Assessing the impact of climate change on annual typhoon rainfall—a stochastic simulation approach

Cheng, Kit‐Yan; Hou, Ju-Chen; Wu, Yii-Chen; Liou, Jyh‐Ming

doi:10.1007/s10333-009-0183-9

Cited by 15 publications

(11 citation statements)

References 13 publications

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“…Additional data fitting was implemented with NSQM, which utilizes the temporally-varying statistical parameters reflecting the temporal trend captured by the original RCM and thus provides a more realistic projection with seamless connection with the baseline scenario fitted to the historical observation. The GCM or RCM does not include the local heavy rainfall and typhoon generation mechanism, which can be a reason for the underestimation of the summer precipitation [25]. Recently, Murakami et al [26] developed a typhoon projection technique with high-resolution MRI-AGCMon a 20-km scale and applied it for an ensemble projection using the same model on a 60-km scale.…”

Section: Statistical Downscaling: Overviewmentioning

confidence: 99%

“…The total amount, duration and intensities of tropical cyclone events showed typically skewed distributions of Gamma, Gumbel, Log-Pearson Type III, etc. [25,37,38]. The national probability map [39] of Korea was produced based on the Gumbel distribution, which was feasible for extreme storm events in most areas.…”

Section: Statistical Downscaling-stochastic Typhoon Simulation Sub-momentioning

confidence: 99%

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Terrestrial Sediment Yield Projection under the Bias-Corrected Nonstationary Scenarios with Hydrologic Extremes

Moon¹,

Kang

2016

Water

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For reliable prediction of sediment yield in a watershed, fine-scale projections for hydro-climate components were first obtained using the statistical bias correction and downscaling scheme based on the combination of an Artificial Neural Network (ANN), Nonstationary Quantile Mapping (NSQM) and Stochastic Typhoon Synthesis (STS) sub-modules. Successively, the hydrologic runoff and sediment yield from the land surfaces were predicted through the long-term continuous watershed model, Soil and Water Assessment Tool (SWAT), using the bias-corrected and downscaled Regional Climate Model (RCM) output under the Intergovernmental Panel on Climate Change's (IPCC's) A1B climate change scenario. The incremental improvement of the combined downscaling process was evaluated successfully during the baseline period, which provides projected confidence for the simulated future scenario. The realistic simulation of sediment yield is closely related to the rainfall event with high intensity and frequency. During the long-term future period, the Coefficient of River Regime (CORR) reaches 353.9 (27.2% increase with respect to baseline). The projection for annual precipitation by 2040 and 2100 is a 25.7% and a 57.2% increase with respect to the baseline period, respectively. In particular, the increasing CORR rate (33.4% and 72.5%) during the flood season is much higher than that for the annual total amount. However, the sediment yield is expected to increase by 27.4% and 121.2% during the same periods, which exhibits steeper trends than the hydrologic runoff. The June, July, August (JJA) season occupies 83.0% annual total sediment yield during the baseline period, which is similar during the projection period. The relative change of sediment yield is 1.9-times higher than that of dam inflows.

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Section: Statistical Downscaling: Overviewmentioning

confidence: 99%

Section: Statistical Downscaling-stochastic Typhoon Simulation Sub-momentioning

confidence: 99%

Terrestrial Sediment Yield Projection under the Bias-Corrected Nonstationary Scenarios with Hydrologic Extremes

Moon¹,

Kang

2016

Water

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“…While at the same time, they also trigger devastating disasters such as floods, debris flows, landslides, etc. In addition, high concentration sediments carried in streamflow during and after typhoon events may cause serious water supply problems (Cheng et al 2009). As a result, impact assessment of climate change on annual typhoon rainfalls is imperative for a sound decision-making in coping with and adapting to climate change.…”

Section: Introductionmentioning

confidence: 99%

“…However, the scenarios set for GCMs are not directly linked to basin-scale hydrological processes, even though most practices of water resources management and measures that should be taken to cope with potential climate changes are essentially in basin-scale (Cheng et al 2009). Another critical issue one needs to be aware of is that these GCMs are essentially deterministic models which yield unique outputs under given initial conditions.…”

Section: Introductionmentioning

confidence: 99%

Assessing the impact of climate change on basin-average annual typhoon rainfalls with consideration of multisite correlation

Hou

Liou

et al. 2011

Paddy Water Environ

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The effects of climate change on synoptic scale storms like typhoons can have profound impacts on practices of water resources management. A stochastic multisite simulation approach is proposed for assessing the impact of climate changes on basin-average annual typhoon rainfalls (BATRs) under certain synthesized climate change scenarios. Number of typhoon events and event-total rainfalls are considered as random variables characterized by the Poisson and gamma distributions, respectively. The correlation structure of event-total rainfalls at different rainfall stations is found to be significant (higher than 0.80) and plays a crucial role in the proposed stochastic simulation approach. Basin-average annual typhoon rainfalls were simulated for the Shihmen Reservoir watershed in northern Taiwan by considering changes in the mean values of annual number of typhoon events and event-total rainfalls, while assuming the correlation structure of multisite typhoon rainfalls to remain unchanged. The simulation results indicate that changes in expected values of BATR can be easily projected with simpler models; however, changes in extreme properties of BATR are more complicated. Comparing to changes in expected values of BATRs, lesser changes in more extreme events can be observed. This is due to the reduction in coefficient of skewness of gamma distribution BATR under different climate change scenarios. With consideration of the multisite correlation structure, changes in BATRs become more significant. Thus, in assessing the impacts of climate change on many hydrological and environmental variables which exhibit significant spatial correlation pattern, the multisite correlation structure needs to be taken into consideration.

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“…The Ministry of Science and Technology also set out to determine the impact of future climate change in Taiwan. Compared with the average rainfall for the current period (1974 -2003), rainfall will increase roughly 10 -30% at the end of this century with higher intensity and longer duration (Cheng et al 2009;Hsu et al 2011;Water Resource Agency 2013).…”

Section: Introductionmentioning

confidence: 99%

Landslide Impact Assessment Using Projection Rainfall Data from Climate Change Scenario

Wu¹,

Shih²,

Li³

et al. 2016

Terr. Atmos. Ocean. Sci.

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This study ascertains landslide impact under climate change. The disaster impact under climate change was estimated by calculating the variation in safety factor (FS value). The result shows less landslide impact for the late 21 st century (2075 -2099) than in the late 20 th century (1979 -2003). The relationship between rainfall characteristics and landslide susceptibility was then clarified. A total of 40 out of 82 typhoon events from the late 20 th century and 40 out of 88 events from the late 21 st century were selected for estimating landslide impact. The landslide ratio in each event is calculated to find the variation in landslide occurrence between the late 20 th and the late 21 st century. The result proved that landslide occurrence is highly dependent on the rainfall characteristics. Landslides occurred earlier during each rainfall event for the late 21 st century, which is consistent with rainfall characteristics, e.g., high intensity and short duration, for the late 21 st century.

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Assessing the impact of climate change on annual typhoon rainfall—a stochastic simulation approach

Cited by 15 publications

References 13 publications

Terrestrial Sediment Yield Projection under the Bias-Corrected Nonstationary Scenarios with Hydrologic Extremes

Terrestrial Sediment Yield Projection under the Bias-Corrected Nonstationary Scenarios with Hydrologic Extremes

Assessing the impact of climate change on basin-average annual typhoon rainfalls with consideration of multisite correlation

Landslide Impact Assessment Using Projection Rainfall Data from Climate Change Scenario

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