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Tropical Cyclone Research and Review  
  Tropical Cyclone Research and Review--2020, 9 (2)   Published: 2020-06-15
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Third assessment on impacts of climate change on tropical cyclones in the Typhoon Committee Region - Part II: Future projections

Eun Jeong Cha, Thomas R. Knutson, Tsz-Cheung Lee, Ming Ying, et al.
Tropical Cyclone Research and Review. 2020, 9 (2): 75;  doi: 10.1016/j.tcrr.2020.04.005
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This paper assesses published findings on projections of future tropical cyclone (TC) activity in the ESCAP/WMO Typhoon Committee Region under climate change scenarios. This assessment also estimates the projected changes of key TC metrics for a 2 C anthropogenic global warming scenario for the western North Pacific (WNP) following the approach of a WMO Task Team, together with other reported findings for this region. For projections of TC genesis/frequency, most models suggest a reduction of TC frequency, but an increase in the proportion of very intense TCs over the WNP in the future. However, some individual studies project an increase in WNP TC frequency. Most studies agree on a projected increase of WNP TC intensity over the 21st century. All available projections for TC related precipitation in the WNP indicate an increase in TC related precipitation rate in a warmer climate. Anthropogenic warming may also lead to changes in TC prevailing tracks. A further increase in storm surge risk may result from increases in TC intensity. The most confident aspect of forced anthropogenic change in TC inundation risk derives from the highly confident expectation of further sea level rise, which we expect will exacerbate storm inundation risk in coastal regions, assuming all other factors equal.

Recent advances in research on tropical cyclogenesis

Brian H. Tang, Juan Fang, Alicia Bentley, Gerard Kilroy, et al.
Tropical Cyclone Research and Review. 2020, 9 (2): 87;  doi: 10.1016/j.tcrr.2020.04.004
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This review article summarizes recent (2014 - 2019) advances in our understanding of tropical cyclogenesis, stemming from activities at the ninth International Workshop on Tropical Cyclones. Tropical cyclogenesis involves the interaction of dynamic and thermodynamic processes at multiple spatio-temporal scales. Studies have furthered our understanding of how tropical cyclogenesis may be affected by external processes, such as intraseasonal oscillations, monsoon circulations, the intertropical convergence zone, and midlatitude troughs and cutoff lows. Additionally, studies have furthered our understanding of how tropical cyclogenesis may be affected by internal processes, such as the organization of deep convection; the evolution of the “pouch” structure; the role of friction; the development of the moist, warm core; the importance of surface fluxes; and the role of the mid-level vortex. A relatively recent class of idealized, numerical simulations of tropical cyclogenesis in radiativeconvective equilibrium have highlighted the potential importance of radiative feedbacks on tropical cyclogenesis. We also offer some recommendations to the community on future directions for tropical cyclogenesis research.

Improvements in tropical cyclone forecasting through ensemble prediction system at NCMRWF in India

Anumeha Dube, Raghavendra Ashrit, Sushant Kumar, Ashu Mamgain
Tropical Cyclone Research and Review. 2020, 9 (2): 106;  doi: 10.1016/j.tcrr.2020.04.003
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This paper deals with the comparison of cyclone forecasts from the two versions of the operational global ensemble prediction system (EPS) at the National Centre for Medium Range Weather Forecasting (NEPS). The previous version had a horizontal resolution of 33 km with 44 ensemble members (NEPS) whereas the updated version of this EPS has a resolution of 12 km with 11 members (NEPS-UP). The ensemble mean forecasts from both the models are compared using the direct position (DPE), along (ATE) and cross track (CTE) errors. For the verification of strike probability, Brier Score (BS), Brier Skill Score (BSS), Reliability Diagram, Relative Operating Characteristic (ROC) Curve and Root Mean Square Error (RMSE) in mean Vs Spread in members are used. For verification of intensity, RMSE in maximum wind speed from the ensemble mean forecasts are compared.
Comparison of ensemble mean tracks from both models showed lower errors in NEPS-UP for all forecast lead times. The decrease in the DPE, ATE and CTE in NEPS-UP was around 38%, 48% and 15% respectively. NEPS-UP showed lower BS and higher BSS values indicating a better match between observed frequencies and forecast probabilities as well as higher prediction skills. The reliability diagram showed higher accuracy for NEPS-UP as compared to NEPS. The ROC curves showed that for forecasts with higher probabilities the hit rate was high in NEPSUP. There was a greater consensus between the RMSE and Spread for NEPS-UP at all lead times. It was also seen that the RMSE in mean showed a 41% decrease from NEPS to NEPS-UP. On comparing maximum wind, it was found that for all lead times the RMSE in maximum wind speed for NEPS-UP was lower than NEPS.

Forcing ocean model with atmospheric model outputs to simulate storm surge in the Bangladesh coast

Nabir Mamnun, Lucy M. Bricheno, Md Rashed-Un-Nabi
Tropical Cyclone Research and Review. 2020, 9 (2): 117;  doi: 10.1016/j.tcrr.2020.04.002
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Tropical cyclones are devastating hazards and have been a major problem for the coastal population of Bangladesh. Among the advancements in atmospheric and oceanic prediction, accurate forecasting of storm surges is of specific interest due to their great potential to inflict loss of life and property. For decades, the numerical model based storm surge prediction systems have been an important tool to reduce the loss of human lives and property damage. In order to improve the accuracy in predicting storm surge and coastal inundation, recent model development efforts tended to include more modeling components, such as meteorology model and surface wave model in storm surge modeling. In this study, we used the outputs of an atmospheric model to force the ocean model for simulating storm surges in the Bay of Bengal with particular focus on the Bangladesh coast. The ability of the modeling system was investigated simulating water levels in the Bangladesh coast of two tropical cyclones Sidr (2007) and Aila (2009). The effectiveness of the model was verified through comparing the obtained computational outputs against tide gauge data. The cyclone tracks and intensities reproduced by the atmospheric model were reasonable, though the model had a tendency to overestimate the cyclone intensity during peaks and also close to coast. The water levels are reproduced fairly well by the ocean model, although errors still exist. The root mean square errors in water level at different gauges range from 0.277 to 0.419 m with coefficient of correlation (R2) between 0.64 and 0.97 in case of Sidr and 0.209-0.581 m with R2 0.62 to 0.98 for Aila. The overall coupled modeling system is found to be useful with reasonable accuracy and precision, though there are spaces for improvement. Higher-resolution modeling approaches are recommended to gain more skills.

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