
$250.09K
1
11

$250.09K
1
11
Trader mode: Actionable analysis for identifying opportunities and edge
This market will resolve to the temperature range that contains the highest temperature recorded by NOAA at the Taiwan Taoyuan International Airport in degrees Celsius on 29 Mar '26. The resolution source for this market will be information from NOAA, specifically the highest reading under the "Temp" column on the specified date once information is finalized for all hours on that date, available here: https://www.weather.gov/wrh/timeseries?site=RCTP To toggle between Fahrenheit and Celsius, cl
AI-generated analysis based on market data. Not financial advice.
This prediction market focuses on forecasting the maximum temperature recorded at Taiwan Taoyuan International Airport on March 27, 2026. The market resolves based on data from the National Oceanic and Atmospheric Administration (NOAA), specifically the highest reading from the 'Temp' column on that date from NOAA's weather observation page for the airport station (site code RCTP). Participants are essentially betting on which temperature range will contain the official high for that specific day and location. This type of market falls under climate prediction, where short-term weather outcomes are used as measurable events for financial speculation or hedging purposes. Interest stems from meteorological enthusiasts, financial traders looking for uncorrelated assets, and individuals or businesses with exposure to weather-dependent activities in northern Taiwan. The market's resolution depends entirely on the finalized data from a single, authoritative U.S. government source, removing ambiguity about the outcome. The focus on a major international airport ensures consistent, high-quality instrumentation and reporting standards, making the data reliable for settlement.
Prediction markets for weather events have existed in informal forms for centuries but gained modern structure with the advent of electronic trading and reliable public data. The Chicago Mercantile Exchange launched the first standardized weather derivative contracts in 1999, allowing businesses to hedge against temperature fluctuations. These financial instruments created a framework for pricing weather risk, which later evolved into binary prediction markets on specific outcomes like daily highs. The choice of Taoyuan Airport as a location is significant. Historically, Taipei's official weather station was located in the downtown district, but urban heat island effects led to a warming bias in long-term records. In contrast, Taoyuan Airport, situated approximately 40 km west of central Taipei, provides a less urbanized and more consistent observation environment, though it is still warmer than mountainous regions of Taiwan. March weather in northern Taiwan is historically transitional, marking the shift from the cool, dry winter monsoon to the warm, humid pre-summer period. Temperatures can vary significantly based on the strength of southerly winds or the persistence of continental high-pressure systems bringing cooler air from China.
Beyond gambling, these markets serve as aggregation tools for dispersed information. The trading price reflects the collective judgment of all participants about the likely temperature, potentially outperforming individual forecast models. This has value for industries sensitive to March weather in Taiwan, such as agriculture for early rice and fruit crops, tourism planning for the spring season, and energy utilities anticipating electricity demand for cooling. For meteorology, the market's probability assessment can be compared to official model ensembles, providing a real-time check on forecast confidence. A significant deviation between market prices and scientific forecasts could indicate either a flaw in the models or specialized knowledge among traders. Politically, accurate weather prediction is always critical for Taiwan, especially for water resource management and disaster preparedness ahead of the typhoon and plum rain seasons that follow spring.
As of early 2025, seasonal forecast models from agencies like the CWA, NOAA's Climate Prediction Center, and the Japan Meteorological Agency are beginning to issue preliminary outlooks for the March 2026 period. These outlooks consider large-scale climate drivers such as the state of the El Niño-Southern Oscillation (ENSO), which is currently in a neutral phase but is projected by some models to trend toward La Niña by late 2025. La Niña conditions can influence winter and spring weather patterns in East Asia, potentially leading to a cooler and wetter than average end to winter in Taiwan, with effects that may linger into March. The specific daily forecast for March 27, 2026, will not be available until approximately one week before the date.
NOAA's observation data for station RCTP is logged in Coordinated Universal Time (UTC). The date for the daily high is determined by the UTC day. Traders must convert this to local Taiwan Time (UTC+8) to understand which 24-hour period corresponds to the local calendar date of March 27.
Prediction market rules typically specify a backup data source or a resolution method for such contingencies. This often involves using archived data from alternative reliable sources like the CWA or the World Meteorological Organization after a defined waiting period. The specific rules are detailed in the market's creation document.
Taoyuan Airport is generally 1 to 3 degrees Celsius cooler than downtown Taipei on clear, calm days due to the urban heat island effect in the city. However, during cold air outbreaks with strong winds, the temperature difference can be minimal. The airport is less representative of the urban population's experience but offers more consistent meteorological observations.
No. Operational weather models only provide specific forecasts for about 10-15 days into the future. Predictions for a date like March 27, 2026, made in 2025 are based on seasonal climate outlooks, which only predict broad temperature and precipitation anomalies (above/below average) over a month or season, not daily specifics.
Educational content is AI-generated and sourced from Wikipedia. It should not be considered financial advice.
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