Tropical Cyclone Count Forecasting Using a Dynamical Seasonal Prediction System: Sensitivity to Improved Ocean Initialization

This study investigates the predictability of tropical cyclone (TC) seasonal count anomalies using the Centro Euro-Mediterraneo per i Cambiamenti Climatici–Istituto Nazionale di Geofisica e Vulcanologia (CMCC-INGV) Seasonal Prediction System (SPS). To this aim, nine-member ensemble forecasts for the...

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Published in:Journal of Climate
Main Authors: Alessandri, A., Borrelli, A., Gualdi, S., Scoccimarro, E., Masina, S.
Other Authors: Alessandri, A.; CMCC, Borrelli, A.; CMCC, Gualdi, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia, Scoccimarro, E.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia, Masina, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia, CMCC, Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia
Format: Article in Journal/Newspaper
Language:English
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/2122/7322
https://doi.org/10.1175/2010JCLI3585.1
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spelling ftingv:oai:www.earth-prints.org:2122/7322 2023-05-15T17:36:23+02:00 Tropical Cyclone Count Forecasting Using a Dynamical Seasonal Prediction System: Sensitivity to Improved Ocean Initialization Alessandri, A. Borrelli, A. Gualdi, S. Scoccimarro, E. Masina, S. Alessandri, A.; CMCC Borrelli, A.; CMCC Gualdi, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia Scoccimarro, E.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia Masina, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia CMCC Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia 2011-06 http://hdl.handle.net/2122/7322 https://doi.org/10.1175/2010JCLI3585.1 en eng Journal of Climate /24 (2011) http://hdl.handle.net/2122/7322 doi:10.1175/2010JCLI3585.1 restricted tropical cyclones seasonal forecast 01. Atmosphere::01.01. Atmosphere::01.01.02. Climate article 2011 ftingv https://doi.org/10.1175/2010JCLI3585.1 2022-07-29T06:06:05Z This study investigates the predictability of tropical cyclone (TC) seasonal count anomalies using the Centro Euro-Mediterraneo per i Cambiamenti Climatici–Istituto Nazionale di Geofisica e Vulcanologia (CMCC-INGV) Seasonal Prediction System (SPS). To this aim, nine-member ensemble forecasts for the period 1992–2001 for two starting dates per year were performed. The skill in reproducing the observed TC counts has been evaluated after the application of a TC location and tracking detection method to the retrospective forecasts. The SPS displays good skill in predicting the observed TC count anomalies, par- ticularly over the tropical Pacific and Atlantic Oceans. The simulated TC activity exhibits realistic geo- graphical distribution and interannual variability, thus indicating that the model is able to reproduce the major basic mechanisms that link the TCs’ occurrence with the large-scale circulation. TC count anomalies prediction has been found to be sensitive to the subsurface assimilation in the ocean for initialization. Comparing the results with control simulations performed without assimilated initial conditions, the results indicate that the assimilation significantly improves the prediction of the TC count anomalies over the eastern North Pacific Ocean (ENP) and northern Indian Ocean (NI) during boreal summer. During the austral counterpart, significant progresses over the area surrounding Australia (AUS) and in terms of the probabilistic quality of the predictions also over the southern Indian Ocean (SI) were evidenced. The analysis shows that the improvement in the prediction of anomalous TC counts follows the enhancement in forecasting daily anomalies in sea surface temperature due to subsurface ocean initialization. Furthermore, the skill changes appear to be in part related to forecast differences in convective available potential energy (CAPE) over the ENP and the North Atlantic Ocean (ATL), in wind shear over the NI, and in both CAPE and wind shear over the SI. Published 2963–2982 3.7. ... Article in Journal/Newspaper North Atlantic Earth-Prints (Istituto Nazionale di Geofisica e Vulcanologia) Austral Indian Pacific Journal of Climate 24 12 2963 2982
institution Open Polar
collection Earth-Prints (Istituto Nazionale di Geofisica e Vulcanologia)
op_collection_id ftingv
language English
topic tropical cyclones
seasonal forecast
01. Atmosphere::01.01. Atmosphere::01.01.02. Climate
spellingShingle tropical cyclones
seasonal forecast
01. Atmosphere::01.01. Atmosphere::01.01.02. Climate
Alessandri, A.
Borrelli, A.
Gualdi, S.
Scoccimarro, E.
Masina, S.
Tropical Cyclone Count Forecasting Using a Dynamical Seasonal Prediction System: Sensitivity to Improved Ocean Initialization
topic_facet tropical cyclones
seasonal forecast
01. Atmosphere::01.01. Atmosphere::01.01.02. Climate
description This study investigates the predictability of tropical cyclone (TC) seasonal count anomalies using the Centro Euro-Mediterraneo per i Cambiamenti Climatici–Istituto Nazionale di Geofisica e Vulcanologia (CMCC-INGV) Seasonal Prediction System (SPS). To this aim, nine-member ensemble forecasts for the period 1992–2001 for two starting dates per year were performed. The skill in reproducing the observed TC counts has been evaluated after the application of a TC location and tracking detection method to the retrospective forecasts. The SPS displays good skill in predicting the observed TC count anomalies, par- ticularly over the tropical Pacific and Atlantic Oceans. The simulated TC activity exhibits realistic geo- graphical distribution and interannual variability, thus indicating that the model is able to reproduce the major basic mechanisms that link the TCs’ occurrence with the large-scale circulation. TC count anomalies prediction has been found to be sensitive to the subsurface assimilation in the ocean for initialization. Comparing the results with control simulations performed without assimilated initial conditions, the results indicate that the assimilation significantly improves the prediction of the TC count anomalies over the eastern North Pacific Ocean (ENP) and northern Indian Ocean (NI) during boreal summer. During the austral counterpart, significant progresses over the area surrounding Australia (AUS) and in terms of the probabilistic quality of the predictions also over the southern Indian Ocean (SI) were evidenced. The analysis shows that the improvement in the prediction of anomalous TC counts follows the enhancement in forecasting daily anomalies in sea surface temperature due to subsurface ocean initialization. Furthermore, the skill changes appear to be in part related to forecast differences in convective available potential energy (CAPE) over the ENP and the North Atlantic Ocean (ATL), in wind shear over the NI, and in both CAPE and wind shear over the SI. Published 2963–2982 3.7. ...
author2 Alessandri, A.; CMCC
Borrelli, A.; CMCC
Gualdi, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia
Scoccimarro, E.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia
Masina, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia
CMCC
Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia
format Article in Journal/Newspaper
author Alessandri, A.
Borrelli, A.
Gualdi, S.
Scoccimarro, E.
Masina, S.
author_facet Alessandri, A.
Borrelli, A.
Gualdi, S.
Scoccimarro, E.
Masina, S.
author_sort Alessandri, A.
title Tropical Cyclone Count Forecasting Using a Dynamical Seasonal Prediction System: Sensitivity to Improved Ocean Initialization
title_short Tropical Cyclone Count Forecasting Using a Dynamical Seasonal Prediction System: Sensitivity to Improved Ocean Initialization
title_full Tropical Cyclone Count Forecasting Using a Dynamical Seasonal Prediction System: Sensitivity to Improved Ocean Initialization
title_fullStr Tropical Cyclone Count Forecasting Using a Dynamical Seasonal Prediction System: Sensitivity to Improved Ocean Initialization
title_full_unstemmed Tropical Cyclone Count Forecasting Using a Dynamical Seasonal Prediction System: Sensitivity to Improved Ocean Initialization
title_sort tropical cyclone count forecasting using a dynamical seasonal prediction system: sensitivity to improved ocean initialization
publishDate 2011
url http://hdl.handle.net/2122/7322
https://doi.org/10.1175/2010JCLI3585.1
geographic Austral
Indian
Pacific
geographic_facet Austral
Indian
Pacific
genre North Atlantic
genre_facet North Atlantic
op_relation Journal of Climate
/24 (2011)
http://hdl.handle.net/2122/7322
doi:10.1175/2010JCLI3585.1
op_rights restricted
op_doi https://doi.org/10.1175/2010JCLI3585.1
container_title Journal of Climate
container_volume 24
container_issue 12
container_start_page 2963
op_container_end_page 2982
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