Supplemental Documentation for GEOS Aerosol Products
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Allison Collow↗
Engineering topics
Arlindo M Da Silva
Publications and source records attributed to Arlindo M Da Silva.
Analysis of the MODIS Above-Cloud Aerosol Retrieval Algorithm Using MCARS
The Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS) presently produces synthetic radiance data from Goddard Earth Observing System version 5 (GEOS-5) model output as if the Moderate Resolution Imaging Spectroradiometer (MODIS) was viewing a combination of atmospheric column inclusive of clouds, aerosols and a variety of gases and land/ocean surface at a specific location. In this paper we use MCARS to study the MODIS Above-Cloud AEROsol retrieval algorithm (MOD06ACAERO). MOD06ACAERO is presently a regional research algorithm able to retrieve aerosol optical thickness over clouds, in particular absorbing biomass burning aerosols overlying marine boundary layer clouds in the Southeastern Atlantic Ocean. The algorithm’s ability to provide aerosol information in cloudy conditions makes it a valuable source of information for modeling and climate studies n an area where current clear sky-only operational MODIS aerosol retrievals effectively have a data gap between the months of June and October. We use MCARS for a verification and closure study of the MOD06ACAERO algorithm. The purpose of this study is to develop a set of constraints a model developer might use during assimilation of MOD06ACAERO data. Our simulations indicate that the MOD06ACAERO algorithm performs well for marine boundary layer clouds in the SE Atlantic provided some specific screening rules are observed. For the present study, a combination of five simulated MODIS data granules was used for a dataset of 13.5 million samples with known input conditions. When pixel retrieval uncertainty was less than 30%, optical thickness of the underlying cloud layer was greater than 4 and scattering angle range within the cloud bow was excluded, MOD06ACAERO retrievals agreed with the underlying ground truth (GEOS-5 cloud and aerosol profiles used to generate the synthetic radiances) with a slope of 0.913, offset of 0.06, and RMSE=0.107. When only near-nadir pixels were considered (view zenith angle within +/-20 degrees) the agreement with source data further improved (0.977, 0.051 and 0.096 respectively). Algorithm closure was examined using a single case out of the five 38 used for verification. For closure, the MOD06ACAERO code was modified to use GEOS-5 temperature and moisture profiles as ancillary. Agreement of MOD06ACAERO retrievals with source data for the closure study had a slope of 0.996 with offset -0.007 and RMSE of 0.097 at pixel uncertainty level of less than 40%, illustrating the benefits of high-quality ancillary atmospheric data for such retrievals.
MODIS↗
Evaluation and Intercomparison of Wildfire Smoke Forecasts from Multiple Modeling Systems for the 2019 Williams Flats Fire
Wildfire smoke is one of the most significant concerns of human and environmental health, associated with its substantial impacts on air quality, weather, and climate. However, biomass burning emissions and smoke remain among the largest sources of uncertainties in air quality forecasts. In this study, we evaluate the smoke emissions and plume forecasts from 12 state-of-the-art air quality forecasting systems during the Williams Flats fire in Washington State, US, August 2019, which was intensively observed during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign. Model forecasts with lead times within 1 d are intercompared under the same framework based on observations from multiple platforms to reveal their performance regarding fire emissions, aerosol optical depth (AOD), surface PM2.5, plume injection, and surface PM2.5 to AOD ratio. The comparison of smoke organic carbon (OC) emissions suggests a large range of daily totals among the models, with a factor of 20 to 50. Limited representations of the diurnal patterns and day-to-day variations of emissions highlight the need to incorporate new methodologies to predict the temporal evolution and reduce uncertainty of smoke emission estimates. The evaluation of smoke AOD (sAOD) forecasts suggests overall underpredictions in both the magnitude and smoke plume area for nearly all models, although the high-resolution models have a better representation of the fine-scale structures of smoke plumes. The models driven by fire radiative power (FRP)-based fire emissions or assimilating satellite AOD data generally outperform the others. Additionally, limitations of the persistence assumption used when predicting smoke emissions are revealed by substantial underpredictions of sAOD on 8 August 2019, mainly over the transported smoke plumes, owing to the underestimated emissions on 7 August. In contrast, the surface smoke PM2.5 (sPM2.5) forecasts show both positive and negative overall biases for these models, with most members presenting more considerable diurnal variations of sPM2.5. Overpredictions of sPM2.5 are found for the models driven by FRP-based emissions during nighttime, suggesting the necessity to improve vertical emission allocation within and above the planetary boundary layer (PBL). Smoke injection heights are further evaluated using the NASA Langley Research Center's Differential Absorption High Spectral Resolution Lidar (DIAL-HSRL) data collected during the flight observations. As the fire became stronger over 3–8 August, the plume height became deeper, with a day-to-day range of about 2–9 km a.g.l. However, narrower ranges are found for all models, with a tendency of overpredicting the plume heights for the shallower injection transects and underpredicting for the days showing deeper injections. The misrepresented plume injection heights lead to inaccurate vertical plume allocations along the transects corresponding to transported smoke that is 1 d old. Discrepancies in model performance for surface PM2.5 and AOD are further suggested by the evaluation of their ratio, which cannot be compensated for by solely adjusting the smoke emissions but are more attributable to model representations of plume injections, besides other possible factors including the evolution of PBL depths and aerosol optical property assumptions. By consolidating multiple forecast systems, these results provide strategic insight on pathways to improve smoke forecasts.
AOD↗
Detecting Nighttime Fire Combustion Phase by Hybrid Application of Visible and Infrared Radiation from Suomi NPP VIIRS
An accurate estimation of biomass burning emissions is 1 partially limited by the lack of knowledge of fire burning phase (smoldering vs. flaming). In recent years, several fire detection products have been developed to provide information of fire radiative power (FRP), location, size, and temperature of fire pixels, but no information regarding fire burning phase is retrieved. The Day-Night band (DNB) aboard Visible Infrared Imaging Radiometer Suite (VIIRS) is sensitive to visible light from flaming fires in nighttime scenes. In contrast, VIIRS 4 m moderate resolution band #13 (M13), though capable of detecting fires at all phases, has no direct sensitivity for discerning fire phase. However, the hybrid usage of VIIRS DNB and M-bands data is hampered by their different scanning technology and spatial resolution. In this study, we present a novel method to rapidly and accurately resample DNB pixel radiances to the footprint of M-band pixels, accounting for onboard detector aggregation schemes and bowtie effect removals. The visible energy fraction (VEF) is subsequently introduced as an indicator of fire burning phase VEF is calculated as the ratio of visible light power (VLP) to FRP for each fire pixel retrieved from the VIIRS 750 m active fire product. A global distribution of VEF values, and thereby the fire phase, is quantitatively obtained, showing smaller VEF values in regions with mostly smoldering wildfires, such as peatland fires in Indonesia, larger VEF values in regions with flaming wildfires over grasslands and savannas in the sub-Sahelian region, and the largest VEF values associated with gas flaring in the Middle East. Mean VEF for different land cover types or regions is highly correlated with modified combustion efficiency (MCE). These results, together with a case study of the 2018 California Camp Fire, show that the VEF has the potential to be an indicator of fire combustion phase for each fire pixel, appropriate for estimating emission factors at the satellite pixel level.
Jun Wang↗
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↗
Extreme Air Pollution Events in Hokkaido, Japan Traced Back to Early Snowmelt and Large-Scale Wildfires Over East Eurasia: Case Studies
To identify the unusual climate conditions and their connections to air pollutions in a remote area due to wildfires, we examine three anomalous large-scale wildfires in May 2003, April 2008, and July 2014 over East Eurasia, as well as how products of those wildfires reached an urban city, Sapporo, in the northern part of Japan (Hokkaido), significantly affecting the air quality. NASA's MERRA-2 (the Modern-Era Retrospective analysis for Research and Applications, Version 2) aerosol re-analysis data closely reproduced the PM2.5 variations in Sapporo for the case of smoke arrival inJuly 2014. Results show that all three cases featured unusually early snowmelt in East Eurasia, accompanied by warmer and drier surface conditions in the months leading to the fires, inducing long-lasting soil dryness and producing environmental conditions conductive to active wildfires. Due to prevailing anomalous synoptic-scale atmospheric motions, smoke from those fires eventually reached a remote area, Hokkaido, and worsened the air quality in Sapporo. In futurestudies, continuous monitoring of the timing of Eurasian snowmelt and the air quality from the source regions to remote regions, coupled with the analysis of atmospheric and surface conditions, may be essential in more accurately predicting the effects of wildfires on air quality.
MERRA-2↗
Developing and Diagnosing Climate Change Indicators of Regional Aerosol Optical Properties
Given the importance of aerosol particles to radiative transfer via aerosol-radiation interactions, a methodology for tracking and diagnosing causes of temporal changes in regional-scale aerosol populations is illustrated. The aerosol optical properties tracked include estimates of total columnar burden (aerosol optical depth, AOD), dominant size mode (Ångström exponent, AE), and relative magnitude of radiation scattering versus absorption (single scattering albedo, SSA), along with metrics of the structure of the spatial field of these properties. Over well-defined regions of North America, there are generally negative temporal trends in mean and extreme AOD, and SSA. These are consistent with lower aerosol burdens and transition towards a relatively absorbing aerosol, driven primarily by declining sulfur dioxide emissions. Conversely, more remote regions are characterized by increasing mean and extreme AOD that is attributed to increased local wildfire emissions and long-range (transcontinental) transport. Regional and national reductions in anthropogenic emissions of aerosol precursors are leading to declining spatial autocorrelation in the aerosol fields and increased importance of local anthropogenic emissions in dictating aerosol burdens. However, synoptic types associated with high aerosol burdens are intensifying (becoming more warm and humid), and thus changes in synoptic meteorology may be offsetting aerosol burden reductions associated with emissions legislation.
Ryan C Sullivan↗
AOD Distributions and Trends of Major Aerosol Species over a Selection of the World's Most Populated Cities Based on the 1st Version of NASA's MERRA Aerosol Reanalysis
NASA recently extended the Modern-Era Retrospective Analysis for Research and Application (MERRA) with an atmospheric aerosol reanalysis which includes five particulate species: sulfate, organic matter, black carbon, mineral dust and sea salt. The MERRA Aerosol Reanalysis (MERRAero) is an innovative tool to study air quality issues around the world for its global and constant coverage and its distinction of aerosol speciation expressed in the form of aerosol optical depth (AOD). The purpose of this manuscript is to apply MERRAero to the study of urban air pollution at the global scale by analyzing the AOD over a period of 13 years (2003-2015) and over a selection of 200 of the world's most populated cities in order to assess the impacts of urbanization, industrialization, air quality regulations and regional transport which affect urban aerosol load. Environmental regulations and the recent global economic recession have helped to decrease the AOD and sulfate aerosols in most cities in North America, Europe and Japan. Rapid industrialization in China over the last two decades resulted in Chinese cities having the highest AOD values in the world. China has nevertheless recently implemented emission control measures which are showing early signs of success in many cities of Southern China where AOD has decreased substantially over the last 13 years. The AOD over South American cities, which is dominated by carbonaceous aerosols, has also decreased over the last decade due to an increase in commodity prices which slowed deforestation activities in the Amazon rainforest. At the opposite, recent urbanization and industrialization in India and Bangladesh resulted in a strong increase of AOD, sulfate and carbonaceous aerosols in most cities of these two countries. The AOD over most cities in Northern Africa and Western Asia changed little over the last decade. Emissions of natural aerosols, which cities in these two regions tend to be mostly composed of, don't tend to fluctuate significantly on an annual basis.
Urban air pollution↗
Total Dust Deposition Flux During Precipitation in Toyama, Japan, in the Spring of 2009: A Sensitivity Analysis with the NASA GEOS-5 Model
We compared the observed total dust deposition fluxes during precipitation (TDP) mainly at Toyama in Japan during the period January - April 2009 with results available from four NASA GEOS-5 global model experiments. The modeled results were obtained from three previous experiments and carried out in one experiment, which were all driven by assimilated meteorology and simulating aerosol distributions for the time period. We focus mainly on the observations of two distinct TDP events, which were reported in Osada et al. (2011), at Toyama, Japan, in February (Event B) and March 2009 (Event C). Although all of our GEOS-5 simulations captured aspects of the observed TDP, we found that our low horizontal spatial resolution control experiment performed generally the worst. The other three experiments were run at a higher spatial resolution, with the first differing only in that respect from the control, the second adding imposed a prescribed corrected precipitation product, and the final experiment adding as well assimilation of aerosol optical depth based on MODIS observations. During Event C, the increased horizontal resolution could increase TDP with precipitation increase. There was no significant improvement, however, due to the imposition of the corrected precipitation product. The simulation that incorporated aerosol data assimilation performed was by far the best for this event, but even so could only reproduce less than half of the observed TDP despite the significantly increased atmospheric dust mass concentrations. All three of the high spatial resolution experiments had higher simulated precipitation at Toyama than was observed and that in the lower resolution control run. During Event B, the aerosol data assimilation run did not perform appreciably better than the other higher resolution simulations, suggesting that upstream conditions (i.e., upstream cloudiness), or vertical or horizontal misplacement of the dust plume did not allow for significant improvement in the simulated aerosol distributions. Furthermore, a detailed comparison of observed hourly precipitation and surface particulate mass concentration data suggests that the observed TDP during Event B was highly dependent on short periods of weak precipitation correlated with elevated dust surface concentrations, important details possibly not captured well in a current global model.
Dust; Wet deposition; Numerical modeling; Japan; P↗
The GOddard SnoW Impurity Module (GOSWIM) for the NASA GEOS-5 Earth System Model: Preliminary Comparisons with Observations in Sapporo, Japan
The snow darkening module evaluating dust, black carbon, and organic carbon depositions on mass and albedo has been developed for the NASA Goddard Earth Observing System, Version 5 (GEOS-5) Earth System Model, as the GOddard SnoW Impurity Module (GOSWIM). GOSWIM consists of the snow albedo scheme from a previous study (Yasunari et al. 2011) with updates and a newly developed mass concentration scheme, using aerosol depositions from the chemical transport model (GOCART) in GEOS-5. Compared to observations at Sapporo, the numerical experiments, forced by observation-based meteorology and aerosol depositions from GOES-5, better simulated the seasonal migration of snow depth, albedos, and impurities of dust, BC, and OC in the snow surface. However, the magnitude of the impurities is underestimated, compared to the sporadic snow impurity measurements. Increasing the deposition rates of dust and BC could explain the differences on the snow darkening effect between observation and simulation. Ignoring BC deposition can possibly lead to an extension of snow cover duration in Sapporo for four days. Comparing the off-line GOSWIM and the GEOS-5 global simulations, we found that determining better local precipitation and deposition rates of the aerosols are key factors in generating better GOSWIM snow darkening simulation in NASA GEOS-5.
land surface processes↗
The Aerosol Component of the ACCP Study
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David M Winker↗
Aerosols, Clouds, Convection, and Precipitation (ACCP) - Orbital Summary
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David M Winker↗
Exploring the Elevated Water Vapor Signal Associated With the Free Tropospheric Biomass Burning Plume Over the Southeast Atlantic Ocean
In southern Africa, widespread agricultural fires produce substantial biomass burning (BB) emissions over the region. The seasonal smoke plumes associated with these emissions are then advected westward over the persistent stratocumulus cloud deck in the southeast Atlantic (SEA) Ocean, resulting in aerosol effects which vary with time and location. Much work has focused on the effects of these aerosol plumes, but previous studies have also described an elevated free tropospheric water vapor signal over the SEA. Water vapor influences climate in its own right, and it is especially important to consider atmospheric water vapor when quantifying aerosol–cloud interactions and aerosol radiative effects. Here we present airborne observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign over the SEA Ocean. In observations collected from multiple independent instruments on the NASA P-3 aircraft (from near-surface to 6–7 km), we observe a strongly linear correlation between pollution indicators (carbon monoxide (CO) and aerosol loading) and atmospheric water vapor content, seen at all altitudes above the boundary layer. The focus of the current study is on the especially strong correlation observed during the ORACLES-2016 deployment (out of Walvis Bay, Namibia), but a similar relationship is also observed in the August 2017 and October 2018 ORACLES deployments. Using reanalyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and specialized WRF-Chem simulations, we trace the plume–vapor relationship to an initial humid, smoky continental source region, where it mixes with clean, dry upper tropospheric air and then is subjected to conditions of strong westward advection, namely the southern African easterly jet (AEJ-S). Our analysis indicates that air masses likely left the continent with the same relationship between water vapor and carbon monoxide as was observed by aircraft. This linear relationship developed over the continent due to daytime convection within a deep continental boundary layer (up to ∼5–6 km) and mixing with higher-altitude air, which resulted in fairly consistent vertical gradients in CO and water vapor, decreasing with altitude and varying in time, but this water vapor does not originate as a product of the BB combustion itself. Due to a combination of conditions and mixing between the smoky, moist continental boundary layer and the dry and fairly clean upper-troposphere air above (∼6 km), the smoky, humid air is transported by strong zonal winds and then advected over the SEA (to the ORACLES flight region) following largely isentropic trajectories. Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) back trajectories support this interpretation. This work thus gives insights into the conditions and processes which cause water vapor to covary with plume strength. Better understanding of this relationship, including how it varies spatially and temporally, is important to accurately quantify direct, semi-direct, and indirect aerosol effects over this region.
Kristina Pistone↗
Biomass Burning Smoke and Coincident Water Vapor Over the Southeast Atlantic Stratocumulus Region: Results from Observations and Models
In southern Africa, widespread agricultural fires produce substantial biomass burning (BB) emissions over the region. The seasonal smoke plumes associated with these emissions are then advected westward over the persistent stratocumulus cloud deck in the Southeast Atlantic (SEA) Ocean. We present airborne observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign over the SEA. Using multiple airborne datasets, we observe a strongly linear correlation between biomass burning indicators (carbon monoxide (CO) and aerosol loading) and atmospheric water vapor content, seen at all altitudes above the boundary layer. This relationship was particularly strong in the 2016 observations, but was also present in the 2017 and 2018 deployments. Using ECMWF and MERRA-2 reanalyses and specialized WRF-Chem simulations, we trace the plume-vapor relationship to an initial humid, smoky continental source region, where it mixes with clean, dry upper-tropospheric air and then is subjected to conditions of strong westward advection, namely the South African Easterly Jet (AEJ-S). Our analysis indicates that airmasses likely left the continent with the same relationship between water vapor and carbon monoxide as was observed by aircraft. This linear relationship developed over the continent due to daytime convection within a deep continental boundary layer (up to ~5-6km) and mixing with higher-altitude air, which resulted in fairly consistent vertical gradients in CO and water vapor, decreasing with altitude and varying in time, but this water vapor does not originate as a product of the BB combustion itself. The smoky, humid mixed air is then subjected to strong zonal winds and advected over the SEA following largely isentropic trajectories. HYSPLIT back trajectories support this interpretation. With better understanding of this relationship, and its spatial and temporal variations, we are working towards accurately quantifying the radiative and dynamical effects of both aerosol and water vapor over this region.
Kristina Pistone↗
AOS The Atmosphere Observing System Synergistic Aerosol, Cloud, Convection and Precipitation Measurement and Modeling Systems
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Arlindo M Da Silva↗
Towards a next generation of NASA fire information system: Harnessing the full power of NASA fire data and models
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fire emissions↗
The Tables of Aerosol Optics (TAO) Project
The Table of Aerosol Optics (TAO) project is a community repository of optics computations (extinction, absorption, single-scatter albedo, lidar ratio, etc) that are useful for global models and remote sensing applications. TAO expands upon historical efforts (e.g., Hess et al., 1998) by building an open database that uses recent measurements and new computational techniques for non-spherical particles. The ‘open’ aspect of TAO is important, since the size distributions, hygroscopicities, refractive indices, and morphological recommendations of today will undoubtedly yield to different values in the future; the open framework of TAO allows scientists to keep adding new computations to the database as the science evolves. TAO is meant to be a community repository where specialists can put their computations for other scientists to use. So for instance, some groups are advancing new techniques that can accommodate complex fractal aggregates of black carbon, other groups are working on realistic irregular shapes for mineral dust, and different groups are updating the hygroscopicity of various aerosol types using new techniques. The TAO database gives these scientists a place to distribute their products. As TAO grows, modelers and remote sensing specialists will look to TAO as a place to find a wide variety of choices for testing. Meanwhile, global modelers can also use TAO to lobby for new tables that accommodate their needs. Eventually, TAO will provide mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at popular remote sensing and global modeling wavelengths (0.25-40 µm) for all pertinent species (sulfate, sea salt, BC, OC, BrC, dust, etc.). TAO will also accept computations for aerosol ‘type’ (e.g., biomass burning, urban, background, etc.) that may include regional and seasonal variability. Multiple tables may be created for each species or type to account for the multiple valid size distributions, hygroscopicities, complex refractive indices, and shapes that can be found in the literature.
Greg Schuster↗
The Tables of Aerosol Optics (TAO) Project
The Table of Aerosol Optics (TAO) project is a community repository of optics computations (extinction, absorption, single-scatter albedo, lidar ratio, etc) that are useful for global models and remote sensing applications. TAO expands upon historical efforts (e.g., Hess et al., 1998) by building an open database that uses recent measurements and new computational techniques for non-spherical particles. The ‘open’ aspect of TAO is important, since the size distributions, hygroscopicities, refractive indices, and morphological recommendations of today will undoubtedly yield to different values in the future; the open framework of TAO allows scientists to keep adding new computations to the database as the science evolves. TAO is meant to be a community repository where specialists can put their computations for other scientists to use. So for instance, some groups are advancing new techniques that can accommodate complex fractal aggregates of black carbon, other groups are working on realistic irregular shapes for mineral dust, and different groups are updating the hygroscopicity of various aerosol types using new techniques. The TAO database gives these scientists a place to distribute their products. As TAO grows, modelers and remote sensing specialists will look to TAO as a place to find a wide variety of choices for testing. Meanwhile, global modelers can also use TAO to lobby for new tables that accommodate their needs. Eventually, TAO will provide mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at popular remote sensing and global modeling wavelengths (0.25-40 µm) for all pertinent species (sulfate, sea salt, BC, OC, BrC, dust, etc.). TAO will also accept computations for aerosol ‘type’ (e.g., biomass burning, urban, background, etc.) that may include regional and seasonal variability. Multiple tables may be created for each species or type to account for the multiple valid size distributions, hygroscopicities, complex refractive indices, and shapes that can be found in the literature.
Elisabeth Andrews↗