WORKSHOP : (20 Minutes)
WORKSHOP : (20 Minutes)
©Himawari
Goal:
Provide an overview of satellite imagery, cloud formation, and how satellite data can be interpreted to assess cloud growth and precipitation potential.
Overview:
Satellites like Himawari 9 provide real-time data on cloud patterns, temperature, and moisture in the atmosphere.
We will focus on how satellite imagery can help meteorologists understand cloud development and predict precipitation.
Why It Matters?
Meteorologists use cloud imagery to forecast weather, track storms, and issue warnings.
Understanding cloud growth and precipitation potential is critical for weather prediction, aviation, and agriculture (use in cloud seeding).
What is the RAMMB Slider?
Developed by the Regional and Mesoscale Meteorology Branch (RAMMB) of NOAA.
A web-based visualization tool that provides animated satellite imagery from satellites like Himawari-9 (East Asia-Pacific region).
Useful for meteorologists, cloud seeding teams, and researchers for tracking storms, cloud growth, and rainfall potential.
☁️ Cloud Identification
Infrared bands (e.g., Band 13) show cloud-top temperature:
→ Colder = taller clouds = more likely to rain after seeding.
🌧️ Precipitation Clues
Infrared channels (IR) help estimate cloud-top temperatures.
Spot rapid vertical growth = possible convective (rain-producing) clouds.
🎯 Timing the Seeding
Useful for targeting and timing flights by observing cloud maturity stages.
🛰️ Supplement to Ground Observations & Radar
Complements AWS, radar, and visual ground-based observations.
Live Demo: How to Use RAMMB Slider
Demo for Band 3 Visible:
> Go to RAMMB Slider website
> Select Himawari-9 → Area: Full Disk or Southeast Asia/Philippines
> Choose Band 3 Visible for daytime, for cloud texture.
> Select animation range (e.g., 1–3 hours) and press Play
> Highlight a cloud cluster and move slider bar to show cloud development.
📌 Observe:
How the cloud evolves (vertical growth = good seeding target).
Movement direction – helpful in targeting watersheds/dam areas.
Demo for Band 13 Infrared:
> Go to RAMMB Slider website
> Select Himawari-9 → Area: Full Disk or Southeast Asia/Philippines
> Choose Band 13 Infrared for cloud-top temperature.
> Select animation range (e.g., 1–3 hours) and press Play
> Highlight a cloud cluster and move slider bar to show cloud development.
📌 Observe:
Point out a growing cloud mass – show how it cools over time in animation
Highlight movement direction (for targeting seeding area)
Emphasize rapid cooling = strong updraft = good cloud growth
> Go to RAMMB Slider website
> Select Himawari-9 → Area: Full Disk or Southeast Asia/Philippines
> Choose Day Cloud Phase Distinction for daytime, for cloud texture.
> Select animation range (e.g., 1–3 hours) and press Play
> Highlight a cloud cluster and move slider bar to show cloud development.
🌥️ What is Day Cloud Phase Distinction?
A composite RGB product (Red-Green-Blue) from Himawari-9 that helps distinguish:
✅ Cloud type
✅ Phase (water or ice)
✅ Cloud top height
Especially valuable during daylight hours only (uses visible and near-IR bands).
🎯 Why It Matters for Cloud Seeding Monitoring
Helps identify mature cumulus clouds that are starting to glaciate (turn into ice)—
👉 a prime target for warm or cold cloud seeding.
Glaciating clouds suggest vertical development and freezing-level proximity.
🖌️ Interpreting the Colors (Simplified):
Color Meaning Implication for Cloud Seeding
Bright Green Thick water clouds Growing cumulus (good candidate)
Yellowish-Green Glaciating clouds Excellent for cold seeding
Orange/Brown Ice clouds / Anvils Already mature or decaying
White Tall, cold clouds May already be precipitating
Reference Material: Day Cloud Phase Distinction
Key Takeaways for Cloud Seeding Operations
✅ Use the RAMMB Slider to identify potential seedable clouds.
✅ Watch for rapid cloud growth and cold tops.
✅ Support real-time flight decisions, validate seeding impact via post-event analysis.
✅ Best used in combination with radar, AWS, and pilot reports.
References: https://rammb2.cira.colostate.edu/training/visit/quick_reference/