Evaluating the Performance of a Regional-Scale Photochemical Modelling System: Part I Ozone Predictions

We present a detailed evaluation of the seasonal performance of the Community Multiscale Air Quality (CMAQ) modelling system and the PSU/NCAR meteorological model coupled to a new Numerical Emission Model for Air Quality (MNEQA). The combined system simulates air quality at a fine resolution (3 km as horizontal resolution and 1 h as temporal resolution) in north-eastern Spain, where problems of ozone pollution are frequent. An extensive database compiled over two periods, from May to September 2009 and 2010, is used to evaluate meteorological simulations and chemical outputs. Our results indicate that the model accurately reproduces hourly and 1-h and 8-h maximum ozone surface concentrations measured at the air quality stations, as statistical values fall within the EPA and EU recommendations. However, to further improve forecast accuracy, three simple bias-adjustment techniques mean subtraction (MS), ratio adjustment (RA), and hybrid forecast (HF) based on 10 days of available comparisons are applied. The results show that the MS technique performed better than RA or HF, although all the bias-adjustment techniques significantly reduce the systematic errors in ozone forecasts

A performance evaluation of MM5/MNEQA/CMAQ air quality modelling system to forecast ozone concentrations in Catalonia

We examine the ability of a modelling system to forecast the formation and transport of ozoneover Catalonia, at the NE of the Iberian Peninsula. To this end, the Community MultiscaleAir Quality (CMAQ) modelling system developed by the United States Environmental ProtectionAgency (US EPA) and the PSU/NCAR mesoscale modelling system MM5 are coupled to a newemission model, the Numerical Emission Model for Air Quality (MNEQA). The outputs of themodelling system for the period from May to October 2008 are compared with ozone measure-ments at selected air-monitoring stations belonging to the Catalan Government. Results indicatea good behaviour of the model in reproducing diurnal ozone concentrations, as statistical valuesfall within the EPA and EU regulatory frameworks

The MONARCH high-resolution reanalysis of desert dust aerosol over Northern Africa, the Middle East and Europe (2007–2016)

One of the challenges in studying desert dust aerosol along with its numerous interactions and impacts is the paucity of direct in situ measurements, particularly in the areas most affected by dust storms. Satellites typically provide column-integrated aerosol measurements, but observationally constrained continuous 3D dust fields are needed to assess dust variability, climate effects and impacts upon a variety of socio-economic sectors. Here, we present a high-resolution regional reanalysis data set of desert dust aerosols that covers Northern Africa, the Middle East and Europe along with the Mediterranean Sea and parts of central Asia and the Atlantic and Indian oceans between 2007 and 2016. The horizontal resolution is 0.1◦ latitude × 0.1◦ longitude in a rotated grid, and the temporal resolution is 3 h. The reanalysis was produced using local ensemble transform Kalman filter (LETKF) data assimilation in the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH) developed at the Barcelona Supercomputing Center (BSC). The assimilated data are coarse-mode dust optical depth retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue Level 2 products. The reanalysis data set consists of upper-air variables (dust mass concentrations and the extinction coefficient), surface variables (dust deposition and solar irradiance fields among them) and total column variables (e.g. dust optical depth and load). Some dust variables, such as concentrations and wet and dry deposition, are expressed for a binned size distribution that ranges from 0.2 to 20 µm in particle diameter. Both analysis and first-guess (analysis-initialized simulation) fields are available for the variables that are diagnosed from the state vector. A set of ensemble statistics is archived for each output variable, namely the ensemble mean, standard deviation, maximum and median. The spatial and temporal distribution of the dust fields follows well-known dust cycle features controlled by seasonal changes in meteorology and vegetation cover. The analysis is statistically closer to the assimilated retrievals than the first guess, which proves the consistency of the data assimilation method. Independent evaluation using Aerosol Robotic Network (AERONET) dust-filtered optical depth retrievals indicates that the reanalysis data set is highly accurate (mean bias = −0.05, RMSE = 0.12 and r = 0.81 when compared to retrievals from the spectral de-convolution algorithm on a 3-hourly basis). Verification statistics are broadly homogeneous in space and time with regional differences that can be partly attributed to model limitations (e.g. poor representation of small-scale emission processes), the presence of aerosols other than dust in the observations used in the evaluation and differences in the number of observations among seasons. Such a reliable high-resolution historical record of atmospheric desert dust will allow a better quantification of dust impacts upon key sectors of society and economy, including health, solar energy production and transportation. The reanalysis data set (Di Tomaso et al., 2021) is distributed via Thematic Real-time Environmental Distributed Data Services (THREDDS) at BSC and is freely available at http://hdl.handle.net/21.12146/c6d4a608-5de3-47f6-a004-67cb1d498d98 (last access: 10 June 2022).This research has been supported by the DustClim project, which is part of ERA4CS, an ERA-NET programme co-funded by the European Union’s Horizon 2020 research and innovation programme (grant no. 690462); the European Research Council (FRAGMENT (grant no. 773051)); grant no. RYC-2015- 18690 funded by MCIN/AEI/10.13039/501100011033 and ESF Investing in your future; grant no. CGL2017-88911-R funded by MCIN/AEI/10.13039/501100011033 and ERDF A way of making Europe; the AXA Research Fund (AXA Chair on Sand and Dust Storms); the European Commission, Horizon 2020 Framework Programme (grant no. 792103 (SOLWARIS)); and ATMO-ACCESS (Access to Atmospheric Research Facilities) funded in the frame of the programme H2020-EU.1.4.1.2 (grant no. 101008004, 1 April 2021–31 March 2025). Jerónimo Escribano and Martina Klose have received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreements H2020-MSCACOFUND-2016-754433 and H2020-MSCA-IF-2017-789630, respectively. Martina Klose received further support through the Helmholtz Association’s Initiative and Networking Fund (grant no. VH-NG-1533). This work has been partially funded by the contribution agreement between AEMET and BSC to carry out development and improvement activities of the products and services supplied by the World Meteorological Organization (WMO) Barcelona Dust Regional Center (i.e. the WMO Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) Regional Center for Northern Africa, the Middle East and Europe).Peer ReviewedArticle signat per 24 autors/es: Enza Di Tomaso (1) , Jerónimo Escribano (1) , Sara Basart (1) , Paul Ginoux (2) , Francesca Macchia (1) , Francesca Barnaba (3) , Francesco Benincasa (1), Pierre-Antoine Bretonnière (1), Arnau Buñuel (1), Miguel Castrillo (1), Emilio Cuevas (4) , Paola Formenti (5) , María Gonçalves (1,6), Oriol Jorba (1), Martina Klose (1,7), Lucia Mona (8), Gilbert Montané Pinto (1) , Michail Mytilinaios (8), Vincenzo Obiso (1,a), Miriam Olid (1), Nick Schutgens (9) , Athanasios Votsis (10,11), Ernest Werner (12), and Carlos Pérez García-Pando (1,13) // (1) Barcelona Supercomputing Center (BSC), Barcelona, Spain; (2) NOAA Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, USA; (3) Consiglio Nazionale delle Ricerche–Istituto di Scienze dell’Atmosfera e del Clima (CNR–ISAC), Rome, Italy; (4) Izaña Atmospheric Research Center (IARC), Agencia Estatal de Meteorología (AEMET), Santa Cruz de Tenerife, Spain; (5) Université Paris Cité and Univ Paris-Est Créteil, CNRS, LISA, 75013 Paris, France; (6) Department of Project and Construction Engineering, Universitat Politècnica de Catalunya – BarcelonaTech (UPC), Terrassa, Spain; (7) Department Troposphere Research, Institute of Meteorology and Climate Research (IMK-TRO), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany; (8) Consiglio Nazionale delle Ricerche–Istituto di Metodologie per l’Analisi Ambientale (CNR–IMAA), Tito Scalo (PZ), Italy; (9) Department of Earth Sciences, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands; (10) Section of Governance and Technology for Sustainability (BMS-CSTM), University of Twente, Enschede, the Netherlands; (11) Weather and Climate Change Impact Research, Finnish Meteorological Institute (FMI), Helsinki, Finland; (12) Agencia Estatal de Meteorología (AEMET), Barcelona, Spain; (13) ICREA, Catalan Institution for Research and Advanced Studies, Barcelona, Spain anow at: NASA Goddard Institute for Space Studies (GISS), New York, New York, USAObjectius de Desenvolupament Sostenible::13 - Acció per al Clima::13.3 - Millorar l’educació, la conscienciació i la capacitat humana i institucional en relació amb la mitigació del canvi climàtic, l’adaptació a aquest, la reducció dels efectes i l’alerta primerencaObjectius de Desenvolupament Sostenible::13 - Acció per al ClimaPostprint (published version

The MONARCH high-resolution reanalysis of desert dust aerosol over Northern Africa, the Middle East and Europe (2007-2016)

One of the challenges in studying desert dust aerosol along with its numerous interactions and impacts is the paucity of direct in-situ measurements, particularly in the areas most affected by dust storms. Satellites typically provide columnintegrated aerosol measurements, but observationally-constrained continuous 3D dust fields are needed to assess dust variability, climate effects and impacts upon a variety of socio-economic sectors. Here, we present a high resolution regional reanalysis data set of desert dust aerosols that covers Northern Africa, the Middle East and Europe along with the Mediterranean sea and parts of Central Asia, and the Atlantic and Indian Oceans between 2007 and 2016. The horizontal resolution is 0.1° latitude × 0.1° longitude, and the temporal resolution is 3 hours. The reanalysis was produced using Local Ensemble Transform Kalman Filter (LETKF) data assimilation in the Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) developed at the Barcelona Supercomputing Center (BSC). The assimilated data are coarse-mode dust optical depth retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue Level 2 products. The reanalysis data set consists of upper air (dust mass concentrations and extinction coefficient), surface (dust deposition and solar irradiance fields, among them) and total column (e.g., dust optical depth and load) variables. Some dust variables, such as concentrations and wet and dry deposition, are expressed for a binned size distribution that ranges from 0.2 to 20 μm in particle diameter. Both analysis and first-guess (analysis-initialized simulation) fields are available for the variables that are diagnosed from the state vector.We acknowledge the DustClim project which 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’s Horizon 2020 research and innovation programme (Grant n. 690462)

Predicción de la calidad del aire multiescala con el modelo MONARCH en el Centro Nacional de Supercomputación

Ponencia presentada en: VI Simposio Nacional de Predicción, celebrado en los servicios centrales de AEMET, en Madrid, del 17 al 19 de septiembre de 2018.En esta contribución se presentará una visión general del modelo MONARCH, los desarrollos recientes referentes a los procesos físico-químicos de la atmósfera, el acoplamiento con el nuevo modelo de emisiones multiescala HERMESv3, y su sistema de asimilación de datos basado en la metodología por conjuntos Local Ensemble Transform Kalman Filter. A continuación, se discutirán ejemplos de aplicación del mismo a distintas escalas espaciales: 1) predicción de aerosoles global a 50 km, 2) predicción de ozono y material particulado en España a 4 km, y 3) predicción de óxidos de nitrógeno a escala urbana a 10 m. Finalmente, se mostrarán los trabajos en asimilación de datos de medidas satelitales de espesor óptico orientados a desarrollar análisis de aerosoles con especial énfasis en el polvo mineral

Phenomenology of high-ozone episodes in NE Spain

Ground-level and vertical measurements (performed using tethered and non-tethered balloons), coupled with modelling, of ozone (O3), other gaseous pollutants (NO, NO2, CO, SO2) and aerosols were carried out in the plains (Vic Plain) and valleys of the northern region of the Barcelona metropolitan area (BMA) in July 2015, an area typically recording the highest O3 episodes in Spain. Our results suggest that these very high O3 episodes were originated by three main contributions: (i) the surface fumigation from high O3 reservoir layers located at 1500-3000 m a.g.l. (according to modelling and non-tethered balloon measurements), and originated during the previous day(s) injections of polluted air masses at high altitude; (ii) local/regional photochemical production and transport (at lower heights) from the BMA and the surrounding coastal settlements, into the inland valleys; and (iii) external (to the study area) contributions of both O3 and precursors. These processes gave rise to maximal O3 levels in the inland plains and valleys northwards from the BMA when compared to the higher mountain sites. Thus, a maximum O3 concentration was observed within the lower tropospheric layer, characterised by an upward increase of O3 and black carbon (BC) up to around 100-200 m a.g.l. (reaching up to 300 µg m−3 of O3 as a 10 s average), followed by a decrease of both pollutants at higher altitudes, where BC and O3 concentrations alternate in layers with parallel variations, probably as a consequence of the atmospheric transport from the BMA and the return flows (to the sea) of strata injected at certain heights the previous day(s). At the highest altitudes reached in this study with the tethered balloons (900-1000 m a.g.l.) during the campaign, BC and O3 were often anti-correlated or unrelated, possibly due to a prevailing regional or even hemispheric contribution of O3 at those altitudes. In the central hours of the days a homogeneous O3 distribution was evidenced for the lowest 1 km of the atmosphere, although probably important variations could be expected at higher levels, where the high O3 return strata are injected according to the modelling results and non-tethered balloon data. Relatively low concentrations of ultrafine particles (UFPs) were found during the study, and nucleation episodes were only detected in the boundary layer. Two types of O3 episodes were identified: type A with major exceedances of the O3 information threshold (180 µg m−3 on an hourly basis) caused by a clear daily concatenation of local/regional production with accumulation (at upper levels), fumigation and direct transport from the BMA (closed circulation); and type B with regional O3 production without major recirculation (or fumigation) of the polluted BMA/regional air masses (open circulation), and relatively lower O3 levels, but still exceeding the 8 h averaged health target. To implement potential O3 control and abatement strategies two major key tasks are proposed: (i) meteorological forecasting, from June to August, to predict recirculation episodes so that NOx and VOC abatement measures can be applied before these episodes start; (ii) sensitivity analysis with high-resolution modelling to evaluate the effectiveness of these potential abatement measures of precursors for O3 reduction

Evaluating the Performance of a Regional-Scale Photochemical Modelling System: Part I Ozone Predictions

We present a detailed evaluation of the seasonal performance of the Community Multiscale Air Quality (CMAQ) modelling system and the PSU/NCAR meteorological model coupled to a new Numerical Emission Model for Air Quality (MNEQA). The combined system simulates air quality at a fine resolution (3 km as horizontal resolution and 1 h as temporal resolution) in north-eastern Spain, where problems of ozone pollution are frequent. An extensive database compiled over two periods, from May to September 2009 and 2010, is used to evaluate meteorological simulations and chemical outputs. Our results indicate that the model accurately reproduces hourly and 1-h and 8-h maximum ozone surface concentrations measured at the air quality stations, as statistical values fall within the EPA and EU recommendations. However, to further improve forecast accuracy, three simple bias-adjustment techniques mean subtraction (MS), ratio adjustment (RA), and hybrid forecast (HF) based on 10 days of available comparisons are applied. The results show that the MS technique performed better than RA or HF, although all the bias-adjustment techniques significantly reduce the systematic errors in ozone forecasts

Predicción de la calidad del aire multiescala con el modelo MONARCH en el Centro Nacional de Supercomputación [Presentación]

Presentación realizada en el VI Simposio Nacional de Predicción "Memorial Antonio Mestre", celebrado en la sede central de AEMET en Madrid del 17 al 19 de septiembre de 2018

MONARCH regional reanalysis of desert dust aerosols: an initial assessment

Aerosol reanalyses are a well-established tool for monitoring aerosol trends, for validation and calibration of weather chemical models, as well as for the enhancement of strategies for environmental monitoring and hazard mitigation. By providing a consistent and complete data set over a sufficiently long period, they address the shortcomings of aerosol observational records in terms of temporal and spatial coverage and aerosol speciation. These shortcomings are particularly severe for dust aerosols. A 10-year dust aerosol regional reanalysis has been recently produced on the Barcelona Supercomputing Center HPC facilities at the high spatial resolution of 0.1°. Here we present a brief description and an initial assessment of this data set. An innovative dust optical depth data set, derived from the MODIS Deep Blue products, has been ingested in the dust module of the MONARCH model by means of a LETKF with a four-dimensional extension. MONARCH ensemble has been generated by applying combined meteorology and emission perturbations. This has been achieved using for each ensemble member different meteorological fields as initial and boundary conditions, and different emission schemes, in addition to stochastic perturbations of emission parameters, which we show is beneficial for dust data assimilation. We prove the consistency of the assimilation procedure by analyzing the departures of the assimilated observations from the model simulations for a two-month period. Furthermore, we show a comparison with AERONET coarse optical depth retrievals during a period of 2012, which indicates that the reanalysis data set is highly accurate. While further analysis and validation of the whole data set are ongoing, here we provide a first evidence for the reanalysis to be a useful record of dust concentration and deposition extending the existing observational-based information intended for mineral dust monitoring.We acknowledge the DustClim project which 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’s Horizon 2020 research and innovation programme (Grant n. 690462). BSC co-authors also acknowledge support from the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant n. 773051; FRAGMENT), the AXA Research Fund, the 60 Spanish Ministry of Science, Innovation and Universities (grant n. RYC-2015-18690 and CGL2017-88911-R), the European Union’s Horizon 2020 research and innovation programme (grant n. 792103; SOLWARIS). This work has been partially funded by the contribution agreement between AEMET and BSC to carry out development and improvement activities of the products and services supplied by the WMO Sand and Dust Storm Regional Centres. Jerónimo Escribano and Martina Klose have received funding from the European Union’s Horizon 2020 research and innovation programme, respectively, under the Marie Skłodowska-Curie grant agreements H2020-MSCA-COFUND-2016- 65 754433 and H2020-MSCA-IF-2017-789630. Martina Klose further acknowledges support through the Helmholtz Association’s Initiative and Networking Fund (grant agreement n. VH-NG-1533). We acknowledge PRACE (eDUST, eFRAGMENT1, and eFRAGMENT2) and RES (AECT-2019-3-0001, AECT-2020-1-0007, AECT-2020-3-0013) for awarding access to MareNostrum at the BSC and for providing technical support.Peer ReviewedObjectius de Desenvolupament Sostenible::13 - Acció per al ClimaPostprint (author's final draft