Average Wind Direction Research Articles

Regression and multivariate models for predicting particulate matter concentration level.

The devastating health effects of particulate matter (PM10) exposure by susceptible populace has made it necessary to evaluate PM10 pollution. Meteorological parameters and seasonal variation increases PM10 concentration levels, especially in areas that have multiple anthropogenic activities. Hence, stepwise regression (SR), multiple linear regression (MLR) and principal component regression (PCR) analyses were used to analyse daily average PM10 concentration levels. The analyses were carried out using daily average PM10 concentration, temperature, humidity, wind speed and wind direction data from 2006 to 2010. The data was from an industrial air quality monitoring station in Malaysia. The SR analysis established that meteorological parameters had less influence on PM10 concentration levels having coefficient of determination (R 2) result from 23 to 29% based on seasoned and unseasoned analysis. While, the result of the prediction analysis showed that PCR models had a better R 2 result than MLR methods. The results for the analyses based on both seasoned and unseasoned data established that MLR models had R 2 result from 0.50 to 0.60. While, PCR models had R 2 result from 0.66 to 0.89. In addition, the validation analysis using 2016 data also recognised that the PCR model outperformed the MLR model, with the PCR model for the seasoned analysis having the best result. These analyses will aid in achieving sustainable air quality management strategies.

Observation of wind shear during evening transition and an estimation of submicron aerosol concentrations in Beijing using a Doppler wind lidar

The wind speed and direction measured over six months by a Doppler wind lidar (Windcube-8) were compared with wind cup anemometers mounted on the 325-m Beijing meteorological tower (BMT). Five mountain–plain wind cases characterized by wind direction shear were selected based on the high-frequency (1.1 s) wind profile of the Windcube-8 and analyzed with 1-h mesoscale surface weather charts. Also analyzed was the relationship between in-situ PM1 (aerodynamic diameter ≤ 1 μm) concentrations measured at 260 m on BMT and the carrier-to-noise ratio (CNR) of the co-located Windcube-8. The results showed that the 10-min averaged wind speed and direction were highly correlated (R = 0.96–0.99) at three matched levels (80, 140, and 200 m). The evening transition duration was 1–3 h, with an average wind speed of 1 m s–1 at 80 m above the ground. In addition, there was a zero horizontal-wind-speed zone along the wind direction shear line, and in one case, the wind speed was characterized by a Kelvin–Helmholtz gravity wave. The variability of the PM1 concentrations was captured by the CNR of the Windcube-8 in a fair weather period without the long-range transport of dust.

Caracterização do Regime de Ventos no Piauí Para o Aproveitamento de Energia Eólica

Resumo O presente estudo apresenta uma caracterização do regime de ventos em algumas regiões do estado do Piauí, realizada por meio da análise do perfil da velocidade média horária e mensal dos ventos bem como da freqüência da direção dos mesmos. O objetivo principal do trabalho é identificar possíveis sítios de geração de energia eólica no Piauí a partir do uso de uma ferramenta computacional: o software Windographer®. Utilizando-se a base de dados do ano de 2010 do Instituto Nacional de Meteorologia (INMET) foram analisados os municípios de Valença, Floriano, Alvorada do Gurgueia, Oeiras, Caracol, São João do Piauí, Paulistana e Parnaíba. Para cada município são apresentados graficamente o regime de ventos horário e mensal bem como da sua direção predominante no período estudado. Os resultados mostraram que os municípios de Paulistana e Parnaíba se destacaram por apresentarem um potencial eólico satisfatório para o aproveitamento de energia elétrica.

Tropical Cyclone Center Positions from Sequences of HDSS Sondes Deployed along High-Altitude Overpasses

Abstract A method is developed to calculate the zero-wind center (ZWC) position from a sequence of Yankee High Density Sounding System (HDSS) dropwindsondes deployed during a high-altitude overpass of a tropical cyclone. The approach is similar to the Willoughby and Chelmow technique in that it utilizes the intersections of bearings normal to the wind directions across the center to locate the ZWC position. Average wind directions over 1-km layers are calculated from the accurate global positioning system (GPS) latitude–longitude positions as the HDSS sonde falls from the 60 000-ft flight level of the NASA WB-57 to the ocean surface. An iterative procedure is used to also account for the storm translation, which is necessary to put these high-frequency HDSS observations into a storm-relative coordinate system. The Tropical Cyclone Intensity (TCI-15) mission into Hurricane Joaquin on 4 October 2015 is examined here. The ZWC positions from two center overpasses indicate the vortex tilts from 1- to 10-km elevation and rotates cyclonically with height.

Validation of Gaussian plume model Aeropol against Cabauw field experiment

The Gaussian dispersion model AEROPOL is validated against the Cabauw (1977-1978) dataset, applying the parameters and rules from the Model Validation Kit. The purpose to revisit this experiment is preparation for fast response to buoyant accidental releases. In the AEROPOL model, the classical Pasquill-Gifford stability and a scheme based on Lagrangian time scales (the Gryning scheme) are used as alternatives. Validation is based on correlation, fractional bias, fractional sigma, NMSE and fraction in factor 2, applying these statistics to maximal arc-wise, near-centreline and cross-wind integrated concentrations. Both parameterisations are found to be fairly adequate. The Gryning scheme results in moderately underestimated concentrations, which are well correlated with the experimental ones. The Pasquill parameterisation, in contrast, represents the concentrations well on average, but with larger scatter. The average wind direction and speed between the lowest measurement level and release level are found to be good approximations to represent the position of the Gaussian plume.

Validation of Gaussian plume model Aeropol against Cabauw field experiment

The Gaussian dispersion model AEROPOL is validated against the Cabauw (1977-1978) dataset, applying the parameters and rules from the Model Validation Kit. The purpose to revisit this experiment is preparation for fast response to buoyant accidental releases. In the AEROPOL model, the classical Pasquill-Gifford stability and a scheme based on Lagrangian time scales (the Gryning scheme) are used as alternatives. Validation is based on correlation, fractional bias, fractional sigma, NMSE and fraction in factor 2, applying these statistics to maximal arc-wise, near-centreline and cross-wind integrated concentrations. Both parameterisations are found to be fairly adequate. The Gryning scheme results in moderately underestimated concentrations, which are well correlated with the experimental ones. The Pasquill parameterisation, in contrast, represents the concentrations well on average, but with larger scatter. The average wind direction and speed between the lowest measurement level and release level are found to be good approximations to represent the position of the Gaussian plume.

Analysis and probabilistic modeling of wind characteristics of an arch bridge using structural health monitoring data during typhoons

The accurate evaluation of wind characteristics and wind-induced structural responses during a typhoon is of significant importance for bridge design and safety assessment. This paper presents an expectation maximization (EM) algorithm-based angular-linear approach for probabilistic modeling of field-measured wind characteristics. The proposed method has been applied to model the wind speed and direction data during typhoons recorded by the structural health monitoring (SHM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. In the summer of 2015, three typhoons, i.e., Typhoon Chan-hom, Typhoon Soudelor and Typhoon Goni, made landfall in the east of China and then struck the Jiubao Bridge. By analyzing the wind monitoring data such as the wind speed and direction measured by three anemometers during typhoons, the wind characteristics during typhoons are derived, including the average wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and power spectral density (PSD). An EM algorithm-based angularlinear modeling approach is proposed for modeling the joint distribution of the wind speed and direction. For the marginal distribution of the wind speed, the finite mixture of two-parameter Weibull distribution is employed, and the finite mixture of von Mises distribution is used to represent the wind direction. The parameters of each distribution model are estimated by use of the EM algorithm, and the optimal model is determined by the values of R2 statistic and the Akaike

Direction and Timing of Dispersal ofScirtothrips dorsalis(Thysanoptera: Thripidae) on Select Ornamental Host Plant Species in South Florida

Abstract Chilli thrips, Scirtothrips dorsalis Hood (Thysanoptera: Thripidae), is a troublesome pest of agronomic, vegetable, fruit, and ornamental crops. Scirtothrips dorsalis dispersal and monitoring were evaluated under field and greenhouse conditions in Homestead and Apopka, Florida, in 2007. A field test examined dispersal from Knock-Out® rose, Rosa ‘Radrazz’ (Rosaceae), onto green buttonwood, Conocarpus erectus L. (Combretaceae), and ‘Emerald Green’ schefflera, Schefflera arboricola Forst & Forst ‘Emerald Green’ (Araliaceae). Fewer adults were caught in traps set north, east, or south than west of rose plants corresponding to the average wind direction. Scirtothrips dorsalis flights increased during the morning to early afternoon, peaked about 9:00 a.m. to 2:00 p.m. EST, then decreased to almost no flights by 8:00 p.m. Warmer temperature and lower humidity corresponded to more adults caught per hour with most flights occurring after the accumulation of 300 degree-hours. ‘Emerald Green’ schefflera was...

Hydroclimatic controls on non-stationary stream water ages in humid tropical catchments

Streams in humid tropical countries provide a wide range of ecosystem services, yet a good understanding of their hydrological functioning is severely limited by lack of data. The transit time of water is a fundamental characteristic of catchment functioning and can often be related to water quality dynamics, thus providing potentially important information for water managers in these environments. In this study, we applied the widely used lumped convolution integral model in a moving window approach to acknowledge the time-variance of transit time distributions (TTD) and resulting moments such as the mean transit time (MTT). We show that for a two-year (2012–2014) rainfall-runoff stable isotope record from almost daily sampling in a humid tropical 30km2 catchment in southern Costa Rica, the MTTs are generally short (<one year), but exhibit distinct inter and intra-annual patterns. The drier year (2012–13), which was under the influence of El-Niño causing less precipitation, exhibited MTTs up to one year. In contrast, the wetter year (2013–14) resulted in MTT estimates <100days. Similar patterns were found at an intra-annual scale: the dry season MTTs were on average 185days and only 15days during the wet season. This can be explained by high rainfall volumes (>3m/year) and events occurring throughout the year, the seasonality of rainfall and distinct moisture origin (Pacific, Atlantic and land surface), the likely dominance of quick near-surface flow paths and relatively low subsurface storage of the underlying volcanic and sedimentary rocks. The moisture origin of rainfall was found to be the most dominant driver of time-variable TTDs as indicated by the changing average wind directions following the transition from the dry into the wet season. This isotope study revealed a highly dynamic system that is likely to be sensitive to environmental change.

Quality control of the RMI's AWS wind observations

Abstract. Wind observations are important for a wide range of domains including among others meteorology, agriculture and extreme wind engineering. To ensure the provision of high quality surface wind data over Belgium, a new semi-automated data quality control (QC) has been developed and applied to wind observations from the automated weather stations operated by the Royal Meteorological Institute of Belgium. This new QC applies to 10 m 10 min averaged wind speed and direction, 10 m gust speed and direction, 2 m 10 min averaged wind speed and 30 m 10 min averaged wind speed records. After an existence test, automated procedures check the data for limits consistency, internal consistency, temporal consistency and spatial consistency. At the end of the automated QC, a decision algorithm attributes a flag to each particular data point. Each day, the QC staff analyzes the preceding day's observations in the light of the assigned quality flags.

DINÁMICA OCÉANO-ATMÓSFERA Y SU INFLUENCIA EN LA BIOMASA FITOPLANCTÓNICA, EN LA ZONA COSTERA DEL DEPARTAMENTO DEL MAGDALENA, CARIBE COLOMBIANO

From February to June 2008 at inshore sites of the Magdalena region, specifically in Gaira and Granate inlets and Taganga Bay, six field trips were done comparing the main dry and short rainy seasons. The main aim was to determine the coupled ocean-atmosphere influence on the upwelling intensity, considering the physical and chemical variability within the water column between 0 and 60 m and the response of the phytoplankton community measured as chlorophyll a. Atmospheric, oceanographic, and biological conditions were evaluated following the Eulerian method. According to the oceanic and atmospheric conditions during the research period, Ekman transport and continental upwelling processes occurred through February and April, in response to adequate conditions: average wind speed (&gt;4.0 m/s) and wind direction (parallel and perpendicular to the coast). Physical and chemical anomalies were detected in the water mass, such as low temperature (25.34±0.82°C), high salinity (35.5±0.30) and oxygen subsaturation (70.6±7.8 %). The inorganic nutrient supply was higher during upwelling processes,consequently, the system was defined as mesotrophic, causing greater phytoplankton chlorophyll a biomass with level up to 1.60 μg/L. "La Niña" 2007/2008 event, which covered the period of this of this research, did not incite any important disturbance over the typical upwelling conditions.

Atmospheric Dispersion Study of TRS Compounds Emitted from a Pulp Mill Plant in Coastal Regions of the Uruguay River, South America

ABSTRACTThe atmospheric dispersion of total reduced sulfur (TRS) emissions from the pulp mill plant of Fray Bentos, Uruguay is simulated. The local authorities of the Environmental Monitoring Program (EMP) of Gualeguaychu, Argentina, received social complaints of malodor presence in different places of the region. An atmospheric dispersion model coupled to a boundary layer forecast model is used to simulate 11 events in which the EMP officials attended the scene in order to verify the situation. The validation of modeled winds with the observations from a meteorological tower indicates reasonably accurate wind forecasts. The spatial layout of the modeled TRS plumes is compared with the geographical distribution of points in the area where the social complaints were recorded. Nine of the 11 studied events are successful modeling cases since a positive (negative) in situ verification matches with a plume position over (far from) the site. In one of the two unsuccessful modeling cases, although the plume is marginally distant from the site, the average wind direction error is the largest one of all the events. In the other case the modeled plume is in fact over the site, but the situation was negatively verified. The reason for the disagreement could be the wind direction changes during the event. This was the longest modeled case that lasted for 7 hours and the plume was meandering during that time; first from SSW to the S, then back the SSW, and finally to the S and SSE. The conclusion of the study is that, despite the inherent uncertainty of numerical simulations, the implemented modeling system shows versatility and proves to be a useful tool not only for diagnostic studies but also for preventing conflictive situations since it can produce reasonably accurate forecast of plume position and its potential impact.

Human health risk assessment of mercury vapor around artisanal small-scale gold mining area, Palu city, Central Sulawesi, Indonesia

Emissions of elemental mercury, Hg(0), from artisanal small-scale gold mining activities accounted for 37% of total global Hg(0) emissions in 2010. People who live near gold-mining areas may be exposed to high concentrations of Hg(0). Here, we assessed the human health risk due to Hg(0) exposure among residents of Palu city (Central Sulawesi Province, Indonesia). The area around the city has more than 60t of gold reserves, and the nearby Poboya area is the most active gold-mining site in Indonesia. Owing to its geography, the city experiences alternating land and sea breezes.Sampling was done over a period of 3 years (from 2010 Aug. to 2012 Dec.) intermittently with a passive sampler for Hg(0), a portable handheld mercury analyzer, and a mercury analyzer in four areas of the city and in the Poboya gold-processing area, as well as wind speeds and directions in one area of the city. The 24-h average concentration, wind speed, and wind direction data show that the ambient air in both the gold-processing area and the city was always covered by high concentration of mercury vapor. The Hg(0) concentration in the city was higher at night than in the daytime, owing to the effect of land breezes. These results indicate that the inhabitants of the city were always exposed to high concentrations of Hg(0).The average daytime point-sample Hg(0) concentrations in the city, as measured with a handheld mercury analyzer over 3 days in July 2011, ranged from 2096 to 3299ngm−3. In comparison, the average daytime Hg(0) concentration in the Poboya gold-processing area was 12,782ngm−3. All of these concentrations are substantially higher than the World Health Organization air-quality guideline for annual average Hg exposure (1000ngm−3). We used the point-sample concentrations to calculate hazard quotient ratios by means of a probabilistic risk assessment method. The results indicated that 93% of the sample population overall was at risk (hazard quotient ratio ≥1 and cut off at the 95th percentile value of the sample population) of mercury toxicity, that is, damage to the central nervous system due to chronic exposure. The corresponding percentages for the northern, central, southern, and western areas of the city were 83%, 84%, 95%, and 95%, respectively. Our results indicate that the residents of Palu city are at serious risk from exposure to high concentrations of atmospheric Hg(0).

A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part 1: Wind and Turbulence

Numerical-weather-prediction models are often used to supply the mean wind and turbulence fields for atmospheric transport and dispersion plume models as they provide dense horizontally- and vertically-resolved geographic coverage in comparison to typically sparse monitoring networks. Here, the Weather Research and Forecasting (WRF) model was run over the month-long period of the Joint Urban 2003 field campaign conducted in Oklahoma City and the simulated fields important to transport and dispersion models were compared to measurements from a number of sodars, tower-based sonic anemometers, and balloon soundings located in the greater metropolitan area. Time histories of computed wind speed, wind direction, turbulent kinetic energy (e), friction velocity ( $$u_*$$ ), and reciprocal Obukhov length (1 / L) were compared to measurements over the 1-month field campaign. Vertical profiles of wind speed, potential temperature ( $$\theta $$ ), and e were compared during short intensive operating periods. The WRF model was typically able to replicate the measured diurnal variation of the wind fields, but with an average absolute wind direction and speed difference of $$35^\circ $$ and $$1.9\hbox { m s}^{-1}$$ , respectively. Using the Mellor-Yamada-Janjic (MYJ) surface-layer scheme, the WRF model was found to generally underpredict surface-layer TKE but overpredict $$u_*$$ that was observed above a suburban region of Oklahoma City. The TKE-threshold method used by the WRF model’s MYJ surface-layer scheme to compute the boundary-layer height (h) consistently overestimated h derived from a $$\theta $$ gradient method whether using observed or modelled $$\theta $$ profiles.

Estimating the offshore wind resources of the State of Ceará in Brazil

The onshore wind power is consolidated; the challenge is to reach the same level of maturity for offshore exploitation. Brazil has no offshore wind power plants and there are few studies in this direction. This paper aims to estimate the offshore wind resources in the State of Ceará, in Brazil. The investigation uses a mesoscale atmospheric computer model, the Regional Atmospheric Modeling System (RAMS), with horizontal resolution of 2 km, which estimates the offshore average wind speed, average wind direction, power density and turbulence taking into account the bathymetry data and navigation routes along the coast of Ceará. The wind potential was evaluated in three representative periods, La Niña, El Niño and Neutral year, analyzing the dry and rainy season for each period. The results indicate an average wind speed above 8 m/s and power density above 720 W/m2 no matter the period evaluated, in the dry season. The predominant wind direction in the observed dry periods was from East to West and the turbulence intensity is smaller during dry season of El Niño. Besides, the bathymetry of the State of Ceará is shallow and the large ships route is far beyond the coast, offering no danger to future endeavors.

Development of PLS–path model for understanding the role of precursors on ground level ozone concentration in Gulfport, Mississippi, USA

Ground-level ozone (GLO) is produced by a complex chain of atmospheric chemical reactions that depend on precursor emissions from natural and anthropogenic sources. GLO concentration in a particular location is also governed by local weather and climatic factors. In this work an attempt was made to explore a Partial Least Squares Path Modeling (PLS–PM) approach to quantify the interrelationship between local conditions (weather parameters and primary air pollution) and GLO concentrations. PLS path modeling algorithm was introduced and applied to GLO concentration analyses at Gulfport, Mississippi, USA. In the present analysis, three latent variables were selected: PRC (photochemical reaction catalyst), MP (meteorological factor), and OPP (other primary air pollutants). The three latent variables included 14 indicators for the analysis; with PRC having two (extraterrestrial radiation on horizontal surface, and extraterrestrial radiation normal to the sun), MP having nine (temperature, dew point, relative humidity, pressure, visibility, maximum wind speed, average wind speed, precipitation, and wind direction) and OPP having three (NO2, PM2.5, and SO2) parameters. The resulting model revealed that PRC had significant direct impact on GLO concentration but very small overall effect. This is because PRC had significant indirect negative impact on GLO via MP. Thus, when both direct and indirect effects were taken into account, PRC emerged as having the weakest effect on GLO. The third variable (OPP) also had a positive impact on GLO concentration.

A case study on occurrence of an unusual structure in the sodium layer over Gadanki, India

The height-time-concentration map of neutral sodium (Na) atoms measured by a Na lidar during the night of 18 to 19 March 2007 over Gadanki, India (13.5° N, 79.2° E) reveals an unusual structure in the Na layer for around 30 min in the altitude range of 92 to 98 km which is similar to the usual ‘C’ type structures observed at other locations. In order to understand the physical mechanism behind the generation of this unusual event, an investigation is carried out combining the data from multiple instruments that include the meteor wind radar over Thiruvananthapuram, India (8.5° N, 77° E) and the SABER instrument onboard the TIMED satellite. The temperature and wind profiles from the data set provided by these instruments allow us to infer the Richardson number which is found to be noticeably less than the canonical threshold of 0.25 above 92 km over Thiruvananthapuram suggesting the plausible generation of Kelvin-Helmholtz (KH) billows over southwestern part of the Indian subcontinent. Based on the average wind speed and direction over Thiruvananthapuram, it is proposed that the KH-billow structure was modified due to the background wind and was advected with it in nearly ‘frozen-in’ condition (without significant decay) in the northeastward direction reaching the Na lidar location (Gadanki). This case study, therefore, presents a scenario wherein the initially deformed KH-billow structure survived for a few hours (instead of a few minutes or tens of minutes as reported in earlier works) in an apparently ‘frozen-in’ condition under favorable background conditions. In this communication, we suggest a hypothesis where this deformed KH-billow structure plays crucial role in creating the abovementioned unusual structure observed in the Na layer over Gadanki.

A stochastic fire spread model for north Patagonia based on fire occurrence maps

Understanding fire spread in different ecosystems is of fundamental importance for conservation, management and anticipating the effects of environmental changes. Tailoring existing fire spread models to particular landscapes is challenging because it demands a substantial data collection effort. Here we develop an objective way to fit simple stochastic fire spread models based on readily available data from documented fire events (i.e. approximate ignition point, preexisting vegetation, final perimeter, topography, and average wind direction). We use a simulation-based approach founded on Approximate Bayesian Computation, which allows for a thorough exploration of parameter space as well as the quantification of uncertainty around best estimates. As illustration, we use data from nine fire events that occurred during dry years in northern Patagonia, Argentina. We found that fire spreads readily in shrublands, while forests tend to act as firebreaks. Topography has a strong effect not only because fire moves easily upslope but also because it modulates wind direction. Finally, aspect affects fire spread mainly in forests, probably due to its effects on fuel moisture. Simulating fire spread sampling parameters from the approximated joint posterior distribution resulted in individual fires roughly similar to the ones used for model fitting. Furthermore, the fitted model was able to produce simulated fire-size distributions in good agreement with the historical record for dry years in Nahuel Huapi National Park, Patagonia. The approach presented here can be used in places where standard fuel models have not yet been developed.

Comparing measurements of the horizontal wind speed of a 2D Multi-Lidar and a cup anemometer

Wind measurements of a 2D Multi-Lidar and a mast mounted cup anemometer are compared in this study. Average wind speed and direction as well as the turbulence intensity of the wind speed are considered. Data analysis is mainly performed using standard regression analysis on 10 minute average data and the calculation of the power spectral density. The results show a good agreement regarding wind speed and direction and the turbulence intensity of the horizontal wind.

Needles of Pinus halepensis as biomonitors of bioaerosol emissions.

We propose using the surface of pine trees needles to biomonitor the bioaerosol emissions at a composting plant. Measurements were based on 16S rRNA gene copy numbers of Saccharopolyspora rectivirgula, a bioindicator of composting plant emissions. A sampling plan was established based on 29 samples around the emission source. The abundance of 16S rRNA gene copies of S. rectivirgula per gram of Pinus halepensis needles varied from 104 to 102 as a function of the distance. The signal reached the background level at distances around the composting plant ranging from 2 km to more than 5.4 km, depending on the local topography and average wind directions. From these values, the impacted area around the source of bioaerosols was mapped.