scholarly journals Improving Ensemble Volcanic Ash Forecasts by Direct Insertion of Satellite Data and Ensemble Filtering

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1215
Author(s):  
Meelis J. Zidikheri ◽  
Chris Lucas

Improved quantitative forecasts of volcanic ash are in great demand by the aviation industry to enable better risk management during disruptive volcanic eruption events. However, poor knowledge of volcanic source parameters and other dispersion and transport modelling uncertainties, such as those due to errors in numerical weather prediction fields, make this problem very challenging. Nonetheless, satellite-based algorithms that retrieve ash properties, such as mass load, effective radius, and cloud top height, combined with inverse modelling techniques, such as ensemble filtering, can significantly ameliorate these problems. The satellite-retrieved data can be used to better constrain the volcanic source parameters, but they can also be used to avoid the description of the volcanic source altogether by direct insertion into the forecasting model. In this study we investigate the utility of the direct insertion approach when employed within an ensemble filtering framework. Ensemble members are formed by initializing dispersion models with data from different timesteps, different values of cloud top height, thickness, and NWP ensemble members. This large ensemble is then filtered with respect to observations to produce a refined forecast. We apply this approach to 14 different eruption case studies in the tropical atmosphere. We demonstrate that the direct insertion of data improves model forecast skill, particularly when it is used in a hybrid ensemble in which some ensemble members are initialized from the volcanic source. Moreover, good forecast skill can be obtained even when detailed satellite retrievals are not available, which is frequently the case for volcanic eruptions in the tropics.

2021 ◽  
Vol 83 (2) ◽  
Author(s):  
S. Engwell ◽  
L. Mastin ◽  
A. Tupper ◽  
J. Kibler ◽  
P. Acethorp ◽  
...  

AbstractUnderstanding the location, intensity, and likely duration of volcanic hazards is key to reducing risk from volcanic eruptions. Here, we use a novel near-real-time dataset comprising Volcanic Ash Advisories (VAAs) issued over 10 years to investigate global rates and durations of explosive volcanic activity. The VAAs were collected from the nine Volcanic Ash Advisory Centres (VAACs) worldwide. Information extracted allowed analysis of the frequency and type of explosive behaviour, including analysis of key eruption source parameters (ESPs) such as volcanic cloud height and duration. The results reflect changes in the VAA reporting process, data sources, and volcanic activity through time. The data show an increase in the number of VAAs issued since 2015 that cannot be directly correlated to an increase in volcanic activity. Instead, many represent increased observations, including improved capability to detect low- to mid-level volcanic clouds (FL101–FL200, 3–6 km asl), by higher temporal, spatial, and spectral resolution satellite sensors. Comparison of ESP data extracted from the VAAs with the Mastin et al. (J Volcanol Geotherm Res 186:10–21, 2009a) database shows that traditional assumptions used in the classification of volcanoes could be much simplified for operational use. The analysis highlights the VAA data as an exceptional resource documenting global volcanic activity on timescales that complement more widely used eruption datasets.


2011 ◽  
Vol 11 (9) ◽  
pp. 4333-4351 ◽  
Author(s):  
A. Stohl ◽  
A. J. Prata ◽  
S. Eckhardt ◽  
L. Clarisse ◽  
A. Durant ◽  
...  

Abstract. The April–May, 2010 volcanic eruptions of Eyjafjallajökull, Iceland caused significant economic and social disruption in Europe whilst state of the art measurements and ash dispersion forecasts were heavily criticized by the aviation industry. Here we demonstrate for the first time that large improvements can be made in quantitative predictions of the fate of volcanic ash emissions, by using an inversion scheme that couples a priori source information and the output of a Lagrangian dispersion model with satellite data to estimate the volcanic ash source strength as a function of altitude and time. From the inversion, we obtain a total fine ash emission of the eruption of 8.3 ± 4.2 Tg for particles in the size range of 2.8–28 μm diameter. We evaluate the results of our model results with a posteriori ash emissions using independent ground-based, airborne and space-borne measurements both in case studies and statistically. Subsequently, we estimate the area over Europe affected by volcanic ash above certain concentration thresholds relevant for the aviation industry. We find that during three episodes in April and May, volcanic ash concentrations at some altitude in the atmosphere exceeded the limits for the "Normal" flying zone in up to 14 % (6–16 %), 2 % (1–3 %) and 7 % (4–11 %), respectively, of the European area. For a limit of 2 mg m−3 only two episodes with fractions of 1.5 % (0.2–2.8 %) and 0.9 % (0.1–1.6 %) occurred, while the current "No-Fly" zone criterion of 4 mg m−3 was rarely exceeded. Our results have important ramifications for determining air space closures and for real-time quantitative estimations of ash concentrations. Furthermore, the general nature of our method yields better constraints on the distribution and fate of volcanic ash in the Earth system.


2018 ◽  
Vol 18 (6) ◽  
pp. 4019-4038 ◽  
Author(s):  
Alejandro Marti ◽  
Arnau Folch

Abstract. Volcanic ash modeling systems are used to simulate the atmospheric dispersion of volcanic ash and to generate forecasts that quantify the impacts from volcanic eruptions on infrastructures, air quality, aviation, and climate. The efficiency of response and mitigation actions is directly associated with the accuracy of the volcanic ash cloud detection and modeling systems. Operational forecasts build on offline coupled modeling systems in which meteorological variables are updated at the specified coupling intervals. Despite the concerns from other communities regarding the accuracy of this strategy, the quantification of the systematic errors and shortcomings associated with the offline modeling systems has received no attention. This paper employs the NMMB-MONARCH-ASH model to quantify these errors by employing different quantitative and categorical evaluation scores. The skills of the offline coupling strategy are compared against those from an online forecast considered to be the best estimate of the true outcome. Case studies are considered for a synthetic eruption with constant eruption source parameters and for two historical events, which suitably illustrate the severe aviation disruptive effects of European (2010 Eyjafjallajökull) and South American (2011 Cordón Caulle) volcanic eruptions. Evaluation scores indicate that systematic errors due to the offline modeling are of the same order of magnitude as those associated with the source term uncertainties. In particular, traditional offline forecasts employed in operational model setups can result in significant uncertainties, failing to reproduce, in the worst cases, up to 45–70 % of the ash cloud of an online forecast. These inconsistencies are anticipated to be even more relevant in scenarios in which the meteorological conditions change rapidly in time. The outcome of this paper encourages operational groups responsible for real-time advisories for aviation to consider employing computationally efficient online dispersal models.


Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 342 ◽  
Author(s):  
Meelis J. Zidikheri ◽  
Chris Lucas

Poor knowledge of dispersion model source parameters related to quantities such as the total fine ash mass emission rate, its effective spatial distribution, and particle size distribution makes the provision of quantitative forecasts of volcanic ash a difficult problem. To ameliorate this problem, we make use of satellite-retrieved mass load data from 14 eruption case studies to estimate fine ash mass emission rates and other source parameters by an inverse modelling procedure, which requires multidimensional sampling of several thousand trial simulations with different values of source parameters. We then estimate the dependence of these optimal source parameters on eruption height. We show that using these empirical relationships in a data assimilation procedure leads to substantial improvements to the forecasts of ash mass loads, with the use of empirical relationships between parameters and eruption height having the added advantage of computational efficiency because of dimensional reduction. In addition, the use of empirical relationships, which encode information in satellite retrievals from past case studies, implies that quantitative forecasts can still be issued even when satellite retrievals of mass load are not available in real time due to cloud cover or other reasons, making it especially useful for operations in the tropics where ice and water clouds are ubiquitous.


2019 ◽  
Author(s):  
Isabelle A. Taylor ◽  
Elisa Carboni ◽  
Lucy J. Ventress ◽  
Tamsin A. Mather ◽  
Roy G. Grainger

Abstract. Ash clouds are a geographically far reaching hazard associated with volcanic eruptions. To minimise the risk that these pose to aircraft and to limit disruption to the aviation industry, it is important to closely monitor the emission and atmospheric dispersion of these plumes. The altitude of the plume is an important consideration and is an essential input into many models of ash cloud propagation. CO2 slicing is an established technique for obtaining the top height of meteorological clouds and previous studies have demonstrated that there is potential for this method to be used for volcanic ash. In this study, the CO2 slicing technique has been adapted for volcanic ash and applied to spectra obtained from the Infrared Atmospheric Sounding Interferometer (IASI). Simulated ash spectra are first used to select the most appropriate channels and then demonstrate that the technique has merit for determining the altitude of the ash. These results indicate a strong match between the true heights and CO2 slicing output with a root mean square error (RMSE) of less than 800 m. Following this, the technique was applied to spectra obtained with IASI during the Eyjafjallajökull and Grimsvötn eruptions in 2010 and 2011 respectively, both of which emitted ash clouds into the troposphere, and which have been extensively studied with satellite imagery. The CO2 slicing results were compared against those from an optimal estimation scheme, also developed for IASI, and a satellite borne LiDAR is used for validation. Overall, the CO2 slicing tool performs better than the optimal estimation scheme. The CO2 slicing heights returned a RMSE value of 2.2 km when compared against the LiDAR. This is lower than the RMSE for the optimal estimation scheme (2.8 km). The CO2 slicing technique is a relatively fast tool and the results suggest that this method could be used to get a first approximation of the ash cloud height, potentially for use for hazard mitigation, or as an input for other retrieval techniques or models of ash cloud propagation.


2013 ◽  
Vol 13 (17) ◽  
pp. 8569-8584 ◽  
Author(s):  
M. Boichu ◽  
L. Menut ◽  
D. Khvorostyanov ◽  
L. Clarisse ◽  
C. Clerbaux ◽  
...  

Abstract. Depending on the magnitude of their eruptions, volcanoes impact the atmosphere at various temporal and spatial scales. The volcanic source remains a major unknown to rigorously assess these impacts. At the scale of an eruption, the limited knowledge of source parameters, including time variations of erupted mass flux and emission profile, currently represents the greatest issue that limits the reliability of volcanic cloud forecasts. Today, a growing number of satellite and remote sensing observations of distant plumes are becoming available, bringing indirect information on these source terms. Here, we develop an inverse modelling approach combining satellite observations of the volcanic plume with an Eulerian regional chemistry-transport model (CHIMERE) to characterise the volcanic SO2 emissions during an eruptive crisis. The May 2010 eruption of Eyjafjallajökull is a perfect case study to apply this method as the volcano emitted substantial amounts of SO2 during more than a month. We take advantage of the SO2 column amounts provided by a vast set of IASI (Infrared Atmospheric Sounding Interferometer) satellite images to reconstruct retrospectively the time series of the mid-tropospheric SO2 flux emitted by the volcano with a temporal resolution of ~2 h, spanning the period from 1 to 12 May 2010. We show that no a priori knowledge on the SO2 flux is required for this reconstruction. The initialisation of chemistry-transport modelling with this reconstructed source allows for reliable simulation of the evolution of the long-lived tropospheric SO2 cloud over thousands of kilometres. Heterogeneities within the plume, which mainly result from the temporal variability of the emissions, are correctly tracked over a timescale of a week. The robustness of our approach is also demonstrated by the broad similarities between the SO2 flux history determined by this study and the ash discharge behaviour estimated by other means during the phases of high explosive activity at Eyjafjallajökull in May 2010. Finally, we show how a sequential IASI data assimilation allows for a substantial improvement in the forecasts of the location and concentration of the plume compared to an approach assuming constant flux at the source. As the SO2 flux is an important indicator of the volcanic activity, this approach is also of interest to monitor poorly instrumented volcanoes from space.


2013 ◽  
Vol 13 (3) ◽  
pp. 6553-6588 ◽  
Author(s):  
M. Boichu ◽  
L. Menut ◽  
D. Khvorostyanov ◽  
L. Clarisse ◽  
C. Clerbaux ◽  
...  

Abstract. Depending on the magnitude of their eruptions, volcanoes impact the atmosphere at various temporal and spatial scales. The volcanic source remains a major unknown to rigorously assess these impacts. At the scale of an eruption, the limited knowledge of source parameters, including time-variations of erupted mass flux and emission profile, currently represents the greatest issue that limits the reliability of volcanic cloud forecasts. Today, a growing number of satellite and remote sensing observations of distant plumes are becoming available, bringing indirect information on these source terms. Here, we develop an inverse modeling approach combining satellite observations of the volcanic plume with an Eulerian regional chemistry-transport model (CHIMERE) to better characterise the volcanic SO2 emissions during an eruptive crisis. The May 2010 eruption of Eyjafjallajökull is a perfect case-study to apply this method as the volcano emitted substantial amounts of SO2 during more than a month. We take advantage of the SO2 column amounts provided by a vast set of IASI (Infrared Atmospheric Sounding Interferometer) satellite images to reconstruct retrospectively the time-series of the mid-tropospheric SO2 flux emitted by the volcano with a temporal resolution of ~2 h, spanning the period from 1 to 12 May 2010. The initialisation of chemistry-transport modelling with this reconstructed source allows for a reliable simulation of the evolution of the long-lived tropospheric SO2 cloud over thousands of kilometres. Heterogeneities within the plume, which mainly result from the temporal variability of the emissions, are correctly tracked over a time scale of a week. The robustness of our approach is also demonstrated by the broad similarities between the SO2 flux history determined by this study and the ash discharge behaviour estimated by other means during the phases of high explosive activity at Eyjafjallajökull in May 2010. Finally, we show how a sequential IASI data assimilation allows for a substantial improvement in the forecasts of the location and concentration of the plume compared to an approach assuming constant flux at the source. As the SO2 flux is an important indicator of the volcanic activity, this approach is also of interest to monitor poorly instrumented volcanoes from space.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1359
Author(s):  
Soi Ahn ◽  
Joon-Bum Jee ◽  
Kyu-Tae Lee ◽  
Hyun-Jong Oh

In this study, a technique facilitating the enhanced detection of airborne volcanic ash (VA) has been developed, which is based on the use of visible (VIS), near-infrared (NIR), and infrared (IR) bands by meteorological satellite systems. Channels with NIR and IR bands centered at ~3.8, 7.3, 8.7, 10.5, and 12.3 μm are utilized, which enhances the accuracy of VA detection. The technique is based on two-band brightness temperature differences (BTDs), two-band brightness temperature ratios (BTRs), and background image BTDs. The physical effects of the observed BTDs and BTRs, which can be used to distinguish VA from meteorological clouds based on absorption differences, depend on the channel and time of day. The Advanced Meteorological Imager onboard the GEOKOMPSAT-2A (GK-2A) satellite has several advantages, including the day- and nighttime detection of land and ocean. Based on the GK-2A data on several volcanic eruptions, multispectral data are more sensitive to volcanic clouds than ice and water clouds, ensuring the detection of VA. They can also be used as an input to provide detailed information about volcanoes, such as the height of the VA layer and VA mass. The GK-2A was optimized, and an improved ash algorithm was established by focusing on the volcanic eruptions that occurred in 2020. In particular, the 3.8 μm band was utilized, the threshold was changed by division between day and night, and efforts were made to reduce the effects of clouds and the discontinuity between land and ocean. The GK-2A imagery was used to study volcanic clouds related to the eruptions of Taal, Philippines, on 12 January and Nishinoshima, Japan, from 30 July–2 August to demonstrate the applicability of this product during volcanic events. The improved VA product of GK-2A provides vital information, helping forecasters to locate VA as well as guidance for the aviation industry in preventing dangerous and expensive interactions between aircrafts and VA.


2017 ◽  
Author(s):  
Alejandro Marti ◽  
Arnau Folch

Abstract. Volcanic ash modeling systems are used to simulate the atmospheric dispersion of volcanic ash and to generate forecasts that quantify the impacts from volcanic eruptions on infrastructures, air quality, aviation, and climate. The efficiency of response and mitigation actions is directly associated to the accuracy of the volcanic ash cloud detection and modeling systems. Operational forecasts build on off-line coupled modeling systems where meteorological variables are updated at the specified coupling intervals. Despite the concerns from other communities regarding the accuracy of this strategy, the quantification of the systematic errors and shortcomings associated to the off-line modeling systems has received no attention. This paper employs the NMMB-MONARCH-ASH model to quantify these errors by employing different quantitative and categorical evaluation scores. The skills of the off-line coupling strategy are compared against those from an on-line forecast considered to be the best estimate of the true outcome. Case studies are considered for a synthetic eruption with constant eruption source parameters and for two historical events, which suitably illustrate the severe aviation disruptive effects of European (2010 Eyjafjallajökull) and South-American (2011 Cordón Caulle) volcanic eruptions. Evaluation scores indicate that systematic errors credited to off-line modeling are of the same order of magnitude that those associated to the source term uncertainties. In particular, traditional off-line forecasts employed in operational model setups can result in significant uncertainties, failing to reproduce, in the worst cases, up to 45–70 % of the ash cloud of an on-line forecast. These inconsistencies are anticipated to be even more relevant in scenarios where the meteorological conditions change rapidly in time. The outcome of this paper encourages operational groups responsible for real‐time advisories for aviation to consider employing computationally efficient on-line dispersal models.


2021 ◽  
Vol 9 ◽  
Author(s):  
Zhixuan Cao ◽  
Marcus Bursik ◽  
Qingyuan Yang ◽  
Abani Patra

Volcanic ash transport and dispersion (VATD) models simulate atmospheric transport of ash from a volcanic source represented by parameterized concentration of ash with height. Most VATD models represent the volcanic plume source as a simple line with a parameterized ash emission rate as a function of height, constrained only by a total mass eruption rate (MER) for a given total rise height. However, the actual vertical ash distribution in volcanic plumes varies from case to case, having complex dependencies on eruption source parameters, such as grain size, speed at the vent, vent size, buoyancy flux, and atmospheric conditions. We present here for the first time the use of a three-dimensional (3D) plume model based on conservation laws to represent the ash cloud source without any prior assumption or simplification regarding plume geometry. By eliminating assumed behavior associated with a parameterized plume geometry, the predictive skill of VATD simulations is improved. We use our recently developed volcanic plume model based on a 3D smoothed-particle hydrodynamic Lagrangian method and couple the output to a standard Lagrangian VATD model. We apply the coupled model to the Pinatubo eruption in 1991 to illustrate the effectiveness of the approach. Our investigation reveals that initial particle distribution in the vertical direction, including within the umbrella cloud, has more impact on the long-range transport of ash clouds than does the horizontal distribution. Comparison with satellite data indicates that the 3D model-based distribution of ash particles through the depth of the volcanic umbrella cloud, which is much lower than the observed maximum plume height, produces improved long-range VATD simulations. We thus show that initial conditions have a significant impact on VATD, and it is possible to obtain a better estimate of initial conditions for VATD simulations with deterministic, 3D forward modeling of the volcanic plume. Such modeling may therefore provide a path to better forecasts lessening the need for user intervention, or attempts to observe details of an eruption that are beyond the resolution of any potential satellite or ground-based technique, or a posteriori creating a history of ash emission height via inversion.


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