Greenland ice-core data have revealed large decadal climate variations over the North Atlantic that can be related to a major source of low-frequency variability, the North Atlantic Oscillation. Over the past decade, the Oscillation has remained in one extreme phase during the winters, contributing significantly to the recent wintertime warmth across Europe and to cold conditions in the northwest Atlantic. An evaluation of the atmospheric moisture budget reveals coherent large-scale changes since 1980 that are linked to recent dry conditions over southern Europe and the Mediterranean, whereas northern Europe and parts of Scandinavia have generally experienced wetter than normal conditions.

http://science.sciencemag.org/content/sci/269/5224/676.full.pdf

Decadal Trends in the North Atlantic Oscillation: Regional Temperatures and Precipitation

A new Ensemble Empirical Mode Decomposition (EEMD) is presented. This new approach consists of sifting an ensemble of white noise-added signal (data) and treats the mean as the final true result. Finite, not infinitesimal, amplitude white noise is necessary to force the ensemble to exhaust all possible solutions in the sifting process, thus making the different scale signals to collate in the proper intrinsic mode functions (IMF) dictated by the dyadic filter banks. As EEMD is a time–space analysis method, the added white noise is averaged out with sufficient number of trials; the only persistent part that survives the averaging process is the component of the signal (original data), which is then treated as the true and more physical meaningful answer. The effect of the added white noise is to provide a uniform reference frame in the time–frequency space; therefore, the added noise collates the portion of the signal of comparable scale in one IMF. With this ensemble mean, one can separate scales naturall...

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Ensemble empirical mode decomposition: a noise-assisted data analysis method

https://hal.archives-ouvertes.fr/hal-00457602/document

A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests

. By coordinating the design and distribution of global climate model simulations of the past, current, and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP historical simulations (1850–near present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP; (2) common standards, coordination, infrastructure, and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble; and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP historical simulations, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. Participation in CMIP6-Endorsed MIPs by individual modelling groups will be at their own discretion and will depend on their scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: – How does the Earth system respond to forcing? – What are the origins and consequences of systematic model biases? – How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and CMIP6 historical simulations, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.

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Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization

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.

Volcanic aerosol forcing can affect global climate, but its role in climate prediction remains poorly understood. We isolate the impact of volcanic eruptions on multiyear-to-decadal climate prediction skill by comparing two suites of initialized decadal hindcasts conducted with and without historical volcanic forcing. Unexpectedly, the inclusion of volcanic forcing in the prediction system significantly degrades the forecast skill of detrended multiyear-to-decadal sea surface temperature (SST) variability in the central-eastern tropical Pacific. The ensemble mean hindcasts produce multiyear-to-decadal tropical Pacific SST cooling in response to large tropical volcanic eruptions through thermodynamic and El Niño–Southern Oscillation (ENSO)–like dynamic processes. However, in observations, these eruptions coincided with tropical Pacific warming, which is well predicted by the no-volcano hindcasts and, hence, is likely related to internal climate variability. Improved model representation of volcanic response and its interaction with internal climate variability is required to advance prediction of tropical Pacific decadal variability and associated global impacts.

https://www.science.org/doi/pdf/10.1126/sciadv.add9364?download=true

Volcanic forcing degrades multiyear-to-decadal prediction skill in the tropical Pacific

Decadal Variability in the North Pacific Ocean in a Coupled Physical-Ecosystem Model

Abstract Benchmarking climate model simulations against observations of the climate is core to the process of building realistic climate models and developing accurate future projections. However, in many cases, models do not match historical observations, particularly on regional scales. If there is a mismatch between modeled and observed climate features, should we necessarily conclude that our models are deficient? Using several illustrative examples, we emphasize that internal variability can easily lead to marked differences between the basic features of the model and observed climate, even when decades of model and observed data are available. This can appear as an apparent failure of models to capture regional trends or changes in global teleconnections, or simulation of extreme events. Despite a large body of literature on the impact of internal variability on climate, this acknowledgment has not yet penetrated many model evaluation activities, particularly for regional climate. We emphasize that using a single or small ensemble of simulations to conclude that a climate model is in error can lead to premature conclusions on model fidelity. A large ensemble of multidecadal simulations is therefore needed to properly sample internal climate variability in order to robustly identify model deficiencies and convincingly demonstrate progress between generations of climate models. 

/pdf/importance-of-internal-variability-for-climate-model-11q1qwde.pdf

Importance of internal variability for climate model assessment

: The impact on the Gulf Stream and Kuroshio from Arctic sea ice loss is investigated using the Community Climate System Model version 4 (CCSM4) model for their important roles during climate change. Results show that the Gulf Stream (Kuroshio) weakens (strengthens) in response to Arctic sea ice loss via ocean (atmosphere) adjustments. More precisely, the Kuroshio acceleration is mainly due to the anomalous wind stress over the North Pacific, while the ocean gyre adjustments in the Atlantic are responsible for the weakened Gulf Stream. As positive buoyancy fluxes induced by Arctic sea ice loss triggers a slowdown of the Atlantic Meridional Overturning Circulation (AMOC), the Gulf Stream decelerates evidently, which current speed decreases about 5-8 cm/s in the upper ocean. Resulted from less advection and horizontal diffusion in the temperature budget, less poleward warm water leads to a narrow sea surface cooling sandwiched between strong warm-21 ing in the subpolar and subtropical Atlantic. Furthermore, colder surface decreases the upward heat 22 flux (mainly latent heat flux) along the Gulf Stream Extension (GE) path, which leads to a warming 23 hole in the atmosphere.

Clara Deser

Papers

Volcanic forcing degrades multiyear-to-decadal prediction skill in the tropical Pacific

Decadal Variability in the North Pacific Ocean in a Coupled Physical-Ecosystem Model

Importance of internal variability for climate model assessment

Contrary Responses of the Gulf Stream and the Kuroshio to Arctic Sea Ice Loss

Interannual fires as a source for subarctic summer decadal climate variability mediated by permafrost thawing