获取高精度气象数据!Python一键下载Open-Meteo逐小时观测数据

pip install pandas openmeteo-requests requests-cache retry-requests

import pandas as pdimport openmeteo_requestsimport requests_cachefrom retry_requests import retry# 1. 初始化 Open-Meteo API 客户端，配置缓存与重试机制cache_session = requests_cache.CachedSession(".cache", expire_after=3600)retry_session = retry(cache_session, retries=5, backoff_factor=0.2)openmeteo = openmeteo_requests.Client(session=retry_session)def download_meteo_data(    lat, lon, start_date_bj, end_date_bj, output_csv="meteo_data.csv"):    # 2. 将输入的北京时间日期转换为 UTC 日期以适配 API    start_dt_utc = pd.to_datetime(start_date_bj) - pd.Timedelta(hours=8)    end_dt_utc = pd.to_datetime(end_date_bj) - pd.Timedelta(hours=8)    # 3. 设置 API 请求参数    url = "https://archive-api.open-meteo.com/v1/archive"    params = {        "latitude": lat,        "longitude": lon,        "start_date": start_dt_utc.strftime("%Y-%m-%d"),        "end_date": end_dt_utc.strftime("%Y-%m-%d"),        "hourly": [            "temperature_2m",            "relative_humidity_2m",            "rain",            "surface_pressure",            "cloud_cover",            "wind_speed_10m",            "wind_direction_10m",            "boundary_layer_height",            "shortwave_radiation",        ],        "wind_speed_unit": "ms",        "timezone": "auto",    }    print(f"正在请求数据，经度：{lon}，纬度：{lat}...")    responses = openmeteo.weather_api(url, params=params)    response = responses[0]    # 4. 解析小时数据    hourly = response.Hourly()    start_timestamp = hourly.Time()    end_timestamp = hourly.TimeEnd()    interval = hourly.Interval()    utc_time_range = pd.date_range(        start=pd.to_datetime(start_timestamp, unit="s", utc=True),        end=pd.to_datetime(end_timestamp, unit="s", utc=True),        freq=pd.Timedelta(seconds=interval),        inclusive="left",    )    # 定义带单位的列名，提升数据可读性    col_temp = "temperature_2m [°C]"    col_rh = "relative_humidity_2m [%]"    col_rain = "rain [mm]"    col_press = "surface_pressure [hPa]"    col_cloud = "cloud_cover [%]"    col_ws = "wind_speed_10m [m/s]"    col_wd = "wind_direction_10m (10 m) [°]"    col_pbl = "boundary_layer_height [m]"    col_ghi = "shortwave_radiation [W/m²]"    hourly_data = {        "text_time_utc": utc_time_range,        col_temp: hourly.Variables(0).ValuesAsNumpy(),        col_rh: hourly.Variables(1).ValuesAsNumpy(),        col_rain: hourly.Variables(2).ValuesAsNumpy(),        col_press: hourly.Variables(3).ValuesAsNumpy(),        col_cloud: hourly.Variables(4).ValuesAsNumpy(),        col_ws: hourly.Variables(5).ValuesAsNumpy(),        col_wd: hourly.Variables(6).ValuesAsNumpy(),        col_pbl: hourly.Variables(7).ValuesAsNumpy(),        col_ghi: hourly.Variables(8).ValuesAsNumpy(),    }    df = pd.DataFrame(data=hourly_data)    # 5. UTC 转北京时间（UTC+8）    df["Time (Beijing)"] = df["text_time_utc"].dt.tz_convert("Asia/Shanghai")    df["Time (Beijing)"] = df["Time (Beijing)"].dt.tz_localize(None)    df = df.drop(columns=["text_time_utc"])    # 将时间列调整至首列    cols = ["Time (Beijing)"] + [c for c in df.columns if c != "Time (Beijing)"]    df = df[cols]    # 6. 统一数据精度，保留三位小数    round_columns = {        col_rh: 3,        col_press: 3,        col_ws: 3,        col_wd: 3,    }    df = df.round(round_columns)    # 7. 精准筛选北京时间范围内的数据    start_filter = pd.to_datetime(start_date_bj)    end_filter = pd.to_datetime(end_date_bj) + pd.Timedelta(hours=23, minutes=59)    df = df[(df["Time (Beijing)"] >= start_filter) & (df["Time (Beijing)"] <= end_filter)]    # 8. 保存为 UTF-8 编码 CSV 文件    df.to_csv(output_csv, index=False, encoding="utf-8-sig")    print("气象数据下载完成，已成功保存为CSV文件！")if __name__ == "__main__":    # 可自定义修改：经纬度、起止时间、文件名称    LATITUDE = 30.6502      # 纬度（示例：成都）    LONGITUDE = 104.068     # 经度（示例：成都）    # 北京时间起止日期，格式固定 YYYY-MM-DD    START_DATE_BJ = "2026-05-01"    END_DATE_BJ = "2026-05-02"    # 自动生成文件名称    OUTPUT_FILE = f"./{START_DATE_BJ}_to_{END_DATE_BJ}_hourly_meteo.csv"    # 执行数据下载    download_meteo_data(        lat=LATITUDE,        lon=LONGITUDE,        start_date_bj=START_DATE_BJ,        end_date_bj=END_DATE_BJ,        output_csv=OUTPUT_FILE    )