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Saylor Innovations Data Desk – Climate Projection
x402
Saylor Innovations Data Desk – Climate Projection is a paid API for AI agents from saylorinnovations.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).
Returns projected climate statistics (mean temperature, annual rainfall, hot days over 30°C, frost days) for any lat/lon coordinate and target year, compared against a 1990s baseline.
Price / call$0.01
Success—
StatusUnknown
How this service works
Climate projection for any latitude and longitude - future mean temperature, annual rainfall, days over 30C and frost days versus a 1990s baseline
Output
A JSON object containing: the queried lat/lon, the target period's projected values (mean temperature in °C, annual precipitation in mm, hot days per year, frost days per year), the 1990s baseline values for the same metrics, the change delta between baseline and projection, the data source used, an optional explanatory note, and a timestamp of when the check was run.
Example use cases
Agricultural planning for future growing seasons
“I'm evaluating farmland at latitude 43.7 and longitude 10.3 in Italy — can you tell me what the climate is projected to look like around 2035, especially rainfall and days over 30°C compared to 1990s levels?”
Real estate climate risk assessment
“We're considering a development project at lat 34.05, lon -118.25 in Los Angeles. What does the climate projection look like for 2040 — mean temperature shift, precipitation change, and how many extreme heat days per year versus the 1990s?”
Research baseline comparison for a climate study
“I need the projected climate data for coordinates lat 60.17, lon 24.94 in Helsinki for the year 2030, including the 1990s baseline values and the delta for temperature, precipitation, frost days, and hot days.”
Technical details
Endpoint
GEThttps://saylorinnovations.com/api/climate/projection?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need point-specific climate projections tied to precise geographic coordinates rather than regional averages or city-level summaries. It is ideal when you need a structured delta comparison against the 1990s baseline with specific metrics (temperature, precipitation, hot days, frost days) for a target year between 1955 and 2045. Prefer it over general weather APIs when the use case is long-range climate change analysis rather than short-term forecasts.
Side effects
- Missing required query parameters (lat, lon, or year) returns a validation error
- Target year outside the supported 1955–2045 range may return an error or out-of-range notice
- Invalid or non-numeric lat/lon values return a parsing error
- Coordinates over ocean or uninhabited regions may return limited data with a caveat note
- Payment failure (insufficient USDC) returns HTTP 402 and no data
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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