Above Ground Level Research Articles

Wildfire Smoke Observations in the Western United States from the Airborne Wyoming Cloud Lidar during the BB-FLUX Project. Part I: Data Description and Methodology

Abstract During the summer of 2018, the upward-pointing Wyoming Cloud Lidar (WCL) was deployed on board the University of Wyoming King Air (UWKA) research aircraft for the Biomass Burning Flux Measurements of Trace Gases and Aerosols (BB-FLUX) field campaign. This paper describes the generation of calibrated attenuated backscatter coefficients and aerosol extinction coefficients from the WCL measurements. The retrieved aerosol extinction coefficients at the flight level strongly correlate (correlation coefficient, rr > 0.8) with in situ aerosol concentration and carbon monoxide (CO) concentration, providing a first-order estimate for converting WCL extinction coefficients into vertically resolved CO and aerosol concentration within wildfire smoke plumes. The integrated CO column concentrations from the WCL data in nonextinguished profiles also correlate (rr = 0.7) with column measurements by the University of Colorado Airborne Solar Occultation Flux instrument, indicating the validity of WCL-derived extinction coefficients. During BB-FLUX, the UWKA sampled smoke plumes from more than 20 wildfires during 35 flights over the western United States. Seventy percent of flight time was spent below 3 km above ground level (AGL) altitude, although the UWKA ascended up to 6 km AGL to sample the top of some deep smoke plumes. The upward-pointing WCL observed a nearly equal amount of thin and dense smoke below 2 km and above 5 km due to the flight purpose of targeted fresh fire smoke. Between 2 and 5 km, where most of the wildfire smoke resided, the WCL observed slightly more thin smoke than dense smoke due to smoke spreading. Extinction coefficients in dense smoke were 2–10 times stronger, and dense smoke tended to have larger depolarization ratio, associated with irregular aerosol particles.

Evaluation of Height, Area, and Capacity of Concrete Elevated Water Reservoirs in a Tertiary Institution in Benin City, Nigeria

The objective of this work is to determine the height, area, and capacity of two concrete elevated water reservoirs in a Tertiary Institution in Benin City, Nigeria, to serve as reference to existing controls for future monitoring exercise. The two water reservoir involved in reality are of different shapes and sizes. The elevated heights, areas, and capacities of reservoir one and two suspended above their legs are: (8.106m, 362.778m2, 2940.680m3, and 7.485m, 320.400m2, 296.132m3), respectively. The total heights of the reservoir one and two above ground level (AGL) are approximately 22m and 18m. Statistical analysis of uncertainty in height measurement showed, 0.0153 for reservoir one and 0.0412 for reservoir two. The provision of the necessary information by the REM method about the elevated water reservoirs showed its efficacy. This method is recommended for use in the measurement of inaccessible structure/feature. The type of data and information such as provided in this work are required for institutional water board documentation, water use planning, and archival purpose.

Evaluating Mesquite Distribution Using Unpiloted Aerial Vehicles and Satellite Imagery

Encroachment of woody plant species on rangelands is of critical concern for rangeland health and function. Recent advances in unpiloted aerial vehicles (UAVs) technology have opened new opportunities for natural resource personnel to quantify features within the landscape. Our goal was to combine information derived from UAV and Sentinel-2 imagery to quantify the presence and spatial distribution of mesquite (Prosopis glandulosa). The specific objectives were to 1) evaluate the accuracy of UAVs to estimate mesquite height and 2) classify mesquite using a combination of height metrics and spectral information by combining UAV and Sentinel-2 remote sensing data. We conducted our study in three different ecoregions in Texas. We collected on-site tree height field measurements and created two UAV-derived height outputs at 50 m and 100 m above ground level (AGL). We then used a random forest classification with data derived from the UAV to inform Sentinel-2 imagery of mesquite locations to assess its presence at the landscape level. Linear regression analysis showed that 50-m AGL mesquite height estimates from UAV explained 95% of the variability. Variability explained from 100 m AGL height estimates was slightly lower at 92%. Accuracy assessments from using UAV training data to predict mesquite presence using Sentinel-2 imagery yielded overall accuracy of > 80% for all sites, user accuracies up to 86%, and producer accuracies up to 92%. UAV-derived heights of mesquite were reliable. UAV imagery can be used as training data for Sentinel-2 satellite imagery to assess mesquite presence on Texas rangelands. Being able to combine the high spatial resolution of the UAV imagery with the high temporal resolution of the Sentinel-2 satellite imagery could improve our ability to use UAVs to monitor rangelands.

Investigation of Metrics for Assessing Human Response to Drone Noise.

Novel electric air transportation is emerging as an industry that could help to improve the lives of people living in both metropolitan and rural areas through integration into infrastructure and services. However, as this new resource of accessibility increases in momentum, the need to investigate any potential adverse health impacts on the public becomes paramount. This paper details research investigating the effectiveness of available noise metrics and sound quality metrics (SQMs) for assessing perception of drone noise. A subjective experiment was undertaken to gather data on human response to a comprehensive set of drone sounds and to investigate the relationship between perceived annoyance, perceived loudness and perceived pitch and key psychoacoustic factors. Based on statistical analyses, subjective models were obtained for perceived annoyance, loudness and pitch of drone noise. These models provide understanding on key psychoacoustic features to consider in decision making in order to mitigate the impact of drone noise. For the drone sounds tested in this paper, the main contributors to perceived annoyance are perceived noise level (PNL) and sharpness; for perceived loudness are PNL and fluctuation strength; and for perceived pitch are sharpness, roughness and Aures tonality. Responses for the drone sounds tested were found to be highly sensitive to the distance between drone and receiver, measured in terms of height above ground level (HAGL). All these findings could inform the optimisation of drone operating conditions in order to mitigate community noise.

Evaluating changes in horse behavior as a response to small unmanned aerial vehicles

• The application of small unmanned aerial systems (sUAS) has expanded to include livestock management, however the effects of sUAS disturbance on domestic horses ( Equus calibus ) has not been well documented. • We developed an ethogram to classify and record horse behaviors and changes in response to disturbance using a DJI Phantom 4 Pro sUAS by monitoring horse behavior at 5 second intervals from 3 m, 15 m, and 33 m above ground level (AGL). • We found vigilance was the most common behavior after initial approach at all AGLs. • Horses took evasive measures after approximately 20 seconds at lower AGL (i.e., <3 m). • The recovery to the control behavior occurred sooner at higher AGLs and most horses recovered within 60 seconds. • sUAS could be a valuable tool in horse management, including their potential use during domestic and free-roaming horse roundups.

Analysis of 5.5 years of atmospheric CO2, CH4, CO continuous observations (2014–2020) and their correlations, at the Observatoire de Haute Provence, a station of the ICOS-France national greenhouse gases observation network

Since 2014, a 100 m tall tower measures continuously greenhouse gases at the Observatoire de haute Provence (OHP) located in the southeast of France (43° 55′ 51″ N, 5° 42′ 48″ E) as a monitoring station of the French National Greenhouse Gases Observation network (ICOS-Fr). This rural station allows to study the short, mid, and long terms variability of atmospheric CO2, CH4 and CO concentrations at the continental, regional and local scales in a region characterized by a Mediterranean climate. Measurements are performed using cavity ring-down spectroscopy at three levels above ground level (AGL); 10 m, 50 m and 100 m. Using the ICOS European Infrastructure procedure to calibrate and ensure the data quality control, the precision of our datasets matches the international WMO/GAW recommendations. Time series from July 2014 to February 2020 were analysed. We inferred a mean annual growth rate at 100 m AGL of 2.7 ppm/year for CO2 (7.8 ppb/year for CH4) over the period of study, whereas no significant annual growth rate was found for CO. These growth rates are comparable to other remote ICOS and WMO/GAW sites. A seasonal amplitude of 13 ppm, 30 ppb, 45 ppb was found for atmospheric CO2, CH4 and CO, respectively. As expected, the amplitude of the diurnal cycle of these three species varies in function of the season, from 2.6 (1.6) ppm in winter and 10.7 (6.6) ppm in summer for CO2, 3.7 (5.1) and 7.7 (7.1) ppb for CH4, and contrary to CO2 and CH4 smaller amplitude in summer with 2.15 (2.5) ppb and 9.3 (8.9) ppb in winter for CO at 10 m (100 m) AGL. Significant correlations (R2 between 0.67 and 0.91) between the three species have been detected, especially in the winter season. Using thresholds on wind speed and on the standard variation of hourly concentrations, more than 16% of the data were identified to be enriched either: 1/by regional anthropogenic plumes; 2/during stable synoptic conditions inducing the accumulation of anthropogenic emissions in the atmospheric boundary layer (13%); and 3/by local's sources inducing short pollution events (3%). On average, ΔCO/Δ CO2 ratios of 3.72 ± 0.06 ppb/ppm and 0.8 ± 0.2 ppb/ppm for Δ CH4/ΔCO were inferred during local pollution events in winter and are typical of traffic and residential heating as given by the local bottom-up emissions inventory delivered by the regional air quality agency ATMOSUD. Adding specific tracers or isotopic measurements would be very interesting to distinguish anthropogenic sources and monitor the evolution of their characteristics as emission ratios at the OHP station. Filtering out these conditions, about 84% of the data are not undergoing the influence of local and regional anthropogenic plumes, and are thus representative of “background” CO2, CO and CH4 concentrations at the local to the regional scales. These background conditions are shown to be dependent on wind speed and direction.

Method for assessing radon Re-Entrainment risks from above ground level discharges from sub-slab depressurization systems

Above ground level (ABL) discharges are commonly employed in northern climates to release radon-containing soil gases from sub-slab depressurization radon mitigation systems. While there are many practical reasons to employ this in cold climates (e.g., to avoid ice build-up), it does inherently elevate the outdoor radon concentrations, and raises the possibility of radon re-entrainment back into living spaces of the emitting house, and its neighbors. A method has been developed for assessing outdoor radon dispersion and re-entrainment risks. It links computational fluid dynamics calculations for evaluating outdoor concentrations, and regional multi-annual meteorological records that give the occurrence probability for different wind speed, wind direction, and atmospheric stability conditions. When combined with assumptions about indoor/outdoor concentration ratios, annual average exposure concentrations to radon can be estimated. Concentrations along surfaces of the emitting house are often quite high close to the exhaust vent, and air exchange into the house from nearby open windows, air intakes, etc., and can result in high indoor concentrations. Re-entrainment into the neighboring house is often less serious, though certain circumstances can lead to radon being trapped in the space between the two buildings, which leads to higher exposure.

Digital Terrain Modelling by Remotely Piloted Aircraft: Optimization and Geometric Uncertainties in Precision Coffee Growing Projects

The implantation of coffee crop plantations requires cartographic data for dimensioning areas and planning the planting line. Digital terrain models (DTMs) obtained from remotely piloted aircraft (RPA) can contribute to efficient data collection for topography making this technique applicable to precision coffee projects. Aiming to achieve efficiency in the collection, processing and photogrammetric products quality, flight configurations and image processing were evaluated. Two hundred sixty-five points obtained by Global Navigation Satellite System (GNSS) receivers characterized the topographic surface. Then eighteen flight missions were carried out by RPA in the configurations of altitude above ground level (AGL) and frontal and lateral image overlay. In addition, different point cloud formats evaluated the image processing (time) efficiency in DTM. Flights performed at 120 m AGL and 80 × 80% overlap showed higher assertiveness and efficiency in generation DTMs. The 90 m AGL flight showed great terrain detail, causing significant surface differences concerning the topography obtained by GNSS. An increase in image overlap requires longer processing times, not contributing linearly to the geometric quality of orthomosaic. Slope ranges up to 20% are considered reliable for precision coffee growing projects; above 20% overestimates the slope values of the land. Changes in flight settings and image processing are satisfactory for precision coffee projects. Image overlap reduction was significant in reducing the processing time without influencing the quality of the DTMs. In addition, image processing performed in shallow point clouds did not interfere with the DTMs quality.

An analysis of the 10 MW Butoni wind farm in the Tropical Southwest Pacific Island of Fiji

This study carries out an analysis of the 10 MW Butoni wind farm in the tropical southwest Pacific island of Fiji using 6 years of uninterrupted near-surface wind observations (2013–2018). The standard wind-industry software, WAsP is used to analyse and evaluate the wind characteristics of the wind farm and the surrounding areas. The modelled and operational AEP are discussed with the related economic analysis together with the main causes for the under-performance of the wind farm. The results revealed that the mean wind speed, power density and the AEP at the Butoni wind farm are below the utility-scale standard of 6.4 m/s, 300 W/m2 and 500 MWh/year/turbine respectively, at 55 m above ground level (AGL). The main reason for the under-performance of the wind farm is that it was commissioned for a low mean wind speed regime of Wind Power Class 1. The wind farm has a lower-than-expected capacity factor of 5.4% and a higher wind shear coefficient of 0.35. An economic analysis revealed that the payback time is 24.5 years, and the cost of energy generation is FJD $ 0.55/kWh.

Assessment of the Wind Energy Potential of Two Burundian Sites

1-year hourly wind speed data from two Burundian stations, namely Bujumbura and Muyinga, have been processed in this work to bring an efficient help for the planning and installation of wind energy conversion systems (WECS) at those localities. Mean seasonal and diurnal variations of wind direction and wind shear exponent have been derived. Two-parameter Weibull probability density functions (PDFs) fitting the observed monthly and annual wind speed relative frequency distributions have been implemented. As shown through three complementary statistical tests, the fitting technique was very satisfactory. A wind resource analysis at 10 m above ground level (AGL) has led to a mean power density at Bujumbura which is almost thirteen fold higher than at Muyinga. The use of the empirical power law to extrapolate wind characteristics at heights from 150 to 350 m AGL has shown that energy potential of hilltops around Muyinga was only suitable for small, individual scale wind energy applications. At the opposite, wind energy potential of ridge-tops and hilltops around Bujumbura has been found suitable for medium and large scale electricity production. For that locality and at those heights, energy outputs and capacity factors (CF or Cf) have been computed for ten selected wind turbines (WTs), together with costs of electricity (COE) using the present value of cost (PVC) method. Amongst those WTs, YDF-1500-87 and S95-2.1 MW have emerged as the best options for installation owing to their highest CF and lowest COE. Moreover, an analysis of those two quantities at monthly basis for YDF-1500-87 WT has led to its best performance in the dry season. Compared to the average present COE of household hydroelectricity consumption, results of this study have evidenced economical feasibility and benefit of WECS setting in selected Burundian sites in order to supplement traditional electricity sources.

Deep Learning-Based Object Detection System for Identifying Weeds Using UAS Imagery

Current methods of broadcast herbicide application cause a negative environmental and economic impact. Computer vision methods, specifically those related to object detection, have been reported to aid in site-specific weed management procedures for targeted herbicide application within a field. However, a major challenge to developing a weed detection system is the requirement for a properly annotated database to differentiate between weeds and crops under field conditions. This research involved creating an annotated database of 374 red, green, and blue (RGB) color images organized into monocot and dicot weed classes. The images were acquired from corn and soybean research plots located in north-central Indiana using an unmanned aerial system (UAS) flown at 30 and 10 m heights above ground level (AGL). A total of 25,560 individual weed instances were manually annotated. The annotated database consisted of four different subsets (Training Image Sets 1–4) to train the You Only Look Once version 3 (YOLOv3) deep learning model for five separate experiments. The best results were observed with Training Image Set 4, consisting of images acquired at 10 m AGL. For monocot and dicot weeds, respectively, an average precision (AP) score of 91.48 % and 86.13% was observed at a 25% IoU threshold (AP @ T = 0.25), as well as 63.37% and 45.13% at a 50% IoU threshold (AP @ T = 0.5). This research has demonstrated a need to develop large, annotated weed databases to evaluate deep learning models for weed identification under field conditions. It also affirms the findings of other limited research studies utilizing object detection for weed identification under field conditions.

Characteristic Analysis of Dual-Polarization Weather Radar Echoes of Convective Precipitation and Snowfall in the Mount Everest Region

This paper introduces the X-band weather radar dual-polarization parameters of isolated convective cell precipitation and meso/microscale snowfall on Mount Everest and presents the first precipitation observations based on dual-polarization weather radar in this area. Compared with the Chengdu Plain, Mount Everest experienced convective precipitation on smaller horizontal and vertical scales with a narrower Zdr probability density spectrum (uniformly distributed around approximately 0). The Zh profile on Mount Everest displayed two peaks, unlike that over the plains, and the precipitation at the strong convective core was denser. Furthermore, during winter snowfall on the northern slope of Mount Everest, when the boundary layer exhibited sufficient water vapor and dynamic uplift, due to the low boundary layer temperature (&lt;0 °C), water vapor produced stratiform clouds in the middle and lower layers (approximately 1.5 km above ground level (AGL)). Water vapor condensation at 1.5–2.5 km AGL led to latent heat release, which increased the temperature of regional stratiform clouds with increasing height. Consequently, the temperature at the stratiform cloud top height (2.5 km AGL) unexpectedly exceeded 0 °C. Additionally, the −20 °C isotherm was at approximately 4 km AGL, indicating that the middle- and upper-layer atmospheric temperatures remained low. Therefore, thermal instability occurred between the stratiform cloud top height and the middle/upper atmosphere, forming convective motion. These findings confirm the occurrence of elevated winter snowfall convection above Mount Everest and may have certain reference value for retrieving raindrop size distributions, quantitatively estimating precipitation, and parameterizing cloud microphysical processes in numerical prediction models for the Qinghai-Tibetan Plateau.

Interactive effects of biotic stressors and provenance on chemical defence induction by holm oak (Quercus ilex)

Key MessageThe patterns of induced chemical defences in Quercus ilex leaves are specific to the biotic stress factor that causes them. Interactive effects between stressors depend on provenance.Quercus forests are suffering serious decline worldwide, closely linked to the consequences of climate change. The increase of biotic stressors threatens the survival of the holm oak (Quercus ilex), a dominant tree species in the Mediterranean Basin. A better understanding of its resistance mechanisms is urgently required to enable a better control of its decline. In this work, the ability of holm oaks from six Iberian provenances to respond to multiple biotic damage is studied through an analysis of their induced chemical defence patterns. Using 2016 seedlings established in a common garden trial (6 regions × 12 families/region × 7 seedlings/family × 4 treatments), biotic damage was induced at the root level (by infection with the widespread pathogen Phytophthora cinnamomi) and at the above-ground level (by mechanical defoliation). The levels of constitutive and induced total phenols, total tannins and condensed tannins were measured. Results showed that (1) the defensive chemical patterns present significant local and geographical variation, (2) survival to stress is more related to constitutive defences than induced ones, (3) the induced response is stressor-specific, and (4) there is an interactive effect amongst stressors whose sign (induction/inhibition) depends on the provenance. These findings on biotic stressor effects on the chemical defences and survival of holm oak can contribute to the development of genetic material selection programs in the integrated control of the widespread decline of Quercus.

High-Resolution Modeling of Mesoscale Circulation in the Atmospheric Boundary Layer over a Complex Coastal Area

We evaluated the performance of the high-resolution (333 m) Weather Research and Forecasting (WRF) model in simulating the flow structure at a complex coastal site in Boseong, South Korea, on 15 July 2018, against observations obtained from a 300 m tower and radiosonde, and analyzed the model results to interpret the measurements. The study site is surrounded by mountains, valleys, and bays, and is adjacent to the South Sea; thus, it is influenced by terrain-forced flow and thermally driven circulation. The study day was characterized by the development of nighttime low-level wind maximum (LLWM) and daytime sea breeze under weak synoptic wind conditions. Although the WRF model simulated the onset and cessation of a sea breeze later than was observed, it showed good skill in reproducing the near-surface temperatures, wind vectors, and vertical profiles of potential temperatures and wind vectors in the atmospheric boundary layer at the study site. We analyzed the model results at 05:30 and 14:30 LST when the model’s performance was good for wind. At 05:30 LST, hydraulic jump produced weak wind conditions below 300 m above ground level (AGL), and westerly down-valley flow developed near the surface, leading to an LLWM. At 14:30 LST, heating over land produced a thermal high over land at 1800 m AGL, counteracting the synoptic pressure gradient, and leading to weak wind conditions at this level. We performed three sensitivity simulations to examine the dependence of flow structure on the horizontal and vertical resolution. The results show that an early-morning hydraulic jump can be simulated by applying a high-resolution model in both the horizontal and vertical grids, and the simulated onset and cessation times of the sea breeze depend on the model’s resolution. The dependence of flow structure on the model resolution has been discussed.

Performance Evaluation of the WOFOST Model for Estimating Evapotranspiration, Soil Water Content, Grain Yield and Total Above-Ground Biomass of Winter Wheat in Tensift Al Haouz (Morocco): Application to Yield Gap Estimation

The main goal of this investigation was to evaluate the potential of the WOFOST model for estimating leaf area index (LAI), actual evapotranspiration (ETa), soil moisture content (SM), above-ground biomass levels (TAGP) and grain yield (TWSO) of winter wheat in the semi-arid region of Tensift Al Haouz, Marrakech (central Morocco). An application for the estimation of the Yield Gap is also provided. The model was firstly calibrated based on three fields data during the 2002–2003 and 2003–2004 growing seasons, by using the WOFOST implementation in the Python Crop simulation Environment (PCSE) to optimize the different parameters that provide the minimum difference between the measured and simulated LAI, TAGP, TWSO, SM and ETa. Then, the model validation was performed based on the data from five other wheat fields. The results obtained showed a good performance of the WOFOST model for the estimation of LAI during both growing seasons on all validation fields. The average R2, RSME and NRMSE were 91.4%, 0.57 m2/m2, and 41.4%, respectively. The simulated ETa dynamics also showed a good agreement with the observations by eddy covariance systems. Values of 60% and 72% for R2, 0.8 mm and 0.7 mm for RMSE, 54% and 31% for NRMSE are found for the two validation fields, respectively. The model’s ability to predict soil moisture content was also found to be satisfactory; the two validation fields gave R2 values equal to 48% and 49%, RMSE values equal to 0.03 cm3/cm3 and 0.05 cm3/cm3, NRMSE values equal to 11% and 19%. The calibrated model had a medium performance with respect to the simulation of TWSO (R2 = 42%, RSME = 512 kg/ha, NRMSE = 19%) and TAGP (R2 = 34% and RSME = 936 kg/ha, NRMSE = 16%). After accurate calibration and validation of the WOFOST model, it was used for analyzing the gap yield since this model is able to estimate the potential yield. The WOFOST model allowed a good simulation of the potential yield (7.75 t/ha) which is close to the optimum value of 6.270 t/ha in the region. Yield gap analysis reveals a difference of 5.35 t/ha on average between the observed yields and the potential yields calculated by WOFOST. Such difference is ascribable to many factors such as the crop cycle management, agricultural practices such as water and fertilization supply levels, etc. The various simulations (irrigation scenarios) showed that early sowing is more adequate than late sowing in saving water and obtaining adequate grain yield. Based on various simulations, it has been shown that the early sowing (mid to late December) is more adequate than late sowing with a total amount of water supply of about 430 mm and 322 kg (140 kg of N, 80 kg of P and 102 kg of K) of fertilization to achieve the potential yield. Consequently, the WOFOST model can be considered as a suitable tool for quantitative monitoring of winter wheat growth in the arid and semi-arid regions.

Use of Drones With Thermal Infrared to Locate White‐tailed Deer Neonates for Capture

ABSTRACTDrones are growing in popularity and are used to locate individual animals, estimate ungulate population size, and monitor endangered species. Our goal was to assess the efficacy of using drones to locate neonatal white‐tailed deer (Odocoileus virginianus) for capture. During May–June 2019 and June 2020, we used a drone equipped with thermal‐infrared (TIR) and conventional multispectral red‐green‐blue (RGB) cameras to locate and confirm fawn thermal signatures in Minnesota's southern farmland region. We confirmed 29 and 71 fawn thermal signatures in 2019 and 2020, respectively. We captured 13 fawns to validate the methodology (detection and identification) of using drones for capture in 2019. We flew the drone for 47.3 hours covering 792 hectares (17 hectares per hour) in 2019 and flew for 41.1 hours and covered 1640 hectares (40 hectares per hour) in 2020. We worked 201.5 person‐hours with a mean crew size of 4 people that required 6.9 person‐hours to locate each fawn in 2019, whereas we worked 145.7 person‐hours with a mean crew size of 4 people that required 70% less effort and resulted in 2.1 person‐hours to locate each fawn in 2020. Flight efficiency was highest at 60 m above ground level (AGL) with a speed of 9 m/s; however, diurnal use of drones made identifying fawn thermal signatures difficult as thermal loading of the environment quickly reduced the temperature differential between vegetation and signatures. We found TIR‐equipped drones to be an efficient method to locate and subsequently capture fawns in open habitats in comparison to other capture methods such as vaginal implant transmitters (VITs), ground searches, or monitoring doe behavior. We recommend flying at night or in cloudy conditions to avoid false positives. © 2021 The Wildlife Society.

Hymec: Surface Precipitation Type Estimation at the German Weather Service

AbstractThe analysis and forecast of precipitation characteristics is a key task for national meteorological services for providing high-quality weather forecasts and warnings. Beside the precipitation amount, the precipitation type is essential to describe and evaluate the recent, ongoing, and future weather situations. This paper introduces a new surface-based hybrid hydrometeor classification algorithm. The presented method combines polarimetric radar observations at radar beam height from the C-band dual-polarization weather radar network of the German Weather Service [Deutscher Wetterdienst (DWD)] with corrected thermodynamical profiles of numerical weather prediction (NWP) model output and extrapolates the hydrometeor classes at radar beam height to a height of 2 m above ground level (AGL). The implemented technique parameterizes the microphysical processes in the lower troposphere based on the appropriate thermodynamical profile that the hydrometeors have to pass along their way from the radar beam height to the surface. Due to errors in NWP output, the NWP vertical profiles of temperature and humidity are adjusted by using several types of surface stations with high spatial and temporal resolution. Verification results show considerable improvements in the hydrometeor classification near the ground compared to the radar sweep height. After an additional positive in-house evaluation, the presented method is integrated into DWD’s operational environment. The topic of this paper is to describe the processing steps for the computation of the near-surface precipitation type. In addition, example cases and a verification study complement the explanations.

Discriminating between Tornadic and Non-Tornadic Supercells: A New Hodograph Technique

Thompson and Edwards (2000) first noted a prominent hodograph kink separating primarily speed shear from primarily directional shear in the environments of some supercells producing significant tornadoes. Responding to this observation, we compared similar thermodynamic and shear environments between the Moore, Oklahoma tornado of 3 May 1999 and non-tornadic supercell thunderstorms occurring in north Texas on 23 April 2003. The results suggest that certain characteristics of the kink could discriminate between tornadic and non-tornadic supercells. This combination of features consisted of a strong (&gt; 10 m s-1) nearly straight-line hodograph below 500 m above ground level (AGL) and storm-relative inflow orthogonal to the base of this hodograph segment at 10 m, yielding almost purely streamwise storm-relative inflow.&#x0D; We evaluated this hypothesis by analyzing 67 severe convective events, 65 of which were supercells, in Oklahoma from 1997-2004, and dividing the events into non-tornadic, weak-tornadic (F0-­F1), and significant-tornadic (F2-­F5) storm classes. The results show improved discrimination between storm classes for 10-­500 m storm-relative helicity and bulk shear magnitude when compared to 10-­1000 m calculations of the same. Also, histograms of the critical angle (defined by the storm-relative inflow vector at 10 m and 10-­500 m shear vector) revealed that the tornadic storms, and in particular the significant tornadic storms, tended to be characterized by angles near 90°, whereas the non-tornadic storms were not. Although the results are based on a relatively small sample, they suggest that a careful consideration of the evolution of the low-level hodograph in both time and space in relation to the storm motion can potentially be a valuable aid in forecasting supercell tornadoes.

Industrial Masonry Chimney Geometry Analysis: A Total Station Based Evaluation of the Unmanned Aerial System Photogrammetry Approach.

High industrial chimney inclination monitoring and analysis is crucial from a stability point of view because, if not maintained, it can pose a great potential hazard for its surroundings. Various modern approaches of chimneys’ geometrical parameters determination have been proposed and are actively in use. However, little research regarding the applicability of the unmanned aerial system (UAS)-based photogrammetric approach of chimney structural monitoring has been conducted and a comprehensive analysis with validated methods is lacking. Therefore, this research is focused on the determination of geometrical structural parameters of a masonry chimney whereby two independent methods have been applied. Reference values of the chimney geometrical parameters have been determined by precise total station (TS) measurements and, in relation to them, the applicability of the UAS-based photogrammetric approach is evaluated. Methodologically, the reference and validation values of the chimney geometrical parameters have been determined based on double modeling of the chimney structure. Firstly, cross-sectional elliptical regression has been applied to determine the geometrical values of the chimney at predefined above-ground levels (AGLs). Secondly, the spatial chimney axis has been derived by polynomial regression to determine the inclination of the full chimney structure. Lastly, the structural stability of the chimney is validated based on its axis inclination whereby permitted deviations are determined according to the European Standard EN 1996-1-1:2005. Experimental results of our research show that consistently better results are gained by TS-based surveys and, although the determination of the chimney’s geometrical values by the UAS-based approach is certainly possible, great attention must be given to the accuracy of the UAS-generated point cloud (PC) if high accuracy results are needed.

Electricity production and comparative analysis for wind availability power potential assessment at four sites in Egypt

This research represents the first wind energy potential assessment that covers major provinces in Egypt. The paper investigates a realistic study technically and economically of wind energy as a talented renewable source for electricity production of various regions in Egypt. More accurate prediction and measurement of wind speed and direction allow wind plants to supply clean, renewable power to businesses, and homeowners at lower costs. Wind resource assessments must be precise in order for wind farms to be built successfully. Wind resource assessments have been carried out in this study. Wind resources evaluation and precise assessment of wind capacity for the four selected sites in Egypt’s provinces from 2017 for 3 years at 10, 50 m above ground level (AGL): Hurgada, Aswan, Alexandria, and the capital of Egypt (Cairo). The wind speed data is taken from NASA for different sites in Egypt. The average annual wind speed was estimated to be 4.44, 4.31, 4.91, and 3.9 m/s at 10 m height, respectively. The economical factors such as NPC and COE in the selected regions are estimated. The optimum location for wind assessment in Egypt is Alexandria which gives maximum wind speed, maximum annual energy, minimum levelized cost of energy, and highest capacity factor. The proposed wind assessment will generated 20,1729 kWh of electricity per year and electricity generation cost per kWh/$ is 0.0818844. This planned cost of wind electric generation is compatible with the local electricity tariff. Also, Feasibility of Construction small wind turbine in this site is investigated. In addition, a criterion of wind farm site selection is presented here with Environmental Impact Assessment (EIA) study through Birds Migration aspect that decreases with increase turbine tower length and short blade length. Through reducing Egypt’s domestic fossil fuel consumption, this work will potentially save tons of carbon emissions each year.