3.1.1 Annual mean
Figure 1a shows the evolution from 1901 to 2100 of the annual mean surface air temperature (SAT) anomalies averaged over China based on the MME with one inter-model STD. It shows that the SAT continues to increase from the 1970s to the end of 21st century under the RCP2.6, RCP4.5 and RCP8.5 scenarios, with the strongest and most continuous warming under RCP8.5, and flattened or even weakened warming under RCP4.5 and RCP2.6 through the mid 21st century. The SAT difference among the three scenarios is weak in the early 21st century, and gradually increases with integration time. To analyze the uncertainties in SAT projection, the box and whisker plot in Fig. 1a shows one inter-model STD with the MME SAT and inter-model range. The results show a remarkable increase in uncertainty with time under the three emissions scenarios, with the largest uncertainty under RCP8.5 and the smallest under RCP2.6. By the end of the 21st century, the annual mean SAT increases by 1.3\circ C 0.7\circ C, 2.6\circ C 0.8\circ C and 5.2\circ C 1.2\circ C, relative to the present state (1986-2005), under the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively; the inter-model ranges are -0.4°C to 2.9°C, 0.8°C to 4.3°C, and 3.7°C to 7.6°C, respectively.
Figure 2 shows the spatial distribution of the annual mean SAT changes over China in the early, mid and end of the 21st century, relative to 1986-2005, under the RCP2.6, RCP4.5 and RCP8.5 scenarios. It shows a homogenous warming pattern across China, with greater warming in western and northeastern China, and weaker warming in southeastern China. This pattern resembles the observed pattern of SAT change during the late 20th century found by (Ren et al., 2005), (Zhou and Yu, 2006) and (Li et al., 2010). By the end of the 21st century, the increase in the annual mean SAT exceeds 4°C over most of China, and more than 6°C over North Xinjiang, the Tibetan Plateau and northeastern China. There is a certain confidence in the projected SAT changes, as indicated by a signal to noise ratio greater than 1 across all grids over China. In addition, the uncertainty in the SAT projection measured by one inter-model STD is also larger in western and northeastern China than southeastern China (figures not shown for brevity).
The future changes and uncertainties in the annual mean SAT averaged over individual sub-regions in China are shown in Fig. 3. Spatially, the greatest warming is over the TP, followed by NWC, NEC, NC, EC and SC. This forms a spatial structure over China that is generally stable, invariant with emissions scenario and integration time. Taking RCP8.5 as an example, by the end of the 21st century, the annual mean SAT averaged over TP, NWC, NEC, NC, EC, SWC and SC increases by 5.5°C, 5.5°C, 5.5°C, 5.0°C, 4.7°C, 4.5°C and 4.1°C, respectively, with a maximum inter-sub-region discrepancy of 1.4°C.
The uncertainties, in all individual sub-regions, increase with integration time and emissions scenario. Taking NEC as an example, under the RCP8.5 scenario, the uncertainties measured by one inter-model STD in the early, mid and end of the 21st century are 0.5\circ C, 0.8°C, and 1.3°C, respectively; at the end of the century, the uncertainties under RCP2.6, RCP4.5 and RCP8.5 are 0.8°C, 0.9°C, and 1.3°C, respectively. In comparison with the uncertainty in the national average SAT, the uncertainties at a sub-regional scale are larger in the sub-regions over northern China (NEC, NWC, TP, NC) and smaller in the sub-regions over southern China (EC, SC, SWC). Spatially, the largest uncertainty is found in NWC and NEC, followed by TP, NC and EC, and the least in SC and SWC. Taking RCP8.5 as an example, by the end of the 21st century the uncertainties in NWC, NEC, TP, NC, EC, SC and SWC are 1.3°C, 1.3°C, 1.3°C, 1.2°C, 1.1°C, 1.0°C, and 1.0°C, respectively. In addition, the inter-sub-region discrepancy of uncertainty increases with intensified emissions.
3.1.2 Seasonality
The future changes and uncertainties in the SAT averaged over China and individual sub-regions are analyzed from the perspective of seasonality. Figure 4 shows the changes in seasonal mean SAT in the mid 21st century. Future changes in SAT averaged over the whole of China show slight seasonal variations, with the greatest increases of 1.5°C, 2.2°C and 3.0°C in autumn, and the smallest increases of 1.4°C, 2.0°C and 2.7°C in spring under RCP2.6, RCP4.5 and RCP8.5, respectively. In comparison, the sub-regional average SAT shows visible seasonal variation, especially in NEC, followed by NWC, NC, EC and TP, with the least in SWC and SC. In most sub-regions, the seasonality of future SAT is generally consistent under the three emissions scenarios, with the SAT increase greatest in autumn and least in spring. The intensity of the seasonal variation is larger under the RCP8.5 than RCP2.6/RCP4.5 scenario. Spatially, for the seasonal mean SAT, the greatest increase is in northern China (TP, NEC and NWC) and the least in southern China (SWC and SC), forming a spatial pattern across China that is season independent, like the pattern of annual mean SAT. Taking the RCP8.5 scenario as an example, by the middle of the 21st century, the increases in SAT averaged over NEC, TP, NWC, NC, EC, SWC and SC are 3.3°C, 3.1°C, 3.1°C, 2.9°C, 2.9°C, 2.6°C and 2.4°C, respectively in autumn, and 2.5°C, 3.0°C, 2.8°C, 2.5°C, 2.4°C, 2.4°C and 2.3°C, respectively in spring.
The uncertainties in SAT projection averaged over the whole of China show little seasonal variation under the three emissions scenarios. However, on a sub-regional scale, the uncertainty shows certain seasonal variations, whose intensity increases are related to the emissions scenario, and has larger seasonal variability in western than eastern China. Specifically, there is no consistent seasonality in the uncertainties in any individual sub-region or emissions scenario, indicating that seasonal variation of uncertainty is region and emissions-scenario dependent. Spatially, the largest uncertainty is found in northern China (TP, NEC and NWC) and the least in southern China (SWC and SC), forming a spatial pattern that is season independent, like the pattern of uncertainty in annual mean SAT.
The future changes and uncertainties in seasonal mean SAT averaged over China and individual sub-regions at the end of the century are shown in Fig. 5. For the national average SAT, the greatest increase occurs in winter under RCP8.5/RCP4.5 and in autumn under RCP2.6 (5.3°C, 2.6°C and 1.4°C, respectively), and the smallest occurs in spring under RCP8.5, RCP4.5 and RCP2.6 (4.9°C, 2.4°C and 1.3°C, respectively). Under the RCP8.5 scenario, the SAT increases averaged over NEC, TP, NWC, NC, EC, SWC and SC are 6.2°C, 5.9°C, 5.5°C, 5.2°C, 4.6°C, 4.2°C and 4.0°C in winter, and 4.7°C, 5.5°C, 5.1°C, 4.6°C, 4.4°C, 4.4°C and 4.1°C in spring, respectively. The uncertainties in the seasonal mean SAT projection at the end of the century, on national and sub-regional scales, show certain seasonal variations that are region and emissions-scenario dependent.
3.2.1 Annual mean
Figure 1b shows the evolution from 1901 to 2100 of the annual mean precipitation anomaly percentage averaged over China based on the CMIP5 MME with one inter-model STD. It shows that precipitation increases under a background of global warming in the 21st century, with the greatest increases under RCP8.5, and the increases under the RCP2.6 and RCP4.5 scenarios being somewhat flattened. The uncertainty in precipitation projection increases with integration time and emissions scenario. By the end of the 21st century, the annual mean precipitation increases by 5% 5%, 8% 6% and 12% 8%, relative to the present state (1986-2005), under the RCP2.6, RCP4.5 and RCP8.5 scenarios, respectively; the inter-model ranges are -3% to 22%, -1% to 26% and -2% to 31%, respectively. Note that the change signals of precipitation show less scenario dependence in the early stage of the 21st century. In comparison with the SAT, the increasing rate in precipitation during the 21st century is smaller, but with a larger uncertainty in projection.
Figure 6 shows the spatial distribution of annual mean precipitation anomaly percentage over China in the early, mid and end of the 21st century, relative to 1986-2005, under the RCP2.6, RCP4.5 and RCP8.5 scenarios. The increase in precipitation is widespread across China with a larger percentage in northern China than southern China, except for a weak drying projected in the early 21st century in southern China. Taking the RCP8.5 as an example, at the end of the century the precipitation increase exceeds 15% north of the Yellow River Basin, and as much as 40% in most of northwestern China, whereas the increase is only about 5% in southern China. However, precipitation projection is at a low confidence level, especially for the near-future projection, and spatially for the projection over southern China.
The future changes and uncertainties in the annual mean precipitation anomaly percentage averaged over individual sub-regions in China are shown in Fig. 7. Spatially, the greatest increasing percentage is in NEC, followed by NC, TP and NWC, and the smallest is in SWC and SC, forming a stable spatial structure across China, invariant with emissions scenario and integration time. Taking RCP8.5 as an example, by the end of the century, the annual mean precipitation over NEC, NC, TP, NWC, EC, SWC and SC increase by 19%, 18%, 17%, 15%, 6%, 5% and 3%, respectively, with the maximum inter-sub-region discrepancy reaching 16.5%.
The uncertainties in precipitation projection, over all individual sub-regions, increase with integration time and emissions scenario. Taking NEC as an example, under the RCP8.5 scenario, the uncertainties measured by one inter-model STD in the early, mid and end of the 21st century are 4%, 7%, and 10%, respectively; while at the end of the century, the uncertainties under RCP2.6, RCP4.5 and RCP8.5 are 7%, 9%, and 10%, respectively. The uncertainties in the sub-regional average precipitation are generally larger in comparison with the uncertainty in the national average. The largest uncertainty is found in northern China (NC, NEC), followed by western China (NWC, TP), and southern China (SWC, SC, EC) in the mid and late 21st century; the spatial distribution of uncertainty in precipitation projection is different in the early 21st century.
3.2.2 Seasonality
The future changes and uncertainties in the precipitation anomaly percentage averaged over China and the seven sub-regions are analyzed from the perspective of seasonality. Figure 8 shows the changes in the seasonal mean precipitation anomaly percentage in the middle of the 21st century. Future changes in precipitation averaged over the whole of China show evident seasonal variations under the RCP2.6, RCP4.5 and RCP8.5 scenarios, with the largest increasing percentage in spring (7%, 8% and 11%), followed by summer (7%, 8% and 10%), and winter (3%, 5% and 7%). The sub-regional average precipitation also shows a seasonal variation, especially in the TP and NEC, followed by SWC, NC and EC, and the least in NWC and SC. However, the seasonality features in the individual sub-regions are different from each other, and vary with emissions scenario. Under the RCP8.5 scenario, by the middle of the century, the precipitation averaged over NEC, SWC, TP, SC, NC, EC, and NWC increases by 27%, 21%, 21%, 8%, 5%, 3% and 1% in winter, and 9%, 10%, 3%, 7%, 3%, 3% and 2% in summer, respectively.
The uncertainty in precipitation projection averaged over the whole of China shows evident seasonal variations under the RCP2.6, RCP4.5 and RCP8.5 scenarios, with the largest uncertainty in winter ( 7%, 8% and 10%) and the least in autumn ( 5%, 6% and 6%). The uncertainty in precipitation projection also shows seasonal variation on a sub-regional scale, with larger seasonal variability in northern China than southern China. For individual sub-regions, there is no consistent seasonality in precipitation uncertainty. In most sub-regions, precipitation uncertainty is largest in winter, followed by autumn, and the least in spring.
The future changes and uncertainties in the seasonal mean precipitation anomaly percentage averaged over China and individual sub-regions at the end of the 21st century are shown in Fig. 9. The national average precipitation increases are greatest in spring (7%, 10% and 20% under RCP2.6, RCP4.5 and RCP8.5), followed by summer (6%, 10% and 18%), and smallest in winter (4%, 9% and 15%). The associated uncertainty also shows seasonal variation, with the largest uncertainty in winter (11% and 10%) and the smallest in autumn ( 8% and 6%) under the RCP4.5/RCP2.6 scenario, and with the largest uncertainty in spring ( 16%) and the smallest in autumn ( 9%) under the RCP8.5 scenario. For individual sub-regions, the seasonal variations of precipitation and associated uncertainties are similar to those in the middle of the century, but with larger amplitudes.