干旱区生态环境知识资源中心(Arid): Spatiotemporal Assessment of Temperature Data Products for the Detection of Warming Trends and Abrupt Transitions over the Largest Irrigated Area of Pakistan

Arid

DOI	10.1155/2020/3584030
	Spatiotemporal Assessment of Temperature Data Products for the Detection of Warming Trends and Abrupt Transitions over the Largest Irrigated Area of Pakistan
	Nawaz, Zain; Li, Xin; Chen, Yingying; Wang, Xufeng; Zhang, Kun; Nawaz, Naima; Guo, Yanlong; Meerzhan, Akynbekkyzy
通讯作者	Chen, YY
来源期刊	ADVANCES IN METEOROLOGY
ISSN	1687-9309
EISSN	1687-9317
出版年	2020
卷号	2020
英文摘要	Reliable and accurate temperature data acquisition is not only important for hydroclimate research but also crucial for the management of water resources and agriculture. Gridded data products (GDPs) offer an opportunity to estimate and monitor temperature indices at a range of spatiotemporal resolutions; however, their reliability must be quantified by spatiotemporal comparison against in situ records. Here, we present spatial and temporal assessments of temperature indices (T-max, T-min, T-mean, and DTR) products against the reference data during the period of 1979-2015 over Punjab Province, Pakistan. This region is considered as a center for agriculture and irrigated farming. Our study is the first spatiotemporal statistical evaluation of the performance and selection of potential GDPs over the study region and is based on statistical indicators, trend detection, and abrupt change analysis. Results revealed that the CRU temperature indices (T-max, T-min, T-mean, and DTR) outperformed the other GDPs as indicated by their higher CC andR(2)but lower bias and RMSE. Furthermore, trend and abrupt change analysis indicated the superior performances of the CRUTmin and T-mean products. However, the T-max and DTR products were less accurate for detecting trends and abrupt transitions in temperature. The tested GDPs as well as the reference data series indicate significant warming during the period of 1997-2001 over the study region. Differences between GDPs revealed discrepancies of 1-2 degrees C when compared with different products within the same category and with reference data. The accuracy of all GDPs was particularly poor in the northern Punjab, where underestimates were greatest. This preliminary evaluation of the different GDPs will be useful for assessing inconsistencies and the capabilities of the products prior to their reliable utilization in hydrological and meteorological applications particularly over arid and semiarid regions.
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000572069100001
WOS关键词	PRECIPITATION DATASETS ; AIR-TEMPERATURE ; UNITED-STATES ; RIVER-BASIN ; CLIMATE ; RAINFALL ; REGION ; VARIABILITY ; STREAMFLOW ; NORTHWEST
WOS类目	Meteorology & Atmospheric Sciences
WOS研究方向	Meteorology & Atmospheric Sciences
来源机构	中国科学院青藏高原研究所
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/326463
作者单位	[Nawaz, Zain; Wang, Xufeng; Meerzhan, Akynbekkyzy] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Remote Sensing Gansu Prov, Lanzhou 730000, Peoples R China; [Nawaz, Zain; Wang, Xufeng; Meerzhan, Akynbekkyzy] Univ Chinese Acad Sci, Beijing 100049, Peoples R China; [Li, Xin; Chen, Yingying; Zhang, Kun; Guo, Yanlong] Chinese Acad Sci, Inst Tibetan Plateau Res, Beijing 100101, Peoples R China; [Li, Xin; Chen, Yingying] CAS Ctr Excellence Tibetan Plateau Earth Sci, Beijing 100101, Peoples R China; [Nawaz, Naima] Univ Agr Faisalabad, Dept Rural Sociol, Faisalabad 38040, Pakistan
推荐引用方式 GB/T 7714	Nawaz, Zain,Li, Xin,Chen, Yingying,et al. Spatiotemporal Assessment of Temperature Data Products for the Detection of Warming Trends and Abrupt Transitions over the Largest Irrigated Area of Pakistan[J]. 中国科学院青藏高原研究所,2020,2020.
APA	Nawaz, Zain.,Li, Xin.,Chen, Yingying.,Wang, Xufeng.,Zhang, Kun.,...&Meerzhan, Akynbekkyzy.(2020).Spatiotemporal Assessment of Temperature Data Products for the Detection of Warming Trends and Abrupt Transitions over the Largest Irrigated Area of Pakistan.ADVANCES IN METEOROLOGY,2020.
MLA	Nawaz, Zain,et al."Spatiotemporal Assessment of Temperature Data Products for the Detection of Warming Trends and Abrupt Transitions over the Largest Irrigated Area of Pakistan".ADVANCES IN METEOROLOGY 2020(2020).