The 2018–2019 weak El Niño: Predicting the risk of a dengue outbreak in Machala, Ecuador

Sea surface temperature conditions in the central-eastern tropical Pacific indicated a mild El Ni&#241;o event in October 2018, which continued throughout the spring of 2019. The global El Ni&#241;o Southern Oscillation (ENSO) forecast consensus was that these generally weak warm patterns would persist at least until the end of the summer. El Ni&#241;o and its impact on local climatic conditions in southern coastal Ecuador influence the inter-annual transmission of dengue fever in the region. In this study, we use an ENSO model to issue forecasts of El Ni&#241;o for the year 2019, which are then used to predict local climate variables, precipitation and minimum temperature, in the city of Machala, Ecuador. All these forecasts are incorporated in a dengue transmission model, specifically developed and tested for this area, to produce out-of-sample predictions of dengue risk. Predictions are issued at the beginning of January 2019 for the whole year, thus providing the longest forecast lead time of 12 months. Preliminary results indicated that the mild El Ni&#241;o event did not provide the optimum climate conditions for dengue transmission, with the model predicting a very low probability of a dengue outbreak during the typical peak season in Machala in 2019. This is contrary to 2016, when a large El Ni&#241;o event resulted in excess rainfall and warmer temperatures in the region, and a dengue outbreak occurred 3 months earlier than expected. This event was successfully predicted using a similar prediction framework to the one applied here. With the present study, we continue our &#160;efforts to build and test a climate service tool to issue early warnings of dengue outbreaks in the region.

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A multi--criterion simulation model to determine dengue outbreaks

Computer Science ◽

10.7494/csci.2020.21.3.3819 ◽

2020 ◽

Vol 21 (3) ◽

Author(s):

Piotr Jakubowski ◽

Hasitha Erandi ◽

Anuradha Mahasinghe ◽

Sanjeewa Perera ◽

Andrzej Ameljańczyk

Keyword(s):

Sri Lanka ◽

Simulation Model ◽

Related Data ◽

Dengue Outbreak ◽

Western Province ◽

Dengue Transmission ◽

Dengue Outbreaks ◽

Outbreak Situation

In this study we develop a multi-criteria model to identify dengue outbreak periods. To validate the model, we perform simulation using dengue transmission related data in the Western Province, Sri Lanka. Our results indicate that the developed model can be used to predict the dengue outbreak situation in a given region upto one month.

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Using Seasonal Climate Variability Forecasts to Plan Forest Plantation Establishment

EDIS ◽

10.32473/edis-ae282-2004 ◽

1969 ◽

Vol 2004 (17) ◽

Author(s):

Norman Breuer ◽

Matthew Langholtz ◽

David Zierden ◽

Clyde Fraisse

Keyword(s):

Inventory Management ◽

Southern Oscillation ◽

Climatic Conditions ◽

Plantation Establishment ◽

Natural Forests ◽

University Of Florida ◽

Climate Conditions ◽

Seasonal Climate ◽

Pests And Diseases ◽

High Level

Atmospheric scientists are now able to predict seasonal climate variations, with a relatively high level of skill. Knowledge of climatic conditions allows us to develop a seasonal management strategy for forest plantations and managed natural forests. Areas of application include seedling establishment, preparing for pests and diseases, fire management, harvest schedules and inventory management. This publication provides strategies to consider for pine plantation establishment in Florida and southern Alabama and Georgia. Seasonal climate conditions can be better predicted for this region because it is affected by the El Niño Southern Oscillation (ENSO) phenomenon. This document is ABE354, one of a series of the Agricultural and Biological Department, Florida Cooperative Extension Service, Institute of Food and Sciences, University of Florida. Published November 2004. https://edis.ifas.ufl.edu/ae282

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El Niño modifies nutrient status in oil palm and helps foliage to recover from yellowing symptoms: new analysis and perspectives

Cahiers Agricultures ◽

10.1051/cagri/2021021 ◽

2021 ◽

Vol 30 ◽

pp. 34

Author(s):

Bernard Dubos ◽

Marcel de Raïssac

Keyword(s):

Oil Palm ◽

El Niño ◽

Magnesium Deficiency ◽

El Nino ◽

Southern Oscillation ◽

Weather Conditions ◽

Annual Rainfall ◽

Mineral Deficiency ◽

Local Climate ◽

Climate Conditions

In Ecuador, oil palm plantations from the Quinindé-Quevedo region are subject to El Niño/Southern Oscillation (ENSO) with a preponderance of La Niña weather conditions. With more than 2,000 mm, the total annual rainfall is theoretically non-limiting but, with only 1,000 h, the total annual sunshine is well below the 1,800 h minimum recommended. Starting in the 1970s, the frequent occurrence of frond yellowing symptoms in the region became a recurrent worry for growers, convinced that they were facing the expression of a mineral deficiency. In this study, we used experimental results to examine the actual role of mineral nutrition in yellowing manifestation. We described the effects of two El Niño events (1982/1983 and 1997/1998) on climate variables and analysed their putative consequences on palm physiological functioning that could explain the observed foliage recovery. Our analysis led us to conclude that a direct mineral deficiency was not involved, as the soil reserves for the main nutrients were not to blame. We rejected the most frequently proposed hypothesis, whereby yellowing is caused by magnesium deficiency. Our study revealed the key role played by nitrogen, the best indicator of yellowing. Variations in N status appear to be linked to the same factors that determine the symptoms and we opted for the hypothesis of physiological disruption generated by low solar radiation levels under normal conditions. The study also reveals the need to consider specific optimum contents for N and Mg and to adjust fertilizer recommendations to local climate conditions.

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Climate variation drives dengue dynamics

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1618558114 ◽

2016 ◽

Vol 114 (1) ◽

pp. 113-118 ◽

Cited By ~ 73

Author(s):

Lei Xu ◽

Leif C. Stige ◽

Kung-Sik Chan ◽

Jie Zhou ◽

Jun Yang ◽

...

Keyword(s):

Temporal Dynamics ◽

Southern China ◽

Transmission Rate ◽

Predictive Tool ◽

Climate Conditions ◽

Mosquito Abundance ◽

Dengue Transmission ◽

Reduction Strategies ◽

Dengue Outbreaks ◽

The City

Dengue, a viral infection transmitted between people by mosquitoes, is one of the most rapidly spreading diseases in the world. Here, we report the analyses covering 11 y (2005–2015) from the city of Guangzhou in southern China. Using the first 8 y of data to develop an ecologically based model for the dengue system, we reliably predict the following 3 y of dengue dynamics—years with exceptionally extensive dengue outbreaks. We demonstrate that climate conditions, through the effects of rainfall and temperature on mosquito abundance and dengue transmission rate, play key roles in explaining the temporal dynamics of dengue incidence in the human population. Our study thus contributes to a better understanding of dengue dynamics and provides a predictive tool for preventive dengue reduction strategies.

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Araucaria growth response to solar and climate variability in South Brazil

Annales Geophysicae ◽

10.5194/angeo-36-717-2018 ◽

2018 ◽

Vol 36 (3) ◽

pp. 717-729 ◽

Cited By ~ 7

Author(s):

Alan Prestes ◽

Virginia Klausner ◽

Iuri Rojahn da Silva ◽

Arian Ojeda-González ◽

Caren Lorensi

Keyword(s):

Climate Variability ◽

Tree Ring ◽

Growth Response ◽

Classical Method ◽

Southern Oscillation ◽

Ring Width ◽

The Sun ◽

Local Climate ◽

Climate Conditions ◽

Growth Series

Abstract. In this work, the Sun–Earth–climate relationship is studied using tree growth rings of Araucaria angustifolia (Bertol.) O. Kuntze collected in the city of Passo Fundo, located in the state of Rio Grande do Sul (RS), Brazil. These samples were previously studied by Rigozo et al. (2008); however, their main interest was to search for the solar periodicities in the tree-ring width mean time series without interpreting the rest of the periodicities found. The question arises as to what are the drivers related to those periodicities. For this reason, the classical method of spectral analysis by iterative regression and wavelet methods are applied to find periodicities and trends present in each tree-ring growth, in Southern Oscillation Index (SOI), and in annual mean temperature anomaly between the 24 and 44∘ S. In order to address the aforementioned question, this paper discusses the correlation between the growth rate of the tree rings with temperature and SOI. In each tree-ring growth series, periods between 2 and 7 years were found, possibly related to the El Niño/La Niña phenomena, and a ∼ 23-year period was found, which may be related to temperature variation. These novel results might represent the tree-ring growth response to local climate conditions during its lifetime, and to nonlinear coupling between the Sun and the local climate variability responsible to the regional climate variations. Keywords. History of geophysics (solar–planetary relationships) – meteorology and atmospheric dynamics (climatology; palaeoclimatology)

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Ecological specificities of the interaction between animal breeding and climate changes, caused by greenhouse gas emissions

Agricultural science and practice ◽

10.15407/agrisp4.03.062 ◽

2017 ◽

Vol 4 (3) ◽

pp. 62-72

Author(s):

O. Zhukorsky ◽

O. Nykyforuk ◽

N. Boltyk

Keyword(s):

Greenhouse Gases ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Climatic Conditions ◽

Animal Breeding ◽

Gas Emissions ◽

Climate Conditions ◽

Emissions Inventory ◽

Theoretical Substantiation ◽

Global Problems

Aim. Proper development of animal breeding in the conditions of current global problems and the decrease of anthropogenic burden on environment due to greenhouse gas emissions, caused by animal breeding activity, require the study of interaction processes between animal breeding and external climatic conditions. Methods. The theoretical substantiation of the problem was performed based on scientifi c literature, statistical informa- tion of the UN Food and Agriculture Organization and the data of the National greenhouse gas emissions inventory in Ukraine. Theoretically possible emissions of greenhouse gases into atmosphere due to animal breeding in Ukraine and specifi c farms are calculated by the international methods using the statistical infor- mation about animal breeding in Ukraine and the economic-technological information of the activity of the investigated farms. Results. The interaction between the animal breeding production and weather-and-climate conditions of environment was analyzed. Possible vectors of activity for the industry, which promote global warming and negative processes, related to it, were determined. The main factors, affecting the formation of greenhouse gases from the activity of enterprises, aimed at animal breeding production, were characterized. Literature data, statistical data and calculations were used to analyze the role of animal breeding in the green- house gas emissions in global and national framework as well as at the level of specifi c farms with the consid- eration of individual specifi cities of these farms. Conclusions. Current global problems require clear balance between constant development of sustainable animal breeding and the decrease of the carbon footprint due to the activity of animal breeding.

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Relationship between Relative Maturity and Grain Yield of Maize (Zea mays L.) Hybrids in Northwest New Mexico for the 2003–2019 Period

Agriculture ◽

10.3390/agriculture10070290 ◽

2020 ◽

Vol 10 (7) ◽

pp. 290

Author(s):

Koffi Djaman ◽

Curtis Owen ◽

Margaret M. West ◽

Samuel Allen ◽

Komlan Koudahe ◽

...

Keyword(s):

New Mexico ◽

Grain Yield ◽

Sprinkler Irrigation ◽

Growing Season ◽

Climatic Conditions ◽

Agricultural Science ◽

Production Optimization ◽

Science Center ◽

Early Season ◽

Climate Conditions

The highly variable weather under changing climate conditions affects the establishment and the cutoff of crop growing season and exposes crops to failure if producers choose non-adapted relative maturity that matches the characteristics of the crop growing season. This study aimed to determine the relationship between maize hybrid relative maturity and the grain yield and determine the relative maturity range that will sustain maize production in northwest New Mexico (NM). Different relative maturity maize hybrids were grown at the Agricultural Science Center at Farmington ((Latitude 36.69° North, Longitude 108.31° West, elevation 1720 m) from 2003 to 2019 under sprinkler irrigation. A total of 343 hybrids were grouped as early and full season hybrids according to their relative maturity that ranged from 93 to 119 and 64 hybrids with unknown relative maturity. The crops were grown under optimal management condition with no stress of any kind. The results showed non-significant increase in grain yield in early season hybrids and non-significant decrease in grain yield with relative maturity in full season hybrids. The relative maturity range of 100–110 obtained reasonable high grain yields and could be considered under the northwestern New Mexico climatic conditions. However, more research should target the evaluation of different planting date coupled with plant population density to determine the planting window for the early season and full season hybrids for the production optimization and sustainability.

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El Niño, La Niña, and the Forecastability of the Realized Variance of Heating Oil Price Movements

Sustainability ◽

10.3390/su13147987 ◽

2021 ◽

Vol 13 (14) ◽

pp. 7987

Author(s):

Mehmet Balcilar ◽

Elie Bouri ◽

Rangan Gupta ◽

Christian Pierdzioch

Keyword(s):

El Niño ◽

Predictive Value ◽

El Nino ◽

Southern Oscillation ◽

La Niña ◽

Realized Variance ◽

La Nina ◽

Out Of Sample ◽

Heating Oil ◽

Price Movements

We use the heterogenous autoregressive (HAR) model to compute out-of-sample forecasts of the monthly realized variance (RV) of movements of the spot and futures price of heating oil. We extend the HAR–RV model to include the role of El Niño and La Niña episodes, as captured by the Equatorial Southern Oscillation Index (EQSOI). Using data from June 1986 to April 2021, we show evidence for several model configurations that both El Niño and La Niña phases contain information useful for forecasting subsequent to the realized variance of price movements beyond the predictive value already captured by the HAR–RV model. The predictive value of La Niña phases, however, seems to be somewhat stronger than the predictive value of El Niño phases. Our results have important implications for investors, as well as from the perspective of sustainable decisions involving the environment.

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The effects of ENSO, climate change and human activities on the water level of Lake Toba, Indonesia: a critical literature review

Geoscience Letters ◽

10.1186/s40562-021-00191-x ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Hendri Irwandi ◽

Mohammad Syamsu Rosid ◽

Terry Mart

Keyword(s):

Climate Change ◽

Water Level ◽

Human Activities ◽

Southern Oscillation ◽

Climatic Conditions ◽

Water Levels ◽

Dominant Factor ◽

Climate Projections ◽

Continuous Increase ◽

The Future

AbstractThis research quantitatively and qualitatively analyzes the factors responsible for the water level variations in Lake Toba, North Sumatra Province, Indonesia. According to several studies carried out from 1993 to 2020, changes in the water level were associated with climate variability, climate change, and human activities. Furthermore, these studies stated that reduced rainfall during the rainy season due to the El Niño Southern Oscillation (ENSO) and the continuous increase in the maximum and average temperatures were some of the effects of climate change in the Lake Toba catchment area. Additionally, human interventions such as industrial activities, population growth, and damage to the surrounding environment of the Lake Toba watershed had significant impacts in terms of decreasing the water level. However, these studies were unable to determine the factor that had the most significant effect, although studies on other lakes worldwide have shown these factors are the main causes of fluctuations or decreases in water levels. A simulation study of Lake Toba's water balance showed the possibility of having a water surplus until the mid-twenty-first century. The input discharge was predicted to be greater than the output; therefore, Lake Toba could be optimized without affecting the future water level. However, the climate projections depicted a different situation, with scenarios predicting the possibility of extreme climate anomalies, demonstrating drier climatic conditions in the future. This review concludes that it is necessary to conduct an in-depth, comprehensive, and systematic study to identify the most dominant factor among the three that is causing the decrease in the Lake Toba water level and to describe the future projected water level.

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Skill assessment of post-processing methods for ECMWF SEAS5 seasonal forecasts over Europe

10.5194/egusphere-egu21-11019 ◽

2021 ◽

Author(s):

Alice Crespi ◽

Marcello Petitta ◽

Lucas Grigis ◽

Paola Marson ◽

Jean-Michel Soubeyroux ◽

...

Keyword(s):

Large Scale ◽

Production Management ◽

Spatial Scales ◽

Research Field ◽

Skill Assessment ◽

Post Processing ◽

Seasonal Forecasts ◽

Climate Services ◽

Local Climate ◽

Climate Conditions

Seasonal forecasts provide information on climate conditions several months ahead and therefore they could represent a valuable support for decision making, warning systems as well as for the optimization of industry and energy sectors. However, forecast systems can be affected by systematic biases and have horizontal resolutions which are typically coarser than the spatial scales of the practical applications. For this reason, the reliability of forecasts needs to be carefully assessed before applying and interpreting them for specific applications. In addition, the use of post-processing approaches is recommended in order to improve the representativeness of the large-scale predictions of regional and local climate conditions. The development and evaluation downscaling and bias-correction procedures aiming at improving the skills of the forecasts and the quality of derived climate services is currently an open research field. In this context, we evaluated the skills of ECMWF SEAS5 forecasts of monthly mean temperature, total precipitation and wind speed over Europe and we assessed the skill improvements of calibrated predictions.For the calibration, we combined a bilinear interpolation and a quantile mapping approach to obtain corrected monthly forecasts on a 0.25&#176;x0.25&#176; grid from the original 1&#176;x1&#176; values. The forecasts were corrected against the reference ERA5 reanalysis over the hindcast period 1993&#8211;2016. The processed forecasts were compared over the same domain and period with another calibrated set of ECMWF SEAS5 forecasts obtained by the ADAMONT statistical method.The skill assessment was performed by means of both deterministic and probabilistic verification metrics evaluated over seasonal forecasted aggregations for the first lead time. Greater skills of the forecast systems in Europe were generally observed in spring and summer, especially for temperature, with a spatial distribution varying with the seasons. The calibration was proved to effectively correct the model biases for all variables, however the metrics not accounting for bias did not show significant improvements in most cases, and in some areas and seasons even small degradations in skills were observed.The presented study supported the activities of the H2020 European project SECLI-FIRM on the improvement of the seasonal forecast applicability for energy production, management and assessment.

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