Abstract: As a core discipline linking meteorological conditions and agricultural production, agrometeorology is foundational for ensuring national food security and sustainable agricultural development. Since its establishment in 1956, Chinese Academy of Meteorological Sciences (CAMS) has consistently prioritized agrometeorological research as priority development areas. Its evolution can be categorized into 4 main phases: Initial establishment and exploration (during the year of 1956-1982), integration of scientific research with operational services (during the year of 1982-2002), the innovation and enhancement phase (during the year of 2002-2024), and high-quality development phase (since the year of 2024). A comprehensive disciplinary system has been developed, encompassing basic observation, technological innovation, theoretical breakthroughs, and operational services. Over the past 70 years, a series of remarkable achievements have been achieved in agrometeorology.
In the field of agricultural climatic resources research, CAMS has completed multi-level agricultural climatic zonation across the country, clarifying spatiotemporal distribution patterns of light, heat, water, and other key climatic resources. On this basis, a quality evaluation model for agricultural climatic resource has been developed. These innovative achievements have been recognized with National Science and Technology Progress Awards.
In the field of climate change impacts research, CAMS has analyzed spatiotemporal evolutionary characteristics of agricultural climatic resources under future climate scenarios. Subsequently, mechanisms affecting crop cultivation systems, growth, development, and yield have been revealed, and several adaptation strategies have been proposed.
In the field of agrometeorological disasters research, CAMS has established over 30 agrometeorological disaster indicators by incorporating advanced approaches such as 3S technology and artificial intelligence. Some of these indicators have been adopted and issued as national or industry standards. Furthermore, a technical system for dynamic monitoring and early warning of agrometeorological disasters has been established, achieving a warning accuracy exceeding 80%.
In the field of crop yield forecasting, a methodological system for agrometeorological yield statistical forecasting and remote sensing-based yield estimation has been established, delivering a forecasting accuracy of over 95%. This system supports the national operational service for crop yield forecasting. Moreover, Chinese Agricultural Meteorology Model (CAMM) has been independently developed and upgraded from version 1.0 to 3.0. At present, CAMM enables operational monitoring and prediction for six crops at a 5-km grid scale. Gucheng Ecological and Agrometeorological Experiment Station also provides long-term in-situ observations and strong technical support.
In the future, agrometeorological research should focus on deepening compound meteorological disaster mechanisms, promoting the integrated application of new technologies, transforming scientific research achievements, and expanding international cooperation, thereby continuously empower the high-quality development of agrometeorology.