Bridging organizations in agricultural carbon markets and poverty alleviation: An analysis of pro-Poor carbon market projects in East Africa

International agricultural carbon market projects face significant challenges in delivering greenhouse gas mitigation objectives whilst also seeking to provide additional benefits for poverty alleviation. The carbon credit producer (the smallholder farmer) and carbon credit buyer in the carbon market transaction typically operate at different spatial and temporal scales. Buyers operate at a global scale, responding to opportunities for financial speculation and both private and public climate action plans. Farmers operate within households, farms, and immediate agricultural landscapes, pursuing livelihood and food security needs. These different scales often result in mismatches of timing, payment, and knowledge in market transactions and can be partially rectified by project developers who serve to broker the relationship between the farmers and the buyers. We examined eight East African agricultural carbon market projects to determine how project developers function as bridging organizations and minimize the mismatches between these actors. Results show that projects better bridged the timing and payment gap between buyers and producers when project developers provided non-monetary benefits or direct monetary assistance to farmers. However, knowledge gaps remained a significant barrier for farmers wishing to participate in the market. We discuss how project developers brokered relationships in ways that reflected their interests and highlight the limitations, trade-offs, and challenges that must be overcome if win-win outcomes of poverty alleviation and climate change mitigation are to be realized.     

The Gordian knot of mangrove conservation: Disentangling the role of scale,services and benefits

Mangrove forests are among the most threatened tropical ecosystems. Their role as providers of important ecosystem services such as coastal protection, carbon storage and nursery habitats for economically important species is increasingly acknowledged. But mangrove destruction continues, and we might have to face the prospect of a world deprived of the services offered by mangrove ecosystems. Mangrove transformation and destruction is often caused by mismatches in mangrove system management. These root in interests that focus on selected ecosystem services only, but also result from a problem of fit between the spatial scales at which ecosystem services are provided, and those at which their benefits are realized. We argue that a combination of the ecosystem services concept with a careful approach to the issue of scales will help to overcome these problems and improve the management of mangrove systems. Drawing on two case studies from Indonesia and Brazil, we illustrate the relevance of our findings for different ecosystem services.     

A statistical model to downscale local daily temperature extremes from synoptic-scale atmospheric circulation patterns in the Australian region

 The study seeks to describe one method of deriving information about local daily temperature extremes from larger scale atmospheric flow patterns using statistical tools. This is considered to be one step towards downscaling coarsely gridded climate data from global climate models (GCMs) to finer spatial scales. Downscaling is necessary in order to bridge the spatial mismatch between GCMs and climate impact models which need information on spatial scales that the GCMs cannot provide. The method of statistical downscaling is based on physical interaction between atmospheric processes with different spatial scales, in this case between synoptic scale mean sea level pressure (MSLP) fields and local temperature extremes at several stations in southeast Australia. In this study it was found that most of the day-to-day spatial variability of the synoptic circulation over the Australian region can be captured by six principal components. Using the scores of these PCs as multivariate indicators of the circulation a substantial part of the local daily temperature variability could be explained. The inclusion of temperature persistence noticeably improved the performance of the statistical model. The model established and tested with observations is thought to be finally applied to GCM-simulated pressure fields in order to estimate pressure-related changes in local temperature extremes under altered CO₂ conditions. Received: 26 March 1996 / Accepted: 20 September 1996     

Multiple scales and regulatory gaps in environmental change: the case of salmon aquaculture

The significance of multiple scales within processes of global environmental change has attracted increasing attention. Yet the fundamental tasks of linking multiple levels at which regulatory decisions are required to multiple scales of impacts have only recently been identified. This paper addresses the importance of attention to multiple scales in regulatory decisions, how those decisions should link together across scales of governance or decision-making, and how mismatches among scales of impact and scales of regulation can lead to regulatory gaps and breakdowns. This paper begins by presenting a definition of a cross-scale regulatory problem, building on the concept of an externality. It argues that virtually all-significant environmental regulatory problems involve multiple scales at which decisions are required, and that coordination of these decisions is one of the major issues in regulatory design. The paper provides a generalization of what is needed for effective cross-scale regulation, and then discusses the example of salmon aquaculture in British Columbia to illustrate these points. In our view, gaps and mismatches in the regulatory framework across institutional scales appear to contribute to social controversy over salmon aquaculture. These gaps include (i) the site-by-site orientation of the current regulatory process, even though the major impacts are cumulative, and regional in significance, and (ii) the degree to which limitations on the extent of salmon aquaculture are implemented by local governments, even though provincial and federal governments have the mandate and expertise to address these questions.     

Brazil's Amazon forest in mitigating global warming: unresolved controversies

Brazil's Amazon rainforest provides an important environmental service with its storage of carbon, thereby reducing global warming. A growing number of projects and proposals intend to reward carbon storage services. Reducing emissions from deforestation and forest degradation is currently a key issue for negotiations on an international agreement that is to take effect in 2013. Various issues require decisions that will have substantial impacts on both the effectiveness of mitigation and the scale of Amazonia's potential role. These decisions include the effects that money generated from payments can have, the spatial scale of mitigation (e.g. projects or countries and sub-national political units), whether to have voluntary or mandatory markets, and whether these reductions will generate carbon credits to offset emissions elsewhere. It is argued that national-level programmes, combined with a national target under the United Nations Framework Convention on Climate Change, are the best solution for Brazil in terms of both capturing international funding and stimulating the major cuts in global emissions that are needed to minimize climate risk to the Amazon rainforest. The high likelihood of passing a tipping point for maintaining the Amazon rainforest implies the need for urgency in altering current negotiating positions.     

Predictability in limited area and global models

Summary Selected small domain LAM forecasts modulated by highly corrugated underlying topography, and driven by different state-of-science outer models suggest that uncertain outer model guidance for LAMs produces large, domain averaged sensitivity. A further literature survey indicates that many LAM forecasts are relatively insensitive to details of the local initial state, and that mesoscales show slight error growth, in contradiction to classical predictability theory. A series of global predictability experiments is presented in order to reconcile the contradiction. The experiments imply that, even in baroclinically unstable atmospheres, the most common sources of local error growth are associated with small uncertainties of the larger spatial scales rather than small uncertainties of the smaller spatial scales. Variable resolution, real-data experiments of barotropic versions of the global model display substantial mesoscale error growth, due principally to the effect of larger scales. The uncertainties possessing largest spatial scale appear as boundary uncertainties in LAMs, and explain the strong boundary sensitivity and weak local initial data sensitivity observed in many LAMs. We infer that accurate depiction of the largest spatial scales is a first order priority for accurate local prediction, and that for the advective portion of the dynamics, errors of the outer model that provides lateral boundary conditions may impose the largest current practical limitation for many LAM predictions.With 10 Figures     

Demand for biodiversity protection and carbon storage as drivers of global land change scenarios

Many global land change scenarios are driven by demand for food, feed, fiber, and fuel. However, novel demands for other ecosystem services give rise to nexus issues and can lead to different land system changes. In this paper we explore the effects of including multiple different demands in land change scenarios. Our reference scenario is driven by demands for crop production, ruminant livestock production, and provisioning of built-up area. We then compare two alternative scenarios with additional demands for terrestrial carbon storage and biodiversity protection, respectively. These scenarios represent possible implementations of globally agreed policy targets. The simulated land system change scenarios are compared in terms of changes in cropland intensity and area, as well as tree and grassland area changes. We find that the carbon and biodiversity scenarios generally result in greater intensification and less expansion of cropland, with the biodiversity scenario showing a stronger intensification effect. However, the impact of setting the targets impacts different world regions in different ways. Overall, both scenarios result in a larger tree area compared to the reference scenario, while the carbon scenario also yields more grassland area. The land systems simulated while accounting for these additional demand types show strong patterns of specialization and spatial segregation in the provisioning of goods and services in different world regions. Our results indicate the relevance of including demands for multiple different goods and services in global land change assessments.     

Integrating agriculture and climate change mitigation at landscape scale: Implications from an Australian case study

Rural and regional hinterlands provide the ecosystem service needs for increasingly urbanised communities across the globe. These inter-related ecosystem services provide key opportunities in securing climate change mitigation and adaptation. Their integrated management in the face of climate change, however, can be confounded by fragmentation within the complex institutional arrangements concerned with natural resource management. This suggests the need for a more systemic approach to continuous improvement in the integrated and adaptive governance of natural resources.This paper explores the theoretical foundations for integrated natural resource management and reviews positive systemic improvements that have been emerging in the Australian context. In setting clear theoretical foundations, the paper explores both functional and structural aspects of natural resource governance systems. Functional considerations include issues of connectivity, knowledge use and capacity within the natural resource decision making environment. Structural considerations refer to the institutions and processes that undertake planning through to implementation, monitoring and evaluation.From this foundation, we review the last decade of emerging initiatives in governance regarding the integration of agriculture and forests across the entire Australian landscape. This includes the shift towards more devolved regional approaches to integrated natural resource management and recent progress towards the use of terrestrial carbon at landscape scale to assist in climate change mitigation and adaptation. These developments, however, have also been tempered by a significant raft of new landscape-scale regulations that have tended to be based on a more centralist philosophy that landowners should be providing ecosystem services for the wider public good without substantive reward.Given this background, we explore a case study of efforts taken to integrate the management of landscape-scale agro-ecological services in the Wet Tropics of tropical Queensland. This is being achieved primarily through the integration of regional natural resource management planning and the development of aggregated terrestrial carbon offset products at a whole of landscape scale via the Degree Celsius initiative. Finally, the paper teases out the barriers and opportunities being experienced, leading to discussion about the global implications for managing climate change, income generation and poverty reduction.     

Supply of carbon sequestration and biodiversity services from Australia's agricultural land under global change

Global agroecosystems can contribute to both climate change mitigation and biodiversity conservation, and market mechanisms provide a highly prospective means of achieving these outcomes. However, the ability of markets to motivate the supply of carbon sequestration and biodiversity services from agricultural land is uncertain, especially given the future changes in environmental, economic, and social drivers. We quantified the potential supply of these services from the intensive agricultural land of Australia from 2013 to 2050 under four global outlooks in response to a carbon price and biodiversity payment scheme. Each global outlook specified emissions pathways, climate, food demand, energy price, and carbon price modeled using the Global Integrated Assessment Model (GIAM). Using a simplified version of the Land Use Trade-Offs (LUTO) model, economic returns to agriculture, carbon plantings, and environmental plantings were calculated each year. The supply of carbon sequestration and biodiversity services was then quantified given potential land use change under each global outlook, and the sensitivity of the results to key parameters was assessed. We found that carbon supply curves were similar across global outlooks. Sharp increases in carbon sequestration supply occurred at carbon prices exceeding 50 $ tCO₂⁻¹ in 2015 and exceeding 65 $ tCO₂⁻¹ in 2050. Based on GIAM-modeled carbon prices, little carbon sequestration was expected at 2015 under any global outlook. However, at 2050 expected carbon supply under each outlook differed markedly, ranging from 0 to 189 MtCO₂ yr⁻¹. Biodiversity services of 3.32% of the maximum may be achieved in 2050 for a 1 $B investment under median scenario settings. We conclude that a carbon market can motivate supply of substantial carbon sequestration but only modest amounts of biodiversity services from agricultural land. A complementary biodiversity payment can synergistically increase the supply of biodiversity services but will not provide much additional carbon sequestration. The results were sensitive to global drivers, especially the carbon price, and the domestic drivers of adoption hurdle rate and agricultural productivity. The results can inform the design of an effective national policy and institutional portfolio addressing the dual objectives of climate change and biodiversity conservation that is robust to future uncertainty in both national and global drivers.     

A conceptual framework for time and space scale interactions in the climate system

 Interactions involving various time and space scales, both within the tropics and between the tropics and midlatitudes, are ubiquitous in the climate system. We propose a conceptual framework for understanding such interactions whereby longer time scales and larger space scales set the base state for processes on shorter time scales and smaller space scales, which in turn have an influence back on the longer time scales and larger space scales in a continuum of process-related interactions. Though not intended to be comprehensive, we do cite examples from the literature to provide evidence for the validity of this framework. Decadal time scale base states of the coupled climate system set the context for the manifestation of interannual time scales (El Nino/Southern Oscillation, ENSO and tropospheric biennial oscillation, TBO) which are influenced by and interact with the annual cycle and seasonal time scales. Those base states in turn influence the large-scale coupled processes involved with intraseasonal and submonthly time scales, tied to interactions within the tropics and extratropics, and tropical–midlatitude teleconnections. All of these set the base state for processes on the synoptic and mesoscale and regional/local space scales. Events at those relatively short time scales and small space scales may then affect the longer time scale and larger space scale processes in turn, reaching back out to submonthly, intraseasonal, seasonal, annual, TBO, ENSO and decadal. Global coupled models can capture some elements of the decadal, ENSO, TBO, annual and seasonal time scales with the associated global space scales. However, coupled models are less successful at simulating phenomena at subseasonal and shorter time scales with hemispheric and smaller space scales. In the context of the proposed conceptual framework, the synergistic interactions of the time and space scales suggest that a high priority must be placed on improved simulations of all of the time and space scales in the climate system. This is particularly important for the subseasonal time scales and hemispheric and smaller space scales, which are not well simulated at present, to improve the prospects of successfully forecasting phenomena beyond the synoptic scales. Received: 3 April 2000/ Accepted: 6 November 2000     

Ranking the risk of CO2 emissions from seagrass soil carbon stocks under global change threats

Seagrass meadows are natural carbon storage hotspots at risk from global change threats, and their loss can result in the remineralization of soil carbon stocks and CO₂ emissions fueling climate change. Here we used expert elicitation and empirical evidence to assess the risk of CO₂ emissions from seagrass soils caused by multiple human-induced, biological and climate change threats. Judgments from 41 experts were synthesized into a seagrass CO₂ emission risk score based on vulnerability factors (i.e., spatial scale, frequency, magnitude, resistance and recovery) to seagrass soil organic carbon stocks. Experts perceived that climate change threats (e.g., gradual ocean warming and increased storminess) have the highest risk for CO₂ emissions at global spatial scales, while direct threats (i.e., dredging and building of a marina or jetty) have the largest CO₂ emission risks at local spatial scales. A review of existing peer-reviewed literature showed a scarcity of studies assessing CO₂ emissions following seagrass disturbance, but the limited empirical evidence partly confirmed the opinion of experts. The literature review indicated that direct and long-term disturbances have the greatest negative impact on soil carbon stocks per unit area, highlighting that immediate management actions after disturbances to recover the seagrass canopy can significantly reduce soil CO₂ emissions. We conclude that further empirical evidence assessing global change threats on the seagrass carbon sink capacity is required to aid broader uptake of seagrass into blue carbon policy frameworks. The preliminary findings from this study can be used to estimate the potential risk of CO₂ emissions from seagrass habitats under threat and guide nature-based solutions for climate change mitigation.     

A study on combining global and regional climate model results for generating climate scenarios of temperature and precipitation for the Netherlands

Climate scenarios for the Netherlands are constructed by combining information from global and regional climate models employing a simplified, conceptual framework of three sources (levels) of uncertainty impacting on predictions of the local climate. In this framework, the first level of uncertainty is determined by the global radiation balance, resulting in a range of the projected changes in the global mean temperature. On the regional (1,000–5,000 km) scale, the response of the atmospheric circulation determines the second important level of uncertainty. The third level of uncertainty, acting mainly on a local scale of 10 (and less) to 1,000 km, is related to the small-scale processes, like for example those acting in atmospheric convection, clouds and atmospheric meso-scale circulations—processes that play an important role in extreme events which are highly relevant for society. Global climate models (GCMs) are the main tools to quantify the first two levels of uncertainty, while high resolution regional climate models (RCMs) are more suitable to quantify the third level. Along these lines, results of an ensemble of RCMs, driven by only two GCM boundaries and therefore spanning only a rather narrow range in future climate predictions, are rescaled to obtain a broader uncertainty range. The rescaling is done by first disentangling the climate change response in the RCM simulations into a part related to the circulation, and a residual part which is related to the global temperature rise. Second, these responses are rescaled using the range of the predictions of global temperature change and circulation change from five GCMs. These GCMs have been selected on their ability to simulate the present-day circulation, in particular over Europe. For the seasonal means, the rescaled RCM results obey the range in the GCM ensemble using a high and low emission scenario. Thus, the rescaled RCM results are consistent with the GCM results for the means, while adding information on the small scales and the extremes. The method can be interpreted as a combined statistical–dynamical downscaling approach, with the statistical relations based on regional model output.     

A Global Inventory of Burned Areas at 1 Km Resolution for the Year 2000 Derived from Spot Vegetation Data

Biomass burning constitutes a major contribution to global emissions of carbon dioxide, carbon monoxide, methane, greenhouse gases and aerosols. Furthermore, biomass burning has an impact on health, transport, the environment and land use. Vegetation fires are certainly not recent phenomena and the impacts are not always negative. However, evidence suggests that fires are becoming more frequent and there is a large increase in the number of fires being set by humans for a variety of reasons. Knowledge of the interactions and feedbacks between biomass burning, climate and carbon cycling is needed to help the prediction of climate change scenarios. To obtain this knowledge, the scientific community requires, in the first instance, information on the spatial and temporal distribution of biomass burning at the global scale. This paper presents an inventory of burned areas at monthly time periods for the year 2000 at a resolution of 1 kilometer (km) and is available to the scientific community at no cost. The burned area products have been derived from a single source of satellite-derived images, the SPOT VEGETATION S1 1 km product, using algorithms developed and calibrated at regional scales by a network of partners. In this paper, estimates of burned area, number of burn scars and average size of the burn scar are described for each month of the year 2000. The information is reported at the country level. This paper makes a significant contribution to understanding the effect of biomass burning on atmospheric chemistry and the storage and cycling of carbon by constraining one of the main parameters used in the calculation of gas emissions.     

陆地生态系统固碳速率立体监测方法:进展与挑战

全球CO₂浓度增加造成的全球变暖已成为人类亟需解决的问题,陆地生态系统在过去几十年一直扮演着重要的碳汇角色,吸收了30％左右的人类活动排放CO₂。本文调研分析了陆地生态系统固碳速率空间估算方法,包括样地调查、通量监测、模型模拟、遥感估算等,梳理了各种估算方法的研究现状与进展。样地调查、通量观测等方法可以提供点尺度的固碳速率直接测量信息,但存在观测样本有限、空间代表性不足等问题。模型模拟方法可以从机理的角度描述陆地碳、水、能量循环,模拟预测陆地生态系统固碳速率的状态和变化。然而,在模型建立过程中,抽象和简化会引入结构与假设的不确定性,以及模型驱动数据引入的不确定性等问题是碳循环模型模拟方法面临的重大挑战。卫星遥感具有全球覆盖、分辨率精细、时间序列观测等优点,结合机器学习方法,为地球大数据驱动的全球碳源汇估算提供了新的研究范式。但是,当前各种固碳速率的监测方法还没有满足高度时空异质性的陆地生态系统固碳量监测需求,未来需要整合地面观测、模型模拟和卫星遥感等多种技术手段,提供区域和全球尺度的陆地生态系统碳汇精确估算方法体系和科学数据产品。     

Carbon storage in Chinese terrestrial ecosystems: approaching a more accurate estimate

China is an important region for the global study of carbon because of its vast territory with various climate regimes, diverse ecosystems, and long-term human disturbances and land-use history. Carbon storage in ecosystems in China has been estimated using inventory and modeling methods in the past two decades. However, different methods may result in varied magnitudes and forms of carbon storage. In this study, the current status of carbon storage in terrestrial ecosystems in China, including the impacts of land use, is summarized in the national, regional, and biome scales. Significant differences in data have existed among studies. Such differences are mainly attributed to variations in estimation methods, data availability, and periods. According to available national-scale information on Chinese terrestrial ecosystems, vegetation carbon in China is 6.1 Pg C to 76.2 Pg C (mean 36.98 Pg C) and soil carbon is 43.6 Pg C to 185.7 Pg C (mean 100.75 Pg C). The forest sector has vegetation carbon of 3.26 Pg C to 9.11 Pg C (mean 5.49 Pg C), whereas the grassland sector has 0.13 Pg C to 3.06 Pg C (mean 1.41 Pg C). Soil carbon in the forest and grassland sectors exhibits more significant regional variations. Further studies need a comprehensive methodology, which combines national inventory, field measurement, eddy covariance technique, remote sensing, and model simulation in a single framework, as well as all available data at different temporal and spatial scales, to fully account for the carbon budget in China.     

Sharing the globe: The role of attachment to place

Issues posed by global environmental change can be viewed as the problem of the commons on a larger geographic scale. A framework for analysing how geographic scale affects governments' ability to manage environmental problems is suggested here. It is based on interactions between four dimensions: production-consumption relationships; distribution of the benefits and costs of various activities; level of administrative control; and spatial scale of individuals' attachment to place. Global environmental problems can be viewed as a case where benefits from polluting activities are spatially concentrated relative to costs. The difficulty in addressing such problems stems from the discrepancy in geographic scale between adverse impacts and level of administrative control. The possibility of adapting institutional structures to match the scale of the problems is examined, in light of the increasing spatial scale of production-consumption relationships in the post-industrial world and the growing demand for local control across the globe. The geographic scale of ideological attachment to place is identified as an important variable in determining the ability to respond to large-scale environmental problems.     

The global value of coastal wetlands for storm protection

Coastal wetlands provide a range of valuable ecosystem services, including protecting coastal communities from storms. We estimated for the first time the global value of these storm protection services for all coastal wetlands for both damages avoided and lives saved. We used the historical tracks of 1,014 tropical cyclones since 1902 that recorded property damage and/or human casualties in 71 countries/regions. We used Bayesian and OLS statistical techniques to relate storm damages and lives lost to: wind speed, storm forward speed, the year of the storm, the volume of ocean water proximal to landfall, and GDP, population, and coastal wetlands in the swath of the storm. Based on current storm probabilities, we estimate the median annual global value of coastal wetlands for storm protection at $447 billion/yr (2015$US) ($213 - $837 billion/yr, 90% CI) and 4,620 lives saved per year (3,320 – 6,550, 90% CI). The 40 million hectares of coastal wetlands in storm prone areas provided an average of $11,000/ha/yr in avoided storm damages. The frequency and intensity of tropical cyclones has been increasing in recent decades and is projected to further increase with climate change. Consequently, the already significant benefits from protecting and restoring coastal wetlands will become increasingly important and valuable in the future. These results justify much larger investments in conservation and restoration of coastal wetlands.     

Mean flux estimation and cospectra of airborne carbon dioxide and water vapour eddy flux measurements in the planetary surface layer

CO₂ and H₂O eddy-flux measurements derived from airborne vertical wind and concentration data are examined to determine the accuracy of the eddy-flux estimate in moderately unstable conditions within the surface layer. Integral scale estimation is used to determine the minimum length of a sample required to achieve a given accuracy. Cospectral analysis is used to examine the scales responsible for the transport of water vapour and carbon dioxide in the surface layer. Cospectra are found to broaden as the sampling altitude increases, a well known result. At low altitudes, the cospectrum is found to become negative for large scales. A significant fraction of the flux is carried by this range of scales, which suggests that scales larger than the boundary-layer height may play an important role in the transport at low altitudes.     

An Issue of Permanence: Assessing the Effectiveness of Temporary Carbon Storage

In this paper, we present a method to quantify the effectiveness of carbon mitigation options taking into account the `permanence' of the emissions reduction. While the issue of permanence is most commonly associated with a `leaky' carbon sequestration reservoir, we argue that this is an issue that applies to just about all carbon mitigation options. The appropriate formulation of this problem is to ask `what is the value of temporary storage?' Valuing temporary storage can be represented as a familiar economic problem, with explicitly stated assumptions about carbon prices and the discount rate. To illustrate the methodology, we calculate the sequestration effectiveness for injecting CO₂ at various depths in the ocean. Analysis is performed for three limiting carbon price assumptions: constant carbon prices (assumes constant marginal damages), carbon prices rise at the discount rate (assumes efficient allocation of a cumulative emissions cap without a backstop technology), and carbon prices first rise at the discount rate but become constant after a given time (assumes introduction of a backstop technology). Our results show that the value of relatively deep ocean carbon sequestration can be nearly equivalent to permanent sequestration if marginal damages (i.e., carbon prices) remain constant or if there is a backstop technology that caps the abatement cost in the not too distant future. On the other hand, if climate damages are such as to require a fixed cumulative emissions limit and there is no backstop, then a storage option with even very slow leakage has limited value relative to a permanent storage option.     

Scale-dependent regional climate predictability over North America inferred from CMIP3 and CMIP5 ensemble simulations

Through the analysis of ensembles of coupled model simulations and projections collected from CMIP3 and CMIP5, we demonstrate that a fundamental spatial scale limit might exist below which useful additional refinement of climate model predictions and projections may not be possible. That limit varies among climate variables and from region to region. We show that the uncertainty (noise) in surface temperature predictions (represented by the spread among an ensemble of global climate model simulations) generally exceeds the ensemble mean (signal) at horizontal scales below 1000 km throughout North America, implying poor predictability at those scales. More limited skill is shown for the predictability of regional precipitation. The ensemble spread in this case tends to exceed or equal the ensemble mean for scales below 2000 km. These findings highlight the challenges in predicting regionally specific future climate anomalies, especially for hydroclimatic impacts such as drought and wetness.