scholarly journals Model-based aviation advice on distal volcanic ash clouds by assimilating aircraft in situ measurements

2016 ◽  
Vol 16 (14) ◽  
pp. 9189-9200 ◽  
Author(s):  
Guangliang Fu ◽  
Arnold Heemink ◽  
Sha Lu ◽  
Arjo Segers ◽  
Konradin Weber ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Transport Model ◽  
Real Life ◽  
Forecast Accuracy ◽  
In Situ Measurements ◽  
Northwestern Part ◽  
Ash Plume ◽  
Potential Improvement ◽  
Ash Transport

Abstract. The forecast accuracy of distal volcanic ash clouds is important for providing valid aviation advice during volcanic ash eruption. However, because the distal part of volcanic ash plume is far from the volcano, the influence of eruption information on this part becomes rather indirect and uncertain, resulting in inaccurate volcanic ash forecasts in these distal areas. In our approach, we use real-life aircraft in situ observations, measured in the northwestern part of Germany during the 2010 Eyjafjallajökull eruption, in an ensemble-based data assimilation system combined with a volcanic ash transport model to investigate the potential improvement on the forecast accuracy with regard to the distal volcanic ash plume. We show that the error of the analyzed volcanic ash state can be significantly reduced through assimilating real-life in situ measurements. After a continuous assimilation, it is shown that the aviation advice for Germany, the Netherlands and Luxembourg can be significantly improved. We suggest that with suitable aircrafts measuring once per day across the distal volcanic ash plume, the description and prediction of volcanic ash clouds in these areas can be greatly improved.

scholarly journals Model-based aviation advice on distal volcanic ash clouds by assimilating aircraft in-situ measurements

2016 ◽  
Author(s):  
G. Fu ◽  
A. W. Heemink ◽  
S. Lu ◽  
A. J. Segers ◽  
K. Weber ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Transport Model ◽  
Real Life ◽  
Forecast Accuracy ◽  
In Situ Measurements ◽  
North West ◽  
The North ◽  
Ash Plume ◽  
Potential Improvement

Abstract. The forecast accuracy of distal volcanic ash clouds is important for providing valid aviation advice during volcanic ash eruption. However, because the distal part of volcanic ash plume is far from the volcano, the influence of eruption information on this part becomes rather indirect and uncertain, resulting in inaccurate volcanic ash forecasts in these distal areas. In our approach, we use real-life aircraft in-situ observations, measured in the North-West part of Germany during the 2010 Eyjafjallajokull eruption, in an ensemble-based data assimilation system combined with a volcanic ash transport model to investigate the potential improvement on the forecast accuracy with regard to the distal volcanic ash plume. We show that the error of the analyzed volcanic ash state can be significantly reduced through assimilating real-life in-situ measurements. After a continuous assimilation, it is shown that the aviation advice for Germany, the Netherlands and Belgium can be significantly improved. We suggest that with suitable aircrafts measuring once per day across the distal volcanic ash plume, the description and prediction of volcanic ash clouds in these areas can be greatly improved.

The Carbon:²³⁴Thorium ratios of sinking particles in the California Current Ecosystem 2: Examination of a thorium sorption, desorption, and particle transport model

2019 ◽  
Author(s):  
Michael Stukel ◽  
Thomas Kelly
Keyword(s):  
Organic Carbon ◽  
Water Column ◽  
Particulate Organic Carbon ◽  
Transport Model ◽  
California Current ◽  
In Situ Measurements ◽  
Power Law Distribution ◽  
Sinking Particles ◽  
Organic Carbon Concentration

Thorium-234 (234Th) is a powerful tracer of particle dynamics and the biological pump in the surface ocean; however, variability in carbon:thorium ratios of sinking particles adds substantial uncertainty to estimates of organic carbon export. We coupled a mechanistic thorium sorption and desorption model to a one-dimensional particle sinking model that uses realistic particle settling velocity spectra. The model generates estimates of 238U-234Th disequilibrium, particulate organic carbon concentration, and the C:234Th ratio of sinking particles, which are then compared to in situ measurements from quasi-Lagrangian studies conducted on six cruises in the California Current Ecosystem. Broad patterns observed in in situ measurements, including decreasing C:234Th ratios with depth and a strong correlation between sinking C:234Th and the ratio of vertically-integrated particulate organic carbon (POC) to vertically-integrated total water column 234Th, were accurately recovered by models assuming either a power law distribution of sinking speeds or a double log normal distribution of sinking speeds. Simulations suggested that the observed decrease in C:234Th with depth may be driven by preferential remineralization of carbon by particle-attached microbes. However, an alternate model structure featuring complete consumption and/or disaggregation of particles by mesozooplankton (e.g. no preferential remineralization of carbon) was also able to simulate decreasing C:234Th with depth (although the decrease was weaker), driven by 234Th adsorption onto slowly sinking particles. Model results also suggest that during bloom decays C:234Th ratios of sinking particles should be higher than expected (based on contemporaneous water column POC), because high settling velocities minimize carbon remineralization during sinking.

scholarly journals Data assimilation for volcanic ash plumes using a satellite observational operator: a case study on the 2010 Eyjafjallajökull volcanic eruption

2017 ◽  
Vol 17 (2) ◽  
pp. 1187-1205 ◽  
Author(s):  
Guangliang Fu ◽  
Fred Prata ◽  
Hai Xiang Lin ◽  
Arnold Heemink ◽  
Arjo Segers ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Volcanic Ash ◽  
Three Dimensional ◽  
Forecast Accuracy ◽  
Improve Model ◽  
Powerful Approach ◽  
Using Data ◽  
D Model

Abstract. Using data assimilation (DA) to improve model forecast accuracy is a powerful approach that requires available observations. Infrared satellite measurements of volcanic ash mass loadings are often used as input observations for the assimilation scheme. However, because these primary satellite-retrieved data are often two-dimensional (2-D) and the ash plume is usually vertically located in a narrow band, directly assimilating the 2-D ash mass loadings in a three-dimensional (3-D) volcanic ash model (with an integral observational operator) can usually introduce large artificial/spurious vertical correlations.In this study, we look at an approach to avoid the artificial vertical correlations by not involving the integral operator. By integrating available data of ash mass loadings and cloud top heights, as well as data-based assumptions on thickness, we propose a satellite observational operator (SOO) that translates satellite-retrieved 2-D volcanic ash mass loadings to 3-D concentrations. The 3-D SOO makes the analysis step of assimilation comparable in the 3-D model space.Ensemble-based DA is used to assimilate the extracted measurements of ash concentrations. The results show that satellite DA with SOO can improve the estimate of volcanic ash state and the forecast. Comparison with both satellite-retrieved data and aircraft in situ measurements shows that the effective duration of the improved volcanic ash forecasts for the distal part of the Eyjafjallajökull volcano is about 6 h.

scholarly journals Novel statistical emulator construction for volcanic ash transport model Ash3d with physically motivated measures

2020 ◽  
Vol 476 (2242) ◽  
pp. 20200161
Author(s):  
Qingyuan Yang ◽  
E. Bruce Pitman ◽  
Elaine Spiller ◽  
Marcus Bursik ◽  
Andrea Bevilacqua
Keyword(s):  
Wind Field ◽  
Volcanic Ash ◽  
Transport Model ◽  
Initial Conditions ◽  
Hazard Analysis ◽  
Construction Simulation ◽  
Transport Models ◽  
Physical Knowledge ◽  
Geophysical Processes ◽  
Ash Transport

Statistical emulators are a key tool for rapidly producing probabilistic hazard analysis of geophysical processes. Given output data computed for a relatively small number of parameter inputs, an emulator interpolates the data, providing the expected value of the output at untried inputs and an estimate of error at that point. In this work, we propose to fit Gaussian Process emulators to the output from a volcanic ash transport model, Ash3d. Our goal is to predict the simulated volcanic ash thickness from Ash3d at a location of interest using the emulator. Our approach is motivated by two challenges to fitting emulators—characterizing the input wind field and interactions between that wind field and variable grain sizes. We resolve these challenges by using physical knowledge on tephra dispersal. We propose new physically motivated variables as inputs and use normalized output as the response for fitting the emulator. Subsetting based on the initial conditions is also critical in our emulator construction. Simulation studies characterize the accuracy and efficiency of our emulator construction and also reveal its current limitations. Our work represents the first emulator construction for volcanic ash transport models with considerations of the simulated physical process.

scholarly journals Retrieval of total column and surface NO<sub>2</sub> from Pandora zenith-sky measurements

2019 ◽  
Author(s):  
Xiaoyi Zhao ◽  
Debora Griffin ◽  
Vitali Fioletov ◽  
Chris McLinden ◽  
Jonathan Davies ◽  
...  
Keyword(s):  
Transport Model ◽  
Surface Concentration ◽  
In Situ Measurements ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Chemical Transport Model ◽  
High Quality ◽  
Vertical Column

Abstract. Pandora spectrometers can retrieve nitrogen dioxide (NO2) vertical column densities (VCDs) via two viewing geometries: direct-sun and zenith-sky. The direct-sun NO2 VCD measurements have high quality (0.1 DU accuracy in clear-sky conditions) and do not rely on any radiative transfer model to calculate air mass factors (AMFs); however, they are not available when the sun is obscured by clouds. To perform NO2 measurements in cloudy conditions, a simple but robust NO2 retrieval algorithm is developed for Pandora zenith-sky measurements. This algorithm derives empirical zenith-sky NO2 AMFs from coincident high-quality direct-sun NO2 observations. Moreover, the retrieved Pandora zenith-sky NO2 VCD data are converted to surface NO2 concentrations with a scaling algorithm that uses chemical-transport-model predictions and satellite measurements as inputs. NO2 VCDs and surface concentrations are retrieved from Pandora zenith-sky measurements made in Toronto, Canada, from 2015 to 2017. The retrieved Pandora zenith-sky NO2 data (VCD and surface concentration) show good agreement with both satellite and in situ measurements. The diurnal and seasonal variations of derived Pandora zenith-sky surface NO2 data also agree well with in situ measurements (diurnal difference within ±2 ppbv). Overall, this work shows that the new Pandora zenith-sky NO2 products have the potential to be used in various applications such as future satellite validation in moderate cloudy scenes and air quality monitoring.

scholarly journals Simulating Secondary Inorganic Aerosols using the chemistry transport model MOCAGE version R2.15.0

2015 ◽  
Vol 8 (4) ◽  
pp. 3593-3651 ◽  
Author(s):  
J. Guth ◽  
B. Josse ◽  
V. Marécal ◽  
M. Joly
Keyword(s):  
North America ◽  
Transport Model ◽  
Regional Scale ◽  
In Situ Measurements ◽  
Aerosol Composition ◽  
Chemistry Transport Model ◽  
Inorganic Aerosols ◽  
Modis Aod ◽  
Inorganic Aerosol

Abstract. In this study we develop a Secondary Inorganic Aerosol (SIA) module for the chemistry transport model MOCAGE developed at CNRM. Based on the thermodynamic equilibrium module ISORROPIA II, the new version of the model is evaluated both at the global scale and at the regional scale. The results show high concentrations of secondary inorganic aerosols in the most polluted regions being Europe, Asia and the eastern part of North America. Asia shows higher sulfate concentrations than other regions thanks to emissions reduction in Europe and North America. Using two simulations, one with and the other without secondary inorganic aerosol formation, the model global outputs are compared to previous studies, to MODIS AOD retrievals, and also to in situ measurements from the HTAP database. The model shows a better agreement in all geographical regions with MODIS AOD retrievals when introducing SIA. It also provides a good statistical agreement with in situ measurements of secondary inorganic aerosol composition: sulfate, nitrate and ammonium. In addition, the simulation with SIA gives generally a better agreement for secondary inorganic aerosols precursors (nitric acid, sulfur dioxide, ammonia) in particular with a reduction of the Modified Normalised Mean Bias (MNMB). At the regional scale, over Europe, the model simulation with SIA are compared to the in situ measurements from the EMEP database and shows a good agreement with secondary inorganic aerosol composition. The results at the regional scale are consistent with those obtained with the global simulations. The AIRBASE database was used to compare the model to regulated air quality pollutants being particulate matter, ozone and nitrogen dioxide concentrations. The introduction of the SIA in MOCAGE provides a reduction of the PM2.5 MNMB of 0.44 on a yearly basis and even 0.52 on a three spring months period (March, April, May) when SIA are maximum.

scholarly journals Ozone pollution during the COVID-19 lockdown in the spring 2020 over Europe analysed from satellite observations, in situ measurements and models

2021 ◽  
Author(s):  
Juan Cuesta ◽  
Lorenzo Costantino ◽  
Matthias Beekmann ◽  
Guillaume Siour ◽  
Laurent Menut ◽  
...  
Keyword(s):  
Large Scale ◽  
Transport Model ◽  
Surface Ozone ◽  
In Situ Measurements ◽  
Satellite Observations ◽  
Emission Inventories ◽  
Ozone Pollution ◽  
Chemistry Transport Model ◽  
Near Surface

Abstract. We present a comprehensive study integrating satellite observations of ozone pollution, in situ measurements and chemistry transport model simulations for quantifying the role of anthropogenic emission reductions during the COVID-19 lockdown in spring 2020 over Europe. Satellite observations are derived from the IASI+GOME2 multispectral synergism, which provides particularly enhanced sensitivity to near-surface ozone pollution. These observations are first analysed in terms of differences between the average on 1–15 April 2020, when the strictest lockdown restrictions took place, and the same period in 2019. They show clear enhancements of near-surface ozone in Central Europe and Northern Italy, and some other hotspots, which are typically characterized by VOC-limited chemical regimes. An overall reduction of ozone is observed elsewhere, where ozone chemistry is limited by the abundance of NOx. The spatial distribution of positive and negative ozone concentration anomalies observed from space is in relatively good quantitative agreement with surface in situ measurements over the continent (a correlation coefficient of 0.55, a root-mean-squared difference of 11 ppb and the same standard deviation and range of variability). An average bias of ∼8 ppb between the two observational datasets is remarked, which can partly be explained by the fact the satellite approach retrieves partial columns of ozone with a peak sensitivity above the surface (near 2 km of altitude). For assessing the impact of the reduction of anthropogenic emissions during the lockdown, we adjust the satellite and in situ surface observations for withdrawing the influence of meteorological conditions in 2020 and 2019. This adjustment is derived from the chemistry transport model simulations using the meteorological fields of each year and identical emission inventories. This observational estimate of the influence of lockdown emission reduction is consistent for both datasets. They both show lockdown-associated ozone enhancements in hotspots over Central Europe and Northern Italy, with a reduced amplitude with respect to the total changes observed between the two years, and an overall reduction elsewhere over Europe and the ocean. Satellite observations additionally highlight the ozone anomalies in the regions remote from in situ sensors, an enhancement over the Mediterranean likely associated with maritime traffic emissions and a marked large-scale reduction of ozone elsewhere over ocean (particularly over the North Sea), in consistency with previous assessments done with ozonesondes measurements in the free troposphere. These observational assessments are compared with model-only estimations, using the CHIMERE chemistry transport model. For analysing the uncertainty of the model estimates, we perform two sets of simulations with different setups, differing in the emission inventories, their modifications to account for changes in anthropogenic activities during the lockdown and the meteorological fields. Whereas a general qualitative consistency of positive and negative ozone anomalies is remarked between all model and observational estimates, significant changes are seen in their amplitudes. Models underestimate the range of variability of the ozone changes by at least a factor 2 with respect to the two observational data sets, both for enhancements and decreases of ozone, while the large-scale ozone decrease is not simulated. With one of the setups, the model simulates ozone enhancements a factor 3 to 6 smaller than with the other configuration. This is partly linked to the emission inventories of ozone precursors (at least a 30 % difference), but mainly to differences in vertical mixing of atmospheric constituents depending on the choice of the meteorological model.

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