Non-stationary extreme value analysis in a changing climate

By Linyin Cheng, Amir Aghakouchak, Eric Gilleland, R. Katz. Climatic Change, 2014

509 citations recorded by the source corpus.

Subfields: Finance, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/6f9238d97e70cfd8136b9824d3af5e69befdf5f7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Finance

1. Giovanni Besio
2. C. Bracken
3. N. V. Umamahesh
4. Luc Feyen
5. L. Alfieri
6. S. E. Debele
7. Michalis I. Vousdoukas
8. Upmanu Lall

In Global and Planetary Change

1. S. E. Debele
2. E. Bogdanowicz
3. N. V. Umamahesh
4. V. Agilan
5. Giovanni Besio
6. C. Bracken
7. Luc Feyen
8. L. Alfieri

Citations in the corpus

• A Bayesian Hierarchical Approach to Multivariate Nonstationary Hydrologic Frequency Analysis (2018, methodology): “…setting when the GEV parameters may be time varying, the return level can be computed in each year, which is known as the effective return level (Cheng et al., 2014) qpðtÞ5lðtÞ1 rðtÞ nðtÞ ½ð2log pÞ 2nðtÞ21 (18) In the case of nonstationary GEV parameters, a stationary return level can be…”
• A hierarchical Bayesian GEV model for improving local and regional flood quantile estimates (2016, background): “The traditional assumption of stationarity in such analyses has been relaxed by explicitly modeling the time variation of the parameters (Kwon et al., 2008; Villarini et al., 2010; Villarini et al., 2009; Cunderlik and Burn, 2003; Cheng et al., 2014; Towler et al., 2010; Lima et al., 2015).”
• Modelling nonlinear trend for developing non‐stationary rainfall intensity–duration–frequency curve (2017, methodology): “In this study, the low-risk (more conservative) approach (Cheng et al., 2014) is used to calculate location parameter value, i.”
• A comparison of three approaches to non-stationary flood frequency analysis (2017, methodology): “, quantile regression methods (Koenker 2005) or Bayesian hierarchical estimation (Cheng et al. 2014; Yan and Moradkhani 2015, 2016).”
• The transformed-stationary approach: a generic and simplified methodology for non-stationary extreme value analysis (2016, methodology): “4, the TS methodology has advantages over SS (e.g. Vousdoukas et al. 2016) and EM (e.g. Cheng et al., 2014; Gilleland and Katz, 2015; Izaguirre et al., 2011; Méndez et al., 2006; Menéndez et al., 2009; Mudersbach and Jensen, 30 2010; Russo et al., 2014; Sartini et al., 2015), both in terms of…”