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NASA NTRS2024

Interannual Lightning Variability within the TRMM LIS Dataset Using an ENSO Perspective

The Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) was used to investigate inter-annual variability of lightning from 1998-2014 within the 38° S – 38° N range. Previous studies have indicated that the El-Niño/Southern Oscillation (ENSO) phenomenon is one significant contributor to inter-annual lightning variability, potentially the dominant mechanism on the global scale. This period of 16 years contained four warm- (El Niño), eight cold- (La Niña), and four neutral-phase ENSO years based on the oceanic Niño index. Large magnitude lightning anomalies were found during the warm phase of ENSO, with mean warm-phase anomalies of > 10 Fl (1000 km) −2 min −1 in north-central Africa and Argentina. This includes a +35 Fl (1000 km) −2 min −1 anomaly in Argentina during the 2009 El Niño. In general, large-scale anomalies of thermodynamic properties and upper-atmospheric vertical motion coincided with the lightning anomalies observed in both Africa and South America. The anomaly over north-central Africa, however, was characterized by a 6-week shift in the annual lightning maximum with the warm phase, a result of the more complex environmental response to ENSO over the Sahel. The most consistent ENSO anomalies with appreciable lightning were found in southeastern Africa, northwestern Brazil, central Mexico, and the southern Red Sea. Of these, all but the Mexico region had enhanced lightning with the cold phase and suppressed lightning with the warm phase.

Austin G. Clark↗
NASA NTRSDate not supplied

Evaluation of TAO Observation System on ENSO Predictions from the GMAO S2S Forecast System

Since the early 1990’s, the Tropical Atmosphere Ocean (TAO) mooring array has been instrumental for observing Kelvin and Rossby wave propagation which is key for El Nino/Southern Oscillation (ENSO) prediction. However, recent funding and programmatical issues have highlighted the need to rigorously assess the impact of the TAO observing system on ENSO predictions. Therefore, we evaluate the TAO using data assimilation observation denial experiments (also known as Observing System Evaluation or OSE experiments). This presentation will evaluate the TAO observing impact on both reanalyses and prediction of the big 2015 El Nino. We have completed reanalyses for July 2014-Dec 2015 for both the CONTROL experiment (that assimilates all available data) and the NOTAO experiment (that is identical to the CONTROL but withholds all TAO observations) using the best available NASA GEOS-S2S V3 seasonal prediction system. Validation of these reanalyses shows that TAO assimilation generally improves comparisons of temperature and salinity versus gridded in situ observations. Temperature is universally improved above the thermocline near the equator, but the biggest improvement is found in the eastern Pacific, just below the thermocline, where the variation of the thermocline defines ENSO events. In addition, a surprising result is that even with relatively few observations, salinity is improved throughout the equatorial region except near 120oW near the surface. ENSO forecasts were performed that were initialized from these CONTROL and NOTAO reanalyses. For the 9-month forecasts which were initialized in January, July, and October 2015, the NINO3.4 SST shows that the CONTROL forecasts are warmer and closer to observations than the NOTAO forecasts. We will show that upwelling and shoaling of the mixed layer amplifies the ENSO signal due to TAO assimilation. Prior to (after) April 2015, this upwelling is caused by relatively stronger Rossby (Kelvin) waves in the CONTROL than in the NOTAO experiments.

E. Hackert↗
DOE OSTI2022

Dynamics of ENSO Phase–Locking and Its Biases in Climate Models

Here, the contributions of different oceanic feedbacks to the El Niño–Southern Oscillation (ENSO) phase-locking are examined by deriving ENSO dynamics based on the recharge-discharge framework. In observations, the significant winter preference of the ENSO peak is determined by a strong seasonal modulation of SST growth rate, which is controlled by the zonal advective and thermodynamic feedbacks. However, the majority of climate models fail to simulate ENSO phase-locking because the contribution of zonal advective feedback to the seasonal modulation of the SST growth rate is much smaller compared to observations. The weak annual cycle of the SST-current coupling coefficient and small annual mean of the negative climatological zonal SST gradient are two factors contributing to the weak-biased seasonality of zonal advective feedback. Further analysis shows that the Niño3.4 SSTA has better phase-locking performance than Niño3 SSTA in the climate models due to the better simulation of zonal advection feedback in the Niño3.4 region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Biomass Burning Emissions of Black Carbon over the Maritime Continent and ENSO Variability

Fire emissions from the Maritime Continent (MC) over the western tropical Pacific are strongly influenced by El Niño–Southern Oscillation (ENSO), posing various climate effects to the Earth system. Here, in this study, we show that the historical biomass burning emissions of black carbon (BC bb ) aerosol in the dry season from the MC are strengthened in El Niño years due to the dry conditions. The eastern Pacific type of El Niño exerts a stronger modulation in BC bb emissions over the MC region than the central Pacific type of El Niño. Based on simulations using the fully coupled Community Earth System Model (CESM), the impacts of increased BC bb emissions on ENSO variability and frequency are also investigated in this study. With BC bb emissions from the MC scaled up by a factor of 10, which enables the identification of climate response from the internal variability, the increased BC bb heats the local atmosphere and changes land–sea thermal contrast, which suppresses the westward transport of the eastern Pacific surface water. It leads to an increase in sea surface temperature in the eastern tropical Pacific, which further enhances ENSO variability and increases the frequency of extreme El Niño and La Niña events. This study highlights the potential role of BC bb emissions on extreme ENSO frequency, and this role may be increasingly important in the warming future with higher wildfire risks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Tropical Indian Ocean Mediates ENSO Influence Over Central Southwest Asia During the Wet Season

El Niño–Southern Oscillation (ENSO) modulates wet season (November–April) precipitation over Central Southwest Asia (CSWA), however, intraseasonal characteristics of its influence are largely unknown, which can be important for its subseasonal to seasonal hydroclimate predictability. Here we show that the ENSO-CSWA teleconnection varies intraseasonally and is a combination of direct and indirect positive influences. The direct influence is through a Rossby wave-like pattern in the tail months. The indirect influence is through an atmospheric dipole of diabatic heating anomalies in the tropical Indian Ocean (TIO) as a result of ENSO-forced response, which also generates a Rossby wave-like forcing and persists throughout the wet season. ENSO exerts its strongest influence when both direct and indirect modes are in phase, while the relationship breaks down when the two modes are out of phase. The atmospheric teleconnection through the atmospheric diabatic heating anomalies in the TIO is reproducible in numerical simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Equatorial Origin of the Observed Tropical Pacific Quasi-Decadal Variability From ENSO Nonlinearity

Quasi-decadal (QD) climate variability is detected in the tropical Pacific based on the recent 70 years of observations. This QD variability is identified in equatorial sea surface temperatures (SSTs), the pattern of which resembles the Central Pacific (CP) El Niño-Southern Oscillation (ENSO) but extends further meridionally to the northeastern subtropical Pacific. Whereas equatorial upper-ocean heat content and SSTs are in quadrature for ENSO, these two quantities are almost in phase on the QD timescale. Further analysis shows that nonlinear dynamical heating, primarily originating from strong El Niño events, tends to lead QD SSTs by a quarter of its dominant period (approximately 30 months) and shapes the dominant QD periodicity in observations. Here, our results suggest that the observed QD variability largely originates from ENSO nonlinearity and thus is fundamentally different from ENSO's oscillatory nature.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Exploring the Relative Importance of the MJO and ENSO to North Pacific Subseasonal Predictability

Abstract Here we explore the relative contribution of the Madden‐Julian Oscillation (MJO) and El Niño Southern Oscillation (ENSO) to midlatitude subseasonal predictive skill of upper atmospheric circulation over the North Pacific, using an inherently interpretable neural network applied to pre‐industrial control runs of the Community Earth System Model version 2. We find that this interpretable network generally favors the state of ENSO, rather than the MJO, to make correct predictions on a range of subseasonal lead times and predictand averaging windows. Moreover, the predictability of positive circulation anomalies over the North Pacific is comparatively lower than that of their negative counterparts, especially evident when the ENSO state is important. However, when ENSO is in a neutral state, our findings indicate that the MJO provides some predictive information, particularly for positive anomalies. We identify three distinct evolutions of these MJO states, offering fresh insights into opportune forecasting windows for MJO teleconnections.

58 GEOSCIENCES↗
DOE OSTI2022

ENSO modulation of summertime tropospheric ozone over China

Ozone (O 3 ) is one of the most critical pollutants affecting air quality in China in recent years. In this study, different impacts of the El Niño–Southern Oscillation (ENSO) warm/cold phases on summertime tropospheric O 3 over China are examined based on model simulations, ground measurements, and reanalysis data. Summertime surface O 3 concentrations in China show a positive correlation with ENSO index during years 1990–2019, with the largest increases by 20% over southern China in El Niño (warm phase) relative to La Niña (cold phase) years. The ENSO modulation extends to the middle and even upper troposphere. Our analysis indicates that O 3 flux convergence associated with weakened southerlies is the primary reason for the increase in tropospheric O 3 over southern China. In addition, the O 3 increase during El Niño years is mainly from domestic emissions in China. This study highlights the potential significance of ENSO in modulating tropospheric O 3 concentrations in China, with great implications for O 3 pollution mitigation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The QBO–MJO Connection: A Possible Role for the SST and ENSO

We examine the hypothesis that the observed connection between the stratospheric quasi-biennial oscillation (QBO) and the strength of the Madden–Julian oscillation (MJO) is modulated by the sea surface temperature (SST)—for example, by El Niño–Southern Oscillation (ENSO). A composite analysis shows that, globally, La Niña SSTs are remarkably similar to those that occur during the easterly phase of the QBO. A maximum covariance analysis suggests that MJO power and SST are strongly linked on both the ENSO time scale and the QBO time scale. We analyze simulations with a modified configuration of version 2 of the Community Earth System Model, with a high top and fine vertical resolution. The model is able to simulate ENSO, the QBO, and the MJO. The ocean-coupled version of the model simulates the QBO, ENSO, and MJO, but does not simulate the observed QBO–MJO connection. When driven with prescribed observed SST anomalies based on composites for QBO east and QBO west (QBOE and QBOW), however, the same atmospheric model produces a modest enhancement of MJO power during QBOE relative to QBOW, as observed. We explore the possibility that the SST anomalies are forced by the QBO itself. Indeed, composite Hovmöller diagrams based on observations show the propagation of QBO zonal wind anomalies all the way from the upper stratosphere to the surface. Also, subsurface ocean temperature composites reveal a similarity between the western Pacific and Indian Ocean subsurface signal between La Niña and QBOE.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

The Evolution of Tropical Precipitation Patterns During ENSO Events Using 21+ Years of GPCP Merged Data

The ENSO phenomenon is characterized by fluctuations in the climate system of the tropical Pacific. Quantifying changes in the precipitation component of this system is important in understanding the distribution of heating in the atmosphere which drives the large-scale circulation and affects the weather patterns in the mid-latitudes. Monitoring precipitation anomalies in the Pacific is also an important component for tracking the evolution of ENSO. The most timely and complete observations of the earth come from satellite instruments. In this study, the state of the art satellite-gauge merged monthly precipitation data set from the Global Precipitation Climatology Project (GPCP) is used to depict tropical rainfall patterns during ENSO events over the past two decades and quantify these patterns using indices. This analysis will be complemented by daily precipitation data which can resolve the Madden-Julian Oscillation and westerly wind burst events. The 1997-98 El Nino and 1998-2000 La Nina were the best observed ENSO cycle in the historic record. Prior to the El Nino (in terms of anomalous warming of the east Pacific) dry anomalies over the Maritime Continent were observed in February 1997 as a westerly wind burst advected convection to the east. The largest SST anomalies occurred around November-December 1997, which were followed by the largest precipitation anomalies in the beginning of 1998. The largest precipitation departures from normal were not colocated with the SST anomalies, but were further west, In the spring of 1998 negative precipitation anomalies to the north of the equator intensified, signaling the mature phase of the El Nino. A rapid increase in the precipitation-based La Nina index from December-January 1998 to March-April 1998 signaled the coming La Nina. The 1982-1983 El Nino was comparable in strength (according to several indices) and the precipitation patterns evolved in a similar fashion. For the 1998-2000 La Nina, the coldest anomalies, were confined to the central equatorial Pacific, while the driest anomalies were found in the west Pacific,

Curtis, Scott↗
NASA NTRS2001

Sensitivity of the Tropical Atmospheric Energy Balance to ENSO-Related SST Changes: Comparison of Climate Model Simulations to Observed Responses

This paper focuses on how fresh water and radiative fluxes over the tropical oceans change during ENSO warm and cold events and how these changes affect the tropical energy balance. At present, ENSO remains the most prominent known mode of natural variability at interannual time scales. While this natural perturbation to climate is quite distinct from possible anthropogenic changes in climate, adjustments in the tropical water and energy budgets during ENSO may give insight into feedback processes involving water vapor and cloud feedbacks. Although great advances have been made in understanding this phenomenon and realizing prediction skill over the past decade, our ability to document the coupled water and energy changes observationally and to represent them in climate models seems far from settled (Soden, 2000 J Climate). In a companion paper we have presented observational analyses, based principally on space-based measurements which document systematic changes in rainfall, evaporation, and surface and top-of-atmosphere (TOA) radiative fluxes. Here we analyze several contemporary climate models run with observed SSTs over recent decades and compare SST-induced changes in radiation, precipitation, evaporation, and energy transport to observational results. Among these are the NASA / NCAR Finite Volume Model, the NCAR Community Climate Model, the NCEP Global Spectral Model, and the NASA NSIPP Model. Key disagreements between model and observational results noted in the recent literature are shown to be due predominantly to observational shortcomings. A reexamination of the Langley 8-Year Surface Radiation Budget data reveals errors in the SST surface longwave emission due to biased SSTs. Subsequent correction allows use of this data set along with ERBE TOA fluxes to infer net atmospheric radiative heating. Further analysis of recent rainfall algorithms provides new estimates for precipitation variability in line with interannual evaporation changes inferred from the da Silva, Young, Levitus COADS analysis. The overall results from our analysis suggest an increase (decrease) of the hydrologic cycle during ENSO warm (cold) events at the rate of about 5 W/sq m per K of SST change. Model results agree reasonably well with this estimate of sensitivity. This rate is slightly less than that which would be expected for constant relative humidity over the tropical oceans. There remain, however, significant quantitative uncertainties in cloud forcing changes in the models as compared to observations. These differences are examined in relationship to model convection and cloud parameterizations Analysis of the possible sampling and measurement errors compared to systematic model errors is also presented.

Robertson, Franklin R.↗
NASA NTRS2012

The Response of Tropospheric Ozone to ENSO in Observations and a Chemistry-Climate Simulation

The El Nino-Southern Oscillation (ENSO) is the dominant mode of tropical variability on interannual time scales. ENSO appears to extend its influence into the chemical composition of the tropical troposphere. Recent results have revealed an ENSO induced wave-l anomaly in observed tropical tropospheric column ozone. This results in a dipole over the western and eastern tropical Pacific, whereby differencing the two regions produces an ozone anomaly with an extremely high correlation to the Nino 3.4 Index. We have successfully reproduced this result using the Goddard Earth Observing System Version 5 (GEOS-5) general circulation model coupled to a comprehensive stratospheric and tropospheric chemical mechanism forced with observed sea surface temperatures over the past 25 years. An examination of the modeled ozone field reveals the vertical contributions of tropospheric ozone to the column over the western and eastern Pacific region. We will show targeted comparisons with observations from NASA's Aura satellite Microwave Limb Sounder (MLS), and the Tropospheric Emissions Spectrometer (TES) to provide insight into the vertical structure of ozone changes. The tropospheric ozone response to ENSO could be a useful chemistry-climate model evaluation tool and should be considered in future modeling assessments.

Oman, L. D.↗
NASA NTRS2011

A Statistical Model of Tropical Cyclone Tracks in the Western North Pacific with ENSO-Dependent Cyclogenesis

A new statistical model for western North Pacific Ocean tropical cyclone genesis and tracks is developed and applied to estimate regionally resolved tropical cyclone landfall rates along the coasts of the Asian mainland, Japan, and the Philippines. The model is constructed on International Best Track Archive for Climate Stewardship (IBTrACS) 1945-2007 historical data for the western North Pacific. The model is evaluated in several ways, including comparing the stochastic spread in simulated landfall rates with historic landfall rates. Although certain biases have been detected, overall the model performs well on the diagnostic tests, for example, reproducing well the geographic distribution of landfall rates. Western North Pacific cyclogenesis is influenced by El Nino-Southern Oscillation (ENSO). This dependence is incorporated in the model s genesis component to project the ENSO-genesis dependence onto landfall rates. There is a pronounced shift southeastward in cyclogenesis and a small but significant reduction in basinwide annual counts with increasing ENSO index value. On almost all regions of coast, landfall rates are significantly higher in a negative ENSO state (La Nina).

Yonekura, Emmi↗
NASA NTRS2012

The Response of Lower Atmospheric Ozone to ENSO in Aura Measurements and a Chemistry-Climate Simulation

The El Nino-Southern Oscillation (ENSO) is the dominant mode of tropical variability on interannual time scales. ENSO appears to extend its influence into the chemical composition of the tropical troposphere. Recent work has revealed an ENSO-induced wave-1 anomaly in observed tropical tropospheric column ozone. This results in a dipole over the western and eastern tropical Pacific, whereby differencing the two regions produces an ozone anomaly with an extremely high correlation to the Nino 3.4 Index. We have successfully reproduced this feature using the Goddard Earth Observing System Version 5 (GEOS-5) general circulation model coupled to a comprehensive stratospheric and tropospheric chemical mechanism forced with observed sea surface temperatures over the past 25 years. An examination of the modeled ozone field reveals the vertical contributions of tropospheric ozone to the column over the western and eastern Pacific region. We will show composition sensitivity in observations from NASA s Aura satellite Microwave Limb Sounder (MLS) and the Tropospheric Emissions Spectrometer (TES) and a simulation to provide insight into the vertical structure of these ENSO-induced ozone changes. The ozone changes due to the Quasi-Biennial Oscillation (QBO) in the extra-polar upper troposphere and lower stratosphere in MLS measurements will also be discussed.

Oman, L. D.↗
NASA NTRS2018

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO S2S Forecast System

El Nino/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would be of great benefit for society. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean density. Satellite Sea Surface Salinity (SSS), combined with temperature, help to identify ocean density changes and associated mixing near the ocean surface. We assess the impact of satellite SSS observations for improving near-surface dynamics within ocean analyses and how these impact dynamical ENSO forecasts using the NASA GMAO (Global Modeling and Assimilation Office) Sub-seasonal to Seasonal (S2S_v2.1) coupled forecast system (Molod et al. 2018 - i.e. NASA's contribution to the NMME (National Multi-Model Ensemble) project). For all initialization experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF ( Local Ensemble Transform Kalman Filter) scheme similar to Penny et al., 2013. A separate reanalysis additionally assimilates Aquarius V5 (September 2011 to June 2015) and SMAP (Soil Moisture Active Passive) V4 (March 2015 to present) along-track data.We highlight the impact of satellite SSS on ocean reanalyses by comparing validation statistics of experiments that assimilate SSS versus our current prediction system that withholds SSS. We find that near-surface validation versus observed statistics for salinity are slightly degraded when assimilating SSS. This is an expected result due to known biases between SSS (measured by the satellite at approximately 1 centimeter) and in situ measurements (typically measured by Argo floats at 3 meters). On the other hand, a very encouraging result is that both temperature, absolute dynamic topography, and mixed layer statistics are improved with SSS assimilation. Previous work has shown that correcting near-surface density structure via gridded SSS assimilation can improve coupled forecasts. Here we present results of coupled forecasts that are initialized from the GMAO S2S reanalyses that assimilates/withholds along-track (L2) SSS. In particular, we contrast forecasts of the overestimated 2014 El Nino, the big 2015 El Nino, and the minor 2016 La Nina. For each of these ENSO scenarios, assimilation of satellite SSS improves the forecast validation. Improved SSS and density upgrades the mixed layer depth leading to more accurate coupled air/sea interaction.

Hackert, E.↗
NASA NTRS2020

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the NASA/GMAO Seasonal Forecast System

We assess the impact of satellite sea surface salinity (SSS) observations on dynamical ENSO forecasts. Assimilation of SSS improves the mixed layer depth (MLD) and modulates the Kelvin waves associated with ENSO. In column 2, the initialization differences between experiments that assimilate SSS minus those withholding SSS assimilation are presented. Column 3 shows examples of forecasts generated for the different phases of ENSO assimilating the different satellite SSS. In general, for all phases of ENSO, SSS assimilation improves forecasts. The far right column compares ensemble means for assimilation of individual and combined SMOS, Aquarius, and SMAP SSS forecasts. Finally, the latest forecasts are presented comparing assimilation versus no- assimilation of satellite SSS for single forecasts over the last year.

Hackert, E.↗
NASA NTRS2018

The Salience of Nonlinearities in the Boreal Winter Response to ENSO: North Pacific and North America

The prominence of nonlinearities in the response to El Niño as compared to La Niña, to moderate El Niño events as compared to extreme El Ninño events, and to different flavors of El Niño events, are analyzed using the NASA Goddard Earth Observing System Chemistry-Climate Model. In the Central North Pacific region where the sea level pressure response to El Niño-Southern Oscillation (ENSO) peaks, nonlinearities are relatively muted. In contrast, changes to the east of this region (i.e. the far-Northeastern Pacific) and to the north of this region (over Alaska) in response to different ENSO phases are more clearly nonlinear, and become statistically robust after more than 15 events are considered. The relative prominence of these nonlinearities is related to the zonal wavenumber of the tropical precipitation response. Associated with these nonlinearities over the far-Northeastern Pacific are nonlinearities in precipitation over Western United States and surface temperature over Northwest North America and Midwestern United States. In all regions at least 15 events of each type are necessary before nonlinearities can be identified as statistically significant at the 95% confidence level due to the presence of internal atmospheric variability. As there have only been a similar number of ENSO events to the total needed for significance since 1920, it is not surprising that it has been difficult to establish statistically significant nonlinearities using observational data.

Nonlinearities↗
DOE OSTI2024

Estimating Uncertainty in Simulated ENSO Statistics

Abstract Large ensembles of model simulations are frequently used to reduce the impact of internal variability when evaluating climate models and assessing climate change induced trends. However, the optimal number of ensemble members required to distinguish model biases and climate change signals from internal variability varies across models and metrics. Here we analyze the mean, variance and skewness of precipitation and sea surface temperature in the eastern equatorial Pacific region often used to describe the El Niño–Southern Oscillation (ENSO), obtained from large ensembles of Coupled model intercomparison project phase 6 climate simulations. Leveraging established statistical theory, we develop and assess equations to estimate, a priori, the ensemble size or simulation length required to limit sampling‐based uncertainties in ENSO statistics to within a desired tolerance. Our results confirm that the uncertainty of these statistics decreases with the square root of the time series length and/or ensemble size. Moreover, we demonstrate that uncertainties of these statistics are generally comparable when computed using either pre‐industrial control or historical runs. This suggests that pre‐industrial runs can sometimes be used to estimate the expected uncertainty of statistics computed from an existing historical member or ensemble, and the number of simulation years (run duration and/or ensemble size) required to adequately characterize the statistic. This advance allows us to use existing simulations (e.g., control runs that are performed during model development) to design ensembles that can sufficiently limit diagnostic uncertainties arising from simulated internal variability. These results may well be applicable to variables and regions beyond ENSO.

54 ENVIRONMENTAL SCIENCES↗