等值线

本节介绍如何使用 cedarkit-maps 绘制 500hPa 位势高度等值线图。

首先导入需要使用的包。包括：

• 数据结构：numpy, pandas

• cedarkit 工具套件

  • 数据准备：reki

    • 数据查找函数： find_local_file

    • GRIB2文件要素加载函数：load_field_from_file

  • 气象可视化：cedarkit.maps

    • 绘图板：Panel

    • 底图布局：EastAsiaMapTemplate

    • 绘图样式：ContourStyle, ContourLabelStyle

import numpy as np
import pandas as pd

from reki.data_finder import find_local_file
from reki.format.grib.eccodes import load_field_from_file

from cedarkit.maps.style import ContourStyle, ContourLabelStyle
from cedarkit.maps.chart import Panel
from cedarkit.maps.domains import EastAsiaMapTemplate

设置绘图的数据参数，使用 CMA-GFS 2024 年 11 月 14 日 00 时次 024 时效数据。

system_name = "CMA-GFS"
data_type = "cma_gfs_gmf/grib2/orig"
start_time = pd.to_datetime("2024-11-14 00:00:00")
forecast_time = pd.to_timedelta("24h")

加载数据

获取 GRIB2 数据路径

file_path = find_local_file(
    data_type,
    start_time=start_time,
    forecast_time=forecast_time,
)
file_path

PosixPath('/g3/COMMONDATA/OPER/CEMC/GFS_GMF/Prod-grib/2024111400/ORIG/gmf.gra.2024111400024.grb2')

加载 500 hPa 位势高度场。位势高度在 ecCodes 的内置要素名为 gh

h_500_field = load_field_from_file(
    file_path,
    parameter="gh",
    level_type="pl",
    level=500
) / 10.0
h_500_field

<xarray.DataArray 'gh' (latitude: 1440, longitude: 2880)> Size: 33MB
array([[527.97007813, 527.97007813, 527.97007813, ..., 527.97007813,
        527.97007813, 527.97007813],
       [527.90007813, 527.90007813, 527.90007813, ..., 527.90007813,
        527.90007813, 527.90007813],
       [527.82007813, 527.82007813, 527.82007813, ..., 527.82007813,
        527.82007813, 527.82007813],
       ...,
       [484.42007813, 484.42007813, 484.42007813, ..., 484.42007813,
        484.42007813, 484.42007813],
       [484.41007813, 484.41007813, 484.41007813, ..., 484.41007813,
        484.41007813, 484.41007813],
       [484.39007813, 484.39007813, 484.39007813, ..., 484.39007813,
        484.39007813, 484.39007813]])
Coordinates:
    time        datetime64[ns] 8B 2024-11-14
    step        timedelta64[ns] 8B 1 days
    valid_time  datetime64[ns] 8B 2024-11-15
    pl          float64 8B 500.0
  * latitude    (latitude) float64 12kB 89.94 89.81 89.69 ... -89.81 -89.94
  * longitude   (longitude) float64 23kB 0.0 0.125 0.25 ... 359.6 359.8 359.9

xarray.DataArray

'gh'

• latitude: 1440
• longitude: 2880

• 528.0 528.0 528.0 528.0 528.0 528.0 ... 484.4 484.4 484.4 484.4 484.4

  array([[527.97007813, 527.97007813, 527.97007813, ..., 527.97007813,
          527.97007813, 527.97007813],
         [527.90007813, 527.90007813, 527.90007813, ..., 527.90007813,
          527.90007813, 527.90007813],
         [527.82007813, 527.82007813, 527.82007813, ..., 527.82007813,
          527.82007813, 527.82007813],
         ...,
         [484.42007813, 484.42007813, 484.42007813, ..., 484.42007813,
          484.42007813, 484.42007813],
         [484.41007813, 484.41007813, 484.41007813, ..., 484.41007813,
          484.41007813, 484.41007813],
         [484.39007813, 484.39007813, 484.39007813, ..., 484.39007813,
          484.39007813, 484.39007813]])

• Coordinates: (6)
  • time
    ()
    datetime64[ns]
    2024-11-14

    array('2024-11-14T00:00:00.000000000', dtype='datetime64[ns]')

  • step
    ()
    timedelta64[ns]
    1 days

    array(86400000000000, dtype='timedelta64[ns]')

  • valid_time
    ()
    datetime64[ns]
    2024-11-15

    array('2024-11-15T00:00:00.000000000', dtype='datetime64[ns]')

  • pl
    ()
    float64
    500.0

    array(500.)

  • latitude
    (latitude)
    float64
    89.94 89.81 89.69 ... -89.81 -89.94

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    array([ 89.9375,  89.8125,  89.6875, ..., -89.6875, -89.8125, -89.9375])

  • longitude
    (longitude)
    float64
    0.0 0.125 0.25 ... 359.8 359.9

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    array([0.00000e+00, 1.25000e-01, 2.50000e-01, ..., 3.59625e+02, 3.59750e+02,
           3.59875e+02])

• Indexes: (2)
  • latitude
    PandasIndex

    PandasIndex(Index([ 89.9375,  89.8125,  89.6875,  89.5625,  89.4375,  89.3125,  89.1875,
            89.0625,  88.9375,  88.8125,
           ...
           -88.8125, -88.9375, -89.0625, -89.1875, -89.3125, -89.4375, -89.5625,
           -89.6875, -89.8125, -89.9375],
          dtype='float64', name='latitude', length=1440))

  • longitude
    PandasIndex

    PandasIndex(Index([    0.0,   0.125,    0.25,   0.375,     0.5,   0.625,    0.75,   0.875,
               1.0,   1.125,
           ...
            358.75, 358.875,   359.0, 359.125,  359.25, 359.375,   359.5, 359.625,
            359.75, 359.875],
          dtype='float64', name='longitude', length=2880))

• Attributes: (0)

配置

定义等值线层次

h_contour_lev = np.linspace(500, 588, endpoint=True, num=23)
h_contour_lev

array([500., 504., 508., 512., 516., 520., 524., 528., 532., 536., 540.,
       544., 548., 552., 556., 560., 564., 568., 572., 576., 580., 584.,
       588.])

定义等值线颜色

h_contour_colos = "blue"

定义线宽

h_linewidths = np.where(h_contour_lev == 588, 1.4, 0.7)

定义等值线样式 (ContourStyle)，包括等值线标签样式 (ContourLabelStyle)

hgt_style = ContourStyle(
    levels=h_contour_lev,
    colors="blue",
    linewidths=h_linewidths,
    label=True,
    label_style=ContourLabelStyle(
        colors="black",
        fontsize=8,
    )
)

绘制

创建中国区域底图布局

domain = EastAsiaMapTemplate()

绘制等值线，设置标题

panel = Panel(domain=domain)
panel.plot(h_500_field, style=hgt_style)

domain.set_title(
    panel=panel,
    graph_name="500 hPa Height(10gpm)",
    system_name=system_name,
    start_time=start_time,
    forecast_time=forecast_time,
)
panel.show()