NDLI: Study on daily mean temperature modeling

Content Provider	IEEE Xplore Digital Library
Author	Qin Kun Peng Junhuan
Copyright Year	2014
Description	Author affiliation: Sch. of Land Sci. & Technol., China Univ. of Geosci. (Beijing), Beijing, China (Qin Kun; Peng Junhuan)
Abstract	Daily mean temperature is the important atmospheric parameter; also have been one of the essential data sets for climate change study. And by now the studies on daily mean temperature mainly focus on Kriging theory based methods, which is to realize gridding, interpolating, extrapolating and analysis in time dimension and/or space dimension. However, it's supposed that small scale variation part in the spatial data has been met stationary assumption in Kriging based methods. It's may not be suitable for sorts of atmospheric data, and daily mean temperature included. In this paper, we propose a new method for modeling daily mean temperature and prove it by the daily mean temperature data set downloaded from China Meteorological Data Sharing Service System, which lasts 52a(1961-2012)including over 800 meteorological stations nationwide distributed in China. Considering the spatial correlation among this spatial data and longitude\latitude\height, to build a new multiplicative multiple regression model based correlation coefficients to describe the big scale expectation function in daily mean temperature data set and meanwhile in comparison with traditional Kriging method. The result shows that the zero-mean residual from this new method, which represents the small scale random function in this data set, doesn't show spatial correlation with longitude\latitude\height and its spatial heterogeneity(0°/45°/90°/135°direction semivariograms) performs in nearly isotropy with better stationarity. Meanwhile the standard deviation and stable standard deviation almost smaller than those from traditional Kriging method, 95.63% and 91.80% respectively. In conclusion, the new method models daily mean temperature data set better than traditional Kriging method. After cross validation, the mean error (ME) is -0.003 and root-mean-square error (RMSE) is 1.652 from the new method, and traditional Kriging method results are 0.005 and 1.877 respectively.
Starting Page	221
Ending Page	225
File Size	889030
Page Count	5
File Format	PDF
e-ISBN	9781479941841
DOI	10.1109/EORSA.2014.6927882
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-06-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Correlation coefficient Daily mean temperature Temperature distribution Analytical models Correlation Non-stationary Data models Cross validation Standards Kriging Meteorology
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in