Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 15, issue 2
Articles | Volume 15, issue 2
https://doi.org/10.5194/gmd-15-535-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-535-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 2
Methods for assessment of models
 | 
25 Jan 2022
Methods for assessment of models |  | 25 Jan 2022

A method for assessment of the general circulation model quality using the K-means clustering algorithm: a case study with GETM v2.5

Urmas Raudsepp and Ilja Maljutenko

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Cited articles

Argo: Argo float data and metadata from Global Data Assembly Centre (Argo GDAC) – Snapshot of Argo GDAC of August 10st 2020, SEANOE [data set], https://doi.org/10.17882/42182#76230, 2020. 
Bholowalia, P. and Kumar, A.: EBK-means: A clustering technique based on elbow method and K-means in WSN, International Journal of Computer Applications, 105, 17–24, 2014. 
Burchard, H. and Bolding, K.: GETM – a general estuarine transport model, scientific documentation, Tech. Rep. EUR 20253 EN, European Commission (220), 2002. 
Celebi, M. E., Kingravi, H. A., and Vela, P. A.: A comparative study of efficient initialization methods for the K-means clustering algorithm, Expert Syst. Appl., 40, 200–210, https://doi.org/10.1016/j.eswa.2012.07.021, 2013. 
CMEMS: CMEMS-PQ-StrategicPlan, available at: https://marine.copernicus.eu/sites/default/files/wp-content/uploads/2017/03/CMEMS-PQ-StrategicPlan-v1.6-1.pdf (last acess: 18 February 2021), 2016. 
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A model's ability to reproduce the state of a simulated object is always a subject of discussion. A new method for the multivariate assessment of numerical model skills uses the K-means algorithm for clustering model errors. All available data that fall into the model domain and simulation period are incorporated into the skill assessment. The clustered errors are used for spatial and temporal analysis of the model accuracy. The method can be applied to different types of geoscientific models.
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