A methodology for investigating dust model performance using synergistic EARLINET/AERONET dust concentration retrievals

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 Infra-Structure 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, DREAM-ABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. The observations, which include coincident multi-wavelength lidar and sun photometer measurements, were processed with the Lidar-Radiometer Inversion Code (LIRIC) to retrieve aerosol concentration profiles. The methodology proposed here shows advantages when compared to traditional evaluation techniques that utilize separately the available measurements such as separating the contribution of dust from other aerosol types on the lidar profiles and avoiding model assumptions related to the conversion of concentration fields to aerosol extinction values. When compared to LIRIC retrievals, the simulated dust vertical structures were found to be in good agreement for all models with correlation values between 0.5 and 0.7 in the 1-6 km range, where most dust is typically observed. The absolute dust concentration was typically underestimated with mean bias values of -40 to -20 mu g m(-3) at 2 km, the altitude of maximum mean concentration. The reported differences among the models found in this comparison indicate the benefit of the systematic use of the proposed approach in future dust model evaluation studies

Operational Dust Prediction

Over the last few years, numerical prediction of dust aerosol concentration has become prominent at several research and operational weather centres due to growing interest from diverse stakeholders, such as solar energy plant managers, health professionals, aviation and military authorities and policymakers. Dust prediction in numerical weather prediction-type models faces a number of challenges owing to the complexity of the system. At the centre of the problem is the vast range of scales required to fully account for all of the physical processes related to dust. Another limiting factor is the paucity of suitable dust observations available for model, evaluation and assimilation. This chapter discusses in detail numerical prediction of dust with examples from systems that are currently providing dust forecasts in near real-time or are part of international efforts to establish daily provision of dust forecasts based on multi-model ensembles. The various models are introduced and described along with an overview on the importance of dust prediction activities and a historical perspective. Assimilation and evaluation aspects in dust prediction are also discussed

Tropospheric and stratospheric smoke over Europe as observed within EARLINET/ACTRIS in summer 2017

For several weeks in summer 2017, strong smoke layers were observed over Europe at numerous EARLINET stations. EARLINET is the European research lidar network and part of ACTRIS and comprises more than 30 ground-based lidars. The smoke layers were observed in the troposphere as well as in the stratosphere up to 25 km from Northern Scandinavia over whole western and central Europe to the Mediterranean regions. Backward trajectory analysis among other tools revealed that these smoke layers originated from strong wild fires in western Canada in combination with pyrocumulus convection. An extraordinary fire event in the mid of August caused intense smoke layers that were observed across Europe for several weeks starting on 18 August 2017. Maximum aerosol optical depths up to 1.0 at 532 nm were observed at Leipzig, Germany, on 22 August 2017 during the peak of this event. The stratospheric smoke layers reached extinction coefficient values of more than 600 Mm−1 at 532 nm, a factor of 10 higher than observed for volcanic ash after the Pinatubo eruption in the 1990s. First analyses of the intensive optical properties revealed low particle depolarization values at 532 nm for the tropospheric smoke (spherical particles) and rather high values (up to 20%) in the stratosphere. However, a strong wavelength dependence of the depolarization ratio was measured for the stratospheric smoke. This indicates irregularly shaped stratospheric smoke particles in the size range of the accumulation mode. This unique depolarization feature makes it possible to distinguish clearly smoke aerosol from cirrus clouds or other aerosol types by polarization lidar measurements. Particle extinction-to-backscatter ratios were rather low in the order of 40 to 50 sr at 355 nm, while values between 70-90 sr were measured at higher wavelengths. In the western and central Mediterranean, stratospheric smoke layers were most prominent in the end of August at heights between 16 and 20 km. In contrast, stratospheric smoke started to occur in the eastern Mediterranean (Cyprus and Israel) in the beginning of September between 18 and 23 km. Stratospheric smoke was still visible in the beginning of October at certain locations (e.g. Evora, Portugal), while tropospheric smoke was mainly observed until the end of August within Europe. An overview of the smoke layers measured at several EARLINET sites will be given. The temporal development of these layers as well as their geometrical and optical properties will be presented

Impact of WRF model PBL schemes on air quality simulations over Catalonia, Spain

Here we analyze the impact of four planetary boundary-layer (PBL) parametrization schemes from the Weather Research and Forecasting (WRF) numerical weather prediction model on simulations of meteorological variables and predicted pollutant concentrations from an air quality forecast system (AQFS). The current setup of the Spanish operational AQFS, CALIOPE, is composed of the WRF-ARW V3.5.1 meteorological model tied to the Yonsei University (YSU) PBL scheme, HERMES v2 emissions model, CMAQ V5.0.2 chemical transport model, and dust outputs from BSC-DREAM8bv2. We test the performance of the YSU scheme against the Assymetric Convective Model Version 2 (ACM2), Mellor-Yamada-Janjic (MYJ), and Bougeault-Lacarrère (BouLac) schemes. The one-day diagnostic case study is selected to represent the most frequent synoptic condition in the northeast Iberian Peninsula during spring 2015; regional recirculations. It is shown that the ACM2 PBL scheme performs well with daytime PBL height, as validated against estimates retrieved using a micro-pulse lidar system (mean bias = − 0.11 km). In turn, the BouLac scheme showed WRF-simulated air and dew point temperature closer to METAR surface meteorological observations. Results are more ambiguous when simulated pollutant concentrations from CMAQ are validated against network urban, suburban, and rural background stations. The ACM2 scheme showed the lowest mean bias (− 0.96 μg m− 3) with respect to surface ozone at urban stations, while the YSU scheme performed best with simulated nitrogen dioxide (− 6.48 μg m− 3). The poorest results were with simulated particulate matter, with similar results found with all schemes tested.The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013): People, ITN Marie Curie Actions Programme (2012–2016) in the frame of ITaRS under grant agreement no. 289923. Simulations were executed on the MareNostrum supercomputer at the Barcelona Supercomputing Centre, under grants SEV-2011-00067 of Severo Ochoa program and CGL2013-46736-R, awardedby theSpanish Government.Specialthanks to Francesc Rocadenbosch and the UPC Remote Sensing Laboratory for use of the extended Kalman filter technique. The authors wish to thank Victor Valverde for his assistance with the air quality simulations.Peer Reviewe

TARJETA DE VISITA [Material gráfico]

EUROPACopia digital. Madrid : Ministerio de Educación, Cultura y Deporte, 201

Emissions of Gases and Aerosols. Progress, Modeling Needs and Emerging Issues. Report of the 2009 GEIA-ACCENT Conference on emissions, ACCENT Report 4.2009, 2009.

Report of the 2009 GEIA-ACCENT Conferenc