In [1]:
%run basics
%matplotlib
In [2]:
ncname=qcio.get_filename_dialog()
In [3]:
ds=qcio.nc_read_series(ncname)
In [12]:
Fsd,f,a=qcutils.GetSeriesasMA(ds,"Fsd")
Fc,f,a=qcutils.GetSeriesasMA(ds,"Fc")
Ts,f,a=qcutils.GetSeriesasMA(ds,"Ts")
ustar,f,a=qcutils.GetSeriesasMA(ds,"ustar")
In [15]:
Fc_night=numpy.ma.masked_where(Fsd>10,Fc)
ustar_night=numpy.ma.masked_where(Fsd>10,ustar)
Ts_night=numpy.ma.masked_where(Fsd>10,Ts)
Fc_night_filtered=numpy.ma.masked_where(ustar<0.4,Fc_night)
Ts_night_filtered=numpy.ma.masked_where(ustar<0.4,Ts_night)
Fc_night_filtered_mean=numpy.ma.mean(Fc_night_filtered)
ustar_min=numpy.ma.minimum(ustar_night)
ustar_max=numpy.ma.maximum(ustar_night)
In [11]:
fig=plt.figure()
plt.plot(ustar_night,Fc_night,'b.')
plt.plot([ustar_min,ustar_max],[Fc_night_filtered_mean,Fc_night_filtered_mean],'r-')
plt.xlabel("u* (m/s)")
plt.ylabel("NEE (umol/m2/s)")
plt.show()
In [18]:
fig=plt.figure()
plt.plot(Ts_night_filtered,Fc_night_filtered,'bo')
plt.xlabel("Ts (C)")
plt.ylabel("NEE (umol/m2/s)")
plt.title("Howard Springs: Nocturnal NEE vs Ts")
plt.show()
In [ ]: