数据下载 | 探空数据自动下载&可视化基础

#导入模块
import datetime 
from metpy.units import units
from siphon.simplewebservice.wyoming import WyomingUpperAir

# 设置下载时段（这里是UTC时刻）
start = datetime.datetime(2019, 8, 1, 0)
end = datetime.datetime(2019, 8, 2, 0)

datelist = []
while start<=end:
    datelist.append(start)
    start+=datetime.timedelta(hours=12)

# 选择下载站点（以北京为例）
stationlist = ['54511']

# 批量下载
for station in stationlist:
    for date in datelist:
        try:
            df = WyomingUpperAir.request_data(date, station)
            df.to_csv(station+'_'+date.strftime('%Y%m%d%H')+'.csv',index=False)
            print(f'{date.strftime("%Y%m%d_%H")}下载成功')
        except Exception as e:
            print(f'{date.strftime("%Y%m%d_%H")}下载失败: {e}')
            pass

import pandas as pd
import metpy.calc as mpcalc
from metpy.cbook import get_test_data
from metpy.plots import add_metpy_logo, SkewT
from metpy.units import units
import matplotlib.pyplot as plt
df = pd.read_csv('./54511_2019080200.csv')
df.info()

p = df['pressure'].values * units.hPa
T = df['temperature'].values * units.degC
Td = df['dewpoint'].values * units.degC
wind_speed = df['speed'].values * units.knots
wind_dir = df['direction'].values * units.degrees
u, v = mpcalc.wind_components(wind_speed, wind_dir)

fig = plt.figure(figsize=(9, 9))
skew = SkewT(fig, rotation=45)

# Plot the data using normal plotting functions, in this case using
# log scaling in Y, as dictated by the typical meteorological plot.
skew.plot(p, T, 'r')
skew.plot(p, Td, 'g')
skew.plot_barbs(p, u, v)
skew.ax.set_ylim(1050, 300)
skew.ax.set_xlim(0, 40)

# Calculate LCL height and plot as black dot. Because `p`'s first value is
# ~1000 mb and its last value is ~250 mb, the `0` index is selected for
# `p`, `T`, and `Td` to lift the parcel from the surface. If `p` was inverted,
# i.e. start from low value, 250 mb, to a high value, 1000 mb, the `-1` index
# should be selected.
lcl_pressure, lcl_temperature = mpcalc.lcl(p[0], T[0], Td[0])
skew.plot(lcl_pressure, lcl_temperature, 'ko', markerfacecolor='black')

# Calculate full parcel profile and add to plot as black line
prof = mpcalc.parcel_profile(p, T[0], Td[0]).to('degC')
skew.plot(p, prof, 'k', linewidth=2)

# Shade areas of CAPE and CIN
skew.shade_cin(p, T, prof)
skew.shade_cape(p, T, prof)

# An example of a slanted line at constant T -- in this case the 0
# isotherm
skew.ax.axvline(0, color='c', linestyle='--', linewidth=2)

# Add the relevant special lines
skew.plot_dry_adiabats()
skew.plot_moist_adiabats()
skew.plot_mixing_lines()

fig = plt.figure(figsize=(9, 9))
skew = SkewT(fig, rotation=45)
skew.plot_dry_adiabats()
skew.plot_moist_adiabats()
skew.plot_mixing_lines()