Impact of RCM Spatial Resolution on the Reproduction of Local, Subdaily Precipitation

Jonas Olsson Research and Development (Hydrology), Swedish Meteorological and Hydrological Institute, Norrköping, Sweden

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Peter Berg Research and Development (Hydrology), Swedish Meteorological and Hydrological Institute, Norrköping, Sweden

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Akira Kawamura Department of Civil and Environmental Engineering, Tokyo Metropolitan University, Tokyo, Japan

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Abstract

Many hydrological hazards are closely connected to local precipitation (extremes), especially in small and urban catchments. The use of regional climate model (RCM) data for small-scale hydrological climate change impact assessment has long been nearly unfeasible because of the low spatial resolution. The RCM resolution is, however, rapidly increasing, approaching the size of small catchments and thus potentially increasing the applicability of RCM data for this purpose. The objective of this study is to explore to what degree subhourly temporal precipitation statistics in an RCM converge to observed point statistics when gradually increasing the resolution from 50 to 6 km. This study uses precipitation simulated by RCA3 at seven locations in southern Sweden during 1995–2008. A positive impact of higher resolution was most clearly manifested in 10-yr intensity–duration–frequency (IDF) curves. At 50 km the intensities are underestimated by 50%–90%, but at 6 km they are nearly unbiased, when averaged over all locations and durations. Thus, at 6 km, RCA3 apparently generates low-frequency subdaily extremes that resemble the values found in point observations. Also, the reproduction of short-term variability and less extreme maxima were overall improved with increasing resolution. For monthly totals, a slightly increased overestimation with increasing resolution was found. The bias in terms of wet fraction and wet spell characteristics was overall not strongly dependent on resolution. These metrics are, however, influenced by the cutoff threshold used to separate between wet and dry time steps as well as the wet spell definition.

Corresponding author address: Jonas Olsson, Research and Development (Hydrology), Swedish Meteorological and Hydrological Institute, Folkborgsvägen 17, 60176 Norrköping, Sweden. E-mail: jonas.olsson@smhi.se

Abstract

Many hydrological hazards are closely connected to local precipitation (extremes), especially in small and urban catchments. The use of regional climate model (RCM) data for small-scale hydrological climate change impact assessment has long been nearly unfeasible because of the low spatial resolution. The RCM resolution is, however, rapidly increasing, approaching the size of small catchments and thus potentially increasing the applicability of RCM data for this purpose. The objective of this study is to explore to what degree subhourly temporal precipitation statistics in an RCM converge to observed point statistics when gradually increasing the resolution from 50 to 6 km. This study uses precipitation simulated by RCA3 at seven locations in southern Sweden during 1995–2008. A positive impact of higher resolution was most clearly manifested in 10-yr intensity–duration–frequency (IDF) curves. At 50 km the intensities are underestimated by 50%–90%, but at 6 km they are nearly unbiased, when averaged over all locations and durations. Thus, at 6 km, RCA3 apparently generates low-frequency subdaily extremes that resemble the values found in point observations. Also, the reproduction of short-term variability and less extreme maxima were overall improved with increasing resolution. For monthly totals, a slightly increased overestimation with increasing resolution was found. The bias in terms of wet fraction and wet spell characteristics was overall not strongly dependent on resolution. These metrics are, however, influenced by the cutoff threshold used to separate between wet and dry time steps as well as the wet spell definition.

Corresponding author address: Jonas Olsson, Research and Development (Hydrology), Swedish Meteorological and Hydrological Institute, Folkborgsvägen 17, 60176 Norrköping, Sweden. E-mail: jonas.olsson@smhi.se
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