(S.2) Probabilistic forecasts of TC-induced hazards
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1 M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 1 / 30 (S.2) Probabilistic forecasts of TC-induced hazards Marie-Dominique LEROUX, Hubert Quetelard, François Bonnardot Météo-France, La Réunion 5-8 December 2017, Macao, China
2 M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 2 / 30 Talk outline 1 Framework Motive Hits and threats in the SWIO
3 M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 2 / 30 Talk outline 1 Framework Motive Hits and threats in the SWIO 2 Storm surge prediction Storm surge model Statistical approach (storm surge database) Storm surge prediction (range of heights)
4 M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 2 / 30 Talk outline 1 Framework Motive Hits and threats in the SWIO 2 Storm surge prediction Storm surge model Statistical approach (storm surge database) Storm surge prediction (range of heights) 3 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity High-resolution ensemble of wind and pressure elds Probabilistic forecast products
5 Framework Motive M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 3 / 30 Talk outline 1 Framework Motive Hits and threats in the SWIO 2 Storm surge prediction Storm surge model Statistical approach (storm surge database) Storm surge prediction (range of heights) 3 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity High-resolution ensemble of wind and pressure elds Probabilistic forecast products
6 Framework Motive M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 4 / 30 Motive Better predict storm surge hazards A strong recommendation from WMO Executive Council after TC Nargis (May 2008, Burma, Bay of Bengal) Objective: La Réunion RSMC must provide information on storm surge hazards in the SWIO
7 Framework Hits and threats in the SWIO M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 5 / 30 Talk outline 1 Framework Motive Hits and threats in the SWIO 2 Storm surge prediction Storm surge model Statistical approach (storm surge database) Storm surge prediction (range of heights) 3 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity High-resolution ensemble of wind and pressure elds Probabilistic forecast products
8 Framework Hits and threats in the SWIO SWIO 17-yr climatology Coastal hits and threats (TC center within 100 km of the coast) over M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 6 / 30
9 Framework Hits and threats in the SWIO SWIO 17-yr climatology Coastal hits and threats (TC center within 100 km of the coast) over Mozambique is hit once a year M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 6 / 30
10 Framework Hits and threats in the SWIO SWIO 17-yr climatology Coastal hits and threats (TC center within 100 km of the coast) over Mozambique is hit once a year Madagascar is hit (threatened) twice (once) a year M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 6 / 30
11 Framework Hits and threats in the SWIO SWIO 17-yr climatology Coastal hits and threats (TC center within 100 km of the coast) over Mozambique is hit once a year Madagascar is hit (threatened) twice (once) a year Vmax 10 min = 135 kt (Fantala, April 2016, Farquhar atoll) ( M.D. Leroux (LACy) ) IWTCLP-IV 5-8 Dec 2017, Macao 6 / 30
12 Storm surge prediction Storm surge model M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 7 / 30 Talk outline 1 Framework Motive Hits and threats in the SWIO 2 Storm surge prediction Storm surge model Statistical approach (storm surge database) Storm surge prediction (range of heights) 3 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity High-resolution ensemble of wind and pressure elds Probabilistic forecast products
13 Storm surge prediction Storm surge model M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 8 / 30 The model Characteristics Hydrodynamic model based on the Saint-Venant equations (P. Daniel, Météo-France, 1990) forced by 10-m wind and sea-level pressure Total sea level rise = astronomical tide + storm surge + wave setup No inland penetration of surge GEBCO global one arc-minute bathymetric grid
14 Storm surge prediction Storm surge model M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 8 / 30 The model Characteristics Hydrodynamic model based on the Saint-Venant equations (P. Daniel, Météo-France, 1990) forced by 10-m wind and sea-level pressure Total sea level rise = astronomical tide + storm surge + wave setup No inland penetration of surge GEBCO global one arc-minute bathymetric grid Deterministic storm surge forecasting Ocial RSMC forecast - contains implicit errors (motion, intensity, structure) - dicult to accurately quantify the storm surge risk Uncertainty cone based on EPS forecast with 75% probability (Dupont et al., 2011)
15 Storm surge prediction Statistical approach (storm surge database) M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 9 / 30 Talk outline 1 Framework Motive Hits and threats in the SWIO 2 Storm surge prediction Storm surge model Statistical approach (storm surge database) Storm surge prediction (range of heights) 3 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity High-resolution ensemble of wind and pressure elds Probabilistic forecast products
16 Storm surge prediction Statistical approach (storm surge database) M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 10 / 30 2 tools storm surge climatology in SWIO coastal areas (atlas of maximum heights) upstream risk analysis for planning purposes storm surge probabilistic maps in association with an ocial RSMC track forecast forecasting tool (since 2015), eective risk communication
17 Storm surge prediction Statistical approach (storm surge database) M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 10 / 30 2 tools storm surge climatology in SWIO coastal areas (atlas of maximum heights) upstream risk analysis for planning purposes storm surge probabilistic maps in association with an ocial RSMC track forecast forecasting tool (since 2015), eective risk communication Database of simulations Model run over 2 x2 domains centered on 591 coastal and oshore (15 NM) reference locations ( x 8NM). Owing to the model resolution ( x 1.85 km), storm surge heights are available for coastal points.
18 Storm surge prediction Statistical approach (storm surge database) M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 10 / 30 Database of simulations Model run over 2 x2 domains centered on 591 coastal and oshore (15 NM) reference locations ( x 8NM). Owing to the model resolution ( x 1.85 km), storm surge heights are available for coastal points. For a relevant sample of hypothetical storms generated with varying TC parameters:
19 Storm surge prediction Statistical approach (storm surge database) M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 10 / 30 Database of simulations Model run over 2 x2 domains centered on 591 coastal and oshore (15 NM) reference locations ( x 8NM). Owing to the model resolution ( x 1.85 km), storm surge heights are available for coastal points. For a relevant sample of hypothetical storms generated with varying TC parameters: Varying TC parameters storm direction: [20-360], every 20 forward speed: [5-20] kt, every 5 kt intensity V max : [60-130] kt, every 10 kt storm size via CP: -15 hpa, 0, +15 hpa relative to the wind-pressure relationship (Atkinson and Holliday, 1977) RMW: [5-25] NM, every 5 NM
20 Storm surge prediction Statistical approach (storm surge database) M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 11 / 30 Example (Mauritius)
21 Storm surge prediction Storm surge prediction (range of heights) M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 12 / 30 Talk outline 1 Framework Motive Hits and threats in the SWIO 2 Storm surge prediction Storm surge model Statistical approach (storm surge database) Storm surge prediction (range of heights) 3 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity High-resolution ensemble of wind and pressure elds Probabilistic forecast products
22 Storm surge prediction Storm surge prediction (range of heights) M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 13 / 30 Surge prediction Possibilities run the model on the latest RSMC ocial track forecast (or on archived TCs): one deterministic scenario run the model for reference locations within the uncertainty cone (to account for the track dispersion) Example (TC Bejisa, 2014) Vmax = 80 kt Max surge height 51 cm
23 Storm surge prediction Storm surge prediction (range of heights) M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 14 / 30 Surge prediction with uncertainty communication Possibilities run the model on the latest RSMC ocial track forecast (or on archived TCs) run the model for reference locations within the uncertainty cone (to account for the track dispersion) run the model with a range of values (RMW, V max, CP, motion speed and direction) around the ocial forecast (to account for the intensity and structure uncertainties) Will give the possible maximum surge heights expected on the coastal points of the impacted domain
24 Storm surge prediction Storm surge prediction (range of heights) M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 15 / 30 Example (TC Bejisa, 2014) V max increases (60 80 kt ) Max surge height increases (29 51 cm
25 Storm surge prediction Storm surge prediction (range of heights) M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 15 / 30 Example (TC Bejisa, 2014) V max increases (60 80 kt ) Max surge height increases (29 51 cm Max surge height 64 cm Vmax[60 80] kt, CP [-15;0;+15] hpa, RMW [10-20] NM HDG [ ], SPD [5-10] kt
26 Storm surge prediction Storm surge prediction (range of heights) M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 16 / 30 Possibilities run the model on the latest RSMC ocial track forecast (or on archived TCs) run the model for reference locations within the uncertainty cone (to account for the track dispersion) run the model with a range of values (RMW, V max, CP, motion speed and direction) around the ocial forecast (to account for the intensity and structure uncertainties) Better communicate on uncertainties This tool maps the range of possible storm surge heights expected for values around the ocial forecast Can we get probabilistic maps for storm surge risk ( ensemble surge prediction)? Can we determine the risk of a critical threshold or warning level being exceeded?
27 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 17 / 30 Talk outline 1 Framework Motive Hits and threats in the SWIO 2 Storm surge prediction Storm surge model Statistical approach (storm surge database) Storm surge prediction (range of heights) 3 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity High-resolution ensemble of wind and pressure elds Probabilistic forecast products
28 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 18 / 30 Method to build ensemble scenarii (1/4) Around the RSMC ocial forecast (Quetelard et al., 2018) A two-step method: Step 1: Cluster climatological errors Errors between the best track and the ocial RSMC forecast in the sample (826 vectors of AT, CT, V max errors) for each leadtime 0, 12, 24, 30, 42, 60, and 72 h Identify 40 clusters of typical errors using an ascending hierarchical classication Assign a probability to each of the 40 classes (according to the number of sample forecasts that compose it) 40 climatology-built departures from the RSMC forecast (position + V max )
29 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 19 / 30 Method to generate ensemble scenarii (2/4) Example (TC Ethel, 2012) 40 climatology-built probabilistic forecasts, each associated to quantied maximum wind and position departures from the ocial RSMC forecast
30 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 20 / 30 Method to generate ensemble scenarii (3/4) Step 2: Consider the event predictability ECMWF EPS forecast realigned on the RSMC ocial forecast
31 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 21 / 30 Example (TC Ethel, 2012) ECMWF EPS forecast realigned on RSMC ocial forecast
32 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 22 / 30 Method to generate ensemble scenarii (3/4) Step 2: Consider the event predictability ECMWF EPS forecast realigned on the RSMC ocial forecast as in Dupont et al. (2011) Assign each of the 51 EPS members to the nearest climatological class original set of 40 classes some 15 or 30 scenarii Probability of a scenario = that of the climatological class weighted by the number of EPS members that fall into that class
33 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 23 / 30 Example (TC Ethel, 2012) 40 climatology-built forecasts 21 scenarii
34 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 24 / 30 Method to generate ensemble scenarii (4/4) Model evaluation Overall, these hybrid probabilistic forecasts are more skillfull than: Original EPS forecasts EPS forecasts realigned on the RSMC ocial forecast 40 climatology-built forecasts except for cases when the EPS deterministic forecast was better than the RSMC ocial forecast
35 Probabilistic forecasts of TC-induced hazards High-resolution ensemble of wind and pressure elds M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 25 / 30 Talk outline 1 Framework Motive Hits and threats in the SWIO 2 Storm surge prediction Storm surge model Statistical approach (storm surge database) Storm surge prediction (range of heights) 3 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity High-resolution ensemble of wind and pressure elds Probabilistic forecast products
36 Probabilistic forecasts of TC-induced hazards High-resolution ensemble of wind and pressure elds M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 26 / 30 Method For each individual scenario (at each lead time), wind and pressure elds are generated through mesoscale modeling (Meso-NH) forced by ECMWF IFS elds.
37 Probabilistic forecasts of TC-induced hazards High-resolution ensemble of wind and pressure elds M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 26 / 30 Method For each individual scenario (at each lead time), wind and pressure elds are generated through mesoscale modeling (Meso-NH) forced by ECMWF IFS elds. Example (TC Bejisa, 2014)
38 Probabilistic forecasts of TC-induced hazards Probabilistic forecast products M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 27 / 30 Talk outline 1 Framework Motive Hits and threats in the SWIO 2 Storm surge prediction Storm surge model Statistical approach (storm surge database) Storm surge prediction (range of heights) 3 Probabilistic forecasts of TC-induced hazards Ensemble scenarii for TC track and intensity High-resolution ensemble of wind and pressure elds Probabilistic forecast products
39 Probabilistic forecasts of TC-induced hazards Probabilistic forecast products M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 28 / 30 Probabilistic products high resolution ensemble of wind and pressure elds chance of exceeding dierent wind thresholds ensemble storm surge or wave forecasts
40 Probabilistic forecasts of TC-induced hazards Probabilistic forecast products M.D. Leroux (LACy) IWTCLP-IV 5-8 Dec 2017, Macao 29 / 30 Examples of probabilistic forecast products 23 scenarii for TC Dineo (2017) probability of wind exceeding 48 kt in the next 60 hours probability of wind exceeding 48 kt from 00 to 06 UTC probability of wind exceeding 64 kt (TC Bejisa)
41 Bibliography I Atkinson, G. and C. R. Holliday, 1977: Tropical cyclone minimum sea level pressure/maximum sustained wind relationship for the Western North Pacic. Mon. Wea. Rev., 105, Dupont, T., M. Plu, P. Caro, and G. Faure, 2011: Verication of ensemble-based uncertainty circles around tropical cyclone track forecasts. Wea. Forecasting, 26(5), Quetelard, H. M., F. D. Bonnardot, G. D. Jumaux, and M. Bessa, 2018: Probabilistic forecasts of tropical cyclone track and intensity through ensemble techniques. Quart. J. Roy. Meteor. Soc., in preparation.
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