El Nino Events Research Articles

Exploring El Nino effects on agricultural area using Landsat images analysis: A case study in Bondowoso Regency, Indonesia

El Nino, which hit Indonesia in 2023, poses severe food security threats due to the high dry season with no rainfall and minimal cloud cover and can trigger serious drought problems if it happen for a long time. This study aimed to explore the impact on agricultural land in Bondowoso Regency during El Nino events. The analysis in this study primarily uses land surface temperature (LST) and normalized difference vegetative index (NDVI) map distribution. The Landsat data from USGS are collected and processed to become LST and NDVI distribution maps. Data analysis focused on the agricultural area layers based on data from the Indonesia geospatial portal. Referring to the LST and NDVI map distribution, the notable rise of LST starts in August 2023, and the peak is in October 2023. Around 46% of areas in the Bondowoso regency are detected as hotspot areas, which had LST above 30<sup>o</sup>C in October 2023. El Nino affects the irrigated lands and rain-fed fields more than the plantations. The NDVI alteration data does not show that the Bondowoso Regency is experiencing extraordinary drought due to the short-term impact of El Nino. However, the emergence of numerous areas in the moderate NDVI category warns that stress affecting vegetation is starting to occur. Mitigation plans should be prepared for the long-term impact of El Nino, particularly in the hotspot areas. This study could be a comprehension tool for the government and farmers to prepare mitigation plans.

Regime shift of skeletal δ13C after 1997/1998 El Nino event in Porites coral from Green Island, Taiwan

The 1997/1998 El Niño event caused mass coral bleaching and mortality in many tropical and subtropical regions, including corals on Green Island, Taiwan, in the northwestern Pacific Ocean. This study analyzed coral carbon isotope ratios (δ13C), oxygen isotope ratios (δ18O), and Sr/Ca ratios for 29 years, including the 1997/1998 El Niño period, to examine how high water temperature events are recorded in coral geochemical indicators. Sr/Ca ratios in coral skeletons from Green Island show the lowest peak, means the highest temperature during the 1997/1998 El Niño period. However, we couldn’t observe high-temperature events on δ18O. Furthermore, a negative δ13C shift was observed after El Niño events. The regime shift of δ13C might have been caused by temporal bleaching and/or a decrease in symbiotic algae due to high water temperature stress under the continuous decrease in δ13C in DIC due to the Suess effect.

Impact of Enso on Indian Monsoon and Food Production

El Nino is a big ocean-atmosphere climate interaction It happens when Sea Temperatures (SST) warm up in central and eastern parts of the Equatorial Pacific. Whereas La Nina is the opposite event of it, when ocean SST cools down in those same areas. Together, El Nino and La Nina are known as the El Nino Southern Oscillation Index (O). Usually, El Nino brings warm and dry weather to southern & eastern inland regions of India, Australia, Indonesia, Philippines, Malaysia, and the central Pacific islands. The variations of Indian summer monsoon Rainfall (ISMR) are linked to changes in sea surface temperatures over the equatorial Pacific & Indian Oceans. ENSO events really affect summer rainfall in India and major droughts have faced during El Nino events. When El Nino kicks in, it often leads to weak monsoons & higher temperatures in India. This raises the chances of droughts, which could upset crop production & water supply in India. The lack of rain because of El Nino causes crop production to drop, especially short-duration Kharif crops. This situation can lead to higher inflation rates & slower GDP growth, since agriculture is such a huge part of India’s economy. Therefore, this paper provide information about how El Nino affects climate throughout various regions of India, especially regarding monsoons and growing food.

How Do Futures Contracts on Agricultural Commodities Respond to El Nino Weather Events?

This study examines how futures contracts on wheat, soybeans, corn and sugarcane respond to El Nino weather events over the period March 2010 to April 2024. We use the monthly ENSO forecast data from the Climate Prediction Center of the National Oceanic and Atmospheric Administration to benchmark the start of an El Nino forecast, which we define as the first reporting month in which a current or forecasted El Nino probability exceeds 50%. We examine two periods around each event: the six months leading up to the El Nino forecast, and the six months following the event date. We find that El Nino weather events have significant effects on commodity futures prices. Wheat, soybean and corn futures prices (expressed in dollars) generally decline after an El Nino forecast, consistent with improved harvests due to an increase in rain. We also find that El Nino events are associated with increased volatility in commodity futures markets. Our study can inform hedgers and speculators who participate in the agricultural derivatives markets, as well as policymakers who may be interested in initiating or adjusting any subsidies granted to farmers or food consumers, as compensation for price pressures.

Assessment of Drought Adaptation in Hevea Brasiliensis PB 260 Clone Seedlings During El Nino Events

Assessment of Drought Adaptation in Hevea Brasiliensis PB 260 Clone Seedlings During El Nino Events

Dynamics of Rice Imports in Indonesia: Analysis of Development, Causative Factors, Impacts and Solutions

This research aims to understand the development of rice imports, the factors driving rice imports, the impact of rice imports, and steps to increase production and reduce rice imports in Indonesia. This research uses a descriptive qualitative approach. Data collection uses secondary data from CNBC Indonesia YouTube news videos and rice import data from the Central Statistics Agency. The data analysis technique uses the Interactive Model from Miles et al. (2014). The research results show that based on data recorded at the Central Bureau of Statistics, Indonesia imported rice from 2000-2023 to maintain availability, strengthen rice reserves, anticipate El Nino events, and increase population. The impact of rice imports is to maintain the situation's stability, but if the policy is inappropriate, it can harm domestic farmers. Efforts that the government can make to increase production and reduce rice imports include implementing the steps successfully implemented by Cambodia, immediately creating a program to increase rice production, and focusing more on intensifying land productivity increases.

How to improve global environmental governance? Lessons learned from climate risk and climate policy uncertainty

Investigating the conduction mechanism between climate risk and climate policy uncertainty is crucial to enhance global environmental governance. The analysis uses the full- and sub-sample methodologies to recognise the correlation between Southern Oscillation Index (SOI) and U.S. climate policy uncertainty (CPU). The quantitative analysis shows favorable and adverse effects from SOI to CPU, where the La Nina phenomena accompany the positive impacts, and the negative influences are related to the El Nino events. This conclusion highlights that climate change risks would bring more uncertainties to climate policies in the U.S., which is not conducive to enhancing global environmental governance. In turn, CPU exerts an adverse impact on SOI during the Trump administration, suggesting that high uncertainty of U.S. climate policies weakens the ability to cope with the global climate crisis, intensifying climate change risks such as the occurrence of El Nino phenomena. Under the severe climate crisis and extreme weather background, this discussion would put forward significant lessons for improving global environmental governance by effectively preventing and responding to climate changes, ensuring the continuity and consistency of climate policies, and strengthening international cooperation on climate change.

Atmospheric CO2 Isotopic Variations, with Estimation of Ocean and Plant Source Contributions

This analysis uses both atmospheric CO2 concentrations and the accompanying δ13C isotopic measurements of CO2 over 40 years from 1978 to 2015 observed at ten different latitudes from 90° S to 82 °N. Atmospheric CO2 is separated into two components of CO2 attributable to deep ocean and to plant (including fossil fuel) sources. The isotopic values assigned to the two components are δ13C = 0‰ and −26‰, respectively. The latitude variations in residual source component CO2 show the ocean source component peaking at the equator. This contrasts with the residual plant source component that peaks in the Arctic Circle region. Seasonal comparisons show no change in the ocean component peaking at the equator and no significant changes in its variation with latitude, while the plant component shows seasonal changes of the order of 15 ppm at high latitudes. The ocean component shows clear anomalous behavior in the three years following the 1989 Pacific Ocean regime shift (a shift independently identified from the changed biological time series). By contrast, the residual plant component shows a correlation in the timing of maxima in its annual variations with the timing of El Nino events over the time span of 1985–2015. It also shows a discontinuity in annual variation coinciding with the 1995 AMO phase change. We conclude that the ocean and plant components of atmospheric CO2 relate to independent sources of atmospheric CO2 and have approximately equal magnitudes. The observations are consistent with a hypothesis that variations in the ocean components have an origin from upwelling water from deep ocean currents, and variations in plant components are dominated by a combination of fossil fuel CO2, phytoplankton productivity, and forest and peat fires, which primarily occur in the northern hemisphere.

Cause of Substantial Global Mean Sea Level Rise Over 2014–2016

AbstractGlobal mean sea level rose by 15 mm over June 2014 – May 2016. This rise is 7 mm larger than the 8 mm increase associated with the long‐term trend of 4 mm/yr estimated over 2006–2016. Using a combination of satellite gravimetry data and in situ measurements, we find that 20% of this rise is explained by ocean thermal expansion and 80% by an ocean mass increase, the latter being largely correlated with an equivalent terrestrial water storage (TWS) decrease. Half of the global ocean mass increase during that period can be attributed to the South American continent where we find a significant contribution of the TWS over the Amazon basin (5 mm). This TWS change between oceans and continents occurred during two El Nino events: one aborted in 2014–2015 and an extreme event in 2015–2016 which affected precipitation patterns, especially over the equatorial Pacific ocean and over South America.

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.

Space–time heterogeneity of drought characteristics in Sabah and Sarawak, East Malaysia: implications for developing effective drought monitoring and mitigation strategies

Natural calamities like droughts have harmed not just humanity throughout history but also the economy, food, agricultural production, flora, animal habitat, etc. A drought monitoring system must incorporate a study of the geographical and temporal fluctuation of the drought characteristics to function effectively. This study investigated the space–time heterogeneity of drought features across Sabah and Sarawak, East Malaysia. The Standardized Precipitation Index (SPIs) at timescales of 1-month, 3-months, and 6-months was selected to determine the spatial distribution of drought characteristics. Rainfall hydrographs for the area for 30 years between 1988 and 2017 have been used in this study. A total of six five-year sub-periods were studied, with an emphasis on the lowest and highest drought occurrence. The sub-periods were a division of the 30 years over an arbitrary continual division for convenience. The results showed that the sub-periods 1993–1997 and 2008–2012 had the highest and lowest comparative drought events. The drought conditions were particularly severe in Central and Eastern parts of East Malaysia, owing to El Nino events and the country's hilly terrain. Understanding how and when drought occurs can aid in establishing and developing drought mitigation strategies for the region.

Impact of El-Nino and La-Nina Episodes on Rainfall Variability and Crop Yield

El Nino and La Nina events have an impact on the Indian monsoon in terms of less rainfall than average and more rainfall in La Nina years. El-Nino events are more likely to see rainfall variability during the monsoon and depressions over the Bay of Bengal (July-August). ENSO is a disruption in ocean surface temperatures and atmospheric circulation over the Pacific Ocean leading to wide spread changes in rainfall/precipitation regimes around the world. El Nino years' effects on crop production in India as a result of lower rainfall during the south-west monsoon. In the kharif season (June to September), crops suffer from moisture and have lower yields in El-Nino years, but the opposite in La-Nina years. The El Nino is associate with the possibility of drought like situation at many occasions and La Nina is the opposite of El-Nino events.

Validation of Satellite Rainfall Product (GPM-IMERG) an Bali and Nusa Tenggara: A Comparison of Normal Seasons, El Nino and La Nina Events

Bali and Nusa Tenggara are regions where monsoonal wind changes and strange interactions between the ocean and atmosphere influence rainfall. The purpose of this research is to evaluate Integrated Multi-Satellite Retrievals for GPM (IMERG) rainfall data using in-situ observations from Bali and Nusa Tenggara, Indonesia, while considering seasonal variations and the El Nino-Southern Oscillation (ENSO) phenomenon. The study combines rainfall data from synoptic stations with rain gauge measurements over ten years, from January 2012 to December 2021, to obtain more accurate verification results. The study's findings indicate that, apart from the transitional seasons, IMERG data provides substantial estimates of monthly rainfall accumulation with low error values for both light and heavy rainfall. The study also reveals that the islands' complexity and topography can impact each province's validation values. The verification results show excellent accuracy in flat terrain areas and moderate elevations, while performance decreases in regions with high altitudes. These findings are significant because IMERG data can estimate rainfall for regions lacking monitoring stations during specific seasons and active ENSO conditions. Thus, this information can serve as a valuable tool to address the issue of data unavailability in hard-to-access areas and contribute to optimizing water resource management and weather-related disaster mitigation. Keywords: Validation, Rainfall, IMERG, ENSO

Pola Kebakaran Hutan di Areal Konservasi Studi Kasus di Taman Nasional Bromo Tengger Semeru

Forest fires are disasters that can occur due to environmental conditions that support one of them, such as El Nino events or extreme climatic conditions. One of the factors that influences the occurrence of extreme climates is rainfall. Forest fires in Indonesia are mostly caused by human activities, which are supported by extreme climatic conditions. Forest areas that have the potential to cause forest fires include conservation areas that are closely related to human activities. Conservation areas that are closely related to humans include the Bromo Tengger Semeru National Park (TNBTS). TNBTS has the function of a conservation area as well as a tourist area. The existence of humans who become tourists or visitors in conservation area locations creates opportunities for forest fires in conservation areas that are supported by extreme climatic conditions. TNBTS has a rainfall pattern, with the lowest rainfall occurring in May-Jun-Jul-Aug-Sept, while the highest is in Nov-Dec-Jan-Feb-Mar. When there is low rainfall, it can cause the TNBTS area to be prone to fire, so it is necessary to take preventive measures in the month before the dry season occurs. Prevention as an effort to control forest fires can be done by keeping the area tighter at the start of the dry season, namely in May. Based on hotspot data of fire incidents from 2001–2020, the most frequent occurrences were in other nationalities in 2001, 2014, and 2019. Based on the results of identification using data, not all hotspots can be declared fire incidents, but heat generated from the existing crater of Mount Semeru at the TNBTS location.
 Keywords: Bromo Tengger Semeru, Forest Fire, Conservation Area, Hotspot, National Park

The Impact of ENSO on the Precipitation in Iraq Regions

Abstract Precipitation is considered one of the important weather variables in determining the climate of any region in the world, and perhaps the precipitation in Iraq is witnessing an incomprehensible seasonal fluctuation. The work tries to identify the reasons for this fluctuation, from one season to another. The monthly average precipitation data in Iraq was obtained by Global Precipitation Climatology Project GPCP. Also, data for sea surface temperature anomalies (SST) for the four El Nino regions, as well as relative humidity and zonal wind speed were obtained from the National Centres for Environmental Prediction NCEP and National Centre for Atmospheric Research NCAR. The study period extended from 1980 to 2022, where the correlation of monthly precipitation average in Iraq with El Nino and La Niña events was tested, and it was found that there was a positive proportional effect of the El Nino event on the increase in rainfall rates in Iraq, the correlation coefficient R about 0.8 in North and Northern-East of Iraq. To explain this, the correlation between El Niño events, relative humidity, and zonal wind speed was tested. It was found that there is a proportional effect of El Nino on the relative humidity and an inverse effect on the zonal wind speed. Central and southern Iraq is less affected by El Niño and La Niña events, as the correlation coefficient of monthly precipitation average with El Niño phenomenon is approximately 0.5 to 0.6.

Multiyear versus single‐year El Niño events: Contrasting their impacts on South American seasonal precipitation

AbstractDifferences in the seasonal distribution of precipitation over South America (SA) associated with single‐year (SY) and multiyear (MY) El Niño (EN) events were analysed based on reanalysis data for the 1901–2012 period. The results suggest that Pacific Sea Surface Temperature (SST) anomalies associated with MY EN events interact with the tropical Atlantic and Indian Oceans SST from austral fall to spring, after the event's first year, affecting SA precipitation distribution in subsequent seasons. Compared to SY EN events, which reproduce well the north–south dipolar precipitation anomaly pattern over SA, the MY EN events show differences in the intensity and positioning of precipitation anomalies. Precipitation decreases over northern SA during all seasons are observed for SY and MY EN events except for differences in magnitudes. Variations in the position and longitudinal extension of the downward motions of Walker circulation in response to these events explain these differences. Over southern and southeastern SA, differences in anomaly positioning are more evident. The positive precipitation anomalies over these regions in the austral spring and summer are weakened and southward shifted during the MY EN in relation to those during SY EN events. These variations are associated with the Rossby‐wave train pattern path that depends on the EN and season. Consequently, the associated local atmospheric circulation patterns also depend on the season. The intense (weak) South American low‐level jet (SALLJ) for the first year of MY EN contrasts with the weak or inexistence (intense) SALLJ for the SY EN during summer (springer). Complementary to previous studies, the results indicate that the differences in the intensity and duration of the SY and MY EN events contribute to changes in the EN‐related atmospheric teleconnection pattern that impacts SA precipitation. The results can be useful for climate prediction and monitoring purposes.

Rainfall Anomaly and Its Effect on the Clove Productivity in Two Regions with Different Rain Pattern In Maluku

Clove production in Maluku fluctuates from year to year, one of which is influenced by rainfall anomalies. This study aimed of describing extreme rainfall events and analyzing the relations between rainfall and clove productivity in two areas with different rainfall patterns in Maluku. This study used a survey method by using interviews and Focus Group Discussions with several farmer respondents as well as collecting climatic data from related agencies. Data analysis was divided into rainfall data generation, rainfall analysis in extreme conditions, and regression analysis to assess the effect of rainfall on clove productivity. The results showed that a very extreme El Nino event caused a decrease in rainfall on Nusalaut Island by 1868 mm or 57% of its normal condition, and in Air Buaya District by 875 mm or 42% of its normal condition. Very extreme La Nina events caused rainfall to increase in Nusalaut Island by 2059 mm or 62% of its normal condition, and in Air Buaya District by 1193 mm or 37% of its normal condition. The results of the regression analysis showed that the value of the coefficient of determination (R²) for Nusalaut Island by 84.8% and for Air Buaya District by 70.8%; this shows that rainfall has a significant effect on clove productivity.

The Impact of Climate Change on the Productivity of Nutmeg (Myristica fragrans Houtt.) in Kamal Village, West Kairatu District

The research conducted in the village of Kamal, West Kairatu District, aims to prove that climate change has occurred and the relationship between climate and nutmeg productivity. The plant survey research used a random sampling method, the strata were determined based on the number of productive nutmeg plants, 30 samples of nutmeg plants were taken from 15 farmers. The analysis carried out was an analysis of rainfall under extreme conditions using rainfall data for the last 30 years (1992-2021 period) as well as an analysis of the relationship between rainfall and nutmeg productivity using regression analysis which tested using the Program Minitab 21. The results of the study showed that there was a deviation from extreme rainfall in Kamal village, namely the very extreme EL Nino event which caused rainfall in Kamal village to be 992 mm from normal conditions. a very extreme La Nina event caused rainfall in Kamal Village to increase by 1197 mm. The impact of climate change on the productivity of nutmeg in Kamal village is very closely related, namely the higher the rainfall, the higher the productivity of nutmeg, as indicated by the accuracy value of R2 = 82.1%.

Increasing risk of simultaneous occurrence of flash drought in major global croplands

Simultaneous occurrence of flash drought in major croplands can pose challenges for global food security. However, drivers of flash drought co-occurrence in the observed and future climate remain unrecognized. Using observations and climate model simulations, we examine the simultaneous occurrence of flash droughts in 16 major global croplands that grow wheat, rice, and maize. We show that significant warming combined with decreasing precipitation led to an increased frequency of flash droughts in several major croplands during the observed climate (1981–2020). The simultaneous occurrence of flash drought in many croplands in the same year has significantly (p-value = 0.007) increased during 1981–2020 and is likely to continue. Nine out of 16 major global croplands are projected to witness an increased frequency of flash droughts under the warming climate. The observed and projected rise in flash droughts in global croplands is mainly driven by vapor pressure deficit. The positive phase of El Nino Southern Oscillation influences flash drought co-occurrence in 10 out of 16 major cropland regions and remains a dominating factor of flash droughts co-occurrence in the future. Enhanced climate warming and increased frequency of El Nino events can further enhance the occurrence of simultaneous flash droughts in several major croplands, with substantial implications for food production.

A delay‐differential model for representing small pelagic fish stock dynamics and its application for assessing alternative management strategies under environmental uncertainty

AbstractWe present a novel adaptation of the classic discrete delay‐difference model, a continuous delay‐differential model (cDDM), which can adequately represent population dynamics of stocks that turn over rapidly and continuously over time (e.g., small pelagic fish, small tunas, and shrimps). We used the Northern‐Central Peruvian anchoveta stock (Engraulis ringens, Engraulidae) as a case study for implementing the cDDM and conducted a management strategy evaluation (MSE) through stochastic optimization in policy space (SOPS). Our results showed that cDDM integrated with SOPS efficiently searches optimum and near‐optimum harvest control rules (HCR) and is an alternative to pre‐setting arbitrary HCRs as in traditional MSE. The cDDM showed comparable stock biomass and recruitment estimate reconstructions to more complex stock assessment models described for anchoveta. We concluded that the anchoveta stock is sustainably managed and is an example of adaptive fisheries management under high ocean‐climate variability and uncertainty. Contrary to fishery textbooks, the anchoveta's collapse was not entirely due to the 1972 El Niño (EN) but a recruitment failure preceding EN. Our reconstructions revealed that low recruitment (or recruitment failure) could still occur at high stock biomass. Anchoveta's stock biomass is larger than pre‐collapse, likely due to favourable environmental conditions (a cooling trend) and management, despite more frequent and stronger EN events. SOPS quickly revealed that harvest strategies with large base biomass (>5 mmt) lead to higher interannual stock variability and would not produce substantial increases in long‐term yield. Alternative HCRs with lower base biomass, while adjusting for productivity regimes, have similar long‐term yields without affecting the long‐term average stock.