Making the Case for High-Resolution Regional Ocean Reanalyses: An Example with the Red Sea

Coastal oceans host 40% of the world population and amount to $1.5 trillion of the global economy. Studying, managing, and developing the coastal regions require decades-long information about their environment. Long-term ocean measurements are, however, lacking for most coastal regions and often global reanalyses are used instead. These are, however, coarse in nature and tuned for the global circulations. The Red Sea (RS) is a narrow basin connected to the Indian Ocean through the Bab-al-Mandab Strait. Despite being the busiest commercial crossroad and hosting the world’s third largest coral reef system, the RS lacks long-term observations. A recent increase in population and an unprecedented acceleration in governmental and industrial developments further emphasized the need for long-term datasets to support its development and the sustainability of its habitats, and to understand its response to a changing climate. Toward this end, we have generated a 20-yr high-resolution reanalysis for the RS (RSRA) using a state-of-the-art ensemble data assimilation system incorporating available observations. Compared to global reanalyses, RSRA provides a markedly better description of the RS general and mesoscale circulation features, their variability, and trends. In particular, RSRA accurately captures the three-layer summer transport through the Bab-al-Mandab, simulated as two-layer transport by some global reanalyses. It further reproduces the seasonal anomalies, whereas global reanalyses misidentify some seasons as anomalous. Global reanalyses further overestimate the interannual variations in salinity, misrepresent the trend in temperature, and underestimate the trend in sea level. Our study clearly emphasizes the importance of generating dedicated high-resolution regional ocean reanalyses. 

Data assimilation Ensembles Model comparison Ocean Models Reanalysis data Regional Models