Ensemble-based data assimilation of volcanic aerosols using FALL3D+PDAF

2021 ◽  
Author(s):  
Leonardo Mingari ◽  
Andrew Prata ◽  
Federica Pardini
Keyword(s):  
Data Assimilation ◽  
Information Transfer ◽  
High Performance ◽  
Volcanic Ash ◽  
Numerical Models ◽  
Volcanic Eruptions ◽  
Column Height ◽  
Eruption Column ◽  
Operational Environment ◽  
Assimilation System

<p>Modelling atmospheric dispersion and deposition of volcanic ash is becoming increasingly valuable for understanding the potential impacts of explosive volcanic eruptions on infrastructures, air quality and aviation. The generation of high-resolution forecasts depends on the accuracy and reliability of the input data for models. Uncertainties in key parameters such as eruption column height injection, physical properties of particles or meteorological fields, represent a major source of error in forecasting airborne volcanic ash. The availability of nearly real time geostationary satellite observations with high spatial and temporal resolutions provides the opportunity to improve forecasts in an operational context. Data assimilation (DA) is one of the most effective ways to reduce the error associated with the forecasts through the incorporation of available observations into numerical models. Here we present a new implementation of an ensemble-based data assimilation system based on the coupling between the FALL3D dispersal model and the Parallel Data Assimilation Framework (PDAF). The implementation is based on the last version release of FALL3D (versions 8.x) tailored to the extreme-scale computing requirements, which has been redesigned and rewritten from scratch in the framework of the EU Center of Excellence for Exascale in Solid Earth (ChEESE). The proposed methodology can be efficiently implemented in an operational environment by exploiting high-performance computing (HPC) resources. The FALL3D+PDAF system can be run in parallel and supports online-coupled DA, which allows an efficient information transfer through parallel communication. Satellite-retrieved data from recent volcanic eruptions were considered as input observations for the assimilation system.</p>

scholarly journals Data Assimilation of Volcanic Aerosols using FALL3D+PDAF

2021 ◽  
Author(s):  
Leonardo Mingari ◽  
Arnau Folch ◽  
Andrew T. Prata ◽  
Federica Pardini ◽  
Giovanni Macedonio ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Volcanic Ash ◽  
Volcanic Eruptions ◽  
Column Height ◽  
Model Parameters ◽  
Eruption Column ◽  
Mass Loading ◽  
Multiple Model ◽  
Volcanic Aerosols ◽  
Forecast Quality

Abstract. Modelling atmospheric dispersal of volcanic ash and aerosols is becoming increasingly valuable for assessing the potential impacts of explosive volcanic eruptions on infrastructures, air quality, and aviation. Management of volcanic risk and reduction of aviation impacts can strongly benefit from quantitative forecasting of volcanic ash. However, an accurate prediction of volcanic aerosol concentrations using numerical modelling relies on proper estimations of multiple model parameters which are prone to errors. Uncertainties in key parameters such as eruption column height, physical properties of particles or meteorological fields, represent a major source of error affecting the forecast quality. The availability of near-real-time geostationary satellite observations with high spatial and temporal resolutions provides the opportunity to improve forecasts in an operational context by incorporating observations into numerical models. Specifically, ensemble-based filters aim at converting a prior ensemble of system states into an analysis ensemble by assimilating a set of noisy observations. Previous studies dealing with volcanic ash transport have demonstrated that a significant improvement of forecast skill can be achieved by this approach. In this work, we present a new implementation of an ensemble-based Data Assimilation (DA) method coupling the FALL3D dispersal model and the Parallel Data Assimilation Framework (PDAF). The FALL3D+PDAF system runs in parallel, supports online-coupled DA and can be efficiently integrated into operational workflows by exploiting high-performance computing (HPC) resources. Two numerical experiments are considered: (i) a twin experiment using an incomplete dataset of synthetic observations of volcanic ash and, (ii) an experiment based on the 2019 Raikoke eruption using real observations of SO2 mass loading. An ensemble-based Kalman filtering technique based on the Local Ensemble Transform Kalman Filter (LETKF) is used to assimilate satellite-retrieved data of column mass loading. We show that this procedure may lead to nonphysical solutions and, consequently, conclude that LETKF is not the best approach for the assimilation of volcanic aerosols. However, we find that a truncated state constructed from the LETKF solution approaches the real solution after a few assimilation cycles, yielding a dramatic improvement of forecast quality when compared to simulations without assimilation.

Ensemble-Based Data Assimilation of volcanic ash clouds from satellite observations: application to the 24 December 2018 Mt.Etna explosive eruption.

2021 ◽  
Author(s):  
Federica Pardini ◽  
Stefano Corradini ◽  
Antonio Costa ◽  
Lorenzo Guerrieri ◽  
Tomaso Esposti Ongaro ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Kalman Filters ◽  
Volcanic Ash ◽  
Explosive Eruption ◽  
Numerical Models ◽  
Numerical Procedure ◽  
Optimal Solution ◽  
Volcanic Eruptions ◽  
Satellite Observations ◽  
Mt Etna

<p>Explosive volcanic eruptions release high amounts of ash into the atmosphere. Accurate tracking and forecasting of ash dispersal into the atmosphere and quantification of its uncertainty is of fundamental importance for volcanic hazard mitigation. Numerical models represent a powerful tool to monitor ash clouds in real-time, but limits and uncertainties affect numerical results. A way to improve numerical forecasts is by assimilating satellite observations of ash clouds through Data Assimilation algorithms, such as Ensemble-based Kalman Filters. In this study, we present the implementation of the so-called Local Ensemble Transform Kalman Filters inside a numerical procedure which simulates the release and transport of volcanic ash during explosive eruptions. The numerical procedure consists of the eruptive column model PLUME-MoM coupled with the tephra transport and dispersal model HYSPLIT. When satellite observations are available, ash maps supplied by PLUME-MoM/HYSPLIT are sequentially corrected/modified using ash column loading as retrieved from space. The new volcanic ash state represents the optimal solution with minimized uncertainties with respect to numerical estimates and observations. To test the Data Assimilation procedure, we used satellite observations of the volcanic cloud released during the explosive eruption that occurred at Mt. Etna (Italy) on 24 December 2018. Satellite observations have been carried out by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument, on board the Meteosat Second Generation (MSG) geostationary satellite. Results show that the assimilation procedure significantly improves the current ash state and the forecast. In addition, numerical tests show that the use of sequential Kalman Filters does not require a precise initialization of the numerical model, being able to improve the forecasts as the assimilation cycles are performed.</p>

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.

Calculating and communicating ensemble-based volcanic ash concentration risk for aviation

2021 ◽  
Author(s):  
Natalie Harvey ◽  
Helen Dacre ◽  
Antonio Capponi
Keyword(s):  
Volcanic Ash ◽  
Numerical Models ◽  
Volcanic Eruptions ◽  
Risk Level ◽  
Aircraft Icing ◽  
Risk Matrix ◽  
High Concentration ◽  
Forecast Lead Time ◽  
Aviation Hazards ◽  
Robust Decisions

<p>During volcanic eruptions Volcanic Ash Advisory Centers (VAAC) produce forecasts of ash location and concentration. However, these forecasts are deterministic and do not take into account the inherent uncertainty in the forecasts due to incomplete knowledge of the volcano’s eruption characteristics and imperfect representation of atmospheric processes in numerical models. This means flight operators have incomplete information regarding the risk of flying following an eruption, which could result in overly conservative decisions being made. There is a need for a new generation of volcanic ash hazard charts allowing end users to make fast and robust decisions using risk estimates based on  state-of-the-art probabilistic forecast methods .</p><p> </p><p>In this presentation, a method for visualizing ash concentration matrix using a risk-matrix approach will be applied to two volcanic eruptions, Grimsvotn (2011) and Raikoke (2019). These risk-matrix graphics reduce the ensemble information into an easy-to-use decision-making tool. In this work the risk level is determined by combining the concentration of volcanic ash and the likelihood of that concentration occurring.</p><p> </p><p>When applying this technique to the Grimsvotn eruption, the airspace containing volcanic ash concentrations deemed to be associated with the highest risk (high likelihood of exceeding a high concentration threshold) to aviation are reduced by over 85% compared to using an ensemble that gives an ash distribution similar to the VAAC issued deterministic forecast. The reduction during the Raikoke eruption can be as much as 40% at a forecast lead time of 48 hours. This has the potential to reduce the disruption to airline operations.  This tool could be extended to include other aviation hazards, such as desert dust, aircraft icing and clear air turbulence.</p><p> </p>

scholarly journals Spectral Transformation Using a Cubed-Sphere Grid for a Three-Dimensional Variational Data Assimilation System

2015 ◽  
Vol 143 (7) ◽  
pp. 2581-2599 ◽  
Author(s):  
Hyo-Jong Song ◽  
In-Hyuk Kwon
Keyword(s):  
Data Assimilation ◽  
Numerical Models ◽  
Three Dimensional ◽  
Spectral Element ◽  
Variational Data Assimilation ◽  
Specific Humidity ◽  
Spectral Transformation ◽  
Cubed Sphere ◽  
Data Assimilation System ◽  
Assimilation System

Abstract Atmospheric numerical models using the spectral element method with cubed-sphere grids (CSGs) are highly scalable in terms of parallelization. However, there are no data assimilation systems for spectral element numerical models. The authors devised a spectral transformation method applicable to the model data on a CSG (STCS) for a three-dimensional variational data assimilation system (3DVAR). To evaluate the 3DVAR system based on the STCS, the authors conducted observing system simulation experiments (OSSEs) using Community Atmosphere Model with Spectral Element dynamical core (CAM-SE). They observed root-mean-squared error reductions: 24% and 34% for zonal and meridional winds (U and V), respectively; 20% for temperature (T); 4% for specific humidity (Q); and 57% for surface pressure (Ps) in analysis and 28% and 27% for U and V, respectively; 25% for T; 21% for Q; and 31% for Ps in 72-h forecast fields. In this paper, under the premise that the same number of grid points is set, the authors show that the use of a greater polynomial degree, np, produces better performance than use of a greater element count, ne, on equiangular coordinates in terms of the wave representation.

scholarly journals Atmospheric processes affecting the separation of volcanic ash and SO<sub>2</sub> in volcanic eruptions: inferences from the May 2011 Grímsvötn eruption

2017 ◽  
Vol 17 (17) ◽  
pp. 10709-10732 ◽  
Author(s):  
Fred Prata ◽  
Mark Woodhouse ◽  
Herbert E. Huppert ◽  
Andrew Prata ◽  
Thor Thordarson ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Early Stage ◽  
Volcanic Eruptions ◽  
Radiation Balance ◽  
Eruption Column ◽  
Density Currents ◽  
Volcanic Emissions ◽  
Main Column ◽  
The Masses ◽  
High Level

Abstract. The separation of volcanic ash and sulfur dioxide (SO2) gas is sometimes observed during volcanic eruptions. The exact conditions under which separation occurs are not fully understood but the phenomenon is of importance because of the effects volcanic emissions have on aviation, on the environment, and on the earth's radiation balance. The eruption of Grímsvötn, a subglacial volcano under the Vatnajökull glacier in Iceland during 21–28 May 2011 produced one of the most spectacular examples of ash and SO2 separation, which led to errors in the forecasting of ash in the atmosphere over northern Europe. Satellite data from several sources coupled with meteorological wind data and photographic evidence suggest that the eruption column was unable to sustain itself, resulting in a large deposition of ash, which left a low-level ash-rich atmospheric plume moving southwards and then eastwards towards the southern Scandinavian coast and a high-level predominantly SO2 plume travelling northwards and then spreading eastwards and westwards. Here we provide observational and modelling perspectives on the separation of ash and SO2 and present quantitative estimates of the masses of ash and SO2 that erupted, the directions of transport, and the likely impacts. We hypothesise that a partial column collapse or sloughing fed with ash from pyroclastic density currents (PDCs) occurred during the early stage of the eruption, leading to an ash-laden gravity intrusion that was swept southwards, separated from the main column. Our model suggests that water-mediated aggregation caused enhanced ash removal because of the plentiful supply of source water from melted glacial ice and from entrained atmospheric water. The analysis also suggests that ash and SO2 should be treated with separate source terms, leading to improvements in forecasting the movement of both types of emissions.

scholarly journals Past 220 year bipolar volcanic signals: remarks on common features of their source volcanic eruptions

2002 ◽  
Vol 35 ◽  
pp. 217-223 ◽  
Author(s):  
Mika Kohno ◽  
Yoshiyuki Fujii
Keyword(s):  
Ice Sheets ◽  
Ice Cores ◽  
Background Level ◽  
Volcanic Eruptions ◽  
Column Height ◽  
Eruption Column ◽  
Low Latitudes ◽  
Explosive Volcanic Eruptions ◽  
The Antarctic ◽  
Santa Maria

AbstractDuring the past 220 years, prominent signals of non-sea salt sulfate ion (nssSO42–) concentration exceeding the background level, including both marine biogenic and anthropogenic SO42–, were found in shallow ice cores from site H15 in East Antarctica and Site-J in southern Greenland. They were mostly correlated with past explosive volcanic eruptions. on the basis of this result and published results of shallow ice cores and snow pits at various locations on the Antarctic and Greenland ice sheets, eight common signals were found, of which six were assigned to the following explosive eruptions: El Chichόn, Mexico, in 1982; Agung, Indonesia, in 1963; Santa Maria, Guatemala, in 1902; Krakatau, Indonesia, in 1883; Cosiguina, Nicaragua, in 1835; an unknown volcano between 1831 and 1834; Tambora, Indonesia, in 1815; and an unknown volcano in 1809. Volcanic eruptions which have a potential to imprint their signals in both the Antarctic and Greenland ice sheets were characterized by (1) location in low latitudes between 20˚N and 10˚ S, and (2) eruption column height ≥25 km, corresponding to a volcanic explosivity index (VEI) ≥5.

Impact of Combined Assimilation of Radar and Rainfall Data on Short-Term Heavy Rainfall Prediction: A Case Study

2020 ◽  
Vol 148 (5) ◽  
pp. 2211-2232 ◽  
Author(s):  
Juanzhen Sun ◽  
Ying Zhang ◽  
Junmei Ban ◽  
Jing-Shan Hong ◽  
Chung-Yi Lin
Keyword(s):  
Data Assimilation ◽  
Heavy Rainfall ◽  
Numerical Models ◽  
Radar Data ◽  
Rainfall Data ◽  
Data Sources ◽  
Short Term ◽  
Rainfall Prediction ◽  
Data Assimilation System ◽  
Assimilation System

Abstract Radar and surface rainfall observations are two sources of operational data crucial for heavy rainfall prediction. Their individual values on improving convective forecasting through data assimilation have been examined in the past using convection-permitting numerical models. However, the benefit of their simultaneous assimilations has not yet been evaluated. The objective of this study is to demonstrate that, using a 4D-Var data assimilation system with a microphysical scheme, these two data sources can be assimilated simultaneously and the combined assimilation of radar data and estimated rainfall data from radar reflectivity and surface network can lead to improved short-term heavy rainfall prediction. In our study, a combined data assimilation experiment is compared with a rainfall-only and a radar-only (with or without reflectivity) experiments for a heavy rainfall event occurring in Taiwan during the passage of a mei-yu system. These experiments are conducted by applying the Weather Research and Forecasting (WRF) 4D-Var data assimilation system with a 20-min time window aiming to improve 6-h convective heavy rainfall prediction. Our results indicate that the rainfall data assimilation contributes significantly to the analyses of humidity and temperature whereas the radar data assimilation plays a crucial role in wind analysis, and further, combining the two data sources results in reasonable analyses of all three fields by eliminating large, unphysical analysis increments from the experiments of assimilating individual data only. The results also show that the combined assimilation improves forecasts of heavy rainfall location and intensity of 6-h accumulated rainfall for the case studied.

scholarly journals Estimation of the vertical profile of sulfur dioxide injection into the atmosphere by a volcanic eruption using satellite column measurements and inverse transport modeling

2008 ◽  
Vol 8 (14) ◽  
pp. 3881-3897 ◽  
Author(s):  
S. Eckhardt ◽  
A. J. Prata ◽  
P. Seibert ◽  
K. Stebel ◽  
A. Stohl
Keyword(s):  
Vertical Profile ◽  
Volcanic Ash ◽  
Transport Model ◽  
A Priori ◽  
Volcanic Eruptions ◽  
Inversion Method ◽  
Volcanic Plume ◽  
Operational Environment ◽  
Data Set ◽  
Emission Profile

Abstract. An analytical inversion method has been developed to estimate the vertical profile of SO2 emissions from volcanic eruptions. The method uses satellite-observed total SO2 columns and an atmospheric transport model (FLEXPART) to exploit the fact that winds change with altitude – thus, the position and shape of the volcanic plume bear information on its emission altitude. The method finds the vertical emission distribution which minimizes the total difference between simulated and observed SO2 columns while also considering a priori information. We have tested the method with the eruption of Jebel at Tair, Yemen, on 30 September 2007 for which a comprehensive observational data set from various satellite instruments (AIRS, OMI, SEVIRI, CALIPSO) is available. Using satellite data from the first 24 h after the eruption for the inversion, we found an emission maximum near 16 km above sea level (a.s.l.), and secondary maxima near 5, 9, 12 and 14 km a.s.l. 60% of the emission occurred above the tropopause. The emission profile obtained in the inversion was then used to simulate the transport of the plume over the following week. The modeled plume agrees very well with SO2 total columns observed by OMI, and its altitude agrees with CALIPSO aerosol observations to within 1–2 km. The inversion result is robust against various changes in both the a priori and the observations. Even when using only SEVIRI data from the first 15 h after the eruption, the emission profile was reasonably well estimated. The method is computationally very fast. It is therefore suitable for implementation within an operational environment, such as the Volcanic Ash Advisory Centers, to predict the threat posed by volcanic ash for air traffic. It could also be helpful for assessing the sulfur input into the stratosphere, be it in the context of volcanic processes or also for proposed geo-engineering techniques to counteract global warming.

scholarly journals Estimation of the vertical profile of sulfur dioxide injection into the atmosphere by a volcanic eruption using satellite column measurements and inverse transport modeling

2008 ◽  
Vol 8 (1) ◽  
pp. 3761-3805 ◽  
Author(s):  
S. Eckhardt ◽  
A. J. Prata ◽  
P. Seibert ◽  
K. Stebel ◽  
A. Stohl
Keyword(s):  
Vertical Profile ◽  
Volcanic Ash ◽  
Transport Model ◽  
A Priori ◽  
Volcanic Eruptions ◽  
Inversion Method ◽  
Volcanic Plume ◽  
Operational Environment ◽  
Data Set ◽  
Emission Profile

Abstract. An analytical inversion method has been developed to estimate the vertical profile of SO2 emissions from volcanic eruptions. The method uses satellite-observed total SO2 columns and an atmospheric transport model (FLEXPART) to exploit the fact that winds change with altitude – thus, the position and shape of the volcanic plume bear information on its emission altitude. The method finds the vertical emission distribution which minimizes the total difference between simulated and observed SO2 columns while also considering a priori information. We have tested the method with the eruption of Jebel at Tair on 30 September 2007 for which a comprehensive observational data set from various satellite instruments (AIRS, OMI, SEVIRI, CALIPSO) is available. Using satellite data from the first 24 h after the eruption for the inversion, we found an emission maximum near 16 km above sea level (asl), and secondary maxima near 5, 9, 12 and 14 km a.s.l. 60% of the emission occurred above the tropopause. The emission profile obtained in the inversion was then used to simulate the transport of the plume over the following week. The modeled plume agrees very well with SO2 total columns observed by OMI, and its altitude and width agree mostly within 1–2 km with CALIPSO observations of stratospheric aerosol produced from the SO2. The inversion result is robust against various changes in both the a priori and the observations. Even when using only SEVIRI data from the first 15 h after the eruption, the emission profile was reasonably well estimated. The method is computationally very fast. It is therefore suitable for implementation within an operational environment, such as the Volcanic Ash Advisory Centers, to predict the threat posed by volcanic ash for air traffic. It could also be helpful for assessing the sulfur input into the stratosphere, be it in the context of volcanic processes or also for proposed geo-engineering techniques to counteract global warming.

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