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社区首页 >专栏 >代码实战 | Skyborn 0.40 弯曲箭头完全指南：从平面到剖面

代码实战 | Skyborn 0.40 弯曲箭头完全指南：从平面到剖面

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用户11172986
发布于 2026-05-20 21:19:39
发布于 2026-05-20 21:19:39
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文章被收录于专栏：气python风雨气python风雨

🌬️ Skyborn 0.40 弯曲箭头完全指南：从平面到剖面

📌 文章标签：Python | 气象可视化 | Skyborn 0.40 | 弯曲箭头 | 剖面流线图 | 大气科学 ⏱️ 阅读时间：约 12 分钟 💻 代码可运行：是

💬 写在前面

hello，大家好，这里是气python风雨，小编最近购入了空气炸锅，正在认真研究菜谱中。但skyborn的作者唐突更新了，说是带来了完全体的弯曲箭头。前几期弯曲箭头的阅读量都不错，那不得不写一篇文章了

顺带说一句有读者反馈看了教程去画了图，ta的导师觉得很满意，小编挺高兴的

Skyborn 迎来了 0.40 版本的重大更新！作为气象可视化领域的"宝藏库"，这次升级不仅重构了底层风场分析管线，还大幅优化了弯曲箭头（Curly Vector）的绘制性能。最激动人心的是——剖面弯曲箭头正式登场了！🎉

本教程将带你从 ERA5 再分析数据出发，完整演示 Skyborn 0.40 的平面与剖面弯曲箭头绘制流程，一文搞定专业大气风场可视化！

🆕 Skyborn 0.40 更新了哪些内容？

在动手画箭头之前，先快速浏览一下 0.40 版本的核心变化，这能帮助你理解为什么现在要升级：

✨ New Features

  • 大气诊断扩展：新增 DCAPE、热带气旋/增长率计算路径等编译诊断模块的 Python 绑定，支撑大气柱工作流。
  • 混合坐标与 Sigma 插值现代化：扩展了 vinth2p 家族，提供更清晰的 column-major 与 C-order 入口，优化 ECMWF 处理逻辑，更新混合坐标与 Sigma 重映射辅助函数。

🔧 Improvements

  • 球谐与风场分析重构：精简球谐函数与简化向量风内部实现，降低包装器开销、提升缓存效率，公开 API 更清晰。
  • 绘图管线加速：将更多散点与弯曲向量的验证/采样工作下沉到原生辅助函数，减少 Python 侧开销和临时数组抖动。 👉 这意味着 curly_vector 绘制更快、内存更省！
  • 构建与文档清理：持续 Meson 构建现代化，重新整理接口文档与测试。

🗑️ Cleanup

  • 废弃旧 API：移除了旧的 Iris 接口及其他未使用的 legacy 路径，收紧了风场分析/谱辅助 API。
  • 回归覆盖：针对插值、绘图、谱辅助和风场分析路径增加了聚焦测试。

⚠️ 重要提醒：0.40 版本中，curved_quiver() 已更名为 curly_vector()，旧名称不再可用。请检查你的历史代码并同步更新！

一、安装 Skyborn 0.40

如果你还在使用旧版本，先升级到 0.40：

代码语言：javascript
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!pip install skyborn -U -i https://pypi.mirrors.ustc.edu.cn/simple/
代码语言：javascript
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Looking in indexes: https://pypi.mirrors.ustc.edu.cn/simple/
Collecting skyborn
  Downloading https://mirrors.ustc.edu.cn/pypi/packages/f6/e1/aa6e30d216268ffdd3f71469a674ee5f5a323f926004ff0ea79e533906b2/skyborn-0.4.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (2.7 MB)
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Installing collected packages: skyborn
Successfully installed skyborn-0.4.0
代码语言：javascript
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import skyborn as skb
print(f"Skyborn version: {skb.__version__}")
代码语言：javascript
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Skyborn version: 0.4.0

二、什么是 Skyborn 的"弯曲箭头"？

听到"弯曲箭头"，你可能会想到这样：

代码语言：javascript
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↗️ 或者 ↘️

但 Skyborn 的弯曲流线图是这样的：

代码语言：javascript
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〰️ 〰️ 〰️

↘️ ↙️ 〰️ 〰️ 它绘制的是矢量场的流线（streamlines），流线上带有指示风向的箭头。相比普通箭头，流线能更好地展示风场的连续性和演变趋势，是大气科学可视化的"标配"！

📚 **名词解释**：流线是某一时刻速度场中的一条曲线，曲线上每点的切线方向与该点的速度方向一致。简单说，就是"风的轨迹线"。

🆕 0.40 版本新特性：剖面弯曲箭头

之前的版本只能绘制平面（水平层）弯曲箭头。0.40 版本新增了 ncl_preset='profile' 参数支持，允许我们在垂直剖面（如纬度-高度剖面、经度-高度剖面）上绘制弯曲箭头，直观展示三维环流结构！

三、数据准备

本教程使用 ERA5 再分析数据，包含气压层上的 u、v、w、z、t、r、q 等变量。数据范围：

  • 时间：2023年8月2日 – 8月5日（6小时间隔）
  • 层次：1 hPa – 1000 hPa（37个气压层）
  • 区域：10°N–70°N，90°E–180°E
  • 分辨率：0.25°
代码语言：javascript
复制
import xarray as xr
import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import cartopy.feature as cfeature

# Load ERA5 data
ds = xr.open_dataset('/home/mw/input/era58091/ERA5-2023-08_pl.nc')

# Inspect data structure
print(ds)
print("\nTime range:", ds.time.values[0], "to", ds.time.values[-1])
print("Level range:", ds.level.values.min(), "hPa -", ds.level.values.max(), "hPa")
print("Spatial range: Lat", ds.latitude.values.min(), "°N to", ds.latitude.values.max(), "°N")
print("Spatial range: Lon", ds.longitude.values.min(), "°E to", ds.longitude.values.max(), "°E")
代码语言：javascript
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<xarray.Dataset> Size: 4GB
Dimensions:    (longitude: 361, latitude: 241, level: 37, time: 20)
Coordinates:
  * longitude  (longitude) float32 1kB 90.0 90.25 90.5 ... 179.5 179.8 180.0
  * latitude   (latitude) float32 964B 70.0 69.75 69.5 69.25 ... 10.5 10.25 10.0
  * level      (level) int32 148B 1 2 3 5 7 10 20 ... 875 900 925 950 975 1000
  * time       (time) datetime64[ns] 160B 2023-08-02 ... 2023-08-05T16:00:00
Data variables:
    z          (time, level, latitude, longitude) float64 515MB ...
    r          (time, level, latitude, longitude) float64 515MB ...
    t          (time, level, latitude, longitude) float64 515MB ...
    q          (time, level, latitude, longitude) float64 515MB ...
    u          (time, level, latitude, longitude) float64 515MB ...
    v          (time, level, latitude, longitude) float64 515MB ...
    w          (time, level, latitude, longitude) float64 515MB ...
Attributes:
    Conventions:  CF-1.6
    history:      2024-01-09 16:38:26 GMT by grib_to_netcdf-2.25.1: /opt/ecmw...

Time range: 2023-08-02T00:00:00.000000000 to 2023-08-05T16:00:00.000000000
Level range: 1 hPa - 1000 hPa
Spatial range: Lat 10.0 °N to 70.0 °N
Spatial range: Lon 90.0 °E to 180.0 °E
代码语言：javascript
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ds.z.min()
代码语言：javascript
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ds.level
代码语言：javascript
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from metpy.calc import vertical_velocity
from metpy.units import units
w = vertical_velocity(ds.w , ds.level, ds.t)

四、平面弯曲箭头绘制

⚠️ API 变化提醒：Skyborn 0.40 中，curved_quiver() 已更名为 curly_vector()。同时，当传入 xarray Dataset 时，请将 ds 作为第一个位置参数传入，不再支持 ds=... 关键字参数形式与 ax=... 混用。

4.1 快速上手：绘制 500 hPa 风场

代码语言：javascript
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# Select 500 hPa, 2023-08-02 00UTC
ds_500 = ds.sel(level=500, time='2023-08-03T00:00:00.000000000', method='nearest')

fig, ax = plt.subplots(figsize=(12, 8), subplot_kw={'projection': ccrs.PlateCarree()})

# ✅ Skyborn 0.40 新 API：curly_vector
# ds 作为第一个位置参数传入
quiver_set = skb.plot.curly_vector(
    ds_500,              # xarray Dataset（第一个位置参数）
    x='longitude',
    y='latitude',
    u='u',
    v='v',
    density=1,           # 流线密度
    arrowsize=2,       # 箭头大小
    color='steelblue',
    ref_length=0.6,   # 流线颜色
    linewidth=1
)

# Add map features
ax.coastlines(resolution='50m', linewidth=0.3)
ax.add_feature(cfeature.LAKES, alpha=0.5)
ax.add_feature(cfeature.RIVERS, alpha=0.5)
ax.gridlines(draw_labels=True, linewidth=0.3, linestyle='--', alpha=0.7)

ax.set_extent([90, 180, 10, 70], crs=ccrs.PlateCarree())
ax.set_title('🌐 Skyborn 0.40 平面弯曲箭头 — 500 hPa 风场\n2023-08-02 00UTC', fontsize=14)

# Add reference arrow key (0.40 new feature)
skb.plot.curly_vector_key(quiver_set, U=20, units='m/s', loc='lower right')

plt.tight_layout()
plt.show()
代码语言：javascript
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/opt/conda/lib/python3.11/site-packages/cartopy/mpl/geoaxes.py:527: UserWarning: Glyph 127760 (\N{GLOBE WITH MERIDIANS}) missing from font(s) Source Han Sans SC.
  super()._update_title_position(renderer)
/opt/conda/lib/python3.11/site-packages/cartopy/mpl/geoaxes.py:527: UserWarning: Glyph 127760 (\N{GLOBE WITH MERIDIANS}) missing from font(s) Source Han Sans SC.
  super()._update_title_position(renderer)
/opt/conda/lib/python3.11/site-packages/cartopy/mpl/geoaxes.py:524: UserWarning: Glyph 127760 (\N{GLOBE WITH MERIDIANS}) missing from font(s) Source Han Sans SC.
  return super().draw(renderer=renderer, **kwargs)
output
output

output

4.2 填色风场图：风速叠加弯曲箭头

将风速标量场作为填色背景，叠加弯曲箭头，信息密度更高：

代码语言：javascript
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fig, ax = plt.subplots(figsize=(14, 9), subplot_kw={'projection': ccrs.PlateCarree()}, dpi=150)

# Compute wind speed
u = ds_500['u']
v = ds_500['v']
spd = np.hypot(u, v)  # 风速标量

lon = ds_500.longitude.values
lat = ds_500.latitude.values

# Wind speed shading
cf = ax.contourf(lon, lat, spd, levels=20, cmap='Spectral_r', extend='both', transform=ccrs.PlateCarree())

# Overlay white curly vectors
quiver_set = skb.plot.curly_vector(
    ds_500,
    x='longitude',
    y='latitude',
    u='u',
    v='v',
    density=1,
    arrowsize=2,
    color='white',
    ref_length=0.6,
    linewidth=0.3,
)

# Map elements
ax.coastlines(resolution='50m', linewidth=0.8, color='black')
gl = ax.gridlines(draw_labels=True, linewidth=0.3, linestyle='--', alpha=0.7)
gl.top_labels = False
gl.right_labels = False

ax.set_extent([90, 180, 10, 70], crs=ccrs.PlateCarree())
ax.set_title('ERA5 500 hPa 风速填色 + 弯曲箭头\n2023-08-02 00UTC', fontsize=14)

# Colorbar
cbar = plt.colorbar(cf, ax=ax, shrink=0.7, pad=0.02, aspect=30)
cbar.set_label('Wind Speed (m/s)', fontsize=12)

# Reference arrow
skb.plot.curly_vector_key(quiver_set, U=20, units='m/s', loc='lower left')

plt.tight_layout()
plt.show()
output
output

output

五、剖面弯曲箭头绘制（0.40 新功能 ⭐）

这是 Skyborn 0.40 最令人兴奋的新能力！通过设置 ncl_preset='profile'，我们可以在垂直剖面上绘制弯曲箭头，直观展示经向环流、纬向环流等三维结构。

5.1 沿纬度-高度剖面（固定经度）

选取 120°E 经线，展示南北方向风场随高度的变化：

代码语言：javascript
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import metpy.calc as mpcalc
# Select 120°E profile, 2023-08-02 00UTC
ds_profile_lon = ds.sel(longitude=150, time='2023-08-02T00:00:00.000000000', method='nearest')

# Reverse levels so 1000 hPa is at bottom
ds_profile_lon = ds_profile_lon.isel(level=slice(None, None, -1))

# trans omega to w
ds_profile_lon['ww'] = mpcalc.vertical_velocity(
   ds_profile_lon['w'],
   ds_profile_lon['level'],
    ds_profile_lon['t']
) *1000

fig, ax = plt.subplots(figsize=(12, 8))

# Use ncl_preset='profile' for profile curly vectors
quiver_profile = skb.plot.curly_vector(
    ds_profile_lon,
    x='latitude',
    y='level',
    u='v',
    v='ww',
    density=1,
    arrowsize=1,
    color='darkblue',
    ncl_preset='profile',linewidth=0.6# ⭐ 关键参数：启用剖面预设
)

ax.set_yscale('log')
ax.invert_yaxis()
ax.set_ylim(1000, 100)
ax.set_xlim(10, 70)
ax.set_xlabel('Latitude (°N)', fontsize=12)
ax.set_ylabel('Pressure (hPa)', fontsize=12)
ax.set_title('🆕 Skyborn 0.40 剖面弯曲箭头 — 120°E 经向风场\n2023-08-02 00UTC', fontsize=14)
ax.grid(True, linestyle='--', alpha=0.5)

# Set y-axis ticks to common pressure levels
ax.set_yticks([1000, 850, 700, 500, 300, 200, 100])
ax.set_yticklabels(['1000', '850', '700', '500', '300', '200', '100'])

plt.tight_layout()
plt.show()
output
output

output

5.2 剖面填色 + 弯曲箭头叠加

将温度场作为填色背景，叠加风场弯曲箭头

代码语言：javascript
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fig, ax = plt.subplots(figsize=(14, 8))



lon_vals = ds_profile_lat.longitude.values
lev_vals = ds_profile_lat.level.values

# Temperature shading
t = ds_profile_lat['t'] - 273.15# Convert to °C
cf = ax.contourf(lon_vals, lev_vals, t, levels=20, cmap='RdBu_r', extend='both')

# Overlay curly vectors
quiver_overlay = skb.plot.curly_vector(
    ds_profile_lat,
    x='longitude',
    y='level',
    u='u',
    v='ww',
    density=1,
    arrowsize=1.5,
    color='black',
    ncl_preset='profile'
)

ax.set_yscale('log')
ax.invert_yaxis()
ax.set_ylim(1000, 100)
ax.set_xlim(90, 180)
ax.set_xlabel('Longitude (°E)', fontsize=12)
ax.set_ylabel('Pressure (hPa)', fontsize=12)
ax.set_title('40°N 温度填色 + 风场弯曲箭头\n2023-08-02 00UTC', fontsize=14)
ax.grid(True, linestyle='--', alpha=0.5)

ax.set_yticks([1000, 850, 700, 500, 300, 200, 100])
ax.set_yticklabels(['1000', '850', '700', '500', '300', '200', '100'])

cbar = plt.colorbar(cf, ax=ax, shrink=0.7, pad=0.02, aspect=30)
cbar.set_label('Temperature (°C)', fontsize=12)

plt.tight_layout()
plt.show()
output
output

output

六、核心参数速查表

Skyborn 0.40 curly_vector() 的常用参数整理如下：

参数

作用

调节技巧

ds

xarray 数据集

✅ 作为第一个位置参数传入

x

x 坐标变量名

如 'longitude'、'latitude'、'level'

y

y 坐标变量名

如 'latitude'、'level'

u

u 分量变量名

风的东西方向分量

v

v 分量变量名

风的南北/垂直方向分量

density

流线疏密

平面用 2-5；剖面用 2-4

linewidth

线宽

0.5-1.5 比较合适

arrowsize

箭头大小

0.8-1.5，根据整体比例调整

color

线条颜色

'steelblue'、'navy'、'white'

arrowstyle

箭头样式

'->' 空心线、'-

cmap

颜色映射

当 color 传入 2D 场时使用

alpha

透明度

0.3-1.0，叠加填色时建议 0.6-0.9

ncl_preset

NCL 预设模式

None（平面默认）或 'profile'（剖面）

integration_direction

积分方向

'forward'、'backward'、'both'

此外，0.40 新增的 curly_vector_key() 可用于在图上添加参考箭头图例，支持 U（参考风速）、units（单位）、loc（位置）等参数。

七、小结

Skyborn 0.40 的弯曲箭头功能在继承原有优点的基础上，实现了全面提升：

  • ✅ API 更名：curved_quiver() → curly_vector()，语义更清晰
  • ✅ 性能提升：更多计算下沉到原生层，Python 开销更低
  • ✅ 剖面支持：ncl_preset='profile' 让垂直剖面弯曲箭头成为可能
  • ✅ 图例工具：新增 curly_vector_key()，一键添加专业参考箭头

💡 小提示：弯曲箭头对数据格式要求较严格（需 xarray Dataset 或严格对齐的数组）。如果你的数据是非标准网格，建议先用 xarray 或 metpy 进行插值和坐标规范化处理。

屏幕前的你学会了吗？

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原始发表：2026-05-19，如有侵权请联系 cloudcommunity@tencent.com 删除
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目录
  • 🌬️ Skyborn 0.40 弯曲箭头完全指南：从平面到剖面
    • 💬 写在前面
    • 🆕 Skyborn 0.40 更新了哪些内容？
      • ✨ New Features
      • 🔧 Improvements
      • 🗑️ Cleanup
    • 一、安装 Skyborn 0.40
    • 二、什么是 Skyborn 的"弯曲箭头"？
      • 🆕 0.40 版本新特性：剖面弯曲箭头
    • 三、数据准备
    • 四、平面弯曲箭头绘制
      • 4.1 快速上手：绘制 500 hPa 风场
      • 4.2 填色风场图：风速叠加弯曲箭头
    • 五、剖面弯曲箭头绘制（0.40 新功能 ⭐）
      • 5.1 沿纬度-高度剖面（固定经度）
      • 5.2 剖面填色 + 弯曲箭头叠加
    • 六、核心参数速查表
    • 七、小结
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