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Steven Pawson

Publications and source records attributed to Steven Pawson.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Grid-Stretching Capability for the GEOS-Chem 13.0.0 Atmospheric Chemistry Model

Modeling atmospheric chemistry at fine resolution globally is computationally expensive; the capability to focus on specific geographic regions using a multi scale grid is desirable. Here, we develop, validate, and demonstrate stretched grids in the GEOS-Chem atmospheric chemistry model in its high-performance implementation (GCHP). These multiscale grids are specified at runtime by four parameters that offer users nimble control of the region that is refined and the resolution of the refinement. We validate the stretched-grid simulation versus global cubed-sphere simulations. We demonstrate the operation and flexibility of stretched-grid simulations with two case studies that compare simulated tropospheric NO2column densities from stretched-grid and cubed-sphere simulations to retrieved column densities from the TROPOspheric Monitoring Instrument (TROPOMI). The first case study uses a stretched grid with a broad refinement covering the contiguous US to produces imulated columns that perform similarly to a C180 (∼50 km) cubed-sphere simulation at less than one-ninth the computational expense. The second case study experiments with a large stretch-factor for a global stretched-grid simulation with a highly localized refinement with∼10 km resolution for California. We find that the refinement improves spatial agreement with TROPOMI columns compared to a C90 cubed-sphere simulation of comparable computational demands. Overall we find that stretched grids in GEOS-Chem are a practical tool for fine resolution regional- or continental-scale simulations of atmospheric chemistry. Stretched grids are available in GEOS-Chem version 13.0.0

GEOS-Chem↗
NASA NTRS2021

Impacts of the Eruption of Mount Pinatubo on Surface Temperatures and Precipitation Forecasts With the NASA GEOS Subseasonal-to-Seasonal System

A contemporary seasonal forecasting system is used to study the impacts of a volcanic sulfate injection into the stratosphere on the seasonal forecasts for surface temperatures, the El Niño Southern Oscillation (ENSO), and precipitation. The focus is a case study of the June 1991 eruption of Mt. Pinatubo, Philippines and the period from July 1991 to February 1992. Version 2 of the Goddard Earth Observing System (GEOS) subseasonal-to-seasonal (S2S) forecasting system is used in this study. GEOS-S2S includes the GOddard Chemistry, Aerosols, Radiation and Transport (GOCART) aerosol module, which allows to prognostically simulate aerosol distributions. GOCART is coupled to the radiation and cloud modules to include the impact of the eruption on forecasted radiation and precipitation. The coupled GEOS-S2S system was initialized in May 1991 with fields based on observations to produce ten-member 9-month forecasts with and without the volcanic sulfur injection. The results of these ensemble experiments demonstrate that including Mt. Pinatubo in seasonal forecasts would improve the forecasts of the 1991–1992 global mean temperature and precipitation but worsen the forecast of ENSO by strengthening of El Niño beyond what showed in observations. Most significant changes in the forecasts of temperatures and precipitation are limited to the tropics. The only land area where the inclusion of Pinatubo significantly lowered the forecasted precipitation is tropical Africa.

Mt. Pinatubo↗
NASA NTRS2021

Bias-Correcting Carbon Fluxes Derived From Land-Surface Satellite Data for Retrospective and Near Real-Time Assimilation Systems

The ability to monitor and understand natural and anthropogenic variability in atmospheric carbon dioxide(CO2) is a growing need of many stakeholders across the world. Systems that assimilate satellite observations, given their short latency and dense spatial coverage, into high resolution global models are valuable, if not essential, tools for addressing this need. A notable drawback of modern assimilation systems is the long latency of many vital in-put datasets, e.g., inventories, in situ measurements, and re-processed remote-sensing data can trail the current date by months to years. This paper describes techniques for bias-correcting surface fluxes derived from satellite observations of the Earth’s surface to be consistent with constraints from inventories and in situ CO2 datasets. The techniques are applicable in both short-term forecasts and retrospective simulations, thus taking advantage of the coverage and short latency of satellite data while reproducing the major features of long-term inventory and in situ records. Our approach begins with a standard collection of diagnostic fluxes which incorporate a variety of remote-sensing driver data, viz. vegetation indices, fire radiative power, and nighttime lights. We then apply an empirical sink so that global budgets of the diagnostic fluxes match given atmospheric and oceanic growth rates for each year. This step removes coherent, systematic flux errors that produce biases inCO2which mask the signals an assimilation system hopes to capture. Depending on the simulation mode, the empirical sink uses different choices of atmospheric growth rates: estimates based on observations in retrospective mode and projections based on seasonal fore-casts of sea surface temperature in forecasting mode. The retrospective fluxes, when used in simulations with NASA’s Goddard Earth Observing System (GEOS), reproduce marine boundary layer measurements with comparable skill to those using fluxes from a modern inversion system. The forecasted fluxes show promising accuracy in their application to the analysis of changes in the carbon cycle as they occur.

CO2↗
NASA NTRS2021

Description of the NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0

The Goddard Earth Observing System composition forecast (GEOS-CF) system is a high-resolution (0.25 degree) global constituent prediction system from NASA’s Global Modeling and Assimilation Office (GMAO). GEOS-CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA’s broad range of space-based and in-situ observation sand to support flight campaign planning, support of satellite observations, and air quality research. GEOS-CF expands on the GEOS weather and aerosol modeling system by introducing the GEOS-Chem chemistry module to provide analyses and 5-day forecasts of atmospheric constituents including ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), and fine particulate matter (PM2.5). The chemistry module integrated in GEOS-CF is identical to the offline GEOS-Chem model and readily benefits from the innovations provided by the GEOS-Chem community.Evaluation of GEOS-CF against satellite, ozone sonde and surface observations show realistic simulated concentrations of O3, NO2, and CO, with normalized mean biases of -0.1 to -0.3, normalized root mean square errors (NRMSE) between 0.1-0.4, and correlations between 0.3-0.8. Comparisons against surface observations highlight the successful representation of air pollutants under a variety of meteorological conditions, yet also highlight current limitations, such as an over prediction of summertime ozone over the Southeast United States. GEOS-CFv1.0 generally overestimates aerosols by 20-50% due to known issues in GEOS-Chem v12.0.1 that have been addressed in later versions.The 5-day hourly forecasts have skill scores comparable to the analysis. Model skills can be improved significantly by applying a bias-correction to the surface model output using a machine-learning approach.

GEOS-CF↗
NASA NTRS2021

Global Impact of COVID-19 Restrictions on the Atmospheric Concentrations of Nitrogen Dioxide and Ozone

Social-distancing to combat the COVID-19 pandemic has led to widespread reductions in air pollutant emissions. Quantifying these changes requires a business-as-usual counterfactual that accounts for the synoptic and seasonal variability of air pollutants. We use a machine learning algorithm driven by information from the NASA GEOS-CF model to assess changes in nitrogen dioxide (NO2) and ozone (O3) at 5,756 observation sites in countries from January through June 2020. Reductions in NO2 coincide with timing and intensity of COVID-19 restrictions, ranging from 60% in severely affected cities (e.g., Wuhan, Milan) to little change (e.g., Rio de Janeiro, Taipei). On average, NO2 concentrations were (13-23) % lower than business as usual from February 2020 onward. China experienced the earliest and steepest decline, but concentrations since April have mostly recovered and remained within 5% to the business-as-usual estimate. NO2 reductions in Europe and the US have been more gradual with a halting recovery starting in late March. We estimate that the global NOx (NO+NO2) emission reduction during the first 6 months of 2020 amounted to 3.1 (2.6-3.6) TgN, equivalent to 5.5(4.7-6.4) % of the annual anthropogenic total. The response of surface O3 is complicated by competing influences of non-linear atmospheric chemistry. While surface O3 increased by up to 50% in some locations, we find the overall net impact on daily average O3 between February -June 2020 to be small. However, our analysis indicates a flattening of the O3 diurnal cycle with an increase in nighttime ozone due to reduced titration and a decrease in daytime ozone, reflecting a reduction in photochemical production.

Christoph A Keller↗
NASA NTRS2020

The Impacts of Fossil Fuel Emission Uncertainties and Accounting for 3-D Chemical CO2 Production on Inverse Natural Carbon Flux Estimates from Satellite and In Situ Data

Atmospheric carbon dioxide (CO2) inversions for estimating natural carbon fluxes typically do not allow for adjustment of fossil fuel CO2 emissions, despite significant uncertainties in emission inventories and inadequacies in the specification of international bunker emissions in inversions. Also, most inversions place CO2 release from fossil fuel combustion and biospheric sources entirely at the surface. However, a non-negligible portion of the emissions actually occurs in the form of reduced carbon species, which are eventually oxidized to CO2 downwind. Omission of this ‘chemical pump’ can result in a significant redistribution of the inferred total carbon fluxes among regions. We assess the impacts of different prescriptions of fossil fuel emissions and accounting for the chemical pump on flux estimation, with a novel aspect of conducting both satellite CO2 observation-based and surface in situ-based inversions. We apply 3-D carbon monoxide (CO) loss rates archived from a state-of-the-art GEOS chemistry and climate model simulation in a forward transport model run to simulate the distribution of CO2 originating from oxidation of carbon species. We also subtract amounts from the prior surface CO2 fluxes that are actually emitted in the form of fossil and biospheric CO, methane, and nonmethane volatile organic compounds (VOCs). We find that the posterior large-scale fluxes are generally insensitive to the finer-scale spatial differences between the ODIAC and CDIAC fossil fuel CO2 gridded datasets and assumptions about international bunker emissions. However, accounting for 3-D chemical CO2 production and the surface correction shifts the global carbon sink, e.g., from land to ocean and from the tropics to the north, with a magnitude and even direction that depend on assumptions about the surface correction. A GOSAT satellite-based inversion is more sensitive to the chemical pump than one using in situ observations, exhibiting substantial flux impacts of 0.28, 0.53, and -0.47 Pg C yr(exp -1) over tropical land, global land, and oceans, due to differences in the horizontal and vertical sampling of the wo observation types. Overall, the biases from neglecting the chemical pump appear to be minor relative to the flux estimate uncertainties and the differences between the in situ and GOSAT inversions, but their relative importance will grow in the future as observational coverage further increases and satellite retrieval biases decrease.

James S Wang↗
NASA NTRS2020

Mechanisms Linked to Recent Ozone Decreases in the Northern Hemisphere Lower Stratosphere

Previous studies have robustly identified a decrease since 1998 in lower stratospheric (LS) 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 Modern‐Era Retrospective analysis for Research and Applications, Version 2 (MERRA‐2). 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.

Ozone↗
NASA NTRS2019

Global Assimilation of Loon Stratospheric Balloon Observations

Accurate analyses of stratospheric winds are important for determining realistic constituent transport and providing improved diagnostic studies and forecasts of the stratosphere. This study examines impacts on global meteorological analyses resulting from using winds derived from Loon superpressure balloons in the lower stratosphere (hereafter Loon winds) as additional input observations to the Goddard Earth Observing System (GEOS) data assimilation system. To fully investigate the impacts of assimilating the Loon winds, two steps are taken: (1) comparison of the GEOS analysis winds with Loon winds (Control experiment) and (2) examination of the impacts of assimilating the Loon winds into the GEOS data assimilation system (Loon experiment). The time period selected is June–August 2014 when over 150 Loon balloons were launched, mainly in the Southern Hemisphere. In the middle latitudes, the Loon winds and Control winds agree well (Loon balloon zonal wind observation minus forecast, O − F, root‐mean‐square (RMS) values of ~2.75 m/s) and assimilating the Loon winds has a small impact (O − F RMS values unchanged). In the tropics, the Loon observations and Control analysis winds differ more than in middle latitudes (zonal wind O − F RMS ~3.75 m/s) and assimilating the Loon winds improves the zonal wind O − F RMS by ~1 m/s. In selected cases where the Loon observations and Control analysis differ greatly (O − F RMS values greater than 10 m/s), assimilating Loon winds significantly decreases the zonal wind O − F RMS by 5 m/s. These decreases in O − F RMS values show that the 6‐hr forecasts are improved at the Loon balloon observation locations. While satellites routinely measure Earth's global temperatures from space, in situ wind measurements are relatively scarce, consisting mainly of a network of ground‐based weather balloons. Since only a limited number of the weather balloons even reach stratospheric altitudes, there is a need for additional stratospheric observations. One option for addition wind information is the use of experimental superpressure balloons (SPBs). SPBs can remain in the stratosphere for many months traveling with the winds and hence, by reporting their changing positions, providing in situ wind observations. These SPBs experiments are generally limited in terms of time period and number of balloons. However, over the past few years Loon has been launching hundreds of SPBs (hereafter called Loon balloons) providing a more consistent set of observations of wind in the stratosphere. Here we assimilate some of the Loon balloon winds into the NASA GEOS global data assimilation system. The data assimilation system combines all observations with an atmospheric model to produce global analysis of winds and temperatures. Results show that including the Loon balloon wind information noticeably affects the global analysis as well as forecasts with the largest impact in the tropics. These results provide direction to future model and analysis improvements.

L. Coy↗
NASA NTRS2018

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 Niño-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.

SST↗
NASA NTRS2014

Satellite Data of Atmospheric Pollution for U.S. Air Quality Applications: Examples of Applications, Summary of Data End-user Resources, Answers to Faqs, and Common Mistakes to Avoid

Satellite data of atmospheric pollutants are becoming more widely used in the decision-making and environmental management activities of public, private sector and non-profit organizations. They are employed for estimating emissions, tracking pollutant plumes, supporting air quality forecasting activities, providing evidence for "exceptional event" declarations, monitoring regional long-term trends, and evaluating air quality model output. However, many air quality managers are not taking full advantage of the data for these applications nor has the full potential of satellite data for air quality applications been realized. A key barrier is the inherent difficulties associated with accessing, processing, and properly interpreting observational data. A degree of technical skill is required on the part of the data end-user, which is often problematic for air quality agencies with limited resources. Therefore, we 1) review the primary uses of satellite data for air quality applications, 2) provide some background information on satellite capabilities for measuring pollutants, 3) discuss the many resources available to the end-user for accessing, processing, and visualizing the data, and 4) provide answers to common questions in plain language.

remote sensing↗
NASA NTRSDate not supplied

Arctic and Boreal Model Development in GMAO

Ongoing research in the GMAO seeks to improve the representation atmospheric, land, and ocean processes in the boreal Arctic and other polar regions. This talk touches on a range of topics, including improvements to sea ice and land ice representation in our subseasonal-to-seasonal prediction system and the initiation of a new collaborative effort with the Cryospheric Sciences Laboratory to develop a high resolution, polar-focused atmospheric reanalysis.

Arctic Boreal↗