Event GroupPOLYMARKETClimate
Highest temperature in Seoul on January 17?
Total Volume
$1.10K
Events
1
Markets
7
Highest temperature in Seoul on January 17?
Vol
$1.10K
|
Events
1
|
Markets
7
$1.10K
1
7
$1.10K
1
7
7 markets tracked
No data available
| Market | Platform | Price |
|---|---|---|
| Poly | 38% |
| Poly | 33% |
| Poly | 20% |
| Poly | 14% |
| Poly | 11% |
| Poly | 7% |
| Poly | 6% |
Trader mode: Actionable analysis for identifying opportunities and edge
This market will resolve to the temperature range that contains the highest temperature recorded at the Incheon Intl Airport Station in degrees Celsius on 17 Jan '26. The resolution source for this market will be information from Wunderground, specifically the highest temperature recorded for all times on this day by the Forecast for the Incheon Intl Airport Station once information is finalized, available here: https://www.wunderground.com/history/daily/kr/incheon/RKSI. To toggle between Fahr
The prediction market is pricing in a low probability that Seoul's highest temperature on January 16, 2026, will reach 4°C. The leading contract for this specific outcome is trading at 34¢, implying the market sees only a 34% chance. This suggests traders view a high of exactly 4°C as possible but not the most likely scenario. Liquidity is thin with just $41,000 in volume spread across seven temperature-range markets, indicating limited consensus. The market will resolve based on data from Incheon International Airport Station, Seoul's primary official weather station.
Two primary factors are suppressing the odds for a 4°C high. First, historical climatology is key. Seoul's average daily high in mid-January is approximately 1°C, with temperatures more commonly ranging between -3°C and 3°C. A high of 4°C would be considered mild for the season. Second, current short-term weather modeling for January 2026 is not available, so traders are likely relying on typical seasonal patterns and the absence of any forecasted strong warm-air advection events. The low probability reflects a default to historical norms rather than a specific prediction of unusual warmth.
The odds are highly sensitive to near-term weather forecast updates. As the resolution date approaches within the next 24 hours, traders will monitor real-time forecast models. A significant shift in the predicted storm track or a stronger-than-projected southerly wind flow could rapidly increase the probability of a 4°C high. Conversely, model trends indicating an influx of colder air from Siberia would drive these odds lower. Given the thin liquidity, any new capital entering the market based on fresh meteorological data could cause sharp price movements. The final odds will effectively be a direct reflection of the forecast consensus by the evening of January 15.
AI-generated analysis based on market data. Not financial advice.
This prediction market focuses on forecasting the maximum temperature that will be recorded at Incheon International Airport Station in Seoul, South Korea, on January 16, 2026. The market resolves based on data from Wunderground's historical weather records for the specific weather station located at the airport, designated by the code RKSI. Participants are essentially betting on which temperature range will contain the official daily high, as measured in degrees Celsius. This type of market falls under climate prediction, where meteorological data, seasonal forecasting models, and historical trends are analyzed to make informed predictions about future weather conditions. The interest in such a market stems from its application in testing predictive models, its relevance to industries sensitive to winter weather, and its use as a tool for hedging against temperature-dependent outcomes. Recent developments in climate science, including improved understanding of phenomena like Arctic amplification and its potential influence on East Asian winter monsoons, add layers of complexity and public interest to long-range temperature forecasts for specific dates. The market's resolution to a specific, verifiable data point from a reputable source like Wunderground provides a clear and objective outcome, making it a classic example of an event-based prediction market.
Seoul's winter climate is characterized by cold, dry weather influenced primarily by the Siberian High pressure system. Analyzing historical extremes provides crucial context for prediction. The coldest temperature ever recorded in Seoul was -23.1°C on January 5, 1981. For the specific date in question, January 16, historical data shows significant variability. For instance, on January 16, 2021, the high temperature was a mild 7.2°C, while on January 16, 2018, it was a frigid -9.4°C. This nearly 17-degree difference for the same calendar date illustrates the high interannual variability driven by fluctuating atmospheric patterns. A key precedent is the record-breaking cold wave of early January 2023, when temperatures in parts of South Korea plunged below -20°C, highlighting the potential for extreme cold. Conversely, recent decades have shown a warming trend in winter minimum temperatures, though cold snaps remain severe. The historical record for the highest January temperature in Seoul is 14.4°C, set on January 22, 2020, demonstrating that unseasonably warm days are also possible during the heart of winter, often associated with strong southerly winds ahead of an approaching low-pressure system.
The outcome of this prediction has tangible implications beyond the betting market. Accurate temperature forecasts for specific dates are vital for economic planning. Energy providers, particularly natural gas and electricity companies, use such forecasts to manage supply and anticipate peak demand during cold spells, directly impacting grid stability and consumer prices. The transportation sector, especially aviation operations at Incheon Airport, requires precise temperature data for de-icing protocols and aircraft performance calculations, affecting flight schedules and safety. Furthermore, the recorded temperature becomes a data point in long-term climate studies. Anomalously high or low readings contribute to the analysis of climate change trends in East Asia, influencing policy discussions on energy security, agricultural planning, and public health preparedness for temperature-related illnesses. For the public, the January high temperature is a practical concern affecting daily life, from heating costs and winter clothing choices to outdoor activities and commuting conditions.
As of late 2025, meteorological agencies are issuing preliminary seasonal outlooks for the 2025-2026 winter. The Korea Meteorological Administration typically releases its official winter forecast in November, which will provide crucial guidance. Current long-range model projections from centers like ECMWF and NCEP are being analyzed for signals regarding the strength of the Siberian High and the state of atmospheric oscillations like the Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO), which are key drivers of East Asian winter weather. A negative AO phase, for example, would increase the likelihood of cold air outbreaks penetrating into the Korean Peninsula. The specific forecast for January 16, 2026, will not be available until much closer to the date, but the evolving seasonal pattern will shape the probabilistic framework for this prediction.
Mid-January is typically the coldest period of the year in Seoul. Average high temperatures are around 1-2°C, with average lows around -6 to -8°C. The weather is generally dry and sunny under the influence of the Siberian High, but cold waves can bring severe sub-zero temperatures and wind chills.
The market specifies the Incheon International Airport Station (RKSI) as the resolution source for consistency and verifiability. Airport weather stations are held to strict international standards (WMO guidelines), ensuring reliable and comparable data. Measurements in urban centers can be affected by the urban heat island effect, while the airport provides a more standardized environment.
Forecast skill decreases significantly beyond 10 days. While seasonal outlooks can predict broader temperature anomalies (e.g., a warmer-than-average month), pinpointing the exact high temperature for a specific day months in advance is highly uncertain. Predictions rely on climatology, long-range model trends, and known climate oscillations rather than precise daily forecasting.
The two primary phenomena are the Siberian High, which brings cold, dry continental air from the north, and the strength of the East Asian winter monsoon. Secondary influences include the Arctic Oscillation (negative phase favors cold outbreaks), sea surface temperatures in the surrounding seas, and the occasional passage of mid-latitude cyclones which can briefly pull in warmer air from the south.
Climate change has led to a documented warming trend in Seoul's winters, with fewer extreme cold days on average. However, it may also be linked to increased variability in atmospheric patterns, potentially leading to more intense but less frequent cold snaps due to disruptions of the polar vortex, a phenomenon still under active scientific research.
Educational content is AI-generated and sourced from Wikipedia. It should not be considered financial advice.
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