scholarly journals A complex aerosol transport event over Europe during the 2017 Storm Ophelia in CAMS forecast systems: analysis and evaluation

2020 ◽  
Vol 20 (21) ◽  
pp. 13557-13578 ◽  
Author(s):  
Dimitris Akritidis ◽  
Eleni Katragkou ◽  
Aristeidis K. Georgoulias ◽  
Prodromos Zanis ◽  
Stergios Kartsios ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Data Assimilation ◽  
Saharan Dust ◽  
Atmospheric Composition ◽  
Orthogonal Polarization ◽  
Aerosol Transport ◽  
Forecast System ◽  
Air Quality Forecast ◽  
Regional Forecast

Abstract. In mid-October 2017 Storm Ophelia crossed over western coastal Europe, inducing the combined transport of Saharan dust and Iberian biomass burning aerosols over several European areas. In this study we assess the performance of the Copernicus Atmosphere Monitoring Service (CAMS) forecast systems during this complex aerosol transport event and the potential benefits that data assimilation and regional models could bring. To this end, CAMS global and regional forecast data are analysed and compared against observations from passive (MODIS: Moderate Resolution Imaging Spectroradiometer aboard Terra and Aqua) and active (CALIOP/CALIPSO: Cloud-Aerosol LIdar with Orthogonal Polarization aboard Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite sensors and ground-based measurements (EMEP: European Monitoring and Evaluation Programme). The analysis of the CAMS global forecast indicates that dust and smoke aerosols, discretely located on the warm and cold fronts of Ophelia, respectively, were affecting the aerosol atmospheric composition over Europe during the passage of the Storm. The observed MODIS aerosol optical depth (AOD) values are satisfactorily reproduced by the CAMS global forecast system, with a correlation coefficient of 0.77 and a fractional gross error (FGE) of 0.4. The comparison with a CAMS global control simulation not including data assimilation indicates a significant improvement in the bias due to data assimilation implementation, as the FGE decreases by 32 %. The qualitative evaluation of the IFS (Integrated Forecast System) dominant-aerosol type and location against the CALIPSO observations overall reveals a good agreement. Regarding the footprint on air quality, both CAMS global and regional forecast systems are generally able to reproduce the observed signal of increase in surface particulate matter concentrations. The regional component performs better in terms of bias and temporal variability, with the correlation deteriorating over forecast time. Yet, both products exhibit inconsistencies on the quantitative and temporal representation of the observed surface particulate matter enhancements, stressing the need for further development of the air quality forecast systems for even more accurate and timely support of citizens and policy-makers.

scholarly journals A complex aerosol transport event over Europe during the 2017 Storm Ophelia in CAMS forecast systems: analysis and evaluation

2020 ◽  
Author(s):  
Dimitris Akritidis ◽  
Eleni Katragkou ◽  
Aristeidis K. Georgoulias ◽  
Prodromos Zanis ◽  
Stergios Kartsios ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Data Assimilation ◽  
Qualitative Evaluation ◽  
Monitoring And Evaluation ◽  
Saharan Dust ◽  
Atmospheric Composition ◽  
Orthogonal Polarization ◽  
Aerosol Transport ◽  
Air Quality Forecast

Abstract. In mid-October 2017 Storm Ophelia crossed over western coastal Europe, inducing the combined transport of Saharan dust and Iberian biomass burning aerosols over several European areas. In this study we assess the performance of the Copernicus Atmosphere Monitoring Service (CAMS) forecast systems during this complex aerosol transport event, and the potential benefits that data assimilation and regional models could bring. To this end, CAMS global and regional day-1 forecast data are analyzed and compared against observations from passive (MODIS: Moderate resolution Imaging Spectroradiometer aboard Terra and Aqua) and active (CALIOP/CALIPSO: Cloud-Aerosol Lidar with Orthogonal Polarization aboard Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellites, and ground-based measurements (EMEP: European Monitoring and Evaluation Programme). The analysis of CAMS global forecast indicates that dust and smoke aerosols, discretely located on the warm and cold front of Ophelia, respectively, are affecting the aerosol atmospheric composition over Europe during the passage of the Storm. The observed MODIS Aerosol Optical Depth (AOD) values are satisfactorily reproduced by CAMS global forecast system, with a shared variance of 60 % and a fractional gross error (fge) of 0.4. The comparison with a CAMS global control simulation not including data assimilation, indicates a significant improvement in the bias due to data assimilation implementation, as the fge decreases by 32 %. The qualitative evaluation of the IFS dominant aerosol type and location against the CALIPSO observations reveals a good agreement. Regarding the footprint on air quality, both CAMS global and regional forecast systems are generally able to reproduce the observed signal of increase in surface particulate matter concentrations, with the regional component performing better in terms of bias and temporal variability. Yet, both products exhibit inconsistencies on the quantitative and temporal representation of the observed surface particulate matter enhancements, stressing the need for further development of the air quality forecast systems, for even more accurate and timely support of citizens and policy-makers.

scholarly journals What Can We Expect from Data Assimilation for Air Quality Forecast? Part I: Quantification with Academic Test Cases

2019 ◽  
Vol 36 (2) ◽  
pp. 269-279 ◽  
Author(s):  
Laurent Menut ◽  
Bertrand Bessagnet
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
Nitrogen Dioxide ◽  
Atmospheric Composition ◽  
Quality Analysis ◽  
Test Cases ◽  
Ozone Formation ◽  
Air Quality Forecast ◽  
Maximum Benefit ◽  
Academic Test

Abstract Data assimilation has been successfully used for meteorology for many years and is now used more and more for atmospheric composition issues (air quality analysis and forecast). The data assimilation of pollutants remains difficult and its deployment is currently in progress. It is thus difficult to have quantitative knowledge of what we can expect as the maximum benefit. In this study we propose a simple framework to make this quantification. In this first part, the gain of data assimilation is quantified using academic but realistic test cases over an urbanized polluted area and during a summertime period favorable to ozone formation. Different data assimilation configurations are tested, corresponding to different amounts of data available for assimilation. For ozone (O3) and nitrogen dioxide (NO2), it is shown that the benefit resulting from data assimilation lasts from a few hours to a possible maximum of 60 and 21 h, respectively. Maps of the number of hours are presented, spatializing the benefit of data assimilation.

scholarly journals Comparison of chemical lateral boundary conditions for air quality predictions over the contiguous United States during pollutant intrusion events

2021 ◽  
Vol 21 (4) ◽  
pp. 2527-2550
Author(s):  
Youhua Tang ◽  
Huisheng Bian ◽  
Zhining Tao ◽  
Luke D. Oman ◽  
Daniel Tong ◽  
...  
Keyword(s):  
Air Quality ◽  
Boundary Conditions ◽  
Model Performance ◽  
Chemical Species ◽  
Saharan Dust ◽  
Atmospheric Composition ◽  
Lateral Boundary ◽  
Model Framework ◽  
Air Quality Forecast ◽  
Lateral Boundary Conditions

Abstract. The National Air Quality Forecast Capability (NAQFC) operated in the US National Oceanic and Atmospheric Administration (NOAA) provides the operational forecast guidance for ozone and fine particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) over the contiguous 48 US states (CONUS) using the Community Multi-scale Air Quality (CMAQ) model. The existing NAQFC uses climatological chemical lateral boundary conditions (CLBCs), which cannot capture pollutant intrusion events originating outside of the model domain. In this study, we developed a model framework to use dynamic CLBCs from the Goddard Earth Observing System Model, version 5 (GEOS) to drive NAQFC. A mapping of the GEOS chemical species to CMAQ's CB05–AERO6 (Carbon Bond 5; version 6 of the aerosol module) species was developed. The utilization of the GEOS dynamic CLBCs in NAQFC showed the best overall performance in simulating the surface observations during the Saharan dust intrusion and Canadian wildfire events in summer 2015. The simulated PM2.5 was improved from 0.18 to 0.37, and the mean bias was reduced from −6.74 to −2.96 µg m−3 over CONUS. Although the effect of CLBCs on the PM2.5 correlation was mainly near the inflow boundary, its impact on the background concentrations reached further inside the domain. The CLBCs could affect background ozone concentrations through the inflows of ozone itself and its precursors, such as CO. It was further found that the aerosol optical thickness (AOT) from satellite retrievals correlated well with the column CO and elemental carbon from GEOS. The satellite-derived AOT CLBCs generally improved the model performance for the wildfire intrusion events during a summer 2018 case study and demonstrated how satellite observations of atmospheric composition could be used as an alternative method to capture the air quality effects of intrusions when the CLBCs of global models, such as GEOS CLBCs, are not available.

scholarly journals Development and evaluation of an advanced National Air Quality Forecast Capability using the NOAA Global Forecast System version 16

2021 ◽  
Author(s):  
Patrick Campbell ◽  
Youhua Tang ◽  
Pius Lee ◽  
Barry Baker ◽  
Daniel Tong ◽  
...  
Keyword(s):  
Air Quality ◽  
Surface Ozone ◽  
Atmospheric Composition ◽  
Limited Area ◽  
Global Forecast System ◽  
Forecast System ◽  
Near Surface ◽  
Wildfire Smoke ◽  
Air Quality Forecast ◽  
Quality Forecast

Abstract. A new dynamical core, known as the Finite Volume Cubed-Sphere (FV3) and developed at both NASA and NOAA, is used in NOAA’s Global Forecast System (GFS) and in limited area models (LAMs) for regional weather and air quality applications. NOAA has also upgraded the operational FV3GFS to version 16 (GFSv16), and includes a number of significant developmental advances to the model configuration, data assimilation, and underlying model physics, particularly for atmospheric composition to weather feedback. Concurrent with the GFSv16 upgrade, we couple the GFSv16 with the Community Multiscale Air Quality (CMAQ) model to form an advanced version of the National Air Quality Forecast Capability (NAQFC) that will continue to protect human and ecosystem health in the U.S. Here we describe the development of the FV3GFSv16 coupling with a “state-of-the-science” CMAQ model version 5.3.1. The GFS-CMAQ coupling is made possible by the seminal version of the NOAA-ARL Atmosphere-Chemistry Coupler (NACC), which became the next operational NAQFC system (i.e., NACC-CMAQ) on July 20, 2021. NACC-CMAQ has a number of scientific advancements that include satellite- based data acquisition technology to improve land cover and soil characteristics, and inline wildfire smoke and dust predictions that are vital to predictions of fine particulate matter (PM2.5) concentrations during hazardous events affecting society, ecosystems, and human health. The GFS-driven NACC-CMAQ has significantly different meteorological and chemical predictions than the previous operational NAQFC, where evaluation of NACC-CMAQ shows generally improved near-surface ozone and PM2.5 predictions and diurnal patterns, both of which are extended to a 72-hour (3-day) forecast with this system.

scholarly journals Description and Evaluation of the Fine Particulate Matter Forecasts in the NCAR Regional Air Quality Forecasting System

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 302
Author(s):  
Rajesh Kumar ◽  
Piyush Bhardwaj ◽  
Gabriele Pfister ◽  
Carl Drews ◽  
Shawn Honomichl ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Information Dissemination ◽  
Fine Particulate Matter ◽  
Model Errors ◽  
Air Quality Forecast ◽  
Fine Particulate ◽  
Regional Air Quality ◽  
Forecasting System ◽  
Air Quality Forecasting

This paper describes a quasi-operational regional air quality forecasting system for the contiguous United States (CONUS) developed at the National Center for Atmospheric Research (NCAR) to support air quality decision-making, field campaign planning, early identification of model errors and biases, and support the atmospheric science community in their research. This system aims to complement the operational air quality forecasts produced by the National Oceanic and Atmospheric Administration (NOAA), not to replace them. A publicly available information dissemination system has been established that displays various air quality products, including a near-real-time evaluation of the model forecasts. Here, we report the performance of our air quality forecasting system in simulating meteorology and fine particulate matter (PM2.5) for the first year after our system started, i.e., 1 June 2019 to 31 May 2020. Our system shows excellent skill in capturing hourly to daily variations in temperature, surface pressure, relative humidity, water vapor mixing ratios, and wind direction but shows relatively larger errors in wind speed. The model also captures the seasonal cycle of surface PM2.5 very well in different regions and for different types of sites (urban, suburban, and rural) in the CONUS with a mean bias smaller than 1 µg m−3. The skill of the air quality forecasts remains fairly stable between the first and second days of the forecasts. Our air quality forecast products are publicly available at a NCAR webpage. We invite the community to use our forecasting products for their research, as input for urban scale (<4 km), air quality forecasts, or the co-development of customized products, just to name a few applications.

scholarly journals The value of satellite observations in the analysis and short-range prediction of Asian dust

2019 ◽  
Vol 19 (2) ◽  
pp. 987-998 ◽  
Author(s):  
Angela Benedetti ◽  
Francesca Di Giuseppe ◽  
Luke Jones ◽  
Vincent-Henri Peuch ◽  
Samuel Rémy ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Data Assimilation ◽  
Optical Depth ◽  
Short Range ◽  
Asian Dust ◽  
Satellite Observations ◽  
Global Model ◽  
Deep Blue ◽  
Dust Events

Abstract. Asian dust is a seasonal meteorological phenomenon which affects east Asia, and has severe consequences on the air quality of China, North and South Korea and Japan. Despite the continental extent, the prediction of severe episodes and the anticipation of their consequences is challenging. Three 1-year experiments were run to assess the skill of the model of the European Centre for Medium-Range Weather Forecasts (ECMWF) in monitoring Asian dust and understand its relative contribution to the aerosol load over China. Data used were the Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target and the Deep Blue aerosol optical depth (AOD). In particular the experiments aimed at understanding the added value of data assimilation runs over a model run without any aerosol data. The year 2013 was chosen as representative of the availability of independent AOD data from two established ground-based networks (AERONET, Aerosol Robotic Network, and CARSNET, China Aerosol Remote Sensing Network), which could be used to evaluate experiments. Particulate matter (PM) data from the China Environmental Protection Agency were also used in the evaluation. Results show that the assimilation of satellite AOD data is beneficial to predict the extent and magnitude of desert dust events and to improve the short-range forecast of such events. The availability of observations from the MODIS Deep Blue algorithm over bright surfaces is an asset, allowing for a better localization of the sources and definition of the dust events. In general both experiments constrained by data assimilation perform better than the unconstrained experiment, generally showing smaller normalized mean bias and fractional gross error with respect to the independent verification datasets. The impact of the assimilated satellite observations is larger at analysis time, but lasts into the forecast up to 48 h. The performance of the global model in terms of particulate matter does not show the same degree of skill as the performance in terms of optical depth. Despite this, the global model is able to capture some regional pollution patterns. This indicates that the global model analyses may be used as boundary conditions for regional air quality models at higher resolution, enhancing their performance in situations in which part of the pollution may have originated from large-scale mechanisms. While assimilation is not a substitute for model development and characterization of the emission sources, results indicate that it can play a role in delivering improved monitoring of Asian dust optical depth.

Long-Range Transport of Anthropogenically and Naturally Produced Particulate Matter in the Mediterranean and North Atlantic: Current State of Knowledge

2007 ◽  
Vol 46 (8) ◽  
pp. 1230-1251 ◽  
Author(s):  
George Kallos ◽  
Marina Astitha ◽  
Petros Katsafados ◽  
Chris Spyrou
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
North America ◽  
Atlantic Ocean ◽  
Long Range ◽  
Saharan Dust ◽  
Long Range Transport ◽  
Transport And Transformation ◽  
New Findings ◽  
Range Transport

Abstract During the past 20 years, organized experimental campaigns as well as continuous development and implementation of air-pollution modeling have led to significant gains in the understanding of the paths and scales of pollutant transport and transformation in the greater Mediterranean region (GMR). The work presented in this paper has two major objectives: 1) to summarize the existing knowledge on the transport paths of particulate matter (PM) in the GMR and 2) to illustrate some new findings related to the transport and transformation properties of PM in the GMR. Findings from previous studies indicate that anthropogenically produced air pollutants from European sources can be transported over long distances, reaching Africa, the Atlantic Ocean, and North America. The PM of natural origin, like Saharan dust, can be transported toward the Atlantic Ocean and North America mostly during the warm period of the year. Recent model simulations and studies in the area indicate that specific long-range transport patterns of aerosols, such as the transport from Asia and the Indian Ocean, central Africa, or America, have negligible or at best limited contribution to air-quality degradation in the GMR when compared with the other sources. Also, new findings from this work suggest that the imposed European Union limits on PM cannot be applicable for southern Europe unless the origin (natural or anthropogenic) of the PM is taken into account. The impacts of high PM levels in the GMR are not limited only to air quality, but also include serious implications for the water budget and the regional climate. These are issues that require extensive investigation because the processes involved are complex, and further model development is needed to include the relevant physicochemical processes properly.

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