Spatial and Temporal Variation of the Near-Surface Wind Environment in the Sahara Desert, North Africa

The Sahara Desert is the largest source of dust on Earth, and has a significant impact on global atmospheric changes. Wind is the main dynamic factor controlling the transport and intensity of dust in the Sahara Desert. This study comprehensively analyzed the spatial and temporal variation in the wind regime of the Sahara Desert from 1980 to 2019 using data from 17 meteorological stations to improve awareness of global atmospheric changes and the intensity of regional aeolian activities. All wind speed parameters decreased from northwest to southeast. While there were significant differences in the trends of temporal variation in wind speed among the different regions, there was an overall decreasing trend across the Sahara Desert, with an average wind speed of 0.09 m s−1 10 a−1. This decrease was closely related to wind frequency. The easterly, westerly, and northerly winds dominated, with more complex wind direction in the northern region. Seasonal differences in wind direction were observed in all regions. The wind direction frequency of wind speeds >6 m s−1 exceeded those with wind speeds <6 m s−1 in the western and northern regions, whereas other regions showed an opposite pattern. The highest drift potential (DP) and resultant drift potential (RDP) were found in the western and northern regions, and during spring and winter. There was a trend of decreasing annual variation in DP and RDP in all regions. The directional variability (RDP/DP) indicated mostly intermediate and high variability in wind direction. Resultant drift direction (RDD) indicated that a mainly southwest wind direction. No apparent trends in temporal variation in RDD and RDP/DP were observed. Total DP was strongly influenced by DP and the magnitude and frequency of strong winds in the prevailing wind direction. No strong correlation between wind regimes and dune types was observed in this desert, indicating the complexity of factors affecting dune morphology.

Jump bifurcation phenomenon during varying wind speeds in floating offshore wind turbines

Floating Offshore Wind Turbines (FOWTs) are susceptible to an instability which has come to be called negative damping. Conventional land based wind turbine controllers when used with FOWTs may cause large amplitude platform pitch oscillations. Most controllers have since been improved to reduce motions due to this phenomenon. In this paper, the motions induced using one of the original controllers is studied. The current study is performed using the coupled time domain program FAST-SIMDYN that was developed in Marine Dynamics Laboratory (MDL) at Texas A&M University. It is capable of studying large amplitude motions of Floating Offshore Wind Turbines. FOWTs use various controller algorithms of operation based on the available wind speed depending on various power output objectives i.e., to either maximize or level out power absorption. It is observed that the transition region for controllers is often chaotic. So most studies focus on operations away from the transition region below and above the transition wind speeds. Here we study the transition region using the theoretical insight of non-linear motion response of structures. This study reveals the presence of a very interesting and potentially hazardous nonlinear phenomenon, bifurcation. This finding could help explain the chaotic motion response that is observed in the transition region of controllers. Understanding the nature and cause of bifurcation could prove very useful for future design of FOWT controllers.

Lidar-derived aerosol concentration and their relationship with horizontal winds over an urban location

Lidar-derived aerosol vertical profiles obtained at Pune, a low latitude tropical station, on about 535 days during a ten-year period (1987 – 96) along with simultaneous pilot-balloon wind (speed and direction) data of India Meteorological Department, Pune have been used in the study to investigate the influence of horizontal winds on the aerosol characteristics in the lower atmosphere. Aerosol column content in the atmospheric boundary layer (surface to 1100 m altitude above ground-level) as well as aerosol number density at the surface level (at 50 m) showed relatively higher values over the lidar site whenever the winds were blowing from the main urban and industrial regions of the city of Pune. This effect was found to be more pronounced during the winter season. Wind speeds also correlate well with increased aerosol loading, but only during selected high wind speed episodes. Thus the study shows that the short- and long-term increases in aerosol concentration/loading over the observation site are, to a large extent, influenced by horizontal winds in the surface layers and this in turn, can be attributed to the increasing human/urban activity around the lidar site over the years.

Estimation of monsoon wind characteristics in India

A detailed statistical analysis of monthly average wind speed data of monsoon period (June-September) for the year 1921-90 for 57 stations spread all over India have been reported. Probability densities, average wind speeds, standard deviations, kurtosis and skewness of wind speed frequency distribution for each station have been worked out. Histograms depicting relative frequency distribution of average wind speeds have also been prepared. It is observed that the different histograms do not exhibit any similarity among themselves indicating thereby that no single distribution is uniformly applicable for all the stations. It is also seen that the average wind speeds during monsoon period over major part of India varies from 7 to 14 kmph. Further, at most of the stations average monsoon wind speed is generally higher than average annual wind speeds. It is also noted that most of the time the wind speed exceeds 10 kmph in coastal regions of Gujarat and southern parts of the peninsular India. The information generated is of multi fold application such as (i) Identification of sites suitable for installation of Wind Energy Conversion Systems (ii) Development of Driving Rain Index and (iii) Design of buildings for creating comfortable environment indoors.

DMSP-SSM/I retrieval of proper surface winds during monsoon depression

Recently developed various global microwave algorithms for DMSP-SSM/I satellite data are used for the estimation of surface winds over the Indian ocean. Sea surface wind speeds from these algorithms are compared with sea surface wind speeds reported by coincidental Minicoy island (lowest height 2 m a.s.l.) station over the Arabian sea. A statistical comparison of these algorithms is made in terms of rms error, correlation coefficient, bias and standard deviation. Algorithm of Petty showed best results in the comparison. On the basis of this algorithm a notable characteristic feature such as acquiring of large area of strong surface winds (12-15 ms-1) to the south of dipping of monsoon trough in head Bay and then encircling of these winds during further development of low and depression (22-27 July 1992) is observed. This complete life cycle monitoring assessment of monsoon depression in respect of surface winds based on DMSP-SSM/I satellite data encourages to utilise our IRS-P4 (Oceansat-1) satellite data at different frequencies to emerge more details of various weather systems over the Indian region.

Wind and wave regime over the Bombay high area under the influence of cyclonic storms

Temporal distributions of wind and wave over Bombay High Area (BHA) during cyclone period have been studied. Ten years’ (1990-99) data of BHA during cyclone period have been used. It is found that under the influence of cyclonic storms strong southwesterly winds prevail over the BHA in pre-monsoon and weaker east to southeasterly winds during post-monsoon. Southwesterly wave with heights exceeding 20 feet are encountered in BHA during pre-monsoon and south easterlies with wave height reaching up to 12 feet in post monsoon. Analysis of situations with different storm locations also yielded similar results. Relationships between wind speeds and wave height as well as the distance of the storm centre over BHA have been established.

Bayesian method for estimating Weibull parameters for wind resource assessment in the Equatorial region: a comparison between two-parameter and three-parameter Weibull distributions

The two-parameter Weibull distribution has garnered much attention in the assessment of windenergy potential. The estimation of the shape and scale parameters of the distribution has broughtforth a successful tool for the wind energy industry. However, it may be inappropriate to use thetwo-parameter Weibull distribution to assess energy at every location, especially at sites wherelow wind speeds are frequent, such as the Equatorial region. In this work, a robust technique inwind resource assessment using a Bayesian approach for estimating Weibull parameters is firstproposed. Secondly, the wind resource assessment techniques using a two-parameter Weibulldistribution and a three-parameter Weibull distribution which is a generalized form of twoparameterWeibull distribution are compared. Simulation studies confirm that the Bayesianapproach seems a more robust technique for accurate estimation of Weibull parameters. Theresearch is conducted using data from seven sites in Equatorial region from 1o N of Equator to 19oSouth of Equator. Results reveal that a three-parameter Weibull distribution with non-zero shiftparameter is a better fit for wind data having a higher percentage of low wind speeds (0-1 m/s) andlow skewness. However, wind data with a smaller percentage of low wind speeds and highskewness showed better results with a two-parameter distribution that is a special case of threeparameterWeibull distribution with zero shift parameter. The results also demonstrate that theproposed Bayesian approach and application of a three-parameter Weibull distribution areextremely useful in accurate estimate of wind power and annual energy production.

Evaluating dust emission model performance using dichotomous satellite observations of dust emission

Measurements of dust in the atmosphere have long been used to calibrate dust emission models. However, there is growing recognition that atmospheric dust confounds the magnitude and frequency of emission from dust sources and hides potential weaknesses in dust emission model formulation. In the satellite era, dichotomous (presence = 1 or absence = 0) observations of dust emission point sources (DPS) provide a valuable inventory of regional dust emission. We used these DPS data to develop an open and transparent framework to routinely evaluate dust emission model (development) performance using coincidence of simulated and observed dust emission (or lack of emission). To illustrate the utility of this framework, we evaluated the recently developed albedo-based dust emission model (AEM) which included the traditional entrainment threshold (u*ts) at the grain scale, fixed over space and static over time, with sediment supply infinite everywhere. For comparison with the dichotomous DPS data, we reduced the AEM simulations to its frequency of occurrence in which soil surface wind friction velocity (us*) exceeds the u*ts, P(us* > u*ts). We used a global collation of nine DPS datasets from established studies to describe the spatio-temporal variation of dust emission frequency. A total of 37,352 unique DPS locations were aggregated into 1,945 1° grid boxes to harmonise data across the studies which identified a total of 59,688 dust emissions. The DPS data alone revealed that dust emission does not usually recur at the same location, are rare (1.8 %) even in North Africa and the Middle East, indicative of extreme, large wind speed events. The AEM over-estimated the occurrence of dust emission by between 1 and 2 orders of magnitude. More diagnostically, the AEM simulations coincided with dichotomous observations ~71 % of the time but simulated dust emission ~27 % of the time when no dust emission was observed. Our analysis indicates that u*ts was typically too small, needed to vary over space and time, and at the grain-scale u*ts is incompatible with the us* scale (MODIS 500 m). During observed dust emission, us* was too small because wind speeds were too small and/or the wind speed scale (ERA5; 11 km) is incompatible with the us* scale. The absence of any limit to sediment supply caused the AEM to simulate dust emission whenever P (us* > u*ts), producing many false positives when and where wind speeds were frequently large. Dust emission model scaling needs to be reconciled and new parameterisations are required for u*ts and to restrict sediment supply varying over space and time. Whilst u*ts remains poorly constrained and unrealistic assumptions persist about sediment supply and availability, the DPS data provide a basis for the calibration of dust emission models for operational use. As dust emission models develop, these DPS data provide a consistent, reproducible, and valid framework for their routine evaluation and potential model optimisation. This work emphasises the growing recognition that dust emission models should not be evaluated against atmospheric dust.

Occurrence of Low-Level Jets over the Eastern U.S. Coastal Zone at Heights Relevant to Wind Energy

Two years of high-resolution simulations conducted with the Weather Research and Forecasting (WRF) model are used to characterize the frequency, intensity and height of low-level jets (LLJ) over the U.S. Atlantic coastal zone. Meteorological conditions and the occurrence and characteristics of LLJs are described for (i) the centroids of thirteen of the sixteen active offshore wind energy lease areas off the U.S. east coast and (ii) along two transects extending east from the U.S. coastline across the northern lease areas (LA). Flow close to the nominal hub-height of wind turbines is predominantly northwesterly and southwesterly and exhibits pronounced seasonality, with highest wind speeds in November, and lowest wind speeds in June. LLJs diagnosed using vertical profiles of modeled wind speeds from approximately 20 to 530 m above sea level exhibit highest frequency in LA south of Massachusetts, where LLJs are identified in up to 12% of hours in June. LLJs are considerably less frequent further south along the U.S. east coast and outside of the summer season. LLJs frequently occur at heights that intersect the wind turbine rotor plane, and at wind speeds within typical wind turbine operating ranges. LLJs are most frequent, intense and have lowest core heights under strong horizontal temperature gradients and lower planetary boundary layer heights.