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Article

Analyzing Space–Time Coherence in Precipitation Seasonality across Different European Climates

1
IMAA-CNR (Institute of Methodologies for Environmental Analysis-Italian National Research Council), C.da Santa Loja, 85050 Tito Scalo (PZ), Italy
2
Department of Physics, University of Naples “Federico II”, 80126 Naples (NA), Italy
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(1), 171; https://doi.org/10.3390/rs12010171
Submission received: 11 November 2019 / Revised: 6 December 2019 / Accepted: 30 December 2019 / Published: 3 January 2020
(This article belongs to the Section Environmental Remote Sensing)

Abstract

Seasonality is a fundamental feature of environmental systems which critically depend on the climate annual cycle. The regularity of the precipitation regime, in particular, is a basic factor to sustain equilibrium conditions. An incomplete or biased understanding of precipitation seasonality, in terms of temporal and spatial properties, could severely limit our ability to respond to climate risk, especially in areas with limited water resources or fragile ecosystems. Here, we analyze precipitation data from the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) at 0.050 resolution to study the spatial features of the precipitation seasonality across different climate zones in Central-Southern Europe during the period 1981–2018. A cluster analysis of the average annual precipitation cycle shows that seasonality under the current climate can be synthesized in the form of a progressive deformation process of the annual cycle, which starts from the northernmost areas with maximum values in summer and ends in the south, where maximum values are recorded in winter. Our analysis is useful to detect local season-dependent changes, enhancing our understanding of the geography of climate change. As an example of application to this issue, we discuss the seasonality analysis in a simulated scenario based on IPCC projections.
Keywords: precipitation seasonality; CHIRPS data; climate change; image time series; European climates precipitation seasonality; CHIRPS data; climate change; image time series; European climates
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MDPI and ACS Style

Lanfredi, M.; Coluzzi, R.; Imbrenda, V.; Macchiato, M.; Simoniello, T. Analyzing Space–Time Coherence in Precipitation Seasonality across Different European Climates. Remote Sens. 2020, 12, 171. https://doi.org/10.3390/rs12010171

AMA Style

Lanfredi M, Coluzzi R, Imbrenda V, Macchiato M, Simoniello T. Analyzing Space–Time Coherence in Precipitation Seasonality across Different European Climates. Remote Sensing. 2020; 12(1):171. https://doi.org/10.3390/rs12010171

Chicago/Turabian Style

Lanfredi, Maria, Rosa Coluzzi, Vito Imbrenda, Maria Macchiato, and Tiziana Simoniello. 2020. "Analyzing Space–Time Coherence in Precipitation Seasonality across Different European Climates" Remote Sensing 12, no. 1: 171. https://doi.org/10.3390/rs12010171

APA Style

Lanfredi, M., Coluzzi, R., Imbrenda, V., Macchiato, M., & Simoniello, T. (2020). Analyzing Space–Time Coherence in Precipitation Seasonality across Different European Climates. Remote Sensing, 12(1), 171. https://doi.org/10.3390/rs12010171

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