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Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model's ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic

Feedbacks involving low-level clouds remain a primary cause of uncertainty in global climate model projections. This issue was addressed by examining changes in low-level clouds over the Northeast Pacific in observations and climate models. Decadal fluctuations were identified in multiple, independent cloud data sets, and changes in cloud cover appeared to be linked to changes in both local temperature structure and large-scale circulation. This observational analysis further indicated that clouds act as a positive feedback in this region on decadal time scales. The observed relationships between cloud cover and regional meteorological conditions provide a more complete way of testing the realism of the cloud simulation in current-generation climate models. The only model that passed this test simulated a reduction in cloud cover over much of the Pacific when greenhouse gases were increased, providing modeling evidence for a positive low-level cloud feedback.

The Subseasonal Experiment (SubX) is a multimodel subseasonal prediction experiment designed around operational requirements with the goal of improving subseasonal forecasts. Seven global models have produced 17 years of retrospective (re)forecasts and more than a year of weekly real-time forecasts. The reforecasts and forecasts are archived at the Data Library of the International Research Institute for Climate and Society, Columbia University, providing a comprehensive database for research on subseasonal to seasonal predictability and predictions. The SubX models show skill for temperature and precipitation 3 weeks ahead of time in specific regions. The SubX multimodel ensemble mean is more skillful than any individual model overall. Skill in simulating the Madden–Julian oscillation (MJO) and the North Atlantic Oscillation (NAO), two sources of subseasonal predictability, is also evaluated, with skillful predictions of the MJO 4 weeks in advance and of the NAO 2 weeks in advance. SubX is also able to make useful contributions to operational forecast guidance at the Climate Prediction Center. Additionally, SubX provides information on the potential for extreme precipitation associated with tropical cyclones, which can help emergency management and aid organizations to plan for disasters.

The possible role that tropical Pacific SSTs played in driving the megadroughts over North America during the medieval period is addressed. Fossil coral records from the Palmyra Atoll are used to derive tropical Pacific SSTs for the period from a.d. 1320 to a.d. 1462 and show overall colder conditions as well as extended multidecadal La Niña–like states. The reconstructed SSTs are used to force a 16-member ensemble of atmosphere GCM simulations, each with different initial conditions, with the atmosphere coupled to a mixed layer ocean outside of the tropical Pacific. Model results are verified against North American tree ring reconstructions of the Palmer Drought Severity Index. A singular value decomposition analysis is performed using the soil moisture anomaly simulated by another 16-member ensemble of simulations forced by global observed SSTs for 1856–2004 and tree ring reconstructions of the Palmer Drought Severity Index for the same period. This relationship is used to transfer the modeled medieval soil moisture anomaly (relative to the modern simulation) into a model-estimated Palmer Drought Severity Index. The model-estimated Palmer Drought Severity Index reproduces many aspects of both the interannual and decadal variations of the tree ring reconstructions, in addition to an overall drier climate that is drier than the tree ring records suggest. The model-estimated Palmer Drought Severity Index simulates two previously identified “megadroughts,” a.d. 1360–1400 and a.d. 1430–60, with a realistic spatial pattern and amplitude. In contrast, the model fails to produce a period of more normal conditions in the early fifteenth century that separated these two megadroughts. The dynamical link between tropical SSTs and the North American megadroughts is akin to that operating in modern droughts. The model results are used to argue that the tropical Pacific played an active role in driving the megadroughts. However, the match between simulated and reconstructed hydroclimate is such that it is likely that both the coral-reconstructed SST anomalies contain significant errors and that SST anomalies in other basins also played a role in driving hydroclimate variations over North America during the late medieval period.