Total differentiation The local derivative is linked to the total derivative by:

$\frac{\partial T}{\partial t} = \frac{DT}{Dt} - \mathbf{U} \cdot \nabla T$

and the -$ \mathbf{U} \cdot \nabla T$ term represent the change by advection.

So, for example cold air blowing in a region of warm temperatures will bring cold advection and it will contribute negatively to the local derivative.

I have trouble interpreting the $\frac{DT}{Dt}$ term. If it represents how the temperature is changing withing the flow regardless of the flow moving to cooler/warmer regions, what could this be caused by ? Say expansion and consequent cooling of the air parcels ?

As far as the question "What can be causing this?," there are a variety of reasons. Let's look at the First law of Thermodynamics (including molecular diffusion): $$\frac{DU}{Dt}=c_p\frac{DT}{Dt}=Q-p\frac{D\alpha}{Dt}+\nu \nabla^2 U$$, where $U$ is the internal energy of the ideal gas, $Q$ is diabatic heating, $p$ is pressure, and $\alpha$ is the specific volume, $\nu$ is the molecular diffusivity, and $c_p$ is the isobaric specific heat capacity.

So, without diabatic heating, one way is to change the volume or pressure, which varies the most with changes in altitude (you can rewrite the $-p\frac{D\alpha}{Dt}$ term as $\alpha \frac{Dp}{Dt}\approx \alpha \frac{\partial p}{\partial z}\approx\alpha\rho g=g=-\Gamma_d c_p$, $\Gamma_d$ is the dry adiabatic lapse rate). Using that relationship, (1) may be rewritten as $$\frac{\partial T}{\partial t}=\frac{Q}{c_p}+\nu\nabla^2T-\frac{g}{c_p}-\Gamma_d- \vec{u} \cdot\nabla T$$ Another way is through molecular heat exchange, which is so small it is usually neglected, unless it is in a micrometeorological context. And then there is diabatic heating, perhaps the most loaded term of the equation.

Diabatic heating is any heating source that requires entropy to change. This includes latent heat exchange, radiative heating, etc. Turbulent mixing may arguably be considered in this for large scales, but not small scales.


It is possible to reduce global sea level via filling empty lowlands with ocean water? There are empty lowlands in Australia and Iran like Dasht-e Lut. If we fill these lands with ocean water then could we reduce the global sea level and save coastal cities like venice?

Based on calculations of the effect of melting ice on sea level, we know that to effect a 1 mm change in global sea level requires around 360 km3 water. The largest lake by volume, Lake Baikal, contains just under 24,000 km3 of water. So if you created an equivalent lake you would lower sea level by 66 mm. At current rates of global sea level rise that would offset less than 20 years of melting ice and thermal expansion.


Where are these volcanos as seen in this space tweet? In his recent tweet from the International Space Station as it's current Mission 56 Commander, NASA astronaut Andrew J. Feustel says:

  This is #Indonesia as viewed from the @Space_Station. With the low clouds it is easy to see the peaks of the volcanoes associated with the Sunda Megathrust subduction zone that lies at the tectonic boundary of the Indo-Australian and Eurasian plates.

I can't visualize where these are on Earth, mostly because of the cloud cover in the image. Where is this?

This was taken looking from around above or near Western Australia, looking north. You can see a fuzzy green patch to the centre and left of the photo. That's the eastern part of Java.

Here's the image where I labelled some of the volcanoes, and a reference image from Google Earth.


What has been the influence of the moon on Earth's temperature? What proportion of Earth's internal heat is generated by tidal flexion as a result of the orbiting moon, and would it have been significantly greater four billion years ago when the moon was closer? Has it ever been enough to affect surface temperature to an easily measurable extent?

note: This is not a duplicate of the following because there are no clear, quantitative answers specifically about heat generated by tidal flexion. Instead those answers focus on heat produced in the oceans.

Is the Earth heated up by the tides?
How much energy does the Moon transfer to the Earth, does this affect the Earth's surface temperature?

The complications of calculating the moon's contributions to earth's heat budget are touched on in Emergence of a Habitable Planet (2007) by Zahnle, et.al. in Space Science Reviews, a paper trying to determine   when in earth's history the planet's surface would become cool enough to support life. The portion of the paper that relates to tidal heating suggests that the early moon contributed substantially to the interior heat of the earth system for about 1.2 million years, but as the moon's orbit widened, the earth cooled and solidified, and water condensed into oceans, the moon's contributions gradually became minimal.

  Viscous damping of tidal motions generates heat. Therefore tidal
  heating occurs most strongly in materials that are solid but close to
  melting. This introduces the possibility of a governing feedback that
  works through the dependence of viscosity on temperature. If tidal
  dissipation exceeds what the atmosphere can radiate, the excess heat
  raises the temperature, which lowers the viscosity, which in turn
  lowers the rate of tidal dissipation. This looks like a stable
  feedback. It follows that, while tidal dissipation was important, the
  base of the mantle was solid but the rest of it was fluid, and tidal
  heating generated almost all of the thermal energy radiated to space.
  In the limit of an asymptotically thick steam atmosphere, tidal
  dissipation would have been regulated to generating heat at the
  runaway greenhouse limit of ∼140 W/m2.

In a caption for a figure the authors also note:

  Tidal heating plays an important role in prolonging the magma ocean.
  Tidal forcing wanes as the Moon evolves away from the Earth.
  Thereafter heat flow is controlled by convection of the solid mantle.
  By 4.4 Ga the global average heat flow would have been ∼0.5 W/m2.
  Later in the Hadean typical heat flows would have been 0.2–0.3 W/m2,
  not enormously larger than what they are now. For comparison heat flow
  today is 0.065 W/m2 through the continents and 0.1 W/m2 through the
  ocean crust.


Can mining trigger earthquakes? Are earthquakes more common in mining regions than they would otherwise be? e.g. is the frequency of earthquakes in those regions different when mining is occurring than when it is not?

I am interested in earthquakes generally, but also particularly interested in earthquakes strong enough to have damaging impacts (to life and infrastructure).

Yep, mining can trigger earthquakes.

According to a Scientific American article:

  We've been monitoring [The Geysers] since 1975. All the earthquakes we see there are [human] induced. When they move production into a new area, earthquakes start there, and when they stop production, the earthquakes stop.

This is talking about geothermal power. They create small little fractures, which cause tiny earthquakes. They then harness this power for electricity.

Earthquakes can also be caused by coal mining and other mining, according to this study:

  Klose has identified more than 200 human-caused temblors, mostly in
  the past 60 years. "They were rare before World War II," he said.

  Most were caused by mining, he said, but nearly a third came from
  reservoir construction.

  Oil and gas production can also trigger earthquakes, he added.

  Three of the biggest human-caused earthquakes of all time, he pointed
  out, occurred in Uzbekistan's Gazli natural gas field between 1976 and
  1984 (map of Uzbekistan).

Another study also concluded this.


How do the swirls and veins in marble form in detail? I am finding surprisingly little information about this. I imagine that the process is somewhat like foliation except because the particles that go into marble (to my knowledge) don't have any noticeable elongation you get more amorphous billowing shapes rather than more regular layers. Any more details on this?

EDIT: Or does it have something to do with the magma intrusions that contribute to the marble formation process?

What you see in marble are not veins (for example in the picture of yours). By the term vein in geology we mean a magmatic intrusion in the rock in the form of vein. Can a marble have magma real veins? Yes. The process is explained here: https://en.wikipedia.org/wiki/Intrusive_rock
The 'veins' you are referring to are coming from the different beds of the rock formation. Beds form by the deposition of layers of sediment on top of each other and they might have variations in mineral composition.
As BillOer mentioned already, marble is a metamorphic rock formed from limestone. Can I have different type of 'veins' and swirls in the metamorphosed limestone in comparison with the initial limestone? YES. Why? Because during the metamorphic phase, pressure and heat is applied to the rock. So, we might have a partial melt and re - crystallization, a pressure slide forming swirls and new 'veins'.


Meteorology in Canada I'm interested in understanding how meteorology works in Canada (esp. from an Open Data perspective).

Can someone explain, or provide resources, that indicates an overview of the actors involved on the spectrum from initial data measurement through to the weatherperson on the TV screen?

My main concern is to understand if data is made freely available, but I am also interested in the various players and their position in the public/private sector. (I feel that this is relatively well documented for the USA, but I can't find the story in Canada).

Canada is fairly similar to the US in how this works.  As pointed out in a comment, Environment Canada is the primary provider of observation and forecast data within Canada.  You can access plots of this data and somewhere on that site you can probably also get access to the raw data files to process on your own.

Canada also partners with other states to provide data globally that others can use, some of which provide global model products such as ECMWF and NOAA.  The data from the Euro is not completely open but the data from the GFS is freely available.

The person on TV is working with their fellow station meteorologists and often under a chief meteorologist.  They are going to look at data provided by Environment Canada observations and model output, global model data from others and perhaps private sector weather provider companies who themselves ingest all of that data and have operational meteorologists on staff.

The general flows of data will be

Observations taken by Environment Canada are ingested
Data is shared with other weather agencies, Canada ingests global weather from others
EC runs forecast models
EC makes observational and model data available

Private sector companies may use a workflow like:

Ingest data from government sources
Process data, run models, make forecasts
Make that data available to clients

TV stations will have a flow like:

Ingest data from EC, global models and possibly private sector companies
Interpret data and make local forecasts
Present forecasts to the public.


Stochastic seismic inversion Could anyone recommend a free and reliable software capable of Stochastic seismic inversion for my project? am aware that Petrel is capable of Genetic inversion based on a non-linear multi-trace approach but i have no clue what that is about, I prefer stochastic method because it is more reliable. Any help?

You may want to investigate the Delivery package available from

http://www-old.dpr.csiro.au/StochasticSeismicInversion/

'Delivery is an open-source, trace-based Bayesian seismic inversion code for use in oil reservoir characterisation at the early development and appraisal stage. See the Computers and Geosciences paper for most of the details, and the Delivery4D preliminary writeup for the time-lapse modelling.'


Permeability of well screen as a limitation to a slug-in test If you were to do a slug-in test where you put in a known volume of water, would there be a point where, say if the formation was extremely permeable, the permeability of the screen itself would be measured?

High permeability (K) values for rock /sediment would be 1x10+2 to 1x10+5 (darcy)
The table below shows permeability values for sand/gravel packs placed around the well screen.  Well Screen itself would have even higher K values.

I would say, that well screen itself (not including the sand and gravel pack around the well screen) will not limit the results of slut test results.

Essentially, for the well screen to limit slug test results, you need to place the well into a large cave or min void and the use a very large slug volume if you hope to measure the screen itself.

Note: Permeability values can approach very large values in limestone with caves.

Note: my answer assumes that the well construction materials and methods are known that were used to install the well being tested.  I am also assuming the well has a manufactured well screen not a piece of pipe with 3 hack saw cuts to allow water to flow. Not knowing the well configuration, can reduce the accuracy of slug test results.

Source: Petrowiki


How much energy is needed to alter the path of a hurricane? Suppose we spot an Atlantic hurricane very early. How much energy should we expend to alter its track:

with nuclear detonations (let's forget about the side effects for the moment)?
with a large orbital geostationary mirror illuminating say, the subtropical ridge?
by any other means (microwave heating in the troposphere?)

References on these and other methods from the NOAA Hurricane FAQ:

Silver iodide
Aerosols/surface modification
Nukes, specifically:

  A fully developed hurricane can release heat energy at a rate of  $5-20\centerdot10^{13}$ watts and converts less than 10% of the heat into the mechanical energy of the wind. The heat release is equivalent to a 10-megaton nuclear bomb exploding every 20 minutes. According to the 1993 World Almanac, the entire human race used energy at a rate of $10^{13}$ watts in 1990, a rate less than 20% of the power of a hurricane.

Water absorbing substances
Surface cooling with icebergs
Expending hurricane's energy
High altitude particulate seeding
Hygroscopic particle seeding
Miscellaneous means

Why the above-mentioned FAQ isn't enough

It's incomplete (doesn't include heating/illumination from satellites)
Doesn't include a fully-developed nuclear scenario
Has no formula linking time since hurricane formation, energy applied and cross-track difference at landfall on the East Coast

This is not a complete answer, but offers insights to research of some perspectives of the question you raised.
There has been a document recently written about this, Controlling Hurricanes
Can hurricanes and other severe tropical
storms be moderated or deflected? (Hoffman, 2004). In it, there are several main considerations, one major consideration in relation to your questions is that studies show that changes in the energy available can potentially alter the path of a hurricane.  The studies reported in the article

confirms that these massive, chaotic systems are susceptible to
minor changes in their initial conditions—for instance, the air temperature and
humidity near the center of the storm and in the surrounding regions

Using computer simulations of hurricanes, they confirmed that

changes in
precipitation, evaporation and air temperature could alter a
storm’s path or weaken its winds.

Even though the article suggests one of your suggestions, about microwave heating of the air or the water, this power would be harnessed by satellite based solar panels, the main simulated methods appear not to be a case of adding the energy to the hurricane itself - but rather robbing the hurricane of its energy sources, examples include
Cloud seeding with silver iodide or similar material is suggested, these would promote precipitation, which would rob the eye wall of

the water it needs to grow and
intensify

Another method, and rather unique is the use of biodegradable oil on the water's surface, specifically

Biodegradable oil could be distributed across
the sea surface in the path of a hurricane
to limit evaporation—the source of a
storm’s energy

A study by Stanford University, reported in the article Offshore wind farms could tame hurricanes before they reach land, Stanford-led study says (Carey, 2014), suggest by computer modelling that

"We found that when wind turbines are present, they slow down the outer rotation winds of a hurricane," Jacobson said. "This feeds back to decrease wave height, which reduces movement of air toward the center of the hurricane, increasing the central pressure, which in turn slows the winds of the entire hurricane and dissipates it faster."

The data indicated that

In the computer model, by the time Hurricane Katrina reached land, its simulated wind speeds had decreased by 36-44 meters per second (between 80 and 98 mph) and the storm surge had decreased by up to 79 percent.
For Hurricane Sandy, the model projected a wind speed reduction by
35-39 meters per second (between 78 and 87 mph) and as much as 34
percent decrease in storm surge.

In terms of using a nuclear detonation to stop or divert a hurricane, the author of the article Can You Stop a Hurricane by Nuking It? (2012) describes the potential effectiveness of this method

might be about as effective as trying to stop a speeding Buick with a feather.

mainly due to as you said in your question:

the same amount of energy released by exploding a 10-megaton nuclear bomb every 20 minutes.

A nuke on water nearby may make the hurricane worse, by heating the water, thus 'feeding' the hurricane.


How, exactly, do scientists know location of earliest continents? How can scientists know where the earliest continents were located?  Supposedly, Pangaea has formed, re-formed, moved all around, etc.

Do paleogeologists primarily rely on paleomagnetism, paleontology, or what?

Well, the really earliest continents, the answer is we don't. As you go further back the uncertainties get larger and larger. It has been speculated that there have been around 4-5 super continents like Pangaea. Before Pangaea there was Rodinia, but before that it gets more and more sketchy.

The oldest ocean floor is only Jurassic. So ocean palaeomagnetism is only good back to the Jurassic, but can be extrapolated a bit beyond that. You have continental magnetism and this helps place the palaeo-latitude - for example, we know the UK was just south of the Equator in the early Palaeozoic. That doesn't give you relative location but is an important piece of the jigsaw.

The other is stratigraphy. Yes that includes palaeontology, but before the Palaeozoic, palaeontology is limited (eg. do Ediacaran species have global or regional distribution? what about earlier single celled organisms?). It can also include rock correlations, isotope signatures, etc. For example, the Lewisian Gneiss is a piece of Archaeon craton in NW Scotland that has some well studied dyke sequences. If you find similar gneisses elsewhere with the same dates and dykes with the same chemical signatures, then you can hypothesise they were a part of the same unit and they split after the dyke intrusion.


Probability ( weather tomorrow = weather today)? What is the probability that the weather tomorrow will be equal to the weather today (e.g. more specifically, if we know there had been more than 1mm precipitation during one day, what is the conditional probability that there will be more than 1mm precipitation also the next day)?
Can you guide me to some references?

I want to use this example in a lecture to illustrate to physics students the concept of probability in forecasting.

As mentioned, the term you are looking for is persistence.  Generally its strength varies wildly depending on what variable you are looking at, the location, and by whether you also further select other factors like season and other meteorological variables.

I would expect daily precipitation persistence is a relatively bad predictor, given that precipitation is often either a short-term event driven by very transient dynamics like frontal passage, or sees a fairly random spatial distribution over small areas driven by small perturbations and nonlinear interactions (thus typically leading to rain PoPs regularly being more useful than binary forecasts).

Persistence is often used as a basis to compute forecast skill... but it seems to be be reported in research using more sophisticated summarization metrics like skill scores than straight probabilities.

However, with a little searching I did at least find A Markov Chain Model for the Probability of Precipitation Occurrence in Intervals of Various Length by James E. Caskey, Jr., which did at least have a table along the lines you've asked... for Denver, Colorado between 1949-1958, using 0.01" (0.254 mm) as the condition:

For those struggling to figure the values out, in this table when $\rho_1$ is similar to $r_1$, utility of precipitation persistence is low.

Colorado is a mountainous area, so I could imagine large-scale wind direction aloft probably proves more significant than many areas.  For a location like Florida in the summer or Oklahoma in the spring, I'd imagine the skill is lower as persisting variables are less important.  Still, because humidity often varies more slowly, regularly controlled by air masses and large scale wind directions, which often are directed by large synoptic weather features, there will likely be at least some difference in the conditional probabilities in all locations/seasons.

Don't know if that data is useful enough for your lecture purposes, but hopefully it offers a branch to seek into.  You may be able to dig up a few more similar tables by searching on through research journal results in places like the AMS or, if need and desire be, could calculate such variables from station data available at sites like NCEI.


Is the concept of seismogenic zone still relevant after the 2011 Japan earthquake? The concept of subduction seismogenic zone, where megathrust seisms occur in a layer between an upper and a lower limit is well documented in the 1990/early 2000 literature :

Some example :

Pacheco, J. F., Sykes, L. R., & Scholz, C. H. (1993), Nature of seismic coupling along simple plate boundaries of the subduction type. Journal of Geophysical Research: Solid Earth, 98(B8), 14133–14159. http://doi.org/10.1029/93JB00349
Hyndman, R. D., Yamano, M. and Oleskevich, D. A. (1997), The seismogenic zone of subduction thrust faults. Island Arc, 6: 244–260. doi:10.1111/j.1440-1738.1997.tb00175.x

But is this concept still accurate and used in the scientific community now ? i.e. after the megaseisms of Indonesia in 2004 and Tohoku in 2011, where huge areas break up to the surface and generate big megatsunamis. More exactly, is the notion of upper limit still making sense and, if yes, what are the currently-supposed parameters which control it ?

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

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


How big is the influence of tree leaves on global windsystems? As anybody knows, there are a lot of forests.
I stumbled upon the question whether these have any effect on the global wind-systems.

Imagine the following situation. All trees suddenly die in an instant. Soon the leaves will dry and fall down, thus only the wood-part remains standing.

The wind can now blow much easier through the trees.

But will this really have an effect?

Do forests influence the windsystems around the earth significantly? How would these winds change, if at all? Would storm-like squalls be more common?

Wind is largely driven by differences in atmospheric pressure.

The effect of trees and forests is to force the winds to flow over the forests. The loss of leaves in forests would result in winds having a larger impact at ground level. Also, due to the change in the surface roughness to air flow because of the loss of leaves the wind would lose less of its energy.

It has been suggested in this paper, though not yet fully accepted by many, that water vapour in the atmosphere due to evaporation and transpiration can contain sufficient latent heat to accelerate air and drive winds.


What are Atmospheric Rossby Waves and how do they affect the weather? I've been researching Atmospheric Rossby waves but from the multiple sources I used they all seem to be in conflict. Some say Rossby waves are parcels of air moving from east to west due to the coriolis effect (which seems like a description for a jet stream) while others sources say it's the curving of the jet streams. I have a hard time understanding Atmospheric Rossby waves and how they affect the weather and climate.

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


Current temperature increase VS decrease during the little ice age Looking at the following temperature reconstructions i have two questions (source: wikipedia):

Why is the y-axis centered around -0.2 °C?
Why are the consequences of the current temperature increase by +0.4 °C considered so "catastrophic" when the -0.8 °C during the little ice age  was not?
Maybe i am mistaken but looking at the chart the current +0.4 °C doesn't seem so much more varying from the median that the -0.8 °C do.

To be sure about why it appears to be centered around -0.2°C, you'd have to go to the original source of the graph.  However, as an educated guess, I would imagine that they are showing the anomaly compared to some recent period, such as 1961-1990 or 1971-2000, as is commonly done.  From your Wikimedia Commons link, this figure appears to be original work by a Wikipedia author.  The link does not appear to state this, so this is rather sloppy and perhaps illustrates why it's preferable to obtain information from peer reviewed sources.

If the temperature increase stays at +0.4°C, it is not catastrophic.  However, considering the greenhouse gases (GHG) we have already pumped into the atmosphere, temperature increase will not stay at +0.4°C.  With currently projected increases in GHG emissions, the global average temperature increase may range from anything between +1.5°C and +6.5°C, with some regions exhibiting far larger temperature increases than that.  At such scales, the entire climate system might enter a different state, which means many regions will have climates very unlike before.  And then I'm not even mentioning the problems associated with sea level rise yet.


Why are thrust faults older than normal faults in the Himalayan-Tibetan plateau? In the Himalayan-Tibetan plateau, both normal and thrust faults are observed. Geological
age dating suggests thrust faults are older (before 18-20 Ma) than the normal faults (after 18-20
Ma). Explain this observation.

Why is this the case? I'm unable to explain this using whatever I have learned so far. I am a beginner in the field of Earth Sciences, and I would appreciate a detailed answer (or any helpful pointers) so I can better understand these concepts!
Thank you!
P.S. I'm also new to this website, so pardon me if my question isn't in line with any of the guidelines. Let me know how I can improve it.

In line with what strawberry-sunshine has answered, and to put it into more layman terms, after a compressive episode there's a distensive one.
Imagine you have a volume of sand, and you are compressing it horizontally in one direction, it is confined in the other horizontal direction and the only force acting vertically is gravity.
During compression, the sand will reorder itself in response to the applied stress: this reorganization are the equivalent of the thrust faults. You keep applying force until movement is negligible. Then you stop applying it althogether. The weight of the sand will force a second reorganization to adapt to the new conditions. This is the equivalent of a distensive period, and the displacements inside the sand mass are the equivalent of the normal faults developed in the second stage of the orogen.
Although reality is more complicated that that, I hope this example helps you understanding why normal faults can be younger than thrust faults.
Best regards


Is the Earth's hot inner core necessary for life? The inner core of the Earth has an enormous temperature of around 4300 degrees Celsius.  Is this large inner core temperature an important factor contributing to the ideal temperature that is necessary to maintain life as we know it on the Earth's outer-crust and atmosphere, or is the temperature of the core quite irrelevant to the temperature on the Earth's crust?

Whether the high temperatures of the core is strictly necessary to maintain a habitable temperature at the surface I'm not sure, as the global temperatures are largely controlled by insolation and the greenhouse effect. The black-body radiation temperature of the Earth is about -18 °C, and even a more realistic estimate of the surface temperature without an atmosphere is around 1 °C [1]. That being said, it depends on what you define as life, if the Earth had no atmosphere the temperature would have been lower, but organisms would have adapted to that if they existed in the first place.

As Neo and winwaed also mentioned, the molten iron in the core does protect organisms against harmful radiation from the sun, by providing the Earth with a shielding magnetic field.

Also, the hot core and mantle most likely did influence the origin of life to begin with, as near hydrothermal vents in the ocean floor conditions might have been or are suitable for spontaneous reactions that lead to the formation of self-reproducing molecules [2]. Note this is not in the Darwinian sense Neo talks about (Darwin's book is called On the Origin of Species, not On the Origin of Life), but in the microbiological and geological sense.

[1] https://en.wikipedia.org/wiki/Black-body_radiation#Temperature_of_Earth
[2] Martin, W., J. Baross, D. Kelley, M.J. Russell (2008) Hydrothermal vents and the origin of life. Nature


How quickly is the Earth shrinking? Except for ice, acetic acid, bismuth and gallium and a few other things materials generally shrink when they cool and solidify, so I'm pretty sure Earth has as well.

It probably wouldn't be measurable over a period of years, but models of the Earth's current and historic rates of heat flow can probably be used to estimate a rate of change of Earth's average size and possibly oblateness.

Right now WGS84 uses 6378137.0 meters for Earth's equatorial radius and a flattening at the poles of about 1/298.257222.

How fast might those change over any given million years?

(Related to answers to the question Thermal expansion of Earth, which I only realized after having saved this answer. So, in principle, a double post, but I was asked to undelete :-))
Earth's thermal history may give some hints -- not sure if this is an actual answer to the question. It seems like Earth's radius depends on the layering of mantle convection, and that though there were significant changes during the Archean Eon and earlier, the current and recent (since the late Archean) shrinking rate is slow (a reduction of 12km in radius in 2.5Gy).
Source:
Expanding-contracting Earth by Tsuchiya et al. 2013 in Geoscience Frontiers

Questions that remain:
What about the core ?
And is mass loss or gain from astronomical processes significant enough ?
I would like to add that WGS 84 is a reference ellipsoid, and height values can be (are) given as positive or negative numbers. They can be updated every now and then by satellite. Also, I would assume that tectonic processes or local anomalies may by far outweigh any signal from thermal shrinking over the course of next centuries or even millennia (speculation).


Are trends in crossplots of compositional data from different analyses valid? Some geochemistry papers that I have read contain crossplots of compositional components that resulted from different analyses of a rock sample.  For example, one is the percent volume of TiO2 versus parts per million (ppm) of Nb.  Results from such a plot seem highly suspect to me because of the closed nature of both attributes.  However, I am not a geochemist, so I would appreciate any feedback on the validity of such results from both a geochemical and data analysis perspective.

The question is not exactly clear. Are you asking about the different methods used to analyse the rock, or are you asking about using closed (aka compositional) data in a bivariate plot?

Using different methods

This is just fine, as long as both methods are accurate. For instance, you can analyse a mineral for major elements (e.g. TiO2) using an electron probe, and then use LA-ICP-MS for trace elements (e.g. Nb). If both methods are properly standardised and all possible interferences are taken care of there is no reason why the analyses should not be used together. If the analysis was not performed properly, I wouldn't trust even as single one, regardless of whether it is used in a database together with data acquired using a different method.

Closed data

Closed data means that it has to sum to 1 or 100%, and this can cause correlations that don't necessarily mean anything. A simple example is an MgO vs FeO plot in olivine. Of course there would be a negative correlation! This type of plot would be obvious and wouldn't tell us a thing. However, in more complicated cases, this becomes less and more of a problem. It mostly depends on a case by case basis. Note that if you're comparing a major element (TiO2) with a trace element (Nb), there is less of a problem. The trace element is not one of the components that hardly has any implications for the close problem. Whether you have 10, 20 or 100 ppm Nb will not change anything for the 5% of TiO2 you got in your rock.

Classic statistics done on compositional data is almost always wrong. In the past 20 years or so, a new statistical field called "compositional data analysis" has emerged to solve some of the problems arising from the closure problem. In short, it means that you have to transform all of your data to log-ratio form, do your stats, and transform it back. This can't solve all of the problems, however.

Now, the question is - do we care that it's wrong? In the vast majority of papers, there is hardly any statistics done of compositional data, and many correlations and trends are eyeballed and drawn by hand. Often, the hassle of doing statistics the correct way does not actually contribute everything. I've heard senior petrologists claim more than once that "if it looks like a line, it is a line. If it doesn't, then it is not a line. I don't need the R2 and p-values for that".


Why do some parts of the West Coast of North America get hot later in the year than others? Southern California is currently in the midst of a heat wave, which is an unwelcome stress for stay-at-home laws during the Covid-19 pandemic. Indeed, the California coast sees its warmest temperatures in well into the fall, peaking in September-November, often with a secondary peak through April-May. This is also the peak of the wildfire season. Go north about 300-600 miles to Washington or Oregon (and southwestern BC) and the warmest times of the year (plus the peak of the wildfire season) are smack dab in the middle of early July through to mid-August, like in most of the CONUS excluding the Desert Southwest. NOAA's map of when the average "warmest day of the year" is in the CONUS shows this difference quite clearly. Why the difference? I know that the California coast is Csa/Csb while Washington and Oregon and BC are Cfb, but I don't think that explains everything.

I am not an expert, but ...

the pacific ocean has seasonal patterns:

You can think of the water coming from the North being colder, the one from the South warmer.
On top of that, then you have associated rainfall etc. that will affect the climate (it can work both ways, warmer water may mean more rain, then more cloud coverage so less solar radiation so slightly colder days).


What is a reasonable range of values for resistance to heat flux? I am developing a simple parameterisation scheme script to predict surface temperature.

The script calculates six heat fluxes including sensible heat flux using a resistance to heat flux parameter.  The literature I've checked describes resistance to heat flux as taking values greater than 0 and having units of $\rm{s} ~ \rm{m}^{-1}$.

Sensible heat flux is calculated as,

$Q_H = \frac{\rho c_p \Delta T}{r_H}$,

where $\rho$ is air density, $c_p$ is specific heat at constant pressure, $\Delta T$ is change in temperature between the ground layer and the surface layer and $r_H$ is resistance to heat flux.

What is a reasonable range of values for resistance to heat flux in meteorology?

A single range would be useful but ranges for urban, agricultural, forest, desert, mountain and marine areas would be preferable.

Additionally, I'm open to alternative suggestions for calculating sensible heat flux but using x % of solar radiation feels overly simple.

For context:

My script is currently predicting day time temperatures which are probably too low and night time temperatures which are probably too high.  I'd like to verify that the sensible heat flux calculation is the cause but I need to know what reasonable values for resistance to heat flux are.

This is based on the second chapter of David Stensrud's Parameterisation Schemes book and is inspired by Luke Madaus' blog post, Digging into a "simple" weather model.

Alec Bennett calculates resistance to heat flux values in an urban canyon as part of his MSc in meteorology dissertation: Heat Fluxes from Street Canyons.

The calculated values range from 76.6 to 84.2 and are based on measurements taken on May 18th and 19th 2004 from 08:00 to 17:00 (both days).

See the two tables in the Appendix on page 68 for the full range of values.

I have not read the entire thesis.  It's unclear to me what confidence I should place in these values.


How does heat get transported between the surface layer, twilight zone, and the deep ocean? Just as importantly, how do we measure the heat that's transported from the surface layer into the twilight zone and deep oceans?

I think the simplest answer is through water mass formation, the resulting thermohaline circulation, mixing caused by wind predominantly in shallow regions, and through downwelling processes. The heat exchanged with the atmosphere in the surface layers determine the temperature of the near-surface water. From there, mixing (caused by wind, for instance) will transfer some of the heat to lower layers in the ocean. In the case of areas of water mass formation, the sinking of surface waters is usually enhanced. When the water masses are away from the ocean boundaries (surface and bottom), then the thermohaline circulation controls the transport and exchange between water parcels and thus the heat transfer.


Which type of seismic sensors usually used in Earthquake Early Warning? As I'm a newbie in seismology and related area, I would like to know which type of seismic sensors usually used in earthquake early warning systems?

Accelerometers, preferably triaxial (i.e., those that record horizontal and vertical motion). Beyond that your question is indeed a bit too open-ended. Some use many cheap MEMS (http://onlinelibrary.wiley.com/doi/10.1029/2008GL036572/epdf; https://www.theverge.com/circuitbreaker/2017/7/13/15963996/raspberry-pi-seismograph-early-warning-earthquakes; these are similar to those found in phones), some use more expensive but reliable equipment (https://kinemetrics.com/post_products/episensor-es-t/)...


Should total ground heat flux be 0? In the context of the land surface, the ground absorbs heat from radiation (also some times from precipitation and advection), and releases heat through evapotranspiration, advection and radiation, and run-off. If it were a closed system, you would expect the net heat loss/gain to be zero (at least on a reasonably long time scale, that irons out daily and seasonal cycles, and noise). However, there is also heat from the mantle to consider, and also heat conduction to the oceans.

Are there other avenues for heat loss or gain from the soil? Are any of these significant in a climatological context? Or should the total heat flux into (or out of) the ground from the atmosphere be equal to zero (or close enough for practical purposes, over time scales longer than a year)?

It depends what your practical purposes are. Maybe you can treat it as 0. But in general, no, because it is not closed, due to geothermal heat flux, and anthropogenic imbalances. Also, even if assuming 0, that would be over long time scales and integrated over the earth surface. There are spatial heterogeneities.


How does elevation affect the amount of rainfall received? How does elevation affect the amount of rainfall received? Does elevation affect precipitation?

Elevation affects temperature which affects the amount of rain. Most raingauges around the world are within a few hundred metres of sea-level, i.e the range in which most people live. Within this range the rainfall-elevation relationship often appears to be linear. However, as the temperature gets cooler with altitude, the maximum precipitable moisture decreases drastically, so the rainfall-altitude curve reflexes back upon itself, so that there is an elevation of maximum precipitation ('EMP'). This variation variies with several factors, such as continentality, 'tropicality', aspect, rain shadow and barrier effect. Some examples of the EMP, are (in metres): Tajikistan 3800,
Alberta Canada 2360, European Alps, 2250, NW Pakistan1500, Oman 1400 to 2200, Kilimanjaro Tanzania 1500, and Hawaii 900. In the case of polar regions the EMP is ground level because the rainfall-altitude relationship is nearly always negative. Above the EMP the rainfall decreases rapidly with altitude, which is why high mountainous regions are essentially deserts.

Wherever there is significant relief in a catchment, the first step is to determine whether the catchment is all below the EMP. The second step is to process the historic record to see if a second order, or even third order rainfall altitude regression is a significant improvement upon 'linear'. If you want further refinement the seasonal rainfalls, or rainfalls from different directions, often have markedly differing rainfall-altitude relationships. If you want to go the whole hog, and be scientific about it, then the rainfall approximates a multi-variate solution, with components of
altitude, altitude squared, aspect, regional trend, rain shadow and barrier effect. This can be solved as an equation of the form: $$R = aH + BH^{2} + cA + dT + eS +f'BE'$$


Term for the thing that shines radiation onto a black body I think I have the hang of black-body radiation: a black body receives radiation passively and then emits some portion of it (the earth emits stored solar heat, e.g.).

Is there a parallel term for something like the sun that generates its own radiation?

The Sun is also regarded as a black body. Any body that radiates energy following Planck's law of black-body radiation, and absorbes energy at all wavelengths can be considered as a black body. This is an idealization, but if Earth is approximated to a black body, the Sun can be considered one as well.

The case of the sun is not very different to that of Earth: The stuff that makes up both is mostly opaque (plasma for the sun rock for the Earth), but at some point both bodies become transparent (in the Sun when it is cold enough such that electrons recombine with atomic nucleus and form gases, in the Earth at the base of the atmosphere), the base of the transparent layer and the transparent layers themselves emit electromagnetic radiation according to their temperature following Planck's law of black-body radiation, and absorb pretty much any incoming radiation regardless of its wavelength.

The concept of black body (or gray body) only refers at the fact that a body absorb all (or a constant fraction for a gray body) the energy it receives regardless of the wavelength (color), therefore it looks black. Similarly, it must emit in all wavelength too, with the intensity at each wavelength (color) following Planck's law of black-body radiation.

Therefore a mirror is not a black body, neither is a fluorescent lamp, nor a tomato. Because a tomato reflects red light more than green. However, if the thermal balance of a tomato is mainly controlled by the exchange of infrared radiation, you can treat it as a black body, because it acts as one in the infrared spectrum (i.e. if your eyes were sensitive to infrared radiation only, a tomato would look black or gray). In the same way, despite the fact that Earth isn't black, it can be approximated to a black body and with such approximation you can get very accurate results of its energy balance.

Going back to your point. Black bodies can have internal energy sources (like the Sun), and in the absence of the Sun, the hot interior of Earth would also act as an energy source and the Earth would emit more energy than it receives, in the same way the Sun does.

So anything can shine radiation onto a black body, that is precicely because it is a black body and absorb all kinds of electromagnetic radiation. I hope this clarifies your doubt.


How on "Earth" can you make all those measurements of Earth forming? This question is a result of recent news that Earth had a "boring billion" years in which mountains ceased to grow, and subsequently hindered life evolution.
The article went on to give extraordinary details the scientists have provided.
They know that the Earth's mountains were not growing anymore, the crust was then thinning, and the ocean life couldn't get nutrients to help evolution.
There was also a recent animation of Earth's tectonic plates over their lifetime and how the continents shaped into what they are now.
How did they know all that stuff?  How did they know the tectonic plate moved from here to here a few billion years ago? Or how mountains no longer grow, or, or, or...
I understand the concept of carbon-dating, and that's about it. Are there are any other crazy methods that enable them to make these mind-blowing measurements?
I don't mind a detailed, jargon-filled explanation, but hopefully it can still make sense to someone generally interested in Science like myself.

How on “Earth” can you make all those measurements of Earth forming?

One word: Zircons.
Zircons rank very high amongst the techniques used to measure the age of the Earth, and the age at which the Earth later cooled down. One of the key elements in zircons is zirconium. There are other elements that have similar chemical characteristics to zirconium. One of these is uranium. Both uranium 235 and uranium 238 eventually decay to lead. Lead is extremely incompatible with zirconium from a chemical perspective. All of the lead in a zircon could only have resulted from radioactive decay.
The question focuses on the "boring billion" years in the Earth's history that occurred well after the Earth formed (over three billion years after the Earth formed). Zircons were key in that analysis as well. There are other elements other than uranium that are chemically compatible with zirconium. One of these is europium. The presence or absence of europium in zircons indicates whether or not mountains were eroding at the time those zircons formed. The ratio of uranium to lead in those zircons indicates how old those zircons are.


The Role of the Antarctic Circumpolar Vortex & Ocean Current in Keeping Antarctica Frozen An offshoot from the question how does Antarctica stay frozen?

Do the Anatarctic circumpolar vortex and circumpolar ocean current play a role in keeping Antarctica frozen?

The Antarctic Circumpolar Current keeps the warm waters away from the higher latitudes because Antarctica is disconnected from other land masses. This in turn amplifies the westerlies and therefore, polar front Antarctic Circumpolar Current prevent any warmer air/water to enter the high latitudes of Antarctica.[more on this: wikipedia]

During the Oligoncene/Eocene boundary about 32 million years ago, the Tasman Passage opened which gave rise to the onset of Antarctic glaciation [more on this wikipedia]


What determines how fast clouds move? Do cirrus clouds in the upper troposphere move faster than cumulus and stratus clouds in the lower atmosphere?

What about clouds associated with extratropical systems, compared with clouds in the tropics?

Cloud particles are suspended in air, and their movement is governed by:

Wind; whichever way the wind blows, the clouds go (with some exceptions such as lenticular clouds; thanks jamesqf comment).  The wind is often strongest in the upper troposphere (there are no clouds in the upper atmosphere), so upper tropospheric clouds will move faster than near-surface clouds.
Convection: strong updrafts will force particles upward, as will forced convection by wind reaching obstacles
Particle size: larger particles are more likely to fall down.  Note that "fall down" may be used either relative to the surrounding air, or relative to the ground (i.e. precipitation that may or may not reach the ground).

So the type of cloud is indirectly relevant: different cloud types are associated with different particle sizes, are to a larger or smaller degree the consequence of convection, and are more or less likely to contain precipitation-sized particles.


How to split climate modes of variability into positive, negative and neutral phases? How can I split all the climate modes of variability that you can find here, into positive, negative and neutral phases?

I know that depending on the climate mode there exist different methods of achieving this.

Do you know any general literature that can help me?

Thanks

I think thats a lot of information on the link you pasted. and the indexes shown there are mostly in time (time-series).
Please note two important steps.
FIRST: the index you want to use is already produced in scientific way and published so how is the index produce please read the relevant paper for that which can help. Apart from that these indexes are mostly (Not all of them) are usually developed to capture/shows standardized/normalized/Anomalous  behaviors of the system. So these indexes are representation of the systems with mean of zero and standard deviation of usually one in case of standardized index, and so does varies for each one of them. The anomaly is different story and i won't go there.

SECOND: Now the deviation of the index from mean (which is zero) shows the deviation from mean conditions (that means from neutral conditions). So positive and negative will show the modes of system based on intended interpretation. like for strength positive deviation will be termed as strong and vice versa.

Finally you can select the positive and negative years as modes of climate with positive and negative deviation from mean. Further to dig deep you can look for mechanism and principals that led to these deviations.

If you want to use your data and look for modes of climate, then i will suggest PCA, SVD and EOF analysis which may not be applicable in this case.
I hope that will help


Looking at ocean depth/latitude profiles of dissolved oxygen and nitrate. Why is dissolved oxygen low when nitrate is high? I was looking at a depth profile of a segment of the Atlantic Ocean. What is the relationship between dissolved oxygen and nitrate? When nitrate is high, dissolved oxygen is low and vice versa. I've been trying to work out why this is, but I'm drawing a blank.

In general the relationship between dissolved oxygen and nitrate is complex. While in areas of water mass formation, especially in the Arctic and Antarctic Oceans, nutrient concentration and dissolved oxygen can be high, water mass evolution and biological activity can rapidly modified these concentration. The relationship is affected by several factors including: 1) the age of the water mass: the "older" the water mass (longer time since in equilibrium with atmospheric oxygen), the lower the dissolved oxygen concentration; and 2) the proximity to primary productive areas like the surface: the higher the primary production, the lower the nitrate concentration.

In some parts of the interior of the Atlantic Ocean, the water masses present (North Atlantic Deep Water, Antarctic Bottom Water) are pretty old and haven't been in contact with the surface layers for a while, so their oxygen concentration is high while they remain nutrient rich. The water masses in the surface layers have recently been in contact with the atmosphere and thus have a high oxygen concentration. Meanwhile, by being near the surface they are subject to primary production that tends to rapidly consume the nutrients (like nitrate). The relationship is highly variable spatially specially near the coastal regions, where processes like upwelling/downwelling can rapidly modified nutrient and oxygen concentrations.


Why is there a logarithmic grid on this plot? Why is there a logarithmic grid when these wireline density and neutron porosity logs have linear scale labels, and when these logs are usually displayed on linear scales?

It's a mistake.

You probably know this, but for anyone who's interested, these wireline logs are:

DRHO — density ('RHO') correction (delta, or 'D') in g/cc.
DPHI — porosity ('PHI') from density ('D'), as a fractional proportion.
NPHI — porosity from the neutron log ('N'), as a fractional proportion.

All of these logs are usually displayed on a linear scale. Indeed it wouldn't make sense to display them on a log scale, which is mainly for displaying resistivity logs, e.g. the induction log. Even if they were, it wouldn't make sense to show the usual 4 octaves (0.2 to 2000 for resistivity), given the range of the data and the scale of porosity values geologists are interested in.

It's not clear if the data have actually been displayed on a log scale, or if it's just that the grid has been erroneously added. I would treat the data with suspicion.


What causes jagged appearance of mountains in SE Asia? For some time now, I've noticed that mountains in southeast Asia seem to be unusually "jagged" with steep surfaces.  My basic knowledge of how mountains are formed (via geologic processes) tells me that it's more common to find mountains like these in glacial areas (e.g. northern Canada, Norway, etc.), whereas those formed by tectonic plate collisions appear more "traditional" (e.g. main range of Himalayas, Andes, etc.), and geologically old mountains have a weathered appearance (e.g. Appalachians).

What caused/causes these SE Asian mountains to have their distinct appearance?

Examples (from Flickr):

David Hammen has already answered with the correct term in his comment.

Karsts are formed as water dissolve rocks, typically carbonates (as limestone or dolomite) or evaporites.

Karst landscapes can originate from karst caves, formed by groundwater flowing through the rocks. When the caves eventually collapse (see image here) a rugged landscape is left behind. Karsts are also formed on the surface as limestone dissolves and forms spectacular landscapes, as the Tsingy in Madagascar or from sea erosion, e.g. calanques (karstic valleys).

The landscape is also known as Pepino Hills sometimes mogotes, if they are surrounded by flat landscape.

Another interesting feature is that as karst caves collapse, the cavity fills up with material from the ceiling and the cavity can continue to migrate upwards through the stratigraphy. Those karsts can be important channels for groundwater or petroleum. Sometimes the collapse material is more resistant to erosion than the surrounding rocks, and we get pinnacles of karst breccia left behind.


Why do climate experts from the UN/IPCC rarely mention Grand Solar Minimum? I've read many papers about Grand Solar Minimums and Glassberg Minimums, known to science for a very long time, and studied and monitored with many public funds. History shows solar activity is the main driver of our climate, and additional contributors like orbital parameters and geomagnetic field intensity are also still connected to how much energy the Earth gets from the Sun.

The present trend towards a Grand Solar Minimum was predicted since the '70s and we already see signs of it in solar activity and in our climate, yet it seems to have consistently been ignored by climate experts, by our governments, and by the media. Why is this the case?

Solar activity reconstructed from tree rings and Carbon-14 data:

(Some pertinent studies regarding such Minimums include the iconic paper J.A.Eddy, 1976: The Maunder Minimum and this 2014 paper by Valentina Zharkova on predicting the next solar cycles, among many others.)

The IPCC do mentions solar minimums and maximums, as part of extremely careful treatment they do of the reconstructions and predictions for the changes in solar irradiance. The Assessment Report 5, Working Group 1, Chapter 8, have a whole section (~4 pages) dealing with solar irradiances.

If the IPCC don't mention grand solar maximums/minumums that often, is because the research in the area have shown that solar minimums and maximums have smaller impact in climate than other factors. Therefore, such factors deserve more attention, like Greenhouse gases or land use changes. These factors deserve more attention both because they have a greater impact on climate and because we can do something about them. When it comes to solar activity we can't do much anyway.

The work of the IPCC is to combine the research of the whole scientific community, their conclusions are not based in the result of a single study but in the combination of pretty much all of them. Some studies could be contradictory, so instead of cherry-picking what suits them, they compare and combine all the studies to have the most reliable answers and a good idea of the uncertainties. If predictions of multiple models differ a lot it means uncertainties are large. If they all give the same result, we can be a bit more confident about it.

For example, the figure 8.11 compares the reconstruction of solar irradiance between years 1750 and 2000 from six studies:

You can see how the Dalton minimum shows up around 1810-1820, but the total solar irradiance change is rather small (less than 1 W for over a total of 1360 W).

Here some excerpts from the IPCC reports that are relevant to this question, and where solar minimums are mention and considered in the wider context of climatic forcing (text between square brackets were added by me for clarification):

Page 662:

  Satellite observations of total solar irradiance (TSI) changes from
  1978 to 2011 show that the most recent solar cycle minimum was lower
  than the prior two. This very likely led to a small negative RF [Radiative Forcing] of
  –0.04 (–0.08 to 0.00) W m$^{–2}$ between 1986 and 2008. The best
  estimate of RF due to TSI changes representative
  for the 1750 to 2011 period is 0.05 (to 0.10) W  m$^{–2}$. This is
  substantially smaller than the AR4 estimate due to the addition of the
  latest solar cycle and inconsistencies in how solar RF has been
  estimated in earlier IPCC assessments. There is very low confidence
  concerning future solar forcing estimates, but there is high
  confidence that the TSI RF variations will be much smaller than the
  projected increased forcing due to GHG during the forthcoming decades.
  {8.4.1, Figures 8.10, 8.11}

Page 690 (explicit mentions of grand solar minimums):

  8.4.1.3 Attempts to Estimate Future Centennial Trends of Total Solar Irradiance

  Cosmogenic isotope and sunspot data (Rigozo et al., 2001;
  Solanki and Krivova, 2004; Abreu et al., 2008) reveal that currently
  the Sun is in a grand activity maximum [a.k.a. grand solar maximum] that began about 1920 (20th
  century grand maximum). However, SC [solar cycle] 23 showed an activity decline not
  previously seen in the satellite era (McComas et al., 2008; Smith and
  Balogh, 2008; Russell et al., 2010). Most current estimations suggest
  that the forthcoming solar cycles will have lower TSI [Total Solar Irradiation] than those for
  the past 30 years (Abreu et al., 2008; Lockwood et al., 2009; Rigozo
  et al., 2010; Russell et al., 2010). Also there are indications that
  the mean magnetic field in sunspots may be diminishing on decadal
  level. A linear expansion of the current trend may indicate that of
  the order of half the sunspot activity may disappear by about 2015
  (Penn and Livingston, 2006). These studies only suggest that the Sun
  may have left the 20th century grand [solar] maximum and not that it is
  entering another grand [solar] minimum. But other works propose a grand [solar]
  minimum during the 21st century, estimating an RF within a range of
  -0.16 to 0.12 W m$^{–2}$ between this future minimum and the present-day TSI (Jones et al., 2012). However, much more evidence is needed and at
  present there is very low confidence concerning future solar forcing
  estimates.

  Nevertheless, even if there is such decrease in the solar
  activity, there is a high confidence that the TSI RF variations will
  be much smaller in magnitude than the projected increased forcing due
  to GHG (see Section 12.3.1).

Summarizing, the IPCC consider solar irradiance variations, the timing of solar minimums and maximums. However, it consider also many other factors that also affect Earth's energy budget. Then, they do predictions based on the combined effect of all these factors. In contrast, some people tend to focus on just one factor (as solar activity) and erroneously assume that it will dominate over all the others.

For the particular case of solar activity, as you can see in the cites above. The IPCC acknowledge the possible occurrence of a solar minimum in the future, but combining all the models they conclude that there is a high confidence that its effects will be much smaller in magnitude than the projected increased forcing due greenhouse gases.

Part of the reason your question might not be well received is because it starts from an assumption that is false: "climate experts from the UN/IPCC never mention Grand Solar Minimum". They do mention it, and if you follow the references in the IPCC you will find plenty of discussion about Dalton, Maunder and older Grand Solar Minimums. And part of that discussion is to estimate the real impact that those events can have in Earth's climate. Then the IPCC get those estimates and figure out how they interplay with the many other factors that conjugate to determine current and future Earth's climate.


Temperature as a function of luminosity and greenhouse gas concentrations The evidence seems clear that there is an interrelationship between solar luminosity, greenhouse gas concentrations, and temperature.

Has temperature as a function of luminosity and greenhouse gas concentrations been developed?  If so, what is the accuracy and precision?

You need a radiative transfer model and global climate model to do it with greenhouse gases.  you can derive the temperature without greenhouse gases as discussed below:

The absorption is highly variable depending on wavelength and can be seen in this graphic:

Radiative transfer through the atmosphere is specific to pressure, temperature, and wavelength. So in order to calculate the contribution of greenhouse gases you need to know their concentration distribution both vertically and horizontally not to mention an accurate representation of the atmospheric conditions. It's not one general function... it's millions of functions that all get integrated together and vary dynamically in time and space. I suggest you look at the HITRAN database for the complexities in absorption potential of different greenhouse gases.

You may also be interested in climate sensitivity paramaters.
From wikipedia http://en.wikipedia.org/wiki/Climate_sensitivity :

"For coupled atmosphere-ocean global climate models (e.g. CMIP5) the climate sensitivity is an emergent property: it is not a model parameter, but rather a result of a combination of model physics and parameters. By contrast, simpler energy-balance models may have climate sensitivity as an explicit parameter.
 (ΔTs) = λ (ΔRF)
The terms represented in the equation relate radiative forcing (RF) to linear changes in global surface temperature change (ΔTs) via the climate sensitivity λ."

This is convenient because if you know the change in concentration of a gas and the corresponding RF you can compute a change in surface temperature.  Though, I believe the climate sensitivity parameters are particularly for certain time and concentration regimes.


Sources or strategies for stone identification I have a bunch of semi-precious stones here, but I am not very learned in geology etc and I would like to have some way to know what kind of stones they are. As far as I understand question about stone identification are considered off-topic here. Is there such a reliable source so I can identify the stones by myself?

Thank you!

Are your stones raw or are they cut & polished as they would appear if mounted in jewellery pieces? There are tests such as streak & hardness which can be done to raw stones but not to polished stones because these test would damage the polished surface.

There are a number of websites that can be used, such as:

Rock Identification Made Easy
Rocks: Igneous, Metamorphic and Sedimentary

Tests that should be done include:

Color
Luster
Hardness - usually involves testing with the blade of a pocket knife
or similar
Grain size - the size of mineral grains in the stones. If no mineral
grains are obvious the stone may be "glassy"
Streak - the color left on a piece of white ceramic when the stone is
rubbed on the ceramic.


What are the major differences between weather models and climate models? Some weather models include GFS (Global Forecast System) and NAM (North American Mesoscale Model).

Some climate models include CCSM (Community Climate System Model) and the NASA GISS (Goddard Institute for Space Studies) model.

What are the differences in the types of physics, parameterizations, and other properties that they use?

The major differences between weather and climate models are many.  At their core lie the same set of primitive equations, but from here there are many differences.

A weather model only (skillfully) predicts about 10 days into the future, while a climate model integrates forward in time for hundreds of years.  The main difference here is that in a weather model, we care about the when and where of a storm or front.  In a climate model, you get weather, but you don't really care too much where or exactly when the weather is as you are looking for a long term means (e.g. a weather model cares where a hurricane is, and when/where it will impact land, whereas a climate model may only care the average number of hurricanes per year and not about where the details of those storms).

Other differences:

Spatial / temporal resolution

Because climate models run for much longer into the future than a weather model, it will have more integration timesteps for the same temporal scale.  This is relaxed by increasing the model timestep, but for numerical stability reasons the higher your timestep the more coarse your spatial resolution must be.  As a result, in general, climate models run at larger temporal and spatial scales than weather models.  The coarser resolution may force more parameterizations in the climate models.  For example a 3 km weather model may explicitly resolve convection, whereas a 30 km climate model will certainly not and need to parameterize convection.
Data Assimilation (DA)

Weather and climate models vary in their use of DA.  The biggest difference is how DA is used to "spin up" the model to the initialization time.  For weather models, if DA is used at all, you may only have a few DA steps spaced a few hours apart before the model starts integrating into the future.  For a climate model the DA period may be 100 years long before the present time is reached and forecasting begun.   However:

  This incorporation [of DA into climate models] occurs at a number of stages of the model development, including parametrization of sub-grid scale effects and model tuning. The process is not, however, done systematically and current practice is not thought of as "data assimilation."  There seems to be a growing realization that DA will have a significant role to play in future climate model development. This is, in part, driven by the need to quantify uncertainty in the model predictions. Nevertheless, there is not a consensus as to how DA should be used in these large-scale climate models. (source: http://www.samsi.info/working-groups/data-assimilation-ipcc-level-models-climate-uq )

Coupled models

Weather models may represent the ocean as a parameterized surface flux (of momentum, moisture, etc) or perhaps handle it through data assimilation.  Climate models typically couple the atmosphere model to an ocean model and simulate the ocean as well.  The climate models in actuality are typically suites of models that all communicate with each other.  You may have a model for atmosphere, one for soil, one for ocean, one for vegetation, one for chemistry, etc.  A weather model may have these features, but typically as parameterizations.
Spatial coverage

Weather models vary from global models to very localized regional models, which can in some cases be very idealized.  Climate models tend to be global.  This doesn't change the physics involved, but can influence the specific forms of the equations.  A global model will solve in spherical coordinates and many use spectral methods.  Regional weather models will use Cartesian coordinates and may make other assumptions that simplify the physics for the specific purpose the model (e.g. a storm scale idealized weather model may neglect Coriolis).


Why does relative humidity drop if I open the window in winter? What about the temperature drop? I understand that 40% rel. hum. at 0 °C is less absolute humidity than 40% at 20 °C. However, assume that we have 2$~m^3$ of air. Both are 40% humid at 20 °C. Now we exchange 1$~m^3$ with air that is 40% humid at 0°C. Then according to this picture we should get 7$~g\, m^{-3}$ and 2$~g\, m^{-3}$ of absolute humidity for each part. So that's 4.5$~g\, m^{-3}$ on average. Now the temperature should be 10 °C (right?). Then, 4.5$~g\, m^{-3}$ means a relative humidity of around 50%! So why does relative humidity drop in reality? Is it because the temperature would actually be higher somehow?

Let's do this with accurate equations. We know how to calculate the saturated water vapour pressure for temperature $T$:
$$e_s(T)=e_{s0}e^{\frac{h_i}{R_w}(\frac{1}{T_{s0}}-\frac{1}{T})}=610\text{ Pa} \times e^{5423(\frac{1}{273\text{ K}}-\frac{1}{T})}$$
$e_s$ is saturated water vapour pressure as function of $T$ in Pascals
$T$ is the temperature in Kelvins
So, the saturated water vapour pressure at $T=0°C=273K$ is equal to $e_s(273K)=610 Pa$. Similarly, $e_s(293K)=2360Pa$ and $e_s(283K)=1230Pa$.
So we have two parcels of air: 1. 20°C, 40% and 2. 0°C, 40%. What are the masses of the water vapour in both parcels?
$$e=f\times e_s(T)$$
$f$ is relative humidity, $e$ is the water vapour pressure
$$m(T)=\frac{eV}{R_w T}=\frac{f\times e_s(T)\times V}{R_w\times T}=\frac{fe_s(T)V}{461\frac{J}{kg}T}$$
$$m(293K)=0.0070kg$$
$$m(273K)=0.0019kg$$
The next step is to combine these two masses:
$$M=m(293K)+m(273K)=0.0089kg$$
So the density is $\rho=\frac{M}{V}=0.0045\frac{kg}{m^3}$
The water vapour pressure is given by:
$$e=\rho RT=587Pa$$
The relative humidity is then:
$$f=\frac{e}{e_s(283K)}=0.477$$
So this is around 48% of the relative humidity.
Why did I put here so many equations? Simple! These equations hold on high degree of accuracy, so they can't be wrong. Why would the relative humidity drop in reality?

Also, for Skew-T Log-P lovers:

This solution is even more concise and less error prone.


How should I choose the block size in constrained model-based inversion? In constrained model based inversion, block size (in ms) is one of the inversion parameters. Specifying the block size value in the software divides the pseudo-velocity log into that number of layers or blocks. A smaller block size means higher resolution but that doesn't mean that one should specify smallest value because sometimes inversion result gets unstable. So how should one assign the block size parameter in model-based inversion?

It depends.†

Some factors to consider:

The sample interval of your seismic data. there's not a lot of point in being smaller than that. For most legacy data it's 4 ms; these days it's often 2 ms. This is a lower bound; you can increase from here if your data have limited bandwidth; there's no point using less than 8 ms for data that's just noise past 50 Hz.
What is the scale of your problem? If this is part of an exploration exercise and the model is areally large, then you can safely and justifiably lose temporal resolution. If it's a reservoir characterization problem, then there's probably some feature you really care about: minor reservoir units, thin heterogeneities, etc.
How much time have you got? Small samples means more compute time, more statistics, more fiddling with details. It also means more time to simulate later, if you're doing flow modeling. Since you will no doubt end up doing everything multiple times, you need a model that is both useful and iterable.

I think there are at least a couple of approaches that avoid having to choose now and stick with it:

Start large, figure out the workflow, then reduce the size and watch the stability. Iterate until you have the right combination of detail, stability, and convenience.
Model the big picture at low resolution, and more interesting subsets of the data at high resolution. Make the large interval an integer multiple of the small to facilitate merging them later.

Note that some properties, such as velocity, are scale-dependent. Be careful how you upscale them. Read up on Backus averaging, starting with Chris Liner's recent work.

† How's that for a geoscientists's answer?


Why is the ice on a frozen lake sometimes cracked? The YouTube video Skating Lake Baikal, the world's deepest lake - BBC News shows a very heavily cracked lake. It doesn't just appear to be a fault line. It appears to be an actual crack that started that goes all the way to the surface. I believe it's natural. I have two questions. My first question is

  When an ice layer on a frozen lake is cracked the way I described, is it plausible that it happened completely naturally with no human intervention such as having walked on it when it was thin?

My second question is

  If the answer to my first question is yes, then what is one plausible cause of it?

If the answer to the first question is yes, I really only need the answer of one plausible cause of ice being cracked in that way without human intervention. However, it would be nice if you could give me as many plausible causes from fundamentally different categories as you can find.

Ice does crack completely naturally without human intervention. There are many reasons it could do so, one is as mentioned before mechanical stress from in- and outflow that lifts/settles the ice cover.

Another one is temperature stress from density changes, because ice changes its density e.g. depending on diurnal temperature changes or simply by cooling as it thickens (or warming as it thaws).

... and more.

Changing density:
https://www.engineeringtoolbox.com/ice-thermal-properties-d_576.html


I have found this fossil tooth, could it be pliosaur ? Or maybe theropod? Lenght: 10 mm, striated, circular cross-section

Site: Brno-Hády (limestone quarry), Moravia, Czech republic, central Europa

Age: Jurassic, oxford

The site is a good source of fossil shark teeth, but this tooth I am wondering about has absolutely different structure and does not have as strong luster as shark teeth have.

An example of shark tooth fossil from Brno-Hády site:

See my shark-tooth photos here.

Most likely plesiosaur. That fluted structure is indicative of marine reptile teeth. My first guess was mosasaur but their are a lot of plesiosaurs from that formation so I would go with that. It is obviously a shed tooth which makes it harder. shark teeth flare out at the base becasue they attach differently than marine reptile teeth, sharks need more surface area for a strong connection.  Hopefully a marine reptile person can give you a tighter identification, I mostly work on dinosaurs.


Identifying sedimentary rocks in hand specimen I'm currently learning how to identify rocks in hand specimen. The initial classification into igneous, metamorphic, and sedimentary is mostly ok, but I'm having a problem with further identifying sedimentary rocks—I don't know how to tell if they're calcareous or siliceous without using HCl, which seems somewhat impractical to use on every sedimentary rock I see. Is there any good way of telling?

When learning to distinguish between siliceous and calcareous samples you should use a handlens.  Look for quartz, feldspars or micas.  Quartz clasts may be frosted, or you may be able to see conchoidal fracture.  Calcite will be very soft compared to both feldspar and quartz, and should fail to scratch copper (or at least not scratch it very well, while a quartz rich sedimentary hand sample will scratch glass.

For really fine grained stuff, there are times when you may need to use the context of site where the sample is from if you don't have HCL.  There can be sedimentary rocks that are made up of siliceous clasts that react with HCL due to calcite in the matrix, so HCL can be misleading.  I've even found that some mudstones and limestones can have an organic odor.

Lastly, there are structures that can suggest if a sample is siliceous or calcareous.  Styolites would suggest non-siliceous while thermal alterations like liesegang banding would suggest siliceous.

The more samples you tackle, the easier it gets.


Why is the warm phase of the Pacific Decadal Oscillation associated with stronger El Niños? This is a question inspired by the post at Cliff Mass Weather Blog: "Is a Super El Nino Coming Next Winter?".

  There is something else.  You ever hear of the Pacific Decadal
  Oscillation?  This is a cyclic phenomenon of the Pacific ocean that
  has a great impact on sea surface temperatures and other parameters.
  A graph is shown below.  We were in the warm phase from roughly 1976
  to roughly 2005 and now appear to be in a cool phase.  The strongest
  El Niños like to be in the warm phase, which is not where we are now.
  So perhaps we should be careful about predicting super El Niños.

I'm wondering: do we have a mechanistic explanation as for why?

According to the State Climate Office of North Carolina webpage Global Patterns - Pacific Decadal Oscillation (PDO), experts believe

  the PDO can intensify or diminish the impacts of ENSO according to its phase. If both ENSO and the PDO are in the same phase, it is believed that El Niño/La Niña impacts may be magnified. Conversely, if ENSO and the PDO are out of phase, it has been proposed that they may offset one another, preventing "true" ENSO impacts from occurring.

Essentially, almost analogous to constructive and destructive interference in sound.

Another relationship, from the University of Alaska, Fairbanks webpage The Pacific Decadal Oscillation also asserts that

  A positive, or warm phase PDO, produces climate and circulation patterns that are very similar to El Niño. Likewise, a negative, or cool phase PDO, produces climate and circulation patterns similar to La Niña (Gershunov and Barnett, 1998).

As can be seen in the image below:

Image source: Pacific Decadal Oscillation (PDO) Graphics

The consequences for forecasting are summed up by the NASA News web-article A Quirky El Niño as being the case

  If El Niño begins during a cool phase of the PDO, El Niño tends to be milder and less predictable. El Niños that come during a warm PDO are stronger and "better behaved, in the sense that we can predict their consequences

References:

Gershunov, A. and T.P. Barnett. Interdecadal modulation of ENSO teleconnections. Bulletin of the American Meteorological Society, 79(12): 2715-2725.


Are "rainy season" and "less rainy season" good ways to describe Amazon seasons in English scientific language? I'm a Brazilian native. Here, the English translation to the most didactic way to express the Amazon seasons are: "rainy season", and "less rainy season", because it always rains a lot, but there is a period when there is less. Does anyone know if this is the best way to express this in English scientific language?

Dry season

While not being very descriptive, 'dry season' is in general use, even for rainforests (Af Koppen climate, if you will). Example papers using the terminology here.


Is it inevitable that a mega tsunami will hit America? According to a documentary, "Mega Tsunami - A wave of destruction", most mega tsunamis are caused by landslides creating tsunamis 10 times the size as those caused by earthquakes. It was said that there is a volcano in the Canary islands that holds water in an enclosed basin, which heats up every time the volcano erupts. It was said that this basin will cause the surrounding lands to crack and produce a massive landslide that will lead to a tsunami reaching America with a height as tall as a 50 story building.

Is it true that this mega tsunami is inevitable or very likely to occur?

As a lecturer I had during my undergraduate put it: if you draw your information from BBC/Discovery Channel documentaries, you will believe we could get a 100-million-people-killing disaster every week.  The collapse of the Cumbre Vieja is but one of those perceived threats.

How do such documentaries get their info?  Scientists develop models, then run them.  Remember than all models are wrong, but some are useful.  Using their models, they speculate that if the substance of the mountain has a certain shape, and if the volcano erupts in a certain way, and if this causes a landslide in a particular way, with a couple of more ifs, then they speculate that there might be a huge tsuname destroying the eastern US.  Do they state this with certainty?  Absolutely not.  Do other scientists agree with them?  Not really.  Does Discovery channel care that it doesn't appear very likely?  No.

The already linked Wikipedia article Cumbre Vieja#Future threats answers this particular one better than I can do.  Don't worry and sleep well ;-).

Oh, and you must visit, it is spectacular!

La Palma, 27 December 2012.  Certainly, the inhabitants of the shores of the Cumbre Vieja are more at risk than the inhabitants of the US east coast. (P.S. I'm cheating, this is actually some 15 km north of the dangerous part of the slope.  But still, if this mega-tsunami does happen, I think the TV networks will forget about the poor islanders :()


What are Horton's laws? Robert E. Horton coined these four laws:  the law of stream numbers, the law of stream lengths, the limits of infiltration capacity, and the runoff-detention-storage relation.

What are they specifically? Googling only yielded me paywalled articles and test questions. A good answer will state the laws and provide a brief explanation of what they mean. I want to understand what they tell me about river systems and what comparisons between different rivers I can make based on them. I'm not looking for an in-depth examination, or for an excourse on the purely mathematical side.

Physicalgeography.net and the Colorado State basic hydraulic page have a good explanation of Horton's Laws.

The first thing that needs to be done in analysing a drainage basin is to classify the stream segments in a basin according to Strahler's method. For each stream order tabulate:

the number of segments
the average length of the segments
the average area of drainage for the segments

According to Physicalgeography.net the bifurcation ratio is the ratio between the number of stream segments in one order and the number of stream segments in the next order.

Horton saw that the bifurcation ratio was always around 3, this he called the Law of Stream Numbers. Apparently a bifurcation ratio of 3 also applies to plant roots, branching of woody plants, veining in leaves and the human circulatory system. I get the impression that without knowing about it, Horton was laying some ground work for fractal mathematics that came to prominence in the 1980s, with the work of Benoit Mandelbrot.

With the Law of Stream Lengths, the average length of stream for each order is calculated, then cumulate lengths found before length ratios between segment orders can be calculated.

Colorado State basic hydraulic page has a more mathematical approach to explaining Horton's Laws, but it's very good. It gives a worked example of how to determine the all the coefficients.

Additional information is also on this site as well.


What is the name of this landform? These are from the movie Insomnia.

Also available in this video from 4 seconds to 8 seconds. What is the name of this landform? Are these just snow on Lapies? or These are some form of glaciated landform?

This is a large glacier calving event. Calving occur at the front of the glacier, probably a very wet (and likely warm based) glacier where a considerable amount of water is flowing out of the system (thus from the glacier to the sea). The amount of water is important as it can accelerate the ice flow speed on the valley floor, enabling the breaking of big ice chunks along the way. This is what typical calving events looks like: https://pubs.usgs.gov/of/2004/1216/c/images/calving1.gif

When the glacier ice is moving fast in a valley, and encounter hard rock outcrops on the valley floor followed by sudden drops in topography the ice will break, making it what is known as an ice fall: https://pubs.usgs.gov/of/2004/1216/i/images/icefall1.gif , or if the topography is moderate, seracs instead https://pubs.usgs.gov/of/2004/1216/s/images/serac1.gif .

But typical events of normal glacier dynamics as aforementioned does only answer a part of the question. What happened in these picture is that the glacier chunks went seaborne, in a fjord, after a big calving event. The fjord prevent the glacier fragments to spread, forcing these to move along the fjord. This next picture as reported by ABC news show a big calving event that happened in Greenland in 2018, similar to the picture you are showing:

(Source and caption: Tabular icebergs float in the Sermilik Fjord after a large calving event at the Helheim glacier near Tasiilaq, Greenland, June 23, 2018. Source: ABC News https://abcnews.go.com/International/watch-billions-tons-ice-collapse-climate-change-impacting/story?id=57972318)

Here we see the perspective of the rock walls on both sides preventing the spreading and concentrating the glacier chunks.


What exactly are "ambient aerosols"? I see this term being used everywhere, but I have not been able to find a formal definition for "ambient aerosols".

In the field, in which I work, the term _ambient aerosol` is related to the water content of aerosol particles.

Commonly in the atmosphere, water is attached to particles. The amount of water attached to particles depends on the relative humidity (in ambient air). Increasing relative humidity means more water and, hence, larger particle/droplet diameter. When we provide a measured/modeled particle diameter, we need to note whether the diameter is given as dry, as wet at XX% relative humidity or as wet at ambient relative humidity.

Maybe it is also used in other contexts.


Stratosphere height vs. Temperature based on ozone concentration Why does temperature increase as height increases in the stratosphere (15 km - 60 km above earth), when the ozone molecules are most concentrated at about 25 km?

There are two main points to make here.
The first point is that UV radiation is entering the stratosphere from above (ignoring angular dependencies and scattering), so is preferentially absorbed by ozone higher in the stratosphere.  This is a form of the Beer-Lambert law, which leads to greater absorption higher in the stratosphere.
The second point is that the Dobson Units used in your plot standardize for (partial) pressure and temperature differences between different heights in the stratosphere, so that you can compare the mass or number density of ozone at different levels.  But it doesn't tell you how much ozone there is relative to all the other gases making up the air at a particular height.  A common way to look at this is the mole mixing ratio:

A height–latitude cross section of annual average ozone mixing ratio (ppmv) from the climatology.
Source: McPeters et al (2005), Ozone climatological profiles for satellite retrieval algorithms, GRL.

While the ozone concentration peaks around 20 km, the mixing ratio peaks around 30 to 40 km and doesn’t decline so abruptly with height.  Where the mixing ratio is greater, absorption of a particular amount of UV radiation can have a greater effect on the overall air temperature at that height.
The net effect of these two properties is that heating of the stratosphere by UV absorption (see plot below) peaks in the upper stratosphere around 50 km.  This is why the greatest temperatures are found in the upper stratosphere.

Heating from absorption of UV radiation (K/day)
Source: Haigh (1984) Radiative heating in the lower stratosphere and the distribution of ozone in a two‐dimensional model, QJRMS.


How do I convert between different east longitude coordinates? I have two datasets that represent longitude in different ways. The first represents longitude as degrees from east to 180, but then as negative east so that I have a series which looks like:

[0:180, -180:0];

I then have another dataset that represents longitude as degrees east but with a range of 0 to 360, i.e.:

0:360;

In order to convert these to the same format, can I simply use this?

lon2(lon2 > 180) = lon2(lon2 > 180)-360;

Note my example here is written in MATLAB. This basically shows that I can change the second longitude coordinates by simply subtracting 360 from those longitude values that are greater than 180. Does this make sense?

The database with the negative longitude angles is storing longitude as eastings and westings, whereas the other database is storing everything as eastings.

It appears you prefer your data as eastings and westings. Your methodology for changing eastings greater than 180 degrees to westings is correct: where the longitude angle is greater than 180 subtract 360 from it (i.e. longitude angle - 360).


Are these igneous Liesegang rings on a popular Oahu, Hawaii hike? I hiked the Lanikai Pillbox trail (Oahu, HI). I noticed eroded concentric rings in the igneous rock with a hard center. I'm unable to find the geologic cause of these rings. Are they Liesegang rings? There were several instances (~20) I observed on the hike.

Not knowing the setting and judging from the image alone in this trampled environment, I think we're looking at a form of chemical weathering called "spheroidal weathering".
The gist is this (from the linked wiki page):
Penetrating water alters the bed-rock along cracks or joints, causing volume changes between altered and unaltered parts. These differences result in the formation of spheroidal layers that are removed by erosion (or trampling), leaving a central relatively unaltered boulder/pebble.
Liesegang rings are somewhat enigmatic, not sure if the term is applicable here.


What is serpentinization, in the context of disappearance of surface water on Mars? The recent paper in Nature The divergent fates of primitive hydrospheric water on Earth and Mars (Nature 552, 391–394 (21 December 2017)
doi:10.1038/nature25031) has been linked by many recent news articles. Essentially much of Mars' original surface water may have been incorporated into metamorphic rock, rather than lost to space following the collapse of it's magnetic field then followed by it's atmosphere.

It is suggested that the higher iron content of surface minerals on Mars relative to that of Earth lead to enhanced serpentinization.

I'm having a hard time understanding the use of the term serpentinization as used in the abstract of the Nature paper shown below.

Wikipedia shows a serpentine subgroup of minerals and the mineral serpentinite itself, as well as an image of a rock formation with serpentine patterns.

In this context, does serpentinization just refer to the formation of some hydrated minerals that happen to be of a class that is historically been referred to as serpentinite or it's subgroup, or is serpentinization  a process that always produces serpentine patterns?

  Despite active transport into Earth’s mantle, water has been present on our planet’s surface for most of geological time. Yet water disappeared from the Martian surface soon after its formation. Although some of the water on Mars was lost to space via photolysis following the collapse of the planet’s magnetic field, the widespread serpentinization of Martian crust suggests that metamorphic hydration reactions played a critical part in the sequestration of the crust. Here we quantify the relative volumes of water that could be removed from each planet’s surface via the burial and metamorphism of hydrated mafic crusts, and calculate mineral transition-induced bulk-density changes at conditions of elevated pressure and temperature for each. The metamorphic mineral assemblages in relatively FeO-rich Martian lavas can hold about 25 per cent more structurally bound water than those in metamorphosed terrestrial basalts, and can retain it at greater depths within Mars. Our calculations suggest that in excess of 9 per cent by volume of the Martian mantle may contain hydrous mineral species as a consequence of surface reactions, compared to about 4 per cent by volume of Earth’s mantle. Furthermore, neither primitive nor evolved hydrated Martian crust show noticeably different bulk densities compared to their anhydrous equivalents, in contrast to hydrous mafic terrestrial crust, which transforms to denser eclogite upon dehydration. This would have allowed efficient overplating and burial of early Martian crust in a stagnant-lid tectonic regime, in which the lithosphere comprised a single tectonic plate, with only the warmer, lower crust involved in mantle convection. This provided an important sink for hydrospheric water and a mechanism for oxidizing the Martian mantle. Conversely, relatively buoyant mafic crust and hotter geothermal gradients on Earth reduced the potential for upper-mantle hydration early in its geological history, leading to water being retained close to its surface, and thus creating conditions conducive for the evolution of complex multicellular life.

does serpentinization just refer to the formation of some hydrated minerals that happen to be of a class that is historically been referred to as serpentinite or it's subgroup

Yes. In simple terms, the reaction is enstatite + forsterite + water = serpentine.
MgSiO3 + Mg2SiO4 + 2H2O = Mg3Si2O5(OH)4
Forsterite and enstatite (or more generally, olivine and pyroxene) are common minerals in mafic igneous rocks. The formation of serpentine locks up water in the resulting solid crystal structure.
You can see more examples of serpentine forming reactions on page 5 of this PDF file.

or is serpentinization a process that always produces serpentine patterns?

No. There is no such thing as "serpentine patterns". The image you link to is of "folded serpentinite". The "serpentinite" bit of it are the green layers, regardless of whether they are folded or  not. The nice photogenic folded part is a later tectonic event that is unrelated to the formation of the serpentinite.