From 88425d7e6f949d7868c299d44aef4b86959b763e Mon Sep 17 00:00:00 2001 From: csyhuang Date: Thu, 6 Apr 2023 21:06:50 -0500 Subject: [PATCH] include Emily's fix --- scripts/nhn_grl2022/graph_plot_module.py | 301 ++++++++++++----------- scripts/nhn_grl2022/sample_run_script.py | 2 +- 2 files changed, 157 insertions(+), 146 deletions(-) diff --git a/scripts/nhn_grl2022/graph_plot_module.py b/scripts/nhn_grl2022/graph_plot_module.py index eb8d643..9672cb6 100644 --- a/scripts/nhn_grl2022/graph_plot_module.py +++ b/scripts/nhn_grl2022/graph_plot_module.py @@ -262,53 +262,53 @@ def plot_figure1d_2a(t_filename): def plot_figure3_and_S1(lwa_flux_filename): + ncin1 = Dataset(lwa_flux_filename, 'r', format='NETCDF4') lwa = ncin1.variables['lwa'] lwa = (np.array(lwa)) - z = np.zeros((91,360)) - z[:,:] = lwa[100,:,:]-lwa[76,:,:] # m = 100 is 00 UTC 26 June 2021, m = 76 is 00 UTC 20 June 2021 + z = np.zeros((91, 360)) + z[:, :] = lwa[100, :, :] - lwa[76, :, :] # m = 100 is 00 UTC 26 June 2021, m = 76 is 00 UTC 20 June 2021 - zs = np.zeros((91,360)) # smoothed z # + zs = np.zeros((91, 360)) # smoothed z # #### smoothing in longitude #### - n = 5 # smoothing width # + n = 5 # smoothing width # j = 0 - while(j < 91): + while (j < 91): zx = np.zeros(360) - zx[:] = z[j,:] + zx[:] = z[j, :] nn = -n - while(nn < n+1): - zy = np.roll(zx,nn) - zs[j,:] = zs[j,:] + zy[:]/(2*n+1) - nn = nn+1 - j = j+1 - - - cl2 = np.arange(-80,90,10) - x = np.arange(0,360) - y = np.arange(0,91) + while (nn < n + 1): + zy = np.roll(zx, nn) + zs[j, :] = zs[j, :] + zy[:] / (2 * n + 1) + nn = nn + 1 + j = j + 1 + + cl2 = np.arange(-80, 90, 10) + x = np.arange(0, 360) + y = np.arange(0, 91) plt.rcParams.update({'font.size': 16}) fig = plt.figure(figsize=(10, 5)) - ax5 = fig.add_subplot(1,1,1,projection=ccrs.PlateCarree(180)) - plt.xlim(140, 280) + ax5 = fig.add_subplot(1, 1, 1, projection=ccrs.PlateCarree(180)) + plt.xlim(-40, 100) plt.ylim(10, 80) plt.title('Column LWA Change 00 UTC 20 - 26 June 2021') - #plot.xlabel('Longitude') + # plot.xlabel('Longitude') plt.ylabel('Latitude', fontsize=22) - ax5.set_extent([-220, -80, 10, 80], ccrs.PlateCarree()) - ax5.coastlines(alpha = 0.7) + ax5.coastlines(alpha=0.7) ax5.set_aspect('auto', adjustable=None) - ax5.set_xticks([140,160,180,200,220,240,260,280], crs=ccrs.PlateCarree()) + ax5.set_xticks([140, 160, 180, 200, 220, 240, 260, 280], crs=ccrs.PlateCarree()) ax5.set_yticks([10, 20, 30, 40, 50, 60, 70, 80], crs=ccrs.PlateCarree()) lon_formatter = LongitudeFormatter(zero_direction_label=True) lat_formatter = LatitudeFormatter() ax5.xaxis.set_major_formatter(lon_formatter) ax5.yaxis.set_major_formatter(lat_formatter) - ott = ax5.contourf(x,y,zs,levels=cl2,transform=ccrs.PlateCarree(),cmap='rainbow') - fig.colorbar(ott,ax=ax5,label='LWA (m/s)') - plt.savefig('dLWA_0.png', bbox_inches='tight', dpi =600) + ott = ax5.contourf(x[140:281], y[10:81], zs[10:81, 140:281], levels=cl2, transform=ccrs.PlateCarree(), + cmap='rainbow') + fig.colorbar(ott, ax=ax5, label='LWA (m/s)') + plt.savefig('dLWA_0.png', bbox_inches='tight', dpi=600) ncin1 = Dataset(lwa_flux_filename, 'r', format='NETCDF4') ua1 = ncin1.variables['ua1'] @@ -329,185 +329,196 @@ def plot_figure3_and_S1(lwa_flux_filename): ep4 = ncin6.variables['ep4'] ep4 = (np.array(ep4)) - f1 = np.zeros((91,360)) - f2 = np.zeros((91,360)) - f11 = np.zeros((91,360)) - f22 = np.zeros((91,360)) + f1 = np.zeros((91, 360)) + f2 = np.zeros((91, 360)) + f11 = np.zeros((91, 360)) + f22 = np.zeros((91, 360)) - z1 = np.zeros((91,360)) - z2 = np.zeros((91,360)) - z3 = np.zeros((91,360)) - dt = 3600.*6. + z1 = np.zeros((91, 360)) + z2 = np.zeros((91, 360)) + z3 = np.zeros((91, 360)) + dt = 3600. * 6. a = 6378000. - dl = 2.*np.pi/360. - dp = 2.*np.pi/360. - m = 76 # m = 76 is 20 June 2021 00 UTC - while(m < 100): # m = 100 is 26 June 2021 00 UTC - #m = 52 # m = 52 is 14 June 2021 00 UTC - #while(m < 76): # m = 76 is 20 June 2021 00 UTC - - z3[:,:] = z3[:,:]+0.5*dt*ep4[m,:,:] - z3[:,:] = z3[:,:]+0.5*dt*ep4[m+1,:,:] - f1[:,:] = f1[:,:]+(0.5/24.)*(ua1[m,:,:]+ua2[m,:,:]+ep1[m,:,:]) - f1[:,:] = f1[:,:]+(0.5/24.)*(ua1[m+1,:,:]+ua2[m+1,:,:]+ep1[m+1,:,:]) - f11[:,:] = f11[:,:]+(0.5/24.)*(ua1[m-24,:,:]+ua2[m-24,:,:]+ep1[m-24,:,:]) - f11[:,:] = f11[:,:]+(0.5/24.)*(ua1[m-23,:,:]+ua2[m-23,:,:]+ep1[m-23,:,:]) + dl = 2. * np.pi / 360. + dp = 2. * np.pi / 360. + m = 76 # m = 76 is 20 June 2021 00 UTC + while (m < 100): # m = 100 is 26 June 2021 00 UTC + # m = 52 # m = 52 is 14 June 2021 00 UTC + # while(m < 76): # m = 76 is 20 June 2021 00 UTC + + z3[:, :] = z3[:, :] + 0.5 * dt * ep4[m, :, :] + z3[:, :] = z3[:, :] + 0.5 * dt * ep4[m + 1, :, :] + f1[:, :] = f1[:, :] + (0.5 / 24.) * (ua1[m, :, :] + ua2[m, :, :] + ep1[m, :, :]) + f1[:, :] = f1[:, :] + (0.5 / 24.) * (ua1[m + 1, :, :] + ua2[m + 1, :, :] + ep1[m + 1, :, :]) + f11[:, :] = f11[:, :] + (0.5 / 24.) * (ua1[m - 24, :, :] + ua2[m - 24, :, :] + ep1[m - 24, :, :]) + f11[:, :] = f11[:, :] + (0.5 / 24.) * (ua1[m - 23, :, :] + ua2[m - 23, :, :] + ep1[m - 23, :, :]) j = 0 - while(j < 90): - phi = dp*j - const = 0.5*dt/(2.*a*np.cos(phi)*dl) - z2[j,:]=z2[j,:]+const*(ep2[m,j,:]-ep3[m,j,:]) - z2[j,:]=z2[j,:]+const*(ep2[m+1,j,:]-ep3[m+1,j,:]) - f2[j,:] = f2[j,:]+(0.25/24.)*(ep2[m,j,:]+ep3[m,j,:])/np.cos(phi) - f2[j,:] = f2[j,:]+(0.25/24.)*(ep2[m+1,j,:]+ep3[m+1,j,:])/np.cos(phi) - f22[j,:] = f22[j,:]+(0.25/24.)*(ep2[m-24,j,:]+ep3[m-24,j,:])/np.cos(phi) - f22[j,:] = f22[j,:]+(0.25/24.)*(ep2[m-23,j,:]+ep3[m-23,j,:])/np.cos(phi) + while (j < 90): + phi = dp * j + const = 0.5 * dt / (2. * a * np.cos(phi) * dl) + z2[j, :] = z2[j, :] + const * (ep2[m, j, :] - ep3[m, j, :]) + z2[j, :] = z2[j, :] + const * (ep2[m + 1, j, :] - ep3[m + 1, j, :]) + f2[j, :] = f2[j, :] + (0.25 / 24.) * (ep2[m, j, :] + ep3[m, j, :]) / np.cos(phi) + f2[j, :] = f2[j, :] + (0.25 / 24.) * (ep2[m + 1, j, :] + ep3[m + 1, j, :]) / np.cos(phi) + f22[j, :] = f22[j, :] + (0.25 / 24.) * (ep2[m - 24, j, :] + ep3[m - 24, j, :]) / np.cos(phi) + f22[j, :] = f22[j, :] + (0.25 / 24.) * (ep2[m - 23, j, :] + ep3[m - 23, j, :]) / np.cos(phi) i = 1 - while(i < 359): - z1[j,i] = z1[j,i]-const*(ua1[m,j,i+1]+ua2[m,j,i+1]+ep1[m,j,i+1]-ua1[m,j,i-1]-ua2[m,j,i-1]-ep1[m,j,i-1]) - z1[j,i] = z1[j,i]-const*(ua1[m+1,j,i+1]+ua2[m+1,j,i+1]+ep1[m+1,j,i+1]-ua1[m+1,j,i-1]-ua2[m+1,j,i-1]-ep1[m+1,j,i-1]) - i = i+1 - z1[j,0] = z1[j,0]-const*(ua1[m,j,1]+ua2[m,j,1]+ep1[m,j,1]-ua1[m,j,359]-ua2[m,j,359]-ep1[m,j,359]) - z1[j,0] = z1[j,0]-const*(ua1[m+1,j,1]+ua2[m+1,j,1]+ep1[m+1,j,1]-ua1[m+1,j,359]-ua2[m+1,j,359]-ep1[m+1,j,359]) - z1[j,359] = z1[j,359]-const*(ua1[m,j,0]+ua2[m,j,0]+ep1[m,j,0]-ua1[m,j,358]-ua2[m,j,358]-ep1[m,j,358]) - z1[j,359] = z1[j,359]-const*(ua1[m+1,j,0]+ua2[m+1,j,0]+ep1[m+1,j,0]-ua1[m+1,j,358]-ua2[m+1,j,358]-ep1[m+1,j,358]) - j = j+1 - m = m+1 - - z1s = np.zeros((91,360)) # smoothed z1 # - z2s = np.zeros((91,360)) # smoothed z2 # - z3s = np.zeros((91,360)) # smoothed z3 # + while (i < 359): + z1[j, i] = z1[j, i] - const * ( + ua1[m, j, i + 1] + ua2[m, j, i + 1] + ep1[m, j, i + 1] - ua1[m, j, i - 1] - ua2[ + m, j, i - 1] - ep1[m, j, i - 1]) + z1[j, i] = z1[j, i] - const * ( + ua1[m + 1, j, i + 1] + ua2[m + 1, j, i + 1] + ep1[m + 1, j, i + 1] - ua1[m + 1, j, i - 1] - + ua2[m + 1, j, i - 1] - ep1[m + 1, j, i - 1]) + i = i + 1 + z1[j, 0] = z1[j, 0] - const * ( + ua1[m, j, 1] + ua2[m, j, 1] + ep1[m, j, 1] - ua1[m, j, 359] - ua2[m, j, 359] - ep1[m, j, 359]) + z1[j, 0] = z1[j, 0] - const * ( + ua1[m + 1, j, 1] + ua2[m + 1, j, 1] + ep1[m + 1, j, 1] - ua1[m + 1, j, 359] - ua2[ + m + 1, j, 359] - ep1[m + 1, j, 359]) + z1[j, 359] = z1[j, 359] - const * ( + ua1[m, j, 0] + ua2[m, j, 0] + ep1[m, j, 0] - ua1[m, j, 358] - ua2[m, j, 358] - ep1[m, j, 358]) + z1[j, 359] = z1[j, 359] - const * ( + ua1[m + 1, j, 0] + ua2[m + 1, j, 0] + ep1[m + 1, j, 0] - ua1[m + 1, j, 358] - ua2[ + m + 1, j, 358] - ep1[m + 1, j, 358]) + j = j + 1 + m = m + 1 + + z1s = np.zeros((91, 360)) # smoothed z1 # + z2s = np.zeros((91, 360)) # smoothed z2 # + z3s = np.zeros((91, 360)) # smoothed z3 # #### smoothing in longitude #### j = 0 - while(j < 91): + while (j < 91): z1x = np.zeros(360) - z1x[:] = z1[j,:] + z1x[:] = z1[j, :] z2x = np.zeros(360) - z2x[:] = z2[j,:] + z2x[:] = z2[j, :] z3x = np.zeros(360) - z3x[:] = z3[j,:] + z3x[:] = z3[j, :] nn = -n - while(nn < n+1): - z1y = np.roll(z1x,nn) - z1s[j,:] = z1s[j,:] + z1y[:]/(2*n+1) - z2y = np.roll(z2x,nn) - z2s[j,:] = z2s[j,:] + z2y[:]/(2*n+1) - z3y = np.roll(z3x,nn) - z3s[j,:] = z3s[j,:] + z3y[:]/(2*n+1) - nn = nn+1 - j = j+1 + while (nn < n + 1): + z1y = np.roll(z1x, nn) + z1s[j, :] = z1s[j, :] + z1y[:] / (2 * n + 1) + z2y = np.roll(z2x, nn) + z2s[j, :] = z2s[j, :] + z2y[:] / (2 * n + 1) + z3y = np.roll(z3x, nn) + z3s[j, :] = z3s[j, :] + z3y[:] / (2 * n + 1) + nn = nn + 1 + j = j + 1 ##### Wind vectors ###### - x1 = np.arange(0,24)*15.+5. - y1 = np.arange(0,30)*3. - xx,yy = np.meshgrid(x1,y1) - uu = np.zeros((30,24)) - vv = np.zeros((30,24)) + x1 = np.arange(0, 24) * 15. + 5. + y1 = np.arange(0, 30) * 3. + xx, yy = np.meshgrid(x1, y1) + uu = np.zeros((30, 24)) + vv = np.zeros((30, 24)) j = 0 - while(j < 30): + while (j < 30): i = 0 - while(i < 24): - uu[j,i] = f1[j*3,i*15+5]-f11[j*3,i*15+5] - vv[j,i] = f2[j*3,i*15+5]-f22[j*3,i*15+5] - i = i+1 - j = j+1 - - - cl1 = np.arange(-200,220,20) - x = np.arange(0,360) - y = np.arange(0,91) + while (i < 24): + uu[j, i] = f1[j * 3, i * 15 + 5] - f11[j * 3, i * 15 + 5] + vv[j, i] = f2[j * 3, i * 15 + 5] - f22[j * 3, i * 15 + 5] + i = i + 1 + j = j + 1 + + cl1 = np.arange(-200, 220, 20) + x = np.arange(0, 360) + y = np.arange(0, 91) plt.rcParams.update({'font.size': 16}) fig = plt.figure(figsize=(10, 5)) - ax6 = fig.add_subplot(1,1,1,projection=ccrs.PlateCarree(180)) - plt.xlim(0, 360) + ax6 = fig.add_subplot(1, 1, 1, projection=ccrs.PlateCarree(180)) + plt.xlim(-40, 100) plt.ylim(10, 80) plt.title('Integrated column -div (Fx + Fy) 20 - 26 June 2021') plt.ylabel('Latitude', fontsize=22) - ax6.set_extent([-220, -80, 10, 80], ccrs.PlateCarree()) - ax6.coastlines(alpha = 0.7) + ax6.coastlines(alpha=0.7) ax6.set_aspect('auto', adjustable=None) - ax6.set_xticks([140,160,180,200,220,240,260,280], crs=ccrs.PlateCarree()) + ax6.set_xticks([140, 160, 180, 200, 220, 240, 260, 280], crs=ccrs.PlateCarree()) ax6.set_yticks([10, 20, 30, 40, 50, 60, 70, 80], crs=ccrs.PlateCarree()) lon_formatter = LongitudeFormatter(zero_direction_label=True) lat_formatter = LatitudeFormatter() ax6.xaxis.set_major_formatter(lon_formatter) ax6.yaxis.set_major_formatter(lat_formatter) - ott = ax6.contourf(x,y,z1s+z2s,levels=cl1,transform=ccrs.PlateCarree(),cmap='rainbow') - fig.colorbar(ott,ax=ax6,label='(m/s)') - ax6.quiver(xx[2:-2,:],yy[2:-2,:],uu[2:-2, :],vv[2:-2, :],transform=ccrs.PlateCarree()) - plt.savefig('divFx+Fy_0.png', bbox_inches='tight', dpi =600) - - cl1 = np.arange(-200,220,20) - x = np.arange(0,360) - y = np.arange(0,91) + ott = ax6.contourf(x[140:281], y[10:81], z1s[10:81, 140:281] + z2s[10:81, 140:281], levels=cl1, + transform=ccrs.PlateCarree(), cmap='rainbow') + fig.colorbar(ott, ax=ax6, label='(m/s)') + ax6.quiver(xx[2:-2, :], yy[2:-2, :], uu[2:-2, :], vv[2:-2, :], transform=ccrs.PlateCarree()) + plt.savefig('divFx+Fy_0.png', bbox_inches='tight', dpi=600) + + cl1 = np.arange(-200, 220, 20) + x = np.arange(0, 360) + y = np.arange(0, 91) plt.rcParams.update({'font.size': 16}) fig = plt.figure(figsize=(10, 5)) - ax6 = fig.add_subplot(1,1,1,projection=ccrs.PlateCarree(180)) - plt.xlim(0, 360) + ax6 = fig.add_subplot(1, 1, 1, projection=ccrs.PlateCarree(180)) + plt.xlim(-40, 100) plt.ylim(10, 80) plt.title('Integrated column -div Fy 20 - 26 June 2021') plt.xlabel('Longitude', fontsize=22) plt.ylabel('Latitude', fontsize=22) - ax6.set_extent([-220, -80, 10, 80], ccrs.PlateCarree()) - ax6.coastlines(alpha = 0.7) + ax6.coastlines(alpha=0.7) ax6.set_aspect('auto', adjustable=None) - ax6.set_xticks([140,160,180,200,220,240,260,280], crs=ccrs.PlateCarree()) + ax6.set_xticks([140, 160, 180, 200, 220, 240, 260, 280], crs=ccrs.PlateCarree()) ax6.set_yticks([10, 20, 30, 40, 50, 60, 70, 80], crs=ccrs.PlateCarree()) lon_formatter = LongitudeFormatter(zero_direction_label=True) lat_formatter = LatitudeFormatter() ax6.xaxis.set_major_formatter(lon_formatter) ax6.yaxis.set_major_formatter(lat_formatter) - ott = ax6.contourf(x,y,z2s,levels=cl1,transform=ccrs.PlateCarree(),cmap='rainbow') - fig.colorbar(ott,ax=ax6,label='(m/s)') - ax6.quiver(xx[2:-2,:],yy[2:-2,:],uu[2:-2, :],vv[2:-2, :],transform=ccrs.PlateCarree()) - plt.savefig('divFy_0.png', bbox_inches='tight', dpi =600) - - cl1 = np.arange(-200,220,20) - x = np.arange(0,360) - y = np.arange(0,91) + ott = ax6.contourf(x[140:281], y[10:81], z2s[10:81, 140:281], levels=cl1, transform=ccrs.PlateCarree(), + cmap='rainbow') + fig.colorbar(ott, ax=ax6, label='(m/s)') + ax6.quiver(xx[2:-2, :], yy[2:-2, :], uu[2:-2, :], vv[2:-2, :], transform=ccrs.PlateCarree()) + plt.savefig('divFy_0.png', bbox_inches='tight', dpi=600) + + cl1 = np.arange(-200, 220, 20) + x = np.arange(0, 360) + y = np.arange(0, 91) plt.rcParams.update({'font.size': 16}) fig = plt.figure(figsize=(10, 5)) - ax6 = fig.add_subplot(1,1,1,projection=ccrs.PlateCarree(180)) - plt.xlim(0, 360) + ax6 = fig.add_subplot(1, 1, 1, projection=ccrs.PlateCarree(180)) + plt.xlim(-40, 100) plt.ylim(10, 80) plt.title('Integrated low-level source 20 - 26 June 2021') - ax6.set_extent([-220, -80, 10, 80], ccrs.PlateCarree()) - ax6.coastlines(alpha = 0.7) + ax6.coastlines(alpha=0.7) ax6.set_aspect('auto', adjustable=None) - ax6.set_xticks([140,160,180,200,220,240,260,280], crs=ccrs.PlateCarree()) + ax6.set_xticks([140, 160, 180, 200, 220, 240, 260, 280], crs=ccrs.PlateCarree()) ax6.set_yticks([10, 20, 30, 40, 50, 60, 70, 80], crs=ccrs.PlateCarree()) lon_formatter = LongitudeFormatter(zero_direction_label=True) lat_formatter = LatitudeFormatter() ax6.xaxis.set_major_formatter(lon_formatter) ax6.yaxis.set_major_formatter(lat_formatter) - ott = ax6.contourf(x,y,z3s,levels=cl1,transform=ccrs.PlateCarree(),cmap='rainbow') - fig.colorbar(ott,ax=ax6,label='(m/s)') - plt.savefig('EP4_0.png', bbox_inches='tight', dpi =600) - - cl1 = np.arange(-200,220,20) - x = np.arange(0,360) - y = np.arange(0,91) + ott = ax6.contourf(x[140:281], y[10:81], z3s[10:81, 140:281], levels=cl1, transform=ccrs.PlateCarree(), + cmap='rainbow') + fig.colorbar(ott, ax=ax6, label='(m/s)') + plt.savefig('EP4_0.png', bbox_inches='tight', dpi=600) + + cl1 = np.arange(-200, 220, 20) + x = np.arange(0, 360) + y = np.arange(0, 91) fig = plt.figure(figsize=(10, 5)) - ax6 = fig.add_subplot(1,1,1,projection=ccrs.PlateCarree(180)) - plt.xlim(0, 360) + ax6 = fig.add_subplot(1, 1, 1, projection=ccrs.PlateCarree(180)) + plt.xlim(-40, 100) plt.ylim(10, 80) plt.title('Integrated residual 20 - 26 June 2021') - ax6.set_extent([-220, -80, 10, 80], ccrs.PlateCarree()) - ax6.coastlines(alpha = 0.7) + ax6.coastlines(alpha=0.7) ax6.set_aspect('auto', adjustable=None) - ax6.set_xticks([140,160,180,200,220,240,260,280], crs=ccrs.PlateCarree()) + ax6.set_xticks([140, 160, 180, 200, 220, 240, 260, 280], crs=ccrs.PlateCarree()) ax6.set_yticks([10, 20, 30, 40, 50, 60, 70, 80], crs=ccrs.PlateCarree()) lon_formatter = LongitudeFormatter(zero_direction_label=True) lat_formatter = LatitudeFormatter() ax6.xaxis.set_major_formatter(lon_formatter) ax6.yaxis.set_major_formatter(lat_formatter) - ott = ax6.contourf(x,y,zs-z1s-z2s-z3s,levels=cl1,transform=ccrs.PlateCarree(),cmap='rainbow') - fig.colorbar(ott,ax=ax6,label='(m/s)') - ax6.quiver(xx[2:-2,:],yy[2:-2,:],uu[2:-2, :],vv[2:-2, :],transform=ccrs.PlateCarree()) - plt.savefig('Residual_0.png', bbox_inches='tight', dpi =600) + ott = ax6.contourf(x[140:281], y[10:81], + zs[10:81, 140:281] - z1s[10:81, 140:281] - z2s[10:81, 140:281] - z3s[10:81, 140:281], levels=cl1, + transform=ccrs.PlateCarree(), cmap='rainbow') + fig.colorbar(ott, ax=ax6, label='(m/s)') + ax6.quiver(xx[2:-2, :], yy[2:-2, :], uu[2:-2, :], vv[2:-2, :], transform=ccrs.PlateCarree()) + plt.savefig('Residual_0.png', bbox_inches='tight', dpi=600) + plt.show() plt.close("all") diff --git a/scripts/nhn_grl2022/sample_run_script.py b/scripts/nhn_grl2022/sample_run_script.py index 9069cd7..cbcc26a 100644 --- a/scripts/nhn_grl2022/sample_run_script.py +++ b/scripts/nhn_grl2022/sample_run_script.py @@ -18,7 +18,7 @@ plot_figure3e, plot_figure3f, plot_figure4, plot_figure5 data_dir = "grl2021_data/" -to_generate_data = True +to_generate_data = True # Set this to False if wave activity and fluxes are computed and stored in netCDF file already # --- Load the zonal wind and QGPV at 240hPa --- # u_file = Dataset(data_dir + '2021_06_u.nc', mode='r')