Comparison of CMIP5 and CMIP6 Multi-Model Ensemble for Precipitation Downscaling Results and Observational Data: The Case of Hanjiang River Basin

Dong Wang,Jiahong Liu,Weiwei Shao,Hao Wang,Xin Su,Chao Mei

doi:10.3390/atmos12070867

Dong Wang, Jiahong Liu + Show 4 more

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https://doi.org/10.3390/atmos12070867

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Abstract

Evaluating global climate model (GCM) outputs is essential for accurately simulating future hydrological cycles using hydrological models. The GCM multi-model ensemble (MME) precipitation simulations of the Climate Model Intercomparison Project Phases 5 and 6 (CMIP5 and CMIP6, respectively) were spatially and temporally downscaled according to a multi-site statistical downscaling method for the Hanjiang River Basin (HRB), China. Downscaled precipitation accuracy was assessed using data collected from 14 meteorological stations in the HRB. The spatial performances, temporal performances, and seasonal variations of the downscaled CMIP5-MME and CMIP6-MME were evaluated and compared with observed data from 1970–2005. We found that the multi-site downscaling method accurately downscaled the CMIP5-MME and CMIP6-MME precipitation simulations. The downscaled precipitation of CMIP5-MME and CMIP6-MME captured the spatial pattern, temporal pattern, and seasonal variations; however, precipitation was slightly overestimated in the western and central HRB and precipitation was underestimated in the eastern HRB. The precipitation simulation ability of the downscaled CMIP6-MME relative to the downscaled CMIP5-MME improved because of reduced biases. The downscaled CMIP6-MME better simulated precipitation for most stations compared to the downscaled CMIP5-MME in all seasons except for summer. Both the downscaled CMIP5-MME and CMIP6-MME exhibit poor performance in simulating rainy days in the HRB.

Highlights

The results demonstrate that the performances of the CMIP5-model ensemble (MME) and weresignificantly significantly improved after deviation correction, correction, indicating thatindicating the equidistant cumulative distribution functions matching method (EDCDFm) that the were improved after deviation is suitable
In July and August, when the bias exceeded 20 mm. These months include the rainy days of the Hanjiang River Basin (HRB). These results indicate that the downscaled CMIP6 and CMIP5 global climate model (GCM) poorly simulate heavy rainfall
Gusain et al [8] assessed CMIP5 and CMIP6 GCM precipitation simulations for indicative characteristics that represent the complex dynamics of Indian summer monsoon rainfall and found significant improvement in CMIP6 models in capturing the spatiotemporal pattern of monsoon rainfall over India, in the Western Ghats and the northeast foothills of the Himalayas

Summary

Methods

The HRB, with an area of 1.59 × 105 km , is located between 30◦ 80 –34◦ 110 N and 106◦ 120 –114◦ 140 E, and spans the provinces of Shanxi, Hubei, Henan, Sichuan, Gansu, and Chongqing (Figure 1). The west and central areas of the HRB are mountainous and semi-mountainous, whereas the east is a plain habitat with an elevation ranging from 0 to 3577 m (Figure 1). The second step is temporal downscaling, in which the spatially downscaled monthly data are temporally downscaled into daily data using a single-site climate generator (CLIGEN). The final step re-creates the spatial correlation of the precipitation sequences for the meteorological stations based on the shuffle method [12]

Results

Discussion

Conclusion