Suchergebnisse

In this study we present an evaluation of the Comprehensive Air Quality Model with extensions (CAMx) for Thessaloniki using radiometric and lidar data. The aerosol mass concentration profiles of CAMx are compared against the PM2.5 and PM2. 5−10 concentration profiles retrieved by the Lidar-Radiometer Inversion Code (LIRIC). The CAMx model and the LIRIC algorithm results were compared in terms of mean mass concentration profiles, center of mass and integrated mass concentration in the boundary layer and the free troposphere. The mean mass concentration comparison resulted in profiles within the same order of magnitude and similar vertical structure for the PM2. 5 particles. The mean centers of mass values are also close, with a mean bias of 0.57 km. On the opposite side, there are larger differences for the PM2. 5−10 mode, both in the boundary layer and in the free troposphere. In order to grasp the reasons behind the discrepancies, we investigate the effect of aerosol sources that are not properly included in the model's emission inventory and in the boundary conditions such as the wildfires and the desert dust component. The identification of the cases that are affected by wildfires is performed using wind backward trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model in conjunction with satellite fire pixel data from MODerate-resolution Imaging Spectroradiometer (MODIS) Terra and Aqua global monthly fire location product MCD14ML. By removing those cases the correlation coefficient improves from 0.69 to 0.87 for the PM2. 5 integrated mass in the boundary layer and from 0.72 to 0.89 in the free troposphere. The PM2.5 center of mass fractional bias also decreases to 0.38 km. Concerning the analysis of the desert dust component, the simulations from the Dust Regional Atmospheric Model (BSC-DREAM8b) were deployed. When only the Saharan dust cases are taken into account, BSC-DREAM8b generally outperforms CAMx when compared with LIRIC, achieving a correlation of 0.91 and a mean bias of −29.1 % for the integrated mass in the free troposphere and a correlation of 0.57 for the center of mass. CAMx, on the other hand, underestimates the integrated mass in the free troposphere. Consequently, the accuracy of CAMx is limited concerning the transported Saharan dust cases. We conclude that the performance of CAMx appears to be best for the PM2.5 particles, both in the boundary layer and in the free troposphere. Sources of particles not properly taken into account by the model are confirmed to negatively affect its performance, especially for the PM2. 5−10 particles. ; The authors would like to acknowledge the EU projects MACC-III (Monitoring Atmospheric Composition and Climate – III, grant agreement no. 633080) and MACC-II project (Monitoring Atmospheric Composition and Climate – Interim Implementation, grant agreement no. 283576). The simulated results presented in this research paper have been produced using the EGI and HellasGrid infrastructures. The ACTRIS-2 project from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 654109 is gratefully acknowledged. The authors would also like to acknowledge the support provided by the Scientific Computing Center at Aristotle University of Thessaloniki throughout the progress of the work on air quality forecasting. BSC-DREAM8b simulations were performed on the Mare Nostrum supercomputer hosted by Barcelona Supercomputing Center-Centro Nacional de Supercomputacion (BSC-CNS). S. Basart wants to acknowledge the CICYT project (CGL2013-46736). Elina Giannakaki acknowledges the support of the Academy of Finland (project no. 270108). ; Peer Reviewed ; Postprint (published version)

In this study we present an evaluation of the Comprehensive Air Quality Model with extensions (CAMx) for Thessaloniki using radiometric and lidar data. The aerosol mass concentration profiles of CAMx are compared against the PM2.5 and PM2. 5−10 concentration profiles retrieved by the Lidar-Radiometer Inversion Code (LIRIC). The CAMx model and the LIRIC algorithm results were compared in terms of mean mass concentration profiles, center of mass and integrated mass concentration in the boundary layer and the free troposphere. The mean mass concentration comparison resulted in profiles within the same order of magnitude and similar vertical structure for the PM2. 5 particles. The mean centers of mass values are also close, with a mean bias of 0.57 km. On the opposite side, there are larger differences for the PM2. 5−10 mode, both in the boundary layer and in the free troposphere. In order to grasp the reasons behind the discrepancies, we investigate the effect of aerosol sources that are not properly included in the model's emission inventory and in the boundary conditions such as the wildfires and the desert dust component. The identification of the cases that are affected by wildfires is performed using wind backward trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model in conjunction with satellite fire pixel data from MODerate-resolution Imaging Spectroradiometer (MODIS) Terra and Aqua global monthly fire location product MCD14ML. By removing those cases the correlation coefficient improves from 0.69 to 0.87 for the PM2. 5 integrated mass in the boundary layer and from 0.72 to 0.89 in the free troposphere. The PM2.5 center of mass fractional bias also decreases to 0.38 km. Concerning the analysis of the desert dust component, the simulations from the Dust Regional Atmospheric Model (BSC-DREAM8b) were deployed. When only the Saharan dust cases are taken into account, BSC-DREAM8b generally outperforms CAMx when compared with LIRIC, achieving a correlation of 0.91 and a mean bias of −29.1 % for the integrated mass in the free troposphere and a correlation of 0.57 for the center of mass. CAMx, on the other hand, underestimates the integrated mass in the free troposphere. Consequently, the accuracy of CAMx is limited concerning the transported Saharan dust cases. We conclude that the performance of CAMx appears to be best for the PM2.5 particles, both in the boundary layer and in the free troposphere. Sources of particles not properly taken into account by the model are confirmed to negatively affect its performance, especially for the PM2. 5−10 particles. ; The authors would like to acknowledge the EU projects MACC-III (Monitoring Atmospheric Composition and Climate – III, grant agreement no. 633080) and MACC-II project (Monitoring Atmospheric Composition and Climate – Interim Implementation, grant agreement no. 283576). The simulated results presented in this research paper have been produced using the EGI and HellasGrid infrastructures. The ACTRIS-2 project from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 654109 is gratefully acknowledged. The authors would also like to acknowledge the support provided by the Scientific Computing Center at Aristotle University of Thessaloniki throughout the progress of the work on air quality forecasting. BSC-DREAM8b simulations were performed on the Mare Nostrum supercomputer hosted by Barcelona Supercomputing Center-Centro Nacional de Supercomputacion (BSC-CNS). S. Basart wants to acknowledge the CICYT project (CGL2013-46736). Elina Giannakaki acknowledges the support of the Academy of Finland (project no. 270108). ; Peer Reviewed ; Postprint (published version)

This paper assesses the quality of IASI (Infrared Atmospheric Sounding Interferometer)/Metop-A (IASI-A) and IASI/Metop-B (IASI-B) ozone (O3) products (total and partial O3 columns) retrieved with the Fast Optimal Retrievals on Layers for IASI Ozone (FORLI-O3; v20151001) software for 9 years (2008-July 2017) through an extensive intercomparison and validation exercise using independent observations (satellite, ground-based and ozonesonde). Compared with the previous version of FORLI-O3 (v20140922), several improvements have been introduced in FORLI-O3 v20151001, including absorbance look-up tables recalculated to cover a larger spectral range, with additional numerical corrections. This leads to a change of ĝ1/4 4 % in the total ozone column (TOC) product, which is mainly associated with a decrease in the retrieved O3 concentration in the middle stratosphere (above 30 hPa/25 km). IASI-A and IASI-B TOCs are consistent, with a global mean difference of less than 0.3 % for both daytime and nighttime measurements; IASI-A is slightly higher than IASI-B. A global difference of less than 2.4 % is found for the tropospheric (TROPO) O3 column product (IASI-A is lower than IASI-B), which is partly due to a temporary issue related to the IASI-A viewing angle in 2015. Our validation shows that IASI-A and IASI-B TOCs are consistent with GOME-2 (Global Ozone Monitoring Experiment-2), Dobson, Brewer, SAOZ (Système d'Analyse par Observation Zénithale) and FTIR (Fourier transform infrared) TOCs, with global mean differences in the range of 0.1 %-2 % depending on the instruments compared. The worst agreement with UV-vis retrieved TOC (satellite and ground) is found at the southern high latitudes. The IASI-A and ground-based TOC comparison for the period from 2008 to July 2017 shows the long-Term stability of IASI-A, with insignificant or small negative drifts of 1 %-3 % decadeĝ'1. The comparison results of IASI-A and IASI-B against smoothed FTIR and ozonesonde partial O3 columns vary with altitude and latitude, with the maximum ...

This paper presents an extensive intercomparison and validation for the ozone (O3) product measured by the two Infrared Atmospheric Sounding Interferometers (IASIs) launched on board the MetOp-A and MetOp-B satellites in 2006 and in 2012 respectively. IASI O3 total columns and vertical profiles obtained from Fast Optimal Retrievals on Layers for IASI (FORLI) v20140922 software (running up until recently) are validated against independent observations during the period 2008-2014 on a global scale. On average for the period 2013-2014, IASI-A and IASI-B total ozone columns (TOCs) retrieved using FORLI are consistent, with IASI-B providing slightly lower values with a global difference of only 0.2±0.8%. The comparison between IASI-A and IASI-B O3 vertical profiles shows differences within ±2% over the entire altitude range. Global validation results for 7 years of IASI TOCs from FORLI against the Global Ozone Monitoring Experiment-2 (GOME-2) launched on board MetOp-A and Brewer-Dobson data show that, on average, IASI overestimates the ultraviolet (UV) data by 5-6% with the largest differences found in the southern high latitudes. The comparison with UV-visible SAOZ (Système d'Analyse par Observation Zénithale) measurements shows a mean bias between IASI and SAOZ TOCs of 2-4% in the midlatitudes and tropics and 7% at the polar circle. Part of the discrepancies found at high latitudes can be attributed to the limited information content in the observations due to low brightness temperatures. The comparison with ozonesonde vertical profiles (limited to 30km) shows that on average IASI with FORLI processing underestimates O3 by ∼ 5-15% in the troposphere while it overestimates O3 by ∼ 10-40% in the stratosphere, depending on the latitude. The largest relative differences are found in the tropical tropopause region; this can be explained by the low O3 amounts leading to large relative errors. In this study, we also evaluate an updated version of FORLI-O3 retrieval software (v20151001), using look-up tables recalculated ...

Atmospheric ozone plays a key role in air quality and the radiation budget of the Earth, both directly and through its chemical influence on other trace gases. Assessments of the atmospheric ozone distribution and associated climate change therefore demand accurate vertically resolved ozone observations with both stratospheric and tropospheric sensitivity, on both global and regional scales, and both in the long term and at shorter timescales. Such observations have been acquired by two series of European nadir-viewing ozone profilers, namely the scattered-light UV-visible spectrometers of the GOME family, launched regularly since 1995 (GOME, SCIAMACHY, OMI, GOME-2A/B, TROPOMI, and the upcoming Sentinel-5 series), and the thermal infrared emission sounders of the IASI type, launched regularly since 2006 (IASI on Metop platforms and the upcoming IASI-NG on Metop-SG). In particular, several Level-2 retrieved, Level-3 monthly gridded, and Level-4 assimilated nadir ozone profile data products have been improved and harmonized in the context of the ozone project of the European Space Agency's Climate Change Initiative (ESA Ozone-cci). To verify their fitness for purpose, these ozone datasets must undergo a comprehensive quality assessment (QA), including (a) detailed identification of their geographical, vertical, and temporal domains of validity; (b) quantification of their potential bias, noise, and drift and their dependences on major influence quantities; and (c) assessment of the mutual consistency of data from different sounders. For this purpose we have applied to the Ozone-cci Climate Research Data Package (CRDP) released in 2017 the versatile QA and validation system Multi-TASTE, which has been developed in the context of several heritage projects (ESA's Multi-TASTE, EUMETSAT's O3M-SAF, and the European Commission's FP6 GEOmon and FP7 QA4ECV). This work, as the second in a series of four Ozone-cci validation papers, reports for the first time on data content studies, information content studies and ...

The paper makes a convincing case that the Brewer network is capable of detecting enhanced SO2 columns, as observed, e.g., after volcanic eruptions. For this reason, large volcanic eruptions of the past decade have been used to detect and forecast SO2 plumes of volcanic origin using the Brewer and other ground-based networks, aided by satellite, trajectory analysis calculations and modelling. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 654109.

The paper makes a convincing case that the Brewer network is capable of detecting enhanced SO2 columns, as observed, e.g., after volcanic eruptions. For this reason, large volcanic eruptions of the past decade have been used to detect and forecast SO2 plumes of volcanic origin using the Brewer and other ground-based networks, aided by satellite, trajectory analysis calculations and modelling. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 654109.

Systematic measurements of dust concentration profiles at a continental scale were recently made possible by the development of synergistic retrieval algorithms using combined lidar and sun photometer data and the establishment of robust remote-sensing networks in the framework of Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS)/European Aerosol Research Lidar Network (EARLINET). We present a methodology for using these capabilities as a tool for examining the performance of dust transport models. The methodology includes considerations for the selection of a suitable data set and appropriate metrics for the exploration of the results. The approach is demonstrated for four regional dust transport models (BSC-DREAM8b v2, NMMB/BSC-DUST, DREAMABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. ; The financial support of the ACTRIS Research Infrastructure Project supported by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 262254 is gratefully acknowledged. This project has also received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 289923 – ITaRS. S. Basart and J. M. Baldasano acknowledge the CICYT project (CGL2010-19652 and CGL2013-46736) and Severo Ochoa (SEV- 2011-00067) programme of the Spanish Government. This program has received funding from the Ministry of Education and Science of the Republic of Serbia through project III43007.

Systematic measurements of dust concentration profiles at a continental scale were recently made possible by the development of synergistic retrieval algorithms using combined lidar and sun photometer data and the establishment of robust remote-sensing networks in the framework of Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS)/European Aerosol Research Lidar Network (EARLINET). We present a methodology for using these capabilities as a tool for examining the performance of dust transport models. The methodology includes considerations for the selection of a suitable data set and appropriate metrics for the exploration of the results. The approach is demonstrated for four regional dust transport models (BSC-DREAM8b v2, NMMB/BSC-DUST, DREAMABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. ; The financial support of the ACTRIS Research Infrastructure Project supported by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 262254 is gratefully acknowledged. This project has also received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 289923 – ITaRS. S. Basart and J. M. Baldasano acknowledge the CICYT project (CGL2010-19652 and CGL2013-46736) and Severo Ochoa (SEV- 2011-00067) programme of the Spanish Government. This program has received funding from the Ministry of Education and Science of the Republic of Serbia through project III43007.