Producing Daily and Embedded Hourly Rainfall Data Using a Novel Weather Generator


The number of worldwide extreme drought and flood events has risen significantly in recent years. Many studies confer that climate change may cause more intensive and extreme events. Simulating the impact of climate change often requires weather data as inputs to assessment models. Stochastic weather generators have been developed to produce weather data with the same temporal resolution based on the outputs of GCMs. Reservoir simulation normally uses operational rules in daily and hourly time steps for water supply and flood reduction, respectively. Simulating consecutive drought and flood events simultaneously requires a weather generator to produce different temporal resolution data. This work develops a continuous weather generator to generate daily and hourly precipitation data for regular wet days and severe storms, respectively. Daily rainfall data is generated for regular wet days using Exponential distribution or Weibull distribution, while the total rainfall data for severe storms is generated using the Pearson type III or Log Pearson type III distribution. Moreover, hourly rainfall is determined based on generated hyetographs. Simulation results indicate that the proposed continuous weather generator can generate daily and hourly rainfall reasonably. The proposed weather generator is thus highly promising for use in evaluating how climate change impacts reservoir operations that are significantly influenced by more frequent and intensive consecutive drought and flood events.

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Published by The Chinese Geoscience Union