ANOMALY CONSTRUCTION IN CLIMATE DATA: ISSUES AND CHALLENGES

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dc.contributor.authorKawale, Jaya
dc.contributor.authorChatterjee, Snigdhansu
dc.contributor.authorKumar, Arjun
dc.contributor.authorLiess, Stefan
dc.contributor.authorSteinbach, Michael
dc.contributor.authorKumar, Vipin
dc.date.accessioned2026-03-05T19:35:51Z
dc.date.issued2011
dc.description2011 Conference on Intelligent Data Understanding, CIDU 2011, October 19-21, 2011, Mountain View, California, USA
dc.description.abstractEarth science data consists of a strong seasonality component as indicated by the cycles of repeated patterns in climate variables such as air pressure, temperature and precipitation. The seasonality forms the strongest signals in this data and in order to find other patterns, the seasonality is removed by subtracting the monthly mean values of the raw data for each month. However since the raw data like air temperature, pressure, etc. are constantly being generated with the help of satellite observations, the climate scientists usually use a moving reference base interval of some years of raw data to calculate the mean in order to generate the anomaly time series and study the changes with respect to that.
dc.description.urihttps://climatechange.cs.umn.edu/docs/sahel.pdf
dc.format.extent15 pages
dc.genreconference papers and proceedings
dc.genrepreprints
dc.identifierdoi:10.13016/m2tn6n-ywhn
dc.identifier.urihttp://hdl.handle.net/11603/42026
dc.language.isoen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Mathematics and Statistics Department
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.titleANOMALY CONSTRUCTION IN CLIMATE DATA: ISSUES AND CHALLENGES
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0002-7986-0470

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