Are there separate functions to plot cross-track or along-track plots or horizontal view only?

[syedhamidali]

Hi,
I was trying to plot vertical cross-track and along-track, and I tried the drpy.graph.case_study(filename=file,center_lat=19,center_lon=76). However, it gives all the plots at different frequencies. I am interested in vertical plots only with the y-axis in km; the reason is that I want to superimpose lightning data on it. I know I have to convert the data into cartesian grids using Pyproj by choosing some reference points. But, I haven't ever done so, and not sure how to do that. Any help will be appreciated.
Thank you!

Here is what I tried

In[1]:

import drpy
import datetime as dt
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import pandas as pd
import cartopy.crs as ccrs
import cartopy.feature as feat
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER


# In[2]:


def add_Map(ax):
    gl = ax.gridlines(crs=ccrs.PlateCarree(), linewidth=1, color='black', alpha=0.5, 
                         linestyle='--', draw_labels=True)
    gl.xlabels_top = False
    gl.ylabels_left = True
    gl.ylabels_right=False
    gl.xlines = False
    gl.ylines = False
    gl.xformatter = LONGITUDE_FORMATTER
    gl.yformatter = LATITUDE_FORMATTER
    ax.add_feature(feat.BORDERS, lw = 0.5)
    ax.add_feature(feat.LAND, lw = 0.3, fc = [0.9,0.9,0.9])
    ax.add_feature(feat.COASTLINE, lw = 0.5)
    ax.add_feature(feat.OCEAN, alpha = 0.5)
    ax.add_feature(feat.STATES.with_scale("10m"), alpha = 0.5, lw = 0.5)


# In[3]:


def crop_area(dpr, minlat, maxlat, minlon, maxlon):
    '''
    dpr: GPMDPR object, minlat(float), maxlat(float),
    minlon(float), maxlon(float)
    '''
    cropped_area = dpr.ds.where((dpr.ds["Longitude"] >= minlon) & (dpr.ds["Longitude"] <= maxlon) &
             (dpr.ds["Latitude"] >= minlat) & (dpr.ds["Latitude"] <= maxlat), drop=True)
    return cropped_area


# In[4]:


# io = drpy.io.netrunner("Research", "[email protected]", dt.datetime(2016, 2, 28, 15, 0), 
#                        dt.datetime(2016, 2, 28, 15, 30))


# In[5]:


df16 = pd.read_csv("Data/28feb16/14.49to15.49.csv")
df16['time'] = pd.to_datetime(df16['LightningTimeString'])
df16 = df16[['time','Height','Longitude','Latitude','StrokeType']]


# In[6]:


file = "2A.GPM.DPR.V9-20211125.20160228-S145020-E162252.011373.V07A.HDF5"


# In[7]:


dpr = drpy.core.GPMDPR(filename=file)
# dpr.ds


# In[8]:


minlat=15
maxlat= 22
minlon=70
maxlon=80
india = crop_area(dpr, minlat, maxlat, minlon, maxlon)


# In[9]:

plt.figure(figsize = [6, 3.5])
ax = plt.axes(projection=ccrs.PlateCarree())
ax.set_extent([minlon+3, maxlon-3, minlat+2, maxlat-2])
gpmplot = india['zFactorFinal'].isel(nfreq=0).max(axis=2).plot.pcolormesh(x='Longitude',y='Latitude',
                                                                vmin = 0, vmax = 60,
                                                                cmap=drpy.graph.cmaps.HomeyerRainbow)
ax.set_title(pd.to_datetime(india['zFactorFinal'].isel(nfreq=0).time[0,0].values).strftime('%Y-%m-%d %H:%M'))
sctr = df16[df16["StrokeType"] == 1].plot(x = "Longitude", y = "Latitude", 
                                   kind = "scatter",  alpha = 0.2, marker = "X", s = 1, ax=ax, label = "IC", c = "k")
add_Map(ax)

# In[10]:
c = drpy.graph.case_study(filename=file,center_lat=19,center_lon=76)
c.plotter_cross(135)

[syedhamidali]

I wonder how I missed it, height (m) was already in the dpr object.

india['zFactorFinal'].isel(nfreq = 0)[:,25,:].plot(y = "height", x = "Longitude", 
                                                   vmin = -10, vmax = 60,
                                                   ylim = (0,11e3))

[dopplerchase]

Yeah, sorry for the delay. Its been a busy week. The height parameter isn't in files for V06 and earlier, so we use to have to calculate it manually, which was annoying. But I am glad the height is in the files now.

Just a note with this DPR files, the Ka-band zFactorFinal (last dimension index 1) is not what you might think it is. It is actually the retrieved DSD parameter that are then forward calculated to get Ka assuming Mie scattering. The Ku is the attenuation corrected Ku.

[syedhamidali]

Okay, thank you for this information!