From c065992fb0024a52efefcfee50080510a97f2e36 Mon Sep 17 00:00:00 2001
From: "2569718930@qq.com" <2569718930@qq.com>
Date: Sun, 8 Feb 2026 02:27:21 +0800
Subject: [PATCH] feat: implement multi-source weather data collection for
OpenWeatherMap, Visual Crossing, and NOAA METAR.
---
bot_listener.py | 74 +++++++++++++++++++-------
src/data_collection/weather_sources.py | 23 ++++++--
2 files changed, 75 insertions(+), 22 deletions(-)
diff --git a/bot_listener.py b/bot_listener.py
index 1d8fb916..bcd7bf50 100644
--- a/bot_listener.py
+++ b/bot_listener.py
@@ -13,7 +13,7 @@ from src.utils.config_loader import load_config
from src.data_collection.weather_sources import WeatherDataCollector
def analyze_weather_trend(weather_data, temp_symbol):
- """根据实测与预测分析气温态势"""
+ """根据实测与预测分析气温态势，增加峰值时刻预测"""
insights = []
metar = weather_data.get("metar", {})
@@ -23,46 +23,70 @@ def analyze_weather_trend(weather_data, temp_symbol):
return ""
curr_temp = metar.get("current", {}).get("temp")
- forecast_high = open_meteo.get("daily", {}).get("temperature_2m_max", [None])[0]
+ daily = open_meteo.get("daily", {})
+ forecast_high = daily.get("temperature_2m_max", [None])[0]
wind_speed = metar.get("current", {}).get("wind_speed_kt", 0)
# 获取当地时间小时
- local_time_str = open_meteo.get("current", {}).get("local_time", "")
+ local_time_full = open_meteo.get("current", {}).get("local_time", "")
try:
- local_hour = int(local_time_str.split(" ")[1].split(":")[0])
+ local_date_str = local_time_full.split(" ")[0] # YYYY-MM-DD
+ local_hour = int(local_time_full.split(" ")[1].split(":")[0])
except:
- local_hour = datetime.now().hour # 降级方案
+ local_date_str = datetime.now().strftime("%Y-%m-%d")
+ local_hour = datetime.now().hour
+
+ # --- 增加：峰值时刻预测逻辑 ---
+ hourly = open_meteo.get("hourly", {})
+ times = hourly.get("time", [])
+ # 优先寻找高精模型的逐小时数据
+ temps = hourly.get("temperature_2m_hrrr_conus") or hourly.get("temperature_2m_ecmwf_ifs") or hourly.get("temperature_2m", [])
+
+ peak_hours = []
+ if times and temps and forecast_high is not None:
+ for t_str, temp in zip(times, temps):
+ if t_str.startswith(local_date_str):
+ # 记录所有接近最高温的小时 (容差 0.2)
+ if abs(temp - forecast_high) <= 0.2:
+ hour = t_str.split("T")[1][:5]
+ peak_hours.append(hour)
+ if peak_hours:
+ window = f"{peak_hours[0]} - {peak_hours[-1]}" if len(peak_hours) > 1 else peak_hours[0]
+ insights.append(f"⏱️ 预计峰值时刻：今天 {window} 之间。")
+ if local_hour < int(peak_hours[0].split(":")[0]):
+ insights.append(f"🎯 博弈建议：关注该时段实测能否站稳 {forecast_high}{temp_symbol}。")
+
if curr_temp is not None and forecast_high is not None:
diff = forecast_high - curr_temp
# 1. 气温节奏判定
- if local_hour >= 16:
+ if local_hour >= 17:
if curr_temp >= forecast_high - 0.5:
- insights.append(f"✅ 今日峰值已达：当前 {curr_temp}{temp_symbol} 已触及预报最高温，后续将进入回落通道。")
+ insights.append(f"✅ 今日峰值已达：当前已触及预报最高，大概率已定格。")
else:
- insights.append(f"📉 处于降温期：气温已开始从峰值下滑，今日大概率不会再反弹。")
- elif 11 <= local_hour < 16:
- if diff > 1.5:
- insights.append(f"📈 升温进程中：距离预报最高温还有约 {diff:.1f}° 空间，午后余热尚存。")
+ insights.append(f"📉 处于降温期：气温已跌落峰值，今日反弹乏力。")
+ elif 10 <= local_hour < 17:
+ if diff > 1.2:
+ insights.append(f"📈 升温进程中：距离峰值还有约 {diff:.1f}° 空间，正向高点冲击。")
else:
- insights.append(f"⚖️ 高位横盘：气温已基本涨满，将在当前水平小幅波动，直至日落。")
+ insights.append(f"⚖️ 高位横盘：气温已在高位，将在当前水平小幅波动。")
else:
- insights.append(f"🌅 早间爬升：气温正在起步。")
+ insights.append(f"🌅 早间爬升：气温正快速起步，等待午后冲击。")
# 2. 湿度与露点带来的“粘性”分析
humidity = metar.get("current", {}).get("humidity")
dewpoint = metar.get("current", {}).get("dewpoint")
- if humidity and humidity > 80:
- insights.append(f"💦 闷热高湿：空气湿度极大 ({humidity}%)，这会像保温层一样锁住热量，导致夜间降温非常缓慢。")
+ if humidity and humidity > 80 and local_hour >= 18:
+ insights.append(f"💦 闷热高湿：湿度极高 ({humidity}%)，将显著锁住夜间热量。")
if dewpoint is not None and curr_temp - dewpoint < 2.0 and local_hour >= 18:
- insights.append(f"🌡️ 触及露点底线：气温已非常接近露点，进一步下降的空间将被强力压缩，气温将“跌不动了”。")
+ insights.append(f"🌡️ 触及露点支撑：气温已跌至露点支撑位，降温将变慢。")
- # 3. 风力带来的剧烈波动预警
+ # 3. 风力
if wind_speed >= 15:
- insights.append(f"🌬️ 大风预警 ({wind_speed}kt)：强风可能带来锋面过境，注意气温可能出现非正常的剧烈跳变。")
+ insights.append(f"🌬️ 大风预判：当前风力较大 ({wind_speed}kt)，气温可能出现非线性波动。")
elif wind_speed >= 10:
insights.append(f"🍃 清劲风：空气流动快，虽然有助于散热，但可能伴随阵风引起微小波动。")
@@ -163,10 +187,22 @@ def start_bot():
city_today_str = city_now.strftime("%Y-%m-%d")
msg_lines.append(f"\n📊 Open-Meteo 7天预测")
+ model_split = daily.get("model_split")
for i, (d, t) in enumerate(zip(dates[:7], max_temps[:7])):
day_label = "今天" if d == city_today_str else d[5:]
indicator = "👉 " if d == city_today_str else " "
- msg_lines.append(f"{indicator}{day_label}: 最高 {t}{temp_symbol}")
+
+ # 如果是今天且存在模型分歧，则特别标注
+ if d == city_today_str and model_split:
+ ecmwf = model_split.get("ecmwf")
+ hrrr = model_split.get("hrrr")
+ if ecmwf and hrrr and abs(ecmwf - hrrr) > 0.5:
+ msg_lines.append(f"{indicator}{day_label}: 最高 {t}{temp_symbol} ⚠️")
+ msg_lines.append(f" (模型分歧: ECMWF {ecmwf} | HRRR {hrrr})")
+ else:
+ msg_lines.append(f"{indicator}{day_label}: 最高 {t}{temp_symbol}")
+ else:
+ msg_lines.append(f"{indicator}{day_label}: 最高 {t}{temp_symbol}")
if metar:
icao = metar.get("icao", "")
diff --git a/src/data_collection/weather_sources.py b/src/data_collection/weather_sources.py
index 35a4b682..5b6906fc 100644
--- a/src/data_collection/weather_sources.py
+++ b/src/data_collection/weather_sources.py
@@ -343,9 +343,10 @@ class WeatherDataCollector:
"_t": int(time.time()), # 禁用缓存，强制刷新
}
- # 对于美国市场，使用华氏度
+ # 对于美国市场，使用华氏度并请求更多的模型共识
if use_fahrenheit:
params["temperature_unit"] = "fahrenheit"
+ params["models"] = "ecmwf_ifs,hrrr_conus"
response = self.session.get(
url,
@@ -360,7 +361,23 @@ class WeatherDataCollector:
utc_offset = data.get("utc_offset_seconds", 0)
timezone_name = data.get("timezone", "UTC")
- # 计算精确的当地时间而不是气象站 bucket 时间
+ # 处理多模型数据 (如果请求了 models 参数，返回结构会变化)
+ daily_data = data.get("daily", {})
+ if "temperature_2m_max_ecmwf_ifs" in daily_data:
+ # 获取首日的各模型峰值比较
+ ecmwf_max = daily_data.get("temperature_2m_max_ecmwf_ifs", [])
+ hrrr_max = daily_data.get("temperature_2m_max_hrrr_conus", [])
+
+ # 记录多模型分歧
+ daily_data["model_split"] = {
+ "ecmwf": ecmwf_max[0] if ecmwf_max else None,
+ "hrrr": hrrr_max[0] if hrrr_max else None
+ }
+ # 设置主显示值为 HRRR (当地高精)
+ if hrrr_max:
+ daily_data["temperature_2m_max"] = hrrr_max
+
+ # 计算精确的当地时间
now_utc = datetime.utcnow()
local_now = now_utc + timedelta(seconds=utc_offset)
local_time_str = local_now.strftime("%Y-%m-%d %H:%M")
@@ -375,7 +392,7 @@ class WeatherDataCollector:
"local_time": local_time_str,
},
"hourly": data.get("hourly", {}),
- "daily": data.get("daily", {}),
+ "daily": daily_data,
"unit": "fahrenheit" if use_fahrenheit else "celsius",
}
except Exception as e: