From de6a10379d67594f9aa385ce1e225c528512ad2d Mon Sep 17 00:00:00 2001 From: "2569718930@qq.com" <2569718930@qq.com> Date: Mon, 23 Feb 2026 21:23:52 +0800 Subject: [PATCH] docs: Clean up merge conflict markers and update betting strategy tips in README. --- README.md | 113 ++++++++++++++++++++++++------------------------------ 1 file changed, 51 insertions(+), 62 deletions(-) diff --git a/README.md b/README.md index 77ef27c1..cbc5d8e4 100644 --- a/README.md +++ b/README.md @@ -8,10 +8,7 @@ An intelligent weather bot for prediction markets and professional weather betti - **Python 3.11+** - Dependencies: `pip install -r requirements.txt` - <<<<<<< HEAD -- # **Environment**: Configure `METEOBLUE_API_KEY` in `.env` to enable high-precision London forecasts. - **Environment Variables**: Set `TELEGRAM_BOT_TOKEN` in `.env` (required). Optionally set `METEOBLUE_API_KEY` for London high-precision forecasts. - > > > > > > > e575440acfd8b5f1e8c30e83dfcb972d26175729 ### VPS Deployment (Recommended) @@ -69,21 +66,21 @@ py -3.11 run.py ### Supported Cities -| City | Aliases | METAR Station | Extra Sources | -| :----------- | :--------------------- | :------------------------ | :------------ | -| London | `lon`, `伦敦` | EGLC (City Airport) | Meteoblue | -| Paris | `par`, `巴黎` | LFPG (Charles de Gaulle) | — | -| Ankara | `ank`, `安卡拉` | LTAC (Esenboğa) | MGM | -| New York | `nyc`, `ny`, `纽约` | KLGA (LaGuardia) | NWS | -| Chicago | `chi`, `芝加哥` | KORD (O'Hare) | NWS | -| Dallas | `dal`, `达拉斯` | KDAL (Love Field) | NWS | -| Miami | `mia`, `迈阿密` | KMIA (International) | NWS | -| Atlanta | `atl`, `亚特兰大` | KATL (Hartsfield-Jackson) | NWS | -| Seattle | `sea`, `西雅图` | KSEA (Sea-Tac) | NWS | -| Toronto | `tor`, `多伦多` | CYYZ (Pearson) | — | -| Seoul | `sel`, `首尔` | RKSI (Incheon) | — | -| Buenos Aires | `ba`, `布宜诺斯艾利斯` | SAEZ (Ezeiza) | — | -| Wellington | `wel`, `惠灵顿` | NZWN (Wellington) | — | +| City | Aliases | METAR Station | Extra Sources | +|:---|:---|:---|:---| +| London | `lon`, `伦敦` | EGLC (City Airport) | Meteoblue | +| Paris | `par`, `巴黎` | LFPG (Charles de Gaulle) | — | +| Ankara | `ank`, `安卡拉` | LTAC (Esenboğa) | MGM | +| New York | `nyc`, `ny`, `纽约` | KLGA (LaGuardia) | NWS | +| Chicago | `chi`, `芝加哥` | KORD (O'Hare) | NWS | +| Dallas | `dal`, `达拉斯` | KDAL (Love Field) | NWS | +| Miami | `mia`, `迈阿密` | KMIA (International) | NWS | +| Atlanta | `atl`, `亚特兰大` | KATL (Hartsfield-Jackson) | NWS | +| Seattle | `sea`, `西雅图` | KSEA (Sea-Tac) | NWS | +| Toronto | `tor`, `多伦多` | CYYZ (Pearson) | — | +| Seoul | `sel`, `首尔` | RKSI (Incheon) | — | +| Buenos Aires | `ba`, `布宜诺斯艾利斯` | SAEZ (Ezeiza) | — | +| Wellington | `wel`, `惠灵顿` | NZWN (Wellington) | — | ### Example @@ -99,15 +96,15 @@ py -3.11 run.py ### 1. 🏛️ Multi-Source Data Fusion -| Source | Role | Coverage | Strength | -| :---------------------- | :---------------------- | :-------------- | :-------------------------------------------------------------------------------- | -| **Multi-Model (5 NWP)** | **Consensus Scoring** | Global | ECMWF, GFS, ICON, GEM, JMA — 5 fully independent NWP models via Open-Meteo | +| Source | Role | Coverage | Strength | +| :---------------------- | :---------------------- | :-------------- | :-------------------------------------------------------------------------- | +| **Multi-Model (5 NWP)** | **Consensus Scoring** | Global | ECMWF, GFS, ICON, GEM, JMA — 5 fully independent NWP models via Open-Meteo | | **Open-Meteo** | Base Forecast | Global | 72h hourly curves, sunrise/sunset, **sunshine duration**, **shortwave radiation** | -| **Open-Meteo Ensemble** | **Uncertainty Range** | Global | 51-member ensemble: median, P10, P90 spread for confidence assessment | -| **Meteoblue (MB)** | Precision Consensus | London Only | Multi-model aggregation; excellent for microclimates | -| **METAR** | **Settlement Standard** | Global Airports | Polymarket settlement source; real-time airport observations | -| **NWS** | Official (US) | US Only | US National Weather Service high-fidelity forecasts | -| **MGM** | Observations (Turkey) | Ankara Only | Turkish State Met Service: pressure, cloud cover, feels-like, 24h rainfall | +| **Open-Meteo Ensemble** | **Uncertainty Range** | Global | 51-member ensemble: median, P10, P90 spread for confidence assessment | +| **Meteoblue (MB)** | Precision Consensus | London Only | Multi-model aggregation; excellent for microclimates | +| **METAR** | **Settlement Standard** | Global Airports | Polymarket settlement source; real-time airport observations | +| **NWS** | Official (US) | US Only | US National Weather Service high-fidelity forecasts | +| **MGM** | Observations (Turkey) | Ankara Only | Turkish State Met Service: pressure, cloud cover, feels-like, 24h rainfall | > ⚠️ **All NWP model queries use airport coordinates** (matching METAR station), not city center. This eliminates systematic bias between forecast and settlement locations. @@ -151,11 +148,11 @@ py -3.11 run.py The bot queries **5 independent NWP models** (ECMWF, GFS, ICON, GEM, JMA) to rate forecast agreement: -| Level | Condition (°C / °F) | Meaning | -| :------------ | :--------------------- | :------------------------------------------------------ | -| 🎯 **High** | Spread ≤ 0.8°C / 1.5°F | All 5 models converge — high confidence, low risk | -| ⚖️ **Medium** | Spread ≤ 1.5°C / 3.0°F | Minor disagreement — moderate confidence | -| ⚠️ **Low** | Spread > 1.5°C / 3.0°F | Major divergence — high uncertainty, wait for more data | +| Level | Condition (°C / °F) | Meaning | +|:---|:---|:---| +| 🎯 **High** | Spread ≤ 0.8°C / 1.5°F | All 5 models converge — high confidence, low risk | +| ⚖️ **Medium** | Spread ≤ 1.5°C / 3.0°F | Minor disagreement — moderate confidence | +| ⚠️ **Low** | Spread > 1.5°C / 3.0°F | Major divergence — high uncertainty, wait for more data | Primary models: **ECMWF IFS** (Europe), **GFS** (US NOAA), **ICON** (Germany DWD), **GEM** (Canada), **JMA** (Japan). Plus Meteoblue (London) and NWS (US) when available. Ensemble median is excluded to avoid double-counting. @@ -173,22 +170,22 @@ A tight range = high confidence in the forecast. A wide range = the atmosphere i A composite score combining three factors to advise on betting timing: -| Factor | Score | -| :------------------------------------ | :---- | -| Peak already passed | +3 | -| ≤ 2h to peak | +2 | -| ≤ 4h to peak | +1 | -| Model consensus: High | +2 | -| Model consensus: Medium | +1 | -| Actual ≈ Forecast (gap ≤ 0.5°) | +2 | -| Actual close to Forecast (gap ≤ 1.5°) | +1 | +| Factor | Score | +|:---|:---| +| Peak already passed | +3 | +| ≤ 2h to peak | +2 | +| ≤ 4h to peak | +1 | +| Model consensus: High | +2 | +| Model consensus: Medium | +1 | +| Actual ≈ Forecast (gap ≤ 0.5°) | +2 | +| Actual close to Forecast (gap ≤ 1.5°) | +1 | -| Total ≥ | Signal | Advice | -| :------ | :--------------------- | :---------------------------- | -| 5 | ⏰ **Ideal** | Low uncertainty — good to bet | -| 3 | ⏰ **Good** | Consider small positions | -| 2 | ⏰ **Cautious** | Keep observing | -| <2 | ⏰ **Not Recommended** | High uncertainty — wait | +| Total ≥ | Signal | Advice | +|:---|:---|:---| +| 5 | ⏰ **Ideal** | Low uncertainty — good to bet | +| 3 | ⏰ **Good** | Consider small positions | +| 2 | ⏰ **Cautious** | Keep observing | +| <2 | ⏰ **Not Recommended** | High uncertainty — wait | ### 6. 🧠 Smart Trend Analysis (Plain Language) @@ -253,23 +250,15 @@ graph TD ## 🎯 Betting Strategy Tips -<<<<<<< HEAD - -1. **Check Consensus**: Compare Open-Meteo and Meteoblue (MB). Consensus usually implies higher probability. -2. **Watch the Peak**: Use `/city` frequently during predicted peak windows to catch momentum. -3. **Weighting Hierarchy**: Settlement is **METAR**; high-accuracy trend is **MB** (London); Official (NWS/MGM) is the "anchor." -4. # **Geographic Risk**: Pay close attention to cities where "Bias will significantly amplify." -5. **Check Model Consensus**: The 🎯/⚖️/⚠️ rating tells you immediately if the forecast is reliable. -6. **Use the Entry Signal**: Wait for ⏰ **Ideal** or **Good** timing before placing bets. Don't bet early when uncertainty is high. -7. **Watch Ensemble Spread**: A tight 90% band (< 2°) means model confidence is high — this is where edges live. -8. **Watch the Peak Window**: Use `/city` frequently during predicted peak hours. -9. **Settlement Priority**: Settlement is always based on **METAR** data, rounded to integer via Wunderground. -10. **Geographic Risk**: Pay attention to bias warnings, especially for high-risk cities like Seoul and Chicago. -11. **Solar Radiation Clues**: If the bot reports "warm advection driven" 🌙, the temperature was pushed by warm air, not sunlight — this pattern often breaks model predictions. -12. **Wind Conflicts**: When METAR and MGM show opposite wind directions, expect temperature volatility. +1. **Check Model Consensus**: The 🎯/⚖️/⚠️ rating tells you immediately if the forecast is reliable. +2. **Use the Entry Signal**: Wait for ⏰ **Ideal** or **Good** timing before placing bets. Don't bet early when uncertainty is high. +3. **Watch Ensemble Spread**: A tight 90% band (< 2°) means model confidence is high — this is where edges live. +4. **Watch the Peak Window**: Use `/city` frequently during predicted peak hours. +5. **Settlement Priority**: Settlement is always based on **METAR** data, rounded to integer via Wunderground. +6. **Geographic Risk**: Pay attention to bias warnings, especially for high-risk cities like Seoul and Chicago. +7. **Solar Radiation Clues**: If the bot reports "warm advection driven" 🌙, the temperature was pushed by warm air, not sunlight — this pattern often breaks model predictions. +8. **Wind Conflicts**: When METAR and MGM show opposite wind directions, expect temperature volatility. --- _Last updated: 2026-02-22_ - -> > > > > > > e575440acfd8b5f1e8c30e83dfcb972d26175729