I’m trying to get JULES to calculate the average over the time interval 11.30-13.00 of a 15 day time period. For now I think it is averaging over the whole day. And I am trying to do a similar thing with light co2 and surface pressure.
Hi Wenyao:
You can see that t_growth_gb is computed from tl_1_gb.
If you look in the code for tl_1_gb with grep -ir tl_1_gb (after first changing directory to the root directory of your code repository), you can see where that is defined. It turns out to be defined as forcing%tl_1_ij, so you can do a grep -ir tl_1_ij * | grep -v ‘ftl_1_ij’. The extra grep is to not print out lines that have ‘ftl_1_ij’.
You will see a line of the grep output that says: src/io/model_interface/populate_var.inc: CALL cube_get_data(cube,forcing%tl_1_ij)
So the forcing data for near-surface air-temperature tl_1_ij is read in from the forcing data files, as defined in your suite.
The tl_1_gb is the near-surface air temperature for compressed-to-landpoints (depending on the landpoint index l, whereas the tl_1_ij is the near-surface air temperature for i,j coordinates before compression to landpoints. Both are in Kelvin.
I also see crop_vars%tl_1_day_av_gb in that same file that you have.
So you can do grep -r tl_1_day_av_gb *.
One of the grep lines shows: src/science/vegetation/crop_date_mod.F90: tl_1_day_av_gb(l) = tl_1_day_av_gb(l) + tl_1(i,j) / REAL(tspd).
Maybe you can use similar code for what you want? You might need to get the crop model fully working with your suite to do that?
Patrick
Thanks for your reply. Just to make sure I understand what you mean. Are you saying that I have to change the definition of my forcing data files otherwise I would not be able to limit it down to a smaller time frame? And thank you for pointing for the tl_1_day_av_gb. I will take a look at that as well.
Hi Wenyao
Yes, I suspect that you might be using 6-hourly forcing data. If you want averages over 1.5-hour time periods over 15 days, you probably need forcing data with time increments of less than or equal to 1.5 hours.
Pa
Thanks for your help. In that case would it work if I simply interpolate the data into a higher frequency and only keep the data from 11.30-13.00? Will this affect the rest of the model.
Hi Wenyao
Interpolating to higher frequency might be a good first step, but in reality, I think you need native high-frequency data to do what you want to do. Otherwise, you will likely miss the phenomena around noon that you want to observe.
Patrick
