实用编程 | Python+Matplotlib制作超高分辨率动态气象/海洋要素可视化动图

气象学家

发布于 2021-11-16 10:58:19

9990

发布于 2021-11-16 10:58:19

文章被收录于专栏：气象学家

Animated version of Gulf Stream sea surface temperatures done with

@oceanographer from yesterday - inspired by the moving media #art installations @refikanadol! Shading and texture comes from simulated zonal currents #SciArt @neuro_rish@matplotlib #FESOM2

FESOM2 SST shaded by U component of velocity

Example of scalar field visualization shaded by corresponding vector field.Data used are from FESOM2 model simulations with 1km resolution in Gulf Stream area. Data are interpolated to regular 1/100 degree grid.

数据空间上进行了插值，大概就是1km左右的格点分辨率了。

链接: (数据+代码+测试图)

https://github.com/koldunovn/FESOM_SST_shaded_by_U

代码:

import xarray as xr
import numpy as np
import matplotlib.pylab as plt
import matplotlib.cm as cm

###Download data:
#wget https://zenodo.org/record/4759091/files/GF_FESOM2_testdata.tar.gz
###Unpack data:
#gunzip GF_FESOM2_testdata.tar.gz
#tar -xvf GF_FESOM2_testdata.tar
###Open netCDF files

sst = xr.open_dataset('./GF_FESOM2_testdata/sst.nc')
u = xr.open_dataset('./GF_FESOM2_testdata/u_surf.nc')
v = xr.open_dataset('./GF_FESOM2_testdata/v_surf.nc')

###Plot the figure with U shading

fig, ax = plt.subplots(
            1,
            1,
            constrained_layout=True,
            figsize=(10,10),
        )
ax.imshow(np.flipud(sst.sst.values), cmap=cm.RdBu_r,  vmin=12, vmax=24)
ax.imshow(np.flipud(u.u_surf.values), alpha=0.3, cmap=cm.gray, vmin=-.3, vmax=0.3)
ax.axis('off');
### plt.savefig('./out_figure.png', dpi=300)

###Plot the figure with V shading

fig, ax = plt.subplots(
            1,
            1,
            constrained_layout=True,
            figsize=(10,10),
        )
ax.imshow(np.flipud(sst.sst.values), cmap=cm.RdBu_r,  vmin=12, vmax=24)
ax.imshow(np.flipud(v.v_surf.values), alpha=0.3, cmap=cm.gray, vmin=-.3, vmax=0.3)
ax.axis('off');

###Rotate "light source" for U by 45 degrees
direct = np.rad2deg(np.arctan2(v.v_surf.values, u.u_surf.values))
speed_rot = np.hypot(u.u_surf.values, v.v_surf.values)

myangle = 45
U = speed_rot * np.cos(np.deg2rad(myangle - direct))
# V = speed_rot * np.sin(np.deg2rad(myangle - direct))
fig, ax = plt.subplots(
            1,
            1,
            constrained_layout=True,
            figsize=(10,10),
        )
ax.imshow(np.flipud(sst.sst.values), cmap=cm.RdBu_r,  vmin=12, vmax=24)
ax.imshow(np.flipud(U), alpha=0.3, cmap=cm.gray, vmin=-.3, vmax=0.3)
ax.axis('off');

测试图: