Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.

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Climate Change 2007: The Physical Science Basis.

Whether the characteristics of tropical cyclones have altered, or will alter, in a changing climate has been subject of considerable debate. An overview of recent research indicates that greenhouse warming will cause stronger storms, on average, but a decrease in the frequency of tropical cyclones. Whether the characteristics of tropical cyclones have changed or will change in a warming climate — and if so, how — has been the subject of considerable investigation, often with conflicting results. Large amplitude fluctuations in the frequency and intensity of tropical cyclones greatly complicate both the detection of long-term trends and their attribution to rising levels of atmospheric greenhouse gases. Trend detection is further impeded by substantial limitations in the availability and quality of global historical records of tropical cyclones. Therefore, it remains uncertain whether past changes in tropical cyclone activity have exceeded the variability expected from natural causes. However, future projections based on theory and high-resolution dynamical models consistently indicate that greenhouse warming will cause the globally averaged intensity of tropical cyclones to shift towards stronger storms, with intensity increases of 2–11% by 2100. Existing modelling studies also consistently project decreases in the globally averaged frequency of tropical cyclones, by 6–34%. Balanced against this, higher resolution modelling studies typically project substantial increases in the frequency of the most intense cyclones, and increases of the order of 20% in the precipitation rate within 100 km of the storm centre. For all cyclone parameters, projected changes for individual basins show large variations between different modelling studies.

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Tropical cyclones and climate change

Recent research has strengthened the understanding of the links between climate and tropical cyclones (TCs) on various timescales Geological records of past climates have shown century-long variations in TC numbers While no significant trends have been identified in the Atlantic since the late 19th century, significant observed trends in TC numbers and intensities have occurred in this basin over the past few decades, and trends in other basins are increasingly being identified However, understanding of the causes of these trends is incomplete, and confidence in these trends continues to be hampered by a lack of consistent observations in some basins A theoretical basis for maximum TC intensity appears now to be well established, but a climate theory of TC formation remains elusive Climate models mostly continue to predict future decreases in global TC numbers, projected increases in the intensities of the strongest storms and increased rainfall rates Sea level rise will likely contribute toward increased storm surge risk Against the background of global climate change and sea level rise, it is important to carry out quantitative assessments on the potential risk of TC-induced storm surge and flooding to densely populated cities and river deltas Several climate models are now able to generate a good distribution of both TC numbers and intensities in the current climate Inconsistent TC projection results emerge from modeling studies due to different downscaling methodologies and warming scenarios, inconsistencies in projected changes of large-scale conditions, and differences in model physics and tracking algorithms WIREs Clim Change 2016, 7:65–89 doi: 101002/wcc371

For further resources related to this article, please visit the WIREs website

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A new version of the general circulation model CNRM-CM has been developed jointly by CNRM-GAME (Centre National de Recherches Meteorologiques—Groupe d’etudes de l’Atmosphere Meteorologique) and Cerfacs (Centre Europeen de Recherche et de Formation Avancee) in order to contribute to phase 5 of the Coupled Model Intercomparison Project (CMIP5). The purpose of the study is to describe its main features and to provide a preliminary assessment of its mean climatology. CNRM-CM5.1 includes the atmospheric model ARPEGE-Climat (v5.2), the ocean model NEMO (v3.2), the land surface scheme ISBA and the sea ice model GELATO (v5) coupled through the OASIS (v3) system. The main improvements since CMIP3 are the following. Horizontal resolution has been increased both in the atmosphere (from 2.8° to 1.4°) and in the ocean (from 2° to 1°). The dynamical core of the atmospheric component has been revised. A new radiation scheme has been introduced and the treatments of tropospheric and stratospheric aerosols have been improved. Particular care has been devoted to ensure mass/water conservation in the atmospheric component. The land surface scheme ISBA has been externalised from the atmospheric model through the SURFEX platform and includes new developments such as a parameterization of sub-grid hydrology, a new freezing scheme and a new bulk parameterisation for ocean surface fluxes. The ocean model is based on the state-of-the-art version of NEMO, which has greatly progressed since the OPA8.0 version used in the CMIP3 version of CNRM-CM. Finally, the coupling between the different components through OASIS has also received a particular attention to avoid energy loss and spurious drifts. These developments generally lead to a more realistic representation of the mean recent climate and to a reduction of drifts in a preindustrial integration. The large-scale dynamics is generally improved both in the atmosphere and in the ocean, and the bias in mean surface temperature is clearly reduced. However, some flaws remain such as significant precipitation and radiative biases in many regions, or a pronounced drift in three dimensional salinity.

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The CNRM-CM5.1 global climate model: description and basic evaluation

[1] Arctic amplification (AA) – the observed enhanced warming in high northern latitudes relative to the northern hemisphere – is evident in lower-tropospheric temperatures and in 1000-to-500 hPa thicknesses. Daily fields of 500 hPa heights from the National Centers for Environmental Prediction Reanalysis are analyzed over N. America and the N. Atlantic to assess changes in north-south (Rossby) wave characteristics associated with AA and the relaxation of poleward thickness gradients. Two effects are identified that each contribute to a slower eastward progression of Rossby waves in the upper-level flow: 1) weakened zonal winds, and 2) increased wave amplitude. These effects are particularly evident in autumn and winter consistent with sea-ice loss, but are also apparent in summer, possibly related to earlier snow melt on high-latitude land. Slower progression of upper-level waves would cause associated weather patterns in mid-latitudes to be more persistent, which may lead to an increased probability of extreme weather events that result from prolonged conditions, such as drought, flooding, cold spells, and heat waves.

More Evidence Linking Arctic Amplification to Extreme Weather in Mid-Latitudes

Abstract. Decadal climate predictions, obtained by constraining the initial condition of a dynamical model through a truthful estimate of the observed climate state, provide an accurate assessment of near-term climate change and are a useful tool to inform decision-makers on future climate-related risks. Here we present results from the CMIP6 (Coupled Model Intercomparison Project Phase 6) Decadal Climate Prediction Project (DCPP) decadal hindcasts produced with the operational CMCC (Euro-Mediterranean Center on Climate Change) decadal prediction system (DPS), based on the fully coupled CMCC-CM2-SR5 dynamical model. A 20-member suite of 10-year retrospective forecasts, initialized every year from 1960 to 2020, is performed using a full-field initialization strategy. The predictive skill for key variables is assessed and compared with the
skill of an ensemble of non-initialized historical simulations so as to
quantify the added value of the initialization. In particular, the CMCC DPS is able to skillfully reproduce past climate surface and subsurface temperature fluctuations over large parts of the globe. The North Atlantic Ocean is the region that benefits the most from initialization, with the largest skill enhancement occurring over the subpolar region compared to historical simulations. On the other hand, the predictive skill over the Pacific Ocean rapidly decays with forecast time, especially over the North Pacific. In terms of precipitation, the skill of the CMCC DPS is significantly higher than that of the historical simulations over a few specific regions, including the Sahel, northern Eurasia, and over western and central Europe. The Atlantic multidecadal variability is also skillfully predicted, and this likely contributes to the skill found over remote areas through downstream influence, circulation changes, and teleconnections. Considering the relatively small ensemble size, a remarkable prediction skill is also found for the North Atlantic Oscillation, with maximum correlations obtained in the 1–9 lead year range. Systematic errors also affect the forecast quality of the CMCC DPS,
featuring a prominent cold bias over the Northern Hemisphere, which is not
found in the historical runs, suggesting that, in some areas, the adopted
full-field initialization strategy likely perturbs the equilibrium state of
the model climate quite significantly. The encouraging results obtained in this study indicate that climate
variability over land can be predictable over a multiyear range, and
they demonstrate that the CMCC DPS is a valuable addition to the current
generation of DPSs. This stresses the need to further explore the potential
of the near-term predictions, further improving future decadal systems and
initialization methods, with the aim to provide a reliable tool to inform decision-makers on how regional climate will evolve in the next decade.


The Euro-Mediterranean Center on Climate Change (CMCC) decadal prediction system

Seasonal prediction system at CMCC.

Effects of Tropical Cyclones on Ocean Heat Transport as simulated by a High Resolution Coupled General Circulation Model

The new CMCC - Seasonal Prediction System.

The Kuroshio Extension (KE) is the inertial meandering jet formed by the convergence of the Kuroshio and Oyashio currents in the Northern Pacific. It is widely mentioned in the literature that the KE variability is bimodal on interannual to decadal time scale. The nature of this low frequency variability (LFV) is still under debate; intrinsic oceanic mechanisms are known to play a fundamental role in the phenomenon but there is also evidence from observations that the KE LFV is connected with changes in broader patterns associated with the Pacific Decadal Oscillation, which is in its turn generated by the dominant decadal mode of the sea level pressure variability in the North Pacific. We investigate the respective contributions of oceanic and atmospheric drivers of the KE variability by taking advantage of the OCCIPUT 1/4° global model dataset: it consists in an ensemble of 50 ocean–sea ice hindcasts performed over the period 1960–2015 (hereafter OCCITENS), and in a one-member 330-year climatological simulation (hereafter OCCICLIM). In this context, OCCITENS simulates both the intrinsic and forced variability, while OCCICLIM simulates the "pure" intrinsic variability. We explore several features of the KE, finding analogies between the OCCICLIM and OCCITENS datasets with autonomous and non-autonomous dynamical systems respectively. This approach aims to apply concepts from the dynamical systems theory on complex and realistic ocean simulations. In this framework, the results suggest that both oceanic and atmospheric drivers control the KE LFV, and that the effect of the low-frequency atmospheric forcing reduces the phase space region explored by the system through synchronization mechanisms. The system’s intrinsic variability can be paced, and therefore clustered over the system’s pullback attractor under the effect of the time dependent forcing.

Alessio Bellucci

Papers

The Euro-Mediterranean Center on Climate Change (CMCC) decadal prediction system

Seasonal prediction system at CMCC.

Effects of Tropical Cyclones on Ocean Heat Transport as simulated by a High Resolution Coupled General Circulation Model

The new CMCC - Seasonal Prediction System.

Interannual to decadal variability of the Kuroshio extension: analyzing an ensemble of global hindcasts from a dynamical system viewpoint