Projections of southern hemisphere tropical cyclone track density using CMIP5 models
- Bell, Samuel, Chand, Savin, Tory, Kevin, Dowdy, Andrew, Turville, Christopher, Ye, Harvey
- Authors: Bell, Samuel , Chand, Savin , Tory, Kevin , Dowdy, Andrew , Turville, Christopher , Ye, Harvey
- Date: 2019
- Type: Text , Journal article
- Relation: Climate Dynamics Vol. 52, no. 9-10 (2019), p. 6065-6079
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- Description: A recently validated algorithm for detecting and tracking tropical cyclones (TCs) in coarse resolution climate models was applied to a selected group of 12 models from the Coupled Model Intercomparison Project (CMIP5) to assess potential changes in TC track characteristics in the Southern Hemisphere (SH) due to greenhouse warming. Current-climate simulations over the period 1970–2000 are first evaluated against observations using measures of TC genesis location and frequency, as well as track trajectory and lifetime in seven objectively defined genesis regions. The 12-model (12-M) ensemble showed substantial skill in reproducing a realistic TC climatology over the evaluation period. To address potential biases associated with model interdependency, analyses were repeated with an ensemble of five independent models (5-M). Results from both the 12-M and 5-M ensembles were very similar, instilling confidence in the models for climate projections if the current TC-climate relationship is to remain stationary. Projected changes in TC track density between the current- and future-climate (2070–2100) simulations under the Representatives Concentration 8.5 Pathways (RCP8.5) are also assessed. Overall, projection results showed a substantial decrease (~ 1–3 per decade) in track density over most parts of the SH by the end of the twenty-first century. This decrease is attributed to a significant reduction in TC numbers (~ 15–42%) consistent with changes in large-scale environmental parameters such as relative vorticity, environmental vertical wind shear and relative humidity. This study may assist with adaption pathways and implications for regional-scale climate change for vulnerable regions in the SH.
- Authors: Bell, Samuel , Chand, Savin , Tory, Kevin , Dowdy, Andrew , Turville, Christopher , Ye, Harvey
- Date: 2019
- Type: Text , Journal article
- Relation: Climate Dynamics Vol. 52, no. 9-10 (2019), p. 6065-6079
- Full Text:
- Reviewed:
- Description: A recently validated algorithm for detecting and tracking tropical cyclones (TCs) in coarse resolution climate models was applied to a selected group of 12 models from the Coupled Model Intercomparison Project (CMIP5) to assess potential changes in TC track characteristics in the Southern Hemisphere (SH) due to greenhouse warming. Current-climate simulations over the period 1970–2000 are first evaluated against observations using measures of TC genesis location and frequency, as well as track trajectory and lifetime in seven objectively defined genesis regions. The 12-model (12-M) ensemble showed substantial skill in reproducing a realistic TC climatology over the evaluation period. To address potential biases associated with model interdependency, analyses were repeated with an ensemble of five independent models (5-M). Results from both the 12-M and 5-M ensembles were very similar, instilling confidence in the models for climate projections if the current TC-climate relationship is to remain stationary. Projected changes in TC track density between the current- and future-climate (2070–2100) simulations under the Representatives Concentration 8.5 Pathways (RCP8.5) are also assessed. Overall, projection results showed a substantial decrease (~ 1–3 per decade) in track density over most parts of the SH by the end of the twenty-first century. This decrease is attributed to a significant reduction in TC numbers (~ 15–42%) consistent with changes in large-scale environmental parameters such as relative vorticity, environmental vertical wind shear and relative humidity. This study may assist with adaption pathways and implications for regional-scale climate change for vulnerable regions in the SH.
Review of tropical cyclones in the Australian region : Climatology, variability, predictability, and trends
- Chand, Savin, Dowdy, Andrew, Ramsay, Hamish, Walsh, Kevin, Tory, Kevin, Power, Scott, Bell, Samuel, Lavender, Sally, Ye, Hua, Kuleshov, Yuri
- Authors: Chand, Savin , Dowdy, Andrew , Ramsay, Hamish , Walsh, Kevin , Tory, Kevin , Power, Scott , Bell, Samuel , Lavender, Sally , Ye, Hua , Kuleshov, Yuri
- Date: 2019
- Type: Text , Journal article , Review
- Relation: Wiley Interdisciplinary Reviews: Climate Change Vol. 10, no. 5 (2019), p. 1-17
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- Description: Tropical cyclones (TCs) can have severe impacts on Australia. These include extreme rainfall and winds, and coastal hazards such as destructive waves, storm surges, estuarine flooding, and coastal erosion. Various aspects of TCs in the Australian region have been documented over the past several decades. In recent years, increasing emphasis has been placed on human-induced climate change effects on TCs in the Australian region and elsewhere around the globe. However, large natural variability and the lack of consistent long-term TC observations have often complicated the detection and attribution of TC trends. Efforts have been made to improve TC records for Australia over the past decades, but it is still unclear whether such records are sufficient to provide better understanding of the impacts of natural climate variability and climate change. It is important to note that the damage costs associated with tropical cyclones in Australia have increased in recent decades and will continue to increase due to growing coastal settlement and infrastructure development. Therefore, it is critical that any coastal infrastructure planning and engineering decisions, as well as disaster management decisions, strongly consider future risks from tropical cyclones. A better understanding of tropical cyclones in a changing climate will provide key insights that can help mitigate impacts of tropical cyclones on vulnerable communities. An objective assessment of the Australian TCs at regional scale and its link with climate variability and change using improved and up-to-date data records is more imperative now than before. This article is categorized under: Paleoclimates and Current Trends > Modern Climate Change.
- Authors: Chand, Savin , Dowdy, Andrew , Ramsay, Hamish , Walsh, Kevin , Tory, Kevin , Power, Scott , Bell, Samuel , Lavender, Sally , Ye, Hua , Kuleshov, Yuri
- Date: 2019
- Type: Text , Journal article , Review
- Relation: Wiley Interdisciplinary Reviews: Climate Change Vol. 10, no. 5 (2019), p. 1-17
- Full Text:
- Reviewed:
- Description: Tropical cyclones (TCs) can have severe impacts on Australia. These include extreme rainfall and winds, and coastal hazards such as destructive waves, storm surges, estuarine flooding, and coastal erosion. Various aspects of TCs in the Australian region have been documented over the past several decades. In recent years, increasing emphasis has been placed on human-induced climate change effects on TCs in the Australian region and elsewhere around the globe. However, large natural variability and the lack of consistent long-term TC observations have often complicated the detection and attribution of TC trends. Efforts have been made to improve TC records for Australia over the past decades, but it is still unclear whether such records are sufficient to provide better understanding of the impacts of natural climate variability and climate change. It is important to note that the damage costs associated with tropical cyclones in Australia have increased in recent decades and will continue to increase due to growing coastal settlement and infrastructure development. Therefore, it is critical that any coastal infrastructure planning and engineering decisions, as well as disaster management decisions, strongly consider future risks from tropical cyclones. A better understanding of tropical cyclones in a changing climate will provide key insights that can help mitigate impacts of tropical cyclones on vulnerable communities. An objective assessment of the Australian TCs at regional scale and its link with climate variability and change using improved and up-to-date data records is more imperative now than before. This article is categorized under: Paleoclimates and Current Trends > Modern Climate Change.
- Chand, Savin, Dowdy, Andrew, Bell, Samuel, Tory, Kevin
- Authors: Chand, Savin , Dowdy, Andrew , Bell, Samuel , Tory, Kevin
- Date: 2020
- Type: Text , Book chapter
- Relation: Springer Climate p. 251-273
- Full Text: false
- Reviewed:
- Description: Impacts of tropical cyclones in the South Pacific Island countries are of great significance. Now with the growing threats from human-induced climate change, the need for effective disaster risk management and adaptation strategies for these island countries is more important than before. In order to implement appropriate strategies, a comprehensive understanding of South Pacific tropical cyclone activity—and how it is likely to change as a result of human-induced climate change—is essential. While a number of past studies have examined various aspects of tropical cyclone activity in the South Pacific basin, a review that consolidates those studies with new information is essential. In this chapter, we first examine tropical cyclone data quality for the South Pacific basin and then review the robustness of the relationship between South Pacific tropical cyclones and drivers of natural climate variability. Note that an understanding of the limitations of the data quality is important to determine the extent of natural climate variability and signatures—if any—of human-induced climate change on tropical cyclones. We then examine the influence of climate change on tropical cyclones using up-to-date historical observations and climate model projections. © Springer Nature Switzerland AG 2020.
Declining tropical cyclone frequency under global warming
- Chand, Savin, Walsh, Kevin, Camargo, Suzana, Kossin, James, Tory, Kevin, Wehner, Michael, Chan, Johnny, Klotzbach, Philip, Dowdy, Andrew, Bell, Samuel, Ramsay, Hamish, Murakami, Hiroyuki
- Authors: Chand, Savin , Walsh, Kevin , Camargo, Suzana , Kossin, James , Tory, Kevin , Wehner, Michael , Chan, Johnny , Klotzbach, Philip , Dowdy, Andrew , Bell, Samuel , Ramsay, Hamish , Murakami, Hiroyuki
- Date: 2022
- Type: Text , Journal article
- Relation: Nature Climate Change Vol. 12, no. 7 (2022), p. 655-661
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- Description: Assessing the role of anthropogenic warming from temporally inhomogeneous historical data in the presence of large natural variability is difficult and has caused conflicting conclusions on detection and attribution of tropical cyclone (TC) trends. Here, using a reconstructed long-term proxy of annual TC numbers together with high-resolution climate model experiments, we show robust declining trends in the annual number of TCs at global and regional scales during the twentieth century. The Twentieth Century Reanalysis (20CR) dataset is used for reconstruction because, compared with other reanalyses, it assimilates only sea-level pressure fields rather than utilize all available observations in the troposphere, making it less sensitive to temporal inhomogeneities in the observations. It can also capture TC signatures from the pre-satellite era reasonably well. The declining trends found are consistent with the twentieth century weakening of the Hadley and Walker circulations, which make conditions for TC formation less favourable. © 2022, The Author(s).
- Authors: Chand, Savin , Walsh, Kevin , Camargo, Suzana , Kossin, James , Tory, Kevin , Wehner, Michael , Chan, Johnny , Klotzbach, Philip , Dowdy, Andrew , Bell, Samuel , Ramsay, Hamish , Murakami, Hiroyuki
- Date: 2022
- Type: Text , Journal article
- Relation: Nature Climate Change Vol. 12, no. 7 (2022), p. 655-661
- Full Text:
- Reviewed:
- Description: Assessing the role of anthropogenic warming from temporally inhomogeneous historical data in the presence of large natural variability is difficult and has caused conflicting conclusions on detection and attribution of tropical cyclone (TC) trends. Here, using a reconstructed long-term proxy of annual TC numbers together with high-resolution climate model experiments, we show robust declining trends in the annual number of TCs at global and regional scales during the twentieth century. The Twentieth Century Reanalysis (20CR) dataset is used for reconstruction because, compared with other reanalyses, it assimilates only sea-level pressure fields rather than utilize all available observations in the troposphere, making it less sensitive to temporal inhomogeneities in the observations. It can also capture TC signatures from the pre-satellite era reasonably well. The declining trends found are consistent with the twentieth century weakening of the Hadley and Walker circulations, which make conditions for TC formation less favourable. © 2022, The Author(s).
Statistical calibration of long-term reanalysis data for australian fire weather conditions
- Biswas, Soubhik, Chand, Savin, Dowdy, Andrew, Wright, Wendy, Foale, Cameron, Zhao, Xiaohui, Deo, A
- Authors: Biswas, Soubhik , Chand, Savin , Dowdy, Andrew , Wright, Wendy , Foale, Cameron , Zhao, Xiaohui , Deo, A
- Date: 2022
- Type: Text , Journal article
- Relation: Journal of Applied Meteorology and Climatology Vol. 61, no. 6 (2022), p. 729-758
- Full Text: false
- Reviewed:
- Description: Reconstructed weather datasets, such as reanalyses based on model output with data assimilation, often show systematic biases in magnitude when compared with observations. Postprocessing approaches can help adjust the distribution so that the reconstructed data resemble the observed data as closely as possible. In this study, we have compared various statistical bias-correction approaches based on quantile–quantile matching to correct the data from the Twentieth Century Reanalysis, version 2c (20CRv2c), with observation-based data. Methods included in the comparison utilize a suite of different approaches: a linear model, a median-based approach, a nonparametric linear method, a spline-based method, and approaches that are based on the lognormal and Weibull distributions. These methods were applied to daily data in the Australian region for rainfall, maximum temperature, relative humidity, and wind speed. Note that these are the variables required to compute the forest fire danger index (FFDI), widely used in Australia to examine dangerous fire weather conditions. We have compared the relative errors and performances of each method across various locations in Australia and applied the approach with the lowest mean-absolute error across multiple variables to produce a reliable long-term biascorrected FFDI dataset across Australia. The spline-based data correction was found to have some benefits relative to the other methods in better representing the mean FFDI values and the extremes from the observed records for many of the cases examined here. It is intended that this statistical bias-correction approach applied to long-term reanalysis data will help enable new insight on climatological variations in hazardous phenomena, including dangerous wildfires in Australia extending over the past century. © 2022 American Meteorological Society.
Using historical tropical cyclone climate datasets to examine wind speed recurrence for coastal Australia
- Bell, Samuel, Dowdy, Andrew, Ramsay, H., Chand, Savin, Su, C., Ye, Harvey
- Authors: Bell, Samuel , Dowdy, Andrew , Ramsay, H. , Chand, Savin , Su, C. , Ye, Harvey
- Date: 2022
- Type: Text , Journal article
- Relation: Scientific Reports Vol. 12, no. 1 (2022), p.
- Full Text:
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- Description: Likelihood estimates of extreme winds, including those from tropical cyclones (TCs) at certain locations are used to inform wind load standards for structural design. Here, wind speed average recurrence intervals (ARIs) determined from TC climate data dating back to the 1970s in two quantile–quantile adjusted reanalysis datasets (ERA5 and BARRA [1990]), and best-track observations for context, were compared with Standardized ARIs (AS/NZS) across seven tropical and two subtropical Australian inland coastal regions. The novelty of this work lies in determining TC-wind speed ARIs from a range of datasets that are not typically used to evaluate this metric. Inherent differences between the data used to determine the Standard ARIs (large sample size allow for larger extrapolations; GEV function) and TC data ARIs (smaller sample size and less certain data; the more asymptotic Lognormal/Weibull functions are used) led to the use of different extreme value functions. Results indicated that although these are two distinct ways of determining design wind speeds, when they are considered equivalent, there was a moderate reproduction of the ARI curves with respect to the Standard in both reanalysis datasets, suggesting that similar analyses using climate model products can provide useful information on these types of metrics with some caveats. Trends in TC wind strength affecting coastal Australia were also analyzed, indicating a potential slight downtrend in tropical West coast TC wind strength and slight uptrend for tropical East coast TC wind strength, noting considerable uncertainty given the short time period and limitations of data quality including over longer time periods. Such trends are not only limited to the relationship between TC intensity and anthropogenic warming, but also to regional changes in TC frequency and track direction. This could lead to significant trends emerging in regional Australian TC wind gust strength before several decades of warming have occurred. It is hoped that climate models can provide both longer-term and a more homogenous base for these types of evaluations and subsequent projections with respect to climate change simulations. © 2022, Crown.
- Authors: Bell, Samuel , Dowdy, Andrew , Ramsay, H. , Chand, Savin , Su, C. , Ye, Harvey
- Date: 2022
- Type: Text , Journal article
- Relation: Scientific Reports Vol. 12, no. 1 (2022), p.
- Full Text:
- Reviewed:
- Description: Likelihood estimates of extreme winds, including those from tropical cyclones (TCs) at certain locations are used to inform wind load standards for structural design. Here, wind speed average recurrence intervals (ARIs) determined from TC climate data dating back to the 1970s in two quantile–quantile adjusted reanalysis datasets (ERA5 and BARRA [1990]), and best-track observations for context, were compared with Standardized ARIs (AS/NZS) across seven tropical and two subtropical Australian inland coastal regions. The novelty of this work lies in determining TC-wind speed ARIs from a range of datasets that are not typically used to evaluate this metric. Inherent differences between the data used to determine the Standard ARIs (large sample size allow for larger extrapolations; GEV function) and TC data ARIs (smaller sample size and less certain data; the more asymptotic Lognormal/Weibull functions are used) led to the use of different extreme value functions. Results indicated that although these are two distinct ways of determining design wind speeds, when they are considered equivalent, there was a moderate reproduction of the ARI curves with respect to the Standard in both reanalysis datasets, suggesting that similar analyses using climate model products can provide useful information on these types of metrics with some caveats. Trends in TC wind strength affecting coastal Australia were also analyzed, indicating a potential slight downtrend in tropical West coast TC wind strength and slight uptrend for tropical East coast TC wind strength, noting considerable uncertainty given the short time period and limitations of data quality including over longer time periods. Such trends are not only limited to the relationship between TC intensity and anthropogenic warming, but also to regional changes in TC frequency and track direction. This could lead to significant trends emerging in regional Australian TC wind gust strength before several decades of warming have occurred. It is hoped that climate models can provide both longer-term and a more homogenous base for these types of evaluations and subsequent projections with respect to climate change simulations. © 2022, Crown.
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