From dc41e8b2fa1bf1583d8878325d54f8fb8f15be40 Mon Sep 17 00:00:00 2001
From: "2569718930@qq.com" <2569718930@qq.com>
Date: Mon, 9 Feb 2026 09:46:31 +0800
Subject: [PATCH] Update bot listener functionality.
---
bot_listener.py | 125 ++++++++++++++++++++++++++++++++----------------
1 file changed, 83 insertions(+), 42 deletions(-)
diff --git a/bot_listener.py b/bot_listener.py
index 3ba8f9ea..5ab5ff01 100644
--- a/bot_listener.py
+++ b/bot_listener.py
@@ -19,6 +19,9 @@ def analyze_weather_trend(weather_data, temp_symbol):
metar = weather_data.get("metar", {})
open_meteo = weather_data.get("open-meteo", {})
+ mb = weather_data.get("meteoblue", {})
+ nws = weather_data.get("nws", {})
+ mgm = weather_data.get("mgm", {})
if not metar or not open_meteo:
return ""
@@ -26,7 +29,22 @@ def analyze_weather_trend(weather_data, temp_symbol):
curr_temp = metar.get("current", {}).get("temp")
max_so_far = metar.get("current", {}).get("max_temp_so_far") # 今日实测最高
daily = open_meteo.get("daily", {})
- forecast_high = daily.get("temperature_2m_max", [None])[0]
+
+ # === 核心：整合多源预报最高温 ===
+ forecast_highs = [daily.get("temperature_2m_max", [None])[0]]
+ if mb.get("today_high") is not None:
+ forecast_highs.append(mb["today_high"])
+ if nws.get("today_high") is not None:
+ forecast_highs.append(nws["today_high"])
+ if mgm.get("today_high") is not None:
+ forecast_highs.append(mgm["today_high"])
+
+ forecast_highs = [h for h in forecast_highs if h is not None]
+ # 取预报中的最高值作为风险防御基准
+ forecast_high = max(forecast_highs) if forecast_highs else None
+ # 取最低值用于判断是否“已触及预报高位”
+ min_forecast_high = min(forecast_highs) if forecast_highs else forecast_high
+
wind_speed = metar.get("current", {}).get("wind_speed_kt", 0)
# 获取当地时间小时
@@ -41,37 +59,36 @@ def analyze_weather_trend(weather_data, temp_symbol):
# === 核心判断：实测是否已超预报 ===
if max_so_far is not None and forecast_high is not None:
if max_so_far > forecast_high + 0.5:
- # 实测已超预报！
+ # 实测已超所有预报！
exceed_by = max_so_far - forecast_high
- insights.append(f"🚨 预报已被击穿：实测最高 {max_so_far}{temp_symbol} 已超预报 {forecast_high}{temp_symbol} 约 {exceed_by:.1f}°！")
- insights.append(f"💡 博弈建议：市场需重新评估，关注更高温度区间。")
- # 直接返回，不再显示过时的建议
- if wind_speed >= 10:
- insights.append(f"🍃 清劲风：空气流动快，可能伴随阵风引起微小波动。")
+ insights.append(f"🚨 预报已被击穿：实测最高 {max_so_far}{temp_symbol} 已超所有预报上限 {forecast_high}{temp_symbol} 约 {exceed_by:.1f}°！")
+ insights.append(f"💡 博弈建议：市场需重新评估，当前可能存在极端异常增温。")
return "\n💡 态势分析\n" + "\n".join(insights)
- # --- 峰值时刻预测逻辑 ---
+ # --- 峰值时刻预测逻辑 (仍以 Open-Meteo 逐小时数据为准) ---
hourly = open_meteo.get("hourly", {})
times = hourly.get("time", [])
temps = hourly.get("temperature_2m", [])
peak_hours = []
- if times and temps and forecast_high is not None:
+ om_high = daily.get("temperature_2m_max", [None])[0]
+ if times and temps and om_high is not None:
for t_str, temp in zip(times, temps):
if t_str.startswith(local_date_str):
- if abs(temp - forecast_high) <= 0.2:
+ if abs(temp - om_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。")
- # 只有在实测还没超预报时才给这个建议
+ # 只有在还没进入峰值时段且还没达到预报高点时才给这个建议
if local_hour < int(peak_hours[0].split(":")[0]) and (max_so_far is None or max_so_far < forecast_high):
insights.append(f"🎯 博弈建议：关注该时段实测能否站稳 {forecast_high}{temp_symbol}。")
+ is_peak_passed = False
if curr_temp is not None and forecast_high is not None:
- diff = forecast_high - curr_temp
+ diff_max = forecast_high - curr_temp
# 1. 气温节奏判定 (动态参考峰值时刻)
last_peak_h = int(peak_hours[-1].split(":")[0]) if peak_hours else 15
@@ -79,19 +96,22 @@ def analyze_weather_trend(weather_data, temp_symbol):
if local_hour > last_peak_h:
# 已经过了预报的峰值时段
- if curr_temp >= forecast_high - 0.5 or (max_so_far and max_so_far >= forecast_high - 0.5):
+ is_peak_passed = True
+ # 如果实测已经接近“任一”主流预报的最高温 (使用 min_forecast_high)
+ if max_so_far and max_so_far >= min_forecast_high - 0.5:
insights.append(f"✅ 今日峰值已过：气温已触及或接近预报最高，目前处于高位波动或缓慢回落。")
else:
- insights.append(f"📉 处于降温期：已过预报峰值时段，且当前气温乏力，冲击高点概率降低。")
+ # 虽然时间过了，但离最高温还有差距
+ insights.append(f"📉 处于降温期：已过预报峰值时段，且当前气温乏力 ({curr_temp}{temp_symbol})，冲击最高预报 {forecast_high}{temp_symbol} 的概率降低。")
elif first_peak_h <= local_hour <= last_peak_h:
# 正在峰值窗口内
- if diff <= 0.8:
+ if diff_max <= 0.8:
insights.append(f"⚖️ 高位横盘：正处于预测峰值时段，气温将在当前水平小幅波动。")
else:
insights.append(f"⏳ 峰值窗口中：虽在预报高点时段，但目前仍有差距，紧盯最后冲刺。")
elif local_hour < first_peak_h:
# 还没到峰值窗口
- if diff > 1.2:
+ if diff_max > 1.2:
insights.append(f"📈 升温进程中：距离峰值时段还有 {first_peak_h - local_hour}h，正向高点冲击。")
else:
insights.append(f"🌅 临近峰值：即将进入高点时段，气温已处于预报高位。")
@@ -99,56 +119,61 @@ def analyze_weather_trend(weather_data, temp_symbol):
# 回退逻辑
insights.append(f"🌌 夜间/早间：等待日出后的新一轮波动。")
- # 2. 湿度与露点带来的“粘性”分析
+ # 2. 湿度与露点分析 (仅在傍晚以后)
humidity = metar.get("current", {}).get("humidity")
dewpoint = metar.get("current", {}).get("dewpoint")
- 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"🌡️ 触及露点支撑：气温已跌至露点支撑位，降温将变慢。")
+ if local_hour >= 18:
+ if humidity and humidity > 80:
+ 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:
+ 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
if wind_speed >= 15:
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。")
+ insights.append(f"🍃 清劲风：空气流动快，虽然有助于散热，但在升温期可能带来暖平流加速。")
# 4. 云层遮挡分析 (仅在升温期/峰值期有意义)
clouds = metar.get("current", {}).get("clouds", [])
if clouds and local_hour <= last_peak_h + 1:
- # 取覆盖范围最大的云层
- main_cloud = clouds[-1] # METAR 通常按高度由低到高排列，最后一层往往代表主要云量
+ main_cloud = clouds[-1]
cover = main_cloud.get("cover", "")
-
if cover == "OVC":
- insights.append(f"☁️ 全阴锁温：机场上空完全遮挡，阳光增温几乎停滞，很难冲破预报高点。")
+ insights.append(f"☁️ 全阴锁温：机场上空完全遮挡，阳光增温几乎停滞，很难再冲高点。")
elif cover == "BKN":
- insights.append(f"🌥️ 云层显著：天空大部被遮挡，日照受限，升温速率将明显放缓。")
+ insights.append(f"🌥️ 云层显著：天空大部被遮挡，日照受限，升温斜率受阻。")
elif cover in ["SKC", "CLR", "FEW"]:
- insights.append(f"☀️ 晴空万里：日照强烈，无云层遮挡，气温有冲向预报上限甚至超出的动能。")
+ if not is_peak_passed:
+ insights.append(f"☀️ 晴空万里：日照强烈，无云层遮挡，气温有冲向预报上限甚至超出的动能。")
- # 5. 特殊天气现象分析
+ # 5. 特殊天气现象
wx_desc = metar.get("current", {}).get("wx_desc")
if wx_desc:
if any(x in wx_desc.upper() for x in ["RA", "DZ", "RAIN", "DRIZZLE"]):
- insights.append(f"🌧️ 降雨压制：当前有降雨，蒸发吸热将显著拉低实时气温。")
+ insights.append(f"🌧️ 降雨压制：当前有降雨，蒸发吸热将显著抑制升温。")
elif any(x in wx_desc.upper() for x in ["SN", "SNOW", "GR", "GS"]):
- insights.append(f"❄️ 固态降水：正在降雪或冰雹，气温将由于相变吸热而持续低迷。")
+ insights.append(f"❄️ 固态降水：正在降雪或冰雹，气温将持续低迷。")
elif any(x in wx_desc.upper() for x in ["FG", "BR", "HZ", "FOG", "MIST"]):
insights.append(f"🌫️ 能见度受限：当前有雾/霭，阻挡阳光并带来高湿，会大幅延缓升温周期。")
- # 6. 风向与能见度
- try:
- wind_dir = float(metar.get("current", {}).get("wind_dir", 0))
- # 北半球简化逻辑：北风冷，南风暖
- if 315 <= wind_dir or wind_dir <= 45:
- insights.append(f"🌬️ 偏北风：冷空气处于主导地位，午后增温阻力较大。")
- elif 135 <= wind_dir <= 225:
- insights.append(f"🔥 偏南风：正从低纬度输送暖湿气流，气温有超预期上涨的潜力。")
- except (TypeError, ValueError):
- pass
+ # 6. 风向平流分析 (仅在未进入降温期前显示)
+ if not is_peak_passed or local_hour <= last_peak_h + 2:
+ try:
+ wind_dir = float(metar.get("current", {}).get("wind_dir", 0))
+ # 北半球简化逻辑：北风 cold，南风 warm
+ if 315 <= wind_dir or wind_dir <= 45:
+ insights.append(f"🌬️ 偏北风：冷空气处于主导地位，午后增温阻力较大。")
+ elif 135 <= wind_dir <= 225:
+ # 只有在当前温度离最高预测还有距离时，南风才有意义
+ if diff_max > 0.5:
+ if is_peak_passed:
+ insights.append(f"🔥 偏南风：存在暖平流支撑，但已过传统峰值时段，冲击上限 {forecast_high}{temp_symbol} 的动能正在衰减。")
+ else:
+ insights.append(f"🔥 偏南风：正从低纬度输送暖平流，气温仍有向上突围的潜力。")
+ except (TypeError, ValueError):
+ pass
try:
visibility = metar.get("current", {}).get("visibility_mi")
@@ -159,6 +184,22 @@ def analyze_weather_trend(weather_data, temp_symbol):
except (TypeError, ValueError):
pass
+ # 7. 模型准确度预警 (针对用户反馈的 MB 偏高问题)
+ if is_peak_passed and max_so_far is not None:
+ model_checks = []
+ if om_high and om_high > max_so_far + 1.5:
+ model_checks.append(f"Open-Meteo ({om_high}{temp_symbol})")
+ mb_h = mb.get("today_high")
+ if mb_h and mb_h > max_so_far + 1.5:
+ model_checks.append(f"Meteoblue ({mb_h}{temp_symbol})")
+ nws_h = nws.get("today_high")
+ if nws_h and nws_h > max_so_far + 1.5:
+ model_checks.append(f"NWS ({nws_h}{temp_symbol})")
+
+ if model_checks:
+ insights.append(f"⚠️ 预报偏高：目前实测远低于 " + "、".join(model_checks) + "，判定预报模型今日表现过度乐观。")
+
+
if not insights:
return ""