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

Maria Lanfredi,Vito Imbrenda,Rosa Coluzzi,Maria Macchiato,Tiziana Simoniello

doi:10.3390/rs12010171

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.

Highlights

Climate spatial variability around the world is determined by many factors, such as latitude, orography, influence of oceans, and direction of prevailing winds
Many ecological studies have documented the negative effects of asynchronous climate changes, i.e., changes that are unevenly distributed throughout the year and do not affect the annual regime uniformly
These season-dependent alterations, especially if they are contrasting, can dramatically limit the reactive capabilities of species and ecosystems. These studies suggest that climate-related predictive frameworks should account for spatial and temporal irregularity to fully capture the spectrum of potential future climate change effects

Summary

Introduction

Climate spatial variability around the world is determined by many factors, such as latitude, orography, influence of oceans, and direction of prevailing winds. These season-dependent alterations, especially if they are contrasting (with a decrease of the value of climate variables in some parts of the year and an increase in others), can dramatically limit the reactive capabilities of species and ecosystems These studies suggest that climate-related predictive frameworks should account for spatial and temporal irregularity to fully capture the spectrum of potential future climate change effects (see [6] for a review). The precipitation data from the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) [14] offer estimates over land with 0.050 resolution and quasi-global coverage and have proven to be useful to study environmental change, supporting, in particular, seasonal drought predictions (see [15] and reference therein) The availability of such spatially continuous, long-term observations makes it possible to strengthen knowledge about precipitation variability within and across different climate zones, thereby enabling the identification of space-time trajectories of regional climate. Risk of floods and/or landslides triggered by extreme rainfall events are noticeable in the central-northern part of the study area, entailing loss of human life and severe damage to communities [31,32,33,34,35,36,37,38]

CHIRPS Data

Cluster Analysis of Average Seasonal Patterns by K-means

Cluster Analysis of Sample Time Distributions

C11 CC22 CC33 CCC454 CC65 C6