보고서 정보
주관연구기관 |
서울대학교 산학협력단 Seoul National University |
보고서유형 | 3단계보고서 |
발행국가 | 대한민국 |
언어 |
한국어
|
발행년월 | 2015-03 |
과제시작연도 |
2014 |
주관부처 |
기상청 Korea Meteorological Administration(KMA) |
과제관리전문기관 |
한국기상산업진흥원 Korea Meteorological Industry Promotion Agency |
등록번호 |
TRKO201500013447 |
과제고유번호 |
1365001846 |
사업명 |
기상기술개발사업 |
DB 구축일자 |
2015-08-15
|
키워드 |
태풍.예측.현업화.통계-역학모델.비정역학 지역모델.typhoon.forecast.operationalize.statistical-dynamical model.non-hydrostatic regional model.
|
DOI |
https://doi.org/10.23000/TRKO201500013447 |
초록
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본 연구과제의 목적은 여름철 태풍활동을 과학적으로 이해하고 통계-역학 하이브리드 모형을 활용해 그 활동성을 예측하는 것이다. 먼저 북서태평양 태풍 강도의 중위도와 저위도 간비균질성을 발견하였고 그 원인을 분석하였다. 이어서 북서태평양의 기후적 태풍 진로를 대표적 7개 유형으로 분류하고 열대 및 중위도 대규모 순환장 변동성과의 관련성을 조사하였다. 이를 기반으로 각 태풍 진로 별 통계 모형을 개발하고 7개 유형 예측결과를 종합함으로써 여름철 태풍 진로 최종 예측지도를 생산하는 예측모형을 개발하였다. 이 예측모형의 예측성능을 2010년
본 연구과제의 목적은 여름철 태풍활동을 과학적으로 이해하고 통계-역학 하이브리드 모형을 활용해 그 활동성을 예측하는 것이다. 먼저 북서태평양 태풍 강도의 중위도와 저위도 간비균질성을 발견하였고 그 원인을 분석하였다. 이어서 북서태평양의 기후적 태풍 진로를 대표적 7개 유형으로 분류하고 열대 및 중위도 대규모 순환장 변동성과의 관련성을 조사하였다. 이를 기반으로 각 태풍 진로 별 통계 모형을 개발하고 7개 유형 예측결과를 종합함으로써 여름철 태풍 진로 최종 예측지도를 생산하는 예측모형을 개발하였다. 이 예측모형의 예측성능을 2010년도 사례분석을 통해 검증하였고 자동화 작업을 수행해 국가태풍센터에 현업화 기술이전을 진행하였다. 본래 이 예측모형은 5월 초 예측시점을 기반으로 개발되었으나 예측시점을 당해연도 봄철 및 겨울철로 선행화 할 경우 예측성능을 평가하였다. 또한 통계-역학 하이브리드 방식을 통해 예측구역을 확장하여 북서태평양 뿐만 아니라 북대서양 허리케인 계절예측 모형을 개발하였다. 역학모형 시뮬레이션을 통한 태풍활동 계절예측 연구의 시초로써, 관측 해수면 온도를 경계자료로 처방하여 고해상도 비정역학 지역모형(WRF) 에서 태풍활동을 모의하였다. 모의된 태풍활동의 기후적 양상을 분석하여 WRF 모형의 현업활용 가능성을 모색하였다.
Abstract
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This research and development project entitled as “Prediction of medium- and long-range tropical cyclone (TC) activity using the statistical-dynamical forecast system” has been conducted since 2012. The main object of this project is development of accurate prediction model for tropical cyclone acti
This research and development project entitled as “Prediction of medium- and long-range tropical cyclone (TC) activity using the statistical-dynamical forecast system” has been conducted since 2012. The main object of this project is development of accurate prediction model for tropical cyclone activity in summertime and operationalize the system to the National Typhoon Center, Korea Meteorology Administration. Because the TC activities in summertime cause enormous economic damages for coastal areas, we should attempt the seasonal prediction of TC activities to prepare the risk in advance. The detailed contents of the scientific results from the project are described as follows.
The spatial distribution of trends in TC intensity over the western North Pacific Ocean (WNP) during the period 1977–2010 was examined using five TC datasets. The spatial distribution of the TC intensity was expressed by seasonally averaged maximum wind speeds in 5˚ × 5˚ horizontal grids. The trends showed a spatial inhomogeneity, with a weakening in the tropical Philippine Sea (TP) and a strengthening in southern Japan and its southeastern ocean (SJ). This distribution could be described by TC intensification rate and genesis frequency, with the aid of the climatological direction of TC movement. The increasing intensification rate around the center of the WNP could mostly account for the increasing intensity over the SJ region, while the influence of both intensification rate and local genesis frequency mattered in the TP region because of the effect of the newly generated and less-developed weak TCs on the TC intensity. Thermodynamic variables (e.g., sea surface temperature, potential intensity, and 268C isotherm depth) showed almost homogeneous changes in space, possibly favoring intensification rate and genesis frequency over the entire WNP. However, the decreasing intensification rate and genesis frequency in some tropical regions conflicted with the impact of thermodynamic variables; rather, they were in accord with the impact of dynamic variables (i.e., vorticity and wind shear). In conclusion, the spatially inhomogeneous trends in TC intensity could be explained by considering the thermodynamic and dynamic aspects in combination through intensification rate and genesis frequency. The threat of intense TCs to East Asia has increased in recent decades. Integrated analyses of five available TC data sets for the period 1977–2010 revealed that the growing threat of TCs primarily results from the significant shift that the spatial positions of the maximum intensity of TCs moved closer to East Asian coastlines from Vietnam to Japan. This shift incurs a robust increase in landfall intensity over east China, Korea and Japan. In contrast, an increase of TC genesis frequency over the northern part of the South China Sea leads to a reduction in the maximum TC intensity before landfall, because of their short lifetime; thus, there are no cleartendencies in the landfall intensity across Vietnam, south China and Taiwan. All changes are related to the strengthening of the Pacific Walker circulation, closely linked with the recent manifestation that the warming trend of sea surface temperature in the tropical western Pacific is much higher than that in the central to eastern Pacific.
Tropical cyclone formation close to the coastline of the Asian continent presents a significant threat to heavily populated coastal countries. A case study of Tropical Storm Mekkhala (2008) that developed off the coast of Vietnam is presented using the high-resolution analyses of the European Centre for Medium-Range Weather Forecasts/Year of Tropical Convection and multiple satellite observations. The authors have analyzed contributions to the formation from large-scale intraseasonal variability, synoptic perturbations, and mesoscale convective systems (MCSs). Within a large-scale westerly wind burst (WWB) associated with the Madden–Julian oscillation (MJO), synoptic perturbations generated by two preceding tropical cyclones initiated the pre-Mekkhala low-level vortex over the Philippine Sea. Typhoon Hagupit produced a synoptic-scale wave train that contributed to the development of Jangmi, but likely suppressed the Mekkhala formation. The low-level vortex of the pre-Mekkhala disturbance was then initiated in a confluent zone between northeasterlies in advance of Typhoon Jangmi and the WWB. A key contribution to the development of Mekkhala was from diurnally varying MCSs that were invigorated in the WWB. The oceanic MCSs, which typically develop off the west coast of the Philippines in the morning and dissipate in the afternoon, were prolonged beyond the regular diurnal cycle. A combination with the MCSs developing downstream of the Philippines led to the critical structure change of the oceanic convective cluster, which implies the critical role of mesoscale processes. Therefore, the diurnally varying mesoscale convective processes over both the ocean and land are shown to have an essential role in the formation of Mekkhala in conjunction with large-scale MJO and the synoptic-scale TC influences.
This study investigates the relationship between TC–induced heavy rainfall over East Asia (EA) and large-scale climate variability during June–October for the period of 1961–2005. An empirical orthogonal function analysis is applied to the seasonal-total TC-induced heavy rainfall obtained in meteorological stations over EA. The first leading mode shows a dipole pattern between South China (SC) and Northeast Asia (NEA; i.e., Southeast-East China, Taiwan, and Japan). This dipole pattern is found to be associated with the two modes of sea surface temperature (SST) variations over the Pacific: one in the tropical Pacific, and the other spanning from EA to the North Pacific Ocean. The former is located in the NINO4 region, while the latter is characterized by the North Pacific center of the Pacific Decadal Oscillation (PDO). The dipole mode is generally well explained by the combined NINO4 and PDO impacts on TC tracks. During positive NINO4, cyclonic steering flows appear over inshore Southeast China, which increases recurving TCs. Meanwhile, the midlatitude North Pacific SST warming during negative PDO is overlaid by the barotropic anticyclone. The anomalous steering easterlies along 20–40。N related to the anticyclone increase TC occurrence toward Southeast-East China and Taiwan. Furthermore, the precipitable water greatly increases in the mid-latitude ocean during negative PDO years, which may help to enhance the rainfall amount while TCs approach Japan. To sum up, in a climatological sense, the first mode of TC-induced heavy rainfall over EA can be interpreted by the combined variations of negative (positive) PDO with positive (negative) NINO4.
This study investigated the TC rainfall (PTC) contribution to the interdecadal change in summer (June, July and August) rainfall (PTotal) over South China between 1981-1992 (ID1) and 1993-2002 (ID2). In an area-averaged sense, the interdecadal change in PTotal was largely attributed to non-TC rainfall for the summer total and months of June and July, while PTC became comparable in August. When the month-to-month spatial variability was considered, noticeable negative PTC contributions showed up over the southeastern coast, Hainan Island, and Taiwan in June and over the southern coastal regions in July. In contrast, a positive PTC contribution spread over South China with its maxima over the southern coastal regions in August, a pattern which appeared to be diametrically opposed to that of the negative PTC contribution in July, though the latter was less significant. The negative PTC contribution over the coastal and insular regions in June and July corresponded to less TC activity there. In June, it was attributed to reduced basin-wide TC activity due to prevailing unfavorable large-scale environments in ID2, whereas, in July, to less TC approaches from the Philippine Sea due to an enhanced cyclonic circulation centered on Taiwan in ID2. Conversely, in August, the overall enhanced positive PTC contribution was mainly by the direct influences of increased TC formations over the South China Sea in ID2.
Skillful predictions of the seasonal TC activity are important in mitigating the potential destruction from the TC approach/landfall in many coastal regions. In this study, a novel approach for the prediction of the seasonal TC activity over the western North Pacific is developed to provide useful probabilistic information on the seasonal characteristics of the TC tracks and vulnerable areas. The developed model, which is termed the “track-pattern-based model”, which is characterized by two features: 1) a hybrid statistical–dynamical prediction of the seasonal activity of seven track patterns obtained by fuzzy c-means clustering of historical TC tracks and 2) a technique that enables researchers to construct a forecasting map of the spatial probability of the seasonal TC track density over the entire basin. The hybrid statistical–dynamical prediction for each pattern is based on the statistical relationship between the seasonal TC frequency of the pattern and the seasonal mean key predictors dynamically forecast by the National Centers for Environmental Prediction Climate Forecast System in May. The leave-one-out cross validation shows good prediction skill, with the correlation coefficients between the hindcasts and the observations ranging from 0.71 to 0.81. Using the predicted frequency and the climatological probability for each pattern, the authors obtain the forecasting map of the seasonal TC track density by combining the TC track densities of the seven patterns. The hindcasts of the basinwide seasonal TC track density exhibit good skill in reproducing the observed pattern. The El Niño–/La Niña–related years, in particular, tend to show a better skill than the neutral years.
Fourteen named TCs formed in the WNP in 2010, representing the lowest count since 1951. Both low activity during the typhoon season (June–October) and quiescence during the pre- and posttyphoon seasons were major contributing factors. Despite overall low activity, TC activity along land boundaries was enhanced because the overall genesis locations of TCs shifted to the north and west and a majority of them affected the coastal countries in the WNP. These features are attributed to the expansion of the subtropical high and weakening of the monsoon trough associated with the rapid transition of the 2009/10 El Niño to the 2010/11 La Niña. The National Typhoon Center (NTC) in South Korea utilizes the recently developed track-pattern-based model of the hybrid statistical–dynamical type as the operational long-range TC forecast system. This model fairly forecast the anomalous spatial distribution of TC track density for the 2010 typhoon season.Ahigher-than-normal track density was successfully forecast near Korea and Japan. This is attributed to the overall skillful forecast of TC count for each pattern by the NTC model, though some deficiencies in forecasting extremes for some patterns are evident. The total seasonal genesis frequency integrated over the seven patterns is well below normal (about 16.4) close to the observations. The fair predictability in 2010 using the NTC model is attributed to the skillful forecast of the ENSO transition by the National Centers for Environmental Prediction Climate Forecast System, in addition to the validity of the NTC model itself.
Recently, the NTC at the Korea Meteorological Administration launched a track-pattern-based model that predicts the horizontal distribution of tropical cyclone (TC) track density from June to October. This model is the firrst approach to target seasonal TC track clusters covering the entire WNP basin, and may represent a milestone for seasonal TC forecasting, using a simple statistical method that can be applied at weather operation centers. In this note, we describe the procedure of the track-pattern-based model with brief technical background to provide practical information on the use and operation of the model. The model comprises three major steps. First, long-term data of WNP TC tracks reveal seven climatological track clusters. Second, the TC counts for each cluster are predicted using a hybrid statistical-dynamical method, using the seasonal prediction of large-scale environments. Third, the final forecast map of track density is constructed by merging the spatial probabilities of the seven clusters and applying necessary bias corrections. Although the model is developed to issue the seasonal forecast in mid-May, it can be applied to alternative dates and target seasons following the procedure described in this note. Work continues on establishing an automatic system for this model at the NTC.
The automated prediction system for seasonal TC activity is established at the NTC of the Korea Meteorological Administration (KMA) to provide effective operation and control of the system for user who lacks knowledge of the system. For automation of the system, two procedures which include subjective decisions by user are performed in advance, and their output data are provided as input data. To provide the capability to understand the operational processes for operational user, the input and output data are summarized with each process, and the directory structure is reconstructed following KMA’s standard. We introduce a user interface using namelist input parameters to effectively control operational conditions which is fixed or should be manually set in the previous version of the prediction system. To operationally use early prediction which become available through the automation, its performances are evaluated according to initial condition dates. As a result, high correlations between the observed and predicted TC counts are kept for all track clusters even though advancing the initial condition date from May to January.
A long-range prediction system of TC activity over the WNP has been operated in the National Typhoon Center of the Korea Meteorological Administration since 2012. The model forecasts the spatial distribution of TC tracks averaged over the period June~October. In this study, we separately developed TC prediction models for summer (June-August) and autumn (September-November) period based on the current operating system. To perform the three-month WNP TC activity prediction procedure readily, we modified the shell script calling in environmental variables automatically. The user can apply the model by changing these environmental variables of namelist parameter in consideration of their objective. The validations for the two seasons demonstrate the great performance of predictions showing high pattern correlations between hindcast and observed TC activity. In addition, we developed a post-processing script for deducing TC activity in the Korea emergency zone from final forecasting map and its skill is discussed.
A seasonal prediction model of TC activities for the period August-October over the North Atlantic (NA) has been developed on the basis of TC track patterns. Using the fuzzy c-means method, a total of 432 TCs in the period 1965-2012 are categorized into the following four groups: 1) TCs off the East Coast of the United States, 2) TCs over the Gulf of Mexico, 3) TCs that recurve into the open oceans of the central NA, and 4) TCs that move westward in the southern NA. The model is applied to predict TC activities separately for these four TC groups in conjunction with global climate forecasts (e.g., SST, vertical wind shear, zonal wind and vorticity at 850 hPa) from the National Centers for Environmental Prediction Climate Forecast System version 2. By adding the distributions of the four TC tracks with weighting factors, this seasonal TC forecast model provides the spatial distribution of TC activities over the entire NA basin. Multiple forecasts initialized in six consecutive months from February to July are generated at monthly intervals to examine the applicability of this model in operational TC forecasting. Cross-validations of individual forecasts show that the model can reasonably predict the observed TC frequencies over NA at the 99% confidence level. The model shows a stable spatial prediction skill, proving its advantage for forecasting regional TC activities several months in advance. In particular, the model can generate reliable information on regional TC counts in the near-coastal regions as well as in entire NA basin.
A track-pattern-based model provides deterministic forecasting results of seasonal TC track density for the corresponding ocean basins. Through the statistical ensemble analysis, the model can produce final forecasting map as well as its confidence interval level. By post-processing of ensemble analysis regionally, we can estimate the confidence level with objective viewpoint.
Observational records reveal that the number of TCs approaching East Asia in July– October is positively correlated with SSTs in the equatorial and northern off-equatorial central Pacific (CP) oceans, indicating the significant impact of CP El Niño (CP-EN). Through experiments using a Weather Research and Forecast (WRF) model–based regional climate model, this study demonstrates that it is northern off-equatorial CP warming, rather than equatorial CP warming, that effectively induces local anomalous steering flows pertinent to the observed increase in TC activity over East Asia during CP-EN. Sensitivity experiments, in which the prescribed CP-EN-related SST anomaly is confined near the equator, do not capture the observed TC increase over East Asia, whereas those including the off-equatorial region successfully reproduce observed atmospheric and TC variabilities. The off-equatorial CP SST anomaly acts to expand the anomalous cyclonic response in the Philippine Sea farther northward. This produces a tunnel effect in the East China Sea, by which more TCs move to East Asian coastal regions (e.g., east China, Taiwan, Korea, and Japan).
In conclusion, there are still several challenges to overcome to improve the track-pattern-based seasonal forecast model for basin-wide TC activity and diagnose scientific TC activity issues. To attempt this unknowns, further improvements and researches will be addressed in future studies.
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