Part 1: Product Demand Forecasting Using Weather Data

2025.12.01

Product demand forecasting that incorporates weather data is an essential approach for optimizing inventory management, improving sales planning, and maximizing revenue. At Japan Weather Association (JWA), we leverage proprietary weather data together with product sales data to deliver highly accurate demand forecasts. With JWA’s demand forecasting, companies can both maximize sales opportunities and reduce inventory-related costs.

This article introduces the mechanism behind JWA’s high-precision product demand forecasting using weather data. The impact of demand forecasting, industry-specific use cases, and our initiatives to further improve accuracy will be covered in Part 2, scheduled for release on December 8, 2025.

Key Points of This Article

• High-accuracy demand forecasting powered by weather data × sales data
  By combining JWA’s weather data with historical sales performance, we achieve highly precise product demand forecasts.
• High-precision weather forecasts enable high-precision demand forecasts
  JWA’s proprietary forecasting models provide an accurate understanding of weather trends up to two years ahead.

Table of Contents

1. How Weather Shapes Consumer Behavior and the Importance of Product Demand Forecasting

• With extreme weather events occurring worldwide, industries such as energy, retail, food, and agriculture are increasingly affected by weather-related risks.
• Weather is one of the few areas in which future conditions can be predicted using physical models. If demand can be forecast in advance, companies can gain many benefits, including more accurate sales projections, optimized inventory, and reduced costs.
• Consumer behavior is strongly influenced by weather factors such as temperature and precipitation.

• Accurately capturing external factors such as weather and seasonal variations is becoming increasingly important for future supply chain optimization.

2. JWA’s Demand Forecasting Methodology

• Forecasting Based on Past Sales Data × Weather Data
  • Step 1: Visualizing the correlation between weather data and product sales
    By analyzing sales data for multiple products together with weather data, JWA visualizes how sales patterns are related to weather conditions across different seasons and regions.
  • Step 2: Building demand forecasting models for each product
    JWA gathers and organizes all data necessary for analysis, conducts the analysis, and builds the demand forecasting models.
  • Step 3: Providing Information
    Based on the constructed forecasting models, JWA delivers information that can be applied to sales and inventory planning.

For more details, please click: Product Demand Forecasting

• Using the Industry’s First Long-Term Weather Forecast Data Up to Two Years Ahead
  • With the advice and cooperation of Professor Hiroaki Ueda at the University of Tsukuba, JWA has developed a new seasonal forecasting method for Japan using machine learning. This method incorporates indicators such as convective activity and sea surface temperatures in the tropical and subtropical regions, which have a high correlation with Japan’s weather. As a result, forecasts of unusual weather patterns are now possible more than a year in advance—such as extreme winter warmth or record-breaking summer heat—which was previously considered difficult to predict. Furthermore, forecast accuracy has also improved significantly, with prediction errors at a six-month lead time reduced by up to 40% compared with the traditional method (which forecast only up to six months ahead).
  • This “2-Year Long-Term Weather Forecast” is already being utilized in industries such as power and apparel. For example, in the power industry, it has become possible to forecast power supply and demand more than a year in advance with smaller errors—something that was previously difficult to achieve. By applying these forecasts to their operational and procurement planning, power generation companies and electricity retail companies can expect greater efficiency and reduced costs.

For more details on “2-Year Long-Term Weather Forecast,” please click: What are Long-Term Forecasts? JWA’s Proprietary “2-Year Long-Term Weather Forecast” and Its Business Applications Part 1 / Part 2

3. JWA’s Weather Forecast Accuracy: The Foundation of Reliable Demand Forecasts

• JWA Blend of Models
  • In 2024, the “JWA Blend of Models” achieved higher accuracy than forecasts issued by the Japan Meteorological Agency (JMA) for both “accuracy rate of precipitation forecasts on the day” and “accuracy rate of hourly weather forecasts for the following day.”
  • For maximum and minimum temperature forecasts up to seven days ahead, the forecasts from “JWA Blend of Models” consistently showed smaller errors and higher accuracy compared with JMA’s forecasts.

For details of “JWA Blend of Models,” please click: Technology

For details of forecast accuracy, please click: 2024 Japan Weather Association’s Forecast Accuracy Verification Results

• 2-Year Long-Term Weather Forecast
  • In its Weather Marketing Report: 2025 Weather Outlook – A Colder Winter Followed by Early Spring, and a Hot Summer with Sharp Contrasts (Only Available in Japanese) issued on December 20, 2024, Japan Weather Association predicted “an early end to the rainy season”, “extremely hot summer temperatures”, and “a lingering late-summer heat.”
  • In fact, the 2025 summer season saw a record-early end to the rainy season and the hottest summer on record, followed by a prolonged period of severe lingering late-summer heat. As of December 2024, Japan Weather Association was able to forecast the general summer trend.

For information on the accuracy and use cases of the 2-Year Long-Term Weather Forecast, please click: “ Accuracy and Use Cases of the Two-Year Long-Term Weather Forecast – Capturing the Remarkable Extreme Heat of Summer 2025 in Advance and Contributing to Preparedness for ‘Weather Risks in Business’ ” (Only Available in Japanese)

4. Conclusion

JWA’s product demand forecasting is a weather-data-driven service that supports inventory optimization, maximization of sales opportunities, and cost reduction.

The effects of demand forecasting, industry-specific use cases, and efforts to improve accuracy will be covered in Part 2, scheduled for release on December 8, 2025.

For more details on product demand forecasting, please click: Product Demand Forecasting

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