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da Silva, Arlindo

Publications and source records attributed to da Silva, Arlindo.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Modeled and observed properties related to the direct aerosol radiative effect of biomass burning aerosol over the southeastern Atlantic

Biomass burning smoke is advected over the southeastern Atlantic Ocean between July and October of each year. This smoke plume overlies and mixes into a region of persistent low marine clouds. Model calculations of climate forcing by this plume vary significantly in both magnitude and sign. NASA EVS-2 (Earth Venture Suborbital-2) ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) had deployments for field campaigns off the west coast of Africa in 3 consecutive years (September 2016, August 2017, and October 2018) with the goal of better characterizing this plume as a function of the monthly evolution by measuring the parameters necessary to calculate the direct aerosol radiative effect. Here, this dataset and satellite retrievals of cloud properties are used to test the representation of the smoke plume and the underlying cloud layer in two regional models (WRF-CAM5 and CNRM-ALADIN) and two global models (GEOS and UM-UKCA). The focus is on the comparisons of those aerosol and cloud properties that are the primary determinants of the direct aerosol radiative effect and on the vertical distribution of the plume and its properties. The representativeness of the observations to monthly averages are tested for each field campaign, with the sampled mean aerosol light extinction generally found to be within 20 % of the monthly mean at plume altitudes. When compared to the observations, in all models, the simulated plume is too vertically diffuse and has smaller vertical gradients, and in two of the models (GEOS and UM-UKCA), the plume core is displaced lower than in the observations. Plume carbon monoxide, black carbon, and organic aerosol masses indicate underestimates in modeled plume concentrations, leading, in general, to underestimates in mid-visible aerosol extinction and optical depth. Biases in mid-visible single scatter albedo are both positive and negative across the models. Observed vertical gradients in single scatter albedo are not captured by the models, but the models do capture the coarse temporal evolution, correctly simulating higher values in October (2018) than in August (2017) and September (2016). Uncertainties in the measured absorption Ångstrom exponent were large but propagate into a negligible (<4 %) uncertainty in integrated solar absorption by the aerosol and, therefore, in the aerosol direct radiative effect. Model biases in cloud fraction, and, therefore, the scene albedo below the plume, vary significantly across the four models. The optical thickness of clouds is, on average, well simulated in the WRF-CAM5 and ALADIN models in the stratocumulus region and is underestimated in the GEOS model; UM-UKCA simulates cloud optical thickness that is significantly too high. Overall, the study demonstrates the utility of repeated, semi-random sampling across multiple years that can give insights into model biases and how these biases affect modeled climate forcing. The combined impact of these aerosol and cloud biases on the direct aerosol radiative effect (DARE) is estimated using a first-order approximation for a subset of five comparison grid boxes. A significant finding is that the observed grid box average aerosol and cloud properties yield a positive (warming) aerosol direct radiative effect for all five grid boxes, whereas DARE using the grid-box-averaged modeled properties ranges from much larger positive values to small, negative values. It is shown quantitatively how model biases can offset each other, so that model improvements that reduce biases in only one property (e.g., single scatter albedo but not cloud fraction) would lead to even greater biases in DARE. Across the models, biases in aerosol extinction and in cloud fraction and optical depth contribute the largest biases in DARE, with aerosol single scatter albedo also making a significant contribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Modeling the smoky troposphere of the southeast Atlantic: a comparison to ORACLES airborne observations from September of 2016

The southeast Atlantic is home to well-defined smoke outflow from Africa coinciding vertically with extensive marine boundary-layer cloud decks, both reaching their climatological maxima in spatial extent around September. A framework is put forth for evaluating the performance of a range of global and regional aerosol models against observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) airborne mission in September 2016. The sparse airborne observations are first aggregated into 2o grid boxes and into three vertical layers: the cloud-topped marine boundary layer (MBL), the layer from cloud top to 3 km, and the 3-6 km layer. Aerosol extensive properties simulated for the entire study region for all September suggest that the 2016 ORACLES observations are reasonably representative of the regional monthly average, with systematic deviations of 30% or less. All six models typically place the bottom of the smoke layer at lower altitudes than do the airborne lidar observations by 300-1400 m, whereas model aerosol top heights are within 0-500 m of the observations. All but one of the models that report carbonaceous aerosol masses underestimate the ratio of particulate extinction to the masses, a proxy for mass extinction efficiency, in 3-6 km. Notable findings on individual models include that WRF-CAM5 predicts the mass of black carbon and organic aerosols with minor (~10% or less) biases. GEOS-5 overestimates the carbonaceous particle masses in the MBL by a factor of 3-6. Extinction coefficients in the free troposphere (FT) and above-cloud aerosol optical depth (ACAOD) are 10-30% lower in WRF-CAM5, 30-50% lower in GEOS-5, 10-40% higher in GEOS-Chem, 10-20% higher in EAM-E3SM except for the practically unbiased 3-6 km extinction, and 20-70% lower in the Unified Model, than the airborne in situ, lidar and sunphotometer measurements. ALADIN-Climate also underestimates the ACAOD, by 30%. GEOS-5 and GEOS-Chem predict carbon monoxide in the MBL with small (10% or less) negative biases, despite their overestimates of carbonaceous aerosol masses. Overall, this study highlights a new approach to utilizing airborne aerosol measurements for model diagnosis.

Shinozuka, Yohei↗
NASA NTRS2020

Aerosol Retrievals from Different Polarimeters During the ACEPOL Campaign Using a Common Retrieval Algorithm

In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON – the Netherlands Institute for Space Research. The campaign took place in October–November 2017 over the western part of the United States. During ACEPOL six different instruments were deployed on the NASA ER-2 high-altitude aircraft, including four multi-angle polarimeters (MAPs): SPEX airborne, the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI), and the Research Scanning Polarimeter (RSP). Also, two lidars participated: the High Spectral Resolution Lidar-2 (HSRL-2) and the Cloud Physics Lidar (CPL). Flights were conducted mainly for scenes with low aerosol load over land, but some cases with higher AOD were also observed. We perform aerosol retrievals from SPEX airborne, RSP (410–865 nm range only), and AirMSPI using the SRON aerosol retrieval algorithm and compare the results against AERONET (AErosol RObotic NETwork) and HSRL-2 measurements (for SPEX airborne and RSP). All three MAPs compare well against AERONET for the aerosol optical depth (AOD), with a mean absolute error (MAE) between 0.014 and 0.024 at 440 nm. For the fine-mode effective radius the MAE ranges between 0.021 and 0.028 µm. For the comparison with HSRL-2 we focus on a day with low AOD (0.02–0.14 at 532 nm) over the California Central Valley, Arizona, and Nevada (26 October) as well as a flight with high AOD (including measurements with AOD>1.0 at 532 nm) over a prescribed forest fire in Arizona (9 November). For the day with low AOD the MAEs in AOD (at 532 nm) with HSRL-2 are 0.014 and 0.022 for SPEX and RSP, respectively, showing the capability of MAPs to provide accurate AOD retrievals for the challenging case of low AOD over land. For the retrievals over the smoke plume a reasonable agreement in AOD between the MAPs and HSRL-2 was also found (MAE 0.088 and 0.079 for SPEX and RSP, respectively), despite the fact that the comparison is hampered by large spatial variability in AOD throughout the smoke plume. A good comparison is also found between the MAPs and HSRL-2 for the aerosol depolarization ratio (a measure of particle sphericity), with an MAE of 0.023 and 0.016 for SPEX and RSP, respectively. Finally, SPEX and RSP agree very well for the retrieved microphysical and optical properties of the smoke plume.

Fu, Guangliang↗
NASA NTRS2019

Lidar-Polarimeter Retrieval OSSEs in Support of NASA's Aerosols and Clouds-Convection-Precipitation (ACCP) Study

The 2017 Decadal Survey (DS) highlighted Earth System Science themes, science and application questions, and several high priority objectives that have led to the inclusion of Aerosols (A) and Clouds-Convection-Precipitation (CCP) as Designated Observables (DOs). On June 1, 2018, several NASA centers (GSFC, LaRC, JPL, MSFC, GRC and ARC) submitted a joint Study Plan to the NASA Earth Science Division for the Aerosol (A) and Cloud, Convection, and Precipitation (CCP) Pre-formulation Study (A-CCP). The DS and the A-CCP team recognized the science merit in combining the A and CCP DOs for both enhancing the ability to address a number of science objectives and also to provide an expanded capability to address additional objectives beyond those addressed by individual DOs.A critical element of the A-CCP observing strategy is to make extensive use of new passive and active sensors as well as of the so-called Program-of-Record (PoR), complemented by a fully integrated sub-orbital component. Central to this observing system design is the adoption of a Value Framework in which quantitative assessment of the science benefits of space-and air-borne assets is a key element. Given pre-defined A-CCP science objectives and geophysical variables with desired accuracies, A-CCP relies on a spectrum of Observing System Simulation Experiments (OSSEs) aimed at addressing pixel level retrieval uncertainties and sampling trade-offs. In this talk we will discuss a subset of Retrieval OSSEs being considered for A-CCP, namely, synergistic lidar-polarimeter retrievals of particular relevance for the A-CCP aerosol science objectives. Starting with aerosol states from the GEOS-5 Nature Run (G5NR) sampled along specific satellite orbits, we simulate polarized radiances at the desired polarimeter wavelengths with the Vector Linearized Direct Ordinate Radiative Transfer (VLIDORT) model, alongside the lidar signal for the relevant lidars with realistic error characterization. Next, inversions are performed with the Generalized Retrieval of Aerosol and Surface Properties (GRASP) system and the accuracy of the retrieved geophysical variables are assessed. In this presentation we will highlight results for key architectures being considered for A-CCP.

da Silva, Arlindo↗
NASA NTRS2019

Assimilation of Aerosol Observations in the NASA GEOS Model

In the GEOS near real-time system, as well as in MERRA-2 which is the latest reanalysis produced at NASA's Global Modeling Assimilation Office (GMAO), the assimilation of aerosol observations is performed by means of a so-called analysis splitting method. The prognostic model is based on the GEOS model radiatively coupled to GOCART aerosol module and includes assimilation of bias-corrected Aerosol Optical Depth (AOD) at 550 nm from various space-based remote sensing platforms. In line with the transition of the GEOS meteorological data assimilation system to a hybrid Ensemble-Variational formulation, we are updating the aerosol component of our assimilation system to a variational ensemble type of scheme. In this talk we will examine the impact of replacing the current analysis splitting scheme with this new approach. Starting with the assimilation of satellite based single-channel retrievals; we will discuss the impact of this aerosol data assimilation technique on the 3D aerosol distributions by means of innovation statistics and verification against independent datasets such as the Aerosol Robotic Network (AERONET) and surface PM2.5. We will also present preliminary results related to the introduction of new aerosol data types in GEOS, including multi-spectral AOD retrievals.

AERONET↗
NASA NTRS2018

Prognostic Emissions in GEOS

Prognostic emissions enable seamless applications of atmospheric chemistry and aerosol models across scales. Prognostic emissions also facilitate direct and higher order interactions and feedbacks between components in an integrated modeling system and thus enhance the model representativeness. On the other hand they also require more attention and strict validation to ensure model integrity. In this talk I will discuss recent developments related to prognostic emissions of mineral dust, primary marine aerosols and biomass burning in the NASA GEOS model and outline some of the challenges stemming from limited ability to represent subscale and stochastic processes.

Darmenov, Anton↗
NASA NTRS2017

Update on the NASA GEOS-5 Aerosol Forecasting and Data Assimilation System

GEOS-5 is the Goddard Earth Observing System model. GEOS-5 is maintained by the NASA Global Modeling and Assimilation Office. Core development is within GMAO,Goddard Atmospheric Chemistry and Dynamics Laboratory, and with external partners. Primary GEOS-5 functions: Earth system model for studying climate variability and change, provide research quality reanalyses for supporting NASA instrument teams and scientific community, provide near-real time forecasts of meteorology,aerosols, and other atmospheric constituents to support NASA airborne campaigns.

GEOS-5↗
NASA NTRS2017

GEOS-5 During ORACLES: Status Update

In this talk we summarize the GEOS-5 capabilities to be deployed during the ORACLES 2016 Campaign. We describe model configuration, data products and web services available. We also discuss the measurement and flight requirements for the GEOS-5 Team.

Cloud↗
NASA NTRS2016

CATS Aerosol Typing and Future Directions

The Cloud Aerosol Transport System (CATS), launched in January of 2015, is a lidar remote sensing instrument that will provide range-resolved profile measurements of atmospheric aerosols and clouds from the International Space Station (ISS). CATS is intended to operate on-orbit for at least six months, and up to three years. Status of CATS Level 2 and Plans for the Future:Version. 1. Aerosol Typing (ongoing): Mode 1: L1B data released later this summer; L2 data released shortly after; Identify algorithm biases (ex. striping, FOV (field of view) biases). Mode 2: Processed Released Currently working on correcting algorithm issues. Version 2 Aerosol Typing (Fall, 2016): Implementation of version 1 modifications Integrate GEOS-5 aerosols for typing guidance for non spherical aerosols. Version 3 Aerosol Typing (2017): Implementation of 1-D Var Assimilation into GEOS-5 Dynamic lidar ratio that will evolve in conjunction with simulated aerosol mixtures.

McGill, Matt↗
NASA NTRS2016

Evaluation of MERRAero (MERRA Aerosol Reanalysis)

This presentation focuses on MERRA Aerosol Reanalysis (MERRAero) which is the first aerosol reanalysis produced at GMAO. This presentation involve an overview of MERRAero. The evaluation of MERRAero absorption and the evaluation of MERRAero Surface PM 2.5 will also be discussed.

Aerosol↗
NASA NTRS2015

Using Satellite Observations to Evaluate the AeroCOM Volcanic Emissions Inventory and the Dispersal of Volcanic SO2 Clouds in MERRA

Simulation of volcanic emissions in climate models requires information that describes the eruption of the emissions into the atmosphere. While the total amount of gases and aerosols released from a volcanic eruption can be readily estimated from satellite observations, information about the source parameters, like injection altitude, eruption time and duration, is often not directly known. The AeroCOM volcanic emissions inventory provides estimates of eruption source parameters and has been used to initialize volcanic emissions in reanalysis projects, like MERRA. The AeroCOM volcanic emission inventory provides an eruptions daily SO2 flux and plume top altitude, yet an eruption can be very short lived, lasting only a few hours, and emit clouds at multiple altitudes. Case studies comparing the satellite observed dispersal of volcanic SO2 clouds to simulations in MERRA have shown mixed results. Some cases show good agreement with observations Okmok (2008), while for other eruptions the observed initial SO2 mass is half of that in the simulations, Sierra Negra (2005). In other cases, the initial SO2 amount agrees with the observations but shows very different dispersal rates, Soufriere Hills (2006). In the aviation hazards community, deriving accurate source terms is crucial for monitoring and short-term forecasting (24-h) of volcanic clouds. Back trajectory methods have been developed which use satellite observations and transport models to estimate the injection altitude, eruption time, and eruption duration of observed volcanic clouds. These methods can provide eruption timing estimates on a 2-hour temporal resolution and estimate the altitude and depth of a volcanic cloud. To better understand the differences between MERRA simulations and volcanic SO2 observations, back trajectory methods are used to estimate the source term parameters for a few volcanic eruptions and compared to their corresponding entry in the AeroCOM volcanic emission inventory. The nature of these mixed results is discussed with respect to the source term estimates.

OMI SO2↗