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If you are interested in downloading ERA5 (or any other data available on the CDS) soon, I have made a github repository explaining how to do so using the new beta version (and its API) of the store. This is explained using Alliance Canada cluster (cedar) and intended to help download big datasets automatically (e.g., hourly data for several years). Please note that this will only be possible on Cedar because it is the only cluster with computer nodes with access to the internet. 

Here is the link to the repository:

https://github.com/binmenja/cds-beta-api

The repo contains the scripts required and instructions to setup the API. You will have to change the paths to write the data and adjust the variables/region/period you want to download.

Please let me know if you have any questions or suggestions to improve the repo @ benjamin.riotbretecher@mail.mcgill.ca.

The ongoing climate change is driven by the greenhouse effect of such radiative gases as CO2. It however has been a challenge to acquire an accurate long-term radiation record, like the Keeling curve of the CO2 concentration, to irrefutably nail down climate change. Lei’s research found that the over 20-years AERI data measured at the SGP site presents such a highly wanted radiative Keeling curve and discloses interesting climate change signals of both CO2 itself (climate forcing) and mid-latitude clouds (climate feedback).

I just made public my GitHub repository with a Matlab library for RRTMG, which I had announced here and had stored on Guillimin.

https://github.com/blyankinshtein/rrtmg_libraries

The library contains functions to run both RRTMG Longwave and Shortwave, by creating tape-files from ERA-Interim data and some standard atmospheric profiles.

Any questions are welcome. Enjoy!

This is the method I used to compute vertical integration of energy flux based on ERA-Interim 4 times daily datasets. It mainly includes how vertical integral should be done based on model level and what errors may results in if adopted improper integration scheme.

Variables should be based on model level and please refer to Trenberth 2002 to see the comparison between the difference between the computation under model level and pressure level.
The dimension of each variable is ntime*nlev*nlat*nlon. As I focus on one time slice computation, time dimension is 1.

Take thermal energy flux VT as an example.
V and T are both defined on midpoint layer and their dimension is 60*nlat*nlon. Here are the calculation steps:
1. compute VT=V*T at each layer (60*nlat*nlon)
2. calculate the pressure of each layer under vertical hybrid coordinate.
Note: nlev of vertical hybrid coordinate is 61 as we want to know the pressure of layer interfaces associated with hybrid coordinate. In this way, we can get the pressure difference between two adjacent layer dp = p(lower)-p(upper) (60*nlat*nlon)
3. do vertical integration, sum(VT*dp) at each layer.
Done!

Previously, I mistook that V and T are defined at layer interfaces and took the average of VT between two adjacent layer to represent the thermal flux between these two layers. Actually as V and T are already at midpoint layer, I shouldn’t do average again. And the underestimation of this wrong method can reach about 1/3 at some place. Experience in tears…

Hope this will be of help to you😊.