scholarly journals Investigating Interannual Variability of Precipitation at the Global Scale: Is There a Connection with Seasonality?

2012 ◽  
Vol 25 (16) ◽  
pp. 5512-5523 ◽  
Author(s):  
S. Fatichi ◽  
V. Yu. Ivanov ◽  
E. Caporali

Abstract Interannual variability of precipitation can directly or indirectly affect many hydrological, ecological, and biogeochemical processes that, in turn, influence climate. Despite the significant importance of the phenomenon, few studies have attempted to elucidate spatial patterns of this variability at the global scale. This study uses land gauge precipitation records of the Global Historical Climatology Network, version 2, as well as reanalysis data to provide an assessment of the spatial organization of characteristics of precipitation interannual variability. The coefficient of variation, skewness, and short- and long-range dependence of the precipitation variability are analyzed. Among the major inferences is that the coefficient of variation of annual precipitation shows a significant correlation with intra-annual seasonality. Specifically, subyearly precipitation anomalies occurring in locations with pronounced seasonality affect the total yearly amount, imposing a higher variability in the annual precipitation fluctuations. Furthermore, the study illustrates that a positive skewness of the distribution of annual precipitation is a robust property worldwide and its magnitude is related to the coefficient of variation. Additionally, annual precipitation exhibits very weak small-lag autocorrelation. Conversely, the intensity of long-memory–long-range dependence is significantly larger than zero, hinting that organized long-term variations are an important feature of the interannual variability of precipitation.

Hydrology ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 177
Author(s):  
Panayiotis Dimitriadis ◽  
Aristoteles Tegos ◽  
Demetris Koutsoyiannis

The stochastic structures of potential evaporation and evapotranspiration (PEV and PET or ETo) are analyzed using the ERA5 hourly reanalysis data and the Penman–Monteith model applied to the well-known CIMIS network. The latter includes high-quality ground meteorological samples with long lengths and simultaneous measurements of monthly incoming shortwave radiation, temperature, relative humidity, and wind speed. It is found that both the PEV and PET processes exhibit a moderate long-range dependence structure with a Hurst parameter of 0.64 and 0.69, respectively. Additionally, it is noted that their marginal structures are found to be light-tailed when estimated through the Pareto–Burr–Feller distribution function. Both results are consistent with the global-scale hydrological-cycle path, determined by all the above variables and rainfall, in terms of the marginal and dependence structures. Finally, it is discussed how the existence of, even moderate, long-range dependence can increase the variability and uncertainty of both processes and, thus, limit their predictability.


2018 ◽  
Vol 111 ◽  
pp. 301-318 ◽  
Author(s):  
Hristos Tyralis ◽  
Panayiotis Dimitriadis ◽  
Demetris Koutsoyiannis ◽  
Patrick Enda O'Connell ◽  
Katerina Tzouka ◽  
...  

2018 ◽  
Vol 556 ◽  
pp. 891-900 ◽  
Author(s):  
Theano Iliopoulou ◽  
Simon Michael Papalexiou ◽  
Yannis Markonis ◽  
Demetris Koutsoyiannis

2020 ◽  
Vol 57 (4) ◽  
pp. 1234-1251
Author(s):  
Shuyang Bai

AbstractHermite processes are a class of self-similar processes with stationary increments. They often arise in limit theorems under long-range dependence. We derive new representations of Hermite processes with multiple Wiener–Itô integrals, whose integrands involve the local time of intersecting stationary stable regenerative sets. The proof relies on an approximation of regenerative sets and local times based on a scheme of random interval covering.


Author(s):  
Jan Beran ◽  
Britta Steffens ◽  
Sucharita Ghosh

AbstractWe consider nonparametric regression for bivariate circular time series with long-range dependence. Asymptotic results for circular Nadaraya–Watson estimators are derived. Due to long-range dependence, a range of asymptotically optimal bandwidths can be found where the asymptotic rate of convergence does not depend on the bandwidth. The result can be used for obtaining simple confidence bands for the regression function. The method is illustrated by an application to wind direction data.


2006 ◽  
Vol 16 (18) ◽  
pp. 1331-1338 ◽  
Author(s):  
Christos Christodoulou-Volos ◽  
Fotios M. Siokis

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