The goal to stabilize global average surface temperature at lower than 2°C above pre-industrial level has been extensively discussed in climate negotiations. A number of publications state that achieving this goal will require net anthropogenic carbon emissions (defined as anthropogenic emissions minus anthropogenic sinks such as carbon capture and sequestration and reforestation) to be reduced to zero between years 2050 and 2100. At the same time, it is also shown in the literature that decreases of non-CO₂ emissions can significantly affect the allowable carbon budget. In this study, we explore possible emission pathways under which surface warming will not exceed 2°C, by means of emission-driven climate simulations with an Earth System Model of Intermediate Complexity linked to an Economic Projection and Policy Analysis Model. We carried out a number of simulations from 1861 to 2500 for different values of parameters defining the strength of the climate system response to radiative forcing and the strength of the natural carbon sources and sinks under different anthropogenic emission projections. Although net anthropogenic emissions need to be reduced to zero eventually to achieve climate stabilization, the results of our simulations suggest that, by including significant reductions in non-CO₂ emissions, net carbon emissions do not have to be zero by 2050 or even 2100 to meet the 2°C target because of offsets due to the natural carbon sinks in the oceans and terrestrial ecosystems. We show that net anthropogenic carbon emissions falling from today’s 9.5 GtC/year to 2.5–7 GtC/year by 2050 and then to 1–2.8 GtC/year by 2100 are consistent with a 2°C target for a range of climate sensitivities (2.0–4.5°C) similar to the IPCC likely range. Changes in the surface temperature beyond 2100 depend on the emission profiles after 2100. For post-2100 carbon emissions decreasing at a rate of about 1.5% per year along with continued decreases in non-CO₂ emissions, our projections indicate that natural ecosystems will be able to absorb enough carbon to prevent surface temperature from rising further. A major reason for our results is that the land and ocean uptake rates are a function of the total atmospheric CO2 concentration and, due to the very long lifetime of CO₂, this does not decrease anywhere near as fast as the imposed CO₂ emissions. The required mixes of energy technologies and the overall costs to achieve the 2°C target are highly dependent on the assumptions about the future costs of low-carbon and zero-carbon emitting technologies. In all our projections, the global energy system requires substantial transformations in a relatively short time.

Carbon tetrachloride (CCl₄) is an ozone-depleting substance, which is controlled by the Montreal Protocol and for which the atmospheric abundance is decreasing. However, the current observed rate of this decrease is known to be slower than expected based on reported CCl₄ emissions and its estimated overall atmospheric lifetime. Here we use a three-dimensional (3-D) chemical transport model to investigate the impact on its predicted decay of uncertainties in the rates at which CCl₄ is removed from the atmosphere by photolysis, by ocean uptake and by degradation in soils. The largest sink is atmospheric photolysis (74 % of total), but a reported 10 % uncertainty in its combined photolysis cross section and quantum yield has only a modest impact on the modelled rate of CCl₄ decay. This is partly due to the limiting effect of the rate of transport of CCl₄ from the main tropospheric reservoir to the stratosphere, where photolytic loss occurs. The model suggests large interannual variability in the magnitude of this stratospheric photolysis sink caused by variations in transport. The impact of uncertainty in the minor soil sink (9 % of total) is also relatively small. In contrast, the model shows that uncertainty in ocean loss (17 % of total) has the largest impact on modelled CCl₄ decay due to its sizeable contribution to CCl₄ loss and large lifetime uncertainty range (147 to 241 years). With an assumed CCl₄ emission rate of 39 Gg year⁻¹, the reference simulation with the best estimate of loss processes still underestimates the observed CCl₄ (overestimates the decay) over the past 2 decades but to a smaller extent than previous studies. Changes to the rate of CCl₄ loss processes, in line with known uncertainties, could bring the model into agreement with in situ surface and remote-sensing measurements, as could an increase in emissions to around 47 Gg year⁻¹. Further progress in constraining the CCl₄ budget is partly limited by systematic biases between observational datasets. For example, surface observations from the National Oceanic and Atmospheric Administration (NOAA) network are larger than from the Advanced Global Atmospheric Gases Experiment (AGAGE) network but have shown a steeper decreasing trend over the past 2 decades. These differences imply a difference in emissions which is significant relative to uncertainties in the magnitudes of the CCl₄ sinks.

Precipitation-gauge observations and atmospheric reanalysis are combined to develop an analogue method for detecting heavy precipitation events based on prevailing large-scale atmospheric conditions. Combinations of atmospheric variables for circulation (geopotential height and wind vector) and moisture (surface specific humidity, column and up to 500-hPa precipitable water) are examined to construct analogue schemes for the winter [December–February (DJF)] of the “Pacific Coast California” (PCCA) region and the summer [June–August (JJA)] of the Midwestern United States (MWST). The detection diagnostics of analogue schemes are calibrated with 1979–2005 and validated with 2006–14 NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA). All analogue schemes are found to significantly improve upon MERRA precipitation in characterizing the occurrence and interannual variations of observed heavy precipitation events in the MWST. When evaluated with the late twentieth-century climate model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5), all analogue schemes produce model medians of heavy precipitation frequency that are more consistent with observations and have smaller intermodel discrepancies than model-based precipitation. Under the representative concentration pathways (RCP) 4.5 and 8.5 scenarios, the CMIP5-based analogue schemes produce trends in heavy precipitation occurrence through the twenty-first century that are consistent with model-based precipitation, but with smaller intermodel disparity. The median trends in heavy precipitation frequency are positive for DJF over PCCA but are slightly negative for JJA over MWST. Overall, the analyses highlight the potential of the analogue as a powerful diagnostic tool for model deficiencies and its complementarity to an evaluation of heavy precipitation frequency based on model precipitation alone.