Western Mediterranean droughts fostered by Arctic sea-ice loss

Western Mediterranean droughts fostered by Arctic sea-ice loss Ramiro I. Saurral1,2,3,4, Francisco J. Doblas-Reyes1,5, James A. Screen6, Jennifer L. Catto6, Stephanie Hay6, and Hao Yu6 1 Barcelona Supercomputing Center (BSC), Barcelona, Spain 2 CONICET-Universidad de Buenos Aires. Centro de Investigaciones del Mar y la Atmósfera (CIMA), Buenos Aires, Argentina 3 Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Ciencias de la Atmósfera y los Océanos, Buenos Aires, Argentina 4 CNRS-IRD-CONICET-UBA. Instituto Franco-Argentino para el Estudio del Clima y sus Impactos (IRL 3351 IFAECI), Buenos Aires, Argentina 5 Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain 6 Department of Mathematics and Statistics, University of Exeter, Exeter, United Kingdom Corresponding author: Ramiro I. Saurral (ramiro.saurra[email protected]) Manuscript (non-LaTeX) 1 Early Online Release: This preliminary version has been accepted for publication in Journal of Climate, may be fully cited, and has been assigned DOI 10.1175/JCLI-D-25-0066.1. The final typeset copyedited article will replace the EOR at the above DOI when it is published. © 2025 American Meteorological Society. This is an Author Accepted Manuscript distributed under the terms of the default AMS reuse license. For information regarding reuse and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). Unauthenticated | Downloaded 05/15/25 02:37 PM UTC “This is the accepted version of the following article: Saurral, R. I., F. J. Doblas-Reyes, J. A. Screen, J. L. Catto, S. Hay, and H. Yu, 2025: Western Mediterranean droughts fostered by Arctic sea-ice loss. J. Climate, https://doi.org/10.1175/JCLI-D-25-0066.1, in press CC BY 4.0 license Addendum for Research Funded by cOAlition S Organizations 2 ABSTRACT Cut-off lows (COLs), defined as isolated mid-tropospheric low pressure systems, are responsible for a large fraction of the annual mean and extreme precipitation over the Mediterranean Sea region. In this study we quantify the impacts from Arctic sea-ice loss on the frequency and distribution of COLs. We use model outputs from the Polar Amplification Model Intercomparison Project (PAMIP) forced only by the projected reduction in the amount of Arctic sea ice in a globe 2ºC warmer than in the preindustrial period. We find that sea-ice loss can, through alterations to the upper-level jet already documented in previous studies, significantly affect the frequency of COLs over southern Europe: in particular, a sharp reduction is simulated over the northeast Atlantic and the Iberian Peninsula as a consequence of more anticyclonic conditions prevailing over that region. This reduction in the number of COLs is accompanied by significantly less precipitation over the western Mediterranean, which could potentially lead to water availability affectation there. Keywords: Sea ice; Arctic Amplification; cut-off lows; extreme precipitation; droughts Accepted for publication in Journal of Climate. DOI 10.1175/JCLI-D-25-0066.1. Unauthenticated | Downloaded 05/15/25 02:37 PM UTC 3 1. Introduction Arctic sea-ice loss and its associated impacts on the atmospheric circulation have been a topic of active research in recent years (e.g. Gervais et al., 2024; Notz and Stroeve, 2016; Screen and Simmonds, 2010; Screen et al., 2018; Smith et al., 2022; Ye et al., 2024; Zappa et al., 2018). It is well established that the polar regions of the Northern Hemisphere have warmed substantially more than the global average during the past decades (Chemke et al., 2021; Previdi et al., 2021; Rantanen et al., 2022; Serreze et al., 2009; Wang et al., 2016) partly due to sea-ice loss (Goosse et al., 2018; Screen and Simmonds, 2010) and changes in the regional circulation (Zhang et al., 2023). The reduction in sea-ice cover and the associated warming of the surface ocean have triggered positive feedback mechanisms which have acted to intensify the regional lower-tropospheric warming (e.g., Boeke et al., 2021; Dai and Jenkins, 2023; He et al., 2019), even though it has been recently shown that this excessive warming could occur even without considering sea ice (Russotto and Biasutti, 2020; England and Feldl, 2024). Previous studies have concluded that future sea-ice loss over the Arctic could lead to a number of impacts on the climate of the midlatitudes. These include a potential shift in the location of the tropospheric upper-level jet (Barnes and Screen, 2015; Previdi et al., 2021; Screen and Blackport, 2019; Screen et al., 2022; Ye et al., 2023), changes in the occurrence of extreme weather events (Cohen et al., 2014) and alterations to daily weather patterns (Gervais et al., 2024), among others. Future sea-ice melt is also expected to lead to a significant reduction of cold extremes affecting midlatitudes (Lo et al., 2023) as well as to large changes in the frequency, intensity and associated wind speeds of extratropical cyclones (Hay et al., 2023). At the same time, it has been shown that the observed larger warming over the Arctic region compared to the global mean (known as Arctic Amplification, AA) has already reduced the day-to-day surface temperature variance across the Northern Hemisphere (Screen, 2014; Blackport et al., 2021). Naturally, there are many other drivers of climate variability in midlatitudes beyond sea-ice loss, and the relative contribution of sea-ice loss relative to other factors differs between seasons, regions and variables (e.g. Hay et al., 2022; Oudar et al., 2017; Yu et al., 2024). In this study, however, we focus exclusively on the role of sea-ice loss. The ongoing loss of sea-ice cover over the Arctic region may lead to sea ice-free conditions by mid-century (Kim et al., 2023; Shen et al., 2023), which could impact the midlatitude climate. In this regard, a number of modelling studies have shown inconsistent results on the possible Accepted for publication in Journal of Climate. DOI 10.1175/JCLI-D-25-0066.1. Unauthenticated | Downloaded 05/15/25 02:37 PM UTC 4 linkages between AA and midlatitude weather and climate (Blackport and Screen, 2020; Galytska et al., 2023; Screen et al., 2018) in some cases due to undersampling the actual internal variability of the climate system (Peings et al., 2021; Ye et al., 2024), which motivates further analysis of the physical mechanisms sustaining such interactions. This also includes dedicated assessments on how AA may alter the spatial distribution, frequency, intensity and pathways of synoptic-scale systems responsible not only for everyday weather but also for the occurrence of extremes. An example of such systems are cut-off lows (COLs), which are known to be associated with extreme rainfall events over several midlatitude regions. COLs are defined as cold-core quasi-barotropic low pressure systems that form in the midto upper-levels of the troposphere from an amplified baroclinic trough. This trough, under conducive patterns of horizontal temperature and relative vorticity advection, segregates a vorticity maximum that becomes detached from the main flow, leading to the formation of a COL (Palmen and Newton, 1969; Price and Vaughan, 1992). These systems typically form over several regions around the globe such as eastern Australia (Grosfeld et al., 2021), southern Africa (Favre et al., 2013), western South America (Choquehuanca et al., 2025; Pinheiro et al., 2017), the eastern North Atlantic and North Pacific as well as over China (Nieto et al., 2005) and can lead to severe weather conditions including strong winds and heavy rainfall (Muñoz and Shultz, 2021). In particular over Europe, COLs originating in the eastern North Atlantic region usually reach the Mediterranean Sea, where they can trigger intense rainfall events which account for a significant fraction of the total annual precipitation (Mastrantonas et al., 2021; Nieto, 2021; Porcù et al., 2007). Therefore, any effect on the frequency of COLs emerging either from natural variability or as a forced climate change response could lead to significant impacts on the distribution and magnitude of extreme rainfall events as well as on total rainfall amounts, which might be particularly relevant for the Mediterranean Sea region. The main objective of this study is to assess whether Arctic sea-ice loss can, through alterations in the tropospheric circulation, modulate the distribution and frequency of COLs originating in and affecting the Mediterranean Sea region, and how these could affect precipitation variability. It is worth mentioning that a recent paper by Hay et al. (2023) concluded that Arctic sea-ice loss can indeed shape several properties of surface extratropical cyclones such as their frequency, mean intensity or mean speed. However, most of the COLs affecting the Mediterranean Sea do not have a surface signature (i.e. are not accompanied by a low pressure system at the surface; Nieto et al., 2005) while still being capable of bringing severe weather Accepted for publication in Journal of Climate. DOI 10.1175/JCLI-D-25-0066.1. Unauthenticated | Downloaded 05/15/25 02:37 PM UTC 5 conditions, which supports a dedicated analysis of COLs variability and changes over that region. In this study, we use a set of Polar Amplification Model Intercomparison Project (PAMIP) experiments to address the potential impacts of sea-ice melt on COLs and how these can modulate extreme rainfall events and total precipitation over the Mediterranean Sea region. These results could be of particular relevance in the context of the severe drought conditions that have been plaguing several parts of the western Mediterranean Sea region in recent years. It is worth stressing here, however, that from the approach used in this study we cannot conclude that Arctic sea-ice loss has caused (or will cause) precipitation anomalies over southern Europe, but rather if it could (see relevant discussion in Barnes and Screen, 2015). We propose in turn a plausible physical mechanism linking sea-ice loss to the variability of COLs and Mediterranean precipitation. This manuscript is structured as follows: Section 2 outlines the datasets and methods used in the study, including a description of the algorithm used to identify COLs. Results on the impacts from sea-ice loss on the frequency of COLs and their linkages with precipitation over the Mediterranean Sea region are included in Section 3. Finally, a discussion of results and the concluding remarks are summarized in Section 4. 2. Data and methods a. PAMIP experiments The PAMIP experiments (Smith et al., 2019) used in this study are named pdSST-pdSIC (“PD”) and pdSST-futArcSIC (“FUT”) and were designed as representative of present day and future (when global warming is 2°C above the pre-industrial level) sea-ice conditions. The model outputs consist of 100 ensemble members per climate model of 14-month-long atmosphereonly time-slice runs in which a seasonal cycle of monthly mean sea-surface temperature (SST) and sea-ice concentration (SIC) is considered. The first two months of each simulation are considered as spin up and discarded, resulting in a 12-month-long period for analysis (from the month of June of the first year to the month of May of the following year). In the case of PD, the prescribed seasonal cycles of SST and SIC are obtained from observations in the period 1979-2008 from the Hadley Centre Ice and Sea Surface Temperature data set (HadISST; Rayner et al., 2003), while in the case of FUT the Arctic SIC is derived from the ensemble Accepted for publication in Journal of Climate. DOI 10.1175/JCLI-D-25-0066.1. Unauthenticated | Downloaded 05/15/25 02:37 PM UTC 6 mean of CMIP5 model projections from the 30-year period in which global mean temperature is 2 ºC above that in the pre-industrial period. Areas in which sea ice is lost have their corresponding SST values taken from future projections, while elsewhere they are the same as in the PD experiments. As in similar studies (e.g. Hay et al., 2023), the responses to sea-ice loss are computed as the ensemble-mean difference between FUT and PD, with statistical significance assessed in two steps: first applying a two-sided Student’s t-test with a p-value of 5% and then improving it by computing the false discovery rate proposed by Wilks (2006) in order to avoid overestimating rejection of the null hypothesis (i.e. labeling as “significant” a difference that is actually not). Variables considered for this study are daily 500-hPa geopotential height (h500) and daily precipitation covering the Northern Hemisphere area between 20ºN and 70ºN, as well as monthly-mean zonal wind speed at 500 hPa (u500). These were obtained from seven different PAMIP models (AWI-CM-1-1-MR, CESM2, CNRMCM6-1, EC-Earth3, FGOALS-f3-L, IPSL-CM6A-LR and MIROC6) based on the availability of daily h500 data, all of which were regridded into a common 1.5ºx1.5º grid prior to the computation of the metrics. The plots and analysis in this study are mostly built on the multimodel ensemble means (MMEM). b. COL detection algorithm We use the detection algorithm proposed by Kasuga et al. (2021) to identify COLs at daily time step. This scheme allows for the identification of COLs by using a 2D slope function applied to the h500 field. The algorithm looks for local minima in h500 occurring together with local maxima in the “average slope” of the same variable, which is defined as the spatial average of the h500 slopes from a given point P towards the east, west, north and south from the point at a given distance R. This distance R varies from 200 to 2100 km in increments of 100 km in order to cover the typical spatial extent of these weather-scale systems (Kentarchos and Davies, 1998). A given point P is tagged as a COL if a local minimum in h500 and a local maxima of the average slope occur simultaneously. This methodology is applied to all points P within the study domain, resulting in daily fields of COL occurrence and location. It should be mentioned that Kasuga et al. (2021) also propose a number of restrictions to these conditions in order to avoid classifying as COLs systems that are either too small or lie too close to the equator, for example. These same restrictions are also applied in this study. Another point worth noting is that the scheme developed by Kasuga et al. (2021) is, in spite of its simplicity of relying on a single variable at a single vertical level, as accurate in detecting COLs as other more sophisticated detection schemes that make use of more variables/levels for their computations Accepted for publication in Journal of Climate. DOI 10.1175/JCLI-D-25-0066.1. Unauthenticated | Downloaded 05/15/25 02:37 PM UTC 7 (e.g. the one proposed by Muñoz et al., 2020). The scheme from Kasuga et al. (2021) has been used in a number of studies, including a recent assessment of the skill of the operational GFS model to forecast COL formation and displacement globally (Lupo et al., 2023). For a more detailed description of the COL detection scheme please refer to Kasuga et al. (2021) and Lupo et al. (2023). In this study, the detection algorithm was applied to daily h500 fields over the Northern Hemisphere regions between 20ºN and 70ºN of PAMIP experiments. In order to validate the outcomes of the detection scheme, a similar procedure was applied to daily ERA5 (Hersbach et al., 2020) reanalysis data of h500. The daily outputs of the algorithm were aggregated annually and their analysis was centered over an extended Mediterranean Sea region running from 10ºW to 30ºE and from 35ºN to 50ºN to account for COLs that originate west of the Iberian Peninsula and affect southern Europe (Nieto et al., 2005; Porcù et al., 2007). c. Assessment of COL-precipitation relationship Linkages between COLs and precipitation over the Mediterranean Sea region are explored by using the methodology proposed by Catto et al. (2012) and refined by Catto and Pfahl (2013) and Pfahl and Wernli (2012). This method was already applied on the exploration of linkages between precipitation and surface cyclones (Pfahl and Wernli, 2012) and fronts (Catto et al., 2012; Catto and Pfahl, 2013), but it is directly adaptable to other weather features such as the one considered in this study. The automatic procedure assigns a given precipitation event to a COL if a COL lies within a 5º box around the precipitation location, as proposed in Catto et al. (2012) for surface fronts. The outputs of the methodology are the proportion of precipitation events (i.e. days with non-zero precipitation amount) occurring with a nearby COL at each grid point (Freq) and the proportion of precipitation amounts falling in association with a nearby COL relative to the annual total amount (Prec). The procedure is applied in this study to all precipitation events as well as to those associated with extreme events, i.e. daily precipitation values exceeding the corresponding 90th and 99th percentiles (P90 and P99, respectively) at each grid point in order to quantify also the contribution of COLs to the most extreme precipitation events. Following this methodology, we derive the contribution of COLs to annual precipitation (both in terms of occurrence of precipitation and of its magnitude) and to the occurrence of extreme precipitation events (i.e., days exceeding P90 and P99 of daily precipitation) in PD and FUT PAMIP experiments. For further details on the methodology for detecting COL-precipitation associations, please refer to Catto and Pfahl (2013) and Pfahl and Accepted for publication in Journal of Climate. DOI 10.1175/JCLI-D-25-0066.1. Unauthenticated | Downloaded 05/15/25 02:37 PM UTC 8 Wernli (2012). Significance of the differences in P90 and P99 in FUT relative to PD PAMIP experiments was assessed by assuming as null hypothesis that the two groups (FUT and PD) are identical (i.e. they belong to the same population and can therefore be combined into a single sample). This pooled dataset is shuffled and split into two groups of the same sizes as the original ones. Differences in percentiles obtained from these groups are computed several times (in our case we performed 1000 iterations). We then computed the fraction of the sample that actually exceeds the given threshold (P90 or P99), and when that fraction was below the significance level used here (p-level=0.05), we considered the difference as being significant. This was repeated for all grid points and the two percentiles under analysis, P90 and P99. 3. Results a. COLs in PAMIP experiments and their contribution to precipitation The MMEM annual-mean distribution of COLs in PD PAMIP experiments as well as their contribution to precipitation events and amounts are displayed in Fig. 1. The spatial field (Fig. 1a) depicts three well-defined frequency maxima: one extending from the northeast Atlantic into the Iberian Peninsula, a second one covering most of the eastern Mediterranean Sea, and a third one centered over higher latitudes between Greenland and Iceland. For reference, the annual-mean field derived from ERA5 data in the same period as in the PD experiments (19792008; Fig. S1 in the Supplemental Material) is overall similar, even though the magnitudes in PAMIP are slightly overestimated over the regions with highest COL frequency, and in particular over the eastern Mediterranean and southern Greenland. Still, these results highlight the ability of PAMIP models to capture the areas with highest COL activity over the North Atlantic region and Europe, even more so considering that very little inter-model spread is found over those areas (not shown). Accepted for publication in Journal of Climate. DOI 10.1175/JCLI-D-25-0066.1. Unauthenticated | Downloaded 05/15/25 02:37 PM UTC 9 Figure 1 MMEM annual-mean (a) frequency of COLs (in number of events per year) and their contribution to (b) southern Europe annual precipitation events (days with pr>0.0 mm) and (c) annual precipitation amounts in PD experiments. Accepted for publication in Journal of Climate. DOI 10.1175/JCLI-D-25-0066.1. Unauthenticated | Downloaded 05/15/25 02:37 PM UTC 16 linear fit (slope) with its confidence interval (alpha=0.05) in the upper-left corner. Correlations significantly different from zero are indicated with an asterisk. In order to complement our analysis, in Fig. 6 we show the MMEM variations in annual and extreme precipitation over southern Europe after sea-ice loss. The annual-mean field (Fig. 6a) depicts a significant reduction in total annual precipitation over most of central and eastern Spain, while a slight increase is simulated over northwestern Spain and a broader area with positive variations is found over central Europe, covering much of eastern France and southern Germany. At the same time, variations in the magnitudes of P90 and P99 (Fig. 6b,c) show qualitatively similar patterns, but for P90 most of the changes are small and non-significant. On the other hand, the affectation to P99 arising from sea-ice loss is large and significant over basically the same area of the western Mediterranean as found for the annual mean, once again stressing the larger impact from COLs to the more extreme precipitation events over that region. 4. Discussion and conclusions Cut-off lows (COLs) are a driver of extreme precipitation over the western Mediterranean Sea region. Still, it is unclear whether and how these could be affected by the ongoing loss of Arctic sea-ice, which is expected to continue in the future. In this study we have used a set of dedicated Polar Amplification Model Intercomparison Project (PAMIP) experiments to identify the simulated response of COLs frequency and distribution over southern Europe to reduced Arctic sea ice, and how these could affect mean and extreme precipitation. The pattern of sea-ice reduction used to force the experiments is related to a global warming of 2°C above the preindustrial level. From the results obtained in our study, we can first conclude that PAMIP models are able to represent the present-day spatial distribution, seasonality and frequency of COLs over Europe, even though with a slight overestimation of their magnitude in some areas. Meanwhile, the computation of the differences in COL density under future (i.e. with reduced sea-ice cover) relative to present conditions showed a reduction in COLs over parts of southwestern Europe, and in particular over the Iberian Peninsula. This results from an intensification of the westerly winds around 50ºN which is caused by a tightening of the meridional pressure gradient in response to higher geopotential heights to its south and more cyclonic conditions further north, Accepted for publication in Journal of Climate. DOI 10.1175/JCLI-D-25-0066.1. Unauthenticated | Downloaded 05/15/25 02:37 PM UTC 17 even though this last feature is not consistently simulated by all the PAMIP models considered in our study. It should be stressed, however, that these variations in the atmospheric circulation arise only from future sea-ice loss and should by no means be considered as projections. In fact, several studies (e.g. Hay et al., 2022; Screen et al., 2022) have shown that changes on the atmospheric circulation of the Northern Hemisphere midlatitudes driven by sea-ice loss are opposite in sign to those driven by greenhouse gases increase, leading to a “tug-of-war” between both effects. As such, the future affectation to COL frequency over southern Europe resulting from both mechanisms acting together may be very different to that derived in the present study. In fact, a very recent paper by Mishra et al. (2025) suggests that both effects taken together would lead to overall small changes to the frequency of COLs over the region considered in this study, even though with large differences between seasons. Accepted for publication in Journal of Climate. DOI 10.1175/JCLI-D-25-0066.1. Unauthenticated | Downloaded 05/15/25 02:37 PM UTC 18 Figure 6 MMEM differences in the magnitudes of (a) annual mean precipitation (in mm month-1) and (b) P90 (c) P99 (in mm day-1) in FUT relative to PD simulations. Differences that result significantly different from zero (p<pFDR) are highlighted in dots. Regarding the linkages between COLs and precipitation over the Mediterranean Sea region, we found a tight relationship between both variables particularly for days with intense precipitation (considered here as those exceeding percentiles 90 and 99 of the distribution). We Accepted for publication in Journal of Climate. DOI 10.1175/JCLI-D-25-0066.1. Unauthenticated | Downloaded 05/15/25 02:37 PM UTC 19 also identified a significant drop in the annual precipitation associated with COLs over the western Mediterranean, as well as a sharp reduction in the magnitude of P99 over that region. It is interesting to mention that most of the differences identified in precipitation are located to the east of the area with the largest differences in COL frequency. This results from the fact that the largest precipitation activity in COLs is commonly located on their eastern flank where the largest upper-level divergence (and associated upward motion) is found (e.g. Porcù et al., 2007). Our results also suggest that the dynamic relationship existing between COLs and precipitation over the western Mediterranean region should not change under sea-ice loss. In this regard, the simulated reduction in mean and extreme precipitation is explained by the decrease in COLs reaching that region. As a side note, it is worth noting that most of the variations in COL frequency in PAMIP experiments is concentrated during the winter season (not shown), which is consistent with the fact that AA has its largest fingerprint on the atmospheric circulation during that season (e.g. Previdi et al., 2021). The main objective of our study was to document potential affectations to COLs forced exclusively by Arctic sea-ice loss. This approach prevents any direct comparison with the observed variability and trends of COLs within the region of interest, given that many other internal and external forcings would not be taken into account. However, it is noteworthy that observed trends in COL frequency during the last 40 years (Fig. S2) show decreasing (increasing) frequency over the northeast Atlantic (south of Greenland and British Isles) in a somewhat similar pattern to that derived from the PAMIP models, which hints at a plausible contribution from sea-ice loss. This motivates future work to attribute the observed COL trends external forcing, including the potential role of sea-ice loss, which would be relevant to understanding the drivers of the drought conditions affecting large areas of southern Europe and how these might evolve in the future. Acknowledgments This work is part of the Polar-to-mid-latitude linkage effects on cold air outbreaks (Polar2MidLat) project, funded by the European Union’s Horizon 2021 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 101061202. Data availability statement Accepted for publication in Journal of Climate. DOI 10.1175/JCLI-D-25-0066.1. Unauthenticated | Downloaded 05/15/25 02:37 PM UTC 20 The PAMIP data is accessible on the Earth System Grid Federation website (https://esfgnode.llnl.gov/search/cmip6/). The ERA5 data is freely available through the Copernicus Climate Data Store (https://cds.climate.copernicus.eu/). Accepted for publication in Journal of Climate. 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