• Energy Research

Significance One of the most concerning consequences of human-induced increases in atmospheric greenhouse gas concentrations is the potential for rapid regional transitions in the climate system. Yet, despite much public awareness of how “tipping points” may be crossed, little information is available as to exactly what may be expected in the coming centuries. We assess all Earth System Models underpinning the recent 5th Intergovernmental Panel on Climate Change report and systematically search for evidence of abrupt changes. We do find abrupt changes in sea ice, oceanic flows, land ice, and terrestrial ecosystem response, although with little consistency among the models. A particularly large number is projected for warming levels below 2°. We discuss mechanisms and include methods to objectively classify abrupt climate change.

During summer 2007 the Arctic sea-ice shrank to the lowest extent ever observed. The role of the atmospheric energy transport in this extreme melt event is explored using the state-of-the-art ERA-Interim reanalysis data. We find that in summer 2007 there was an anomalous atmospheric flow of warm and humid air into the region that suffered severe melt. This anomaly was larger than during any other year in the data (1989-2008). Convergence of the atmospheric energy transport over this area led to positive anomalies of the downward longwave radiation and turbulent fluxes. In the region that experienced unusual ice melt, the net anomaly of the surface fluxes provided enough extra energy to melt roughly one meter of ice during the melting season. When the ocean successively became ice-free, the surface-albedo decreased causing additional absorption of shortwave radiation, despite the fact that the downwelling solar radiation was smaller than average. We argue that the positive anomalies of net downward longwave radiation and turbulent fluxes played a key role in initiating the 2007 extreme ice melt, whereas the shortwave-radiation changes acted as an amplifying feedback mechanism in response to the melt. © 2010 Springer-Verlag.

Project: IPCC Data Distribution Centre : Supplementary data sets for the Sixth Assessment Report - For the Sixth Assessment Report of the IPCC (AR6) input/source and intermediate datasets underlying the AR6 were collected and long-term archived. This project compliments CMIP6 data subset and snapshot analyzed for the WGI AR6. Summary: This data set contains detailed elements the sea level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. In particular, it contains relative sea level projections that exclude the background term (representing primarily land subsidence or uplift). It includes probability distributions for all the workflows described in AR6 WGI 9.6.3.2. P-boxes derived from these distributions are available in the sister entry 'IPCC-DDC_AR6_Sup_PBox'. These data may be of use for users who want to substitute their own estimates of the background term. Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool. See https://zenodo.org/communities/ipcc-ar6-sea-level-projections for additional related data sets.

These data sets contain the sea level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. The dataset groups contain the full set of samples for the global projections (see IPCC AR6 WGI Sea Level Projections global) as well as summary relative sea level projections (see IPCC AR6 WGI Sea Level Projections regional and, without the AR6 estimate of background sea level process rates, see IPCC AR6 WGI Sea Level Projections regional novlm). The confidence output files correspond most directly to the figures and tables in the report. The IPCC AR6 sea level change projection files are provided in a simplified format but represent a more complicated workflow involving combinations of multiple lines of evidence for the various individual contributors to sea level change. It's highly recommended using the data as provided in the confidence output files to remain consistent with the assessment in IPCC AR6 Chapter 9 (see IPCC AR6 WGI Sea Level Projections HowTos for details). Required Acknowledgements and Citation: In order to document the impact of these sea level rise projections, users of the data are obligated to cite chapter 9 of WGI contribution to the IPCC AR6, the FACTS model description paper, and the version of the data set used. When using these data in a publication, please include the information provided in IPCC AR6 WGI Sea Level Projections Acknowledgments. Disclaimer: The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law. Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool. See https://zenodo.org/communities/ipcc-ar6-sea-level-projections for additional related data sets.

This data set contains detailed elements the sea level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. In particular, it contains relative sea level projections that exclude the background term (representing primarily land subsidence or uplift). It includes probability distributions for all the workflows described in AR6 WGI 9.6.3.2. P-boxes derived from these distributions are available in the sister entry 'IPCC-DDC_AR6_Sup_PBox '. These data may be of use for users who want to substitute their own estimates of the background term. Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool. See https://zenodo.org/communities/ipcc-ar6-sea-level-projections for additional related data sets.

Significance There is a long-standing debate about whether climate models are able to simulate large, abrupt events that characterized past climates. Here, we document a large, spontaneously occurring cold event in a preindustrial control run of a new climate model. The event is comparable to the Little Ice Age both in amplitude and duration; it is abrupt in its onset and termination, and it is characterized by a long period in which the atmospheric circulation over the North Atlantic is locked into a state with enhanced blocking. To simulate this type of abrupt climate change, climate models should possess sufficient resolution to correctly represent atmospheric blocking and a sufficiently sensitive sea-ice model.

AbstractPast studies have concluded that climate models of previous generations tended to underestimate the large warming trend that has been observed in summer over western Europe in the last few decades. The causes of this systematic error are still not clear. Here, we investigate this issue with a new generation of climate models and systematically explore the role of large-scale circulation in that context.As an ensemble, climate models in this study warm less over western Europe and warm more over eastern Europe than observed on the 1951–2014 period, but it is difficult to conclude this is directly due to systematic errors given the large potential impact of internal variability. These differences in temperature trends are explained to an important extent by an anti-correlation of sea level pressure trends over the North Atlantic / Europe domain between models and observations. The observed trend tends to warm (cool) western (eastern) Europe but the simulated trends generally have the opposite effect, both in new generation and past generation climate models. The differences between observed and simulated sea level pressure trends are likely the result of systematic model errors, which might also impact future climate projections. Neither a higher resolution nor the realistic representation of the evolution of sea surface temperature and sea ice leads to a better simulation of sea level pressure trends.