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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.

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At least 505 records · Page 28

PACE Microphysical Aerosol Properties from Polarimetry (PACE-MAPP)

We present the Plankton, Aerosols, Clouds and Ecosystems Microphysical Aerosol Properties from Polarimetry (PACE-MAPP) polarimetric remote sensing algorithm developed for the newly launched NASA PACE satellite observing system. The objective of PACE-MAPP is to retrieve detailed fine-mode (marine, pollution and smoke) and coarse-mode (sea-salt and dust) aerosol properties over the ocean for a range of light to heavy aerosol loadings using PACE’s polarimetric-imaging capabilities at multiple angles and wavelengths from the ultraviolet (UV) to the near-infrared (NIR). An additional objective for PACE-MAPP is to discriminate aerosols from thin clouds. The PACE-MAPP polarimetric remote sensing retrieval algorithm uses coupled atmosphere-ocean vector radiative transfer, optimal estimation, artificial intelligence and powerful inherent optical property look-up-tables for the Earth’s aerosol, cloud, and hydrosol particles. PACE-MAPP is the only retrieval algorithm designed to invert aerosol/ocean products using both polarimeters onboard PACE. We present results using PACE-MAPP to retrieve aerosol and ocean remote sensing products from measurements by the Hyper-Angular Rainbow Polarimeter #2 (HARP2) and Spectro-polarimeter for Planetary Exploration one (SPEXone) polarimeter instruments onboard PACE.

Snorre Stamnes↗

Three Years of Airborne Observations During NASA Activate: A Statistical Summary of Chemical, Optical, and Microphysical Aerosol Properties Over the Western North Atlantic Ocean

Airborne observations are critical to understanding Earth’s climate system and surface-level air quality by providing both spatial and vertical information that is not possible through ground measurement networks or satellite observations. Airborne platforms allow assessments of long-range transport, vertical redistribution, boundary-layer dynamics, and cloud-aerosol-interactions that are critical to model evaluation and satellite validation. Still, the high cost and effort of aircraft operations can limit measurement campaigns to short, focused time periods. Multiple deployments are often necessary for seasonal comparisons, and results can be limited if target phenomenon are infrequent. Subsequent analyses typically focus on case studies, especially if deployment conditions are climatologically anomalous. The NASA ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment) mission was designed to overcome these limitations by operating semi-continuously over multiple months during multiple seasons. Flight plans were intentionally simple, repetitive, and systematic to provide a statistically robust dataset that could be utilized similarly to a ground-network. Here, we present an overview of three years (2020-2022) of aerosol measurements from the NASA HU-25 Falcon aircraft supporting the ACTIVATE mission. Data from 179 flights were considered, the majority of which were based at NASA Langley Research Center and flown locally over the Wester North Atlantic Ocean just east of Hampton, VA, USA. Airmass characteristics tended to transition from continental outflow near the coast to mostly marine over the open ocean. Seasonal, diurnal, spatial, and vertical trends in aerosol microphysical, optical, and chemical properties are discussed in the context of synoptic scale meteorology. Statistical benefits of the ACTIVATE sampling strategy are discussed with regard to future model evaluation.

Luke D Ziemba↗

Karhunen-Loeve expansion analysis of uncertainties in cloud microphysical property retrievals

Here, this study proposes a methodology of quantifying uncertainties for cloud retrievals on model resolution to facilitate the comparison with model outputs. Primary component analysis is applied to reduce the dimension of random variables (up to a factor of 50) and reveal the cross correlations in the input data, making large sampling computationally feasible and uncertainty quantification accurate and reliable. Our approach has the capability of parameterizing input uncertainties and attributing the uncertainties in the retrieval output to each individual source, which allows sensitivity analysis of cloud retrieval algorithms and provides directions for improving observation instruments as well as strategies. We applied the method to characterize uncertainties in cloud ice water content (IWC) retrieved from the DOE Atmospheric Radiation Measurement (ARM) programs baseline cloud microphysical retrieval algorithm (MICROBASE). We test it with a selected ice cloud case observed on 9 March 2000 at the ARM Southern Great Plains site during its 2000 cloud intensive observing period. The test results indicate that (1) uncertainties in the output retrieved by MICROBASE are comparable amongst different retrievals; (2) The mean values obtained by our UQ method are closer to the aircraft data with less errors compared to the direct ensemble average; (3) Ice water path (IWP) generally incurred larger uncertainty in optically thin ice clouds and there was more variability in vertical in the retrieved IWC; and (4) Uncertainties in the output are mainly due to the interactions among different modes of ARM radar pro files.

54 ENVIRONMENTAL SCIENCES↗

MODIS comparisons with northeastern Pacific in situ stratocumulus microphysics

Abstract Vertical sounding measurements within stratocumuli during two aircraft field campaigns, Marine Stratus/stratocumulus Experiment (MASE) and Physics of Stratocumulus Top (POST), are used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius ( r e ). In situ COT, LWP, and r e were calculated using 5 m vertically averaged droplet probe measurements of complete vertical cloud penetrations. MODIS COT, LWP, and r e 1 km pixels were averaged along these penetrations. COT comparisons in POST showed strong correlations and a near 1:1 relationship. In MASE, comparisons showed strong correlations; however, MODIS COT exceeded in situ COT, likely due to larger temporal differences between MODIS and in situ measurements. LWP comparisons between two cloud probes show good agreement for POST but not MASE, giving confidence to POST data. Both projects provided strong LWP correlations but MODIS exceeded in situ by 14–36%. MODIS in situ r e correlations were strong, but MODIS 2.1 µm r e exceeded in situ r e , which contributed to LWP bias; in POST, MODIS r e was 20–30% greater than in situ r e . Maximum in situ r e near cloud top showed comparisons nearer 1:1. Other MODIS r e bands (3.7 µm and 1.6 µm) showed similar comparisons. Temporal differences between MODIS and in situ measurements, airplane speed differences, and cloud probe artifacts were likely causes of weaker MASE correlations. POST COT comparison was best for temporal differences under 20 min. POST data validate MODIS COT but it also implies a positive MODIS r e bias that propagates to LWP while still capturing variability.

54 ENVIRONMENTAL SCIENCES↗

Untangling Dynamical and Microphysical Controls for the Structure of Stratocumulus

Stratocumulus clouds that are an important component of the Earth climate system can exhibit diverse structures, from solid decks to broken cloud fields with strikingly different abilities to reflect solar radiation. Amazingly, these different cloud formations can occur within the same or nearly the same environment, as evident by a common presence of pockets of open cells surrounded by overcast areas. These intriguing features not only provide for spectacular satellite images, but also present a challenge for climate models striving to predict the correct cloud amount. While open cells have been linked to the presence of precipitation and low droplet concentrations, complete understanding of the many complex and interacting processes leading to their formation is lacking. Here we show that the structure of stratocumulus can be linked to two timescales: an updraft timescale, t_up, and a precipitation initiation timescale, t_r. When drizzle is initiated within updrafts (t_r ≤ t_up), cloud water in the outflow is depleted enough that an overcast cloud cannot be sustained. Using a simple parcel model, we relate these timescales to three observable parameters (droplet number concentration, Nc, cloud depth, H, and updraft speed, w) and derive a functional representation for this relationship. Well-documented observed and simulated cases of open and closed cell stratocumulus fit well into the classification based on our model.

climate↗

Coastal-Fog Microphysics Using In-Situ Observations and GOES-R Retrievals

Here, the objective of this work is to evaluate GOES-R based fog conditions occurred during the C-FOG (Toward Improving Coastal Fog Prediction) field campaign. C-FOG is designed to advance understanding of fog formation, development, and dissipation over coastal environments to improve its predictability. The project took place along coastlines and open water environments of Eastern Canada (Nova Scotia, NS and the Island of Newfoundland, NL) during August-October of 2018 where environmental conditions play an important role for late season’s fog formation. During the C-FOG field campaign, instruments were located at the Ferryland Supersite, NL, with 2 main sites, and five satellite sites, as well as on the Research Vessel (R/V) Hugh R. Sharp. Key measurement instruments included a Gondola carrying a CDP (cloud droplet probe) and a BCP (backscatter cloud probe) was used for measuring droplet spectra from 1-75 µm on the R/V. A LPM (laser precipitation monitor) with 100 µm-1 cm size range and an OPC (optical particle counter) with 0.3-17 µm at 16 spectral channels provided information for fog and drizzle discrimination. Remote sensing platforms (e.g. profiling microwave radiometer, PMWR), Ceilometer, Lidar), meteorological towers, tethered balloons, and GOES-R products (e.g. fog coverage and droplet size and liquid water path) were used to evaluate fog over horizontal and vertical dimensions. Results suggest that effective radius, phase, liquid water path, and liquid water content values obtained from GOES-R and PMWR were comparable to ground based in-situ observations. It is concluded that integration of observations and nowcasting products may help improve short term local fog predictions.

54 ENVIRONMENTAL SCIENCES↗

Aerosol variability, synoptic‐scale processes, and their link to the cloud microphysics over the northeast Pacific during MAGIC

Abstract Shipborne aerosol measurements collected from October 2012 to September 2013 along 36 transects between the port of Los Angeles, California (33.7°N, 118.2°), and Honolulu, Hawaii (21.3°N, 157.8°W), during the Marine ARM GPCI (Global Energy and Water Cycle Experiment (GEWEX)‐Cloud System Study (GCSS)‐Pacific Cross‐section Intercomparison) Investigation of Clouds campaign are analyzed to determine the circulation patterns that modulate the synoptic and monthly variability of cloud condensation nuclei (CCN) in the boundary layer. Seasonal changes in CCN are evident, with low magnitudes during autumn/winter, and high CCN during spring/summer accompanied with a characteristic westward decrease. CCN monthly evolution is consistent with satellite‐derived cloud droplet number concentration N d from the Moderate Resolution Imaging Spectroradiometer. One‐point correlation ( r ) analysis between the 1000 hPa zonal wind time series over a region between 125°W and 135°W, 35°N and 45°N, and the N d field yields a negative r (up to −0.55) over a domain that covers a zonal extent of at least 20° from the California shoreline, indicating that N d decreases when the zonal wind intensifies. The negative r expands southwestward as the zonal wind precedes N d by up to 3 days, suggesting a transport mechanism from the coast of North America mediated by the California low‐coastal jet, which intensifies in summer when the aerosol concentration and N d reach a maximum. A first assessment of aerosol‐cloud interaction (ACI) is performed by combining CCN and satellite N d values from the Fifteenth Geostationary Operational Environmental Satellite. The CCN‐ N d correlation is 0.66–0.69, and the ACI metric defined as ACI = ∂ln( N d )/∂ln(CCN) is high at 0.9, similar to other aircraft‐based studies and substantially greater than those inferred from satellites and climate models.

Painemal, David↗