Extending the Atmospheric River Concept to Aerosol and Trace Gas Transports
No abstract provided
Wong, Corisa↗
Engineering topics
da Silva, Arlindo
Publications and source records attributed to da Silva, Arlindo.
The Aerosol, Clouds, Convection, and Precipitation Mission Study: Observing System Simulation Experiments for Multi-angle Polarimeters
No abstract available
Castellanos, Patricia↗
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↗
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↗
Observing System Simulation Experiment for a Multi-Angle Polarimeter
No abstract available
Castellanos, Patricia↗
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↗
Impact of Geostationary Aerosol Observations on the GEOS Aerosol Forecasting System: Preliminary Results for ABI on GOES-16
No abstract available
da Silva, Arlindo↗
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↗
Aerosol Forecasting, Reanalysis and Potential Connection to SPARTAN
No abstract available
da Silva, Arlindo↗
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↗
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↗
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↗
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↗
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↗
Comparison of GFED3, QFED2 and FEER1 Biomass Burning Emissions Datasets in a Global Model
Biomass burning contributes about 40% of the global loading of carbonaceous aerosols, significantly affecting air quality and the climate system by modulating solar radiation and cloud properties. However, fire emissions are poorly constrained in models on global and regional levels. In this study, we investigate 3 global biomass burning emission datasets in NASA GEOS5, namely: (1) GFEDv3.1 (Global Fire Emissions Database version 3.1); (2) QFEDv2.4 (Quick Fire Emissions Dataset version 2.4); (3) FEERv1 (Fire Energetics and Emissions Research version 1.0). The simulated aerosol optical depth (AOD), absorption AOD (AAOD), angstrom exponent and surface concentrations of aerosol plumes dominated by fire emissions are evaluated and compared to MODIS, OMI, AERONET, and IMPROVE data over different regions. In general, the spatial patterns of biomass burning emissions from these inventories are similar, although the strength of the emissions can be noticeably different. The emissions estimates from QFED are generally larger than those of FEER, which are in turn larger than those of GFED. AOD simulated with all these 3 databases are lower than the corresponding observations in Southern Africa and South America, two of the major biomass burning regions in the world.
biomass burning↗
Nighttime Aerosol Optical Depth Measurements Using a Ground-based Lunar Photometer
In recent years it was proposed to combine AERONET network photometer capabilities with a high precision lunar model used for satellite calibration to retrieve columnar nighttime AODs. The USGS lunar model can continuously provide pre-atmosphere high precision lunar irradiance determinations for multiple wavelengths at ground sensor locations. When combined with measured irradiances from a ground-based AERONET photometer, atmospheric column transmissions can determined yielding nighttime column aerosol AOD and Angstrom coefficients. Additional demonstrations have utilized this approach to further develop calibration methods and to obtain data in polar regions where extended periods of darkness occur. This new capability enables more complete studies of the diurnal behavior of aerosols, and feedback for models and satellite retrievals for the nighttime behavior of aerosols. It is anticipated that the nighttime capability of these sensors will be useful for comparisons with satellite lidars such as CALIOP and CATS in additional to ground-based lidars in MPLNET at night, when the signal-to-noise ratio is higher than daytime and more precise AOD comparisons can be made.
Berkoff, Tim↗
Exploring Dust Impacts on Tropical Systems from the NASA HS-3 Field Campaign
One of the overall scientific goals of the NASA Hurricane and Severe Storm Sentinel (HS-3) field campaign is to better understand the role of the Saharan Air Layer (SAL) in tropical storm development. During the 2012 HS-3 deployment, the Cloud Physics Lidar (CPL) observed dust within SAL air in close proximity to a developing Nadine (September 11, 2012). Throughout the mission, the NASA GEOS-5 modeling system supported HS-3 by providing 0.25 degrees resolution 5-day global forecasts of aerosols, which were used to support mission planning. The aerosol module was radiatively interactive within the GEOS-5 model, but aerosols were not directly coupled to cloud and precipitation processes. In this study we revisit the aerosol forecasts with an updated version of the GEOS-5 model. For the duration of Hurricane Nadine, we run multiday climate simulations leading up to each respective Global Hawk flight with and without aerosol direct interaction. For each set of simulations, we compare simulated dust mass fluxes to identify differences in SAL entrainment related to the interaction between dust aerosols and the atmosphere. We find that the direct effects of dust induce a low level anticyclonic circulation that temporarily shields Nadine from the intrusion of dry air, leading to a more intense storm.
hurricanes↗