NDLI: Mining time-lagged relationships in spatio-temporal climate data

Content Provider	IEEE Xplore Digital Library
Author	Kawale, J. Liess, S. Kumar, V. Lall, U. Ganguly, A.
Copyright Year	2012
Description	Author affiliation: University of Minnesota, Minneapolis, US (Kawale, J.; Liess, S.; Kumar, V.) \|\| Northeastern University, Boston, US (Ganguly, A.) \|\| Columbia University, New York, USA (Lall, U.)
Abstract	Time series data in climate are often characterized by a delayed relationship between two variables, for example precipitation and temperature anomalies occurring at a place might also occur at another place after some time. These lagged relations generally signify the time lag between the cause and the effect or the spread of a common cause and are important to study and understand as they can aid in prediction. Identifying lagged relationships in climate data is challenging due to the various complex dependencies present in the data like spatial and temporal auto-correlation, seasonality, trends and long distance teleconnections. In this paper, we present a general framework for finding all pairs of lagged positive and negative relations that can exist in a given spatio-temporal dataset. We use a graph based approach based upon the concept of shared reciprocal nearest neighbor to generate cluster pairs of locations sharing similar or opposing behavior for every time lag. Our framework can be generalized to extract multivariate lagged relationships across different variables thus can be used to understand the lagged response of one variable on another. We show the utility of our approach by extracting some of the known delayed relationships like the Madden Julian Oscillation (MJO) and the Pacific North American (PNA) pattern at different lags using the sea level pressure dataset provided by the NCEP/NCAR. Our approach can be broadly applied to other problems in spatio-temporal domain to extract lagged relationships.
Starting Page	130
Ending Page	135
File Size	2327801
Page Count	6
File Format	PDF
ISBN	9781467346252
e-ISBN	9781467346276
DOI	10.1109/CIDU.2012.6382194
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Earth Correlation Time series analysis Clustering algorithms Sea level Oscillators 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
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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