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.

The growth in global methane (CH4) concentration, which had been ongoing since the industrial revolution, was observed to stall around the year 2000, before resuming globally in 2007. Here, we evaluate the role of the hydroxyl radical (OH), the major CH4 sink, in the recent CH4 growth. We also examine the influence of systematic uncertainties in OH on CH4 emissions inferred from atmospheric observations. We use observations of 1,1,1-trichloroethane (CH3CCl3), which is lost primarily through reaction with OH, to estimate OH levels as well as CH3CCl3 emissions, whose uncertainty has previously limited the accuracy of OH estimates. We find a 61% - 73% probability that a decline in OH has contributed to the post-2007 methane rise. Our median solution suggests that CH4 emissions increased relatively steadily during the late 1990s and early 2000s, after which, growth was more modest. This solution obviates the need for a sudden, statistically significant change in total CH4 emissions around the year 2007 to explain the atmospheric observations, and contributes to the decline in the atmospheric 13CH4/12CH4 ratio. Our approach indicates that significant OH-related uncertainties in the CH4 budget remain, and we find that it is not possible to implicate, with a high degree of confidence, rapid global CH4 emissions changes as the primary driver of recent trends, when our inferred OH trends and these uncertainties are considered.

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.