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David Edwards

Publications and source records attributed to David Edwards.

Toward Improving Short-Term Predictions of Fine Particulate Matter Over the United States Via Assimilation of Satellite Aerosol Optical Depth Retrievals

This study develops a new approach to improve simulations of the particulate matter of aerodynamic diameter smaller than 2.5μm (PM2.5) in the Community Multiscale Air Quality (CMAQ) model via assimilation of Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth(AOD) retrievals using the Grid point Statistical Interpolation (GSI) system. In contrast to previous studies that only consider errors due to transport, our computation of the background error covariance matrix incorporates uncertainties in anthropogenic emissions. To understand the impact of this approach, three experiments (one background and two assimilations) are performed over the contiguous United States(CONUS) from 15 July to 14 August 2014. The background CMAQ experiment significantly underestimates both the MODIS AOD and surface PM2.5levels. MODIS AOD assimilation pushes both the CMAQ AOD and surface PM2.5distributions toward the observed distributions, but CMAQ still underestimates the observations. Averaged over CONUS, the two assimilation experiments with and without including the anthropogenic emission uncertainties improve the correlation coefficient between the model and independent observations of PM2.5 by ~67% and ~48%, respectively, and reduces the mean bias by ~38% and~10%, respectively. The assimilation improves the model performance everywhere over CONUS, except the New York and Wisconsin, where CMAQ overestimates the observed PM2.5during nighttime after assimilation likely because of overcorrection of aerosol mass concentrations by the AOD assimilation. Future work should incorporate uncertainties in other processes (biomass burning and biogenic emissions, deposition, chemistry, transport, and boundary conditions) to further enhance the value of assimilating spaceborne AOD retrievals.

Assimilation↗

Advancing the Science of Both Coastal Ocean Biophysics and Atmospheric Pollution Chemistry: A Final Report to the Nasa Earth Science Division by the GEO-CAPE Team

The 2007 Decadal Survey (DS) included the recommendation for the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission to launch in 2013–2016 to advance the science of both coastal ocean biophysics and atmospheric-pollution chemistry. In 2009 the NASA Earth Science Division (ESD) initiated study activities for GEO-CAPE and 8 other near- to medium-term missions to help determine the readiness of these conceptual missions to begin the formulation phase. In FY15 the GEO-CAPE mission study team completed a white paper summarizing the results of the pre-formulation work accomplished to date: https://geo-cape.larc.nasa.gov/pdf/GEO-CAPE_2009-2015_SummativeWhitePaper.pdf The team was directed to complete a final report in FY18. This document, prepared as an addendum to the FY15 white paper, serves as the GEO-CAPE final report and focuses only on FY16-18 activities and on summarizing the final state.

Geostationary Coastal and Air Pollution Events↗

On the Feasibility of Monitoring Carbon Monoxide in the Lower Troposphere from a Constellation of Northern Hemisphere Geostationary Satellites: Global Scale Assimilation Experiments (Part II)

This paper describes the second phase of an Observing System Simulation Experiment (OSSE) that utilizes the synthetic measurements from a constellation of satellites measuring atmospheric composition from geostationary (GEO) Earth orbit presented in part I of the study. Our OSSE is focused on carbon monoxide observations over North America, East Asia and Europe where most of the anthropogenic sources are located. Here we assess the impact of a potential GEO constellation on constraining northern hemisphere (NH) carbon monoxide (CO) using data assimilation. We show how cloud cover affects the GEO constellation data density with the largest cloud cover (i.e., lowest data density) occurring during Asian summer. We compare the modeled state of the atmosphere (Control Run), before CO data assimilation, with the known 'true' state of the atmosphere (Nature Run) and show that our setup provides realistic atmospheric CO fields and emission budgets. Overall, the Control Run underestimates CO concentrations in the northern hemisphere, especially in areas close to CO sources. Assimilation experiments show that constraining CO close to the main anthropogenic sources significantly reduces errors in NH CO compared to the Control Run. We assess the changes in error reduction when only single satellite instruments are available as compared to the full constellation. We find large differences in how measurements for each continental scale observation system affect the hemispherical improvement in long-range transport patterns, especially due to seasonal cloud cover. A GEO constellation will provide the most efficient constraint on NH CO during winter when CO lifetime is longer and increments from data assimilation associated with source regions are advected further around the globe.

Geo Stationary Constellation↗

On the Feasibility of Monitoring Carbon Monoxide in the Lower Troposphere from a Constellation of Northern Hemisphere Geostationary Satellites (PART 1)

By the end of the current decade, there are plans to deploy several geostationary Earth orbit (GEO) satellite missions for atmospheric composition over North America, East Asia and Europe with additional missions proposed. Together, these present the possibility of a constellation of geostationary platforms to achieve continuous time-resolved high-density observations over continental domains for mapping pollutant sources and variability at diurnal and local scales. In this paper, we use a novel approach to sample a very high global resolution model (GEOS-5 at 7 km horizontal resolution) to produce a dataset of synthetic carbon monoxide pollution observations representative of those potentially obtainable from a GEO satellite constellation with predicted measurement sensitivities based on current remote sensing capabilities. Part 1 of this study focuses on the production of simulated synthetic measurements for air quality OSSEs (Observing System Simulation Experiments). We simulate carbon monoxide nadir retrievals using a technique that provides realistic measurements with very low computational cost. We discuss the sampling methodology: the projection of footprints and areas of regard for geostationary geometries over each of the North America, East Asia and Europe regions; the regression method to simulate measurement sensitivity; and the measurement error simulation. A detailed analysis of the simulated observation sensitivity is performed, and limitations of the method are discussed. We also describe impacts from clouds, showing that the efficiency of an instrument making atmospheric composition measurements on a geostationary platform is dependent on the dominant weather regime over a given region and the pixel size resolution. These results demonstrate the viability of the "instrument simulator" step for an OSSE to assess the performance of a constellation of geostationary satellites for air quality measurements.

GEOS-5↗

Moon-to-Mars Planetary Construction Technology (MMPACT) Scoop, Tamp, Filter (STF) Sub-System

NASA’s Space Technology Mission Directorate “champions technologies needed to live on and explore the Moon” [1]. This includes capabilities that capitalize on existing lunar resources and carry out surface manufacturing and construction activities. The goal of the Moon-to-Mars Planetary Construction Technology (MMPACT) Project is to mature these two capabilities. The primary resource on the Moon and the primary feedstock for manufacturing and construction is regolith. In the past, astronauts launched, landed, and lived in a spacecraft. NASA envisions a future where we make living spaces on the lunar surface instead. The innovative technologies required for lunar surface construction may be something never seen before, or they may be adaptations of existing technologies. This paper summarizes recent efforts to develop and test a scoop, tamp and filter (STF) sub-system to prepare and deposit lunar regolith for a laser-based vitreous material transformation system being developed under a NASA contract by ICON, inc., which is hoped to eventually be used for automated additive construction with indigenous regolith on the Moon.

Moon↗