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Pawson, Steven

Publications and source records attributed to Pawson, Steven.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Envisioning U.S. Climate Predictions and Projections to Meet New Challenges

In the face of a changing climate, the understanding, predictions, and projections of natural and human systems are increasingly crucial to prepare and cope with extremes and cascading hazards, determine unexpected feedbacks and potential tipping points, inform long-term adaptation strategies, and guide mitigation approaches. Increasingly complex socio-economic systems require enhanced predictive information to support advanced practices. Such new predictive challenges drive the need to fully capitalize on ambitious scientific and technological opportunities. These include the unrealized potential for very high-resolution modeling of global-to-local Earth system processes across timescales, reduction of model biases, enhanced integration of human systems and the Earth Systems, better quantification of predictability and uncertainties; expedited science-to-service pathways, and co-production of actionable information with stakeholders. Enabling technological opportunities include exascale computing, advanced data storage, novel observations and powerful data analytics, including artificial intelligence and machine learning. Looking to generate community discussions on how to accelerate progress on U.S. climate predictions and projections, representatives of Federally-funded U.S. modeling groups outline here perspectives on a six-pillar national approach grounded in climate science that builds on the strengths of the U.S. modeling community and agency goals. This calls for an unprecedented level of coordination to capitalize on transformative opportunities, augmenting and complementing current modeling center capabilities and plans to support agency missions. Tangible outcomes include projections with horizontal spatial resolutions finer than 10 km, representing extremes and associated risks in greater detail, reduced model errors, better predictability estimates, and more customized projections to support next generation climate services.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

NASA's High-Resolution GEOS Forecasting and Reanalysis Products: Support for TOLNet

Stratospheric intrusions (SIs) the introduction of ozone-rich stratospheric air into the troposphere – have been the interest of decades of research for their link with surface ozone air quality exceedances, especially at the high elevations in the western USA in springtime; however, the impact of SIs in the remaining seasons and over the rest of the USA is less clear. We can expect MERRA-2 to realistically represent both atmospheric dynamics and composition. The operational GEOS weather forecasting system, GEOS-FP, has a similar ozone observing system to MERRA-2, while NASA's new global high-resolution air quality forecast system, GEOS-CF, combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12), simulating a wide range of additional air pollutants and tracers which strengthens this detailed analysis of the intrusions and the sources for the high ozone concentrations. Using a multitude of observational datasets, including lidar, air craft, ozonesondes and air quality monitoring surface sites, in combination with the GEOS forecast and reanalysis products, we aim to provide the public with tools which are available in near-real time to enhance their capability to identify the impact of stratospheric air on surface ozone concentrations separate from anthropogenic sources. In particular, improved understanding of the connections between large-scale climate variability and local-scale dynamically-driven air quality events may support improved seasonal prediction of SI events.

Knowland, K. Emma↗
NASA NTRS2020

Lower-Stratospheric Tracer Trends and Variability from Reanalyses

Previous studies have robustly identified a decrease since 1998 in lower stratospheric ozone in the Northern Hemisphere (NH). While this ozone decrease is qualitatively explained as resulting from changes in the large-scale circulation, there is not yet a quantitative mechanistic explanation of these changes. Here we explore the drivers of recent ozone changes using two different configurations of the Goddard Earth Observing System (GEOS) general circulation model. The first configuration of GEOS includes a full chemistry module and is constrained with meteorological fields from the MERRA-2 reanalysis. This configuration (M2GMI) is used to analyze an idealized tracer that covaries closely with ozone on interannual and decadal timescales, revealing that recent ozone decreases in the NH subtropics are associated with a poleward expansion of upwelling in the NH LS, with reduced (enhanced) downwelling over northern subtropics (midlatitudes). The second configuration of GEOS is a free-running version of the GEOS Chemistry-Climate Model (CCM) that is used to perform a ten-member ensemble of free-running simulations. Comparisons of the two configurations reveal that, while the free-running model can produce negative ozone changes in the NH LS, the magnitude of these changes is significantly weaker, relative to both M2GMI and MERRA-2; moreover, these weaker ozone decreases are consistent with weaker simulated changes in the residual circulation. Finally, we examine the GEOS model results in the broader context of the hindcast simulations performed as part of Phase 1 of the Chemistry Climate Modeling Initiative. We show that the majority of the free-running simulations considered here also exhibit weaker long-term residual circulation changes, compared to reanalyses.

Wargan, Kris↗
NASA NTRS2020

Local to Global Air Quality Simulations using the NASA GEOS Composition Forecast Model, GEOS-CF

We give an overview of the NASA Global Earth Observing System Composition Forecast model (GEOS-CF), a high-resolution (roughly 25-km) global composition model developed by the NASA Global Modeling and Assimilation Office (GMAO). This system combines the GEOS weather and aerosol model with the GEOS-Chem chemistry module to provide a holistic view of atmospheric composition that captures a wide range of air pollutants such as ozone,nitrogen oxides, volatile organic compounds, and fine particulate matter.Given the global extent of the model, GEOS-CF captures large-scale processes such as long-range transport of air pollutants, across ocean basins and continents.

Knowland, Emma K.↗
NASA NTRS2020

OMI Measurements of Bromine Monoxide and Implications for Missing Sources of Polar Bromine in GEOS-Chem

The OMI satellite instrument provides total column measurements of bromine monoxide (BrO) with daily global coverage. Reactive bromine compounds (Br and BrO) catalytically destroy ozone in both the stratosphere and troposphere. The current emission scheme of brominated source gases in the GEOS-Chem chemical transport model well represents the stratospheric burden of bromine. However, halogen research in GEOS-Chem has largely focused on the influence of halogens on the tropospheric oxidative capacity. In the troposphere, the distribution of brominated compounds is more variable and significant uncertainties remain in the chemical processes governing the sources and sinks of reactive bromine compounds. In this study, we use GEOS-Chem simulated stratospheric columns of BrO to separate the tropospheric signal of BrO from the OMI total column measurements. The resulting tropospheric BrO columns are used to identify seasonal and regional anomalies in tropospheric BrO not currently represented in GEOS-Chem. In particular, periods of elevated tropospheric BrO during polar spring are observable by OMI, and past studies have connected these so-called "bromine explosion" events to near complete removal of surface ozone. Due to significant uncertainties in the springtime polar source of reactive bromine, many global models, including GEOS-Chem, do not simulate these tropospheric ozone depletion events. Consequently, OMI-based tropospheric columns of BrO are useful tool for investigating the impact of bromine explosion events on tropospheric ozone depletion episodes as well as background air quality.

Wales, Pamela↗
NASA NTRS2020

High Resolution Global Coupled Chemistry-Meteorology Simulations Using the NASA GEOS Composition Forecast System, GEOS-CF

We will give an overview of the NASA Global Earth Observing System Composition Forecast system (GEOS-CF), a high-resolution (0.25 degree) global composition model developed by the NASA Global Modeling and Assimilation Office (GMAO). This system combines the GEOS weather and aerosol model with the GEOS-Chem chemistry module (version 12) to provide a holistic view of atmospheric composition that captures a wide range of air pollutants such as ozone, nitrogen oxides, volatile organic compounds, and fine particulate matter. The spatial resolution of 0.25 degrees (approx. 25 km) is fine enough to resolve local features such as nighttime ozone titration previously resolved only by urban or regional models. Furthermore, since there are no boundary conditions for a global model, the GEOS-CF captures large-scale processes such as long-range transport of air pollutants from forest fires. Comparisons against surface observations highlight the model’s overall capability to reproduce the diurnal variability of air pollutants under a variety of meteorological conditions. In addition, we show how machine learning techniques can be used to correct for sub-grid variability, which further improves model estimates at a given surface observation site. The GEOS-CF system offers a new tool for scientists and the public health community alike and is being developed jointly with several government and non-profit partners. As an example, we will show the use of GEOS-CF during the Satellite Coastal and Oceanic Atmospheric Pollution Experiment (SCOAPE). The campaign, conducted in collaboration between NASA and the Bureau of Ocean Energy Management (BOEM), aims to investigate the response of onshore air quality to Outer Continental Shelf (OCS) oil and gas exploration, development and production. Detailed gas-phase chemistry, as provided by GEOS-CF, is critical to understand the formation of air pollution related to hydrocarbon emissions from offshore oil and gas activities. The accuracy of GEOS-CF can be further improved by incorporating detailed offshore emissions compiled by BOEM.

Knowland, K. Emma↗
NASA NTRS2019

Seasonal Forecasting of the Quasi-Biennial Oscillation

The ability to seasonally forecast the Quasi-Biennial Oscillation (QBO) was examined using NASA S2S (Sub-seasonal to Seasonal), 9-month, retrospective forecasts. Validation of these forecasts showed that the S2S retrospective QBO forecasts improved skill in predicting the QBO amplitude and phase over a simple QBO phase propagation model at forecast lead times of 1 to 3 months. Results from an initial assessment of whether more accurate QBO forecasts can improve Northern Hemisphere winter sea level pressure forecasts showed no significant forecast improvement at a 1-month lead time, indicating the need for improved stratosphere-troposphere QBO coupling metrics and pathway identification. Overall, these results suggest that future improvements in representing the QBO in global models can increase the ensemble fraction of valid 1 to 3 month QBO forecasts and potentially extend useful QBO forecasts beyond 3 months.

Coy, Lawrence↗
NASA NTRS2019

Constraining the Earth System with EOS-Aura Observations

NASA's Goddard Earth Observing System (GEOS) model and data assimilation system is a flexible, modular global system that is used for applications that range from weather prediction to climate analysis. Resolving scales ranging from a few kilometers to several tens of kilometers, with scale-aware parametrization settings, the GEOS system offers NASA scientists and their partners a flexible system that is attuned to bringing in observations from all components of the Earth System. The GEOS system thus serves as a tool that enhances the value to NASA of observations from individual instruments, by bringing them into context with the full suite of "operational" observations and other research datasets. This presentation will emphasize how the GEOS system has been used to extend the value of observations from EOS-Aura, in conjunction with other NASA and non-NASA observations. One example is atmospheric ozone from the OMI and MLS instruments, that has been used extensively in GEOS systems for both weather (GEOS-FP) and the MERRA-2 reanalysis. The presentation will emphasize the value of these ozone datasets for studying long-term changes of ozone since 2004 and will discuss prospects of continuing such analyses in the post-Aura era. A new configuration of GEOS, the Composition Forecasting (CF) system has recently gone in to production: this uses a full troposphere-stratosphere chemistry mechanism (GEOS-Chem) to analyze and predict global constituent distributions, including surface air quality. While constituent observations are not yet assimilated into GEOS-CF, EOS-Aura data are used substantially to evaluate the system and plans are in place to introduce assimilation at a later stage. Examples from GEOS-CF will be shown to illustrate the value of EOS-Aura observations. Discussions will focus on the likely value of long-term analyses of EOS-Aura observations in context of understanding potential impacts on the health of humans and the biosphere, including the importance of sustaining long-term, global observing systems such as that pioneered by EOS-Aura.

Pawson, Steven↗
NASA NTRS2019

Near Real-Time Air Quality Forecasts Using the NASA GEOS Model

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) system combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗
NASA NTRS2019

Near Real-Time Air Quality Forecasts Using the NASA GEOS Model

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) system combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗
NASA NTRS2019

Near Real-Time Global Composition Forecasts at 25km Horizontal Resolution

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) system combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗
NASA NTRS2019

GEOS-Chem and the GMAO: Reaction, Replay and Reanalysis

This presentation summarizes the evolution of chemical modeling in the GMAO, showing how the parallel tracks for mission support, using forecasts over several days, and chemistry-climate coupling, using multi-decadal simulations, are converging in the future. The presentation emphasizes the new GEOS Composition Forecasting system (GEOS CF) and its potential role in future reanalyses of NASA's EOS Aura data and the testing needed to use this in chemistry-climate simulations.

Pawson, Steven↗
NASA NTRS2019

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

The 2017 Atlantic 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 ~0.96°C above the 1901-2017 average (warmest on record): about ~0.42°C from a long-term upward trend and the rest (~80%) attributed to the Atlantic Meridional Mode (AMM). The contribution to the SST from the North Atlantic Oscillation (NAO) over the EMDR was a weak warming, while that from El Nino Southern Oscillation (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 may be key factors in driving the strong TC activity in 2017.

Lim, Young-Kwon↗
NASA NTRS2019

Long-Term Ozone Variability and Trends from Reanalyses: Can It Be Done?

Stratospheric ozone concentrations have begun to show early signs of recovery following the implementation of the Montreal Protocol and its amendments as well as in response to decreasing upper-stratospheric temperatures. Secular trends in stratospheric ozone are modulated by considerable interannual variability and systematic changes in transport patterns that are expected under increasing concentrations of greenhouse gases, especially in the lower stratosphere. These factors necessitate the continued close monitoring of stratospheric ozone in upcoming decades, with a special focus on the lower stratosphere.As highly resolved data sets combining a plethora of observations with model simulations atmospheric reanalyses are, in principle, well suited for the task. All major reanalyses generate ozone output. However, significant spurious discontinuities that arise from step changes in the observing systems prevent a straightforward analysis of ozone trends and long-term variability. Building on our recent work, in this presentation we will demonstrate that trend detection is nonetheless possible using the ozone record from NASA's MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, Version 2) reanalysis bias-corrected using a chemistry model simulation as a transfer function. Next, we will outline several strategies to reduce artificial discontinuities in the ozone record in future NASA reanalyses. This discussion will be illustrated by an example of joint assimilation of bias-corrected ozone profiles from the Microwave Limb Sounder (MLS) on the Aura satellite (2004 to present) and the Ozone Mapping Profiler Suite Limb Profiler (OMPS-LP) sensors that are expected to operate on future NOAA platforms.

Wargan, Krzysztof↗
NASA NTRS2019

Capturing Connections Between the Water, Energy, and Carbon Cycles with the NASA GEOS

Studying biosphere-atmosphere interactions is complex as water, energy and carbon cycles and their feedback processes have to be integrated. At NASA GMAO, we investigate these interactions with an Earth system model that allows us to explore and quantify relevant feedbacks associated with the exchanges of carbon, water, and energy fluxes within the atmosphere, within the land, and across the land-atmosphere interface. Current biosphere-atmosphere modeling research at GMAO includes a study to understand the relative contributions of land carbon flux variability and atmospheric dynamics to atmospheric CO2 variability in time and space. For this study, we use a unique capability of the NASA GEOS model, a "replay" mode that forces the model to reproduce the weather systems captured by the MERRA-2 reanalysis. Another study investigates the impact of imposed regional drought on land carbon fluxes and on subsequent atmospheric CO2 concentrations, thereby revealing interactions between the water and carbon cycles. Using the new coupled carbon-climate modeling capability, current GMAO efforts at subseasonal-to-seasonal forecasting are now being expanded, at least in research mode, to include forecasts of carbon and phenological state.

Lee, Eunjee↗