lab5 start

EAPS 431 - Spring 2018‎ > ‎

let's get the Springfest sounding loaded and separated into individual variable arrays, plot T vs height and T vs log(P)

import numpy as np

import matplotlib.pyplot as plt

%matplotlib inline

filename = '/scratch/scholar/mebaldwi/EAPS431/20160416_1642Z_Purdue_Oval.txt'

data = np.genfromtxt(filename, delimiter=',',skip_header=3)

lat=data[:,0]

lon=data[:,1]

time=data[:,2]

height_m=data[:,3]

press_mb=data[:,4]

temp_C=data[:,5]

mix_ratio_gkg=data[:,6]

wind_spd_ms=data[:,7]

wind_dir_deg=data[:,8]

temp_K=temp_C+273.15

height_msl=height_m+190.

press_Pa=press_mb*100.

theta=temp_K*(1000./press_mb)**0.286

plt.plot(temp_K,height_msl)

plt.xlabel('temp K')

plt.ylabel('height m')

plt.axis([200, 300, 0, 16000])

fig, ax = plt.subplots()
ax.plot(temp_K,press_mb,color='b',linewidth=1)
ax.set_yscale('log')
ax.set_xlabel('temp K')
ax.set_ylabel('pressure mb')
ax.set_xlim(200, 300)
ax.set_ylim(1025, 100)
ax.set_xticks(np.arange(200,301,10))
ax.set_yticks([1000,850,700,600,500,400,300,250,200,150,100])
ax.set_yticklabels(['1000', '850','700','600','500','400','300','250','200','150','100'])

Stuve code

# Stuve chart code

x = np.arange(220, 460, 10)

y = np.arange(100, 1026, 25)

theta_2D, P_2D = np.meshgrid(x, y)

T_2D=theta_2D*(P_2D/1000.)**0.286

y = np.arange(40000, 102600, 2500)

x = np.array([0.1, 0.2, 0.4, 0.6, 0.8, 1.0, 1.5, 2., 3., 4., 6., 8., 10., 12., 16., 20.])

labels=['0.1', '0.2', '0.4', '0.6', '0.8', '1', '1.5', '2', '3', '4', '6', '8', '10', '12', '16', '20']

x = x/1000.

ws_2D, Pws_2D = np.meshgrid(x, y)

ws_T_2D=1./(1./273.15-1.844e-4*np.log(ws_2D*Pws_2D/611.3/(ws_2D+0.622)))

fig, ax = plt.subplots()

ax.set_yscale('log')

ax.set_xlabel('temp K')

ax.set_ylabel('pressure mb')

ax.set_title('Stuve chart')

ax.set_xlim(200, 300)

ax.set_ylim(1025, 400)

ax.minorticks_off()

ax.set_xticks(np.arange(200,301,10))

ax.set_yticks([1000,850,700,600,500,400])

ax.set_yticklabels(['1000', '850','700','600','500','400'])

ax.grid(True)

ax.plot(ws_T_2D,Pws_2D*0.01,color='#a4c2f4',linestyle='dashed')

ax.plot(T_2D,P_2D,color='#f6b26b')

for i in np.arange(16):

ax.text(ws_T_2D[3,i],Pws_2D[3,i]*0.01,labels[i],color='#0000f4',ha='center',weight='bold')

ax.text(ws_T_2D[22,i],Pws_2D[22,i]*0.01,labels[i],color='#0000f4',ha='center',weight='bold')

fig.set_size_inches(10,8)

calculate dewpoint from mixing ratio and pressure

mixratio_kgkg=(mix_ratio_gkg+0.0001)/1000.

To=273.15

RoverL=1.844e-4

eps=0.622

eo=611.3

td=1./(1/To-RoverL*np.log((mixratio_kgkg*press_Pa/(eo*(mixratio_kgkg+eps)))))

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