Identifying temporal trend patterns of temperature means and extremes over the Central Highlands, Vietnam

• Published in: Meteorology and atmospheric physics Vol. 134; no. 3
• Main Authors: Phuong, Dang Nguyen Dong, Huyen, Nguyen Thi, Tu, Le Hoang, Ha, Phan Thi, Nhat, Tran Thong, Loi, Nguyen Kim
• Format: Journal Article
• Language: English
• Published: Vienna Springer Vienna 01-06-2022; Springer Nature B.V
• Subjects: Aquatic Pollution; Atmospheric Sciences; Climate action; Daily temperatures; Earth and Environmental Science; Earth Sciences; Highlands; Math. Appl. in Environmental Science; Meteorology; Minimum temperatures; Original Paper; Slopes; Statistical analysis; Temperature; Temperature extremes; Temperature index; Terrestrial Pollution; Tests; Trend analysis; Trends; Waste Water Technology; Water Management; Water Pollution Control; Vietnam
• ISSN: 0177-7971; 1436-5065
• DOI: 10.1007/s00703-022-00886-6

Conducting an in-depth quantification of warming conditions in a given region is crucially conducive to devising more informed, credible, and effective climate actions. The traditional approach commonly is to apply a single monotonic trend test for specified beginning and ending times within a predetermined period, which is sensitive to the analyzed period. Thus, the present study aimed to apply multiple non-parametric statistical trend tests to the observed daily mean, maximum, and minimum temperature records at 12 sites located proportionally to the whole extent of the Central Highlands, Vietnam. This approach was implemented by performing Sen’s slope estimator and block bootstrapping Mann–Kendall tests repeatedly with various beginning and ending years for all possible periods of at least 10 years in length during 1980–2019. This study also delved into non-monotonic trend components in temperature means and extremes by employing an innovative trend analysis (ITA) methodology. The outcomes indicated significant warming trends in the annual mean, maximum, and minimum temperatures, with the estimated trend slopes varying mainly from 0.30–0.43, 0.09–0.25, and 0.41–0.52 °C/decade, respectively. Most extreme temperature indices (i.e., Max Tmin, Min Tmin, warm spell duration indicator, warm days/nights) were characterized mainly by positive trends. The results also pointed out higher warming levels in the annual mean and minimum temperatures than the annual maximum one, and likewise, most extreme temperature indices deriving from daily minimum temperature exhibited faster rates than those from maximum one. These findings highlight the superiority of applying the multiple trend tests and ITA method to clarify temporal trend patterns.