Search NASA⌕ Search

SEARCH · Search NASA

Results for “El Niño”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Tropical Three-dimensional Cloud Climatology during El Niño Events with CALIPSO Level-3 Cloud Products

The El Niño–Southern Oscillation (ENSO) is a large-scale climatic phenomenon that originates in the tropical Pacific Ocean but affects global climate patterns. Its warm phase El Niño occurs irregularly every two to seven years and peaks in winter. A previous case study showed opposite cloud anomalies at high, middle and low altitude regions during a weak 2006/2007 El Niño and a moderate 2009/2010 El Niño, suggesting a non-linear response of tropical clouds to El Niño sea surface temperature (SST) forcing. To further understand the cloud response to SST, we examine the three-dimensional (3-D) cloud anomalies during all recent five El Niño events since 2006 using level-3 (L3) cloud products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission. During its 17+ years operation, CALIPSO delivered near-global measurements of cloud and aerosol profiles at unprecedented high resolution and sensitivity. In this work, we provide a comprehensive picture of cloud anomalies during El Niño, with a particular focus on thin cirrus clouds at high altitudes, which are challenging for passive sensor detection algorithms. Specifically, the vertical cloud anomalies are calculated with the L3 3-D Cloud Occurrence Product, the horizontal cloud anomalies are from the L3 Global Energy and Water Exchanges (GEWEX) product, and the ice cloud extinction profiles and ice water content are obtained from the L3 Ice Cloud product. These findings will improve current knowledge of ENSO from a new perspective.

El Nino↗
NASA NTRS2017

Large Anomalies in Lower Stratospheric Water Vapor and Ice During the 2015–2016 El Niño

The strong and unusual El Niño of 2015-2016 produced a remarkable perturbation to the hydrologic budget of the tropical tropopause layer (14-19 km). This region regulates stratospheric water vapor, which has a direct radiative impact on surface temperatures. To first order, the coldest tropical tropopause temperature regulates the amount of water vapor entering the stratosphere by controlling the amount of dehydration in the rising air. Here we show that tropical convective cloud ice and associated cirrus evaporating at unusually high altitudes might also have a role in stratospheric hydration. The 2015-2016 El Niño produced decadal record water vapor amounts in the tropical Western Pacific, coincident with warm tropopause temperature anomalies. In the Central Pacific, convective cloud ice was observed 2 km above the anomalously cold tropopause. A trajectory-based dehydration model based on two reanalysis temperature and wind fields can account for only about 0.5-0.6 ppmv of the ~0.9 ppmv tropical lower stratospheric moistening observed during this event. This suggests that unresolved convective dynamics and/or associated sublimation of lofted ice particles also contributed to lower stratospheric moistening. These observations suggest that convective moistening could contribute to future climate change-induced stratospheric water vapor increases.

Atmospheric chemistry↗
NASA NTRS2018

Connecting Indonesian Fires and Drought With the Type of El Niño and Phase of the Indian Ocean Dipole During 1979-2016

This study advances the previous understanding of the role of climate variability on Indonesian fire activity, by considering (i) the presence of different types of El Niño and (ii) the interaction between El Niño and the Indian Ocean Dipole (IOD). We classify 12 El Niño events during 1979-2016 into Eastern Pacific (EP) and Central Pacific (CP) types (four and eight El Niño events, respectively) and analyze observational data of sea surface temperature, precipitation, drought code, biomass burning carbon emission, visibility, and aerosol optical depth accordingly. We find that more intense and prolonged Indonesian drought and fires occur in the EP type, during which the emitted carbon amounts almost double those in the CP type. By further separating the CP type El Niño according to the phase of the IOD, that is, positive and negative, we show that fire seasons with less burning intensity and shorter duration are predominantly associated with weakly positive or even negative phase of the IOD phenomena. Moreover, fire intensity exhibits geographic diversity: fires are always more intensive in southern Kalimantan than in southern Sumatra in all El Niño events, although it is less dry in the former region. The outcome of this study can be applied to drought early warning, fire management, and air quality forecast in Indonesia and adjacent areas by identifying the type of El Niño and the phase of the IOD in advance.

IOD phenomena↗
NASA NTRS2019

El Niño Related Tropical Land Surface Water and Energy Response in MERRA-2

The El Niño Southern Oscillation (ENSO) is a coupled Earth system circulation phenomena that reaches all around the globe. The heat added to the atmosphere by increased precipitation produces circulation changes that have global reach and, over time, warms the entire tropical band, and much of the Earth. Many studies have noted that El Niño causes warm and dry (and sometimes drought) conditions over tropical land masses. We develop a composite analysis of El Niño to identify the predominate features of tropical land response. This analysis shows that the land’s lagged response is related to a reduction clouds that leads to increase surface shortwave radiation that increases the surface temperature. The precipitation lag is somewhat longer, and then leads to a reduction in soil water and, in concert with increased SW induced surface warming, leads to increased sensible heating of the atmosphere above. The M2AMIP simulation generally captures these features, but the response is strongest with increased temporal and spatial proximity to the El Niño peak warming. The regionality of these features is also discussed, and it is noted that even the strongest individual El Niño events can vary from this composite mechanistic paradigm.

Bosilovich, Michael G.↗
NASA NTRS2020

El Niño Related Tropical Land Surface Water and Energy Response in MERRA-2

Though El Niño events each have distinct evolutionary character they typically provide systematic large scale forcing for warming and increased drought frequency across the tropical continents. We assess this response in the MERRA-2 reanalysis and in a ten-member model AMIP ensemble. The lagged response (3-4 months) of mean tropical land temperature to El Niño warming in the Pacific Ocean is well represented. MERRA-2 reproduces the patterns of precipitation in the tropical regions, while the AMIP ensemble reproduces some regional responses better than others. Model skill is dependent on event forcing strength and temporal proximity to the peak of the sea surface warming. A composite approach centered on maximum Niño3.4 SSTs and lag relationships to energy fluxes and transports is used to identify mechanisms supporting tropical land warming. The composite necessarily moderates weather scale variability of the individual events, while retaining the systematic features across all events. We find that that reduced continental upward motions lead to reduced cloudiness and more shortwave radiation at the surface, as well as reduced precipitation. The increased shortwave heating at the land surface, along with reduced soil moisture leads to warmer surface temperature, more sensible heating and warming of the lower troposphere. While the composite provides a broad picture of the mechanisms governing the hydrologic response to El Niño forcing, the regional and temporal response in any given event can be quite variable. The 2015-16 El Niño, one of the strongest events, demonstrates some of the forced response noted in the composite, but with shifts in the evolution that depart from the composite, demonstrating the limitations of the composite and individuality of El Niño.

Michael G Bosilovich↗
NASA NTRS2023

Explainable deep learning for insights in El Niño and river flows

The El Niño Southern Oscillation (ENSO) is a semi-periodic fluctuation in sea surface temperature (SST) over the tropical central and eastern Pacific Ocean that influences interannual variability in regional hydrology across the world through long-range dependence or teleconnections. Recent research has demonstrated the value of Deep Learning (DL) methods for improving ENSO prediction as well as Complex Networks (CN) for understanding teleconnections. However, gaps in predictive understanding of ENSO-driven river flows include the black box nature of DL, the use of simple ENSO indices to describe a complex phenomenon and translating DL-based ENSO predictions to river flow predictions. Here we show that eXplainable DL (XDL) methods, based on saliency maps, can extract interpretable predictive information contained in global SST and discover SST information regions and dependence structures relevant for river flows which, in tandem with climate network constructions, enable improved predictive understanding. Our results reveal additional information content in global SST beyond ENSO indices, develop understanding of how SSTs influence river flows, and generate improved river flow prediction, including uncertainty estimation. Observations, reanalysis data, and earth system model simulations are used to demonstrate the value of the XDL-CN based methods for future interannual and decadal scale climate projections.

SST↗
NASA NTRS2020

Satellite Sea Surface Salinity Observations Impact on El Niño/Southern Oscillation Predictions: Case Studies from the NASA GEOS Seasonal Forecast System

El Niño/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would have great societal benefit. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean salinity. Satellite sea surface salinity (SSS), combined with temperature, help to improve the estimates of ocean density changes and associated near-surface mixing. For the first time, we assess the impact of satellite SSS observations for improving near-surface dynamics within ocean reanalyses and how these initializations impact dynamical ENSO forecasts using NASA’s coupled forecast system (GEOS-S2S-2). For all initialization experiments, all available sea level and in situ temperature and salinity observations are assimilated. Separate observing system experiments (OSE) additionally assimilate Aquarius, and SMAP, SMOS, and these datasets combined. We highlight the impact of satellite SSS on ocean reanalyses by comparing experiments with and without the application of SSS assimilation. Next, we compare case studies of coupled forecasts for the big 2015 El Niño, the 2017 La Niña, and the weak El Niño in 2018 that are initialized from GEOS-S2S-2 spring reanalyses that assimilate and withhold along-track SSS. For each of these ENSO-event case studies, assimilation of satellite SSS improves the forecast validation with respect to observed NINO3.4 anomalies (or at least reduces the forecast uncertainty). Satellite SSS assimilation improved characterization of the mixed layer depth leading to more accurate coupled air/sea interaction and better forecasts. These results further underline the value of satellite SSS assimilation into operational forecast systems.

Eric Hackert↗
NASA NTRS2023

Tropical Three-dimensional Cloud Climatology during El Niño Events with CALIPSO Level-3 Cloud Products

A previous case study showed opposite cloud anomalies at high, middle and low altitude regions during a weak 2006/2007 El Niño and a moderate 2009/2010 El Niño. In this work, we use CALIPSO Level 3 (L3) Cloud Products to provide a comprehensive picture of cloud anomalies during all recent five El Niño events since 2006, with a particular focus on thin cirrus clouds at high altitudes, which are challenging for passive sensor detection algorithms. Specifically, the vertical cloud anomalies are calculated with the L3 Cloud Occurrence Product, the horizontal cloud anomalies are from the L3 GEWEX product, and the ice cloud extinction profiles and ice water content are obtained from the L3 Ice Cloud product. The cloud anomalies are further analyzed with the magnitude and pattern of sea surface temperature (SST) anomalies. These findings will improve current knowledge of ENSO from a new perspective.

El Nino↗
NASA NTRS2024

Investigating the Strength and Variability of El Niño Southern Oscillation Teleconnections to Hydroclimate and Maize Yields in Southern and East Africa

The state of the El Niño Southern Oscillation (ENSO) is critical for seasonal climate forecasts, but recent events diverged substantially from expectations in many regions, including Sub-Saharan Africa where seasonal forecasts are critical tools for addressing food security. Here, we evaluate 39 years (1982–2020) of data on hydroclimate, leaf area index, and maize yields to investigate the strength of ENSO teleconnections in southern and East Africa. Teleconnections to precipitation, soil moisture, and leaf area index are generally stronger during ENSO phases that cause drought conditions (El Niño in southern Africa and La Niña in East Africa), with seasonality that aligns well with the maize growing seasons. Within maize growing areas, however, ENSO teleconnections to hydroclimate and vegetation are generally weaker compared to the broader geographic regions, especially in East Africa. There is also little evidence that the magnitude of the ENSO event affects the hydroclimate or vegetation response in these maize regions. Maize yields in Kenya, Malawi, South Africa, and Zimbabwe all correlate significantly with hydroclimate and leaf area index, with South Africa and Zimbabwe showing the strongest and most consistent yield responses to ENSO events. Our results highlight the chain of causality from El Niño and La Niña forcing of regional anomalies in hydroclimate to vegetation health and maize yields in southern and East Africa. The large spread across individual ENSO events, however, underscores the limitations of this climate mode for seasonal climate prediction in the region, and the importance of finding additional sources of skill for improving climate and yield forecasts.

El Niño Southern Oscillation↗
NASA NTRS2020

The Boreal Winter El Niño Precipitation Response over North America: Insights into Why January is More Difficult to Predict than February

This study examines the within−season monthly variation of the El Niño response over North America during December−March using the NASA/GEOS model. In agreement with previous studies, the skill of 1−month lead GEOS coupled model forecasts of precipitation over North America is largest (smallest) for February (January), with similar results in uncoupled mode. A key finding is that the relatively poor January skillis the result ofthe model placing the main circulation anomaly over the northeast Pacific slightly to the west of the observed, resulting inprecipitation anomalies that lie off the coast instead of over land as observed. In contrast, during February the observed circulation anomaly over the northeast Pacific shifts westward, lining up with the predicted anomaly which is essentially unchanged from January, resulting in both the observed and predicted precipitation anomalies remaining off the coast. Furthermore, the largest precipitation anomalies occur along the southern tier of states associated with an eastward extended jet–something that the models capture reasonably well. Simulations with a stationary wave model indicate that the placement of January El Niño response to the west of the observed over the northeast Pacificis the result of biases in the January climatological stationary waves, rather than errors in the tropical Pacific El Niño heating anomalies in January. Furthermore, evidence is provided that the relatively poor simulation of the observed January climatology, characterized by a strengthened North Pacific jet and enhanced ridge over western North America, can be traced back to biases in the January climatology heating over the Tibet region and the tropical western Pacific.

Young-kwon Lim↗
NASA NTRS2019

Global Disease Outbreaks Associated with the 2015-2016 El Niño Event

Interannual climate variability patterns associated with the El Niño-Southern Oscillation phenomenon result in climate and environmental anomaly conditions in specific regions worldwide that directly favor outbreaks and/or amplification of variety of diseases of public health concern including chikungunya, hantavirus, Rift Valley fever, cholera, plague, and Zika. We analyzed patterns of some disease outbreaks during the strong 2015–2016 El Niño event in relation to climate anomalies derived from satellite measurements. Disease outbreaks in multiple El Niño-connected regions worldwide (including Southeast Asia, Tanzania, western US, and Brazil) followed shifts in rainfall, temperature, and vegetation in which both drought and flooding occurred in excess (14–81% precipitation departures from normal). These shifts favored ecological conditions appropriate for pathogens and their vectors to emerge and propagate clusters of diseases activity in these regions. Our analysis indicates that intensity of disease activity in some ENSO-teleconnected regions were approximately 2.5–28% higher during years with El Niño events than those without. Plague in Colorado and New Mexico as well as cholera in Tanzania were significantly associated with above normal rainfall (p < 0.05); while dengue in Brazil and southeast Asia were significantly associated with above normal land surface temperature (p < 0.05). Routine and ongoing global satellite monitoring of key climate variable anomalies calibrated to specific regions could identify regions at risk for emergence and propagation of disease vectors. Such information can provide sufficient lead-time for outbreak prevention and potentially reduce the burden and spread of ecologically coupled diseases.

El Nino↗
NASA NTRS2023

Anomalous Net Biome Exchange Over Amazonian Rainforests Induced by the 2015/16 El Niño: Temperature-dominated Total Flux but Soil Dryness-Shaped Spatial Pattern

The magnitude and spatial pattern of anomalous net biome exchange (NBE) induced by the 2015/16 El Niño over Amazonian rainforests remain uncertain. We here investigated them using multi-model posterior NBE products in the Orbiting Carbon Observatory-2 (OCO-2) version 10 modeling intercomparison project. Results suggest that relative to the annual NBE average in 2017/18, larger anomalous carbon release occurred over the eastern and northern Amazonian rainforests in 2015/16, with a total flux of approximately 0.4 PgC yr−1 after assimilating satellite-observed column CO2 concentrations (XCO2) over land. We further find that this anomalous spatial pattern was predominantly determined by soil dryness, while the total positive NBE anomaly was dominated by higher temperature with its contribution of approximately 68～70%. We believe that atmospheric inversions assimilating more satellite-observed XCO2 in future can provide us more comprehensive understanding how Amazonian rainforests cope with the abiotic stresses induced by El Niño events.

Jun Wang↗
NASA NTRS2021

Coral Oxygen Isotopic Records Capture the 2015/2016 El Niño Event in the Central Equatorial Pacific

Coral oxygen isotopes (δ^(18)O) from the central equatorial Pacific provide monthly resolved records of El Niño-Southern Oscillation activity over past centuries to millennia. However, calibration studies using in situ data to assess the relative contributions of warming and freshening to coral δ^(18)O records are exceedingly rare. Furthermore, the fidelity of coral δ^(18)O records under the most severe thermal stress events is difficult to assess. Here, we present six coral δ^(18)O records and in situ temperature, salinity, and seawater δ^(18)O data from Kiritimati Island (2°N, 157°W) spanning the very strong 2015/16 El Niño event. Local sea surface temperature (SST) anomalies of +2.4 ± 0.4°C and seawater δ^(18)O anomalies of −0.19 ± 0.02‰ contribute to the observed coral δ^(18)O anomalies of −0.58 ± 0.05‰, consistent with a ∼70% contribution from SST and ∼30% from seawater δ^(18)O. Our results demonstrate that Kiritimati coral δ^(18)O records can provide reliable reconstructions even during the largest class of El Niño events.

Oxygen isotope anomalies↗
NASA NTRS2022

Mid-Pliocene El Niño/Southern Oscillation Suppressed By Pacific Intertropical Convergence Zone Shift

The El Niño/Southern Oscillation (ENSO), the dominant driver of year-to-year climate variability in the equatorial Pacific Ocean, impacts climate pattern across the globe. However, the response of the ENSO system to past and potential future temperature increases is not fully understood. Here we investigate ENSO variability in the warmer climate of the mid-Pliocene (~3.0–3.3 Ma), when surface temperatures were ~2–3 °C above modern values, in a large ensemble of climate models—the Pliocene Model Intercomparison Project. We show that the ensemble consistently suggests a weakening of ENSO variability, with a mean reduction of 25% (±16%). We further show that shifts in the equatorial Pacific mean state cannot fully explain these changes. Instead, ENSO was suppressed by a series of off-equatorial processes triggered by a northward displacement of the Pacific intertropical convergence zone: weakened convective feedback and intensified Southern Hemisphere circulation, which inhibit various processes that initiate ENSO. The connection between the climatological intertropical convergence zone position and ENSO we find in the past is expected to operate in our warming world with important ramifications for ENSO variability.

Atmospheric dynamics↗
NASA NTRS2021

Reduced El NiñO Variability in the Mid-Pliocene According to the Pliomip2 Ensemble

The mid-Pliocene warm period (3.264–3.025 Ma) is the most recent geological period during which atmospheric CO 2 levels were similar to recent historical values (∼400 ppm). Several proxy reconstructions for the mid-Pliocene show highly reduced zonal sea surface temperature (SST) gradients in the tropical Pacific Ocean, indicating an El Niño-like mean state. However, past modelling studies do not show these highly reduced gradients. Efforts to understand mid-Pliocene climate dynamics have led to the Pliocene Model Intercomparison Project (PlioMIP). Results from the first phase (PlioMIP1) showed clear El Niño variability (albeit significantly reduced) and did not show the greatly reduced time-mean zonal SST gradient suggested by some of the proxies. In this work, we study El Niño–Southern Oscillation (ENSO) variability in the PlioMIP2 ensemble, which consists of additional global coupled climate models and updated boundary conditions compared to PlioMIP1. We quantify ENSO amplitude, period, spatial structure and “flavour”, as well as the tropical Pacific annual mean state in mid-Pliocene and pre-industrial simulations. Results show a reduced ENSO amplitude in the model-ensemble mean (−24 %) with respect to the pre-industrial, with 15 out of 17 individual models showing such a reduction. Furthermore, the spectral power of this variability considerably decreases in the 3–4-year band. The spatial structure of the dominant empirical orthogonal function shows no particular change in the patterns of tropical Pacific variability in the model-ensemble mean, compared to the pre-industrial. Although the time-mean zonal SST gradient in the equatorial Pacific decreases for 14 out of 17 models (0.2 ∘C reduction in the ensemble mean), there does not seem to be a correlation with the decrease in ENSO amplitude. The models showing the most “El Niño-like” mean state changes show a similar ENSO amplitude to that in the pre-industrial reference, while models showing more “La Niña-like” mean state changes generally show a large reduction in ENSO variability. The PlioMIP2 results show a reasonable agreement with both time-mean proxies indicating a reduced zonal SST gradient and reconstructions indicating a reduced, or similar, ENSO variability.

mid-Pliocene warm period↗
NASA NTRS2022

Influence of Vegetation on Simulation of the Water Balance and Hydrological Response to El Niño–Southern Oscillation in Western Tropical South America

Land surface models (LSMs) rely on vegetation parameters for use in hydrological and energy balance analysis, monitoring, and forecasting. This study examines the influence that vegetation representation in the Noah-Multiparameterization (Noah-MP) LSM has on hydrological simulations across the diverse climate zones of western tropical South America (WTSA), with specific consideration of hydrological variability associated with El Niño–Southern Oscillation (ENSO). The influence of model representation of vegetation on simulated hydrology is evaluated through three simulation experiments that use 1) satellite-derived constant MODIS; 2) satellite-derived time-varying MODIS; and 3) the Noah-MP dynamic leaf model. We find substantial differences in vegetation fields between these simulations, with the Noah-MP dynamic leaf model diverging significantly from satellite-derived vegetation fields in many ecoregions. Impacts on simulated hydrology were, however, found to be modest across climate zones, except for select extreme events. Also, although impacts on hydrology under ENSO-induced variability were small, we find that the Noah-MP dynamic leaf model simulates a positive relationship between rainfall and vegetation in humid ecoregions of WTSA, where satellite observations may indicate the opposite. The relatively small sensitivity of simulated hydrology to vegetation scheme suggests that the performance of hydrological monitoring and forecasting in WTSA that uses Noah-MP is largely unaffected by the choice of vegetation scheme, such that using a simple climatological default is generally no worse than adopting more complicated options. The presence of some differences between the time-varying and constant MODIS simulations for hydrologic extremes, however, indicates that time-varying MODIS configuration might be more suitable for hydrological hazards applications.

South America↗