Articles | Volume 14, issue 1
https://doi.org/10.5194/gmd-14-73-2021
https://doi.org/10.5194/gmd-14-73-2021
Model experiment description paper
 | 
07 Jan 2021
Model experiment description paper |  | 07 Jan 2021

A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales

Hsi-Yen Ma, Chen Zhou, Yunyan Zhang, Stephen A. Klein, Mark D. Zelinka, Xue Zheng, Shaocheng Xie, Wei-Ting Chen, and Chien-Ming Wu

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Cited articles

Adames, Á, F. and Kim, D.: The MJO as a Dispersive, Convectively Coupled Moisture Wave: Theory and Observations, J. Atmos. Sci., 73, 913–941, https://doi.org/10.1175/JAS-D-15-0170.1, 2016. 
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-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. 
Ahn, M.-S., Kim, D., Sperber, K. R., Kang, I.-S., Maloney, E., Waliser, D., and Hendon, H.: MJO simulation in CMIP5 climate models: MJO skill metrics and process-oriented diagnosis, Clim. Dynam., 49, 4023–4045, https://doi.org/10.1007/s00382-017-3558-4, 2017. 
Barton, N. P., Klein, S. A., Boyle, J. S., and Zhang, Y.: Arctic synoptic regimes: Comparing domain-wide Arctic cloud observations with CAM4 and CAM5 during similar dynamics, J. Geophys. Res., 117, D15205, https://doi.org/10.1029/2012JD017589, 2012. 
Barton, N. P., Klein, S. A., and Boyle, J. S.: On the contribution of longwave radiation to global climate model biases in Arctic lower tropospheric stability, J. Climate, 27, 7250–7269, https://doi.org/10.1175/JCLI-D-14-00126.1, 2014. 
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Short summary
We propose an experimental design of a suite of multi-year, short-term hindcasts and compare them with corresponding observations or measurements for periods based on different weather and climate phenomena. This atypical way of evaluating model performance is particularly useful and beneficial, as these hindcasts can give scientists a robust picture of modeled precipitation, and cloud and radiation processes from their diurnal variation to year-to-year variability.