A nonparametric model for stochastic generation of daily rainfall amounts

By T. Harrold, Ashish Sharma, Simon J. Sheather. 2003

82 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/42053363bf0eeaf30caa07bf329af22e3b77ff07

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

1. Balaji Rajagopalan
2. William Kleiber
3. R. Katz
4. Andrew Verdin
5. J. Beersma
6. E. Zagona
7. T. Fulp
8. J. Prairie

In Ocean Engineering

1. William Kleiber
2. Balaji Rajagopalan
3. Andrew Verdin
4. R. Katz

Citations in the corpus

• Modified K-NN Model for Stochastic Streamflow Simulation (2006, methodology): “These approaches have also been successfully applied to rainfall modeling Lall et al. 1996; Harrold et al. 2003b; flood frequency Lall et al. l993; Moon and Lall 1994; groundwater applications Adamoski and Feluch 1991; and streamflow forecasting Smith 1991.”
• Coupled stochastic weather generation using spatial and generalized linear models (2015, background): “Kernel density-based generators of precipitation (Lall and Sharma 1996; Harrold et al. 2003; Mehrotra and Sharma 2007) and other variables (Rajagopalan et al. 1997a, b) have been shown to perform very well at capturing non-normal and nonlinear features.”
• Joint probability of precipitation and discharge deficits in the Netherlands (2004, background): “The latter is necessary to reproduce longer-term variability [e.g., Harrold et al., 2003a, 2003b].”