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  • Establishing a Selection of Dust Event Case Studies for Regions in the Global South

    Abstract: Airborne dust is an essential component of climatological and biogeochemical processes. Blowing dust can adversely affect agriculture, transportation, air quality, sensor performance, and human health. Therefore, the accurate characterization and forecasting of dust events is a priority for air quality researchers and operational weather centers. While dust detection and prediction capabilities have evolved over the preceding decades, the weather modeling community must continue to improve the location and timing of individual dust event fore-casts, especially for extreme dust outbreaks. Accordingly, Researchers at the US Army Engineer Research and Development Center (ERDC) are establishing a series of reference case study events to enhance dust transport model development and evaluation. These case studies support ongoing research to increase the accuracy of simulated dust emissions, dust aerosol transport, and dust-induced hazardous air quality conditions. This report documents five new contributions to the reference inventory, including detailed assessments of dust storms from three regions with differing meteorological forcing regimes. Here, we examine two extreme dust episodes that affected India, a multiday berg wind event in southern Africa, a strong but short-lived dust plume from the Atacama Desert of Chile, and a narrow, isolated dust plume emanating from a dry lake bed in Patagonia.
  • Establishing a Series of Dust Event Case Studies for East Asia

    Abstract: Dust aerosols have a wide range of effects on air quality, health, land-management decisions, aircraft operations, and sensor data interpretations. Therefore, the accurate simulation of dust plume initiation and transport is a priority for operational weather centers. Recent advancements have improved the performance of dust prediction models, but substantial capability gaps remain when forecasting the specific location and timing of individual dust events, especially extreme dust outbreaks. Operational weather forecasters and US Army Engineer Research and Development Center (ERDC) researchers established a series of reference case study events to enhance dust transport model evaluation. These reference case studies support research to improve modeled dust simulations, including efforts to increase simulation accuracy on when and where dust is lofted off the ground, dust aerosols transport, and dust-induced adverse air quality issues create hazardous conditions downstream. Here, we provide detailed assessments of four dust events for Central and East Asia. We describe the dust-event lifecycle from onset to end (or when dust transports beyond the area of interest) and the synoptic and mesoscale environ-mental conditions governing the process. Analyses of hourly reanalysis data, spaceborne lidar and aerosol optical depth retrievals, upper-air soundings, true-color satellite imagery, and dust-enhanced false-color imagery supplement the discussions.
  • Microbial Activity in Dust-Contaminated Antarctic Snow

    Abstract: During weather events, particles can accumulate on the snow near the Pegasus ice and Phoenix compacted-snow Runways at the US McMurdo Station in Antarctica. The deposited particles melt into the surface, initially forming steep-sided holes, which can widen into patches of weak and rotten snow and ice. These changes negatively impact the ice and snow runways and snow roads trafficked by vehicles. To understand the importance of microbes on this process, we examined deposited dust particles and their microbial communities in snow samples collected near the runways. Snow samples were analyzed at the Cold Regions Research and Engineering Laboratory where we performed a respiration study to measure the microbial activity during a simulated melt, isolated microorganisms, examined particle-size distribution, and performed 16S rRNA gene sequencing. We measured higher levels of carbon dioxide production from a sample containing more dust than from a sample containing less dust, a finding consistent with viable dust-associated microbial communities. Additionally, eleven microorganisms were isolated and cultured from snow samples containing dust particles. While wind patterns and satellite images suggest that the deposited particles originate from nearby Black Island, comparisons of the particle size and chemical composition were inconclusive.
  • Application of a Satellite-Retrieved Sheltering Parameterization (v1.0) for Dust Event Simulation with WRF-Chem v4.1

    Abstract: Roughness features (e.g., rocks, vegetation, furrows) that attenuate wind flow over the soil surface can affect the magnitude and distribution of sediment transport in aeolian environments. Existing transport models often rely on vegetation attributes derived from static land use datasets or remotely sensed greenness indicators to incorporate sheltering effects on simulated particle mobilization. These approaches do not represent the 3D nature or spatiotemporal changes of roughness element sheltering and ignore the sheltering contribution of nonvegetation roughness features and brown vegetation common to dryland environments. We used an albedo-based sheltering parameterization in a dust transport modeling application of the Weather Research and Forecasting model with Chemistry (WRF-Chem). This method estimates sheltering effects on surface wind friction speeds and dust entrainment from the shadows cast by subgrid-scale roughness elements. We applied the albedo-derived drag partition to the Air Force Weather Agency (AFWA) dust emission module and studied simulated PM10 concentrations using the Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model as implemented in WRF-Chem v4.1. Our results demonstrate how dust transport simulation and forecasting with the AFWA dust module can be improved in vegetated drylands by calculating dust emission flux with surface wind friction speed from a drag partition treatment.
  • Establishing a Series of Dust Event Case Studies for North Africa

    Abstract: Dust aerosols often create hazardous air quality conditions that affect human health, visibility, agriculture, and communication in various parts of the world. While substantial progress has been made in dust-event simulation and hazard mitigation over the last several decades, accurately forecasting the spatial and temporal variability of dust emissions continues to be a challenge. This report documents an analysis of atmospheric conditions for a series of dust events in North Africa. The researchers highlight four analyzed events that occurred between January 2016 to present in the following locations: (1) the western Sahara Desert; (2) East Algeria and the Iberian Peninsula; (3) Chad-Bodélé Depression; (4) Algeria and Morocco. For each event, the researchers developed an overview of the general synoptic, mesoscale, and local environmental forcing conditions that controlled the event evolution and used a combination of available lidar data, surface weather observations, upper-air soundings, aerosol optical depth, and satellite imagery to characterize the dust conditions. These assessments will support downstream forecast model evaluation and sensitivity testing; however, the researchers also encourage broader use of these assessments as reference case studies for dust transport, air quality modeling, remote sensing, soil erosion, and land management research applications.
  • Simulating Environmental Conditions for Southwest United States Convective Dust Storms Using the Weather Research and Forecasting Model v4.1

    Abstract: Dust aerosols can pose a significant detriment to public health, transportation, and tactical operations through reductions in air quality and visibility. Thus, accurate model forecasts of dust emission and transport are essential to decision makers. While a large number of studies have advanced the understanding and predictability of dust storms, the majority of existing literature considers dust production and forcing conditions of the underlying meteorology independently of each other. Our study works towards filling this research gap by inventorying dust-event case studies forced by convective activity in the Desert Southwest United States, simulating select representative case studies using several configurations of the Weather Research and Forecasting (WRF) model, testing the sensitivity of forecasts to essential model parameters, and assessing overall forecast skill using variables essential to dust production and transport. We found our control configuration captured the initiation, evolution, and storm structure of a variety of convective features admirably well. Peak wind speeds were well represented, but we found that simulated events arrived up to 2 hours earlier or later than observed. Our results show that convective storms are highly sensitive to initialization time and initial conditions that can preemptively dry the atmosphere and suppress the growth of convective storms.
  • Implementation of an Albedo-Based Drag Partition into the WRF-Chem v4.1 AFWA Dust Emission Module

    ABSTRACT: Employing numerical prediction models can be a powerful tool for fore-casting air quality and visibility hazards related to dust events. However, these numerical models are sensitive to surface conditions. Roughness features (e.g., rocks, vegetation, furrows, etc.) that shelter or attenuate wind flow over the soil surface affect the magnitude and spatial distribution of dust emission. To aide in simulating the emission phase of dust transport, we used a previously published albedo-based drag partition parameterization to better represent the component of wind friction speed affecting the immediate soil surface. This report serves as a guide for integrating this parameterization into the Weather Research and Forecasting with Chemistry (WRF-Chem) model. We include the procedure for preprocessing the required input data, as well as the code modifications for the Air Force Weather Agency (AFWA) dust emission module. In addition, we provide an example demonstration of output data from a simulation of a dust event that occurred in the Southwestern United States, which incorporates use of the drag partition.
  • The AFWA Dust Emission Scheme for the GOCART Aerosol Model in WRF-Chem v3.8.1

    Abstract: Airborne particles of mineral dust play a key role in Earth’s climate system and affect human activities around the globe. The numerical weather modeling community has undertaken considerable efforts to accurately forecast these dust emissions. Here, for the first time in the literature, we thoroughly describe and document the Air Force Weather Agency (AFWA) dust emission scheme for the Georgia Institute of Technology–Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) aerosol model within the Weather Research and Forecasting model with chemistry (WRF-Chem) and compare it to the other dust emission schemes available in WRF-Chem. The AFWA dust emission scheme addresses some shortcomings experienced by the earlier GOCART-WRF scheme. Improved model physics are designed to better handle emission of fine dust particles by representing saltation bombardment. WRF-Chem model performance with the AFWA scheme is evaluated against observations of dust emission in southwest Asia and compared to emissions predicted by the other schemes built into the WRF-Chem GOCART model. Results highlight the relative strengths of the available schemes, indicate the reasons for disagreement, and demonstrate the need for improved soil source data.
  • Microscale Dynamics between Dust and Microorganisms in Alpine Snowpack

    ABSTRACT:  Dust particles carry microbial and chemical signatures from source regions to deposition regions. Dust and its occupying microorganisms are incorporated into, and can alter, snowpack physical properties including snow structure and resultant radiative and mechanical properties that in turn affect larger-scale properties, including surrounding hydrology and maneuverability. Microorganisms attached to deposited dust maintain genetic evidence of source substrates and can be potentially used as bio-sensors. The objective of this study was to investigate the impact of dust-associated microbial deposition on snowpack and microstructure. As part of this effort, we characterized the microbial communities deposited through dust transport, examined dust provenance, and identified the microscale location and fate of dust within a changing snow matrix. We found dust characteristics varied with deposition event and that dust particles were generally embedded in the snow grains, with a small fraction of the dust particles residing on the exterior of the snow matrix. Dust deposition appears to retard expected late season snow grain growth. Both bacteria and fungi were identified in the collected snow samples.