Field Campaign Research Articles

Development, optimization and validation of automated volatile organic compound data analysis using an on-line thermal desorption gas chromatograph with dual detection and application to measurements in ambient air

Because of their major role in indoor and outdoor air pollution, even at trace levels, VOCs are of great interest, and their monitoring requires sensitive analytical instruments. Several techniques are commonly used, such as portable sensors, Proton Transfer Reaction Mass Spectrometry (PTR-MS) and Thermal Desorption Gas Chromatography (TD-GC). The latter is widely used off- and on-line with Flame Ionization Detectors (FID) or Mass Spectrometers (MS). Given the large number of molecules detected per chromatogram, the data generated by these monitoring techniques are usually checked and reprocessed manually. This process is extremely time consuming and could result in human error. The challenge is to provide reliable results as quickly as possible.In this study, the performances of an on-line TD-GC system with dual detection FID and MS were tested. The Method Detection Limits (MDL), linearities and accuracies of 60 VOCs (alkanes, aromatics, oxygenated and halogenated) were calculated both for FID and MS detectors. The MDLs and accuracies ranged from 0.006 to 0.618 ppbv and from 77 % to 100 % for FID, and from 0.018 to 0.760 ppbv and from 80 % to 100 % for MS. Both detectors showed good complementarity and allowed the development of two programs to facilitate data analysis. These algorithms were designed to autonomously select optimal results between FID and MS detectors, and were evaluated for outdoor and indoor measurement conditions. Measuring VOCs in field campaigns is challenging, and it is anticipated that these programs could be extended to other types of dual-detector systems or for the comparison of data from different calibrated instruments.

Drone and ground-truth data collection, image annotation and machine learning: A protocol for coastal habitat mapping and classification

Aerial drone imaging is an efficient tool for mapping and monitoring of coastal habitats at high spatial and temporal resolution. Specifically, drone imaging allows for time- and cost-efficient mapping covering larger areas than traditional mapping and monitoring techniques, while also providing more detailed information than those from airplanes and satellites, enabling for example to differentiate various types of coastal vegetation. Here, we present a systematic method for shallow water habitat classification based on drone imagery. The method includes:•Collection of drone images and creation of orthomosaics.•Gathering ground-truth data in the field to guide the image annotation and to validate the final map product.•Annotation of drone images into – potentially hierarchical – habitat classes and training of machine learning algorithms for habitat classification.As a case study, we present a field campaign that employed these methods to map a coastal site dominated by seagrass, seaweed and kelp, in addition to sediments and rock. Such detailed but efficient mapping and classification can aid to understand and sustainably manage ecologically and valuable marine ecosystems.

High-resolution urban climate simulations for heat and health applications in Philadelphia

Stakeholders need high-resolution urban climate information for city planning and adaptation to climate risks. Climate models have too coarse a spatial resolution to properly represent cities at the relevant scale, and downscaled products often fail to account for urban effects. We propose here a methodological framework for producing high-resolution urban databases that are used to drive the SURFEX-TEB land surface and urban canopy models. A historical simulation is carried out over the period 1991–2020, based on a reanalysis of the city of Philadelphia (Pennsylvania, USA). The simulation is compared with observations outside and inside the city, as well as with a field campaign. The results show good agreement between the model and observations, with average summer biases of only −1 °C and + 0.8 °C for daily minimum and maximum temperatures outside the city, and almost none inside. The simulation is used to calculate the maximum daily heat index (HIX) and to study emergency heat alerts. The HIX is slightly overestimated and, consequently, the model simulates too many heat events if not bias corrected. Overall, HIX conditions at Philadelphia International Airport are found to be suitable proxies for city-wide summer conditions, and therefore are appropriate to use for emergency heat declarations.

Machine learning tool for wave overtopping prediction based on the safety-operability ratio

The phenomenon of wave overtopping affects both the safety of people and port facilities, as well as the operability of a port. This work aims to develop a predictive tool based on artificial intelligence to predict wave overtopping over a breakwater, and to reach a compromise between safeguarding people and port efficiency. The data used came from an extensive field campaign lasting 6.5 years. During this research, the overtopping events were recorded and integrated with the forecast data available from the Port. The model used is the random forest, which was applied with the metrics AUC-PR and F2 score to a weighted dataset. The validation results show a recall for alignments of 0.91 and 0.89, while in the test it reaches 0.94 and 0.95. The dangerousness of the wave overtopping was also analyzed, reducing the dangerous false negatives to 2 and to 14 in the two alignments studied. Operability per alignment was unnecessarily affected during validation by 4 and 10 days over 26.5 months, and in the test by 4 and 3 days over 6.5 months. The results show a proven tool with real data, capable of predicting wave overtopping, and a methodology that can be exported to other ports.

Unclassical Radical Generation Mechanisms in the Troposphere: A Review.

Hydroxyl (OH) and hydroperoxyl (HO2) radicals, collectively known as HOx radicals, are crucial in removing primary pollutants, controlling atmospheric oxidation capacity, and regulating global air quality and climate. An imbalance between radical observations and simulations has been identified based on radical closure experiments, a valuable tool for accessing the state-of-the-art chemical mechanisms, demonstrating a deviation between the existing and actual tropospheric mechanisms. In the past decades, researchers have attempted to explain this deviation and proposed numerous radical generation mechanisms. However, these newly proposed unclassical radical generation mechanisms have not been systematically reviewed, and previous radical-related reviews dominantly focus on radical measurement instruments and radical observations in extensive field campaigns. Herein, we overview the unclassical generation mechanisms of radicals, mainly focusing on outlining the methodology and results of radical closure experiments worldwide and systematically introducing the mainstream mechanisms of unclassical radical generation, involving the bimolecular reaction of HO2 and organic peroxy radicals (RO2), RO2 isomerization, halogen chemistry, the reaction of H2O with O2 over soot, epoxide formation mechanism, mechanism of electronically excited NO2 and water, and prompt HO2 formation in aromatic oxidation. Finally, we highlight the existing gaps in the current studies and suggest possible directions for future research. This review of unclassical radical generation mechanisms will help promote a comprehensive understanding of the latest radical mechanisms and the development of additional new mechanisms to further explain deviations between the existing and actual mechanisms.

Empowering London Primary School Communities to Know and Tackle Air Pollution Exposure

This study tested the effectiveness of participatory methods to engage primary school communities in London with air pollution issues to help them identify, understand, and reduce their air pollution exposure. Three primary schools with high pollution levels participated in environmental educational activities, including air quality workshops and field campaigns involving different methods, time schedules, and project scopes. Participants completed surveys before and after these activities to measure their understanding, perceptions, and behavior. After the workshops, students admitted feeling more skillful in monitoring air quality and confident in incorporating this education into daily life and teaching others. They shared their results with peers, school leadership, and the community and led campaigns to help design experiments, choose measurement locations, and reduce air pollution exposure in schools. The results showed increased concern about air pollution, a better understanding of its causes and impacts, and more reported reduction behaviors. An Air Pollution Exposure Index (APEI) was combined with participatory monitoring data to raise awareness and understanding among students on typical school-day exposure. Feedback indicates that the tool was useful in defining air pollution exposure status and identifying exposure risks. Overall, this study contributes to the evidence of the feasibility and impact of student-led environmental education interventions These interventions involve collecting personalized exposure data, co-planning mitigations with school community groups, and employing methods to raise awareness of air pollution and empower pupils to identify potential solutions and change behaviors.

The Response of Tropopause-Overshooting Convection over North America to Climate Change

Abstract Recent field campaigns, observational studies, and modeling work have demonstrated that extratropical tropopause-overshooting convection has a substantial, and previously underestimated impact on stratospheric water vapor concentrations. This necessitates improved understanding of how tropopause-overshooting convection will respond to a warming climate. A growing body of research indicates that environments conducive to severe thunderstorms will occur more often and be increasingly unstable in the future, but no study has examined how this may be related to increased overshooting. To rectify this, this study leverages an existing pseudo-global warming (PGW) experiment to evaluate potential future changes in tropopause-overshooting convection over North America. We examine two 10-year simulations consisting of (1) a retrospective period (2003 – 2012) forced by ERA-interim initial and boundary conditions (the control simulation), and (2) the same retrospective period with CMIP5 ensemble-mean high-end emission scenario climate changes added to the initial and boundary conditions (the PGW simulation). Tropopause-overshooting convection in the control simulation is validated against observed overshoots from both ground-based radar observations in the United States and GOES satellite observations over North America. The model is shown to effectively simulate the observed regional distribution, annual cycle, and diurnal cycle of tropopause-overshooting convection. The projected response of tropopause-overshooting convection in the PGW simulation is found to increase more than 250% across the model domain, and the projected seasonal period of frequent tropopause-overshooting convection is shown to extend into late-summer. Additionally, tropopause-overshooting convection with extreme tropopause-relative heights (> 4 km) are more frequent in a warmed climate scenario.

Multitemporal sentinel-1 SAR data sensitivity analysis at phenological growth stages of green gram

ABSTRACT This research investigated the green gram crop by employing a time series of Sentinel-1A Single Look Complex (SLC) and Sentinel-2 datasets, which corresponded to different phenological growth stages of the crop. Field campaigns were conducted on the acquisition dates of Sentinel-1A datasets for the entire crop cycle to estimate crop height and soil moisture. In line with these observations, temporal variations in 10 salient Synthetic Aperture Radar (SAR) parameters, obtained from Sentinel-1A datasets, are systematically analysed, which elucidated the importance of dual-polarized SAR parameters in the diverse phenological growth stages of the crop. Moreover, the Normalized Difference Vegetation Index (NDVI) values from Sentinel-2 datasets, estimated at various green gram growth stages, are categorized into initial (NDVI ≤ 0.5), intermediate (0.5 < NDVI < 0.8), and maximum growth of the crop (NDVI ≥ 0.8), which are then aligned with corresponding SAR and ground-measured parameters. The inversion model development and sensitivity analysis were carried out to correlate ground-measured parameters with SAR parameters across various growth stages based on the categorization of NDVI values as well as for the entire growing season of the crop. Backscattering intensities are found to have good sensitivity to crop height at its intermediate growth (r ≥ 0.75). Among vegetation indices, the Polarimetric Radar Vegetation Index (PRVI) showed significant sensitivity to crop height in its intermediate growth stage (r ≈ 0.77). H-A-Alpha decomposition parameters displayed notable sensitivity to soil moisture in the initial and maximum growth stages of green gram. This study demonstrates the effectiveness of Sentinel-1 dual-polarized SAR parameters in monitoring green gram phenological growth stages. The parameters show substantial sensitivity to both green gram height and soil moisture.

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

AbstractThe 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 (PM10) 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.

Overview of the MOSAiC expedition: Ecosystem

The international and interdisciplinary sea-ice drift expedition “The Multidisciplinary drifting Observatory for the Study of Arctic Climate” (MOSAiC) was conducted from October 2019 to September 2020. The aim of MOSAiC was to study the interconnected physical, chemical, and biological characteristics and processes from the atmosphere to the deep sea of the central Arctic system. The ecosystem team addressed current knowledge gaps and explored unknown biological properties over a complete seasonal cycle focusing on three major research areas: biodiversity, biogeochemical cycles, and linkages to the environment. In addition to the measurements of core properties along a complete seasonal cycle, dedicated projects covered specific processes and habitats, or organisms on higher taxonomic or temporal resolution in specific time windows. A wide range of sampling instruments and approaches, including sea-ice coring, lead sampling with pumps, rosette-based water sampling, plankton nets, remotely operated vehicles, and acoustic buoys, was applied to address the science objectives. Further, a broad range of process-related measurements to address, for example, productivity patterns, seasonal migrations, and diversity shifts, were made both in situ and onboard RV Polarstern. This article provides a detailed overview of the sampling approaches used to address the three main science objectives. It highlights the core sampling program and provides examples of habitat- or process-specific sampling. The initial results presented include high biological activities in wintertime and the discovery of biological hotspots in underexplored habitats. The unique interconnectivity of the coordinated sampling efforts also revealed insights into cross-disciplinary interactions like the impact of biota on Arctic cloud formation. This overview further presents both lessons learned from conducting such a demanding field campaign and an outlook on spin-off projects to be conducted over the next years.

Stratospheric Hydration Processes in Tropopause‐Overshooting Convection Revealed by Tracer‐Tracer Correlations From the DCOTSS Field Campaign

AbstractHydration of the stratosphere by tropopause‐overshooting convection has received increasing interest due to the extreme concentrations of water vapor that can result and, ultimately, the climate warming potential such hydration provides. Previous work has recognized the importance of numerous dynamic and physical processes that control stratospheric water vapor delivery by convection. This study leverages recent comprehensive observations from the NASA Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) field campaign to determine the frequency at which each process operates during real events. Specifically, a well‐established analysis technique known as tracer‐tracer correlation is applied to DCOTSS observations of ozone, water vapor, and potential temperature to identify the occurrence of known processes. It is found that approximately half of convectively‐driven stratospheric hydration samples show no indication of significant air mass transport and mixing, emphasizing the importance of ice sublimation to stratospheric water vapor delivery. Furthermore, the temperature of the upper troposphere and lower stratosphere environment and/or overshoot appears to be a commonly active constraint, since the approximate maximum possible water vapor concentration that can be reached in an air mass is limited to the saturation mixing ratio when ice is present. Finally, little evidence of relationships between dynamic and physical processes and their spatial distribution was found, implying that stratospheric water vapor delivery by convection is likely facilitated by a complex collection of processes in each overshooting event.

Evaluation of WRF-Chem air quality forecasts during the AEROMMA and STAQS 2023 field campaigns

ABSTRACT A real-time air quality forecasting system was developed using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to provide support for flight planning activities during the NOAA Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) and NASA Synergistic TEMPO Air Quality Science (STAQS) 2023 field campaigns. The forecasting system operated on two separate domains centered on Chicago, IL, and New York City, NY, and provided 72-hour predictions of atmospheric composition, aerosols, and clouds. This study evaluates the Chicago-centered forecasting system’s 1-, 2-, and 3-day ozone (O3) forecast skill for Chiwaukee Prairie, WI, a rural area downwind of Chicago that often experiences high levels of O3 pollution. Comparisons to vertical O3 profiles collected by a Tropospheric Ozone Lidar Network (TOLNet) instrument revealed that forecast skill decreases as forecast lead time increases. When compared to surface measurements, the forecasting system tended to underestimate O3 concentrations on high O3 days and overestimate on low O3 days at Chiwaukee Prairie regardless of forecast lead time. Using July 25, 2023, as a case study, analyses show that the forecasts underestimated peak O3 levels at Chiwaukee Prairie during this regionwide bad air quality day. Wind speed and direction data indicates that this underestimation can partially be attributed to lake breeze simulation errors. Surface fine particulate matter (PM2.5) measurements, Geostationary Operational Environmental Satellite-16 (GOES-16) aerosol optical depth (AOD) data, and back trajectories from the NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model show that transported Canadian wildfire smoke impacted the Lake Michigan region on this day. Errors in the forecasted chemical composition and transport of the smoke plumes also contributed to underpredictions of O3 levels at Chiwaukee Prairie on July 25, 2023. The results of this work help identify improvements that can be made for future iterations of the WRF-Chem forecasting system. Implications: Air quality forecasting is an important tool that can be used to inform the public about upcoming high pollution days so that individuals may plan accordingly to limit their exposure to health-damaging air pollutants. Forecasting also helps scientists make decisions about where to make observations during air quality field campaigns. A variety of observational datasets were used to evaluate the accuracy of an air quality forecasting system that was developed for NOAA and NASA field campaigns that occurred in the summer of 2023. These evaluations inform areas of improvement for future development of this air quality forecasting system.

Evaluation of near‐surface and boundary‐layer meteorological conditions that support cold‐fog formation using Cold Fog Amongst Complex Terrain field campaign observations

AbstractCold fog refers to a type of fog that forms when the temperature is below 0°C. It can be composed of liquid, ice, and mixed‐phase fog particles. Cold fog happens frequently over mountainous terrain in the cold season, but it is difficult to predict. Using observations from the Cold Fog Amongst Complex Terrain (CFACT) field campaign conducted in Heber Valley, Utah, in the western United States during January and February of 2022, this study investigates the meteorological conditions in the surface and boundary layers that support the formation of wintertime ephemeral cold fog in a local area of small‐scale mountain valleys. It is found that fog formation is susceptible to subtleties in forcing conditions and is supported by several factors: (1) established high pressure over the Great Basin with associated local clear skies, calm winds, and a stable boundary layer; (2) near‐surface inversion with saturation near the surface and strong moisture gradient in the boundary layer; (3) warm (above‐freezing) daytime air temperature with a large diurnal range, accompanied with warm soil temperatures during the daytime; (4) a period of increased turbulence kinetic energy (above 0.5 m2·s−2), followed by calm conditions throughout the fog's duration; and (5) supersaturation with respect to ice. Then, the field observations and identified supporting factors for fog formation were utilized to evaluate high‐resolution (˜400 m horizontal grid spacing) Weather Research and Forecasting (WRF) model simulations. Results show that the WRF model accurately simulates the mesoscale conditions facilitating cold‐fog formation but misses some critical surface and atmospheric boundary conditions. The overall results from this paper indicate that these identified factors that support fog formation are vital to accurately forecasting cold‐fog events. At the same time, they are also critical fields for the NWP model validation.

Measurements of Atmospheric HO2 Radicals Using Br-CIMS with Elimination of Potential Interferences from Ambient Peroxynitric Acid.

As a promising direct measurement method of atmospheric hydroperoxyl radicals (HO2), bromide chemical ionization mass spectrometry (Br-CIMS) has been first demonstrated by Sanchez et al. (Atmos. Meas. Tech. 2016, 9, 3851-3861). However, field application of this method is currently still sparse, and there is still a gap between measured HO2 concentrations and calculated ones derived from the atmospheric equilibrium between HO2 and peroxynitric acid (HO2NO2). In this work, we constructed an improved Br-CIMS with optimizations of custom-built front-end devices, chamber pressures, and instrumental voltages to achieve a 3σ detection limit of 0.5 ppt at an integration time of 60 s and a sensitivity of 1-3 cps ppt-1 under a total reagent ion signal of 0.2 MHz for HO2 detection. HO2NO2, a product from atmospheric reactions between HO2 and NO2, can also be detected by Br-CIMS, whose interference on the HO2 measurement was found but nearly eliminated by regulating key CIMS voltages to minimize the decomposition of (BrHO2NO2)- ions in the MS. In addition, a 2 week field campaign was carried out in urban Shanghai, demonstrating that the interference of HO2 from ambient HO2NO2 was less than 10% of the true HO2 signal under our optimized CIMS voltage setting. Our study suggests that Br-CIMS is a reliable technique for atmospheric HO2 measurements.

Mismanaged plastic waste as a predictor for river plastic pollution

Hydrometeorological processes are often assumed to be key drivers of plastic transport. However, the predominant focus on these factors overlooks the impact of anthropogenic factors, such as mismanaged plastic waste (MPW) on plastic transport variability. Here, we investigate the roles of both anthropogenic and hydrometeorological factors on plastic pollution in the Odaw catchment, Ghana. Data on macroplastic transport and density were collected at ten locations between December 2021 and December 2022. We tested for differences between the wet and dry seasons and applied a multiple regression analysis to examine the separate and combined impact of hydrometeorological variables (rainfall, discharge, and windspeed) on macroplastic transport. Additionally, we analyzed the spatial correlation in macroplastic transport/density with MPW and population density. Data collection involved visual counting of floating macroplastics at 10 river locations and counting litter at 9 riverbanks and land locations. Rainfall data was sourced from TAHMO (Trans-African Hydrometeorological Observatory), discharge was measured during field campaigns, and windspeed data sourced from a global climate data provider. We used globally modelled MPW estimates to represent anthropogenic factors. Contrary to previous studies, we found no seasonal differences in macroplastic pollution and only weak correlations were observed between the hydrometeorological variables and macroplastic transport. However, a strong correlation was observed between MPW and macroplastic pollution. We hypothesize that, the influence of hydrometeorological factors on macroplastic transport depend on the relative impact of anthropogenic factors. Our research highlights the limited role of hydrometeorology, showing the significant role of mismanaged plastic waste to field monitored macroplastic pollution variability in the catchment. This insight is essential for future research as it highlights the importance of holistically investigating both anthropogenic and hydrometeorological factors in explaining plastic transport and retention dynamics. This insight is essential for developing interventions that effectively address plastic pollution in catchments.

Integrated Water Field Campaign (NASA)

Integrated Water Field Campaign (NASA)

Changes in the suspended floc properties by bed erosion in a macrotidal muddy flat: Case of Asan Bay, Korea

Intertidal flats have closely connected sediment transport systems with tidal channels. The properties of suspended sediments derived by horizontal advection and local erosion were examined under various current and wave. A field campaign was conducted over two weeks (October 17–31, 2021) in the Asan intertidal flat. Suspended sediments were in the form of flocs, which are clumps of particles, with an average floc size (davg) of 70–275 μm. The maximum current velocity and water level at each tidal cycle continuously decreased from 0.19 to 0.04 m s−1 and from 5 to 2 m, respectively. In accordance with the hydrodynamic conditions, continuous decrease in davg from spring to neap tides was superimposed by flood-ebb variations in davg. Geological heterogeneity between channels and flats can be significantly influenced by tide and wind conditions. Under tide-dominant conditions, the spring tidal current was strong enough to transport macroflocs with davg of 200–500 μm into the intertidal flats. The grown macroflocs up to 1.6 times of davg at early flood tide were deposited in the flats during the slack tide and transported back to the channels by ebb tidal current. Under wind-dominant conditions, the suspended flocs originated primarily from the bed by erosion. The deposited macroflocs or microflocs were entrained into water column and transported to adjacent tidal channel as microflocs or flocculi. The structure of the advected flocs had more varied density in the range of 42–147 kg m−3, compared to the eroded flocs. Under severe erosion, the structure of suspended flocs was similar to that of advected flocs despite their smaller size. This suggests that bed erosion supplied more porous flocs into the water column than those transported by advection. Consequently, the intertidal flats are at an increased risk of erosion due to the diverse structure of flocs.

Remote Sensing Applied to Pasture Monitoring: A Review

Objective: The goal of this study was to review the results obtained by various authors for large-scale pasture monitoring via remote sensing; to monitor the development and degradation conditions of pastures according to case studies; and to analyze data, images, and Geographic Information System (GIS) procedures in relevant works. Theoretical Framework: In this topic, the principles that guided the literature review are presented, including a discussion of the search for remote sensing results related to pastures in large geographical areas, and case studies in works that denote the technological potential from field sampling and results worldwide are also presented. Method: Research methods associated with different themes, keywords, and regions were adopted to identify results from research in the area of remote sensing applied to surveying the conditions of pastures in the different typologies in the studied regions. Results and Discussion: The literature review in this study highlights the advances and methodologies developed for the evaluation of pasture conditions and mapping, from which it was possible to observe the stage of degradation of this vegetation, which is essential for agricultural production. Research Implications: The potential of using remote sensing materials and mechanisms for pasture assessment, mapping areas in stages of degradation and identifying vegetation vigor is highly valuable in large-scale pasture management. The presented literature indicates that pasture vegetation varies greatly according to geographic region, indicating great complexity in deriving its phenological conditions and showing that field campaigns are essential for the description and establishment of a relationship between the foliar canopy and sensor response. Originality/Value: This literature review addresses large-scale remote sensing surveys of pastures, contributing to research on the conditions of this vegetation. The bibliography presented in this review can support studies on mapping the pasture degradation process through remote sensing images and data.

Airborne measurements of mesoscale divergence at high latitudes during HALO-(AC)3

Abstract Boundary layer cloud transformations at high latitudes play a key role for the Arctic climate and are partially controlled by large-scale dynamics such as subsidence. While measuring large- and mesoscale divergence on spatial scales on the order of 100 km has proven notoriously difficult, recent airborne campaigns in the subtropics have successfully applied measurement techniques using multiple dropsonde releases in circular flight patterns. In this paper it is shown that this method can also be effectively applied at high latitudes, in spite of the considerable differences in atmospheric dynamics compared to the subtropics. To show the applicability, data collected during the airborne HALO-(AC)3 field campaign near Svalbard in Spring 2022 were analysed, where several flight patterns involving multiple dropsonde launches were realized by two aircraft. This study presents a first overview of the results. We find that the method indeed yields reliable estimates of mesoscale gradients in the Arctic, producing robust vertical profiles of horizontal divergence and consequently, subsidence. Sensitivity to aspects of the method is investigated, including dependence on sampling area and the divergence calculation.

Wave-driven current and vortex patterns at an open beach: Insights from phase-resolving numerical computations and Lagrangian measurements

Wave-driven currents have a substantial impact on local circulation patterns in and across the surf zone, and are responsible for cross-shore and longshore exchange of mass and momentum over a broad range of spatial and temporal scales. Nearshore currents may drive sediment transport, lead to beach erosion, and also affect the spread of bacteria and other marine microorganisms, as well as the distribution of pollutants such as chemicals and microplastics. In addition, surf zone currents can cause hazardous conditions for beach-goers in the form of rip currents.It is known from previous work (Chen et al., 2003; Feddersen et al., 2011; Hally-Rosendahl and Feddersen, 2016) that Boussinesq-type models in combination with appropriate boundary conditions and wave breaking capabilities can function as powerful tools for the analysis of circulation patterns in the surf zone. In the present work, data from a recent field campaign reported on in Bjørnestad et al. (2021) are used to further validate the capability of Boussinesq systems to simulate nearshore dynamics.The numerical model is then used to study the influence of tidal elevation, peak direction and directional spread of the incoming wavefield on the quantity, extent, and circulatory magnitude of the nearshore circulation. In addition, fundamental features such as horizontal eddies are investigated, and comparisons are made to solid-body rotation and irrotational vortices.Overall, it is observed that local variations in the bathymetry across the surf zone are the controlling factor regarding the size of these circulations, and an increasing tidal level, which can be seen as a uniform offset to the bathymetry, favors the generation of larger vortex patterns. For a given tidal stage, the directional spread of the incoming wavefield has the most pronounced influence on the size and strength of the nearshore eddies while the peak direction has the strongest effect on the total number of circulations.