An R package to visualize and communicate uncertainty in seasonal climate prediction

被引：25

作者：

Frias, M. D. ^{[1
]}

Iturbide, M. ^{[2
]}

Manzanas, R. ^{[2
]}

Bedia, J. ^{[1
]}

Fernandez, J. ^{[1
]}

Herrera, S. ^{[1
]}

Cofino, A. S. ^{[1
]}

Gutierrez, J. M. ^{[2
]}

机构：

[1] Univ Cantabria, Dept Mat Aplicada & Ciencias Comp, Grp Meteorol, Avda Castros S-N, E-39005 Santander, Spain

[2] Univ Cantabria, CSIC, Inst Fis Cantabria IFCA, Grp Meteorol, Avda Castros S-N, E-39005 Santander, Spain

来源：

ENVIRONMENTAL MODELLING & SOFTWARE | 2018年 / 99卷

关键词：

visualizeR; Probabilistic visualization; Seasonal forecast; R; PROBABILISTIC FORECASTS; PRECIPITATION FORECASTS; VERIFICATION; PREDICTABILITY; RECALIBRATION; EVENTS; SKILL; ENSO;

D O I：

10.1016/j.envsoft.2017.09.008

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Interest in seasonal forecasting is growing fast in many environmental and socio-economic sectors due to the huge potential of these predictions to assist in decision making processes. The practical application of seasonal forecasts, however, is still hampered to some extent by the lack of tools for an effective communication of uncertainty to non-expert end users. visualizeR is aimed to fill this gap, implementing a set of advanced visualization tools for the communication of probabilistic forecasts together with different aspects of forecast quality, by means of perceptual multivariate graphical displays (geographical maps, time series and other graphs). These are illustrated in this work using the example of the strong El Nino 2015/16 event forecast. The package is part of the climate4R bundle providing transparent access to the ECOMS-UDG climate data service. This allows a flexible application of visualizeR to a wide variety of specific seasonal forecasting problems and datasets. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：101 / 110

页数：10