Gerald A. Meehl

An Overview of CMIP5 and the Experiment Design

The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades...

The next generation of scenarios for climate change research and assessment

Advances in the science and observation of climate change are providing a clearer understanding of the inherent variability of Earth’s climate system and its likely response to human and natural influences. The implications of climate change for the environment and society will depend not only on the response of the Earth system to changes in radiative forcings, but also on how humankind responds through changes in technology, economies, lifestyle and policy. Extensive uncertainties exist in future forcings of and responses to climate change, necessitating the use of scenarios of the future to explore the potential consequences of different response options. To date, such scenarios have not adequately examined crucial possibilities, such as climate change mitigation and adaptation, and have relied on research processes that slowed the exchange of information among physical, biological and social scientists. Here we describe a new process for creating plausible scenarios to investigate some of the most challenging and important questions about climate change confronting the global community.

THE WCRP CMIP3 Multimodel Dataset: A New Era in Climate Change Research

A coordinated set of global coupled climate model [atmosphere–ocean general circulation model (AOGCM)] experiments for twentieth- and twenty-first-century climate, as well as several climate change commitment and other experiments, was run by 16 modeling groups from 11 countries with 23 models for assessment in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Since the assessment was completed, output from another model has been added to the dataset, so the participation is now 17 groups from 12 countries with 24 models. This effort, as well as the subsequent analysis phase, was organized by the World Climate Research Programme (WCRP) Climate Variability and Predictability (CLIVAR) Working Group on Coupled Models (WGCM) Climate Simulation Panel, and constitutes the third phase of the Coupled Model Intercomparison Project (CMIP3). The dataset is called the WCRP CMIP3 multimodel dataset, and represents the largest and most comprehensive international global coupled climate model experiment and multimodel analysis effort ever attempted. As of March 2007, the Program for Climate Model Diagnostics and Intercomparison (PCMDI) has collected, archived, and served roughly 32 TB of model data. With oversight from the panel, the multimodel data were made openly available from PCMDI for analysis and academic applications. Over 171 TB of data had been downloaded among the more than 1000 registered users to date. Over 200 journal articles, based in part on the dataset, have been published so far. Though initially aimed at the IPCC AR4, this unique and valuable resource will continue to be maintained for at least the next several years. Never before has such an extensive set of climate model simulations been made available to the international climate science community for study. The ready access to the multimodel dataset opens up these types of model analyses to researchers, including students, who previously could not obtain state-of-the-art climate model output, and thus represents a new era in climate change research. As a direct consequence, these ongoing studies are increasing the body of knowledge regarding our understanding of how the climate system currently works, and how it may change in the future.

The Importance of Land-Cover Change in Simulating Future Climates

Adding the effects of changes in land cover to the A2 and B1 transient climate simulations described in the Special Report on Emissions Scenarios (SRES) by the Intergovernmental Panel on Climate Change leads to significantly different regional climates in 2100 as compared with climates resulting from atmospheric SRES forcings alone. Agricultural expansion in the A2 scenario results in significant additional warming over the Amazon and cooling of the upper air column and nearby oceans. These and other influences on the Hadley and monsoon circulations affect extratropical climates. Agricultural expansion in the mid-latitudes produces cooling and decreases in the mean daily temperature range over many areas. The A2 scenario results in more significant change, often of opposite sign, than does the B1 scenario.

SOLAR INFLUENCES ON CLIMATE

The development of this review article has evolved from work carried out by an international team of the International Space Science Institute (ISSI), Bern, Switzerland, and from work carried out under the auspices of Scientific Committee on Solar Terrestrial Physics (SCOSTEP) Climate and Weather of the Sun‐Earth System (CAWSES‐1). The support of ISSI in providing workshop and meeting facilities is acknowledged, especially support from Y. Calisesi and V. Manno. SCOSTEP is acknowledged for kindly providing financial assistance to allow the paper to be published under an open access policy. L.J.G. was supported by the UK Natural Environment Research Council (NERC) through their National Centre for Atmospheric Research (NCAS) Climate program. K.M. was supported by a Marie Curie International Outgoing Fellowship within the 6th European Community Framework Programme. J.L. acknowledges support by the EU/FP7 program Assessing Climate Impacts on the Quantity and Quality of Water (ACQWA, 212250) and from the DFG Project Precipitation in the Past Millennium in Europe (PRIME) within the Priority Program INTERDYNAMIK. L.H. acknowledges support from the U.S. NASA Living With a Star program. G.M. acknowledges support from the Office of Science (BER), U.S. Department of Energy, Cooperative Agreement DE‐FC02‐97ER62402, and the National Science Foundation. We also wish to thank Karin Labitzke and Markus Kunze for supplying an updated Figure 13, Andrew Heaps for technical support, and Paul Dickinson for editorial support. Part of the research was carried out under the SPP CAWSES funded by GFG. J.B. was financially supported by NCCR Climate–Swiss Climate Research.

Challenges in Combining Projections from Multiple Climate Models

Recent coordinated efforts, in which numerous general circulation climate models have been run for a common set of experiments, have produced large datasets of projections of future climate for various scenarios. Those multimodel ensembles sample initial conditions, parameters, and structural uncertainties in the model design, and they have prompted a variety of approaches to quantifying uncertainty in future climate change. International climate change assessments also rely heavily on these models. These assessments often provide equal-weighted averages as best-guess results, assuming that individual model biases will at least partly cancel and that a model average prediction is more likely to be correct than a prediction from a single model based on the result that a multimodel average of present-day climate generally outperforms any individual model. This study outlines the motivation for using multimodel ensembles and discusses various challenges in interpreting them. Among these challenges are that the number of models in these ensembles is usually small, their distribution in the model or parameter space is unclear, and that extreme behavior is often not sampled. Model skill in simulating present-day climate conditions is shown to relate only weakly to the magnitude of predicted change. It is thus unclear by how much the confidence in future projections should increase based on improvements in simulating present-day conditions, a reduction of intermodel spread, or a larger number of models. Averaging model output may further lead to a loss of signal— for example, for precipitation change where the predicted changes are spatially heterogeneous, such that the true expected change is very likely to be larger than suggested by a model average. Last, there is little agreement on metrics to separate ‘‘good’’ and ‘‘bad’’ models, and there is concern that model development, evaluation, and posterior weighting or ranking are all using the same datasets. While the multimodel average appears to still be useful in some situations, these results show that more quantitative methods to evaluate model performance are critical to maximize the value of climate change projections from global models.

An Introduction to Trends in Extreme Weather and Climate Events: Observations, Socioeconomic Impacts, Terrestrial Ecological Impacts, and Model Projections*

Weather and climatic extremes can have serious and damaging effects on human society and infrastructure as well as on ecosystems and wildlife. Thus, they are usually the main focus of attention of the news media in reports on climate. There are some indications from observations concerning how climatic extremes may have changed in the past. Climate models show how they could change in the future either due to natural climate fluctuations or under conditions of greenhouse gas-induced warming. These observed and modeled changes relate directly to the understanding of socioeconomic and ecological impacts related to extremes.

Trends in Extreme Weather and Climate Events: Issues Related to Modeling Extremes in Projections of Future Climate Change*

Projections of statistical aspects of weather and climate extremes can be derived from climate models representing possible future climate states. Some of the recent models have reproduced results previously reported in the Intergovernmental Panel on Climate Change (IPCC) Second Assessment Report, such as a greater frequency of extreme warm days and lower frequency of extreme cold days associated with a warmer mean climate, a decrease in diurnal temperature range associated with higher nighttime temperatures, increased precipitation intensity, midcontinent summer drying, decreasing daily variability of surface temperature in winter, and increasing variability of northern midlatitude summer surface temperatures. This reconfirmation of previous results gives an increased confidence in the credibility of the models, though agreement among models does not guarantee those changes will occur. New results since the IPCC Second Assessment Report indicate a possible increase of extreme heat stress events in a warm...

Contributions of External Forcings to Southern Annular Mode Trends

Abstract An observed trend in the Southern Hemisphere annular mode (SAM) during recent decades has involved an intensification of the polar vortex. The source of this trend is a matter of scientific debate with stratospheric ozone losses, greenhouse gas increases, and natural variability all being possible contenders. Because it is difficult to separate the contribution of various external forcings to the observed trend, a state-of-the-art global coupled model is utilized here. Ensembles of twentieth-century simulations forced with the observed time series of greenhouse gases, tropospheric and stratospheric ozone, sulfate aerosols, volcanic aerosols, solar variability, and various combinations of these are used to examine the annular mode trends in comparison to observations, in an attempt to isolate the response of the climate system to each individual forcing. It is found that ozone changes are the biggest contributor to the observed summertime intensification of the southern polar vortex in the second ...

Effects of Black Carbon Aerosols on the Indian Monsoon

Abstract A six-member ensemble of twentieth-century simulations with changes to only time-evolving global distributions of black carbon aerosols in a global coupled climate model is analyzed to study the effects of black carbon (BC) aerosols on the Indian monsoon. The BC aerosols act to increase lower-tropospheric heating over South Asia and reduce the amount of solar radiation reaching the surface during the dry season, as noted in previous studies. The increased meridional tropospheric temperature gradient in the premonsoon months of March–April–May (MAM), particularly between the elevated heat source of the Tibetan Plateau and areas to the south, contributes to enhanced precipitation over India in those months. With the onset of the monsoon, the reduced surface temperatures in the Bay of Bengal, Arabian Sea, and over India that extend to the Himalayas act to reduce monsoon rainfall over India itself, with some small increases over the Tibetan Plateau. Precipitation over China generally decreases due to...