Tools chosen: kalshi_direct kalshi_related polymarket_related claude_news code_execution

Sub-questions (Fermi decomposition)

Planner reasoning

This is a long-horizon climate question resolving on annual global mean surface temperature anomaly exceeding +2.0°C vs 1850-1900 baseline in any year before 2050. Key drivers are the current warming trend, recent record years (2023/2024 already near/above 1.5°C), and climate model projections. The Kalshi market price is the primary anchor; scientific data on warming rate informs the base rate.

# Current state The question resolves YES if any single calendar year before 2050 records a global mean surface temperature anomaly ≥ +2.0°C above the 1850–1900 pre-industrial baseline. Current anomaly stands at ~1.47–1.60°C (2024–2025), leaving a ~0.40–0.53°C gap to the threshold. # Timeline of key events - **2024**: First calendar year to exceed +1.5°C above pre-industrial (~1.60°C, Copernicus/Berkeley Earth) — confirmed - **2023–2025**: First 3-year period averaging >1.5°C above pre-industrial — confirmed (Copernicus) - **2025**: Global anomaly ~1.47°C (Copernicus), third-warmest year on record — confirmed - **2025 (IGCC)**: Human-induced warming rate at all-time high of ~0.27°C/decade (2016–2025) — confirmed - **IPCC AR6**: Under high-emissions scenarios, CMIP6 median 2°C exceedance year ~2043 (range 2034–2052) — confirmed - **Stanford AI study**: 50% chance 2°C breached even under net-zero-by-2050s scenario — reported --- # Event Will the world record a single calendar year ≥ +2.0°C above pre-industrial levels before January 1, 2050? # Outcomes to forecast - **Yes**: At least one calendar year before 2050 logs ≥ +2.0°C anomaly - **No**: No calendar year before 2050 reaches +2.0°C # Kalshi market anchor **Current YES price: 75.00%** - 7-day change: flat (0%) - 30-day change: −5% (from ~80%) - Range over 68 days: 74–83% - Volume: ~52 contracts/day (thin market) # Sub-question answers 1. **Most recent annual anomaly?** — 2024: +1.60°C (Copernicus/Berkeley Earth); 2025: +1.47°C (Copernicus). Gap to 2.0°C threshold: ~0.40–0.53°C. 2. **Current warming rate and linear extrapolation?** — NOAA: ~0.20°C/decade since 1975; IGCC 2025: human-induced rate ~0.27°C/decade (2016–2025). At 0.20°C/decade from 1.48°C baseline, deterministic crossover hits exactly ~2050; at 0.27°C/decade, crossover is ~2043. 3. **IPCC/model probability of single year >2°C before 2050?** — CMIP6 high-emissions median exceedance year ~2043 (range 2034–2052); under flat emissions, median ~2052. IPCC AR6 defines GWLs via 20-year averages, not single years — single-year exceedance happens earlier than sustained average crossing. 4. **Interannual variability / El Niño effect?** — Observed σ ≈ 0.10–0.20°C year-to-year. Strong El Niño years push ~0.1–0.2°C above trend (e.g., 2024 spike). Monte Carlo with σ=0.15 gives 96% cumulative probability; σ=0.10 gives 87%. 5. **Kalshi price and trend?** — 75% YES, down ~5% over 30 days, flat over 7 days. Thin volume limits signal reliability. # Key facts (high-confidence, factual) 1. [Copernicus/ECMWF] 2024 = +1.60°C above 1850–1900 baseline, warmest year on record 2. [Copernicus] 2025 = +1.47°C, third-warmest on record 3. [NOAA] Warming trend: ~0.20°C/decade since 1975 4. [IGCC 2025/Copernicus] Human-induced warming rate: ~0.27°C/decade (2016–2025) 5. [Carbon Brief/CMIP6] High-emissions median 2°C exceedance: ~2043; range 2034–2052 6. [Monte Carlo, code_execution] At 0.20°C/decade + σ=0.15: P(any year ≥2°C before 2050) ≈ 96%; range 87–99% across σ assumptions 7. [Stanford AI study] 50% chance of >2°C even under rapid decarbonization scenario # Cross-market signals - **Kalshi related**: EU 2030 climate goals: 41% (declining); India 2030 climate goals: 66%; US 2025 climate goals: 6.5% — consistent with pessimism about mitigation - **Polymarket**: No directly relevant markets found - **Sportsbook implied**: N/A # Analyst opinions and speculation - IPCC AR6: 2°C long-term average unlikely before 2050 under most scenarios, but single-year exceedance is an easier bar - Stanford AI: Even aggressive mitigation leaves 50% chance of 2°C breach at some point this century; 2-in-3 chance of 2.1°C peak - Key definitional nuance: this market resolves on a single calendar year, not a 20-year average — single-year threshold is crossed earlier than sustained warming # Directional lean per outcome - **Yes (≥2°C before 2050)**: Strong support — current trend (0.20–0.27°C/decade) points to crossover ~2043–2050; interannual variability (El Niño) can push a year over threshold even before trend reaches it; 25-year window provides many "shots"; Monte Carlo central estimate 87–99%; mitigation scenarios show limited near-term emissions reductions - **No**: Supporting evidence — 0.40–0.53°C gap is still substantial; aggressive policy action could slow trend; IPCC 20-year average 2°C unlikely before 2050; recent 30-day price drop from 80%→75% may reflect updated expectations # Gaps / unknowns - Future emissions trajectory (biggest uncertainty; trend rate is the key lever) - El Niño/La Niña timing in 2030s–2040s - Carbon-cycle feedbacks (permafrost, ocean absorption changes) - Whether aerosol reductions accelerate warming further - Resolution ambiguity: which dataset/agency triggers resolution? # Calibration anchors - **Kalshi current YES price: 75%** (primary anchor, thin volume, recently declining) - Monte Carlo at assumed 0.20°C/decade: ~87–99% — notably higher than Kalshi - CMIP6 high-emissions median exceedance ~2043 supports high probability - Gap between Monte Carlo (~90%+) and Kalshi (75%) may reflect model overconfidence in constant trend, or market pricing in meaningful mitigation probability - Reasonable calibrated estimate: **80–88%** YES, acknowledging some probability of faster-than-expected decarbonization bending the curve

1. Both forecasters treat the 0.20–0.27°C/decade warming rate as though it will persist linearly, but neither adequately weights the possibility that aerosol reduction (as fossil fuels decline) could *accelerate* near-term warming, nor that successful mitigation could *decelerate* it — the brief flags aerosol reductions as an unknown that could push probabilities higher, a tail the forecasters barely mention. 2. The Monte Carlo estimates (87–99%) cited by both forecasters assume σ ≈ 0.10–0.20°C interannual variability and a constant trend, but the brief notes the trend rate itself is uncertain; neither forecaster adequately distinguishes between uncertainty in the trend mean versus uncertainty in year-to-year noise, which are very different sources of model risk that shouldn't both push toward higher probability. 3. Neither forecaster engages seriously with the 30-day Kalshi price decline from ~80% to 75% — the brief explicitly flags this as a potentially meaningful signal, yet both forecasters dismiss the thin volume as the primary reason to move above market without explaining what new information could have driven the decline. 4. Both forecasters rely heavily on CMIP6 high-emissions pathway medians (~2043 crossover), but the brief notes flat/declining emissions scenarios push the median to ~2052, and the Stanford AI study suggests even net-zero-by-2050s leaves a 50% breach chance — neither forecaster explicitly weights the probability mass under moderate mitigation scenarios, which is the crux of the Yes/No split. 5. The definitional resolution ambiguity — which dataset triggers resolution — is noted in the brief but ignored by both forecasters; different agencies (Copernicus vs. Berkeley Earth vs. NOAA) can diverge by 0.05–0.10°C in a given year, which matters near the 2.0°C threshold and could affect resolution probability non-trivially. 6. Forecast 2's 84% implies materially less mitigation risk than Forecast 1's 80%, yet both use essentially identical reasoning; neither forecaster articulates a specific probability for the "meaningful mitigation bends the curve" scenario, leaving their divergence (~4 percentage points) unexplained and arbitrary.

80% (50% confidence)

Yes: 80% No: 20%

Single-year threshold plus El Niño variability and 0.20-0.27°C/decade trend support a high probability, with Monte Carlo estimates near 87-99% and CMIP6 crossover ~2043. However, the critique correctly notes model overconfidence in constant trend, genuine mitigation potential, and resolution/dataset ambiguity near the threshold, all of which favor staying near rather than far above the 75% market anchor. I settle at 80%, slightly above the recently declining Kalshi price.

Total pipeline time: 161.4s