Title: Adjusting skewness and maximum 0.5-h intensity in CLIGEN to improve extreme event and sub-daily intensity generation for assessing climate change impacts Author
Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 6, 2013
Publication Date: N/A
Interpretive Summary: Recent weather records in US showed that precipitation trend is changing towards having more frequent and larger storms. The increase in number of large storms will definitely increase risks of having more severe soil loss and flooding. To better grasp this risk, climate change scenarios used for assessing this risk should properly reflect the increasing trend of having more severe storms. In order to better simulate this trend, this work is set out to find ways to adjust two model parameters (skewness coefficient and maximum 30-min rainfall intensity) of a climate generator (a computer program that can mathematically generating daily weather). Daily precipitation from a total of 41 weather stations were used in this study. It was found that the ratio of 99.9th percentile to mean daily precipitation was a good predictor for adjusting skewness coefficient. A strong linear relationship was found between skewness coefficient and this ratio for all sites. For adjustment of maximum 30-min intensity, relative change of monthly mean precipitation is found to be a good predictor, and a linear relationship is established, which can be used for the adjustment. Results from this work should be useful to scientists and engineers who study the impacts of climate change on natural resources, especially soil and water.
Technical Abstract: Both measured data and GCM/RCM projections show an general increasing trend in extreme rainfall events as temperature rises in US. Proper simulation of extreme events is particularly important for assessing climate change impacts on soil erosion and hydrology. The objective of this paper is to find ways to adjust skewness coefficient and maximum 0.5-h intensity in CLIGEN to improve generations of extreme events as well as sub-daily rainfall intensity for better assessment of climate change impacts on hydrology and soil erosion. Eighteen weather stations (eight from Oklahoma and 10 around world) and 23 stations from eastern US were used to develop adjustments for skewness coefficient and maximum 0.5-h intensity, respectively. It was found that the ratio of 99.9th percentile to mean daily precipitation was a good predictor for adjusting skewness coefficient. Strong linear correlation was found between skewness coefficient and the ratio for all sites. The linear regression fitted to all 18 sites showed an intercept of 0.514, a slope of 0.245, and an r2 of 0.858 (P<0.0001). This relationship seems suitable to adjust skewness coefficient around the world. Relative changes of maximum 0.5-h intensity were positively correlated to relative changes of monthly mean precipitation for most sites in east of the Rocky Mountain. The linear fit to all 23 sites without an intercept produced a slope of 0.666 and an r2 of 0.427 (P<0.0001), which can be used for a first order adjustment of maximum 0.5-h intensity in CLIGEN for the region if site-specific adjustment relationship is unavailable.