A dataset of automatic observations of wind speed and wind direction in the typical agricultural ecosystem of the hilly region in the Sichuan Basin (2004–2022)

Wind direction and wind speed have significant impacts on the water cycle, material and energy balance, and microclimate of agricultural ecosystems. They are indispensable key driving variables for the development and validation of ecosystem models (such as hydrological models, carbon cycle models, and pollutant dispersion models). In climate change research, monitoring long-term trends in wind speed and direction can help improve our understanding of how climate change affects atmospheric circulation and the frequency of extreme weather events, thereby assessing its potential impacts on ecosystem structure and function. However, there is a lack of long-term observational datasets of wind direction and wind speed for typical agricultural ecosystems in the hilly regions of the subtropical Sichuan Basin. The Yanting Station is located in the hilly agricultural ecosystem region of the subtropical Sichuan Basin and serves as a foundational, public-interest agricultural ecosystem experimental observation and research platform within the Chinese Ecosystem Research Network and the National Field Science Observation and Research Network, representing an important observation site in the upper reaches of the Yangtze River. This dataset is compiled and calculated based on long-term networked observations collected by the automated meteorological observation system at Yanting Station. After primary quality control at the field station and secondary quality control and review by the Atmospheric Sub-Center, the authenticity, reliability, and uniformity of the observational data format are ensured, and the data are highly comparable to those collected from other networked automatic observation stations. The dataset includes hourly, daily, and monthly values for wind direction and wind speed deprived from 2-minute, 10-minute, and one-hour observations, as well as related calculated values. It provides data support for research into the material and energy balances in agricultural ecosystems under changing microclimatic conditions and their potential impacts on ecosystem structure and function.