Advancing decadal-scale climate prediction in the North Atlantic sector

Remotely sensing potential climate change tipping points across scales

Potential climate tipping points pose a growing risk for societies, and policy is calling for improved anticipation of them. Satellite remote sensing can play a unique role in identifying and anticipating tipping phenomena across scales. Where satellite records are too short for temporal early warning of tipping points, complementary spatial indicators can leverage the exceptional spatial-temporal coverage of remotely sensed data to detect changing resilience of vulnerable systems. Combining Earth observation with Earth system models can improve process-based understanding of tipping points, their interactions, and potential tipping cascades. Such fine-resolution sensing can support climate tipping point risk management across scales.

Skillful prediction of summer rainfall in the Tibetan Plateau on multiyear time scales

Skillful near-term climate predictions of rainfall over the Tibetan Plateau (TP), the Asian water tower, benefit billions of people. On the basis of the state-of-the-art decadal prediction models, we showed evidence that although the raw model outputs show low predicted ability for the summer Inner TP (ITP) rainfall due to low signal-to-noise ratios in models, we can produce realistic predictions by extracting the predictable signal from large ensemble predictions along with a postprocessing procedure of variance adjustment. The results indicate that the summer ITP rainfall is highly predictable on multiyear time scales. The predictability of ITP rainfall originates from the Silk Road pattern driven by sea surface temperature over the subpolar gyre region in North Atlantic. Real-time forecasts suggest that the ITP will become wetter, with 12.8% increase in rainfall during 2020-2027 relative to 1986-2005. Our results will help the water resources management in the surrounding regions.

Contrasting surface warming of a marginal basin due to large-scale climatic patterns and local forcing

The Mediterranean Sea is one of the first regions where sea surface temperature (SST) increase was linked to greenhouse effects and global warming. Due to its sensitivity to climate variability and its high impact on local and remote climate conditions, much effort has been made to assess the SST variability in the Mediterranean as a whole. However, the Mediterranean is composed of several basins, each of which plays a different role in its conveyor belt’s function. This study focuses on the basin of the Tyrrhenian Sea which represents one of the crucial areas for deep mixing of the Mediterranean main water masses. Thirty-seven years (1982–2018) of satellite-derived data were used to investigate the SST variability in relation to large-scale and local forcing mechanisms. A significant warming trend of 0.034 ± 0.004 °C/year was found, which led to an average warming of 1.288 ± 0.129 °C over the considered period. The observed warming presents time-dependent spatial patterns as well as changes in the seasonal cycle. Our results highlight that the Tyrrhenian’s individual long-term surface variability has different characteristics than the Mediterranean as a whole and provide insight into the relative influence of large-scale teleconnection patterns and local air-sea interaction on this variability.

Quo vadis Pantanal? Expected precipitation extremes and drought dynamics from changing sea surface temperature

Climate change poses a critical threat to the Pantanal, the largest wetland in the world. Models indicate an increase in the frequency of extreme precipitation events and extended periods of drought. These changes can amplify consequences for Pantanal’s ecological functioning, which has already experienced intensive human modification of its hydrological system and environmental health. The present study analyzed the spatial and temporal dynamics of rainfall and resulting extremes in the Brazilian area of the Upper Paraguay River Basin (UPRB) along with a co-evaluation of the global Sea Surface Temperature data (SST). The predicted results indicate that wet extreme precipitation events will become more frequent in the highlands, while severe and prolonged droughts triggered by warming SSTs in the Northern Hemisphere (North Atlantic and North Pacific oceans) will affect the Pantanal. The linear relations between precipitation with SST of very specific oceanic regions and even from specific oceanic indexes obtained in the present study significantly improve the forecasting capacity, mainly from a resulting reduction to two months of the lead-time between SST warming to concomitant precipitation impacts, and by explaining 80% of Pantanal´s precipitation variation from major oceanic indexes (e.g., ENSO, PDO, NAO, ATL3). Current SST trends will result in inter- and intra-annual flooding dynamic alterations, drastically affecting the Pantanal ecosystem functioning, with consequences for wildlife diversity and distribution. Regarding the foreseeable global climate and land use change scenarios, the results from the present study provide solid evidence that can be used at different decision-making levels (from local to global) for identifying the most appropriate management practices and effectively achieving sustainability of the anthropic activity occurring in the Pantanal.

Climate Change Impact in the Ria de Aveiro Lagoon Ecosystem: A Case Study

Climate change and global sea-level rise are major issues of the 21st century. The main goal of this study is to assess the physical and biogeochemical status of the Ria de Aveiro lagoon (Portugal) under future climate scenarios, using a coupled physical/ eutrophication model. The impact on the lagoon ecosystem status of the mean sea level rise (MSLR), the amplitude rise of the M2 tidal constituent (M2R), the changes in the river discharge, and the rising of the air temperature was investigated. Under MSLR and M2R, the results point to an overall salinity increase and water temperature decrease, revealing ocean water dominance. The main lagoon areas presented salinity values close to those of the ocean waters (~34 PSU), while a high range of salinity was presented for the river and the far end areas (20–34 PSU). The water temperature showed a decrease of approximately 0.5–1.5 °C. The responses of the biogeochemical variables reflect the increase of the oceanic inflow (transparent and nutrient-poor water) or the reduction of the river flows (nutrient-rich waters). The results evidenced, under the scenarios, an overall decreasing of the inorganic nitrogen concentration and the carbon phytoplankton concentrations. A warm climate, although increasing the water temperature, does not seem to affect the lagoon’s main status, at least in the frame of the model used in the study.

Consistent multi-decadal variability in global temperature reconstructions and simulations over the Common Era

Multi-decadal surface temperature changes may be forced by natural as well as anthropogenic factors, or arise unforced from the climate system. Distinguishing these factors is essential for estimating sensitivity to multiple climatic forcings and the amplitude of the unforced variability. Here we present 2,000-year-long global mean temperature reconstructions using seven different statistical methods that draw from a global collection of temperature-sensitive paleoclimate records. Our reconstructions display synchronous multi-decadal temperature fluctuations, which are coherent with one another and with fully forced CMIP5 millennial model simulations across the Common Era. The most significant attribution of pre-industrial (1300-1800 CE) variability at multi-decadal timescales is to volcanic aerosol forcing. Reconstructions and simulations qualitatively agree on the amplitude of the unforced global mean multi-decadal temperature variability, thereby increasing confidence in future projections of climate change on these timescales. The largest warming trends at timescales of 20 years and longer occur during the second half of the 20^th century, highlighting the unusual character of the warming in recent decades.

Benchmark decadal forecast skill for terrestrial water storage estimated by an elasticity framework

A reliable decadal prediction of terrestrial water storage (TWS) is critical for a sustainable management of freshwater resources and infrastructures. However, the dependence of TWS forecast skill on the accuracy of initial hydrological conditions and decadal climate forecasts is not clear, and the baseline skill remains unknown. Here we use decadal climate hindcasts and perform hydrological ensemble simulations to estimate a benchmark decadal forecast skill for TWS over global major river basins with an elasticity framework that considers varying skill of initial conditions and climate forecasts. The initial condition skill elasticity is higher than climate forecast skill elasticity over many river basins at 1-4 years lead, suggesting the dominance of initial conditions at short leads. However, our benchmark skill for TWS is significantly higher than initial conditions-based forecast skill over 25 and 31% basins for the leads of 1-4 and 3-6 years, and incorporating climate prediction can significantly increase TWS prediction skill over half of the river basins at long leads, especially over mid- and high-latitudes. Our findings imply the possibility of improving decadal TWS forecasts by using dynamical climate prediction information, and the necessity of using the new benchmark skill for verifying the success of decadal hydrological forecasts.

Predictability of phases and magnitudes of natural decadal climate variability phenomena in CMIP5 experiments with the UKMO HadCM3, GFDL-CM2.1, NCAR-CCSM4, and MIROC5 global earth system models

Data from decadal hindcast experiments conducted under CMIP5 were used to assess the ability of CM2.1, HadCM3, MIROC5, and CCSM4 Earth System Models (ESMs) to hindcast sea-surface temperature (SST) indices of the Pacific Decadal Oscillation (PDO), the tropical Atlantic SST gradient (TAG) variability, and the West Pacific Warm Pool (WPWP) SST variability from 1961 to 2010. The ESMs were initialized at specific times with observed data to make 10- and 30-year hindcasts/forecasts. Deterministic and probabilistic skill estimates show predictability of detrended WPWP index to 5 years' lead time and of non-detrended WPWP index to 10 years' lead time. These estimates also show atypical skill dependence of PDO and TAG indices on lead times, with increasing skill in the middle to end of 10-year hindcasts. The skill of ESMs to hindcast an observed DCV index (signal skill) is surprisingly greater than the skill to hindcast their own DCV index (noise skill) at some lead times. All ESMs hindcast occurrence frequencies of positive and negative phases of the indices, and probabilities of same-phase transitions from one year to the next reasonably well. Four, major, low-latitude volcanic eruptions are associated with phase transitions of all observed and some of the ensemble-average hindcast indices. All ESMs' WPWP index hindcasts respond correctly to all eruptions as do three observed PDO phase transitions. No one of the ESMs' hindcasts of the TAG index responds correctly to these eruptions. Some of the ESMs hindcast correct phase transitions in the absence of eruptions also, implying that initializations with observed data are beneficial in predicting phase transitions. The skills of DCV indices' phase prediction up to at least two years in advance can be used to inform societal impacts adaptation decisions in water resources management and agriculture. The Atlantic region's responses in these ESMs appear to be fundamentally incorrect.

Role of subsurface ocean in decadal climate predictability over the South Atlantic

Decadal climate predictability in the South Atlantic is explored by performing reforecast experiments using a coupled general circulation model with two initialization schemes; one is assimilated with observed sea surface temperature (SST) only, and the other is additionally assimilated with observed subsurface ocean temperature and salinity. The South Atlantic is known to undergo decadal variability exhibiting a meridional dipole of SST anomalies through variations in the subtropical high and ocean heat transport. Decadal reforecast experiments in which only the model SST is initialized with the observation do not predict well the observed decadal SST variability in the South Atlantic, while the other experiments in which the model SST and subsurface ocean are initialized with the observation skillfully predict the observed decadal SST variability, particularly in the Southeast Atlantic. In-depth analysis of upper-ocean heat content reveals that a significant improvement of zonal heat transport in the Southeast Atlantic leads to skillful prediction of decadal SST variability there. These results demonstrate potential roles of subsurface ocean assimilation in the skillful prediction of decadal climate variability over the South Atlantic.

Decadal climate predictability in the southern Indian Ocean captured by SINTEX-F using a simple SST-nudging scheme

Decadal climate variability in the southern Indian Ocean has great influences on southern African climate through modulation of atmospheric circulation. Although many efforts have been made to understanding physical mechanisms, predictability of the decadal climate variability, in particular, the internally generated variability independent from external atmospheric forcing, remains poorly understood. This study investigates predictability of the decadal climate variability in the southern Indian Ocean using a coupled general circulation model, called SINTEX-F. The ensemble members of the decadal reforecast experiments were initialized with a simple sea surface temperature (SST) nudging scheme. The observed positive and negative peaks during late 1990s and late 2000s are well reproduced in the reforecast experiments initiated from 1994 and 1999, respectively. The experiments initiated from 1994 successfully capture warm SST and high sea level pressure anomalies propagating from the South Atlantic to the southern Indian Ocean. Also, the other experiments initiated from 1999 skillfully predict phase change from a positive to negative peak. These results suggest that the SST-nudging initialization has the essence to capture the predictability of the internally generated decadal climate variability in the southern Indian Ocean.

Strong Dependence of U.S. Summertime Air Quality on the Decadal Variability of Atlantic Sea Surface Temperatures

We find that summertime air quality in the eastern U.S. displays strong dependence on North Atlantic sea surface temperatures, resulting from large-scale ocean-atmosphere interactions. Using observations, reanalysis data sets, and climate model simulations, we further identify a multidecadal variability in surface air quality driven by the Atlantic Multidecadal Oscillation (AMO). In one-half cycle (~35 years) of the AMO from cold to warm phase, summertime maximum daily 8 h ozone concentrations increase by 1-4 ppbv and PM2.5 concentrations increase by 0.3-1.0 μg m-3 over much of the east. These air quality changes are related to warmer, drier, and more stagnant weather in the AMO warm phase, together with anomalous circulation patterns at the surface and aloft. If the AMO shifts to the cold phase in future years, it could partly offset the climate penalty on U.S. air quality brought by global warming, an effect which should be considered in long-term air quality planning.

Reconciling controversies about the 'global warming hiatus'

Between about 1998 and 2012, a time that coincided with political negotiations for preventing climate change, the surface of Earth seemed hardly to warm. This phenomenon, often termed the 'global warming hiatus', caused doubt in the public mind about how well anthropogenic climate change and natural variability are understood. Here we show that apparently contradictory conclusions stem from different definitions of 'hiatus' and from different datasets. A combination of changes in forcing, uptake of heat by the oceans, natural variability and incomplete observational coverage reconciles models and data. Combined with stronger recent warming trends in newer datasets, we are now more confident than ever that human influence is dominant in long-term warming.

Improved decadal climate prediction in the North Atlantic using EnOI-assimilated initial condition

Decadal prediction experiments of Beijing Climate Center climate system model version 1.1 (BCC-CSM1.1) participated in Coupled Model Intercomparison Project Phase 5 (CMIP5) had poor skill in extratropics of the North Atlantic, the initialization of which was done by relaxing modeled ocean temperature to the Simple Ocean Data Assimilation (SODA) reanalysis data. This study aims to improve the prediction skill of this model by using the assimilation technique in the initialization. New ocean data are firstly generated by assimilating the sea surface temperature (SST) of the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) dataset to the ocean model of BCC-CSM1.1 via Ensemble Optimum Interpolation (EnOI). Then a suite of decadal re-forecasts launched annually over the period 1961-2005 is carried out with simulated ocean temperature restored to the assimilated ocean data. Comparisons between the re-forecasts and previous CMIP5 forecasts show that the re-forecasts are more skillful in mid-to-high latitude SST of the North Atlantic. Improved prediction skill is also found for the Atlantic multi-decadal oscillation (AMO), which is consistent with the better skill of Atlantic meridional overturning circulation (AMOC) predicted by the re-forecasts. We conclude that the EnOI assimilation generates better ocean data than the SODA reanalysis for initializing decadal climate prediction of BCC-CSM1.1 model.

Skillful prediction of northern climate provided by the ocean

It is commonly understood that a potential for skillful climate prediction resides in the ocean. It nevertheless remains unresolved to what extent variable ocean heat is imprinted on the atmosphere to realize its predictive potential over land. Here we assess from observations whether anomalous heat in the Gulf Stream's northern extension provides predictability of northwestern European and Arctic climate. We show that variations in ocean temperature in the high latitude North Atlantic and Nordic Seas are reflected in the climate of northwestern Europe and in winter Arctic sea ice extent. Statistical regression models show that a significant part of northern climate variability thus can be skillfully predicted up to a decade in advance based on the state of the ocean. Particularly, we predict that Norwegian air temperature will decrease over the coming years, although staying above the long-term (1981–2010) average. Winter Arctic sea ice extent will remain low but with a general increase towards 2020.

The degree to which ocean heat is imprinted on the atmosphere and can be used to predict climate remains unclear. Here, the authors demonstrate skillful observation-based prediction of northwestern European and Arctic climate from upstream sea surface temperature anomalies in the subpolar North Atlantic.

Recent Progress in Understanding and Predicting Atlantic Decadal Climate Variability

PURPOSE OF REVIEW

Recent Atlantic climate prediction studies are an exciting new contribution to an extensive body of research on Atlantic decadal variability and predictability that has long emphasized the unique role of the Atlantic Ocean in modulating the surface climate. We present a survey of the foundations and frontiers in our understanding of Atlantic variability mechanisms, the role of the Atlantic Meridional Overturning Circulation (AMOC), and our present capacity for putting that understanding into practice in actual climate prediction systems.

RECENT FINDINGS

The AMOC-or more precisely, the buoyancy-forced thermohaline circulation (THC) that encompasses both overturning and gyre circulations-appears to underpin decadal timescale prediction skill in the subpolar North Atlantic in retrospective forecasts. Skill in predicting more wide-ranging climate variations, including those over land, is more limited, but there are indications this could improve with more advanced models.

SUMMARY

Preliminary successes in the field of initialized Atlantic climate prediction confirm the climate relevance of low-frequency Atlantic Ocean dynamics and suggest that useful decadal climate prediction is a realizable goal.

Decadal predictions of the North Atlantic CO2 uptake

As a major CO₂ sink, the North Atlantic, especially its subpolar gyre region, is essential for the global carbon cycle. Decadal fluctuations of CO₂ uptake in the North Atlantic subpolar gyre region are associated with the evolution of the North Atlantic Oscillation, the Atlantic meridional overturning circulation, ocean mixing and sea surface temperature anomalies. While variations in the physical state of the ocean can be predicted several years in advance by initialization of Earth system models, predictability of CO₂ uptake has remained unexplored. Here we investigate the predictability of CO₂ uptake variations by initialization of the MPI-ESM decadal prediction system. We find large multi-year variability in oceanic CO₂ uptake and demonstrate that its potential predictive skill in the western subpolar gyre region is up to 4–7 years. The predictive skill is mainly maintained in winter and is attributed to the improved physical state of the ocean.

Predictability of variations in the ocean carbon sink has remained unexplored in previous decadal prediction studies based on modern Earth system models. Here, the authors show that potential predictive skill of the ocean CO₂ uptake in the North Atlantic western subpolar gyre region is up to 4–7 years.

Ocean Data Assimilation in Support of Climate Applications: Status and Perspectives

Ocean data assimilation brings together observations with known dynamics encapsulated in a circulation model to describe the time-varying ocean circulation. Its applications are manifold, ranging from marine and ecosystem forecasting to climate prediction and studies of the carbon cycle. Here, we address only climate applications, which range from improving our understanding of ocean circulation to estimating initial or boundary conditions and model parameters for ocean and climate forecasts. Because of differences in underlying methodologies, data assimilation products must be used judiciously and selected according to the specific purpose, as not all related inferences would be equally reliable. Further advances are expected from improved models and methods for estimating and representing error information in data assimilation systems. Ultimately, data assimilation into coupled climate system components is needed to support ocean and climate services. However, maintaining the infrastructure and expertise for sustained data assimilation remains challenging.

Skilful multi-year predictions of tropical trans-basin climate variability

Tropical Pacific sea surface temperature anomalies influence the atmospheric circulation, impacting climate far beyond the tropics. The predictability of the corresponding atmospheric signals is typically limited to less than 1 year lead time. Here we present observational and modelling evidence for multi-year predictability of coherent trans-basin climate variations that are characterized by a zonal seesaw in tropical sea surface temperature and sea-level pressure between the Pacific and the other two ocean basins. State-of-the-art climate model forecasts initialized from a realistic ocean state show that the low-frequency trans-basin climate variability, which explains part of the El Niño Southern Oscillation flavours, can be predicted up to 3 years ahead, thus exceeding the predictive skill of current tropical climate forecasts for natural variability. This low-frequency variability emerges from the synchronization of ocean anomalies in all basins via global reorganizations of the atmospheric Walker Circulation.

Sea surface temperature anomalies in the tropical Pacific can influence global atmospheric circulation, yet prediction of this atmospheric signal is limited to less than 1 year. Here, the authors present observational and modelling evidence for multi-year predictability.

Application of the singular spectrum analysis technique to study the recent hiatus on the global surface temperature record

Global surface temperature has been increasing since the beginning of the 20th century but with a highly variable warming rate, and the alternation of rapid warming periods with 'hiatus' decades is a constant throughout the series. The superimposition of a secular warming trend with natural multidecadal variability is the most accepted explanation for such a pattern. Since the start of the 21st century, the surface global mean temperature has not risen at the same rate as the top-of-atmosphere radiative energy input or greenhouse gas emissions, provoking scientific and social interest in determining the causes of this apparent discrepancy. Multidecadal natural variability is the most commonly proposed cause for the present hiatus period. Here, we analyze the HadCRUT4 surface temperature database with spectral techniques to separate a multidecadal oscillation (MDV) from a secular trend (ST). Both signals combined account for nearly 88% of the total variability of the temperature series showing the main acceleration/deceleration periods already described elsewhere. Three stalling periods with very little warming could be found within the series, from 1878 to 1907, from 1945 to 1969 and from 2001 to the end of the series, all of them coincided with a cooling phase of the MDV. Henceforth, MDV seems to be the main cause of the different hiatus periods shown by the global surface temperature records. However, and contrary to the two previous events, during the current hiatus period, the ST shows a strong fluctuation on the warming rate, with a large acceleration (0.0085°C year(-1) to 0.017°C year(-1)) during 1992-2001 and a sharp deceleration (0.017°C year(-1) to 0.003°C year(-1)) from 2002 onwards. This is the first time in the observational record that the ST shows such variability, so determining the causes and consequences of this change of behavior needs to be addressed by the scientific community.

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.

Regional projections of North Indian climate for adaptation studies

Adaptation is increasingly important for regions around the world where large changes in climate could have an impact on populations and industry. The Brahmaputra-Ganges catchments have a large population, a main industry of agriculture and a growing hydro-power industry, making the region susceptible to changes in the Indian Summer Monsoon, annually the main water source. The HighNoon project has completed four regional climate model simulations for India and the Himalaya at high resolution (25km) from 1960 to 2100 to provide an ensemble of simulations for the region. In this paper we have assessed the ensemble for these catchments, comparing the simulations with observations, to give credence that the simulations provide a realistic representation of atmospheric processes and therefore future climate. We have illustrated how these simulations could be used to provide information on potential future climate impacts and therefore aid decision-making using climatology and threshold analysis. The ensemble analysis shows an increase in temperature between the baseline (1970-2000) and the 2050s (2040-2070) of between 2 and 4°C and an increase in the number of days with maximum temperatures above 28°C and 35°C. There is less certainty for precipitation and runoff which show considerable variability, even in this relatively small ensemble, spanning zero. The HighNoon ensemble is the most complete data for the region providing useful information on a wide range of variables for the regional climate of the Brahmaputra-Ganges region, however there are processes not yet included in the models that could have an impact on the simulations of future climate. We have discussed these processes and show that the range from the HighNoon ensemble is similar in magnitude to potential changes in projections where these processes are included. Therefore strategies for adaptation must be robust and flexible allowing for advances in the science and natural environmental changes.

Understanding the causes of recent warming of mediterranean waters. How much could be attributed to climate change?

During the past two decades, Mediterranean waters have been warming at a rather high rate resulting in scientific and social concern. This warming trend is observed in satellite data, field data and model simulations, and affects both surface and deep waters throughout the Mediterranean basin. However, the warming rate is regionally different and seems to change with time, which has led to the question of what causes underlie the observed trends. Here, we analyze available satellite information on sea surface temperature (SST) from the last 25 years using spectral techniques and find that more than half of the warming tendency during this period is due to a non-linear, wave-like tendency. Using a state of the art hydrodynamic model, we perform a hindcast simulation and obtain the simulated SST evolution of the Mediterranean basin for the last 52 years. These SST results show a clear sinusoidal tendency that follows the Atlantic Multidecadal Oscillation (AMO) during the simulation period. Our results reveal that 58% of recent warming in Mediterranean waters could be attributed to this AMO-like oscillation, being anthropogenic-induced climate change only responsible for 42% of total trend. The observed acceleration of water warming during the 1990s therefore appears to be caused by a superimposition of anthropogenic-induced warming with the positive phase of the AMO, while the recent slowdown of this tendency is likely due to a shift in the AMO phase. It has been proposed that this change in the AMO phase will mask the effect of global warming in the forthcoming decades, and our results indicate that the same could also be applicable to the Mediterranean Sea. Henceforth, natural multidecadal temperature oscillations should be taken into account to avoid underestimation of the anthropogenic-induced warming of the Mediterranean basin in the future.

Initialized near-term regional climate change prediction

Climate models are seen by many to be unverifiable. However, near-term climate predictions up to 10 years into the future carried out recently with these models can be rigorously verified against observations. Near-term climate prediction is a new information tool for the climate adaptation and service communities, which often make decisions on near-term time scales, and for which the most basic information is unfortunately very scarce. The Fifth Coupled Model Intercomparison Project set of co-ordinated climate-model experiments includes a set of near-term predictions in which several modelling groups participated and whose forecast quality we illustrate here. We show that climate forecast systems have skill in predicting the Earth's temperature at regional scales over the past 50 years and illustrate the trustworthiness of their predictions. Most of the skill can be attributed to changes in atmospheric composition, but also partly to the initialization of the predictions.

Near-term climate prediction is an information tool used in climate adaptation services. This study analyses the quality of the predictions, showing that near-term climate forecasts have good skill in predicting temperature at regional scales, where most of the skill is attributed to atmospheric composition changes.

Marine ecosystem response to the Atlantic Multidecadal Oscillation

Against the backdrop of warming of the Northern Hemisphere it has recently been acknowledged that North Atlantic temperature changes undergo considerable variability over multidecadal periods. The leading component of natural low-frequency temperature variability has been termed the Atlantic Multidecadal Oscillation (AMO). Presently, correlative studies on the biological impact of the AMO on marine ecosystems over the duration of a whole AMO cycle (∼60 years) is largely unknown due to the rarity of continuously sustained biological observations at the same time period. To test whether there is multidecadal cyclic behaviour in biological time-series in the North Atlantic we used one of the world's longest continuously sustained marine biological time-series in oceanic waters, long-term fisheries data and historical records over the last century and beyond. Our findings suggest that the AMO is far from a trivial presence against the backdrop of continued temperature warming in the North Atlantic and accounts for the second most important macro-trend in North Atlantic plankton records; responsible for habitat switching (abrupt ecosystem/regime shifts) over multidecadal scales and influences the fortunes of various fisheries over many centuries.

Oceanographers' contribution to climate modelling and prediction: progress to date and a future perspective

The ocean plays an essential role in determining aspects of the climate through its influence on coupled processes involving the atmosphere, cyrosphere and biogeochemistry, including budgets of heat and carbon dioxide and sea-level rise. Here, the key developments in ocean modelling over the past 20 years are reviewed and the prospects for the next 20 years are outlined, considering a hierarchy of idealized, conceptual and realistic modelling frameworks. It is emphasized that any long-term modelling strategy needs to be underpinned and complemented by fundamental theoretical and observational research activities. The need to be aware of the societal and technological drivers that will shape future research directions is also articulated.

Causes and consequences of past and projected Scandinavian summer temperatures, 500-2100 AD

Tree rings dominate millennium-long temperature reconstructions and many records originate from Scandinavia, an area for which the relative roles of external forcing and internal variation on climatic changes are, however, not yet fully understood. Here we compile 1,179 series of maximum latewood density measurements from 25 conifer sites in northern Scandinavia, establish a suite of 36 subset chronologies, and analyse their climate signal. A new reconstruction for the 1483–2006 period correlates at 0.80 with June–August temperatures back to 1860. Summer cooling during the early 17th century and peak warming in the 1930s translate into a decadal amplitude of 2.9°C, which agrees with existing Scandinavian tree-ring proxies. Climate model simulations reveal similar amounts of mid to low frequency variability, suggesting that internal ocean-atmosphere feedbacks likely influenced Scandinavian temperatures more than external forcing. Projected 21st century warming under the SRES A2 scenario would, however, exceed the reconstructed temperature envelope of the past 1,500 years.

Tracking the Atlantic Multidecadal Oscillation through the last 8,000 years

Understanding the internal ocean variability and its influence on climate is imperative for society. A key aspect concerns the enigmatic Atlantic Multidecadal Oscillation (AMO), a feature defined by a 60- to 90-year variability in North Atlantic sea-surface temperatures. The nature and origin of the AMO is uncertain, and it remains unknown whether it represents a persistent periodic driver in the climate system, or merely a transient feature. Here, we show that distinct, ∼55- to 70-year oscillations characterized the North Atlantic ocean-atmosphere variability over the past 8,000 years. We test and reject the hypothesis that this climate oscillation was directly forced by periodic changes in solar activity. We therefore conjecture that a quasi-persistent ∼55- to 70-year AMO, linked to internal ocean-atmosphere variability, existed during large parts of the Holocene. Our analyses further suggest that the coupling from the AMO to regional climate conditions was modulated by orbitally induced shifts in large-scale ocean-atmosphere circulation.

The origin of the Atlantic Multidecadal Oscillation, a semi-periodic variability of sea-surface temperature, is unknown. Knudsen et al. show that 55- to 70-year climate oscillations existed throughout the last 8,000 years, suggesting that the Atlantic Multidecadal Oscillation is a permanent feature of the Holocene climate induced by internal ocean variability.

Forecasting the dynamics of a coastal fishery species using a coupled climate--population model

Marine fisheries management strives to maintain sustainable populations while allowing exploitation. However, well-intentioned management plans may not meet this balance as most do not include the effect of climate change. Ocean temperatures are expected to increase through the 21st century, which will have far-reaching and complex impacts on marine fisheries. To begin to quantify these impacts for one coastal fishery along the east coast of the United States, we develop a coupled climate-population model for Atlantic croaker (Micropogonias undulatus). The model is based on a mechanistic hypothesis: recruitment is determined by temperature-driven, overwinter mortality of juveniles in their estuarine habitats. Temperature forecasts were obtained from 14 general circulation models simulating three CO2 emission scenarios. An ensemble-based approach was used in which a multimodel average was calculated for a given CO2 emission scenario to forecast the response of the population. The coupled model indicates that both exploitation and climate change significantly affect abundance and distribution of Atlantic croaker. At current levels of fishing, the average (2010-2100) spawning biomass of the population is forecast to increase by 60-100%. Similarly, the center of the population is forecast to shift 50 100 km northward. A yield analysis, which is used to calculate benchmarks for fishery management, indicates that the maximum sustainable yield will increase by 30 100%. Our results demonstrate that climate effects on fisheries must be identified, understood, and incorporated into the scientific advice provided to managers if sustainable exploitation is to be achieved in a changing climate.

Pacific decadal oscillation hindcasts relevant to near-term climate prediction

Decadal-scale climate variations over the Pacific Ocean and its surroundings are strongly related to the so-called Pacific decadal oscillation (PDO) which is coherent with wintertime climate over North America and Asian monsoon, and have important impacts on marine ecosystems and fisheries. In a near-term climate prediction covering the period up to 2030, we require knowledge of the future state of internal variations in the climate system such as the PDO as well as the global warming signal. We perform sets of ensemble hindcast and forecast experiments using a coupled atmosphere-ocean climate model to examine the predictability of internal variations on decadal timescales, in addition to the response to external forcing due to changes in concentrations of greenhouse gases and aerosols, volcanic activity, and solar cycle variations. Our results highlight that an initialization of the upper-ocean state using historical observations is effective for successful hindcasts of the PDO and has a great impact on future predictions. Ensemble hindcasts for the 20th century demonstrate a predictive skill in the upper-ocean temperature over almost a decade, particularly around the Kuroshio-Oyashio extension (KOE) and subtropical oceanic frontal regions where the PDO signals are observed strongest. A negative tendency of the predicted PDO phase in the coming decade will enhance the rising trend in surface air-temperature (SAT) over east Asia and over the KOE region, and suppress it along the west coasts of North and South America and over the equatorial Pacific. This suppression will contribute to a slowing down of the global-mean SAT rise.

Ecology and the ratchet of events: climate variability, niche dimensions, and species distributions

Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and more-fundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics.

Long-term natural variability and 20th century climate change

Global mean temperature at the Earth's surface responds both to externally imposed forcings, such as those arising from anthropogenic greenhouse gases, as well as to natural modes of variability internal to the climate system. Variability associated with these latter processes, generally referred to as natural long-term climate variability, arises primarily from changes in oceanic circulation. Here we present a technique that objectively identifies the component of inter-decadal global mean surface temperature attributable to natural long-term climate variability. Removal of that hidden variability from the actual observed global mean surface temperature record delineates the externally forced climate signal, which is monotonic, accelerating warming during the 20th century.

Indicators on economic risk from global climate change

Climate change mitigation requires a rapid decrease of global emissions of greenhouse gases (GHGs) from their present value of 8.4 Gt/C/year to, as of current knowledge, approximately 1 GtC/year by the end of the century. The necessary decrease of GHG emissions will have large impacts on existing and new investments with long lifetimes, such coal-fired power plants or buildings. Strategic decision making for major investments can be facilitated by indicators that express the likelihood of costly retrofitting or shut-down of carbon intensive equipment over time. We provide a set of simple indicators that support assessment and decision making in this field. Given a certain emissions target, carbon allowance prices in a cap-and-trade plan will depend on the development of the global economy and the degree to which the target is approached on the global and national levels. The indicators measure the degree to which a given emissions target is approached nationally and assess risks for long-lived investments subject to a range of emissions targets. A comparative case study on existing coal-fired power plants with planned plants and utility-scale photovoltaic power-plants confirms that high risk for coal-fired power plants is emerging. New legislation further confirms this result.

Climate predictability in the second year

In this paper, the predictability of climate arising from ocean heat content (OHC) anomalies is investigated in the HadCM3 coupled atmosphere-ocean model. An ensemble of simulations of the twentieth century are used to provide initial conditions for a case study. The case study consists of two ensembles started from initial conditions with large differences in regional OHC in the North Atlantic, the Southern Ocean and parts of the West Pacific. Surface temperatures and precipitation are on average not predictable beyond seasonal time scales, but for certain initial conditions there may be longer predictability. It is shown that, for the case study examined here, some aspects of tropical precipitation, European surface temperatures and North Atlantic sea-level pressure are potentially predictable 2 years ahead. Predictability also exists in the other case studies, but the climate variables and regions, which are potentially predictable, differ. This work was done as part of the Grid for Coupled Ensemble Prediction (GCEP) eScience project.

Chapter 1. Impacts of the oceans on climate change

The oceans play a key role in climate regulation especially in part buffering (neutralising) the effects of increasing levels of greenhouse gases in the atmosphere and rising global temperatures. This chapter examines how the regulatory processes performed by the oceans alter as a response to climate change and assesses the extent to which positive feedbacks from the ocean may exacerbate climate change. There is clear evidence for rapid change in the oceans. As the main heat store for the world there has been an accelerating change in sea temperatures over the last few decades, which has contributed to rising sea-level. The oceans are also the main store of carbon dioxide (CO2), and are estimated to have taken up approximately 40% of anthropogenic-sourced CO2 from the atmosphere since the beginning of the industrial revolution. A proportion of the carbon uptake is exported via the four ocean 'carbon pumps' (Solubility, Biological, Continental Shelf and Carbonate Counter) to the deep ocean reservoir. Increases in sea temperature and changing planktonic systems and ocean currents may lead to a reduction in the uptake of CO2 by the ocean; some evidence suggests a suppression of parts of the marine carbon sink is already underway. While the oceans have buffered climate change through the uptake of CO2 produced by fossil fuel burning this has already had an impact on ocean chemistry through ocean acidification and will continue to do so. Feedbacks to climate change from acidification may result from expected impacts on marine organisms (especially corals and calcareous plankton), ecosystems and biogeochemical cycles. The polar regions of the world are showing the most rapid responses to climate change. As a result of a strong ice-ocean influence, small changes in temperature, salinity and ice cover may trigger large and sudden changes in regional climate with potential downstream feedbacks to the climate of the rest of the world. A warming Arctic Ocean may lead to further releases of the potent greenhouse gas methane from hydrates and permafrost. The Southern Ocean plays a critical role in driving, modifying and regulating global climate change via the carbon cycle and through its impact on adjacent Antarctica. The Antarctic Peninsula has shown some of the most rapid rises in atmospheric and oceanic temperature in the world, with an associated retreat of the majority of glaciers. Parts of the West Antarctic ice sheet are deflating rapidly, very likely due to a change in the flux of oceanic heat to the undersides of the floating ice shelves. The final section on modelling feedbacks from the ocean to climate change identifies limitations and priorities for model development and associated observations. Considering the importance of the oceans to climate change and our limited understanding of climate-related ocean processes, our ability to measure the changes that are taking place are conspicuously inadequate. The chapter highlights the need for a comprehensive, adequately funded and globally extensive ocean observing system to be implemented and sustained as a high priority. Unless feedbacks from the oceans to climate change are adequately included in climate change models, it is possible that the mitigation actions needed to stabilise CO2 and limit temperature rise over the next century will be underestimated.