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A kernel density estimation approach and statistical generalized additive model of Western North Pacific typhoon activities

- Wang, Xiang, Wahiduzzaman, Md, Yeasmin, Alea

  • Authors: Wang, Xiang , Wahiduzzaman, Md , Yeasmin, Alea
  • Date: 2022
  • Type: Text , Journal article
  • Relation: Atmosphere Vol. 13, no. 7 (2022), p.
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  • Description: This paper presents a development of a statistical model of typhoon genesis, tracks based on kernel density estimation and a generalized additive model (GAM). Modeling of typhoon activity is ultimately beneficial to the people living in coastal zones, insurance/re-insurance companies, policy, planning and decision departments. A 50-year record (1972–2021) of typhoon track observations from the International Best Track Archive Climate Stewardship have been used to observe the distribution of typhoon genesis by kernel density estimation. The tracks are simulated through the development of a GAM. It reproduces the observation well. A distance calculation approach between observed and simulated tracks’ landfall have been used to validate the model and the model shows a very good skill (approximately 75%). © 2022 by the authors.

Detection and verification of tropical cyclones and depressions over the South Pacific Ocean basin using ERA-5 reanalysis dataset

- 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

Seasonal movement prediction of tropical cyclone over the North Indian Ocean by using atmospheric climate variables in statistical models

- Wahiduzzaman, Md, Yeasmin, Alea, Luo, Jing-Jia

  • Authors: Wahiduzzaman, Md , Yeasmin, Alea , Luo, Jing-Jia
  • Date: 2020
  • Type: Text , Journal article
  • Relation: Atmospheric Research Vol. 245, no. (2020), p. 1-13
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  • Description: In this study, the contribution of atmospheric climate variables to the prediction skill of tropical cyclone (TC) activity over the North Indian Ocean (NIO) has been investigated. Statistical forecast models are developed through generalised linear model (GLM) and generalised additive model (GAM) for tropical cyclone trajectories over the NIO using atmospheric climate variables as predictors. TC from the Joint Typhoon Warning Centre and sets of climate predictor data were analysed for a period of 35-year (1979-2013). The velocity field is predicted by fitting GAM in each month and season. Hindcast validation method is applied to assess the reliability of the model. The skill of the GAM model is compared with GLM and found to be more successful in forecasting TC movement over the NIO region.
  • Description: M.Wahiduzzaman has been supported by Nanjing University of Information Science and Technology, China postdoctoral fellowship fund. Authors are grateful to three anonymous reviewers for their input which improved the quality of the manuscript.

Spatial modelling of bacterial diversity over the selected regions in Bangladesh by next-generation sequencing : role of water temperature

- Akter, Nabila, Wahiduzzaman, Md, Yeasmin, Alea, Islam, Kazi, Luo, Jing-Jia

  • Authors: Akter, Nabila , Wahiduzzaman, Md , Yeasmin, Alea , Islam, Kazi , Luo, Jing-Jia
  • Date: 2020
  • Type: Text , Journal article
  • Relation: Applied Sciences (Switzerland) Vol. 10, no. 7 (2020), p.
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  • Description: In this study, a spatial model has been developed to investigate the role of water temperature to the distribution of bacteria over the selected regions in the Bay of Bengal, located in the southern region of Bangladesh using next-generation sequencing. Bacterial concentration, quantitative polymerase chain reactions, and sequencing were performed on water samples and identified Acidobacteria, Actinobacteria, Bacteroidetes, Chlorobi, Chloroflexi, Cyanobacteria, Firmicutes, Nitrospirae, Planctomycetes, Proteobacteria, and Verrucomicrobia. The spatial model tessellated the parts of the Bay of Bengal with hexagons and analyzed the relationship between the distribution of bacteria and water temperature. A geographically weighted regression was used to observe whether water temperature contributed strongly or weakly to the distribution of bacteria. The residuals were examined to assess the model's fitness. The spatial model has the potential to predict the bacterial diversity in the selected regions of Bangladesh. © 2020 by the authors.

Statistical forecasting of tropical cyclone landfall activities over the North Indian Ocean rim countries

- Wahiduzzaman, Md, Yeasmin, Alea

  • Authors: Wahiduzzaman, Md , Yeasmin, Alea
  • Date: 2019
  • Type: Text , Journal article
  • Relation: Atmospheric Research Vol. 227, no. (2019), p. 89-100
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  • Description: This paper investigates the forecast potential of tropical cyclone (TC)landfall probabilities over the North Indian Ocean (NIO)rim countries using ocean-climate predictor variables in a new statistical seasonal forecast model. A Poisson regression model was used to predict the landfall probabilities for a period of 35 years of TC observations (1979–2013)from the Joint Typhoon Warning Center and the predictor variables include sea surface temperature, Southern Oscillation Index and ocean heat content. Poisson regression was found skilful in hindcasting of tropical cyclone landfall frequency for the NIO region with a correlation coefficient in the forecasted hindcast time series of 0.65 and 31% improvement above climatology. In the present study, genesis was modelled by kernel density estimation, tracks were fitted using a generalised additive model (GAM)approach with a Euler integration step, and landfall location was estimated using a country mask. This GAM model that is previously demonstrated very skilful to simulate TC landfall across the NIO rim countries by Wahiduzzaman et al. (2017, 2019)deems skilful for this study. © 2019 Elsevier B.V.
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