Non-linear loss of suitable wine regions over Europe in response to increasing global warming.

Evaluating the potential climatic suitability for premium wine production is crucial for adaptation planning in Europe. While new wine regions may emerge out of the traditional boundaries, most of the present-day renowned winemaking regions may be threatened by climate change. Here, we analyse the future evolution of the geography of wine production over Europe, through the definition of a novel climatic suitability indicator, which is calculated over the projected grapevine phenological phases to account for their possible contractions under global warming. Our approach consists in coupling six different de-biased downscaled climate projections under two different scenarios of global warming with four phenological models for different grapevine varieties. The resulting suitability indicator is based on fuzzy logic and is calculated over three main components measuring (i) the timing of the fruit physiological maturity, (ii) the risk of water stress and (iii) the risk of pests and diseases. The results demonstrate that the level of global warming largely determines the distribution of future wine regions. For a global temperature increase limited to 2°C above the pre-industrial level, the suitable areas over the traditional regions are reduced by about 4%/°C rise, while for higher levels of global warming, the rate of this loss increases up to 17%/°C. This is compensated by a gradual emergence of new wine regions out of the traditional boundaries. Moreover, we show that reallocating better-suited grapevine varieties to warmer conditions may be a viable adaptation measure to cope with the projected suitability loss over the traditional regions. However, the effectiveness of this strategy appears to decrease as the level of global warming increases. Overall, these findings suggest the existence of a safe limit below 2°C of global warming for the European winemaking sector, while adaptation might become far more challenging beyond this threshold.

Multiyear predictability of tropical marine productivity.

With the emergence of decadal predictability simulations, research toward forecasting variations of the climate system now covers a large range of timescales. However, assessment of the capacity to predict natural variations of relevant biogeochemical variables like carbon fluxes, pH, or marine primary productivity remains unexplored. Among these, the net primary productivity (NPP) is of particular relevance in a forecasting perspective. Indeed, in regions like the tropical Pacific (30°N-30°S), NPP exhibits natural fluctuations at interannual to decadal timescales that have large impacts on marine ecosystems and fisheries. Here, we investigate predictions of NPP variations over the last decades (i.e., from 1997 to 2011) with an Earth system model within the tropical Pacific. Results suggest a predictive skill for NPP of 3 y, which is higher than that of sea surface temperature (1 y). We attribute the higher predictability of NPP to the poleward advection of nutrient anomalies (nitrate and iron), which sustain fluctuations in phytoplankton productivity over several years. These results open previously unidentified perspectives to the development of science-based management approaches to marine resources relying on integrated physical-biogeochemical forecasting systems.

Toward machine-assisted tuning avoiding the underestimation of uncertainty in climate change projections.

Documenting the uncertainty of climate change projections is a fundamental objective of the inter-comparison exercises organized to feed into the Intergovernmental Panel on Climate Change (IPCC) reports. Usually, each modeling center contributes to these exercises with one or two configurations of its climate model, corresponding to a particular choice of "free parameter" values, resulting from a long and often tedious "model tuning" phase. How much uncertainty is omitted by this selection and how might readers of IPCC reports and users of climate projections be misled by its omission? We show here how recent machine learning approaches can transform the way climate model tuning is approached, opening the way to a simultaneous acceleration of model improvement and parametric uncertainty quantification. We show how an automatic selection of model configurations defined by different values of free parameters can produce different "warming worlds," all consistent with present-day observations of the climate system.

Early warning signal for a tipping point suggested by a millennial Atlantic Multidecadal Variability reconstruction.

Atlantic multidecadal variability is a coherent mode of natural climate variability occurring in the North Atlantic Ocean, with strong impacts on human societies and ecosystems worldwide. However, its periodicity and drivers are widely debated due to the short temporal extent of instrumental observations and competing effects of both internal and external climate factors acting on North Atlantic surface temperature variability. Here, we use a paleoclimate database and an advanced statistical framework to generate, evaluate, and compare 312 reconstructions of the Atlantic multidecadal variability over the past millennium, based on different indices and regression methods. From this process, the best reconstruction is obtained with the random forest method, and its robustness is checked using climate model outputs and independent oceanic paleoclimate data. This reconstruction shows that memory in variations of Atlantic multidecadal variability have strongly increased recently-a potential early warning signal for the approach of a North Atlantic tipping point.

On the risk of abrupt changes in the North Atlantic subpolar gyre in CMIP6 models.

CMIP5 models have been shown to exhibit rapid cooling events in their projections of the North Atlantic subpolar gyre. Here, we analyze the CMIP6 archive, searching for such rapid cooling events in the new generation of models. Four models out of 35 exhibit such instabilities. The climatic impacts of these events are large on decadal timescales, with a substantial effect on surface temperature over Europe, precipitation pattern in the tropics-most notably the Sahel and Amazon regions-and a possible impact on the mean atmospheric circulation. The mechanisms leading to these events are related to the collapse of deep convection in the subpolar gyre, modifying profoundly the oceanic circulation. Analysis of stratification in the subpolar gyre as compared with observations highlights that the biases of the models explain relatively well the spread in their projections of surface temperature trends: models showing the smallest stratification biases over the recent period also show the weakest warming trends. The models exhibiting abrupt cooling rank among the 11 best models for this stratification indicator, leading to a risk of encountering an abrupt cooling event of up to 36.4%, slightly lower than the 45.5% estimated in CMIP5 models.

Increased risk of near term global warming due to a recent AMOC weakening.

Some of the new generation CMIP6 models are characterised by a strong temperature increase in response to increasing greenhouse gases concentration1. At first glance, these models seem less consistent with the temperature warming observed over the last decades. Here, we investigate this issue through the prism of low-frequency internal variability by comparing with observations an ensemble of 32 historical simulations performed with the IPSL-CM6A-LR model, characterized by a rather large climate sensitivity. We show that members with the smallest rates of global warming over the past 6-7 decades are also those with a large internally-driven weakening of the Atlantic Meridional Overturning Circulation (AMOC). This subset of members also matches several AMOC observational fingerprints, which are in line with such a weakening. This suggests that internal variability from the Atlantic Ocean may have dampened the magnitude of global warming over the historical era. Taking into account this AMOC weakening over the past decades means that it will be harder to avoid crossing the 2 °C warming threshold.

Alleviation of an Arctic Sea Ice Bias in a Coupled Model Through Modifications in the Subgrid-Scale Orographic Parameterization.

In climate models, the subgrid-scale orography (SSO) parameterization imposes a blocked flow drag at low levels that is opposed to the local flow. In IPSL-CM6A-LR, an SSO lift force is also applied perpendicular to the local flow to account for the effect of locally blocked air in narrow valleys. Using IPSL-CM6A-LR sensitivity experiments, it is found that the tuning of both effects strongly impacts the atmospheric circulation. Increasing the blocking and reducing the lift lead to an equatorward shift of the Northern Hemisphere subtropical jet and a reduction of the midlatitude eddy-driven jet speed. It also improves the simulated synoptic variability, with a reduced storm-track intensity and increased blocking frequency over Greenland and Scandinavia. Additionally, it cools the polar lower troposphere in boreal winter. Transformed Eulerian Mean diagnostics also show that the low-level eddy-driven subsidence over the polar region is reduced consistent with the simulated cooling. The changes are amplified in coupled experiments when compared to atmosphere-only experiments, as the low-troposphere polar cooling is further amplified by the temperature and albedo feedbacks resulting from the Arctic sea ice growth. In IPSL-CM6A-LR, this corrects the warm winter bias and the lack of sea ice that were present over the Arctic before adjusting the SSO parameters. Our results, therefore, suggest that the adjustment of SSO parameterization alleviates the Arctic sea ice bias in this case. However, the atmospheric changes induced by the parametrized SSO also impact the ocean, with an equatorward shift of the Northern Hemisphere oceanic gyres and a weaker Atlantic meridional overturning circulation.

Author Correction: Tropical explosive volcanic eruptions can trigger El Niño by cooling tropical Africa.

The original version of this Article omitted a reference to previous work in 'Mann, M.E., Cane, M.A., Zebiak, S.E., Clement, A., Volcanic and Solar Forcing of the Tropical Pacific Over the Past 1000 Years, J. Climate 18, 447-456 (2005)'. This has been added as reference 62 at the end of the fourth sentence of the fourth paragraph of the Introduction: 'Early studies using simple coupled ocean-atmosphere models26 proposed that following volcano-induced surface cooling, upwelling in the eastern equatorial Pacific acting on a reduced vertical temperature contrast between the ocean surface and interior leads to anomalous warming in this region, thereby favouring El Niño development the following year12, 27, 62.' This has been corrected in the PDF and HTML versions of the Article.

Publisher Correction: Tropical explosive volcanic eruptions can trigger El Niño by cooling tropical Africa.

A correction to this article has been published and is linked from the HTML version of this article.

Tropical explosive volcanic eruptions can trigger El Niño by cooling tropical Africa.

Stratospheric aerosols from large tropical explosive volcanic eruptions backscatter shortwave radiation and reduce the global mean surface temperature. Observations suggest that they also favour an El Niño within 2 years following the eruption. Modelling studies have, however, so far reached no consensus on either the sign or physical mechanism of El Niño response to volcanism. Here we show that an El Niño tends to peak during the year following large eruptions in simulations of the Fifth Coupled Model Intercomparison Project (CMIP5). Targeted climate model simulations further emphasize that Pinatubo-like eruptions tend to shorten La Niñas, lengthen El Niños and induce anomalous warming when occurring during neutral states. Volcanically induced cooling in tropical Africa weakens the West African monsoon, and the resulting atmospheric Kelvin wave drives equatorial westerly wind anomalies over the western Pacific. This wind anomaly is further amplified by air-sea interactions in the Pacific, favouring an El Niño-like response.El Niño tends to follow 2 years after volcanic eruptions, but the physical mechanism behind this phenomenon is unclear. Here the authors use model simulations to show that a Pinatubo-like eruption cools tropical Africa and drives westerly wind anomalies in the Pacific favouring an El Niño response.

Bidecadal North Atlantic ocean circulation variability controlled by timing of volcanic eruptions.

While bidecadal climate variability has been evidenced in several North Atlantic paleoclimate records, its drivers remain poorly understood. Here we show that the subset of CMIP5 historical climate simulations that produce such bidecadal variability exhibits a robust synchronization, with a maximum in Atlantic Meridional Overturning Circulation (AMOC) 15 years after the 1963 Agung eruption. The mechanisms at play involve salinity advection from the Arctic and explain the timing of Great Salinity Anomalies observed in the 1970s and the 1990s. Simulations, as well as Greenland and Iceland paleoclimate records, indicate that coherent bidecadal cycles were excited following five Agung-like volcanic eruptions of the last millennium. Climate simulations and a conceptual model reveal that destructive interference caused by the Pinatubo 1991 eruption may have damped the observed decreasing trend of the AMOC in the 2000s. Our results imply a long-lasting climatic impact and predictability following the next Agung-like eruption.

Comment on "Multiyear prediction of monthly mean Atlantic Meridional Overturning Circulation at 26.5°N".

Matei et al. (Reports, 6 January 2012, p. 76) claim to show skillful multiyear predictions of the Atlantic Meridional Overturning Circulation (AMOC). However, these claims are not justified, primarily because the predictions of AMOC transport do not outperform simple reference forecasts based on climatological annual cycles. Accordingly, there is no justification for the "confident" prediction of a stable AMOC through 2014.