ABSTRACT:The aim of this work is to determine to what extent precipitation modulated by the Madden-Julian Oscillation (MJO) over East Africa can be forecast by the operational global Met Office Unified Model (MetUM). Observed patterns of rainfall were analysed over Kenya, Tanzania and Uganda and used to validate MetUM forecasts made over the period [2005][2006][2007][2008][2009][2010][2011][2012]. It was found that there is a large seasonal dependence on the MJO for episodes of enhancement and suppression of rainfall over the inland highlands and the coastal lowlands, particularly from March to May and October to December, when the Intertropical Convergence Zone is located directly over the region. In phases 2-4 of the MJO lifecycle, there is an enhancement of precipitation over the highland regions and suppression over the coast. This dipole is reversed throughout phases 6-8. These findings corroborate previous studies undertaken over the region. The observed patterns were replicated well by the MetUM global model, even up to a forecast lead time of 5 days (T + 120 h), though some minor drift is apparent and convective and suppressed centres tend to stray from those of the observed rainfall. Model resolution is thought to be a key component of this difference. The systematic errors will likely improve with further plans for model resolution and physics upgrades, although the overall quality of the MetUM's ability to forecast the MJO over this region is sound.

Abstract:Ocean heat uptake is a key indicator of climate change, in part because it contributes to sea-level rise. Quantifying the uncertainties surrounding ocean heat uptake and sea-level rise are important in assessing climate-related risks. Here, comprehensive global climate model ensembles are used to evaluate uncertainties surrounding decadal trends in depth-integrated global steric sea-level rise due to thermal expansion of the ocean. Results are presented against observational estimates, which are used as a guide to the state of recent literature. The first ensemble uses the Community Earth System Model (CESM), which samples the effects of internal variability within the coupled Earth system including contributions from the sub-surface ocean. We compare and contrast these results with an ensemble based on the Coupled Model Intercomparison Project Phase 5 (CMIP5), which samples the combined effects of structural model differences and internal variability. The effects of both internal variability and structural model differences contribute substantially to uncertainties in modeled steric sea-level trends for recent decades, and the magnitude of these effects varies with depth. The 95% range in total sea-level rise trends across the CESM ensemble is 0.151 mm·year −1 for 1957-2013, while this range is 0.895 mm·year −1 for CMIP5. These ranges increase during the more recent decade of 2005-2015 to 0.509 mm·year −1 and 1.096 mm·year −1 for CESM and CMIP5, respectively. The uncertainties are amplified for regional assessments, highlighting the importance of both internal variability and structural model differences when considering uncertainties surrounding modeled sea-level trends. Results can potentially provide useful constraints on estimations of global and regional sea-level variability, in particular for areas with few observations such as the deep ocean and Southern Hemisphere.

Extreme temperature events can have considerable negative impacts on sectors such as health, agriculture, and transportation. Observational evidence indicates the severity and frequency of warm extremes are increasing over much of the United States, but there are sizeable challenges both in estimating extreme temperature changes and in quantifying the relevant associated uncertainties. This study provides a simple statistical framework using a block maxima approach to analyze the representation of warm temperature extremes in several recent global climate model ensembles. Uncertainties due to structural model differences, grid resolution, and internal variability are characterized and discussed. Results show that models and ensembles differ greatly in the representation of extreme temperature over the United States, and variability in tail events is dependent on time and anthropogenic warming, which can influence estimates of return periods and distribution parameter estimates using generalized extreme value (GEV) distributions. These effects can considerably influence the uncertainty of model hindcasts and projections of extremes. Several idealized regional applications are highlighted for evaluating ensemble skill and trends, based on quantile analysis and root-mean-square errors in the overall sample and the upper tail. The results are relevant to regional climate assessments that use global model outputs and that are sensitive to extreme warm temperature. Accompanying this manuscript is a simple toolkit using the R statistical programming language for characterizing extreme events in gridded datasets.

Due to its large heat capacity and circulation, the ocean contributes significantly to global heat uptake, global heat transport, spatial temperature patterns, and variability. Quantifying ocean heat uptake across different temporal and spatial scales is important to quantify Earth's climate response to anthropogenic warming. Here we evaluate ocean adjustment time scales from two different fully coupled climate model ensembles using the Community Earth System Model. Both ensembles use the same model version, anthropogenic and natural forcings, and coupling configurations, but we initialize the ensembles in two different ways: (1) sampling joint internal variability of the ocean–atmosphere system (unique atmosphere and ocean conditions) and (2) sampling the internal variability of the atmosphere only (unique atmosphere, identical ocean conditions). Uncertainty due to internal variability is used as a proxy to quantify the time scales of ocean temperature adjustment at different depths and basins in Community Earth System Model. Time scales of equilibration are longer in the deep ocean than the upper ocean, highlighting the vertical structure of dynamic adjustment. The Atlantic equilibrates on shorter time scales (82 years above 1,000 m, 140 years below 1,000 m) relative to the Pacific (106 years above 1,000 m, 444 years below 1,000 m) in Community Earth System Model due to the large North Atlantic Deep Water formation and strong overturning circulation in the Atlantic. These results have broad implications for analyzing internal climate variability, ocean adjustment, and drift in global coupled model experiments and intercomparisons.

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