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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Changes in TOA SW Fluxes over Marine Clouds When Estimated via Semiphysical Angular Distribution Models

Top-of-atmosphere (TOA) shortwave (SW) angular distribution models (ADMs) approximate—per angular direction of an imagined upward hemisphere—the intensity of sunlight scattered back from a specific Earth–atmosphere scene. ADMs are, thus, critical when converting satellite-borne broadband radiometry into estimated radiative fluxes. This paper applies a set of newly developed ADMs with a more refined scene definition and demonstrates tenable changes in estimated fluxes compared to currently operational ADMs. Newly developed ADMs use a semiphysical framework to consider cloud-top effective radius (¯¯R_e) and above-cloud water vapor (ACWV), in addition to accounting for surface wind speed and clouds’ phase, fraction, and optical depth. In effect, instantaneous TOA SW fluxes for marine liquid-phase clouds had the largest flux differences (of up to 25 W m−2) for lower solar zenith angles and cloud optical depth greater than 10 due to extremes in ¯¯R_e or ACWV. In regions where clouds had persistently extreme levels of ¯¯R_e (here mostly for ¯¯R_e < 7μm and ¯¯R_e > 15μm) or ACWV, instantaneous fluxes estimated from Aqua, Terra, Meteosat-8, and Meteosat-9 satellites using the two ADMs differed systematically, resulting in significant deviations in daily mean fluxes (up to ±10 W m^(−2)) and monthly mean fluxes (up to ±5 W m^(−2)). Flux estimates using newly developed, semiphysical ADMs may contribute to a better understanding of solar fluxes over low-level clouds. It remains to be seen whether aerosol indirect effects are impacted by these updates.

angular distribution models (ADMs)↗
NASA NTRS2017

Determining Cloud Thermodynamic Phase from Micropulse Lidar Network Data

Determining cloud thermodynamic phase is a critical factor in studies of Earth's radiation budget. Here we use observations from the NASA Micro Pulse Lidar Network (MPLNET) and thermodynamic profiles from the Goddard Earth Observing System, version 5 (GEOS-5) to distinguish liquid water, mixed-phase, and ice water clouds. The MPLNET provides sparse global, autonomous, and continuous measurements of clouds and aerosols which have been used in a number of scientific investigations to date. The use of a standardized instrument and a common suite of data processing algorithms with thorough uncertainty characterization allows for straightforward comparisons between sites. Lidars with polarization capabilities have recently been incorporated into the MPLNET project which allows, for the first time, the ability to infer a cloud thermodynamic phase. This presentation will look specifically at the occurrence of ice and mixed phase clouds in the temperature region of -10 C to -40 C for different climatological regions and seasons. We compare MPLNET occurrences of mixed-phase clouds to an historical climatology based on observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) spacecraft.

mixing layer height↗
NASA NTRS2014

Cloud Thermodynamic Phase Detection with Polarimetrically Sensitive Passive Sky Radiometers

The primary goal of this project has been to investigate if ground-based visible and near-infrared passive radiometers that have polarization sensitivity can determine the thermodynamic phase of overlying clouds, i.e. if they are comprised of liquid droplets or ice particles. While this knowledge is important by itself for our understanding of the global climate, it can also help improve cloud property retrieval algorithms that use total (unpolarized) radiance to determine Cloud Optical Depth (COD). This is a potentially unexploited capability of some instruments in the NASA Aerosol Robotic Network (AERONET), which, if practical, could expand the products of that global instrument network at minimal additional cost. We performed simulations that found, for zenith observations, cloud thermodynamic phase is often expressed in the sign of the Q component of the Stokes polarization vector. We chose our reference frame as the plane containing solar and observation vectors, so the sign of Q indicates the polarization direction, parallel (negative) or perpendicular (positive) to that plane. Since the quantity of polarization is inversely proportional to COD, optically thin clouds are most likely to create a signal greater than instrument noise. Besides COD and instrument accuracy, other important factors for the determination of cloud thermodynamic phase are the solar and observation geometry (scattering angles between 40 and 60 degrees are best), and the properties of ice particles (pristine particles may have halos or other features that make them difficult to distinguish from water droplets at specific scattering angles, while extreme ice crystal aspect ratios polarize more than compact particles). We tested the conclusions of our simulations using data from polarimetrically sensitive versions of the Cimel 318 sun photometerradiometer that comprise AERONET. Most algorithms that exploit Cimel polarized observations use the Degree of Linear Polarization (DoLP), not the individual Stokes vector elements (such as Q). For this reason, we had no information about the accuracy of Cimel observed Q and the potential for cloud phase determination. Indeed, comparisons to ceilometer observations with a single polarized spectral channel version of the Cimel at a site in the Netherlands showed little correlation. Comparisons to Lidar observations with a more recently developed, multi-wavelength polarized Cimel in Maryland, USA, show more promise. This divergence between simulations and observations has prompted us to begin the development of a small test instrument called the Sky Polarization Radiometric Instrument for Test and Evaluation (SPRITE). This instrument is specifically devoted to the accurate observation of Q, and the testing of calibration and uncertainty assessment techniques, with the ultimate goal of understanding the practical feasibility of these measurements.

Knobelspiesse, Kirk D.↗
DOE OSTI2024

Processes Associated with Boundary Layer Cloud Ice Phase Precipitation in the High Southern Latitudes (Final Technical Report)

This is a final technical report for DOE Award No. DE-SC0018995. Using data collected during the MARCUS deployment of the 2nd ARM mobile facility, this project sought to address the following scientific questions: 1. What are the conditions that govern phase partitioning in supercooled boundary layer clouds over the high latitude Southern Oceans? 2. To what extent are supercooled mixed phase clouds responsible for the high cloud fractions over the Southern Ocean and do these mixed phase clouds contribute to the model biases in absorbed shortwave radiation? 3. Can the cloud properties and phase partitioning over the Southern Ocean be linked to the underlying aerosol environment? 4. How do the aerosol properties at the surface vary spatially and seasonally over the high latitude Southern Ocean and what processes control these features? 5. How well defined are the atmospheric compositional boundaries between Southern Ocean marine, Antarctic free tropospheric, and Antarctic surface airmasses, and how does this influence the chemistry and physics of the Southern Ocean atmosphere? In this project we published three peer review journal articles that address these questions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Snow Reconciles Observed and Simulated Phase Partitioning and Increases Cloud Feedback

The surprising increase of Earth's climate sensitivity in the most recent Coupled Model Intercomparison Project (CMIP) models has been largely attributed to extratropical cloud feedback, which is thought to be driven by greater supercooled water in present-day cloud phase partitioning (CPP). Here we report that accounting for precipitation in the Goddard Institute for Space Studies ModelE3 radiation scheme, neglected in more than 60% of CMIP6 and 90% of CMIP5 models, systematically changes its apparent CPP and substantially increases its cloud feedback, consistent with results using CMIP models. Including precipitation in the comparison with Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements and in model radiation schemes is essential to faithfully constrain cloud amount and phase partitioning, and simulate cloud feedbacks. Our findings suggest that making radiation schemes precipitation-aware (missing in most CMIP6 models) should strengthen their positive cloud feedback and further increase their already high mean climate sensitivity.

Earth's climate sensitivity↗
DOE OSTI2021

Snow Reconciles Observed and Simulated Phase Partitioning and Increases Cloud Feedback

The surprising increase of Earth's climate sensitivity in the most recent coupled model intercomparison project (CMIP) models has been largely attributed to extratropical cloud feedback, which is thought to be driven by greater supercooled water in present-day cloud phase partitioning (CPP). Here, we report that accounting for precipitation in the Goddard Institute for Space Studies ModelE3 radiation scheme, neglected in more than 60% of CMIP6 and 90% of CMIP5 models, systematically changes its apparent CPP and substantially increases its cloud feedback, consistent with results using CMIP models. Including precipitation in the comparison with cloud–aerosol lidar and infrared pathfinder satellite observations (CALIPSO) measurements and in model radiation schemes is essential to faithfully constrain cloud amount and phase partitioning, and simulate cloud feedbacks. Our findings suggest that making radiation schemes precipitation-aware (missing in most CMIP6 models) should strengthen their positive cloud feedback and further increase their already high mean climate sensitivity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Urbanization-induced land and aerosol impacts on sea-breeze circulation and convective precipitation

Abstract. Changes in land cover and aerosols resulting from urbanization may impact convective clouds and precipitation. Here we investigate how Houston urbanization can modify sea-breeze-induced convective cloud and precipitation through the urban land effect and anthropogenic aerosol effect. The simulations are carried out with the Chemistry version of the Weather Research and Forecasting model (WRF-Chem), which is coupled with spectral-bin microphysics (SBM) and the multilayer urban model with a building energy model (BEM-BEP). We find that Houston urbanization (the joint effect of both urban land and anthropogenic aerosols) notably enhances storm intensity (by ∼ 75 % in maximum vertical velocity) and precipitation intensity (up to 45 %), with the anthropogenic aerosol effect more significant than the urban land effect. Urban land effect modifies convective evolution: speed up the transition from the warm cloud to mixed-phase cloud, thus initiating surface rain earlier but slowing down the convective cell dissipation, all of which result from urban heating-induced stronger sea-breeze circulation. The anthropogenic aerosol effect becomes evident after the cloud evolves into the mixed-phase cloud, accelerating the development of storm from the mixed-phase cloud to deep cloud by ∼ 40 min. Through aerosol–cloud interaction (ACI), aerosols boost convective intensity and precipitation mainly by activating numerous ultrafine particles at the mixed-phase and deep cloud stages. This work shows the importance of considering both the urban land and anthropogenic aerosol effects for understanding urbanization effects on convective clouds and precipitation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

The Mixed-Phase Arctic Cloud Experiment (M-PACE)

The Mixed-Phase Arctic Cloud Experiment (M-PACE) was conducted September 27 through October 22, 2004 on the North Slope of Alaska. The primary objective was to collect a data set suitable to study interactions between microphysics, dynamics and radiative transfer in mixed-phase Arctic clouds. Observations taken during the 1997/1998 Surface Heat and Energy Budget of the Arctic (SHEBA) experiment revealed that Arctic clouds frequently consist of one (or more) liquid layers precipitating ice. M-PACE sought to investigate the physical processes of these clouds utilizing two aircraft (an in situ aircraft to characterize the microphysical properties of the clouds and a remote sensing aircraft to constraint the upwelling radiation) over the Department of Energy s Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) on the North Slope of Alaska. The measurements successfully documented the microphysical structure of Arctic mixed-phase clouds, with multiple in situ profiles collected in both single-layer and multi-layer clouds over two ground-based remote sensing sites. Liquid was found in clouds with temperatures down to -30 C, the coldest cloud top temperature below -40 C sampled by the aircraft. Remote sensing instruments suggest that ice was present in low concentrations, mostly concentrated in precipitation shafts, although there are indications of light ice precipitation present below the optically thick single-layer clouds. The prevalence of liquid down to these low temperatures could potentially be explained by the relatively low measured ice nuclei concentrations.

Verlinde, J.↗
DOE OSTI2022

Combined Effect of the Wegener–Bergeron–Findeisen Mechanism and Large Eddies on Microphysics of Mixed-Phase Stratiform Clouds

Abstract The process of glaciation in mixed-phase stratiform clouds was investigated by a novel Lagrangian–Eulerian model (LEM) in which thousands of adjoining Lagrangian parcels moved within a turbulent-like velocity field with statistical parameters typical of the Arctic boundary layer. We used detailed bin microphysics to describe the condensation/evaporation processes in each parcel, in which droplets, aerosols, and ice particles were described using size distributions of 500 mass bins. The model also calculated aerosol mass inside droplets and ice particles. Gravitational sedimentation of droplets and ice particles was also accounted for. Assuming that droplet freezing is the primary source of ice particles, the Arctic clouds observed in Indirect and Semi-Direct Aerosol Campaign (ISDAC) were successfully simulated. The model showed that at a low ice particle concentration typical of ISDAC, large vortices (eddies) led to a quasi-stationary regime, in which mixed-phase St existed for a long time. The large eddies controlled the water partitioning in the mixed-phase clouds. Droplets formed and grew in updrafts, typically reaching the cloud top, and evaporated in downdrafts. Ice particles grew in updrafts and downdrafts. The Wegener–Bergeron–Findeisen (WBF) mechanism was efficient in downdrafts and some parts of updrafts, depending on ice concentration and vertical velocity. At low ice concentrations, the effect of ice on the phase partitioning was negligible. In this regime, liquid droplets were found near the cloud top, whereas ice particles precipitated through the cloud base. When ice concentration exceeded about 10 L −1 , the WBF mechanism led to glaciation of almost the entire cloud, with the exception of narrow cloud regions associated with strong updrafts. At ice particle concentrations of a few tens per liter, the oscillatory regime took place due to the ice–liquid interaction. The microphysical structure of mixed-phase St forms as a combined effect of cloud dynamics (large eddies) and the WBF mechanism.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Determining Cloud Thermodynamic Phase from the Polarized Micro Pulse Lidar

A method to distinguish cloud thermodynamic phase from polarized Micro Pulse Lidar (MPL) measurements is described. The method employs a simple enumerative approach to classify cloud layers as either liquid water, ice water, or mixed-phase clouds based on the linear volume depolarization ratio and cloud top temperatures derived from Goddard Earth Observing System, version 5 (GEOS-5) assimilated data. Two years of cloud retrievals from the Micro Pulse Lidar Network (MPLNET) site in Greenbelt, MD are used to evaluate the performance of the algorithm. The fraction of supercooled liquid water in the mixed-phase temperature regime (-37 °C – 0 °C) calculated using MPLNET data is compared to similar calculations made using the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on board the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite, with reasonable consistency.

Jasper R Lewis↗
DOE OSTI2021

Multi-channel Imager Algorithm (MIA): A novel cloud-top phase classification algorithm

The current Geostationary Operational Environmental Satellites (GOES-16 and 17) cloud-top phase classification algorithm is based primarily on empirical thresholds at multiple wavelengths that have varying absorption capabilities for water and ice. The performance of current GOES-16 cloud-top phase product largely depends on the accuracy of the selection of reflectance ratios. Here this study aims at presenting a novel cloud-top phase classification algorithm (the Multi-channel Imager Algorithm, MIA) that provides a more judicious selection of relationships between channels using a supervised K-mean clustering method on multi-channel Red-Green-Blue images. The K-mean clustering method works analogously to how human eyes separate different colors in a microphysical color rendering set of satellite images, which differentiates water, ice and unclassified thin clouds. For water phase, cloud-top temperature information is used to further distinguish supercooled water. To evaluate the performance of the MIA, an extensive comparison with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Moderate Resolution Imaging Spectroradiometer, and current GOES-16 cloud-top phase products is conducted, using CALIOP as the benchmark. Compared to the current GOES-16 cloud-top phase product, MIA demonstrates a substantial improvement in phase classification, where hit rate increases from 69% to 76% over the Continental United States and 58% to 66% over the full disk domain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling impacts of ice-nucleating particles from marine aerosols on mixed-phase orographic clouds during 2015 ACAPEX field campaign

Abstract. A large fraction of annual precipitation over the western United States comes from wintertime orographic clouds associated with atmospheric rivers (ARs). Transported African and Asian dust and marine aerosols from the Pacific Ocean may act as ice-nucleating particles (INPs) to affect cloud and precipitation properties over the region. Here we explored the effects of INPs from marine aerosols on orographic mixed-phase clouds and precipitation at different AR stages for an AR event observed during the 2015 ACAPEX field campaign under low dust (<0.02 cm−3) conditions. Simulations were conducted using the chemistry version of the Weather Research and Forecasting Model coupled with the spectral-bin microphysics at 1 km grid spacing, with ice nucleation connected with dust and marine aerosols. By comparing against airborne and ground-based observations, accounting for marine INP effects improves the simulation of AR-precipitation. The marine INPs enhance the formation of ice and snow, leading to less shallow warm clouds but more mixed-phase and deep clouds, as well as to a large spillover effect of precipitation after AR landfall. The responses of cloud and precipitation to marine INPs vary with the AR stages, with more significant effects before AR landfall and post-AR than after AR landfall, mainly because the moisture and temperature conditions change with the AR evolution. This work suggests weather and climate models need to consider the impacts of marine INPs since their contribution is notable under low dust conditions despite the much lower relative ice nucleation efficiency of marine INPs.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2024

Cloud Top Phase Characterization of Extratropical Cyclones over the Northeast and Midwest United States: Results from IMPACTS

Cloud top phase (CTP) impacts cloud albedo and pathways for ice particle nucleation, growth, and fallout within extratropical cyclones. This study uses airborne lidar, radar, and Rapid Refresh analysis data to characterize CTP within extratropical cyclones as a function of cloud top temperature (CTT). During the 2020, 2022, and 2023 Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign deployments, the Earth-Resources 2 (ER-2) aircraft flew 26 research flights over the Northeast and Midwest U.S. to sample the cloud tops of a variety of extratropical cyclones. A training dataset was developed to create probabilistic phase classifications based on Cloud Physics Lidar measurements of known ice and liquid clouds. These classifications were then used to quantify dominant CTP in the top 150 m of clouds sampled by the Cloud Physics Lidar in storms during IMPACTS. Case studies are presented illustrating examples of supercooled liquid water at cloud top at different CTT ranges (-3°C -20°C. Liquid-bearing cloud tops were found at CTTs as cold as -37ºC.

Troy J. Zaremba↗
DOE OSTI2024

Broadband and filter radiometers at Ross Island, Antarctica: detection of cloud ice phase versus liquid water influences on shortwave and longwave radiation

Abstract. Surface radiometer data from Ross Island, Antarctica, collected during the austral summer 2015–2016 by the US Department of Energy Atmospheric Radiation Measurement (ARM) program West Antarctic Radiation Experiment (AWARE), are used to evaluate how shortwave and longwave irradiance respond to changing cloud properties as governed by contrasting meteorological regimes. Shortwave atmospheric transmittance is derived from pyranometer measurements, and cloud conservative-scattering optical depth is derived from filter radiometer measurements at 870 nm. With onshore flow associated with marine air masses, clouds contain mostly liquid water. With southerly flow over the Transantarctic Mountains, orographic forcing induces substantial cloud ice water content. These ice and mixed-phase clouds attenuate more surface shortwave irradiance than the maritime-influenced clouds and also emit less longwave irradiance due to colder cloud base temperature. These detected irradiance changes are in a range that can mean onset or inhibition of surface melt over ice shelves. This study demonstrates how basic and relatively low-cost broadband and filter radiometers can be used to detect subtle climatological influences of contrasting cloud microphysical properties at very remote locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluating EAMv2 Simulated High Latitude Clouds Using ARM Measurements in the Northern and Southern Hemispheres

Here, this study evaluates high latitude stratiform mixed-phase clouds (SMPC) in the atmosphere model of the Energy Exascale Earth System Model version 2 (EAMv2) by utilizing one-year-long ground-based remote sensing measurements from the Atmospheric Radiation and Measurement (ARM) program. A nudging approach is applied to model simulations for a constrained comparison with the ARM observations. Observed and modeled SMPCs are sampled and collocated to address the difference in data resolution, so that we can consistently evaluate their macrophysical properties at the North Slope of Alaska (NSA) site in the Arctic and the McMurdo (AWR) site in the Antarctic. We found that EAMv2 overestimates SMPC frequency of occurrence at both sites. However, the model captures the observed larger cloud frequency of occurrence at the NSA site. For collocated SMPCs, the annual statistics of observed cloud macrophysics are generally reproduced at the NSA site, while at the AWR site, there are larger biases. Compared to the AWR site, the lower cloud top and cloud base and the warmer cloud top temperature observed at NSA are well simulated. On the other hand, simulated cloud phase is substantially biased. The model largely overestimates liquid water path, and the ice water path is underestimated at NSA, but at AWR, the liquid water path is frequently underestimated due to the dominance of snow in Antarctic SMPCs. As a result, the observed hemispheric difference in cloud phase partitioning is misrepresented in EAMv2. This study implies that additional model development is needed for high latitude mixed-phase clouds.

54 ENVIRONMENTAL SCIENCES↗