Estimating the velocity of pyroclastic density currents using an operational dual-PRF radar
Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, appli...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Syarifuddin, Magfira [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022transfer abstract |
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| Übergeordnetes Werk: |
Enthalten in: Aromatic composition and potent odorants of the “specialty coffee” brew “Bourbon Pointu” correlated to its three trade classifications - Piccino, Sébastien ELSEVIER, 2014transfer abstract, an international journal on the geophysical, geochemical, petrological, economic and environmental aspects of volcanology and geothermal research, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:424 ; year:2022 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.jvolgeores.2021.107462 |
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ELV057079218 |
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| 245 | 1 | 0 | |a Estimating the velocity of pyroclastic density currents using an operational dual-PRF radar |
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| 520 | |a Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. | ||
| 520 | |a Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. | ||
| 700 | 1 | |a Jenkins, Susanna F. |4 oth | |
| 700 | 1 | |a Taisne, Benoit |4 oth | |
| 700 | 1 | |a Oishi, Satoru |4 oth | |
| 700 | 1 | |a Basuki, Ahmad |4 oth | |
| 700 | 1 | |a Iguchi, Masato |4 oth | |
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10.1016/j.jvolgeores.2021.107462 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001701.pica (DE-627)ELV057079218 (ELSEVIER)S0377-0273(21)00291-2 DE-627 ger DE-627 rakwb eng 630 VZ 640 VZ 540 VZ 660 VZ 340 330 VZ 2 ssgn INTRECHT DE-1a fid 83.00 bkl Syarifuddin, Magfira verfasserin aut Estimating the velocity of pyroclastic density currents using an operational dual-PRF radar 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. Jenkins, Susanna F. oth Taisne, Benoit oth Oishi, Satoru oth Basuki, Ahmad oth Iguchi, Masato oth Enthalten in Elsevier Science Piccino, Sébastien ELSEVIER Aromatic composition and potent odorants of the “specialty coffee” brew “Bourbon Pointu” correlated to its three trade classifications 2014transfer abstract an international journal on the geophysical, geochemical, petrological, economic and environmental aspects of volcanology and geothermal research Amsterdam [u.a.] (DE-627)ELV017774535 volume:424 year:2022 pages:0 https://doi.org/10.1016/j.jvolgeores.2021.107462 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-INTRECHT GBV_ILN_70 83.00 Volkswirtschaft: Allgemeines VZ AR 424 2022 0 |
| spelling |
10.1016/j.jvolgeores.2021.107462 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001701.pica (DE-627)ELV057079218 (ELSEVIER)S0377-0273(21)00291-2 DE-627 ger DE-627 rakwb eng 630 VZ 640 VZ 540 VZ 660 VZ 340 330 VZ 2 ssgn INTRECHT DE-1a fid 83.00 bkl Syarifuddin, Magfira verfasserin aut Estimating the velocity of pyroclastic density currents using an operational dual-PRF radar 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. Jenkins, Susanna F. oth Taisne, Benoit oth Oishi, Satoru oth Basuki, Ahmad oth Iguchi, Masato oth Enthalten in Elsevier Science Piccino, Sébastien ELSEVIER Aromatic composition and potent odorants of the “specialty coffee” brew “Bourbon Pointu” correlated to its three trade classifications 2014transfer abstract an international journal on the geophysical, geochemical, petrological, economic and environmental aspects of volcanology and geothermal research Amsterdam [u.a.] (DE-627)ELV017774535 volume:424 year:2022 pages:0 https://doi.org/10.1016/j.jvolgeores.2021.107462 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-INTRECHT GBV_ILN_70 83.00 Volkswirtschaft: Allgemeines VZ AR 424 2022 0 |
| allfields_unstemmed |
10.1016/j.jvolgeores.2021.107462 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001701.pica (DE-627)ELV057079218 (ELSEVIER)S0377-0273(21)00291-2 DE-627 ger DE-627 rakwb eng 630 VZ 640 VZ 540 VZ 660 VZ 340 330 VZ 2 ssgn INTRECHT DE-1a fid 83.00 bkl Syarifuddin, Magfira verfasserin aut Estimating the velocity of pyroclastic density currents using an operational dual-PRF radar 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. Jenkins, Susanna F. oth Taisne, Benoit oth Oishi, Satoru oth Basuki, Ahmad oth Iguchi, Masato oth Enthalten in Elsevier Science Piccino, Sébastien ELSEVIER Aromatic composition and potent odorants of the “specialty coffee” brew “Bourbon Pointu” correlated to its three trade classifications 2014transfer abstract an international journal on the geophysical, geochemical, petrological, economic and environmental aspects of volcanology and geothermal research Amsterdam [u.a.] (DE-627)ELV017774535 volume:424 year:2022 pages:0 https://doi.org/10.1016/j.jvolgeores.2021.107462 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-INTRECHT GBV_ILN_70 83.00 Volkswirtschaft: Allgemeines VZ AR 424 2022 0 |
| allfieldsGer |
10.1016/j.jvolgeores.2021.107462 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001701.pica (DE-627)ELV057079218 (ELSEVIER)S0377-0273(21)00291-2 DE-627 ger DE-627 rakwb eng 630 VZ 640 VZ 540 VZ 660 VZ 340 330 VZ 2 ssgn INTRECHT DE-1a fid 83.00 bkl Syarifuddin, Magfira verfasserin aut Estimating the velocity of pyroclastic density currents using an operational dual-PRF radar 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. Jenkins, Susanna F. oth Taisne, Benoit oth Oishi, Satoru oth Basuki, Ahmad oth Iguchi, Masato oth Enthalten in Elsevier Science Piccino, Sébastien ELSEVIER Aromatic composition and potent odorants of the “specialty coffee” brew “Bourbon Pointu” correlated to its three trade classifications 2014transfer abstract an international journal on the geophysical, geochemical, petrological, economic and environmental aspects of volcanology and geothermal research Amsterdam [u.a.] (DE-627)ELV017774535 volume:424 year:2022 pages:0 https://doi.org/10.1016/j.jvolgeores.2021.107462 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-INTRECHT GBV_ILN_70 83.00 Volkswirtschaft: Allgemeines VZ AR 424 2022 0 |
| allfieldsSound |
10.1016/j.jvolgeores.2021.107462 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001701.pica (DE-627)ELV057079218 (ELSEVIER)S0377-0273(21)00291-2 DE-627 ger DE-627 rakwb eng 630 VZ 640 VZ 540 VZ 660 VZ 340 330 VZ 2 ssgn INTRECHT DE-1a fid 83.00 bkl Syarifuddin, Magfira verfasserin aut Estimating the velocity of pyroclastic density currents using an operational dual-PRF radar 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. Jenkins, Susanna F. oth Taisne, Benoit oth Oishi, Satoru oth Basuki, Ahmad oth Iguchi, Masato oth Enthalten in Elsevier Science Piccino, Sébastien ELSEVIER Aromatic composition and potent odorants of the “specialty coffee” brew “Bourbon Pointu” correlated to its three trade classifications 2014transfer abstract an international journal on the geophysical, geochemical, petrological, economic and environmental aspects of volcanology and geothermal research Amsterdam [u.a.] (DE-627)ELV017774535 volume:424 year:2022 pages:0 https://doi.org/10.1016/j.jvolgeores.2021.107462 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-INTRECHT GBV_ILN_70 83.00 Volkswirtschaft: Allgemeines VZ AR 424 2022 0 |
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Estimating the velocity of pyroclastic density currents using an operational dual-PRF radar |
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Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. |
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Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. |
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Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV057079218</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626044501.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">220808s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.jvolgeores.2021.107462</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001701.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV057079218</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0377-0273(21)00291-2</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">630</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">640</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">540</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">660</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">340</subfield><subfield code="a">330</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">2</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">INTRECHT</subfield><subfield code="q">DE-1a</subfield><subfield code="2">fid</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">83.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Syarifuddin, Magfira</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Estimating the velocity of pyroclastic density currents using an operational dual-PRF radar</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022transfer abstract</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Pyroclastic density currents are one of the deadliest hazards produced by a volcano. Understanding their dynamics and generation mechanisms is critical for developing better hazard mitigation strategies. This study presents a method for retrieving velocity profiles across a natural moving PDC, applied here to a PDC generated by collapsing column during the eruption of Sinabung Volcano, Indonesia, on 19 February 2018 at the onset time of 08:53. We used an operational dual Pulse Repetition Frequency (PRF) weather radar, located ~7.8 km to the SE of the volcano, to estimate the velocity profile components of the volcanic plume: updraft, fallout, and horizontal advection. Doppler radar data was post-processed by applying two different filters: median and Laplacian, to correct errors associated with dealiased Doppler velocities. The Laplacian filter method was more effective in correcting the dealiasing errors by producing a more continuous velocity field without over smoothing its values. Following the dealiasing process, the velocity profile components were retrieved according to radar parameters such as Doppler velocities, copolar correlation, and reflectivity intensity factor. Initially, the pyroclastic clast was released at a lower exit velocity of ~120 m/s (84 s after the onset). A maximum of ~190 m/s exit velocity was then observed at 08:57:52 (292 s after onset). Lower exit velocity in the initial phase and less than 10 m/s estimated wind speed are the main factors causing the partial collapse of the plume at ~2.5 km height above the vent. The part of the collapsing column was associated with a more than 50 dBZ reflectivity intensity factor of fallout velocity exceeding −50 m/s at 126 s after the onset. Dilute PDCs were observed until 09:09:34 (994 s after onset), moving downslope at SE sector at a maximum velocity of −84 m/s (i.e., in the direction of the radar) . The extracted velocity components are essential parameters in the numerical model of PDCs and tephra dispersal, enforcing the benefit of weather radar to complement the remote monitoring system of volcanic hazards.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Jenkins, Susanna F.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Taisne, Benoit</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Oishi, Satoru</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Basuki, Ahmad</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Iguchi, Masato</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Piccino, Sébastien ELSEVIER</subfield><subfield code="t">Aromatic composition and potent odorants of the “specialty coffee” brew “Bourbon Pointu” correlated to its three trade classifications</subfield><subfield code="d">2014transfer abstract</subfield><subfield code="d">an international journal on the geophysical, geochemical, petrological, economic and environmental aspects of volcanology and geothermal research</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV017774535</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:424</subfield><subfield code="g">year:2022</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.jvolgeores.2021.107462</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-INTRECHT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">83.00</subfield><subfield code="j">Volkswirtschaft: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">424</subfield><subfield code="j">2022</subfield><subfield code="h">0</subfield></datafield></record></collection>
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