Engineering topics

Schmitt, Carl

Publications and source records attributed to Schmitt, Carl.

4 records

DOE OSTI2024

The Abundance and Sources of Ice Nucleating Particles Within Alaskan Ice Fog

Abstract The Alaskan Layered Pollution and Chemical Analysis (ALPACA) field campaign included deployment of a suite of atmospheric measurements in January–February 2022 with the goal of better understanding atmospheric processes and pollution under cold and dark conditions in Fairbanks, Alaska. We report on measurements of particle composition, particle size, ice nucleating particle (INP) composition, and INP size during an ice fog period (29 January–3 February). During this period, coarse particulate matter (PM 10 ) concentrations increased by 150% in association with a decrease in air temperature, a stronger temperature inversion, and relatively stagnant conditions. Results also show a 18%–78% decrease in INPs during the ice fog period, indicating that particles had activated into the ice fog via nucleation. Peroxide and heat treatments performed on INPs indicated that, on average, the largest contributions to the INP population were heat‐labile (potentially biological, 63%), organic (31%), then inorganic (likely dust, 6%). Measurements of levoglucosan and bulk and single‐particle composition corroborate the presence of dust and aerosols from combustion sources. Heat‐labile and organic INPs decreased during the peak period of the ice fog, indicating those were preferentially activated, while inorganic INPs increased, suggesting they remained as interstitial INPs. In general, INP concentrations were unexpectedly high in Fairbanks compared to other locations in the Arctic during winter. The fact that these INPs likely facilitated ice fog formation in Fairbanks has implications for other high latitude locations subject to the hazards associated with ice fog.

Meteorology & Atmospheric Sciences↗

DOE OSTI2022

Fog particle concentrations

ngVIPS metadata and caveats: Column 1: Time, seconds after midnight UTC of beginning of time period. (60 sec values) Column 2: Relative concentration. Notes: Concentration values are observed values and assume ~4.0 m/s wind speed. (#/cm^3) Caveats: Observed particles with a very few exceptions were on the order of a few pixels (less than 10 microns). The size differential was insufficient to determine a particle size distribution. As the temperatures were relatively warm (and it can be 10C warmer inside the instrument) it is anticipated that some solid ice particles could have melted and some smaller liquid drops could have evaporated. A cyclic nature to the high resolution data was observed and determined to be caused by a focus issue. Each 60 second period included ~25 images. Particles are collected on a glass disk, but the disk isn't perfectly centered causing small particles to be slightly out of focus during part of the rotation. For that reason, we chose to report the average of the five highest values in a time period rather the average of all values. Higher resolution can be made available upon request, but a conversation with the PI would be important to fully understand the planned usage and if the higher resolution data were to be useful for the task. Please contact instrument PI, Carl Schmitt (naturalsystemsresearch@gmail.com) with any questions about these data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Next-Generation Video Ice Particle Sampler Field Campaign Report

The next-generation video ice particle sampler (ngVIPS) was operated on the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s tethered balloon system (TBS) during the IFFExO (Ice Fog Field Experiment at Oliktok Point) project in November, 2020. The purpose of the project was to study ice fog microphysics and the environmental conditions during ice fog to enable better predictions during low-visibility conditions. This project was conducted at the site of the third ARM Mobile Facility (AMF3) at Oliktok Point, Alaska. Among a suite of other instruments, the ngVIPS was operated to observe atmospheric ice particles.

47 OTHER INSTRUMENTATION↗

NASA NTRS2005

Effective Radius of Ice Cloud Particle Populations Derived from Aircraft Probes

The effective radius(r(sub e)) is a crucial variable in representing the radiative properties of cloud layers in general circulation models. This parameter is proportional to the condensed water content (CWC) divided by the extinction (sigma). For ice cloud layers, parameterizations for r(sub e), have been developed from aircraft in-situ measurements 1) indirectly, using data obtained from particle spectrometer probes and assumptions or observations about particle shape and mass to get the ice water content (IWC) and area to get sigma, and recently 2) from probes that measure IWC and sigma directly. This study compares [IWC/sigma] derived from the two methods using data sets acquired from comparable instruments on two aircraft, one sampling clouds at mid-levels and the other at upper-levels during the CRYSTAL-FACE field program in Florida in 2002. The sigma and IWC derived by each method are compared and evaluated in different ways for each aircraft data set. Direct measurements of sigma exceed those derived indirectly by a factor of two to two and a half. The IWC probes, relying on ice sublimation, appear to measure accurately except when the IWC is high or the particles too large to sublimate completely during the short transit time through the probe. The IWC estimated from the particle probes are accurate when direct measurements are available to provide constraints and useful information in high IWC/large particle situations. Because of the discrepancy in sigma estimates between the direct and indirect approaches, there is a factor of 2 to 3 difference in [IWC/sigma] between them. Although there are significant uncertainties involved in its use, comparisons with several independent data sources suggest that the indirect method is the more accurate of the two approaches. However, experiments are needed to resolve the source of the discrepancy in sigma.

Heymsfield, Andrew J.↗