How to measure elevation above sea level Elevation is often measured in terms of "[unit of length] above sea level." Considering that the oceans aren't a uniform height, how is this measured?

It's actually an inordinately difficult problem. Neither the land nor the sea level is stable. A tide gauge along a coast needs 30 to 40 years of data to filter out the very noisy tidal and other weather signals. By the time one has homed in upon a precise average, one is already within the time-frame of land uplift or subsidence, and that is before we even think about the complexities of climate-change generated sea level rise, or quasi-decadal oceanic oscillations. Then there is the question of Earth's non-homogeneous gravity which affects local sea levels. For example if we correctly measure the elevation of a Himalayan peak relative to average sea level at the Gurarat coast, west India, we get an elevation of 'h1'. We can then measure the same peak relative to sea level in the Ganges delta, east India, which we will call 'h2'. We can make all the usual corrections for Earth's curvature etc., yet h1 will be different to h2 - though both are 'correct'.

There is no stable bench mark on 'God's Earth', so maybe the answer is to get off the planet completely. Satellite orbits are not perfect, but they are predictable, so satellite-based measurements of elevation are the best available.


Agricultural non point source of pollution (AGNPS) model input data How to input climate data for AGNPS model? AGNPS model is developed USDA https://www.nrcs.usda.gov/wps/portal/nrcs/detailfull/null/?cid=stelprdb1042468

tldr;

On the official support page titled AGNPS Climate Data -- agGEM & preGEM you find a download link to a climate data template file. Your data files need to have this format. All meteorological variables are written into this file. The template file contains daily data. It is not clear if either the data has to have daily resolution or the data can be finer (hourly) or coarser (monthly) resolved.

detailed answer

Everything I write down below is described on one the official support pages for AGPNS: http://go.usa.gov/KL0 (This is the official short link provided by the United States Department of Agriculture (USDA))

Remarks

The meteorological input data files for AGNPS model (Agricultural non-point Source Pollution Model) are actually called climate input data, although the files contain short term meteorological data.
All the provided programs are Windows executables.

generate climate input data files for known locations

Use the program agGEM. This program uses an existing statistical parameter file (maybe: == climatological data?) of meteorological data to generate a climate input data file for AGNPS. There are 233 stations in the US, for which such statistical parameter files exist. There is no information on the support page whether the data are measurement or model data. The program can be downloaded without registration from the support page linked above. The existing statistical parameter files can be also downloaded on that page.

generate your own statistical parameter file

The USDA provides a program called preGEM to generated statistical parameter files. preGEM needs an input data file with a long time series of meteorological data. What long means is to decide by the use.

The format of this particular input data file is not clear. According to the agGEM & preGEM documentation file one can choose between two types of text files: csv and fixed format (see the manual what the latter means) during the execution of preGEMs. However, a preGEM input template is provided on the support page, which is a xls file. Maybe one can also choose xls as format for the input data file.

Please be aware that there are a lot of options when you save a xls as csv via the spreadsheet software of your choice: delimiters for strings, delimiter between columns (comma, tab, semicolon, ...) etc.

Build your own climate input data file

There is a climate input data template provided on the given support page. You can generate your own file without using arGEM and preGEM. There is a file header which nicely describes how the file has to be structured. The file looks as follows:

*************************************************
*** a few words of explanation:
*** The Climate input data for AGNPS has the following fixed format.
*** The first line is required and must contain the current version ID
*** The second line may contain any info the user wishes.
***
*** The third line contains site latitude, longitude, elevation,
*** temperature lapse rate with elevation,
*** percentage N in the precip, and unit code.
*** The temperature lapse rate units are degrees F per foot or degrees C
*** per meter of elevation and can be left at zero.
*** The nitrogen percentage in the precip is currently not used in the
*** program, but units are percentage by weight.
*** The unit code is 1 for English and 0 for metric.
***
*** The fourth line contains the start date for the data.
*** The fifth line contains the end date for the data.
***
*** The sixth through eighth lines contain data column headings
***
******* climate file starts below this line:
Climate File Input Version ID:          5.00
   56  Princeville
   22.0708  159.1234    345.00   -0.0036    0.0000         1
01/01/0001
12/31/0100
     Daily   -Air Temperature-   Precip-     Dew        Sky      ----- Wind -----   Solar     Storm    Potent-
    Date     Maximum   Minimum   itation     Point     Cover     Speed  Direction Radiation  Type ID    ial ET
mm/dd/yyyy     [ºF]      [ºF]      [in]      [ºF]       [%]      [mph]       [º] [BTU/h/ft^2]    [-]      [in]
01/01/0001     73.08     67.10      0.00     59.46      75.4      3.67               87.30
01/02/0001     77.12     60.72      0.08     61.19      39.2      5.61              123.27
01/03/0001     78.22     58.41      0.28     60.80      80.9      3.85               79.23
01/04/0001     79.22     60.80      0.24     60.81      34.7      2.43              127.03
01/05/0001     80.62     69.15      1.84     67.06      79.8      6.96               79.44
01/06/0001     82.05     66.88      0.25     64.65      30.0      4.29              128.66
01/07/0001     80.89     62.94      0.07     60.28      52.7      3.59              114.29
01/08/0001     77.59     63.79      0.00     60.51      33.0      4.14              129.61
01/09/0001     75.78     61.29      0.00     57.00      53.0      3.69              115.94
01/10/0001     74.65     57.61      0.11     54.61      46.9      4.04              122.56
01/11/0001     78.17     60.47      0.52     61.41      38.5      5.44              126.81
01/12/0001     74.93     64.24      1.18     62.55      67.1      5.47               99.94
01/13/0001     74.97     62.35      0.63     66.70      84.6      3.82               73.72
******* This line and below are not in the input file.
*** In this template the data ends on 01/13/0001, but the actual file
*** must obviously continue to 12/31/0100 because of the specified
*** end date on line 5.


What is the better way to deal the missing and negative cells of satellite snow cover data Daily and monthly MODIS snow cover L3 data has downloaded, next to deal with missing and negative cells.
Different types of interpolation are being used to fill the missing cells. I want to fill the missing cells with mean of 3 surrounding values but it is very hard because in some cases large portion of data is missing?
I know to mask the NaN cell by using (nanmean) command and long term mean of same area can also be use.

Permafrost Presence/Absence Mapping of the Qinghai-Tibet Plateau Based on Multi-Source Remote Sensing Data but I am looking any possible way beside these.

What is the best way beside above mentioned two to deal the missing and negative cells of MODIS snow cover data?

Note; I am using matlab environment for this purpose.

You could fill the gaps with the analysis products of numerical weather prediction. NCAR for example (RDA UCAR) hosts the NCEP North American Regional Reanalysis (NARR) with data from 1979 to 2018 including snow cover (NARR) in 3-hourly intervals.

But I would guess it depends on your goal:
You can make an educated guess (bayesian approach, combining measured and predicted variables) about the true state of the snow cover, but what was not measured can not be pulled out of nowhere.


In -20 °C weather, creeks below waterfalls here form ice columns. What are these called? Ice-canoes? I would like to know the name(s) of this ice formation.
How common or rare is it?
What other regions of the world does this occur in?
What specific requirements are needed to produce it and could it be reliably produced in a lab or a fountain or pond?
What other structures are similar to this?

We also have a video which shows the center of the growing columns bubbling with orange froth, which appears to supply material to the sides of the columns as it grows.

These columns appear to be about two feet or 60 cm high and about eight inches or 20 cm in diameter for the largest ones.

They do not look like they take the shapes of crystals, rather, like the precipitation chimneys of undersea hydrothermal vents.

I heard that this kind of structure has been seen in Nova Scotia. I also heard they form in more than one creek in or near Hamilton, Ontario, Canada (where the pictures and videos were taken). I also heard this has happened in other years, not just this year.

These are classed as ice spikes. You are correct in noting the occurrence downstream of waterfalls, as this extra turbulence is part of the formation process. The USGS page here has information on the formations, photographs and a list of criteria involved in their formation:

  The winter conditions at each of the ice formation’s locations were
  similar:

  Freezing or sub-zero temperatures and low flow in channel during    winter months
  Ice covered the surface of the stream and accumulated at depths long    the banks restricting flow
  In each instance, water flowed over a structure such as a weir or    beaver dam causing turbulence in the flow
  Due to the turbulence and restriction in flow, water emerged from    small surface openings downstream of the structure and began to
  freeze – probably rapidly in some cases due to the sub-zero
  temperatures at times
  Whether the freezing water resulted in a “columnar” or a “frothy,    bubble” ice structure depended on the unique conditions at each
  location and the weather conditions over time


Is a San Andreas volcano possible? This question is, in part, inspired from the 1997 Hollywood movie Volcano, where a fictional volcano erupted out of the La Brea Tar Pits in Los Angeles.

The San Andreas Fault is a transform fault plate boundary (see image below):

Image from the USGS Glossary entry for transform faults, with a definition:

  A transform fault is a special variety of strike-slip fault that accommodates relative horizontal slip between other tectonic elements, such as oceanic crustal plates.

A specific type of transform fault is a 'leaky transform fault', which according to a source used on its Wikipedia page describes the tectonic movement at this type of faulting as being:

  In addition to the regular strike-slip motion observed at transform boundaries, an oblique extensional component is present, resulting in motion of the plates that is not parallel to the plate boundary.

Illustrated below:

Is there any evidence that oblique tectonic movement occurs along the San Andreas Fault?

Hence, is a San Andreas volcano possible?

Yes. In fact there are already volcanos associated with the San Andreas fault system.

Neenach is an extinct Miocene volcano split in half by the San Andreas fault. Garry Hayes wrote a nice blog post about this volcano system: A Volcano Sundered: A Field Trip Along the San Andreas Fault.

If you'll allow some latitude in what counts as 'a San Andreas volcano', then there is active volcanism too. The Salton Buttes are a group of rhyolitic volcanos in the Brawley Seismic Zone, a set of oblique transform faults — actually in the axis of the active Gulf of California rift — on the south-east shore of the Salton Sea. You can see them in this Google Maps image (on the right; the big fields are 800 m across):

The Space Shuttle photo (left) of the Imperial Valley annotated by the USGS shows the relationship between the San Andreas fault, about 5 km from the volcanos, the Brawley Seismic Zone (BSZ), and the Imperial Fault to the south. At this scale, it's essentially one big fault system.


Soil Science and the carbon cycle - is carbon released from soil into the atmosphere? Is carbon lost from topsoil when it's degraded/removed? What is the scientific process?

There are two ways carbon is released from soil.

The first is cellular respiration of plants that uses previously stored energy (visualized in this chart).

The second is when heterotrophs consume organic carbon below ground and respire carbon dioxide.

The sum of these is called soil respiration, which I think was the process you were asking about.


Do dams reduce the flow of river downstream? There is a conflict between Egypt and Ethiopia, because the latter wants to build a dam on the Nile river. Citing this article:

  [Egypt] fears the Nile dam will reduce its share of the river and leave the
  country with dwindling options as it seeks to protect its main source
  of fresh water.

What do they mean by "reduce its share of the river"? As far as I understand, the dam will create a reservoir, which will initially divert some water to be filled, but once that is done, the flow of the river should be the same. Is Egypt worried about this initial reduction, or do dams somehow reduce the flow of a river?

If so, what is the mechanism? I would guess that this is due to increased evaporation from the river, since the reservoir has a bigger surface than the usual river, but then again, it also collects more rain.

Once a dam has been constructed in a river, the natural flow of water will be disrupted.

You correctly state that initially there will be a period required for the dam to fill. Until then, little of no water will flow beyond the dam.

Dams are created for one or more of three reasons:

To supply potable water to a population of humans for domestic or
industrial purposes.
For agricultural purposes.
To generate hydro-electricity.

Water released from a dam prior to it being full may be to restore some flow for environmental reasons, because hydro electricity may need to be generated or it may be needed for agricultural reasons.

To protect dams from overfilling and damaging the dam wall spillways are generally constructed to allow the excess water to flow beyond the dam. For dams without a spillway, the dam gates will be opened to reduce the amount of water in the dam to protect the dam from failure.

One of the issues with dams is they prevent sediment carried by the river to travel the full length of the river. This can be detrimental to the natural replenishment of some farmlands of nutrient rich sediment and it is detrimental to the replenishment of nutrients to fish breeding regions near the mouths of rivers. This happened when the Egyptians built the Asswan Dam.

The other issue with dams is that people downstream of the dam cannot rely of the natural flow of the river, in terms of timing of flows and quantities of flow. This is the main concern for Egypt. It relies heavy on the Nile River as its main source of fresh water for hydro-electricity generation, agriculture and water for people to drink.


What could be causing microseisms on Mars? The anouncement published in Science Mini tremors detected on Mars for first time says that the Mars lander InSight is detecting microseisms on Mars after various vibrations produced by the lander and its interaction with the wind are excluded.

The above linked Wikipedia article says:

  In seismology, a microseism is defined as a faint earth tremor caused by natural phenomena. Sometimes referred to as a "hum", it should not be confused with the anomalous acoustic phenomenon of the same name. The term is most commonly used to refer to the dominant background seismic and electromagnetic noise signals on Earth, which are caused by water waves in the oceans and lakes. Characteristics of microseism are discussed by Bhatt. Because the ocean wave oscillations are statistically homogenous over several hours, the microseism signal is a long-continuing oscillation of the ground. The most energetic seismic waves that make up the microseismic field are Rayleigh waves, but Love waves can make up a significant fraction of the wave field, and body waves are also easily detected with arrays. Because the conversion from the ocean waves to the seismic waves is very weak, the amplitude of ground motions associated to microseisms does not generally exceed 10 micrometers. (several citations available in original article)

We can exclude large surface bodies of water on Mars, so the vibrations must be coming from other sources.

Question: What could be causing microseisms on Mars?

I think that the mechanism suggested in the article fits the bill the best:

  On Earth, microseisms are ubiquitous, caused largely by the sloshing
  of the ocean by storms and tides. Mars, despite the dreams of science
  fiction writers, has no present-day oceans. Instead, this newly
  discovered noise is likely caused by low-frequency pressure waves from
  atmospheric winds that rattle the surface, inducing shallow,
  longer-period waves in the surface, called Rayleigh waves, Lognonné
  said.

See e.g., https://www.lpi.usra.edu/meetings/lpsc2012/pdf/1994.pdf , for a modeling study of the microseismic events on Mars due to wind.


How to quickly or easily prove the world is spherical? A relative of mine has recently introduced me to the modern flat earth theory, which she believes in. Setting aside for the moment that it is ridiculous, and that sending up some balloons with cameras on would provide evidence to the contrary, how could one evidence that it is in fact spherical from ground based observation?

I immediately thought about citing the observations of Aristotle and measurements of Eratosthenes, something that one can do themselves, but of course they have an answer for that regarding curving light to explain variation of the sun's elevation with latitude. Also refraction backed up by observations of ships on the horizon appearing to be above the horizon (due to refraction) and so light-based observations of a curved body of water are out. To make it even harder, the belief has been adjusted to allow for a flat earth that curves slightly but is not spherical, so objects gradually disappearing over the horizon aren't proof and neither is observing the curvature from a plane! For every argument there is a counter argument, and I, as a layman, don't know how to prove e.g. that the light isn't curving as described.

Without getting into countering non-scientific flaws such as the massive amount of government-level collusion that would be needed to maintain this conspiracy, how might one go about demonstrating it or designing a practical experiment for which the conclusion cannot be refuted. Is this even possible when someone can claim e.g. light curving through the atmosphere in a particular way, without having to back it up? I'm not familiar enough with scientific theory to know how one establishes certainty, or if it is based on a balance of probability (i.e. more proof of one theory than of the contrary).

Note: This is a thought exercise only, I do not expect to actually convince my relative while she is going through a personal crisis for which this is one of many symptoms, that is a separate issue. She holds a degree in aeronautical engineering so it isn't caused by a lack of intelligence.

To answer my own question based on the useful comments here, my favorite methods were:

The earth's shadow cast on the moon during an eclipse. It is easy to observe and the flat earth counter argument is so insane that if it is offered you should just walk away.
Shadows differ from place to place. The same experiment as Eratosthenes but you can carry this out locally with a piece of large card, 2 obelisks and a light source casting a shadow. Now bend the card and observe the change in shadows. The same effect could then be observed on the earth's surface. The counter argument of curved rays of light is weakened by the fact you can reproduce it locally.
triple-right triangle:
You move in a straight line for a long enough distance Turn right
90° degrees, walk in that same direction for the same distance Turn
again to the right 90° degrees and walk again the same distance
After this you'll end up at the starting point. This is not possible
on a flat surface since you'd just be "drawing" a half-finished
square. Not sure how practical this is as you'd have to walk a long way!
Although not technically about the earth being flat, in a flat earth theory the sun orbits, or at least moves over the earth. A simple way to discount this is observing parallax with surrounding stars.
It is not too difficult to prove the earth curves at least, such as by observing more objects over the horizon the further you go up. And even measuring the curvature is not difficult. Thus I believe a person could drive the length of the African continent, observing the curvature and measuring the straight line distance, and modelling that alone would show the earth curves beyond what could be acceptable on a flat earth, without all the water running off the edge!
One I haven't seen mentioned yet is showing that the flat earth map cannot work. In a flat earth, apparently, the north pole is at the centre and south pole is a ring around the outside. Pick a land mass close to the south pole, and another on the opposite side of the map. The distance you would need to travel to reach one from the other by e.g. flying east around the map would be enormous and not congruent with the flight times or shipping times in real life.
Earth is warmer near the equator, for obvious reasons in a non-flat world but the counter argument would have to be pretty imaginative.
Sunrise and sunset do not happen at the same time for everyone on earth. The difference in timezones, which can be observed by taking a trip to different countries, cannot reasonably be explained by a curved but nearly flat earth.
Experiments with gravity, but flat-earthers reject the complication of gravity (things drop just because). So I avoided this one, but it would be a compelling way to demonstrate why people on the other side of a spherical earth are not on their heads.


Extent of the Persian Gulf Is there a consensus on when the Persian Gulf reached its modern day levels? So far the material I have read says the Persian Gulf attained its present levels around 4000 BCE, but I am not too sure. Any suggestions? Thanks.

You are pretty much spot on in terms of the date.  According to the article Shoreline reconstructions for the Persian Gulf since the last
glacial maximum (Lambeck, 1996) based on models of glacio-hydro-isostatic effects of the end of the last ice age and the article Early State Formation
in Southern Mesopotamia:
Sea Levels, Shorelines,
and Climate Change (Kennett and Kennett, 2006) indicate from archaeological observations that at around 6000 years before present (~4000 BCE) that the present shorelines were approximately shaped.  Both articles record an initial inundation of the Tigris-Euphrates delta.

The process is summarised in the image below:

Image source: University of California - Santa Barabara


Has the present rise of CO2 ppm been proved to be caused by human activity? The level of CO2 in the atmosphere has risen roughly from 300 to 400ppm over the last 60 years.

What are the reliable calculations showing that such a rise has been caused by human activity? I am looking for something like "X millions of tones of kerosene was burnt between 1980 and 2010 which produced Y millions tones of CO2 which effected in additional Z ppm of CO2 in the atmosphere".

US EPA

Some of the carbon goes into the oceans and soil:

Wikipedia

The cumulative contribution to the atmosphere is  the area of the light blue region of this chart.

CarbonBrief,  Le Quéré, C. et al. (2016)


Sensible and Latent Heat. how to separate them I need help with latent and sensible heat. P.S: I have been through all Wikipedia and other pages that say phase change and temperature change.

My Question is: if there is convection, it will take the heat away from surface, what is the chances that the heat taken is latent or sensible?

Evaporation is also convection and heat transfer is also convection, so where does sensible and latent heat stands in this story.

First some definitions:

Latent heat is the heat that leaves or enters a system during a process where the temperature of the system stays constant. Phase changes are prime examples where latent heat leaves (exothermic) or enters (endothermic) a system. Ice melts (endothermic) and water freezes (exothermic) at constant temperature. Sensible heat is the heat that enters or exits a system when the temperature of the system changes. Heating or cooling water are cases that involve sensible heat. All heat flow between two systems requires a temperature difference between the systems. Convection is heat flow between two systems by movement of mass. The two other heat flows are conduction and radiation.

Now to the questions:

During a phase change, the temperature of the system stays constant. The heat gained or lost is called latent heat. To vaporize a liquid, we must supply heat. Hence vaporization is endothermic (heat enters the system). To get the heat into the system, we must set the surroundings at a hotter temperature. Otherwise the heat will not flow. The process by which the heat flows can be any one of the three modes. We can set a pot of water in a pan on an electric heater and realize conduction from the burner to the pan to the water. We can set use a hair dryer to blow hot air over the pot and realize (forced) convection from the air to the pan. Finally, we can set the pot a small distance above the glowing electric burner and realize radiation from the electric burner to the pot.

By contrast, consider the case of a day where the outside temperature is below freezing and the air is still. A duck pond in the yard is not frozen over. Clearly, it’s water temperature is above freezing. Should we jump in the duck pond to warm up? Of course not! The natural convection coefficient of stagnate water is higher than the natural convection coefficient of stagnate air (and the difference only becomes greater in flowing water versus flowing air). The water pulls heat from us by convection faster than the air does at the same temperature, and our body temperature will drop faster than when we would stay standing in the still air. Also, while the conduction coefficient of water is larger than that for air, the main heat transfer in a fluid is convection, even in stagnate cases. The heat that flows out of our body as our body temperature drops is sensible heat.


Would the climate still rise when we reduce our carbon footprint down to zero? Every electrical device consumes electric energy and almost every one of them I can think of produces heat as a byproduct. This also applies on every kind of machine powered vehicle. Even our bodies produce a small amount of heat. Almost everything produces a small or high amount of heat. This only gets more and more with more people on this planet and continuing industrialization. Just think of all the giant production around the world and all the means of transportation - they all produce a massive amount of heat.
If you put hundred cups of hot tea into one room the room temperature rises as the tea cools, right? This is heat transfer.
I asked myself wether we would still have a negative effect on the climate even when we (could) reduce our carbon footprint down to zero today or not. We would still produce a lot of heat with almost everything we do.
To what extent has heat production a negative effect on the climate compared to co2 emission?
And why is heat production never payed attention to?

While I can't comment on whether the global temperature would still rise if humanity's carbon footprint were reduced to zero, I do know that the heat our machines produce would not contribute any net warming effect. The issue is not the amount of heat which is entering the atmosphere -- it's where and when that heat came from.
Assuming that we are successful in reaching 100% wind, water, and solar energy, the energy consumed at the end use would be from only seconds to at most a year ago:

Seconds: Solar power from photovoltaic panels is collected, converted to electricity, transmitted to the grid, and used almost instantaneously
Hours to days: Wind is primarily generated by daily fluctuations in surface temperature caused by the sun
Months: The water in rivers which power hydroelectric dams is generated by seasonal patterns in precipitation, which is a function of changes in solar intensity over the course of the year

In contrast, the energy we're using today from fossil fuels is tens to hundreds of millions of years old, containing energy harvested from the sun over a period of over a hundred million years (source).
The energy from wind, water, and solar sources is being added to our atmosphere anyway -- we just convert it into different forms to use it for other purposes in between its transit from the sun to the planet.
By contrast, the energy from fossil fuels had been locked away, safely stored for 100 million years or more. Until we started drilling and mining, it was no longer having any significant impact on the planet.
This also applies to the food we consume -- the energy that fruits and vegetables store is at most a year old -- for animal products, it's at most two to three years old.


How to set up a domain from namelist in WRF? I'm fairly inexperienced with WRF and was wondering if anyone could point me in the direction of any helpful resources for it.

The task I have is to make a simple 9 km domain, but I'm having trouble understanding what some of the variables actually do/mean?

Specifically,  e_we/sn , dx/dy , and how a nested domain works.

There is a WRF domain Wizard offered by ESRL. You can download it here. Also, don't make the same mistake I made using Lambert Conformal- keep stand_lon the same as your ref_lon.


What are the differences between Climatology, Meteorology and Atmospheric Science? Please explain the main differences between Climatology, Meteorology and Atmospheric Science.

Thank you

Atmospheric science is the generic study of the atmosphere. This includes climatology, air quality, and meteorology. It is often all-encompassing.

Climatology- the study of climate, the atmosphere over an extended period of time. This can usually be seen from either a statistical or physical perspective. Usually, the statistical approach looks at climate extrema. Physical climatology studies the processes that drive climate, and may be used as reconstruction, or prediction. Some of the processes that meteorologists may neglect, such as aerosols and long term trends in oceanography, are very relevant in climatology. Climatology is also a subset of atmospheric science.

Meteorology is the study of weather, especially in forecasting. Often, meteorologists interface with the public, via television, forensic meteorology, produce forecasts etc. In regards to research, meteorologists often study improvements to atmospheric models, or other aspects to forecasting. Some research meteorologists study mechanisms behind certain weather phenomena, in order to improve understanding, say of severe weather, atmospheric chemistry, turbulence, etc.

For reference:

Meteorology time scales: Seconds-Weeks
Climatology time scales: Months-decades

In summary:

Atmospheric science is a generic term describing the study of the atmosphere.
Meteorology is the study of the atmosphere, generally in the short term. Occupationally, it involves interfacing with the public. Research meteorologists study a vast number of topics.
Climatology studies the evolution of the atmosphere over long timescales, including how it may be changing. Some of the things that meteorologists may neglect, climatologists must consider.


Can Cirrocumulus and Cirrostratus appear at the same time? I see cirrocumulus fading away in the front and bunch of cirrostratus in the back. However, I was taught that cirrocumulus appear when the upper atmosphere is unstable while cirrostratus appear when the atmosphere is stable, so seeing both together is confusing.

Clouds don't really form in a fully stable atmosphere, so the distinction between "stable" and "unstable" is not real here. An approaching warm front in particular offers many types of clouds, and among other types one may well see high-altitude cirrus, cirrocumulus and cirrostratus clouds appearing together.
Beach weather approaching ... but first:
Wikipedia  gives the following description of the wide variety of clouds that may appear in the case of an approaching warm front.

Cirrus, cirrostratus, altostratus, nimbostratus, then stratus. Other clouds can also often be seen, including cirrocumulus amongst the approaching cirrus, altocumulus with or instead of altostratus (particularly if the front is weak), and occasionally cumulonimbus along with or instead of nimbostratus in summer. Additionally, stratocumulus often appears underneath the main altostratus deck and stratus fractus typically forms in precipitation falling from the thick nimbostratus layer. Often in warm temperatures, rain bearing cumulus congestus clouds can appear under the cirrostratus, and more rarely altocumulus castellanus clouds if convection is sufficient. In cold humid conditions, low airmass stratus or fog may obscure the main frontal clouds.

A picture from the article, showing the major cloud types:

Source: https://commons.m.wikimedia.org/wiki/File:Warm_front.svg#mw-jump-to-license. By WP user Kelvinsong.  License in link.
We see that the cirrus and cirtostratus clouds are adjacent, and from the table entry quoted above that cirrocumulus clouds can appear among the cirrus clouds.  Since in reality some overlap will occur between the different cloud regions, an approaching warm front is likely to produce a region where cirrus, cirrocumulus, and cirristratus clouds can be seen together.


How sensitive are typical seismometers? NASA recently landed a seismometer on Mars, with what sounds an impressive detection ability, with press reports gushing it is "able to detect vibrations smaller than a hydrogen atom." A more technical description is

  SEIS [...] is capable of measuring
  accelerations down to $10^{-9} m/s^2/\sqrt{Hz}$ over frequencies of 0.001 to 10
  Hz and $5 \times 10^{-8} m/s^2/\sqrt{Hz}$ from 0.01 to 100 Hz

-- which still seems pretty impressive. How does this compare to typical terrestrial equipment?

The table below gives you a nice summary snapshot up to 2015.

Reference:  Kamp, P.J., 2016. Towards an Ultra Sensitive Seismic Accelerometer (Master's thesis, University of Twente).

Sercel accelerometer, the top one in the table, is widely used in Oil and Gas industry, for example, to monitor induced seismicity. Below is an excerpt from the article: "A high-sensitivity MEMS-based accelerometer", by J. Laine and D. Mougenot (2014), The Leading Edge, 33(11).

1 g is about ~10 m/s^2 (9.80665) so 1 ng ~ 10^-8  m/s^2. For the Sercel then 360 ng mentioned in the paper (three times the rms noise level) = 3.6 ^10-6 m/s^2.

Correct me if I am wrong.


Recovery From the Great Dying 252 million years ago, Earth underwent its worst, most violent chapter in the form of the Permian-Triassic extinction event, or "The Great Dying".  70% of the terrestrial species and 95% of the marine species became extinct.

There was one thing that I had noticed in Permian and Triassic landmasses--both periods had Pangaea, all the world's continents clumped together into one singular landmass.  And recent evidence has found that it took life ten million years to recover from the Great Dying.

So why did it take so long?  Was the damage of the Great Dying that extensive?  Or did Pangaea play a part in delaying the recovery process?

A recent 2016 Stanford University study reported in the article "Oxygen-starved oceans held back life's recovery after the 'Great Dying'", suggests that

  Analysis of ancient seabed rocks from disparate locations reveal that life did not rebound until anoxia had fully ebbed.

Specifically, the researchers found evidence from a lot of places around the world that, according to the researchers, point to a possible conclusion that globally

  anoxic conditions reduced seawater oxygen levels by 100-fold at the onset of the mass extinction. Oxygen levels then slowly rose, only returning to pre-extinction levels after 5 million years, corresponding to when the climate became more stable and life regained its former diversity.

This research paints a picture that the mass extinction event resulted in a global anoxic event, that took the Earth a considerable amount of time to recover from.


Is there any consensus of what caused the Lusi Mud Volcano eruptions in Indonesia? In May, 2006, the Lusi Mud Volcano in eastern Java, Indonesia came to life, smothering much of the surrounding land in mud.

According to the article Indonesia's Infamous Mud Volcano Could Outlive All of Us (Normile, 2011), there is considerable uncertainty about what actually triggered the eruption in the first place.  The main ideas of what possibly caused the eruption, as reported in the article are:

Nearby drilling
A relatively nearby 6.3 magnitude earthquake 2 days earlier.

Is there any consensus of what caused the Lusi Mud Volcano eruptions in Indonesia?

No, there is no consensus.

In fact, there's quite a bit of debate about it — around the 2 causes you mentioned. To sum up the proposed triggers:

The eruption happened about 2 days after the 2006 Yogyakarta earthquake, which killed over 5000 people. Lupi et al (2013), Sawolo et al. (2011), and others including the Indonesian government, favour this as the trigger.
The eruption happened about 200 m away from Lapindo Brantas's Banjar Panji 1 exploration well. There were early signs of trouble in the well, which started when the earthquake happened. At the time, the incident was treated as a blow-out, relief wells were drilled, etc. Davies et al. (2011), and others, blame this.

Last year I blogged about Lusi. The first-order cause was not my focus (though I insinuated that I thought the well exploited a predisposition set up by the earthquake); I focused instead on the history of the event. But much of the controversy emerged in the comments, which are worth reading.

Rather than trying to synthesize everything into an elegant summary, I'll just point out two of the complications in all this:

The Lupi et al (2013) argument has serious flaws, because the authors misinterpreted the sonic (DT) log from the well. This was partly, but not completely, resolved by the corrigendum published in 2014. In a nutshell, the fast layer they argued for was a logging artifact.
There is a legal backdrop to the argument, which may not be compatible with an objective scientific debate. For the company, there is the question of liability and thus reparations, which could be expensive. For the government, there is the question of international financial relief, some of which is contingent on Lusi being a natural disaster.

The debate may not be satisfactorily resolved for some time. It seems to be one of those unhelpful debates where, to the participants at least, there is no uncertainty. My heuristic in such situations is to assume this means that "it's complicated".

References

Davies, R, S Mathias, R Swarbrick and M Tingay (2011). Probabilistic longevity estimate for the LUSI mud volcano, East Java. Journal of the Geological Society 168, 517–523. DOI 10.1144/0016-76492010-129.
Lupi, M, EH Saenger, F Fuchs and SA Miller (2013). Lusi mud eruption triggered by geometric focusing of seismic waves. Nature Geoscience 6, 642–646 (2013) DOI 10.1038/ngeo1884.
Sawolo, N, E Sutriono, B Istadi, A Darmoyo (2009). The LUSI mud volcano triggering controversy: was it caused by drilling? Marine & Petroleum Geology 26 (9), 1766–1784. DOI 10.1016/j.marpetgeo.2009.04.002.


Where do riverbed stones come from? Have they always been here since the river was formed?  Are some newer than others?

Riverbed 'stones' - I assume you mean things like pebbles, boulders, etc. are pieces of rock that have weathered out and been deposited in the river. Some come from rock that is very close to where they are located and some have been transported from very far away. In general (and it is a very broad generalization) the rounder the stone, the longer it has been in the river and the more likely it is to have come from far away. Of course that depends on the hardness of the rock, and other factors, too.

Some rocks are newer than others. Some have been formed quite recently and some are billions of years old.


If today's Earth becomes warmer, how will it compare to the Earth of the Cretaceous period? Most pessimistic scenarios about climate change predicts a global rise of temperature of several Celsius degrees over the course of the 21st century if no action is taken. While such a shift in temperature has many implications such as rising seal levels (due to the melting of ice near the poles) and a mass extinction event, the Earth has recordedly had eras warmer than today in the past, such as the Cretaceous period. For reminders, Cretaceous is the last geological period before the extinction of dinosaurs, and it had notably higher sea levels and a warmer global surface temperature (4 °C above today's average surface temperature).

Assume now that the average surface temperature will rise as predicted by the aforementioned pessimistic scenarios, and that the seal levels will rise drastically.

How would tomorrow's Earth (in this scenario) compare to the Earth of the Cretaceous period ? Would it be in a similar state (besides temperature and sea levels), and perhaps share similar climates around the world, or would various factors I didn't mention (such as the ratio of oxygen in the air) make it very different ?

During the cretaceous the earth was on average 4 degrees warmer, but a 4 degree average results in nearly no change at the equator but a significantly higher rise at the poles, 8 to 15 degrees warmer. Antarctica was not covered in an icecap in the cretaceous period, although smaller ones may have formed periodically. Northern antarctica was largely covered in wet forest. Ecologically you would see wet temperate forest similar to those in australia and south america.

Note however warming was not the the only factor different positions of continents leads to a significantly different ocean circulation. Higher sea levels turn lowlands into seas changing rainfall patterns significantly. So the cretaceous is not a great predictor of the near future climate.

Source 1

Source 2


Are there secondary causes of sea level change? Aside from the fraction of water stored as ice on land and temperature of the water, are there other factors that change sea level, and if so what are is the magnitudes of the these changes?

For example, by how much does sediment and soluble matter entering the ocean change sea level? What about volcanoes and tectonic activity? Is there a tendency toward hydrostatic equilibrium where the Earth is entirely covered by an ocean of uniform depth?

Yes, there are lots of other factors.

Factors affecting sea levels are no different from other natural processes: there is a large number of coupled, non-linear effects, operating on every time scale, and at every length scale, and across many orders of magnitude.

The Wikipedia page Current sea level rise lists many of the known processes. And I wrote a blog post, Scales of sea-level change, a couple of years ago with a long list, mostly drawn from Emery & Aubrey (1991). Here's the table from it:

Reference
Emery, K & D Aubrey (1991). Sea-Levels, Land Levels and Tide Gauges. Springer-Verlag, New York, 237p.


How to derive the (dry) deposition velocity for particles in the atmosphere In atmospheric dispersion modelling the deposition velocity of particulate matter is often described by:
$$
v_d = \frac{1}{r_A+r_B+r_A r_B v_g}+v_g \hspace{10mm}(1)
$$
where $r_A$ is the aerodynamic resistance (describing turbulent fluxes in the surface layer), $r_B$ is the viscous resistance (molecular diffusion in the quasi-laminar sublayer) and $v_g$ is the terminal fall velocity of the particles.

How is $(1)$ derived?

It is used in numerous models but I haven't found any references explaining how the expression is derived. The closest I've found is in this book by Seinfeld and Pandis (ISBN: 9781118947401), chapter 19.

There, it is explained that $(1)$ is derived from the following system of equations describing the total flux through an assumed constant flux layer:
$$
F
= \frac{C_3-C_2}{r_A} + v_g C_3
= \frac{C_2+C_1}{r_B} + v_g C_2
= \frac{C_3-C_1}{r_t}
\hspace{10mm} (2)
$$
where $C_3$ is the particle concentration at the top of the surface layer, $C_2$ is the concentration between the surface layer and the viscous sublayer and $C_1$ is the concentration of still airborne particles at the surface.

At this stage it is assumed all particles close to the surface will adhere to the surface so that $C_1$ is practically 0. Then $(2)$ can be simplified to:
$$
\frac{C_3}{r_t}
= \frac{C_3-C_2}{r_A} + v_g C_3
= \frac{C_2}{r_B} + v_g C_2
\hspace{10mm} (3)
$$

By elimination of $C_3$ and $C_2$ from $(3)$ one is supposed to end up with $(1)$, since $v_d=r_t^{-1}$. I've tried doing this but end up with this instead:
$$
v_d = \frac{1}{r_t}
= \frac{1}{r_A+r_B+r_A r_B v_g} + \frac{v_g}{r_A(\frac{1}{r_B}+v_g) +1}
$$

So either my algebra is a bit rusty or there are additional assumption involved...

After some more work I got it working, this might not be the shortest solution possible. There are no further assumptions needed, just pure algebra.
The solution is a bit tedious to reach, so it's not too surprising that this is usually not included in the literature.

Start by splitting $(3)$ into two separate equations
$$
\begin{cases}
\frac{C_3}{r_t}=\frac{C_3-C_2}{r_a}+v_g C_3\hspace{10mm}(4)\\
\frac{C_3}{r_t}=\frac{C_2}{r_b}+v_g C_2\hspace{17mm}(5)
\end{cases}
$$
Get $C_3$ by multiplying $(5)$ with $r_t$ and breaking out $C_2$:
$$
C_3 = C_2 r_t (\frac{1}{r_b} + v_g)\hspace{10mm}(6)
$$
Divide $(4)$ by $C_3$:
$$
\frac{1}{r_t}=\frac{1-C_2/C_3}{r_a}+v_g\hspace{10mm}(7)
$$
Insert $(6)$ in $(7)$:
$$
\frac{1}{r_t}
=\frac{1-\frac{C_2}{C_2r_t(1/r_t+v_g)}}{r_a}+v_g
=\frac{ \frac{1}{r_b}+v_g-\frac{1}{r_t} }{ r_a(\frac{1}{r_b}+v_g)}+v_g
\hspace{10mm}
$$
Move $r_t$ to LHS, i.e. add $\left(r_t \cdot r_a(\frac{1}{r_b}+v_g)\right)^{-1}$ to both sides:
$$
\frac{1}{r_t}\left(1 + \frac{1}{r_a(\frac{1}{r_b}+v_g)}\right)
= \frac{1}{r_a}+v_g
$$
Divide by $\left(1+\frac{1}{r_a(\frac{1}{r_b}+v_g)} \right)$ on both sides:
$$
\frac{1}{r_t}
=\frac{1/r_a+v_g}{\left(1+\frac{1}{r_a(\frac{1}{r_b}+v_g)} \right)}
$$
Multiply numerator and denominator (RHS) by $r_a$ and simplify:
$$
= \frac{1+v_g r_a}{\left(r_a+\frac{1}{(\frac{1}{r_b}+v_g)} \right)}
= \frac{1+v_g r_a}{\left(r_a\frac{(\frac{1}{r_b}+v_g)}{(\frac{1}{r_b}+v_g)}+\frac{1}{(\frac{1}{r_b}+v_g)} \right)}
= \frac{(1+v_gr_a)(\frac{1}{r_b}+v_g)}{r_a(\frac{1}{r_b}+v_g)+1}
$$
Re-organize the numerator and split it:
$$
=\frac{ \frac{1}{r_b}+v_g+v_g\frac{r_a}{r_b} +v_g^2 r_a }{r_a(\frac{1}{r_b}+v_g)+1}
=\frac{ \frac{1}{r_b}+v_g\left(r_a(\frac{1}{r_b} +v_g)+1\right) }{r_a(\frac{1}{r_b}+v_g)+1}
=\frac{ \frac{1}{r_b}}{r_a(\frac{1}{r_b}+v_g)+1} + v_g
$$
If we now move $r_b$ in the first term on the RHS to the denominator we end up with the final expression:
$$
\frac{1}{r_t} = \frac{1}{r_a + r_b + r_a r_b v_g } + v_g
$$


Are Argo probe data used for numerical weather prediction (NWP)? Argo probes broadcast surface measurements (among other things) on the worlds oceans, far away from traditional surface observations.  Yin et al. (2010) study the assimilation of these measurements in an ocean model, but according to an unsourced remark on Wikipedia:

  When a float transmits a profile it is quickly converted to a format that can be inserted on the GTS (Global Telecommunications System). The GTS is operated by the World Meteorological Organisation, or WMO, specifically for the purpose of sharing data needed for weather forecasting. Thus all nations who are members of the WMO receive all Argo profiles within a few hours of the acquisition of the profile..

The ocean model by Yin et al. (2010) is not a weather forecasting model.  Are there any operational agencies that actually use Argo probe data for numerical weather prediction?  Are there any publications on the impact this has had on forecast skill?

One of the issues with ARGO data is that in most cases it does not provide data from the real surface of the ocean. When they ascend from their drifting depth (usually at 1000 or 2000 meters) to the surface, most of them stop recording at a depth of around 5 meters from the surface. From SeaBird (the company that provides the CTD sensors in most ARGO floats, SSalOceanSciencesMar08-5Pages.pdf): "...to avoid degrading the salinity accuracy by ingesting sea surface contaminants, the pump is turned off at approximately 5 decibars beneath the surface as the Argo float ascends." This creates problems when assimilating into atmospheric models because of inconsistencies between the satellite-derived sea surface temperature and the ARGO temperature at 5 meters. To address this issue and provide better surface flux information, some ARGO floats are equipped with a second temperature and salinity sensor (STS) that only measures in the proximity of the surface.


How salty can snow/sleet be? Can enough salt particulates be in the air to create salty snow or ice that is undrinkable?

Will ice form in sub zero temperatures through condensation in salty air?

Considering there are evaporation ponds worldwide (San Francisco Bay is full of them, and Morton used to, and may still, have the majority) used for harvesting sea salt, it's doubtful that any salt deposits would end up in the Martian atmosphere. And the atmosphere of Mars is too thin to hold salt blown from existing salt deposits, so salt blown into the atmosphere by Martian dust storms would quickly settle out of the atmosphere.


Why did people draw so many continuous squares in the sand on the beach at Cape Juby? At Cape Juby, Morocco, we can see with Google Maps a rectangle of 3 km long, in which there is hundreds of little squares. What method was used to draw these squares on the sand? More importantly, why are these square drawn?

They are not perfectly straight. Making them with modern GPS equipment should not be too difficult, you just keep a fixed distance to the previous line. They are only 5-6 meters wide.

Googling for cape juby tarfaya sand beach experiment I found this 16 Jan 2013 entry from the blog An overland adventure mentioning:
"Between the road and the sea is another experiment to save Tarfaya from being swallowed up by the Ergs (=sand dunes), mangrove. These trees have been introduced here from the tropics as one of the few salt loving, sand rooting toughs. They seem quite young from the window of the truck so I am guessing it is too early to tell if the project has been a success."

Maybe this is what you are seeing. I have contacted the blog writer to ask for confirmation. Update: The author confirmed that this is indeed what you're seeing: "Yes. Shame there is no picture."

Subsequent Googling for tarfaya mangrove turns up more info (often in French, where palétuvier is indeed mangrove), e.g. this Les mangoves du Sahara chapter from the Book Maroc 8 - Sud du Maroc et Sahara Occidental. This Lonely Planet E-Book PDF Marokko Reiseführer which is almost a literal translation, mentions a 900 meter long strip, but the artifact in the picture is approx 3.2 km.

The planting project was named The Manzanar project


Lake Manasarovar v.s. Lake Rakshastal: fresh-water v.s. salt-water In Tibetan Plateau, about 4600m elevation, If Lake Manasarovar and Lake Rakshastal ("lake of the demon" ) used to be the same lake, but due to the tectonic activity now they are separated to two by small hills, how come Lake Manasarovar is a fresh-water lake while Lake Rakshastal is a salt-water lake?

Before they were separated, was the overall old lake a fresh-water lake or a salt-water lake?

Is that just because Lake Rakshastal is in the Endorheic basin and Lake Manasarovar is not within the Endorheic basin?

Also, Lake Manasarovar overflows into lake Rakshastal which is a salt-water endorheic lake. These lakes used to be part of the Sutlej basin and were separated due to tectonic activity.

You pretty much answered the question yourself.  Lake Rakshastal, along with most of the lakes along the Tibetan plateau is, indeed an endorheic lake.  The important meaning of that term is that there is no outflow from that basin.  Water evaporates, but as with any evaporative process, the minerals in the water stay behind and become more concentrated.  Since Lake Manasrovar flows into Lake Rakshastal, the water that leaves takes the minerals in contains with it, leading to a much lesser concentration left behind as new water flows in, and, most importantly, out of that lake.


How does metamorphism change talc into soapstone? My understanding is that soapstone is talc (hydrated magnesium silicate) which has been metamorphically transformed. However, it is not clear to me how this transformation affects the talc.
What is the difference between talc and soapstone?

Soapstone is a form of talc. It is basically talc plus other minerals, such as micas, chlorite and amphiboles, depending on the initial rocks that were metamorphosed. Soapstone is also called a talc-schist.
Soapstone is formed by the metamorphism of ultramafic protoliths, such as dunite or serpentinite and the metasomatism of siliceous dolomites. The metamorphism occurs in the regions where tectonic plates are present, where the rocks are subjected to heat and pressure, with flowing liquids, but without melting. Soapstone is derived from hydrothemal alteration of peridotite and related ultramafic rocks.


What are the implications of the recent discovery that plants regulate their temperature around 21°C? They told us at school and still keep telling our kids that trees don't regulate their temperature, but in 2008 it was discovered that they do. And to me it all makes sense now. It must have serious implications on urban planning and fight against climate change, what are they?

I am shooting a bit for the hip here to be honest, this answer is opinion, not a researched position, but...

To imply that a object, be it plant, animal, or inanimate object with the ability to self regulate their temperature has the ability to have implications on climate change on a global scale, at least a positive one, ignores the physical laws of entropy.  That statement assumes that by positive effects means slowing of warming.

Entropy as a basic rule of physics always increases.  For this purpose, you can consider entropy to be the total energy in the system, with the energy of concern here being "heat".  If a plant (or anything) raises its temperature, it also extracts that heat from somewhere else.  If the surrounding environment is warmer, it can do that by simply absorbing heat, otherwise it does that by using other energy by chemical or physical processes.  These processes always are net zero in entropy or increase entropy thus increase total system energy usually seen as heat.  The same is true when the plant needs to lower its temperature, it can exchange heat with surrounding environment or through physical or chemical means lower its temperature, but doing so will again either be net zero energy or an increase in energy/heat.

Plants do have an almost exemption of this rule though, they grow, and in doing so the store some energy, temporarily taking some of that energy out of the equation.  This stored energy, and thus heat, is then released when the plant dies and decays, is used as food, or when millions of years of the stored energy is used in the form of fossil fuels, again resulting in a net increase in total entropy in the system.

Plants can and are used for localized climate moderation, but the contribution that would be applied to their ability to regulate their own temperature I would think is somewhere between insignificant and a slight negative in terms of slowing global warming.  The more significant aspect is in areas like slowing ground heating of denuded areas, cleaning pollutants from the air, storing of energy for later use, and many other aspects of plant chemistry and relationship with its environment.  For instance, the shade provided by a single tree I would guess outweighs any effect cause by temperature regulation of many trees.  I would be happy to see any study to the contrary, but I do not see that as possible within the known laws of physics.


Can ultrasounds be used to map the density of large underground regions? This question arose from a related one at Physics.SE, along with my own personal quest to better understand mineralogical prospecting.

I want to know if some kind of ultrasound machine can determine the density of rock, soil, or mountains. Could it see everything within range? For example, could it see a region of high density and a region of low density behind it? Or would one block the other? What would the range be?

And how accurate would it be (in density readings and exact location readings)? More accurate than a gravimetric map?

I'm asking because I want to know if ultrasounds can be used for mineralogic prospecting (exploring for ores that can be mined). It seems like it would be a lot easier to use ultrasounds than to dig a lot of exploratory shafts.

Sound-like waves are routinely used to image the subsurface, but mostly well below the ultra-sound band.

Several methods involve sound-like vibrations:

Reflection seismic — the most important subsurface remote sensing tool we have
Refraction seismic — important, but niche, and has a lot in common with reflection
Acoustic logging — uses ultrasound, which you specifically asked about

What do you mean, 'sound-like'?

I say 'sound-like', because we normally think of sound as a vibration that we can hear, conducted through air or maybe water or building materials. In seismic methods — such as we might use prospecting for minerals, oil and gas, water, geothermal resources, etc. — we use very low frequencies, typically in the 4–256 Hz range (about 6 octaves). You can certainly hear some of these frequencies, but not those below about 20 Hz, which are often the strongest frequencies in our signal.

Why is seismic reflection such a big deal?

From thousands of field recordings, usually shot in a grid over a land or marine area, we can reconstruct an image of the subsurface using a process called tomography. The data might be 2D (a vertical cross-section) or 3D (a volume, analogous to a CAT scan). In some cases, this image is excellent and reveals a great deal about the geology of the region. Here's an example from a paper by Moore et al. (Science, November 2007):

How much can you see?

A large survey might be hundreds of square kilometres, or many tens of kilometres long in the case of 2D data. We can image well down to about 6–8 km, and we can image something down to about 20 km. The typical resolution of seismic is on the order of tens of metres horizontally and a few metres vertically (about a quarter of a wavelength). This is much better than gravity or magnetics. You might think, "Why not use higher frequencies for imaging — surely you'd see more?" Yes! We would love to use ultrasound (say) for imaging. The problem is that high frequencies are absorbed more efficiently by the medium (mostly rock and water) and actually heat it up very slightly.

What can you find out with sound?

In many cases, we can go beyond an image of the subsurface and deduce some physical properties of the earth, especially the speed of sound in the rock and the density of the rock. Sound reflections depend on changes in acoustic impedance, and are dependent on the incidence angle, so all the physics really stems from that relationship.

What about acoustic logging?

Acoustic logging or sonic logging is an important counterpart to seismic imaging, because the logs — run along a borehole using special tools — are the best link between the acoustic properties of the rock. They thus link us to the seismic image that depends on those acoustic properties. So we don't image anything with this data, because it's one dimensional, but it's a key calibration point. Acoustic logging does use ultrasound in the 20 kHz range, but the attenuation issue is not a problem in the vicinity of the borehole.


How does the sand appear on Hawaiian beaches It's quite surprising to me that there's only one beach with black sand on Hawaii (maybe not exactly one beach, but it's only a very small fraction). The concern is, if the whole Hawaii is volcanic, therefore made of frozen lava, the sand should be black everywhere.

I suppose the true reason is that the sand on the beaches is not "made of Hawaii" or "made in Hawaii". However, I wonder how did the white sand make it there?

I think the easy answer comes from the Hawaii Department of Land and Natural Resources:

  Beaches in Hawaii may be made of 'black sand' derived from the erosion of volcanic rocks, of 'white sand' made by marine organisms, or a mixture of both. On the windward side of the Big Island, for example, black sand beaches are very common. The beach at South Point is almost entirely green sand composed of olivine, a common mineral found in the volcanic rocks here in Hawaii. On the Kona coast of the Big Island and on the other islands, the beaches have a range of mixed compositions, some with a high volcanic (detrital) component, some dominated by calcareous (reef-derived) sediment. Beach and submarine sands in Kailua Bay on windward Oahu (my research area) are almost entirely composed of calcarous, reef-derived material. On average, only about 5% of the sand grains are volcanic minerals or rock fragments. Every beach is unique and has its own source and type of sediments.

They even address some of the questions regarding "foreign import" here.


How was Venice flooded? If I understand this correctly, Venice was not flooded due to sudden rainfall causing rivers to overflow, but due to the high tides. These high tides were caused by an alignment of sun, which was expanding the waters of the oceans disproportionately on one hemisphere and moon, which shifted the center of gravity of the moon-earth system in such a way that water rose on the same hemisphere.

In the news articles that I see, they also mention strong winds. This would make sense. High baseline + waves = a lot of water in the city. But in these photos everything seems to be calm. No waves, no wind, just an abnormally high level of water:

https://www.theatlantic.com/photo/2018/10/venice-under-water/574396/?fbclid=IwAR1DWLs_W39ndpdLWLZ1f6wlDDw8ZJmcBqyVM555O9DL5a_DhuY0mPQDi38

For me this doesn't make any sense. If the winds subsided and the flooding was caused purely by tidal effects, which are astronomical events, shouldn't it have been predictable months, if not years in advance?

Venice can't really be flooded by rivers, since there are none worth mentioning throughout the city.
High tides are predictable, yes.
Take a look at how Venice is situated. The historic city is sheltered behind low sandbanks/islands, which form the foremost coastline. Still the laguna is - obviously - connected to the open sea. Meaning: Huge waves, like in the open sea, wont rush through the city's channels, since they are dispersed by these islands. Still, in some images the water is quite choppy - a sign for rather windy conditions. Furthermore, all the houses of the city act like additional "islands", calming the surface of the water by dispersing larger waves into smaller and smaller ones. However, wind does not only create waves, it pushes the water also into the direction it is blowing to. In case of the Scirocco, which blows from northern Africa across the Mediterranean right into the Adriatic Sea, at which northern end Venice is situated. Thus, this wasn't simply a high tide, it was a spring tide, a combination of favourable planetary alignment and wind conditions. And, as already commented, winds/weather are quite hard to predict.

The whole process actually has a local name: "Acqua alta". It is nothing new, simply the intensity was noteworthy.


What lithologies are deemed most suitable for the storage of nuclear waste I have visited storage- and test facilities that are within salt and clay (Opalinuston) lithologies. What are other lithologies that are considered for the storage of nuclear waste and what are their advantages?

Nuclear wastes should be stored in containers designed to contain and isolate radioactive material from the environment. One possibility for the storage of these containers would then be to place them in a repository located in a tectonically stable, dry, geological formation.

As far as lithological characteristics are concerned, it would be best to locate the container repository in rock having mechanical and chemical properties that would limit transport properties and slow or contain the spread of material in the event of a container failure.

Advantageous properties include:

1) low permeability and few joints and fractures

2) low strength, so that plastic deformation of the rock would tend to reduced stress and close fractures.

3) mineralogy-fluid chemistry that tends to bind and immobilize radionuclides.

Volcanic tuffs (zeolite-rich), salt deposits, and clay deposits would be examples of lithology having some (but not necessarily all) these characteristics. Granites and columnar jointed basalts may be examples of less advantageous lithology.

As @david valentine said, the lithology would be only one of many factors that need to be considered.


How reliable would measuring global heating from satellite be? Some anthropogenic global heating (AGH) skeptics deny that any global heating is occurring. I figured out a way that could be used to refute them. A weighted average of all of the thermal points on the Earth could be computed on a daily basis. These thermal points are obtained from thermal images.

These points would be satellite resolution distance apart. This would provide an actual measure of global heating. We could subtract out the effects of cities and volcanoes by simply ignoring every value above a certain threshold. One example of such a threshold would be the average of all of the points for that day.

Would this be a reasonable way to double check the trend of global temperature anomalies?

Measuring long-term temperature trends from satellites is possible, but difficult due to a variety of reasons.

This is ongoing research.

In short: the satellites that have been around long enough were built for measuring weather, not climate, and the standards to which instruments need to be built to measure one are entirely different from the other.

We have had satellite measurements of the atmosphere since the 1960s, and operationally since the late 1970s.  Those have always included infrared radiometer measurements, which means that, in principle, we can construct a record of surface (both land and sea) and atmospheric temperatures for the past 40 years at least.  The sensors themselves aren't very complicated — but to determine a trend we would need to be very confident about their uncertainty, stability, and inter-satellite variability.

If you were to simply take 40 years of HIRS infrared measurements and plot them, you don't know if the changes are due to atmospheric or instrumental changes.

From 2015 to 2019, I was part of the FIDUCEO project which aimed to bring the science of metrology (science of measurement) to satellite observations.  Taking 40 years of AVHRR (for sea surface temperature) or HIRS (for atmospheric temperature and humidity) measurements, with 16 different editions of the instrument over a period of 40 years.  But AVHRR was built to look at pictures of clouds.  If you look at pictures of clouds, the user doesn't care if one satellite has its pictures 0.5% brighter than the previous one.  They just tweak their monitor a bit!  But if you take the global climate system, then that corresponds to more than 1K temperature difference, which for the oceans, would be huge.  In FIDUCEO, we aimed to:

Develop a metrology of Earth Observation
Produce Fundamental Climate Data Records (FCDRs) for various operational meteorological instruments in visible, infrared, and microwave, meaning:

Per-datum metrologically traceable uncertainty characterisation;
Per-datum information on correlation structures: which component of the error estimate cancels out when averaging and which component remains;
Harmonisation between the various satellite sensors.

Here are 40 years of HIRS (versions 2, 3, and 4), on which we tried to do some harmonisation.  The top panel shows global average brightness temperature per 24-hour period, as measured by channel 2 which IIRC peaks somewhere in the stratosphere, so this would correspond roughly to an atmospheric temperature somewhere up in the stratosphere (which, incidentally, is cooling as the Earth's surface is warming):

The different colours indicate different satellites.  As you can see, there are both jumps between satellites, and trends within one satellite.  Some of this is expected, as polar-orbiting sun-synchronous satellites have a drifting local equator crossing time, but some of it is due to instrumental problems.  Some of those problems are captured by the structured uncertainty in the bottom panel, but not all of it.  The data only go back to the mid-1980s, because before that, there weren't enough overlaps to constrain the differences between subsequent pairs of satellites based on simultaneous nadir overpasses (SNOs).  For satellites in the early 1980s and late 1970s, the coefficients to calibration the thermometres measuring the temperature of the on-board calibration target appear to have been lost.  For the earliest satellites the header data does not match available documentation.  Software to produce this figure is on Github, raw source data are available from NOAA CLASS, some processed data from FIDUCEO.

This is for a global average.  To do this regionally would add additional complications.

The CLARREO programme is proposed to be the first in-orbit SI reference for accurate calibration.  Had we had that for the past 40 years, our job would be easier.  But CLARREO is still waiting for funding.

So the answer to your question is: with what we have now — not good enough — yet.

But if you are contemplating a career in satellite techno-archeology, I recommend it.  It's great fun.


Net fluxes of carbon caused by humans The current and future amount of carbon (in the form of carbon dioxide) in the atmosphere and the hydrosphere is what currently concerns and occupies many people.

I am looking for a big picture of the net fluxes between different carriers of carbon that gives a good idea where the anthropogenic CO2 emissions (and other greenhouse gases) actually did come from (compared to e.g. 1500, 1800, 1900, 1950 and 2000).

So I am looking for rough (and possibly estimated) numbers like these - optimally in an overview, so the numbers sum up to 100:

p1% by fossil fuel burning
p2% from the natural biosphere (which decreased), esp. deforestation
p3% from cultivated biosphere (which increased), incl. methane emissions from cattle
p4% from industrial abiotic chemical processes, e.g. cement production
pk% other important sources with pk > 1%?
p6% other?

There are various charts but not exactly what you want. This one combines burning, industry and cement but shows land sources and sinks separately:

CarbonBrief,  Le Quéré, C. et al. (2016)


Evaporation loss formulas A while ago I created a spreadsheet to calculate evaporation loss. I found several formulas to do that, two from Kevin Rafferty and one from Engineering Toolbox. The one from Engineering Toolbox was too convoluted, and I couldn't figure out how to write it in Excel. The ones from Rafferty were fairly straightforward, but the two he published were different and yield different results.

The first is from Kevin Rafferty, P.E., Pond Heat Loss, 1986:

$$ W_p=\frac{(1 + 0.225v)/0.018}{85.74 \times (T_s+460)} \times (P_w-P_a) \times 144 \times A $$

Where:

$W_p$ = Rate of evaporation in lbm/h
$A$ = Pond surface area in ft$^2$
$v$ = Air velocity in ft/sec
$P_w$ = Saturation vapor pressure of pond water in psia
$P_a$ = Saturation pressure air dew point in psia
$T_s$ = Surface temperature °F

The other is from Kevin Rafferty, P.E., Tonya Boyd, Aquaculture Information Package, 1998:

$$ W_p=(0.097+0.38v) \times (P_w-P_a) \times A $$

Where:

$W_p$ = Rate of evaporation (lbm/h)
$A$ = Pond surface area (ft$^2$)
$v$ = Air velocity (mph)
$P_w$ = Saturation vapor pressure of pond water (psia)
$P_a$ = Saturation pressure at the air dew point (psia)

$P_w$ is calculated by the formula

$$ P_w = 6.11 \times 10^\left({7.5T_s}/{237.3 + T_s)}\right) $$

$P_a$ is calculated by the same formula except that the dew point temperature in °F is used in place of $T_s$, so the pond surface temperature is used in both main formulas, except that in the second formula it is used to calculate the pond saturation vapor pressure.

The spreadsheet file can be found here.

Does anyone have any idea which is the more accurate?

There isn't much to choose between them. They are both variants of the same general equation. They both take account of the three main variables: temperature, rate of advective removal of moisture (proportional to surface wind velocity), and difference in vapour pressure (which can be related to humidity). In countries using SI units there are several other evaporation equations along similar lines Some other equations do not take adequate account of advection (the 'v' parameter), and hence I would advise against using such equations.
Strictly, the best equation, favoured by FAO, and in a slightly modified form by the American society of Civil Engineers, is the classic Penman-Monteith equation:

from https://en.wikipedia.org/wiki/Penman%E2%80%93Monteith_equation
But this is a pain to calculate, so most people, including myself, put it in the 'too hard basket'.
Whatever equation you decide to use on your spreadsheet, be aware of potential errors from ground conduction (underestimate of E), higher salinity (depresion of E), and boundary effects, especially in areas of high advective exposure.


On La Vagabonde what Citizen Science is Possible? The Catamaran La Vagabonde is a high tech vessel that's designed to be as carbon neutral as possible.

Subject to the constraints of space, time and safety, what citizen science projects would be possible on this vessel?

Ok, trying an answer. I don't know if citizen science is actually done. Possible would be sample collection, physical data (water temperature, air temperature), weather conditions, sigthings of rubbish, animals or unusual phenomena. Actually, before the space age ships collected and exchanged weather data to produce on ship weather charts for example. Afaik, this is not practical any more, merchant ships anyway and increasingly recreational vessels (if the owner can afford) have satellite data and internet on board.

Data collection in itself is no problem, but the calibration to make them comparable and combinable is. In simple words, one can't just buy a thermometre and bind it to the mast, they'd differ by a lot. Recreative vessels have their routes on the oceans. In Atlantic terms, now (November) they set out in hundreds and thousands into the Caribbean, in spring some them return (the northern route is more strenuous ;-)). There is not that much to be had science wise because they all measure similar things (in between the sunbathing on their catamarans).

And, there actually is concern that too much citizen science could leave a negative carbon footprint.

Something to read: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4159111/


Latitude and Daylight Hours What is the relationship between the latitude and daylight hours for each season?

When I interpret the answer for the question, I believe the number of daylight hours decreases as the latitude increases as fall goes to winter. Then, when winter goes to spring, and spring goes to summer, the daylight hours increase as the earth rotates. Though, my answer is vague, in my opinion.

This tool lets you determine daylight hours from latitude for any day of the year.

I feel like this answer should be longer, but there is not much more to say.


How is heavy rainfall determined in National Climate Assessment I'm trying to understand/reproduce/revise this chart in the Southeast section of the United States National Climate Assessment. The truncated scale for the bars is what caught by eye as a classic chart lie, but I'm also wondering about other features: different thresholds (besides 3 inches) and different aggregations (besides decades).

Original caption for this chart plus a map next to it:

  Figure 19.3: The figure shows variability and change in (left) the
  annual number of days with precipitation greater than 3 inches
  (1900–2016) averaged over the Southeast by decade and (right)
  individual station trends (1950–2016). The number of days with heavy
  precipitation has increased at most stations, particularly since the
  1980s. Sources: NOAA NCEI and CICS-NC.

The vague source citations are not particularly helpful, but I did find NOAA's Global Historical Climatology Network Daily downloadable data. That has daily precipitation data for 100,000 stations around the world, with about 12,000 in the Southeast. However, in a given year, I'm seeing 100 to 200 days with precipitation above 3 inches, but the chart indicates a different order of magnitude.

What does "days with precipitation greater than 3 inches" mean in this context?

I'm guessing there must be a "per station" part to it, but I still can't guess the exact math. The simplest treatment, a weighted average of each stations rate of heavy rain, produces the chart below.

It's close (same order of magnitude and peaks in 40s, 70s and recent), but not quite the same. Is there a different data source? Or a different treatment for irregular samples? Or a way to account for increasing number of stations?

Update after comments:
If I filter on stations with at least 110 years of data and use only years with 200+ days of data, I get the following, which is closer. (Using the same scale as the original, but avoiding bar truncation by just showing the tops.)

Most decades have lower values than the original.

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

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

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


Will the Earth's core cool? I am doing a school project and need to know...

Will the Earth's mantle or core ever cool? If so, how?

Thank you!

Yes. It's kept warm by slowly  decaying primordial radioactive elements. They are: Uranium (238) and Thorium (232). The half life of the first is 4.4 billion years, the second around 14 billion years.

They heat the surface even to this date, and it's around 0.2K warmer than if they were absent.

Owing to their continued decay, this temperature differential will decrease .

Extension: On the most popular models (and David Hammen's comment :-) ), Uranium and Thorium are in the crust and   mantle, and not in the core. Despite that, their radioactive decay heats the Earth.


What is a Micro-Aethalometer; how do portable Black Carbon (BC) Monitors work? The screenshot below is from MIT's Erik Velasco's presentation Particle exposure and dosage on public transport. My question is about the small, portable Black Carbon (BC) monitor.

From my reading, Black Carbon refers to mostly carbon particles, mostly produced in natural and anthropogenic combustion processes (e.g. forest fires, vehicles...). Unlike most of the particles that fall into the PM10 and PM2.5 classifications, it seems that a very important fraction of BC comes from very small particles of the order 0.1 microns since they are formed during a short time during combustion.

0.1 micron particles are hard to detect using laser scatterometry since they scatter very weakly compared to the larger particles, and the size of the portable meter shown seems quite small for an advanced scatterometer.

Question: How do small, portable Black Carbon (BC) Monitors work? I believe this one is called a Micro-Aethalometer in the presentation; what basic principles do they use to quantify BC in the air that fits in such a small form factor?

From Particle exposure and dosage on public transport, open image in new window for full size.

From The Aeroflex: A Bicycle for Mobile Air Quality Measurements, Bart Elen et al. Sensors 2013, 13, 221-240; doi:10.3390/s130100221 open image in new window for full size.

Following @ Friddy's comment, I started reading Aethlabs AE51 FAQ and was quite surprised!
While a conventional aethalometer use a long tape and move it to the new position after each measurement (which could be as fast as one measurement per minute), the compact device shown in the image in question uses a single filter position, and just keeps measuring as it gets darker and darker as black carbon collects.

Q: Do all the microAeth use the same filters?
A: No. The microAeth AE51 uses a T60 Teflon-coated borosilicate glass fiber filter strip which has 1 sampling location and must be manually replaced. The microAeth MA200 uses a roll of Polytetrafluoroethylene (PTFE) filter material housed in a filter tape cartridge which has 15 sampling locations that can automatically advance. The microAeth MA300 and MA350 use a roll of Polytetrafluoroethylene (PTFE) filter material that is housed in a filter tape cartridge which has 85 sampling locations that can automatically advance. Filter tape cartridges have to be manually replaced much less often than a single use filter strip.

Also:

[...] A guide for measurement limits regarding saturation can be found on the AE51 Specifications Sheet. For example, filters need to be changed according to the following BC concentration/flow rate ranges:

 - Avg.   5 µg BC/m3   for 24 hours    @ 100 ml/min
 - Avg. 100 µg BC/m3   for  3 hours    @ 50 ml/min
 - Avg.   1 mg BC/m3   for 15 minutes  @ 50 ml/min

Compare this to a conventional aethalometer:

Source

Source


What geological mechanisms result in the great depth of the Mariana Trench? According to the Mariana Trench Oceanography page is at a maximum depth of

  is 11,033 meters (36,201 feet)

The 'Challenger Deep' being the name of the deepest point.

I understand that it is a subduction trench, but my question is, what geological mechanism result in the great depth of the Mariana Trench over other trenches?

As taken from Wikipedia:

There are several factors that control the depth of trenches. The most important control is the supply of sediment, which fills the trench so that there is no bathymetric expression. It is therefore not surprising that the deepest trenches (deeper than 8,000 m (26,000 ft)) are all nonaccretionary. In contrast, all trenches with growing accretionary prisms are shallower than 8,000 m (26,000 ft).
A second order control on trench depth is the age of the lithosphere at the time of subduction. Because oceanic lithosphere cools and thickens as it ages, it subsides. The older the seafloor, the deeper it lies and this determines a minimum depth from which seafloor begins its descent. This obvious correlation can be removed by looking at the relative depth, the difference between regional seafloor depth and maximum trench depth. Relative depth may be controlled by the age of the lithosphere at the trench, the convergence rate, and the dip of the subducted slab at intermediate depths.
Finally, narrow slabs can sink and roll back more rapidly than broad plates, because it is easier for underlying asthenosphere to flow around the edges of the sinking plate. Such slabs may have steep dips at relatively shallow depths and so may be associated with unusually deep trenches, such as the Challenger Deep.

A simple picture for anyone who doesn't understand how these trenches form:

(source: wikispaces.com)
Also, the Mariana Trench isn't the only super deep trench in the ocean... 10 deepest parts of the ocean


What does mean "background" in statistics or geostatistics? somebody told me it was a bottom value , but I still don't get the whole picture.

Note: Since there is more than one use case of background in geostatistics, I will pick only one. If this is not the right background you are looking for, please edit and clarify your question.

Answer: A data point can be given by an absolut value A or a background value B plus a deviation D where B + D = A.

Example: If you are looking at a map showing the mean temperature of year X, you can look at the absolute field A or on its deviation D from the climatological year mean temperature of 1961-1990 B. Sometimes the latter tells you more, depending on what you are interested in. Additionally, analyses and statistical methods are often applied to the deviation field instead of the absolute field to identify patterns.


What does "rapid" mean in terms of igneous rock formation? Specifically, what time period would it take for obsidian as opposed to basalt, to form? (I need to know how much faster obsidian cools than basalt.)

Obsidian is volcanic glass of felsic composition (i.e. SiO2-rich) whereas basalt is a volcanic rock which may or may not be (partially) glassy of mafic composition (i.e. SiO2-poor). So when you're saying

  obsidian as opposed to basalt

...you're comparing apples and oranges. So instead of discussing obsidian versus basalt, let's discuss phaneritic versus aphanitic versus glassy rocks, in the context of being melted by dragons (because that's what you're asking in your question).

Phaneritic rocks are those with coarse crystals, easily observable to the naked eye. The best example is granite, like the stuff you see in pavements and kitchen tops. These rocks form by slow underground cooling so this is not something that dragons can make.
Aphanitic rocks are those with very fine crystals that are only visible with a microscope. Basalt is the most obvious example. To the naked eye they may look like glassy, but they do not have the characteristic conchoidal fractures you see in obsidian.
Glassy rocks (that I'm pretty sure have a fancy name that starts with hyalo, I just can't remember what it is) have no crystals in them so they're basically glass. Obsidian is the best example.

Note that there could be combinations of those, just to confuse you even more: for example you can have aphanitic rocks with large crystals of minerals (known as porphyritic textures) or a rock that's mostly glass but has some crystals floating around in it.

When you have dragons melting rocks, the cooling of the rock is done very rapidly in air. This can be minutes to hours, depending on the size of the block being melted. This is definitely rapid enough to form rocks. But, the final form of the rock also depends on the chemical composition. Felsic rocks have very high viscosities and low diffusion rates, and even relatively slow cooling (days?) can form obsidian. That's actually the reason that obsidian is most common in felsic rocks. Mafic rocks, on the other hand, require very rapid cooling to form glass (for example, erupting into water), and even then they make have some "quench" crystals of olivine or pyroxene.

Felsic rocks also have lower melting points than mafic rocks. This all leads to the conclusion:

Yes, dragons can make obsidian, and it's quite easy

Take a granite (or even sand-bearing mud), melt it with some dragon fire, and let it just cool. The high SiO2 content will make the melting point rather low (let's say below 1000 °C). The high viscosity will ensure that it stays where it is rather than flow somewhere else (think of basalt flows of Hawaii versus Mt St Helens felsic lava domes). Obsidian will surely form.


How big was the eye of the El Reno tornado? As far as I know, the EF-3 El Reno tornado is by far the largest tornado since meteorologists have started observing them. Tornadoes also have eyes, like hurricanes, but are way too small compared to hurricanes. The El Reno tornado should make an exception, as it was 2.6 miles (4.2 kilometers) in diameter. But what about it’s eye? Can it be compared to a small hurricane, like Tropical Storm Marco? Even as the smallest hurricane, it’s still about 3.5 times the size of El Reno, so would their eyes have about the same ratio, or maybe a completely different ratio?
P.S. A cyclone, a hurricane, and a typhoon are pretty much the same thing. I just use hurricane because I live in America.
This is my fist question, so Im a little nervous :)

There is no eye in the centre of a tornado's funnel, if we see the eye as a near circular cloudless area from bottom to tropopause, surrounded by a wall of towering clouds. Some interpretational leeway may lie in the low angular windspeed in the centre of the vortex, but that is not comparable to a hurricane's eye. Force of the central updraft is still strong enough to keep debris in suspension.
A vortex forms from updraft, warm air including 'macroscopic particles' is sucked into the cloud, while a hurricane's eye forms because of sinking air in the centre of a much larger and longer lasting storm system. There may, though, be water spouts under the individual thunderstorms of a hurricane's eyewall. Cause for rotation of a hurricane is coriolis force, while the vortex rotation is thought to be caused by vertical windsheer in the horizontal inflow. Hurricanes gain their energy from warm sea water, while thunderstorms are caused by vertical labilization of the atmosphere along a frontal line.
Here's a publication about the El Reno tornado. No structure that could be interpreted as an eye can be found in the interpretation of the radar data (Figure 15), and there's still a huge black thundercloud right above it.
Thunderstorms with tornados and tropical storms like hurricanes and typhoons are fundamentally different in how they form and evolve, their size and structure, much information on both phenomena can be found on the internet.
And, btw., TS Marco 2008 didn't have an eye either, I believe.


Why doesn't subducted earth crust melt? If you take a look at a typical picture tectonic plate subducting under another plate, the subducting plate is always drawn as deep (seemingly tens of km) into molten rock, but the subducted part of the plate itself is not molten. Why are the subducted plates not drawn as shallower into the magma?

My logic looking at this is the following: the surrounding medium is hot enough to melt rock. Alright, rock may take time to melt. A typical continental plate moves 10cm/year which yields 100,000 years / 10km. Is an order of a hundred thousand years really not enough time to melt that subducted plate? Why are so many textbooks drawing it subducted and unmelted to such depths?

...the submerging plate is always drawn as deep (seemingly tens of km) into molten rock...

It's actually hundreds of kilometres, not tens of them. But let me correct a common misconception:

The mantle is solid rock. It is not molten rock.

So subduction leads solid rock into more solid rock.

  the surrounding medium is hot enough to melt rock

The surrounding medium is hot enough to melt rock only under very special circumstances, the two most common being:

If the rock gains water somehow (yes, water under pressure helps rock to melt), or
If even hotter rock from down below rises up and decompresses.

  Why are so many textbooks drawing it submerged and unmelted to such depths?

Because it doesn't melt. The subducting plate goes down faster than it heats up. Therefore, pressure increases faster then temperature. This does not allow melting of the subducting slab.

What does happen? The slab loses water. Remember - this was oceanic crust and it's wet. On moderate heating, the water from hydrous minerals (serpentine etc) is lost to the mantle rocks above it. Because the mantle rocks above the slab are hot, the addition of water causes them to melt. We see this all the time in the form of arc volcanoes. The Pacific "rim of fire" is the most famous example of this process.

I would say that some very limited amount of melting may actually happen, but in terms of volume % of the entire slab it's likely to be negligible. The contribution of this melting to global volcanism is also likely to be negligible.


Does WRF simulation use sigma or eta vertical coordinate system? Could you tell me what the  WRF's vertical coordinate system is? Sigma or eta?

According to the User WRF Guide document, uses a terrain-following hydrostatic pressure coordinate while the WRF namelist has eta level. Are both of them same?

WRF is using the sigma (terrain-following) vertical coordinate. However, as @gansub has already referred, in WRF V3.9 you can now select a hybrid sigma-pressure vertical coordinate. The advantage of this is that the coordinate is terrain-following near the surface, but it 'converts' to pressure levels at higher levels, which improves the accuracy of the calculation of the pressure gradient. Over very steep terrain the sigma coordinate extends this steepness throughout the atmosphere which is not very ideal.

For sigma coordinates, you still define the eta-levels. (Note that it sigma coordinates is just a normalisation of pressure)
$$
\sigma = \frac{p-p_t}{p_s-p_t}
$$
where $p$ is specified through
$$
p=A+Bp_s.
$$
It has been a few years since I played around with WRF, so I don't know how this change affects computational efficiency. If you get any results on this that will be interesting to hear.


Earthquake database for fault I am trying to understand Deterministic Seismic Hazard analysis for which I believe seismic waves corresponding to a seismic sources (such as faults) are required to prepare the Gutenberg Richter curve and select an appropriate earthquake corresponding to a particular return period. However I do not know from where I can obtain the seismic data?

Perhaps the Global Significant Earthquake Database request form from NOAA would help?


What's the minimum number of days needed for reporting a "monthly average" of daily satellite retrievals? NASA's Earth Observing System produces many maps of air quality and land-surface variables, from instruments like MODIS, AIRS, OMI, VIIRS, etc.  Both NASA and the scientific community produce maps of the retrieved data on a daily basis, but there are often gaps (e.g.  no data) for many locations because of clouds, satellite coverage, or other limitations.  Daily retrievals are often averaged by month or season so that a complete global map (or sub-region) can be made and then presented to the public and put into publications.
Some locations have very few retrievals available for a monthly average (e.g. if there is a predominant cloud mass that sticks around for a long time).  So, researchers must choose some threshold where no data is reported.  As a graduate student, I would report the average if I had at least 4 days in the month, which seemed reasonable to me at the time for some reason.  However, the number of available data points for a monthly average fluctuates so much, that the minimum number of members in the monthly average that I chose affected my temporal trendlines.
What's the minimum number of days needed for satellite-derived maps of monthly averages?  I can't call 3 days of data a "monthly average" in good faith, but is 4 days enough?  For the purposes of this question, assume there is only one possible data retrieval per day per geo-location.

Provide a monthly average in every grid cell, and describe how many measurements were used for each cell.

There is no fixed rule for the minimum number of days for reporting a monthly average.  A reasonable threshold will depend on the geophysical quantity of interest y, in particular on how much y varies on short and long timescales.

If y varies from month to month, but does not vary a lot from day to day (example: sea surface temperature), you can probably get away with reporting a monthly average even when only one or two days have cloud-free measurements.  On the other hand, if you're measuring precipitation, your signal will be relatively noisy even if you choose a threshold of 20 days.  And any threshold is going to introduce a bias, because a lack of observation is typically due to clouds.  Although you will get a bias in any case.  In other words, if you only have one day per month you see a gap and in the clouds to observe whatever you want to know, it is a pity to throw it away.  Therefore, personally I choose a minimum of 1 observation.

Critically important though: when releasing the product, add a field that tells the user how many days worth of measurements make up the monthly average in any given cell!  Like that, the user can decide which ones to use and which ones not to use.  More broadly speaking: producers should document everything they do.

For your specific examples: search for the ATBD and/or scientific papers describing the product.  Hopefully, there is a field in the level-3 product that describes the number of measurements per cell.  If the answer is not in there, write to the producers and tell them to redo the product...  You will need this information to accurately calculate a yearly average!


What is this big Black Mass in Syria, as seen on google maps? What is this big black dot on the satellite view of google maps, located in Syria at about 4:00 from Damascus?

This is the Al-Safa Volcano in Syria. According to Wikipedia it last erupted in 1850 AD.