Convective distribution of dust over the Arabian Peninsula: the impact of model resolution

Abstract

Abstract. Along the coasts of the Arabian Peninsula, convective dust storms are a considerable source of mineral dust to the atmosphere. Reliable predictions of convective dust events are necessary to determine their effects on air quality, visibility, and the radiation budget. In this study, the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) is used to simulate a 2016 summertime dust event over the Arabian Peninsula and examine the variability in dust fields and associated vertical transport due to the choice of convective parameterization and convection-permitting versus parameterized convection. Simulations are run at 45 and 15 km grid spacing with multiple cumulus parameterizations, and are compared to a 3 km simulation that permits explicit dry and moist convective processes. Five separate cumulus parameterizations at 15 km grid spacing were tested to quantify the spread across different parameterizations. Finally, the impact these variations have on radiation, specifically aerosol heating rates is also investigated. On average, in these simulations the convection-permitting case produces higher quantities of dust than the parameterized cases in terms of dust uplift potential, vertical dust concentrations, and vertical dust fluxes. Major drivers of this discrepancy between the simulations stem from the convection-permitting case exhibiting higher surface wind speeds during convective activity; lower dust emission wind threshold velocities due to drier soil; and more frequent, stronger vertical velocities which transport dust aloft and increase the atmospheric lifetime of these particles. For aerosol heating rates in the lowest levels, the shortwave effect prevails in the convection-permitting case with a net cooling effect, whereas a longwave net warming effect is present in the parameterized cases. The spread in dust concentrations across cumulus parameterizations at the same grid resolution (15 km) is an order of magnitude lower than the impact of moving from parameterized towards explicit convection. We conclude that tuning dust emissions in coarse-resolution simulations can only improve the results to first-order and cannot fully rectify the discrepancies originating from disparities in the representation of convective dust transport.

Rain, Wind, and Dust Connections in the Sahel

“…The spatial resolution of large‐scale meteorological models is generally suitable to simulate synoptic events but they cannot resolve correctly mesoscale updrafts and downdrafts that are responsible for most of the highest dust emissions in many areas (e.g., Bukowski & van den Heever, 2020; Pantillon et al., 2016). In particular, these models are unable to simulate the dust events associated with MCSs, mainly because their parameterization of the convection does not represent correctly the density currents and their propagation (e.g., Garcia‐Carreras et al., 2013; Largeron et al., 2015; Marsham et al., 2011).…”

Improving dust simulations in WRF-Chem v4.1.3 coupled with the GOCART aerosol module

“…WRF-Chem is a popular open-source tool that is widely used to study atmospheric chemistry, air quality, and aerosols (Jish Prakash et al, 2015;Khan et al, 2015;Kalenderski et al, 2013;Kalenderski and Stenchikov, 2016;Parajuli et al, 2019;Anisimov et al, 2017;Osipov and Stenchikov, 2018). This model has been used extensively to study aerosols and their impact on air quality (Fast et al, 2006(Fast et al, , 2009Ukhov et al, 2020a, b;Parajuli et al, 2020), climate (Zhao et al, 2010(Zhao et al, , 2011Chen et al, 2014;Fast et al, 2006) and to analyze dust outbreaks (Bian et al, 2011;Chen et al, 2014;Fountoukis et al, 2016;Ma et al, 2019;LeGrand et al, 2019;Su and Fung, 2015;Eltahan et al, 2018;Bukowski and van den Heever, 2020) in the ME and north Africa (Zhang et al, 2015;Flaounas et al, 2016;Rizza et al, 2017;Karagulian et al, 2019;Rizza et al, 2018), North America (Zhao et al, 2012), India (Dipu et al, 2013;Kumar et al, 2014), and Australia (Nguyen et al, 2019). Many aforementioned studies utilized the WRF-Chem model coupled with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) aerosol module (Chin et al, 2002).…”

“…The GOCART module simulates major tropospheric aerosol components, including sulfate, dust, black and organic carbon, and sea salt, and includes algorithms for dust and sea salt emissions, dry deposition, and gravitational settling. The GOCART module is one of the most popular aerosol modules used in WRF-Chem (Bian et al, 2011;Dipu et al, 2013;Kumar et al, 2014;Chen et al, 2014;Su and Fung, 2015;Zhang et al, 2015;Flaounas et al, 2016;Fountoukis et al, 2016;Rizza et al, 2017;Flaounas et al, 2017;Nabavi et al, 2017;Chen et al, 2018;Rizza et al, 2018;Ma et al, 2019;LeGrand et al, 2019;Parajuli et al, 2019;Yuan et al, 2019;Ukhov et al, 2020a;Eltahan et al, 2018;Nguyen et al, 2019;Bukowski and van den Heever, 2020).…”

A fast visible-wavelength 3D radiative transfer model for numerical weather prediction visualization and forward modeling

“…Modified values of surface albedo and ARF are used in the presence of snow or ice cover with maximum values in the forward-scattering direction. Similar to earlier work (Cox and Munk, 1954), a sun glint model with a fixed value of mean wave slope is used over water except that waves are given a random orientation without a preferred direction. Scattering from below the water surface is also considered.…”