The Assessment of Typhoon Hazards at Regional-Scales in the Pacific Regions with Downscaling Numerical Experiments Tetsuya Takemi Fourth Capacity Building Workshop of the WMO/IOC Data Buoy Cooperation Panel (DBCP) for the North Pacific Ocean and Its Marginal Seas (NPOMS-4) Korea Maritime and Ocean University, Busan, Korea, 2-4 November Disaster Prevention Research Institute, Kyoto University

Motivation Tropical cyclones are one of the major meteorological hazards, and sometimes cause devastating damages especially in developing countries which are vulnerable to such hazards; e.g., Cyclone Sidr (2007), Cyclone Nargis (2008), Typhoon Haiyan (2013), and Cyclone Pam (2015). Quantitative estimation of the impacts on natural disasters is important for the purpose of disaster prevention and mitigation. Assessment of such impacts under global warming is also important for future disaster management. Typhoon Haiyan (2013) and Cyclone Pam (2015) are two of the Category-5 storms in the Pacific regions in recent years.

Worst-case scenario for hazard assessment Past extreme events can be regarded as a baseline for designing measures and planning on disaster prevention and mitigation at a regional level. Tropical cyclones are one of the major meteorological hazards in the Pacific regions. Assessment of the impacts due to extreme tropical cyclones is critically important for setting disaster prevention and mitigation measures. The impact assessments due to extreme tropical cyclones can be performed through considering worst-case scenarios.

Natural hazard by strongest tropical cyclones Challenge: – “Is the maximum intensity of 900 hPa or below quantitatively simulated by a regional meteorological model?” – “Is the storm surge quantitatively reproduced with the use of the meteorological model outputs?” †Investigate how the quantitative representations of Typhoon Haiyan (2013) and Cyclone Pam (2013) in regional meteorological simulations impact the assessment of the resulting hazards

What are added values in high-res downscaling? Convective processes are sufficiently resolved. (Some part of) turbulent processes are explicitly resolved. Detailed terrain features are closely captured.

Super Typhoon Haiyan (2013) (From Digital Typhoon) Track Central pressure Maximum intensity Central pressure: 895 hPa Max wind speed: 65 m/s (best track)

Model and experimental settings Model: WRF/ARW Version Initial and boundary conditions: – Atmosphere: NCEP Final Analysis (FNL) – SST: NCEP FNL or JMA MGDSST Domain & resolution: 3 km/1 km – Domain 1 (3 km): 4000 km x 2000 km – Domain 2 (1 km): 2000 km x 700 km, and etc. – Vertical levels: 56 – Model top: 20 hPa Simulation period: – 0000 UTC 5 Nov – 0000 UTC 10 Nov 2013

Simulation of storm surge in Leyte Gulf (m) Maximum water surface elevation with the use of the WRF outputs Circle points indicate the measurements. Mori, N., M. Kato, S. Kim, H. Mase, Y. Shibutani, T. Takemi, K. Tsuboki, and T. Yasuda (2014), Local amplification of storm surge by Super Typhoon Haiyan in Leyte Gulf, Geophys. Res. Lett., 41,

Effects of climate change on worst storm surge Takayabu, I., K. Hibino, H. Sasaki, H. Shiogama, N. Mori, Y. Shibutani, T. Takemi, 2015: Climate change effects on the worst-case storm surge: a case study of Typhoon Haiyan. Env. Res. Lett., 10,

Intensity of tropical cyclones Natural conditions (w/o warming) Present climate (w/ global warming) Takayabu, I., et al. 2015, Env. Res. Lett., 10, Minimum central pressure Maximum wind speed

Storm surge Increase the water level by 10—20 % due to global warming for the worst-case storm surge from a Haiyan-class typhoon Takayabu, I., et al. 2015, Env. Res. Lett., 10, Present climate (w/ global warming) Natural conditions (w/o warming)

Cyclone Pam in March 2015 (Kochi University, Weather Information; (Digital Typhoon; Cyclone Pam Typhoon Bavi

Model and experimental settings Model: WRF/ARW Version Initial and boundary conditions: NCEP Final Analysis (FNL) Simulation period: 0000 UTC 3 Mar – 0000 UTC 15 Mar 2015 Domain 1 Area horizontal grid Domain 2 Area horizontal grid Spectral nudging Cumulus param CASE km x 3600 km 3 km NoneD1On (D1) CASE km x 4500 km 9 km 3000 km x 3000 km 3 km D1On (D1) CASE km x 4500 km 9 km 3000 km x 3000 km 3 km D1Off CASE km x 4500 km 6 km 2500 km x 3000 km 2 km D1Off CASE km x 4500 km 6 km 2500 km x 3000 km 2 km D1, D2Off

Track and intensity of simulated Pam Track Intensity

Issues in typhoon hazard assessment The temporal and spatial changes of severe rain and wind by typhoons critically depend on the intensity, track, and translation speed of typhoons. Therefore, accurate representation of such typhoon features is required for assessing the impacts on natural hazards at regional scales. Past disaster-spawning case(s) can be regarded as a worst- case scenario for a specific region and provide insightful guidance/planning on the prevention and mitigation of natural disasters. Effects of global warming on typhoon hazards can be quantified through adding climate changes on a worst-case typhoon: Pseudo-global warming experiment.

Typhoon Vera (1959): “Isewan Typhoon” Downscaling experiments with the WRF model – Initial and boundary conditions: JRA-55 Typhoon Vera (1959) “Isewan Typhoon”: September 1959 – Minimum central pressure: 895 hPa – Storm surge/high waves in the Ise Bay – River discharge in the Yodo River basin – The highest resolution of the nested domains: 1km Assessing the impacts of global warming – Pseudo-global warming (PGW) experiments †Climate change deficit between future and present climate simulated by MRI-AGCM

JRA55 JRA55+PGW Domain 1 5-km grid Domain 2 1-km grid Isewan Typhoon September 1959 Future September: PGW Initial time1959Future MCP (hPa) / / / / / MWS (m/s) / / / / / (Mori and Takemi 2015)

Summary Accurate representation of the intensity, track, and translation speed of typhoons in downscaling experiments is desirable for quantitative assessments of impacts on natural hazards at regional-scales. Past extreme cases provide basic guidance for disaster prevention and mitigation not only under the current climate condition but also under global warming through considering a worst-case scenario among various levels of natural hazards and risks. Close collaboration between meteorologist and users (engineers, national/local government officials, operational sectors, etc.) is important for impact assessment studies.