A key determinant of atmospheric circulation patterns and regional climatic conditions is sea surface temperature (SST). This has been the motivation for the development of various teleconnection methods aiming to forecast hydro-climatic variables. Among such methods are linear projections based on teleconnection gross indices (such as the ENSO, IOD, and NAO) or leading empirical orthogonal functions (EOFs). However, these methods deteriorate drastically if the predefined indices or EOFs cannot account for climatic variability in the region of interest. This study introduces a new hydro-climatic forecasting method that identifies SST predictors in the form of dipole structures. An SST dipole that mimics major teleconnection patterns is defined as a function of average SST anomalies over two oceanic areas of appropriate sizes and geographic locations. The screening process of SST-dipole predictors is based on an optimization algorithm that sifts through all possible dipole configurations (with progressively refined data resolutions) and identifies dipoles with the strongest teleconnection to the external hydro-climatic series. The strength of the teleconnection is measured by the Gerrity Skill Score. The significant dipoles are cross-validated and used to generate ensemble hydro-climatic forecasts. The dipole teleconnection method is applied to the forecasting of seasonal precipitation over the southeastern US and East Africa, and the forecasting of streamflow-related variables in the Yangtze and Congo Rivers. These studies show that the new method is indeed able to identify dipoles related to well-known patterns (e.g., ENSO and IOD) as well as to quantify more prominent predictor-predictand relationships at different lead times. Furthermore, the dipole method compares favorably with existing statistical forecasting schemes. An operational forecasting framework to support better water resources management through coupling with detailed hydrologic and water resources models is also demonstrated.

O objetivo desta pesquisa foi investigar a relação linear existente entre a Temperatura de Superfície do Mar (TSM) dos oceanos Pacífico e Atlântico e a vazão do rio Madeira, localizado na parte sul da região Norte do Brasil. A investigação foi feita nas escalas mensal, sazonal e anual, para o período de 1968 a 2009. A hipótese de que alterações climáticas na região Norte do Brasil estariam associadas a episódios de aquecimento e resfriamento dos oceanos globais, já que quando ocorrem têm o potencial de modificar o padrão de precipitação em áreas remotas do globo, foi a motivação central da pesquisa. A pesquisa foi desenvolvida com base em análises estatísticas para os dados de TSM, índices climáticos e a vazão do rio Madeira. Observou-se que a vazão mensal do rio Madeira apresenta correlação linear significativa com áreas específicas dos oceanos Atlântico e Pacífico. No Oceano Atlântico Norte, são significativas as correlações obtidas nos setores tropical (área AT3) e norte (área AT1). O setor subtropical do Atlântico Norte (AT2) apresenta correlações lineares não tão expressivas como suas áreas tropical e norte. O Atlântico Sul não apresenta áreas com correlações lineares significativas com a vazão. As áreas com correlação significativa do Atlântico Norte (AT1) apresentam valores negativos máximos entre -0,6 e -0,4. Os valores de correlação linear entre a vazão mensal do rio Madeira e a TSM do Atlântico (AT2) apresentam um pequeno aumento para os cálculos realizados com defasagem temporal de até nove meses, entre 0,3 a 0,4 para 5 meses de defasagem entre a vazão e a TSM. A TSM do setor oeste do Pacífico tropical apresenta fortes valores negativos de correlação linear com a vazão do rio Madeira, com valores máximos que variam entre -0,7 e -0,4. Tal qual acontece para o Atlântico, as águas superficiais do Pacífico tropical oeste apresentam um pequeno aumento dos valores de correlação linear para defasagens maiores entre a TSM e a vazão. As áreas com forte correlação negativa no setor oeste do Pacífico tropical foram denominadas PA1, no norte, e PA3, no sul. Uma pequena área com correlação significativa e positiva a leste da bacia do Pacífico, junto à costa do Chile, foi denominada PA2. Nesta área os valores máximos de correlação linear entre a vazão mensal e a TSM variam entre 0,2 e 0,4. A análise de correlação linear entre a vazão anual do rio Madeira e índices climáticos indicam que os índices ODP, MEI e OAN são os mais bem correlacionados com a vazão, apresentando valores iguais a 0,89, 0,86 e 0,85, respectivamente. Com base na TSM das áreas bem correlacionadas com a vazão do rio Madeira e nos índices climáticos considerados, foi desenvolvido um modelo estocástico de regressão linear múltipla para a previsão da vazão trimestral com antecedência de um trimestre. A TSM das áreas do setor oeste do Pacífico tropical, PA1, e do Atlântico Norte tropical, AT3, constituíram as variáveis selecionadas para a elaboração do modelo estocástico. O modelo estocástico foi desenvolvido para o início da série temporal considerada, de 1968 a 1988, e apresentou um ajuste linear com coeficiente de determinação igual a 78%. A verificação do modelo foi feita para o final da série, de 1989 a 2009. O erro médio normalizado calculado pela diferença entre os valores de vazão previstos pelo modelo e os observados foi igual a 40%. Desta forma, conclui-se que a vazão trimestral do setor sul da região Norte do Brasil é uma variável que pode ser prevista com base na variabilidade da temperatura das águas superficiais dos oceanos Pacífico e Atlântico. A análise do comportamento atmosférico com base em períodos específicos de anomalias de TSM no Atlântico Norte tropical indica que a ocorrência de TSMs mais altas (baixas) que o normal foram acompanhadas por ventos de leste mais fracos (fortes). Foram analisados os campos atmosféricos médios para os meses chuvosos de novembro a março para as variáveis Velocidade Vertical (Omega) em 500 e 850 hPa, divergência e vorticidade do vento. Os resultados obtidos demonstram que em média, a variabilidade atmosférica foi determinante no que se refere às anomalias apresentadas pela vazão. / The objective of this research was to investigate the linear relation between the sea surface temperature (SST) over Pacific and Atlantic oceans and the outflow of the Madeira river, located at the southern part of the Northern region of Brazil. The investigation considered monthly, seasonal and annual scales, to the period between 1968 to 2009. The consideration about the influence of heating and cooling of oceanic areas over climate around the world constitutes the main hypothesis taken in account in the study. The research was developed based on statistical analysis considering SST, climatic indexes and river outflow data. The monthly outflow for Madeira River shows significant linear correlation to SST at specific areas over Atlantic and Pacific. Over North Atlantic, the linear correlation values are significant at the tropical and north sectors, namely AT3 and AT1, respectively. The subtropical sector of North Atlantic presents positive correlation but not too expressive as the tropical and north areas of Atlantic. South Atlantic does not present significant values of linear correlation with the river outflow. The area with significant correlation over North Atlantic (AT1) presents maximum negative values ranging between -0,6 and -0,4. In general, the greater the interval between river outflow and SST data, greater is the linear correlation values. SST data from the western sector of tropical Pacific presents strong negative correlation with Madeira River outflow data, and shows maximum values ranging between -0,7 and -0,4. The areas to the West of Pacific showing high negative correlation were named PA1 and PA3, to northern and southern sectors, respectively. A small area that shows significant positive linear correlation to the river outflow data, PA2, is located over the eastern side of Pacific basin, very closed to the coast of Chile. In this area, the linear maximum correlation values range between 0,2 and 0,4. Linear correlation analysis between annual river outflow data and climatic indices indicates that PDO, MEI and NAO are those more correlated with the river outflow data, presenting values equal to 0,89, 0,86 e 0,85, respectively. Based on averaged SST and climatic indices well correlated to the Madeira River outflow data, a stochastic model was developed in order to forecast the river outflow in seasonal scale. SST from west of tropical Pacific, PA1, and from tropical North Atlantic, AT3, were selected to build up the stochastic model. The stochastic model was developed considering the first half of the total series, between 1968 and 1988, while the last period was used to validate the model, between 1989 and 2009. The linear adjusting over the first period reach a determining coefficient equal to 78% and the normalized mean error obtained for the second period was equal to 40%. Thus, we conclude that the seasonal outflow for Madeira River is a climatic variable that can be forecast based on the SST variability over specific areas on Pacific and Atlantic oceans. The analysis of atmospheric behavior based on specific periods of SST anomalies in the tropical North Atlantic indicates that the occurrence of SSTs higher (lower) than normal was accompanied by easterly winds weak (strong). We analyzed the average atmospheric fields for the rainy months from November to March for variables Vertical Speed (Omega) at 500 and 850 hPa, divergence and vorticity of the wind. The results show that approximately the atmospheric variability was decisive with regard to the deficiencies presented by the ouflow.

Piura ha sido una de las regiones más afectadas por inundaciones a causa de los eventos de lluvias extremas. En los años de 1982-1983,1998 y 2017 se registraron innumerables pérdidas en infraestructura como consecuencias del fenómeno de "El Niño”, siendo este último producto del incremento inusual de la temperatura superficial del mar (TSM). El análisis de la asociación entre las anomalías de temperatura superficial del mar (ATSM) y las precipitaciones máximas (PPmáx) que ocurrieron en la zona norte del Perú (Región Piura) tiene como fin describir el comportamiento de ATSM en relación con las lluvias de gran escala. Para esto se utilizaron correlaciones cruzadas con aplicación de desfases temporales a fin de encontrar la intensidad en la que se asocian dichos parámetros. Para las PPmáx se extrajeron datos del producto grillado Piscop, el cual usa como base de información y calibración los registros de las estaciones meteorológicas. En tanto que, para las ATSM se extrajeron datos de ERA5-ECMWF calibrado mediante estaciones oceanográficas. Del análisis se observó que las precipitaciones máximas que se registran en la región Piura presentan mayor asociación y significancia menor o igual a 5% cuando se aplican desplazamientos temporales a las ATSM, de 1 mes para puntos ubicados en las regiones NIÑO 1 y NIÑO 2, y de 2 meses para puntos ubicados en las regiones NIÑO 3 y NIÑO 4. Finalmente, la mayor asociación se origina entre las variaciones inusuales de TSM producidas en el punto 3.3 y las PPmáx con desplazamientos temporales de 3 meses. / Piura has been one of the most affected regions by floods due to extreme rain events. In the years of 1982-1983, 1998, and 2017 innumerable losses in infrastructure were registered as a consequence of the "El Niño" effect, the latter being considered as a product of the unusual increase in sea surface temperature. Analysis of the association between sea surface temperature anomalies (SSTA) and extreme rainfall (ER) which occurred in the north of Peru (Piura región) to describe the behavior of SSTA in relation to large-scale rainfalls. For this, cross-correlations with the application of time lags were used in order to find the intensity in which SSTA and ER are associated. For ER, data were extracted from the Piscop grilled product, which is based on information and calibration of records of meteorological stations. While data for the SSTA was extracted from ERA5-ECMWF calibrated by oceanographic stations. From the analysis was observed that maximum precipitations that are recorded in the Piura region present a greater association and significance less than or equal to 5% when time-lag are applied to SSTA, for 1 month for points ubicated in the regions NIÑO 1 and NIÑO 2, and for 2 months points ubicated in the regions NIÑO 3 and NIÑO 4. Finally, the greatest association originates between the unusual variation of SST produced in the 3.3 SSTA point and the ER whit time-lag of 3 months. / Trabajo de investigación

No description available.

La costa norte del Perú es una de las regiones con más impacto negativo por las inundaciones a causa de los eventos de lluvias extremas. El fenómeno del Niño de los años de 1982 – 1983, 1998 y 2017 ocasionaron innumerables pérdidas en infraestructura, se considera que este evento es producto del incremento inusual de la temperatura superficial del mar (TSM). El análisis de la teleconexión entre las anomalías de temperatura superficial del mar (ATSM) y las precipitaciones máximas (PPmáx) que ocurrieron en la costa norte del Perú (Tumbes, Piura y Lambayeque) tiene como objetivo describir la tendencia del comportamiento de las ATSM en relación con las lluvias de gran escala. Para esto se utilizaron correlaciones cruzadas con aplicación de desfases temporales a fin de encontrar la intensidad en la que se asocian las ATSM y las PPmáx. Los datos para la obtención de las PPmáx se extrajeron del producto grillado Piscop, el cual usa como base de información y calibración los registros de las estaciones meteorológicas. En tanto que, para la obtención de las ATSM se extrajeron datos de ERA5-ECMWF calibrado mediante estaciones oceanográficas. Del análisis se observó que las precipitaciones máximas que se registran en la región norte del Perú presentan mayor asociación y significancia menor o igual a 5% cuando se aplican desplazamientos temporales a las ATSM, de 1 mes para puntos ubicados en las regiones NIÑO 1 y NIÑO 2, y de 3 meses para puntos ubicados en las regiones NIÑO 3 y NIÑO 4. Finalmente, la mayor asociación se origina entre las variaciones inusuales de TSM producidas en el Punto de ATSM 3.3 y las PPmáx con desplazamientos temporales de 3 meses. / The north coast of Peru is one of the most negative impact regions by floods due to extreme rain events. "El Niño" effect in 1982-1983, 1998, and 2017 years was caused innumerable losses in infrastructure, that event is considered as a product of an unusual increase in sea surface temperature. Analysis of teleconnection between sea surface temperature anomalies (SSTA) and extreme rainfall (ER) which occurred on the north coast of Peru (Tumbes, Piura y Lambayeque) to describe tren of the behavior of SSTA to large-scale rainfalls. For that reason, cross-correlations with an application of time lags were used to find the intensity in which SSTA and ER are associated. The data for obtaining ER were extracted from the Piscop grilled product, which is based on information and calibration of records of meteorological stations. While obtaining SSTA was extracted from ERA5- ECMWF calibrated by oceanographic stations. From the analysis was observed that maximum precipitations that are recorded on the north coast of Peru present a greater association and significance less than or equal to 5% when time-lag is applied to SSTA, for 1 month for points ubicated in regions NIÑO 1 and NIÑO 2, and for 3 months points ubicated in regions NIÑO 3 and NIÑO 4. Finally, the greatest association originates between an unusual variation of SST produced in 3.3 SSTA point and ER whit a time-lag of 3 months. / Tesis

In the recent scenario of climate change, the natural variability and uncertainty associated with the hydrologic variables is of great concern to the community. This thesis opens up a new area of multi-disciplinary research. It is a promising field of research in hydrology and water resources that uses the information from the field of atmospheric science. A new way to identify and capture the variability and uncertainty associated with the hydrologic variables is established through this thesis. Assessment of hydroclimatic teleconnection for Indian subcontinent and its use in basin-scale hydrologic time series analysis and forecasting is the broad aim of this PhD thesis. The initial part of the thesis is devoted to investigate and establish the dependence of Indian summer monsoon rainfall (ISMR) on large-scale Oceanic-atmospheric circulation phenomena from tropical Pacific Ocean and Indian Ocean regions. El Niño-Southern Oscillation (ENSO) is the well established coupled Ocean-atmosphere mode of tropical Pacific Ocean whereas Indian Ocean Dipole (IOD) mode is the recently identified coupled Ocean-atmosphere mode of tropical Indian Ocean. Equatorial Indian Ocean Oscillation (EQUINOO) is known as the atmospheric component of IOD mode. The potential of ENSO and EQUINOO for predicting ISMR is investigated by Bayesian dynamic linear model (BDLM). A major advantage of this method is that, it is able to capture the dynamic nature of the cause-effect relationship between large-scale circulation information and hydrologic variables, which is quite expected in the climate change scenario. Another new method, proposed to capture the dependence between the teleconnected hydroclimatic variables is based on the theory of copula, which itself is quite new to the field of hydrology. The dependence of ISMR on ENSO and EQUINOO is captured and investigated for its potential use to predict the monthly variation of ISMR using the proposed method. The association of monthly variation of ISMR with the combined information of ENSO and EQUINOO, denoted by monthly composite index (MCI), is also investigated and established. The spatial variability of such association is also investigated. It is observed that MCI is significantly associated with monthly rainfall variation all over India, except over North-East (NE) India, where it is poor. Having established the hydroclimatic teleconnection at a comparatively larger scale, the hydroclimatic teleconnection for basin-scale hydrologic variables is then investigated and established. The association of large-scale atmospheric circulation with inflow during monsoon season into Hirakud reservoir, located in the state of Orissa in India, has been investigated. The strong predictive potential of the composite index of ENSO and EQUINOO is established for extreme inflow conditions. So the methodology of inflow prediction using the information of hydroclimatic teleconnection would be very suitable even for ungauged or poorly gauged watersheds as this approach does not use any information about the rainfall in the catchment. Recognizing the basin-scale hydroclimatic association with both ENSO and EQUINOO at seasonal scale, the information of hydroclimatic teleconnection is used for streamflow forecasting for the Mahanadi River basin in the state of Orissa, India, both at seasonal and monthly scale. It is established that the basin-scale streamflow is influenced by the large-scale atmospheric circulation phenomena. Information of streamflow from previous month(s) alone, as used in most of the traditional modeling approaches, is shown to be inadequate. It is successfully established that incorporation of large-scale atmospheric circulation information significantly improves the performance of prediction at monthly scale. Again, the prevailing conditions/characteristics of watershed are also important. Thus, consideration of both the information of previous streamflow and large-scale atmospheric circulations are important for basin-scale streamflow prediction at monthly time-scale. Adopting the developed approach of using the information of hydroclimatic teleconnection, hydrologic variables can be predicted with better accuracy which will be a very useful input for better management of water resources.

No description available.