Why can't the meteorologists predict for sure if the day would be rainy even on the beginning of the day sometimes?

The probability of precipitation (POP) has to take into account the areal coverage of some region, e.g. the broadcast market of your local TV station, but perhaps the size of your local county or region.

Because of this the POP is calculated as

$\mathrm{POP} = C \times A$

where $C$ is the confidence it will rain somewhere within the forecast region and $A$ how much of the area will experience the precipitation.

So a 100% chance of rain means it is going to rain in the entire forecast region and they are confident that it will rain.  That is a high bar, as spatial coverage of storms is often localized.

For example, if one storm is going to track through your city and its path is only going to cover 15% of the area, even if we are 100% sure it is going to happen, that still only yields a "15% chance of rain".  This is because people living in that area where the storm goes though will get rained on, but the other people will not.  This also helps average out temporal and spatial errors in the forecast.


What would a graph of magnitude >7.5 earthquakes over last 400 years compared to Grand Solar Minimums look like?

As others have pointed already in the comments, there is no earthquake data extending that far back. But we do have data for the last century. In a similar way to my answer to this question. Here I've plotted the yearly count of all of the earthquakes worldwide from 1900 to 2018 of magnitude greater of 7,7.5, 8, or 8.5 found in the USGS Earthquake Catalog that span back to year 1900 (bars), along with the total number of sunspots per year from the Sunspot Index and Long-term Solar Observations (red line).  Here is the resultant graph:

As you can see, there is not any significant correlation between frequencies of large earthquakes of any size and the solar activity. The solar record shows the well-proven 11 year solar cycle (actually it's a 22 year cycle with two similar halves). On the other hand, the earthquakes show no clear pattern.

Unfortunately, for the grand minimums like Maunder and Dalton's solar minimums we do not have a reliable earthquake record. Nevertheless, given that EVERYTHING we know about physics and earthquakes suggest that there is NO mechanism by which solar activity could possibly influence earthquakes. And provided that there is no evidence of such correlation in the 100+ years of the instrumental record. There is absolutely no reason to believe that such correlation exist. The answer to this question should be informative too.


The information you provide is rather limited, however, I want to try and disentangle this. The way I see it, you are mixing three different concepts in your questions. I will work through the semi-circle, through the elliptical towards the hyperbolic assumption.

Semi-Circle

This is a GIF of a central source emiting a wave in a homogeneous space:

You can stop the gif at any time (drag it with your mouse) and all wavefronts will be concentric. You can also see this, when you look at the wave equation. Changes in time equal the velocity times changes in space. If the velocity is constant, a change in time will cause a equal change of wave propagation in any available direction. While often, we work in (x,y,z)-coordinates, here it's easiest to assume that our wave source is at $(0,0,0)$ and if our propagation is equal in all directions, our vector pointing to these points in space is the radius of a perfect sphere.

Of course, if we're looking at a half-space like we do in seismics, we have a half-sphere and if we scale back to 2D we have a semi-circle surrounding our source. So if we dig up a huge patch of subsurface and place receivers all around our source, those equally distant from the source should respond at the same time after igniting the source.

Ellipsis

In Fig. 13 you see the semi-circle. There are several important things to note in this image. The first would be the receiver. The receiver is off-center, but all those receivers in the semi-circle example are too. What makes this different, is that instead of several receivers recording the wave simultaneously, here, it's one singular receiver. Additionally, before our source was nice and centric, now it's off-center.

Unfortunately, this is not enough to make sense of Fig. 13. Firstly, for the semi-circle we were looking at direct waves. In Fig. 13 we see reflected waves. Now, they assume constant velocity again, which means there clearly must be a density change to make a reflection happen. This brings us to a simple theoretical question: "I have a measurement with the traveltime $T$. Which locations in the subsurface would have to have a density change to explain my measurement of $T$?"

So essentially, you are constructing a plane where the ray path from the source toward the plane, added to the ray path from that incident point on the plane to the receiver is always of the length $T$. Luckily, this is exactly how a half ellipse is formed.

You can actually try this with a string. Take a string of the length $T$, fix one end on the source location, one at the receiver location and then put a pen in the sling and trace the outmost location you can reach with the pen in the sling. You have created a surface below your acquisition, which could all have caused a response at your receiver at the time $T$.

Fun fact: If you put the source and the receiver back to location $x=0$, your ellipsis becomes a circle again. It's not the semi-circle from before, as before we had a direct wave, now we're looking at a surface of equal reflection traveltime. You can see this in the following figure CC-BY-SA Ag2gaeh:

Hyperbola

Figure 14 will again take us a step closer to migration. Before, you looked at One source off-center and one receiver off-center. Now we switch gears again. Let's look at the easiest case here, $x=0$. Here the source and the receiver are at the same location, so the travel time $T_0$ to the imaging point I is equal in length before and after reflection from the subsurface point. But from before we know that this place I could be anywhere on a semi-circle in the subsurface (which would be an ellipse, if it wasn't for the fact the $S=R$, as we saw before).

So we need something to convince our math, that instead of placing our image point I "anywhere on a semi-circle", we want the exact location. Here, we have several ways to look at it. If the image point $I$ in the subsurface is actually a point, we call it diffractions. The special property of diffractions is, that they will always reflect your wave right back at you (they diffract the wave, so they scatter the wave in all directions, hence, also back at you). So if you place your source and your receiver at location x=1 in this image, we can construct a triangle between the points $I$, $x=0$ and $x=1$. That means our traveltime T_1 can be calculated with good ol' Pythagoras ($a^2 + b^2 = c^2$):
$$1^2 + (T_0/2)^2 = (T_1/2)^2,$$
and we can do this for every point so that:
$$T_N = 2 * \sqrt(N^2 + T_0^2/4)$$
and then:
$$T_N = T_0 * \sqrt((2N/T_0)^2 + 1)$$
This coincidentally describes the eccentricity of a hyperbola. This is one way to go about finding diffraction hyperbolae, there are several others, but I tried to stick with the provided figures.


Different atmospheric models available for personal usage?

Unfortunately, I don't think such a numerical model exists that would be suitable for high school students' understanding. The simplest climate model around is a zero-dimensional (energy balance) climate model, but a background on mathematics, and programming may be necessary. You can find one here. Wikipedia has one listed. Michael Mann has the source code for such a model, but it is written in MATLAB (you may be able to run it in OCTAVE, since MATLAB is licensed). There are likely many more than just these, considering multiple layers, volcanic eruptions, etc.

The code for the models listed are simplified models that do not consider things like clouds, aerosols, eddy diffusion, etc. This is where Global Climate Models (GCMs) differ. They must consider how fine details, some of which aren't considered by weather models, affect the climate. Therefore, they are usually complicated. Most GCMs I have seen are written in FORTRAN, which is an antiquated language, but computationally efficient. This makes even easy concepts obtuse.

While I have not dealt specifically with CESM, I can infer some things about it. By definition, CESM is an earth systems model, not an exoplanet model. You may be able to adapt some of the parameters to other planets, but it becomes too difficult for just one person to do (because of FORTRAN). There are models for other places, such as GCMs for Mars, but they are difficult to run and not necessarily accurate. Clusters are needed due to memory limitations, and how long they run for.


How does the composition of volcanic rock change as it makes its ascent towards the surface?

Does the composition of the volcanic rock change drastically according to the distance between the magma column and the mouth of the volcano at the time the rock is formed?

The metal composition of the magma will not change drastically. By metal I mean the basic constituents of the rock: mostly silicon but also iron, calcium, aluminum, magnesium, etc. I will add that there are processes that can affect metal composition (chiefly mineral fractionation) but I think its influence is minor when you're talking the the uppermost part of the volcano where it erupts.

What can and does change is the volatile composition. The magma is depleted of gases. Take for example a bottle of coke. When you open it, the CO2 bubbles out. The coke itself remains coke, but its chemistry changes a bit (and it tastes bad) because the CO2 is out. The magma may also change oxidation state. This, together with the volatile degassing may eventually affect the minerals that crystallise from the magma.

  (Or) do the rocks melt and recrystallize frequently as the boundary moves, only attaining their final composition before they are ejected into the air?

No. Once a rock crystallises you are going to need quite a lot of energy to melt it again, and this is not a likely process to occur in a system open to the atmosphere where heat is free to leave the volcanic system.


I haven't looked into ERA-Interim wave data a huge amount but I know around 1991 it started to assimilate ocean wave data from satellite altimeters (ERS-1).
See the first figure here
https://climatedataguide.ucar.edu/climate-data/era-interim

I remember Jean-Raymond Bidlot who runs WAM at ECWMF showing me so experiments with and without the assimilation into the wave. I think the Hs differed by ~1m in large events so not insignificant.


Is it possible for a natural fluorescent mineral to glow from the sun's rays?

The lifetime of a fluorescence excited state is on the nanosecond to microsecond time scale.  So once the excitation source light is removed, the emission of light will stop within microseconds.

Note that fluorescence is distinct from phosphoresence, and phosphorescence can involve longer lifetime excited states.

Spectroscopic Characterization of the Uranium Carbonate Andersonite provides quantitative information on fluorescence lifetimes for Andersonite, and lifetimes are in the microsecond range.

Regarding phosphorescence, see Phosphorescence; or, The emission of light by minerals, plants, and animals (1862):

  SEVERAL substances manifest the strange property  of emitting light
  when they are placed in darkness,  after having been exposed for some
  time to the  direct rays of the sun. In some cases a very short
  exposure to sunlight is sufficient to excite the  manifestation of
  this remarkable property, and in  others the direct rays of the sun
  are not necessary :  it suffices that the substance experimented upon
  be exposed to the dull light of a cloudy day. To  this phenomenon the
  denomination of Phosphores-  cence after insolation has been given.

  ' The substances which possess this property in  the highest degree
  are the Bologna stone, or solar  phosphorus, certain varieties of
  fluor-spar and  carbonate of lime, some fossils, calcined shells or
  pearls, phosphate of lime, arseniate of lime, etc.  Many diamonds
  shine with brilliancy in the dark  if they have previously undergone
  an exposure of  some seconds' duration only to solar light. But  no
  substance surpasses in this respect sulphuret  of barium.

  It is now a long time since the cobbler of Bologna,,  in Italy,
  astonished and amused his friends with a  peculiar substance since
  known as Bologna phosphorus, Bologna stone, or Solar phosphorus,
  which  shines brightly in the dark after having been placed  in the
  sunlight for some time. This substance is  sulphuret of barium. The
  cobbler prepared it by  heating red-hot with charcoal a piece of
  sulphate  of baryta, or Barytine, (Fig. I,) a stone which he...


What effect does concretization (paving/flooring with concrete) has on ground water table

I found this on the USGS website. It states the effect of increased pavement coverage due to urbanization is to reduce the recharge rate of ground water, because the water is diverted elsewhere.

Also, with urbanization comes the use of storm water drains. The rain water that would have soaked into the ground and recharged the ground water is diverted to streams via the storm water systems (pipes and channels) which can result in flooding elsewhere.


High-resolution georeferenced population data

For "historical" population data, you can refer to the Gridded Population of the World (GPW), version 4. This dataset makes available estimates of population at ~1 km resolution (30 arc second) for the years 2000, 2005, 2010, 2015, 2020.

The GPWv4 was also used by the European Commission's Joint Research Centre for the Global Human Settlement project. This dataset makes available residential population estimates for target years 1975, 1990, 2000 and 2015 at 250m and 1km spatial resolution.

If you also need future projections, you can refer to the Shared Socioeconomic Pathways (SSP) scenarios downscaled by Murakami and Yamagata (2019), available here, or by Jones and O'Neill (2016), made available through the ISIMIP project portal.


Calculating Love numbers (tidal deformation) for non-homogeneous planets

I actually just found an article that explains such a calculation in detail, using a matrix propagator method: Padovan et al. 2018
This is a calculation for gas giants or bodies in hydrostatic equilibrium. The calculation of the Love numbers for terrestrial planets that have viscoelastic behaviour requires the rheology (which includes models for the rigidity). I did not find the equations that need to be solved in that case, but a similar matrix propagator method can be used apparently.
I will not repeat the matrix propagation method here, as it is quite well elaborated in the paper I just mentioned, except for the equation you have to start from, which is explained in another article, but looks a bit too complicated for me at this point.


Why don't scientists use fire entry suits to study volcanoes?

I'm a volcanologist and I have worked on erupting volcanoes. First of all, volcanologists almost never actually wear those suits. Heat is almost never the hazard that matters in the situations in which we work. The hazards are usually the chance of being hit by ballistics, or getting gassed. The reason you see those suits so often is that they look really cool on TV.

I do know that Katia and Maurice Krafft wore them commonly, but their goal was to get as close to explosive eruptions as possible, as frequently as possible, for as long as possible. This strategy leads to death. It was a tragedy when the Kraffts (and 41 others) were killed at Unzen, but not entirely a surprising one, in retrospect. Modern volcanologists tend to be far more cautious and you might say that the heroic age of volcanology is over.

When you're working on an erupting volcano, some major things you can do to reduce risk are:

Wear a helmet. This would have saved lives at Galeras.
Reduce the amount of time you spend in the hazard zone. This means you need to work quickly, which often means carry less and don't wear silly protective gear like heat suits.
Wear a gas mask, usually with SO2 scrubber cartridge. Ever try to jog up a hill in one of these? It becomes hard to breathe, and the mask quickly fills up with condensation from your breath. Communication through a radio or otherwise is hindered. Everything takes longer, so sometimes the masks are left off in the interest of #2.
Increase your situational awareness. Maintain communications with someone who is watching data from instruments such as seismometers and tiltmeters. Also, make sure you have unobstructed vision so that you can potentially step out of the way of lava bombs which are falling towards you. Again, PPE such as a heat suit or even a gas mask can work against this.

As for the idea of "picking up" lava with your hands, remember that lava is extremely viscous, so it takes quite a lot of force to pull a sample out of a flow. The colder lavas to which you refer are even more viscous than hotter lavas. Anyway, I doubt there are any gloves that can deal with prolonged contact with a 650C fluid. (Remember that fluids and solids are far more conductive than a gas and will transfer far more heat.) I think trying to sample lava with hands would be far more "awkward" than using a pole, which is really quite a simple, easy way to do it.

Edit: I just thought of another reason volcanologists can't dress like firefighters. Expense. Volcanologists have an extremely hard time getting sufficient funding. I actually asked for an SCBA for my work in the fumarolic ice caves of Mt Erebus, where CO2 is high. We couldn't afford it on our grant. Instead, I just carefully monitor gas levels and there are caves which I cannot enter because we read dangerous levels of gas at the entrances.

Edit: I highly recommend that anyone interested in this subject read No Apparent Danger and Volcano Cowboys.


Given the subject matter of the paper, I'd assume that it stands for carbon, and the whole expression refers to milligrams of carbon (or organic carbon) per litre of lake water.


Modelling extreme rainfall events: 'blanket approches' when considering soil infiltration

I would be surprised if the rainfall-runoff relationship would show a linear relationship for extreme events. I would consider that to be a blanket approach, if you mean using a constant coefficient. So consider using a higher order relationship.

Another thing to consider is whether the rainfall runoff relationship depends on the soil moisture. Maybe check out how other models like SWAT deal with this.

To be honest, I think that the amount of soil infiltration will be insignificant for extreme rain events because it occurs too slowly compared to the rainfall rate and other uncertainties.


Public sources of topographical data of Earth?

This is an interesting and common question, so I'll try to give a good answer here, that I think is a good place, as well as GIS and Open Data SE.
First, regarding the format, you will never find data natively stored in text or tabular form, because the large data volume would lead to huge files very difficult to handle. Data is usually stored in binary files, common standards are .hgt and .tif. And there are many software and utilities that can export small subsets of the data into text, csv, or tabular formats.

I'll list here the global or near to global sources. All of them have advantages and disadvantages, and all have data gaps and artifacts, specially in areas with rough topography. So depending of your area of interest, one or the other can be better.

SRTM (Shuttle Radar Topographic Mission)

Resolution: 1 arc-sec (~30 m)
Data epoch: February 11$^{th}$ to 22$^{nd}$ 2000
Data type: Integer
Vertical reference: Orthometric (geoidal)

The most widely used standard, due to its quality, resolution, and coverage. It covers the whole globe between latitudes 60°N and 56°S.

In contrast to all other datasets, all the data was acquired in a 11-day mission, therefore, it have unmatched consistency, specially in areas with rapid terrain changes like glaciers, open pit mines, cities, etc.

The space shuttle was carrying two radars that created two independent terrain models, the coverage above corresponds to the SAR-C instrument that produced the data that is most widely used. The second instrument was the X-SAR, that had a narrower swath, and does not have global coverage.

There are multiple versions of these datasets:

SRTM v3

The latest official release is version 3. It comes in its original form, that includes data gaps and a gap-filled version, on which those gaps have been filled with data coming from multiple sources (but primarily ASTER GDEM).

The data can be accessed through multiple gateways, some of them are:

USGS EarthExplorer
NASA EarthData
LP DAAC Global Data Explorer
USGS data server (Version 2.1)

CGIAR SRTM

An independent post-processing of SRTM data.  Known also as SRTM v4.  It consists of a gap-filled version of SRTM using an advanced algorithm. It is only available at 3 arcsec resolution (90 meters) . It can be downloaded at the CGIAR SRTM Download manager

NASADEM

The SRTM data was reprocessed with cutting edge technology, improving accuracy and reducing data gaps. In contrast to other SRTM versions, it offers also a ellipsoidal version of the data (instead of geoidal), and the data comes in floating point values (instead of integers). NASADEM is expected to be the last official release of SRTM data. This DEM is still in the development phase but should be released at any time. A provisional version has been released and can be downloaded at the MEaSUREs data repository. More information on how to use this data can be found in my answer here.

This dataset should NOT be confused with the "NASA Shuttle Radar Topography Mission Global 1 arc second V003" (SRTMGL1). Which corresponds to the SRTM v3 data described above.

ViewFinderPanoramas

Some individuals like Jonathan de Ferranti, tackled the gargantuan task of doing a manual quality assessments of all the gaps of the SRTM and areas that have erroneous data. To then fix it using many sources, including many national mapping agencies from around the world. He produced a great version of SRTM with most errors fixed. Unfortunately, all this work was done before the worldwide release of full resolution SRTM data in 2014, therefore, for most of the world this data have only 3 arc-sec resolution (~90 m). And it can be downloaded at ViewFinderPanoramas.org.

SRTM X-SAR

Data from the second radar on board the Endevour space shuttle during the SRTM mission. It has slightly higher resolution (~20 m) but worst coverage, because the multiple swaths did not overlap, so for example, over North America the coverage looks like this:

This data can be downloaded from DLR Geoservice.

ASTER GDEM

Resolution: 1 arc-sec (~30 m)
Data epoch: 2000 to 2011
Data type: Integer
Vertical reference: Orthometric (geoidal)

With almost complete coverage between 83°N and 83°S, GDEM was produced from more 1.5 million stereo pair images by ASTER sensor. A joint project between JAXA and NASA on board of Terra satellite. This is the coverage of the latest release:

The current version is GDEM v3 (released on August 5 2019). This Release also includes the ASTER Water Body Dataset (ASTWBD), a valuable dataset to correct terrain models. GDEM v3 is available from:

NASA EarthData
Japan Space Systems

ALOS World 3D

Resolution: 5m (paid), 30 m (free)
Data epoch:  2006 to 2011
Data type: Integer
Vertical reference: Orthometric (geoidal)

Somehow the successor of ASTER, ALOS and its instrument PRISM, also offer stereo capability and higher resolution. And it was used to generate a new DEM with near global coverage:

The free 30 m resolution version of the data (with maximum resolution of 5 m), can be downloaded at JAXA AW3D30 DSM data page (need to sign up first). Current version is AW3D30 v2.2 (released in April 2019).

GSDEM30

The "Global Seamless DEM 30" is a 1-arcsec (~30 m) DEM that was constructed by merging unfilled SRTM, ALOS World 3D, and ASTER GDEM v2 datasets. By combining all these sources, it reduces data-gaps and significantly improves the quality of the data in regions where any of the base DEMs performs poorly. Data can be downloaded from the Wuhan University's SENDIMAGE servers. More details of the data merging process can be found in this paper.

TanDEM-X WorldDEM

Resolution: 12m (paid), 90 m (free)
Data epoch:  2010 to 2015
Data type: Floating point
Vertical reference: Ellipsoidal

The latest radar base global elevation model, created from two satellites orbiting in tandem formation (TanDEM-X), allowing high accuracy single-pass InSAR and DEM generation with truly global coverage. The free 90 meter resolution data can be downloaded from DLR Geoservice.

ArticDEM and REMA

Resolution: 2m
Data epoch:  2007 to 2018

This two projects turned the polar areas from being the ones with the worst available topographic data to the ones with the best data. By computing DEM's from millions of stereo image pairs from the high-resolution imaging satellites of DigitalGlobe. ArticDEM covers all latitudes north of 60°N:

And REMA covers all latitudes south of 60°S:

The data can be explored and downloaded from the ArcticDEM Exporer, and Antarctic REMA Explorer.


It is an artifact of the processing software when it processes Multibeam Bathymetric Survey data.
You can get the lines of the different surveys from NGBC at NOAA (https://maps.ngdc.noaa.gov/viewers/bathymetry/). As you can see in the image below both lines you see in your example correspond to multibeam data. In the area there is a fair amount of single-beam bathymetry, but the multibeam bathy is often weighted differently creating artifacts in some cases.
The GEBCO bathymetry does not contain the artifact.


Why does sea level correspond to boundary between oceanic and continental crust?

Sea-level only sort-of corresponds to the oceanic–continental crust boundary.

In depth, they don't correspond at all:

It's the same story at an active margin: the plate boundary at a subduction zone is buried several kilometres beneath a wedge of sediment:

What about spatially? As you can see from this map, they don't correspond all that well spatially either: they are commonly 100s of kilometres apart, sometimes more.

The difference, shaded grey in the map, is the continental shelf. It is sometimes emergent (e.g. at the end of the Permian, or during ice ages, when global sea-levels are low). It is sometimes, as now, flooded. The vertical change of ca. 100–250 m means a lateral change of 100s of km, because the shelf is almost flat.

OK, enough nit-picking, roughly speaking, why are the oceans on oceanic crust?

Continental crust is relatively thick and low density (ca. 2700 kg/m$^3$), compared to oceanic crust (25–70 km and ca. 2900 kg/m$^3$). So it 'floats' higher on the thin, dense mantle (7–10 km and ca. 3300 kg/m$^3$). When a new rift forms, it creates a depression and space for new oceanic-style crust. This is happening right now in the Gulf of California, the Baikal Rift Zone, and in the extensive East African Rift system. All of these places have large lakes and/or are extensively below sea-level. It's a divergent 'tear' in the continental crust, so intuitively we might expect a depression. As it fills with thin oceanic crust, the depression is maintained and eventually fills with ocean water.

Why is ocean crust so thin? I don't have a lot of expertise here, but I think it's determined by the relative rates of melting and cooling, and the heat balance at the ridge and subduction zones. There's a nice answer to this question on Reddit, complete with links. As insinuated in that thread, the thermo- and chemo-dynamics of the spreading centres and subduction zones are intimately related to the presence of the ocean, so together they make a complex system (indeed, the entire planet is a complex system), as @stali points out in his comments and answer.


What is "small layer thickness" defined as in terms of bulk Richardson number approaching gradient Richardson number?

Strictly speaking, $\lim_{\Delta z \to 0} Ri=Ri_b$. This is because the gradient Richardson number: $$Ri=\frac{\frac{g}{T_v}\frac{\partial \theta_v}{\partial z}}{\left(\frac{\partial U}{\partial z}\right)^2++\left(\frac{\partial V}{\partial z}\right)^2}$$ can be approximated as $$Ri \approx\frac{\frac{g}{T_v}\frac{\Delta \theta_e}{\Delta z}}{\left(\frac{\Delta U}{\Delta z}\right)^2++\left(\frac{\Delta V}{\Delta z}\right)^2} \tag{1}$$
which can be rewritten as the Bulk Richardson Number: $$Ri_b=\frac{\frac{g\Delta z \Delta \theta_v}{T_v}}{(\Delta U)^2+(\Delta V)^2} \tag{2}$$. The derivation of (2) from (1) is left as an exercise for the reader.


MERRA-2 Reanalysis data V and U wind are missing values over land at 1000 hPa pressure level

TL;DR: It is not a problem, it is a feature.

As it was pointed in the comments, 1000 hPa over land (and sometimes over ocean) is below the surface. MERRA is just fair enough not to put any values where they do not exist. Other reanalyses use some procedure to fill the gaps and make fields without holes. The procedure is reanalysis specific, and, can ususlly be found in corresponding technical manual. The gap-filled fields have little physical meaning anyway.

If the gaps do not make sense for you, 1000-hPa wind is, probably, not the field you need. E.g. if you are after near-surface wind, 10-m wind is more appropriate quantity.


Ground level ozone formation and NO2 dependence over time

I am unsure of the details of your dataset (length, temporal resolution, location, etc.)

For he one day time lag, it is easily explained. NO2 is consumed to produce ozone, so as NO2 decreases, O3 increases. However, for that reaction to occur, you need UV radiation. So as NO2 decreases, ozone increases.

For the fourth day lag, I would be a bit suspicious to take meaning out of this, due to my lack of knowledge on details of the dataset. For example, it could've been cloudy preventing the production of NO2 and ozone, but letting NO build up, such that when the sky cleared, the NO was allowed to photlyze, but that is just a guess.


What are Atmospheric Rossby Waves and how do they affect the weather?

Where to start....
If you take a look at midlatitude weather on any given day, you will find a pattern of upper tropospheric winds that look like this (source: NWS):
.
Notice how it looks like a wave? These are called Rossby waves. You may imagine that the jet stream is imbedded in the ups and downs of these pressure contours. If we take a look at a typical winter storm (here is a random storm from 2003):
Notice how wavy the 500 mb heights are? Don't they resemble the first figure?
Now you might say "I've seen those things and they definitely move west to east." This is true. That is because the prevailing wind is westerly (in the above examples). This can be shown in a mathematical analysis, though it should be noted that baroclinic Rossby waves (mostly in the midlatitudes) propagate slower than barotropic Rossby waves, which is what this analysis works on.
I can probably into more extensive detail about Rossby waves, but I'll just end here.


According to the online chapter Water Vapor (University of British Columbia), the two variables you ask about are defined as:

Absolute humidity

$$\rho_{v}=\frac{m_{water\ vapour}}{volume}$$

Liquid water content

$$\rho_{LWC}=\frac{m_{liquid\ water}}{volume}$$

The main difference is that absolute humidity measures the mass of water vapour and the LWC measures the mass of suspended or falling liquid water content in a unit volume of air. A handy definition linking the two terms is (from the linked document):

  LWC is the liquid-water analogy to the absolute
  humidity for water vapor.


Dependence of solar irradiation through the atmosphere on Sun's altitude

I believe you could use pyranometer data at various elevations to get a non-spectral measurement of the total irradiance received at the Earth's surface.  From here: http://en.wikipedia.org/wiki/Pyranometer

  A pyranometer is a type of actinometer used to measure broadband solar irradiance on a planar surface and is a sensor that is designed to measure the solar radiation flux density (W/m2) from a field of view of 180 degrees.
  Pyranometers are frequently used in meteorology, climatology, solar energy studies and building physics. They can be seen in many meteorological stations - typically installed horizontally and next to solar panels - typically mounted with the sensor surface in the plane of the panel.

If you want something more accurate, a pyrheliometer or radiometer is used.  From http://www.esrl.noaa.gov/gmd/grad/starmeas.html

  Direct solar irradiance is the solar radiation that passes directly though the atmosphere from the sun without being scattered or absorbed by the atmosphere. Typically it is measured on a surface that is kept normal to the direction of the center of the sun's disk. That surface is held normal to the sun's position by a solar tracker. Pyrheliometers are most commonly used to measure total direct solar irradiance. The most accurate measurements of this quantity are obtained from absolute cavity radiometers which serve as calibration standards and are being increasingly used operationally.


At what latitudes does daytime last exactly 24 hours once in the year?

The latitudes today are 66°33′46.1″ N and S, the Arctic and Antarctic Circles.

By definition, north of the Arctic circle, and south of the Antarctic circle, everywhere gets at least one day with no sunset, which I guess is what you mean by 'exactly 24 hours of daylight'?

From the linked article:

  North of the Arctic Circle, the sun is above the horizon for 24 continuous hours at least once per year (and therefore visible at midnight) and below the horizon for 24 continuous hours at least once per year (and therefore not visible at noon).


The process is carried out by solving an "inverse problem" and there are many ways to estimate the moment depending on the observable. For example if you have some measurements of ground deformation following the earthquake (using GPS/InSAR) then by combing a physics based model, with an optimizer, you can estimate the area/slip distribution that best explains the observations. Once you know the area/slip distribution then you can estimate the moment.

The physical models can be simple or complex (e.g., semi-analytical or fully numerical). Same goes for the optimizer (local or global). For computationally expensive numerical models global optimization is typically not feasible. For local optimization you need a 'reasonable' initial model.


How would pesticide vapor drift behave near a valley?

While @Gordon Stanger gave an overall perspective about pesticides in general in his answer you can deduce some key points about the micrometeorological conditions of the area.

Assuming pesticides as relatively large aerosol particles/droplets spayed quite close to ground they are mainly dry deposited to surfaces. If your house is as close to the pesticide spaying areas as your schematic implies, you might have a problem (assuming pesticides are dangerous to you, more in @Gordon Stangers answer) only if during the spraying air gets trapped into the valley.

Assuming the spraying is only done in daytime and summertime the chances of an inversion in the valley are smaller and they would only stabilize the air preventing mixing with your valley air and pesticide air.

Strong winds (if the location is near a coast (probable sea breeze) or it's otherwise known to be windy) might carry some pesticides to your direction, but overall adding vertical mixing dramatically lowering the average concentrations.

Your most worst case scenario is if calm (not windy) very sunny days are very often. Sun will in different times of days heat at least either of the slopes of the valley causing air to rise on that side. Replacing air is sucked from the other side creating a steady flow from pesticide rich agricultural areas to your valley. Pesticide being assumed a large aerosol will deposit most likely in the valley (if not in the bottom then in the drafts uphill).

Also rainy weather is good for you as the pesticides will most likely wet deposit near their source.


Why did the Persian Gulf shrink during the influence of Ancient Mesopotamia?

There has been lots of works trying to reconstruct the evolution of the Gulf shoreline through time. They do not agree on the exact same dates (see this review by Sissakian et al. 2020), but they generally agree that there was first a transgression (sea level rise) episode following the last ice age, then a regression (sea level drop). Reasons invoked to explain the regression are (not mutually exclusive):

Change in climate. The sea level peaked around the post-glacial climatic optimum. After that, the climate got cooler, which means more ice at the poles and less water in the seas.
Sediment filling of the Mesopotamian delta. The Euphrates and the Tigris carry a lot a sediments, which progressively accumulate in the lowlands, making the Gulf shoreline advance (seaward).
Neotectonics. There are evidence for anticline growth under the area, which could have contributed to its rise above sea level. This activity also changed river paths, which could have promoted point 2.


How long does it take to refresh the entire water supply in the Earth's atmosphere?

The term you are looking for is called residence time or residency time.  This UCAR Science article suggests it is about 9 days on average.  This should be verifiable by dividing the average global precipitable water by the average global daily precipitation.

I don't see any reason why the residency time of water would offer any hint of weather predictability limits. If the equations to predict evapotranspiration used in forecast models have skill, shouldn't the 9 days not be the limit (and how limiting a factor it is would depend upon how skillful those equations are)? The residence times of vehicles on roadways is probably near/less than an hour, yet we can forecast traffic quite reasonably well in advanced in at least many circumstances (and that's prone to the much more volatile nature of human choice/error)!

Indeed I think the "residence time" of energy in the lower troposphere, if such an idea even has sense, may well be shorter than a day for the Earth given the continual heavy IR absorption and reemission rates in the atmosphere, and the dominant input being solar energy. But we can forecast much longer periods than that well.  We have great understanding of insolation into the Earth-air system, and then quite solid skill at predicting its transfer, even with the complexity of clouds and other feedbacks.  So we can outdo such a timescale even if energy passes through the system indeed quite quickly.  Likewise, there seems to be no reason for the 9 days to be a particularly meaningful limit on the atmosphere.


Does bathymetry affect ocean topography/height?

Oceanic topography of the sea surface $\zeta$ can be defined as the height of the sea surface relative to a particular level surface, the geoid. The geoid to be the level surface that coincided with the surface of the ocean at rest (a list of geoids with application to oceanography can be found in Talone et al., 2014).

Variations in sea surface height (topography) are due to processes that result in ocean motion: ocean currents, tides, and changes in barometric pressure from the inverted barometer effect. As a result, we usually call it "dynamic topography" or "dynamic height". As geoid undulations are of order 100 times larger than the dynamic height, the shape of the sea surface is dominated by local geoid variations caused by gravity with the effect of the currents being much smaller.

In the image you provide what you have is "dynamic height" and thus is a deviation from the geoid and the result of oceanic currents. By knowing the dynamic height, we can get an idea of the surface geostrophic current:
$\mathrm{u_s= − {g\over f} {\delta\zeta\over\delta y}}$; $\mathrm{v_s= − {g\over f} { \delta\zeta\over\delta x}}$ where f is the Coriolis parameter,  g is gravity, and $\zeta$ is the height of the sea surface above the level surface (geoid).

Now, there is a direct effect between currents and bathymetry that sometimes is referred to as Taylor columns. The Taylor-Proudman theorem enforces that vertical columns of fluid move along contours of constant fluid depth. The basic idea behind this is that in order to conserve vorticity, fluid parcels tend to follow bathymetric contours (isobaths). So to answer your question, bathymetry affects ocean topography indirectly by affecting ocean currents.


Would there still be wind if Earth had no water?

I wouldn't say water is naturally cooler than air.  What I would say is that water has a higher heat capacity than air.  This means it takes more energy to affect the same increase in temperature and conversely it takes water longer to cool down than air.  You can see this at night near bodies of water when the sea breeze changes to a land breeze as the land becomes cooler than the water - water temperatures tend to be stable across diurnal cycles.

I would also contest the statement that water cools the air.  Water does both heating and cooling.  When water evaporates into air, the air cools.  However take a look at any thunderstorm you see -- that is water causing heating as it condenses and freezes.  Water on the surface can also contribute to both heating and cooling.  During the day the cool water surface will have a heat flux that cools the air while at night the opposite may be true.  This depends on the air temperature and the SST.

Now on to your question, yes, there would still be wind if there were no water.  The energy that drives the wind is differential solar heating at the earths surface.  Variations in the surface topography and the shape of the earth mean that the solar flux isn't constant across the earth.  As long as we have a sun we will have surface pressure differences and wind.  Without water we would also see a stronger equator-to-pole temperature gradient (look at temperature variations right now on continents versus open ocean).  This would result in stronger winds that we see today.


is there any technique developed that can estimate depth of bedrock?

A small scale seismic survey as well.

I remember as students we found the water table using a 100m refraction line and a sledge hammer sound source. Scale that up from ~5m to 100m you're going to need a longer line and a larger sound source. Reflection might also become more convenient. Still a lot smaller than a typical 2d survey line though!


What was the density and composition of Earth's atmosphere during the Cretaceous warmest period?

Recent analysis of the contents of air bubbles preserved in prehistoric amber reveal the oxygen composition to be 32% back then compared to just under 21% today.  These tiny bubbles have remained trapped in these amber samples for about 80 million years, which dates them well into the Cretaceous era when dinosaurs and other huge creatures roamed the earth.

Said analysis also revealed that nitrogen made up the rest save 1% for Argon, CO2, and other trace gases. The percentage of CO2 was not specifically stated but mentioned as similar oxygen to CO2 ratio as today's atmosphere.  Whether the total air pressure air density of the atmosphere was greater back then is not mentioned, most likely because this would be difficult to ascertain from the samples.

An atmosphere 50% richer in oxygen but at the same atmospheric pressure and density at sea level as today would have allowed land animals to get by with a lower lungs to total body mass ratio and thus allowed the existence of extra massive creatures such as dinosaurs.

I assert that the asteroid that struck the Yucatan area 65 million years ago caused most of the forests and other terrestrial vegetation to ignite into flames.  The whole earth would have been on fire, at the end of which the oxygen levels were depleted to what they are today.  This is confirmed by analysis amber air bubbles from 40 million years ago, post asteroid impact, revealing an atmospheric composition and oxygen levels closer to today's.

Dinosaurs and other massive terrestrial animals could not then make a comeback since the lower oxygen content of the atmosphere would have restricted metabolism to maintain massive body sizes.


Here is how I would do this. ECMWF's ECCODES has a tool called bufr_ls and you can use that to  write the contents of that output to a text file. Then I would read that file into a scripting language such as Python and write out the contents as a GRIB file using PyGrib. You can also explore the output of bufr_dump and convert that also to GRIB if you wish. The full list of all BUFR format tools from ecCodes is given in this link BUFR tools
For more information regarding either of those softwares you can reach out to their support network and then get your doubts resolved.

UPDATE

If you want a 100 % Pythonic solution then you can try  Python-Bufr which basically wraps ECMWF BUFR or use this python BUFR library - bufrpy


Would climate change result in an increase in seismic activities?

Dilation of the Earth's surface due to atmospheric temperature changes will be negligible due to the amount of temperature increase.
Stronger precipitation will not directly lead to an increase in seismic activity. The force of the raindrops will be too small, even over a prolonged periods of time. If stronger precipitation were to occur, the most likely result will be an increase in soil erosion and landslides.
The reduction in glacial mass and the increase in water depth will change ground surface stresses. Where there will be an increase in the depth of water there will an increase in the overburden pressure produced by the water. This may cause an increase in localized seismic activity in some areas.
The loss of glacial mass will lead to post-glacial rebound in affected areas, predominantly: Antarctica, Greenland, Canada, Alaska. As the affected areas adjust to the lack, or reduction, of overbearing (overburden) pressure previously supplied by the glacial ice there will be an increase in seismic activity in those regions.


Yes, you can increase evaporation by spraying the sea water as an aerosol because this increases surface area. It's the same with fresh water too, but why would you want to do it? It wouldn't have any noticeable effect on the humidity of the general area. The only useful effect that I can see concerns fresh water only. Spraying the water from a pond or small lake as fine droplets would increase the oxygen content and benefit the fish. Hot weather depletes the oxygen in the water and sometimes fish become distressed, so if you want to save your valuable coy carp it might be a good idea. In the ocean it doesn't work, the sea is too vast.


Short answer, its not well studied. It is most likely a diagenic process just because that is the source of most fractures in rock.

https://www.sciencedirect.com/science/article/abs/pii/S0166516297000128

https://www.sciencedirect.com/science/article/pii/S1674775514000341


Any site for monitoring equatorial oceanic waves?

There are a few sea surface height datasets available on PO.DAAC (the Physical Oceanography Distributed Active Archive Center), but this one seems to be (near-)real-time and global: the SARAL Near-Real-Time Value-added Operational Geophysical Data Record Sea Surface Height Anomaly.
It was launched in 2013 so there is just 3 years of data so far but it should help I think.

Similarly you have a few current datasets such as the OSCAR 1 degree ocean surface currents dataset which was launched in 1992.

These are all raw datasets though, so you'll have to do the data processing and the plotting yourself.

The altimetry data provides a good way of looking at waves. Apart from SARAL, AVISO provides high quality, remotely sensed, gridded and raw altimetry data.


Why were both the sun and the moon red today?

Smoke.  There was significant smoke across the USA, which attenuated the light from the sun/moon due to increased scattering.  The smoke particles effectively cause the light to reflect in different directions, so you see more colors.

See below for the HMS Smoke Polygons for the day, which clearly shows smoke over your region from the intense smoke/wildfire activity in the Pacific Northwest.  You can also see the NASA Worldview composite of VIIRS visible imagery for the day, with fire locations in red.


First of all, a plateau as an area of flat topography which stands at higher elevation than the surrounding region; it does not need to be at high elevation in absolute terms. Indeed, there are plateaux below sea level.

There are several different processes at the origin of the plateaux in the map you link.

Some, such as the Deccan and the Columbia plateau, are the results of infill of volcanic rocks in an accomodation space during voluminous volcanic eruptions, called "flood basalts". These flood basalts effectively flow into topographic depressions, thus flattening the topography and resulting in a plateau.
Note that there are also oceanic plateaux which are formed by large magma outpours- they are usually below sea level. Examples of this are the Caribbean Oceanic Plateau and the Ontong-Java plateau.

Other plateaux such as the Altiplano and Loess plateau appear to be a result of basin infill by mainly sedimentary processes, either by water or wind transport. Past erosion removed material from topographic highs and dumped it in topographic lows, thus flattening out the relief. This is effectively a peneplenation process operating locally.

Although the high elevation of the Tibetan plateau is undoubtedly due to tectonic uplift, the cause of flat topography appears is likely to reflect relief reduction by combined erosion and deposition as above. It is unclear whether this was an ancient peneplain which was pushed upwards, or a more recent feature.


How often do king tides (perigean spring tides) occur?

The perigean spring tides arise when the spring tide occurs during the time of shortest distance between Moon and Earth. As the full moon on October 15-16, 2016 occurred near perigee, then it can be consider a "supermoon" even if the difference in Moon size was not that great. The fact is that the October full moon was not even the largest of the year; that will occur in November:

  The November 14, 2016 full moon – closest and largest full moon is 2016 – will also be the largest full moon thus far in the 21st century (2001 to 2100). It’ll be the closest encounter between the Earth and moon until November 25, 2034.

Thus, the mid-October was exceptional in a sense, but will be surpassed by the  November event.

With regard to the effect on tides, the combination of the $M_2$ and $S_2$ tidal constituents gives rise to the spring/neap cycle. Meanwhile, the $N_2$ tidal constituent arises from the fluctuating distance of the Moon from Earth and its frequency is 1 cycle/month less than that of $M_2$ and 3 cycles/month less than that of $S_2$.

We can resynthesize a time series of tidal elevation  based on only these three tidal constituents ($M_2$, $S_2$, and $N_2$). The resulting time series of amplitudes has an envelop that shows the size of the spring tides. As can be seen in the figure, even including only these three constituents, the resulting variability in the size of the spring tides (12 years shown) is pretty high. The problem is how to define "king tides". There are some spring tides that are larger than others, but even among the largest there is variability. This is where the uncertainty on the definition of the recurrence interval of the "king tides" comes from. Ultimately, it seems that having ~2 peaks ("king tides") per year is a good approximation. Including 3 constituents is a significant simplification and the entire series gets more complicated when additional constituents are included and defining a "king tide" is also more difficult.


Is San Andreas fault horizontal or vertical?

See the image below. In the picture, the San Andreas Fault dip is nearly 90 degrees or exactly vertical; The strike is pointing North.

Most normal faults and reverse faults (such as the Sierra Madre) are not vertical, but rather dip in either direction. (In the picture the Sierra Madre appears to have a dip of about 45 degrees).

In real life, the dip of the San Andreas is not perfectly vertical, but is variable, depending on where in California you are.

Strike and dip can be measured using a Brutton Compass.


What geologic features could this video game environment be modeled from, and how do they form?

Looking at the landscape, it almost appears to be a highland, with steep valleys carved by a misty river - which suggests possible waterfalls.  I am reminded of Victoria Falls, on the border of Zimbabwe and Zambia (part of the landscape pictured below)

Image source

The geological processes that formed these features is summarised in the webpage The Geology of Victoria Falls as a series of tectonic and erosional activity over an ancient basaltic bedrock, forming a series of near parallel gorges (shown below and from the webpage linked before).


Relationship between pressure, temperature and density in meterology

'Locally' and 'synoptically' are conflicting adjectives. Synoptic means overall, or large horizontal scale- think thousands of kilometers.

You are right on some accounts. Synoptically, pressure doesn't change much, depending on your qualitative definition of 'much.' On a percent scale or day-to-day experience, absolute temperature fluctuates more than pressure. But the gap of those fluctuations result in changes of density, leading to changes in buoyancy.

The vertical momentum equation :$$\frac{\partial w}{\partial t}+(\vec{v}\cdot\nabla_H)w+w\frac{\partial w}{\partial z}=-\frac{1}{\rho}\frac{\partial P}{\partial z}- g + \nabla^2w$$ when applied to synoptic scales can be treated as approximately hydrostatic: $$\frac{\partial P}{\partial z}=-\rho g$$.
From this equation, as well as the ideal gas law, the hypsometric equation may be derived.

Although the vertical gradient of pressure is large, gravity is also large, which explains why the atmosphere is not lost to space and vertical motions aren't usually large in horizontal scale.

Using said hypsometric equation, it can be shown that changes in vertically-averaged temperature lead to synoptic scale changes in surface pressure.


Why is hydrogen formation in serpentinisation an exothermic reaction?

Under normal circumstances your suggestion might be correct, but bear in mind that the serpentinization reaction takes place under very negative Eh, and very high pH conditions (pH 12 or more). This abnormal combination is right on the boundary of water-hydrogen stability conditions. In hyperalkaline springs, which result from the reaction water + peridotite = serpentine, there is hardly a free molecule of oxygen left in solution.


Is there any possible future for high energy geophysics? If so how it is going to revolutionize our knowledge about Earth's interior?

I don't think neutrinos will be much good for mapping the interior of the Earth, the reason being that they rarely interact with matter and are said to be able to pass through 11 light years of solid lead without being stopped (though I would take that claim with a pinch of salt). However, so many pass through the Earth from the other side that  a tiny number will interact and muons from these interactions have been detected coming upward through the ocean!

Muons seem to be more useful, and have already been used to detect secret chambers in the Great Pyramid. They undoubtedly have applications to volcanology, but don't have the penetration powers of neutrinos. Muons are very transient charged particles which decay in a minute fraction of a second to become electrons or positrons. Because of their ultra-brief lifetime and electric charge they can't penetrate very far, hundreds of metres rather than hundreds of miles, so although they are a useful tool I don't think they will revolutionise geology in general. They might revolutionise the more limited field of geophysics.

Cosmic rays are high energy protons and atomic nuclei originating in the sun and other stars, sometimes in supernovae, but their energy is very variable. Most are stopped high in the atmosphere, but their secondary radiations, which include muons, often reach the surface of he Earth. Owing to their randomness and unpredictability, they are unlikely to prove very useful.


How do scientists reconstruct pre Cretaceous continent if all plates that are currently left are younger than Cretaceous?

You forgot about continents

First of all, it's necessary to point out the false premise in your question: It is not true that "all plates that are currently left are younger than Cretaceous".  There is a near-continuous record of rocks stretching all the way back to the Hadean Eon 4 billion years ago.  And there are older crystals called zircons that are found as inclusions in younger rocks.

The thing is, these rocks are on land, part of continental crust. Your question seems to be unaware of the existence of  continental crust. Of course, since you're not currently sitting at the bottom of the ocean, you're on top of continental crust right now. Most of the big tectonic plates are part oceanic and part continental.

Continents have been built up little by little over geological time. Their rocks are a mixed-up jigsaw puzzle of various types and ages. It's the geologist's job to figure out how those pieces fit together.

Here's just a taste, and it doesn't even show the complexity of the puzzle in North America by a long shot:

(courtesy of United States Geological Survey, via Wikimedia Commons)

It is true that the oceanic plates are mostly destroyed by subduction, but the oceanic crust has to go beneath something, and that's often a continent. Besides, subduction helps make continents grow:

not all of the rock is subducted: some seafloor sediments are scraped off and piled against continental margins
The top layers of rock that are subducted melt, and the melted rock bubbles its way up through the overlying crust, producing plutons and volcanic arcs. Sometimes these are on continents (such as the Cascades and Andes) so their rocks directly add mass to them.
When the volcanoes are out in the ocean, the subduction process pulls them into continents and they get cemented to the edge. Sometimes they form little mini- continents (such as Japan and New Zealand).

The oldest oceanic crust currently at the seafloor is in the eastern Mediterranean. In an article in Nature Geoscience Roi Granot of Ben-Gurion University of the Negev suggests that the [Herodotus Basin] is a remnant of ancient Tethys Ocean, having formed up to 340 Ma during the Early Carboniferous period. Most oceanic crust is 200 million years old (Jurassic) or younger.  They're an important part of putting the puzzle together, but as I stated at the beginning of my answer, the geological record is much older, because of continental rocks.

Finally, there is really old oceanic crust in the form of ophiolites, which are bits of oceanic crust that have been incorporated into continents.  Since they're no longer part of the oceanic conveyor belt, some can be quite old. The oldest is about 3.8 billion years old.


What are the temperature and pressure conditions an ROV design would have to deal with to descend to 4000m?

For pressure, you can use something simple like the fact that pressure increases by around 1 atm with each 10 m of water depth. You can also use some very simple calculators that assume a constant density (not a bad assumption) and gives you the different unit conversion.

For temperature, it varies a fair amount depending on where in the ocean. The average vertical profile for mid-latitudes, looks something like:

 (Windows to the Universe).

If you need more detail temperature information for a specific location, you can look into the World Ocean Atlas, which provides observed temperature, salinity (and in some cases other parameters like ph) for the entire world.

My suggestion is that, if you need any specific information, you might ask the people at the Woods Hole Oceanographic Institution (for instance) that deal with this kind of problem on a regular basis.


North Atlantic Oscillation (NAO) future prediction - Academic papers?

A good start is the article by Goodkin et al. (2008) that relates past fluctuations of NAO to climate variability and argues that in the late 20th century NAO changes are much more dramatic as a result of enhanced energy (temperature) in the northern hemisphere. (Source WHOI)

Visbeck et al. (2001) describe the complex relationship between NAO and climate change associated with greenhouse gases:

  Because global average temperatures are dominated by temperature variability over the northern land masses, a significant fraction of the recent warming trend in global surface temperatures can be explained as a response to observed changes in atmospheric circulation. Because the NAO is a natural mode of the atmosphere, one could argue that much of the recent warming is not related to the build-up of greenhouse gases in the atmosphere over the past century. This viewpoint, however, ignores the possibility that anthropogenic climate change might influence modes of natural variability, perhaps making it more likely that one phase of the NAO is preferred over the other.

As for predictions of the future effects cause by emission scenarios, that seems to be an ongoing topic of research. A couple of good starting point might be Yeager et al. (2012) and the book chapter by Hurrell et al. (2013) on the effects of climate change on NAO.


Is the concept of seismogenic zone still relevant after the 2011 Japan earthquake?

Tohoku is the seismogenic zone, the asperity model explained this small repeating earthquake well. It was said massive earthquake will occur in Nankai Trough. As their expectation was wrong, [Kato and Yoshida, 2011],[Hori and Miyazaki, 2011] created new models.
ref Notice japanese source.

Here is new model of Sansoken(National institute of advanced industrial science and technology). In this model, asperity model is still alive.


Crystallization path of diopside-wollastonite-silica systems

The diopside–wollastonite–silica system ($\ce{CaMgSi2O6-CaSiO3-SiO2}$) was never studied for crystallisation paths in igneous systems. This is not a system encountered in terrestrial magmas, so no one bothered.

However, it was studied as part of a more general lime–magnesia–silica ($\ce{CaO-MgO-SiO2}$) system by material scientists and they came up with this:

Source: Steel Data

You can see small fields for "Diop" and "wolla" slightly above the centre of the diagram. This is not an easy diagram though, and it's of limited use to geologists. If you're studying ternary systems I recommend you go through these instead: Ternary Phase Diagrams


Why do rivers have 'wells' in mountains?

The presence of water underground has nothing to do with sea level in mountainous country.

When rain fails on a mountain, or snow falls on a mountain and the snow eventually melts, the water from the rain or snow melt mostly travels downhill via rivers to the sea.

In getting to a river some of the water will fall on the ground. In places where the ground is covered by soil, water can travel through the soil via the pore spaces between the grains of soil. Similarly if porous rock, such as sandstone lies beneath the soil water can travel through the pores in the rock.

If a layer of impervious rock lies under the porous rock or soil, the water cannot move downwards, due to gravity, any further. This can lead to water accumulating in the soil or porous rock and saturating the soil or rock. In such situations an aquifer can form. The top of the saturated zone in an aquifer is called a water table.

The ground beneath a river is saturated and the surface of the river shows the water table exposed to atmosphere. Thus in mountainous regions the ground beneath rivers will be saturated and capable of supporting a well developed from the bank of a river.


Did an impact crater influence the formation of uranium deposits in South Australia?

Sort answer: from what we already know, NO.
A comet (or asteroid) impact can influence mineral composition near the crater (high pressure and temperature) but this impact is small and diminishes quickly in respect of the radius. There is no documented quantitative difference of a mineral deposit versus its radius from an impact crater (not in cm and meters scale, but in km scale). Thus, we cannot assume that there is correlation between uranium deposits of Australia (or any other country) and impact craters.
Uranium deposits can be formed in many ways:
As you can see from the list, 7 out of 15 ways of uranium formation, occur in Australia. None of them due to comet impact.

1. Intrusive deposits
In South Australia, Radium Hill was mined 1954-62, and large bodies of low-grade mineralisation occur in the Olary Province.

2. Granite-related deposits
The dimensions of the openings have a wide range, from the massive veins of pitchblende at Jachymov deposit (Czech Republic), to the narrow pitchblende-filled cracks, faults and fissures in some of the ore bodies in Europe, Canada and Australia.

3. Polymetallic iron-oxide breccia complex deposits

4. Volcanic-related deposits
In Australia, they are minor – Ben Lomond and Maureen in Qld are the most significant.

5. Metasomatite deposits
Valhalla and Skal (Australia)

6. Metamorphite deposits

7. Proterozoic unconformity deposits
Australia (the Alligator Rivers region in the Pine Creek Geosyncline, NT and Rudall River area, WA).

8. Collapse breccia pipe deposits

9. Sandstone deposits
Basal channel deposits – wide channels filled with permeable sediments. Examples are Dalur and Khiagda (Russia) and Beverley and Honeymoon (South Australia).
Mafic dykes or sills in Proterozoic sandstones – Examples at Matoush (Canada) and Westmoreland (Australia).

10. Palaeo-quartz-pebble conglomerate deposits

11. Surficial deposits

12. Lignite-coal
Mulga Rock (Western Australia).

13. Carbonate deposits

14. Phosphate deposits

15. Black shale deposits


What factors explain mountain glacier retreat variability?

There is indeed a large variability in glacier behavior, even between neighboring ones. If you look harder, you will even find advancing glaciers right beside others receding quickly. There are multiple factors that can explain such variability, I will list the most important ones:

Orographic control: A climatic change can affect differently neighbouring glaciers. If the wind, air moisture or temperature changes, the corresponding changes in precipitation or solar irradiation can vary on different areas of a mountain massif due to its topography, therefore affecting differently each glacier. A classic and illustrative example is the orographic precipitation illustrated by the figure below. It explains why the windward side of a mountain range could have bigger glaciers than the other. Now, in the case of an increase in -let's say- temperature and air moisture content (that usually come together), the associated  increase in precipitation might benefit snow accumulation in one side more than the other, while the temperature will affect both more or less in the same way. Leading to leeward  glaciers receding faster than windward ones.

Topographic controls: All glaciers flow downhill, and the speed of such flow depends on the resistance the bedrock, valley walls, moraines, etc. A glacier that is in steady state (i.e. not advancing nor receding) is in balance between snow accumulation in its upper reaches and melting in its lower areas. Even if there is no changes in accumulation or melting, this balance can be broken if the speed of the glacier changes. If the ice is taken faster from its cold head to the warm front, that will increase the melting and more snow would be needed to offset the additional melting.
Most of the resistance to flow is provided by constrictions of the valley walls or protrusions of the bed. As in the figure below (from here), taking a floating ice tongue as example (a.k.a. ice shelf) where most of the resistance to flow comes from the bed protrusion below the "ice rise", in this case such protrusion is called a "pinning point".
Now, going back to your question: Even if two glaciers that are receding at the same rates, eventually one could recede behind a constriction, therefore its speed will increase, pushing it further out of balance, so it will start loosing mass faster than its neighbor and at some point that will show up as a more pronounced shrinking in images like the ones you were studying.
In the case of ice shelves (like the one in the figure), loosing contact with a pinning point can lead to the collapse and breakup of large sections of the floating tongue in very quick and dramatic events.

Reaction time scales: Neighbouring glaciers can have huge differences in mass. And that means that they don't react with the same speed environmental changes. In a very small glacier, you will see advance after a few years of high accumulation. However, in a very large glacier, a few years of high accumulation doesn't make much of a difference. And the glacier can still recede after such events, perhaps due to a few decades of low accumulation that happen a hundred years ago.
Area is not volume: What you see in the images are changes in area not volume. So even if two glaciers are loosing the same amount of mass per year. If one is thinner than the other, you will see that the thicker one shrink less that the other.
Hypsometry: It  refers to the distribution of values of surface elevation of a glacier. For example if two of the glaciers you are observing span from 1,500 to 2,500m of elevation, but one of them have 90% of its surface above 2,000m of elevation, and the other only a 30%. You will observe that a change in temperature that push the average freezing line from 1,800m to 2,000m will affect the second glacier much more than the first, because it will suffer a larger increase in the fraction of its surface exposed to melting temperatures.
Surging glaciers: Some glaciers undergo what is call a glacial surges. They show a cyclical behavior in which they advance very quick over few years and then recede slowly over decades to then start over again. I won't go in detail about this process that is very complex and still poorly understood. But in the images you observe, they might be some variability also to the presences of glacier surges.

Other factors could be more complex weather redistribution patterns, bed topography, bedrock lithology, basin divide migration, frontal wasting (calving) for lake and marine terminating glaciers, etc.


How do perennial rivers in high alpine areas maintain year round flows?

Not claiming to be an expert, but I think the process you're referring to is called pressure melt. This effect occurs when the pressure at the bottom of the glacier is high enough to either shift the melting point slightly (melting point decreases by 0.7$\,^{\circ}$C per km of ice according to this link, which provides some more background information on processes and conditions inside glaciers), which combined with frictional energy from the constant movement of the glacier, and, in some regions, geothermal energy causes a constant supply of liquid water. Since these discharges are usually concentrated under the ice (also the principle behind the formation of eskers), leading to large discharges at a few emergence points with enough energy to prevent them from freezing over.


How do cold air masses reach South America?

The Pacific coast of South America is affected by the Humboldt Current, a wind-driven "upwelling" system running counterclockwise that is cold and windy but nutrient rich..

The "six o'clock" position indeed touches Antarctica, and then the right edge of the "clock" reaches Chile, Peru, Ecuador, and Colombia, as far north as the Galapagos Islands near the equator, making those areas cooler than equivalent latitudes on the Atlantic coast.

The reason the currents don't "originate" in the Antarctica is because they are part of a circular system that spans a whole ocean in the southern hemisphere. But they "make stops" there.

The ocean and atmosphere mutually interact to create a "coupled" system that brings about the so-called ENSO El Nino (La Nina) Southern Oscillation, with its characteristic weather changes.


Could we sequester CO$_2$ by dumping forests in deep oceans?

So, there's really two questions here.

1) if we were to take wood and store it in a way that prevents decomposition, would this help reduce atmospheric CO2? and

2) Would sinking it into the bottom of an ocean trench achieve this?

So, first things first, yes removing wood from the contemporary carbon cycle does reduce atmospheric CO2. We already do this (at least temporarily) by using timber for making things - depending on the type of product this has a half-life of anything from a couple of years (paper or biomass fuel) to about 50 (for sawlogs). You can achieve a similar effect by planting new forests - so carbon is locked up in living biomass.

We could come up with a more permanent solution, and this would have to be economic (and not require more CO2 emissions to accomplish than we saved in the first place). Current research is looking at sequestration of carbon as charcoal (as this is more biologically stable than wood which is a source of food for a lot of species). This can either be spread on the land as biochar, or I suppose buried terrestrially - I'm thinking of abandoned coal mines.

I'm not aware of deep sea storage as a widely considered option, and I suspect that this is mainly due to the techno-economic cost, and lack of research - the debate is still ongoing for many other more established carbon sequestration technologies. I don't believe there has been much investigation into the stability of wood in deep water (though it lasts for thousands of years in anoxic peat bog conditions - so I see no obvious reason why it wouldn't work).


It looks like a submarine canyon incised into the seafloor and shelf by repeated sediment "flushing". Given the location, earthquakes probably flush huge quantities of sediments from the low angle plains to the north, through the canyons, and into the abyssal plain to the south. You might find these canyons in any tectonically active seafloor that sees heavy sediment loading from, say, a mountainous tropical region. This one's not that big, compared to New Zealand's Hikurangi Channel, at nearly 700 km.
There's another one off the SE coast of Hokkaido Island. What, precisely, locally controls the formation of these canyons is an interesting question.


Would ultrasound be a valid method of mapping ocean floors given the perceived "gel" is ocean water?

It seems that attenuation is much greater at ultrasound frequencies:
50 khz   12-15 dB/km
0.5khz   0.024 dB/km

It depends on what distance and resolution you need.


Thermohaline: Why is cold and dense seawater salty when warm water holds more dissolved salts?

Warm water does hold more salt - at saturation, but seawater isn't even close to saturation. Surface sea water gets warm, starts to evaporate (hence clouds) and therefore gets denser. So it sinks to the ocean floor, where it cools down to about 4 deg Celsius, and gets denser still. But it still is a very long way from being saturated with salt, so 'how much salt the water can hold' doesn't come into it.


I believe it is metamorphic due to the absence of crystals that can indicate ignious rock, and the absence of particles that would show it as a sedimentary rock. You can make an educated guess by folowing the advice of the website Rock Identification Made Easy


On what basics, can scientists predict the effects of climate change?

Climate science seems to be as relevant as other types of science. It's just that it has been organized ridiculed after the formation of IPCC in the 80's. It has a lot of heritage from physics and there are a lot of signs of a climate emergency.

Your question is not fully clear. Some effects are impossible to predict in detail while other is not. Down a prediction of the global temperature and the concentration of atmospheric CO₂ made by ExxonMobile's researcher 1980.


What are the best maps, if any, we have of the convection cells in the Earth's mantle?

If you're looking for a cool, well detailed map of convection cells that looks like a modern weather map....forget it. What you're looking for has been notoriously difficult to produce, if not impossible. Even the most advanced seismic tomography techniques using seismic wavespeeds can only resolve mantle "features" thousands of kilometers in scale, but really, only in the X-Y plane. These techniques do a poor job of resolving anything in the Z plane.

Even the locations of convection cell boundaries appears harder to find than theory suggests. Currently, the influence of convection boundaries has been mapped from the surface elevations of oceanic plates, but those maps look like odd "heat maps" indicating where oceanic crust has domed up beneath upward mantle flow. No vertical flow lines boundaries are even remotely suggested with these two-dimensional maps. You can read the actual paper published in Nature, 2016 here: Global dynamic topography observations reveal limited influence of large-scale mantle flow


What is the difference between a high-resolution model and a regular model run?

High resolution means that the grid mesh the model uses is fine, or put another way, $dx$, $dy$, $dz$, and $dt$ are small numbers.  A model like the HRRR uses a horizontal resolution of 3 km, whereas some of the older regional models used horizontal resolutions of 30 km (though even the NAM is using 5 km these days).  Comparing resolutions to GFS and ECMWF models is a bit less straightforward because those models solve in a spherical coordinate system using spectral methods, and resolution will vary with latitude).

Higher horizontal grid resolution also implies higher vertical resolution and a smaller timestep.  The vertical resolution will be a consequence of wanting to avoid large aspect ratios in your grid box and the smaller timestep follows from the need for numerical stability (see CFL criterion).  The biggest direct result of the increased resolution and decreased timestep are increased memory and drastically increased computational requirements.  Because of this, operational forecast model resolutions will be limited by how long is acceptable for the model to run before output is available, which is a function of the supercomputer crunching the numbers.  You will generally find much higher resolutions in non-forecast research settings than operationally.  For example, I simulate supercell thunderstorms with 250 m horizontal resolution, but I can also spare an entire day to simulate a few hours whereas an operational model only has a few hours to simulate many days in a much larger domain than I use.

I don't believe there is a specific requirement to call a model "high resolution" and I think you'll find that the implied resolutions will be quite different between a climate modeler and a mesoscale modeler.

Differences in accuracy in higher resolution models generally boils down to resolving more of the physics explicitly.  A model running with 30 km resolution cannot resolve convection (thunderstorms), and must parameterize this as a sub-gridscale effect.  You might see terms like "cloud resolving" applied to high resolution models because of this.  A model running at 3 km resolution will be able to explicitly resolve convection.  A large eddy simulation (using filtered Navier-Stokes equations) will be limited to resolving eddies on a scale based on the grid resolution, and will parameterize the smaller scales.  Please see this paper1 for further discussion on the impact of resolution on resolving deep moist convection.

Finally, the data going into the model will make a difference (weather is chaotic and extremely sensitive to the initial conditions).  The HRRR is initialized from the RAP with a data assimilation period for observed radar.  RAP is currently a 13 km model but is moving to 3 km this summer. RAP gets its background fields from GFS and assimilates quite a bit of data on top of that.  While the smaller grid boxes help capture more of the physics, the quality of the data fed into the model is also helping quite a bit with accuracy because it improves the initial conditions.

Bryan, George H., John C. Wyngaard, J. Michael Fritsch, 2003: Resolution Requirements for the Simulation of Deep Moist Convection. Mon. Wea. Rev., 131, 2394–2416.
doi: http://dx.doi.org/10.1175/1520-0493(2003)131<2394:RRFTSO>2.0.CO;2


How can I learn to make mesoscale/synoptic analyses of major weather events?

You're definitely on the right path with wanting to dig into raw data yourself.  RAP has always been a pretty solid source of useful basic data.

But in terms of making sense of the data, it indeed will take some practice. You can feel like you're not getting it at all, but suddenly pieces will start to click, much like riding a bike.

Basically, you need to start building from those that know these things.  As such, one good insight can be in reading NWS forecast discussions, which you can find among the rich data at kamala.cod.edu or in one big set at this NWS link.

But, at least in terms of storms, I think the place to start has to be the same place that the CWG article relied upon: the Storm Prediction Center.  Specifically:

Convective outlooks will explain the day's weather picture and large key features
Mesoscale discussions offer insight into the finer details that make all the difference, ones which even the most seasoned meteorologists may not always recognize.
Then the mesoanalysis tool allows you to dig more into the data yourself and see overlays of a deep variety of parameters.  But the tool that may be right down your alley may be the composite map generator tool, which allows you to combine just the noteworthy parts of the key elements onto one image and see how they line up.
And then the Severe Weather Events Archive allows you to dig into a great deal of past events, and the Outbreaks Browser lets you see the bigger events in a very sharp, graphical way.

And there's plenty of other great things there too; climatologies, publications, education pages, etc.  Now, obviously the majority of this information focuses most directly on severe weather setups (though the SPC does actually also issue winter weather mesoscale discussions [the WPC now does heavy rain MDs, and of course the NHC does the main discussions on tropical systems]), and only regard US events.  But these tools can really help even those interested more in other areas and topics get a better understanding of the bigger picture, which sync up well into just about every topic of synoptic and mesoscale meteorology, regardless of location.

Now, in terms of helping you personally narrow down onto the key elements, so that you could make your own composite map... the classic ingredients necessary for thunderstorms (also see here) can be a good starting point:

Instability... the predisposition of rising air to continue rising.  Basically warm (and moist) surface air and anomalously cold air aloft.
Moisture... high dewpoints create clouds more readily, form them at lower heights (important for tornadoes), and produce more precipitation/energy for storms.  Plus it helps the instability.
Trigger... something to get the air moving to rise so that the ingredients can be realized.  There are a WIDE range of possibilities here.  Important ones for storms include fronts, the dryline, vorticity advection aloft (incoming vort maxes you see spinning around on water vapor imagery), favorable jet streak quadrants, strong temperature advection (e.g. low-level jets), outflow boundaries, seabreezes/lakebreezes/riverbreezes, gravity waves, diffluence aloft, terrain/orographic lift, horizontal convection rolls/cloud streets, isentropic upglide, and differential heating boundaries.  Suffice to say there are a lot of options in play, though some are more common than others.  But you'd be surprised how quickly you can get used to finding them with practice.  (And it's really a pity there isn't greater information/graphics/videos/explanations on some of those topics... perhaps some of these will eventually work their way here to be questions that can encourage a better, clearer reference to form)

And finally, to really ramp up severe weather, and also primary to tornado threat, you add in ingredient four...

Wind shear... different winds at different height.  A combination of how much directional difference there is and how much speed difference.  Significantly impacted by upper level jet streaks, low-level jets, and the direction of the surface flow is.

This may sound like a ton.  But taking a second look at that Accuweather graphic, it's those same ingredients:

So with those basics to start at, the pictures have a pattern to them.  And then when you add in the finer details discussed, you can really find the deeper things you won't on the more basic composites.  You can see what really DID make all the difference.  In the end, it's an investigative science, a continual game of making and refining theories, and it's something you only get better at with practice.  Even top meteorologists still don't always have the answers; I don't know whether anyone has come up with a perfect explanation yet for why the supercells on Sunday in Central Florida didn't produce prolific tornadoes.  Forecasts do still fail.  And so we're always trying to better clear up the details of each past event, so that we'll be better at the next one.

A couple final links... it seems like this journal article might be fairly interesting and approachable for you... and then websites like Stormtrack can be a really great asset, as that's where quite a few chasers/meteorologists often congregate to discuss big weather events.  The more time you spend looking at this stuff, engaging in conversation, challenging the reasoning you/others have, and learning, the better you'll be able to form a clearer picture of what's going on.  A much better picture than any news article will ever give!


How close to the magnetic poles will a compass be accurate?

Regions where the strength of the horizontal component (H) of the magnetic field is small (i.e. where the field is close to vertical near the magnetic poles) define where a compass won't work reliably.

For example where H drops below 5000nT is considered unreliable for values of magnetic declination as per the error calculations in the World Magnetic Model 2015 report. I've seen aviation charts (of which I can't find an example) where 6000nT (also based on the WMM as that's the industry standard there too) is used to define where another navigation aid should be take preference.

You can get an idea of the geographic distances involved from this map of the 2015 horizontal field intensity over the northern hemisphere. The distance of a given field strength value to the pole isn't a fixed value as the field isn't exactly a dipole, so the south pole map looks quite different, but you get a realistic idea at least. Something like within 2,500km in the North, and a few hundred km in the South.

As @Tactopoda pointed out, declination can be very large within thousands of km of a magnetic pole, and the annual rate of change of H is also much greater than elsewhere, hence why a compass isn't very reliable, even where it can give a consistent reading.


Is there no means through which such a large volume of surface water, perhaps delivered by comets, could be subsumed in to the mantle through tectonic processes?

Definitely. This was happening throughout most of Earth's history, it's happening now, and it will happen in the future.

Subduction occurring in subduction zones are the main mechanism (only mechanism?) of taking stuff from the surface and pushing it down deep into the mantle. Oceanic crust gets hydrated by reacting with the ocean water. Primary magmatic minerals such as pyroxene and olivine are altered into a variety of hydrous minerals: serpentine, amphibole, epidote, chlorite, talc, etc. Once this hydrated crust gets subducted most of the water is volatilised and gets lost to overlying mantle, and even flux-melting it so you end up having volcanoes. Here's a picture:

Source: nature.com

Recent research shows that not all water is lost. Some of it may actually survive the way down deep into the mantle. The identity of the carrier minerals and the exact conditions are still a field of active research and new discoveries are constantly being made. This would most likely form water-rich and water-poor regions in the mantle. The water content of the mantle will thus be quite heterogeneous, which raises the question of how representative was the ringwoodite discovery. After all, it's only one data point.

So to summarise it, yes. Water from the surface can end up in the mantle. This doesn't necessarily mean that this is what is happening, and it may be equally likely that the mantle water is indeed primordial.


Can someone provide a map of Nazca lines with this image in it?

go2peru  has a nice set of maps of the Nazca area.


Can minimum relative humidity be greater than maximum relative humidity?

I think you might be getting confused. There is relative humidity. If you put in different values, you will get different results. For instance, if you replace the variable names of one of your functions (say replace Min with Max), you will have the same exact function.
Relative humidity is a ratio of the amount of water vapor in the air to the amount of water vapor that could be in the air (saturation vapor pressure $e_s$): $$RH=100\%\times\frac{e}{e_s}$$ Since the saturation vapor pressure decreases with increasing temperature (Clausius Clapeyeron equation):$$e_s=611 \exp\left(\frac{L_v}{R_v}\left[\frac{1}{273.15}-\frac{1}{T}\right]\right)$$ it is conceivable, and also not uncommon, for the maximum relative humidity to occur when the temperature and specific humidity is at a minimum.
So can the minimum relative humidity be greater than the maximum relative humidity? By definition of minimum and maximum, no. But the times that the minimum and maximum relative humidity occur are often counter-intuitive.


Why doesn't the sun reach its highest point overhead at exactly 12:00 noon?

It's not a question of latitude but longitude and time zones.

Prior to the advent of railway transportation the time set on clocks varied from towns within close proximity because the clocks were set to noon when the Sun was at its highest in the sky. This was more apparent for towns east and west of each other (ie different longitudes).

When railway transportation was developed there was a need to standardize times so that train timetables could be developed and arrival and departure times would be accurate and consistent

This precipitated the development of time zones. Each time zone is approximately 15 degrees of longitude wide, but there are differences because of national/regional priorities. China which has a similar longitudinal extent as the contiguous states of the US has only one time zone, whereas there are four in the contiguous states of US.

Within a band of longitude the time is the same. In the time zones immediately east and west, the time is one hour more (east) and one hour less (west) - ignoring difference due to daily savings.

The reason for time zone being approximately 15 degrees of longitude wide is the rate of spin of the Earth is 15 degrees/hour (360 degrees every 24 hours).

You state that in your town, noon is either 12:30 or 13:30, depending on daylight saving time. The reason for noon occurring at half past the hour is due to the boundaries of the time zone where you live. Where I live, noon is approximately at quarter past the hour.


1) I would call the formation a sea stack.  Effectively you have a band of rock which is either more resistant to the forces of erosion and weathering from the sea, or is located on top of a more resistant strata.  The more eroded portion is just that, a more eroded portion, and by its absence tend to identify the rest as a sea stack.
2) The matrix, the rock with the fossils, looks like a limey shale, or a limestone with a lot of shale or clay in it.  It appears to have a component of lime or CaCO3 in it.  This could be confirmed by placing a small amount of dilute HCL or Muriatic Acid on the rock and seeing if it fizzes.
3) There are definitely crinoid stem sections in this rock, as mentioned by JulPal.  If you look carefully at this rock you will likely find a number of other fossils.

To get a tighter description you will have to give more information about the rocks

Treatment of this rock with a dilute acid bath might show a number of fossils.  See the article here https://museum.wales/articles/2011-06-07/Fossils-in-stone-acid-preparation-of-fossils/


How is heavy rainfall determined in National Climate Assessment

After contacting the author of the chart, I believe the following defines the process behind the chart.

Data source: NOAA's Global Historical Climatology Network Daily station data for "PCPT".
Use only stations in the Southeast states which have data for 90% of days from 1895 to 2011, to match stations used previous edition of the climate report.
Use only years with at least 300 days of data.
Remove data values that have been flagged in GHND for quality issues.
Count the number of days of heavy rainfall (3 or more inches) for each station and year.
Using a 1° by 1° lat/lon grid, average counts of stations in the same grid cell.
Report the average of all grid cell-years for a given decade.

I have still not been able to reproduce the chart because I have had trouble getting clean data. Will update with a chart when that happens.


Should I worry about copper pipe outside attracting lightning strikes?

Any build up of static electricity in the ground will seek to connect with opposite charge in a storm cloud, and will spark through the line of least resistance. Any high metal structure, whether it is copper or not, is a candidate for the line of least electrical resistance. You may be able to protect your copper support by a higher lightning conductor (sharp spikey, high, pointing up, and well earthed, preferably to the local water table). Also bear in mind that the lightning can jump over short distances possibly to your copper support.

I once observed a lightning strike on a house close to where I live in South Australia. The lightning hit a TV aerial, jumped to the metal guttering around the roof, jumped to metal window frames, and made contact with the house's internal wiring. It was like a bomb had gone off. Every electrical appliance that was plugged in was fried. The guttering kind of exploded, and a sour smell of 'charred house' lingered for weeks.

So yes, you should be concerned!


How are CO2 emission effects and high altitude effects of air travel compared to each other?

The CO2 is a greenhouse gas which causes a net heating effect as it retains additional solar radiation, the exact magnitude of this effect is still highly debated. The high altitude effects you've mentioned are often referred to as "jet exhaust shading" and it's estimated, based on some temperature data from the week after the 9/11 attacks in the US, that it causes roughly 4°C of cooling, this is because the jet exhaust contains water which condenses out as high albedo clouds, and sulfur compounds that absorb solar radiation as well as the CO2.


High vertical resolution atmospheric sounding data

Looking for similar for another recent question, I stumbled across https://www.sparc-climate.org/data-centre/data-access/fisaps/ which lists quite a few options on HVRRD (high vertical resolution radiosonde data)
Looks like a lot to sift through, but if your project can work for past data over the US, I found that from ftp://ftp.ncdc.noaa.gov/pub/data/ua/rrs-data/ I was able to download the files and extract them using their software, resulting in data every second, typically about 5-10 meters apart... here's a clipped view with a rough idea of the type of data it has (also has v-wnd):

Perhaps that fits your needs?
If not, and you can't find any useful data from the first link, maybe also try looking around https://madis-data.ncep.noaa.gov/madisPublic1/data/point/ ... there's things like ACARS (commercial aircraft sounding data), MADIS data (satellite), radio profilers, etc.  Though less confident you'll find a resolution you want, never hurts to try.
But hopeful you'll find what you need with the HVRRD stuff!