2011
DOI: 10.1007/s00704-011-0527-4
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Decadal oscillations in rainfall and air temperature in the Paute River Basin—Southern Andes of Ecuador

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Cited by 46 publications
(35 citation statements)
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“…1; Mejia et al, 1996). Given the strong topographic gradients in the basin, it is possible that this method leads to a systematic bias as rainfall amounts in the area are known to increase with altitude (Mora and Willems, 2012). However, even if this would be the case, the data can still be used to assess temporal trends in rainfall amounts.…”
Section: Time Series Of Land Cover Datamentioning
confidence: 98%
“…1; Mejia et al, 1996). Given the strong topographic gradients in the basin, it is possible that this method leads to a systematic bias as rainfall amounts in the area are known to increase with altitude (Mora and Willems, 2012). However, even if this would be the case, the data can still be used to assess temporal trends in rainfall amounts.…”
Section: Time Series Of Land Cover Datamentioning
confidence: 98%
“…In the study area, the usefulness of the QPM has been demonstrated by Mbungu et al (2012), Moges et al (2014), Nyeko-Ogiramoi et al (2013), Onyutha and Willems (2014a, b), and Willems (2011, 2012) but limited to specific catchments in the Nile Basin. Outside the study area, this method was also applied by Willems (2013) for rainfall extremes in Europe, and Mora and Willems (2012) for the Andes region of Ecuador. The shortcomings of the above recent studies that applied the QPM on the rainfall variability of the Nile Basin as addressed in this study include (1) lack of attempts to investigate any possible linkages of the rainfall variability to ocean-atmosphere interactions by Mbungu et al (2012) and Onyutha and Willems (2014a, b); (2) the use of few climate indices or series to explain rainfall variability by Moges et al (2014), Nyeko-Ogiramoi et al (2013), and Taye and Willems (2012); and (3) the limitation of the variability study to sub-catchments of the Nile Basin.…”
Section: Introductionmentioning
confidence: 99%
“…This study used a length of 12 years, which allowed the identification of high and low inter-annual anomalies. Other authors, e.g., Torrence and Webster [61], Mora and Willems [62], and Villazon [42], found similar times for the SOI decadal oscillation period.…”
Section: Climate Variability and Trendsmentioning
confidence: 58%
“…The QPM climate anomaly is then defined as the mean ratio of the quantile derived from the subseries over the corresponding quantile (for the same exceedance probability) from the reference series, and for all quantiles or exceedance probabilities above the given threshold. Figure 2 shows the different steps in the estimation of the climate anomaly [53,54,62]: (1) Generate subseries with a length of L years from the reference series. (2) Extract independent values from each subseries and from the reference series; in this study, annual mean values are considered; these values are ranked from the highest to the lowest value, where i is the rank order.…”
Section: Climate Variability and Trendsmentioning
confidence: 99%
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