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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Quantifying the Effect of Mixing on the Mean Age of Air in CCMVal-2 and CCMI-1 Models

The stratospheric age of air (AoA) is a useful measure of the overall capabilities of a general circulation model (GCM) to simulate stratospheric transport. Previous studies have reported a large spread in the simulation of AoA by GCMs and coupled chemistry-climate models (CCMs). Compared to observational estimates, simulated AoA is mostly too low. Here we attempt to untangle the processes that lead to the AoA differences between the models and between models and observations. AoA is influenced by both mean transport by the residual circulation and two-way mixing; we quantify the effects of these processes using data from the CCM inter-comparison projects CCMVal-2 (Chemistry-Climate Model Validation Activity 2) and CCMI-1 (Chemistry-Climate Model Initiative, phase 1). Transport along the residual circulation is measured by the residual circulation transit time (RCTT). We interpret the difference between AoA and RCTT as additional aging by mixing. Aging by mixing thus includes mixing on both the resolved and subgrid scale. We find that the spread in AoA between the models is primarily caused by differences in the effects of mixing and only to some extent by differences in residual circulation strength. These effects are quantified by the mixing efficiency, a measure of the relative increase in AoA by mixing. The mixing efficiency varies strongly between the models from 0.24 to 1.02. We show that the mixing efficiency is not only controlled by horizontal mixing, but by vertical mixing and vertical diffusion as well. Possible causes for the differences in the models' mixing efficiencies are discussed. Differences in subgrid-scale mixing (including differences in advection schemes and model resolutions) likely contribute to the differences in mixing efficiency. However, differences in the relative contribution of resolved versus parameterized wave forcing do not appear to be related to differences in mixing efficiency or AoA.

CCMI↗
DOE OSTI2021

Attribution of the Australian bushfire risk to anthropogenic climate change

Abstract. Disastrous bushfires during the last months of 2019 and January 2020 affected Australia, raising the question to what extent the risk of these fires was exacerbated by anthropogenic climate change. To answer the question for southeastern Australia, where fires were particularly severe, affecting people and ecosystems, we use a physically based index of fire weather, the Fire Weather Index; long-term observations of heat and drought; and 11 large ensembles of state-of-the-art climate models. We find large trends in the Fire Weather Index in the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis (ERA5) since 1979 and a smaller but significant increase by at least 30 % in the models. Therefore, we find that climate change has induced a higher weather-induced risk of such an extreme fire season. This trend is mainly driven by the increase of temperature extremes. In agreement with previous analyses we find that heat extremes have become more likely by at least a factor of 2 due to the long-term warming trend. However, current climate models overestimate variability and tend to underestimate the long-term trend in these extremes, so the true change in the likelihood of extreme heat could be larger, suggesting that the attribution of the increased fire weather risk is a conservative estimate. We do not find an attributable trend in either extreme annual drought or the driest month of the fire season, September–February. The observations, however, show a weak drying trend in the annual mean. For the 2019/20 season more than half of the July–December drought was driven by record excursions of the Indian Ocean Dipole and Southern Annular Mode, factors which are included in the analysis here. The study reveals the complexity of the 2019/20 bushfire event, with some but not all drivers showing an imprint of anthropogenic climate change. Finally, the study concludes with a qualitative review of various vulnerability and exposure factors that each play a role, along with the hazard in increasing or decreasing the overall impact of the bushfires.

van Oldenborgh, Geert Jan (ORCID:0000000268989535)↗
DOE OSTI2017

Projected precipitation changes within the Great Lakes and Western Lake Erie Basin: a multi‐model analysis of intensity and seasonality

ABSTRACT The Great Lakes region encompasses the largest freshwater lake network in the world and supports a diverse network of agriculture, transportation, and tourism. Recently, Lake Erie has experienced increased hypoxia events, which have been attributed to agricultural practices and changes in run‐off. Here we examine the projected changes in extreme precipitation events to address concerns regarding regional agriculture, surface run‐off, and subsequent water quality. Precipitation projections within the overall Great Lakes Basin and the Western Lake Erie Basin subregion are examined using climate model simulations of varying spatial resolutions to understand historical precipitation and projected future precipitation. We develop three model ensembles for the historical period (1980–1999) and the mid‐century (2041–2060) that cover a range of spatial resolutions and future emissions scenarios, including: (1) 12 global model members from the fifth Climate Model Intercomparison Project ( CMIP5 ) using Representative Concentration Pathway ( RCP ) 8.5, (2) ten regional climate model ( RCM ) members from the North American Regional Climate Change Assessment Program driven by CMIP3 global models using the A2 emissions scenario, and (3) two high resolution RCM simulations ( RCM4 ) driven by CMIP5 global models using the RCP 8.5 scenario. For the historical period, all model ensembles overestimate winter and spring precipitation, and many of the models simulate a summer drying that is not observed. At mid‐century, most of the models predict a 10–20% increase in precipitation depending on the time of year. Daily probability distribution functions from three model ensembles reveal spring seasonal increases in high precipitation event probabilities when compared to the historical period, suggesting an increase in the frequency of high intensity precipitation at mid‐century. Overall, the presence of lakes or higher spatial resolution does not ensure improved representation of historical processes, and more complex interactions between large‐scale dynamics, local feedbacks, and physical parameterizations drive the model spread.

Basile, Samantha J.↗
DOE OSTI2015

Final Report for “Simulating the Arctic Winter Longwave Indirect Effects. A New Parameterization for Frost Flower Aerosol Salt Emissions” (DESC0006679) for 9/15/2011 through 9/14/2015

Description of the Project: This project has improved the aerosol formulation in a global climate model by using innovative new field and laboratory observations to develop and implement a novel wind-driven sea ice aerosol flux parameterization. This work fills a critical gap in the understanding of clouds, aerosol, and radiation in polar regions by addressing one of the largest missing particle sources in aerosol-climate modeling. Recent measurements of Arctic organic and inorganic aerosol indicate that the largest source of natural aerosol during the Arctic winter is emitted from crystal structures, known as frost flowers, formed on a newly frozen sea ice surface [Shaw et al., 2010]. We have implemented the new parameterization in an updated climate model making it the first capable of investigating how polar natural aerosol-cloud indirect effects relate to this important and previously unrecognized sea ice source. The parameterization is constrained by Arctic ARM in situ cloud and radiation data. The modified climate model has been used to quantify the potential pan-Arctic radiative forcing and aerosol indirect effects due to this missing source. This research supported the work of one postdoc (Li Xu) for two years and contributed to the training and research of an undergraduate student. This research allowed us to establish a collaboration between SIO and PNNL in order to contribute the frost flower parameterization to the new ACME model. One peer-reviewed publications has already resulted from this work, and a manuscript for a second publication has been completed. Additional publications from the PNNL collaboration are expected to follow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Improving tide-estuary representation in MPAS-Ocean (Final Report)

The overarching goal of this research is to produce a skill-assessed tide-estuary representation, including BGC (biogeochemistry) components of the ecosystem, into the MPAS-O global climate modeling system. Specifically, in the original proposal we proposed one-way nesting, into global MPAS-O, of a high-resolution model for TES (tidal and estuary systems) including the coupling of the BGC components. We have completed the proposed tasks during the past 4 years. Specifically, after extensive consultation with the MPAS-O group during the first year, we have decided to go beyond the original proposal and to two-way nest SCHISM into MPAS-O. As a result, SCHISM-CoSiNE (with CoSiNE being the BGC model) is now fully integrated into MPAS-O as a subroutine (more precisely, an analysis member) and can be invoked as MPAS-O is running with two-way exchange of information between the TES and global models (with proper spatial interpolation done on the fly). As originally proposed, we have also developed the new finite-volume (FV) model MPAS-OI (aka ELCIRC-sub) for TES. We have conducted several tests using the coupled MPAS-SCHISM- CoSiNE model and also MPAS-OI for Columbia River, San Francisco Bay and Chesapeake Bay. Four journal publications have been produced so far as the result of the project and 1 is under review (cf. Publication section). With these achievements, we will be ready to conduct fully coupled simulations of TES and global ocean anywhere, as soon as some missing capabilities in MPAS-O (e.g. tides, improved ability to handle the boundary conditions, and streamlining of the global BGC model) are worked out. The significance of the outcome of this project cannot be overstated. It marks the first time, as far as we know, that a global climate model is tightly coupled to a bona fide nearshore and terrestrial model (SCHISM system); in fact SCHISM is the first bona fide compound flooding model that seamlessly covers the coastal ocean, estuaries, rivers and watersheds (Ye et al. 2020; Zhang et al. 2020). The coupled model will reduce the errors and uncertainties of the MPAS-O global climate model system. It also complements and extends on-going E3SM project, as the latter seeks in the long-term to include components required to simulate impacts of sea-level change and storm surge on coastal regions, including wave models and focusing resolution in coastal and storm-track regions, as an important component of the Cryosphere-ocean system. Note that a spectral wave model (the unstructured-grid version of Wave Watch III, aka Wind Wave Model) is already incorporated inside the SCHISM system and is therefore directly accessible in the coupled system.

58 GEOSCIENCES↗
DOE OSTI2025

Subsurface Cooling and Sea Surface Temperature Pattern Formation Over the Equatorial Pacific

Abstract The equatorial cold tongue region has not warmed up in response to historical radiative forcing in the real world, contrary to the strong warming often simulated by climate models. Here we demonstrate that climate models fail to represent one or both of the key processes driving observed sea surface temperature (SST) pattern formation: a realistic surface wind stress pattern shaping subsurface cooling through wind‐driven circulation changes, and effective connectivity between subsurface and surface temperatures via upwelling and mixing. Consequently, none of the models approximate the observed lack of cold tongue SST warming and strengthening of zonal SST gradient across the equatorial Pacific. Furthermore, those that come closest achieve this due to interhemispheric warming differences rather than equatorial dynamics as observed. Addressing different origins of subsurface cooling in observations and simulations, and how they connect to SST, will lead to improved understanding of tropical Pacific SST changes to date and how they will evolve in the future.

Jiang, Feng [Lamont‐Doherty Earth Observatory Colu↗
NASA NTRS1982

A note on the maintenance of the atmospheric kinetic energy

The winter simulations of the GLAS climate model and the NCAR community climate model are used to examine the maintenance of the atmospheric kinetic energy. It is found that the kinetic energy is generated in the lower latitudes south of the maximum westerlies, transported northward and then, destroyed in the midlatitudes north of the maximum westerlies. Therefore, the atmospheric kinetic energy is maintained by the counterbalance between the divergence (convergence) of kinetic energy flux and generation (destruction) of kinetic energy in lower (middle) latitudes.

Chen, T.-C.↗
DOE OSTI2019

Hierarchical sensitivity analysis for simulating barrier island geomorphologic responses to future storms and sea-level rise

This paper presents a new application of an advanced hierarchical sensitivity analysis of a new climate model of barrier island geomorphological evolution. The implemented sensitivity analysis in this study integrates a hierarchical uncertainty framework with a variance-based global sensitivity analysis to decompose the different model input uncertainties. The analysis can provide quantitative and accurate measurements for the relative importance of uncertain model input factors while considering their dependence relationships. The climate model used in this research was the barrier island profile (BIP) model, which is a new computer code developed to simulate barrier island morphological evolution over periods ranging from years to decades under the impacts of accelerated future sea-level rise and long-term changes in the storm climate. In the application of the model, the BIP model was used to evaluate the responses of a series of barrier island cross-sections derived for Santa Rosa Island, Florida, to random storm events and five potential accelerated rates of sea-level rise projected over the next century. The uncertain model input factors thus include the scenario uncertainty caused by alternative future sea-level rise scenarios and the parametric uncertainties of random storm parameters and dune characteristics. The study results reveal that the occurrence of storms is the most important factor for the evolution of sand dunes on the barrier island and the impact of sea-level rise is essential to the morphological change of the island backshore environment. The analysis can provide helpful insights for coastal management and planning. This hierarchical sensitivity analysis is mathematically general and rigorous and can be applied to a wide range of climate models.

Dai, Heng↗
DOE OSTI2019

Evaluating Large-Eddy Simulations of Boundary-Layer Cloud Response to Climate Change using MAGIC Observations

Over the cool waters off California, a persistent and extensive deck of low-lying clouds forms atop a shallow, turbulent layer of moist air extending 500-2000 meters above the ocean, above which the air is much warmer and drier. Its west edge varies with weather and season and is typically half way to Hawaii. This cloud deck and similar cloud decks elsewhere reflect sunlight back to space, cooling the underlying ocean and indeed the entire planet. They must be accurately represented by a climate model to correctly simulate our current climate or future global warming. Most climate models suggest these cloud decks will thin and break up in a warmer CO 2 -enriched climate, so extra sunlight would reach the ocean surface and amplify warming worldwide. But these models have difficulty accurately simulating the cloud thickness and extent because the turbulent cloud-forming air currents are much too small to be simulated by their coarse computational grid. In 2012-2013, the DOE Atmospheric Radiation Measurement MAGIC program instrumented a container ship transiting between California and Hawaii to observe clouds and rain, small particles (aerosols), and weather conditions. Data were obtained from 20 4-6 day cruises in each direction. This study tested whether a sophisticated ‘large-eddy simulation’ (LES) of the turbulent air motions that create the clouds in this region accurately predicts the variations in cloud properties seen across the different cruises. If so, that model is more believable for predicting cloud changes in this region in a future warmer climate. Our LES used a numerical mesh over a 6.4x6.4 km region with 50 m horizontal and 5 m vertical grid spacing to simulate the cloud-forming eddies and the sharp overlying transition between moist and dry air. To better compare with MAGIC observations, we configured our model to simulate a region that moved along with the ship. We used a weather forecast model to specify effects of the large-scale air flow. We compared our results with balloon ascents, a radar and other instruments pointed upward at the clouds, measurements of downward sunlight and infrared radiation, aerosols, and weather variables for all suitable cruise periods. Our LES was remarkably skillful in predicting the cloudiness variations measured by the ship. MAGIC also sampled mesoscale cells, regions of cloud thickening and thinning over distances of 10-50 km. An LES run over a larger region 100 km on a side shows these cells form spontaneously, enhanced by strong radiative heat loss at the cloud tops.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Long-term leaf C:N ratio change under elevated CO 2 and nitrogen deposition in China: Evidence from observations and process-based modeling

Climate change, elevating atmosphere CO 2 (eCO 2 ) and increased nitrogen deposition (iNDEP) are altering the biogeochemical interactions between plants, microbes and soils, which further modify plant leaf carbon-nitrogen (C:N) stoichiometry and their carbon assimilation capability. Many field experiments have observed large sensitivity of leaf C:N ratio to eCO 2 and iNDEP. However, the large-scale pattern of this sensitivity is still unclear, because eCO 2 and iNDEP drive leaf C:N ratio toward opposite directions, which are further compounded by the complex processes of nitrogen acquisition and plant-and-microbial nitrogen competition. Here, we attempt to map the leaf C:N ratio spatial variation in the past 5 decades in China with a combination of data-driven model and process-based modeling. These two approaches showed consistent results. Over different regions, we found that leaf C:N ratio had significant but uneven changes between 2 time periods (1960-1989 and 1990-2015): a 5% ± 8% increase for temperate grasslands in northern China, a 3% ± 6% increase for boreal grasslands in western China, and by contrast, a 7% ± 6% decrease for temperate forests in southern China, and a 3% ± 5% decrease for boreal forests in northeastern China. Additionally, the structural equation models indicated that the leaf C:N change was sensitive to ΔNDEP, ΔCO 2 and ΔMAT rather than ΔMAP and ecosystem types. In this work, process-based modeling suggested that iNDEP was the main source of soil mineral nitrogen change, dominating leaf C:N ratio change in most areas in China, while eCO 2 led to leaf C:N ratio increase in low iNDEP area. This study also indicates that the long-term leaf C:N ratio acclimation was dominated by climate constraint, especially temperature, but was constrained by soil N availability over decade scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector

Abstract. Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5∘ × 0.5∘ global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.

58 GEOSCIENCES↗
DOE OSTI2019

Impacts of Observational Constraints Related to Sea Level on Estimates of Climate Sensitivity

Reduced complexity climate models are necessary tools for quantifying decision-relevant uncertainties, given their flexibility, computational efficiency, and suitability for large-ensemble frameworks necessary for statistical estimation using resampling techniques (e.g. Markov chain Monte Carlo—MCMC). Here we document a new version of the simple, open-source, global climate model Hector, coupled with a one-dimensional diffusive heat and energy balance model (Diffusion Ocean Energy balance CLIMate model; DOECLIM) and a sea-level change module (Building blocks for Relevant Ice and Climate Knowledge; BRICK) that also represents contributions from thermal expansion, glaciers and ice caps, and polar ice sheets. We apply a Bayesian calibration approach to quantify model uncertainties surrounding 39 model parameters with prescribed radiative forcing, using observational information from global surface temperature, ocean heat uptake, and sea-level change. Furthermore, we find sea-level change as an observational constraint sharpens inference for the upper tail of posterior climate sensitivity estimates (the 97.5 percentile is tightened from 6.5 K to 5.3 K). The addition of sea-level change as an observational constraint also has implications for probabilistic projections of global surface temperature (the 97.5 percentile for RCP8.5 2100 temperature decreases 0.3 K) and sea-level rise (the 97.5 percentile for RCP8.5 2100 sea level decreases 0.5 m).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1983

A study of the kinetic energy generation with general circulation models

The history data of winter simulation by the GLAS climate model and the NCAR community climate model are used to examine the generation of atmospheric kinetic energy. The contrast between the geographic distributions of the generation of kinetic energy and divergence of kinetic energy flux shows that kinetic energy is generated in the upstream side of jets, transported to the downstream side and destroyed there. The contributions from the time-mean and transient modes to the counterbalance between generation of kinetic energy and divergence of kinetic energy flux are also investigated. It is observed that the kinetic energy generated by the time-mean mode is essentially redistributed by the time-mean flow, while that generated by the transient flow is mainly responsible for the maintenance of the kinetic energy of the entire atmospheric flow.

Chen, T.-C.↗
NASA NTRS2014

Why Does the Stratosphere Get Moister During the 21st Century?

All chemistry-climate models predict that 1) the TTL warms during the 21st century and 2) that the humidity of air entering the stratosphere increases over this same period. It seems reasonable to conclude that the former causes the latter, but to our knowledge no one has actually tested that. We do so here by analyzing one chemistry-climate model in detail (the Goddard Earth Observing System Chemistry Climate Model, GEOSCCM) and find that the warming of the TTL explains only a fraction of the increase in humidity of air entering the stratosphere. We do this by using meteorological fields from the model to drive a trajectory model, which estimates the water vapor variations in response to the large-scale temperature field. Water vapor simulated by the trajectory model increases by about one quarter of the amount it increases in the GEOSCCM. We conclude that, over the 21st century, an increase in the flux of ice through the TTL is responsible for most of the increase in the humidity of air entering the stratosphere in this model.

water vapor↗
NASA NTRS1982

Mid-latitude model analysis of solar radiation, the upper layers of the sea, and seasonal climate

A simplified, time-dependent energy balance climate model is run at the latitude belt 40-50 deg N. The model solves for the temperatures of the land, air, and 12 vertical oceanic layers, and it includes a wind stirred mixed layer. A change in model ocean optical turbidity from relatively clear (Jerlov 1) to particle rich (Jerlov III) conditions decreases the effective thickness of the oceanic layer in which heat is stored seasonally and increases the seasonal variation of sea surface temperature by 2-3 C. A decrease in the liquid water content of clouds by a factor of 4 warms the model climate and increases the seasonal variation of sea surface temperatures by 2-3 C. A 2-3 C change in the seasonal variation of sea surface temperature is also obtained by varying oceanic mixing through a factor of 2 change in the surface wind speed.

Charlock, T. P.↗
DOE OSTI2021

Evaluating Diurnal and Semi-Diurnal Cycle of Precipitation in CMIP6 Models Using Satellite- and Ground-Based Observations

We report the diurnal and semi-diurnal cycle of precipitation simulated from CMIP6 models during 1996-2005 are evaluated globally between 60°S and 60°N, as well as at ten selected locations representing three categories of diurnal cycle of precipitation: (1) afternoon precipitation over land, (2) early morning precipitation over ocean, and (3) nocturnal precipitation over land. Three satellite-based and two ground-based rainfall products are used to evaluate the climate models. Globally, the ensemble mean of CMIP6 models shows a diurnal phase of 3 to 4 hours earlier over land and 1 to 2 hours earlier over ocean, when compared with the latest satellite products. These biases are in line with what were found in previous versions of climate models but reduced compared to the CMIP5 ensemble mean. Analysis at the selected locations complimented with in-situ measurements further reinforces these results. Several CMIP6 models have shown a significant improvement in the diurnal cycle of precipitation compared to their CMIP5 counterparts, notably on delaying afternoon precipitation over land. This can be attributed to the use of more sophisticated convective parameterizations. Most models are still unable to capture the nocturnal peak associated with elevated convection and propagating mesoscale convective systems, with a few exceptions that allow convection to be initiated above the boundary layer to capture nocturnal elevated convection. We also quantify an encouraging consistency between the satellite- and ground-based precipitation measurements despite differing spatiotemporal resolutions and sampling periods, which provides confidence in using them to evaluate the diurnal and semi-diurnal cycle of precipitation in climate models.

58 GEOSCIENCES↗
NASA NTRS2014

Long-Term Changes in Lower Tropospheric Baseline Ozone Concentrations:

Two recent papers have quantified long-term ozone (O3) changes observed at northernmidlatitude sites that are believed to represent baseline (here understood as representative of continental to hemispheric scales) conditions. Three chemistry-climate models (NCAR CAM-chem, GFDL-CM3, and GISS-E2-R) have calculated retrospective tropospheric O3 concentrations as part of the Atmospheric Chemistry and Climate Model Intercomparison Project and Coupled Model Intercomparison Project Phase 5 model intercomparisons. We present an approach for quantitative comparisons of model results with measurements for seasonally averaged O3 concentrations. There is considerable qualitative agreement between the measurements and the models, but there are also substantial and consistent quantitative disagreements. Most notably, models (1) overestimate absolute O3 mixing ratios, on average by approximately 5 to 17 ppbv in the year 2000, (2) capture only approximately 50% of O3 changes observed over the past five to six decades, and little of observed seasonal differences, and (3) capture approximately 25 to 45% of the rate of change of the long-term changes. These disagreements are significant enough to indicate that only limited confidence can be placed on estimates of present-day radiative forcing of tropospheric O3 derived from modeled historic concentration changes and on predicted future O3 concentrations. Evidently our understanding of tropospheric O3, or the incorporation of chemistry and transport processes into current chemical climate models, is incomplete. Modeled O3 trends approximately parallel estimated trends in anthropogenic emissions of NO(sub x), an important O3 precursor, while measured O3 changes increase more rapidly than these emission estimates.

atmospheric composition↗
NASA NTRS2016

The Impact of ENSO on Trace Gas Composition in the Upper Troposphere to Lower Stratosphere

The El Nino-Southern Oscillation (ENSO) is the dominant mode of interannual variability in the tropical troposphere and its effects extend well into the stratosphere. Its impact on atmospheric dynamics and chemistry cause important changes to trace gas constituent distributions. A comprehensive suite of satellite observations, reanalyses, and chemistry climate model simulations are illuminating our understanding of processes like ENSO. Analyses of more than a decade of observations from NASAs Aura and Aqua satellites, combined with simulations from the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM) and other Chemistry Climate Modeling Initiative (CCMI) models, and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis have provided key insights into the response of atmospheric composition to ENSO. While we will primarily focus on ozone and water vapor responses in the upper troposphere to lower stratosphere, the effects of ENSO ripple through many important trace gas species throughout the atmosphere. The very large 2015-2016 El Nino event provides an opportunity to closely examine these impacts with unprecedented observational breadth. An improved quantification of natural climate variations, like those from ENSO, is needed to detect and quantify anthropogenic climate changes.

ENSO↗