2024/09/07-08 Typhoon Yagi
Heavy precipitation and strong winds in Typhoon Yagi in Vietnam mostly strengthened by human-driven climate change
Press Summary (First Published 2024/09/10
Depressions near Northern Vietnam similar to Typhoon Yagi are up to 18 mm/day (up to 20%) wetter and locally up to 6 km/h (up to 5%) windier in the present than they have been in the past.
We have low confidence in the robustness of our approach given the available climate data, as Typhoon Yagi was a largely unique event in the data record
We mostly ascribe the high precipitation and the strong winds of Typhoon Yagi to human-driven climate change and natural climate variability likely played a modest role (low confidence).
Event Description
Typhoon Yag followed a trajectory from the Philippines through southern China to northern Vietnam from September 1 to 8, 2024, making landfall in northern Vietnam on September 7, 2024. Typhoon Yagi is one of the most powerful typhoons in the region over the past decade with wind gusts exceeding 150 km/h in Hanoi (Vietnam) and 227 km/h in Hainan (China). Typhoon are tropical cyclones and are named this way when they occur in the northwest Pacific Ocean. All tropical cyclones, including typhoons are characterized by a rotating, low-pressure system with strong winds, heavy rain, and thunderstorms. Typhoon Yagi wreaked havoc across the Philippines, China, and Vietnam due to heavy rain and strong winds, leading to severe flooding and landslides, power cuts, and significant agricultural damage, leaving 3 million without electricity and claiming at least 59 people lives and more than 700 injured and missing people. Our analysis focus on September 7 and 8.
The Surface Pressure Anomalies reveal large depression areas up to -10 hPa mainly centered over Vietnam coastal areas. Temperature Anomalies display up to +2°C warmer temperatures over the oceans and up to -2°C cooler temperatures over the continental areas. Precipitation data show larger precipitations up to 150 mm/day over a large area of the domain analyzed. Windspeed Data indicate strong winds (50-100 km/h) over the coastal area of Vietnam.
We remind you that our analysis is based on MSWX data. This product does integrate some station observations, notably for rainfall data, but the values it provides and that we report here can nonetheless be different from those observed at single weather stations.
Climate and Data Background for the Analysis
The IPCC AR6 WGI’s Summary for Policymakers states that “it is likely that the global proportion of major (Category 3–5) tropical cyclone occurrence has increased over the last four decades [...]; these changes cannot be explained by internal variability alone (medium confidence). [...]. Event attribution studies and physical understanding indicate that human-induced climate change increases heavy precipitation associated with tropical cyclones (high confidence), but data limitations inhibit clear detection of past trends on the global scale.” (A.3.4)
Our analysis approach rests on looking for weather situations similar to those of the event of interest having been observed in the past. For this event, we have low confidence in the robustness of our approach given the available climate data, as the event is largely unique in the data record. Moreover, the analogues approach does not guarantee that the identified past events do actually correspond to tropical cyclones.
ClimaMeter Analysis
We analyze here (see Methodology for more details) how events similar to Typhoon Yagi in September 2024 changed in the present (2002–2023) compared to what they would have looked like if they had occurred in the past (1979–2001) in the region [104°E 110°E 18°N 24°N]. The Surface Pressure Changes show a modest (<1 hPa) deepening over northern Vietnam. Temperature Changes see an increase up to +1°C in the area near the landfall. Precipitation Changes show a large increase up to 18 mm/day (up to 20%). Windspeed Changes also display up to 6 km/h (+5% increase) windier in limited areas far from the cyclone. We find an increase of similar depressions in August and a decrease in September and October, compared to the past period. Considering the affected urban areas, only Mon Cai is significantly wetter in the present than in the past with an increase of precipitation up to 20 mm/day (25%). Finally, we find that sources of natural climate variability, notably the Atlantic Multidecadal Oscillation, may have only partly influenced the event. This means that the changes we see in the event compared to the past may be mostly due to human driven climate change
Conclusion
Based on the above, we conclude (with low confidence) that depressions near Vietnam, similar to Typhoon Yagi, have become up to 18 mm/day (up to 20%) wetter and up to 6 km/h (up to 5%) windier in the present than they have been in the past. We interpret Typhoon Yagi as a largely unique event for which natural climate variability played a minor role.
Quotes & Contact Authors
- Carmen Alvarez-Castro, UPO, Spain 📨 mcalvcas@upo.es 🗣️Spanish, English, Italian, French
- Stella Bourdin, University of Oxford, UK stella.bourdin@physics.ox.ac.uk French, English
-Davide Faranda, IPSL-CNRS, France 📨davide.faranda@lsce.ipsl.fr 🗣️French, Italian, English
Additional Information : Complete Output of the Analysis
NB1: The following output is specifically intended for scientists and contain details that are fully understandable only by reading the methodology described in Faranda, D., Bourdin, S., Ginesta, M., Krouma, M., Noyelle, R., Pons, F., Yiou, P., and Messori, G.: A climate-change attribution retrospective of some impactful weather extremes of 2021, Weather Clim. Dynam., 3, 1311–1340, https://doi.org/10.5194/wcd-3-1311-2022, 2022.
NB2: Colorscales may vary from the ClimaMeter figure presented above.
The figure shows the average of surface pressure anomaly (msl) (a), average 2-meter temperatures anomalies (t2m) (e), cumulated total precipitation (tp) (i), and average wind-speed (wspd) in the period of the event. Average of the surface pressure analogs found in the counterfactual [1979-2000] (b) and factual periods [2001-2022] (c), along with corresponding 2-meter temperatures (f, g), cumulated precipitation (j, k), and wind speed (n, o). Changes between present and past analogues are presented for surface pressure ∆slp (d), 2 meter temperatures ∆t2m (h), total precipitation ∆tp (i), and windspeed ∆wspd (p): color-filled areas indicate significant anomalies with respect to the bootstrap procedure. Violin plots for past (blue) and present (orange) periods for Quality Q analogs (q), Predictability Index D (r), Persistence Index Θ (s), and distribution of analogs in each month (t). Violin plots for past (blue) and present (orange) periods for ENSO (u), AMO (v) and PDO (w). Number of the Analogues occurring in each subperiod (blue) and linear trend (black). Values for the peak day of the extreme event are marked by a blue dot. Horizontal bars in panels (q,r,s,u,v,w) correspond to the mean (black) and median (red) of the distributions.