Cheng-Shang Lee

Dr. Cheng-Shang Lee


Research Focus & Metrics

Academic Career Length

43Years (1984-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 2013 in Journal of Hydrology
Verified
Journal Article
Open access
LHLing-Feng Hsiao
Ling-Feng Hsiao
MYMing-Jen Yang
Ming-Jen Yang
CLCheng-Shang Lee
Cheng-Shang Lee
HKHung-Chi Kuo
Hung-Chi Kuo
DSDong-Sin Shih
Dong-Sin Shih
GLGwo-Fong Lin
Gwo-Fong Lin
SummaryIn this study, an ensemble meteorological modeling system is one-way coupled with a hydrological model to predict typhoon rainfall and flood responses in a mountainous watershed in Taiwan. This ensemble meteorological model framework includes perturbations of the initial conditions, data analysis methods, and physical parameterizations. The predicted rainfall from the ensemble meteorological modeling system is then used to drive a physically distributed hydrological model for flood responses in the Lanyang basin during the landfall of Typhoon Nanmadol (2011). The ensemble forecast provides track forecasts that are comparable to the operational center track forecasts and provides a more accurate rainfall forecast than a single deterministic prediction. The runoff forecast, which is driven by the ensemble rainfall prediction, can provide uncertainties for the runoff forecasts during typhoon landfall. Thus, the ensemble prediction system provides useful probability information for rainfall and runoff forecasting

1 February 2006 in Natural Hazards
Verified
Journal Article
Closed access
PDF file
CLCheng-Shang Lee
Cheng-Shang Lee
LHLi-Rung Huang
Li-Rung Huang
HSHorng-Syi Shen
Horng-Syi Shen
SWShi-Ting Wang
Shi-Ting Wang

1 August 2010 in Monthly Weather Review
Verified
Journal Article
Closed access
CLCheng-Shang Lee
Cheng-Shang Lee
Kevin K.W. CheungKevin K.W. Cheung
Kevin K.W. Cheung
WFWei-Ting Fang
Wei-Ting Fang
RERussell L. Elsberry
Russell L. Elsberry
A tropical cyclone (TC) size parameter, which is defined here as the radius of 15 m s−1 near-surface wind speed (R15), is calculated for 145 TCs in the western North Pacific during 2000–05 based on QuikSCAT oceanic winds. For the 73 TCs that intensified to typhoon intensity during their lifetimes, the 33% and 67% respective percentiles of R15 at tropical storm intensity and at typhoon intensity are used to categorize small, medium, and large TCs. Whereas many of the small TCs form from an easterly wave synoptic pattern, the monsoon-related formation patterns are favorable for forming medium to large TCs. Most of these 73 TCs stay in the same size category during intensification, which implies specific physical mechanisms for maintaining TC size in the basin. The 18 persistently large TCs from the tropical storm to the typhoon stage mostly have northwestward or north-northwestward tracks, while the 16 persistently small TCs either move westward–northwestward in lower latitudes or develop at higher latitudes with various track types. For the large TCs, strong low-level southwesterly winds exist in the outer core region south of the TC center throughout the intensification period. The small TCs are more influenced by the subtropical high during intensification. The conclusion is that it is the low-level environment that determines the difference between large and small size storms during the early intensification period in the western North Pacific.

30 May 2012 in Weather and Forecasting
Verified
Journal Article
Open access
LHLing-Feng Hsiao
Ling-Feng Hsiao
DCDer-Song Chen
Der-Song Chen
YKYing-Hwa Kuo
Ying-Hwa Kuo
YGYong-Run Guo
Yong-Run Guo
TYTien-Chiang Yeh
Tien-Chiang Yeh
CLCheng-Shang Lee
Cheng-Shang Lee
In this paper, the impact of outer loop and partial cycling with the Weather Research and Forecasting Model’s (WRF) three-dimensional variational data assimilation system (3DVAR) is evaluated by analyzing 78 forecasts for three typhoons during 2008 for which Taiwan’s Central Weather Bureau (CWB) issued typhoon warnings, including Sinlaku, Hagupit, and Jangmi. The use of both the outer loop and the partial cycling approaches in WRF 3DVAR are found to reduce typhoon track forecast errors by more than 30%, averaged over a 72-h period. The improvement due to the outer loop approach, which can be more than 42%, was particularly significant in the early phase of the forecast. The use of the outer loop allows more observations to be assimilated and produces more accurate analyses. The assimilation of additional nonlinear GPS radio occultation (RO) observations over the western North Pacific Ocean, where traditional observational data are lacking, is particularly useful. With the lack of observations over the tropical and subtropical oceans, the error in the first-guess field (which is based on a 6-h forecast of the previous cycle) will continue to grow in a full-cycling limited-area data assimilation system. Even though the use of partial cycling only shows a slight improvement in typhoon track forecast after 12 h, it has the benefit of suppressing the growth of the systematic model error. A typhoon prediction model using the Advanced Research core of the WRF (WRF-ARW) and the WRF 3DVAR system with outer loop and partial cycling substantially improves the typhoon track forecast. This system, known as Typhoon WRF (TWRF), has been in use by CWB since 2010 for operational typhoon predictions.

1 January 2015 in Journal of Hydrology
Verified
Journal Article
Closed access
Josh Tsun-Hua YangJosh Tsun-Hua Yang
Josh Tsun-Hua Yang
SYSheng-Chi Yang
Sheng-Chi Yang
JHJui-Yi Ho
Jui-Yi Ho
GLGwo-Fong Lin
Gwo-Fong Lin
GHGong-Do Hwang
Gong-Do Hwang
CLCheng-Shang Lee
Cheng-Shang Lee

23 December 2008 in Natural Hazards and Earth System Sciences
Verified
Journal Article
Open access
PDF file
Kevin K.W. CheungKevin K.W. Cheung
Kevin K.W. Cheung
LHL.-R. Huang
L.-R. Huang
CLCheng-Shang Lee
Cheng-Shang Lee
Due to the Central Mountain Range with an elevation up to about 4 km, the amount and distribution of rainfall in Taiwan associated with typhoons or tropical cyclones (TCs) depends not only on the distribution of convection within the TCs (internal structure) and influences from monsoon-scale environmental flow, but also on the orographic effect. This study analyzes the spatial and temporal characteristics of rainfall associated with 62 TC cases that affected Taiwan by using observations from the 371 automatic rain stations available in the period 1989–2002. It is found from the climatology maps that highly different rainfall distributions occurred for TCs that approached the Taiwan area from different directions. By performing objective clustering analysis of the rainfall time series of all the rain gauges, several characteristic temporal rainfall profiles are obtained. The geographic distribution of rain gauges that possess a particular temporal profile is also consistent with the possible TC track types that bring maximum rain to the Taiwan area at different times. Based on data in the 1989–2002 period, the development of a TC rainfall climatology-persistence (CLIPER) model is described. CLIPER is an optimized combination of climatology and persistence with different relative weighting for different forecast periods. Independent cases (other than the model development database) during 2003–2004 are used to validate the model. Objective measures like equitable threat score and bias score show that CLIPER's skill is acceptable for practical applications for 24-h rain threshold below 100 mm. However, the underestimation bias for more heavy rainfall is serious and CLIPER seems to have better performance for the northwestern Taiwan than for the other locations. Future directions for improvement of the CLIPER model are discussed.