View angle dependence of MODIS liquid water path retrievals in warm oceanic clouds

We investigated the view angle dependence of domain mean Moderate Resolution Imaging Spectroradiometer (MODIS) liquid water path (LWP) and that of corresponding cloud optical thickness, effective radius, and liquid cloud fraction as proxy for plane-parallel retrieval biases. Independent Advanced Microwave Scanning Radiometer–EOS LWP was used to corroborate that the observed variations with sun-view geometry were not severely affected by seasonal/latitudinal changes in cloud properties. Microwave retrievals showed generally small (<10%) cross-swath variations. The view angle (cross-swath) dependence of MODIS optical thickness was weaker in backscatter than forward scatter directions and transitioned from mild ∩ shape to stronger ∪ shape as heterogeneity, sun angle, or latitude increased. The 2.2 µm effective radius variations always had a ∪ shape, which became pronounced and asymmetric toward forward scatter in the most heterogeneous clouds and/or at the lowest sun. Cloud fraction had the strongest and always ∪-shaped view angle dependence. As a result, in-cloud MODIS cloud liquid water path (CLWP) showed surprisingly good view angle (cross-swath) consistency, usually comparable to that of microwave retrievals, due to cancelation between optical thickness and effective radius biases. Larger (20–40%) nadir-relative increases were observed in the most extreme heterogeneity and sun angle bins, that is, typically in the polar regions, which, however, constituted only 3–8% of retrievals. The good consistency of MODIS in-cloud CLWP was lost for gridbox mean LWP, which was dominated by the strong cloud fraction increase with view angle. More worryingly, MODIS LWP exhibited significant and systematic absolute increases with heterogeneity and sun angle that is not present in microwave LWP

A cloud detection neural network for above-aircraft clouds using airborne cameras

For aerosol, cloud, land, and ocean remote sensing, the development of accurate cloud detection methods, or cloud masks, is extremely important. For airborne passive remotesensing, it is also important to identify when clouds are above the aircraft since their presence contaminates the measurements of nadir-viewing passive sensors. We describe the development of a camera-based approach to detecting clouds above the aircraft via a convolutional neural network called the cloud detection neural network (CDNN). We quantify the performance of this CDNN using human-labeled validation data where we report 96% accuracy in detecting clouds in testing datasets for both zenith viewing and forward-viewing models. We present results from the CDNN based on airborne imagery from the NASA Aerosol Cloud meteorology Interactions oVer the western Atlantic Experiment (ACTIVATE) and the Clouds, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex). We quantify the ability of the CDNN to identify the presence of clouds above the aircraft using a forward-looking camera mounted inside the aircraft cockpit compared to the use of an all-sky upward-looking camera that is mounted outside the fuselage on top of the aircraft. We assess our performance by comparing the flight-averaged cloud fraction of zenith and forward CDNN retrievals with that of the prototype hyperspectral total-diffuse Sunshine Pyranometer (SPN-S) instrument’s cloud optical depth data. A comparison of the CDNN with the SPN-S on time-specific intervals resulted in 93% accuracy for the zenith viewing CDNN and 84% for the forward-viewing CDNN. The comparison of the CDNNs with the SPN-S on flight-averaged cloud fraction resulted in an agreement of .15 for the forward CDNN and .07 for the zenith CDNN. For CAMP2Ex, 53% of flight dates had above-aircraft cloud fraction above 50%, while for ACTIVATE, 52% and 54% of flight dates observed above-aircraft cloud fraction above 50% for 2020 and 2021, respectively. The CDNN enables cost-effective detection of clouds above the aircraft using an inexpensive camera installed in the cockpit for airborne science research flights where there are no dedicated upward-looking instruments for cloud detection, the installation of which requires time-consuming and expensive aircraft modifications, in addition to added mission cost and complexity of operating additional instruments

Wintertime Synoptic Patterns of Midlatitude Boundary Layer Clouds Over the Western North Atlantic: Climatology and Insights From In Situ ACTIVATE Observations

The synoptic evolution of boundary layer clouds over the western North Atlantic is described by means of a regime classification based on Self-Organizing Maps. The analysis is able to capture events with low and high low-cloud coverage. High-cloud coverage days are associated with cold-air outbreaks (CAOs). The combination of cold and dry conditions gives rise to an enhancement of surface heat fluxes during CAO, consistent with an increase in cloud fraction. In addition, prevailing winds during CAO days explain the occurrence of a synoptic maximum in cloud droplet number concentration, linked to transport of continental aerosol over the ocean. Overall, the dynamics of midlatitude low clouds substantially differ from archetypal stratocumulus clouds regimes

Large-Eddy Simulations of Marine Boundary Layer Clouds Associated with Cold-Air Outbreaks during the ACTIVATE Campaign. Part I: Case Setup and Sensitivities to Large-Scale Forcings

ABSTRACT: Large-eddy simulation (LES) is able to capture key boundary layer (BL) turbulence and cloud processes. Yet, large-scale forcing and surface turbulent fluxes of sensible and latent heat are often poorly prescribed for LESs. We derive these quantities from measurements and reanalysis obtained for two cold-air outbreak (CAO) events during Phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) in February–March 2020. We study the two contrasting CAO cases by performing LES and test the sensitivity of BL structure and clouds to large-scale forcings and turbulent heat fluxes. Profiles of atmospheric state and large-scale divergence and surface turbulent heat fluxes obtained from ERA5 data agree reasonably well with those derived from ACTIVATE field measurements for both cases at the sampling time and location. Therefore, we adopt the time-evolving heat fluxes, wind, and advective tendencies profiles from ERA5 data to drive the LES. We find that large-scale thermodynamic advective tendencies and wind relaxations are important for the LES to capture the evolving observed BL meteorological states characterized by the hourly ERA5 data and validated by the observations. We show that the divergence (or vertical velocity) is important in regulating the BL growth driven by surface heat fluxes in LESs. The evolution of liquid water path is largely affected by the evolution of surface heat fluxes. The liquid water path simulated in LES agrees reasonably well with the ACTIVATE measurements. This study paves the path to investigate aerosol–cloud–meteorology interactions using LES informed and evaluated by ACTIVATE field measurements

Spatially-coordinated airborne data and complementary products for aerosol, gas, cloud, and meteorological studies: The NASA ACTIVATE dataset

The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol-cloud-meteorology interactions. An HU-25 Falcon and King Air conducted systematic and spatially coordinated flights over the northwest Atlantic Ocean. This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes

Evolution of an Atmospheric Kármán Vortex Street From High‐Resolution Satellite Winds: Guadalupe Island Case Study

Vortex streets formed in the stratocumulus‐capped wake of mountainous islands are the atmospheric analogues of the classic Kármán vortex street observed in laboratory flows past bluff bodies. The quantitative analysis of these mesoscale unsteady atmospheric flows has been hampered by the lack of satellite wind retrievals of sufficiently high spatial and temporal resolution. Taking advantage of the cutting‐edge Advanced Baseline Imager, we derived kilometer‐scale cloud‐motion winds at 5‐min frequency for a vortex street in the lee of Guadalupe Island imaged by Geostationary Operational Environmental Satellite‐16. Combined with Moderate Resolution Imaging Spectroradiometer data, the geostationary imagery also provided accurate stereo cloud‐top heights. The time series of geostationary winds, supplemented with snapshots of ocean surface winds from the Advanced Scatterometer, allowed us to capture the wake oscillations and measure vortex shedding dynamics. The retrievals revealed a markedly asymmetric vortex decay, with cyclonic eddies having larger peak vorticities than anticyclonic eddies at the same downstream location. Drawing on the vast knowledge accumulated about laboratory bluff body flows, we argue that the asymmetric island wake arises from the combined effects of Earth's rotation and Guadalupe's nonaxisymmetric shape resembling an inclined flat plate at low angle of attack. However, numerical simulations will need to establish whether or not the selective destabilization of the shallow atmospheric anticyclonic eddies is caused by the same mechanisms that destabilize the deep columnar anticyclones of laboratory flows, such as three‐dimensional vertical perturbations due to centrifugal or elliptical instabilities

On assessing ERA5 and MERRA2 representations of cold-air outbreaks across the Gulf Stream

Author Posting. © American Geophysical Union, 2021. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 48(19), (2021): e2021GL094364, https://doi.org/10.1029/2021GL094364.The warm Gulf Stream sea surface temperatures strongly impact the evolution of winter clouds behind atmospheric cold fronts. Such cloud evolution remains challenging to model. The Gulf Stream is too wide within the ERA5 and MERRA2 reanalyses, affecting the turbulent surface fluxes. Known problems within the ERA5 boundary layer (too-dry and too-cool with too strong westerlies), ascertained primarily from ACTIVATE 2020 campaign aircraft dropsondes and secondarily from older buoy measurements, reinforce surface flux biases. In contrast, MERRA2 winter surface winds and air-sea temperature/humidity differences are slightly too weak, producing surface fluxes that are too low. Reanalyses boundary layer heights in the strongly forced winter cold-air-outbreak regime are realistic, whereas late-summer quiescent stable boundary layers are too shallow. Nevertheless, the reanalysis biases are small, and reanalyses adequately support their use for initializing higher-resolution cloud process modeling studies of cold-air outbreaks.This work was supported by NASA grant 80NSSC19K0390 to ACTIVATE, a NASA Earth Venture Suborbital-3 (EVS-3) investigation funded by NASA's Earth Science Division and managed through the Earth System Science Pathfinder Program Office. The Pacific Northwest National Laboratory (PNNL) is operated for the US Department of Energy (DOE) by Battelle Memorial Institute under Contract DE-AC06-76RLO 1830.2022-03-0

Large-Eddy Simulations of Marine Boundary Layer Clouds Associated with Cold-Air Outbreaks during the ACTIVATE Campaign. Part I: Case Setup and Sensitivities to Large-Scale Forcings

Large-eddy simulation (LES) is able to capture key boundary layer (BL) turbulence and cloud processes. Yet, large-scale forcing and surface turbulent fluxes of sensible and latent heat are often poorly prescribed for LESs. We derive these quantities from measurements and reanalysis obtained for two cold-air outbreak (CAO) events during Phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) in February–March 2020. We study the two contrasting CAO cases by performing LES and test the sensitivity of BL structure and clouds to large-scale forcings and turbulent heat fluxes. Profiles of atmospheric state and large-scale divergence and surface turbulent heat fluxes obtained from ERA5 data agree reasonably well with those derived from ACTIVATE field measurements for both cases at the sampling time and location. Therefore, we adopt the time-evolving heat fluxes, wind, and advective tendencies profiles from ERA5 data to drive the LES. We find that large-scale thermodynamic advective tendencies and wind relaxations are important for the LES to capture the evolving observed BL meteorological states characterized by the hourly ERA5 data and validated by the observations. We show that the divergence (or vertical velocity) is important in regulating the BL growth driven by surface heat fluxes in LESs. The evolution of liquid water path is largely affected by the evolution of surface heat fluxes. The liquid water path simulated in LES agrees reasonably well with the ACTIVATE measurements. This study paves the path to investigate aerosol–cloud–meteorology interactions using LES informed and evaluated by ACTIVATE field measurements

Airborne HSRL-2 measurements of elevated aerosol depolarization associated with non-spherical sea salt

Airborne NASA Langley Research Center (LaRC) High Spectral Resolution Lidar-2 (HSRL-2) measurements acquired during the recent NASA Earth Venture Suborbital-3 (EVS-3) Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) revealed elevated particulate linear depolarization associated with aerosols within the marine boundary layer. These observations were acquired off the east coast of the United States during both winter and summer 2020 and 2021 when the HSRL-2 was deployed on the NASA LaRC King Air aircraft. During 20 of 63 total flight days, particularly on days with cold air outbreaks, linear particulate depolarization at 532 nm exceeded 0.15–0.20 within the lowest several hundred meters of the atmosphere, indicating that these particles were non-spherical. Higher values of linear depolarization typically were measured at 355 nm and lower values were measured at 1,064 nm. Several lines of evidence suggest that these non-spherical particles were sea salt including aerosol extinction/backscatter ratio (“lidar ratio”) values of 20–25 sr measured at both 355 and 532 nm by the HSRL-2, higher values of particulate depolarization measured at low (< 60%) relative humidity, coincident airborne in situ size and composition measurements, and aerosol transport simulations. The elevated aerosol depolarization values were not correlated with wind speed but were correlated with salt mass fraction and effective radius of the aerosol when the relative humidity was below 60%. HSRL-2 measured median particulate extinction values of about 20 Mm−1 at 532 nm associated with these non-spherical sea salt particles and found that the aerosol optical depth (AOD) contributed by these particles remained small (0.03–0.04) but represented on average about 30%–40% of the total column AOD. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) spaceborne lidar aerosol measurements during several cold air outbreaks and CALIOP retrievals of column aerosol lidar ratio using column AOD constraints suggest that CALIOP operational aerosol algorithms can misclassify these aerosols as dusty marine rather than marine aerosols. Such misclassification leads to ∼40–50% overestimates in the assumed lidar ratio and in subsequent retrievals of aerosol optical depth and aerosol extinction