Javascript must be enabled to continue!
Ensemble-based volcanic ash forecasts using satellite retrievals for quantitative verification
View through CrossRef
<p>Volcanic ash poses a significant hazard for aviation. If an ash cloud forms as result of an eruption, it forces a series of flight planning decisions that consider important safety and economic factors. These decisions are made using a combination of satellite retrievals and volcanic ash forecasts issued by Volcanic Ash Advisory Centres.&#160; However, forecasts of ash hazard remain deterministic, and lack quantification of the uncertainty that arises from the estimation of eruption source parameters, meteorology and uncertainties within the dispersion model used to perform the simulations. Quantification of these uncertainties is fundamental and could be achieved by using ensemble simulations. Here, we explore how ensemble-based forecasts &#8212; performed using the Met Office dispersion model NAME &#8212; together with sequential satellite retrievals of ash column loading, may improve forecast accuracy and uncertainty characterization.</p><p>We have developed a new methodology to evaluate each member of the ensemble based on its agreement with the satellite retrievals available at the time. An initial ensemble is passed through a filter of verification metrics and compared with the first available set of satellite observations. Members far from the observations are rejected. The members within a limit of acceptability are used to resample the parameters used in the initial ensemble, and design a new ensemble to compare with the next available set of satellite observations. The filtering process and parameter resampling are applied whenever new satellite observations are available, to create new ensembles propagating forward in time, until all available observations are covered.</p><p>Although the method requires the run of many ensemble batches, and it is not yet suited for operational use, it shows how combining ensemble simulations and sequential satellite retrievals can be used to quantify confidence in ash forecasts. We demonstrate the method by applying it to the recent Raikoke (Kurii Islands, Russia) eruption, which occurred on the 22<sup>nd</sup> July 2019. Each ensemble consists of 1000 members and it is evaluated against 6-hourly HIMAWARI satellite ash retrievals.</p>
Title: Ensemble-based volcanic ash forecasts using satellite retrievals for quantitative verification
Description:
<p>Volcanic ash poses a significant hazard for aviation.
If an ash cloud forms as result of an eruption, it forces a series of flight planning decisions that consider important safety and economic factors.
These decisions are made using a combination of satellite retrievals and volcanic ash forecasts issued by Volcanic Ash Advisory Centres.
&#160; However, forecasts of ash hazard remain deterministic, and lack quantification of the uncertainty that arises from the estimation of eruption source parameters, meteorology and uncertainties within the dispersion model used to perform the simulations.
Quantification of these uncertainties is fundamental and could be achieved by using ensemble simulations.
Here, we explore how ensemble-based forecasts &#8212; performed using the Met Office dispersion model NAME &#8212; together with sequential satellite retrievals of ash column loading, may improve forecast accuracy and uncertainty characterization.
</p><p>We have developed a new methodology to evaluate each member of the ensemble based on its agreement with the satellite retrievals available at the time.
An initial ensemble is passed through a filter of verification metrics and compared with the first available set of satellite observations.
Members far from the observations are rejected.
The members within a limit of acceptability are used to resample the parameters used in the initial ensemble, and design a new ensemble to compare with the next available set of satellite observations.
The filtering process and parameter resampling are applied whenever new satellite observations are available, to create new ensembles propagating forward in time, until all available observations are covered.
</p><p>Although the method requires the run of many ensemble batches, and it is not yet suited for operational use, it shows how combining ensemble simulations and sequential satellite retrievals can be used to quantify confidence in ash forecasts.
We demonstrate the method by applying it to the recent Raikoke (Kurii Islands, Russia) eruption, which occurred on the 22<sup>nd</sup> July 2019.
Each ensemble consists of 1000 members and it is evaluated against 6-hourly HIMAWARI satellite ash retrievals.
</p>.
Related Results
Calculating and communicating ensemble-based volcanic ash concentration risk for aviation
Calculating and communicating ensemble-based volcanic ash concentration risk for aviation
<p>During volcanic eruptions Volcanic Ash Advisory Centers (VAAC) produce forecasts of ash location and concentration. However, these forecasts are deterministic and ...
The Story of the Lost Thai Classical Music Ensemble: The Wang Bang Kholaem Ensemble
The Story of the Lost Thai Classical Music Ensemble: The Wang Bang Kholaem Ensemble
This article was written to answer the following two questions, which are 1) What is the history of the Wang Bang Kholaem ensemble? What were the reasons for its establishment and ...
A global volcanic eruption source parameter database with application to determination of ashfall risk to infrastructure
A global volcanic eruption source parameter database with application to determination of ashfall risk to infrastructure
<p>Volcanic eruption sequences are often very long in length, and can cause significant downtimes and damage to infrastructure. Over the course of the H2020 EURATOM N...
Probabilistic Short-Term Solar Driver Forecasting with Neural Network Ensembles
Probabilistic Short-Term Solar Driver Forecasting with Neural Network Ensembles
Space weather indices are used to drive forecasts of thermosphere
density, which directly affects objects in low-Earth orbit (LEO) through
atmospheric drag force. A set of proxies ...
Diabot: A Predictive Medical Chatbot using Ensemble Learning
Diabot: A Predictive Medical Chatbot using Ensemble Learning
Accessibility to medical knowledge and healthcare costs are the two major impediments for common man. Conversational agents like Medical chatbots, which are designed keeping in vie...
Information Resources Economy in Satellite Systems based on New Microwave Polarizers with Tunable Posts
Information Resources Economy in Satellite Systems based on New Microwave Polarizers with Tunable Posts
One of the fundamental problems of modern digital telecommunications is the economy of digital information and frequency resources, which are highly limited. The introduction of no...
Probabilistic Solar Proxy Forecasting With Neural Network Ensembles
Probabilistic Solar Proxy Forecasting With Neural Network Ensembles
AbstractSpace weather indices are used commonly to drive forecasts of thermosphere density, which affects objects in low‐Earth orbit (LEO) through atmospheric drag. One commonly us...
Comparison of vertical deformation of the Earth's surface obtained using grace-based GGMS and GNSS data: a case study of South-Eastern Poland
Comparison of vertical deformation of the Earth's surface obtained using grace-based GGMS and GNSS data: a case study of South-Eastern Poland
The development of knowledge on geodynamic processes is one of the most important issues in the Earth’s science. Over decades, geodetic techniques have been applied to study the ge...
Recent Results
Steilneset minnested
Steilneset minnested
Louise Bourgeois, Installations (Art), 2011, Forlaget Press...
Surgimento e consolidação da Documentação: subsídios para compreensão da história da Ciência da Informação no Brasil
Surgimento e consolidação da Documentação: subsídios para compreensão da história da Ciência da Informação no Brasil
As denominações Biblioteconomia, Documentação e Ciência da Informação marcam presença no Brasil, mas a segunda configura-se como a menos conhecida. Deste modo, o artigo apresenta m...
Marcus tullIus Cicero’s works in the textbook on eloquence “The Mohyla Speaker” (1636)
Marcus tullIus Cicero’s works in the textbook on eloquence “The Mohyla Speaker” (1636)
The article analyses which works of Marcus Tullius Cicero are mentioned and (or) quoted in the textbook on the rhetoric of the Kyiv-Mohyla Academy “Orator Mohileanus” (1636) by Jos...