Communities that depend extensively on agriculture are experiencing losses in income and crop production due to the rising frequency of extreme weather events. Agro-advisories, which provide accurate weather information in a timely manner, can reduce agricultural losses. In the Solan region, the temperature and rainfall variability were determined by a standardized anomaly index with trend analysis conducted via the MK test and Sen’s slope test for the period of 1991–2022. The Mann–Kendall and Sen’s slope test indicated that annual mean Tmax is significantly increasing (S = 1.23°C yr–1 and Q = 0.02°C yr–1), while Tmin is significantly decreasing (S = –1.49°C yr–1 and Q = –0.01°C yr–1). Therefore, medium-range weather forecasting systems are essential for making informed decisions, sustainable resource management, and disaster preparedness. The Meteorological Centre, Shimla, provided a value-added medium-range weather forecast, which was validated against actual data recorded in the Agrometeorological observatory, UHF Nauni, from 2016–2017 and 2022–2023. The results revealed that the annual correct accuracy of the forecast followed the order of rainfall > wind speed > minimum temperature > relative humidity (M) > maximum temperature > relative humidity (E). With respect to the mean annual rainfall forecast, the accuracy was 70.6%. The mean annual accuracy of Tmax, Tmin, relative humidity (M and E), and wind speed were 41.7, 48.8, 48.3, 39.8, and 66.7%, respectively. The rainfall forecast precision was highest during the post-monsoon season, with an accuracy of 93.8%, while the precision was 30.4% during the southwest monsoon season. Except for morning and evening relative humidity, a higher correct accuracy was depicted during the post-monsoon season for rainfall, Tmax, Tmin, and wind speed. Among the years and seasons, the maximum Hanssen and Kuipers (HK) scores were 0.92 and 0.98, respectively, and the corresponding ratios were 96.74 and 97.83% for the post-monsoon season during 2016–2017 and 2017–2018, respectively. In the region, the trends of correct forecasts increased for maximum and minimum temperatures; however, they decreased for rainfall, relative humidity (M and E), and wind speed. The adoption of services (AAS) by farmers was found to be 78 to 83% satisfactory in different blocks of the Solan district. The analysis of long-term climatic variables reveals a notable shift in climate patterns, underscoring the critical importance of accurate and timely weather forecasts combined with advisories to enable farmers to make informed decisions for crop planning, thereby mitigating weather-induced risks. The dynamic feedback mechanism from farmers prioritizes improvement in weather forecasting models.

Evaluating medium-range weather forecasts for agriculture in Himachal Pradesh’s mid-hill region

期刊论文
发表日期：

2025年6月26日

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Purnima Mehta,
Satish Kumar Bhardwaj

摘要

Communities that depend extensively on agriculture are experiencing losses in income and crop production due to the rising frequency of extreme weather events. Agro-advisories, which provide accurate weather information in a timely manner, can reduce agricultural losses. In the Solan region, the temperature and rainfall variability were determined by a standardized anomaly index with trend analysis conducted via the MK test and Sen’s slope test for the period of 1991–2022. The Mann–Kendall and Sen’s slope test indicated that annual mean T_max is significantly increasing (S = 1.23°C yr^–1 and Q = 0.02°C yr^–1), while T_min is significantly decreasing (S = –1.49°C yr^–1 and Q = –0.01°C yr^–1). Therefore, medium-range weather forecasting systems are essential for making informed decisions, sustainable resource management, and disaster preparedness. The Meteorological Centre, Shimla, provided a value-added medium-range weather forecast, which was validated against actual data recorded in the Agrometeorological observatory, UHF Nauni, from 2016–2017 and 2022–2023. The results revealed that the annual correct accuracy of the forecast followed the order of rainfall > wind speed > minimum temperature > relative humidity (M) > maximum temperature > relative humidity (E). With respect to the mean annual rainfall forecast, the accuracy was 70.6%. The mean annual accuracy of T_max, T_min, relative humidity (M and E), and wind speed were 41.7, 48.8, 48.3, 39.8, and 66.7%, respectively. The rainfall forecast precision was highest during the post-monsoon season, with an accuracy of 93.8%, while the precision was 30.4% during the southwest monsoon season. Except for morning and evening relative humidity, a higher correct accuracy was depicted during the post-monsoon season for rainfall, T_max, T_min, and wind speed. Among the years and seasons, the maximum Hanssen and Kuipers (HK) scores were 0.92 and 0.98, respectively, and the corresponding ratios were 96.74 and 97.83% for the post-monsoon season during 2016–2017 and 2017–2018, respectively. In the region, the trends of correct forecasts increased for maximum and minimum temperatures; however, they decreased for rainfall, relative humidity (M and E), and wind speed. The adoption of services (AAS) by farmers was found to be 78 to 83% satisfactory in different blocks of the Solan district. The analysis of long-term climatic variables reveals a notable shift in climate patterns, underscoring the critical importance of accurate and timely weather forecasts combined with advisories to enable farmers to make informed decisions for crop planning, thereby mitigating weather-induced risks. The dynamic feedback mechanism from farmers prioritizes improvement in weather forecasting models.