Spatiotemporal dynamics of annual, seasonal, and extreme temperature over upper Indus basin

Ahmad, Ijaz; Li, Wang; Zhang, Fan

doi:10.1007/s00704-022-04310-2

Cited by 1 publication

(1 citation statement)

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“…(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.…”

Section: Discussionmentioning

confidence: 99%

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

Nerantzaki,

Papalexiou,

Rajulapati

et al. 2023

Earth's Future

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We merge classical extreme value methods to extract high (high temperatures (HT)) and low (low temperatures (LT)) temperatures and form time series having at least one extreme value per year. Observed daily maximum and minimum temperature records are used from 4,797 quality‐controlled, global, surface stations over 1970–2019. We assess changes in the magnitude and frequency of extreme temperatures by introducing and applying novel methods that exploit the definition of stationarity. Analysis shows significant increasing (40.6% of the stations) and decreasing (41.1%) trends in the frequency of high and LT, respectively, and increasing trends in both high‐ and low‐temperature values (35.6% and 49.7%). Globally, HT and LT frequencies are increasing and decreasing, respectively, by 0.9% and 1.1% per year, relative to the expected frequencies under the assumption of stationarity. The global mean annual HT and LT magnitudes are increasing by 0.004 and 0.016°C/year compared to the expected ones under stationarity. The results indicate that the assumption of stationarity fails to explain the observed changes. The proposed methods are an alternative approach to classical extreme value methods and a useful tool to reveal changes in extremes in the era of earth‐system change.

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