title: Scaling of extreme rainfall areas at a planetary scale.
abstract: Event magnitude and area scaling relationships for rainfall over different regions of the world have been presented in the literature for relatively short durations and over relatively small areas. In this paper, we present the first ever results on a global analysis of the scaling characteristics of extreme rainfall areas for durations ranging from 1 to 30 days. Broken power law models are fit in each case. The past work has been focused largely on the time and space scales associated with local and regional convection. The work presented here suggests that power law scaling may also apply to planetary scale phenomenon, such as frontal and monsoonal systems, and their interaction with local moisture recycling. Such features may have persistence over large areas corresponding to extreme rain and regional flood events. As a result, they lead to considerable hazard exposure. A caveat is that methods used for empirical power law identification have difficulties with edge effects due to finite domains. This leads to problems with robust model identification and interpretability of the underlying relationships. We use recent algorithms that aim to address some of these issues in a principled way. Theoretical research that could explain why such results may emerge across the world, as analyzed for the first time in this paper, is needed.
authors.affiliation: Department of Civil Engineering, The City University of New York (City College), New York, New York 10031, USA.
authors.forename: Naresh
authors.initials: N
authors.lastname: Devineni
authors.affiliation: Department of Earth and Environmental Engineering, Columbia University, New York, New York 10027, USA.
authors.forename: Upmanu
authors.initials: U
authors.lastname: Lall
authors.affiliation: Bureau of Hydrology, Changjiang Water Resources Commission, Wuhan 430010, China.
authors.forename: Chen
authors.initials: C
authors.lastname: Xi
authors.affiliation: Institute for Environmental Studies (IVM), VU University, Amsterdam, De Boelelaan 1087, 1081 HV Amsterdam, The Netherlands.
authors.forename: Philip
authors.initials: P
authors.lastname: Ward
mesh_terms: D003198:Computer Simulation; D004190:Disasters / Q000706:statistics & numerical data*; D018534:Earth, Planet; D004784:Environmental Monitoring / Q000379:methods / Q000706:statistics & numerical data*; D055868:Floods / Q000706:statistics & numerical data*; D015233:Models, Statistical; D011891:Rain