Uncertainty in hottest years ranking: analysis of Tibetan Plateau surface air temperature
Changes in surface air temperature can directly affect hydrology, agriculture, and ecosystems through extreme climate events such as heat waves. For this reason, and to improve climate change adaptation strategies, it is important to investigate the ranking of hottest years. In this study, the Wilco...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2017-07-01
|
| Series: | Atmospheric and Oceanic Science Letters |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/16742834.2017.1330646 |
| _version_ | 1818350945181892608 |
|---|---|
| author | Wei HUA Kai-Qin YANG Guang-Zhou FAN |
| author_facet | Wei HUA Kai-Qin YANG Guang-Zhou FAN |
| author_sort | Wei HUA |
| collection | DOAJ |
| description | Changes in surface air temperature can directly affect hydrology, agriculture, and ecosystems through extreme climate events such as heat waves. For this reason, and to improve climate change adaptation strategies, it is important to investigate the ranking of hottest years. In this study, the Wilcoxon signed-rank test and Monte Carlo simulation are used to estimate the ranking of the hottest years for the Tibetan Plateau (TP) in recent decades, and the uncertainty in the ranking. The Wilcoxon signed-rank test shows that the top 10 hottest years on record over the TP mainly occur after 1998. The top three hottest years are ranked as 2006, 2009, and 2010, but there is almost no significant difference between them. When both sampling and observational errors are considered, only five years have a non-zero probability of being the hottest year, with the three highest probabilities being for the years 2006 (~47.231%), 2009 (~40.390%), and 2010 (~12.376%). Similarly, with respect to a given year that is among the 10 hottest years, our results show that all the years among the ranks of 1–10 resulting from the Wilcoxon signed-rank test have probabilities above 10%, while the years 2001 and 2012 have probabilities of 3% and 4%. |
| first_indexed | 2024-12-13T18:29:54Z |
| format | Article |
| id | doaj.art-c9eb4cd282344db9a44318b7ab24b0dc |
| institution | Directory Open Access Journal |
| issn | 1674-2834 2376-6123 |
| language | English |
| last_indexed | 2024-12-13T18:29:54Z |
| publishDate | 2017-07-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Atmospheric and Oceanic Science Letters |
| spelling | doaj.art-c9eb4cd282344db9a44318b7ab24b0dc2022-12-21T23:35:30ZengKeAi Communications Co., Ltd.Atmospheric and Oceanic Science Letters1674-28342376-61232017-07-0110433734110.1080/16742834.2017.13306461330646Uncertainty in hottest years ranking: analysis of Tibetan Plateau surface air temperatureWei HUA0Kai-Qin YANG1Guang-Zhou FAN2Chengdu University of Information TechnologyChengdu University of Information TechnologyChengdu University of Information TechnologyChanges in surface air temperature can directly affect hydrology, agriculture, and ecosystems through extreme climate events such as heat waves. For this reason, and to improve climate change adaptation strategies, it is important to investigate the ranking of hottest years. In this study, the Wilcoxon signed-rank test and Monte Carlo simulation are used to estimate the ranking of the hottest years for the Tibetan Plateau (TP) in recent decades, and the uncertainty in the ranking. The Wilcoxon signed-rank test shows that the top 10 hottest years on record over the TP mainly occur after 1998. The top three hottest years are ranked as 2006, 2009, and 2010, but there is almost no significant difference between them. When both sampling and observational errors are considered, only five years have a non-zero probability of being the hottest year, with the three highest probabilities being for the years 2006 (~47.231%), 2009 (~40.390%), and 2010 (~12.376%). Similarly, with respect to a given year that is among the 10 hottest years, our results show that all the years among the ranks of 1–10 resulting from the Wilcoxon signed-rank test have probabilities above 10%, while the years 2001 and 2012 have probabilities of 3% and 4%.http://dx.doi.org/10.1080/16742834.2017.1330646Hottest yearsuncertaintyrankingTibetan Plateau |
| spellingShingle | Wei HUA Kai-Qin YANG Guang-Zhou FAN Uncertainty in hottest years ranking: analysis of Tibetan Plateau surface air temperature Atmospheric and Oceanic Science Letters Hottest years uncertainty ranking Tibetan Plateau |
| title | Uncertainty in hottest years ranking: analysis of Tibetan Plateau surface air temperature |
| title_full | Uncertainty in hottest years ranking: analysis of Tibetan Plateau surface air temperature |
| title_fullStr | Uncertainty in hottest years ranking: analysis of Tibetan Plateau surface air temperature |
| title_full_unstemmed | Uncertainty in hottest years ranking: analysis of Tibetan Plateau surface air temperature |
| title_short | Uncertainty in hottest years ranking: analysis of Tibetan Plateau surface air temperature |
| title_sort | uncertainty in hottest years ranking analysis of tibetan plateau surface air temperature |
| topic | Hottest years uncertainty ranking Tibetan Plateau |
| url | http://dx.doi.org/10.1080/16742834.2017.1330646 |
| work_keys_str_mv | AT weihua uncertaintyinhottestyearsrankinganalysisoftibetanplateausurfaceairtemperature AT kaiqinyang uncertaintyinhottestyearsrankinganalysisoftibetanplateausurfaceairtemperature AT guangzhoufan uncertaintyinhottestyearsrankinganalysisoftibetanplateausurfaceairtemperature |