NCEP reanalysis model levels ECMWF Model Levels

The above link describes the coefficients used to define the ECMWF model levels in pressure in order to compute geopotential height. Is there a similar data for NCEP reanalysis model or is the data already on pressure levels in which case the above step is not required ? To be precise I am looking for the identical data for the T62 NCEP reanalysis data(2.5 x 2.5).
The NCEP reanalysis model uses the sigma vertical coordinate. The same question can be rephrased in the following manner

1) What are the values of the sigma levels and where can they be downloaded?
For e.g. if the sigma level is 0.995 and the surface pressure is 1000 hPa then the pressure at the sigma level 0.995 is 995 hPa.

2) Are the sigma levels of the NCEP reanalysis model comparable to the a and b coefficients of the ECMWF model ?

UPDATE

The hybrid vertical coordinate of UCAR Community Atmosphere Model(CAM 3.0) describes a similar equation to that of ECMWF and has explicit coefficients A and B as shown below

$p(\eta,p_s) = A(\eta)p_0 + B(\eta)p_s$

where p is pressure, $p_s$ is surface pressure, $p_0$ is a specified constant reference pressure and A and B are coefficients that specify the coordinate being used and are defined only at the discrete model levels.

GOAL - I have code that uses ECMWF data as input to run a few calculations. I am looking to run the same code using NCEP renanalysis model data.

Reference

Page 6 Section 2.2.1 Vertical Discretization
Simmons, A.J., Burridge, D.M., An Energy and Angular Momentum Conserving Vertical Coordinate Finite Difference Scheme and Hybrid Vertical Coordinate, Monthly Weather Review 758-766,1981
Collins, W. D., P. J. Rasch, and Others, Description of the NCAR Community Atmosphere Model (CAM 3.0), Technical Report NCAR/TN-464+STR, National Center for Atmospheric Research, Boulder, Colorado, 210 pp., 2004. CAM

Grid Resolution of the NCEP/NCAR reanalysis data

The data is available on different grids depending on the variables of interest:

The original grid is a T62 Gaussian grid, which grid cells do not have a constant lon-lat spacing over the whole globe (see e.g. Gaussian grid at Wikipedia), with 28 sigma levels. The sigma levels are listed on this page, where also the surface pressure is available for download. According to the FAQ, the sigma coordinate equals "pressure in current level"/"surface pressure". Thus, the pressure on each sigma level can be obtained via the available data.
Secondly, some variables, such as air temperature, are available interpolated onto an equally spaced lon-lat grid of 2.5° x 2.5° resolution with 17 pressure levels. These data are available here including data files with the geopotential height. The pressure levels are listed on the same page.

Comparability with A and B coefficients of ECMWF

The ECMWF uses the coefficients A and B as well as the reference pressure $p_0$ to describe the levels. NCEP uses just one coefficient ($\sigma$) for this purpose:

$$
\begin{align}
& \text{ECMWF:} & p\left(\eta,p_s\right) &= A\left(\eta\right) \times p_0 + B\left(\eta\right) \times p_s \\
& \text{NCEP:} & p\left(\eta,p_s\right) &= \sigma\left(\eta\right) \times p_0 \\
\end{align}
$$

When we had $p_0 = 0\ \text{bar}$, both representations were the same. In the given situation, there is no unambiguous mapping from a known $\sigma\left(\eta\right)$ to a set of $A\left(\eta\right)$ and $B\left(\eta\right)$. At least if there are no further limiting conditions.

Normally, I do not deal with vertical coordinate systems. Therefore, I am not sure how data on different vertical layers is compared with each other (except of the obvious: interpolating the one data set onto the vertical coordinates of the other data set).

Summary

1) Yes, here and here.

The variables Air Temperature, Geopotential Height, Relative Humidity, Specific Humidity, Omega (Vertical Velocity), U-Wind, and V-Wind are available on the second grid (2.5° x 2.5° horizontal resolution; 17 pressure levels).
The variables Divergence, Specific Humidity, Virtual Air Temperature, and Relative Vorticity are available on the first grid (T62 Gaussian grid; 28 sigma layers). In order to calculate the model pressure at each sigma level, the surface pressure is additionally provided (T62 Gaussian grid but no vertical resolution). Also the topographic data (Orography) is provided on the same resolution as the surface pressure.

2) The vertical layer representations by $\sigma$ coordinates, on the on side, and by a set of $A$, $B$ and $p_0$, on the other side, are similar to each other but not directly comparable to each other. However, for most practical applications the data on the second grid, which is easier to handle, might be sufficient.

I am not sure if these answers to the question are satisfactory.


Can ice caps reform if they disappear? Excuse my ignorance. I'm under the impression that there are various types of ice at the poles, but I don't know the difference or the significance of each type, so, in terms of whatever is actually melting in these areas as a result of climate change, is it possible that it could come back if greenhouse gas emissions were eliminated or something like that? Basically, I'm assuming that the ice caps are necessary in order to maintain the habitability of the planet for humans, so is there some sort of threshold of melting that would essentially count as a point of no return or is there always the possibility of seeing the ice caps return to safe levels?

Yes, polar ice can melt -- significantly, if not completely, with substantial effects on human civilization. And it can stabilize and recover, but the question is at what pace relative to human civilization.

There are generally three types of polar ice:

Ice sheets: "An ice sheet is a mass of glacial land ice extending more than 50,000 square kilometers (20,000 square miles). The two ice sheets on Earth today cover most of Greenland and Antarctica."
Ice shelves: "Permanent floating sheets of ice that connect to a landmass."
Sea ice: "Sea ice is frozen ocean water. It forms, grows, and melts in the ocean. In contrast, icebergs, glaciers, and ice shelves float in the ocean but originate on land."

Sea ice is usually 1-2 meters thick; shelf ice is 100-200 meters thick; sheet ice is one to several kilometers thick.

The poles differ significantly. It's often pointed out that the Arctic is an ocean surrounded by land and the Antarctic is land surrounded by ocean. The North Pole is occupied by sea ice, about half of which melts every summer and reforms every winter.

At the other extreme are the ice "caps," more or less the ice sheets in Greenland and Antarctica that extrude ice in the form of glaciers and ice shelves that continuously flow into the ocean, breaking apart and melting.

To take just Greenland: Greenland has had some degree of glaciation for ~38 million years, but lost much or almost all of its ice during a warming period about 400,000 years ago, suggesting that the current ice sheet was created in that time.

  The evidence suggests nearly total ice-sheet loss may result from
  warming of more than a few degrees above mean 20th century values, but
  this threshold is poorly defined (perhaps as little as 2 °C or more
  than 7 °C).]5

(That melt ice is equivalent to about 7.3 meters of global sea level rise.)

So, yes, the ice sheets can melt away; how quickly they can melt will be driven by the amount and pace of CO2 emissions; the extent of that melting will be affected by the duration of that CO2 in the atmosphere and the impact of potential feedbacks.

The formation of an ice sheet -- glaciation -- can occur relatively rapidly in the correct conditions, according to this IPCC Assessment report on paleoclimate, which notes glaciation occurring in some regions of the world within a period of centuries.

In the short term, the most obvious impact we're seeing from global warming is the steady decline in the extent of Arctic Sea ice, at about 2.6 per decade since the satellite record began in 1979. Research suggests that this ice can come back, eventually:

  The central finding of this study is that sea ice loss is fully
  reversible in a state-of-the-art GCM over a range of CO2
  concentrations from the 1990s level to nine times higher. We find no
  evidence for threshold behavior in the summer or winter ice cover in
  either hemisphere. Thus if tipping points exist for future sea ice
  retreat in nature, it is for subtle reasons, i.e., through processes
  that are absent or inadequately represented in this model.

However, this team of researchers suggested an extensive project to prevent a worst-case scenario:

  This loss of sea ice represents one of the most severe positive
  feedbacks in the climate system, as sunlight that would otherwise be
  reflected by sea ice is absorbed by open ocean. It is unlikely that
  CO2 levels and mean temperatures can be decreased in time to prevent
  this loss, so restoring sea ice artificially is an imperative. Here we
  investigate a means for enhancing Arctic sea ice production by using
  wind power during the Arctic winter to pump water to the surface,
  where it will freeze more rapidly.


Temperature rise when snowing Why does the temperature rise when it is snowing? Is it due to:

cloud cover
snow requires humid air and warmer air can carry more humidity (so in this case it would be the other way around, i.e. it snows because it is warmer)
something else?

Snow fall can occur under several conditions. In this I am assuming conditions typical for mid to high latitudes. Association with cold-warm fronts are probably most common. Snow fall in mountainous areas can be associated with orogenic clouds and precipitation, when air is raised due to topography creating conditions for precipitation. In addition it is possible to have convective precipitation although such conditions are much more common during summer conditions yielding rain (and when severe e.g. hail).

So when snow fall occurs in association with warm fronts, one could expect a warming since warm air replaces the cold when the front s passing. My guess is that it is this that you have experienced. However, since it is also possible to obtain snow fall during the passing of a cold front the opposite may occur. The orographic conditions concern a more steady situation where the air is affected by  a mountain which is stationary so I would not expect large changes in air temperature unless the air moving across the mountains itself changed temperature for one or another reason. Convective snow fall would not likely yield marked changes in temperature as I see it since the snow would be created by vertical movement of warmer air, cooling to form the snow. I would rather expect a slight cooling, similar to what happens under a heavy rain shower in summer.

So in short, the warming you mention is not generally  associated with snow fall per se but likely associated with the passing of a warm front.


What kind of rock or stone is this? Where did it come from? I found this on the side of the road in Oregon, i think it was left or forgoten about thats why it was left there but it has crystal pockets, multiple colors, some smooth sides, perfect circles and swirles. Ive never seen anything like it and hope some one can tell me more about its origins or classification. Rock? Meteroite? Plz help.   Ignore the bits of bright green in some of the photos , that is from a towel the rock was wiped with.
(https://i.stack.imgur.com/JUkRT.jpg)

Quite an interesting stone.  I cannot identify all of it but given its location, and the patterns it is primarily Agate, a type of crypto-crystalline quartz.  The fourth picture down shows a layer of lace agate across the top of the stone at that location, it is underlain with a more massive translucent agate.  In the Oregon area there are many areas with volcanic rock.  The silicas have dissolved from the volcanic material in the past and this silca has been slowly deposited to form the rock you found.  The following links give you an idea of the types of agate you can find.

Types of agate

A more detailed description of types and formation.

I would warn you that there are a number of names for the various types of agates and the naming doesn't seem to follow any convention.


What percentage of Earth's surface is arid? Is there available information on how much of Earth surface is arid climate?

It will depend on the exact definition of "arid" and the period of time. But using the widely used and accepted Köppen climate classification, "arid" would correspond to the four climates in climatic group B: "Dry (desert and semi-arid) climates". Using the most up-to-date present climate data (2006) provided by the WORLD MAPS OF KÖPPEN-GEIGER CLIMATE CLASSIFICATION at 0.5° of resolution, that looks like this (in an equal area projection):

We get that the four arid climates (group B), add up to $4.401 \times
 10^7 {km}^2$ of a total of $1.527 \times
 10^8 {km}^2$ inventoried in the dataset (A good match for the figure of of global land area of $1.489 \times 10^8 km^2$ listed by wikipedia), leading to a grand total of 28.8% of Earth's land surface corresponding to arid climates.


Beta plane approximation: variation of Coriolis parameter The Beta plane approximation put me in confusion.

Beta plane approximation explain me how the Coriolis parameter changes with latitude.

Beta parameter changes with the cos(latitude) but this is refers to the equator or my latitude (arbitrary point)?
If i go southward latitude decrease so cos(latitude) is max at the equator but the Coriolis parameter is usually minimum at the equator. I made confusion with their relationship.

Beta plane approximation is related at the Beta effect or is it the same?
I don't understand its implication on the westward intensification.

Thank you in advance.

The Beta effect describes how the Coriolis force affects fluid motion depending on spatial changes due to the curvature of the Earth. In other words, it describes the variation of the Coriolis parameter with latitude.

One can model this change exactly or approximate it via Taylor series expansion at a given latitude. The latter option is typically used to make the theoretical analysis of geophysical phenomena possible because the equations are easier to solve. This is the Beta plane approximation, where the Coriolis parameter varies linearly in space.


How is Air Quality Index relevant to both PM2.5 and NO2 I am comparing NO2 and PM2.5 levels in the pre-2020 Jan-April and 2020 Jan-April (representing air quality during lockdown and under no-lockdown conditions).

The data was from the aqicn website (https://aqicn.org/data-platform/covid19/). The data is not raw concentrations, it is converted into the US EPA standard, which I believe is represented as AQI values.

Can someone please explain why with PM2.5, the data reaches from 'Good' to 'Hazardous', whereas the NO2 is only within the 'Good' bracket.
I'm hoping it is because PM2.5 is more  harmful than NO2?

But if it is because I should be using a different scale for NO2 (e.g., 0-10 = Good, 10-20 = Moderate, etc.) I'd like to know - I haven't been able to find different AQI scales for different pollutants.

Most locations in the US don't see high concentrations of pollutants like NO2 and CO anymore.  They are largely no longer an air quality problem and air is "Good" in regards to those pollutants.  Especially during "lockdown", when traffic is light.  This is largely thanks to tailpipe emissions standards for vehicles and a much more fuel efficient fleet. On the other hand, PM2.5 has multiple sources that cause high concentrations, and we are much more likely to see the AQI vary beyond "Good" PM2.5 (e.g. outdoor fires, wood-stoves, secondary aerosol formation).

The AQI is based on health-based evidence, with a different concentration threshold for each pollutant.  These are all put onto the AQI scale for simple communication to the public. If concentrations of NO2 had reached levels of the NAAQS, then you would see your graph plot into those AQI levels (note NO2 doesn't go as far up in "AQI" values as PM2.5 on your graph because those NO2 concentrations were never detected by the monitor).

The National Ambient Air Quality Standard (NAAQS) for nitrogen dioxide (NO2) is a 1-hour NO2 standard of 100 parts per billion (ppb). See https://www3.epa.gov/airnow/no2.pdf and page 2 here: http://njaqinow.net/App_Files/2016/AQI%202016.pdf which has the break levels for each pollutant, shown below:


What reflects UV radiation more: stratus clouds or cumulus clouds? Interested in this since I sometimes look down on the clouds in the plane, and wonder if some of the reflected UV-A radiation might damage my eyes.

According to the below albedo rating diagram (percentage is reflection of incident radiation) cumulus cloud is the greater total spectrum reflector so it will reflect more UV that equivalent stratus formations.

Do note that water vapour does however absorb the vast majority of UV (≈100nm) that it intercepts as we can see in this diagram:

So overall cloud UV reflectance will be quite low.


Is the association of fluorescent minerals calcite, fluorite, and apatite with fluorescent rare-Earth minerals a coincidence? If I understand this answer and this comment correctly, minerals like calcite, fluorite, and apatite are "commonly associated with (Rare Earth Element) REE deposits", and like some REEs also fluoresce when exposed to UV light. But the intrinsic fluorescent properties of those minerals are not caused by REEs.

Is this just a pleasant coincidence; the presence of one fluorescent mineral is often associated with the presence of another fluorescent mineral even though their fluorescence mechanisms are different?

Or do minerals like calcite, fluorite, and apatite tend to fluoresce because they contain REEs, thus observation of their fluorescence is a direct indicator of the presence of REEs? Or do REEs only modify the color of their fluorescence, but not necessarily cause it?

The answer to your question is probably the second:

  Or do REEs only modify the color of their fluorescence, but not necessarily cause it?

I will give an example of apatite. Here's a cathodoluminescence (luminescence excited by electrons) energy spectrum of a natural apatite. Source.

You can see several different rare earths triggering the luminescence, but there's also manganese. Apatites from granites usually have lots of manganese, and very little rare earths. So their luminescence would be dominated by the 2.1 eV range, which would be yellow. In contrast, apatite from REE deposits would be dominated by Ce, giving a blue-violet colour. They will also have lots of Nd, but that does not help us because it's in the infra-red range.


Checking the bedrock with radiowaves - how does it work? I've heard long ago that the rock material deeply below surface are checked by a device that acts like radar - it sends radiowaves into the ground, and geologists find out from reflections that what type of rock can be found there.

What's the name of this device or method, and how is it possible to differentiate rocks from radiowave reflection?

Do you mean Ground Penetrating Radar? This is typically limited to very shallow depths though - eg. archaeological investigations, police forensics (finding graves), and civil engineering site investigations. The latter can go to tens of meters and would be used for planning foundations, excavations, etc (I know of an example where it was used for site characterization for a planned rowing lake). The depth limit is typically due to attenuation in brackish groundwaters. Ice applications can typically go further due to the lack of conducting liquid water.

Or are you thinking of Reflection ('Active') Seismic Surveys, which work on a similar principle but using sound waves. Sound waves can travel to the far side of the Earth (cf. large earthquake 'P' waves), but reflection surveys are typically looking at the upper crust (few km) and rarely go beyond the base of the crust (aka the 'Moho') which is a strong seismic reflector. Reflection seismic surveys are widely used in the oil business.


Is non-randomly-sampled historical data representative? I'm a global warming skeptic, and one of my concerns is the accuracy of historical global temperatures. Since these temperatures weren't sampled at random locations or gridded points, can they be considered an accurate representation of "global temperature"?

Thoughts/etc:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3982162/ talks about this in a temporal sense, since using the average of the minimum and maximum daily temperatures at a given location isn't really a great way of determining average temperature. However, it doesn't discuss geographical random sampling/gridding.
http://onlinelibrary.wiley.com/doi/10.1002/joc.4580/full notes this problem exists, and takes uniformly gridded measurements, but it's limited to a specific region and time period (1979-2012).
I know climate scientists slice the Earth up into grids to avoid clustering bias, but that's not the same thing, and isn't useful if the original readings don't accurately represent the slice/region.
I also realize that climate scientists have other measures of global warming, but linear regression of actual temperature measurements seems to be the most used to convince the public, so their accuracy seems important.
As a skeptic, I'd also like to know if, in general, most of the arguments for global warming are statistical in nature (ie, linear regression on measured variables), or the statistical ones are just the most "photogenic" for public consumption? In other words, is the whole non-randomly-sampled/gridded temperature argument a red herring?

EDIT (to clarify question):

To determine the Earth's mean surface temperature, we can employ one of these methods:

Measure the Earth's temperature at every point and average. Of course, this is physically impossible, since a point is a 0-dimensional mathematical abstraction, but we can do something close with satellites.
Select a large number of random points on the Earth's surface (this random distribution is uniform in longitude, but not in latitude-- in latitude, it would look like a cosine curve), measure the temperature, and average. In addition to giving us a mean, it would give us a standard deviation so we can say "we are 95% confident that the Earth's true mean temperature is X plus or minus Y".
Take a uniformly spaced grid (non trivial, since the distance between longitudes vary by latitude), measure the temperature at those points and average. This is similar to the first approach, but with fewer points. Unless we believe our grid points introduce a bias, this should be as accurate as random sampling.

My problem: temperature measurements in the past were made using NONE of these methods. The points where temperature was measured were not chosen randomly or in a gridded fashion. Therefore, how can they be an accurate measurement of historical temperature, even if we only consider temperature changes?

NOTE: I realize surface temperature isn't the best measure of global warming, since water has a much higher specific heat than land (among other things), but that's my focus for this question.

Samples don't need to be random to be valid, it helps but it is not essential especially if exhaustive, consistent, and has a large sample size, especially when dealing with observational studies. Representative sample is different than random sample. Remember we are not trying to attain the global temperature to the highest degree of accuracy in one instant, we are trying to measure the change in temperature over a long span of time. Thus consistency in location is more important than randomizing location.

The fact that the sampling points do not move is essential, we know temperature is affected by regional conditions if the samples were re-randomized(moved) with every measurement it would make it less accurate not more. Remember what is being measured, the change, because the sampling points are not moved the the change will be accurate because it essentially becomes a stratified sample. If I am measuring changes in engine temperature for instance I don not want to measure at a different point each time, as long as the points(locations) are consistent the sample will retain high accuracy. A random sampling would be LESS accurate because it would invite confounding because we know the distribution of temperature across the engine (or globe) is not random. Any shift in location between measurements would invite confounding data. Almost no science uses a truly random samples, it's just not possible. Consider things like exhaustive sampling, cluster sampling, stratified sampling, and systematic sampling all are used more often than true random sampling and each is more accurate than random in the right circumstances.

Consider an example, say you are trying to measure the temperature change in an engine over time. Where on the engine I attach my sensors does not matter as long as I do not move them, especially if I put many sensors on it. I could put thirty sensors all on the left side engine, and it would measure the change in temperature very accurately, compared to moving the sensors between every measurement. Don't fall for the perfect solution fallacy. Also remember this is an observational/descriptive study by its very nature.

Each point on the map is more like a repetition, the real independent is the time at which they are sampled, which is either stratified or clustered depending on which study you refer too. Note that multiple sets of data points are also compared. NOAA, BEST, etc. are each independent data sets that can be compared, and show the same pattern.

High and low are used for measurements because that is all that was recorded in the oldest measurements, so changing the format would require throwing out all that data, drastically shortening the sample size (loosing more than half the time span). In this case the accuracy gained by the much larger number of samples is more than would be gained by a random or grid location. Random is rarely possible with historic data which is why the size and consistency of the data set is so important. The nice thing is these are also compared to other sampling methods on other time scales to test to see if they show the same pattern. Historic scientists are aware of the limitations of their data which is why independent verification is so important.

Now consider ice core data, I was surprised when you said surface temperature was the most used, I see ice core data far more often, because it records a much longer span of time, and records other things (like $CO_{2}$ content) as well. Again each core is a repetition and the core can be sampled in a random or stratified way, stratified is the most common because it is more exhaustive in a core sample. Ice cores are also compared to ice cores for m other locations.

Another consideration is cross-comparison, that is the use of multiple independent forms of measure, ice core compared to satellite, compared to surface, etc. Dozens of different forms of measurements/experiments are compared and show the same pattern.

This is probably one of the best overviews of the science I have seen. It is a little old (2013) so if anyone has seen a more recent version I would love to use it instead.


Does erosion make mountains become higher? Recently at the American Museum of Natural History in New York, I saw a display set that claimed erosion makes mountains rise higher, counterintuitively. The explanation was that the material removed from a mountain due to erosion makes it much lighter. Since the mountain sits on a landmass that is floating atop magma, a lighter landmass rises higher. (Similarly, boats rise higher in water when weight is removed from them.)

I have been looking for resources online to confirm this, but none mention it. They tend to claim that pressure due to shifting tectonic plates is the cause of mountain growth, and if they mention erosion at all, they only discuss it as a possible shrinking factor.

What do actual geologists have to say about this? Does it depend on the mountain range?

This actually does happen, a feedback loop between the Himalayas and the Indian monsoon.

The Indian Plate is actively shoving itself under the Eurasian Plate, creating the Himalayas.

At the same time, monsoon storms come up against the southern side of the Himalayas. The high mountains enhance the storms' rainfall, and the mountains erode much more on the southern side than the northern side.

Material is transported from the Eurasian Plate down onto the Indian Plate, and the weight removed from the mountains causes isostatic rebound of the Eurasian Plate, allowing the Indian plate to slide underneath, enhancing the uplift of the Himalayas., keeping the monsoon rainfall on their south side, etc.

There's a more detailed explanation and some nice images here.


Mild climate, low-humidity city all year round Where in the world can I find a place with mild / warm and non-humid climate all year round?

What I'm looking for is a city with these characteristics:
- monthly average low temperature > 5°C (41°F)
- monthly average high temperature < 27°C (81°F)
- low humidity levels
- at least 500k people
- English or Spanish as first language

Low humidity means nowhere near the coast or near any large lakes. Warm winter temperatures without being too hot in summer means tropical high elevation or lower latitude inland sub-tropical. Parts of sub-Saharan Africa might suit, although cities like Kampala or Nairobi have relative humidities which reach the high 70s. As Milancuric writes, you need to be more specific about 'low humidity'.


Is the Arctic ice dissapearing faster than IPCC models say? Are observations of Arctic sea ice in accord with what the IPCC forecasts says they should be? And as such is the ice reducing in an exponential or linear way?

For instance, from https://www.scientificamerican.com/article/how-the-ipcc-underestimated-climate-change/:

  Projection: The IPCC has always confidently projected that the Arctic
  ice sheet was safe at least until 2050 or well beyond 2100. Reality:
  Summer ice is thinning faster than every climate projection, and today
  scientists predict an ice-free Arctic in years, not decades.

And then is this prediction based on the curved line on the left (found here)
or the straight one on the right (found here)
(both are from NSIDC data):

The IPCC said "Although the Hadley Centre climate model underestimates sea-ice extent and thickness, the trends of the two models are similar. Both models predict continued decreases in sea-ice thickness and extent (Vinnikov et al., 1999), so that  by 2050, sea-ice extent is reduced to about 80% of area it covered at the mid-20th century."
The graph on this IPCC page shows a predicted decline in annual average extent of about half a million km$^2$ from 2000 to now. Your monthly average graph shows a somewhat faster decline over this period.

The SA article talks about the much more drastic decline in minimum (September) extent.

I can't find any IPCC prediction of minimums, so you could say the IPCC failed to predict it or you could say it's in accord with what the IPCC did predict about annual averages.

Ice volume is also declining rapidly.


Is it certain that hundred year floods have finite variance? It just occurred to me to ask this.

It's easy to get a statistical distribution that does not have finite variance. For example, you can sometimes get that when the thing that is measured comes from two random variables, one divided by the other. Sometimes you can't measure a variance. Sometimes you can get a statistical distribution that doesn't even have a mean.

When that happens, if you don't notice, you can get a mean and standard distribution from the data. And when you collect more data it will seem to mostly fit. But you get big outliers more often than you'd expect. As you recompute your mean and standard deviation, with more data the standard deviation keeps increasing. Because the longer you keep measuring, the more unexpected events you will have that go outside the predicted range.

Without knowing much at all about floods, they seem to fit this pattern. The news keeps announcing floods that were supposed to be unlikely, unexpected.

Of course, for all I know this is just the news reporting things that should have been expected. Of all the thousands of places we calculate hundred-year-flood levels for, every year we should expect floods that high at one percent of them. Maybe what's happening is really exactly what should be expected.

But it's testable. With enough data you can check whether flooding ought to fit a finite-variance distribution or not.

How well has it been tested?

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

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

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


How can poor tropical soils be enriched by biological means? I have been reading a lot recently about agriculture in Africa, and one of the big impediments in a lot of places is the poor quality of the soil. Primarily this refers to a lack of usable molecular nutrients in the soil that plants need (nitrogen, phosphorous, and potassium, primarily).

I understand there are a few different methods of soil enrichment; however, these processes are geological in nature. All of the high-population density subsistence agricultural parts of the wet-and-dry tropics are directly correlated to soils that are enriched by one or more of these mechanisms.

The first mechanism is direct deposition of nutrients by volcanism from the last hundred million years or so. This is the mechanism responsible for high population densities around the East African rift, Indonesia, Ethiopia, southern India and the Phillipines. The next mechanism is flood plain deposition of eroded materials from somewhere upstream. This is responsible for fertile, high density regions like north India, Egypt, Nigeria, and most of Southeast Asia. These areas have high population densities (of subsistence farmers) other ares in the tropics have very low densities (northern Australia, most of the Sahel, most of southern Africa).

In the temperate regions, however, there is a biological means for creating fertile soils. The plains of the American Midwest or Ukraine have had neither recent volcanism nor extensive floodplains, yet are covered in rich, black chernozem soils. Evidently, these soils are produced by the deposition and incomplete decay (due to hard winters) of grasses.

Is there a biological process that can create rich agricultural soils in either the wet-and-dry tropics?

EDIT - Despite the introduction, the purpose of this post is not about agriculture, or what we could do today to to rejuvenate poor soils. This is about natural processes that would take place on timescales of tens or hundreds of thousands of years, or longer.

There are two main problems that "wear out" soil, and people working on this deal with both of them.

A soil might be low in organic matter and nitrogen, perhaps because all the crops were sold away and the topsoil eroded off. This would also happen on a new sandbank, or where a landslide had revealed a lot of subsoil. Naturally what happens is that the site is colonized by "primary succession" plants that are good at surviving there. These plants photosynthesize carbon compounds, and have bacteriological associates that fix nitrogen out of the atmosphere. The plants and bacteria live and die and leave detritus that slowly turns into richer soil, and somewhat more complex "secondary succession" plants move in. Reclamation agriculture or reforestry helps this along, and agroforestry tries to forestall soil loss by growing trees instead of arable crops.

But C and N are not all that plants and bacteria are made of -- just about everything else, eg P and K and Mg and Ca, comes from the geological parent material of the soil. When as anions and cations these elements are being traded and fought over by plants and microbes, they are soluble, and over time they will weather out of the soil. Over geological time they weather out of the underlying rock, which is the problem in the oldest parts of the Earth, and then it's difficult for even primary succession plants to grow.

Hawaii is a beautiful natural laboratory for this, as the islands are made of the same lava but are of very different ages. The classic work on this is by Vitousek; here's an open access paper following up on it: Primary Succession on a Hawaiian Dryland Chronosequence.

There's a ecology-economy group trying to fix this problem in Haiti. Haiti has exported so much, for historical reasons, that their soil is terrible and they have to import a lot of food although they were recently a very NPP-productive place. SOIL works on designing and introducing composting toilets so that the elements imported as food are incorporated into agricultural soil instead of running off (causing public health and fisheries problems as they go!). It's a very nice virtuous-circle, though it takes a lot of work to keep it going.


What are the cubic formations found inside Larimar gemstones? I recently noticed what appears to be common cubic formations just beneath the surface of Pectolite (Larimar) gemstones. They quite resemble transparent sugar sprinkles. Each formation isn't perfectly cubic, and it should be noted that no two are identical. Such inclusions can be seen in both polished and unpolished stones. I was wondering what these cubic formations are made of, how/why they might be formed, and what they are formally referred to as.

Below are two images; the first being of a 15.5ct unpolished Larimar stone, and the second being a 7.4ct polished Larimar stone. Both images clearly depict the aforementioned inclusions. Based on the images provided, I would estimate that the width of a single inclusion lies between 0.25mm and 0.75mm.

P.S, Larimar is found primarily in the Dominican Republic. It is a form of Pectolite with a unique blue color caused by the copper in its composition. My question encompasses all Larimar in general, not just the images provided. My research into the subject has been unfruitful. I've found no source mentioning these inclusions, and it is exceedingly difficult to find source material on something so difficult to universally articulate. It's possible that the inclusions are Triclinic crystal systems, but why they stand out from the rest of the stone is beyond me.

One source states that:

  Calcite and hematite are often found as inclusions within deposits of Larimar stone.

Calcite and hematite may not be the the answer to my question, as the description of such inclusions from another site states that:

  Hematite can create fern-like “red plume” patterns, calcite crystals.

Calcite and hematite may not be the the answer to my question

Hematite is not the answer, but calcite is.

The inclusions are not cubic, they are rhombohedral. This is precisely how calcite looks like.

  but why they stand out from the rest of the stone is beyond me.

Because calcite is a translucent mineral, and pectolite is not. You can drop some vinegar on the inclusions and you will see that they fizz a bit - this is how calcite reacts to acid.

You can read this for some more information:

http://www.openaccessjournals.siftdesk.org/articles/full-text/X-ray-Photoelectron-Spectroscopy-study.html


Are craters on Earth covered by vegetation? When you look at other planets and moons in our solar system most of them have lots of craters. If Earth had no vegetation and water would it also look like this image of Charon?

Image Credit: NASA/JHUAPL/SwRI

Without water there would be no multi-billion year history of plate tectonics, no glacial action, and no fluvial erosion, so the Earth would look unrecognizably primitive. But we have an atmosphere, so all the impact crater rims would be subject to aeolian erosion whilst low points, including crater bowls, would have aeolian sedimentary infill. Volcanic activity would be much more obvious, and would also tend to obliterate craters, as it has in numerous other examples in the solar system. Earth would therefore appear as a rather muted, sediment-draped version of the moon.


Details on Ocean floor Taking for example the attached image, when looking at the ocean floor, there appears to be areas (strips, some of which I have drawn red lines by) of greater detail. Is this accurate detail? From ships that have passed over the area?

Those are bathymetric survey tracks.

The survey artifacts are very straight and regular in character, compared to geological features. What you're seeing is an increased level of detail along the survey line, which contrasts with the relatively smooth background model.

I labeled some of the features in this answer to a related question:

NOAA Reference: Did I find the lost underwater civilization of Atlantis?


Barite and Acantharians Acantharians are planktonic protists (abundant in today oceans), sister-group to polycystine Radiolarians, that have the particularity of biomineralizing complex skeletons in strontium sulfate SrSO4 (i. e. celestine).
Those protists have no (as far as I know) fossil record for the good reason that celestine is soluble in seawater once the organism decayed.
However it has been speculated (e. g. Bernstein et al. 1992) that acantharian-derived celestine could be at the origin of the formation of Sr-rich barite.

What is the status of this hypothesis? If this is still considered true, is there a way to differentiate unambiguously acantharian-derived barite from other kind of barite?

This would of course have interesting paleontological implications.

Source:
Bernstein, R. E., Byrne, R. H., Betzer, P. R., Greco, A. M., 1992. Morphologies and transformations of celestite in seawater: The role of acantharians in strontium and barium geochemistry. Geochimica et Cosmochimica Acta, 56: 3273-3279.

There is still some uncertainty, but some recent research is detailed below:

In research reported in the article Barite in the ocean – occurrence, geochemistry and
palaeoceanographic applications (Griffith and Paytan, 2012), recent observations and research found that

  Using the non-carbonate Sr content in
  suspended particles to track the presence of
  acantharia, van Beek et al. (2007) suggest that
  acantharian dissolution does contribute signifi-
  cantly to barite formation in the upper 500 m of
  the water column

However, a lack of a definitive correlation between the barite concentrations and acantharian distributions suggest that

  these organisms are
  not required for the formation of barite in the
  water column (Bertram & Cowen, 1997)

and that further observations

  provided direct evidence to support
  the water column micro-environment mechanism
  of marine barite formation and to verify that
  barite can form in the absence of acantharia.

The concentration of strontium in barite is a record of the Sr isotopic composition of the formation fluids, which according to the article has its source from sea water, sediments (both marine and terrigenous) and hydrothermal fluids.

It is this last point, particularly about the Sr concentrations in sea-water, which according to the article Sedimentation of acantharian cysts in the Iceland Basin: Strontium as a ballast for deep
ocean particle flux, and implications for acantharian reproductive strategies (Martin et al. 2010) state can fluctuate by several percent

  By precipitating celestite, Acantharia can reduce surface
  seawater strontium (Sr) concentrations by up to 5%

Experimentally the authors found that

  Sr fluxes we report are
  too high to be attributed to nonacantharian sources.


Could Australia's bushfires aerosols actually decrease global temperature? Given the vastness and intensity of the bushfires that have been going on in Australia for weeks now, to the point they are generating their own weather and having an impact thousands kilometers away from their origin, an analogy with volcanic eruptions spurred to my mind and I wondered: could the net effect of these bushfires actually be a measurable cooling down of global temperature, as it happened with Mount Pinatubo, at least in the short term?

Well, the amount and intensity of wild fires are a direct outcome of global warming, that's not really news.

According to this article that cites a work i can't find, until the mid of December 2019 the Australian fires emitted ~250million tons of carbon, ~50% of Australia's yearly production. A recovery in the coming decades is unlikely, because the ecosystem is already compromised. It is "too optimistic" to assume that the forests will regrow and they will "never end up accumulating as much carbon as they had before". Instead, large areas of burning forests must more and more be seen as a biospheric component that can turn from a carbon sink to a source.

Here's an example (sorry paywalled, but the abstract has the interesting points and it is peer reviewed) for boreal forest fires, where fires can lead from net accumulation over several fire events to a net loss, leading to a positive feedback. A similar process is expected for the Amazon rain forest fires.

To the question: an exact answer seems to be difficult. It depends on how much aerosols end up where in the atmosphere and stays for how long. The effect can be modelled: Here, a fire aerosol laiden atmosphere's lower 6km can be warmed because they become a heat trap. The trap is caused because aerosols have a stabilizing effect on the upper atmosphere. A forest fire's plume has a different composition than a volcanic eruption !

This paper describes a similar effect, the absorption of solar radiation by carbon can heat the atmosphere.

I am aware that there may be other effects, inclduing atmospheric cooling, but i leave that part to somebody else. All in all, the negative effects of carbon release and the potential loss of regenerative abilities of the biosphere - because of drought, erosion, loss of biodiversity and the ecosystem, soil sterilization, invasive organisms as well as the difficulties to respond in time because of the sheer area affected by fire (all depending on intensity, duration and area) - by far outweigh any cooling effects of wild fires.


Is there a database of global rainfall time series? Is there any institute out there collecting time series data of precipitation, and making them accessible online? I need data for a few different locations, but:

Low spatial resolution is fine. For example, if I need rainfall time series for France, a space-averaged value would be satisfactory.
Low accuracy is fine. For example, remote sensing rather than in situ, or rainfall measured in a few points and then interpolated, would be satisfactory as well.

Yes. Nearly global satellite and radar derived rainfall data are hosted by NASA Goddard Space Flight Center, namely:

Tropical Rainfall Measurement Mission (TRMM) aboard the TRMM Microwave Imager (TMI), a multi-channel, dual polarized, conical scanning passive microwave radiometer designed to measure rain rates over a wide swath under the TRMM satellite. TRMM was launched on November 27, 1997 into a semi-equatorial (+/- 35 deg) orbit carrying 5 instruments. Three levels of data processing are available on the NASA's server, where higher level indicates more processing, quality control, and merging of multiple raw datasets. For your purposes, use level 3 TRMM as it combines satellite data from multiple swaths with precipitation radar data and other sources, and provide 3-hourly data in the 60S-60N latitude band, at 0.25 degree horizontal resolution.
Global Precipitation Measurement mission was launched in early 2014, and provides full global coverage at 0.1 degree horizontal resolution at 30 minute intervals in time. This product is in its very early stages, and is still under development and testing.

In both cases, if you are interested in more precise rainfall estimates at a particular point in space and time, look at level 1 data. It is raw data that provides a time step for every single point along an orbital trajectory of the satellite. Use with caution.

In addition, ground validation data is available on the same server, and some or most of these data is assimilated (merged) into level 3 TRMM and GPM products.

Once you download the data, you can use their data viewer, THOR, or use your favorite programming language or analysis software to display it yourself.


What is difference between divergent boundary and hot spot? As I know, both divergent boundary and hot spot are formed by rise of magma of convention, but divergent boundary is a line and hot spot is a point, is there difference between 2 kinds of rising magma?

Divergent boundaries occur at the boundary between plates. A divergent boundary is where two tectonic plates are actively being pushed apart. Divergent boundaries create rift valleys on land and eventually ridges on ocean floors, where hotter material wells up from the mantle, cools and form new crust. For example, the East African Rift Valley (a divergent boundary), is pushing apart the African plate, separating Somalia from the continent. Eventually the rift valley will flood, producing a ocean between the newly split plates with the East African Rift becoming a mid-ocean ridge.

Hot-spots, or mid-plate tectonic activity, occur away from boundaries between plates. A hot-spot is where a plate is moving over a stationary mantle plume. Hot-spots are responsible for island-chains, such as those seen in Hawaii, which form as the plate slides over the plume or even volcanoes on land, like Yellowstone. The islands of Hawaii lie thousands of kilometres away from the boundaries of the Pacific plate on which they sit. A nice feature is that the Hawaiian island chain lies in a north-westerly line that matches the direction the Pacific plate is moving.

The main thing to keep in mind is that divergent boundaries occur at the boundaries of plates. Hot-spots occur in the middle of plates, often thousands of kilometres away from the boundaries of the plates.


What is the average depth of the ocean? We know that the ocean depth is varies from ocean to ocean. Mariana trench is about 11 km deep. If we consider as a whole, what is the average depth of the ocean?

About four kilometers, see, for example:
http://www.mbgnet.net/salt/oceans/data.htm
But bear in mind that much of the oceans, especially in the southern hemisphere, have scarcely been mapped at all, so it is currently impossible to give an accurate estimate.


Can we change the temperature in atmosphere? In the laboratory we can maintain the low level temperature like 0 to -13 degrees.
Like that can we do this process in atmosphere. For instance atmosphere temperature is 35 degrees can we change the temperature to 20 degrees or 50 degrees? Is it possible or not? If it's possible how can we do that?

You are talking about terra-forming on a global scale. To cool the entire atmosphere would result in two separate amounts of energy, one would be the thermal energy removed from the atmosphere, and the other would be the energy expended in the process. Both would be astronomic in magnitude, and orders of magnitude more than all previous components of the anthropic energy balance. How and where would we store such prodigious quantities of energy? Also, it would cost more than the gross economic product of the planet. And would it solve the problem? No, quite the reverse. It would only add to the greenhouse gas emissions. Even if we cooled the planet by 20 degrees, it would only be a matter of time before thermal equilibrium with respect to the atmospheric CO2 and water vapour would be regained. So there would be no long-term gain.

In order to cool the planet significantly we would have to reduce carbon emissions to practically nothing, and then use carbon capture and storage to depress global CO2 from the current 404 ppm to about 320 ppm. If we could do that in time for the next Milankovitch glacial entry point (an orbital feature), then there is a reasonable chance than we could put Earth back into 'glacial mode'. But as time goes by, this gets less and less likely. By the time we double CO2 relative to the pre-industrial era,  another glacial epoch looks highly unlikely. By the time we triple the CO2, we can kiss goodbye to glaciation for ever.


Do daily operations (max, min etc) on climate model data reference different periods because of UTC? If I calculate daily accumulated precipitation or daily maximum temperature from global climate data, will I be getting statistics over different local times, because the operation uses the climate model time which is UTC?

So for example, on day N I will get the maximum temperature from

midnight to 11:59pm in London, Dhaka, Portugal (UTC 0)
10am on day N to 9:59am on day N+1 in eastern Australia (UTC+10)
5pm on day N-1 to 4:59pm on day N in western US and Canada (UTC-7)

Yes, your understanding is correct.

(this is a really short answer because I can't think what else to say!)

I'm no expert on this type of simulation, but I suspect that any application where you care whether something happens in day 158 or day 159 is probably not an application that you want to be using a global climate model for...


Why is the creation of water from the combustion of hydrocarbons not listed as a cause for rising sea levels? https://iopscience.iop.org/article/10.1088/1748-9326/aa8390
According to this paper, water is created by burning hydrocarbon fuels. It seems like a major thing to exclude from "reasons the sea levels are increasing".
From the paper:

The annual global formation of water from combustion of hydrocarbon
fuels from 2005–2015 amounted to an average of $1.2 \times 10^{13} kg⋅yr^{-1}$, as
shown in figure 1. By comparison, the atmosphere is estimated to hold
on average approximately $1.3 \times 10^{16}$ kg of water, while the global
rates of irrigation-induced and natural evaporation are on the orders
of $10^{15}$ and $10^{17} kg⋅yr^{-1}$, respectively.

I understand from the figures, the amount of water introduced into the atmosphere is small compared to irrigation and natural evaporation, but that is only dealing with water that is already there.  This paper details that we are essentially pulling hydrogen out of the earth, combining it with atmosphere oxygen and creating water.
Water vapor is already listed as a GHG, so maybe it is just being swept along with that term?
I have to be making a connection that doesn't exist, right? Otherwise it would be noticed by someone / anyone else.
Make me understand why I am wrong to think that the creation of water by burning hydrocarbon fuels is adding to the amount of water in the oceans.
Thank you,

1.2 x 10^13 kg equals 12,000,000,000,000 l water. One liter equals 0.001 m³, while one km³ equals one billion (1 x 10^9) m³. So we're supposedly adding 12 km³ water to the atmosphere per year.
According to wikipedia the total oceanic surface is about 361,900,000 km². If we spread the added amount of water over all the oceans, we end up with a sea level rise of 0,03316 mm per year. The german wikipedia page on sea level rise claims - based on the  5th chapter of the Fourth Assessment Report by the IPCC from 2007 - that the annual sea level rise between 1993 and 2003 due to thermal expansion was about 1,6 ± 0,50 mm.
Since we didn't take into account sinking surface above oceanic hydrocarbon sources or the increased atmospheric capacity for water vapour due to heating, which both are connected to the effect you are interested in, I'd estimate there is an existing, but almost negligible contribution to sea level rise. Other effects contribute way more - and all of them will likely peter out, once we reduce fossil fuel consumption significantly.


Geological maps of British Columbia I’ve been doing research into mineral deposits in B.C. I’ve been overlaying old claims maps onto Google Earth maps. Are there any good public maps for metallic minerals for British Columbia online?

Although not a geologic map this site has a nice map of mines for silver, gold, copper, molybdenum, and zinc.  Below is a screenshot of just a portion of the pdf you can download.


Lack of annual slash-and-burn in North America? In many areas of South America, Africa, India and Southeast Asia, "slash-and-burn" agriculture is employed whereby every year the stubble from the previous year is burned along with other live cuttings.

In North America, this does not seem to have ever happened. It is true that in New England (where I am from) the old-time farmers cut down all the trees and burned them to get pot ash, but this seems to have been a one time event. Once land was cleared of trees, it was not burned over and over again. Also, in many cases land was cleared without burning at all, the trees and stumps simply being hauled away.

Is there some difference in climate that results in tropical areas being subjected to repeated annual burnings whereas lands in North America are not? What causes the difference?

Slash and burn has been used in North America and still is at times.  I see regular field burning near me where fields are particularly rocky and tilling if impractical for the crops grown.  It also occurs when there is intrusions of some noxious weeds that are controllable through fire as effectively and much cheaper than chemical controls.

In general, I would consider slash and burn in disfavor because of it consumptive nature.  The practice does provide some otherwise missing nutrients, but it consumes large quantities of biomass while doing so.  More favored in many regions it to use that biomass to supplement the soil by tilling it in and allowing it to aerate the soil while slowly breaking down and augmenting the soil.  Between being fortunate enough to have good soil to begin with, or the ability to augment with either natural or chemical supplements, many North American farms do not need the quick fix burning can supply so opt for the slower, longer term solution of turning in the organic materials.


Why did "Glaciologist Princess Elsa" have to leave the glacier because it was too warm? This tweet shows "Glaciologist Princess Elsa" is actually Caltech geophysics PhD student and cryoseismologist Celeste Labedz.

The BBC News article What's a 'Science Princess' doing in an ice field in Alaska? says in a figure caption:

  Celeste Labedz had to cut her research trip short as the glacier was too warm.

Question: What risks or problems would a "too warm" glacier pose to a geophysics and cryoseismology based expedition? Might the problem have been more related to safety or to the quality of the data?

I'm the scientist in the article; someone just saw this question and emailed me about it! (I'm on as a guest here since I don't have an account, so you'll hopefully trust it's me. Even if you don't believe it's me, I hope the answer will still be useful.)

It's entirely a safety issue. The best way to get around on the surface of the glaciers in this area is to cross-country ski on the snowy surface. If that snow gets thin or melts away completely, it's very risky to be on the glacier because the crevasses in the ice below become exposed. We're all trained in crevasse rescue, but we'd rather no one fall in the first place! My field site normally has ample snow thickness at the time I was there, but an early and extreme heat wave in the area put the whole icefield about a month ahead in the melt season. We did our best getting as much data as possible, but ultimately safety comes first and we had to get out of there.


Which are the equations needed to calculate how much moving Earth's water with dams would change Earth's rotation speed? According to this article Drops of Jupiter

  Raising 39 trillion kilograms of water 175 meters above sea level will
  increase the Earth’s moment of inertia, and thus slow its rotation.
  However, the impact will be extremely small. NASA scientists
  calculated the shift of such a mass will increase the length of day by
  only 0.06 microseconds

is it possible to know which equations NASA used or is it too complicated to calculate that for regular people ? (thus it would be NASA required to do the math)

You need to calculate the change in the moment of inertia of the Earth and use conservation of angular momentum. In the case of eg. a large dam, (most of) the water will ultimately come from the sea, effectively removing a thin layer of water. The contribution of the removed water to the moment of inertia depends on the distance from the rotation axis and hence on the latitude. This is a fairly simple calculation if we assume the world is all ocean. A more precise calculation would have to take into account the shapes of the oceans. You also need the moment of inertia of the earth, which depends on the density as a function of depth.

The moment of inertia of the lake is $m(R\cos L)^2$ and the moment of inertia of a spherical shell is $\frac{2}{3}mR^2$, where m is the mass of water, $R$ is the Earth's radius and $L$ is the latitude of the lake (30.82305 degrees for Three Gorges). The relative change in the moment of inertia of the earth is then
$$\frac{mR^2(\cos^2 L - \frac{2}{3})}{I}$$
(where $I$ is the Earth's moment of inertia, $8.04×10^{37}$ kg·m$^2$) or
$$1.97×10^{-11}(\cos^2 L - \frac{2}{3}) .$$
Multiplying by the number of microseconds in a day ($8.64 \times 10^{10}$) gives:
$$1.7(\cos^2 L - \frac{2}{3}) = 1.7 × 0.071 = 0.12\,\mu\text{s}$$

Why the difference from NASA's $0.06$ ? Note that the expression changes sign at  $\cos^2 L = \frac{2}{3}$ or $L ≈ 35$ degrees (fairly close to the latitude of Three Gorges). The Earth will actually speed up if the lake is at high latitudes and slow down if it is at the equator. The $\frac{2}{3}$ term comes from the "all ocean" assumption. I presume NASA took into account the shapes of the oceans and got a more accurate value for this term.


How would an icicle "grow" upwards? The other day a friend of my dad's showed him a picture of an icicle that appeared to be "growing" upwards out of a crack in a sidewalk. There were no roofs, overhangs or vehicles parked near by... It looked like a stalagmite you would see in a cave. It looked something like this*:

.

How could this happen?

* Note that this is not the actual icicle, I used this picture for an example.

If there is enough water underground, in a sealed reservoir (like under the concrete in the picture), as that water freezes, it will expand, putting pressure on what ever water is left unfrozen. That water will be squeezed out through what ever cracks it can find - in this case, upwards. Because the water is already near-freezing (perhaps even slightly below, if it's super cooled), it will freeze very quickly when it hits the air (which will be much colder than the ground, late at night). But if there is still water being pushed up from below, that ice will have to move out of the way (it's weaker than concrete). The friction of the flow of cool upwards might warm it just enough to keep it liquid, and the "stalagmite" will end up with a hollow core that the water is being pumped through, and that structure can just keep building on itself, until it is toppled by wind or gravity.

The picture is a bit grainy, but it looks like that's what's happened there. It also looks like the side of the hollow "stalagmite" has fallen off up the top, and released a bit of the remaining water (or maybe it just melted in the sun).

Edit: Hah, I knew I'd seen this somewhere before - in my freezer! This page describes how Ice spikes form - I basically got it right. It seems that they're more likely to form with de-mineralised water, and the temperature has to be within certain narrow limits.


How would the Earth look without water in the oceans? Has there ever been a movie, a documentary, or an image that provides a visualization of the oceans without water? I'm writing an article on geology and I thought a visual representation would be of great importance. Any help is appreciated.

National Geographic made a documentary called Drain the Ocean, this is You Tube link to part one. the other three parts are there as well.


Why is the concept of "mass extinction" a relatively recent development in geology? The concept of "mass extinctions", with its catastrophic connotations, is a relatively recent development in the geological sciences. It evolved in the early 1980s, driven by two landmark publications in the journal Science:

Alvarez et al. (1980) Extraterrestrial Cause for the Cretaceous-Tertiary Extinction: The proposal that a asteroid or another large impactor caused the K-T K-Pg mass extinction,
Raup & Sepkoski (1982) Mass Extinctions in the Marine Fossil Record: Suggesting the "Big Five" mass extinctions.

Why did this idea develop only in the 1980s? It was known since the 19th century that extinctions had occurred. Even the stratigraphic time is divided into units constrained by different fauna found in the fossil records. What was it that made the change from a "gradualist" perspective of things to the "catastrophic" point of view?

The idea of mass extinction is not that recent actually: Cuvier (1798), Buckland (1823) and d'Orbigny (1851) for instance were already talking about global catastrophes in earth history, linked to extinctions. But during the same period, Brocchi (1814) and Lyell (1832) proposed that extinctions of species occurred individually and were a gradual process (either only linked to an intrinsic taxa longevity for Brocchi, or variations in the environment for Lyell). Darwin, following Lyell, also thought that extinctions were gradual and not catastrophic. He also noted the fact that hiatuses in the fossil record or artificial concentration in some strata could show apparent extinction event.

The issue with mass extinction is that to demonstrate their existence you need to be able to demonstrate extinction synchronicity and quantify the amount of species going extinct (to show that it is more than just background noise).

Demonstrating the synchronicity of one mass extinction is what Alvarez et al. 1980 managed to do thanks to the Iridium layer at the K/Pg boundary. More generally, the possibility of correlating extinctions precisely is something that evolved in par with the evolution of stratigraphic tools, and the 1970-1980s is the period during which high-resolution stratigraphic methods arose (chronostratigraphy, magnetostratigraphy, stable isotope stratigraphy for instance).

Quantifying mass extinction is what Jack Sepkoski did with his compendium of marine invertebrates (see Sepkoski 1978, 1979; Raup & Sepkoski 1982, etc.). Today, the PbDb (PaleoBiology DataBase) is the project which focusses on that specific issue (see for instance Alroy et al. 2001). It still remains today the main hurdle in studying mass extinctions.

Alroy, J. et al., 2001. Effects of sampling standardization on estimates of Phanerozoic marine diversification. PNAS, 98(11): 6261-6266.
Alvarez, L. W. et al., 1980. Extraterrestrial Cause for the Cretaceous-Tertiary Extinction. Science, 208: 1095-1108.
Brocchi, 1814. Conchiologia fossile subapennina, con osservazioni geologische sugli Apennini e sul suolo adiacente. Stamperia reale. (link to 1843 reedition)
Buckland, 1823. Reliquiae Diluvianae or, Observations on the Organic Remains attesting the Action of a Universal Deluge. Murray, London.
Cuvier, G., 1798. Mémoire sur les espèces d'éléphans vivants et fossiles. Mémoires de l'institut national des sciences et des lettres, 2: 1-32.
d'Orbigny, A. 1851. Cours élémentaires de paléontologie et de géologie stratigraphique. Masson, Paris.
Lyell, C. 1832. Principles of Geology. Murray, London.
Raup D. M. & Sepkoski J. J. Jr, 1982. Mass Extinctions in the Marine Fossil Record. Science, 215: 1501-1503.
Sepkoski J. J. Jr, 1978. A kinetic model of Phanerozoic taxonomic diversity I. Analysis of marine orders. Paleobiology, 4: 223-251.
Sepkoski J. J. Jr, 1979. A kinetic model of Phanerozoic taxonomic diversity II. Early Phanerozoic families and multiple equilibria. Paleobiology, 5: 223-251.


Code for DEM based flow routing in R I have a DEM as shown for which I have determined flow paths using D8 algorithm (My own code) in R. The resulting DEM with the flow paths is also shown. The flow paths are generated in the form of lines with the help of lines function in R, joining the centers of each pixel in the direction of steepest slope. I would like to perform flow routing with flow paths being derived on the DEM. It should be noted that the flow paths are just lines plotted on the DEM using lines function and elevation of the pixels.

Is there any way to perform flow routing for a hypothetical storm event in R?

Take a look at the RSAGA package on CRAN, or the rgdal package. Many of the GIS methods can be done in R but basically act as a wrapper for saga or gdal. RSAGA is likely your best bet for processing terrains for flow analysis.

I also know of Dan Moore from UBC who does a lot of work with R and GIS applications, worth taking a look there and certainly those algorithms can be done in R directly.

There is also another post in the GIS forum on using TauDEM in R, worth taking a look as well. TauDEM in R - additional SO post

In general, rseek is an excellent search engine for exactly this type of problem in case you don't find what you are looking for in those links above.

For actual flood routing, you may be interested in the Height Above Nearest Drainage Model (HAND), which uses the same type of D8 flow accumulation algorithm to build a rapid method for floodplain mapping. Good paper on that some other 1D methods.


Is ice also created ín cold water of the oceans? Salt water of the oceans could freeze into ice at a temperature of -1,8C. Now there is a lot ice on the poles but of all the floating ice how much is that a grown in and of the water itself?

With other words, is the current of the ocean waters an obstacle for creating ice or is there a minimum temperature at which water in each case will turn into ice independent of currentstreams and is this temperature reached in the articpoles?

So I'm not asking about snow what is pressed into ice on the poles.

The National Snow and Ice Data Center website describes the process of ice formation on polar oceans. Virtually all of the young ice is made from ocean water which retains some brine in the process of forming. Older ice tends to lose the brine and have it replaced by air bubbles.

Surface ice would form differently, either by frost, which tends to form in patterns or in snow fall.  Over many years it might be possible for snowfall and surface forming ice to build up on top of permanent ocean ice. I'm not sure what the ratio could eventually become, but if sea ice was to be mostly from the air, it would need to be very old where over time, enough ice formed on top and the original ice melted from the bottom.  On average I suspect most sea ice is ocean ice though, even multi-year ice.

When temperatures are low enough (below -1.8 °C), ice forms naturally in polar ocean-water.  See phase diagram:   http://antoine.frostburg.edu/chem/senese/101/solutions/images/saltwater-phase-diagram.gif

Salt can freeze along with water in ice below -21 °C, but oceans tend to circulate quite efficiently, so -21 °C water is unlikely in oceans.


Crystallization path of diopside-wollastonite-silica systems Can someone please explain to me (or give a source) how the crystallization diagram of the diopside-wollastonite-silica system looks. I am a new learner of geology and trying to learn ternary 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 anticyclones bring clear skies in summertime? It's obvious that in summer anticyclones bring hot weather. But why clear skies?

Heat evaporates the moisture and should lead to the cloud formation, shouldn't it?

Why anticyclones are also called areas of high pressure

Let's call anticyclones areas of high pressure.

Areas of high pressure (anticyclones), pull air towards the earth's surface. The increase in the number of air particles near the earth's surface causes a higher pressure for things on the earth, hence the name.

Impact of high pressure areas on weather

High-pressure areas don't always bring hot weather.

High pressure areas do prevent the chances of clouds forming. Why? Because more air is pushing down around the earth's surface, rather than rising up in the air where it can cool and form clouds. This is why areas of high pressure (anti-cyclones) bring clear skies.

Because high-pressure areas prevent clouds forming, this can cause hot fine weather in summer when the temperatures are warm and sunny days are long, or cold weather in winter, when sunlight hours are short and the lack of clouds means any warm can escape from earth's surface and back out into space.

Background info on clouds and heat

Heat generated by the sun travels two ways:

Towards Earth: From the sun, through space, hitting the earth
Away From Earth: From the earth and back out into space

Clouds reflect heat.

Either away from earth, as incoming sunlight hits the tops of
clouds, or
towards earth, as heat radiating away from earth's surface towards space hits the bottom of a cloud and bounces back

Areas of high pressure stop clouds from forming, which can mean warm summer days or cold winter days for the reason above! (In summer, a lot of sunlight can get through to the earth's surface, in winter when there's little sun, any of the earth's heat escapes into space with no cloud to stop it!)

I presume you are a beginner, so I've given a basic and easy to understand answer. Once you wrap your head around this, I can update with more details.


Any recommendations for a good online lecture series on Metamorphic Petrology Any recommendations for a good online lecture series on Metamorphic Petrology?
Thank you in advance.

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


How do I explain why the Tibetan plateau is colder than lowlands at similar latitudes? A common layman explanation for why does it get colder to higher elevations (considering only the troposphere here) qualitatively boils down to The Sun heats the Earth's surface and the Earth's surface heats the atmosphere.  I remember that, every time I heard or read this explanation as a child, I thought: then why is the Tibetan plateau still colder than lowlands at the same latitude?  After all, the solar energy reaching the surface in Tibet is no less.  Clearly there is more to it.

Considering a remark from a quantum physics lecturer that you only really understand something after you've taught the subject twice, I'm phrasing my question as such: How does one explain, in layman terms, why the Tibetan plateau is colder than lowlands at similar latitudes?

The answer is because the Earth is not a static system.

Due to the ideal gas law, air cools as it rises.  This is referred to as the dry adiabatic lapse rate.  However, you are curious why every location on earth is not the same temperature at the same latitude.  We know this is not true. But why is not true?  Weather.

The earth, as with most natural phenomenon, attempts to achieve static equilibrium.  The differences in incoming and outgoing radiation leave the earth with net energy reserves that need to be balanced out.  Weather is the mechanism that the Earth uses to attempt to achieve balance.

Okay, so we know that weather is disrupting static equilibrium on earth.  But how does that work?  Wind.  Or better yet, advection.  Advection is simply the transport of an atmospheric parameter (such as moisture, temperature, or rotation) from one location to another.  So, wind can 'transport' temperature, moisture, and rotation.

You don't necessarily need a storm to advect any of these parameters. In fact, they are always in motion.  Cold air is always moving away from the poles.

Still, that doesn't quite answer it, does it?  Well, imagine you are hundreds or thousands of miles away from Tibet.  You aren't in a mountainous region anymore but instead a flatlands at sea level. The environmental lapse rate is 6.5°C/1000m above this location (because we are not dealing with an air parcel).  Tibet is 4500m - 8850m high.   That would be around approximately 32.5°C of cooling at 5000m.  The air that advects into Tibet from elsewhere is on average of 32.5-50°C cooler than at sea level.

So, it isn't so much that Tibet is receiving less radiation than other points at the same latitude (its not). Its more that, the air at other locations at the elevation of Tibet is much cooler than the air at sea level. Remember, we measure air temperature!


Does the Antarctic Ozone Hole affect the rest of the world? Sometimes you read about skin cancer and the ozone hole in Australia.
But when you look it up the ozone hole is basically just near the South Pole, and maybe a bit above the North Pole (because that’s where it’s really cold).

But has the rest of the world even been really affected? Looking at this NASA graphic it doesn’t seem there were significant changes for most people.  Perhaps the average ozone levels in Europe or Australia even increased?

The ozone hole size changes according to the season. It is usually larger in winter because cold temperature Why is the Ozone Layer 'hole' more pronounced in the Southern Hemisphere?

And in this graph you can see that the ozone level is lower in Australia, South Africa and south America area. http://www.cpc.ncep.noaa.gov/products/stratosphere/sbuv2to/gif_files/sbuv18_sh_latest.gif

In a broader scale, it does have an impact to the rest of the world. A thinning ozone can cause stratosphere cooling. Scientists are still studying this http://www.ucsusa.org/global_warming/science_and_impacts/science/ozone-hole-and-gw-faq.html#.WJx_YLNqPU8


In hydraulic fracturing, can total oil/gas production be broken down by stage? I have a hydraulic fracturing data set with some wells and each well is broken up into stages. My response is total well production and my goal is to be able to predict this total well production. The number of wells is extremely low (<10) for any prediction task though but there are many stages per well and each stage has a rich feature set. To synthetically increase my number of observations I want to try to derive a per stage production that is a little smarter than simply dividing the total well production by number of stages. I am thinking of using Gibbs Sampling to produce observations of stage production using the total well production and stage features as givens and a mild assumption of what the covariance matrix would look like. I am wondering from a hydraulic fracturing perspective if it makes sense to think of the total production being a sum of the individual stages?

For reference I am thinking of multiple stages in terms of this video: https://www.youtube.com/watch?v=bABA8WkxG04

Don't bother trying to isolate production by stage unless you have a production survey.  Even then it is often irrelevant as the chance of restimulating the specific rock that is lower producing is small.


Need seismic data and digital well log data from the same area? I am currently working on a project that involves the input of seismic attributes (instantaneous amplitude, instantaneous frequency etc.) to a machine learning/deep learning model (eg. A Neural Network) . The output given by the model are petrophysical properties such as Porosity,Permeability etc.

To create this model, I need seismic as well as digital well log data from the same area which I have not been able to find.

The SEG has a list of open file seismic data sets here: https://wiki.seg.org/wiki/Open_data

For a number of these surveys well logs are also given.


Lab procedure for analyzing/assessing the presence of semi-volatile solids I'm looking for a lab experiment design that shows how to measure the presence of semi-volatile solids in water (and not sludge or soil or solids). All I have found so far are chromotography/mass spectometry methods. Are there any ‘less advanced’ methods? My professor says there are, but I can’t find them.

Does anybody here know of such methods, or where I should start looking for them?

It seems to me you should draft an analytical procedure first in which you include the compounds (or compound-groups) you want to identify (qualitative) and what detection limits you need. Then get a list of methods or instruments you have access to. Then see which methods / instruments fulfil your analytical requirements. You might need to make aliquots and use two or more methods to cover all the requirements.

Complexity is usually the last thing to worry about, because you have to use what instruments you have, and often times the analytical requirements are only fulfilled by one instrument. The methods mentioned on the page you linked also guarantee that your measurements will be comparable to other peoples measurements.

Look for advice in books and lecture notes about "analytical chemistry" and "instrumental analytics". Personally I think infrared spectroscopy is pretty simple, but I don't know what your detection limit requirements are ("trace level" is very vague), and depending on your samples there might be a lot of overlap from the different organics (It also depends on how well you have to distinguish them).


Best book/s of oceanic data treatment and analysis? I would like to purchase a/some books which are really good and practical references to get into the oceanic data (wave heights,currents and sea level) treatment and statistical analysis, coming from in-situ instruments (buoys, ADCPs, etc...) or from simulation models.

It would be great if such book has also some connection with some programming language (Python/R for example).

Anyone could help?

Thanks.

My personal best is the Emery & Thomson "Data Analysis in Physical Oceanography". You can find some used versions of the previous editions for a much cheaper price. If you are able to manage the methods described in that book, you will be in good shape. The only one of your requirements it doesn't do is the coding part. If I had to choose one book, I would definitely buy this one and then search for code elsewhere.

If you want a book that provides some code and explains some of the analysis, you could try the Malek-Madani "Physical Oceanography: A Mathematical Introduction with Matlab". It is theoretical rather than focus on data analysis.

A relatively cheap book with some useful codes, not specific to Oceanography is Middleton "Data Analysis in the Earth Sciences using Matlab". Some of it might be slightly outdated, but still useful.


About Earthquakes and their properties I know this sounds like a crazy observation but San Francisco has a lot of HUGE buildings in the downtown area , millions of tons or probably more. Many Scientists think a big earthquake there is 'overdue' or maybe 'delayed' for some reason. I was thinking could all the millions or billions of extra 'tonnage' of buildings that has been built over the last 20 years say, could all this 'MASSIVE' pressure on the ground in San Francisco be somehow delaying the build up of any instabilities in the underground areas ? Maybe all the massive buildings in all big cities can serve to 'dampen' any underground instability. Do Earthquakes mainly strike near areas where there are not that many MASSIVE buildings?

The presence or absence of a large number of massive buildings has no bearing on where and when earthquakes occurs, or their magnitudes; particularly along major fault systems such as the San Andreas Fault.

Earthquakes mainly occur on tectonic plate boundaries, such as the San Andreas Fault, near San Francisco, or the fault systems through Turkey, Italy, New Zealand, near Japan and the Rift Valley in Africa. However, this does not preclude earthquakes from occurring elsewhere, such as in the middle of a tectonic plate.

For many decades some Australians thought that Australia was immune to earthquakes because it lies in the middle of the Indo-Australian plate; then a number of large earthquakes occurred in the latte half of the 20th Century causing people to have a rethink.

The fact is geological faults occur everywhere: some are major, others are minor; some are active, others aren't. If ground movement occurs on a fault an earthquake or tremor will happen regardless of any extra weight on the Earth's surface at any location.

The San Andreas Fault, like many major faults, is not one single fault, but a fault zone of sub parallel faults of varying lengths. The accumulation of stresses along the individual faults are not uniform throughout the entire system. There is no precisely predictable pattern to when an earthquake will occur or where along these major fault systems

There is a picture on the following website showing the system of faults in the San Andreas Fault in the San Francisco bay area.

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

The size and occurrence of a earthquakes along tectonic plate boundaries is dependent on the speed at which the plates are moving past each other and how much they snag on each other and the strength of the rock at the snag points. With very strong rock at the snag points a lot of pressure can build up over a long time and when that pressure is eventually released when the rock breaks or slips a strong earthquake will occur.

Many earthquakes will occur within the San Andreas Fault system, but it doesn't necessarily mean that San Francisco will be affected any time soon or how badly it will be affected.


Where is the calmest place on Earth? I have done some research online, and I've found out that Antarctica has the calmest winds (lowest maximum wind speed) recorded on Earth. However, it is uninhabitable for human life. Other very calm areas are the doldrums, but they are over water.

Therefore, I would like to know: What is the calmest place on Earth that is on or over land other than Antarctica?

PS: I'm also pondering this question about balloon chains, so I'm also interested in the places with the calmest overall wind column all the way from the troposphere to the mesosphere.

The main resistance that winds have to their movements comes from the topography and surface obstacles. Therefore, as a general rule the closer to the surface the less wind you will find. But I guess you are interested in the winds in areas clear of surface obstacles, otherwise the answer would a be a cave or a dense forest somewhere.

To figure out what is the calmest place on Earth wind-wise, we can use one of the global datasets that NASA put together (initially to help with solar and wind energy planning). One of them is a 10-year average (July 1983 - June 1993) of wind speed at 50 m above surface, ignoring the effect of trees and other non-topographic obstacles at a resolution of one degree (roughly 111 km or less).
I just loaded that dataset and searched for the minimum (and maximum) values, this is how it looks:

The minimum is not actually in Antarctica as your research suggested, but in the Amazon at longitude 68° west and latitude 0° (that's Brazil near the border with Colombia), with a mean wind speed of 1.55 m/s (5.6 km/h).

This is an enlarged version of the most relevant area overlaid with a world map for easier interpretation:

In line to what was stated at the beginning, the maximum happens in an area were the lack of landmasses allow it to blow unimpeded around the world. And it happens at 60° W -52° S, reaching a mean wind speed of 12.62 m/s (45 km/h).

Note that this analysis is valid for broad areas. And of course individual weather stations at punctual locations can give different values. As for Antarctica, the winds there are mainly catabatic, therefore at the top of antarctic domes the average wind speed are very low. For example the average at Dome C is 10.1 km/h and 9.4 km/h at Dome F. However, those values are still bigger than what NASA's models suggest for the Amazonas.

I think the model I used here is reliable. As an exercise, you can see all the images that show up in a Google search for "global mean wind speed" and you see that most images show a similar pattern, where Antarctica doesn't seem to contain the calmest place.

The model used to produce these datasets is a reanalysis, it means it takes all the weather data of the past (weather stations and satellite data) and attempts to reconstruct how exactly was the weather over the whole word. A similar kind of model takes only past weather data and attempts to predict how will be the weather over the whole world. That's a much more difficult problem, prone to bigger errors but that's actually what all the weather forecast we see on TV are based upon. One of the best global forecast models is called GFS (Global Forecast System) that is produced by NOAA's Environmental Modeling Center.

To have a sense of how winds vary in different locations and altitudes you can explore the GFS  data using Cameron Beccario's amazing vizualization tool. There you can see the predicted global wind patterns all the way from the surface to more than 26 km of altitude (here you can find a table with referential equivalences between pressure levels in hPa and altitudes). Despite those are not multi-year averages, they are still very informative. Muze, the author of the question, pieced together a beautiful animated gif that show how the above mentioned visualization looks like for the elevation range of the jet streams at about 10 km of altitude (250 hPa):

Finally, I have to note that I've interpreted "calmest" as the minimum mean wind speed. However, it would be sensible also to consider it as the place with the lowest maximum wind speed or some other metric, that would perhaps change the picture described above. And maybe using that metric one of the Antarctic domes could be the "calmest" place. But I won't extend the answer further with any possible interpretation for "calmest".


Using acoustics to measure the composition, density, and hardness of layers I am an engineering student at Alfred University and some fellow classmates and I are doing a competition, but one of the tasks we need to complete is autonomously measuring the composition, density, and hardness of layers of overburden. I was thinking that using acoustics would be possible to accomplish these things. What follows is exactly what we have to do:

"2.Create a digital core that contains the following information: The number of overburden layers in their test station
A sequence of the layers in order from softness to hardest
The thickness of each layer
The digital core should result from information garnered using system telemetry and not via placing a ruler down the hole. Teams may not touch the layers to determine hardness."

The reading has to be continuous. For example another way we could do this is measure the resistance on our auger as it tries to dig a hole. This would provide a continuous reading, but might not be accurate because our frame holding the auger may not be solid.

The question is "can we use sound waves to measure the composition, density, and hardness of each layer?" The total overburden depth will be between 0.5 and 0.8 m. I don't know if this is a large enough volume to measure all of these things using sound waves.

The answer to your question is 'yes': you can probe a medium of arbitrary complexity using sound waves, and relate the propagating wave to the physical properties encountered on its path: the stiffness (Hooke's law), density (Newton's law), and you can locate the layers by figuring out where the stiffness and density change. If the competition only requires you to submit a hypothetical method, such a seismological method certainly fits the bill.

Unfortunately, when it comes to practically implementing such a method; I advice against it. You'll find too many obstacles on your path that require expert input and money. For example:

You require a very well controlled source: you need to know exactly the source function (the wavelet) that ends up in your medium; which is distorted by the actuator's frequency response, and which is distorted by the usually weak coupling between your source and the medium.
You require a high-resolution receiver as well, to record the signal that propagated within the medium, which is similarly not trivial to create.
After you have solved these (difficult!) problems, you have to turn your recording at the surface into a quantitative 2-D/3-D physical model of the Earth, i.e. a model that tells you the velocity of the medium and the thickness of each layer. This requires extensive data-processing and typically requires many numerical wave simulations; only then, when your numerical simulation predicts data that resembles the data that you recorded, you may assume that you may have found the approximate physical state of the medium. This technique is called Full-Waveform Inversion, and is the only one I'm aware of that will provide the answer to all your questions.

The problems in the last point are due to the fact that surface recordings provide a massively underdetermined problem. Say, as an example that you drop a weight onto the medium, and then it takes 100ms before you hear the first echo come from the medium. Then you infer that the wave traveled back and forth to depth with a certain velocity. This gives an equation: $100\ \text{ms} \approx \frac{2h}{V}$ that doesn't reveal what the depth $h$ actually is or what the velocity $V$ actually is! The problem is thus poorly constrained by the data, and you require a lot of data to get a good understanding of the subsurface. Then, furthermore, your waves propagate in an elastic medium which excites many types of waves: compressional waves, shear waves, surface waves, $\dots$,  which all travel at different speeds and are sensitive to different physical properties. You require some good data-processing to isolate only the wave that you are interested in!

As said in the comments, the size of the medium is no limitation, you simply scale up the wave's frequencies to the ultra-sound region! It is generally thought that you can locate objects in the Earths subsurface when they are separated by a distance $d\geq\lambda/2$, where $\lambda=\frac{V}{f}$ is the wavelength, with $V$ the velocity of the medium and $f$ the wave's frequency. The average speed of a compressional wave in rocks is about 5km/s, thus you require a frequency of at least $f=\frac{5\,000\ \text{m/s}}{2d\ \text{m}}$ to find your object of size $d$. If you resolution requires separation up to 1cm, you require a wave with a frequency of at least 80 $\text{kHz}$: well into the ultra-sound territory!

I'm sorry to give such a demotivating answer, but seismology is simply too complex to be a viable project for anything but a fully-fledged multi-year commercial or PhD project. My suggestion would be to build a variation to a Cone Penetration Test, which measures the resistance to pushing a cone into the ground (which is directly related to the hardness of the rock!) at a fixed speed. Whenever the resistance changes you are encountering a new layer, such that the size and number of layers is easily inferred. That would satisfy all the requirements, I think. Then again, I have no expertise with the Cone Penetration Test, and perhaps it is not as easy as I think...