The reversibility of sea level rise

During the last century, global climate has been warming, and projections indicate that such a warming is likely to continue over coming decades. Most of the extra heat is stored in the ocean, resulting in thermal expansion of seawater and global mean sea level rise. Previous studies have shown that after CO2 emissions cease or CO2 concentration is stabilized, global mean surface air temperature stabilizes or decreases slowly, but sea level continues to rise. Using idealized CO2 scenario simulations with a hierarchy of models including an AOGCM and a step-response model, the authors show how the evolution of thermal expansion can be interpreted in terms of the climate energy balance and the vertical profile of ocean warming. Whereas surface temperature depends on cumulative CO2 emissions, sea level rise due to thermal expansion depends on the time profile of emissions. Sea level rise is smaller for later emissions, implying that targets to limit sea level rise would need to refer to the rate of emissions, not only to the time integral. Thermal expansion is in principle reversible, but to halt or reverse it quickly requires the radiative forcing to be reduced substantially, which is possible on centennial time scales only by geoengineering. If it could be done, the results indicate that heat would leave the ocean more readily than it entered, but even if thermal expansion were returned to zero, the geographical pattern of sea level would be altered. Therefore, despite any aggressive CO2 mitigation, regional sea level change is inevitable.

Using synoptic type analysis to understand New Zealand climate during the Mid-Holocene

Diagnosing the climate of New Zealand from low-resolution General Circulation Models (GCMs) is notoriously difficult due to the interaction of the complex topography and the Southern Hemisphere (SH) mid-latitude westerly winds. Therefore, methods of downscaling synoptic scale model data for New Zealand are useful to help understand past climate. New Zealand also has a wealth of palaeoclimate-proxy data to which the downscaled model output can be compared, and to provide a qualitative method of assessing the capability of GCMs to represent, in this case, the climate 6000 yr ago in the Mid-Holocene. In this paper, a synoptic weather and climate regime classification system using Empirical Orthogonal Function (EOF) analysis of GCM and reanalysis data was used. The climate regimes are associated with surface air temperature and precipitation anomalies over New Zealand. From the analysis in this study, we find at 6000 BP that increased trough activity in summer and autumn led to increased precipitation, with an increased north-south pressure gradient ("zonal events") in winter and spring leading to drier conditions. Opposing effects of increased (decreased) temperature are also seen in spring (autumn) in the South Island, which are associated with the increased zonal (trough) events; however, the circulation induced changes in temperature are likely to have been of secondary importance to the insolation induced changes. Evidence from the palaeoclimate-proxy data suggests that the Mid-Holocene was characterized by increased westerly wind events in New Zealand, which agrees with the preference for trough and zonal regimes in the models.

The atmospheric impact of uncertainties in recent Arctic Sea ice reconstructions

There are significant discrepancies between observational datasets of Arctic sea ice concentrations covering the last three decades, which result in differences of over 20% in Arctic summer sea ice extent/area and 5%–10% in winter. Previous modeling studies have shown that idealized sea ice anomalies have the potential for making a substantial impact on climate. In this paper, this theory is further developed by performing a set of simulations using the third Hadley Centre Coupled Atmospheric Model (HadAM3). The model was driven with monthly climatologies of sea ice fractions derived from three of these records to investigate potential implications of sea ice inaccuracies for climate simulations. The standard sea ice climatology from the Met Office provided a control. This study focuses on the effects of actual inaccuracies of concentration retrievals, which vary spatially and are larger in summer than winter. The smaller sea ice discrepancies in winter have a much larger influence on climate than the much greater summer sea ice differences. High sensitivity to sea ice prescription was observed, even though no SST feedbacks were included. Significant effects on surface fields were observed in the Arctic, North Atlantic, and North Pacific. Arctic average surface air temperature anomalies in winter vary by 2.5°C, and locally exceed 12°C. Arctic mean sea level pressure varies by up to 5 mb locally. Anomalies extend to 45°N over North America and Eurasia but not to lower latitudes, and with limited changes in circulation above the boundary layer. No statistically significant impact on climate variability was simulated, in terms of the North Atlantic Oscillation. Results suggest that the uncertainty in summer sea ice prescription is not critical but that winter values require greater accuracy, with the caveats that the influences of ocean–sea ice feedbacks were not included in this study.

Brief communication: Earthquake–cloud coupling through the global atmospheric electric circuit

We illustrate how coupling could occur between surface air and clouds via the global electric circuit – through Atmospheric Lithosphere–Ionosphere Charge Exchange (ALICE) processes – in an attempt to develop a physical understanding of the possible relationships between earthquakes and clouds

The 2013 hot, dry summer in Western Europe

The European summer of 2013 was marked by hot and dry conditions in Western Europe associated with a northward shifted Atlantic storm track and a positive phase of the SNAO. Model results suggest that, relative to a 1964–93 reference period, changes in SST/SIE explain 63% (±26%) of the area-averaged warming signal over Western Europe, with the remaining 37% (±29%) explained by the direct impact of changes in anthropogenic radiative forcings from GHG and aerosols. The results further suggest that the anomalous atmospheric circulation, and associated low rainfall, were also influenced both by changes in SST/SIE and by the direct impact of changes in radiative forcings; however, the magnitude of the forced signals in these variables is much less, relative to internal variability, than for surface air temperature. Further evidence suggests that changes in North Atlantic SST were likely an important factor in explaining the striking contrast between the European summers of 2013 and that of 2012. A major area for further work is to understand more completely the mechanisms that explain these influences.

Abrupt CO2 experiments as tools for predicting and understanding CMIP5 representative concentration pathway projections

A fast simple climate modelling approach is developed for predicting and helping to understand general circulation model (GCM) simulations. We show that the simple model reproduces the GCM results accurately, for global mean surface air temperature change and global-mean heat uptake projections from 9 GCMs in the fifth coupled model inter-comparison project (CMIP5). This implies that understanding gained from idealised CO2 step experiments is applicable to policy-relevant scenario projections. Our approach is conceptually simple. It works by using the climate response to a CO2 step change taken directly from a GCM experiment. With radiative forcing from non-CO2 constituents obtained by adapting the Forster and Taylor method, we use our method to estimate results for CMIP5 representative concentration pathway (RCP) experiments for cases not run by the GCMs. We estimate differences between pairs of RCPs rather than RCP anomalies relative to the pre-industrial state. This gives better results because it makes greater use of available GCM projections. The GCMs exhibit differences in radiative forcing, which we incorporate in the simple model. We analyse the thus-completed ensemble of RCP projections. The ensemble mean changes between 1986–2005 and 2080–2099 for global temperature (heat uptake) are, for RCP8.5: 3.8 K (2.3 × 1024 J); for RCP6.0: 2.3 K (1.6 × 1024 J); for RCP4.5: 2.0 K (1.6 × 1024 J); for RCP2.6: 1.1 K (1.3 × 1024 J). The relative spread (standard deviation/ensemble mean) for these scenarios is around 0.2 and 0.15 for temperature and heat uptake respectively. We quantify the relative effect of mitigation action, through reduced emissions, via the time-dependent ratios (change in RCPx)/(change in RCP8.5), using changes with respect to pre-industrial conditions. We find that the effects of mitigation on global-mean temperature change and heat uptake are very similar across these different GCMs.

On judging the credibility of climate predictions

Incorporating a prediction into future planning and decision making is advisable only if we have judged the prediction’s credibility. This is notoriously difficult and controversial in the case of predictions of future climate. By reviewing epistemic arguments about climate model performance, we discuss how to make and justify judgments about the credibility of climate predictions. We propose a new bounding argument that justifies basing such judgments on the past performance of possibly dissimilar prediction problems. This encourages a more explicit use of data in making quantitative judgments about the credibility of future climate predictions, and in training users of climate predictions to become better judges of credibility. We illustrate the approach using decadal predictions of annual mean, global mean surface air temperature.

A comparison of two dust uplift schemes within the same general circulation model

Aeolian dust modelling has improved significantly over the last ten years and many institutions now consistently model dust uplift, transport and deposition in general circulation models (GCMs). However, the representation of dust in GCMs is highly variable between modelling communities due to differences in the uplift schemes employed and the representation of the global circulation that subsequently leads to dust deflation. In this study two different uplift schemes are incorporated in the same GCM. This approach enables a clearer comparison of the dust uplift schemes themselves, without the added complexity of several different transport and deposition models. The global annual mean dust aerosol optical depths (at 550 nm) using two different dust uplift schemes were found to be 0.014 and 0.023—both lying within the estimates from the AeroCom project. However, the models also have appreciably different representations of the dust size distribution adjacent to the West African coast and very different deposition at various sites throughout the globe. The different dust uplift schemes were also capable of influencing the modelled circulation, surface air temperature, and precipitation despite the use of prescribed sea surface temperatures. This has important implications for the use of dust models in AMIP-style (Atmospheric Modelling Intercomparison Project) simulations and Earth-system modelling.

The inconstancy of the transient climate response parameter under increasing CO₂

In the Coupled Model Intercomparison Project Phase 5 (CMIP5), the model-mean increase in global mean surface air temperature T under the 1pctCO2 scenario (atmospheric CO2 increasing at 1% yr−1) during the second doubling of CO2 is 40% larger than the transient climate response (TCR), i.e. the increase in T during the first doubling. We identify four possible contributory effects. First, the surface climate system loses heat less readily into the ocean beneath as the latter warms. The model spread in the thermal coupling between the upper and deep ocean largely explains the model spread in ocean heat uptake efficiency. Second, CO2 radiative forcing may rise more rapidly than logarithmically with CO2 concentration. Third, the climate feedback parameter may decline as the CO2 concentration rises. With CMIP5 data, we cannot distinguish the second and third possibilities. Fourth, the climate feedback parameter declines as time passes or T rises; in 1pctCO2, this effect is less important than the others. We find that T projected for the end of the twenty-first century correlates more highly with T at the time of quadrupled CO2 in 1pctCO2 than with the TCR, and we suggest that the TCR may be underestimated from observed climate change.

What does global mean temperature tell us about local climate?

The subject of climate feedbacks focuses attention on global mean surface air temperature (GMST) as the key metric of climate change. But what does knowledge of past and future GMST tell us about the climate of specific regions? In the context of the ongoing UNFCCC process, this is an important question for policy-makers as well as for scientists. The answer depends on many factors, including the mechanisms causing changes, the timescale of the changes, and the variables and regions of interest. This paper provides a review and analysis of the relationship between changes in GMST and changes in local climate, first in observational records and then in a range of climate model simulations, which are used to interpret the observations. The focus is on decadal timescales, which are of particular interest in relation to recent and near-future anthropogenic climate change. It is shown that GMST primarily provides information about forced responses, but that understanding and quantifying internal variability is essential to projecting climate and climate impacts on regional-to-local scales. The relationship between local forced responses and GMST is often linear but may be nonlinear, and can be greatly complicated by competition between different forcing factors. Climate projections are limited not only by uncertainties in the signal of climate change but also by uncertainties in the characteristics of real-world internal variability. Finally, it is shown that the relationship between GMST and local climate provides a simple approach to climate change detection, and a useful guide to attribution studies.

A global empirical system for probabilistic seasonal climate prediction

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961–2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño–Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

Atmospheric impact of Arctic Sea ice loss in a coupled ocean–atmosphere simulation

The atmospheric response to an idealized decline in Arctic sea ice is investigated in a novel fully coupled climate model experiment. In this experiment two ensembles of single-year model integrations are performed starting on 1 April, the approximate start of the ice melt season. By perturbing the initial conditions of sea ice thickness (SIT), declines in both sea ice concentration and SIT, which result in sea ice distributions that are similar to the recent sea ice minima of 2007 and 2012, are induced. In the ice loss regions there are strong (~3 K) local increases in sea surface temperature (SST); additionally, there are remote increases in SST in the central North Pacific and subpolar gyre in the North Atlantic. Over the central Arctic there are increases in surface air temperature (SAT) of ~8 K due to increases in ocean–atmosphere heat fluxes. There are increases in SAT over continental North America that are in good agreement with recent changes as seen by reanalysis data. It is estimated that up to two-thirds of the observed increase in SAT in this region could be related to Arctic sea ice loss. In early summer there is a significant but weak atmospheric circulation response that projects onto the summer North Atlantic Oscillation (NAO). In early summer and early autumn there is an equatorward shift of the eddy-driven jet over the North Atlantic as a result of a reduction in the meridional temperature gradients. In winter there is no projection onto a particular phase of the NAO.

Small global-mean cooling due to volcanic radiative forcing

In both the observational record and atmosphere-ocean general circulation model (AOGCM) simulations of the last ∼∼ 150 years, short-lived negative radiative forcing due to volcanic aerosol, following explosive eruptions, causes sudden global-mean cooling of up to ∼∼ 0.3 K. This is about five times smaller than expected from the transient climate response parameter (TCRP, K of global-mean surface air temperature change per W m−2 of radiative forcing increase) evaluated under atmospheric CO2 concentration increasing at 1 % yr−1. Using the step model (Good et al. in Geophys Res Lett 38:L01703, 2011. doi:10.​1029/​2010GL045208), we confirm the previous finding (Held et al. in J Clim 23:2418–2427, 2010. doi:10.​1175/​2009JCLI3466.​1) that the main reason for the discrepancy is the damping of the response to short-lived forcing by the thermal inertia of the upper ocean. Although the step model includes this effect, it still overestimates the volcanic cooling simulated by AOGCMs by about 60 %. We show that this remaining discrepancy can be explained by the magnitude of the volcanic forcing, which may be smaller in AOGCMs (by 30 % for the HadCM3 AOGCM) than in off-line calculations that do not account for rapid cloud adjustment, and the climate sensitivity parameter, which may be smaller than for increasing CO2 (40 % smaller than for 4 × CO2 in HadCM3).

Decadal predictions with the HiGEM high resolution global coupled climate model: description and basic evaluation

This paper describes the development and basic evaluation of decadal predictions produced using the HiGEM coupled climate model. HiGEM is a higher resolution version of the HadGEM1 Met Office Unified Model. The horizontal resolution in HiGEM has been increased to 1.25◦ × 0.83◦ in longitude and latitude for the atmosphere, and 1/3◦ × 1/3◦ globally for the ocean. The HiGEM decadal predictions are initialised using an anomaly assimilation scheme that relaxes anomalies of ocean temperature and salinity to observed anomalies. 10 year hindcasts are produced for 10 start dates (1960, 1965,..., 2000, 2005). To determine the relative contributions to prediction skill from initial conditions and external forcing, the HiGEM decadal predictions are compared to uninitialised HiGEM transient experiments. The HiGEM decadal predictions have substantial skill for predictions of annual mean surface air temperature and 100 m upper ocean temperature. For lead times up to 10 years, anomaly correlations (ACC) over large areas of the North Atlantic Ocean, the Western Pacific Ocean and the Indian Ocean exceed values of 0.6. Initialisation of the HiGEM decadal predictions significantly increases skill over regions of the Atlantic Ocean,the Maritime Continent and regions of the subtropical North and South Pacific Ocean. In particular, HiGEM produces skillful predictions of the North Atlantic subpolar gyre for up to 4 years lead time (with ACC > 0.7), which are significantly larger than the uninitialised HiGEM transient experiments.

How do green roofs mitigate urban thermal stress under heat waves?

As the climate warms, heat waves (HW) are projected to be more intense and to last longer, with serious implications for public health. Urban residents face higher health risks because urban heat islands (UHIs) exacerbate HW conditions. One strategy to mitigate negative impacts of urban thermal stress is the installation of green roofs (GRs) given their evaporative cooling effect. However, the effectiveness of GRs and the mechanisms by which they have an effect at the scale of entire cities are still largely unknown. The Greater Beijing Region (GBR) is modeled for a HW scenario with the Weather Research and Forecasting (WRF) model coupled with a state-of-the-art urban canopy model (PUCM) to examine the effectiveness of GRs. The results suggest GR would decrease near-surface air temperature (ΔT2max = 2.5 K) and wind speed (ΔUV10max = 1.0 m s-1) but increase atmospheric humidity (ΔQ2max = 1.3 g kg-1). GRs are simulated to lessen the overall thermal stress as indicated by apparent temperature (ΔAT2max = 1.7 °C). The modifications by GRs scale almost linearly with the fraction of the surface they cover. Investigation of the surface-atmosphere interactions indicate that GRs with plentiful soil moisture dissipate more of the surface energy as latent heat flux and subsequently inhibit the development of the daytime planetary boundary layer (PBL). This causes the atmospheric heating through entrainment at the PBL top to be decreased. Additionally, urban GRs modify regional circulation regimes leading to decreased advective heating under HW.