Preserving low-frequency variability in generated daily rainfall sequences
By Rajeshwar Mehrotra, Ashish Sharma. 2007
82 citations recorded by the source corpus.
Subfields: Global and Planetary Change, Soil Science
View Paper: https://www.semanticscholar.org/paper/56661712ca7083808544869249533334a764df1f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Global and Planetary Change
- Vijay P. Singh
- András Bárdossy
- Anne-Catherine Favre
- Guillaume Évin
- B. Hingray
- Anshuman Mishra
- Fabio Oriani
- Julien Straubhaar
In Soil Science
- Anne-Catherine Favre
- András Bárdossy
- Fabio Oriani
- Julien Straubhaar
- Philippe Renard
- Gregoire Mariethoz
- Chao Li
- Vijay P. Singh
Citations in the corpus
- Simulation of rainfall time series from different climatic regions using the direct sampling technique (2014, background): “…(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, b) as conditional variables for the estimation of the MC parameters.”
- A bivariate mixed distribution with a heavy‐tailed component and its application to single‐site daily rainfall simulation (2013, methodology): “This model was then adjusted and incorporated into other multisite rainfall simulation and downscaling models [Mehrotra and Sharma, 2005, 2007a, 2007b, 2010; Mehrotra et al., 2012].”
- Stochastic generation of multi-site daily precipitation focusing on extreme events (2018, background): “While nonparametric densities with Gaussian kernels (Mehrotra and Sharma, 2007a, 2010) offer the flexibility of fitting the observed range of precipitation amounts, their tail also belongs to the domain of attraction of the Gumbel distribution and suffers from the same drawbacks.”
- Copula based multisite model for daily precipitation simulation (2009, methodology): “Mehrotra et al.(2006) compared three multi-site stochastic weather generators, including (i) a parametric hidden Markov model (HMM), (ii) the Srikanthan(2005) multi-site stochastic precipitation generation model proposed by Wilks (1998) and (iii) a non-parametric K-nearest neighbour (KNN) model, con”