IPCC AR5 WGI Chapter 14 - A Review
Climate Phenomena and their Relevance for Future Regional Climate Change
Tropical Phenomena
Convergence Zones
Large-scale convection over the tropical oceans is focused into long, narrow convergence zones associated with regions of different sea surface temperatures (SST). Latent heat release during convection (i.e. as ocean water is evaporated and condenses to fall as rain) drives atmospheric circulation and therefore affects global climate. These convergence zones are associated with high mean precipitation. In CMIP5 model projections, rainfall increases in areas with warming SST, following a ‘warmer-get-wetter’ pattern. The specific pattern of SST warming is a significant model uncertainty contributing to intermodal variability with regards to precipitation changes in these convergence zones. Fig. 14.8 illustrates this modeled precipitation increase in convergence zones.
The three major convergence zones are the Inter-Tropical Convergence Zone (ICTZ) in the tropical Pacific and Atlantic, South Pacific Convergence Zone (SPCZ), and South Atlantic Convergence Zone (SACZ). The ICTZ migrates north and south of the equator following the sun, and is generally expected to follow the ‘warmer-get-wetter’ trend. The SPCZ is projected to produce more spatially restricted rainfall events due to a reduction in the SST gradient across the region in a warming climate, potentially leading to longer dry spells in the southwest Pacific. CMIP5 models project a southward shift of the SACZ due to increased Pacific SST and changes in atmospheric circulation.
Other Tropical Climate Phenomena
The Madden-Julian Oscillation (MJO) is the primary mode of tropical variability within seasons, and affects tropical cyclone activity and monsoons. The variance in the MJO is expected to increase in a warming climate, but the magnitude of this change remains uncertain due to the sensitivity to future patterns of SST that are not well modeled at present. The tropical Indian Ocean SST is affected by two modes of interannual variability: the Indian Ocean Basin (IOB) mode and the Indian Ocean Dipole (IOD) mode, both of which are well simulated by CMIP5. A notable modeling result from CMIP5 is that the IOD variability in SST is projected to remain essentially unchanged into the future (Fig. 14.11). Lastly, the Atlantic Ocean features a northward-displaced ICTZ that is typically not well simulated by CMIP5 models. SST variability in the tropical Atlantic is controlled by the Atlantic meridional mode (AAM).
Figure 14.8 | (Upper panel) Annual mean precipitation percentage change (dP/P in green/gray shade and white contours at 20% intervals), and relative SST change (colour contours at intervals of 0.2°C; negative dashed) to the tropical (20°S to 20°N) mean warming in RCP8.5 projections, shown as 23 CMIP5 model ensemble mean. (Lower panel) Sea surface temperature (SST) warming pattern indices in the 23-model RCP8.5 ensemble, shown as the 2081–2100 minus 1986–2005 difference. From left: Northern (EQ to 60°N) minus Southern (60°S to EQ) Hemisphere; equatorial (120°E to 60°W, 5°S to 5°N) and Southeast (130°W to 70°W, 30°S to 15°S) Pacific relative to the tropical mean warming; zonal SST gradient in the equatorial Pacific (120°E to 180°E minus 150°W to 90°W, 5°S to 5°N) and Indian (50°E to 70°E, 10°S to 10°N minus 90°E to 110°S, 10°S to EQ) Oceans. (Rightmost) Spatial correlation (r) between relative SST change and precipitation percentage change (dP/P) in the tropics (20°S to 20°N) in each model. (The spatial correlation for the multi-model ensemble mean fields in the upper panel is 0.63). The circle and error bar indicate the ensemble mean and ±1 standard deviation, respectively. The upper panel is a CMIP5 update of Ma and Xie (2013), and see text for indices in the lower panel.
Figure 14.11 | CMIP5 multi-model ensemble mean standard deviations of interannual variability for September to November in pre-industrial (PiControl; blue bars) and RCP8.5 (red) runs: (a) the Indian Ocean dipole index defined as the western (50°E to 70°E, 10°S to 10°N) minus eastern (90°E to 110°E, 10°S to 0°) SST difference; (b) zonal wind in the central equatorial Indian Ocean (70°E to 90°E, 5°S to 5°N); and (c) sea surface height in the eastern equatorial Indian Ocean (90°E to 110°E, 10°S to 0°). The standard deviation is normalized by the pre-industrial (PiControl) value for each model before ensemble average. Blue box-and-whisker plots show the 10th, 25th, 50th, 75th and 90th percentiles of 51-year windows for PiControl, representing natural variability. Red box-and-whisker plots represent inter-model variability for RCP8.5, based on the nearest rank. (Adapted from Zheng et al., 2013.)