Trends in temperature data: Micro-foundations of their nature
通过分析单个温度网格的数据，发现全球平均温度围绕一个带有一次结构突变的线性确定性趋势呈平稳过程，这对气候变化检测和预测研究有重要意义。
Determining whether Global Average Temperature (GAT) is an integrated process of order 1, I(1), or a stationary process around a trend function is crucial for detection, attribution, impact, and forecasting studies of climate change. In this paper, we investigate the nature of trends in GAT building on the analysis of individual temperature grids. Our micro-founded evidence suggests that GAT is stationary around a non-linear deterministic trend in the form of a linear function with one structural break. This break can be attributed to a combination of breaks on individual grids and the standard aggregation method under acceleration in global warming. • The nature of temperature trends is crucial for climate studies. • Stochastic or deterministic trends in average temperature are typically assumed. • Individual-grids analysis indicates deterministic trends with breaks. • Aggregation method may generate ADF unit roots and deepen structural breaks in data. • Accounting for structural breaks is key for valid unit root tests.