First, read my highly related answers to your other questions:

https://chemistry.stackexchange.com/q/67403/8083

https://chemistry.stackexchange.com/q/72483/8083

  The forsterite might make decent clear glass

Probably not, see above.

  fayalite can be processed with hydrogen to get iron, water, and silica, and the silica can be used to make glass

Again, probably not. To make the fayalite component react fully in reasonable time you are going to need to mill the olivine to very fine dust. Then, separating the silica from this fine dust in solid form is almost impossible. This will require heavy liquids (like polytungstate) which are not available on the moon. Doing this in liquid form and centrifuging will require heating, which will inevitable cause reaction of forsterite and silica to form enstatite: $\ce{SiO2 + Mg2SiO4 = 2MgSiO3}$, which is useless for glass making.

  Is a controlled fractional crystallization process feasible on the Moon?

Basically yes. This would be similar to a distillation process that slowly over repeated melting and solidification processes will remove Mg-rich solid from Fe-rich liquid. The problem is that even very low amounts (1% and lower) of Fe in forsterite will colour it green, which is undesirable for your glass. And that's without even considering the forsterite is not a good glass material (see links above). Seperating the Mg out will become harder and harder as you go along in your process.

Good glass material has alkalis in it. Fortunately, some lunar rocks have Na and K in them (e.g. the KREEP basalts). It has about 1 % of potassium, which could be enriched in fractional crystallisation. The problem is that you will also enrich the glass in Th, making it slightly radioactive and possibly browning with time.


The differences in gases produced by asteroids impacting crystalline and sedimentary rocks

A New Scientist article (with a somewhat amusing title) Fracking Hell investigates this exact question in some detail.  The difference is made by an analogue to the process of fracking.

Instead of the water use in human-engineered process of fracking breaking the underlying rocks up to release the methane for commercial purposes. The considerably larger impact of an asteroid does the same thing in a massively uncontrolled manner - in sedimentary rocks, it pulverises the sedimentary rock, releasing the gases that were trapped in it, such as sulphur from evaporites in the vicinity of the Chixculub impact; other gases can include hydrocarbons, halocarbons (salt + hydrocarbons), chlorine to name a few.

The amount of gases released from within the sedimentary rocks were enough to cause mass extinctions (in an essentially extraterrestrial version of what is believed to have occurred during the Siberian Traps event).

In crystalline rocks (such as igneous and metamorphic rocks), according to the article, the rocks are far more stable and do not release such amounts of climate changing gases than sedimentary strata in an impact event.  Although these rocks can contain gas bubbles etc, they have been found to relatively 'inert; in terms of gaseous release compared to sedimentary rocks, such as the 100km diameter Manicouagan crater in Canada, an event not associated with a mass extinction.

Essentially, the impacts can be devastating for either scenario, but the impact itself is not the only cause of mass extinctions, it appears that a large factor of the mass extinctions is due to the climatic change that results from the released gases uncontrollably 'fracked' out of the sedimentary rocks. Of course, if an impact is large enough, it could pulverise several layer of rock unlocking deep pockets of gases.


A good book or source for climate science and meteorology basics?

Cambridge University Earth Sciences Department's reading list particularly suggests:

Pierrehumbert, R.T. (2012), Principles of Planetary Climate. Cambridge University Press, Cambridge UK, ISBN:9780521865562.
IPPC assessment reports
Cronin, T.M., 2010. Paleoclimates: Understanding Climate Change Past and Present. Columbia University Press, ISBN 978-0-231-14494-0

... plus many others, with a range of focuses, all of which are made explicit.

Other books include:

Physics of the Climate System, Peixoto and Oort
An introduction to dynamic meteorology, James Holton


coriolis force in atmospheric/ocean modeling

Here are your choices with regard to modeling the atmosphere. There aren't many, and only one of them makes sense.

Model the atmosphere from the perspective of an inertial frame of reference.
Good luck with that! As an advisor told me decades ago, "Name one!" It's certainly not an Earth-centered frame; the Earth is orbiting the Sun. It's certainly not Sun-centered frame; the Sun is orbiting Jupiter, Saturn, Uranus, and Neptune. It's certainly not the solar system barycenter (center of mass); the solar system is orbiting the Milky Way. The Milky Way barycenter? Nope. The Milky Way and the Andromeda galaxy are accelerating toward one another. No matter how far afield we look, we see gravity (and even further afield, metric expansion of space) that hides this inertial frame from us.
Use a non-rotating frame centered at the solar system barycenter.
The International Celestial Reference Frame is one such frame. This is more or less a constructible frame. Here we either ignore or account for the acceleration toward the center of the Milky Way, the Andromeda galaxy, and stuff further afield. It does makes sense to ignore those extraneous accelerations; they are very, very tiny, and the variation across the solar system is tinier yet. There's another issue with any such construction. The ICRF almost certainly is rotating. The predecessor of the ICRF, the J2000 frame: Scientists now know it was rotating. The same goes for the predecessor of the J2000 frame, the B1950 frame. In fact, scientists know the ICRF is rotating. The ICRF has been upgraded to ICRF version 2.0. And that too is rotating. Scientists just don't know how much.
Use a non-rotating frame centered at the Earth's center of mass (aka Earth-centered inertial).
Even if the ICRF was perfect, there is no way one can reasonably model the Earth's atmosphere in a computer program from the perspective of such a frame. The length and velocity scales needed to properly model the atmosphere and the length and velocity scales using a solar system barycenter frame just don't match. Oil and water. Even worse, it's a Sesame Street moment! ("One of these things is not like the others, One of these things just doesn't belong.")
The thing that doesn't belong is the solar system barycenter. The only reasonable way to model the Earth's atmosphere is to use an Earth-centered perspective. Now a computer program is starting to have a chance to represent the atmosphere, and do so in a way that is computationally feasible. An Earth-centered frame is accelerating, but we can handle that. We can pretend that $\vec F=m \vec a$ still applies. This result in fictitious tidal accelerations. It's not a problem. Physics still works.
Use an Earth-centered, Earth-fixed reference frame.
A problem remains with the Earth-centered inertial frame described in option #3. The Earth, the atmosphere, and the oceans are rotating, and at different rates. This means that "starting to have a chance" was a bit overoptimistic. It makes much, much more sense to use a frame that rotates with the Earth. This adds even more fictitious forces, the centrifugal and Coriolis forces, but once again, that's not a problem. In fact, this simplifies things to the point where meteorologists do finally have a chance to represent the atmosphere in a way that is computationally feasible.

Option #4, the one that requires fictitious third body forces (aka tidal forces), fictitious centrifugal forces, and fictitious Coriolis forces, is the only option that makes a bit of sense from the perspective of modeling the atmosphere.


What causes the "ripples" that extend east-west along the mid-atlantic ridge?

These are transform faults that result from differential spreading rates of the middle ocean ridge. As such they are part of the plate boundary. Possible causes are different production rates of magma, thermal differences of the sea floor, differences of relative plate movement.

https://en.wikipedia.org/wiki/Transform_fault

https://en.wikipedia.org/wiki/Mid-ocean_ridge

Paywalled:
Dynamical Instability Produces Transform Faults at Mid-Ocean Ridges

And:
Wilson, 1965: A New Class of Faults and their Bearing on Continental Drift

Inactive transform faults extending beyond the spreading zone are sometimes generally named "fracture zone".

But transform faults can also reach all the way to the next subduction zone (e.g. Azores-Gibraltar fault zone) and be responsible for devastating earthquakes.


A few thoughts - assuming like you say that the aqua-planet is the same size as earth, and all else being equal, it's best to consider the two major classes of waves:

Nondispersive wind generated waves: Here the maximum wave height is a function of wind speed (fetch). However, wind speed in general is not a function of wave height (unless you invoke concepts like walker-circulation from ENSO, but you wouldn't get ENSO since there are no continental boundaries).

The relationship between maximum wave height and fetch in deep water, can be described empirically as $$H_{max}=0.332 \sqrt{F}$$

So this all goes to say that it is impossible to determine $H_{max}$ without knowing something about the atmosphere dynamics. If you assume that the atmospheric dynamics are the same as on earth (in terms of storm statistics), then this little empirical relation would suggest wind generated wave heights should be no different for an equally sized aqua-planet. Larger planets do however have larger storms...

Eddies and planetary waves Eddies are waves, yet quite different from wind generated waves. While they certainly don't reach the impressive heights of wind-generated waves, their wavelengths are several orders of magnitude larger. And so technically, you could say they are in fact "bigger" waves. Along with eddies, there planetary waves such as Rossby waves and Kelvin waves. All these eddies and planetary waves are limited in size by the Rossby radius of deformation. Which is to say, their maximum size is effectively limited by the curvature of the earth.

Upshot To get larger wind generated waves, you need larger storms. Therefore you need a larger planet (e.g. great red spot on jupiter). To get larger planetary waves and eddies, you also need a larger planet! The reason that larger planets have both larger storms and larger planetary wave/eddies is the same ~ which is that the rossby radius is bigger for a bigger planet.

You might be interested to check out something called the "aqua planet experiment" project. These are general circulation models run on a hypothetical planet with no continent, they're all just atmosphere and ocean. The image below is cloud cover output from an aqua-planet simulation.


"Sand" is generally made up of whatever eroded rock type is nearby, minus the most easily eroded (and windswept) components. Typically, dunes are made up of highly resistant quartz grains, like the stuff that blows off of white sand beaches, for example, or feldspar sands which are even more erosion resistant (in certain cases). There are also very soft white gypsum sands in New Mexico who owe their existence to a nearby, inexhaustible supply of gypsum evaporites.

As for limestone sands, I've never heard of it although it's certainly possible given very specific circumstances. Nevertheless, that's not what controls dune morphology. Dune shape is almost entirely controlled by both wind and sand supply and similarly shaped dunes will occur regardless of grain composition if dune-forming components are the same.


This question is very similar to: Why does the "Ring of Fire" pretty much define "Pacific Rim"

The high levels of volcanoes and earthquakes are primarily due to subduction. So why is the Pacific surrounded by subduction zones?

Think back to Pangaea. This was a supercontinent that formed in the late Palaeozoic. Virtually all of the Earth's land masses were concentrated in one large supercontinent. When this broke up, the new continents moved away from each other. Fast forward 200Ma or so, and you find that the continents have moved so far apart that they are now converging on a point on the other side of the planet - the continents are moving towards each other! Hence the remains of the super ocean (which was actually multiple ocean plates - today's Pacific & Nazca plates, plus the Farrallon plate (RIP),etc ) is shrinking as the continental plates move towards it. This destruction of the ocean plate(s) occurs at subduction zones.

This is a big picture generalisation. Not all of the Pacific's boundaries are marked with subduction zones (e.g. North America has two large strike slip systems + a new spreading ridge). Also, not all of the continents are converging on each other. Africa is doing a pirouette, India is moving northwards, etc.


What causes variation of seabed depth relative to fixed chart datum?

Your question is actually a three-part question in disguise, of which I cannot answer all parts, but let me tell you what I do know.

Part 1: What causes variations in vertical position within the context of the refered sentence?

If you read that section more carefully it is not so much variation of the seabed depth, but variation in the measurement of the seabed depth. Using known fixed structures on the seabed they found out that different runs give a different vertical position of these structures. Let me expand your quote:

  [...] Repeated sampling of stable immobile seabed structures (fishing drag-board traces, ship wrecks) indicates that the reconstructed overall vertical position with respect to a fixed chart datum may vary by more than 10 cm from survey to survey. The causes of this variation have not been resolved yet. Hence, without a vertical reference present within the surveyed area overall variations in the seabed of less than 20 cm cannot be derived unambiguously over periods longer than several months. In contrast, using a fixed seabed structure as vertical reference the precision of multibeam data can be less then half a meter in the horizontal and one centimetre in the vertical [...]

This means that in situations without stable vertical references measurements at different times cannot be compared easily, and simply subtracting the bed heights would not necessarily give the change in bed height over the elapsed time.

However, when there are stable structures, such as a ship's wreck, you can use the difference in the measurements of the vertical position of that structure to correct measurements of the entire seabed, giving a much better vertical precision.

Part 2: What causes variations in the measurements between measurement runs?

The section referenced mentions that the exact causes of the different measurements have not been resolved. Most likely it is a combination of inaccuracies of the used instruments, on which I'm definitely not an expert, and I'm not even sure this is the right Stack Exchange to ask that question.

Part 3: What causes true variations in the absolute seabed height?

This is an entire field of research on its own, called coastal morphodynamics, which is too broad to be answered in a single Stack Exchange answer. Without a specific question you wouldn't get a more sensible answer than it a depends on the seabed composition and water flow.


Error trying to download ERA5 data: Exception: Missing/incomplete configuration file: C:\Users\username/.cdsapirc

I had the same problem but have just found the solution after an hour or so of trawling through forums! The problem was that the code 'api.py' could not find the '.cdsapirc' file. The file type has to actually be 'CDSAPIRC' and not a 'txt' file. The icon for the file will then be displayed in your folder as blank and the name will be '.cdsapirc'. I found the solution on here: https://www.wikihow.com/Create-and-Delete-Files-and-Directories-from-Windows-Command-Prompt. I created the file using the following steps:

Navigate to 'C:\Users\username' (or you can just move it later).
In Command Prompt, write 'type nul > .cdsapirc' and press Enter.
Right-click the file and press 'Edit with Notepad++' (probably works with other programs).
Paste the text that you already mentioned (key, etc).
Save and close the document.

Hope that works :)


If the Sun disappeared, how long would it take for the Earth to freeze beyond excavatable depths?

Step wise approach:

Right now when the surface is very cold, the frost depth here (Alberta, -40 min winter temps) can reach 8 feet.  Below about 30 feet seasonal temperature changes are under a degree.

Around depths of 100 feet temperatures start to rise, increasing about 25C/km or 1F/70 feet.

First approximation then for zero solar input (effective temp -270K) would be that you would need (270+20)/25 = ~12 km of depth to have roughly room temperature conditions.

We currently can't dig holes that deep.

The world's deepest is 3.9 km in South Africa.  Note that at 25C/km the temperature at that depth is well over boiling point.  Air is compressed at the surface, then chilled.  Air expansion in the working levels of the mine expands and cools further.

This assumes that the earth's insulation value is linear with depth.

Now:  Time: We can put a lower bound on it:

A year's temperature variation right now reaches 30 feet, with most of that being in a fraction of that.  So suppose that it penetrates at 30 feet per year.  I think this is too much, but it serves as a bound.  At 30 feet per year it would take 33 years per thousand feet, or about 110 years per kilometer. At present depts of 3.9 km, we have about 4 centuries.

In practice you wouldn't do it like this.  Go deep enough to get away from the worst, built an insulated cave, and run heat exchange tubing deeper to heat your cozy refuge until whoever borrowed the sun puts it back.


Stratigraphy of limestone applied to the Great Pyramid of Giza

Theoretically? Maybe! Practically? No. Identifying the general quarry site by comparing lithology is often possible. It might be possible to identify a block as coming from a particular level in a quarry by detailed characterisation of micro-fossil assemblages. Geochemical analyses could assist. However the practical problems are almost certainly insurmountable:

The limestone rocks used in the pyramids were deposited in a marine reef environment, so deposition rates could be quite high. This means that with small age differences between the top and bottom there may be negligible variation in the micro-fossils.
The parts of the quarry from which rock was taken are, by definition, not there to be sampled. You would have to take your comparison core from the edge of the quarry and you would presumably be looking at the stratigraphy of the layer on the outside of the pyramid which may have come from the centre of the quarry. Reef limestones can change their characteristics significantly over short distances.
The exposed limestone blocks will have been altered by weathering - so would probably need destructive sampling by coring to gather material for comparison.
As an analogy, matching individual blocks to layers in a quarry would be like trying to match sawn wood to individual tree stumps in a forest. Conceptually possible, but would take an awful lot of work and even more luck.


Agricultural non point source of pollution (AGNPS) model input data

tldr;

On the official support page titled AGNPS Climate Data -- agGEM & preGEM you find a download link to a climate data template file. Your data files need to have this format. All meteorological variables are written into this file. The template file contains daily data. It is not clear if either the data has to have daily resolution or the data can be finer (hourly) or coarser (monthly) resolved.

detailed answer

Everything I write down below is described on one the official support pages for AGPNS: http://go.usa.gov/KL0 (This is the official short link provided by the United States Department of Agriculture (USDA))

Remarks

The meteorological input data files for AGNPS model (Agricultural non-point Source Pollution Model) are actually called climate input data, although the files contain short term meteorological data.
All the provided programs are Windows executables.

generate climate input data files for known locations

Use the program agGEM. This program uses an existing statistical parameter file (maybe: == climatological data?) of meteorological data to generate a climate input data file for AGNPS. There are 233 stations in the US, for which such statistical parameter files exist. There is no information on the support page whether the data are measurement or model data. The program can be downloaded without registration from the support page linked above. The existing statistical parameter files can be also downloaded on that page.

generate your own statistical parameter file

The USDA provides a program called preGEM to generated statistical parameter files. preGEM needs an input data file with a long time series of meteorological data. What long means is to decide by the use.

The format of this particular input data file is not clear. According to the agGEM & preGEM documentation file one can choose between two types of text files: csv and fixed format (see the manual what the latter means) during the execution of preGEMs. However, a preGEM input template is provided on the support page, which is a xls file. Maybe one can also choose xls as format for the input data file.

Please be aware that there are a lot of options when you save a xls as csv via the spreadsheet software of your choice: delimiters for strings, delimiter between columns (comma, tab, semicolon, ...) etc.

Build your own climate input data file

There is a climate input data template provided on the given support page. You can generate your own file without using arGEM and preGEM. There is a file header which nicely describes how the file has to be structured. The file looks as follows:

*************************************************
*** a few words of explanation:
*** The Climate input data for AGNPS has the following fixed format.
*** The first line is required and must contain the current version ID
*** The second line may contain any info the user wishes.
***
*** The third line contains site latitude, longitude, elevation,
*** temperature lapse rate with elevation,
*** percentage N in the precip, and unit code.
*** The temperature lapse rate units are degrees F per foot or degrees C
*** per meter of elevation and can be left at zero.
*** The nitrogen percentage in the precip is currently not used in the
*** program, but units are percentage by weight.
*** The unit code is 1 for English and 0 for metric.
***
*** The fourth line contains the start date for the data.
*** The fifth line contains the end date for the data.
***
*** The sixth through eighth lines contain data column headings
***
******* climate file starts below this line:
Climate File Input Version ID:          5.00
   56  Princeville
   22.0708  159.1234    345.00   -0.0036    0.0000         1
01/01/0001
12/31/0100
     Daily   -Air Temperature-   Precip-     Dew        Sky      ----- Wind -----   Solar     Storm    Potent-
    Date     Maximum   Minimum   itation     Point     Cover     Speed  Direction Radiation  Type ID    ial ET
mm/dd/yyyy     [ºF]      [ºF]      [in]      [ºF]       [%]      [mph]       [º] [BTU/h/ft^2]    [-]      [in]
01/01/0001     73.08     67.10      0.00     59.46      75.4      3.67               87.30
01/02/0001     77.12     60.72      0.08     61.19      39.2      5.61              123.27
01/03/0001     78.22     58.41      0.28     60.80      80.9      3.85               79.23
01/04/0001     79.22     60.80      0.24     60.81      34.7      2.43              127.03
01/05/0001     80.62     69.15      1.84     67.06      79.8      6.96               79.44
01/06/0001     82.05     66.88      0.25     64.65      30.0      4.29              128.66
01/07/0001     80.89     62.94      0.07     60.28      52.7      3.59              114.29
01/08/0001     77.59     63.79      0.00     60.51      33.0      4.14              129.61
01/09/0001     75.78     61.29      0.00     57.00      53.0      3.69              115.94
01/10/0001     74.65     57.61      0.11     54.61      46.9      4.04              122.56
01/11/0001     78.17     60.47      0.52     61.41      38.5      5.44              126.81
01/12/0001     74.93     64.24      1.18     62.55      67.1      5.47               99.94
01/13/0001     74.97     62.35      0.63     66.70      84.6      3.82               73.72
******* This line and below are not in the input file.
*** In this template the data ends on 01/13/0001, but the actual file
*** must obviously continue to 12/31/0100 because of the specified
*** end date on line 5.


Comparing Pros and Cons of SWAT and HSPF

This is a broad question, the best way to compare the models is to go through the manuals and compare the process algorithms to see how the various hydrologic processes are handled. There are other considerations as well, including:

what environment/watershed are you modelling? How large, how urbanized, what type of soils/environment/precipitation vs evapotranspiration, how important are snow processes, etc., and compare that to what the models were made for
what is the purpose of your modelling? Your choice of model will be different if you are looking at water balance vs flood forecasting vs water quality estimates
what data do you have available? Some models are more intensive with data requirements than others, and if you only have daily precipitation and temperature (as is typical) than that will restrict some model types
what level of accuracy do you need? The timestep options in the models will make a difference

That being said, generally my understanding from a broad perspective is that:
- HSPF is a more detailed hydrologic model with larger data requirements for input forcings, and has also a more comprehensive process library with respect to water quality
- SWAT as you said was developed for agricultural regions, has less strict data requirements and also some ability to model water quality parameters (though less detailed than HSPF)

Depending on the purpose of your modelling, you may want to consider:

starting with a simpler model, such as GR4J, just to get the ball rolling before investing more time into complex models, particularly if just need simple answers from the model
using a flexible model where the processes can be modified on the fly and you are not committed to a particular set of algorithms when you choose the modelling framework, e.g. the Raven hydrologic modelling framework

Hope that helps!


What's the minimum number of days needed for reporting a "monthly average" of daily satellite retrievals?

Provide a monthly average in every grid cell, and describe how many measurements were used for each cell.

There is no fixed rule for the minimum number of days for reporting a monthly average.  A reasonable threshold will depend on the geophysical quantity of interest y, in particular on how much y varies on short and long timescales.

If y varies from month to month, but does not vary a lot from day to day (example: sea surface temperature), you can probably get away with reporting a monthly average even when only one or two days have cloud-free measurements.  On the other hand, if you're measuring precipitation, your signal will be relatively noisy even if you choose a threshold of 20 days.  And any threshold is going to introduce a bias, because a lack of observation is typically due to clouds.  Although you will get a bias in any case.  In other words, if you only have one day per month you see a gap and in the clouds to observe whatever you want to know, it is a pity to throw it away.  Therefore, personally I choose a minimum of 1 observation.

Critically important though: when releasing the product, add a field that tells the user how many days worth of measurements make up the monthly average in any given cell!  Like that, the user can decide which ones to use and which ones not to use.  More broadly speaking: producers should document everything they do.

For your specific examples: search for the ATBD and/or scientific papers describing the product.  Hopefully, there is a field in the level-3 product that describes the number of measurements per cell.  If the answer is not in there, write to the producers and tell them to redo the product...  You will need this information to accurately calculate a yearly average!


Is there a massive drop in quality of Cretaceous vs. Triassic dinosaur fossils?

No, there is no massive difference in fossil quality due to the extra 200 million years or so that the oldest dinosaur fossils have spent in the ground compared to the most recent ones at the end of the Cretaceous. Once fossils are properly fossilised, they remain unchanged unless something happens to the rocks. This could be weathering, which damages or destroys many valuable fossils, including recent ones like hominids, or it could be metamorphism, which damages or destroys them with heat.

I have seen a photo of a one-billion-year-old fossil from the late Precambrian of a marine algae reliably dated by the new Rhenium 187 - Osmium 187 method, and it was in an excellent state of preservation. Likewise with fossils preserved in amber, some of which are tens of millions of years old but look as fresh as if they had only died yesterday.


If you take a look at the atmospheric circulation pattern, the Hadley Cells in particular, they tell the story. The northern edge of Africa is on the descending edge of a Hadley Cell, which means

  Having lost most of its water vapor to condensation and precipitation
  in the upward branch of the Hadley cell circulation, the descending
  air is dry. As the air descends, low relative humidities are produced
  as the air is warmed adiabatically by compression from the overlying
  air, producing a region of higher pressure.

The main air mass being dry already, and the High pressure system generated by the descending air mass along the 30 degree lines work to make the physics required for precipitation just not want to happen in these regions. You have to get a combination of enough humidity to reach saturation, and then cool the air to reach its dew point.  The desert region formed by the lack of atmospheric moisture(remember Hadley cell) can't add any humidity of its own through evaporation or transpiration, so the global patterns dominate, even being right on the oceans edge.

Note that Hadley cell edges at the 30 degree south also cut through the Namib,Kalahari, and in South America the Atacama deserts, with their own ocean exposure.


How to calculate Lifted Index from ERA5 pressure level data?

Metpy 1.0 has a lifted_index function, which requires a profile temperature parameter, which in turn can be calculated using the parcel_profile function. That requires having the dew point temperature, which you would either have to have directly, or calculate from another moisture content variable. I'm not sure what your r variable is, so I'm not sure whether that could help you with such a calculation. Also, rather than using numpy arrays, using xarray for working with netcdf input variables tends to be easier and more efficient.


Does earth itself emit electromagnetic waves?

Yes, the earth emits electromagnetic radiation.

It emits infrared radiation with wavelengths of about 1 µm to 1 mm. This is heat, essentially, and much of it radiates into space:

Most if not all of the earth's rocks are radioactive (e.g. because of minerals containing isotopes in the uranium decay chain, such as potassium-40) and emit gamma radiation with wavelengths around $10^{-12}$ m. I'm not sure how much of this radiation would make it through the atmosphere.

You said you're not interested in atmospheric phenomena, but I wonder what the relative contributions of subsurface and atmosphere (e.g. the auroral kilometric radiation), as well as manmade sources, would be to the total signature. The planets emit radio waves (ask a radio astronomer), but I suspect most of that energy is from their atmospheres, since Jupiter and Saturn are especially bright. This book by Vázquez, Pallé and Montañés Rodríguez (2010; Springer) looks like it might address some of this, e.g. in Chapter 4.


How much does the weight of urban structures (buildings) affect the compaction (permeability, porosity, density) of alluvial sediments below a city?

This question might be more appropriate for the SE Engineering site.

The thing about soils is that they vary from place to place. Some are sandy, some contain more clay than others and the thicknesses of layers is also variable. All this influences how different soils react to surface loading stresses, such as from building foundations/footings.

Immediately below the footings the soils will experience the greatest stress increases. As discussed in this document, particularly from page 10 onwards, the magnitude of stress the soil experiences from footings decreases with depth - see the effect of a point load $Q$, applied to the surface, on the upper right of page 12. At a depth $z$, the vertical stress $\sigma_v$ has a certain higher value. At a depth of $2z$, the value of $\sigma_v$ is lower.

One reason why the affect of surface loads decreases with depth is due to the nature of soil particles and how they lie in relation to each other. Soil particles are not uniform in size or shape, so they rarely lie directly on top of each other. There are gaps between soil particles, called pores. The pores can hold ground water.

Compaction and consolidation of soils will reduce the volume (size) of pore spaces. Foundation loadings will only affect the soil beneath them.

Because soil particles do not lie directly on top of each other, one particle may lie above two or more particles, the stress exprienced by the upper soil particle will be transferred to the other particles. Providing the soil is deep enough, the affect of this is the to, over depth, transfer vertical stresses to horizontal stresses.

Ultimately, if a soil profile is deep enough, the stress the lower reaches of the soil experience due to urban development will be small and will not affect ground water movement.


What is the difference between climate change and global warming?

Is "Climate Change" a derived theory within "Global Warming", or vice versa?
  Is "Climate Change" a reiteration of an earlier theory, "Global Warming"?
  Are these terms in fact synonymous?

In order,

Vice versa.
No.
No.

"Climate change" (and its kin, "climatic change") is a far older term than is "global warming." The terms "climate change" / "climatic change" are and always have been the dominant terms used in the scientific literature (over "global warming"). Anthropogenic global warming is but one aspect of anthropogenic climate change, which in turn is but one aspect of climate science. In particular, increased global warming (above natural) is one of the climatic consequences of humans dumping very large amounts of greenhouse gases into the atmosphere.

Since climate change is the older concept, climate change cannot have derived from "global warming", and it is not a reiteration of an earlier theory.

Some references that show that "climate change" is an old term:

Ellsworth Huntington (1917), "Climatic change and agricultural exhaustion as elements in the fall of Rome," The Quarterly Journal of Economics (1917): 173-208.

Richard Joel Russell (1941), "Climatic change through the ages," Climate and Man, U.S. Department of Agriculture: 67.

Edmund Schulman (1956), "Dendroclimatic changes in semiarid America," University of Arizona Press, Tucson Arizona.

NASA - What's in a Name? Global Warming vs. Climate Change

Update
There was a lot of discussion on this topic. That discussion may eventually vanish. The question ended up asking for references, lots and lots of references. I do not have the time or the inclination to do that. What I can do is supply links to sites that do supply those references:

David Appell, "Some Early and Important Works on Climate Science, Carbon Dioxide, and Human Influence."

American Institute of Physics, "Bibliography by year: The Discovery of Global Warming."

Intergovernmental Panel on Climate Change, "Fifth Assessment Report."


Does the EPA have a list of the nation's major environmental issues?

The US EPA mandate is quite broad as are the range of environmental issues. The issues aren't really amenable to such a list because it is subjective to decide what is 'major' except in very broad terms. Major could mean greatest risk or it could mean of greatest importance to address soon. Those could be different things, for example, carbon dioxide emissions are high risk but difficult to address whereas an industrial site with leaky chemical drums might have only a local risk but need dealing with right away to contain the problem.

The 'Learn the issues' tab gives the important areas in a general sense; you could look at the EPA organisation chart to see where they are putting their resources.

For the specific case of pollution from old industries, The Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA or Superfund) maintains the National Priorities List (NPL) for sites needing cleanup.


In answer to the title question, "yes"!
Here are some videos from Montserrat Soufriere Hills where the phenomenon has been extensively studied (probably more than anywhere else):

http://www.geo.mtu.edu/volcanoes/west.indies/soufriere/govt/images/051296/

As well as Krakatoa, Mt Pelee's (Martinique) 1902 eruption managed to ignite ships in the harbour when the main town was destroyed - which suggests the pyroclastic flows crossed the harbour.

Also my u/g mapping area in North Wales included the Snowdon Volcanic Group. It and related tuffs appear to have been erupted over water and/or wet estuary type environments (there is open to debate).


Every time the rays of the sun come into contact with earth they have to first be reflected back to the ozone layer before returning to earth. This has a cooling effect on the earth temperature. Since the industrial revolution the ozone layer has been severely depleted by the greenhouse gas emissions. Remember the sun is a ball of burning gases, whose light reaches earth early morning within eight minutes. If the earth just moved an inch away in space from the position set approximately from the sun, earth could freeze and no living organism would survive. In the same regard if it moved an inch closer to the sun every life would be incinerated.


What are the distinguishing features of an "artificial seismic wave" (e.g. a large underground explosion)

Several things can indicate that a seismic event is an explosion and not an earthquake.

Firstly, the depth of the source. The shallowest earthquakes tend to have a hypocentre that is at least a couple of km below the ground surface and some earthquakes in certain parts of the world can go down to about 700 km. Artificial explosions on the other hand, will be very shallow, with a hypocentre that is essentially at the surface.

Secondly, and more importantly, the P-wave radiation pattern (and S-wave as well) for an explosion is fundamentally different to that of an earthquake. This can be investigated by plotting the polarities of the first arriving waves of a seismic event on a stereonet, with the position on the net being determined by the azimuth of the source from the receiving station and the outgoing angle of the wave from the source.

Earthquakes radiate P-waves in four lobes, with alternating polarities. This is called a double couple source and it produces a fault plane solution with two positive and two negative quadrants.

An explosion, radiates P-waves equally in all directions and so produces an isotropic pattern.

You may have seen reports of a second seismic event after the nuclear test which has been interpreted as a tunnel collapse. This also has a distinctive focal mechanism, called a compensated linear vector dipole (CLVD).

The photo shows directions of first motion at the source (a) (outwards = positive, inwards = negative), the P-wave radiation pattern (b), the steroplot of each focal mechanism (c).

These links give some further introduction to how stereonets are used to analyse earthquakes:

https://ocw.mit.edu/courses/earth-atmospheric-and-planetary-sciences/12-510-introduction-to-seismology-spring-2010/lecture-notes/lec18.pdf

http://www.ucl.ac.uk/EarthSci/people/lidunka/GEOL2014/Geophysics4%20-%20Seismic%20waves/Seismology/Earthquake%20Seismology2.htm

http://rses.anu.edu.au/~nick/teachdoc/lecture11.pdf


ppmV versus μmol/mol for atmospheric CO2 - how to convert?

According to the US Carbon Dioxide Information Analysis Center :
Though in their data table they use the term "ppmv", they explain:

The CO2 mixing ratios are reported as micromoles per mole (µmol/mol = ppmv) of dry air in the World Meteorological Organization (WMO) X85 mole fraction scale, traceable to primary standards at the Scripps Institution of Oceanography (SIO)

This is further explained in The WMO Mole Fraction Scales for CO2 and other greenhouse gases, and uncertainty of the atmospheric measurements:

Abbreviations can be ppm, ppb, etc., whereas widely used abbreviations such as ppmv (the v is for volume) are wrong and should be abandoned. When reviewing papers, or when we are co-authors, we should convince first authors to abandon the ppmv notation. Volume has nothing to do with mole fraction.

Supposing you know the mole fraction, if you literally wanted to calculate the parts per million by volume, first you need to define what that would mean.  Are you interested in the ratio of the volume of CO2 separately isolated relative to the whole volume? Or are you interested in the volume of CO2 separately isolated, relative to the sum of all the gases separately isolated? For either of these methods, you would need to choose a temperature and pressure, such as the actual temperature and pressure of a sample, or standard temperature and pressure.
Then you need an equation of state at least for the CO2, that is more real than the ideal gas law, such as van der Waals.


The first part of the association is that increasing levels of greenhouse gases in the atmosphere will cause rising temperatures on earth. Here is some information on why that is so, if you are interested. Now assuming that temperatures are currently going up (they are), there are two mechanisms that will connect this to rising sea level, melting of ice on land, and thermal expansion of water

Land Ice

As climate lawyers are quick to point out, if floating sea ice melts, it doesn't really change the level of the ocean (much) because floating ice displaces a volume equal to an equivalent mass of water. As we will see in the next part, the temperature change from ice melting and then warming will cause some changes.

Meanwhile, there is about 2.8 million cubic km of ice locked in Greenland's ice cap and 26 million in Antarctica. These two sheets, if fully melted would cause about 7m and 58m of sea level rise, respectively. They will not melt immediately; while the topic is under debate, Greenland will probably take a millennium to melt completely. Antarctica is larger, colder and more isolated from world temperatures fluctuations due to the circumpolar currents, and would probably take a much longer time to melt fully.

Thermal Expansion of water

The density of seawater changes with temperature. Using data from this chart (Data-Table 9), the density of seawater (at 35000 ppm salinity) at 10 C is $1.0270 \frac{\text{g}}{\text{cm}^3}$ and at 15 C is at $1.0260 \frac{\text{g}}{\text{cm}^3}$. Therefore, there is an estimated $\frac{1.027-1.026}{5} = .001 \frac{\text{g}}{\text{cm}^3}$ change per degree C, or a $\frac{.001}{1.027} = .097 \% $ increase in volume for a one degree C increase in temperature from 10 C to 11 C.

Not all the earth's ocean's are at 10 C, but using this as an estimator, the $1.35 \times10^9 \text{ km}^3$ will increase by $1.31 \times10^6 \text{ km}^3$ with a 1 C increase in temperature. If you divide that by the surface area of the ocean, 510 million $\text{ km}^2$, you get an approximately 2.5 meter increase in sea level.

That calculation is not at all rigorous; deep ocean water is colder than 10 C and at lower temperatures thermal expansion is much less (just look at the linked chart to see), but it does demonstrate that there will be a detectable rise in sea level from thermal expansion of seawater as the planet heats up.


Is there a general equation to know how big of an area is affected by an earthquake?

No, there isn't, because the area affected depends on so many factors, some of them unknowable. Magnitude, cause, depth, geology (which may be very variable in different parts of the area) etc. Besides which, the easiest way to tell which areas are affected is to monitor reports from observers. In the final analysis, the data that aid agencies want to know is which areas ARE affected rather than which might theoretically be affected if all relevant factors were known, which they rarely will be.


How accurate is a tipping-bucket rain gauge?

The following simulation results shows that the Tipping Bucket estimates suffer from significant errors if based on time scales less than ten to fifteen minutes.

Comparison of Tipping-Bucket Error Statistics:

(Source of above diagrams)

  In this study we attempted to characterize the errors associated
  with tipping-bucket rain gauges when used to provide rainfall
  intensity estimates at small temporal scales. The main source of the
  TB gauge sampling error is its sampling mechanism and its inability
  to capture the small temporal features of the rainfall time series. We
  found significant error levels in the 1-min estimates especially at
  low rain rates, but we also found that as the time scale of the
  computed rain rates increased, the error decreased substantially. With
  time scales longer than 15 min, the error becomes negligible. The
  gauge’s performance and its associated errors are sensitive to the
  applied sampling interval and the bucket volume. Therefore, we
  recommend sampling intervals on the order of 5–10 s, along with a
  bucket size no larger than 0.254 mm (0.01).  Our analysis wasbased on
  rainfall observations that were mostly dominated by convective storms
  with few stratiform events. Similar analysis may be needed to
  investigate the scope of applicability of the developed formulas under
  different climatological regimes. However, the formulas serve as a
  first-order approximation that can be used in practical applications. (Source)


Has there ever been a study done on the effect of steam/thermal pollution on climate

While the effect might be measurable (just barely) it's small.   We add about 30 billion tons of CO2 to the air every year.   About half of that gets absorbed into the oceans (give or take), the remaining 15 billion tons remains in the atmosphere for a long time.

280 PPM CO2 the post ice-age, pre industrial revolution number works out to about 1,000 billion tons of CO2.   Adding 15 billion tons per year, at the current rate, it would take about 66 years to double the 280 PPM to 560 PPM.   That's, of-course, very much an approximation and the ocean absorption rate probably doesn't remain constant it depends on the change in concentration and change in ocean temperature.

Water vapor, however.   While the output varies depending on fuel the mass of water added by burning fossil fuels is about 1/2 the mass of CO2, so 15 billion tons per year.   The amount of water vapor in the atmosphere at any given time is by this estimate about 5,700 billion tons.    Adding 15 billion tons of water vapor to the atmosphere per year might be enough to be significant, but as pointed out in the comments, water vapor leaves the atmosphere very quickly.  Unlike CO2, which takes a long time to filter out.   The half-life of water is days, the half-life of CO2 is probably a century or more.

If extensive driving or fossil fuel burning is done in low humidity areas, it seems feasible that some warming could be added by the increase in water vapor, but I expect that effect would be small but perhaps measurable.   In high humidity areas it would be irrelevant.   I've never heard of a study that looked at this in any detail.    That said, the intuitively obvious answer is that the effect would be tiny.   A tiny fraction of of the effect of CO2.    That said, water vapor does need to be included in the study as warmer temperatures hold more water vapor, so, as the Earth warms, water vapor in the atmosphere increases and pushes the warming along even more.   That's a well known feedback mechanism.    The effect of water from burning fossil fuels is likely very tiny because it's too little and too temporary and the net total amount of water vapor in the air is still primarily a factor of temperature, weather patterns and wind direction.    It is, however, probably not zero.  There's likely some tiny effect, but I've never heard of a study that looked into it.


Time for water vapor to generate more greenhouse effect than latent heat?

I am doing some calculations on this question myself. The atmospheric lapse rate is about 6.5K/1.000m. The adiabatic lapse rate is 9.8K/1.000 and the dry lapse rate of the naturally unstable atmosphere of Earth should even be 10.8K. So arguably the constant transport of latent heat by vapor from the surface into the atmosphere is reducing the lapse rate by some 4.3K/1.000m. Without a doubt the GHE would be much larger if it was not for the latent heat provided by vapor.
The GHE itself is a function of the emission temperature, which again is a function of the emission altitude. Vapor increases this emission altitude, which is why it is considered a GHG, the most significant one actually.
We need to ask what size GHE has (not 33K, but less), what bigger size it counterfactually had without latent heat and a lapse rate of 10.8K, determine the share of vapor in this case, and compare it to the (negative) effect of latent heat. Depending on what is bigger, vapor is either a GHG or an anti-GHG. From all the modelling so far I get definitely the latter result.


Haze in Arizona / Grand Canyon that gets more apparent around noon - smog or something else?

Most of the haze I've seen in AZ is blown dust. If it's windy and hazy, it's probably dust. There is little moisture/humidity to create haze. Pollution is also a possibility. It would have to travel from somewhere else as there isn't a lot of civilization in that area.


Are the processes of the rock cycle currently in dynamic equilibrium?

It's an interesting question, but in practice I think it's impossible to answer. It's very difficult to measure the rates of many of those processes, and the divisions between rock types can be quite ill-defined (for example, in migmatites). There's no scientific instrument we can point at a chunk of the earth which will tell us "in this region, 29.4 megatons of sedimentary rock became metamorphic rock during the past year".

What we can say, at least, is that the global balance of these processes is not constant over time. For example, during the Deccan Traps eruptions there was an increase in the rate of formation of igneous rock through solidification of magma.

The classic rock cycle diagram you posted probably encourages this kind of question, because it makes it look like a neat, closed system with well-defined boundaries and comparable quantities of each rock type. It's a very useful simplification for many purposes, but remember that these processes are occurring at or near the earth's surface. This whole system sits on top of the mantle (which is vast compared to the volume of crustal rock), and material is continually being passed between the two, so it's far from being a closed system.


How will cloud feedback effects on the climate change as the result of global warming?

We don't really know.

Climate models agree that the feedback is profound.  Significant.  Unfortunately, they do not agree about the magnitude of the feedback.  Nor about the sign.  The problem is that there are competing feedbacks.  Clouds act similar to greenhouse gases, because they absorb and re-emit terrestrial radiation.  But they also reflect solar radiation.  These feedbacks compete, and both have a large uncertainty.  The net effect is the difference between the two, and the difference between two quantities with a large uncertainty, has a very large uncertainty.

This is a major topic of research and it has been a major source of uncertainty in global climate models for... decades.  A major paper on the topic, a bit old but still mostly true, is:

Stephens, Graeme L., 2005: Cloud Feedbacks in the Climate System: A Critical Review. J. Climate, 18, 237–273. doi: http://dx.doi.org/10.1175/JCLI-3243.1

Quoting from this article, published in 2005:

  Thus we have no clear theory that suggests the accumulated effects of cloud feedbacks are in any way a function of global-mean temperature or, as posed, ΔT.

And from IPCC AR4 WG1, published in 2007:

  Cloud feedbacks remain the largest source of uncertainty in climate sensitivity estimates.

The most state-of-the-art knowledge at the time of writing is summarised in IPCC AR5 WG1 chapter 7 (PDF), which stated in 2013:

  Owing to the large magnitudes of the SWCRE [short wave cloud radiative effect] and LWCRE [long wave cloud radiative effect], clouds have the potential to cause significant climate feedback (Section 7.2.5). The sign of this feedback on climate change cannot be determined from the sign of CRE [cloud radiative effect] in the current climate, but depends instead on how climate-sensitive the properties are that govern the LWCRE and SWCRE.

Does that mean we can say nothing?  Well, it's not quite so pessimistic.  There are many attempts to answer this question.  The figure below shows estimates for the regional distribution of the shortwave and longwave cloud radiative effect, again from AR5 WG1:

Figure 7.7 | Distribution of annual-mean top of the atmosphere (a) shortwave, (b) longwave, (c) net cloud radiative effects averaged over the period 2001–2011 from the Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Ed2.6r data set (Loeb et al., 2009) and (d) precipitation rate (1981–2000 average from the GPCP version 2.2 data set; Adler et al., 2003).  Figure reference:  Boucher, O., D. Randall, P. Artaxo, C. Bretherton, G. Feingold, P. Forster, V.-M. Kerminen, Y. Kondo, H. Liao, U. Lohmann, P. Rasch, S.K. Satheesh, S. Sherwood, B. Stevens and X.Y. Zhang, 2013: Clouds and Aerosols. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

This suggests the effect is negative, but the debate goes on.  To be continued!


How important is Sahara dust for the Amazon?

Lovett (2010) describe that as the soils in the Amazon Basin are actually nutrient poor, due to nutrients such as the phosphorous and iron supplied by the Saharan dust, being leached out via the higher rainfall.  The Saharan sediment is rich in nutrients as, according to Lovett (2010), it is essentially dried up lake bed sediments, mostly (56%, according to Fisher, 2007) coming from the Bodélé depression in Chad, Africa, which is composed of diatom shells which have significant (but not excessive) amounts of phosphorous and iron - this is a finite source.

Mahowald et al. (2014) explain that phosphorus availability constrains both carbon uptake and loss, hence, the amount of phosphorus in a forest is a limiting factor for rainforests (and other environments).  Atmospheric phosphorus, such as that from the Sahara is linked with the long term productivity of the Amazon.  Mahowald et al. also state that biomass burning is also a source of aerosol phosphorus.

In terms of variability, Lovett also explains that these plumes are seasonal - during summer, they go across the Caribbean and winter, traversing south to the Amazon.  It is believed that at current rates of dust dispersal, this nutrient input could last for another millennia - however, there is considerable uncertainty due to uncertainty in the climate models about the Sahara becoming wetter or drier in future.

If drier, Lovett asserts that there would be more dust, allowing the continued input to the Amazon, whereas increased precipitation, i.e. a wetter Sahara would result in less dust, hence less nutrient input to the Amazon.  Miller et al. (2014) explain that many climate models predict that enhanced dust aerosol loading would reduce precipitation due to the dimming effect reducing evaporation, hence making the environment drier.  However, aerosols, including dust, are a major source of uncertainty in climate modelling.

Anthropogenic activity is also a significant source of uncertainty in long term climate modelling, it is suggested by Mahowald et al. that current land use changes in the Amazon itself is having a significant effect on the phosphorus input in the Amazon and surrounding forests.

A generalised view of the phosphorus cycle is provided below (from Wikipedia):

For the Amazon, the important differences are that atmospheric deposition is a vital input, and that leaching and runoff are more important loss mechanisms. (Crop harvest is also relevant due to human activity in the basin).

References

Fisher, 2007, Amazon forest relies on dust from one Saharan valley, New Scientist

Lovett, 2010, African dust keeps Amazon blooming, Nature News

Mahowald et al. 2014, Impacts of biomass burning emissions and land use change on Amazonian atmospheric phosphorus cycling and deposition, Global Geochemical Cycles

Miller et al. 2014, Impact of Dust Radiative Forcing upon Climate, Mineral Dust


How deep could the surface of the Earth's crust get?

Challenger Deep (10.99km) in the Mariana's Trench is the deepest part of the ocean floor. This is probably close to the deepest theoretically possible ocean floor with the  current thermal regime.

With the current thermal regime, the deepest 'steady state' ocean floor depth is about 5.5-6km ( cooling curves at Muller et al ) - limit is reached as the ocean crust cools and subsides. The crust (lithosphere) is effectively floating on the mantle (asthenosphere), and this steady state situation is known as 'isostatic equilibrium'.

You can get deeper by moving from a static to a dynamic situation. A subduction zone provides this - the subducting plate is moving and being pushed down, resulting in a deep ocean trench. Eg. The Mariana's, or the trench offshore Chile. A fast subduction zone should go deeper. A deep hole like this will also tend to fill with sediment. The fastest subduction zones move at about 16cm (and these are only the short arcs). The physical characteristics of the ocean crust will also vary a little (thickness, temperature), but beyond these parameters it is difficult to make the hole deeper, as it were.


How much mass has humanity added to the planet?

All mass used in construction on Earth comes from material on Earth.  Since mass is conserved, there is no change.  If we start harvesting material from the moon or asteroids for use in construction on Earth, then there would be a net increase in mass.  But currently, the net mass of Earth has decreased due to man, since we have launched many satellites into space which came from material on Earth.


In a study conducted in Taiwan Impact of the Urban Heat Island Effect on Precipitation over a Complex Geographic Environment in Northern Taiwan (Lin et al. 2011), found that by observations that

  The UHI effect plays an important role in perturbing thermal and dynamic processes; it affects the location of thunderstorms and precipitation over the complex geographic environment in northern Taiwan.

Hance, the situation and potential models of the distribution of rainfall are further complicated by the surrounding topography.

However, NASA's Earth Observatory page The Impact of City Landscapes on Rain presents 3 hypotheses for urban effects on rainfall, paraphrased below:

As you mentioned, the Urban Heat Island, forms a bubble of warmer air and potentially creates atmospheric instability, resulting in

  as the city-warmed air rises, it cools and forms rain-producing clouds that soak the area downwind.

The buildings and other structures cause a disruption to the ambient air flow, resulting in

  the city’s buildings provide a source of lift to push warm, moist, surface air into the cooler air above it, where it can develop into rain clouds.

Similar to no.2, the buildings split the flow of air around the warmer city, these parcels of air return together on the other side:

  When the two halves of the storm come back together downwind of the city, the air is pushed up like the two colliding trains. The rising air forms rain clouds.

When I did studies of the effects of aerosols (particularly particulate matter) in urban environments, there were many observations to suggest that some particulate matter could potentially become the cloud condensation nuclei that changes cloud cover and hence rainfall patterns.


Why do modern windmills turn clockwise, but classic mills turn counter-clockwise?

It is to do with the angle of the blade, it has nothing to do with the direction of the wind. If the blade is slightly facing clockwise then the wind will push it to turning anticlockwise. If the blade is slightly facing anticlockwise then the wind will push it up and become clockwise. There is no reason from a physics perspective that governs which direction of rotation is best. Modern wind turbines are manufactured in factories who use the same design of blades, this can reduce the cost of production and present a coherent view. While windmills in the past are produced in small local subsistence workshop and don't have standardization.


A good database of tectonic plates is available at the Institute for Geophysics of the University of Texas. The database includes present conditions and past and future conditions. They provide ASCII files in their ftp site.
 Source

Another option is the data from Peter Bird at UCLA that he described in his article "An updated digital model of plate boundaries", $G^3$, 2003. He provides the data in ASCII format in their ftp site (they include a readme file with the description of the data).


Why is it that "With higher CO2, the dry gets drier and the wet gets wetter"?

To my best knowledge, the paper by Held & Soden (2006) is the first paper that discussed the concept of the rich get richer. They used the climate change experiments generated for the Fourth Assessment of the intergovernmental panel on Climate Change or in other words, climate projections using climate models forced with different CO2 scenarios.
One of their findings is that:

Assuming that the lower-tropospheric relative humidity is unchanged
and that the flow is un-changed, the poleward vapor transport and the
pattern of evaporation minus precipitation (E - P) increases
proportionally to the lower-tropospheric vapor, and in this sense wet
regions get wetter and dry regions drier.

To explain, assuming warming earth leads to more evaporation and an increase in the air capacity to carry water vapor, therefore, relative humidity can be assumed unchanged in the lower-tropospheric. Simoustanly, with warmer mid and higher latitudes the act of the atmosphere (through General Circulation) to redistribute the heat is reduced. Thus, more water vapor remains in the regions of evaporation leading to wet regions get wetter and dry regions drier.
Yes, this result is widely accepted in the community.


In an idealised scenario (ie where the plane is flying due north or south at a and there are no other perturbations to its course apart from the Coriolis effect), yes. And I guess it would be the most efficient course too!


Yes. So far as aquifers are concerned, Antarctica is just like any other continent. The Ice is 4 kilometres thick in places, but at the bottom there is water. If there is any place where water is not found at the base of the ice sheet, there will be an aquifer within a few miles. There are about 400 sub-glacial lakes in Antarctica, the most well known being Lake Vostok in Russian Antarctic Territory.

Lake Vostok is very large and deep, covered by 4 Km of ice, and Russian scientists have recently drilled down to it in the hope of finding living organisms. Although it is completely dark down there they were not disappointed, and many micro-organisms were found, but no vertebrates. There is a large, dry valley deep in Antarctica where precipitation is negligible and bare ground is everywhere, but how this affects underground water resources I don't think anyone could say.


Why is ocean salinity not a good chronometer?

A good chronometer is one that satisfies the following conditions:

We know exactly how much it had of something when it began
We know exactly the rate of the accumulation of the thing, and the rate is constant.

For example, U-Pb dating in zircon is an excellent chronometer. We know exactly how much Pb is in zircon when it crystallises (= none) and we know exactly the rate of Pb accumulation by radioactive decay of U (with two separate isotopes, not one! Rejoice!).

On the other hand, sodium in the ocean is a terrible chronometer. First of all, we don't have full understanding of how and when the ocean formed, let alone how much sodium they contained in the beginning. In contrast to Pb in zircon that starts with zero and goes up, the amount of sodium in the ocean is a function of many variables. These variables change with time. How much sodium do rivers input into the ocean? Depends. During orogenic periods quite a lot. During other periods less than a lot. Volcanic eruptions? Periods such as the Siberian or Deccan traps surely input a lot, but what about other periods? Removal of sodium is also non a constant process. As bon said in the comments, you have mass removal events such as the Messinian crisis. Sodium lost in ocean floor alteration is a function of how much seafloor spreading you have at that time, and the rest of the ocean chemistry. All this changes throughout geological time. The rate is not constant!

The paper that you linked to from the Institute for Creation Research has a long list of inputs and outputs of sodium and attempts to quantify it. First of all, I would be skeptical of anything coming out of there, because religiously motivated people tend to cherry-pick the data that fits their belief. But ignore that, even if their data is 100% correct, it is still correct for today. For now. As mentioned before, the input and output fluxes change drastically over time. It is impossible to assume a constant rate for that!

Quoting from that paper:

  It is God’s world that we are studying by scientific
  methods. It is God’s handiwork that we are learning
  about through those studies. God deserves to be
  praised  and  honoured—and  believed—for  what
  we  have  been  able  to  learn  about  his  world.  If
  our careful study of God’s world brings us false
  or unreliable information, then what can it mean
  for the Psalmist to sing, “The heavens are telling
  the glory of God; the skies proclaim the work of his
  hands.”?

Other than the fact that this passage does not belong in a scientific paper, it mentions the scientific method. Well, they fail at the scientific method because they make assumptions that make their entire study invalid.

2019 EDIT

A new open access paper shows that quite a lot of chlorine ends up in subduction zones, and removed from the oceans. As there are different subduction fluxes throughout geological time, this is another reason for salinity being a bad chronometer.


Yes, but it will not be a very good dataset. You will only be limited to the size of the dataset.

You can use Python's griddata function. But of course, you will need to make your grid before using the function. Or you can use the interp2d function.


How would a particle travel in a hurricane?

You can find diagrams of air flow in hurricanes. If your balloon has neutral buoyancy it will go with the flow. Good luck in the complicated currents in the rainbands and eyewall.


You noticed they're often in University towns... but you may've missed that most sites are also in locations with National Weather Service offices:

Upper air stations (left) and NWS offices (right)

So NWS offices that are launch locations in the US include the twice (or more) per day launches in the responsibilities of its employees.

A few NWS Offices are indeed in buildings at universities (to foster cooperation between the office and research purposes); those include Tallahassee/FSU, Norman/SPC/NSSL/OU, Miami/NHC/FIU.

There may be a few launch sites not located NWS Office locations.  Most such sites are likely at other scientific facilities; I know XMR is actually at NASA's facilities in Cape Canaveral.  (Note: launches at XMR have indeed often been at odd times and been a bit less reliably done)  Still, it's possible that a few such stations are also standalone or at separate airports.  Indeed there certainly historically have been employees hired at many airport observation stations to supplement the (now) automated instruments with visual observations - I had a friend work at the Tallahassee Airport doing so only about a decade ago.  So it shouldn't be beyond reasoning that launches could be done at such spots if uniquely needed.  And I do expect some launch sites in other parts of the world are perhaps staffed in such ways (or by automated measures???).

I haven't actually been in the room where official launches are made, but at FSU saw quite a few from nearby offices, and have been around other sites too.  Still I don't know the precise specs on the equipment, but as far as I understand it, launch sites typically include either a shed/garage or rooftop platform room with a built-in large tube to launch into.  Such rooms hold the supplies and equipment.  Then there is indeed also a radio receiving station to get observations and movements back from the balloon:

From what I've seen, it typically takes a single person a few minutes to inflate the balloon, attach the equipment, and make the launch.  I know that at some sites in very difficult conditions (heavy winds)  multiple people may sometimes be needed to make the launch in order to control the large unwieldy balloon and equipment to prevent issues with tangling in nearby structures.  As mentioned, launch sites in built up areas often have a launch tube to help guide it on a safe starting trajectory.  In more sparse sites or NWS Offices at airports, they are indeed more like fields... so I believe they typically just go outside and release it from a spot clear of downwind obstructions.  Not the most fun in a thunderstorm or hurricane!  (Yes, there have been some amazing launches in such conditions!)


Are we changing Earth's weather with global warming?

First, regarding your assumptions, here is a graphic from this online textbook.

As you can see, your first assumption is correct, surface radiation is much more significant than thermals. Your second assumption is also correct, 'Back Radiation' and 'Emitted by Atmosphere' flows are significant, but absorption of heat by the ground from the air isn't even featured on this chart. So conductive heat transfer from air to ground is negligible.

This page gives some good background on how carbon dioxide contributes to global warming, and, as you said, it is due to absorption of infra-red radiation from both the ground and the air. Specifically, CO$_2$ absorbs IR wavelengths that can 'escape' absorption in water vapor (the primary greenhouse gas) in the range 12-15 $\mu$m, as shown in the graphic below.

With more thermal radiation absorbed in the air, less escapes into space, and the net energy balance of Earth is positive which results in a slow and steady warming.


This is primarily an exercise in interpreting a minimalist diagram. Believe me, you will have to learn to read even sketchier diagrams.

That said, the test had the correct answer to the question. Unambiguously, there are only three plates.

The left and right plates each contain a piece of continental crust and a piece of oceanic crust connected by a passive continental margin. In each case, the oceanic terrane and the continental terrane move as a unit, so there's only one plate on the left and only one on the right. With the middle, oceanic-only plate, that makes three.

Although the diagram you gave us is a little more simplified than I'm comfortable with, you can tell that whoever drew the diagram meant for the left and right plates to contain passive margins. The elliptical loops of arrows are intended to be interpreted as convection cells in the mantle, and each cell drags the lithosphere above as a unit. So, anything above any one convection cell should be interpreted as one plate.

Here is a slightly more detailed diagram showing a passive margin:

(Source: Wikipedia, CC 3.0)


How are flying drones and unmanned vehicled used for exploring volcanoes?

Here's a partial answer:

The Trail by Fire expedition 1.5 -- "We're a team of young volcanologists planning to measure the entire flux of gases emitted by volcanoes along the Nazca subduction zone." -- driving through South America has "a fleet of quadcopters with gas sensing and sampling capabilities, establishing a remote presence in the volcanic plumes we encounter along the Trail by Fire."

On their sponsors page they list the science payload for each of three Matrix quadcopters (more details about the mechanisms and some custom kit are on the page), which are used because of the difficulty and hazard of climbing to the vents along the mountain chain and sampling the plumes:

An Ocean Optics Flame UV-DOAS spectrometer for SO2 measurements
A multigas sensor built by INGV (Italy)
A gas collector to bring plume gas to the Delta Ray Spectrometer

There's also a bit of drone footage included in the videos on their blog page.

Note that their goal is specifically to understand the gases: "Our objective is to provide the first accurate and large-scale estimate of the flux of volatile species (H2O, H2, CO2, CO, SO2, H2S, HCl, HF, and more) emitted by volcanoes of the Nazca subduction zone."

(Disclaimer: I only know about this because one of the researchers worked for my institution during last year's initial expedition. A review of the literature may show more published uses of drones and UAVs beyond simply shooting video.)


What is this "crystal ball" located at a meteorological station?

It's a Campbell-Stokes sunshine recorder, used to record the times at which the sun is shining. It acts as a lens, focusing the sunlight onto a piece of card. If the sun is shining, the focused beam will burn a hole through the card at that point.

Here's a closer view of a sunshine recorder in Wendelstein, Bavaria:

Source: Wikimedia Commons

And here's a used recording card with holes burned through it:

Source: Wikimedia Commons


What are the tectonic implications of the Quaternary Igwisi Hills, Tanzania, kimberlite volcanics?

The Igwisi Hills kimberlites erupted through the Archaean aged Tanzanian Craton, which resides in between the eastern and western branches of the East Africa Rift (1), in the vicinity of the Gregory Rift (2). It is a series of 3 volcanoes, evidence has shown that these eruptions were the result small volume monogenetic eruptions (3).

Seismic studies and observations detected that the cratonic lithosphere base is approximately 170km, after which, there is anomalously low velocities to a depth of about 350km (1), which according to models described by Weeraratne et al. (1) indicate that beneath the cratonic crust, there is the presence of high temperature and the presence of melt:

a transition to a younger 'more fertile' asthenosphere.
crucially in terms of the local tectonics, indicate the presence of a mantle plume head causing the craton to experience uplift.

The mineralogy of xenoliths in the pyroclasts and lava further indicate that there has been small degrees of carbonate-apatite bearing peridotite source melts from depths greater than 110km. (2)

Brown et al. (3) conclude that the fact that these kimberlitic volcanics are so comparatively young, they may indicate that a new phase of kimberlite activity may be starting in the Tanzanaian craton, especially when considering the mantle plume and active rifting in the adjacent East Africa Rift branches.  This suggests that a link between kimberlite volcanism and the supercontinent cycle maybe too much of a simplistic view, when the reality is probably closer to individual plate reorganisation (in this case, the eventual splitting of the African continent).

References

(1) Weeraratne et al. 2003, Evidence for an upper mantle plume beneath the Tanzanian craton from Rayleigh wave tomography, Journal and Geophysical Research.

(2) Dawson, 1994, Quaternary kimberlitic volcanism on the Tanzania Craton, Contributions to Mineralogy and Petrology (abstract only - paywalled)

(3) Brown et al. 2012, Eruption of kimberlite magmas: physical volcanology, geomorphology and age of the youngest kimberlitic volcanoes known on earth (the Upper Pleistocene/Holocene Igwisi Hills volcanoes, Tanzania), Explore Bristol Research (abstract only - paywalled)


Quantitative mapping of air pollution Sifakis and Paronis

Homogeneous simply means “the same”. In the paper you have read about AOT (Aerosol Optical Thickness, I'm assuming?), the software used to process the data requires the user to select a grid cell size – at a sufficiently small size, the properties of the atmosphere can be assumed to be the same everywhere inside the cell, i.e. homogeneous, to allow the software to perform its calculations. There's little point in selecting a grid cell size smaller than the distance scales that are interesting and/or meaningful, or smaller than the scale on which anyone could/would measure the properties of the atmosphere you are interested in.  As an extreme example, there would be little point in finding/calculating the Aerosol Optical Thickness for every square centimetre across a geographical region!


How can we accurately quantify the degree of scientific certainty that global heating is caused by humans?

There are a few ways

Basically the best way is to see how many experts in the field are convinced, as great as it would be to assess the evidence individually, one person can't be an expert in everything and unless you and your audience are a climate scientists most papers are going to be beyond a lay assessment. So the best thing you can do for the lay public is look to the experts, people who have spent decades researching the subject and have the best ability to assess the data, and see what their assessment is.

NASA has a wonderful site dedicated to collecting assessments. They fall into three rough categories.

Meta analysis

A meta analysis of published works shows the number of scientific papers rejecting anthropomorphic climate change is vanishingly small (0.7%) and shrinking. those uncertain was even smaller (0.3%)

Professional survey

the same analysis also surveyed 29,000 published climatologists and showed a 97% support for anthropomorphic climate change and the rest being largely no-position. this is even skewed by expertise, when accounting for the number of published papers (a rough way of measuring expertise) it shows even stronger support among more published authors with most of the opposition being from authors that only publish a small number of papers.

Public statements by relevant scientific societies.

The American Meteorological Society and Geological Society of America as well as many others have made public statements in favor of anthropomorphic climate change. And of course you have the statements by the Intergovernmental Panel on Climate Change.


How is ocean salinity measured from space?

In a nutshell:

The instrument measures microwave radiances (after calibration)
If we know the sea surface temperature, we can use radiances to calculate emissivity.
The emissivity at 1.4 GHz is itself a function of near-surface ocean salinity.

However, in reality, it's more complicated, because there are other factors that come into the equation, such as surface roughness, which depends on wind.  Remote sensing problems are often underdetermined, and we need to make assumptions in order to retrieve the desired quantity.  Measuring ocean salinity from space is a classical inverse problem.

You can find details in the highly cited paper:

  Kerr, Yann H., Philippe Waldteufel, J-P. Wigneron, J. Martinuzzi, Jordi Font, and Michael Berger. "Soil moisture retrieval from space: The Soil Moisture and Ocean Salinity (SMOS) mission." Geoscience and Remote Sensing, IEEE Transactions on 39, no. 8 (2001): 1729-1735. (weblink).

which addresses both soil moisture and ocean salinity.


Convergent cross mapping (CCM) is a recently developed tool to answer the question you've asked. It's based on tools developed in nonlinear time series analysis and dynamical systems theory. It allows you to:
1) determine if a causal relationship between two variables is present
2) establish the direction of causality
3) do so even in the presence of noise.

As for an interesting application, check out the paper Causal feedbacks in climate change [van Nes et al., 2015], where CCM is applied to co2 and temperature based on the Vostok data sets.

EDIT: Below I've added a more detailed explanation of CCM to show the original poster that this technique does indeed answer their question, as well as to show it has a rigorous mathematical underpinning.

The general idea of convergent cross mapping is based on phase space reconstruction [F. Takens, 1981],[H. Abarbanel, 1996]. Numbers 1 through 5 explain the idea behind phase space reconstruction, which is needed to understand CCM. Numbers 6 through 8 very briefly explain CCM. References are listed at the bottom for more depth.

1) A physical system that is described by a set of equations (e.g. conservation of mass, momentum, etc) has a phase space. The solution to the system of equations is a trajectory through (or subset of) the phase space.

2) An attractor is a subset of the phase space that the trajectories/solutions evolve toward.

3) If you know the governing attractor, then you have all solutions of the system for all time.

4) Taken’s theorem says that one can reconstruct the attractor of the system based on a single observable. For example, if temperature, pressure, and velocity are the three variables of the system, then you only need measurements from one of these variables to reconstruct the attractor of the system. State space reconstruction

5) The reconstructed attractor is not exactly the “true” attractor, but it has a direct 1:1 mapping to the true attractor. Taken's theorem

6) If two observables belong to the same system, then they each have a reconstructed attractor with a direct mapping to the true attractor. The reconstructed attractors also have a direct mapping to one another. Convergent cross mapping

7) It is then possible to make predictions on one observable, based on the reconstructed attractor of the other observable, if they are in fact from the same attractor (causally related). Time series and attractors

8) Last, a series of tests/predictions with the data help to establish the direction of, strength of, and linearity of the interactions between the two variables. This is detailed in the papers [sugihara et al., 2012] and [van Nes et al., 2015].

To answer your question "given two observed variables, how do you tell if an third variable is simply forcing the two observed variables, making them appear correlated? First, the process of phase space reconstruction would yield an estimate of the "embedding dimension", which is an estimate of the dimension of the phase space (how many variables there). In the CCM framework, a one-way forcing relationship between the two known variables (v1 and v2) would be attractor for v1 can make skillful predictions of v2, but attractor v2 can not make skillful predictions for v1. Contingent upon the situation where you have an idea of what the third variable is (v3), I think what you could do is the following, take the reconstructed attractor of v3 and make predictions on both v1 and v2, and show that v3 has more predictive power on v1 (compared to v2), and that v3 has more predictive power on v2 (compared to v1). I'm not sure about this though.

Also, if the forcing (v3) is thought to be linear, you could simply remove/detrend v3 from v1 and v2, as is done when you remove seasonality from temperature data.

Note: There is MATLAB code available to mess around with this technique. I believe you can find similar codes in R as well.

References

Sugihara et al., 2012, Detecting causality in complex ecosystems.
van Nes et al., 2015, Causal feedbacks in climate change.
Abarbanel, Analysis of Observed Chaotic Data,1996, Springer publishing.
Takens, 1981, Detecting strange attractors in turbulence


How to calculate hourly rainfall projections?

The Probability Of Precipitation or POP is the exceedance probability over a given area for a given duration. The exceedance amount is generally taken as 0.25 mm, but may be any specified value. Again, the time $t$ must be specified, and is usually 3, 6, 12 or 24 hours.

Strictly speaking, the POP is meaningless unless the area under consideration is also specified, although in public weather forecasts this is seldom indicated. Individual storm cells generally have a footprint only a few kilometers wide, so obviously, the larger the area the higher the probability of precipitation, but the lower the average rainfall.

As for the confidence, this is a function of rainfall record duration and continuity, and raingauge network density.


What are the differences between alluvial, eluvial and colluvial deposits?

Your question is almost a duplicate of What is the difference between eluvium and alluvium?, but you also ask about colluvial deposits. The accepted answer for that question references this convenient guide from the Australian Museum, which also covers colluvial deposits:

Alluvial: Detrital material which is transported by a river and usually deposited along the river's pathway, either in the riverbed itself or on its floodplain.
Colluvial: Weathered material transported by gravity action such as on scree slopes.
Eluvial: Weathered material still at or near its point of formation.


How to download FLDAS data from earth data

To download the data from earth data, the following needs to be done

Go to https://urs.earthdata.nasa.gov/ and create an account. Note the username and password which will be used to download the data.

In your linux root create a file .netrc and enter the following
machine urs.earthdata.nasa.gov login your_login password your_password

Go to https://disc.gsfc.nasa.gov/datasets and search your dataset of interest and then click it

4.On the right hand side you will see a get data button, click that button.
5.Now a dialog box will open, click get data

Now another dialog box will open, click download links list, a list of the files will get downloaded.

Now in the terminal fire the following command
wget --load-cookies ~/.urs_cookies --save-cookies ~/.urs_cookies --auth-no-challenge=on --keep-session-cookies --content-disposition -i <url.txt>

Meanwhile before step 7 two things need to be done. One, you need to just create this file ~/.urs_cookies and the second is that you have to authorize the data that you are downloading.


How can I learn to spot fossils and fossil-bearing rocks on the Jurassic coast?

You are correct when you say it is mostly a matter of getting your eye in and getting used to the shapes and types of rock you need to be looking at. Hopefully however the below information will help you find a few more fossils or at least be of interest to you.

The main fossil bearing beds in Lyme Regis are from the Jurassic period and formed in a warm sea, hence the marine fossils.The Jurassic strata (layers of rock) in this area are mainly composed of grey limestones, shales and marls (lime rich mudstones).  These are the rocks you want to focus on when searching for fossils (see image below taken facing church cliffs).

The majority of the very well preserved ammonites are found in the limestone and can be found inside limestone nodules or lying loose on the beach. This rock is very hard and will require a good geological hammer and maybe a chisel to split. This is often easiest if you find a nodule with lines of weakness or cracks that you can split it along. It is also a good idea to look for signs that the rock contains a fossil before trying to break it, part of a fossil may be visible on the surface of the rock.

You can identify the limestone by it's lighter grey colour and hardness, it should be quite hard to break without a hammer.

It is however possible to find ammonites in the shale and mudstones, the ammonites in these however tend to be less well preserved. These rocks are typically a darker grey and very easy to break. However there are other fossils that can be found in these shales, including belemnite rostrum (belemnite guards). These bullet shaped fossils are from an ancient relative of the squid and the cuttlefish and are very abundant in certain areas.

Finally there are very soft mudstone beds out near Church Cliffs that you can walk across along the foreshore and are rich in belemnites, as well as pyrite (fools gold) and pyritised ammonites. These are formed when the original shell is replaced by pyrite in low oxygen conditions such as deep on a muddy sea floor and can be recognised by their golden colour and shine.

All the best with your fossil hunting!


Is it reasonable to approximate the swinging building (base of the building) during an earthquake to a simple harmonic motion?

By the definition of simple harmonic motion (restoring force proportional to displacement), no. You need to take into account damping.


How far away can you see a thunderstorm?

The top of a cumulonimbus cloud is usually about 40,000 feet and can reach heights of over 60,000 feet, which would be visible for a distance of 245 or 300 miles, respectively.  Of course, that would be the very top that would be visible at those distances, but it puts it well within the 125 mile distance from which you saw the storm.

The following formula was used:

$$\text{distance} = 3958.8 * \arccos(3958.8/(3958.8+\text{height}))$$

where $3958.8 \ \mathrm{mi}$ is the mean radius of earth.

This formula calculates the distance from an observer to the horizon, which for a six-foot tall person is close enough. If you wanted to calculate the distance an object would be visible from (given absolute atmospheric clarity) you'd have to calculate this twice (from observer to horizon and horizon to object) and add the results.


What evidence is there linking melting ice caps and changes in tectonic movement?

Continents move slowly. Glaciations are ephemeral in comparison.

That said, there apparently is a huge connection between plate tectonics and whether the Earth is in icehouse or hothouse conditions. There was very little if any ice on the Earth when the Earth was in hothouse (aka greenhouse) conditions. Dinosaurs roamed close to the poles. The Earth's climate was (and is) considerably cooler during icehouse Earth conditions. Widespread glaciation has only occurred during icehouse Earth conditions. Note that we are currently under icehouse Earth conditions; we just happen to be between glaciations.

The following conditions that contribute to icehouse Earth are all due to plate tectonics:

Having a continent parked over a pole.
For example, Antarctica is currently parked over the South Pole. This is not a sufficient condition, however. Antarctica has been parked over the South Pole for 100 million years or so. The Earth has been in icehouse conditions for the last 30 million or so years, and in ice age conditions for about the last 2.3 million years.
Having significant land masses within 45 degrees of a pole.
With the possible exception of snowball Earth (icehouse Earth gone wild), icehouse conditions need significant amounts of land near a pole. Having one continent parked over the pole but most of the continents close to the equator doesn't create icehouse conditions.
Having relatively low seafloor spreading at midoceanic ridges.
This is crucial, for two reasons. Lots of seafloor spreading means lots of CO2 being released into the oceans and eventually into the atmosphere, thereby enhancing the greenhouse effect. Lots of seafloor spreading also means more and higher midoceanic ridges. This raises the sea level, which in turn increases the amount of Earth's surface covered by water, which in turn decreases the Earth's albedo. Reduced seafloor spreading means reduced CO2 levels, reduced sea level, and increased albedo.
Having oceanic currents keep equatorial regions warm, polar regions cool.
The opening of the Drake Passage about 41 million years ago and the opening of the Tasmanian Gateway about 35 million years ago enabled the cold circum-Antarctic current to form. This is when Antarctica turned from just cold to < expletive deleted > cold. The closure of the Panama seaway between 13 and 2.6 million years was the last nail in the coffin regarding current ice age (as opposed to mere icehouse) conditions.


Missing pages in Knauss' "Introduction to Physical Oceanography, 2nd edition"?

I own the Second edition, 2005 reissue of this textbook, purchased through Amazon in August 2009.

After p308, my copy has only one more page of content (p309), which is the last page of the Index. You indeed have a faulty copy. I recommend you send it back for replacement again and request them to inspect the copy before shipping.

If you are still unlucky with the second replacement, I would try e-mailing the publisher with your purchase invoice and request a pdf of the book which would complement your hardcopy with the missing page.


I too have found this nomenclature rather confusing.  I am pretty sure that trace-based inversion is merely where each seismic trace is inverted independently of surrounding traces. This would take into account most deterministic/probabilistic inversion types (e.g. model, coloured, sparse, etc). In contrast, geostatistical inversion would not strictly be trace-based inversion, as it uses a spatial and temporal variogram to takes into account the expected results of surrounding traces during the inversion, even though it does invert on a trace-by-trace basis. Confusing.

The following paper describes trace and geostatistical inversion methods:
Germán Merletti, and Julio Hlebszevitsch. 2003. Geostatistical Inversion for the Lateral Delineation of Thin Layer Hydrocarbon Reservoirs: A Case Study in San Jorge Basin, Argentina. SEG 2003.

I've found the following paper very useful for understanding seismic inversion (geostatistical isn't discussed, though):
Dennis Cooke and John Cant. 2010. Model-based Seismic Inversion: Comparing deterministic and probabilistic approaches. CSEG Recorder, Vol. 35, No. 4.


Take all the CO2 in the atmosphere and put it into a layer on the surface of earth, how thick would the layer be?

Ok, based on the comments above, this is where I am at...

earth's radius is $6371 \text{ km}$
earth is a sphere
There is approximately $3 \cdot 10^{15}$ kg of CO2 in earth's atmosphere
The density of CO2 at 1atm is $\dfrac{1.977 \text{ kg}}{\text{ m}^3}$

So, first, with assumption (3 and 4) we can compute the volume of CO2 in the atmosphere to be $\approx 1.52 \cdot 10^{15} \text{ m}^3$ or $1.52 \cdot 10^6 \text{ km}^3$.

So, now we can find the thickness of the layer by solving the equation

$\begin{align*}
1.52 \cdot 10^6 &= \dfrac{4 \pi \cdot (6371 + x)^3}{3} - \dfrac{4 \pi (6371)^3}{3} \\
\end{align*}$

Where $x$ is the thickness of the layer of CO2 on earth's surface in km.

$\begin{align*}
1.52 \cdot 10^6 \text{ km}^3 &= \dfrac{4 \pi \cdot (6371 + x)^3}{3} - \dfrac{4 \pi (6371)^3}{3} \\[.5pc]
\dfrac{3}{4\pi} \cdot 1.52 \cdot 10^6 \text{ km}^3 &= (6371+x)^3 - 6371^3 \\
\dfrac{1.14}{\pi} \cdot 10^6 \text{ km}^3&= (6371+x)^3 - 6371^3 \\
3.63 \cdot 10^5 +6371^3 \text{ km}^3 &= (6371 + x)^3 \\
\sqrt[3]{3.63 \cdot 10^5 +6371^3 \text{ km}^3} &= 6371 + x \\
6371.0029811 \text{ km} &\approx 6371 + x \\
.0029811 \text{ km} &\approx x
\end{align*}$

So, the layer of CO2 on earth's surface would be 2.98 meters thick...


Does cloud fraction of 0 for low clouds means it was raining?

Depending on context, cloud fraction can mean:

the fraction of the visible sky covered by clouds (total cloud fraction).  This is what an observer from below or above sees and this is what is normally reported by measurements
the fraction of a particular area and altitude covered by clouds.  This is what is typically reported by models.

The differing definitions need to be kept in mind when comparing models to measurements.

Under normal circumstances, clouds are a necessary but not a sufficient requirement for precipitation (there are some exceptions).

To answer your titular question: No, a cloud fraction of 0 for low clouds does not mean it was raining.  Nor does it necessarily mean it was not raining.  Remember: a total cloud fraction of 0 means a clear sky, a total cloud fraction of 1 means a completely covered sky.  So a low level cloud fraction of 0 means there are no low level clouds.

To answer the question you ask in the content of your post: Statistically speaking, yes.  The quantities low-level cloud fraction, cloud optical thickness, and total cloud fraction do contain information about precipitation.

If the total cloud fraction is zero, there is no precipitation.

If the cloud fraction for low clouds is zero, but for mid-level or high clouds is non-zero, it may or may not be raining.

Cloud optical thickness should correlate with precipitation occurrence and intensity.

However, these quantities do not provide complete information about precipitation.  You can't say with full certainty that a day is rainy based on these quantities alone — but you can say which days certainly aren't.