资源环境科技发展态势分析平台

Statistical rainfall climatologies for application to problems in ecohydrology or urban flood hydrology employ indices such the average rainfall depth per rain day or rain hour, and the average daily or hourly rainfall intensity. These subsume fine-temporal-scale aspects of rainfall arrival such as sub-hourly intermittency that vary among locations with different climatic conditions. Rainfall duration and intensity derived from data aggregated to hourly or daily level thus involve some bias, generally overestimating the duration of rainfall and underestimating rainfall rates, and this bias will vary with location. The magnitude of bias is documented for two Australian locations having rainfall records of high temporal resolution: one arid and one wet tropical.

Rainfall data aggregated to hourly or daily level yield substantial overestimates of time raining, and underestimates of rainfall rates. The magnitude of bias is shown to differ between the two field locations where on average rain is only recorded during 3.6 hr (14.9%) of a rain day at the arid location, but 8.2 hr (34%) at the wet tropical site. Resulting bias in estimates of time raining and of rainfall intensities is worse at the arid location. The significance of intermittency in particular for the detection of the effects of climate change on temporal rainfall climatology is explored. If intermittency varies with climate change, but is concealed through the use temporally aggregated rainfall data, erroneous assessments of changes in rainfall intensities may result. The use of rainfall events rather than clock-period data appears to reduce some of these effects, but there is still a failure to reflect short-period,high-intensity rainfall that may be important to soil erosion and the loss of carbon, nutrients, and agrochemicals from agricultural land.