Questions on downloading and processing ERA5 temperature tendencies
Hi there!
The summary of my question is as follows. Overall, there are three questions.
Q1. The speed of processing and downloading temperature tendencies is too slow.
I have downloaded the temperature tendencies in ERA5 with the horizontal resolution of 0.75 degrees for December-to-February for the period 1979-2022. Every time I download a tendency file containing one time step because the code provided ‘conversion_from_ml_to_pl.py’ could only deal with tendency files with one time step [see Q2 for details]. So I am wondering if there is any way to increase the processing and downloading speed of temperature tendencies?
Q2. The problem with the code ‘conversion_from_ml_to_pl.py’.
As mentioned above, only one time step file could be successfully converted from model level to pressure level. Once there are files with two or more time steps, I got the following errors like,
Not all required lnsp dimensions found -exiting ('time', 'step', 'latitude', 'longitude')
Not all required variable dimensions found -exiting ('time', 'step', 'hybrid', 'latitude', 'longitude')
Not all required variable dimensions found -exiting ('time', 'step', 'hybrid', 'latitude', 'longitude')
Not all required variable dimensions found -exiting ('time', 'step', 'hybrid', 'latitude', 'longitude')
Not all required variable dimensions found -exiting ('time', 'step', 'hybrid', 'latitude', 'longitude').
So I am wondering if you could help me to solve this question.
Q3. Which method is more suitable to interpolate the 0.75 degrees data to 1.5 degrees?
The relatively high horizontal resolution of 0.75 degrees makes our next calculation more time consuming. So we want to use a relatively low resolution of 1.5 degrees instead. However, as mentioned above, downloading temperature tendencies in ERA5 is much more time-consuming than downloading other common variables. So I am here to ask what kind of interpolation method is more suitable to interpolate the data from 0.75 degrees to 1.5 degrees.
Looking forward to any reply!
Best,
Bo Liu