Forecasts Of Tropical Cyclone Activity Research Articles

A Statistical Intraseasonal Prediction Model of Extended Boreal Summer Western North Pacific Tropical Cyclone Genesis

Abstract An L2 regularized logistic regression model is developed in this study to predict weekly tropical cyclone (TC) genesis over the western North Pacific (WNP) Ocean and subregions of the WNP including the South China Sea (SCS), the western WNP (WWNP), and the eastern WNP (EWNP). The potential predictors for the TC genesis model include a time-varying TC genesis climatology, the Madden–Julian oscillation (MJO), the quasi-biweekly oscillation (QBWO), and ENSO. The relative importance of the predictors in a constructed L2 regression model is justified by a forward stepwise selection procedure for each region from a 0-week to a 7-week lead. Cross-validated hindcasts are then generated for the corresponding prediction schemes out to a 7-week lead. The TC genesis climatology generally improves the regional model skill, and the importance of intraseasonal oscillations and ENSO is regionally dependent. Over the WNP, there is increased model skill over the time-varying climatology in predicting weekly TC genesis out to a 4-week lead by including the MJO and QBWO, whereas ENSO has a limited impact. On a regional scale, ENSO and then either the MJO or QBWO are the two most important predictors over the EWNP and WWNP after the TC genesis climatology. The MJO is found to be the most important predictor over the SCS. The logistic regression model is shown to have comparable reliability and forecast skill scores to the ECMWF dynamical model on intraseasonal time scales. Significance Statement Skillful forecasts of tropical cyclone activity on time scales from short-range to seasonal are now issued operationally. Although there has been great progress in the understanding of physical mechanisms driving tropical cyclone (TC) activity, intraseasonal prediction of TCs remains a significant scientific challenge. This study develops a statistically based intraseasonal model to predict weekly TC genesis over the western North Pacific Ocean basin. The intraseasonal prediction model developed here for TC genesis over the western North Pacific basin shows skill extending out to four weeks. We discuss the regional dependence of the model skill on ENSO and other subseasonal climate oscillations. This approach provides skillful intraseasonal forecasting of TCs over the western North Pacific basin.

Wintertime Rossby Wave Breaking Persistence in Extended-Range Seasonal Forecasts of Atlantic Tropical Cyclone Activity

Abstract In this study, we examine the wintertime environmental precursors of summer anticyclonic wave breaking (AWB) over the North Atlantic region and assess the applicability of these precursors in predicting AWB impacts on seasonal tropical cyclone (TC) activity. We show that predictors representing the environmental impacts of subtropical AWB on seasonal TC activity improve the skill of extended-range seasonal forecasts of TC activity. There is a significant correlation between boreal winter and boreal summer AWB activity via AWB-forced phases of the quasi-stationary North Atlantic Oscillation (NAO). Years with above-normal boreal summer AWB activity over the North Atlantic region also show above-normal AWB activity in the preceding boreal winter that tends to force a positive phase of the NAO that persists through the spring. These conditions are sustained by continued AWB throughout the year, particularly when El Niño–Southern Oscillation plays less of a role at forcing the large-scale circulation. While individual AWB events are synoptic and nonlinear with little predictability beyond 8–10 days, the strong dynamical connection between winter and summer wave breaking lends enough persistence to AWB activity to enable predictability of its potential impacts on TC activity. We find that the winter–summer relationship improves the skill of extended-range seasonal forecasts from as early as an April lead time, particularly for years when wave breaking has played a crucial role in suppressing TC development.

Implementation of Tropical Cyclone Detection Scheme to CCAM model for Seasonel Tropical Cyclone Prediction over the Vietnam East Sea

Implementation of Tropical Cyclone Detection Scheme to CCAM model for Seasonel Tropical Cyclone Prediction over the Vietnam East Sea

Seasonal Forecasts of Tropical Cyclone Activity Over the Western North Pacific: A Review

ABSTRACT The attempt of this article is to provide a literature review on recent development and progress in seasonal forecasts for tropical cyclone (TC) activity over the western North Pacific (WNP). Since the predictability of seasonal TC activity mainly comes from the slowly-evolving sea surface temperature (SST) conditions and the large-scale atmospheric circulation teleconnection patterns, our current understanding on the relationships between the interannual TC variability and tropical SST forcing and variations of various climate modes is first reviewed. It serves as the scientific basis and gives us ideas how predictable the seasonal TC activity is. The main body of the article focuses on an overview of the forecast approaches and methodologies, including statistical and dynamical models and their combination, currently used in seasonal forecasts for TCs over the WNP, and an initial assessment of their prediction skills in the past decade or so. Some outstanding issues, including the intrinsic limitation of predictability due to various uncertainties and the areas for future developments, are also briefly discussed. It is expected that the quality of the scientifically based seasonal TC forecasts would be steadily improved with the advancement in the forecast techniques and the driving of society needs.

Role of ENSO in the interannual relationship between Tibetan Plateau winter snow cover and Northwest Pacific tropical cyclone genesis frequency

Previous studies have revealed a significantly negative correlation between prior winter snow cover over the Tibetan Plateau (TPSC) and tropical cyclone genesis frequency (TCF) over the western North Pacific (WNP) in the following typhoon season. This study revisited this relationship based on long-term observational data. The results showed that the interannual correlation between TCF over the WNP and TPSC experienced a shift in the early 1990s. This correlation is significant during only 1993–2012 and is considerably weak during 1976–1992. The possible reasons causing the shift were examined further, and the results demonstrated that the central Pacific (CP) El Nino-Southern Oscillation (ENSO) has played a vital role in intensifying the interannual relationship between TCF over the WNP and TPSC since the early 1990s. During 1993–2012, TPSC was negatively related to CP ENSO. When TPSC was higher than (lower than) normal, CP ENSO was often in its cold (warm) phase. Such a combination remarkably enhances the relationship of TPSC with the zonal land-sea thermal difference and thus with the summer monsoon over the WNP. Additionally, it enhances the modulation of TPSC on the dynamical environments controlling TCF. As a result, the linkage between TPSC and TCF was significantly strengthened in this period. In sharp contrast, due to the weak relationship between TPSC and ENSO followed by the weak modulation of TPSC on the summer monsoon over the WNP and the dynamical environment during 1976–1992, the linkage between TPSC and TCF was weak during this time period. The results from additional dynamical diagnostic analyses further showed that during 1993–2012 CP ENSO modulated the barotropic energy conversion of zonal winds over the WNP, contributing to the intensified relationship between TPSC and TCF. These results will improve seasonal forecasting of tropical cyclone activity over the WNP.

Seasonal Forecasts of Tropical Cyclone Activity in a High-Atmospheric-Resolution Coupled Prediction System*

Abstract Seasonal forecast skill of the basinwide and regional tropical cyclone (TC) activity in an experimental coupled prediction system based on the ECMWF System 4 is assessed. As part of a collaboration between the Center for Ocean–Land–Atmosphere Studies (COLA) and the ECMWF called Project Minerva, the system is integrated at the atmospheric horizontal spectral resolutions of T319, T639, and T1279. Seven-month hindcasts starting from 1 May for the years 1980–2011 are produced at all three resolutions with at least 15 ensemble members. The Minerva system demonstrates statistically significant skill for retrospective forecasts of TC frequency and accumulated cyclone energy (ACE) in the North Atlantic (NA), eastern North Pacific (EP), and western North Pacific. While the highest scores overall are achieved in the North Pacific, the skill in the NA appears to be limited by an overly strong influence of the tropical Pacific variability. Higher model resolution improves skill scores for the ACE and, to a lesser extent, the TC frequency, even though the influence of large-scale climate variations on these TC activity measures is largely independent of resolution changes. The biggest gain occurs in transition from T319 to T639. Significant skill in regional TC forecasts is achieved over broad areas of the Northern Hemisphere. The highest-resolution hindcasts exhibit additional locations with skill in the NA and EP, including land-adjacent areas. The feasibility of regional intensity forecasts is assessed. In the presence of the coupled model biases, the benefits of high resolution for seasonal TC forecasting may be underestimated.

Seasonal probabilistic forecasting of tropical cyclone activity in the North Indian Ocean

AbstractCoastal flooding due to tropical cyclones (TCs) is a major concern in low‐lying areas of the North Indian Ocean. In the past few years, there have been devastating TCs (e.g. Nargis and Layla in the Bay of Bengal and Gonu in the Arabian Sea) that have galvanised efforts to better understand and forecast such events. Here, we focus on the role of sea‐surface temperature (SST) as a predictor of TC intensification. We develop a statistical downscaling model that identifies patterns of large‐scale SST associated with TC activity in terms of occurrence rate and expected tracks. Finally, we use the Climate Forecast System v2 to construct a probabilistic forecast of TC activity for the coming months/season. We demonstrate that this approach is an integral component of a very early TC warning system.

Seasonal forecasting of tropical cyclone activity in the Australian and the South Pacific Ocean regions

AbstractThe Australian Bureau of Meteorology (Bureau) issues operational tropical cyclone (TC) seasonal forecasts for the Australian region (AR) and the South Pacific Ocean (SPO) and subregions therein. The forecasts are issued in October, ahead of the Southern Hemisphere TC season (November to April). Improvement of operational TC seasonal forecasts can lead to more accurate warnings for coastal communities to prepare for TC hazards. This study investigates the use of support vector regression (SVR) models, exploring new explanatory variables and non-linear relationships between them, the use of model averaging, and lastly the integration of forecast intervals based on a bias-corrected and accelerated non-parametric bootstrap. Hindcasting analyses show that the SVR model outperforms several benchmark methods. Analysis of the generated models shows that the Dipole Mode Index, 5VAR index and the Southern Oscillation Index are the most frequently selected as explanatory variables for TC seasonal forecasting in all regions. The usage of ENSOrelated covariates implies that definitions of regions and subregions may have to be updated to achieve optimal forecasting performance. Overall, the new SVR methodology is an improvement over the current linear discriminant analysis models and has the potential to increase accuracy of TC seasonal forecasts in the AR and SPO.

Seasonal forecasting of tropical cyclone activity in the coastal region of Vietnam using RegCM4.2

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 62:115-129 (2015) - DOI: https://doi.org/10.3354/cr01267 Seasonal forecasting of tropical cyclone activity in the coastal region of Vietnam using RegCM4.2 Tan Phan-Van*, Long Trinh-Tuan, Hai Bui-Hoang, Chanh Kieu Department of Meteorology, VNU Hanoi University of Science, 334 Nguyen Trai, Thanh Xuan, Hanoi, Vietnam *Corresponding author: tanpv@vnu.edu.vn ABSTRACT: This study presents an experimental seasonal forecast of tropical cyclone (TC) activity for Vietnam’s coastal region during the 2012-2013 typhoon seasons, using the Regional Climate Model (RegCM, version 4.2) to downscale the global Climate Forecasting System (CFS) forecast. Using an improved vortex tracking algorithm that detects vortex centers efficiently, RegCM reasonably forecasts the general distribution of TC counts in time as well as the TC track pattern during the entire experimental period from February to July 2012 and 2013, despite significant underestimation of the TC counts in the global CFS forecasts that are used as initial and lateral boundary conditions for the RegCM model. Further examination of the storm activity in the Vietnam East Sea that directly influences Vietnam’s coastal region shows, however, that RegCM tends to overestimate the TC frequency in this sub-region compared to observation. This suggests that direct applications of the RegCM model for seasonal forecasts of TC activity in Vietnam’s coastal region has a significant bias that will need to be corrected before the model can provide useful information. KEY WORDS: Seasonal forecasting · Tropical cyclone · TC detection · Vietnam · Dynamical downscaling Full text in pdf format PreviousNextCite this article as: Phan VT, Long TT, Hai BH, Kieu C (2015) Seasonal forecasting of tropical cyclone activity in the coastal region of Vietnam using RegCM4.2. Clim Res 62:115-129. https://doi.org/10.3354/cr01267 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 62, No. 2. Online publication date: January 14, 2015 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2015 Inter-Research.

Seasonal Prediction of Climate Extremes for the Pacific: Tropical Cyclones and Extreme Ocean Temperatures

Climate change and climate extremes have a major impact on Australia and Pacific Island countries. Of particular concern are tropical cyclones and extreme ocean temperatures. As a practical response to climate change, through the Pacific Australia Climate Change Science and Adaptation planning Program (PACCSAP), enhanced web-based information tools to provide seasonal forecasts for climatic extremes in the Western Pacific have been developed. Using the dynamical seasonal prediction model POAMA (Predictive Ocean Atmosphere Model for Australia), we aim to improve accuracy of seasonal forecasts of tropical cyclone activity and extreme sea surface temperatures for the Western Pacific. Since the PACCSAP has commenced, encouraging scientific and technological results have been obtained, particularly in the development of web-based information tools to provide climatic extremes forecasts in the Pacific and the Australian regions. Improvements to a statistical model for seasonal tropical cyclone prediction in the Australian region have been made. Additional functionality was added to the Pacific Tropical Cyclone Data Portal, such as enhanced flexibility of spatial and temporal selection. New web-based information tool for sea surface temperature seasonal prediction is also currently under development. Improved knowledge of extreme climatic events, together with the assistance of tailored forecast tools, will help enhance the resilience and adaptive capacity of Australia and Pacific Island Countries under climate change.

Experimental Dynamical Seasonal Forecasts of Tropical Cyclone Activity at IRI

Abstract The International Research Institute for Climate and Society (IRI) has been issuing experimental seasonal tropical cyclone activity forecasts for several ocean basins since early 2003. In this paper the method used to obtain these forecasts is described and the forecast performance is evaluated. The forecasts are based on tropical cyclone–like features detected and tracked in a low-resolution climate model, namely ECHAM4.5. The simulation skill of the model using historical observed sea surface temperatures (SSTs) over several decades, as well as with SST anomalies persisted from the previous month’s observations, is discussed. These simulation skills are compared with skills of purely statistically based hindcasts using as predictors recently observed SSTs. For the recent 6-yr period during which real-time forecasts have been made, the skill of the raw model output is compared with that of the subjectively modified probabilistic forecasts actually issued. Despite variations from one basin to another, the levels of hindcast skill for the dynamical and statistical forecast approaches are found, overall, to be approximately equivalent at fairly modest but statistically significant levels. The dynamical forecasts require statistical postprossessing (calibration) to be competitive with, and in some circumstances superior to, the statistical models. Skill levels decrease only slowly with increasing lead time up to 2–3 months. During the recent period of real-time forecasts, the issued forecasts have had higher probabilistic skill than the raw model output, due to the forecasters’ subjective elimination of the “overconfidence” bias in the model’s forecasts. Prospects for the future improvement of dynamical tropical cyclone prediction are considered.

Possible influence of the Antarctic Oscillation on tropical cyclone activity in the western North Pacific

The present study investigates how large‐scale atmospheric circulation in the Southern Hemisphere (SH) modulates tropical cyclone (TC) activity in the western North Pacific (WNP) during a typhoon season (July, August, and September; boreal summer). The variation of the SH circulation of interest is the Antarctic Oscillation (AAO). In the positive phase of AAO relative to its negative phase, two anomalous highs develop over the western Pacific in both hemispheres: a huge anticyclone in southeastern Australia and a relatively weak anticyclone in the East China Sea. These teleconnection patterns are examined and compared with previous analyses. Related to the AAO variations, a statistically significant alteration of TC activities is found over the WNP. The difference in the mean TC passage numbers over the East China Sea (120°–140°E, 20°–40°N) between the eight highest‐AAO years and the eight lowest‐AAO years is as large as 2, equivalent to a 50–100% increase from the climatology. This change is primarily a result of more TCs forming over the eastern Philippine Sea. On the other hand, TC passage numbers slightly decrease over the South China Sea. These changes in TC activity are predominant in August and are consistent with changes in low‐level vorticity over the subtropical WNP. The influence of SH circulation variability on large‐scale environments and tropical convection in the subtropical NH suggest a possible usage of AAO variation for long‐range forecasting of TC activity over the WNP.

Improvements in the Seasonal Forecasting of Tropical Cyclone Activity over the Western North Pacific

A recent scheme to predict tropical cyclone (TC) activity over the western North Pacific partially failed in 1997 and 1998, during which a warm and a cold event of the El Nino-Southern Oscillation (ENSO) occurred, respectively. This paper presents results of two approaches to improve on such predictions. The first is to include new predictors that are related to ENSO based on some recent research, and the second is to provide an updated prediction by incorporating monthly values of predictors in April and May of the current year. The results suggest that new predictors related to ENSO can indeed be identified, which include temporal changes in the Southern Oscillation index, strength of the Australian monsoon, and intensity of the subtropical high in the South Pacific. These predictors, together with those selected from the original prediction scheme, are combined to form a modified scheme that in general gives better forecasts of TC activity. The updated scheme that includes April and May predictors further improves the accuracy of the predictions. Real-time predictions from both schemes for the year 2000, which were made in April and June, are found to be largely accurate. Both schemes show better skill compared with the original one.

Modulation of hurricane activity in the gulf of mexico by the madden-julian oscillation

The Madden-Julian oscillation (MJO) is a large-scale episodic modulation of tropical winds and precipitation that travels eastward from Asia to America, with a characteristic repeat time of 30 to 60 days. Here it is shown that when MJO wind anomalies in the lower troposphere of the eastern Pacific are westerly, Gulf of Mexico and western Caribbean hurricane genesis is four times more likely than when the MJO winds are easterly. Accurate predictions of the MJO may lead to improved long-range forecasts of tropical cyclone activity.

Seasonal Forecasting of Tropical Cyclone Activity over theWestern North Pacific and the South China Sea

Abstract This paper presents the development of operational statistical forecasts of seasonal tropical cyclone (TC) activity over the western North Pacific (WNP) and the South China Sea (SCS) based on 30 yr of data (1965–94). Predictors include monthly values of indices representing (a) the El Nino–Southern Oscillation phenomenon, and (b) the environmental conditions over East Asia and the WNP for the months from April of the previous year to March of the current year. Trends and short-term oscillations of the TC activity are also incorporated. The prediction equations are derived from the predictors of individual parameters using the Projection Pursuit Regression technique, which is a statistical method that reduces high-dimensional data to a lower-dimensional subspace before the regression is performed. This technique is found to provide explanations of certain nonlinear variations of the predictands. The predictions from individual parameters are then tested using the jackknife technique. Those predict...