Regional Frequency Analysis applied to extreme rainfall events: Evaluating its conceptual assumptions and constructing null distributions

In Situ Flood Frequency Analysis Used for Water Resource Management in Kelantan River Basin

“…Furthermore, it is most effective when the tail of the distribution is heavier, and the sample size is small. The minimal amount of data available is well recognized to raise the level of uncertainty in both parameter and quantile estimates (Blain et al, 2021).…”

Is it possible to apply the regional frequency analysis to daily extreme air temperature data?

“…Estimating the probability of extreme meteorological events is a difficult task because, by definition, they occur at longreturn periods (> 100 years), which usually surpass the available length of meteorological records (Goudenhoofdt et al 2017, Blain et al 2021. Although this difficulty is a major challenge for any study addressing weather extremes, it is particularly relevant for tropical and subtropical regions where the availability and quality of long-running air temperature series are a matter of great concern.…”

“…The frequency distributions of the data series forming a homogeneous group are expected to share a unique shape, apart from a local/at-site scaling factor (index flood; μ), which and usually is taken to be the population mean at each site and estimated by the sample mean of each series. Therefore, data from all weather stations in this group may be used to fit a unique parametric function, which is taken as "the regional distribution" (Hosking and Wallis 1993, 1997, Fowler and Kilsby 2003, Viglione et al 2007, Caporali et al 2008, Svensson and Jones 2010, Goudenhoofdt et al 2017, Blain et al 2021. In simple terms, a homogeneous group formed by 10 meteorological series with a length of records equal to 20 years is considered.…”

“…In addition, this technique enables estimation at ungauged sites by transferring information coming from nearby gauged sites (Renard 2011). Along with these desirable features, the RFA also evaluates the quality of the meteorological series forming the group (Blain et al 2021). The RFA performs this quality assessment on a regional basis by means of the discordancy measure (d) that assesses the presence of discordant sites within a pre-delimitated group.…”

“…The above-mentioned qualities emphasize the importance of applying the RFA-Lmom in any region of the world, including those where there is a lack of long-running meteorological records (Blain et al 2021). Nevertheless, to the authors' best knowledge there is no study that applied the RFA-Lmom to extreme air temperature data.…”