How does sub‐hourly rainfall intermittency bias the climatology of hourly and daily rainfalls? Examples from arid and wet tropical Australia

Abstract

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 finetemporal-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 shortperiod, high-intensity rainfall that may be important to soil erosion and the loss of carbon, nutrients, and agrochemicals from agricultural land.

Subhourly rainfall in a convection-permitting model

“…The same amount of precipitation spread over different time periods will affect many land surface processes [19], such as the amount of precipitation absorbed by the soil, converted to runoff, and re-evaporated by the atmosphere, all of which are important considerations in hydrological modelling and climate modelling in general. Future changes in the intermittency of rainfall may be masked at hourly timescales, leading to flawed estimates of changes in precipitation intensities and their impacts [24]. Identifying shortcomings in the character of modelled subhourly precipitation is thus important for ongoing CPM development.…”

Mesoscale Mapping of Sediment Source Hotspots for Dam Sediment Management in Data-Sparse Semi-Arid Catchments

“…One example found herein was the rainfall intensity and associated kinetic energy as a crucial variable leading to sediment detachment. During a rainstorm event, rainfall intensity changes several times [128], but daily aggregates, or maximum 30-, 15-, or 6-min intensities are used to calculate rainfall energy in soil erosion models, while more fine-scale data on intensity variability are not available.…”

“…In our continuously changing world, sediment management is likely to fail if it continues to target long-term mean values rather than variability. Sediment management might fall behind ongoing and future environmental trends if it continues to omit in the most influential factors and their compound effects [128,136]. Eco-hydrological hindcast modeling for water and sediment management [87,88] provides a step forward for addressing management challenges related to ongoing change.…”

Sub-Daily Rainfall Intensity Extremes: Evaluating Suitable Indices at Australian Arid and Wet Tropical Observing Sites

“…The It has to be remembered that rain hours typically contain some rainless time. Elsewhere, the author [15] has reported that afternoon rainfall tends to exhibit higher intermittency, which reaches a minimum during the early morning intensity peak. Therefore, true intensities in the afternoon are higher than suggested by the data of Figure 5.…”

“…This index is simply the total rainfall depth over a period such as a month or a year, divided by the number of rain days in that period; it is therefore the mean wet day rainfall. This is perhaps more correctly described as a measure of the wetness of rain days, and can only be loosely connected with the actual intensity when raining, since rain commonly falls for only a part of each rain day [14,15]. Locations with different degrees of rainfall intermittency (or different variance of rainday intensities) may exhibit different intensities when raining, even if their SDII values are the same.…”