{"title":"全球高原降水动态及其与可能驱动因素的相互作用","authors":"Haider Abbas , Azfar Hussain , Ming Xu","doi":"10.1016/j.gloplacha.2024.104529","DOIUrl":null,"url":null,"abstract":"<div><p>The climate and ecosystem in the highland regions are fragile and vulnerable to climate change. This study used ERA5, CRU, and CHIRPS at 0.5° × 0.5° resolution to assess spatiotemporal precipitation trends over global highlands from 1981 to 2021. The Standardized anomaly index (SAI) is used to evaluate the comparative anomalies between the datasets, while the Mann-Kendall and Sen Slope estimator tests the precipitation trends. Empirical orthogonal function (EOF), pixel-wise correlation, and detrended cross-correlation (DCCA) were employed to investigate the dominant precipitation patterns and their relationships with regional climatic impacts, while the wavelet analysis determines ocean-atmospheric factors in the time-frequency domain. The SAI correlation strongly relates to CRU-CHIRPS for precipitation estimates in North America (NA) R<sup>2</sup> = 0.84, Europe R<sup>2</sup> = 0.71, and South America (SA), whereas CRU-ERA5 showed better results in the Asian highlands R<sup>2</sup> = 0.29, highlighting regional differences in the precipitation dynamics. For precipitation, EOF1 showed a positive variance in most highland regions, but a negative variance prevailed in the Tibetan Plateau (TP), whereas EOF1–2 explained ∼32%, 33%, and 30% variance globally for ERA, CRU, and CHRIPS, respectively. A strong positive correlation is observed between precipitation and mean temperature (TMP) in North America (NA) and the European Alps. However, a significant negative correlation prevailed in the TP and some parts of NA, indicating that these factors can significantly influence the precipitation dynamics in the highlands. Additionally, Detrended Cross-Correlation Analysis (DCCA) has verified that there are positive correlations between precipitation and key climatic factors such as total column water vapor (TCWV), potential evaporation (PEV), and soil moisture (SM). In addition, the influence of ocean-atmospheric (interannual and decadal) coherence patterns originating from the Pacific and Atlantic Oceans indicates a significant impact on precipitation variability, especially in the Asian highlands. This study can contribute to a better understanding of mechanisms and serve as a reference for forecasting precipitation dynamics to develop corresponding strategies in global highlands.</p></div>","PeriodicalId":55089,"journal":{"name":"Global and Planetary Change","volume":"240 ","pages":"Article 104529"},"PeriodicalIF":4.0000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Precipitation dynamics and its interactions with possible drivers over global highlands\",\"authors\":\"Haider Abbas , Azfar Hussain , Ming Xu\",\"doi\":\"10.1016/j.gloplacha.2024.104529\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The climate and ecosystem in the highland regions are fragile and vulnerable to climate change. This study used ERA5, CRU, and CHIRPS at 0.5° × 0.5° resolution to assess spatiotemporal precipitation trends over global highlands from 1981 to 2021. The Standardized anomaly index (SAI) is used to evaluate the comparative anomalies between the datasets, while the Mann-Kendall and Sen Slope estimator tests the precipitation trends. Empirical orthogonal function (EOF), pixel-wise correlation, and detrended cross-correlation (DCCA) were employed to investigate the dominant precipitation patterns and their relationships with regional climatic impacts, while the wavelet analysis determines ocean-atmospheric factors in the time-frequency domain. The SAI correlation strongly relates to CRU-CHIRPS for precipitation estimates in North America (NA) R<sup>2</sup> = 0.84, Europe R<sup>2</sup> = 0.71, and South America (SA), whereas CRU-ERA5 showed better results in the Asian highlands R<sup>2</sup> = 0.29, highlighting regional differences in the precipitation dynamics. For precipitation, EOF1 showed a positive variance in most highland regions, but a negative variance prevailed in the Tibetan Plateau (TP), whereas EOF1–2 explained ∼32%, 33%, and 30% variance globally for ERA, CRU, and CHRIPS, respectively. A strong positive correlation is observed between precipitation and mean temperature (TMP) in North America (NA) and the European Alps. However, a significant negative correlation prevailed in the TP and some parts of NA, indicating that these factors can significantly influence the precipitation dynamics in the highlands. Additionally, Detrended Cross-Correlation Analysis (DCCA) has verified that there are positive correlations between precipitation and key climatic factors such as total column water vapor (TCWV), potential evaporation (PEV), and soil moisture (SM). In addition, the influence of ocean-atmospheric (interannual and decadal) coherence patterns originating from the Pacific and Atlantic Oceans indicates a significant impact on precipitation variability, especially in the Asian highlands. This study can contribute to a better understanding of mechanisms and serve as a reference for forecasting precipitation dynamics to develop corresponding strategies in global highlands.</p></div>\",\"PeriodicalId\":55089,\"journal\":{\"name\":\"Global and Planetary Change\",\"volume\":\"240 \",\"pages\":\"Article 104529\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Global and Planetary Change\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0921818124001760\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOGRAPHY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global and Planetary Change","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0921818124001760","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
Precipitation dynamics and its interactions with possible drivers over global highlands
The climate and ecosystem in the highland regions are fragile and vulnerable to climate change. This study used ERA5, CRU, and CHIRPS at 0.5° × 0.5° resolution to assess spatiotemporal precipitation trends over global highlands from 1981 to 2021. The Standardized anomaly index (SAI) is used to evaluate the comparative anomalies between the datasets, while the Mann-Kendall and Sen Slope estimator tests the precipitation trends. Empirical orthogonal function (EOF), pixel-wise correlation, and detrended cross-correlation (DCCA) were employed to investigate the dominant precipitation patterns and their relationships with regional climatic impacts, while the wavelet analysis determines ocean-atmospheric factors in the time-frequency domain. The SAI correlation strongly relates to CRU-CHIRPS for precipitation estimates in North America (NA) R2 = 0.84, Europe R2 = 0.71, and South America (SA), whereas CRU-ERA5 showed better results in the Asian highlands R2 = 0.29, highlighting regional differences in the precipitation dynamics. For precipitation, EOF1 showed a positive variance in most highland regions, but a negative variance prevailed in the Tibetan Plateau (TP), whereas EOF1–2 explained ∼32%, 33%, and 30% variance globally for ERA, CRU, and CHRIPS, respectively. A strong positive correlation is observed between precipitation and mean temperature (TMP) in North America (NA) and the European Alps. However, a significant negative correlation prevailed in the TP and some parts of NA, indicating that these factors can significantly influence the precipitation dynamics in the highlands. Additionally, Detrended Cross-Correlation Analysis (DCCA) has verified that there are positive correlations between precipitation and key climatic factors such as total column water vapor (TCWV), potential evaporation (PEV), and soil moisture (SM). In addition, the influence of ocean-atmospheric (interannual and decadal) coherence patterns originating from the Pacific and Atlantic Oceans indicates a significant impact on precipitation variability, especially in the Asian highlands. This study can contribute to a better understanding of mechanisms and serve as a reference for forecasting precipitation dynamics to develop corresponding strategies in global highlands.
期刊介绍：
The objective of the journal Global and Planetary Change is to provide a multi-disciplinary overview of the processes taking place in the Earth System and involved in planetary change over time. The journal focuses on records of the past and current state of the earth system, and future scenarios , and their link to global environmental change. Regional or process-oriented studies are welcome if they discuss global implications. Topics include, but are not limited to, changes in the dynamics and composition of the atmosphere, oceans and cryosphere, as well as climate change, sea level variation, observations/modelling of Earth processes from deep to (near-)surface and their coupling, global ecology, biogeography and the resilience/thresholds in ecosystems.
Key criteria for the consideration of manuscripts are (a) the relevance for the global scientific community and/or (b) the wider implications for global scale problems, preferably combined with (c) having a significance beyond a single discipline. A clear focus on key processes associated with planetary scale change is strongly encouraged.
Manuscripts can be submitted as either research contributions or as a review article. Every effort should be made towards the presentation of research outcomes in an understandable way for a broad readership.
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