气候变化领域集成服务门户(CCPortal): A dynamic linear model of monthly minimum and maximum temperature changes in three physiographic regions of the Central Himalayas

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DOI	10.3354/cr01582
	A dynamic linear model of monthly minimum and maximum temperature changes in three physiographic regions of the Central Himalayas
	Regmi B.; Lamichhane S.
发表日期	2019
ISSN	0936-577X
起始页码	1
结束页码	8
卷号	79 期号:1
英文摘要	Robust statistical techniques are required to estimate the trend in meteorological data, where data are available only for a limited period with too many missing observations. We examined the application of a dynamic linear model (DLM) for estimating changes in time series meteorological data. For this purpose, we used maximum and minimum monthly temperatures recorded over 36 yr at 6meteorological stations representing 3 physiographic regions in the Central Himalayas. Temperature changes over time may be influenced by hidden processes, such as seasonality. To elucidate such processes, we estimated a Fourier-form seasonal model with 12 seasons with 2 harmonics. TheDLMmodel fit was evaluated based on the distribution of standardized residuals and the p-value of Ljung-Box statistics.We reported the level of temperature change from 1980 to 2015. TheDLMresults were compared with more conventional, simple linear regression analysis (SLR). Although a significant trend of temperature increase was observed in the Central Himalayas, the change was not uniform across the physiographic regions. Localized changes in temperature levelsmay be due to geographic configuration and micro-climate. Notably, the SLR showed a similar trend of average annual temperature change to that of the DLM but overestimated the magnitude of the change. SLR is easily executed but is sensitive to outliers and non-normality in the observations. Under these circumstances, DLM may be amore robustmodeling technique for estimating changes in meteorological data. © Inter-Research 2019.
英文关键词	Central Himalayas; Global warming; Kalman filter; Mann-Kendall trend test; Markov chain; Seasonality and trend; Simple linear regression (SLR); State-space model
语种	英语
scopus关键词	geographical distribution; global warming; Kalman filter; Markov chain; microclimate; model; regression analysis; seasonality; temperature gradient; trend analysis; Himalayas
来源期刊	Climate Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/146922
作者单位	Department of Biological Sciences, University of Arkansas, Fayetteville, AR 72703, United States; Department of Mathematical Sciences, University of Arkansas, Fayetteville, AR 72703, United States; Division of Human Genetics, Ohio State University College of MedicineOH 43210, United States
推荐引用方式 GB/T 7714	Regmi B.,Lamichhane S.. A dynamic linear model of monthly minimum and maximum temperature changes in three physiographic regions of the Central Himalayas[J],2019,79(1).
APA	Regmi B.,&Lamichhane S..(2019).A dynamic linear model of monthly minimum and maximum temperature changes in three physiographic regions of the Central Himalayas.Climate Research,79(1).
MLA	Regmi B.,et al."A dynamic linear model of monthly minimum and maximum temperature changes in three physiographic regions of the Central Himalayas".Climate Research 79.1(2019).