Articles | Volume 14, issue 2
Geosci. Model Dev., 14, 1007–1035, 2021
https://doi.org/10.5194/gmd-14-1007-2021
Geosci. Model Dev., 14, 1007–1035, 2021
https://doi.org/10.5194/gmd-14-1007-2021

Methods for assessment of models 23 Feb 2021

Methods for assessment of models | 23 Feb 2021

Understanding the development of systematic errors in the Asian summer monsoon

Gill M. Martin et al.

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Cited articles

Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., Arkin, P., and Nelkin, E.: The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–present), J. Hydrometeorol., 4, 1147–1167, 2003. 
Amaya, D. J., Kosaka, Y., Zhou, W., Zhang, Y., Xie, S., and Miller, A. J.: The North Pacific Pacemaker Effect on Historical ENSO and Its Mechanisms, J. Climate, 32, 7643–7661, https://doi.org/10.1175/JCLI-D-19-0040.1, 2019. 
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011. 
Blockley, E. W., Martin, M. J., McLaren, A. J., Ryan, A. G., Waters, J., Lea, D. J., Mirouze, I., Peterson, K. A., Sellar, A., and Storkey, D.: Recent development of the Met Office operational ocean forecasting system: an overview and assessment of the new Global FOAM forecasts, Geosci. Model Dev., 7, 2613–2638, https://doi.org/10.5194/gmd-7-2613-2014, 2014. 
Bowler, N., Arribas, A., Beare, S., Mylne, K. E., and Shutts, G.: The local ETKF and SKEB: Upgrades to the MOGREPS short-range ensemble prediction system, Q. J. Roy. Meteor. Soc., 135, 767–776, 2009. 
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Short summary
Our study highlights a number of different techniques that can be employed to investigate the sources of model error. We demonstrate how this methodology can be used to identify the regions and model components responsible for the development of long-standing errors in the Asian summer monsoon. Once these are known, further work can be done to explore the local processes contributing to this behaviour and their sensitivity to changes in physical parameterisations and/or model resolution.