Enhanced evaluation of hourly and daily extreme precipitation in Norway from convection-permitting models at regional and local scales

Abstract. Convection-permitting regional climate models (CPRCMs) have demonstrated enhanced capability in capturing extreme precipitation compared to regional climate models (RCMs) with convection parameterization schemes. Despite this, a comprehensive understanding of their added values in terms of daily or hourly extremes, especially at the local scale, remains limited. In this study, we conduct a thorough comparison of daily and hourly extreme precipitation from the HARMONIE Climate (HCLIM) model at 3 km resolution (HCLIM3) and 12 km resolution (HCLIM12) across Norway's diverse landscape, divided into five regions, using both gridded and in situ observations. Our main focus is on investigating the added value of CPRCMs (i.e., HCLIM3) compared to RCMs (i.e., HCLIM12) for extreme precipitation from regional to local scales and on quantifying to what extent CPRCMs can reproduce the orographic effect on extreme precipitation at both daily and hourly scales. We find that HCLIM3 matches observations better than HCLIM12 for daily and hourly extreme precipitation across most grid points in Norway, while HCLIM12 underestimates the extremes, especially for hourly extremes. At the regional scale, HCLIM3 captures the maximum 1 d precipitation (RX1 d) and the maximum 1 h precipitation (Rx1 h) more accurately across most regions and seasons, with some exceptions. Specifically, for daily extremes, it shows larger summer biases in the east, south and west, as well as return levels biases in the east; for hourly extremes, larger biases are observed in the summer and in the west compared to HCLIM12. Besides this, for the local scale, HCLIM3 also outperforms HCLIM12 in most regions and seasons, except for a slightly larger summer bias in terms of daily extremes in the south and west. Overall, HCLIM3 consistently demonstrates added value in simulating daily extremes in the middle and northern regions at both regional and local scales, as well as in simulating hourly extremes at all 10 stations, compared with HCLIM12. Both HCLIM3 and HCLIM12 capture the seasonality of daily extremes well, while HCLIM3 performs better for the hourly extremes, accurately representing their frequency and intensity. Additionally, both models capture the reverse orographic effect of Rx1 h at the regional scale, with no added value seen in HCLIM3, while, at the local scale, HCLIM3 shows added value compared to HCLIM12 in representing the reverse orographic effect of Rx1 d in all seasons except summer. This study highlights the importance of more realistic CPRCMs in providing reliable insights into the characteristics of precipitation extremes across Norway's five regions. Such information is crucial for effective adaptation management to mitigate severe hydro-meteorological hazards, especially for the local extremes.