Is the frost-risk score a guaranteed forecast?

No. The score is provided for decision support and should be used together with official meteorological warnings, local observation and expert review.

Which factor matters most in the score?

Overnight minimum temperature and how quickly it approaches freezing form the largest part of the total score.

Which data sources does Tarım İklim use?

The service uses OpenWeatherMap forecast data as the primary source and can evaluate Open-Meteo as a fallback source where appropriate.

METHODOLOGY

How is agricultural frost risk calculated?

Tarım İklim does not read overnight temperature alone. It evaluates temperature, humidity, wind and cloud cover together to generate a clear 0-100 decision-support signal.

Four-factor scoring model

60%

Temperature

Overnight minimum temperature and the rate of approach to freezing are the primary signal.

15%

Humidity

Low humidity can increase radiative heat loss; higher humidity can soften risk in some conditions.

15%

Wind

Calm air increases radiation-frost risk; light air movement can reduce inversion effects.

10%

Cloud cover

Clear sky accelerates overnight heat loss; cloud cover can provide a protective effect.

Risk thresholds

0-20Low

Standard monitoring is usually sufficient.

21-50Moderate

Sensitive crops and low-elevation parcels should be checked.

51-80High

Plan cover, irrigation, fogging or greenhouse measures.

81-100Critical

Urgent protection action and multi-channel notification are recommended.

Alert timing

Frost risk becomes most critical overnight and toward dawn. The system therefore monitors the following night during the evening; email, Telegram or push notification preferences may be triggered at high and critical thresholds.

Limitations and proper use

Microclimate, parcel elevation, cover status, irrigation, soil moisture and crop phenology can change frost impact. The score is not a guaranteed damage forecast. Official meteorological warnings, local measurements and agronomic expert review should be considered before critical decisions.

Expertise process

The methodology is developed by evaluating agricultural decision-support needs, data engineering, meteorological forecast data and field-use scenarios together. The goal is to turn complex forecast data into a risk signal that growers and agricultural businesses can read quickly.