ABSTRACT. We construct a new class of finite-dimensional C * -quantum groupoids at roots of unity q = e iπ/ℓ , with limit the discrete dual of the classical SU(N ) for large orders. The representation category of our groupoid turns out to be tensor equivalent to the well known quotient C * -category of the category of tilting modules of the non-semisimple quantum group U q (sl N ) of Drinfeld, Jimbo and Lusztig.As an algebra, the C * -groupoid is a quotient of U q (sl N ). As a coalgebra, it naturally reflects the categorical quotient construction. In particular, it is not coassociative, but satisfies axioms of the weak quasi-Hopf C * -algebras: quasi-coassociativity and non-unitality of the coproduct. There are also a multiplicative counit, an antipode, and an R-matrix.For this, we give a general construction of quantum groupoids for complex simple Lie algebras g = E 8 and certain roots of unity. Our main tools here are Drinfeld's coboundary associated to the R-matrix, related to the algebra involution, and certain canonical projections introduced by Wenzl, which yield the coproduct and Drinfeld's associator in an explicit way. Tensorial properties of the negligible modules reflect in a rather special nature of the associator. We next reduce the proof of the categorical equivalence to the problems of establishing semisimplicity and computing dimension of the groupoid. In the case g = sl N we construct a (non-positive) Haar-type functional on an associative version of the dual groupoid satisfying key non-degeneracy properties. This enables us to complete the proof.

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<p>An advanced dust reanalysis with high spatial (at 10km x 10km) and temporal resolution is produced in the framework of DustClim project (Dust Storms Assessment for the development of user-oriented Climate Services in Northern Africa, Middle East and Europe) [1], aiming to provide reliable information on dust storms current conditions and predictions, focusing on the dust impacts on various socio-economic sectors.</p><p>This regional reanalysis is based on the assimilation of dust-related satellite observations from MODIS instrument [2], in the Multiscale Online Nonhydrostatic Atmosphere Chemistry model (NMMB-MONARCH) [3], over the region of Northern Africa, Middle East and Europe. The reanalysis is now available for a seven-year period (2011-2016) providing the following dust products: Columnar and surface concentration, distributed in 8 dust particle size bins, with effective radius ranging from 0,15μm to 7,1μm, dust load, dry and wet dust deposition, dust optical depth (DOD) and coarse dust optical depth (radius>1μm) at 550nm and profiles of dust extinction coefficient at 550nm.</p><p>A thorough evaluation of the reanalysis is in progress to assess the quality and uncertainty of the dust simulations, using dust-filtered products, retrieved from different measurement techniques, both from in-situ and remote sensing observations. The datasets considered for the DustClim reanalysis evaluation, provide observations of variables that are included in the model simulations. The DOD is provided by AERONET network [4] and by IASI [5], POLDER [6], MISR [7] and MODIS space-borne sensors; Dust extinction profiles are provided by ACTRIS/EARLINET network [8] and CALIPSO/LIVAS dataset [9]; Dust PM10 surface concentrations derived from INDAAF/SDT [10] network and estimated from PM10 measurements [11] performed within EEA/EIONET [12] network; Dust deposition measurements collected by the INDAAF/SDT and the CARAGA/DEMO [13] networks; Dust size distribution from in situ observations (ground-based and airborne); And column-averaged dust size distribution at selected stations from the AERONET network.</p><p>In this work, we present the results of the model evaluation for the year 2012. The first evaluation results will focus on dust extinction coefficient profiles from EARLINET and LIVAS, on DOD using AERONET, MISR and MODIS datasets, and on dust PM10 concentration from INDAAF/SDT network. Moreover, a DOD climatology covering the whole reanalysis period (2011-2016) will be compared with the results obtained from AERONET network.</p><p> </p><p>References</p><p>[1] https://sds-was.aemet.es/projects-research/dustclim</p><p>[2] https://modis.gsfc.nasa.gov/</p><p>[3] Di Tomaso et al., <em>Geosci. Model Dev.</em>, <strong>10</strong>, 1107-1129, doi:10.5194/gmd-10-1107-2017., 2017.</p><p>[4] https://aeronet.gsfc.nasa.gov/</p><p>[5] Cuesta et al., <em>J. Geophys. Res.</em>, <strong>120</strong>, 7099-7127, 2015.</p><p>[6] http://www.icare.univ-lille1.fr/parasol/overview/</p><p>[7] https://misr.jpl.nasa.gov/</p><p>[8] https://www.earlinet.org/</p><p>[9] Marinou et al., <em>Atmos. Chem. Phys.</em>, <strong>17</strong>, 5893–5919, https://doi.org/10.5194/acp-17-5893-2017, 2017.</p><p>[10] https://indaaf.obs-mip.fr/</p><p>[11] Barnaba et al., <em>Atmospheric environment</em>, <strong>161</strong>, 288-305, 2017.</p><p>[12] https://www.eionet.europa.eu/</p><p>[13] Laurent et al., <em>Atmos. Meas. Tech.</em>, <strong>8</strong>, 2801–2811, 2015.</p><p> </p><p> </p><p>Acknowledgement</p><p>DustClim project is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462).</p>

<p>In December 2019, a contract between CNR and ECMWF was signed for a pilot ACTRIS/EARLINET data provision to the Copernicus Atmosphere Monitoring Service (CAMS). Such pilot contract (CAMS21b) aims to put in place a first data provision for a set of selected stations and it will demonstrate the feasibility of fully traceable and quality-controlled data provision for the whole network.</p><p>In CAMS21b, the main effort is devoted to design, test and set up the provision of quality-controlled ACTRIS/EARLINET products in Real Real Time (RRT) and/or Near Real Time (NRT) to CAMS. The activities are focused on the automatic centralized data processing and data provision, ensuring the full traceability of the products from the data acquisition level up to the final quality-controlled data level. Most of the activities are done at ARES, the EARLINET/ACTRIS data center node at CNR, for assuring the centralized, harmonized and quality-controlled processing in compliance with FAIR principles.</p><p>New modules and submodules of the ACTRIS/EARLINET Single Calculus Chain (SCC) as well as optimized algorithms for cloud screening have been designed. Additional procedures were implemented for improving the quality of the data provided in NRT, but also for the quality control of the Level 2 products which are delivered with a time delay.</p><p>The release of a new version of SCC and of QC procedure is planned for mid-February.</p><p>The data provision started in October 2020 at the test site of Potenza. A system has been set up for measurement reporting and monitoring of KPIs (Key Performance Indicators). After 3 months of measurements, the overall data provision system showed no critical points.</p><p>In January 2021, the provision started for a group of 9 stations which are seen as representative for the whole network in terms of instrumental capability, but also ensuring a good geographical coverage of the European continent.</p><p>In order to accommodate also measurements from non-continuous operation systems, a measurement schedule has been set up, compromising between the need of a large number of measurements and costs/efforts at each station. The measurement schedule has been designed through a representativeness study and foresees 6 slots of measurements per week, 3 in daytime and 3 in nighttime conditions.</p><p>The successful implementation of the pilot allows the provision of aerosol optical property profiles to the CAMS services. from a set of observational sites distributed over the different European regions. These profiles is expected to be of interest for the assimilation, near real time evaluation and re-analysis evaluation of several CAMS products, including the aerosol load over Europe for air quality issues, atmospheric composition, climate forcing and solar and UV products. This allows for having a systematic solution for looking into specific events as they develop (e.g. the dust plume that you investigated earlier this month or the Californian fires in September), supporting or contradicting model forecasts. This pilot is the first provision of aerosol profiles from a high-quality ground-based network in NRT for this kind of applications. It is expected that these efforts will be continued in the next phase of CAMS/Copernicus (2021-2027).</p>

Abstract. Aerosol reanalysis datasets are model-based observationally constrained continuous 3D aerosol fields with relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects and impacts upon socio–economic sectors, such as health. Here we compare and assess the recently published MONARCH high resolution regional desert dust reanalysis over Northern Africa, the Middle East and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS, MISR and IASI space-borne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows for at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products, are factors that bias the reanalysis assessment. We, therefore, also used ground-based DOD observations provided by 238 stations of the AERONET network located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking into consideration these results, the MONARCH reanalysis assessment showed that total and coarse DOD simulations are consistent with satellite and ground-based data, capturing qualitatively the major dust sources in the area as well as the dust transport patterns. Moreover, the reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases were found over the Sahara Desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (−0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low as the low relative bias in the Sahara Desert (< 0.5) and over the adjacent maritime regions (< 1), certifies. Similarly, over areas with intense dust activity the linear correlation coefficient between the reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean and the Arabian Sea, and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions where large amounts of observations are available, allowing for robust model assessment.