The National Center for Atmospheric Research regional climate model (RegCM) is employed to study the dynamics of the Turkana low-level jet that lies between the Ethiopian and the East African highlands, and also investigate the mechanisms responsible for the observed dry conditions over the Lake Turkana basin that lies in the wider section of the Turkana channel. The role of the large-scale orography and two other forcing factors namely the large-scale monsoonal flow and the Turkana channel depth are investigated in order to understand the kinematics of the jet. The simulated patterns of the Turkana easterly low-level jet compares well with its observed characteristics. Strong winds are indicated in the channel throughout the study period of October to December, with the wind speed decreasing in the middle and wider region of the channel. A split in the jet core is also shown in the middle of the channel. The level of maximum winds (ϳ11 m s Ϫ1) occurs in the layers 930-hPa and 650-hPa levels. The dynamics of the Turkana channel is explained in terms of the orographic channeling effects associated with the Bernoulli theorem as applied to barotropic steady and nonviscous flows. The main results on the forcing mechanisms responsible for the development of the jet can be summarized as follows: (a) orographic forcing is the most important factor, (b) the large-scale monsoon background flow is important in determining the wind speed in the jet cores, (c) the depth of the channel determines the vertical structure and location of the jet cores, and (d) thermal and frictional forcing play equivalent role as that of the large-scale background winds in the formation and maintenance of the jet. Divergence and anticyclonic vorticity partly explains the observed split in the jet cores in the middle of the channel. The dry conditions observed over the Lake Turkana basin are explained in terms of dominant downward vertical velocity, decrease in moisture flux convergence, and increase in temperature flux divergence that inhibit active developments of mesoscale circulations and their interactions with large-scale flow over these areas. The identified regions of strong winds associated with the jet are important to the safety in the aviation industry. These regions may also provide alternative renewable energy resources in the form of wind energy.

Complex traffic situations and high driving workload are the leading contributing factors to traffic crashes. There is a strong correlation between driving performance and driving workload, such as visual workload from traffic signs on highway off-ramps. This study aimed to evaluate traffic safety by analyzing drivers’ behavior and performance under the cognitive workload in complex environment areas. First, the driving workload of drivers was tested based on traffic signs with different quantities of information. Forty-four drivers were recruited to conduct a traffic sign cognition experiment under static controlled environment conditions. Different complex traffic signs were used for applying the cognitive workload. The static experiment results reveal that workload is highly related to the amount of information on traffic signs and reaction time increases with the information grade, while driving experience and gender effect are not significant. This shows that the cognitive workload of subsequent driving experiments can be controlled by the amount of information on traffic signs; Second, driving characteristics and driving performance were analyzed under different secondary task driving workload levels using a driving simulator. Drivers were required to drive at the required speed on a designed highway off-ramp scene. The cognitive workload was controlled by reading traffic signs with different information, which were divided into four levels. Drivers had to make choices by pushing buttons after reading traffic signs. Meanwhile, the driving performance information was recorded. Questionnaires on objective workload were collected right after each driving task. The results show that speed maintenance and lane deviations are significantly different under different levels of cognitive workload, and the effects of driving experience and gender groups are significant. The research results can be used to analyze traffic safety in highway environments, while considering more drivers’ cognitive and driving performance.

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