Agriculture & Environment Climate intelligence for the fields, forests, and atmosphere.

Grow smarter with
weather data that explains itself.

Precision agriculture, environmental monitoring, and climate research all depend on accurate, context-aware weather data. WeatherLens delivers accuracy-scored forecasts, multi-year climate normals, and historical observed conditions — with the confidence metrics to know when to act and when to wait.

Climatenormals for any coordinate
365-dayhistorical archive
Globalany lat/lon, any day

Built for Land and Atmosphere

From planting calendars to carbon monitoring, WeatherLens powers weather-intelligent applications at every scale.

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Precision Crop Management
Combine 16-day forecasts with multi-year climate normals to optimize planting windows, irrigation scheduling, and harvest timing. Surface anomalous conditions before they become crop losses.
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Livestock & Pasture Management
Heat stress indices, freeze warnings, and precipitation forecasts with confidence scores. Know when forecast uncertainty is high and build buffer days into pasture rotation plans.
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Water Resource Management
Historical precipitation data and climate baselines support reservoir modeling, drought severity assessment, and irrigation district planning for the full growing season.
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Forestry & Wildfire Risk
Wind speed, humidity, and precipitation drought history directly drive wildfire risk models. Historical archive feeds fuel moisture models; forecast accuracy scores set alert confidence.
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Climate Research & Monitoring
Access multi-year climate normals for any coordinate globally. Pair with observed actuals to study anomalies, trend deviations, and climate signal attribution at field scale.
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Carbon & ESG Monitoring
Climate baselines and historical temperature data support Scope 3 emissions modeling, carbon sequestration estimates, and ESG weather-related risk disclosures.

Forecasts are only half the story. Context is everything.

Farmers and climate scientists don't just need to know what the weather will be. They need to know if it's normal — and how much to trust the prediction.

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Climate Normals — Any Day, Any Location
Query /api/v1/climate for multi-year weighted averages at any lat/lon for any day of year. Surface baseline high/low temperatures, normal precipitation, and seasonal patterns so your application can contextualize every forecast reading automatically.
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Historical Observed Actuals
Pro plan includes 365 days of observed conditions for any global coordinate. Build phenological models, validate irrigation decisions, and feed retrospective analysis pipelines without standing up your own data collection infrastructure.
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Forecast Accuracy by Region
Our /accuracy endpoint scores how well forecasts have performed at your specific field coordinates — by lead time and by source. Know whether a 7-day rainfall forecast deserves 90% confidence or 60% confidence for better irrigation decision-making.
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Global Coverage — Field-Level Precision
Query any lat/lon on Earth. NWS precision for US agricultural zones, Open-Meteo global coverage for international operations. No need to manage multiple vendor relationships for different growing regions.

Planting Decision Intelligence

Combine forecast, climate normal, and accuracy data in one workflow.

Planting window advisor — Python
import httpx, os

KEY = os.environ["WEATHERLENS_KEY"]
BASE = "https://weatherlens.dev/api/v1"
FIELD = {"lat": 41.5868, "lon": -93.6250}  # Central Iowa

# Pull 10-day forecast
forecast = httpx.get(f"{BASE}/forecast",
    params={**FIELD, "days": 10},
    headers={"X-API-Key": KEY}).json()

# Pull climate normals for seasonal context
climate = httpx.get(f"{BASE}/climate",
    params=FIELD, headers={"X-API-Key": KEY}).json()

# Pull accuracy data for this region
accuracy = httpx.get(f"{BASE}/accuracy",
    params=FIELD, headers={"X-API-Key": KEY}).json()

# Evaluate planting window
soil_safe_days = [
    day for day in forecast["forecast"]
    if day["lowF"] > 32           # no frost
    and day["precipProbPct"] < 40 # dry enough to plant
]

print(f"Safe planting days next 10 days: {len(soil_safe_days)}")
print(f"Forecast confidence (7-day): {accuracy['tempWithin2F_7day']:.0%}")
print(f"Climate normal frost-free date: {climate['lastFrostDate']}")

Start with free climate data access

100 free API calls per day, including climate normals and accuracy scores. Historical archive on Pro. No credit card required to start.