Research Areas

Weather, AQI and NWP

Coupling of aerosols within numerical weather prediction modeling

Aerosols and their impact in our forecasts

satellite, iss, international space station

Dust and Clouds from the ISS. Source: NASA

Over the last two decades much progress has been achieved in terms of characterizing aerosol properties, identifying their spatiotemporal extent, and determining their role in the planetary radiative balance (Ramanathan et al., 2001). As a result of that endeavor, the scientific community has been able to recognize that aerosols have a “direct effect” on climate by modifying the planet’s radiative budget and redistributing heat in the atmosphere, and an “indirect effect” by modifying cloud development, precipitation, and optical properties (IPCC, 2014). Additionally, it is implicit that these effects are reliant on aerosol altitude, and on the reflectance (albedo) of the underlying surface (Lyapustin et al., 2011; Bauer and Menon, 2012; Xu et al., 2017). Aerosols are now regular components of numerical weather prediction models (NWP), and it has been shown through model sensitivity studies that aerosol radiative coupling effects are not trivial regarding their influence on resolved weather processes (Carmona et al., 2008; Milton et al., 2008; Mulcahy et al., 2014; Oyola et al., 2016, 2019; Toll et al., 2016). For example, increased aerosol scattering and absorption of incoming shortwave (SW) and outgoing longwave radiation (OLR) fields modify the atmospheric heating profile and can affect both large-scale and regional circulation patterns (Haywood et al., 2005; Mulcahy et al., 2010). Furthermore, the omission of the scattering and absorption properties, in particular for mineral dust and biomass burning, was identified in case study analysis as the principal cause of significant biases (in the order of 50–56 W m−2, over dust source regions) in both model OLR at the top-of-atmosphere (TOA) (Haywood et al., 2005) and surface SW radiation fields (Milton et al., 2008). Examples of significant improvement found in NWP skill when considering aerosols include forecasts of the African Easterly Jet at the European Centre for Medium-Range Forecast (ECMWF) and reduction of temperature and precipitation seasonal mean-biases (e.g., Thompkins et al., 2005; Rodwell and Jung, 2008). In the case of real-time or near real-time prognostic aerosols, Mulcahy et al. (2014) demonstrated an overall improvement in the NWP radiative budget fields by means of an improved representation of the direct radiative forcing, while Toll et al. (2015, 2016) demonstrated improvement in forecast of near-surface fields over extreme aerosol events, such as the 2010 fires that occurred in Russia.

Nevertheless, significant uncertainty remains when it comes to understanding the atmosphere’s response to different aerosol physical properties, particularly on day-to-day scales that impact weather and air quality. Despite the potential benefits of proper aerosol characterization in NWP systems, aerosols physics have to date not been fully coupled with the operational weather modeling components for several reasons. Our research groups focuses on improving aerosol representation by (a) exploring current and future satellite remote sensing capabilities to improve the  representation and knowledge of aerosol spatiotemporal distribution in NWP models — particularly in the vertical, (b) advance the understanding of the physical/chemical effects of aerosols on the atmospheric energy balance, and in particular their various interactions with clouds, which are not well constrained in weather models; and (c) exploring current and new computational techniques that can improve aerosol representation in NWP.