High temporal variability not trend dominates Mediterranean precipitation

Abstract

State-of-the-art climate models project a substantial decline in precipitation for the Mediterranean region in the future¹. Supporting this notion, several studies based on observed precipitation data spanning recent decades have suggested a decrease in Mediterranean precipitation^2-4, with some attributing a large fraction of this change to anthropogenic influences^3,5. Conversely, certain researchers have underlined that Mediterranean precipitation exhibits considerable spatiotemporal variability driven by atmospheric circulation patterns^6,7 maintaining stationarity over the long term^8,9. These conflicting perspectives underscore the need for a comprehensive assessment of precipitation changes in this region, given the profound social, economic and environmental implications. Here we show that Mediterranean precipitation has largely remained stationary from 1871 to 2020, albeit with significant multi-decadal and interannual variability. This conclusion is based on the most comprehensive dataset available for the region, encompassing over 23,000 stations across 27 countries. While trends can be identified for some periods and subregions, our findings attribute these trends primarily to atmospheric dynamics, which would be mostly linked to internal variability. Furthermore, our assessment reconciles the observed precipitation trends with Coupled Model Intercomparison Project Phase 6 model simulations, neither of which indicate a prevailing past precipitation trend in the region. The implications of our results extend to environmental, agricultural and water resources planning in one of the world's prominent climate change hotspots¹⁰.

Fig. 1. Spatial distribution of annual precipitation trend in different analysed periods.

a,c,e,g,i, Magnitude of the change (in per cent) at each station. a, 1871–2020; c, 1901–2020; e, 1931–2020; g, 1951–2020; i, 1981–2020. b,d,f,h,j, Sign and statistical significance of the change at each station. b, 1871–2020; d, 1901–2020; f, 1931–2020; h, 1951–2020; j, 1981–2020. The circles contain the percentage of stations showing positive and negative significant (and nonsignificant) changes.

Fig. 2. Evolution of annual and seasonal average precipitation anomalies over the Mediterranean region.

a, Evolution of annual series. b–e, Evolution of seasonal series: winter (b), spring (c), summer (d) and autumn (e). The different lines represent the time series obtained from the available series for five different analysis time frames—1871–2020 (red), 1901–2020 (blue), 1931–2020 (brown), 1951–2020 (green) and 1981–2020 (pink). The anomalies were calculated using the 1981–2020 period as the reference for all cases. The percentages shown in each plot represent the magnitude of change observed for each period, starting from the given date and ending in 2020. Changes that are statistically significant (P < 0.05) are highlighted in bold.

Fig. 3. Evolution of annual average precipitation over the Mediterranean region for three analysis periods along with the modelled annual precipitation.

a–f, Modelled precipitation based on the seasonal NAO and MO (a–d; a, 1901–2020; b, 1931–2020; c, 1951–2020; d, 1981–2020), and the seasonal frequency of storms and presence of ridges and blocks, in addition to the seasonal NAO and MO, exclusively for the periods 1951–2020 (e) and 1981–2020 (f). Green lines represent the evolution of the residuals for each regression model. The percentage of annual precipitation variability explained by each model is indicated, along with the magnitude and significance of the residual change. The variables and their weights in the models are provided in Supplementary Tables 1 and 2.

Fig. 4. Density plots of the magnitude of change in the annual and seasonal precipitation.

The density curves represent the available precipitation observatories and all the grid cells from the different CMIP5 and CMIP6 models for the different periods. a–e, Annual. f–j, Winter. k–o, Spring. p–t, Summer. u–y, Autumn. Purple: observations, teal: CMIP5, orange: CMIP6.

Extended Data Fig. 1. Evolution of the number of meteorological stations used in this study.

In black the number of stations with raw data. In blue the final number of stations reconstructed and homogenized used for each period.

Extended Data Fig. 2. Spatial distribution of the original available meteorological stations.

The information is provided both for the overall total and for the individual periods.

Extended Data Fig. 3. Data availability conditions for the data used in this study across the various countries involved.

Striped lines indicate countries where the data (all data or a subset of stations) are available in a public repository. Find additional details in the Supplementary Excel file.

Extended Data Fig. 4. Number of stations used for the analysis of precipitation trends across different periods.

The data are presented as a function of the percentage of gaps filled in each complete series for the corresponding period.

Extended Data Fig. 5. Box-plots illustrating agreement and error statistics between observed and modelled precipitation data at the monthly temporal scale.

These statistics encompass the agreement index (d), the mean average error (MAE), and the Pearson’s r coefficient. Within each box-plot, the central horizontal line represents the median, the shaded box spans the 25th and 75th percentiles, and the whiskers extend to the 10th and 90th percentiles.

Extended Data Fig. 6. Relationship between observed and modelled precipitation data.

The analysis considers the reconstruction procedure for the entire available series spanning from 1871 to 2020. Each plot incorporates agreement and error statistics, namely, d, mean average error (MAE), and Pearson’s r. The colours used in the plots represent point densities, while the black points specifically represent a sample of 1,500 points that exhibit a higher level of disagreement between observed and modelled precipitation.