Vezzoli Renata, Salvadori Gianfausto, De Michele Carlo
Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), Regional Models and geo-Hydrological Impacts Division (REMHI), Capua (CE), I-81043, Italy.
Università del Salento, Dipartimento di Matematica e Fisica, Lecce, I-73100, Italy.
Sci Rep. 2017 Sep 21;7(1):12071. doi: 10.1038/s41598-017-12343-1.
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 described, providing a non-parametric assessment exploiting the Copula Theory. These procedures allow to understand (i) whether the models are able to reproduce the distributional features of the observations, and (ii) how the models perform (e.g., in terms of future climate projections and changes). The proposed methodological approach is appropriate also in contexts different from climate studies, to evaluate the performance of any model of interest: methods to check a model per se are sketched out, investigating whether its outcomes are (statistically) consistent.
为此，人们构思了复杂的模型，其中涉及许多通过观测数据校准的参数。此类模型的输出用于研究对洪水、干旱等相关现象的影响。为了评估此类模型的性能，人们使用矩/分位数等统计量，并与历史数据进行比较。然而，这可能还不够：某些矩/分位数的正确估计并不意味着观测数据和模拟数据的概率分布相匹配。在这项工作中，概述了一种分布多元方法，同时考虑到气候变量通常是相关的这一事实。描述了合适的统计检验，提供了一种利用Copula理论的非参数评估。这些程序能够理解：（i）模型是否能够再现观测值的分布特征，以及（ii）模型的表现如何（例如，在未来气候预测和变化方面）。所提出的方法在不同于气候研究的背景下也适用，以评估任何感兴趣模型的性能：勾勒出检查模型本身的方法，研究其结果是否（在统计上）一致。
