This project combines advanced biogeochemical and genetic modeling to understand ecosystem dynamics in the Red Sea. It captures key seasonal and interannual patterns in chlorophyll and nutrient transport, linking them to global climate drivers. Genetic analysis reveals that ocean currents and environmental conditions better explain species connectivity than distance alone, offering valuable insights for conservation and marine management.
The project aims at establishing a new paradigm for understanding the dynamics and predictability of precipitation within the Arabian Peninsula, which will encompass both large-scale atmospheric circulation variability and explicit, high-resolution regional atmospheric modeling of organized convective systems.
We are using extreme high resolution general circulation models, and observations at the BAM to shed light on the multi-scale processes of the water exchange through the BAM and their impact on the Red Sea general circulation on various time scales.
This project aims at building a framework for monitoring and predicting oil spills based on remote sensing and our in-house assimilative Red Sea ocean-atmospheric models.
As part of the Center of Excellence NEOM at KAUST, and in collaboration with Imperial College, Delft-Deltares, and the University of Athens, we are working on developing an intelligent virtual design and managing environment that will enable planners and policy makers to develop and manage their city, while being mindful of the health and well-being of its citizens and the environment, and to optimize the usage of its resources
The initiative is a collaborative work with Scripps Institution of Oceanography (SIO), Massachusetts Institute of Technology (MIT), the National Center of Atmospheric Research (NCAR), and Plymouth Marine Laboratory (PML).
The goal of this project is to combine the dynamics of an eddy-resolving configuration of the MIT general circulation ocean model (MITgcm) with all available data in the Red Sea to determine the most accurate and complete estimates of the past and future circulation and variability of the Red Sea. We are using the outputs of these simulations to better understand the climate and the circulation of the Red Sea.
Prediction of coastal flooding due to hurricanes, tropical storms and tsunamis is a problem of international importance. We are working with Prof. Clint Dawson's group from the University of Texas at Austin on developing an advanced data assimilation system for predicting storm surge based on the ADCIRC model and ensemble Kalman filtering techniques.
We are working with Dr. George Triantafyllou from HCMR to develop a 3D coupled physical-biogeochemical model at fine-scale and with multiple depth layers to simulate the ecosystem of the Red Sea. The model will efficiently simulate the pathways of dissolved inorganic nutrients, the fate of particulate organic matter, and the variability of the living functional groups (phyto/zooplankton, bacteria, etc).