From 22a578f98fd3047b3a0dc5a0e2e9942dab31eea9 Mon Sep 17 00:00:00 2001 From: AmandaloveYang <2569718930@qq.com> Date: Sat, 14 Feb 2026 13:48:35 +0800 Subject: [PATCH] feat: plain language analysis + sunrise sunset + MGM pressure cloud data --- bot_listener.py | 100 +++++++++++++++++-------- src/data_collection/weather_sources.py | 5 +- 2 files changed, 72 insertions(+), 33 deletions(-) diff --git a/bot_listener.py b/bot_listener.py index a3453274..f9bf47f2 100644 --- a/bot_listener.py +++ b/bot_listener.py @@ -62,8 +62,8 @@ def analyze_weather_trend(weather_data, temp_symbol): if max_so_far > forecast_high + 0.5: is_breakthrough = True 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} 已超所有预报上限 {forecast_high}{temp_symbol} 约 {exceed_by:.1f}°！") - insights.append(f"💡 建议：市场需重新评估，当前可能存在物理层面的超预期增温。") + insights.append(f"🚨 实测已超预报：实测最高 {max_so_far}{temp_symbol} 超过了所有预报的天花板 {forecast_high}{temp_symbol}，多了 {exceed_by:.1f}°！") + insights.append(f"💡 建议：预报已经不准了，实际温度比所有模型预测的都高，需要重新判断。") # --- 峰值时刻预测逻辑 (仍以 Open-Meteo 逐小时数据为准) --- hourly = open_meteo.get("hourly", {}) @@ -81,10 +81,10 @@ def analyze_weather_trend(weather_data, temp_symbol): 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。") + insights.append(f"⏱️ 预计最热时段：今天 {window}。") # 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}。") + insights.append(f"🎯 关注重点：看看那个时段温度能不能真的到 {forecast_high}{temp_symbol}。") is_peak_passed = False if curr_temp is not None and forecast_high is not None: @@ -98,30 +98,30 @@ def analyze_weather_trend(weather_data, temp_symbol): # 已经过了预报的峰值时段 is_peak_passed = True if is_breakthrough: - insights.append(f"🌡️ 超常规表现：虽然时间已过预报峰值，但气温击穿上限后仍维持在高位，需警惕降温推迟。") - # 如果实测已经接近“任一”主流预报的最高温 (使用 min_forecast_high) + insights.append(f"🌡️ 异常高温：最热的时间已经过了，但温度还是比预报高，降温可能会来得比较晚。") + # 如果实测已经接近"任一"主流预报的最高温 (使用 min_forecast_high) elif 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。") + insights.append(f"✅ 今天最热已过：温度已经到了预报最高值附近，接下来会慢慢降温了。") else: # 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。") + insights.append(f"📉 开始降温：最热时段已过，现在 {curr_temp}{temp_symbol}，看起来很难再涨到预报的 {forecast_high}{temp_symbol} 了。") elif first_peak_h <= local_hour <= last_peak_h: # 正在峰值窗口内 if is_breakthrough: - insights.append(f"🔥 狂暴拉升：正处于预测峰值时段，实测正以前所未有的态势压制所有预报，上限已失守。") + insights.append(f"🔥 极端升温：正处于最热时段，温度已经超过所有预报，还在继续往上走！") elif 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。") + insights.append(f"⚖️ 到顶了：正处于最热时段，温度基本到位，接下来会在这个水平上下浮动。") 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。") + insights.append(f"⏳ 最热时段进行中：虽然在最热时段了，但离预报最高温还差一些，继续观察。") elif local_hour < first_peak_h: # 还没到峰值窗口 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。") + insights.append(f"📈 还在升温：离最热时段还有 {first_peak_h - local_hour} 小时，温度还会继续往上走。") 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。") + insights.append(f"🌅 快到最热了：马上就要进入最热时段，温度已经接近预报高位了。") else: # 回退逻辑 - insights.append(f"🌌 夜间/早间：等待日出后的新一轮波动。") + insights.append(f"🌌 夜间：等明天太阳出来后再看新一轮升温。") # 2. 湿度与露点分析 (仅在傍晚以后) humidity = metar.get("current", {}).get("humidity") @@ -129,15 +129,15 @@ def analyze_weather_trend(weather_data, temp_symbol): 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。") + insights.append(f"💦 湿度很高：湿度 {humidity}%，空气很潮湿，夜里热量散不掉，降温会很慢。") 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。") + insights.append(f"🌡️ 降温快到底了：温度已经接近露点（空气中水汽开始凝结的温度），再往下降会很困难。") # 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。") + insights.append(f"🌬️ 风很大：风速 {wind_speed}kt，温度可能会忽高忽低。") elif wind_speed >= 10: - 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。") + insights.append(f"🍃 有风：风速适中，白天可能会把远处的暖空气吹过来，帮助升温。") # 4. 云层遮挡分析 (仅在升温期/峰值期有意义) clouds = metar.get("current", {}).get("clouds", []) @@ -145,38 +145,38 @@ def analyze_weather_trend(weather_data, temp_symbol): 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，很难再冲高点。") + insights.append(f"☁️ 阴天：天完全被云盖住了，太阳照不进来，温度很难再往上涨了。") elif cover == "BKN": - insights.append(f"🌥️ 云层显著：天空大部被遮挡，日照受限，升温斜率受阻。") + insights.append(f"🌥️ 云比较多：天空大部分被云挡住了，日照不足，升温会比较慢。") elif cover in ["SKC", "CLR", "FEW"]: 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。") + insights.append(f"☀️ 大晴天：阳光直射，没什么云，有利于温度继续往上冲。") # 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，蒸发吸热将显著抑制升温。") + insights.append(f"🌧️ 在下雨：雨水蒸发会吸收热量，温度很难涨上去。") 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，气温将持续低迷。") + insights.append(f"❄️ 在下雪/冰雹：温度会一直低迷。") 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。") + insights.append(f"🌫️ 有雾/霾：阳光被挡住了，湿度也高，升温会很慢。") - # 6. 风向平流分析 (仅在未进入降温期前显示) + # 6. 风向分析 (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。") + insights.append(f"🌬️ 吹北风：从北方来的冷空气，会压制升温。") elif 135 <= wind_dir <= 225: # 只有在当前温度离最高预测还有距离时，或者已经击穿但还在上升时，南风才有意义 if diff_max > 0.5 or (is_breakthrough and curr_temp >= max_so_far): if is_peak_passed and not is_breakthrough: - 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。") + insights.append(f"🔥 吹南风：南方的暖空气还在吹过来，但最热时段已过，后劲不足了。") else: - status = "气温仍有向上突围的潜力" if not is_breakthrough else "可能推高击穿后的极端高位" - insights.append(f"🔥 偏南风：正从低纬度输送暖平流，{status}。") + status = "温度还有继续上涨的空间" if not is_breakthrough else "可能把温度推得更高" + insights.append(f"🔥 吹南风：南方的暖空气正在吹过来，{status}。") except (TypeError, ValueError): pass @@ -185,11 +185,11 @@ def analyze_weather_trend(weather_data, temp_symbol): if visibility is not None: vis_val = float(str(visibility).replace("+", "").replace("-", "")) if vis_val < 3 and local_hour <= 11: - insights.append(f"🌫️ 早晨低见度：能见度极差 ({vis_val}mi)，阳光无法打透，早间升温将非常缓慢。") + insights.append(f"🌫️ 早上能见度差：只能看到 {vis_val} 英里远，阳光穿不透，上午升温会很慢。") except (TypeError, ValueError): pass - # 7. 模型准确度预警 (针对用户反馈的 MB 偏高问题) + # 7. 模型准确度预警 if is_peak_passed and max_so_far is not None: model_checks = [] if om_high and om_high > max_so_far + 1.5: @@ -202,7 +202,19 @@ def analyze_weather_trend(weather_data, temp_symbol): 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。") + insights.append(f"⚠️ 预报偏高了：实测远低于 " + "、".join(model_checks) + "，这些预报今天报高了。") + + # 8. MGM 气压分析 (仅安卡拉) + mgm_pressure = mgm.get("current", {}).get("pressure") + if mgm_pressure is not None and not is_peak_passed: + if mgm_pressure < 900: + insights.append(f"📉 气压偏低：{mgm_pressure}hPa，可能有暖湿气流过境，有利于温度上升。") + + # 9. MGM 官方最高温交叉验证 + mgm_max = mgm.get("current", {}).get("mgm_max_temp") + if mgm_max is not None and max_so_far is not None: + if abs(mgm_max - max_so_far) > 1.5: + insights.append(f"📊 数据差异：MGM 官方记录最高 {mgm_max}{temp_symbol}，METAR 记录 {max_so_far}{temp_symbol}，相差 {abs(mgm_max - max_so_far):.1f}°。") if not insights: @@ -365,6 +377,14 @@ def start_bot(): future_forecasts.append(f"{d[5:]}: {t}{temp_symbol}") msg_lines.append("📅 " + " | ".join(future_forecasts)) + # --- 3.5 日出日落 --- + sunrises = daily.get("sunrise", []) + sunsets = daily.get("sunset", []) + if sunrises and sunsets: + sunrise_t = sunrises[0].split("T")[1][:5] if "T" in str(sunrises[0]) else sunrises[0] + sunset_t = sunsets[0].split("T")[1][:5] if "T" in str(sunsets[0]) else sunsets[0] + msg_lines.append(f"🌅 日出 {sunrise_t} | 🌇 日落 {sunset_t}") + # --- 4. 核心 实测区 (合并 METAR 和 MGM) --- # 基础数据优先用 METAR cur_temp = metar.get("current", {}).get("temp") if metar else mgm.get("current", {}).get("temp") @@ -412,6 +432,22 @@ def start_bot(): msg_lines.append(f" [MGM] 🌡️ 体感: {m_c.get('feels_like')}°C | 💧 {m_c.get('humidity')}%") msg_lines.append(f" [MGM] 🌬️ {dir_str}{wind_dir}° ({m_c.get('wind_speed_ms')} m/s) | 🌧️ {m_c.get('rain_24h') or 0}mm") + + # 新增：气压和云量 + extra_parts = [] + pressure = m_c.get("pressure") + if pressure is not None: + extra_parts.append(f"🌡 气压: {pressure}hPa") + cloud_cover = m_c.get("cloud_cover") + if cloud_cover is not None: + cloud_desc_map = {0: "晴朗", 1: "少云", 2: "少云", 3: "散云", 4: "散云", 5: "多云", 6: "多云", 7: "很多云", 8: "阴天"} + cloud_text = cloud_desc_map.get(cloud_cover, f"{cloud_cover}/8") + extra_parts.append(f"☁️ 云量: {cloud_text}({cloud_cover}/8)") + mgm_max = m_c.get("mgm_max_temp") + if mgm_max is not None: + extra_parts.append(f"🌡️ MGM最高: {mgm_max}°C") + if extra_parts: + msg_lines.append(f" [MGM] {' | '.join(extra_parts)}") if metar: m_c = metar.get("current", {}) diff --git a/src/data_collection/weather_sources.py b/src/data_collection/weather_sources.py index 1453355d..bc6278fe 100644 --- a/src/data_collection/weather_sources.py +++ b/src/data_collection/weather_sources.py @@ -356,6 +356,9 @@ class WeatherDataCollector: "wind_speed_kt": round(ruz_hiz_kmh / 1.852, 1) if ruz_hiz_kmh is not None else None, "wind_dir": latest.get("ruzgarYon"), "rain_24h": latest.get("toplamYagis"), + "pressure": latest.get("aktuelBasinc"), + "cloud_cover": latest.get("kapalilik"), # 0-8 八分位云量 + "mgm_max_temp": latest.get("maxSicaklik"), # MGM 官方实测最高温 "time": latest.get("veriZamani"), # 观测时间 "station_name": latest.get("istasyonAd") or latest.get("adi") or latest.get("merkezAd") or "Ankara Esenboğa" } @@ -446,7 +449,7 @@ class WeatherDataCollector: "longitude": lon, "current_weather": "true", "hourly": "temperature_2m", - "daily": "temperature_2m_max,apparent_temperature_max", + "daily": "temperature_2m_max,apparent_temperature_max,sunrise,sunset", "timezone": "auto", "forecast_days": forecast_days, "_t": int(time.time()), # 禁用缓存，强制刷新