Probabilistic Volcanic Hazard Assessment (PVHA)

 A Use Case by

Short description

PVHA methodologies provide a framework for assessing the likelihood of a given measure of intensity of different volcanic phenomena, such as tephra loading on the ground, airborne ash concentration, pyroclastic flows, etc., being exceeded at a particular location within a given time period. This pilot deals with regional long- and short-term PVHA. Regional assessments are crucial for a better land-use planning and for counter-measurements for risk mitigation actions of civil protection authorities. Because of the computational costs required to adequately simulate volcanic phenomena, PVHA is most based on single or very few selected reference scenarios. Independently of the degree of approximation of the used numerical model, PVHA for tephra loading and/or airborne ash concentration will necessitate a high number (typically several thousands, in order to capture variability in meteorological and volcanological conditions) of tephra dispersion simulations of which each is moderately intensive. This pilot will comprise both long- and short-term probabilistic hazard assessment for volcanic tephra fallout by adopting and improving a methodology recently proposed (Sandri et al., 2016) able to capture aleatory and epistemic uncertainties. Long term probabilistic hazard assessment for PDCs will also be envisaged, focussing on aleatory and epistemic uncertainties on Eruptive Source Parameters. Since tephra fallout models allow also a consistent treatment of spatially and temporally variable wind fields and can describe also phenomena like ash aggregation, an Exascale capacity will allow also to spatially extend, for the first time, the PVHA for evaluating potential impact from all active volcanoes in Italy on the entire national territory.

Results & Achievements

The award of PRACE resources, in association with PD3 (High-resolution volcanic plume simulation ) and PD12 (High-Resolution Volcanic Ash Dispersal Forecast), to run FALL3d simulations at the required target resolution and spatial domain.

The prototypal version of PVHA_WF to process the simulations and produce hazard maps.

The application of PVHA_WF to the case of Campi Flegrei volcano, in Southern Italy, in an illustrative example for the days 5, 6 and 7 December 2019, to show the proof-of-concept and feasibility

Objectives

The objective of this use case is to provide innovative hazard maps with uncertainty, and overcoming the current limits of PVHA imposed so far by the high computational cost required to adequately simulate complex volcanic phenomena (such as tephra dispersal) while fully exploring the natural variability associated to such volcanic phenomena, on a country-size domain (~thousands of km) at a high resolution (one to few km).

Technologies

Workflow

PVHA_WF_st fetches the monitoring data (seismic and deformation) and, together with the configuration file of the volcano, calculates the eruptive forecasting (probability curves and vent opening positions) and uses the output file from  alphabeta_MPI.py to create the volcanic hazard probabilities and maps. 

PVHA_WF_lt uses the configuration file of the volcano to calculate the eruptive forecasting and, together with the output file from alphabeta_MPI.py, creates the volcanic hazard probabilities and maps. 

Meteo data download process is fully automated. PVHA_WF_st and PVHA_WF_lt connect to the Climate Data Store (Copernicus data server) and download the meteorological data associated with a specified analysis grid. These data will later be used to obtain the results of tephra deposition by FALL3D. 

Software involved

FALL3D

Use Case Owner

Laura Sandri
INGV Bologna

Collaborating Institutions

INGV
BSC
IMO

High-Resolution Volcanic Ash Dispersal Forecast

 A Use Case by

Short description

Operational volcanic ash dispersal forecasts are routinely used to prevent aircraft encounters with volcanic ash clouds and to perform re-routings avoiding contaminated airspace areas. However, a gap exists between current operational forecast products (e.g. issued by the Volcanic Ash Advisory Centers) and the requirements of the aviation sector and related stakeholders. Two aspects are particularly critical: 1) time and space scales of current forecasts are coarse (for example, the current operational setup of the London VAAC at U.K. Met. Office outputs on a 40 km horizontal resolution grid and 6 hour time averages) and; 2) quantitative forecasts. Several studies (e.g. Kristiansen et al., 2012) have concluded that the main source of epistemic/aleatory uncertainty in ash dispersal forecasts comes from the quantification of the source term (eruption column height and strength) which, very often, is not fully-constrained on real time. This limitation can be circumvented in part by integrating into models ash cloud observations away from the source, typically from satellite retrievals of fine ash column mass load (i.e. vertical integration of concentration). Model data assimilation has the potential to improve ash dispersal forecasts by an efficient joint estimation of the (uncertain) volcanic source parameters and the state of the ash cloud.

Results & Achievements

Implementation of ensemble forecasts in FALL3D to run different ensemble members (realizations) as a single model run.

A new workflow component has been developed to retrieve ash (and SO2) cloud column mass from last-generation satellite instrumentation.

A new satellite data assimilation module based on the Parallel Data Assimilation Framework (PDAF) has been implemented.

Objectives

Volcanic ash cloud forecasts are performed shortly before or during an eruption in order to predict expected fallout rates in the next hours/days and/or to prevent aircraft encounters with volcanic clouds. These forecasts constitute the main decision tool for flight cancellations and airplane re-routings avoiding contaminated airspace areas. However, an important gap exists between current operational products and the actual requirements from the aviation industry and related stakeholders in terms of model resolution, frequency of forecasts, and quantification of airborne ash concentration. This pilot demonstrator is implementing an ensemble-based data assimilation system (workflow) combining the FALL3D dispersal model with high-resolution geostationary satellite retrievals in order to furnish high-resolution forecasts

Technologies

Workflow

Use case workflow includes the following components:

The download and pre-process of required meteorological data.

The download of raw satellite data and the cloud mass quantitative retrievals (SEVIRI retrievals at 0.1º resolution, 1-hour frequency).

The ensemble forecast execution using the FALL3D model (i.e. the HPC component of the workflow)

No WMS available yet (work in progress)

Software involved

 

FALL3D code

Use Case Owner

Arnau Folch
Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC-CNS)

Collaborating Institutions

BSC
INGV
IMO

ChEESE: New open access publication on Probabilistic Tsunami Hazard Analysis

5. January 2021
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Check out new open access publication by ChEESE CoE on Probabilistic Tsunami Hazard Analysis.
(c) ChEESE

New POP CoE blog post: Speedups of a Volcanic Hazard Assessment Code

11. November 2020

Latest blog post by POP CoE – discover how their work on The Probabilistic Volcanic Hazard Assessment Work Flow package (PVHA_WF) led to speedups of around 500x over the total execution time.

The package is a workflow created for the ChEESE CoE Pilot Demonstrator 6 (PD6).

>> POP CoE Blog Post
>> ChEESE Pilot Demonstrators

(c) POP CoE

ETP4HPC handbook 2020 released

6. November 2020

The 2020 edition of the ETP4HPC Handbook of HPC projects is available. It offers a comprehensive overview over the European HPC landscape that currently consists of around 50 active projects and initiatives. Amongst these are the 14 Centres of Excellence and FocusCoE, that are also represented in this edition of the handbook.

>> Read here

HPC Centres of Excellence @ Supercomputing '20

4. November 2020

Due to restrictions caused by the global COVID-19 pandemic, the SC20 conference – the world’s leading HPC event – will take place online this year from November 9-19. 

Find below the CoE’s contributions to the 2020 edition of the Supercomputing Conference.

From research to societal relevance: How ChEESE and urgent computing may enhance INGV´s hazard forecasting

19. October 2020

Cheese

ChEESE is helping to dramatically improve near real-time hazard assessment and hazard forecasting services which will positively impact natural hazard observatories and warning centers in Europe. Learn in this article how ChEESE and urgent computing may enhance INGV´s hazard forecasting. 

>> Read More

(c) ChEESE