[1] Quantifying how global warming impacts the spatiotemporal distribution of precipitation represents a key scientific challenge with profound implications for human welfare. Utilizing monthly precipitation data from Coupled Model Intercomparison Project (CMIP3) climate change simulations, the results here show that the occurrence of very dry (<0.5 mm/day) and very wet (>10 mm/day) months comprises a straightforward, robust metric of anthropogenic warming on tropical land region rainfall. In particular, differencing tropics-wide precipitation frequency histograms for 25-year periods over the late 21st and 20th centuries shows increased late-21st-century occurrence of histogram extremes both in the model ensemble and across individual models. Mechanistically, such differences are consistent with the view of enhanced tropical precipitation spatial gradients. Similar diagnostics are calculated for two 15-year subperiods over 1979-2008 for the CMIP3 models and three observational precipitation products to assess whether the signature of late-21st-century warming has already emerged in response to recent warming. While both the observations and CMIP3 ensemble-mean hint at similar amplification in the warmer (1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008) subinterval, the changes are not robust, as substantial differences are evident among the observational products and the intraensemble spread is large. Comparing histograms computed from the warmest and coolest years of the observational period further demonstrates effects of internal variability, notably the El Niño/Southern Oscillation, which appear to oppose the impact of quasi-uniform anthropogenic warming on the wet tail of the monthly precipitation distribution. These results identify the increase of very dry and wet occurrences in monthly precipitation as a potential signature of anthropogenic global warming but also highlight the continuing dominance of internal climate variability on even bulk measures of tropical rainfall.

The South Pacific convergence zone (SPCZ) is simulated as too zonal a feature in the current generation of climate models, including those in phase 5 of the Coupled Model Intercomparison Project (CMIP5). This zonal bias induces errors in tropical convective heating, with subsequent effects on global circulation. The SPCZ structure, particularly in the subtropics, is governed by the tropical-extratropical interaction between transient synoptic systems and the mean background state. In this study, analysis of synoptic variability in the simulated subtropical SPCZ reveals that the basic mechanism of tropical-extratropical interaction is generally well simulated, with storms approaching the SPCZ along comparable trajectories to observations. However, there is a broad spread in mean precipitation and its variability across the CMIP5 ensemble. Intermodel spread appears to relate to a biased background state in which the synoptic waves propagate. In particular, the region of mean negative zonal stretching deformation or ''storm graveyard'' in the upper troposphere is displaced in CMIP5 models to the northeast of its position in reanalysis data, albeit with pronounced ('258) intermodel longitudinal spread. Precipitation along the eastern edge of the SPCZ shifts in accordance with a storm graveyard shift, and in general models with stronger storm graveyards show higher precipitation variability. Building on prior SPCZ research, it is suggested that SPCZs simulated by CMIP5 models are not simply too zonal; rather, in models the subtropical SPCZ manifests a diagonal tilt similar to observations while SST biases force an overly zonal tropical SPCZ, resulting in a more discontinuous SPCZ than observed.

One theorized control on the position of the South Pacific convergence zone (SPCZ) is the amount of low-level inflow from the relatively dry southeastern Pacific basin. Building on an analysis of observed SPCZ region synoptic-scale variability by Lintner and Neelin, composite analysis is performed here on two reanalysis products as well as output from 17 models in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Using low-level zonal wind as a compositing index, it is shown that the CMIP5 ensemble mean, as well as many of the individual models, captures patterns of wind, specific humidity, and precipitation anomalies resembling those obtained for reanalysis fields between weak- and strong-inflow phases. Lead–lag analysis of both the reanalyses and models is used to develop a conceptual model for the formation of each composite phase. This analysis indicates that an equatorward-displaced Southern Hemisphere storm track and an eastward-displaced equatorial eastern Pacific westerly (wind) duct are features of the weak-inflow phase although, as indicated by additional composite analyses based on these features, each appears to account weakly for the details of the low-level inflow composite anomalies. Despite the presence of well-known biases in the CMIP5 simulations of the SPCZ region climate, the models appear to have some fidelity in simulating synoptic-scale relationships between low-level winds, moisture, and precipitation, consistent with observations and simple theoretical understanding of interactions of dry air inflow with deep convection.

Current‐generation climate models exhibit various errors or biases in both the spatial distribution and intensity of precipitation relative to observations. In this study, empirical orthogonal function analysis is applied to the space‐model index domain of precipitation over the Pacific from Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations to explore systematic spread of simulated precipitation characteristics across the ensemble. Two significant modes of spread, generically termed principal uncertainty patterns (PUPs), are identified in the December‐January‐February precipitation climatology: the leading PUP is associated with the meridional width of deep convection, while the second is associated with tradeoffs in precipitation intensity along the South Pacific Convergence Zone, the Intertropical Convergence Zone (ITCZ), and the spurious Southern Hemisphere ITCZ. An important factor distinguishing PUPs from the analogy to time series analysis is that the modes can reflect either true systematic intermodel variance patterns or internal variability. In order to establish that the PUPS reflect the former, three complementary tests are performed by using preindustrial control simulations: a bootstrap significance test for reproducibility of the intermodel spatial patterns, a check for robustness over very long climatological averages, and a test on the loadings of these patterns relative to interdecadal sampling. Composite analysis based on these PUPs demonstrates physically plausible relationships to CMIP5 ensemble spread in simulated sea surface temperatures (SSTs), circulation, and moisture. Further analysis of atmosphere‐only, prescribed SST simulations demonstrates decreased spread in the spatial distribution of precipitation, while substantial spread in intensity remains.

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