CL2.13

During El Niño, the upwelling in the eastern equatorial Pacific (EEP) slows, leading to a warm sea surface temperature (SST) anomaly, and the tropical troposphere warms. Only SSTs in regions with atmospheric deep convection, typically the warmest SSTs, affect the temperature of the tropical free troposphere. The warming of the EEP, which is home to the coldest tropical SSTs and does not experience atmospheric convection, therefore appears insufficient to explain the observed warming of the troposphere. Here, we examine the physical processes that lead to the warming of the warmest SSTs using both a global atmosphere-ocean coupled climate model and the ECMWF reanalysis. We show that SSTs in convecting regions do not warm as a result of ocean dynamics (upwelling), but as a result of a net heat flux from the atmosphere to the ocean following a weakening of surface winds and decrease in evaporation. This increased ocean heat uptake in convecting regions opposes the decrease in ocean heat uptake in the rest of the tropics during El Nino. This process may be important for linking surface temperature to ocean heat uptake changes, and the contribution of internal variability in the form of ENSO and IPO to the forced response observed over the historical record.

How to cite: Hogikyan, A., Fueglistaler, S., and Resplandy, L.: What warms the warmest waters during El Niño?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3340, https://doi.org/10.5194/egusphere-egu21-3340, 2021.

Analysis of a long control run of the Hadley Centre coupled model shows that ENSO asymmetry is weak. We use the same model in our seasonal and decadal prediction systems, and while on seasonal timescales the initialised prediction realistically captures the amplitude of extreme El Niño events, on longer timescales the predictions revert to the control behaviour i.e. there are no very large El Niño events. This may impact on our ability evaluate the risk of extreme regional events. Here we show results exploring asymmetry in both the control model, and also from a number of perturbed parameter experiments, each a plausible realisation of the control.

How to cite: Ineson, S., Dunstone, N., Scaife, A., and Yamazaki, K.: ENSO asymmetry: the search for extreme El Niño events in HadGEM, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9593, https://doi.org/10.5194/egusphere-egu21-9593, 2021.

A recent high-resolution ocean model study of the strong El Ninos of 1982-1983 and 1997-1998 highlighted a previously neglected ocean mechanism which was active during their growth.   The mechanism involved a weakening of both the Equatorial Current and the tropical instability eddies in mid-ocean.  It also involved an increase in the strength of the North Equatorial Counter Current due to the passage of the annual Rossby wave.

      This presentation reports how satellite altimeter and satellite SST data was used to validate the model results the key areas, confirming the changes in the current and eddy fields and the resulting eastward extension of the region of highest SST values.  The SST changes were sufficient to trigger new regions deep-atmospheric convection and so had the potential to have a significant impact on the development of the El Nino and the resulting changes in the large scale atmospheric circulation.

How to cite: Webb, D., Coward, A., and Snaith, H.: Using Satellite Altimeter and SST Observations of the 1997-1998 El Nino to Check the Key Ocean Processes Involved in a Strong El Nino., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-297, https://doi.org/10.5194/egusphere-egu21-297, 2020.

The El Niño-Southern Oscillation (ENSO) is linked with energy exchange between the ocean, atmosphere and space. By using the particle dispersion model FLEXPART the atmospheric energy transport originating from the Tropical Pacific is analysed, with special focus on the connection to the Atlantic Ocean during El Niño. The Lagrangian model was filled homogeneously with five million, globally distributed particles, which were then traced forward in time from 1990 until 2016. Due to the domain-filling option used in FLEXPART, the particles represent the atmospheric mass transport. From this 26 year-long Lagrangian Reanalysis Dataset, particles between 5°S-5°N and 170°W-100°W were selected and followed both forward and backward in time. Therefore, the source regions of the energy and moisture in the Tropical Pacific can be detected, but also where they are further transported. Special focus is placed on the connection to the Atlantic Ocean. By analysing the different forms of energy (potential, - internal, - and latent energy), their transport from the Tropical Pacific into the Atlantic Ocean can be quantified. In addition, the differences between El Niño and La Niña are studied, as well as strong and weak El Niño cases.

How to cite: Baier, K., Stohl, A., Mayer, M., and Haimberger, L.: Energy Export from the Tropical Pacific via the Atmosphere – a Lagrangian Perspective, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2935, https://doi.org/10.5194/egusphere-egu21-2935, 2021.

El Niño is a large-scale ocean-atmospheric coupling phenomenon in the Pacific. The interaction among marine and atmospheric variables over the tropical Pacific modulate the evolution of El Niño. The latest research shows that machine learning and neural network (NN) have appeared as effective tools to achieve meaningful information from multiple marine and atmospheric parameters. In this paper, we aim to predict the El Niño index more accurately and increase the forecast efficiency of El Niño events. Here, we propose an approach combining a neural network technique with long short-term memory (LSTM) neural network to forecast El Niño phenomenon. The attributes of model are resulted from physical explanation which are tested with the experiments and observations. The neural network represents the connection among multiple variables and machine learning creates models to identify the El Niño events. The preliminary experimental results exhibit that training NN-LSTM model on network metrics time series dataset provides great potential for predicting El Niño phenomenon at lag times of up to more than 6 months.  

How to cite: Song, W., Lu, W., and Dong, Q.: El Niño Index forecasting using machine learning techniques , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5146, https://doi.org/10.5194/egusphere-egu21-5146, 2021.

The most dominant mode of oceanic climate variability on an interannual scale is the El Niño-Southern Oscillation (ENSO), which is characterized by anomalous sea surface temperatures (SSTs) in the equatorial Pacific. The SST fields associated with ENSO show strong variability between different events, also known as ENSO diversity. While the diversity of SST patterns have a strong impact on local climate, ecosystem and society, the spatial differences between ENSO events are not yet fully understood.

In this work, we present a data-driven approach to model SST anomaly patterns in the Pacific using a deep generative model. In particular, we use a variational autoencoder (VAE) to nonlinearly decompose the monthly SST anomalies into a low dimensional ‘latent’ space. VAEs are probabilistic models with neural network transition functions which allow us to model nonlinear features, quantify uncertainty, and include prior knowledge. In our approach, we use mutual information to favor a disentangled latent space with respect to a ground truth derived from correlation-based spatial SST clustering. The VAE-based approach improves upon earlier non-linear dimensionality reduction methods like kernel PCA which only optimize for statistical properties.

Our results indicate that the anomalous SST field diversity can be explained primarily by 1) an eastern equatorial Pacific component, 2) a central equatorial Pacific component and 3) a transequatorial component. The components capture underlying spatial correlations to regions in the Northern Pacific and to the basin wide horseshoe pattern. We also observe an asymmetry between the warm and cool phases of the components.

How to cite: Schlör, J. and Goswami, B.: A data-driven generative model for sea surface temperature fields in the tropical Pacific, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12362, https://doi.org/10.5194/egusphere-egu21-12362, 2021.

Tropical Pacific upwelling-dependent ecosystems are the most productive and variable worldwide, mainly due to the influence of El Niño Southern Oscillation (ENSO). ENSO can be forecasted seasons ahead thanks to assorted climate precursors (local-Pacific processes, pantropical interactions). However, owing to observational data scarcity and bias-related issues in earth system models, little is known about the importance of these precursors for marine ecosystem prediction. With recently released reanalysis-nudged global marine ecosystem simulations, these constraints can be sidestepped, allowing full examination of tropical Pacific ecosystem predictability. By complementing historical fishing records with marine ecosystem model data, we show herein that equatorial Atlantic Sea Surface Temperatures (SSTs) constitute a superlative predictability source for tropical Pacific marine yields, which can be forecasted over large-scale areas up to 2 years in advance. A detailed physical-biological mechanism is proposed whereby Atlantic SSTs modulate upwelling of nutrient-rich waters in the tropical Pacific, leading to a bottom-up propagation of the climate-related signal across the marine food web. Our results represent historical and near-future climate conditions and provide a useful springboard for implementing a marine ecosystem prediction system in the tropical Pacific.

How to cite: Gómara, I., Rodríguez-Fonseca, B., Mohino, E., Losada, T., Polo, I., and Coll, M.: Skillful prediction of tropical Pacific fisheries provided by Atlantic Niños, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3190, https://doi.org/10.5194/egusphere-egu21-3190, 2021.

The tropical Indian Ocean has warmed by 1 degree Celsius since the mid-twentieth century. This warming is likely to continue as the atmospheric carbon dioxide levels keep rising. Here, we discuss how the warming trend could influence the El Niño Southern Oscillation (ENSO) via interaction with the Pacific and the Atlantic Ocean mean state and variability. The warming trend leads to the strengthening of easterlies in the western equatorial Pacific, subsequent downwelling and increase of the mixed later depth in the west, and an increase in the subsurface temperature gradient across the equatorial Pacific. In the eastern equatorial Pacific, the response of upwelling ocean currents to surface wind stress decreases, resulting in a weakening of ENSO amplitude. The Indian Ocean warming influences ENSO via the Atlantic Ocean as well. There, it is associated with the strengthening of equatorial easterly winds, and anomalous warming in the west and upwelling induced cooling in the east, especially in austral winter, during the peak of the Atlantic Niño. Consequently, this results in a decrease of the amplitude of Atlantic Niño events and weakening of the Atlantic Niño-ENSO teleconnection, thereby hindering the transition of El Niño events to La Niña events. Thus, the Indian Ocean warming trend is found to modulate tropical Pacific and Atlantic mean state and variability, with implications for ENSO predictability under a warming climate.

How to cite: Dhame, S., Taschetto, A., Santoso, A., Liguori, G., and Meissner, K.: Warming of the Indian Ocean weakens the Atlantic Niño - El Niño Southern Oscillation connection , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13911, https://doi.org/10.5194/egusphere-egu21-13911, 2021.

Since the start of the 21st century, El Niño-Southern Oscillation (ENSO) variability has changed, supporting generally weaker Central Pacific El Niño events. Recent studies suggest that stronger trade winds in the equatorial Pacific could be a key driving force contributing to this shift. One possible mechanism to drive such changes in the mean tropical Pacific climate state is the enhanced warming trends in the tropical Indian Ocean (TIO) relative to the rest of the tropics. TIO warming can affect the Walker circulation in both the Pacific and Atlantic basins by inducing quasi-stationary Kelvin and Rossby wave patterns. Using the latest coupled-model from Insitut Pierre Simon Laplace (IPSL-CM6), ensemble experiments are conducted to investigate the effect of TIO sea surface temperature (SST) on ENSO variability. Applying a weak SST nudging over the TIO region, in four ensemble experiments we change mean Indian ocean SST by -1.4°C, -0.7°C, +0.7°C, and +1.4°C and find that TIO warming changes the magnitude of the mean equatorial Pacific zonal wind stress proportionally to the imposed forcing, with stronger trades winds corresponding to a warmer TIO. Surprisingly, ENSO variability increases in both TIO cooling and warming experiments, relative to the control. While a stronger ENSO for weaker trade winds, associated with TIO cooling, is expected from previous studies, we argue that the ENSO strengthening for stronger trade winds, associated with TIO cooling, is related to the induced changes in ocean stratification. We illustrate this effect by computing different contributions to the Bjerknes stability index. Thus, our results suggest that the tropical Indian ocean temperatures are an important regulator of TIO mean state and ENSO dynamics.

How to cite: Ferster, B., Fedorov, A., Mignot, J., and Guilyardi, E.: ENSO response to changes in the tropical Indian ocean temperature, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2881, https://doi.org/10.5194/egusphere-egu21-2881, 2021.

The predictability of El Niño and La Niña is investigated. In this case, the recently discovered so-called Global Atmospheric Oscillation (GAO) is considered (Serykh et al., 2019). Assuming GAO to be the main mode of short-term climatic variability, this study defines an index that characterizes the dynamics and relationships of the extratropical components of the GAO and El Niño – Southern Oscillation (ENSO). Due to the general propagation of the GAO’s spatial structure from west to east, another index – predictor of ENSO is defined. The cross-wavelet analysis between both of these indices and the Oceanic Niño Index (ONI) is performed. This analysis reveals a range of timescales within which the closest relationship between the GAO and ONI takes place. Using this relationship, it is possible to predict El Niño and La Niña with a lead-time of approximately 12 months (Serykh and Sonechkin, 2020a).

Using data on the distribution of temperatures in the Pacific, Indian, and Atlantic Oceans, large-scale structures of spatial and temporal variations of these temperatures are investigated (Serykh and Sonechkin, 2020b). A structure is found which is almost identical to the spatial and temporal sea surface temperature (SST) structure that is characteristic of the GAO. Variations in water temperature in a near-equatorial zone of the Pacific Ocean at depths up to about 150 meters behave themselves in the same way as variations in sea surface height and SST. At even greater depths, variations in water temperature reveal a "striped" structure, which is, however, overall similar to that of SST variations. Variations of water temperature at depths in all three oceans spread from east to west along the equator with a period of 14 months. This makes it possible to think that the dynamics of these temperatures are controlled by the so-called Pole tides. The surface North Pacific Pole Tide was found previously responsible for excitation of El Niño (Serykh and Sonechkin, 2019). The deep Pole tides in the Southern Atlantic and Southern Indian Ocean appear to be triggers of the Atlantic El Niño and Indian Ocean Dipole (IOD). Thus, IOD manifests itself at the depth of the thermocline more clearly than on the surface of the Indian Ocean. The out-of-phase behavior of El Niño and IOD is explained by the 180-degree difference in the longitudes of these phenomena.

References

Serykh I.V., Sonechkin D.M. Nonchaotic and globally synchronized short-term climatic variations and their origin // Theoretical and Applied Climatology. 2019. Vol. 137. No. 3-4. pp 2639–2656. https://doi.org/10.1007/s00704-018-02761-0

Serykh I.V., Sonechkin D.M., Byshev V.I., Neiman V.G., Romanov Yu.A. Global Atmospheric Oscillation: An Integrity of ENSO and Extratropical Teleconnections // Pure and Applied Geophysics. 2019. Vol. 176. pp 3737–3755. https://doi.org/10.1007/s00024-019-02182-8

Serykh I.V., Sonechkin D.M. El Niño forecasting based on the global atmospheric oscillation // International Journal of Climatology. 2020a. https://doi.org/10.1002/joc.6488

Serykh I.V., Sonechkin D.M. Interrelations between temperature variations in oceanic depths and the Global atmospheric oscillation // Pure and Applied Geophysics. 2020b. Vol. 177. pp 5951–5967. https://doi.org/10.1007/s00024-020-02615-9

How to cite: Serykh, I. and Sonechkin, D.: Interactions of temperature fluctuations of the Pacific, Indian and Atlantic oceans with Global atmospheric oscillation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-232, https://doi.org/10.5194/egusphere-egu21-232, 2020.

The Atlantic Multidecadal Variability (AMV) has been linked to the observed slowdown of global warming over 1998-2012 through its impact on the tropical Pacific. Given the global importance of tropical Pacific variability, better understanding this Atlantic-Pacific teleconnection is key for improving climate predictions, but the robustness and strength of this link is uncertain. Analysing a multi-model set of sensitivity experiments, we find that models differ by a factor 10 in simulating the amplitude of the Equatorial Pacific cooling response to observed AMV warming. The inter-model spread is mainly driven by different amounts of moist static energy injection from the tropical Atlantic surface into the upper troposphere. We reduce this inter-model uncertainty by analytically correcting models for their mean precipitation biases and we quantify that, following an observed 0.26ºC AMV warming, the equatorial Pacific cools by 0.16ºC with an inter-model standard deviation of 0.03ºC.

How to cite: Ruprich-Robert, Y. and the the AMV - Tropical Pacific study team: Impacts of Atlantic Multidecadal Variability on the Tropical Pacific: a multi-model study, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3477, https://doi.org/10.5194/egusphere-egu21-3477, 2021.

The El Niño Southern Oscillation (ENSO) is the leading mode of global climate variability on interannual timescales. On longer time-scales, decadal variability in the Pacific is responsible for modulating the rate of global warming (Meehl et al 2013, Maher et al 2014 Henley & King 2017). Whether Pacific Decadal Variability (PDV) modulates ENSO teleconnections is an important research question that has largely been investigated using the observational record. PDV is shown to modulate Australian rainfall (Power et al 1999, Arblaster et al 2002, Verdon et al, 2004, King et al 2013), which has impacts for flood frequency (Franks and Kuczera, 2002, Kiem et al, 2003, Pui et al 2011). PDV has also been shown to modulate ENSO precipitation teleconnections over Africa (Dong & Dai 2015), Texas (Khedun et al 2014), and Europe (Zanchettin et al 2008) as well as ENSO temperature teleconnections over New Zealand (Salinger et al 2001). While these observationally based studies suggest connections between ENSO teleconnections and PDV, the short observational record contains only two PDV phase changes. In addition, calculating PDV using a lowpass filter on the region that contains ENSO could also cause statistical artefacts in the results (Power at al, 2006, Westra et al 2015). These limitations can be addressed using climate models. Arblaster et al (2002) use atmosphere only simulations and find similar results to observational studies over Australia. Dong and Dai (2015) further investigate global modulation using 4 ensemble members of a single model. These modelling studies are limited in their use of single models and while they include a larger dataset than the observational record, previous work has only used small ensemble sizes. In this study, we address both the issue of small datasets and the dependence on results on the model used by utilising four single model initial-condition large ensembles.  Each model ensemble has a minimum of 20 members enabling investigation of multiple realizations of PDV and ENSO covariability. Over the historical period, using one ensemble member results in a record that is indeed too short to accurately quantify the influence of PDV on ENSO teleconnections. We then composite events for different phases of the PDV and ENSO using all ensemble members. Initial results show that PDV strongly influences ENSO temperature teleconnections over North America.  We find that stronger teleconnections occur when an El Niño occurs during a positive phase of PDV or a La Niña occurs in a negative phase of the PDV. Similarly, PDV phase affects precipitation over Australia, where co-occurring El Niño and positive PDV phases and La Niña and negative PDV phases have larger precipitation anomalies. Finally we investigate whether this modulation of ENSO teleconnections by the PDV is projected to change under strong anthropogenic forcing. We find greater inter-model agreement for precipitation teleconnections than for temperature teleconnections.  Ongoing work will assess the underlying physical mechanisms behind these results. 

How to cite: Maher, N., Capotondi, A., and Kay, J.: Global modulation of ENSO teleconnections by Pacific Decadal Variability, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12790, https://doi.org/10.5194/egusphere-egu21-12790, 2021.

Correctly capturing the teleconnection between the ENSO and Europe is of importance for seasonal prediction. Here we investigate how systematic model biases may affect this teleconnection. A two–step bias–correction process is applied to an atmospheric general circulation model to reduce errors in the climatology. The bias–corrections are applied to the troposphere and stratosphere separately and together to produce a range of climates. ENSO type sensitivity experiments are then performed to reveal the impact of differing climatologies on ENSO–Europe teleconnections.

The bias–corrections do not affect the response of the tropical atmosphere, nor the Aleutian Low, to strong ENSO anomalies. However, the anomalous upward wave flux and the response of the northern hemisphere polar vortex differs between the climatologies. We attribute this to a reduced sensitivity of waves to the strength of the Aleutian Low. Despite the differing responses of the polar vortex, the NAO response is similar between the climatologies, implying that for strong ENSO events the stratospheric response may not be the primary driver for the ENSO–North Atlantic teleconnection.

How to cite: Tyrrell, N. and Karpechko, A.: Minimal impact of model biases on northern hemisphere ENSO teleconnections., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4025, https://doi.org/10.5194/egusphere-egu21-4025, 2021.

El Niño-Southern Oscillation can influence the Tropical North Atlantic (TNA), leading to anomalous sea surface temperatures (SST) at a lag of several months. Several mechanisms have been proposed to explain this teleconnection. These mechanisms include both tropical and extratropical pathways, contributing to anomalous trade winds and static stability over the TNA region. The TNA SST response to ENSO has been suggested to be nonlinear. Yet the overall linearity of the ENSO-TNA teleconnection via the two pathways remains unclear. Here we use reanalysis data to confirm that the SST anomaly (SSTA) in the TNA is nonlinear with respect to the strength of the SST forcing in the tropical Pacific, as further increases in El Niño magnitudes cease to create further increases of the TNA SSTA. We further show that the tropical pathway is more linear than the extratropical pathway by sub-dividing the inter-basin connection into extratropical and tropical pathways. The extratropical pathway is modulated by the North Atlantic Oscillation (NAO) and the location of the SSTA in the Pacific, but this modulation insufficiently explains the nonlinearity in TNA SSTA. As neither extratropical nor tropical pathways can explain the nonlinearity, this suggests that external factors are at play. Further analysis shows that the TNA SSTA is highly influenced by the preconditioning of the tropical Atlantic SST. This preconditioning is found to be associated with the NAO through SST-tripole patterns.

How to cite: Casselman, J. W., Taschetto, A. S., and Domeisen, D. I. V.: Non-linearity in the pathway of El Niño-Southern Oscillation to the tropical North Atlantic, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7483, https://doi.org/10.5194/egusphere-egu21-7483, 2021.

This research analyses the observed relationship between eastern and central Pacific El Niño Southern Oscillation (ENSO) events and Australian monsoon rainfall (AUMR) on a decadal timescale during the December to March monsoon months. To assess the decadal influence of the different flavours of ENSO on the AUMR, we focus on the phases of the Interdecadal Pacific Oscillation (IPO) over the period 1920 to 2020.  The AUMR is characterized by substantial decadal variability, which appears to be linked to the positive and negative phases of the IPO. During the past two historical negative IPO phases, significant correlations have been observed between central Pacific sea surface temperature (SST) anomalies and AUMR over both the northeast and northwest of Australia. This central Pacific SST-AUMR relationship has strengthened from the first negative IPO phase (mid-1940s to the mid-1970s) to the second (late 1990s to mid-2010s), while the eastern Pacific SST-AUMR influence has weakened. Composite rainfall anomalies over Australia reveal a different response of AUMR to central Pacific El Niño/La Niña and eastern Pacific La Niña events during positive IPO and negative IPO phases. This research clearly shows that ENSO's influence on AUMR is modulated by Pacific decadal variability, however this teleconnection, in itself, can change between similar decadal Pacific states.  Going forward, as decadal prediction systems improve and become more mainstream, the IPO phase could be used as a potential source for decadal predictability of the tendency of AUMR.  

How to cite: Heidemann, H., Ribbe, J., Henley, B. J., Cowan, T., Pudmenzky, C., Stone, R., and Cobon, D. H.: The relationship between the El Niño Southern Oscillation and Australian monsoon rainfall on decadal time-scales, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10482, https://doi.org/10.5194/egusphere-egu21-10482, 2021.

Identification of El Niño warm events and their types has traditionally been deterministic, based mainly on whether a pre-defined index exceeded a critical value. However, uncertainties in both sea surface temperature (SST) measurements and their interpolation into a gridded analysis can impact identification of and confidence in El Niño variability, particularly earlier in the record. Although several different classification methods for El Niño exist, researchers lack an effective reference and evaluation system to identify advantages and disadvantages of a given index for a given application. Therefore, this study quantifies the impacts of both data- and method-related uncertainties on different El Niño classification methods, considering different types of uncertainty, different types of analysis, different teleconnection mechanisms and expressions of El Niño impact and different types of climate data. To aid in these objectives, El Niño classification methods are evaluated from five aspects: reliability, accuracy, precision, flexibility, and simplicity. The core analysis is based on probabilistic, uncertainty-aware classifications applied to a large ensemble of historical SST realizations. The results are then used to conduct a more general evaluation of how different types of uncertainty propagate through the different classification methods, and provide guidance on the strengths and weaknesses of these indices for different applications.

How to cite: Zhu, M., Wright, J., Ilyas, M., and Brierley, C.: Uncertainties in SST datasets and implications for El Niño event classification, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5240, https://doi.org/10.5194/egusphere-egu21-5240, 2021.

From 2014 through 2016, a significant El Niño event and the North Pacific warm anomaly (a.k.a., “the blob”) resulted in a marine heatwave across the Eastern North Pacific Ocean. To develop a deeper understanding of the impacts of El Niño on the Southern California Bight (SCB), we used coastal cyanobacteria populations in order to “bi-directionally” link shifts in microbial diversity and biogeochemical conditions. We sequenced the rpoC1 gene from the ecologically important picocyanobacteria Prochlorococcus and Synechococcus at 434 time points from 2009–2018 in the MICRO time series at Newport Beach, CA. Across the time series, we observed an increase in the abundance of Prochlorococcus relative to Synechococcus as well as elevated frequencies of clades commonly associated with low-nutrient and high-temperature conditions. The relationships between environmental and diversity trends appeared to operate on differing temporal scales. In addition, microdiverse populations from the Prochlorococcous HLI clade as well as Synechococcus Clade II that shifted in response to the 2015 El Niño did not return to their pre-heatwave composition by the end of this study. This research demonstrates that El Niño-driven warming in the SCB can result in persistent changes in key microbial populations.

How to cite: Larkin, A., Moreno, A., Fagan, A., and Martiny, A.: Persistent El Nino driven shifts in marine cyanobacteria populations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6952, https://doi.org/10.5194/egusphere-egu21-6952, 2021.

Climate change, in particular the rise in tropical sea surface temperatures, is the greatest threat to coral reef ecosystems today and causes climatic extremes affecting the livelihood of tropical societies. The combination of long-term global warming and interannual El Niño-related warm events has severely affected corals and coral reefs throughout the tropical ocean basins. Mass coral bleaching, a result of large-scale temperature stress, was first observed during the 1982/83 El Niño, and was followed by much more severe, global scale bleaching events during the El Niño years of 1997/98 and 2010, culminating in the most wide-spread and most destructive global bleaching episode to date, which lasted from 2014-2017. The interval between recurrent mass coral bleaching events driven by anomalously high sea surface temperatures is becoming too short for a full recovery of mature coral reef assemblages and will have dramatic effects on future coral reef growth. Assessing how future warming will change coral reef ecosystems and tropical climate variability is therefore of extreme urgency.

The recently established Priority Programme „Tropical Climate Variability and Coral Reefs – A Past to Future Perspective on Current Rates of Change at Ultra-High Resolution“ (SPP 2299; https://www.spp2299.tropicalclimatecorals.de/) of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) aims to enhance our current understanding of tropical marine climate variability and its impact on coral reef ecosystems in a warming world, by quantifying climatic and environmental changes during both the ongoing warming and past warm periods on timescales relevant for society. Ultra-high resolution coral geochemistry provides a tool to understand the temporal response of corals and coral reefs to ongoing climate and environmental change, to reconstruct past tropical climate and environmental variability and to use these data in conjunction with advanced statistical methods, earth system modelling and observed ecosystem responses for improved projections of future changes in tropical climate and coral reef ecosystems.

The Priority Programme is organised around three major research topics in order to fuel interdisciplinary collaboration among various disciplines: (a) Large-scale ocean, climate & environment reconstructions, (b) Coral & reef-scale response to current environmental stress, and (c) Climate, reef & proxy modelling – Climate & proxy advanced statistics. The strongly interdisciplinary Priority Programme will bring together expertise in the fields of climate, environmental and ecosytem research in a sustainable manner, and aims to provide an ultra-high resolution past to future perspective on current rates of change to project how tropical marine climate variability and coral reef ecosystems will change in a warming world.

How to cite: Felis, T. and Pfeiffer, M.: Tropical Climate Variability and Coral Reefs - A Past to Future Perspective on Current Rates of Change at Ultra-High Resolution, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2353, https://doi.org/10.5194/egusphere-egu21-2353, 2021.

The mid-Piacenzian or mid-Pliocene warm period (mPWP, 3.264 – 3.025 Ma) is the most recent geological period to see atmospheric CO­₂ levels similar to the present-day values (~400 ppm). Some proxy reconstructions for the mPWP show reduced zonal SST gradients in the tropical Pacific Ocean, possibly indicating an El Niño-like mean state in the mid-Pliocene. However, past modelling studies do not show the same results. Efforts to understand mPWP climate dynamics have led to the Pliocene Model Intercomparison Project (PlioMIP). Results from the first phase (PlioMIP1) showed clear El Niño variability (albeit significantly reduced) and did not show the greatly reduced time-mean zonal SST gradient suggested by some of the proxies.

In this work, we study ENSO variability in the PlioMIP2 ensemble, which consists of additional global coupled climate models and updated boundary conditions compared to PlioMIP1. We quantify ENSO amplitude, period and spatial structure as well as the tropical Pacific annual mean state in a mid-Pliocene and pre-industrial reference simulation. Results show a reduced El Niño amplitude in the model- ensemble mean, with 11 out of 13 individual models showing such a reduction. Furthermore, the spectral power of this variability considerably decreases in the 3–7-year band and shifts to higher frequencies compared to pre-industrial. The spatial structure of the dominant EOF shows no particular change in the patterns of tropical Pacific variability in the model-ensemble mean, compared to the pre-industrial. Further analyses that will be presented include the correlation of the zonal SST gradient with the El Niño amplitude, investigation of shift in El Niño flavour, and a discussion of the coupled feedbacks at play in the mid-Pliocene tropical Pacific Ocean.

How to cite: Oldeman, A., Baatsen, M., von der Heydt, A., Dijkstra, H., and Tindall, J.: Reduced El Niño variability in the PlioMIP2 model ensemble, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10002, https://doi.org/10.5194/egusphere-egu21-10002, 2021.

How to cite: Abdelkader Di Carlo, I., Braconnot, P., Marti, O., and Elliot, M.: How is the increase in the variability of ENSO events over the last 6000 years linked to the mean state change of the tropical Pacific Ocean ?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3395, https://doi.org/10.5194/egusphere-egu21-3395, 2021.

Year-to-year variations of the Maritime Continent (MC, 80E-160E & 18S-26N) rainfall is strongly influenced by ENSO variability. Seasonal predictability of the MC rainfall heavily relies on climate models’ ability to simulate realistic ENSO developments and its teleconnection. Here we analyze 32 available state-of-the-art CMIP6 models, and find that most models are able to simulate the observed negative ENSO-rainfall teleconnection [i.e., drier than normal during El Niño and wetter than normal during La Niña] over the MC during the boreal winter (DJF, when ENSO normally peaks). Using the sign-adjusted bias analysis for the historical period [1980-2014], we show that CMIP6 models tend to systematically underestimate the negative correlation in the central MC and overestimate the positive correlation in the eastern MC due to the westward intrusion of the positive correlation within the tropical Pacific. In regard to changes in the ENSO-rainfall teleconnection over the MC under global warming, the multi-model mean suggests that, by the end of the 21st century [2065-2099] under the highest emission scenario (SSP585), the negative ENSO-rainfall teleconnection over the western and central MC will strengthen while the positive teleconnection over the eastern MC will weaken. These spatially opposing changes of ENSO teleconnection under global warming could induce dramatic multi-sectoral impacts within the MC.

How to cite: Chen, C., Sahany, S., Moise, A. F., Chua, X. R., Hassim, M. E., Lim, G., and Prasanna, V.: Opposing changes of ENSO-rainfall teleconnection over the Maritime Continent under global warming, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6931, https://doi.org/10.5194/egusphere-egu21-6931, 2021.

The El Niño-Southern Oscillation (ENSO) has previously been shown to influence the winter North Atlantic Oscillation (NAO).  In this presentation we investigate the ENSO-NAO teleconnection in historical and RCP8.5 scenario CMIP5 simulations, and show a future strengthening of the teleconnection under RCP8.5.  The teleconnection strength is associated with increased tropical east Pacific rainfall variability.  Stratospheric and tropospheric teleconnection pathways are examined, with both pathways having stronger links in future.  The stratospheric pathway involves the Aleutian Low and the stratospheric polar vortex, with a downward influence on the NAO.  This pathway is clearest in the high-top models that better resolve the stratosphere.  The tropospheric pathway is driven by the Pacific subtropical jet strengthening and extending further into the Atlantic in future, generating increased baroclinicity in the Caribbean and influencing the Atlantic storm track.  Our results suggest increasing influence of tropical rainfall on extratropical circulation in future.

How to cite: Fereday, D., Chadwick, R., Knight, J., and Scaife, A.: Tropical rainfall linked to stronger future ENSO-NAO teleconnection in CMIP5 models, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8425, https://doi.org/10.5194/egusphere-egu21-8425, 2021.