The 2019/20 Australian black summer bushfires were particularly severe in many respects, including its early commencement, large spatial coverage, and large number of burning days, preceded by record ...dry and hot anomalies. Determining whether greenhouse warming has played a role is an important issue. Here, we examine known modes of tropical climate variability that contribute to droughts in Australia to provide a gauge. We find that a two-year consecutive concurrence of the 2018 and 2019 positive Indian Ocean Dipole and the 2018 and 2019 Central Pacific El Niño, with the former affecting Southeast Australia, and the latter influencing eastern and northeastern Australia, may explain many characteristics of the fires. Such consecutive events occurred only once in the observations since 1911. Using two generations of state-of-the-art climate models under historical and a business-as-usual emission scenario, we show that the frequency of such consecutive concurrences increases slightly, but rainfall anomalies during such events are stronger in the future climate, and there are drying trends across Australia. The impact of the stronger rainfall anomalies during such events under drying trends is likely to be exacerbated by greenhouse warming-induced rise in temperatures, making such events in the future even more extreme.
El Niño’s intensity change under anthropogenic warming is of great importance to society, yet current climate models’ projections remain largely uncertain. The current classification of El Niño does ...not distinguish the strong from the moderate El Niño events, making it difficult to project future change of El Niño’s intensity. Here we classify 33 El Niño events from 1901 to 2017 by cluster analysis of the onset and amplification processes, and the resultant 4 types of El Niño distinguish the strong from the moderate events and the onset from successive events. The 3 categories of El Niño onset exhibit distinct development mechanisms. We find El Niño onset regime has changed from eastern Pacific origin to western Pacific origin with more frequent occurrence of extreme events since the 1970s. This regime change is hypothesized to arise from a background warming in the western Pacific and the associated increased zonal and vertical sea-surface temperature (SST) gradients in the equatorial central Pacific, which reveals a controlling factor that could lead to increased extreme El Niño events in the future. The Coupled Model Intercomparison Project phase 5 (CMIP5) models’ projections demonstrate that both the frequency and intensity of the strong El Niño events will increase significantly if the projected central Pacific zonal SST gradients become enhanced. If the currently observed background changes continue under future anthropogenic forcing, more frequent strong El Niño events are anticipated. The models’ uncertainty in the projected equatorial zonal SST gradients, however, remains a major roadblock for faithful prediction of El Niño’s future changes.
The year 2015 was special for climate scientists, particularly for the El Niño Southern Oscillation (ENSO) research community, as a major El Niño finally materialized after a long pause since the ...1997/1998 extreme El Niño. It was scientifically exciting since, due to the short observational record, our knowledge of an extreme El Niño has been based only on the 1982/1983 and 1997/1998 events. The 2015/2016 El Niño was marked by many environmental disasters that are consistent with what is expected for an extreme El Niño. Considering the dramatic impacts of extreme El Niño, and the risk of a potential increase in frequency of ENSO extremes under greenhouse warming, it is timely to evaluate how the recent event fits into our understanding of ENSO extremes. Here we provide a review of ENSO, its nature and dynamics, and through analysis of various observed key variables, we outline the processes that characterize its extremes. The 2015/2016 El Niño brings a useful perspective into the state of understanding of these events and highlights areas for future research. While the 2015/2016 El Niño is characteristically distinct from the 1982/1983 and 1997/1998 events, it still can be considered as the first extreme El Niño of the 21st century. Its extremity can be attributed in part to unusually warm condition in 2014 and to long‐term background warming. In effect, this study provides a list of physically meaningful indices that are straightforward to compute for identifying and tracking extreme ENSO events in observations and climate models.
Plain Language Summary
The El Niño Southern Oscillation (ENSO) continues to boast its prominence as Earth's strongest source of year‐to‐year climate variability with the appearance of a remarkable El Niño event in 2015–2016. The 2015/2016 El Niño was indeed a strong event with dramatic impact on a global scale. However, it exhibited distinct characteristics from those of past extreme El Niños in modern instrumental record. This challenges our previous understanding of an extreme El Niño which is important for ENSO prediction, monitoring, and future projections. The 2015/2016 El Niño has diversified the small sample of ENSO events in our short instrumental record. It has facilitated important discussions on our progress in understanding the nature of ENSO and its extremes, how they respond to greenhouse warming, and what the climate science community should do next in their quest to fully grasp the complexity of ENSO behavior. These are covered in this review paper which establishes the 2015/2016 El Niño as the first extreme El Niño of the 21st century.
Key Points
The 2015/2016 El Niño is the first extreme El Niño of the 21st century
The 2015/2016 El Niño contributes to a better understanding of ENSO extremes
Multiple simple indices can be used to monitor and identify ENSO extremes
The Indian Ocean Dipole (IOD) affects weather and climate in many parts of the world, but a realistic simulation of the IOD in state‐of‐the‐art climate models remains a challenge. In most models, IOD ...peak‐season amplitudes are systematically larger than that of the observed, a bias that deterministically affects climate projections in IOD‐affected regions. Understanding the cause of this bias is therefore essential for alleviating model errors and reducing uncertainty in climate projections. Here it is shown that most Coupled Model Intercomparison Project Phase Three (CMIP3) and CMIP5 models produce too strong a Bjerknes feedback in the equatorial Indian Ocean, leading to the IOD bias. The thermocline‐sea surface temperature (SST) feedback exerts the strongest influence on the simulated IOD amplitude; models simulating a stronger thermocline‐SST feedback systematically generate a greater IOD amplitude. The strength of the thermocline‐SST feedback in most models is predominantly controlled by the climatological west‐east slope of the equatorial thermocline, which features an unrealistic mean slope tilting upward toward the eastern Indian Ocean. The unrealistic thermocline structure is accompanied by too strong a mean easterly wind and an overly strong west‐minus‐east SST gradient. The linkage of the mean climatic conditions, feedback strength, and projected climate highlights the fundamental importance of realistically simulating these components of the climate system for reducing uncertainty in climate change projections in IOD‐affected regions.
Key Points
Climate models, including CMIP5, simulate too strong an amplitude of the IOD
The IOD amplitude is controlled by an unrealistic mean tilt in the thermocline
Alleviating this bias will help reduce uncertainty in climate projections
An assessment of how well climate models simulate the Indian Ocean dipole (IOD) is undertaken using 20 coupled models that have partaken in phase 5 of the Coupled Model Intercomparison Project ...(CMIP5). Compared with models in phase 3 (CMIP3), no substantial improvement is evident in the simulation of the IOD pattern and/or amplitude during austral spring September–November (SON). The majority of models in CMIP5 generate a larger variance of sea surface temperature (SST) in the Sumatra–Java upwelling region and an IOD amplitude that is far greater than is observed. Although the relationship between precipitation and tropical Indian Ocean SSTs is well simulated, future projections of SON rainfall changes over IOD-influenced regions are intrinsically linked to the IOD amplitude and its rainfall teleconnection in the model present-day climate. The diversity of the simulated IOD amplitudes in models in CMIP5 (and CMIP3), which tend to be overly large, results in a wide range of future modeled SON rainfall trends over IOD-influenced regions. The results herein highlight the importance of realistically simulating the present-day IOD properties and suggest that caution should be exercised in interpreting climate projections in the IOD-affected regions.
Over the past decade the southern catchments of the Murray Darling Basin (MDB), responsible for much of Australia's agricultural output, have experienced a severe drought (termed the “Big Dry”) with ...record high temperatures and record low inflow. We find that during the Big Dry the sensitivity of soil moisture to rainfall decline is over 80% higher than during the World War II drought from 1937–1945. A relationship exists between soil moisture and temperature independent of rainfall, particularly in austral spring and summer. Annually, a rise of 1°C leads to a 9% reduction in soil moisture over the southern MDB, contributing to the recent high sensitivity. Since 1950, the impact from rising temperature contributes to 45% of the total soil moisture reduction. In a warming climate, as the same process also leads to an inflow reduction, the reduced water availability can only be mitigated by increased rainfall. Other implications for future climate change are discussed.
During austral spring of 2019, an extreme positive Indian Ocean Dipole (pIOD) event occurred, with cold sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean (EEIO) and ...warming in the west. Although the growth of the EEIO cold anomalies involves forcing by equatorial nonlinear advection, unique to the 2019 pIOD is an air‐sea heat flux that was a forcing to the EEIO cold anomalies, rather than a damping as in previous extreme events. This unique thermodynamic forcing is due to a large latent cooling, which is supported by an unusually strong wind speed contributed by a large southerly anomaly as part of a long‐term trend. The wind trend is underpinned by a mean state SST change featuring slower warming off Sumatra‐Java. Given that a similar SST trend pattern is projected under greenhouse warming, the likelihood of such thermodynamical forcing operating more frequently in the future needs to be considered.
Plain Language Summary
The occurrence of 2019 extreme pIOD event features the strongest easterly wind anomalies and southerly wind anomalies on record, leading to the strongest wind speed that facilitates the latent cooling to overcome the increased radiative warming over the eastern equatorial Indian Ocean, leading to the unique thermodynamical forcing. This is the first time seen in such extreme pIOD event and is part of a long‐term increasing trend, supported by background changes in SST. As most climate models project a similar SST pattern over the Indian Ocean, it suggests that this unique thermodynamical forcing may operate more frequently under global warming.
Key Points
The 2019 positive Indian Ocean Dipole is a rare extreme event since 1900, second only to the strongest in 1997
Unique to the 2019 event is an air‐sea heat flux forcing the growth of cold anomalies in the eastern Indian Ocean, rather than damping
The unique feature is due to a windspeed‐induced increase in evaporation, supported by a warming pattern as projected for a warming climate
Abstract
Accurately representing the Indian Ocean Dipole (IOD) is crucial for reliable climate predictions and future projections. However, El Niño-Southern Oscillation (ENSO) and IOD interact, ...making it necessary to evaluate ENSO and IOD simultaneously. Using the historical simulation from 32 fifth phase of Coupled Model Intercomparison Project (CMIP5) models and 34 CMIP6 models, here we find that there are some modest changes in the basic characteristics of the IOD and ENSO from CMIP5 to CMIP6. Firstly, there is a slight shift in the seasonality of IOD toward an earlier peak in September in CMIP6, from November in CMIP5. Secondly, inter-model spread in the frequency of ENSO and the IOD has reduced in CMIP6 relative to CMIP5. ENSO asymmetry is still underestimated in CMIP6, based on the skewness of the Niño3 index, while the IOD skewness has degraded from CMIP5. Finally, mean state SST biases impact on the strength of the IOD; the Pacific cold tongue mean state is important in CMIP5, but in CMIP6 the Pacific warm pool mean state is more important.
The El Niño-Southern Oscillation (ENSO) is the dominant and most consequential climate variation on Earth, and is characterized by warming of equatorial Pacific sea surface temperatures (SSTs) during ...the El Niño phase and cooling during the La Niña phase. ENSO events tend to have a centre-corresponding to the location of the maximum SST anomaly-in either the central equatorial Pacific (5° S-5° N, 160° E-150° W) or the eastern equatorial Pacific (5° S-5° N, 150°-90° W); these two distinct types of ENSO event are referred to as the CP-ENSO and EP-ENSO regimes, respectively. How the ENSO may change under future greenhouse warming is unknown, owing to a lack of inter-model agreement over the response of SSTs in the eastern equatorial Pacific to such warming. Here we find a robust increase in future EP-ENSO SST variability among CMIP5 climate models that simulate the two distinct ENSO regimes. We show that the EP-ENSO SST anomaly pattern and its centre differ greatly from one model to another, and therefore cannot be well represented by a single SST 'index' at the observed centre. However, although the locations of the anomaly centres differ in each model, we find a robust increase in SST variability at each anomaly centre across the majority of models considered. This increase in variability is largely due to greenhouse-warming-induced intensification of upper-ocean stratification in the equatorial Pacific, which enhances ocean-atmosphere coupling. An increase in SST variance implies an increase in the number of 'strong' EP-El Niño events (corresponding to large SST anomalies) and associated extreme weather events.
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