# In[11]: plt.figure() plt.plot(star['tau']) # In[11]: plt.figure() plt.plot(star['utc'],star['tau']) # In[13]: star['ref'] = Sp.smooth(star['ref'],20) # In[14]: plt.figure() plt.plot(star['utc'],star['ref'],'x-') # ## Load the important MODIS files # In[12]: myd06_file = fp+'MODIS\\MYD06_L2.A2013050.1725.006.2014260074007.hdf'
# <codecell>
# first convert measurements to Sp class, with inherent parameters defined
meas = Sp.Sp(m)
meas.params()
# <markdowncell>
# Plot the parameters for the specified time
# <codecell>
fig2,ax2 = plt.subplots(5,3,sharex=True,figsize=(15,8))
ax2 = ax2.ravel()
for i in range(meas.npar-1):
ax2[i].plot(meas.utc,Sp.smooth(meas.par[:,i],3))
ax2[i].set_title('Parameter '+str(i))
ax2[i].grid()
ax2[i].set_xlim([17,19])
if i > 11:
ax2[i].set_xlabel('UTC [h]')
fig2.tight_layout()
plt.show()
# <headingcell level=3>
# Prepare the LUT for the modeled spectra
# <codecell>
iwat = np.argmin(abs(ssfr.tmhrs-twat))
# In[36]:
alb = ssfr.nspectra1/ssfr.zspectra1
alb[alb<=0.0] = 0.0
alb[alb>=1.0] = 1.0
alb[np.isnan(alb)] = 0.0
# In[37]:
plt.figure()
plt.plot(wvl,alb[iwat,:],'b.')
plt.plot(wvl,Sp.smooth(alb[iwat,:],6),'r')
plt.xlim([350,1700])
plt.ylim([0,1])
plt.ylabel('Albedo')
plt.xlabel('Wavelength [nm]')
plt.title('Surface albedo, above water UTC: %.4f' % ssfr.tmhrs[iwat])
plt.savefig(fp+'dc8/'+daystr+'_surface_albedo_ice.png',dpi=600,transparent=True)
# In[38]:
plt.figure()
plt.plot(wvl,alb[iice,:],'b.')
plt.plot(wvl,Sp.smooth(alb[iice,:],6),'r')
plt.xlim([350,1700])
try:
ccn[i] = recarray_to_dict(ccn[i])
except:
pass
ccn[i]['alt'] = nearest_neighbor(hsk[i]['Start_UTC'],hsk[i]['GPS_Altitude'],ccn[i]['UTC_mid'],dist=1.0/3600.0)
# ## Check out AMS data
# In[185]:
plt.figure()
cs = ['r','g','b','k','c','y']
for i,d in enumerate(days):
#plt.plot(ams[i]['UTC_mid'],ams[i]['Org_STP'],'x',color=cs[i],label=d,alpha=0.3)
plt.plot(ams[i]['UTC_mid'],Sp.smooth(ams[i]['Org_STP'],16),'-',color=cs[i],alpha=0.6,label=d)
plt.legend(frameon=False)
plt.xlabel('UTC')
plt.ylabel('Org_STP')
# In[210]:
plt.figure()
plt.plot(ams[2]['UTC_mid'],Sp.smooth(ams[2]['Org_STP'],14))
plt.plot(ams[2]['UTC_mid'],Sp.smooth(ams[2]['SO4_STP'],14),'-g')
plt.plot(ams[2]['UTC_mid'],Sp.smooth(ams[2]['Chl_STP'],14),'-c')
plt.plot(star[2]['Start_UTC'],star[2]['COD']/200.0,'xk')
plt.plot(star[2]['Start_UTC'],star[2]['REF']/100.0,'+r')
plt.xlim(15,15.8)
