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Abstract Long‐range aerosol transport is an important physical mechanism for ecological, biological, and hydrological elements of the earth system. Regarding the latter, regional climate models have no way of assimilating future aerosol concentrations, so dust aerosol emissions must be parameterized using local landscape and meteorological conditions. The purpose of this study is to evaluate the accuracy of different dust emission settings within the Weather Research and Forecasting model coupled with chemistry (WRF‐Chem) to facilitate future dynamical downscaling work. This study performs nine WRF‐Chem hindcasts, each utilizing a different dust emission configuration, from 1 March to 31 May 2015, coinciding with a Saharan air layer (SAL) dust outbreak during the 2015 Caribbean drought. WRF‐Chem aerosol optical depth (AOD) and Gálvez‐Davison Index (GDI), a convective forecasting parameter, are validated against analogous MODIS, AERONET, and ERA5 products. In aggregate, the GOCART dust emission scheme with Air Force Weather Agency modifications (GOCART‐AFWA) achieved the best balance between AOD and GDI accuracy when employing the default tuning constant (1.00). As the schemes emitted dust more aggressively, WRF‐Chem produced warming at 500 hPa, reducing GDI over the central and eastern Atlantic near the modeled dust trajectory. Though AOD was generally too low over the southwest Atlantic, the eastern Caribbean occupies a transition zone between negative and positive AOD biases where this field was hindcast with relative accuracy. Meanwhile, areas with positive AOD biases were associated with negative GDI biases (and vice versa) indicating the covariability between SAL dust loadings and thermodynamic conditions in the tropical north Atlantic.
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Synoptic Analysis and WRF‐Chem Model Simulation of Dust Events in the Southwestern United States
Abstract Dust transported from rangelands of the Southwestern United States (US) to mountain snowpack in the Upper Colorado River Basin during spring (March‐May) forces earlier and faster snowmelt, which creates problems for water resources and agriculture. To better understand the drivers of dust events, we investigated large‐scale meteorology responsible for organizing two Southwest US dust events from two different dominant geographic locations: (a) the Colorado Plateau and (b) the northern Chihuahuan Desert. High‐resolution Weather Research and Forecasting coupled with Chemistry model (WRF‐Chem) simulations with the Air Force Weather Agency dust emission scheme incorporating a MODIS albedo‐based drag‐partition was used to explore land surface‐atmosphere interactions driving two dust events. We identified commonalities in their meteorological setups. The meteorological analyses revealed that Polar and Sub‐tropical jet stream interaction was a common upper‐level meteorological feature before each of the two dust events. When the two jet streams merged, a strong northeast‐directed pressure gradient upstream and over the source areas resulted in strong near‐surface winds, which lifted available dust into the atmosphere. Concurrently, a strong mid‐tropospheric flow developed over the dust source areas, which transported dust to the San Juan Mountains and southern Colorado snowpack. The WRF‐Chem simulations reproduced both dust events, indicating that the simulations represented the dust sources that contributed to dust‐on‐snow events reasonably well. The representativeness of the simulated dust emission and transport in different geographic and meteorological conditions with our use of albedo‐based drag partition provides a basis for additional dust‐on‐snow simulations to assess the hydrologic impact in the Southwest US.
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- Award ID(s):
- 2012091
- PAR ID:
- 10522343
- Publisher / Repository:
- Journal of Geophysical Research - Atmospheres
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Atmospheres
- Volume:
- 129
- Issue:
- 13
- ISSN:
- 2169-897X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1029/2023JD040650
