High Resolution Ensemble Prediction of Typhoon Morakot (2009) May 11, 2011

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1 High Resolution Ensemble Prediction of Typhoon Morakot (2009) Ying-Hwa Kuo 1,* and Xingqin Fang 1,2 1 National Center for Atmospheric Research, Boulder, Colorado, USA 2 Department of Atmospheric Sciences, School of Environmental Sciences and Engineering, Sun Yat-Sen University, Guangzhou, China May 11, 2011

2 Observed Rainfall of Typhoon Morakot (2009) From August 6 to 10, 2009, extraordinary rainfall was brought over Taiwan by Typhoon Morakot, breaking 50 year s precipitation record, causing a loss of more than 700 people and estimated property damage exceeding US$3.3 billion * Objective analysis ~450 automatic stations Accumulated rainfall: (a) 96-h on August 6-10 (b) 24-h on August 8-9 Typhoon Morakot (2009) Max. 24-h gauge 1504 mm Max. 96-h gauge 2874mm at Chiayi County (windward slope of CMR) 24-h rain world record 1825 mm

225º ) Two sets of ensemble simulations with and without Taiwan topography: EN0600 (m1-32) and NTEN0600 (m1-32), ICBC perturbation by WRF 3DVAR 144h simulation

3 Data and Methodology --- Experiment Design Taiwan topography is removed for sensitive experiment, but its land surface features still retained. Two deterministic simulations with and without Taiwan topography: ec0600 and ecnt0600, ICBC from ECMWF high resolution analysis (0.225º 0.225º ) Two sets of ensemble simulations with and without Taiwan topography: EN0600 (m1-32) and NTEN0600 (m1-32), ICBC perturbation by WRF 3DVAR 144h simulation started from 0000UTC 6 to 0000 UTC 12 Aug Domains: 2-way 36-km ( ), 12-km ( ) and 4-km ( ) 36 levels to the top of 20 hpa ARW WRF physics: WSM5, YSU, Noah, RRTM, Goddard, BMJ (all)

Question: What is the role of Taiwan topography in this extreme rainfall event?

amplifies the local rainfall extremes in the spatial distribution of rainfall, it plays a key role in making

With Taiwan topography Intensive rainfall areas (>800 mm) well captured Extremes (>2500 mm) captured, with

4 Question: What is the role of Taiwan topography in this extreme rainfall event? Taiwan topography enhances and focuses the rainfall along the windward side of the mountain and thus greatly amplifies the local rainfall extremes in the spatial distribution of rainfall, it plays a key role in making Typhoon Morakot a record-breaking rainfall event. With Taiwan topography Intensive rainfall areas (>800 mm) well captured Extremes (>2500 mm) captured, with displacements Peak 3128 mm Without Taiwan topography Even rainfall distribution No obvious local rainfall enhancement Peak 616 mm, less than 20% 96-h Rain EN0600 mean OBS 96-h Rain NTEN0600 mean

5 3-h rainfall rate from ensemble system with and without topography 3-h OAR is positive during the entire simulation 3-h OAR is up to about 25 mm after landfall 96-h OAR is 382 mm * OAR: Orographically Additive Rainfall OAR= EN0600_mean - NTEN0600_mean OAR landfall left Taiwan

The variability of the storm track and intensity The simulated track of ensemble members (green line), the single deterministic simulation (blue line), and the average track of

6 The variability of the storm track and intensity The simulated track of ensemble members (green line), the single deterministic simulation (blue line), and the average track of the ensembles (red line) of EN0600 (top) and NTEN060 (bottom). The JMA best track (modified by analysis from Taiwan Central Weather Bureau) is superimposed by thick black line as OBS.

7 a. The rainfall probability forecast (a) D2 (b) D2 (c) D3 (d) D3 500 mm 1000 mm 500 mm 1000 mm D2 00/7-00/8 D3 00/8-00/9 (e) 2Ds 1000 mm (f) 2Ds 1500 mm (g) 4Ds 1500 mm (h) 4Ds 2500 mm 2Ds 00/7-00/9 4Ds 00/6-00/10 The rainfall probability distribution (%) exceeding the thresholds of (a) 500, (b) 1000 mm for 24-h rainfall ending at 0000 UTC 8 August; (c) 500, (d) 1000 mm for 24-h rainfall ending at 0000 UTC 9 August; (e) 1000, (f) 1500 mm for 48-h rainfall ending at 0000 UTC 9 August; (g) 1500, (h) 2500 mm for 96-h rainfall ending at 0000 UTC 10 August estimated from the 32 members of EN0600. The observed rainfall at the corresponding threshold is superimposed by the blue line.

Data and Methodology --- Experiment Design Six sets of ensemble experiments with different CU settings in the 3 2- way domains, 36-km (280 172), 12-km

perturbed from ECMWF high resolution analysis (0.225º 0.225º ) by WRF 3DVAR 96h simulation started from 0000UTC 6 to 0000 UTC 10 Aug.

8 Data and Methodology --- Experiment Design Six sets of ensemble experiments with different CU settings in the 3 2- way domains, 36-km ( ), 12-km ( ) and 4-km ( ): CU_01 BBB CU_03 BBE CU_05 BEE CU_07 KKK CU_09 KKE CU_11 KEE Each ensemble set has the same 8-member ensemble ICBC: perturbed from ECMWF high resolution analysis (0.225º 0.225º ) by WRF 3DVAR 96h simulation started from 0000UTC 6 to 0000 UTC 10 Aug levels to the top of 20 hpa ARW WRF physics: WSM5, YSU, Noah, RRTM, Goddard Taiwan topography is removed for sensitive experiment, but its land surface features still retained.

9 Ensemble average track Single deterministic simualtion track With Terrain EC No Terrain FNL 01 BBB 03 BBE 05 BEE 07 KKK 09 KKE 11 KEE 13 NC

10 SLP IC FNL_36km IC EC_12km 500 hpa Z

11 Summary Simulations with BMJ scheme on 36-km and 12-km all have westward and southward track bias. Simulations with Kain-Fritsch scheme do not have such bias Without topography, the storm tracks tend to shift northward: Without CMR, southwesterly monsoon flow can push the storm track further north

12 Ensemble mean 96-h rainfall 00/6-00/10 OBS

13 Four-day accumulated ensemble mean rainfall from the various cumulus parameterization experiments BBB KKK BBE KKE BEE KEE ALL OBS

14 2d-cape and 850 hpa wind vector (M4_BBB, M4_BBE, and M4_BEE) M4_BBB 2d-cape and 850 hpa wind vector (M4_KKK, M4_KKE, and M4_KEE) M4_KKK M4_BBE M4_KKE M4_BEE M4_KEE

CU sensitivity: BBE(&BBB) and BEE differ much KKE(&KKK) and KEE do not differ much BEE and KEE do not differ much BBE(CU_03) and BEE(CU_05) KKE(CU_09) and KEE(CU_11) Implication: --- Using BMJ on

15 CU sensitivity: BBE(&BBB) and BEE differ much KKE(&KKK) and KEE do not differ much BEE and KEE do not differ much BBE(CU_03) and BEE(CU_05) KKE(CU_09) and KEE(CU_11) Implication: --- Using BMJ on 12 km resolution may have important impacts on low level and high level flow patterns; KF does not have these impacts. --- If CU is used only on 36 km resolution, the tracks are not sensitive to CU.

16 Diagnostics on CU sensitivity --- M4 with BBE and BEE M4_BBE and M4_BEE share similar westbound tracks from 00/6 to 12/7, they separate around 00/8, about 50 km away from Taiwan.

17 650 hpa smoothed absolute vorticity and wind (M4_BBE) 650 hpa smoothed absolute vorticity and wind (M4_BEE) SLP and surface wind (M4_BBE) SLP and surface wind (M4_BEE)

18 Analysis of 53 typhoons that came close to Taiwan, by Wang (1980). Strong Typhoons Weak Typhoons

19 Does the super ensemble perform better than any sub-ensemble? Do you find out any best CU? Track --- Yes Rainfall --- Yes, improve rainfall over Chiayi and southern Taiwan Best CU --- Not sure at this point. Only test two Cu Pa schemes, also only one case

20 Summary Deterministic high-resolution prediction of the extreme rainfall event of Morakot (2009) is exceedingly difficult, as uncertainties in initial conditions and model physics can have significant influence on storm tracks and rainfall prediction. Probability forecast using high-resolution ensemble can provide useful information on extreme rainfall associated with Morakot (2009). The performance of high-resolution ensemble is sensitive to model physics: Use of BMJ scheme on 12-km grid produced a weaker storm track with westward and southward bias; while Kain-Fristch scheme did not. Super ensemble, including both uncertainties in initial conditions and physics, gave superior performance in track forecasts

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