South Oscillation Research Articles

A New ENSO Statistical Prediction Model considering Extratropical Effects and Its Application to the Prediction of the 2015/16 El Niño Event

Abstract Understanding the evolution mechanisms and providing accurate predictions for ENSO continue to be a challenge for the research community. In recent years, some studies pointed out that the extratropical Pacific atmosphere and ocean variations may affect the evolution of ENSO, which is different from the classical theoretical framework of ENSO. In this study, by combining tropical atmosphere and ocean predictors with extratropical precursors, an ENSO statistical prediction model was constructed. It was found that including extratropical predictors can significantly enhance the prediction skills of the model. The Victoria mode index (VMI) can significantly improve the prediction skills in the 10–12-month lead model and can effectively help the model cross the spring predictability barrier (SPB). When predicting 6–8 months in advance, the South Pacific Oscillation index (SPOI) can improve the prediction skills, but the degree of the improvement is relatively small. The model was also applied to conduct prediction experiments on the 2015/16 El Niño event. It was found that the model can successfully predict the event nearly 1 year in advance, mainly due to the inclusion of the VMI. Due to the interdecadal variation in the relationship between predictors and ENSO, when constructing the 6-month lead model, using data since 2000 and replacing the 6-month lead VMI with a 10-month lead, one can effectively improve the model’s prediction skills, especially in predicting the intensity of 2015/16 El Niño events, which has shown significant improvement.

Chile Niño/Niña in the coupled model intercomparison project phases 5 and 6

The north and central coast of Chile is influenced by El Niño-Southern Oscillation (ENSO) through oceanic and atmospheric teleconnections. However, it also experiences episodic oceanic warmings off central Chile (30°S) lasting a few months that are not necessarily associated with ENSO. These episodes, called “Chile Niño” events, besides their ecological and socio-economical impacts, have also the potential to influence tropical Pacific variability. Here, we investigate how realistically the models in the Coupled Model Intercomparison Project (CMIP, Phases 5 and 6) simulate Chile Niño/Niña (CN) events, and quantify their changes under anthropogenic forcing. Despite limitations of the global models in simulating realistically coastal upwelling dynamics, we show that they simulate reasonably well the observed spatial pattern, amplitude and seasonal evolution of CN events. They however fail to properly represent the positive skewness from observations. The analysis of a sub-group of models (36) that simulate ENSO realistically reveals that CN events increase in amplitude and variance in the future climate with no changes in their frequency of occurence. This is interpreted as resulting from compensating effects amongst changes in remote drivers and local feedbacks. In particular, ENSO variance increases while that of the South Pacific Oscillation decreases. Conversely, we found that while the Wind-Evaporation-SST feedback tends to increase and the coupling between mixed-layer depth and SST weakens, favoring the development of CN events, the thermocline and wind-SST feedbacks decrease. However, only the change in the thermocline feedback is correlated to changes in CN variance amongst the models, suggesting a dominant role of local oceanic stratification changes in constraining the sensitivity of CN to global warming.

Evaluation of the PM2.5 concentrations in South America: Climatological patterns and trend analysis

This study assessed the concentration of particulate matter with an aerodynamic diameter of 2.5 (PM2.5) over South America (SA) based on climatological patterns and trend analysis. This study used monthly PM2.5 data from the Copernicus Atmosphere Monitoring Service (CAMS) at the European Centre for Medium-range Weather Forecasts from 2003 to 2022. The bilinear interpolation method was applied to the data resampling from 0.75° × 0.75°–0.25° × 0.25° spatial resolution, and subsequently, the climatological analysis was performed on seasonal and annual scales of PM2.5 concentrations for the 20-year series. The assessment comprised three main stages: 1) descriptive statistics, 2) seasonal and annual climatology patterns, and 3) trend analysis (Mann-Kendall - MK and Pettitt tests). Results indicated that the largest annual PM2.5 concentrations were found in the Amazon region and northern Paraguay due the El-Niño South Oscillation events (2003–2005, 2007, 2010, 2020, and 2022). The annual average PM2.5 concentrations exceeded the WHO recommended limit (5 μg m−3), ranging from 15.57 μg m−3 (1999) and 22.74 μg m−3 (2007 and 2010). The highest PM2.5 concentrations were observed in the Amazon and Chile (Santiago), reaching 160.4 μg m−3 annually and 177.8 μg m−3 seasonally (spring). Elevated seasonal PM2.5 concentrations were attributed to increased deforestation and wildfires associated with meteorological systems such as the Bolivian high and subtropical jets during dry periods (winter and spring). The MK test revealed a significant reduction in PM2.5 concentrations between 2003 and 2022, observed in Argentina (north), Brazil (arc of reforestation), Bolivia (south), and Chile (north). Reduction values varied between 0.5 and 10 μg m−3.year−1 annually and during winter, attributed to no-tillage practices in regions cultivating commodities. The Pettitt test also identified significant structural changes occurring in 2006–2008 and 2010–2011, aligning with areas highlighted in the MK test. This study provides valuable insights for air quality and environmental monitoring managers to mitigate PM2.5 pollution in SA.

The Interdecadal Changes in the Spatial Structure of the South Pacific Oscillation and Its Implication for ENSO Diversity

Abstract The South Pacific Oscillation (SPO), characterized by a north–south dipole-like pattern of sea level pressure anomalies, is one of the key factors in understanding tropical–extratropical interactions in the South Pacific. We show that in boreal summer (June–August), the center of the northern lobe sea level pressure anomalies in the SPO is shifted to the east gradually after the 1960–70s. This study focuses on the relationship between the boreal summer SPO and following winter El Niño–Southern Oscillation (ENSO) diversity before and after the eastward shift of the SPO’s subtropical lobe. The eastward shift of the SPO’s subtropical lobe altered both the seasonal footprint mechanism and the trade wind charging mechanism associated with the SPO and thus profoundly influenced the ENSO diversity. It is revealed that when the northern lobe of the SPO shifts to the west of its average location, it tends to strengthen the eastern Pacific (EP) El Niño mainly via the seasonal footprint mechanism. But after the SPO’s northern lobe shifts to the east of its average location, it tends to promote the development of central Pacific (CP) El Niño mainly via the trade wind charging mechanism. The changes in the spatial structure of convection over the tropical Pacific and Indian Oceans may be one of the possible causes for the eastward shift in the SPO’s northern lobe. The findings in the present study have implications for a better understanding of ENSO diversity. Significance Statement Previous studies have demonstrated that the South Pacific Oscillation (SPO), as an important El Niño–Southern Oscillation (ENSO) precursor in the South Pacific, has the potential to provide an enhancement of the prediction of specific ENSO flavor. However, the historical variation in the SPO’s spatial structure and related changes in the relationship with the diversity of ENSO are still unclear. In this paper, we show that the subtropical lobe of the boreal summer (June–August) SPO is shifted to the east gradually after the 1960–70s. The changes in the spatial structure have also altered both the seasonal footprint mechanism and the trade wind charging mechanism which play important roles in the developmental processes of different types of ENSO. Our work highlights the importance of the interdecadal changes in the spatial structure of the SPO in understanding the relationship between the SPO and ENSO diversity.

Exploring the Centennial-Scale Climate History of Southern Brazil with Ocotea porosa (Nees & Mart.) Barroso Tree-Rings

This article explores the dendrochronological potential of Ocotea porosa (Nees & Mart) Barroso (Imbuia) for reconstructing past climate conditions in the General Carneiro region, Southern Brazil, utilizing well-established dendroclimatic techniques. A total of 41 samples of Imbuia were subjected to dendroclimatic analysis to reconstruct precipitation and temperature patterns over the period from 1446 to 2011. Notably, we achieved the longest reconstructions of spring precipitation and temperature for the Brazilian southern region, spanning an impressive 566-year timeframe, by employing a mean chronology approach. To achieve our objectives, we conducted a Pearson’s correlation analysis between the mean chronology and the climatic time series, with a monthly temporal resolution employed for model calibration. Impressively, our findings reveal significant correlations with coefficients as high as |rx,P| = 0.32 for precipitation and |rx,T| = 0.45 for temperature during the spring season. Importantly, our climate reconstructions may elucidate a direct influence of the El Niño—South Oscillation phenomenon on precipitation and temperature patterns, which, in turn, are intricately linked to the natural growth patterns of the Imbuia trees. These results shed valuable light on the historical climate variability in the Southern Brazil region and provide insights into the climatic drivers affecting the growth dynamics of Ocotea porosa (Nees & Mart) Barroso.

Seasonally Alternate Roles of the North Pacific Oscillation and the South Pacific Oscillation in Tropical Pacific Zonal Wind and ENSO

Abstract The western-central equatorial Pacific (WCEP) zonal wind affects El Niño–Southern Oscillation (ENSO) by involving a series of multiscale air–sea interactions. Its interannual variation contributes the most to ENSO amplitude. Thus, understanding the predictability of the WCEP interannual wind is of great importance for better predictions of ENSO. Here, we show that the North Pacific Oscillation (NPO) and the South Pacific Oscillation (SPO) alternate in fueling this interannual wind from late boreal winter to austral winter in the presence of background trade winds in different hemispheres. During the boreal winter–spring, the NPO registers footprints in the tropics by benefiting from the Pacific meridional mode and modulating the northwestern Pacific intertropical convergence zone (NITCZ). However, as austral winter approaches, the SPO takes over the role of the NPO in maintaining the anomalous NITCZ. Moreover, the interannual wind is further driven to the east in the positive phase of the SPO, by intensified central-eastern equatorial Pacific convection resulting from tropical–extratropical heat flux adjustments. A reconstructed WCEP interannual wind index involving only the NPO and the SPO possesses a long lead time for ENSO prediction of nearly one year. These two extratropical boosters enhance the viability of equatorial Pacific zonal wind anomalies associated with the large growth rate of ENSO, and the one in the winter hemisphere seems to be more efficient in forcing the tropics. Our result further indicates that the NPO benefits a long-lead prediction of the WCEP interannual wind and ENSO, while the SPO is the dominant extratropical predictor of ENSO amplitude. Significance Statement ENSO is closely linked to the interannual variability of equatorial Pacific zonal wind, and ENSO prediction is impeded by the weak predictability of the wind. We have found that the North Pacific Oscillation and the South Pacific Oscillation take turns in affecting the interannual variability of the zonal wind from the late boreal winter to austral winter, and the winter hemisphere extratropical booster is more efficient in modulating tropical convection and the associated surface winds. An estimated zonal wind index constructed by the two extratropical precursors possesses a long lead time for ENSO prediction. Our result provides useful information for better predicting ENSO by further considering winter hemisphere extratropical climate variability.

On method of regional non-stationary flood frequency analysis under the influence of large reservoir group and climate change

Global climate change and reservoir regulations can alter the natural flow of rivers. Influenced by these two drivers, flood sequences may no longer satisfy the assumption of stationary, thereby making it difficult to accurately analysis flood frequency and to design water conservancy projects. Therefore, it is of great significance to analyse the non-stationary frequency of flood sequences in a changing environment. In this study, we proposed a method for conducting nonstationary flood frequency analysis caused by cascade reservoirs as well as the low-frequency climate indices. The proposed non-stationary model 2, with the explanatory variables of climate indices and modified reservoir index (MRI), was compared with the traditional stationary model and the widely used non-stationary model 1 with time as the explanatory variable. The study was conducted at six hydrological stations in the main stream and tributaries of the upper reaches of the Yangtze River in China (considered as the Three Gorges Reservoir Area). The results of the generalized additive model for location, scale and shape (GAMLSS) showed that the Akaike information criterion and Bayesian information criterion values of the proposed non-stationary model method 2 are smaller than those of the two comparison models. When the low-frequency South Oscillation Index is high or the Arctic Oscillation and North Pacific Oscillation are low, the stationary model underestimates the design value of flood quantiles compared with the non-stationary model 2. Compared with the non-stationary model 1, the MRI and low-frequency climate indices as the explanatory variables in model 2 can better describe the non-stationary characteristics of flood frequency and amplitude. In addition, the non-stationary model considering external physical factors can provide better prediction of future design flood compared with two traditional models.

Climate variability of the southern Amazon inferred by a multi-proxy tree-ring approach using Cedrela fissilis Vell.

The analysis of climate variability and development of reconstructions based on tree-ring records in tropical forests have been increasing in recent decades. In the Amazon region, ring width and stable isotope long-term chronologies have been used for climatic studies, however little is known about the potential of wood traits such as density and chemical concentrations. In this study, we used well-dated rings of Cedrela fissilis Vell. from the drought-prone southern Amazon basin to assess the potential of using inter-annual variations of annually-resolved ring width, wood density, stable oxygen isotope (δ18OTR) measured in tree-ring cellulose and concentration of Sulfur (STR) and Calcium (CaTR) in xylem cells to study climate variability. During wet years, Cedrela fissilis produced wider and denser rings with higher CaTR and lower STR, as well as depleted δ18OTR values. During dry years, a wider range of responses was observed in growth, density and STR, while lower CaTR and enriched δ18OTR values were found. The annual centennial chronologies spanning from 1835 to 2018 showed good calibration skills for reconstructing local precipitation, evapotranspiration (P-PET), Amazon-wide rainfall, as well as climate modes related to sea surface temperature (SST) anomalies such as El Niño South Oscillation (ENSO), Tropical Northern Atlantic (TNA), and the Western Hemisphere Warm Pool (WHWP) oscillations. CaTR explained 42 % of the variance of local precipitation (1975–2018), RW explained 30 % of the P-PET variance (1975–2018), while δ18OTR explained 60 % and 57 % of the variance of Amazon rainfall (1960–2018) and El Niño 3.4 (1920–2018), respectively. Our results show that a multi-proxy tropical tree-ring approach can be used for high-reliable reconstructions of climate variability over Amazon basin at inter-annual and multidecadal time scales.

District-Level Seasonal Rainfall Characteristics over Andhra Pradesh and its Global Teleconnections in Changing Climate

Investigating the trends and changes in rainfall over vulnerable regions is of huge importance in this global warming era. The present study intensively investigates the rainfall over the Indian state, Andhra Pradesh (AP), and its 13 districts using a high-resolution (0.25°×0.25°) gridded rainfall analysis dataset from India Meteorological Department (IMD) for the study period of 118 years (1901-2018). For this, normality, homogeneity, persistence, and change-point tests are performed and changes in the district-level rainfall in the present global warming period (1991-2018) as compared to the pre-global warming period (1901-1990) is also analyzed.
 The results suggest that the long-term average annual rainfall over AP is 882 mm and most of the rainfall is contributed by the monsoon (55.7%) and the post-monsoon rainfall (32.8%). The coefficient of variation is low (high) during monsoon (winter). The coastal region receives more rainfall than the inland districts. The post-monsoon rainfall over AP is more consistent than in other seasons, and the persistence is only during the southwest monsoon season. The southwest monsoon and post-monsoon rainfall have increased (by about 10%) over most of the districts in the recent period. The Nino3.4 region SST (South Oscillation Index; SOI) has a significant negative (positive) relationship with southwest summer monsoon rainfall in most of the districts. The relationship of Nino 3.4 SST and DMI is strikingly similar for post-monsoon and has significantly weakened in recent decades. This study is useful for proper planning and mitigation measures for the agricultural and water resources sector at the district level over AP in this global warming era.

The ENSO-induced South Pacific Meridional Mode

Previous studies have investigated the role of the Pacific meridional mode (PMM), a climate mode of the mid-latitudes in the Northern and Southern Hemisphere, in favoring the development of the El Niño Southern Oscillation (ENSO). However little is known on how ENSO can influence the development of the PMM. Here we investigate the relationship between ENSO and the South Pacific Meridional Mode (SPMM) focusing on strong SPMM events that follows strong El Niño events. This type of events represents more than 60% of such events in the observational record and the historical simulations of the CESM Large ensemble (CESM-LE). It is first shown that such a relationship is rather stationary in both observations and the CESM-LE. Our analyses further reveal that strong SPMM events are associated with a coastal warming off northern central Chile peaking in Austral winter resulting from the propagation of waves forced at the equator during the development of El Niño events. The time delay between the ENSO peak (Boreal winter) and this coastal warming (Austral winter) can be understood in terms of the differential contribution of the equatorially-forced propagating baroclinic waves to the warming along the coast. In particular, the difference in phase speeds of the waves (the high-order mode the wave the slower) implies that they do not overlap along their propagation south of 20°S. This contributes to the persistence of warm coastal SST anomalies off Central Chile until the Austral summer following the concurrent El Niño event. This coastal warming is favorable to the development of strong SPMM events as the South Pacific Oscillation become active during that season. The analysis of the simulations of the Coupled Intercomparison Project phases 5 and 6 (CMIP5/6) indicates that very few models realistically simulate this ENSO/SPMM relationship and associated oceanic teleconnection.

Seasonal Predictability of the East Atlantic Pattern in Late Autumn and Early Winter

AbstractThe North Atlantic Oscillation (“NAO”) and the East Atlantic Pattern (“EAP”) dominate winter atmospheric variability over the North Atlantic. Unlike the NAO, seasonal predictability of the EAP has remained elusive. A multi‐model ensemble of seasonal predictions yields skillful forecasts of the EAP in late autumn and early winter, complementing NAO prediction skill in winter. The shift in prediction skill from EAP to NAO reflects the ability of the ensemble to forecast the evolving influence of the El Niño South Oscillation on the North Atlantic region. In early winter, the ensemble correctly forecasts the key tropical–extratropical teleconnections, resulting in skillful predictions of the EAP and western European temperatures and rainfall. However, the modeled tropical–extratropical teleconnections are weak compared to observations, contributing to a signal to noise error in predictions of the EAP. Improving the strength of such teleconnections would improve predictions of the EAP and associated surface climate.

Long term oscillations of Mediterranean sardine and anchovy explained by the combined effect of multiple regional and global climatic indices

It is widely known that the abundance and distribution dynamics of populations of small pelagic clupeid fish, such as sardines and anchovies, are affected by large-scale climate variability, which may lead to changeovers to new regimes of small pelagics. However, long-distance climatic oscillations, such as El Niño/La Niña and the Pacific Decadal Oscillation, have been little explored in the Western Mediterranean Sea. We investigated the possible effects of the South Oscillation Index (i.e. the atmospheric oscillation coupled with the El Niño/La Niña) and Pacific Decadal Oscillation on fluctuations in catches of European anchovy (Engraulis encrasicolus) and sardine (Sardina pilchardus) in the Western Mediterranean Sea, and their association with regional climate oscillations (i.e. the Atlantic Multidecadal Oscillation, the North Atlantic Oscillation, the Western Mediterranean Oscillation index, and the Arctic Oscillation). The study covered two periods: (a) landings between 1950 and 2016; and (b) abundance, biomass, and physical condition (i.e., relative condition index) between 2004 and 2016. The main large-scale climatic oscillations in the region were studied using General Additive Models to investigate the relationship between a time series of species measures of European sardine and anchovy from Geographical Subarea 06. Results show that the long-term Pacific Decadal Oscillation favours sardine landings, whereas the combined effect of the Western Mediterranean Oscillation Index and the Atlantic Multidecadal Oscillation favours anchovy. We discuss potential links between the present findings and changes in the plankton community caused by prevailing winds in the region driven by long-distance climate oscillations and their impact on the reduction in small pelagic fish populations in the study area.

Analysis of Extreme Temperature Variations on the Yunnan-Guizhou Plateau in Southwestern China over the Past 60 Years

Analysis of variations in 12 extreme temperature indices at 68 meteorological stations on the Yunnan-Guizhou Plateau (YGP) in southwestern China during 1960–2019 revealed widespread significant changes in all temperature indices. The temperature of the hottest days and coldest nights show significantly increasing trends, and the frequencies of the warm days and nights also present similar trends. The temperature of the coldest night has a significant and strong warming trend (0.38 °C/decade), whereas the frequency of frost days shows the fastest decrease (1.5 days/decade). Increases in the summer days are statistically significant, while a decreasing trend for the diurnal temperature range is not significant. Furthermore, there were significant differences in the changes of temperature indices between 1960–1989 and 1990–2019. Most parts of the YGP underwent significant warning, manifesting that the mountainous regions are relatively sensitive and vulnerable to climate change. The correlation coefficients between the temperature indices and various geographical factors (latitude, longitude, and height) reflect the complexity of regional temperature variability and indicate enhanced sensitivity of extreme temperatures to geographical factors on the YGP. It was also found that extreme temperatures generally had weaker correlations with the El Nino-Southern Oscillation, North Pacific Index, Southern Oscillation Index, North Atlantic Oscillation, and East Asian Summer Monsoon Index than with the South Asian summer monsoon index, Nino4 indices and Arctic Oscillation, and there were more insignificant correlations. Regional trends of the extreme temperature indices reflect the non-uniform temperature change over the YGP, which is due to the complex interaction between atmospheric circulation patterns and local topography. The results of this study have important practical significance for mitigating the adverse effects of extreme climatic changes, in particular for the YGP with its typical karst geomorphology and fragile ecological environment.

On the weakening association between South Asian Monsoon and Atlantic Multidecadal Oscillation

On the weakening association between South Asian Monsoon and Atlantic Multidecadal Oscillation

Recent global warming as a proximate cause of deforestation and forest degradation in northern Pakistan.

Instrumental climatological records such as weather stations data of northern areas of Pakistan are not sufficient to assess the forest extreme events reliably. To understand the past climatic variability, tree ring width based climatic reconstruction is the best alternative to trace climate variability that goes back in time. Quercus Incana is the most sensitive species to drought and climatic variation in northern Pakistan. However, very little research quantifies the rate of ongoing climatic changes. A total of 65 tree cores were collected from two sites to understand the radial growth of Q. Incana to extreme drought events. The radial growth is mainly affected by high temperatures during May-July. In addition, radial growth exhibits a positive correlation with February-June precipitation while it is negatively correlated with the September precipitation. The radial growth decrease, particularly in harsh climatic conditions. The reconstructed tree ring record was strongly coherent with the May-June self-calibrated Palmer drought severity index (scPDSI) and reliable in reconstructing drought variability for the period 1750–2014. During the past 264 years, wet periods were found during 1980–2010, 1812–1836, and 1754–1760, while dry periods were found during 1896–1922, 1864–1876, and 1784–1788. Our reconstruction explains 39.8% of the scPDSI variance. The extreme drought and wet years we arrived at were in close agreement with the drought and wet periods that occurred in northern Pakistan. Wavelet analysis revealed drought variability at periodicities of 2.2–2.5, 3.3, 3–4, 16.7, 16.8, and 68–78.8 years. Hence it is concluded that deforestation and forest degradation rate increased with extreme drought and wet years. Overall, the variation of drought in northern Pakistan seems to have been affected due to El Nino south oscillation, Pacific decadal oscillation, or Atlantic multi-decadal oscillations.

Dengue Climate Variability in Rio de Janeiro City with Cross-Wavelet Transform

Dengue is one of the most prominent tropical epidemic diseases present in the Rio de Janeiro city and Southeast part of Brazil, due to the widespread conditions of occurrence of the dengue vector, the mosquito Aedesaegypti, such as high-temperature days interlaced with afternoon or nocturnal rainstorms in summer. This work has the objective of investigating the relationships between variabilities of the El Ni?o-South Oscillation (ENSO) and greater epidemics of dengue in Rio de Janeiro city. To accomplish this goal, the analysis and signal decomposition by cross-wavelet transform (WT) was applied to obtain the cross variability associated with variations of power and phase of both signals by characteristic periods and along with the time series. Data considered in the analysis are (the decimal logarithm of normalized value) of the monthly available notifications of dengue worsening, provided by the public health system of Brazil, and the Southern Oscillation Index (SOI) Ni?o 3.4 data, provided by the National Oceanic and Atmospheric Administration (NOAA), in the period 2000-2017. A maximum cross-wavelet power close to 0.45 was obtained for the representative period of 1 year and also to periods between 3 and 4 years, associated with the positive phase of the SOI index (i.e. , La Ni?a) or with a transition to the positive phase. The evolution of the combined variability of SOI and dengue can be expressed by progressive differences in phase along the time, eventually resulting in yielding phases (i.e., La Niña-Dengue epidemic).

Linking the atmospheric Pacific-South American mode with oceanic variability and predictability

While Pacific climate variability is largely understood based on El Niño-Southern Oscillation (ENSO), the North Pacific focused Pacific decadal oscillation and the basin-wide interdecadal Pacific oscillation, the role of the South Pacific, including atmospheric drivers and cross-scale interactions, has received less attention. Using reanalysis data and model outputs, here we propose a paradigm for South Pacific climate variability whereby the atmospheric Pacific-South American (PSA) mode acts to excite multiscale spatiotemporal responses in the upper South Pacific Ocean. We find the second mid-troposphere PSA pattern is fundamental to stochastically generate a mid-latitude sea surface temperature quadrupole pattern that represents the optimal precursor for the predictability and evolution of both the South Pacific decadal oscillation and ENSO several seasons in advance. We find that the PSA mode is the key driver of oceanic variability in the South Pacific subtropics that generates a potentially predictable climate signal linked to the tropics.

Influence of Indian Ocean dipole on rainfall variability and extremes over southern Africa

Extreme weather events; floods and droughts are common in southern Africa (SA) consisting of 8 countries (Botswana, Namibia, South Africa, Lesotho, Swaziland, Mozambique, Zimbabwe, parts of Angola and Zambia). This study examines the linkage between the SA October-December (OND) rainfall, the Indian Ocean Dipole (IOD) and the South Atlantic Oscillation Dipole (SAOD). Empirical Orthogonal Functions (EOF) technique is used to establish the dominant mode of variability of OND rainfall, as correlation analysis is applied to quantify the relationship between the indices; IOD [Dipole Mode Index (DMI)], SAOD Index (SAODI) and OND rainfall variability. Results show that the dominant mode of variability of OND rainfall exhibits a dipole pattern over SA and there exists a significant correlation at 95% confidence level between the area average OND rainfall (rainfall index (RFI)) and DMI, with a correlation coefficient of -0.3. The relationship between the mean SA OND rainfall and the positive phase of IOD varies greatly in space, ranging from one country to another. Further analysis of the dry and wet of SAOND rainfall years reveal that wet years are associated with convergence at surface level (850 hPa) and divergence at upper level (200 hPa), depicting rising motion in the region, whereas dry years are associated with divergence at low level and convergence at upper level, implying descending motion. The study recommends further research on a reduced spatial scale, for instance at a country level to ascertain the effect of IOD on individual country’s weather. This will help in accurate monitoring of the evolution of IOD events to improve quality of seasonal weather forecasts in the region.

Sea Ice Changes in the Pacific Sector of the Southern Ocean in Austral Autumn Closely Associated With the Negative Polarity of the South Pacific Oscillation

AbstractWe present an explanation for the sea ice concentration trends in the Pacific sector of the Southern Ocean (PSSO) in austral autumn (April‐June) during 1979–2018. Sea ice has decreased in the Bellingshausen Sea and increased in the Ross Sea, concurrently with a negative trend in the South Pacific Oscillation (SPO). SPO statistically explains 43% of the sea ice concentration trend averaged over PSSO. Convective activities over East Africa and the southwestern Indian Ocean, the Interdecadal Pacific Oscillation (IPO), and extratropical processes excite a wavetrain that propagates from the Indian Ocean to the Southern Ocean and South America. The wavetrain contributes to the decrease of the autumn SPO index, which influences sea ice changes over PSSO. During the negative phase of SPO, an anomalous surface anticyclonic wind field over high‐latitude South Pacific Ocean generates anomalous sea ice concentrations via heat advection and wind forcing on ice drift.

As chuvas do baixo rio Iguaçu (Sudoeste do Paraná) no período de 1976 a 2016

A Bacia Hidrográfica do Baixo Rio Iguaçu está localizada no Sudoeste do estado do Paraná e no decorrer dos anos, passou a apresentar importância significativa, sobretudo no que se refere à agropecuária, abastecimento urbano e geração de energia. Contudo, ainda são raras as pesquisas científicas que abordam a área analisada. Frente a isso, o presente trabalho, objetiva caracterizar o regime pluviométrico do Baixo Rio Iguaçu no período de 1976 até 2016. Para tanto, no regime de precipitações, utilizou-se de parâmetros estatísticos de tendência central e o método de interpolação krigagem, a fim de espacializar os dados de chuva de 31 estações pluviométricas. Os resultados destacam a influência do El Niño e da Oscilação Decadal do Pacífico no regime de chuvas da área estudada.