Sub-regional Workshop on WMO Strategic Plan 2028-2031 for the South-West Pacific
About the Sub-regional Workshop
The sub-regional workshop on the WMO Strategic Plan 2028-2031 for the South-West Pacific has been scheduled for 8 September 2025.
The WMO Strategic Plan delivers the high-level vision, mission, core values and overarching priorities of the Organization. It outlines the Organization's long-term goals and strategic objectives, enabling prioritization of key activities carried out during its stated period.
To ensure that the voices of the South-West Pacific region is captured in the upcoming iteration of the WMO Strategic Plan, we encourage all RA V Members to register for this informal workshop!
Target Audience
• Permanent Representatives (PRs)
• Hydrological Advisers
Key Objectives
• Collect input from Members on needs, priorities and vision
• Discuss global and regional trends
• Share transformations required to stay relevant
• Identify proposed actions in the short-, medium- and long-term
Important Details
• Language: English ONLY
• Workshop Date: 08 September 2025
• Time: 03:00 - 07:00 UTC
Event Schedule
| Time (UTC) | Session | Speaker | Affiliation |
|---|---|---|---|
| 06:00-06:10 | Opening and Introduction |
CL
Ms Christy Leung
|
Hong Kong Observatory (HKO) |
| 06:10-06:25 | Latest development in volcanic ash information for aviation |
NA
Mr Nishijo Akira
|
VAAC Tokyo, Japan Meteorological Agency (JMA) |
| 06:25-06:40 | Volcanic ash monitoring and collaborative decision making in airport |
RP
Ms Resa Pratikasari
|
Badan Meteorologi, Klimatologi, dan Geofisika (BMKG) |
| 06:40-06:55 | Sand dust monitoring and forecast in Northeast Asia |
HC
Ms Hua Cong
|
RSMC-ASDG Beijing, China Meteorological Administration (CMA) |
| 06:55-07:10 | Sand dust monitoring and forecast for aviation applications |
HL
Mr Han Lei
|
Civil Aviation Authority of China (CAAC) |
| 07:10-07:20 | Break | - | - |
| 07:20-07:35 | Low visibility monitoring and forecast in the Middle East |
AK
Mr Amer Khalil
|
Qatar Civil Aviation Authority (QCAA) |
| 07:35-07:50 | Nowcasting in its context |
RM
Dr Rajeev Kumar Mehajan
|
Indian Air Force (IAF) |
| 07:50-08:05 | Aviation weather service in India |
VD
Dr V.R. Durai
|
India Meteorological Department (IMD) |
| 08:05-08:20 | Aerodrome nowcasting service in Hong Kong, China |
CL
Ms Christy Leung
|
Hong Kong Observatory (HKO) |
| 08:20-08:50 | Q&A / Discussion |
JL
Mr Jochen Luther
|
World Meteorological Organization (WMO) Secretariat |
| 08:50-09:00 | Closing and Conclusion |
CL
Ms Christy Leung
|
Hong Kong Observatory (HKO) |
Note: For each timeslot, the last 3 minutes are reserved for Q&A.
-->Register Here
We look forward to your active participation!
Q&A from the Webinar
Find responses to questions from the webinar
Why do VAACs not use autonomous drones to support the identification of volcanic activities and direction of volcanic ash?
+In general, VAACs do not have the capability to observe volcanoes directly. It is typically up to the national met service or relevant agency to deploy the drones (if any) for local monitoring. While VAAC Tokyo does not deploy drones, it is an interesting consideration for JMA.
Has there been any discussion on the requirement of SO2 information for the aviation committee within VAACs?
+While the aviation community is also interested in SO2 information, they are currently focused on QVA. IAVW has, since the last meeting, paused the discussion on SO2.
Amonth the methods used in satellite-based detection of volcanic ash clouds - namely thermal infrared channels, brightness temperature difference (TBD) technique, and RGB composite imagery - which method is considered more effective for operational use, and why? ?
+Depending on the situation; if available, RGB composite is able to quite clearly distinguish volcanic ash and meteorological cloud. Infrared channel is useful in the night when the visible channel is not available. Operators should check all channels so as to not miss volcanic ash
How does the evaluation result of volcanic ash distribution from QVA compare to observations?
+Tokyo VAAC compares its QVA forecast samples with the ash mass-loading on past actual events. QVA forecast works quite well in some cases but not always. There are large uncertainties in both QVA parameterization and ash mass-loading obtained from satellite analysis. The VAAC community is also seeking a common verification method for VAA and QVA.
How do you determine the height of a volcanic ash column when there is no height checkpoint?
+Plume height is mainly estimated by the brightness temperature of the cloud. Reports from observations and pilots are also important sources.
What is the update frequency for VAAC when a volcanic eruption occurs?
+At least every 6 hours.
Is there any possibility for non-VAACs to use QVA method, or QVA modelling tools? For example, in analytical use in volcanic research.
+THere are no plans at this stage but some institutes may publish a paper or document on QVA methods. QVA data for actual events are available in a similar way as VAA.
Can the dust model used by RSMC-ASDG Beijing be used for the distribution of radioactive clouds?
+The dust model is trained on dust observations and so, may not be applicable to radioactive clouds.
Can the dust model forecast used by RSMC-ASDG Beijing be used in Central and South Asia?
+Yes, the dust model is transferable to other parts of the world.
Is there a collaboration between Qatar and KSA dust storm center to support the forecasters and aeronautical operations?
+Yes as both are in a similar region in the Middle East and the transboundary nature of sand and dust storms.
How does HKO issue low-level wind shear warnings?
+HKO uses the doppler radar for monitoring wind shear conditions during microbursts and the LIDAR for clear air conditions. When large changes in the headwinds are detected, an automatic alert is issued.
How does HKO deal with wind direction/wind speed/wind gust forecast in terms of nowcasting? It was mentioned that there is work done in using ML for observed wind data using XBoost. In the process, does the nowcasting product output directly provide wind nowcast or do HKO forecasters have to derive it based on dBz movement or optical flow?
+The deep-learning model uses observed data for the nowcasting of westerly sea breezes only, as the prevailing wind condition in Hong Kong is easterly. For changes in prevailing wind conditions, airport operations are affected. Therefore, the nowcasting product is used primarily for the nowcasting of wind changes. The output produces a probability of wind change.