Abstract
We review the growing evidence for a widespread inconsistency between the low strength of predictable signals in climate models and the relatively high level of agreement they exhibit with ...observed variability of the atmospheric circulation. This discrepancy is particularly evident in the climate variability of the Atlantic sector, where ensemble predictions using climate models generally show higher correlation with observed variability than with their own simulations, and higher correlations with observations than would be expected from their small signal-to-noise ratios, hence a ‘signal-to-noise paradox’. This unusual behaviour has been documented in multiple climate prediction systems and in the response to a number of different sources of climate variability. However, we also note that the total variance in the models is often close in magnitude to the observed variance, and so it is not a simple matter of models containing too much variability. Instead, the proportion of Atlantic climate variance that is predictable in climate models appears to be too weak in amplitude by a factor of two, or perhaps more. In this review, we provide a range of examples from existing studies to build the case for a problem that is common across different climate models, common to several different sources of climate variability and common across a range of timescales. We also discuss the wider implications of this intriguing paradox.
It is well established that El Niño–Southern Oscillation (ENSO) impacts the North Atlantic–European (NAE) climate, with the strongest influence in winter. In late winter, the ENSO signal travels via ...both tropospheric and stratospheric pathways to the NAE sector and often projects onto the North Atlantic Oscillation. However, this signal does not strengthen gradually during winter, and some studies have suggested that the ENSO signal is different between early and late winter and that the teleconnections involved in the early winter subperiod are not well understood. In this study, we investigate the ENSO teleconnection to NAE in early winter (November–December) and characterize the possible mechanisms involved in that teleconnection. To do so, observations, reanalysis data and the output of different types of model simulations have been used. We show that the intraseasonal winter shift of the NAE response to ENSO is detected for both El Niño and La Niña and is significant in both observations and initialized predictions, but it is not reproduced by free-running Coupled Model Intercomparison Project phase 5 (CMIP5) models. The teleconnection is established through the troposphere in early winter and is related to ENSO effects over the Gulf of Mexico and Caribbean Sea that appear in rainfall and reach the NAE region. CMIP5 model biases in equatorial Pacific ENSO sea surface temperature patterns and strength appear to explain the lack of signal in the Gulf of Mexico and Caribbean Sea and, hence, their inability to reproduce the intraseasonal shift of the ENSO signal over Europe.
One of the most repeatable phenomena seen in the atmosphere, the quasi-biennial oscillation (QBO) between prevailing eastward and westward wind jets in the equatorial stratosphere (approximately 16 ...to 50 kilometers altitude), was unexpectedly disrupted in February 2016. An unprecedented westward jet formed within the eastward phase in the lower stratosphere and cannot be accounted for by the standard QBO paradigm based on vertical momentum transport. Instead, the primary cause was waves transporting momentum from the Northern Hemisphere. Seasonal forecasts did not predict the disruption, but analogous QBO disruptions are seen very occasionally in some climate simulations. A return to more typical QBO behavior within the next year is forecast, although the possibility of more frequent occurrences of similar disruptions is projected for a warming climate.
The Atlantic Multidecadal Oscillation (AMO) is a near‐global scale mode of observed multidecadal climate variability with alternating warm and cool phases over large parts of the Northern Hemisphere. ...Many prominent examples of regional multidecadal climate variability have been related to the AMO, such as North Eastern Brazilian and African Sahel rainfall, Atlantic hurricanes and North American and European summer climate. The relative shortness of the instrumental climate record, however, limits confidence in these observationally derived relationships. Here, we seek evidence of these links in the 1400 year control simulation of the HadCM3 climate model, which produces a realistic long‐lived AMO as part of its internal climate variability. By permitting the analysis of more AMO cycles than are present in observations, we find that the model confirms the association of the AMO with almost all of the above phenomena. This has implications for the predictability of regional climate.
In winter 2013/14 a succession of storms hit the UK leading to record rainfall and flooding in many regions including south east England. In the Thames river valley there was widespread flooding, ...with clean-up costs of over £1 billion. There was no observational precedent for this level of rainfall. Here we present analysis of a large ensemble of high-resolution initialised climate simulations to show that this event could have been anticipated, and that in the current climate there remains a high chance of exceeding the observed record monthly rainfall totals in many regions of the UK. In south east England there is a 7% chance of exceeding the current rainfall record in at least one month in any given winter. Expanding our analysis to some other regions of England and Wales the risk increases to a 34% chance of breaking a regional record somewhere each winter.A succession of storms during the 2013-2014 winter led to record flooding in the UK. Here, the authors use high-resolution climate simulations to show that this event could have been anticipated and that there remains a high chance of exceeding observed record monthly rainfall totals in many parts of the UK.
The atmospheric response to Arctic and Antarctic sea ice changes typical of the present day and coming decades is investigated using the Hadley Centre global climate model (HadGEM3). The response is ...diagnosed from ensemble simulations of the period 1979 to 2009 with observed and perturbed sea ice concentrations. The experimental design allows the impacts of ocean–atmosphere coupling and the background atmospheric state to be assessed. The modeled response can be very different to that inferred from statistical relationships, showing that the response cannot be easily diagnosed from observations. Reduced Arctic sea ice drives a local low pressure response in boreal summer and autumn. Increased Antarctic sea ice drives a poleward shift of the Southern Hemisphere midlatitude jet, especially in the cold season. Coupling enables surface temperature responses to spread to the ocean, amplifying the atmospheric response and revealing additional impacts including warming of the North Atlantic in response to reduced Arctic sea ice, with a northward shift of the Atlantic intertropical convergence zone and increased Sahel rainfall. The background state controls the sign of the North Atlantic Oscillation (NAO) response via the refraction of planetary waves. This could help to resolve differences in previous studies, and potentially provides an “emergent constraint” to narrow the uncertainties in the NAO response, highlighting the need for future multimodel coordinated experiments.
Abstract
We provide a methodology to estimate possible extreme changes in seasonal rainfall for the coming decades. We demonstrate this methodology using Indian summer monsoon rainfall as an example. ...We use an ensemble of 1669 realizations of Indian summer monsoon rainfall from selected seasonal prediction systems to estimate internal variability and show how it can exacerbate or alleviate forced climate change. Our estimates show that for the next decade there is a ∼60% chance of wetting trends, whereas the chance of drying is ∼40%. Wetting trends are systematically more favoured than drying with the increasing length of the period. However, internal variability can easily negate or overwhelm the wetting trends to give temporary drying trends in rainfall. This provides a quantitative explanation for the varying trends in the past observational record of rainfall over India. We also quantify the likelihood of extreme trends and show that there is at least a 1% chance that monsoon rainfall could increase or decrease by one fifth over the next decade and that more extreme trends, though unlikely, are possible. We find that monsoon rainfall trends are influenced by trends in sea-surface temperatures over the Niño3.4 region and tropical Indian Ocean, and ∼1.5° cooling or warming of these regions can approximately double or negate the influence of climate change on rainfall over the next two decades. We also investigate the time-of-emergence of climate change signals in rainfall trends and find that it is unlikely for a climate change signal to emerge by the year 2050 due to the large internal variability of monsoon rainfall. The estimates of extreme rainfall change provided here could be useful for governments to prepare for worst-case scenarios and therefore aid disaster preparedness and decision-making.
ABSTRACT
Recent changes are found in the means and variability of the North Atlantic Oscillation (NAO) index. There has been a sustained significant recent decrease in the summer NAO since the 1990s ...and, at the same time, a striking increase in variability of the winter – especially December – NAO that resulted in three of five (two of five) record high (record low) NAO Decembers occurring during 2004–2013 in the 115‐year record. These NAO changes are related to an increasing trend in the Greenland Blocking Index (GBI, high pressure over Greenland) in summer and a more variable GBI in December. The enhanced early winter NAO variability originates mainly at the southern node of the NAO but is also related to the more variable GBI in December. Transition seasons (spring and autumn) have remained relatively unchanged over the last 30 years. These results are corroborated using several NAO indices. The Arctic Oscillation (AO) index, although strongly correlated with the NAO, does not show the recent sustained significant summer decrease, but it does show enhanced early winter variability. These recent observed changes are not present in the current generation of global climate models, although the latest process studies do offer insight into their causes. We invoke several plausible climate forcings and feedbacks to explain the recent NAO changes.
As part of the Geoengineering Model Intercomparison Project a numerical experiment known as G6sulfur has been designed in which temperatures under a high-forcing future scenario (SSP5-8.5) are ...reduced to those under a medium-forcing scenario (SSP2-4.5) using the proposed geoengineering technique of stratospheric aerosol intervention (SAI). G6sulfur involves introducing sulfuric acid aerosol into the tropical stratosphere where it reflects incoming sunlight back to space, thus cooling the planet. Here, we compare the results from six Earth-system models that have performed the G6sulfur experiment and examine how SAI affects two important modes of natural variability, the northern wintertime North Atlantic Oscillation (NAO) and the Quasi-Biennial Oscillation (QBO). Although all models show that SAI is successful in reducing global mean temperature as designed, they are also consistent in showing that it forces an increasingly positive phase of the NAO as the injection rate increases over the course of the 21st century, exacerbating precipitation reductions over parts of southern Europe compared with SSP5-8.5. In contrast to the robust result for the NAO, there is less consistency for the impact on the QBO, but the results nevertheless indicate a risk that equatorial SAI could cause the QBO to stall and become locked in a phase with permanent westerly winds in the lower stratosphere.
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