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Questions related to Atmospheric Modeling
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Hi there,
I am new to atmospheric modeling. When I am trying to do some 0D chemical simulation, I find it difficult to specify the actinic fluxes change in the process. It seems that in most models the photolysis reactions are given with a photolysis rate that does not change with light of different intensity and wavelength. This could work for filed measurements as sun zenith angle is given or calculated. But if a chamber experiment is to be simulated, fixed photolysis rate cannot reproduce the actual condition.
Is there any 0D model that takes light intensity and wavelength into consideration to get a detailed simulation of photolysis reactions? Or any suggestions on model modification?
Thanks!
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Hello Duzitian Li, I work at EUPHORE simulation chambers. Even though I have little experience in modelling, I can tell you at least what I do when using the Master Chemical Mechanism (MCMv3.3.1 and AtChem2), a well-known box model for chamber simulations. We measure the jno2 in the chamber and I constrain it in the model. After that, the model calculate the other photolysis rates and declination degree if you do not provide them (taking into account the longitude, latitude, and day of the year). After that, you can also, by using a factor (jno2measured/jno2calculated), you can adjust your other photolysis rates.
On the website (http://mcm.york.ac.uk/roots.htt), you can find everything about this OD model, its mechanisms and how it calculates every photolysis rate way better detailed.
Cheers!
Rubén Soler
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Hi everyone
I am trying to run the CESM model, in order to evaluate teleconnection in a rising temperature levels, in low-mid atmosphere conditions and the rainfall patterns in the Andes of South America.
But, I am newbie in this, so I am having some troubles indeed, when I execute the ./create_newcase this command does not create a new folder into my directory, I was finding out what I did wrong but I am lost
Can anyone  help with this one?
Thanks a lot!
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That is a good question.
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HI everybody
I am trying to run the CESM-atm model, but I don't get where is the path for the data, I am attaching an image of what must be the structure of the path.
By the way, I am running this model in my personal lap, so I had to do the porting proccess before, so I don't  think that would be really the problem here.
Could anyone explain me what I must do for downloading the data for the model?
Thanks a lot!
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That is a good question.
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I am working on atmospheric modeling using AERMOD and I find it difficult to find the heights of various buildings surrounding the emission sites, especially in areas that cannot be represented in 3D on google earth. Is there another way of finding the height?
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Usually, the floor height of one floor in high-rise buildings is 3.5 m approx. You can estimate the building height by knowing the number of floors.
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I want to run WRF - ARW model for a small domain of 100X100 km at a grid size of 3X3 km or smaller for forecasting weather parameters, which will be used as an input in a crop simulation model to forecast crop yield.
I need to purchase the required hardware and software for it but I'm very confused of the requirements and specifications which are required for the purpose.
I seek help to answer the following questions:
(1) What is the minimum and optimum H/W specification required and available in the market (preferably in India).
(2) What Linux OS Version and other compilers that would required to be installed?
Thanks
Vinay Sehgal
Indian Agricultural Research Institute, New Delhi
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There is no need to use a very high specification to run WRF-ARW. Actually this depends on the resolution, region and time of forecasting. You need to install any suitable version of Linux such as Fedora, Obinto, etc. Then you should download, unpack, compile the source code that is available on the internet.
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I am working on atmospheric modeling and I seem to have a problem obtaining meteorological data for the area under study, Athi River in Machakos County and Industrial Area in Nairobi, both areas in Kenya. Any assistance would be appreciated
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Hello sir,
Just talk to the people working in the Kenya Meteorological department. I know they charge a fee but there is a way, if you state you are a student they can assist you.
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I am looking for some models that can provide visibility forecasting products. I found that ECMWF may have these datasets, but I don't know how to download these datasets. I hope someone can provide me some help. It can be a download link for data. It can also be the method of downloading data, I will be grateful to him.
Set I- Atmospheric Model high resolution 10-day forecast (HRES)
Set III- Atmospheric model Ensemble 15-day forecast (ENS)
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I want to know the medium range rainfall forecast datasets for Indian Region. Can you suggest me some sources where the data is available?
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Hello,
I am interested in how the concentration of O2 varies over time close to ground level. I have been informed that the concentration can drop when an inversion layer is present in the local area due to reduced atmospheric mixing and have seen this effect in data collected by my group.
What else can lead to O2 changes?
Also, what is the best way to identify when an inversion layer is present?
Background:
The reason for my asking is that my group use a constant value for oxygen concentration and use atmospheric air to calibrate our continuous gas oxygen analysers. These analysers are used for a clinical measurement called whole body room calorimetry, where we compare the changes in oxygen concentration of a room (nearly air tight) and air being pumped in to it. Further in the data processing, we calculate the amount of oxygen used by a person, which along with other gas exchange rates is used to calculate biological power output and fuel oxidation ratios.
Thanks for reading.
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Thank you Valerio!
That's all very interesting.
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Physical oceanography
Oceanography
Satellite oceanography
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Dear Jagadeesan,
You may check sentinel 3 data provided by ESA.
Best of luck!
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Did somebody use Ameriflux data before? And applied it into Penman-Monteith equation or calculating aerodynamic resistance?
When I need to compute the aerodynamic resistance, I need to know the canopy heights and measurement heights of each site in AmeriFlux first. But I really did not find the descriptions of these on the website of FluxNet. I can only find some of them in reference papers but just part of them. And this can take much time.
So, I wondered if somebody knows where I can find canopy heights and measurement heights for Fluxnet sites(like Ameriflux) easily, can you tell me or send me a link. I know I can "find" them but I did not find actually. Thanks for your time.
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I have published a paper named Determinants of the asymmetric parameter in the generalized complementary principle of evaporation. In the supporting information, you can find the canopy heights and measurement heights of 217 EC sites. To be noted, some of the canopy heights (e.g., for grass or wetland) are infered from refs.
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In the output of WRF model, clear-sky doesn't mean a clear sky day, which means may have some clouds in the sky. Then my question is how model treat the values at some cloudy grid points. Are the values will be zero. Could anybody give me an example, like SWDOWNC, SWUPTC  and so on.
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i agree with Mr.William
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What is the most accurate way of calculating wind direction (2D NESW), wind speed and vertical wind movement using 3D Ultrasonic Anemometer data in the form of uX-uY-uZ m/s (or U-V-W vector) data? I am looking for calculations, methods and/or sources for these approaches.
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I would like to download ensemble mean, daily data from the CERA-20C reanalysis product in a fast and efficient way.
In the following page:
CERA-20C Atmospheric model, daily data (enda) retrieval efficiency#20CAtmosphericmodel,dailydata(enda)retrievalefficiency-Requestingensemblemean(ep),multipleyears,surface(sfc)
an efficient script to download such type of data is provided. However, when I run the python script only one month at a time is downloaded from the server, and the downloading of the next month is queued. The resulting netcdf files are small, because I am interested on a small area and few parameters, and also the corresponding processing and downloading times are very short (1-2 seconds). However the queue time is around 1 hour. Since I need to download 110*12=1320 months, this procedure will take weeks instead of the few minutes that would be needed if the data would be downloaded all at once.
I wonder if there is a procedure to download all the data at once.
Here is the script that I'm using
#!/usr/bin/env python
import calendar
from ecmwfapi import ECMWFDataServer
server = ECMWFDataServer()
server.retrieve({
"class": "ep",
"dataset": "cera20c",
"date": "19010101/TO/20101231",
"expver": "1",
"levtype": "sfc",
"param": "166.128",
"step": "0",
"stream": "enda",
"time": "00:00:00/03:00:00/06:00:00/09:00:00/12:00:00/15:00:00/18:00:00/21:00:00",
"type": "em",
"area": "50/20/51/22",
"grid": "0.25/0.25",
"format": "netcdf", .
"target": "U10m_tot.nc",
})
Thank you.
Sebastiano
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Either the queue restriction is made by the server on your ip address (to reduce the traffic), or it is because of the method you use (the python script might be not effective)
For the former reason, there are some workarounds
  1. Use multiple computers, (if you use two computers, you can make one for odd years, and the other for even years, if you can use more computers, you can split the data between them, the mode computer, the faster you finish)
  2. Use a VPN service, that changes your IP address. After downloading each file, disconnect and reconnect the VPN to renew the IP, each reconnection may take 3 minutes, (less than one hour)
  3. Contact the site administrator asking to email the data for you all at once.
If the latter, try to modify the script, by :
  • specifying only one year in the "date": "19010101/TO/20101231", or maybe less, three months or so. it might works!
  • what is the "step": "0", stands for, read the documentation, it might be a setting to download more than a month each time.
  • try specifying only one area "area": "50/20/51/22".
Best regards
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The Madden-Julian Oscillation (MJO) event occurring earlier this year (2015) was said to be the strongest ever, based on its RMM index. I wonder if there is anyone ranking all the MJO events based on whatever criteria (e.g. RMM index, precipitation).
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As I know there is no historical ranking because (1) MJO discovered in 70s (2) still there is no universal accepted theory of MJO (3) reproduction of MJO by most GCM models is not doable.
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I'm facing with this problem since 2 weeks ago. I know that this is possible with grads, but to do this it is necessary the post processing of data. I think that this is possible with NCL.
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Hello José Francisco León-Cruz kindly see an NCL code at https://github.com/Anthony2Git/WRF_Research/blob/master/extract_lonlat_wrf.ncl that I created to extract T2 & T2MEAN timeseries from wrfout at specific locations based their latitude and longitude attributes.
Thanks
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Dear all,
    Is there any link to get real time solar data to verify my forecast results in India?
Regards,
Malleswararao M
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YES, via Solcast. And it is FREE
My company Solcast offers FREE access to solar radiation data for researchers like yourself, read more at:
And
We look forward to supporting you & other researchers on ResearchG
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I am getting confused with the different tools and their function in WRF-Chem. can any one suggest that which tool in WRF-Chem (MEGAN or MADE or others..) is appropriate for estimating temperature and precipitation for different concentration of CO2 and Aerosols as a forcing agent?   
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We have successfully compiled WRF-Chem software in specific domain, we have got various parameters. Which is the optimum parameter we can compare with the temperature obtained from ground monitored station ?
Thank you in advance...
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-Note the limitations of any suggested methods
-And what the conditions that considered during the simulations and/or the experiments.
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The methods for prediction of the dispersion of LNG are under intensive development and it is difficult to recommend any specific model at this stage. For the detailed information please consult the recent PhD thesis. The application of Computational Fluid Dynamics (CFD) is discussed in the PhD Thesis: “Liquified Natural Gas (LNG) vapor dispersion modeling with computational Fluid dynamics codes” by Ruifeng Qi. The text is available at:
The general review of available techniques is also presented in the dissertation by Walter Chukwunonso Ikealumba: “Mathematical Modelling of LNG Dispersion Under Various Conditions”, the text can be found at:
The limitations of existing models are discussed extensively in the above thesis.
Personally, I believe that the modeling of LNG vapors is much more complicated that simulation of traditional air pollutants, however, some of the experience, particularly with the meteorological data will be useful in modeling of this emerging air pollutant.
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The Earth's atmosphere is an important compartment of our planet with respect to climate and its changes. When developing atmospheric models to estimate the Earth's heat balance, estimating the partial volume of some of its molecules and particles is crucial. Hence an important starting point is the accurate estimation of the Earth's atmosphere volume and more specifically that of the lower part of the atmosphere, e.g., the troposphere. How does one proceed to accurately calculate the volume of the troposphere?
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Hello Frank,
This is an excellent observation; based on the recent review of the literature it is evident that the most commonly used (and the most accurate until now) is the estimate provided in my first answer. The issue of errors with respect to the spherical approximation is still in the center of an active debate. The most important element in this discussion is selection of a coordinate system for modeling of the atmosphere (both for weather and climate applications).
The interesting paper addressing the nuances of the problem was published recently in the QJRMS:
“Spheroidal coordinate systems for modelling global atmospheres”
Q. J. R. Meteorol. Soc. 134: 261–270 (2008)
In many of our current estimates there is a discrepancy between the spherical shape used in the dynamic models and the ellipsoidal formula used in JGR paper. There are definitely numerous justifications of this fact but certainly it is worthwhile to perform the corresponding estimates of errors in calculations related to atmospheric chemistry, mass balances and heating rates.
Sincerely,
Janusz
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I want to know how extract of precipitation data for specific coordinates (longitude/latitude) from the netCDF file that I downloaded. Or how to convert the file from netCDF extension to CSV file. I'll be Thankful for any help.
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Hi Adir,
The easiest way to extract a variable at a given point from a netCDF file is by using the NCO tools (free software), the command you need is (ncks):
ncks -v u10max,v10max -d lon,145.7292 -d lat,-40.9972 infile,nc outfile.nc
here I am extracting variables 'u10max' and 'v10max' from the point (145.7292,-40.9972) from the file 'infile.nc' and writing them to the file 'outfile.nc' (for a list of all the commands in NCO see: http://nco.sourceforge.net/#Definition)
You can convert any netCDF file to plain text (*.txt) using the command:
ncdump infile.nc > outfile.txt
Hope it helps,
Augusto
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I have been using a NCL script to for some data operation and visualisation. It takes two ".nc" files from two different folder as input and provides the output in the terminal. Now, I have around hundred files, for which the same script to be operated. I tried to read all the files in the folder and create a loop to carry forward the task, but failed. Concatenating the data from all files will not work for my case, since the files does not contain same length of dimension. Can anyone provide a solution for my case? Thanking everyone in anticipation !
P.S: I am attaching a screenshot of the NCL code for your reference. 
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I think the best option is to write a script in the shell (in Linux) or batch (in windows) along with NCL and CDO.  
The script helps you to call .nc file one by one and within the script your NCL or CDO code process the .nc file.
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I want to study the trend of cloud cover over an area of interest. I want to do monthly, annual and seasonal analysis for the same. I want to know about the generation of annual cloud cover data from monthly data
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You might be also interested in a Global 1-km Cloud Cover dataset based on 15 years of MODIS. Check the attached link.
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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?
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Having done some GIS analysis, and if I understand your question and goals about mapping in this case, you will always face an issue with averaging.  For example, say you have a temperature measure. That measure covers some amount of space.  Depending on where you make measurements, there is always going to be spatial variation in the temperature measure which could have a lot of parameters depending on the size of the space.  For example, I take a temperature measure at Point X.  How far away (X + n) does that measure reach?  Are there other climate factors within the space parameter (X + n) that could affect the temperature?  In other words, the temperature measure for a space is already being defined as an average for the space, even if you have multiple measures within that space.  If there is one measure, you are assuming it has some space scope, and it is the average for that space.  So, this can't be avoided at some level of conceputalization or analysis.
So even if you are using small space (ie. as in a hotspot analysis), your measure is still representing an average for that space, UNLESS you can argue that the temperature is the true measure of the actual temperature in that given space.
Now, across a given space (X) over a period of time, you could assess changes in temperature. I'm not really sure of the method here as applied to climate change, but NASA has a visual example, using radar images ....https://earthobservatory.nasa.gov/GlobalMaps/view.php?d1=TRMM_3B43M&d2=MOD13A2_M_NDVI
How you would model that statistically -- I'm not that smart!
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 I am working on a precipitation-run off model. I need accurate precipitation data for my study watershed located in a portion of Kansas, United State. I have some COOP stations in my watershed but these stations contain a bunch of missing data. As a solution, I downloaded grid data from PRIM for grid points where COOP stations are already located in my study area.
Is PRISM using observational data and just filling missing data with regression method or using simulation data for whole grid points and observational data convert to simulation data?
In other words, to increase the accuracy of my precipitation data, is it better to use PRISM data individually or is it better to use PRISM data just to fill temporal missing gaps in my observational data?
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Hi Shima,
As far as I know, PRISM uses weather station records to produce the grided date sets with 4km x 4km and 1km x 1km resolution using a numerical model which is a kind of regression model. I suggest you to have a look at DAYMET data set that provides the precipitation with 1km x 1km dataset. If I were you, I used PRISM dataset just for filling and missing records. 
Bests,
Mahyar
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I mean something similar to the Nusselt number in Rayleigh-Benard convection. We found an increase of heat transfer (Nusselt number) in helical-vortex RB convection
and would like to carry out a similar analysis for the rotating deep convection in the tropics.
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you have to calculate the Nusselt number, then the friction factor from the pressure drop and compare the results for each case by the following equation:
Efficiency = (Nu-Nuo)/((f-fo)^(1/3))
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Atmospheric phenomena:
* local displacement floating of Earth magnetic poles
* magnetic pole tilt and reverse orientation of magnetic field lines
Earth Meteorological and Climate Phenomena:
* Global Climate Change
Cosmic and Atmospheric phenomena:
* Solar activity (index) dynamics
* Solar wind and cosmic high energetiv particle radiation
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The question is if investigations have been done to a causal relationship among the above described phenomena mainly their long term dynamics.
Run short: Is long term climate (periodic) dynamics correlated to geological and cosmic (periodic) dynamics on long time scales?
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Both Aqua and Terra provide AOD value combining Deep Blue and Dark Target algorithm with corresponding Quality Flag value. They also have Aerosol cloud fraction data for corresponding grids. I want to use these AOD value for estimation of ambient PM2.5. I discarded the cells with QF less than 3 (as suggested by research). My query is whether further filtration of AOD values are required based on Cloud fraction data. That is, whether I have to discard those AOD value for which corresponding Cloud Fraction Value is approx.1.
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I have modeled Persian Gulf (salinity, temperature, and currents) by using  FVCOM model. meteorological data have downloaded in ECMWF web site. The model had unstabled before 2 year Run and temperature decrease to -20 degree centigrade.
Now I know the problem is heat flux data. Can anyone help me about  "Net surface heat flux" and "Shortwave irradiation flux at the surface (w/m2)"?
1- Where can I obtain "Net surface heat flux and Shortwave irradiation flux at the surface (w/m2)"?
2- How can I change heat flux coefficient in FVCOM model?
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Thanks a lot 
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Need help on decoding Sun Irradiation Meteo Weather IWEC or IMGW epw Data Formats. What are the names of data columns in epw file?
Here is example file.
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Standard names for column headers for epw files are, in order:
Year,
Month,
Day,
Hour,
Datasource,
DryBulb {C},
DewPoint {C},
RelHum {%},
Atmos Pressure {Pa},
ExtHorzRad {Wh/m2},
ExtDirRad {Wh/m2},
HorzIRSky {Wh/m2},
GloHorzRad {Wh/m2},
DirNormRad {Wh/m2},
DifHorzRad {Wh/m2},
GloHorzIllum {lux},
DirNormIllum {lux},
DifHorzIllum {lux},
ZenLum {Cd/m2},
WindDir {deg},
WindSpd {m/s},
TotSkyCvr {.1},
OpaqSkyCvr {.1},
Visibility {km},
Ceiling Hgt {m},
PresWeathObs,
PresWeathCodes,
Precip Wtr {mm},
Aerosol Opt Depth {.001},
SnowDepth {cm},
Days Since Last Snow,
Albedo {.01},
Rain {mm},
Rain Quantity {hr}
Those in the file given do not seem to deviate from these, based on the orders of magnitude in each column. Obviously beware of missing values (which are typically a slew of 9s).
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Does it meaningful for qualify the contribution from plant and soil to Bowen ratio (H/LET)? That is, are Hv/T (Hv is heat flux from vegetation/T is transpiration) and Hs/E (Hs is heat flux from soil layer/E is evaporation) meaningful?
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A generic intro to atmospheric balance can be found in lecture 14 of Dennis Hartmann nickname Dennis www.atmos.washington.edu. Bowen ratio is an approximation that is applied to uniform profiles.
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Dear All,
I would like to ask how should be the lowest vertical data interpreted if they are placed below surface level? For example, in the Alpine region with the average altitude of ~1500 m asl the vertical layers of 1000 or 975 hPa are very often significantly below the surface level (if calculation are based on geopotential height). How are those values then calculated? Is there any physical meaning of those data?
Kind regards,
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The situation described in your question is typical for all conversions between the sigma type coordinates employed in the model and the pressure based coordinates used for storing, displaying and collecting the meteorological data. In the case of variables below the terrain level the problem is particularly complicated. The results will vary significantly depending on temperature profiles (they are assumed) and the constraints imposed during extrapolation of the dynamical fields. The related problems are discussed extensively in the paper addressing vertical interpolation of meteorological fields
In my opinion there are still some opportunities to improve the existing methods of extrapolation.
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I need to download some meteorological parameters include precipitation,
temperature, pressure, wind speed, specific humidity, downward short‐wave radiation, upward short‐wave radiation, downward long‐wave radiation and upward long‐wave radiation.
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i got data from Fortran program to how can i plot data in Matlab?
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@Shreen Elsapa
After verification of the program I see that it works quite well. The arrays X,Y,Z,U,V,W appearing as the arguments in stream3 can be transferred directly from the fortran environment. In order to create nice graphical effects I would like to suggest using some additional routines (to supplement stream3) from the standard Matlab suite
streamparticles For plotting particles marking the flow
streamslice For plotting streamlines on the cross-sections
streamribbon For the display of flow with information about curl
streamtube For the display of flow with information about div
My general impression is that with the use of these 4 additional routines Matlab can easily match results obtained from more complex systems used for flow visualization.
I hope that this information is useful.
Sincerely, J. Pudykiewicz
PS. All the best in applying Matlab for flow visualization
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I am looking for measured irradiance data for some locations in India - for satellite irradiance data validation purposes. I was trying to get BSRN stations data, but they are not ready yet for India. I am not sure if IMD has data. I really appreciate your help for any information.
Thanks,
Alemu
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Dear Mohamed and Lucien,
Thank you very much for your time and information.
Best,
Alemu
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what are the main component of physics one should be careful about when using coarse resolution input data in WRF (say 225km x 225km) in order to reduce bias and errors?
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@Saurabh Singh i think Mr @Peter Hoffmann ant Mr @Sopan Kurkute gave dood suggestions. i may suggest in addition that first to examine the type of land use data (MODIS and USGS ) sometimes MODIS overestimates the surface température while USGS underestimates it.
If possible i recommend you to use observation nudging but that does not really solve meteorological problem
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I have been working on boundary-layer meteorology and turbulence for about 20 years. My jobs focused mainly on the turbulent processes in the CBL and their parameterization. I want to do something on the SBL.
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Thermal imaging camera can also be very useful for looking at spatiotemporal surface (or even fog top) temperature variation in very fine detail. This has been used to great effect for instance in the recent METCRAX-II and LANFEX field campaigns looking at SBLs in complex terrain in the USA and UK. Thomas et al (Boundary-Layer Meteorol (2012) 142:177–192) also use a very novel technique involving distributed fibre-optics to study vertical 2D slices of temperature over time under similar conditions. Though not directly, since they measure temperature, these options do allow some visualisation of turbulent processes.
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I want to calculate column amount of ozone using vertical profile data.
say  900-700 hPa  column amount of ozone.
I want to work on this in matlab. please share any matlab code in this regard and it will be very helpful for my work
Thanks in advance
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1) Compute the molecule number per layer: 
 O3[molecules/m3]= O3[ppm]*NA / TK * P /R /1000            
where
  • NA - Avogadro number  6.022E23 molecules/gmol
  • TK -Temperature Kelvin (layer mean temperature) 
  •  P - pressure in atm (layer mean pressure)
  • R - gas constant 82.057 mL atm /(K mgmol)
  • 1000 conversion factor (1000 mgmol=1gmol)
  • Note that 1 ppm = 1 mL/1'000,000 mL = 1 mL/m3
2) Compute the molecules per area by multiplying with the layer height
O3(molecules/cm2)= O3[molecules/m3] Height(m)(1 m2/10000 cm2)
3) Compute Total column by adding every layer
O3(Total)= O3(molecules/cm2)1 +O3(molecules/cm2)2 +... +O3(molecules/cm2)n
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Hello, I want to investigate the influence of different calculation of PBL height on the simulated results of WRF model. Can I use two different  methods( one is based on Richardson  number, the other is based on TKE profile) to calculat PBL height in the same   PBL scheme? If can not, how do it ? Thanks.
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Dear all
Thanks for your answers.
Sincerely yours
Yongqing Cai
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i am working on weather prediction project.objective is to predict rainfall.
i want station data of the india region having this parameters.
1 temperature,2.humidity,3.rainfall,4.water vapour,5.pressure,6.wind speed
i want the data without missing values(as it help to decrease the error)
.i tried to fetch the data from the different site but most of site is having indiavidual data like only rainfall ,only temperature,...
but as i want to train the model i want this all parameters together measured for particular station ofr for particular region
please suggest the freely available data(if possible)
i went through IMD PUNE site.(how much time it take to get the data in hand)
thank you 
suggestions are welcomed !!!
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Dear Sirs, 
I am working with drought indices and in order to accurately represent the spatial variability of the are I am working in, I need many weather stations. I do have ten stations with almost no gaps in the data but the rest of the stations have at least a 10-year gap. Is it possible to fill those gaps with satellite data and then perform homogeneity test in order ti detect breaks in the data? Shall I copy and paste the missing data or any kind of interpolation or preprocess is needed before "merging" both observed and estimated data from remote sensors? 
My area of interest is almost 150.000 km2, relatively flat so topography shouldn't be an issue in case an interpolation is needed. 
Thank you all very much
Regards, 
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Maybe you can also fill the gaps by the surrounding station data, assuming that the gaps do not occur at the same time. I think it is critical to fill up with a different type of data (derived variables from satellite), at least not without bias correction.
If the terrain is flat (as you state), the correlation length of the station data is usually high. Then, the correlation can be used for filling the gaps.
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Dear all,
I am looking for daily minimum temperature data (50 years back in time) for Russia and Japan.
Any suggestions highly appreciated.
Cheers
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Dear George,
very good idea. I will check if I can access.
Thanking all of you!!!!
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I am trying to determine the SSR, STR, SSRC and STRC for my region. After retrieving the NetCDF (details below), I multiplied the scale factor and added the offset. Thereafter, I divided the values by 21600 and 32400, for the steps of 6 and 9 respectively. I am still getting very high values. i.e. in the range of 105. I have attached the code I am using to extract data from the NetCDF file. It is a MATLAB Script. Could someone help with this? Thanks in advance.
Stream:Atmospheric model
Area:28.0°N 78.0°E 24.0°N 82.0°E
Type:Forecast
Dataset:interim_daily
Step:6, 9, 12
Version:1
Type of level:Surface
Time:00:00:00
Date:20160601 to 20160930
Grid:0.125° x 0.125°
Parameter:Boundary layer height, Surface net solar radiation, Surface net solar radiation, clear sky, Surface net thermal radiation, Surface net thermal radiation, clear sky
Class:ERA Interim
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Hi Eric and Chintan,
I sorted out the problem. Actually, on importing variables from NetCDF files, MATLAB automatically applies the scale factor and addition offsets. It need not be done manually.
So, I was actually applying the scale and offset twice, which was causing the high error values. Now, I am getting values quite within range. 
Thank you for all your help. 
Geet
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As I am not familiar with ECMWF data. I have obtained daily Climate Reanalysis data from ECMWF ERA-Interim. I have converted it to the text file and excel file format. The data obtained for various parameters are as follow;
Temperature, Min, Max Temp. Solar radiation, DewPoint Temp, SnowDepth   (Time:12  Step: 03), Precipitation (Time: 00 & 12   Step: 12), Sunshine duration(Time: 00 & 12  Step: 09). 
The required input file format of the model, for example, is as; 
Year--day--Temp--Prec--SRD--Daylength
2011--01---
2011--02---
2011--03---
---
---
2011--365---
2012--1---
2012--2---
---
2012--365--- and so on.....
The data obtained is not on daily format rather is a lot of data on time basis.
Would anybody help how to process this data to get daily data from day 1 to day 365 per year for each parameter?
Your guidance/help in this regard will highly be appreciated.
Thank you and regards,  
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Dear Arshad Ali Shedayi,
I am not able to get your objective properly, but as per my understanding, I can guide you about ECMWF especially ERA-interim datasets. 
First, you have to know about the entities involved in the ECMWF data.
ECMWF data contains both instantaneous as well as accumulated (flux) parameters.  
Now when you use any instantaneous parameters like temperature, dew point temp etc. You will have the value of that parameter at selected time, but in flux parameter, you will have accumulated value from your forecast start. Additionally, for instantaneous parameter, you can start your forecast from four different times (0,6,12,18) and you can select any of the forecast step (0,3,6,9,12), but for  accumulated parameter, you can start your forecast only for two-time (0 and 12) and you will have step options (3,6,9,12) but you can not able to get accumulated parameter on instantaneous time because accumulated means from some time to some time. It means from 0-hour to 3-hour, where instantaneous means at 0-hour or at 3-hour. 
Example.
Temperature:-
Temp is instantaneous value so you will get this at any time
Precipitation:-
Prec. has accumulated means you will get accumulated value between two times.
Now when you select the temperature and start your forecast with 0-hour and 12-hour with forecast step-3  than actually, you are running your model with available measurements at 0-hour and 12-hour and you are forecasting for 3-hours and 15 hours. So you will have temperature value at 3-hour and 15-hour.
Whereas, when you select precipitation for 0-hour and 12-hour with step 3. It means same as above you start your model at 0-hour and 12-hour with available measurements but you are having accumulated values for 0 to 3 hours and 12 to 15 hours. it means you have three three hours accumulated values of precipitation and you can not simply compare this accumulated values with instantaneous values. It is not that simple to work with this.
Hope I am able to make sense about the ECMWF data.
Thank you
With Regards
Piyush Patel
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Is the model ORCHIDEE available for public use or is it available for a few selected research organizations only?
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Hello Shawn
you are right its an error because of an absence of ksh shell, however, I would suggest getting the ksh shell rather than changing the shell. because you would find that many of the scripts in ORCHIDEE use ksh.
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Specifically, I'm looking for data from the Amazon region.
The models we use more often are WRF, BRAMS and RegCM, so any formats read by those models are useful.
Thank you!
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Hello,
Maybe the MUST project could interest you.
Biltoft, C.A. 2001. Customer Report for Mock Urban Setting Test (MUST). DPG Doc. No. WDTC-FR-01-121, West Desert Test Center, U.S. Army Dugway Proving Ground, Dugway, UT 84022-5000.
Best Regards
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I want to use WRF model for downscaling HadGEM2-ES and GFDL-ESM2M GCMs for future climate change projections (also reference period 1971-2000). But I want to know which dynamical core (ARW or NMM) is suitable for it where I have three nested domain with different resolutions.  
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Hi Mustafa,
ARW will be better choice for downscaling. ARW has more complex dynamic and physics settings than very limited choices in NMM. NMM is highly used for forecasting while ARW is for research and atmospheric sciences.
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I am trying to do Atmospheric correction for HYPERION L1 GST Image in FLAASH using ENVI 5.2. I have used Hyperion tool for converting the image to Cube using MTL data. And using Band math VNIR divided by 40 and SWIR by 80 to convert DN to Radiance. And merging the file using ENVI standard option in ENVI 5.2. Though I checked the literature, none of the spectra has showing higher value near 400 to 500 nm ie from Band 1 to band 30.
What is the reason for those values? What do i want to do or correct in my procedure? Please let me now.
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Dear Aravind
There are 220 unique spectral channels collected with a complete spectrum covering from 357 - 2576 nm. The Level 1 Radiometric product has a total of 242 bands but only 198 bands are calibrated. Because of an overlap between the VNIR and SWIR focal planes, there are only 196 unique channels. Calibrated channels are 8-57 for the VNIR, and 77-224 for the SWIR. The reason for not calibrating all 242 channels is mainly due to the detectors' low responsivity. The bands that are not calibrated are set to zero in those channels.
The digital values of the Level 1 product are 16-bit radiances and are stored as a 16-bit signed integer. The SWIR bands have a scaling factor of 80 and the VNIR bands have a scaling factor of 40 applied. The units are W/m2 SRµm. VNIR L = Digital Number / 40 SWIR L = Digital Number / 80.
bands 8 to 30  (427 nm to 651 nm) should not all have low values and this depends on the material (vegetation, built urban areas, water...etc). The values should be between 0 and 1.
It is obvious that you have error in doing atmospheric correction. Check your parameters.
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While searching for cosmic dust and debris from nuclear bomb tests, Christian Junge discovered in 1960 a layer of microscopic aerosol particles between the tropopause and about 18 miles (30 km) altitude. These particles are composed of sulfuric acid and water and are formed by the chemical transformation of sulfur-containing gases . This layer is called the Junge Layer or the Stratospheric Aerosol Layer (http://www.albany.edu/faculty/rgk/atm101/junge.htm). According to Solomon et al. (2011; Science) recent measurements demonstrate that the "background” stratospheric aerosol layer is persistently variable rather than constant, even in the absence of major volcanic eruptions. Several independent data sets show that stratospheric aerosols have increased in abundance since 2000. Near-global satellite aerosol data imply a negative radiative forcing due to stratospheric aerosol changes over this period of about –0.1 watt per square meter, reducing the recent global warming that would otherwise have occurred. Observations from earlier periods are limited but suggest an additional negative radiative forcing of about –0.1 watt per square meter from 1960 to 1990. Climate model projections neglecting these changes would continue to overestimate the radiative forcing and global warming in coming decades if these aerosols remain present at current values or increase.
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Indeed,  the Kremser et al paper is highly recommended, more insights into dynamical mechanisms you'll find in my 2015 ACP paper:
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Hi,
  I need ftp real time link to download cloud amount and Aerosol optical depth from MODIS. can anyone provide me this?. Instead of ordering data and analyzing data manually is not possible.
Thanks & Regards,
Malleswararao M
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Additionaly, FTP site of MODIS L2 atmosphere data is following,
Giovanni, providing L3 data, is another nice DB ! 
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I'm trying to apply the method of liu-liang 2010 [1]. They use potential temperature difference between 20mb and 5mb above surface and a threshold of 1K for land and 0.2K for ocean and ice. But in my situation, the location of interest (Istanbul, Turkey) is between 2 sea and, in my opinion, can not be classified either as land or ocean. So, I think that I need to choose different threshold for stability classification near surface. Is there someone that is familiar with boundary layer meteorology and can point me to the right direction on this issue? I actually prefer answers from someone that is familiar especially with this article.
1- Liu and Liang, 2010, Observed Diurnal Cycle Climatology of Planetary Boundary Layer Height
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Thank you for the answer, Mrs. Cazorla. My question was a little cursory, so let me detail. I have sounding data with 1mb vertical resolution and I apply a statistical smoothing method that minimize the error between data points. Soundings are at 02 and 14 local time twice a day. My purposes are to identify PBLH and define a proper critical bulk richardson number but also I need to determine the stability condition near surface. We know that the pollutants near surface are affected by PBLH but also by stability/instability. For instance, stratification in a SBL will definitely effect the measurements of pollutants. My final goal is to use the calculated/observed meteorological parameters as input in a statistical machine learning model and investigate the parameter importance objectively and estimate the model performance. This kind of algorithms has stability issues and results might change by removing/adding one or two outliers. So, I need to calculate inputs as much as precisely.
Let me emphasize that I know PBLH determination methods by sounding are developed under some subjective assumptions. They moslty do not give the real PBLH but a representation of PBLH. I'm ok with this. 
"A sharp positive gradient in the potential temperature vertical profile will indicate an inversion above the surface that signals the upper boundary of the mixing layer."
This is an indicator of SBL and a sharp negative potential temperature gradient (PTG) is also might be an indicator of CBL. At this time, I have to answer the question; What should be the PTG threshold to determine the SBL or CBL? In [1], Dai et al, determined sharpness of PTG as 6.5 K/100m for SBL and 1.0 K/100m for CBL over arctic ocean. I'm pretty sure there are a lot of thresholds for PTG in the around. Also if you have high resolution sounding data, there is always a possibility to catch a spurious sharp PTG (negative or positive) near very close to surface, especially in an urban area (For instance, heat island effect especially in summer nights). So, at least for an urban area, search algorithm for a sharp PTG should start from an exact height above the surface to detect PBL instead of urban boundary layer. Beside this, sharpest PTG method will be highly based on vertical resolution. If we inspect a sounding profile visually, a neutral profile might be selected as convective or stable by PTG method. The issues mentioned here are valid for mixing ratio, too. 
As a side note, lots of authors using sounding data avoid using relative humidity because of the measurement uncertainty. This is the reason why I'm trying to avoid using mixing ratio.
"If what you are looking for (aside from identifying pblh) is to identify stability and instability layers in your sounding data, then I suggest using the Skew T - log P diagram method. There are operational meteorology manuals that can lead you slowly through this graphical method to find those layers."
I'm looking forward an objective algorithm instead of a graphical method and mainly interested in near surface stability classification.
Apart from all of these, I compared correlation between PM10 concentration and potential temperature differences between different levels. PT difference between -1mb and -15mb above the surface gives me the best correlation (41%) with PM10 and let me emphasize that this is a significant peak. I know that PBLH or stability near surface is not only the parameter effects the dispersion of pollutants but the 8 years data might show this connection. Let's assume that you are reviewing a paper and authors of the paper selected -1 and -15mb above the surface to determine the stability based on 41% correlation. what would be your comment on this? Do you think that this is a reasonable approach?
At the end, I can calculate the PBLH in one or another way but I want to know what I did even if I make small mistake. I can use the PTG thresholds mentioned in [1] without questioning, but this makes me feel uncomfortable in the deep.
1- Dai, C., Gao, Z., Wang, Q., & Cheng, G. (2011). Analysis of atmospheric boundary layer height character-istics over the Arctic Ocean using the aircraft and GPS soundings. Atmos. Oceanic Sci. Lett, 4(2), 124–130. http://doi.org/10.1080/16742834.2011.11446916
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Hello
Can someone explain me what kind of data the CESM model use? and if it is observed or reanalysis? Futhermore, If is possible to run only the CAM model, using CESM compset?
I'm using the CESM 1_2_2 which I've already portted, but as I'm new working with this model, I need some help.
I hope any of you, who are more related modelling with CESM or CAM, can help me with this one.
Cheers!
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Dear Carlos,
Community Earth System Model (CESM):
The Community Climate Model (CCM) was created by NCAR in 1983 as a freely available global atmosphere model for use by the wider climate research community. The formulation of the CCM has steadily improved over the past two decades, computers powerful enough to run the model have become relatively inexpensive and widely available, and usage of the model has become widespread in the university community, and at some national laboratories.For more details see following links:
-CESM 1.0 Experiments, Data and Diagnostics
-CESM 1.2 Experiments, Data and Diagnostics
Here are linhs and attached files in topics
-Running CESM
- NCO 4.6.2-beta02 User Guide - SourceForge
- COLLABORATIVE PROJECT: OCEAN-ATMOSPHERE INTERACTION ...
Best regards
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Hi everyone
Can you advise me of changing atmospheric temperature in CESM-model. I've been running some cases, but there were just examples of different websites.
I know that I can built my own case, but I don't know how to change temperature in the model. I meant, what I want to find is, what would happen if the atmosphere get warmer, and what would be the changes in the rainfall patterns in the Andes region.
If anyone can help me sharing some link or anything that put me in the right direction, I will really appreciate it.
Thanks a lot!
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I think the best step to start is by reading the part of the POP2 FAQ that deals with this subject: 
In your case, search the code for "tavg_TEMP" and use that code as your guide for adding tavg_TEMP_2.  Note that you will also need to add TEMP_2 to your *_tavg_contents file in your $CASE/SourceMods/src.pop2 directory.
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I am getting relatively lower downward diffuse flux when I increase the ozone concentration in lower atmosphere at around 40 degree of solar zenith angle. Can we define this effects in terms of multiple scattering ? How?
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Dear Bikas,
I presume (1) you mean "lower downward diffuse solar radiation flux", and (2) you are working with a model of radiation transfer in the atmosphere, where you can modify the vertical profile of ozone concentration. Please confirm this.
Unless you are running your simulations for a region affected by a decrease in the stratospheric ozone (the so-called "ozone hole"), solar radiation is significantly absorbed in the relevant spectral bands (in particular in the UV) within that upper layer. Adding more ozone in the troposphere will have a limited impact in terms of absorption on the total downward irradiance at the planetary surface. However, please indicate how large an increase you are considering.
It is not clear to me that a marginally higher concentration of ozone in the troposphere will significantly change its scattering properties. However, if your model allows for a variety of chemical reactions and interactions between atmospheric gases and pollutants, it is possible that it predicts the formation of other airborne compounds which may result in additional absorption in other spectral bands or in a higher scattering, for instance if this results in the formation of particulates (aerosols).
Please provide additional information on your problem to solicit further ideas and perhaps more appropriate responses. Regards, Michel.
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Hi,
   I want to use GEOS5-AOD data (aerosol data as input to WRF in addition to GFS). Can any one help me where can I download GEOS5-AOD for India or Global data?
Thanks & Regards,
Malleswararao M
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Hello, recently I was also looking for GEOS5-AOD data and I found this page:  http://www.map.nasa.gov/cgi-bin/viewer.cgi?project
You will see two buttons at the bottom of the page. In "Public" button select the option "GEOS5 Aerosols (GEOS.fp.fcst.)" (there are other aerosol options so you must be sure this is the correct one) and click on "Select Project".  The rest is up to you.  I think you must be working with WRF-Solar.  I don't remember  if  what you find  in this page is exactly AOD at 550nm.
If you find a better way please answer me back. I'm also using WRF-Solar and I'm interested in aerosol data.  Thank you!!
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I followed the typical method of adding 9 components of transient eddies, stationary eddies and meridional circulation which I integrate using the method of simpson (equation attached in figures)
The figures are the annual average of daily data and zonal mean (not every 6 hrs as I need to compare with data from my experiments, which are daily mean), pressure is integrated between 1000 hPa and 300 hPa, because of Specific Humidity goes between these values.
First I calculate about 1 year of reanalysis data of NCEP / NCAR (1984) and then 10 years (1984-1994) looking for differences that might exist between the two calculations.
My problem is that I do not get a smooth curve MHT as seen in most publications, the amplitude is different (without having errors on the script and units).
What procedure must be used to obtain the curve MHT? there is a special process?
Thanks!
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I take between 700 hPa and 300 hPa and I got the amplitude value that I was looking for and a minimun/maximun at -+50 Lat, but now I have a lot of noise...  
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I have a serie of about 90 medium-range forecasts (3 months, daily) from 'old' and 'new' versions of the atmospheric model starting from the same initial data. How can I judge whether or not the change of serie-mean errors and scores (say, H500 RMSE) between two model versions is statistically significant. I suppose that there should be a conventional method to do it. The Student's t-test seems to be inappropriate in this case, because the errors of forecast (run each 24 hours) are autocorrelated and error series from 'old' and 'new' models are not independent.
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the best way is as followed: suppose that you have time series of both model, for example, rms time series of both for 500 hPa geopotentiel. you first compute time serie of difference.  Now 2 methods are used. First one is bootstrap or similar method, to compute an estimation of difference of rms distribution, and numerically  decide if the actually difference is significant or not (inside a chosen confidence interval). But successive bootstrap samples are correlated, and the result will be hardly corrupted. To have a good result, you must use the correlation correction as presented in Serge Farge paper, derived from Guy Der Megreditchian studies. But SG has proven that this boostrap method is  not efficient. you will have a more rapid and secure result by using student test, provided you decrease freedom degrees as it is presented in SF paper (always derived from GDM theory). Please ask us (SF or myself) if you need concret indication about these methods.
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Hello good to all,
Need your help to figure out  the problem in running WRF (nesting domain).
Actually, I am testing the model using nests, (10km ,5 km).There is the issue with executing real.exe. I guess it's with domain setting. however I have  followed  the mentioned steps, max dom: 2, start_time ,end_time, e_we and e_sn and dx, by, (from input.wps),history_interval, top_atmosphere etc.and linked met_em* as well but unable to find the error. 
There is the screen capture of the error if anyone knows how to solve this problem.(as it is still unable to run real.exe, I could not get rsl.error file).
thank you 
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Hi, for me the error  message indicates some error in namelist.input file. 
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I want to measure sensible heat flux in the optic path of the LI7500 above a forest canopy with eddy covariance, but the datalogger was just on the ground surface for an old version of colsed path system (LI7000), so I have to use long-cable to collect the10-hz data. But I found the sensible heat flux calculated from the long-cable thermocouples was 30% lower than that from the CSAT3. Direct comparison between two thermocouples (a 1 m long and 100 feet long cable) also get similar result.
I want to know why long-cable attenuated significantly. Thanks!
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Hi,
any cable acts as a resistance element and the cable length increases that resistance. Any voltage entering the cable will have a certain attenuation at the end of the cable. In the simplest case the attenuation is just a function of the cable length (direct current only) and the attenuation in terms of voltages can be calculated by
L(u) = 20 LOG u1/u2
when measured voltages u1 and u2. The actual attenuation is a function of cable length, material and also how the cable is constructed (shielded cable) etc. 
If the signal is changing with a certain frequency there is another factor depending on that frequency added up to the simple case attenuation and you get:
L(f) = k1 + k2 * f + k3 * Sqrt(f)
with k1 = L(u) the attenuation of the direct current (resistance), k2 the attenuation parameter of the dielectricum (alternating current) and k3 the attenuation parameter according to the "skin-effect" of a cylindrical cable. Info on these parameters should be given by the cable specifications.
hope that's helps you
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Hi, all
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.
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Robert Grumbine
Thank you very much sir
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Dear Researcher, 
I need guidance regarding extraction of precipitation data of my study area using TRMM or PERSIAN-CDR. Both these satellite data sets have daily and monthly precipitation data sets. I want to extract data for a specified catchment, I am not good in programming and Matlab. I only know how to read the files using matlab. Kindly guide me how to extract data for specified latitude and longitude, I will highly appreciate If you share Matlab code or any tutorial.
Regards
shahid 
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% This program is to read a TRMM 3B42 daily binary file
fid = fopen('3B42_daily.2009.05.31.7.bin', 'r');
precipitation = fread(fid, [1440, 400], 'float','b'); fclose(fid)
precipitation = rot90(precipitation);
 
for i_lat = 400:-1:1
for j_lon = 1:1440
    lat = 49.875 - 0.25*(i_lat - 1)
    if j_lon <= 720
         lon = 0.125 + 0.25*(j_lon - 1)
         else
          lon = 0.125 + 0.25*(j_lon - 1) - 360.0
         end
     daily_rain_total = precipitation(i_lat, j_lon)
     end
end
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I wish to model the stratospheric water vapor using remote sensing and geo spatial techniques in my summer project.
So, I want to know how we can model the stratospheric water content in the GIS environment and thereby I can do the comparison study with my calculated value?
And please provide me the links of the research papers done in this topic.
Thank you...
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I am looking at taking design rainfall estimates and fitting these to the SCS rainfall distributions and simulating these through a hydraulic model at a number of locations globally. Without further study analysing local rainfall patterns across the globe is it acceptable to use this approach. What are the limitations of this and what other quick approaches can be applied. Note I have considered triangular hyetograph methods and I do not have IDF relationships to use methods such as the alternating block and Chicago methods. 
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I am not in my computer, but will upload an example by Feaster et al of (USGS) using actual peak flow data from the various identified physiographic areas.  The SCS method is something I would not choose without some local validation or if I had better options.  Perhaps you will get a response of someone who likes the SCS method.
Alot depends on the risk, if you are wrong with flood peak and frequency predictions will lives and property be damaged, or will a remote logging or farm road blow out and have to be fixed.  On high risk sites and conditions, you want to find as much information as you can.  I just want you to understand that a model to be applied globally should get ample technical review, as people and communities may try to use it.  You may never know how it might be applied, so make sure you properly describe assumptions and limits, and see if you can find some data sets to validate it under varying circumstances.  
Of all the hydrology work, perhaps flood prediction and estimating its effects under varying circumstances is the most demanding responsibility.  Flood related deaths globally is high, so you are working on a needed subject.
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I am trying to build the meteorological database which ArcSWAT need. However I cannot find some of meteorological parameters which ArcSWAT need from the climate of Canada, include:
1.RAINHHMX(mon):Maximum 0.5 hour rainfall in entire period of record for month.
2.SOLARAV(mon):Average daily solar radiation for month (MJ/m 2 /day).
3.DEWPT(mon):Average daily dew point temperature for each month (ºC)or relative humidity (fraction) can be input.
4.WNDAV(mon):Average daily wind speed in month (m/s).
I can find hourly data of wind speed and dew point temperature, but I need daily data of them. I can calculate the average daily data from hourly data, but it is quite a big work, since in that way I have many years of data to calculate.About 'RAINHHMX', from Internet I saw some people believed that it could assume taking 1/3 of max daily rainfall of a month, but I am not sure this is believable.Besides, I can find the data of sunshine of duration from climate of Canada, so can I get SOLARAV(mon) from sunshine of duration?
Thanks a lot in advance.
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Dear Yiu,
1. RAINHHMX - The assumption of 1/3 of max daily rainfall has been addressed by senior researchers as good estimate in case of no other options. I have applied this assumption many times.
2. SOLARAV - If you have the daily sunshine duration data, you can get solar radiation by the "angstrom-prescott model" approach (search for it in google). However, you would need estimate values for couple of constants. Now if you manage to find some previous studies with those estimates for constants, then SOLARAV is done.
3 & 4. DEWPT and WINDAV - You mentioned that you already have hourly data for these. In that case, I think its just that you have to work to get daily data. At least you are lucky to have data to work with :-) . However, there is a short cut - Try googling "Pivot Table in Excel" to learn about a very useful tool for people working with loads of time series data like us. Using Pivot table in MS Excel, your hourly to daily conversion work will be much easier.
Hope it helps. Cheers!
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Does anyone know how to extract values from a netCDF? I dowloaded temperature data for the whole Mediterranean Sea from MYOCEAN database for a range of depths (1-5000m). I need to extract values of temperature at the lowest depth (bottom temperature) for my sampled stations (these varies between 10-800m depth.
Thank you very much in advance.
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Hi Vale!
Don't know if you have matlab but if you do
%% Open netcdf
ncid = netcdf.open('yourfile.nc','NC_NOWRITE');
%% Get all information about the netcdf file
fileinfo = ncinfo('yourfile.nc');
disp(fileinfo);
%% get info on a dimension
dim_0=netcdf.inqVar(ncid,0);
dim_1=netcdf.inqVar(ncid,1);
dim_X=netcdf.inqVar(ncid,X); (with X==max number dimension in the file)
%% get values corresponding to a dimension
var_0 = netcdf.getVar(ncid,0); (e.g. var_0=latitude)
var_1 = netcdf.getVar(ncid,1); (e.g. var_1=longitude)
var_X= netcdf.getVar(ncid,X); (e.g. var_X=SST)
All done!
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I am working on snow water equivalent model. As a part of it I use the semi empirical HUT emission model for simulating snow brightness temperature and my main problem is the extinction coefficient of the atmosphere and its transmissivity in 19 &37 GHz? There is some graphs for United States and Europe atmosphere but it doesn’t exist for Iran, and of course I don’t know enough about the atmosphere models and I’m not interested to go through it so much.
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Hello Mohammad.
A site you may want to visit is the following:
Then I am attaching a couple of papers that may help you.
Hope this helps...
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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 try to predict orbital life time of CubeSat  
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Hi 
I would like to learn more about EP flux and residual circulation. Recent studies using mainly GCM output and explain their results using EP flux and GW drag. As I learn from few study material, the EP flux is related to Eddies. Shall We use EP flux for explaining Tropical latitudes. I am also facing problem with plotting the EP flux vectors and residual circulation. So, I would like to learn in depth about these topics and also to get some hands on experience.
Thank you in advance,
With best regards
Kishore 
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Hi Kishore, 
For lecture notes I suggest starting on this site:
Chapter 11, which discusses wave drag and Eliassen-Palm flux, is probably what your looking for and at the end of the document there is a list of ten or so references, which are probably of interest. The link to the Chapter 11 pdf is below:
The site appears to be owned by Aarnout van Delden from Utrecht University, Netherlands. 
In terms of plotting EP flux vectors I'd suggest start by looking here:
which points to the links below for further advice on calculating and plotting EP flux divergence. 
There is also a reference to: 
Edmon, H.J., B.J. Hoskins, and M.E. McIntyre,1980:
Eliassen-Palm cross sections for the troposphere.
J. Atmos. Sci., 37:2600-2616
Hope that's of some help, 
Andrew
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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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I have a question and I hope that somebody can help me.
I am using SDSM model for downscaling global climate data (CanESM2 and NCEP data) to my study area. I need to make a calibration for these data with measurements data for the same period (1961-2005), but I need to use half of these data (1961-1990) for calibration and second half for validation (1991-2005). My question is: when I applied calibration process in SDSM model the software does not work for the period 1961-1990. Whereas, it works when I applied for the whole period (1961-2005) could anybody assist me?
Note: I do not have this problem with Temperature data.
Thanks in advance
Thanks in advance
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Please, change the question, because the calibration is an independent task but time-series, or other, statistical method of the precipitation parameters determined is also an independent task. 
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CO2 fluxes are in molecule/cm2/s. I don't know how to convert it into ppmv. I would be most grateful if anyone can give me some suggestions.
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Thank you sir.... than you for your information....