scholarly journals Assessing Biogeography of Coffee Rust Risk in Brazil as Affected by the El Niño Southern Oscillation

Plant Disease ◽  
2020 ◽  
Vol 104 (4) ◽  
pp. 1013-1018 ◽  
Author(s):  
F. D. Hinnah ◽  
P. C. Sentelhas ◽  
M. L. Gleason ◽  
P. M. Dixon ◽  
X. Zhang
Keyword(s):  
Relative Humidity ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Weather Conditions ◽  
Minas Gerais ◽  
Coffee Rust ◽  
Minas Gerais State ◽  
The World ◽  
Sst Anomaly

The El Niño Southern Oscillation (ENSO) is an oceanic-atmospheric phenomenon influencing worldwide weather and climate. Its occurrence is determined by the sea surface temperature (SST) anomaly of the 3.4 Niño region in the Pacific Ocean (5°N–5°S, 120°–170°W). El Niño (EN), Neutral (NT), and La Niña (LN) are the three possible phases of ENSO, respectively, for warm, normal, and cold SST anomaly. As in other regions around the world, weather in Brazil is influenced by ENSO phases. The country is the major coffee producer in the world, and production is strongly influenced by weather conditions, which affect plant yield, harvest quality, and interactions with pests and diseases. Coffee leaf rust (CLR), caused by the fungus Hemileia vastatrix, is a major cause of coffee yield and quality losses in Brazil, and requires fungicide spray applications every season. Because CLR is highly influenced by weather conditions, it is possible to use weather variables to simulate its progress during the cropping cycle. Therefore, the aims of this study were to estimate CLR infection rate based on a validated empirical model, which has daily minimum air temperature and relative humidity as inputs, and to assess the extent of ENSO influence on the annual risk of this disease at 45 sites in Brazil. Cumulative infection rates (CIR) were estimated daily from October to June of each growing season and location, based on the prevailing ENSO phase. Differences between the extreme phases (EN-LN) were assessed by the Two-One-Sided-Tests (TOST) method. Analysis of data from eight sites, located mainly in Paraná State, provided evidence of CIR differences between EN and LN phases (G1). Evidence of no difference of CIR between EN and LN was found in 18 sites (G2), whereas 19 sites showed no evidence of differences (G3) due to relatively large variation of CIR within the same ENSO phase. The G1 sites are located mostly in Southern Brazil, where ENSO exerts a well-defined influence on rainfall regime. In contrast, the G2 sites are mainly in Minas Gerais State, which is characterized as a transition region for ENSO influence on rainfall. The G3 sites are located between the northern region of Minas Gerais State and southern region of Bahia State, which is characterized by a subhumid climate that is usually very dry during winter, and where rainfall can vary up to 300% from one year to another, influencing relative humidity and resulting in a high CIR variability. Therefore, ENSO had a well-defined influence on CIR only in Paraná State, a region with minor importance for coffee production in Brazil. No ENSO influence was found in more northerly zones where the majority of Brazilian coffee is produced. This is the first evidence of ENSO-linked regional impact on the risk of coffee rust.

scholarly journals El Niño–Southern Oscillation and Associated Climatic Conditions around the World during the Latter Half of the Twenty-First Century

2018 ◽  
Vol 31 (15) ◽  
pp. 6189-6207 ◽  
Author(s):  
Scott B. Power ◽  
François P. D. Delage
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Precipitation Variability ◽  
Climatic Conditions ◽  
First Century ◽  
The Pacific ◽  
The World ◽  
Projected Changes ◽  
Mean State

Increases in greenhouse gas emissions are expected to cause changes both in climatic variability in the Pacific linked to El Niño–Southern Oscillation (ENSO) and in long-term average climate. While mean state and variability changes have been studied separately, much less is known about their combined impact or relative importance. Additionally, studies of projected changes in ENSO have tended to focus on changes in, or adjacent to, the Pacific. Here we examine projected changes in climatic conditions during El Niño years and in ENSO-driven precipitation variability in 36 CMIP5 models. The models are forced according to the RCP8.5 scenario in which there are large, unmitigated increases in greenhouse gas concentrations during the twenty-first century. We examine changes over much of the globe, including 25 widely spread regions defined in the IPCC special report Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX). We confirm that precipitation variability associated with ENSO is projected to increase in the tropical Pacific, consistent with earlier research. We also find that the enhanced tropical Pacific variability drives ENSO-related variability increases in 19 SREX regions during DJF and in 18 during JJA. This externally forced increase in ENSO-driven precipitation variability around the world is on the order of 15%–20%. An increase of this size, although substantial, is easily masked at the regional level by internally generated multidecadal variability in individual runs. The projected changes in El Niño–driven precipitation variability are typically much smaller than projected changes in both mean state and ENSO neutral conditions in nearly all regions.

scholarly journals Use of a Genesis Potential Index to Diagnose ENSO Effects on Tropical Cyclone Genesis

2007 ◽  
Vol 20 (19) ◽  
pp. 4819-4834 ◽  
Author(s):  
Suzana J. Camargo ◽  
Kerry A. Emanuel ◽  
Adam H. Sobel
Keyword(s):  
Tropical Cyclone ◽  
Relative Humidity ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Vertical Wind Shear ◽  
Vertical Shear ◽  
Interannual Variations ◽  
Genesis Potential Index ◽  
Potential Index

Abstract ENSO (El Niño–Southern Oscillation) has a large influence on tropical cyclone activity. The authors examine how different environmental factors contribute to this influence, using a genesis potential index developed by Emanuel and Nolan. Four factors contribute to the genesis potential index: low-level vorticity (850 hPa), relative humidity at 600 hPa, the magnitude of vertical wind shear from 850 to 200 hPa, and potential intensity (PI). Using monthly NCEP Reanalysis data in the period of 1950–2005, the genesis potential index is calculated on a latitude strip from 60°S to 60°N. Composite anomalies of the genesis potential index are produced for El Niño and La Niña years separately. These composites qualitatively replicate the observed interannual variations of the observed frequency and location of genesis in several different basins. This justifies producing composites of modified indices in which only one of the contributing factors varies, with the others set to climatology, to determine which among the factors are most important in causing interannual variations in genesis frequency. Specific factors that have more influence than others in different regions can be identified. For example, in El Niño years, relative humidity and vertical shear are important for the reduction in genesis seen in the Atlantic basin, and relative humidity and vorticity are important for the eastward shift in the mean genesis location in the western North Pacific.

scholarly journals Climatic Risk Zoning for Potential Occurrence of Cacao Moniliasis Disease in Northeastern Brazil Under The Influence of ENSO Phases

2021 ◽  
Author(s):  
Ícaro Monteiro Galvão ◽  
Gislaine Silva Pereira ◽  
Paulo Sentelhas
Keyword(s):  
Relative Humidity ◽  
Latin American ◽  
Air Temperature ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
The State ◽  
Northeastern Brazil ◽  
Cocoa Production ◽  
Enso Phases

Abstract Air temperature and relative humidity are the main drivers of many fungal diseases, such as moniliasis (Moniliophthora roreri), which affects cocoa production worldwide. This disease occurs in some Latin American countries; however, it has not yet occurred in Brazil. Moniliasis could cause serious damage to the Brazilian cocoa production if present in the country. Therefore, to know the risks of moniliasis to cocoa production in the largest Brazilian producing region, in the state of Bahia, this study investigated the climatic favorability for the occurrence of this disease in this state, by defining and mapping the climatic risks and by assessing the influence of El Niño Southern Oscillation (ENSO) phases on it. Daily air temperature and relative humidity data from 28 weather stations of the national weather network in the state of Bahia, between 1988 and 2018, were employed to determine the risk index for cocoa moniliasis occurrence (RICM), based on the number of days favorable to the disease, which was categorized in five levels of favorability, ranging from “unfavorable” to “very favorable”. Seasonal and annual RICM maps were generated by a multiple linear regression procedure, considering raster layers of latitude, longitude, and altitude. The maps showed a high spatial and temporal RICM variability in the state of Bahia, with the highest risk for moniliasis occurrence in the eastern part of the state, where most producing areas are located. The ENSO phase showed to influence cocoa moniliasis occurrence, with the years with a transition between El Niño and Neutral phases being the most critical for this disease in majority of assessed locations. These results show that cocoa producers in the state of Bahia, Brazil, should be concerned with moniliasis occurrence as a potential disease for their crops, mainly in the traditional producing regions and when ENOS is in a transition from El Niño to Neutral.

scholarly journals The Predictability of Interdecadal Changes in ENSO Activity and ENSO Teleconnections

2006 ◽  
Vol 19 (19) ◽  
pp. 4755-4771 ◽  
Author(s):  
Scott Power ◽  
Malcolm Haylock ◽  
Rob Colman ◽  
Xiangdong Wang
Keyword(s):  
Time Scales ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
La Niña ◽  
Enso Teleconnections ◽  
La Nina ◽  
Sst Anomaly ◽  
The Relationship ◽  
Interdecadal Changes

Abstract El Niño–Southern Oscillation (ENSO) in a century-long integration of a Bureau of Meteorology Research Centre (BMRC) coupled general circulation model (CGCM) drives rainfall and temperature changes over Australia that are generally consistent with documented observational changes: dry/hot conditions occur more frequently during El Niño years and wet/mild conditions occur more frequently during La Niña years. The relationship between ENSO [as measured by Niño-4 or the Southern Oscillation index (SOI), say] and all-Australia rainfall and temperature is found to be nonlinear in the observations and in the CGCM during June–December: a large La Niña sea surface temperature (SST) anomaly is closely linked to a large Australian response (i.e., Australia usually becomes much wetter), whereas the magnitude of an El Niño SST anomaly is a poorer guide to how dry Australia will actually become. Australia tends to dry out during El Niño events, but the degree of drying is not as tightly linked to the magnitude of the El Niño SST anomaly. Nonlinear or asymmetric teleconnections are also evident in the western United States/northern Mexico. The implications of asymmetric teleconnections for prediction services are discussed. The relationship between ENSO and Australian climate in both the model and the observations is strong in some decades, but weak in others. A series of decadal-long perturbation experiments are used to show that if these interdecadal changes are predictable, then the level of predictability is low. The model’s Interdecadal Pacific Oscillation (IPO), which represents interdecadal ENSO-like SST variability, is statistically linked to interdecadal changes in ENSO’s impact on Australia during June–December when ENSO’s impact on Australia is generally greatest. A simple stochastic model that incorporates the nonlinearity above is used to show that the IPO [or the closely related Pacific Decadal Oscillation (PDO)] can appear to modulate ENSO teleconnections even if the IPO–PDO largely reflect unpredictable random changes in, for example, the relative frequency of El Niño and La Niña events in a given interdecadal period. Note, however, that predictability in ENSO-related variability on decadal time scales might be either underestimated by the CGCM, or be too small to be detected by the modest number of perturbation experiments conducted. If there is a small amount of predictability in ENSO indices on decadal time scales, and there may be, then the nonlinearity described above provides a mechanism via which ENSO teleconnections could be modulated on decadal time scales in a partially predictable fashion.

scholarly journals A Verified Estimation of the El Niño Index Niño-3.4 since 1877

2009 ◽  
Vol 22 (14) ◽  
pp. 3979-3992 ◽  
Author(s):  
Lucia Bunge ◽  
Allan J. Clarke
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Correlation Coefficients ◽  
Sea Surface ◽  
Monthly Time Series ◽  
Sst Anomaly

Abstract Decadal and longer time-scale variabilities of the best known El Niño–Southern Oscillation (ENSO) indexes are poorly correlated before 1950, and so knowledge of interdecadal variability and trend in ENSO indexes is dubious, especially before 1950. To address this problem, the authors constructed and compared physically related monthly ENSO indexes. The base index was El Niño index Niño-3.4, the sea surface temperature (SST) anomaly averaged over the equatorial box bounded by 5°N, 5°S, 170°W, and 120°W; the authors also constructed indexes based on the nighttime marine air temperature over the Niño-3.4 region (NMAT3.4) and an equatorial Southern Oscillation index (ESOI). The Niño-3.4 index used the “uninterpolated” sea surface temperature data from the Second Hadley Centre Sea Surface Temperature dataset (HadSST2), a dataset with smaller uncertainty and better geographical coverage than others. In constructing the index, data at each point for a given month were weighted to take into account the typical considerable spatial variation of the SST anomaly over the Niño-3.4 box as well as the number of observations at that point for that month. Missing monthly data were interpolated and “noise” was reduced by using the result that Niño-3.4 has essentially the same calendar month amplitude structure every year. This 12-point calendar month structure from April to March was obtained by an EOF analysis over the last 58 yr and then was fitted to the entire monthly time series using a least squares approach. Equivalent procedures were followed for NMAT3.4 and ESOI. The new ESOI uses Darwin atmospheric pressure in the west and is based on theory that allows for variations of the atmospheric boundary layer depth across the Pacific. The new Niño-3.4 index was compared with NMAT3.4, the new ESOI, and with a record of δ18O from a coral at Palmyra, an atoll inside the region Niño-3.4 (Cobb et al.). Correlation coefficients between Niño-3.4 and the three monthly indexes mentioned above before 1950 are 0.84, 0.87, 0.73 and 0.93, 0.86, 0.73 for decadal time scales. These relatively high correlation coefficients between physically related but independent monthly time series suggest that this study has improved knowledge of low-frequency variability. All four indexes are consistent with a rise in Niño-3.4 SST and the weakening of the equatorial Pacific winds since about 1970.

scholarly journals El-Niño southern oscillation and rainfall erosivity in the headwater region of the Grande River Basin, Southeast Brazil

2011 ◽  
Vol 8 (6) ◽  
pp. 10707-10738 ◽  
Author(s):  
C. R. Mello ◽  
L. D. Norton ◽  
N. Curi ◽  
S. N. M. Yanagi ◽  
A. M. Silva
Keyword(s):  
River Basin ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Minas Gerais ◽  
Rainfall Pattern ◽  
Rainfall Erosivity ◽  
Rainfall Events ◽  
Rainfall Depth ◽  
Erosive Rainfall

Abstract. Relationships between regional climate and oceanic and atmospheric anomalies are important tools in order to promote the development of models for predicting rainfall erosivity, especially in regions with substantial intra-annual variability in the rainfall regime. In this context, this work aimed to analyze the rainfall erosivity in headwaters of Grande River Basin, Southern Minas Gerais State, Brazil. This study considered the two most representative environments, the Mantiqueira Range (MR) and Plateau of Southern Minas Gerais (PSM). These areas are affected by the El Nino Southern Oscillation (ENSO) indicators Sea Surface Temperature (SST) for Niño 3.4 Region and Multivariate ENSO Index (MEI). Rainfall erosivity was calculated for individual rainfall events from January 2006 to December 2010. The analyses were conducted using the monthly data of ENSO indicators and the following rainfall variables: rainfall erosivity (EI30), rainfall depth (P), erosive rainfall depth (E), number of rainfall events (NRE), number of erosive rainfall events (NEE), frequency of occurrence of an early rainfall pattern (EP), occurrence of late rainfall pattern (LP) and occurrence of intermediate rainfall patter (IP). Pearson's coefficient of correlation was used to evaluate the relationships between the rainfall variables and SST and MEI. The coefficients of correlation were significant for SST in the PSM sub-region. Correlations between the rainfall variables and negative oscillations of SST were also significant, especially in the MR sub-region, however, the Person's coefficients were lesser than those obtained for the SST positive oscillations. The correlations between the rainfall variables and MEI were also significant but lesser than the SST correlations. These results demonstrate that SST positive oscillations play a more important role in rainfall erosivity, meaning they were more influenced by El-Niño episodes. Also, these results have shown that the ENSO variables have potential to be useful for rainfall erosivity forecasting in this region.

scholarly journals El-Nino/Southern Oscillation (ENSO): Recent Evolution and Possibilities for Long Range Flow Forecasting in the Brahmaputra-Jamuna River

2013 ◽  
Vol 8 (3) ◽  
pp. 179-185 ◽  
Keyword(s):  
Long Range ◽  
El Niño ◽  
Stream Flow ◽  
Lead Time ◽  
El Nino ◽  
Southern Oscillation ◽  
Flood Forecasting ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
The World

The El Nino-Southern Oscillation is the dominant pattern of short-term climate variation, and is therefore of great importance in climate studies. Some recent studies showed the teleconnection between stream flow and the El-Nino Southern Oscillation (ENSO) of the equatorial Pacific Ocean. This paper presents an overview of the relationship between ENSO and stream flow in the Brahmaputra-Jamuna and the potential for wet season flow forecasting. This seasonal forecast of stream flow is very invaluable to the management of land and water resources, particularly in Bangladesh to improve the predictability of severe flooding. Over the years, large investments have been made to build physical infrastructure for flood protection, but it has been proved that it is not feasible, both economically and technically, to adopt solely structural mitigation approach. The choice of non-structural measures in this country focused mainly on flood forecasting because many of the nonstructural measures including flood plain zoning, compulsory acquisition of flood prone land, relocation etc have also been proved inappropriate for Bangladesh. The aim of this research is to find out an effective and long-lead flow forecasting method with lead time greater than hydrological time scale, using El Nino-Southern Oscillation index. Some studies indicate that SST can be predicted one to two years in advance using several ocean/ coupled ocean atmosphere models, therefore the ability to predict flow patterns in rivers will be highly enhanced if a strong relationship between river discharge and ENSO exists, and is quantified. With this view, to assess the strength of teleconnection between river flow and ENSO, at first correlation analyses between ENSO indices of any year and wet season flow of that year have been done. Here sea surface temperature (SST) has been used as ENSO index. This correlation analysis demonstrates a noteworthy relationship between natural variability of average flow of the months July-August-September (JAS) of the Brahmaputra-Jamuna River with SST of the corresponding months. Then discriminant prediction approach, also known as “Categoric Prediction” has been used here for the assessment of long range flood forecasting possibilities. This approach will be able to forecast the category of flow (high, average or low) using the category of predictor (predicted SST) at a sufficient lead time. In order to judge the forecast skill, a synoptic parameter “Forecasting Index” has also been used. This discriminant approach will improve the forecasting lead-time while the hydrologic forecast through rainfall-runoff modeling could provide a lead time on the order of the basin response time, which is several days or so. As the Ganges–Brahmaputra river basin is one of the most populous river basins of the world and is occupied by some developing countries of the world like Bangladesh, any reduction in the uncertainty about the flood in the Brahmaputra-Jamuna River would contribute a lot to the improvement in flow forecasting as well as to the economic development of the country.

scholarly journals Climatological Variability of Fire Weather in Australia

2018 ◽  
Vol 57 (2) ◽  
pp. 221-234 ◽  
Author(s):  
Andrew J. Dowdy
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Weather Conditions ◽  
Fire Season ◽  
Fire Weather ◽  
Clear Trend ◽  
Climatological Variability ◽  
In Fire

AbstractLong-term variations in fire weather conditions are examined throughout Australia from gridded daily data from 1950 to 2016. The McArthur forest fire danger index is used to represent fire weather conditions throughout this 67-yr period, calculated on the basis of a gridded analysis of observations over this time period. This is a complementary approach to previous studies (e.g., those based primarily on model output, reanalysis, or individual station locations), providing a spatially continuous and long-term observations-based dataset to expand on previous research and produce climatological guidance information for planning agencies. Long-term changes in fire weather conditions are apparent in many regions. In particular, there is a clear trend toward more dangerous conditions during spring and summer in southern Australia, including increased frequency and magnitude of extremes, as well as indicating an earlier start to the fire season. Changes in fire weather conditions are attributable at least in part to anthropogenic climate change, including in relation to increasing temperatures. The influence of El Niño–Southern Oscillation (ENSO) on fire weather conditions is found to be broadly consistent with previous studies (indicating more severe fire weather in general for El Niño conditions than for La Niña conditions), but it is demonstrated that this relationship is highly variable (depending on season and region) and that there is considerable potential in almost all regions of Australia for long-range prediction of fire weather (e.g., multiweek and seasonal forecasting). It is intended that improved understanding of the climatological variability of fire weather conditions will help lead to better preparedness for risks associated with dangerous wildfires in Australia.

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