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Arunas P. Kuciauskas, Peng Xian, Edward J. Hyer, Mayra I. Oyola, and James R. Campbell

Abstract

During the spring and summer months, the greater Caribbean region typically experiences pulses of moderate to heavy episodes of airborne African dust concentrations that originate over the Sahara Desert and propagate westward across the tropical North Atlantic basin. These dust episodes are often contained within the Saharan air layer (SAL), an elevated air mass (between 850–500 hPa) marked by very dry and warm conditions within the lowest levels. During its westward transport, the SAL’s distinct environmental characteristics can persist well into the Gulf of Mexico and southern United States. As a result, the Caribbean population is susceptible to airborne dust levels that often exceed healthy respiratory limits. One of the major responsibilities within the National Weather Service in San Juan, Puerto Rico (NWS-PR), is preparing the public within their area of responsibility (AOR) for such events. The Naval Research Laboratory Marine Meteorology Division (NRL-MMD) is sponsored by the National Oceanic and Atmospheric Administration (NOAA) to support the NWS-PR by providing them with an invaluable “one stop shop” web-based resource (hereafter SAL-WEB) that is designed to monitor these African dust events. SAL-WEB consists of near-real-time output generated from ground-based instruments, satellite-derived imagery, and dust model forecasts, covering the extent of dust from North Africa, westward across the Atlantic basin, and extending into Mexico. The products within SAL-WEB would serve to augment the Advanced Weather Interactive Processing System (AWIPS-II) infrastructure currently in operation at the NWS-PR. The goal of this article is to introduce readers to SAL-WEB, along with current and future research underway to provide improvements in African dust prediction capabilities.

Open access
Jared W. Marquis, Mayra I. Oyola, James R. Campbell, Benjamin C. Ruston, Carmen Córdoba-Jabonero, Emilio Cuevas, Jasper R. Lewis, Travis D. Toth, and Jianglong Zhang

Abstract

Numerical weather prediction systems depend on Hyperspectral Infrared Sounder (HIS) data, yet the impacts of dust-contaminated HIS radiances on weather forecasts has not been quantified. To determine the impact of dust aerosol on HIS radiance assimilation, we use a modified radiance assimilation system employing a one-dimensional variational assimilation system (1DVAR) developed under the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Numerical Weather Prediction–Satellite Application Facility (NWP-SAF) project, which uses the Radiative Transfer for TOVS (RTTOV). Dust aerosol impacts on analyzed temperature and moisture fields are quantified using synthetic HIS observations from rawinsonde, Micropulse Lidar Network (MPLNET), and Aerosol Robotic Network (AERONET). Specifically, a unit dust aerosol optical depth (AOD) contamination at 550 nm can introduce larger than 2.4 and 8.6 K peak biases in analyzed temperature and dewpoint, respectively, over our test domain. We hypothesize that aerosol observations, or even possibly forecasts from aerosol predication models, may be used operationally to mitigate dust induced temperature and moisture analysis biases through forward radiative transfer modeling.

Open access
James R. Campbell, David A. Peterson, Jared W. Marquis, Gilberto J. Fochesatto, Mark A. Vaughan, Sebastian A. Stewart, Jason L. Tackett, Simone Lolli, Jasper R. Lewis, Mayra I. Oyola, and Ellsworth J. Welton
Open access