Questions related to Atmospheric Sciences
The terms on the RHS represent the subgrid-scale, and the ones on the LHS represent the large scale, yet both are coarse-grained-averaged. So why do the terms on the RHS still represent the subgrid scale?
This article confirms that only a small part of the fallout from volcanic plumes is by individual greins falling with terminal velocity through the air below the main plume.
The main fallout is in streaks, that is vertical flow of ash laden air, actually a gravitational ash laden air current created by aggregation of ash in the main plume . Same kind of gravitational flow has been observed in heavy rain- and hail-storms.
The physical explanation of this phenomen is when grains flow through air, the flow resistance they drag the air with them. Further description and a measurement of a large streak fallout in Sakurajima, Japan, can be found in:
Eliasson, Jonas, Junichi Yoshitani, Konradin Weber, Nario Yasuda, Masato Iguchi, and Andreas Vogel. "Airborne measurement in the ash plume from Mount Sakurajima: analysis of gravitational effects on dispersion and fallout." International Journal of Atmospheric Sciences 2014 (2014).
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?
We all know that the process of teaching and learning is a philosophy. Therefore, educational institutions are interested in finding the best means and tools that make the learner receive lessons in an effective and thoughtful manner, taking into account the factors of speed and accuracy. Meteorology is a physical science concerned with the atmosphere in which humans live, just as fish live in the sea. Weather phenomena are processes that occur in a large laboratory, which is the atmosphere, in which many factors that take place together influence each other. Being a teacher, learner or new meteorologist, what is the most important topic that should be focused on and understood?
I am a research scholar in the field of atmospheric science. I am willing to discuss with you about convection.
Convection is an important process in reality and in the weather-climate models. There are commonly two ways of treating convection: quasi-equilibrium (QE) convection and non-QE (e.g., triggered) convection. In the QE convection category, the convection may be considered to be in a state of statistical equilibrium with the large-scale convection. While for triggered-like non-QE convection, high-frequency (> 0.5 CPD), small-scale waves will interact with the convection, in which QE does not work anymore.
Can anyone kindly explain more for me comprehensively the difference between QE and non-QE convection?
I appreciate any answers from you!
Whenever I search for papers on google scholar regarding my topic i.e. 'Economic Evaluation of the Impact of Air Pollution on Public Health in Delhi', most research papers are based on Atmospheric Sciences. I intend to focus my review on the aspect of Economics. Kindly help me with the most relevant search engines or techniques, that might make my search for relevant articles easy.
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.
I am interested in knowing about the lifetime of a chemical species in the atmosphere. What are the techniques that can be applied in order to estimate the lifetime of a certain chemical species in the atmosphere based on the physical and chemical properties at different length and time scales? Is there any analytical or computational technique that can be used to estimate within limits of permissible errors? or can it be analysed from Earth Observation data?
I'm trying to find out the physics how a fast and slow (separately) moving Hurricane/Tropical Cyclone/Typhoon influence storm surge generation. But so far I haven't found any detail explanation except some generalized statements.
I am a third year Mechanical Engineering student from Sardar Vallabhbhai National Institute of Technology Surat, India. I am interested in pursuing higher studies in the field of space sciences, in particular study of planetary hydrodynamics, astrophysical plasma and electrical activities in planetary atmospheres.
I am looking for universities as I want to pursue higher studies and a career in the field mentioned above. Please give your suggestions and recommendations in the following format.
Name of university
Research group, associated research (current, past and future prospects)
Cloud morphology and cloud movements are often associated with nature of flow in a planetary atmosphere both locally and globally. They have us an inference about the atmospheric circulation.
Atmospheric transport processes are associated with both molecular dispersion and bulk transport of mass, momentum and energy.
Turbulence is associated with chaotic behavior of fluids in motion. In this regard, I would like to ask what are the effects of turbulent flow on the cloud morphology, both at macroscopic scales (i.e. features observable to naked eyes) and microscopic domain (aerosol and ion transport).
I read some texts on the nature of turbulence, and Kolmogorov scales. Is there any way to possibly estimate the effect, both in qualitative and quantitative manner?
Kindly suggest me regarding the following:
Can we install and run WRF using virtual cpu's with the help of intel compilers. If yes, what is the minimum number of virtual cpu's are required to generate 72 hr forecast run with 15 mins temporal resolution and 9 km spatial resolution for 400 * 400 grid points for real time forecasts?.
Awaiting your reply,
Thanks & regards,
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.
I am looking for sources to learn about the computational methods applied to study atmospheric sciences. I have been learning computational fluid dynamics i.e. finite element and finite difference methods. Where should one start if one wants to study and get a good hold over the computational approach?
I have come across many statistical methods to study rarified medium and radiation matter interactions. Can anyone suggest a few sources regarding the same?
I am looking for video, exercise, practice options, books and tutorial of python for atmosphere and ocean science (climate, hydrology, hydro climatology, cryosphere).
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?
Can anyone please specify the HPC or server configuration details (including price, area and other factors into account) to run WRF-ARW over India (50 E to 110E and 10S to 45N) at least at 9 km resolution daily four times to generate 72hrs forecast. Please specify which compiler will satisfy the needs. If possible with gcc/gfortran, what is the minimum HPC or server configuration required including the price?
Thanks & Regards,
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.
I am getting all other data sets like Relative Humidity, U-wind, V-wind etc. in NCEP site (https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.pressure.html), But I am requiring Relative Vorticity in pressure levels. Can someone shed light on whether such product is available or not ?
Dear All This is Suman from IIT Kharagpur, India. I have a very silly query which described as follows. Any sort of insight is will be appreciated. Harmonic analysis is a basic mathematical technique used in various branches. In the field of meteorology and atmospheric sciences, we regularly use harmonic analysis for the elimination of annual (1st harmonic) and semi-annual (2nd harmonic) variation from different data. From the earlier literature it is noticed in most of the cases long term series of monthly data is used for that purpose. For example if there is a complete series of 30 (1951-1980) years monthly data (30*12=360 months), then to eliminate seasonal variability of the original data 1st, 2nd and sometime 3rd harmonics will be subtracted considering a Fourier series of 12 harmonics (for 12 months). Please make me correct it I am wrong. In my case, it is something similar but I don't have whole data as I am interested in seasonal study (Indian Summer Monsoon). I have also 30 years of data having only June, July, August and September. It means the data I have June, July, August of 1951, June, July, August of 1952 June, July, August of 1953 and so on. Now if I want to eliminate the seasonal harmonics then what to do? As I don't have data for all months, it is unscientific to use the above procedure for my data. Is the idea is only applicable for complete data (I mean having all months data)? Please help. Suman Maity Ph.D student IIT Kharagpur India.
If these organisms' threshold is exceeded, in the long run, will it develop evolutionary defenses or mechanisms to absorb too little or too much CO2?
This article says that the earth's CO2 level rose to 400ppm. I want to know its effects on upwelling, both in the short and long run. Also its effect on photosynthetic organisms which love CO2, and more importantly chemosynthetic organisms, which will have an abundance of CO2.
I'm a student of atmospheric sciences, and I'm analyzing two different hurricanes, I'm using latent heat flux data from NARR, but I'm not sure about the results that I obtain because all of them are negative values, which I interpret as condensation...I've read this from nasa's page https://svs.gsfc.nasa.gov/3199 and they obtained opposite values during the development of hurricane Frances, I don't know if I should multiply by -1 or there's an agreement for the interpretation of the results of this kind of data from NARR?
If I could have your help I'd be very greatful, this is part of the work I'm currently doing
Can anyone provide me the link which are free to download relative humidity (with hourly temporal resolution) with 1 day real time lag?.
Thanks & Regards,
Does anyone know how frequently sand storms and dust storms that arise from middle east or north africa travel to Pakistan and North India? I was wondering, in view of the already worsening air pollution levels in North India, events such as dust and sand storms reaching the subcontinent may exacerbate the situation. How rare or common are such sand and dust storms being carried from their place of origin (usually middle east and north africa) and intermix with fog or haze intensified by smoke or other atmospheric pollutants in another far off location? Has there been any similar, possible mixing of phenomena (dust storm and smog) reported/documented/studied anywhere around the globe at any time, preferably that was also caught by polar or geostationary satellites?
I was looking at a true-color or natural color satellite image acquired on 29th Oct. 2017 by the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the joint NASA/NOAA Suomi-National Polar orbiting Partnership (S-NPP) satellite around early afternoon. I've attached a screenshot of the image as well as provided the full link to access the satellite imagery. These satellite images have been stitched together to create a global mosaic. Unlike MODIS, VIIRS do not show any data gaps (except sun glints!). I found this satellite image particularly compelling because it clearly shows the sand storm picking up over northern Saudi Arabia and moving around Iraq, Iran, Caspian Sea towards Afghanistan with the movement of wind. I also think the Earth's rotation from west to east has a role to play in the movement and direction of the wind laden with sand and dust. But it seems difficult to understand their dynamics. The smog over North India and parts of Pakistan can be differentiated from the sand storm over middle east in this satellite image. In North India this is the time of the year when there are intentional crop fires due to the traditional slash-and-burn agriculture practice.
I need to downscale precipitation and temperature from IPCC4 GCMs (in LARS-WG) for the baseline and future in the Generator menu. Of course it generates future data once u select the GCM and time period but I can't understand the science in that and how to generate for the baseline data so as to calibrate and validate with the observed data.
Dear RG Community, I have the need to estimate the PBL height for the area of Milan (Italy) in two years (2011, 2014) as 12-hours values more or less. These data will be necessary to run a model for the estimation of airborne pollutants, removed by vegetation.
Searching in the web I found this database
but I don't know how and if it is "easily" possible to calculate PBL from them. I will be very gratefull if some collegue can help me to better deepen the problem. Thanks in advance.
I am comparing two rainfall datasets at different time scales (e.g. daily, monthly and annual). I am using mean error, mean absolute error and root mean square error. One way to make comparison is using mm/day for daily, mean mm/day for monthly and annual scale. But I am using accumulated rainfall, as a result, the error statistics is not comparable at different scales (error increasing as moving from daily towards annual scale). Kindly suggest how to normalize my error statistics to make it comparable.
I have measurements of pressure (p), temperature (T) and relative humidity (i.e. water vapour content, RH) and I'd like to know if there's a simple way to calculate atmospheric transmissivity from these quantities, and for the transverse (i.e. horizontal, same altitude) direction. I've looked at several atmospheric radiation models such as Modtran but these are all for depth-integrated calculations, and it seems to me that there must be a simple way to do this if we don't need to take into account the varying optical properties of the different atmospheric layers. Are these three measurements (and assumptions for the concentrations of other atmospheric gases such as 400 ppm CO2) sufficient? I'm specifically interested in transmission in the thermal infrared band (7.5-13.5 microns). Thanks for any help that you can provide.
Reading the related literature, although there were lots of paper regarding the effect of humidity on the output performance of PV panels, I have just seen two paper mentioned the effect of humidity on the accumulation of dust.
DOES ANY ONE KNOW ANY FURTHER STUDY OR CAN SHARE ANY INFORMATION IN THIS REGARDS?
1. According to the research done by Oguntoke et al , atmospheric humidity had negative correlations with dust fall. Mean relative humidity below 50% and mean wind speed above 4 m/s were predicted as critical levels for dust episodes incidence at sites that recorded “heavy” and “very heavy” dust fall.
2. Said and Walwil , showed that the adhesion increases with increase in humidity due to the presence of condensed water in the gap between the particle and surface which forms water capillary bridge between the bead and the surface. So dew drops in the morning as well as the amount of humidity could influence the process of dust accumulation.
 Oguntoke, O., Ojelede, M. E., & Annegarn, H. J. (2013). Frequency of mine dust episodes and the influence of meteorological parameters on the Witwatersrand area, South Africa. International Journal of Atmospheric Sciences, 2013.
 Said, S. A., & Walwil, H. M. (2014). Fundamental studies on dust fouling effects on PV module performance. Solar Energy, 107, 328-337.
I was trying to plot the global (spatial) distribution of a certain parameter (let's say temperature or precipitation). What I found that plotting a time averaged figure would not be effective in my case. I want to understand how a certain parameter is changing globally/ regionally on a temporal scale. Can any one suggest me any idea or plot type for such analysis?
Please, let me know how can I convert total precipitation unit (at ECMWF data) to mm per month?? ( I downloaded at 00:00 and 12:00 hours)
By preparing carbonate-rich water from deionized water and carbonate salts, the alkalintiy keeps changing over time. I assume there is a non-equilibrium with the atmospheric CO2, thus the constant change over days.
How can I produce synthetic water of known and fixed HCO3- content (at pH 8), avoiding this change of alkalinity over time?
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.
Conference Paper Helical Organization of Tropical Cyclones
I am examining long-term rainfall records. We have identified a 22-year cycle (this cycle is well known in South Africa) at our site, and have fitted a wave function to the seasonal (July to June, cumulative) data that spans 128 years. This gives a wave with 6 peaks (6 full cycles).
Research question: does the wave function predict the 13 (ca 10%) driest years?
Approach: I calculated that 20.5% of all possible years should fall within the lowest 10% of predicted rainfall values. (This is because of the shape of a sine curve; a linear ‘saw tooth’ function would include 10% of years in the lowest 10% of predicted values.)
Accordingly, it is predicted that, if randomly distributed, there should be 13 x 20.5% = 2.67 seasons within lowest 10% of predicted rainfall values (bottoms of the 'troughs'), and the rest should fall outside these troughs.
Results: It emerges that 7 of the driest seasons fell within these troughs. (I interpret this an an indication that this gives us some prediction capability as to when very dry seasons will occur.)
My question here: How can I determine statistically what would be a higher-than-expected number of dry seasons falling within the troughs? E.g. would it be four , or five, or what?
I've attached a graph showing the wave function and when the 13 driest years occurred, omitting the original data for simplicity.
The Southern Ocean [40~65S] accounts for about 15% of Earth's surface area. Satellite observations show that the Southern Ocean features near 90% of cloud coverage all year around. My question is what factors make the Southern Ocean so cloudy?
I'm looking for a long-term time series of the East Atlantic / West Russia (EA/WR) atmospheric circulation pattern. Ideally the time series would cover the last 200 years with decadal resolution at worst. Do you know any published sediment core, speleothem or whatever proxy from e.g. central Europe or western Russia that would capture this climate pattern and provide information about the long-term EA/WR dynamics?
Thanks for your help!
Working on High Resolution Radiossonde Profiles and open for collaborators.
We have a dataset comprising almost 76 hours with launching every 3 hours during 18 UTC 29 May to 21 UTC 01 June 2016.
Follow some plot of raw profile dataset as example.
If you have some interest on co-authoring this job, please be welcome.
Assume at some location clear sky OLR at TOA is 270 w/sq m assuming earth surface emissivity is one. Then say emissivity is 0.92. Then there will be scattering and reflection and some of the reflection will escape. Therefore what escapes is > 0.92 x 270 w/sqm. Say fraction of 270 w/sq m observed is Fr = 0.97 (It should be between 0.92 and one).
(a) Is there a name for Fr?
(b) Is there a "best" value for Fr averaged over earth's surface?
Its main use will be to gather weather parameters for wildlife research. I would need to leave it for at least 3 months in desertic and temperate environments. I can have access to it quite often so data retrieval or batteries should not be a problem.
I have 3-hourly precipitation of TRMM 3B42 for 17 years with HDF format . and I must compare this data with ground gauge station data . is there anybody know which software can I use for this goal?
Please how can we run seasonal trajectories (e.g. backward) of several years using the GUI of HYSPLIT model? In which option of GUI where we can combine several months (in order to create seasons: DJF, MAM, JJA and SON)
Hope to hear from you.
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?
The KP, CH equations were all obtained from internal wave models. some results are also obtained about the rotating fluid. I want to know whether they are also right for large scale atmospheric motions. Is it possible for us to derive the equations for the original equations by weakly nonlinear method.
And the ZK equation are used to simulate the motion of plasmas when considering the magnetic field, can we obtain a likely result for atmospheric motion for the original primitive equations.
I am trying to dimension an activated charcoal adsorber to remove ambient VOCs before the air enters a system where I will collect plant volatiles. Can anyone provide information on the required contact time of air and activated charcoal? How much activated charcoal do I need per volume of air?
I want to do my master thesis on geopotential height investigation over different pressure levels. I have 30 years historic data set, Please guide me what can i do for my master thesis with this geopotential height. My study area is south asia
I have a modeled output from WRF for both past and future climate (the output is every 30 minutes for 30 years.) I also have past observed station data (every 30 minutes). I want to bias correct my modeled data from the observed data to remove biases in my modeled output. Can anyone suggest me which is the best method to use in order to achieve this ?
In literature I found only slightly negative values for the Angstrom exponent for aerosol optical depth which occurs in presence of coarse mode aerosols. There is one work (Jaroslawski et al. 2003) where they had AODs reaching -10.
How is this for cloud drops?
We know that the standard density of air is 1.225 kg/m3 (at sea level, 15 oC, & 1 atm). The density, however, is not constant as it changes daily according to the local atmospheric pressure, temperature, elevation, and humidity maybe.
For a certain day(i), is it safe to apply the ideal gas law, i.e., ρi=PiM/RTi ? Is the elevation and humidity taken into account in this formula? Is there a better widely applicable recipes?
Your shared thoughts and discussions are highly appreciated,
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?
I have been bit confused about the accuracy and precision details mentioned about an Eddy covariance system, which comprises of a sonic anemometer and a C02/H20 measurement.
Usually for a Gill sonic and IRGA-Licor 7500, the accuracy and precision are mentioned like these:
3-D Sonic Anemometer, Gill Solent Windmaster Pro
Orthogonal wind velocities u, v, and w
Range: ± 20 m/s
Accuracy: u,v =1.5% root mean square (RMS) error, w =3% RMS error
Resolution: 0.01 m/s
Sonic temperature (from speed of sound (SOS))
Range: -40 to +60 deg C (307-367 m s-1)
Accuracy: 3% RMS error in SOS
Resolution: 0.02 deg C
Range: 0 to 110 mmol/m3
Accuracy: ~ 1% (limited by calibration procedure)
Precision: ~ 4 umol/m3
(typical RMS instrument noise)
Range: 0 to 2000 mmol m-3
Accuracy: ~ 1% (limited by calibration)
Precision: 0.14 mmol/m3
(typical RMS instrument noise)
By reading this, I can understand the RMS noise for the CO2 and H20 measurements are 4 umol/m3 and 0.14 mmol/m3 respectively.
But what about the RMS noise for velocity and sonic temperature measurements? Is it the resolution of u,v and w and T measurements which are mentioned?
I would be very grateful if any expert on EC system can clear this query of mine.
What are the advantages and disadvantages of Disdrometer for determining rain drop size distribution? And how about other methods like high-speed imaging or etc.? Which methods do you prefer if Disdrometer is not available?
It is an observed fact that presence of moisture in atmospheric air brings down the atmospheric pressure. What is the mechanism for this process and scientific reasons associated with this fact?
Scientists from weather,atmospheric science, environment and meteorology can give a clear picture of this phenomenon.
I am working on a project known as atmospheric water generator,where i am using silica gel as a desicant to extract water vapour from humid air and gets adsorbed.So i want to use that adsorbed water molecules to pure drinking water.Please suggest me the detailed methods on how to do so.
Hello everyone, I'm working on automation model CMAQ and need to know about tools to make operations with the different chemical species to produce the PM10, PM25 and others, I am interested in to know programs that allows me to automate this work like GrADS for WRF model outputs for example, any ideas?
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......
I downloaded total precipitation of the ERA INTERIM dataset but the unit is "m" and I'd like to convert to mm/day. Any help is very appreciated.
For example: tp = 0.19181 m => mm/day = ?
Though earth's atmosphere exists beyond 50 KM high and up to 100 KM, 99.9% air is only available up to 50 KM height. Water vapor is found only up to 10-12 KM, which factors are not favoring moisture to rise beyond this height?
Weather/Atmospheric/Environmental scientists can answer this question.
I am trying to simulate storm surge and inland inundation along the region of Bay of Bengal using ADCIRC model . Is there a way to get the required information for preparing the fort.14 and fort. 22 files from open sources or commercial.
The early proterozoic was the time when free oxygen was introduced to atmosphere (GOE) but, it is believed that earths environment was fully anoxic before GOE. Though, there are evidences of whiffs of oxygen before final introduction of free oxygen in the atmosphere. the large part of deeper ocean was anoxic or sub-oxic. In light of this background, I want to know the range of concentration of oxygen present in these environments.
measuring matter Moisture content commonly conducted by using oven then take the ratio of dry matter and wet matter. this method is so common and accurate enough but takes a long timewhile sometimes we need the value of water content as soon as posible. I ever heard MC meter could measure the water content of a material instantly but i wondering if its accurate enough as The "oven method" and also how this apparatus actually works.
NB:i measure water content of compost raw materials such Paddy straw, Bagasse etc.
Dear Respected Researchers,
I am developing an atmospheric correction method using Landsat data set and later, will also test on MODIS and VIIRS data sets. Therefore, I am looking for spectral reflectance measurements acquired in-situ using hand-held multi spectrometer. The location and size of area, and temporal frequency of the measurements don't matter. I understand that reflectance measurements are not freely available, and acquired by individual investigators using their limited financial resources. So, it will be highly appreciated and acknowledged if someone provide me surface reflectance measurements acquired in-situ.