The Importance of a Weather Contract Settlement Source Audit
When researching prediction markets like Polymarket and Kalshi, the difference between a successful hypothesis and a flawed assumption often comes down to the fine print. A comprehensive weather contract settlement source audit is the foundational step every researcher must take before logging a single simulated trade. In the fast-paced environment of weather prediction, it is incredibly easy to look at a general weather app, see a temperature, and assume you know how a market will resolve. However, prediction markets do not settle based on general weather apps. They settle based on highly specific, legally binding contract rules that dictate exactly which data source, at which time, and under which rounding rules the final outcome will be determined. By building a rigorous pre-simulation checklist, you protect your research from careless errors and ensure that your simulation data accurately reflects the reality of the platform's resolution process.
Reading the Fine Print: Contract Rules and Definitions
The first step in your weather contract settlement source audit is to read the contract rules word for word. On platforms like Polymarket and Kalshi, the contract rules are the ultimate law of the market. You must identify exactly what metric is being measured. Is it the daily high temperature, the daily low temperature, or the total precipitation? Once you know the metric, you must define the time period. Does the day run from midnight to midnight local time, or is it based on Coordinated Universal Time (UTC)? A temperature spike at 11:30 PM local time might count for today in one market, but tomorrow in another if the market uses a different time zone standard.
Furthermore, you must understand the specific definitions of the weather events. For example, in a precipitation market, does a trace amount of rain count as measurable precipitation, or does the contract require at least 0.01 inches to resolve as a YES? These definitions are not standardized across all platforms or even all contracts on the same platform. Your pre-simulation checklist must include a dedicated step to copy and paste the exact contract rules into your notes, highlighting the specific conditions required for resolution.
Finding and Verifying the Named Observation Source
Once you understand the rules, the next phase of your weather contract settlement source audit is identifying the exact observation station named in the contract. Prediction markets do not use a city's average temperature; they use a specific weather station, often located at a major airport. You must know exactly where this station is and how it reports its data.
For historical context and baseline research, you might look at the NCEI Integrated Surface Database. As a matter of record, NCEI describes a global archive of hourly and synoptic surface observations, which is invaluable for understanding the historical climatology of the specific station named in your contract.
For real-time or near real-time observation checks during your simulation, you might reference aviation data. For instance, the Aviation Weather Center Data API is a common tool. It is critical to remember that the API offers observation evidence but does not replace the contract platform's finalized result. You are using these tools to gather evidence and monitor the station's output, but the contract rules will always specify the ultimate source of truth, which is often a specific daily climate report issued by the National Weather Service.
Checking Units, Rounding, and Time Zones
A critical and often overlooked component of a weather contract settlement source audit is the verification of units and rounding rules. Does the contract resolve based on degrees Fahrenheit or degrees Celsius? If the raw data from the named observation source is reported in Celsius but the contract is in Fahrenheit, you must know the exact conversion formula the platform uses.
Rounding rules are equally vital. If a contract resolves as YES if the temperature is 80 degrees or higher, what happens if the official station records 79.6 degrees? Does the platform round up to 80, or does it truncate the decimal, leaving it at 79? Some contracts specify that they use the integer value reported in a specific daily summary, while others might calculate the value from hourly reports and apply standard mathematical rounding. Your pre-simulation checklist must explicitly state the rounding rules for the specific contract you are researching. Additionally, double-check the time zone of the reporting source versus the time zone of the contract. A mismatch here can lead to simulating a win when the actual market would result in a loss.
Separating Forecast Evidence from Settlement Authority
To be successful in your research, you must clearly distinguish between forecasts, observations, and platform-finalized settlement results. A forecast is a prediction of what might happen, generated by meteorological models like the GFS or ECMWF. Forecasts are tools for forming a hypothesis. An observation is the actual data recorded by the weather station as the event happens. Observations provide real-time evidence of the unfolding reality.
However, neither the forecast nor the raw observation is the final word. The platform-finalized settlement result is the ultimate authority. Even if you watch a thermometer hit 100 degrees, if the contract states that the resolution source is a specific report published the next day, and that report says 99 degrees due to a sensor calibration rule, the market settles at 99 degrees. Your weather contract settlement source audit must explicitly identify the entity that holds the settlement authority. During your simulation, you must wait for this final authority to publish its result before logging your simulated trade as a win or a loss. Never assume that your raw observation data will perfectly match the finalized settlement without verifying the official report.
Common Pitfalls in Source Verification
Even experienced researchers can fall into traps if they skip their weather contract settlement source audit. One of the most common pitfalls is assuming that all contracts on a single platform share the same rules. For example, Polymarket might have one set of rules for a monthly temperature market and a completely different set of rules for a daily temperature market. Kalshi might use a specific API endpoint for one city, but rely on a different reporting mechanism for a city where that endpoint is historically unreliable.
Another frequent error is ignoring the data delay clause. Many contracts include stipulations about what happens if the primary data source fails to report on time. They will list a secondary or tertiary fallback source. If you are simulating a trade and the primary station goes offline, your checklist should immediately tell you where to look next. If you haven't audited the fallback sources, your simulation will stall, and your research will lose its accuracy. Always document the entire chain of resolution authority in your pre-simulation notes. This level of detail separates casual observers from serious market researchers.
Building Your MeteoX Simulation Routine
Integrating a weather contract settlement source audit into your daily routine is the best way to build discipline. Start by creating a standardized template for every market you research. Fill out the contract rules, the named observation source, the rounding rules, and the designated settlement authority before you even look at a forecast.
Remember that MeteoX is designed to help you practice this exact workflow in a risk-free environment. We encourage all researchers to utilize our platform to test their hypotheses against real-world data. Please note that this workflow is simulation-only; MeteoX does not submit external orders or connect to real-money exchanges. Our goal is to provide you with the tools to refine your analytical skills.
To explore more about how our platform can enhance your research, visit the MeteoX Trade homepage. If you want to dive deeper into specific market dynamics and research strategies, check out our other articles on the MeteoX blog. By consistently applying this pre-simulation checklist, you will develop a sharper, more objective approach to analyzing weather prediction markets.
Sources and further reading
- Aviation Weather Center Data API — The API offers observation evidence but does not replace the contract platform's finalized result.
- NCEI Integrated Surface Database — NCEI describes a global archive of hourly and synoptic surface observations.