Conditioning stochastic properties of daily precipitation on indices of atmospheric circulation

Kiely, Gérard; Albertson, J. D.; Parlange, M. B.; Katz, Richard W.

doi:10.1017/s1350482798000656

Cited by 23 publications

(13 citation statements)

References 24 publications

(29 reference statements)

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“…This mixture modelling approach enables capture of both low frequency variations in dry-or wetspell preponderance as well as seasonal variability in rainfall occurrence (e.g. Kiely et al, 1998;Wilby 2001b). We modelled drought duration independent of initial conditions or time of year whereas Vargas et al (2011) showed that spell length (albeit based on daily precipitation records) depends on occurrence start date.…”

Section: Discussionmentioning

confidence: 99%

Persistence of Hydrometeorological Droughts in the United Kingdom: A Regional Analysis of Multi-Season Rainfall and River Flow Anomalies

et al. 2015

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Section: Discussionmentioning

confidence: 99%

Persistence of Hydrometeorological Droughts in the United Kingdom: A Regional Analysis of Multi-Season Rainfall and River Flow Anomalies

et al. 2015

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“…For example, Parlange (1993, 1996) used a twostate index of monthly mean sea level pressure to condition daily rainfall parameters for sites in California and found that the conditional model reduced the over-dispersion of monthly precipitation that was evident in the output of an unconditional model. Kiely et al (1998) applied a similar approach to condition the occurrence and intensity parameters of a daily precipitation model for Valentia, Ireland and acquired improved estimates of the standard deviation of monthly precipitation. Wilby (1998) obtained modest improvements in monthly precipitation statistics for sites in central and eastern England using the North Atlantic Oscillation (NAO) index and sea surface temperature (SST) anomalies linearly to condition the seasonal parameters of a stochastic rainfall model.…”

Section: Introductionmentioning

confidence: 99%

Downscaling summer rainfall in the UK from North Atlantic ocean temperatures

Wilby

2001

Hydrol. Earth Syst. Sci.

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Annual series of three stochastic rainfall model parameters -the seasonal wet day amount (or intensity), the conditional dry-day probability (or dry-spell persistence), and the conditional wet-day probability (or wet-spell persistence) -were examined using daily rainfall records for ten UK stations for the period 1901-1995. The purpose was first, to determine the extent to which these indices of summer (June-August) rainfall were correlated with empirical orthogonal functions (EOFs) of summer North Atlantic sea surface temperature (SST) anomalies: second, to evaluate the skill of EOFs of preceding winter (December-February) SSTs for summer rainfall forecasting and downscaling. Correlation analyses suggest that observed increases in summer dry-spell persistence since the 1970s coincided with positive SST anomalies in the North Atlantic. In contrast, wet-spell persistence and intensities were relatively weakly correlated with the same patterns, implying that the use of SSTs is justifiable for conditioning occurrence but not intensity parameters. Furthermore, the correlation strengths were greater for EOFs of SSTs than those reported for area-average SST anomalies, indicating that the pattern of SST anomalies conveys important information about seasonal rainfall anomalies across the UK. When EOFs of winter SSTs were used to forecast summer rainfall in Cambridge, the skill was once again greater for dry-spells than either wet-spells or intensities. However, even for dry-spells, the correlation with observationswhilst statistically significant -was still rather modest (r<0.4). Nonetheless, the results are comparable to previous investigations of summer rainfall across Europe, and suggest that forecasting skill (across the UK) originates from the predictability of the rainfall occurrence process.

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“…Among the different proposed techniques, exhaustively reviewed by Sharma and Mehrotra (2010), the most commonly adopted approach to the problem since the 1960s is the Markov-chain (MC) simulation: in its classical form, it is a linear model which cannot simulate the variability and persistence at different scales. Solutions to deal with this limitation consist of introducing exogenous climatic variables and large-scale circulation indexes (Hay et al, 1991;Bardossy and Plate, 1992;Katz and Parlange, 1993;Woolhiser et al, 1993;Hughes and Guttorp, 1994;Wallis and Griffiths, 1997;Wilby, 1998;Kiely et al, 1998;Hughes et al, 1999), lower-frequency daily rainfall covariates (Wilks, 1989;Briggs and Wilks, 1996;Jones and Thornton, 1997;Katz and Zheng, 1999) or an index based on the short-term daily historical or previously generated record (Harrold et al, 2003a, b;Mehrotra and Sharma, 2007a;Mehrotra and Sharma, 2007b) as conditioning variables for the estimation of the MC parameters. By doing this, nonlinearity is introduced in the prior model, and the MC parameters change with time as a function of some specific lowfrequency fluctuations.…”

Section: Introductionmentioning

confidence: 99%

Simulation of rainfall time series from different climatic regions using the direct sampling technique

Oriani

Straubhaar

Renard

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. The direct sampling technique, belonging to the family of multiple-point statistics, is proposed as a nonparametric alternative to the classical autoregressive and Markovchain-based models for daily rainfall time-series simulation. The algorithm makes use of the patterns contained inside the training image (the past rainfall record) to reproduce the complexity of the signal without inferring its prior statistical model: the time series is simulated by sampling the training data set where a sufficiently similar neighborhood exists. The advantage of this approach is the capability of simulating complex statistical relations by respecting the similarity of the patterns at different scales. The technique is applied to daily rainfall records from different climate settings, using a standard setup and without performing any optimization of the parameters. The results show that the overall statistics as well as the dry/wet spells patterns are simulated accurately. Also the extremes at the higher temporal scale are reproduced adequately, reducing the well known problem of overdispersion.

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Conditioning stochastic properties of daily precipitation on indices of atmospheric circulation

Cited by 23 publications

References 24 publications

Persistence of Hydrometeorological Droughts in the United Kingdom: A Regional Analysis of Multi-Season Rainfall and River Flow Anomalies

Persistence of Hydrometeorological Droughts in the United Kingdom: A Regional Analysis of Multi-Season Rainfall and River Flow Anomalies

Downscaling summer rainfall in the UK from North Atlantic ocean temperatures

Simulation of rainfall time series from different climatic regions using the direct sampling technique

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