Tropical cyclone activity in the Solomon Islands region : climatology, variability, and trends
- Haruhiru, Alick, Chand, Savin, Turville, Christopher, Ramsay, Hamish
- Authors: Haruhiru, Alick , Chand, Savin , Turville, Christopher , Ramsay, Hamish
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Climatology Vol. 43, no. 1 (2023), p. 593-614
- Full Text:
- Reviewed:
- Description: This study examines the climatology, variability, and trends of tropical cyclones (TCs) affecting the Solomon Islands (SI) territory, in the wider southwest Pacific (SWP), using the South Pacific Enhanced Archive for Tropical Cyclones (SPEArTC) database. During the period 1969/1970–2018/2019, 168 TCs were recorded in the SI territory. A cluster analysis is used to objectively partition these tracks into three clusters of similar TC trajectories to obtain better insights into the effects of natural climate variability, particularly due to the El Niño–Southern Oscillation (ENSO) phenomenon, which otherwise is not very apparent for TCs when considered collectively in the SI region. We find that TCs in clusters 1 and 3 show enhanced activity during El Niño phase, whereas TCs in cluster 2 are enhanced during La Niña and neutral phases. In addition to being modulated by ENSO, TCs in clusters 2 and 3 show statistically significant modulation at an intraseasonal timescale due to the Madden–Julian Oscillation (MJO) phenomenon. There are also some indications through sophisticated Bayesian modelling that TCs in clusters 2 and 3 are slightly influenced by the Interdecadal Pacific Oscillation (IPO). These results can have substantial implications for cluster-specific development of TC prediction schemes for the SI region. © 2022 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society.
- Authors: Haruhiru, Alick , Chand, Savin , Turville, Christopher , Ramsay, Hamish
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Climatology Vol. 43, no. 1 (2023), p. 593-614
- Full Text:
- Reviewed:
- Description: This study examines the climatology, variability, and trends of tropical cyclones (TCs) affecting the Solomon Islands (SI) territory, in the wider southwest Pacific (SWP), using the South Pacific Enhanced Archive for Tropical Cyclones (SPEArTC) database. During the period 1969/1970–2018/2019, 168 TCs were recorded in the SI territory. A cluster analysis is used to objectively partition these tracks into three clusters of similar TC trajectories to obtain better insights into the effects of natural climate variability, particularly due to the El Niño–Southern Oscillation (ENSO) phenomenon, which otherwise is not very apparent for TCs when considered collectively in the SI region. We find that TCs in clusters 1 and 3 show enhanced activity during El Niño phase, whereas TCs in cluster 2 are enhanced during La Niña and neutral phases. In addition to being modulated by ENSO, TCs in clusters 2 and 3 show statistically significant modulation at an intraseasonal timescale due to the Madden–Julian Oscillation (MJO) phenomenon. There are also some indications through sophisticated Bayesian modelling that TCs in clusters 2 and 3 are slightly influenced by the Interdecadal Pacific Oscillation (IPO). These results can have substantial implications for cluster-specific development of TC prediction schemes for the SI region. © 2022 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society.
Subseasonal prediction framework for tropical cyclone activity in the Solomon Islands region
- Haruhiru, Alick, Chand, Savin, Sultanova, Nargiz, Ramsay, Hamish, Sharma, Krishneel, Tahani, Lloyd
- Authors: Haruhiru, Alick , Chand, Savin , Sultanova, Nargiz , Ramsay, Hamish , Sharma, Krishneel , Tahani, Lloyd
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Climatology Vol. 43, no. 12 (2023), p. 5763-5777
- Full Text:
- Reviewed:
- Description: Recently, we developed seasonal prediction schemes with improved skill to predict tropical cyclone (TC) activity up to 3 months in advance for the Solomon Islands (SI) region (5°–15°S, 155°–170°E) using sophisticated Bayesian regression techniques. However, TC prediction at subseasonal timescale (i.e., 1–4 weeks in advance) is not being researched for that region despite growing demands from decision makers at sectoral level. In this paper, we first assess the feasibility of developing subseasonal prediction frameworks for the SI region using a pool of predictors that are known to affect TC activity in the region. We then evaluate multiple predictor combinations to develop the most appropriate models using a statistical approach to forecast weekly TC activity up to 4 weeks in advance. Predictors used include indices of various natural climate variability modes, namely the Madden–Julian Oscillation (MJO), the El Niño–Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and the Interdecadal Pacific Oscillation (IPO). These modes often have robust physical and statistical relationships with TC occurrences in the SI region and the broader southwest Pacific territory as shown by preceding studies. Additionally, we incorporate TC seasonality as a potential predictor given the persistence of TCs occurring more in certain months than others. Note that a model with seasonality predictor alone (hereafter called the “climatology” model) forms a baseline for comparisons. The hindcast verifications of the forecasts using leave-one-out cross-validation procedure over the study period 1975–2019 indicate considerable improvements in prediction skill of our logistic regression models over climatology, even up to 4 weeks in advance. This study sets the foundation for introducing subseasonal prediction services, which is a national priority for improved decision making in sectors like agriculture and food security, water, health and disaster risk mitigation in the Solomon Islands. © 2023 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society.
- Authors: Haruhiru, Alick , Chand, Savin , Sultanova, Nargiz , Ramsay, Hamish , Sharma, Krishneel , Tahani, Lloyd
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Climatology Vol. 43, no. 12 (2023), p. 5763-5777
- Full Text:
- Reviewed:
- Description: Recently, we developed seasonal prediction schemes with improved skill to predict tropical cyclone (TC) activity up to 3 months in advance for the Solomon Islands (SI) region (5°–15°S, 155°–170°E) using sophisticated Bayesian regression techniques. However, TC prediction at subseasonal timescale (i.e., 1–4 weeks in advance) is not being researched for that region despite growing demands from decision makers at sectoral level. In this paper, we first assess the feasibility of developing subseasonal prediction frameworks for the SI region using a pool of predictors that are known to affect TC activity in the region. We then evaluate multiple predictor combinations to develop the most appropriate models using a statistical approach to forecast weekly TC activity up to 4 weeks in advance. Predictors used include indices of various natural climate variability modes, namely the Madden–Julian Oscillation (MJO), the El Niño–Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and the Interdecadal Pacific Oscillation (IPO). These modes often have robust physical and statistical relationships with TC occurrences in the SI region and the broader southwest Pacific territory as shown by preceding studies. Additionally, we incorporate TC seasonality as a potential predictor given the persistence of TCs occurring more in certain months than others. Note that a model with seasonality predictor alone (hereafter called the “climatology” model) forms a baseline for comparisons. The hindcast verifications of the forecasts using leave-one-out cross-validation procedure over the study period 1975–2019 indicate considerable improvements in prediction skill of our logistic regression models over climatology, even up to 4 weeks in advance. This study sets the foundation for introducing subseasonal prediction services, which is a national priority for improved decision making in sectors like agriculture and food security, water, health and disaster risk mitigation in the Solomon Islands. © 2023 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society.
Tropical cyclones and depressions over the South Pacific Ocean since the late 19th century : assessing synergistic relationship between the El Niño Southern Oscillation and Interdecadal Pacific Oscillation
- Yeasmin, Alea, Chand, Savin, Sultanova, Nargiz
- Authors: Yeasmin, Alea , Chand, Savin , Sultanova, Nargiz
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Climatology Vol. 43, no. 12 (2023), p. 5422-5443
- Full Text:
- Reviewed:
- Description: Tropical cyclones (TCs) and tropical depressions (TDs), hereafter collectively referred to as tropical storms, often exhibit large year-to-year variability in the South Pacific Ocean basin. Many past studies have examined this variability in relation to the El Niño Southern Oscillation (ENSO) phenomenon, particularly using observational data from the post-satellite era (i.e., after the 1970s when TC observations became more consistent). However, less emphasis is placed on how tropical storms are modulated at interdecadal and decadal time scales such as due to Interdecadal Pacific Oscillation (IPO). This is because post-satellite data are available for relatively short time period (i.e., post-1970s), limiting our understanding of the IPO–TC relationship in the South Pacific. Here, using NOAA-CIRES 20th Century Reanalysis (20CR) dataset, we reconstruct historical records (1871–2014) of TC and depression proxies for the South Pacific Ocean basin, and then utilize these reconstructed proxies to first understand the connections between TC–ENSO and TC–IPO over the 20th century, and then investigate the combined effects of ENSO–IPO effects on TCs and depressions. Results show that La Niña (El Niño) is more dominant on TC activity than El Niño (La Niña) over the western subregion 140–170° E (eastern sub-region, 170–220° E) as expected. We also show that TC numbers are strongly modulated by the IPO phenomenon with, on average, more TCs occurring during the positive phase than during the negative phase of the IPO in both western and eastern sub-regions. We show for the first time (using a long-term reconstructed TC dataset) that the combined phases of El Niño and + IPO account for increased TC activity, as opposed to the combined phase of La Niña and
- Authors: Yeasmin, Alea , Chand, Savin , Sultanova, Nargiz
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Climatology Vol. 43, no. 12 (2023), p. 5422-5443
- Full Text:
- Reviewed:
- Description: Tropical cyclones (TCs) and tropical depressions (TDs), hereafter collectively referred to as tropical storms, often exhibit large year-to-year variability in the South Pacific Ocean basin. Many past studies have examined this variability in relation to the El Niño Southern Oscillation (ENSO) phenomenon, particularly using observational data from the post-satellite era (i.e., after the 1970s when TC observations became more consistent). However, less emphasis is placed on how tropical storms are modulated at interdecadal and decadal time scales such as due to Interdecadal Pacific Oscillation (IPO). This is because post-satellite data are available for relatively short time period (i.e., post-1970s), limiting our understanding of the IPO–TC relationship in the South Pacific. Here, using NOAA-CIRES 20th Century Reanalysis (20CR) dataset, we reconstruct historical records (1871–2014) of TC and depression proxies for the South Pacific Ocean basin, and then utilize these reconstructed proxies to first understand the connections between TC–ENSO and TC–IPO over the 20th century, and then investigate the combined effects of ENSO–IPO effects on TCs and depressions. Results show that La Niña (El Niño) is more dominant on TC activity than El Niño (La Niña) over the western subregion 140–170° E (eastern sub-region, 170–220° E) as expected. We also show that TC numbers are strongly modulated by the IPO phenomenon with, on average, more TCs occurring during the positive phase than during the negative phase of the IPO in both western and eastern sub-regions. We show for the first time (using a long-term reconstructed TC dataset) that the combined phases of El Niño and + IPO account for increased TC activity, as opposed to the combined phase of La Niña and
Characterizing Australia's east coast cyclones (1950–2019)
- Gray, Jessie, Verdon-Kidd, Danielle, Jaffrés, Jasmine, Hewson, Michael, Clarke, John, Sharma, Krishneel, English, Nathan
- Authors: Gray, Jessie , Verdon-Kidd, Danielle , Jaffrés, Jasmine , Hewson, Michael , Clarke, John , Sharma, Krishneel , English, Nathan
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Climatology Vol. 43, no. 7 (2023), p. 3324-3352
- Full Text:
- Reviewed:
- Description: East coast cyclones (ECCs) provide an essential reprieve from dry periods across eastern Australia. They also deliver flood-producing rains with significant economic, social and environmental impacts. Assessing and comparing the influence of different types of cyclones is hindered by an incomplete understanding of ECC typology, given their widely variable spatial and temporal characteristics. This study employs a track-clustering method (probabilistic, curve-aligned regression model) to identify key cyclonic pathways for ECCs from 1950 to 2019. Six spatially independent clusters were successfully distinguished and further sub-classified (coastal, continental and tropical) based on their genesis location. The seasonality and long-term variability, intensity (maximum Laplacian value ± 2 days) and event-based rainfall were then evaluated for each cluster to quantify the impact of these lows on Australia. The highest quantity of land-based rainfall per event is associated with the tropical cluster (Cluster 6), whereas widespread rainfall was also found to occur in the two continental clusters (clusters 4 and 5). Cyclone tracks orientated close to the coast (clusters 1, 2 and 3) were determined to be the least impactful in terms of rainfall and intensity, despite being the most common cyclone type. In terms of interannual variability, sea surface temperature anomalies suggest an increased cyclone frequency for clusters 1 (austral winter) and 4 (austral spring) during a central Pacific El Niño. Furthermore, cyclone incidence during IOD-negative conditions was more pronounced in winter for clusters 1, 2, 3— and clusters 4 and 5 in spring. All cyclones also predominantly occurred in SAM-positive conditions. However, winter ECCs for clusters 1 and 3 had a higher frequency in SAM-negative. This new typology of ECCs via spatial clustering provides crucial insights into the systems that produce extreme rainfall across eastern Australia and should be used to inform future hazard management of cyclone events. © 2023 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society.
- Authors: Gray, Jessie , Verdon-Kidd, Danielle , Jaffrés, Jasmine , Hewson, Michael , Clarke, John , Sharma, Krishneel , English, Nathan
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Climatology Vol. 43, no. 7 (2023), p. 3324-3352
- Full Text:
- Reviewed:
- Description: East coast cyclones (ECCs) provide an essential reprieve from dry periods across eastern Australia. They also deliver flood-producing rains with significant economic, social and environmental impacts. Assessing and comparing the influence of different types of cyclones is hindered by an incomplete understanding of ECC typology, given their widely variable spatial and temporal characteristics. This study employs a track-clustering method (probabilistic, curve-aligned regression model) to identify key cyclonic pathways for ECCs from 1950 to 2019. Six spatially independent clusters were successfully distinguished and further sub-classified (coastal, continental and tropical) based on their genesis location. The seasonality and long-term variability, intensity (maximum Laplacian value ± 2 days) and event-based rainfall were then evaluated for each cluster to quantify the impact of these lows on Australia. The highest quantity of land-based rainfall per event is associated with the tropical cluster (Cluster 6), whereas widespread rainfall was also found to occur in the two continental clusters (clusters 4 and 5). Cyclone tracks orientated close to the coast (clusters 1, 2 and 3) were determined to be the least impactful in terms of rainfall and intensity, despite being the most common cyclone type. In terms of interannual variability, sea surface temperature anomalies suggest an increased cyclone frequency for clusters 1 (austral winter) and 4 (austral spring) during a central Pacific El Niño. Furthermore, cyclone incidence during IOD-negative conditions was more pronounced in winter for clusters 1, 2, 3— and clusters 4 and 5 in spring. All cyclones also predominantly occurred in SAM-positive conditions. However, winter ECCs for clusters 1 and 3 had a higher frequency in SAM-negative. This new typology of ECCs via spatial clustering provides crucial insights into the systems that produce extreme rainfall across eastern Australia and should be used to inform future hazard management of cyclone events. © 2023 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society.
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