47 research outputs found

    Towards an end-to-end analysis and prediction system for weather, climate, and Marine applications in the Red Sea

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    AbstractThe Red Sea, home to the second-longest coral reef system in the world, is a vital resource for the Kingdom of Saudi Arabia. The Red Sea provides 90% of the Kingdom’s potable water by desalinization, supporting tourism, shipping, aquaculture, and fishing industries, which together contribute about 10%–20% of the country’s GDP. All these activities, and those elsewhere in the Red Sea region, critically depend on oceanic and atmospheric conditions. At a time of mega-development projects along the Red Sea coast, and global warming, authorities are working on optimizing the harnessing of environmental resources, including renewable energy and rainwater harvesting. All these require high-resolution weather and climate information. Toward this end, we have undertaken a multipronged research and development activity in which we are developing an integrated data-driven regional coupled modeling system. The telescopically nested components include 5-km- to 600-m-resolution atmospheric models to address weather and climate challenges, 4-km- to 50-m-resolution ocean models with regional and coastal configurations to simulate and predict the general and mesoscale circulation, 4-km- to 100-m-resolution ecosystem models to simulate the biogeochemistry, and 1-km- to 50-m-resolution wave models. In addition, a complementary probabilistic transport modeling system predicts dispersion of contaminant plumes, oil spill, and marine ecosystem connectivity. Advanced ensemble data assimilation capabilities have also been implemented for accurate forecasting. Resulting achievements include significant advancement in our understanding of the regional circulation and its connection to the global climate, development, and validation of long-term Red Sea regional atmospheric–oceanic–wave reanalyses and forecasting capacities. These products are being extensively used by academia, government, and industry in various weather and marine studies and operations, environmental policies, renewable energy applications, impact assessment, flood forecasting, and more.</jats:p

    Towards an end-to-end analysis and prediction system for weather, climate, and marine applications in the Red Sea

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    Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 102(1), (2021): E99-E122, https://doi.org/10.1175/BAMS-D-19-0005.1.The Red Sea, home to the second-longest coral reef system in the world, is a vital resource for the Kingdom of Saudi Arabia. The Red Sea provides 90% of the Kingdom’s potable water by desalinization, supporting tourism, shipping, aquaculture, and fishing industries, which together contribute about 10%–20% of the country’s GDP. All these activities, and those elsewhere in the Red Sea region, critically depend on oceanic and atmospheric conditions. At a time of mega-development projects along the Red Sea coast, and global warming, authorities are working on optimizing the harnessing of environmental resources, including renewable energy and rainwater harvesting. All these require high-resolution weather and climate information. Toward this end, we have undertaken a multipronged research and development activity in which we are developing an integrated data-driven regional coupled modeling system. The telescopically nested components include 5-km- to 600-m-resolution atmospheric models to address weather and climate challenges, 4-km- to 50-m-resolution ocean models with regional and coastal configurations to simulate and predict the general and mesoscale circulation, 4-km- to 100-m-resolution ecosystem models to simulate the biogeochemistry, and 1-km- to 50-m-resolution wave models. In addition, a complementary probabilistic transport modeling system predicts dispersion of contaminant plumes, oil spill, and marine ecosystem connectivity. Advanced ensemble data assimilation capabilities have also been implemented for accurate forecasting. Resulting achievements include significant advancement in our understanding of the regional circulation and its connection to the global climate, development, and validation of long-term Red Sea regional atmospheric–oceanic–wave reanalyses and forecasting capacities. These products are being extensively used by academia, government, and industry in various weather and marine studies and operations, environmental policies, renewable energy applications, impact assessment, flood forecasting, and more.The development of the Red Sea modeling system is being supported by the Virtual Red Sea Initiative and the Competitive Research Grants (CRG) program from the Office of Sponsored Research at KAUST, Saudi Aramco Company through the Saudi ARAMCO Marine Environmental Center at KAUST, and by funds from KAEC, NEOM, and RSP through Beacon Development Company at KAUST

    Efektivitas Longitudinal Evaluation of Performance (LEP) Sebagai Penilaian Formatif dalam Mencapai Kompetensi Klinik Pencabutan Gigi Anak

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    Background: At the end of the clinical learning phase, it is expected that students achieve competency already set. In the clinical study, direct observation and the provision of feedback by the clinical instructor are important. Therefore, lack of direct observation and feedback is one of the shortages of current medical education Objective: To determine the effectiveness of Longitudinal Evaluation of Performance (LEP) to achieve competence in child tooth extraction and to determine the student�s perception of the clinical learning process in the Child Dental Health Department (IKGA), Faculty of Dentistry, University of Hasanuddin (FKG UNHAS). Methods: This was a quasi-experimental study using �posttest only with control group� study design. The subjects were 39 students of clinical rotations in the study site divided randomly into two groups, namely the intervention group (clinical learning group with LEP) and the control group (group with current learning method). Both groups completed the requirements of the case of the child's teeth extraction as many as 6 cases and 1 case in the post test. The competency achievement was measured using the long case method with using LEP assessment sheet in forms of rating scale, followed by a discussion session. The entire samples filled out questionnaires on the perceptions of clinical learning process. Statistical analysis used the Mann-Whitney test. Qualitative data were analyzed by 2 reviewers. Results: The value of the procedure and communication skills in the intervention group was higher than that in the control group (p <0.05). Students' perception of the importance of direct observation was higher in the intervention group than that in the control group (<0.05). Level of agreement on the importance of direct observation and feedback indicated a high value, while the qualitative data indicated that the LEP method had several advantages such as the presence of feedback that made students know their shortcomings during their stud
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