Articles | Volume 12, issue 2
https://doi.org/10.5194/gmd-12-735-2019
https://doi.org/10.5194/gmd-12-735-2019
Methods for assessment of models
 | 
19 Feb 2019
Methods for assessment of models |  | 19 Feb 2019

Similarities within a multi-model ensemble: functional data analysis framework

Eva Holtanová, Thomas Mendlik, Jan Koláček, Ivanka Horová, and Jiří Mikšovský

Related authors

Historical changes in drought characteristics and its impact on vegetation cover over Madagascar
Herijaona Hani-Roge Hundilida Randriatsara, Eva Holtanova, Karim Rizwan, Hassen Babaousmail, Mirindra Finaritra Tanteliniaina Rabezanahary, Kokou Romaric Posset, Donnata Alupot, and Brian Odhiambo Ayugi
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-191,https://doi.org/10.5194/nhess-2024-191, 2024
Preprint under review for NHESS
Short summary
Imprints of climate forcings in global gridded temperature data
Jiří Mikšovský, Eva Holtanová, and Petr Pišoft
Earth Syst. Dynam., 7, 231–249, https://doi.org/10.5194/esd-7-231-2016,https://doi.org/10.5194/esd-7-231-2016, 2016
Short summary
Novel indices for the comparison of precipitation extremes and floods: an example from the Czech territory
M. Müller, M. Kašpar, A. Valeriánová, L. Crhová, E. Holtanová, and B. Gvoždíková
Hydrol. Earth Syst. Sci., 19, 4641–4652, https://doi.org/10.5194/hess-19-4641-2015,https://doi.org/10.5194/hess-19-4641-2015, 2015
Short summary

Related subject area

Atmospheric sciences
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024,https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024,https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary
Observational operator for fair model evaluation with ground NO2 measurements
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024,https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024,https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024,https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary

Cited articles

Annan, J. D. and Hargreaves, J. C.: On the meaning of independence in climate science, Earth Syst. Dynam., 8, 211–224, https://doi.org/10.5194/esd-8-211-2017, 2017. 
Belda, M., Holtanová, E., Kalvová, J., and Halenka, T.: Global warming-induced changes in climate zones based on CMIP5 projections, Clim. Res., 71, 17–31, https://doi.org/10.3354/cr01418, 2017. 
Christensen, J. H. and Christensen, O. B.: A summary of the PRUDENCE model projections of changes in European climate during this century, Clim. Change, 81(Supp. 1), 7–30, https://doi.org/10.1007/s10584-006-9210-7, 2007. 
Craven, P. and Wahba, G.: Smoothing noisy data with spline functions, Numerische Mathematik, 31, 377–403, 1978. 
Crhová, L. and Holtanová, E.: Simulated relationship between air temperature and precipitation over Europe: sensitivity to the choice of RCM and GCM, Int. J. Clim., 38, 1595–1604, https://doi.org/10.1002/joc.5256, 2018. 
Download
Short summary
We present a methodological framework for the analysis of climate model uncertainty based on the functional data analysis approach, an emerging statistical field. The novel method investigates the multi-model spread, taking into account the behavior of entire simulated climatic time series, encompassing both past and future periods. We also introduce an innovative way of visualizing climate model similarities based on a network spatialization algorithm that enables an unambiguous interpretation.