Identifying Key Sources of Uncertainty in Climate Change Projections

What sources of uncertainty shouldbe included in climate change projections and whatgains can be made if specific sources of uncertaintyare reduced through improved research?DIALOGUE, anintegrated assessment model, has been used to answerthese questions. Central in the approach of DIALOGUEis the concept of parallel modeling, i.e., for eachstep in the chain from emissions to climate change anumber of equivalent models areimplemented. The followingconclusions are drawn:The key source of uncertainty in global temperatureprojections appears to be the uncertainty inradiative forcing models. Within this group ofmodels uncertainty within aerosol forcing models isabout equal to the total forcing of greenhouse gasmodels. In the latter group CO₂ is dominant.The least important source of uncertainty appears tobe the gas cycle models. Within this group of modelsthe role of carbon cycle models is dominant.Uncertainty in global temperature projections hasnot been treated consistently in the literature.First, uncertainty should be calculated as a productof all uncertainty sources. Second, aparticular choice of a base year for global warmingcalculations influences the ranking of uncertainty.Because of this, a comparison of ranking resultsacross different studies is hampered. We argue that`pre-Industrial' is the best choice for studies onuncertainty.There is a linear relationship between maximumuncertainty in the year 2100 and cumulativeemissions of CO₂ over the period 1990–2100:higher emissions lead to more uncertainty.     

A Demonstration of the Uncertainty in Projections of UK Climate Change Resulting from Regional Model Formulation

Regional climate models (RCMs) are now commonly used to downscale climate change projections provided by global coupled models to resolutions that can be utilised at national and finer scales. Although this extra tier of complexity adds significant value, it inevitably contributes a further source of uncertainty, due to the regional modelling uncertainties involved. Here, an initial attempt is made to estimate the uncertainty that arises from typical variations in RCM formulation, focussing on changes in UK surface air temperature (SAT) and precipitation projected for the late twenty-first century. Data are provided by a relatively large suite of RCM and global model integrations with widely varying formulations. It is found that uncertainty in the formulation of the RCM has a relatively small, but non-negligible, impact on the range of possible outcomes of future UK seasonal mean climate. This uncertainty is largest in the summer season. It is also similar in magnitude to that of large-scale internal variations of the coupled climate system, and for SAT, it is less than the uncertainty due to the emissions scenario, whereas for precipitation it is probably larger. The largest source of uncertainty, for both variables and in all seasons, is the formulation of the global coupled model. The scale-dependency of uncertainty due to RCM formulation is also explored by considering its impact on projections of the difference in climate change between the north and south of the UK. Finally, the implications for the reliability of UK seasonal mean climate change projections are discussed.     

Uncertainty in Regional Climate Model Mean Runoff Projections under Climate Change: Case Study of Labrador's Churchill River Basin

An ensemble of seven climate models from the North American Regional Climate Change Assessment Program (NARCCAP) was used to examine uncertainty in simulated runoff changes from a base period (1971–2000) to a future period (2041–2070) for the Churchill River basin, Labrador, Canada. Three approximations for mean annual runoff from each ensemble member were included in the analysis: (i) atmospheric moisture convergence, (ii) the balance between precipitation and evaporation, and (iii) instantaneous runoff output from respective land-surface schemes. Using data imputation (i.e., reconstruction) and variance decomposition it was found that choice of regional climate model (RCM) made the greatest contribution to uncertainty in the climate change signal, whereas the boundary forcing of a general circulation model (GCM) played a smaller, though non-negligible, role. It was also found that choice of runoff approximation made a substantial contribution to uncertainty, falling between the contribution from RCM and GCM choice. The NARCCAP output and imputed data were used to calculate mean and median annual changes and results were presented via probability distribution functions to facilitate decision making. Mean and median increases in runoff for the basin were found to be 11.2% and 8.9%, respectively.     

全球气候变化预估最新研究进展

总结了近5 a来对全球气候变化预估的研究进展,着重分析和介绍近几年全球气候变化预估研究的特点,热点和难点。     

IPCC第五次评估报告全球和区域气候预估图集评述

正与以往4次IPCC评估报告~①相比,第五次评估报告(AR5)增加了附录一:"全球和区域气候预估图集"~([1])。该图集是AR5的特色之一,它利用国际耦合模式比较计划第五阶段(CMIP5)~([2])全球气候模式的部分数据,给出了一系列全球和区域气候变化的图形。这些图形显示了全球和若干不同次大陆尺度区域在不同季节的表面气温变化和降水相对变化     

Projections of Climate Change over China for the 21st Century

1. IntroductionUnder the background of global warming in the20th century, it was also getting warmer of 0.2-0.7°C/100 yr over China for the last 100 years, espe-cially for the last 50 years (0.6-0.9°C/50 yr) based onthe instrumental observations (Wang and Gong, 2000;Ren et al., 2004; Zhao et al., 2004). In another way, itwas noticed that the concentration of greenhouse gasesand sulfate aerosols in the atmosphere increased by thehuman emissions. Some new evidences indicated thatthe greenho…     

Communicating Uncertainty in Climate Information for China: Recommendations and Lessons Learned for Climate Services

Uncertainty is an inherent characteristic of climate forecasts and projections.While there is an expanding body of international research on identifying what cl...     

Temperature Extremes from Canadian Regional Climate Model (CRCM) Climate Change Projections

Future climate projections of extreme events can help forewarn society of high-impact events and allow the development of better adaptation strategies. In this study a non-stationary model for Generalized Extreme Value (GEV) distributions is used to analyze the trend in extreme temperatures in the context of a changing climate and compare it with the trend in average temperatures.

The analysis is performed using the climate projections of the Canadian Regional Climate Model (CRCM), under an IPCC SRES A2 greenhouse gas emissions scenario, over North America. Annual extremes in daily minimum and maximum temperatures are analyzed. Significant positive trends for the location parameter of the GEV distribution are found, indicating an expected increase in extreme temperature values. The scale parameter of the GEV distribution, on the other hand, reveals a decrease in the variability of temperature extremes in some continental regions. Trends in the annual minimum and maximum temperatures are compared with trends in average winter and summer temperatures, respectively. In some regions, extreme temperatures exhibit a significantly larger increase than the seasonal average temperatures.

The CRCM projections are compared with those of its driving model and framed in the context of the Coupled Model Intercomparison Project, phase 3 (CMIP3) Global Climate Model projections. This enables us to establish the CRCM position within the CMIP3 climate projection uncertainty range. The CRCM is validated against the HadEX2 dataset in order to assess the CRCM representation of temperature extremes in the present climate. The validation is also framed in the context of CMIP3 validation results. The CRCM cold extremes validate better and are closer to the driving model and CMIP3 projections than the hot extremes.     

中国干湿变化的高分辨率区域气候模式预估

本文使用三个全球气候模式驱动下的高分辨率区域气候模式RegCM4的试验数据,首先评估了RegCM4对参考时段（1986～2005年）中国干燥度指数（AI）的模拟能力,而后根据典型浓度路径中等排放（RCP4.5）情景下RegCM4试验对中国未来干湿变化进行了预估研究。结果表明,RegCM4能够合理模拟中国区域AI的空间分布。两种潜在蒸散发计算方法得到的参考时段AI在空间分布和数值上存在一定差异,尤其是在中国西部高海拔地区和北方地区。在三个全球气候模式驱动场作用下的RegCM4预估试验中,21世纪中期（2046～2065年）和末期（2081～2098年）中国区域平均AI较参考时段分别减小2%～4%和2%～5%,其中西北中部变湿,其他地区均变干。不同地区未来干湿变化的主要影响因素存在差异,西北中部降水变化为主导因素,其他地区主要受控于升温所引起的潜在蒸散发变化。     

试论短期气候预测的不确定性

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Statistical Projections of Ocean Climate Indices off Newfoundland and Labrador

ABSTRACT

Present global climate models (GCMs) are unable to provide reliable projections of physical oceanographic properties on the continental shelf off Newfoundland and Labrador. Here we first establish linear statistical relationships between oceanographic properties and coastal air temperature based on historical observations. We then use these relationships to project future states of oceanographic conditions under different emission scenarios, based on projected coastal air temperatures from global (Canadian Earth System Model, version 2 (CanESM2), Geophysical Fluid Dynamics Laboratory's Earth System Model, version 2M (GFDL-ESM2M)) and regional (Canadian Regional Climate Model (CRCM)) climate models. Estimates based on CanESM2 agree reasonably well with observed trends, but the trends based on two other models result in substantial underestimates. Projected trends are closer to observations under a high emission scenario than under median-level emission scenarios. Over the next 50 years, the increases in projected sea surface temperature off eastern Newfoundland (Station 27) range from 0.4° to 2.2°C. The increases in bottom ocean temperature over the Newfoundland and Labrador Shelves range from 0.4° to 2.1°C. The area of the cold intermediate layer (<0°C) on the Flemish Cap (47°N) section is projected to decrease by 9–35% of the 1981–2010 average. The decline in sea-ice extent off Newfoundland and Labrador ranges from 20 to 77% of the average (0.4–1.5?×?10⁵?km²), and the reduction in the number of icebergs at 48°N off Newfoundland ranges from 30% to nearly 100% of the norm at this latitude. Despite differences among the models and scenarios, statistical projections indicate that conditions in this region will reach or exceed their maxima (sea surface temperature, bottom ocean temperature) and reach or fall below their minima (sea-ice extent, number of icebergs) that were observed during the course of monitoring activities over the past 30–60 years, possibly as early as 2040. We note, however, that the statistical relationships based on historical data may not hold in the future because of the changing influence of input from Arctic waters and because of large uncertainties in projected air temperatures from GCMs.     

气候模式对北冰洋地区气候变化模拟评估和未来预估

正在全球气候变化研究中,北冰洋地区(包括北冰洋海水和海冰区以及周边陆地和岛屿积雪冻土区)受到极大的重视,因为在全球变暖中,北冰洋的变暖和海冰融化是最引起注意的问题之一。因此,气候模式对北冰洋地区气候变化的模拟评估以及对未来的预估,受到极大的重视,本文将综述近些年这方面的研究~([1-4])。     

Climate Comparisons and Change Projections for the Northwest Atlantic from Six CMIP5 Models

Abstract

Key physical variables for the Northwest Atlantic (NWA) are examined in the “historical” and two future Representative Concentration Pathway (RCP) simulations of six Earth System Models (ESMs) available through Phase 5 of the Climate Model Intercomparison Project (CMIP5). The variables are air temperature, sea-ice concentration, surface and subsurface ocean temperature and salinity, and ocean mixed-layer depth. Comparison of the historical simulations with observations indicates that the models provide a good qualitative and approximate quantitative representation of many of the large-scale climatological features in the NWA (e.g., annual cycles and spatial patterns). However, the models represent the detailed structure of some important NWA ocean and ice features poorly, such that caution is needed in the use of their projected future changes. Monthly “climate change” fields between the bidecades 1986–2005 and 2046–2065 are described, using ensemble statistics of the changes across the six ESMs. The results point to warmer air temperatures everywhere, warmer surface ocean temperatures in most areas, reduced sea-ice extent and, in most areas, reduced surface salinities and mixed-layer depths. However, the magnitudes of the inter-model differences in the projected changes are comparable to those of the ensemble-mean changes in many cases, such that robust quantitative projections are generally not possible for the NWA.     

Optimal Technology R&D in the Face of Climate Uncertainty

This paper explores optimal near-term technology R&D in the face of uncertain damages caused by the buildup of greenhouse gases. The paper puts particular emphasis on understanding how optimal near-term R&D expenditures might vary based on the technologies pursued in the R&D program. The exploration is conducted in the context of varying impacts from R&D on the global abatement cost function. The R&D planning problem is considered first within a theoretical framework and is then pursued in a stylized application using the DICE model. The paper provides intuition into the circumstances under which near-term technology R&D might increase or decrease under uncertainty, thereby serving as a hedge against climate uncertainty.     

Planning for Sea Level Rise and Shore Protection Under Climate Uncertainty

Attention is focused here on the effect of additional sources of uncertainty derived from climate change on the cost-benefit procedures applied by coastal planners to evaluate shoreline protection projects. The largest effect would be felt if planners were trying to achieve the first best economic optimum. Given the current view that the seas will rise by significantly less than one meter through the year 2100, present procedures should work reasonably well assuming (1) informed vigilance in monitoring the pace of future greenhouse induced sea level rise, (2) careful attention to the time required for market-based adaptation to minimize the economic cost of abandonment, and (3) firm support of the credibility of an announced policy to proceed with plans to retreat from the sea when warranted. Assumptions (1) and (2) might be satisfied in reality, even cursory review of existing policy makes it clear that meeting (3) is a "long shot" at the very best. In any case, planners should periodically revisit potential protection sites, especially in the wake of catastrophic events, to assess the impact of the most recent information on sea level rise trajectories, local development patterns, and protection costs on the decision calculus.     

Reducing Uncertainties in Climate Projections with Emergent Constraints:Concepts,Examples and Prospects

Models disagree on a significant number of responses to climate change, such as climate feedback, regional changes,or the strength of equilibrium climate sensitivity. Emergent constraints aim to reduce these uncertainties by finding links between the inter-model spread in an observable predictor and climate projections. In this paper, the concepts underlying this framework are recalled with an emphasis on the statistical inference used for narrowing uncertainties, and a review of emergent constr...     

Uncertainty in Projection of Climate Extremes: A Comparison of CMIP5 and CMIP6

Climate projections by global climate models(GCMs) are subject to considerable and multi-source uncertainties.This study aims to compare the uncertainty in projection of precipitation and temperature extremes between Coupled Model Intercomparison Project(CMIP) phase 5(CMIP5) and phase 6(CMIP6), using 24 GCMs forced by 3 emission scenarios in each phase of CMIP. In this study, the total uncertainty(T) of climate projections is decomposed into the greenhouse gas emission scenario uncertainty(S, mean inter-scenario variance of the signals over all the models), GCM uncertainty(M, mean inter-model variance of signals over all emission scenarios), and internal climate variability uncertainty(V, variance in noises over all models, emission scenarios, and projection lead times); namely,T = S + M + V. The results of analysis demonstrate that the magnitudes of S, M, and T present similarly increasing trends over the 21 st century. The magnitudes of S, M, V, and T in CMIP6 are 0.94–0.96, 1.38–2.07, 1.04–1.69, and 1.20–1.93 times as high as those in CMIP5. Both CMIP5 and CMIP6 exhibit similar spatial variation patterns of uncertainties and similar ranks of contributions from different sources of uncertainties. The uncertainty for precipitation is lower in midlatitudes and parts of the equatorial region, but higher in low latitudes and the polar region. The uncertainty for temperature is higher over land areas than oceans, and higher in the Northern Hemisphere than the Southern Hemisphere. For precipitation, T is mainly determined by M and V in the early 21 st century, by M and S at the end of the 21 st century; and the turning point will appear in the 2070 s. For temperature, T is dominated by M in the early 21 st century, and by S at the end of the 21 st century, with the turning point occuring in the 2060 s. The relative contributions of S to T in CMIP6(12.5%–14.3% for precipitation and 31.6%–36.2% for temperature) are lower than those in CMIP5(15.1%–17.5% for precipitation and 38.6%–43.8% for temperature). By contrast, the relative contributions of M in CMIP6(50.6%–59.8% for precipitation and 59.4%–60.3% for temperature) are higher than those in CMIP5(47.5%–57.9% for precipitation and 51.7%–53.6% for temperature). The higher magnitude and relative contributions of M in CMIP6 indicate larger difference among projections of various GCMs. Therefore, more GCMs are needed to ensure the robustness of climate projections.