Asymmetric trends of extreme temperature over the Loess Plateau during 1998–2018

Abstract

A slowdown in the warming rate of the global mean surface temperature has been observed since late 1990s. However, it is still controversial whether the spatiotemporal variability of extreme temperature events will increase after global warming slowdown, and whether the regional diversity of change trends will increase. Here, we investigated the variations in extreme temperature indices over the Loess Plateau in China since 1961 and focused on the recent global warming slowdown (1998-2018). We found that, during 1961-2018, all the extreme temperature indices showed a significant warming trend and its intensity varied according to extreme temperature indices over different regions. A warming slowdown of annual mean temperature during 1998-2018 was primarily due to the slight increases of annual mean maximum temperatures (TXm) while the annual mean minimum temperature (TNm) still indicated prominently warming trends. During the recent warming slowdown period, the warm indices showed continued intensification of the warming trends, while the cold indices showed a slight cooling trend. Moreover, all extreme temperature indices showed the largest warming trend in summer and a slight cooling trend in winter. Overall, the extreme temperature events have become more diverse in spatial and temporal, indicating that regional climate are more unstable than previously reported for this region. Further analyses revealed that the extreme temperature events during the recent warming slowdown Zhiyong Ding and Jia Pu contributed equally to this study.

Analysis of Extreme Temperature Variations on the Yunnan-Guizhou Plateau in Southwestern China over the Past 60 Years

“…We carried out data quality control before the calculation of extreme indices due to differences in meteorological data from different stations, instruments and data acquisition procedures. Criteria for quality control included: replacement of all missing values (originally coded as −99.9) with an internal format recognized by the R statistical software; elimination of any negative differences between the daily maximum and minimum temperatures; outlying of a threshold determined by the mean value ± 3 standard deviations [19,22,23]. Once datasets were quality controlled, the spatial coverage, completeness, and homogeneity of the datasets had to be evaluated as climatic time series often modifications in terms of station location, instrumentation, or observation procedures.…”

“…To examine the nonlinear trend in each extreme temperature index of each station, the nonparametric Mann-Kendall (M-K) test was employed [30,31]. The M-K test, recommended by the WMO, is a powerful trend detection method that is widely used in meteorological and hydrological time-series analyses in different parts of the world [23,25,32,33]. To further investigate whether there is a change in the variations of temperature extremes in different periods, the whole period (1960-2019) was divided into two periods of 1960-1989 and 1990-2019 in this study.…”

Nonstationarity in High and Low‐Temperature Extremes: Insights From a Global Observational Data Set by Merging Extreme‐Value Methods

“…(2018) used classic statistical approaches (Annual Maxima) to define the extreme temperature series and their trends globally. A plethora of regional studies have recently surfaced aiming to assess extreme temperature trends mainly in Asia (Ahmad et al., 2023; Ding et al., 2021; Ma et al., 2022; Om et al., 2022; Wang et al., 2021; Yatim et al., 2019; Yosef et al., 2019; S. Zhang et al., 2022), but also Latin America (Meseguer‐Ruiz et al., 2019; Ruiz‐Alvarez et al., 2020; Sanches et al., 2023), Europe (Tošić et al., 2023) Antarctica (Wei et al., 2019), and New Zealand (Caloiero, 2017), among other regions. Here we use an alternative method (H1‐L1) for obtaining the extreme value series and assess global changes in extreme temperature.…”

Impacts of large-scale circulation patterns on the temperature extremes in the cold regions of China with global warming

“…Climate change has had different impacts on temperature at varying time scales (from seasonal to multidecadal). Compared with the average temperature, the changes in temperature extremes can better reflect the overall situation of climate systems, and great achievements have been achieved in the recent decades with regard to temperature extreme changes (Alexander et al, 2006;You et al, 2013;Alexander and Arblaster, 2017;Dong et al, 2019;Ding et al, 2021). Meanwhile, temperature extremes are also closely related to local ecosystems and human health, as extreme cold waves and heat waves affect the critical temperature tolerance conditions of humans, animals, and plants, resulting in damages to agriculture and pastures and in human life threats (Zhou C. et al, 2020;Yu et al, 2020;Li et al, 2022).…”

“…This makes the region ideal for researchers to study climate change. However, most previous studies have focused on the changes in the temperature extremes only in some parts of China (Li et al, 2010;Li et al, 2012;You et al, 2013;Deng et al, 2014;Sun W. et al, 2016;Tong et al, 2019;Ding et al, 2021), and the researches on the temperature extremes in the whole CRC are relatively scarce (Yin et al, 2019;Zhou Z. et al, 2020), Moreover, the studies on the latest observational data did not consider the whole CRC. There have only been a few studies on the statistical relationships between temperature extremes and ocean-atmospheric interaction circulation patterns (You et al, 2013;Shi et al, 2018a;Zhou Z. et al, 2020;Ding et al, 2021).…”