North Indian ocean tropical cyclone activity in CMIP5 experiments : future projections using a model-independent detection and tracking scheme
- Bell, Samuel, Chand, Savin, Tory, Kevin, Ye, Hua, Turville, Christopher
- Authors: Bell, Samuel , Chand, Savin , Tory, Kevin , Ye, Hua , Turville, Christopher
- Date: 2020
- Type: Text , Journal article
- Relation: International Journal of Climatology Vol. 40, no. 15 (2020), p. 6492-6505
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- Description: The sensitivity of tropical cyclone (TC) projection results to different models and the detection and tracking scheme used is well established. In this study, future climate projections of TC activity in the North Indian Ocean (NIO) are assessed with a model- and basin-independent detection and tracking scheme. The scheme is applied to selected models from the coupled model intercomparison project phase 5 (CMIP5) experiments forced under the historical and representative concentration pathway 8.5 (RCP8.5) conditions. Most models underestimated the frequency of early season (April–June) TCs and contained genesis biases equatorward of ~7.5°N in comparison to the historical records. TC tracks detected in reanalysis and model data were input to a clustering algorithm simultaneously, with two clusters in the Arabian Sea and two in the Bay of Bengal (k = 4). Projection results indicated a slight decrease of overall TC genesis frequency in the NIO, with an increase of TC genesis frequency in the Arabian Sea (30–64%) and a decrease in the Bay of Bengal (22–43%), consistent between clusters in each of these sub-regions. These changes were largely due to changes in the pre-monsoon season (April–June) where Bay of Bengal TCs significantly decreased, consistent with changes in vertical ascent. Northern Arabian Sea TCs significantly increased during the pre-monsoon season, consistent with changes in vertical wind shear and relative humidity. There was a projected increase of TC frequency in the post-monsoon season (October–December), consistent with changes in relative humidity and vertical ascent, although not all clusters followed this trend; noting a different response in the southern Bay of Bengal. In turn, these projections caused changes to the climate averaged TC track density, including a decrease (up to 2 TCs per decade) affecting the eastern coast of India and a small increase (up to 0.5 TCs per decade) affecting eastern Africa, Oman and Yemen. © 2020 Royal Meteorological Society
- Authors: Bell, Samuel , Chand, Savin , Tory, Kevin , Ye, Hua , Turville, Christopher
- Date: 2020
- Type: Text , Journal article
- Relation: International Journal of Climatology Vol. 40, no. 15 (2020), p. 6492-6505
- Full Text:
- Reviewed:
- Description: The sensitivity of tropical cyclone (TC) projection results to different models and the detection and tracking scheme used is well established. In this study, future climate projections of TC activity in the North Indian Ocean (NIO) are assessed with a model- and basin-independent detection and tracking scheme. The scheme is applied to selected models from the coupled model intercomparison project phase 5 (CMIP5) experiments forced under the historical and representative concentration pathway 8.5 (RCP8.5) conditions. Most models underestimated the frequency of early season (April–June) TCs and contained genesis biases equatorward of ~7.5°N in comparison to the historical records. TC tracks detected in reanalysis and model data were input to a clustering algorithm simultaneously, with two clusters in the Arabian Sea and two in the Bay of Bengal (k = 4). Projection results indicated a slight decrease of overall TC genesis frequency in the NIO, with an increase of TC genesis frequency in the Arabian Sea (30–64%) and a decrease in the Bay of Bengal (22–43%), consistent between clusters in each of these sub-regions. These changes were largely due to changes in the pre-monsoon season (April–June) where Bay of Bengal TCs significantly decreased, consistent with changes in vertical ascent. Northern Arabian Sea TCs significantly increased during the pre-monsoon season, consistent with changes in vertical wind shear and relative humidity. There was a projected increase of TC frequency in the post-monsoon season (October–December), consistent with changes in relative humidity and vertical ascent, although not all clusters followed this trend; noting a different response in the southern Bay of Bengal. In turn, these projections caused changes to the climate averaged TC track density, including a decrease (up to 2 TCs per decade) affecting the eastern coast of India and a small increase (up to 0.5 TCs per decade) affecting eastern Africa, Oman and Yemen. © 2020 Royal Meteorological Society
- Yeasmin, Alea, Chand, Savin, Turville, Christopher, Sultanova, Nargiz
- Authors: Yeasmin, Alea , Chand, Savin , Turville, Christopher , Sultanova, Nargiz
- Date: 2021
- Type: Text , Journal article
- Relation: International Journal of Climatology Vol. 41, no. 11 (2021), p. 5318-5330
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- Description: Tropical cyclones (TCs) are one of the most destructive synoptic systems and can cause enormous loss of life and property damages in the South Pacific island nations. The impact of tropical depressions (TDs, i.e. weaker systems that do not develop into TCs) can also be staggering in the region in terms of heavy flooding and landslides, but a lack of complete records often hinders research involving TD impacts. A methodology has been developed here to detect TDs in the ERA-5 reanalysis dataset (the fifth generation ECMWF atmospheric reanalysis of the global climate) using the Okubo–Weiss–Zeta parameter (OWZP) detection scheme. The new South Pacific Enhanced Archive for Tropical Cyclones dataset (SPEArTC), the Dvorak analysis of satellite-based cloud patterns over the South Pacific Ocean basin, and a rainfall dataset for various stations and historical archives have been utilized to validate ERA5-derived TCs and TDs for the period between 1979 and 2019. Results indicate that the OWZP method shows substantial skill in capturing the realistic climatological distribution of TDs (as well as TCs) for the South Pacific Ocean in the ERA5 reanalysis, paving a way forward for future climatological studies involving the impacts of TCs and TDs over the island nations using longer-term reanalyses products such as the 20th-century reanalysis dataset that extends back to the 1850s. © 2021 Royal Meteorological Society
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
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- 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
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- 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
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- 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
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