Datasets for the CMIP6 Scenario Model Intercomparison Project (ScenarioMIP) Simulations with the Coupled Model CAS FGOALS-f3-L

Zhao, Shuwen; Yu, Yongqiang; Lin, Pengfei; Liu, Hailong; He, Bian; Bao, Qing; Guo, Yikun; Hua, Lijuan; Chen, Kangjun; Wang, Xiaowei

doi:10.1007/s00376-020-0112-9

Cited by 21 publications

(8 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also, CMIP6 has upgraded its new future scenarios, with the combination of radiative forcing levels of the representative concentration pathways used in the 5th phase of CMIP and the shared socioeconomic pathways (SSPs; O'Neill et al ., 2016; Ullah et al ., 2022; Wu et al ., 2020), which makes them more reasonable. The SSPs describe five different scenarios of social development in the future without the impact of climate change or climate policies (SSP1: sustainability, SSP2: middle of the road, SSP3: regional rivalry, SSP4: inequality, SSP5: fossil fuel development) (O'Neill et al ., 2016; Zhao et al ., 2021).…”

Section: Introductionmentioning

confidence: 99%

Evaluating observed and future spatiotemporal changes in precipitation and temperature across China based on CMIP6‐GCMs

Arshad

et al. 2022

Intl Journal of Climatology

View full text Add to dashboard Cite

The present study aimed to evaluate the performance of 46 global climate models (GCMs) from the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6) in the historical simulation of precipitation and temperature, and select the best performing GCMs for future projection across China and three major river basins. This study uses four shared socioeconomic pathways (SSPs), namely SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5 relative to the base period (1961–2014). Initially, 46 models were evaluated across China employing an improved Taylor diagram method. Based on relatively better performance, 10 best‐performing models (TBMs) were selected out of 46 models for further evaluation. The results show that historical temperature was well reproduced by CMIP6 over the study regions with a high correlation coefficient (CC). All the TBMs produced good CC ranging from 0.8 to 0.99 presenting the precipitation and temperature distribution well. Meanwhile, EC‐Earth3 and EC‐Earth3‐Veg well simulated the precipitation and temperature amounts as well as trends over selected three river basins. The multimodel ensemble mean (MME) underestimates temperature over China and selected three basins with bias values of −0.53, −0.21, −0.91, and −0.68°C, respectively. In contrast, MEM overestimated the simulated precipitation with the amount of 27.7, 32.4, 21.0, and 104.6% across China and selected three basins. During future projections, increased precipitation and temperature trends are projected over three selected river basins as well as all across China. The increasing trend of future precipitation over China under SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5 scenarios are 0.65, 0.86, 1.29, and 0.76 mm·a−1, whereas, the increasing trend of temperature is 0.008, 0.028, 0.050, and 0.065°C·a−1, respectively. Comparatively, the greater the radiation force, the higher projected increases in precipitation and temperature across China and three major river basins were observed. The extent of CMIP6 models over the target region and its river basins calls for further deep assessment of the attribution and possible implementation of robust methods that can accurately simulate the observed patterns for future practice.

show abstract

Section: Introductionmentioning

confidence: 99%

Evaluating observed and future spatiotemporal changes in precipitation and temperature across China based on CMIP6‐GCMs

Arshad

et al. 2022

Intl Journal of Climatology

View full text Add to dashboard Cite

show abstract

“…The Shared Socioeconomic Pathways (SSPs) scenarios used in AR6 include the SSP1 (Sustainability), SSP2 (Middle of the road), SSP3 (Regional Rivalry), SSP4 (Inequality), and SSP5 (Fossil-fueled Development) pathways 3 . The CMIP6 future scenario experiments are classified into core priority groups, including 1) the tier-1 experiments with SSPs 1–2.6, 2–4.5, 3–7.0, and 5–8.5, and the tier-2 experiments with SSPs 1–1.9, 4-3.4, 4–6.0, and 5–3.4 4 .…”

Section: Background and Summarymentioning

confidence: 99%

A 10-km CMIP6 downscaled dataset of temperature and precipitation for historical and future Vietnam climate

et al. 2023

View full text Add to dashboard Cite

High-resolution climate projections are mandatory for many applications and impact assessments in environmental and management studies. In response to the needs in Vietnam, this study constructs a new precipitation and temperature daily dataset for Vietnam, at a high spatial resolution of 0.1° × 0.1°, based on the outputs of 35 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The Bias Correction and Spatial Disaggregation (BCSD) method is adopted to bias-correct monthly GCM simulations using observation data, then subsequently temporally disaggregate them into daily data. The new dataset is called CMIP6-VN, covering the present-time period 1980–2014 and future projections for 2015–2099 from both CMIP6 tier-1 (Shared Socioeconomic Pathways (SSPs) 1–1.26, 2–4.5, 3–7.0, and 5–8.5) and tier-2 (SSPs 1–1.9, 4–3.4, 4–6.0) experiments. Results indicated the good performance of CMIP6-VN for the historical period, suggesting that the dataset could be used for studies on climate change assessment and impacts in Vietnam.

show abstract

“…Riahi et al, 2017). In the ScenarioMIP design, the CO 2 concentrations for SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 scenarios would be about 400, 520, 800 and 1,050 ppm by the end of the 21st century (Zhan et al, 2019).…”

Section: Features Of the Newly Released Cmip6 Datamentioning

confidence: 99%

Projected dry/wet regimes in China using SPEI under four SSP‐RCPs based on statistically downscaled CMIP6 data

Chen

Yao

et al. 2022

Intl Journal of Climatology

View full text Add to dashboard Cite

Dry/wet conditions are one of the key constituents of climate change. The understanding of dry/wet variability is vital for production and water resources management. In this research, the temporal variations of 12‐month timescale standardized precipitation evapotranspiration (SPEI) over 2021–2100 under the SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5 scenarios in seven subregions and China's mainland were investigated over the baseline period of 1961–2000. The run theory was used to project the variations of dry/wet frequency, duration and severity at different levels during 1961–2000, 2021–2060 and 2061–2100 based on the estimated SPEI. The results showed that dry tendency would occur in northwest China. The linear trend for SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5 were −0.056, −0.031, 0.009 and −0.072 per decade, respectively. While wet tendency would occur in the other regions over 2021–2100. The mild, moderate and severe dry/wet duration and severity over 2021–2060 and 2061–2100 would gradually decrease. Except for northwest China and Qinghai‐Tibetan Plateau, the extreme drought duration and severity would increase in the other subregions, while the extreme wet duration and severity would increase in most regions of China. The drought frequency in north China would range from 0 to 14 times and be smaller than the other regions over 2021–2060 and 2060–2100. However, the wet frequency in south China would be larger than that in the other regions. The dry/wet frequency duration and severity for the SSP5‐8.5 scenario would be the largest among the four scenarios. The projected dry/wet conditions can provide useful information for future water resources management.

show abstract

Datasets for the CMIP6 Scenario Model Intercomparison Project (ScenarioMIP) Simulations with the Coupled Model CAS FGOALS-f3-L

Cited by 21 publications

References 34 publications

Evaluating observed and future spatiotemporal changes in precipitation and temperature across China based on CMIP6‐GCMs

Evaluating observed and future spatiotemporal changes in precipitation and temperature across China based on CMIP6‐GCMs

A 10-km CMIP6 downscaled dataset of temperature and precipitation for historical and future Vietnam climate

Projected dry/wet regimes in China using SPEI under four SSP‐RCPs based on statistically downscaled CMIP6 data

Contact Info

Product

Resources

About