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...

/pdf/ensemble-empirical-mode-decomposition-a-noise-assisted-data-4htvj7tcuy.pdf

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.

/pdf/overview-of-the-coupled-model-intercomparison-project-phase-5gldl9y9dz.pdf

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.

/pdf/climate-change-2007-the-physical-science-basis-1x93ttz9jt.pdf

Climate Change 2007: The Physical Science Basis.

The inherent uncertainty of precipitation variability, trends, and extremes due to internal variability, with implications for Western US water resources

In this paper, we briefly discuss changes in large-scale oscillations such as the El Nino/Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the northern and southern annular modes (NAM and SAM), changes in the polar and tropical troposphere, and interactions between the stratosphere and troposphere in a changing climate. We consider both changes in variability as well as trends in the mean state. We conclude, that to fully understand how modes of variability will change in a changing climate, we need additional analysis of observations, both paleo and present day, and a solid fundamental understanding of mechanisms. Understanding of mechanisms necessarily requires use of models, ranging from simple to complex. Such models need to be fully coupled, between atmosphere and ocean, and need to include a fully resolved middle atmosphere as well.

Changes in Variability Associated with Climate Change


The mean-state bias and the associated forecast errors of the El Niño-Southern Oscillation (ENSO) are investigated in a suite of two-year lead retrospective forecasts conducted with the Community Earth System Model, version 1 for 1954-2015. The equatorial Pacific cold tongue in the forecasts is too strong and extends excessively westward due to a combination of the model’s inherent climatological bias, initialization imbalance, and errors in initial ocean data. The forecasts show a stronger cold tongue bias in the first year than that inherent to the model due to the imbalance between initial subsurface oceanic states and model dynamics. The cold tongue bias affects not only the pattern and amplitude but also the duration of ENSO in the forecasts by altering ocean-atmosphere feedbacks. The predicted sea surface temperature anomalies related to ENSO extend to the far western equatorial Pacific during boreal summer when the cold tongue bias is strong, and the predicted ENSO anomalies are too weak in the central-eastern equatorial Pacific. The forecast errors of pattern and amplitude subsequently lead to errors in ENSO phase transition by affecting the amplitude of the negative thermocline feedback in the equatorial Pacific and tropical interbasin adjustments during the mature phase of ENSO. These ENSO forecast errors further degrade the predictions of wintertime atmospheric teleconnections, land surface air temperature, and rainfall anomalies over the Northern Hemisphere. These mean-state and ENSO forecast biases are more pronounced in forecasts initialized in boreal spring-summer than other seasons due to the seasonal intensification of the Bjerknes feedback.

Clara Deser

Papers

The inherent uncertainty of precipitation variability, trends, and extremes due to internal variability, with implications for Western US water resources

Changes in Variability Associated with Climate Change

The equatorial Pacific cold tongue bias in CESM1 and its influence on ENSO forecasts

How Well Do We Know the Surface Impact of Sudden Stratospheric Warmings

Proceedings of the NASA Workshop on Decadal Climate Variability