Editing IPCC:AR6/WGI/Chapter-10 (section)

==== 10.6.4.5 Model Simulation and Attribution Over the Historical Period ====

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Observational datasets show large agreement on the historical (1960–2014) temperature evolution at basin-wide scale (Figure 10.20e), with an enhanced warming since the 1990s, and the early decades of the 21st century being on average approximately more than 1°C warmer than late 19th century levels ( [[#van%20der%20Schrier--2013|van der Schrier et al., 2013]] ; [[#Cramer--2018|Cramer et al., 2018]] ; [[#Lionello--2018|Lionello and Scarascia, 2018]] ; Figure 10.20e). Over recent decades, the surface air temperature of the Mediterranean including the Mediterranean Sea has warmed by around 0.4°C per decade ( [[#Macias--2013|Macias et al., 2013]] ). Observed trends over land show large geographical heterogeneity (Figure 10.20d) and notable differences exist amongst different datasets at grid point scale (Figure 10.20c; [[#Qasmi--2021|Qasmi et al., 2021]] ).

Several mechanisms have been proposed for the enhanced Mediterranean warming, although their relative importance and the possible interplay between them are not fully understood. Circulation changes might have contributed to this enhanced warming (Figure 10.20a). [[#Sutton--2012|Sutton and Dong (2012)]] argued that the AMV induced a shift around the 1990s towards warmer southern European summers. This mechanism is associated with a linear baroclinic atmospheric response to the AMV-related surface heat flux. Also [[#O’Reilly--2017|O’Reilly et al. (2017)]] related warm summer decades to the AMV, but the connection was shown to be mainly thermodynamic. [[#Qasmi--2021|Qasmi et al. (2021)]] estimate an increase in Mediterranean summer temperature of 0.2°C–0.8°C during a positive AMV.

Increased warming over land compared to the sea is expected due to the lapse-rate changes associated with tropospheric moisture contrasts ( [[#Kröner--2017|Kröner et al., 2017]] ; [[#Byrne--2018|Byrne and O’Gorman, 2018]] ; [[#Brogli--2019b|Brogli et al., 2019b]] ; Figure 10.20a). Enhanced land–sea temperature contrast leads to relative humidity and soil moisture feedbacks ( [[#Rowell--2006|Rowell and Jones, 2006]] ), the latter also depending on weather regimes ( [[#Quesada--2012|Quesada et al., 2012]] ). The globally enhanced land–sea contrast in near surface temperature is also a robust result in CMIP5 and CMIP6 models ( [[IPCC:Wg1:Chapter:Chapter-4#4.5.1.1|Section 4.5.1.1]] ).

Due to its semi-arid climate, strong atmosphere–land coupling has contributed to the larger increase of mean summer temperature compared to the increase of annual mean temperature ( [[#Seneviratne--2006|Seneviratne et al., 2006]] ). In particular, during drought spells, limits to evaporation due to low soil moisture provide a positive feedback and enhances the intensity of heatwaves ( [[#Lorenz--2016|Lorenz et al., 2016]] ; Box 11.1). By comparing reanalysis-driven RCM simulations with observations, [[#Knist--2017|Knist et al. (2017)]] found that RCMs are able to reproduce soil moisture interannual variability, spatial patterns, and annual cycles of surface fluxes over the period 1990–2008, revealing a strong land–atmosphere coupling especially in southern Europe in summer. In addition cloud feedbacks can modulate the Mediterranean summer temperature ( [[#Mariotti--2012|Mariotti and Dell’Aquila, 2012]] ).

The observed trends over 1901–2010 are outside the range of internal variability shown in CMIP5 pre-industrial control experiments and consistent with, or greater than those simulated by experiments including both anthropogenic and natural forcings ( [[#Knutson--2013|Knutson et al., 2013]] ) and therefore partly attributable to anthropogenic forcing. The decrease of anthropogenic aerosols over Europe including the Mediterranean resulting from European de-industrialisation and air pollution policies ( [[#Turnock--2016|Turnock et al., 2016]] ) has been highlighted as an important contributor to the observed warming ( [[#Ruckstuhl--2008|Ruckstuhl et al., 2008]] ; [[#Philipona--2009|Philipona et al., 2009]] ; [[#de%20Laat--2013|de Laat and Crok, 2013]] ; [[#Nabat--2014|Nabat et al., 2014]] ; [[#Besselaar--2015|Besselaar et al., 2015]] ; [[#Dong--2017|Dong et al., 2017]] ; [[#Boé--2020a|Boé et al., 2020a]] ). [[#Pfeifroth--2018|Pfeifroth et al. (2018)]] argue that this brightening is mainly due to cloud changes caused by the indirect aerosol effect with a minor role for the direct aerosol effect, in contrast to [[#Nabat--2014|Nabat et al. (2014)]] and [[#Boers--2017|Boers et al. (2017)]] who attribute it to the direct aerosol effect. Using model sensitivity experiments, [[#Nabat--2014|Nabat et al. (2014)]] also associated the increase in Mediterranean SST since 1980–2012 with the decrease in aerosol concentrations (Atlas.8.2, Atlas.8.3 and Atlas.8.5).

Over the period 1960–2014, observed trends over land are consistent with those of most of the multi-model or SMILEs ensembles (Figure 10.20f), although large differences exist for individual models and ensemble members. The modelled ensemble-mean trends show large geographical variations. Generally, both global and regional models often underestimate the observed trend especially over parts of North Africa, Italy, the Balkans and Turkey. The cold bias in global models is related to simulated SLP trends that are anti-correlated to the observed trend, which is probably due to systematic model errors ( [[#Boé--2020b|Boé et al., 2020b]] ). Biases in the simulation of soil-moisture and cloud-cover might also have contributed to the underestimation of the warming trend in GCMs ( [[#van%20Oldenborgh--2009|van Oldenborgh et al., 2009]] ). The CORDEX results (at both 0.44° and 0.11° resolution) show consistently smaller values than those in global models and the available datasets (Figure 10.20g; [[#Vautard--2021|Vautard et al., 2021]] ). This is partly due to the overestimation in the temperature evolution before 1990 (Figure 10.20e), possibly because of differences in the aerosol forcing ( [[#Boé--2020a|Boé et al., 2020a]] ), although the driving global models also have a cold bias ( [[#Vautard--2021|Vautard et al., 2021]] ). Cold biases for recent decades are also found in Med-CORDEX simulations ( [[#Dell’Aquila--2018|Dell’Aquila et al., 2018]] ) and by RCM simulations over the southern part of the Mediterranean, Middle East and North Africa region ( [[#Almazroui--2016|Almazroui, 2016]] ; [[#Almazroui--2016a|Almazroui et al., 2016a]] , b; [[#Zittis--2017|Zittis and Hadjinicolaou, 2017]] ; [[#Ozturk--2018|Ozturk et al., 2018]] ), although higher resolution, new bare soil albedo and modified aerosol parametrization significantly improve the results ( [[#Bucchignani--2016a|Bucchignani et al., 2016a]] , b, 2018). Despite large differences in the multi-model mean trend (Figure 10.20g), in most of the land points the observed trend lies within the model range in all ensembles. For the SST bias exhibited by coupled RCMs the choice of driving global model has the largest impact ( [[#Darmaraki--2019|Darmaraki et al., 2019]] ; [[#Soto-Navarro--2020|Soto-Navarro et al., 2020]] ).

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