Climate forecasts become meaningful only when they are translated into actionable decisions through user engagement, impact-based forecasting, and institutional frameworks that connect scientific predictions to sector-specific responses in agriculture, disaster management, and energy sectors.
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26th Session of the ASEAN Climate Outlook Forum | May 22, 2026Ajouté :
All right. Thank you so much for sharing the uh results with us. Results of the survey. So it's good to see that the reach of the action crosses our borders. Right. So we having the uh slight difficulties on promoting our keynote speaker as a panelist. So perhaps M can >> can accept. All right. All right. She already accepted the request. So I think we can start the program.
All right. Right. Okay. So, uh, good morning everyone. It is once again my pleasure to welcome you all to the 26th session of the Ashan client forum. I'm Jeremiah from the USDA and I will serve as your master ceremony for today. So we are being streamed live on the official Facebook and YouTube pages of the Pagasa. So if you're watching this through any of these channels, feel free to share them with your friends, colleagues and family so that they can also watch this program.
>> All right. So we have now come to the last day of our week program and I invite uh everyone to please join us for the opening ceremonies.
See my Power might You are God. Why you love A whisper in the breeze it calls our name.
Across the seas we are the same.
Through tides that rise, through storms that weigh, we sail as one beneath the sun.
One vision, one ocean. Together in motion we rise. We shine. We reach for the sky.
One heart, one dream through the waters we gleam. As young we are one. Till the end of time.
The stars above they light our way.
From golden dawn to dusky grace.
We weave the thread of hope today.
With every shore we dream for more.
One vision, one ocean. Together in motion.
We rise, we shine, we reach for the sky.
One heart, one dream. Under the waters we gleam as young we are one to the end of time together we rise we shine we reach for the sky.
Heat.
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All right, thank you very much. You may now all settle down. And to officially start our program, let's hear a short welcome message from our administrator and the permanent uh representative of the Philippines with WMO, Dr. Nataniel P. Servando.
>> Good morning to uh good morning everyone. Distinguished guests, partners and colleagues. It is my uh pleasure to welcome you to the final day of the 26th session of the can climate outlook forum. I am uh proud to uh to to say that this event is part of uh the series of uh activities that uh the Philippines is hosting uh being chair of the Philippines being chair of AAN uh this year. Allow me to acknowledge our distinguished guests and partners joining us today. uh foremost uh the honorable secretary uh Maria Antonia Loaga, special envoy for disaster risk reduction and management Philippines.
M Thank you, Mom, for joining us uh today despite of your busy schedule. Mr. Ben Churchill, director of the regional office of uh for Asia and the Southwest Pacific of the World Meteorological Organization or WMO.
Mr. Cayan Hick Singh from the ASAN Specialized Meteorological Center, Mr. Peter Khalil Fer from from Rimes, Miss Krishna Potra Tanage uh from the ASEAN Coordinating Center for Humanitarian Assistance on Disaster Management and our partners from the Food and Agriculture Organization of the United Nations, from the International Rice Resist Institutes Institute and other regional international organizations.
Most importantly, I wish to express our deep gratitude to our users, our colleagues from various government agencies, the disaster risk reduction and management community, the agriculture and water sectors, the health sector, the energy sector, and other stakeholders.
Your presence here today is a clear reminder that climate information only becomes meaningful when it is uses when it is used. So uh we have uh more than 100 participants online joining online in fact about 133 uh one of the biggest u gatherings online over the past days.
The ASEAN COF 26 has demonstrated the strength of regional collaboration through technical discussions and shared expertise. We have developed a consensus outlook for the coming season particularly um uh El Nino is expected to emerge and uh projected to be uh very strong uh based from uh forecast from different uh uh forecast climate uh uh centers.
And uh of course uh um today we turn our focus to an equally important aspect ensuring that this information is translated into action.
The theme of this year's forum, navigating our future together, translating climate in forecast into action, highlights the need to bridge the gap between climate science and decision making. In Southeast Asia, climate risks remain significant.
Floods, droughts, tropical cyclones, and heat extremes continue to affect community and economies across the region.
In this context, the role of climate services is crucial.
However, providing forecast alone is not sufficient. We must ensure that climate information is accessible, understandable and relevant to the needs of users.
This requires stronger engagement with the stakeholders across sectors agriculture, disaster risk reduction, water management, health and energy.
Today's user engagement webinar provides an opportunity to strengthen this engagement through the presentations and discussions ahead. We will see how climate information is being applied in p practice. We will learn from experiences, identifi identify challenges and explore ways to improve the delivery and use of this use of this climate information and services.
Equally important is uh the dialogue between providers and users of climate information.
This dialogue allows us to better understand user needs and to refine our products and services accordingly.
It ensures that our work has practical value and contributes to informed decision making.
At AANA COP, we continue to strengthen our efforts in this area, enhancing climate services, advancing early warning systems, and promoting impactbased forecasting.
At the same time, we recognize that effective climate action requires strong partnerships.
Regional platforms such as the CEN COP play a a key role in fostering collaboration and ensuring that climate information supports resilience and sustainable development.
Before I end this message, I would like to express my gratitude to my colleagues at DT Pagasa for hosting and organizing this 26th session of the CAN COP.
Despite the challenges of convening virtually, USD PAGAS has ensured that this forum remains to provide a strong and effective platform for regional cooperation.
As uh we conclude this forum, let us rem affirm our shared commitment to collaboration, innovation and service.
Let us continue working together to ensure that climate science informs decisions and supports our communities across the can region. Thank you for your continued participation and support. I wish everyone a meaningful and productive session. Mabhai and good morning to everyone.
>> Thank you very much docn for that uh warm welcome message. Let's hear another welcome message from the director of the regional office for Asia in the southwest Pacific of the World Meteorological Organization, Mr. Ben Churchill.
>> Well, thank you and good morning, your excellencies, Madame Maria Antonia Yulo Loaga, the special envoy of the president of the Philippines for disaster risk reduction and management.
And of course, as we just heard from uh Dr. Nathaniel T. Savando, the permanent representative of the Philippines with the World Meteorological Organization, WMO, and administrator of the Philippine Atmospheric Geophysical and Astronomical Services Administration, Pagasa, colleagues from the Association of Southeast Asian Nations, Azan, member states, and the National Meteorological and Hydraological Services, distinguished partners. Um, I will make a special call out to our users as well, very well represented. And ladies and gentlemen, um on behalf of Professor Celestee Salo, the secretary general of the WO and in the entire WO secretariat, which includes uh the regional office for Asia Pacific, of which I'm director, I'm delighted to welcome you all to the 26th session of the Azan climate outlook forum and in particular to the user engagement webinar on this its last day.
First, I would like to express my sincere appreciation uh to uh Dr. Sabando um uh and also to to do the OST Pagasa for kindly hosting this forum online notwithstanding the challenging circumstances confronting all of us today. As always, I am extremely grateful to the Azan cough working group coordinated by the Azan Specialized Meteorological Center, ASMC at the Center for Climate Research Singapore, uh which coincident coincidentally also hosts our RAP office um comprising experts from our NMHses in the region and key partners including the UK Met Office under the weather and climate information services or wiser Asia-Pacific program and also the regional multi-hazard early warning system for Africa and Asia rhymes.
for your invaluable support. My thanks go out also to the multiple global global producing centers for seasonal prediction which provide essential global and standardized forecast products and verification.
In March this year, WO launched its flagship report, the state of the global climate in 2025.
This report confirms that 2015 to 2025 are the hottest 11 years on record and that 2025 was the second or third hottest year on record at about 1.43° C above the 1850 to 1900 average. In Southeast Asia, cyclone Senya, the first known system to reach tropical cyclone intensity in the Straits of Malaca, resulted in severe flooding in late November. Typhoons also cause record rainfall and flooding in Vietnam uh as well as Thailand later in June and July.
We will launch the state of the climate in Asia and the Southwest Pacific reports which will provide more granular information on key climate indicators in the region. In the meantime, we are at the cusp of the return of an El Nino with some predicting more extreme weather events and a rise in global temperatures to record heights. The signs are clear. Last month was the joint third warmest April on record globally. Wo's new global seasonal climate update signals a clear shift in the equatorial Pacific with sea surface temperatures rising rapidly. I heard that a hot topic over the previous days was the relative oceanic nino index or Rooney um which seems to offer a clearer, more reliable way to track El Nino and Leninoia. Several global centers and now increasingly Azan member states are adopting this new index alongside other traditional indices.
While a fuller assessment of this impending El Nino will be available very soon, it is imperative that we work together to prepare ourselves in our region. We can expect significantly drier conditions and its related challenges to hit us harder than usual with much reduced rainfall. It is therefore timely that the focus of a Azovv 26 is to support the NHS's to deliver actionable forecasts and support climate informed decision-making. We're already seeing a surge in interest from national and international humanitarian agencies for this information. And it's good. It's in fact it's very good that some of us of them are with us today.
Climate information creates the most value when it informs decisions at the right time and at the right scale. So we must ensure that climate outlooks are not only produced but are understood, accessible and importantly actionable by all. To truly protect lives and livelihoods, we must include representatives of social and economic sectors in the COFF process. Azan Coff is a prime example of effective regional collaboration that underpins national decision-making and results in tangible benefits. It is fully aligned with the principal objectives of the UN early warnings for all initiative translating science into actionable information for governments, communities and vulnerable sectors. In particular, it brings all relevant stakeholders together to forge consensus outlooks that will help take early and anticipatory action across all sectors. Our collaboration here this week also dovetales with WMO's active support for climate outlook and climate forums as well as the work of the WO regional associations in Asia and the Southwest Pacific and of the Southeast Asia regional climate center network which I'm very pleased to say is nearing designation.
Through these platforms, our members can achieve a base level of preparedness at the regional level which continually improves their climate services.
In closing, as we enter the final and public segment of this forum, you will shortly be briefed on the consensus climate outlook for June to August 2026.
Then we will have a few presentations from our partners and fellow experts, including on pertinent topics such as impactbased forecasting. I have no doubt whatsoever that today's session will be instructive in preparing ourselves for the months ahead. So with that, I wish you all a highly productive and collaborative final day of Azenov 26.
Thank you so much for your engagement and I look forward to seeing many of you hopefully in person at future Azenovs and other regional events. Thank you very much for your attention and your engagement today.
>> Thank you very much uh Mr. Churchill. As always uh we are very much grateful for your support especially uh in Pagasa all these years. Let's hear another message from Mr. Kai Wanjen from the Assean Specialized Meteorological Center.
>> Thank you for the opportunity to deliver this welcome message. Her excellency Mario Antonia, Special Envoy for Disaster Risk Reduction. Dr. Natalia Savanto, administrator of the Department of Science and Technology Pagasa. Mr. Ben Churchill, director of the WMO regional office for Asia and Southwest Pacific. Distinguished guests, ladies and gentlemen, a very good morning. On behalf of the ASEAN specialized methological center, it is my pleasure to welcome everyone to the last day of the 26 asan where we turn our focus to user engagement. A warm thank you to Pagasa for hosting this forum and for bringing us all together this week.
I would also like to take this opportunity to thank the trainers from Noah, the Bureau of Meteorology and the UK MAT office for their excellent pre-climate outlook forum training and to all the global producing centers and national meteorological and hydraological services for their contributions to the knowledge exchange and consensus outlook over the past few days. Today's webinar brings together a wonderful mix of voices from disaster risk management, agriculture, fisheries and beyond. This is precisely what our team navigating our future together translating climate forecast into actions calls for. The work of our meteorological community does not end with the production of a forecast or outlook. is only complete when that information reaches the people who need it most and when it is used to make better decisions on the ground. Whether it is a farmer planning for a season ahead or a disaster manager preparing for potential hazards, climate information has a vital role to play.
Your presence and perspectives today here today are what make that translation possible. With that, I wish everyone a fruitful and engaging session and I look forward to the rich discussions and insights that today will bring and to leaving with a stronger shared commitment to putting climate information into action. Thank you very much.
>> Right. Thank you so much uh sir for that warm message. And now to introduce to us our special guest who will deliver the keynote message. Let's first welcome Miss Telma Acinko from the USD Pagasa.
Thank you Jared.
Sir, >> good morning everyone.
Uh it is my pleasure to introduce our uh listing our uh keynote speaker for today, her excellency Maria Antonia Tony Yula Yulu Luis Saga is the former secretary of the department of environment and natural resources of the Philippines. She is the special envoy of the president for disaster risk reduction and management.
She likewise serves as a special consultant on disaster risk reduction and management strategist to the NDRMC and acts as the exclusive and official license of the NDRMC chairman to the private sector. As secretary she revitalized the Philippines resource development sector by posting strongly for responsible resilient sustainable investment to forestry, water and minerals. Her leadership was grounded in science and inclusive consultation, evidence informed policy innovation and strategic engagement with the private sector, academia and civil society.
Tony established the department's office for integrated environmental science, its national natural resource geospatial database and the Philippines first ocean environment task force linking ocean science with environmental protection and national security protect transform a transis disciplinary initiative to build local governments resilient through their hands-on environmental and natural resource management. ment. She led the Philippines delegation to the UN framework on convention on climate change, the UN office for disaster risk reduction and convention on biological diversity. She obtained a sit for the Philippines on the board of fund for responding to loss and damage of FRLD in COP 28 and hosted the Asia-Pacific Ministrial Conference on disaster risk reduction on in Manila in 2024. She spearheaded the Philippine successful selection as the host country for the Fldd board last year. Before joining government, Tony worked in finance and property development while serving on boards of academic institution and science focus foundation.
She she served as a technical adviser to the Philippine Disaster Resilience Foundation and became president of the National Resilience Council, a public private partnership advancing climate goals and disaster risk reduction from 2017 to 2022. So from 2007 to 2016 she was the executive director of Manila Observatory a 160-year-old scientific research institution specializing in its meric and earth sciences for sustainable development and community resil resilience. So let us all welcome Miss Tony Loy Saga as our keynote is speaker. Good morning everybody.
Thank you very much u Masinko for that lengthy intro in introduction.
Good morning to all. Good morning uh Dr. Nathaniel Cervando our administrator of Pagasa. Mr. Ben Churchill, director of the Southwest Pacific uh WMO office. Um sir Mr. Cayon Zen of ASMC and and the other uh distinguished guests and delegates, colleagues, partners. Ladies and gentlemen, I'm honored to join you today on behalf of National Defense Secretary of the Government of the Philippines, Gilberto Judora Jr. for the user engagement webinar of the 26th session of the ASEAN climate outlook forum or ASEAN COF.
Allow me to extend our sincere appreciation to Pagasa, the ASEAN Specialized Meteorological Center or ASMC, the WMO, the regional integrated multi-hazard early warning system or rhymes, the United Kingdom's Met Office or UKMO, and our ASEAN partners for organizing this very important forum and for continuously advancing regional cooperation on climate services and disaster resilience.
ASEAN COF remains a vital platform that strengthens our collective understanding of climate risks and enhances cooperation among ASEAN member states.
At a time when climate variability and extreme weather events are becoming more intense and frequent and as risks in turn grow more complex, forums such as this are increasingly important in ensuring that scientific knowledge is translated into timely and meaningful action. In the Philippines, climate and weather information serve as critical foundations of our disaster risk reduction and management system. We recognize the effective disaster prevention, preparedness and risk reduction. They begin with science informed risk assessment, reliable forecasting and timely dissemination of warnings. Seasonal climate outlooks provide valuable guidance which enable national agencies, local government units, sectors and communities to craft strategies and adopt tools and technologies for resilience.
Actionable weather information enables coordination and allows each to anticipate and prepare for potential impacts on lives, livelihoods, infrastructure, agriculture, water resources, energy, and public health.
The Philippine DRRM framework promotes a transdisciplinary, whole of government and whole of society approach. This means that prevention, preparedness, and resilience are shared responsibilities between scientific institutions, government agencies, local governments, the private sector, humanitarian organizations, civil society, and communities themselves.
Impactbased forecasting must therefore be timely, user and needsdriven and at the level of granularity necessary to be truly valuable to decision support systems of multiple stakeholders.
This specificity is especially critical to transformative interventions that will build adaptive capacity in vulnerable populations.
The theme of ASEAN COVF 26, translating climate forecasts into action, strongly aligns with the Philippines continuing efforts to strengthen strategic and proactive disaster risk management.
Forecast-based decisionmaking enables authorities to undertake and implement prevention and anticipatory actions such as investing in resilient infrastructure, issue early warnings. Design focused and targeted response and trigger safety and protection measures such as preemptive evacuation that can lead to early recovery.
The Philippines has institutionalized the predesaster risk assessment or PIDRA process since 2014 as a key anticipatory action mechanism. The PIDRA provides a comprehensive framework for assessing hazards, exposure, vulnerabilities, and potential impacts to support timely preparedness and response actions.
Recently, the PEDRA was revised in terms of its guidelines and it now places greater emphasis on looking at worst case scenario-based risk assessment across all DRRM levels.
In addition, the country continues to strengthen its early warning systems and impactbased forecasting capacities through the emergency alert and warning message system implemented by Republic Act number 10639 or the free mobile disaster alerts act.
Hazard specific and area focused alerts are disseminated directly to the public.
Various dissemination platforms including advisories, digital communication channels and monitoring dashboards further help ensure that warnings are understandable, actionable and people centered.
Having done this, however, we must all still continuously strive to make the last mile the first mile when addressing the needs of the most vulnerable.
The Philippines along with our Assean neighbors continues to face increasing climate variability and the possibility of compound hazards and cascading risks associated with tropical cyclones, flooding, drought, extreme rainfall, and rising temperatures.
But even as our climate is changing, we must note that our societies are changing as well.
Our evolving needs and challenges therefore underscore the critical importance of stronger climate services, sustained investments in resilience building and closer regional cooperation as climate and disaster risks do not recognize national borders. Asan solidarity and cooperation remain indispensable to advancing regional resilience.
collaboration on climate outlook development, information sharing, capacity building and scienceinformed disaster reduction significantly enhances our collective preparedness across the region.
The Philippines highly values our continued partnership with ASEAN member states and international organizations in advancing climate invol informed people centered DRRM strategies.
As we move forward, the Philippines reaffirms its commitment to strengthen climate informed disaster risk reduction, anticipatory action and regional cooperation.
We encourage continued collaboration among meteorological agencies, DRRM institutions, development partners, researchers, and users to ensure that climate information consistently leads to timely, coordinated, and life-saving action.
We are confident that the ASEAN COF 26 will further strengthen regional resilience and contribute to a safer, more adaptive and disaster resilient ASEAN community.
Thank you very much. On behalf of Secretary Gilberto Judora Jr., we wish everyone a productive ASEAN cough 26.
>> All right. Thank you so much, Mom Tony, for uh gracing us your presence and delivering the keynote message. For the solidarity message, let's hear from our partner at the regional integrated multi-hazard early warning system or rhymes, Mr. Peter Khalil Ferrer.
>> Distinguished guest and colleagues, um her excellency Maria Antonia Yulo Loyaga, special envoy for the disaster risk reduction and management. Um Dr. Nathaniel Cervando, administrator of Pagasa and permanent representative of the Philippines with um WMO. Uh Mr. Ben Churchill, director of the regional office for Asia in the Southwest Pacific of the WMO, colleagues from the Asan Specialized Meteorological Center and the AHA center, representatives from the SEAN NHS, development partners, ladies and gentlemen, a pleasant morning to everyone. Um it is my honor to join you today and on behalf of our director general, Mr. Arjuna Mal Sububaya. I would like to um express our sincere appreciation to dod Pagasa for hosting the 26th session of the ASAN climate outlook forum and to all ASAN NHSS regional climate centers partners and participants joining us today.
As our region continues to face um increasing climate variability and extreme weather events, asenov remains an important platform for collaboration, learning and regional solidarity. Beyond producing seasonal outlooks, um, Ashen COV demonstrates the value of working together as a community, sharing expertise, experiences, and scientific knowledge to support better climate informed decisions across Southeast Asia. Over the past days, um, we have seen meaningful discussions and exchanges among NMHs, regional climate centers, and partners, uh, reflecting the continued commitment of the SAN climate community to strengthen regional cooperation and climate services.
Uh these discussions are especially important as we continue exploring ways to make um climate information more actionable, accessible, and responsive to the needs of our communities and decision makers.
This year's theme, navigating our future together, translating climate forecast into action, is both timely and meaningful. As climate risks become more complex and uncertain, there is an increasing need not only to improve our forecasts, but also to ensure that climate information becomes more understandable, actionable, and useful for governments, communities, and climate sensitive sectors.
Ryan is honored to continue supporting asenov and the broader efforts of Asan NHSS in strengthening climate services, early warning systems, and regional cooperation. We also highly value the strong partnership among Pagasa, ASMC, WMO, uh the CRCC network, UK Met Office and all participating institutions that continue to make this forum possible. We also recognize that the strength of Asenov lies not only in the science but in the relationship and trust built among institutions and individuals over the years. These partnerships are essential as we collectively work toward more people centered and impactbased climate services for the region. Rhymes stands in solidarity with all Asayan member states and partners in advancing inclusive, accessible and actionoriented climate information services for the benefit of our communities. Thank you very much and I wish everyone a successful and productive continuation and closing of this 26 session of the Asaian.
Thank you so much Peter for the continued support of rhymes in the conduct of the ashen cough. Another solidarity message will be delivered by Krishna Chanaha from the AEAN coordinating center for humanitarian assistance on disaster management or the AHA center.
>> Thank you very much Mr. Jeremiah. Good morning excellencies, distinguished ladies and gentlemen, partners and colleagues. On behalf of the Aendra, I would like to extend uh my warmest uh congratulation to the DOS Tagasa, SMC, WMO, Rhymes, Wiser, Asia-Pacific and all other partners for successfully convening the 26th Assean climate outlook forum or assean 26.
The center highly values aan as an important regional platform that strengthens collaborations among climate meteorological and disasters management communities across the Southeast Asia helping translate climate information into actionable disaster management.
Our region remains one on of the most vulnerable regions in the world to hydromeological hazards. According to the ASEAN disasters information network or Adinet, more than 90% of disasters in ASEAN are associated with hydrometeorological hazards including floods, tropical cyclones, storms, droughts and rain induced landslides.
These disasters continue to affect millions of people every year, disrupting livelihoods, infrastructure, food security, and economic development across the region.
Last year, tropical cyclone senar reminded us that even low probability events can result in severe and cascading uh regional impacts. Together with the norththeast monsoon, Senar affected several ASEAN member states including Indonesia, Malaysia and Thailand, demonstrating how interconnected and exposed our region is to increasingly complex climate and weather related hazards.
These transboundary hazards remind us that while some hazards may occur infrequently, their consequences can be devastating if the success management measures are in in insufficient.
This year with the El Nino affected uh expected to develop amidst the uh warmer climate, we are reminded to remain vigilant, strengthen our collaboration and reinforce our collective solidarity to en to ensure a resilient ASEAN.
This reinforces the importance of Asan C. Climate outlooks, seasonal forecasts and impactbased forecasting are not merely technical products but essential tools to support early action and risk informed decision making enabling us to respond to the disasters faster.
Mobilize greater resources and establish stronger coordination. Align with our commitment of Asia of the one Asian one response. This year theme navigating our future together translating climate forecasts into action strongly resonates with Assean commitment to strengthening resilience through collaboration and science-based decision making. At the R center, we continue to work closely with ASEAN member states and partners and stand ready to support and to strengthen disasters monitoring, regional information sharing, early monitoring and preparedness efforts. We believe that stronger collaboration between the NMHS and the AMOS, regional and international partners, including academia and humanitarian organizations will further strengthen our collective capacity to address emerging climate risk and protect vulnerable communities across Assean. Once again we commend DOS Pagasa SMC WMO Rhymes Wiser Asia Pacific and all other partners and wish you this forum to be a very success. Thank you.
>> All right. Thank you very much sir for that message. On behalf of uh the USD Pagasa and the USD and the whole team that put together this ashen puff 26 allow me to extend our deepest thanks to all of you. And with that, we now move forward to the next part of our program.
But before that, uh let's take a quick uh photoop session before we have our short health break to commemorate the last day of our session. So um since you are using the webinar account of WO, we won't be able to allow our participants to open their cameras. So I'd like to ask instead our panelists to please uh open your cameras and uh wear your best smiles. We only have one panel, so that's that's easy enough. So, I'll be taking the screenshot now.
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All right. Thank you so much.
So, we will now be having our very quick health break, let's say 2 minutes, and be back here and resume our program. Um I'll be starting the timer and then we will now proceed with the presentations after that.
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All right, let's continue our program. I hope everybody is back inside the meeting room. So we have a lot of presentations stored for our participants for us to understand and of course appreciate the importance of a collaborative work for the Ashen region and um what has been done to improve our capacities in dealing with uh this changing climate. So just a few reminders before we begin. Each presenter will be given 15 minutes each to present. So, please kindly take note of the time and um uh limit your discussion within the allotted time. So, don't worry. I'll be flashing the timer here beside my head and you'll hear a beep sound and once the timer ends, you'll have two minutes to wrap wrap up your presentation. Now without further ado, let's begin with our first presenter, Miss Analisa Solis of DOS Pagasa and representative of the Ashen COVF working group who will now be presenting to us the consensus outlook for the June July August 2026 season.
>> Yeah, thank you. Good morning. Uh can you hear me?
>> Can you hear me?
>> Yes, ma'am. We can hear you. Okay. So, good morning everyone and distinguished guests and users of weather inclined services across Southeast Asia. So we are now in our fourth and final day of the Asia COV 26 and we would like to extend our sincere appreciation to all the NMHs in Southeast Asia for your active participation throughout the 4day ASEAN COP 26 session and for your valuable contributions to the discussions, presentations and consensus process to come up with this consensus outlook for June July August 2020 season. So at this point in time allow me to read the draft version of the Asian COP 26 outlook bulletin for June, July, August for your review.
Okay. So it says in terms of conditions and outlook recent sea surface temperature anomalies over the equatorial Pacific Ocean during April May 2026 overall indicated and neutral conditions were present. However, persistent warming over most of the Nino regions together with atmospheric indicators such as decreased cloudiness over most parts of Southeast Asia and anomalous low-level westerly east of the Philippines support the development of El Ninoike conditions. Meanwhile, the Indian Ocean remains in neutral Indian Ocean dipole phase. International climate outlooks predict a moderate El Nino is likely to develop during June to August or June July August 2026. After June, July August, most models predict continued strengthening into a strong to very strong El Nino while the rest predict only moderate El Nino conditions to persist through the remainder of the year. If a very strong El Nino occurs, this does not necessarily indicate bigger impacts in Southeast Asia climate, but rather that typical impacts from El Nino events are more likely to occur. The IOD is also predicted to transition to positive IOD conditions through the latter part of 2026, although with less confidence than the predicted.
The onset of the 2026 Southwest monsoon season has been or is expected to be near average across much of the Aselan region except for Viet over Vietnam and Lao PBR where the later than average onset occurred. Overall, the strength of the southwest monsoon is predicted to be near or stronger than average over most parts of Southeast Asia. For June, July, August 2026, tropical cyclone frequency is predicted to be below to near average across the region.
For temp for temperature outlook above above normal temperatures are expected across most parts of Southeast Asia. The exception is over the southern maritime continent in parts of northern Vietnam and northern southern and coastal Myanmar where near to above normal temperatures are predicted for rainfall.
Below normal rainfall conditions are likely over much of the maritime continent including the southern Philippines, Brunai, Salam and Singapore. The exception is over Malaysia where below to near normal or near normal rainfall is predicted for much of the country and central and northern Philippines where a mix of near to above normal rainfall is predicted. A mix of below to average normal rainfall is predicted over mainland Southeast Asia. Below to near normal rainfall is predicted over central Thailand, parts of southern Thailand, central Cambodia, and southern Vietnam. Near normal rainfall is predicted over the northern half of Myanmar, southern Lao PDR and mountainous regions of northern Vietnam and southern Vietnam.
Above normal rainfall is predicted over coastal and southern Myanmar and parts of northern Lao PDR with near to above normal rainfall over parts of northern Thailand, Cambodia and Vietnam. So this is the consensus drop outlook for June, July, August uh 2026 and this initial drop is available for further refinement. uh for ASEAN NHS participants, members of the ASEAN co-working group, please kindly share your comments, corrections or suggestions by 27 May 2026 around 09 UTC to allow the ASEAN CO Secretariat to finalize the bulletin for official release and we are targeting that all or before 30th May this can be published to the official website maintained by ASMC Singapore as well as at the WMO website.
So once again, so thank you very much for your active involvement these past four days and see you at the next ASEA on top 27 in November. Thank you. Back to you Karen.
>> All right. Thank you so much Miss Anna for presenting presenting to us the consensus outlook for the next June July uh June July August 2026 season. For our next presentation, it will be delivered by the senior scientist from the International Rice Research Institute, Dr. Alice Labort. Her presentation is titled Climate Plus: Integrating Climate Forecast, Special Analytics and Agro Advisories. Go ahead, ma'am.
>> Should I share my screen?
>> Yes, ma'am. Go ahead.
>> One moment.
Are you able to see my screen?
>> Yes, ma'am.
>> Okay. Um, thank you very much for this invitation, distinguished guests and participants. I'm very pleased to share with you our work at the International Rice Research Institute uh in partnership with the OSD PAG ASA in translating forecasts into actionable advisories for rice farmers. This uh uh research is in uh under the CGR climate action science program and also in collaboration uh with the alliance of biodiversity and seat the department of agriculture regional field office 5 field rice and agricultural training institute. So first let me talk about um one moment because I cannot can you see the full screen >> you can see the entire presentation.
Okay. Um so first let me talk about the rice crop manager advisory service. So this is a web and mobile phonebased digital agricultural platform that consolidates farmer and field registration field red geo referencing advisories data management and reporting. So this is has been developed uh with in with support from the DA national rice program and has been operationalized. So this is already being implemented throughout the country through our um regional field offices and agricultural technicians. So here um agricultural technicians armed with the rice crop manager advisory service interviews farmers and gives them a one-page recommendations that provide information on a use of quality seeds uh no early spraying for example and nutrient management recommendations. So in terms of what uh grade of fertilizer to apply when and how much. So these pre-season recommendations are provided to farmers in the form of a onepage print out and then reinforced in season with SMS reminders. So as I mentioned this is already operational but there is no inseason adjustments. So of course like if there's strong rain or there is typhoon there should be adjustments in the way farmers are are provided with advisory. So this is what we are doing right now uh in collaboration with Pagasa.
Okay. To translate the weather um seasonal and 10-day forecast coming from Pagasa and inform this rice a uh rice crop manager advisory service to adjust the recommendations given to farmers. Uh so essentially um this uh gets the the forecast from Pagasa also including when there's a typhoon uh about to enter uh the country.
So this is how it works.
Uh let me just remove this part because I cannot see. Um and so RCM gets from Pagasa forecasta forecast through an API enabling timely weather adjusted recommendations. So um uh uh so whether informed aggro advices are autogenerated and sent to farmers as SMS. No. So so sending of SMS is supported by the DA agricultural training institute via the existing uh platform and farmer contract services.
So what climate plus does is it translates the weather information into crop stage specific and contextaware and actionable advisories that farmers can realist realistically implement to protect their investment and reduce your cost. Now, of course, you can provide more general advisories, but what climate plus does is it adjusts based on the crop growth stage because you will have a different advisory depending on the crop uh growth stage uh of the farmers. So for this particular implementation we have piloted this in learning sites in the 2024 wet season uh and reached 226 farmers in Kamarinur and in the 2025 wet season we provided advisories to 16,000 farmers in Isabella and uh Belel region and we also bundled this uh in cooperation with the Philippine Crop Insurance Corporation with insurance.
So um how does the climate plus uh framework look like? So we have a two-layer decision logic. So the first one based on Pagasa six month forecast and also field location whether the field of the farmer is flown to prod flood uh and his crop calendar and water regime. So whether it's irrigated or rainfed and whether he has available supplemental irrigation and based on the six-month forecast um the potential climate risk for that farmer is assessed and then uh whether informed aggro advisories is provided. The second stage or the second layer is looking at um the 10-day forecast. So based on the estimated critical uh rice growth stage uh the recommended fertilizer rates uh an SMS is sent to adjust the recommendation given to farmers. So let me illustrate by providing specific example. Um so let's say during the panical initiation stage of of the crop let's say from Pagasa we received a 10-day forecast that there is moderate rainfall for two consecutive days. So the agro advisory for that particular farmer is to delay fertilizer application. So the message that he would receive uh through SMS is hi farmer name based on the 10day weather forecast uh for your municipality there will be moderate rainfall from August 23 to 24 during panical emissation stage.
So you should delay fertilizer application and apply the recommended rate after flood water recedes.
So if there is another forecast of say let's say heavy rainfall during maturity or harvest stage of of uh the field of the farmer then he will receive this message uh to harvest early if possible and protect the grain. No. You can see the criticality of knowing when um or at which crop growth stage the field is because you will provide a different aggro advisory depending on the growth stage. So here the advisory is okay strong wind and heavy rain are expected from October 23 onwards and during maturity stage harvest early and protect grains from wetting.
So based on the implementation in the wet season in 2024 um these are the results. So 69% of the farmers we interviewed said that the weather informed advisories were easy to understand. 60% of the farmers indicated the weather informed advisories were accurate. 80% of farmers indicated the weather in informed advisories were helpful and 74% of farmers believed they reduced their losses due to the advisories no with the help of the advisories. So looking at um for example uh in the results 94% adjusted their fertilizer application due to the advisory on heavy rainfall and 94% adjusted their fertilizer application due to limited rainfall. No, so because those are also two important things and then 55% harvested early as a result of the recommendation. Um based on the survey uh looking at the yield comparison uh those who harvested early and followed the recommendation their yield was 2.1 tons per hectar. Of course this is uh a bit low but of course there was some situation there with regard to uh that affected the yield but those who did not harvest early uh rece uh harvested much lower no at 1.8 eight tons per hectare.
So we are uh so so we are only you looking at h for this particular implementation we only look at uh rainfall but we are improving the system in collaboration of course with bagasa uh talking them with them. So our aronomists are talking with them closely to see what other recommendations we can provide based on you know uh the weather forecast that are available and how can we further improve the recommendations for the layer one pre-season recommendation as well as the second layer which is the inseason recommendation. So we do have several uh discussions uh also looking at pest and diseases. Uh of course drought is a very important uh consideration particularly this year and that is going to be implemented uh within the year.
So these are also additional um uh references and advisories based on uh for example looking also at drought and salinity exposure uh in addition to to yield to to rainfall sorry so climate plus also integrates data from different levels so we also look at as I mentioned already six month seasonal forecast uh whether it's above near or below normal and where it is used in the two-layer framework. Uh the sonoptic station is also being used. We're also looking at the municipal level in terms of the 10-day forecast and also typhoon damage records and also looking now at the Barangai level in terms of the floodprone rice areas. These are also coming from satellitebased assessment uh also from the Philippine rice information system uh coming from Phil Rice.
And we're also looking at field level data uh coming from the RCM historical uh data.
So what we are doing right now is to further enhance climate plus uh improving the decision logic using API as shared by Pagasa forecast on temperature humidity and inclusion of probabilistic weather forecast in the Philippines to improve the agro advisory. So the upper brigade with upgraded solution will be replicated in India particularly Odishia to enable localized and datadriven agro advisories. Um we're also uh doing capacity enhancement uh stakeholder engagement uh to strengthen the institutional and human capacities and climate plus operation in the Philippines and also conduct multistakeholder engagement to co-develop pathways for scaling and sustainability.
Um recently we also held a human- centered design um workshop and this will be applied to refine content format, delivery, timing and localization of climate plus. Uh in addition to that work, we're also uh looking at early warning system for floods. So this is a work being led by the alliance of biodiversity in seat in seat to fine-tune and validate a low compute rise flood inundation model for the Philippines uh using prison data to support operations of regional field office uh in be region um including engagement and training of partners and the development of a strategy for model integration within their operational procedures.
Um rice crop manager has been developed uh in other countries. Um I mentioned already Odisha in India but also in Indonesia and in Kanto province in Vietnam. So technically this um climate plus integration with aggro advisories can also integration with a forecast can also be uh included in these other countries where RCM is already operational.
Uh with that I would like to end my presentation and once again thank our partners and also thank you for this opportunity to share our work uh together with the USD paga and our other partners uh in the Philippines. Thank you very much.
>> All right. Thank you so much Dr. Alice.
I'm I'm really amazed doc. No, it's it's very interesting to see and hear that our forecast products are being actually applied by our partner farmers and yielded actually very good results. And as always, we thank Erie for their um continued support and for sharing with us this uh very interesting and extremely useful innovations especially to our farmers and agricultural extension workers. So our next presentation would be the ENSO primer for Ashan agriculture sector to be presented by uh Dr. Peter Wolski from the University of Cape Town.
>> Uh good morning everyone.
>> Good morning sir.
>> Can you hear me? Yes, that's fine.
Can I can I share the screen?
>> Yes sir. Go ahead.
>> Sure.
I have to figure out how to do it. Ah, not this one. Stop. Stop. Stop. Stop again. Sure.
>> This one.
All right. Can you see my presentation?
>> Yes, sir. We can see your presentation.
>> Fantastic. I'll put in a slide in a um presentation mode and off we go. So, good morning everyone. Uh my name is Pvski. I come to you from uh climate system analysis group from University of Cape Town in South Africa and I wanted to present u a short talk about uh impacts of ENSA and Alinia on a climate and agriculture that uh is uh created as a was together with my colleague Kathine Antia uh in the framework of a short project uh organized by the FAO and uh specialized metrical center. Uh so the scope of this of this activity the scope of this project is uh regional uh rather than local and we focus here on drought and agriculture. Uh and we want to illustrate uh where and when uh elino impact impacts occur at the regional level based analysis of historical data. So we're not looking at forecasts, we're looking at at historical uh data and try to unpack uh to understand uh how intense and where the impacts are. So the the audience of this is really uh the people who are working in agriculture sector uh and perhaps methology. So I probably won't be uh telling uh many new things but we try to um u compile uh the state of knowledge and uh compile uh results of of of some dedicated data analysis uh to create that uh picture of what is happening in the region in response to uh Elinas.
So uh to start um I wanted to um to show you uh how do we in how do we our approach to index and so to understand when the u occurs and um basically it's all done using uh one of the many indices the standards u are n 3.4 four and ocean Nino index and perhaps in Nyo Modaki. Uh but those traditional indices are based on uh temporal anomaly of sea surface temperature in the Pacific uh ocean and uh they don't take into account uh the global warming the the the increase in overall increase in temperature. So it might appear that ENSO are elos are increasing in intensity in time. So we've used a recently developed a new index which is called relative oceanic linear index uh that uh takes into account spatial anomalies in linear region and uh does not show uh intensification of of of of recent nas compared to uh historical ones. uh so that's considered more appropriate because the the impact is expected to be or influence on the atmosphere is expected to be uh resulting from those relative anomalies from the spatial anomalies as well as as a temporal uh now to uh to contextualize uh the impacts of ninas uh we have to look at uh the diverse climates within the within the regions within the region And uh we've basically unpacked this uh evaluating two different I mean there several sub regions but considering them within the framework of a of a rainfall seasonality. Uh so we have this uh what we call summer rainfall regime in the northern part of the region uh with rains between May and Octo and October and are driven by which are driven by uh southwest monsoon and in to the south we have the u Australia Austral uh here in this in this report in this in those analysis um and in uh that southern region uh it rains more between October and May. Uh so there is no clear uh dry season of course. Uh so there is it rains more during the rainy season.
Uh and that rain is driven by um north northeast monsoon.
Uh so now how does the seasonality of rainfall align uh align with the seasonality of Enzone? Um as this figure illustrates we have those different seasons different rainy seasons in different uh different regions. Uh to the north we would have a rainy season that basically aligns with the development phase of of of N. So during the Elino years uh during the in the period where in period between May roughly in October and October, November, December we have a peak of Arinia and during the decay. So that uh uh and that follows a decay phase and uh the uh rainy season during in winter info regime to the south of the region would align with peak and decay um of the Elino evolution.
Um now we can start unpacking um how does the Nino affect uh those different sub regions and and and reasons and and seasons. Um so um u anomalies under an rainfall anomalies under Nino which illustrated here um are almost exclusively negative. Uh there are some regions where they are positive but uh they're very very small ones. Um and um so in general leads to reduced rainfall across the entire region. Uh but those magnitudes magnitudes of of anomalies uh vary strongly between seasons and sub regions. Um so we have a particularly so in in in this figure I show uh when the main rainy seasons occur using those rectangles there. So we can see that uh the strongest anomalies uh rainfall anomalies fall actually outside of the of the those main rainy seasons uh showing us that you know that the strong impacts are during the dry season uh in basically in both rainfall uh regions in the to the north and to the south. um and uh I don't show it here but uh you know going to uh other data we can see that um the rainfall anomalies are driven mostly by reduction in uh rain days rather than reduction in um rainfall intensities and um the anomalies in in rainfall result in uh expected in the same direction of anomalies in uh in indices that are other indices, environmental indices that are strongly linked to uh to rainfall. So indices such as NTVI and soil moisture so show patterns related to uh to rainfall anomalies.
Now um we can look at the uh temperature anomalies and uh again we see mostly in the warmer temperatures uh although not everywhere uh not in all uh regions and those temperature anomalies appear strong uh appear to be strong only after uh no peaks. So in December uh to uh to May in some regions actually according to this particular data set appears that uh there are cooler conditions uh during for example in mark.
Um now if we stand up unpacking um rainfall anomalies um we see that although in general on average uh uh leads to uh lower rainfall in the region across all the sub regions uh the individual years individual nine years are not necessarily uh not necessarily dry. So most of the uh driest uh years experienced uh historically and were uh under El Nino conditions. Uh but in some years uh even though there was a NA in some years uh regions experienced average or above average u rainfall and particularly um Myanmar and uh central uh mainland East Asia did not uh do not show very strong uh anomalies and undermin and show uh quite a lot of wet years uh during an conditions. So looking at those individual years and uh counting them uh we can uh derive empirical probability of of a year being a drought year. um uh that that is based on those historical uh data and uh that map shows those probabilities and you can see that uh we have a basically very strong probably very high probabilities very like high likelihood of a year being drought year uh we're looking here at one in three years drought um under El Nino uh in the southern region in in a maritime continent region in the winter uh rainfall um region and uh in the in the in the north in the summer rainfall region probabilities are much lower and basically we see no influence of Myanmar but uh uh some very sort of divided uh conditions are but those probabilities would express what you know the probability the possibility that uh uh year materializes as wet or dry. So those probabilities are relatively low in the northern uh northern region in the in a in a mainland uh east Asia um and slightly higher in the Philippines.
Um now we can look at what is a combined impact of so and IOD IOD being another uh large scale uh climate driver that influences rainfall uh regionally and globally. And um I compiled here anomalies uh similar picture. I'm done this. I'm taking a picture to the one that I shown uh uh previously and uh another one uh where we uh identified the years that are that had a strong positive uh IOD uh and uh were Nino years uh which is roughly half of the all the NO years in the in the historical times and we can see that u you know the overall whole uh magnitude of anomalies does not change but we do not have uh those wet years under uh IODD uh conditions and uh it appears that uh uh that uh IOD increases uh increases drought increases the severity of uh the rainfall anomalies only in the uh in in in this region in the central uh mainland at uh Asia.
Um um now we also unpacked um how does how do the Elino driven anomal for anomalies link to the growing seasons and that analysis is done on the country uh basis because that links to uh to production anomalies and anomalies in uh yield uh of various crops. Um and those data are available only at the country uh level.
And in here we could see that um uh that there is uh I mentioned that uh that Elino driven anomalies rainfall anomalies manifest uh strongly in dry season and this aligns uh mostly with the secondary uh rise growing season. Uh so we can see those uh numbers being strong for example in the Philippines uh and uh in the uh winter and for region uh countries um and um um in the mainland Southeast Asia uh we would have a impact mostly on the in during the harvest uh phase of the first year first year of El Nino and during a um planting phase of the second year of El Nino. Um and uh notably Philippines and Vietnam show slightly different patterns there. uh perhaps because they have a uh slightly also slight I mean in different patterns of rainfall anomalies with respect to um with respect to planting seasons because those planting seasons are uh slightly different than elsewhere there.
Um so do we see impacts of uh historical and elinos in agricultural production?
uh that's uh rather tricky to show uh because u you know if when we look at historical figures of of production they are dominated by uh long-term trend long-term increases in in production yield uh in production in uh uh planted area. Um and uh what we do for those analysis, we basically run a running mean of each of those uh production curves, calculate anomalies and try to relate those anomalies uh back to uh to uh to NSO and Elia. And what we see here is that um anomalies in general correlate negatively with Elino. Um so we have a lower yields under any conditions. Um but that negative anomaly is only consistent for the second year output.
So the the output during the second year of of Nino. So uh the year uh when the decay phase occurs um correlations uh during the first year of Nino are they vary between the countries and perhaps um they that variation results from the fact from this sort of alignment of of cropping pattern uh and uh the strength of the uh anomalies, rainfall anomalies uh during particular parts of the that of the growing season but we haven't unpacked it in that detail yet yet. Uh we also tried to do uh to analyze uh a combined effect of ENSO and global fertilizer prices which is uh relatively relevant uh this year. Um but we could see very little uh combined impact but again uh this is uh probably uh because of the deficiency of uh uh you know long-term uh data here.
>> Apologies uh we also looked at >> for cutting you off please >> uh wrap up your presentation in the interest of time.
>> Yes, that's the one one before the start. So we also looked at the impact of neon on fisheries. Uh but it appears that it's you know that there is a signal a strong signal uh of in terms of surface temperatures um with cooler temperatures on the during the development phase of of alinius and and strong warming on the peak and and uh at the decay phase. Um but the complexity of uh so there is a potential that there is impact but uh we didn't manage to to unpack this in detail because uh it's uh the rather complex system. There is many factors confounding factors that affect um potentially fisheries yields. So uh to finalize uh we have a couple of messages here. Um we know that an is associated with lower rainfall warmer temperatures in the region but those rainfall anomalies vary between sub regions and across the seasons. Um we have a understanding that not all result in drought. Uh but there is a higher chance of drought in the winter rainfall region than the summer rainfall region. uh and uh lineers affect agriculture product production with impacts manifested consistently across the region during the second year but less consistently during the first year of the media episode. Um for rice uh those impacts results from how the seasonally varying rainfall anomalies align with phases of the growing season.
Uh thank you.
>> All right. Thank you so much Dr. Wolski.
very interesting study. Uh it can actually help us understand more about the relationship of ENSO with rainfall not just locally but also uh regionally.
Very helpful indeed especially in the context of agricultural planning. So once again thank you very much. Our next presentation would be coming from Mr. Tensha Dori the international CIS specialist of the FAO Philippines. He will be presenting to us the development of the national subnational CIS platform for agriculture and fisheries in the Philippines.
Hey, good morning. Just just give me a moment.
Okay. Yeah.
Let me check.
So, uh are you able to see my screen? Uh J.
>> Yes. Go ahead.
>> Uh thank you. So, uh maybe I'll uh stop the video. So good morning and I hope uh maybe good afternoon to some. So I'm Sentoji as Jerem mentioned uh working uh with the uh FE Philippines. So I'll be briefly uh discussing our ongoing work.
So no much of uh technicalities or you know the use case applications but uh uh our efforts in terms of uh developing uh primary services uh for agriculture. So you know it it is more of a holistic approach than you know uh and or a use case scenario or a single event. So we are taking uh our work you know uh across all stages of agriculture uh planning and you know also uh planning from short-term to long-term. So in a way we are uh building uh long-term uh climate resilience in the agriculture sector.
So partners uh for building uh climate resilience in the agriculture sector. So particularly uh we have uh an ongoing uh project which is one of the you know big biggest project uh in the Philippines when it comes to the uh climate resilience in the agriculture sector and we are partnering with the department of agriculture Pagasa uh and the project uh is uh funded uh by the green climate fund. So at the national level uh FEO, the department of agriculture and Pakasa all these three agencies are the implementing agencies.
At the same time uh FOE is also the uh accredited uh entity. So collaboratively we are you know partnering to uh build uh long-term resilience uh in the face of climate change in the agriculture sector in the Philippines. So just to provide you an overview uh uh a quick glimpse of the uh project. The project is a 7-year project which uh which started in 2024.
Uh and uh the project has uh crosscutting uh uh themes. So we are working on both you know the adaptation aspects as well as uh the uh mitigation aspects and the project uh is spread across the uh whole nation you know starting from south to the north uh across five regions and nine provinces and also 100 municipalities. Within the 100 municipalities we have also uh established uh learning groups. Although uh the process of starting establishing the learning group is still going on. So we'll be uh by the uh 20 end of 2028 we will have already established uh 1,500 learning groups where we will engage uh the the farmers in the CIS uh climate information services learning climate resilience technology learning and then you know mainstreaming of uh gender and environment uh en environmental social safeguards in both CIS and CRA uh practices. is so the project has three main outcome.
So the outcome one is strengthening institutional capacity for developing uh climate information services to support climate resilient agriculture. So this is the component uh which I'm currently leading and then the other two component is the one is on adoption of climate resilient uh technologies and also uh developing enterprises by the farmers.
The third one is then mainstreaming you know the climate resilient frameworks the markets uh the j the agenda and other uh environmental social safeguards into both our climate resilient practices as well as the climate information services. So now uh coming back to the outcome one so how we are looking at in terms of uh strengthening uh institutional capacity for climate information services. So in 2024 uh when the project started what we did was we did an assessment across these five regions you know trying to understand the existing capacities in terms of you know climate services and the gaps and also you know the plans or activities that the each stakeholders may have you know moving forward. And what we have what we did is we assess you know uh in four areas the capacity to use and implement uh climate services or climate information services in their specific applications. We looked at the product utilizations because uh as you are you all are aware Pakasa has a range of you know information starting from now casting uh to you know climate change projection and we really wanted to see how these products are being utilized whether it is optimally utilized or underutilized or you know uh somehow in the moderate usage and then we also looked at infrastructures in the particularly in the regions and provinces as well as in the municipalities you know the infrastructures to enable you know climate in climate services use. And thirdly, we looked at the uh institutional uh collaboration and coordination in terms of uh applying, generating and then you know uh disseminating uh or communicating climate information services from the center agencies to the uh farmers or to the end users and then you know the feedback mechanisms that are existing uh within the existing setup and then based on our findings what we have come out is we uh came out with an objective. So what we wanted to do is we wanted based on our findings we wanted to link science and institutions and society to strengthen how we use you know uh climate information services for our day-to-day planning or our long-term planning or our long-term investments.
So what uh we are aiming is we want to uh leverage or take advantage of the global uh knowledge, global resources, glo global skills then bringing it you know coupling it with the regional resources and skills such as from ASEAN or other you know uh regional centers and then bringing this down to the national level further strengthening the national products and services of Pagasa and then at the same time at the national level we have the department of agriculture you know who is responsible and is the frontliner in terms of dealing with the farmers. So they have this uh agriculture technology agriculture data and information. So at the national level we wanted to bring you know Pakasa and department of agriculture together to develop relevant climate agromeological information and services to the farmers.
So at the national level how we are developing the capacity is through trainings regional workshops you know focus group discussion and forums and also through the development of tools and systems and guidance to enable to capacitate our national partners you know the Pagasa and DA for the climate information services and uh when we do these things our objective is to be you know uh user centric so meaning whatever we generate in terms of uh in The climate information services whether we use it seasonal forecast whether use we use it medium range weather forecast or whether we use historical uh observations those information the end output that we want we generate should is userentric and meaning you know if you develop risk thresholds for heavy rainfalls then it has to be userentric meaning it should be location specific the communication the community specific you know Because what we have found out is there are a lot of thresholds being developed as currently and then those thresholds do not fit or is not reliable or relevant to all the communities. So that has to be you know userentric and similarly simplified impact outlooks and then ultimately uh actionable advisories. So in order to uptake these uh kind of location specific uh you know actionable information the community or the farmers needs to be capacitated. So how we are doing? We are doing it through as I mentioned learning groups then farmers field school and also we are consistently carrying out trainings and advocacies with the farmers with the provincial with the municipal you know uh uh staff uh in terms of uh how to use those climate information, where to access, how to use, how to communicate and also what are the limitations when you use these uh climate information services. So ultimately through these uh you know analysis building these aims and objectives what we found uh what we realize is we need to build up or strengthen uh CIS governance. So meaning we need to have a proper institutional structure that enables the in uh CIS uh climate information development enables communic communication and enables you know consistent feedback so that the climate information or the climate services are consistently improved and is relevant uh to you know each specific users. So based on based on the global framework for climate services and also the national framework of climate services of WO we came out uh with this uh structure you know the climate uh we call it CIS climate information services implementation framework. So this is uh an institutional mechanism you know a multistakeholder mechanism to enhance not just the coordination. So coordination does exist but you know the collaboration is limited as of now between the agencies when it comes to climate services. So we wanted to strengthen the collaboration and then institutional partnership as as well as their roles and responsibilities. So through this structure so we have uh the plans are already uh you know in place and we are in the we are currently in the process of setting up these uh institutional setup. So we have uh national uh climate information uh services center which will be you know hosted at department of agriculture center office. So we are putting department of agriculture as a pivotal here because when it comes to agriculture we are dealing with the farmers, fishers and you know uh other um uh sectors you know farming sectors which in which DA department of agriculture is the you know the frontliner the the main agency communicating uh with those uh sectors and then at the same time with the equal responsibility at the national level so we have Pagasa who will be supporting uh the department of agriculture for for climate services. You know that would include a range of weather and climate information and data. And then we have uh something called CIS support system.
So we have multistakeholder or interdisciplinary technical working groups set up at the national level, the regional level and provincial level with specific. So but overall their main you know responsibility is to provide strategic guidance in terms of developing climate information services climate resilient technologies and also vetting on you know the technologies that we introduce whether this is relevant whether this would be workable or not. So they they they they will be the ones who will be guiding the the national centers and then you know in to further support this national CIS centers we have five regional CI centers as of now uh in the five project regions then provincial CIS centers which would be supporting the regional centers. So those information from the national will be you know uh disseminated to the or transferred to the regions. regions will have their own uh you know region specific information and then accordingly the provinces will have uh their own provin provincial specific weather and climate information ultimately disseminating to farmers and then the it also allows a structured mechanism to you know collect feedback you know from the communities to the provincial centers provincial centers to regional and then the national centers for improvement of consistent improvement of climate information services. So ultimately this framework allows the institutionalization of climate information services within the national uh institutional setup. So that you know even after the phased out of the projects the use of CIS is sustained which otherwise at present is not the case. Uh except for few uh projects lot of uh climate related projects which are supported through projects have not been sustained after the project phased out.
So that was the that that was one of the main gaps and through this CIS implementation framework by establishing this institutional mechanism. So what we are looking at is to sustain these CISUs even beyond the project phases and this is more you know a complex uh system you know how we information will be flowing within these uh CIS implementation framework how we will be developing this agromelogical uh services and products so I'll not uh discuss this into detail but this system actually delineates you know specific role rules and responsibilities of each stakeholders at each level as you seen you know the national the regional and the provincials. So this is how it will flow and also it also sets up clear guidelines and clear structures in how we should be collecting feedbacks so that you know there is a consistent improvement in uh input in terms for improving those agological advisories or agrometoologgical informations and products. So just to conclude on the framework development. So when we were developing this framework which I just mentioned. So how we engage is not just the national stakeholder but we engage the stakeholders starting from national to the regional provincial, municipals and even the communities. We also sat together with the farmers and discuss them you know what are the challenges of accessing climate information as of now and what are what are the other options that you see then you know enables you enables you to use those information consistently in a more sustained way. So that's this and then in order to enable this we have also uh developed uh climate information services platform and to most of the NHMS you may be aware that WMA has something called climate in uh climate services toolkit. So this climate information services platform that we are currently developing in a way functions as a climate services toolkit but uh with more you know features and capabilities. The meaning it is similar to climate services toolkit which is a you know kind of a one-stop shop for climate data forecast tools and guidance but it also enables has enables or works as a decision support tool you know which has alia presented similar to this one but we are not focused on one uh specific crop or one specific event. So this uh platform will also serves as a decision support system that ultimately you'll be able to provide localized and user specific actionable advisories across different time scales. For the starting we are using seasonal forecast and also the medium range uh which is 10 days weather forecast from Pakasa.
And uh another key aspect that we have involved is while developing these formats and also the advisory formats the structures how we will communicate this information. Uh it's not how we wanted or it's not how Pagasa or DA wanted it. We involve our farmers like what kind of format you would want it because what we have found out is although there's a variety or numerous weather and climate information but these are not you know uh location specific or they they are not tailored to the specific need of the farmers. So we really need to sit with them and you know ask them although the weather weather information available is already relevant to the region they are not able to consume. So in order to make that information consumable so engaging these uh local communities is very critical. So yeah this is the last slide. So >> okay >> as of now we have already generated these uh informations although the work is still in progress. So the main area of our work we will be focusing on the seasonal climate advisory for agriculture. Then the 10 day, five days and also based on Pagas, you know the uh ENSO alerts we have also we are also providing ENSO bulletins specifically for agriculture and then agroclimatic information you know particularly the pest degree days you know and also growing degree days and key lessons learned is uh although this is just work in progress as I mentioned but what uh we have found out is if you're able to engage the local communities. If you are able to engage the local agencies such as regions and provinces then the you know sustainability is assured. So if you see in the picture this is from one of the regional CIS centers that in region five and now they have in fact they have become better than the national CIS centers because they have they are consistently you know uh working and they are consistently interacting with the farmers in the provinces and in the communities. And then also uh what is important is also having this structured institutional mechanism is key to the sustenance of these kind of uh you know centers or the sustenance of climate information flow.
So what we have found is the institutionization or implementation of CIS implementation framework has further enhanced the sustenance of climate information services across the nation you know from the from the national to the region provinces and then you know feedback mechanisms from the communities until the national uh CIS center. I will stop here. Thank you.
>> All right. Thank you so much uh Teno. So as you can see a lot has been done by the GCFappa project and we are still planning to do more in the coming years.
So to all our participants you can use the Q&A button to submit your questions to our resource persons. So we will answer them during our open forum session. So our RPs I can see are already actively answering your questions as we go about the session.
Thank you. So our next presentation would be from the UNS cup represented by Miss Parvati Subha and she will be presenting to us the impact based forecasting for the seasonal outlook of the JJ 2026 season.
>> Thank you. Uh am I audible?
>> Yes, we can hear you.
>> Um good morning to all distinguished speakers and uh my dear colleagues. So today I'll be sharing uh the ESCAP uh impactbased forecasting outlook for the current season that is JJS uh 2026.
Um let me quickly share my screen.
>> Yes. Uh I hope my screen is visible.
>> I'm sorry. Can you switch your display?
We can see the notes of your slides.
>> Okay.
All right.
>> Yes, >> that's better.
>> Okay.
Um, so today the objectives are twofold for the discussion. uh we will be presenting the outlook for the GJS season and also we will be showing the latest uh product u digital product from escap which is the offline QGIS tool uh that can be easily used um and uh it it is accessible uh in every system on the latest version of QGIS in your uh in in your uh computers. So um we will be showcasing the results based on uh the plug-in output. So um giving a bit of an introduction um about the impact based forecasting methodology that we use at ESCAP. So we take the um seasonal outlook uh from in the form of the temperature and the precipitation anomalies and use the exposure data including the population agriculture infrastructure uh data sets. Um and we combined these uh hazard and exposure layers to identify the risk hotspots and identify the patterns that are um that are being shown for the current season.
Um why it matters because it provides policy makers a clearer uh understanding of the impactbased outlook and with the new uh latest output which is the QGIS plug-in uh we are able to generate reports uh within a matter of minutes so that um if you have the seasonal forecast outlook you can already generate the IBF report for your region or your sub region um based on uh the exposure layers that that is required.
So a little bit of a introduction on the rapid IBF tool. Um so ESCAP has been supporting impactbased forecasting since 2021 and uh we already had an online version of this tool available uh in our ESCAP risk and resilience portal. Um where the seasonal forecast from every region is updated. Um and we you can also access the historical uh seasonal data sets from this online portal. And uh what we basically do is we upload the seasonal forecast and in instantly get the exposure results uh for agriculture, energy and uh population count. So um the data sets are readily available online and um you can check out the rapid IBF online as well uh using the escapisk resilience portal. But today we will be discussing the offline version um of the ESCAP uh rapid IBF which can be used in um any QGIS uh software that you have in your system. Um even if someone is uh very new to GIS, we have provided an easyto- read technical guide uh in the website which can be accessed and you can uh use that guide to install this plug-in and run the analysis on your own system. Uh so what the plug-in does is basically it can upload all the seasonal forecast data and the exposure data reclassify it based on your requirements and generate the IBF report uh for that that particular season. So uh today I'll be discussing the uh seasonal outlook results using the same plug-in. Um as we know the precipitation temperature anomalies have been already discussed at length and uh we are aware that um for the mainland Southeast Asia um this uh this season uh there's a mix of both um near to above normal and below normal rainfall. Um but for the majority of uh region um the temperature anomaly is uh likely to be above normal.
Um once we have the seasonal outlook as I mentioned earlier we overlay it with the exposure layers. Um so for this context we using the total population count data from world pop. We also have the rice production data from FAO map span and we also use the power plants and the hydrop power plant locations uh from uh the Asia-Pacific energy portal.
So um using these exposure layers we can uh generate the results um for for the different uh sectoral outlook um using using the seasonal outlook data.
So um coming to the first aspect which is the potential impact of above normal precipitation on the total population we can see that the main countries at risk are Vietnam, Philippines and Myanmar. um especially in uh Vietnam almost 65 million people um are likely to be exposed to the amnormal rainfall condition um out of which um 64 million are exposed to the low likelihood.
Coming to the moderate risk uh we have uh in Philippines 47 million people uh which is almost half of the total population will be likely to be exposed to the moderate likelihood. Um and similarly in Myanmar uh around 10 million people um are likely to be exposed to the moderate risk of abnormal rainfall.
Uh coming to the below normal rainfall mainly three countries are at risk which is uh Indonesia, Philippines and Vietnam. Uh we will be coming to the details of below normal rainfall outlook in the other sectoral reports as well which is uh the agriculture sector report and the energy sector report.
Uh talking about the rising temperature risk uh for this season we expect above normal rainfall for almost all entire region of Southeast Asia and especially at risk are the countries of Indonesia, Philippines and Vietnam uh with around 97 million people being likely to be exposed to high likelihood of above normal temperature uh in Vietnam. And in Philippines we have around uh 99% of the total population which is likely to be exposed to high likelihood of above normal temperatures. All the detailed reports will be available um soon after uh in the form of the IBF reports that are generated using the QGIS plug-in.
Uh coming to the agriculture sector outlook uh we have gone a step further to incorporate uh the seasonal nature of um agriculture sector. So as we know uh the temperature and precipitation outlook can have a different impact um on each crop and it can have a different impact based on the crop um crop growing stage. So uh for for the Southeast Asian region we have considered rice um as the main crop for the uh for the agriculture outlook as we know the rice crop is likely to be in the sewing and growing stage uh during this particular season.
So uh we have considered that aspect into account uh while generating the IBF reports. Um if you visit the ESCAP risk and resilience portal you will also be able to get a detailed idea of the methodology used for this purpose and uh we will also have uh we have also provided the information on how the uh temperature and precipitation anomalies impact different crops at different crop grow crop growing stages as well. Um so uh for for this context we have the potential impact of above normal temperature on agriculture. Um as we can see in the charts um there are three countries which are likely to be at moderate to high risk. So uh in Vietnam almost all of the total rice production um in the country is exposed to high likelihood of above normal temperature.
Um and in Thailand and Indonesia uh we have around 30 million metric tons and 21 million metric tons of rice which are likely to be exposed um to high uh temperature anomaly.
Coming to a similar aspect which is the below normal rain uh rainfall uh impact on agriculture. As we know that the below normal rainfall and the above normal temperature can have a compound effect on the crop growing stage for the rice crop and the increased water stress uh due to this uh rising temperature and reduced rainfall can have effect on the tillering head development and the grain filling stages for the rice crop. So um there are three countries again that are likely to be affected by below normal rainfall. We can see that Indonesia, Philippines and Vietnam are again um in the in the list of highly exposed countries in terms of um exposure to below normal rainfall in the uh season.
Coming to above normal rainfall, we have uh parts of Vietnam, um eastern and western parts of Myanmar and also Thailand um whose rice production is exposed to above normal rainfall um in the region.
Now equally important is is the factor of considering the energy sector's contribution. So if you look at the seasonal outlook um what we have done here is for the energy sector we have uh extracted the data for the power plant locations. We also have the data for the maximum capacity uh in megawatts for each of the hydropower plants. Um apart from hydropower plants we also have data on other sources of power plants which include the nuclear oil um and thermal uh sources. So uh here we can see the potential impact of precipitation on the hydropower plants. Um the charts show the number of plants which are exposed under each category of um above or below normal rainfall. As we can see in the in the uh conclusion uh nearly 77 power plants in Lao PDR are exposed to above normal rainfall. Similarly in Myanmar and Philippines we have um around 50% of the total power plants are exposed uh to the likelihood of above normal rainfall.
Um so usually in case of rainfall the uh rain as as you know rainfall is critical during this particular season the JJ season uh for filling the reservoirs and below normal rainfall condition is more challenging uh for the energy production uh in several countries. So we also have the outlook on below normal rainfall which is provided here. Um as you can see from the earlier outlooks as well, Indonesia, Philippines, um uh these are the countries which are likely to be exposed to below normal rainfall. Um to um in addition to the Indonesian Philippines, we also have Malaysia under the um radar for uh high likelihood of exposure to below normal rainfall. uh which is likely to affect the energy demand uh in these countries um as the supply of energy is dependent on a lot of hydropower production. Um so these are the outlooks that we have uh provided for the um for the presentation but we also have um additional outlooks that are prepared for the total power plants and for other major crops in the region. So uh if anyone is interested we can also provide the outlook for other uh other other uh exposure as well.
Coming to the way forward u more detailed data uh which will help us uh in generating the sharper insights. Um as you know already uh the the data that we use are uh the the global u raers that we have from FAO and from worldp.
But if you have additional data sets especially for agriculture or energy sector and would like to uh display the impact based forecasting result um using the exposure data sets then we will be happy to collaborate and u help uh in help support the generation of IBF reports. Um the next steps also include uh we have uh another project uh called climise which is a tool uh which is an adaptation uh focus tool which will integrate different adaptation relevant indicators for the entire Asia-Pacific region is going to be a userfriendly decision support uh tool. Um and we also have uh extended um plans on integrating more uh deeper exposure analysis for the IBF outlooks and we'll have uh over the over the coming months we will have sector specific applications of IBF beyond agriculture and the energy sector as well. Um thank you so much. Um and I look forward to any questions you may have in the Q&A session.
>> All right. Thank you Miss uh Subha.
Excellent presentation from the UNS Cup.
So our participants can actually access this link and explore it right if they want.
>> Yeah. So last but not the least, I'd like to call on again Miss Telmemeo, the project leader of the uh GCF uh funded project multi-hazard impactbased forecasting and early warning system for the Philippines project to present to us the um recent innovations and improvements of the GCF uh MVuse project.
Uh, mom, can you swap displays? We can see the notes.
The button is located at at the top of the screen. That's better. Much better.
story. Uh good morning everyone.
Uh distinguished guests and delegates, colleagues and partners from the Assan region. It is an honor to present the Philippines ongoing efforts in advancing impactbased forecasting and early warning systems through our uh miduse project.
So, the Philippines is exposed uh to uh several hazards such as tropical cyclones that could lead to severe winds, floods, storm shortages, and landslides. That increasing climate variability and intensifying extreme weather events are placing greater pressure on national and local disaster preparedness systems. So this challenge is no longer only forecasting hazard accurately but the bigger challenge is ensuring that forecasts lead to timely and effective decision before impacts occur.
So what are the key identified gaps in the early warning system? First is the disconnect between forecast and actions.
Traditional forecasts explain what the weather will be but often fail to explain what communities should do.
Technical language limits understanding among non technical users and forecast must evolve into decision support tools as well. The second gap is gaps in science communication and information utilization. Weak linkage between information providers and end users and limited translation of forecast into actionable and user centered information. And the third is the fragmented linkages between preparedness and response. Existing systems are still heavily responseoriented. Investments are often mobilized after impacts have already occurred. Preparedness and anticipatory action remain weekly institutionalized.
So the GCF uh the first GCF project that we have in the Philippines is uh approved in 2019 but in implementation was affected by COVID 19. So we start uh accessing our funds 2023. Beside these uh challenges, the project from uh will able to sustain its commitment in institutionalized anticipatory and impact based approaches despite operational constraints. So said this is the first G project. Then uh the project covers four pilot representing different hazard context in the Philippines. to Gigaro severe wind and flood. Legospi city severe wind and flood. Palo severe wind and storm surge and Ubatan deaoro severe wind and landslide. These sites were selected because they represent highly exposed and hazard-prone localalities. The project design ensures that methodologies can later be scaled nationally.
So the over goal of the project is to increase resilience and enhance livelihoods of vulnerable communities.
MIPUS is fundamentally a people centered resilience initiative. The focus is not only reducing mortality but also minimizing livelihood disruption displacement and long-term soio economic losses.
The miputs adopts a multi- agency implementation structure. Pagasa we implement uh four outputs. So the Pagasa leads the outcome output one leads hazard forecasting and impactbased forecasting development together with MGB that does the landslide and office of the civil defense leads preparedness and response and integration. So output to we develop the impact and response table and also the knowledge decision support tool that will be used uh by the project. Then department of interior local government supports localization and institutionalization of the LGU level while the world food program uh uh mainly uh lead in the output tree contributes in the anticipatory action and humanitarian coordination expertise. This demonstrate that effective early warning system require institutional interoperability not isolated technical systems. So output four is uh the main uh main streaming that will be led by the department of interior local government.
So again uh the key identify gaps in the uh early warning system the how we address that. So we adopt the WMO framework for impact based forecasting the project bridges providers the first mile and to the last mile the users of weather information. This major step from oneway forecast dissemination toward collaborative risk communication.
Forecasts are transformed into impact assessment, recommended action and decision triggers. The objective is to ensure that forecasts lead to directly to preparedness and exploratory action.
So we also adopt the 4x4 matrix in terms of that incorporates uh impact severity and forecast uncertainty.
uh the the x is the the impact level and the y is the likelihood of the impact.
But then uh we try to change uh for the Philippine context the color. So uh wherein the severe will all be red and the significant will be orange and minor will be yellow. uh for responders they will also see the 4x4 but for the the public they will only see the one-dimensional the color.
So so how do we do that by addressing uh how we address how we compute for the impact. So by integrating hazard exposure and vulnerability.
Then uh first of course the the hazard modeling for example uh there is a tropical cyclone Pagasa issues a truck uh this example is super typhoon one then transform that into uh severe wind. Then number two is exposure mapping or uh exposure data. So the local exposure data set are identif identify building types, infrastructure and exposed assets. So in here for the four project site, it shows you the distribution of the topology of the houses that being uh used in the project. We partnered with the UPI University of the Philippines for uh development of the uh the vulnerability curves. So uh the third one is the vulnerability curves. So uh for the all the building types uh we look at the fragility card fragility curves that is slight moderate extensive and severe. So in here is the the impact assessment wherein uh the threshold is being uh conferred with stakeholders like minimal is less than 1% minor is 1 to 30% damage 30 to 70 is significant and greater than 70 is higher. So this is how then uh the percentage of structures are affected are used as a thresholds and there is an equivalent uh hazard.
So in here uh shows you for uh if the uh local government units have their own uh uh exposure data they we could have any specific uh threshold for the different uh impact level. But if without uh uh struct uh exposure detailed exposure data then we use the general assuming there is a homogeneous uh building uh types across the area. So here you would see to gigaro and the gaspi has and also batanes has a higher uh trigger for a severe then for like palo and and also uh new batan has a lesser threshold for going to severe. So we intend to have this taste one nationwide for the severe wind and we're going to use we intend to use the PSA data using that uh CBMS data for the exposure database. So here is an example of uh of uh issuance of one last year.
Internally we've been uh issuing it for the project sites but here is a for example the areas uh the the area is uh uh for first issuance second issue once and the third issuance. So if it's a minimal there you only in the text we issue the likelihood. Here is example wherein uh you have your society and economy, housing and buildings, agree transport, health and safety and lifeline and utilities. So if they have the detailed exposure data then you were able to get the population female and male uh PWD senior citizens and so on. And for the buildings in terms of wood, masonry, concrete and steel. For this example, you see as early as uh six uh or next three days there is an expected landfall. The severe model is able to provide forecast which area likely to experience uh impacts. For dinongan for example, the impact level is translated into like significant or issued at uh November 9. Then init issued at November 7 uh low likelihood of uh severe and 10 very low likelihood of minimal. November 8th uh medium likelihood of severe and low likelihood of minimal by 10 and this will be in a calendar base but uh on the actual it's uh significant. So that is a sample and this one is for uh other areas. If there is no forecasted impact then there will be no issued on November 10. So that is how we we intend to have that. Another one that we have done is uh by establishing uh the national impact tables per sector. So I said we have the housing and buildings. So for the impact uh uh warnings that we have we use the housing and buildings. Then we have health and safety lifeline and utilities transport and agree. So what we did here is we have a focus group discussion to uh to for the sectors to do their uh impact statement as well as response and their threshold as well. So that is also done for the different hazard that we address. So the same uh methodology the UPIs also develop uh vulnerability curves for floods, storm surge and landslide. So this is the sample of uh issuance for flood storm surge and landslide. Landslide is issued by the minds and geoscience of DNR. So here how we develop uh the impact table and response table. So it takes time from bottom approach to national as well. So uh the sector and also did a sector validation. So next week we'll also meet with them again since we're about to operationalize in terms of uh confirming their threshold as well for the different sectors. So here are some of the pictures that we have to ensure that these stressors are operationally relevant and actionable. Extensive consultation and technical workshops were conducted with sectoral experts and government stakeholders. So this pre uh this process ensured that the threshold reflect existing operational practices, sector specific vulnerabilities and actual decision making requirements at both national and local levels. So here is a sample beyond forecasting impacts.
The project also develop response tables. This link projected impacts to recommended preparedness and response actions. This creates a direct operational bridge between forecast and action. The system therefore supports anticipatory decision making instead of retractive dispense. And here uh WFP uh work with us in terms of working uh with the pilot areas in uh doing the crisis timeline. So uh how they use the IBF warning as well as existing products and services of Pagaza from the TC threat two weeks to a three day for the IBF. So they identify what are the anticipatory actions from uh TC uh from 15 days from our TC threads down to our IVF as well. So here is a sample of uh again I have seen earlier for the escap they already have that platform.
So we're still developing that platform from uh first mile to last mile from it will be a role base wherein from forecasters role base there uh left side is the dashboard for forecasters where wherein they could adjust the and the issuance of the actual uh uh actual warning and also a local dashboard wherein they could look into the specific area and the the calendar as well as the number of population and so on. So this is uh still ongoing the development of our risk tool. So this is a MAC tool wherein uh it will could be uh used by the different sectors wherein they could uh uh access and do their risk assessment. So it will be a role based. So if uh the local government units have their own data, they could also use their detailed exposure data as well. So here for the second gap in science communication and information uh so here link uh impact based forecasting what the weather will be to what the weather will do. So we link with the uh with effective uh when they translate into actions IBF our goal is to bridge the gap between the providers and weather information and the last mile users. So the pre as uh uh for the pedra scenario building uh as we sent the miuse will come in the exposure understanding and the risk and of course um for the beyond beyond predisaster risk assessment. The Mibius project is also developing a strategic communication plan to address the gaps in science communication wherein the four pillars of early warning for all.
We address the the risk knowledge of detection, communication and response wherein we address it by having a stratcom with the strategies and mechanism as well as uh different components. So this one is a a communication framework that ties everything together. These outcomes are achieved through the four pillars of early warning for all with its specific communication role and cutting across everything is the dead seat framework.
Ensuring that every strategy and every message in this plan is designed with most vulnerable in mind. No left no one gets left behind. So from the national level to local level and to the community level the direct engagement and inclusive communication. So here are the the goal uh operational as well as a strategic objective. So this one is go beyond the project wherein uh the stratcom wherein the first uh the short-term medium-term and the long term it become institutionalized and sustained action. So that one is led by the BIT and also their existing listto protocol is uh already being aligned to the uh IBF and they have their pre their charlie is the severe where in the pre-impact impacts and they have done that for the the the bravo is for their significant and alpha is minor. So these are done and I think I have so many uh fragmented link linkages. So here in the Philippines uh we had recently enacted the RA 12287 or the declaration of state of eminent disaster act. This is a landmark policy reform supporting anticipatory action. The law allows governments to mobilize resources before impacts occur based on forecasted severe impacts. So the me the use will uh serve as a tool for uh for this law as well in terms of preposition preemptive by corporation anticipatory financing and early intervention.
So who will declare it is uh from the president or the MDMC or the local uh and then basis of declaration it is uh from the pedra and recommending body is from the NDMC and criteria for declaration is pro from the forecast and projection. So currently they're looking at miduse to be if it you are forecasting the next three days as severe. So source of funding they could have the GA then also uh this uh portion of local DRM fund dedicated for anticipatory action. This law was able uh uh helped by other NOS's as well and uh that's why we are still uh working on uh the IRR to be signed and it's a no regret approach. If hazard forecast change, the bill adopts a no regret policy, meaning that any anticipatory action taken are designed to still benefit communities even if the expected disaster does not occur or predicted.
So the despite progress several challenges remain model uncertainties, institutional readiness and decision making acceptance and of course IBF requires confidence not only in science but also in governance systems and institutional culture. Sustained investment in capacity development, communication and operationalization remain necessary. The future of early warning system lies not only in improving forecast but improving the ability of institution and communities to act early and to act decisively. And with that uh thank you at as uh climate risk continue to intensify across AEAN region regional cooperation in impactbased forecasting and anticipatory action becomes increasingly important as we see that the IBF for seasonal forecast shared by ESCAP earlier is can be replicated to our countries as well.
So thank you for that sharing and I look forward for our continued collaboration toward a more resilient AEAN region.
Thank you and Salam.
>> All right. Thank you, Mom Talma. Again, another excellent presentation. Looking forward to see and uh use that tool, ma'am. So, these are just um uh one of the innovations and projects that Pagasa is doing to um improve our capacities and and ultimately help our stakeholders respond accordingly to any hazards that they may face.
So at this point we have already finished all the presentations and I am now uh opening the floor for any questions that you may have for our presenters. So in the interest of time um as as much as we want to answer all your questions uh we will only uh accommodate at least uh two to three questions perhaps. So don't worry if uh uh we will be providing you with our uh email address to send in your questions to our uh resource person. So I can see that uh we have two answered questions.
So I'll skip that and we have three open questions. So perhaps we can stick with these uh three questions. So again don't worry we will send you our email address uh to send in your questions to our resource person. So first question um from ton ton ton durun darun.
So the question is um according to the impact of El Nino this year what would be the um I think it's recommended for sector to consider to response to the impact.
So perhaps at least in the Philippine context, Mom Anna can or mom Telma could answer the question.
>> Yeah, maybe for the first for the whole Asen.
>> Oh, for the whole Asan region. So TA, do do you have any inputs on this?
>> Uh, sure. Thank you very much uh for the for the question. I'll also answer on behalf of Pure who had to leave because it was very very early in the morning for him. Um I I think from his earlier presentation we saw that while in general when we think of El Nino for the Azan region we think increased chance of drier and warmer conditions that this really depends on the time of year and the location you are. So the response will really depend on which sector you're in and what time of the year is of most concern. Um but we already heard through ESCAT's presession presentation as well that many sectors could be affected. Of course agriculture uh but also health disaster risk reduction water resources a big one as well. So I mean even at the let's from ASMC's point of view while we can provide some regional inputs really I think um if you're interested at the national level uh it's good to contact the NMHses because they will be the authority about the impacts at the national and subnational level and also help perhaps work together to come up with actions that can be taken. Thanks.
>> Yes. Thanks DEA. Uh do you have any additional inputs mama?
>> Okay. So um >> oh go ahead ma'am.
>> Yeah so in the case of the Philippines so there has been a lot of coordination meetings among the national government concern agencies through the national task force on El Nino. So with this uh potential impact depending so the national task force of El Nino uh convening all five pillar uh five pillars namely the agriculture uh for food and food security the energy the health the water resources sector and public safety. So with this uh task force of El Nino with the with the uh pursuant to the executive order number 54 on the reconstitution and reactivating of the task force El Nino. So the national government together with the local government has already uh established the strategic national action plan for El Nino since 2023 2024 El Nino and with this intending 2026 2027 El Nino. So we are now revisiting and try to update all the strategic action plans written for those uh pillars. So for those five important sectors. So uh coordination on meeting and dialogue is ongoing including different uh uh not only the national as well as the local but including the private sector as well. So this is coordinated against a pool of nation and a full of governments.
All right, thank you so much Mamana and Thea for answering this question. Let's move forward. Um, another question is uh from Wang.
Uh, this question is directed to Teno.
So, his question is uh Teno, what is your opinion on applying the framework on other sectors like disaster risk reduction, health or collaboration with others?
>> Yeah. Uh, thank thank you. uh for the question and yes this is a very good question uh to be uh straightforward yes that this can be you know uh replicated to any other sector in fact this framework is not just limited to agriculture sector by the way uh if you uh go through the global framework for climate services or WO or even their guidance on the national framework for climate services actually the national framework for climate services should consist of all all the sectors. So this framework should consist of all the sectors but for the starting because uh bringing together all the sectors and then implementing this framework would be very difficult. So the best approach is taking and you know face- wise approach and prioritizing the sectors.
So since FU closely works with department of agriculture so we thought that we will start this framework with the department of agriculture in collaboration with Pagas. Yes you can uh definitely replicate this in other sector but and I would also recommend you know have this as a nationalized framework across all sectors but then take it as a face wise so that you know you can really find out whether this kind of framework is really working or not. So yes it can work but take it face wise prioritizing your sector and then less you can actually move on. Yeah thank you Jerry.
>> All right thank you teno. Um another question from uh Dr. Haime Bordales one of our colleagues from the GCF APA project. So to Miss Parvata Subha um the question is is your IBF designed primarily for the main crops such as rice or corn or is it adaptable for uh various crops within the ashen region?
So did you develop an impact table for each crop?
>> Um so we have it currently for rice, wheat and maze. Um and uh so FAO map spam has I think 46 main crops for which the the crop production um layers are available. Um apart from that if there's any other exposure data source that we can use for the ASEAN region specifically we can always implement that uh using the using the data that we have but currently as we using the FAO map span we'll be able to provide the IBF sectoral outlook for the 46 main crops that has been identified. Yeah.
>> All right. So thank you. Thank you Miss Subha. Um I I I think we still have time. We're supposed to end at 12:30, but um it's it's only 12:05, so I think we can still accommodate at least at least this these remaining questions that I can see at the Q&A box. So from an anonymous attendee um the question is have you have there also been observations on um whether these elino conditions have correlated with catastrophic levels of disasters in the past which may potentially recur in the future. Perhaps uh DEA can answer this question.
>> Yeah. Um in terms of catastrophic dance uh disasters I I cannot say uh but I do know that there was a report a few years ago actually from the ESCAP was led by looking at uh under El Nino or especially stronger El Nino. This is when we in Southeast Asia tend to see the most extensive drought conditions.
Um I believe our colleague from the AHA center has also stepped off but I just wanted to they recently actually pointed out in a discussion that it's it's not just the disasters themselves but also the response um they were sharing about a disaster nothing actually not related to any sort of climate phenomena but because of high temperatures it actually increased heat stress for those responding to the disaster as well. So, while I can't say anything about catastrophic death disasters, um, El Nino and warmer and drier conditions may also impact how we respond to them, any that do occur.
>> All right. Thanks, DA. Um, another question from an anonymous attendee. So perhaps I think can answer this or anyone from FAO. So how can anticipatory action be implemented in stormprone regions of developing countries without the involvement of NOS's?
>> Anyone panel?
>> Maybe I'll take that first but uh I'll also request madame to do that. uh they they have been working together with uh WFP on the anticipated but based on my personal experience you know working with the government for the past decades. Yes, definitely you can uh do the anticipatory uh action yourselves you know because the main reason why we people are agencies are doing with NGO is because at the end of the day we are taking care of the most vulnerable communities that are hard hit by the hazards and then we need to compensate them though it's not always that government has allocate funds to support those so that's where the NOS's or other international dollars come into play to really support uh in terms of financial but of course also in terms of the technical capacities in you know uh implementing uh anticipated action because when you implement anticipated action it's not just one window meaning just heavy rainfall and you act on that one so it involves a range of players a lot of uh process you know so it's always good to work with uh you know key partners exchanging knowledge and technology I would uh always recommend that but definitely you can do it but you also need to have you all the resources and infrastructures in place before you do that. Yeah. Thank you.
>> All right. Perhaps Melma can add >> Yeah.
>> to this question.
>> So I could only talk for the the context of the Philippines wherein uh the NOS's uh help us in uh having the our uh enacted law the 12287 in the declaration of state of eminent disaster act. So this one is a uh is now being uh be going to be used in in the country wherein uh anticipatory actions will be triggered through our midfuse warning.
So forecast. So basically uh one enabling is policy as well as our impact based forecasting. So in this in the Philippines uh we had this harmonization because the NOS's has different triggers as well in the uh anticipatory action but again uh the enabling policy as well as an environment where on all uh actors uh national as well as NGO come up with a framework that is uh uh localized within your country because each country has its own way of uh responding in their DRR as well. But anticipator auction can also be shared on how we do it. And I think IBF is the way because in IBF you were able to forecast uh at least 3 days uh ahead for you to be able to access uh to resources. But again uncertainty is uh still a challenge for us modelers as well. But uh the uh the way to go is to enhance our our communication to address uh how to communicate uncertainty and also how the people will act before an impact will occur. Thank you.
>> All right. Thanks. Thanks mama. Thanks momma. Um man is raising her hand.
Yeah because I can't put my question as a a panelist but I have question to miss forbat suba.
Yeah. So you have mentioned that uh there is ongoing uh uh development of the adaptation tool called clma. So may we ask if there would be possibilities that in the next Assean cop uh uh sessions and this could as since this is a group two that could be utilized by the ASEAN uh region and says would there be possibilities in the next ASEAN session as PO sessions this could serve as some of pre capacity building activities within the ASEAN region is the other plans. Thank you.
Miss Parvati, can we use that uh the clean wise for for the preoff session?
I think she dropped on the call. She's still here, Miss Barbati.
>> Sorry. Uh I think I lost my internet connectivity in in between. Uh was there a question about the KMA wise?
Yes. Uh Mamana, can you please uh repeat your question?
Mamana is is actually asking if we can utilize the KMA wise um tool developed by UNSCAP perhaps in the next session of the Ashen COV capacity building. Yes.
>> Yes. I think uh by the by the next session in the October, right? I think uh it it will be ready at least in the first initial stage. So right now what we are trying to do is we are trying to u map out the adaptation um different adaptation practices in agriculture energy sector and in the wash sector. Uh so we're trying to map out the geocoordinates of the different uh adaptations and also trying to identify what are the key risks associated with each of those regions uh which the adaptation is trying to resolve. So um we hoping that this will be ready by um by the next session so that we can have an initial uh presentation on on that aspect as well. Thank you so much.
>> All right. Thank you so much ma'am. So I I I think I can squeeze in these two more questions two last question for our session. So a question from an anonymous attendee. Why have there been almost no cyclones in the Indian Ocean this year, March, April, and May 2026? And why has global cyclone activity has been comparatively low?
I think the can answer this one.
Um, I was going to say we're not at the end of May yet, so come back for Azenov in October. Um I'm not sure actually our Pagasa colleagues if they want to answer because Pagasa actually lead the effort around tropical cyclones for the Southeast Asia regional climate center center network. So they have may have something more to add otherwise I'll just say good question and do come back in October and we can discuss more.
M perhaps M Telma or mom Anna have inputs on this about the um almost no cyclones in the Indian Ocean.
So Pasa as the consortium member of the lead center for climate monitoring for season uh lead center for for long range seasonal forecasting together with the ASMC you only provide a tropical cyclone frequency forecast for Southeast Asia that are developing in the southwest Pacific in the Pacific but for the we still don't have that kind of forecast or prediction uh for for for what is happening in India. So perhaps maybe in the next uh series I will try to coordinate with the SAS MAC maybe in the South Asia because most of the tropical cyclone activity in Indian Ocean is being discussed at the Saskcope the South Asia climate uh outlet forum.
Thank you.
>> All right. Thanks mama and for our last question from um Miss Margie Sugar. So this question is for the UN escapati.
Is the UN escap plugin used for micro level like village or district level so the community can quantify their risk themselves to operationalize their anticipatory action and response.
>> Um absolutely. So the the plug-in was designed uh keeping in mind that uh there will be requirements from the user to uh generate the impact based report at the subnational the regional or at the the local level. So uh all we need to do is we need to have the the boundary admin boundary level uh layer for the village or the locality that we are concerned with. And once we have that boundary layer, u anybody can run the QGIS plug-in using the the seasonal forecast outlook and the population or agriculture um exposure and only the only difference that that we need to do is adding the boundary and uh if we are focusing on the local level, we can immediately generate the impact report at the local level.
>> All right. Uh so currently um yeah just adding on one more point that currently we are adapting the tool to include more local languages. So uh if anybody is interested in collaborating on that aspect to add uh you know local language reports uh for the plug-in uh we would be very happy to collaborate on that as well. Thank you.
>> Thank you uh unscap. So all right that's that's it. Um if you have any more questions we will be providing you our email address at the chat box so that you can send in your questions to our resource person.
So again thanks everyone especially to our resource persons for answering the questions for this open forum and uh we now move forward to the last part of our program. So we will be flashing on your screen a QR code for our participants to answer and evaluate the ashen cough 26. So feel free to put in any comments or suggestions that you would like us to address. So another announcement as mentioned by uh Miss Anna earlier. So the draft consensus outlook for the JJA 2026 is yet to be finalized and we are um requesting our partner Ashan NMHs to kindly evaluate and put in your comments um if if you have any corrections for the finalized document until the 27th of May 2026 09 UTC.
Okay, so that's it. Once again, big thanks to our presenters.
>> Yes, ma'am.
>> Yeah, perhaps we can have a group photo with the webinar participants and I think uh we maybe ask to >> I think is it possible to to promote the participants to panelists so that they can turn on their cameras? I think I think it's is it possible I'm sorry it's uh unfortunately um >> Pashant cannot promote the participants to panelist >> yes it's too many people but we thank everyone for your participation in this uh the last day of our ashen cough so once again the QR code flash on your screen um kindly answer the evaluation form and then put in any comments that you like or that you would like us to address.
>> Thank you and see you again in next 2027 27 but uh in November I'll be retired by then. So thank you for this opportunity to having met you all and Hope you're going to have a productive 27.
Bye everyone.
>> Thank you. Big thanks to Jeremiah as well. Excellent job, MC.
>> Fantastic.
>> Thank you so much everyone for joining.
>> Yes. Yes. Excellent job to Jeremiah and all Pagata colleagues. This has been really great. Ajinov, thank you so much.
And Madame Thala, yes. Thanks also for all your support uh for this Ajinov but also very past Ajinov. I think this is actually the third time the Philippines have hosted. Virginia, every time you do a great job. So, thank you very much.
>> Thank you as well, Ben and TA as well as our invited panelists uh Teno and Palvati. Uh thank you for sharing >> and from Erie as well, our partner, a very strong partner from Erie. So again, >> thank you. Thank you.
>> Thank you. All right.
>> All right. Thank you so much everyone.
So once again, we look forward to seeing you in the next Ashenov 27 this November.
So stay safe and have a pleasant day ahead. Thanks everyone.
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