scholarly journals Performance assessment of a volcanic ash transport model mini-ensemble used for inverse modeling of the 2010 Eyjafjallajökull eruption

2012 ◽  
Vol 117 (D20) ◽  
Author(s):  
N. I. Kristiansen ◽  
A. Stohl ◽  
A. J. Prata ◽  
N. Bukowiecki ◽  
H. Dacre ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Inverse Modeling ◽  
Volcanic Ash ◽  
Transport Model ◽  
Ash Transport

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 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.

A volcanic ash transport model and analysis of Mount St. Helens ashfall

1985 ◽  
Vol 90 (D6) ◽  
pp. 10620-10630 ◽  
Author(s):  
Arthur T. Hopkins ◽  
Charles J. Bridgman
Keyword(s):  
Volcanic Ash ◽  
Transport Model ◽  
Mount St Helens ◽  
Ash Transport

scholarly journals Estimation of Volcanic Ash Emissions Using Trajectory-Based 4D-Var Data Assimilation

2016 ◽  
Vol 144 (2) ◽  
pp. 575-589 ◽  
Author(s):  
S. Lu ◽  
H. X. Lin ◽  
A. W. Heemink ◽  
G. Fu ◽  
A. J. Segers
Keyword(s):  
Data Assimilation ◽  
Vertical Distribution ◽  
Volcanic Ash ◽  
Transport Model ◽  
Volcanic Eruptions ◽  
Emission Rates ◽  
Plume Height ◽  
Ill Posed ◽  
Total Difference ◽  
The Vertical Distribution

Abstract Volcanic ash forecasting is a crucial tool in hazard assessment and operational volcano monitoring. Emission parameters such as plume height, total emission mass, and vertical distribution of the emission plume rate are essential and important in the implementation of volcanic ash models. Therefore, estimation of emission parameters using available observations through data assimilation could help to increase the accuracy of forecasts and provide reliable advisory information. This paper focuses on the use of satellite total-ash-column data in 4D-Var based assimilations. Experiments show that it is very difficult to estimate the vertical distribution of effective volcanic ash injection rates from satellite-observed ash columns using a standard 4D-Var assimilation approach. This paper addresses the ill-posed nature of the assimilation problem from the perspective of a spurious relationship. To reduce the influence of a spurious relationship created by a radiate observation operator, an adjoint-free trajectory-based 4D-Var assimilation method is proposed, which is more accurate to estimate the vertical profile of volcanic ash from volcanic eruptions. The method seeks the optimal vertical distribution of emission rates of a reformulated cost function that computes the total difference between simulated and observed ash columns. A 3D simplified aerosol transport model and synthetic satellite observations are used to compare the results of both the standard method and the new method.

scholarly journals Analysis of the ETNA 2015 Eruption Using WRF–Chem Model and Satellite Observations

Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1168
Author(s):  
Umberto Rizza ◽  
Eleonora Brega ◽  
Maria Teresa Caccamo ◽  
Giuseppe Castorina ◽  
Mauro Morichetti ◽  
...  
Keyword(s):  
Volcanic Eruption ◽  
Volcanic Ash ◽  
Mediterranean Area ◽  
Satellite Observations ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Airport Management ◽  
Local Stakeholders ◽  
Satellite Sensors ◽  
Ash Transport

The aim of the present work is to utilize a new functionality within the Weather Research and Forecasting model coupled with Chemistry (WRF–Chem) that allows simulating emission, transport, and settling of pollutants released during the Etna 2015 volcanic activities. This study constitutes the first systematic application of the WRF–Chem online-based approach to a specific Etna volcanic eruption, with possible effects involving the whole Mediterranean area. In this context, the attention has been focused on the eruption event, recorded from 3–7 December 2015, which led to the closure of the nearby Catania International Airport. Quantitative meteorological forecasts, analyses of Etna volcanic ash transport, and estimates of the ash ground deposition have been performed. In order to test the performance of the proposed approach, the model outputs have been compared with data provided by satellite sensors and Doppler radars. As a result, it emerges that, as far as the selected eruption event is concerned, the WRF–Chem model reasonably reproduces the distribution of SO2 and of volcanic ash. In addition, this modeling system may provide valuable support both to airport management and to local stakeholders including public administrations.

scholarly journals Error correlation between CO<sub>2</sub> and CO as constraint for CO<sub>2</sub> flux inversions using satellite data

2009 ◽  
Vol 9 (19) ◽  
pp. 7313-7323 ◽  
Author(s):  
H. Wang ◽  
D. J. Jacob ◽  
M. Kopacz ◽  
D. B. A. Jones ◽  
P. Suntharalingam ◽  
...  
Keyword(s):  
Inverse Modeling ◽  
Large Scale ◽  
Transport Model ◽  
Meteorological Data ◽  
Correlation Coefficients ◽  
Surface Fluxes ◽  
Satellite Observations ◽  
Carbon Surface ◽  
Chemical Transport Model ◽  
Error Correlation

Abstract. Inverse modeling of CO2 satellite observations to better quantify carbon surface fluxes requires a chemical transport model (CTM) to relate the fluxes to the observed column concentrations. CTM transport error is a major source of uncertainty. We show that its effect can be reduced by using CO satellite observations as additional constraint in a joint CO2-CO inversion. CO is measured from space with high precision, is strongly correlated with CO2, and is more sensitive than CO2 to CTM transport errors on synoptic and smaller scales. Exploiting this constraint requires statistics for the CTM transport error correlation between CO2 and CO, which is significantly different from the correlation between the concentrations themselves. We estimate the error correlation globally and for different seasons by a paired-model method (comparing GEOS-Chem CTM simulations of CO2 and CO columns using different assimilated meteorological data sets for the same meteorological year) and a paired-forecast method (comparing 48- vs. 24-h GEOS-5 CTM forecasts of CO2 and CO columns for the same forecast time). We find strong error correlations (r2>0.5) between CO2 and CO columns over much of the extra-tropical Northern Hemisphere throughout the year, and strong consistency between different methods to estimate the error correlation. Application of the averaging kernels used in the retrieval for thermal IR CO measurements weakens the correlation coefficients by 15% on average (mostly due to variability in the averaging kernels) but preserves the large-scale correlation structure. We present a simple inverse modeling application to demonstrate that CO2-CO error correlations can indeed significantly reduce uncertainty on surface carbon fluxes in a joint CO2-CO inversion vs. a CO2-only inversion.

scholarly journals Operational Modelling of Umbrella Cloud Growth in a Lagrangian Volcanic Ash Transport and Dispersion Model

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 200 ◽  
Author(s):  
Helen N. Webster ◽  
Benjamin J. Devenish ◽  
Larry G. Mastin ◽  
David J. Thomson ◽  
Alexa R. Van Eaton
Keyword(s):  
Flow Rate ◽  
Volcanic Ash ◽  
Dispersion Model ◽  
Volume Flow Rate ◽  
Gravity Current ◽  
Volume Flow ◽  
Lateral Spread ◽  
Lagrangian Model ◽  
Model Predictions ◽  
Ash Transport

Large explosive eruptions can result in the formation of an umbrella cloud which rapidly expands, spreading ash out radially from the volcano. The lateral spread by the intrusive gravity current dominates the transport of the ash cloud. Hence, to accurately forecast the transport of ash from large eruptions, lateral spread of umbrella clouds needs to be represented within volcanic ash transport and dispersion models. Here, we describe an umbrella cloud parameterisation which has been implemented into an operational Lagrangian model and consider how it may be used during an eruption when information concerning the eruption is limited and model runtime is key. We examine different relations for the volume flow rate into the umbrella, and the rate of spreading within the cloud. The scheme is validated against historic eruptions of differing scales (Pinatubo 1991, Kelud 2014, Calbuco 2015 and Eyjafjallajökull 2010) by comparing model predictions with satellite observations. Reasonable predictions of umbrella cloud spread are achieved using an estimated volume flow rate from the empirical equation by Bursik et al. and the observed eruption height. We show how model predictions can be refined during an ongoing eruption as further information and observations become available.

scholarly journals Volcanic ash modeling with the online NMMB-MONARCH-ASH v1.0 model: model description, case simulation, and evaluation

2017 ◽  
Vol 17 (6) ◽  
pp. 4005-4030 ◽  
Author(s):  
Alejandro Marti ◽  
Arnau Folch ◽  
Oriol Jorba ◽  
Zavisa Janjic
Keyword(s):  
Volcanic Ash ◽  
Prediction Models ◽  
Transport Model ◽  
Weather Prediction ◽  
Mount Etna ◽  
Model Description ◽  
Tephra Dispersal ◽  
Coupling Strategy ◽  
Simulation And Evaluation ◽  
Ash Cloud

Abstract. Traditionally, tephra transport and dispersal models have evolved decoupled (offline) from numerical weather prediction models. There is a concern that inconsistencies and shortcomings associated with this coupling strategy might lead to errors in the ash cloud forecast. Despite this concern and the significant progress in improving the accuracy of tephra dispersal models in the aftermath of the 2010 Eyjafjallajökull and 2011 Cordón Caulle eruptions, to date, no operational online dispersal model is available to forecast volcanic ash. Here, we describe and evaluate NMMB-MONARCH-ASH, a new online multi-scale meteorological and transport model that attempts to pioneer the forecast of volcanic aerosols at operational level. The model forecasts volcanic ash cloud trajectories, concentration of ash at relevant flight levels, and the expected deposit thickness for both regional and global configurations. Its online coupling approach improves the current state-of-the-art tephra dispersal models, especially in situations where meteorological conditions are changing rapidly in time, two-way feedbacks are significant, or distal ash cloud dispersal simulations are required. This work presents the model application for the first phases of the 2011 Cordón Caulle and 2001 Mount Etna eruptions. The computational efficiency of NMMB-MONARCH-ASH and its application results compare favorably with other long-range tephra dispersal models, supporting its operational implementation.

scholarly journals Importance of fossil fuel emission uncertainties over Europe for CO<sub>2</sub> modeling: model intercomparison

2011 ◽  
Vol 11 (13) ◽  
pp. 6607-6622 ◽  
Author(s):  
P. Peylin ◽  
S. Houweling ◽  
M. C. Krol ◽  
U. Karstens ◽  
C. Rödenbeck ◽  
...  
Keyword(s):  
Inverse Modeling ◽  
Fossil Fuel ◽  
Transport Model ◽  
Carbon Sink ◽  
Temporal Distribution ◽  
Co2 Concentration ◽  
Emission Inventories ◽  
Transport Models ◽  
Diurnal Cycles ◽  
Fossil Fuel Emission

Abstract. Inverse modeling techniques used to quantify surface carbon fluxes commonly assume that the uncertainty of fossil fuel CO2 (FFCO2) emissions is negligible and that intra-annual variations can be neglected. To investigate these assumptions, we analyzed the differences between four fossil fuel emission inventories with spatial and temporal differences over Europe and their impact on the model simulated CO2 concentration. Large temporal flux variations characterize the hourly fields (~40 % and ~80 % for the seasonal and diurnal cycles, peak-to-peak) and annual country totals differ by 10 % on average and up to 40 % for some countries (i.e., the Netherlands). These emissions have been prescribed to seven different transport models, resulting in 28 different FFCO2 concentrations fields. The modeled FFCO2 concentration time series at surface sites using time-varying emissions show larger seasonal cycles (+2 ppm at the Hungarian tall tower (HUN)) and smaller diurnal cycles in summer (−1 ppm at HUN) than when using constant emissions. The concentration range spanned by all simulations varies between stations, and is generally larger in winter (up to ~10 ppm peak-to-peak at HUN) than in summer (~5 ppm). The contribution of transport model differences to the simulated concentration std-dev is 2–3 times larger than the contribution of emission differences only, at typical European sites used in global inversions. These contributions to the hourly (monthly) std-dev's amount to ~1.2 (0.8) ppm and ~0.4 (0.3) ppm for transport and emissions, respectively. First comparisons of the modeled concentrations with 14C-based fossil fuel CO2 observations show that the large transport differences still hamper a quantitative evaluation/validation of the emission inventories. Changes in the estimated monthly biosphere flux (Fbio) over Europe, using two inverse modeling approaches, are relatively small (less that 5 %) while changes in annual Fbio (up to ~0.15 % GtC yr−1) are only slightly smaller than the differences in annual emission totals and around 30 % of the mean European ecosystem carbon sink. These results point to an urgent need to improve not only the transport models but also the assumed spatial and temporal distribution of fossil fuel emission inventories.

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