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First download the esmf tar file from http://www.earthsystemmodeling.org/esmf_releases/public/ESMF_7_1_0r/reg/ESMF_Framework_Down.html Then install netcdf library and gfortran compiler using sudo apt-get install git tcsh pkg-config sudo apt-get install gfortran sudo apt-get install netcdf-bin libnetcdf-dev libnetcdff-dev sudo apt-get install openmpi-bin ...


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When I look at problems like these I first check to see if there is a well tested and well documented implementation already rather than reinventing the wheel. In this case MetPy temperature advection is a well tested software that does many of the things meteorologists want including calculating finite differences with the right map scale factors. Since ...


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I got the solution https://www.researchgate.net/post/How_to_convert_the_units_of_specific_cloud_liquid_water_from_ERA5_kg_kg_to_kg_m2 and https://www.nwpsaf.eu/site/download/documentation/rtm/docs_rttov12/rttov_gas_cloud_aerosol_units.pdf In the above link the conversions between $\small\mathsf{kg/kg}$ , $\small\mathsf{g/m^3}$ , $\small\mathsf{kg/m^2}$ ...


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Based on an answer from ECMWF support which OP can confirm to my best understanding relative vorticity in the ECMWF model is not calculated using grid points and finite differences (centered and forward and backward). Instead it is calculated using spectral approaches in meteorology. There is a package in Fortran called spherepack and a python wrapper as ...


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The simplest way I've found in Python is to use the getvar function with the 'ua,' 'va,' or 'wa' variables from the WRF-Python module. Alternatively, you can take the midpoint between the staggers. Edit: For example, using the WRF-Python module, you can get the destaggered wind variables with the following code import netcdf4 as nc import wrf f=...


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I've come to a solution. I have followed @gansub's suggestion to check what there is already there, before reinventing the wheel. I found MetPy's code very (too) well structured, so the code for advection was sparse among several different functions; not so immediate to trace back and put a function together. However, GrADS brings a very nice example on how ...


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So i don't know for how many timesteps you've integrated. And I don't really understand what you have done to obtain the temperature $\rm T[t,s,y,x]$ in your second box, but this seems a bit like a redundant operation: the end result is $T:=T$, so of course your right side looks like the left side, in terms of the temperature colourmap. I don't understand ...


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