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| Market | Platform | Price |
|---|---|---|
Will it **rain** in New York City on Friday? | Kalshi | 20% |
Trader mode: Actionable analysis for identifying opportunities and edge
On Jan 16, 2026 If the number of inches of precipitation recorded at Central Park, New York on January 16, 2026 is strictly greater than 0, then the market resolves to Yes. The Payout Criterion only encompasses Expiration Values that are strictly greater than inches. If the Expiration Value is T (when the target is 0) for Trace or R for Record (where the record set is strictly greater than ), then the market resolves to Yes. This market will close and expire the sooner of the first 10:00 AM E
Prediction markets currently assign a low 20% probability to measurable precipitation occurring in New York City on January 16, 2026. This price, trading on Kalshi, indicates the market views a dry day as the strong consensus outcome. A 20% chance suggests traders see about a 1-in-5 likelihood of rain, framing it as a possible but relatively unlikely event.
Two primary meteorological and historical factors are suppressing the probability. First, mid-January in New York City is within the core of winter, where precipitation is more likely to fall as snow or a wintry mix rather than liquid rain. The market specifically bets on liquid precipitation exceeding a trace amount, which reduces odds compared to a market covering all precipitation types. Second, long-term climatology provides a baseline. The average probability of measurable precipitation on any given January day in Central Park is approximately 25-30%. The current 20% market price sits slightly below this historical average, reflecting a neutral to dry initial forecast for that specific date nearly two years in advance.
The odds will remain relatively stable but gradually become more volatile as the date approaches and actionable weather models begin to form. The first significant catalyst will be the emergence of reliable forecast models roughly 10-14 days prior to January 16, 2026. A consistent signal for a major coastal storm or a warmer system pushing into the region would cause the "Yes" probability to rise sharply from its current low level. Conversely, model consensus showing high pressure and dry air dominance would solidify the low probability. Given the extreme time horizon, this market currently prices almost pure climatology, which will be replaced by dynamic weather forecasting as the event nears.
AI-generated analysis based on market data. Not financial advice.
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This prediction market focuses on whether measurable precipitation will occur in New York City on January 16, 2026, specifically at the Central Park weather station, which serves as the city's official climatological observation site. The market resolves to 'Yes' if the recorded precipitation exceeds zero inches, including trace amounts (T) or record-setting precipitation (R) that are strictly greater than zero. This type of weather prediction market allows participants to trade contracts based on their assessment of future meteorological conditions, blending climatological data with financial speculation. The market will close and expire at the earlier of two times: the first 10:00 AM Eastern Time after the observation period or according to its predetermined expiration protocol. Interest in such markets stems from their utility for hedging weather-related risks, testing forecasting models, and providing a collective intelligence assessment of future weather events that can complement traditional meteorological predictions. These markets have gained attention from agricultural planners, event organizers, insurance companies, and climate researchers who seek probabilistic assessments of specific weather outcomes beyond standard forecasts.
Central Park has served as New York City's official weather observation site since 1869, providing one of the longest continuous urban climate records in the United States. The station's historical data reveals that January is typically New York's second-coldest month with average precipitation of 3.65 inches, though this includes both rain and melted snow equivalent. On January 16 specifically, historical records show precipitation occurring approximately 35% of the time based on data from 1991-2020, with measurable precipitation (greater than 0.01 inches) occurring about 25% of January 16ths. The most significant January 16 precipitation event occurred in 1978 when 1.96 inches of rain fell, while numerous January 16ths have recorded trace amounts or no precipitation. Winter precipitation patterns in New York City have shown increased variability in recent decades, with some research suggesting climate change may be altering the frequency and intensity of winter precipitation events in the Northeast. The historical baseline for January precipitation at Central Park is 3.65 inches based on the 1991-2020 climate normal period, though individual days show considerable variation from this monthly average.
Weather prediction markets provide valuable probabilistic assessments that complement traditional forecasting, offering quantified uncertainty measures that help businesses, governments, and individuals make better-informed decisions. For New York City specifically, January precipitation predictions influence winter preparedness budgets, transportation planning, retail operations, and utility company resource allocation. The economic implications extend to numerous sectors including aviation (with the three major New York airports handling thousands of daily flights), construction (where winter weather affects timelines), and hospitality (where precipitation impacts tourism and events). Beyond immediate economic considerations, these markets contribute to our understanding of collective forecasting intelligence and market efficiency in processing complex meteorological information. They also serve as testbeds for evaluating climate models and assessing how well different forecasting approaches perform for specific date predictions years in advance.
As of late 2024, climate models and seasonal outlooks are beginning to provide initial indications for the winter of 2025-2026, though specific daily predictions for January 2026 remain highly uncertain. The Climate Prediction Center's most recent seasonal outlooks suggest near-normal precipitation probabilities for the Northeast U.S. during winter 2025-2026, but these broad seasonal forecasts have limited utility for specific daily predictions. Current El Niño-Southern Oscillation conditions and projections will influence winter 2026 patterns, but the specific phase and strength of ENSO during that period cannot be determined with high confidence at this lead time. Prediction market activity for this date remains minimal due to the distant time horizon, with most trading expected to intensify as the date approaches and shorter-range forecasts become available.
The National Weather Service uses standardized rain gauges at the Central Park weather station, typically tipping-bucket or weighing gauges that measure liquid precipitation to the nearest 0.01 inches. Measurements are taken daily at a specific observation time, with special procedures for frozen precipitation that is melted before measurement.
A trace (T) indicates detectable precipitation that measures less than 0.01 inches in the standard rain gauge. For this prediction market, trace amounts resolve to 'Yes' since they represent precipitation strictly greater than zero, though they fall below the minimum measurable threshold.
Specific daily precipitation predictions two years ahead have essentially no skill beyond climatological averages. Seasonal outlooks provide probabilistic guidance for broader periods, but daily specifics cannot be reliably forecast more than about 10 days in advance with current technology.
The National Weather Service has backup measurement procedures and alternative observation sites that would be used according to established protocols. Prediction market rules typically specify Central Park as the official source, with contingency plans for data unavailability detailed in market specifications.
January precipitation in New York City can occur as rain, snow, sleet, or freezing rain, with average temperatures near freezing creating variability. Liquid equivalent measurements convert all forms to water content, so the market resolves based on this liquid measurement regardless of precipitation type.
Key influences include the position of the jet stream, North Atlantic Oscillation phase, El Niño-Southern Oscillation conditions, Arctic oscillation patterns, and local geographic factors. These large-scale climate patterns interact to determine storm tracks and precipitation timing in the Northeast U.S.
Educational content is AI-generated and sourced from Wikipedia. It should not be considered financial advice.
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