A distributional multivariate approach for assessing performance of climate-hydrology models.

ABSTRACT: One of the ultimate goals of climate studies is to provide projections of future scenarios: for this purpose, sophisticated models are conceived, involving lots of parameters calibrated via observed data. The outputs of such models are used to investigate the impacts on related phenomena such as floods, droughts, etc. To evaluate the performance of such models, statistics like moments/quantiles are used, and comparisons with historical data are carried out. However, this may not be enough: correct estimates of some moments/quantiles do not imply that the probability distributions of observed and simulated data match. In this work, a distributional multivariate approach is outlined, also accounting for the fact that climate variables are often dependent. Suitable statistical tests are descr

SUBMITTER: Vezzoli R 

PROVIDER: S-EPMC5608904 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature