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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Lidar measurements of cloud extinction coefficient distribution and its forward scattering phase function according to multiply scattered lidar returns

The study of the inversion algorithm for the single scatter lidar equation, for quantitative determination of cloud (or aerosol) optical properties, has received much attention over the last thirty years. Some of the difficulties associated with the solution of this equation are not yet solved. One problem is that a single scatter lidar equation has two unknowns. Because of this, the determination of the far-end boundary value, in the case of Klett's algorithm, is a problem if the atmosphere is optically inhomogeneous. Another difficulty concerns multiple scattering. There is a large error in the extinction distribution solution, in many cases, if only the single scattering component is considered, while neglecting the multiple scattering component. However, the use of multiple scattering in the remote sensing of aerosol or cloud optical properties is promising. In our early study, an inversion method for simultaneous determination of the cloud (or aerosol) Extinction Coefficient Distribution (ECD) and its Forward Scattering Phase Function (FSPF) was proposed according to multiply scattered lidar returns with two fields of view for the receiver. The method is based on a parameterized multiple scatter lidar equation. This paper is devoted to further numerical tests and an experimental study of lidar measurements of cloud ECD and FSPF using this method.

Qiu, Jinhuan↗
NASA NTRS2001

Overview of ACE-Asia Spring 2001 Investigations on Aerosol Radiative Effects and Related Aerosol Properties

A primary, ACE-Asia objective was to quantify the interactions between aerosols and radiation in the Asia-Pacific region. Toward this end, radiometric and related aerosol measurements were made from ocean, land, air and space platforms. Models that predict aerosol fields guided the measurements and are helping integrate and interpret results. Companion overview's survey these measurement and modeling components. Here we illustrate how these components were combined to determine aerosol radiative. impacts and their relation to aerosol properties. Because clouds can obscure or change aerosol direct radiative effects, aircraft and ship sorties to measure these effects depended on predicting and finding cloud-free areas and times with interesting aerosols present. Pre-experiment satellite cloud climatologies, pre-flight aerosol and cloud forecasts, and in-flight guidance from satellite imagery all helped achieve this. Assessments of aerosol regional radiative impacts benefit from the spatiotemporal coverage of satellites, provided satellite-retrieved aerosol properties are accurate. Therefore, ACE-Asia included satellite retrieval tests, as part of many comparisons to judge the consistency (closure) among, diverse measurements. Early results include: (1) Solar spectrally resolved and broadband irradiances and optical depth measurements from the C-130 aircraft and at Kosan, Korea yielded aerosol radiative forcing efficiencies, permitting comparisons between efficiencies of ACE-Asia and INDOEX aerosols, and between dust and "pollution" aerosols. Detailed results will be presented in separate papers. (2) Based on measurements of wavelength dependent aerosol optical depth (AOD) and single scattering albedo the estimated 24-h a average aerosol radiative forcing efficiency at the surface for photosynthetically active radiation (400 - 700 nm) in Yulin, China is approx. 30 W sq m per AOD(500 nm). (3) The R/V Brown cruise from Honolulu to Sea of Japan sampled an aerosol optical depth gradient, with AOD(500 nm) extremes from 0.1 to 1.1. On the Pacific transit from Honolulu to Hachijo AOD(500 nm) averaged 0.2, including increases to 0.4 after several storms, suggesting the strong impact of wind-generated seasalt. The AOD maximum, found in the Sea of Japan, was influenced by dust and anthropogenic sources. (4) In Beijing, single scattering albedo retrieved from AERONET sun-sky radiometry yielded midvisible SSA=0.88 with strong wavelength dependence, suggesting a significant black carbon component. SSA retrieved during dust episodes was approx. 0.90 and variable but wavelength neutral reflecting the presence of urban haze with the dust. Downwind at Anmyon Island SSA was considerably higher, approx. 0.94, but wavelength neutral for dust episodes and spectrally dependent during non dust periods. (5) Satellite retrievals show major aerosol features moving from Asia over the Pacific; however, determining seasonal-average aerosol effects is hampered by sampling frequency and large-scale cloud systems that obscure key parts of aerosol patterns. Preliminary calculations using, satellite-retrieved AOD fields and initial ACE-Asia aerosol properties (including sulfates, soot, and dust) yield clear-sky aerosol radiative effects in the seasonal-average ACE-Asia plume exceeding those of manmade greenhouse gases. Quantifying all-sky direct aerosol radiative effects is complicated by the need to define the height of absorbing aerosols with respect to cloud decks.

Russell, Philip B.↗
NASA NTRS2017

CATS Version 2 Aerosol Feature Detection and Applications for Data Assimilation

The Cloud Aerosol Transport System (CATS) lidar has been operating onboard the International Space Station (ISS) since February 2015 and provides vertical observations of clouds and aerosols using total attenuated backscatter and depolarization measurements. From February March 2015, CATS operated in Mode 1, providing backscatter and depolarization measurements at 532 and 1064 nm. CATS began operation in Mode 2 in March 2015, providing backscatter and depolarization measurements at 1064 nm and has continued to operate to the present in this mode. CATS level 2 products are derived from these measurements, including feature detection, cloud aerosol discrimination, cloud and aerosol typing, and optical properties of cloud and aerosol layers. Here, we present changes to our level 2 algorithms, which were aimed at reducing several biases in our version 1 level 2 data products. These changes will be incorporated into our upcoming version 2 level 2 data release in summer 2017. Additionally, owing to the near real time (NRT) data downlinking capabilities of the ISS, CATS provides expedited NRT data products within 6 hours of observation time. This capability provides a unique opportunity for supporting field campaigns and for developing data assimilation techniques to improve simulated cloud and aerosol vertical distributions in models. We additionally present preliminary work toward assimilating CATS observations into the NASA Goddard Earth Observing System version 5 (GEOS-5) global atmospheric model and data assimilation system.

data assimilation↗
NASA NTRS2007

Cloud Optical Depth Retrievals from Solar Background "signal" of Micropulse Lidars

Pulsed lidars are commonly used to retrieve vertical distributions of cloud and aerosol layers. It is widely believed that lidar cloud retrievals (other than cloud base altitude) are limited to optically thin clouds. Here we demonstrate that lidars can retrieve optical depths of thick clouds using solar background light as a signal, rather than (as now) merely a noise to be subtracted. Validations against other instruments show that retrieved cloud optical depths agree within 10-15% for overcast stratus and broken clouds. In fact, for broken cloud situations one can retrieve not only the aerosol properties in clear-sky periods using lidar signals, but also the optical depth of thick clouds in cloudy periods using solar background signals. This indicates that, in general, it may be possible to retrieve both aerosol and cloud properties using a single lidar. Thus, lidar observations have great untapped potential to study interactions between clouds and aerosols.

Chiu, J. Christine↗
NASA NTRS2018

Aerosol-Radiation-Cloud Interactions in the South-East Atlantic: Results from the ORACLES-2016 Deployment and a First Look at ORACLES-2017 and Beyond

Seasonal biomass burning (BB) in Southern Africa during the Southern hemisphere spring produces almost a third of the Earth's BB aerosol particles. These particles are lofted into the mid-troposphere and transported westward over the South-East (SE) Atlantic, where they interact with one of the three semi-permanent subtropical stratocumulus (Sc) cloud decks in the world. These interactions include adjustments to aerosol-induced solar heating and microphysical effects. The representation of these interactions in climate models remains highly uncertain, because of the scarcity of observational constraints on both, the aerosol and cloud properties, and the governing physical processes. The first deployment of the NASA P-3 and ER-2 aircraft in the ORACLES (ObseRvations of Aerosols Above Clouds and Their IntEractionS) project in August/September of 2016 has started to fill this observational gap by providing an unprecedented look at the SE Atlantic cloud-aerosol system. We provide an overview of the first deployment, highlighting aerosol absorptive and cloud-nucleating properties, their vertical distribution relative to clouds, the locations and degree of aerosol mixing into clouds, cloud changes in response to such mixing, and cloud top stability relationships to the aerosol. We also expect to describe preliminary results of the second ORACLES deployment from Sao Tome and Pri­ncipe in August 2017. We will make an initial assessment of the differences and similarities of the BB plume and cloud properties as observed from a deployment site near the plume's northern edge. We will conclude with an outlook for the third ORACLES deployment in October 2018.

Redemann, Jens↗
DOE OSTI2025

Variability of Eastern North Atlantic Summertime Marine Boundary Layer Clouds and Aerosols Across Different Synoptic Regimes Identified With Multiple Conditions

Abstract This study estimates the meteorological covariations of aerosol and marine boundary layer (MBL) cloud properties in the eastern North Atlantic (ENA) region, characterized by diverse synoptic conditions. Using a deep‐learning‐based clustering model with mid‐level and surface daily meteorological data, we identify seven distinct synoptic regimes during the summer from 2016 to 2021. Our analysis, incorporating reanalysis data and satellite retrievals, shows that surface aerosols and MBL clouds exhibit clear regime‐dependent characteristics, whereas lower tropospheric aerosols do not. This discrepancy likely arises from synoptic regimes determined by daily large‐scale conditions, which may overlook air mass histories that predominantly dictate lower tropospheric aerosol conditions. Focusing on three regimes dominated by northerly winds, we analyze the Atmospheric Radiation Measurement Program (ARM) ENA observations on Graciosa Island in the Azores. In the subtropical anticyclone regime, fewer cumulus clouds and more single‐layer stratocumulus clouds with light drizzle are observed, along with the highest cloud droplet number concentration (Nd), surface cloud condensation nuclei (CCN) and surface aerosol levels. The post‐trough regime features more broken or multi‐layer stratocumulus clouds with slightly higher surface rain rate, and lower Nd and surface CCN levels. The weak trough regime is characterized by the deepest MBL clouds, primarily cumulus and broken stratocumulus clouds, with the strongest surface rain rate and the lowest Nd, surface CCN and surface aerosol levels, indicating strong wet scavenging. These findings highlight the importance of considering the covariation of cloud and aerosol properties driven by large‐scale regimes when assessing aerosol indirect effects using observations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2008

Lidar System for Airborne Measurement of Clouds and Aerosols

A lidar system for measuring optical properties of clouds and aerosols at three wavelengths is depicted. The laser transmitter is based on a Nd:YVO4 laser crystal pumped by light coupled to the crystal via optical fibers from laser diodes that are located away from the crystal to aid in dissipating the heat generated in the diodes and their drive circuits. The output of the Nd:YVO4 crystal has a wavelength of 1064 nm, and is made to pass through frequency-doubling and frequency-tripling crystals. As a result, the net laser output is a collinear superposition of beams at wavelengths of 1064, 532, and 355 nm. The laser operates at a pulse-repetition rate of 5 kHz, emitting per-pulse energies of 50 microJ at 1064 nm, 25 microJ at 532 nm and 50 microJ at 355 nm. An important feature of this system is an integrating sphere located between the laser output and the laser beam expander lenses. The integrating sphere collects light scattered from the lenses. Three energy-monitor detectors are located at ports inside the integrating sphere. Each of these detectors is equipped with filters such that the laser output energy is measured independently for each wavelength. The laser output energy is measured on each pulse to enable the most accurate calibration possible. The 1064-nm and 532-nm photodetectors are, more specifically, single photon-counting modules (SPCMs). When used at 1064 nm, these detectors have approximately 3% quantum efficiency and low thermal noise (fewer than 200 counts per second). When used at 532 nm, the SPCMs have quantum efficiency of about 60%. The photodetector for the 355-nm channel is a photon-counting photomultiplier tube having a quantum efficiency of about 20%. The use of photon-counting detectors is made feasible by the low laser pulse energy. The main advantage of photon-counting is ease of inversion of data without need for complicated calibration schemes like those necessary for analog detectors. The disadvantage of photon-counting detectors is that they inherently have narrow dynamic ranges. However, by using photon-counting detectors along with a high-repetition rate laser, it is possible to obtain wide dynamic range through accumulation of counts over many pulses.

McGill, Matthew↗
NASA NTRS2001

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar orbiting, sun-synchronous, platform at an altitude of 705 kilometers, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 meters (2 bands), 500 meters (5 bands) and 1000 meters (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation we review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of (i) developing a cloud mask for distinguishing clear sky from clouds, (ii) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (iii) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (iv) determining atmospheric profiles of moisture and temperature, and (v) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 degree (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented.

King, Michael D.↗
NASA NTRS2001

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands from 0.415 to 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation I will review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of: (1) developing a cloud mask for distinguishing clear sky from clouds, (2) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (3) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (4) determining atmospheric profiles of moisture and temperature, and (5) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 deg (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented. Finally, I will present some highlights from the land and ocean algorithms developed for processing global MODIS observations, including: (1) surface reflectance, (2) vegetation indices, leaf area index, and FPAR, (3) albedo and nadir BRDF-adjusted reflectance, (4) normalized water-leaving radiance, (5) chlorophyll-a concentration, and (6) sea surface temperature.

King, Michael D.↗
DOE OSTI2025

Evaluation of E3SM Simulated Aerosols and Aerosol‐Cloud Interactions Across GCM and Convection‐Permitting Scales

This paper introduces an Earth system modeling testbed for predicting aerosols and aerosol‐cloud interactions (ACIs) at convection‐permitting scales. Using the Energy Exascale Earth System Model (E3SM) version 2 with a four‐mode Modal Aerosol Module, we conduct simulations at 3.25 km resolution on a regionally refined mesh (RRM) across four regions with distinct aerosol and cloud regimes. Results are compared with the standard 100 km E3SM configuration and evaluated against satellite, aircraft, and ground‐based observations. We find that increasing model resolution improves heavy precipitation simulation but amplifies positive bias in light drizzle at coarse resolution. These resolution‐induced changes affect cloud and aerosol properties to varying degrees across regions. Generally, cloud cover and liquid water path (LWP) show better agreement with satellite retrievals at 3.25 km, though surface‐based comparisons suggest otherwise. Aerosol composition remains poorly represented at both resolutions. The RRM increases Aitken mode aerosol number concentrations via enhanced new particle formation. However, accumulation mode aerosols are decreased at higher resolution as aerosol removals become more efficient. This partially contributes to fewer cloud condensation nuclei (CCN) and lower cloud droplet number concentrations (N d ), which produces larger model biases in some scenarios. These findings suggest that solely increasing horizontal resolution to kilometer scales is insufficient to broadly improve aerosol and cloud predictions without concurrent advancements in physical and chemical process representations. Nonetheless, the RRM moderately improves key ACI relationships such as CCN‐N d correlation, reflecting enhanced aerosol activation representation. The LWP‐N d relationship is also better captured by RRM, suggesting a better characterization of LWP adjustment.

Huang, Meng [Pacific Northwest National Laboratory↗
NASA NTRS2011

EPIC Radiance Simulator for Deep Space Climate ObserVatoRy (DSCOVR)

The Deep Space Climate ObserVatoRy (DSCOVR) is a planned space weather mission for the Sun and Earth observations from the Lagrangian L1 point. Onboard of DSCOVR is a multispectral imager EPIC designed for unique observations of the full illuminated disk of the Earth with high temporal and 10 km spatial resolution. Depending on latitude, EPIC will observe the same Earth surface area during the course of the day in a wide range of solar and view zenith angles in the backscattering view geometry with the scattering angle of 164-172 . To understand the information content of EPIC data for analysis of the Earth clouds, aerosols and surface properties, an EPIC radiance Simulator was developed covering the UV -VIS-NIR range including the oxygen A and B-bands (A=340, 388, 443, 555, 680, 779.5, 687.7, 763.3 nm). The Simulator uses ancillary data (surface pressure/height, NCEP wind speed) as well as MODIS-based geophysical fields such as spectral surface bidirectional reflectance, column water vapor, and properties of aerosols and clouds including optical depth, effective radius, phase and cloud top height. The original simulations are conducted at 1 km resolution using the look-up table approach and then are averaged to 10 km EPIC radiances. This talk will give an overview of the EPIC Simulator with analysis of results over the continental USA and northern Atlantic.

Lyapustin, Alexei↗
NASA NTRS2016

COMMIT in 7-SEAS/BASELInE: Operation of and Observations from a Novel, Mobile Laboratory for Measuring In-Situ Properties of Aerosols and Gases

Trace gases and aerosols (particularly biomass-burning aerosols) have important implications for air quality and climate studies in Southeast Asia (SEA). This paper describes the purpose, operation, and datasets collected from NASA Goddard Space Flight Center's (NASA/GSFC) Chemical, Optical, and Microphysical Measurements of In-situ Troposphere (COMMIT) laboratory, a mobile platform designed to measure trace gases and optical/microphysical properties of naturally occurring and anthropogenic aerosols. More importantly, the laboratory houses a specialized humidification system to characterize hygroscopic growth/enhancement, a behavior that affects aerosol properties and cloud-aerosol interactions and is generally underrepresented in the current literature. A summary of the trace gas and optical/microphysical measurements is provided, along with additional detail and analysis of data collected from the hygroscopic system during the 2015 Seven South-East Asian Studies (7-SEAS) field campaign. The results suggest that data from the platform are reliable and will complement future studies of aerosols and air quality in SEA and other regions of interest.

aerosols↗
NASA NTRS2018

Satellite Observations of Cloud-Related Variations in Aerosol Properties

This paper presents an overview of our efforts to characterize and better understandcloud-related changes in aerosol properties. These efforts primarily involved the statistical analysisof global or regional datasets of Moderate Resolution Imaging Spectroradiometer (MODIS) andCloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol and cloud observations. Theresults show that in oceanic regions, more than half of all aerosol measurements by passive satelliteinstruments come from near-cloud areas, where clouds and cloud-related processes may significantlymodify aerosol optical depth and particle size. Aerosol optical depth is also shown to increasesystematically with regional cloud amount throughout the Earth. In contrast, it is shown thateffective particle size can either increase or decrease with increasing cloud cover. In bimodal aerosolpopulations, the sign of changes depends on whether coarse mode or small mode aerosols are mostaffected by clouds. The results also indicate that over large parts of Earth, undetected cloud particlesare not the dominant reason for the satellite-observed changes with cloud amount, and that 3Dradiative processes contribute about 30% of the observed near-cloud changes. The findings underlinethe need for improving our ability to accurately measure aerosols near clouds.

aerosol; cloud; satellite↗
DOE OSTI2025

Interpretable ensemble learning unveils main aerosol optical properties in predicting cloud condensation nuclei number concentration

Variations in cloud condensation nuclei number concentration (N CCN ) significantly influence cloud microphysics, yet direct N CCN measurements remain challenging. Here, we present an N CCN ensemble learning (NEL) model utilizing ensemble learning and interpretability analysis on aerosol optical parameters. Validated at two land sites, two ocean sites and one polar site within the Atmospheric Radiation Measurement program, the mean absolute percentage error range of the NEL model across different environments is from 12% to 36%, demonstrating high accuracy. Key findings reveal that aerosol optical parameters can serve as predictors for N CCN . Aerosol scattering and backscattering coefficients, absorption coefficient, backscatter fraction (BSF), and Ångström exponent (AE) are positively correlated with N CCN , while single scattering albedo shows negative correlations. N CCN prediction at land sites is highly sensitive to BSF, largely driven by the backscattering coefficient, as fine particles dominate in these sites. At ocean sites, N CCN prediction is more sensitive to AE, primarily influenced by the scattering coefficient, due to the higher proportion of larger particles. At the polar site, N CCN prediction shows sensitivity to both BSF and AE, mainly driven by the scattering coefficient, as polar sites are cleaner and contain larger particles. These differences reflect the variation in particle size and number concentration across different environments.

Atmospheric science↗
NASA NTRS1992

Infrared properties of Titan's clouds and aerosols

Using Voyager 1 Infrared Interferometer Spectrometer (IRIS) data, the infrared properties of Titan's north polar hood continuum were deduced. Stratospheric opacities were found to increase monotonically with wavenumber between 250 and 600/cm. The increase becomes more extreme with decreasing altitude; this behavior is consistent with a photochemical aerosol overlying layers of condensated organics lower down. Stratospheric optical thicknesses of order 0.1 were found at 600/cm, which became smaller as the wavelength decreased. An aerosol mass mixing ratio approximately 6 x 10 exp -8 and a mass flux approximately 10 exp -14 g/sq cm/s was inferred at 160 km. The column abundance for condensed C4N2 was found to exceed that for the vapor by a factor of 30 or more. An upper limit of 4 x 10 exp -10 was inferred for the mole fraction of gaseous C4N2.

Samuelson, Robert E.↗
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↗