Where did the sand in the Sahara come from?

The sand IS the original dirt, or at least what's left of it.
Sand is one of the major constituents of soil. Soils are roughly half minerals by volume and those minerals are silt, sand, and clay. In fact sand is often the largest single constituent of most common soils. Silt and clay are smaller and lighter, and can be moved by wind much easier when dry, this leads to the removal of everything but the heavier sand particles in very dry conditions.   What has happened is that without water and life to bind the material together, wind has removed all the lighter particles leaving nothing but sand and pebbles. Wind is good at sorting grains by size so each area tends to only have one grains size.
Where it came from originally
. Sand is just weathered rock, if you look at a map of the sahara there are quite a few scattered mountains and highlands in the desert. That is where the sand (and the original silt and clay) came from originally, weathering of rock, and the sahara is mostly exposed rock, with sand only making up a minority of its surface.
I suggest the wiki for getting started on soil science, if you are interested, https://en.wikipedia.org/wiki/Soil
More on what sand is, http://www.sandatlas.org/sand/
More on wind driven sorting, https://people.ucsc.edu/~jzachos/migrated/eart120/lectures_08/LECT7B.pdf


How to calculate the specific humidity based on the saturated specific humidity?

The answer is easy. Replace $T$ with $T_d$, where $T_d$ is the dewpoint temperature.
I will say I am not all that familiar with those equations, but that is besides the point.


Making a local geological field trip an interesting and educational event for children?

You live in an very good state for interesting geology, rock collecting, etc.  In regards to looking for things the kids can collect, view and otherwise analyse the PDF, "The Collectors Guide to Rocks, Minerals, and Fossil Localities of Utah" would be a good start to your research.  The publication is from the Utah government and covers a large number of areas in the state.  Over 30 years ago I made a trip to the Caineville just east of Capital Reef National Monument and collected pelecypods, they where laying on the soil with the occasional gypsum spars.  I believe the area is in the document I suggest you read, I doubt I could find it now but there was lots to find in the area in general including some evaporative type minerals, agates, and fossils.

You also have the Great Salt Lake, some areas would be good to collect and view brine shrimp, protozoa, and algae with a microscope, many would be easily viewable with a dissecting microscope.  You could also discuss the geological history of lake Bonneville of which the Great Salt Lake is but a remnant.

Finally the Gem Trails of Utah guide can provide some sites where collecting might be appropriate, though this publication is getting old and doesn't focus much on geology.

The land status and access to these areas change frequently and sometimes it is difficult to locate the sites, expect some failures in your adventures.  I would also suggest that you field check the surrounding areas because published areas often get damaged by careless individuals.  Finally, would also suggest you follow leave no trace principals as much as possible within a collecting trip, the scenery and wildlife in many of these areas are really impressive and it is a shame to see it all dug up by collectors.

As a final thought most states have some form of Geological Road Maps, there are some listed on this government site.


How do cations control the crystal structure of silicate minerals?

I would say that cations would control the structure in several ways; in the case of aluminum octahedra in aluminosilicates, for example, they might completely influence it by causing the presence of completely separate alternating layers of bonded octahedra. The octahedra may even dominate the unit-cell, appearing in a larger numerical and volumetric capacity than the tetrahedra.

Additionally, the different bonded cations have different polarities, and by extension, exert different forces on the relevant bonds; this plays a huge role in determining how the structure responds under conditions of high pressure relevant to the Earth's interior, e.g determining where shearing takes place, etc.


What is the reasoning behind the statement "Faulting will occur along the plane where the shear stress is the highest"?

This statement is referring to depths within the crust where the lithostatic pressure is sufficiently high to suppress the formation of dilatant fractures. Rock is a brittle material, and if loaded to failure while under little or no confining pressure, it may fail by the growth of mode-I fractures oriented normal to the least compressive stress. At depth in the crust, the overburden weight of rock may cause sufficient pressure to suppress the growth of mode-I fractures, but if the stress is sufficient to cause mode-II fractures, these tend to grow in the plane of maximum shear stress.


Growth of polar vortices vs projective geometry; what does this figure mean?

I suspect that this diagram has nothing to do with polar vortices in the meteorological sense. It’s hard to prove a negative, but digging into the source of this image led me in some very non-meteorological directions.

The file itself is entitled ‘Growth measure and vortices’ on Wikimedia (note absence of ‘polar’), with a source of ‘own work’ (by the user ‘Snowy Weather’) and the description ‘Projective geometry block in a Waldorf high school’.

Apart from the ‘Projective geometry’ page, the only Wikipedia page using this image is the one on Waldorf education, where it’s described as ‘Student work from a projective geometry block in a Waldorf high school’. The image was added to both the projective geometry article and the Waldorf article by the same user (not the original uploader of the image), who doesn't seem to have any background in meteorology. This makes me suspect that the ‘polar’ may have been added in error.

On the ‘Projective geometry’ page, the image is described as being ‘based on the work of Lawrence Edwards’. Almost certainly, this must refer to Edwards’ book Projective Geometry, which seems from the reviews to be rather esoteric:

‘The reason why modern materialists are unable to understand anything of a spiritual nature is that their ways of thinking, based purely upon sense perception, are much too rigid. Books such as this can help loosen such rigidity.’
‘… some of the terms that Edwards uses (e.g. "breathing involution") may actually be his own creation… and this made cross-referencing the book with other projective geometry texts a little harder.’

The same author has written a book entitled The Vortex of Life – again, not related to meteorology – suggesting to me that he may be quite keen on the word ‘vortex’, perhaps in a broader or more unusual sense than one might find in the mainstream of scientific literature.

In short: the word ‘polar’ may or may not have been added in error by a Wikipedia editor, but in either case I am fairly confident that the ‘polar vortices’ referred to here have nothing to do with meteorology.


How to distinguish P, S, Love, and Rayleigh waves in a seismogram?

There are two important ways to recognize different types of waves in seismic records:

Their velocity. These waves travel at different speeds: P-waves are fastest, then S-waves, then Love waves, then Rayleigh. Since seismic recordings are measures of earth displacement, particle velocity, or water pressure over elapsed time, this means the waves show up at different times in the record. If we know or guess their velocities, then we can model the arrival times at various stations and try to recognize the different wavefronts. Here's one example of a shot record (distance x on the horizontal axis, time t on the vertical) where you can see reflected P-waves and Rayleigh waves: the slope of the arrivals is a function of wave speed. Once we can discriminate them in some domain (commonly t–x, f–x, or tau–p), we can design filters that exploit this fact.
Their mode of oscillation. The waves are distinguished by different types of particple motion. For example, P-waves are longitudinal, S-waves are transverse, Rayleigh waves are circular. So if we have a sensor that can detect particle motion in three dimensions, we can recognize waveforms that way. In the oil & gas industry, where seismic reflection data is an important tool, so-called multi-component (or three-component, or 3C) sensors are now widespread; here's one example. I'm afraid it's beyond me, but I know one of the methods they use to unpack the different waveform polarizations is singular value decomposition.

Reconciling P- and S-wave reflections is one of the great problems in reflection seismology today. Everything is made more complicated by the fact that these waves can convert from one to the other. For example, when P-waves reflect from an elastic interface, like rock broundaries, some energy is converted into S-waves. Furthermore, some recording equipment is more sensitive to vertical ground motion than to horizontal (e.g. single component geophones), so our records are often strongly filtered. The result is that unpeeling multiple wave types is not easy.


After quite a bit of conversation on Twitter, I think it's arbitrary. Tradition is probably the prevailing reason.

It would be interesting to go back through the literature to see who first used it. My hunch is that it goes back to the Zoeppritz equations (Zoeppritz 1919), which feature both $V_\text{S}/V_\text{P}$ and $V_\text{P}/V_\text{S}$. I bet Aki & Richards (1980) also had something to do with its propagation, at least in the exploration geophysics community.

Thinking about it, I think there are some good reasons to use $V_\text{S}/V_\text{P}$ instead of $V_\text{P}/V_\text{S}$.

It's well-behaved

As the OP said, $V_\text{S}/V_\text{P}$ behaves nicely, being constrained in the range [0,1) for rocks and fluids (and weird things like bitumen) — compared to $V_\text{P}/V_\text{S}$, which varies in the range 1 to infinity/undefined. I suppose you could call that 'neat'...

It's a good gas indicator

If you have a background of brine (say) and want to see gas anomalies, then my insufficient research suggests that $V_\text{S}/V_\text{P}$ is actually a better discriminator:

It's in the Aki–Richards equation

This is the formulation from Avseth et al. (2006):

$$ R(\theta) = \frac{1}{2} \frac{\Delta \rho}{\rho} - 2 \left( \! \frac{V_\mathrm{S}}{V_\mathrm{P1}} \! \right)^2 \frac{\Delta \rho}{\rho} \sin^2 \theta + \frac{1}{2} \frac{\Delta V^2_\mathrm{P}}{V^2_\mathrm{P}} \frac{1}{\cos^2 \theta_\mathrm{avg}} - 4 \left( \! \frac{V_\mathrm{S}}{V_\mathrm{P1}} \! \right)^2 \frac{\Delta V^2_\mathrm{S}}{V^2_\mathrm{S}} \sin^2 \theta $$

Refer to the book or SubSurfWiki for the symbol definitions etc.

Hmm, none of these are reasons why $V_\text{P}/V_\text{S}$ prevails. This is starting to look like the $\pi$ vs $\tau$ debate...

References

Aki, K, and PG Richards (1980). Quantitative Seismology: Theory and Methods. WH Freeman and Co.
Avseth, P, T Mukerji, G Mavko (2006). Quantitative Seismic Interpretation. Cambridge University Press.
Castagna, J, and H Swan (1997). Principles of AVO crossplotting. The Leading Edge, Society of Exploration Geophysicists, 17, 337–342.
Smith, T, et al (2003). Gassmann fluid substitutions; a tutorial. Geophysics (April 2003), 68(2):430-440. DOI 10.1190/1.1567211.
Zoeppritz, KB (1919). Erdbebenwellen VII. VIIb. Über Reflexion und Durchgang seismischer Wellen durch Unstetigkeitsflächen. Nachrichten von der Königlichen Gesellschaft der Wissenschaften zu Göttingen, Mathematisch-physikalische Klasse, 66-84.


I will first focus on the 214Bi decay. The 3.272 MeV is the total amount available for the β- decay, i.e. the difference between the ground states of 214Bi and 214Po. If you have a beta decay into the ground state of of 214Po, which happens in 19.9 % of cases (all data are from Firestone, R. B. et al., “Table of Isotopes”, 8th ed., 1998, p. 9211, in short “ToI”), there will be no gamma emission from 214Po, the 3.272 MeV are distributed between the electron and the electron antineutrino. However, in 16.9 % of cases, the decay leads to an excited state of 214Po with an energy of 1764.499 keV which can then deexcite among other possibilities by emission of a 1764.494 keV gamma photon (15.36 % of beta decays). The decay can produce a large number of gamma ray lines, but most happen with low probability. You can have a look at page 23 of this 214Bi table of radionuclides extract to get an impression.

In summary, the 3.272 MeV get distributed in varying proportion to the electron and the electron antineutrino from the beta decay, zero or more gamma-ray photons, and some small amount to nuclear recoil, etc.

In the case of 40K decaying via electron capture to 40Ar (10.72 % of cases), the total decay energy (Q-value) is 1504.9 keV. Most of the time (10.67 %), this goes to an excited state (1460.859 keV), which in turn gives rise to the 1460.830 keV gamma-ray line. The rest of the energy goes to the electron neutrino.

Similarly, for 208Tl, the 5000.9 keV is the Q-value of the β--decay. Most of the time (48.7 %), the decay proceeds via an excited state (3197.743 keV) of 208Pb, which deexcites via another excited state (2614.551 keV) where 99 % of decays also lead. This state the deexcites via the emission of a 2614.533 keV gamma ray photon. I believe the 2.82 MeV from Fig. 15.1 is a typo, since the reference in Reynolds’ book points to the article “Airborne Gamma-Ray Spectrometry Surveys”. There Fig. 4.4-1 is the same as Fig. 15.1 from the book, but in rather low resolution and with hard-to-read numbers. The text, however discusses the 2.62 MeV gamma ray line, which is very likely a rounded value of the 2614.533 keV from the “Table of Isotopes”.

The sum of the probabilities of different gamma ray lines from the same decay can be larger than 100 % if the deexcitation happens via a gamma-ray cascade, i.e. if the nucleus first transitions into an intermediate excited state and then again to the ground state or further intermediate states. This means that a single beta decay results in multiple gamma-ray emissions. This is illustrated in the Wikipedia article on Gamma rays using the example of the 60Co decay which results in two photons emitted in > 99.9 % of cases.


How many trees would I have to plant to solve Global Warming?

In 2010 anthropogenic emissions (not including land use change) were approximately 9167 million metric tonnes.  Your data on trees holding 13 lbs (5.9 kg) of carbon per year equates to 169.6 trees per metric tonne of emissions.

So to take up all of the emissions from 2010 you would need 1,545,000,000,000 trees.  A mature forest has only about 100 trees per acre (400 per hectare), so you would need 15,545,000,000 acres of mature forest.  This equals an area of 24,290,000 mi2 (62,910,000 km2).  This is approximately the land area of Asia, Europe, and Australia combined!
The surface area of land on the planet is about 150,000,000 km2, so in principle we would need to add cover onto 42% of the current land (or we could take soil from deep ocean floors to landfill 1/5th of the oceans!) in order to plant enough trees to solve the problem.

This also assumes that the 13 pounds (5.9 kg) of carbon figure is for mature forests, rather than for growing trees (see comments for further discussion).  If this value is for young developing trees, it would indicate less be attainable in the longrun.  If the 13 pounds is for a developed forest, perhaps a greater amount could be removed in early years as a temporary quicker fix.

There is also the problem that forested land is likely to have a lower albedo than the land surface that it covers, and hence the planet will reflect less sunlight back into space which would lead to some extra warming, so we would also need to compensate for that somehow.  Apparently about 26% of Earth's land is already covered with forests.  I rather doubt over half of the uncovered land surface is suitable for new forests, the continents have large bands either side of the equator that are generally too arid, and the regions close to the poles are too cold.

In short, it isn't going to work, even with the most generous assumptions about forest CO2 exchanges (unless of course I have made an arithmetic error, which is definitely a possibility).


The cited paper, and ones like it, are young earth creationist nonsense. The Geoscience Research Institute is an arm of the Seventh Day Adventists, whose official position is that "in a recent six-day creation the Lord made “the heavens and the earth, the sea, and all that is in them” and rested on the seventh day." This is a central tenet of Seventh Day Adventism (it's in the very name of the religion); teaching or writing about an Earth that is billions of years old is explicitly forbidden.

Young earth creationists are wont to attack radiocarbon dating because it has significant limitations. Samples can be contaminated in situ, during extraction, during storage, in transportation, and in processing. Contrary to Giem's claim that "the hypothesis that machine background can account for this carbon-14 has been universally rejected by researchers in the field, and for good reason," several of the papers cited by Giem were scientists trying to assess the machine background and other limitations of their techniques.

For example, Giem cited Aerts-Bijma et al. seven times. This paper looked at "AMS sample handling in Groningen." This lab attempts to perform radiocarbon dating in an automated, assembly line fashion, taking about an hour to perform an analysis. This is fine for archeology studies with budget constraints. The paper by Aerts-Bijma found their approach has limits.

One issue with carbon dating is that the previous run can contaminate the next. To test this, Aerts-Bijma et al. ran two sets of tests against the same sample of anthracite. In one, they interspersed each measurement by carbon dating 100% modern carbon. This gave an artificially high carbon-14 reading for the anthracite. In the other, they didn't do such a dumb thing and found a lower floor. Giem reported the intentionally mishandled reading.

Other labs have lower floors by following more stringent but significantly more expensive procedures. Carbon compound scintillators such as those used to detect neutrinos need carbon that has extremely low amounts of carbon-14. The best source of such carbon is old hydrocarbons that have not suffered in situ contamination. Techniques have been developed to measure carbon-14 to one part per 1018 to ensure that those sources are indeed old and uncontaminated. These techniques are well beyond the budget of a typical archeological study. Giem did not report these because they go against his claims.


Trees: What does "highly tapering stem" mean?

A "highly tapering stem" is simply that the trunk of the tree is less cylindrical and more conical in profile. It's a problem because while you may have a lot of timber volume you don't have as much timber that is usable because you'll end up with a higher proportion of sawmill waste.

I'm English and have a degree in forestry. Regardless of comments elsewhere, a "highly tapering stem" is perfectly good terminology, although I agree that it could be clearer. I would tend to say "a high degree of tapering" or a "more tapered stem" for clarity's sake.

A full description of this can be found in Forest Mensuration: a handbook for practitioners by Matthews and Mackie on page 114. (They refer to a tapering log, because they are discussing felled timber).


The probabilities are generally based on long term recurrence rates. You can read about the details in the Working Group on Earthquake Probabilities page Earthquake Probability Models.

The last major earthquake on Southern SAF was in 1857 which means that the average slip deficit on the fault is around ~8.0 m (the Pacific plate is sliding past at a rate of 55 mm/yr). Using empirical scaling laws you can estimate the magnitude of the earthquake that is required to release the accumulated strain. However, the 8.0 m slip deficit is an upper bound as some of the deformation in the region is accommodated by other fault systems, e.g., Elsinore and San Jacinto faults (sub-parallel to SAF) as well as the Eastern California Shear Zone which was the site of Landers/Hector Mine earthquakes in the 90s.


WRF/Chem: Editing NetCDF (wrfchemi files) for own emissions

You can try the R package eixport, with wrf_put

# example
# Read the array emissions,
CO <- wrf_get(file = "Path_to_WRFCHEMI", name = "E_CO")
# Change the values, here you should use your data
CO[] = rnorm(length(CO))
# Inyect your emissions into the wrfchemi
wrf_put(file = "Path_to_WRFCHEMI", name = "E_CO", POL = CO)

  How to deal with the speciation (my shapefile has only PM10 and
  PM2.5). where exactly do I place this in the new emissions file (the
  edited wrfchemi)I want. There are many pm species there (like pm2.5
  nucleation mode, pm, etc). I am not sure what weights to put on these.

You need to know the speciation for your local. At my department at Uni. of São Paulo, we use the following speciation of PM 2.5 (g/h/km^2)

e_so4i = 0.0077, e_so4j = 0.0623, e_no3i = 0.00247, e_no3j = 0.01053, e_pm2.5i = 0.1, e_pm2.5j = 0.3, e_orgi = 0.0304, e_orgj = 0.1296, e_eci = 0.056, e_ecj = 0.024, h2o = 0.277

Check this

  My emissions are not time dependent, and what do I do when I edit the
  wrfchemi file for this. (the wrfchemi files I have now are also not
  time dependent)

You need to first edit the namelist.wps and namelist.input to the desired length of time. Then, after running  ./real.exe you will have the wrfinput_d0x. At this stage you can use wrf_create which creates a wrfchemi file with 0. Read the manual to see if you want two 0-12z 12-0z files or one file with the length for all hours. Then you can use wrf_put. Just follow the example and read the manual.

You might also try the R package EmissV

References:

Ibarra-Espinosa et al., (2018). eixport: An R package to export
emissions to atmospheric models. Journal of Open Source Software,
3(24), 607, https://doi.org/10.21105/joss.00607 Schuch et al.,
(2018).
EmissV: an R package to create vehicular and other emissions
for air quality models. Journal of Open Source Software, 3(30), 662,
https://doi.org/10.21105/joss.00662


Has the number of natural disasters per year increased significantly in the years since human-caused climate change started?

We have no evidence to suggest that the rate or magnitude of earthquakes has, in general, increased: while earthquakes are having a greater effect on humans, this is entirely - as best we can tell - due to increased population density, and the propensity of people to build cities immediately above major fault planes (because they channel water to the surface along impermeable fault debris). Populations settling above the surface expressions of major faults isn't much of an issue when you're living in tents in a sparse community, but once you get high-density populations living in skyscrapers with poorly-enforced building regulations death and injury rates rise very rapidly. For more detail and onward references see the USGS FAQ on this topic.

For statistics on extreme weather phenomena/natural disasters, particularly relating to precipitation and flooding, the IPCC is an excellent resource. There is of course some degree of difficulty with reporting bias (as with earthquakes), but the IPCC are extremely rigorous in calculating - and providing - bounds on probabilities and certainties. In particular, see Working Group 2: Impacts, Adaptation, and Vulnerability; their summary for policy-makers has to say:

  Impacts from recent climate-related extremes, such as heat waves, droughts, floods, cyclones, and wildfires, reveal significant vulnerability and exposure of some ecosystems and many human systems to current climate variability (very high confidence).

For more details, see the final draft of WG2's contribution to the Fifth Assessment Report (AR5). Particularly worthy of highlight are the FAQ and chapter 18.4.3, which has to say:

  The last several decades have seen changes in the frequency and intensity of extreme weather events including extreme temperature, droughts, heavy rainfall, and tropical and extratropical cyclones with low to very high confidence, depending on the type of extreme event (IPCC, 2012, WGI AR5 Chapter 2). However, the impacts of extreme weather events also depend on the vulnerability and exposure of systems. It is possible that climate change can affect vulnerability and exposure, but typically both are primarily influenced by non-climate confounders, most notably economic development.


What is the status of the Raymo & Ruddiman idea that Tibet cooled the Earth?

The Tibetan Plateau uplift is still generally considered as playing a role in the Neogene cooling through the process you explained in your question (see for instance the seminal Zachos et al. 2001 and more recently Garzione 2008).
It is probable that other phenomena played a role as well such as the diversification of diatoms (which are, today, the most efficient biological carbon sink, e. g. Goldman 1993; Ragueneau et al 2000) around 15 Ma (Lazarus et al 2014 [Disclaimer: I am a co-author of the latter paper] ) or changes in the ocean circulation (specifically an increase in the proportion of bottom water originating from the Southern Ocean; Flower & Kennett 1994).
That being said, the cooling in question here would be the one starting at ca. 15 Ma. However the Cenozoic cooling trend started way earlier, in the Early Eocene (after the Early Eocene Climatic Optimum, aka EECO), with ice on the eastern Antarctic
continent as early as the Late Eocene / Early Oligocene (see again Zachos et al 2001).

Sources:

Flower, B. P. & Kennett, J. P., 1994. The middle Miocene climatic transition: East Antarctic ice sheet development, deep ocean circulation and global carbon cycling. Palaeogeography, Palaeoclimatology, Palaeoecology, 108: 537-555.

Garzione, C. N., 2008. Surface uplift of Tibet and Cenozoic global cooling. Geology, 36: 1003-1004.

Goldman, J. C., 1993. Potential role of large oceanic diatoms in new primary production. Deep-Sea Research I, 40(1): 159-168.

Lazarus, D., Barron, J., Renaudie, J., Diver, P., & Türke, A., 2014. Cenozoic Planktonic Marine Diatom Diversity and Correlation to Climate Change. Plos One, 9(1): e84857.

Ragueneau, O., Tréguer, P., Leynaert, A., Anderson, R. F., Brzezinski, M. A., DeMaster, D. J., Dugdale, R. C., Dymond, J., Fischer, G., François, R., Heinze, C., Maier-Reimer, E., Martin-Jézéquel, E., Nelson, D. M., Quéguiner, B., 2000. A review of Si cycle in the modern ocean: recent progress and missing gaps in the application of biogenic opal as a paleoproductivity proxy. Global and Planetary Change, 26: 317-365.

Zachos, J., Pagani, M., Sloan, L., Thomas, E., Billups, K., 2001. Trends, rhythms, and aberrations in global climate 65 Ma to Present. Science, 292:686-693.


What's with this anomaly in this sounding (the CAPE and CIN readings)?

Your screenshot lists the raob as station 72357 on 2013-06-01 00Z.  Station 72357 is OUN and the sounding for that day time is available at the SPC sounding archive.

The SPC sounding analysis shows 3351 J kg$^{-1}$ CAPE and -76 J kg$^{-1}$ CIN for surface parcels.

My speculation for your anomolous non-physical values of CAPE and CIN is that the algorithm used in that software perhaps doesn't handle the lack of stratopheric data well.  The calculation of CAPE is the parcel buoyancy integrated from the level of free convection (LFC) to the equilibrium level (EL).  This sounding has no EL because the temperature data stops before the tropopause and never increases to equal the temperature of the lifted parcel.  A naive algorithm that does not take this into account would have issues calculating the CAPE and potentially produce undefined output.  I think that is the case in the software in your screenshot.


How much of the petroleum ever formed has made it into reservoir rocks?

In its 1995 assessment of total world oil supplies, the U.S. Geological Survey (USGS) estimated that about 3 trillion barrels of recoverable oil originally existed on Earth and that about 710 billion barrels of that amount had been consumed by 1995.
Britannica

There may be much larger quantities that are not "recoverable", depending on technology and economics.
Also, for example, 914 persistent natural seeps across the Gulf of Mexico collectively discharged about 500,000 barrels of oil per year. If that has been seeping for millions of years, that is a lot of oil that is not in reservoirs.


What is the value of calculating the elevation of mountains in the past? (paleoelevation)

Compared to some other fields in geology, this one actually has immediate practical implications.

By "knowing the history of mountains", you can learn a lot about processes that involve erosion, weathering, seismicity, etc. This is important for risk management and mitigation. Landslides and rockfalls are a significant risk in some countries. There are many ways of studying these processes, one of them being the interpretation of past events: their causes and effects. This is also true for earthquakes (which as you know, move mountains up and down).


What is a Geophysical Model Function (GMF)?

In remote sensing you often do not directly measure the variable of interest, i.e., you measure it via some other variable that you can measure (depending on the type of instrumentation). The model function is simply the function which relates the observed variable to the variable of interest, just like y=f(x).

E.g., y could be wind speed, and x the energy measured by the scatterometer.


How much and what kind of radiation passes through a cloud?

Here is not a detailed article, but one you might find some informative thoughts in:  http://www.americanscientist.org/issues/pub/sunshine-on-a-cloudy-day

On a basic note, any generalization starting with "clouds block x or x%" are far too general to compare actual percentages.  It assumes a cloud is a cloud is a cloud.   They are not.  What a cloud actually does to block or not block electro-magnetic radiation is not an absolute.  It varies by type of cloud, thickness, altitude, angle of the sun and likely many other factors.  As a generality, clouds block a part of visible, UV and IR light depending on a number of factors especially depth of the cloud.  Some of the EM waves are absorbed, some reflected and others pass through.  The UV end of the spectrum tends towards passing through while the IR end is more prone to being reflected which helps to create a greenhouse effect.  These are often presented as absolutes, but are actually generalities.


How reliable would measuring global heating from satellite be?

Measuring long-term temperature trends from satellites is possible, but difficult due to a variety of reasons.

This is ongoing research.

In short: the satellites that have been around long enough were built for measuring weather, not climate, and the standards to which instruments need to be built to measure one are entirely different from the other.

We have had satellite measurements of the atmosphere since the 1960s, and operationally since the late 1970s.  Those have always included infrared radiometer measurements, which means that, in principle, we can construct a record of surface (both land and sea) and atmospheric temperatures for the past 40 years at least.  The sensors themselves aren't very complicated — but to determine a trend we would need to be very confident about their uncertainty, stability, and inter-satellite variability.

If you were to simply take 40 years of HIRS infrared measurements and plot them, you don't know if the changes are due to atmospheric or instrumental changes.

From 2015 to 2019, I was part of the FIDUCEO project which aimed to bring the science of metrology (science of measurement) to satellite observations.  Taking 40 years of AVHRR (for sea surface temperature) or HIRS (for atmospheric temperature and humidity) measurements, with 16 different editions of the instrument over a period of 40 years.  But AVHRR was built to look at pictures of clouds.  If you look at pictures of clouds, the user doesn't care if one satellite has its pictures 0.5% brighter than the previous one.  They just tweak their monitor a bit!  But if you take the global climate system, then that corresponds to more than 1K temperature difference, which for the oceans, would be huge.  In FIDUCEO, we aimed to:

Develop a metrology of Earth Observation
Produce Fundamental Climate Data Records (FCDRs) for various operational meteorological instruments in visible, infrared, and microwave, meaning:

Per-datum metrologically traceable uncertainty characterisation;
Per-datum information on correlation structures: which component of the error estimate cancels out when averaging and which component remains;
Harmonisation between the various satellite sensors.

Here are 40 years of HIRS (versions 2, 3, and 4), on which we tried to do some harmonisation.  The top panel shows global average brightness temperature per 24-hour period, as measured by channel 2 which IIRC peaks somewhere in the stratosphere, so this would correspond roughly to an atmospheric temperature somewhere up in the stratosphere (which, incidentally, is cooling as the Earth's surface is warming):

The different colours indicate different satellites.  As you can see, there are both jumps between satellites, and trends within one satellite.  Some of this is expected, as polar-orbiting sun-synchronous satellites have a drifting local equator crossing time, but some of it is due to instrumental problems.  Some of those problems are captured by the structured uncertainty in the bottom panel, but not all of it.  The data only go back to the mid-1980s, because before that, there weren't enough overlaps to constrain the differences between subsequent pairs of satellites based on simultaneous nadir overpasses (SNOs).  For satellites in the early 1980s and late 1970s, the coefficients to calibration the thermometres measuring the temperature of the on-board calibration target appear to have been lost.  For the earliest satellites the header data does not match available documentation.  Software to produce this figure is on Github, raw source data are available from NOAA CLASS, some processed data from FIDUCEO.

This is for a global average.  To do this regionally would add additional complications.

The CLARREO programme is proposed to be the first in-orbit SI reference for accurate calibration.  Had we had that for the past 40 years, our job would be easier.  But CLARREO is still waiting for funding.

So the answer to your question is: with what we have now — not good enough — yet.

But if you are contemplating a career in satellite techno-archeology, I recommend it.  It's great fun.


What is meant by Global-warming Potential (GWP)?

Rather than using the GWP as a ratio, they are expressing the GWP as compared to a release of $\ce{CO2}$ with equivalent radiative effects.  To use their numbers use the mass they give you and a GWP ratio of 1 for that mass (as if it were carbon dioxide).  From what I've seen for chemical industry sales and marketing literature it is fairly common that they express GWP this way in units of "$\ce{CO2}$ equivalent".

In other words, they are saying whatever their product is made of and its production methods have the same radiative forcing as $x$ kg of $\ce{CO2}$.


In answering this complex question, I think it's important to consider the form of carbon that is utilized and the overall reactions involved (warning: somewhat lengthy diversion ahead, and advance apologies if such is already understood by this audience). In the long-term carbon cycle, atmospheric $\ce{CO_{2,(g)}}$ drives weathering on land, importantly of silicates. $\ce{CO_{2,(g)}}$ dissolves in pure water as aqueous ion ($\ce{CO_{2,(aq)}}$) and carbonic acid ($\ce{H_2CO_{3(aq)}}$).
$$ \ce{CO_{2,(g)} + {H_{2}O_{(l)}}  <=> {H_2CO_{3,(aq)}} }$$
but true carbonic acid is unstable, and the vast majority of this total dissolved carbon is thus present as the aqueous ion $\ce{CO_{2,(aq)}}$, with concentrations obeying the simple Henry's law relation (not shown). We can write this net reaction is
$$ \ce{CO_{2} + {H_{2}O}  <=> {H_2CO_{3,(aq)}} <=> H^{+}_{(aq)} + HCO_^{-}_{3,(aq)} }$$
Bicarbonate also reflects the association/dissociation reaction involving pure carbonate ion,
$$
\ce{H^{+} + CO_^{2-}_{3} <=> HCO_^{-}_{3}}
$$
Weathering of a continental silicate, e.g., a normative wollastonite (chosen for simplicity), can thus be written as$$
\ce{ CaSiO_3 + H_{2}O +2CO_{2} -> 2 HCO_^{-}_{3} + Ca^{2+} + SiO_{2}}
$$
The important point is that the dissolved carbon delivered to seawater by continental weathering is as bicarbonate, and surface seawater pH ($\sim 8)$ in approximate equilibrium with atmospheric $\ce{CO_{2}}$ indeed reflects this distribution of dissolved species. If we write the equilibrium for skeletal calcium carbonate as
$$\ce{ CaCO_{3} <=> CO_^{2-}_{3} + Ca^{2+}}$$
we can combine the above equations to give the overall reaction for the dissolution/precipitation of $\ce{CaCO_3}$ in seawater (incorporating the mass balance on $\ce{CO_2}$ from reactions 1, 2, 3, and 5 -- sorry I can't get MathJax to turn equation numbering on) as,
$$
\ce{CaCO_{3} + H_{2}O + CO_{2} = Ca^{2+} + 2HCO_^{-}_{3} }
$$
Thus in this context, an important result is that, in the overall mass balance associated with precipitation of $\ce{CaCO_{3}}$ (i.e., driving the above reaction to the left), $\ce{CaCO_{3}}$ serves as a source, not a sink of carbon, because it liberates one mole of $\ce{CO_2}$ originally delivered as bicarbonate to seawater from silicate weathering. In the larger view (long term geochemical cycling), marine carbonates are a temporary sink for carbon that is ultimately subducted and returned to the atmosphere by vulcanism and other magmatic processes. The carbonates residing on the continents today (e.g., Paleozoic) have, in contrast, a much longer residence or cycling time that their modern pelagic equivalents.

Now, to your question: ocean acidification (titration of seawater by atmospheric $\ce{CO_2}$, driving the last reaction to the right) per se is buffered by the attack of this sink of $\ce{CaCO_3}$ producing more bicarbonate. Sequestration of carbon by growing shellfish will, according to the above, consume (some of) this bicarbonate, and produce $\ce{CO_2}$ as a result. The larger, key question to me, is the rate at which the existing store of sedimentary $\ce{CaCO_3}$, particularly in surface water where it is being formed, dissolves in response to this attack.

Edited for clarity, typos


How to compare the oil production in barrel vs production in tons

I suspect that 3.75 million tons of oil is actually tons of oil equivalent (toe). This is a unit of energy rather than mass. The US uses a barrel of oil equivalent (boe) as a measure of energy. The advantage of these energy units is that natural gas, coal, and refined petroleum products can all be measured in terms of tons or barrels of oil equivalent.

The US still measures oil production in volume. Depending on the quality of the crude oil, it takes between 6.5 and 7.9 barrels of oil to yield one ton of oil equivalent, with 7.33 barrels as an average value. That means that the 1 131 557 443 barrels produced in Texas in 2016 represents somewhere between 143 to 174 million tons of oil equivalent.


How is heat transferred from the core through the mantle to the crust?

It is still a little known fact that radiation play an important role in the Earth's mantle. Experiments show that mantle-material becomes transparent to infrared radiation at increasing pressures (http://www.esrf.eu/news/general-old/general-2004/earthbadro/index_html).

I would also say that the mantle is currently not understood in a way where estimates of heat-conduction-type versus depth can be accurately made. The heterogeneity of heat transfer (Cold detached subduction-slabs sinking to various depths and hot plumes quickly rising from the D''-layer) makes the question even more difficult.


Can reforestation sequester our annual carbon emissions?

Reforestation is a one-off gain in carbon storage. Once a forest is fully mature, the carbon cycles back into the atmosphere as trees die and decay or are burned. So no, this will not sequester all the emissions from fossil-fuel burning. It could help offset it in the short term, but probably mainly just offsets the carbon dioxide from deforestation.


upper air data(observation) and analysis step for GFS model

You are right that upper air soundings are typically only done twice a day, and even at quite a coarse observation spacing.

And that upper air data is definitely very important in models.

I'd suggest that, firstly, it's important to note that even a broad, very hazy picture aloft really helps a great deal at the surface.  That can be seen in the quasigeostrophic omega equation.  Basically the large-scale highs and lows and jet streaks drive much of the vertical air motion in the atmosphere.  Plus there aren't quite as many complexities caused by terrain/ground cover/moisture/differential heating that the surface layer sees.
So because the evolution of those large-scale features is pretty straightforward over the course of a day, the early morning's upper-level forecast is still quite reliable and helpful 6 hours later.

But that said, smaller scale shortwaves and vorticity maxima are absolutely vital to weather forecasting too.  And with smaller size and more transient nature, neglecting their changes over 6 hours is likely to really harm forecasts when it comes to critical subtle differences such as you'd see in a tornado outbreak or hurricane track.

So indeed, how DO we recognize those changes?

Well, we do have a second source that these days is probably at least as important as soundings, perhaps even moreso - satellite imagery.

See for example this satellite page.  You can turn on HDW-low, HDW-mid, HDW-high.  As far as I understand it, the models are ingesting that information readily (and likewise cloud coverage, which are just as important).  I believe some satellites also have vertical temperature sounders that are used more now as well.

And third, we also have some other data sources that help.
In certain parts of the world, we've got radars.  I believe at least some of the better models these days are using that data... there's plenty of wind data to be had from velocities (though it would seem challenging to use/analyze it given things like range-folded velocities and the ambiguity of tangential winds see the intro to [this article]).

Plus, I believe at least the ECMWF has had real success in ingesting ACARS... atmospheric data that are generally reported by all commercial aircraft.

But... all that said, your point still has some real potency.  Especially when we note that, when it comes to our best model, the ECMWF... it still only runs twice a day.  Maybe other reasons drive the decision, but you'd think they still weigh how improved such forecasts are.  So it seems fairly likely that they've determined that long-range forecasts don't improve much when they are still based heavily upon that older information.

But then, I think everyone would agree that having hourly models available like the HRRR is very useful in important nowcasting situations, such as severe weather awareness.  So maybe the overlooked small data changes are (counterintuitively?) more important to long-range forecasting than short-term.  Definitely an interesting question you've raised!


How do the known abrupt climate change events fit into the xkcd Earth temperature timeline?

The apparent contradiction comes primarily from #1 but #2 also pays a small role here...

Temperature decreases during the Younger Dryas greater than $2^{\circ}$C are believed to have occurred almost exclusively above $30^{\circ}$N in latitude. The bulk of the tropics are thought to have been relatively stable during this time and the southern polar region showed slight warming. Additionally, global temperature averages are generally weighted by area and only one fourth of the earths surface lies between $30^{\circ}$N and the North Pole. All this combines to produce what is thought to be around 0.6$^{\circ}$C of global cooling at the start of the Younger Dryas (Carlson, 2013).

Randall does cite several sources in the top right of his graphic but Shakun et al. (2012) is the only one that presents meaningful temperature data during the Younger Dryas. And in fact, the comic's proxy data (dashed) temperature curve closely matches the temperature curve presented in this article over this period (curve d in the figure below).

Interestingly, while Shakun et al. (2012) does show a global temperature decrease close to $0.6^{\circ}$C 12,000 years ago, the change doesn't appear to happen abruptly (at least not on the scale of decades). In the text of the paper the authors state that they built their temperature data set from 80 different proxy measurements taken over a wide range of locations. It turns out that these proxy measurements have a relatively long time resolution (a median value of about 200 years). That means that while the changes may have occurred very quickly this temperature curve is going to fail to capture that variability and appear "smoothed out". This does make the xkcd graphic a little misleading since the large temperature increase at the end is produced from data using a much finer time resolution, but this is a flaw common to all "hockey stick" temperature plots.


What current evidence is there for a Glacial Hudson River Valley deluge?

" Who's studied the glacial dam breaking South and having cleared the Hudson River valley, forming the Verrazano Narrows, NY Harbor, Staten and Long Island, and washing through to the Atlantic Continental Shelf?"

There's a USGS group at Woods Hole that's done a bit of work on this back in 2004:

A catastrophic meltwater flood event and the formation of the
Hudson Shelf Valley   -From the paper:

The ancestral Hudson River is generally thought to
have had a long history that began in the Late Cretaceous.
Uplift and tilting of the margin, resulting in
landward erosion and seaward growth, continued into
the Tertiary.

The Hudson River was repeatedly downcut into Cretaceous
coastal-plain strata during periods of Pleistocene marine
regression.
Scouring of the lower Hudson River during the last
glaciation formed a fiord in the region north of New York
City.
More recent fluvial downcutting was amplified by
drainage of late Wisconsinan glacial lakes, culminating in the failure of the terminal
moraine dam at the Narrows, which is a break in the
Harbor Hill moraine between Staten Island and
Long Island, New York. Borehole data across the
Narrows suggest that more than 100 m of Pleistocene
and Cretaceous sedimentary material was eroded as a
result of this breaching event. Uchupi et al. (2001) proposed that deposition
of sediment lobes on the continental shelf and erosion of the HSV were a consequence of
this catastrophic drainage.

You might scour the references at the back of the paper and do some googling to find any more recent follow-up work they may have done. You could also try this guy at Woods Hole: Jeffrey P. Donnelly. He's first author on a paper titled:

Catastrophic meltwater discharge down the Hudson Valley: A potential trigger for the Intra-Allerød cold period

The paper is short on the drama of breached glacial dams, but long on how the sudden discharge of freshwater into an ocean alters circulation to cause a brief period of climate change. Fascinating stuff!


Difference between model parameter and observable parameter

Inverse problems deal with creating theories based on observed data, as opposed to making predictions about the real world based on existing theoretical models, so the "results of the measurement of observable parameter" is a confusing way of saying "the real measurements being used as data". Parameter simply refers to the value being measured.

An example would be if you have a forestry block and you want to understand why some trees are preforming better than others; you'd measure a whole group of variables that formed a set of parameters, one of which might be "tree health" based on say height, girth, leaf activity, and transpiration rate and another that's "soil fertility" based on key nutrient levels, particle size distribution, bulk density, and water holding capacity. The relationship between those two parameters then lets you formulate a theory that you can apply at other sites that you know the "soil fertility" of to predict the growth of trees there.

In the real world you have to test your theory with what in my GIS classes they called a "Ground Truth", that's where you go out and measure the parameters of a different real world site being used for the same crop and see if your theory accounts for the results at that site (we did them to confirm the relationship between satellite readings and on-the-ground data). When you've done this at a number of sites and the measurements all conform to your theory you can start applying your model as a predictive formula for sites not yet in use.


Are these clouds exhibiting gravity waves?

These are rotor clouds, and are manifestations of "Lee Waves", a particular kind of internal "gravity wave" (better defined as "buoyancy effect").

Forced convection helps form these clouds as warm, moist air is forced upward by both wind from behind and the mountain barrier in front. The upward movement forces cooling and condensation of vapor into clouds. Once past the mountain barrier, this instability dissipates it's momentum through a series of less intense waves as a function of distance away from the mountain range. The clouds themselves are "standing": they do not move, but are constantly regenerated by the windward moist air mass; nor do they build increasingly larger as they are dissipated on their lee side.


How to prepare GrADS's .ctl file to convert grd file into .nc file in batch mode?

After some trial n error I figured it out using the following shell script

#!/bin/bash

day_number () {
year=$1
leap="false"

if [ $((year % 4)) -ne 0 ] ; then
   :
elif [ $((year % 400)) -eq 0 ] ; then
     leap="true"
elif [ $((year % 100)) -eq 0 ] ; then
   :
else

   leap="true"
fi
if [ "$leap" == "true" ];
then
   echo 366
else
   echo 365
 fi
}

for j in {1901..2015};
do
days=$(day_number j)
echo "DSET /home/amit/climate_data/rf/year${j}_rfp25.grd
TITLE Gridded rainfall
UNDEF -999.0
XDEF  135  LINEAR  66.5 0.25
YDEF  129  LINEAR  6.5 0.25
ZDEF   1 linear 1 1
* CHANGE TDEF TO 366 FOR LEAP YEARS
TDEF ${days}  LINEAR 1jan${j} 1DY
VARS  1
rf 0 99 GRIDDED RAINFALL
ENDVARS">year${j}_rfp25.ctl
done


Why are the latest additions to the Hawaiian-Emperor seamount chain the highest?

As it was explained to me at university there are two factors; buoyancy and erosion.

Rock buoyancy is a major factor, fresh Basalt is hot and dry and has a much lower density than older oceanic crust. This is why the mid-Atlantic ridge rises above the surrounding seabed.

The effect is even more pronounced with seamounts because they're composed of even hotter rock that takes much longer to cool and wet. As seamounts age they cool, making them denser. As they cool, they absorb water, making them still denser. Where that water interacts with the still cooling rock, secondary mineralisation occurs, which fills gas pockets and other voids, making the rock denser again.

All of this results in the seamount sinking farther into the crust which reduces it's height above sea-level over, relatively short, geological time.

At the same time the mounts are sinking they're also being weathered from above. This shortens them, and also disguises the depression in the seabed from the sinking mountain with debris from above, since erosion generally slows as the mounts sink deeper. Also, as they move north out of tropical waters and coral growth stops, they stop growing at all.

The newer mounts are taller only because they're younger, hotter, and drier, they'll sink and shrink as they age.


How to interpret correctly this chart about nitrogen oxide?

A person answered to me on a dedicated Facebook group. He suggests that the labels are about areas, not lines, so the grey area (emissions in Sweden), is only the visible area, it does not continue below the dark area (emissions abroad). I find this representation very confusing.

As an example, the emissions in Sweden in 2008 are 225 - 100 = 125, the difference between the total and the dark area, and not 100 as I thought.

This way, the correct answer is 1100, because the upper line already represents the total emissions, and between 2004 and 2008 we have an average of 225 for 5 years.


How can agricultural ammonia lead to PM2.5 production in the atmosphere?

Acid/Base Chemistry

Gaseous ammonia (NH$_3$) acts as a base when it dissolves in water. The reactions are below.

NH$_3$(g) + H$_2$O(l) $\rightleftharpoons$ NH$_3$(aq)

NH$_3$(aq) + H$_3$O$^+$(aq) $\rightleftharpoons$ NH$_4^+$(aq) + H$_2$O(l)

The end product is an ammonium ion. We also have gas phase species SO$_2$ and NO$_2$ in air. They dissolve in water to form the conjugates of the acids H$_2$SO$_4$ and HNO$_3$ (e.g. SO$_4^{2-}$).

The protonized ammonium and the deprotonized acids (e.g. NO$_3^-$) are not gaseous anymore. They are also NOT solids. They are dissolved ions.

Precipitation and Nucleation

Ammonium cations react with the acid anions in an acid/base reaction to form a salt complex. An example is ammonium sulfate (NH$_4$)$_2$SO$_4$. When the concentration is low, salts remain as dissolved species in water. As the salt concentration increases, at some point, the salt condenses to a solid (it precipitates out of solution). Salt concentrations increase as the water droplets in the air take on more acid and base species. Salt concentrations also increase as the water droplets evaporate. This causes the water droplets to act as sites for the formation of solid salt particles.

Air also contains other solids as ultra-fine particles. Think ... dust.

All solid surfaces in water act as sites to catalyze the further capture of dissolved salts. They act as proton exchange mediators, better than the liquid phase itself.

The process of formation of a solid particle or capture of a dissolved species onto a solid surface is called nucleation. Nucleation is followed by growth. Some of the solid salts can alternatively redissolve when the conditions are reversed ... e.g. the concentration of the salt in solution surrounding it decreases.

The figure below illustrates the entire process using ammonia and nitric acids (formed from nitrogen dioxide).

Image caption: The compounds in green colored font are located at (mostly wet) particle surfaces or are dissolved in droplet water. Compounds written in black colored font are gaseous. A second arrow head is missing at the arrow connecting gaseous $HNO_3$ and particle-bounds $HNO_3$. Gaseous $NH_3$ is missing in this figure.

Because proton-exchange favorably takes place at surfaces or in droplets, the particles grow favorably rather than redissolve (see below).

References

An exemplary particle size distribution is shown below (own work (Neumann, 2016, Fig. 2.1) but content based on Seinfeld and Pandis (2006a, Fig. 2.7,p.59) which is based on Whitby and Cantrell (1976)). The Y-axis shows particle abundance (roughly; please see Fig 2.2 in the linked document above for details).

The major source of the coarse particles on the right are primary emissions of particles (dust, sea salt, ...). The accumulation mode particles in the center are partly caused by primary emissions (fine sea salt, combustion processes, ...) and partly grown from smaller particles (Aitken mode or ultra-fine particles). Actually, the ultra-fine particles are grown from so called nucleation mode particles by the condensation of further atmospheric gaseous compounds. The nucleation mode is missing here (and merged with the Aitken mode). Nucleation mode particles are those particles, which are formed by ammonia and atmospheric acids.

Other sources for these nucleation mode particles are gaseous organic compounds, which lump together to form particles. The latter particles are also called SOA (secondary organic aerosol). Isoprene is one of the compounds that forms SOA.

Health Impacts

When we combine air polluted by combustion emissions ($NO_X$) with air affected by agricultural emissions, we can expect the formation of ammonium nitrate particles ($NH_4^+$ + $NO_3^-$). Ammonium nitrate can irritate the eyes, nose and lungs. As stated in a comment and to the best of my knowledge, ammonium nitrate particles are not as harmful as e.g. fine soot particles. But I am not a expert on this field.

Ammonium sulfate (from $SO_2$ from combustion emissions) have been shown to have negative health impacts on the respiratory system but also on the cardiovascular system (heart etc.; if the particles are sufficiently small to pierce the lung-blood barrier).

Ultra fine ammonium nitrate particles can be nuclei for condensation of further gaseous compounds -- e.g. VOC (volatile organic compounds) --, which might have harmful impacts on our respiratory system.

notes

Commonly, atmospheric particles are not dry spheres/lumps of matter but somehow associated with water: water droplets with dissolved compounds or a solid core with water attached to the surface; whereas dissolved compounds might be dissolved in the water of the latter type.

The atmospheric life time of gaseous acids is very short because they tend to get attached to water (and deprotonize -- reducing the pH value of the water). Partly, the reaction from precursors to acids takes place in the wet particle/droplet phase. E.g. most of produced sulfuric acid ($H_2SO_4$) takes place in the wet phase.

tl;dr

Thus, we foster the growth of ultra-fine nuclei by the condensation of ammonia (as base) and condensation/formation of acids.

References:

Seinfeld and Pandis, 2006: Atmospheric Chemistry and Physics: From Air Pollution to Climate Change.
Whitby and Cantrell, 1976: Fine particles in Proc. Int. Conf. Environ. Sens. and Asses.


What is the Moon's distance from viewer at horizon?

As noted by others, the moon follows an elliptical orbit, which will lead to the greatest change in distance regardless of the observation angle.

However, we can place some upper and lower bounds on what the distance at the horizon would be by using the maximum and minimum orbital radii (the apogee and perigee respectively) along with Pythagoras's theorem.

In the image above, the larger circle represents the Earth, and the smaller is the Moon. $R$ is the radius of the Earth, $d$ is the orbital distance of the moon from the Earth's centre, and $x$ is the distance of the Moon from the observer when the Moon is on the horizon.

Pythagoras's theorem states that

$$d^2 = x^2 + R^2$$

Which we can rearrange to give $x$,

$$x = \sqrt{d^2 - R^2}$$

Now just substitue the numbers in. I used the following values from the Orbit of the Moon wiki:

Perigee: 362600 km, Apogee: 405400 km, average orbital distance: 385000km, radius of the Earth: 6371km

At Apogee, $x$ = 405349 km

At Perigee, $x$ = 362544 km

At average orbital distance, $x$ = 384947 km

  From a viewers standpoint When the moon starts to rise at the horizon, Is the moon at the furthest distance from the viewer visually?

As noted above, viewing angle is not the primary factor in the distance calculation. However, for a given point in its orbit, the Moon is at its furthest visible radius from the Earth at the Horizon. We can see this by comparing to the Moons distance when directly above the observer. This will be the Moon's orbital radius minus the radius of the Earth. For each orbital point this is:

At Perigee: 356229 km, at Apogee: 399029 km, at average orbital distance: 378629 km

Each of which is around 6300 km closer than when the same orbital configuration is viewed at the Horizon. The Moon may appear larger at the horizon, and hence closer, but this is an illusion.

  The Moon differs from most satellites of other planets in that its orbit is close to the plane of the ecliptic, and not to Earth's equatorial plane

For the horizon distance, the position of the observer on the Earth makes no difference: when the Moon is at the Horizon the distance, for a given orbital configuration, will be the same (minus altitude differences on the Earth's surface). However, from some observational positions the Moon will never be directly above, so the second part is location dependent.

  I want one source from each of the following governments sites- ( U.K gov)(Russian gov)and (Chinese gov) and the sources HAVE to all state a ''similar'' distance.

I doubt that this data is available publicly on government websites. If it was, you could probably find it yourself.


Is it certain that hundred year floods have finite variance?

I'm sure a statistics guru over on cross-validated could answer this better for you, but here's some general info on estimating flood frequency fyi.

The 100 year flood has a 1% probability of occurring in any given year. It is typically estimated by fitting some type of an extreme value distribution to observed flood peaks with additional skew adjustments to account for regional influences or upstream regulation.  In the US, the standard approach is to fit a Log Pearson Type III distribution to log transformed observed flood peaks.  Until recently, Bulletin#17B was the FEMA approved method for flood risk hydrology when a sufficient record of flood peaks was available.  It was superseded March 2018 by Bulletin#17C which has some improved statistical methods.

As far as your question regarding finite variance, my understanding is that the LP III distribution asymptotically approaches unity and thus remains unbounded without finite variance since from a risk perspective there could always be a larger flood that has not yet been measured.  There are also methods for estimating a Probable Maximum Flood (PMF) that is meant to represent the most extreme combination of meteorological and hydrologic conditions that are reasonably possible in a catchment.


The building material comes from minerals dissolved in the ocean, mainly $\mathrm{Ca}^{2+}$, $\mathrm{Mg}^{2+}$, and $\mathrm{HCO}_3^{–}$, but of course there are all sorts of biochemical details. Most limestone originated as the skeletons of micro- and macro-organisms, such as plankton and coral.

The minerals come in turn from the erosion of older rocks (among other places). For example, here are the famous white cliffs near Dover, UK, where massive amounts of calcium carbonate, mostly stable since the Cretaceous, are falling into the sea, where it will be re-used:

This attrition is part of the rock cycle and a very slow-moving part of the carbon cycle. These are well-studied and reasonably well-understood.

You seem to suggest there is a paradox, that there's just constant deposition and no erosion or dissolution. But there is no paradox. The earth is not becoming thicker and thicker, material is not coming from space (not in substantial quantities anyway), and there's no need to invoke any processes we don't understand sufficiently to explain our large-scale observations. We know this because those processes would have a measurable effect on all sorts of things: the earth's orbit, climate, plate tectonics, and so on. There would be, I suggest, a strong low-frequency trend in all sorts of signals (stable isotopes, organism growth rates, sedimentation rates, volcanism rates, and so on).

The image is by Flickr/Harvey Barrison, CC-BY-SA.


Science-quality tools for global and regional tidal heights and transports are available at
http://volkov.oce.orst.edu/tides/global.html.


How much plastic settles to the bottom of the oceans each year?

About 18.2 million tons sink to the ocean floor.

Every year, an astonishing 260 million tons of plastic waste is produced, and about 10% of it ends up in the ocean. Over time, roughly 70% of the plastic that ends up in the ocean sinks to the ocean floor.

Therefore 18.2 million tons of plastic waste end up on the ocean floor.

I used this article for my numbers.


Why is the South Pole colder than the North Pole?

The most obvious reason why the South pole is colder than the North pole is altitude. The Arctic is mostly covered by ocean and low lying land whereas the Antarctic continent is really quite high, with an average height of about 2,400m. The environmental lapse rate in the troposphere is about 6.5°C/km and so this corresponds to about a 15°C temperature difference between the Arctic and Antarctic based on altitude alone. Obviously the actual temperature difference is greater than this so there must be something else at work. Most of Antarctica is only this high because it has a couple of kilometres of ice sitting on top of it and so this doesn't explain why there is a huge, permanent (at least for the last ~35 million years) ice sheet sitting there in the first place.

There are two main reasons why a large ice sheet can persist at the South pole. First is that the southern polar region is currently covered by a large continental land mass (Antarctica). Land has a much lower heat capacity than water and so in the Arctic, the ocean acts as a large reservoir of heat, mainly transported there from lower latitudes and this limits the sea ice thickness. Conversely, in Antarctica snow can accumulate on the land and, if it does not melt in the summer, it will be buried next winter, leading to ice accumulation.

The second reason is the existence of the cold Antarctic Circumpolar Current which flows from west to east and is the largest ocean current in the world, with a mean transport of 100-150Sv. This cold current, transporting huge volumes of water, serves to thermally insulate Antarctica from the warmer subtropical waters to the north, cooling the continent. The openings of the Drake Passage and the Tasman Gateway, the exact timings of which are debated but are generally thought to have both happened by about 30 million years ago, allowed the formation of the ACC and are roughly coincident with the onset of permanent glaciation in Antarctica.

An additional factor in the present day, as mentioned @winwaed, is that southern hemisphere winter solstice currently coincides with aphelion (roughly), which produces colder winters in the southern hemisphere, allowing extreme temperatures of -94.7°C to be reached. The flip side of this is that summer solstice coincides with perihelion, which produces higher summer temperatures.


Saharian calima dust, apart of Fe2O3 does contain FeO?

I think you are correct. Typical sand is silica (white) with a little Fe2O3 (red) to give a "sand" color. FeO is black and over geological time in air, oxidizes further to Fe3O4 with hydroxides and hydrates (black and dark brown) and eventually Fe2O3.


How far from basalt bedrock can magnetometic survey find archaeological features?

You can get a good idea of the magnitude and wavelengths of typical archaeological magnetic anomalies with a literature search. For instance this page shows a magnetic map of fire hearths http://en.wikipedia.org/wiki/Magnetic_survey_(archaeology)

Geology is a lot more complicated though and there are many variables that might affect the background magnetic signature. It doesn't matter how much you study up on basalt rock properties you still won't know enough about the rocks in your project area to predict the outcome of a survey.

Your best hope is to use prior experience from other surveys close to your project area. If a survey worked in one farmer's field then it will probably work in the adjacent field as well.

If no one has collected any magnetic data close to your project area then go ask the geophysicists if they will do a test line or two. If it works great, if not then try something else like magnetic gradiometry, resistivity or ground probing radar.

Sorry I can't give you a definitive answer to your question. I understand what you are asking but geology is just too complex to give you a useful rule of thumb.


Is there a freely usable map of Earth cave systems and/or density?

You might like to check World Cave List which has a pretty extensive list of caves, their depths, and lengths.
For example:

This list has been automatically produced from our World Caves Database.
Total depth and length of all caves currently collected in the database:

Number of caves = 2424
Caves deeper than 300m = 1075
Caves longer than 3kms = 1628
Cumulated depth = 648 932 m
Cumulated length = 17 930 192 m


I can't be definite but my three best guesses are Travertine, Agate and maybe Halite, if it fizzes in mild acid it's Travertine, a form of Limestone, if it dissolves in hot water it's Halite, or Rocksalt, otherwise if it's more or less inert it's probably Agate, an amorphous silicate. I find Halite unlikely, the other two are probably pretty equally likely in that location.


Why do maps of melanoma prevalence correlate negatively with UV index, negatively with ground ozone, and positively with atmospheric ozone levels?

I cannot address your specific questions, but with regards to cancer, Cedric Garland has analyzed and presented similar data and attributed a lower incidence of cancer with a higher production of vitamin D at the lower latitudes as a possible reason. Mina Bissel at Berkeley labs and others have discovered that cells in isolation can lead to cancer. The other connecting link is that vitamin D promotes intercellular communications and thus may be aiding whatever process it is that leads to cancer. If you just google these names, vitamin D and cancer, you will find links to most if not all the papers.


Where did the atmosphere's nitrogen come from?

There was some free nitrogen in the secondary atmosphere, and also some ammonia (NH3). Ammonia is present today in the atmospheres of Jupiter, Saturn and other gas giants in the outer solar system. The main constituent of the Earth's primeval atmosphere was carbon dioxide, which also makes up the bulk of the atmospheres of Venus and Mars. The ammonia eventually decomposed into nitrogen and hydrogen.

When we look at the atmospheres of Mars and Venus, we see that they contain only 3 percent nitrogen, while our atmosphere contains 78 percent. The main reason for this is that Mars and Venus still retain most of their primeval CO2, while Earth's has largely disappeared because of biological processes (coal,limestone etc). The atmosphere of Titan also contains a massive percentage of nitrogen because competing gases, apart from methane, have mostly disappeared, frozen out by the intense cold

We also need to consider outgassing from volcanoes. These emissions consist mainly of CO2 and water vapour, but there are small amounts of nitrogen and ammonia, and other gases as well.


What is the loudest thunder ever recorded (dB) at ground level and where did it occur?

Thunder 1 mile away-117 dB
Thunder 1/2 mile away-121 dB
Lightning strike just meters away from you-125 dB


Why should there not be water deep (e.g. below 6 kms) in the Earth's crust?

There are two reasons for this surprising finding:

Compaction. Once you have high pressures at depth, the less dense material goes up. Take a bucket of water, put sand in it, and squeeze the sand really hard. Water goes up. Then, you'd expect no water at depth of several kilometres.
Even if you somehow had free water at these depths, the expectation is that they would form hydrous but solid minerals. For example, adding water to diopside, enstatite, and quartz leads to the formation of hydrous, but solid, tremolite:
$$\ce{2CaMgSi2O6 + 3MgSiO3 + SiO2 + H2O = Ca2Mg5Si8O22(OH)2}$$
or, adding water to quartz and corundum leads to the formation of kaolinite:
$$\ce{Al2O3 + 2SiO2 + 2H2O = Al2Si2O5(OH)4}$$
Increasing pressure leads to the equilibrium in these reactions shifting to the products, i.e. the solid hydrous phases without any free water.

As to why the water was actually found there, there's still some debate in the scientific community. One of the explanations ("...must have come from deep-crust minerals and had been unable to reach the surface because of a layer of impermeable rock") is definitely reasonable. The other ("scientists theorize that the water is comprised of hydrogen and oxygen atoms which were squeezed out of the surrounding rocks due to the incredible pressure.") is probably incorrect.
This (paywalled) paper provides an overview in a very accessible language: https://doi.org/10.2138/gselements.16.6.381


What is the meaning of -999 degrees Celsius?

The value -999 is likely the "fill value" used in the dataset when data is missing or is not being properly filtered or handled when displayed.  In the specific case on the website you cite, it is likely a problem with the algorithm for wind chill (the "feels like" temperature this time of year).

It isn't a physical value and only means the value is missing. Furthermore, -999°C is not a possible value because absolute zero is –273.15°C, and it's not possible to be colder than this (at least not in any meaningful way, and certainly not because of wind chill). The coldest recorded temperature on earth is around –90°C.


According to the National Geographic Education Encyclopedia webpage about continents, defines these as the main divisions of continuous land, extending out to the edge of the continental shelf - this also includes much of the surrounding islands. In the case of the division between Europe and Asia, this division is largely due to cultural differences.

The exceptions to this are what are referred to as 'microcontinents', that National Geographic site describes as being landmasses that are 'geologically distinct' from the neighbouring continents.

There seems to not be a consensus on a tectonics based definition of a continent; however, given that continents change over time, it is suggested in the article Continents as lithological icebergs: the importance of buoyant
lithospheric roots  (Abbott et al. 1997) as implying that the particular lithosphere is "unsubductble' over two 0.25 billion year time periods - which, according to the authors, include mid-level and lower crustal levels, and that timeframe would also include Precambrian cratons as their core.


Could a reported rainfall pH of 3.1 actually be realistic?

A quick literature search seems to confirm Gordons estimation, even at the scale of a whole bucket:

  [T]he annual mean pH, based upon
  samples collected weekly during 1970-1971 and weighted proportionally to
  the amount of water and pH during each period of precipitation, was 4.03
  at the Hubbard Brook Experimental Forest, New Hampshire; 3.98 at Ithaca,
  New York; 3.91 at Aurora, New York; and 4.02 at Geneva, New York. Measurements
  on individual rainstorms frequently showed values between pH 3
  and 4 at all of these locations. Data from the National Center for Atmospheric
  Research included precipitation pH values as low as 2.1 in the northeastern
  United States during November 1964.

Patel, C. K. N., E. G. Burkhardt, and C. A. Lambert. "Acid rain: a serious regional environmental problem." Science 184 (1974): 1176-1179.


How to create a model to predict the salmon run

You can use a program called Stella (which costs money) but there is also a free program that does nearly the same thing called Vensim.  These software packages allow you to build simple dynamic models using a GUI interface.

The materials (including salmon run scenario model files) for Andy Ford's "Modeling the Environment" class, which he taught for  many years, are here:
http://public.wsu.edu/~forda/models.html
with the "Smolts Migration Model" and "Salmon Harvest Simulator" prebuilt.

His text can be obtained online, the title is
"Modeling the Environment: An Introduction To System Dynamics Modeling Of Environmental Systems"

  Andrew Ford is Professor of Environmental Science and Regional Planning at Washington State University. He teaches modeling with an emphasis on environmental problems in the west, and he is the author of the Island Press text on Modeling the Environment. He uses the system dynamics approach to modeling, and he is the recipient of the Jay W. Forrester Award for the outstanding contribution to the field of system dynamics.


Magma resultant from group 1 and group 2 elements?

So let's break it down part by part:

  He sets forth that magma is not actually created from heat / pressure buildup, etc.

There is not a single mechanism for magma formation in the Earth. Magma can form by heating, decompression, infiltration of fluids (such as water), fluxing (by light elements e.g. B, F, P etc) and more. These are all well established methods for magma formation, with an immense amount of evidence. This evidence includes independent observations from seismology, geochemistry, fluid mechanics, and probably most important - experimental simulation of these processes.

  it is generated from a catalytic reaction from massive interactions of water with large group 1 and group 2 metal pockets or clusters within the earth's crust.

By "metal pockets" I mean that you mean metals with valence 0 - i.e. in the metallic state and not bound with other minerals. This is simply not true - especially for group 1 and 2 metals. These metals are highly reactive. Just search online for videos of "sodium party". The Earth's mantle has abundant oxygen in it (bound in silicates) and any group 1 or 2 metal will simply not exist as a metal. Even if for some obscure reason it would happen, where are the magmas containing these metal (more than they occur in magmas on a natural basis)? This simply doesn't make any sense.

  He further explained how the water enters into these pockets via
  various fissures both from our oceans and other bodies of water
  (noting some study from last year where researchers found incredible
  volumes of water 700 kilometers underground).

First of all, the chemical and physical behaviour of water is completely different when you compare ocean floor settings and the deep mantle. Water may flow in fissures under the ocean, but once you get to several 10s of kilometres deep, the rocks become ductile and water can no longer flow in cracks and fissures. Regarding last year discovery of water in the mantle - this is really a sad story of poor science communication. What was actually discovered was that a certain mineral can contain water in its crystal structure. It's still a solid mineral and still a rock. Same like the water in concrete - it's not actually liquid water. See these two questions for more info:

What are the implications of the recent discovery that huge oceans exist close to the mantle of the Earth?

Do ringwoodite minerals point to an "ocean's worth" of water, or a true subterranean ocean?

  One side note was regarding the contents of magmatic rocks being surprisingly high in alkali metals, etc.

Most magmatic rocks contain a perfectly reasonable amounts of alkali metals. There are some rocks that have high alkali contents (and they have funny names too!), but this is not something that requires a different explanation from what is known so far from experiments and other studies. Yes, there are rocks with abnormally high alkali contents, and there is still research going on in that subject.

  but I was out of my depth

I think this is the key word in here actually. Perhaps that professor was "dumbing down" his ideas to make it more accessible? This occasionally happens with us scientists, and in a lot of cases the listener simply understands something completely different from what the scientist meant. Another example of poor science communication, unfortunately.


Is a glacier advancing or retreating? How to tell?

The easiest way is to look a the glacier margins. If the ice is in contact with vegetation or rock covered in lichens or moss, it means it is most likely advancing. If you see a band of life-less rock in between the ice and the first plants/lichens/moss, it means it is retreating.

Some examples I've seen myself:

This glacier in Geenland is advancing, you can see the ice and vegetation in contact

Same glacier, you can see how it is even pushing vegetation, proving it is advancing

However, advancing glaciers are the exception. In most cases they are reatreating and what you see is a band of life-less rock surrounding the ice like this:

Retreating Amalia glacier in Patagonia

The advancing or retreating state of a glacier can have different time-scales. For example a glacier can be retreating on a decade scale, but it might advance every winter, but the recession on summer is large enough to produce a net retreat every year. Small glaciers can also react very quick to weather variations, therefore even if one is receding at a century scale, it can advance one year due to exceptional snow accumulation over few years. So you have to interpret this observations with care, and consider what's the timescale at which the plants/moss/lichens can colonize the rock in the area, which in temperate and low elevations will be between a few years and a decade.
Moraines, trim lines and other features can tell you about the advancing/receding history of a glacier at longer timescales.


Eruptive fissures in Hawaii associated with Kilauea; what are they? What is really happening?

It can be either an eruption from the top of an existing tube or deep surface cracks opening up existing magmatic systems. I believe, from what I've been hearing in the news, that in this case they are in fact fresh fractures, tectonic in origin, that have relieved local over burden and allowed magma to rise to the surface in areas that had previously been dormant for an extended period.


Why does Mars' experience an 'ice age' at high axis obliquity, when Earth experiences an ice age at low axis obliquity

If I understood it correctly, the important point is the temperature difference between mars and earth. On earth increasing obliquity, as you wrote, leads to increased melting of ice, ie. you increase the amount of liquid water on earth.

On mars average temperatures even during summer are too low to allow for liquid water. Higher obliquity doesn't really lead to a melting of ice. It mainly increases sublimation thereby increasing the water content of the atmosphere also on lower latitudes. The water vapour freezes out and leads to ice shields extended to lower latitudes.

So in short, since temperatures on mars are too low to allow for liquid water, the extend of the ice cover is larger, when the ice receives increased insolation.
Whereas on earth the ice cover is larger when insolation is low, since it gains mass from the pool of liquid water.


Any recommendations for a good online lecture series on Metamorphic Petrology

ClassCentral.com, SouthAlabama.Edu, ndsu.com, ocw.mit.edu
You can learn a lot from these sites.


A show is a visual indication of hydrocarbons, in the jargon of petroleum exploration, it is typically used to describe a drilling. It could be e.g. a Gas show in the drilling fluid. Show evaluation is an important tool to understand a reservoir.

When hydrocarbons reach the surface naturally, we call it a petrolium seep.

Technically, I guess, a seep could be a show if it's used to map a play but I never heard the term used in that context.


How to get cell indices from latitude and longitude in WRF model grids?

I've been a WRF user for almost 5 years now, and contributed code to a recent public release. I am not aware that WPS (WRF Preprocessing System) has such a tool that takes in the grid and point coordinates and returns the appropriate index. However, it is very straightforward to do so yourself. Some suggest using an external library, I think that may be an overkill for such a simple task. Here is what you need to do:

1) Run geogrid.exe to generate the parent grid. Since you don't know the exact location of the nest yet, set max_dom = 1 in namelist.wps. This will generate a file called geo_em.d01.nc.

2) Look at the geo_em.d01.nc file to find the right indices for your child domain. i_parent_start and j_parent_start refer to the x and y indices on the parent grid at which the southwest corner of the child grid will be positioned. XLONG_M and XLAT_M are the longitude and latitude grids of the mass (pressure) points. Using a programming language of choice, find the grid cell that is closest to your desired location for the child nest corner. This is typically done by looking for the minimum value of distance between desired location and all the points on the grid. For example, in Fortran, you can do something like:

integer :: i_parent_start,j_parent_start
integer,dimension(2) :: coords

coords = minloc((lon0-xlong_m)**2+(lat0-xlat_m)**2)
i_parent_start = coords(1)
j_parent_start = coords(2)

where xlong_m and xlat_m are 2-dimensional arrays that you read from the grid, and lat0 and lon0 are the desired coordinates of the child nest southwest corner. Similarly, if you use Python, you could do:

import numpy as np

j_parent_start,i_parent_start = np.unravel_index(\
    np.argmin((lon0-xlong_m)**2+(lat0-xlat_m)**2),xlon_m.shape)

# Add one because WRF indices start from 1
i_parent_start += 1
j_parent_start += 1

3) Now edit namelist.wps again, set the i_parent_start and j_parent_start to the values that you calculated in step 3, set max_dom = 2, and re-run geogrid.exe. The child domain file geo_em.d02.nc should be created.

4) Look at the geo_em.d02.nc file. Repeat the procedure until happy with the domain location.

About the parent_grid_ratio parameter. This is an integer factor of child grid refinement relative to the parent grid. For example, if set to 3, and parent grid resolution is 12 km, the child grid resolution will be 4 km. Odd values for parent_grid_ratio (3, 5, etc.) are recommended because for even values, interpolation errors arise due to the nature of Arakawa C-grid staggering. parent_grid_ratio = 3 is the most commonly used value, and recommended by myself.


The most abundant elements are:

Element  Approximate % by weight

Oxygen        46.6
Silicon       27.7
Aluminum       8.1
Iron           5.0
Calcium        3.6
Sodium         2.8
Potassium      2.6
Magnesium      2.1
All others     1.5

Source:http://hyperphysics.phy-astr.gsu.edu/hbase/Tables/elabund.html

Based on data from a number of NASA and ESA spacecraft and rovers,
(Fine summary on wikipedia: https://en.wikipedia.org/wiki/Composition_of_Mars). The four top elements are most likely the same. They are roughly the same on Mars and Earth and may be in the basic proportions

Oxygen
Silicon
Aluminum
Iron

I would expect at some point that the relative abundance of elements on Mars to deviate from that on Earth based on the following differences:

Earth and Mars were most likely formed at two very different distances from the center of our solar system.  This may have significantly affected the elemental abundances between the two planets.
Earth has had significant amounts of water since from very early in its history, as recorded by some of the oldest rocks on Earth which are meta-sedimentary deposits in Australia.
We do not known how much water has ever been on Mars. Mars is currently very dry.  Water plays a big role in element distribution on Earth and my guess is water will have played a smaller role on Mars.
Lastly, I am becoming convinced that biologic activity has also significantly affected element distribution on Earth.  Bacteria/Archaea have been found in deep rocks in South African gold mines, which is remarkable. Bacteria and Archaea may play a larger role in various geological processes than traditionally thought.  The Mantle is no longer viewed has dry and sterile.
Life on Mars (even as  Bacteria/Archaea) is yet to verified.


How to determine the transmissivity of a system of rocks and faults from the stationary drawdown pattern?

I would suggest Bense (Hydrologische Karakterisering van Breukzones in Zuid-Oost Nederland), as a starting point. It provides a clear view of a few methods used in the past and an indication of the level of detail needed for the analysis, possibly helping you narrow down your search to a suitable method. Mostly Dutch (not a problem, judging by your name), but few international sources too.

I have attempted to ascertain something similar in a spatial model (MODFLOW) recently. From experience, I can tell you that the placement of measurement locations is vital, especially when estimating fault resistances. In my case, the available observations offered no evidence supporting the presence of a fault, even though upward seepage and indicator species were widely observed.


Clouds are made up of very tiny liquid water droplets that have small fall speeds.  This means that with just a little bit of upward velocity in the wind, the cloud water can remain aloft and appear to float.  Clouds are not always static blobs -- if you watch some clouds you will see that air can flow through them, condensing into new cloud where it goes in and evaporating into clear air on its way out (easily visible in mountain wave clouds).

The reason clouds tend to have a consistent base altitude is due to how temperature and water vapor behave in the boundary layer.  On sunny, windy days the boundary layer is well mixed and potential temperature and water vapor mixing ratio are constant with height.  With a constant potential temperature the actual temperature will decrease at about 10$^\circ$C per kilometer of height.  With constant specific humidity and decreasing temperature as we go upward this means the relative humidity is increasing.  At some height the relative humidity becomes 100% and we call this height the lifted condensation level (LCL), which will also be the height of the cloud bases.  If surface characteristics are similar across an area, so will be the LCL and this will make all the clouds in the area have similar bases.  You were on the right track with the significant change in air composition, but it is a thermodynamic change with pressure playing a significant role.


Is there major potential for vertical farming?

As our planet gets warmer less area will be avaliable for farming so vertical farming will be needed to supply food for a growing population.

Vertical farming will not replace traditional farming but it will be an addition to this.

Vertical farming can be effective in growing food by using less energy,We can use only the part of the light spectrum that plants need(UV-Blue-Red-IR)And avoid producing un needed green light(plants do not use the green part of the spectrum).

The use of water can be a lot lower in vertical farming as any evaporated water can be captured and recycled.

The need of plant nutrients can be reduced significantly,One only needs to add the nutrients the plants remove(so no runoff of nutrients at all).

The use of pesticides can be close to eliminated and this is good news for insects that are needed in the production of food and for the consumers of the food.

A very large part of the water used in prossesing of the product can be recycled and used to create more food,So less water will be wasted.

A lot of the organic waste can be used as animal feed directly(Roots stems and flowers material not usable for human consumption).

So the answer to your question is yes there is potential in doing this,How large potential there realy is i do not know but i think it might be significant.

The prosess uses more CO2 than it releases(if renewable energy is used) so it is cleaner for the environment,It can be done anywhere so less emission of CO2 during transport to the consumers.


Has the Average Volume of Volcanic Emissions Been Constant Since the Last Major Fluctuation?

If you have access, I would recommend you to read this short chapter of the Encyclopedia of Volcanoes. In summary:

At ocean ridges, studies show a steady rate of oceanic crust production during the Cenozoic. There have been fluctuations before, maybe due to the breakup of Pangea or other major tectonic events. The present volcanic production rate is ~20 km$^3$ per year.
At volcanic arcs, it is harder to constrain because of the poor preservation of volcanic material. Tephra layers found in deep sea drilling cores show some peaks in explosive activity "in the Quaternary (0-5 Ma), the middle Miocene (c. 13-17 Ma), and potentially the Eocene (c. 37-42 Ma)". This is not well explained. There is also a shorter term variability due to deglaciation episodes: mass unloading depressurize magmatic systems. A conservative estimate of the modern output is 0.5 km$^3$ per year.
Finally, Large Igneous Provinces (LIPs) are very episodic (long-term average of one LIP every 10-20 Ma) but they emit a large volume (generally > 1 million km$^3$) in a relatively short period of time (a few million years). LIP emplacement coincide with major mass extinction events.


stretch phenomena after NMO application on seismic data

My understanding is the following (NB: it could be wrong!).

The assumption is that on a common shot gather, your travel time follows a hyperbolic curve:
$$
f(x)=t^2=t_0^2 + \frac{x^2}{v^2},
$$
where $t_0$ is the zero-offset travel time, $x$ the offset and $v$ the speed of the medium above the interface. The hyperbolic travel-times, for example, create gathers like the one shown in https://wiki.seg.org/wiki/NMO_stretching#/media/File:Ch03_fig1-9.png (which is figure '(a)' below).
Furthermore, the recorded wavelet has the same shape along the time ($t$) direction, regardless of which offset ($x$) you recorded it. Hence, on the figure below, check that there is no discernible change in the wavelet shape in figure '(a)' below as you move along the hyperbolic curve.
Then, NMO correction essentially comes down to stretching the original data. In the figure '(a)' below, I put a red line close to the zero offset point, and a purple line at far offset. In figure '(b)', which is an NMO-corrected picture, I highlight that same lines, with identical colors. You see that the zero offset  (red line) hardly requires a change, but the far offset (purple line) needs to be stretched considerably to create a flat curve in the diagram! A neat feature is that at at ~90% of the offsets, you still see 2 events cross in both figures '(a)' and '(b)', to indeed confirm that we just stretch the traces with no real further magic behind it...

So, the wavelet shape is constant in the vertical direction everywhere in figure '(a)', but is seriously stretched out in figure '(b)'.

From the page of the linked figure: "Note that stretching is confined mainly to large offsets and shallow times. For example, a waveform with a 30-Hz dominant frequency at 2000-m offset and t0 = 0.25 s shifts to nearly 10 Hz after NMO correction. Because of the stretched waveform at large offsets, stacking the NMO-corrected CMP gather will severely damage the shallow events. This problem can be circumvented by muting the stretched zones in the gather."

tl;dr: because the red and purple line in figure '(a)' must become the red and purple line in figure '(b)', the wavelets of particularly the purple line are stretched.


Trying to calculate the percentage of carbon emissions that is offset by 45,000 acres?

What kind of forest, 45,000 acres of What?
If it's boreal forest it's a slow carbon sink
If its tropical, it'll be faster
Forests are largely carbon neutral in terms of carbon emissions. In temperate forests they emit carbon when they go inert for the season.Trees are roughly 50% carbon (dry weight) by mass. Increases in standing timber are directly correlated with increases in bound carbon. But once those trees die they decompose to anerobic co2 again. To grow a pound of wood, a tree uses 1.47 pounds of carbon dioxide and gives off 1.07 pounds of oxygen. An acre of trees might grow 4,000 pounds of wood in a year, using 5,880 pounds of carbon dioxide and giving off 4,280 pounds of oxygen in the process. However deciduous temperate forests put out co2. Tree's with Long life spans and ideal growing conditions are however better carbon sinks, as they accumulate cellulose they sequester carbon. Once they're mature they slow down and become carbon neutral. Trees that largely never stop growing are good carbon sinks
Redwoods
Eucalyptus
douglas fir
Lawson cypress

Tall Tropical specimens
Koompassia
Menara
Bertholletia (Brazil Nut)


Deriving shallow water equations: why is the vertical velocity equal to the material derivative of the surface level?

This is a statement of the kinematic free surface boundary condition: there can be no normal flow through the boundary, only tangential flow along it. Equivalently, the normal velocity (relative to the interface) of the free surface position is the same as the velocity of the fluid.
Defining the position of the free surface as
$$ z = \eta(x,y,t) $$
then taking the material derivative
$$\frac{\partial z}{\partial t} +
u\frac{\partial z}{\partial x} +
v\frac{\partial z}{\partial y} +
w\frac{\partial z}{\partial z} =
\frac{D\eta}{Dt}
$$
Every term on the LHS besides $\frac{\partial z}{\partial z}=1$ goes to $0$ due to the fact that $z$ is an independent coordinate (see this answer for reference), leaving us with
$$w(z=\eta) = \frac{D\eta}{Dt}$$


In what way does the orientation of fossils help? What can we infer from that?

Lots of bones are long and thin and fairly heavy, to turn them all in the same direction water flow has to be fairly fast, we see the same thing today. fast flowing water turns bones and logs to present the least drag. This is important because it was one of the first ways used to establish bones whether had been moved by the environment after death.