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Matthew Collins

Abstract

This paper describes El Niño–Southern Oscillation (ENSO) interannual variability simulated in the second Hadley Centre coupled model under “control” and “greenhouse warming” scenarios. The model produces a very reasonable simulation of ENSO in the control experiment—reproducing the amplitude, spectral characteristics, and phase locking to the annual cycle that are observed in nature. The mechanism for the model ENSO is shown to be a mixed SST–ocean dynamics mode that can be interpreted in terms of the “ocean recharge paradigm” of Jin.

In experiments with increased levels of greenhouse gases, no statistically significant changes in ENSO are seen until these levels approach four times preindustrial values. In these experiments, the model ENSO has an approximately 20% larger amplitude, a frequency that is approximately double that of the current ENSO (implying more frequent El Niños and La Niñas), and phase locks to the annual cycle at a different time of year. It is shown that the increase in the vertical gradient of temperature in the thermocline region, associated with the model’s response to increased greenhouse gases, is responsible for the increase in the amplitude of ENSO, while the increase in meridional temperature gradients on either side of the equator, again associated with the models response to increasing greenhouse gases, is responsible for the increased frequency of ENSO events.

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Matthew Collins and Myles R. Allen

Abstract

The relative importance of initial conditions and boundary conditions in interannual to decadal climate predictability is addressed. A simple framework is developed in which (i) ensembles of climate model simulations with changing external forcing can be measured against climatology to get an estimate of the timescale on which changing boundary conditions can provide predictive skill, and (ii) the rate of spread of ensembles of simulations with small perturbations to the initial conditions can be measured against climatology to assess the timescale at which the information in the initial conditions is degraded by chaotic error growth. A preliminary test of the method on a limited number of climate model simulations is presented.

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Samantha Ferrett, Matthew Collins, and Hong-Li Ren

Abstract

This study examines the extent of the Pacific double–intertropical convergence zone (ITCZ) bias in an ensemble of CMIP5 coupled general circulation models and the relationship between this common bias and equatorial Pacific evaporative heat flux feedbacks involved in El Niño–Southern Oscillation (ENSO). A feedback decomposition method, based on the latent heat flux bulk formula, is implemented to enable identification of underlying causes of feedback bias and diversity from dynamical and thermodynamical processes. The magnitude of mean precipitation south of the equator in the east Pacific (an indicator of the extent of the double-ITCZ bias in a model) is linked to the mean meridional surface wind speed and direction in the region and is consequently linked to diversity in the strength of the wind speed response during the ENSO cycle. The ENSO latent heat flux damping is weak in almost all models and shows a relatively large range in strength in the CMIP5 ensemble. While both humidity gradient and wind speed feedbacks are important drivers of the damping, the wind speed feedback is an underlying cause of the overall damping bias for many models and is ultimately more dominant in driving interensemble variation. Feedback biases can also persist in atmosphere-only (AMIP) runs, suggesting that the atmosphere model plays an important role in latent heat flux damping and double-ITCZ bias and variation. Improvements to coupled model simulation of both mean precipitation and ENSO may be accelerated by focusing on the atmosphere component.

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Samantha Ferrett, Matthew Collins, and Hong-Li Ren

Abstract

The rate of damping of tropical Pacific sea surface temperature anomalies (SSTAs) associated with El Niño events by surface shortwave heat fluxes has significant biases in current coupled climate models [phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. Of 33 CMIP5 models, 16 have shortwave feedbacks that are weakly negative in comparison to observations, or even positive, resulting in a tendency of amplification of SSTAs. Two biases in the cloud response to El Niño SSTAs are identified and linked to significant mean state biases in CMIP5 models. First, cool mean SST and reduced precipitation are linked to comparatively less cloud formation in the eastern equatorial Pacific during El Niño events, driven by a weakened atmospheric ascent response. Second, a spurious reduction of cloud driven by anomalous surface relative humidity during El Niño events is present in models with more stable eastern Pacific mean atmospheric conditions and more low cloud in the mean state. Both cloud response biases contribute to a weak negative shortwave feedback or a positive shortwave feedback that amplifies El Niño SSTAs. Differences between shortwave feedback in the coupled models and the corresponding atmosphere-only models (AMIP) are also linked to mean state differences, consistent with the biases found between different coupled models. Shortwave feedback bias can still persist in AMIP, as a result of persisting weak shortwave responses to anomalous cloud and weak cloud responses to atmospheric ascent. This indicates the importance of bias in the atmosphere component to coupled model feedback and mean state biases.

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Alexander Todd, Matthew Collins, F. Hugo Lambert, and Robin Chadwick

Abstract

Large uncertainty remains in future projections of tropical precipitation change under global warming. A simplified method for diagnosing tropical precipitation change is tested here on present-day El Niño–Southern Oscillation (ENSO) precipitation shifts. This method, based on the weak temperature gradient approximation, assumes precipitation is associated with local surface relative humidity (RH) and surface air temperature (SAT), relative to the tropical mean. Observed and simulated changes in RH and SAT are subsequently used to diagnose changes in precipitation. Present-day ENSO precipitation shifts are successfully diagnosed using observations (correlation r = 0.69) and an ensemble of atmosphere-only (0.51 ≤ r ≤ 0.8) and coupled (0.5 ≤ r ≤ 0.87) climate model simulations. RH (r = 0.56) is much more influential than SAT (r = 0.27) in determining ENSO precipitation shifts for observations and climate model simulations over both land and ocean. Using intermodel differences, a significant relationship is demonstrated between method performance over ocean for present-day ENSO and projected global warming (r = 0.68). As a caveat, the authors note that mechanisms leading to ENSO-related precipitation changes are not a direct analog for global warming–related precipitation changes. The diagnosis method presented here demonstrates plausible mechanisms that relate changes in precipitation, RH, and SAT under different climate perturbations. Therefore, uncertainty in future tropical precipitation changes may be linked with uncertainty in future RH and SAT changes.

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Timothy J. Mosedale, David B. Stephenson, and Matthew Collins

Abstract

A simple linear stochastic climate model of extratropical wintertime ocean–atmosphere coupling is used to diagnose the daily interactions between the ocean and the atmosphere in a fully coupled general circulation model. Monte Carlo simulations with the simple model show that the influence of the ocean on the atmosphere can be difficult to estimate, being biased low even with multiple decades of daily data. Despite this, fitting the simple model to the surface air temperature and sea surface temperature data from the complex general circulation model reveals an ocean-to-atmosphere influence in the northeastern Atlantic. Furthermore, the simple model is used to demonstrate that the ocean in this region greatly enhances the autocorrelation in overlying lower-tropospheric temperatures at lags from a few days to many months.

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Jonathan D. Beverley, Matthew Collins, F. Hugo Lambert, and Robin Chadwick

Abstract

El Niño–Southern Oscillation (ENSO) is the leading mode of interannual climate variability, and it exerts a strong influence on many remote regions of the world, for example in northern North America. Here, we examine future changes to the positive-phase ENSO teleconnection to the North Pacific/North America sector and investigate the mechanisms involved. We find that the positive temperature anomalies over Alaska and northern North America that are associated with an El Niño event in the present day are much weaker, or of the opposite sign, in the CMIP6 abrupt 4×CO2 experiments for almost all models (22 out of 26, of which 15 have statistically significant differences). This is largely related to changes to the anomalous circulation over the North Pacific, rather than differences in the equator-to-pole temperature gradient. Using a barotropic model, run with different background circulation basic states and Rossby wave source forcing patterns from the individual CMIP6 models, we find that changes to the forcing from the equatorial central Pacific precipitation anomalies are more important than changes in the global basic state background circulation. By further decomposing this forcing change into changes associated with the longitude and magnitude of ENSO precipitation anomalies, we demonstrate that the projected overall eastward shift of ENSO precipitation is the main driver of the temperature teleconnection change, rather than the increase in magnitude of El Niño precipitation anomalies, which is nevertheless seen in the majority of models.

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Matthew Collins, Timothy J. Osborn, Simon F. B. Tett, Keith R. Briffa, and Fritz H. Schweingruber

Abstract

Validation of the decadal to centennial timescale variability of coupled climate models is limited by the scarcity of long observational records. Proxy indicators of climate, such as tree rings, ice cores, etc., can be utilized for this purpose. This study presents a quantitative comparison of the variability of the third version of the Hadley Centre ocean–atmosphere coupled model with a network of temperature-sensitive tree-ring densities covering the northern high latitudes. The tree-ring density records are up to 600 years long, and temperature reconstructions based on two different methods of removing the bias due to changing tree age are used. The first is a standard method that may remove low-frequency variability on timescales of the order of the tree life span (i.e., multidecadal to century timescales). The second (age-band decomposition) maintains low-frequency variability by only comparing similar age tree rings at each site, thus avoiding the need to remove the age effect (but at the cost of greater uncertainty in the earlier years when fewer tree cores are available). The variability of the model control simulation, which represents only the internal variability of the climate system, agrees reasonably well with the tree-ring reconstructions using the standard method at the regional level, although the model may underestimate the variance of mean Northern Hemisphere land temperature by as much as a factor of 1.8 on all timescales if one takes account of the uncertainty in the tree-ring reconstructions. Agreement with the age-band decomposition tree-ring reconstructions is less good with the model underestimating the hemispheric variance by as much as a factor of 2.1 on all timescales and by as much as a factor of 3.0 on decadal to centennial timescales. Underestimation of the natural variability of climate by the model would be serious as it may lead to false detections of climate change or erroneously low uncertainty estimates in future climate predictions. However, it is shown that some of this underestimation may be due to the lack of natural climate forcing in the model control simulation due, for example, to solar variability and volcanic eruptions. The study suggests that further quantification of the uncertainties in the proxy data, and inclusion of natural climate forcings in the model simulations, are important steps in making comparisons of climate models with the proxy record over the last 1000 years.

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Harry Mutton, Robin Chadwick, Matthew Collins, F. Hugo Lambert, Ruth Geen, Alexander Todd, and Christopher M. Taylor

Abstract

Projections of future West African monsoon (WAM) precipitation change in response to increasing greenhouse gases are uncertain, and an improved understanding of the drivers of WAM precipitation change is needed to help aid model development and better inform adaptation policies in the region. This paper addresses one of those drivers, the direct radiative effect of increased CO2 (i.e., the impact of increased CO2 in the absence of SST warming and changes in plant physiology). An atmosphere-only model is used to examine both the equilibrium response and the evolution of the change over the days following the instantaneous CO2 increase. In response to the direct radiative effect, WAM precipitation increases due to a weakening of the shallow meridional circulation over North Africa, advecting less dry air into the convective column associated with the monsoon. Changes in the shallow circulation are associated with atmospheric and surface warming patterns over North Africa. A large-scale atmospheric warming pattern, whereby North Africa warms more than the monsoon region, leads to a northward shift in the Saharan heat low. In response to increased precipitation in the Sahel, local soil moisture feedbacks play a key role in determining the low-level circulation change and the location of the intertropical discontinuity. The large-scale warming patterns over North Africa result from differing levels of constraint applied by convective quasi-equilibrium. While this constraint acts strongly in the equatorial WAM region, preventing the region from warming in response to the direct radiative effect, North Africa is not strongly constrained and is therefore able to warm.

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Timothy J. Mosedale, David B. Stephenson, Matthew Collins, and Terence C. Mills

Abstract

This study uses a Granger causality time series modeling approach to quantitatively diagnose the feedback of daily sea surface temperatures (SSTs) on daily values of the North Atlantic Oscillation (NAO) as simulated by a realistic coupled general circulation model (GCM). Bivariate vector autoregressive time series models are carefully fitted to daily wintertime SST and NAO time series produced by a 50-yr simulation of the Third Hadley Centre Coupled Ocean–Atmosphere GCM (HadCM3). The approach demonstrates that there is a small yet statistically significant feedback of SSTs on the NAO. The SST tripole index is found to provide additional predictive information for the NAO than that available by using only past values of NAO—the SST tripole is Granger causal for the NAO. Careful examination of local SSTs reveals that much of this effect is due to the effect of SSTs in the region of the Gulf Steam, especially south of Cape Hatteras. The effect of SSTs on NAO is responsible for the slower-than-exponential decay in lag-autocorrelations of NAO notable at lags longer than 10 days. The persistence induced in daily NAO by SSTs causes long-term means of NAO to have more variance than expected from averaging NAO noise if there is no feedback of the ocean on the atmosphere. There are greater long-term trends in NAO than can be expected from aggregating just short-term atmospheric noise, and NAO is potentially predictable provided that future SSTs are known. For example, there is about 10%–30% more variance in seasonal wintertime means of NAO and almost 70% more variance in annual means of NAO due to SST effects than one would expect if NAO were a purely atmospheric process.

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