Live probability: Will the next CPI print come in above consensus? — Stable evergreen URL for a recurring question: Will the next CPI print come in above consensus? Auto-resolves to the current market instance and rolls forward on resolution, so the answer is always about the next occurrence. Response adds current_slug and rolls_to_next_at to the standard probability shape.

Live probability: Will the next US GDP print show growth? — Stable evergreen URL for a recurring question: Will the next US GDP print show growth? Auto-resolves to the current market instance and rolls forward on resolution, so the answer is always about the next occurrence. Response adds current_slug and rolls_to_next_at to the standard probability shape.

Live probability: Which party wins the next US presidential election? — Stable evergreen URL for a recurring question: Which party wins the next US presidential election? Auto-resolves to the current market instance and rolls forward on resolution, so the answer is always about the next occurrence. Response adds current_slug and rolls_to_next_at to the standard probability shape.

Live probability: Who controls the Senate after the next election? — Stable evergreen URL for a recurring question: Who controls the Senate after the next election? Auto-resolves to the current market instance and rolls forward on resolution, so the answer is always about the next occurrence. Response adds current_slug and rolls_to_next_at to the standard probability shape.

Live probability: Will the US enter a recession this year? — Stable evergreen URL for a recurring question: Will the US enter a recession this year? Auto-resolves to the current market instance and rolls forward on resolution, so the answer is always about the next occurrence. Response adds current_slug and rolls_to_next_at to the standard probability shape.

Live probability: Who wins the next World Series? — Stable evergreen URL for a recurring question: Who wins the next World Series? Auto-resolves to the current market instance and rolls forward on resolution, so the answer is always about the next occurrence. Response adds current_slug and rolls_to_next_at to the standard probability shape.

Hourly Atlanta weather forecast (blend model, method labeled) — Hourly weather forecast for Atlanta: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Atlanta coordinates built in.

Will it rain in Atlanta during your event window — Event-window weather odds for Atlanta: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Atlanta coordinates built in.

Hourly Austin weather forecast (blend model, method labeled) — Hourly weather forecast for Austin: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Austin coordinates built in.

Will it rain in Austin during your event window — Event-window weather odds for Austin: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Austin coordinates built in.

Hourly Boston weather forecast (blend model, method labeled) — Hourly weather forecast for Boston: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Boston coordinates built in.

Will it rain in Boston during your event window — Event-window weather odds for Boston: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Boston coordinates built in.

Hourly Charlotte weather forecast (blend model, method labeled) — Hourly weather forecast for Charlotte: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Charlotte coordinates built in.

Will it rain in Charlotte during your event window — Event-window weather odds for Charlotte: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Charlotte coordinates built in.

Hourly Chicago weather forecast (blend model, method labeled) — Hourly weather forecast for Chicago: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Chicago coordinates built in.

Will it rain in Chicago during your event window — Event-window weather odds for Chicago: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Chicago coordinates built in.

Hourly Dallas weather forecast (blend model, method labeled) — Hourly weather forecast for Dallas: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Dallas coordinates built in.

Will it rain in Dallas during your event window — Event-window weather odds for Dallas: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Dallas coordinates built in.

Hourly Denver weather forecast (blend model, method labeled) — Hourly weather forecast for Denver: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Denver coordinates built in.

Will it rain in Denver during your event window — Event-window weather odds for Denver: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Denver coordinates built in.

Hourly Detroit weather forecast (blend model, method labeled) — Hourly weather forecast for Detroit: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Detroit coordinates built in.

Will it rain in Detroit during your event window — Event-window weather odds for Detroit: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Detroit coordinates built in.

Hourly Houston weather forecast (blend model, method labeled) — Hourly weather forecast for Houston: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Houston coordinates built in.

Will it rain in Houston during your event window — Event-window weather odds for Houston: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Houston coordinates built in.

Hourly Jacksonville weather forecast (blend model, method labeled) — Hourly weather forecast for Jacksonville: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Jacksonville coordinates built in.

Will it rain in Jacksonville during your event window — Event-window weather odds for Jacksonville: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Jacksonville coordinates built in.

Hourly Las Vegas weather forecast (blend model, method labeled) — Hourly weather forecast for Las Vegas: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Las Vegas coordinates built in.

Will it rain in Las Vegas during your event window — Event-window weather odds for Las Vegas: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Las Vegas coordinates built in.

Hourly Los Angeles weather forecast (blend model, method labeled) — Hourly weather forecast for Los Angeles: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Los Angeles coordinates built in.

Will it rain in Los Angeles during your event window — Event-window weather odds for Los Angeles: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Los Angeles coordinates built in.

Hourly Miami weather forecast (blend model, method labeled) — Hourly weather forecast for Miami: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Miami coordinates built in.

Will it rain in Miami during your event window — Event-window weather odds for Miami: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Miami coordinates built in.

Hourly Minneapolis weather forecast (blend model, method labeled) — Hourly weather forecast for Minneapolis: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Minneapolis coordinates built in.

Will it rain in Minneapolis during your event window — Event-window weather odds for Minneapolis: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Minneapolis coordinates built in.

Hourly Nashville weather forecast (blend model, method labeled) — Hourly weather forecast for Nashville: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Nashville coordinates built in.

Will it rain in Nashville during your event window — Event-window weather odds for Nashville: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Nashville coordinates built in.

Hourly New York City weather forecast (blend model, method labeled) — Hourly weather forecast for New York City: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the New York City coordinates built in.

Will it rain in New York City during your event window — Event-window weather odds for New York City: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the New York City coordinates built in.

Hourly Philadelphia weather forecast (blend model, method labeled) — Hourly weather forecast for Philadelphia: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Philadelphia coordinates built in.

Will it rain in Philadelphia during your event window — Event-window weather odds for Philadelphia: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Philadelphia coordinates built in.

Hourly Phoenix weather forecast (blend model, method labeled) — Hourly weather forecast for Phoenix: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Phoenix coordinates built in.

Will it rain in Phoenix during your event window — Event-window weather odds for Phoenix: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Phoenix coordinates built in.

Hourly point forecast for any coordinate, up to 168 hours — Hourly temperature, feels-like, precipitation probability/amount, wind, gusts, humidity, and cloud cover for an exact lat/lon: NWS-derived series, bias-blended with our calibrated station model where covered. Imperial by default (units=metric available). Requests beyond 168 hours are capped at the model's current horizon. Longer…

Hourly Portland weather forecast (blend model, method labeled) — Hourly weather forecast for Portland: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Portland coordinates built in.

Will it rain in Portland during your event window — Event-window weather odds for Portland: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Portland coordinates built in.

Percentile bands (p10–p90) for temp, precip, or wind — Hourly p10/p25/p50/p75/p90 bands for one variable at a coordinate. Temperature bands come from the model's empirical calibration; precipitation and wind bands are NWS-derived approximations, disclosed in the response's method label. Metric units (°C, mm, kph). Horizons cap at 168h. Use it to reason about uncertainty, not just point values.

Hourly San Antonio weather forecast (blend model, method labeled) — Hourly weather forecast for San Antonio: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the San Antonio coordinates built in.

Will it rain in San Antonio during your event window — Event-window weather odds for San Antonio: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the San Antonio coordinates built in.

Hourly San Diego weather forecast (blend model, method labeled) — Hourly weather forecast for San Diego: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the San Diego coordinates built in.

Will it rain in San Diego during your event window — Event-window weather odds for San Diego: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the San Diego coordinates built in.