Hello,

I downloaded snowfall data from 1979 to 2020, once for all months and once for every month separately, as netcdf files; i.e. I have one .nc file containing snowfall data from Jan to Dec for 1979 to 2020 (all_months.nc), and then I have 12 separated .nc files each containing snowfall data of a month from 1979 to 2020 (jan.nc, feb.nc, ..., dec.nc).

I have noticed that the scale_factor and add_offset for snowfall data change, such that the unpacked values are slightly different despite looking at the same month (e.g. Values for October from all_month.nc are slightly different from those from oct.nc). I am calculating the yearly trends in snowfall for each month, and in some cases the trend change from having a significant trend to not having one as the p-value changes (even if the values of the slope is close). 

What would be the reason for such differences? Sorry if this is a simple question, and thank you in advance.

1 Comment

  1. Kevin Marsh

    Hi

    The scale_factor and add_offset are adjusted for each request to give an output netCDF file of a similar size to the input GRIB data size. The actual values sldo depend on the data range in the whole grib file, so I would expect some variation between different requests. How large are the differences you see?

    Thanks,
    Kevin


Feedback: C3S User Satisfaction Survey - CAMS User Satisfaction Survey

Web: C3S Help and Support - CAMS Help and Support