How NWS Measures Precipitation for Market Settlement

Kalshi weather markets settle based on observations from specific Automated Surface Observing System (ASOS) stations operated by the NWS. For example, Chicago contracts reference KORD (O'Hare International Airport), New York uses KLGA (LaGuardia Airport), and Denver settles on KDEN (Denver International Airport). These stations represent the official observation point for each city market, and no other weather stations—including nearby manual observation sites, CoCoRaHS volunteer networks, or commercial weather services—affect settlement outcomes.

ASOS stations record precipitation automatically using heated tipping-bucket rain gauges that measure liquid-equivalent precipitation in 0.01-inch increments. The gauge consists of two small buckets mounted on a pivot; when one bucket collects 0.01 inches of water, it tips and empties while the other bucket moves into position. Each tip generates an electronic signal logged by the ASOS computer system. During winter, the gauge is heated to melt snow and sleet into liquid form before measurement, which means snow depth is not what determines settlement—liquid equivalent is.

The ASOS system transmits observations to NWS servers every minute, with formal METAR reports generated hourly and special reports (SPECI) issued when conditions change significantly. For daily precipitation totals used in Kalshi settlement, the NWS aggregates all tipping-bucket measurements from 00:00 to 23:59 UTC (7 PM to 6:59 PM Eastern the following day for East Coast stations). This UTC-based observation day often confuses new traders who assume a calendar day alignment—a storm that arrives at 8 PM Eastern on January 15th contributes to the January 16th UTC observation day used for settlement.

The 8-inch diameter tipping-bucket rain gauge standard on ASOS stations has known accuracy limitations that traders must understand. These gauges measure reliably between 0.01 and 4 inches per hour, but extreme rainfall rates above 4 inches per hour can cause undercounting because the buckets tip before fully filling, missing water that flows through during the tipping motion. This undercatch phenomenon affected measurement during Hurricane Harvey in Houston (KIAH), where manual gauges at the same airport recorded higher totals than the automated ASOS system.

Wind causes another systematic measurement error called wind-induced undercatch, where wind flow over the gauge opening creates turbulence that deflects raindrops and snowflakes away from the collector. The NWS estimates this effect causes 2-10% undercatch for rain and 20-50% undercatch for snow depending on wind speed and precipitation type. ASOS gauges use wind shields (Alter shields) to minimize this effect, but the problem persists especially at exposed airport locations. Kansas City (KMCI) and Minneapolis (KMSP) airports experience particularly high wind-induced undercatch during winter storms due to their flat, open terrain.

For snow measurement, ASOS stations convert snowfall to liquid equivalent using the heated gauge, but the NWS also maintains manual snow measurement protocols at many sites. Observers place snow boards—white painted boards laid flat on the ground—to measure snowfall depth and use heated copper cylinders to collect and melt snow core samples for liquid equivalent verification. However, only the automated ASOS liquid equivalent measurement feeds into the official daily precipitation total used for Kalshi settlement. A storm producing 10 inches of snow typically yields 0.80 to 1.20 inches of liquid equivalent depending on snow density, though fluffy Colorado powder (common at KDEN) may show 15:1 or 20:1 snow-to-liquid ratios while heavy Sierra cement at Reno (KRNO) approaches 5:1 or 6:1 ratios.

The NWS records precipitation as "trace" (abbreviated T in observations) when measurable moisture falls but totals less than 0.01 inches. This occurs frequently with light drizzle, brief snow flurries, or fog precipitation. For Kalshi markets, trace precipitation is critical to understand because most contracts specify a minimum threshold like "Will [City] receive at least 0.10 inches of precipitation?"—and trace amounts do not count toward this threshold. A day with 0.00 inches (no precipitation) and a day with trace precipitation both settle identically as No for a 0.10-inch threshold contract.

Trace measurements affect trading strategy particularly in marginal precipitation scenarios. Seattle (KSEA) averages 150 days per year with measurable precipitation (≥0.01 inches) but an additional 30-40 days with trace amounts that don't meet settlement thresholds. During weak frontal passages or morning fog events, the difference between 0.00 inches (trace) and 0.01 inches (measurable) often comes down to whether the rain gauge tips exactly once—a binary outcome that creates high variance in low-precipitation markets. Phoenix (KPHX) provides another example where summer monsoon microbursts may produce visible rainfall that evaporates before reaching the gauge or registers only as trace, frustrating traders expecting monsoon activity to trigger settlement.

The ASOS system records trace precipitation through its present weather sensor (a forward-scatter visibility sensor that detects hydrometeors) even when the tipping-bucket gauge shows zero accumulation. This means the METAR observation might show "-RA" (light rain) in the present weather field while the precipitation accumulation remains 0.00 inches. For settlement purposes, only the numeric accumulation matters—the qualitative present weather observations do not influence contract outcomes. Traders monitoring live weather conditions must distinguish between precipitation occurrence (what they see in radar or present weather codes) and measurable accumulation that reaches the 0.01-inch threshold required for most Kalshi contract settlement.

NWS precipitation data undergoes multiple quality control stages that can affect settlement timing and occasionally settlement values. ASOS stations transmit raw observations to the National Centers for Environmental Information (NCEI) where automated algorithms flag suspicious values—precipitation rates exceeding climatological norms, consecutive identical readings suggesting sensor failure, or missing data periods. Regional NWS Weather Forecast Offices then review flagged data, comparing ASOS readings against nearby manual observations, radar-estimated rainfall, and observer reports before certifying official daily totals.

This quality control process typically completes within 24-48 hours of the observation day, but corrections can occur weeks later if sensor malfunctions are discovered. Kalshi uses preliminary NWS data available shortly after the observation period ends for initial settlement, with a correction window allowing adjustments if official NWS values change. In practice, corrections affecting settlement occur in roughly 0.1-0.3% of contract days, usually involving sensor failures during extreme weather. Detroit (KDTW) experienced a notable correction in January 2022 when the ASOS gauge froze during a blizzard, initially reporting 0.15 inches when the actual liquid equivalent was 0.98 inches after manual measurement verification.

Traders should understand that Kalshi settlement sources specify "official NWS observations" which means the certified data from the NWS database, not real-time METAR feeds that some weather apps display. Third-party weather services occasionally show different precipitation totals than NWS official records because they use different quality control methods, time aggregation windows, or supplementary data sources. For settlement disputes, only the daily precipitation value published in NWS Climate Prediction System (CPS) data or visible in NCEI archives matters. Philadelphia (KPHL) markets settle on the precipitation total shown in NWS records for station KPHL, regardless of what Weather Underground, Weather.com, or airport terminal displays might show.

Understanding NWS measurement protocols reveals systematic biases that create trading edges. Airport ASOS locations typically sit at lower elevations than surrounding terrain, affecting precipitation totals in cities with topographic variation. Denver (KDEN) at 5,434 feet elevation receives less snow than neighborhoods in Boulder or Golden at 6,000+ feet because orographic lift enhances precipitation at higher elevations. Traders expecting "Denver snow" based on Front Range storm reports may overestimate KDEN accumulation and overpay for Yes contracts.

The heated rain gauge design creates another exploitable pattern in mixed precipitation events. When temperatures hover between 30-34°F, precipitation falls as wet snow or sleet that melts rapidly in the heated gauge funnel, but some crystals bounce out or blow away before melting, causing systematic undercatch of 10-30% compared to true liquid equivalent. This affects trading in cities prone to marginal winter precipitation like Washington DC (KDCA), Baltimore (KBWI), and Charlotte (KCLT). Markets pricing snow events at these locations should account for measurement undercatch reducing observed totals below forecast liquid equivalent.

The UTC observation day boundary creates arbitrage opportunities when storms track predictably across time zones. A Pacific storm hitting San Francisco (KSFO) at 9 PM Pacific (05:00 UTC the next day) counts toward the following UTC day, while precipitation arriving at 6 PM Pacific (02:00 UTC the next day) counts toward the current UTC day. Traders monitoring storm timing can identify mispriced contracts when markets fail to account for which side of the 00:00 UTC boundary (4 PM Pacific, 7 PM Eastern) the bulk of precipitation will fall. This timing edge proved profitable during the January 2023 California atmospheric river events when sequential markets mispriced storm arrival timing relative to the UTC settlement boundary.