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Monsoon precipitation affects natural and social systems in East Asia, one of the most densely populated regions in the world. Monsoon precipitation variability is strongly influenced by El Niño-Southern Oscillation (ENSO) and may be related to the phase of the Pacific Decadal Oscillation (PDO). However, a collective understanding of the long-term PDO-ENSO-monsoon relationship remains limited because related studies are almost exclusively based on short instrumental records. Although paleoclimate proxies for PDO and ENSO are currently available, there is a lack of high-quality proxies for East Asian summer monsoon (EASM) precipitation. Moreover, the strengthening of the ENSO-EASM relationship since the 1970s has raised the question of anthropogenic impact. Reconstructing EASM precipitation is thus crucial to understanding its variability under natural and anthropogenic forcings. In this study, we addressed these challenges using tree ring oxygen isotopes of red cypress (Chamaecyparis formosensis Matsum), a long-lived endemic tree species in Taiwan. We developed an annual-resolved and well-validated EASM precipitation proxy from 1533 CE to 2011 which explained 49 % of the variance in instrumental precipitation. In comparison with multiple paleoclimate proxies, we revealed that PDO persistently modulated the ENSO-EASM relationship over the past half-millennium. The ENSO-EASM relationship was enhanced during the positive PDO phases and dynamically weakened during the negative PDO phases, notably in the early-17th, 18th, and early to mid-20th centuries. The strengthened relationship since the 1970s concurred with an unusually high PDO and ENSO and fell within its natural variability. Nevertheless, as the amplitude of the PDO is predicted to weaken under warming, the modulation effects may become less predictable.

Monsoon precipitation affects natural and social systems in East Asia, one of the most densely populated regions in the world. Monsoon precipitation variability is strongly influenced by El Niño-Southern Oscillation (ENSO) and may be related to the phase of the Pacific Decadal Oscillation (PDO). However, a collective understanding of the long-term PDO-ENSO-monsoon relationship remains limited because related studies are almost exclusively based on short instrumental records. Although paleoclimate proxies for PDO and ENSO are currently available, there is a lack of high-quality proxies for East Asian summer monsoon (EASM) precipitation. Moreover, the strengthening of the ENSO-EASM relationship since the 1970s has raised the question of anthropogenic impact. Reconstructing EASM precipitation is thus crucial to understanding its variability under natural and anthropogenic forcings. In this study, we addressed these challenges using tree ring oxygen isotopes of red cypress (Chamaecyparis formosensis Matsum), a long-lived endemic tree species in Taiwan. We developed an annual-resolved and well-validated EASM precipitation proxy from 1533 CE to 2011 which explained 49 % of the variance in instrumental precipitation. In comparison with multiple paleoclimate proxies, we revealed that PDO persistently modulated the ENSO-EASM relationship over the past half-millennium. The ENSO-EASM relationship was enhanced during the positive PDO phases and dynamically weakened during the negative PDO phases, notably in the early-17th, 18th, and early to mid-20th centuries. The strengthened relationship since the 1970s concurred with an unusually high PDO and ENSO and fell within its natural variability. Nevertheless, as the amplitude of the PDO is predicted to weaken under warming, the modulation effects may become less predictable.

The North Pacific sea surface temperature (SST) has a profound climatic influence. The El Niño-Southern Oscillation (ENSO) significantly impacts the North Pacific SST; however, the influence of the distinct phases of ENSO on SST predictability remains unclear. To overcome the model limitations, this study assessed SST predictability under diverse ENSO phases using reanalysis. The predictability limit of the North Pacific SST under La Niña (8.4 months) is longer than that under Neutral (5.9 months) and El Niño (5.5 months) conditions, which unveils asymmetry. This asymmetry mirrors contemporary multimodal prediction skills. Error growth dynamics reveal La Niña's robust signal strength with a slow error growth rate, in contrast to El Niño's weaker signal and faster error growth. There exhibits intermediate signal strength and elevated error growth in Neutral condition. Physically, predictability signal strength aligns with SST variability, whereas the error growth rate correlates with atmospheric-ocean heating anomalies. La Niña, which induces positive heating anomalies, minimizes the impact of atmospheric noise, resulting in lower error growth. The result is beneficial for improving North Pacific SST predictions. © 2024. The Authors.

It is well established that El Niño–Southern Oscillation (ENSO) impacts the North Atlantic–European (NAE) climate, with the strongest influence in winter. In late winter, the ENSO signal travels via both tropospheric and stratospheric pathways to the NAE sector and often projects onto the North Atlantic Oscillation. However, this signal does not strengthen gradually during winter, and some studies have suggested that the ENSO signal is different between early and late winter and that the teleconnections involved in the early winter subperiod are not well understood. In this study, we investigate the ENSO teleconnection to NAE in early winter (November–December) and characterize the possible mechanisms involved in that teleconnection. To do so, observations, reanalysis data and the output of different types of model simulations have been used. We show that the intraseasonal winter shift of the NAE response to ENSO is detected for both El Niño and La Niña and is significant in both observations and initialized predictions, but it is not reproduced by free-running Coupled Model Intercomparison Project phase 5 (CMIP5) models. The teleconnection is established through the troposphere in early winter and is related to ENSO effects over the Gulf of Mexico and Caribbean Sea that appear in rainfall and reach the NAE region. CMIP5 model biases in equatorial Pacific ENSO sea surface temperature patterns and strength appear to explain the lack of signal in the Gulf of Mexico and Caribbean Sea and, hence, their inability to reproduce the intraseasonal shift of the ENSO signal over Europe., Natural Environment Research Council (UK), European Research Council, Depto. de Física de la Tierra y Astrofísica, Fac. de Ciencias Físicas, TRUE, pub

The upper-level jet stream is a critical element of atmospheric circulation, driving synoptic systems and extreme weather events. This study analyzes the impact of upper-level jets on South American (SA) summer temperature and precipitation under different El Niño-Southern Oscillation (ENSO) phases. Using the ERA5 reanalysis dataset from 1979 to 2022, we perform a daily multiparametric characterization of the jet stream, considering its spatial and temporal discontinuities. Besides latitude and intensity, we find that the departure and number of branches of the subtropical jet (STJ) and the longitudinal extent of the Pacific branch of the polar front jet (PFJ) are needed for their description. An additional parameter is required to characterize the STJ due to its absence on around 40% of summer days over SA. Moreover, we observe distinct long-term changes in PFJ parameters across different ocean basins. Three synoptic weather types (WTs) of the upper-level zonal wind are identified: normal conditions, a prominent STJ pattern, and a PFJ-only pattern. The latter pattern is associated with anticyclonic anomalies at 500hPa in the South Atlantic Ocean and an active SA Convergence Zone, which favors clear skies and warm (wet and cold) conditions in southern SA (Brazil). Consistently, the probability of experiencing warm spells in central Argentina is increased more than twofold. Finally, we detect that the temperature anomalies associated with the WTs are independent of the ENSO phase. However, ENSO modulates the frequency of the WTs: during La Niña (El Niño), the PFJ-only (prominent STJ) pattern is more common., Unión Europea. H2020, Depto. de Física de la Tierra y Astrofísica, Fac. de Ciencias Físicas, TRUE, pub

The watershed basin of the Chalpi Grande River is located in the Ecuadorian Amazon. This basin, being above 3200 m a.s.l. It has characteristics of Andean and Amazonian ecosystems. The conservation of this basin is extremely important because the supply of 2.2 m3/s for the Metropolitan District of Quito depends on this river. The objective of this research is the characterization of the additional climate of 31 years (1985-2015) of records of temperature, precipitation and flow of the Chalpi Grande River based on the historical records of INAMHI, EPMAPS and FONAG. These were systematized records filled in based on statistical methods and remote sensors for data validation. The climatic temperature shows increases both in the behaviors and in the trends of the winter and summer seasons; as well as in the trends of climatic parameters that can be the effect of atmospheric phenomena, such as the latent problem of climate change., La cuenca hidrográfica del río Chalpi Grande se encuentra ubicada en la amazonia ecuatoriana. Esta cuenca al estar por encima de los 3200 m s.n.m posee características de ecosistemas andinos y amazónicos. La conservación de esta cuenca es de suma importancia debido a que de este río depende el abastecimiento de 2.2 m3/s para el Distrito Metropolitano de Quito. El objetivo de esta investigación es la caracterización de la variabilidad climática de 31 años (1985 – 2015) de registros de temperatura, precipitación y caudal del río Chalpi Grande en base a los registros históricos del INAMHI, EPMAPS y FONAG. Estos registros fueron sistematizados y rellenados en base a métodos estadísticos y sensores remotos para la validación de datos. La variabilidad climática muestra incrementos tanto en los comportamientos como en las tendencias de las estaciones de invierno y verano; como también en las tendencias de los parámetros climáticos que pueden ser efecto de los fenómenos atmosféricos, como el problema latente del cambio climático.

Salinity can influence microbial communities and related functional groups in lacustrine sediments, but few studies have examined temporal variability in salinity and associated changes in lacustrine microbial communities and functional groups. To better understand how microbial communities and functional groups respond to salinity, we examined geochemistry and functional gene amplicon sequence data collected from 13 lakes located in Kiritimati, Republic of Kiribati (2° N, 157° W) in July 2014 and June 2019, dates which bracket the very large El Niño event of 2015-2016 and a period of extremely high precipitation rates. Lake water salinity values in 2019 were significantly reduced and covaried with ecological distances between microbial samples. Specifically, phylum- and family-level results indicate that more halophilic microorganisms occurred in 2014 samples, whereas more mesohaline, marine, or halotolerant microorganisms were detected in 2019 samples. Functional Annotation of Prokaryotic Taxa (FAPROTAX) and functional gene results (nifH, nrfA, aprA) suggest that salinity influences the relative abundance of key functional groups (chemoheterotrophs, phototrophs, nitrogen fixers, denitrifiers, sulfate reducers), as well as the microbial diversity within functional groups. Accordingly, we conclude that microbial community and functional gene groups in the lacustrine sediments of Kiritimati show dynamic changes and adaptations to the fluctuations in salinity driven by the El Niño-Southern Oscillation.

The impact of climate change on humans is ever greater, ironically because of anthropogenic factors such as globalization. In the case of vectorborne diseases as leishmaniases, the climate change (CC) can affect their epidemiology by shifting the biology and ecology of its vectors, reservoirs and pathogens. In this descriptive review, a search was made in BioMed Central, PubMed and Biblioteca virtual em saúde and aims to provide information available about the effect of CC on incidence and seasonal and spatial distribution of the leishmaniases, the pathogen and its vectors, and how it can impact the emergence and resurgence of this disease in Latin American countries, highlighting the problem in Mexico. Information generated from 2002 to 2021 was collected from scientific data bases. We found 48 articles, including six review articles. The great potential of leishmaniasis to expand its geographic distribution ranges, variation of its transmission cycles, substantial increase in the number of cases and increase in the investment for the exploration of alternatives of its treatment and control, this has caused that leishmaniasis leave the “neglected diseases” status and be re-categorized as “emerging diseases”., El impacto del cambio climático en los humanos es cada vez mayor, irónicamente debido a factores antropogénicos como la globalización. En el caso de enfermedades transmitidas por vectores como las leishmaniasis, el cambio climático (CC) puede afectar su epidemiología al modificar la biología y ecología de sus vectores, reservorios y patógenos. En esta revisión descriptiva, se realizó una búsqueda de información en BioMed Central, PubMed y Biblioteca virtual em saúde y se tuvo como objetivo proporcionar información disponible sobre el efecto del CC en la incidencia y distribución estacional y espacial de la leishmaniasis, el patógeno y sus vectores, y cómo puede impactar en la aparición y resurgimiento de esta enfermedad en los países de América Latina, destacando la problemática en México. Se buscó información de 2002 a 2021, en bases de datos de artículos científicos. Se encontraron 48 referencias, incluyendo seis artículos de revisión. El gran potencial de las eishmaniasis para ampliar sus rangos de distribución geográfica, la variación de sus ciclos de transmisión, el aumento sustancial del número de casos y el aumento de la inversión para la exploración de alternativas de su tratamiento y control, ha provocado que las leishmaniasis sean categorizadas como enfermedades emergentes.

Terrestrial ecosystems have taken up about 32% of the total anthropogenic CO2 emissions in the past six decades1. Large uncertainties in terrestrial carbon-climate feedbacks, however, make it difficult to predict how the land carbon sink will respond to future climate change2. Interannual variations in the atmospheric CO2 growth rate (CGR) are dominated by land-atmosphere carbon fluxes in the tropics, providing an opportunity to explore land carbon-climate interactions3-6. It is thought that variations in CGR are largely controlled by temperature7-10 but there is also evidence for a tight coupling between water availability and CGR11. Here, we use a record of global atmospheric CO2, terrestrial water storage and precipitation data to investigate changes in the interannual relationship between tropical land climate conditions and CGR under a changing climate. We find that the interannual relationship between tropical water availability and CGR became increasingly negative during 1989-2018 compared to 1960-1989. This could be related to spatiotemporal changes in tropical water availability anomalies driven by shifts in El Niño/Southern Oscillation teleconnections, including declining spatial compensatory water effects9. We also demonstrate that most state-of-the-art coupled Earth System and Land Surface models do not reproduce the intensifying water-carbon coupling. Our results indicate that tropical water availability is increasingly controlling the interannual variability of the terrestrial carbon cycle and modulating tropical terrestrial carbon-climate feedbacks.

Mean wave energy flux (hereinafter WEF) is assessed in the Caribbean Sea from a 60-year (1958–2017) wave hindcast. We use a novel approach, based on neural networks, to identify coherent regions of WEF and their association with different climate patterns. This method allows for a better evaluation of the underlying dynamics behind seasonal and inter-annual WEF variability, including the effect induced by the latitudinal migration of the Intertropical Convergence Zone (ITCZ) and the influence of El Niño-Southern Oscillation (ENSO) events. Results show regional differences in WEF variability likely due to both intensification and migration of the ITCZ. WEF exhibits a strong semi-seasonal signal in areas of the continental shelf, with maxima reached in January and June, in agreement with the known sea surface temperature and sea-level pressure variability patterns. At larger scales, WEF shows a significant correlation with the Oceanic Niño Index (ONI, which is the primary index for tracking the ocean part of ENSO climate pattern), depicting positive values in the central and western sides of the basin and negative ones at the eastern side.

The watershed basin of the Chalpi Grande River is located in the Ecuadorian Amazon. This basin, being above 3200 m a.s.l. It has characteristics of Andean and Amazonian ecosystems. The conservation of this basin is extremely important because the supply of 2.2 m3/s for the Metropolitan District of Quito depends on this river. The objective of this research is the characterization of the additional climate of 31 years (1985-2015) of records of temperature, precipitation and flow of the Chalpi Grande River based on the historical records of INAMHI, EPMAPS and FONAG. These were systematized records filled in based on statistical methods and remote sensors for data validation. The climatic temperature shows increases both in the behaviors and in the trends of the winter and summer seasons; as well as in the trends of climatic parameters that can be the effect of atmospheric phenomena, such as the latent problem of climate change., La cuenca hidrográfica del río Chalpi Grande se encuentra ubicada en la amazonia ecuatoriana. Esta cuenca al estar por encima de los 3200 m s.n.m posee características de ecosistemas andinos y amazónicos. La conservación de esta cuenca es de suma importancia debido a que de este río depende el abastecimiento de 2.2 m3/s para el Distrito Metropolitano de Quito. El objetivo de esta investigación es la caracterización de la variabilidad climática de 31 años (1985 – 2015) de registros de temperatura, precipitación y caudal del río Chalpi Grande en base a los registros históricos del INAMHI, EPMAPS y FONAG. Estos registros fueron sistematizados y rellenados en base a métodos estadísticos y sensores remotos para la validación de datos. La variabilidad climática muestra incrementos tanto en los comportamientos como en las tendencias de las estaciones de invierno y verano; como también en las tendencias de los parámetros climáticos que pueden ser efecto de los fenómenos atmosféricos, como el problema latente del cambio climático.

The watershed basin of the Chalpi Grande River is located in the Ecuadorian Amazon. This basin, being above 3200 m a.s.l. It has characteristics of Andean and Amazonian ecosystems. The conservation of this basin is extremely important because the supply of 2.2 m3/s for the Metropolitan District of Quito depends on this river. The objective of this research is the characterization of the additional climate of 31 years (1985-2015) of records of temperature, precipitation and flow of the Chalpi Grande River based on the historical records of INAMHI, EPMAPS and FONAG. These were systematized records filled in based on statistical methods and remote sensors for data validation. The climatic temperature shows increases both in the behaviors and in the trends of the winter and summer seasons; as well as in the trends of climatic parameters that can be the effect of atmospheric phenomena, such as the latent problem of climate change., La cuenca hidrográfica del río Chalpi Grande se encuentra ubicada en la amazonia ecuatoriana. Esta cuenca al estar por encima de los 3200 m s.n.m posee características de ecosistemas andinos y amazónicos. La conservación de esta cuenca es de suma importancia debido a que de este río depende el abastecimiento de 2.2 m3/s para el Distrito Metropolitano de Quito. El objetivo de esta investigación es la caracterización de la variabilidad climática de 31 años (1985 – 2015) de registros de temperatura, precipitación y caudal del río Chalpi Grande en base a los registros históricos del INAMHI, EPMAPS y FONAG. Estos registros fueron sistematizados y rellenados en base a métodos estadísticos y sensores remotos para la validación de datos. La variabilidad climática muestra incrementos tanto en los comportamientos como en las tendencias de las estaciones de invierno y verano; como también en las tendencias de los parámetros climáticos que pueden ser efecto de los fenómenos atmosféricos, como el problema latente del cambio climático.

The watershed basin of the Chalpi Grande River is located in the Ecuadorian Amazon. This basin, being above 3200 m a.s.l. It has characteristics of Andean and Amazonian ecosystems. The conservation of this basin is extremely important because the supply of 2.2 m3/s for the Metropolitan District of Quito depends on this river. The objective of this research is the characterization of the additional climate of 31 years (1985-2015) of records of temperature, precipitation and flow of the Chalpi Grande River based on the historical records of INAMHI, EPMAPS and FONAG. These were systematized records filled in based on statistical methods and remote sensors for data validation. The climatic temperature shows increases both in the behaviors and in the trends of the winter and summer seasons; as well as in the trends of climatic parameters that can be the effect of atmospheric phenomena, such as the latent problem of climate change., La cuenca hidrográfica del río Chalpi Grande se encuentra ubicada en la amazonia ecuatoriana. Esta cuenca al estar por encima de los 3200 m s.n.m posee características de ecosistemas andinos y amazónicos. La conservación de esta cuenca es de suma importancia debido a que de este río depende el abastecimiento de 2.2 m3/s para el Distrito Metropolitano de Quito. El objetivo de esta investigación es la caracterización de la variabilidad climática de 31 años (1985 – 2015) de registros de temperatura, precipitación y caudal del río Chalpi Grande en base a los registros históricos del INAMHI, EPMAPS y FONAG. Estos registros fueron sistematizados y rellenados en base a métodos estadísticos y sensores remotos para la validación de datos. La variabilidad climática muestra incrementos tanto en los comportamientos como en las tendencias de las estaciones de invierno y verano; como también en las tendencias de los parámetros climáticos que pueden ser efecto de los fenómenos atmosféricos, como el problema latente del cambio climático.

Hydroclimate affects the radial growth responses of trees, but the drivers of their spatial and population variability are not sufficiently understood. We addressed this issue by sampling several conifer populations located at the same latitude, but at different longitude and elevation in western (W) and eastern (E) Mexican regions. We used dendroecology to disentangle how earlywood width (EW), latewood width (LW) and adjusted LW (LWadj), i.e. the residuals after removing EW influences on LW, responded to climate variables (temperature and precipitation), climate indices (Southern Oscillation Index, SOI, Niño 3.4, Pacific Decadal Oscillation, PDO) and a drought index (Standardised Precipitation-Evapotranspiration Index, SPEI). The W species (Pinus herrerae Martínez, Pinus durangensis Martínez, Abies durangensis Martínez and Cupressus lusitanica Mill.) showed lower growth rates than the E species (Pinus hartwegii Lindl., Picea mexicana Martínez, Pseudotsuga menziesii (Mirb.) Franco and Abies vejari Martínez). Growth in W benefits mostly from high precipitation in the prior winter and current spring and it is limited by high temperatures in spring, whereas growth in the E showed similar but weaker responses. Furthermore, positive (negative) correlations were found in radial growth with the Niño 3.4 (SOI) and the PDO from the prior to current autumns, which were again stronger in absolute terms in the W than in the E regions, excepting SOI in summer. In the W, P. durangensis and C. lusitanica were the least and most responsive species to spring drought, respectively; whilst P. menziesii and A. vejari were very responsive to spring drought compared to P. hartwegii in the E. Our results suggest greater responsiveness to hydroclimate and atmospheric patterns in the W than in the E region. These findings allow better interpretations of future changes in growth and composition in Mexican conifer forests, considering that climate models forecast warmer spring conditions and

The Tumaco multivariate index (TMI) is a multidecadal monthly index constructed with unique time series of sea surface temperature, surface air temperature and rain measured at Tumaco bay, in the southern Pacific coast of Colombia, and available since 1961. In this work, this index is re-evaluated after the addition of in situ sea level data, and its properties for different standardization periods are compared against oceanic El Niño–Southern Oscillation (ENSO) and other derived indices. In particular, we propose a modified TMI, hereinafter referred as TMI4, whose potential to identify the expected sign and the amount of future variations of rain induced by ENSO events in Colombia is analysed for selected extreme episodes. Results indicate that after the inclusion of sea level data, TMI4 can anticipate the development of El Niño events before the ENSO 3 and some other sea surface temperature-based regional indices, although its predictability depends on the ENSO type (canonical or Modoki). The explanation is that sea level includes new information into TMI4 on the onset of El Niño events. In particular, the signal of intraseasonal sea level anomalies carried by downwelling Kelvin waves is detected at Tumaco tide-gauge. Moreover, the analysis of the differences, both in magnitude and spatial distribution, of rainfall anomalies induced by positive (El Niño) and negative (La Niña) ENSO events characterized by TMI4 are regionally presented. As a result, we find that TMI4 is especially suited for extensive northern and western areas of mainland Colombia. For completeness, in the appendix we briefly introduce the semi-automated implementation of TMI4, including a visual interface, which is currently being tested by personnel within the operational oceanography area at Centro de Investigaciones Oceanográficas e Hidrográficas del Pacífico (Dimar-CCCP).

Precipitation prediction at seasonal timescales is important for planning and management of water resources as well as preparedness for hazards such as floods, droughts and wildfires. Quantifying predictability is quite challenging as a consequence of a large number of potential drivers, varying antecedent conditions, and small sample size of high-quality observations available at seasonal timescales, that in turn, increases prediction uncertainty and the risk of model overfitting. Here, we introduce a generalized probabilistic framework to account for these issues and assess predictability under uncertainty. We focus on prediction of winter (Nov-Mar) precipitation across the contiguous United States, using sea surface temperature-derived indices (averaged in Aug-Oct) as predictors. In our analysis we identify "predictability hotspots," which we define as regions where precipitation is inherently more predictable. Our framework estimates the entire predictive distribution of precipitation using copulas and quantifies prediction uncertainties, while employing principal component analysis for dimensionality reduction and a cross validation technique to avoid overfitting. We also evaluate how predictability changes across different quantiles of the precipitation distribution (dry, normal, wet amounts) using a multi-category 3 × 3 contingency table. Our results indicate that well-defined predictability hotspots occur in the Southwest and Southeast. Moreover, extreme dry and wet conditions are shown to be relatively more predictable compared to normal conditions. Our study may help with water resources management in several subregions of the United States and can be used to assess the fidelity of earth system models in successfully representing teleconnections and predictability.

The Indian and Pacific Oceans surround the Maritime Continent (MC). Major modes of sea surface temperature variability in both oceans, including the Indian Ocean Dipole (IOD) and El Niño-Southern Oscillation (ENSO), can strongly affect precipitation on the MC. The prevalence of fires in the MC is closely associated with precipitation amount and terrestrial water storage in September and October. Precipitation and terrestrial water storage, which is a measurement of hydrological drought conditions, are significantly modulated by Indian Ocean Dipole (IOD) and El Niño events. We utilize long-term datasets to study the combined effects of ENSO and the IOD on MC precipitation during the past 100 years (1900-2019) and find that the reductions in MC precipitation and terrestrial water storage are more pronounced during years when El Niño and a positive phase of the IOD (pIOD) coincided. The combined negative effects are produced mainly through an enhanced reduction of upward motion over the MC. Coincident El Niño-pIOD events have occurred more frequently after 1965. However, climate models do not project a higher occurrence of coincident El Niño-pIOD events in a severely warming condition, implying that not the global warming but the natural variability might be the leading cause of this phenomenon.

The Indian and Pacific Oceans surround the Maritime Continent (MC). Major modes of sea surface temperature variability in both oceans, including the Indian Ocean Dipole (IOD) and El Niño-Southern Oscillation (ENSO), can strongly affect precipitation on the MC. The prevalence of fires in the MC is closely associated with precipitation amount and terrestrial water storage in September and October. Precipitation and terrestrial water storage, which is a measurement of hydrological drought conditions, are significantly modulated by Indian Ocean Dipole (IOD) and El Niño events. We utilize long-term datasets to study the combined effects of ENSO and the IOD on MC precipitation during the past 100 years (1900-2019) and find that the reductions in MC precipitation and terrestrial water storage are more pronounced during years when El Niño and a positive phase of the IOD (pIOD) coincided. The combined negative effects are produced mainly through an enhanced reduction of upward motion over the MC. Coincident El Niño-pIOD events have occurred more frequently after 1965. However, climate models do not project a higher occurrence of coincident El Niño-pIOD events in a severely warming condition, implying that not the global warming but the natural variability might be the leading cause of this phenomenon.

Precipitation prediction at seasonal timescales is important for planning and management of water resources as well as preparedness for hazards such as floods, droughts and wildfires. Quantifying predictability is quite challenging as a consequence of a large number of potential drivers, varying antecedent conditions, and small sample size of high-quality observations available at seasonal timescales, that in turn, increases prediction uncertainty and the risk of model overfitting. Here, we introduce a generalized probabilistic framework to account for these issues and assess predictability under uncertainty. We focus on prediction of winter (Nov-Mar) precipitation across the contiguous United States, using sea surface temperature-derived indices (averaged in Aug-Oct) as predictors. In our analysis we identify "predictability hotspots," which we define as regions where precipitation is inherently more predictable. Our framework estimates the entire predictive distribution of precipitation using copulas and quantifies prediction uncertainties, while employing principal component analysis for dimensionality reduction and a cross validation technique to avoid overfitting. We also evaluate how predictability changes across different quantiles of the precipitation distribution (dry, normal, wet amounts) using a multi-category 3 × 3 contingency table. Our results indicate that well-defined predictability hotspots occur in the Southwest and Southeast. Moreover, extreme dry and wet conditions are shown to be relatively more predictable compared to normal conditions. Our study may help with water resources management in several subregions of the United States and can be used to assess the fidelity of earth system models in successfully representing teleconnections and predictability.

Arctic sea ice has decreased substantially and is projected to reach a seasonally ice-free state in the coming decades. Little is known about whether dwindling Arctic sea ice is capable of influencing the occurrence of strong El Niño, a prominent mode of climate variability with global impacts. Based on time slice coupled model experiments, here we show that no significant change in the occurrence of strong El Niño is found in response to moderate Arctic sea-ice loss that is consistent with satellite observations to date. However, as the ice loss continues and the Arctic becomes seasonally ice-free, the frequency of strong El Niño events increases by more than one third, as defined by gradient-based indices that remove mean tropical Pacific warming induced by the seasonally ice-free Arctic. By comparing our time slice experiments with greenhouse warming experiments, we conclude that at least 37-48% of the increase of strong El Niño near the end of the 21st century is associated specifically with Arctic sea-ice loss. Further separation of Arctic sea-ice loss and greenhouse gas forcing only experiments implies that the seasonally ice-free Arctic might play a key role in driving significantly more frequent strong El Niño events.

The El Niño-Southern Oscillation phenomenon leaves its mark both in North America and in South America, both in the natural and cultural coastal landscape, where its implications cover the areas: economic, social, political, cultural and institutional. The objective of the present was to expose four keys so that the population understands said phenomenon. The method used was geographical since it exposes the causes, explains the development and its dynamics over time while proposing a solution to mitigate this phenomenon, especially at the local level. The methodology involved office work complemented with field work on the Mexican coast, particularly in Guerrero. Among the results are: a) a global planisphere where the intensity with which the El Niño-Southern Oscillation affects the different continents is shown in different colors and b) the climatic variability is increasing, so the negative effects for some people and positive for others will continue. Conclusions: 1) El Niño-Southern Oscillation is recurrent in an average period of two to seven years; the phenomenon is identified between the months between December-March of each year and 2) The link between environmental protection with sustainable development is urgent in order to protect human health, increase biodiversity, sustainable management of fragile ecosystems present in coastal areas., El fenómeno El Niño-Oscilación del Sur, deja su impronta tanto en América del Norte como en América del Sur tanto en el paisaje natural como cultural costero donde sus implicaciones abarcan los rubros: económico, social, político, cultural e institucional. El objetivo del presente fue exponer cuatro claves para que la población comprenda dicho fenómeno. El método empleado fue el geográfico dado que expone las causas, explica el desarrollo y su dinámica en el tiempo a le vez que se propone una solución para mitigar dicho fenómeno sobre todo a nivel local. La metodología implicó trabajo de gabinete complementado con trabajo de campo en las costas del litoral mexicano, particularmente en Guerrero. Entre los resultados se tienen: a) un planisferio a nivel global donde se muestra en diversos colores la intensidad con que afecta el Niño-Oscilación del Sur a los diferentes continentes y b) la variabilidad climática cada vez es mayor por lo que, los efectos negativos para algunas personas y positivos para otras continuarán. Conclusiones: 1) El Niño-Oscilación del Sur es recurrente en un periodo promedio de dos a siete años; el fenómeno es identificado entre los meses comprendidos entre diciembre-marzo de cada año y 2) La vinculación entre la protección ambiental con el desarrollo sustentable es urgente a fin de, proteger la salud humana, incremento de la biodiversidad, manejo sostenible de ecosistemas frágiles presentes en las zonas costeras.

Mean wave energy flux (hereinafter WEF) is assessed in the Caribbean Sea from a 60-year (1958–2017) wave hindcast. We use a novel approach, based on neural networks, to identify coherent regions of WEF and their association with different climate patterns. This method allows for a better evaluation of the underlying dynamics behind seasonal and inter-annual WEF variability, including the effect induced by the latitudinal migration of the Intertropical Convergence Zone (ITCZ) and the influence of El Niño-Southern Oscillation (ENSO) events. Results show regional differences in WEF variability likely due to both intensification and migration of the ITCZ. WEF exhibits a strong semi-seasonal signal in areas of the continental shelf, with maxima reached in January and June, in agreement with the known sea surface temperature and sea-level pressure variability patterns. At larger scales, WEF shows a significant correlation with the Oceanic Niño Index (ONI, which is the primary index for tracking the ocean part of ENSO climate pattern), depicting positive values in the central and western sides of the basin and negative ones at the eastern side.

The Tumaco multivariate index (TMI) is a multidecadal monthly index constructed with unique time series of sea surface temperature, surface air temperature and rain measured at Tumaco bay, in the southern Pacific coast of Colombia, and available since 1961. In this work, this index is re-evaluated after the addition of in situ sea level data, and its properties for different standardization periods are compared against oceanic El Niño–Southern Oscillation (ENSO) and other derived indices. In particular, we propose a modified TMI, hereinafter referred as TMI4, whose potential to identify the expected sign and the amount of future variations of rain induced by ENSO events in Colombia is analysed for selected extreme episodes. Results indicate that after the inclusion of sea level data, TMI4 can anticipate the development of El Niño events before the ENSO 3 and some other sea surface temperature-based regional indices, although its predictability depends on the ENSO type (canonical or Modoki). The explanation is that sea level includes new information into TMI4 on the onset of El Niño events. In particular, the signal of intraseasonal sea level anomalies carried by downwelling Kelvin waves is detected at Tumaco tide-gauge. Moreover, the analysis of the differences, both in magnitude and spatial distribution, of rainfall anomalies induced by positive (El Niño) and negative (La Niña) ENSO events characterized by TMI4 are regionally presented. As a result, we find that TMI4 is especially suited for extensive northern and western areas of mainland Colombia. For completeness, in the appendix we briefly introduce the semi-automated implementation of TMI4, including a visual interface, which is currently being tested by personnel within the operational oceanography area at Centro de Investigaciones Oceanográficas e Hidrográficas del Pacífico (Dimar-CCCP).

The El Niño Southern Oscillation (ENSO) is a principal component of global climate variability known to influence a host of social and economic outcomes, but its systematic effects on human health remain poorly understood. We estimate ENSO's association with child nutrition at global scale by combining variation in ENSO intensity from 1986-2018 with children's height and weight from 186 surveys conducted in 51 teleconnected countries, containing 48% of the world's under-5 population. Warmer El Niño conditions predict worse child undernutrition in most of the developing world, but better outcomes in the small number of areas where precipitation is positively affected by warmer ENSO. ENSO's contemporaneous effects on child weight loss are detectable years later as decreases in height. This relationship looks similar at both global and regional scale, and has not appreciably weakened over the last four decades. Results imply that almost 6 million additional children were underweight during the 2015 El Niño compared to a counterfactual of neutral ENSO conditions in 2015. This demonstrates a pathway through which human well-being remains subject to predictable climatic processes.

The El Nino Southern Oscillation (ENSO) dominates the conversation about predictability of climate extremes and early warning and preparedness for floods and droughts, but in Africa other modes of climate variability are also known to influence rainfall anomalies. In this study, we compare the role of ENSO in driving flood hazard over sub-Saharan Africa with modes of climate variability in the Indian and Atlantic Oceans. This is achieved by applying flood frequency approaches to a hydrological reanalysis dataset and streamflow observations for different phases of the ENSO, Indian Ocean Dipole and Tropical South Atlantic climate modes. Our results highlight that Indian and Atlantic Ocean modes of climate variability are equally as important as ENSO for driving changes in the frequency of impactful floods across Africa. We propose that in many parts of Africa a larger consideration of these unsung climate modes could provide improved seasonal predictions of associated flood hazard and better inform adaptation to the changing climate.

The El Nino Southern Oscillation (ENSO) dominates the conversation about predictability of climate extremes and early warning and preparedness for floods and droughts, but in Africa other modes of climate variability are also known to influence rainfall anomalies. In this study, we compare the role of ENSO in driving flood hazard over sub-Saharan Africa with modes of climate variability in the Indian and Atlantic Oceans. This is achieved by applying flood frequency approaches to a hydrological reanalysis dataset and streamflow observations for different phases of the ENSO, Indian Ocean Dipole and Tropical South Atlantic climate modes. Our results highlight that Indian and Atlantic Ocean modes of climate variability are equally as important as ENSO for driving changes in the frequency of impactful floods across Africa. We propose that in many parts of Africa a larger consideration of these unsung climate modes could provide improved seasonal predictions of associated flood hazard and better inform adaptation to the changing climate.

The El Nino Southern Oscillation (ENSO) dominates the conversation about predictability of climate extremes and early warning and preparedness for floods and droughts, but in Africa other modes of climate variability are also known to influence rainfall anomalies. In this study, we compare the role of ENSO in driving flood hazard over sub-Saharan Africa with modes of climate variability in the Indian and Atlantic Oceans. This is achieved by applying flood frequency approaches to a hydrological reanalysis dataset and streamflow observations for different phases of the ENSO, Indian Ocean Dipole and Tropical South Atlantic climate modes. Our results highlight that Indian and Atlantic Ocean modes of climate variability are equally as important as ENSO for driving changes in the frequency of impactful floods across Africa. We propose that in many parts of Africa a larger consideration of these unsung climate modes could provide improved seasonal predictions of associated flood hazard and better inform adaptation to the changing climate.

Trans-Pacific transport of enhanced ozone plumes has been mainly attributed to fossil fuel combustion in Asia in spring, but less attention has been paid to vegetation fires in Asia. Here we show that the El Niño-Southern Oscillation (ENSO)-modulated fires in Southeast Asia, rather than Asian fossil fuel plumes, dominate the interannual variability of springtime trans-Pacific transport of ozone across the entire North Pacific Ocean. During El Niño springs, the intensified fires from both the Indochinese Peninsula and Indonesia, together with large-scale circulation anomalies, result in enhanced ozone plumes that stretch over 15 000 km in both the lower-middle and upper troposphere. This enhancement is also observed in the in situ measurements of ozone concentration, with an almost 10% increase at Mauna Loa Observatory, Hawaii, a unique site to monitor the long-distance transport over the North Pacific. This study reports an unexpectedly strong influence of vegetation fires, linked with climate variability, on global tropospheric chemistry and proves once more how complex the interactions in the climate system are.

The El Nino Southern Oscillation (ENSO) dominates the conversation about predictability of climate extremes and early warning and preparedness for floods and droughts, but in Africa other modes of climate variability are also known to influence rainfall anomalies. In this study, we compare the role of ENSO in driving flood hazard over sub-Saharan Africa with modes of climate variability in the Indian and Atlantic Oceans. This is achieved by applying flood frequency approaches to a hydrological reanalysis dataset and streamflow observations for different phases of the ENSO, Indian Ocean Dipole and Tropical South Atlantic climate modes. Our results highlight that Indian and Atlantic Ocean modes of climate variability are equally as important as ENSO for driving changes in the frequency of impactful floods across Africa. We propose that in many parts of Africa a larger consideration of these unsung climate modes could provide improved seasonal predictions of associated flood hazard and better inform adaptation to the changing climate.

This paper presents the main physical and human-induced stresses that have shaped the recent evolution of the Patía River delta, the largest and best-developed delta on the western margin of South America. During the Holocene, the Patía Delta moved southward and the northern part became an estuarine system characterized by large extensions of mangrove ecosystems. However, a major human-induced water diversion, starting in 1972, diverted the Patía flow to the Sanguianga River, and shifted the active delta plain back to its former Holocene location. This discharge diversion has led to sediment starvation of the southern delta lobe and changed the northern estuarine system into an active delta plain. In addition, coastal areas of the Patía delta subsided as a result of a devastating tsunami in 1979. Morphological changes along the delta coast are evidenced by: (1) coastal retreat along the whole delta front during the period 1986-2001; (2) coastal retreat along the abandoned delta lobe for the period 2001-2008; 56% of the southern delta shoreline is retreating and only 4% of the coast shows signs of accretion; (3) progradation of the northern delta region during the period 2001-2008; the discharge diversion of the Patía River to the Sanquianga has apparently balanced the observed trends in coastal erosion and sea-level rise (5.1mmyr -1 for the period 1984-2006, after the 1979 tsunami); (4) formation of transgressive barrier islands with exposed peat soils in the surf zone; and (5) abandonment of former active distributaries in the southern delta plain with associated inlet closure. In the northern delta lobe, major geomorphic changes include: (1) distributary channel accretion by morphological processes such as sedimentation (also in crevasses), overbank flow, increasing width of levees, inter-distributary channel fill, and colonization of pioneer mangrove; (2) freshening conditions in the Sanguianga distributary channel, a hydrologic change that has shifted the upper

The stratigraphic, geochemical, and organic matter study of the late Holocene San Nicolás succession of the Cauca paleolake (Santa Fé-Sopetrán pull-apart basin) in the middle Cauca Valley, northern Colombia, suggests that it was deposited in a ria lake environment, at sedimentary accumulation rates in excess of 600 cm ky-1 between ~3500 and ~500 yr BP. Laminated deposition occurred, first under igapo (black-water), and then under varzea (white-water) conditions. The transition occurred ca. 3000 yr BP, a time of major change in El Niño/Southern Oscillation (ENSO) behavior in the Cariaco Basin, thus reflecting the southern migration of the intertropical convergence zone and intensified rain upstream the Cauca Valley. A second, but less conspicuous change occurred ca. 2000 yr BP, which apparently corresponds to the intensified and/or more frequent ENSO activity in the Galapagos Islands. Our contribution describes, for the first time, a ria lake sedimentary succession from the northern Andes and demonstrates the high potential of these hitherto undervalued deposits for the reconstruction of the paleohydrological history of the northern Andes. © 2012 Springer Science+Business Media Dordrecht.

The Atlantic Multidecadal Oscillation (AMO), is a major driving climate mechanism, in the eastern Caribbean Sea and the South Atlantic Ocean in relation to the dynamics of the South American Monsoon System (SAMS) for the late Holocene. Here we document the AMO signal in the San Nicolás-1 core of the Cauca paleolake (Santa Fé-Sopetrán Basin) in the northern Andes. Wavelet spectrum analysis of the gray scale of the San Nicolás-1 core provides evidence for a 70 yr AMO periodicity for the 3750 to 350 yr BP time interval, whose pattern is analogous to the one documented for the Cariaco Basin. This supports a possible correlation between enhanced precipitation and ENSO variability with a positive AMO phase during the 2000 to 1500 yr BP interval, and its forcing role on the Cauca ria lake deposits, which led to increased precipitation and to the transition from a igapo (black water) to a varzea (white water) environment ca. 3000 yr BP. © Author(s) 2015.

Tropical Pacific upwelling-dependent ecosystems are the most productive and variable worldwide, mainly due to the influence of El Niño Southern Oscillation (ENSO). ENSO can be forecasted seasons ahead thanks to assorted climate precursors (local-Pacific processes, pantropical interactions). However, owing to observational data scarcity and bias-related issues in earth system models, little is known about the importance of these precursors for marine ecosystem prediction. With recently released reanalysis-nudged global marine ecosystem simulations, these constraints can be sidestepped, allowing full examination of tropical Pacific ecosystem predictability. By complementing historical fishing records with marine ecosystem model data, we show herein that equatorial Atlantic Sea Surface Temperatures (SSTs) constitute a superlative predictability source for tropical Pacific marine yields, which can be forecasted over large-scale areas up to 2 years in advance. A detailed physical-biological mechanism is proposed whereby Atlantic SSTs modulate upwelling of nutrient-rich waters in the tropical Pacific, leading to a bottom-up propagation of the climate-related signal across the marine food web. Our results represent historical and near-future climate conditions and provide a useful springboard for implementing a marine ecosystem prediction system in the tropical Pacific

The El Niño-Southern Oscillation (ENSO), which includes El Niño and La Niña phases, affects oceanographic conditions and primary productivity of marine ecosystems at a global scale. During El Niño events, warm temperatures in the central and eastern tropical Pacific de crease primary productivity, affecting the biology of many species including sea turtles. We aimed to determine the effect of ENSO (as a global index) and primary productivity in the foraging areas (as a local index) on remigration intervals (number of years between nesting seasons) and seasonal reproductive output (clutch size and number of clutches in a season) of green turtles Chelonia mydas in the North Pacific off Costa Rica, an area highly influenced by ENSO. We used the Multivariate ENSO Index (MEI) and mean values of chlorophyll a from previously identified feeding areas for this population over different time periods (up to 3 yr before the nesting season). Chlorophyll a levels in foraging areas and MEI strongly influenced the reproductive frequency of green turtles. Variability in the remigration intervals was better explained by models that in - cluded chlorophyll levels 2 and 3 yr before the onset of the nesting season and MEI conditions in the previous 3 yr. Models using global and local indexes were equally good at predicting changes in the remigration intervals. Positive values of MEI (El Niño phase) and lower levels of chlorophyll a corresponded to longer remigration intervals. No statistically significant relationships were found between seasonal reproductive output and MEI or chlorophyll a levels. As El Niño events may become more frequent and last longer due to climate change, the lifetime reproductive output of green turtles in this area may be compromised in the future.

The El Nino Southern Oscillation (ENSO) dominates the conversation about predictability of climate extremes and early warning and preparedness for floods and droughts, but in Africa other modes of climate variability are also known to influence rainfall anomalies. In this study, we compare the role of ENSO in driving flood hazard over sub-Saharan Africa with modes of climate variability in the Indian and Atlantic Oceans. This is achieved by applying flood frequency approaches to a hydrological reanalysis dataset and streamflow observations for different phases of the ENSO, Indian Ocean Dipole and Tropical South Atlantic climate modes. Our results highlight that Indian and Atlantic Ocean modes of climate variability are equally as important as ENSO for driving changes in the frequency of impactful floods across Africa. We propose that in many parts of Africa a larger consideration of these unsung climate modes could provide improved seasonal predictions of associated flood hazard and better inform adaptation to the changing climate.

Antarctic sea ice has paradoxically become more extensive over the past four decades despite a warming climate. The regional expression of this trend has been linked to changes in vertical redistribution of ocean heat and large-scale wind-field shifts. However, the short length of modern observations has hindered attempts to attribute this trend to anthropogenic forcing or natural variability. Here, we present two new decadal-resolution records of sea ice and sea surface temperatures that document pervasive regional climate heterogeneity in Indian Antarctic sea-ice cover over the last 2,000 years. Data assimilation of our marine records in a climate model suggests that the reconstructed dichotomous regional conditions were driven by the multi-decadal variability of the El Niño Southern Oscillation and Southern Annular Mode (SAM). For example, during an El Niño/SAM– combination, the northward sea-ice transport was reduced while heat advection from the subtropics to the Southern Ocean increased, which resulted in reduced sea-ice extent in the Indian sector as sea ice was compacted along the Antarctic coast. Our results therefore indicate that natural variability is large in the Southern Ocean and suggest that it has played a crucial role in the recent sea-ice trends and their decadal variability in this region.

Several countries are extremely susceptible to climate change and the El Niño-costero phenomenon affected more than two million people in Ecuador, Colombia, and Peru. We aimed to evaluate the microbiological quality of stagnant waters in Lambayeque region, Peru during the lockdown caused by El Niño-costero phenomenon. We conducted a cross-sectional study performed in the four Lambayeque’s districts: (Chiclayo’s downtown, Mocupe, San José, and Pimentel), Perú. Two simultaneous samples were taken from each evaluation districts and were transported to Laboratory for their entire microbiological analysis. We isolate of human-pathogenic parasite (Trichuris trichiura (Linnaeus, 1771) and Entamoeba histolytica Schaudinn, 1903), and bacteria (Staphylococcus aureus Rosenbach 1884 and Salmonella typhi (Schroeter, 1886)) that showed patterns of resistance to conventional first-line antimicrobials (penicillin, nalidixic acid, nitrofurantoin, and chloramphenicol). Likewise, we showed evidence of microorganisms related to the sampling site (district) and with the degree of affectation by the phenomenon. Our result suggests that the stagnant waters of four districts of Lambayeque presented Human-pathogenic parasites and bacteria of high-medical importance by the sudden changes in the climate through El Niño-costero phenomenon., Varios países son extremadamente susceptibles al cambio climático y el fenómeno El Niño-costero afectó a más de dos millones de personas en Ecuador, Colombia y Perú. Nuestro objetivo fue evaluar la calidad microbiológica de las aguas estancadas en la región de Lambayeque, Perú, durante el estado de emergencia causado por el fenómeno El Niño-costero mediante un estudio transversal realizado en cuatro distritos de Lambayeque: (Centro de Chiclayo, Mocupe, San José y Pimentel), Perú. Se tomaron dos muestras simultáneas de cada distrito de evaluación, y se trasladaron a Lima para su análisis microbiológico completo. Aislamos parásitos patógenos humanos (Trichuris trichiura (Linnaeus, 1771) y Entamoeba histolytica Schaudinn, 1903) y bacterias (Staphylococcus aureus Rosenbach, 1884 y Salmonella typhi (Schroeter, 1886)) que presentaban patrones de resistencia a los antimicrobianos convencionales de primera línea (penicilina, ácido nalidíxico, nitrofurantoína y cloranfenicol). Asimismo, mostramos evidencia de microorganismos relacionados con el sitio de muestreo (distrito) y con el grado de afectación por el fenómeno. Nuestro resultado sugiere que las aguas estancadas de cuatro distritos de Lambayeque presentaron parásitos patógenos humanos y bacterias de alta importancia médica por los cambios repentinos en el clima a través del fenómeno El Niño-costero.

In the California Current Ecosystem, El Niño acts as a natural phenomenon that is partially representative of climate change impacts on marine bacteria at timescales relevant to microbial communities. Between 2014-2016, the North Pacific warm anomaly (a.k.a., the "blob") and an El Niño event resulted in prolonged ocean warming in the Southern California Bight (SCB). To determine whether this "marine heatwave" resulted in shifts in microbial populations, we sequenced the rpoC1 gene from the biogeochemically important picocyanobacteria Prochlorococcus and Synechococcus at 434 time points from 2009-2018 in the MICRO time series at Newport Beach, CA. Across the time series, we observed an increase in the abundance of Prochlorococcus relative to Synechococcus as well as elevated frequencies of ecotypes commonly associated with low-nutrient and high-temperature conditions. The relationships between environmental and ecotype trends appeared to operate on differing temporal scales. In contrast to ecotype trends, most microdiverse populations were static and possibly reflect local habitat conditions. The only exceptions were microdiversity from Prochlorococcous HLI and Synechococcus Clade II that shifted in response to the 2015 El Niño event. Overall, Prochlorococcus and Synechococcus populations did not return to their pre-heatwave composition by the end of this study. This research demonstrates that extended warming in the SCB can result in persistent changes in key microbial populations.

This study compares the impacts of the El Niño–Southern Oscillation (ENSO) on sea surface temperatures (SSTs) in the tropical North Atlantic Ocean and the tropical Indian Ocean during 1958–2004. It is found that the tropical atmospheric processes mediating the ENSO impacts are different between the two oceans for two reasons. First, the ENSO-induced anomalous Walker circulation is more extensive over the Atlantic than over the Indian Ocean. As a result, the atmospheric bridge (AB) mechanism is the major contributor to the differences in ENSO teleconnections between the two oceans. Secondly, SSTs in the tropical North Atlantic are under a greater control of the atmospheric thermal forcing than those in the tropical Indian Ocean. Due to these different controls, the tropospheric temperature (TT) mechanism also contributes to the different ENSO teleconnections. When compared with the observations, the mean of thirty-seven models from the Coupled Model Intercomparison Project Phase 5 overestimates the ENSO-induced SST response in the tropical Indian Ocean but underestimates the response in the tropical North Atlantic. The overestimation is brought about by a westward extension of ENSO SST anomalies in the models, which causes the AB mechanism to produce an overly strong impact on Indian Ocean SSTs. On the other hand, the underestimation is caused by a weaker-than-observed sensitivity in the simulated Atlantic SSTs to the thermal forcing produced by the TT mechanism.

Information theoretic (IT) approaches to quantifying causal influences have experienced some popularity in the literature, in both theoretical and applied (e.g., neuroscience and climate science) domains. While these causal measures are desirable in that they are model agnostic and can capture non-linear interactions, they are fundamentally different from common statistical notions of causal influence in that they (1) compare distributions over the effect rather than values of the effect and (2) are defined with respect to random variables representing a cause rather than specific values of a cause. We here present IT measures of direct, indirect, and total causal effects. The proposed measures are unlike existing IT techniques in that they enable measuring causal effects that are defined with respect to specific values of a cause while still offering the flexibility and general applicability of IT techniques. We provide an identifiability result and demonstrate application of the proposed measures in estimating the causal effect of the El Niño-Southern Oscillation on temperature anomalies in the North American Pacific Northwest.

Fire emissions of gases and aerosols alter atmospheric composition and have substantial impacts on climate, ecosystem function, and human health. Warming climate and human expansion in fire-prone landscapes exacerbate fire impacts and call for more effective management tools. Here we developed a global fire forecasting system that predicts monthly emissions using past fire data and climate variables for lead times of 1 to 6 months. Using monthly fire emissions from the Global Fire Emissions Database (GFED) as the prediction target, we fit a statistical time series model, the Autoregressive Integrated Moving Average model with eXogenous variables (ARIMAX), in over 1,300 different fire regions. Optimized parameters were then used to forecast future emissions. The forecast system took into account information about region-specific seasonality, long-term trends, recent fire observations, and climate drivers representing both large-scale climate variability and local fire weather. We cross-validated the forecast skill of the system with different combinations of predictors and forecast lead times. The reference model, which combined endogenous and exogenous predictors with a 1 month forecast lead time, explained 52% of the variability in the global fire emissions anomaly, considerably exceeding the performance of a reference model that assumed persistent emissions during the forecast period. The system also successfully resolved detailed spatial patterns of fire emissions anomalies in regions with significant fire activity. This study bridges the gap between the efforts of near-real-time fire forecasts and seasonal fire outlooks and represents a step toward establishing an operational global fire, smoke, and carbon cycle forecasting system.

The El Nino-Southern Oscillation (ENSO) is one of the most significant climate variability signals. Studying the changes in ENSO-induced precipitation variability (ENSO precipitation) in the past climate offers a possibility to a better understanding of how they may change under future climate conditions. This study uses simulations performed with the European community Earth-System Model (EC-Earth) to investigate the relative contributions of dynamic effect (the circulation anomalies together with the climatological specific humidity) and thermodynamic effect (the specific humidity anomalies together with the climatological circulation) on the changes in ENSO precipitation in the past warm and cold climates, represented by the Pliocene and the Last Glacial Maximum (LGM), respectively. The results show that the changes in ENSO precipitation are intensified (weakened) over the tropical western Pacific but weakened (intensified) over the tropical central Pacific in Pliocene (LGM) compared with the pre-industrial (PI) simulation. Based on the decomposed moisture budget equation, these changes in ENSO precipitation patterns are highly related to the dynamic effect. The mechanism can be understood as follows: the zonal gradient of the mean sea surface temperature (SST) over the tropical Indo-Pacific is increased (reduced) during the Pliocene (LGM), leading to the strengthening (weakening) of Pacific Walker Circulation as well as a westward (eastward) shift. In the Pliocene, the westward shift of Walker Circulation results in an increased (decreased) ENSO-induced low-level vertical velocity variability in the tropical western Pacific (central Pacific), and, in turn, favoring convergent (divergent) moisture transport through a dynamic process, and then causing intensified (weakened) ENSO precipitation there. The opposite mechanism exists in LGM. These results suggest that changes in the zonal SST gradient over tropical Indo-Pacific under different climate conditions determ

Fire emissions of gases and aerosols alter atmospheric composition and have substantial impacts on climate, ecosystem function, and human health. Warming climate and human expansion in fire-prone landscapes exacerbate fire impacts and call for more effective management tools. Here we developed a global fire forecasting system that predicts monthly emissions using past fire data and climate variables for lead times of 1 to 6 months. Using monthly fire emissions from the Global Fire Emissions Database (GFED) as the prediction target, we fit a statistical time series model, the Autoregressive Integrated Moving Average model with eXogenous variables (ARIMAX), in over 1,300 different fire regions. Optimized parameters were then used to forecast future emissions. The forecast system took into account information about region-specific seasonality, long-term trends, recent fire observations, and climate drivers representing both large-scale climate variability and local fire weather. We cross-validated the forecast skill of the system with different combinations of predictors and forecast lead times. The reference model, which combined endogenous and exogenous predictors with a 1 month forecast lead time, explained 52% of the variability in the global fire emissions anomaly, considerably exceeding the performance of a reference model that assumed persistent emissions during the forecast period. The system also successfully resolved detailed spatial patterns of fire emissions anomalies in regions with significant fire activity. This study bridges the gap between the efforts of near-real-time fire forecasts and seasonal fire outlooks and represents a step toward establishing an operational global fire, smoke, and carbon cycle forecasting system.

This study compares the impacts of the El Niño–Southern Oscillation (ENSO) on sea surface temperatures (SSTs) in the tropical North Atlantic Ocean and the tropical Indian Ocean during 1958–2004. It is found that the tropical atmospheric processes mediating the ENSO impacts are different between the two oceans for two reasons. First, the ENSO-induced anomalous Walker circulation is more extensive over the Atlantic than over the Indian Ocean. As a result, the atmospheric bridge (AB) mechanism is the major contributor to the differences in ENSO teleconnections between the two oceans. Secondly, SSTs in the tropical North Atlantic are under a greater control of the atmospheric thermal forcing than those in the tropical Indian Ocean. Due to these different controls, the tropospheric temperature (TT) mechanism also contributes to the different ENSO teleconnections. When compared with the observations, the mean of thirty-seven models from the Coupled Model Intercomparison Project Phase 5 overestimates the ENSO-induced SST response in the tropical Indian Ocean but underestimates the response in the tropical North Atlantic. The overestimation is brought about by a westward extension of ENSO SST anomalies in the models, which causes the AB mechanism to produce an overly strong impact on Indian Ocean SSTs. On the other hand, the underestimation is caused by a weaker-than-observed sensitivity in the simulated Atlantic SSTs to the thermal forcing produced by the TT mechanism.

Information theoretic (IT) approaches to quantifying causal influences have experienced some popularity in the literature, in both theoretical and applied (e.g., neuroscience and climate science) domains. While these causal measures are desirable in that they are model agnostic and can capture non-linear interactions, they are fundamentally different from common statistical notions of causal influence in that they (1) compare distributions over the effect rather than values of the effect and (2) are defined with respect to random variables representing a cause rather than specific values of a cause. We here present IT measures of direct, indirect, and total causal effects. The proposed measures are unlike existing IT techniques in that they enable measuring causal effects that are defined with respect to specific values of a cause while still offering the flexibility and general applicability of IT techniques. We provide an identifiability result and demonstrate application of the proposed measures in estimating the causal effect of the El Niño-Southern Oscillation on temperature anomalies in the North American Pacific Northwest.

In the California Current Ecosystem, El Niño acts as a natural phenomenon that is partially representative of climate change impacts on marine bacteria at timescales relevant to microbial communities. Between 2014-2016, the North Pacific warm anomaly (a.k.a., the "blob") and an El Niño event resulted in prolonged ocean warming in the Southern California Bight (SCB). To determine whether this "marine heatwave" resulted in shifts in microbial populations, we sequenced the rpoC1 gene from the biogeochemically important picocyanobacteria Prochlorococcus and Synechococcus at 434 time points from 2009-2018 in the MICRO time series at Newport Beach, CA. Across the time series, we observed an increase in the abundance of Prochlorococcus relative to Synechococcus as well as elevated frequencies of ecotypes commonly associated with low-nutrient and high-temperature conditions. The relationships between environmental and ecotype trends appeared to operate on differing temporal scales. In contrast to ecotype trends, most microdiverse populations were static and possibly reflect local habitat conditions. The only exceptions were microdiversity from Prochlorococcous HLI and Synechococcus Clade II that shifted in response to the 2015 El Niño event. Overall, Prochlorococcus and Synechococcus populations did not return to their pre-heatwave composition by the end of this study. This research demonstrates that extended warming in the SCB can result in persistent changes in key microbial populations.

Late Quaternary volcanic basins are active landscapes from which detailed archives of past climate and seismic and volcanic activity can be obtained. A multidisciplinary study performed on a transect of sediment cores was used to reconstruct the depositional evolution of the highelevation Laguna del Maule (LdM) (36 S, 2180ma.s.l., Chilean Andes). The recovered 5m composite sediment sequence includes two thick turbidite units (LT1 and LT2) and numerous tephra layers (23 ash and 6 lapilli). We produced an age model based on nine new 14C AMS dates, existing 210Pb and 137Cs data, and the Quizapú ash horizon (1932 CE). According to this age model, the relatively drier Early Holocene was followed by a phase of increased productivity during the mid-Holocene and higher lake levels after 4.0 ka cal BP. Major hydroclimate transitions occurred at ca. 11, 8.0, 4.0 and 0.5 ka cal BP. Decreased summer insolation and winter precipitation due to a southward shift in the southern westerly winds and a strengthened Pacific Subtropical High could explain Early Holocene lower lake levels. Increased biological productivity during the mid- Holocene ( 8:0 to 6.0 ka cal BP) is coeval with a warm-dry phase described for much of southern South America. Periods of higher lake productivity are synchronous to a higher frequency of volcanic events. During the Late Holocene, the tephra layers show compositional changes suggesting a transition from silica-rich to silica-poor magmas at around 4.0 ka cal BP. This transition was synchronous with increased variability of sedimentary facies and geochemical proxies, indicating higher lake levels and increased moisture at LdM after 4.0 ka cal BP, most likely caused by the inception of current El Niño-Southern Oscillation and Pacific Decadal Oscillation (ENSO-PDO) dynamics in central Chile. © 2020 Copernicus GmbH. All rights reserved.

Nonstructural carbohydrates (NSCs) are essential for maintenance of plant metabolism and may be sensitive to short- and long-term climatic variation. NSC variation in moist tropical forests has rarely been studied, so regulation of NSCs in these systems is poorly understood. We measured foliar and branch NSC content in 23 tree species at three sites located across a large precipitation gradient in Panama during the 2015-2016 El Niño to examine how short- and long-term climatic variation impact carbohydrate dynamics. There was no significant difference in total NSCs as the drought progressed (leaf P = 0.32, branch P = 0.30) nor across the rainfall gradient (leaf P = 0.91, branch P = 0.96). Foliar soluble sugars decreased while starch increased over the duration of the dry period, suggesting greater partitioning of NSCs to storage than metabolism or transport as drought progressed. There was a large variation across species at all sites, but total foliar NSCs were positively correlated with leaf mass per area, whereas branch sugars were positively related to leaf temperature and negatively correlated with daily photosynthesis and wood density. The NSC homoeostasis across a wide range of conditions suggests that NSCs are an allocation priority in moist tropical forests.

Nonstructural carbohydrates (NSCs) are essential for maintenance of plant metabolism and may be sensitive to short- and long-term climatic variation. NSC variation in moist tropical forests has rarely been studied, so regulation of NSCs in these systems is poorly understood. We measured foliar and branch NSC content in 23 tree species at three sites located across a large precipitation gradient in Panama during the 2015-2016 El Niño to examine how short- and long-term climatic variation impact carbohydrate dynamics. There was no significant difference in total NSCs as the drought progressed (leaf P = 0.32, branch P = 0.30) nor across the rainfall gradient (leaf P = 0.91, branch P = 0.96). Foliar soluble sugars decreased while starch increased over the duration of the dry period, suggesting greater partitioning of NSCs to storage than metabolism or transport as drought progressed. There was a large variation across species at all sites, but total foliar NSCs were positively correlated with leaf mass per area, whereas branch sugars were positively related to leaf temperature and negatively correlated with daily photosynthesis and wood density. The NSC homoeostasis across a wide range of conditions suggests that NSCs are an allocation priority in moist tropical forests.

Streams and rivers process and transport carbon to downstream systems and are important components of global and regional carbon budgets. Ecosystem functions, including gross primary production (GPP) and ecosystem respiration (ER), can be used to improve understanding of carbon cycling and ecosystem health in lotic systems. Whole-stream metabolism (GPP and ER) has been studied extensively in headwater streams. However, we know less about the variability in GPP and ER in aridland rivers and tributary streams despite being globally abundant and vulnerable systems to changing climate. This dissertation explores temporal and spatial variation of GPP and ER in a montane stream and along the Middle Rio Grande (MRG) using long-term, high-resolution water quality data. Analysis of temporal signals reveal strong inter-annual variability in ER and GPP and shifts from autotrophic to heterotrophic status within and across years for these open canopy sites. We found snowmelt discharge to be an important driver of metabolism, however, the response varied across sites either increasing or decreasing with increasing snowmelt. During the summer, short and frequent pulses in turbidity levels from monsoon rainstorms decreased GPP at sites along the MRG. Our findings suggest that complex combinations of temporally variable factors such as snow accumulation and melt, and their role in connecting terrestrial and aquatic ecosystems, can lead to substantial within-stream variation in autotrophic or heterotrophic status. At sites along the MRG, a combination of discharge, turbidity, geomorphology and substrate type are key determinants of daily GPP and trophic conditions.