Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “ACI”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Strategizing emission cuts in China to mitigate short-term warming from clean air policies

Aerosol-cloud interactions remain one of the largest sources of uncertainty in estimates of anthropogenic climate forcing. Reducing aerosols to achieve air quality improvement and climate goals can cause unintended warming due to the weakening of aerosol cooling. Here we investigate the climate impacts of spatially optimized sulfur dioxide (SO 2 ) emission reduction under a carbon-neutral pathway in China. We find that targeting reduction in highly polluted regions in China significantly suppresses the rise in effective radiative forcing due to aerosol-cloud interactions (ERF aci ) during 2020–2060. Owing to the nonlinear aerosol-cloud interaction, the optimized emission reduction strategy limits the regional average increase in ERF aci of more than 0.89 W m −2 to less than 0.13 W m −2 in the short-term future during 2020–2040 and weakens the ERF aci increase by two-thirds in 2060 over China. These findings demonstrate the critical role of targeted emission control in mitigating short-term climate risks while pursuing air quality goals.

Zhu, Yitong [Nanjing Univ. of Information Science ↗
DOE OSTI2021

Simulations of Multi-Mode Combustion Regimes Realizable In a Gasoline Direct Injection Engine

Lean and dilute gasoline compression ignition (GCI) operation in spark ignition (SI) engines are an attractive strategy to attain high fuel efficiency and low NOx levels. However, this combustion mode is often limited to low-load engine conditions due to the challenges associated with autoignition controllability. In order to overcome this constrain, multi-mode (MM) operating strategies, consisting of advanced compression ignition (ACI) at low load and conventional SI at high load, have been proposed. In this three-dimensional computational fluid dynamics study, the concept of multi-mode combustion using two RON98 gasoline fuel blends (Co-Optima Alkylate and E30) in a gasoline direct injection (GDI) engine were explored. To this end, a new reduced mechanism for simulating the kinetics of E30 fuel blend is introduced in this study. To cover the varying engine load demands for multi-mode engines, primary combustion dynamics observed in ACI and SI combustion modes was characterized and validated against experimental measurements. In order to implement part-load conditions, a strategy of mode transition between SI and ACI combustion (i.e., mixed-mode combustion) was then explored numerically by creating a virtual test condition. The results obtained from the mixed-mode simulations highlight an important feature that deflagrative flame propagation regime coexists with ignition-assisted end-gas autoignition. This study also identifies a role of turbulent flow property adjacent to premixed flame front in characterizing the mixed-mode combustion. The employed hybrid combustion model was verified to perform simulations aiming at suitable range of multi-mode engine operations.

Kim, Sayop↗
DOE OSTI2021

Facilitating better and faster simulations of aerosol-cloud interactions in Earth system models

Focal Area(s): 1. Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising a hierarchy of models. 2. Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: One major challenge that Earth system models (ESMs) face in providing credible prediction of the Earth system and its water cycle characteristics (e.g., mean state, variability, and extreme events) is to accurately simulate aerosol-cloud interactions (ACI). The physical, chemical, and dynamical processes affecting ACI are extremely complex and they range from nanoscale to planetary scale. In each model development cycle, scientists spend significant efforts investigating model deficiencies and uncertainties associated with aerosols (e.g., emissions, chemical processes, aerosol microphysics, and transport) and clouds (e.g., macrophysics, microphysics, turbulence, and large-scale circulation) in order to develop improved treatments. However, despite decades of active research, ACI is still a major source of uncertainty in climate projections, even though great progress has been made. Specific scientific challenges include: (i) Parameterizations are developed based on limited data; (ii) The complexity of a parameterization required for accurate predictions is not understood; (iii) Incomplete and unknown physics leads to errors in the fully coupled Earth system; and (iv) Complex physics is computationally too expensive to employ in ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Baselining the Indirect Effect by Improving Quantification of Sea Spray and Marine Sources at Ascension Island (Final Report)

Oceans cover two-thirds of the Earth and understanding the interactions of aerosols with clouds in these large marine regions requires quantifying the man-made contributions to the budget of cloud-drop forming particles (known as cloud condensation nuclei, or CCN) relative to the non-manmade “baseline” conditions and understanding the meteorology of boundary layer clouds. Modeling studies have shown substantial uncertainties and sensitivities to natural marine CCN sources, meaning that to reduce uncertainties in indirect effects we must be able to better quantify the CCN budget in ocean regions. While models provide important constraints on these uncertainties, actually reducing uncertainties requires substantial observations in open-ocean and coastal regions in order to establish the baseline on which manmade emissions are added. The tropical South Atlantic Ocean is one of the least-sampled regions of the planet, making the comprehensive measurements of the Department of Energy Atmospheric Radiation Measurement Layered Atlantic Smoke Interactions with Clouds (LASIC) campaign provides the longest record of aerosol size distribution measurements from a differential mobility analyzer in a cloud-influenced marine location in the ARM database, with 17 months of ground-based aerosol size distribution measurements. This project addressed the research topic of Aerosol-Cloud Interactions (ACI) by supporting three publications from the LASIC measurements: 1. The ARM measurements were combined with a new value-added technique that was pioneered by the Russell group for quantifying sea salt. This quantification of sea salt uses supermicron scattering measurements for retrieving reasonable sea spray mass concentrations, providing the best-available, observationally-constrained estimate of the sea spray mode properties when supermicron size distribution measurements are not available. 2. The fitted modes of the distribution were used to investigate the signatures of cloud processing for very clean to very smoky aerosol conditions, revealing not only differences in the particles that activate in clouds but also in the mechanisms that control that droplet formation process. In clean air, the size required to form a cloud droplet is influenced by the number of particles, as well as how quickly particles take up water during growth in cloud. 3. Building on this aerosol characterization, cloud and meteorological conditions were used to evaluate aerosol-related changes in cloud albedo and optical depth. We introduced a new method of decomposing the impact of aerosols on clouds known as the Twomey effect by incorporating retrieved supersaturation from two independent sets of observations to constrain the feedback of aerosol particles on cloud properties. The method quantifies the reduction of the Twomey effect at high aerosol concentrations, which has never been explained quantitatively by observations. In addition, the results provide the first direct validation for the conditions observed in the tropical South Atlantic of a parcel-based approach that is embedded in many climate models. Together these findings illustrate how ARM extended field campaigns in stratocumulus-covered regions can be used to constrain ACI processes with direct observations, providing specific radiative effects without models. By making such process-specific constraints available to improve ACI in global climate models, ARM observations play a key role in supporting model development.

58 GEOSCIENCES↗
DOE OSTI2020

Reducing uncertainties in satellite estimates of aerosol–cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observations

Satellite quantification of aerosol effects on clouds relies on aerosol optical depth (AOD) as a proxy for aerosol concentration or cloud condensation nuclei (CCN). However, the lack of error characterization of satellite-based results hampers their use for the evaluation and improvement of global climate models. We show that the use of AOD for assessing aerosol–cloud interactions (ACIs) is inadequate over vast oceanic areas in the subtropics. Instead, we postulate that a more physical approach that consists of matching vertically resolved aerosol data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite at the cloud-layer height with Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua cloud retrievals reduces uncertainties in satellite-based ACI estimates. Combined aerosol extinction coefficients (σ) below cloud top (σBC) from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and cloud droplet number concentrations (N d ) from MODIS Aqua yield high correlations across a broad range of σBC values, with σBC quartile correlations ≥0.78. In contrast, CALIOP-based AOD yields correlations with MODIS Nd of 0.54–0.62 for the two lower AOD quartiles. Moreover, σBC explains 41% of the spatial variance in MODIS N d , whereas AOD only explains 17%, primarily caused by the lack of spatial covariability in the eastern Pacific. Compared with σBC, near-surface σ weakly correlates in space with MODIS N d , accounting for a 16% variance. It is concluded that the linear regression calculated from ln(N d )–ln(σBC) (the standard method for quantifying ACIs) is more physically meaningful than that derived from the Nd–AOD pair.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Opportunistic experiments to constrain aerosol effective radiative forcing

Aerosol–cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide “opportunistic experiments” (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Aircraft in-situ measurements from SOCRATES constrain the anthropogenic perturbations of cloud droplet number

Aerosol-cloud interactions (ACI) in warm clouds alter reflected shortwave radiation by influencing cloud microphysical and macrophysical properties. The variable of state controlling ACI is the cloud droplet number concentration (N d ). Here, we examine the perturbations in N d due to anthropogenic aerosols (ΔN d, PD-PI ) using a perturbed parameter ensemble (PPE) hosted in the sixth Community Atmosphere Model (CAM6). Surrogate models are created for the CAM6 PPE outputs and are used to generate 1 million model variants of CAM6 by sampling 45 sources of parameter uncertainty. The range of uncertain physical parameters related to ACI are constrained with observations of aerosol and cloud properties from SOCRATES. The likely range of uncertain parameters and the associated range of ΔN d, PD-PI are more strongly constrained with observations of N d relative to observations of cloud condensation nuclei. We conduct sensitivity tests of how constraints on ΔN d, PD-PI are affected by systematic uncertainties in observations and our limitations in our surrogate models created for CAM6 PPE outputs. Based on this, we provide guidance on the impact of reducing systematic uncertainty in airborne microphysical observations and in surrogate models.

Song, Ci [Univ. of Wyoming, Laramie, WY (United St↗
DOE OSTI2025

Constraining aerosol–cloud adjustments by uniting surface observations with a perturbed parameter ensemble

Abstract. Aerosol–cloud interactions (ACIs) are the largest source of uncertainty in inferring the magnitude of future warming consistent with the observational record. The effective radiative forcing due to ACI (ERFaci) is dominated by liquid clouds and is composed of two terms: the change in cloud albedo due to redistributing liquid over a larger number of cloud droplets (Nd) and the change in cloud macrophysical properties due to changes in cloud microphysics. These terms are, respectively, referred to as the radiative forcing due to ACI (RFaci) and aerosol–cloud adjustments. While the magnitude of RFaci is uncertain, its sign is confidently negative and results in a cooling in the historical record. In contrast, the adjustment of cloud liquid water path (LWP) to enhanced Nd and associated radiative forcing is uncertain in sign. Increased LWP in response to increased Nd is consistent with precipitation suppression, while decreased LWP in response to increased Nd is consistent with enhanced evaporation from cloud top. Observational constraints of these processes are poor in part because of causal ambiguity in the relationship between Nd and LWP. To better understand this relationship, precipitation (P), Nd, and LWP surface observations from the Eastern North Atlantic (ENA) atmospheric observatory are combined with the output from a perturbed parameter ensemble (PPE) hosted in the Community Atmosphere Model version 6 (CAM6). This allows for causal interpretation of observed covariability. Observations of precipitation and cloud from ENA constrain the range of possible LWP aerosol–cloud adjustments relative to the prior from the PPE by 15 %, resulting in a global value that is confidently positive (a historical cooling) ranging from 2.1 to 6.9 g m−2. It is found that observed covariability between Nd and LWP is dominated by coalescence scavenging and that this observed covariability is not strongly related to aerosol–cloud adjustments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Cloud condensation nuclei concentrations derived from the CAMS reanalysis

Determining number concentrations of cloud condensation nuclei (CCN) is one of the first steps in the chain in analysis of cloud droplet formation, the direct microphysical link between aerosols and cloud droplets, and a process key for aerosol–cloud interactions (ACI). However, due to sparse coverage of in situ measurements and difficulties associated with retrievals from satellites, a global exploration of their magnitude, source as well as temporal and spatial distribution cannot be easily obtained. Thus, a better representation of CCN numbers is one of the goals for quantifying ACI processes and achieving uncertainty-reduced estimates of their associated radiative forcing. Here, we introduce a new CCN dataset which is derived based on aerosol mass mixing ratios from the latest Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA) in a diagnostic model that uses CAMSRA aerosol properties and a simplified kappa-Köhler framework suitable for global models. The emitted aerosols in CAMSRA are not only based on input from emission inventories using aerosol observations, they also have a strong tie to satellite-retrieved aerosol optical depth (AOD) as this is assimilated as a constraining factor in the reanalysis. Furthermore, the reanalysis interpolates for cases of poor or missing retrievals and thus allows for a full spatiotemporal quantification of CCN numbers. The derived CCN dataset captures the general trend and spatial and temporal distribution of total CCN number concentrations and CCN from different aerosol species. A brief evaluation with ground-based in situ measurements demonstrates the improvement of the modelled CCN over the sole use of AOD as a proxy for CCN as the overall correlation coefficient improved from 0.37 to 0.71. However, we find the modelled CCN from CAMSRA to be generally high biased and find a particular erroneous overestimation at one heavily polluted site which emphasises the need for further validation. The CCN dataset (https://doi.org/10.26050/WDCC/QUAERERE_CCNCAMS_v1, Block, 2023), which is now freely available to users, features 3-D CCN number concentrations of global coverage for various supersaturations and aerosol species covering the years 2003–2021 with daily frequency. This dataset is one of its kind as it offers lots of opportunities to be used for evaluation in models and in ACI studies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Ion Transmission to the Focal Plane of the Chandra X-Ray Observatory

The severe degradation in spectrometric performance observed by the AXAF CCD Imaging Spectrometer (ACIS) instrument on-board the Chandra X-ray Observatory (CXO) was associated with a sharp increase in charge transfer inefficiency combined with relatively constant dark current. It was also observed that damage occurred only during passage through the earth's radiation belts, and only when ACIS remained in the focal plane during the passage. Subsequent measurements and analyses support the conjecture that the damaging radiation entered through the Observatory's High-Resolution Mirror Assembly (HRMA) aperture. A mechanism whereby low energy magnetospheric protons and/or heavier ions are scattered through the HRMA and reach the focal plane with just enough energy to stop in the CCD's charge transfer region currently provides a reasonably consistent explanation of all observed phenomena. In this paper, we will describe analyses which support this conclusion. Simulations using standard ion transmission codes were used to generate a bi-directional response function (BDRF) for the mirror surfaces and transmission through the various path elements. The BDRF was convolved with the geometry via ray-trace. Damage estimates using measured proton fluence and ground measurements of ACIS- type CCD damage vs. proton energy will be presented and compared with observed on- orbit damage.

Kolodziejczak, J. J.↗
NASA NTRS2003

The Chandra X-Ray Observatory Radiation Environment Model

CRMFLX (Chandra Radiation Model of ion FluX) is an environmental risk mitigation tool for use as a decision aid in planning the operations times for Chandra's Advanced CCD Imaging Spectrometer (ACIS) detector. The accurate prediction of the proton flux environment with energies of 100 - 200 keV is needed in order to protect the ACIS detector against proton degradation. Unfortunately, protons of this energy are abundant in the region of space Chandra must operate, and the on-board Electron, Proton, and Helium Instrument (EPHIN) does not measure proton flux levels of the required energy range. In addition to the concerns arising from the radiation belts, substorm injections of plasma from the magnetotail may increase the protons flux by orders of magnitude in this energy range. The Earth's magnetosphere is a dynamic entity, with the size and location of the magnetopause driven by the highly variable solar wind parameters (number density, velocity, and magnetic field components). Operational times for the telescope must be made weeks in advance, decisions which are complicated by the variability of the environment. CRMFLX is an engineering model developed to address these problems and provides proton flux and fluence statistics for the terrestrial outer magnetosphere, magnetosheath, and solar wind for use in scheduling ACIS operations. CRMFLX implements a number of standard models to predict the bow shock, magnetopause, and plasma sheet boundaries based on the sampling of historical solar wind data sets. Measurements from the GEOTAIL and POLAR spacecraft are used to create the proton flux database. This paper describes the recently released CRMFLX v2 implementation that includes an algorithm that propagates flux from an observation location to other regions of the magnetosphere based on convective ExB and VB-curvature particle drift motions in electric and magnetic fields. This technique has the advantage of more completely filling out the database and makes maximum use of limited data obtained during high Kp periods or in areas of the magnetosphere with poor satellite coverage.

Blackwell, W. C.↗
NASA NTRS2004

Chandra X-ray Observations of Jovian Low-latitude Emissions: Morphological, Temporal, and Spectral Characteristics

Chandra observed X-rays from Jupiter during 24-26 February 2003 for about 40 hours with the ACIS-S and HRC-I instruments. The analysis of Jovian low-latitude "disk" Xray emissions are presented and compared with the high-latitude "auroral" emissions. We report the first Chandra ACIS-S measured X-ray spectrum (0.3-2 keV) of Jupiter's low-latitude disk The disk X-ray emission is harder and extends to higher energies than the auroral spectrum. The temporal variation in the Jovian disk X-rays is on an average consistent with those in the solar X-rays observed by GOES, and TIMED/SSE. Contrary to the auroral X-rays, the disk emissions are uniformly distributed over Jupiter; no indication of longitudinal dependence or correlation with surface magneh field strength is visible. Also, unlike the approx. 40 +/- 20 min periodic oscillations seen in the auroral X-ray emissions, the disk emissions do not show any periodic oscillations. The disk spectrum seems to be consistent with resonant and fluorescent scattering of solar X-rays by the Jovian upper atmosphere. Jupiter's disk is found to be about 50% dimmer in soft X-rays in February 2003 compared that in December 2000, which is consistent with the decrease in solar activity. No evidence of lightning-induced X-rays is seen in the Chandra X-ray data. The Jovian disk spectra observed with Chandra-ACIS is stronger than that observed with XMM-Newton two months later during April 28-29, 2003. The XMM-Newton Xray image of Jupiter shows evidence of limb darkening on the anti-sunward side as seen from Earth, as well as an asymmetry with respect to the subsolar point: suggesting a solar driven process.

Bhardwaj, Anil↗
NASA NTRS2007

X-Ray Dust Scattering At Small Angles: The Complete Halo Around GX13+1

The exquisite angular resolution available with Chandra should allow precision measurements of faint diffuse emission surrounding bright sources, such as the X-ray scattering halos created by interstellar dust. However, the ACIS CCDs suffer from pileup when observing bright sources, and this creates difficulties when trying to extract the scattered halo near the source. The initial study of the X-ray halo around GX13+1 using only the ACIS-I detector done by Smith, Edgar & Shafer (2002) suffered from a lack of sensitivity within 50" of the source, limiting what conclusions could be drawn. To address this problem, observations of GX13+1 were obtained with the Chandra HRC-I and simultaneously with the RXTE PCA. Combined with the existing ACIS-I data, this allowed measurements of the X-ray halo between 2-1000". After considering a range of dust models, each assumed to be smoothly distributed with or without a dense cloud along the line of sight, the results show that there is no evidence in this data for a dense cloud near the source, as suggested by Xiang et al. (2005). In addition, although no model leads to formally acceptable results, the Weingartner & Draine (2001) and all but one of the composite grain models from Zubko, Dwek & Arendt (2004) give particularly poor fits.

Smith, Randall K.↗
NASA NTRS2012

Real Time Space Weather Support for Chandra X-ray Observatory Operations

NASA launched the Chandra X-ray Observatory in July 1999. Soon after first light in August 1999, however, degradation in the energy resolution and charge transfer efficiency of the Advanced CCD Imaging Spectrometer (ACIS) x-ray detectors was observed. The source of the degradation was quickly identified as radiation damage in the charge-transfer channel of the front-illuminated CCDs, by weakly penetrating ("soft", 100-500 keV) protons as Chandra passed through the Earth s radiation belts and ring currents. As soft protons were not considered a risk to spacecraft health before launch, the only on-board radiation monitoring system is the Electron, Proton, and Helium Instrument (EPHIN) which was included on Chandra with the primary purpose of monitoring energetic solar particle events. Further damage to the ACIS detector has been successfully mitigated through a combination of careful mission planning, autonomous on-board radiation protection, and manual intervention based upon real-time monitoring of the soft-proton environment. The AE-8 and AP-8 trapped radiation models and Chandra Radiation Models are used to schedule science operations in regions of low proton flux. EPHIN has been used as the primary autonomous in-situ radiation trigger; but, it is not sensitive to the soft protons that damage the front-illuminated CCDs. Monitoring of near-real-time space weather data sources provides critical information on the proton environment outside the Earth's magnetosphere due to solar proton events and other phenomena. The operations team uses data from the Geostationary Operational Environmental Satellites (GOES) to provide near-real-time monitoring of the proton environment; however, these data do not give a representative measure of the soft-proton (less than 1 MeV) flux in Chandra s high elliptical orbit. The only source of relevant measurements of sub-MeV protons is the Electron, Proton, and Alpha Monitor (EPAM) aboard the Advanced Composition Explorer (ACE) satellite at L1, with real-time data provided by NOAA's Space Weather Prediction Center. This presentation will discuss radiation mitigation against proton damage, including models and real-time data sources used to protect the ACIS detector system.

O'Dell, Stephen L.↗
NASA NTRS2013

Modeling Contamination Migration on the Chandra X-ray Observatory - II

During its first 14 years of operation, the cold (about -60C) optical blocking filter of the Advanced CCD Imaging Spectrometer (ACIS), aboard the Chandra X-ray Observatory, has accumulated a growing layer of molecular contamination that attenuates low-energy x rays. Over the past few years, the accumulation rate, spatial distribution, and composition have changed. This evolution has motivated further analysis of contamination migration within and near the ACIS cavity. To this end, the current study employs a higher-fidelity geometric model of the ACIS cavity, detailed thermal modeling based upon temperature data, and a refined model of the molecular transport.

O'Dell, Stephen L.↗
NASA NTRS2016

How We Can Constrain Aerosol Type Globally

In addition to aerosol number concentration, aerosol size and composition are essential attributes needed to adequately represent aerosol-cloud interactions (ACI) in models. As the nature of ACI varies enormously with environmental conditions, global-scale constraints on particle properties are indicated. And although advanced satellite remote-sensing instruments can provide categorical aerosol-type classification globally, detailed particle microphysical properties are unobtainable from space with currently available or planned technologies. For the foreseeable future, only in situ measurements can constrain particle properties at the level-of-detail required for ACI, as well as to reduce uncertainties in regional-to-global-scale direct aerosol radiative forcing (DARF). The limitation of in situ measurements for this application is sampling. However, there is a simplifying factor: for a given aerosol source, in a given season, particle microphysical properties tend to be repeatable, even if the amount varies from day-to-day and year-to-year, because the physical nature of the particles is determined primarily by the regional environment. So, if the PDFs of particle properties from major aerosol sources can be adequately characterized, they can be used to add the missing microphysical detail the better sampled satellite aerosol-type maps. This calls for Systematic Aircraft Measurements to Characterize Aerosol Air Masses (SAM-CAAM). We are defining a relatively modest and readily deployable, operational aircraft payload capable of measuring key aerosol absorption, scattering, and chemical properties in situ, and a program for characterizing statistically these properties for the major aerosol air mass types, at a level-of-detail unobtainable from space. It is aimed at: (1) enhancing satellite aerosol-type retrieval products with better aerosol climatology assumptions, and (2) improving the translation between satellite-retrieved aerosol optical properties and species-specific aerosol mass and size that are tracked in aerosol transport and climate models used to assess aerosol forcing and its anthropogenic components. This presentation will summarize where we stand on the development of the SAM-CAAM concept.

DARF↗
NASA NTRS2017

Modeling Contamination Migration on the Chandra X-Ray Observatory - IV

During its first 18 years of operation, the cold (about -60degC) optical blocking filters of the Advanced CCD Imaging Spectrometer (ACIS), aboard the Chandra X-ray Observatory, has accumulated a growing layer of molecular contamination, which attenuates low-energy x rays. Over the past several years, the accumulation rate, spatial distribution, and composition have changed. This evolution has motivated further analysis of contamination migration within and near the ACIS cavity, in part to evaluate potential bake-out scenarios intended to reduce the level of contamination. This paper, the fourth on this topic, reports the results of recent contamination-migration simulations and their relevance to a decision whether to bake-out the ACIS instrument.

X-ray astronomy CCDs↗
NASA NTRS2022

Opportunistic Experiments to Constrain Aerosol Effective Radiative Forcing

Aerosol-cloud interactions (ACI) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The non-linearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well defined sources provide ‘opportunistic experiments’ (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatio-temporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors.We review the different experimental conditions and conduct a synthesis of the available satellite data sets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.

Matthew W Christensen↗