Rainfall Seasonality: Description, Spatial Patterns and Change Through Time

Walsh, R. P. D.; Lawler, Damian

doi:10.1002/j.1477-8696.1981.tb05400.x

Cited by 358 publications

(350 citation statements)

References 6 publications

(4 reference statements)

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“…One of these is the sequential variability introduced for the case of 1 min rainfall in storms (Conrad and Pollack, 1962;Huff, 1970). In the case of very different time scales, as with monthly amounts, Walsh and Lawler (1981) proposed a seasonal rainfall index, similar to the one previously used by Ayoade (1970). In our case, we accept a concept similar to entropy (Martín-Vide, 1984, 1987Burgueño, 1989Burgueño, , 1993.…”

Section: Temporal Irregularity Indexmentioning

confidence: 85%

“…A debatable issue is how to define a threshold level for the temporal irregularity beyond which a series can be considered irregular in time. An attempt was made by Walsh and Lawler (1981), who introduced a set of empirical classes for their seasonal index that ranged from 0 (all months with equal rainfall) to 1.83 (all the annual rainfall concentrated in a month). In our case, certain classes were also introduced, although averaged deviations between two consecutive elements of a series had to be represented.…”

Section: Temporal Irregularity Indexmentioning

confidence: 99%

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Spatial and temporal variability of the daily rainfall regime in Catalonia (northeastern Spain), 1950–2000

Lana

Martínez

Serra

et al. 2004

Intl Journal of Climatology

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Spatial and temporal patterns in the daily rainfall regime of Catalonia (northeastern Spain) recorded for the 1950-2000 period are analysed from several points of view, including the irregularity of the time series in terms of entropy, the Mann-Kendall test for time trends, a principal component analysis (PCA), an average linkage (AL) clustering algorithm and, finally, a power spectrum analysis, which includes a comparison of white-noise and Markovian red-noise hypotheses. The analyses are based on three monthly variables derived from the amounts recorded on a daily basis: the average daily rainfall and the standard deviation of the daily rainfall for each month, together with the corresponding coefficient of variation. The joint spatial-temporal variability is manifested by the irregularity index, which is characterized by relevant values in all cases and gradients from the north (Pyrenees and Pre-Pyrenees mountain ranges) to the south (Ebro Valley) and to the Mediterranean coast. The interpretation of the factor scores derived from the PCA and of the clusters obtained from the AL algorithm also describes the complex spatial distribution of the daily rainfall regime, given that the effects of atmospheric circulation patterns on rainfall regimes are conditioned by the complex orography of Catalonia and its proximity to the Mediterranean Sea. The factor loadings associated with the PCA also suggest a distinction between hot, cold and mild seasons. Finally, it is worth noting that monthly series are usually accompanied by white background noise and, in a few cases, signs of Markovian behaviour and some significant periodicities, which are generally of less than 10 months and which change from one cluster to another.

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Section: Temporal Irregularity Indexmentioning

confidence: 85%

Section: Temporal Irregularity Indexmentioning

confidence: 99%

Spatial and temporal variability of the daily rainfall regime in Catalonia (northeastern Spain), 1950–2000

Lana

Martínez

Serra

et al. 2004

Intl Journal of Climatology

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“…Here we use the seasonality index (SI) proposed by Walsh and Lawler (1981) to quantify the wind speeds seasonality in China:…”

Section: Methodsmentioning

confidence: 99%

Wind speed trends over China: quantifying the magnitude and assessing causality

Chen

Pryor

2012

Intl Journal of Climatology

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ABSTRACT:Temporal trends in 10-m wind speeds from homogeneous observational data sets from 540 weather stations and reanalysis data sets are quantified and compared. Also, possible physical cause of inconsistencies between the data sets and temporal trends and variability in wind speeds are investigated. Annual mean wind speeds from the observational data exhibit pronounced downward trends especially in the upper percentiles and during spring. The NCEP/NCAR reanalysis reproduces the observed wind speeds, seasonality and temporal trends better than the ERA-40 even though it shows larger interannual fluctuations. The warm and cold AO and ENSO phases have significant influence on probability distribution of wind speeds, thus internal climate variability is a major source of both interannual and long-term variability.

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“…The seasonality index of precipitation (SI) is designed to assess the degree of variability in monthly rainfall throughout the year [26]. It is defined as follows:…”

Section: Precipitation Heterogeneity Indexesmentioning

confidence: 99%

Spatial and Temporal Variations of Precipitation Extremes and Seasonality over China from 1961~2013

Tao

Wang

Song

et al. 2018

Water

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Using the 0.5 • × 0.5 • gridded Chinese ground precipitation dataset from 1961-2013, spatial and temporal variations in precipitation extremes, total precipitation, the seasonality of precipitation and their linkages in the context of climate change are investigated using the Mann-Kendall trend test, Pettitt change-point test and correlation analysis. The investigation focuses on four extreme indices, i.e., the annual maximum number of consecutive dry days (CDD), the annual maximum number of consecutive wet days (CWD), the annual total precipitation when daily precipitation is greater than 95th percentile (R95pTOT), and the maximum 1-day precipitation (RX1day). The results show that precipitation extremes increased in northwestern China, especially Xinjiang, Tibet and Qinghai (CWD, R95pTOT and RX1day), and scattered parts of southeastern China (R95pTOT and RX1day), but decreased over considerable parts of southwestern China (CWD) and some small parts of northern China (CWD, R95pTOT and RX1day); the spatial patterns of the trends in precipitation extremes and that of total precipitation exhibit considerable similarity over China, which indicates the close relationship between changes in precipitation extremes and total precipitation; change points are detected in different periods ranging from early 1970s to early 2000s for different regions and extreme precipitation indices, and the spatial patterns of the abrupt changes of extreme indices are similar to those of the trends in extreme indices; the concentration index (CI) is strongly positively correlated with R95pTOT and RX1day in most areas in northern China (from the northeast to the northwest) and southwestern China (including Sichuan, Chongqing Guizhou and Guangxi), which means for these regions, the temporal heterogeneity of daily precipitation over a year is dominated by heavy rainfall amounts. The seasonality index of precipitation (SI) is positively related to R95pTOT and RX1day over most areas above 30 • N, indicating that heavy precipitation events have a better chance to occur in places with a strong seasonal variation in annual precipitation in these areas, but for most areas below 30 • N, the positive relationship is not significant.

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Rainfall Seasonality: Description, Spatial Patterns and Change Through Time

Cited by 358 publications

References 6 publications

Spatial and temporal variability of the daily rainfall regime in Catalonia (northeastern Spain), 1950–2000

Spatial and temporal variability of the daily rainfall regime in Catalonia (northeastern Spain), 1950–2000

Wind speed trends over China: quantifying the magnitude and assessing causality

Spatial and Temporal Variations of Precipitation Extremes and Seasonality over China from 1961~2013

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