Journal
INTERNATIONAL JOURNAL OF CLIMATOLOGY
Volume 42, Issue 14, Pages 7087-7102Publisher
WILEY
DOI: 10.1002/joc.7631
Keywords
CMIP6; evaporation; inter-model spread; moisture flux; precipitation; Southeast Asia
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This study evaluated the performance of climate precipitation in Southeast Asia using an ensemble of 48 global climate models. The models were able to reproduce monsoonal features, but overestimated precipitation in certain areas. The moisture budget analysis indicated that dynamic convergence was the dominant factor contributing to model bias and inter-model uncertainty. The study also found that models with higher resolutions performed better. The evaluation provided useful insights into rainfall mechanisms and could inform future high-resolution downscaling experiments.
This study evaluated the performance of the climatological precipitation over Southeast Asia using an ensemble of 48 global climate models/earth system models from the sixth phase of Coupled Model Intercomparison Project (CMIP6) suite of experiments. Multi-source observational data sets were used to evaluate the historical simulation data of the CMIP6 ensembles towards the semi-year mean of precipitation during November-April (NDJFMA) and May-October (MJJASO). The results indicate that the CMIP6 models were able to reproduce the large-scale monsoonal features. Precipitation is overestimated over most eastern ocean areas in NDJFMA and over most areas in MJJASO. In terms of the ensemble bias and inter-model uncertainty, the diagnosis of moisture budget indicates the dominant item is the dynamic convergence and the other important items have dynamic advection and evaporation. The main types of pattern bias were examined through the inter-model empirical orthogonal function analysis, which is correlated with the global sea surface temperature and moisture flux. The climatological evaluation yielded a higher pattern correlation and a lower root-mean square error in NDJFMA than MJJASO. Most of the models have greater standard deviations among the spatial grids than observations, especially in NDJFMA. The models with higher resolutions showed a better performance than those with lower resolutions. A model performance index is defined for the convenient comparison, the best three models are CNRM-CM6-1, EC-Earth3-Veg and NorESM2-MM, and the worst three are INM-CM4-8, AWI-ESM-1-1-LR and MCM-UA-1-0. This evaluation study provided useful analytics in understanding model behaviour and processes related to rainfall mechanisms which could be further examined in high-resolution downscaling experiments in future studies.
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