Tree-ring maximum latewood density reveals unprecedented warming and long-term summer temperature in the upper Indus Basin, northern Pakistan

Abstract

Understanding long-term temperature variability in the Upper Indus Basin (UIB), northern Pakistan, and its driving mechanisms is challenging due to the scarcity of long observational records and available literature. In this study, we reconstructed a 651-year (1370–2020 CE) warm-season (March–September) temperature record using the tree-ring maximum latewood density (MXD) of blue pine (Pinus wallichiana). The reconstruction explains 57 % of the variance in actual temperature during the common calibration period (1972–2020 CE). Our analysis identified ten high-temperature periods (temperature > 20.9 °C) and nineteen low-temperature periods (temperature < 19.8 °C), with the coldest years being 1392, 1707, 1817, and 1837, and the warmest years being 2013, 2016, 2017, and 2018. Spatial correlation analysis reveals a significant positive correlation with field temperature, predominantly in neighboring regions, and a significant negative correlation with relative humidity and precipitation. Multi-taper spectral analysis shows inter-annual (1.9, 2.5, 2.7, 5.5 years) and interdecadal (11, 18, 23, 25, 40, 71 years) cycles, suggesting a potential linkage with the Atlantic Multidecadal Oscillation (AMO). The negative linkage between our reconstruction and the region's standardized Palmer Drought Severity Index (scPDSI) indicates that continued temperature increase could result in severe drought in northern Pakistan in the near future. During the 20th century, the UIB experienced two distinct warming phases: 1948–1970 CE and 1994–2020 CE. The warming rate during 1994–2020 CE was 0.5 °C higher, indicating unprecedented recent warming. The reconstructed temperature record also demonstrates a large-scale spatiotemporal signal and a strong connection with most recorded volcanic eruptions. These findings enhance our understanding of long-term temperature variability in the region, highlighting the significance of MXD in reconstructing past temperature patterns.