The eastward shift of the Walker Circulation in response to global warming and its relationship to ENSO variability

This study investigates the global warming response of the Walker Circulation and the other zonal circulation cells (represented by the zonal stream function), in CMIP3 and CMIP5 climate models. The changes in the mean state are presented as well as the changes in the modes of variability. The mean zonal circulation weakens in the multi model ensembles nearly everywhere along the equator under both the RCP4.5 and SRES A1B scenarios. Over the Pacific the Walker Circulation also shows a significant eastward shift. These changes in the mean circulation are very similar to the leading mode of interannual variability in the tropical zonal circulation cells, which is dominated by El Niño Southern Oscillation variability. During an El Niño event the circulation weakens and the rising branch over the Maritime Continent shifts to the east in comparison to neutral conditions (vice versa for a La Niña event). Two-thirds of the global warming forced trend of the Walker Circulation can be explained by a long-term trend in this interannual variability pattern, i.e. a shift towards more El Niño-like conditions in the multi-model mean under global warming. Further, interannual variability in the zonal circulation exhibits an asymmetry between El Niño and La Niña events. El Niño anomalies are located more to the east compared with La Niña anomalies. Consistent with this asymmetry we find a shift to the east of the dominant mode of variability of zonal stream function under global warming. All these results vary among the individual models, but the multi model ensembles of CMIP3 and CMIP5 show in nearly all aspects very similar results, which underline the robustness of these results. The observed data (ERA Interim reanalysis) from 1979 to 2012 shows a westward shift and strengthening of the Walker Circulation. This is opposite to what the results in the CMIP models reveal. However, 75 % of the trend of the Walker Circulation can again be explained by a shift of the dominant mode of variability, but here towards more La Niña-like conditions. Thus in both climate change projections and observations the long-term trends of the Walker Circulation seem to follow to a large part the pre-existing dominant mode of internal variability.     

Uncertainty of ENSO-amplitude projections in CMIP5 and CMIP6 models

There is a long-standing debate on how the El Niño/Southern Oscillation (ENSO) amplitude may change during the twenty-first century in response to global warming. Here we identify the sources of uncertainty in the ENSO amplitude projections in models participating in the Coupled Model Intercomparison Phase 5 (CMIP5) and Phase 6 (CMIP6), and quantify scenario uncertainty, model uncertainty and uncertainty due to internal variability. The model projections exhibit a large spread, ranging from increasing standard deviation of up to 0.6 °C to diminishing standard deviation of up to − 0.4 °C by the end of the twenty-first century. The ensemble-mean ENSO amplitude change is close to zero. Internal variability is the main contributor to the uncertainty during the first three decades; model uncertainty dominates thereafter, while scenario uncertainty is relatively small throughout the twenty-first century. The total uncertainty increases from CMIP5 to CMIP6: while model uncertainty is reduced, scenario uncertainty is considerably increased. The models with “realistic” ENSO dynamics have been analyzed separately and categorized into models with too small, moderate and too large ENSO amplitude in comparison to instrumental observations. The smallest uncertainties are observed in the sub-ensemble exhibiting realistic ENSO dynamics and moderate ENSO amplitude. However, the global warming signal in ENSO-amplitude change is undetectable in all sub-ensembles. The zonal wind-SST feedback is identified as an important factor determining ENSO amplitude change: global warming signal in ENSO amplitude and zonal wind-SST feedback strength are highly correlated across the CMIP5 and CMIP6 models.

     

Analysis of the Slab Ocean El Nino atmospheric feedbacks in observed and simulated ENSO dynamics

In a recent study it was illustrated that the El Nino Southern Oscillation (ENSO) mode can exist in the absence of any ocean dynamics. This oscillating mode exists just due to the interaction between atmospheric heat fluxes and ocean heat capacity. The primary purpose of this study is to further explore these atmospheric Slab Ocean ENSO dynamics and therefore the role of positive atmospheric feedbacks in model simulations and observations. The positive solar radiation feedback to sea surface temperature (SST), due to reduced cloud cover for anomalous warm SSTs, is the main positive feedback in the Slab Ocean El Nino dynamics. The strength of this positive cloud feedback is strongly related to the strength of the equatorial cold tongue. The combination of positive latent and sensible heat fluxes to the west and negative ones to the east of positive anomalies leads to the westward propagation of the SST anomalies, which allows for oscillating behavior with a preferred period of 6–7 years. Several indications are found that parts of these dynamics are indeed observed and simulated in other atmospheric or coupled general circulation models (AGCMs or CGCMs). The CMIP3 AGCM-slab ensemble of 13 different AGCM simulations shows unstable ocean–atmosphere interactions along the equatorial Pacific related to stronger cold tongues. In observations and in the CMIP3 and CMIP5 CGCM model ensemble the strength and sign of the cloud feedback is a function of the strength of the cold tongue. In summary, this indicates that the Slab Ocean El Nino dynamics are indeed a characteristic of the equatorial Pacific climate that is only dominant or significantly contributing to the ENSO dynamics if the SST cold tongue is sufficiently strong. In the observations this is only the case during strong La Nina conditions. The presence of the Slab Ocean ENSO atmospheric feedbacks in observations and CGCM model simulations implies that the family of physical ENSO modes does have another member, which is entirely driven by atmospheric processes and does not need to have the same spatial pattern nor the same time scales as the main ENSO dynamics.     

Weakened SST variability in the tropical Atlantic Ocean since 2000

A prominent weakening in equatorial Atlantic sea surface temperature (SST) variability, occurring around the year 2000, is investigated by means of observations, reanalysis products and the linear recharge oscillator (ReOsc) model. Compared to the time period 1982–1999, during 2000–2017 the May–June–July SST variability in the eastern equatorial Atlantic has decreased by more than 30%. Coupled air–sea feedbacks, namely the positive Bjerknes feedback and the negative net heat flux damping are important drivers for the equatorial Atlantic interannual SST variability. We find that the Bjerknes feedback weakened after 2000 while the net heat flux damping increased. The weakening of the Bjerknes feedback does not appear to be fully explainable by changes in the mean state of the tropical Atlantic. The increased net heat flux damping is related to an enhanced response of the latent heat flux to the SST anomalies (SSTa). Strengthened trade winds as well as warmer SSTs are suggested to increase the air–sea specific humidity difference and hence, enhancing the latent heat flux response to SSTa. A combined effect of those two processes is proposed to be responsible for the weakened SST variability in the eastern equatorial Atlantic. The ReOsc model supports the link between reduced SST variability, weaker Bjerknes feedback and stronger net heat flux damping.     

Analysis of the non-linearity in the pattern and time evolution of El Niño southern oscillation

In this study the observed non-linearity in the spatial pattern and time evolution of El Niño Southern Oscillation (ENSO) events is analyzed. It is shown that ENSO skewness is not only a characteristic of the amplitude of events (El Niños being stronger than La Niñas) but also of the spatial pattern and time evolution. It is demonstrated that these non-linearities can be related to the non-linear response of the zonal winds to sea surface temperature (SST) anomalies. It is shown in observations as well as in coupled model simulations that significant differences in the spatial pattern between positive (El Niño) versus negative (La Niña) and strong versus weak events exist, which is mostly describing the difference between central and east Pacific events. Central Pacific events tend to be weak El Niño or strong La Niña events. In turn east Pacific events tend to be strong El Niño or weak La Niña events. A rotation of the two leading empirical orthogonal function modes illustrates that for both El Niño and La Niña extreme events are more likely than expected from a normal distribution. The Bjerknes feedbacks and time evolution of strong ENSO events in observations as well as in coupled model simulations also show strong asymmetries, with strong El Niños being forced more strongly by zonal wind than by thermocline depth anomalies and are followed by La Niña events. In turn strong La Niña events are preceded by El Niño events and are more strongly forced by thermocline depth anomalies than by wind anomalies. Further, the zonal wind response to sea surface temperature anomalies during strong El Niño events is stronger and shifted to the east relative to strong La Niña events, supporting the eastward shifted El Niño pattern and the asymmetric time evolution. Based on the simplified hybrid coupled RECHOZ model of ENSO it can be shown that the non-linear zonal wind response to SST anomalies causes the asymmetric forcings of ENSO events. This also implies that strong El Niños are mostly wind driven and less predictable and strong La Niñas are mostly thermocline depth driven and better predictable, which is demonstrated by a set of 100 perfect model forecast ensembles.     

Walker circulation controls ENSO atmospheric feedbacks in uncoupled and coupled climate model simulations

Many climate models strongly underestimate the two most important atmospheric feedbacks operating in El Niño/Southern Oscillation (ENSO), the positive (amplifying) zonal surface wind feedback and negative (damping) surface-heat flux feedback (hereafter ENSO atmospheric feedbacks, EAF). This hampers a realistic representation of ENSO dynamics in these models. Here we show that the atmospheric components of climate models participating in the 5th phase of the Coupled Model Intercomparison Project (CMIP5) when forced by observed sea surface temperatures (SST), already underestimate EAF on average by 23%, but less than their coupled counterparts (on average by 54%). There is a pronounced tendency of atmosphere models to simulate stronger EAF, when they exhibit a stronger mean deep convection and enhanced cloud cover over the western equatorial Pacific (WEP), indicative of a stronger rising branch of the Pacific Walker Circulation (PWC). Further, differences in the mean deep convection over the WEP between the coupled and uncoupled models explain a large part of the differences in EAF, with the deep convection in the coupled models strongly depending on the equatorial Pacific SST bias. Experiments with a single atmosphere model support the relation between the equatorial Pacific atmospheric mean state, the SST bias and the EAF. An implemented cold SST bias in the observed SST forcing weakens deep convection and reduces cloud cover in the rising branch of the PWC, causing weaker EAF. A warm SST bias has the opposite effect. Our results elucidate how biases in the mean state of the PWC and equatorial SST hamper a realistic simulation of the EAF.     

Comparing the spatial structure of variability in two datasets against each other on the basis of EOF-modes

In analysis of climate variability or change it is often of interest how the spatial structure in modes of variability in two datasets differ from each other, e.g. between past and future climate or between models and observations. Often such analysis is based on Empirical Orthogonal Function (EOF) analysis or other simple indices of large-scale spatial structures. The present analysis lays out a concept on how two datasets of multivariate climate variability can be compared against each other on basis of EOF analysis and how the differences in the multivariate spatial structure between the two datasets can be quantified in terms of explained variance in the leading spatial patterns. It is also illustrated how the patterns of largest differences between the two datasets can be defined and interpreted. We illustrate this method on the basis of several well-defined artificial examples and by comparing our approach with examples of climate change studies from the literature. These literature examples include analysis of changes in the modes of variability under climate change for the sea level pressure (SLP) of the North Atlantic and Europe, the SLP of the Southern Hemisphere, the surface temperature of the Northern Hemisphere, the sea surface temperature of the North Pacific and for precipitation in the tropical Indo-Pacific.