Southern Oscillation Research Articles

Climate pattern effects on global economic conditions

This study investigates how El Niño–Southern Oscillation (ENSO) climate patterns affect global economic conditions. Prior research suggests that ENSO phases, particularly El Niño, influence economic outcomes, but with limited consensus on their broader macroeconomic impacts. Using a novel monthly dataset from 20 economies, covering 80% of global output from 1999 to 2022, we employ a global augmented vector autoregression with local projections (GAVARLP) model. The empirical findings suggest that El Niño boosts output with minimal inflationary effects, reducing global economic policy uncertainty, while La Niña raises food inflation, which can amplify aggregate inflation as a “second-round” effect, amplifying uncertainty. These findings shed light on the transmission channels of climate shocks and highlight the significant role of ENSO in shaping global economic conditions, emphasizing why climate shocks should be a concern for policy markers.

Assessment of Bleaching Stress Vulnerability of Lakshadweep Islands using Google Earth Engine (GEE)

Coral reefs, among the Earth’s most diverse and valuable ecosystems, face unprecedented challenges due to climate change. Coral bleaching is a phenomenon wherein corals lose their symbiotic zooxanthellae owing to various stressors, leading to a whitening effect of the coral tissues. In recent decades, climate change has intensified coral bleaching events. Multiple stressors, including elevated Sea Surface Temperature (SST), extreme irradiance levels, and various biotic and abiotic factors trigger bleaching events. Coral bleaching is primarily driven by thermal stress caused by elevated SSTs. Climate change has worsened bleaching’s frequency and intensity. Global bleaching events are often linked to planetary ocean-atmospheric circulation processes such as El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). This study focused on assessing the vulnerability of coral reefs in the Lakshadweep region of India from 2016 to 2023 using National Oceanic and Atmospheric Administration’s Climate Data Record Optimum Interpolation Sea Surface Temperature (NOAA CDR OISST) daily data. GOOGLE EARTH ENGINE (GEE) is a cloud computing platform which is used to collect and generate the base data for this study. The vulnerability assessment utilized two bleaching indices: SST anomaly and Degree Heating Week (DHW). Analysis of DHW data reveals that 2020 experienced the highest SST anomaly residence time due to IOD event of 2019, as compared to 2016 and 2023 which are known El Niño years. All Lakshadweep islands exhibited vulnerability, although in varying degrees across different areas. Based on the magnitude, intensity, and frequency of bleaching stress, the islands are categorized into different categories of vulnerability. This study identifies Baliyapaniyam, Cheriyam-Kalpeni and Suhelipar reefs as very highly vulnerable reefs in Lakshadweep. This study highlights the urgent need for monitoring and management measures to mitigate the impacts of climate change on coral reef ecosystems using spatial vulnerability patterns.

Exploring climate stabilisation at different global warming levels in ACCESS-ESM-1.5

Abstract. Under the Paris Agreement, signatory nations aim to keep global warming well below 2 °C above pre-industrial levels and preferably below 1.5 °C. This implicitly requires achieving net-zero or net-negative greenhouse gas emissions to ensure long-term global temperature stabilisation or reduction. Despite this requirement, there have been few analyses of stabilised climates, and there is a lack of model experiments to address our need for understanding the implications of the Paris Agreement. Here, we describe a new set of experiments using the Australian Community Climate and Earth System Simulator Earth system model (ACCESS-ESM-1.5) that enables the analysis of climate evolution under net-zero emissions, and we present initial results. Seven 1000-year-long simulations were run with global temperatures stabilising at levels in line with the Paris Agreement and at a range of higher global warming levels (GWLs). We provide an overview of the experimental design and use these simulations to demonstrate the consequences of delayed attainment of global net-zero carbon dioxide emissions. We show that there are substantial differences between transient and stabilising climate states and differences in stabilisation between GWLs. As the climate stabilises under net-zero emissions, we identify significant and robust changes in temperature and precipitation patterns including continued Southern Ocean warming and changes in regional precipitation trends. Changes under net-zero emissions differ greatly between regions, including contrasting trajectories of sea ice extent between the Arctic and Antarctic. We also examine the El Niño–Southern Oscillation (ENSO) and find evidence of reduced amplitude and frequency of ENSO events under climate stabilisation relative to projections under transient warming. An analysis at specific GWLs shows that significant regional changes continue for centuries after emission cessation and that these changes are stronger at higher GWLs. Our findings suggest substantial long-term climate changes are possible even under net-zero emission pathways. These simulations are available for use in the community and will hopefully motivate further experiments and analyses based on other Earth system models.

Impact of ENSO on Cloud Distribution and Rainfall Variability in Tangerang Regency

A type of climate variation in the Pacific Ocean known as El Niño Southern Oscillation (ENSO) is defined by an increase in sea surface temperature (SST) in the Central and Eastern equatorial areas, which affects the amount of rainfall that falls and increases. In Indonesia, the rainy season typically persists from October to March, whereas the dry season persists from April to September. Research on the influence of ENSO on rainfall has been carried out in several areas, but has not been carried out in the Tangerang area. This study aims to ascertain how the ENSO phenomena affect rainfall fluctuations and cloud distribution in the Regency of Tangerang. The secondary data, which includes information on rainfall, cloud cover, wind direction, and speed, was acquired from BMKG Meteorology Budiarto. In addition, data from the Australian Bureau of Meteorology (BOM) website's Southern Oscillation Index (SOI) was used. Surface weather analysis and Pearson correlation analysis are the data analysis techniques used. The results presented that based on surface weather study, ENSO events had a consequence on cloud distribution in Tangerang Regency. The clouds lead when the ENSO phenomenon occurs, namely Cumulus and Nimbostratus clouds with a 4-8 octa cloud cover. Meanwhile, the correlation test results show that ENSO influences seasonal and annual rainfall variations in the district of Tangerang. The largest correlation between SOI and annual rainfall occurred in 2015 with a correlation value of r-0.84 (very strong). Meanwhile, the greatest correlation between SOI and seasonal rainfall occurred in July-September with a correlation value of r=0.67 (strong).

Temporal-spatial characteristics of climate drought and its effects on grain yield in Hunan Province, China

The examination of the spatiotemporal characteristics and developmental trends of drought is crucial for enhancing water resource management, bolstering drought resistance, and improving disaster prevention capabilities. This study employs the Standardized Precipitation Evapotranspiration Index (SPEI) and grain yield data across various time scales, in conjunction with methodologies such as Run Theory, Mann-Kendall, and Standardized Yield Residual Series, to conduct an in-depth investigation into the spatiotemporal variation characteristics of meteorological drought in Hunan Province and its impact on grain yield. The findings suggest that: (1) Since 1960, the likelihood of seasonal drought occurrence in Hunan Province has been ranked as autumn > winter > spring > summer, with mild drought occurring most frequently, followed by moderate drought, while the frequency of severe and extreme drought remains low. (2) Meteorological drought in Hunan Province exhibits spatial differences at the seasonal scale, with the overall drought changes in spring and summer displaying a non-significant upward trend; the western and southern regions exhibit a trend of aridification in autumn; and in winter, the Zhangjiajie and Xiangxi regions show an insignificant downward trend. (3) From 1960 to 2022, grain production in Hunan Province has demonstrated a pattern of fluctuation and increase. The meteorological yield of grain crops displays a high-low-high spatial distribution from south to north. Concurrently, there is a positive correlation between short-term climate change and meteorological output, while long-term climate change is not evident. (4) El Niño Southern Oscillation (ENSO) is a significant circulation factor affecting meteorological drought in Hunan Province, and the meteorological drought in autumn and winter in Hunan Province is significantly influenced by ENSO. The research findings can provide reference significance and a scientific basis for drought research and comprehensive management in Hunan Province, and offer data and theoretical support for promoting economic development.

ANÁLISE ESPACIAL E TEMPORAL DE EVENTOS DE SECAS NA REGIÃO HIDROGRÁFICA ALTO RIO PARANÁ DE 1990 A 2020

The Paraná River Hydrographic Region is of great socioeconomic relevance for Brazil. Therefore, due to the history of droughts in the region, the aims of the current study were to assess rainfall spatial and temporal variability, as well as to analyze drought features based on using the Normalized Percentage Index (NPI) to contribute to water management processes in Upper Paraná River (UPR). The study area encompasses 14 Planning and Management Units, distributed in Goiás, Mato Grosso do Sul, Minas Gerais and São Paulo states. Climate data were obtained from the National Hydrometeorological Network database. A geostatistical analysis of rainfall was carried out, based on the annual series of 408 stations, and subsequently the calculation of NPI for classifying the droughts severity. All periods analyzed (1990-2020) showed spatial dependence (moderate to high), allowing the elaboration of droughts maps. The dry and rainy periods and areas did not indicate direct influence of El Niño-Southern Oscillation (ENSO). Mato Grosso do Sul and São Paulo units were the main contributors to the identified droughts. The data showed that 2010-2020 was the driest decade of the period, with a greater contribution from the 2019/2020 period, where droughts exceeded 60% of the area for two consecutive years, an event never identified in the last 3 decades. The NPI curves referring to “initial drought” and “mild” allowed verifying years of water crisis when their summed percentages reached at least 50% of the region. The methodology used is versatile, allowing its use in any watershed. Keywords: Rains. Water management. NPI. Kriging.

Dynamics of Sandy Shorelines and Their Response to Wave Climate Change in the East of Hainan Island, China

Beach erosion and shoreline dynamics are strongly affected by alterations in nearshore wave intensity and energy, especially in the context of global climate change. However, existing works do not thoroughly study the evolution of the sandy coasts of eastern Hainan Island, China, nor their responses to wave climate change driven by climate variability. This study focuses on the open sandy coast and assesses shoreline evolutionary dynamics in response to wave climate variability over a 30-year period from 1994 to 2023, using an open-source software toolkit that semi-automatically identify the shorelines (CoastSat v2.4) and reanalysis wave datasets (ERA5). The shorelines of the study area were extracted from CoastSat, and then tidal correction and outlier correction were performed for clearer shorelines. Combining the shoreline changes and wave conditions derived from ERA5, the dynamics of the shorelines and their response to wave climate change were further studied. The findings reveal that the average long-term shoreline change rate along the eastern coast of Hainan Island is 0.03 m/year, with 44.8% of transects experiencing erosion and 55.2% showing long-term accretion. And distinct evolutionary patterns emerge across different sections. Interannual variability is marked by alternating erosion and siltation cycles, while most sections of the coast experiences clear seasonal fluctuations, with accretion typically occurring during summer and erosion occurring in winter. El Niño–Southern Oscillation (ENSO) cycles drive changes in parameters including significant wave height, mean wave period, wave energy flux, and mean wave direction, leading to long-term changes in wave climate. The multi-scale behavior of the sandy shoreline responds distinctly to the ongoing changes in wave climate triggered by ENSO viability, with El Niño events typically resulting in accretion and La Niña periods causing erosion. Notably, mean wave direction is the metric most closely linked to changes in the shoreline among all the others. In conclusion, the interplay of escalating anthropogenic activities, natural processes, and climate change contributes to the long-term evolution of sandy shorelines. We believe this study can offer a scientific reference for erosion prevention and management strategies of sandy beaches, based on the analysis presented above.

Trend and teleconnection analysis of temperature extremes in New South Wales, Australia

AbstractThis study investigates possible trends and teleconnections in temperature extremes in New South Wales (NSW), Australia. Daily maximum and minimum temperature data covering the period 1971–2021 at 26 stations located in NSW were used. Three indices, which focus on daily maximum temperature, daily minimum temperature, and average daily temperature in terms of Excessive Heat Factor (EHF) were investigated to identify the occurrence of heatwaves (HWs). The study considered HWs of different durations (1-, 5-, and 10-days) in relation to intensity, frequency, duration, and their first occurrence parameters. Finally, the influences of three global climate drivers, namely – the El Niño/Southern Oscillation (ENSO), the Southern Annular Mode (SAM), and the Indian Ocean Dipole (IOD) were investigated with associated heatwave attributes for extended Austral summers. In this study, an increasing trend in both hot days and nights was observed for most of the selected stations within the study area. The increase was more pronounced for the last decade (2011–2021) of the investigated time period. The number, duration and frequency of the heatwaves increased over time considering the EHF criterion, whereas no particular trend was detected in cases of TX90 and TN90. It was also evident that the first occurrence of all the HWs shifted towards the onset of the extended summer while considering the EHF criterion of HWs. The correlations between heatwave attributes and climate drivers depicted that heatwave over NSW was positively influenced by both the IOD and ENSO and negatively correlated with SAM. The findings of this study will be useful in formulating strategies for managing the impacts of extreme temperature events such as bushfires, floods, droughts to the most at-risk regions within NSW.

Pengaruh Curah Hujan terhadap Tinggi Muka Air Tanah Gambut Saat Fenomena El Nino di Sub Kesatuan Hidrologis Gambut Sungai Mendahara-Sungai Lagan

This research aims to analyze the effect of rainfall on the peat groundwater level (GWL) in the Mendahara River-Lagan River Peat Hydrological Sub Unit (sub KHG) during the El Nino phenomenon. The analysis was carried out using a simple linear regression method on 3 dominant land covers, namely private oil palm plantations, community oil palm plantations and secondary swamp forests, where 2023 is an El Nino year. The results of the research show that in the year private oil palm plantation land cover had the strongest influence on the amount of rainfall distribution compared to community oil palm plantation land cover and secondary swamp forest with R2 values of 76.14%, 58.03% and 51,42%. The value of the coefficient of determination (R2) means that the dynamics of TMAT fluctuations can be explained by the amount of rainfall distribution, while the rest is influenced by other variables not studied.

Global Marine Heatwaves Under Different Flavors of ENSO

AbstractMarine heatwaves (MHWs) have caused devasting ecological and socioeconomic impacts worldwide. Understanding the connection of regional events to large‐scale climatic drivers is key for enhancing predictability and mitigating MHW impacts. Despite the reported connection between MHWs globally and El Niño–Southern Oscillation (ENSO), establishing statistically significant links between different types of ENSO events and MHWs remains challenging due to the limited duration of observational data. Here, we use 10,000 years of simulations from a Linear Inverse Model (LIM) to address this issue. Our findings reveal distinct connections between MHWs and ENSO, with diverging influences from different flavors of El Niño and La Niña events. In addition, under long‐lasting El Niño conditions, the likelihood of MHWs increases by up to 12‐fold in the Indian and Pacific Oceans. This study highlights the global connections between ENSO diversity and variations in MHW events.

Boolean Delay Equations: a dynamical approach to modeling complex systems

Boolean delay equations (BDEs) are equations with discrete variables evolving in continuous time. They serve as exploratory tools in the study of nonlinear and complex systems. In this review paper, we outline their formulation and illustrate their properties by application to a solid-earth problem and a climate one. The first problem is the seismotectonic description and prediction of earthquakes and of their clustering. The second one is that of the coupled atmosphere-ocean phenomenon of the El Niño-Southern Oscillation (ENSO). Both involve irregular behavior that is hard to predict, although some form of cyclicity is present in both, especially in ENSO. The paper concludes with broad perspectives on the further use of BDEs in the geosciences and elsewhere.

Interdecadal Variations in the Seasonal Cycle of Explosive Growth of Southern Hemisphere Storms with Impacts on Southern Australian Rainfall

Interdecadal variations, since the middle of the 20th century, in the seasonal cycle of Southern Hemisphere extratropical synoptic scale weather systems, are studied and related to associated anomalies in Southern Australian rainfall over south-west Western Australia (SWWA) and southeast Australia (SEA). A data-driven method is employed in which atmospheric fluctuations, specified from 6-hourly lower-tropospheric reanalysis data, are spectrally analysed in space and time to determine the statistics of the intensity and growth rates of growing and decaying eddies. Extratropical storms, blocking and north-west cloud band weather types are investigated in two frequency bands, with periods less than 4 days and between 4 and 8 days, and in three growth rate and three decay rate bins. Southern Australian rainfall variability is found to be most related to changes in explosive storms particularly in autumn and winter. During the first 10 years of the Australian Millennium Drought (AMD), from 1997 to 2006, dramatic changes in rainfall and storminess occurred. Rainfall declines ensued over SEA in all seasons, associated with corresponding reductions in the intensity of fast-growing storms with periods less than 4 days. These changes, compared with the 20-year timespans of 1949 to 1968 and 1975 to 1994, also took place for the longer duration of 1997 to 2016, apart from summer. Over SWWA, autumn and winter rainfall totals have decreased systematically with time for each of the 10-year and 20-year timespans analysed. Southern Australian rainfall variability is also found to be closely related to the local, hemispheric or global features of the circulation of the atmosphere and oceans that we characterise by indices. Local circulation indices of sea level pressure and 700 hPa zonal winds are good predictors of SWWA and SEA annual rainfall variability particularly in autumn and winter with vertical velocity generally less so. The new Subtropical Atmospheric Jet (SAJ) and the Southern Ocean Regional Dipole (SORD) indices are found to be the most skilful non-local predictors of cool season SWWA rainfall variability on annual and decadal timescales. The Indian Ocean Dipole (IOD) and Southern Oscillation Index (SOI) are the strongest non-local predictors of SEA annual rainfall variability from autumn through to late spring, while on the decadal timescale, different indices dominate for different 3-month periods.

Unravelling the Influence of ENSO and SAM Patterns on Skate Growth: The Case of the Shorttail Yellownose Skate in Patagonia, Argentina

ABSTRACTIn recent decades, the growth, physiology and distribution of many elasmobranch species have been altered as a result of environmental changes that affect prey abundance, availability and composition. Consequently, variations in nutrient input during climate events could manifest in the growth of their hard tissues. This study focuses on assessing the impact of the El Niño‐Southern Oscillation (ENSO) and the Southern Annular Mode (SAM) on the growth of Shorttail Yellownose skate (Zearaja brevicaudata) in Patagonia, Argentina. To achieve this, vertebrae from 115 Z. brevicaudata specimens were analysed, and growth rings were dated and measured. By using cubic splines with varying flexibility, we constructed three standard chronologies. Generalized additive models (GAMs), the chronology with the best the R‐bar () and expressed population signal (EPS) were employed and values obtained from them linked to annual time series data of the Multivariate ENSO Index (MEI) and SAM, considering lags in the biological response. Surprisingly, no significant association was found with the MEI time series. However, a noteworthy positive association emerged between the chronology and the SAM time series lagged by 1 year, suggesting that SAM‐related climatic conditions could delay their transfer into the Patagonian marine ecosystem, subsequently impacting the growth of this ectothermic predator.

A prototype early warning system for diarrhoeal disease to combat health threats of climate change in the asia-pacific region

Abstract Ongoing climate variability and change are increasing the burden of diarrhoeal disease worldwide. Meaningful early warning systems with adequate lead times (weeks to months) are needed to guide public health decision–making and enhance community resilience against health threats posed by climate change. Toward this goal, we trained various machine-learning models to predict diarrhoeal disease rates in Nepal (2002–2014), Taiwan (2008–2019), and Vietnam (2000–2015) using temperature, precipitation, previous disease rates, and El Niño Southern Oscillation phases. We also compared the performance of shallow time-series neural network (NN), Random Forest Regressor, artificial nn, gradient boosting regressor, and long short-term memory–based methods for their effectiveness in predicting diarrhoeal disease burden across multiple countries. We evaluated model performance using a test dataset and assessed the accuracy of predicted diarrhoeal disease incidence rates for the last year of available data in each district. Our results suggest that even in the absence of the most recent disease surveillance data, a likely scenario in most low- and middle-income countries, our NN-based early warning system using historical data performs reasonably well. However, future studies are needed to perform prospective evaluations of such early warning systems in real-world settings.

Persistently active El Niño–Southern Oscillation since the Mesozoic

The El Niño-Southern Oscillation (ENSO), originating in the central and eastern equatorial Pacific, is a defining mode of interannual climate variability with profound impact on global climate and ecosystems. However, an understanding of how the ENSO might have evolved over geological timescales is still lacking, despite a well-accepted recognition that such an understanding has direct implications for constraining human-induced future ENSO changes. Here, using climate simulations, we show that ENSO has been a leading mode of tropical sea surface temperature (SST) variability in the past 250 My but with substantial variations in amplitude across geological periods. We show this result by performing and analyzing a series of coupled time-slice climate simulations forced by paleogeography, atmospheric CO2 concentrations, and solar radiation for the past 250 My, in 10-My intervals. The variations in ENSO amplitude across geological periods are little related to mean equatorial zonal SST gradient or global mean surface temperature of the respective periods but are primarily determined by interperiod difference in the background thermocline depth, according to a linear stability analysis. In addition, variations in atmospheric noise serve as an independent contributing factor to ENSO variations across intergeological periods. The two factors together explain about 76% of the interperiod variations in ENSO amplitude over the past 250 My. Our findings support the importance of changing ocean vertical thermal structure and atmospheric noise in influencing projected future ENSO change and its uncertainty.

Compound Hot and Dry Events in Argentina and Their Connection to El Niño‐Southern Oscillation

ABSTRACTThis work studies the simultaneous and sequential occurrence of hot and dry months in the summer season in Argentina, north of 40°S, based on three different databases: meteorological stations, a gridded observational dataset and a reanalysis product. The influence of the El Niño‐Southern Oscillation (ENSO) over the occurrence of these compound events is specially analysed using a logistic regression model. Monthly maximum temperature and precipitation data are used for the period 1979–2022 in four sub‐regions of Argentina: Northwestern Argentina (NOA), Northeastern Argentina (NEA), Cuyo (central‐western Argentina) and the Pampas (central‐eastern Argentina). Simultaneous hot and dry months and hot months preceded by dry months are the most frequent compound events. The highest frequencies are found in the centre part of the study region and NEA for simultaneous compound events, and in NOA and the Pampas region for sequential ones. In general terms, all datasets show a good representation of the spatio‐temporal variability of hot and dry months. The insights of the influence of ENSO on compound events revealed that La Niña enhances the occurrences of hot and dry months throughout the study region, with the exception of NOA, where El Niño conditions promote the occurrence of these events. Based on logistic regression models, we successfully quantify the relationship between ENSO and hot and dry months and demonstrate that ENSO plays a significant role as a driver of compound hot and dry events in the central region, Cuyo, NEA and a portion of the Pampas. This research contributes to the understanding of compound events in Argentina and how they are influenced by major drivers of climate variability providing useful information for the development of a predictive system for such events.

Tornado Occurrence in the United States as Modulated by Multidecadal Oceanic Oscillations Using Empirical Model Decomposition

Studies have analyzed U.S. tornado variability and correlated F1–F5 tornado occurrence with various natural climate oscillations and anthropogenic factors. Using a relatively new empirical mode decommission (EMD) method that extracts time-frequency modes adaptively without priori assumptions like traditional time-series analysis methods, this study decomposes U.S. tornado variability during 1954–2022 into intrinsic modes on specific temporal scales. Correlating the intrinsic mode functions (IMFs) of EMD with climate indices found that 1. the U.S. overall tornado count is negatively (positively) correlated with the Atlantic Multidecadal Oscillation (AMO) index (the Southern Oscillation Index (SOI)); 2. the negative (positive) correlation tends to be more prevalent in the western (eastern) U.S.; 3. the increase in weak (F1–F2) and decrease in strong (F3–F5) tornadoes after around 2000, when both the AMO and the Pacific Decadal Oscillation (PDO) shifted phases, are likely related to their secular trends and low-frequency IMFs; and 4. the emerging Dixie Tornado Alley coincides with an amplifying intrinsic mode of the SOI that correlates positively with the eastern U.S. and Dixie Alley tornadoes. The long-term persistence of these climate indices can offer potential guidance for future planning for tornado hazards.

Interannual moisture variability on the Qinghai Plateau: Trends, patterns, and implications

Investigating surface dry-wet patterns on the Qinghai Plateau (QP) is crucial for water allocation, ecological sustainability, and climate variability adaptation strategies. Existing discrepancies in the QP dry-wet trends and distribution characteristics underscored the need for a more refined analysis. This study utilized the Thornthwaite Moisture Index (IM) to quantify changes in surface dryness and wetness under prevailing climatic conditions. Linear trend regression and ensemble empirical mode decomposition (EEMD) were applied to study the dynamic and periodic characteristics of the QP from 1980 to 2018.Our findings revealed a decrease from southeast to northwest in IM, with the semi-arid and sub-humid transition line aligning closely with the 400 mm isohyet. The dry-wet transition line exhibited a northwestward trend over the past four decades. Possibly influenced by monsoon circulation and El Niño-Southern Oscillation (ENSO), the annual IM displayed a quasi-cycle of 3 to 5 years, manifested by a dry period (1990–2004) and a wet period (2005–2012). However, spatial differences existed, challenging the universality of the “Dry gets Drier and Wet gets Wetter (DDWW)” pattern. Precipitation (PRCP) changes could predict over 90 % of IM spatiotemporal variations. Additionally, the IM response to Average Temperature (TAVG) exhibited an inverted U-shaped curve, with a boundary (−3.8 °C) below which cooler regions became wetter and above which they became drier. The observed warming and precipitation shifts suggested that continued warming could lead to warmer and wetter climates, potentially causing ecological and environmental problems. Therefore, examining the surface moisture budget is of critical scientific and practical significance, in order to provide a decision-making basis for mitigating and adapting to climate change.

Impact of El Niño−Southern Oscillation on Quasi‐Biweekly Oscillation Over the Western North Pacific in Boreal Winter

ABSTRACTImpacts of El Niño−Southern Oscillation (ENSO) on the quasi‐biweekly oscillation over the western North Pacific (WNP‐QBWO) in boreal winter are investigated in the study. The WNP‐QBWO in boreal winter primarily propagates westward from the tropical western Pacific to WNP. During the La Niña winter, the QBWO over the WNP has stronger intensity and propagates westward at a faster speed, while it is weaker and propagates more slowly during the El Niño winter. The possible mechanisms may involve the ENSO‐related background moisture and zonal wind vertical shear changes that can significantly modulate the WNP‐QBWO's behaviours in boreal winter. A 2.5‐layer atmospheric model is applied in the study and confirms the results. It is further revealed that the moisture change is dominant in modulating the WNP‐QBWO's intensity, while both the moisture and vertical shear changes may together contribute to the zonally propagating speed of the WNP‐QBWO in boreal winter. These results can deepen our understanding of dynamic processes associated with the WNP‐QBWO in boreal winter and are conducive to the predictability study.

Low cloud-SST variability over the summertime subtropical Northeast Pacific: Role of extratropical atmospheric modes

Abstract Over the subtropical Northeast Pacific (NEP), highly reflective low clouds interact with underlying sea-surface temperature (SST) to constitute a local positive feedback. Recent modeling studies showed that, together with wind-evaporation-SST (WES) feedback, the summertime low cloud-SST feedback promotes nonlocal trade wind variations, modulating subsequent evolution of El Niño-Southern Oscillation (ENSO). This study aims to identify drivers of summertime low-cloud variations, using satellite observations and global atmosphere model simulations forced with observed SST. A trans-basin teleconnection is identified, where the North Tropical Atlantic (NTA) warming induced by the North Atlantic Oscillation (NAO) increases precipitation, exciting warm Rossby waves that extend into the NEP. The resultant enhancement of static stability promotes summertime low cloud-SST variability. By regressing out the effects of the preceding ENSO and NTA SST, atmospheric internal variability over the extratropical North Pacific, including the North Pacific Oscillation (NPO), is found to drive the NEP cooling by latent heat loss and subsequent summer low cloud-SST variability. With the help of the background trade winds and WES feedback, the SST anomalies extend southwestward from the low-cloud region, accompanied by ENSO in the following winter. This suggests the nonlocal effects of low clouds identified by recent studies. Analysis of a 500-year climate model simulation corroborates the NTA and NPO forcing of NEP low cloud-SST variability and subsequent ENSO.