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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Dissipation of Mixed-Phase Arctic Clouds and Its Relationship to Aerosol Properties - Final Technical Report

The overarching objective of this project was to further our understanding of low-level Arctic cloud behavior in ultra-low aerosol concentration environments. To this end, we used a combination of modeling and analysis of DOE ARM datasets to understand the frequency of aerosol-limited cloud dissipation events, to understand the microphysical processes that lead to aerosol-limited dissipation, and to understand how above-cloud aerosol particles can work to maintain low-level clouds that exist in boundary layers with ultra-low aerosol concentrations. We found that aerosol-limited dissipation is unlikely to occur at the DOE long-term observation facilities at North Slope Alaska and Oliktok Point but possibly does occur at higher latitudes in the Arctic. At these higher latitudes, aerosol concentrations are frequently observed to be higher, often substantially higher, than in the boundary layer. These reservoirs can be sufficient to maintain low-level clouds. When they are insufficient, clouds appear to dissipate due to a depletion of liquid water through precipitation that is reinforced by a shutdown of the dynamical processes that support these clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

ARM data-oriented metrics and diagnostics package for climate model evaluation (ARM-DIAGS-V3) version 3

A Python-based metrics and diagnostics package is currently being developed by the ARM Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term high frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, precipitation, and aerosols. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison as demonstrated in Zhang et al. (2018) and Zhang et al. (2020). The mean of the CMIP model can be served as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, aerosol optical depth, and radiative fluxes, with plan to extend to more fields, such as the evaluation of model simulated aerosol physicochemical properties and cloud microphysics properties. Process-oriented diagnostics focusing on aerosol, cloud, and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. In addition to the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Tropical Western Pacific (TWP) atmospheric observatories in the ARMDIAGS version 2.0, the version 3.0 package have extended to the data collected at the ARM Eastern North Atlantic (ENA) atmospheric observatory and the Observation and Modeling of the Green Ocean Amazon (GOAMAZON) field campaign. The metrics and diagnostics package are currently built upon standard Python libraries and additional Python packages developed by DOE (CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first provide an overview of major metrics in section 2. The input data, which constitutes the core content of the metrics and diagnostics package, is summarized in section 3. A user's guide documenting the workflow/structure of the version 3.0 codes and including step-by-step instruction for running the package is described in section 4.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Boundary Layer Exploration of Aerosols and Clouds ON Ships (BEACONS)

BEACONS aims to demonstrate autonomous deployment of a shipborne system that routinely observes atmospheric, cloud, and aerosol properties. These observations enable scientists to study aerosol-cloud interactions, advancing energy resilience and the Department of Energy's mission to improve model prediction. Key Project Outcomes Autonomous deployment of aerosol and cloud measurement systems aboard a Pasha Hawaii Marjorie C commercial ship. Six-month campaign for continuous, high-resolution aerosol and cloud data collection with minimal crew intervention. Development and testing of instruments in two phases, advancing from essential to complex systems. AI-ready processed data on the BEACONS Data Platform for near-real-time data access. Validation of aerosol-cloud interaction hypotheses for improved modeling. Establishment of best practices for instrument deployment in marine environments. Scientific collaboration to support the U.S. Department of Energy (DOE) Biological and Environmental Research (BER) mission.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

Promise and Capability of NASA's Earth Observing System to Monitor Human-Induced Climate Variations

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. The Moderate Resolution Imaging Spectroradiometer (MODIS), developed as part of the Earth Observing System (EOS) and launched on Terra in December 1999 and Aqua in May 2002, is designed to meet the scientific needs for satellite remote sensing of clouds, aerosols, water vapor, and land and ocean surface properties. This sensor and multi-platform observing system is especially well suited to observing detailed interdisciplinary components of the Earth s surface and atmosphere in and around urban environments, including aerosol optical properties, cloud optical and microphysical properties of both liquid water and ice clouds, land surface reflectance, fire occurrence, and many other properties that influence the urban environment and are influenced by them. In this presentation I will summarize the current capabilities of MODIS and other EOS sensors currently in orbit to study human-induced climate variations.

King, M. D.↗
NASA NTRS2022

Seasonal Updraft Speeds Change Cloud Droplet Number Concentrations in Low Level Clouds Over the Western North Atlantic

To determine the impact of dynamic and aerosol processes on marine low clouds, we examine the seasonal impact of updraft speed w and cloud condensation nuclei concentration at 0.43 % supersaturation () on the cloud droplet number concentration (N(C)) of low-level clouds over the western North Atlantic Ocean. Aerosol and cloud properties were measured with instruments on board the NASA LaRC Falcon HU-25 during the ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment) mission in summer (August) and winter (February–March) 2020. The data are grouped into different loadings, and the density functions of NC and w near the cloud bases are compared. For low updrafts (w < 1.3 m s−1), NC in winter is mainly limited by the updraft speed and in summer additionally by aerosols. At larger updrafts (w > 3 m s−1), NC is impacted by the aerosol population, while at clean marine conditions cloud nucleation is aerosol-limited, and for high it is influenced by aerosols and updraft. The aerosol size distribution in winter shows a bimodal distribution in clean marine environments, which transforms to a unimodal distribution in high due to chemical and physical aerosol processes, whereas unimodal distributions prevail in summer, with a significant difference in their aerosol concentration and composition. The increase of is accompanied with an increase of organic aerosol and sulfate compounds in both seasons. We demonstrate that NC can be explained by cloud condensation nuclei activation through upwards processed air masses with varying fractions of activated aerosols. The activation highly depends on w and thus supersaturation between the different seasons, while the aerosol size distribution additionally affects NC within a season. Our results quantify the seasonal influence of w and on NC and can be used to improve the representation of low marine clouds in models.

Simon Kirschler↗
DOE OSTI2021

The CLoud–Aerosol–Radiation Interaction and Forcing: Year 2017 (CLARIFY-2017) measurement campaign

The representations of clouds, aerosols, and cloud–aerosol–radiation impacts remain some of the largest uncertainties in climate change, limiting our ability to accurately reconstruct past climate and predict future climate. The south-east Atlantic is a region where high atmospheric aerosol loadings and semi-permanent stratocumulus clouds are co-located, providing an optimum region for studying the full range of aerosol–radiation and aerosol–cloud interactions and their perturbations of the Earth's radiation budget. While satellite measurements have provided some useful insights into aerosol–radiation and aerosol–cloud interactions over the region, these observations do not have the spatial and temporal resolution, nor the required level of precision to allow for a process-level assessment. Detailed measurements from high spatial and temporal resolution airborne atmospheric measurements in the region are very sparse, limiting their use in assessing the performance of aerosol modelling in numerical weather prediction and climate models. CLARIFY-2017 was a major consortium programme consisting of five principal UK universities with project partners from the UK Met Office and European- and USA-based universities and research centres involved in the complementary ORACLES, LASIC, and AEROCLO-sA projects. The aims of CLARIFY-2017 were fourfold: (1) to improve the representation and reduce uncertainty in model estimates of the direct, semi-direct, and indirect radiative effect of absorbing biomass burning aerosols; (2) to improve our knowledge and representation of the processes determining stratocumulus cloud microphysical and radiative properties and their transition to cumulus regimes; (3) to challenge, validate, and improve satellite retrievals of cloud and aerosol properties and their radiative impacts; (4) to improve the impacts of aerosols in weather and climate numerical models. This paper describes the modelling and measurement strategies central to the CLARIFY-2017 deployment of the FAAM BAe146 instrumented aircraft campaign, summarizes the flight objectives and flight patterns, and highlights some key results from our initial analyses.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Aerosol Properties in Cloudy Environments from Remote Sensing Observations: A Review of the Current State of Knowledge

Aerosol properties are fundamentally different near clouds than away from clouds. This paper reviews the current state of knowledge of aerosol properties in the near-low-cloud environment and quantitatively compares them with aerosols far from clouds, according to remote sensing observations. It interprets observations of aerosol properties from different sensors using satellite, aircraft, and ground-based observations. The correlation (and anticorrelation) between proximity to cloud and aerosol properties is discussed. Retrieval artifacts in the near-cloud environment are demonstrated and quantified for different sensor attributes and environmental conditions. Finally, the paper describes the possible corrections for near-cloud enhancement in remote sensing retrievals. This study is timely in view of science definition studies for NASA’s Aerosol, Cloud, Convection and Precipitation (ACCP) mission, which will also seek to directly link aerosol properties to nearby clouds.

A. Marshak↗
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↗
NASA NTRS2018

Seasonal Predictability of Cloud Droplet Number Concentration

Aerosol emissions modify the properties of clouds hence impacting climate. The aerosol indirect effect may have offset part of the global warming caused by anthropogenic greenhouse gas emissions during the industrial era. It however remains unclear whether the same effect is significant over time scales relevant for seasonal and weather climate prediction. Answering such a question has been difficult since most weather prediction systems lack a proper representation of the aerosol evolution and transport and their interaction with clouds. Even in advanced systems it is not clear to what extent cloud microphysical properties are predictable over subseasonal to seasonal time scales. Such an issue is addressed in this study. We use a set of 30 year, four ensemble member, 9 month lead hindcast simulations of the NASA GEOS seasonal prediction system (GEOS-S2S) to study the predictability of cloud droplet number concentration in warm stratocumulus clouds. The latest version GEOS-S2S system implements interactive aerosol as well as a two moment cloud microphysics scheme therefore it is suitable for studying the aerosol indirect effect on climate. Long term retrievals from the MODIS (Moderate Resolution Imaging Spectroradiometer) are used to validate the model predictions and assess its skill in predicting cloud droplet number concentration.

Barahona, Donifan↗
DOE OSTI2024

Aerosol-induced closure of marine cloud cells: enhanced effects in the presence of precipitation

Abstract. The Weather Research Forecasting (WRF) version 4.3 model is configured within a Lagrangian framework to quantify the impact of aerosols on evolving cloud fields. Kilometer-scale simulations utilizing meteorological boundary conditions are based on 10 case study days offering diverse meteorology during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA). Measurements from aircraft, the ground-based Atmosphere Radiation Measurement (ARM) site at Graciosa Island in the Azores, and A-Train and geostationary satellites are utilized for validation, demonstrating good agreement with the WRF-simulated cloud and aerosol properties. Higher aerosol concentration leads to suppressed drizzle and increased cloud water content in all case study days. These changes lead to larger radiative cooling rates at cloud top, enhanced vertical velocity variance, and increased vertical and horizontal wind speed near the base of the lower-tropospheric inversion. As a result, marine cloud cell area expands, narrowing the gap between shallow clouds and increasing cloud optical thickness, liquid water content, and the top-of-atmosphere outgoing shortwave flux. While similar aerosol effects are observed in lightly to non-raining clouds, they tend to be smaller by comparison. These simulations show a relationship between cloud cell area expansion and the radiative adjustments caused by liquid water path and cloud fraction changes. The adjustments are positive and scale as 74 % and 51 %, respectively, relative to the Twomey effect. While higher-resolution large-eddy simulations may provide improved representation of cloud-top mixing processes, these results emphasize the importance of addressing mesoscale cloud-state transitions in the quantification of aerosol radiative forcing that cannot be attained from traditional climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TRACER-Vertical Profile of Aerosol in Convective System (TRACER-VPACS) Field Campaign Report

We investigated physicochemical properties of aerosol at different altitudes during the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility Tracking Aerosol Convection Interactions Experiment (TRACER). We used ARM’s tethered balloon system (TBS) and multi-modal offline analysis techniques available at DOE’s Environmental Molecular Sciences Laboratory (EMSL) at Pacific Northwest National Laboratory (PNNL) and at the Advanced Light Source (ALS) at the Lawrence Berkley National Laboratory (LBNL). The main scientific aim of this project was to understand the influence of the vertical profile of aerosol composition on the properties of deep convective clouds. The effect of aerosol properties on convective activity is still poorly understood and debated. For example, previous studies suggested that higher concentration of hygroscopic aerosol may lead to lower collection efficiency and eventually delay in onset of precipitation and total amount of precipitation. However, some observations suggested that increased aerosol concentration may result in vigorous convection and a higher amount of precipitation. In addition, the radiative forcing of the ambient aerosol is strongly influenced by the vertical distribution of aerosols and their chemical composition, and not well constrained in climate models. The estimation of the indirect effect of aerosol also has a significant uncertainty due to the spatial variation of the aerosol, especially at the cloud base. Detailed size-resolved chemical composition studies of aerosol and their microphysical properties, along with in situ measurements from ARM’s mobile facilities, help to improve our understanding of the role of aerosol in deep convective cloud formation over a broad range of environmental thermodynamic and aerosol conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Influence of Surface Aerosol Injection on Stratocumulus‐to‐Cumulus Transition: Cloud‐Surface Coupling and Background Aerosol Concentrations

The influence of surface aerosol injection on the stratocumulus‐to‐cumulus transition (SCT) is explored using large‐eddy simulations. We examine how cloud‐surface coupling (or the strength of the marine boundary layer (MBL) stratification that limits vertical turbulent mixing and convection) impacts the vertical transport of aerosols, and how injected aerosols influence cloud properties and associated cloud radiative effects during the SCT. By injecting aerosols at different stages of the SCT, noting that cloud is more decoupled from the surface over time due to entrainment warming, we find that cloud‐surface coupling significantly affects aerosol vertical transport. However, injection timing (before drizzle if any) does not notably affect the SCT and the efficiency of marine cloud brightening, because aerosol number concentrations due to injections at different times rapidly converge before the transition onset. By varying the background aerosol concentration, we find that injected aerosols can significantly extend the persistence of stratocumulus decks by suppressing precipitation in clean environments but have little impact on stratocumulus breakup with higher background aerosol concentrations due to saturated aerosol effects. In clean MBLs, the SCT‐delay‐induced increase in cloud fraction dominates the overall cooling effects in response to aerosols, followed by Twomey effects. These cooling effects are slightly offset by decreased liquid water path (LWP) due to entrainment drying. In polluted MBLs, the Twomey effect is more dominant, followed by cloud fraction adjustments, and these coolings are also partly offset by LWP adjustments. All the simulations are made in relatively small domains in which injected aerosols are homogenized over a short time scale.

Zhang, Haipeng [Univ. of Maryland, College Park, M↗
NASA NTRS2019

Exploring Aerosols Near Clouds With High‐Spatial‐Resolution Aircraft Remote Sensing During SEAC(4)RS

Since aerosols are important to our climate system, we seek to observe the variability of aerosol properties within cloud systems. When applied to the satellite‐borne Moderate‐resolution Imaging Spectroradiometer (MODIS), the Dark Target retrieval algorithm provides global aerosol optical depth (AOD; at 0.55 μm) in cloud‐free scenes. Since MODIS' resolution (500‐m pixels, 3‐ or 10‐km product) is too coarse for studying near‐cloud aerosol, we ported the Dark Target algorithm to the high‐resolution (~50‐m pixels) enhanced‐MODIS Airborne Simulator (eMAS), which flew on the high‐altitude ER‐2 during the Studies of Emissions, Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys Airborne Science Campaign over the United States in 2013. We find that even with aggressive cloud screening, the ~0.5‐km eMAS retrievals show enhanced AOD, especially within 6 km of a detected cloud. To determine the cause of the enhanced AOD, we analyze additional eMAS products (cloud retrievals and degraded‐resolution AOD), coregistered Cloud Physics Lidar profiles, MODIS aerosol retrievals, and ground‐based Aerosol Robotic Network observations. We also define spatial metrics to indicate local cloud distributions near each retrieval and then separate into near‐cloud and far‐from‐cloud environments. The comparisons show that low cloud masking is robust, and unscreened thin cirrus would have only a small impact on retrieved AOD. Some of the enhancement is consistent with clear‐cloud transition zone microphysics such as aerosol swelling. However, 3‐D radiation interaction between clouds and the surrounding clear air appears to be the primary cause of the high AOD near clouds.

aerosol retrieval algorithm↗
NASA NTRS2014

Retrieval, Inter-Comparison, and Validation of Above-Cloud Aerosol Optical Depth from A-train Sensors

Absorbing aerosols produced from biomass burning and dust outbreaks are often found to overlay lower level cloud decks and pose greater potentials of exerting positive radiative effects (warming) whose magnitude directly depends on the aerosol loading above cloud, optical properties of clouds and aerosols, and cloud fraction. Recent development of a 'color ratio' (CR) algorithm applied to observations made by the Aura/OMI and Aqua/MODIS constitutes a major breakthrough and has provided unprecedented maps of above-cloud aerosol optical depth (ACAOD). The CR technique employs reflectance measurements at TOA in two channels (354 and 388 nm for OMI; 470 and 860 nm for MODIS) to retrieve ACAOD in near-UV and visible regions and aerosol-corrected cloud optical depth, simultaneously. An inter-satellite comparison of ACAOD retrieved from NASA's A-train sensors reveals a good level of agreement between the passive sensors over the homogeneous cloud fields. Direct measurements of ACA such as carried out by the NASA Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) can be of immense help in validating ACA retrievals. We validate the ACA optical depth retrieved using the CR method applied to the MODIS cloudy-sky reflectance against the airborne AATS and 4STAR measurements. A thorough search of the historic AATS-4STAR database collected during different field campaigns revealed five events where biomass burning, dust, and wildfire-emitted aerosols were found to overlay lower level cloud decks observed during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS- 2013, respectively. The co-located satellite-airborne measurements revealed a good agreement (RMSE less than 0.1 for AOD at 500 nm) with most matchups falling within the estimated uncertainties in the MODIS retrievals. An extensive validation of satellite-based ACA retrievals requires equivalent field measurements particularly over the regions where ACA are often observed from satellites, i.e., south-eastern Atlantic Ocean, tropical Atlantic Ocean, northern Arabian Sea, South-East and North-East Asia.

validation↗
NASA NTRS2004

Angular Distribution Models for Top-of-Atmosphere Radiative Flux Estimation from the Clouds and the Earth's Radiant Energy System Instrument on the Terra Satellite: Methodology - Part 1

The Clouds and Earth's Radiant Energy System (CERES) provides coincident global cloud and aerosol properties together with reflected solar, emitted terrestrial longwave and infrared window radiative fluxes. These data are needed to improve our understanding and modeling of the interaction between clouds, aerosols and radiation at the top of the atmosphere, surface, and within the atmosphere. This paper describes the approach used to estimate top-of-atmosphere (TOA) radiative fluxes from instantaneous CERES radiance measurements on the Terra satellite. A key component involves the development of empirical angular distribution models (ADMs) that account for the angular dependence of Earth's radiation field at the TOA. The CERES Terra ADMs are developed using 24 months of CERES radiances, coincident cloud and aerosol retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological parameters from the Global Modeling and Assimilation Office (GMA0) s Goddard Earth Observing System DAS (GEOS-DAS V4.0.3) product. Scene information for the ADMs is from MODIS retrievals and GEOS-DAS V4.0.3 properties over ocean, land, desert and snow, for both clear and cloudy conditions. Because the CERES Terra ADMs are global, and far more CERES data is available on Terra than was available from CERES on the Tropical Rainfall Measuring Mission (TRMM), the methodology used to define CERES Terra ADMs is different in many respects from that used to develop CERES TRMM ADMs, particularly over snow/sea-ice, under cloudy conditions, and for clear scenes over land and desert.

Loeb, N. G.↗