【WRF数据准备】批量下载ERA5再分析数据-气象驱动数据

气象驱动数据-ERA5再分析数据的手动下载可以参考我的另一博客-【WRF数据准备】气象驱动数据-ERA5再分析数据（Copernicus）。

本博客详细介绍批量下载ERA5再分析数据，并给出完整实现代码。

批量下载 ERA5 的气压层（pressure level）和地面层（single level）数据（GRIB 格式），自动循环日期，并分别保存为不同文件名。

准备工作

1. 安装 cdsapi 模块

conda activate myenv3.10

# 使用 conda 或 pip 安装 cdsapi
pip install cdsapi
conda install cdsapi

验证安装是否成功，可以执行以下命令测试：

python -c "import cdsapi; print('✅ cdsapi 已成功安装')"

如果没有报错，就表示安装成功了。

2. .cdsapirc 文件配置

可以从 CDS 网站获取 和 ：CDS 网站-Climate Data Store

登录后，页面顶部会显示 API key，例如：

url: https://cds.climate.copernicus.eu/api/v2
key: <uid>:<api-key>

在 ~/ 文件夹下新建.cdsapirc 文件，并填入以上内容即可。

实现代码

retrieve.grid.sh 脚本

#!/bin/bash
# retrieve.grid.sh
# 下载 ERA5 气压层 + 地面层数据

# 确保使用正确的 Conda 初始化方式
conda activate myenv3.10

echo "当前 Python 路径：$(which python)"

year=2022
mon=07

for dd in 01 02 03 04 05 06 07 08 09 $(seq -w 10 31); do
    echo "===== 正在下载：${year}-${mon}-${dd} ..."

    # 替换模板中的占位符
    sed -e "s/yyyy/${year}/g" -e "s/mm/${mon}/g" -e "s/dd/${dd}/g" grib.pre.2022.baz > grib.pre.py
    sed -e "s/yyyy/${year}/g" -e "s/mm/${mon}/g" -e "s/dd/${dd}/g" grib.sur.2022.baz > grib.sur.py

    # 下载气压层
    echo "===== 下载气压层数据 ..."
    python grib.pre.py
    if [ -f download.grib ]; then
        mv download.grib ERA5_PRE_${year}-${mon}-${dd}.grib
    else
        echo "气压层下载失败：ERA5_PRE_${year}-${mon}-${dd}.grib"
    fi

    # 下载地面层
    echo "===== 下载地面层数据 ..."
    python grib.sur.py
    if [ -f download.grib ]; then
        mv download.grib ERA5_SUR_${year}-${mon}-${dd}.grib
    else
        echo "地面层下载失败：ERA5_SUR_${year}-${mon}-${dd}.grib"
    fi

    echo "完成：${year}-${mon}-${dd}"
done

grib.pre.2022.baz 模板（ERA5 气压层）

#!/usr/bin/env python
import cdsapi

client = cdsapi.Client()

client.retrieve(
    "reanalysis-era5-pressure-levels",
    {
        "product_type": "reanalysis",
        "variable": [
            "geopotential", "relative_humidity", "specific_humidity",
            "temperature", "u_component_of_wind", "v_component_of_wind"
        ],
        "year": "yyyy",
        "month": "mm",
        "day": "dd",
        "time": [
            "00:00", "01:00", "02:00", "03:00", "04:00", "05:00",
            "06:00", "07:00", "08:00", "09:00", "10:00", "11:00",
            "12:00", "13:00", "14:00", "15:00", "16:00", "17:00",
            "18:00", "19:00", "20:00", "21:00", "22:00", "23:00"
        ],
        "pressure_level": [
            "1", "2", "3", "5", "7", "10", "20", "30", "50", "70",
            "100", "125", "150", "175", "200", "225", "250", "300",
            "350", "400", "450", "500", "550", "600", "650", "700",
            "750", "775", "800", "825", "850", "875", "900", "925",
            "950", "975", "1000"
        ],
        "format": "grib",
        "area": [56, 70, 15, 140]
    },
    "download.grib"
)

grib.sur.2022.baz 模板（ERA5 地面层）

#!/usr/bin/env python
import cdsapi

client = cdsapi.Client()

client.retrieve(
    "reanalysis-era5-single-levels",
    {
        "product_type": "reanalysis",
        "variable": [
            "10m_u_component_of_wind", "10m_v_component_of_wind",
            "2m_dewpoint_temperature", "2m_temperature",
            "mean_sea_level_pressure", "sea_surface_temperature",
            "surface_pressure", "skin_temperature",
            "snow_density", "snow_depth",
            "soil_temperature_level_1", "soil_temperature_level_2",
            "soil_temperature_level_3", "soil_temperature_level_4",
            "volumetric_soil_water_layer_1", "volumetric_soil_water_layer_2",
            "volumetric_soil_water_layer_3", "volumetric_soil_water_layer_4",
            "land_sea_mask", "sea_ice_cover"
        ],
        "year": "yyyy",
        "month": "mm",
        "day": "dd",
        "time": [
            "00:00", "01:00", "02:00", "03:00", "04:00", "05:00",
            "06:00", "07:00", "08:00", "09:00", "10:00", "11:00",
            "12:00", "13:00", "14:00", "15:00", "16:00", "17:00",
            "18:00", "19:00", "20:00", "21:00", "22:00", "23:00"
        ],
        "format": "grib",
        "area": [56, 70, 15, 140]
    },
    "download.grib"
)

运行方式

chmod +x retrieve_era5_2022_07.sh
./retrieve_era5_2022_07.sh

或者直接运行：

bash retrieve_era5_2022_07.sh

终端下载界面如下：

参考