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Advanced Analytical Methods for Climate Research
Case study 2: Daily rainfall in Western Ireland

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This case study provides an example of the use of GLMs as simulation models. In this case simulation is used to obtain assessments of risk from extreme weather in a changing climate.


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    Background to the study

    The Galway Bay area of Western Ireland (see figure opposite) experiences flooding every winter. However, this flooding was exceptionally severe in the winters of 1990, 1991, 1994 and 1995. Prior to the 1990s, such severe flooding had occurred on average every 30 years. After the 1991 flood event, the Irish Government commissioned an extensive study whose aims were:
    • To assess the extent to which the flooding was caused by abnormal rainfall, rather than other factors such as changes in land use.
    • To determine whether or not rainfall patterns in the area are changing systematically.
    • To explore a variety of engineering solutions to the flooding problem, and determine their likely effectiveness.
    In order to assess the likely effectiveness of engineering solutions, it was necessary to provide plausible scenarios, at a daily timescale, for future rainfall in the area.
    The graph opposite shows the mean daily rainfall amounts over the study area for the December-February period each year, between 1942 and 1996. It is clear from this that there were some extremely high winter rainfalls in the area in the 1990s, and that these coincide with the flooding episodes. There is therefore some systematic structure in the rainfall record, which is associated with severe flood events.

    Unfortunately, this systematic structure is difficult to detect in the daily rainfall record, which is very noisy. Ideally, any analysis of changing climate in this area would be based on means at monthly timescales or longer to smooth out this noise. However, the need for future rainfall scenarios at a daily scenario means that ultimately a study of daily rainfall is required. Generalized Linear Models are able to identify weak signals in noisy data, and are therefore particularly appropriate for this kind of problem.

    Another feature of GLMs is that they are easy to simulate. Via simulation, it is possible to obtain probability distributions for any quantity of interest that can be derived from a daily rainfall sequence. An example is shown in the figure opposite. Here, 1000 daily rainfall sequences have been generated for the period 1989-1997. From each of these sequences, the areal rainfalls from December to February each year have been calculated. This gives, for each year, a distribution of 1000 winter rainfalls against which to compare the observed rainfall. Hence the extent to which the large flood events are `extreme' can be judged.

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    Questions of interest

    There are many interesting questions that arise in this case study, for example:
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    Page last updated: 26th April 2001.