Position correction in dust storm forecasting using LOTOS-EUROS v2.1: grid-distorted data assimilation v1.0

When calibrating simulations of dust clouds, both the intensity and the position are important. Intensity errors arise mainly from uncertain emission and sedimentation strengths, while position errors are attributed either to imperfect emission timing or to uncertainties in the transport. Though many studies have been conducted on the calibration or correction of dust simulations, most of these focus on intensity solely and leave the position errors mainly unchanged. In this paper, a grid-distorted data assimilation, which consists of an image-morphing method and an ensemble-based variational assimilation, is designed for realigning a simulated dust plume to correct the position error. This newly developed grid-distorted data assimilation has been applied to a dust storm event in May 2017 over East Asia. Results have been compared for three configurations: a traditional assimilation configuration that focuses solely on intensity correction, a grid-distorted data assimilation that focuses on position correction only and the hybrid assimilation that combines these two. For the evaluated case, the position misfit in the simulations is shown to be dominant in the results. The traditional emission inversion only slightly improves the dust simulation, while the grid-distorted data assimilation effectively improves the dust simulation and forecasting. The hybrid assimilation that corrects both position and intensity of the dust load provides the best initial condition for forecasting of dust concentrations.

Position correction in dust storm forecast using LOTOS-EUROS v2.1: grid distorted data assimilation v1.0

When calibrating simulations of dust clouds, both the intensity and the position are important. Intensity errors arise mainly from uncertain emission and sedimentation strengths, while position errors are attributed either to imperfect emission timing, or to uncertainties in the transport. Though many studies have been conducted on the calibration or correction of dust simulations, most of these focus on intensity solely, and leave the position errors mainly unchanged. In this paper, a grid distorted data assimilation, which consists of an imaging morphing method and an ensemble-based variational assimilation, is designed for re-aligning a simulated dust plume to correct the position error. This new developed grid distorted data assimilation has been applied to a dust storm event in May 2017 over East Asia. Results have been compared for three configurations: a traditional assimilation that focuses solely on intensity correction, a grid distorted data assimilation that focuses on position correction only, and the hybrid assimilation that combines these two. For the evaluated case, the position misfit in the simulations is shown to be dominant in the results. The traditional emission inversion improves only slightly the dust simulation, while the grid distorted data assimilation effectively improves the dust simulation and forecast. The hybrid assimilation that corrects both position and intensity of the dust load provides the best initial condition for forecast of dust concentrations.

Ice clouds detection with NOMAD-LNO onboard ExoMars Trace Gas Orbiter

<p>This work takes advantage of the NOMAD spectrometer observations, on board the 2016 ExoMars Trace Gas Orbiter. ExoMars is an ESA-Roscosmos joint mission consisting of a rover and an orbiter (Trace Gas Orbiter - TGO). The Nadir and Occultation for Mars Discovery (NOMAD) is one of the four instruments on board TGO. The instrument is a suite of three spectrometers designed to observe the atmosphere and the surface of Mars in the UV, visible and IR. For this study, the Limb, Nadir and Occultation (LNO) channel, operating in the IR, is selected [1][2].  We focus on specific signatures in the [2.3 - 3.8 μm] range of NOMAD-LNO in order to study the possible detection of clouds at these wavelengths in the infrared.</p><p>For this study, we have selected the order 169 ([2611.8 nm - 2632.7 nm]) located in the vicinity of 2.7 µm CO<sub>2</sub>/H<sub>2</sub>O ices absorption band. We search for the presence of ice clouds in MY 34 (L<sub>S </sub>= 150° - 360°) and MY 35 for observations with a solar zenith angle below 80 degrees.  The detection method is adapted from Bellucci et al., 2019 [3] and L. Ruiz Lozano et al., 2020 [4].  The initial results indicate a number of detections in the Tharsis region consistent with the known ‘W’ clouds [6][7].  Finally, these results will be compared with the NOMAD-UVIS observations ([230 nm - 310 nm]) obtained at the same TGO orbits.</p><p><strong>Acknowledgements<br></strong></p><p>The NOMAD experiment is led by the Royal Belgian Institute for Space Aeronomy (IASB-BIRA), assisted by Co-PI teams from Spain (IAA-CSIC), Italy (INAF-IAPS), and the United Kingdom (Open University). This project acknowledges funding by the Belgian Science Policy Office (BELSPO), the Belgian Fonds de la Recherche Scientifique – FNRS under grant number 30442502 (ET_HOME) and the FRIA, with the financial and contractual coordination by the ESA Prodex Office (PEA 4000103401, 4000121493), by Spanish Ministry of Science and Innovation (MCIU) and by European funds under grants PGC2018-101836-B-I00 and ESP2017-87143-R (MINECO/FEDER), as well as by UK Space Agency through grants ST/R005761/1, ST/P001262/1, ST/R001405/1 and ST/R001405/1 and Italian Space Agency through grant 2018-2-HH.0.</p><p> </p><p><strong>References</strong><br>[1] A.C. Vandaele et al., 2015. Optical and radiometric models of the NOMAD instrument part I: the UVIS channel. Optics Express, 23(23):30028–30042.<br>[2] E. Neefs et al., 2015. NOMAD spectrometer on the ExoMars trace gas orbiter mission: part 1—design, manufacturing and testing of the infrared channels. Applied optics, 54(28):8494–8520.<br>[3] G. Bellucci et al., 2019. TGO/NOMAD Nadir observations during the 2018 global dust storm event, EPSC-DPS 2019<br>[4] L. Ruiz Lozano et al., 2020. Use of TGO-NOMAD nadir observations for ice detection, EPSC Abstracts, Vol. 14, Virtual EPSC 2020, EPSC2020-748. <br>[5] M. Vincendon, et al., 2011. New near‐IR observations of mesospheric CO2 and H2O clouds on Mars, J. Geophys. Res., 116, E00J02, doi:10.1029/2011JE003827.<br>[6] J. L. Benson, et al., 2003. The seasonal behavior of water ice clouds in the Tharsis and Valles Marineris regions of Mars: Mars Orbiter Camera Observations, Icarus, Volume 165, Issue 1, 2003, Pages 34-52, ISSN 0019-1035, https://doi.org/10.1016/S0019-1035(03)00175-1.</p>

Dust Transport from Inland Australia and Its Impact on Air Quality and Health on the Eastern Coast of Australia during the February 2019 Dust Storm

Dust storms originating from Central Australia and western New South Wales frequently cause high particle concentrations at many sites across New South Wales, both inland and along the coast. This study focussed on a dust storm event in February 2019 which affected air quality across the state as detected at many ambient monitoring stations in the Department of Planning, Industry and Environment (DPIE) air quality monitoring network. The WRF-Chem (Weather Research and Forecast Model—Chemistry) model is used to study the formation, dispersion and transport of dust across the state of New South Wales (NSW, Australia). Wildfires also happened in northern NSW at the same time of the dust storm in February 2019, and their emissions are taken into account in the WRF-Chem model by using Fire Inventory from NCAR (FINN) as emission input. The model performance is evaluated and is shown to predict fairly accurate the PM2.5 and PM10 concentration as compared to observation. The predicted PM2.5 concentration over New South Wales during 5 days from 11 to 15 February 2019 is then used to estimate the impact of the February 2019 dust storm event on three health endpoints, namely mortality, respiratory and cardiac disease hospitalisation rates. The results show that even though as the daily average of PM2.5 over some parts of the state, especially in western and north western NSW near the centre of the dust storm and wild fires, are very high (over 900 µg/m3), the population exposure is low due to the sparse population. Generally, the health impact is similar in order of magnitude to that caused by biomass burning events from wildfires or from hazardous reduction burnings (HRBs) near populous centres such as in Sydney in May 2016. One notable difference is the higher respiratory disease hospitalisation for this dust event (161) compared to the fire event (24).

Dust Transport from Inland Australia and its Impact on Air Quality and Health on the Eastern Coast of Australia during the February 2019 Dust Storm.

Dust storms originating from Central Australia and western New South Wales frequently cause high particles concentration at many sites across New South Wales, both inland and along the coast. This study focussed on a dust storm event in February 2019 which affect air quality across the state as detected at many ambient monitoring stations in the Department of Planning, Industry and Environment (DPIE) air quality monitoring network. The WRF-Chem (Weather Research and Forecast Model – Chemistry) model is used to study the formation, dispersion and transport of dust across the state of New South Wales (NSW, Australia). Wildfires also happened in northern NSW at the same time of the dust storm in February 2019, and their emissions are taken into account in WRF-Chem model by using Fire Inventory from NCAR (FINN) as emission input. The model performance is evaluated and is shown to predict fairly accurate the PM2.5 and PM10 concentration as compared to observation. The predicted PM2.5 concentration over New South Wales during 5 days from 11 to 15 February 2019 is then used to estimate the impact of the February 2019 dust storm event on three health endpoints namely mortality, respiratory and cardiac diseases hospitalisation rates. The results show that even though as the daily average of PM2.5 over some parts of the state, especially in western and north western NSW near the centre of the dust storm and wild fires, are very high (over 900 µg/m3), the population exposure is low due to the sparse population. The top five Statistical Area Level 4 regions with the most impact in term of mortality, respiratory diseases hospitalisation and cardiac disease hospitalisation are Far West and Orana, Newcastle and Lake Macquarie, New England and North West, Sydney – Inner South West and either Central Coast (mortality) or Sydney – Parramatta (respiratory diseases hospitalisation) or Sydney – Inner West (cardiac diseases hospitalisation). Generally, the health impact is similar in order of magnitude to that caused by biomass burnings events from wildfires or from hazardous reduction burnings (HRBs) near populous centres such as in Sydney in May 2016. One notable difference is the higher respiratory diseases hospitalisation for this dust event (161) compared to fire event (24).

Air quality changes in Ukraine during the April 2020 wildfire event

The paper analyzes air quality changes in Ukraine during a wildfire event in April 2020 and a dust storm episode during the 16th of April 2020. The wildfire event contained two episodes of active fires and huge pollutants' emission: 4-14 April and 16-21 April, respectively. Using the Sentinel-5P data of CO and NO 2 column number density and ground-based measurements, there was estimated air quality deterioration. Advection of polluted air masses and analysis of affected territories were made in combination with a Web-based HYSPLIT model. Satellite data described air quality changes better than in-situ measurements. Data intercomparison showed better coincidence in regions that were not affected by wildfire emissions. The paper described the dust storm event based on absorbing aerosol index (AAI) data that occurred between two wildfire episodes.

Dust Storm Event of February 2019 in Central and East Coast of Australia and Evidence of Long-Range Transport to New Zealand and Antarctica

Between 11 and 15 February 2019, a dust storm originating in Central Australia with persistent westerly and south westerly winds caused high particle concentrations at many sites in the state of New South Wales (NSW); both inland and along the coast. The dust continued to be transported to New Zealand and to Antarctica in the south east. This study uses observed data and the WRF-Chem Weather Research Forecast model based on GOCART-AFWA (Goddard Chemistry Aerosol Radiation and Transport–Air Force and Weather Agency) dust scheme and GOCART aerosol and gas-phase MOZART (Model for Ozone And Related chemical Tracers) chemistry model to study the long-range transport of aerosols for the period 11 to 15 February 2019 across eastern Australia and onto New Zealand and Antarctica. Wildfires also happened in northern NSW at the same time, and their emissions are taken into account in the WRF-Chem model by using the Fire Inventory from NCAR (FINN) as the emission input. Modelling results using the WRF-Chem model show that for the Canterbury region of the South Island of New Zealand, peak concentration of PM10 (and PM2.5) as measured on 14 February 2019 at 05:00 UTC at the monitoring stations of Geraldine, Ashburton, Timaru and Woolston (Christchurch), and about 2 h later at Rangiora and Kaiapoi, correspond to the prediction of high PM10 due to the intrusion of dust to ground level from the transported dust layer above. The Aerosol Optical Depth (AOD) observation data from MODIS 3 km Terra/Aqua and CALIOP LiDAR measurements on board CALIPSO (Cloud-Aerosol LiDAR and Infrared Pathfinder Satellite Observations) satellite also indicate that high-altitude dust ranging from 2 km to 6 km, originating from this dust storm event in Australia, was located above Antarctica. This study suggests that the present dust storms in Australia can transport dust from sources in Central Australia to the Tasman sea, New Zealand and Antarctica.

Dust Storm Event of February 2019 in Central and East Coast of Australia and Evidence of Long-Range Transport to New Zealand and Antarctica

Between 11 to 15 February 2019, a dust storm originating from Central Australia with persistent westerly and south westerly winds caused high particles concentration at many sites in the state of New South Wales (NSW), both inland and along the coast. The dust continued on to New Zealand and to Antarctica in the south east. This study uses observed data from air quality monitoring stations in NSW and New Zealand, MODIS 3km AOD (Aerosol Optical Depth) product from Terra/Aqua and lidar aerosol profile from CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite data, and the Weather Research Forecast WRF-Chem model based on GOCART-AFWA (Goddard Chemistry Aerosol Radiation and Transport – Air Force and Weather Agency) dust scheme and GOCART aerosol and gas-phase MOZART (Model for Ozone And Related chemical Tracers) chemistry model to study the long-range transport of aerosols for the period 11 to 15 February 2019 across eastern Australia and onto New Zealand and Antarctica. Wild fires also happened in northern NSW at the same time and their emissions are taken into account in WRF-Chem model by using Fire Inventory from NCAR (FINN) as emission input. Modelling results by the WRF-Chem model show that for the Canterbury region of South Island of New Zealand, peak concentration of PM10 (and PM2.5) as measured on 14 February 2019 at 05:00 UTC at the monitoring stations of Geraldine, Ashburton, Timaru and Woolston (Christchurch), which are more than 100km from each other and at Rangiora, Kaiapoi about 2 hours later, correspond to the prediction of high PM10 due to intrusion of dust to ground level from transported dust layer above. The Aerosol Optical Depth (AOD) observation data from MODIS Terra/Aqua and CALIOP lidar measurements on board CALIPSO satellite also indicate that high altitude of dust, originated from this dust storm event in Australia, was located above Antarctica. This study suggests that at present dust storms in Australia can transport dust from sources in Central Australia to the Tasman sea, New Zealand and Antarctica. This process has been going on for at least the last 170k years as indicated by dust found in ice cores from Antarctica and sediment records in the Tasman Sea.