Characteristics of rainfall during tropical cyclone periods in Taiwan

Cheung K. K. W., Huang L.-R., and Lee C.-S.: Characteristics of rainfall during tropical

cyclone periods in Taiwan. Nat. Hazards, 8, 1463–1474, 2008

Introduction

• According to the records of CWB of Taiwan in the period 1961–2004 : 5 TCs affected, nearly 2 made landfall. About 74% of these TCs occurred during Jul – Sep.

• Typhoon Mindulle (2004) that was accompanied by strong Asian summer monsoonal southwesterlies and resulted in large amount of rainfall in the southwest area of Taiwan (Lee et al., 2006).

• To improve the skill of rainfall prediction from the short range (1–12 h) up to 3 days.

• To provide a detailed statistical analysis of the characteristics of TC-related rainfall.

Data• By 1989, the automatic rain gauge

network was completed that made the total number of rain stations to be 371 including several off-coast island stations, and the number keeps increasing in recent years.

• As can be seen in the figure, the rain stations are quite uniformly distributed in the plain area but are less dense in the Central Mountain Range (CMR).

• Data from these 371 rain stations are updated every ten minutes and they are sent automatically through a radio wireless network into the CWB.

•61 TCs during 1989–2002 are considered in this study.•The E-W tracks : 34 TCs, formed in the monsoon trough region east of the Philippines or central North Pacific and then migrated westward.•The S-N tracks : 27 TCs, formed in either the western North Pacific (WNP) or South China Sea (SCS) and then migrated northward.

½ landfall

Tropical cyclone tracks

located at the south or southwest

TC circulation and orographic lifting

located at northeast

TC circulation and orographic lifting

located more to the west

Contour : hourly rain rate 2mm/hr

Spatial characteristics

Temporal characteristicsCluster 4 : TCs approached Taiwan from the east (the E-W members) or from the south (the S-N members that formed in the SCS or Philippines).Cluster 5 : TCs approached Taiwan from the WNP.Cluster 1, 2, 6 : Occur later when the TCs landfalling, then pass through the CMR of Taiwan or northward to higher latitudes.

Monsoon-related rainfall patterns

Mindulle

Doug

Doug (1994), Kai-Tak (2000), Mindulle (2004)

a. The southwesterly flow during the summer monsoon period induced by TC circulation

b. During the autumn the warm, moist TC confronts the cold, dry winter monsoonal flow that produces near frontal rainfall to the area.

Monsoon-related rainfall patterns (continue)

Seth (1994), Zeb (1998), Xangsane (2000)

Climatology-persistence (CLIPER)

• The CLIPER model is a simple weighted combination of TC rainfall climatology and persistence for estimating rainfall in the future.

• CLIPER= α× climatology+(1−α) × persistence

α=1 : climatologyα=0 : persistence

α=0.4 : 0–3-hα=0.7 : 3–6-h

118

27

19

126

Obs.

Typhoon Aere (2004) 12:00UTC 25 August

CLIPER

50%

Obs.

Typhoon Mindulle (2004) 00:00 UTC 2 July

CLIPER

Obs.

Typhoon Longwang (2005) 03:00 UTC 2 Oct

CLIPER

Summary

• Temporal profiles have a particular geographic distribution that should be determined by the different impact directions of the TCs.

• The spatial characteristics of TC rainfall is studied by establishing corresponding rainfall climatology in a grid covering the Taiwan area.

• The average rainfall distribution when a TC center is at a particular position relative to Taiwan can easily be extracted from this climatological database.

Summary (continue)

• The reason for this underestimation is that CLIPER takes no consideration at all of the TC structure and synoptic-scale environmental factors. Therefore, these factors will be taken into account when developing a more generalized statistical TC rainfall model.

• Orographic effect is an important factor that affects TC rainfall.

• The convection structure and rainfall pattern of all TCs approaching the area will be modified by the CMR.

Simulation of the Recent MultidecadalIncrease of Atlantic Hurricane ActivityUsing an 18-km-Grid Regional Model

Knutson, T. R., J. J. Sirutis, S. T. Garner, I. M. Held, and R. E. Tuleya, 2008: Simulation of

the recent multidecadal increase of Atlantic hurricane activity using an 18-km-grid

regional model. Bull. Amer. Meteor. Soc., 88, 1549–1565.

• Statistical analyses : given the limited length of available TC activity data and concerns about the reliability of historical TC data (Landsea et al. 2004; 2005; 2006).

• Typical global climate models : often considered inadequate for simulations Atlantic interannual/interdecadal variability and trends in TC or hurricane activity.

• Global atmospheric model simulations with ~20- to 30-km grid spacing are now feasible on the largest supercomputers available (Oouchi et al. 2006; Bengtsson et al. 2007), and are promising tools for research in this area since models of this resolution appear capable of generating storms of hurricane strength.

?Future

Part of a cycle

Long-term trend

Combination?

New high resolution regional model covering the North Atlantic.

Surrounding tropical Atlantic hurricane variations and trends.

Model1 was used to perform an initial set of 26 seasonal simulations (1980–2005).Discovered a code error

The code error was corrected and the model retuned (yielding Model2), followed by a rerun of all 27 seasons (along with 2006).

ModelE will refer to the ensemble of results obtained from the Model1 and Model2 runs combined.

690 × 300 horizontal grid has a spacing of 1/6° (~18 km) and 45 unevenly spaced vertical levels, with the lowest model level at a height of 22 m.

August–October 1980–2006GPCP

Observations

Model 2

Long-term means and aggregate storm statistics

Too highToo high

937hPa

47 m/s

882 hPa (Wilma in 2005)

85 m/s (Camille in 1969)

Interannual variability and trends in TC activity

El Nino

Unusually active seasons Unusually quiet seasons

La Nina

El Nino

La Nina

El Nino

29 May - 31 December

Active

Inactive

shuts down

Excessive activity

CONCLUSIONS• Simulated 27 Atlantic hurricane seasons (August–October, 1980–20

06) using a new regional nested model, which is forced on the boundaries and nudged on the largest interior spatial scales toward NCEP reanalysis.

• ACE and PDI that agree remarkably well with observed variations, including the trend toward increasing activity over the period 1980–2005 as well as other interannual variations.

• Atlantic tropical storm and hurricane frequency versus ENSO are well captured in the model.

Future work • To use the model to assess the relative roles of dynamical and ther

modynamical factors in the recent increase of Atlantic hurricane activity.

• Also plan to attempt simulations of pre-1980 Atlantic TC activity to see whether the model can reproduce either the reported variations in hurricane activity since the 1950s or the reported century-scale rising trend in Atlantic TC counts.

Thank you!!

accumulated cyclone energy (ACE)

power dissipation index (PDI)

颶風威力耗散指數： PDI 與近地面最大風速的三次方成正比，也就是說當風速愈大， PDI 值就愈高，意味著颶風的強度及破壞力也愈高

累積氣旋能量： ACE 可反應出在颶風季節裡颶風的強度和持續時間。

Relative lullreactive

The Atlantic basinThe years 1995 to 2000 experienced the highest level of North Atlantic hurricaneactivity in the reliable record. Compared with the generally low activityof the previous 24 years (1971 to 1994), the past 6 years have seen a doublingof overall activity for the whole basin, a 2.5-fold increase in major hurricanes($50 meters per second), and a Þvefold increase in hurricanes affecting theCaribbean. The greater activity results from simultaneous increases in NorthAtlantic sea-surface temperatures and decreases in vertical wind shear. Becausethese changes exhibit a multidecadal time scale, the present high level ofhurricane activity is likely to persist for an additional ;10 to 40 years. The shiftin climate calls for a reevaluation of preparedness and mitigation strategies