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A Multi Linear Regression Model to Derive Dust PM10 in the Sahel Using AERONET Aerosol Optical Depth and CALIOP Aerosol Layer Products

Jean-François Léon, Nadège Martiny, Sébastien Merlet
2020 Remote Sensing  
We propose a new method to retrieve PM10 dust surface concentrations from sun photometer aerosol optical depth (AOD) and CALIPSO/CALIOP Level 2 aerosol layer products.  ...  The method is based on a multi linear regression model that is trained using co-located PM10, AERONET and CALIOP observations at 3 different locations in the Sahel.  ...  observatories in Africa and providing the PM10 and aerosol optical depth, respectively.  ... 
doi:10.3390/rs12183099 doaj:21f34ca1aab344758a5c3e8774f47782 fatcat:h4w5opdw2zflvil2mjjcj3vb6a

Current State of the global operational aerosol multi‐model ensemble: an update from the International Cooperative for Aerosol Prediction (ICAP)

Peng Xian, Jeffrey S. Reid, Edward J. Hyer, Charles R. Sampson, Juli I. Rubin, Melanie Ades, Nicole Asencio, Sara Basart, Angela Benedetti, Partha Bhattacharjee, Malcolm E. Brooks, Peter R. Colarco (+14 others)
2019 Quarterly Journal of the Royal Meteorological Society  
Evaluated with ground-based Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) and data assimilation quality MODerate-resolution Imaging Spectroradiometer (MODIS) retrieval products, the ICAP-MME  ...  Since the first International Cooperative for Aerosol Prediction (ICAP) multi-model ensemble (MME) study, the number of ICAP global operational aerosol models has increased from five to nine.  ...  Since 2012, the system has contributed with global mineral dust and sea-salt aerosol forecasts to the multi-model ensemble of ICAP at a resolution of 1.4 • × 1 • on 24 hybrid sigma-pressure levels.  ... 
doi:10.1002/qj.3497 pmid:31787783 pmcid:PMC6876662 fatcat:rkyzy77z2fh5vkitxaayml7bdq

Operational Dust Prediction [chapter]

Angela Benedetti, José Maria Baldasano, Sara Basart, Francesco Benincasa, Olivier Boucher, Malcolm E. Brooks, Jen-Ping Chen, Peter R. Colarco, Sunlin Gong, Nicolas Huneeus, Luke Jones, Sarah Lu (+12 others)
2014 Mineral Dust  
Dust prediction in numerical weather prediction-type models faces a number of 223 224 A. Benedetti et al. challenges owing to the complexity of the system.  ...  The various models are introduced and described along with an overview on the importance of dust prediction activities and a historical perspective.  ...  The WMO SDS-WAS Dust Model Evaluation Initiative For the evaluation of the WMO SDS-WAS multi-model ensemble, the dust optical depth (DOD) forecast by the models is first drawn together with the AERONET  ... 
doi:10.1007/978-94-017-8978-3_10 fatcat:m2kmyddk4zg75id34yjqzdgcim