Why radiative forcing might fail as a predictor of climate change

Radiative forcing has been widely used as a metric of climate change, i.e. as a measure by which various contributors to a net surface temperature change can be quantitatively compared. The extent to which this concept is valid for spatially inhomogeneous perturbations to the climate system is tested. A series of climate model simulations involving ozone changes of different spatial structure reveals that the climate sensitivity parameter is highly variable: for an ozone increase in the northern hemisphere lower stratosphere, it is more than twice as large as for a homogeneous CO₂ perturbation. A global ozone perturbation in the upper troposphere, however, causes a significantly smaller surface temperature response than CO₂. The variability of the climate sensitivity parameter is shown to be mostly due to the varying strength of the stratospheric water vapour feedback. The variability of the sea-ice albedo feedback modifies climate sensitivity of perturbations with the same vertical structure but a different horizontal structure. This feedback is also the origin of the comparatively larger climate sensitivity to perturbations restricted to the northern hemisphere extratropics. As cloud feedback does not operate independently from the other feedbacks, quantifying its effect is rather difficult. However, its effect on the variability of for horizontally and vertically inhomogeneous perturbations within one model framework seems to be comparatively small.This revised version was published online March 2005 with corrections to table 5.     

Climate change in fact and in theory: Are we collecting the facts?

For the past 100 years, a mostly volunteer group of observers has formed the backbone of the U.S. National Weather Service (NWS) Cooperative (CO-OP) network. These stations have provided most of the observations used to satisfy the Department of Commerce's statutory mandate of 1890... to establish and record the climatic conditions of the United States (15 USCA 313). Originally, this network was intended primarily for agriculture, but many other uses of the data have since emerged, such as the climatic planning of weather sensitive activities, input to engineering design studies, and input and verification for weather and river forecasts. In recent years, heightened awareness regarding climatic change and variability has challenged this network with yet another mission: the monitoring and detection of climate change. While not designed for that mission, the CO-OP network has proved useful in this respect. However, with some changes in operation, it could become even more valuable in monitoring for climatic change, and could do so in a most economical way. Similar practices instituted worldwide will be necessary for comprehensive study of climate change to the degrees of detail necessary to address specific policy issues and practical local-scale decision making.     

Vulnerability of Island Tropical Montane Cloud Forests to Climate Change, with Special Reference to East Maui, Hawaii

Island tropical montane cloud forests may be among the most sensitive of the world's ecosystems to global climate change. Measurements in and above a montane cloud forest on East Maui, Hawaii, document steep microclimatic gradients. Relatively small climate-driven shifts in patterns of atmospheric circulation are likely to trigger major local changes in rainfall, cloud cover, and humidity. Increased interannual variability in precipitation and hurricane incidence would provide additional stresses on island biota that are highly vulnerable to disturbance-related invasion of non-native species. Because of the exceptional sensitivity of these microclimates and forests to change, they may provide valuable listening posts for detecting the onset of human-induced global climate change.     

利用红外卫星云图资料估计降水量方法的研究

在条件气候均匀及范围足够大取样区域,研讨面平均雨强与云覆盖率、云顶表面亮度温度的标准偏差、云覆盖率时间的变化率三者之间的关系,得到用１ｈ间隔的数字化红外卫星资料估计降水的三种模式。通过对１９９１年７月５日、６日、１０日降水过程的实例分析表明,对于日降水量的估计,效果较为理想。模式可用于与邓样时间和地点的相似气象条件区,且不需要对云进行分离和跟踪、考察对流单体的生命史演变过程,便于应用。     

Assessing the Consequences of Climate Change for Food and forest Resources: A View from the IPCC

Important findings on the consequences of climate change for agriculture and forestry from the recently completed Third Assessment Report (TAR) of the Intergovernmental Panel on Climate Change (IPCC) are reviewed, with emphasis on new knowledge that emerged since the Second Assessment Report (SAR). The State-Pressure-Response-Adaptation model is used to organize the review. The major findings are:

• Constant or declining food prices are expected for at least the next 25 yr, although food security problems will persist in many developing countries as those countries deal with population increases, political crisis, poor resource endowments, and steady environmental degradation. Most economic model projections suggest that low relative food prices will extend beyond the next 25 yr, although our confidence in these projections erodes farther out into the 21st century.
• Although deforestation rates may have decreased since the early 1990s, degradation with a loss of forest productivity and biomass has occurred at large spatial scales as a result of fragmentation, non-sustainable practices and infrastructure development.
• According to United Nations estimates, approximately 23% of all forest and agricultural lands were classified as degraded over the period since World War II.
• At a worldwide scale, global change pressures (climate change, land-use practices and changes in atmospheric chemistry) are increasingly affecting the supply of goods and services from forests.
• The most realistic experiments to date – free air experiments in an irrigated environment – indicate that C₃ agricultural crops in particular respond favorably to gradually increasing atmospheric CO₂ concentrations (e.g., wheat yield increases by an average of 28%), although extrapolation of experimental results to real world production where several factors (e.g., nutrients, temperature, precipitation, and others) are likely to be limiting at one time or another remains problematic. Moreover, little is known of crop response to elevated CO₂ in the tropics, as most of the research has been conducted in the mid-latitudes.
• Research suggests that for some crops, for example rice, CO₂ benefits may decline quickly as temperatures warm beyond optimum photosynthetic levels. However, crop plant growth may benefit relatively more from CO₂ enrichment in drought conditions than in wet conditions.
• The unambiguous separation of the relative influences of elevated ambient CO₂ levels, climate change responses, and direct human influences (such as present and historical land-use change) on trees at the global and regional scales is still problematic. In some regions such as the temperate and boreal forests, climate change impacts, direct human interventions (including nitrogen-bearing pollution), and the legacy of past human activities (land-use change) appear to be more significant than CO₂ fertilization effects. This subject is, however an area of continuing scientific debate, although there does appear to be consensus that any CO₂ fertilization effect will saturate (disappear) in the coming century.
• Modeling studies suggest that any warming above current temperatures will diminish crop yields in the tropics while up to 2–3 ^°C of warming in the mid-latitudes may be tolerated by crops, especially if accompanied by increasing precipitation. The preponderance of developing countries lies in or near the tropics; this finding does not bode well for food production in those countries.
• Where direct human pressures do not mask them, there is increasing evidence of the impacts of climate change on forests associated with changes in natural disturbance regimes, growing season length, and local climatic extremes.
• Recent advances in modeling of vegetation response suggest that transient effects associated with dynamically responding ecosystems to climate change will increasingly dominate over the next century and that during these changes the global forest resource is likely to be adversely affected.
• The ability of livestock producers to adapt their herds to the physiological stress of climate change appears encouraging due to a variety of techniques for dealing with climate stress, but this issue is not well constrained, in part because of the general lack of experimentation and simulations of livestock adaptation to climate change.
• Crop and livestock farmers who have sufficient access to capital and technologies should be able to adapt their farming systems to climate change. Substantial changes in their mix of crops and livestock production may be necessary, however, as considerable costs could be involved in this process because investments in learning and gaining experience with different crops or irrigation.
• Impacts of climate change on agriculture after adaptation are estimated to result in small percentage changes in overall global income. Nations with large resource endowments (i.e., developed countries) will fare better in adapting to climate change than those with poor resource endowments (i.e., developing countries and countries in transition, especially in the tropics and subtropics) which will fare worse. This, in turn, could worsen income disparities between developed and developing countries.
• Although local forest ecosystems will be highly affected, with potentially significant local economic impacts, it is believed that, at regional and global scales, the global supply of timber and non-wood goods and services will adapt through changes in the global market place. However, there will be regional shifts in market share associated with changes in forest productivity with climate change: in contrast to the findings of the SAR, recent studies suggest that the changes will favor producers in developing countries, possibly at the expense of temperate and boreal suppliers.
• Global agricultural vulnerability is assessed by the anticipated effects of climate change on food prices. Based on the accumulated evidence of modeling studies, a global temperature rise of greater than 2.5 ^°C is likely to reverse the trend of falling real food prices. This would greatly stress food security in many developing countries.

     

Towards evaluating cloud response to climate change using clustering technique identification of cloud regimes

Most of the discrepancies in the climate sensitivity of general circulation models (GCMs) are believed to be due to differences in cloud radiative feedback. Analysis of cloud response to climate change in different ‘regimes’ may offer a more detailed understanding of how the cloud response differs between GCMs. In which case, evaluation of simulated cloud regimes against observations in terms of both their cloud properties and frequency of occurrence will assist in assessing confidence in the cloud response to climate change in a particular GCM. In this study, we use a clustering technique on International Satellite Cloud Climatology Project (ISCCP) data and on ISCCP-like diagnostics from two versions of the Hadley Centre GCM to identify cloud regimes over four different geographical regions. The two versions of the model are evaluated against observational data and their cloud response to climate change compared within the cloud regime framework. It is found that cloud clusters produced by the more recent GCM, HadSM4, compare more favourably with observations than HadSM3. In response to climate change, although the net cloud response over particular regions is often different in the two models, in several instances the same basic processes may be seen to be operating. Overall, both changes in the frequency of occurrence of cloud regimes and changes in the properties (optical depth and cloud top height) of the cloud regimes contribute to the cloud response to climate change.     

Climate change and snow-cover duration in the Australian Alps

This study uses a model of snow-cover duration, an observed climate data set for the Australian alpine area, and a set of regional climate-change scenarios to assess quantitatively how changes in climate may affect snow cover in the Australian Alps. To begin, a regional interannual climate data set of high spatial resolution is prepared for input to the snow model and the resulting simulated interannual and spatial variations in snow-cover duration are assessed and compared with observations. The model provides a reasonable simulation of the sensitivities of snow-cover duration to changes in temperature and precipitation in the Australian Alps, although its performance is poorer at sites highly marginal for snow cover. (In a separate comparison, the model also performs well for sites in the European Alps.) The input climate data are then modified in line with scenarios of regional climate change based on the results of five global climate models run in enhanced greenhouse experiments. The scenarios are for the years 2030 and 2070 and allow for uncertainty associated with projecting future emissions of greenhouse gases and with estimating the sensitivity of the global climate system to enhanced greenhouse forcing. Attention focuses on the climate changes most favourable (best-case scenario) and least favourable (worst-case scenario) for snow cover amongst the range of climate changes in the scenarios. Under the best case scenario for 2030, simulated average snow-cover duration and the frequency of years of more than 60 days cover decline at all sites considered. However, at the higher sites (e.g., more than 1700 m) the effect is not very marked. For the worst case scenario, a much more dramatic decline in snow conditions is simulated. At higher sites, simulated average snow cover duration roughly halves by 2030 and approaches zero by 2070. At lower sites (around 1400 m), near zero average values are simulated by 2030 (compared to durations of around 60 days for current climate).These simulated changes, ranging between the best and worst case, are likely to be indicative of how climate change will affect natural snow-cover duration in the Australian Alps. However, note that the model does not allow directly for changes in the frequency and intensity of snow-bearing circulation systems, nor do the climate-change scenarios allow possible changes in interannual variability (particularly that due to the El Niño-Southern Oscillation) and local topographical effects not resolved by global climate models. The simulated changes in snow cover are worthy of further consideration in terms of their implications for the ski industry and tourism, water resources and hydroelectric power, and land-use management and planning.68 Barada Crescent, Aranda ACT 2614, Australia.     

Atmospheric circulation climate changes

The role of the atmospheric circulation in climate change is examined. A review is given of the information available in the past record on the atmosheric circulation and its role in climate change, firstly at the surface via sea level pressure in both the northern and southern hemispheres and secondly for the free atmosphere. As with most climate information, the climate record is compromised by non-physical inhomogeneities arising from changes in observing and analyzing techniques and changes in data coverage. Problems with and threats to the rawinsonde network are discussed. Global analyses produced by the operational centers, U.S. National Meteorological Center (NMC) and the European Centre for Medium Range Weather Forecasts (ECMWF), for weather forecasting purposes contain many discontinuous changes in the analyses arising from improvements in the system used to produce them. A discussion is given of the prospects for and motivation behind an activity known as reanalysis in which the historical data are reanalyzed using a state-of-the-art system that is held constant for the entire record. The only sources of spurious change then are the changes in the observing system, such as the introduction of space-based observations. Recommendations are made on needed actions for better understanding and monitoring climate change.The role of the atmospheric circulation and the strong links to other variables such as temperature, precipitation and wind are established and illustrated with a survey of decadal variability, the evidence for it, and the way in which the observed atmospheric circulation is involved in the Pacific and Atlantic sectors. The importance of teleconnections is stressed, especially in the winter half year, for understanding local climate change. The likelihood that changes will be manifested in the frequency and intensity of preferred modes of behavior in the atmosphere, such as the El Niño-Southern Oscillation and Pacific-North American teleconnection patterns, rather than in changes in the modes is also emphasized. The recently observed climate changes and the tendency for an unprecedented prolonged El Niño are interpreted in this framework. The key coupled atmosphere-ocean character of decadal variability is noted with the atmosphere providing the spatial scales, the ocean the memory, but also with the need for collaborative, as opposed to destructive, interactions through the atmospheric circulation.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

An overview of the mink study

Highlights of the previous papers in this series are reviewed. Methodology developed for the MINK study has improved the ability of impacts analysis to deal with questions of (1) spatial and temporal variability in climate change; (2) CO₂-enrichment effects; (3) the reactions of complex enterprises (farms and forests) to climate change and their ability to adjust and adapt; and (4) integrated effects on current and, more particularly, on future regional economies. The methodology also provides for systematic study of adjustment and adaptation opportunities and of the inter-industry linkages that determine what the overall impacts on the regional economy might be. The analysis shows that with a 1930s dust bowl climate the region-wide economic impacts would be small, after adjustments in affected sectors. In this final paper we consider whether synergistic effects among sectoral impacts and more severe climate change scenarios might alter this conclusion. The MINK analysis, as is, leads to the conclusion that a strong research capacity will be required to ensure that technologies facilitating adaptation to climate change will be available when needed. The capacity to deal with climate change also requires an open economy allowing for free trade and movement of people and for institutions that protect unpriced environmental values. More severe climate scenarios and negative synergisms can only strengthen these conclusions.     

A Climate Change Scenario for the Tropics

This paper describes the construction of a climate change scenario for a region representing the extended Tropics – 30° N to 30° S – using a methodology that combines results from a simple climate model and a Global Climate Model (GCM) transient climate change experiment. The estimated date by which this climate change scenario might be realized ranges from as early as the end of the 2030s to as late as well into the 22nd century. The central estimate is for this scenario to describe the climate of the 2060s, which would represent a global warming rate of about 0.2 °C per decade, with associated atmospheric CO₂ concentrations estimated to be about 560 ppmv, 55% higher than 1990 levels. The role of anthropogenic aerosols in offsetting part of this future global warming and altering the regional character of the changes has not been considered. The paper presents changes in mean temperature; mean rainfall; rainfall seasonality, variability, frequency, and intensity and soil moisture. These patterns of change derive from only one GCM climate change experiment; different experiments would yield different patterns for the same global warming. There is also some discussion about possible changes in tropical cyclone (TC) activity, although since TCs remain poorly modelled in GCMs, the full range of possibilities (from reduced activity, through no change, to increased activity) should be considered in any impact assessment.     

21世纪气候变化情景下环北极地区植被生长季与活动积温变化

基于部门间影响模式比较计划（ISI-MIP, Inter-Sectoral Impact Model Intercomparison Project)对CMIP5中5个气候（地球）系统模式模拟结果的降尺度数据,利用多模式集合预估了气候变化情景下21世纪环北极地区植被生长季与活动积温变化。研究发现:1）多模式集合模拟能够基本再现观测的初、终霜日及无霜期长度与>10°C积温的空间分布特征以及1979～2004年各指标变化趋势的空间分布特征,但其对气候变化年际变率的模拟能力较弱;2）至21世纪末,终霜日最多将提前60 d,初霜日将推迟20～40 d,无霜期延长幅度最高可达100 d,积温将增加1000～1200°C。其中RCP8.5情景下,各指标变幅最大,RCP2.6情景下变幅最小;3）各指标变幅呈现出较大的空间差异,亚欧大陆中西部的变幅普遍较大,随着气候变暖,>10°C积温增加幅度表现出明显的纬度地带性,南部增幅较大,北部增幅较小。     

Estimation of impact of climate change on the peak discharge probability of the river Rhine

RHINEFLOW is a GIS based water balance model that has been developed to study the changes in the water balance compartments of the river Rhine basin on a monthly time basis. The model has been designed to study the sensitivity of the Rhine discharge to a climate change. The calculated discharge has been calibrated and validated on the period 1956 to 1980. For this period the model efficiency of RHINEFLOW is between 0.74 and 0.81 both for the entire Rhine and for its tributaries. Also calculated values for variations in other compartments, e.g. snow storage and actual evapotranspiration, were in good agreement with the measured values.Since a high correlation between monthly discharge and peak discharge was found for the period 1900–1980 The RHINEFLOW model is used to assess the probability of exceedence for discharge peaks under possible future climate conditions.The probabilities of exceedence were calculated from the conditional probabilities of peak discharges for a series of 15 classes of monthly discharges. Comparison of a calculated frequency distribution of high discharge peaks with observed peaks in a test series showed that the method performs well.Scenarios for temperature changes between 0 °C and plus 4 °C and precipitation changes between plus 20% and minus 20% have been applied. Within this range flood frequencies are more sensitive for a precipitation change than for a temperature change. The present two-year return period peak flow (6500–7000 m³/s) decreases by about 6% due to a temperature rise of 4 °C; a precipitation decrease of 20% leads to 30% lower two-year peaks whilst 20% precipitation increase raises them by approximately 30%.Application of a Business As Usual (BAU) and an Accelerated Policy (AP) climate scenario resulted in a significant increase in probability of peak flows for the BAU scenario, while for the AP scenario no significant change could be found. Due to sampling errors, accurate estimations of recurrence times of discharge peaks7000 m³/s require a longer sampling time series than 90 years. For management purposes the method can be applied to estimate changes of probabilities of events with a relatively long recurrence time.     

我国云量及其与降水关系的研究进展综述

云是大气垂直运动和湿状况的综合体现,云量的变化从另一个侧面反映了气候变化。气候模式中云参数的任何变化,都可能对全球气候产生重大影响。本文主要总结了近几十年有关我国云量的时空变化及其与降水关系的研究成果,同时也指出了目前多种云资料的优缺点。此外提出应充分利用现有的资料来研究云量最多、云层最厚的西南地区云的特征及其变化。      

Adapting stochastic weather generation algorithms for climate change studies

While large-scale climate models (GCMs) are in principle the most appropriate tools for predicting climate changes, at present little confidence can be placed in the details of their projections. Use of tools such as crop simulation models for investigation of potential impacts of climatic change requires daily data pertaining to small spatial scales, not the monthly-averaged and large-scale information typically available from the GCMs. A method is presented to adapt stochastic weather generation models, describing daily weather variations in the present-day climate at particular locations, to generate synthetic daily time series consistent with assumed future climates. These assumed climates are specified in terms of the commonly available monthly means and variances of temperature and precipitation, including time-dependent (so-called transient) climate changes. Unlike the usual practice of applying assumed changes in mean values to historically observed data, simulation of meteorological time series also exhibiting changes in variability is possible. Considerable freedom in climate change scenario construction is allowed. The results are suitable for investigating agricultural and other impacts of a variety of hypothetical climate changes specified in terms of monthly-averaged statistics.     

Nutrient cycling and biomass growth at a North American hardwood site in relation to climate change: ForSVA assessments

The biomass growth and nutrient cycling model ForSVA (forest-soil-vegetation-atmosphere model) is used to analyze potential changes in nutrient cycling (Ca, Mg, K, N, S) and forest biomass production in response to four climate-change scenarios. The analysis is done for an old-growth hardwood stand within the Turkey Lakes watershed north of Lake Superior, Ontario. With ForSVA, any effects due to species interactions, competition, and resulting species shifts are not addressed explicitly. Instead, the calculations are based on functional relationships that primarily respond to soil and climate conditions in general, and to structural changes within the forest itself. The simulations cover a period of about 200 years, and suggest that a principal change in annual pattern of soil moisture is to be expected for the UKMO climate scenario, and that this scenario will likely induce a major change of vegetation covertype resulting from major changes in seasonal soil moisture conditions and a general lack of snow during winter. In contrast, the OSU, GISS and GFDL scenarios should not cause a principal change in forest type, but the soil will be somewhat drier than what is currently the case. However, increased precipitation rates and/or air temperatures during summer and spring should, in combination, increase actual evapotranspiration rates, and such increases should increase net primary production. For example, calculations with GFDL suggest that cumulative wood biomass at the Turkey Lakes site can be expected to increase by 25%. Foliage biomass and fine root production can be expected to increase by 70% from current conditions. It is assumed that within-tree allocation of photosynthate is not affected by climate.     

Evaluation of a component of the cloud response to climate change in an intercomparison of climate models

Most of the uncertainty in the climate sensitivity of contemporary general circulation models (GCMs) is believed to be connected with differences in the simulated radiative feedback from clouds. Traditional methods of evaluating clouds in GCMs compare time–mean geographical cloud fields or aspects of present-day cloud variability, with observational data. In both cases a hypothetical assumption is made that the quantity evaluated is relevant for the mean climate change response. Nine GCMs (atmosphere models coupled to mixed-layer ocean models) from the CFMIP and CMIP model comparison projects are used in this study to demonstrate a common relationship between the mean cloud response to climate change and present-day variability. Although atmosphere–mixed-layer ocean models are used here, the results are found to be equally applicable to transient coupled model simulations. When changes in cloud radiative forcing (CRF) are composited by changes in vertical velocity and saturated lower tropospheric stability, a component of the local mean climate change response can be related to present-day variability in all of the GCMs. This suggests that the relationship is not model specific and might be relevant in the real world. In this case, evaluation within the proposed compositing framework is a direct evaluation of a component of the cloud response to climate change. None of the models studied are found to be clearly superior or deficient when evaluated, but a couple appear to perform well on several relevant metrics. Whilst some broad similarities can be identified between the 60°N–60°S mean change in CRF to increased CO₂ and that predicted from present-day variability, the two cannot be quantitatively constrained based on changes in vertical velocity and stability alone. Hence other processes also contribute to the global mean cloud response to climate change.     

A Perspective on Water Resources in China: Interactions between Climate Change and Soil Degradation

Water is one of the most critical resources in China. Climate change and soil degradation will be two major, interrelated environmental challenges faced by managers of water resources in coming decades. In this study, we used a water-balance model and updated databases to assess the interacting impacts of climate change and soil degradation on Chinas future water resources. We plotted the spatial pattern of changes in actual and potential evapotranspiration, soil moisture deficits, and surface runoff across China in the 2020s using a resolution of 0.5° latitude and longitude under scenarios based on climate change, soil degradation, and a combination of the two. The results showed that climate change would affect the magnitude and spatial pattern of water resources on a national scale. Some regions in central, southwestern, and northeastern China would become more vulnerable to disastrous drought and floods as a result of soil degradation. Under the combined impacts of climate change and soil degradation, soil moisture deficits would increase most in central, western, and southwestern China; surface runoff would increase most in southeastern China. More detailed process-based models are needed to capture feedback mechanisms more effectively.     

Simulation of marine stratocumulus: effect of precipitation parameterization and sensitivity to droplet number concentration

Marine stratocumulus observations show a large variability in cloud droplet number concentration (CDNC) related to variability in aerosol concentration. Changes in CDNC modify the cloud reflectivity, but also affect cloud water content, cloud lifetime, and cloudiness, through changes in precipitation. In mesoscale models and general circulation models (GCMs), precipitation mechanisms are parameterized. Here we examine how the precipitation parameterization can affect the simulated cloud. Simulations are carried out with the one-dimensional version of the hydrostatic primitive equation model MAR (Modéle Atmosphérique Régional) developed at the Université catholique de Louvain. It includes a E- turbulence closure, a wide-band formulation of the radiative transfer, and a parameterized microphysics including prognostic equations for water vapour, cloud droplets and rain drops concentrations. In a first step, the model is used to simulate a horizontally homogeneous stratocumulus deck observed during the Atlantic Stratocumulus Transition Experiment (ASTEX) on the night of 12–13 June 1992. The observations show that the model is able to realistically reproduce the vertical structure of the cloud-topped boundary layer. In a second step, several precipitation parameterizations commonly used in mesoscale models and GCMs are tested. It is found that most parameterizations tend to overestimate the precipitation, which results in an underestimation of the vertically integrated liquid water content. Afterwards, using those parameterizations that are sensitive to CDNC, several simulations are performed to estimate the effect of CDNC variations on the simulated cloud. Based upon the simulation results, we argue that currently used parameterizations do not enable assessment of such a sensitivity.     

The respective roles of surface temperature driven feedbacks and tropospheric adjustment to CO2 in CMIP5 transient climate simulations

An overview of radiative climate feedbacks and ocean heat uptake efficiency diagnosed from idealized transient climate change experiments of 14 CMIP5 models is presented. Feedbacks explain about two times more variance in transient climate response across the models than ocean heat uptake efficiency. Cloud feedbacks can clearly be identified as the main source of inter-model spread. Models with strong longwave feedbacks in the tropics feature substantial increases in cloud ice around the tropopause suggestive of changes in cloud-top heights. The lifting of the tropical tropopause goes together with a general weakening of the tropical circulation. Distinctive inter-model differences in cloud shortwave feedbacks occur in the subtropics including the equatorward flanks of the storm-tracks. Related cloud fraction changes are not confined to low clouds but comprise middle level clouds as well. A reduction in relative humidity through the lower and mid troposphere can be identified as being the main associated large-scale feature. Experiments with prescribed sea surface temperatures are analyzed in order to investigate whether the diagnosed feedbacks from the transient climate simulations contain a tropospheric adjustment component that is not conveyed through the surface temperature response. The strengths of the climate feedbacks computed from atmosphere-only experiments with prescribed increases in sea surface temperatures, but fixed CO₂ concentrations, are close to the ones derived from the transient experiment. Only the cloud shortwave feedback exhibits discernible differences which, however, can not unequivocally be attributed to tropospheric adjustment to CO₂. Although for some models a tropospheric adjustment component is present in the global mean shortwave cloud feedback, an analysis of spatial patterns does not lend support to the view that cloud feedbacks are dominated by their tropospheric adjustment part. Nevertheless, there is positive correlation between the strength of tropospheric adjustment processes and cloud feedbacks across different climate models.     

The challenges of monitoring national climate policy: learning lessons from the EU

One of the most central and novel features of the new climate governance architecture emerging from the 2015 Paris Agreement is the transparency framework committing countries to provide, inter alia, regular progress reports on national pledges to address climate change. Many countries will rely on public policies to turn their pledges into action. This article focuses on the EU’s experience with monitoring national climate policies in order to understand the challenges that are likely to arise as the Paris Agreement is implemented around the world. To do so, the research employs – for the first time – comparative empirical data submitted by states to the EU’s monitoring system. Our findings reveal how the EU’s predominantly technical interpretation of four international reporting quality criteria – an approach borrowed from reporting on GHG fluxes – has constrained knowledge production and stymied debate on the performance of individual climate policies. Key obstacles to more in-depth reporting include not only political concerns over reporting burdens and costs, but also struggles over who determines the nature of climate policy monitoring, the perceived usefulness of reporting information, and the political control that policy knowledge inevitably generates. Given the post-Paris drive to achieve greater transparency, the EU’s experience offers a sobering reminder of the political and technical challenges associated with climate policy monitoring, challenges that are likely to bedevil the Paris Agreement for decades to come.

Policy relevance

The 2009 Copenhagen summit ushered in a more bottom-up system of international climate governance. Such systems typically depend on strong monitoring approaches to assess past performance and estimate future national contributions over time. This article shows why decision makers at multiple governance levels should pay serious attention to empirical data on the experiences and challenges that have emerged around monitoring in the EU, a self-proclaimed climate leader. The analysis highlights key political and administrative challenges that policy makers will likely encounter in implementing climate policy monitoring and ensuring transparency in the spirit of the Paris Agreement.