Sultan Al-Yahyai

Impact of climate change on the wheat-growing season over Iran

The objective of this paper is to derive and analyze the present and future climate projections over the region of wheat production over Iran. In addition, the projected future climate fluctuation results will be used to assist the maximum performance of wheat and to be used as the main basis for planning changes in the farming calendar in Iran. Observed climate (temperature and degree day) changes during the period (1951–2009) will be discussed. Projected future changes up to 2100 based on the MAGICC/SCENGEN 5.3 compound model was utilized. Furthermore, 18 scenarios were used to derive a single GCM model referred to as the United Kingdom Hadley Center Global Environment Model, which will be used to select the worst, best, and average scenario.

Contribution of atmospheric processes to the degradation of air quality: case study (Sohar Industrial Area, Oman)

The impact of the air pollution generated by any industrial activities may be further aggravated if the location of the industrial area is exposed to certain atmospheric characteristics. Under such conditions, the likelihood of accumulation of local air pollution is high. This paper uses two approaches (statistical and numerical simulation) to investigate the contribution of atmospheric processes towards degradation of air quality. A case study of the two approaches was conducted over Sohar Industrial Area in the Sultanate of Oman. Measured wind data were used to account for specific atmospheric characteristics such as stagnation, ventilation, and recirculation using the statistical approach. In the second approach, numerical weather prediction model was used to simulate mesoscale circulation phenomena such as sea breeze and its contribution to the processes affecting the air quality. The study demonstrates that the atmospheric processes appear to contribute substantially to the degradation of air quality in the Sohar Industrial Area. The statistical analysis shows that the atmospheric dilution potential of Sohar Industrial Area is prone to stagnation and recirculation, rather than ventilation. Moreover, model simulation shows that there is a seasonal variation in the contribution of atmospheric processes to the degradation of the air quality at Sohar Industrial Area.

Estimating wind resource over Oman using meso-scale modeling

The High Resolution Model (HRM) which is a Numerical Weather Prediction (NWP) meso-scale model was used to estimate wind resource over Oman at 7 km resolution. The simulation was conducted for year 2009. Wind resource at different vertical levels was calculated. Seasonal and annual means are also presented. Model simulation results were validated through a comparison to two weather stations measurements. Good correlation between simulation results and real measurements was obtained.

Trajectory Calculation as Forecasting Support Tool for Dust Storms

In arid and semiarid regions, dust storms are common during windy seasons. Strong wind can blow loose sand from the dry surface. The rising sand and dust is then transported to other places depending on the wind conditions (speed and direction) at different levels of the atmosphere. Considering dust as a moving object in space and time, trajectory calculation then can be used to determine the path it will follow. Trajectory calculation is used as a forecast supporting tool for both operational and research activities. Predefined dust sources can be identified and the trajectories can be precalculated from the Numerical Weather Prediction (NWP) forecast. In case of long distance transported dust, the tool should allow the operational forecaster to perform online trajectory calculation. This paper presents a case study for using trajectory calculation based on NWP models as a forecast supporting tool in Oman Meteorological Service during some dust storm events. Case study validation results showed a good agreement between the calculated trajectories and the real transport path of the dust storms and hence trajectory calculation can be used at operational centers for warning purposes.

Wind resource assessment using numerical weather prediction models and multi-criteria decision making technique: case study (Masirah Island, Oman)

The Authority for Electricity Regulation in Oman has recently announced the implementation of a 500 kW wind farm pilot project in Masirah Island. Detailed wind resource assessment is then required to identify the most suitable location for this project. This paper presents wind resource assessment using nested ensemble numerical weather prediction (NWP) models approach at 2.8 km resolution and multi-criteria decision making (MCDM) technique. A case study based on the proposed approach is conducted over Masirah Island, Oman. The resource assessment over the island was based on the mean wind speed and wind power distribution over the entire island at different heights. In addition, important criteria such as turbulence intensity and peak hour matching are also considered. The NWP model results were verified against the available 10 m wind data observations from the meteorological station in the northern part of the island. The resource assessment criteria were evaluated using MCDM technique to score the locations over the island based on their suitability for wind energy applications. Two MCDM approaches namely equally weighted and differently weighted criteria were implemented in this paper.

Geometrical approach for wind farm symmetrical layout design optimization

Wind farm layout orientation plays an important factor to reduce the total wake loss and hence increase the capacity factor of the wind farm. Different wind farms layout design optimization techniques are widely used and classified into five different types including, Pattern Search Algorithm (PSAs), Gradient Search Algorithms (GSAs), Greedy Heuristic Algorithms (GHAs), Simulated Annealing Algorithms (SAAs), and Genetic Algorithms (GAs). The quality of the optimized solution depends on the complexity of the used algorithm. This paper proposes a simple geometrical approach which can be easily used by designers in setting their initial layout which will save significant computational time during the design optimization process. It considers symmetrical wind farm layouts which satisfy visual environmental constraints. The proposed approach shows that the optimum wind farm layout is displaced around 18o from the predominant wind median axis. Validation of the proposed approach is also presented for three sites in the Sultanate of Oman using the European computer program “Wind Atlas Analysis and Application Program (WAsP)”.

Optimal micro-siting of small wind turbine using numerical simulation

The main objective of this study is to conduct an optimal micro-siting of 1kW wind turbine to provide electricity for the eco-house project at Sultan Qaboos University (SQU). The study utilizes the Numerical Weather Prediction models data to provide the required wind information. WAsP application is used to calculate the wind climatology and the annual energy production. It was found the closest potential site can generate 1.945MW at 10m and 2.938MW at 30m above the ground. On the other hand, the farthest potential site which is around 45m away from the eco-house can generate 1.449MW and 3.150MW at 10m and 30m above the ground respectively.

Wind resource assessment over Iran using weather station data

This paper investigates the wind energy potential over 42 sites in Iran. Ten years of wind data (1996–2005) were used from weather stations located at these sites. Different criteria were considered, including vertical wind profile, wind power density (WPD), wind frequency distribution, wind sustainability, seasonal variation, turbulence intensity and peak demand matching. Air density and roughness length, which play important role in the calculation of the WPD potential, were derived for each station site. Simple scoring was used to rank the mostly windy sites. It is concluded that Sistan and Bluchistan governorate (Zabol) has the highest potential. Zahedan, Jazireh Kish and Ardebil also have high wind power potential.

Evaluation of ensemble NWP models for dynamical downscaling of air temperature over complex topography in a hot climate: A case study from the Sultanate of Oman

This paper evaluates the use of ensemble numerical weather prediction (NWP) models for dynamical downscaling of temperature over a complex, hot region. This approach delivers information about the uncertainty of the NWP models and provides probabilistic information for comparison with the currently used single NWP model. An ensemble system was constructed using four members with a 7 km resolution over Oman. Two limited-area models (LAMs), the high-resolution model (HRM) and the model from the Consortium for Small-Scale Modeling (COSMO) formed the ensemble members. The two LAMs were derived and initialized using the general circulation model (GCM) data from the German Global Model (GME), which runs at 40 km resolution, using two different initial atmospheric states. The first initial state was provided by the 3Dvar data assimilation system at the German Weather Service (Deutscher Wetterdienst, DWD),and the second initial state was provided from the reanalysis data (ERA-Interim) from the European Centre for Medium-Range Weather Forecasts (ECMWF). The results reveal the uncertainty in temperature prediction related to the uncertainty of the NWP models that were used and indicate that there is no best model for the entire domain. On average, the ensemble mean performed better than individual members.

Recent Observed Climate Change Over Oman

This study examined trends in temperature and precipitation parameters for the Sultanate of Oman in the period between 1980 and 2013. The data set has been carefully checked for the quality control for its homogeneity with the help of low density (8 stations) and it was possible to arrive at a clear picture of climate change in Oman. The results of this study found that the general pattern of Oman’s mean annual temperature is of warming, with all stations, subregions and all Oman average showing statistically significant warming at 0.05 level. Across stations of Khasab and Sohar, highest and statistically significant mean annual warming trends are found (0.5 °C decade−1). Results of seasonal warming showed consistent and widespread most of the year except in wintertime. These trends are mostly higher in magnitude over the non-monsoonal area relative to the monsoonal areas in across Oman. The increase in the mean annual maximum temperature is less widespread in relation to the mean annual temperature, which has reported statistically significant increase only for 2 stations. The highest statistically significant trend of 1.6 °C decade−1 reported at Khasab station and for minimum temperature, all stations observed and sub-regions across Oman on an average show statistically significant warming trends, with the highest annual trends observed in the monitoring station of Sohar (1.1 °C decade−1). Data monitored at stations of Saiq and Thumrait reported 0.6 °C decade−1. Total precipitation of annual values show only at 2 stations with statistically significant trends. Out of studied 8 stations, only two stations show negative trends (i.e. Saiq = −74.0 mm decade−1 and Salalah = −10.8 mm decade−1). Further, trends observed at remaining stations are negative and statistically not significant. Therefore, the results of this study offer an evidence that climate of Oman has changed during the past three decades.