How could an earthquake be stopped once triggered?

This is a very big stretch of the imagination and the technology to do so does not exist and most likely never will. But, adapting noise cancelling technology to cancelling the waves produced by earthquakes could be considered.

A system to do so would require an earthquake monitoring system coupled with a wave & strength analysis system that would then produce an out of phase wave pattern to cancel out the earthquake waves.

Some of the problems with this would be the response times required & how to generate a out of phase wave system of equal magnitude to the earthquake waves. Extreme care would be needed so that the out of phase wave generator did not cause a similar amount of damage, or more, than the earthquake waves.

Also, the out of phase wave generator would need to be able to produce wave patterns at extreme short notice, repeatedly & possible continuously to ensure immediate responses.

The wave generator would also have to produce waves of extreme complexity in three dimensions from pulse waves to shearing type waves.

To ensure fast analysis times of complex wave patterns, quantum computers (which currently do not exist) would need to be used.

Such a system would be complex and expensive.


It mostly has to do with the fact many minerals are partially translucent.

Trace impurities or even crystal structure can dominate the color of a translucent material but when ground in to a fine powder (streak) they can no longe do so and you can see the true color.

In other minerals surface oxidation can mask the true color.


Will California become a subduction zone in the distant future

Before the transform process of the San Andreas Fault zone we know today, there was indeed a subduction zone event taking place in this same region near now coastal California during the late Jurassic to late Cretaceous periods.
Today the city of San Francisco physically represents the aftermath of the ancient clash of mighty tectonic titans as the city and surrounding land and oceanic areas consist of and exists on several terranes and melanges which accreted, or formed, during this time, which make up the assemblage known as the Franciscan Complex. These assemblages are an illustrative historical account of events that formed while the mighty Pacific Plate aggressively rammed its way in an easterly direction toward the equally colossal North American Plate. There was a key player who’s pretty much laid to rest now and that was the ancient tectonic Farallon Plate in this same region off of California before the - modern day, neverending, gorgeous, and ever-dynamic coastline. This ancient plate now rests somewhere underneath Utah or there about, theoretically. Although and obviously not as robust as either plate forcing it into its “Malachi crunch” (uh oh, now I’m dating my own “...Days”), it was sizable yet, so while it was forced to dive underneath the North American plate for as much as a mass apparently its size can be, until eventually becoming so plugged up and impeding its displacement from the ongoing movement of the Pacific Plate, forcing it to redirect its great energy force elsewhere. This systematic transition of backed up energy marks the birth of the famous, very active San Andreas transform fault! For more on SAF: https://geo.libretexts.org/Bookshelves/Geography_(Physical)/Supplemental_Materials%3A_Physical_Geography_(Lenkeit-Meezan)/08%3A_Shaping_the_Lithosphere/8.03%3A_Orogenesis%2C_Faults_and_Earthquakes
Equally fascinating is that the subduction of the Farallon Plate formed the Sierra Mountain Range orogenesis by way of folding and uplift, while tensional stress of the orogeny stretched things out on both Eastern and Western locations of the Sierra’s and “simultaneously” formed the Great Valley which California’s Central Valley of today was/is vastly part of, as well as the creation of the Great Basin on the far eastern side of the Sierra Nevada Mtn. Range.


Why did a branch against a window prevent condensation?

The branch block outgoing infrared radiation and reflect some of it back to the window this will keep the temperature slightly above the condensation point.
Infrared radiation is the same as heat radiation.
Most objects will block and reflect infrared radiation and this is why dew does not form under a tree or under different types of roofs and objects partially covering the ground.
The CO2 in our atmosphere has a similar effect,absorbing and re emitting the infrared radiation keeping earth warm at night,had it not been for the different greenhouse gasses the temperature changes during the day night cycles had been a lot larger.


Weather conditions to create significant glacier growth

Hold on, you're talking about growth of the glacier's tongue, not necessarily the whole glacier itself. To my best knowledge, flow dynamics of ice in glaciers still are not wholly understood, meaning we do not really know, why sometimes glaciers seem to grow so rapidly (protruding their tongue).

A prerequisite is the presence of enough ice in the growth-area of the glacier (growth area is the part above the snowline), meaning above average snowfalls in the years or even decades before the easier observable tongue growth. More snow compacts to more ice, generating more pressure on the whole glacier body, finally causing the outflow of the tongue.


Your question is a bit confusing, but there is a strong connection between temperature and wind,in their spatial gradiant I would say, however, instead of temporal differences.

Imagine winds are only driven by changes in pressure (higher temperatures -> lower pressure and vice versa). Imagine there are two surface areas with different temperatures (say some frozen lake and a nice grass field in the sun nearby). Therefore the horizontal pressure gradient (due to horizontal temperature gradient) would force the existence of wind, blowing from the High to the Low pressure zones.

Now imagine another situation where there is no horizontal gradient (differences) of temperature nor pressure. The surface is homogeneous. Now imagine all the homogenous surface gets warmer at the same rate, but still remains homogeneous). There would be no reason, thus, for stronger winds (apart from molecular-scale phenomena due to warming, but I believe is not the focus here).

To summarize: winds driven by temperature differences do get stronger if temperature differences spatially increase. A high temperature, alone, does not say much and is way to vague to relate to what you ask.

You could also think of Antartica: very cold and high speed winds. Just to give a hint of how more complicated the relation between temperature and wind may be.


Other than the South Pole where is the windless place on Earth?

Truth be told, there is no such place. The atmosphere is a fluid, and a fluid moves. If a fluid did not move, it would not be a fluid.

Proof of concept- If you exhale, the carbon dioxide, water vapor, and other materials that form your breath would need to move, otherwise you would asphyxiate. That movement can be classified as wind, therefore wind exists.

Concerning the reference to your other question, there is no such a location. Consider the surface. Usually we assume the surface is fixed, which is fine over solid land. Because of this, there must be drag on the atmosphere. This drag slows the wind down. Since the air closest to the ground is slower than the air a bit further from the ground, there must be shear. Therefore shear is unavoidable.

For this entire monologue, I have spoken only on the small scales. It is worth noting that on the larger scales, that your linked question is true. A feature of geostrophic theory is the existence of Taylor columns. The Great Red Spot on Jupiter can be considered an example of such a Taylor Column (Ingersoll 1969).


Historically, how did the total amount of salt / NaCl on Earth develop?

Here is a graph describing modern estimates of ocean salinity throughout the Phanerozoic (past ~550 million years).
The original PDF of this study can be found here:

Hay, W.W., Migdisov, A., Balukhovsky, A.N., Wold, C.N., Flögel, S. and Söding, E., 2006. Evaporites and the salinity of the ocean during the Phanerozoic: Implications for climate, ocean circulation and life. Palaeogeography, Palaeoclimatology, Palaeoecology, 240(1-2), pp.3-46.

As this graph shows, it is not linear at all and actually decreasing since the end of the Precambrian. This is a result of many factors including changing volume of ocean water, and the global chloride cycle. The details are all described in that paper.


Remember that you are concerned about stability fields. The lines on your stability diagram are the places where two minerals are in equilibrium. One one side one mineral will be more stable, on the other side the other one will be.

Let's talk about $\ce{Ca}$ first. The reactions all have the same $\ce{Ca}$ so it's activity isn't a factor in their relative stability. If you write a combined reaction for any mineral to another, it will cancel out. Try it. Calcite stability has nothing to do with $\ce{Mg}$ or $\ce{SO4}$ it's stability will only depend on $\ce{CO3}$ and $\ce{Ca}$. But wait, you know $\mathrm{ln}\,a_{\ce{CO3}}$ so you can calculate $\mathrm{ln}\,a_\ce{Ca}$ in equilibrium with calcite. So you can use that to help figure out where calcite is the most stable.

You only have one equation where sulfate is included. What direction will that stability boundary take on your diagram? Say you want to divide your diagram space into areas of calcite vs gypsum stability, how could you combine the two solubility equations to come up with the conversion of one mineral to the other? What dissolved species activities enter into the equation (hint: you know one of the two). Given that you can figure out the other one and plot that on you diagram.

Can you follow a similar process for calcite and dolomite (hint: yes)? What about calcite and huntite? Is there any part of the diagram where huntite is more stable than dolomite (or vice versa)?

Now figure out the stability relationship between dolomite and gypsum. What angle will the line take on your plot? Figure out where it will occur by combining reactions. This is a bit trickier but the $\mathrm{ln}\,a$ values will depend on the $\mathrm{ln}\,K$ for the combined reaction.

Now erase any lines in a field where those two minerals are less stable than anything else.

Good luck and let us know if you get stuck. I didn't want to just give you the answer because I'd have to actually work it out.


How long will it take for the ocean to erode Rockall?

Impossible to give an accurate answer because nobody has ever studied rates of erosion of this kind of rock in such a setting. Typical long-term rates of cliff cut-back in an exposed position are 5 to 20 cm per year, but that is for average rock, which is much softer than Rockall. This is a complex rock, mainly comprising Aegirine Granite, and containing some unique minerals. I'm guessing that the combination of sea salt corrosion, frequent wetting and drying, and chemically aggressive leachate from all that guano will result in a rate of chemical erosion of 0.5 to 5.0 mm per year. Let us say 2 mm per year - a high value but under the extreme circumstances, certainly plausible.  Given that the rock is only about 25 metres along the lesser axis, and that chemical and weathering attack will occur on all sides, that should give a 'demolition rate' of about 6000 to 7000 years. But that's only chemical erosion. There is also the physical erosion to consider. None of the photographs I have seen give a good impression of the potential for basal abrasion. What your photograph does indicate however is that there are eroding oblique fractures. These will facilitate sea water and wave ingress which will eventually fragment the rock and accelerate its demise. Overall I would be very surprised if there is anything left above the waves in 4000 to 5000 years from now. Even without erosion, climate change is likely to raise sea level at least 7 metres by that time, in which case it may completely disappear in as little as 2000 to 3000 years.


The short answer is yes, the edges (boundaries) of tectonic plates do occur at the mid-oceanic ridges, such as the Mid-Atlantic ridge.

There are three types of tectonic plate boundaries:

Transform Boundaries where the plates slide past each other sideways, such as at the San Andreas Fault.
Divergent Boundaries where the plates are moving apart, such as the Mid-Atlantic Ridge  and the East African Rift.
Convergent Boundaries where one plate slides beneath the other plate, such as the Andes mountain range & the Japanese island
arc.


How do you tell if smoky quartz has been irradiated?

It can be hard to distinguish man-made smoky quartz from natural smoky quartz. Traditional methods for irradiation to convert quartz to smoky quartz tends to leave the quartz crystals looking more black than translucent smoky brown.  This is caused in part by the rapid irradiation time for man-made smoky quartz.  I am sure a more patient man made process could produce more naturally smoky quartz.

The best way to determine if smoky quartz is man-made or not is to know the location for the quartz specimen.  Arkansas, USA produces mostly clear quartz and very little natural smoky quartz.  Dark smoky quartz from Arkansas is almost certainly artificially made.  I have a specimen of dark smoky quartz which is almost black from Bear Lodge mountain, Wyoming that is definitely natural.

Best practice, if smoky quartz specimen does not have a well known location, assume its man-made never pay alot for it.


How and why humidity and vapour pressure change as a parcel of air with an unchanging amount of water vapor rises, expands, and cools

The imortant point is that absolute humidity is defined as

mass of water per volume of air

So if the parcel of air expands, and still has the same water content, there is less mass of water per volume, hence the absolute humidity decreases.

Maybe most if not all of the question depends on this and is much more clear now?


How do I calculate Per capita $\ce{CO2}$ emissions?

You have the right idea, but you have your units and orders of magnitude confused.
You have started with knowing that Canada has 34 million people, and emits 0.55Gt - i.e. $0.55 \times 10^9$ tonnes - per year.

Now rather than just using those figures, think about the units that you have, and the units that you've been asked to give the answer in. How many kilograms are in a gigatonne? Once you have a figure for kilograms per year, how will you convert this to kilograms per day?

NB I haven't checked your actual figures - only your arithmetic!


How can we determine the size and composition of Earth's inner core?

We know the the size of the inner core through seismology. From my answer to this question: How are subsurface wave speeds determined without subsurface sensors?, we can determine the speeds of the different layers of earth. Pictured below is a diagram of raypaths going through the earth from the 1994 Northridge Earthquake in Southern California:

(image from http://serc.carleton.edu/NAGTWorkshops/geophysics/seismic11/overview.html)

As you can see the earthquake causes many raypaths, some of which go all the layers of Earth. From Huygen's Principle we know that there are infinitely many ray paths, meaning that there is a raypath, depending on location, that

Goes through only the crust
Goes through the crust + mantle
Goes through the crust + mantle + outer core
Goes through the crust + mantle + outer core + inner core

and arrives at the same seismometer (probe that measures vibrations, or seismic waves in this case). Depending on the composition of these layers, the ray paths will have different arrival times. The difference between these arrival times are important, we call them lag times, which seismologists can use as a proxy for distance. The lag time between the 3rd and 4th raypath I mentioned above could be used as a proxy for the radius of of the inner core, but we probably would not get a good answer from that. More over, we use this seismic data along with other data types to constrain its size.

We can use gravity data to understand get the mass of the earth. See this question for how that can be achieved: How is the mass of the Earth determined?

Using the mass of the earth, its size, and assuming that density increases with depth, we can form a seismic wave model (in the first question I linked) which would give us a more accurate lag time to distance conversion.

We also know that Earth is made up of the same stuff as the Sun, by examining its composition through the light spectrum.

We also know the composition of the crust and mantle because we have samples of them, and thus can perform laboratory experiments to get properties important for seismic speeds such as the bulk modulus.

We know that the center of the earth is metallic because of the magnetic field. It was the Trela model that first proposed this. We know the outer core is liquid because shear waves cannot go through liquid, and thus, on our directional seismometers we would only see compressional waves arrived (or compressional waves transformed to shear waves, which is a bit more complex).

Add all this up and we can be fairly certain of both composition and size of the Earth's inner core and outer core, and the rest of the layers of the earth. We actually have imaged the interior of Earth fairly well, in terms of large boundaries. Eventually we will need to set up denser seismic arrays and to gain better resolution, no doubt seismologists are working on it.


Does Climate Data Store provide daily mean of ERA 5 reanalysis data?

tl;dr

I would suggest using the Toolbox of the Copernicus CDS. Via the Toolbox, you can choose datasets, process them and download the processed results. You have to be registered and logged-in to use the Toolbox.

How to find out how to select the dataset of interest

Use the search of the CDS and go to the bottom of the page. There, you can click/tab Show Toolbox request.

The page is extended and you get some code.

Access the Copernicus CDS Toolbox

Now go to the top of the page and click/tab Toolbox or go to this URL: https://cds.climate.copernicus.eu/toolbox-editor

You have to be registered to the Copernicus CDS service and be logged-in to be able to use the Toolbox. On the left, you have some example scripts. You can select datasets, process them, create figures, download data and much more. Amongst others, cdo (Climate Data Operators) can be used to process the data. The programming has to be done in Python.

You can select a dataset, calculate daily means and download the processed data via the Toolbox. Combining the cdo example (slightly modified) with the code from the search (described above) should yield some useful code for you.

Example code for the Copernicus CDS Toolbox

Here is an example request, which obtains a part of the data you want. It obtains only data for the year 2007 and for three pressure levels.

import cdstoolbox as ct

@ct.application(title='Retrieve Data')
@ct.output.download()
def retrieve_sample_data():
    data = ct.catalogue.retrieve(
        'reanalysis-era5-pressure-levels',
        {
            'product_type': 'reanalysis',
            'pressure_level': [
                '1', '2', '3',
            ],
            'year': '2007',
            'month': [
                '01', '02', '03',
                '04', '05', '06',
                '07', '08', '09',
                '10', '11', '12',
            ],
            'day': [
                '01', '02', '03',
                '04', '05', '06',
                '07', '08', '09',
                '10', '11', '12',
                '13', '14', '15',
                '16', '17', '18',
                '19', '20', '21',
                '22', '23', '24',
                '25', '26', '27',
                '28', '29', '30',
                '31',
            ],
            'time': [
                '00:00', '01:00', '02:00',
                '03:00', '04:00', '05:00',
                '06:00', '07:00', '08:00',
                '09:00', '10:00', '11:00',
                '12:00', '13:00', '14:00',
                '15:00', '16:00', '17:00',
                '18:00', '19:00', '20:00',
                '21:00', '22:00', '23:00',
            ],
        }
    )

    data_daily = ct.climate.daily_mean(data)

    return data_daily


Is this a former volcano in the Hamad Plateau, in the Syrian desert?

My Rand-McNally Atlas shows the signature for lava fields in that area. The elevations in Google Maps indicate concentric contour lines with only small differences in elevation, rising from 600m at the outer perimeter to 700m in its center. This a shallow cone-shaped formation. Best I can tell from Wikipedia (compare the picture there), this feature is:

  As-Safa (Arabic: الصفا, Aṣ-Ṣafā), also known as Tulul al-Safa (تلول
  الصفا, Tulūl Eṣ-Ṣafā), Arabic for Al-Safa hills, is a hilly region
  which lies in southern Syria, north-east of Jabal Al-Arab volcanic
  plateau.  It consists of a basaltic lava field of volcanic origin,
  covering an area of 220 square kilometres, and contains at least 38
  cinder cones.

NASA Earth Observatory provides a satellite view as well and gives a few more details regarding the very noticeable dark area:

  Es Safa contains numerous vents that have been active during the
  Holocene Epoch (beginning approximately 12,000 years ago). The most
  recent recorded activity was a boiling lava lake observed in the area
  around 1850. The dark lava flow field (center) likely represents the
  latest activity of the volcanic field, and is emplaced over older,
  lighter colored flows.


Is a billion years of Earth's history missing?

There was an article in that year's Scientific American, which I've read in the Polish edition. I don't have that paper now, but I think this was that one: http://www.scientificamerican.com/article/the-oldest-rocks-on-earth/

The discovery is described in short here: http://news.nationalgeographic.com/news/2014/02/140224-oldest-crust-australia-zircon-science/. It's about Zircon crystals, that are to be 4.4 billion years old. However, as the article states, the found is not (yet?) widely researched. But it's accepted, there are rocks that are 3.8 billion years old.

The problem is, only a special kind of crystals could survive the conditions on the young Earth, and zircons are one of them. They preserve only some part of the information about the geological history of the Earth. So it's not like that, that nothing has survived the first billion years, it's only a special minerals and rock did. It's not enough to answer many questions that are of top importance, like the origins of the life (but probably no geological sources would ever do, because of the fragility of the speculated pre-cellular life forms). However, we do get a lot of valuable information that will allow us to learn many facts about the Earth's history we didn't know before.


Is the Unified Theory of Climate (Nikolov & Zeller) compatible with the AGW/GHG theory in any respect?

The paper you linked lists as its first reference Volokin and ReLlez, 2014; a paper that addresses the magnitude of the Earth's greenhouse effect. The validity of the paper you found largely hinges on the reputation of the Volokin and ReLlez, so we will investigate that one first.

The science of Volokin and ReLlez

The traditional way to determine the 'greenhouse effect' of a planet is to compare actual planetary temperatures with Stefan-Boltzmann blackbody temperature based on the luminosity of the star, distance from star, and the albedo and emissivity of the planet. This calculation is done in Volokin and ReLlez and can also be found on Wikipedia.

Volokin and ReLlez are arguing that the actual greenhouse effect should be measured using the albedo of a bare planet stripped of its clouds. The Earth's albedo is 0.294, but they propose a bare albedo of the Earth of between 0.122 and 0.13. They then make an argument that simple albedo calculations are not very accurate, and that a use of Holder's Inequality should be used to integrate the effects of albedo and radiation incidence angle over the exposed surface of the bare planet. Redoing the Stefan-Boltzmann expected temperature calculations with this new method, they then calculate that actual 'greenhouse effect' of the Earth is more like 90 K, instead of the 33 K normally cited. This is significant because temperature magnitude of the Earth's greenhouse effect affects the climate sensitivity factor of global warming models.

I actually think this paper is pretty interesting. The core of its mathematical arguments seems valid (though I didn't try to work any of it out myself) However, the conclusions are not very good, and not very related to much of the mathematical arguments in the body. While there is an argument to be made that calculating expected surface temperature should assume a bare planet, the authors are basically concluding that all temperature differences between the bare planet and the observed Earth should be assigned to the greenhouse effect. That just isn't supported by the information they present. The Earth's actual atmosphere and biosphere are much more dynamic than the bare model they are presenting; the formation of high-albedo clouds by equatorial rainforests,and the presence of high-albedo sand in the sunniest places on Earth are just two non-greenhouse related effects that account for temperature differences between the author's ideal bare Earth and the real Earth.

While they consider a lot of interesting factors, I think Volokin and ReLlez are guilty of making too much of a spherical cow estimate. The author's make an argument for one thing, then make some huge leaps to an unsupported conclusion. All in all, I don't think that the author's conclusion of a 90 K greenhouse effect is valid.

The publication of the reference

Whatever its scientific merits, the paper doesn't look very good upon meta review. First off, the authors used fake names to publish the paper in an open access site. In fact, it is the same two authors of the paper you linked, except that they spelled their names backwards (Nikolov -> Volokin; Zeller -> ReLlez). Ummm...what? Also, they later retracted the paper. Also also, the journal they published in is now defunct. All in all, this is not a sign that the paper is good science.

Back to the original paper

So the paper that you are asking about (Nikolov and Zeller, 2017) is based on a paper by the same authors which has not-very-good conclusions, and was generally published in a shady manner. That's a big black mark at the very outset.

This paper is pretty long and detailed, and I admit I did not read all of it. But the kill shot for me was on the very first page:

  We  began  our  study  with  the  premise  that  processes
  controlling   the  Global  Mean  Annual  near-surface  Temperature
  (GMAT)  of  Earth   are  also  responsible  for  creating  the
  observed  pattern  of  planetary   temperatures across the Solar
  System. Thus, our working hypothesis was  that  a  general  physical
  model  should  exist,  which  accurately  describes   equilibrium
  GMATs  of  planets  using  a  common  set  of  drivers.

That is great, but we have already gone over how these authors are attempting to oversimplify a bare planet approach for predicting expected temperatures. The predictor variables they are using are stellar irradiance, blackbody reference temperature, greenhouse gas partial pressure and density, atmospheric pressure and density, and reference pressure for greenhouse fluids. We can see the authors are once again ignoring the effects of cloud formation and the way the biosphere affects albedo, amongst other things.

On a methodology note, the authors use a regression model to try to get some useful results. As a statistician (not a planetary scientist), this strikes me as a poor choice. Regression analysis of complex systems is a good way to get insight into what factors are important in affecting this system. I think they can be very useful for predicting trends, but I do not believe they are good for providing predictions that are accurate by physical science standards.

For example, I'm writing a paper right now that uses regression analysis to predict subway ridership at each station on a subway network. This is a very complex system (like planetary atmospheres), and our goal is to get error scores of 0.2 or so. That is great for predicting subway ridership, not so much for planetary temperatures. An error score of 0.2 is like predicting a temperature to be 300 K but it is actually 360 K. That's not good enough. So I just don't know what the authors are really trying to accomplish using a regression approach, especially with so few predictor variables. The physics behind the interaction of the predictor variables is pretty well known, so there isn't a lot of value if determining the correlations of the predictor values to the planet surface temperature; it is as if they are using the regression to test if the physics is correct. Finally, the data set is way too small to be using a regression analysis. Their only available data points are the planets and moons in our own solar system.

Conclusion

Well I wrote a lot there, and hopefully it is all comprehensible. All in all, there are some interesting bits to Nikolov and Zeller's approach, but I think they are over simplifying some things and are using a non-physical science applicable methodology to obtain questionable conclusions.

Honestly, I don't think that anyone should be treating their research pejoratively (I'm looking at you Andrew Jon Dodds in the comments). It is interesting, and it is certainly novel (from everything I've read). It just doesn't have great conclusions. And that's fine! Most research probably doesn't lead anywhere useful. At least they tried something. People seem to be mad at them just because the results are contrary to the general climate change consensus. Research should be appraised on its merits (or lack thereof) and not on whether its conclusions match preconceptions.


Is lower tropospheric temperature relevant to measure global warming?

Last month, the lower tropospheric temperature dropped 0.28°C from February to March, which seems like a huge drop even if it's due to seasonal reasons.

That is not what the linked article says. It instead says that the monthly lower tropospheric temperature UAH anomaly dropped by 0.28°C from February to March. The monthly temperature anomaly is the difference between the worldwide average temperature for that month in some year and the worldwide average temperature for that month over a baseline set of years, 1981 to 2010 in the case of the UAH temperature anomaly.

Seasonal temperature variations tend to be much stronger over land than over ocean. The other is that the Northern Hemisphere contains significantly more land than does the Southern Hemisphere. The combination of these two effects make worldwide temperatures exhibit a seasonal variation that reflects seasons in the Northern Hemisphere. February to March marks the transition from meteorological winter to meteorological spring (which starts on March 1 rather than March 22). One would expect March to be warmer than February, worldwide.

This is exactly what the GISTEMP records show:

source: https://data.giss.nasa.gov/gistemp/graphs_v4

Two key things can be extracted from the above graph: (1) There has been a general trend of warming since 1880, and (2) March 2020 was warmer than February 2020. What about monthly temperature anomalies, which is one of the topics in the question? The graph below portrays monthly GISTEMP temperature anomalies for recent years:

source: Same as above

The key relevant features from the above graphs is that while the monthly GISTEMP temperature for March 2020 was 0.62°C higher than that for February 2020, the monthly GISTEMP temperature anomaly for March 2020 was 0.06°C lower than that for February 2020.

Thus GISTEMP, which is based on temperature measurements near the surface, may have seen a muted version of the effect observed in the UAH data, which are based on satellite observations. I used "may have" because the 0.06°C drop seen by the GISTEMP model is barely above the 0.05°C uncertainty claimed for that model. The UAH model claims the same uncertainty (0.05°C), so their reported 0.28°C drop was apparently real.

  My question is, is lower tropospheric temperature relevant to measuring global warming?

The graph below compares surface-based measures (MET office, NASA, and NOAA) with satellite-based estimates (RSS and UAH). The MET office data starts in 1850 while the satellite data (UAH and RSS) don't start until 1981.

source: https://www.carbonbrief.org/explainer-how-surface-and-satellite-temperature-records-compare

All five datasets see the same general picture, which is temperatures generally rising, but with noisy peaks and troughs. Sometimes the satellite-based observations show variations that are not seen in the surface-based measurements, and other times it's the other way around. But in general, both see warming.

The satellites do not carry tethered thermometers that measure temperature at various heights in the atmosphere. They instead measure the intensities of electromagnetic radiation at various frequencies. The frequencies of interest for the UAH and RSS models are those at which the atmosphere is opaque.

There are issues with this approach. Excessive cloudiness (or the lack of clouds) can confuse the algorithms used to translate observations to temperatures. The instruments that measure the data degrade, and degrade unequally. To counteract this latter effect, radiosondes that do measure temperature are regularly launched to coincide with satellite passes so that the satellite instruments and algorithms can be recalibrated. Finally, while the satellite data do show a recent sharp climb (recent meaning the last six years or so), it's not nearly as steep as the increase observed near the surface by weather stations that actually do use thermometers.


Why do meteorologists use DM and equal height surfaces for some maps?

First, yes, DM does appear to be decameters (though Dm would be more proper).  D was actually the abbreviation I was taught for deca in grade school 20 years ago, but it appears da has become the official standard prefix now, perhaps because it was confused with deci (d).  They also list the spelling deka instead of deca as well, perhaps for similar reasons (though that may well still vary by locale?)

Now, actually all typical plots aloft are the varying height values where a given pressure is found (850 mb, 500 mb, 200 mb, etc).

Why do we look at height variations on set pressure levels?

First, for background, it's important to realize that, by and large, pressure and height are proportional, such that either one can determine a strong approximation of the other.  For large-scale weather you can directly invert them using forms of the hydrostatic equation.

$$\dfrac{\partial p}{\partial z} = -\rho g$$

Basically this proves extremely accurate when vertical acceleration is small, which is generally anywhere outside of intense thunderstorms.  Even when it is less perfect, it's a pretty useful approximation for pressure variations important on the scale of synoptic weather.

Actually, the basic weather pressure map we're used to RELIES upon this relationship... typical storm pressures we hear are 900-1000 mb, and maps often look like:

But you'll find that pressure at the ground is lower in most locations than is indicated on such a map.  This is because, despite being called "surface maps", they're actually sea-level pressure maps.  At any station situated above sea-level a weather balloon cannot acquire that sea-level pressure.  So the pressure must be extrapolated downward using these same equations.

But that still doesn't answer why we'd opt for isohypses...

One benefit may be that height maps are similar to topographic maps.

But it well truly stem from early meteorological rules of thumb.  One important forecasting tool before advanced weather models came from the thickness equation (an application of the hydrostatic approximation).  It works out that the thickness between 500 mb and 1000 mb was a helpful indication of what kind of precipitation would fall.  Values lower than 5400 m indicate that the air column is probably cold enough for snow.

It seems quite feasible that this was relationship was noticed even before the equations were understood.  1000 mb is very close to the surface pressure in many of the big cities during the early development of meteorology (such as New York City, Boston, London, and Paris).  So all they'd need to notice is a connection of the 500 mb height and the precipitation type.  This might be easier than spotting a pattern of ratios of 5400 m pressure values to surface pressure values around 0.5.

In the end, it probably goes back to how early upper-air observations were recorded.  It may well have been some guy going up in the balloons until radio, so would they have recorded at equal heights or equal pressures?  Or when radio and the early instrumentation were developed, what would draw them to choose set pressures or set heights?  I don't know the history well enough to give a certain answer to that.

In the modern era, models quite often use pressure coordinates (or similar sigma coordinates).  In addition, if you wished to calculate the quasigeostrophic omega equation or apply the quasigeostrophic height tendency equation, perhaps equal pressure maps might be slightly more useful.  However, I tend to doubt either of these are nearly significant in the overall development of the practice.

Also, why dekameters specifically?

A good contour interval at 500 mb proves to be 60 meters.  With the precision of that final digit being so trivial, and with international communication being precious, they opted to just transmit the first three values.  So 5400 meters just became 540, so dekameters.

Now, on the other hand, at 850 mb the reasonable contour was just 30 meters. (I believe for a long time, they opted to only send the last three digits of the height [as values are typically around 1200-1600 meters, the leading 1 is superfluous].  You can see reporting like this still on the University of Wyoming's website).  At a 30 meter interval, that final digit is twice just a little more helpful to place contours.  So meters were once used for 850 mb or 925 mb versus dekameters for 500 mb.

But, this has additional implications.... The reason these 850 mb heights fluctuate less than the 500 mb heights is because air density decreases with height.  The same mass of air takes up more room at higher heights.  So pressure changes more slowly as you rise:

But not only does this lead to different scales being important on different pressure levels... it could well answer that question of why they chose to record at equally spaced pressures instead of heights in early ballooning.  Otherwise, they'd end up recording a ton of extra upper-level values which proved rather without value.

And why 500 mb values?  The 500 mb map is a very central pressure level (near the level of non-divergence).  Low-level maps like 850 mb will have lows more connected in shape/position to surface lows than lows aloft [850 is often looked at more for thermal and moisture setup].  Upper-level maps like 200 and 300 mb won't have closed lows [and are looked at a lot for wind structure, in addition to short and long-wave trough positions]. So a central level like 500 mb proves to be a very good level to look at upper-level low strength.


Are marine fossils in the mountain happens due to lower sea levels?

Leonardo was wrong about this.  It is not due to sea level dropping (except in very isolated cases), it's due to the land rising.  Sedimentary rocks that form in sea beds are often uplifted by tectonic processes to form mountains and plateaus.  See e.g. https://en.wikipedia.org/wiki/Sedimentary_rock


What geological processes can cause local biases in the fossil record?

I have studied archaeology, not paleonthology nor geology, so most of my answer is either extrapolation of what applies on younger material or layman's five cents. Still I hope it will be useful somehow.

You already mentioned the fossilization processes - this is bit distant from my field so I'm glad that you are not asking for details on them. In archaeological record, organic material can survive for centuries only under specific condition, often similar to those leading to fossilization. These conditions are one of the main factors contributing to the density of remains of ancient people and the animals and plants accompanying them, along with past human behavior.

Inhumation helps to preserve the bones, or, with specific grave construction and acidic soil, hair and even soft tissues (Egtved girl is a famous example). Anyway, animals or even plants never practiced any ceremonial burials, so this behavioral aspect is marginal for ancient fossils. Just that organisms whose habitat was more prone to fossilization are preserved more often - but this is still part of deposition and fossilization stage.

Excluding the fossilization processes (which are crucial), geological stability is the factor number one (or number two, after them). The more volcanic activity, earthquake and/or erosion, the higher chance the fossils will be destroyed. As an archeologist, I had to learn at least a little on erosion, because they can destroy the artifacts we would like to find, or at least move them so that we might be confused in evaluating the context; I believe this applies even more for the millions of years of the fossils' lifespan. If I'm right (I might be wrong; this is not my field), this is not as important as the conditions for fossilization, because the erosion and other processes that might destroy or degrade the fossils are spread more evenly than the good conditions for fossilization.


Airports with longest continuous temperature records

I found a pretty easy-to-digest resource from NOAA here:

ftp://ftp.ncdc.noaa.gov/pub/data/noaa/isd-history.csv

It has a list of temperature sources (including airports), with their start/end dates that they were measuring.


Where can I get archived hourly temperature data?

The authoritative sources for your data are:

ASOS: Automated Surface Observation Systems at airports, and
MADIS:  the Meteorological Assimilation Data Ingest System, from NOAA

Those are collections based on calibrated, maintained equipment, with good geographic coverage.

And Wunderground already archives them, so it's a matter of selecting and using those, rather than the Wunderground data from their own source, the collection of personal weather stations.


What's the difference between cleavage and fracture?

They are not synonymous.

Cleavage means breaking along planes defined by crystallographic directions. For example, cubic crystals like halite, NaCl, often cleave along directions that follow the cubic form. However, with a different bond strength, like fluorite $\ce{CaF2}$, the crystals cleave most easily along octahedral directions, similar to two pyramids sharing a base.

Fracture is when the break does not form along the crystallographic directions. It then can be grainy or conchoidal (like breaking glass).

Fracture is also used to describe the breaking of rocks as opposed to single crystals. In this case planar fracture follows the direction of forces that formed the rock.


How would I use data to find specific humidity and mixing ratio?

The online calculator is giving you the specific humidity, which at a relative humidity of 43% is 43% of the saturation specific humidity at that temperature.

Reading from the chart, a rough estimate for the saturation specific humidity is ~37.5 g/kg at 35°C. 43% of this is 16.1 g/kg, which is close to the value given by the calculator.


How to better understand the RIP-nomenclature used in the CMIP5 project?

The RIP-nomenclature is used to distinguish between different runs of the same scenario within a modeling center rather than to indicate any similarity across modeling centers.  Strictly it's within and across models not centers, because some centers have more than one model, e.g., the MIROC center submitted models MIROC5, MIROC4h, MIROC-ESM, etc.  So r1i1p1 for some scenario is typically just the ensemble member that happened to be run first for each model.  One caveat is that whichever historial ensemble member you pick for each model, you should use the same member from the corresponding RCP scenario, e.g., historical r3i1p1 should join seamlessly with rcp8.5 r3i1p1:

  A  recommendation  for  CMIP5  is  that  each  so-called  RCP  (future  scenario)  simulation  should when  possible  be  assigned  the  same  realization  integer  as  the  historical  run  from  which  it  was initiated.

  From Taylor et al (2012) CMIP5 Data Reference Syntax (DRS) and Controlled Vocabularies (pdf)

There's loads more detail in that Data Reference Syntax doc that I've linked to, and a summary of it on the IPSL website.  Karl Taylor gave a presentation that summarised it even more succinctly:

  r = “realization”: simulations started from equally likely initial conditions
  that lead to equally likely realizations of the true climate trajectory
  i = “initialization”: only used in decadal predictions, to distinguish among
  different initialization procedures
  p = “physics”: to identify simulations that are very closely related (e.g.,
  “perturbed physics” ensemble members or simulations forced by slightly
  modified parameterizations)

In practice, the "initialization" and "physics" ensemble members are a bit specialist and the vast majority of CMIP5 users just stick to the rNi1p1 members, and most of them probably just stick to r1i1p1 from each model (e.g, Peng et al, 2019) for simplicity.  You should feel free to use any of the "realisation" members from each model, and you could pick r1i1p1 from one model and r10i1p1 from another.  I'd advise sticking to one ensemble member from each model though, to avoid your analysis over-representing the forced responses of models that submitted more realizations to the CMIP5 database.

To address your final question, it's more common to look at the variance across the models for a given scenario.  But there are also plenty of studies that use the variance within each model ensemble to estimate the uncertainty of a model property due to internal variability, e.g., emergent constraints on climate sensitivity.  It really depends what you're investigating.


Is there any covalent crystals that can be easily synthesized?

Silicon carbide is covalent and can be synthesized at atmospheric pressure by the Acheson process. Temperatures may actually be somewhat higher than your range but are easily achieved by the process.

1,4 dichlorobenzene (used in moth balls) is a compound that forms crystals at low temperatures. I think the molecules in the crystal are joined only by weak bonds so I don't know if that is what you are after.


It does make sense.
As you said - glaciers have lower 18O/16O. This is because they have less 18O overall. Therefore, the oceans have more 18O. But this is today.

At the Cretaceous there were no continental ice sheets, so what we said previously is not relevant. There are no ice sheets to take all of the 16O, so it's all in the ocean. This results in a lower overall 18O/16O ratio.


reverse time migration for wave equation PDE using SBP-SAT

I have no experience with SBP-SAT methods, but you may try and go through the references in (and potentially contact the authors of) this paper https://arxiv.org/pdf/1802.06123.pdf .

Personally, I don't see a strict need for using such 'complicated' modelling methods for RTM. In the ideal case, you have deghosted (i.e., upgoing) recorded data and a smooth velocity model. Then, using standard low-order finite-difference modelling on a uniform grid should already provide fairly good results at fairly little cost. Likely, you'll achieve better results by optimizing the data & velocity model than improving your numerical code beyond the standards. This simple MATLAB code https://csim.kaust.edu.sa/files/ErSE328.2013/LAB/WE_LABS/index.html already does a brilliant job using 2nd order accuracy in time and 8th order accuracy in space, using a simple FD method.

Of course, if you are doing state-of-the-art (academic) research or are dealing with a very atypical velocity model with an extreme dynamic range, these are interesting topics to look into, and I hope that someone may be able to help you... But I hope that my answer may help you right now.


How do archaeologists address time dilation when analyzing carbon dating results?

For all intents and purposes, the Earth represents one frame of reference, as @kwinkunks states. Therefore no effect.

Yes the gravitational field on top of a mountain is slightly less than at sea level. This is very small though. Variations in gravity over the Earth's surface typically vary at most by a few hundred milligals (ie. "one part in 10,000" order of magnitude).

I doubt you would be able to measure General Relativistic effects due to such small field changes (even integrated over 10,000 years) - and even if you could, they are much smaller than other sources of error (e.g. the atmospheric C14 curve, and sampling errors).


The story told in the movie about the meteorite is fictional. Here is a quote:

  The Kartenhoff, the oldest in human possession. The very meteorite
  which made this crater.

The Kartenhoff is a fictional meteorite (I found few sources about the movie saying so, this is the most comprehensive one). It is not the oldest known to humans, and it didn't make the crater shown in the movie. That crater is in fact the Gara Medouar, a crater-like formation created by erosion NOT a meteorite (here more info about it). This link will take you to a view of it on Google Maps.

All the above make me think that the object shown in the movie is not a real meteorite (maybe not even a real object and just crated digitally), however it is definitely inspired in a real one. As it have the color of an iron meteorite and its characteristic regmaglypts (indentations on the surface of a meteorite created by ablation while falling through the atmosphere). As mention by Trond Hansen in the comments, perhaps ir was inspired by the Willamette Meteorite. With 15 ton in weight, it is much larger than the one on the movie (it is 3x2 m) but have a remarkably similar shape and general aspect.

(Picture from Wikipedia commons, originally here)

In terms of shape, iron meteorites (that are a small fraction of all existing meteorites), tend to have very irregular shapes. Therefore, to find one as "perfect" as the one in the movie is unlikely, but not imposible. A Google Images search for iron meteorite, would show you in a glimpse the vast diversity of shapes, been generally irregular.

Now when it comes to size, they can be much larger than that. Some examples are the "El Chaco" meteorite found in Campo del Cielo, Argentina, weighting 37 ton.

(image taken from DESTINO INFINITO)

Or the largest iron meteorite know, the Hoba meteorite, with 66 tons.

(image taken from TripAdvisor and submitted by user huys25)

The reason we found meteorites up to about that size only, is because they are small enough to suffer a significant slow-down when falling though the atmosphere. Larger meteorites hit the surface so fast that the energy released vaporize the meteorite, so only the crater is left with no traces of the impacting body.


Causes of fluctuations in atmospheric oxygen in past 300 Mya

Here's a somewhat different looking graph, from Oxygen and Evolution,
Robert A. Berner et al., Science 316, 557 (2007):

The graph shows three marked drops in O2 levels, each corresponding to an extinction event. These are intervals 4, 9, and 11. Interval 9, the largest such drop, represents the end Permian event about 252 million years ago. Interval 11 corresponds to the end Triassic event, 201 million years ago. The unsourced wikipedia graph linked in the question has at most a superficial resemblance to this sourced graph.

Now for your two questions.

  What they don't explain, however, is why oxygen has declined for the last ~100 Mya. For example, is this explicable in terms of volcanism?

I would take even the sourced graph that I used with a grain of salt. That unsourced wikipedia graph: A very large block of salt is needed.

  They do explain the Permian decline in terms of volcanic activity, but why do volcanoes affect oxygen levels?

It is very widely conjectured that the end Permian extinction event was caused by the Siberian Traps. This extreme volcanism may have triggered coal fires, thereby reducing oxygen levels. This remains conjecture.

What isn't conjecture is that the end Permian event killed off almost all life extant at that time, including much of the algae and plants that produce oxygen. Without a continuous supply of new oxygen, oxygen sinks such as unweathered rock will inevitably result in a decline in oxygen levels.


Cooling film area to undo global warming

I will answer the question with some simplifying assumptions that might then provide a coarse guess of the area needed. First lets assume that temperatures have risen $1^{o}C$ and that the cooling film acts as increasing surface albedo effectively reflecting that an additional fraction of sunlight (93/1366) from earth. By following the footsteps of the idealized greenhouse model we can derive the surface temperature as:
$$T_{s} = \bigg(\frac{S_{0}(1 - \alpha_{p})}{4 \sigma (1 - \frac{\epsilon}{2})}\bigg)^{1/4}$$
Where $T{_s}$ is surface temperature, $S_{0}$ is the solar constant ($1366W/m^ 2$), $\alpha_{p}$ is the planetary albedo, $\sigma$ is the Stefan Boltzmann constant and $\epsilon$ is the emissivity. By approximating the planetary albedo as 0.3 and emissivity as 0.78 we get that the surface temperature of is 288K. We can now set that the surface temperature is one degree smaller and there is an addition to the planetary albedo due to the cooling films. Solving for albedo:
$$\alpha_{p} = -\bigg(\frac{T_{s}^{4}4\sigma (1-\frac{\epsilon}{2})}{S_{0}} - 1\bigg)$$
By substituting the values we find that planetary albedo has to be about 0.31, so cooling of one degree has been reached by a 0.01 additional albedo. The ratio of the cooling film absorbency and solar constant $\frac{93}{1366} \approx 0.07$ can be seen as the additional planetary albedo if the cooling film is installed globally. This being seven times the needed change of albedo implies that a seventh of earths surface should be covered.

This doesn't take into account any secondary effects, that all areas of earth aren't equally important, that earths albedo isn't constant, nor is the emissivity, angle of radiation matters, this equation doesn't really take into account greenhouse effect(it just uses values that provides in current state case reasonable numbers), et cetera. More accurate answer would come by running a climate model and tweaking albedo in fixed grid cells.


How much of the current global warming is due to human influence?

Firstly it is worth demonstrating that 97% of climate scientists agree that climate-warming trends over the past century are very likely due to human activities.

  W. R. L. Anderegg, “Expert Credibility in Climate Change,” Proceedings
  of the National Academy of Sciences Vol. 107 No. 27, 12107-12109 (21
  June 2010); DOI: 10.1073/pnas.1003187107.

  P. T. Doran & M. K. Zimmerman, "Examining the Scientific Consensus on
  Climate Change," Eos Transactions American Geophysical Union Vol. 90
  Issue 3 (2009), 22; DOI: 10.1029/2009EO030002.

  N. Oreskes, “Beyond the Ivory Tower: The Scientific Consensus on
  Climate Change,” Science Vol. 306 no. 5702, p. 1686 (3 December 2004);
  DOI: 10.1126/science.1103618.

But what percentage of the increase is attributed to humans?  Probably almost of all of it.

The scientist Gavin Schmidt from NASA was asked this question on realclimate.org

His response was as follows:

  Over the last 40 or so years, natural drivers would have caused
  cooling, and so the warming there has been (and some) is caused by a
  combination of human drivers and some degree of internal variability.
  I would judge the maximum amplitude of the internal variability to be
  roughly 0.1 deg C over that time period, and so given the warming of
  ~0.5 deg C, I'd say somewhere between 80 to 120% of the warming.
  Slightly larger range if you want a large range for the internal
  stuff. [emphasis added]

The rapid increase in the human-driven component of the forcing are increasingly dwarfing the small, slow natural forcings, rendering them increasingly irrelevant.


Local Weather Forecast (Self-Learning Algorithm)

(not an answer, too long for a comment)

Strictly speaking, the answer is yes, since the temperature generally increases during the day and falls at night (and local time is a local variable), the barometric pressure and humidity can indicate if a storm is coming (there were some really old fashioned weather prediction "clocks" that did this). Realistically, upcoming weather in your local area depends on what's nearby, since that's the weather that moves into your area. Also make sure you don't overfit your model: even a model that perfectly fits your existing data isn't necessarily predictive. Finally, there are lots of weather data available, including local weather data, and you might want to use those data as well.


Someone (Casey?) can probably provide a fuller answer, but the basic idea is that ice molecules are kind of locked into place by the molecular structure of the ice crystal, and can't vibrate very much. Increase the energy, and the molecules vibrate more until the molecular attraction is disrupted to become water, when they vibrate a lot. Increase the energy still further and the individual molecules are flying about like crazy, thereby turning into a gas. Water is an extraordinary compound. The energy required to break the attraction between molecules in the liquid state is a whopping 2258 kilo-joules per kilogram - a handy property that brought about the age of steam, and the industrial revolution.

It is this phase transition energy (latent heat) that produces the cooling. The principle of conservation of energy, as applied in nature, requires that to balance the energy gain by the water vapour, there has to be an equivalent energy loss somewhere - hence the cooling effect on the liquid.


Yes, there are a lot of waves in wind. The wave you may be looking for is called a gravity wave (aka buoyancy wave). To name a few other waves
Rossby Waves, Gravity Waves, Inertio-Gravity waves, Sound Waves, Kelvin Waves

I am sure there are more than just those few waves out there.


What are these clearings in Amazon rainforest?

Hard to say. Some could be clearings for log landings, some for small villages or outposts used by the military or others, some cleared due to natural disturbance in the area (e.g. fire from lightening strikes) though I'd expect the latter to have sparse canopy and not be totally clear.

Many of these patches don't have signs of good access routes (other than by air or through thick vegetation). No doubt there can be smaller trails and rivers under the canopy, but we don't see any substantial routes with canopy cleared overhead. Therefore, logging and mining seems less likely, though both occur in the region. Smaller scale operations, like a clearing for more sun-loving plants by a local human population, could account for some of these though.

On the village or outpost possibility

Consider these clearings:

Two relatively nearby clearings, one with what appears to be grainy rocks but could be thatched roofs of a village
Another nearby clearing that appears to have a significant amount of its soil covered in a darker shaded texture, again perhaps thatched roofs
And another clearing, partially open and partially with this same darker texture to it in a shape that could certainly be a spread of small buildings in a community

I searched for on-the-ground views of potential villages and found a few that could match the view from above.

Here's a large communal structure in a clearing which could match some of the textures we see. Some indigenous groups of the Amazon live in large structures like this as a community, and some just use large structures like this as ceremonial communal spaces.

Here's a set of buildings in a village clearing. Note how close the forest canopy comes to the buildings. Given how thick the forest is, it's probably not easy to manage, but that could be all the more reason to get to bare ground in these village clearings.

Here's a pretty amazing example of small scale clearings and manipulation of the forest landscape by indigenous communities. While we're not seeing this from a satellite, it points out how the lack of texture nearby and between these clearings doesn't necessarily mean there's no trails or human presence. It appears these structures are surrounded by unusual tree canopies - perhaps banana or another agroforest crop - which could be cultivated from nearby shelters.

In conclusion, a likely possibility is that these clearings are signs of relatively-isolated small-scale villages or outposts.


How are Richter magnitudes of past earthquakes estimated?

The approximate magnitude of ancient historic earthquakes may be estimated using a Magnitude/Intensity comparison based on modern earthquakes.  Earthquake intensity may be estimated from the descriptions written down by people. The Chinese officials made detailed records of the damage caused by large earthquakes.


Difference between soil Water Holding Capacity and soil pore volume?

As Friddy says, if it's not constrained and relatively intact you're going to have issues with pore volume calculations. Generally the saturate-and-dry method, using a soil core, will give you both the water mass and the mass of sediment. Then you'd use the average density of soil (which will depend somewhat on the minerology, and if it's got lots of organic matter--which can be calculated by burning off OM in a 400 C oven) to get at the particle volume. The known volume of the core minus the estimated particle volume would give you the pore volume.

Googling bulk density and particle density should find lots of info on how exactly to do this calculation.


How big was the eye of the El Reno tornado?

There is no eye in the centre of a tornado's funnel, if we see the eye as a near circular cloudless area from bottom to tropopause, surrounded by a wall of towering clouds. Some interpretational leeway may lie in the low angular windspeed in the centre of the vortex, but that is not comparable to a hurricane's eye. Force of the central updraft is still strong enough to keep debris in suspension.
A vortex forms from updraft, warm air including 'macroscopic particles' is sucked into the cloud, while a hurricane's eye forms because of sinking air in the centre of a much larger and longer lasting storm system. There may, though, be water spouts under the individual thunderstorms of a hurricane's eyewall. Cause for rotation of a hurricane is coriolis force, while the vortex rotation is thought to be caused by vertical windsheer in the horizontal inflow. Hurricanes gain their energy from warm sea water, while thunderstorms are caused by vertical labilization of the atmosphere along a frontal line.
Here's a publication about the El Reno tornado. No structure that could be interpreted as an eye can be found in the interpretation of the radar data (Figure 15), and there's still a huge black thundercloud right above it.
Thunderstorms with tornados and tropical storms like hurricanes and typhoons are fundamentally different in how they form and evolve, their size and structure, much information on both phenomena can be found on the internet.
And, btw., TS Marco 2008 didn't have an eye either, I believe.


Are there more earthquakes near the equator or poles?

Most earthquakes happen at the edges of the Earth's tectonic plates. Look at a better sample of earthquake epicenters collected using modern seismological techniques and compare to this List of tectonic plates

Earthquake epicenters are concentrated at the edges, and more sparse in plate interiors, but there are regions of high seismicity at high and low latitudes.

If you really want to know whether the concentration of earthquake epicenters is greater near the equator than near the poles, then you should try the following:

1) Divide the surface of the globe into ~30 regions of equal area.

2) Make a table with a row for each region. Give the table two columns: the region's latitude (L), and the number of epicenters in the region (E).

3) Compute the arithmetic average of E for all 30 regions, call this G. Take the square-root of G and call this D.

4) Now look at your table.  How many regions have a concentration E>5*G? How many of these are located at 'polar' latitudes and how many are located at 'equatorial' latitudes?

5) If you find that 80% or more of the E>5*G regions are in 'equatorial' regions, then that is probably evidence that significantly more earthquakes are measured in 'equatorial' regions. If you don't find this much, the effect is small.


Is the epicenter always directly above the hypocenter?

By definition, the answer is yes:

  epicenter, the point on the earth's surface vertically above the focus of an earthquake, or the Hypocenter

according to Merriam-Webster or a many other sources.


How do we use oxygen isotopes as temperature proxy?

This is somewhat a general answer.  According to the Royal Chemical Society webpage Chemical climate proxies (Evans, 2013), the rarer and heavier $\ce{^18O}$ isotope in water generally evaporates after and condenses (and precipitates) out earlier than the lighter and more common $\ce{^16O}$ isotope, shown in the diagram below:

Source: University of Michigan's page Past Climates on Earth

The colder the environment, the quicker the atmospheric water vapour condenses, hence the quicker the $\ce{^18O}$ isotope is depleted, giving a lower ratio of $\ce{^18O}$ to $\ce{^16O}$ (referred to by the RSC page as $\delta{\ce{^18O}}$) by the time it reaches the poles.  In contrast, a warmer environment would mean that the water vapour condenses later and slower, meaning that less $\ce{^18O}$ laden water vapour condenses, resulting in a higher $\delta{\ce{^18O}}$ value.

In short, it is not so much of the amount of $\ce{^16O}$, but rather the ratio of $\ce{^18O}$ to $\ce{^16O}$ isotopes present, otherwise known as $\delta{\ce{^18O}}$.

The following Earth Observatory diagram demonstrates the present-time process, showing the differences between warm and cold environments:

Source: Earth Observatory's page: Paleoclimatology: The Oxygen Balance


Why is the Sahara so much larger than the other horse latitude deserts?

I think the size of the continent is a big contributor.  If there's very little cloud cover, and little rain, the air just keeps drying out the ground.  Try finding a good map of surface or lower-level winds, and just compare how long it takes an air parcel to go from over ocean to the Sahara.  Sometimes the winds will come straight from the oceans, but often they come from over land: the Near East and Asia.

But yes, all your examples end at mountain ranges.  Or rather, start there.  At the horse latitudes and on the equator-ward edges of the subtropical ridges, winds mostly blow east to west, not west to east.  A number of these deserts are thus in rain shadows of a sort (https://en.wikipedia.org/wiki/Rain_shadow).  This kinda ties in with the above: Since the wind blows east to west, the air that blows over the Sahara hasn't just been over Africa but also much of Asia, drying out along the way.

My explanation for Australia would be this.  It doesn't have major mountain chains, so it's not in a rain shadow.  But it doesn't have mountains, so there's nothing to initiate orographic precipitation.  It's convective precipitation or nothing, once you get inland.  And since the ground is dry, convective precipitation doesn't have much of a water source, so it doesn't rain much and the ground stays dry.  Someone with more background on Australia should chime in on that, though.


How to calculate 3-hour flux values in ERA-Interim?

After my original answer, and some back and forth in the comments, turns out I got the answer right by a bit of fools luck, and we sorted it out...

The thing is, despite flux being commonly thought of in physics as BetterExplained.com suggests:

  Timing: We measure flux at a single point in time. Freeze time and ask
  “Right now, at this moment, how much stuff is passing through my
  surface?”. If your field doesn’t change over time, then all is well.
  If your field does change, then you need to pick a point in time to
  measure the flux.

But, fairly counter-intuitively to many, meteorological models often, despite naming their variables as flux (such as sshf... surface sensible heat flux), actually store them as accumulations.  This ECMWF whitepaper on archive data specifications explains:

  Physical fluxes archived by the ECMWF model are accumulated since the
  start of the relevant forecast, and therefore in units of
  $\mathrm{Jm^{−2}}$ (or $\mathrm{W m^{−2}\cdot s}$).  Thus, a daily
  mean (in $\mathrm{W m^{− 2}}$) is obtained by retrieving the
  accumulated fluxes at $\mathrm{t_1=t}$ and $\mathrm{t_2=t}+ \mathrm{24\;hours}$ (where
  $\mathrm{t}$ is the time of the start of the average), taking the difference
  and dividing by 86400, the number of seconds in a day.

So, though intuitively, you might think the surface sensible heat flux at 6 hours would just be the sshf variable in the 6 hour file, it isn't.  To get the best estimate of the flux, you'd need to calculate it as:

$$\mathrm{\frac{fluxvar_{(this\;timestep)} - fluxvar_{(previous\;timestep)}}{timestep_{(in\;hours)}\cdot3600}}$$

So if you want to find the average flux between hours 3 and 6, you'd do:

$$\mathrm{\frac{fluxvar_{(t=6hr)} - fluxvar_{(t=3hr)}}{3\cdot3600}}$$

A couple of questions that Vidhi asked about that may be worthwhile understanding to others:

Why did the website quoted show the calculation as $\mathrm{({fluxvar_{(t=6hr)} - fluxvar_{(t=3hr)})/10800}}$, but not $\mathrm{({fluxvar_{(t=3hr)} - fluxvar_{(t=0hr)})/10800}}$... instead just using $\mathrm{{fluxvar_{(t=3hr)}}/10800}$

Because indeed, in this strange accumulation form $\mathrm{fluxvar_{(t=0hr)}}$ by definition is zero.  The variable may or may not exist in the $\mathrm{t=0hr}$ file, but if it does, it should be pointless to include as it had better be 0 if it is indeed accumulation.

The site quoted only mentions hours 3, 6, 9, and 12.  I have 15, 18, and 21 as well, how do I deal with this?

The same math applies... but remember, if you're dealing with forecast model archive (rather than reanalysis data), you want to use the shortest future hour possible.  So actually, rather than use 00Z's $\mathrm{t=12hr}$, you want to be using 12Z's $\mathrm{t=0hr}$, such that, when calculating the 9Z to 12Z flux average, best is$\mathrm{({fluxvar_{(12Z\;t=0hr)} - fluxvar_{(00Z\;t=9hr)})/10800}}$.  Because you only need steps 0, 3, 6, and 9 before the next archived model/reanalysis file (for a twice a day model), the 12/15/18/21 values really are the 0/3/6/9 values (just from the next model run).

Anytime derived values (variables that aren't in the model itself, but require a formula to determine) need calculating, such as total surface heat flux, just make sure that when you combine the variables (in this case the shortwave, longwave, sensible, and latent heats), you only divide by the timestep once (don't divide by 10800 in the separate input variables beforehand, then divide by 10800 again after combining them).

The models are strange to many.  I just happened to incorrectly remember what a flux was, and get the "divide by 10800" math right (probably in part due to horror memories of working with similar files in years gone by!).  But hopefully this helps some confused people!


What do weather forecasters mean when they say "50% chance of rain"?

In the US, meteorologists forecast the probability of ANY amount of precipitation falling.  The minimum amount of that we deem acceptable to meet this criteria is .01".  So, we are forecasting the probability of one hundredth of an inch of precipitation to fall at a location.

We look at observational data from ground stations, satellites, and computer models and combine it with our knowledge of meteorology/climate and our past experiences with similar weather systems to create a probability of precipitation.

A 10% chance of rain means that 10 times out of 100 with this weather pattern, we can expect at least .01" at a given location.

Likewise, a 90% chance of rain would mean that 90 times out of 100 with this weather pattern, we can expect at least .01" at a given location.

Similarly, the Storm Prediction Center issues severe threat probabilities.   You can see things like 5% chance of tornado or 15% chance of severe hail.

This simply means 5 times out of 100 in this scenario we can expect a tornado.  Or 15 times out of 100 you can expect severe hail with thunderstorms.

By definition, there is no difference in the amount of rain forecast by a 10% chance or a 90% chance.  Instead, that information is defined elsewhere, typically by a Quantitative Precipitation Forecast (QPF).

Meteorologists are still struggling with the best ways to inform the public about the differences between high chance, low QPF events versus low chance, high QPF events, and everything else in between.

Meteorologists are still human and have their own wet or dry biases that can hedge the chance of precipitation you see.   Recently, forecasts are relying more on bias-correction techniques and statistical models to remove the human bias from precipitation forecasts.


Does a registry for fallen meteors exist?

The short answer is "yes" and the links are provided below.

Fireball reports: https://www.amsmeteors.org/fireballs/fireball-report/
Classified meteorites: https://www.lpi.usra.edu/meteor/


Will a nuclear bomb stop an earthquake from happening?

A nuclear explosion in the subsurface will result in ground motion which in theory can trigger an earthquake (due to passage of dynamic waves) if a locked fault has already accumulated sufficient strain over the last few decades/centuries due to slow motion of plates.

Having said that all the nuclear stockpile in the world is not enough to obliterate even a small part of the plate boundary. The 1960 Chilean earthquake released accumulated strain energy of the order of 3 Gigatons of TNT or 200 Gigatons of TNT equiv or 12 million Hiroshima type bombs (Numbers are based on calculations by JC Lahr and are available at http://www.jclahr.com/alaska/aeic/magnitude/energy_calc.html)

So yes, an explosion in the subsurface can probably act as a trigger for an impending earthquake but it cannot stop if from reoccurring again after few decades/centuries.


Cross-line fold of a towed-streamer survey

By midpoint range he refers to the size (length in the crossline direction) of the area in the subsurface that is illuminated by one pass of the boat. In a simple case of flat and parallel layers, that range is half of the size of the "spread" or receiver patch. BTW, this is true both in inline or crossline directions.

By coverage he means how the subsurface is illuminated by the combination of many passes of the patch over the area of a 3D survey. In common practice, passes are overlapped in the surface by half the crossline size of the patch so that the areas of subsurface illumination are contiguous with no overlap.


Difference between thermal and contact aureole

Contact aureole, thermal aureole and metamorphic aureole are all synonyms referring to the peripheral aureole of recrystallized rocks around an intrusion of an igneous body due to the heat flux between the intrusion and the box rock.

You can read several examples quoting both terms as synonyms:

The Wikipedia article on metamorphic types includes a section heading of

  "Contact (thermal)"

And another example is frontiersin.org where the subject regularly interchanges the terms to prevent monotony in the writing.


If rocks are stones, what type of rock are gallstones?

The nature of this question is more about biological chemistry than it is about earth science. This is because gall stones have nothing to do with geology, but chemical processes in the body.

Consequently, it would be inappropriate to apply geological classifications, such as igneous, sedimentary or metamorphic, to gall stones.

Due to the way gall stones are formed - layers of bile coating a nucleus - they could be describes as being concretions.


How to interpret seismic interferometry data?

It is a differential InSAR image that shows wrapped phase in radians which is a measure of the change in range (or distance) between the ground surface and a (more or less) fixed point in space from which the radar images were acquired (keep in mind that two SAR images are required to create an interferogram). To get the actual range change you have to unwrap the interferogram.

You can think of the fringes as contour lines. Areas where spacing between the fringes is tight, represent areas with high deformation, e.g., near the fault. The wavelength of the radar determines the fringe spacing.

A better looking interferogram for the Nepal earthquake is at http://topex.ucsd.edu/nepal/ (made using SAR data acquired by the L-band ALOS-2 satellite operated by the Japanese Space Agency, JAXA).


Why are most peninsulas oriented north-south?

Starting from the bottom of your question I would not compare planets with plate tectonics with planets that don't have this process. During rifting of a tectonic plate a triple junction will be the most favourable way of faulting the crust. After that two arms of the rift are favoured and the third one becomes a failed rift (aulacogen). Because of this process linear features on a planet will be very emphasized.

The current geometry of mid ocean ridges and subduction zones does fall into a strong north-south pattern (Exceptions are Antarctica and the Aleutian trench). This might also be due to the fact that the plates form a system that in all its complexity still strives for lower stress and effective heat transport. In this case a parallel system of mid-ocean-ridges and subduction zones might be more favourable than a totally random alignment of those features.

The dynamics of the inner Earth are of course not independent of the plates and it is difficult to assign causality. Nonetheless you could again think of a complex system that seeks for efficiency (pragmatism if you will). With subduction plates being plate-shaped, circulation above and beneath them will probably be more stable in a cylindrical fashion. So the heat distribution on the upwelling side of the circulation should also create linear features. In any case we just happen to live in a time where the system went for a North-South oriented minimum.

Continuing this thought process we can also find an explanation why features in this tectonic-north-south part of the world are oriented in this way. Many north-south striking islands have north-south striking back-arc-basins that separate them from their main land masses. And peninsulas are sometimes the arms of failed rifts or the tapering of back-arc-basins. Outside of this prevalent orientation we see features like Nowaja Semlja with very different orientations.

But be cautious with this theory. Assigning each feature on Earth to a north-south and east-west orientation gives you a 50 % chance that a randomly aligned feature will confirm your theory. Even four directions still give you 25 % chance. So the more directions you consider the harder it is to prove the theory. I am not aware of anybody doing a global peninsula inventory, so it would be interesting to see this.


Where on Earth is the most windless lake with its own micro climate sea breeze?

Wind Vortex on a Lake: the only thing I can visualize is a Tornado on a Lake.

Examples: Pine Lake tornado, Lake of the prairies Tornado

Technically speaking, a breeze/wind cannot be contained within a Lake, unless the lake is covered by mountain-cliffs or canyons at all sides. Maybe something like Marietas Island's hidden beach or Melissani Cave, but much larger would sustain a self contained breeze.


Why does Earth have abundant oxygen in the atmosphere?

This is only a partial answer as it doesn't explain why the excess of O2 stayed but one thing you have to appreciate is the fact that aerobic respiration appeared almost half a billion years after photosynthesis, so we can't really say that photosynthesis and respiration have always balanced each other.

Cyanobacteria (and with them photosynthesis) are believed to have appeared somewhen between 3 and 2.5Ga (e. g. Altermann & Kazmierczak 2003, Brocks et al. 2003) while Mitochondria (and with them aerobic respiration) are thought to have evolved somewhen between 2 and 1.5Ga (see e. g. Hedges et al. 2004).

There was therefore at least half a billion year during which cyanobacteria were producing O2 with no one able to breathe it.


Why is helium only found in wells mixed with natural gas?

Helium is produced by the radioactive decay of primordial uranium and thorium. It should not be strongly associated with non-primordial 'fossil' hydrocarbons.

The first statement is correct. The second is not. There are several reasons that helium should be strongly associated with non-primordial hydrocarbons. Both are fluids found predominately in the crust due to the highly lithophilic nature of uranium and thorium in the case of helium and the fossil origin in the case of hydrocarbons. Being a gas, helium is somewhat soluble in hydrocarbons. Like most gases, helium solubility in hydrocarbons increases with pressure. Unlike many gases, helium solubility in hydrocarbons increases with temperature.

Trapped hydrocarbons thusly act as a trap for helium. In places where hydrocarbons aren't present, helium might be trapped by some capping rock, or it might escape through the tiniest of pores. As the smallest gas (even molecular hydrogen is larger), helium is wont to find a way to escape to the surface -- unless temporarily trapped by a trapped liquid.


Can I interpolate rainfall data from stations outside of watershed for the watershed?

Yes, you can interpolate the rainfall from stations outside the watershed. However, the quality of the interpolation will depend on the distance between the stations and the watershed, the prevailing weather patterns, and to some extent the topography.

For example, it probably wouldn't be appropriate to use a station on the rainy side of a mountain divide in estimating rainfall in the rainshadow. One way to get an idea on how good you estimates are is to compare the actual rainfall at a station with the interpolated rainfall at that location, when you leave it out of the dataset.


Are there any DIY conductivity sensors that will hold calibration for long periods? {multiple months}

I've built DIY conductivity probes for subglacial measurements. Unfortunately my sensors remain under ~100m of ice so I haven't be able to recover them to check the calibration, but for the same reason, I've taken multiple measurements to reduce calibration drift, as I'm unable to re-calibrate them. So far, they have produced sensible data for 2+ years, but I haven't check the calibration. However I can share the results of my tests and research in order to produce a stable sensor.

There are two main types of conductivity measurements: The first one is the potentiometric method. This is the most common one, and measures conductivity by creating an electric current between two or more electrodes embedded in the medium to measure. The second type is the inductive method, in which is a magnetic field what goes trough the medium, and you measure conductivity through variations in the induction effect that that magnetic field have in a coil.

(picture  taken from Knight)

Inductive probes are contactless, therefore, the most stable ones. However, they are more complex to build and don't work well with very low conductivity (< 100 uS/cm). Glacier water is often in that very low conductivity range, something that, in addition to the higher complexity made me choose the potentiometric method (you can see a bit of my attempts to put together an induction sensor in this forum).

For potentiometric probes, oxidation, deposition of salts or others chemicals can change the calibration parameters. This would be enhanced when direct current is used, as that will create acids in the water that will quickly corrode the probe. To reduce that problem, probes of inert materials are used, like platinum, gold or graphite (more common in DIY projects due to its lower cost). But to reduce deposition of chemical compounds in the probes you still need to avoid direct currents and use high-frequency alternating currents with zero mean, otherwise if there is a net current towards one electrode, you will accumulate acids or ions there that can degrade or coat the electrode and change its properties (i.e. change the calibration).

The picture above shows an example of an electric signal that can be generated using a false ground and the PWM output of an Arduino board. The setup could be as follows:

Where R1 and R2 have in general to be equal to ensure a signal with zero mean, and the value have to be chosen depending of the range of conductivity values you want to measure and the resolution. If you want to cover  a wide range (pure cave water to marine water), you will have very low resolution (un less you use a AD converter with more resolution than the 10-bits provided by Arduino boards). Alternatively you can have multiple sensors each one optimized for a different range.

For probes meant to be deployed outside of lab conditions, concentric electrodes are recommended, otherwise natural currents going trough the ground/water can affect the measurements. The setup I used is this one:

Where a central graphite electrode is surrounded by a ring of graphite electrodes. As  you can't solder to graphite, I used conductive epoxy to glue it to a piece of plumbing copper tube modified with legs so it can be solder to a PCB. It looks like this:

To avoid gluing, some people choose aluminium or stainless steel electrodes, that are affordable and do not suffer much of chemical corrosion.

Some of the data that was produced by this probes were used for this publication.

Many comercial setups use three or four electrodes. I don't understand all the advantages of those sensors. In some cases they are just multiple sensors each one calibrated  for a specific range.
I've also seen three concentric electrodes. I haven't do the math, but my suspicion is that they measure the current in two independent electrodes with different surface area. Then, you can model and calculate the resistivity of the layer of deposits/corrosion that covers the electrodes and compensate your reading accordingly, reducing the calibration drift issues.


What causes these mound-like ground formations?

They're landslide deposits; Mam Tor gets its name, which translates as "mother hill", from the regular landslides that come off the higher slopes and form hillocks further down into the valley.


Why do tectonic plates have a tendency to drift closer to the equator?

I'm not a tectonicist or a science historian, but as far as I know the ‘pole flight force’ or Polfluchtkraft was introduced by Wegener in his theory of continental drift. Essentially it's just the application of centrifugal force to continents (or, if we are now considering it within the plate tectonic paradigm, to plates). As stated in the Wikipedia article you link to, this force is far too weak to account for plate motions, and this very fact was one of the reasons for the scientific community's rejection of continental drift. Modern tectonics doesn't seem to consider it even as a measurable contributing factor. The only modern references I've found to it have been in historical contexts, such as in Krause (2007). The subtitle of this paper, ‘Vergessene Begriffe der Geologiegeschichte’, translates to ‘forgotten concepts of geological history’, and as far as I can tell this is an accurate summary of Polflucht's current status.

Krause, R.A., 2007. Die Polfluchtkraft: Der LELY-Versuch
– Vergessene Begriffe der Geologiegeschichte. Polarforschung 76 (3), 133–140. DOI: 10013/epic.29962


How does humidity vary with height in the Earth's atmosphere?

Humidity strongly varies as a function of time and space, which is why standard atmospheres like CIRA may choose to omit it at all.  It simply doesn't make sense to include an “average” humidity profile, because such an average is not meaningful.

However, there are other sources for relative humidity profiles.  You can obtain them from reanalysis data.  If you want probabilities, you could calculate them from reanalysis.  I have not used probabilities, but I have used profiles from Anderson et al. (1986) in the past:

Anderson, G. P., S. A. Clough, F. X. Kneizys, J. H. Chetwynd, and E. P. Shettle (1986), AFGL atmospheric constituent profiles (0–120 km), AFGL, TR-86-0110.

Anderson transcribes them in his paper, which is in PDF and not ideal to read.  The same data are distributed along with the Atmospheric Radiative Transfer Simulator (see also Wikipedia article).  This radiative transfer model comes with a set of XML files, that includes profiles from both CIRA and from Anderson et al.  Those are not probabilities but “typical” H₂O profiles for five scenarios: tropical, mid-latitude summer, mid-latitude winter, sub-arctic summer, and sub-arctic winter.  For example, a mid-latitude summer H₂O profile can be found at this link.  The data are in XML so should be easy to read, but they also provide reading routines for Matlab and Python.  The unit is volume mixing ratio, which may actually be more suitable than relative humidity if you are interested in calculating air density.


Can climate change cause earthquakes, tsunamis, or volcanic eruptions?

A quote from the summary of the book you listed:

  feeding torrents of freshwater into ocean basins that rapidly filled
  to present levels. The removal of the enormous weight of ice at high
  latitudes caused the crust to bounce back triggering earthquakes in
  Europe and North America and provoking an unprecedented volcanic
  outburst in Iceland. A giant submarine landslide off the coast of
  Norway sent a tsunami crashing onto the Scottish coast while around
  the margins of the continents the massive load exerted on the crust by
  soaring sea levels encouraged a widespread seismic and volcanic
  rejoinder.

Could not access the other links.  This is clearly bordering on pseudoscience.  I admit I have not read the book but the summary makes it sound like junk science.  As a scientist I am skeptical and all of this seems like a stretch. I sure would like to know how crustal rebound (isotasy) affects a volcanic hot spot in the middle of the ocean.  The hot spot is most likely generated at the core-mantle boundary where convective cells in the core meet the mantle and melt it. The whole scenario sounds like a bad movie. Is there anything that someone will not blame on global warming? And how would we ever know that a landslide in Norway was due to crustal rebound/global warming?

But the author is disingenuous.  Even if he is correct, he implies that the changing climate in the past and any potential events associated with that changing climate might be related to changing climate today.   But climate change of the recent past has been due to the earth cycles set out by Milankovich and not to man-made global warming.  How can the two be compared when in the past we had a 6 degree change and now we are looking at only about a 1 degree change up until now.  Sounds like he is desperate to sell his book and hypotheses.


Why do those glaciers form on the lee side of the mountains?

The key is with wind-drifting. The predominant westerlies cause snow to drift into protected places. We should perhaps recall that glaciers exist because they are essentially snow-catchers in a landscape that is sufficiently suitable for some of the snow to survive the summer melt period. The drifting and depositing of snow on the eastern side of mountains thus favours formation of glaciers in such locations. If you take a trip using Google Earth into the Swedish mountains to the East of the area you describe you will see that glaciers are also in north and south-trending valleys where of course they catch snow for the same reason. In this case it is the larger scale geomorphology that dictates the location and direction of glaciers. The latter implies that a glacier is not just formed in the lee direction of the predominant wind direction but also requires a suitable landscape geomorphology which affects the location of where the glacier forms.


Can someone help me identify this crystal

It looks like Tourmaline which can be a lot of different colours but green-black is, I believe, the most common.


What separates the Karakoram Range, the Hindu Kush, and the Himalayan Range?

The River Indus in Jammu and Kashmir of India and Gilgit-Baltistan under Pakistan control is usually taken as the dividing line between Himalayas and Karakoram.

The River Gilgit, a tributary of the Indus flowing from the North-west has its confluence with the Indus from the North-East near the town of Juglot or Jaglot about 45 km south east of Gilgit on the Karakoram Highway in Gilgit District and then the Indus flows south from here.

The confluence between these rivers is known as "Tri Junction Point" or "Junction Point of Three Mountain Ranges". It is located at the junction of the 3 lofty mountain ranges, the Karakoram, Himalayas and Hindukush.

To the North of this confluence or to the north of both Indus and Gilgit rivers is Karakoram.
To the south  of the Indus before merger and to the East after merger are the Himalayas
To the south of Gilgit river and West of the merged Indus is Hindukush.

In the Ladakh district of India, there is an east west range called the Ladakh range to the north of Indus, and sometimes this is taken as an extension of Karakorams. Beyond or to the north of Ladakh Range is the Shyok River, a tributary of Indus that flows westwards and joins the Indus near Skardu, and more commonly the mountains to the north of Shyok are called Karakoram range.


Can garbage be sent into the (near-)center of the world?

No. In fact, I don't know why David Hammen didn't say that instead of commenting.
The deepest hole that mankind ever dug was barely a scratch on the Earth's surface when you look at its size. They didn't even reach the mantle. The hole is only 12km deep, took about 20 years to create, and is still only 1/3 of the way to the mantle! Also, the hole is nothing through which you could dump garbage. It's only NINE inches in diameter.
Have you wondered what it means to dump trash into the Earth? Trash takes up space. There are no known voids in the deep Earth. It is very dense. To make room for trash, first you would have to dig the IMMENSELY expensive hole. Doing this also wastes energy. Then, you would need to invent technology to dig out a massive space, working from inside a nine-inch hole that goes over 7 miles into the Earth's surface. How expensive would that be? Is it even possible to carve out a space in the Earth under that much pressure without it collapsing? Given that scientists have only managed to keep open a nine-inch hole, you can bet we currently don't have available technology to build any kind of void for trash, let alone a void big enough to hold enough trash to make more room on the surface.


Why does the meridional overturning circulation take the convoluted path that it takes?

The diagram presented in the question is a very simplified version of the meridional overturning circulation. It is overly simplistic and generally creates very large misunderstandings.

A good reference to the evolution of the Meridional Overturning Circulation diagrams is the work by Richardson (2008). Just in case you don't have access to Progress in Oceanography, you can click here and see if that works.

The diagram that I find more useful and, while a simplification, still rather realistic is the one by Schmitz (1996).

Now let's answer the question about the "weird loop". We need to realize that, in the diagram presented, the blue arrows represent flow of deep water (denser water, usually colder), while the red arrows represent surface water flow (lighter water, usually warmer). The loops in the Pacific and Indian ocean represent a transition from cold water into warmer water usually through mixing. The exact location of the mixing and upward vertical flow (upwelling) does not occur in the areas represented by the loop in the diagram, but rather in several other locations in the Pacific and Indian Ocean (for instance, upwelling in the California Current System, mixing in the Indonesian Throughflow).


Is there a correlation between hot springs and earthquakes?

Yes, there is a correlation.

In other words: places with hot springs are more likely to experience earthquakes than places without hot springs. The relationship is scale-dependent in time and space (your house might not sit on a hot spring but still get earthquakes).

Ideally I'd dig around and find actual data to quantify this spatial correlation (and I hope someone does!), but for now I will settle for qualitative evidence at the continental scale. I offer a visual correlation between the two datasets in question. First, geothermal springs:

Now earthquakes:

Like any correlation in geoscience, it's not perfect. But, broadly speaking, there is one.

Footnote: Actually, there are at least two correlations. As with fracking for shale gas, well stimulations and other industrial activity in geothermal fields has recently been blamed for induced seismicity in places like the Imperial Valley of southern California. Sometimes correlation does imply causation!