New estimates of future changes in extreme rainfall across the UK using regional climate model integrations. 1. Assessment of control climate

Annual maxima (AM) series of precipitation from 15 simulations of the North American Regional Climate Change Assessment Program (NARCCAP) have been analysed for gridpoints covering Canada and the northern part of United States. The NARCCAP Regional Climate Models' simulations have been classified into the following three groups based on the driving data used at the RCMs boundaries: (1) NCEP (6 simulations); (2) GCM-historical (5 simulations); and (3) GCM-future (4 simulations). Historical simulations are representative of the 1968-2000 period while future simulations cover the 2041-2070 period. A reference common grid has been defined to ease the comparison. Multi-model average intensities of AM precipitation of 6-, 12-, 24-, 72-, and 120-h for 2-, 5-, 10-, and 20-year return periods have been estimated for each simulation group. Comparison of results from NCEP and GCM-historical groups shows good overall agreement in terms of spatial distribution of AM intensities. Comparison of GCM-future and GCM-historical groups clearly shows widespread increases with median relative changes across all gridpoints ranging from 12 to 18% depending on durations and return periods. Fourteen Canadian climatic regions have been used to define regional projections and average regional changes in intense precipitation have been estimated for each duration and return period. Uncertainties on these regional values, resulting from inter-model variability, were also estimated. Results suggest that inland regions (e.g. Ontario and more specifically Southern Ontario, the Prairies, Southern Quebec) will experience the largest relative increases in AM intensities while coastal regions (e.g. Atlantic Provinces and the West Coast) will experience the smallest ones. These projections are most valuable inputs for the assessment of future impact of climate change on water infrastructures and the development of more efficient adaptation strategies.

Section: Discussionmentioning

confidence: 99%

Future changes in intense precipitation over Canada assessed from multi‐model NARCCAP ensemble simulations

Mailhot

Beauregard

Talbot

et al. 2011

“…Judging by Figure 2(f) given in Osborn and Hulme (2002), it is unusual for the Durham region to not have a stronger increase in heavy winter rainfall in the period so is not clear, but it may relate to stronger and more frequent westerly and south-westerly flows over the UK in winter (Osborn et al, 2000); these flows tend to produce heavier rainfall on the western side of the country but not to the east of the Pennine Hills. Indeed, Fowler et al (2005) using regional climate model integrations suggested that regions on the leeward side of the areas of high elevation, such as north-east England, show a classic 'rain-shadow' effect with very small increases in simulated mean annual rainfall. In this respect, Durham may be more like some of the East Anglian stations than the upland stations close to the west.…”

Section: Discussionmentioning

confidence: 99%

Inter‐decadal variability in daily rainfall at Durham (UK) since the 1850s

Burt¹,

Horton²

2006

Abstract:Records of daily rainfall at Durham (UK) are analysed from 1850 to the present. The most notable wet period is the 1870s, followed by a protracted period of below-average rainfall. Other than the 1870s, summers tended to be much wetter than winters during the latter part of the 19th century. In the 20th century, summers had become drier and winters wetter. To analyse large daily totals, three thresholds, 15, 22.6, and 25 mm, are used. For all three indices, the frequency of large falls was highest from the 1860s to the 1880s, followed by a low frequency in the 1900s. Since then, the general trend has been for totals to gradually increase. There is a clear division for the annual total rainfall, number of heavy falls (≥15 mm), and proportion of total rainfall provided by heavy falls in the winter (154 mm, 147 days, 12%, respectively) and spring (140 mm, 180 days, 16%) seasons in comparison to the summer (181 mm, 329 days, 28%) and autumn (186 mm, 304 days, 23%) seasons. However, since 1990, winter total rainfall (164 mm) has overtaken the summer total (154 mm). Furthermore, since 1990, heavy falls of rain in spring (23 days) and the proportion of total rainfall (26%) have overtaken summer heavy rain (17 days) and the proportions of rainfall in both summer (24%) and autumn (24%). In terms of heavy rainfall, winters have seen only a small increase in its relative importance, whereas its relative importance declined from the 1960s to the mid-1990s for summers. The widely recognised increase in the winter : summer ratio of rainfall since the 1960s is clearly evident. Overall, there has been a narrowing of the differences between seasons in terms of the frequency of heavy falls of rain in the 1990s.

“…Frei et al, 2003), extreme climate events (e.g. Fowler et al, 2005a;Frei et al, 2006) and regional scale climate anomalies, or non-linear effects, such as those associated with the El Niño Southern Oscillation (e.g. Leung et al, 2003a).…”

Section: Dynamical Downscalingmentioning

confidence: 99%

Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling

Fowler

Blenkinsop

Tebaldi

2007

1,925

1,491

Abstract:There is now a large published literature on the strengths and weaknesses of downscaling methods for different climatic variables, in different regions and seasons. However, little attention is given to the choice of downscaling method when examining the impacts of climate change on hydrological systems. This review paper assesses the current downscaling literature, examining new developments in the downscaling field specifically for hydrological impacts. Sections focus on the downscaling concept; new methods; comparative methodological studies; the modelling of extremes; and the application to hydrological impacts.Consideration is then given to new developments in climate scenario construction which may offer the most potential for advancement within the 'downscaling for hydrological impacts' community, such as probabilistic modelling, pattern scaling and downscaling of multiple variables and suggests ways that they can be merged with downscaling techniques in a probabilistic climate change scenario framework to assess the uncertainties associated with future projections. Within hydrological impact studies there is still little consideration given to applied research; how the results can be best used to enable stakeholders and managers to make informed, robust decisions on adaptation and mitigation strategies in the face of many uncertainties about the future. It is suggested that there is a need for a move away from comparison studies into the provision of decision-making tools for planning and management that are robust to future uncertainties; with examination and understanding of uncertainties within the modelling system.