Bayesian Network Analysis of Land-Atmosphere Interactions Affecting Burned Areas in India During the 2022 South Asia Heatwave

Bayesian Network Analysis of Land-Atmosphere Interactions Affecting Burned Areas in India During the 2022 South Asia Heatwave

IEEE International Geoscience and Remote Sensing Symposium (IEEE IGARSS 2024), Acting for Sustainability and Resilience, 7-12 July 2024, Athens, Greece.-- 4 pages

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Main Authors: Irawan, Amir Mustofa, Vall-llossera, Mercè, López-Martínez, Carlos, Camps, Adriano, Chaparro, David, Portal, Gerard, Pablos, Miriam, Alonso-González, Alberto
Other Authors: Agencia Estatal de Investigación (España)
Format: capítulo de libro biblioteca
Language:English
Published: Institute of Electrical and Electronics Engineers 2024-07
Online Access:http://hdl.handle.net/10261/368639
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spelling dig-icm-es-10261-3686392024-09-26T11:56:46Z Bayesian Network Analysis of Land-Atmosphere Interactions Affecting Burned Areas in India During the 2022 South Asia Heatwave Irawan, Amir Mustofa Vall-llossera, Mercè López-Martínez, Carlos Camps, Adriano Chaparro, David Portal, Gerard Pablos, Miriam Alonso-González, Alberto Agencia Estatal de Investigación (España) IEEE International Geoscience and Remote Sensing Symposium (IEEE IGARSS 2024), Acting for Sustainability and Resilience, 7-12 July 2024, Athens, Greece.-- 4 pages This study addresses discerning causal relationships in complex systems, a key aspect of interpretable machine learning. It focuses on the unusual and intense early summer weather in South Asia during April and May 2022 that led to an increased number of forest fires. This work employs a Bayesian network (BN), constructed using the NOTEARS algorithm, to analyse the contribution of various land and atmospheric variables on the extent of burned areas. In a scenario analysis using peak values of 300-hPa meridional circulation index and 500-hPa Geopotential Height Anomalies, indicative of a strong atmospheric block, the likelihood of large burned areas (>3.06 log ha or >1150 ha) increases from 36.6% to 41.6%. This is due to a rise of conditional probabilities in the Vapor Pressure Deficit (VPD) (> 5.21 kPa) by 24.8%, and the Land Surface Temperature (LST) (>45.7°C) by 15.6%. In addition, sensitivity and spatial analyses indicate that extreme dry conditions, characterized by high LST and VPD due to the trapping effects of the omega block jet stream pattern, were the primary factors influencing the extent of burned areas during the 2022 South Asia heatwave With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S) Peer reviewed 2024-09-26T11:55:41Z 2024-09-26T11:55:41Z 2024-07 capítulo de libro IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium (2024) CEX2019-000928-S http://hdl.handle.net/10261/368639 10.1109/IGARSS53475.2024.10642105 en https://doi.org/10.1109/IGARSS53475.2024.10642105 Sí none Institute of Electrical and Electronics Engineers
institution ICM ES
collection DSpace
country España
countrycode ES
component Bibliográfico
access En linea
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region Europa del Sur
libraryname Biblioteca del ICM España
language English
description IEEE International Geoscience and Remote Sensing Symposium (IEEE IGARSS 2024), Acting for Sustainability and Resilience, 7-12 July 2024, Athens, Greece.-- 4 pages
author2 Agencia Estatal de Investigación (España)
author_facet Agencia Estatal de Investigación (España)
Irawan, Amir Mustofa
Vall-llossera, Mercè
López-Martínez, Carlos
Camps, Adriano
Chaparro, David
Portal, Gerard
Pablos, Miriam
Alonso-González, Alberto
format capítulo de libro
author Irawan, Amir Mustofa
Vall-llossera, Mercè
López-Martínez, Carlos
Camps, Adriano
Chaparro, David
Portal, Gerard
Pablos, Miriam
Alonso-González, Alberto
spellingShingle Irawan, Amir Mustofa
Vall-llossera, Mercè
López-Martínez, Carlos
Camps, Adriano
Chaparro, David
Portal, Gerard
Pablos, Miriam
Alonso-González, Alberto
Bayesian Network Analysis of Land-Atmosphere Interactions Affecting Burned Areas in India During the 2022 South Asia Heatwave
author_sort Irawan, Amir Mustofa
title Bayesian Network Analysis of Land-Atmosphere Interactions Affecting Burned Areas in India During the 2022 South Asia Heatwave
title_short Bayesian Network Analysis of Land-Atmosphere Interactions Affecting Burned Areas in India During the 2022 South Asia Heatwave
title_full Bayesian Network Analysis of Land-Atmosphere Interactions Affecting Burned Areas in India During the 2022 South Asia Heatwave
title_fullStr Bayesian Network Analysis of Land-Atmosphere Interactions Affecting Burned Areas in India During the 2022 South Asia Heatwave
title_full_unstemmed Bayesian Network Analysis of Land-Atmosphere Interactions Affecting Burned Areas in India During the 2022 South Asia Heatwave
title_sort bayesian network analysis of land-atmosphere interactions affecting burned areas in india during the 2022 south asia heatwave
publisher Institute of Electrical and Electronics Engineers
publishDate 2024-07
url http://hdl.handle.net/10261/368639
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