upper air data(observation) and analysis step for GFS model Global forecast systems(GFS)  gives analysis and forecasts at different time steps. Their main source of input is upper air data which is recorded only twice in a day(observation comes at 00 and 12). But analysis step which incorporates the observations is done at 00,06,12,18 hrs. How is that ?Is my basic understanding understanding completely wrong?

You are right that upper air soundings are typically only done twice a day, and even at quite a coarse observation spacing.

And that upper air data is definitely very important in models.

I'd suggest that, firstly, it's important to note that even a broad, very hazy picture aloft really helps a great deal at the surface.  That can be seen in the quasigeostrophic omega equation.  Basically the large-scale highs and lows and jet streaks drive much of the vertical air motion in the atmosphere.  Plus there aren't quite as many complexities caused by terrain/ground cover/moisture/differential heating that the surface layer sees.
So because the evolution of those large-scale features is pretty straightforward over the course of a day, the early morning's upper-level forecast is still quite reliable and helpful 6 hours later.

But that said, smaller scale shortwaves and vorticity maxima are absolutely vital to weather forecasting too.  And with smaller size and more transient nature, neglecting their changes over 6 hours is likely to really harm forecasts when it comes to critical subtle differences such as you'd see in a tornado outbreak or hurricane track.

So indeed, how DO we recognize those changes?

Well, we do have a second source that these days is probably at least as important as soundings, perhaps even moreso - satellite imagery.

See for example this satellite page.  You can turn on HDW-low, HDW-mid, HDW-high.  As far as I understand it, the models are ingesting that information readily (and likewise cloud coverage, which are just as important).  I believe some satellites also have vertical temperature sounders that are used more now as well.

And third, we also have some other data sources that help.
In certain parts of the world, we've got radars.  I believe at least some of the better models these days are using that data... there's plenty of wind data to be had from velocities (though it would seem challenging to use/analyze it given things like range-folded velocities and the ambiguity of tangential winds see the intro to [this article]).

Plus, I believe at least the ECMWF has had real success in ingesting ACARS... atmospheric data that are generally reported by all commercial aircraft.

But... all that said, your point still has some real potency.  Especially when we note that, when it comes to our best model, the ECMWF... it still only runs twice a day.  Maybe other reasons drive the decision, but you'd think they still weigh how improved such forecasts are.  So it seems fairly likely that they've determined that long-range forecasts don't improve much when they are still based heavily upon that older information.

But then, I think everyone would agree that having hourly models available like the HRRR is very useful in important nowcasting situations, such as severe weather awareness.  So maybe the overlooked small data changes are (counterintuitively?) more important to long-range forecasting than short-term.  Definitely an interesting question you've raised!


Chloride ions for the salty seawater Where does the chloride ions that are required for the salty taste of sea water come from ?

I know that it is the weathering caused by the slightly acidic (due to dissolution of CO2 with water) rain that dissolves minerals in the water which gets carried to ocean. But the sodium ions/atoms require chloride ions/atoms for the salty taste. But I don't think chloride would be present in the rocks.

Please explain.

Chlorine is a very reactive element. Contrary to your statement, chlorine occurs in many rocks and minerals.

The mineral apatite, with the composition: Ca5(PO4)3(F,Cl,OH), is a natural source of chlorine. Virtually all rocks contain chlorine.

Chlorine even occurs occurs in alkaline magmas.

One of the most common minerals containing chlorine is common salt, which is sodium chloride, NaCl.

Geologically, chlorine is everywhere. When rocks are exposed to water and acids minerals, including chlorine, dissolve into solution and they are transported to lakes, salt lakes, aquifers and oceans.


In the northern hemisphere only, what percentage of the surface is land? Across the whole Earth, about 70% of the surface is water and 30% is land.

What I want, though, is to restrict the scope to the northern hemisphere (NH) only. What percentage of NH surface is land?

It would also be good to clarify exactly how we define "land". If I'm not mistaken, the 70/30 split of water/land actually places inland rivers and lakes as land area.

Please also cite a source for this. The only google result I found with an answer was yahoo questions.

I get 40.44%
With a workflow using a tiny bit of Python.

After Polygorial‘s comment I am adding (Feb 17, 2021 update) point zero to state more explicitly that this method requires a map like the one I used (Gall-Peters projection) with equal area projection, as regions of same area on the Earth’s surface will have the same area on the map, and therefore same number of pixels.

Invert and import B/W image of equal area projection for the Northern hemisphere (land = white pixels). Source of original image (full globe): Wikimedia Commons.

Store as Numpy array.

Calculate total number of pixels in image array (black + white).

Calculate total number of white pixels (1s) by summing the entire array (black pixels (0s) will amount to zero).

Calculate percentage of white pixels.

UPDATE September 20, 2018
As suggested by @JeopardyTempest in a comment, as a validation test I run the script for the full image with both hemispheres, and got the expected 30%


The relationship between specific discharge and flux How are specific discharge and flux linked?

Is flux simply specific discharge × area? And when we speak of flux of an element eg. N-flux, is that specific discharge × concentration × area?

I assume you are talking about the fluid dynamics description of flux, which is the rate of volume flow across a unit area.

1.

  Is flux simply specific discharge × area?

Yes you are correct.

$$Specific~Discharge = \frac{Volumetric~Flux}{Area}$$

therefore

$$Volumetric~Flux = Specific~Discharge~\cdot~Area$$

2.

  And when we speak of flux of an element eg. N-flux, is that specific
  discharge × concentration × area?

When you speak of an element the rationale is the same but will depend on whether the model you are devising contains 1D, 2D or 3D fluid elements. The latter is defined as above.


Why is fluid pressure in a fractured rock reservoir only dependent on hydrostatic pressure? Why does lithostatic pressure not play a role? (or does it?)

Fluid (or 'pore') pressure does not depend only on hydrostatic pressure — it also depends on stratigraphy, fluid content, and the geological history of the rock.

The fluid 'stack' can be thought of as a (mostly) connected body of fluid — dominantly brine and hydrocarbons. The rock 'stack' is a similarly interconnected body. The fluid stack defines a typical soft lower limit of pore pressures; the rock stack defines the hard upper bound.

In practice, we don't experience lithostatic pressure in the pores because at some level of stress below lithostatic pressure, we find the fracture pressure. If the pore pressure reaches this level, the rock breaks and pressure equilibrates. This is the mechanism behind induced hydraulic fracturing, or fracking.

But pore pressure does not have to be hydrostatic. 'Geopressure' or 'overpressure' or underpressure can occur if a stratigraphic layer is unusually tight, for example salt, and a porous formation experiences rapid uplift or burial. We might also depart from hydrostatic pressure as the density of the pore fluid changes, with salinity or gas saturation for example.

This cartoon shows pressure measurements (green) in a gas well. The other trends can be computed from models or data (for example the bulk density log). The shallow part of the well is hydrostatic; the deeper section shows overpressure. Natural gas is low density, so the gas zone shows a different trend. Clearly there will be a potentially dangerous pressure kick as the drill penetrates the top of the reservoir. If the gas trend were to hit fracture pressure, the trap would leak and the hydrocarbons would escape — a common natural phenomenon.

You might also like to read these related questions:

Why is the lithostatic pressure gradient 1 psi/ft? How is it derived from density?
How do I derive the formula for lithostatic (overburden) pressure?
What is the reasoning behind the statement "Faulting will occur along the plane where the shear stress is the highest"?


The geology of local landscapes and small scale features I'm learning geology to understand the processes behind the formation of my local landscape.

I understand the processes behind big features, such as mountains. But I'm struggling to understand the processes behind small local features, such as hills.

I live in Reading, Berkshire, South-East England, with a typical landscape of rolling of grassy hills and clay strata. Similar to this image below.

What geological processes would be responsible for the formation of this landscape?

Additional Information

Strata:

I dug a hole in my garden and found there is a thin layer of soil, then a large amount of clay with a variety of rocks and pebbles.

Features:

The main features are a landscape of rolling-hills and grassy plains.

Question

What geologic processes are responsible for the formation of these low-hills and clay strata?

Were the hills once mountains, now eroded?

(this is consciously the start of the answer - my regional geology books -cf. above comment, are packed away due to a house move).

The rolling hills are very distinctive of the English Jurassic & Cretaceous. Relatively low dipping rocks - long wavelength folds. The ridges are due to rocks that are more resistant to erosion. For example, the English chalk forms the North Downs and South Downs (and the Yorkshire & Lincolnshire Wolds). Chalk is actually more resistant to erosion that some of the surrounding rocks (don't believe me? Have a look at Beachy Head or Flamborough Point!).  These ridges have influenced pre-Roman history - eg. the Ridgeway follows a series of these ridges.

I may be out of date on this, but the folding is usually blamed on the formation of the Alps. The Alps are a long way off, but their influence can be felt as mild folding. The cause must be after the youngest Cretaceous that is present (which I think is the chalk?) - and there was only really the Alps, the Paleogene North Atlantic Volcanism (eg. Skye, Arran, Mull), and opening of the North Atlantic to choose from.

As for your soils: This is where the Regional guide will help. The soils are much more recent. A decent explanation will probably involve at least one ice age, and river courses which have since changed (eg. the proto-Thames used to flow from the North!)


Temperature at 2 m MERRA2 I need MERRA2 data with Temperature at 2m.

I'm checking on https://disc.gsfc.nasa.gov/daac-bin/FTPSubset2.pl but I can't find this variable.

Suggestions where I can find them? Or anyone that did have or has the same problem?

Thank you for the help.

When I visit that link, the first option at the top ("Data Product") defaults to inst3_3d_asm_Np, which is atmospheric variables in pressure levels.  I suspect you need to change that dropdown option to inst1_2d_asm_Nx, which is surface and near-surface variables.  The list is shows me for that option is,

DISPH = zero plane displacement height
PS = surface pressure
QV10M = 10-meter specific humidity
QV2M = 2-meter specific humidity
SLP = sea level pressure
T10M = 10-meter air temperature
T2M = 2-meter air temperature    <---- Here it is!
TO3 = total column ozone
TOX = total column odd oxygen
TQI = total precipitable ice water
TQL = total precipitable liquid water
TQV = total precipitable water vapor
TROPPB = tropopause pressure based on blended estimate
TROPPT = tropopause pressure based on thermal estimate
TROPPV = tropopause pressure based on epv estimate
TROPQ = tropopause specific humidity using blended tropp estimate
TROPT = tropopause temperature using blended tropp estimate
TS = surface skin temperature
U10M = 10-meter eastward wind
U2M = 2-meter eastward wind
U50M = eastward wind at 50 meters
V10M = 10-meter northward wind
V2M = 2-meter northward wind
V50M = northward wind at 50 meters


monthly temperatue by state I am trying to find out monthly average temperature and average rainfall for states of USA from 2015 to 2017. To my surprise I am not able to find it anywhere.  Please help.

I could find this link - which provides data in a format I want. However, they took average of 30 years, 1981 to 2010. I need data for individual months, starting from Jan 2015 to Dec 2017 (36 data points).

It may take a few minutes of work this way...

But did find digging through NCDC's climate data inventory, the climatological rankings pages should help find what you're looking for if you're looking for their full state averages.

However, I think can help you a step further with addresses to go through: if you replace STATENUMBER in the address of:

  Temperature: https://www.ncdc.noaa.gov/cag/statewide/time-series/STATENUMBER/tavg/1/4/1895-2018?base_prd=true&begbaseyear=1901&endbaseyear=2000

Instead with each of the numbers 1 through 48, you can get the state data for each of the US contiguous states.  And Alaska is 50.  Likewise with precip:

  Precipitation: https://www.ncdc.noaa.gov/cag/statewide/time-series/STATENUMBER/pcp/1/4/1895-2018?base_prd=true&firstbaseyear=1901&lastbaseyear=2000

However, it looks like disappointingly Hawaii (and territories) doesn't get the same data produced, or at least available anywhere I can find on that site.  If you really want to seek that out, you might consider using Honolulu and Juan climate reports for a reasonable proxy, or the answer to the question Current Global Climate Dataset? on GSE may offer a rough avenue towards fair gridded information.

Not the easiest avenue, would love to see something better (and hopeful if you do go through this tedious method, perhaps post it to a Github repo or such so that more data may be easily available in the future to others facing the same problem.


Global warming - why doesn´t mankind collect heat (thermal energy) and turn it into electricity or send it to space? Why doesnt mankind "collect" thermal energy (there has to be some way: thermal couplings, detour over chemical energy, whatever) and after it has been concentrated at one point, turn it to electrical energy (like steam turbines do) or at least radiate it to space?

Your middle school physics perhaps hasn't gotten to thermodynamics yet. The three laws of which can be summarized as 1) You can't win; 2) You can't even break even; 3) You can't leave the game.

The crucial point here is that heat engines don't actually work on heat, they work on temperature differences.  So you can't really "collect" heat and turn it into other forms of energy, because you need a colder place to transfer the heat to in order to convert the heat to say electricity.  Which is why power plants are usually situated by oceans, lakes, or rivers, in order to use the water as the cold side of the generator.  (And ones that aren't have large cooling towers, in order to use the air.)

When you do move heat around, say with the heat pumps used for home heating and cooling, you're always using some extra energy to "pump" the heat from one place or another.  If you're heating, you move some heat from the ground outside to your house, but the net result is that the system of ground+house gets a bit warmer, because the electricity used for the pump becomes heat.

WRT sending the heat back into space, that's actually the cause of global warming.  Atmospheric CO2 acts as an insulating blanket, preventing some of the sun's heat from being radiated back out into space.  By increasing the amount of CO2 in the atmosphere, we've increased the thickness of the blanket, so the Earth gets warmer.


Calculating Stream Flow from Rainfall Data I have been given the following data:

Month
N
T (degrees C)
Monthly Rainfall (mm)

1
0.68
1.12
391.1

2
0.82
1.40
163.1

3
0.98
3.04
296.5

4
1.15
4.77
157.7

The list goes on.
From this and using the Thornthwaite Equation, I calculated both I and Ep
(Where Ep = monthly potential evaporation (mm), N = relative day length, T = average monthly temperature in celcius, I = monthly heat index)
(3 d.p.)

Month
I
Ep

1
0.106
114.941

2
0.148
123.972

3
0.474
100.546

4
0.932
94.192

The list goes on.
From this I need to calculate riverflow/streamflow given as monthly rain - Ep.
Thus:
(3 d.p.)

Month
Riverflow

1
276.159

2
39.128

3
195.954

4
63.508

The list goes on.
However, I have been asked for 2 reasons why the flow I have predicted would be inaccurate. In other words, to more accurately predict riverflow what extra data would I need?

Calculating river flow from rainfall - evaporation is a simplification. Firstly you are assuming that you can accurately measure rainfall, then that theoretical estimates of evaporation are correct which, given how much land cover and vegetation vary, is unlikely.
Next consider the pathway from raindrop hitting the soil to the river. It's clearly not instantaneous. That raindrop can evaporate directly, run off over the ground surface or soak into soil. In the soil it can be taken up by vegetation or infiltrate and become groundwater recharge. Depending on soil and aquifer characteristics this introduces a delay in the conversion of rainfall to runoff. In the real world this delay could be weeks, months or even years. In your example it's also worth thinking about low temperatures. Is rain falling as rain or is it snow?
Thirdly consider how water can get diverted from its pathway to a river. Is water abstracted from the pathway (i.e. from an aquifer),  or from the river directly?  Conversely reservoirs may regulate flows, either up or down depending on management.


calculation monocationic elements How to calculate of the number of monocationic millimoles?
If I have concentrations of: $SiO_2$, $TiO_2$, $K_2O$, $MgO$, $MnO$, $Na_2O$, etc.

How can I get $Na^+$, $Mg^{2+}$, $Mn^{2+}$ ..?

This is part of an intent to calculate the weathering intensity scale suggested by Meunier et al. (2013), but it is a doubt suitable to any kind of use of oxides, so post it apart from it. See a related WIS question.

Reference: Meunier, A.; Caner, L.; Hubert, F.; El Albani, A. and Prêt, D. (2013). The weathering intensity scale (WIS): An alternative approach of the Chemical Index of Alteration (CIA). American Journal of Science, 313(2), p.113-143. doi: 10.2475/02.2013.03

Oxygen is always divalent negative. An oxide has to be charge balanced, meaning the total has to be zero.

Therefore, some like CaO means you have Ca2+O2-.
Something like SiO2 is going to be Si4+2O2-.
Something like Na2O is going to be 2Na+O2-.

As you can see, the charges all sum to zero, given that oxygen is negative two.

Let's work out an example:

You have 1 moles of each: K2O, MgO, and ZrO2. You will have one mole of Mg2+, one mole of Zr4+, and two moles of K+.


Do icebergs have any impact on ecology? Are icebergs neutral actors in the environment, or do they have any impact on the local ecology.  Do they have any environmental impacts that might influence any part of the biosphere?

Yes, they have many impacts:

They provide a substrate for algae to grow and they can have whole ecosystems under them. You might think that such substrate is transient because it is melting, but Arctic and Antarctic waters are often below zero degrees Celsius, therefore, freshwater ice doesn't melt. You can find many articles about such ecosystems (here is one).
They transport sediments and nutrients into the ocean.
They provide safe rest areas for animals like seals, birds and penguins.
They impact the temperature of surface waters, specially in fjords.
They stir the sea floor in shallow waters

And there must be more ways they impact the environment and ecosystems but those are the ones I can think about right now.


Why don't green house gases escape into space? I have never heard an explanation as to what  traps GHGs. What holds them in place? Has research been conducted to assess the efficacy of say triggering a change in their chemical composition into a compound that would render them inert or less impactful or 'setting them free' so to speak?

The reason the atmosphere (including GHGs) stays attached to the earth is gravity. This is called the Hydrostatic Equilibrium. There is one GHG that this does not fully apply to: water vapor. While water vapor can be considered to be in hydrostatic balance, the fact that it undergoes a phase change (and becomes dissociated if it reaches too far up) prevents it from being more evenly distributed vertically like $\ce{CO_2}$ or $\ce{CH_4}$.


Why is Montana warmer than Wyoming? The National Climatic Data Center (NCDC) data shows the mean temperature from 1971-2000 for Montana was 5.97°C (42.74°F) and Wyoming's was 5.54°C (41.98°F).

Montana is at a higher latitude, so this is surprising.

As mentioned in the comments, the 1km difference in average elevation of Wyoming in comparison to Montana plays a major role, as from the website Wyoming State Climate Office,

  Because of its elevation, Wyoming has a relatively cool climate.

However, there is a bit more to it than that, the presence of numerous valleys

  provide ideal pockets for the collection of cold air drainage at night. Protecting mountain ranges prevent the wind from stirring the air, and the colder heavier air settles into the valleys often sending readings well below zero.


Why are climate anomalies calculated relative to 1981-2010 average? What is the purpose for doing this? Is it inaccurate to calculate anomalies for variables such as sea surface temperature and precipitation based on a different time period?

In theory the choice of baseline average is irrelevant, because the purpose of using anomalies to to clearly see the change over time, allowing different absolute values to be compared.

Although in climate studies, we try to use baselines that are as 'pre-industrial' as possible to try and get the change from 'natural'.


Trends in atmospheric CO2 I plotted the atmospheric CO2-concentrations to see trends and wondered especially about the phase around 1600 in the plot which I find very interesting. Etienne Godin already told me some facts in the comments of another thread, but I'm curious about more details, since I'm a newbie in this area.

source: https://www1.ncdc.noaa.gov/pub/data/paleo/contributions_by_author/frank2010/smoothedco2.txt

Where I plotted the column ALL_50_full.

What do you say?

Since CO2 concentration is responsible of temperature, that trend is related to the little ice age, where Earth cooled a little. Wikipedia article describes several possible causes for that, one of the is the answer of Keith, but others might be orbital cycles, solar activity, volcanic activity and ocean circulation.
Also is possible that is just a cycle that repeats itself each 1000 or 1500 years.


What is the relationship between raw seismic data, CMP Stacking, NMO & Machine Learning I recently joined a geophysics project to assist with some of their machine learning modeling but am trying to gather the domain knowledge required to participate.

Something I don't quite understand is the common-midpoint stack, Normal MoveOut & raw data. I have these seg-y files and I am able to plot them in python. They look fine to me, but I am reading a lot about CMP stacking, weighted CMP stacking and NMO. Are seg-y files considered to be "raw seismic data". Is the CMP and NMO process something that happens at the stage I am getting the files? I am confused because these seem to be standard practices yet I am unable to find an implementation for any of this in any programming language. Are there any tools you recommend for preparing seismic data for machine learning modeling?

SEG-Y files are a general purpose archival format. So they can be "anything". 2D seismic, 3D seismic, raw, processed, unstacked or even derivatives (seismic attributes).

How to get information about your data in the SEG-Y file:
SEG-Y contain 3 types of headers that describe the data.

The EBCDIC header is a 40 by 80 character sheet that is a remnant from the times of punchhole cards (I'm not joking). Usually it contains info about the state of the seismic. Processing workflow, acquisition geometries etc. The binary header has some more fixed data about the data set. The trace headers contrain every separate data set from the acquisition. Nice blog by Agile Scientific here.

You can read about the details of seismic processing and conventions in the open access book "Seismic Data Analysis". It used to be several hundred dollars and has been cited in every seismic lecture I have ever attended. However, I'll give you some answers now.

Common Midpoints

CMP stacking, weighted CMP and NMO are highly entangled.

A seismic measurement, listens really close to the reflection from the subsurface. However, it's a little noisy. "Stacking" is recording the same place over and over, then adding it up to cancel out random noise and enhance coherent signal. However, just doing it in the same area would be very inefficient, therefore we change the acquisition over the point we illuminate, in the picture you see that we have a nice fan of ray geometries going to the same point in the middle, the Common MidPoint CMP. This leads some interesting behaviour.

Normal Moveout

this is the formulation to calculate how a record from a different angle can be shifted to be in line with another record for the aforementioned stacking. As you can imagine the records that have longer ray paths take longer, depending on the velocity of the rock they travel through. This shift down-ward is namen Normal MoveOut (NMO). The equation above is an approximation, but it's good enough for this explanation, check out the book for more info on this.

Post-Stack vs. Pre-Stack

A seismic acquisition over a 2D area is named 3D seismic, because X-Y-T (recording time). The data, repeated over the same point in X-Y as mentioned above will have several record with the same T and a different "offset" between the source and the receiver. That means, 3D seismic data coming fresh out of the field will be four-dimensional. This is called pre-stack. Once we do a lot of data preconditioning and filtering and a smarter version of the CMP stacking above, we get 3D seismic that is actually three-dimensional.

Stacking versus Migration

Stacked data will have all kinds of weird wave effects in it. Usually geologists will work on "migrated" data. A migration aims to find the "true" location of a reflector, reversing wave effects. I suspect you might get this one.

Time versus Dpeth

You may have wondered from before about X-Y-T. T stands for time not depth, that is because our data is measured in recording time and most geophysicists will work in time. Most likely the migration even is done in time and you get a X-Y-T cube. However, depth-conversion does happen, but it depends on a accurate time-depth relationship. People tend not to trust these too much. Caveat: A depth migration does not have to result in a X-Y-Z cube that you get.

Practical Advice

As a practical guide, you may want to start at the EBCDIC header. Was your data processed? Stacked? Migrated? Do you have a T-cube or Z-cube?
Familiarize yourself with the binary header and a couple trace headers. What are the extents of your data? Etc.

Machine Learning

Most machine learning is done in proprietary code. The only open source code I know of in seismic deep learning is MalenoV. However, loading a full 3D seismic into RAM will not always be possible. Loading it into the GPU RAM will seldomly be possible. This is the first place, where you are free to come up with a smart solution.

Bonus

Here is a list of Free Geophysics Software and an awesome list of open geoscience. These aren't exhaustive, but a good start.


How can odor travel be tracked Odd question, but what data would be needed to to calculate how far winds will carry a strong odor (such as the smells of a restaurant, pizza parlor or burning wood/building?

There is wind direction and wind speed. But how does one measure the strength of an odor and predict how far it will travel or how far the winds will carry it before it disappears?

The first problem to tackle is "what is an odor"?  An odor is a chemical aerosol or gas, which are small molecules suspended in the atmosphere.  To track the odors of pizza or burning wood you would first need to identify the molecules associated with the scent.  One example is α-pinene, which is the molecule that gives pine trees their scent.  Food cooking typically gives off other volatile organic compounds (VOCs) and the particular matter associated with it.  VOCs physically and chemically combine to form more types of aerosols and there can also be increases in ozone.

Meteorology, emissions sources, and atmospheric photochemistry are combined in chemical transport models (CTMs) so that the air quality can be predicted.  One example is WRF-Chem, which is used for large regions and many sources. Another example is CALPUFF, which is better suited for near-source impacts and capturing the effects of complex terrain. The reason you want a model with chemistry is that molecules can be reactive and will change as they interact with other molecules turning them into things that no longer smell like pizza or wood burning.  The reason you need a meteorological model is so that pollutants will be advected with the wind and interact with the moisture budget, solar radiation, terrain, etc.

For large-scale plumes you can simulate your molecules as being emitted at a constant rate from a point source and see how this plume evolves with time.  For smaller scale flows like a pizzeria, you may need use a model that can accommodate small scale features like buildings that will have an effect on atmospheric flows.  Lastly, you'll also need to account for other emission sources as the perceived strength of the smell is also going to depend on what else you are smelling (e.g. car exhaust) and these other aerosols may be reactive or combined with the odors you are interested in tracking.

Once you have done this you will have a time varying plume of "smell" as output from your model.  This will likely be output as a number concentration of aerosol molecules per unit volume per grid box.  To turn this into "odor strength" is probably a harder problem and one I am not familiar with.  As a first order approximation though, wherever the plume is located, so is the smell; and the higher the concentration of molecules, the stronger the odor.


Why do maps of melanoma prevalence correlate negatively with UV index, negatively with ground ozone, and positively with atmospheric ozone levels? What is the causal link behind the correlation of melanoma: negatively with UV index, negatively with ozone in the lower atmosphere, and positively with ozone in the upper atmosphere? Intuitively, melanoma would positively correlate with UV index, and negatively with upper atmospheric ozone.

Increased melanoma risk with higher latitude seems to be true on a global scale as well as locally in the US, but is reversed locally in the UK and Australia where melanoma rate negatively correlates with latitude. Could high population density and high ozone in the lower atmosphere be affecting a lower risk of melanoma?

It appears melanoma rates do not always negatively correlate with ozone in the upper atmosphere, and positively with high UV index.
It does appear that melanoma sometimes negatively correlates with population density and ozone in the lower atmosphere (caused by pollution in heavily populated areas).

In this study, Chinese individuals living in the US have a higher risk of melanoma than those in China. The map of the United States with the highest rates of skin cancer (below in blue) appears to strongly correlate with a map of ozone in the lower atmosphere (below in orange).

Positively correlating latitude with rate of melanoma (higher towards the poles)

US map from CDC in cases per 100,000

World map from Nature

Negatively correlating latitude and population density with rate of melanoma

UK

UK melanoma rate map from BBC

UK population density map. Population density seems to negatively correlate with melanoma.

Australia

Australia melanoma guidelines from Cancer.org.au stating the north has a higher risk for melanoma.

Australia population density map. Population density seems to negatively correlate with melanoma.

Negatively correlating latitude with UV index (higher towards the equator)

Positively correlating temperate zones with ozone in the upper atmosphere.

I cannot address your specific questions, but with regards to cancer, Cedric Garland has analyzed and presented similar data and attributed a lower incidence of cancer with a higher production of vitamin D at the lower latitudes as a possible reason. Mina Bissel at Berkeley labs and others have discovered that cells in isolation can lead to cancer. The other connecting link is that vitamin D promotes intercellular communications and thus may be aiding whatever process it is that leads to cancer. If you just google these names, vitamin D and cancer, you will find links to most if not all the papers.


Difference between Meteosat and Insat satellite Images I have seen many times that their are two kinds of Satellite Images shown on the websites like Skymet for India i.e.

Meteosat satellite images
Insat satellite images

I want to understand the basic difference between them.

I am here Adding 2 satellite Images(Meteosat and Insat Images Respectively) for the date of 20/02/2016 and time 8:00AM (IST) to make you understand better visually.

Thanks for your help in advance.

Meteosat:-

The Meteosat series of satellites are geostationary meteorological satellites operated by EUMETSAT under the Meteosat Transition Programme (MTP) and the Meteosat Second Generation (MSG) program.

INSAT:-

INSAT-3D is the first Indian geostationary satellite, equipped with sounder instrument that provides frequent good quality atmospheric profiles (temperature, humidity) over Indian landmass and adjoining areas.

More information is here: Two generations of active Meteosat satellites, Meteosat First Generation (MFG) and Meteosat Second Generation (MSG), providing images of the full Earth disc, and data for weather forecasts.

and here: INSAT-3D, Advanced Weather Satellite, Completes Two Years in the Orbit.


Are there any quantities defined analogically to the virtual temperature, but for other gases? The virtual temperature is a pseudo-temperature taking into account water vapour in the atmosphere in such a way, that the resulting quantity can be used with the ideal gas law and the molar mass for dry air.  Although the most significant in the troposphere, water vapour is not the only trace gas for which the concentration varies through the atmosphere.  Are there any similarly defined pseudo-temperatures, taking into account varying volume mixing ratios for other trace gases?

It is true that water is not the only variable constituent of the atmosphere, but it is capable of large variations (0-5%+) that I'm not sure other trace constituents are capable of outside of plumes from smokestacks / cars / factories / etc.  A virtual temperature for other gases would only be meaningful if their variability imparts a significant change in mass in a parcel such that it becomes important for buoyancy.

That being said, you could easily derive such a virtual temperature, as the virtual temperature is just a proxy for density changes and we can easily calculate this.

For each constituent gas, you can use the ideal gas law as

$$p_i = \rho_i R_i T$$

such that each density of gas $i$ is

$$\rho_i = \dfrac{p_i}{R_i T}$$

and then sum these with dry air ($p_d$)

$$\rho = \dfrac{p-\sum p_i}{R_d T} + {\large\sum} \dfrac{p_i}{R_i T} $$

and then solving for $p$ in terms of $\rho$, $R_d$ and collecting the rest of the terms into a variable and calling it $T_v$.

This process could be used to generically define a virtual temperature for any number of trace gases (single or multiple) as long as you know their mixing ratios with dry air.  I'm not aware of anyone using (on Earth) a virtual temp for anything other than water vapor and suspended hydrometeors (e.g. density potential temperature, $\theta_\rho$) but that certainly doesn't mean no one is.


Percentage of Oxgen left after burning all the available biomass A documentry stated that during the Permian asteroid strike the atmosphere heated up to above 400C, potentially to 600C. As this would ignite most of the biomass, including us, I wondered if this fire would consume so much atmospheric oxygen that it would kill most animal life that survived the fire. Oxygen levels would only need to fall below about 10 percent for this to happen.

Estimates of earth's total biomass vary widely, from 0.5 to 4 trillion tons C, so instead of citing a source, I'll just go with an assumption of $1\times10^{15} \text{kg C}$. Measuring biomass in carbon is a convenient segue to the next assumption: assume that all biomass burns only in $\text{CX + O}_2\,\rightarrow\,\text{CO}_2 + \text{X}$.

Given these assumptions, $1\times10^{15} \text{kg C}\cdot \frac{1 \text{mol C}}{0.012 \text{kg C}} = 8.3 \times10^{16} \text{mol C}$. To react with so many mol's $\text{C}$ we will need the same number of mols of $\text{O}_2$, at molar mass $0.032 \text{kg O}_2$, which gives us a total of $2.7\times10^{15} \text{kg O}_2$ needed.

Oxygen is 20% of the atmosphere, which means there is $5.1\times10^{18} \text{kg atm} \cdot 0.2 \frac{\text{O}_2}{\text{atm}} = 1.0 \times 10^{18} \text{kg O}_2$ available.

Since we have calculated that there are three orders of magnitude as much oxygen available as is needed to burn all biomass, I feel confident saying that global loss of oxygen due to burning biomass was not a cause of the P-Tr extinction.

Also relevant: there is nowhere near a consensus that an asteroid impact caused the P-Tr extinction. To the best of my knowledge, an asteroid strike is not the most popular theory for that specific extinction event.


How did this hole / hollow form within this rock? Can you assist me in understanding how this hollow was formed in this rock. I am told that it has to do with cementation but I believe that geological process produces rounded canonball ( sometimes ) like stones. Is this some sort of hollow ( or reverse ) cementation ? I have also been informed that it was likely formed beneath the surface when the sandstone was forming into rock and it is a completely distinct process from that which the rock has since undergone when it has been exposed to weathering on the surface.

It looks to me that there were voids in this rock when it was formed, caused by gas bubbles These voids might have become filled with sand or other friable material. Weathering eroded the side of the hollow, enlarging it and allowing any finely divided material inside it to trickle out. You should have included something to show scale, but my impression is that your rocks are about six feet tall and not very solid, therefore easily eroded. The round stones you refer to are geodes, which are hollow and usually encrusted in the inside with quartz crystals. In some parts of England they are referred to as 'potato stones', which gives you an idea of what they look like. Some recent posts on this site give you photos of them.


How are hillsides farmed? I would assume hilly land is more labor-intensive to farm than flat land, and more exhausting to humans and animals if traditional farming techniques are used.

How do farmers plant and plow on uneven terrain? And do the furrows on a hill run uphill-downhill, or “horizontally stacked” up the hill’s incline?

Edit: I see why sloped land is more conducive to other kinds of agriculture. Any idea how steep a grade has to be before farming grain on it is more trouble than it’s worth?

The way hillsides are farmed generally depends on the steepness of the hillside. Gentle slopes can be farmed the same way flat land is farmed.

Steeper slops require the hillside to be divided into terraces. The steeper the slope, the narrower the terraces.

Terracing of hillsides in farming reduces erosion because terraces reduce the flow rate of water down the hill. Furrows running down slope can easily transform into erosion gullies.

Terrace farming has been all over the world and for thousands of years. It is speculated that the Hanging Gardens of Babylon,

  may have been built on an artificial mountain with stepped terraces, such as those on a ziggurat.

Slopes in the Andes of South America were terrace mining before AD 1000.


Effects of pressure at sea level According to this answer atmospheric pressure can vary between 870 and 1070 mb.

Can you tell what (if any) effects would there be on sea level if such difference of pressure (200 mb) on two near areas of the ocean, has anything similar has ever been recorded? If there is an elevation (or depression) can you say to what difference in gravity it corresponds? How do pressure effects compare with Earth's non-homogeneous gravity which affects local sea levels?

The effect of atmospheric pressure on sea level is described as "inverted barometer" effect. The basic equation governing the effect (Wunsch & Stammer, 1997) is: $\delta_{IB}  = -{\Delta P_{atm} \over  \rho_{water}*g}$, where $\delta_{IB}$ is the change in sea level, $\Delta P_{atm}$ is the change in atmospheric pressure, and $\rho_{water}$ is the density of water.

A good example of the effect was observed by Close (1918)
 From Wunsch & Stammer, 1997.

In reality, while atmospheric pressure can vary between 870 and 1070 mb, the problem is that it might result in a change of 2m over a distance between high and low pressures that could be many hundreds of km. By comparison, the sea level gradient across the Gulf Stream is on the order of 1m/100km. The other problem is that the ocean adjusts dynamically to the differences in air pressure and the resulting sea level gradient might be smaller.

To convert pressure to force (acceleration), you can use $P=\rho g h$. The biggest differences in $g$ at the surface of Earth are around 50 mgal (50 $\mu m/s^2$) and caused by differences in latitude, altitude, and local topography and geology. The differences in gravity cause by the extra meter of water will be way smaller and can be considered negligible.

Wunsch, C., and D. Stammer (1997), Atmospheric loading and the oceanic “inverted barometer” effect, Rev. Geophys., 35(1), 79–107, doi:10.1029/96RG03037.

Close, C. (1918), The Fluctuations of Mean Sea-Level with Special Reference to Those Caused by Variations in Barometric Pressure. The Geographical Journal 52, no. 1, 51-58.


Life on Earth previous to us I've seen in several places that there seems to be an extinction cycle on Earth of approximately 27 million years. I've read this here:

http://www.dailymail.co.uk/sciencetech/article-1294372/Life-Earth-wiped-27-million-years.html

And also saw a similar explanation on Cosmos last week. Since the Earth is about 4.54 billion years old, that means there have been around 168 different extinction cycles. From what I understand, the Earth will either heat or freeze at extreme temperatures and then either cool or warm until water and life is a possibility again.

Given that this is correct (and definitely correct if I'm wrong, I'm eager to learn!), what are the chances there was a full civilization like ours that got completely wiped out in a different extinction cycle than ours? Is it possible or are there other factors in the history of our planet that would have prevented life from flourishing to the point that we are in now? I do understand that the factors of creating humans exactly like us are pretty drastically low but I suppose I'm referring to 'civilization' as intelligent life.

And a second part to the question, I know there are fossil records in the different layers of sedimentary rock but would there ever have possibly been an extinction event that ruined the Earth so drastically that it destroyed fossils and rocks (i.e. records of the past)? I've read that the oldest fossil found was 3.5 billion years old but it's not conclusive. Do we have a vast record of fossils and life that is billions of years old?

You need to be very wary of anything written in the non-scientific media about science. The media loves woo and controversy because those are the things that garners readers, and that in turn garners advertising revenue.

By way of analogy, suppose as near-adult in gym class someone said "My gym shoes smell bad. Bad! Awfully bad!" Someone else would inevitably take a sniff. If it was bad, really, really bad, he would say so, while gagging. Someone else would say "That bad? Are you sure? Pass it over." That shoe would have quickly been passed around the locker room if it truly did smell worse than death. (Apologies if you are female; females don't do stupid stuff like this.)

The non-scientific media love scientific articles that smell, particularly those articles that smell extremely bad. The media falls under the compulsion of passing these articles around. Good, solid journalism is sorely lacking nowadays. It's much easier to copy someone else's writing than it is to investigate. It's not plagiarism if the original source receives acknowledgement and a fee. You can typically trace those dubious reports that are all over the internet to a single source.

So what's the source of this 27 million year recurring extinction event figure? It's two men who keep peddling this conjecture every other year or so. Here's the article that caused this imbroglio:

A. Melott and R. Bambach, "Nemesis reconsidered," Monthly Notices of the Royal Astronomical Society: Letters, 407:1 99,102 (2010).

Rather than looking to the non-scientific media, it is much better to look to the scientific community and see how much credence they have given to this conjecture. The answer is essentially none. That article has received a grand total of seven (CrossRef), maybe nine (Web of Science) citations in the four years it has been in print. The vast majority of those are either self citations or citations by other fringe scientists who are pushing their own brand of woo. This hypothesis is viewed rather lightly by the scientific community.

Moral of the story: Don't believe everything you read on the internet.

Let's suppose your conjecture is true. What signs would we see of a prior civilization? If the civilization was sufficiently advanced we would see a depletion of resources. If that prior civilization had advanced to the stage of sending stuff into space, we wouldn't see iron where we see it now. We see iron in very, very old banded iron deposits. We don't see any anomalous iron deposits in what would have been cities millions and millions of years ago.

The same goes for coal and oil. Our first discoveries of oil and coil was stuff easily accessible from the surface. Easy pickings. Those easy pickings would not exist if some prior civilization had advanced to the Elizabethan stage, perhaps even Roman level.

What if some calamity had wiped out humanity 2000 years ago? 10,000 years ago? What would a future civilization see millions of years from now? That's a better question. The answer is not much. That future civilization might well not see anything at all. Archaeologists have found fossil records of our ancestors, but that's because we humans are driven to look for those ancestors. A future civilization might not find any fossil humanoids that exhibited a tripling in brain size in just a few million years.

That of course is assuming that intelligent life arose before humanity. That too is dubious. Evolution shows a more or less steady progression in brain size. Dinosaurs might not have been as dumb as people thought 50 years ago, but they were still pretty dumb. Their brains were reptilian. Science fiction writers love the idea of intelligent dinosaurs. That's a rather non-standard view amongst scientists.


Is there a way to calculate the ground and 10m temperature from standard 2m temperature measurements? I am wondering if it is possible at all to calculate the ground temperature and air temperature at 10m above ground from 2m measurements, or at least using data that a standard weather station provides.

I am aware it is an oversimplification, but I cannot seem to find any resources concerning the matter. Any help would be greatly appreciated!

Edit 2017/01/11:

Thank you for your comments, so here is the reason why we are interested in this:

We have noticed that there are often large differences in air temperature between 2m and 10m height, often of 4° to 5°C. I wanted to know if anyone else was interested in this, or are there any models out there which can be used to calculate temperatures at different heights, so a comparison between modelled and real values can be made.

Why is this interesting at all?

It would be great to have a way to know if in a certain area the temperature will not go below 0°C if we have measurements of temperature, humidity and wind at 2m. But, I presume in these days of cheap temperatures sensors and Arduinos, one can always stick a sensor anywere...

There is an equation for a model of vertical variation in air temperature

It unifies concepts from a whole range of sciences. You will need to know the sensible heat flux H from the respective surface (which can be calculated as a result of the energy balance of where you are). Further you can calculate the volumetric specific heat capacity pc(p) of air, which is approximately 1.2 kJ/(m³ K) and relate it to the shear velocity or friction velocity of your surface. This is finally related to the logarithmic measure of the term (z-d)/zH where z is the height of which you want to know the temperature and d is the zero plane displacement. zH finally is the Roughness of your surface.

This has to do with the fact, that heat transfer over surfaces usually is turbulent and not just determined by vertical convection. I recommend you to take a look at Campbell & Norman "An Introduction to Environmental Biophysics" (1998). It's a very comprehensive book and treats all the mentioned concepts.

I'm working on a basic computation of this at the moment but it still needs a little time. Once it's done, I'd be very excited to see if it actually is able to model the measured temperatures. I'll keep you updated on how it's going.


How to calculate flow duration curve for a set of 12 year data? Given, discharge data alone for each month in each year, is it possible to calculate the flow duration curve? Some of the discharge values in some months were found to be 0. Do we need to consider those values?

Spreadsheets work well for this.

You have 12×12 observations so use 144+1 = 145 as the number of observations for calculating your probabilities.

Put your discharge data in a column and sort from highest to lowest. Put a column of Rankings next to it and number from 1 up to your maximum (1 to 144). Put a column next to that and calculate your probability of exceeding each discharge value:

P = Ranking×100/145

(P as a percent)

Graph discharge vs. P.

You need to consider your 0 discharge months in determining the number of periods but you don't need to calculate P for them.  That's handy if you don't want errors in plotting log discharge vs. P.


Causes and concentration of red rain of Kerala The red rain phenomenon in Kerala, India has been reported several times in history (1896, 2001, 2012). The color of the rain seems to be associated with the presence of airborne spores of the algae Trentepohlia annulata. My questions are:

What concentrations of spores are necessary for the rain to achieve this color?
What physical and biological mechanisms are involved to achieve those concentrations in suspension?

Despite the obvious red colour Trentepohlia annulata and numerous related species are blue-green algae. The red colouring comes from beta caroteine and related natural pigments. There are very many such common pigments in nature, comprising scores if not hundreds of compounds, ranging in colour from yellow through orange, red and purple, eg. from lichens on wood bark, carrots, saffron, beetroot, and certain bird feathers/beaks - to name but a few sources. The red colourant masks the natural greenish hue of the original organism. It is a strong colouring compound which is why beta-caroteine and its derivatives are sometimes used in food colouring.

As to the concentration of algal spores, this is difficult to determine because the colour intensity is a function of the pH, exact chemical species of pigment, biological viability of the spores, and presence/absence of co-variable interacting ions in the water. As a very rough guide I would estimate that the concentration of pigment (not the concentration of spores) is likely to be in the order of 20 to 200 mg/l. For a bit of fun, you could get some beta-carotein-based food colourant and experiment on concentration and colour vs. pH.

Trentepohlia annulata and related algal species are pretty much ubiquitous in wet tropical and subtropical environments, but they don't like cold weather. The red colour in your photograph is extraordinary and very unusual. I would assume that conditions of nutrient availability, pH and temperature would have to be 'just right'.

My last comment is pure conjecture on my part - and I may be way off beam here - but maybe the intense red colour could be brought on by the physics of raindrop formation. If very moist warm air, rich in T.a algal cells was rapidly lofted in a tropical convection cell, the sudden cooling could kill off the algal cells, thereby rupturing the cell membranes, and triggering catastrophic release into solution of carotein-related pigment into resulting raindrops, which would normally pass unnoticed. Further concentration could occur by evaporative reduction of raindrop volume, especially if most of the rainfall dissipated into the atmosphere as so-called 'occult rainfall'.


Could the LA County Museum of Art fall into the LaBrea Tar pit during an earthquake? LACMA (the Los Angeles County Museum of Art) is built right next to the famous La Brea Tar Pits and that keeps me up at night†.

Question: What is the subsurface structure like adjacent to the Lake Pit? I'm wondering if the LA County Museum of Art and other buildings near the Lake Pit could actually fall in some day. Is the museum built on bedrock and the tar pit next to it is just a small hole in it, or if "the big one" comes (major earthquake) could soil shift and the art museum end up submersed in tar?

†no it doesn't, drinking too much coffee keeps me up at night.

Google Maps of La Brea Tar Pit and LACMA

Ground truth: LA/Hollywood, so plastic dinosaur...

The two geological faults that may be responsible of large earthquake in proximity of the museum are:

Hollywood fault;
Santa Monica fault (actually many branches, but they all go together as Santa Monica fault).

The museum seems to be enough far away from the fault trace (the surface expression of the fault itself), so it is unlikely that there will be a major shift in the soil.

However, the museum may sink in the soil due to the earthquake mobilizing the soil, especially if composed of loose sand.

The phenomena responsible of the museum "falling in the soil during an earthquake" is liquefaction. The geological service of California provides you an interactive map to check if a certain address may be under liquefaction hazard https://www.americangeosciences.org/critical-issues/maps/interactive-map-california-earthquake-hazard-zones and ...

at the moment the interactive map is not accesible to me. Sorry :)

If liquefaction is possible, either the tar may quickly move and sputter on/in the museum, or the museum may sink in and later tar may infiltrate slowly in the building.


Is it feasible to use depleted oil wells for geothermal production? There is an oil field outside my hometown. I wonder if it is feasible to use the same oil wells for geothermal production after oil production rate drops below profitable point.

In most cases, probably not.

Oil could be considered a metamorphic mineral, formed by "gentle" heating. That is gently on a geological scale - still enough to burn your hands!

Geothermal systems work most efficiently with a large temperature difference (Third Law of Thermodynamics). As soon as the temperatures increase enough to be interesting from a geothermal perspective, you are quickly losing ("overcooking") the oil on a geological timescale.

Therefore most oil fields have had the heat applied in the past and it has since been removed.
However this does not discount the situation where an oil field is still technically "being made" and the hydrocarbons are still being heated, and we just happened to drill it at just the right time. Hence the "in most cases": You might find the odd field where it is practical.

An old field, especially gas ones, could be used for carbon sequestration though. The field has stored methane for 10s if not 100s million years, why not the heavier CO2 instead?


Where does the symmetry of cloudy bands come from? Reading Meteorology Fundamentals by Sylvie Malardel, it says:

  We observe a symmetry of the cloudy bands with respect to the rotation axis of Earth
  and between Northern Hemisphere and Southern Hemisphere.

What is the origin of those symmetries?

The symmetry is caused by the the spherical nature of the Earth, the typical weather features that form at certain latitudes, the formation of circulation cells at specific latitude zones, and the effect of the Coriolis force on the weather systems and cloud bands within them.

The latitude (and hence temperature from insolation) controls to a certain extent the broad scale atmospheric circulations. In the zone just North and South of the Equator, you find the trade winds converging towards the Equator from an easterly direction. Their direction is broadly determined by the Coriolis effect. (I think you can just make them out in the photo).

In the mid-latitudes (30-60 degrees) you frequently find extratropical cyclones in both hemispheres. Their formation is beyond the scope of this brief answer (see Cyclogenesis), but they are effectively a result of consistent suitable conditions to at those specific latitudes for cyclones to form. They are noticeable in the image as being quite spiral shaped.

The symmetry of cyclonic features is perhaps most enhanced by the Coriolis effect, caused by the rotation of the Earth deflecting moving objects (the weather systems including the clouds) in the atmosphere. This (in combination with the pressure gradient force) causes the spiral-shaped features at the mid-latitudes that you can see in the image. The effect works in opposite directions in respective hemispheres, so in the North, the cloudy bands appear to be turned anticlockwise, and in the South they appear clockwise, enhancing the overall symmetries present.

This is one of my favourite widgets for seeing this:

http://earth.nullschool.net/#current/wind/surface/level/orthographic=199.59,9.44,293


Is Desert Sandstone a chemical sedimentary rock? I gather that chemical sedimentary rocks are formed when minerals in solution are supersaturated and therefore they precipitate out.

I also understand that desert sandstone is formed as Iron Oxide rich water evaporates leaving a hematite cement.

Does this mean Desert Sandstone is a chemical sedimentary rocks?

No, it's not.

The overwhelming majority of the material in the rock is clastic, not chemical. Chemical sedimentary rocks are rocks where (almost) all of the material was precipitated, such as travertine, evaporites, etc.

Cementation is a chemical process. As a clastic sedimentary rock has to be cemented somehow, otherwise it would be a sediment rather than a rock, all clastic sedimentary rocks have undergone some chemical process. This does not mean that they are chemical though.

As diagenesis progresses and the rock undergoes more chemical changes it may become a diagenetic clastic sedimentary rock of even a metamorphic one, but never a chemical sedimentary rock. This implies that most, if not all, of its initial mass precipitated out of solution.


At what latitude/longitude was Cornwall, England 75 million years ago? Approaching the end of the Cretaceous period, where on the planet (latitude and longitude) was Cornwall, England? .. Approximately.

The rocks that make up Britain have been slowly drifting north over geologic time.  About 700 million  years ago it was near the South Pole!

I paused this Youtube video at 75 mya, held the end of a toothpick over Cornwall, then played it to the end keeping the toothpick steady over that point, under which the approximate location of Bilbao, Spain eventually slid itself. Bilbao is at 43°15′25″N according to Wikipedia.

So now, think of how longitude is defined: Relative to the meridian through Greenwich. A cursory glance at the video I linked to shows the rocks that make up Great Britain have moved as a unit and haven't rotated appreciably over the last 75 million years. So the longitudes associated with Cornwall haven't changed much in that time.


Adiabatic lapse rate I'm having trouble with the difference between saturated and unsaturated adiabatic lapse rates.

I know the unsaturated adiabatic lapse rate is approximately 5.4°F/1000ft (9.8 °C/1000 metre), in which a "dry" parcel of air cools at that rate. The unsaturated adiabatic lapse rate depends on what?

Why is the unsaturated adiabatic lapse rate lower than the saturated? From searching, I found that the unsaturated adiabatic lapse rate is lower because the air parcel releases its latent heat, which causes the air parcel to cool more slowly, but I don't seem to get it. When a "dry" parcel of air is cooling adiabatically, are we assuming 0% moisture?

Let's start with the simplest fact.  With nothing else going on, air in our atmosphere will always be cooled at 5.4°F/1000ft (or the more widely used 9.8°C/km), due to it expanding in size (often times we'll throw a negative sign: -5.4°F/1000ft... this is just to emphasize that these lapse rates are about the air COOLING).  Every bit of the rising air cools at that rate (the oxygen, the nitrogen, even any water vapor in the air).  All of it will cool at 5.4°F/1000ft.  All rising air always expands at this same rate.

However sometimes there is a second complicating factor: the rising air may cool to the point where it is holding its maximum quantity of water vapor (because when colder, air cannot hold as much water vapor).

When it reaches this point, it is saturated, and any more cooling/rising will force some of its water vapor to condense instead into liquid droplets.  For this gaseous water vapor to become a liquid, its particles must expel quite a lot of energy.  And that energy gets released into the air.

So once air hits this saturation point, though its expansion continues to have a -5.4°F/1000ft impact on the temperature, it also has a second factor, that released phase change energy, warming the air some.  The result is that saturated air doesn't cool as fast.

Whenever air isn't saturated, it cools at the 5.4°F/1000ft (9.8°C/km).  We call this the dry adiabatic lapse rate because nothing else is altering the process.  We aren't assuming 0% moisture.  It doesn't matter, as long as it's not 100% moisture.  Water vapor cools just like every other molecule unless saturated.  The first 6 pages of these notes go into intimate detail for why the value is 9.8°C/km, but basically it depends only on the values for gravity and the specific heat capacity of water, plus any error in the hydrostatic approximation... all of which are minuscule for large air masses in the troposphere.  For all intents and purposes, the dry (unsaturated) adiabatic lapse rate on Earth depends on nothing, it is always 5.4°F/1000ft (9.8°C/km)
Then when air is saturated, because the condensation process hinders the cooldown by adding its energy, we call it the moist adiabatic lapse rate to distinguish it.  Picture moist as having an image of water DROPS, which you only get when saturated, due to condensation.  Moist and dry both have some water vapor.  But only moist has water droplets.  The moist adiabatic lapse rate has a smaller value because it is cooling LESS overall (due to the warming impact from the latent heat release).  But it is still cooling, just less.  The moist adiabatic lapse rate varies depending on how much water is actually released (which is based upon the amount of water held, or consequently, the temperature).  If you really wish to dig into the fine details, this AMS link gives the formula.  But generally the moist adiabatic lapse rate is around 5-7°C/km, or 2.5-4.0°F/1000ft, in the low-levels of the atmosphere.


How are sand blocks formed? My son asked me at the beach how are "sand stones" formed. These are the solid (but fragile) sand conglomerates which you can hold in your hand and which crumble to sand once pressed.

I tried some hand waving about "cement-like" formations and how these grains of sands are held together because they dried "in a specific way" but he was not impressed and neither was I.

Is there a name for these structures so that I can look up how they are formed?

There are two "normal" mechanisms for this effect:

Clay bonding, the beach sand contains a small fraction of clay particles which bond to the grain surfaces and hold the sand together when dry, this is normally the mechanism where the beach is backed by mudstone cliffs or quite close to river mouths supplying fine sediment to the beach.

Evaporite Cementation this is the more widespread and common process then what you are seeing is a small scale, and often abortive/short-lived formation of "Beachrock" this is the most likely explanation and the cause will probably be a rainwater/seawater interaction on the surface of the beach where it is still wet with seawater but no longer wave-washed as the tide recedes.


Marine and freshwater geochemistry As rivers flow into the sea, rivers contain a high concentration of calcium and carbonates, and a low concentration of sodium and chlorine, and for marine water it is vice versa. How come?

The oceans are not saturated in sodium or chlorine. In fact, the chemical makeup of the oceans has remained fairly constant for hundreds of millions of years. Yet rivers and other sources continually bring sodium, chlorine, and other dissolved elements and compounds to the oceans. This means some processes must exist that remove constituent elements at more or less the same rate that the world's rivers and other sources supply these constituents.

It is true that the Earth's rivers bring substantially more calcium and carbonate ions to the oceans than they bring sodium and chlorine ions. Dissolved carbon dioxide from the atmosphere provides another source of carbonate ions. Yet the oceans are indeed substantially depleted of calcium and carbonate compared to the supply from rivers. So why is this?

The oceans are substantially saltier than are the rivers that supply the oceans. This is primarily a result of evaporation. Even with that, sodium and chlorine are but a fraction of their saturation levels in the world's oceans. This is not the case for calcium and carbonate. Carbonates in general have a low saturation level, and amongst common cations, calcium carbonate has a very low saturation level. Calcium carbonate is typically at or near the saturation level in the oceans, and oftentimes above it, particularly near the surface. This makes it very easy for calcium carbonate to come out of solution.

Because calcium and carbonate are at or above the saturation level, just about anything can cause calcium carbonate to form. The key "just about anything" process that causes calcium and carbonate to come out of solution is life.

This means that calcium and carbonate have a rather low residence time in the oceans. The processes that remove sodium and chlorine are much, much slower. The slowness by which sodium and chlorine are removed versus the rapidity by which calcium and carbonate are removed are why the oceans are "upside down" compared to rivers with regard to calcium, carbonate, sodium, and chlorine.


download NASA Earth Exchange Global Daily Downscaled Projections for single lat lon I have a lat lon - 23.14, 83.14 and I need to download the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) data from the below website only for this lat lon.

https://dataserver.nccs.nasa.gov/thredds/catalog/bypass/NEX-GDDP/catalog.html

Is there a tool/website/script that I can use to download the data 2040 - 2060 ? Would someone be willing to show me how to do this?

I did download and process some of the NEX files a year or so ago. Maybe there is a more efficient way to do that now, but what I used is this R script to download the files:

library(RCurl)
opts = curlOptions(proxy='http://10.xxx.xxx.xx:xxxx', userpwd = "you needed NEXGDDPusr:pswd at that time", netrc = TRUE)

var = c("pr","tasmax","tasmin") ##here the variables
rcp = c("rcp45", "rcp85") ##here the scenarios
mod= c("CCSM4", "GFDL-CM3", "IPSL-CM5A-MR", "MIROC5",  "inmcm4")##here the climate models
year=c(seq(2040,2060,1)) # here the time period

for (v in var) {
  for (r in rcp) {
    url<- paste0( 'http://nasanex.s3.amazonaws.com/NEX-GDDP/BCSD/', r, '/day/atmos/', v, '/r1i1p1/v1.0/', sep='') ##here the url (please, note this might be different now)
    for (m in mod) {
      for (y in year) {
        nfile<- paste0(v,'_day_BCSD_',r,"_r1i1p1_",m,'_',y,'.nc', sep='')
        url1<- paste0(url,nfile, sep='')
        destfile<-paste0('D:/NASA_NEX/',r,'/',v,'/',nfile, sep='') ##destination folder
        bin <- getBinaryURL(url1, .opts = opts)
        writeBin(bin, destfile)
        Sys.sleep(1)
        gc()
      }}}}

This, however downloads the global files.

The second stage would be to extract the data for the point you need. For doing this in R you can use something like this. In alternative you can use CDO.


In winter, is pond water warmer with or without a fountain? I have goldfish I know that goldfish can hibernate but I'd like to keep the water warmer for them.  Is moving water colder or warmer than still water?  The water shoots out of "pipes" about 3" above the water's surface.

Thank you for your comments, I have disconnected the water pumps that shoots water into the air.

In nature, fish survive in ponds due to a lack of turnabout of water.

(Fresh) Water has its highest density at 4°C, meaning both warmer and colder water float on top of 4°C water. Wind may push surface water to the bottom, slightly lowering the temperature at the bottom of the pond. Still, once the surface starts to freeze, this proccess is discontinued, creating a temperature-gradient with the relatively warm 4°C water at the bottom - until spring. Thus fish don't freeze to death.

Meaning, leaving your fountain running is a rather bad idea.

As to the issue of possible lack of  oxygen - I can't answer that reliably.


Why does the meridional overturning circulation take the convoluted path that it takes? Why does it take the very weird loop that it takes in the Pacific Ocean? And also in the Indian ocean too?

The diagram presented in the question is a very simplified version of the meridional overturning circulation. It is overly simplistic and generally creates very large misunderstandings.

A good reference to the evolution of the Meridional Overturning Circulation diagrams is the work by Richardson (2008). Just in case you don't have access to Progress in Oceanography, you can click here and see if that works.

The diagram that I find more useful and, while a simplification, still rather realistic is the one by Schmitz (1996).

Now let's answer the question about the "weird loop". We need to realize that, in the diagram presented, the blue arrows represent flow of deep water (denser water, usually colder), while the red arrows represent surface water flow (lighter water, usually warmer). The loops in the Pacific and Indian ocean represent a transition from cold water into warmer water usually through mixing. The exact location of the mixing and upward vertical flow (upwelling) does not occur in the areas represented by the loop in the diagram, but rather in several other locations in the Pacific and Indian Ocean (for instance, upwelling in the California Current System, mixing in the Indonesian Throughflow).


Is fracking likely to produce earthquakes? Post Christchurch-2011 earthquake, there was much concern that fracking in the surrounding areas might lead to further quakes, as was rumoured to have happened elsewhere in the world.

Is there evidence that fundamentally validates or discredits this?

It's not too too likely, but it can happen. A few earthquakes have either been attributed to fracking, or the wastewater produced from fracking.

According to the USGS (for more information, visit that page):

  Many questions have been raised about whether hydraulic fracturing —
  commonly known as “fracking”— is responsible for the recent increase
  of earthquakes. USGS’s studies suggest that the actual hydraulic
  fracturing process is only very rarely the direct cause of felt
  earthquakes. While hydraulic fracturing works by making thousands of
  extremely small “microearthquakes,” they are, with just a few
  exceptions, too small to be felt; none have been large enough to cause
  structural damage. As noted previously, underground disposal of
  wastewater co-produced with oil and gas, enabled by hydraulic
  fracturing operations, has been linked to induced earthquakes.

So, indeed, the disposal of wastewater has been linked to earthquakes.

This study in Geology also came to the same conclusion that the wastewater of fracking caused earthquakes.

An additional study produced by Ohio geologists concluded that a few small earthquakes were due to fracking. I do wonder exactly what they concluded, but the news story doesn't say. It does say this, but it doesn't say exact what this study was, either:

  A U.S. government-funded report released in 2012 found that two worldwide instances of shaking can be attributed to actual extraction of oil and gas, as opposed to wastewater disposal in the ground — a magnitude-2.8 quake in Oklahoma and a magnitude-2.3 quake in England. Both were in 2011.


Does the strength of Earth's magnetic field influence its climate? The strength and orientation of Earth's magnetic field varies with time.

Does this variation of the magnetic field have any influence upon climate? For example, is there any correlation between ice ages and strengthening or weakening or orientation of the field?

There is no significant geomagnetic influence on the cycle of glacials and interglacials. I think the easiest way to determine this is to consider geomagnetic reversals. A reversal obviously involves the largest possible change in the direction of the magnetic field (a full 180°). It also involves some of the largest changes in field intensity, because during a reversal the field intensity drops to a small fraction of its usual value before regrowing to ‘normal’ levels (e.g. Raisbeck et al., 1985). So, if we're expecting geomagnetic field behaviour to have any influence on climate, we'd expect the most obvious effects to appear at reversals.

We can look for this effect by comparing a δ18O record (which gives a proxy for global temperature and ice volume) with a record of magnetic reversals. Here's a figure of the LR04 stack from Lisiecki & Raymo (2005), showing those two records for the past ~5 Myr:

As you can see, nothing spectacular or even noticeable happens at the reversals (the black/white boundaries along the bottom of the plot). They don't seem to correspond to any particular point in the glacial/interglacial cycle.

Of course, it's likely that geomagnetic field strength has some influence on climate, and that these effects are simply swamped by other influences on the spatial and temporal scales we're looking at here. The first possible effect that came to my mind was the geomagnetic field's influence on the amount of incoming cosmic rays, which in turn has an effect on cloud formation. And sure enough, it turns out that Vieira and da Silva (2006) have found such an effect. But I suspect that once you start looking at >10kyr timescales and global signals, such effects get averaged out.

Lisiecki, L. E., & Raymo, M. E. (2005). A Pliocene‐Pleistocene stack of 57 globally distributed benthic δ18O records. Paleoceanography, 20(1).
Raisbeck, G. M., Yiou, F., Bourles, D., & Kent, D. V. (1985). Evidence for an increase in cosmogenic 10Be during a geomagnetic reversal. Nature, 315(6017), 315-317.
Vieira, L. E. A., & da Silva, L. A. (2006). Geomagnetic modulation of clouds effects in the Southern Hemisphere Magnetic Anomaly through lower atmosphere cosmic ray effects. Geophysical research letters, 33(14).


Chicxulub Asteroid Remains? Do scientists know if the Chicxulub asteroid disintegrated completely upon impact or if any (large or small) chunks of the asteroid remained intact? If it is possible that a significant fragment of the asteroid survived could it have been preserved until today somehow (i.e. can it be found)?

There are micro-tectites galore, strewn over thousands of square kilometres. But remains of the actual bolide? Hard to say, because the impact crater is now buried under 600 metres of sediment. Earlier this year the joint IODP-ICDP drilling program drilled to a depth of 1300 metres. As far as I know, their findings are not published yet.


What model best describes the alignment of the Sun and Moon during a lunar eclipse? In the first image the penumbra shadow area is rather small and would match the time length of a lunar eclipse, However, the light source/Sun is far too distant to match the Sun in scale to the Earth in the present solar system model. The second image has the light source/Sun scaled more to the solar system model but the penumbra shadow is much to wide.

It's difficult but not impossible to model the Earth, Moon and Sun, but the scale is a bit tricky to get right if you try to build or draw it.

If we call the Moon's diameter = 1 moon unit, then, Earth's diameter is about 4 moon units.   Distance between Earth and Moon, about 110 units, Sun's diameter, about 400 units, and the big one, the Sun's distance to the earth, about 43,000 moon diameter units.

So if the Moon is big enough to see, but still very small, say 1 mm, then the sun needs to be 40 cm in diameter (about 33% larger than a basketball) and 43 meters away.


Unrealistic solution for advection-diffusion-reaction PDE with heterogeneous porous media About the code: I have a code which simulates concentration from advection-diffusion-reaction PDE in 2D space (X,Y) with time. The solution is obtained using fully implicit finite-difference method and includes the capability to simulate a media with spatially varying permeability and reaction constant (through upwinding by harmonic mean). I have been able to test the code for homogeneous media and it works fine. It's a solution for the following equation:
$$\begin{align}
\frac{\partial C}{\partial t} + \nabla.\left(v  C - D\nabla{C} \right)=  \alpha C
\end{align}$$

Issue: The code gives realistic solution for a medium with uniform layers of permeability as shown below. However, once the medium starts to get more heterogeneous it starts to throw unrealistic results (i.e. negative concentration and large fluctuations with time). Any guesses why I am getting unrealistic results for heterogeneous media (with values in the similar range as uniform layered media)?

UPDATE: I think I have figured the issue for getting negative values and sharp fluctuations in concentration. I think the problem is not with the numerical model, but with the physical values. Even though I was already taking realistic parameter values for which I was getting unrealistic concentration, I had to further adjust them (decrease the convection velocity) to get realistic results

It's not clear exactly what is being modelled here, but it seems to me that there are two ways in which the concentration can 'go negative'. Firstly, the rate of change of concentration can be massive, in which case see what happens when modelling with much smaller time steps. Or, the diffusion term substantially exceeds the advection term, which is physically unlikely. However, you are modelling a large (more than 10-fold) anisotropy, in which almost all the flow will be in the x, horizontal direction - it is almost a one-dimensional problem in fact. So how can the advection be less than the diffusion? In the case of a constant concentration source, such as a saline water body, the negative results don't make sense, in which case the calculations have gone unstable, probably from using too large a time step. In the case of a pulsed source, as the concentration peak passes (along the x direction), the advected concentration rises and falls, such that the lateral (y axis) diffusion increases, then decreases, i.e. the concentration gradient changes direction, becoming negative.

As if this wasn't hard enough, in real life applications the 'sink' terms probably far exceed any back-diffusive effects.


If the earth's surface is negatively charged, why aren't objects close to the surface polarized? A lot of misinformation about earth and it being a sink is spread everywhere, including what I was taught in school, I hope you well-informed folk can help me out.
A sort of side-note, if anyone has a book recommendation explaining these kinds of concepts and everything related to them, please do let me know. It seems as if most books on electrodynamics don't really examine these assumptions we usually make. Examples: why earth is a 'sink' for electrons?; how, when grounding houses -- does a ground connection act as a wire which connects back to the same circuit, even when it's a single wire (taken from Ground wikipedia page) connected to ground?
And the list goes on.
To quote my last question, I found it here: https://electronics.stackexchange.com/a/148684
Quote:
"Current never ever ever ever flows to earth. It only ever flows through earth. Earth is just another wire - albeit a planet sized one. Electrons have to flow from one side of the power source back to the other. They can never flow out and never return." – Majenko
Moving on, the original question:
Why aren't objects close to the surface polarized?
We know that by static inductance, when you rub two of the right materials together, one becomes negatively charged, and the other positively charged. Let's take one and get a neutrally charged material next to it, bringing it closer, we can see that it becomes polarized.
I've read that earth's surface is negatively charged, -500,000 coulombs, to be sure. So bringing a neutrally charged object close to it would make it polarized, is what I think is logical.
So why is my conclusion wrong, if it is wrong (doesn't seem right)? And why is it that earth is charged negatively?

Think of the electric current as a fluid, and a battery or some other source of current as a pump. Change the earth for the ocean.
I don't know about the negatively charged earth's surface, but those -500,000 coulombs are an absolute measure of charge. That charge is distributed over some surface, and the earth's surface is pretty big.


Do ice crystals form in running super-cold water? Crystals of sugar form in hot saturated sugar solution as it cools down, due to excess sugar molecules not fitting in the solution and precipitating as crystals.

In a similar situation, if we have a region where temperatures are well below zero, still water should freeze. But in rivers, water doesn't freeze, because it's flowing. Do ice crystals form in such super-cold water?

(P.S. If you know any applicable tags, please add them.)

A snippet from the linked question:

Fred says:
Also, while water is flowing its potential energy is constantly being converted to heat energy that resists freezing on the molecular level and subsequent crystallization.
For flowing water to freeze, the temperature would have to be exceptionally cold


How did Mount Evans become a mountain? Multiple websites state that the mountain, which is in Colorado, was formed by an intrusion of magma about 1.4 billion years ago, forming a batholith.
On the other hand, the rocky mountains are said to have been formed only recently, perhaps 80 to 50 million years ago.
What then were the major forces that shaped the mountain? Did the batholith 1.4 billion years ago start thrusting the ground upward like a dome mountain, or did it remain flush underground until tectonic plate movement formed all of the rocky mountains?

Just to elaborate on David Hammen's correct comment:

The granite is old. The mountain is fairly young. There is no
contradiction

Mountain belts like the Rockies are built by tectonic forces. Two plate collide, and mountains rise in between. The material that makes up the mountain does not have to form during the collision (although it sometime does).
A "batholith" is just a collection of many granite intrusions, which are mostly underground. They do not have to be mountainous. In most cases they are covered by sedimentary rocks and you don't even know they're there. They only become mountains when you "fold" them. When you fold a piece of paper and it wrinkles, you have to separate the formation of the wrinkles (which happened now) from the manufacturing of the paper (which was in a paper factory, in the past).


Coriolis effect discrepancy. How to deduce the direction of the effect? From what I understand (please correct me if I'm wrong), the Earth rotates counterclockwise as viewed from the north pole. That means from the perspective of the equator to the north pole, it is rotating clockwise. Hence, if I shoot a projectile towards the north pole from the equator, it should move leftwards likewise if I throw a ball towards the person in front of me in a clockwise-rotating turntable. But, in my textbook and Wikipedia it says that it would go rightwards. Where did I get it wrong?

That means from the perspective of the equator to the north pole, it is rotating clockwise

That's the part you got wrong.
As seen from the Equator (as any other point on the Earth), the North pole is not rotating. The rotation only shows up in an external frame of reference. And is actually using an internal frame of reference (like an observer on the equator) what gives rise to the Coriolis force, that is not a real force but just the inertia seen from a rotating frame of reference.

From the Equator, the North pole is in a fix position, as well as the celestial north pole, that is fix to the Equatorial horizon due north. But the starts and the Sun moves around it from East to West, which is COUNTERCLOCKWISE. That's is because the observer is moving Eastwards.

Coriolis is easier to understood if you imagine that any point on the Earth's surface (or the atmosphere) north of the Equator, have to complete a smaller circle around the Earth axis every 24 hours. Therefore, those points are moving Eastwards at a slower speed than the ones at the equator. Hence, if you shoot a projectile to the North, it will have an excess Eastwards velocity relative to the ground under it, so it will tend to go Eastwards. Which will apear like it is turning rightwards.
If the projectile is flying south from the Equator, Eastwards will mean leftwards.

This schematics from Facts About All will help in an example:

Let's imagine you are at at the monument "La Mitad del Mundo" right on the Equatorial line on Ecuador. And you shoot a projectile straight North to Raleigh, North Carolina, 3,960 km North of "La Mitad  del Mundo".

Let's say your canon shoots a frictionless projectile at speed of 1,000 km/h. Then the projectile had a Northwards speed of 1,000 km/h, and an Eastward speed of 1,666 km/h which is the speed the canon at Ecuador have in order to go around the earth center every 24 hours.

Now, in 3.96 hours, the projectile would have reached the latitude of Raleigh, but in the same amount of time the eastward component of its speed took it 6,600 km to the East. However, the eastward velocity of Raleigh is only 1356 km/h

That is because at latitude 35.7° the distance to the Earth rotation axis is only 5,179 km (in contrast with 6,378 km at the equator), therefore, the distance it have to travel around it every 24 hours is only 32,540 km (in contrast to 40,000) requiring a speed of just 1356 km/h.

That means that, while the projectile wast traveling, Raleigh only moved 5,369 km eastwards, 1,231 km less than the projectile, with the consequence that the projectile ended up, 1,231 km to the East of Raleigh (The right as seen from "La Mitad del Mundo"), catastrophically missing the target, and falling in the Atlantic ocean somewhere north of Bermuda.

This excess eastward velocity visualization of Coriolis, seemingly falls apart when considering a projectile shoot due East or West. But it would still be deflected to the right (in the northern hemisphere). An explanation in such case can be found in this answer, however that answer is not as clear as I would like, as it just ignores the vertical effect, also known as Eötvös effect, which is important to make sense of the deflection of a projectile traveling East/West. In short, the increased/decreased velocity of a projectile moving East/West, increase/decrease the centrifugal force, so it moves away/towards from Earth's axis of rotation. This means "moves up" at the equator, and move south/north and up (in different proportions) north of the equator. The rightwards deflection is considered part of the Coriolis effect, while the upwards deflection is the Eötvös effect.


Are there any geological periods found on top of each other that have dinosaurs of that period with in them? In diagrams, It is common to depict geological periods to be directly on top of each other with fossils of that period within them. When looking for evidence of this, I have only found examples of trilobites and shells. However it is common to see this sort of ordering depicted with dinosaurs in them http://www.globalchange.umich.edu/globalchange1/current/lectures/complex_life/fossil_record.html

In high school my teacher said that at the grand canyon we find no fossils at the bottom, further up we find shells, above that we find jellyfish, then fish, then reptiles, then mammals. After doing research I found out that this was not the case. Now I suspect that diagrams that depict this ordering of the fossil record with dinosaurs maybe deception or at least a representation of the fossil record that can be easily misinterpreted by laymen.

So are there any examples of this ordering with dinosaurs? eg Jurassic layer with Jurassic fossils, then on top of that layer there is a Cretaceous layer with Cretaceous fossils?

Note: I know the wording of the question is quite terrible. Feel free to edit it.

There are definitely many examples of overlying Mesozoic strata that contain characteristic dinosaur fossils (and ichnofossils – i.e. trace fossils). One of the best examples is the Mesozoic stratigraphy of Utah and Colorado. However, most geologic intervals are characterised by less ‘famous’ fossil material (e.g. molluscs, trilobites or pollen grains). This does not render correlations involving dinosaurs less valid.

Consider a hypothetical case where some dinosaur footprints are found in a mudstone layer. The mudstone also contains distinctive grains of pollen. In the layer above the mudstone we see no more dinosaur footprints but we still have the same pollen grains. These pollen have been found in other strata (perhaps on the other side of the world!) while the dinosaur foot prints are much more rare. In this case we will be able to correlate these to rock layers much more widely using the pollen than from the dinosaur prints. However, if the mudstone layer is the youngest geological unit known to contain the fossil remnants of that particular dinosaur species (assuming it had a distinctive footprint) then we can assume that the species became extinct. Extinctions are very useful for correlating the relative age of geological units, therefore the last appearance of the dinosaur footprints will provide a tighter age control than the pollen (which persists in the rock record).

I should add that stratigraphic corrections based on the fossil record can be very complex. The scientists who study the fossil record (palaeontologists) spend decades trying to decipher the exact details of the evolution of life on this planet preserved in rocks. Due to the complexity of this science it is very easy for a layperson to get confused or make false assessments.


How to correct PSMSL data for GIA? I have a PSMSL RLR (revised local reference) sea level dataset with records from various tide gauges. Can anyone explain how to correct them for GIA (glacial isostatic adjustment) using the ICE-5G model from here.

I have a netCDF version with 4 components and some ASCII files.

The simple answer is that you just subtract the nearest value from the glacial isostatic adjustment (GIA) model. The values provided by Peltier in your netCDF file are in a grid that is 1 degree x 1 degree. So with the lat/lon position from the tidal gauge sea level data, you choose the closest value to your station and apply the correction. In the PSMSL GIA correction page they already explain that you should be using the centered value (±250 years). If you decide to use the ASCII files, those are already interpolated to the tide gauge station locations. You have additional information in the U. of Colorado GIA websites(1, 2) and in the Peltier (2001) reference.


For a tree over its entire existence, does it actually have a net negative effect on atmospheric CO2? A tree while alive converts CO2 + water -> carbohydrates + O2. However, once the tree dies, it decays, releasing CO2 back into the atmosphere. My question is, over an individual tree's overall existence, does a tree actually contribute to a reduction in atmospheric CO2?
I'm aware there's other pathways a tree could end up as a more long term carbon store (carbonaceous rocks), but mostly interested in if a tree were to die and fall in a forest, decay in 50-150 years, would it have contributed to a net reduction in CO2, or does a tree typically act as more of a temporary 100+ year store of CO2?

A brief review of recent non-paywalled available literature indicates that such an effect likely exists but that it is difficult to quantify based on currently available data.
Some amount of carbon from trees can be sequestered in the soil for periods time significantly longer than the typical above-ground decomposition time of organic matter, potentially for millennia. This clearly lengthens the carbon cycle time, but it is not clear to me whether this represents carbon storage, as there does not seem to be a well established minimum cut-off time for this. The primary source for soil-sequestered carbon are tree roots, with leaf litter constituting a secondary source.
The following paper (preprint online) addresses the question in the specific context of agroforestry, i.e. cropland interspersed with trees. The paper notes multiple times that the processes involved in soil sequestration are not well understood and that quantitative measurements and estimates vary widely, as one would expect based on differences in climatic and soil condition. Note on units: A Mg corresponds to a metric ton.
Klaus Lorenz and Rattan Lala, "Soil organic carbon sequestration in agroforestry systems. A review." Agronomy for Sustainable Development, Vol. 34, No. 2, April 2014, pp. 443-454.

The soil organic carbon (SOC) pool, in particular, is the only terrestrial pool storing some carbon (C) for millennia which can be deliberately enhanced by agroforestry practices. [...] The SOC storage in agroforestry systems is also uncertain and may amount up to 300 Mg C ha−1 to 1 m depth.
[...] Further, between 30 and 300 Mg C ha−1 may be stored in agroforestry soils up to 1-m depth [...] The SOC sequestration depends primarily on the soil C input and soil stabilization processes. Plant root and rhizosphere inputs, in particular, make a large contribution to SOC [...] Litter fall and in turn SOC sequestration may be affected by stand-density management as, for example, higher stocking levels of trees enhance the vegetation C pool.

Another paper that deals specifically with urban trees mentions in passing that the soil accounts for a significant part of the carbon sequestered in non-urban forests (presumably both naturally growing and human-managed):
David J. Nowak and Daniel E. Crane, "Carbon storage and sequestration by urban trees in the USA". Environmental Pollution 116 (2002) 381–389

Another area of the urban forest carbon cycle that this paper does not analyze is urban soils. Sixty-one percent of the total carbon in non-urban forest ecosystems
in the USA is stored in the soil environment (Birdsey and Heath, 1995). The amount of carbon from trees that is retained in urban soils, its residence time, and the amount of carbon currently stored in these soils remains to be investigated. It is likely, however, that urban soils contain less carbon per hectare than forest soils due to lower carbon inputs and increased soil decomposition rates due to warmer air and soil temperatures (e.g. Pouyat et al., 1997).