tai ccat複審總計畫3

總計畫評估組

環境組治理組

TaiCCAT主持人：劉振榮副校長

總計畫評估組

環境組治理組

氣候變遷調適科技整合研究計畫Taiwan integrated research program on Climate Change Adaptation Technology

簡報內容計畫背景總體目標研究挑戰推動架構推動歷程理論基礎跨組連結( 總計畫與三組報告 ) 主要工作預期成果

計畫背景由於氣候變遷衝擊顯著，但卻具有高度的不確定性，臺灣社會應儘早建立全面的調適作為予以因應，以維護人民生命財產、環境生態與國家永續發展，且需考量高不確定性以避免做出錯誤決策。

承續「永續台灣的遠景與策略」及「氣候變遷衝擊調適及因應策略」計畫成果，並考慮國內學界與施政單位有關氣候變遷相關研究之整合必要，推動「氣候變遷調適科技整合研究計畫」。

本計畫為行政院國家永續發展委員會「科技與評估組」 (國科會 ) 之重要計畫，藉由調適科技之推動，支援政府決策，並促進國際合作，以減少生態環境與經濟社會系統脆弱度並提升回復能力。

總體目標支援各部會落實科學研究氣候變遷調適科技學術缺口鑑別與研究發展民眾認知與合作機制之重要性氣候變遷資訊高不確定性與知識不完整性，需要系統整合，並強化環境監測與評估能力，已發展具有強健與富有彈性之調適能力

風險評估、風險分攤、風險治理現況與未來風險之掌握產官學民、跨部會風險共同承擔財務、土地規劃、科技、產業推動

掌握風險資訊（監測、評估）、合理措施（調適措施）、智慧決策（風險治理、土地規劃）、尋找機會（科學與產業發展）

建構各部會因應氣候變遷衝擊所需科技與現有科學知識之橋梁科學知識於科技發展應用之可行性分析科技發展所需前瞻科學研究規劃

建構整合研究架構鑑別跨部會氣候變遷關鍵議題與技術需求發展不同空間尺度跨領域議題之研究架構資訊需求與規格

研究挑戰跨領域性：氣候事件是個綜合環境、文化與政策的複雜現象

不確定性：氣候變遷仍具高度科學不確定性，並須設法喚醒民眾因應意識

高急迫性：氣候事件已在台灣發生，必須盡快檢視並改善我們的環境

因地制宜：氣候調適沒有標準規範，因人與所處環境而異，必須因地制宜

風險分散：由於上述特性，氣候變遷會顯著衝擊，但又具高不確定性，必須將風險分散，並因地制宜，且能彈性調配與系統整合。

農業生產及生物多樣性能源供給及產業

維生基礎建設土地使用

水資源健康海岸

災害

計畫定位行政院永續發展委員會

科技與評估組 ( 國科會 )

氣候變遷研究聯盟(CCliCS)

台灣氣候變遷推估與資訊平台(TCCIP)

氣候變遷調適科技整合研究計畫 (TaiCCAT)

環境監測分析 ( 環境組 )

脆弱度評估 ( 評估組 )

調適治理 ( 治理組 )

整合推動 ( 總計畫 )

經建會 (2012.6)國家氣候變遷調適政策綱領

農業生產及生物多樣性能源供給及產業

維生基礎建設土地使用

水資源健康海岸

災害

計畫定位行政院永續發展委員會經建會

國家氣候變遷調適政策綱領 (2012.6)

科技與評估

( 下游 )氣候變遷調適科技整合研究計畫

(TaiCCAT)

(Patt, 2012)

推動架構國科會

環境組評估組

總計畫

臺灣大學童慶斌教授海洋大學李光敦教授成功大學蘇慧貞教授臺灣大學盧虎生教授中興大學林幸助教授中央大學李明旭教授

海洋大學李明安院長中央大學李錫堤教授中央大學陳良健教授中央大學林唐煌教授臺灣大學李培芬教授成功大學許泰文教授

中研院張靜貞教授台北大學詹士樑教授清華大學范建得教授

主持人：中央大學劉振榮副校長執行秘書：中央大學李河清教授

治理組

Climate

減災措施減災能力建構

過去未來

脆弱度評估

調適治理

先期調適( 過去經驗 )

計劃調適( 未來規劃 )

自發調適( 近程調適 )

現在

環境系統分析

氣候調適能力建構

Weather

脆弱度評估

推動歷程

整合運作

社會大眾

政府學術

環境系統分析

調適治理

第一階段研究架構

第二階段研究發展

第三階段整體推動

核心分組第一階段：規劃第二階段：先期計畫

總計畫

1. 完成國內外氣候變遷調適科技研究現況與研究缺口分析

2. 研究架構規劃，確立總計畫辦公室與三個核心分組。

3. 形成研究團隊與階段推動策略

1. 研究規劃與整合之強化2. 調適科技國際交流與合作管道建立3. 風險治理與空間規劃分析4. 知識平台規劃5. 科學報告規劃

環境監測組

1. 熱島效應2. 崩坍預測模式 (Shihmen Reservoir)

3. 臺灣海峽海溫上升分析4. mullet fishery 糧食安全分析5. 海空交互作用－澎湖冷水入侵災害6. Land-sea interaction for sand

reduce

脆弱度評估

1. 跨領域研究問題分析2. 各領域標準評估流程3. 資訊流分析與問題釐清4. 跨領域脆弱度評估系統動力模式5. 脆弱度與回復力指標系統

調適治理

議題矩陣五：調適治理觀點下的跨組連結

Climate


過去未來

脆弱度評估

調適治理




現在

環境系統分析


Weather

議題矩陣三：脆弱度評估觀點下的跨組連結

Climate


過去未來

脆弱度評估

調適治理




現在

環境系統分析


Weather

議題矩陣四：環境系統分析觀點下的跨組連結

Climate


過去未來

脆弱度評估

調適治理




現在

環境系統分析


Weather

議題矩陣一：部會觀點下的跨組連結

議題矩陣二： IPCC AR5 觀點下的跨組連結

1818計畫網絡分析

主要工作總計畫環境組評估組治理組

核心分組各分組主要目標

總計畫1.提高民眾氣候變遷脆弱度調適科技認知2.建構產、官、學界溝通知識平台3.促進氣候變遷調適科技國際合作

環境組1.提供監測資料加值分析之資訊以掌握生態環境狀態與變化趨勢2.發展以長期監測資料為依據之應變性調適科技3.提出強化監測系統之監測能力建構

評估組1.發展跨領域脆弱度評估之方法與工具以瞭解未來之挑戰2.發展以中長期評估為依據之規劃性調適科技3.提供脆弱度與回復力指標系統與評量工具

治理組1.發展風險治理工具2.發展土地規劃方法3.科學技術輸出與合作架構與流程

核心分組各分組主要工作項目

總計畫1. 撰寫科學報告2.建構產、官、學界知識平台與發展風險溝通方法與機制3.推動氣候變遷調適科技國際合作

環境監測組

1.提供監測資料加值分析之資訊以掌握生態環境狀態與變化趨勢2.發展以長期監測資料為依據之應變性調適科技3.提出強化監測系統之監測能力建構4. 示範計劃推動

脆弱度評估

1.發展跨領域脆弱度評估之方法與工具以瞭解未來之挑戰2.發展以中長期評估為依據之規劃性調適科技3.提供脆弱度與回復力指標系統與評量工具4. 示範計劃推動

調適治理

1.發展風險治理工具2.發展土地規劃方法3.科學技術輸出與合作架構與流程4.社會、人文、與法制議題規劃

環境監測組脆弱度評估組調適治理

鑑別問題跨領域問題

DIKW IKW

工具發展

1. 跨領域評估工具2. 各領域評估工具指標與評量系統

3. 資訊規格與轉換

調適科技

知識平臺

科學報告

總計畫

簡報：劉振榮副校長

總計畫環境組評估組治理組

屬性 D1

D2

D3

D4

D5

D6

S1

S2 S3 S4 S5 S6R1

R2 R3

跨組性

網絡性

整合性

創新性

海洋監測

資料加值

大氣監測

陸地監測

地質監測

海岸監測

生態監測

脆弱評估

能力建構

環境災害

公共衛生

糧食安全

生態系統

水資系統

風險管理

科技規劃

國土規劃

調適科技推動

跨組運作

統籌規劃

示範計畫

國際網絡

整合產出

科學報告

知識平台

評量系統

社會大眾

政府學術

規劃

執行

修正

「台灣氣候變遷推估與資訊平台建置計畫」(TCCIP)

「氣候變遷研究聯盟」(CCliCS)

子項工作

總計畫相互支援

相互支援

彙編氣候變遷衝擊與調適科學報告

發展土地利用規劃之氣候調適措施

氣候衝擊與永續環境科技規劃報告( 總體研究統籌與規劃 )

IPCC AR5 WGII相關章節

國家氣候變遷調適政策綱領 ( 草案 ) 與

部會行動計畫對應支援

建構氣候變遷衝擊與調適知識平台

建立氣候調適研究國際網絡

TaiCCAT 執秘

子計畫 D1 ( 召集 ), D2, D3, D4, D5, D6

環境組

子計畫 S1 ( 召集 ), S2, S3, S4, S5, S6

評估組

子計畫 R1 ( 召集 ), R2, R3

治理組

建立氣候變遷衝擊與調適評量系統

TaiCCAT 副執秘

類別姓名服務機構 /系所職稱在本研究計畫內擔任之

具體工作性質、項目及範圍＊每週平均投入

工作時數比率 (%)

總計畫主持人

劉振榮國立中央大學

太空及遙測研究中心

教授副校長

氣候衝擊與永續環境科技規劃報告( 總體研究統籌規劃 )

( 子項工作 1)

20%

共同主持人

童慶斌(評估組召集 )

國立台灣大學生物環境系統工

程學系

教授主任

氣候變遷衝擊與調適科學報告彙編( 子項工作 2)

氣候變遷衝擊與調適知識平台建構

( 子項工作 3)

20%

共同主持人

李明安(環境組召集 )

國立海洋大學海洋科學與資源

學院

教授院長

20%

共同主持人

張靜貞(治理組召集 )

國立台灣大學中央研究院

教授研究員

20%

共同主持人

王國英國立中央大學環境研究中心

教授主任

20%

共同主持人

詹士樑國立台北大學不動產與城鄉環

境學系

教授主任

示範計畫土地使用規劃之氣候調適措施發展

( 子項工作 4)

20%

共同主持人

李河清國立中央大學通識教育中心

教授氣候調適研究國際網絡建立

( 子項工作 5)20%

博士後研究

江益璋國立中央大學環境研究中心

博士後研究員

支援子項工作 1, 4, 5；支援治理組協同評估組建立

氣候變遷衝擊與調適評量系統100%

博士後研究

李家齊國立中央大學環境研究中心

博士後研究員

支援子項工作 1, 2, 3；支援評估組協同治理組建立

氣候變遷衝擊與調適評量系統100%

運作機制宗旨：跨組協調、進度掌握、成果發表、相關部會與研究單位

協調與聯繫、整合工具與資訊平台建立辦公室 (推動小組 )

主持人：劉振榮副校長執行秘書：李和清教授副執行秘書：童慶斌教授環境組代表：李明安院長、林唐煌教授評估組代表：盧虎生教授、蘇慧貞教授調適組代表：張靜貞教授、詹士樑教授博士後研究人員、研究助理、行政助理

會議參與各組會議與進度訪視：每月推動小組會議：每季召開諮詢委員會：半年召開

研究產出說明

鑑別問題現況災害問題、跨領域問題、空間分散風險問題、民眾與政府共同承擔風險問題、產業與科技發展機會

資料分析監測資料、評估模式所需資料、氣候推估資料

工具發展資料資訊轉換工具、評估工具、溝通工具、決策工具

調適科技軟性科技與硬性科技

知識平台問題說明、 DIKW、標準流程、評估工具、調適知識與科技

科學報告現況分析、未來挑戰評估、調適措施研擬、未來機會探討

國際網絡方法文件標準化、尋求合作夥伴、發展推廣策略

總計畫環境組評估組治理組D1

D2

D3

D4

D5

D6

S1

S2 S3 S4 S5 S6R1

R2 R3

示範計畫

國際網絡

統籌規劃

科學報告

評量系統

知識平台

海洋監測

資料加值

大氣監測

陸地監測

地質監測

海岸監測

生態監測

脆弱評估

能力建構

環境災害

公共衛生

糧食安全

生態系統

水資系統

風險管理

科技規劃

國土規劃

S

D

R

ik資訊詮釋知識發展

di資料加值資訊提供

kw知識應用智慧發展

[脆弱度 ]

[ 暴露度 ]

[調適力 ]

提出需求

提出需求

統籌規劃

Ddi-Sik-Rkw

都會鄉村山地海岸流域離島

總計畫環境組評估組治理組D1

D2

D3

D4

D5

D6

S1

S2 S3 S4 S5 S6R1

R2 R3

示範計畫

國際網絡

統籌規劃

科學報告

評量系統

知識平台

海洋監測

資料加值

大氣監測

陸地監測

地質監測

海岸監測

生態監測

脆弱評估

能力建構

環境災害

公共衛生

糧食安全

生態系統

水資系統

風險管理

科技規劃

國土規劃

示範計畫

Ddi-Sik-Rkw

ik資訊詮釋知識發展

kw知識應用智慧發展

S R[脆弱度 ]

[調適力 ]

di資料加值資訊提供

D[ 暴露度 ]

不要堤防的居民？

訪談：總計畫 + 評估組 + 水規所 (2011.10.28) 聚落：東石鄉網寮漁村 ( 海岸地區 )；環境：地層下陷區、外水 ( 海水 )高於內水；

1986(淹 30天 )、 1990(淹 39天 )、 1992(淹 13天 ) 情境：不常淹水、堤防「圍村」且不便漁業調適：傢俱墊高鹽田滯洪跳上漁筏觀點：當科學知識遇到地方知識

海岸

都會

鄉 (漁 )村

都會鄉村山地海岸流域離島

國際網絡資料加值監測科技資訊解讀評估科技知識應用調適科技

氣候變遷調適科技推動

3636

2011

2012

3737

芬蘭：論文發表the Second Nordic International Conference on Climate Change

Adaptation, Helsinki, Finland, 29-31; http://www.nordicadaptation2012.net/

德國：知識平台Climate Service Center, Hamburg; http://www.climate-service-center.de/

德國：科技法律Center for Environmental Research - UFZ; http://www.ufz.de/index.php?

en=11382

荷蘭：示範計畫Delft University of Technology, Department of Urbanism;

http://www.bk.tudelft.nl/en/about-faculty/departments/urbanism/

日本：論文發表International Conference on Science and Technology for Sustainability;

http://www.scj.go.jp/ja/int/kaisai/jizoku2011/program.html

英國：論文發表Planet Under Pressure 2012; http://www.planetunderpressure2012.net/

美國：論文發表ISA ANNUAL CONVENTION 2012; http://www.isanet.org/blog/2011/04/cfp-

isa-annual-convention-2012.html

荷蘭：洪水治理UNESCO-IHE Institute for Water Education; http://www.unesco-ihe.org/

台灣：國際會議International Symposium on Climate Change Adaptation Technology, 15

September 2012, Taiwan; http://taiccat2012.blogspot.tw/

菲律賓：糧食安全International Rice Research; http://www.irri.org/

歐盟：評量系統CLIMSAVE - climate change integrated assessment methodology for

cross-sectoral adaptation and vulnerability in Europe; http://www.climsave.eu

美國：論文發表24th Annual Conference International Society for Environmental

Epidemiology; http://saeu.sc.edu/reg/isee2012/

Regional climate models

Agriculture and forestry

Energy economics

Water management

Coastal protection

Urban planning and building

Education and communication

Tourism

Traffic

39

2008 to 2014

7 joint regional projects

about 80 million €

德國 UFZ ：調適法規荷蘭 Delft ：空間規劃德國 CSC ：氣候資訊

芬蘭會議：成果發表荷蘭 Delft ：研究交流德國 KomPass ：知識平台

芬蘭會議： IPCC-TaiCCAT交流德國 CSC ：研究交流荷蘭 Delft ：低地考察

IPCCRichard Klein

TaiCCAT江益璋

IPCC SREX Lead AuthorProf. Richard Klein 意見 (2012.9.28)： Judging from the information

provided (TaiCCAT poster), this is a large and ambitious programme.

It's good to see the emphasis on governance, and the integration with disaster risk reduction.

I would be interested in reading more about the programme.

芬蘭會議：成果發表

芬蘭會議： IPCC-TaiCCAT交流

IPCCRichard Klein

TaiCCATYi-Chang Chiang

評估組發表環境組發表芬蘭專題

治理組發表大會貴賓德國專題

綜合討論總計畫發表荷蘭專題

氣象局程主任意見 (2012.9.16) ( 張靜貞老師提供 )： CWB is trying to find partners in various

application areas to promote end-to-end services. I believe TaiCCAT project would be a very good partner that CWB could work with.

綜合討論

I do hope that TaiCCAT would so like to cooperate with government agencies and/or act as a bridge to link government agencies (supplier and consumer) together for better decision making.

總計畫環境組評估組治理組

D1 D2 D3 D4 D5 D6 S1 S2 S3 S4 S5 S6 R

1 R2 R3

海洋監測

資料加值

大氣監測

陸地監測

地質監測

海岸監測

生態監測

脆弱評估

能力建構

環境災害

公共衛生

糧食安全

生態系統

水資系統

風險管理

科技規劃

國土規劃

CASE TAIWANTechnical report

科學報告

知識平台

人類環境氣候

暴露度脆弱度調適力

Data

information

knowledge

wisdom

脆弱度評估環境系統分析調適治理

Driver Response

State

D di S ik R kw

資料加值監測科技資訊解讀評估科技知識應用調適發展

氣候變遷調適科技推動

評量系統學術大眾政府

鑑別問題 v v v

DIKW DIKW IK KW

工具發展 v v

調適科技 v v v

知識平臺 v v v

科學報告 v v v

核心分組各分組主要工作項目第一年第二年第三年

總計畫1. 撰寫科學報告2.建構產、官、學界知識平台與發展風險溝通方法與機制3.推動氣候變遷調適科技國際合作

環境組


評估組


治理組

1.發展風險治理工具2.發展土地規劃方法3.科學技術輸出與合作架構與流程4.社會、人文、與法制議題規劃

核心分組各分組預期成果

總計畫

1.完成科學報告2.完成產、官、學界知識平台3.提出風險溝通方法與機制4.建立實質氣候變遷調適科技國際合作計畫

環境組


評估組


治理組

1.發展氣候變遷風險治理工具2.發展氣候變遷土地規劃方法3.科學技術輸出與合作架構與流程4.社會、人文、與法制議題規劃

環境組

簡報：李明安教授

環境組目標：掌握氣候與生態環境現況變化趨勢與研究發展以監測為依據之近程因應措施，強化監測系統

組成： D1： D2： D3： D4： D5： D6：

這一年來的重要成果： Urban heat Island Landslide prediction model (Shihmen

Reservoir) SST rise in Taiwan Strait Environment & food security for mullet

fishery Air-sea interaction for peng-hu cold water

intrusion Land-sea interaction for sand reduce

Urban Heat Island over Greater Taipei Region (GTR)

ISA1990

Tb1990

UHI1990

ISA1996

ISA2005

Tb1996

Tb2005

UHI1996

UHI2005

(Landsat data used from 1990 to 2009)

+ Brightness temperature of test areas in different season(1999-2003)

U2

U1

U3

R1

R2S3

R3

S1

S2

area1

area2

area3

• U1: Urban1• U2: Urban2• U3: Urban3

• S1: Suburban1• S2: Suburban2• S3: Suburban3

• R1: Rural1• R2: Rural2• R3: Rural3

(Size: 50x50 pixels)

• Forest• Taipei

metropolitan

spring summer winter

Taiwan 20.09 25.06 18.95

Urban 25.12 29.82 22.76

Plain 24.87 26.87 21.13

Tableland 22.4 23.87 20.71

Mountain 14.52 15.99 11.31

12

16

20

24

28

Brightness temperature (Tb) in different season

Bri

ghtn

ess

Tem

per

atu

re (

C

)

582012/2/23

Investigation of UHI and regional precipitation

2000

2100

2200

2300

2400

2500

2600

Year

prec

ipit

ati

on

(mm

)Urban Precipitation (1987~2010)

3

4

5

1961 1969 1977 1985 1993 2001 2009

Year

UH

II(℃

)

Taipei Heat Island (1972~2009)

1000

1500

2000

2500

3000

1940~1950 1950~1960 1960~1970 1970~1980 1980~1990 1990~2000 2000~2010

Pre

cip

itio

n(m

m)

4000

4500

5000

5500

Pre

cip

ition

(mm

)

台北站竹子湖站

Urban and Rural Precipitation

50 10 15 20 25 30 35 40 45 5050 10 15 20 25 30 35 40 45 50

120 E 122 E

MODIS/Terra 2000/07/14 03:10 UTC

25 N

23 N

℃ 50 10 15 20 25 30 35 40 45 5050 10 15 20 25 30 35 40 45 50

120 E

25 N

122 E

23 N

℃

MODIS/Terra 2008/07/24 0230 UTC

2000

38.7

36.3

31.1

36.136.9

28

30

32

34

36

38

40

LS

T(

℃)

33.3

35.5

31.2

32.6

35.4

28

30

32

34

36

38

40

2000 2002 2004 2006 2008Year

LS

T(

℃)

Taipei City

Kaohsiung City

2008

~1990

訓練樣區 NDVI 時序資料

Urban development and heat island over Greater Taipei Region (1990-2009)

60

Land Surface MonitoringWork Scopes

1. Statistical models for landslide and debris flow prediction: Following Lee et al. (2008),we develop new models for landslide and debris flow prediction, and apply to drainage basin of the Shihmen

Reservoir and the Tsengwen River basin. Prediction under extreme rainfall condition will be discussed also.

2. Soil depth estimation: We develop empirical formula for estimation of soil depth at hill slopes by using local data. This formula will be used in estimation of sediment budget and calculation of sediment transport.

3. Simplified method for estimation of sediment budget: Using results from landslide prediction and soil depth estimation, we calculate sediment

budget in each drainage basin. This result can be used to compare with the result from our drainage basin sediment transport system.

4. Geostatistical interpolation of rainfall parameters: Topographic data are joined with rainfall data and a regression Kriging method is used

to perform interpolation for different rainfall parameters. These will be used in landslide and debris flow prediction models and in the drainage

basin sediment transport system.5. Developing a drainage basin sediment transport system: Surface

erosion and channel transport mechanisms will be added in to a drainage basin hydrological model to develop a sediment trasport system.

61

Topographic data, hydrological data, geological data, landslide and debris flow data, and landuse data

DEMGeologic

MapActive Faults

Landslides

Debris Flows

Land Surface MonitoringData Collections

62

Topographic data, hydrological data, geological data, and landuse data, etc. are processed and further used in establishing a

statistical prediction model.

Rainfall Intensity

Slope Slope Roughness

Profile Curvature

NDVI Lithology

Relative Height

Total Slope Height

Wetness Index

Distance to Fault

Land Surface MonitoringData Analysis for landslide prediction

model

63

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

0.64030.007587( )1slP

AUC=0.856

LS sus.index,λ

LS prob., P

sl

Landslide probability curve for Typhoon Aere

Success rate for model AereLandslide probability map under

Aere rainfall

Portion of area

Success

rate

Landslide probability map for Typhoon Aeret and for 100-year return period rainfall at drainage basin of the Shihmen Reservoir

( 石門水庫 ).

Landslide probability map under 100-year return period rainfall

Land Surface MonitoringLandslide Prediction model

Figure Distribution of oceanographic station data around Taiwan (>150,000 sts).

Mapped are all available data from the World Ocean Database‐2009, updated 2011‐04‐21. Shown are only those stations that have both temperature (T) and salinity (S).

Created by Daphne Johnson, National Oceanographic Data Center, NOAA.

-1

-0.5

0

0.5

1

1.5

1981 1984 1987 1990 1993 1996 1999 2002 2005 2008

年別

SST

A (℃

)

SSTA

-1.5

-1

-0.5

0

0.5

1

1.5

2

1957

1960

1963

1966

1969

1972

1975

1978

1981

1984

1987

1990

1993

1996

1999

2002

2005

2008

年別

SS

TA

(℃)

SSTA

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1981 1984 1987 1990 1993 1996 1999 2002 2005 2008

年別

SST

A (

℃)

SSTA

SST increase 1℃

SST increase1.2℃SST increase 1.1℃

SST increase +1.15±0.19 /100 yr ℃

(Source:本研究團隊 )

(Source: nagasaki uni.)

Multi-decadal variability of oceanic climate in the Taiwan Strait was studied using sea surface temperature (SST), which is the most conveniently measured and frequently observed variable related to maritime

climate. We used the 1 degree x 1 degree monthly climatology of SST available from the U.K. Met Office Hadley Centre. Between 1957 and 2011, three distinct regimes were identified. The first regime of fairly

stable or slightly cooling SST lasted through 1976. The regime shift of 1976-1977 led to a super-fast warming of 2.1°C in 22 years, from 23.2°C in 1976 up to 25.3°C in 1998. Another regime shift occurred in

1998-1999, leading to a 1.0°C cooling from 1998 to 2011. The spatial distribution of climate trends across the Taiwan Strait was studied for the first time, revealing a strong spatial gradient along the Strait. In the north (southern East China Sea), the magnitude and rate of the overall SST warming between 1957 and 2011 was

about three times those in the south (northern South China Sea).

Feeding ground

Spawning ground

Grey mullet Caught around

Taiwan has spawning and

nursery grounds in the coastal

waters of southwestern Taiwan, and

feeding grounds of juveniles and

adults are located in the coastal waters

of mainland China about

between latitude 25 and 30 N

Grey mullet

It migrates into the coastal

waters of west Taiwan during

the winter solstice.

Question: The cause of the fluctuation and decline in catch? Overfishing or Climate

change ?

Year

Ca

tch

(1

03n

um

be

r)0

500

1000

1500

2000

2500

3000

1968 1973 1978 1983 1988 1993 1998 2003 2008

Catch

Mean

Since 1958 the annual catch of grey mullet has fluctuated greatly with a peak of 2.54 million fish in 1980 and a minimum of 0.4

million fish in 1990 and 0.2 million in 2000 to 2004. In recent years, it has rapidly declined to about 45 thousands/year in 2007~2009,

causing a concern to its management agency.

2.54 million

Overfishing (Huang et al., 2005)

×

Cross-wavelet coherence between climatic index (a) annual PDO (b) winter WPO (c) autumn ONI and (d) sea surface

temperature with log10 (grey mullet catches).

1958-1978 6–8 yr

8 yr

1–2 yr

2–3 yr

Annual trends of (a) grey mullet catches (black line) and PDO (grey line) and (b) winter SST (black dotted line) from 1958 to

2009.

The annual PDO, the time series trends of annual

catches and PDO showed a fairly good correspondence

A declining trend of the fluctuation in catches and raised trend in winter SST

after 1980s

The PDO might play a role in affecting the grey mullet migrated but the increased of SST would also an important reason caused the

decreased and low catches of grey mullet after 1980.

The catch percentage of grey mullet caught by the Taiwanese fishing boats and collected from the local fisherman

associations in the west coast of Taiwan (a) 1978–1987 (b) 1988–1997 and (c)

1998–2009.

More than 85% of grey mullet was caught in the south of 23.5°N in 1978–1987 in the eastern Taiwan Strait.

In 1988-1997, the fishing grounds moved to north and more than 30% grey mullet was caught in the latitude of 24.5°N where was the low catch fishing ground in 1978–1987, while the parts of fishing grounds moved to north of 25°N after 1998–2008

The latitudinal variation of the 20 °C isotherm of 1958–1967 (purple line), 1968–1977 (brown

line), 1978–1987 (green line), 1988–1997 (blue line), 1998–2009 (Red line), and the IPCC A2

scenario in SSTs of 2050 and 2075 (grey lines) in the western Taiwan in winter.

There is a consistency of north shifted between the grey mullet fishing grounds and the latitudinal variation of the 20 °C isotherm of western Taiwan in winter, while the 20 °C isotherm moved to north of 25°N of the western Taiwan after 1998.The scenario results shows the 20 °C isotherm of wintertime in the west Taiwan will move to 25.5°N in 2050 and cross the 26°N in 2075. The results suggested the climate change caused the increased of SST and weaken the intrusion of the Coastal Current into the Taiwan Strait. Moreover, the phenomena might decreased the abundance of mullet migrated into western Taiwan and shifted the fishing grounds to north part.

Environment- Food security

Air-Sea interaction for observation on Fisheries and Mariculture impact by Extreme Oceanic Environmental Changes in Taiwan

The fishery resource (included cobia and grouper ) disaster with the economic fishery losses about NT$350

million (US$ 11 million) in February 2008.

It suggested that the continuous strong wind might have driven the cold current more southeasterly to the

southern TS and resulted in the great drop in SST.

Sand area in 2009 is smaller 40 % than that in 2012.

FS2 Image (2m) 2009/09/01

2010/09/26

2011/09/30 2012/06/28

Year 2009 2010 2011 2012Area (Ha) 5.59 5.15 3.43 3.40

THE TAICCAT CONFERENCE 09/15 2012

未來工作之預期產品： Urban heat island (UHI) and land use

index Landslide prediction model in Zengwun

Reservoir Ocean warming variability and micro-

climate SST index Dry/flooding, Coast erosion and

inundation index in Chianan Plain. Ci-Gu wetland/Lagoon habitat biodiversity

環境組整合運作方式：就不同空間類型進行組內資料整合與變遷指標分析；例如：

五都之 UHI and land use ( 大氣與陸地資料整合 ) 曾文水庫邊坡崩蹋預測模式 (地質與脆弱度 - 河川水文資料與

模式整合 ) 澎湖離島之大氣海洋交互預警模式與漁業糧食安全及調適策略分析

嘉南平原旱澇指標 ( 大氣與海洋及 TCCIP資料整合分析 ) 極端環境或微氣候變遷的加值資料分析；例如：

提供在極端氣候 - 颱風之影響下的流域 ( 含水庫 ) 崩蹋預測模式

提供嘉南平原旱澇指標的週期變動加值分析

Environmental system analysis on micro-climate and value-added indicator surrounding Taiwan in next 3-year study

Coast

Ecology

City development

UHIclimat

eplant

geology

Inundation

erosion

landslide

coast

pollution

Dry/floodwarm

Foodfisherydisast

er

Water resourc

eBio-

diversity

Environmental system

monitor and data bank

(monitor and analysis)

simulate

Regional climate(Air-tem、 Precip、

Key factor)&

Auxiliary data(GIS)

Public health

Eco-system

Food Securit

y

Disaster

Vulnerability

Assessment

Water

resource

Interaction of TaiCCAT environment Group and TCCIP

Adaptation

Governance

TCCIP-regional climate model(NCDR)

Micro-

Climate

Key

Factor

Value-

added

analysis

Atmosphere

Land

Geology

Ocean

Datasets now available

TCCIP_precip_1km.monthly.nc

TCCIP_precip_5km.monthly.nc

TCCIP_tavg_1km.monthly.nc

TCCIP_tavg_5km.monthly.nc

TCCIP_tmax_1km.monthly.nc

TCCIP_tmax_5km.monthly.nc

TCCIP_tmin_1km.monthly.nc

TCCIP_tmin_5km.monthly.nc

TCCIP_SPEI_1km.xxm.nc* (xx=01, 02,… 48)

Datasets now available (1 Jan 1960 – 31 Dec 2009)

TCCIP_precip_1km.daily.ncTCCIP_precip_5km.daily.nc

(November 2011)

SPEI: Standardized precipitation – evapotranspiration index

Grid-data from TCCIP

Time period: 1960 –2009Month: 1km/5km

tem、 precipDay : 1km/5km precip

與過去研究或現在其他單位計畫之差異： CCliCS for model development & Scenario and TCCIP for

down-scaling and historical data bank. EA: Focus on Micro-climate change and value-added data analysis.

回應部會不同面向 ( 如多樣性與海岸帶管理 )所需指標之分析透過 TCCIP, 總計畫 ,環境組 ,脆弱度及調適治理之整合 ,可針

對極端環境或微氣候變遷所帶來的衝擊 ,提出適切回應；例如：颱風過後 (環境面向 - 大氣 , 陸地 , 海洋與海岸 ), 對養殖漁業

( 糧食與衛生安全 ) 造成衝擊 ,而後續的補償措施 (調適治理 ) 澎湖冷水入侵 (環境面向 - 大氣海洋 )之微氣候變遷造成沿岸

漁業及養殖漁業 ( 糧食與衛生安全 ) 造成衝擊 , ,而後續亦可有適當的調適措施 (調適治理 )

After typhoon, the oyster aquaculture raft was damaged by heavy flooding.

FS2 Image (2m) of 2012/06/08

2012/06/28

Before typhoon, the oyster aquaculture raft was easily

identified by Formosa image.

FS2 Image (2m) of 2012/06/08

-40

-20

0

20

40

60

80

100

120

Day of wind speed > 6 m/s

Dis

tan

ce

of

20

ºC is

ob

ath

refe

rrin

g t

o P

HI (

km

)

02468101214161820222426283032

Da

y o

f w

ind

sp

ee

d >

6 m

/s

Micro-climate case: Warning system of Fisheries and Mariculture to Extreme Oceanic Environmental Changes in Taiwan

-60

-40

-20

0

20

40

60

80

100

<6 7~12 13~18 >19

Period (day)

Dis

tanc

e of

20

isob

ath

refe

rrin

g to

PH

I (km

)

The fishery resource (included cobia and

grouper ) disaster with the economic fishery losses

about NT$350 million (US$ 11 million) in

February 2008.

In 2008 In 2011

More than 1600 and 1000 tons of cage aquaculture fish perished in 2008 and 2011.

http://blog.roodo.com/upupph/archives/15140175.html

Data Source: Central Weather Burial, Taiwan

Cobia, Black king fish(Rachycentron canadum)

Sea Surface Temperature in PHI, 2011.

Flowchart of the decision-making process for cage aquaculture adaptation.

(Marine policy, accepted in 2012)

評估組

簡報：童慶斌教授

評估組目標：評估未來氣候變遷風險，界定不同領域議題間問題，發展跨領域脆弱度評估標準分析流程、評估模式與量化指標系統（永續發展、脆弱度與回復力），並訂定資訊規格與研究發展以評估為依據之中長程調適科技。

組成： S1： S2： S3： S4： S5： S6：

治理組

簡報：張靜貞教授

治理組目標：檢討政策並提出修正建議，並提出政策預警與

結合風險管理之決策機制，包括土地利用規劃與科學發展與推廣策略。

組成： R1： R2： R3：

這一年來的重要成果： Integrated Risk Assessment

Literature Review Profile of Taiwan Capacity Building

Design Analytical Framework to Enhance economic efficiency of resource

allocation decisions Promote transparent and accountable choices

between multiple options Facilitate inclusive decision-making processes

involving diverse stakeholders Conduct Case Studies

122

Source: Swiss Re Economic Research & Consulting, 2011

1. 天災之經濟損失與保險理賠之差距逐年擴大中

2. 這些經濟損失可以透過各式天災財務工具來管理

Integrated Risk Assessment: Literature Review

圖 1 2010 年前八大巨災經濟損失

22,000

7,800

400 700 550 3,000

9,475 6,100

8,000

200

3,300 2,000 1,450

3,100

25

0

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

智利海地紐西蘭美國Hail 美國 Tornadoes 歐洲Xynthia 巴基斯坦中國

地震颶風水災

未保險之損失保險損失單位：百萬美元

Source：Munich Re (2011), Overall picture of natural catastrophes in 2010, Newsletter

123

1. 各國開發程度與投保天災險之差異影響到獲得理賠之比例

2. 天災保險與風險分散機制對民間與政府之好處

Source: Swiss Re Economic Research &

Consulting, 2011

資料來源： Jones and Preston (2010)。

Methodology Based on UN Definitions: Risk = Element at Risk* Natural Hazard* Vulnerability Element at Risk: Whether staple production meets demand Vulnerability: Number of events, Econ loss, Population affected Resilience: Per capita income per year

Ranking Criteria :(1) number of disaster per year; (2) percentage of population affected per year; (3) percentage of economic losses in GDP per year; (4) per capita income per year.

Three rankings from different summations, i.e.,

(1)+(2)+(4), (1)+(3)+(4), (1)+(2)+(3)+(4)

Integrated Risk Assessment: Risk Profile of Taiwan

　 Country

Number of

Disaster per year

(1)

　

% of Population Affected

(2)

　% of Econ

Losses in GDP (3)

　 Per Capita Income (4) 　

(no.) score (%) score (%) score

(US$) score

Australia 4.6 1.95 0.28 1.13 0.25 1.37 52,273 1.00 Brunei 0 1.00 0.00 1.00 0.00 1.00 32,049 2.30 Canada 2 1.41 0.00 1.00 0.01 1.01 45,132 1.14 Chile 2.2 1.45 3.54 2.61 3.34 5.00 11,074 4.14 China 23 5.00 8.76 5.00 0.60 1.88 3,871 4.78 Hong Kong 1 1.21 0.04 1.02 0.00 1.00 31,208 2.37 Indonesia 13.2 3.72 0.41 1.19 0.14 1.20 2,585 4.89 Japan 4.4 1.91 0.10 1.04 0.88 2.29 40,100 1.59 Rep of Korea 1.2 1.25 0.02 1.01 0.00 1.00 20,486 3.31 Malaysia 1.6 1.33 0.15 1.07 0.10 1.15 7,785 4.43 Mexico 6.4 2.32 0.91 1.41 0.20 1.30 9,708 4.26 New Zealand 0.8 1.16 2.93 2.34 2.51 4.67 31,904 2.31 P N Guinea 3.2 1.66 0.84 1.39 0.00 1.00 1,357 5.00 Peru 3.2 1.66 1.74 1.80 0.09 1.13 4,681 4.71 The Philippines

19.4 5.00 8.00 4.65 0.25 1.37 1,962 4.95

Russia 2.6 1.54 0.01 1.01 0.05 1.08 10,599 4.19 Singapore 0 1.00 0.00 1.00 0.00 1.00 40,911 1.51

Taiwan 2.2 1.45 2.02 1.92 0.07 1.11 18,194 3.52

Thailand 4 1.82 11.71 5.00 2.74 5.00 4,529 4.72 USA 16.4 4.38 0.94 1.43 0.16 1.23 46,745 1.00 Viet Nam 6.8 2.40 2.05 1.94 0.74 2.08 1,097 5.00

Natural Disaster Risk in APEC, 2007-2011

Data Sources: EM-DAT DB, FAOSTAT, IMF (World Economic Outlook Database, September 2011)

　 CountryAverage score of

(1)+(2)+(4)Ranking LEVEL

Average score of (1)+(3)+(4)

Ranking LEVELAverage score of (1)+(2)+(3)+(4)

Ranking LEVEL

(1) (1) (1) (2) (2) (2) (3) (3) (3)Australia 1.36 19 L 4.31 18 L 5.44 18 LBrunei 1.43 18 L 4.30 19 L 5.30 19 LCanada 1.19 20 L 3.56 20 L 4.57 20 LChile 2.74 6 H 10.60 4 H 13.21 4 HChina 4.93 1 H 11.66 1 H 16.66 1 HHong Kong 1.53 16 L 4.58 17 L 5.60 17 LIndonesia 3.27 4 H 9.81 5 H 11.00 6 HJapan 1.51 17 L 5.78 15 L 6.83 15 LRep of Korea

1.86 15 L 5.56 16 L 6.57 16 L

Malaysia 2.28 11 L 6.91 11 M 7.98 13 MMexico 2.67 9 M 7.88 8 M 9.30 8 MNew Zealand

1.94 14 M 8.14 7 H 10.48 7 H

P N Guinea 2.68 8 M 7.66 9 M 9.05 10 MPeru 2.72 7 H 7.50 10 M 9.29 9 MPhilippines 4.87 2 H 11.32 3 H 15.97 3 HRussia 2.24 13 M 6.80 12 M 7.81 14 MSingapore 1.17 21 L 3.51 21 L 4.51 21 LTaiwan 2.30 10 M 6.08 14 M 8.00 12 MThailand 3.85 3 H 11.55 2 H 16.55 2 HUSA 2.27 12 M 6.61 13 M 8.04 11 MViet Nam 3.11 5 H 9.48 6 H 11.42 5 H

Natural Disaster Ranking in APEC, 2007-2011

Governance and Institutional Framework

Information and Knowledge Platform

Education and Training

Integrated Risk Assessment: Capacity Building

Successful Adaptation requires Scientific knowledge of climate change

and vulnerability Systematic monitoring of climate,

ecosystem, and social-economic impacts Long-term planning for infrastructure Public education to encourage collective

actions Enforcement on proper societal

adjustment and practices

Design Analytical Framework: Key Elements

1. 發展風險評估工具與決策模式

2. 進行利害關係人之風險溝通

3. 排定優先順序與策略規劃

Design Analytical Tools

132

1. Stochastic Event Module

3. Vulnerability Module

2. Hazard Module

4. Financial Loss Module

Overall Framework of Flood Risk Engineering Model

Case Study: Flood Risk

Policy Options Land Use Planning Building Code Disaster Relief Insurance Program Financing Calculate premiums under different

assumptions on take-up rate. Government’s bottom-layer coverage are

assumed as premium subsidy.

133

Premiums under 4 scenarios with alternative take-up ratesScenario

Take-Up Rate 25% 50% 100% 25% 50% 100% 25% 50% 100% 10% 50% 100%

Estimated Policy# 825,000 1,650,000 3,300,000 825,000 1,650,000 3,300,000 825,000 1,650,000 3,300,000 37,000 185,000 370,000 AAL (NT$ Mill.) 2,738 5,475 10,950 1,575 3,150 6,300 1,163 2,325 4,650 2,160 4,320 4,320

Pure Premium w/o bottom GOV Cover $3,318 $3,318 $3,318 $1,909 $1,909 $1,909 $1,409 $1,409 $1,409 $58,378 $23,351 $11,676

Estimated Policy# 1,075,000 2,150,000 4,300,000 1,075,000 2,150,000 4,300,000 1,075,000 2,150,000 4,300,000 75,000 375,000 750,000 AAL (NT$ Mill.) 324 648 1,296 324 648 1,296 324 648 1,296 605 1,210 1,210

Additional Premium to Include Livingexpense & Electrical & MechanicalEquipment Loss Cover w/ Limit of

NT$20,000

$301 $301 $301 $301 $301 $301 $301 $301 $301 $8,067 $3,227 $1,613

Estimated Policy# 1,900,000 3,800,000 7,600,000 1,900,000 3,800,000 7,600,000 1,900,000 3,800,000 7,600,000 112,000 560,000 1,120,000 AAL (NT$ Mill.) 59 117 234 59 117 234 59 117 234 12 59 117

Additional Premium to Include ConstructedTotal Loss Cover of NT$120 Mill.

$31 $31 $31 $31 $31 $31 $31 $31 $31 $104 $104 $104

Pure Premium w/o bottom GOV Cover -First-Floor Household

$3,349 $3,349 $3,349 $1,940 $1,940 $1,940 $1,440 $1,440 $1,440 $58,483 $23,456 $11,780

Premium w/ additional cost (15%) $3,940 $3,940 $3,940 $2,282 $2,282 $2,282 $1,694 $1,694 $1,694 $68,803 $27,595 $13,859

Pure Premium w/o bottom GOV Cover -Other Household

$332 $332 $332 $332 $332 $332 $332 $332 $332 $8,171 $3,331 $1,718

Premium w/ additional cost (15%) $391 $391 $391 $391 $391 $391 $391 $391 $391 $9,613 $3,919 $2,021

AAL ratio of Bottom 1 bn Layer 30.26% 16.25% 8.49% 44.31% 25.33% 13.35% 48.84% 29.94% 16.65% 40.01% 22.27% 22.27%

Pure Premium w/ bottom GOV Cover of 1billion - First-Floor Household

$2,336 $2,805 $3,065 $1,080 $1,449 $1,681 $737 $1,009 $1,200 $35,084 $18,232 $9,157

Premium w/ additional cost (15%) $2,748 $3,300 $3,606 $1,271 $1,704 $1,978 $867 $1,187 $1,412 $41,275 $21,450 $10,773

Pure Premium w/ bottom GOV Cover ofNT$1 billion - Other Household

$232 $278 $304 $185 $248 $288 $170 $233 $277 $4,902 $2,589 $1,335


AAL ratio of Bottom 1.5 bn Layer 41.85% 23.70% 12.65% 58.19% 35.84% 19.68% 62.04% 40.91% 23.97% 53.08% 31.79% 31.79%Pure Premium w/ bottom GOV Cover of

1.5 billion of First-Floor Household$1,947 $2,555 $2,925 $811 $1,245 $1,558 $547 $851 $1,095 $27,440 $15,999 $8,035

Premium w/ additional cost (15%) $2,291 $3,006 $3,442 $954 $1,464 $1,833 $643 $1,001 $1,288 $32,283 $18,823 $9,453

Pure Premium w/ bottom GOV Cover ofNT$1.5 billion - Other Household

$193 $253 $290 $139 $213 $267 $126 $196 $253 $3,834 $2,272 $1,172


AAL ratio of Bottom 2 bn Layer 50.87% 30.41% 16.69% 67.07% 44.36% 25.53% 69.51% 48.94% 30.28% 62.70% 40.01% 40.01%Pure Premium w/ bottom GOV Cover of 2

billion of First-Floor Household$1,645 $2,331 $2,790 $639 $1,079 $1,445 $439 $735 $1,004 $21,814 $14,071 $7,067

Premium w/ additional cost (15%) $1,936 $2,742 $3,282 $751 $1,270 $1,699 $516 $865 $1,181 $25,664 $16,554 $8,314


$163 $231 $277 $109 $185 $247 $101 $170 $232 $3,048 $1,998 $1,031


AAL ratio of Bottom 3 bn Layer 64.23% 41.91% 24.31% 79.02% 57.69% 35.97% 79.97% 61.24% 40.99% 75.40% 53.08% 53.08%Pure Premium w/ bottom GOV Cover of 3

billion of First-Floor Household$1,198 $1,945 $2,535 $407 $821 $1,242 $288 $558 $850 $14,387 $11,005 $5,527

Premium w/ additional cost (15%) $1,409 $2,289 $2,982 $479 $966 $1,461 $339 $657 $1,000 $16,926 $12,948 $6,503


$119 $193 $251 $70 $141 $213 $67 $129 $196 $2,010 $1,563 $806

Premium w/ additional cost (15%) $140 $227 $296 $82 $165 $250 $78 $151 $231 $2,365 $1,839 $948

S3 S7 S9 S11

Content Cover (3.3 Mill. First Floor Households) (0.37 Mill. First Floor Households)

Living Expense & Electrical & Mechanical Equipment Loss Cover-Limit of NT$ 20,000 (4.3 Mill. 2nd Floor above Households ) (0.75 Mill. Households)

Constructed Total Loss Cover-NT$120 Mill. (7.6 Mill. Households) (1.12 Mill. Households)

Premium w/o Bottom GOV Cover

Premium w/ Bottom 1 Billion GOV Cover

Premium w/ Bottom 1.5 Billion GOV Cover



Major Findings Government involvement is needed to increase

the amount of flood insurance in force Future Work Needed on Modeling Predictions and detection of large-scale natural disasters Integrate climate/hydrology/socio-econ database Improve flood hazard maps Collect risk mitigation/ flood exposure data Upgrade/calibrate risk assessment model Design of multi-peril assessment model

Policy Options –A Tool Box Farm Level: Diversification, insurance Add value to move away from raw product Adopt agricultural research

Supply Chain level: Add value by moving up value chain Improve food research Invest in better infrastructure New distribution methods (network v.s. hub and spoke)

Policy/Market level: Hedging options, price pooling, Food reserves Insurance tools Information (monitoring, early warning)

136

Case Study: Food Security Risk

• APEC Food Emergency Response Mechanism

• Purpose• As an Insurance

Pool for large risk

• Reduces public expenditures on expanding food reserves for natural disasters.

• Risk Assessment

CBA for Rice under Different OptionsData Source and Per Capita Consumption Target

Calculation 3-Month 2-Month 1-Month1. RiceTOTAL BENEFIT (ANNUAL) (1) Food Aid Needs in MT Table 4-6 2,662,873 1,775,098 887,624 (2) Marginal Value per MT in GDP Appendicx C-1 544.52 544.52 544.52 (3) Marginal Value per MT in Welfare Appendicx C-1 535.86 535.86 535.86 (4) Total Benefit in GDP (Mil US$) (4)= (1)*(2) 1,449.99 966.58 483.33 (5) Total Benefit in Welfare (Mil US$) (4)= (1)*(3) 1,426.94 951.21 475.65 TOTAL COST (ANNUAL) (6) Market Price per MT Appendix C-1 333.56 333.56 333.56 (7) Total Procurement Cost in Mil US$ (7)=(1)*(6) 888.22 592.09 296.07 (8) Total Adminstration Cost in Mil US$ Table 2-1 0.18 0.18 0.18 (9) Total Logistic Cost in Mil US$ (9)=(7)*0.27 239.82 159.87 79.94 (10) Total Cost (Mil US$) (10)= (6)+(7)+(8)+(9) 1,128.22 752.14 376.19 Benefit-Cost Ratio (11) in GDP (11)= (4)/(10) 1.285 1.285 1.285 (12) in Welfare (12)=(5)/(10) 1.265 1.265 1.264

• Great variety of options available to make society more resilient to climate risks

• Many components should included Private actors as well as Public policy National effort or with International cooperation

and coordination Risk reducing/sharing as well as

income/efficiency enhancing measures• Most policies require careful, critical appraisal

before being accepted• Need analytical tools• Need to collect information How to deploy and use them adequately and

effectively?

Conclusions

總計畫評估組

環境組治理組

謝謝聆聽

總計畫評估組

環境組治理組

氣候變遷調適科技整合研究計畫Taiwan integrated research program on Climate Change Adaptation Technology

tai ccat複審 總計畫3

Science

tai ccat複審總計畫3