What percentage of the earth's surface is covered by 2D or 3D reflection seismic data? It was recently asserted to me that we have no idea what Planet Earth really looks like below our feet. I responded that (mainly oil-industry) seismic data covers a vast area and so actually we have a fairly good idea. The response was that this seismic coverage is very localised in particular areas.

Some statistics would be useful in this discussion but I'm unable to find any definitive sources.

To be specific, lets assume we are interested in the top 3 kilometers of the crust, and that a minimum 2D seismic spacing of 2 km would be required.

On that basis, what percentage of the earth's surface is covered by reflection seismic data?

Perhaps an easier question would be - what percentage of the earth has discovered oil/gas fields! This data should be easier to find than the surveys themselves, and can probably give you a rough estimate.

For an idea of the publically available seismic surveys conducted around western Australia, this site (https://wapims.dmp.wa.gov.au/wapims) can show you all of their stored survey data. Not sure where you could get other data though, sorry!


What is a massif and what differentiates it from other types of mountains? Wikipedia says that a massif is "a section of a planet's crust that is demarcated by faults or flexures." It goes on to list mountain-like objects.
Is it not true that most mountains are created by faults or flexures? What is it that distinguishes a massif from any other mountain or group of mountains?

My interpretation is that while an individual mountain itself may be part of a mountain range that is marked out by faults and flexures, the actual mountain is demarcated by erosive processes. For example, the Alps in France are a mountain range, demarcated by faults. However, the Matterhorn, shown below, is clearly a mountain figure not marked out by faults or crustal flexing. Instead its prominence from the surrounding regions is caused by the erosion processes of glaciers.

To use the example in the massif Wikipedia article, The Mont Blanc Massif contains peaks within it (Aguille du Midi, the Mont Blanc peak etc., shown below) that are defined by erosion, but the group of these peaks is defined by faulting.


Why was the initial theory of plate tectonics so controversial? I have been set the task of researching plate tectonics, specifically:
"Why was its discovery so important in its time and controversial?"
I do not need a long answer, although more detail is always appreciated.

One of the key aspects of plate tectonics is continental drift.

The person who came up up with the theory of continental drift was Alfred Wegener. He published his theory in 1912.

One of the issues with the theory that geologists at the time had, was that Wegener was not a geologist, but a meteorologist. He was publishing a theory that wasn't associated with his field of science. The other issue the geologists had was based on the commonly held opinion:

that the oceanic crust was too firm for the continents to "simply plough through".

When he published his theory, Wegener did not propose a means by which the different land masses could break away from each other.

Initially, some geologists could only conceive the idea that ocean waves might be responsible for breaking up land masses, but they couldn't reconcile the fact that the lack of sediments and the clean breaks in land masses would not support Wegener's theory. Without knowing about plate tectonics the theory of continental drift was difficult to support.

Another reason why Wegener's idea was not initially accepted was because of the way he proposed that continents used to fit together. This was because of the assumption most people had was that the continents split along the lines of coast lines and not the 200 m isobath proposed by Wegener.

Wegener came up with the idea of continental drift by noticing that all the major land masses appeared to fit together like a jigsaw puzzle.

It wasn't until the early 1950s when data from paleomagnetic studies of India showed that India had once been in the southern hemisphere that data started to support Wegener's theory. Also, it wasn't until the 1960s that sea floor spreading data was available to support the theory.


Is "seismic energy released" a regionalized variable and can be analyzed using geostatistics? In geostatistics, we can assess and analyze regionalized variables. Tectonic stresses releases in seismically active regions by occurring earthquakes. We can calculate and estimate the seismic energy released by an earthquake. Now, the question is this: Is it possible to assess 2-D or 3-D spatial variation of the seismic energy released in a region, using geostatistics rules?

An intrinsic assumption in using geostatistics is that one can approximate a distribution by a polynomial surface. In practice, maybe you can do this in a very simple geological situation, such as an isotropic shockwave arising from sedimentary compaction in horizontal sediments. When it comes to major seismic events at tectonic plate edges I think the seismic energy distribution might be too complex. For example, the seismic energy is attenuated at different rates on either side of a subduction zone, and tends to be channeled along the ocean floor according to local bathymetry and structure (especially along mid-ocean ridges). Also, the shock wave distribution will be different according to whether the source is shallow or deep. Trying to account for such features in a geostatistical model will be a nightmare of complexity - good luck!


The state of Nitrogen, Phosphorous and Potassium during Anaerobic Digession I am planning to go for organic farming and I would like to utilize available weeds as fertilizers with either anaerobic or aerobic digestion. I understand that during the aerobic process (composting), nitrogen, phosphorous and potassium contained within the feed-stock may be converted to nitrate, phosphate and sulfate. I wanted to know what happens to these three components during the anaerobic process? Which process is better in the farming domain, ignoring methane gas availability in the case of anaerobic process.

You're the man who grows coconuts and had a small problem with mimosa plants which you now intend to compost. Don't forget that coconut fronds blown down by the wind and any other waste products from the palms can all go into your compost. In England, earthworms are highly valued in the compost heap, as they help the vegetation break down more efficiently, but I'm not sure how available worms are in Mangalore. If you have a machine that can chop your mimosa cuttings into tiny pieces, that will also help them to compost. Some of the nitrate produced by their roots will find its way to your coconut palms if they are nearby.

Yes, there will be nitrate, phosphate and sulphate in your compost, especially nitrate manufactured by the roots of your mimosa plants. Anaerobic composting still leaves nitrates, phosphates etc in the final product, but also creates methane, which is a very potent greenhouse gas best not released into the atmosphere. The compost also requires an airtight container, so your worms would be suffocated. If your compost is of sufficient quantity to make it worth while, you could tap off the methane and use it as a fuel for cooking.

I think the aerobic process would be best suited to your needs, therefore your compost heap will need to be well aerated. Make a bed of twigs to  build your compost heap on, and that will let air in underneath. You will also need to turn the compost over occasionally to let more air in. Aerobic composting does not produce methane. If you see a thriving population of worms in your compost, things are going well.


What is the current equilibrium surface temperature of Earth, i.e. without the sun? Without the sun to keep the Earth's temperature topped up to something comfortable, what would be the equilibrium surface temperature range. It would obviously be a balance between outgoing radiation and geothermal conduction to the surface. This question is prompted by Anixx's recent question on planetary cooling time without the sun.

Assuming a thermodynamic equilibrium between heat from below and heat escaping into outer space, and assuming an energy from below of 44 to 47 terawatts (the Earth's current internal heat budget), that means the surface temperature would be about 35 or 36 kelvins by the Stefan-Boltzmann law: $$\varepsilon \sigma A T^4 = \phi$$
where $\varepsilon$ is the surface's emissivity in the thermal range (which I assumed to be one), $\sigma$ is the Stefan-Boltzmann constant (5.670367×10-8  W/M2/K4 in SI units) , $A$ is the Earth's surface area, $T$ is the surface temperature, and $\phi$ is the energy supplied to the Earth's surface from below.

Note that atmospheric effects are a non-concern for this very low temperature. The Earth would have no atmosphere except perhaps some trace helium and hydrogen gas.


What is the difference between eluvium and alluvium? I was reading about kimberlite on Wikipedia and it mentioned eluvium. I've heard of alluvium, alluvial fans, alluvial deposits, etc. However, when I looked up eluvium, it sounded exactly like alluvium.
Indeed, looking at the Wikipedia articles, the definitions sound identical to my (expertly untrained) ears:

Alluvium: loose, unconsolidated (not cemented together into
a solid rock) soil or sediments, which has been eroded, reshaped
by water in some form, and redeposited in a non-marine setting.
Eluvium: geological deposits and soils that are derived by in
situ weathering or weathering plus gravitational movement or
accumulation.

So, both of these sound like soil and sediments, eroded and deposited. But obviously, they can't be the same thing.
What's the difference? How can I tell the difference if I see it "in the wild"?

Both are very similar, as they are based on minerals undergoing erosion and the presence of water in the erosion and deposition cycles, the difference is quite subtle, an example is defined in the Gold Prospecting in Western Australia website Alluvial Gold and Eluvial Gold as being

Alluvial deposits are mixed with other deposits and are washed downstream in rivers or transported in among other sediments with water as its medium. An example is that gold deposits this way are smoothed and are ground down the further from the source.

Eluvium deposits are in situ or very near its source, rather than been washed away by water.  For example, eluvial gold are often large nuggets nearer to its source.

A much more succinct definition is provided by the Australian Museum:

Alluvium:

  Detrital material which is transported by a river and usually deposited along the river's pathway, either in the riverbed itself or on its floodplain.

Eluvial:

  Weathered material still at or near its point of formation.


Darwin theory about Japan and China In a letter by Charles Darwin to Asa Gray, introducing to him an abstract about what would Origin of Species, he talked about migration of different forms during the glacial epoch, and the reason why you could find European forms in the tropics. He then said:
From mammalia and shallow sea, I believe
Japan to have been joined to main land of China within no
remote period ; and then the migration north and south before,
during, and after the Glacial epoch would act on Japan,
as on the corresponding latitude of China and the United
States.

I wonder which sea he meant by "shallow sea", and why could this be reason to think that Japan and China were joined?

At the northern and southern ends of the Sea of Japan, there are only short stretches of very shallow sea separating Japan from the mainland. During the Ice Age which ended 12,000 years ago, sea levels were much lower than they are today. It is probable that during the last Ice Age there were land bridges connecting Japan to the mainland at these two points.


Aren’t photons the vector for energy input to earth? As such the fuel for earth’s Carbon cycle.
Wouldn’t photons be the alleged “electromagnetic” mode of energy transfer into earth?
Providing energy for the endothermic photosynthetic processes and heat for all and mass exposed to this energy modality. Mass can be gas, liquid or solid. In All instances converting thermic or light energy into increased molecular motion.
What would be the vector for energy to be transferred out of earth atmosphere into the empty firmament.

Photons do not emit energy but rather, carry stored kinetic energy that has the potential to give or TAKE AWAY heat so, to answer your question, they ARE an energy vector but would think they are not the fuel for the Carbon Cycle since they get scattered by particles and water vapour....which leads me to think they are part of the cocktail, but not the fuel in itself. Here is an excellent visual and summarized source for interactions of radiation with the atmosphere > https://www.nrcan.gc.ca/maps-tools-publications/satellite-imagery-air-photos/remote-sensing-tutorials/introduction/interactions-atmosphere/14635

I believe you have asked an excellent question and look forward to reading the subsequent responses.


What mechanism leads to these spectacular iridescent patterns in clouds labeled as a "Fire Rainbow"? The 21-Feb-2016 BBC new article Singapore 'fire rainbow' cloud phenomenon lights up sky shows several photos of a rainbow-like iridescence in clouds on a sunny day in Singapore (about 1.3 degrees North latitude). Local time was about 17:10, 2 hours before sunset.

I've read about circumhorizontal arcs in this article, but the photos there (and other places) show a definite orientation - approximately parallel to the horizon with red on top (higher elevation angle).

However the photos from Singapore show tight circular patterns that resemble a color-coded contour map around a hill. So I think the explanation for these would not be identical to the explanation for a classic circumhorizontal arc or "Fire Rainbow".

below x2: Photo of the phenomenon seen in Singapore, from  Singapore 'fire rainbow' cloud phenomenon lights up sky. Photo credit: Zhou Guang Ping.

below: example of a circumhorizontal arc from Fire Rainbows: A Rare Cloud Phenomenon.

this looks like mother of pearl clouds https://en.wikipedia.org/wiki/Polar_stratospheric_cloud
they are made of ice crystals very high in the atmosphere the only clouds higher in the atmosphere are noctilucent clouds.if you google mother of pearl clouds there is a lot of pictures and information.
as a result of global warming the stratosphere is getting colder this makes
mother of pearl clouds or rainbow clouds visible from larger areas of our planet then before(more info is needed to dokument this statement of mine).

An other alternative is irradecent clouds,They have many of the same properties as mother of pearl clouds https://en.wikipedia.org/wiki/Cloud_iridescence

The last alternative is a pollen rainbow but they do often form in the direction of the sun or moon(it is a little hard to see if the sun is behind the clouds in your pictures)The colors of a pollen rainbow is often more vibrant than other types of optical phnomena https://soranews24.com/2019/03/09/high-pollen-levels-in-eastern-japan-create-pretty-rainbow-suns/


Can strong winds significantly lower ocean surface levels, or is it really the static pressure differences? The Washington Post article Hurricane Irma is literally sucking the water away from shorelines written by the Post's atmospheric scientist Angela Fritz describes leads with this:

As a meteorologist, there are things you learn in textbooks that you may never see in person. You know they happen theoretically, but the chances of seeing the most extraordinary weather phenomena are slim to none.
This is one of those things — a hurricane strong enough to change the shape of an ocean.
[...](links to images in social media)
Basically, Hurricane Irma is so strong and its pressure is so low, it’s sucking water from its surroundings into the core of the storm.
The wind on Long Island in the Bahamas is from the southeast to the northwest on Saturday. On the northwest side of the island, it would be blowing the water away from the shoreline.
It also may be experiencing the effects of what I call the hurricane “bulge.” In the center of the storm, where there is extreme low pressure, water is drawn upward. Low pressure is basically a sucking mechanism — it sucks the air into it, and when it’s really low, it can change the shape of the surface of the ocean. As the storm draws water toward the center, it gets pulled away from the surroundings
In any case, this isn’t the sign of a tsunami. The water will return to Long Island, and it probably won’t rush back with any great force. It will probably be back by Sunday afternoon.

This explanation is confusing me because it seems to suggest that the water level has dropped due to the wind from the southeast, as well as due to the low pressure, which is "basically a sucking mechanism — it sucks the air into it, and when it’s really low, it can change the shape of the surface of the ocean."
Question: Can strong winds ever lower ocean surface heights significantly directly, or are these drops caused by local static pressure differences independent of the wind. Of course pressure and wind are intimately connected, but each should have its own effect on ocean surface height.
ancillary question: Since the stated wind direction is essentially parallel to the long direction of the island, I don't understand why it would preferentially remove water from one side of the island over the other side. Does this make sense?

below: "Sea gone dry" from this tweet linked in the Washington Post article.

below: From Google Maps, marker is on Long Island, Bahamas. 23.16N, 75.08W.

The explanation for the wind effect on water level at the coast is basically the same as for upwelling circulation. In an upwelling situation, the winds flow parallel to the coast and generate upwelling dynamics: surface Ekman balance is setup (in deep enough waters) with water transport being to the right (left) of the wind in the northern (southern) hemisphere; this causes a deficit along the coast that needs a compensating flow in the deeper part of the water column bringing cold water to the surface. The deficit along the coast and the resulting sloping density levels create a geostrophic balance and that causes the surface water level to drop near the coast (wind set-down).

A good diagram of the processes at play is available from Csanady (1981).
Source: EOS

In reality, the Ekman balance-geostrophic balance combo is a better approximation when the shelf is narrow and there is a stronger connection with the open ocean. In shallower areas, the wind that matter most is not the along-shelf wind, but rather the cross-shelf wind:

Depth of the wind-induced currents and the shoreline

In the case of a hurricane, the winds and atmospheric effects are so strong that it is difficult to separate the two. The article cited in the question mentions the two effects. The fact that the wind lined up with the coastal alignment suggests that wind set-down might have been a factor. It is not that uncommon for wind set-down to be a controlling process (e.g., Red Sea (also)).

Csanady, G. T. (1981). Circulation in the coastal ocean, Part 1. Eos, Transactions American Geophysical Union, 62(2), 9-11.


Does "Arctic Greening" mean an increase in the spatial extent of vegetation, an increase in particular types of vegetation, or both? I am trying to study the impact of biogenic volatile organic compounds (BVOCs) on the atmospheric chemistry of the Arctic Region which has been said to be "greening", by taking HCHO as a proxy.

You have an unclear question. See my comment on the question itself.

Answering just the question:

I've not seen a formal  definition of arctic greening.  Conceptually it's replacing a landscape that is in effect a cold desert with one that has:

Longer growing season.
Greater biodiversity
Greater gross photosynthesis.

You would think that it would also be greater net photosynthesis too, but much of the arctic has large deposits of peat moss, forest duff and sedges. With warmer temperatures we will likely see greater bacterial action on the peat. Not clear which way the carbon/acre figure will move.

It's also not clear what the effect of an open oceans in the high arctic will be.  Depending on the nutrient levels in those waters could see a lot more phytoplankton. BVOC exchange between ocean and atmosphere?

You can get a first level approximation substituting latitude for time. I expect BVOCs to disperse fairly quickly so you would need to measure at ground level. Analyzing a bunch of sites that are representative of the various major communities -- Boreal forest, tree line, tundra/puckey-brush (scrub willow, birch) Tundra/moss, forbs; Rock.

For a preliminary analysis you don't even need to go to the arctic. Use a convenient mountain.

That can nail down quantities of BVOCs. Correlate that with HCOH to see how good a proxy HCOH is for BVOC.

This leaves a bunch of unanswered questions:

Is the time frame for the degradation of HCOH similar to for other BVOCs?  You may have to do radioactive tracer tests in containers set at similar conditions of temperature, pressure and UV illumination.

What are the degradation products?  What are the effects of these?  Do any of the original products or their degradation products acts as catalysts?

I think you have bitten off a big research project.


Rock identification ? What kind of it is? My co-worker had this rock and told me found just behind the store, Big R, and put on the table in the office.

Location is Trindad, Colorado.

Looks like slate to me.
The geological map of Trinidad suggests that the local rocks are shale, which is similar to slate but less compact.


Are the elements of an averaging kernel matrix always centered on the diagonal, or can they be exclusively off-diagonal in rare cases? According to Rodgers (2000) equation 2.80

$$
d_s = \mathrm{tr}(\mathbf{A})
$$

where $d_s$ is the number of degrees of freedom for the signal, tr denotes the trace, and $A$ is the averaging kernel matrix.

I'm trying to properly understand this.  For example, is it theoretically possible for the averaging kernel to have mainly or even exclusively off-diagonal elements?  In practice, this would mean that the retrieved state at height $h$ would correspond to the true state at height $h+1$, if we take remote sounding of an atmospheric column as an example.  In such a (admittedly contrived) example, we could get $d_s=0$, although we do have information in the measurement — it's just displaced.

Is this situation possible?  If yes, does $d_s$ tell the whole story as for the information content in the measurement?

Clive D. Rodgers, Inverse methods for atmospheric sounding, Theory and Practice. ©2000 World Scientific Publishing Co., London, UK.

This statement from Geophysical Data Analysis: Discrete Inverse Theory: William Menke should make things clear for you

  The diagonal elements of the covariance matrix are a measure of the
  width of the distribution of the data, and the off-diagonal elements
  indicate the degree to which pairs of data are correlated.

Regarding the second part of your doubt whether a situation is possible where ds = 0 ; this would imply some error in measurement(for example - some noise) and would not have any implication on the geophysical nature of the data . It would be advisable to take multiple readings at different locations in this kind of situation.

Finally ds provides some insight into the quality of data collected but no true information about the "information content of measurement".


Why does the Inter tropical Convergence Zone shift? I am currently learning at school about the climatic conditions (mainly winds, difference in pressure, Coriolis effect, etc.) that cause and affect the monsoons received by India.

One of the factors mentioned is the shift of the Inter tropical Convergence Zone (ITCZ) towards the Ganga plain in the summers. I tried reading up on Wikipedia to understand this better (here especially), but couldn't understand much.

Could someone explain, in simple terms,
(a) What the ITCZ and monsoon trough are? Are they just regions of low pressure?
(b) What causes this to shift away from the equator?
(c) Does 'convergence' have anything to do with all of this?

On a broader scale the ITCZ and monsoons are related. This is because the global circulation shifts as a result of the tilt of the earth's axis relative to the orbit around the sun. In northern hemisphere summer, the northern hemisphere is tilted towards the sun and receives more radiation (energy) than the southern, and vice versa for northern winter, The southern hemisphere is affected in the same way. Without the tilt we would not experience any seasons.

In the tropics the largest amount of energy reaches the region where the sun is at the zenith. In northern summer this region is north of the equation, where as in winter it is at the south. At the spring and fall equinox it coincides with the equator. Hence the region of maximum energy input wanders seasonally to the north and south of the equator.

Climatologically the region with maximum energy input sets up a circulation in the form of so-called Hadley cells where warm air rises where it is heated the most and then transported at elevation to the north and south. At the location of upward air flow formation of convective clouds yielding precipitation becomes the norm. This zone to which ground winds flow towards the region of maximum energy influx is the ITCZ and because the zone of maximum solar energy influx wanders, the ITCZ flows. The zone is fairly wide so the regions around the equator sees the effects of tropical precipitation more or less without seasonality, actually two rain periods and two drier periods as the ITCZ moves once to the north and once to the south over the region each year. Away from the equator the resulting period of precipitation becomes more and more marked as one moves to the north and south resulting in strongly seasonal rains.

This movement of the large scale circulation on the earth produces several associated effects and the different monsoons are such phenomena. There are several monsoons on the earth created by weather phenomena typical for the specific region. The Asian monsoon is perhaps the most known. The specific conditions leading up to this monsoon is found in the high elevation Tibetan plateau. During the northern winter the plateau sees a larger high pressure forming which generates winds flowing south over India and causing a dry climate. During the northern summer large parts are heated generating a low pressure over land which draws in moist air from the sea yielding strong precipitation. Hence the monsoon follows the same seasonality as is seen in the wander of the ITCZ but the cause for the regional change in seasonal wind and precipitation pattern has a different cause.

So to understand the large scale weather systems and their seasonal patterns, you must start by understanding how solar energy drives the atmospheric circulation. This causes a specific and typical pattern which is locally disrupted by the distribution of land and oceans on the earth. Land masses can be heated more and more quickly than oceans on a seasonal basis, land masses also includes topography that can impede the atmospheric circulation, so it it perhaps obvious that land masses contribute on regional and local scales.


What kind of purple stone is this? I found this stone and I do not know what type of stone is this?

That's amethyst, a violet version of quartz

See here


How does the changing seasons affect the large scale easterly flow of the ITCZ? I am new to climate science and have been learning the basic picture of the intertropical convergence zone (ITCZ) and how this leads to the predominant easterly "trade winds".

The picture that I have learned is the following. As the ITCZ is a belt of low surface pressure along the equator, air is drawn in from the north in the northern hemisphere and from the south in the southern hemisphere. Due to the coriolis effect, the southward winds in the northern hemisphere are deflected westward and the northward winds in the southern hemisphere are also deflected westward, with respect to the earth's reference frame. Thus the winds along the ITCZ blow westwards (i.e. Easterly winds).

However, I also know that the ITCZ is not a perfect circle, and also moves around with the seasons, so that in the northern hemisphere summer it is predominantly in the northern hemisphere, and in the southern hemisphere summer it is predominantly in the southern hemisphere, and on an average day you might find parts of the belt in the northern hemisphere and parts in the southern hemisphere.

But then my basic picture breaks down. Indeed, if the ITCZ lies north of the equator, then the winds approaching from the north are deflected westwards, whilst winds approaching from the south are deflected eastwards. So the trade winds just south of the ITCZ are now westerlies rather than traditional easterlies, and winds are converging at the ITCZ with opposing directions (and presumably rubbing against one another creating friction). A mirror situation holds with the ITCZ south of the equator.

My questions are:

1) Is my above reasoning correct / applicable to the atmosphere?

2) If so, what effects does this have on the properties of the ITCZ, and what are some examples of these effects on weather patterns? I am very happy for explanations as well as references to appropriate texts.

Many thanks!

A.

I hope I can explain this well! I will focus my answer on the ITCZ in the Pacific Ocean. The first point is that the Coriolis force is zero at the equator and maximum at the poles (1). So, another factor comes into play "the walker circulation which is strongly tied to El Niño–Southern Oscillation (ENSO). ENSO states are 3: normal conditions, La Niña, and El Niño.
Given that Coriolis force is minimal around the equator, other wind drivers are more important. El Niño (La Niña) occurs when the tropical Sea surface Temperature (SST) in the central and eastern Pacific ocean is warmer (cooler) than the multi-decadal climate average. During normal conditions, higher pressure over the southeastern Pacific and lower pressure over the western Pacific drive easterly trade winds along the equator (known as Walker circulation), resulting in cold water upwelling and dry weather in the eastern Pacific. When the easterly trades are exceptionally strong, the eastern Pacific becomes colder and drier, resulting in La Niña conditions. The last case, El Niño occurs if the pressure over the eastern Pacific decreases: then easterly winds weaken or reverse direction, leading to a stronger ocean countercurrent that carries warm water into the eastern Pacific beside wetter weather conditions (Ahrens, 2009; Stull, 2018). So during El Niño events, the winds are not always easterlies( heading west) in the western Pacific they are westerlies, and in the eastern Pacific are easterlies. And keep in mind that the ITCZ is strongly linked to warm SST. That is why the ITCZ reaches the northernmost location in September (same as warm SST), although the Solar insolation peak in mid boreal summer (July).
I hope this answers the question. late better than never ;-)


Impossible or improbable? Hurricane crossing the equator No known hurricane has ever crossed the equator.  Hurricanes require the Coriolis force to develop and generally form at least 5° away from the equator since the Coriolis force is zero there.

Are the physics of the earth and tropical systems such that it is impossible for a hurricane to cross the equator after forming, or are the forces working against this occurring so strong that an equator crossing hurricane is an exceedingly rare event we may not witness in 1000+ years?

Improbable.

It is well known that the Coriolis force is needed to form a hurricane, and the figure of 5oN/S as the minimum for formation is widely publicized. You can also find record of tropical storm formation near India as far south as 1.4oN.

The problem of crossing the Equator isn't one of hurricane formation though, it is one of hurricane motion.  Due to Coriolis, a hurricane initially moving parallel to the Equator will start gaining a poleward component to its motion, thus moving it away from the Equator.  But, because this is due to Coriolis, if you could get a storm close enough to the Equator, this effect would not be as strong.  This would be an improbable track, but I'm not willing to call it impossible.  We haven't had satellites all that long, and all we can really say is that it hasn't happened since we've been watching.

If a storm did cross the equator though, what would it do?  Nothing at first, but as it moved further into the opposite hemisphere, Coriolis would be working against the storm and it would spin down, become disorganized and cease to be a hurricane, probably becoming a remnant low.

A tropical disturbance has crossed the equator.  One such disturbance occurred June 27, 2008 in the Atlantic basin (south to north) that retained its clockwise motion for some time:


Impacts of high-altitude emission of greenhouse gases (GHG) compared to sea level GHG emissions I often hear that the emission of greenhouse gases (GHGs) by planes is particularly concerning because the emission of GHGs at high altitudes has an even higher impact on global warming than the emission of GHGs at low altitudes (e.g. sea level). I tried to find scientific evidence (e.g. peer reviewed publications, explanations in scholar books) for this claim on the internet but failed. Is the claim stated in the first sentence of my question true? If yes, could you point me towards respected literature? Thanks!

I think you may be confusing two separate, but related, issues.  Aircraft emissions at high altitudes are a concern for the ozone layer, because the NOx that is emitted by aircraft can catalytically destroy ozone.  Supersonic aircraft fly higher up in the stratosphere than a typical jet, and thus can harm the ozone layer more effectively.  The ozone layer is related to climate change, which is perhaps why you are mixing two issues.  For the most part, aircraft greenhouse gas emissions are not a concern simply due to the altitude they are emitted.  Instead, aircraft GHGs are a concern because they are long-lived in the atmosphere and well-mixed, causing "global" warming.  Furthermore, aircraft emissions are expected to continue increasing for decades.


What types of high-level mathematics are useful in doing climate modelling/meteorology? I'm aware that PDEs, linear algebra, numerical analysis and such are staples of most applied mathematical endeavors. I want to know if there are other areas of "higher" mathematics that have useful applications in climate science (like topology, measure theory, Riemannian geometry, etc) or whether the things I mentioned first are the only really important ones. Thanks.

The question may generate primarily opinion based answers but while it is open one would like to present the following information.

At the outset most of the people I know in the field work in NWP and the reason people avoid higher mathematics(by that I mean looking for analytical solutions or pure math based projects such as you mention topology or Riemannian geometry) is because of the issue of jobs after completion of their respective Ph.ds and post docs. More of the recent advances use approaches from statistics and Big Data and that is because of the massive amounts of data that is available on a daily basis.

Presuming one wants to move on a "path" in academia then there is this application of topology in meteorology - Hairy ball theorem  and this book should provide more information on the topic An Introduction to the Geometry and Topology of Fluid Flows but applications of the material in the book to actual problems in meteorology may be few in so far as I am aware and others can perhaps provide better information. This workshop Complex Analysis And Geometry does provide some applications of differential geometry to meteorology but these I reckon are most of the outlier groups and most of the work is on improving skill of NWP models.

A colleague of mine in academia works on Potential Vorticity and Slow manifolds which is a part of Stability theory and fast manifolds/inertial manifolds. Essentially one is looking for a point after which the flow becomes unstable and why is that ? That is because unstable flows can be ultimately linked to weather forecasting and NWP models. There is the famous paper by Edward Lorenz that reviews that topic - The slow manifold what is it ?

While it is numerical work I  and many others use Vector Spherical Harmonics  because we all deal with global circulation models(spectral method) and others use wavelets to analyze equatorial waves

Finally there is this paper by Tapio Schneider that mentions Gauge transformations


Do rivers/creeks flow underground when they dry up at the surface? In my local area there is a creek which dries up completely in the summer and is flowing strongly in the winter. Is it the case that, at the location where the creek dries up, it continues flowing underground?

If so does it take the same trajectory as the creek? At what typical depths does it start flowing "forward"?

Water in liquid state always takes the fastest route to lower altitude. All rainwater would flow vertically down to the groundwater surface if not the permeability was limited by the material properties.

The permeability controls how fast water infiltrate and penetrate the material. For example, can surface runoff water flow on top of a hard road coating, while water from a watering-can goes into the soft soil in the flower-bed. Gravel, sand and fractured rocks have high permeability whiles shale and non-fractured igneous rock have low permeability. So low, that in many cases it appears to be totally impenetrable on a human time scale.

The same goes for a river. If the river flows on permeable rocks, typical sediments deposited by the river itself (see picture), ground water will also flow in the sediments under the river bed, permitting that water is still entering upstream.

A better way to understand a river or lake in this context, is that it is the surface manifestation of the groundwater table. If you dig a well next to a body of water you’ll reach ground water at the same altitude as the river water surface. The gradient of the groundwater surface and the permeability of the material controls the direction and velocity of the flow.

However, if more water enters a system than the surface can infiltrate, the surplus will flow as surface runoff, typical for wadis (See picture) in desert areas.

So, to answer your question. It depends on the local geology, but ground water will always flow from the precipitation area to the oceans (or a lower point where it can evaporate or being pumped up). Ground water exists everywhere and the gradient of the hydrostatic pressure controls the direction of the flow. As viable rivers shows the ground water table, it is usually rather safe to assume that the ground water under the dry river flows more or less the same direction.

However, ground water flow can be changed by e.g. pumping from irrigation wells. Imagine a flat lying river bed with a well upstream. When enough water is removed from the well and eventually evaporated, ground water will flow towards the well. The water don't 'remember', but follows the law of gravity.


Yearly changes of solar irradiation and atmospheric feedback I think I understand the mechanism of water vapor feedback in climate change pretty well: a (theoretical) temperature increase due to some isolated factor (e.g. increase in $CO_2$ concentration) causes a shift in water vapor saturation density and an additional evaporation rate. The consequential shift in actual water vapor concentration causes additional absorption together with isotropic re-emission, slowing down the radiation transport. So the theoretical temperature rise $\Delta T_{nofb}$ without consideration of feedback is "amplified" by some factor $\beta$, giving the real temperature rise, with feedback

$\Delta T_{wfb} = \beta \Delta T_{nofb}$

Of course I know that this argument has to be replaced by solving a differential equation in a more rigorous treatment. There is no "before" and "after", there is only the combined effect.

But what if we consider the "theoretical" temperature change due to the change in solar irradiation from orbital eccentricity? Shouldn't this be amplified by the same water vapor feedback mechanism as well?

Solar irradiation varies over the year between $1310$ $W/m^2$ and $1420$ $W/m^2$. According to Stefan-Boltzmann's Law in differential form we would have a heating of the ground by direct absorption of sunlight

$\frac{dP}{P}=4 \frac{dT}{T}$

or

$\frac{\Delta P}{P}\approx 4 \frac{\Delta T}{T}$

So I would expect the temperature change due to yearly changes in solar irradiation (but without the effect of water vapor feedback) to be about

$\Delta T \approx \frac{T}{4} \frac{\Delta P}{P} = \frac{290 K}{4} \frac{90 W/m^2 }{1366 W/m^2}\approx 4.8 K$

The favorite answer to this question shows a plot that seems to indicate that the order of magnitude is indeed like that, the global line shows a variation of about $3.8$ $K$. I don't know if this was derived from measurements, but I assume that it is somehow substantiated.

But if we now adopt the assumption that these ~5 Kelvin get amplified by the water vapor feedback as well, and take into account that this amplification is said to be in the order of magnitude ~2 in the context of $CO_2$ entry by mankind, I would expect the amplified yearly temperature change due to the orbital eccentricity of earth to be $~10$ $K$.

Is the linked answer wrong, or is there some flaw in the argument?

I think your ~2 figure for CO2 greenhouse amplification is in error.
* In the last 200 years it's gone from the high 280s to low 400s.  This is an increase of about 50%  Good thing it's not linear as the previous greenhouse effect is overall about 18K.  If there was no effect, the earth would average about 0 C.
* As CO2 increases it takes more bounces for an infrared photon to escape.  But you get some degree of diminishing returns.  Doubling the CO2 doesn't double the greenhouse effect.

But to your question.

Right now we have about 1 degree of additional greenhouse effect.  Compared to the 18 degrees of existing greenhouse effect this is about 5%.

I would expect that this is the factor to use.  So the eccentricity amplification should be about 5%  So 5.25K instead of 5.  or observationally 1.05 * 3.8K


What geological processes can cause local biases in the fossil record? What are the main geological processes that can cause local biases in the fossil record, e.g. when comparing species diversity or species occurances in different areas from the same time period? I know that there exists several processes for fossilisation, and that local environmental conditions are essential for fossilisation (e.g. to allow for rapid burial/sedimentation). However, my question is dealing with processes that affect a fossil record that is already formed (i.e. the period from after formation to present time). I realize that local conditions affecting the formation of fossils is probably the main reason for local biases, but am curious about processes affecting the later stages of preservation.

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

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

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

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


Where can I get archived hourly temperature data? I am looking for historical hourly temperature data from many cities in the US what other data sources are there except wunderground?

UPDATE: I will use the data to compare stations from the same city and need data with high temporal & spatial resolution; currently, one year of data is enough. I am not mentioning a specific US city because I need data from as many cities in the US as possible that meet my requirements. I am working on a big project of forecasting and I want to see the spatial deviations with in many large cities in the US.

The authoritative sources for your data are:

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

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

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


Would epicenters in less-deep areas of ocean tend to reduce the impact of a resulting tsunami somehow (wave "breaks" before getting there?) I just felt an earthquake at in a 6 floor building in Taipei, where I am familliar with how they have felt over the years.

This one felt particularly vertical, and made me feel queezy, while most have side-to-side motion. There was a weak shake, and many seconds later the strong, "queezy" one.

It looks like the epicenter is in less-deep water judging by the color of the water in the attached image. Would the reduced depth make it less likely for a tsunami to reach the shore somehow?

https://www.cwb.gov.tw/V7e/earthquake/

Tsunamis are created when large volumes of water are displaced vertically.

The predominant ways this can happen are when an earthquake of significant magnitude is created at a subduction zone - one tectonic plate subducting under another tectonic plate. During such an event, part of one plate moves downwards or upwards very quickly causing the water above it to be displaced vertically.

The other predominant way a tsunami can occur (seismically) is when an earthquake causes massive subsidence or slumping of material on the ocean floor - such as an underwater landslide. This can also create a significant vertical displacement of water. It is speculated this was the cause of the October 2018 tsunami in Palu, Indonesia.

There are meteorological causes of tsunamis but I won't address them because your question relates to seismically induced tsunamis.

The epicenter of an earthquake, whether under shallow or deep water, is largely immaterial to the creation of tsunamis. What is is critical is whether the earthquake has caused sufficient water to be displaced vertically either through sea floor movements (tectonic plates) or slumping or subsidence of sea floor material.

The difference between a quake under shallow and deep waters would be the size of the tsunami - how much water has been displaced vertically, how much energy has been imparted into the water and thus how high any wave will be and the destructive energy that it has.

Humans have tried to create tsunamis but were largely unsuccessful. During World War II, in Project Seal, New Zealand tried experimenting with explosives in what is now Shakespear Regional Park. Likewise, the US did similar experiments during nuclear weapons testing in the Pacific Ocean - Operations Crossroads and Hardtack, at Bikini Atoll. The heat from the nuclear weapons produced a lot of steam, but not significant tsunamis.


How to interpret hourly precipitation forecast? How should I interpret the hourly precipitation forecasts?

Most of the time, when there is rain in the forecast, the maximum Probability of Precipitation (PoP) in the hourly forecast is about the same as the daily PoP.

My problem is that the hourly PoP forecast usually has several hours at that maximum probability.  If I naively add the odds of getting wet for each hour, I always get a total probability that is much higher than the daily PoP value.

For example, take an hypothetical day where the daily forecast has a 50% PoP.  For the same day, the hourly forecast has 4 hours with a 50% PoP for each hour.  If I compute the chance that I get rain in at least one of the 4 hours, I get 93% PoP (15 out of 16).

How can I reconcile the total daily PoP calculated from the hourly forecast with the actual daily PoP?

The probability of precipitation is most likely to mean the proportion of models in an ensemble or weather models in which precipitation was observed at a particular location over a particular time period.
If you want to work out the probability of it raining during the day, the best approach would be to work out one minus the probability that there was no rain in hour one and there was no rain in hour two and there was no rain in hour three...  Mathematically if $x_i$ represents the presence or absence of rain in hour $i$, then
$P(rain) = 1 - \prod_{i=1}^{24} (1 - P(x_i = 1))$
However, this assumes that the probabilities of rain in each hour are independent, which is unlikely to be true.  To deal with this, we would need to introduce conditional probabilities (which are not supplied by the forecast), i.e.
$P(rain) = 1 - (1 - p(x_1=1)\times(1 - p(x_2=1|x_1))\times(1 - p(x_3=1|x_1,x_2))\times \cdot \times(1 - p(x_{24}=1|x_1,x_2,\ldots,x_{22},x_{23})$
So unfortunately you will not be easily able to reconcile the daily and hourly probabilities as this would require the conditional probabilities (or at least a model of the dependence), which probably is not supplied in the forecast.
In the particular example given in the question, if there were four hours that had a probability of rainfall of 50% then this could mean that 50 out of 100 models in the forecast ensemble had rain that lasted all four hours and the other 50 were dry.  However, it could have meant that 50 models have rain for the first two hours and dry after that, and the other fifty were dry for two hours and then had rain for two hours.  In the first case, the probability of there being rain at some point during the four hours is 50% (as half of the models say there will be no rain at any point) whereas in the second case, the chance of rainfall at some point will be 100% as all the models agree that it will rain during the four hour period, they just disagree as to precisely when it will happen.  The daily forecast works this out by looking at the proportion of models that actually gave some precipitation at some point during the day, but the hourly probabilities in isolation don't give enough information to work out what happened throughout the day in individual model runs.


Is Earth's atmosphere 1600 km thick? Some textbooks say that atmosphere extends up to 1600 km, but exosphere is more than  9000 km thick.
Where is the mistake?

I agree with the comments; some upfront research would be good here, even at a basic level.  A good place to start is this Wikipedia article, which gives not only atmospheric heights but also other characteristics such as composition and the behavior of molecules.
In terms of heights the Wikipedia article suggests 700 km for the lower boundary of the exosphere, versus 1600 km in the question. Neither figure is really wrong because, of course, when you're dealing with atmospheres there is no hard and fast boundary between layers.
Similarly, the 10,000 km altitude given for the top of the exosphere, where it merges with the solar wind, is not hard and fast either; it depends on how you decide where the solar wind becomes dominant over the molecules bound by Earth's gravity.
Moreover, the outer boundary of the exosphere, however you define it, should not really be considered spherical.  The solar wind moves outwards from the Sun, so the exosphere is compressed on the side facing the Sun and pulled out like the tail of a comet on the opposite side.  The same effect is seen with our (and other planets') magnetosphere, because the solar wind also contains electrically charged particles.
I hope I've whetted your appetite for more in-depth exploration.  Good luck!


How/where is randomness/stochasticity used in weather prediction I am seeking information on how weather models use randomness (if at all). From what I can gather daily weather forecasting uses partial differential equations with initial and boundary conditions plugged in from data. Do they use randomness to vary the initial conditions (to account for uncertainty)? Or is there some point in the modeling process where randomness is inserted (e.g. drawing from a normal distribution)? Or are weather models completely deterministic?

I read a thread on EarthScienceSE for probability of precipitation (PoP), and it still isn't clear to me if there is any randomness at all in the model and how its output is averaged over a given area. How are the "confidence in any precipitation" and "coverage area" generated (which are multiplied to get the overall PoP)?

I know that "chance of rain" is a very specific example, but I am interested more generally where randomness is used in common weather models. E.g. "this model uses the normal distribution to estimate this quantity" etc. Specific information is especially appreciated, e.g. name of model and where it uses random numbers. Any help is appreciated!

Probability is used in weather forecasting. I will only highlight some examples due to my lack of knowledge in some areas.
Before initializing a forecast model the data needs to be assimilated. That means we need to somehow put measurements from ground based stations, satellites etc. into the model and fit this data to the grid. We then have an "atmospheric state estimate". This usually involves the minimization of cost functions. Typically the uncertainty of this "atmospheric state estimate" is used in the process of ensemble forecasting. An introduction to data assimilation can be found here at ECMWF. Every operational weather forecasting model has to do this data assimilation process. Since you specifically asked for names, here are a few: Global Forecasting System (GFS, probably the model you weather app uses), ECMWF model (European Center for Medium Range Weather Forecasts), Icosaheadral Nonhydrostatic Model (ICON, operational model of german weather service),High Resolution Local Area Modelling for numerical weather prediction (HIRLAM, operational model of some Scandinavian countries).
In an ensemble forecast the equations are solved as you stated in the question. However, there are certain aspects of the model that are varied to account for uncertainties. These aspects can include the initial conditions (including time, sometimes time-lag is used), variations of parameterizations (and there are a lot of them, basically for every process that can not be resolved by the model grid) and sometimes even multi-model ensembles. The model is then initiated many times to obtain multiple and different forecasts. Again, there is a nice introduction at ECMWF. Some ideas on how to visualize ensemble forecasts can be found here.
All of the above focussed on probability in the course of initializing a model. However, even if no ensemble is used and if we'd know the state of the atmosphere without error - we'd still have to rely on probability due to sub grid scale processes. A prominent example is cloud cover. Suppose we have a mean humidity $q$ in a grid cell (which is what the model gives us). Clouds will only form if $q > q_s$, where $q_s$ is the saturation humidity. Depending on other parameters like temperature a probability density function $Q(T,...)$ is assumed. A possible parameterization for cloud cover could be that the fraction of $Q(T,...)$ larger than $q_s$ defines cloud cover. I will not give examples for typical distributions used, since this is an active area of research. Once more I'd like to refer to ECMWF if you wish to see some details and examples of pdf's used.
Finally, I'd like to add that a main source of uncertainty in models (there is not necessarily probability used) is the parameterization of of convection (shallow and deep). Precipitation is highly related to humidity and convection and therefore large errors are often the result of parameterization.
I hope this helps somewhat.
Edit: Regarding the precipitation problem. What you see at google or the typical weather app is based on model simulations but most certainly not a model output. If google tells you "30% rain probability at your place" then this will most likely refer to a 30% chance that precipitation in an (by google unspecified) area exceeds a certain threshold. The certainty is
is generated by looking at the ensemble. The threshold is exceeded in 30% of the simulations. This is also the reason why a high resolution model is less accurate. It is easier to predict that it's raining 0.1 l somewhere in New York tomorrow than to predict that it rains 0.1 l in the central park tomorrow.


Can they still not predict rain even one week in advance? Every ten minutes, I make an API call to the SMHI's API with the GPS coordinates less than 1 km from here (which cannot possibly matter for accuracy, but does for privacy). SMHI is the Swedish weather forecast "ministry" or however one would translate it. They've been collecting weather stats since the mid-1700s, so you'd think they would be pretty skilled by now. I think they have some of the oldest weather data in the world, but don't quote me on that.
I don't really care about the temperatures, but I do look out for rain. In fact, I automatically clear and update my little "calendar" in my "control panel" with little icons for when this API claims that it will rain in the next 7 days, so that I constantly know how long it's left until the next time it rains. In theory.
I love rain.
Well, yesterday, my calendar was full of those sweet rain icons. I rubbed my hands and started looking forward to a nice week full of wonderful rain, yet now when I wake up, it has updated to be six full days left until the next time it rains again. And this is far from the first time. In fact, it happens all the time. They basically seem to have no idea whatsoever when it's going to rain, until just before it starts.
Are modern weather forecasts this inaccurate? Are they just particularly incompetent over at SMHI? I did integrate another, international API. I guess I should write some mechanism to compare their data with SMHI's. However, I suspect that the international API might well just use SMHI's data for coordinates within Sweden, and I'm not exactly eager to figure out how to make such a comparison.
Is rain forecasting really this inaccurate still? Isn't one week a pretty reasonable window to expect accurate weather data?
This makes me really wonder how accurate those "farmer's calendar" predictions were. It would interest me to see how right they have been compared to modern "scientific" weather forecasting.

I am going to pause and say I don't know anything about SMHI. Therefore I can't comment on their competency. But I am sure they don't appreciate being called incompetent. If you are so passionate about rain, have you considered looking at weather prediction, and trying to beat them?
It is well known that the limit for predictability of weather is 2 weeks. Past that, climatology is just as accurate as modern forecasts in the grand scheme of things. Individual events may have more or less predictability. Precipitation is very hard to forecast, for various reasons including the lack of quality water vapor observations, the complexity of microphysics, and the interaction with other atmospheric physics.
It really depends on the mechanism for rainfall. Different mechanisms have different amounts of predictability. For example, a 5-day forecast of a hurricane is off by an average of 200 miles (321 km). Thunderstorms, especially individual cells, are hard to predict without probability. Extratropical cyclones are a bit easier predicted.
Farmers almanacs are notoriously inaccurate. Moreover, their "predictions" are fuzzy. You'll find better accuracy with actual forecasts.


Laboratory simulation of the Earth's magnetic field I remember reading an article where a scientist was able to make a spinning iron tube with liquid nickel inside and it created a magnetic field, providing a laboratory-scale simulation of the generation of the Earth's magnetic field by convection in the outer core. I can't find any reference to this work on the web. I would like to find documents about such projects and see whether there have been any updates on the research.

Magnetohydrodynamic experiments intended to create laboratory analogues for the Earth's magnetic field generally use molten sodium rather than nickel. You can read about the details of one such project, DRESDYN, in this arXiv preprint.

The central part of the envisioned precession dynamo experiment… will be a cylindrical vessel of approximately 2 m diameter and length, rotating with up to 10 Hz around its symmetry axis, and with up to 1 Hz around another axis whose angle to the first axis can be varied between 90° and 45°. The inner cylindrical shell (made of copper) is immersed into a larger cylindrical stainless container with conical end parts that can later also be used to house alternative inner shells, e.g. in the form of ellipsoids.
The mechanical and safety demands for such a large scale sodium experiment
are tremendous. With a total mass of approximately 20 tons (including the sodium
in the conical end parts and the stainless steel walls) the sodium filled cylinder will have a moment of inertia of around 104 kg m2. With a rotation rate of 10 Hz and a precession rate of 1 Hz, this amounts to a gyroscopic moment of 5 × 106 Nm which requires an extremely massive basement and a careful avoidance of resonances. Further, the experiment must be fenced by a containment which can be quickly flooded with Argon in case of a sodium accident.

Exciting stuff! Here's the project website. According to a presentation at EGU this year, the building is currently under construction.
A group at the University of Maryland is conducting similar research, and has already constructed some experimental sodium dynamos.
I'm not aware of any such experiments involving nickel. Despite its high reactivity, sodium is easier to use for such experiments because of its much lower melting point and density. Nickel's melting point (1455°C) is only 83° below that of iron, so liquid nickel in an iron shell would be a tricky proposition.


What are those arrowlike underwater structures for? Looks like it has something to do with fishing: Google maps link

Those are Yap Traditional Fish Weirs, according to islandculture.info

  In 2008, Yap State Historic Preservation Office (YSHPO) commenced a
  project to survey the fish weirs (aech) around the main island of Yap.
  The aech is a stone/rock structure, usually in the shape of an arrow
  (many have a shaft, some do not), that catch fish after they move
  inside a catchment area at high tide and are trapped when the tide
  goes out. It is thought 700-800 aech may be located around Yap's main
  island which has a coastline of about 100 km in circumference.


Is winter hotter at the Equator? I live in the Northern Emisphere. One of the things I have been taught when I was in high school is that winter is colder than summer because in that season we're at an unfavorable angle and nights last longer than days, despite Earth being closer to the Sun during winter months.

Does this really mean that on the Equator, where day and night are of the same length all year long, winter is the hottest season*?

Does this also mean that Winters in the Southern hemisphere are colder than our Summers and their Winters are hotter than or Summers (or that they would be if not for the Gulf Stream, air currents and other temperature-changing effects)?

*I can think of a different reason that would make equinoxes hotter (more sunrays per surface area when the sun hits from above all day long) but I have no idea of which effect would be greater.

Does this really mean that on the Equator, where day and night are of the same length all year long, winter is the hottest season?

By "winter", I assume you mean December, January, and February. The answer is "No!"

Insolation varies on an annual basis outside of the tropics, one maximum and one minimum every year. This is not the case in tropical regions, where available insolation has two local maxima and two local minima every year. This effect is greatest at the equator. The graph below depicts available insolation at increments of 30 degrees latitude, from the equator to the north pole.

Note that at the equator, available insolation achieves local maxima at the two equinoxes and local minima at the two solstices. The reason is that the Sun is directly overhead at local noon on the equinoxes but is 23.5 degrees from vertical at local noon on the solstices. Sunlight has to travel through more air at the solstices than at the equinoxes.

The slight variations in insolation at the equator are easily overcome by climate. Equatorial regions tend to have wet seasons and dry seasons. When these occur depends much more on wind patterns than it does on aphelion / perihelion.

  Does this also mean that Winters in the Southern hemisphere are colder than our Summers and their Winters are hotter than or Summers?

The answer is once again "No". The slight variation in insolation due to the Earth's eccentric orbit is once again easily overcome by other phenomena. The driving characteristic for this part of the question is that the northern hemisphere has much more land mass than does the southern hemisphere. This means that except for polar regions, southern hemisphere seasons tend to be more moderate than do northern hemisphere seasons.


Prompt gravity signal induced by the 2011 Tohoku-Oki earthquake - could this really be useful for warnings? Edit: Two new items may shed more light on this question:

BBC: Gravity signals rapidly show true size of giant quakes links to:
Science: Observations and modeling of the elastogravity signals preceding direct seismic waves

The Nature Communications paper Prompt gravity signal induced by the 2011 Tohoku-Oki earthquake presents a "...report on the search for a prompt gravity signal during the rupture of the 2011 Mw 9.0 Tohoku-Oki earthquake in data recorded by a superconducting gravimeter in the underground Kamioka Observatory and five nearby broadband seismometers from the Japanese network F-net."

They conclude that with a certainty of about 99% that a prompt gravity signal was detected. The change in position of large masses of crust resulted in a tiny change in gravity even 500 km away and this was within detectable limits of this extremely sensitive instrument.

Since gravity's influence "travels" at the speed of light it is suggested this might be an avenue to be explored for a potential early warning system.

Considering that electrical and optical signals (e.g. the internet or radio or a more dedicated communications system) travel about 2/3 the speed of light in wires and fiber, and even conventional internet pings are of the order of 100 milliseconds or better, is there any suggestion or discussion anywhere else besides this paper that super-sensitive gravimeters would be in any way better and/or cheaper than a network of cheap sensors?

In either case the idea is an early warning for something "big" rather than accurate measurements. Although the paper and analysis is interesting and elegant - is there any serious discussion or speculation that something like this - a prompt gravity signal - could somehow be actually useful as an early warning system?

If you have a sufficient number of sensors, e.g., land-based or ocean-bottom seismometers, in the vicinity of where strong earthquakes typically happen, then it will take a few seconds for seismic waves to reach them, and a few hundred milliseconds for the electric signal to get to a place where a warning could be triggered.

On the other hand, the gravimeter would provide essentially instant warning. So you save a few seconds. At the same time, it takes many many seconds for earthquake waves to travel to the places where the warning would matter. In fact, the earthquake rupture itself may be many many seconds long. And it will take minutes for tsunamis to reach shore.

In other words, what you gain in advance warning time is not actually very large, and it may not be worth the effort. I would also not be surprised if it takes tens of seconds or minutes to actually see the change in gravity in noisy gravity measurements, and/or to take the same amount of time to just process the data.


How many joules are required to mine a unit of coal? Coal is still a major source of energy for generation of electricity. So how much energy is used to extract a unit (tonne/kilogram etc) of coal? And thus what is the efficiency of coal as a source of energy?

The efficiency of coal as a source of electricity is very low: typically of the order of 30%. So losses are of the order of 70%. But losses due to energy expended in the extraction of the coal itself only form a very small proportion of this.

Estimates for extractive losses tend to be of the order of 0.5-5%. That's a huge relative range, because the energy density of different types of coal (J/kg) can vary by a factor of 5; the coal could come from a deep mine or an open-cast; and the amount and kind of mechanisation varies hugely.

But these huge relative variations are completely swamped in absolute terms by the other losses, which are at the very best 20%, and can be 65% or so. Which is why there's not a huge amount of literature on the energy inputs to coal extraction: it's such a small part of total losses, that it gets lost in the rounding.

In the British residential electricity supply, there's about 7% losses from local distribution (UK figure), 2-3% from transmission grid, and about 60% losses at the plant itself, in the form of heat (NB efficiencies here are multiplicative, rather than additive). The British average for 2013 was 64.2% losses in plant - see DUKES 2014 table 5.9

CHP plants mitigate this by capturing a large share of the heat, for distribution in local heat grids. But they still have losses of 5-25% at the plant itself, and then further losses in the heat and electricity distribution system. Call it 20% losses in the best case. Denmark has a lot of high-efficiency coal plants and CHP, but still only managed 55% efficiency, so 45% losses (Danish Electricity Supply '08 Statistical Survey, Table 10).


CO2 emissions per calorie (food) I have seen several lists with CO2 emissions by weight for producing several different food products. I think this is an interesting consideration, and possible argument for vegetarianism/veganism.

I would however prefer a list with CO2 emissions by calorie, as I feel it is a more useful at estimating consumption. Further more the above lists unfairly disadvantage calorie dense foods, or foods with low water content. I haven't been able to find a detailed list (e.g. this is to coarse for my purposes, but otherwise good), so does anyone know of such a list?

Preferably the list should be location neutral (i.e. if transportation CO2 cost is taken into account it should be general enough to apply for all areas)

I answered this question on SustainableLiving.SE. Since no one voted to close this as off-topic, I'll link and summarize my answer here.

I'm glad you asked for it by calorie, since answers on that question had found the data by kilogram, which is not a particularly useful measure. The data source for carbon per kilogram is the Meat Eater's Guide from the Climate Working Group (I believe this is the same as the website you linked, as well); I did the kilogram to calorie calculations from nutritiondata.self.com which gets its numbers from the FDA.

You can read my entire answer, but I will copy the data table for your convenience. Units are kg carbon dioxide emitted per 1000 calories.

Lamb         20.85
Beef         13.78
Turkey        5.83
Broccoli      5.71
Tuna          5.26
Salmon        5.15
Cheese        4.47
Pork          4.45
Yogurt        3.49
Chicken       3.37
Milk          3.17
Eggs          3.06
Rice          2.08
Potatoes      1.46
Beans         1.40
Tomato        1.39
Tofu          1.38
Lentils       0.78
Peanut Butter 0.42
Nuts          0.39


What constitutes a blizzard in meterological terms? Blizzards are most commonly associated with a large amount of snowfall and low visibility. However, snow squalls can induce low visibility whereas a 12" snowfall doesn't have to induce low visibility.

What constitutes a blizzard in meterological terms?

A blizzard is defined as

sustained wind or frequent gusts >= 16 m per second (30 kt or 35 mi per hour)
falling / blowing snow, frequently reducing visibility to less than 400 m (0.25 mi)
3 hours or longer in duration

A storm meeting these qualifications is a blizzard.  Note that snowfall is not necessary, a sustained 35 kt wind blowing snow for 3 hours with low visibility is a blizzard.

  A severe weather condition characterized by high winds and reduced visibilities due to falling or blowing snow.

  The U.S. National Weather Service specifies sustained wind or frequent gusts of 16 m per second (30 kt or 35 mi per hour) or greater, accompanied by falling and/or blowing snow, frequently reducing visibility to less than 400 m (0.25 mi) for 3 hours or longer. Earlier definitions also included a condition of low temperatures, on the order of -7°C (20°F) or lower, or -12°C (10°F) or lower (severe blizzard). The name originated in the United States but it is also used in other countries. In the Antarctic the name is given to violent autumnal winds off the ice cap. In southeastern France, the cold north wind with snow is termed blizzard (see also boulbie).
  Similar storms in Russian Asia are the buran and purga. In popular usage in the United States and in England, the term is often used for any heavy snowstorm accompanied by strong winds.

Source: AMS Glossary: Blizzard


What is the natural replenishment rate of oil? What is the natural replenishment rate of oil? Are extinction events connected with higher production?

Almost nil on human time scales.

The total estimated reserves (this number keeps changing over time) are of the order of 300E9 m^3. For convenience lets say all of this oil formed over the last 300 million years at a constant rate. Then the rate of formation is  1000 m^3 per year or ~6000 barrels of usable oil.

This obviously is a simple back of the envelope calculation and doesn't account for oil that has been lost/degraded/converted to other hydrocarbons over time. Also the rate of formation varies a lot (depends on climate, position/structure of plates and what not).


Will global warming expand the tropical zone It is widely known (to the general audience, I'm not a climatologist) that global warming will let the desert climates migrate further away from the equator towards the poles, such that the South of Europe is becoming more and more desert-ish. (see e.g. this article)
Now my question is: if the desert climates migrate; will the tropical climates also migrate / expand to a broader belt around the equator? Often, it is possible to live quite comfortably as a human in such a region.

It depends on how you define the tropics. Strictly speaking, the tropics can be defined as the area between the tropic of capricorn and the tropic of cancer (23.5$^\circ$N/S respectively). This is because of the earth's axial tilt of 23.5$^\circ$. Since I don't think that the climate change will affect the axial tilt too much, I doubt it.
However, if you define the tropics in terms of climate, probably. Since the Hadley cell is expected to expand with more greenhouse gases, it follows that the tropical weather that accompanies the Hadley cell should expand with it.


Observations of sea ice typology in the Arctic What are the main datasets characterizing sea ice typology, thickness, density, "passability", presence of pressure ridges in the Arctic?

Is it something that can be detected from the air or a space satellite, or from a surface station only?

How extensive is our coverage of ice conditions in the Arctic?

Concerning datasets, there are several, depends on Your final purpose.
One of the simplest is output from OSI-SAF, which has info about Sea Ice edge, concentration, type, emissivity and drift. It is derived mostly from polar orbiting meteorological satellites, I guess.
More detailed info can be found on Univ of Illinois pages
Visual images from  MODIS satellitescan be handy
But, most detailed info about sea ice conditions can be derived with radar satellites, with commercial options like radarsat being available. From free sources, data from Sentinel-1 is available since late 2014.
So the best info is available from satellites, in-situ measurements do not cover most of the area.
Our knowledge of Arctic sea ice is pretty good IMO, at least since 1979 when satellites started to measure the extent. Understanding the age of sea ice is a bit more tricky, as it can be up to ten, maybe even few more years
old.


Why is coal classified as a sedimentary rock? Something just clicked in my head today. Rocks, by the definition I was taught, are composed of minerals which in turn are by definition not organic, so they are or were not alive.

However. Coal, bitumen, and shale are all made of organic matter. Why are they classified under sedimentary carbonaceous rocks?

I'm not sure why you are including shale in your question, unless you are referring to carbonaceous shale, which in not coal, but shale with carbon throughout the matrix of the shale.

Shale is an argillaceous rock, and argillaceous rocks are "detrital sedimentary rocks" [1]. They are composed of clays and the bedding plane within the shales is "due to the orientation of the clay minerals" [1]. Clearly a sedimentary rock.

Coal however, as you state in your question is derived from organic material - vegetation. The deposition of the vegetation material is analogous to the deposition of minerals that formed sedimentary rocks.

Both materials, vegetation and minerals, were transported to a location. In the case of minerals the transportation may have been a long or short distance and carried out by wind, water or gravity (mudslides). Vegetation tends to travel shorter distances than minerals but like the minerals it has traveled and it accumulates.

Over time the vegetation compacts, is heated, undergoes chemical reactions and experiences a very slow form of metamorphosis and petrification.

Being composed of carbon, coal forms a carbonaceous deposit. Having been transported and accumulated in a single deposit it is sedimentary. Having undergone metamorphosis and petrification it is a rock. Consequently it is reasonable to classify coal as a carbonaceous sedimentary rock.

[1] D. G. A Whitten with J. R. V. Brooks, Penguin Dictionary of Geology, 1979


What was the percentage of land mass in prehistoric times when temperatures were high enough that we had no ice caps? I grew curious after watching a presentation about the large creatures of prehistoric times. One of the theories cited about why creatures were so big was the increased oxygen in the atmosphere due to there being no ice caps which meant more available surface area for O2 emitting plant life and the large amount of available landmass for creatures to roam freely. This felt like what could be be historical hand-waving so I'm here looking for facts.

Modern climatologists scientists argue that rising temperatures and melting ice caps risk submerging land masses from the displacement of frozen ice. This is based upon the fact that the volume of water is greater than that of ice.

I did some googling around and saw that most prehistoric representations of Earth and renditions of Pangaea try to squish the shape of our existing continents together but do not address the increase in ocean volume, I assume for illustrative purposes or other simplification. I'm not arguing whether the continents fit together as depicted but rather how much of it existed above the surface of the ocean.

I know that the movements of tectonic plates can also affect what parts of land are underwater by coastal regions shifting lower and those inland shifting higher with the formation of mountains. Water erosion would also play a factor somewhere in all of this in addition to tectonics but only to a point of equilibrium with sea level.

It's interesting to consider that we have found and continue to find historical locations which have since become completely submerged. So it may be safe to assume that the oceans have been already been rising naturally for hundreds of years prior to the industrial revolution through other environmental factors.

Is there a definitive source of study on the subject of the percentage of landmass above sea level across history with relation to ambient temperature and the presence of ice caps?

I'm just a hobbyist who enjoys science and history and have no relevant expertise in this area nit this little idea has had be tickled with anticipation all morning. I would love to learn out more. :)

The real cause rising temperatures is not frozen ocean turning back into water but the volume of the ocean itself expanding (water expands just like everything else when you heat it), and ice on land melting and flowing into the ocean (adding more water).

Ice sheets can be tricky to predict but it has been included in this report . Although for the most part ic just say whether it exists or not reconstructing total volume of ice is currently not something we can determine accurately.

This chart from that report show how ocean temperature and sea level correlate.

This paper shows how the two factors compare, they are are mostly comparable but ice melt (mostly glacier) is starting to overtake expansion. Great chart on page 1157.

As for historical rise, earth used to have two ice sheets, one at each pole (this was responsible for the Asia-North America land bridge), but the northern one has almost completely melted, except for greenland, that is why we had historical sea level rise. There used to be thousands of feet of ice over boston. Land locked ice sheets are very sensitive to temprature, easy to melt, island ones like greenland and antarctica on the other hand create their own sort of insulation by altering circulation. These latter ones are much harder to melt, you need a much greater rise in temprature, which we have created. The last big melt turned england into an island.


Have there been any attempts to measure profiles through deep convective systems using dropsondes? In-situ measurements in deep convective systems, tropical cyclones, etc., are difficult to perform.  Few if any people would like to fly a small aircraft close to its core, and radiosondes or larger balloons would be ripped to pieces.  Even flying high above the top of such a system may not be a pleasant idea.  However, with unmanned aerial vehicles (UAVs or drones), perhaps higher risks can be taken than with manned aircraft.  And whereas radiosondes cannot be launched, dropsondes should not be a problem.

Are there any projects, either operationally or for research purposes, that involve dropping sondes from UAVs flying above deep convective systems, in order to measure profiles of pressure, temperature, as well as cloud and precipitation properties?

NOAA flies routine dropsonde missions into tropical convection if there is anticipated threat to land.  You can find information about these missions in the routine NHC updates for each storm.  This data is used in estimation of hurricane intensity and some of the models assimilate this data to improve storm track and intensity forecasts.

You can learn more about NOAA's hurricane hunters here.

Dropsonde missions over the continental US are problematic.  The mesoscale predictability experiment (MPEX) use dropsondes to determine if better upper air observations could improve predictability in the mesoscale.  One big issue they had is restrictions in where they could drop from the FAA.  They had to provide notice well in advance of the flights and could only conduct missions during certain time windows.  This provided big restrictions in dropsonde missions and would probably make it unsuitable for drops into deep convection (though one might argue with air traffic routing around such convection, that would make drops feasible from an FAA standpoint).

There were some recent talks about MPEX at the 27th Conference on Severe Local Storms in a session about MPEX.  In particular, a talk by Morris Weisman (video) talks a bit about the dropsonde missions.

From another perspective was the DC3 project, which I provided nowcasting in support of aircraft operations.  This project didn't use dropsondes, but instead used aircraft in vertical flight profiles to collect observations from near-surface to tropopause levels.  These profiles were in the vicinity of deep convection, but not within.  This project was primarily interested in how the chemical composition of near-surface air was modified by convection and then transported in upper air outflow.

These aircraft were not dropping dropsondes but I'm not confident a UAV would have been able to fly too much closer to convection to drop into the storms.

In summary, maritime dropsondes are common for getting in-situ measurements of tropical convection, but for continental applications FAA restrictions on dropping things from airplanes makes routine dropsonde missions unfeasible (and I'm assuming these would be done by UAVs as getting NSF aircraft assets to do this would be restricted to short term experiments and not routine operational missions).


Help identifying rock? Found in stream, heavy, has a tin of red lines and dark.  1]]2[grey white, rusty ]3.  Dark lines n rusty lines. Hard to break off piece ain't magnetic

Looks like massive (as in the individual crystals have grown into each other) Quartz, the different colours are due to minerals either dissolved into the crystal structure, those are the dark areas, or simply staining the surface as with the rusty red/orange sections. It could be Calcite or Salt, the first will react with Vinegar and second will dissolved in hot water but both are rather fragile and it would be easy to break off small samples.


Can a 99.9% probability of an M≥ 5 earthquake within a 3-year period be verified? Paper:

Potential for a large earthquake near Los Angeles inferred from the 2014 La Habra earthquake (2015)

Obviously there has been much discussion on  the viability of earthquake prediction. This recent paper presents some rather bold claims:

  The calculated probability for a M ≥ 6 earthquake within a circle of
  radius 100 km, and over the 3 years following 1 April 2015, is 35%.
  For a M ≥ 5 earthquake within a circle of radius 100 km, and over the
  3 years following 1 April 2015, the probability is 99.9%

On the other hand, the USGS is saying those figures are too high:

  The USGS conducts its own look at quake risk in California — the most
  recent version is called Uniform California Earthquake Rupture
  Forecast, Version 3. Jones said that, according to those models, there is only an 85
  percent chance of a magnitude 5 or 6 quake in the same region over a
  three-year period. "It's nowhere near a 99.9 percent number," Jones said.
  USGS released a statement on its Facebook page saying that the lack of
  details on how this number was reached "makes a critical assessment of
  this approach very difficult."

The LA Times has it reported here: http://touch.latimes.com/#section/-1/article/p2p-84786019/ , which says:

  The study’s lead author, Jet Propulsion Laboratory principal research scientist Andrea Donnellan, said in an interview that the 99.9% figure was not a central conclusion of the paper and should not be viewed as an official forecast.
  “As scientists, we were not putting out an official forecast. We were putting out something in a paper to test,” Donnellan said.
  Donnellan said she considers the 99.9% number a test of a model, or algorithm, on the probability of future earthquakes.
  “We never said in this paper we were predicting an earthquake. And we said that's the probability of an event," Donnellan said. "There is still a 0.1% chance it won't happen. So we need to test it. And that's what we are doing as scientists."

Has anyone verified this study? Is there anything wrong with it? How were they able to arrive at such a high probability?

Based on Probabilistic Seismic Hazard Analysis the probability of an earthquake of magnitude $m$ occurring at the source is obtained with the Truncated Exponential Distribution can be given by

$$P(M > m) = \int_{m}^{m_{max}} \frac{\beta e^{-\beta (m - m_{min})}}{\left( 1 - e^{-\beta (m_{max} - m_{min})} \right)}dm$$

where :

$m$ is the magnitude; $m_{min}$ is the minimum magnitude of earthquakes in source; $m_{max}$ is the maximum magnitude of earthquakes in source; $P(M > m)$ is the probability of occurrence of an earthquake with magnitude $M$ larger than $m$; $\beta = b \ln(10)$; $b$ is the slope in the Gutenberg–Richter (G–R) magnitude–frequency relation.

Source : Development of probabilistic seismic hazard analysis for international sites, challenges and guidelines

Additional Read : Gutenberg Richter Law - why exponential distribution was used


'Forcing' in PDSI Calculation I'm new to climate science - starting to get familiar with the field by reading some published articles. Terminology is always hard when starting into a new domain.

In this paper, Dai - Increasing drought under global warming in observations and models, what does the author mean by the term "forcing," in relation to the PDSI?

Here is an example of usage:

  The PDSI is calculated from a water-balance model forced with observed
  precipitation and temperature...

Another example:

  Figure 1a,b shows that the broad patterns of the linear trends from
  1950 to 2010 in observed annual precipitation and calculated
  sc_PDSI_pm using observation-based forcing2

Here is the citation:

  Dai, Aiguo. "Increasing drought under global warming in observations
  and models." Nature Climate Change 3, no. 1 (2013): 52-58.

What does 'forcing' mean?

The PDSI is calculated from model output data. Models do not predict all relevant variables but some data need to be provided externally from the user. These externally provided data are denoted as "forcing" because they "force" the model to move in one direction (colloquially speaking). You might also call it "drive" a model -- but "to force" is the established expression in science.

In this case

In this particular case, the authors use observational data as input data for the model calculations. Therefore, the authors write

  The PDSI is calculated from a water-balance model forced with observed precipitation and temperature...

Other situations

One might force a model also with data from other models. A river run-off model might get input data from an atmospheric/meteorological model, which predicts precipitation and solar radiation at surface level. We could write

  The river run-off model ABC is forced by modeled precipitation and radiation of the XYZ meteorological model.


How can the average coldest day of the year be before the winter solstice? There are parts of the U.S. where, on average, the coldest day of the year comes before December 21st. [source]

How can this be? Why would temperatures start rising again even while days are still growing shorter?

(I would have assumed that daily temperatures should, in general, always lag behind daily insolation, with some sort of hysteresis relationship.)

I have created composite plots from reanalysis data for the dates as partitioned in the image in the question.  I used the full NARR dataset, which covers 1979 to 2014, so I have a few more years of data than is included in the image above.

What can be seen are largely wintertime climatological means.  A persistent subtropical high off the California coast and persistent lows in the north Pacific and Atlantic.  What does change is the mean extent of arctic air which descends into the US as winter progresses and retreats as spring approaches.

Composite NARR MSLP and 500-1000 hPa thickness 1979-2014

Figure 1. From left to right, top to bottom the dates composited are Dec 1-15, 16-20, 21-25, 26-31, Jan 1-5, 6-10, 11-15, 16-20, 21-25, 26-31, Feb 1-15, 16-28, Mar 1-15 and 16-31.  MSLP is contoured every 4 hPa.  Thickness is shaded at intervals of 10 dm.  Click the plot for a larger version.

The signal I can pick out of this is the approaching and retreating cold (using the proxy of 1000-500 mb thickness) that seems to correlate well with the latest dates of cold in the eastern US, particularly in the great lakes and northeast.

What I'm seeing in the west is that initially the subtropical high is broad and surface flowing westerlies impinging on the west coast would originate initially at higher latitudes than the do later in the winter.  By January the subtropical high and the low in the north Pacific have re-oriented so the surface flow is coming from around Hawaii.  The western US will also be subject the reduced seasonal temperature fluctuates from its proximity to the Pacific.  Once the area has cooled and equilibrated with the Pacific, temperatures will be stable.  As the continental landmass would lose more energy and cool, the westerlies coming off the Pacific (now relatively warm) counteract this tendency.  Conversely the east with mostly continental air flows experiences large seasonality and has a long-lasted source of very cold air from our neighbors to the north.

Summary

The west ceases to cool once it equilibrates with the Pacific, which looks like it happens early in winter (because even though the Pacific is cold, it isn't that cold).  Westerlies from the ocean heep the west warm.  East of the rockies there is no influence from large bodies of water and a constant source of cold arctic air and so the east continues to cool throughout the winter, until the pattern changes toward spring (and all the snow melts...).

For a smaller scale example of how water can have this influence, take a look at during the next extreme cold event in the midwest and great lakes, particularly when air is flowing westerly across Wisconsin and into Michigan.  You will observe a large temperature gradient across Lake Michigan, which keeps Michigan warmer (sometimes much warmer) than Wisconsin.  Later in the winter when the lake is frozen, that benefit is lost and so Michigan tends to be cooler later in winter as it is no longer "shielded" by the lakes.

Data

Data was downloaded from NOAA's North American Regional Reanalysis, accessed 17 Feb 2015.  Files accessed include:

ftp://ftp.cdc.noaa.gov/Datasets/NARR/Dailies/monolevel/prmsl*nc
ftp://ftp.cdc.noaa.gov/Datasets/NARR/Derived/pressure/hgt.day.ltm.nc


Loop in the continental divide Various maps of the Continental Divide (the hydrological  feature, not the trail) contain a loop that looks like this:

What is the hydrologic meaning of the loop in Wyoming?

Even if it's a basin, it must have at least a theoretical outlet from which a high enough water level would flow.

Or does the definition of the divide treat this as having no outlet, and hence in neither the Atlantic or Pacific watersheds?

No water flows out of it, apparently...

https://www.onlyinyourstate.com/wyoming/continental-divide-basin-wy/

In summary, there used to be a big lake there, now its a basin with no flows into either ocean. Water there seems to be self contained, accumulating from rainfall and removed by evaporation.