Quantifying Dust Radiative Impact on the Red Sea
Abstract
Dust plays an essential role in the formation of the Red Sea energy balance and circulation regimes. Recent research based on the MODIS and SEVIRI satellite observations and colocated ship-based measurements for the first time revealed extremely high dust optical depths over the Red Sea. Over the southern Red Sea, dust optical depth at 630 nm exceeds 1 during summer seasons. The up-to-date global models do not capture the associated regional climate responses. To quantify dust radiative impact, we employ fully coupled ocean-atmosphere model, which is capable of reproducing regional climate and interactively accounts for the spectral optical properties of aerosols. The dust optical properties are derived from the SEVIRI climatological optical depth and are consistent with the Aeronet inversion algorithm products.
Our long high-resolution (34 years, 10-km atmospheric and 2-km oceanic grid spacings) simulations show that dust radiative cooling significantly perturbs salinity distribution, freshwater budget and circulation regimes in the Red Sea. At the sea surface, dust climatological daily mean radiative effect reaches -60 Wm-2 and 25 Wm-2 in SW and LW, respectively. A range of validations supports these results. The simulated top of the atmosphere dust radiative effect compares well with independently derived GERB satellite product with the uncertainty of 15 Wm-2. The simulated regional energy balance is verified against the top of the atmosphere CERES fluxes with the tight uncertainty of 2.5 Wm-2. Accounting for dust radiative effects reduces the simulated sea surface temperature and heat budget biases in the Red Sea substantially.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.A21I2809S
- Keywords:
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- 0305 Aerosols and particles;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 3305 Climate change and variability;
- ATMOSPHERIC PROCESSESDE: 3322 Land/atmosphere interactions;
- ATMOSPHERIC PROCESSESDE: 1622 Earth system modeling;
- GLOBAL CHANGE