Large spatiotemporal variability in aerosol properties over central Argentina during the CACTI field campaign
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Engineering topics
Publications and source records attributed to Tomlinson, Jason.
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In this campaign, Calibrator for Airborne Aerosol Probes (CAAP), Mesa Photonics provided its U.S. Department of Energy (DOE) Small Business Innovation Research (SBIR) Phase II prototype of a portable, battery-powered monodisperse aerosol/droplet generator to field-calibrate two aerosol/cloud characterization instruments deployed on the DOE Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF) ArcticShark uncrewed aerial system (UAS) during the flight campaign conducted at ARM’s Southern Great Plains (SGP) atmospheric observatory and the Blackwell-Tonkawa airfield (Oklahoma) in May 2024. The CAAP campaign (May 20-24, 2024) partially overlapped with the main ARM AAF campaign, Turbulent Layers Promoting New Particle Formation (NPFTURBULENCE, May 7-27, 2024, Gannet Hallar, principal investigator). The main goal of the CAAP campaign was field validation of calibration of aerosol and cloud probes deployed on the ArcticShark UAS. The campaign also provided an opportunity to test and evaluate the Mesa Photonics’ monodisperse aerosol/droplet generator prototype in the field, under real-life operational conditions.
Accurate airborne aerosol instrumentation is required to determine the spatial distribution of ambient aerosol particles, particularly when dealing with the complex vertical profiles and horizontal variations of atmospheric aerosols. A versatile water-based condensation particle counter (vWCPC) has been developed to provide aerosol concentration measurements under various environments with the advantage of reducing the health and safety concerns associated with using butanol or other chemicals as the working fluid. However, the airborne deployment of vWCPCs is relatively limited due to the lack of characterization of vWCPC performance at reduced pressures. Given the complex combinations of operating parameters in vWCPCs, modeling studies have advantages in mapping vWCPC performance. In this work, we thoroughly investigated the performance of a laminar-flow vWCPC using COMSOL Multiphysics® simulation coupled with MATLAB™. We compared it against a modified vWCPC (vWCPC model 3789, TSI, Shoreview, MN, USA). Our simulation determined the performance of particle activation and droplet growth in the vWCPC growth tube, including the supersaturation, $D$ p,kel,0 (smallest size of particle that can be activated), $D$ p,kel,50 (particle size activated with 50 % efficiency) profile, and final growth particle size D d under wide operating temperatures, inlet pressures $P$ (30–101 kPa), and growth tube geometry (diameter $D$ and initiator length $L$ ini ). The effect of inlet pressure and conditioner temperature on vWCPC 3789 performance was also examined and compared with laboratory experiments. The COMSOL simulation result showed that increasing the temperature difference (Δ$T$) between conditioner temperature $T$ con and initiator $T$ ini will reduce $D$ p,kel,0 and the cut-off size $D$ p,kel,50 of the vWCPC. In addition, lowering the temperature midpoint ($T$ mid = $\frac{T_{con}+T_{ini}}{2}$ increases the supersaturation and slightly decreases the $D$ p,kel . The droplet size at the end of the growth tube is not significantly dependent on raising or lowering the temperature midpoint but significantly decreases at reduced inlet pressure, which indirectly alters the vWCPC empirical cut-off size. Our study shows that the current simulated growth tube geometry ($D$=6.3 mm and $L$ ini =30 mm) is an optimized choice for current vWCPC flow and temperature settings. The current simulation can more realistically represent the $D$ p,kel for 7 nm vWCPC and also achieved good agreement with the 2 nm setting. Using the new simulation approach, we provide an optimized operation setting for the 7 nm setting. This study will guide further vWCPC performance optimization for applications requiring precise particle detection and atmospheric aerosol monitoring.
Cloud droplet number concentration (N d ) is crucial for understanding aerosol-cloud interactions (ACI) and associated radiative effects. We present evaluations of four ground-based N d retrievals based on comprehensive datasets from the Atmospheric Radiation Measurements (ARM) Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. The N d retrieval methods use ARM ENA observatory ground-based remote sensing observations from a Micropulse lidar, Raman lidar, cloud radar, and the ARM NDROP Value-added Product (VAP), all of which also retrieve cloud effective radius (r e ). The retrievals are compared against aircraft measurements from the Fast-Cloud Droplet Probe (FCDP) and the Cloud and Aerosol Spectrometer (CAS) obtained from low-level marine boundary layer clouds on 12 flight days during summer and winter seasons. Additionally, the in situ measurements are used to validate the assumptions and characterizations used in the retrieval algorithms. Statistical comparisons of the probability distribution function (PDF) of the N d and cloud r e retrievals with aircraft measurements demonstrate that these retrievals align well with in situ measurements for overcast clouds, but they may substantially differ for broken clouds or clouds with low liquid water path (LWP). The retrievals are applied to four years of ground-based remote sensing measurements of overcast marine boundary layer clouds at the ARM ENA observatory to find that N d (r e ) values exhibit seasonal variations, with higher (lower) values during the summer season and lower (higher) values during the winter season. The ensemble of various retrievals using different measurements and retrieval algorithms such as those in this paper can help to quantify N d retrieval uncertainties and identify reliable N d retrieval scenarios. Of the retrieval methods, we recommend using the using the Micropulse lidar-based method given its good agreement with in situ measurements, it has less sensitivity to issues arising from precipitation and low cloud LWP/optical depth, and it has broad applicability by functioning for both day and nighttime conditions.
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During the Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA), a variety of in situ optical sensors using shadow imaging, scattering and holography were deployed by the Atmospheric Radiation Measurement (ARM) Aerial Facility to determine cloud properties. Taking advantage of the wide, overlapping range of instrumentation, we compare in situ cloud data from several different measurement methods for droplets up to 100 µm. Further, data processing was tailored to the encountered conditions, leading to good agreement. Improvements include noise reduction for holography and better out-of-focus correction for shadow imaging. Comparison between direct liquid water content measurements and optical sensors showed better agreement at higher droplet number concentrations (>120/cm 3 ).
This dataset contains high resolution image products (orthomosaics) acquired from midsized uncrewed aerial systems, which have been processed for value added quality. The instrument itself, a multispectral imager, the Altum by Micasense, captures 6 spectral bands (red, green blue, NIR, red edge, and LWIR/thermal1) as radiance, which is converted to reflectance. The code used to develop these images first uses tools from the Micasense python library2 to apply dark level corrections, row gradient corrections, and radiometric corrections. Next it uses the processing API from Agisoft Metashape software to align and mosaic the processed imagery, following the processes developed by the USGS' structure from motion workflow documentation3. Captures at different altitudes (recorded in MSL) produce an orthomosaic, a tif image containing information related to the 6 spectral bands, and a digital elevation model (DEM), a tif image containing information related to the elevation of the surveyed terraine. Metadata included in every image can be used to extract lat, lon, and reflectance values. 1https://www.arm.gov/publications/tech_reports/handbooks/doe-sc-arm-tr-281.pdf 2https://micasense.github.io/imageprocessing/MicaSense%20Image%20Processing%20Setup.html 3https://pubs.usgs.gov/of/2021/1039/ofr20211039.pdf
With their extensive coverage, marine low clouds greatly impact global climate. Presently, marine low clouds are poorly represented in global climate models, and the response of marine low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The Eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary layer clouds, whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. In addition, the ENA is periodically impacted by continental aerosols, making it an excellent location to study the cloud condensation nuclei (CCN) budget in a remote marine region periodically perturbed by anthropogenic emissions, and to investigate the impacts of long-range transport of aerosols on remote marine clouds. The Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) campaign was motivated by the need of comprehensive in-situ measurements for improving the understanding of marine boundary layer CCN budget, cloud and drizzle microphysics, and the impact of aerosol on marine low cloud and precipitation. The airborne deployments took place from June 21 to July 20, 2017 and January 15 to February 18, 2018 in the Azores. The flights were designed to maximize the synergy between in-situ airborne measurements and ongoing long-term observations at a ground site. Here we present measurements, observation strategy, meteorological conditions during the campaign, and preliminary findings. Lastly, we discuss future analyses and modeling studies that improve the understanding and representation of marine boundary layer aerosols, clouds, precipitation, and the interactions among them.
Aerosol-cloud interactions remain uncertain in assessing climate change. While anthropogenic activities produce copious aerosol nanoparticles smaller than 10 nanometers, they are too small to act as efficient cloud condensation nuclei (CCN). The mechanisms responsible for particle growth to CCN-relevant sizes are poorly understood. Here, we present aircraft observations of rapid growth of anthropogenic nanoparticles downwind of an isolated metropolis in the Amazon rainforest. Model analysis reveals that the sustained particle growth to CCN sizes is predominantly caused by particle-phase diffusion-limited partitioning of semivolatile oxidation products of biogenic hydrocarbons. Cloud-resolving numerical simulations show that the enhanced CCN concentrations in the urban plume substantially alter the formation of shallow convective clouds, suppress precipitation, and enhance the transition to deep convective clouds. The proposed nanoparticle growth mechanism, expressly enabled by the abundantly formed semivolatile organics, suggests an appreciable impact of anthropogenic aerosols on cloud life cycle in previously unpolluted forests of the world.
Capturing the vertical profiles and horizontal variations of atmospheric aerosols often requires accurate airborne measurements. With the advantage of avoiding health and safety concerns related to the use of butanol or other chemicals, water-based condensation particle counters have emerged to provide measurements under various environments. However, airborne deployments are relatively rare due to the lack of instrument characterization under reduced pressure at flight altitudes. This study investigates the performance of a commercial “versatile” water-based condensation particle counter (vWCPC, model 3789, TSI, Shoreview, MN, USA) under various ambient pressure conditions (500–920 hPa) with a wide range of particle total number concentrations (1500–70 000 cm -3 ). The effect of conditioner temperature on vWCPC 3789 performance at low pressure is examined through numerical simulation and laboratory experiments. We show that the default instrument temperature setting of 30 °C for the conditioner is not suitable for airborne measurement and that the optimal conditioner temperature for low-pressure operation is 27°. Under the optimal conditioner temperature (27°), the 7 nm cut-off size is also maintained. Additionally, we show that insufficient droplet growth becomes more significant under the low-pressure operation. The counting efficiency of the vWCPC 3789 can vary up to 20 % for particles of different chemical compositions (e.g., ammonium sulfate and sucrose particles). However, such variation is independent of pressure.
ARM Aerial Facility (AAF) - Unmanned Aircraft Systems, Infrared Thermometer: Sky brightness temperature
Air temperature and relative humidity recorded by the ARM Aerial Facility (AAF) - Unmanned Aircraft Systems
ARM Aerial Facility (AAF) - Unmanned Aircraft Systems CO2/H2O Analyzer
Data collected from aircraft, with lat/log/alt, and some qc
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