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Spatio-temporal evolution of global surface temperature distributions

Amato, Federico and Guignard, Fabian and Humphrey, Vincent and Kanevski, Mikhail (2020) Spatio-temporal evolution of global surface temperature distributions. In: CI2020: Proceedings of the 10th International Conference on Climate Informatics. Association for Computing Machinery , New York, NY, pp. 37-43. ISBN 978-1-4503-8848-1.

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Climate is known for being characterised by strong non-linearity and chaotic behaviour. Nevertheless, few studies in climate science adopt statistical methods specifically designed for non-stationary or non-linear systems. Here we show how the use of statistical methods from Information Theory can describe the non-stationary behaviour of climate fields, unveiling spatial and temporal patterns that may otherwise be difficult to recognize. We study the maximum temperature at two meters above ground using the NCEP CDAS1 daily reanalysis data, with a spatial resolution of 2.5° by 2.5° and covering the time period from 1 January 1948 to 30 November 2018. The spatial and temporal evolution of the temperature time series are retrieved using the Fisher Information Measure, which quantifies the information in a signal, and the Shannon Entropy Power, which is a measure of its uncertainty — or unpredictability. The results describe the temporal behaviour of the analysed variable. Our findings suggest that tropical and temperate zones are now characterized by higher levels of entropy. Finally, Fisher-Shannon Complexity is introduced and applied to study the evolution of the daily maximum surface temperature distributions.

Item Type:Book Section
Related URLs:
URLURL TypeDescription Paper
Amato, Federico0000-0002-5886-9038
Guignard, Fabian0000-0002-9674-3487
Humphrey, Vincent0000-0002-2541-6382
Kanevski, Mikhail0000-0001-6602-6551
Additional Information:© 2020 Copyright held by the owner/author(s). The research presented in this paper was partly supported by the National Research Program 75 "Big Data" (PNR75, project No. 167285 "HyEnergy") of the Swiss National Science Foundation (SNSF). V.H. is supported by the SNSF grant no. P400P2_180784.
Funding AgencyGrant Number
Swiss National Science Foundation (SNSF)167285
Swiss National Science Foundation (SNSF)P400P2_180784
Subject Keywords:Fisher Information Measure, Shannon Entropy Power, Statistical Complexity, Air Temperature Distributions, Spatio-Temporal Exploratory Data Analysis
Record Number:CaltechAUTHORS:20211214-82839000
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Official Citation:Federico Amato, Fabian Guignard, Vincent Humphrey, and Mikhail Kanevski. 2020. Spatio-temporal evolution of global surface temperature distributions. In 10th International Conference on Climate Informatics (CI2020), September 22–25, 2020, virtual, United Kingdom. ACM, New York, NY, USA, 7 pages.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:112441
Deposited By: George Porter
Deposited On:15 Dec 2021 15:28
Last Modified:01 Feb 2022 22:54

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