Abstract
Relative Humidity (RH) in the arid region of the Tarim Basin is crucial for many reasons. The Tarim Basin has experienced a tendency to become wetter in recent decades, and the RH there also shows an increase over the past decade. However, there has been little examination of these RH changes and especially the changes to the extremes. This study investigates the changes in extreme values and the probability density function (PDF) of summer RH using quantile regression during 2006–2018 to understand the possible reasons for the increase in the summer RH anomaly. We find that extremely high values of RH show a consistent significant increase, while extremely low values have no regionally consistent tendency. The overall average value of RH in the Tarim Basin becomes higher, contributed by the upper half of the PDF. To explore the physical mechanism for these changes, we examine the corresponding regional meteorological anomaly patterns. The patterns indicate that the anomalous southwesterly airflow at 500hPa brings ample moisture into the basin and the ground in the middle of the basin significantly cools down when an extreme wet event occurs, promoting the occurrence of the extreme high RH. In this process, the contributions of water vapor transport and temperature are of equal significance though with different relative timing. These corresponding regional meteorological patterns occur more often in the most recent decade, which coincides with the recent increase in RH extremes in this region.
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Acknowledgements
Author Nian and Fu acknowledge support from the National Natural Science Foundation of China (no. 41675049). This work is also supported in part by a scholarship from the China Scholarship Council (no. 201906010222). We thank Peter Huybers for providing the code for quantile regression.
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Appendix: Methods used to detect the starting point of the recent trend in RH
Appendix: Methods used to detect the starting point of the recent trend in RH
1.1 Sequential Mann–Kendall test
To identify a change point in the summer RH time series, the sequential Mann–Kendall (SQMK) test is adopted. Based on Mann–Kendall test, Sneyers (1991) introduced sequential values to help determine the approximate year of the beginning of a significant trend. This method calculates forward and backward sequences of the test statistic and enables detection of the approximate change point of a trend from the intersection point of the two sequences. The SQMK method is frequently used to identify trend start points (Yang and Tian 2009). For more details and algorithms see Nasri and Modarres (2009).
1.2 Standard normal homogeneity test
We also use another method, the standard normal homogeneity test (SNHT), to check the change point. This technique identifies 2005 as the change point year. Our other results are not sensitive to this distinction; selecting 2005 as the starting year yields similar patterns and tendencies. The SNHT was first applied in climate science by Alexandersson (1986). The non-parametric variant of the SNHT is a popular and effective way to detect a change point (Salehi et al. 2020). Under the null hypothesis, the annual means of summer RH are assumed independent and identically distributed and thus the series is homogeneous. Then the test can detect the year where a break occurs (Kang and Yusof 2012). The details of this method can be found in Pohlert (2020).
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Nian, D., Linz, M., Mooring, T.A. et al. The changing extreme values of summer relative humidity in the Tarim Basin in northwestern China. Clim Dyn 58, 3527–3540 (2022). https://doi.org/10.1007/s00382-021-06110-2
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DOI: https://doi.org/10.1007/s00382-021-06110-2