Search NASA⌕ Search

SEARCH · Search NASA

Results for “cloud phase”

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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Use of Remote Sensing and In-Situ Observations to Develop and Evaluate Improved Representations of Convection and Clouds for the ACME Model

The overachieving goal of the whole CMDV-MCS project is to improve understanding of warm season continental convection and to develop treatments of convection and microphysics capable of representing mesoscale convective systems (MCSs) features in large-scale models. Our tasks for this project contributing to the overachieving goal include: (1) Improve the ice nucleation formulation for MG2 and P3 cloud microphysics schemes; (2) Improve the treatment of subgrid dynamics and thermodynamics driving the ice nucleation in E3SM; and (3) Test the performance of improved ice microphysics in E3SM with observation data. In this project, we have (1) Improved the ice nucleation parameterization for MG2 and P3 in E3SM by implementing two advanced empirical parameterizations with connection to aerosols. The two deterministic heterogeneous ice nucleation parameterizations (i.e., DeMott et al., 2015; Niemand et al., 2012) were merged with the MG2 and P3 cloud microphysics schemes in E3SM. Long-term simulations were conducted to examine the impacts of these new parameterizations on simulated cloud properties; (2) Improved the treatment of subgrid dynamics and thermodynamics driving the ice nucleation in E3SM. We evaluated the double Gaussian PDF of vertical velocity simulated by the Cloud Layers Unified By Binormals (CLUBB) and the sub-column vertical velocity sampled from the Subgrid Importance Latin Hypercube Sampler (SILHS) in E3SM. We introduced the vertical velocity variance induced by topographic gravity waves for ice nucleation and droplet activation; and (3) Tested the performance of improved ice microphysics in E3SM with observation data. We tested the new treatments of ice nucleation in the single column model (SCM) mode for the stratiform mixed-phase clouds observed during 9-10 October 2004 in the DOE ARM Mixed-Phase Arctic Cloud Experiment (M-PACE) and for the convective clouds observed on 20 May 2011 in the Midlatitude Continental Convective Clouds Experiment (MC3E). Modeled ice nucleating particles (INPs) concentrations were compared against observations collected around the globe.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2024

Observational Constraint on A Feedback From Supercooled Clouds Reduces Projected Warming Uncertainty

The increase of carbon-dioxide-doubling-induced warming (climate sensitivity) in the latest climate models is primarily attributed to a larger extratropical cloud feedback. This is thought to be partly driven by a greater ratio of supercooled liquid-phase clouds to all clouds, termed liquid phase ratio. We use an instrument simulator approach to show that this ratio has increased in the latest climate models and is overestimated rather than underestimated as previously thought. In our analysis of multiple models, a greater ratio corresponds to stronger negative cloud feedback, in contradiction with single-model-based studies. We trace this unexpected result to a cloud feedback involving a shift from supercooled to warm clouds as climate warms, which corresponds to greater cloud amount and optical depth and weakens the extratropical cloud feedback. Better constraining this ratio in climate models – and thus this supercooled cloud feedback – impacts their climate sensitivities by up to 1 ˚C and reduces inter-model spread.

Climate and Earth system modelling↗
NASA NTRS2018

Simulations of Arctic Mixed-Phase Boundary Layer Clouds: Advances in Understanding and Outstanding Questions

An overview of mixed-phase boundary layer cloud simulations emphasizes what detailed studies reveal about the level of understanding of microphysical processes, using analogous liquid-phase boundary layer clouds as a reference for the dynamical conditions. We focus primarily on modeling results from three major field campaign case studies, spanning a range of liquid water path, aerosol loading, cloud temperatures, and active processes (including drizzle, aggregation, and riming). Simulations with detailed microphysics are able to reproduce basic aspects of all three case studies, including continuous ice formation within the context of a well-mixed liquid-cloud-topped layer. However, simulations constrained with measurements of ice nuclei generally underpredict the observed amount of ice present, indicating a possible role for ice multiplication that is poorly established. Assumed ice properties may also bear a significant influence on the water vapor budget and reflectivity properties, but remain imprecisely quantified on a case study basis.

Arctic clouds; Mixed-phase clouds; Mixed-phase mic↗
NASA NTRS2001

Cloud Macro- and Microphysical Properties Derived from GOES over the ARM SGP Domain

Cloud macrophysical properties like fractional coverage and height Z(sub c) and microphysical parameters such as cloud liquid water path (LWP), effective droplet radius r(sub e), and cloud phase, are key factors affecting both the radiation budget and the hydrological cycle. Satellite data have been used to complement surface observations from Atmospheric Radiation Measurements (ARM) by providing additional spatial coverage and top-of-atmosphere boundary conditions of these key parameters. Since 1994, the Geostationary Operational Environmental Satellite (GOES) has been used for deriving at each half-hour over the ARM Southern Great Plains (SGP) domain: cloud amounts, altitudes, temperatures, and optical depths as well as broadband shortwave (SW) albedo and outgoing longwave radiation at the top of the atmosphere. A new operational algorithm has been implemented to increase the number of value-added products to include cloud particle phase and effective size (r(sub e) or effective ice diameter D(sub e)) as well as LWP and ice water path. Similar analyses have been performed on the data from the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission satellite as part of the Clouds and Earth's Radiant Energy System project. This larger suite of cloud properties will enhance our knowledge of cloud processes and further constrain the mesoscale and single column models using ARM data as a validation/initialization resource. This paper presents the results of applying this new algorithm to GOES-8 data taken during 1998 and 2000. The global VIRS results are compared to the GOES SGP results to provide appropriate context and to test consistency.

Minnis, P.↗
NASA NTRS1981

Collapse and fragmentation of rotating, adiabatic clouds

A numerical hydrodynamics code has been used to calculate the collapse of rotating, adiabatic clouds. The three-dimensional nature of the calculation allows the clouds to fragment in the dynamic collapse phase. Clouds with adiabatic exponent of 7/5 and initial cos(2 phi) density variations fragment into binary systems if the initial ratio of thermal to gravitational energy is small (about 0.05). Clouds with higher thermal energy, however, damp the density variation and form near-equilibrium ellipsoids, with ratios of rotational to gravitational energy less than the critical value for dynamic growth of nonaxisymmetry in Maclaurin spheroids. Even with an adiabatic pressure law, dynamic fragmentation of a collapsing cloud is possible, implying for star formation theory that the low thermal energy fragments produced in isothermal collapse calculations may undergo a subsequent dynamic fragmentation in the nonisothermal regime.

Boss, A. P.↗
DOE OSTI2019

Cloud feedbacks in extratropical cyclones: insight from long-term satellite data and high-resolution global simulations

A negative extratropical shortwave cloud feedback driven by changes in cloud optical depth is a feature of global climate models (GCMs). A robust positive trend in observed liquid water path (LWP) over the last two decades across the warming Southern Ocean supports the negative shortwave cloud feedback predicted by GCMs. This feature has been proposed to be due to transitions from ice to liquid with warming. To gain insight into the shortwave cloud feedback we examine extratropical cyclone variability and the response of extratropical cyclones to transient warming in GCM simulations. Multi-Sensor Advanced Climatology Liquid Water Path (MAC-LWP) microwave observations of cyclone properties from the period 1992–2015 are contrasted with GCM simulations, with horizontal resolutions ranging from 7 km to hundreds of kilometers. We find that inter-cyclone variability in LWP in both observations and models is strongly driven by the moisture flux along the cyclone's warm conveyor belt (WCB). Stronger WCB moisture flux enhances the LWP within cyclones. This relationship is replicated in GCMs, although its strength varies substantially across models. It is found that more than 80 % of the enhancement in Southern Hemisphere (SH) extratropical cyclone LWP in GCMs in response to a transient 4 K warming can be predicted based on the relationship between the WCB moisture flux and cyclone LWP in the historical climate and their change in moisture flux between the historical and warmed climates. Further, it is found that that the robust trend in cyclone LWP over the Southern Ocean in observations and GCMs is consistent with changes in the moisture flux. We propose two cloud feedbacks acting within extratropical cyclones: a negative feedback driven by Clausius–Clapeyron increasing water vapor path (WVP), which enhances the amount of water vapor available to be fluxed into the cyclone, and a feedback moderated by changes in the life cycle and vorticity of cyclones under warming, which changes the rate at which existing moisture is imported into the cyclone. Both terms contribute to increasing LWP within the cyclone. While changes in moisture flux predict cyclone LWP trends in the current climate and the majority of changes in LWP in transient warming simulations, a portion of the LWP increase in response to climate change that is unexplained by increasing moisture fluxes may be due to phase transitions. The variability in LWP within cyclone composites is examined to understand what cyclonic regimes the mixed-phase cloud feedback is relevant to. At a fixed WCB moisture flux cyclone LWP increases with increasing sea surface temperature (SST) in the half of the composite poleward of the low and decreases in the half equatorward of the low in both GCMs and observations. Cloud-top phase partitioning observed by the Atmospheric Infrared Sounder (AIRS) indicates that phase transitions may be driving increases in LWP in the poleward half of cyclones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Primary and secondary ice production: interactions and their relative importance

A discrepancy of up to 5 orders of magnitude between ice crystal and ice nucleating particle (INP) number concentrations was found in the measurements, indicating the potentially important role of secondary ice production (SIP) in the clouds. However, the interactions between primary and SIP processes and their relative importance remain unexplored. In this study, we implemented five different ice nucleation schemes as well as physical representations of SIP processes (i.e., droplet shattering during rain freezing, ice-ice collisional break-up, and rime splintering) in the Community Earth System Model version 2 (CESM2). We ran CESM2 in the single column mode for model comparisons with the DOE Atmospheric Radiation Measurement (ARM) Mixed-Phase Arctic Cloud Experiment (M-PACE) observations. We found that the model experiments with aerosol-aware ice nucleation schemes and SIP processes yield the best simulation results for the M-PACE single-layer mixed-phase clouds. We further investigated the relative importance of ice nucleation and SIP to ice number and cloud phase as well as interactions between ice nucleation and SIP in the M-PACE single-layer mixed-phase clouds. Our results show that SIP contributes 80 % to the total ice formation and transforms ~30 % of pure liquid-phase clouds simulated in the model experiments without considering SIP into mixed-phase clouds. The SIP is not only a result of ice crystals produced from ice nucleation, but also competes with the ice nucleation by reducing the number concentrations of cloud droplets and cloud-borne dust INPs. Conversely, strong ice nucleation also suppresses SIP by glaciating mixed-phase clouds and thereby reducing the amount of precipitation particles (rain and graupel).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Seasonal Variation of Dust Aerosol Vertical Distribution in Arctic Based on Polarized Micropulse Lidar Measurement

This study investigates the seasonal variation of dust aerosol vertical distribution using polarized Micropulse lidar (MPL) measurements at the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) observatory from January 2013 to September 2017. For the first time, multi-year aerosol backscatter coefficients are retrieved at the ARM NSA site from MPL measurements and are consistent with co-located high spectral resolution lidar (HSRL) measurements. The high-quality aerosol backscatter coefficient retrievals are used to derive the particle depolarization ratio (PDR) at the wavelength of 532 nm, which is used to identify the presence of dust aerosols. The annual cycles of the vertical distributions of dust backscatter coefficient and PDR and dust aerosol optical depth (DAOD) show that aerosol loading has a maximum in late winter and early spring but a minimum in late summer and early autumn. Vertically, dust aerosol occurs in the entire troposphere in spring and winter and in the low and middle troposphere in summer and autumn. Because dust aerosols are effective ice nuclei, the seasonality of dust aerosol vertical distribution has important implications for the Arctic climate through aerosol–cloud–radiation interactions, primarily through impacting mixed-phase cloud processes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Clutter mitigation, multiple peaks, and high-order spectral moments in 35 GHz vertically pointing radar velocity spectra

Abstract. This study presents and applies three separate processing methods to improve high-order moments estimated from 35 GHz (Ka band) vertically pointing radar Doppler velocity spectra. The first processing method removes Doppler-shifted ground clutter from spectra collected by a US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar (KAZR) deployed at Oliktok Point (OLI), Alaska. Ground clutter resulted from multiple pathways through antenna side lobes and reflections off a rotating scanning radar antenna located 2 m away from KAZR, which caused Doppler shifts in ground clutter returns from stationary targets 2.5 km away. After removing clutter in the recorded velocity spectra, the second processing method identifies multiple separate and sub-peaks in the spectra and estimates high-order moments for each peak. Multiple peaks and high-order moments were estimated for both original 2 and 15 s averaged spectra. The third processing step improves the spectrum variance, skewness, and kurtosis estimates by removing velocity variability due to turbulent broadening during 15 s averaging intervals. Applying the multiple peak processing to Doppler velocity spectra during liquid-only clouds can identify cloud and drizzle particles and during mixed-phase clouds can identify liquid cloud and frozen hydrometeors. Consistent with previous studies, this work found that spectrum skewness assuming only a single spectral peak was a good indicator of two hydrometeor populations (for example, cloud and drizzle particles) being present in the radar pulse volume. Yet, after dividing the spectrum into multiple peaks, velocity spectrum skewness for individual peaks is near zero, indicating nearly symmetric peaks. This suggests that future studies should use velocity skewness of single-peak spectra as an indicator of possible multiple hydrometeor populations and then use multiple-peak moments for quantitative studies. Three future activities will continue this work. First, KAZR spectra from several ARM sites have been processed and are available in the ARM archive as a principal investigator (PI) product. ARM programmers are evaluating these processing methods as part of future multiple-peak products generated by ARM. Third, MATLAB code generating the Oliktok Point products has been uploaded as supplemental material for public dissemination.

47 OTHER INSTRUMENTATION↗
NASA NTRS1981

Multichannel scanning radiometer for remote sensing cloud physical parameters

A multichannel scanning radiometer developed for remote observation of cloud physical properties is described. Consisting of six channels in the near infrared and one channel in the thermal infrared, the instrument can observe cloud physical parameters such as optical thickness, thermodynamic phase, cloud top altitude, and cloud top temperature. Measurement accuracy is quantified through flight tests on the NASA CV-990 and the NASA WB-57F, and is found to be limited by the harsh environment of the aircraft at flight altitude. The electronics, data system, and calibration of the instrument are also discussed.

Curran, R. J.↗
NASA NTRS2016

Cloud Regimes as a Tool for Systematic Study of Various Aerosol-Cloud-Precipitation Interactions

Systematic changes of clouds and precipitation are notoriously difficult to ascribe to aerosols. This presentation will showcase yet one more attempt to at least credibly detect the signal of aerosol-cloud-precipitation interactions. We surmise that the concept of cloud regimes (CRs) is appropriate to conduct such an investigation. Previous studies focused on what we call here dynamical CRs, and while we continue to adopt those too for our analysis, we have found that a different way of organizing cloud systems, namely via microphysical regimes is also promising. Our analysis relies on MODIS Collection 6 Level-3 data for clouds and aerosols, and TRMM-TMPA data for precipitation. The regimes are derived by applying clustering analysis on MODIS joint histograms, and once each grid cell is assigned a regime, aerosol and precipitation data can be spatiotemporally matched and composited by regime. The composites of various cloud and precipitation variables for high (upper quartile of distribution) and low (lower quartile) aerosol loadings can then be contrasted. We seek evidence of aerosol effects both in regimes with large fractions of deep ice-rich clouds, as well as regimes where low liquid phase clouds dominate. Signals can be seen, especially when the analysis is broken by land-ocean and when additional filters are applied, but there are of course caveats which will be discussed.

cloud regimes↗
DOE OSTI2024

Impacts of Synoptic-Scale Dynamics on Clouds and Radiation in High Southern Latitudes

High-latitudinal mixed-phase clouds significantly affect Earth's radiative balance. Observations of cloud and radiative properties from two field campaigns in the Southern Ocean and Antarctica were compared with two global climate model simulations. A cyclone compositing method was used to quantify “dynamics-cloud-radiation” relationships relative to the extratropical cyclone centers. Observations show larger asymmetry in cloud and radiative properties between western and eastern sectors at McMurdo compared with Macquarie Island. Most observed quantities at McMurdo are higher in the western (i.e., post-frontal) than the eastern (frontal) sector, including cloud fraction, liquid water path (LWP), net surface shortwave and longwave radiation (SW and LW), except for ice water path (IWP) being higher in the eastern sector. Here, the two models were found to overestimate cloud fraction and LWP at Macquarie Island but underestimate them at McMurdo Station. IWP is consistently underestimated at both locations, both sectors, and in all seasons. Biases of cloud fraction, LWP, and IWP are negatively correlated with SW biases and positively correlated with LW biases. The persistent negative IWP biases may have become one of the leading causes of radiative biases over the high southern latitudes, after correcting the underestimation of supercooled liquid water in the older model versions. By examining multi-scale factors from cloud microphysics to synoptic dynamics, this work will help increase the fidelity of climate simulations in this remote region.

58 GEOSCIENCES↗
DOE OSTI2024

Simulating Mixed‐Phase Open Cellular Clouds Observed During COMBLE: Evaluation of Parameterized Turbulence Closure

Marine cold-air outbreaks, or CAOs, are airmass transformations whereby relatively cold boundary layer (BL) air is transported over relatively warm water. To more deeply understand BL and mixed-phase cloud properties during CAO conditions, the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) took place from late 2019 into early 2020. During COMBLE, the U.S. Department of Energy's first Atmospheric Radiation Measurement Mobile Facility (AMF1) was deployed to Andenes, Norway, far downstream (~1,000 km) from the Arctic pack ice. This study examines the two most intense CAOs sampled at the AMF1 site. The observed BL structures are open cellular with high (~3–5 km) and cold (–30 to –50 °C) cloud tops, and they often have pockets of high liquid water paths (LWPs; up to ~1,000 g m –2 ) associated with strong updrafts and enhanced turbulence. We use a high-resolution mesoscale model to explore how well four turbulence closure methods represent open cellular clouds. After applying a radar simulator to model outputs for direct evaluation, cloud top properties agree well with AMF1 observations (within ~10%), but radar reflectivity and LWP agreement is more variable. Results suggest that the turbulent Prandtl number may play an important role for the simulated BL and cloud properties. All simulations produce enhanced precipitation rates that are well-correlated with a cloud transition. Finally, the eddy-diffusivity/mass-flux approach produces the deepest cloud layer and therefore the largest and most coherent cellular structures. Furthermore, we recommend the use of a non-local turbulence closure approach to better capture turbulent processes in intense CAOs.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Spitzer Phase Curves of KELT-1b and the Signatures of Nightside Clouds in Thermal Phase Observations

We observed two full orbital phase curves of the transiting brown dwarf KELT-1b, at 3.6 and 4.5μm, using the Spitzer Space Telescope. Combined with previous eclipse data from Beatty et al., we strongly detect KELT-1b’s phase variation as a single sinusoid in both bands, with amplitudes of 964±36 ppm at 3.6μm and 979±54 ppm at 4.5μm, and confirm the secondary eclipse depths measured by Beatty et al. We also measure noticeable eastward hotspot offsets of 28°.4±3°.5 at 3.6μm and 18°.6±5°.2 at 4.5μm. Both the day–night temperature contrasts and the hotspot offsets we measure are in line with the trends seen in hot Jupiters, though we disagree with the recent suggestion of an offset trend by Zhang et al. Using an ensemble analysis of Spitzer phase curves, we argue that nightside clouds are playing a noticeable role in modulating the thermal emission from these objects, based on:(1)the lack of a clear trend in phase offsets with equilibrium temperature,(2)the sharp day–night transitions required to have non-negative intensity maps, which also resolves the inversion issues raised by Keating& Cowan,(3)the fact that all the nightsides of these objects appear to be at roughly the same temperature of1000 K, while the dayside temperatures increase linearly with equilibrium temperature, and(4)the trajectories of these objects on a Spitzer color–magnitude diagram, which suggest colors only explainable via nightside clouds.

Hot Jupitors↗
DOE OSTI2023

The fully coupled regionally refined model of E3SM version 2: overview of the atmosphere, land, and river results

Abstract. This paper provides an overview of the United States (US) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2 (E3SMv2) fully coupled regionally refined model (RRM) and documents the overall atmosphere, land, and river results from the Coupled Model Intercomparison Project 6 (CMIP6) DECK (Diagnosis, Evaluation, and Characterization of Klima) and historical simulations – a first-of-its-kind set of climate production simulations using RRM. The North American (NA) RRM (NARRM) is developed as the high-resolution configuration of E3SMv2 with the primary goal of more explicitly addressing DOE's mission needs regarding impacts to the US energy sector facing Earth system changes. The NARRM features finer horizontal resolution grids centered over NA, consisting of 25→100 km atmosphere and land, a 0.125∘ river-routing model, and 14→60 km ocean and sea ice. By design, the computational cost of NARRM is ∼3× of the uniform low-resolution (LR) model at 100 km but only ∼ 10 %–20 % of a globally uniform high-resolution model at 25 km. A novel hybrid time step strategy for the atmosphere is key for NARRM to achieve improved climate simulation fidelity within the high-resolution patch without sacrificing the overall global performance. The global climate, including climatology, time series, sensitivity, and feedback, is confirmed to be largely identical between NARRM and LR as quantified with typical climate metrics. Over the refined NA area, NARRM is generally superior to LR, including for precipitation and clouds over the contiguous US (CONUS), summertime marine stratocumulus clouds off the coast of California, liquid and ice phase clouds near the North Pole region, extratropical cyclones, and spatial variability in land hydrological processes. The improvements over land are related to the better-resolved topography in NARRM, whereas those over ocean are attributable to the improved air–sea interactions with finer grids for both atmosphere and ocean and sea ice. Some features appear insensitive to the resolution change analyzed here, for instance the diurnal propagation of organized mesoscale convective systems over CONUS and the warm-season land–atmosphere coupling at the southern Great Plains. In summary, our study presents a realistically efficient approach to leverage the fully coupled RRM framework for a standard Earth system model release and high-resolution climate production simulations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Assessment of Two Stochastic Cloud Subcolumn Generators Using Observed Fields of Vertically Resolved Cloud Extinction

We evaluate two stochastic subcolumn generators used in GCMs to emulate subgrid cloud variability enabling comparisons with satellite observations and simulations of certain physical processes. Our evaluation necessitated the creation of a reference observational dataset that resolves horizontal and vertical cloud variability. The dataset combines two CloudSat cloud products that resolve two-dimensional cloud optical depth variability of liquid, ice, and mixed phase clouds when blended at ~200 m vertical and ~ 2 km horizontal scales. Upon segmenting the dataset to individual “scenes”, mean profiles of the cloud fields are passed as input to generators that produce scene-level cloud subgrid variability. The assessment of generator performance at the scale of individual scenes and in a mean sense is largely based on inferred joint histograms that partition cloud fraction within predetermined combinations of cloud top pressure –cloud optical thickness ranges. Our main finding is that both generators tend to underestimate optically thin clouds, while one of them also tends to overestimate some cloud types of moderate and high optical thickness. Associated radiative flux errors are also calculated by applying a simple transformation to the cloud fraction histogram errors, and are found to approach values almost as high as 3 Wm-2 for the cloud radiative effect in the shortwave part of the spectrum.

cloud variability↗
NASA NTRSDate not supplied

Machine Learning Application for Improving Cloud Detection and Phase Determination Over Sunglint Regions for Geostationary Satellites

Cloud detection and phase determination over sunglint regions has been a challenge, especially for geostationary (GEO) satellites. Sunglint is observed when the sunlight specular reflection is at the same viewing angle of the satellite sensor. This intense reflection in the visible channels (VIS) is often comparable to that from optically thick clouds. It also contaminates the shortwave infrared channels (SWIR). Consequently, VIS and SWIR channels become less useful - or not useful- when they are saturated, hampering the detection of cloudy and clear-sky pixels. Sunglint contamination happens frequently and exists nearly in every daytime GEO full disk satellite images. However, sunglint intensity and region are difficult to model due to variable viewing geometry and ocean surface conditions. Moreover, existing physical models do not meet the accuracy required for operational GEO satellite cloud detection. We developed a machine learning algorithm to improve cloud detection in sunglint conditions for the NASA Langley’s Satellite ClOud and radiation Property retrieval System (SatCORPS). This poster presents our recent progress in the algorithm development, validation and applications. The algorithm is validated using collocated SatCORPS GOES-East and GOES-West cloud products. We demonstrate that the machine learning cloud detection in sunglint regions is superior to the traditional approach by improving temporal consistency between sunglint and non-sunglint conditions.

Machine Learning, Cloud detection, Sunglint, SatCO↗
DOE OSTI2020

Cloud–Aerosol–Turbulence Interactions: Science Priorities and Concepts for a Large-Scale Laboratory Facility

The purpose of this meeting summary, therefore, is to outline the range of scientific questions, and the facility concepts that were explored.We began the workshop with a series of overview talks to highlight scientific questions that could be investigated in a large-scale aerosol-cloud-turbulence laboratory facility. Topics included warm and mixed-phase cloud microphysics, aerosol and cloud chemistry, atmospheric turbulence, radiative transfer, cloud/aerosol instrumentation, and remote sensing. There was ample time for questions and discussion following each overview presentation. We also broke into groups for several hours at various points to enable more active discussion among all participants.

54 ENVIRONMENTAL SCIENCES↗