or 760 gigawatts using a round figure of 100 watts. That sounds like a lot, but it's only a tiny fraction of the 18 terawatts consumed by humanity, which in turn is a tiny fraction of the 174 petawatts the Earth receives from the Sun.

Indirectly, yes. A growing population and the desire for greater wealth by a growing population (third world nations and developing nations want to move themselves out of those categories) are key drivers of climate change.


If the accuracy of measurement of the earth's volume is not known, how can scientists assert that the earth is not expanding?

In short, the current volume of the earth is known to great precision and modern measurements show no significant expansion at meaningful scales.

Facing 20th century evidence that points on the globe -- such as the edges of continents -- that are now distant from each other were once adjacent, some scientists argued that the only explanation was the ongoing expansion of the earth's surface. That argument collapsed by the 1960s, as overwhelming evidence accumulated for the theory of plate tectonics -- that is, roughly, there are relatively rigid continental plates that move across the surface of the earth, with the ocean floor between them created at the mid-ocean ridges and destroyed by subduction under the continental margins. Broad calculations showed that the volumes of the two processes were close enough to cancel each other out.

In the modern era dependent on the accuracy of satellite positions for GPS, sea-level rise measurement, and other detailed geodetic measurements, there was a need to resolve the question of whether the earth's volume was changing in a more conclusive and precise way.

One of the studies that addresses that is the 2011 paper Accuracy of the International Terrestrial Reference Frame origin and Earth expansion, published in Geophysical Research Letters, a journal of the international American Geophysical Union. Most of the paper discusses the technical processes and calculations, but it concludes:

  A possible secular change in the mean radius of the solid Earth has
  long been suspected from various scientific disciplines. The problem
  was not settled due to lack of a proven theory and the inherent
  difficulty in actually determining such a change. By using the data
  combination and the simultaneous global inverse approach, the issue of
  aliasing from the geophysical processes due to network sparseness is
  largely overcome here. In fact, our uncertainty in the mean expansion
  rate determination is dominated by an ITRF [International Terrestrial Reference Frame ] scale drift uncertainty of
  0.16 mm yr−1 estimated from comparing VLBI [Very Long Baseline Interferometry] and SLR [satellite laser ranging]. In conclusion, no statistically significant present expansion rate is detected by our
  study within the current measurement uncertainty of 0.2 mm yr−1.


How can we measure the thickness of the Earth's mantle?

You are right...noone ever was able to make a borehole that deep. The two deepest boreholes are about. 12.300 m (40.400 ft) - those are the Kola Superdeep Borehole in Russia and the Al Shaheen oil well in Qatar.

So how do we measure the thickness of our subsurface? Think of the earth as an onion with different layers. Each of those layers (lithosphere, asthenosphere, mesospheric mantle, outer core, inner core) contain different mechanical (and chemical) properties. Due to this it is possible to infer indirectly the depth of each layer by using the travel time of refracted/reflected seismic waves (those come from earthquakes).

As mentioned before, each layer contains different mechanical properties, thus making the seismic velocity different in each layer. So on the border of each layer, those changes cause refraction or reflection if large increases in seismic velocity are involved.

Conclusion: no direct measurements possible, only indirectly derived measurements by the speed of travel from seismic waves.


How much cheaper is it to mount oceanographic sensors on elephant seals and other animals, compared using Argo floats and other abiotic sensors?

Each float costs around US$15,000 and communication, deployment and calibrations costs approximately double the through-life cost of each float.

(from http://www.argo.ucsd.edu/Argoflyer_final.pdf)
One can roughly estimate from this source, given a life-span of four years, an Argo float costs slightly over \$3.5k/yr (float only) or \$7k/yr (including deployment and calibration etc.).

...by June 2007, over 95 percent of the goal of 3,000 floats had been deployed...
...With a four-year life span per float ...
...The annual cost of the worldwide Argo program is about $20 million...

(from http://celebrating200years.noaa.gov/magazine/argo/welcome.html#float)
Based on this source all inclusive number will be in the ball park of slightly less than \$7k/yr.
So, without getting into details of whether one can be an alternative to another technically, a primitive cost comparison based on the yearly cost derived from the mentioned article and the links below it is ~7k\$/yr (including deployment and calibration etc.) or ~3.5k/yr (only the float) vs versus \$4k per tag with Tarpon fish. So if one can assume the deployment/retrieval/calibration costs are similar they will cost about the same by the end of first year. After one year the annual cost of a fish tag will keep getting cheaper and cheaper than a float until the end of its life-span.


Why are temperatures within a few degrees of the all-time high actually pretty common?

the coldest temperature is -129 F, and few places ever get anywhere near that.

This is at high altitudes in Antarctica. There are very few places with weather stations (geographically) near there.
There are more places with weather stations near the hottest places, so (because mathematical statistics theorem) there are more record max readings near the global max.


How to determine if this fault is normal, sinistral?

So, the basic geological history is given. From this, the units named Bed 1, were deposited, then tilted. Bed 2 was deposited and tilted (along with Bed 1). The entire sequence was then faulted.

So, how can we tell what the fault did?

First of all, notice that there was movement of the eastern block to the north-west. This can be deduced because all the contacts have been shifted in that direction.

So, let us undo that shift to the north-west:

Now, we can see that the contact between Bed 2 and Bed 1 does not line up. This means that we must have had movement up or down as well. The only way to work this one out is by knowing which way the contact dips. If it dips northwards, then the eastern block moved up. If it dipped south, then it would overlie all the sediments to the south. This suggests that Bed 2 dips northwards.

Upward movement of the eastern block would then reveal Bed 1 when the area was eroded.

My conclusion therefore, is that the fault moved the eastern block north-west and up, relative to the western block.

Did I miss anything? It is late, which I will claim as an excuse. If my logic is unclear, let me know and I can try add more pictures, or video of me waving hands about, which is my usual approach.


The flow accumulation algorithm essentially determines the upstream contributing area of every grid cell; in other words, what area or how many other cells will drain into a given cell. The flow accumulation algorithm is independent of rainfall as it simply determines which areas drain where, which will later be used to determine how much water actually flows based on the rainfall event and the area on which the rain actually occurs. However, the first step is just to figure out the flow directions.

The flow accumulation is typically done as part of a series of algorithms with a given DEM to determine where the river network exists and what the catchment boundaries are. This type of analysis is required in order to delineate watersheds (i.e. determine where the watershed boundaries are and how large they are) and create the building blocks for a hydrologic model, which is used to simulate the rainfall-runoff response and flows at given points, among other processes.

The flow accumulation algorithm typically used is the D8 algorithm, although if you look into the literature there are lots of versions and variations on determining flow accumulation. I am not familiar with the richdem python algorithm, but the units will be some measure of either upstream contributing area or number of upstream units in every grid cell. You will notice that the areas downstream and near outlets of watersheds have higher values, indicating that those areas receive larger contributing areas from the rest of the watershed. The next step in the analysis, likely a flow network tool, will use the grid cells with the largest flow accumulation values to determine the existence of a river network based on high accumulation values (with some value as a threshold).

The ESRI page has a good discussion on how flow accumulation works as well.

Examples

Watershed delineation can be done automatically from a DEM layer, and there are a huge number of tools to do so. Here are some tutorials and guides with GIS software, other tools exist in R or python (as you pointed out).

ArcGIS Watershed Delineation Tutorial with Arc 10.2

QGIS Watershed Delineation Example

Note that prior to the use of DEM tools, contour maps would be used to delineate watersheds by hand. This is done essentially by drawing outlines which cross contours perpendicularly through high areas, and encompass the watershed. A couple examples of that here for you as well. Note that these will not have flow accumulation since that cannot be done easily by hand, that is only a step using the computational tools.

US Department of Agriculture Example

Miscellaneous contour example and slides


Probable rainfall is constrained by several factors, both spatial and temporal. Rainfall modelling is in itself a humongous topic. You may refer to this link for having a good idea of the simulation process & maybe adapt some of the basic equations for a rough estimate by assuming some parameters as minimally affecting your site.


What is the force imposed by underwater currents?

You are looking for the drag force imposed by the fluid flow on an object:

$$F = \dfrac{1}{2} \rho v^{2} C_D A$$

where $\rho$ is the density of the fluid, $v$ is the speed of the flow, $C_D$ is the drag coefficient depending on the shape of the object, and $A$ is the surface area normal to the fluid flow.

Let's plug in some characteristic numbers for scaling. For a current of 1 m s$^{-1}$, fluid density of 1000 kg m$^{-3}$, drag coefficient of 1, surface area of 1 m$^2$, the force imposed by the fluid on the object, according to the equation above, would be 500 N.

Note that this equation is valid only for high $Re$ flows that produce turbulence in the wake of the object. The drag coefficient is estimated empirically and takes into account both skin and form drag of the object.


What is the impact of divergent tectonic plates on old mountain ranges?

The example of the East African Rift was given in a different answer.

Splitting of mountain ranges in two becomes even more apparent as you go up north from there.

The Red Sea between Egypt and Saudi Arabia is a young new spreading ocean, that cuts through Precambrian mountains.

Further north from there, the Dead Sea is a combined transform–rift zone where you have the same thing. Precambrian mountain ranges overlain by Cretaceous sediments (folded into mountain ranges) are being torn apart to form the Dead Sea depression.


Different peak and mininum discharge times for Newfoundland rivers

All of the following parameters would affect seasonal maximum and minimum flow times. Differences between the river basins:

Size of drainage area
Average relief of topography within the drainage area
Amount of groundwater entering the river (near max)
Amount of water leaking into the local water table (near min),
Underlying differences in geology of the river basins
Water usage from each river
localized weather patterns
Sun exposure (for snow melt)

Careful and detailed geological and hydro-geological study of each rover basin would need to be performed to determine exact cause of differences in timing of max and min flow times.


What wind forecast datasets are available for forcing a wave forecast model?

Yes, the GFS model is a global model. The data is released in the public domain, so you can use it for free for any lawful purpose. See complete terms of use here. You can get the data here.


What happens to sea level when a ship sinks?

It would go down.

In order to float, an object must displace a volume of fluid that weighs the same as the boat. In the case of a ship, this volume is less than the gross volume of the boat, including the air inside it. That's why it floats with the gunwales comfortably above the water. So when the boat is floating, it displaces some volume V, so relative sea-level goes up (second panel, below).

However, when the ship is submerged and full of seawater, it displaces a smaller volume than it originally did. If it didn't, it wouldn't have sunk (assuming it hasn't changed in weight).

Since it displaces a smaller volume after sinking, relative sea-level must go down. But it will still be higher than it was before the ship was launched.


Volcanoes in the Alps and Himalayas and the subduction of Tethys Sea

The end of the Tethys Sea and the initiation of the continent-continent collision that formed the Himalayas is thought to have happened about 65 Ma ago (recent studies suggest maybe only 35 Ma). And since then, that colossal collision have produced an estimated 2,500 km of crustal shortening.  That means that 2,500 km of continental surface is gone. A fraction of it was maybe subducted, other fraction squeezed under the other continent and perhaps the larger fraction shortened by thrust and folding. This massive transformation would have been enough to erase a preexisting volcanic arc, that could easily end up under kilometers of rock that came from sediments in the Tethys sea or the sourthern edge of the Eurasian plate (for example mount Everest summit is mostly composed of sedimentary rocks with fragments of trilobites from the Tethys sea).

Nevertheless, part of that volcanic arc indeed is visible now in the surface. No volcanic edifice have survived the cataclysm that give rise to the Himalayas, but the rocks that formed the arc are now known as the Dras Volcanics, a band of volcanic basalts and dacites outcrops that are part of the Indus suture zone. And that are though to originate in the Mesozoic (from about 252 to 66 Ma ago) volcanic arc that existed in the Eurasia plate as a consequence of the subduction of the oceanic crust under the Tethys sea.

This geological map of the Himalayas shows in geen the outcrops of the Indus suture zone.

Taken from The Tethyan Himalayan detrital record shows that India–Asia terminal collision occurred by 54 Ma in the Western Himalaya


Yes, a layer of snow on top of ice can melt in some circumstances. For example, one active area of climate research involves analyzing the optical properties of sea ice as they relate to incoming solar radiation. In some studies (e.g., Ehn et al. 2004) this involves snow layered on top of ice, with the snow explicitly melting (and later refreezing) over the diurnal heating cycle in some cases.

As a more specific recent illustration, this phenomenon was also reported for the Canadian Lowell Glacier in July 2018 by NASA. Abnormally warm air temperatures (up to 29°C/84°F, according to nearby surface observations) over several days resulted in the melting of surface snow while the deeper ice below remained intact - a process referred to as ablation.


Unless they are large or famous earthquakes, I doubt you will find the waveforms for specific earthquakes.

What you will find is a ton of seismic data: http://earthquake.usgs.gov/data/?source=sitenav

which you can request. Once you have requested (downloaded ect) the waveforms (probably in seed format) you will need to analyze the waveforms themselves to find specific earthquakes (request data from a time when you know there was an earthquake) and find the p/s/love ect wave yourself on the seismogram.

To read seed data, you can either find a matlab code or write your own! (Im sure there is a python equivalent at this point.)


Cloud particles are suspended in air, and their movement is governed by:

Wind; whichever way the wind blows, the clouds go (with some exceptions such as lenticular clouds; thanks jamesqf comment).  The wind is often strongest in the upper troposphere (there are no clouds in the upper atmosphere), so upper tropospheric clouds will move faster than near-surface clouds.
Convection: strong updrafts will force particles upward, as will forced convection by wind reaching obstacles
Particle size: larger particles are more likely to fall down.  Note that "fall down" may be used either relative to the surrounding air, or relative to the ground (i.e. precipitation that may or may not reach the ground).

So the type of cloud is indirectly relevant: different cloud types are associated with different particle sizes, are to a larger or smaller degree the consequence of convection, and are more or less likely to contain precipitation-sized particles.


Can we reduce the scale of volcanic eruptions by drilling some canals or bombing some holes in the crater?

I will be using for an example in this answer the collapse of the lava dome at Mount St Helens in 1980. The lava dome on top of the mountain grew between March 20 and May 18, and then a landslide caused by the angle of the top of the dome exceeding the angle of repose of the country rock caused the pressure on the magma chamber underneath to be released, causing it to instantly boil and explode. Your suggestion to relieve pressure by either drilling or bombing would have had the same effect. Drilling or bombing a hole in this dome would have caused the pressure to greatly reduce, making all of the dissolved gases in the chamber to exsolve out, causing the pressure to instantly greatly increase, over what the surrounding rock was capable of containing.

So by bombing or drilling a magma chamber that might be about to explode, you run the very real risk of guaranteeing that it will explode. The precursors earthquakes to the Mount St Helens eruption would have been the signal that something was wrong you would use to justify this intervention, and as a result you would have simply advanced the timetable of eruption.

A good analogy is that of a radiator cap on a hot car engine. The coolant inside the radiator might be sitting at 20 or 30°C over its boiling temperature, but because it is under higher pressure due to the heat and being pumped around, it has not boiled. Once that pressure is relieved, it will instantly boil out of the radiator because of the reduction in pressure.


Why is almost all the landmass on one side of the globe?

NVZ is correct. Get a palaeo-geographical atlas and see how the the distribution of the continents has changed over time. There is much more ocean than land, and it has ever been so, but there is no particular pattern to the way the continents have drifted. It's not quite random because the heat distribution in the mantle isn't random, but given the conveyor belt system of plate tectonics there will always be a tendency for crustal plates to clump together before breaking up and then clumping together somewhere else.


Are there any consequences to carbon capture and storage that also sequesters oxygen?

No, I think there are not. At least not at the scale of the proposed projects. I say this just because $\text{CO}_2$ makes up only a 0.04% of the atmosphere, so even if you burn fossil fuels until you double the pre-industrial amount of CO$_2$ and then capture and bury it back (both the Carbon and Oxygen). You would only drop Oxygen levels from its current 20.95% to 20.91% or something like that, which is not very significant. In a closed space like your bedroom for instance, you would probably make a bigger change in the Oxygen level by just breathing inside for a few minutes.

Also, many chemical reactions that sequester Oxygen and are sensitive to its concentration (oxidation and combustion for example) would work towards keeping equilibrium: they will slow down if there is less Oxygen allowing the concentration to bounce back. Or they will accelerate if there is too much Oxygen, dropping the level back down.


What are the usable minerals that can be found in our daily life?

This question is somewhat vague & broad. It almost looks like a homework question.

For starters, in the kitchen there's salt, NaCl.

In the bathroom, talcum powder, which is ground up talc.

In the garden shed there's fertilizers.

In the yard, soil contains a numerous minerals, which will differ from location to location because of different types of soil. Locations with sandy soils will contain silica.


Tipping bucket rain gauge measurement, normalizing

mm per square meter is a measurement of volume, it's not really a depth divided by an area. You can tell as much because if you have 1 mm per square meter and you increase the coverage area to 2 square meters, the depth doesn't change---the volume increases. You just need to convert your volume measurement.
$$
1.2 mL = 1.2 cm^{3}
$$
1.2 cubic centimeters is equivalent to a 1.2 cm depth over an area of 1 square cm.
$$
1.2 cm = 12 mm
$$
$$
1 cm^{2} * \frac{1 m^{2}}{100^{2} cm^{2}} = 0.0001m^{2}
$$
12mm per 0.0001 square meters is not a useful metric. You have to obviously make the square meters 1 square meter, but you have to be careful. When you increase the area, the depth will necessarily decrease (because the volume has to be equivalent). Multiplying the area by 10,000 square meters per square meter will give you 1 square meter; subsequently, the depth must be divided by the same amount.
$$
\frac{12mm}{10,000} = 0.0012 mm
$$
So you have 0.0012 mm per square meter with each tip of the rain gauge. We can check our work by converting it back to a normal volume.
$$
0.0012 mm * 1 m^{2} * \frac{1000^{2} mm^{2}}{1 m^{2}} = 1200 mm^{3} = 1.2 mL
$$
As a side note, here is a useful tool provided by the United States Geological Survey for converting depth per area measurements to equivalent volumes:
https://water.usgs.gov/edu/activity-howmuchrain-metric.html
Edit
Going back to the depth given by the data sheet, I ran the numbers and
$$
(0.2794mm)/(1000mm/m)*(0.0055m^2) \approx 1.54 mL
$$
which about matches the volume you have. So if you want the depth for one square meter, you just have to multiply the area by the factor of $\frac{1m^{2}}{0.0055m^{2}}$ and divide the depth by the same factor. So essentially you want to multiply the depth by the catchment area of the gauge.
$$
(0.2794 mm) * (0.0055 m^2/m^2) = 0.00154 mm
$$
as the depth for 1 square meter.


How do I interpret the specs of a weather balloon?

The weight of a balloon determines most of its specifications, though I'm not sure if they are generalized or specific to a manufacturer.  Looking at one supplier we can get a feel for what you need.  For a 1 kg payload it looks like you'd want a minimum of a 1200g balloon.  According to the site linked, this 1200g balloon will have:

6.0 ft diameter at launch
113 ft$^3$ volume at release
320 fpm ascent rate
28 ft diameter at burst
109,000 ft altitude at burst
1190 g free lift

If you need 2kg of payload you'd need to size a bigger balloon.  In general your application is not different from the specs of a normal upper-air sounding launch, so you should be able to spec your balloons directly from suppliers of sounding balloons.  All of the balloons for a 1-2 kg payload should burst above 100,000 feet so it just a matter of picking a supplier and a balloon sized for your payload (per the manufacturer specifications).


Why are climate anomalies calculated relative to 1981-2010 average?

In theory the choice of baseline average is irrelevant, because the purpose of using anomalies to to clearly see the change over time, allowing different absolute values to be compared.

Although in climate studies, we try to use baselines that are as 'pre-industrial' as possible to try and get the change from 'natural'.


How would a Mars rover identify a microbialite fossil?

I'm basing this answer off an article: Kevin Lepot, Karim Benzerara, Gordon E. Brown Jr., Pascal Philippot (2008). 'Microbially influenced formation of 2.7 billion-year-old stromatolites'. Nature Geoscience Vol.1 No.2, pp.118–121. DOI: http://dx.doi.org/10.1038/ngeo107

Instruments that are desirable (and are actually used) to study stromatolites/freshwater microbialites:

Raman microspectroscope
Confocal laser scanning microscope
Scanning transmission X-ray microscope
Transmission electron microscope (TEM), including high-resolution TEM
Near-edge X-ray absorption fine structure spectroscope
The usual sets of fine analytical chemistry and microcutting tools

As you might suspect, this may require rather massive, power-hungry and bulky rovers. There is a solution and it's called sample return. Although the tools and instruments are constantly evolving and undergoing miniaturization, a skilled and attentive lab researcher will find out more back here on Earth than a rover on Mars.

Another consideration in favor of sample return is the verifiability of possibly sensational results - the sample will be curated and subdivided between universities and labs worldwide, applying diverse techniques and not relying on a single set of ultra-costly but possibly systematically biased hardware.


Open-source earth model for climate change

NOAA-GDFL model system for CMIP6

The Geophysical Fluid Dynamics Laboratory (GDFL) of the National Oceanic and Atmospheric Administration (NOAA) uses an coupled open source modeling system for their contribution to CMIP6. CMIP6 is the 6th Coupled Model Intercomparion Project (CMIP6) on which basis the Sixth Assessment Report of the IPCC (the upcoming report) will be partly based on.

The model system of the GDFL consists of several components that have to be compiled invidually and couled to each other. The ocean is represented by the Modular Ocean Model v6 (MOM) and the atmosphere is represented by their Atmosphere Model v4.5 (AM). Both models are open source. But, I am not sure under which licence they are published. There are further components needed for the proper climate model system setup. Have a look in this json file for possible combinations.

Educational climate model: Planet Simulator

This text section was already posted by me as an answer to the question Simple Climate Models that Predict Climate Change.

The Meteorological Institute of the University of Hamburg, Germany, provides and simple model called "Planet Simulator" (PlaSim).

The Planet Simulator is mainly made for educational purposes and runs on personal computers. However, it is also parallalized and can be run on HPC clusters. There exists an Documentation and the source code is said to be well commented. The whole source code is open source. The programming language is Fortran. One should be able to compile it with gfortran under Linux.

The Planet Simulator offers a GUI (after compiling successfully) to set up da model simulation and run it. There is code for postprocessing included. Thus, there is not need for additional postprocessing software. If you write out the output as netCDF, which is the quasi-standard output format of climate models, it might be practical to install ncview or Panoply because these are common netCDF viewers with which you can look directly into the output files.


A very quick and general answer, if anyone wants to get more specific, feel free:

  the question is, El Niño phenomenon in Iran is likely to achieve? What
  are the consequences?

Iran's been through several El Nino's, so its not like this year you'll see things you've never seen before.   I mean, you could.  There's always a chance of record breaking weather, but have a look at El Nino's and how often they occur, here and more numerical and monthly specifics here.

If we assume this year will be a strong El Nino, then look back at weather in Iran in winter 97-98 through Summer 1998, and Winter 82-83 into 1983.  Those were the 2 most recent big El Ninos.

I found this article from last month.  You probably have better access to local updates than I do, but it seems that frost and flooding are the primary concerns.    As Gordon Stranger points out, that's not a guarantee, only an increased chance that it happens.

  El Niño is close to Iran

El Nino is in the Pacific Ocean.   The El Nino effect is all over the globe, so it's, in a sense, close to everywhere on earth.  Here's a kind of cool picture of the effects of the 1982-83 El Nino.  Those were just the effects for that one year, and no two El Nino's will affect the globe in the same way, though they can have some similar patterns.

Source

  However, you should be afraid of the possible occurrence of El Niño in
  Iran?

When I first read this, I thought you were suggesting that he be afraid, but reading it again, I think what you're asking is whether you should be afraid.

El Nino probably isn't something to be afraid of cause there's no guarantee the effects will be bad where you are.   It's silly to worry about a 30% increased chance of something happening - which is basically what this is.

If you live in a flood prone area try to prepare for flood.  Have food and drinking water on hand, maybe sandbags to put in-front of your doorway - which might help for a smaller flood.  If you're a farmer, as much as possible, try to prepare for Frost.   Fear isn't helpful, but planning ahead for possible bad weather events is always a good idea.


What is the difference between a "flood" and a "flash flood"?

Flood: An overflow of water onto normally dry land. The inundation of a normally dry area caused by rising water in an existing waterway,
  such as a river, stream, or drainage ditch. Ponding of water at or
  near the point where the rain fell. Flooding is a longer term event
  than flash flooding: it may last days or weeks.

  Flash flood: A flood caused by heavy or excessive rainfall in a short period of time, generally less than 6 hours. Flash floods are
  usually characterized by raging torrents after heavy rains that rip
  through river beds, urban streets, or mountain canyons sweeping
  everything before them. They can occur within minutes or a few hours
  of excessive rainfall. They can also occur even if no rain has fallen,
  for instance after a levee or dam has failed, or after a sudden
  release of water by a debris or ice jam.

  Source: National Weather Service Weather Forecast Office


Is there a measure for the "dominance" of a city's population?

Exciting question... it's something I've wondered as well, both for interest purposes and for utility in programs like you mention (I posed a fairly related question in the cartography SE site proposal).  I've searched a long time but could not find any term/calculation for this... perhaps I too just did not know the correct term to use?

As a result, for a very basic calculation, I created an Excel spreadsheet and worked with US locations to formulate a simplistic prominence... calculating just the distance each city is from the nearest larger city.  The outcome was this Sporcle quiz.

My results are likely not of great use for within a mapping program, as it takes no account of the degree of relative population size... but certainly would be interested in knowing more about that as well, as I've looked for a way to better prioritize the cities shown in a weather mapping solution I use.  Not sure you'd be able to use contouring methods given the discretized nature of population.  Instead I'd imagine perhaps iterating until you find the radius from the city border centroid where the surrounding population matches the population of the city.   That sound like a more complex GIS problem, one I've considered asking before but haven't even been sure how to narrow down into a basic enough question for SE!  Still, if there's no luck here of existing formulas, and you work out what way you want to calculate such a prominence (and can then boil it down to a basic question) GIS StackExchange may be the place to try.  Hopefully you'll give us the link to any questions you propose there so users here can follow any resolution!

If the basic prominence I calculated is somehow useful, I could dig up the full spreadsheet.  I believe I also might have found a potential global dataset as well, but never followed it up.

I cannot exaggerate how exciting it is to see someone else thinking about this topic, and hope your question brings some further better answers from those in the know!


If there's acid rain, is there such thing as acid snow?

As explained by user voltaic at reddit:

  Yes, there is, and it can be more of a problem than acid rain.

  For one, when snow is falling it spends more time travelling through
  the atmosphere before hitting the ground than rain. As a result of
  this, it has more time to collect pollutants, and can become more
  acidic than typical acid rain for the same region. There's additional
  factors that complicate this however, such as the solubility of the
  pollutant, the temperature and the water content of the snow, etc.
  (e.g. warmer snow which is more "wet" is going to dissolve more than
  cooler, drier snow.)

  Once the snow hits the ground, the dissolved pollutants are going to
  stay in solution, or trapped within the crystalline structure of the
  snow until it melts. Because of this, snow can pile up and then thaw,
  releasing all the pollutants and acidic water in a relatively short
  amount of time. This can have fairly substantial effects on the
  environment.

  You can read a bit more about this here:

  http://www.elmhurst.edu/~chm/vchembook/191acidsnow.html
  http://dwb4.unl.edu/Chem/CHEM869V/CHEM869VLinks/www.qesn.meq.gouv.qc.ca/cc/acidrain/info6.htm

Acid snow is also mentioned in passing on the acid rain wikipedia page.

The "fairly substantial effects on the environment", as described by the links above, largely involve a large release of acid during the spring thaw, which effectively releases all of the acid built up over the winter in a relatively short period. This can result in lowered pH in waterways, which can affect fish, amphibians and crustaceans.


What is the reason for differences between these GHCNM and ERSST data?

The maps shown below are from here.

Actually, except for the deplorable comments (your "here" was a self-titled deplorable blog site), the maps are from NOAA itself. The maps without deplorable annotations:

What is the difference between the two data sources used?

The most obvious difference is that as the name implies, the ERSST includes data from over the oceans. These data are gathered by buoys, ships, and satellites. A not so obvious difference is that NOAA's  merged land–ocean surface temperature analysis incorporates GHCN-M land-based stations that are not used in the GHCN-M land-only map. The locations and ages of the 7280 Global Historical Climatology Network (GHCN) stations are depicted below. Note that the vast majority of the stations in Africa are less than twenty years old.

The land-only analysis uses GHCN-M stations only. It does not use satellite data. Because of this it excludes stations that don't have a solid history of measurements from 1981. This would include the GHCN-M station at the Kigali International Airport in Rwanda, whose data coverage over the last 40+ years is only 48%. The GHCN-M-based land-only map only uses about 2600 of the 7280 GHCN-M stations.
The NOAA Merged Land Ocean Global Surface Temperature Analysis uses satellite data as a sanity check. This enables it to use most of the ~4700 GHCN-M stations excluded from the land-only map.


Why has the Earth's average sea level risen 'only' by nine inches after one degree C increase in temperature?

You should take into account isostasy. As there's more water in the oceans, the crust underneath bends under the weight, creating more room for it. At the same time, continental crust heaves above the oceanic, hence the small value.
A question here to be careful about is where the location of the measuring point, as it very well may not be stable.


What sort of climate zones would be present if Earth was tilted like Uranus?

A paper on this topic just appeared: Multiple Climate States of Habitable Exoplanets: The Role of Obliquity and Irradiance.

In case of 90° obliquity, summer and winter would appear together with day and night, respectively. This means, in summer one hemisphere completely faces the Sun with 24h daylight a day causing extreme hot summers. The temperatures in winter very much depend on the hemisphere. In the Southern Hemisphere, oceans are predominant compared to the continents, having a very low albedo makes it possible to store the heat in summer. Thus, the winters in the Southern Hemisphere are still warm. In contrary, the Northern Hemisphere becomes rather cold in winter due to the small heat storage in the oceans.

The equator region is the coldest region on the planet, since this region has the lowest incoming solar radiation (Fig. 1a,b). This could lead to sea ice building around the equator region and provides an alternative hypothesis to Snowball Earth (Williams, 2008): The High Obliquity, Low-latitude Ice, STrong seasonality (HOLIST) hypothesis for pre-Ediacaran glaciation.

The warm poles and the cold equator significantly change the dominating jets. The mechanism can be explained by the thermal wind equation:
$$
p \dfrac{\partial u_g}{\partial p} = \dfrac{R}{f} \dfrac{\partial T}{\partial y} ~~,
$$
where $p$ is the pressure, $u_g$ the geostrophic zonal wind, $R$ the specific gas constant for air, $f$ the Coriolis parameter, $T$ the temperature, and $y$ the meridional distance in meters. The thermal wind equation shows that the vertical change in zonal wind is proportional to the meridional temperature gradient. Thus, the sign change of the meridional temperature gradient causes a sign change of the zonal wind. This means that the dominating jets turn into easterlies due to the reverse meridional temperature gradient (Fig. 1c,d).

However, the climate also depends on the initial condition of the planet, i.e., multiple climate states are possible for the same parameters. In case of 90° obliquity either a so-called "Uncapped Cryoplanet" or an "Aquaplanet" state exists (for further details see Kilic et al., 2017). An Uncapped Cryoplanet has large areas of sea-ice around the equator and a permanent open ocean at the higher latitudes. This climate type posses a previously unknown meridional atmospheric circulation which is neither a thermally direct nor indirect cell but rather a superposition of both cell types (Fig. 1e).

Figure 1: Uncapped Cryoplanet (left column) and the Aquaplanet (right column) for a planet with 90° obliquity in southern summer: (a), (b) zonal mean air temperature, (c), (d) mass stream function (colour, positive for clockwise overturning) and zonal-mean zonal wind (contour, positive for westerlies), and (e), (f) the poleward energy flux for the eddy and the mean contribution, the total energy flux, and the meridional heat flux in the ocean. Note: The figure shows an aquaplanet configuration, i.e., continents were neglected.


If a very huge Earthquake occured anywhere on Earth could waves emerge to come together again on the opposite side?

It is called "antipodal focusing". See for example Antipodal focusing of seismic waves observed with the USArray.

  We present an analysis of the M-w = 5.3 earthquake that occurred in the Southeast Indian Ridge on 2010 February 11 using USArray data. The epicentre of this event is antipodal to the USArray, providing us with an opportunity to observe in details the antipodal focusing of seismic waves in space and time. We compare the observed signals with synthetic seismograms computed for a spherically symmetric earth model

The above paper deals with "body waves" that travel through the interior of the Earth.

There are also Rayleigh waves that travel on the surface and can travel around the Earth several times before dissipating (Wikipedia). Antipodal focusing of seismic waves due to large meteorite impacts on Earth does numerical simulations of surface waves at the antipode of the Chicxulub impact. The waves do not arrive at the antipode at the same time because of Earth’s ellipsoidal shape and different rock properties along their paths.

  Isosurfaces of the norm of the peak displacement vector after a vertical impact for the impact hemisphere (left-hand side) and antipodal hemisphere (right-hand side).

(They say: "Note that contours of the continents are today’s, not their end Cretaceous positions, and therefore do not show the original Chicxulub antipode 65 Ma.")