Inference of Climate Sensitivity from Analysis of the Earth's Energy Budget Piers M. Forster School of Earth and Environment
Total Page：16
File Type：pdf, Size：1020Kb
Inference of Climate Sensitivity from Analysis of the Earth’s Energy Budget Piers M. Forster School of Earth and Environment, University of Leeds, UK [email protected] ANNUAL REVIEWS OF EARTH AND PLANETARY SCIENCES: http://www.annualreviews.org/journal/earth Submitted 14 July 2015, Revised 20 December 2015, Accepted 21 December 2015 Contact: Piers Forster School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK Email: [email protected] 1 Contents Keywords ............................................................................................................................................................. 3 Abstract ................................................................................................................................................................. 3 1 Introduction .............................................................................................................................................. 3 2 The Theoretical Basis ............................................................................................................................ 5 3 Summary of past results ...................................................................................................................... 7 4 ECS from multi-decadal data .............................................................................................................. 9 4.1 Method and periods analyzed ............................................................................................... 11 4.2 Earth’s energy Imbalance data ............................................................................................. 12 4.3 Choice of temperature data .................................................................................................... 13 4.4 Choice of forcing data ............................................................................................................... 14 4.5 Discussion ...................................................................................................................................... 17 5 ECS from interannual data ............................................................................................................... 21 5.1 Data choices .................................................................................................................................. 21 5.2 Methods .......................................................................................................................................... 23 5.3 Discussion ...................................................................................................................................... 24 6 The Way Forward ................................................................................................................................ 26 7 Side bars................................................................................................................................................... 28 8 Acknowledgements ............................................................................................................................. 29 9 References ............................................................................................................................................... 30 10 Tables ................................................................................................................................................... 42 11 Figures ................................................................................................................................................. 45 2 Keywords Transient climate response, ocean heat uptake, radiative forcing, aerosol, simple climate models Abstract Recent attempts to diagnose Equilibrium Climate Sensitivity (ECS) from changes in the Earth’s energy budget point towards values at the low-end of the Intergovernmental Panel on Climate Change Fifth Assessment Report’s (AR5) likely range (1.5 to 4.5 K). These studies employ observations but still require an element of modeling to infer ECS. Their diagnosed effective ECS over the historic period of around 2 K holds up to scrutiny but there is tentative evidence that this underestimates the true ECS from a doubling of carbon dioxide. Different choices of energy imbalance data explain most of the difference between published best estimates while effective radiative forcing (ERF) dominates the overall uncertainty. For decadal analyses the largest source of uncertainty comes from a poor understanding of the relationship between ECS and decadal feedback. Considerable progress could be made by diagnosing ERF in models. [call out sidebar 1 near first mention of ECS] 1 Introduction The equilibrium climate sensitivity (ECS) has taken on almost a mythical status in climate science as the uncertainty that will not go away. From its introduction and first assessment in Charney et al. (1979), until the latest Intergovernmental Panel on Climate Change (IPCC) report (IPCC 2013) its range has hovered 3 around 1.5- 4.5 K. This temperature range represents the uncertainty in global mean warming for a sustained doubling of background carbon dioxide levels. The seeming intransigence of the uncertainty range belies huge improvements in our understanding and quantification of many aspects of climate, including its sensitivity. It is too simplistic to compare the 1979 range to the 2013 range and say that we are no better off. The 1979 Charney range was a subjective judgment based on two basic global climate models. In contrast the 2013 AR5 range was an assessment of multiple lines of evidence including comparing the latest climate models to observations, understanding of the historical record, the paleoclimate record and investigations of changes in the Earth’s energy budget. Additionally the science community has realized that a factor of three uncertainty in ECS does not necessarily imply a factor of three uncertainty in projected warming. A related quantity, the transient climate response (TCR), is much more important for defining warming of the coming century. TCR is defined as how much the world would warm after 70 years of continually increasing CO2 levels (at 1% per year) has a smaller uncertainty range (1.0- 2.5 C, IPCC 2013). As well as the uncertainty in TCR, future climate is affected by uncertainties in projected emissions and feedbacks with the Earth system (such as methane release from Arctic tundra). Further, the impacts of climate are locally realized and future regional rainfall changes (for instance) are not uniquely determined by global temperature change or ECS (Andrews et al 2010). Nevertheless, ECS remains important to constrain, both for its status as a talisman of climate science and for fundamentally understanding how the Earth’s temperature responds to perturbations in its energy budget. 4 Compared to its Fourth Assessment Report (AR4) (IPCC 2007), AR5 reduced its lower bound from 2°C to 1.5 °C and did not make a best estimate. This was a result of publications deriving ECS from the instrumental record (recent historic temperatures and top of atmosphere energy change) tending to have a lower ECS best estimate compared to that from other lines of evidence (see Box 12.2, Figure 2 of Collins et al. (2013)). Since publication of the AR5 report it appears that the instrumental based approaches have continued to diverge from the approaches that compare model climatologies to observation. The purpose of this review article is to critically examine these energy budget approaches and search for possible causes of discrepancy from the different lines of evidence. Section 2 introduces the theoretical basis, Section 3 critically examines past studies concentrating of those published since AR5, Section 4 examines uncertainty in deriving ECS from multi decadal trends, Section 5 examines shorter-timescale approached and Section 6 points to the way forward. 2 The Theoretical Basis The time dependent energy imbalance, 푁 of the Earth (taken as positive downwards), can be split into forcing, response and noise term such that 푁 = 퐹 − 훼푇 + 훾 (1) (e.g. Forster & Gregory 2006, Gregory et al 2002). 퐹 is the radiative forcing, 푇 the globally averaged surface temperature change; 훾 represents a noise term whereby 푁 could be affected by variability unrelated to 푇 (discussed in Section 5); 훼 is the climate feedback parameter which gives the dependency of 푁 on 푇, 5 such that 훼 = −훿푁/훿푇. This formulation is a linear approximation to the global energy budget and remains valid provided T is small. Fourier (1827) was the first to associate planetary temperature with its top of atmosphere energy budget. Stefan (1879) used existing laboratory measurements to deduce the relationship between the temperature of a body and its emitted radiation. This relationship became known as the Stefan Boltzmann law, one of the underpinning laws of physics. Early authors realized that the Earth’s effective emission temperature and its surface temperature were not the same but could be straightforwardly connected through the gray body 4 approximation. 푁 could therefore also be written as 푁 = 퐴푆푅 − 휀휎푇푠 , where ASR is the absorbed solar radiation, 휀 the assumed gray body emissivity of the Earth and 푇푠 the absolute surface temperature. This can be differentiated to give a value for α, assuming the Earth has a blackbody response, such that 훼퐵퐵 = 3 4휀푇푠 . Arrhenius (1896), building on the work of Tyndall (1861), already knew about the role of water vapor and cloud feedbacks