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A large spread exists in both Indian and Australian average monsoon rainfall and in their interannual variations diagnosed from various observational and reanalysis products. While the multi model mean monsoon rainfall from 59 models taking part in the Coupled Model Intercomparison Project (CMIP3 and CMIP5) fall within the observational uncertainty, considerable model spread exists. Rainfall seasonality is consistent across observations and reanalyses, but most CMIP models produce either a too peaked or a too flat seasonal cycle, with CMIP5 models generally performing better than CMIP3. Considering all North-Australia rainfall, most models reproduce the observed Australian monsoon-El Niño Southern Oscillation (ENSO) teleconnection, with the strength of the relationship dependent on the strength of the simulated ENSO. However, over the Maritime Continent, the simulated monsoon-ENSO connection is generally weaker than observed, depending on the ability of each model to realistically reproduce the ENSO signature in the Warm Pool region. A large part of this bias comes from the contribution of Papua, where moisture convergence seems to be particularly affected by this SST bias. The Indian summer monsoon-ENSO relationship is affected by overly persistent ENSO events in many CMIP models. Despite significant wind anomalies in the Indian Ocean related to Indian Ocean Dipole (IOD) events, the monsoon-IOD relationship remains relatively weak both in the observations and in the CMIP models. Based on model fidelity in reproducing realistic monsoon characteristics and ENSO teleconnections, we objectively select 12 ''best'' models to analyze projections in the rcp8.5 scenario. Eleven of these models are from the CMIP5 ensemble. In India and Australia, most of these models produce 5-20 % more monsoon rainfall over the second half of the twentieth century than during the late nineteenth century. By contrast, there is no clear model consensus over the Maritime Continent.

Understanding how the South Pacific convergence zone (SPCZ) may change in the future requires the use of global coupled atmosphere-ocean models. It is therefore important to evaluate the ability of such models to realistically simulate the SPCZ. The simulation of the SPCZ in 24 coupled model simulations of the twentieth century is examined. The models and simulations are those used for the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The seasonal climatology and interannual variability of the SPCZ is evaluated using observed and model precipitation. Twenty models simulate a distinct SPCZ, while four models merge intertropical convergence zone and SPCZ precipitation. The majority of models simulate an SPCZ with an overly zonal orientation, rather than extending in a diagonal band into the southeast Pacific as observed. Two-thirds of models capture the observed meridional displacement of the SPCZ during El Niñ o and La Niñ a events. The four models that use ocean heat flux adjustments simulate a better tropical SPCZ pattern because of a better representation of the Pacific sea surface temperature pattern and absence of cold sea surface temperature biases on the equator. However, the flux-adjusted models do not show greater skill in simulating the interannual variability of the SPCZ. While a small subset of models does not adequately reproduce the climatology or variability of the SPCZ, the majority of models are able to capture the main features of SPCZ climatology and variability, and they can therefore be used with some confidence for future climate projections.

Capsule Summary This paper reviews the current knowledge on detection, attribution and projection of global and regional monsoons (South Asian, East Asian, Australian, South American, North American, and African) under climate change.

Under global warming, increases in precipitation are expected at high latitudes and near major tropical convergence zones in some seasons, while decreases are expected in many subtropical and midlatitude areas in between. In many other areas there is no consensus among models on the sign of the projected change. This is often assumed to indicate that precipitation projections in these regions are highly uncertain. Here, twenty-first century precipitation projections under the Special Report on Emissions Scenarios (SRES) A1B scenario using 24 World Climate Research Programme (WCRP)/Coupled Model Intercomparison Project phase 3 (CMIP3) climate models are examined. In areas with no consensus on the sign of projected change there are extensive subregions where the projected change is “very likely” (i.e., probability > 0.90) to be small (relative to, e.g., the size of interannual variability during the late twentieth century) or zero. The statistical significance of and interrelationships between methods used to identify model consensus on projected change in the 2007 Intergovernmental Panel on Climate Change (IPCC) report are examined, and the impact of interdependency among model projections on statistical significance is investigated. Interdependency among projections is shown to be much weaker than interdependency among simulations of climatology. The results show that there is more widespread consistency among the model projections than one might infer from the 2007 IPCC Fourth Assessment report. This discovery highlights the broader need to identify regions, variables, and phenomena that are expected to be little affected by anthropogenic climate change and to communicate this information to the wider community. This is especially important for projections of climate for the next 1–3 decades.