El Nino-mean state-seasonal cycle interactions in a multi-model ensemble

The modelled El Nino-mean state-seasonal cycle interactions in 23 coupled ocean-atmosphere GCMs, including the recent IPCC AR4 models, are assessed and compared to observations and theory. The models show a clear improvement over previous generations in simulating the tropical Pacific climatology. Systematic biases still include too strong mean and seasonal cycle of trade winds. El Nino amplitude is shown to be an inverse function of the mean trade winds in agreement with the observed shift of 1976 and with theoretical studies. El Nino amplitude is further shown to be an inverse function of the relative strength of the seasonal cycle. When most of the energy is within the seasonal cycle, little is left for inter-annual signals and vice versa. An interannual coupling strength (ICS) is defined and its relation with the modelled El Nino frequency is compared to that predicted by theoretical models. An assessment of the modelled El Nino in term of SST mode (S-mode) or thermocline mode (T-mode) shows that most models are locked into a S-mode and that only a few models exhibit a hybrid mode, like in observations. It is concluded that several basic El Nino-mean state-seasonal cycle relationships proposed by either theory or analysis of observations seem to be reproduced by CGCMs. This is especially true for the amplitude of El Nino and is less clear for its frequency. Most of these relationships, first established for the pre-industrial control simulations, hold for the double and quadruple CO2 stabilized scenarios. The models that exhibit the largest El Nino amplitude change in these greenhouse gas (GHG) increase scenarios are those that exhibit a mode change towards a T-mode (either from S-mode to hybrid or hybrid to T-mode). This follows the observed 1976 climate shift in the tropical Pacific, and supports the-still debated-finding of studies that associated this shift to increased GHGs. In many respects, these models are also among those that best simulate the tropical Pacific climatology (ECHAM5/MPI-OM, GFDL-CM2.0, GFDL-CM2.1, MRI-CGM2.3.2, UKMO-HadCM3). Results from this large subset of models suggest the likelihood of increased El Nino amplitude in a warmer climate, though there is considerable spread of El Nino behaviour among the models and the changes in the subsurface thermocline properties that may be important for El Nino change could not be assessed. There are no clear indications of an El Nino frequency change with increased GHG.

A shift to randomness of brain oscillations in people with autism

BACKGROUND: Resting-state functional magnetic resonance imaging (fMRI) enables investigation of the intrinsic functional organization of the brain. Fractal parameters such as the Hurst exponent, H, describe the complexity of endogenous low-frequency fMRI time series on a continuum from random (H = .5) to ordered (H = 1). Shifts in fractal scaling of physiological time series have been associated with neurological and cardiac conditions. METHODS: Resting-state fMRI time series were recorded in 30 male adults with an autism spectrum condition (ASC) and 33 age- and IQ-matched male volunteers. The Hurst exponent was estimated in the wavelet domain and between-group differences were investigated at global and voxel level and in regions known to be involved in autism. RESULTS: Complex fractal scaling of fMRI time series was found in both groups but globally there was a significant shift to randomness in the ASC (mean H = .758, SD = .045) compared with neurotypical volunteers (mean H = .788, SD = .047). Between-group differences in H, which was always reduced in the ASC group, were seen in most regions previously reported to be involved in autism, including cortical midline structures, medial temporal structures, lateral temporal and parietal structures, insula, amygdala, basal ganglia, thalamus, and inferior frontal gyrus. Severity of autistic symptoms was negatively correlated with H in retrosplenial and right anterior insular cortex. CONCLUSIONS: Autism is associated with a small but significant shift to randomness of endogenous brain oscillations. Complexity measures may provide physiological indicators for autism as they have done for other medical conditions.

Geographical range margins of many taxonomic groups continue to shift polewards

Many species are extending their leading-edge (cool) range margins polewards in response to recent climate change. In the present study, we investigated range margin changes at the northern (cool) range margins of 1573 southerly-distributed species from 21 animal groups in Great Britain over the past four decades of climate change, updating previous work. Depending on data availability, range margin changes were examined over two time intervals during the past four decades. For four groups (birds, butterflies, macromoths, and dragonflies and damselflies), there were sufficient data available to examine range margin changes over both time intervals. We found that most taxa shifted their northern range margins polewards and this finding was not greatly influenced by changes in recorder effort. The mean northwards range margin change in the first time interval was 23 km per decade (N = 13 taxonomic groups) and, in the second interval, was 18 km per decade (N = 16 taxonomic groups) during periods when the British climate warmed by 0.21 and 0.28 °C per decade, respectively. For the four taxa examined over both intervals, there was evidence for higher rate of range margin change in the more recent time interval in the two Lepidoptera groups. Our analyses confirm a continued range margin shift polewards in a wide range of taxonomic groups.

The response of tropospheric circulation to perturbations in lower-stratospheric temperature

A multiple regression analysis of the NCEP-NCAR reanalysis dataset shows a response to increased solar activity of a weakening and poleward shift of the subtropical jets. This signal is separable from other influences, such as those of El Nino-Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO), and is very similar to that seen in previous studies using global circulation models (GCMs) of the effects of an increase in solar spectral irradiance. The response to increased stratospheric (volcanic) aerosol is found in the data to be a weakening and equatorward shift of the jets. The GCM studies of the solar influence also showed an impact on tropospheric mean meridional circulation with a weakening and expansion of the tropical Hadley cells and a poleward shift of the Ferrel cells. To understand the mechanisms whereby the changes in solar irradiance affect tropospheric winds and circulation, experiments have been carried out with a simplified global circulation model. The results show that generic heating of the lower stratosphere tends to weaken the subtropical jets and the tropospheric mean meridional circulations. The positions of the jets, and the extent of the Hadley cells, respond to the distribution of the stratospheric heating, with low-latitude heating forcing them to move poleward, and high-latitude or latitudinally uniform heating forcing them equatorward. The patterns of response are similar to those that are found to be a result of the solar or volcanic influences, respectively, in the data analysis. This demonstrates that perturbations to the heat balance of the lower stratosphere, such as those brought about by solar or volcanic activity, can produce changes in the mean tropospheric circulation, even without any direct forcing below the tropopause.

The mean evolution and variability of the Asian summer monsoon: Comparison of ECMWF and NCEP-NCAR reanalyses

The behavior of the Asian summer monsoon is documented and compared using the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA) and the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) Reanalysis. In terms of seasonal mean climatologies the results suggest that, in several respects, the ERA is superior to the NCEP-NCAR Reanalysis. The overall better simulation of the precipitation and hence the diabatic heating field over the monsoon domain in ERA means that the analyzed circulation is probably nearer reality. In terms of interannual variability, inconsistencies in the definition of weak and strong monsoon years based on typical monsoon indices such as All-India Rainfall (AIR) anomalies and the large-scale wind shear based dynamical monsoon index (DMI) still exist. Two dominant modes of interannual variability have been identified that together explain nearly 50% of the variance. Individually, they have many features in common with the composite flow patterns associated with weak and strong monsoons, when defined in terms of regional AIR anomalies and the large-scale DMI. The reanalyses also show a common dominant mode of intraseasonal variability that describes the latitudinal displacement of the tropical convergence zone from its oceanic-to-continental regime and essentially captures the low-frequency active/break cycles of the monsoon. The relationship between interannual and intraseasonal variability has been investigated by considering the probability density function (PDF) of the principal component of the dominant intraseasonal mode. Based on the DMI, there is an indication that in years with a weaker monsoon circulation, the PDF is skewed toward negative values (i,e., break conditions). Similarly, the PDFs for El Nino and La Nina years suggest that El Nino predisposes the system to more break spells, although the sample size may limit the statistical significance of the results.

Enhancement of ENSO variability by a weakened Atlantic thermohaline circulation in a coupled GCM

A coupled ocean–atmosphere general circulation model is used to investigate the modulation of El Niño–Southern Oscillation (ENSO) variability due to a weakened Atlantic thermohaline circulation (THC). The THC weakening is induced by freshwater perturbations in the North Atlantic, and leads to a well-known sea surface temperature dipole and a southward shift of the intertropical convergence zone (ITCZ) in the tropical Atlantic. Through atmospheric teleconnections and local coupled air–sea feedbacks, a meridionally asymmetric mean state change is generated in the eastern equatorial Pacific, corresponding to a weakened annual cycle, and westerly anomalies develop over the central Pacific. The westerly anomalies are associated with anomalous warming of SST, causing an eastward extension of the west Pacific warm pool particularly in August–February, and enhanced precipitation. These and other changes in the mean state lead in turn to an eastward shift of the zonal wind anomalies associated with El Niño events, and a significant increase in ENSO variability. In response to a 1-Sv (1 Sv ≡ 106 m3 s−1) freshwater input in the North Atlantic, the THC slows down rapidly and it weakens by 86% over years 50–100. The Niño-3 index standard deviation increases by 36% during the first 100-yr simulation relative to the control simulation. Further analysis indicates that the weakened THC not only leads to a stronger ENSO variability, but also leads to a stronger asymmetry between El Niño and La Niña events. This study suggests a role for an atmospheric bridge that rapidly conveys the influence of the Atlantic Ocean to the tropical Pacific and indicates that fluctuations of the THC can mediate not only mean climate globally but also modulate interannual variability. The results may contribute to understanding both the multidecadal variability of ENSO activity during the twentieth century and longer time-scale variability of ENSO, as suggested by some paleoclimate records.

The influence of a weakening of the Atlantic meridional overturning circulation on ENSO

The influences of a substantial weakening of the Atlantic meridional overturning circulation (AMOC) on the tropical Pacific climate mean state, the annual cycle, and ENSO variability are studied using five different coupled general circulation models (CGCMs). In the CGCMs, a substantial weakening of the AMOC is induced by adding freshwater flux forcing in the northern North Atlantic. In response, the well-known surface temperature dipole in the low-latitude Atlantic is established, which reorganizes the large-scale tropical atmospheric circulation by increasing the northeasterly trade winds. This leads to a southward shift of the intertropical convergence zone (ITCZ) in the tropical Atlantic and also the eastern tropical Pacific. Because of evaporative fluxes, mixing, and changes in Ekman divergence, a meridional temperature anomaly is generated in the northeastern tropical Pacific, which leads to the development of a meridionally symmetric thermal background state. In four out of five CGCMs this leads to a substantial weakening of the annual cycle in the eastern equatorial Pacific and a subsequent intensification of ENSO variability due to nonlinear interactions. In one of the CGCM simulations, an ENSO intensification occurs as a result of a zonal mean thermocline shoaling. Analysis suggests that the atmospheric circulation changes forced by tropical Atlantic SSTs can easily influence the large-scale atmospheric circulation and hence tropical eastern Pacific climate. Furthermore, it is concluded that the existence of the present-day tropical Pacific cold tongue complex and the annual cycle in the eastern equatorial Pacific are partly controlled by the strength of the AMOC. The results may have important implications for the interpretation of global multidecadal variability and paleo-proxy data.

The effect of doubled CO2 and model basic state biases on the monsoon-ENSO system. I: Mean response and interannual variability

The impact of doubled CO2 concentration on the Asian summer monsoon is studied using a coupled ocean-atmosphere model. Both the mean seasonal precipitation and interannual monsoon variability are found to increase in the future climate scenario presented. Systematic biases in current climate simulations of the coupled system prevent accurate representation of the monsoon-ENSO teleconnection, of prime importance for seasonal prediction and for determining monsoon interannual variability. By applying seasonally varying heat flux adjustments to the tropical Pacific and Indian Ocean surface in the future climate simulation, some assessment can be made of the impact of systematic model biases on future climate predictions. In simulations where the flux adjustments are implemented, the response to climate change is magnified, with the suggestion that systematic biases may be masking the true impact of increased greenhouse gas forcing. The teleconnection between ENSO and the Asian summer monsoon remains robust in the future climate, although the Indo-Pacific takes on more of a biennial character for long periods of the flux-adjusted simulation. Assessing the teleconnection across interdecadal timescales shows wide variations in its amplitude, despite the absence of external forcing. This suggests that recent changes in the observed record cannot be distinguished from internal variations and as such are not necessarily related to climate change.

Vertical structure of anthropogenic zonal-mean atmospheric circulation change

The atmospheric circulation changes predicted by climate models are often described using sea level pressure, which generally shows a strengthening of the mid-latitude westerlies. Recent observed variability is dominated by the Northern Annular Mode (NAM) which is equivalent barotropic, so that wind variations of the same sign are seen at all levels. However, in model predictions of the response to anthropogenic forcing, there is a well-known enhanced warming at low levels over the northern polar cap in winter. This means that there is a strong baroclinic component to the response. The projection of the response onto a NAM-like zonal index varies with height. While at the surface most models project positively onto the zonal index, throughout most of the depth of the troposphere many of the models give negative projections. The response to anthropogenic forcing therefore has a distinctive baroclinic signature which is very different to the NAM

Calculating the ocean's mean dynamic topography from a mean sea surface and a geoid

In principle the global mean geostrophic surface circulation of the ocean can be diagnosed by subtracting a geoid from a mean sea surface (MSS). However, because the resulting mean dynamic topography (MDT) is approximately two orders of magnitude smaller than either of the constituent surfaces, and because the geoid is most naturally expressed as a spectral model while the MSS is a gridded product, in practice complications arise. Two algorithms for combining MSS and satellite-derived geoid data to determine the ocean’s mean dynamic topography (MDT) are considered in this paper: a pointwise approach, whereby the gridded geoid height field is subtracted from the gridded MSS; and a spectral approach, whereby the spherical harmonic coefficients of the geoid are subtracted from an equivalent set of coefficients representing the MSS, from which the gridded MDT is then obtained. The essential difference is that with the latter approach the MSS is truncated, a form of filtering, just as with the geoid. This ensures that errors of omission resulting from the truncation of the geoid, which are small in comparison to the geoid but large in comparison to the MDT, are matched, and therefore negated, by similar errors of omission in the MSS. The MDTs produced by both methods require additional filtering. However, the spectral MDT requires less filtering to remove noise, and therefore it retains more oceanographic information than its pointwise equivalent. The spectral method also results in a more realistic MDT at coastlines. 1. Introduction An important challenge in oceanography is the accurate determination of the ocean’s time-mean dynamic topography (MDT). If this can be achieved with sufficient accuracy for combination with the timedependent component of the dynamic topography, obtainable from altimetric data, then the resulting sum (i.e., the absolute dynamic topography) will give an accurate picture of surface geostrophic currents and ocean transports.

Climate change and heat-related mortality in six cities Part 2: climate model evaluation and projected impacts from changes in the mean and variability of temperature with climate change

Previous assessments of the impacts of climate change on heat-related mortality use the "delta method" to create temperature projection time series that are applied to temperature-mortality models to estimate future mortality impacts. The delta method means that climate model bias in the modelled present does not influence the temperature projection time series and impacts. However, the delta method assumes that climate change will result only in a change in the mean temperature but there is evidence that there will also be changes in the variability of temperature with climate change. The aim of this paper is to demonstrate the importance of considering changes in temperature variability with climate change in impacts assessments of future heat-related mortality. We investigate future heatrelated mortality impacts in six cities (Boston, Budapest, Dallas, Lisbon, London and Sydney) by applying temperature projections from the UK Meteorological Office HadCM3 climate model to the temperature-mortality models constructed and validated in Part 1. We investigate the impacts for four cases based on various combinations of mean and variability changes in temperature with climate change. The results demonstrate that higher mortality is attributed to increases in the mean and variability of temperature with climate change rather than with the change in mean temperature alone. This has implications for interpreting existing impacts estimates that have used the delta method. We present a novel method for the creation of temperature projection time series that includes changes in the mean and variability of temperature with climate change and is not influenced by climate model bias in the modelled present. The method should be useful for future impacts assessments. Few studies consider the implications that the limitations of the climate model may have on the heatrelated mortality impacts. Here, we demonstrate the importance of considering this by conducting an evaluation of the daily and extreme temperatures from HadCM3, which demonstrates that the estimates of future heat-related mortality for Dallas and Lisbon may be overestimated due to positive climate model bias. Likewise, estimates for Boston and London may be underestimated due to negative climate model bias. Finally, we briefly consider uncertainties in the impacts associated with greenhouse gas emissions and acclimatisation. The uncertainties in the mortality impacts due to different emissions scenarios of greenhouse gases in the future varied considerably by location. Allowing for acclimatisation to an extra 2°C in mean temperatures reduced future heat-related mortality by approximately half that of no acclimatisation in each city.