L. K. Gohar

Radiative Forcing by Well-Mixed Greenhouse Gases: Estimates from Climate Models in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4)

The radiative effects from increased concentrations of well-mixed greenhouse gases (WMGHGs) represent the most significant and best understood anthropogenic forcing of the climate system. The most comprehensive tools for simulating past and future climates influenced by WMGHGs are fully coupled atmosphere-ocean general circulation models (AOGCMs). Because of the importance of WMGHGs as forcing agents it is essential that AOGCMs compute the radiative forcing by these gases as accurately as possible. We present the results of a radiative transfer model intercomparison between the forcings computed by the radiative parameterizations of AOGCMs and by benchmark line-by-line (LBL) codes. The comparison is focused on forcing by CO2, CH4, N2O, CFC-11, CFC-12, and the increased H2O expected in warmer climates. The models included in the intercomparison include several LBL codes and most of the global models submitted to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). In general, the LBL models are in excellent agreement with each other. However, in many cases, there are substantial discrepancies among the AOGCMs and between the AOGCMs and LBL codes. In some cases this is because the AOGCMs neglect particular absorbers, in particular the near-infrared effects of CH4 and N2O, while in others it is due to the methods for modeling the radiative processes. The biases in the AOGCM forcings are generally largest at the surface level. We quantify these differences and discuss the implications for interpreting variations in forcing and response across the multimodel ensemble of AOGCM simulations assembled for the IPCC AR4.

The link between a global 2 °C warming threshold and emissions in years 2020, 2050 and beyond

In the Copenhagen Accord, nations agreed on the need to limit global warming to two degrees to avoid potentially dangerous climate change, while in policy circles negotiations have placed a particular emphasis on emissions in years 2020 and 2050. We investigate the link between the probability of global warming remaining below two degrees (above pre-industrial levels) right through to year 2500 and what this implies for emissions in years 2020 and 2050, and any long-term emissions floor. This is achieved by mapping out the consequences of alternative emissions trajectories, all in a probabilistic framework and with results placed in a simple-to-use set of graphics. The options available for carbon dioxide-equivalent (CO2e) emissions in years 2020 and 2050 are narrow if society wishes to stay, with a chance of more likely than not, below the 2 C target. Since cumulative emissions of long-lived greenhouse gases, and particularly CO2, are a key determinant of peak warming, the consequence of being near the top of emissions in the allowable range for 2020 is reduced flexibility in emissions in 2050 and higher required rates of societal decarbonization. Alternatively, higher 2020 emissions can be considered as reducing the probability of limiting warming to 2 C. We find that the level of the long-term emissions floor has a strong influence on allowed 2020 and 2050 emissions for two degrees of global warming at a given probability. We place our analysis in the context of emissions pledges for year 2020 made at the end of and since the 2009 COP15 negotiations in Copenhagen.

Changes in climate extremes, fresh water availability and vulnerability to food insecurity projected at 1.5°C and 2°C global warming with a higher-resolution global climate model

We projected changes in weather extremes, hydrological impacts and vulnerability to food insecurity at global warming of 1.5°C and 2°C relative to pre-industrial, using a new global atmospheric general circulation model HadGEM3A-GA3.0 driven by patterns of sea-surface temperatures and sea ice from selected members of the 5th Coupled Model Intercomparison Project (CMIP5) ensemble, forced with the RCP8.5 concentration scenario. To provide more detailed representations of climate processes and impacts, the spatial resolution was N216 (approx. 60 km grid length in mid-latitudes), a higher resolution than the CMIP5 models. We used a set of impacts-relevant indices and a global land surface model to examine the projected changes in weather extremes and their implications for freshwater availability and vulnerability to food insecurity. Uncertainties in regional climate responses are assessed, examining ranges of outcomes in impacts to inform risk assessments. Despite some degree of inconsistency between components of the study due to the need to correct for systematic biases in some aspects, the outcomes from different ensemble members could be compared for several different indicators. The projections for weather extremes indices and biophysical impacts quantities support expectations that the magnitude of change is generally larger for 2°C global warming than 1.5°C. Hot extremes become even hotter, with increases being more intense than seen in CMIP5 projections. Precipitation-related extremes show more geographical variation with some increases and some decreases in both heavy precipitation and drought. There are substantial regional uncertainties in hydrological impacts at local scales due to different climate models producing different outcomes. Nevertheless, hydrological impacts generally point towards wetter conditions on average, with increased mean river flows, longer heavy rainfall events, particularly in South and East Asia with the most extreme projections suggesting more than a doubling of flows in the Ganges at 2°C global warming. Some areas are projected to experience shorter meteorological drought events and less severe low flows, although longer droughts and/or decreases in low flows are projected in many other areas, particularly southern Africa and South America. Flows in the Amazon are projected to decline by up to 25%. Increases in either heavy rainfall or drought events imply increased vulnerability to food insecurity, but if global warming is limited to 1.5°C, this vulnerability is projected to remain smaller than at 2°C global warming in approximately 76% of developing countries. At 2°C, four countries are projected to reach unprecedented levels of vulnerability to food insecurity. This article is part of the theme issue ‘The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels’.

The Impact of Bias Correction and Model Selection on Passing Temperature Thresholds

Knowledge of when specific global or local temperature levels are reached is important for decision makers in that it provides a time frame over which adaptation strategies for temperature related climate impacts need to be put in place. The time frame varies depending on the adaptation strategy but can range from a few years to the order of decades. Climate models, however, show a high degree of uncertainty in the timing of passing specific warming levels, limiting their use in adaptation policy development. This study examines the impact of two approaches, which may reduce the uncertainty in modeled timing of reaching specific warming levels. Firstly, the use of different performance metrics to preferentially weight model ensembles and secondly, the application of four bias correction approaches. Using the CMIP5 simulations of the RCPs, our results show that selecting models based on performance or bias correcting model data both reduce the spread in timing of specific warming levels reached in the first half of the century by up to 50% in some regions. This implies the potential of these approaches to support adaptation planning.