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Climate Change and Extreme Weather Events Climate Forecast Applications for Disaster Mitigation in Southeast Asia S.H.M. Fakhruddin

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Presentation on theme: "Climate Change and Extreme Weather Events Climate Forecast Applications for Disaster Mitigation in Southeast Asia S.H.M. Fakhruddin"— Presentation transcript:

1 Climate Change and Extreme Weather Events Climate Forecast Applications for Disaster Mitigation in Southeast Asia S.H.M. Fakhruddin fakhruddin@adpc.net Senior Technical Specialist, Climate Risk Management Division

2 Discussion Topics Extreme Climate Events Program Climate Forecast Application (CFA) for Disaster Mitigation in Philippines and Indonesia Climate Forecast Application in Bangladesh (CFAB) for Flood Risk Management

3 CFA Program Overview Trigger: Developed in response to the severe impacts Niño 1997 98 Period: –1998-2003:Extreme Climate Events Program (documentation of impacts, analysis of institutional responses, identification of opportunities for forecast applications) –2003-2008: Climate Forecast Applications for Disaster Mitigation Program (tools development, capacity building, demonstration projects) Geographical coverage: Indonesia & Philippines (2003-2008) and Timor-Leste (2007-2009) Supported by: Office of Foreign Disaster Assistance of the United States Agency for International Development (OFDA-USAID) ADPC works with local, national, and international partners

4 CFA Demonstration Sites Angat Nusa Tenggara Timur Indramayu Dumangas, Iloilo

5 Indonesia 93% of drought years in Indonesia are linked to El Niño years Severe drought reduced rice yields, requiring to import 5.1 million tonnes of rice Economic crisis devalued rupiah by about 80%, pushing up price of imported rice to four times pre-crisis levels Forest fires - out of control in Sumatra and Kalimantan Philippines El Niño and peso depreciation collide and magnify impacts 60% depreciation of peso Per capita GNP declined by 2.7% Agriculture contracted by 7% and industry by 1.7% Food and basic commodity prices increased rapidly Socio-economic Impacts of ENSO 1997-98 in Indonesia & Philippines

6 El Niño impacts on rice production in the Philippines El Nino

7 El Niño onset years Impacts El Niño on paddy production in Indonesia Impacted = lost over 25% of yield relative to average yield

8 Countries needed timely, usable climate information to manage resources effectively & reduce disaster risks. However, localized & usable climate information was not available to resource managers

9 Reasons why climate information was not available Absence of participatory mechanism for identifying user forecast requirements Available climate information not tailored to users needs and requirements Weak forecast producer-user communication channel Users have difficulty understanding forecast language Community-level dissemination is weak Users have no mechanism for processing climate information once it is received Feedback channel from forecast user to producer is weak or nonexistent in most cases These are the gaps the CFA program aims to address

10 Need/ capacity assessments 1 2 3 4 5 6 Assessment of available technology Capacity building through partnerships Institutionalization of end-to- end system: pilot demonstrations, replication Apply information to enable pro-active decision making Monitor and evaluate applicability of information CFA Methodology: Six step process

11 Focused Intervention: Global climate information providers National institutions End- users

12 End-to-end climate information generation and application system Providing climate outlook Interpreting global climate outlook into local outlook Translating local climate outlook into impact scenarios Communication of response options/ feedback

13 Major Achievements of CFA Indonesia & Philippines

14 The CFA program is instrumental in establishing institutional mechanisms that connect hydro-meteorological communities, risk management institutions, & societies. Farmers in Liquiça district learning basic rainfall observation at the Climate Field School for Farmers.

15 BMG IPB Universities Agriculture Office at District Level Marine and Fishery Forestry Health Tourism Aviation - Maritime Directorate of Plant Protection Dept. of Agriculture Related institutions BMG Translation of Climate Outlook Scientific Language Operational Language (Below Normal) = (Lack of water) Provision of Climate Outlook In meteorological language Conversion of Operational Language into e.g. Crop Management Strategies Dissemination of Information to Farmers and evaluation of Farmers Response Change Crop Pattern ! Change Planting Time ! Change Crop Variety !

16 Institutional mechanism: Indonesia Directorate of Plant Protection IPB Provision of climate outlook BMG Translation of climate outlook into impact outlook Indramayu Agriculture Office Conversion of impact outlook into crop management strategies Dissemination of information to farmers and evaluation of farmers response

17 SUB BAGIAN TATA USAHA Drs. Agung Wradsongko, MP SUBDIT ANALISIS & MITIGASI DAMPAK IKLIM Ir. Jatmiko SUBDIT PENGELOLAAN PHT Ir. Sarsito WGS, MM SEKSI KELEMBAGAAN Ir. B. Indriastuti K SEKSI PEMASYARAKATA N Ir. Dyah Mutiawari SUBDIT PENGENDALIA N OPT Ir. Hari Utomo SEKSI OPT SEREALIA Drs. Ruswandi, MM SEKSI OPT KACANG-2AN DAN UMBI-2AN Ir. Ety Purwanti KELOMPOK JABATAN FUNGSIONAL BALAI PENGUJI MUTU PRODUK TANAMAN Ir. Yayah Roliyah, M Si SEKSI ANALISI IKLIM Ir. Irwan Kamal SEKSI MITIGASI DAMPAK IKLIM Ir. Endang Titi P. MM DIREKTUR PERLINDUNGAN TANAMAN Ir. Ati Wasiati SEKSI PELAYANAN TEKNIK Drs. Oscar Rulli SEKSI PENGELOLAAN SAMPLE Dra. Tantri Indrianti SUB BAGAIN TATA USAHA Suparjo SUB DIT PENGELOLAHA N DATA OPT Ir. Fatra Widjaya, M Si SEKSI INFORMASI & DOKUMENTASI Ir. Yarmiati Munaf SEKSI MONITORING Drs. Tigor Sagala *Subdivision on Climate Analysis and Mitigation Institutional innovation at Indonesian Ministry of Agriculture

18 Institutional mechanism: Philippines

19 8 Standard rain gauge Tipping bucket rain gauge Automatic Weather Station raingauge A pool of meteorologists has been formed & trained to provide tailored climate information for risk management in program countries. Through their interactions with institutions & communities under the Program, they understand that meteorologists should not just produce information but have to relate the information to the user context.

20 BMG Kel-1 : bag sel Haurgelis/ Gabuswetan/ Bangodua Kel-2 : bag.utara Indramayu Kel-3 : bag.utara Anjatan/Sukra Kel-4 : Krangkeng /Karangampel Juntinyuat/ Sliyeg/Kertasemaya/ Jatibarang/Widasari/Sindang/ Lohbener/ bag.Utara Bangodua Kel-5 : Kandanghaur/Bongas/bag.utara Gabuswetan/bag.timur Anjatan/Lohsarang Kel-6 : Cikedung /bag.sel.Gabuswetan /bag.utara Haurgelis/ Lelea Climate Forecasts Updated every month: day 21 25 Forecast delivery: day 26 30 Collection of daily data From day 20 (M-1) day 20

21 Dumangas Climate Field School A farmer shows his revised cropping calendar Institutional and community-level dissemination channels in demonstration sites have been strengthened. Community capacity to use climate information have been built primarily through Climate Field Schools, climate forum, & community-level workshops

22 Indramayu Climate Field School Women farmers participating in the Climate Field School work with extension workers in understanding rainfall graphs Farmers in Losarang subdistrict Indramayu showing rainfall graphs Farmers in Losarang subdistrict Indramayu showing rainfall graphs

23 FARMERS Farmer Groups P1-1 P1-2 -2 -2 FARMERS Farmer Groups P1-1 -1 P1-2 -2 -2P1-2 -2 -2P1-2 -2 -2 Stage 1: training of agricultural extension specialists (district level) Stage 2: training of agricultural extension workers (sub-district) Stage 3: training of heads of farmers groups Stage 4: dialogue with farmers Climate field school: implementation process

24 Instrument areaStation building Forecast applications for disaster mitigation is now internalized and owned by local governments involved in the program

25 Municipal legislation assures local government support to the operations & maintenance of Dumangas Agro-Met Station

26

27 Raingauges in Indramayu Regency

28 Implementation experience: Indramayu, West Java, Indonesia, Dry season 2006-2007

29 WMO El Niño advisory, 2006

30 Preparing program for supporting the action plans and socialization 20072006 Translation

31 Communication Flow BMG June/July August Sept/Oct October 1st2nd January February Mar/Apr April

32 Dumangas community-based flood early warning system

33 The CFA program has been instrumental in demonstrating that use of weather & climate information can save lives and produce tangible economic benefits

34 El Nino 2002-2003 As reported by the Iloilo Provincial Agriculturist, due to early dissemination of the El Niño forecast, farmers in the province were able to mitigate its adverse impacts by switching to alternative crops (e.g. rice to watermelon) El Niño damage - 64.00 M Production of other crops - 732.02 M Difference Php 688.02 M Key coping strategy: crop substitution

35 Climate Forecast Application in Bangladesh

36 Objectives Forecast technology tested and transferred Project Objective 1: Flood Forecast technology tested and transferred, and capacities developed to operationalise: A. 1-10 days forecasts B. 20-25 days forecasts C. 3-6 months forecasts Project Objective 2: Application of flood information through pilot projects at selected sites, showing measurable improvements. on experimental Project Objective 3: Flash flood forecast technology developed and tested on experimental basis for North East Bangladesh

37 Implementation Plan 2006200720082009 Pilot Testing the model, validation & capacity building Technology Transferred to FFWC, physical supports, capacity building Refinement, validation, advisory support & bridging Pilot Testing the model, validation & capacity building 2000-2005 Model Development and Experimental Forecasts Supported by USAID OFDA, ADPC Supported by USAID through CARE Bangladesh

38 Institutional Collaboration For Sustainable End-to-end Flood Forecasts System

39 CFAB Model Area

40 Discharge Forecast Schemes ECMWF Operational ensemble forecast NOAA and NASA (i.e.CMORPH and GPCP) satellite precipitation & GTS rain gauge data Hydrologic model parameters Discharge data Downscaling of forecasts Statistical correction Hydrological Model Lumped Distributed Multi-Model Discharge Forecasting Accounting for uncertainties Final error correction Generation of discharge forecast PDF Critical level probability forecast (I). Initial Data Input (II). Statistical Rendering (III). Hydrological Modeling (IV). Generation of Probabilistic Q (V). Forecast Product

41 Brahmaputra Discharge Forecasts 2008 1-10 day flood forecasts using ECMWF precipitation forecasts

42 Brahmaputra Discharge Forecasts 2007 1-10 day flood forecasts using ECMWF precipitation forecasts

43 2007 Brahmaputra Ensemble Forecasts and Danger Level Probabilities 7-10 day Ensemble Forecasts7-10 day Danger Levels 7 day 8 day 9 day10 day 7 day8 day 9 day10 day

44 Plumes and probability pies for the first Brahmaputra flood July 28-August 6, 2007 High probabilities of exceedance of the danger level by the Brahmaputra at the India-Bangladesh border

45 Plumes and probability pies for the second Brahmaputra flood September 8-16, 2007 For the second flooding, short-term forecasting, successful in providing high probabilities of exceedance of the danger level by the Brahmaputra

46 1-10 Days Forecasts at Bahadurabad 2009

47 1-10 Days Forecasts in the FFWC Website http://www.ffwc.gov.bd/

48 Forecast updates from 72 hrs to 10 days Traditional 3 days forecasts Forecast extended to 10 days

49 20-25 days and Seasonal Forecasts 20-25 days and Seasonal Forecast still in experiment. Not shared to public

50 Pilot Areas

51 Target groupsDecisionsForecast lead time requirement FarmersEarly harvesting of B.Aman, delayed planting of T.Aman10 days Crop systems selection, area of T. Aman and subsequent crops Seasonal Selling cattle, goats and poultry (extreme)Seasonal HouseholdStorage of dry food, safe drinking water, food grains, fire wood 10 days Collecting vegetables, banana1 week With draw money from micro-financing institutions1 week FishermanProtecting fishing nets1 week Harvesting fresh water fish from small ponds10 days DMCsPlanning evacuation routs and boats20 – 25 days Arrangements for women and children20 – 25 days Distribution of water purification tablets1 week Char householdsStorage of dry food, drinking water, deciding on temporary accommodation 1 week Flood risk management at community level decisions and forecast lead time requirement (Eg. Rajpur Union, Lalmunirhat district)

52 USER MATRIX on Disasters, Impacts and Management Plan for Crop, Livestock and Fisheries sector DisastersCropStagesSeason/ month ImpactsTime of flood forecast Alternative management plans Early floodT.AmanSeedling and Vegetativ e stage Kharif II Jun – Jul Damage seedlings Damage early planted T.Aman Delay planting Soil erosion Early June Delayed seedling raising, Gapfilling, skipping early fertilizer application T.AusHarvestin g Kharif I Jun – Jul Damage to the matured crop Early June Advance harvest JuteNear maturity June-JulyYield loss Poor quality May endEarly harvest S.Vegetab les Harvestin g June-JulyDamage yield loss Poor quality Mar - Apr Pot culture (homestead) Use resistant variety High floodT. AmanTilleringKharif - II July-Aug Total crop damageEarly June Late varieties Direct seeding Late planting Late floodT. AmanBootingKharif II Aug-Sep Yield loss and crop damage Early July Use of late varieties Direct seeding Early winter vegetables Mustard or pulses Flood (early, high and late) Cattle-Jun-SepCrisis of food and shelter. Diseases like cholera, worm infestation Early June Food storage, flood shelter, vaccination de-warming FloodNursery table fish Brood fish -June to Aug Inundation of fish farms Damage to the pond embankments Infestation of diseases Loss of standing crops Apr - May Pre-flood harvesting, Net fencing/bana, Fingerlings stocked in flood free pond, High stock density

53 Risk Communication of flood forecasts 2007- 2008

54 54 Sending SMS to Mobile Risk Communication for Flood Forecasts 2007-2008 Mobile phone Flag hoisting

55 Institutional and community responses on 2007 flood forecast: ADPC Field Team Flood forecast issued for two boundary locations Incorporated into customized local model 21 Jul 22 Jul 23 Jul Communicati on to project partners 24 Jul Communicatio n to stakeholders and local DMC members 25 Jul Communicati on to Disaster Emergency Group 26 Jul Discussion of options with local communities, CBOs, local working group members, networks 30 Jul 2 Aug Information to relief agencies about the extent of flooding Local institutions prepared response and relief plans Community in low lands reserved their food, drinking water, fodder requirements Local Disaster Management Committee and Volunteers prepared for rescue Aid agencies arranged logistics and begin dialogue with district administratio n Low lying areas are flooded on 29 th July Relief distribution started in affected locations Flood water exceeded danger level on 28 th July

56 Institutional and community responses on 2008 flood forecast- Report from ADPC field Team Flood forecast issued for two boundary locations Incorporated into customized local model 27 Aug 28 Aug29 Aug Communicati on to project partners 30 Aug Communicatio n to stakeholders and local DMC members Communicatio n to Disaster Emergency Group, DAE, etc 31 Aug04 Sep10 Sep The flood water likely increase Low lying areas are flooded Flood level could further recede and come down below danger level likely Flood water exceeded damaging level on 1 Sep Field team visit and observe the local situation

57 Community responses to flood forecasts

58

59 Economic Beneifits In 2008 Flood, Economic Benefits on average per household at pilot areas –Livestock's = TK. 33,000 per household –HH assets = TK. 18,500 per household –Agriculture = TK 12,500 per household –Fisheries = TK. 8,800 per households Experiment showed that every USD 1 invested, a return of USD 40.85 in benefits over a ten-year period may be realized (WB).

60 Improvement Due to Long Lead Forecasts System FFWC able to increase the lead time from 72 hrs to 10 days This model performs consistently well and correctly predicted 2007 and 2008 floods The flood forecasts provides onset of flood, duration and dates of receding of floods 1-10 days long lead forecasts provides enough lead time to interpret, translate forecast information to users through established communication channels The pilot testing of this long lead forecast information at high risk location revels tangible benefits to the at risk communities

61 Key Lessons Learned: 2007- 2008 Flood 10-days forecast system availability is crucial for live and livelihoods preparedness and local agency response. Response to forecasts in low lying areas related to saving lives and small household assets (dry food, drinking water, fire wood, animal fodder, barrowing credit from micro-financing institutions) Response to flood forecasts in high lands are mostly related to preparedness activities like reserving seedlings for double planting, protecting fisheries, early harvesting, abandoning early planting, protecting livestock and preserving fodder Local institutions during 2007-08 in pilot unions are well informed and prepared for floods in advance

62 The probabilistic nature of 1-10 days forecasts need to be communicated to the users at all level by innovative risk communication tools Capacity to interpret, translate and communicate probabilistic forecast information with impact outlooks with response options at various levels are crucial Long Lead forecasts are one of the best tools to enhance our adaptation to climate change associated risks at present and in future Agency level preparedness SoPs based on probabilistic forecast needs to be developed for livelihoods risk reduction Key Lessons Learned: 2007- 2008 Flood

63 Flash Flood Forecasting Provided experimental 3 days rainfall forecasting for the NE region of Bangladesh in2008 and 2009. The model is integrated with a horizontal resolution of 9 KM X 9KM. The forecasted information showed good result since 2008 Meso-scale rainfall forecast models effectively linked to the existing discharge forecast capability of the FFWC

64 THANK YOU


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