Function to compute true monthly mean from daily mean.

[dabail10]

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Description

I was trying to fix some bad monthly and daily means from the CESM-CICE history files. @jessluo came up with a script to do a group my year and month. We thought this would be a nice addition to esmlab.

What I Did

The path of the data is:

/gpfs/fs1/p/cesm/pcwg/timeseries-cmip6/b.e21.B1850.f09_g17.CMIP6-piControl.001/ice/proc/tseries/day_1

case = "b.e21.B1850.f09_g17.CMIP6-piControl.001"
year1 = "0061"
year2 = "0099"
year1m = "0001"
year2m = "0099"

filename_month = "../month_1/"+case+".cice.h.aicen."+year1m+"01-"+year2m+"12.nc"
filename_day = case+".cice.h1.aicen_d."+year1+"0101-"+year2+"1231.nc"
filename1 = case+".cice.h1.aicen_d_fix."+year1+"0101-"+year2+"1231.nc"
filename2 = case+".cice.h.aicen_fix."+year1m+"01-"+year2m+"12.nc"

ds = xr.open_dataset(filename1)
ds_day = xr.open_dataset(filename_day)
ds_month = xr.open_dataset(filename_month)

aicen_d = ds['aicen_d']

times = ds_day.time_bounds.values
print(times)

leftbounds_yr = [x[0].timetuple()[0] for x in times]
leftbounds_mo = [x[0].timetuple()[1] for x in times]

yrmo = [cftime.datetime(y, m, 15) for y,m in zip(leftbounds_yr,leftbounds_mo)]
yrmo = np.array(yrmo)

print(yrmo.shape)

aicen_d_val = ds.aicen_d.values

aicen_d = xr.DataArray(aicen_d_val, coords={'time':yrmo, 'NCAT':ds.NCAT, 'TLON':ds.TLON, 'TLAT':ds.TLAT},
                       dims=('time','nc','nj','ni'))

aicen2 = aicen_d.groupby('time').mean(dim='time')

aicen = ds_month['aicen']

aicen.values[720:][:][:][:] = np.where(aicen2.values[:][:][:][:]>1.,1.0e30,aicen2.values[:][:][:][:])

print(aicen.values[0][4][370][180])

aicen.to_netcdf(filename2)

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[andersy005]

@dabail10 & @jessluo, thank you for putting this together!

Let us know if you would be motivated enough to put together a pull request to esmlab to do this.

[dabail10]

We would need help formulating this as a more general function that would fit in esmlab. I don't really feel confident about doing that at this point.

[andersy005]

We would need help formulating this as a more general function that would fit in esmlab. I don't really feel confident about doing that at this point.

No worries. I'll handle it for you. Looking forward to your future contributions to esmlab whether it's through issues or pull requests.