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Impact of temporal resolution of precipitation forcing data on modelled urban-atmosphere exchanges and surface conditions

Ward, H., Tan, Y. S., Gabey, A. M., Kotthaus, S. and Grimmond, C. S. B. ORCID: (2018) Impact of temporal resolution of precipitation forcing data on modelled urban-atmosphere exchanges and surface conditions. International Journal of Climatology, 38 (2). pp. 649-662. ISSN 1097-0088

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To link to this item DOI: 10.1002/joc.5200


Representative precipitation data sets are very difficult to obtain due to the inherent spatial and temporal variability of rainfall. Gridded rainfall products exist at various scales, but temporal resolution is coarse (daily or, at best, a few hours). This study demonstrates the impact of low temporal resolution precipitation forcing data (PFD) on modelled energy fluxes, runoff and surface conditions, which could have implications for a range of applications including flood forecasting, irrigation scheduling and epidemiology. An evaporation-interception model originally developed for forests is applied here within the framework of the Surface Urban Energy and Water balance Scheme (SUEWS). The model is forced with rainfall data representative of a range of temporal resolutions (from 5 min to 3 h). Taking the highest resolution case as a reference, differences in model output are found as the temporal resolution of PFD decreases, depending on the timing of rainfall occurrence, intensity and duration. Modelled evaporation, runoff and surface wetness deviate from the reference case, which affect other variables such as the turbulent sensible heat flux. The largest impacts are seen on days with greatest daily total rainfall and, even on days with no rain, differences in antecedent conditions (soil moisture or surface wetness) can cause deviations from the reference case. Errors can be reduced by applying a disaggregation scheme that provides a more realistic distribution of rainfall, importantly, one that allows for intermittent rainfall.

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:71436


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