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Heterogeneity of Scaling of the Observed Global Temperature Data

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2019
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Authors
Blesić, Suzana
Zanchettin, Davide
Rubino, Angelo
Article (Published version)
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Abstract
We investigated the scaling properties of two datasets of the observed near-surface global temperature data anomalies: the Met Office and the University of East Anglia Climatic Research Unit HadCRUT4 dataset and the NASA GISS Land-Ocean Temperature Index (LOTI) dataset. We used detrended fluctuation analysis of second-order (DFA2) and wavelet-based spectral (WTS) analysis to investigate and quantify the global pattern of scaling in two datasets and to better understand cyclic behavior as a possible underlying cause of the observed forms of scaling. We found that, excluding polar and parts of subpolar regions because of their substantial data inhomogeneity, the global temperature pattern is long-range autocorrelated. Our results show a remarkable heterogeneity in the long-range dynamics of the global temperature anomalies in both datasets. This finding is in agreement with previous studies. We additionally studied the DFA2 and the WTS behavior of the local station temperature anomalies ...and satellite-based temperature estimates and found that the observed diversity of global scaling can be attributed both to the intrinsic variability of data and to the methodology-induced variations that arise from deriving the global temperature gridded data from the original local sources. Finally, we found differences in global temperature scaling patterns of the two datasets and showed instances where spurious scaling is introduced in the global datasets through a spatial infilling procedure or the optimization of integrated satellite records.

Keywords:
Climate variability / Surface temperature / Numerical analysis / modeling / Spectral analysis / models / distribution / Time series / Climate variability
Source:
Journal of Climate, 2019, 32, 2, 349-367
Publisher:
  • Amer Meteorological Soc, Boston
Funding / projects:
  • Uncovering information in fluctuating CLimate systems: An oppoRtunity for solving climate modeling nodes and assIst local communiTY adaptation measures (CLARITY) (EU-701785)

DOI: 10.1175/JCLI-D-17-0823.1

ISSN: 0894-8755

WoS: 000453905500001

Scopus: 2-s2.0-85059617081
[ Google Scholar ]
13
10
URI
http://rimi.imi.bg.ac.rs/handle/123456789/956
Collections
  • Radovi istraživača / Researchers' publications
Institution/Community
Institut za medicinska istraživanja
TY  - JOUR
AU  - Blesić, Suzana
AU  - Zanchettin, Davide
AU  - Rubino, Angelo
PY  - 2019
UR  - http://rimi.imi.bg.ac.rs/handle/123456789/956
AB  - We investigated the scaling properties of two datasets of the observed near-surface global temperature data anomalies: the Met Office and the University of East Anglia Climatic Research Unit HadCRUT4 dataset and the NASA GISS Land-Ocean Temperature Index (LOTI) dataset. We used detrended fluctuation analysis of second-order (DFA2) and wavelet-based spectral (WTS) analysis to investigate and quantify the global pattern of scaling in two datasets and to better understand cyclic behavior as a possible underlying cause of the observed forms of scaling. We found that, excluding polar and parts of subpolar regions because of their substantial data inhomogeneity, the global temperature pattern is long-range autocorrelated. Our results show a remarkable heterogeneity in the long-range dynamics of the global temperature anomalies in both datasets. This finding is in agreement with previous studies. We additionally studied the DFA2 and the WTS behavior of the local station temperature anomalies and satellite-based temperature estimates and found that the observed diversity of global scaling can be attributed both to the intrinsic variability of data and to the methodology-induced variations that arise from deriving the global temperature gridded data from the original local sources. Finally, we found differences in global temperature scaling patterns of the two datasets and showed instances where spurious scaling is introduced in the global datasets through a spatial infilling procedure or the optimization of integrated satellite records.
PB  - Amer Meteorological Soc, Boston
T2  - Journal of Climate
T1  - Heterogeneity of Scaling of the Observed Global Temperature Data
EP  - 367
IS  - 2
SP  - 349
VL  - 32
DO  - 10.1175/JCLI-D-17-0823.1
UR  - conv_4454
ER  - 
@article{
author = "Blesić, Suzana and Zanchettin, Davide and Rubino, Angelo",
year = "2019",
abstract = "We investigated the scaling properties of two datasets of the observed near-surface global temperature data anomalies: the Met Office and the University of East Anglia Climatic Research Unit HadCRUT4 dataset and the NASA GISS Land-Ocean Temperature Index (LOTI) dataset. We used detrended fluctuation analysis of second-order (DFA2) and wavelet-based spectral (WTS) analysis to investigate and quantify the global pattern of scaling in two datasets and to better understand cyclic behavior as a possible underlying cause of the observed forms of scaling. We found that, excluding polar and parts of subpolar regions because of their substantial data inhomogeneity, the global temperature pattern is long-range autocorrelated. Our results show a remarkable heterogeneity in the long-range dynamics of the global temperature anomalies in both datasets. This finding is in agreement with previous studies. We additionally studied the DFA2 and the WTS behavior of the local station temperature anomalies and satellite-based temperature estimates and found that the observed diversity of global scaling can be attributed both to the intrinsic variability of data and to the methodology-induced variations that arise from deriving the global temperature gridded data from the original local sources. Finally, we found differences in global temperature scaling patterns of the two datasets and showed instances where spurious scaling is introduced in the global datasets through a spatial infilling procedure or the optimization of integrated satellite records.",
publisher = "Amer Meteorological Soc, Boston",
journal = "Journal of Climate",
title = "Heterogeneity of Scaling of the Observed Global Temperature Data",
pages = "367-349",
number = "2",
volume = "32",
doi = "10.1175/JCLI-D-17-0823.1",
url = "conv_4454"
}
Blesić, S., Zanchettin, D.,& Rubino, A.. (2019). Heterogeneity of Scaling of the Observed Global Temperature Data. in Journal of Climate
Amer Meteorological Soc, Boston., 32(2), 349-367.
https://doi.org/10.1175/JCLI-D-17-0823.1
conv_4454
Blesić S, Zanchettin D, Rubino A. Heterogeneity of Scaling of the Observed Global Temperature Data. in Journal of Climate. 2019;32(2):349-367.
doi:10.1175/JCLI-D-17-0823.1
conv_4454 .
Blesić, Suzana, Zanchettin, Davide, Rubino, Angelo, "Heterogeneity of Scaling of the Observed Global Temperature Data" in Journal of Climate, 32, no. 2 (2019):349-367,
https://doi.org/10.1175/JCLI-D-17-0823.1 .,
conv_4454 .

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