2018
DOI: 10.1155/2018/4712538
|View full text |Cite
|
Sign up to set email alerts
|

Homogeneity Test and Correction of Daily Temperature and Precipitation Data (1978–2015) in North China

Abstract: Homogeneity of climate data is the basis for quantitative assessment of climate change. By using the MASH method, this work examined and corrected the homogeneity of the daily data including average, minimum, and maximum temperature and precipitation during 1978-2015 from 404/397 national meteorological stations in North China. Based on the meteorological station metadata, the results are analyzed and the differences before and after homogenization are compared. e results show that breakpoints are present perv… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
5

Citation Types

0
7
0

Year Published

2019
2019
2022
2022

Publication Types

Select...
8

Relationship

0
8

Authors

Journals

citations
Cited by 14 publications
(7 citation statements)
references
References 17 publications
0
7
0
Order By: Relevance
“…To evidence the degree of applicability of homogeneity test in hydrology, several studies have been done on the homogeneity test to detect and check inhomogeneities of data in the different regions of the world [25,29,[36][37][38][39][40]. Meteorological data homogeneity analysis is the basis for the quantitative assessment of climate change and underpins the reliability of any inferences [41,42].…”
Section: Introductionmentioning
confidence: 99%
“…To evidence the degree of applicability of homogeneity test in hydrology, several studies have been done on the homogeneity test to detect and check inhomogeneities of data in the different regions of the world [25,29,[36][37][38][39][40]. Meteorological data homogeneity analysis is the basis for the quantitative assessment of climate change and underpins the reliability of any inferences [41,42].…”
Section: Introductionmentioning
confidence: 99%
“…Homogeneity test on rainfall datasets have been studied by a lot of researchers globally [15,17,23,24,28,37,42,43,47]. Several factors such as station relocation, changes in instruments, formulae used to calculate mean and many other factors can affect the quality, accuracy and reliability of climate data.…”
Section: Introductionmentioning
confidence: 99%
“…The results show that breakpoints are present pervasively in these temperature data. Most of them appeared after 2000 [10]. In this study, outlier detection and homogeneity test were applied on 20 meteorological stations records of annual precipitation data through Iraq.…”
Section: Introductionmentioning
confidence: 99%