# Presentation: 899055

## A Modeling Study on Typhoon Nari (2001): Landfall Characteristics 

*Ming-Jen Yang**1,2**,* *Hsiao-Ling Huang**1*, *Da-Lin Zhang**2*
*1**National Central University, Taiwan*
*2**University of Maryland, USA*

## Heavy rainfalls induced severe flooding and societal damage !

**Heavy rainfalls induced severe flooding and societal damage !**

- Water World !

- Even Budda cannot save you!

## Why studied Typhoon Nari (2001)?

- Unique track
- Slowly moving
- Long duration
- Warm ocean
- Heavy rainfall
- Severe flooding

**Sui et al. (2002) EOS article**

## Part I: Model Verification 

**Part II: Terrain Sensitivity**
**Part III: Coupling with Runoff Model**

**Content:**

## Part I: Model Verification 

## D1: 54 km
D2: 18 km
D3: 6 km
D4: 2 km

- D2: 18 km
- D3: 6 km
- D4: 2 km

-   MM5
- Domains

- 31 levels
- In vertical

## MM5 model physics (Control)

| Grid Size | 54, 18, 6, 2 km |
| --- | --- |
|   Fcst Period | 84 h |
| Cumulus |  Grell (1993) |
| Microphysics | Reisner et al. (1998) |
| PBL | MRF (Hong and Pan 1996) |
| Radiation | Dudhia (1989) |
| I.C. | ECMWF advanced analysis
(2001/09/15 1200 UTC) |
| B.C. | ECMWF advanced analysis |

- TC initialization: Davis and Low-Nam (2001)

## Track Comparison

| Simulation time (h) | 12 | 24 | 36 | 48  | 60 | 72 | 84 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Track error (km) | 43.3 | 61.2 | 26.8 | 13.4 | 12.0 | 8.5 | 104.8 |

## Time Series of SLP and Vmax

## 24-h rainfall on 09/16 

**6km MM5**

**24-h rainfall on 09/16**** **

**OBS **

## 24-h rainfall on 09/17 

**OBS **

**2km MM5**

**6km MM5**

## 24-h rainfall on 09/18 

**OBS **

**2km MM5**

**6km MM5**

## 3-day rainfall on 09/16~09/18 

**OBS **

**2km MM5**

**6km MM5**

## Relative Percentage of 3-Day Rainfall

- MM5 overforecasts weak TC rainfall (<550mm/3day)
-  but underestimates heavy TC rainfall (>550mm/3day)

- As resolution increases, the simulated rainfall
-   spectrum approached the observed

## Average Rainfall on Taiwan

| Item | N | 09/16 | 09/17 | 09/18 | 3-Day Total |
| --- | --- | --- | --- | --- | --- |
| OBS (in mm) | 325 | 132 | 206 | 97 | 435 |
| 6km MM5 | 1073 | 159 | 104 | 75 | 348 |
| 2km MM5 | 9602 | 175 | 133 | 84 | 383 |

| MM5/OBS | 09/16 | 09/17 | 09/18 | 3-Day Total |
| --- | --- | --- | --- | --- |
| 6km MM5 | 121 %  | 51 %  | 78 %   | 80 %  |
| 2km MM5 | 133 % | 65 %  | 87 %  | 88 %  |

**Percentage wrt Rain Gauge OBS**

## 3-Day Total Rainfall versus Terrain Height

**3-Day Total Rainfall versus Terrain Height**

- Rain
- Gauge
- OBS

- 2km
- MM5

-   vortex
- circulation

- topographic
- precipitation

## Cloud  Features

**CTL: 0916_0000 UTC**

- Isosurface of Snow (0.01 g/kg)
- and Cloud Water (0.3 g/kg)

**Cloud  Features**

## Radar CV Composite Before Landfall 

**OBS**

**MM5**

## Radar CV Composite After Landfall 

**OBS**

**MM5**

## Sounding Comparison(within Eyewall)

**Observed Sounding**

**MM5 Simulation**

## Horizontal Cross Section ofPressure Perturbations

- 0916_1400 UTC

**Horizontal Cross Section of****Pressure Perturbations**

**Radar Retrieval (wrt. a****Station Sounding)**

**MM5 Simulation (wrt. a****Horizontal Area Mean)**

- Courtesy of T.-C. Chen and Y.-C. Liou

**5  ~ 6 hPa**

**8  ~ 9 hPa**

## TRMM Rainrate Comparison 

**MM5: 0915/2100 UTC (6 km grid)**

- TRMM Rainrate Comparison

- Courtesy of W.-J. Chen

## Radial Wind wrt RCWF Radar 

**Obs Vr (6 km pixel)**

**MM5 Vr (dx = 6 km)**

**Radial Wind wrt RCWF Radar **
**@ 3 km Height**

- Courtesy of T.-C. Chen and Y.-C. Liou

**-41.9**

**41.4**

**-45.1**

**43.6**

## MM5 Simulated Vr & Vt

**Tangential Velocity**

**Radial Velocity**

**MM5 Simulated Vr & Vt**
**Nari at Sea (@ 3 km Height)**

- 1-h time-averaged result

## MM5 Simulated Vr & Vt

**Tangential Velocity**

**Radial Velocity**

**MM5 Simulated Vr & Vt**
**Nari Landfall (@ 3 km Height)**

- 1-h time-averaged result

## Over Ocean

- Radar Echo (color)
- Condensational
- Heating (contour)

**Over Ocean**

**After Landfall**

**A**

**B**

- 1-h averaged result

## Over Ocean

- Radar Echo (gray)
- Tangential
- Wind (contour)

**Over Ocean**

**After Landfall**

**A**

**B**

- 1-h averaged result

## Over Ocean

- Radar Echo (gray)
- Radial Wind (contour)

**Over Ocean**

**After Landfall**

**A**

**B**

- 1-h averaged result

## Horizontal Cross Section

- of low-level wind vector

- Vertical Cross Session
- of Vertical Velocity

- Gravity waves in squall lines (Yang and Houze 1995)

## Summary

- ■ After detailed comparisons, the MM5 simulated these features of Typhoon Nari reasonably well: the storm track, the landfalling location, the intensity change and shrinking of eyewall during landfall process, pressure gradient near the inner core, and many observed precipitation and kinematic structures
- ■ Taiwan’s topography enhanced asymmetry on the kinematic structure with higher wave-number variations on the radail wind during the landfall process.
- ■ After landfall, the vertical axis of eyewall and tangential wind tilted toward the terrain, with maximum heating located along the mountain slope.
- ■ Two significant rainfall regimes are found: one with storm’s vortex circulation, and the other with topographic precipitation.

## Part II: Terrain Experiments 

## Terrain Sensitivity Experiments

| Experiment | Description |
| --- | --- |
| 75%Ter |  75% of Taiwan terrain |
| 50%Ter | 50% of Taiwan terrain |
| 25%Ter | 25% of Taiwan terrain |
| NoTer | Flat land on Taiwan |

## 75% Terrain

**50% Terrain**

**25% Terrain**

**No Terrain**

## 75% Terrain

**75% Terrain**

**50% Terrain**

**25% Terrain**

**100% Terrain**

**No Terrain**

**24-h Rainfall**
**On 09/16**

**777**

**928**

**798**

**620**

**861**

## Time series of SLP and Vmax

## Summary

- ■ The terrain impact on Nari’s intensity is quite linear, i.e., higher terrain producing a weaker typhoon.
- ■ However, terrain effects on Nari’s track and the accumulated rainfall on Taiwan are nonlinear.
- ■ Nari’s tracks near Taiwan result from the complicated interactions between the steering flow, Taiwan topography, and terrain-induced mesoscale forcings

## Part III: River Runoff Simulation

**     ****(Coupling MM5 with FLO-2D) **

- In Cooperation with Ming-Hsu Li

- Ref: Li, M.-H.,** **M.-J. Yang, R. Soong, and H.-L. Huang**,** 2005:** **Simulating typhoon
- floods with gauge data and mesoscale modeled rainfall in a mountainous watershed.
*J. Hydrometeor*., **6**, 306–323.

## Shihmen Basin

## DTM of Shihmen Watershed

**DTM of Shihmen Watershed**

##           Ie= rainfall (Ps) excess over infiltration,

**in the FLO-2D runoff model are: **

- where h = river depth
-           Ie= rainfall (Ps) excess over infiltration,
-           Vx, Vy = the depth-averaged velocity in x- and y-dir.,
-           Sox, Soy = the bed-slope components in x- and y-dir.,
-           Sfx, Sfy = the friction-slope components in x- and y-dir.

## Rainfall Comparison(Basin Average)

## Flow Discharge Comparison(Basin Average)

## Gauge Rainfall 

**Gauge Rainfall **

**MM5 Rainfall**

**Simulated River Depths**
**  ****by MM5 Rainfall**

## Summary

- ■ The one-way coupling of MM5 with the FLO-2D runoff model is established and verified for Typhoon Nari (2001).
- ■ The MM5-predicted basin-averaged rainfalls are compared with those by rain gauge data.  This comparisons in rainfall peak amounts and time lags are used to investigate the effect of rainfall forecast error on runoff prediction.
- ■ The error of flood prediction with the MM5 rainfall is mainly caused by the rainfall peak and timing differences, as a result of inherent uncertainties in the simulated rainfalls over a mountainous watershed during typhoon landfall periods.

## Thank You !