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budgetStuff
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wpthlp_dp1=np.mean(np.array(zm.variables['wpthlp_dp1']),(2,3))
wpthlp_mfl=np.mean(np.array(zm.variables['wpthlp_mfl']),(2,3))
wpthlp_cl=np.mean(np.array(zm.variables['wpthlp_cl']),(2,3))
wpthlp_sicl=np.mean(np.array(zm.variables['wpthlp_sicl']),(2,3))
wpthlp_forcing=np.mean(np.array(zm.variables['wpthlp_forcing']),(2,3))
wpthlp_mc=np.me
wpthlp_ta=np.mean(np.array(fzt.variables['wpthlp_ta']),(2,3))
wpthlp_tp=np.mean(np.array(fzt.variables['wpthlp_tp']),(2,3))
wpthlp_bp1=np.mean(np.array(fzt.variables['wpthlp_bp1']),(2,3))
wpthlp_bp2=np.mean(np.array(fzt.variables['wpthlp_bp2']),(2,3))
wpthlp_pr1=np.mean(np.array(fzt.variables['wpthlp_pr1']),(2,3))
wpthlp_pr2=np.mean(np.array(fzt.variables['wpthlp_pr2']),(2,3))
wpthlp_pr3=np.mean(np.array(fzt.variables['wpthlp_pr3']),(2,3))
wpthlp_dp1=np.mean(np.array(fzt.variables['wpthlp_dp1']),(2,3))
wpthlp_splat=np.mean(np.array(fzt.variables['wpthlp_splat']),(2,3))
#wpthlp_ma=np.mean(np.array(fzt.variables['wpthlp_ma']),(2,3))
#wpthlp_cl=np.mean(np.array(fzt.variables['wpthlp_cl']),(2,3))
#wpthlp_sdmp=np.mean(np.array(fzt.variables['wpthlp_sdmp']),(2,3))
#wpthlp_ac=np.mean(np.array(fzt.variables['wpthlp_ac']),(2,3))
wp2_ta=np.mean(np.array(zm.variables['wp2_ta']),(2,3))
wp2_bp=np.mean(np.array(zm.variables['wp2_bp']),(2,3))
wp2_dp1=np.mean(np.array(zm.variables['wp2_dp1']),(2,3))
wp2_dp2=np.mean(np.array(zm.variables['wp2_dp2']),(2,3))
wp2_pr1=np.mean(np.array(zm.variables['wp2_pr1']),(2,3))
wp2_pr2=np.mean(np.array(zm.variables['wp2_pr2']),(2,3))
wp2_pr3=np.mean(np.array(zm.variables['wp2_pr3']),(2,3))
wp2_splat=np.mean(np.array(zm.variables['wp2_splat']),(2,3))
wpthlp_tp=np.mean(np.array(zm.variables['wpthlp_ta']),(2,3))
wpthlp_bp=np.mean(np.array(zm.variables['wpthlp_bp']),(2,3))
wpthlp_pr3=np.mean(np.array(zm.variables['wpthlp_pr3']),(2,3))
wpthlp_pr1=np.mean(np.array(zm.variables['wpthlp_pr1']),(2,3))
ax1.plot(wpthlp_ta[t,:],alt,label='wpthlp_ta')
ax1.plot(wpthlp_bp[t,:],alt,label='wpthlp_bp')
ax1.plot(wpthlp_pr1[t,:],alt,label='wpthlp_pr1')
ax1.plot(wpthlp_pr3[t,:],alt,label='wpthlp_pr3')
import numpy as np
import matplotlib.pyplot as plt
from netCDF4 import Dataset
zm=Dataset('dycoms2_rf01_zm.nc')
thlp2=np.mean(np.array(zm.variables['thlp2']),(2,3))
alt=np.array(zm.variables['altitude'])
fig, ax = plt.subplots()
for t in range(0,360):
ax.cla()
# ax.plot(thlm[t,0:100],alt[0:100],label='thlm')
# ax.plot(thvm[t,0:100],alt[0:100],label='thvm')
# ax.plot(thlprtp[t,0:100],alt[0:100],label='thlprtp')
# ax.plot(thlprcp[t,0:100],alt[0:100],label='thlprcp')
ax.plot(wp2bp[t,0:100],alt[0:100],label='wp2_bp')
ax.plot(thlp2[t,0:100],alt[0:100],label='thlp2')
ax.set_xlabel('[K]')
ax.set_ylabel('height [m]')
ax.set_xlim(-0.0025,0.01)
ax.legend()
ax.set_title("t = {}".format(t))
plt.pause(0.05)
plt.close()
import numpy as np
import matplotlib.pyplot as plt
from netCDF4 import Dataset
zm=Dataset('dycoms2_rf01_zm.nc')
wpthlp=np.mean(np.array(zm.variables['wpthlp']),(2,3))
alt=np.array(zm.variables['altitude'])
wpthlp_bt=np.mean(np.array(zm.variables['wpthlp_bt']),(2,3))
wpthlp_ma=np.mean(np.array(zm.variables['wpthlp_ma']),(2,3))
wpthlp_ta=np.mean(np.array(zm.variables['wpthlp_ta']),(2,3))
wpthlp_tp=np.mean(np.array(zm.variables['wpthlp_tp']),(2,3))
wpthlp_ac=np.mean(np.array(zm.variables['wpthlp_ac']),(2,3))
wpthlp_bp=np.mean(np.array(zm.variables['wpthlp_bp']),(2,3))
wpthlp_pr3=np.mean(np.array(zm.variables['wpthlp_pr3']),(2,3))
wpthlp_pr1=np.mean(np.array(zm.variables['wpthlp_pr1']),(2,3))
wpthlp_pr2=np.mean(np.array(zm.variables['wpthlp_pr2']),(2,3))
wpthlp_dp1=np.mean(np.array(zm.variables['wpthlp_dp1']),(2,3))
wpthlp_mfl=np.mean(np.array(zm.variables['wpthlp_mfl']),(2,3))
wpthlp_cl=np.mean(np.array(zm.variables['wpthlp_cl']),(2,3))
wpthlp_sicl=np.mean(np.array(zm.variables['wpthlp_sicl']),(2,3))
wpthlp_forcing=np.mean(np.array(zm.variables['wpthlp_forcing']),(2,3))
wpthlp_mc=np.mean(np.array(zm.variables['wpthlp_mc']),(2,3))
fig,ax3=plt.subplots()
for t in range(0,360):
ax3.cla()
ax3.plot(wpthlp[t,0:100]*0.1,alt[0:100],'--',label='wpthlp_bt')
ax3.plot(wpthlp_bt[t,0:100],alt[0:100],label='wpthlp_bt')
ax3.plot(wpthlp_tp[t,0:100],alt[0:100],label='wpthlp_tp')
ax3.plot(wpthlp_bp[t,0:100],alt[0:100],label='wpthlp_bp')
ax3.plot(wpthlp_pr1[t,0:100],alt[0:100],label='wpthlp_pr1')
ax3.plot(wpthlp_pr3[t,0:100],alt[0:100],label='wpthlp_pr3')
ax3.plot(wpthlp_ma[t,0:100],alt[0:100],label='wpthlp_ma')
ax3.plot(wpthlp_ta[t,0:100],alt[0:100],label='wpthlp_ta')
ax3.plot(wpthlp_pr2[t,0:100],alt[0:100],label='wpthlp_pr2')
ax3.plot(wpthlp_dp1[t,0:100],alt[0:100],label='wpthlp_dp1')
ax3.plot(wpthlp_mfl[t,0:100],alt[0:100],label='wpthlp_mfl')
ax3.plot(wpthlp_cl[t,0:100],alt[0:100],label='wpthlp_cl')
ax3.plot(wpthlp_sicl[t,0:100],alt[0:100],label='wpthlp_sicl')
ax3.plot(wpthlp_forcing[t,0:100],alt[0:100],label='wpthlp_forcing')
ax3.plot(wpthlp_mc[t,0:100],alt[0:100],label='wpthlp_mc')
ax3.set_xlabel('wpthlp [m K/s2]')
ax3.set_ylabel('height [m]')
ax3.set_xlim(-0.01,0.016)
ax3.legend(loc='right')
ax3.set_title('wpthlp')
plt.pause(0.05)
import numpy as np
import matplotlib.pyplot as plt
from netCDF4 import Dataset
fzt=Dataset('dycoms2_rf01_zt.nc')
#wpthlp=np.mean(np.array(zm.variables['wpthlp']),(2,3))
alt=np.array(fzt.variables['lev'])
wp3_ta=np.mean(np.array(fzt.variables['wp3_ta']),(2,3))
wp3_tp=np.mean(np.array(fzt.variables['wp3_tp']),(2,3))
wp3_bp1=np.mean(np.array(fzt.variables['wp3_bp']),(2,3))
wp3_pr1=np.mean(np.array(fzt.variables['wp3_pr1']),(2,3))
wp3_pr2=np.mean(np.array(fzt.variables['wp3_pr2']),(2,3))
wp3_dp1=np.mean(np.array(fzt.variables['wp3_dp1']),(2,3))
fig,ax3=plt.subplots()
for t in range(0,360):
ax3.cla()
ax3.plot(wp3_ta[t,0:100],alt[0:100],label='wp3_ta')
ax3.plot(wp3_tp[t,0:100],alt[0:100],label='wp3_tp')
ax3.plot(wp3_bp1[t,0:100],alt[0:100],label='wp3_bp1')
# ax3.plot(wp3_bp2[t,0:100],alt[0:100],label='wp3_bp2')
ax3.plot(wp3_dp1[t,0:100],alt[0:100],label='wp3_dp1')
ax3.plot(wp3_pr1[t,0:100],alt[0:100],label='wp3_pr1')
ax3.plot(wp3_pr2[t,0:100],alt[0:100],label='wp3_pr2')
# ax3.plot(wp3_pr3[t,0:100],alt[0:100],label='wp3_pr3')
ax3.set_xlabel('wpthlp [m K/s2]')
ax3.set_ylabel('height [m]')
ax3.set_xlim(-0.01,0.016)
ax3.legend(loc='right')
ax3.set_title('wpthlp')
plt.pause(0.05)
'thlp2_bt', 'thlp2_ma', 'thlp2_ta', 'thlp2_tp', 'thlp2_dp1', 'thlp2_dp2', 'thlp2_cl', 'thlp2_pd', 'thlp2_sf', 'thlp2_forcing', 'thlp2_mc'
thlp2_bt=np.mean(np.array(zm.variables['thlp2_bt']),(2,3))
thlp2_ma=np.mean(np.array(zm.variables['thlp2_ma']),(2,3))
thlp2_ta=np.mean(np.array(zm.variables['thlp2_ta']),(2,3))
thlp2_tp=np.mean(np.array(zm.variables['thlp2_tp']),(2,3))
thlp2_dp1=np.mean(np.array(zm.variables['thlp2_dp1']),(2,3))
thlp2_dp2=np.mean(np.array(zm.variables['thlp2_dp2']),(2,3))
thlp2_cl=np.mean(np.array(zm.variables['thlp2_cl']),(2,3))
thlp2_pd=np.mean(np.array(zm.variables['thlp2_pd']),(2,3))
thlp2_forcing=np.mean(np.array(zm.variables['thlp2_forcing']),(2,3))
thlp2_mc=np.mean(np.array(zm.variables['thlp2_mc']),(2,3))
thlp2_sf=np.mean(np.array(zm.variables['thlp2_sf']),(2,3))
fig,ax3=plt.subplots()
for t in range(0,360):
ax3.cla()
ax3.plot(thlp2[t,0:100]*0.01,alt[0:100],label='thlp2')
ax3.plot(thlp2_ma[t,0:100],alt[0:100],label='thlp2_ma')
ax3.plot(thlp2_ta[t,0:100],alt[0:100],label='thlp2_ta')
ax3.plot(thlp2_tp[t,0:100],alt[0:100],label='thlp2_tp')
ax3.plot(thlp2_dp1[t,0:100],alt[0:100],label='thlp2_dp1')
ax3.plot(thlp2_dp2[t,0:100],alt[0:100],label='thlp2_dp2')
ax3.plot(thlp2_cl[t,0:100],alt[0:100],label='thlp2_cl')
ax3.plot(thlp2_pd[t,0:100],alt[0:100],label='thlp2_pd')
ax3.plot(thlp2_sf[t,0:100],alt[0:100],label='thlp2_sf')
ax3.plot(thlp2_forcing[t,0:100],alt[0:100],label='thlp2_forcing')
ax3.plot(thlp2_mc[t,0:100],alt[0:100],label='thlp2_mc')
ax3.set_xlabel('thlp2 [m K/s2]')
ax3.set_ylabel('height [m]')
ax3.set_xlim(-0.01,0.016)
ax3.legend(loc='right')
ax3.set_title('thlp2')
plt.pause(0.05)
wp3=np.mean(np.array(zt.variables['wp3']),(2,3))
wp3_bt=np.mean(np.array(zt.variables['wp3_bt']),(2,3))
wp3_ma=np.mean(np.array(zt.variables['wp3_ma']),(2,3))
wp3_ta=np.mean(np.array(zt.variables['wp3_ta']),(2,3))
wp3_tp=np.mean(np.array(zt.variables['wp3_tp']),(2,3))
wp3_ac=np.mean(np.array(zt.variables['wp3_ac']),(2,3))
wp3_bp1=np.mean(np.array(zt.variables['wp3_bp1']),(2,3))
wp3_bp2=np.mean(np.array(zt.variables['wp3_bp2']),(2,3))
wp3_pr1=np.mean(np.array(zt.variables['wp3_pr1']),(2,3))
wp3_pr2=np.mean(np.array(zt.variables['wp3_pr2']),(2,3))
wp3_pr3=np.mean(np.array(zt.variables['wp3_pr3']),(2,3))
wp3_dp1=np.mean(np.array(zt.variables['wp3_dp1']),(2,3))
wp3_sdmp=np.mean(np.array(zt.variables['wp3_sdmp']),(2,3))
wp3_cl=np.mean(np.array(zt.variables['wp3_cl']),(2,3))
wp3_splat=np.mean(np.array(zt.variables['wp3_splat']),(2,3))
alt=np.array(zt.variables['altitude'])
plt.plot(np.mean(wp3[180:360,:],0),alt,'k',label='wp3')
plt.plot(np.mean(wp3_bt[180:360,:]*60,0),alt,label='bt')
plt.plot(np.mean(wp3_ma[180:360,:]*60,0),alt,label='ma')
#plt.plot(np.mean(wp3_ta[180:360,:]*60,0),alt,label='ta')
#plt.plot(np.mean(wp3_tp[180:360,:]*60,0),alt,label='tp')
plt.plot(np.mean(wp3_ta[180:360,:]*60+wp3_tp[180:360,:]*60,0),alt,label='ta+tp')
plt.plot(np.mean(wp3_ac[180:360,:]*60,0),alt,label='ac')
plt.plot(np.mean(wp3_bp1[180:360,:]*60,0),alt,label='bp1')
plt.plot(np.mean(wp3_bp2[180:360,:]*60,0),alt,label='bp2')
plt.plot(np.mean(wp3_pr1[180:360,:]*60,0),alt,label='pr1')
plt.plot(np.mean(wp3_pr2[180:360,:]*60,0),alt,label='pr2')
plt.plot(np.mean(wp3_pr3[180:360,:]*60,0),alt,label='pr3')
plt.plot(np.mean(wp3_dp1[180:360,:]*60,0),alt,':',label='dp1')
plt.plot(np.mean(wp3_sdmp[180:360,:]*60,0),alt,':',label='sdmp')
plt.plot(np.mean(wp3_cl[180:360,:]*60,0),alt,':',label='cl')
plt.plot(np.mean(wp3_splat[180:360,:]*60,0),alt,':',label='splat')
plt.xlabel('time [min]')
plt.ylabel('m2/s3')
plt.legend()
plt.show()
plt.plot(np.mean(wp3_dp1_3c[181:360],0),altc,label='clb,cK8 = 3.0')
plt.plot(np.mean(wp3_dp1_35c[181:360],0),altc,label='clb,cK8 = 3.5')
plt.plot(np.mean(wp3_dp1_375c[181:360],0),altc,label='clb,cK8 = 3.75')
plt.plot(np.mean(wp3_dp1_38c[181:360],0),altc,label='clb,cK8 = 3.8')
plt.plot(np.mean(wp3_dp1_39c[181:360],0),altc,label='clb,cK8 = 3.9')
plt.plot(np.mean(wp3_dp1_4c[181:360],0),altc,label='clb,cK8 = 4.0')
plt.plot(np.mean(wp3_dp1_425c[181:360],0),altc,label='clb,cK8 = 4.25')
plt.plot(np.mean(wp3_dp1_45c[181:360],0),altc,label='clb,cK8 = 4.5')
plt.plot(np.mean(wp3_dp1_5c[181:360],0),altc,label='clb,cK8 = 5.0')
plt.plot(np.mean(wp3_dp1_3w[181:360],0),altw,':',label='wrf,cK8 = 3.0')
plt.plot(np.mean(wp3_dp1_35w[181:360],0),altw,':',label='wrf,cK8 = 3.5')
plt.plot(np.mean(wp3_dp1_375w[181:360],0),altw,':',label='wrf,cK8 = 3.75')
plt.plot(np.mean(wp3_dp1_38w[181:360],0),altw,':',label='wrf,cK8 = 3.8')
plt.plot(np.mean(wp3_dp1_39w[181:360],0),altw,':',label='wrf,cK8 = 3.9')
plt.plot(np.mean(wp3_dp1_4w[181:360],0),altw,':',label='wrf,cK8 = 4.0')
plt.plot(np.mean(wp3_dp1_425w[181:360],0),altw,':',label='wrf,cK8 = 4.25')
plt.plot(np.mean(wp3_dp1_45w[181:360],0),altw,':',label='wrf,cK8 = 4.5')
plt.plot(np.mean(wp3_dp1_5w[181:360],0),altw,':',label='wrf,cK8 = 5.0')
plt.xlabel('wp3_dp1 [m/s]')
plt.ylabel('height [m]')
plt.legend()
plt.show()