Extreme El Nino Southern Oscillation Research Articles

Nonlinear impacts of climate anomalies on oil palm productivity

Oil palm contributes to various global needs as one of the most productive oil crops, but there exist ongoing concerns regarding its yield reductions and associated environmental impacts resulting from land conversion. This is the first detailed report investigating the nonlinear threats to estate-level oil palm yields posed by El Niño Southern Oscillation (ENSO) in the equatorial Pacific Ocean, a major driver of climate variability. Using the Malaysian Palm Oil Board administrative records on monthly performances reported by oil palm estates through the e-submissions portal spanning from January 2015 to June 2023, we focused on elucidating the impacts of ENSO on fresh fruit bunch yield, oil extraction rate, and oil yield. We found that both El Niño and La Niña conditions, characterized by extreme levels of ENSO indices cumulated over lags of 0–23 months prior to harvest, were associated with statistically significant reductions in yields. Lag association patterns unveiled that production risks were linked to pre-harvest exposure to extreme ENSO indices in various time windows. Subgroup analyses further revealed that the effects were pronounced in labor-intensive estates and those lacking fertilizer investments. This study underscores the necessity for adaptation strategies in response to future climate anomalies.

The interplay between climate change and ageing: A systematic review of health indicators.

Climate change and rapid population ageing pose challenges for communities and public policies. This systematic review aims to gather data from studies that present health indicators establishing the connection between climate change and the physical and mental health of the older population (≥ 65 years), who experience a heightened vulnerability to the impacts of climate change when compared to other age cohorts. This review was conducted according to the PICO strategy and following Cochrane and PRISMA guidelines. Three databases (PubMed, Scopus and Greenfile) were searched for articles from 2015 to 2022. After applying inclusion and exclusion criteria,nineteen studies were included. The findings indicated that various climate change phenomena are associated with an elevated risk of mortality and morbidity outcomes in older adults. These included cardiovascular, respiratory, renal, and mental diseases, along with physical injuries. Notably, the impact of climate change was influenced by gender, socioeconomic status, education level, and age-vulnerability factors. Climate change directly affected the health of older adults through ambient temperature variability, extreme and abnormal temperatures, strong winds, sea temperature variability, extreme El Niño-southern Oscillation (ENSO) conditions and droughts, and indirectly by air pollution resulting from wildfires. This review presents further evidence confirming that climate change significantly impacts the health and well-being of older adults. It highlights the urgency for implementing effective strategies to facilitate adaptation and mitigation, enhancing the overall quality of life for all individuals.

Neural network approach for detecting spatial changes in catch probability of Engraulis ringens during El Niño‐Southern Oscillation events in northern Chile

AbstractEngraulis ringens (anchovy) is a small pelagic fish of the Family Engraulidae that inhabits the neretic‐coastal zone from northern Peru to south‐central Chile. It is the main resource species of industrial fishing of northern Chile, representing 80% of the annual landings of the purse seine fleet. The history of this fishery (1985–2023) shows a strong decrease in annual industrial landings, especially during extreme El Niño–Southern Oscillation (ENSO) events. The greatest decrease in landings in two decades occurred in 2020, coinciding with a cold La Niña event, which had not been observed in previous La Niña events. We evaluated whether the current decrease in annual landings of E. ringens is associated with oceanographic changes in northern Chile during El Niño or La Niña events. We applied a neuronal network model to identify the spatial and temporal distribution of E. ringens using the catch probability of each boat of the industrial purse seine fleet. The selected oceanographic variables (sea surface temperature, salinity, depth of the mixed layer, sea height and currents) for the 2003–2020 period were obtained from the Copernicus Marine Environment Monitoring Service (CMEMS program) and used as predictor variables of the monthly landings of E. ringens. The neural network model explained 97% of the monthly variability of catch probability of E. ringens by the industrial purse seine fleet. The spatial distribution of catch probability of E. ringens was analyzed independently for El Niño (2015), La Niña (2007, 2013, and 2020), and Neutral (2004) years. We found that catch probability extended further west during La Niña events (except for 2020), occupying a greater area, but were limited to a 10 nautical mile coastal strip during the El Niño event. The spatial distribution of catch probability in the Neutral condition was near the coast, although not as restricted as during the El Niño event. The higher catch probabilities in the La Niña event of 2020 were near the coast, in contrast to the previous La Niña events of 2007 and 2013, due to the restriction of the optimal habitat of E. ringens in response to changes in oceanographic conditions. The application of the results of this study will allow understanding and probably anticipating the consequences that extreme ENSO events could have on the catch probability of the industrial anchovy purse seine fleet in northern Chile.

Improved prediction of extreme ENSO events using an artificial neural network with weighted loss functions

The El Niño–Southern Oscillation (ENSO) causes a wide array of abnormal climates and extreme events, including severe droughts and floods, which have a major impact on humanity. With the development of artificial neural network techniques, various attempts are being made to predict ENSO more accurately. However, there are still limitations in accurately predicting ENSO beyond 6 months, especially for abnormal years with less frequent but greater impact, such as strong El Niño or La Niña, mainly due to insufficient and imbalanced training data. Here, we propose a new weighted loss function to improve ENSO prediction for abnormal years, in which the original (vanilla) loss function is multiplied by the weight function that relatively reduces the weight of high-frequency normal events. The new method applied to recurrent neural networks shows significant improvement in ENSO predictions for all lead times from 1 month to 12 months compared to using the vanilla loss function; in particular, the longer the prediction lead time, the greater the prediction improvement. This method can be applied to a variety of other extreme weather and climate events of low frequency but high impact.

Biomass Burning Emissions of Black Carbon over the Maritime Continent and ENSO Variability

Abstract Fire emissions from the Maritime Continent (MC) over the western tropical Pacific are strongly influenced by El Niño–Southern Oscillation (ENSO), posing various climate effects to the Earth system. In this study, we show that the historical biomass burning emissions of black carbon (BCbb) aerosol in the dry season from the MC are strengthened in El Niño years due to the dry conditions. The eastern Pacific type of El Niño exerts a stronger modulation in BCbb emissions over the MC region than the central Pacific type of El Niño. Based on simulations using the fully coupled Community Earth System Model (CESM), the impacts of increased BCbb emissions on ENSO variability and frequency are also investigated in this study. With BCbb emissions from the MC scaled up by a factor of 10, which enables the identification of climate response from the internal variability, the increased BCbb heats the local atmosphere and changes land–sea thermal contrast, which suppresses the westward transport of the eastern Pacific surface water. It leads to an increase in sea surface temperature in the eastern tropical Pacific, which further enhances ENSO variability and increases the frequency of extreme El Niño and La Niña events. This study highlights the potential role of BCbb emissions on extreme ENSO frequency, and this role may be increasingly important in the warming future with higher wildfire risks.

The impact of global warming on ENSO from the perspective of objective signals

Most studies on the relationship between global warming and El Niño-Southern Oscillation (ENSO) rely on simulation experiments, but they have produced contradictory results, which cannot guarantee the reliability of the experimental findings. To address this challenge, we approached the issue from the perspective of objective ENSO and global warming signals. The effects of global warming on ENSO are not limited to the Earth's surface, but also present in the atmosphere. While objective monitoring indices exist for surface global warming and ENSO signals, objective ENSO and global warming signals in the atmosphere are difficult to obtain. To obtain high-precision ENSO and global warming signals in the atmosphere, we propose using the strategy of ICA (Independent Component Analysis) combined with a non-parametric method. The results of the objective ENSO and global warming signals suggest that the global warming signal leads the ENSO signal by approximately three months and exhibits a clear positive correlation with the ENSO signal, especially the occurrence of strong ENSO events is closely related to global warming, indicating that global warming promotes the occurrence of ENSO events. Under the influence of global warming, the frequency and intensity of ENSO increase, the characteristics and complexity of ENSO atmospheric teleconnections may be altered, and there is a greater tendency for more destructive El Niño events to occur. Since the beginning of the 21st century, the probability of ENSO event has increased significantly. Furthermore, moderate or strong ENSO events tend to develop earlier, and extreme ENSO events not only develop earlier but also prolong their decay phase, leading to an extended lifespan of ENSO events. This paper investigates the effect of global warming on ENSO from the perspectives of objective ENSO and global warming signals, which well supplements the objective factual basis for the previous simulation experimental studies.

Effects of extreme phases of El Niño–Southern Oscillation on rainfall extremes in Alagoas, Brazil

AbstractThe Northeast of Brazil (NEB) is influenced by the phases of El Niño–Southern Oscillation (ENSO), which are associated with increased or decreased rainfall in the East NEB (ENEB). The study evaluated the effects of extreme ENSO phases on rainfall extremes in ENEB. Rainfall data from 54 stations in Alagoas were obtained from the National Water and Basic Sanitation Agency (ANA) and subjected to statistical analysis, with a data imputation method used to fill in gaps in the time series. The Inverse Distance Weighting (IDW) method was consistent and suitable for spatially representing rainfall data in the state of Alagoas, according to the adopted statistical indicators. Extreme, decadal and anomaly maps were interpolated using IDW method in Quantum GIS (QGIS), due to the positioning of the stations. The criteria for analysing extreme ENSO years were based on the Oceanic Niño Index (ONI) for region 3.4, between 1960 and 2016. The results show high interannual variability due to ENSO phases in the climatic mesoregions of Alagoas. In over 70% of extreme ENSO years, rainfall was below average (during strong and very strong El Niño) or above average (during strong La Niña). Some cities in the mesoregions of Alagoas experienced higher rainfall than others, even in extreme ENSO situations, suggesting the influence of physiography and multiscale meteorological systems. On a decadal scale, the East region recorded the highest rainfall accumulations, primarily due to decadal variability of two rainfall cores, corresponding to the Metropolitan Region of Maceió (MRM) and the northern part of the state. An exception is the Upper São Francisco region, which experiences dry decades. The East mesoregion (coast) had higher rainfall records compared to the more continental mesoregions (Hinterland and Arid), regardless of ENSO phases and interannual and decadal scales.

El Niño–Southern Oscillation (ENSO)-driven hypersedimentation in the Poechos Reservoir, northern Peru

Abstract. Although extreme El Niño events (EENEs) have always impacted hydrological anomalies and sediment transport in South America, their intensification by global warming and their association with changes in human activities and land cover after humid periods may lead to the acceleration of sediment transfers in river systems and dam reservoirs. This situation may threaten soil and water resources in arid and semiarid regions highly dependent on water originating from large dams. In this study, we investigated the sediment sequence accumulated in the Poechos Reservoir (northern Peru) and provided a retrospective reconstruction of the interactions of El Niño–Southern Oscillation (ENSO), agricultural practices and vegetation cover changes with sediment dynamics (1978–2019). To this end, a sediment core was dated and characterized by physical and chemical analyses (e.g., scanner tomography, X-ray fluorescence, particle size analysis) to estimate the evolution of sedimentation rates and changes in sediment sources during the last 5 decades. Sediment tracing results indicated the occurrence of changes in sediment sources associated with positive and negative phases of the Eastern Pacific index with a greater contribution of the lowland dry-forest area in comparison to that of the Andean area to sediment during the El Niño events (mean contribution of 76 %; up to 90 % during the coastal El Niño events (CENEs) of 2016–2017). This source contribution was mostly controlled by the stationary rainfall occurring during the EENEs in the lowland dry-forest area characterized by a low vegetation cover. Overall, after an extreme phase of ENSO, like after the EENE 1982–1983, the normal discharges and persistent sediment supplies from the middle- and upper-catchment parts led to river aggradation and the storage of substantial amounts of sediment in alluvial plains. In the absence of a significant EENE between 1983 and 1997, the large volume of sediment stored in the alluvial plains was exported by the EENE 1997–1998 resulting in an increase in sedimentation rate of 140 % after 1997 with a significant aggradation of the deltaic zone of the reservoir. In addition to the impact of extreme climate events on sediment dynamics, the development of agriculture along the riverine system after an extreme phase of ENSO increased the availability of sediments in the main channel of the rivers, easily transported by the next EENE. This study suggests that intensification of human activities associated with a higher frequency of extreme rainfall events amplified the quantity of sediment transported by the river system, which will significantly decrease the lifespan of the reservoir, which is essential to meeting the freshwater demands of the farmers and the populations living in this arid and semiarid region.

Extreme events in the multi-proxy South Pacific drought atlas

Droughts are a natural occurrence in many small Pacific Islands and can have severe impacts on local populations and environments. The El Niño-Southern Oscillation (ENSO) is a well-known driver of drought in the South Pacific, but our understanding of extreme ENSO events and their influence on island hydroclimate is limited by the short instrumental record and the infrequency of ENSO extremes. To address this gap, we developed the South Pacific Drought Atlas (SPaDA), a multi-proxy, spatially resolved reconstruction of the November–April Standardised Precipitation Evapotranspiration Index for the southwest Pacific islands. The reconstruction covers the period from 1640 to 1998 CE and is based on nested principal components regression. It replicates historical droughts linked to ENSO events with global influence, compares well to previously published ENSO reconstructions, and is independently verified against fossil coral records from the Pacific. To identify anomalous hydroclimatic states in the SPaDA that may indicate the occurrence of an extreme event, we used an Isolation Forest, an unsupervised machine learning algorithm. Extreme El Niño events characterised by very strong southwest Pacific drought anomalies and a zonal SPCZ orientation are shown to have occurred throughout the reconstruction interval, providing a valuable baseline to compare to climate model projections. By identifying the spatial patterns of drought resulting from extreme events, we can better understand the impacts these events may have on individual Pacific Islands in the future.

ENSO phase space dynamics with an improved estimate of the thermocline depth

The recharge oscillator model of the El Niño Southern Oscillation (ENSO) describes the ENSO dynamics as an interaction between the eastern tropical Pacific sea surface temperatures (T) and subsurface heat content (thermocline depth; h), defining a dynamical cycle with different phases. h is often approximated on the basis of the depth of the 20 °C isotherm (Z20). In this study we will address how the estimation of h affects the representation of ENSO dynamics. We will compare the ENSO phase space with h estimated based on Z20 and based on the maximum gradient in the temperature profile (Zmxg). The results illustrate that the ENSO phase space is much closer to the idealised recharge oscillator model if based on Zmxg than if based on Z20. Using linear and non-linear recharge oscillator models fitted to the observed data illustrates that the Z20 estimate leads to artificial phase dependent structures in the ENSO phase space, which result from an in-phase correlation between h and T. Based on the Zmxg estimate the ENSO phase space diagram show very clear non-linear aspects in growth rates and phase speeds. Based on this estimate we can describe the ENSO cycle dynamics as a non-linear cycle that grows during the recharge and El Nino state, and decays during the La Nina states. The most extreme ENSO states are during the El Nino and discharge states, while the La Nina and recharge states do not have extreme states. It further has faster phase speeds after the El Nino state and slower phase speeds during and after the La Nina states. The analysis suggests that the ENSO phase speed is significantly positive in all phases, suggesting that ENSO is indeed a cycle. However, the phase speeds are closest to zero during and after the La Nina state, indicating that the ENSO cycle is most likely to stall in these states.

The teleconnection of extreme El Niño–Southern Oscillation (ENSO) events to the tropical North Atlantic in coupled climate models

Abstract. El Niño–Southern Oscillation (ENSO) is a major source for teleconnections, including towards the tropical North Atlantic (TNA) region, whereby TNA sea surface temperatures (SSTs) are positively correlated with ENSO in boreal spring following an ENSO event. However, the Pacific–Atlantic connection can be impacted by different ENSO characteristics, such as the amplitude, location, and timing of Pacific SST anomalies (SSTAs). Indeed, the TNA SSTAs may respond nonlinearly to strong and extreme El Niño events. However, observational data for the number of extreme ENSO events remain limited, restricting our ability to investigate the influence of observed extreme ENSO events. To overcome this issue and to further evaluate the nonlinearity of the TNA SSTA response, two coupled climate models are used, namely the Community Earth System Model version 1 – Whole Atmosphere Community Climate Model (CESM-WACCM) and the Flexible Ocean and Climate Infrastructure version 1 (FOCI). In both models the TNA SSTAs respond linearly to ENSO during extreme El Niño events but nonlinearly to extreme La Niña events for CESM-WACCM. We investigate differences by using indices for all major mechanisms that connect ENSO to the TNA and compare them with reanalysis. CESM-WACCM and FOCI overall represent the teleconnection well, including that the tropical and extratropical pathways are similar to observations. Our results also show that a large portion of the nonlinearity during La Niña is explained by the interaction between Pacific SSTAs and the overlying upper-level divergence.

Interactive effects of the El Niño-Southern Oscillation and Indian Ocean Dipole on the tropical net ecosystem productivity

El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) can exert abiotic stresses on biota to influence regional terrestrial carbon cycling. Here, we investigated their interactive effects on tropical net ecosystem productivity (NEP) when ENSO and IOD simultaneously occur (mainly El Niño & positive IOD [pIOD] and La Niña & negative IOD [nIOD]), based on TRENDYv9 multi-model simulations. Results suggest that NEP anomalies were dominated by IOD over South America near 20°S and Africa south of the Equator, but by ENSO over India and northern South America, and controlled by their amplifying effects over eastern Africa, the Indo-China peninsula, and most of Australia during September-October-November (SON). In the following December-January-February (DJF), IOD legacy effects generally enhanced ENSO-induced NEP anomalies over most of South America, eastern and southern Africa, and Australia. During March-April-May (MAM), the influence of IOD gradually disappeared. Our analysis revealed the dominant role of gross primary productivity (GPP) in these NEP anomalies. We further found asymmetric effects of soil moisture and temperature on NEP anomalies, showing higher correlation coefficients with soil moisture in El Niño & pIOD, but basically with temperature in La Niña & nIOD. Additionally, considering the simultaneous extreme of pIOD and El Niño activity in 1997/98, we calculated their seasonal individual contributions to NEP anomalies. We found that the pIOD event had the greatest influence in SON. During SON in 1997, individual contributions of pIOD and El Niño to NEP caused a land carbon source of −0.34 ± 0.15 and −0.35 ± 0.32 PgC yr−1 over South America, a carbon sink and source of 0.5 ± 0.19 and −0.54 ± 0.14 PgC yr−1 over Africa, and source of −0.08 ± 0.25 and −0.42 ± 0.37 PgC yr−1 over Asia-Pacific, respectively. Understanding interactive effects of IOD and ENSO on regional carbon cycling is crucial due to the more frequent extreme IOD and ENSO events under future climate warming.

Seasonal variability of satellite-derived primary production in the South China Sea from an absorption-based model

Seasonal patterns of marine net primary production (NPP) are crucial for understanding the marine ecosystem and biogeochemical cycles. Uncoupling of seasonal variations between NPP and phytoplankton chlorophyll-a over different areas has attracted much attention. In this study, following a review of previous studies, monthly climatological NPP data from 2003 to 2020, estimated using the Size-fractioned Phytoplankton Pigment Absorption (aph)-based NPP Model (SABPM), were selected to study the seasonal variability of NPP in the South China Sea (SCS). Results showed the spatial differences of NPP seasonality and its departures from climatology in extreme El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) years. Cluster analysis for climatological monthly data identified significant differences of NPP seasonality in five typical regions. In coastal regions along the northern SCS and off eastern Vietnam, NPP exhibited the most obvious seasonal cycle with maximum (minimum) values in summer (winter), attributable mainly to river discharge and summer upwelling. In regions off northwestern Luzon and coast of southern SCS, NPP showed peaks in winter, which were related to strong mixing and upwelling. In northwestern SCS, NPP was high during May–September in phase with sea surface temperature and the primary controlling factors were found to be shallow nutricline depth and wind-driven mixing. Owing to the deep nutricline depth in the central basin, NPP exhibited little seasonal variability; only a weak signal was observed in spring in phase with photosynthetically active radiation. Local dynamics on regulating the nutrient supply and light availability contribute to these regional differences in NPP seasonality, which could also be affected by extreme climate events. The largest anomalies of the NPP seasonal cycle coincide with 2015/2016 ENSO and super IOD in 2020. During these events, enhanced (weakened) westerly winds caused fall (rise) of SLA and increase (decrease) of NPP in coastal regions along the northern SCS and that off eastern Vietnam. Overall, theaph-based model shows a new perspective to study the spatiotemporal variations of NPP in the SCS.

Deep learning for skillful long-lead ENSO forecasts

El Niño-Southern Oscillation (ENSO) is one of the fundamental drivers of the Earth's climate variability. Thus, its skillful prediction at least a few months to years ahead is of utmost importance to society. Using both dynamical and statistical methods, several studies reported skillful ENSO predictions at various lead times. Predictions with long lead times, on the other hand, remain difficult. In this study, we propose a convolutional neural network (CNN)-based statistical ENSO prediction system with heterogeneous CNN parameters for each season with a modified loss function to predict ENSO at least 18–24 months ahead. The developed prediction system indicates that the CNN model is highly skillful in predicting ENSO at long lead times of 18–24 months with high skills in predicting extreme ENSO events compared with the Scale Interaction Experiment-Frontier ver. 2 (SINTEX-F2) dynamical system and several other statistical prediction systems. The analysis indicates that the CNN model can overcome the spring barrier, a major hindrance to dynamical prediction systems, in predicting ENSO at long lead times. The improvement in the prediction skill can partly be attributed to the heterogeneous parameters of seasonal CNN models used in this study and also to the use of a modified loss function in the CNN model. In this study, we also attempted to identify various precursors to ENSO events using CNN heatmap analysis.

The El Niño Southern Oscillation drives multidirectional inter-reef larval connectivity in the Great Barrier Reef.

The El Niño Southern Oscillation (ENSO) is the strongest source of interannual global climate variability, and extreme ENSO events are projected to increase in frequency under climate change. Interannual variability in the Coral Sea circulation has been associated with ENSO, although uncertainty remains regarding ENSO's influence on hydrodynamics and larval dispersal in the adjacent Great Barrier Reef (GBR). We investigated larval connectivity during ENSO events from 2010 to 2017 throughout the GBR, based on biophysical modelling of a widespread predatory reef fish, Lutjanus carponotatus. Our results indicate a well-connected system over the study period with high interannual variability in inter-reef connectivity associated with ENSO. Larval connectivity patterns were highly correlated to variations in the Southern Oscillation Index (SOI). During El Niño conditions and periods of weak SOI, larval dispersal patterns were predominantly poleward in the central and southern regions, reversing to a predominant equatorward flow during very strong SOI and extreme La Niña conditions. These ENSO-linked connectivity patterns were associated with positive connectivity anomalies among reefs. Our findings identify ENSO as an important source of variation in larval dispersal and connectivity patterns in the GBR, which can influence the stability of population dynamics and patterns of biodiversity in the region.

Marine heatwaves and cold-spells in global coral reef zones

Persistent ocean temperature extremes, known as marine heatwaves (MHWs) and marine cold-spells (MCSs), can be devastating for warm-water coral reefs. However, the difference between MHWs and MCSs in the mean and trend across global coral reef zones in the present and future climates remains unclear. In this study, we comparatively assessed these changes using satellite sea surface temperatures during 1982–2021 and the Coupled Model Intercomparison Project Phase 6 climate model projections during 2022–2070. We found distinct differences in the mean and trend between MHW and MCS metrics across global coral reef zones, with a rapid increase in the total days and average duration of MHWs, whereas the MCSs exhibited an opposite trend. Moreover, the increasing trend in the average duration of MHWs and decreasing trend in MCS frequency both induced a nearly permanent MHW state in future projections. Upper-ocean warming was the main driver of the increase in MHWs and the decrease in MCSs. Under greenhouse warming, the area ratio between the MHW and MCS would rapidly increase from 1982 to 2070, reaching nearly 28 times under the Shared Socio-economic Pathway (SSP) 245 and 109 times under SSP585 by the year 2070. As El Niño-Southern Oscillation (ENSO) events are critical for the occurrence of MHWs and coral bleaching in tropical oceans, our results emphasize the necessity for understanding the projected changes in extreme ENSO events.

Contributions of oceanic and continental AAM to interannual variation in ΔLOD with the detection of 2020–2021 La Nina event

As a strong climate element on interannual scales, the El Nino-Southern Oscillation (ENSO) is a major component of global weather and climate change, and it is also closely related to the interannual atmospheric angular momentum (AAM) and length-of-day changes (ΔLOD). Here, we reprocess and compare the interannual variations of AAM, ΔLOD with ENSO indices, with AAM mass and motion terms calculated over land separately from those over the ocean. Three oscillatory components (at ~ 6, ~ 7, ~ 8 years), due to angular momentum changes in Earth's interior, are removed to obtain the interannual ΔLOD solely related to climatic variations. Our results show that the AAM motion term over the ocean contributes the most to interannual ΔLOD, and that the oceanic AAM has larger variability than that over land, especially during the periods of strong ENSO events. After subtracting contributions associated with interior processes, the interannual ΔLOD anomalies corresponding to extreme ENSO events (1982–1983 ~ 0.43, 1997–1998 ~ 0.36, 2015–2016 ~ 0.42 ms) are about half as strong as those found in previous studies (~ 0.91, ~ 0.76, ~ 0.81 ms). Furthermore, we detect an intermediate La Nina event that occurred from August 2020 to May 2021, forcing the interannual ΔLOD to a minimum value of approximately -0.21 ms.

Coral perspective on temperature seasonality and interannual variability in the northern South China Sea during the Roman Warm Period

Few reconstructions of sea-surface temperature (SST) have focused on seasonal and interannual variability, two major components of the global climate system, due to the limited temporal resolution of proxies. This study presents a combined 228-year-long, monthly resolved strontium to calcium ratios (Sr/Ca) record covering the period of 2070–1740 a BP (years before 1950 CE (Common Era)) extracted from three U-series-based sub-fossil Porites corals located on the Xisha Islands, northern South China Sea (SCS). The composite time series allowed for accurate assessment of the natural range of SST variations during snapshots of the Roman Warm Period (RWP). Reconstructed SST revealed that the RWP was characterized by cooler conditions compared with the 20th century, consistent with climatic variations in the western Pacific and East Asia. The amplitude of SST seasonality was within the modern range, except for a lower value at 1980–1928 a BP. Interannual variability associated with El Niño–Southern Oscillation (ENSO) activity was enhanced by 39% relative to 1980–2014 CE. The results of the sliding window demonstrate that ENSO variability persistently strengthened during 2070–2010 a BP, followed by an overall fluctuating attenuation during 1980–1928 a BP. Then, the trends of rising first before descending twice during 1852–1800 a BP appeared. Furthermore, ENSO activity played a leading role in steering short-term changes in SST seasonality in the northern SCS, manifested as stronger ENSO activity with more frequent El Niño events and decreased SST seasonality. Considering that the frequency of extreme ENSO events may strengthen in the future under global warming, the climate in the northern SCS might become more variable and complex.

Sources of Subseasonal Skill and Predictability in Wintertime California Precipitation Forecasts

AbstractThe relation between the El Niño–Southern Oscillation (ENSO) and California precipitation has been studied extensively and plays a prominent role in seasonal forecasting. However, a wide range of precipitation outcomes on seasonal time scales are possible, even during extreme ENSO states. Here, we investigate prediction skill and its origins on subseasonal time scales. Model predictions of California precipitation are examined using Subseasonal Experiment (SubX) reforecasts for the period 1999–2016, focusing on those from the Flow-Following Icosahedral Model (FIM). Two potential sources of subseasonal predictability are examined: the tropical Pacific Ocean and upper-level zonal winds near California. In both observations and forecasts, the Niño-3.4 index exhibits a weak and insignificant relationship with daily to monthly averages of California precipitation. Likewise, model tropical sea surface temperature and outgoing longwave radiation show only minimal relations with California precipitation forecasts, providing no evidence that flavors of El Niño or tropical modes substantially contribute to the success or failure of subseasonal forecasts. On the other hand, an index for upper-level zonal winds is strongly correlated with precipitation in observations and forecasts, across averaging windows and lead times. The wind index is related to ENSO, but the correlation between the wind index and precipitation remains even after accounting for ENSO phase. Intriguingly, the Niño-3.4 index and California precipitation show a slight but robust negative statistical relation after accounting for the wind index.

The influence of groundwater abstraction on interpreting climate controls and extreme recharge events from well hydrographs in semi-arid South Africa

There is a scarcity of long-term groundwater hydrographs from sub-Saharan Africa to investigate groundwater sustainability, processes and controls. This paper presents an analysis of 21 hydrographs from semi-arid South Africa. Hydrographs from 1980 to 2000 were converted to standardised groundwater level indices and rationalised into four types (C1–C4) using hierarchical cluster analysis. Mean hydrographs for each type were cross-correlated with standardised precipitation and streamflow indices. Relationships with the El Niño–Southern Oscillation (ENSO) were also investigated. The four hydrograph types show a transition of autocorrelation over increasing timescales and increasingly subdued responses to rainfall. Type C1 strongly relates to rainfall, responding in most years, whereas C4 notably responds to only a single extreme event in 2000 and has limited relationship with rainfall. Types C2, C3 and C4 have stronger statistical relationships with standardised streamflow than standardised rainfall. C3 and C4 changes are significantly (p < 0.05) correlated to the mean wet season ENSO anomaly, indicating a tendency for substantial or minimal recharge to occur during extreme negative and positive ENSO years, respectively. The range of different hydrograph types, sometimes within only a few kilometres of each other, appears to be a result of abstraction interference and cannot be confidently attributed to variations in climate or hydrogeological setting. It is possible that high groundwater abstraction near C3/C4 sites masks frequent small-scale recharge events observed at C1/C2 sites, resulting in extreme events associated with negative ENSO years being more visible in the time series.