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204 results on '"Basart, S."'

10. Validation report of the CAMS near-real-time global atmospheric composition service: Period December 2021 – February 2022

Author

Arola, A., Basart, S., Benedictow, A., Bennouna, Y., Blechschmidt, A.-M., Bouarar, I., Cuevas, E., Errera, Q., Eskes, H.J., Griesfeller, J., Kapsomenakis, J., Langerock, B., Mortier, A., Pison, I., Pitkänen, M., Ramonet, M., Richter, A., Schulz, M., Tarniewicz, J., Thouret, V., Tsikerdekis, A., Warneke, T., and Zerefos, C.

Published
2022
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12. Validation report of the CAMS near-real-time global atmospheric composition service: Period June – August 2021

Author

Basart, S., Benedictow, Anna M.K., Bennouna, Y., Blechschmidt, Anne M., Chabrillat, S., Christophe, Y., Cuevas, E., El-Yazidi, A., Flentje, H., Fritzsche, P., Hansen, Kaj Mantzius, Im, Ulas, Kapsomenakis, J., Langerock, B., Richter, A., Thouret, V., Wagner, Annette, Warneke, T., Zerefos, C., Ramonet, Michel, Sudarchikova, N., Schulz, M, Errera, Q., and Eskes, H.

Published
2021

14. Validation report of the CAMS near-real-time global atmospheric composition service:Period March – May 2021

Author

Basart, S., Benedictow, Anna M.K., Bennouna, Y., Blechschmidt, Anne M., Chabrillat, S., Christophe, Y., Cuevas, E., El-Yazidi, A., Flentje, H., Fritzsche, P., Hansen, Kaj Mantzius, Im, Ulas, Kapsomenakis, J., Langerock, B., Richter, A., Thouret, V., Wagner, Annette, Warneke, T., Zerefos, C., Errera, Q., Ramonet, Michel, Sudarchikova, N., Schulz, M, and Eskes, H.

Published
2021

15. Forecasting the Northern African Dust Outbreak Towards Europe in April 2011: A Model Intercomparison

Author

Huneeus, N, Basart, S, Fiedler, S, Morcrette, J.-J, Benedetti, A, Mulcahy, J, Terradellas, E, Pérez García-Pando, C, Pejanovic, G, and Nickovic, S

Subjects
Meteorology And Climatology, Earth Resources And Remote Sensing
Abstract

In the framework of the World Meteorological Organisation's Sand and Dust Storm Warning Advisory and Assessment System, we evaluated the predictions of five state-of-the-art dust forecast models during an intense Saharan dust outbreak affecting western and northern Europe in April 2011. We assessed the capacity of the models to predict the evolution of the dust cloud with lead times of up to 72 hours using observations of aerosol optical depth (AOD) from the AErosol RObotic NETwork (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) and dust surface concentrations from a ground-based measurement network. In addition, the predicted vertical dust distribution was evaluated with vertical extinction profiles from the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP). To assess the diversity in forecast capability among the models, the analysis was extended to wind field (both surface and profile), synoptic conditions, emissions and deposition fluxes. Models predict the onset and evolution of the AOD for all analysed lead times. On average, differences among the models are larger than differences among lead times for each individual model. In spite of large differences in emission and deposition, the models present comparable skill for AOD. In general, models are better in predicting AOD than near-surface dust concentration over the Iberian Peninsula. Models tend to underestimate the long-range transport towards northern Europe. Our analysis suggests that this is partly due to difficulties in simulating the vertical distribution dust and horizontal wind. Differences in the size distribution and wet scavenging efficiency may also account for model diversity in long-range transport.

Published
2016
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16. Validation report of the CAMS near-real-time global atmospheric composition service:Period December 2020 – February 2021

Author

Schulz, M., Errera, Q., Ramonet, M., Sudarchikova, N., Eskes, H.J., Basart, S., Benedictow, A., Bennouna, Y., Blechschmidt, A.-M., Chabrillat, S., Christophe, Y., Cuevas, E., El-Yazidi, A., Flentje, H., Fritzsche, P., Hansen, K.M., Im, U., Kapsomenakis, J., Langerock, B., Richter, A., Thouret, V., Wagner, A., Warneke, T., Zerefos, C., Schulz, M, Errera, Q., Ramonet, Michel, Sudarchikova, N., and Eskes, H.

Published
2021

20. Validation report of the CAMS near-real-time global atmospheric composition service:Period September - November 2020

Author

Basart, S., Benedictow, Anna M.K., Bennouna, Y., Blechschmidt, Anne M., Chabrillat, S., Christophe, Y., Cuevas, E., El-Yazidi, A., Flentje, H., Fritzsche, P., Hansen, Kaj Mantzius, Im, Ulas, Kapsomenakis, J., Langerock, B., Richter, A., Thouret, V., Wagner, Annette, Warneke, T., Zerefos, C., Sudarchikova, N., Schulz, M., Errera, Q., Ramonet, Michel, and Eskes, H.

Published
2021

21. Validation report of the CAMS near-real-time global atmospheric composition service: Period June – August 2021

Author

Ramonet, M., Sudarchikova, N., Schulz, M., Errera, Q., Eskes, H.J., Basart, S., Benedictow, A., Bennouna, Y., Blechschmidt, A.-M., Chabrillat, S., Christophe, Y., Cuevas, E., El-Yazidi, A., Flentje, H., Fritzsche, P., Hansen, K.M., Im, U., Kapsomenakis, J., Langerock, B., Richter, A., Thouret, V., Wagner, A., Warneke, T., and Zerefos, C.

Published
2021
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23. Observation characterisation and validation methods document

Author

Eskes, H.J., Basart, S., Benedictow, A., Bennouna, Y., Blechschmidt, A.-M., Chabrillat, S., Christophe, Y., Cuevas, E., Flentje, H., Hansen, K.M., Kapsomenakis, J., Langerock, B., Ramonet, M., Richter, A., Schulz, M., Sudarchikova, N., Wagner, A., Warneke, T., Zerefos, C., and Eskes, H.

Published
2021
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24. Validation report of the CAMS near-real-time global atmospheric composition service: Period March – May 2021

Author

Errera, Q., Ramonet, M., Sudarchikova, N., Schulz, M., Eskes, H.J., Basart, S., Benedictow, A., Bennouna, Y., Blechschmidt, A.-M., Chabrillat, S., Christophe, Y., Cuevas, E., El-Yazidi, A., Flentje, H., Fritzsche, P., Hansen, K.M., Im, U., Kapsomenakis, J., Langerock, B., Richter, A., Thouret, V., Wagner, A., Warneke, T., and Zerefos, C.

Published
2021
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27. Validation report of the CAMS near-real-time global atmospheric composition service: Period September – November 2020

Author

Sudarchikova, N., Schulz, M., Errera, Q., Ramonet, M., Eskes, H.J., Basart, S., Benedictow, A., Bennouna, Y., Blechschmidt, A.-M., Chabrillat, S., Christophe, Y., Cuevas, E., El-Yazidi, A., Flentje, H., Fritzsche, P., Hansen, K.M., Im, U., Kapsomenakis, J., Langerock, B., Richter, A., Thouret, V., Wagner, A., Warneke, T., and Zerefos, C.

Published
2021
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31. Training Materials and Best Practices for Chemical Weather/Air Quality Forecasting

Author

Appel, K., Ching, J., Freitas, E., ́Garcia-Pando, C., Henze, D., Jorba, O., Keller, C., Knievel, J., Lee, P., Makar, P., Masson, V., Delle Monache, L., Saide, P., ́Del Rio, J., Sartelet, K., Sofiev, M., Stockwell, W., Tong, D., Yu, S., Zhang, Y., Zhou, C., Zilitinkevich, S., Aliaga, D., Andrade, M., Basart, S., Benedetti, A., Bocquet, M., Calmarini, S., Carmichael, G., Cope, M., da Silva, A., Duc, H., Flemming, J., Grell, G., Inness, A., Johansson, L., Kaiser, J., Karppinen, A., Kipling, Z., Martilli, A., Mills, G., Pagowski, M., Pfister, G., Ren, C., Rolph, G., Sanchez, B., Sandu, A., Sokhi, R., Zhang , Y., and Baklanov , A.

Published
2020

32. COST Lecture 2019 AE GM Barcelona: International Network to Encourage the Use of Monitoring and Forecasting Dust Products (InDust)

Author

Nemuc, A., Basart, S., Tobías, Aurelio, Nickovic, S., Kazadzis, S., Mona, L., Amiridis, V., Vukovic, A., Christel, I.J., Waldhauserová, P.D., and Monteiro, A.

Abstract

Amongst the most significant extreme meteorological phenomena are the Sand and Dust Storms (SDS). Owing to significant amounts of airborne mineral dust particles generated during these events, SDS have impacts on climate, the environment, human health, and many socio-economic sectors (e.g. aviation, solar energy management). Many studies and reports have underlined that the society has to understand, manage and mitigate the risks and effects of SDS on life, health, property, the environment and the economy in a more unified way. The EU-funded European Cooperation in Science and Technology (COST) Action 'InDust: International network to encourage the use of monitoring and forecasting Dust products' has an overall objective to establish a network involving research institutions, service providers and potential end users on airborne dust information. We are a multidisciplinary group of international experts on aerosol measurements, aerosol modelling, stakeholders and social scientists working together, exchanging ideas to better coordinate and harmonize the process of transferring dust observation and prediction data to users, as well as to assist the diverse socio-economic sectors affected by the presence of high concentrations of airborne mineral dust. This article highlights the importance of being actively engaged in research networking activities, supported by EU and COST actions since common efforts help not only each scientist by shaping their expertise and strengthening their position, but also all communities.

Published
2020

38. Numerical Prediction of Dust

Author

Benedetti, Angela, Baldasano, J. M, Basart, S, Benincasa, F, Boucher, O, Brooks, M, Chen, J. P, Colarco, P. R, Gong, S, Huneeus, N, Jones, L, Lu, S, Menut, L, Mulcahy, J, Nickovic, S, Morcrette, J.-J, Perez, C, Reid, J. S, Sekiyama, T. T, Tanaka, T, Terradellas, E, Westphal, D. L, Zhang, X.-Y, and Zhou, C.-H

Subjects
Meteorology And Climatology
Abstract

Covers the whole breadth of mineral dust research, from a scientific perspective Presents interdisciplinary work including results from field campaigns, satellite observations, laboratory studies, computer modelling and theoretical studies Explores the role of dust as a player and recorder of environmental change This volume presents state-of-the-art research about mineral dust, including results from field campaigns, satellite observations, laboratory studies, computer modelling and theoretical studies. Dust research is a new, dynamic and fast-growing area of science and due to its multiple roles in the Earth system, dust has become a fascinating topic for many scientific disciplines. Aspects of dust research covered in this book reach from timescales of minutes (as with dust devils, cloud processes, and radiation) to millennia (as with loess formation and oceanic sediments), making dust both a player and recorder of environmental change. The book is structured in four main parts that explore characteristics of dust, the global dust cycle, impacts of dust on the Earth system, and dust as a climate indicator. The chapters in these parts provide a comprehensive, detailed overview of this highly interdisciplinary subject. The contributions presented here cover dust from source to sink and describe all the processes dust particles undergo while travelling through the atmosphere. Chapters explore how dust is lifted and transported, how it affects radiation, clouds, regional circulations, precipitation and chemical processes in the atmosphere, and how it deteriorates air quality. The book explores how dust is removed from the atmosphere by gravitational settling, turbulence or precipitation, how iron contained in dust fertilizes terrestrial and marine ecosystems, and about the role that dust plays in human health. We learn how dust is observed, simulated using computer models and forecast. The book also details the role of dust deposits for climate reconstructions. Scientific observations and results are presented, along with numerous illustrations. This work has an interdisciplinary appeal and will engage scholars in geology, geography, chemistry, meteorology and physics, amongst others with an interest in the Earth system and environmental change.

Published
2013

39. Atmospheric Dust Modeling from Meso to Global Scales with the Online NMMB/BSC-Dust Model Part 2: Experimental Campaigns in Northern Africa

Author

Haustein, K, Perez, C, Baldasano, J. M, Jorba, O, Basart, S, Miller, R. L, Janjic, Z, Black, T, Nickovic, S, Todd, M. C, Washington, R, Muller, D, Tesche, M, Weinzierl, B, Esselborn, M, and Schladitz, A

Subjects
Meteorology And Climatology, Geophysics
Abstract

The new NMMB/BSC-Dust model is intended to provide short to medium-range weather and dust forecasts from regional to global scales. It is an online model in which the dust aerosol dynamics and physics are solved at each model time step. The companion paper (Perez et al., 2011) develops the dust model parameterizations and provides daily to annual evaluations of the model for its global and regional configurations. Modeled aerosol optical depth (AOD) was evaluated against AERONET Sun photometers over Northern Africa, Middle East and Europe with correlations around 0.6-0.7 on average without dust data assimilation. In this paper we analyze in detail the behavior of the model using data from the Saharan Mineral dUst experiment (SAMUM-1) in 2006 and the Bodele Dust Experiment (BoDEx) in 2005. AOD from satellites and Sun photometers, vertically resolved extinction coefficients from lidars and particle size distributions at the ground and in the troposphere are used, complemented by wind profile data and surface meteorological measurements. All simulations were performed at the regional scale for the Northern African domain at the expected operational horizontal resolution of 25 km. Model results for SAMUM-1 generally show good agreement with satellite data over the most active Saharan dust sources. The model reproduces the AOD from Sun photometers close to sources and after long-range transport, and the dust size spectra at different height levels. At this resolution, the model is not able to reproduce a large haboob that occurred during the campaign. Some deficiencies are found concerning the vertical dust distribution related to the representation of the mixing height in the atmospheric part of the model. For the BoDEx episode, we found the diurnal temperature cycle to be strongly dependant on the soil moisture, which is underestimated in the NCEP analysis used for model initialization. The low level jet (LLJ) and the dust AOD over the Bodélé are well reproduced. The remaining negative AOD bias (due to underestimated surface wind speeds) can be substantially reduced by decreasing the threshold friction velocity in the model.

Published
2012
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