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Why is re-initialization of WRF needed if metgrid provides met_em files every hour?

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userwrfch

Member
Hi,

I am using WRF to downscale hourly ERA5 data in 2016. I read that it is best practice to do short model runs, e.g., 365 runs for 1 day, where each run is 36 hours long and the first 12 hours are spin-up time. I read that WRF needs this re-initialization in order not to diverge too much from the upper-level meteorological fields, which provide the boundary conditions.

From WPS, I get hourly met_em files, so I am wondering why I need this re-initialization of WRF, as wrf.exe gets input from the boundary conditions through the met_em files for every hour separately? How can it diverge from the boundary conditions if it gets input every hour? Or what am I missing?

Any help would be appreciated.
 
Hi,
It should not be necessary to run WRF in the way that you've read. It's perfectly fine to run for a full year at a time. You only need spin-up of about 12 to 24 hours before the start of the run. Can you provide the source where you read this? Thanks.
 
Thank you very much for the help!

I read this here:
https://www.researchgate.net/post/What-is-the-best-WRF-run-practice-for-long-periods-simulation

and in a couple of papers, e.g. here (they use a similar framework than me):
https://www.researchgate.net/publication/341990951_WRF-based_Dynamical_Downscaling_of_ERA5_Reanalysis_Data_for_High_Mountain_Asia_Towards_a_New_Version_of_the_High_Asia_Refined_Analysis

"The forcing strategy was daily re-initialization [...]. Each run started at 12:00 UTC and contained 36 hr, with the first 12 hr as spin-up time. This strategy avoids the model from deviating too far from the forcing data and provides computational flexibility since daily runs are totally independent of each other and can be computed in parallel and in any sequence."

But it is good to know that it is not necessary in my case. Thanks!
 
It's not necessary if you're using reanalysis. I think using short runs is useful if you're using data assimilation or using wrf for forecast.
 
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