Python可视化 | WRF模式模拟数据后处理（一）
点击下方公众号，回复资料，收获惊喜
import numpy
import cartopy
from cartopy import crs
from cartopy.feature import NaturalEarthFeature, COLORS
import matplotlib.pyplot as plt
from matplotlib.cm import get_cmap
from matplotlib.colors import from_levels_and_colors
from netCDF4 import Dataset
from xarray import DataArray
from wrf import getvar, interplevel, vertcross,vinterp, ALL_TIMES, CoordPair, xy_to_ll, ll_to_xy, to_np, get_cartopy, latlon_coords, cartopy_xlim, cartopy_ylim
from matplotlib.animation import FuncAnimation
from IPython.display import HTML
import os
import warnings
warnings.filterwarnings('ignore')
WRF_DIRECTORY = "../input/wrf3880"
WRF_FILES = ["wrfout_d01_2005-08-28_00_00_00",
"wrfout_d01_2005-08-28_12_00_00",
"wrfout_d01_2005-08-29_00_00_00"]
_WRF_FILES = [os.path.abspath(os.path.join(WRF_DIRECTORY, f)) for f in WRF_FILES]
for f in _WRF_FILES:
if not os.path.exists(f):
raise ValueError("{} does not exist. "
"Check for typos or incorrect directory.".format(f))
def single_wrf_file():
global _WRF_FILES
return _WRF_FILES[0]
def multiple_wrf_files():
global _WRF_FILES
return _WRF_FILES
风羽绘制
u = np.ma.masked_equal(np.zeros((5,5)), 0)
v = np.ma.masked_equal(np.zeros((5,5)), 0)
u[2,2] = 10.0
v[2,2] = 10.0
fig = plt.figure()
ax = plt.axes()
ax.barbs(u, v)
ax.set_xlim(0, 4)
ax.set_ylim(0, 4)
plt.show()
地形绘制
file_path = single_wrf_file()
wrf_file = Dataset(file_path)
terrain = getvar(wrf_file, "ter", timeidx=0)
cart_proj = get_cartopy(terrain)
lats, lons = latlon_coords(terrain)
fig = plt.figure(figsize=(10, 7.5))
geo_axes = plt.axes(projection=cart_proj)
states = NaturalEarthFeature(category='cultural',
scale='50m',
facecolor='none',
name='admin_1_states_provinces_shp')
geo_axes.add_feature(states, linewidth=.5)
geo_axes.coastlines('50m', linewidth=0.8)
levels = numpy.arange(250., 5000., 250.)
plt.contour(to_np(lons), to_np(lats),
to_np(terrain), levels=levels,
colors="black",
transform=crs.PlateCarree())
plt.contourf(to_np(lons), to_np(lats),
to_np(terrain), levels=levels,
transform=crs.PlateCarree(),
cmap=get_cmap("terrain"))
plt.colorbar(ax=geo_axes, shrink=.99)
plt.show()
海平面气压绘制
file_path = single_wrf_file()
wrf_file = Dataset(file_path)
slp = getvar(wrf_file, "slp", timeidx=0)
cart_proj = get_cartopy(slp)
lats, lons = latlon_coords(slp)
fig = plt.figure(figsize=(10, 7.5))
geo_axes = plt.axes(projection=cart_proj)
states = NaturalEarthFeature(category='cultural',
scale='50m',
facecolor='none',
name='admin_1_states_provinces_shp')
geo_axes.add_feature(states, linewidth=.5)
geo_axes.coastlines('50m', linewidth=0.8)
levels = numpy.arange(980.,1030.,2.5)
plt.contour(to_np(lons), to_np(lats),
to_np(slp), levels=levels, colors="black",
transform=crs.PlateCarree())
plt.contourf(to_np(lons), to_np(lats),
to_np(slp), levels=levels,
transform=crs.PlateCarree(),
cmap=get_cmap("jet"))
plt.colorbar(ax=geo_axes, shrink=.86)
plt.show()
截取特定区域绘制海平面气压
file_path = single_wrf_file()
wrf_file = Dataset(file_path)
slp = getvar(wrf_file, "slp", timeidx=0)
slp_shape = slp.shape
center_y = int(slp_shape[-2]/2.) - 1
center_x = int(slp_shape[-1]/2.) - 1
slp_quad = slp[..., 0:center_y+1, center_x:]
cart_proj = get_cartopy(slp_quad)
lats, lons = latlon_coords(slp_quad)
fig = plt.figure(figsize=(10, 7.5))
geo_axes = plt.axes(projection=cart_proj)
states = NaturalEarthFeature(category='cultural',
scale='50m',
facecolor='none',
name='admin_1_states_provinces_shp')
geo_axes.add_feature(states, linewidth=.5)
geo_axes.coastlines('50m', linewidth=0.8)
levels = numpy.arange(980.,1030.,2.5)
plt.contour(to_np(lons), to_np(lats),
to_np(slp_quad), levels=levels, colors="black",
transform=crs.PlateCarree())
plt.contourf(to_np(lons), to_np(lats),
to_np(slp_quad), levels=levels,
transform=crs.PlateCarree(),
cmap=get_cmap("jet"))
plt.colorbar(ax=geo_axes, shrink=.83)
plt.show()
气压场和相对湿度绘制
file_path = single_wrf_file()
wrf_file = Dataset(file_path)
slp = getvar(wrf_file, "slp", timeidx=0)
td2 = getvar(wrf_file, "td2", timeidx=0, units="degF")
u_sfc = getvar(wrf_file, "ua", timeidx=0, units="kt")[0,:]
v_sfc = getvar(wrf_file, "va", timeidx=0, units="kt")[0,:]
cart_proj = get_cartopy(slp)
lats, lons = latlon_coords(slp)
fig = plt.figure(figsize=(10, 7.5))
geo_axes = plt.axes(projection=cart_proj)
states = NaturalEarthFeature(category='cultural',
scale='50m',
facecolor='none',
name='admin_1_states_provinces_shp')
geo_axes.add_feature(states, linewidth=.5)
geo_axes.coastlines('50m', linewidth=0.8)
slp_levels = numpy.arange(980.,1030.,2.5)
td2_levels = numpy.arange(10., 79., 3.)
td2_rgb = numpy.array([[181,82,0], [181,82,0],
[198,107,8], [206,107,8],
[231,140,8], [239,156,8],
[247,173,24], [255,189,41],
[255,212,49], [255,222,66],
[255,239,90], [247,255,123],
[214,255,132], [181,231,148],
[156,222,156], [132,222,132],
[112,222,112], [82,222,82],
[57,222,57], [33,222,33],
[8,206,8], [0,165,0],
[0,140,0], [3,105,3]]) / 255.0
td2_cmap, td2_norm = from_levels_and_colors(td2_levels, td2_rgb, extend="both")
slp_contours = plt.contour(to_np(lons),
to_np(lats),
to_np(slp),
levels=slp_levels,
colors="black",
transform=crs.PlateCarree())
plt.contourf(to_np(lons), to_np(lats),
to_np(td2), levels=td2_levels,
cmap=td2_cmap, norm=td2_norm,
extend="both",
transform=crs.PlateCarree())
thin = [int(x/10.) for x in lons.shape]
plt.barbs(to_np(lons[::thin[0], ::thin[1]]),
to_np(lats[::thin[0], ::thin[1]]),
to_np(u_sfc[::thin[0], ::thin[1]]),
to_np(v_sfc[::thin[0], ::thin[1]]),
transform=crs.PlateCarree())
plt.clabel(slp_contours, fmt="%i")
plt.colorbar(ax=geo_axes, shrink=.86, extend="both")
plt.xlim(cartopy_xlim(slp))
plt.ylim(cartopy_ylim(slp))
plt.show()
850hPa气压场和风场绘制
file_path = single_wrf_file()
wrf_file = Dataset(file_path)
p = getvar(wrf_file, "pressure")
z = getvar(wrf_file, "z", units="dm")
ua = getvar(wrf_file, "ua", units="kt")
va = getvar(wrf_file, "va", units="kt")
wspd = getvar(wrf_file, "wspd_wdir", units="kt")[0,:]
ht_850 = interplevel(z, p, 850)
u_850 = interplevel(ua, p, 850)
v_850 = interplevel(va, p, 850)
wspd_850 = interplevel(wspd, p, 850)
lats, lons = latlon_coords(ht_850)
cart_proj = get_cartopy(ht_850)
fig = plt.figure(figsize=(10,7.5))
ax = plt.axes(projection=cart_proj)
states = NaturalEarthFeature(category='cultural',
scale='50m',
facecolor='none',
name='admin_1_states_provinces_shp')
ax.add_feature(states, linewidth=0.5)
ax.coastlines('50m', linewidth=0.8)
levels = numpy.arange(130., 170., 6.)
contours = plt.contour(to_np(lons),
to_np(lats),
to_np(ht_850),
levels=levels,
colors="black",
transform=crs.PlateCarree())
plt.clabel(contours, inline=1, fontsize=10, fmt="%i")
levels = [25, 30, 35, 40, 50, 60, 70, 80, 90, 100, 110, 120]
wspd_contours = plt.contourf(to_np(lons),
to_np(lats),
to_np(wspd_850),
levels=levels,
cmap=get_cmap("rainbow"),
transform=crs.PlateCarree())
plt.colorbar(wspd_contours, ax=ax, orientation="horizontal", pad=.05, shrink=.75)
thin = [int(x/10.) for x in lons.shape]
plt.barbs(to_np(lons[::thin[0], ::thin[1]]),
to_np(lats[::thin[0], ::thin[1]]),
to_np(u_850[::thin[0], ::thin[1]]),
to_np(v_850[::thin[0], ::thin[1]]),
length=6,transform=crs.PlateCarree())
# Set the map bounds
ax.set_xlim(cartopy_xlim(ht_850))
ax.set_ylim(cartopy_ylim(ht_850))
ax.gridlines()
plt.title("850 MB Height (dm), Wind Speed (kt), Barbs (kt)")
plt.show()
垂直剖面绘制
cross_start = CoordPair(lat=26.75, lon=-91.7)
cross_end = CoordPair(lat=26.75, lon=-86.7)
file_path = multiple_wrf_files()
wrf_file = [Dataset(x) for x in file_path]
slp = getvar(wrf_file, "slp", timeidx=-1)
z = getvar(wrf_file, "z", timeidx=-1)
dbz = getvar(wrf_file, "dbz", timeidx=-1)
Z = 10**(dbz/10.)
z_cross = vertcross(Z, z, wrfin=wrf_file,
start_point=cross_start,
end_point=cross_end,
latlon=True, meta=True)
dbz_cross = 10.0 * numpy.log10(z_cross)
lats, lons = latlon_coords(slp)
cart_proj = get_cartopy(slp)
fig = plt.figure(figsize=(15,5))
ax_slp = fig.add_subplot(1,2,1,projection=cart_proj)
ax_dbz = fig.add_subplot(1,2,2)
states = NaturalEarthFeature(category='cultural', scale='50m', facecolor='none',
name='admin_1_states_provinces_shp')
land = NaturalEarthFeature(category='physical', name='land', scale='50m',
facecolor=COLORS['land'])
ocean = NaturalEarthFeature(category='physical', name='ocean', scale='50m',
facecolor=COLORS['water'])
slp_levels = numpy.arange(950.,1030.,5)
slp_contours = ax_slp.contour(to_np(lons),
to_np(lats),
to_np(slp),
levels=slp_levels,
colors="black",
zorder=3,
transform=crs.PlateCarree())
ax_slp.clabel(slp_contours, fmt="%i")
ax_slp.plot([cross_start.lon, cross_end.lon],
[cross_start.lat, cross_end.lat],
color="yellow",
marker="o",
zorder=3,
transform=crs.PlateCarree())
ax_slp.add_feature(ocean)
ax_slp.add_feature(land)
ax_slp.add_feature(states, linewidth=.5, edgecolor="black")
dbz_levels = numpy.arange(5.,75.,5.)
dbz_contours = ax_dbz.contourf(to_np(dbz_cross), levels=dbz_levels, cmap=get_cmap("jet"))
cb_dbz = fig.colorbar(dbz_contours, ax=ax_dbz)
cb_dbz.ax.tick_params(labelsize=8)
coord_pairs = to_np(dbz_cross.coords["xy_loc"])
x_ticks = numpy.arange(coord_pairs.shape[0])
x_labels = [pair.latlon_str() for pair in to_np(coord_pairs)]
thin = [int(x/5.) for x in x_ticks.shape]
ax_dbz.set_xticks(x_ticks[1::thin[0]])
ax_dbz.set_xticklabels(x_labels[::thin[0]], rotation=45, fontsize=8)
vert_vals = to_np(dbz_cross.coords["vertical"])
v_ticks = numpy.arange(vert_vals.shape[0])
thin = [int(x/8.) for x in v_ticks.shape]
ax_dbz.set_yticks(v_ticks[::thin[0]])
ax_dbz.set_yticklabels(vert_vals[::thin[0]], fontsize=8)
ax_dbz.set_xlabel("Latitude, Longitude", fontsize=12)
ax_dbz.set_ylabel("Height (m)", fontsize=12)
ax_slp.set_title("Sea Level Pressure (hPa)", {"fontsize" : 14})
ax_dbz.set_title("Cross-Section of Reflectivity (dBZ)", {"fontsize" : 14})
plt.show()
时空演变绘制（动画与视频）
file_path = multiple_wrf_files()
wrf_file = [Dataset(f) for f in file_path]
slp_all = getvar(wrf_file, "slp", timeidx=ALL_TIMES)
cart_proj = get_cartopy(slp_all)
fig = plt.figure(figsize=(10,7.5))
ax_slp = plt.axes(projection=cart_proj)
states = NaturalEarthFeature(category='cultural', scale='50m', facecolor='none',
name='admin_1_states_provinces_shp')
land = NaturalEarthFeature(category='physical', name='land', scale='50m',
facecolor=COLORS['land'])
ocean = NaturalEarthFeature(category='physical', name='ocean', scale='50m',
facecolor=COLORS['water'])
slp_levels = numpy.arange(950.,1030.,5.)
num_frames = slp_all.shape[0]
def animate(i):
ax_slp.clear()
slp = slp_all[i,:]
lats, lons = latlon_coords(slp)
ax_slp.add_feature(ocean)
ax_slp.add_feature(land)
ax_slp.add_feature(states, linewidth=.5, edgecolor="black")
slp_contours = ax_slp.contour(to_np(lons),
to_np(lats),
to_np(slp),
levels=slp_levels,
colors="black",
zorder=5,
transform=crs.PlateCarree())
ax_slp.clabel(slp_contours, fmt="%i")
ax_slp.set_xlim(cartopy_xlim(slp))
ax_slp.set_ylim(cartopy_ylim(slp))
return ax_slp
ani = FuncAnimation(fig, animate, num_frames, interval=500)
HTML(ani.to_jshtml())
动画在公众号中不太好放，感兴趣的大家可以去和鲸社区上手玩儿一下。代码获取在好奇心Log公众号后台回复wrf绘图
本文参与 腾讯云自媒体同步曝光计划，分享自微信公众号。
原始发表：2021-08-19，如有侵权请联系 cloudcommunity@tencent.com 删除
评论
登录后参与评论
推荐阅读
目录
腾讯云开发者
