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This study examines the improvement in Coupled Model Intercomparison Project Phase Six (CMIP6) models against the predecessor CMIP5 in simulating mean and extreme precipitation over the East Africa region. The study compares the climatology of the precipitation indices simulated by the CMIP models with the CHIRPS data set using robust statistical techniques for 1981-2005. The results display the varying performance of the general circulation models (GCMs) in the simulation of annual and seasonal precipitation climatology over the study domain. CMIP6 multi-model ensemble mean (hereafter MME) shows improved performance in the local annual mean cycle simulation with a better representation of the rainfall within the two peaks, especially the MAM rainfall relative to their predecessor. Moreover, simulation of extreme indices is well captured in CMIP6 models relative to CMIP5. The CMIP6-MME performed better than the CMIP5-MME with lesser biases in simulating Simple Daily Intensity Index (SDII), consecutive dry days (CDD), and very heavy precipitation days >20 mm (R20mm) over East Africa. Remarkably, most CMIP6 models are unable to simulate extremely wet days (R95p). Some CMIP6 models (e.g., NorESM2-MM and CNRM-CM6-1) depict robust performance in reproducing the observed indices across all analyses. OND season shows wet biases for some indices (i.e., R95p, PRCPTOT), except for SDII, CDD, and R20mm in CMIP6 models. Consistent with other studies, the mean ensemble performance for both CMIP5/6 shows better performance as compared with individual models due to the cancellation of some systematic errors in the

No abstract

This study examines the improvement in coupled intercomparison project phase six (CMIP6) models against the predecessor CMIP5 in simulating mean and extreme precipitation over the East Africa region. The study compares the climatology of the precipitation indices simulated by the CMIP models with the CHIRPS dataset using robust statistical techniques for 1981 – 2005. The results display the varying performance of the general circulation models (GCMs) in the simulation of annual and seasonal precipitation climatology over the study domain. CMIP6-MME shows improved performance in the local annual mean cycle simulation with a better representation of two peaks, especially the MAM rainfall relative to its predecessor. Moreover, simulation of extreme indices is well captured in CMIP6 models relative to its predecessor. The CMIP6-MME performed better than the CMIP5-MME with lesser biases in simulating SDII, CDD, and R20mm over East Africa. Remarkably, most CMIP6 models are unable to simulate extremely wet days (R95p). A few CMIP6 models (e.g., NorESM2-MM and CNRM-CM6-1) depicts robust performance in reproducing the observed indices across all analyses. Conversely, OND season shows the overestimation of some indices (i.e., R95p, PRCPTOT), except for SDII, CDD, and R20mm. Consistent with other studies, the mean ensemble performance for both CMIP5/6 shows better performance due to the cancellation of some systematic errors in the individual models. Generally, the CMIP6 depicts improved performance in the simulation of MAM season akin CMIP5 models. However, the new model generation is still marred with uncertainty, thereby depicting substandard performance over the East Africa domain. This calls for further investigation of attribution studies into the sources of persistent systematic biases and a prerequisite for identifying individual models with robust features that can accurately simulate observed patterns for future usage.

East Asia is undergoing significant climate changes and these changes are likely to grow in the future. It is urgent to characterize both the mechanisms controlling climate and the response of the East Asian climate system at global warming of 1.5 and 2 °C above pre-industrial levels (GW1.5 and GW2 hereafter). This study reviews recent studies on East Asian climate change at GW1.5 and GW2. The intensity and variability of the East Asian summer monsoon are expected to increase modestly, accompanied by an enhancement of water vapor transport. Other expected changes include the intensification of the Western Pacific Subtropical High and an intensified and southward shift of the East Asian jet, while the intensity of the East Asian winter monsoon is projected to reduce with high uncertainty. Meanwhile, the frequency of ENSO may increase in a warming world with great uncertainty. Significant warming and wetting occur in East Asia, with more pronounced intensity, frequency, and duration of climate extremes at GW2 than that at GW1.5. The fine structure of regional climate changes and the presence and location of various warming hotspots, however, show substantial divergence among different model simulations. Furthermore, the Asian climate responses can differ substantially between the transient and stabilized GW1.5 and GW2, which has important implications for emission policies. Thus, to better plan effective mitigation and adaptation activities, further research including an in-depth exploration of the divergent responses in transient versus stabilized scenarios, the quantification of future projection uncertainties, and improvements of the methods to reduce model uncertainties are required.