Example of near-term decadal climate trend predictionbased on tree-ring data

Abstract

<p indent=0mm>Accurately predicting future climate is the ultimate goal of palaeoclimate and climatology research, and it is also a hot topic and extremely difficult problem in the current climate field. In particular, the decadal climate prediction in the next <sc>10–30 years</sc> is of great reference value for government decision-making and medium- and long-term planning. However, up to now, there has been no case of near-term decadal climate prediction reported in the literature. The main problem lies in the slow development of long-term climate prediction theory, and the lack of sufficiently long, accurate, high-resolution, precise, and standardized climate proxy indicators. Tree rings have become an important proxy for the study of past climate change due to their high temporal resolution, accurate dating, wide geographical distribution, and strong continuity. Tree-ring-based reconstruction of climate factors (such as precipitation and temperature) over the past few hundred years has been carried out extensively in China. The tree-ring reconstruction series can reflect the local and regional climate factors in past long periods of time. In addition, the tree-ring reconstruction of climate series strictly follows the principles of data length, coherence, analogy, correlation, dynamics, and period required by statistical prediction. Therefore, by using a variety of mathematical analyses, we reconstructed the precipitation series from 1726 to 1997 based on the width of tree-ring latewood in the Mt. Helan region, and also used Caterpillar-Singular Spectrum Analysis (Caterpillar-SSA), a powerful time-series analysis and prediction method. Through the steps of nesting, singular value decomposition, aggregation, diagonal averaging, and extrapolation, the tree-ring time series in the Mt. Helan region were decomposed and the trend was extrapolated to forecast the precipitation trend from 1998 to 2022. The prediction results showed that the peak of precipitation in the Mt. Helan region occurred around 2002, and the precipitation will continue to decrease in the following <sc>10 years.</sc> The precipitation will reach its lowest point in 2013–2014, and will then increase slightly, but it cannot reach the average level of 1970–2002. Today, more than <sc>20 years</sc> later, actual weather observations can be used to objectively evaluate tree-ring prediction results, with the aim of exploring and improving appropriate near-term decadal climate prediction approaches. Results show that the aforementioned prediction result is close to the real precipitation trend in the subsequent <sc>20 years</sc> at several meteorological stations around the research site. The observation records support this prediction result, grasping the changing trend of first becoming wet, then rapidly drying, and then slowly becoming wet. The extreme drought events appearing during 2013–2014 in the prediction were also confirmed by the observations in the Mt. Helan region. The statistical prediction method of tree-ring reconstruction based on the internal relationship can not only give the continuous change trend, but can also predict the time nodes of extreme climate events. The method’s biggest advantage is that it does not need to rely on a mainframe computer for a long-term and large amount of data calculations. To date, to the best of our knowledge, this is the only published example of statistical prediction of the near-term decadal trend of climate change for <sc>20 years</sc> based on tree-ring data, which substantially advances the statistical prediction capabilities of tree-ring climate proxies. In future climate prediction, it is suggested to combine the numerical model prediction method based on dynamic equation solution with the tree-ring statistics method to obtain better prediction results and improve the ability of climate trend prediction. The combination of model and high-resolution reconstruction series will be an important way of improving the accuracy of climate prediction at present and into the future.