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二零一八熱帶氣旋tropical Cyclones in 2018

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Ḵ暞ᶨℓ⸜䘬䅙ⷞ㯋㕳嶗⼹⚾ TRACKS OF TROPICAL CYCLONES IN 2018 㭷㖍⋼婧ᶾ䓴㗪暞㗪ỵ伖(楁㷗㗪攻ᶲ⋰ℓ㗪), ࡁ؍ ⫷ㅖ㲏ѝཞᮨⴞᆇẋ堐娚㚰䘬ᰕ Daily Positions at 00 UTC(08 HKT), '36/2 Є߃0;2 ⽭ډ the number in the symbol represents the date of the month 坤ԃ 154-8+? 95;2/1 㖂ॱ ԝ߃5): ࣭࣭ 㭷ℕ⮷㗪ỵ伖 ҷ߃';- =;154- 9.'49.'4 Intermediate 6-hourly Positions ੼榆⛃ Є߃0;2 棁䓃 ҷ߃';- )/3'854 0+(/ 崭⻟桙桐 Super Typhoon ҷ߃';- Ь߃9+6 ⻟桙桐 Severe Typhoon 䉷২ ؍ࡵࡁ 桙桐 Typhoon 68'6/8554 :8'3/ Є߃0;2 Ь߃9+6 ⻟䁰䅙ⷞ桐㙜 Severe Tropical Storm 䅙ⷞ桐㙜 Tropical Storm ݦ兺 ?'-/ 榆ԃގ 䅙ⷞỶ㯋⡻ Tropical Depression ҷ߃';- 3'2/19/ 湞䛵 ҹ߃0;4 Ỷ⡻⋨ Low Pressure Area 2++6/ ҷ߃';- 曾曓 䇃ࡁ☓ 054-*'8/ 8;3(/' ҷ߃';- ҷ߃';- ۺ૙ұ .+):58 ҷ߃';- 䜨哿☓ ࠀ২ -'+3/ 3'8/' 䒠㍼Ѻ㾎⺷ 䇃ࡁ☓ ҹ߃0;4 Є߃0;2 :* 8;3(/' Є߃0;2 ҷ߃';- ঁٌ 䒠㍼Ѻ㾎⺷ 3'4-1.;: ۺ௚࢔ :* ૙ұ Ь߃9+6 Hong Kong ҷ߃';- 䒠㍼Ѻ㾎⺷ .+):58 -;'ਬ曾ؿ :* ҷ߃ ٌ॔ +=/4/'8 ҷ߃';- 喗ؖ 954:/4. ҹ߃0;4 3'4?/ 㖂ॱ Є߃0;2 ࠀ২ ԝ▲߃45< =;154- -'+3/ घୌⰧ Є߃0;2 ؍ҹ߃0;4 ࡵࡁ :'8/0') 68'6/8554 Ь߃9+6 घୌⰧ ҹ߃0;4 湞䛵 ٌ॔ ('8/0': ߟܞ啠 954:/4. 曾曓 2++6/ Ь߃9+6 0+2'=': -;' ҷ߃᳦ֺ Є߃0;2 054-*'8/ ࡁ ݦ兺 ֚߃'68 ࣭࣭؍ ?;:; Є߃0;2 嶔䬐Ⱗ ?'-/ 9.'49.'4 ԝ▲߃45< '36/2 (+(/4)' 䒠㍼Ѻ㾎⺷ ҷ߃';- 嶔䬐Ⱗ Є߃0;2 ҷ߃';- ҷ߃';- :* (+(/4)' Є߃0;2 榆ԃގ ҷ߃';- 3'2/19/ ҹ߃0;4 䉷২ 坤ԃ :8'3/ 95;2/1 -;'喗 Ь߃9+6 ҷ߃ܞ٢ ٧٢ 6'(;1 (52'<+4 ࠂ吤 ਬ曾ؿ 棁䓃 ▲߃0'4 ▲߃0'4 ੼榆⛃ :58'0/ +=/4/'8 0+(/ ીֺ )/3'854 ঁٌ -;'ԝ▲߃45< ҹ߃0;4 ҷ߃ ;9'-/ ҷ߃';- :;.ԝ▲߃45< 䜨哿☓ 3'4-1 ⡕מ ;9'-/ Ь߃9+6 '/8'3 ⽭ډ ԝ▲߃45< Є߃0;2喗 154-8+?ܞ٢ ࠂ吤 (52'<+4 Ь߃9+6 :58'0/ ▲߃0'4 ࣥ⡕ ԝ▲߃45< 䒠㍼Ѻ㾎⺷ 䒠㍼Ѻ㾎⺷ ?;:; :* :* ԝ߃5): ԝи߃*+) ߟܞ啠 (+*ԝи߃ ٧٢ 0+2'=': Іٞ 1;)'6 І߃3'8 ԝи߃*+) 9'4(' Іٞ и߃,+( 9'4(' и߃,+( 喗ؖ 3'4?/ ԝ▲߃45< 二零一 八 年 熱帶氣旋 TROPICAL CYCLONES IN 2018 2 二零二零年一月出版 Published January 2020 香港天文台編製 香港九龍彌敦道134A Prepared by: Hong Kong Observatory 134A Nathan Road Kowloon, Hong Kong © 版權所有。未經香港天文台台長同意，不得翻印本刊物任何部分內容。 © Copyright reserved. No part of this publication may be reproduced without the permission of the Director of the Hong Kong Observatory. 本刊物的編製和發表，目的是促進資 This publication is prepared and disseminated in the interest of promoting 料交流。香港特別行政區政府(包括其 the exchange of information. The 僱員及代理人)對於本刊物所載資料 Government of the Hong Kong Special 的準確性、完整性或效用，概不作出 Administrative Region (including its servants and agents) makes no warranty, 明確或暗示的保證、聲明或陳述；在 statement or representation, express or 法律許可的範圍內，對於提供或使用 implied, with respect to the accuracy, 這些資料而可能直接或間接引致任 completeness, or usefulness of the information contained herein, and in so 何損失、損壞或傷害(包括死亡)，亦 far as permitted by law, shall not have any 不負任何法律承擔或責任(包括疏忽 legal liability or responsibility (including 責任)。 liability for negligence) for any loss, damage, or injury (including death) which may result, whether directly or indirectly, from the supply or use of such information. 551.515.2:551.506.1(512.317) 封面 二零一八年九月十六日上午10時24分的雷達回波圖像，當時山竹的強烈螺旋雨帶正影響 香港。 Cover Image of radar echoes at 10:24 a.m. on 16 September 2018. The intense spiral rainband of Mangkhut was affecting Hong Kong at that time. 3 目錄 頁 1. 引言 1.1 熱帶氣旋刊物的沿革 13 1.2 熱帶氣旋等級 14 1.3 熱帶氣旋命名 14 1.4 資料來源 14 1.5 年報內容 15 1.6 香港的熱帶氣旋警告系统 16 2. 二零一八年熱帶氣旋概述 2.1 二零一八年的熱帶氣旋回顧 26 2.2 每月概述 27 3. 二零一八年影響香港的熱帶氣旋 3.1 熱帶風暴艾雲尼(1804) ： 二零一八年六月二日至八日 51 3.2 熱帶風暴山神(1809) ：二零一八年七月十六日至二十四日 63 3.3 強烈熱帶風暴貝碧嘉(1816) ：二零一八年八月九日至十七日 77 3.4 熱帶風暴百里嘉(1823) ：二零一八年九月十日至十三日 89 3.5 超強颱風山竹 (1822) ：二零一八年九月七日至十七日 98 3.6 超強颱風玉兔(1826) ：二零一八年十月二十一日至十一月二日 144 4. 熱帶氣旋統計表 156 5. 二零一八年熱帶氣旋的位置及強度數據 174 附件一: 超強颱風山竹(1822)引致香港直接經濟損失的估算 202 4 CONTENTS page 1. INTRODUCTION 1.1 Evolution of tropical cyclone publications 17 1.2 Classification of tropical cyclones 17 1.3 Naming of tropical cyclones 18 1.4 Data sources 19 1.5 Content 19 1.6 Hong Kong’s Tropical Cyclone Warning System 20 2. TROPICAL CYCLONE OVERVIEW FOR 2018 2.1 Review of tropical cyclones in 2018 36 2.2 Monthly overview 37 3. TROPICAL CYCLONES AFFECTING HONG KONG IN 2018 3.1 Tropical Storm Ewiniar (1804): 2 – 8 June 2018 53 3.2 Tropical Storm Son-Tinh (1809): 16 – 24 July 2018 65 3.3 Severe Tropical Storm Bebinca (1816): 9 – 17 August 2018 79 3.4 Tropical Storm Barijat (1823): 10 – 13 September 2018 90 3.5 Super Typhoon Mangkhut (1822): 7 – 17 September 2018 103 3.6 Super Typhoon Yutu (1826): 21 October – 2 November 2018 146 4. TROPICAL CYCLONE STATISTICS AND TABLES 157 5. TROPICAL CYCLONE POSITION AND INTENSITY DATA, 2018 174 Annex 1: Estimated Direct Economic Losses in Hong Kong caused by Super Typhoon 204 Mangkhut (1822) 5 圖 頁 卷首插圖: 二零一八年北太平洋西部及南海區域的熱帶氣旋路徑圖 1.1 年報內提及的測風站及潮汐測量站之分佈地點 25 2.1 二零一八年在北太平洋西部及南海區域的熱帶氣旋出現次數之每月分佈 46 2.2 二零一八年六個影響香港的熱帶氣旋的路徑圖 46 2.3a 二零一八年九月十四日下午11時超強颱風山竹(1822)的紅外線衛星圖片 47 2.3b 二零一八年十月二十四日下午8時超強颱風玉兔(1826)的紅外線衛星圖片 48 3.1.1a 二零一八年六月二日至八日艾雲尼的路徑圖 58 3.1.1b 艾雲尼接近香港時的路徑圖 59 3.1.2 二零一八年六月五日至八日的雨量分佈 60 3.1.3 二零一八年六月七日下午2時左右的可見光衛星圖片 61 3.1.4 二零一八年六月八日上午9時24分的雷達回波圖像 62 3.1.5 二零一八年六月七日下午6時45分長洲水龍捲報告 62 3.2.1 二零一八年七月十六日至二十四日山神的路徑圖 72 3.2.2a 二零一八年七月十七日至十八日的雨量分佈 73 3.2.2b 二零一八年七月二十三日至二十四日的雨量分佈 73 3.2.3a 二零一八年七月十八日上午2時左右的紅外線衛星圖片 74 3.2.3b 二零一八年七月二十二日上午2時左右的紅外線衛星圖片 75 3.2.4 二零一八年七月十七日晩上10時36分的雷達回波圖像 76 3.3.1a 二零一八年八月九日至十七日貝碧嘉的路徑圖 84 3.3.1b 貝碧嘉接近香港時的路徑圖 85 3.3.2 二零一八年八月九日至十五日的雨量分佈 86 3.3.3 二零一八年八月十五日上午8時左右的可見光衛星圖片 87 3.3.4 二零一八年八月十四日下午2時的雷達回波圖像 88 3.4.1a 二零一八年九月十日至十三日百里嘉的路徑圖 94 3.4.1b 百里嘉接近香港時的路徑圖 95 3.4.2 二零一八年九月十二日下午8時的紅外線衛星圖片 96 3.4.3 二零一八年九月十二日下午4時的雷達回波圖像 97 6 3.5.1a 二零一八年九月七日至十七日山竹的路徑圖 112 3.5.1b 山竹接近香港時的路徑圖 113 3.5.2a 二零一八年九月十四日至十七日山竹最高持續風速的時間序列 114 3.5.2b 二零一八年九月十四日至十七日山竹最低海平面氣壓的時間序列 114 3.5.3 二零一八年九月十四日至十七日的雨量分佈 115 3.5.4a 二零一八年九月十五日上午1時左右的紅外線衛星圖片 116 3.5.4b 二零一八年九月十六日上午11時左右的可見光衛星圖片 117 3.5.5a 二零一八年九月十六日上午10時24分的雷達回波圖像 118 3.5.5b 二零一八年九月十六日下午1時的雷達回波圖像 119 3.5.6 山竹在橫過呂宋前及在南海北部風力結構變化的示意圖 119 3.5.7 二零一八年九月十六日上午8時30分的多普勒雷達回波圖像 120 3.5.8a 二零一八年九月十六日上午11時正香港各站錄得的十分鐘平均風向和風速 122 3.5.8b 二零一八年九月十六日下午2時正香港各站錄得的十分鐘平均風向和風速 123 3.5.9 二零一八年九月十六日在長洲、橫瀾島及北角錄得的十分鐘平均風速 124 3.5.10 二零一八年九月十六日香港天文台、長洲及橫瀾島錄得的海平面氣壓 125 3.5.11 二零一八年九月十六日香港各潮汐站錄得的最高潮位及水浸報告 126 3.5.12 二零一八年九月十六日在鰂魚涌、大埔滘及尖鼻咀錄得的潮位及風暴潮 127 3.5.13 在山竹的影響下，有關電力及食水中斷的報告 128 3.5.14 山竹襲港期間本港多處有樹木倒塌 129 3.5.15 山竹襲港期間本港多處地區受猛風破壞 131 3.5.16 山竹襲港期間玻璃幕牆被吹毀 134 3.5.17 山竹襲港期間巨浪拍岸 136 3.5.18 山竹襲港期間，風暴潮帶來的水浸和破壞 137 3.5.19 山竹襲港期間有船隻擱淺、沉沒或受嚴重破壞 142 3.6.1a 二零一八年十月二十一日至十一月二日玉兔的路徑圖 151 3.6.1b 玉兔接近香港時的路徑圖 152 3.6.2a 二零一八年十月二十四日下午8時左右的紅外線衛星圖片 153 3.6.2b 二零一八年十一月二日上午8時左右的可見光衛星圖片 154 3.6.3 二零一八年十一月一日正午12時的雷達回波圖像 155 7 FIGURE page FRONTISPIECE: Tracks of tropical cyclones in the western North Pacific and the South China Sea in 2018 1.1 Locations of anemometers and tide gauge stations mentioned in this annual 25 report 2.1 Monthly frequencies of the occurrence of tropical cyclones in the western North 46 Pacific and the South China Sea in 2018 2.2 Tracks of the six tropical cyclones affecting Hong Kong in 2018 46 2.3a Infra-red satellite imagery of Super Typhoon Mangkhut (1822) at peak intensity 47 at 11 p.m. on 14 September 2018 2.3b Infra-red satellite imagery of Super Typhoon Yutu (1826) at peak intensity at 48 8 p.m. on 24 October 2018 3.1.1a Track of Ewiniar on 2 – 8 June 2018 58 3.1.1b Track of Ewiniar near Hong Kong 59 3.1.2 Rainfall distribution on 5 – 8 June 2018 60 3.1.3 Visible satellite imagery around 2 p.m. on 7 June 2018 61 3.1.4 Image of radar echoes at 9:24 a.m. on 8 June 2018 62 3.1.5 Waterspout around 6:45 p.m. on 7 June 2018 at Cheung Chau 62 3.2.1 Track of Son-Tinh on 16 – 24 July 2018 72 3.2.2a Rainfall distribution on 17 - 18 July 2018 73 3.2.2b Rainfall distribution on 23 - 24 July 2018 73 3.2.3a Infra-red satellite imagery around 2 a.m. on 18 July 2018 74 3.2.3b Infra-red satellite imagery around 2 a.m. on 22 July 2018 75 3.2.4 Image of radar echoes at 10:36 p.m. on 17 July 2018 76 3.3.1a Track of Bebinca on 9 – 17 August 2018 84 3.3.1b Track of Bebinca near Hong Kong 85 3.3.2 Rainfall distribution on 9 - 15 August 2018 86 3.3.3 Visible satellite imagery around 8 a.m. on 15 August 2018 87 3.3.4 Radar echoes captured at 2 p.m. on 14 August 2018 88 3.4.1a Track of Barijat on 10 - 13 September 2018 94 3.4.1b Track of Barijat near Hong Kong 95 3.4.2 Infra-red satellite imagery around 8 p.m. on 12 September 2018 96 3.4.3 Radar echoes captured at 4 p.m. on 12 September 2018 97 3.5.1a Track of Mangkhut on 7 - 17 September 2018 112 3.5.1b Track of Mangkhut near Hong Kong 113 8 3.5.2a Time series of the maximum sustained wind speed near the centre of Mangkhut 114 on 14 - 17 September 2018 3.5.2b Time series of minimum sea level pressure of Mangkhut on 14 - 17 September 114 2018 3.5.3 Rainfall distribution on 14 - 17 September 2018 115 3.5.4a Infra-red satellite imagery around 1 a.m. on 15 September 2018 116 3.5.4b Visible satellite imagery around 11 a.m.
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    Monday, August 20, 2018 8:30 a.m. EDT Significant Activity – Aug 17-20 Significant Events: Western wildfires Tropical Activity: • Atlantic – No tropical cyclones expected in next 48 hours • Eastern Pacific – No tropical cyclone expected in next 48 hours • Central Pacific – Hurricane Lane (CAT 3) • Western Pacific – Typhoon Cimaron (23W) Significant Weather: • Severe thunderstorms possible – Lower/Middle Mississippi valleys to the Tennessee and Ohio Valleys • Flash flooding possible – Lower Mississippi/Tennessee valleys to Upper Mississippi Valley and Great Lakes • Elevated fire weather – CA, NV, UT, OR & WA • Isolated dry thunderstorms – OR, WA, ID & MT • Red Flag Warnings – UT, OR, WA, & ID Declaration Activity: • Major Disaster Declaration Request – Iowa • Major Disaster Declaration approved – Confederated Tribes of the Colville Reservation • Amendment No. 1 to FEMA-4382-DR-CA Wildfire Summary Fire Name FMAG Acres Percent Evacuations Structures Fatalities / (County) Number Burned Contained (Residents) Threatened Damaged Destroyed Injuries California (1) Mendocino 389,967 79% Mandatory 1,050 (+25) 38 (+2) 277 (+12) Complex 5262-FM-CA 0 / 2 (+10,247) (+3) 1,988 (+859) (1,025 homes) (13 homes) (157 homes) (Mendocino & Lake) Washington (2) Cougar Creek 37,775 (Chelan) 5270-FM-WA 35% Voluntary only 300 homes 0 0 0 / 3 Final (+1,056) Boyds 43% 162 4 (Ferry) 5273-FM-WA 3,065 Voluntary only 0 0 / 7 (+3) Final (+12) (161 homes) (3 homes) Hurricane Lane – Central Pacific Hurricane Lane – CAT 3 (Advisory #22 as of 5:00 a.m. EDT) • Located 675 miles
  • An Efficient Method for Simulating Typhoon Waves Based on A

    An Efficient Method for Simulating Typhoon Waves Based on A

    Journal of Marine Science and Engineering Article An Efficient Method for Simulating Typhoon Waves Based on a Modified Holland Vortex Model Lvqing Wang 1,2,3, Zhaozi Zhang 1,*, Bingchen Liang 1,2,*, Dongyoung Lee 4 and Shaoyang Luo 3 1 Shandong Province Key Laboratory of Ocean Engineering, Ocean University of China, 238 Songling Road, Qingdao 266100, China; [email protected] 2 College of Engineering, Ocean University of China, 238 Songling Road, Qingdao 266100, China 3 NAVAL Research Academy, Beijing 100070, China; [email protected] 4 Korea Institute of Ocean, Science and Technology, Busan 600-011, Korea; [email protected] * Correspondence: [email protected] (Z.Z.); [email protected] (B.L.) Received: 20 January 2020; Accepted: 23 February 2020; Published: 6 March 2020 Abstract: A combination of the WAVEWATCH III (WW3) model and a modified Holland vortex model is developed and studied in the present work. The Holland 2010 model is modified with two improvements: the first is a new scaling parameter, bs, that is formulated with information about the maximum wind speed (vms) and the typhoon’s forward movement velocity (vt); the second is the introduction of an asymmetric typhoon structure. In order to convert the wind speed, as reconstructed by the modified Holland model, from 1-min averaged wind inputs into 10-min averaged wind inputs to force the WW3 model, a gust factor (gf) is fitted in accordance with practical test cases. Validation against wave buoy data proves that the combination of the two models through the gust factor is robust for the estimation of typhoon waves.
  • Efforts for Emergency Observation Mapping in Manila Observatory

    Efforts for Emergency Observation Mapping in Manila Observatory

    Efforts for Emergency Observation Mapping in Manila Observatory: Development of a Typhoon Impact Estimation System (TIES) focusing on Economic Flood Loss of Urban Poor Communities in Metro Manila UN-SPIDER International Conference on Space-based Technologies for Disaster Risk Reduction – “Enhancing Disaster Preparedness for Effective Emergency Response” Session 4: Demonstrating Advances in Earth Observation to Build Back Better September 25, 2018 Ma. Flordeliza P. Del Castillo Manila Observatory EMERGENCY OBSERVATION MAPPING IN MANILA OBSERVATORY • Typhoon Reports • Sentinel Asia Data Analysis Node (2011-present) • Flood loss estimation for urban poor households in Metro Manila (2016-present) 1. Regional Climate Systems (RCS) – Hazard analysis (Rainfall and typhoon forecast) 2. Instrumentation and Efforts before typhoon arrives Technology Development – Automated Weather Stations 3. Geomatics for Environment and Development – Mapping and integration of Hazard, Exposure and Vulnerability layers Observing from space and also from the ground. Efforts during typhoon event Now, incorporating exposure and vulnerability variables Efforts after a typhoon event Data Analysis Node (Post- Disaster Event) Image Source: Secretariat of Sentinel Asia Japan Aerospace Exploration Agency, Sentinel Asia Annual Report 2016 MO Emergency Observation (EO) and Mapping Protocol (15 October 2018) Step 1: Step 2: Step 3: Establish the Apply for EMERGENCY Elevate status to LOCATION/COVERAGE of OBSERVATION to International Disaster EOR Sentinel Asia (SA) Charter (IDC) by ADRC Step 6: Step 5: Step 4: Upload maps in MO, SA MAP Download images & IDC websites PRODUCTION Emergency Observation Mapping Work • December 2011 – T.S. Washi “Sendong” • August 2012 – Southwest Monsoon Flood “Habagat” • ” Emergency Observation Mapping Work • December 2011 – T.S. Washi “Sendong” • August 2012 – Southwest Monsoon Flood “Habagat” • December 2012 – Bopha “Pablo” • August 2013 – Southwest Monsoon Flood and T.S.
  • The 14Th Asia Pacific Conference on Disaster Medicine in Kobe, Japan: a Brief Overview and a Proposal

    The 14Th Asia Pacific Conference on Disaster Medicine in Kobe, Japan: a Brief Overview and a Proposal

    Abstracts of Poster-Presentations-WADEM Congress on Disaster and Emergency Medicine 2019 POSTER PRESENTATIONS 2018 Natural Disaster Response in Japan The 14th Asia Pacific Conference on Disaster Medicine in Dr. Hisayoshi Kondo, Dr. Yuichi Koido, Dr. Hirotaka Uesgi, Kobe, Japan: A Brief Overview and a Proposal Dr. Yoshitaka Kohayagawa, Dr. Ayako Takahashi, Dr. Shinichi Nakayama1, Dr. Takashi Ukai1, Dr. Yuzuru Kawashima, Dr. Miho Misaki, Ms Kayako Chishima, Dr. Shuichi Kozawa1, Dr. Tetsunori Kawase1, Mr. Yoshiki Toyokuni Dr. Satoshi Ishihara1, Dr. Soichiro Kai Kai1, Dr. Ryoma Kayano2, National Disaster Medical Center of Japan, Tachikawa, Japan Dr. Tatsuro Kai3 1. Hyogo Emergency Medical Center, Kobe, Japan Introduction: Japan experienced several major disasters in 2. The WHO Center for Health Development (WHO Kobe 2018. Center), Kobe, Japan Aim: Evaluation of medical response was conducted and prob- 3. Osaka Saiseikai Senri Hospital, Osaka lems determined to solve for future response. Methods: An evaluation conducted on DMAT responding Introduction: The Asia Pacific Conference on Disaster report of Northern Osaka Earthquake, West Japan Torrential Medicine (APCDM) started in 1988 in Osaka, Japan, and the Rain Disaster, Typhoon Jebi, and Hokkaido Iburi East 14th conference was held from October 16-182, 2018, in Kobe. Earthquake. Aim: To give a rundown of the 14th APCDM and a proposal Results: DMAT responded 58 teams for Osaka Northern for WADEM. Earthquake, 119 teams for West Japan Torrential Rain Methods: Retrospective analysis of participants, the category of Disaster, 17 teams for Typhoon Jebi, 67 teams for Hokkaido presentations, and deliverables. Iburi East Earthquake. At the Osaka Northern Earthquake, Results: With “Building Bridges for Disaster Preparedness and by comparing the report of seismic diagnosis, results and, a Response” as its main theme, the 14th APCDM was held near magnitude of each region, hospital damage was evaluated.
  • Appendix II - J Kwun Tong District Summaries of Written/Oral Representations

    Appendix II - J Kwun Tong District Summaries of Written/Oral Representations

    J. Kwun Tong District - 144 - J. Kwun Tong District Appendix II - J Kwun Tong District Summaries of Written/Oral Representations Item No.* DCCAs Representations EAC’s Views No. W O 1 All 1 - Proposes to re-delineate the This proposal is not accepted DCCAs boundaries of all DCCAs and because: change the names and codes of the DCCAs concerned. (i) the number of affected Details are as follows: DCCAs under the proposal made in the representation J01 (Kwun Tong Central) will be 28 more than that in includes Kwun Tong Town the provisional Centre Redevelopment Area, recommendations. The Kwun Tong Industrial Area, affected population under the area in the west of Wai Fat the proposal will be larger, Road, most of the area at Yuet too; and Wah Street (excluding a few blocks of the buildings in the (ii) the EAC must follow the west of Hip Wo Street), Wo existing boundaries of the Lok Estate, and the area in the administrative districts as south of Shing Fung Road specified in Schedules 1 Bridge in G14 (Kai Tak and 3 of the DCO and Central & South) of the comply with the statutory Kowloon City District. criteria set out in the EACO in the delineation of J02 (Kowloon Bay) DCCA boundaries. includes Telford Gardens and its surrounding industrial and commercial areas, and also four industrial and commercial buildings in the west of Auxiliary Police Headquarters. J03 (Kai Yip) includes Kai Yip Estate, Kai Tai Court, Choi Yan House, Choi Yee House, Choi Shun House and Choi Shing House of Choi Tak Estate, Kwun * W: Number of written representations.
  • Consecutive Extreme Flooding and Heat Wave in Japan: Are They Becoming a Norm?

    Consecutive Extreme Flooding and Heat Wave in Japan: Are They Becoming a Norm?

    Received: 17 May 2019 Revised: 25 June 2019 Accepted: 1 July 2019 DOI: 10.1002/asl.933 EDITORIAL Consecutive extreme flooding and heat wave in Japan: Are they becoming a norm? In July 2018, Japan experienced two contrasting, yet consec- increases (Chen et al., 2004). Putting these together, one could utive, extreme events: a devastating flood in early July argue that the 2018 sequential events in southern Japan indicate followed by unprecedented heat waves a week later. Death a much-amplified EASM lifecycle (Figure 1a), featuring the tolls from these two extreme events combined exceeded strong Baiu rainfall, an intense monsoon break, and the landfall 300, accompanying tremendous economic losses (BBC: July of Super Typhoon Jebi in early September. 24, 2018; AP: July 30, 2018). Meteorological analysis on The atmospheric features that enhance the ascent and insta- these 2018 events quickly emerged (JMA-TCC, 2018; bility of the Baiu rainband have been extensively studied Kotsuki et al., 2019; Tsuguti et al., 2019), highlighting sev- (Sampe and Xie, 2010); these include the upper-level westerly eral compound factors: a strengthened subtropical anticy- jet and traveling synoptic waves, mid-level advection of warm clone, a deepened synoptic trough, and Typhoon Prapiroon and moist air influenced by the South Asian thermal low, and that collectively enhanced the Baiu rainband (the Japanese low-level southerly moisture transport associated with an summer monsoon), fostering heavy precipitation. The com- enhanced NPSH. These features are outlined in Figure 1b as prehensive study of these events, conducted within a month (A) the NPSH, and particularly its western extension; (B) the and released by the Japan Meteorological Agency (JMA) western Pacific monsoon trough; (C) the South Asian monsoon; (JMA-TCC, 2018), reflected decades of knowledge of the (D) the mid-latitude westerly jet and quasistationary short Baiu rainband and new understanding of recent heat waves waves, as well as the Baiu rainband itself; these are based on in southern Japan and Korea (Xu et al., 2019).
  • Fast Storm Surge Ensemble Prediction Using Searching Optimization of a Numerical Scenario Database

    Fast Storm Surge Ensemble Prediction Using Searching Optimization of a Numerical Scenario Database

    OCTOBER 2021 X I E E T A L . 1629 Fast Storm Surge Ensemble Prediction Using Searching Optimization of a Numerical Scenario Database a,b,c a,b,c a a a,b,c a,b,c YANSHUANG XIE, SHAOPING SHANG, JINQUAN CHEN, FENG ZHANG, ZHIGAN HE, GUOMEI WEI, a,b,c d d JINGYU WU, BENLU ZHU, AND YINDONG ZENG a College of Ocean and Earth Sciences, Xiamen University, Xiamen, China b Research and Development Center for Ocean Observation Technologies, Xiamen University, Xiamen, China c Laboratory of Underwater Acoustic Communication and Marine Information Technology, Ministry of Education, Xiamen University, Xiamen, China d Fujian Marine Forecasts, Fuzhou, China (Manuscript received 6 December 2020, in final form 10 June 2021) ABSTRACT: Accurate storm surge forecasts provided rapidly could support timely decision-making with consideration of tropical cyclone (TC) forecasting error. This study developed a fast storm surge ensemble prediction method based on TC track probability forecasting and searching optimization of a numerical scenario database (SONSD). In a case study of the Fujian Province coast (China), a storm surge scenario database was established using numerical simulations generated by 93 150 hypothetical TCs. In a GIS-based visualization system, a single surge forecast representing 2562 distinct typhoon tracks and the occurrence probability of overflow of seawalls along the coast could be achieved in 1–2 min. Application to the cases of Typhoon Soudelor (2015) and Typhoon Maria (2018) demonstrated that the proposed method is feasible and effective. Storm surge calculated by SONSD had excellent agreement with numerical model results (i.e., mean MAE and RMSE: 7.1 and 10.7 cm, respectively, correlation coefficient: .0.9).
  • District Profiles 地區概覽

    District Profiles 地區概覽

    Table 1: Selected Characteristics of District Council Districts, 2016 Highest Second Highest Third Highest Lowest 1. Population Sha Tin District Kwun Tong District Yuen Long District Islands District 659 794 648 541 614 178 156 801 2. Proportion of population of Chinese ethnicity (%) Wong Tai Sin District North District Kwun Tong District Wan Chai District 96.6 96.2 96.1 77.9 3. Proportion of never married population aged 15 and over (%) Central and Western Wan Chai District Wong Tai Sin District North District District 33.7 32.4 32.2 28.1 4. Median age Wan Chai District Wong Tai Sin District Sha Tin District Yuen Long District 44.9 44.6 44.2 42.1 5. Proportion of population aged 15 and over having attained post-secondary Central and Western Wan Chai District Eastern District Kwai Tsing District education (%) District 49.5 49.4 38.4 25.3 6. Proportion of persons attending full-time courses in educational Tuen Mun District Sham Shui Po District Tai Po District Yuen Long District institutions in Hong Kong with place of study in same district of residence 74.5 59.2 58.0 45.3 (1) (%) 7. Labour force participation rate (%) Wan Chai District Central and Western Sai Kung District North District District 67.4 65.5 62.8 58.1 8. Median monthly income from main employment of working population Central and Western Wan Chai District Sai Kung District Kwai Tsing District excluding unpaid family workers and foreign domestic helpers (HK$) District 20,800 20,000 18,000 14,000 9.