El Nino Southern Oscillation Index Research Articles

Teleconnection Between Coastal Phytoplankton Blooms Phenomenon in Western North Pacific and El Niño–Southern Oscillation by Time‐Frequency Analysis

AbstractPhytoplankton blooms in coastal marine environments are regard as a double‐edged sword, offering benefits to coastal ecosystems while also posing significant environmental challenges. The occurrence and severity of these blooms are influenced by environmental factors, with climate oscillations playing a crucial role. In this study, we employed two time‐frequency analysis methods to investigate the teleconnection between phytoplankton blooms (denoted by bloom intensity, BI) and El Niño–Southern Oscillation (ENSO) from 2003 to 2020 in eight large marine ecosystems (LMEs) of Western North Pacific which are particularly sensitive to the impacts of climate oscillations and reflect well the impacts on marine ecosystems at different latitudes. These analytical methods unveiled these time series exhibited similar periodicity and synchronization patterns, which indicated the teleconnection between ENSO and phytoplankton blooms in the Western North Pacific. The Hilbert‐Huang Transformation classified the eight LMEs into two categories based on their similarity to BI and MEI in the time‐frequency domain. Specifically, one category is similar to MEI with energy concentrated at low frequencies, while the other category exhibits significant dissimilarity with dispersed energy. Wavelet analysis uncovered a robust coherence between the ENSO and BI across all LMEs, with a 57‐month periodicity. Furthermore, phytoplankton blooms in the Western North Pacific Ocean strengthen with increasing Multivariate ENSO Index on the large spatiotemporal scale due to a decrease in sea surface temperatures. The findings will be useful as a reference for improving understanding of the teleconnection between coastal phytoplankton blooms and climate oscillations in other coastal zones.

Space-time analysis of the relationship between landslides occurrence, rainfall variability and ENSO in the Tropical Andean Mountain region in Colombia

According to studies by the Intergovernmental Panel on Climate Change (IPCC), tropical mountainous areas are experiencing increasingly unfavorable climatic conditions regarding geohazards due to a heightened occurrence of intense rainfall events. These climatic shifts contribute to heightened geological risks, notably an elevated frequency of landslides, exacerbating the challenges faced by these regions. There is an urgent need to understand and measure how rainfall variability affects geo-hydrological hazards, which remain difficult to determine and predict. The complex and non-linear space-time relationships and dynamics of rainfall, El Niño-Southern Oscillation (ENSO), and landslides in the Tropical Andean Mountain region in Colombia require an adequate analysis and understanding of their link in terms of its spatial and temporal component at different scales. By evaluation in annual, seasonal, and monthly scales, additional insights on the relationships using a wavelet spectral analysis and a space-time permutation scan statistics method using SaTScan™ are provided. In this study, a space-time and frequency analysis of landslides using a 42-year (1981–2022) rainfall and Multivariate ENSO Index v2.0 time series is presented. According to the results, landslides closely aligned with rainfall patterns, exhibiting a bimodal annual cycle. The ENSO added complexity, with La Niña years leading to more frequent landslides throughout the year and El Niño years showing concentrated occurrences in specific months. This study highlights the influence of rainfall patterns and antecedent rainfall on landslide occurrence, the impact of ENSO phases on rainfall and landslides, and the increasing trend of landslides in Colombia.

Augmented human thermal discomfort in urban centers of the Arabian Peninsula

Anthropogenic climate change has amplified human thermal discomfort in urban environments. Despite the considerable risks posed to public health, there is a lack of comprehensive research, evaluating the spatiotemporal changes in human thermal discomfort and its characteristics in hot-hyper arid regions, such as the Arabian Peninsula (AP). The current study analyzes spatiotemporal changes in human thermal discomfort categories and their characteristics in AP, using the newly developed high-resolution gridded ERA5-HEAT (Human thErmAl comforT) dataset for the period 1979–2022. In addition, the study assesses the interplay between the Universal Thermal Climate Index (UTCI) and El Niño-Southern Oscillation (ENSO) indices for the study period. The results reveal a significant increase in human thermal discomfort and its characteristics, with higher spatial variability in the AP region. The major urban centers in the southwestern, central, and southeastern parts of AP have experienced significant increases in human thermal discomfort (0.4–0.8 °C), with higher frequency and intensity of thermal stress during the study period. The temporal distribution demonstrates a linear increase in UTCI indices and their frequencies and intensities, particularly from 1998 onward, signifying a transition towards a hotter climate characterized by frequent, intense, and prolonged heat stress conditions. Moreover, the UTCI and ENSO indices exhibit a dipole pattern of correlation with a positive (negative) pattern in the southwestern (eastern parts) of AP. The study’s findings suggest that policymakers and urban planners need to prioritize public health and well-being in AP’s urban areas, especially for vulnerable groups, by implementing climate change adaptation and mitigation strategies, and carefully designing future cities to mitigate the effects of heat stress.

Quantifying the Strength of the El Niño Southern Oscillation and the Indian Ocean Dipole in Influencing the OND Rainfall Season in Tanzania

The current paper examines the strength of variability between the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) in influencing October to December (OND) rainfall over the bimodal rainfall regime of Tanzania. The empirical orthogonal function (EOF), correlation analysis, and composite analysis were used during the data analysis. The results show more rainfall distribution over the western part of the Lake Victoria basin and to the peripheral of the northern coast of the country, thus suggesting that, during the OND rainfall season, the onset starts in the western part of the Lake Victoria basin, then spreads to the rest of the areas under investigation as the season progresses. Furthermore, on the spatial scale, the findings revealed that there is a strong correlation between IOD and ENSO indices and OND rains in the northeastern highlands. Furthermore, a robust temporal correlation is revealed between the mean OND rains over the bimodal rainfall areas and IOD (r = 0.70) compared to ENSO (r = 0.62). The anomalous warming over the western Indian Ocean (positive IOD) has a faster response to OND rains over the bimodal rainfall regime of Tanzania compared to the remote influence induced by anomalous warming from the central equatorial Pacific Ocean (warm phase of ENSO). Meanwhile, dry years are associated with negative IOD and the cold phase of ENSO conditions. The findings offer valuable insights on strategies for mitigating the effects associated with extreme weather events and improving resilience in Tanzania.

Spatial and Temporal Variability Characteristics and Driving Factors of Extreme Precipitation in the Wei River Basin

As global climate change intensifies, the global atmospheric circulation process is undergoing significant changes, and the local water vapor pattern has also changed. This study takes the Wei River Basin as the research area. Firstly, an evaluation index system for extreme precipitation was established, and the time-series characteristics of the magnitude, frequency, and duration of extreme precipitation were analyzed. Statistical methods were used to analyze the non-consistency in time-series changes in extreme precipitation indicators. Using spatial heterogeneity analysis methods, the spatial variation differences in extreme precipitation in the Wei River Basin were identified. This study selected the El Niño-Southern Oscillation (ENSO) index, global land-ocean temperature index (LOTI), and land surface temperature (LST) index to quantitatively evaluate the impact of climate change on regional extreme precipitation and analyzed the correlation between temperature and extreme precipitation, identifying the key driving factors of extreme precipitation changes. The conclusions of this study are as follows: (1) The southern region of the Wei River Basin experiences more frequent and intense precipitation events, while the northern region experiences relatively few. (2) From 1981 to 2021, the intensity, frequency, and duration of precipitation events in the Wei River Basin gradually increased, with the most significant increase in extreme precipitation in the Guanzhong Plain. (3) Global climate change has an important impact on precipitation events in the Wei River Basin. The increase in the ENSO, LOTI, and LST indices may indicate an increase in the probability of drought and flood events in the Wei River Basin. The relationships between extreme precipitation and temperature present a peak structure. This conclusion is helpful to better understand the impact of climate change on extreme precipitation in the Wei River Basin and provides some support for the response to extreme meteorological events under the background of future climate change.

Spatial Patterns of Vegetation Activity Related to ENSO in Northern South America

AbstractInterannual variability of vegetation activity (i.e., photosynthesis) is strongly correlated with El Niño Southern Oscillation (ENSO). Globally, a reduction in carbon uptake by terrestrial ecosystems has been observed during the ENSO warm phase (El Niño) and the opposite during the cold phase (La Niña). However, this global perspective obscures the heterogeneous impacts of ENSO at regional scales. Particularly, ENSO has contrasting impacts on climate in northern South America (NSA) depending on the ENSO phase and geographical location, which in turn affect the activity of vegetation. Furthermore, changes of vegetation activity during multiple ENSO events are not well understood yet. In this study, we investigated the spatial and temporal differences in vegetation activity associated with ENSO variability and its three phases (El Niño, La Niña, Neutral) to identify hotspots of ENSO impacts in NSA, a region dominated by rainforest and savannas. To achieve this, we investigated time series of vegetation variables from 2001 to 2014 at moderate spatial resolution (0.0083°). Data were aggregated through dimensionality reduction analysis (i.e., Global Principal Component Analysis). The leading principal component served as a proxy of vegetation activity (VAC). We calculated the cross‐correlation between VAC and the multivariate ENSO index separately for each ENSO phase. Our results show that El Niño phase has a stronger impact on vegetation activity both in intensity and duration than La Niña phase. Moreover, seasonally dry ecoregions were more susceptible to El Niño impacts on vegetation activity. Understanding these differences is key for regional adaptation and differentiated management of ecosystems.

Analisis Korelasi Statistikal Fenomena Kejadian ENSO dan MJO terhadap Kondisi Klimatologis di Provinsi Riau

El Nino-Southern Oscillation (ENSO) and Madden-Julian Oscillation (MJO) events are significant factors in the global climate system. Riau Province, located on the island of Sumatra, is highly influenced by these phenomena. This study collects climate data from weather stations in Riau Province and reliable sources for ENSO and MJO indices. Statistical analyses, including correlation and regression, are employed to determine the relationship between climate variables in Riau Province and ENSO and MJO. Based on data from 2001-2019, the results reveal a medium category correlation value (r = 0.452) with coefficients a and b of 1.288 and 0.089, respectively. The increased MJO value contrasts with the rainfall during the 2001-2019 timeframe. This information serves as a reference for understanding the ENSO and MJO phenomena in the Riau region.

Long-term Hydrometeorological Time-series Analysis over the Central Highland of West Papua

This article presents an innovative data-driven approach for examining long-term temporal rainfall patterns in the central highlands of West Papua, Indonesia. We utilized wavelet transforms to identify signs of a negative temporal correlation between the El Niño-Southern Oscillation (ENSO) and the 12-month Standardized Precipitation Index (SPI-12). Based on this cause-and-effect relationship, we employed dynamic causality modeling using the Nonlinear Autoregressive with Exogenous input (NARX) model to predict SPI-12. The Multivariate ENSO Index (MEI) was used as an attribute variable in this predictive framework. Consequently, this dynamic neural network model effectively captured common patterns within the SPI-12 time series. The implications of this study are significant for advancing data-driven precipitation models in regions characterized by intricate topography within the Indonesian Maritime Continent (IMC).

The Effect of the El Nino Southern Oscillation on Precipitation Extremes in the Hindu Kush Mountains Range

The El Nino Southern Oscillation (ENSO) phenomenon is devastating as it negatively impacts global climatic conditions, which can cause extreme events, including floods and droughts, which are harmful to the region’s economy. Pakistan is also considered one of the climate change hotspot regions in the world. Therefore, the present study investigates the effect of the ENSO on extreme precipitation events across the Upper Indus Basin. We examined the connections between 11 extreme precipitation indices (EPIs) and two ENSO indicators, the Southern Oscillation Index (SOI) and the Oceanic Niño Index (ONI). This analysis covers both annual and seasonal scales and spans the period from 1971 to 2019. Statistical tests (i.e., Mann–Kendall (MK) and Innovative Trend Analysis (ITA)) were used to observe the variations in the EPIs. The results revealed that the number of Consecutive Dry Days (CDDs) is increasing more than Consecutive Wet Days (CWDs); overall, the EPIs exhibited increasing trends, except for the Rx1 (max. 1-day precipitation) and Rx5 (max. 5-day precipitation) indices. The ENSO indicator ONI is a temperature-related ENSO index. The results further showed that the CDD value has a significant positive correlation with the SOI for most of the UIB (Upper Indus Basin) region, whereas for the CWD value, high elevated stations gave a positive relationship. A significant negative relationship was observed for the lower portion of the UIB. The Rx1 and Rx5 indices were observed to have a negative relationship with the SOI, indicating that El Nino causes heavy rainfall. The R95p (very wet days) and R99p (extreme wet days) indices were observed to have significant negative trends in most of the UIB. In contrast, high elevated stations depicted a significant positive relationship that indicates they are affected by La Nina conditions. The PRCPTOT index exhibited a negative relationship with the SOI, revealing that the El Nino phase causes wet conditions in the UIB. The ONI gave a significant positive relationship for the UIB region, reinforcing the idea that both indices exhibit more precipitation during El Nino. The above observations imply that while policies are being developed to cope with climate change impacts, the effects of the ENSO should also be considered.

Variability, cycles, and trends of mean air temperature north of Colombia

Climate variability is of global interest due to its socioeconomic and environmental effects on the world’s population. In Colombia, temperature changes affect food security, especially for the most vulnerable people in the Caribbean region. We analyzed monthly air temperature in northeastern Colombia (Cesar, La Guajira, and Magdalena departments). We reconstructed time series with missing data using nonlinear principal component analysis. Subsequently, temporal variability, associations with events of climatic variability, and temporal trends were evaluated. Periodicity analyses indicate the dominance of annual variability, although statistically significant associations with periods between 3 and 7 years show the influence of El Niño-Southern Oscillation (ENSO) events. The Spearman correlation coefficient with N = 360 and 95% significance shows a better association with the Multivariate ENSO Index (rsp mean = 0.38) and the Southern Oscillation Index (rsp mean = –0.32). The multi-year monthly analysis shows positive trends, with maximum values between March (1.04 ºC month–1), and June (1.07 ºC month–1) in the valley of the Cesar department, and a minimum in March, at the northernmost La Guajira (0.2 ºC month–1).

ANALISIS KARAKTERISTIK SPASIAL DAN TEMPORAL HOTSPOT DI TAMAN NASIONAL SEBANGAU PROVINSI KALIMANTAN TENGAH

Sebangau National Park, in Central Kalimantan Province, is a wetland conservation area. In 2015, forest and land fires resulted in 455 hectares being burned. The identification of hotspots in this study is based on the number and distribution of hotspots based on satellite imagery data from the Moderate Resolution Imaging Spectroradiometer (MODIS) in 2001–2020. This study identifies hotspots by looking at the influence of rainfall and ENSO (El Nino Southern Oscillation) conditions. The method used is the method of spatial and temporal analysis. The aim of this study was to determine the characteristics of the hotspot distribution pattern in Sebangau National Park, Central Kalimantan Province, both spatially and temporally. There is a similarity between the temporal and spatial characteristics of hotspots in the number of significant additions to the number of hotspots in August, September, and October. The influence of monsoonal rainfall types and climates such as ENSO (El Nino Southern Oscillation) greatly influences the occurrence of hotspot events in Sebangau National Park, Central Kalimantan Province. The distribution pattern of hotspots in Sebangau National Park, Central Kalimantan Province, peaked in October, and the worst addition to the number of hotspots occurred in 2015, when these conditions occurred during the dry season and when the ENSO index (El Nino Southern Oscillation) showed +2.6, where these conditions included strong El Nino categories.

Wavelet Analysis of Ozone Driving Factors Based on ~20 Years of Ozonesonde Measurements in Beijing

A long-term vertical ozone observational dataset has been provided during 2001–2019 by ozonesonde measurements in Beijing on the North China Plain. Previous studies using this dataset primarily focused on the vertical characteristics of climatological ozone and its variation; however, the driving factors of ozone variation have not been well discussed. In this study, by applying the wavelet analysis method (including continuous wavelet transform and cross wavelet) and sliding correlation coefficients to ~20 years of ozonesonde measurements collected in Beijing, we analyzed the dominant modes of ozone column variability within three height ranges over Beijing (total column ozone: TOT; stratospheric column ozone: SCO; and tropospheric column ozone: TCO). Moreover, we also preliminarily discussed the relationship between these three ozone columns and the El Niño Southern Oscillation (ENSO), Quasi-biennial Oscillation (QBO), and 11-year solar activity cycle. The results revealed that the ozone columns within the three height ranges predominantly adhered to interannual variability patterns, and the short-term variabilities in TOT and SCO may have been related to eruptive volcanic activity. In comparison to the TOT and SCO, the TCO was more susceptible to the forcing influences of high-frequency factors such as pollutant transport. Similar to the results in other mid-latitude regions, strong ENSO and QBO signals were revealed in the interannual ozone column variability over Beijing. The TOT and SCO showed positive anomalous responses to ENSO warm-phase events, and the peak of the ENSO warm phase led the winter peaks of the TOT and SCO by approximately 3–6 months. During the strong cold–warm transition phase in 2009–2012, the TOT and SCO showed a significant positive correlation with the ENSO index. The strong seasonality of the meridional circulation process driven by the QBO led to a significant positive correlation between the QBO index and the TOT and SCO in the interannual cycle, except for two periods of abnormal QBO fluctuations in 2010–2012 and 2015–2017, whereas the TCO showed a time-lagged correlation of approximately 3 months in the annual cycle relative to the QBO due to the influence of the thermodynamic tropopause. In addition, analysis of the F10.7 index and the ozone columns revealed that the ozone columns over Beijing exhibited lagged responses to the peaks of sunspot activity, and there was no obvious correlation between ozone columns and 11-year solar activity cycle. Given the complex driving mechanism of the climatic factors on local ozone variability, the preliminary results obtained in this study still require further validation using longer time series of observational data and the combination of chemical models and more auxiliary data.

Equatorward shift of ENSO-related subtropical jet anomalies in recent decades

Using observations, NCEP-NCAR and ERA5 reanalysis datasets, numerical experiments and CMIP6 model outputs, this study investigates long-term changes in the meridional position of subtropical jet anomalies in association with El Niño-Southern Oscillation (ENSO). It is found that the subtropical jet anomalies associated with ENSO index (i.e., Niño3.4 index in this study) over both Northern Hemisphere (NH) and Southern Hemisphere (SH) significantly (at the 99% confidence level) shift equatorward since the 1960s, at the speeds of 1.28 and 1.00° per decade, respectively. In recent six decades, the subtropical jet anomalies have moved equatorward by 4.34 and 3.19° over NH and SH, respectively. Our analysis indicates that the tropical positive sea surface temperature (SST) anomalies associated with Niño3.4 (corresponding to its warm phase) during 1990–2020 (P2) are weaker than those during 1950–1980 (P1). The weak, positive SST anomalies induce tropical weak, positive surface latent heat flux and precipitation anomalies, which heat tropical troposphere and produce weak, positive geopotential height anomaly with a narrow meridional width over the tropics during P2. According to geostrophic wind relations, anomalous positive zonal winds occur over the subtropics in the upper troposphere, meaning strengthened subtropical westerly jets over NH and SH. Hence, the relatively weak, narrow positive geopotential height anomaly during P2 favors the equatorward shift of Niño3.4-related subtropical jet anomalies via geostrophic wind relations. The results from numerical experiments and CMIP6 model outputs also indicate that changes in tropical SST anomalies associated with Niño3.4 contribute to this equatorward shift, supporting the results from reanalysis datasets. These results suggest that the intensity of tropical SST anomalies linked to ENSO should be well resolved to better simulate and predict subtropical jet variations.

The increase in extreme precipitation and its proportion over global land

Changes in extreme precipitation (EP) have a significant impact on the ecology and sustainable development of most regions, especially when considered against a backdrop of global warming. Using trend analysis and other methods, we analyze the changes in nine extreme precipitation indices (EPIs), looking at the proportion of EP in total precipitation from the perspectives of intensity, frequency, and duration. We also utilize a geo-detector method to investigate the impacts of 15 climate factors on EPIs. Our results indicate that although EP and their proportions show an overall increasing trend on a global scale, they had undergone a process of initial decrease followed by increase over the past approximately 70 years. And this overall global increases are charged by the significant increases happened in Northern Hemisphere and western of South America, especially EP intensity and frequency indices, and their proportion. Whereas CDD shows an opposite trend in spatial distribution, the CWD is decreasing globally. The EPIs and their proportions are all highest in the low elevation belt (≤2000 m), followed by the high elevation belt (≥4000 m), and lowest in the mid-elevation belts (2000-4000 m). Most of them have returned to or exceeded the levels of the mid-20th century in all three elevation belts. Only CWD shows a decreasing trend, which indicates that more EP amounts are occurring with less precipitation duration. In some arid areas, this makes it possible that a short period of precipitation may complete the total amount of precipitation for that year. Global temperature is proven to be the most important factor influencing the EPI globally, and followed by the temperature of each region. And the regions of high latitudes of the Northern Hemisphere and Antarctica which are greatly influenced by global temperature demonstrate the Polar amplification effect. The East Atlantic-West Russia Pattern, Atlantic Multi-Decadal Oscillation, and El Nino-Southern Oscillation indices are the secondly important factors leading to changes in the proportion of global EP. At the same time, we also find that the influence of non-monsoon factors on EP is gradually strengthening. This study clarifies changes in EP globally and in various regions, which will help provide a scientific reference for preventing disasters caused by extreme climate change.

ENSO‐Related Fire Weather Changes in Southeast and Equatorial Asia: A Quantitative Evaluation Using Fire Weather Index

AbstractInterannual variability of tropical fire activity has been linked to the El Niño‐Southern Oscillation (ENSO). Here we analyze changes in fire and simultaneous fire weather related to ENSO over Southeast (SEAS) and Equatorial Asia (EQAS) and quantitively evaluate the contribution of key meteorological variables to the fire weather variations for the past decades. During the fire seasons, large increases in fires emerge in El Niño years, which greatly coincides with the more fire‐susceptible weather conditions compared to La Niña years. Moreover, the fires exhibit a more significant correlation with the ENSO index in El Niño years, mainly due to the influence of asymmetry response of the fire weather to ENSO. Composite analysis shows that it is the positive anomalous low‐level geopotential height and less water vapor transportation over SEAS (March–May) and EQAS (August–October) during El Niño that forms the fire‐favoring weather. By conducting tests in calculating fire weather index (FWI) under different ideal conditions, we identified the daily precipitation as the dominant driver of FWI variation, with the contribution reaching 65.5%–77.5% and 60.9%–90.5% for SEAS and EQAS respectively, while decreased relative humidity induces nearly a quarter of increases in FWI in El Niño years. Changes in temperature and wind speed, however, rarely perturb the fire weather for both SEAS and EQAS regions. The quantitative evaluations of individual meteorological variables in shaping fire weather as well as their asymmetrical response in ENSO years could support fire management during fire seasons in Tropical Asia.

Future Projections of the El Niño—Southern Oscillation and Tropical Pacific Mean State in CMIP6

AbstractThe El Niño—Southern Oscillation (ENSO) is an important mode of tropical Pacific atmosphere‐ocean variability that drives teleconnections with weather and climate globally. However, prior studies using state‐of‐the‐art climate models lack consensus regarding future ENSO projections and are often impacted by tropical Pacific sea‐surface temperature (SST) biases. We used 173 simulations from 29 climate models participating in the Coupled Model Intercomparison Project, version 6 (CMIP6) to analyze model biases and future ENSO projections. We analyzed two ENSO indices, namely the ENSO Longitude Index (ELI), which measures zonal shifts in tropical Pacific deep convection and accounts for changes in background SST, and the Niño 3.4 index, which measures SST anomalies in the central‐eastern equatorial Pacific. We found that the warm eastern tropical‐subtropical Pacific SST bias typical of previous generations of climate models persists into many of the CMIP6 models. Future projections of ENSO shift toward more El Niño‐like conditions based on ELI in 48% of simulations and 55% of models, in association with a future weakening of the zonal equatorial Pacific SST gradient. On the other hand, none of the models project a significant shift toward La Niña‐like conditions. The standard deviation of the Niño 3.4 index indicates a lack of consensus on whether an increase or decrease in ENSO variability is expected in the future. Finally, we found a possible relationship between historical SST and low‐level cloud cover biases in the ENSO region and future changes in ELI; however, this result may be impacted by limitations in data availability.

CNN‐Based ENSO Forecasts With a Focus on SSTA Zonal Pattern and Physical Interpretation

AbstractDeep learning (DL) has achieved notable success in El Niño‐Southern Oscillation (ENSO) forecasts. Most DL‐based models focused on forecasting ENSO indices while the zonal distribution of sea surface temperature anomalies (SSTA) over the equatorial Pacific was overlooked. To provide accurate predictions for the SSTA zonal pattern, this study developed a model through leveraging the merits of the cosine distance in constructing the convolutional neural network. This model can skillfully predict the SSTA zonal pattern over the equatorial Pacific 1 year in advance, remarkably outperforming current dynamical models. Moreover, the physical interpretation of the model prediction reveals that the sources for ENSO predictability at different lead times are distinct. For the 10‐month‐lead predictions, the precursors in the north Pacific, south Pacific and tropical Atlantic play critical roles in determining the model behaviors; while for the 16‐month‐lead predictions, the initial signals in the tropical Pacific associated with the discharge‐recharge cycle are essential.

Tropical Pacific Modulation of the Asian Summer Monsoon Over the Last Millennium in Paleoclimate Data Assimilation Reconstructions

AbstractLarge uncertainties exist in climate model projections of the Asian summer monsoon (ASM). The El Niño‐Southern Oscillation (ENSO) is an important modulator of the ASM, but the ENSO‐ASM teleconnection is not stationary. Furthermore, teleconnections between ENSO and the East Asian versus South Asian subcomponents of the ASM exhibit distinct characteristics. Therefore, understanding the variability of the ENSO‐ASM teleconnection is critical for anticipating future variations in ASM intensity. To this end, we here use paleoclimate records to extend temporal coverage beyond the instrumental era by millennia. Recently, data assimilation techniques have been applied for the last millennium, which facilitates physically consistent, globally gridded climate reconstructions informed by paleoclimate observations. We use these novel data assimilation products to investigate variations in the ENSO‐ASM relationship over the last 1,000 years. We find that correlations between ENSO and ASM indices are mostly negative in the last millennium, suggesting that strong ASM years are often associated with La Niña events. During periods of weak correlations between ENSO and the East Asian summer monsoon, we observe an El Niño‐like sea surface temperature (SST) pattern in the Pacific. Additionally, SST patterns associated with periods of weak correlations between ENSO and South Asian summer monsoon rainfall are not consistent among data assimilation products. This underscores the importance of developing more precipitation‐sensitive paleoclimate proxies in the Indian subcontinental realm over the last millennium. Our study serves as a baseline for future appraisals of paleoclimate assimilation products and an example of informing our understanding of decadal‐scale ENSO‐ASM teleconnection variability using paleoclimate data sets.

Tweedie models for Malaysia rainfall simulations with seasonal variabilities

Abstract This study aims to evaluate the suitability of the Tweedie generalised linear model for characterising monthly rainfall patterns across 18 meteorological stations in Peninsular Malaysia. It incorporates harmonic functions consisting of sine and cosine functions as seasonal predictors and El Niño Southern Oscillation (ENSO) indices as climatic predictors. Results indicate that three harmonic functions are essential to accurately portray rainfall dynamics in the southwestern and northwestern regions, while two suffice for the inland and western regions. However, incorporating four harmonic functions is the most optimal representation of the eastern region. An additional 1-month lag in ENSO indices is introduced to the optimal seasonal predictor model. Based on the findings, the southern oscillation index notably impacts monthly rainfall significantly in eastern and inland areas, while meteorological stations in the western and northwestern areas fit better with the multivariate ENSO index. Strikingly, no substantial impact of climate predictors is observed on the monthly rainfall within the southwestern region. Thus, the influence of climate indices is very much influenced by the geographical locations of the regions. Importantly, generating simulated data through the Tweedie model contributes to a more accurate representation of the statistical properties inherent in rainfall analysis.

Ecosystem Management Policy Implications Based on Tonga Main Tuna Species Catch Data 2002–2018

Despite the crucial role played by international and regional tuna fisheries in facilitating the successful implementation of the ecosystem approach to fisheries management, there exist disparities in viewpoints among these stakeholders, resulting in gaps between regional fisheries management and local communities. Nevertheless, the Tongan government, under the Ministry of Fisheries, is dedicated to the efficient management of its tuna resources, aiming to establish it as the preferred and optimal approach for ensuring the long-term sustainability of its tuna fisheries and the ecosystem services they provide to the community. Recognizing that an appropriate legal, policy and institutional framework is in place for sustainable management of tuna, the first part of this paper presents a review of current Tonga fisheries laws and policies for its tuna fisheries. This review reflects the implementation of an information-based management framework, namely the Tonga National Tuna Fishery Management and Development Plan. The tuna fisheries in Tonga mainly catch albacore (Thunnus alalunga), bigeye (Thunnus obesus), skipjack (Katsuwonus pelamis), and yellowfin (Thunnus albacares) tuna. These tuna species are caught within Tonga’s exclusive economic zones and play a crucial role in the country’s economy; hence, it is crucial to examine the spatio-temporal distributions of their catch in relation to their environmental conditions. In pursuit of this goal, the tasks of mapping (i) the spatio-temporal distribution of catch landed at ports and (ii) the spatio-temporal of environmental conditions were performed. The study utilizes longline catch per unit effort data spanning from 2002 to 2018 for albacore, bigeye, skipjack, and yellowfin tuna. It also incorporates data on environmental conditions, including sea surface temperature, sea surface chlorophyll, sea surface current, and sea surface salinity. Additionally, the El Nino Southern Oscillation Index is mapped in relation to catch data to examine the potential effects of climate change on the tuna catch. Results show that bigeye, skipjack, and yellowfin CPUE show a central–northernmost distribution and are primarily caught between latitudes 14° S–22° S, while albacore, shows a central–southern distribution. The highest CPUE for all species are in latitudes 15.5° S–22.5° S and longitudes 172.5° W–176.5° W. The data indicate that sea surface current velocities range from −0.03 to 0.04 ms−1, sea surface salinity ranges from 34.8 to 35.6 PSU, sea surface chlorophyll concentration varies from 0.03 to 0.1 mg m−3, and sea surface temperature fluctuates seasonally, ranging from 18 °C to 30 °C. Mapping also reveals that times of reduced catches in Tonga coincide with periods of moderate to strong El Nino events from 2002 to 2018.