Tropical Cyclone Research and Review最新文献

In this paper, we summarize findings from the Tenth International Workshop on Tropical Cyclones (IWTC-10) subgroup on operational track forecasting techniques and capability.

The rate of improvement in the accuracy of official forecast tracks (OFTs) appears to be slowing down, at least for shorter lead times, where we may be approaching theoretical limits. Operational agencies continue to use consensus methods to produce the OFT with most continuing to rely on an unweighted consensus of four to nine NWP models. There continues to be limited use of weighted consensus techniques, which is likely a result of the skills and additional maintenance needed to support this approach. Improvements in the accuracy of ensemble mean tracks is leading to increased use of ensemble means in consensus tracks.

Operational agencies are increasingly producing situation-dependent depictions of track uncertainty, rather than relying on a static depiction of track forecast certainty based on accuracy statistics from the preceding 5 years. This trend has been facilitated by the greater availability of ensemble NWP guidance, particularly vortex parameter files, and improved spread in ensembles. Despite improving spread-skill relationships, most ensemble NWP systems remain under spread. Hence many operational centers are looking to leverage “super-ensembles” (ensembles of ensembles) to ensure the full spread of location probability is captured. This is an important area of service development for multi-hazard impact-based warnings as it supports better decision making by emergency managers and the community in the face of uncertainty.

This review summarizes the rapporteur report on tropical cyclone (TC) intensity change from the operational perspective, as presented to the 10th International Workshop on TCs (IWTC-10) held in Bali, Indonesia, from Dec. 5–9, 2022. The accuracy of TC intensity forecasts issued by operational forecast centers depends on three aspects: real-time observations, TC dynamical model forecast guidance, and techniques and methods used by forecasters. The rapporteur report covers the progress made over the past four years (2018–2021) in all three aspects. This review focuses on the progress of dynamical model forecast guidance. The companion paper (Part II) summarizes the advance from operational centers. The dynamical model forecast guidance continues to be the main factor leading to the improvement of operational TC intensity forecasts. Here, we describe recent advances and developments of major operational regional dynamical TC models and their intensity forecast performance, including HWRF, HMON, COAMPS-TC, Met Office Regional Model, CMA-TYM, and newly developed HAFS. The performance of global dynamical models, including NOAA's GFS, Met Office Global Model (MOGM), JMA's GSM, and IFS (ECMWF), has also been improved in recent years due to their increased horizontal and vertical resolution as well as improved data assimilation systems. Recent challenging cases of rapid intensification are presented and discussed.

This contribution summarizes the significant progress in a variety of topic areas related to internal tropical cyclone (TC) intensity change processes over 2018–2022 from the WMO Tenth International Workshop on Tropical Cyclones (IWTC-10). These topic areas include surface and boundary layer processes; TC internal structure and microphysical processes; and, radiation interactions with TCs. Recent studies better frame the uncertainty in the surface drag and enthalpy coefficients at high wind speeds. These parameters greatly impact TC intensity and it is therefore important that more direct measurements of these boundary layer parameters are made. Particularly significant scientific strides have been made in TC boundary layers. These advancements have been achieved through improved coupled models, large-eddy simulations, theoretical advancements, and detailed observations. It is now clear that the research field needs to better represent the eddy viscosity throughout the depth of the boundary layer. Furthermore, detailed study of coherent structures in TC boundary layers will likely be a propitious direction for the research community. Meanwhile, in-depth observational field campaigns and assiduous data analysis have made significant headway into verifying theory and modeling studies of intensification processes related to TC vortex alignment, efficient latent heating distributions, and overall 3D structure. Substantial efforts have also been made to better understand the intricate roles radiative processes play in TC evolution and intensity change. Finally, some promising progress has been made in the development of time-dependent theories of TC intensification and the predictability of internal TC intensity change. Overall, there have been well-earned gains in the understanding of intensity change processes intrinsic to the TC system, but the journey is not complete. This paper highlights some of the most relevant and important research areas that are still shedding new light into internal factors governing TC intensity change.

The Tenth International Workshop on Tropical Cyclones (IWTC-10) occurred from 5 to 9 December 2022 in Bali, Indonesia. This workshop continued the goal of the original IWTC, held in 1985 in Bangkok, Thailand, to bring together forecasters and researchers from countries around the world that are impacted by tropical cyclones (TCs) to discuss the latest research and forecast advances and share best practices to improve TC forecasts globally. The workshops have continued as a regular feature of WMO efforts to encourage the advancement of TC forecasting and improve ways of communicating TC hazards to the general public.

Global TC forecasting efforts in the past 10–15 years have emphasized hazards and impacts of landfalling TCs beyond just track and intensity. Additionally, there has been a growing interest in improving the communication of these hazards and impacts, using concepts from social and behavioral sciences, in ways that can lead to effective decision-making from stakeholders (e.g., government officials, emergency managers, media, general public). As such, the theme for IWTC-10 was “Improved TC science and services for better decision-making.” More about this theme, how the workshop was structured around it, and key outcomes from the workshop are discussed in this summary article.

This paper summarizes the progress and activities of tropical cyclone (TC) operational forecast centers during the last four years (2018–2021). It is part II of the review on TC intensity change from the operational perspective in the rapporteur report presented to the 10th International Workshop on TCs (IWTC) held in Bali, Indonesia, from Dec. 5–9, 2022. Part I of the review has focused on the progress of dynamical model forecast guidance. This part discusses the performance of TC intensity and rapid intensification forecasts from several operational centers. It is shown that the TC intensity forecast errors have continued to decrease since the 9th IWTC held in 2018. In particular, the improvement of rapid intensification forecasts has accelerated, compared with years before 2018. Consensus models, operational procedures, tools and techniques, as well as recent challenging cases from 2018 to 2021 identified by operational forecast centers are described. Research needs and recommendations are also discussed.

Southern Malawi is continuously affected by tropical cyclone-related floods (TCRFs), which have negative consequences on households' livelihoods, thereby displacing most households to neighbouring communities of Mozambique. The TCRFs have further threatened national, regional, community, and household food security agenda, which is already constrained by poverty, poor agricultural practices, low use of improved varieties, unaffordable inorganic fertilizers, and fragmenting landholding sizes. Accordingly, households have indigenously engineered resilience-based Sustainable Landscape Management (SLM) practices, like intercropping, agroforestry, cover cropping, and soil and water conservation practices, against the adverse effects of TCRFs on-farm productivity. Hence, this study examines the effect of TCRFs and SLM adoption on-farm productivity. While using rigorous endogenous switching regression econometric tools, the study finds TCRFs reducing farm productivity by 27 percent. After SLM adoption, the study observes farm productivity enhancement by 29–126 percent when households adopt at least one SLM practices under varying degrees of TCRFs. Despite the highlighted advantages of SLM adoption, female farmers are less likely to adopt SLM practices because they do not have access to productive resources. Hence, the study proposes the need of gender targeted extension services, accompanied by some seed capital for SLM adoption. Besides, there is need to sensitize farmers on the complementarities between inorganic fertilizer and SLM practices. Lastly, future studies should assess the effect of sustained SLM adoption or dis-adoption and input intensification on farm productivity.

Global climate change, climate extremes, and overuse of natural resources are all major contributors to the risk brought on by cyclones. In I West Bengal state of India, the Pathar Pratima Block frequently experiences a variety of risks that result in significant loss of life and livelihood. In order to govern coastal society, it is crucial to measure and map the multi-hazards risk status. To depict the multi-hazards vulnerability and risk status, no cutting-edge models are currently being applied. Predicting distinct physical vulnerabilities is possible using a variety of cutting-edge machine learning techniques. This study set out to precisely describe multi-hazard risk using powerful machine learning methods. This study involved the use of Analytic Hierarchical Analysis and two cutting-edge machine-learning algorithms - Random Forest and Artificial Neural Network, which are yet underutilized in this area. The multi-hazards risk was determined by taking into account six criteria. The southern and eastern regions of the research area are clearly identified by the multi-hazards risk maps as having high to extremely high hazards risk levels. Cyclonic hazards and embankment breaching are the main dominant factors among the multi-hazards. The machine learning approach is the most accurate model for mapping the multi-hazards risk where the ROC result of Random forest and artificial neural network is more than the conventional method AHP. Here RF is the most validated model than the other two. The effectiveness, root mean square error, true skill statistics, Friedman and Wilcoxon rank test, and area under the curve of receiver operating characteristic tests were used to evaluate the prediction capacity of newly constructed models. The RMSE values of 0.24 and 0.26, TSS values of 0.82 and 0.73, and AUC values of 88.20% and 89.10% as produced by RF and ANN models, respectively, were all excellent.

Using the 6-hourly reanalysis data of European Center ERA-Interim with horizontal resolution of 0.25° × 0.25° and hourly typhoon operational data provided by the CMA (China Meteorological Administration), a new high-level environmental field factor is derived, and its application during the recurvature period of No. 14 Typhoon Yagi and No. 18 Typhoon Rumbia in 2018 is compared and analyzed. According to the comparison study, there is always a clear positive abnormal value area of high-level environmental field factor on the northeast of Rumbia during its northward movement, implying an obvious alteration of $\nabla •\overrightarrow{u}$ and a big negative gradient of $\nabla \overrightarrow{u}$ on the northeast of Rumbia. With the eastward movement of the westerly trough and the strengthening of the subtropical westerly jet, Rumbia is expected to veer northeast. However, the change of high-level environmental field factor on the northeast of Yagi is not noticeable, and Yagi is far away from the upper-level jet stream, which is not conducive to Yagi's northeast recurvature.