def get_data_from_dropsonde(file):
# file = os.path.join(dropsonde_dir, 'D20150712_201424_PQC.nc')
data = xr.open_dataset(file)
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=RuntimeWarning)
index = data.GPSAlt.values < 4000
ret = {}
ret['TIME']=utils.as_datetime(data.time_offset.values[index])
ret['GGLAT']=data.Lat.values[index]
ret['GGLON']=data.Lon.values[index]
ret['GGALT']=data.GPSAlt.values[index]
ret['RHUM']=data.RH.values[index]
ret['ATX']=data.Temp.values[index]+273.15
ret['PSX']=data.Press.values[index]
ret['DPXC']= data.Dewpt.values[index]+273.15
ret['QV'] = mu.qv_from_p_T_RH(ret['PSX']*100, ret['ATX'], ret['RHUM'])*1000
ret['MR'] = ret['QV']/(1-ret['QV']/1000)
ret['TVIR'] = mu.tvir_from_T_w(ret['ATX'], ret['MR']/1000)
ret['DENS'] = mu.density_from_p_Tv(ret['PSX']*100, ret['TVIR'])
ret['THETA']= mu.theta_from_p_T(ret['PSX'], ret['ATX'])
ret['THETAE']= mu.thetae_from_t_tdew_mr_p(ret['ATX'], ret['DPXC'], ret['MR']/1000, ret['PSX']*100) #equiv pot temp, K we can get this if we really want
ret['QL'] = np.full_like(ret['PSX'], fill_value=np.nan)
ret['THETAL'] = np.full_like(ret['PSX'], fill_value=np.nan)
ret['PLWCC']= np.full_like(ret['PSX'], fill_value=np.nan)
return ret
def get_data_from_flight(flight_num, start=None, end=None, var_list=[]):
flight_file = glob.glob(os.path.join(flight_dir, 'RF{:02d}*.nc'.format(flight_num)))[0]
# data = xr.open_dataset(flight_file, decode_times=False)
# data['time'] = nc.num2date(data.Time[:],units=data.Time.units)
data = xr.open_dataset(flight_file, decode_times=True)
dates = utils.as_datetime(data.Time.values)
alt = data['GGALT'].values
if start is None:
start = dates[0]
if end is None:
end = dates[-1]
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=RuntimeWarning)
index = np.logical_and(np.logical_and(dates >= start, dates <= end), alt < 3600)
[(k, v.long_name) for k,v in data.data_vars.items() if 'Pres' in v.long_name]
ret = {}
ret['TIME'] = dates[index]
for i in var_list:
if i == 'ATX':
ret[i] = data[i].values[index]+273.15
else:
ret[i] = data[i].values[index]
ret['DENS'] = mu.density_from_p_Tv(data['PSX'].values[index]*100, data['TVIR'].values[index]+273.15)
ret['QL'] = data['PLWCC'].values[index]/ret['DENS']
ret['THETAL'] = mu.get_liquid_water_theta(ret['ATX'], ret['THETA'], ret['QL'])
ret['QV'] = data['MR'].values[index]/(1+data['MR'].values[index]/1000)
return ret
label,
xy=(x, y), xytext=(-20, 20),
textcoords='offset points', ha='right', va='bottom',
bbox=dict(boxstyle='round,pad=0.5', alpha=0.5),
arrowprops=dict(arrowstyle = '->', connectionstyle='arc3,rad=0'))
# %% Main execution
if __name__ == "__main__":
path = r'/home/disk/eos4/jkcm/Data/CSET/LookupTable_all_flights.xls'
flight = utils.read_CSET_Lookup_Table(path,
rf_num='all',
sequences=['d', 'k'],
variables=['Date', 'ST', 'ET'])
start_times = utils.as_datetime([utils.CSET_date_from_table(d, t) for d, t in
zip(flight['Date']['values'], flight['ST']['values'])])
end_times = utils.as_datetime([utils.CSET_date_from_table(d, t) for d, t in
zip(flight['Date']['values'], flight['ET']['values'])])
sounding_times = list(zip(flight['rf'], start_times, end_times))
# %% read in data
# get flight info for each sounding
var_list = ['GGLAT', 'GGLON', 'GGALT', 'RHUM', 'ATX', 'MR', 'THETAE', 'THETA', 'PSX', 'DPXC', 'PLWCC']
soundings = []
lt = LoopTimer(len(sounding_times))
for i in sounding_times:
lt.update()
soundings.append(get_data_from_flight(i[0], i[1], i[2], var_list))
add_dropsondes = True
if add_dropsondes: