A coupled earth system model (ESM) has been developed at the Nanjing University of Information Science and Technology (NUIST) by using version 5.3 of the European Centre Hamburg Model (ECHAM), version 3.4 of the Nucleus for European Modelling of the Ocean (NEMO), and version 4.1 of the Los Alamos sea ice model (CICE). The model is referred to as NUIST ESM1 (NESM1). Comprehensive and quantitative metrics are used to assess the model's major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model's assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring-fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific (CP)-ENSO and eastern Pacific (EP)-ENSO; however, the equatorial SST variability, biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden-Julian Oscillation (MJO), and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version (T159) demonstrates improved simulation with respect to the climatology, interannual variance, monsoon-ENSO lead-lag correlation, spatial structures of the leading mode of the Asian-Australian monsoon rainfall variability, and the eastward propagation of the MJO.Key words: coupled climate model, earth system model, climate variability Citation: Cao, J., and Coauthors, 2015: Major modes of short-term climate variability in the newly developed NUIST Earth System Model (NESM).

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The ensemble technique is considered to be an effective approach in enhancing the model capacity of intra-seasonal climate change. Since El Niño-Southern Oscillation is one of the critical modes of interannual variability in the tropical Pacific, an appropriate ensemble technique may help minimize model bias in ENSO forecast. This research includes a modified stochastically perturbed parameterization tendencies scheme in the Community Earth System Model to investigate its impact on ENSO prediction. This revised scheme uses independent noise patterns to perturb the tendencies from different physical parameterizations. In the original scheme, only the same noise is employed. The result suggests that the altered approach is in a position to further reduce sea surface temperatures and gain more skill in uncertainty estimation compared to the original one. ENSO’s amplitude is improved especially of its warm phase El Niño, but there is a limited improvement in its spatial structure. The modified scheme also ameliorated the variability of ENSO by increasing the magnitude toward observation. The power spectrum exhibits an increased representation. Besides those findings, we notice that simple ensemble mean may not be able to represent the climate status as it smoothes out some useful signals.