Atmospheric modeling of natural hazards

Thesis (Ph.D.) University of Alaska Fairbanks, 2021Airborne hazards either in gaseous form or particulate matter can originate from a variety of sources. The most common natural airborne hazards are ash and SO₂ released during volcanic eruptions, smoke emitted caused by wildfires and dust storms. Once released into the atmosphere they can have a significant impact on different parts of the environment e.g. air quality, soil and water, as well as air traffic and ground transportation networks. This latter field is an important aspect of everyday life that is affected during hazardous events. Aviation is one of the most critical ways of transport in this century. Even short interruptions in flight schedules can lead to major economic damages. Volcanic eruptions comprise one of the most important airborne hazards to aviation. These are considered rare as compared to severe weather, but with an extremely high impact. This dissertation focusses on dispersion modeling tools and how they can support emergency response during different phases of volcanic eruption events. The impact of the volcanic ash cloud on the prediction of meteorological parameters and furthermore the dispersion of the ash is demonstrated by applying the Weather Research Forecasting (WRF) model with on-line integrated chemical transport (WRF-Chem) to simulate the 2010 Eyjafjallajökull eruption in Iceland. Comprehensive observational data sets have been collected to evaluate the model and to show the added value of integrating direct-feedback processes into the simulations. The case of the Eyjafjallajökull eruption showed the necessity to further develop the volcanic emission preprocessor of WRF-Chem which has been extended for flexible and complex ash and SO₂ source terms. Furthermore, the thesis describes how scientists could support operational centers to mitigate hazards during a large volcanic eruption event. The author of the dissertation coordinated a large exercise including experts across all Europe within a project funded by the European Union. The exercise aimed to develop and test new tools, models, and data to support real-time decision making in aviation flight planning during a volcanic crisis event. New state-of-the-art modeling applications were integrated into a flight planning software during a fictitious eruption of the Etna volcano in Italy with contributions from scientists, the military and the aviation community.Cooperative Institute for Alaska Research, National Oceanic and Atmospheric Administration cooperative agreement NA13OAR4320056 with the University of AlaskaChapter 1: Introduction --1.1 Airborne hazards and their impact on the environment and aviation -- 1.2 The volcanic risk mitigation system for aviation -- 1.3 Dispersion models support emergency response -- 1.4 Composition of the dissertation -- References. Chapter 2: The effects of simulating volcanic aerosol radiative feedbacks with WRF-Chem during the Eyjafjallajökull eruption, April and May 2010 -- Abstract -- 2.1 Introduction -- 2.2. Simulations setup -- 2.2.1. Model setup and case specifications -- 2.2.2. Volcanic emission preprocessor -- 2.3. Spatial and temporal evaluation of the location of the volcanic plume -- 2.4. Evaluation of meteorological parameters close to the surface -- 2.4.1. Meteorological observations -- 2.4.2. Average meteorological parameters at ground level -- 2.5. Aerosol radiative feedback effects in the model simulations -- 2.5.1. Radiative feedback effects close to the surface -- 2.5.2. Vertical profiles of wind speed and temperature -- 2.5.3. Influence of the radiative feedback effects on the atmospheric stability -- 2.6. The influence of considering the direct effect on the dispersion of the ash cloud -- 2.7. Summary and conclusions -- 2.8. Acknowledgments -- References. Chapter 3: Extension of the WRF-Chem volcanic emission preprocessor to integrate complex source terms and evaluation for different emission scenarios of the Grimsvötn 2011 eruption -- Abstract -- 3.1 Introduction -- 3.2 Extension of the volcanic preprocessor of the WRF-Chem model -- 3.3 WRF-Chem model simulations -- 3.3.1 Model setup -- 3.3.2 Volcanic emission scenarios -- 3.3.3 Model inter-comparison of predicted ash considering aviation regulation aspects -- 3.4 Evaluation of WRF-Chem simulations with observations -- 3.4.1. Comparison of volcanic ash and SO₂ with satellite data -- 3.4.2 Comparison with ground-based observations -- 3.4.2.1 Lidar profiles at selected stations -- 3.4.2.2 Comparison with PM10 observations at selected ground stations -- 3.5. Conclusions -- 3.6 Acknowledgements -- Glossary -- Appendix -- References. Chapter 4: A volcanic-hazard demonstration exercise to assess and mitigate the impacts of volcanic ash clouds on civil and military aviation -- Abstract -- 4.1 Introduction -- 4.2 International exercises -- 4.3 Overview of the EUNADICS-AV demonstration exercise set-up -- 4.3.1 General approach -- 4.3.1.1 The volcanic-eruption scenario -- 4.3.1.2 Data sharing and visualization -- 4.4 Data sets used for the demonstration exercise -- 4.4.1 Artificial observations -- 4.4.1.1 Simulations of the artificial plume evolution -- 4.4.1.2 Generation of artificial observations from SILAM simulations -- 4.4.2 The early-warning system (EWS) -- 4.4.2.1 Volcano observatory, Sicily -- 4.4.2.2 Synthetic ACTRIS EARLINET data -- 4.4.2.3 Synthetic satellite data simulated for IASI and MODIS -- 4.4.3 Model ensemble -- 4.5 The impact of the ash cloud on aviation for the Etna eruption scenario -- 4.5.1 Air navigation service provider -- 4.5.2 Austrian Armed Forces (AAF) -- 4.5.3 Rerouting of flights -- 4.6 Conclusion -- 4.7 Acknowledgements -- Glossary -- References. Chapter 5: Dissertation Summary and Conclusions -- 5.1 Extension and evaluation of the WRF-Chem model -- 5.2 Future perspectives -- References

USER EXPERIENCE WITH MODEL VALIDATION EXERCISES

Gaussian and Lagrangian model runs are evaluated in comparison to field data from the Odour Release and Odour Dispersion project and to wind tunnel data from the Mock Urban Setting Test (MUST). Different statistical metrics are discussed. To conclude which model performs best in the two cases, a weighted multiplier proposed by Sornette et al. (2007) is calculated based on each metric and finally multiplied to one score per model and experiment. The results illustrate once again that a good model performance is strongly dependent on the model input (e.g. terrain data, roughness length). Promising results are received from a combination of the Lagrangian dispersion model LASAT with wind field simulations calculated with the CFD model MISKAM

EVALUATION OF THE OPERATIONAL OZONE FORECAST MODEL OF THE ZAMG WITH MEASUREMENTS OF THE AUSTRIAN AIR QUALITY NETWORK

Operational model forecasts of ozone concentrations are compared to the observations of about 150 air quality stations in Austria. Evaluations of the last three summers revealed that exceedances of the information threshold could be predicted quite well by the model. Investigation of a heat period in summer 2006 indicates possible sources of precursors. The Lagrangian particle model LASAT (www.janicke.de) is used additionally to the chemical model CAMx (www.camx.com) to show the dispersion of the plumes of stacks with high emissions of NOx in the vicinity of Vienna. For two months in summer 2007 sensitivity studies with different input parameters were performed. Model runs with different parameterisations for the vertical diffusion coefficient (Kv) are conducted and experiments with different values of the minimum values of Kv in the lower levels show the influence of this parameter on the nocturnal ozone decrease for different sites. Different model runs with variable boundary conditions at the top of the modelling domain as well as variable total ozone column data are performed

Analysis of meteorology-chemistry interactions during air pollution episodes using online coupled models within AQMEII Phase-2

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).This study reviews the top ranked meteorology and chemistry interactions in online coupled models recommended by an experts’ survey conducted in COST Action EuMetChem and examines the sensitivity of those interactions during two pollution episodes: the Russian forest fires 25 Jul -15 Aug 2010 and a Saharan dust transport event from 1 Oct -31 Oct 2010 as a part of the AQMEII phase-2 exercise. Three WRF-Chem model simulations were performed for the forest fire case for a baseline without any aerosol feedback on meteorology, a simulation with aerosol direct effects only and a simulation including both direct and indirect effects. For the dust case study, eight WRF-Chem and one WRF-CMAQ simulations were selected from the set of simulations conducted in the framework of AQMEII. Of these two simulations considered no feedbacks, two included direct effects only and five simulations included both direct and indirect effects. The results from both episodes demonstrate that it is important to include the meteorology and chemistry interactions in online-coupled models. Model evaluations using routine observations collected in AQMEII phase-2 and observations from a station in Moscow show that for the fire case the simulation including only aerosol direct effects has better performance than the simulations with no aerosol feedbacks or including both direct and indirect effects. The normalized mean biases are significantly reduced by 10-20% for PM10 when including aerosol direct effects. The analysis for the dust case confirms that models perform better when including aerosol direct effects, but worse when including both aerosol direct and indirect effects, which suggests that the representation of aerosol indirect effects needs to be improved in the model.Peer reviewedFinal Published versio

Multi-sectoral Impact Assessment of an Extreme African Dust Episode in the Eastern Mediterranean in March 2018

In late March 2018, a large part of the Eastern Mediterranean experienced an extraordinary episode of African dust, one of the most intense in recent years, here referred to as the “Minoan Red” event. The episode mainly affected the Greek island of Crete, where the highest aerosol concentrations over the past 15 yeas were recorded, although impacts were also felt well beyond this core area. Our study fills a gap in dust research by assessing the multi-sectoral impacts of sand and dust storms and their socioeconomic implications. Specifically, we provide a multi-sectoral impact assessment of Crete during the occurrence of this exceptional African dust event. During the day of the occurrence of the maximum dust concentration in Crete, i.e. March 22nd, 2018, we identified impacts on meteorological conditions, agriculture, transport, energy, society (including closing of schools and cancellation of social events), and emergency response systems. As a result, the event led to a 3-fold increase in daily emergency responses compare to previous days associated with urban emergencies and wildfires, a 3.5-fold increase in hospital visits and admissions for Chronic Obstructive Pulmonary Disease (COPD) exacerbations and dyspnoea, a reduction of visibility causing aircraft traffic disruptions (eleven cancellations and seven delays), and a reduction of solar energy production. We estimate the cost of direct and indirect effects of the dust episode, considering the most affected socio-economic sectors (e.g. civil protection, aviation, health and solar energy production), to be between 3.4 and 3.8 million EUR for Crete. Since such desert dust transport episodes are natural, meteorology-driven and thus to a large extent unavoidable, we argue that the efficiency of actions to mitigate dust impacts depends on the accuracy of operational dust forecasting and the implementation of relevant early warning systems for social awareness

Improving the deterministic skill of air quality ensembles

<p><strong>Abstract.</strong> Forecasts from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as the model itself (e.g. physical parameterization, chemical mechanism). Multi-model ensemble forecasts can improve the forecast skill provided that certain mathematical conditions are fulfilled. We demonstrate through an intercomparison of two dissimilar air quality ensembles that unconditional raw forecast averaging, although generally successful, is far from optimum. One way to achieve an optimum ensemble is also presented. The basic idea is to either add optimum weights to members or constrain the ensemble to those members that meet certain conditions in time or frequency domain. The methods are evaluated against ground level observations collected from the EMEP and Airbase databases.<br><br> The two ensembles were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). Verification statistics shows that the deterministic models simulate better O<sub>3</sub> than NO<sub>2</sub> and PM<sub>10</sub>, linked to different levels of complexity in the represented processes. The ensemble mean achieves higher skill compared to each station's best deterministic model at 39 %–63 % of the sites. The skill gained from the favourable ensemble averaging has at least double the forecast skill compared to using the full ensemble. The method proved robust for the 3-monthly examined time-series if the training phase comprises 60 days. Further development of the method is discussed in the conclusion.</p&gt

Prototype of multi-hazard early warning from EUNADICS-AV systems to trigger model forecasts of European airspace

info:eu-repo/semantics/nonPublishe

Multi-sectoral impact assessment of an extreme African dust episode in the Eastern Mediterranean in March 2018

In late March 2018, a large part of the Eastern Mediterranean experienced an extraordinary episode of African dust, one of the most intense in recent years, here referred to as the “Minoan Red” event. The episode mainly affected the Greek island of Crete, where the highest aerosol concentrations over the past 15 yeas were recorded, although impacts were also felt well beyond this core area. Our study fills a gap in dust research by assessing the multi-sectoral impacts of sand and dust storms and their socioeconomic implications. Specifically, we provide a multi-sectoral impact assessment of Crete during the occurrence of this exceptional African dust event. During the day of the occurrence of the maximum dust concentration in Crete, i.e. March 22nd, 2018, we identified impacts on meteorological conditions, agriculture, transport, energy, society (including closing of schools and cancellation of social events), and emergency response systems. As a result, the event led to a 3-fold increase in daily emergency responses compare to previous days associated with urban emergencies and wildfires, a 3.5-fold increase in hospital visits and admissions for Chronic Obstructive Pulmonary Disease (COPD) exacerbations and dyspnoea, a reduction of visibility causing aircraft traffic disruptions (eleven cancellations and seven delays), and a reduction of solar energy production. We estimate the cost of direct and indirect effects of the dust episode, considering the most affected socio-economic sectors (e.g. civil protection, aviation, health and solar energy production), to be between 3.4 and 3.8 million EUR for Crete. Since such desert dust transport episodes are natural, meteorology-driven and thus to a large extent unavoidable, we argue that the efficiency of actions to mitigate dust impacts depends on the accuracy of operational dust forecasting and the implementation of relevant early warning systems for social awareness.Thanks are due to FCT/MCTES for the financial support to CESAM (UIDP/50017/2020+UIDB/50017/2020) through national funds, and also to the Icelandic Research Fund for the grant no. 207057-051. Authors S. Kazadzis and P. Kosmopoulos would like to acknowledge the European Commission project EuroGEO e-shape (grant agreement No 820852). Also, International Cooperative for Aerosol Prediction (ICAP) and NASA mission researchers are gratefully for providing aerosol data for this study. Aurelio Tobias was supported by MCIN/AEI/10.13039/501100011033 (grant CEX2018-000794-S). S. Kutuzov acknowledges the Megagrant project (agreement No. 075-15-2021-599, 8.06.2021)

Modelling tunnel jet emissions with LASAT: evaluation study with two Austrian data sets (Ehrentalerbergtunnel and Kaisermuhlentunnel)

Two comprehensive data sets are used to investigate the ability of the Lagrangian particle diffusion model LASAT to simulate the dispersion of plumes emitted from tunnel jets. The data sets differ in traffic volume, tunnel geometry and temporal resolution of the measurement data. In the framework of the measurement campaign at the Ehrentalerbergtunnel in Carinthia, seven trace gas experiments with SF6 were conducted in 2001. Short term averages (30 minutes) of concentrations were measured at 25 air quality stations in the vicinity of the tunnel portal during different meteorological conditions. In general the dispersion of the plume depends on the meteorological conditions (wind, stability) and the modification of the flow by terrain and buildings in the vicinity of the portal. The influence of the exit velocity of the tunnel jet must also be considered as well as the difference between the exhaust temperature and the ambient air temperature to account for buoyancy effects. The temperature increment cannot be provided directly as input parameter to LASAT as in case of the tunnel jet velocity although it is an important parameter. With LASAT, the model user can adjust two empirical input parameters to the tunnel specifications. Relationships between these model parameters and the tunnel parameters are developed in this study. They are based on the data set Ehrentalerbergtunnel and provide reasonable input values for the model user. The simulations with LASAT show that the model is able to reproduce the location and the height of the observed peak concentrations very well. The second data set was generated from January to October 2001 at the Kaisermühlentunnel in Vienna. Measurements of NOx at four air quality stations near the portal are available. Because of uncertainties in the emission data caused by vehicle counts in only one direction, only long term averages of concentrations are compared for this data set. The functions between tunnel and model parameters derived for the Ehrentalerbergtunnel are also applied to this site. It is shown that LASAT is able to simulate the position of the plume and that the modelled and the measured concentration values do not deviate more than 30 %. This study reveals that LASAT can be applied to tunnel portal emissions. The model simulations for both the Ehrentalerbergtunnel and Kaisermühlentunnel meet the requirements specified in the Austrian design guideline RVS 9.263 “Ventilation Systems - Pollutant burden at portals”

The Environmental Effects of the April 2020 Wildfires and the Cs-137 Re-Suspension in the Chernobyl Exclusion Zone: A Multi-Hazard Threat

International audienceThis paper demonstrates the environmental impacts of the wildfires occurring at the beginning of April 2020 in and around the highly contaminated Chernobyl Exclusion Zone (CEZ). Due to the critical fire location, concerns arose about secondary radioactive contamination potentially spreading over Europe. The impact of the fire was assessed through the evaluation of fire plume dispersion and re-suspension of the radionuclide Cs-137, whereas, to assess the smoke plume effect, a WRF-Chem simulation was performed and compared to Tropospheric Monitoring Instrument (TROPOMI) satellite columns. The results show agreement of the simulated black carbon and carbon monoxide plumes with the plumes as observed by TROPOMI, where pollutants were also transported to Belarus. From an air quality and health perspective, the wildfires caused extremely bad air quality over Kiev, where the WRF-Chem model simulated mean values of PM2.5 up to 300 µg/m3 (during the first fire outbreak) over CEZ. The re-suspension of Cs-137 was assessed by a Bayesian inverse modelling approach using FLEXPART as the atmospheric transport model and Ukraine observations, yielding a total release of 600 ± 200 GBq. The increase in both smoke and Cs-137 emissions was only well correlated on the 9 April, likely related to a shift of the focus area of the fires. From a radiological point of view even the highest Cs-137 values (average measured or modelled air concentrations and modelled deposition) at the measurement site closest to the Chernobyl Nuclear Power Plant, i.e., Kiev, posed no health risk