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Multifractal cross correlation analysis of agro-meteorological datasets (Including reference evapotranspiration) of California, United States

Sankaran, Adarsh, Krzyszczak, Jaromir, Baranowski, Piotr, Sindhu, Archana Devarajan, Kumar, Nandhineekrishna Pradeep, Jayaprakash, Nityanjali Lija, Thankamani, Vandana and Ali, Mumtaz 2020, Multifractal cross correlation analysis of agro-meteorological datasets (Including reference evapotranspiration) of California, United States, Atmosphere, vol. 11, no. 10, doi: 10.3390/atmos11101116.

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Title Multifractal cross correlation analysis of agro-meteorological datasets (Including reference evapotranspiration) of California, United States
Author(s) Sankaran, Adarsh
Krzyszczak, Jaromir
Baranowski, Piotr
Sindhu, Archana Devarajan
Kumar, Nandhineekrishna Pradeep
Jayaprakash, Nityanjali Lija
Thankamani, Vandana
Ali, MumtazORCID iD for Ali, Mumtaz orcid.org/0000-0002-6975-5159
Journal name Atmosphere
Volume number 11
Issue number 10
Article ID 1116
Total pages 24
Publisher MDPI AG
Place of publication Basel, Switzerland
Publication date 2020-10-01
ISSN 2073-4433
Keyword(s) reference evapotranspiration
agro-meteorological
multifractal
scaling
cross-correlations
persistence
Summary The multifractal properties of six acknowledged agro-meteorological parameters, such as reference evapotranspiration (ET0), wind speed (U), incoming solar radiation (SR), air temperature (T), air pressure (P), and relative air humidity (RH) of five stations in California, USA were examined. The investigation of multifractality of datasets from stations with differing terrain conditions using the Multifractal Detrended Fluctuation Analysis (MFDFA) showed the existence of a long-term persistence and multifractality irrespective of the location. The scaling exponents of SR and T time series are found to be higher for stations with higher altitudes. Subsequently, this study proposed using the novel multifractal cross correlation (MFCCA) method to examine the multiscale-multifractal correlations properties between ET0 and other investigated variables. The MFCCA could successfully capture the scale dependent association of different variables and the dynamics in the nature of their associations from weekly to inter-annual time scales. The multifractal exponents of P and U are consistently lower than the exponents of ET0, irrespective of station location. This study found that joint scaling exponent was nearly the average of scaling exponents of individual series in different pairs of variables. Additionally, the α-values of joint multifractal spectrum were lower than the α values of both of the individual spectra, validating two universal properties in the MFCCA studies for agro-meteorological time series. The temporal evolution of cross-correlation determined by the MFCCA successfully captured the dynamics in the nature of associations in the P-ET0 link.
Language eng
DOI 10.3390/atmos11101116
Indigenous content off
Field of Research 0401 Atmospheric Sciences
0502 Environmental Science and Management
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2020, The Authors
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30145713

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.