Making sense of the early-2000s warming slowdown

It has been claimed that the early-2000s global warming slowdown or hiatus, characterized by a reduced rate of global surface warming, has been overstated, lacks sound scientific basis, or is unsupported by observations. The evidence presented here contradicts these claims

A global assessment of the impact of climate change on water scarcity

This paper presents a global scale assessment of the impact of climate change on water scarcity. Patterns of climate change from 21 Global Climate Models (GCMs) under four SRES scenarios are applied to a global hydrological model to estimate water resources across 1339 watersheds. The Water Crowding Index (WCI) and the Water Stress Index (WSI) are used to calculate exposure to increases and decreases in global water scarcity due to climate change. 1.6 (WCI) and 2.4 (WSI) billion people are estimated to be currently living within watersheds exposed to water scarcity. Using the WCI, by 2050 under the A1B scenario, 0.5 to 3.1 billion people are exposed to an increase in water scarcity due to climate change (range across 21 GCMs). This represents a higher upper-estimate than previous assessments because scenarios are constructed from a wider range of GCMs. A substantial proportion of the uncertainty in the global-scale effect of climate change on water scarcity is due to uncertainty in the estimates for South Asia and East Asia. Sensitivity to the WCI and WSI thresholds that define water scarcity can be comparable to the sensitivity to climate change pattern. More of the world will see an increase in exposure to water scarcity than a decrease due to climate change but this is not consistent across all climate change patterns. Additionally, investigation of the effects of a set of prescribed global mean temperature change scenarios show rapid increases in water scarcity due to climate change across many regions of the globe, up to 2°C, followed by stabilisation to 4°C

Initialization shock in decadal hindcasts due to errors in wind stress over the tropical Pacific

Low prediction skill in the tropical Pacific is a common problem in decadal prediction systems, especially for lead years 2–5 which, in many systems, is lower than in uninitialized experiments. On the other hand, the tropical Pacific is of almost worldwide climate relevance through its teleconnections with other tropical and extratropical regions and also of importance for global mean temperature. Understanding the causes of the reduced prediction skill is thus of major interest for decadal climate predictions. We look into the problem of reduced prediction skill by analyzing the Max Planck Institute Earth System Model (MPI-ESM) decadal hindcasts for the fifth phase of the Climate Model Intercomparison Project and performing a sensitivity experiment in which hindcasts are initialized from a model run forced only by surface wind stress. In both systems, sea surface temperature variability in the tropical Pacific is successfully initialized, but most skill is lost at lead years 2–5. Utilizing the sensitivity experiment enables us to pin down the reason for the reduced prediction skill in MPI-ESM to errors in wind stress used for the initialization. A spurious trend in the wind stress forcing displaces the equatorial thermocline in MPI-ESM unrealistically. When the climate model is then switched into its forecast mode, the recovery process triggers artificial El Niño and La Niña events at the surface. Our results demonstrate the importance of realistic wind stress products for the initialization of decadal prediction

The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

Model experiment description paperProjections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2 °C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017-2018 time frame, and output from the climate model projections made available and analyses performed over the 2018-2020 period.CRESCENDO project members (V. Eyring, P. Friedlingstein, E. Kriegler, R. Knutti, J. Lowe, K. Riahi, D. van Vuuren) acknowledge funding received from the Horizon 2020 European Union’s Framework Programme for Research and Innovation under grant agreement no. 641816. C. Tebaldi, G. A. Meehl and B. M. Sanderson acknowledge the support of the Regional and Global Climate Modeling Program (RGCM) of the U.S. Department of Energy’s, Office of Science (BER), Cooperative Agreement DE-FC02-97ER6240

Closing the sea surface mixed layer temperature budget from in situ observations alone: Operation Advection during BoBBLE

Sea surface temperature (SST) is a fundamental driver of tropical weather systems such as monsoon rainfall and tropical cyclones. However, understanding of the factors that control SST variability is lacking, especially during the monsoons when in situ observations are sparse. Here we use a ground-breaking observational approach to determine the controls on the SST variability in the southern Bay of Bengal. We achieve this through the first full closure of the ocean mixed layer energy budget derived entirely from in situ observations during the Bay of Bengal Boundary Layer Experiment (BoBBLE). Locally measured horizontal advection and entrainment contribute more significantly than expected to SST evolution and thus oceanic variability during the observation period. These processes are poorly resolved by state-of-the-art climate models, which may contribute to poor representation of monsoon rainfall variability. The novel techniques presented here provide a blueprint for future observational experiments to quantify the mixed layer heat budget on longer time scales and to evaluate these processes in models

Statistically derived contributions of diverse human influences to twentieth-century temperature changes

The warming of the climate system is unequivocal as evidenced by an increase in global temperatures by 0.8 °C over the past century. However, the attribution of the observed warming to human activities remains less clear, particularly because of the apparent slow-down in warming since the late 1990s. Here we analyse radiative forcing and temperature time series with state-of-the-art statistical methods to address this question without climate model simulations. We show that long-term trends in total radiative forcing and temperatures have largely been determined by atmospheric greenhouse gas concentrations, and modulated by other radiative factors. We identify a pronounced increase in the growth rates of both temperatures and radiative forcing around 1960, which marks the onset of sustained global warming. Our analyses also reveal a contribution of human interventions to two periods when global warming slowed down. Our statistical analysis suggests that the reduction in the emissions of ozone-depleting substances under the Montreal Protocol, as well as a reduction in methane emissions, contributed to the lower rate of warming since the 1990s. Furthermore, we identify a contribution from the two world wars and the Great Depression to the documented cooling in the mid-twentieth century, through lower carbon dioxide emissions. We conclude that reductions in greenhouse gas emissions are effective in slowing the rate of warming in the short term.F.E. acknowledges financial support from the Consejo Nacional de Ciencia y Tecnologia (http://www.conacyt.gob.mx) under grant CONACYT-310026, as well as from PASPA DGAPA of the Universidad Nacional Autonoma de Mexico. (CONACYT-310026 - Consejo Nacional de Ciencia y Tecnologia; PASPA DGAPA of the Universidad Nacional Autonoma de Mexico

Global-scale climate impact functions: the relationship between climate forcing and impact

Although there is a strong policy interest in the impacts of climate change corresponding to different degrees of climate change, there is so far little consistent empirical evidence of the relationship between climate forcing and impact. This is because the vast majority of impact assessments use emissions-based scenarios with associated socio-economic assumptions, and it is not feasible to infer impacts at other temperature changes by interpolation. This paper presents an assessment of the global-scale impacts of climate change in 2050 corresponding to defined increases in global mean temperature, using spatially-explicit impacts models representing impacts in the water resources, river flooding, coastal, agriculture, ecosystem and built environment sectors. Pattern-scaling is used to construct climate scenarios associated with specific changes in global mean surface temperature, and a relationship between temperature and sea level used to construct sea level rise scenarios. Climate scenarios are constructed from 21 climate models to give an indication of the uncertainty between forcing and response. The analysis shows that there is considerable uncertainty in the impacts associated with a given increase in global mean temperature, due largely to uncertainty in the projected regional change in precipitation. This has important policy implications. There is evidence for some sectors of a non-linear relationship between global mean temperature change and impact, due to the changing relative importance of temperature and precipitation change. In the socio-economic sectors considered here, the relationships are reasonably consistent between socio-economic scenarios if impacts are expressed in proportional terms, but there can be large differences in absolute terms. There are a number of caveats with the approach, including the use of pattern-scaling to construct scenarios, the use of one impacts model per sector, and the sensitivity of the shape of the relationships between forcing and response to the definition of the impact indicator