Coordinated Unmanned Aircraft System (UAS) and Ground-Based Weather Measurements to Predict Lagrangian Coherent Structures (LCSs)

Concentrations of airborne chemical and biological agents from a hazardous release are not spread uniformly. Instead, there are regions of higher concentration, in part due to local atmospheric flow conditions which can attract agents. We equipped a ground station and two rotary-wing unmanned aircraft systems (UASs) with ultrasonic anemometers. Flights reported here were conducted 10 to 15 m above ground level (AGL) at the Leach Airfield in the San Luis Valley, Colorado as part of the Lower Atmospheric Process Studies at Elevation—a Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE) campaign in 2018. The ultrasonic anemometers were used to collect simultaneous measurements of wind speed, wind direction, and temperature in a fixed triangle pattern; each sensor was located at one apex of a triangle with ∼100 to 200 m on each side, depending on the experiment. A WRF-LES model was used to determine the wind field across the sampling domain. Data from the ground-based sensors and the two UASs were used to detect attracting regions (also known as Lagrangian Coherent Structures, or LCSs), which have the potential to transport high concentrations of agents. This unique framework for detection of high concentration regions is based on estimates of the horizontal wind gradient tensor. To our knowledge, our work represents the first direct measurement of an LCS indicator in the atmosphere using a team of sensors. Our ultimate goal is to use environmental data from swarms of sensors to drive transport models of hazardous agents that can lead to real-time proper decisions regarding rapid emergency responses. The integration of real-time data from unmanned assets, advanced mathematical techniques for transport analysis, and predictive models can help assist in emergency response decisions in the future

Comprehensive characterization of an aspen (<i>Populus tremuloides</i>) leaf litter sample that maintained ice nucleation activity for 48 years

Decaying vegetation was determined to be a potentially important source of atmospheric ice nucleation particles (INPs) in the early 1970s. The bacterium Pseudomonas syringae was the first microorganism with ice nucleation activity (INA) isolated from decaying leaf litter in 1974. However, the ice nucleation characteristics of P. syringae are not compatible with the characteristics of leaf litter-derived INPs since the latter were found to be sub-micron in size, while INA of P. syringae depends on much larger intact bacterial cells. Here we determined the cumulative ice nucleation spectrum and microbial community composition of the historic leaf litter sample 70-S-14 collected in 1970 that conserved INA for 48 years. The majority of the leaf litter-derived INPs were confirmed to be sub-micron in size and to be sensitive to boiling. Culture-independent microbial community analysis only identified Pseudomonas as potential INA. Culture-dependent analysis identified one P. syringae isolate, two isolates of the bacterial species Pantoea ananatis, and one fungal isolate of Mortierella alpina as having INA among 1170 bacterial colonies and 277 fungal isolates, respectively. Both Pa. ananatis and M. alpina are organisms that produce heat-sensitive sub-micron INPs. They are thus both likely sources of the INPs present in sample 70-S-14 and may represent important terrestrial sources of atmospheric INPs, a conclusion that is in line with other recent results obtained in regard to INPs from soil, precipitation, and the atmosphere.</p

Birch leaves and branches as a source of ice-nucleating macromolecules

Birch pollen are known to release ice-nucleating macromolecules (INM), but little is known about the production and release of INM from other parts of the tree. We examined the ice nucleation activity of samples from 10 different birch trees (Betula spp.). Samples were taken from nine birch trees in Tyrol, Austria, and from one tree in a small urban park in Vienna, Austria. Filtered aqueous extracts of 30 samples of leaves, primary wood (new branch wood, green in colour, photosynthetically active), and secondary wood (older branch wood, brown in colour, with no photosynthetic activity) were analysed in terms of ice nucleation activity using VODCA (Vienna Optical Droplet Crystallization Analyser), a cryo microscope for emulsion samples. All samples contained ice-nucleating particles in the submicron size range. Concentrations of ice nuclei ranged from 6.7×104 to 6.1×109&thinsp;mg−1 sample. Mean freezing temperatures varied between −15.6 and −31.3&thinsp;°C; the range of temperatures where washes of birch pollen and dilutions thereof typically freeze. The freezing behaviour of three concentrations of birch pollen washing water (initial wash, 1&thinsp;:&thinsp;100, and 1&thinsp;:&thinsp;10&thinsp;000) were significantly associated with more than a quarter of our samples, including some of the samples with highest and lowest activity. This indicates a relationship between the INM of wood, leaves, and pollen. Extracts derived from secondary wood showed the highest concentrations of INM and the highest freezing temperatures. Extracts from the leaves exhibited the highest variation in INM and freezing temperatures. Infrared spectra of the extracts and tested birch samples show qualitative similarity, suggesting the chemical components may be broadly similar.</p

Data Generated during the 2018 LAPSE-RATE Campaign: An Introduction and Overview

Unmanned aircraft systems (UASs) offer innovative capabilities for providing new perspectives on the atmosphere, and therefore atmospheric scientists are rapidly expanding their use, particularly for studying the planetary boundary layer. In support of this expansion, from 14 to 20 July 2018 the International Society for Atmospheric Research using Remotely piloted Aircraft (ISARRA) hosted a community flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE; de Boer et al., 2020a). This field campaign spanned a 1-week deployment to Colorado\u27s San Luis Valley, involving over 100 students, scientists, engineers, pilots, and outreach coordinators. These groups conducted intensive field operations using unmanned aircraft and ground-based assets to develop comprehensive datasets spanning a variety of scientific objectives, including a total of nearly 1300 research flights totaling over 250 flight hours. This article introduces this campaign and lays the groundwork for a special issue on the LAPSE-RATE project. The remainder of the special issue provides detailed overviews of the datasets collected and the platforms used to collect them. All of the datasets covered by this special issue have been uploaded to a LAPSE-RATE community set up at the Zenodo data archive (https://zenodo.org/communities/lapse-rate/, last access: 3 December 2020)

Intercomparison of Small Unmanned Aircraft System (sUAS) Measurements for Atmospheric Science During the LAPSE-RATE Campaign

Small unmanned aircraft systems (sUAS) are rapidly transforming atmospheric research. With the advancement of the development and application of these systems, improving knowledge of best practices for accurate measurement is critical for achieving scientific goals. We present results from an intercomparison of atmospheric measurement data from the Lower Atmospheric Process Studies at Elevation—a Remotely piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. We evaluate a total of 38 individual sUAS with 23 unique sensor and platform configurations using a meteorological tower for reference measurements. We assess precision, bias, and time response of sUAS measurements of temperature, humidity, pressure, wind speed, and wind direction. Most sUAS measurements show broad agreement with the reference, particularly temperature and wind speed, with mean value differences of 1.6 ± 2.6 °C and 0.22 ± 0.59 m/s for all sUAS, respectively. sUAS platform and sensor configurations were found to contribute significantly to measurement accuracy. Sensor configurations, which included proper aspiration and radiation shielding of sensors, were found to provide the most accurate thermodynamic measurements (temperature and relative humidity), whereas sonic anemometers on multirotor platforms provided the most accurate wind measurements (horizontal speed and direction). We contribute both a characterization and assessment of sUAS for measuring atmospheric parameters, and identify important challenges and opportunities for improving scientific measurements with sUAS

Sources of increase in lowermost stratospheric sulphurous and carbonaceous aerosol background concentrations during 1999–2008 derived from CARIBIC flights

This study focuses on sulphurous and carbonaceous aerosol, the major constituents of particulate matter in the lowermost stratosphere (LMS), based on in situ measurements from 1999 to 2008. Aerosol particles in the size range of 0.08–2 µm were collected monthly during intercontinental flights with the CARIBIC passenger aircraft, presenting the first long-term study on carbonaceous aerosol in the LMS. Elemental concentrations were derived via subsequent laboratory-based ion beam analysis. The stoichiometry indicates that the sulphurous fraction is sulphate, while an O/C ratio of 0.2 indicates that the carbonaceous aerosol is organic. The concentration of the carbonaceous component corresponded on average to approximately 25% of that of the sulphurous, and could not be explained by forest fires or biomass burning, since the average mass ratio of Fe to K was 16 times higher than typical ratios in effluents from biomass burning. The data reveal increasing concentrations of particulate sulphur and carbon with a doubling of particulate sulphur from 1999 to 2008 in the northern hemisphere LMS. Periods of elevated concentrations of particulate sulphur in the LMS are linked to downward transport of aerosol from higher altitudes, using ozone as a tracer for stratospheric air. Tropical volcanic eruptions penetrating the tropical tropopause are identified as the likely cause of the particulate sulphur and carbon increase in the LMS, where entrainment of lower tropospheric air into volcanic jets and plumes could be the cause of the carbon increase

Phylogenomic analysis of a 55.1 kb 19-gene dataset resolves a monophyletic Fusarium that includes the Fusarium solani Species Complex

Scientific communication is facilitated by a data-driven, scientifically sound taxonomy that considers the end-user¿s needs and established successful practice. In 2013, the Fusarium community voiced near unanimous support for a concept of Fusarium that represented a clade comprising all agriculturally and clinically important Fusarium species, including the F. solani species complex (FSSC). Subsequently, this concept was challenged in 2015 by one research group who proposed dividing the genus Fusarium into seven genera, including the FSSC described as members of the genus Neocosmospora, with subsequent justification in 2018 based on claims that the 2013 concept of Fusarium is polyphyletic. Here, we test this claim and provide a phylogeny based on exonic nucleotide sequences of 19 orthologous protein-coding genes that strongly support the monophyly of Fusarium including the FSSC. We reassert the practical and scientific argument in support of a genus Fusarium that includes the FSSC and several other basal lineages, consistent with the longstanding use of this name among plant pathologists, medical mycologists, quarantine officials, regulatory agencies, students, and researchers with a stake in its taxonomy. In recognition of this monophyly, 40 species described as genus Neocosmospora were recombined in genus Fusarium, and nine others were renamed Fusarium. Here the global Fusarium community voices strong support for the inclusion of the FSSC in Fusarium, as it remains the best scientific, nomenclatural, and practical taxonomic option availabl

Local finite-time Lyapunov exponent, local sampling and probabilistic source and destination regions

The finite-time Lyapunov exponent (FTLE) is a powerful Lagrangian concept widely used for describing large-scale flow patterns and transport phenomena. However, field experiments usually have modest scales. Therefore, it is necessary to bridge the gap between the concept of FTLE and field experiments. In this paper, two independent observations are discussed: (i) approximation of the local FTLE time series at a fixed location as a function of known distances between the destination (or source) points of released (or collected) particles and local velocity, and (ii) estimation of the distances between the destination (or source) points of the released (or collected) particles when consecutive release (or sampling) events are performed at a fixed location. These two observations lay the groundwork for an ansatz methodology that can practically assist in field experiments where consecutive samples are collected at a fixed location, and it is desirable to attribute source locations to the collected particles, and also in planning of optimal local sampling of passive particles for maximal diversity monitoring of atmospheric assemblages of microorganisms. In addition to deterministic flows, the more realistic case of unresolved turbulence and low-resolution flow data that yield probabilistic source (or destination) regions are studied. It is shown that, similar to deterministic flows, Lagrangian coherent structures (LCS) and local FTLE can describe the separation of probabilistic source (or destination) regions corresponding to consecutively collected (or released) particles

Small fluctuations in the recovery of fusaria across consecutive sampling intervals with unmanned aircraft 100 m above ground level

Abstract The aerobiology of fungi in the genus Fusarium is poorly understood. Recent work has highlighted the role of Lagrangian coherent structures (LCSs) in the movement of fusaria in the lower atmosphere. Here, we extend this work by examining the relationship between the length of atmospheric sampling intervals with autonomous unmanned aerial vehicles (UAVs) and the recovery of fusaria. UAVs were equipped with an array of eight microbesampling devices with four &apos;&apos;inner&apos;&apos; sampling arms and four &apos;&apos;outer&apos;&apos; sampling arms. Each set of arms was used to collect consecutive aerobiological samples during 10 min sampling periods at 100 m above ground level at the Kentland Farm in Blacksburg, Virginia. Fifty-one flights (102 consecutive sampling intervals) were conducted in 2010 and 2011. A correlation analysis showed that the counts of fusaria did not vary between the inner and outer sampling arms from consecutive sampling period of 10 min (r = 0.93, P \ 0.001), and the frequency of colony counts had similar distributions for samples from the inner and outer sampling arms. An analysis of the temporal variation in the collections of Fusarium showed that the similarity between collections decreased over time. This work supports the idea that atmospheric populations of fusaria are well mixed, and large changes in the recovery of fusaria in the lower atmosphere may be attributed to large-scale phenomena (e.g., LCSs) operating across varying temporal and spatial scales. This work may contribute to effective control measures for diseases causes by fusaria in the future