Mineral dust cycle in the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH) Version 2.0

Abstract

Abstract. We present the dust module in the Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) version 2.0, a chemical weather prediction system that can be used for regional and global modeling at a range of resolutions. The representations of dust processes in MONARCH were upgraded with a focus on dust emission (emission parameterizations, entrainment thresholds, considerations of soil moisture and surface cover), lower boundary conditions (roughness, potential dust sources), and dust–radiation interactions. MONARCH now allows modeling of global and regional mineral dust cycles using fundamentally different paradigms, ranging from strongly simplified to physics-based parameterizations. We present a detailed description of these updates along with four global benchmark simulations, which use conceptually different dust emission parameterizations, and we evaluate the simulations against observations of dust optical depth. We determine key dust parameters, such as global annual emission/deposition flux, dust loading, dust optical depth, mass-extinction efficiency, single-scattering albedo, and direct radiative effects. For dust-particle diameters up to 20 µm, the total annual dust emission and deposition fluxes obtained with our four experiments range between about 3500 and 6000 Tg, which largely depend upon differences in the emitted size distribution. Considering ellipsoidal particle shapes and dust refractive indices that account for size-resolved mineralogy, we estimate the global total (longwave and shortwave) dust direct radiative effect (DRE) at the surface to range between about −0.90 and −0.63 W m−2 and at the top of the atmosphere between −0.20 and −0.28 W m−2. Our evaluation demonstrates that MONARCH is able to reproduce key features of the spatiotemporal variability of the global dust cycle with important and insightful differences between the different configurations.

Assimilating spaceborne lidar dust extinction can improve dust forecasts

“…To simulate the dust cycle, we used the Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model (Pérez et al, 2011;Haustein et al, 2012;Jorba et al, 2012;Badia et al, 2017;Di Tomaso et al, 2017;Klose et al, 2021a). MONARCH is a fully online integrated system for meso-to global-scale applications developed at the BSC.…”

“…Dust is described using eight particle-size bins within 0.2-20 µm in diameter. The MONARCH dust module is described in detail in Pérez et al (2011) and Klose et al (2021a). MONARCH offers a diversity of mineral dust emission schemes along with multiple configurations.…”

“…MONARCH offers a diversity of mineral dust emission schemes along with multiple configurations. As shown in Klose et al (2021a), the emission scheme and their specific configuration have a strong impact on the spatial and temporal behaviour of the simulated dust. Because we aim at showing the impact on the forecast by assimilating two different types of observations and not at showing the best of the forecasts, we preferred to avoid fine-tuning and cherry-picking the best-performing emission scheme and configuration for our study case.…”

“…Our study focuses on the assimilation of desert dust aerosol lidar observations around the two most prolific source regions on Earth: northern Africa and the Middle East. Dust models are subject to substantial uncertainties in the description of lower boundary conditions relevant for dust emission, modelled wind speed, dust emission processes, vertical mixing, particle properties, and deposition (Huneeus et al, 2011;Kok et al, 2021;Klose et al, 2021a). Thus, combining modelling with dust observations through DA is a powerful method to increase the quality of emission estimates (Escribano et al, 2016(Escribano et al, , 2017 and dust forecasts.…”

“…Our work involves both modelling and data assimilation aspects along with the handling of observations and their uncertainty. We use the Multiscale Online Non-hydrostatic AtmospheRe CHemistry (MONARCH) model, formerly known as NMMB/BSC-Dust (Pérez et al, 2011;Klose et al, 2021a), enhanced with a local ensemble transform Kalman filter data assimilation capability (Di Tomaso et al, 2017). MONARCH provides dust forecasts at the World Meteorological Organization (WMO) Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) regional centres for northern Africa, the Middle East, and Europe (http://sds-was.aemet.es/, last access: 11 November 2021; http://dust.aemet.es/, last access: 11 November 2021) hosted by the Spanish Meteorological Agency (AEMET) and the Barcelona Supercomputing Center (BSC).…”