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Pawson, Steven

Publications and source records attributed to Pawson, Steven.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

The Central Role of Air Quality Observations in NASA's GEOS Composition Forecasting Model

The NASA GEOS composition forecast model (GEOS-CF) provides global, high-resolution (25 km) air quality forecasts in near-real time. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). The resolution of the forecasts is the highest compared to current, publicly-available global composition forecasts.Air quality observations are an indispensable tool to evaluate the model's ability to capture the strong temporal and spatial gradients of air pollutants across the globe. We show how comparisons against near-real time observations available through OpenAQ (www.openaq.org) demonstrate the model's overall success in reproducing surface concentrations of ozone, nitrogen dioxide, and PM2.5. This analysis also helps identifying current limitations of the model, for example over South America. The model-observation mismatches are most likely caused by uncertainties in the emissions data. Using the example of Rio de Janeiro, we show how the model skill can be improved by using local, high-resolution emission inventories in combination with air quality data.

Keller, Christoph A.↗
NASA NTRS2018

NASA's GEOS Composition Model Assessment of PM2.5 During Wildfires: Inferring the Impact of PM2.5 Exposure on Adverse Respiratory & Cardiovascular Conditions

Particulate matter pollution is a mixture of solid and liquid droplets floating in the air that can lead to reduced air quality and increased adverse health impact. Fine particulate matter (PM2.5) can be emitted into the air from anthropogenic sources such as the burning of fossil fuels, motor vehicles, and powerplant emissions. Exposure to PM2.5 can aggravate pre-existing respiratory and cardiovascular conditions. When PM2.5 is inhaled it can cause damage to the lungs such as reduced lung function and shortness of breath. After being inhaled PM2.5 can enter the bloodstream and cause harm to the heart. One major natural source of PM2.5 exposure is from wildfire smoke. The particulates within the smoke from the wildfires can spread from the initial source region, potentially impacting communities both near and far. During and after wildfire events, PM2.5 levels can exceed the WHO air quality guidelines (10 m.g/m^3 annual mean; 25 m.g/m^3 daily mean), becoming hazardous to an individual's health. Global models can be used to simulate the emission and transport of these particulates and subsequently they can be valuable to air quality forecasting in highly polluted areas. The NASA Goddard Earth Observing System (GEOS) Composition Forecast (GEOS-CF) system has been used to produce near-real time air quality forecasts of atmospheric composition at a high global resolution of 25x25 km2. The GEOS-CF system utilizes the GEOS weather forecast model coupled with GEOS-Chem (version 11) chemistry module to provide analyses and forecasts of various toxic air pollutants, including PM2.5. The GEOS-CF simulated high levels of PM2.5 (40 m.g/m^3 to 250 m.g/m^3 ), exceeding the WHO guidelines, during multiple recent regional and global wildfire seasons, including the 2017 Washington State and Northern and Southern California wildfire seasons. Furthermore, the GEOS-CF simulated PM2.5 applied to a human health assessment model, BenMAP (The Environmental Benefits Mapping and Analysis Program, version 1.3), estimates the impact on adverse respiratory health conditions due to PM2.5 exposure from wildfires. The GEOS-CF predicted PM2.5 during the wildfire season with the corresponding BenMAP results provides an assessment of the human health impact of PM2.5 exposure.

Saunders, Emily↗
NASA NTRS2018

Multidecadal Changes in Lower Stratospheric Ozone: Variability Vs. Trends

As upper stratospheric ozone appears to be recovering as a result of decreasing chlorine loading following the implementation of the Montreal Protocol and its amendments and in agreement with model projections, several recent studies report an apparent decline of ozone concentrations in the lower stratosphere in the last two decades, particularly in the extratropics. Our previous work as well as at least two other studies provide evidence that this decline results from transport changes rather than an intensification of chemical depletion. It remains unclear whether these changes represent long-term internal variability or are a consequence of a climate forcing. Here we perform free-running ensembles of the recent past (1980-2016) using the Goddard Earth Observing System Model (GEOS) at the cubed sphere C180 (approximately half degree) resolution. Two suites of 10-member ensembles are performed, one in which observed sea surface temperature (SSTs) are fully prescribed, and the other in which the linear SST trend over the recent past is removed so as to only retain internal variability. We evaluate the trends in both ozone as well as two idealized tracers with prescribed uniform loss that are used to isolate the role of transport from chemistry and emissions. Probability-distribution-functions of the trends in both ozone and idealized tracers are compared among ensemble members and with observed trends in order to evaluate the likelihood of recent observed declines in lower stratospheric ozone, relative to large internal variability. Moreover, comparisons among simulations with and without imposed SST trends indicate the extent to which dynamically-driven ozone trends reflect forced trends or internal variability in lower stratospheric dynamics.

Wargan, Krzysztof↗
NASA NTRS2018

Global Assimilation of Loon Stratospheric Balloon Observations

Project Loon has an overall goal of providing worldwide internet coverage using a network of long-durationsuper-pressure balloons. Since 2013, Loon has launched over 1600 balloons from multiple tropical and middlelatitude locations. These GPS tracked balloon trajectories provide lower stratospheric wind information overthe oceans and remote land areas where traditional radiosonde soundings are sparse, thus providing uniquecoverage of lower stratospheric winds. To fully investigate these Loon winds we: 1) compare the Loon windsto winds produced by a global data assimilation system (DAS: NASA GEOS) and 2) assimilate the Loon windsinto the same comprehensive DAS. Results show that in middle latitudes the Loon winds and DAS winds agreewell, and the Loon wind assimilation has only a minor impact on the forecasts. However, in the Tropics, thereis often a substantial difference between the assimilated winds and the observed Loon winds, of 8 m/s or morein magnitude. In these cases, assimilating the Loon winds significantly improves the meteorological analysesand subsequently the forecasts of the Loon winds. By highlighting cases where the Loon and DAS winds differ,these results can lead to improved understanding of stratospheric winds, especially in the tropics, as well asaiding analyses of the representation of dynamical forcing mechanisms in the GEOS model.

Coy, Lawrence↗
NASA NTRS2018

The Stratospheric Warming of 2018 in Context of the Earth System

The major stratospheric sudden warming in February 2018 occurred in unison with changes throughout the troposphere in the northern hemisphere. Changes in large-scale dynamics and regional weather patterns are described in this study, along with features in major features of the Earth system, such as sea ice. The focus is on analyses using the Goddard Earth Observing System (GEOS) analyses, weather prediction, and seasonal forecasts. Specific topics to discuss include: - The morphology of the sudden warming, including planetary waves in the troposphere and stratosphere.- Relationships with weather over North America. - Warming over the Arctic and anomalous sea-ice distributions. - Predictability on the one-to-four week timescales. The predictions will be based on routine products generated using the GEOS systems, as well as targeted experiments that focus on the roles of different mechanisms (such as ice-atmosphere interactions).

planetary waves↗
NASA NTRS2018

GEOS-CF Model Assessment of PM2.5 During Wildfires: Inferring the Impact of PM2.5 Exposure on Adverse Respiratory & Cardiovascular Conditions

Exposure to fine particulate matter (PM2.5) can aggravate pre-existing respiratory and cardiovascular conditions. When PM2.5 is inhaled it can cause damage to the lungs such as reduced lung function and shortness of breath. After being inhaled PM2.5 can enter the bloodstream and cause harm to the heart. One major natural source of PM2.5 exposure is from wildfire smoke. The particulates within the smoke from the wildfires can spread from the initial source region, potentially impacting communities both near and far. During and after wildfire events, PM2.5 levels can exceed the WHO air quality guidelines (10 gm^3 annual mean; 25 gm^3 daily mean), becoming hazardous to an individual's health. Global models can be used to simulate the emission and transport of these particulates and subsequently they can be valuable to air quality forecasting in highly polluted areas. The NASA Goddard Earth Observing System (GEOS) version 5 Composition Forecast (GEOS-CF) system has been used to produce near-real time air quality forecasts of atmospheric composition at a high global resolution of 25 km. The GEOS-CF system utilizes the GEOS weather forecast model coupled with GEOS-Chem (version 11) chemistry module to provide analyses and forecasts of various toxic air pollutants, including PM2.5. The GEOS-CF simulated high levels of PM2.5 (40 gm^3 to 250 gm^3 ), exceeding the WHO guidelines, during multiple recent regional and global wildfire seasons, including the 2017 Seattle, WA and Los Angeles, CA wildfire seasons, and biomass burning events in India. Furthermore, the GEOS-CF simulated PM2.5 applied to a human health assessment model, BenMAP (The Environmental Benefits Mapping and Analysis Program, version 1.3), estimates the impact on adverse respiratory health conditions due to PM2.5 exposure from wildfires. The GEOS-CF predicted PM2.5 during the wildfire season with the corresponding BenMAP results provides an assessment of the human health impact of PM2.5 exposure.

Saunders, Emily↗
NASA NTRS2018

Impacts of NASA's Earth Observations on Subseasonal and Seasonal Forecasts

NASA's suite of Earth-observing satellites provides a unique view of many processes on Earth, with relevance on timescales ranging from hours to weeks and even years. NASA's observations span all parts of the Earth system: atmospheric, ocean, land and cryosphere, and include physical, chemical and biological components. This presentation explores use of NASA observations in extended-range prediction, from many days to months, using the Goddard Earth Observing System (GEOS) assimilation and predictive modeling capabilities. The skill of a weather forecast is linked to the fidelity of the initialization process (data assimilation) and the realistic representation of "fast" physical processes in the model. At longer time horizons, the slower "feedback" processes in the Earth System begin to take a more prominent role in the accuracy of the forecast. Simultaneously, forecast-skill attribution transitions away from feature-based metrics that emphasize smaller scales (e.g., representations of fronts and vortices) to metrics that emphasize the statistical distributions of large-scale features (e.g., ENSO diagnostics and teleconnections). This presentation will summarize studies performed using the GEOS-S2S (subseasonal to seasonal) system that explore the impacts of NASA observations on the fidelity of the forecasts. The GEOS-S2S system is configured for the atmosphere-ocean-land-ice model and is initialized using in-situ and space-based observations, including atmospheric aerosols and ozone which are not typically analyzed in such systems. The GEOS-S2S model routinely includes aerosol feedbacks, which systematically impact the realism of the forecasts, providing a first example of how suitable NASA observations impact the performance of the GEOS-S2S system. Studies in which a stratospheric chemistry module is activated in the GEOS-S2S system allow the impacts of ozone radiative feedbacks to be isolated. Space-based observations of sea-surface temperature and altimetry are routinely analyzed for the initialization of the GEOS-S2S system; recent advances allow the use of NASA's sea-surface salinity data, which are shown to impact the long-range skill of the forecasts.

Pawson, Steven↗
NASA NTRS2018

Tracer Transport Differences: Challenges and Implications for Flux Inversions

This poster demonstrates that different chemistry transport models (CTMs), each extensively validated, can have significant differences in the predicted transport of long-lived trace gases. For carbon dioxide (CO2), this difference is 0.5 ppm or greater in the total column. The value exceeds the nominal retrieval error requirements of the Total Carbon Column Observing Network (TCCON) and the Orbiting Carbon Observatory 2 (OCO-2), which were chosen based on the understanding of the accuracy necessary to infer surface fluxes of CO2 on regional and seasonal scales. This suggests that the transport errors of CTMs play a considerable role in the surface flux inversion of satellite-based measurements of long-lived trace gases and the interpretation of the inferred fluxes requires a careful understanding of this role.

Weir, B.↗
NASA NTRS2018

Air Quality Forecasts Using the NASA GEOS Model

We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (~25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5).

Knowland, K. Emma↗
NASA NTRS2018

Recovery of the Disrupted Quasi-Biennial Oscillation

There occurred a unique and significant disruption of the Quasi-Biennial Oscillation (QBO) during the Northern Hemisphere winter of 2015-16. Here we document the return of the QBO to its normal downward phase speed and period based on Singapore soundings, MERRA-2 re-analysis (Modern Era Retrospective Reanalysis for Research and Applications), and a simple QBO model. Daily averaged zonal winds from 100-10 hPa are used to characterized the behavior of the QBO's amplitude and phase as seen in the first two EOFs (Empirical Orthogonal Functions). These EOFs capture the QBO structure and evolution during the pre-disruption, disruption, and post-disruption times. Results show that the amplitude and phase returned to normal by June 2016, however the post-disruption QBO phase was delayed relative to the pre-disruption phase by four tenths of a QBO cycle (~11 months). A rapid, seasonal, phase shift of this magnitude is shown to be unique in the QBO observational record.

Coy, Lawrence↗
NASA NTRS2018

Recent Decline in Extratropical Lower Stratospheric Ozone Attributed to Circulation Changes

The 1998-2016 ozone trends in the lower stratosphere are examined using the Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) and related National Aeronautics and Space Administration products. After removing biases resulting from step changes in the MERRA-2 ozone observations, a discernible negative trend of 1.67 +/- 0.54 Dobson units per decade (DU/decade) is found in the 10-km layer above the tropopause between 20 deg N and 60 deg N. A weaker but statistically significant trend of 1.17 +/- 0.33 DU/decade exists between 50 deg S and 20 deg S. In the Tropics, a positive trend is seen in a 5-km layer above the tropopause. Analysis of an idealized tracer in a model simulation constrained by MERRA-2 meteorological fields provides strong evidence that these trends are driven by enhanced isentropic transport between the tropical (20 deg S-20 deg N) and extratropical lower stratosphere in the past two decades. This is the first time that a reanalysis data set has been used to detect and attribute trends in lower stratospheric ozone.

trend↗
NASA NTRS2018

Views from the 6 Aircraft Campaigns: ACT-America, HIPPO, CONTRAIL, ATom, ORCAS, and ABoVE

This presentation describes the assimilation of airborne measurements of carbon dioxide (CO2) into the Goddard Earth Observing System (GEOS) general circulation model. The main goal is to construct observationally constrained fields of CO2 starting from the bottom of the atmosphere and extending through the entire vertical column. These fields can then be compared directly to retrievals of column CO2 (XCO2) from the Greenhouse Gases Observing Satellite (GOSAT) and the Orbiting Carbon Observatory 2 (OCO-2) by using the averaging kernel and a priori profile. This approach does not equire a direct satellite overpass, but rather an overpass of the much broader region impacted by the assimilation, which alleviates some of the jeopardy of coordinating flights with satellite tracks. Furthermore, checking if the story stays the same or if it changes when the unassimilated fields are compared to the satellite soundings allows us to separate model errors from retrieval errors. This work attempts to answer a number of questions including: What are the possible causes of systematic differences between model and satellite XCO2 over the Pacific Ocean? What is the contribution of tratospheric uncertainty to XCO2 errors? What is the impact of errors in boundary layer physics on modeled XCO2?

Weir, B.↗
NASA NTRS2018

The Roles of Climate Change and Climate Variability in the 2017 Atlantic Hurricane Season

The 2017 hurricane season was extremely active with six major hurricanes, the third most on record. The sea-surface temperatures (SSTs) over the eastern Main Development Region (EMDR), where many tropical cyclones (TCs) developed during active months of August/September, were approximately 0.96 degrees Centigrade above the 1901-2017 average (warmest on record): about 0.42 degrees Centigrade from a long-term upward trend and the rest (around 80 percent) attributed to the Atlantic Meridional Mode (AMM). The contribution to the SST from the North Atlantic Oscillation over the EMDR was a weak warming, while that from ENSO was negligible. Nevertheless, ENSO, the NAO, and the AMM all contributed to favorable wind shear conditions, while the AMM also produced enhanced atmospheric instability. Compared with the strong hurricane years of 2005-2010, the ocean heat content (OHC) during 2017 was larger across the tropics, with higher SST anomalies over the EMDR and Caribbean Sea. On the other hand, the dynamical/thermodynamical atmospheric conditions, while favorable for enhanced TC activity, were less prominent than in 2005-2010 across the tropics. The results suggest that unusually warm SST in the EMDR together with the long fetch of the resulting storms in the presence of record-breaking OHC were key factors in driving the strong TC activity in 2017.

SST↗
NASA NTRS2018

NASA GMAO S2S Prediction System Hindcast and Near-Real Time Operations Strategy

In this presentation we present an overview of the GMAO Sub-Seasonal and Seasonal Prediction System with a focus on the computing time and resources and actual time it takes to complete a full set of hindcasts. The goal is to come up with some solutions to allow us to run more ensemble members for the next version of the system which will be higher resolution and take many more resources.

Kovach, Robin↗
NASA NTRS2018

Effects of Greenhouse Gas Increase and Stratospheric Ozone Depletion on Stratospheric Mean Age of Air in 1960-2010

The relative impacts of greenhouse gas (GHG) increase and stratospheric ozone depletion on stratospheric mean age of air in the 1960-2010 period are quantified using the Goddard Earth Observing System Chemistry-Climate Model. The experiment compares controlled simulations using a coupled atmosphere-ocean version of the Goddard Earth Observing System Chemistry-Climate Model, in which either GHGs or ozone depleting substances, or both factors evolve over time. The model results show that GHGs and ozone-depleting substances have about equal contributions to the simulated mean age decrease, but GHG increases account for about two thirds of the enhanced strength of the lower stratospheric residual circulation. It is also found that both the acceleration of the diabatic circulation and the decrease of the mean age difference between downwelling and upwelling regions are mainly caused by GHG forcing. The results show that ozone depletion causes an increase in the mean age of air in the Antarctic summer lower stratosphere through two processes: (1) a seasonal delay in the Antarctic polar vortex breakup that inhibits young midlatitude air from mixing with the older air inside the vortex, and (2) enhanced Antarctic downwelling that brings older air from middle and upper stratosphere into the lower stratosphere.

stratospheric ozone depletion↗
NASA NTRS2018

Multidecadal Changes in the UTLS Ozone from the MERRA-2 Reanalysis and the GMI Chemistry Model

Long-term changes of ozone in the UTLS (Upper Troposphere / Lower Stratosphere) reflect the response to decreases in the stratospheric concentrations of ozone-depleting substances as well as changes in the stratospheric circulation induced by climate change. To date, studies of UTLS ozone changes and variability have relied mainly on satellite and in-situ observations as well as chemistry-climate model simulations. By comparison, the potential of reanalysis ozone data remains relatively untapped. This is despite evidence from recent studies, including detailed analyses conducted under SPARC (Scalable Processor Architecture) Reanalysis Intercomparison Project (S-RIP), that demonstrate that stratospheric ozone fields from modern atmospheric reanalyses exhibit good agreement with independent data while delineating issues related to inhomogeneities in the assimilated observations. In this presentation, we will explore the possibility of inferring long-term geographically and vertically resolved behavior of the lower stratospheric (LS) ozone from NASA's MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications -2) reanalysis after accounting for the few known discontinuities and gaps in its assimilated input data. This work builds upon previous studies that have documented excellent agreement between MERRA-2 ozone and ozonesonde observations in the LS. Of particular importance is a relatively good vertical resolution of MERRA-2 allowing precise separation of tropospheric and stratospheric ozone contents. We also compare the MERRA-2 LS ozone results with the recently completed 37-year simulation produced using Goddard Earth Observing System in "replay" mode coupled with the GMI (Global Modeling Initiative) chemistry mechanism. Replay mode dynamically constrains the model with the MERRA-2 reanalysis winds, temperature, and pressure. We will emphasize the areas of agreement of the reanalysis and replay and interpret differences between them in the context of our increasing understanding of model transport driven by assimilated winds.

Ozone↗