#UwanPH vs. #YolandaPH: PAGASA explains key differences as typhoon nears Philippines
For more details, please visit https://tribune.net.ph/2025/11/08/uwanph-vs-yolandaph-pagasa-explains-key-differences-as-typhoon-nears-philippines

Today is the 11th anniversary of Typhoon #YolandaPH / #Haiyan devastating the #Philippines 🇵🇭 in 2013 and resulting in over 6,300 lives lost. Eleven years on, Yolanda is still the deadliest typhoon during the 21st century.

To mark this date, I am reposting this Day 18 map (Atmosphere) I did for last year’s #30DayMapChallenge.

https://en.osm.town/@seav/111450294923334516

#TropicalCyclones #typhoons #ExtremeWeather

Eugene Alvin Villar 🇵🇭 (@[email protected])

Attached: 1 image #30DayMapChallenge 🗺️ Day 1️⃣8️⃣: Atmosphere (Took a break to recharge and I’m back and will catch up with the challenge!) I haven’t done any animated map yet, so I figured why not do one now? 😅 This map shows the progression of Public Storm Warning Signals that #PAGASA, the #Philippines’ 🇵🇭 weather bureau, raised over the country as 2013’s #TyphoonYolanda 🌀, also known as #Haiyan, passed through. Additionally the typhoon’s path according to PAGASA and the U.S. JTWC is depicted. #typhoons 1/2

OSM Town | Mapstodon for OpenStreetMap

It seems they never interpolated the storm tracks resulting in these weird strings of circles and arcs? And what’s up with the lack of data in the south? While #TropicalCyclones typically don’t form near nor approach the equator, the hard cutoff at around the 6.6°N latitude is an interesting choice.

Anyway, I can spot 2012’s Typhoon #Bopha / #PabloPH in #Mindanao and 2013’s Typhoon #Haiyan / #YolandaPH in the #Visayas, which tells me that they did use historical data.

🧵 2/3

#Philippines

Just like the 1,444 dedicated mappers in November 2013 who diligently mapped before and after typhoon #YolandaPH (aka #HaiyanPH) struck the country, a recent series of strong typhoons also led to more mappers adding data to the map.