scholarly journals Stochastic Surrogate Model for Meteotsunami Early Warning System in the Eastern Adriatic Sea

2019 ◽  
Vol 124 (11) ◽  
pp. 8485-8499 ◽  
Author(s):  
Cléa Denamiel ◽  
Jadranka Šepić ◽  
Xun Huan ◽  
Célia Bolzer ◽  
Ivica Vilibić
Keyword(s):  
Early Warning ◽  
Surrogate Model ◽  
Early Warning System ◽  
Adriatic Sea ◽  
Warning System

Ensemble technique application to an XBeach-based coastal Early Warning System for the Northwest Adriatic Sea (Emilia-Romagna region, Italy)

2022 ◽  
pp. 104081
Author(s):  
Luis Germano Biolchi ◽  
Silvia Unguendoli ◽  
Lidia Bressan ◽  
Beatrice Maria Sole Giambastiani ◽  
Andrea Valentini
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Adriatic Sea ◽  
Warning System ◽  
Ensemble Technique ◽  
Emilia Romagna Region

scholarly journals Performance of the Adriatic early warning system during the multi-meteotsunami event of 11–19 May 2020: an assessment using energy banners

2021 ◽  
Vol 21 (8) ◽  
pp. 2427-2446
Author(s):  
Iva Tojčić ◽  
Cléa Denamiel ◽  
Ivica Vilibić
Keyword(s):  
Sea Level ◽  
Early Warning ◽  
Surrogate Model ◽  
Early Warning System ◽  
Warning System ◽  
Atmospheric Model ◽  
Air Pressure ◽  
False Alarms ◽  
Deterministic Models ◽  
And Sea Level

Abstract. This study quantifies the performance of the Croatian meteotsunami early warning system (CMeEWS) composed of a network of air pressure and sea level observations, a high-resolution atmosphere–ocean modelling suite, and a stochastic surrogate model. The CMeEWS, which is not operational due to a lack of numerical resources, is used retroactively to reproduce the multiple events observed in the eastern Adriatic between 11 and 19 May 2020. The performances of the CMeEWS deterministic models are then assessed with an innovative method using energy banners based on temporal and spatial spectral analysis of the high-pass-filtered air pressure and sea level fields. It is found that deterministic simulations largely fail to forecast these extreme events at endangered locations along the Croatian coast, mostly due to a systematic northwestward shift of the atmospheric disturbances. Additionally, the use of combined ocean and atmospheric model results, instead of atmospheric model results only, is not found to improve the selection of the transects used to extract the atmospheric parameters feeding the stochastic meteotsunami surrogate model. Finally, in operational mode, the stochastic surrogate model would have triggered the warnings for most of the observed events but also set off some false alarms. Due to the uncertainties associated with operational modelling of meteotsunamigenic disturbances, the stochastic approach has thus proven to overcome the failures of the deterministic forecasts and should be further developed.

scholarly journals Performance of the Adriatic early warning system during the multi-meteotsunami event of 11–19 May 2020: an assessment using energy banners

2021 ◽  
Author(s):  
Iva Tojčić ◽  
Cléa Denamiel ◽  
Ivica Vilibić
Keyword(s):  
Early Warning ◽  
Surrogate Model ◽  
Early Warning System ◽  
Warning System ◽  
Stochastic Approach ◽  
Atmospheric Model ◽  
False Alarms ◽  
Operational Mode ◽  
Atmospheric Disturbances ◽  
Operational Modelling

Abstract. This study quantifies the performance of the Croatian meteotsunami early warning system (CMeEWS) composed of a network of air pressure and sea level observations, a high-resolution atmosphere-ocean modelling suite and a stochastic surrogate model. The CMeEWS, which is not operational due to a lack of numerical resources, is used retroactively to reproduce the multiple events observed in the eastern Adriatic between the 11th and 19th of May 2020. It is found that deterministic simulations largely fail to forecast these extreme events at endangered locations along the Croatian cost mostly due to a systematic northwestward shift of the atmospheric disturbances. Additionally, the use of combined ocean and atmospheric model results, instead of atmospheric model results only, is not found to improve the selection of the transects used to extract the atmospheric parameters feeding the stochastic meteotsunami surrogate model. Finally, in operational mode, the stochastic surrogate model would have triggered the warnings for most of the observed events, but also setting off some false alarms. Due to the uncertainties associated with operational modelling of meteotsunamigenic disturbances, the stochastic approach has thus proven to overcome the failures of the deterministic forecasts and should be further developed.

MODIFIKASI ASESMEN EARLY WARNING SYSTEM UPAYA PENINGKATAN PENERAPAN KESELAMATAN PASIEN

2020 ◽  
Vol 6 (2) ◽  
pp. 112
Author(s):  
Veronika Hutabarat ◽  
Enie Novieastari ◽  
Satinah Satinah
Keyword(s):  
Action Research ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Planning Action

Salah satu faktor dalam meningkatkan penerapan keselamatan pasien adalah ketersediaan dan efektifitas prasarana dalam rumah sakit. Early warning system (EWS) merupakan prasarana dalam mendeteksi perubahan dini  kondisi pasien. Penatalaksanaan EWS masih kurang efektif karena parameter dan nilai rentang scorenya belum sesuai dengan kondisi pasien. Tujuan penulisan untuk mengidentifikasi efektifitas EWS dalam penerapan keselamatan pasien. Metode penulisan action research melalui proses diagnosa, planning action, intervensi, evaluasi dan  refleksi. Responden dalam penelitian ini adalah  perawat yang bertugas di area respirasi dan pasien dengan kasus kompleks respirasi di Rumah Sakit Pusat Rujukan Pernapasan Persahabatan Jakarta. Analisis masalah dilakukan dengan menggunakan diagram fishbone. Masalah yang muncul belum optimalnya implementasi early warning system dalam penerapan keselamatan pasien. Hasilnya 100% perawat mengatakan REWS membantu mendeteksi kondisi pasien, 97,4 % perawat mengatakan lebih efektif dan 92,3 % perawat mengatakan lebih efesien mendeteksi perubahan kondisi pasien. Modifikasi EWS menjadi REWS lebih efektif dan efesien dilakukan karena disesuaikan dengan jenis dan kekhususan Rumah Sakit dan berdampak terhadap kualitas asuhan keperawatan dalam menerapkan keselamatan pasien. Rekomendasi perlu dilakukan monitoring evaluasi terhadap implementasi t.erhadap implementasi REWS dan pengembangan aplikasi berbasis tehnologi

Development of a Pediatric Early Warning System Using Data-Driven Vital Signs

PEDIATRICS ◽  
2016 ◽  
Vol 137 (Supplement 3) ◽  
pp. 256A-256A
Author(s):  
Catherine Ross ◽  
Iliana Harrysson ◽  
Lynda Knight ◽  
Veena Goel ◽  
Sarah Poole ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Vital Signs ◽  
Warning System ◽  
Data Driven ◽  
Using Data

KAJIAN KEKUATAN SINYAL RADIO (RSSI) XBEE DALAM RANGKA PEMASANGAN LANDSLIDE EARLY WARNING SYSTEM (LEWS) DI KABUPATEN GARUT, TASIKMALAYA DAN MAJALENGKA

2019 ◽  
Vol 3 (2) ◽  
pp. 88
Author(s):  
Riski Fitriani
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Received Signal Strength Indicator ◽  
Landslide Early Warning ◽  
Point To Point

Salah satu inovasi untuk menanggulangi longsor adalah dengan melakukan pemasangan Landslide Early Warning System (LEWS). Media transmisi data dari LEWS yang dikembangkan menggunakan sinyal radio Xbee. Sehingga sebelum dilakukan pemasangan LEWS, perlu dilakukan kajian kekuatan sinyal tersebut di lokasi yang akan terpasang yaitu Garut, Tasikmalaya, dan Majalengka. Kajian dilakukan menggunakan 2 jenis Xbee yaitu Xbee Pro S2B 2,4 GHz dan Xbee Pro S5 868 MHz. Setelah dilakukan kajian, Xbee 2,4 GHz tidak dapat digunakan di lokasi pengujian Garut dan Majalengka karena jarak modul induk dan anak cukup jauh serta terlalu banyak obstacle. Topologi yang digunakan yaitu topologi pair/point to point, dengan mengukur nilai RSSI menggunakan software XCTU. Semakin kecil nilai Received Signal Strength Indicator (RSSI) dari nilai receive sensitivity Xbee maka kualitas sinyal semakin baik. Pengukuran dilakukan dengan meninggikan antena Xbee dengan beberapa variasi ketinggian untuk mendapatkan kualitas sinyal yang lebih baik. Hasilnya diperoleh beberapa rekomendasi tinggi minimal antena Xbee yang terpasang di tiap lokasi modul anak pada 3 kabupaten.

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