Carlson, T. N. and Prospero, J. M.: The large-scale movement of Saharan air outbreaks over the northern equatorial Atlantic, J. Appl. Meteorol. Climatol., 11, 283–297, 1972. a
Carroll, B. J., Nehrir, A. R., Kooi, S. A., Collins, J. E., Barton-Grimley, R. A., Notari, A., Harper, D. B., and Lee, J.: Differential absorption lidar measurements of water vapor by the High Altitude Lidar Observatory (HALO): retrieval framework and first results, Atmos. Meas. Tech., 15, 605–626,
https://doi.org/10.5194/amt-15-605-2022, 2022.
a
Collow, A., Buchard, V., Chin, M., Colarco, P., Darmenov, A., and da Silva, A.: Supplemental Documentation for GEOS Aerosol Products, GMAO Office Note No. 22 (Version 1.1), 8 pp.,
http://gmao.gsfc.nasa.gov/pubs/office_notes (last access: 24 November 2023), 2023.
a,
b
Dubovik, O., Sinyuk, A., Lapyonok, T., Holben, B., Mishchenko, M., Yang, P., Eck, T., Volten, H., Muñoz, O., and Veihelmann, B.: Non-spherical aerosol retrieval method employing light scattering by spheroids, Geophys. Res. Lett., 29, 1415,
https://doi.org/10.1029/2001GL014506, 2002.
a,
b
Dunion, J. P. and Velden, C. S.: The impact of the Saharan air layer on Atlantic tropical cyclone activity, B. Am. Meteorol. Soc., 85, 353–366, 2004.
a,
b,
c,
d
Fu, Q. and Liou, K.: On the correlated k-distribution method for radiative transfer in nonhomogeneous atmospheres, J. Atmos. Sci., 49, 2139–2156, 1992. a
Fu, Q. and Liou, K. N.: Parameterization of the radiative properties of cirrus clouds, J. Atmos. Sci., 50, 2008–2025, 1993. a
Fu, Q., Liou, K., Cribb, M., Charlock, T., and Grossman, A.: Multiple scattering parameterization in thermal infrared radiative transfer, J. Atmos. Sci., 54, 2799–2812, 1997. a
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., and Wargan, K.: The modern-era retrospective analysis for research and applications, version 2 (MERRA-2), J. climate, 30, 5419–5454, 2017. a
Global Modeling and Assimilation Office (GMAO): MERRA-2 inst6_3d_ana_Nv: 3d, 6-Hourly, Instantaneous, Model-Level, Analysis, Analyzed Meteorological Fields V5.12.4, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set],
https://doi.org/10.5067/IUUF4WB9FT4W, 2015a.
a
Global Modeling and Assimilation Office (GMAO): MERRA-2 inst3_3d_aer_Nv: 3d, 3-Hourly, Instantaneous, Model-Level, Assimilation, Aerosol Mixing Ratio V5.12.4, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set],
https://doi.org/10.5067/LTVB4GPCOTK2, 2015b.
a
Global Modeling and Assimilation Office (GMAO): MERRA-2 inst3_2d_gas_Nx: 2d, 3-Hourly, Instantaneous, Single-Level, Assimilation, Aerosol Optical Depth Analysis V5.12.4, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set],
https://doi.org/10.5067/HNGA0EWW0R09, 2015c.
a
GOES-R Series Program: NOAA GOES-R Series Advanced Baseline Imager (ABI) Level 1b Data, NOAA National Centers for Environmental Information,
https://doi.org/10.25921/tvws-w071, 2019.
a
Grogan, D. F. and Thorncroft, C. D.: The characteristics of African easterly waves coupled to Saharan mineral dust aerosols, Q. J. Roy. Meteorol. Soc., 145, 1130–1146, 2019. a
Gu, Y., Liou, K., Ou, S., and Fovell, R.: Cirrus cloud simulations using WRF with improved radiation parameterization and increased vertical resolution, J. Geophys. Res.-Atmos., 116, D06119,
https://doi.org/10.1029/2010JD014574, 2011.
a,
b
Gu, Y., Liou, K. N., Ou, S. C., and Fovell, R.: Cirrus cloud simulations using WRF with improved radiation parameterization and increased vertical resolution, J. Geophys. Res., 116, D06119,
https://doi.org/10.1029/2010JD014574, 2022 (data available at:
http://people.atmos.ucla.edu/gu/Fu-Liou-Gu_Radiative_Transfer_Model.htm, last access: 15 May 2022).
a
Huffman, G. J., Bolvin, D. T., Braithwaite, D., Hsu, K.-L., Joyce, R. J., Kidd, C., Nelkin, E. J., Sorooshian, S., Stocker, E. F., Tan, J., and Wolff, D. B.: Integrated multi-satellite retrievals for the global precipitation measurement (GPM) mission (IMERG), Satellite Precipitation Measurement: 1, 343–353, 2020. a
Inness, A., Ades, M., Agustí-Panareda, A., Barré, J., Benedictow, A., Blechschmidt, A.-M., Dominguez, J. J., Engelen, R., Eskes, H., Flemming, J., Huijnen, V., Jones, L., Kipling, Z., Massart, S., Parrington, M., Peuch, V.-H., Razinger, M., Remy, S., Schulz, M., and Suttie, M.: The CAMS reanalysis of atmospheric composition, Atmos. Chem. Phys., 19, 3515–3556,
https://doi.org/10.5194/acp-19-3515-2019, 2019 (data available at:
https://ads.atmosphere.copernicus.eu/datasets/cams-global-reanalysis-eac4?tab=download, last access: 10 September 2023).
a,
b
IPCC: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Core Writing Team, Lee, H., and Romero, J., IPCC, Geneva, Switzerland, 1–34 pp.,
https://doi.org/10.59327/IPCC/AR6-9789291691647.001, 2023.
a
Jones, C., Mahowald, N., and Luo, C.: Observational evidence of African desert dust intensification of easterly waves, Geophys. Res. Lett., 31, 17,
https://doi.org/10.1029/2004GL020107, 2004.
a
Jury, M. R. and Santiago, M. J.: Composite analysis of dust impacts on African easterly waves in the Moderate Resolution Imaging Spectrometer era, J. Geophys. Res.-Atmos., 115, D16213,
https://doi.org/10.1029/2009JD013612, 2010.
a
Kahn, R., Gaitley, B., Martonchik, J., Diner, D., Crean, K., and Holben, B.: Multiangle Imaging Spectroradiometer (MISR) global aerosol optical depth validation based on 2 years of coincident Aerosol Robotic Network (AERONET) observations, J. Geophys. Res.-Atmos., 110, D10S04,
https://doi.org/10.1029/2004JD004706, 2005.
a,
b
Karyampudi, V. M., Palm, S. P., Reagen, J. A., Fang, H., Grant, W. B., Hoff, R. M., Moulin, C., Pierce, H. F., Torres, O., Browell, E. V., and Melfi, S. H.: Validation of the Saharan dust plume conceptual model using lidar, Meteosat, and ECMWF data, B. Am. Meteorol. Soc., 80, 1045–1076, 1999. a
Landsea, C. W., Bell, G. D., Gray, W. M., and Goldenberg, S. B.: The extremely active 1995 Atlantic hurricane season: Environmental conditions and verification of seasonal forecasts, Mon. Weather Rev., 126, 1174–1193, 1998. a
Lawton, Q. A., Majumdar, S. J., Dotterer, K., Thorncroft, C., and Schreck III, C. J.: The influence of convectively coupled Kelvin waves on African easterly waves in a wave-following framework, Mon. Weather Rev., 150, 2055–2072, 2022.
a,
b
Lei, L., Berkoff, T. A., Gronoff, G., Su, J., Nehrir, A. R., Wu, Y., Moshary, F., and Kuang, S.: Retrieval of UVB aerosol extinction profiles from the ground-based Langley Mobile Ozone Lidar (LMOL) system, Atmos. Meas. Tech., 15, 2465–2478,
https://doi.org/10.5194/amt-15-2465-2022, 2022.
a
Lenhardt, E. D., Gao, L., Redemann, J., Xu, F., Burton, S. P., Cairns, B., Chang, I., Ferrare, R. A., Hostetler, C. A., Saide, P. E., Howes, C., Shinozuka, Y., Stamnes, S., Kacarab, M., Dobracki, A., Wong, J., Freitag, S., and Nenes, A.: Use of lidar aerosol extinction and backscatter coefficients to estimate cloud condensation nuclei (CCN) concentrations in the southeast Atlantic, Atmos. Meas. Tech., 16, 2037–2054,
https://doi.org/10.5194/amt-16-2037-2023, 2023.
a
Levy, R. C., Remer, L. A., Kleidman, R. G., Mattoo, S., Ichoku, C., Kahn, R., and Eck, T. F.: Global evaluation of the Collection 5 MODIS dark-target aerosol products over land, Atmos. Chem. Phys., 10, 10399–10420,
https://doi.org/10.5194/acp-10-10399-2010, 2010.
a,
b
Lyapustin, A., Martonchik, J., Wang, Y., Laszlo, I., and Korkin, S.: Multiangle implementation of atmospheric correction (MAIAC): 1. Radiative transfer basis and look-up tables, J. Geophys. Res.-Atmos., 116, D03210,
https://doi.org/10.1029/2010JD014985, 2011.
a
Ma, P.-L., Zhang, K., Shi, J. J., Matsui, T., and Arking, A.: Direct radiative effect of mineral dust on the development of African easterly waves in late summer, 2003–07, J. Appl. Meteorol. Climatol., 51, 2090–2104, 2012. a
Mulcahy, J. P., Walters, D. N., Bellouin, N., and Milton, S. F.: Impacts of increasing the aerosol complexity in the Met Office global numerical weather prediction model, Atmos. Chem. Phys., 14, 4749–4778,
https://doi.org/10.5194/acp-14-4749-2014, 2014.
a,
b
Nalli, N. R. and Stowe, L. L.: Aerosol correction for remotely sensed sea surface temperatures from the National Oceanic and Atmospheric Administration advanced very high resolution radiometer, J. Geophys. Res.-Oceans, 107, 36–1, 2002. a
Nalli, N. R., Joseph, E., Morris, V. R., Barnet, C. D., Wolf, W. W., Wolfe, D., Minnett, P. J., Szczodrak, M., Izaguirre, M. A., Lumpkin, R., and Xie, H.: Multiyear observations of the tropical Atlantic atmosphere: Multidisciplinary applications of the NOAA Aerosols and Ocean Science Expeditions, B. Am. Meteorol. Soc., 92, 765–789, 2011. a
Nowottnick, E. P., Zawislak, J., Nehrir, A. R., Maring, H., Piña, A. J., McCarty, W., Reid, J. S., Chen, S.-H., Rowe, A. K., Sakaeda, N., and Robinson, C. E.: The NASA Convective Processes Experiment-Cabo Verde (CPEX-CV): Mission Overview and Saharan Dust Measurements Obtained in the East Atlantic in September 2022, in: 103rd AMS Annual Meeting, AMS, 2023. a
Oyola, M. I.: Implementation of a Global Dust Physical Sea Surface Temperature Retrieval For Numerical Weather Prediction Applications, Ph.D. thesis, Howard University,
https://www.proquest.com/openview/dddff1a071a32cebd52d963a74f7494e/ (last access: 23 September 2023), 2015.
a,
b
Oyola, M. I., Campbell, J. R., Xian, P., Bucholtz, A., Ferrare, R. A., Burton, S. P., Kalashnikova, O., Ruston, B. C., and Lolli, S.: Quantifying the direct radiative effect of absorbing aerosols for numerical weather prediction: a case study, Atmos. Chem. Phys., 19, 205–218,
https://doi.org/10.5194/acp-19-205-2019, 2019.
a
Petty, G. W.: A First Course in Atmospheric Thermodynamics., Sundog Publishing, 2008. a
Pratt, A. S. and Evans, J. L.: Potential impacts of the Saharan air layer on numerical model forecasts of North Atlantic tropical cyclogenesis, Weather Forecast., 24, 420–435, 2009. a
Ramanathan, V., Crutzen, P. J., Kiehl, J., and Rosenfeld, D.: Aerosols, climate, and the hydrological cycle, Science, 294, 2119–2124, 2001. a
Randles, C., Da Silva, A., Buchard, V., Colarco, P., Darmenov, A., Govindaraju, R., Smirnov, A., Holben, B., Ferrare, R., Hair, J., and Shinozuka, Y.: The MERRA-2 aerosol reanalysis, 1980 onward. Part I: System description and data assimilation evaluation, J. Climate, 30, 6823–6850, 2017. a
Reale, O., Lau, W. K., Kim, K.-M., and Brin, E.: Atlantic tropical cyclogenetic processes during SOP-3 NAMMA in the GEOS-5 global data assimilation and forecast system, J. Atmos. Sci., 66, 3563–3578, 2009. a
Reale, O., Lau, K., and da Silva, A.: Impact of interactive aerosol on the African easterly jet in the NASA GEOS-5 global forecasting system, Weather Forecast., 26, 504–519, 2011. a
Reed, R., Klinker, E., and Hollingsworth, A.: The structure and characteristics of African easterly wave disturbances as determined from the ECMWF operational analysis/forecast system, Meteorol. Atmos. Phys., 38, 22–33, 1988. a
Reed, R. J., Norquist, D. C., and Recker, E. E.: The structure and properties of African wave disturbances as observed during phase III of GATE, Mon. Weather Rev., 105, 317–333, 1977.
a,
b
Sun, Y. and Zhao, C.: Influence of Saharan dust on the large-scale meteorological environment for development of tropical cyclone over North Atlantic Ocean Basin, J. Geophys. Res.-Atmos., 125, e2020JD033454,
https://doi.org/10.1029/2020JD033454, 2020.
a
Toll, V., Gleeson, E., Nielsen, K., Männik, A., Mašek, J., Rontu, L., and Post, P.: Impacts of the direct radiative effect of aerosols in numerical weather prediction over Europe using the ALADIN-HIRLAM NWP system, Atmos. Res., 172, 163–173, 2016.
a,
b
Xu, F., Van Harten, G., Diner, D. J., Kalashnikova, O. V., Seidel, F. C., Bruegge, C. J., and Dubovik, O.: Coupled retrieval of aerosol properties and land surface reflection using the Airborne Multiangle SpectroPolarimetric Imager, J. Geophys. Res.-Atmos., 122, 7004–7026, 2017. a
Yu, H., Tan, Q., Zhou, L., Zhou, Y., Bian, H., Chin, M., Ryder, C. L., Levy, R. C., Pradhan, Y., Shi, Y., Song, Q., Zhang, Z., Colarco, P. R., Kim, D., Remer, L. A., Yuan, T., Mayol-Bracero, O., and Holben, B. N.: Observation and modeling of the historic “Godzilla” African dust intrusion into the Caribbean Basin and the southern US in June 2020, Atmos. Chem. Phys., 21, 12359–12383,
https://doi.org/10.5194/acp-21-12359-2021, 2021.
a
Zawislak, J., Nowottnick, E., and Nehrir, A.: Convective Processes Experiment – Cabo Verde (CPEX-CV) Field Campaign Collection, NASA EOSDIS Global Hydrometeorology Resource Center Distributed Active Archive Center, Huntsville, Alabama, U.S.A., NASA [data set],
https://doi.org/10.5067/CPEXCV/DATA101, 2022a.
a
Zawislak, J., Nowottnick, E. P., Nehrir, A. R., Pina, A., McCarty, W., and Maring, H. B.: Overview of Measurements Collected during NASA's Convective Processes Experiment-Cabo Verde (CPEX-CV) in the East Atlantic in September 2022, AGU Fall Meeting Abstracts, A25B–08, 2022b.
Zhang, J., Reid, J. S., Christensen, M., and Benedetti, A.: An evaluation of the impact of aerosol particles on weather forecasts from a biomass burning aerosol event over the Midwestern United States: observational-based analysis of surface temperature, Atmos. Chem. Phys., 16, 6475–6494,
https://doi.org/10.5194/acp-16-6475-2016, 2016.
a
