scholarly journals Detecting changes in seasonal precipitation extremes using regional climate model projections: Implications for managing fluvial flood risk

2010 ◽  
Vol 46 (3) ◽  
Author(s):  
H. J. Fowler ◽  
R. L. Wilby
2020 ◽  
Author(s):  
Erika Toivonen ◽  
Danijel Belušić ◽  
Emma Dybro Thomassen ◽  
Peter Berg ◽  
Ole Bøssing Christensen ◽  
...  

<p>Extreme precipitation events have a major impact upon our society. Although many studies have indicated that it is likely that the frequency of such events will increase in a warmer climate, little has been done to assess changes in extreme precipitation at a sub-daily scale. Recently, there is more and more evidence that <span>high-resolution convection-permitting models </span><span>(CPMs)</span> (grid-mesh typically < 4 km) can represent especially short-duration precipitation extremes more accurately when compared with coarser-resolution <span>regional climate model</span><span>s </span><span>(RCMs)</span><span>.</span></p><p>This study investigates sub-daily and daily precipitation characteristics based on hourly <span>output data from the HARMONIE-Climate model </span>at 3-km and 12-km grid-mesh resolution over the Nordic region between 1998 and 2018. The RCM modelling chain uses the ERA-Interim reanalysis to drive a 12-km grid-mesh simulation which is further downscaled to 3-km grid-mesh resolution using a non-hydrostatic model set-up.</p><p>The statistical properties of the modeled extreme precipitation are compared to several sub-daily and daily observational products, including gridded and in-situ gauge data, from April to September. We investigate the skill of the model to represent different aspects of the frequency and intensity of extreme precipitation as well as intensity–duration–frequency (IDF) curves that are commonly used to investigate short duration extremes from an urban planning perspective. The high grid resolution combined with the 20-year-long simulation period allows for a robust assessment at a climatological time scale <span>and enables us to examine the added value of high-resolution </span><span>CPM</span><span> in reproducing precipitation extremes over the Nordic </span><span>region</span><span>. </span><span>Based on the tentative results, the high-resolution CPM can realistically capture the </span><span>characteristics </span><span>of precipitation extremes, </span><span>for instance, </span><span>in terms of improved diurnal cycle and maximum intensities of sub-daily precipitation.</span></p>


2021 ◽  
Author(s):  
Christoph Sauer ◽  
Peter Fröhle ◽  
Edgar Nehlsen ◽  
Diana Rechid ◽  
Laurens Bouwer ◽  
...  

<p>Projections of the 21st century potential future climate evolution, especially for precipitation, are associated with high uncertainty and variability. Knowledge of the variability of the projected precipitation and resulting run-offs and the sources of uncertainties form the basis for analysis and assessment of future water-management options as well as potential risks related to droughts and flood events. The variabilities related to climate modelling can only be assessed by using a comparatively large number of climate projections.</p><p>In our research, we apply a large ensemble of regional climate model projections from the regional climate model REMO, driven by different global climate model simulations, at high temporal (hourly timestep) and high spatial (0.11 degree, or about 12.5 km) resolutions. Although the analysis of such big datasets involves considerable computational and storage capacities, this potentially helps to improve the simulation of future hydrological quantities in river catchments. For the analysis of the behaviour of small river catchments, we apply a semi-distributive hydrological model. Annual and winter average precipitation conditions show a robust and statistically significant increase especially for the RCP8.5 scenario. Precipitation ranges are compared with the ranges of runoff based on hydrological impact model runs driven by a set of simulated parameters from the regional climate model ensemble. The analyses are performed for a sub-catchment of the Lower Elbe system (Krückau catchment), which is a typical small basin (area < 200km<sup>2</sup>) close to the city of Hamburg in northern Germany. The model runs cover a long simulation period of 150 years (1950-2100) with a temporal resolution of 1 day. Short term model runs with a temporal resolution of 1 hour were carried out for annual and seasonal (summer/winter) maximum runoff derived from the long-term simulations.</p><p>Average annual runoff shows an increase of 0 to 10 % for the RCP2.6 ensemble and an increase of 0 to 20 % for the RCP8.5 ensemble at the end of the 21st century. Annual and winter average conditions (precipitation sums and average runoff) of the RCP8.5 ensemble show a robust increase across different ensemble simulations. Extreme events however show high variability and no conclusive and robust trend. Analysis shows a good relation between average values of precipitation and average runoff (MQ). Future development of simulated annual maximum runoffs shows only a weak relation with future simulated precipitation extremes. However, summer maximum runoffs tend to show a relation with summer precipitation extremes. The behaviour of winter runoffs might be explained by altered future conditions of snow aggregation and melt in combination with high soil moisture. With increasing average and extreme temperatures, snow fall, snow accumulation and concentrated runoff caused by snow melt in spring are less likely to occur.</p><p>One of the conclusions drawn is that especially for assessing extreme precipitation and its impacts on small hydrological catchments it is necessary to apply regional climate model projections with high spatial and temporal resolution where further improvement is expected by making use of the upcoming generation of climate simulations on convection permitting scale.</p>


2012 ◽  
Vol 43 (4) ◽  
pp. 341-351 ◽  
Author(s):  
Jonas Olsson ◽  
Ulrika Willén ◽  
Akira Kawamura

Urban hydrological climate change impact assessment requires an assessment of how short-term local precipitation extremes, e.g. expressed as intensity-duration-frequency (IDF) curves, are expected to change in the future. This cannot be done on the basis of regional climate model (RCM) results directly, mainly because of the models' coarse spatial grid and resolution-dependent limitations in process descriptions. In this paper, a stochastic model for downscaling short-term precipitation from RCM grid scale to local (i.e. point) scale is formulated and tested using data from Stockholm, Sweden. In principle, additional RCM variables characterising the weather situation are used to convert from grid box average to local precipitation, and estimate the probability of occurrence in an arbitrary point. Finally, local time series are stochastically simulated and IDF curves derived. The results of the application in Stockholm suggest that: (1) observed IDF-curves may be effectively reproduced by the model; and (2) the future increase of local-scale short-term precipitation extremes may be higher than the predicted increase of short-term extremes on the RCM grid scale.


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