| description abstract | AbstractClimate Generator (CLIGEN) is a stochastic weather generator that has been widely used to generate daily precipitation and storm patterns for hydrological and erosion prediction models. Rainfall data with measurement intervals ≤ 30 min are required to compute two parameters for generating storm patterns, namely, the cumulative distribution of the time to peak rainfall intensity (TimePk) and the mean daily maximum 30-min rainfall intensity (MX.5P). High-resolution rainfall data, however, are not widely available around the world. One-minute precipitation data for 18 stations in eastern and central China were aggregated into hourly intervals to evaluate methods to optimally prepare TimePk and MX.5P for CLIGEN. Four sets of the two parameters were used to run CLIGEN for comparison: C0, using the original 1-min data; C1, replacing TimePk with those computed with hourly data; C2, replacing MX.5P with those computed with hourly data with an adjustment factor; and C3, replacing both parameters with those computed with hourly data, and the MX.5P was adjusted as for C2. Results showed that 1) MX.5P computed with hourly data was systematically lower than that computed with the 1-min data, and the bias could be corrected by multiplying by an adjustment factor of 1.40; 2) the difference in generated storm patterns between C0 and C1 was insignificant; and 3) results from C2 and C3 agreed well with those generated from C0. Hourly precipitation data can be used to prepare CLIGEN input parameter values for generating storm patterns for sites where only hourly data are available. | |
