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Atmospheric aerosol particles affect atmospheric radiation and air quility, and there are various size particles in air. Humidity, gravity, air velocity and other fators may influence particles state (aggregate/agglomerate, disperse,sedimentation etc.)
Are there physical models to interpret the state of atmospheric particles?
I sincerely hope you can help me. Thank you!
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Dear Zhao Shu
I have just a few additional observations after a very brief reading of the papers suggested in this discussion thread.
The physical model that we can employ to describe a population of atmospheric aerosol particles is rather complex because it is based on the stochastic coagulation equation of Smoluchowski imbedded in the advection diffusion equation taking into account transport processes. At the same time, we need to keep a track of the internal composition of particles which include solid cores and liquid surrounding, in both cases the chemical composition is not simple. According to my review of the recent literature, a complete model is still beyond our reach. The nature of the aerosol system indeed indicates that the nature is too complex to admit anything but approximations to paraphrase the well known statement of John von Neumann.
Considering the above, I would like to suggest the following review by Riemer et al. (2019): Aerosol Mixing State: Measurements, Modeling, and Impacts
The text is available at:
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Why did bio-aerosols not become a commercial alternative to silver iodide in cloud seeding?
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Going to investigate the use of SNOMAX for cloud seeding here in the West USA.
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I know that some people used a simple index to define the Hadley cell intensity, which is the maximum value in the meridional mass streamfunction within the Hadley cell. However I am wondering whether this definition is too simple, if the meridional span of Hadley cell shrinks due to some reason, could we say that the intensity increases at the same time? Any alternative definitions?
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We have looked AOD data from aeronet site. However, we found a large amount of data is missing for different stations of Nepal. Do you aware of some satellite data for AOD over the regions of Kathmandu? If yes, please let us know the website for data download. Thank you.
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You can use the website of the Eurpean Center to get the required data
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Dear researchers, I want to plot some rainfall trends at different areas of Nepal. Where can I download data for that? Website of Department of Hydrology and Meterology shows that we should buy data from them. I would be very happy to access data freely from any other websites. Thanks.
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I tried to estimate the correlation coefficient of AOD with water precipitation, and AOD with visibility for a short period of time. I found that for a long term data set, researchers have also measured good correlation at polluted cities. I am curious why it gives less correlation value, if we perform our study for a few months data?
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Dear @Sujan Prasad Gautam
Thank you very much.
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Discussion of the state of art on the application of the Ertel's potential vorticity theorem in atmospheric physics & physical oceanography.
Prof. H. Ertel generalized Rossby's work proposal of 1939. Prof. Rossby firstly proposed that instead of the full three-dimensional vorticity vector, the local vertical component of the absolute vorticity is the most important component for large-scale atmospheric flow.
Via an independent paper published in 1942, Prof. Ertel identifying a conserved quantity following the motion of an air parcel proved that a certain quantity called the Ertel potential vorticity is also conserved for an idealized continuous fluid.
Several links to check on the topic powered by ResearchGate:
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A very complete review on Ertel potential vorticity theorem, thank you for suggesting its reading, Prof. Aref Wazwaz .
Best Regards.
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What does this sentence mean related to atmospheric physics" Because zenith radiance does not have a one-to-one relationship with optical depth, it is absolutely impossible to use a monochromatic retrieval.?
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Alastair Bain McDonald , thanks a lot for the reference. Ronald Scheirer was correct with his explanations, but the inhomogeneity and the multiple solution problem associated with it are also mentioned by the authors.
Wiqas Ahmad , one can (should always) consider the remote sensing problem from the point of view of the information content carried by the detected photon. If the photon is directly related to the observed phenomenon, there are high chances that we will retrieve the corresponding properties. If it is linked to the phenomenon only indirectly, the chances are smaller. And of course if the detected photons come from another part of the atmosphere or are caused by a different physical phenomenon, we have no chances. This is a trivial stuff, but it's good to have it in mind when designing a new experimental setup.
Marshak et al. (2004) propose a smart idea of combining two channels, knowing that the spectral behavior of thin and thick clouds is different and that one can use a spectral contrast to distinguish them.
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Is there any effect of Coriolis force in the current of E or F region of ionosphere?
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A related question is whether or not the Coriolis force is strong relative to other forces that a charged particle experiences.
Normally, the electromagnetic forces on a charges particle can be summarized as F = qV X B + qE, where F is force, q is charge, V is velocity, B is magnetic field, and E is electric field.
The Coriolis force on a particle of mass m is 2 m Omega X V.
So we can form two dimensionless numbers giving the ratio of the Coriolis force to the Lorentz and electric forces
D1 = (2 Omega m)/(q B) and D2 = (2 Omega V m)/(q E).
If either D1 or D2 are greater than 1 then the Coriolis force should be very important. If both D1 and D2 are very small, then it isn't.
Anyway, that is my thinking, and I'm happy to be corrected. We can plug numbers into these equations for the ionosphere, but right now, I'm going to bed for today. Thoughts on this are welcome.
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remote sensing
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They are absolutely different. DN is the digital numbers recorded in the raw data satellite data. DN values are converted into radiance and further reflectance values. Both the two parts (atmospheric reflectance and surface reflectance) are contained in the top of atmosphere (TOA) reflectance. Atmospheric reflectance is the sum of reflectance of aerosols and Rayleigh contributions.
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I've calculated Direct Aerosol Radiative Forcing(DARF) values (W/m2) for Ahmedabad and Gandhinagar City, Gujarat, India using SBDART Model (AOD values as an input) at Top Of Atmosphere (TOA), Surface (Surf) and net Atmospheric Radiative Forcing(Atm).
Please let me know how to interpret these values and how to further analyse the data.
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Hi... Yash
Aerosol Direct Radiative Forcing (ADRF) depicts the scattering and absorption of solar radiation by aerosols. the positive values of ADRF indicate the warming and negative values indicate the cooling.
I hope that you have calculated ADRF using up and down radiative flux values. SBDART only provides up and down radiative fluxes later you have to calculate radiative forcing using those values. This method is already published by the many aerosol experts. You can refer to those publications.
Estimated TOA and SFC ADRF indicated the change in flux at TOA and SFC by aerosols. ADRF in the ATM indicates the change in flux within the atmosphere.
Further, you can more clearly associate these estimated radiative forcing to the climate by calculating heating rate. heating rate depicts the warming of the atmosphere. This can easily associate with regional or global climate change.
Herewith I have given you a very basic idea, but I will suggest you to read the related publication and their interpretation. This will give you more idea.
Hope this will help. Feel free to ask me, if you have anything
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Unlike Optically thick clouds, Cirrus Clouds are thin, high altitude clouds formed in the upper troposphere layer of the Earth's Atmosphere. These Cirrus Clouds are not easily identifiable in the satellite images acquired with Passive Remote Sensing Sensors such as Landsat MSS, TM, ETM+, ASTER, SPOT, etc. Although there are different kinds of Cirrus Clouds, the sub-visible Cirrus Clouds are particularly of interest because they can be hiding in plain sight and affect the measurements. However, they can be detected within the Short-wave infrared (SWIR) portion of the electromagnetic spectrum, specifically at ~1.38 µm bouncing off of the ice-crystals in these clouds but are absorbed by water vapor in the lower part the atmosphere. Due to the benefits of this wavelength at 1.38 µm, MODIS (1999 onwards), VIIRS (2011 onwards), Landsat 8 (2013 onwards) and Sentinel 2 (2015 onwards) were introduced with their respective Cirrus Cloud detection bands.
However, in the absence of Cirrus detection bands in passive satellite sensors operating before 1999, is there anyway to pin-point the presence of Cirrus Clouds in historical satellite images? It may be possible to identify Cirrus Clouds in satellite images acquired without cirrus band by comparing it with contemporary/concurrent satellite images acquired with sensors having cirrus band. But otherwise, is there any other alternative way? Is anybody aware of any operational tool/algorithm/products that can identify cirrus clouds in past satellite imagery and provide means for their masking/correction?
This topic may be of particular relevance in time-series studies where historical satellite images are frequently compared with the present. For example, if cirrus scattering affects are not corrected, they can lead to incorrect interpretation in Vegetation Indices such as NDVI.
Sources:
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It really depends on the type of imaging. If, as mentioned before, there is spectrally resolved information, one can make use of the fact that the contribution functions of some channels peak at different altitudes and apply some kind of minimization technique (e.g. see our algorithm for IR sounders https://bit.ly/2VAG2NZ).
However, if the image was obtained only at one wavelength or the contribution functions are too broad or they do not "scan" the whole altitude range then it's more difficult. One can train neural network using this kind of images and a combination of active and passive sounders (e.g. AIRS + CALIOP) serving as a reference, but it's easier to say than to make :)
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Dear researchers,
I'm looking forward to evaluating future wind projection on the Gulf of Oman (or Oman sea) by using Regional Climate Models (RCMs) from CORDEX project, WAS-44 domain and three emission scenarios ( RCPs 26,45,85) for 2020-2050 period of time. Reviewing the literature, I understand it is better to use as many simulation as possible, ensembles of simulations. For that area, uas/vas data generated by following driving models are freely available:
  • ICHEC-EC-EARTH
  • MIROC-MIROC5
  • MOHC-HadGEM2-ES
  • MPI-M-MPI-ESM-LR
  • NCC-NorESM1-M
Knowing the fact that difference in underlying physics in climate models leads to systematic errors in the outputs (bias), I wonder by which method I should correct the final results and perform an uncertainty analysis.
Also, I would appreciate if you could provide me with your comments on selected wind models. Should I include simulations from CMIP5 project as well?
Thank you in advance,
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Dear Amirmahdi Gohari ,
I agree with Miyuru Bandara Gunathilake. Nevertheless, to have an effective evaluation of future wind in the Gulf of Oman, it would be good if you consider at least some of the following points:
1) You are looking for 'Decadal Variability', so some general statistical bias correction methods are not applicable to this long-term climate variability.
2) As Sea Surface Temperature (SST), affects crucially the wind pattern through moist-convection and potential temperature variability (both in zonal and meridional direction), so the applied coupled general circulation models (CGCMs) must have a logical pattern for decadal time scales of SST anomalies over Persian Gulf, Arabian Sea and Indian Ocean.
3) Defining dominant decadal variability of both ocean and atmosphere in synoptic scale. So the question that arises is the applicability of bias correction methods to reduce the synoptic scale systematic biases in decadal forecasts, which are not well documented (at least for Indian Ocean or your desired region as my knowledge). By knowing these modes, we can impose external forcing which is not a source of uncertainty, especially when it is according to observations.
4) EOF based techniques are not appropriate for decadal variability because your run normally is for 5 year or maximum 10 years, so 120 monthly samples are not enough. It worth to mention that running a CGCM model with just initial configuration for more than 5 years is not 100% reliable because of growing instabilities which are not realistic.
5) Two simple methods for decadal variabilities are: simple mean correction and a least-square bias correction method, which have already been applied for decadal forecasts of North Pacific SST anomalies.
6) All the applied CGCM models should be initialised with the same initial and boundary conditions with the same reanalysis data to compare coparables.
7) It would be better to remove high frequency seasonal variability by a method like Trenberth and Hurrell (1994).
8) Utilising probability diagrams to capture extreme events among the model ensembles.
Although the aforementioned hints are just some basics, I hope that is helpful.
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When polar jet stream has southward shift mandering happens, it leads to polar vortex.
It is also true that the magnitude of polar vortex depends on the temperature difference between poles and mid-latitudes.
Moreover, the southward shift of jet stream is related to the southward shift of ITCZ (Intertropical Convergence Zone)
Then, Why polar vortex is not a regular phenomenon?
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Totally agreed with Matthew Mabey . It is a regular phenomenon but complicated and a broad field of study. Just let's add a comment about its dynamics. One fundamental feature of polar vortex is its nonlinear evolution of its instability in diabatic and adiabatic environments. The growth of instability and the most unstable mode of a polar vortex in gamma plane can define the crudest features of the vortex. The stationary state of zonal velocity in 'geostrophic balance' can specify the most unstable mode based on the linear stability analysis that is not universal and varies for each planet.
For more information and having a big picture about underlying dynamics of polar vortex and polar jets on Earth and other planets like Mars or Saturn and vortex in general, I propose to read some relevant articles like:
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Hello every one,
I am looking for downloading Lyman alpha radiation data to compare it with the mean occurrence rate of a phenomena observed only in June and July. I have tried the following link to download the required data.
I want to get the average of the two months, June and July. Is there any way to get the average of the two months in one click or I have to download daily average and then take the average for the required result.
Thanks
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intersting
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Dear RG members
I want to know about a change/changes in atmosphere just above the surface of the Earth can be observed very prior to earthquake initiation.
Regards
IJAZ 
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the professor from Russian State Hydrometeorological Univercity I Bokov studied in n in the field and there is a special a special site for earthquake forecast. try to find his site
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So far, different parameters e.g. Reflectivity, signal to noise ratio, power etc have been used to study PMSE echoes. Could any one suggest me the more useful parameter out of these three or any other they know ?
Thanks
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Depends what one plans to do with the PMSE data. For example, if goal is to investigate the wave activity in the summer mesopause region, probably Doppler velocity is the best to use. If one plans to do a statistical analysis about the phenomena itself, I do not expect big difference using SNR or volume reflectivity. Spectral width is used sometimes to highlight the turbulent areas in the observed region.
So, important is to define the interest of research whether assume PMSE as a tracer and use it to study dynamical processes or obtain background wind, or purpose is to investigate the PMSE morphology, micro-physics etc.
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During field investigations we used Gill ultrasonic anemometer to obtain data about turbulence on a height 2 meters from surface. Using this data (friction velocity, MO length scale, calculated z0 etc.) we want to calculate eddy diffusivity for tracers in layer between 0 (on a height z0+d) and 6 meters. How we can check that famous universal functions (Hogstrom or Businger-Dyer) work in a normal way in certain conditions. Surface seems to be not homogeneous on our site.
I know one simple approach - if calculated z0 values extremely differ from expected (expected z0 is 12% of height of roughness elements such as vegetation according to literature), then MO theory universal functions are not valid.
Can anybody suggest something else?
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Reading papers on this topic, I made two additional notes:
1. For this layer (0-6 meters) it necessary to use corrections of universal functions for roughness sub-layer.
2. Numerous papers suggest simple approach - using filters. For example, u*>0.1 m/s.
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When we found the non-zero helicity generation during TC formation in the tropical atmosphere (2010), our next step was about whether this might be favorable for the initiation of  large-scale helical vortex-instability. Indeed, we found  the instability by analyzing the kinetic energy of the primary (tangential) and secondary (transverse) circulation in our works  (2011-2016). Though the conditions in your experiment are quite different from the atmospheric ones, I would try to analyze the kinetic energy too.
References:
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Concerning experimental measurements, we have made a series of experiments with a focus on non-stationary stage of the cyclonic vortex formation. Time dependence of the kinetic energy of tangential flow is very similar to the ones from numerical simulations except the initial stage. In experiment, after the heating is on the meridional circulation forms relatively fast in comparison with numerical simulations. This fact and similarity of the vortex structure (to the atmospheric ones) are strong arguments toward universal scenario of vortex formation, when we have initial weak large vortex (in our case - solid body rotation) and secondary meridional circulation. 
  Now we are analyzing the results and I hope in a month or two the paper would be ready. The connection between helicity and vortex formation is still an open question. We started new numerical simulations using Open Foam in similar to the laboratory experiment statement. Using data from numerical calculations we will try to understand is helicty indeed important for the vortex formation or it is one of topological characteristicsof the vortical flow. Of course we should remember that our flows are rather laminar than turbulent, so we can not study specific turbulent effects when helicity may be of great importance.
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Yes. I have some experience with numerical modelling and theory of coastal circulations.
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Recently used method for the measurement of CO2 loading
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Dear Shailesh Kumar,
As is known, the CO2 may be in a liquid state at temperatures from -56.6 ° C to -78.5 ° C at a pressure of about 1000 hPa (mean surface pressure). Such conditions on the surface of the atmosphere almost never exist, except for very rare in some parts of northern Siberia (Russia) and Antarctica (South Pole). At the top of the troposphere and at the beginning of the stratosphere there are such low temperatures, but there is the pressure of a very small. Therefore, for liquid CO2 should be even lower temperature. Also, CO2 has no liquid state at pressures below 5200 hPa. So great pressure does not exist anywhere in the Earth's atmosphere.
The answer to your question is that CO2 in atmospheric conditions rarely almost never exist in liquid phase.
Regards,
Milivoj B. Gavrilov
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Hi all, I want to interpret some results of a model, but I do not understand two variables: What is the seasonality in temperature (BIO4) and precipitation (BIO15) ... in which units are expressed? ... Which Represent Because the organisms I am working with are very closely associated with those variables. Thank you. I hope your answers !! ... Greetings.
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I found this: 
temperature seasonality is a measure of temperature change over the course of the year. The worldclim calculates temperature seasonality using the standard deviation of the mean monthly temperature instead of deriving the temperature seasonality coefficient of variation. the larger the standard deviation, the greater the variability of temperature. 
hope you got a glimpse.
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I want to downscale 13km precipitation data to 500 m precipitation data. I have hourly precipitation data. I just want to downscale spatially. All the predictor I have is at 13 km resolution. Is it possible to downscale these 13 km precipitation data spatially?
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Hi Tasnuva:
You don't specify the format of the file you want to interpolate. If this file is in the netCDF format, you can use the R function 'resample' of package 'raster' to interpolate. First transform your netCDF file to multi-band raster using function 'brick'.
Another way of doing spatial interpolation of netCDF files is by using function 'ncap2' of package NCO. Another package you can use is CDO, see functions 'remapbil' and remapbic' for biiinear and bicubic interpolation respectively.
Hope it helps,
Augusto 
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The areas (in the atmsophere) where the humidity and the temperature gradient are high enough allow the clouds to appear. But I do not know if there is any model that explain this phenomenon with thermodynamics. 
Thanks for the answers.
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To answer your question : winds don't exist in those systems that are at a mean pressure of approximately 10^-16 g/cm^3. The purpose of my question was to build a simple analogy and study the formation of dust in those systems at "first order" I would say. And I did. Thank you for your answer.
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What could be the appropriate methodology for identifying non-stationary data periods in sonic anemometers measurements over a mountainous ridge under weak (2 m/s) wind conditions. The vertical turbulence intensity (sigma w / u star) comes out to be quite weak in comparison with the measurements over homogeneous terrain, as well as for complex terrain (excluding mountain ridges). However, for steep alpine slopes (Nadeau, et al., 2013, BLM) the magnitude of (sigma w /u star) is much smaller 0.98, in comparison to which the values estimated for this study over mountain ridge are even smaller (approx. 0.25). Kindly suggest relevant literature or explanations.  
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 can anyone tell me how equatorial wave, Rossby wave and kelvin wave generate and propagate in atmosphere and what are the time period of these waves?
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Ravi,
waves occur in the oceans and in the atmosphere. Both water and air are fluids so the types of waves in both are the same. The Wikipedia articles describe both, e.g.
"Rossby wave
From Wikipedia, the free encyclopedia
 
Rossby wave, also known as planetary waves, are a natural phenomenon in the atmosphere and oceans of planets that largely owe their properties to rotation. Rossby waves are a subset of inertial waves.
Atmospheric Rossby waves on Earth are giant meanders in high-altitude winds that have a major influence on weather. These Rossby waves are associated with pressure systems and the jet stream.[1] Oceanic Rossby waves move along the thermocline: the boundary between the warm upper layer and the cold deeper part of the ocean."
HTH,
Cheers, Alastair.
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At the time of El Nino, the trade winds are weaker at the equator over the Pacific ocean why? please explain those who knows exact answer......
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Ravi - Short answer is that the equatorial trade winds are responding to the change in sea surface temperature gradient along the equator. Longer answer: During an El Nino event, the pattern of equatorial sea surface temperatures change. Normally they are cold near South America and warm near Indonesia. During an El Nino, when the warm water moves eastward towards South America (along the thermocline, and reducing the equatorial upwelling), they weaken that gradient, and sometimes event reverse it. As that E-W SST gradient gets weaker, the trade winds get weaker. The intervening atmospheric variable is the sea level pressure.
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Does anyone know about  the impact of ionospheric warming  on the Earth's atmospheric system? 
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As to the question of ionospheric reflection of radio waves affecting the climate, it is clear that no such effect is expected because the radio waves do not interact with the neutral atmosphere and further the energy of the reflected waves is insignificant (as Prof Rastogi pointed out). A more relevant (although equally unlikely) question would be to ask if the radio waves transmissions (that are of higher power) could have any effect on the climate. It is also highly unlikely for the same reason that radio waves do not interact with the neutral atmosphere.
As regards the effect of ionospheric warming on the Earth's atmospheric system, the answer by David Themens is to the point. Further to this I may add that any warming that can occur in the ionosphere is the consequence and not the cause of possible changes in the atmospheric system. 
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Can anybody share the experience how to prepare the inlet system when I want to try to measure atmospheric nanoparticles (mobility diameter particle as small as 2.5 nm) at high altitude (~4 km)? I attach the meteorological conditions (T < 10 oC, Rh fluctuated, P ~ 650 hPa) at the site (Source: http://www.jma.go.jp/jp/amedas_h/today-50066.html?areaCode=000&groupCode=34). So far, I try to use the plastic tube from the outside to the diffusion dryer (then connect to the nano-SMPS with the flow rate 1.5 lpm) and to the pump with the flow rate 20 lpm. Thank you very much.
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the reference provided by dr Junkermann is exactly what you need
As for the publication: the authors are prime aerosol scientists and members of GAW as you can see in the WMO document
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A METEOROLOGIST CAN ANSWER THIS QUESTION  
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Ken
Just noticed that you also addressed me in the latest reply
Sure it depends on latitude going from towering cumuli up to 20 km in the south of your country to low stratus at the poles; but why do you ask? as always the questioner does not react himself why he asked it and apparently never read a textbook like the one I mentioned or even searched in Wikipedia on the origin of precipitation
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Hello Everybody!
Can anyone indicate me where to get satellite derived precipitation timeseries data for 150 to present with a good spatial resolution and a scientifically recognized source?
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You may also consider the satellite data for the last decades. Go to the International Precipitation Working Group (IPWG) web site:
Cheers,
Vincenzo Levizzani
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What type of statistical model will be best to link atmospheric rivers with daily stream flow extreme ? How such model should be changed to consider an annual flow maxima ?
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I don't know what region you are looking at, but you can use the NCEP model available online to extract information about wind, moisture, geopotential heights, etc. at multiple levels (~ 25mb) from 1000mb to 10mb.  The data is available for download in form of a netcdf file.  Also, you can perform online plotting  of the data with specified coordinates and compare your specific case with the annual average.  In other words you have the option to look for anomalous cases by comparing the annual average. Perhaps you already know the approach, but a good start would be to look at extratropical cyclones where there are both jet streaks and moisture gradients.  The first link takes you to the NCEP model.  Specific and relative humidity is from surface to 300mb are believe.  If you are studying the North American region then I suggest NARR, which has many more options.  The link to that is the second one posted below.   Hope this helps. 
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These clouds are the some of the highest altitude clouds around. Noctilucent clouds mean "night shining" and that is exactly how they look. The phenomenon that creates them is not yet fully understood. if anyone knows about it please answer the question.......
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Noctilucent clouds are seen from the ground during the transition from Civil Twilight (when the is 6 deg below the horizon) to Astronomical Twilight (when the sun is 18 deg below the horizon) so the the lower atmosphere is in the earth's shadow, reducing the the scattered sunlight, but the upper atmosphere(80 to 85 km where the clouds form) is still in direct sunlight.
   They also can be seen during the day from satellite instrument (e.g. Deland et al. JGR, 108, doi:10.1029/2002JD002398).
 While yes little of the tropospheric water vapor reaches the stratosphere, methane (CH4) does, where it becomes oxidized into water vapor (see Wronty et al., JGR, 115, doi:10.1029/2009JD012135)
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All of we know that, noble gases are highly inert in nature.. in periodic table before the Argon, Helium and neon are also there...but why Argon is present more  in the earth atmosphere rather than neon?....
What is the role of argon in evolution of earth's atmosphere..
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When the solar system formed from the nebula, only the massive gravitation enabled the gas giants - Jupiter, Saturn, Neptune etc - to retain the lighter inert gases such as helium. The ones heavier than argon are very rare as mole fractions and only a vanishingly small fraction have escape velocities of > 11.2 km/sec at about 600 K, the temperature in the Earth's thermosphere, where the mean free path is long enough that molecules can follow ballistic trajectories into space. Argon-40 alone has a local source, from the radioactive decay of potassium-40 that has been operative since the formation of the nebula and which continues in Earth's interior. The escape velocity of O-16 atoms from Earth is higher than that of argon-40, and yet Earth has retained its oxygen: only about 10**-84 O atoms have velocities at 600 K large enough to escape Earth's gravitational field. A fuller account can be found in "The Elements: their origin, abundance and distribution", P A Cox, OUP, 1997.
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What is the range of rain infiltration near coastal area?
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Infiltration to me suggest rainfall, but no increase in runoff, the water is absorbed or infiltrates into the soil.  So if this is your meaning, there are many small storms and especially in the growing season when the soils are drier, that all water is absorbed or infiltrates with no stream water response.  In the other hand, there may be periods of maximum wetness or flooding, where almost all incremental rainfall is retained in the floodwaters or moves to streams and discharged as streamflow, but probably less than 100%.  If talking about the whole storm that falls on wet soils, perhaps only 20% infiltrates.  A lot is going to depend on individual factors such as surface depressions, soils, incipient moisture, drainage pattern, stream types, gradient, etc. that can retain or detain water for longer periods so it can eventually infiltrate.  Such as a gully channel system is efficient at moving water and therefore would limit time for water to infiltrate under wet conditions, while braided streams for example are inefficient water and sediment movers, and may retain water on the valley low gradient  landscape longer, allowing more time for infiltration.  Streams with steep channels that have eroded to bedrock with steep contributing slopes may infiltrate less under wet conditions and as example, well drained, deep sandy soils are going to infiltrate more under all conditions than shallow clay soils.  So it is going to depend somewhat to your unique coastal system and types of storm severity and frequency as to how much actually infiltrates.  Also it may depend on exactly what you qualify as infiltration, if the soil absorbs water into its rooting depth and is later transpired by trees, will you count that as infiltration or do you only want to count what gets to deeper groundwater supplies?  In the dormant season, when evapotranspiration is minimal, the amount of rainfall minus streamflow should give you an estimate to consider, and if you had some wells, you could see how much they drop with time and assume that is how much is going to groundwater.  Here are a couple of papers for you. 
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I'm interested in the long-term (~past 100 years) variability in the convective and stratiform precipitation (or alternatively convective - stratiform cloud) over certain European regions. Monthly or annual resolution should be sufficient for the current research problem.
Thanks for any advice in advance.
Zoltan
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One relatively simple method would be to use manually observed cloud type classification and rainfall rate archives, which have a relatively long history in Europe and will offer a longer climatology than remotely sensed data. Of course these will have their limitations (daytime only for manual cloud observations, relative sparsity of long-term rainfall rate data etc.) but may be the only solution available in the first half of the twentieth century. Some archives may not be digitised yet either.
For rainfall rates, anything above 10mmhr-1 (WMO definition of heavy rain and the UK's CAA definition of heavy convective rain) is very likely to be convective, but there is the issue of whether the heaviest rainfall passed over the rain gauge and the stage of convective development etc.
As for data sources, archives can usually be found by contacting national weather services in the countries of interest, with many having online archives available for academic use. For older records, libraries such as the UK Met Office national meteorological library and archives ( http://www.metoffice.gov.uk/learning/library ) are comprehensive, including those from ships. These historical station reports are likely to have observed cloud type at least, if not rainfall rates. Again, many older records will not be digitised yet, which will add time to your project.
Hope this helps,
Alec
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who is related to atmospheric boundary layer
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friction velocity is a reference wind
The equation fo surface friction velocity, u* is the following
u* = ku/(ln(z/zo)-PSIM)
where u is the wind velocity at height z, zo the roughness length, PSIM stability function and k the Von Karman constant (=0.4). It represents surface stress and is also a measure of turbulence near the surface.
see also for alternate definition:
Maximum values could be beyond 1 m/s in case of strongly turbulent motion.
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I do agree that if a pipe is open to atmosphere, the exit pressure is atmospheric. However, I am not sure about the pressure profile along the pipe from the upstream to downstream (atmospheric tank). For example in my case, the pressure gauge about 30ft before entering to the atmospheric tank is about 50psig. Does "atmospheric pressure on the exit" mean that pressure is smoothly decreasing along the pipe from 50 to 0 psig or pressure sharply decreases right before the exit? 
It gets more interesting if the fluid is moving downward through a vertical pipe to an open to atmospheric tank. I believe the pressure along the downward movement increases (elevation head to static head), and then opens to atmosphere.
Here I attached another example to elaborate more. Draining water from a tank through a horizontal pipe. How is the pressure profile along the pipe? If we calculate the pressure on the pipe&tank connector as 50 psig, and the pipe is open to atmosphere, what is the pressure in the middle for example?
It'd be great if you could help me out.
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Pressure in the middle is related to the length of the pipe from the tank due to the friction losses on it. Friction losses can be calculated using Hazen william equation.
I hope I have understood your question. 
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I want to develop a rainfall erosivity map for my study area to be used also as an input to the RUSLE formular. The data is from a single rain gauge in the study area spanning over 30yrs and i am wondering if anyone has an idea how i can use this to develop the rainfall erosivity map. 
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That was fast, i am very grateful. i will look at it and give you a feed back
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Can the spin up time be varied and on what factors does it depend? (Atmospheric Model)
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Dear Abhishek,
The tools used to forecast weather, project likely climate scenarios, or to reanalyze data are all based on or derived from a General Circulation Model (GCM). These models require initial (IC) and boundary conditions (BC) before they can start to run forward and generate estimates of future situations.
Because of intrinsic difficulties (including inevitable uncertainties in the observational data, inconsistencies between those, and probably limitations in the model formulation too), the initial results are unreliable as the model attempts to stabilize. This is the 'spin up' period. Once the fields have adjusted and results become more stable, the model can be stimulated (forced) in a particular way and the results can be trusted, within limits that can themselves be documented.
Hence the spin up time may vary from model to model, and especially with the quality of the IC and BC, as well as with the purpose of the run. Given the cost of high performance computing, there is a trade-off between a long spin up period (to allow the model to 'forget' the IC and BC) and the need to quickly generate useful outcomes. The communities mentioned above (weather, climate, reanalysis) have generated ample materials on this matter.
Cheers, Michel.
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Regarding different time scales, likewise, sea surface temperatures.
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In order to give the general answer to this question we have to
analyze the constitutive relation between the stress tensor and the
deformation tensor in the fluid system.
The stress tensor for fluid is
[T]=-p[I] + [\sigma]
where p is the pressure, [I] is a unit matrix, and
[\sigma] is anisotropic part which could be written
for Stokes fluid (without memory effects) as
[\sigma]=F(v, grad v, [D])
where [D] is deformation tensor.
For fluids with memory [\sigma] depends also on time derivative
of [D].
The answer to the question depends thus on the form of the constitutive
relation between [T] and [D].
For most of the cases considered in meteorology this relation is not reflecting
explicitly the presence of the memory effects.
In reality if we consider that the flow represented by the velocity field v is
truncated at a certain scale we have to modify accordingly the constitutive relation.
Specifically the dynamical effects of the truncated part of the velocity field spectrum
should be accounted in F to reflect the Lagrangian history of the deformation of the fluid elements.
The modified form of F will contain terms which could explain the memory effects.
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During  summer the atmosphere is dry and ionized.Due to this the clouds formed in the early monsoon is electrically active.possibility of lightning strikes is bright .Hence to alert people can we measure the on coming cloud charge?  
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The ionization in the lower atmosphere which is relevant here is produced by galactic cosmic rays and close to the surface by radio-activity from the ground. The ionization profile is maintained irrespective of seasons (solar X rays and EUV radiation play a role in the ionization process only above 60 km). Immediately after winter, land warms up quickly whereas different layers of atmosphere gradually warm up. This process results in temperature gradients that are unstable to convection (lighter and warmer air masses rising against denser and colder air masses higher above). Strong convection, during the pre-monsoon period, is the reason for cumulo-nimbus clouds (thunderclouds) appearing frequently then. There are instruments that capture the large electric fields associated with a charge cloud in the vicinity and so they can be used to alert people in an area couple of hours in advance.
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 I have seen values of 0.8-0.12 inches in the literature...
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I know of past rainfall sites I have visited with daily amounts record to as low as they can get or 0.01 inch is the typical smallest unit of most raingauges (based anyway on my memory).  Now I am with you, in not wanting to call every 0.01 inch a storm for analysis and keeping track of.  If you meant 0.08 to 0.12, I would go with 0.10 inch as the separation point or basically 2-3 mm if metric. But it may depend on the goals of your study and where you live.  In Lima Peru, they get 1 cm per year, so they obviously would keep track of smaller storms than say the rainforest with 2000-3000 mm per year.  As long as you define what your value is, you should be good.  If you are studying less frequent to major events, you might want to start at 1 inch and work up.  But if you did not in Lima, you might be waiting a few decades to get enough storms larger than an iinch to analyze.
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there is a line of maximum wind speed with 115 degree measured from direction of tropical cyclone motion
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I agree with Mr Contreras and I would like to add that if a hurricane makes a landfall, the convective area near the eye decays faster than the rest of the system, at the outer radii of the cyclone and hence the maximum surface winds could be measured in different places. 
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I'm interested in measuring the temperature of the snow over its depth. The temperature should be measured in every 20-25 cm over the up to 2 m snow pack.
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Dear Tomasz,
I know very good book on the subject: S.D. Vinnikov & B.V. Proskuryakov "Hydrophysics", Leningrad,"Hydrometeoizdat", 1988  (unfortunately in Russian)
in which there described the structure of snow and its density. There are several  problems and solutions for multi layer matter, for example snow above ice.
Best wishes
Elena Dolgopolova
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I work on daily rainfall. I perform correction bias methods. After the correction, my bias is corrected very well but my relative RMSE is similar to the one before correction.
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I suspect something is actually going wrong in your calculation. If you have a daily precipitation, p(t), and apply some bias correction that produces p'(t) that is more like some other P(t), your RMSE should decrease because (p'(t) - P(t))^2 should become smaller on average than the original (p(t) - P(t))^2. So either your bias correction isn't actually improving the agreement between p(t) and P(t), or your calculation of RMSE is doing something unexpected. At least, this is where I would start.
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I am using RCM CNRM-CM5-CSIRO-CCAM for precipitation projection in Islamabad, Pakistan. I am getting higher value of precipitation in 2041 to 2070 for RCP 4.5 than that of RCP 8.5. I s it possible?
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Principally it could be, means change in climate somewhere may generate extreme precipitation whereas some places may get extremely low amount of precipitation. 
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Experience weather forecasters called this situation a "dirty ridge" whenever a lot of low clouds (such as stratocumulus) are present but NWP models fail to forecast them and instead predict sunny conditions. This situation often happens. 
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I expect that not all models fails in this respect, but low clouds are problematic for many models due to several reasons. One reason may be that models often lack sufficient vertical resolution to capture the sharp gradients at the cloud top that is a necessary feature for the physics involved; the clouds are also often shallow. Another is that the model's description of moist processes, cloud/radiation interaction or boundary layer turbulence may be inadequate.
One problem is that the presence (or not) of stratocumulus is due to a balance between resolved-scale motions (subsidence in the high-pressure ridge) and motions that in a model are parameterized (turbulent mixing). If the mixing is too weak compared to the subsidence there will not be any clouds; if the mixing is too strong the clouds will be to thick.
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Dear Colleagues, I have temperature T (in Kelvin) and specific humidity (in g/kg), both at different atmospheric pressure levels (pressure in hPa), the problem is that I need Water Vapor Pressure e (in hPa). I have tried all I could and have scoured the internet for a solution but to no avail! I even tried to see if I could just get relative humidity these parameters, but no way. Please, can anybody help here? Thanks in anticipation of help.
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To obtain an accurate estimate of the saturation vapor pressure, you can consult http://journals.ametsoc.org/doi/pdf/10.1175/1520-0450%281993%29032%3C1294%3AAOTAAC%3E2.0.CO%3B2
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Hi all,
I'm planning to collect aerosol samples on polycarbonate filters in an adverse environment. High mountain with high humidity and very low temperatures. The collection system will be composed of inlet tube (taking the sample from outside the building), in-line filter holder (located inside a heated building) and air pump. I'm concerned that the high humidity and the difference between inside and outside temperatures can ruin my samples. Is it a good idea to heat the inlet with a heater tape? Any suggestion? I'm not interested in volatile compounds and the filters are to be analyzed by scanning electron microscopy.
Thanks.
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Dear Sandra, the topic is interesting. I wish these documents may support you.
Moreover, I suppose you will have to consider also the effect of humidity on particle (size for instance..).
Cheers, Valerio 
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Cosmic rays have a slight interaction with clouds. How much significant is that interaction? Can that interaction change the energy budget of Earth and the dynamical processes which interact with the vapor content?
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Short answer: there's been claimed correlations and some theoretical work, but no experimental verification.
Long answer with citations:
A correlation between cosmic ray flux and clouds in Earth’s atmosphere has been described (see, for instance, Marsh and Svensmark, 2000). However, this correlation has been called into question by Sloan and Wolfendale (2008) and Erlykin and Wolfendale (2011). Further, the claim of a correlation between climate change and spiral arm crossings (used to support the cosmic ray–cloud connection) by Shaviv (2002) has been effectively ruled out based on updated knowledge of Galactic dynamics (Overholt et al., 2009). The physical mechanism itself, involving enhanced formation of aerosols and nucleation sites (Tinsley, 2000; Svensmark et al., 2009), while plausible, is not established (Wagner et al., 2001; Pierce and Adams, 2009). The CLOUD experiment at CERN has sought to establish such a mechanism, with inconclusive results (Duplissy et al., 2010, Kirkby et al., 2011).
Marsh, N. and Svensmark, H. (2000) Cosmic rays, clouds, and climate. Space Sci Rev 94:215–230.
Sloan, T. and Wolfendale, A.W. (2008) Testing the proposed causal link between cosmic rays and cloud cover. Environ Res Lett 3, doi:10.1088/1748-9326/3/2/024001.
Erlykin, A.D. and Wolfendale, A.W. (2011) Cosmic ray effects on cloud cover and their relevance to climate change. Journal of Atmospheric and Solar-Terrestrial Physics 73:1681–1686.
Shaviv, N.J. (2002) Cosmic ray diffusion from the galactic spiral arms, iron meteorites, and a possible climatic connection. Phys Rev Lett 89, doi:10.1103/PhysRevLett.89.051102.
Overholt, A.C., Melott, A.L., and Pohl, M. (2009) Testing the link between terrestrial climate change and galactic spiral arm transit. Astrophys J 705, doi:10.1088/0004-637X/705/2/L101.
Tinsley, B.A. (2000) Influence of solar wind on the global electric circuit, and inferred effects on cloud microphysics, temperature, and dynamics in the troposphere. Space Sci Rev 94:231–258.
Svensmark, H., Bondo, T. and Svensmark, J. (2009) Cosmic ray decreases affect atmospheric aerosols and clouds. Geophys Res Lett 36, doi:10.1029/2009GL038429.
Wagner, G., Livingstone, D.M., Masarik, J., Muscheler, R., and Beer, J. (2001) Some results relevant to the discussion of a possible link between cosmic rays and Earth’s climate. J Geophys Res 106:3381–3387.
Pierce, J.R. and Adams, P.J. (2009) Can cosmic rays affect cloud condensation nuclei by altering new particle formation rates? Geophys Res Lett 36, doi:10.1029/2009GL037946.
Duplissy, J., et al. (2010) Results from the CERN pilot CLOUD experiment. Atmos Chem Phys 10:1635–1647.
Kirkby, J., et al. (2011) Role of sulphuric acid, ammonia and galactic cosmic rays in atmospheric aerosol nucleation. Nature 476:429–433.
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Where will be the cirrus ice nuclei concentration maximum with respect to cloud base cloud mid and cloud top altitudes?
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The ice nuclei concentration is not confined in a particular height within the clouds. However, the number concentration of ice crystals is generally larger in the upper part of cirrus clouds due to larger cooling rate by radiation.
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What are all the Microphysical schemes available?
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Usually a one moment scheme is used with rain, snow (and graupel) (and hail). However, novadays 2-moment microphysics schemes are upcoming. See e.g. Beheng and Seifert. All of them are implemented in e.g. the COSMO model.
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How far can particulates travel (horizontally) in the plume model. Is there anything as quasi plume model
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The answer depends on the model applied in a sensitive way since the spread of transported distances is dependend on the velocity field and vertical velocity at emission location. I suggest to try out a standard lagrange transport model first using a prescribed wind field. The further details depend on your particles and more detailed questions. E.g. pollen can be transported very far due to low deposition velocities.
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Hey guys,
I am trying to estimate mainly the pressure but also the temperature that occurs in the plasma of an artificial current that mimics a lightning strike.
Looking forward to your answer and until then let's keep making the world a happier place!
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See, "The Density, Pressure, and Particle Distribution in a Lightning
Stroke near Peak Temperature" by Martin A. Uman, Richard E Orville, and Leon E Salanave in the Journal of Atmospheric Sciences, Volume 21, May, 1964, pp 306-311.
Uman, et al, estimate the average temperature  to be 24000K and a peak pressure of 18 atmospheres. 
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Hi all,
I'm using the ERA INTERIM dataset. I downloaded the data (H, LE and Rn) like below. I know this dataset is not the best.
sshf Surface sensible heat flux [J m**-2]
slhf Surface latent heat flux [J m**-2]
ssr Surface net solar radiation [J m**-2]
But when I view the content for my surprising the values are "strange", see below:
-1 : Date Time Level Gridsize Miss : Minimum Mean Maximum : Parameter name
1 : 1979-01-01 12:00:00 0 1089 0 : -2.6211e+06 -3.0388e+05 1.7202e+06 : sshf
2 : 1979-01-01 12:00:00 0 1089 0 : -1.4553e+07 -2.9573e+06 8.1755e+05 : slhf
3 : 1979-01-01 12:00:00 0 1089 0 : 7.1395e-11 2.1309e+06 9.5987e+06 : ssr
4 : 1979-01-02 12:00:00 0 1089 0 : -2.8324e+06 -3.5041e+05 1.5127e+06 : sshf
5 : 1979-01-02 12:00:00 0 1089 0 : -1.7608e+07 -3.0635e+06 3.9123e+05 : slhf
6 : 1979-01-02 12:00:00 0 1089 0 : 7.1395e-11 2.2015e+06 9.8327e+06 : ssr
The values are very strange. Does anyone can give some tips about the data?
Thanks a lot,
Guilherme Martins.
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Hi Guilherme,
I had similar issue with Le and SH fluxes, which I got for time 12:00 only with the forecast step =3.
So, what I did: a) applied scale and offset to the data given in the original file, and b) devidev by my forecast step 3*60*60 sec.
Values were physical after that,
Hope that helps,
Kind regards,
      Irina
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What is the relation between surface heating rate and precipitation?
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Dear Siva,
As far as I understand your question, thus is a question of surface net heat flux budget in which the precipitation amount is a cooling source. The heat flux due to rain can be evaluated by a formula proportional to the rain amount multiplied by a factor depending on the difference of temperature and humidity between surface and air multiplied by various parameter. You can find the formula in numerous papers. for instance in Gosnel et al JGR 1995; Fairall et al. JGR (2003)...
Hope this can help
Regards,
G.C.
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I would like to compute my diagnostics using this "full" EPflux not just using the ordinary quasi-geostrophic one. The results seem quite different so far.
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Addtional to the paper above, you can have a feel about possible errors in estimatint the full EP flux and EP flux divergence based on reanalysis data sets from the followng paper:
Hua Lu, Thomas J. Bracegirdle, Tony Phillips, and John Turner, 2015: A Comparative Study of Wave Forcing Derived from the ERA-40 and ERA-Interim Reanalysis Datasets. J. Climate, 28, 2291–2311. doi: http://dx.doi.org/10.1175/JCLI-D-14-00356.1
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According to Müller, D., et al. "Aerosol‐type‐dependent lidar ratios observed with Raman lidar." Journal of Geophysical Research: Atmospheres (1984–2012) 112.D16 (2007). Basically Lidar ratio of 20-30 sr are categorized as marine aerosol, 30-40 sr are for polluted marine aerosol, 40-60 sr are for urban aerosol, 50-80 sr are for wood (biomass) burning aerosol. But how about Lidar ratio smaller than 20 sr and greater than 80 sr? Are there any aerosol types corresponding to these Lidar ratio?
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Check my publications. There is one in IEEE in 2010 that my be of help
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Direct and indirect effects of aerosols on clouds are well-known concepts. In the same perspective, I say that the solar radiation reaching the Earth's surface is significantly modulated by direct and indirect multiple interactions with clouds. Does this make sense in a more generalized context? I have the following basis to support my argument of 'direct and indirect multiple interactions with clouds':
(a) The 9 types of clouds are classified as high, medium and low level clouds according to their cloud top pressures. This is a well-known categorization w.r.t ISCCP.
(b) Most of the tropospheric aerosols are confined until atmospheric boundary layer altitude except the case of mineral dust aerosol layers at higher altitudes well above boundary layer heights.
Coming to my phase, 'direct interaction' refers to primary scattering and absorption of radiation with clouds, whereas the 'indirect multiple interaction' refers to the secondary effects of broken cloud fields on solar illumination reaching the ground (i.e., 3D cloud radiative effects). In addition, when there are multiple cloud layers where there is an open envelope of normal atmosphere between the first & second cloud layers, then the interaction with the first layer of cloud is primary while the second layer of cloud has a secondary interaction with the already attenuated radiation from the first cloud layer. I mean to say this also as indirect interaction of incoming solar radiation with clouds.    
Can anyone elucidate if my understanding is wrong in phasing the 'direct and indirect multiple interactions with clouds'?    
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Dear Lakshmi,
You can use those terms as you see fit, as long as you explain what you mean by it. However, giving names of objects or processes is not, by itself, of particular relevance or interest. You may want to focus more on why you would want to distinguish these 'direct' versus 'indirect' effects on the amount of radiation reaching the surface: In other words, what is(are) the advantage(s) and implication(s) of making this distinction?
This being said, please note that aerosols are not limited to the boundary layer: volcanoes and large fires are two examples of processes that can send great quantities of aerosols at high altitude, including in the lower stratosphere in the case of large volcanic eruptions.
If there are multiple clouds layers in the atmosphere, there will be complex radiative interactions within the atmosphere, as well as between the latter and the surface. Again, I'm not sure whether or why the bottom cloud layer would be called the 'first' and the top the 'second', or what is the purpose of calling one 'direct' and the other 'indirect'. In any case, you will need to account for multiple (scattering) interactions between the surface and all atmospheric constituents, including gases, aerosols and clouds.
Cheers, Michel.
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It is generally said that negative (positive) z/L represents the unstable (stable) state of surface layer. How can one quantify the magnitude of instability (stability).
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Let me add a dissenting voice to this discussion. The standard statistical model, which includes the Monin-Obukhov similarity model, does indeed propose that the parameter -z/L is a valid measure of stability in the lowest 10% of the ABL. Early analyses of surface-layer data did indeed suggest just two regimes, one for +ve (stable) and one for -ve (unstable values of z/L). Our present models are almost all based on these results. HOWEVER, this account is known to be inadequate in stable conditions (Mahrt 1998, Theoretical and Computational Fluid Dynamics 11, 263-279 ) where three distinct regimes are now described (Sun et al. 2012, JAS 69: 338-351). The unstable ABL also has three distinct regimes, (cellular convection, roll convection, and a recently-added "unstable very close to neutral” or UVCN regime) (Smedman et al. 2007, QJRMS 133: 37-51). The z/L parameter seems unable to discriminate these regimes. The problem traces back to the failure of the Reynolds similarity hypothesis as a fundamental tool in turbulence theory (McNaughton 2012, BLM 145: 145-163). Given all this, there may not be a single way to characterize boundary-layer stability since each regime will behave differently and, quite possibly, each will have its own scaling parameters and `universal functions'
For practical work the Monin-Obukhov is the only way to go, but be aware that there are wide uncertainties, and the z/L local stability parameter may be quite unsuited to some kinds of analysis. Many text books give good, if uncritical accounts of Monin-Obukhov similarity theory and the associated empirical relationships. Take your pick.
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I am writing IDL code to extract relevant information from an atmospheric profile to be used in radiative transfer model. I'm looking to find regions where clouds exist, so I need to specify the threshold level of the microphysical properties of clouds. Can anyone tell me where can I get the threshold level? Thanks a lot. 
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this is true, but to be on a safe side I would first build a histogram of all available values to understand the units and the dataset itself. If the output is stratified in pressure (it can be IWP per layer or IWC per level) then you have to integrate in the column to get the IWPs (and again, pay attention to the grid units).
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I am trying to investigate the percentage of Brown Carbon absorption at wavelength 532 nm. I need some reference values to compare my finding but unable to get any such work on Google.
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Thank you Teja for the information.
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Is there any method available for the estimation of cloud albedo using satellite observation of shortwave and long wave radiation at TOA for clear and all sky? 
How can we calculate cloud albedo?
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Keep in mind that droplet effective radius is proportional to cloud co-albedo, which is one of the key parameters in all estimates of cloud shortwave radiative properties.  To get a better sense of the effect of droplet size on shortwave flux, I would recommend to check an old Tony Slingo’s paper “A GCM parameterization for the shortwave radiative properties of water clouds” published in JAS in 1989.
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Can anyone please suggest what kind of relation can be expected between solar flux and particulate matter (<10micron)?
Does solar flux impact particulate matter in any way?
Please attach some suggested readings?
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Dear Parth.
In addition to the secondary particulates, I would mention inversions.
Usually the inversion breaks up with increased solar radiation.
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How do long-waves atmospheric blocking patterns lose their energy? And how does it depends on its resonant (vertically) state? I need some references, thanks.
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Maybe you can find some useful discussions in:
Biello and Majda, 2004: The Effect of Meridional and Vertical Shear on the Interaction of Equatorial Baroclinic and Barotropic Rossby Waves. STUDIES IN APPLIED MATHEMATICS112:341–390
and
Tian et. al., 2001: Experimental and numerical studies of an eastward jet over topography. J. Fluid Mech.,vol. 438, pp.129-157.
Best Regards,
Raffaele
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There are models for the structure of hurricane winds (e.g. Holland, 1980, Holland et al., 2010) which are typically applied at the the sea surface for studies of air-sea interaction. We know that in the surface boundary layer, under neutral conditions, Monin-Obikov theory may be applied to find the wind speed as a function of altitude and this is an exponential curve (so called "law of the wall"). Is there any reason that the wind direction might also be a function of altitude? Has the vertical profile of wind direction in a hurricane ever been measured (at a stationary point in the hurricane reference frame)?
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I have to respectfully disagree with Alastair McDonald's reply.  The upper air away from the surface does of course follow the cylindrical circulation (so long as you are still low in the atmosphere).  But the question is about wind close to the surface, which is governed not only by the pressure gradient and coriolis effects of the upper air, but also frictional effects from the surface.
The Eckman calculation is single column, and is indifferent to the large scale circulation.  In a low pressure system you see the effects as air near the ground cuts across the pressure contours at nearly 45 degrees, but upper air follows the pressure contours.  A hurricane is just a massive low pressure system.  The Eckman profile holds at each location, so that the wind near the ground inclines towards the local low pressure (not directly towards it) while higher  air will circulate perpendicular to the pressure.  Higher still the wind becomes vertical, then eventually switches to circulating the opposite direction.  But all this higher stuff is not Eckman circulation, and does not pertain to the question about surface winds.  About a km high the air is moving around the local low pressure; below it begins to turn so that near the ground it has a component towards the low pressure.
Over ocean, the friction is low ccmpared to land, so near the surface the wind will be closer to circulating around the low pressure than over land, but will still have a component towards the low pressure.
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Is there an hourly or daily threshold intensity to differentiate stratiform and convective rainfall without having to calculate the diameter or the distribution of raindrops.
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Dear Justine,
A cloud is called 'stratiform' if its shape is mostly a single, more or less homogeneous layer, with its horizontal spatial extent much larger than its depth. A cloud is said to be 'convective' if convection is the primary physical process for water vapour condensation. Neither of these cloud characterizations (shape and process) say anything about whether there will be any precipitation, and if so what might be the intensity.
You might expect that, on average over large areas and long periods of time, stratiform clouds yield precipitations of limited intensity for some period of time, and that convective clouds tend to generate shorter and more intense rains, but there will be a potentially large overlap between those cases.
For sure, precipitation intensity is unlikely to be a reliable indicator of cloud shape, because many clouds do not precipitate and clouds of different shapes can yield similar rain rates. Besides, there are much better ways (e.g., remote sensing) to characterize either cloud extent and shape, or cloud formation processes.
In any case, if such a threshold intensity existed, it would be highly specific to the particular location--and probably also to the season--of interest. If this information is really crucial, you should consider establishing that threshold for your place of interest.
Lastly, the size and number distribution of raindrops is closely related to the size of cloud droplets, to the drop formation mechanisms and the amount of time spent by raindrops in the cloud. Specifically, large (and hence heavy) raindrops can only be generated in deep, active convective clouds. But all clouds yield small droplets.
Cheers, Michel.
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I run WRF-ARW for different parametrisation  schemes  for sensitivity analysis and I have obtained WRF outputs in 6 hourly bases for precipitation. I have converted these to monthly data (using the cdo 'monavg' command). The problem is that the amount of precipitation (from both rainc and rainnc) is very high and unrealistic. However the result is realistic in 6 hourly bases. Now I want to convert the accumulated precipitation (rainnc and rainc) to daily bases to compare it with gridded observed data sets like from CRU and GPCC. Do you have any idea how I could convert 6 hourly precipitation data to daily using CDO? 
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HI! Not that difficult.
Add both variables and calculate the daily mean and multiply the mean with the number of seconds per day.
(in general the output is on kg per seconds which is equal to mm/seconds.)
A day has 86400 seconds, so type:
cdo -mulc,86400 -daymean InFile Outfile
Afterwards you will have daily sums of precipitation.
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Coupling  RCM with CTM to investigate the effects of climate change on future air quality
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Dr. Xin-Zhong Liang  xliang@umd.edu and Dr. Julian Wang julian.wang@noaa.gov have developed a climate version of WRF.  There are numerous publications that should be possible to locate using a Google search.
The EPA CMAQ team is the best place to get answers about WRF-CMAQ.  Dr. Hall appears to have taken care of that. 
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Dear All,
    I have run the WRF Model yearly (2010,2011, and 2012)  and few years as a single run (2010-2012) using GFS data. After running real_nmm.exe, 
I observed Boundary conditions and Initial conditions for Individual years 2010, 2011 and 2012 with combined year run 2010-2012.
2010: Both Initial and Boundary conditions are Same.
2011: Boundary Conditions are same but Initial conditions different
2012: Boundary Conditions are same but Initial conditions different
Now I compared the Time series of Individual years 2010, 2011 and 2012 with combined year run 2010-2012.
2010: The Wind speed values is same throughout the period.
2011: Wind speed Values are almost correlated well for every month except from Mid of April to August.
2012:Wind speed Values are almost correlated well for every month except from Mid of April to August.
I Observed there is only difference in initial conditions (rest of all are same, Input data, Boundary conditions, Parameterization schemes, same location, resolution etc). So i expected all the months of 2011 and 2012 should be differ from 2010-2012 single run. But it showed difference for few months as mentioned above. I done the similar analysis for another location, The results are same as earlier.
I am unable to understand how to explain this behaviour. I attached all the results in excel file which is in zip file. 
Waiting for your Valuable Ideas, 
Thanks & Regards,
Malleswararao M.
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From Internet i came to know that the Thailand monsoonal season starts from May/June to October.
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Dear All,
       Can anybody hep me how to improve the model output by using observations (mast data). I have done like this. 1) I have done wrf calculations and  have mast data for the same location. And compared the Time series and Correlation. The WRF following same trend like Observations and 0.6 correlation between them.
2) Based on both data,  calculated Slope, Intercept and apply these two parameters to wrf data (y=mx+c) and this modified WRF data again compared with Observations, there is no improvement in correlation and also not following the trend.
 So I need to get best correlation than earlier comparison and needs to followed the trend like observation data. How can I improve it? Any Suggestions Welcome.
Thanks & regards,
Malleswararao M
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Thanks Mouhamed,  I will look into the papers. Can you share me the second paper as a soft copy, i unable to download?
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I have been doing a data analysis for 4-5 years of PM10. I also downloaded UV Aerosol Index for the same period. Now I did a seasonal average and finds that UVAI is higher in summer followed by winter and almost similar in monsoon and post-monsoon. However my Pm10 average is highest during winter followed by post-monsoon, summer and monsoon. Can anyone please suggest what does it indicate. Also please recommend some best articles with this regards if possible.
Thanks,
Parth
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Dear Parth,
Are you using the NASA GES DISC Aerosol Index or a national data set available in your country? As you will see from
that index "detects the presence of uv-absorbing aerosols such as dust and soot".
The proper interpretation of that index is explained later on as follows: "Positive values of Aerosol Index generally represent absorbing aerosols (dust and smoke) while small or negative values represent non-absorbing aerosols and clouds. The Index can be interpreted in terms of optical depth if the index of refraction, particle size distribution, and the height of the aerosol layer are known from other measurements."
Hence this index primarily reports on the absorbing properties of the aerosols in the UV spectral domain. It does not, per se or alone, say anything about the size distribution of the airborne particles, though such information may be derived if multiple other variables are fully specified.
On the other hand, PM10 (and PM2.5) values are indicators of the number of airborne particles of 10 (2.5) micrometers in size or less
irrespective of their chemical composition, and thus of their possible impact in absorbing UV radiation.
There may be a weak link between these two indicators, but it is certainly non trivial. The main question is why did you pick these two indicators or try to relate them a priori? Do you expect a relation? If so, which one and why? What is your hypothesis or starting point?
Cheers, Michel.
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Ozone layer depletion occurs due to reactive radical like chlorine free radical. Ozone layer is present in stratosphere. So how someone can study the ozone layer depletion? Suggest me the methods and techniques are used for the study of ozone layer depletion.
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You can find the ozone trend analysis in the paper by Jonas et al. (www.atmos-chem-phys.net/9/6055/2009/). The trend in the upper stratosphere is exactly as expected from halogen loading and gas phase chemistry. Heterogeneous reactions explain the ozone trend in the lower stratosphere. The formation of PSC-1 (NAT) is not crucial because the activation can happen on/in liquid sulphate aerosol. There were several publications showing this.   
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In climate change/global warming studies, the Stefan Boltzmann formula is often used to estimate the amount of radiant energy which escapes outward into outer space from earth. The formula is derived under the assumption that the relevant emissivity of the emitter is a constant for all wave lengths, and its temperature exponent is 4. However, the Earth’s greenhouse gases permit radiations to pass through the atmosphere freely only in some specific wave length windows. It is shown that the wave length dependence of emissivity can change the effective temperature exponent of the Stefan Boltzmann formula. (Source: Lam, H. S. (2007). On the Effective Stefan-Boltzmann Temperature Exponent of the Earth).
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CO2 is well mixed in the troposhere. It is about 400ppm at all altitudes, with notable exceptions. One is a slight gradient of some 2-3ppm between northern and southern hemisphere, die to the fact that CO2 is consistently being pumped more from locations (i.e., power plants) in the north of the planet. The second is that there may be huge daily and seasonal variations due to photosynthetic uptake and release of CO2...but this is limited perhaps to the first few 100 m form the surface and has not impact on temperatures.
As you know, the effective radiative temperature of the planet (about 15C) never changes, because it is fixed by the energy balance at the top of the atmosphere. What changes is the effective height of where that temperature is. The higher it is in the troposphere, to keep the microwave radiation out to space constant, the warmer the surface temperature.
Best,
Francesco