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Elemental Advantage: Long-Term Weather Forecasting for Agriculture


Source: Unsplash


In the ever-evolving landscape of agriculture, farmers grapple with the unpredictability of weather conditions that profoundly impact their yields. Accurate forecasting of long-term weather patterns can equip decision-makers with the tools to optimize planning and reduce losses. Recognizing the immense potential of this technology, Adatos has developed an advanced AI-powered solution that provides long-term weather forecasts up to 12 months in advance.


Using AI, we analyze more than a decade's worth of historical data, incorporating valuable seasonal trends and considering global climatic phenomena. For instance, our rainfall forecast model is trained using over ten years of satellite rainfall data and the Niño3.4 SST anomaly index, which indicates El Niño conditions in the central tropical Pacific. We have further improved the data quality by calibrating satellite-based rainfall data with on-ground rain gauge data.


The graph below showcases our 1 month rainfall forecast for a specific region in Peninsular Malaysia. Our time series model captures seasonal trends with remarkable precision, achieving a root mean square error (RMSE) of 18mm and 75mm for 1-month and 12-month rainfall forecasting, respectively.



We integrate this rainfall forecast model into crop yield prediction for perennial crops such as oil palm. By incorporating this forecast as one of input features, it significantly improves the accuracy of yield predictions.


Our weather forecasts can transform agricultural planning. Farmers can identify the best periods for planting specific crops based on projected weather patterns, optimizing growing conditions and mitigating risks from adverse weather events. Additionally, our forecasts enable efficient irrigation planning, conserving resources while ensuring optimal plant growth and productivity. Moreover, farmers can strategically plan their harvesting activities, aligning them with projected weather conditions to minimize losses. For example, rain can negatively impact the quality of cotton if it is harvested wet.


As the agricultural industry faces the challenges of climate change and increasing demand, leveraging long-term weather forecasts becomes indispensable for sustainable and efficient practices. Message us on LinkedIn to find out more about weather forecasting, including forecasts for land surface temperature (LST), evapotranspiration, El Niño and La Niña.

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