Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “COMMUNITY ATMOSPHERE MODEL”

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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

CMIP5 model selection for ISMIP6 ice sheet model forcing: Greenland and Antarctica

Abstract. The ice sheet model intercomparison project for CMIP6 (ISMIP6) effort brings together the ice sheet and climate modeling communities to gain understanding of the ice sheet contribution to sea level rise. ISMIP6 conducts stand-alone ice sheet experiments that use space- and time-varying forcing derived from atmosphere–ocean coupled global climate models (AOGCMs) to reflect plausible trajectories for climate projections. The goal of this study is to recommend a subset of CMIP5 AOGCMs (three core and three targeted) to produce forcing for ISMIP6 stand-alone ice sheet simulations, based on (i) their representation of current climate near Antarctica and Greenland relative to observations and (ii) their ability to sample a diversity of projected atmosphere and ocean changes over the 21st century. The selection is performed separately for Greenland and Antarctica. Model evaluation over the historical period focuses on variables used to generate ice sheet forcing. For stage (i), we combine metrics of atmosphere and surface ocean state (annual- and seasonal-mean variables over large spatial domains) with metrics of time-mean subsurface ocean temperature biases averaged over sectors of the continental shelf. For stage (ii), we maximize the diversity of climate projections among the best-performing models. Model selection is also constrained by technical limitations, such as availability of required data from RCP2.6 and RCP8.5 projections. The selected top three CMIP5 climate models are CCSM4, MIROC-ESM-CHEM, and NorESM1-M for Antarctica and HadGEM2-ES, MIROC5, and NorESM1-M for Greenland. This model selection was designed specifically for ISMIP6 but can be adapted for other applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Evaluation of the atmosphere–land–ocean–sea ice interface processes in the Regional Arctic System Model version 1 (RASM1) using local and globally gridded observations

The Regional Arctic System Model version 1 (RASM1) has been developed to provide high-resolution simulations of the Arctic atmosphere–ocean–sea ice–land system. Here, we provide a baseline for the capability of RASM to simulate interface processes by comparing retrospective simulations from RASM1 for 1990–2014 with the Community Earth System Model version 1 (CESM1) and the spread across three recent reanalyses. Evaluations of surface and 2 m air temperature, surface radiative and turbulent fluxes, precipitation, and snow depth in the various models and reanalyses are performed using global and regional datasets and a variety of in situ datasets, including flux towers over land, ship cruises over oceans, and a field experiment over sea ice. These evaluations reveal that RASM1 simulates precipitation that is similar to CESM1, reanalyses, and satellite gauge combined precipitation datasets over all river basins within the RASM domain. Snow depth in RASM is closer to upscaled surface observations over a flatter region than in more mountainous terrain in Alaska. The sea ice–atmosphere interface is well simulated in regards to radiation fluxes, which generally fall within observational uncertainty. RASM1 monthly mean surface temperature and radiation biases are shown to be due to biases in the simulated mean diurnal cycle. At some locations, a minimal monthly mean bias is shown to be due to the compensation of roughly equal but opposite biases between daytime and nighttime, whereas this is not the case at locations where the monthly mean bias is higher in magnitude. These biases are derived from errors in the diurnal cycle of the energy balance (radiative and turbulent flux) components. Therefore, the key to advancing the simulation of SAT and the surface energy budget would be to improve the representation of the diurnal cycle of radiative and turbulent fluxes. The development of RASM2 aims to address these biases. Still, an advantage of RASM1 is that it captures the interannual and interdecadal variability in the climate of the Arctic region, which global models like CESM cannot do.

58 GEOSCIENCES↗
DOE OSTI2019

Uncovering the Forced Climate Response from a Single Ensemble Member Using Statistical Learning

Internal atmospheric variability fundamentally limits predictability of climate and obscures evidence of anthropogenic climate change regionally and on time scales of up to a few decades. Dynamical adjustment techniques estimate and subsequently remove the influence of atmospheric circulation variability on temperature or precipitation. The residual component is expected to contain the thermodynamical signal of the externally forced response but with less circulation-induced noise. Existing techniques have led to important insights into recent trends in regional (hydro-) climate and their drivers, but the variance explained by circulation is often low. Here, we develop a novel dynamical adjustment technique by implementing principles from statistical learning. We demonstrate in an ensemble of Community Earth System Model (CESM) simulations that statistical learning methods, such as regularized linear models, establish a clearer relationship between circulation variability and atmospheric target variables, and need relatively short periods of record for training (around 30 years). The method accounts for, on average, 83% and 78% of European monthly winter temperature and precipitation variability at gridcell level, and around 80% of global mean temperature and hemispheric precipitation variability. We show that the residuals retain forced thermodynamical contributions to temperature and precipitation variability. Accurate estimates of the total forced response can thus be recovered assuming that forced circulation changes are gradual over time. Overall, forced climate response estimates can be extracted at regional or global scales from approximately 3–5 times fewer ensemble members, or even a single realization, using statistical learning techniques. We anticipate the technique will contribute to reducing uncertainties around internal variability and facilitating climate change detection and attribution.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2009

Scientific Benefits of Space Science Models Archiving at Community Coordinated Modeling Center

The Community Coordinated Modeling Center (CCMC) hosts a set of state-of-the-art space science models ranging from the solar atmosphere to the Earth's upper atmosphere. CCMC provides a web-based Run-on-Request system, by which the interested scientist can request simulations for a broad range of space science problems. To allow the models to be driven by data relevant to particular events CCMC developed a tool that automatically downloads data from data archives and transform them to required formats. CCMC also provides a tailored web-based visualization interface for the model output, as well as the capability to download the simulation output in portable format. CCMC offers a variety of visualization and output analysis tools to aid scientists in interpretation of simulation results. During eight years since the Run-on-request system became available the CCMC archived the results of almost 3000 runs that are covering significant space weather events and time intervals of interest identified by the community. The simulation results archived at CCMC also include a library of general purpose runs with modeled conditions that are used for education and research. Archiving results of simulations performed in support of several Modeling Challenges helps to evaluate the progress in space weather modeling over time. We will highlight the scientific benefits of CCMC space science model archive and discuss plans for further development of advanced methods to interact with simulation results.

Kuznetsova, Maria M.↗
DOE OSTI2026

Computational Modeling of Atmospheric Processes at Texas Southern University

Texas Southern University (TSU) is strengthening its research program in atmospheric chemistry and physics with a climate science emphasis by leveraging partnerships with the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Facility, Brookhaven National Laboratory (BNL), and the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). This RDPP-supported program focuses on secondary organic aerosols (SOAs) and reactive atmospheric species that influence cloud formation, precipitation processes, and radiative forcing. SOAs play a critical role in cloud microphysics and Earth’s energy balance, yet the chemical and physical mechanisms governing SOA–cloud interactions remain a significant source of uncertainty in predictive climate models. Through computational modeling, observational data analysis, and national laboratory collaboration, this program develops a skilled cohort of students trained in atmospheric science, environmental data analysis, and climate-relevant modeling. These research experiences build technical competencies that are transferable to careers in government laboratories, academia, and industry. By engaging students from historically underrepresented communities in high-impact climate research, TSU expands participation in the atmospheric sciences workforce while contributing meaningful scientific insights to DOE-supported ARM research activities. This partnership strengthens national capacity in climate science and supports the development of the next generation of atmospheric researchers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Surface Atmosphere Integrated Field Laboratory (SAIL) Science Plan

Mountains are the natural water towers of the world, effectively turning water vapor into readily available fresh water through precipitation, snowpack, and runoff. Unfortunately, Earth system models (ESMs) have persistently been unable to predict the timing and availability of water resources from mountains because the source(s) of model error are difficult to isolate in complex terrain with limited atmospheric or land-surface observations. Further complications arise from the gross scale mismatch between ESM grid box sizes and the relevant scales of mountainous hydrological processes. The mountain hydrometeorology community has repeatedly called for integrated atmospheric and land observations of water and energy budgets in complex terrain that span these scales to establish benchmarks against which scale-dependent models can be further developed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Understanding the Drivers of Atlantic Multidecadal Variability using a Stochastic Model Hierarchy

The relative importance of ocean and atmospheric dynamics in generating Atlantic Multidecadal Variability (AMV) remains an open question. Comparisons between climate models with SLAB and fully-dynamic (FULL) ocean components are often used to explore this question, but cannot reveal how individual ocean processes generate these differences. We build a hierarchy of physically interpretable stochastic models to investigate the contribution of two upper-ocean processes to AMV: the role of seasonal variation and mixed-layer entrainment. This interpretability arises from the stochastic model’s simplified representation of sea surface temperature (SST), considering only the local upper ocean response to white-noise atmospheric forcing and its impact on surface heat exchange. We focus on understanding differences between SLAB and FULL non-eddy resolving pre-industrial control simulations of the Community Earth System Model 1 (CESM), and estimate the stochastic model parameters from each respective simulation. Despite its simplicity, the stochastic model reproduces temporal characteristics of SST variability in the SPG, including reemergence, seasonal-to-interannual persistence and power spectra. Furthermore, unrealistically persistent SST of the CESM-SLAB ocean simulation is reproduced in the equivalent stochastic model configuration where the mixed-layer depth (MLD) is constant. The stochastic model also reveals that vertical entrainment primarily damps SST variability, thus explaining why SLAB exhibits larger SST variance than FULL. Here, the stochastic model driven by temporally stochastic, spatially coherent forcing patterns reproduces the canonical AMV pattern. However, the amplitude of low-frequency variability remains underestimated, suggesting a role for ocean dynamics beyond entrainment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Development of Community, Capabilities and Understanding Through Unmanned Aircraft-Based Atmospheric Research: The LAPSE-RATE Campaign

Members of the international community developing unmanned aircraft for atmospheric research conducted a highly-successful coordinated flight week in Colorado during summer 2018 to collect measurements, develop capabilities, and enhance community in the field. Because unmanned aircraft systems (UAS) offer new perspectives on the atmosphere, their use in atmospheric science is expanding rapidly. In support of this growth, the International Society for Atmospheric Research using Remotely-piloted Aircraft (ISARRA) has been developed and have convened annual meetings and 'flight weeks'. The 2018 flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE), involved a one-week deployment to Colorado's San Luis Valley. Between 14-20 July 2018 over 100 students, scientists, engineers, pilots and outreach coordinators conducted an intensive field operation using unmanned aircraft and ground-based assets to develop datasets, community, and capabilities. In addition to a coordinated 'community day' which offered a chance for groups to share their aircraft and science with the San Luis Valley community, LAPSE-RATE participants conducted nearly 1300 research flights totaling over 250 flight hours. The measurements collected have been used to advance capabilities (instrumentation, platforms, sampling techniques and modeling tools), conduct a detailed system intercomparison study, develop new collaborations, and foster community support for the use of UAS in atmospheric science.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

PyDDA: A Pythonic Direct Data Assimilation Framework for Wind Retrievals

This software assimilates data from an arbitrary number of weather radars together with other spatial wind fields (eg numerical weather forecasting model data) in order to retrieve high resolution three dimensional wind fields. PyDDA uses NumPy and SciPy’s optimization techniques combined with the Python Atmospheric Radiation Measurement (ARM) Radar Toolkit (Py-ART) in order to create wind fields using the 3D variational technique (3DVAR). PyDDA is hosted and distributed on GitHub at https://github.com/openradar/PyDDA. PyDDA has the potential to be used by the atmospheric science community to develop high resolution wind retrievals from radar networks. These retrievals can be used for the evaluation of numerical weather forecasting models and plume modelling. This paper shows how wind fields from 2 NEXt generation RADar (NEXRAD) WSR-88D radars and the High Resolution Rapid Refresh can be assimilated together using PyDDA to create a high resolution wind field inside Hurricane Florence.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Inter-Calibrating CERES Instrument Fluxes Utilizing the CERES Instrument Geostationary Scan Mode Observations

The NASA Clouds and the Earth’s Radiant Energy System (CERES) project provides the scientific community observed top-of-atmosphere (TOA) fluxes to monitor the Earth’s energy imbalance and validate climate models. The CERES instruments onboard the Terra, Aqua, SNPP and NOAA-20 satellites need to be inter-calibrated to provide a continuous and consistent TOA flux record contained in the CERES Energy Balanced and Filled (EBAF) product. The SNPP and NOAA-20 satellites are positioned a half an orbit apart within the same sun-synchronous orbit (1:30 PM equatorial crossing time) thus preventing any direct time-matched observations. The CERES project designed the geostationary scan mode (GEOscan) to inter-calibrate the Geostationary Earth Radiation Budget (GERB) broadband measurement onboard the Meteosat 8-11 satellites. By rotating the orientation of the CERES instrument scan to match the angular configuration of the geostationary scan mode, the comparison of both angle and time matched observations suitable for inter-calibration is possible. To determine if the GEOscan mode is useful for inter-calibrating two CERES instruments placed in the same 16-day repeating orbit, the CERES project placed the Terra and Aqua CERES instruments in GEOscan mode once every 6 days over a rotation of five geostationary domains beginning in February 2023. The GEO imager narrowband to broadband derived radiances are used as transfer radiometers to compare the Terra and Aqua CERES observed radiances. Since both the Terra and Aqua CERES instruments are in GEOscan mode over the same GEO domain and day, the GEO imager calibration is expected to be consistent between the Terra and Aqua overpass times. Any GEO imager narrowband to broadband regional biases should be similar for the Terra and Aqua overpasses. The GEOscan mode Terra and Aqua CERES inter-calibration coefficients for both shortwave and longwave broadband radiances will be compared against the CERES instrument team’s coefficients to determine the viability of this approach. Improvements in the GEO imager narrowband to broadband approaches will also be investigated and verified within this framework.

Kyle Itterly↗
DOE OSTI2014

2014 CESM Tutorial

The 2014 annual tutorial for the Community Earth System Model (CESM) was held on August 11-August 15, 2014 at the National Center for Atmospheric Research in Boulder, CO. It included lectures and practical sessions on numerous aspects of the CESM model. The proceedings submitted here include a description of the tutorial.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hydrological analysis in watersheds with a variable-resolution global climate model (VR-CESM)

Traditionally, watershed-scale hydrology is simulated by distributed hydrological models with offline meteorological forcing data, or by regional regional climate models that link atmospheric and land hydrology interactions. Global climate models (GCMs) are rarely used to study watershed-scale hydrology due to the relatively coarse grid resolution, computationally expensive downscaling, and simplified physical processes. Recently, however, watershed-scale hydrology analysis has become possible in GCMs due to the development of variable-resolution GCMs that dynamically couple the hydrological processes between atmosphere and land systems at fine resolutions in selected regions and coarse resolution elsewhere. In this study, we used the variable-resolution Community Earth System Model (VR-CESM) with refined-resolution (14 km) in the western U.S. and eastern China to evaluate watershed-scale hydrology. Furthermore, we compared the historical VR-CESM outputs with gauge measurements and other hydrological models (e.g., National Water Model in the U.S.) and calibrated the subsurface runoff capacities in four mountainous watersheds. An RCP8.5 projection from 2007 to 2050 is used to estimate the impact of changing precipitation and snow climatology on watershed hydrology. We also analyzed the long-term runoff variability and the possibility of extreme runoff events as simulated by the VR-CESM. Although calibration is not possible in larger-scale watersheds, VR-CESM simulates the long-term annual variability of watersheds and provides insights on climate change impacts on hydrology. We conclude that refined-resolution VR-CESM can be used for watershed-scale hydrology analysis to understand water resources and water balance, in addition to traditional watershed-scale hydrological models. It enables hydrological analysis at multiple watersheds in one simulation and can help understand the two-way dynamics between land surface hydrology and atmospheric processes, and is especially practical for projecting climate change impacts. However, it is challenging to apply VR-CESM for hydrologic analysis in regulated watersheds as human factors (e.g., pumping, irrigation, water diversion) have not been fully addressed in VR-CESM.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Cloud and Aerosol Retrieval for the 2001 GLAS Satellite Lidar Mission

The Geoscience Laser Altimeter System (GLAS) is scheduled for launch in July of 2001 aboard the Ice, Cloud and Land Elevation Satellite (ICESAT). In addition to being a precision altimeter for mapping the height of the Earth's icesheets, GLAS will be an atmospheric lidar, sensitive enough to detect gaseous, aerosol, and cloud backscatter signals, at horizontal and vertical resolutions of 175 and 75m, respectively. GLAS will be the first lidar to produce temporally continuous atmospheric backscatter profiles with nearly global coverage (94-degree orbital inclination). With a projected operational lifetime of five years, GLAS will collect approximately six billion lidar return profiles. The large volume of data dictates that operational analysis algorithms, which need to keep pace with the data yield of the instrument, must be efficient. So, we need to evaluate the ability of operational algorithms to detect atmospheric constituents that affect global climate. We have to quantify, in a statistical manner, the accuracy and precision of GLAS cloud and aerosol observations. Our poster presentation will show the results of modeling studies that are designed to reveal the effectiveness and sensitivity of GLAS in detecting various atmospheric cloud and aerosol features. The studies consist of analyzing simulated lidar returns. Simulation cases are constructed either from idealized renditions of atmospheric cloud and aerosol layers or from data obtained by the NASA ER-2 Cloud Lidar System (CLS). The fabricated renditions permit quantitative evaluations of operational algorithms to retrieve cloud and aerosol parameters. The use of observational data permits the evaluations of performance for actual atmospheric conditions. The intended outcome of the presentation is that climatology community will be able to use the results of these studies to evaluate and quantify the impact of GLAS data upon atmospheric modeling efforts.

Hart, William D.↗
DOE OSTI2015

Pan-spectral observing system simulation experiments of shortwave reflectance and long-wave radiance for climate model evaluation

Abstract. Top-of-atmosphere (TOA) spectrally resolved shortwave reflectances and long-wave radiances describe the response of the Earth's surface and atmosphere to feedback processes and human-induced forcings. In order to evaluate proposed long-duration spectral measurements, we have projected 21st Century changes from the Community Climate System Model (CCSM3.0) conducted for the Intergovernmental Panel on Climate Change (IPCC) A2 Emissions Scenario onto shortwave reflectance spectra from 300 to 2500 nm and long-wave radiance spectra from 2000 to 200 cm –1 at 8 nm and 1 cm –1 resolution, respectively. The radiative transfer calculations have been rigorously validated against published standards and produce complementary signals describing the climate system forcings and feedbacks. Additional demonstration experiments were performed with the Model for Interdisciplinary Research on Climate (MIROC5) and Hadley Centre Global Environment Model version 2 Earth System (HadGEM2-ES) models for the Representative Concentration Pathway 8.5 (RCP8.5) scenario. The calculations contain readily distinguishable signatures of low clouds, snow/ice, aerosols, temperature gradients, and water vapour distributions. The goal of this effort is to understand both how climate change alters reflected solar and emitted infrared spectra of the Earth and determine whether spectral measurements enhance our detection and attribution of climate change. This effort also presents a path forward to understand the characteristics of hyperspectral observational records needed to confront models and inline instrument simulation. Such simulation will enable a diverse set of comparisons between model results from coupled model intercomparisons and existing and proposed satellite instrument measurement systems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Latest Results from NASA Ames’ COSmIC and Optical Constants Facility (OCF): Determining Optical Constants for Titan, Pluto and Protoplanetary Disks Applications

The NASA Ames COsmic SImulation Chamber (COSmIC) is a unique experimental facility that can be used, among many applications, to produce solid particles from gas phase molecular precursors at low temperature (150 K) using a plasma discharge to induce the chemistry in the stream of a free jet expansion. The choice of the initial gas mixture used to produce the solid sample allows the simulation of either cold planetary atmospheres like Titan or Pluto (with N2/CH4-based initial mixtures), or circumstellar environments (with Ar/CxHy-based initial mixtures). The Ames Optical Constants Facility (OCF) allows the determination of optical constants covering a broad wavelength range with high spectral resolution for solid materials, analogs of organic refractory materials formed in planetary and astrophysical environments. The core of the OCF is a Fourier transform infrared (FTIR) spectrometer that allows the continuous characterization of solid samples in the visible to far-infrared (FIR) range (0.59–200 μm, 16,950–50 cm−1). Modeling of the laboratory measurements conducted with the OCF allows the determination of accurate optical constants, n and k, over the full vis-FIR range. Here we present the latest results of two studies that combined (1) experiments performed with COSmIC to produce analogs of aerosols forming in Titan’s atmosphere and analogs of cosmic grains forming in circumstellar envelops, and (2) the characterization of these analogs with the OCF to provide the real and imaginary parts of their refractive indices, n + ik, to the community, from the visible to the FIR. These optical constants can be used as critical input parameters in radiative transfer, atmospheric and reflectance models to interpret observational data of, e.g., Titan’s atmosphere and protoplanetary disks. Providing optical constants for various materials of different compositions allows to explore a broad range of composition by simulating mixtures of materials. We also present a new project to produce analogs of Pluto’s atmospheric aerosols with COSmIC and determine their optical constants with OCF, to be used in reflectance spectra models for the interpretation of New Horizons observations of Lowell Regio, Sputnik Planitia and Cthulhu.

COsmic SImulation Chamber (COSmIC)↗
DOE OSTI2015

Climate and Environmental Sciences Division, North Slope of Alaska Priorities Workshop, September 10–12, 2014

The U.S. Department of Energy (DOE) Climate and Environmental Sciences Division (CESD) within the Office of Biological and Environmental Research (BER), is hosting a series of workshops to solicit community feedback on how key scientific needs, gaps, and priorities in process model understanding and climate model prediction could be addressed through strategic deployment and operation of instruments and routine high resolution modeling. In particular, the use of the Atmospheric Radiation Measurement (ARM) Climate Research Facility—a DOE Office of Science user facility— is being reconfigured to better support the integration of observations and high-resolution modeling and to address these types of emerging science questions. As part of ARM’s reconfiguration, instruments are being concentrated to produce denser observational capabilities at fewer sites. In September 2014, the North Slope of Alaska (NSA) Priorities Workshop was held to obtain scientific input on priorities for observational and scientific research activities related to atmospheric processes in the North Slope region and to identify gaps or needs that limit the ability of the research community to address these scientific priorities. Topics of discussion included capabilities at the existing ARM NSA facilities in Barrow and Oliktok Point, additional observations that may supplement and/or link these facilities (e.g., aircraft, unmanned aerial systems, tethered balloons, scanning radar systems, surface stations), and modeling activities.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2009

Satellite Observations for Detecting and Tracking Changes in Atmospheric Composition

The satellite observations provide constraints on detailed atmospheric modeling, including emissions inventories, indications of transport, harmonized data over vast areas suitable for trends analysis, and a link between spatial scales ranging from local to global, and temporal scales from diurnal to interannual. 1 The National Oceanic and Atmospheric Administration's (NOAA) long-term commitments help provide these observations in cooperation with international meteorological organizations. NASA s long-term commitments will advance scientifically important observations as part of its Earth Science Program, and will assist the transition of the science measurements to applied analyses through the Applied Science Program. Both NASA and NOAA have begun to provide near realtime data and tools to visualize and analyze satellite data,2 while maintaining data quality, validation, and standards. Consequently, decision-makers can expect satellite data services to support air quality decision making now and in the future. The international scientific community's Integrated Global Atmosphere Chemistry Observation System Report3 outlined a plan for ground-based, airborne and satellite measurements and models to integrate the observations into a four-dimensional representation of the atmosphere (space and time) to support assessment and policy information needs. This plan is being carried out under the Global Earth Observation System of Systems (GEOSS). Demonstrations of such an integrated capability4 provide new understanding of the changing atmosphere and link policy decisions to benefits for society. In this article, we highlight the use of satellite data to constrain biomass burning emissions, to assess oxides of nitrogen (NO(x)) emission reductions, and to contribute to state implementation plans, as examples of the use of satellite observations for detecting and tracking changes in atmospheric composition.

Neil, Doreen O.↗