Land-use and sustainability under intersecting global change and domestic policy scenarios: Trajectories for Australia to 2050

Understanding potential future influence of environmental, economic, and social drivers on land-use and sustainability is critical for guiding strategic decisions that can help nations adapt to change, anticipate opportunities, and cope with surprises. Using the Land-Use Trade-Offs (LUTO) model, we undertook a comprehensive, detailed, integrated, and quantitative scenario analysis of land-use and sustainability for Australia’s agricultural land from 2013–2050, under interacting global change and domestic policies, and considering key uncertainties. We assessed land use competition between multiple land-uses and assessed the sustainability of economic returns and ecosystem services at high spatial (1.1 km grid cells) and temporal (annual) resolution. We found substantial potential for land-use transition from agriculture to carbon plantings, environmental plantings, and biofuels cropping under certain scenarios, with impacts on the sustainability of economic returns and ecosystem services including food/fibre production, emissions abatement, water resource use, biodiversity services, and energy production. However, the type, magnitude, timing, and location of land-use responses and their impacts were highly dependent on scenario parameter assumptions including global outlook and emissions abatement effort, domestic land-use policy settings, land-use change adoption behaviour, productivity growth, and capacity constraints. With strong global abatement incentives complemented by biodiversity-focussed domestic land-use policy, land-use responses can substantially increase and diversify economic returns to land and produce a much wider range of ecosystem services such as emissions abatement, biodiversity, and energy, without major impacts on agricultural production. However, better governance is needed for managing potentially significant water resource impacts. The results have wide-ranging implications for land-use and sustainability policy and governance at global and domestic scales and can inform strategic thinking and decision-making about land-use and sustainability in Australia. A comprehensive and freely available 26 GB data pack (http://doi.org/10.4225/08/5604A2E8A00CC) provides a unique resource for further research. As similarly nuanced transformational change is also possible elsewhere, our template for comprehensive, integrated, quantitative, and high resolution scenario analysis can support other nations in strategic thinking and decision-making to prepare for an uncertain future.     

Climate change scenarios for global impacts studies

We describe a set of global climate change scenarios that have been used in a series of studies investigating the global impacts of climate change on several environmental systems and resources — ecosystems, food security, water resources, malaria and coastal flooding. These scenarios derive from modelling experiments completed by the Hadley Centre over the last four years using successive versions of their coupled ocean–atmosphere global climate model. The scenarios benefit from ensemble simulations (made using HadCM2) and from an un-flux-corrected experiment (made using HadCM3), but consider only the effects of increasing greenhouse gas concentrations. The effects of associated changes in sulphate aerosol concentrations are not considered. The scenarios are presented for three future time periods — 30-year means centred on the 2020s, the 2050s and the 2080s — and are expressed with respect to the mean 1961–1990 climate. A global land observed climatology at 0.5° latitude/longitude resolution is used to describe current climate. Other scenario variables — atmospheric CO₂ concentrations, global-mean sea-level rise and non-climatic assumptions relating to population and economy — are also provided. We discuss the limitations of the created scenarios and in particular draw attention to sources of uncertainty that we have not fully sampled.     

Climate change scenarios for precipitation extremes in Portugal

Precipitation indices are commonly used as climate change indicators. Considering four Climate Variability and Predictability-recommended indices, this study assesses possible changes in their spatial patterns over Portugal under future climatic conditions. Precipitation data from the regional climate model Consortium for Small-Scale Modelling–Climate version of the Local Model (CCLM) ensemble simulations with ECHAM5/MPI-OM1 boundary conditions are used for this purpose. For recent–past, medians and probability density functions of the CCLM-based indices are validated against station-based and gridded observational dataset from ENSEMBLES-based (gridded daily precipitation data provided by the European Climate Assessment & Dataset project) indices. It is demonstrated that the model is able to realistically reproduce not only precipitation but also the corresponding extreme indices. Climate change projections for 2071–2100 (A1B and B1 SRES scenarios) reveal significant decreases in total precipitation, particularly in autumn over northwestern and southern Portugal, though changes exhibit distinct local and seasonal patterns and are typically stronger for A1B than for B1. The increase in winter precipitation over northeastern Portugal in A1B is the most important exception to the overall drying trend. Contributions of extreme precipitation events to total precipitation are also expected to increase, mainly in winter and spring over northeastern Portugal. Strong projected increases in the dry spell lengths in autumn and spring are also noteworthy, giving evidence for an extension of the dry season from summer to spring and autumn. Although no coupling analysis is undertaken, these changes are qualitatively related to modifications in the large-scale circulation over the Euro-Atlantic area, more specifically to shifts in the position of the Azores High and associated changes in the large-scale pressure gradient over the area.     

Climate change scenarios and long term projections

Predictions of future temperature increases depend critically on the projections of future greenhouse gas emissions. Yet there is a vigorous debate about how these projections should be undertaken. This paper explores a range of methodological issues surrounding projecting greenhouse emissions over the next century. It points out that understanding future emissions requires a framework that deals with the sources of economic growth and allows for endogenous structural change. It also explores the role of convergence assumptions and the “Castles and Henderson Critique” of the Special Report on Emission Scenarios (SRES) regarding use of Market Exchange Rates (MERs) rather than Purchasing Power Parity exchange rates (PPPs) to benchmark income differentials in the world economy. In the G-Cubed multi-country model, we show that emission projections based on convergence assumptions defined in MER terms, are 40% higher by 2100 than emissions generated using a PPP comparison of income differentials between economies. We support the argument presented by Castles and Henderson, that the use of MERs in the SRES represents a serious analytical error. It is not clear what this means for the SRES projections because the SRES is not transparent in its assumptions. In the G-Cubed model, the error leads to considerably higher emissions projections.     

Implications of global emission policy scenarios for domestic agriculture: a New Zealand case study

Agricultural GHG mitigation policies are important if ambitious climate change goals are to be achieved, and have the potential to significantly lower global mitigation costs [Reisinger, A., Havlik, P., Riahi, K., van Vliet, O., Obersteiner, M., & Herrero, M. (2013). Implications of alternative metrics for global mitigation costs and greenhouse gas emissions from agriculture. Climatic Change, 117, 677–690]. In the post-Paris world of ‘nationally determined contributions’ to mitigation, the prospects for agricultural mitigation policies may rest on whether they are in the national economic interest of large agricultural producers. New Zealand is a major exporter of livestock products; this article uses New Zealand as a case study to consider the policy implications of three global policy scenarios at the global, national and farm levels. Building on global modelling, a model dairy farm and a model sheep and beef farm are used to estimate the changes in profit when agricultural emissions are priced and mitigated globally or not, and priced domestically or not, in 2020. Related to these scenarios is the metric or GHG exchange rate. Most livestock emissions are non-CO₂, with methane being particularly sensitive to the choice of metric. The results provide evidence that farm profitability is more sensitive to differing international policy scenarios than national economic welfare. The impact of the choice of metric is not as great as the impact of whether other countries mitigate agricultural emissions or not. Livestock farmers do best when agricultural emissions are not priced, as livestock commodity prices rise significantly due to competition for land from forestry. However, efficient farmers may still see a rise in profitability when agricultural emissions are fully priced worldwide.

Policy relevance

Exempting agricultural emissions from mitigation significantly increases the costs of limiting warming to 2 °C, placing the burden on other sectors. However, there may be a large impact on farmers if agricultural emissions are priced domestically when other countries are not doing the same. The impacts of global and national climate policies on farmers need to be better understood in order for climate policies to be politically sustainable. Transitional assistance that is not linked to emission levels could help, as long as the incentives to mitigate are maintained. In the long run, efficient farmers may benefit from climate policy; international efforts should focus on mitigation options and effective domestic policy development, rather than on metrics.     

Climate change in California: scenarios and approaches for adaptation

Even with aggressive global action to reduce greenhouse gas emissions, the climate will continue to change for decades due to previous emissions and the inertia in biogeophysical and social systems. Therefore, as a complement to mitigation actions, society must also focus on enhancing its capacity to adapt to the unavoidable impacts of climate change that we are already experiencing and will continue to experience over the next few decades. Resource managers, regional planners, and government agencies need to consider climate risks in their planning. We provide an overview of climate change scenarios for California and suggestions on the use of climate projections in state and regional planning efforts in the future.     

Climate change scenarios for precipitation and potential evapotranspiration over central Belgium

In this article, we examine climate model estimations for the future climate over central Belgium. Our analysis is focused mainly on two variables: potential evapotranspiration (PET) and precipitation. PET is calculated using the Penman equation with parameters appropriately calibrated for Belgium, based on RCM data from the European project PRUDENCE database. Next, we proceed into estimating the model capacity to reproduce the reference climate for PET and precipitation. The same analysis for precipitation is also performed based on GCM data from the IPCC AR4 database. Then, the climate change signal is evaluated over central Belgium using RCM and GCM simulations based on several SRES scenarios. The RCM simulations show a clear shift in the precipitation pattern with an increase during winter and a decrease during summer. However, the inclusion of another set of SRES scenarios from the GCM simulations leads to a less clear climate change signal.     

Reconstruction of New Zealand Temperatures Back to AD 1720 Using Libocedrus bidwillii Tree-Rings

The longest chronology from New Zealand so faris from Libocedrus bidwillii Hook. f. (i.e.,from AD 1992 back to AD 1140, a span of 853 years). A subset of 11 chronologies was selected from anetwork of 23 sites to reconstruct past temperaturesbased on the similarity of significant responsefunctions. A comparison of climate data overdifferent seasons with these 11 chronologies wascarried out using a bootstrap transfer function. Average late-summer (February–March) temperature wasselected for reconstruction based on independentverification results. The reconstructed temperaturewas then presented for the period back to AD 1720. The chronologies reconstructed years experiencing hotsummers better than cold summers. The power spectrumof the reconstructed temperatures showed periodicitiessimilar to those of the observed temperatures. Reconstructed temperatures were significantlycorrelated with other proxy climate reconstructionsderived from tree rings in New Zealand. However,unlike the other tree ring-based reconstructions, theLibocedrus bidwillii series reconstructed boththe 1950s and 1970s warming periods. The resultsalso compared very favourably with other palaeoclimateevidence.     

A Regression-based Assessment of the Predictability of New Zealand Climate Anomalies

Summary Estimates of the predictability of New Zealand monthly and seasonal temperature and rainfall anomalies are calculated using a cross-validated linear regression procedure. Predictors are indices of the large scale circulation, sea-surface temperatures, the Southern Oscillation Index and persistence. Statistical significance is estimated through a series of Monte Carlo trials. No significant forecast relationships are found for rainfall anomalies at either the monthly or seasonal time scale. Temperature forecasts are however considered to exhibit significant skill, with variance reductions of the order of 10–20% in independent trials. Temperature anomalies are most skilfully predicted over the North Island, and skill is greatest in Spring and Summer in most areas. At the monthly time scale, predictors local to the New Zealand region account for most of the forecast skill, while at the seasonal time scale, skill depends strongly upon “remote” predictors defined over regions of the southern hemisphere distant from New Zealand. Indices of meridional flow over the Tasman Sea/New Zealand region are found to be useful predictors, especially for monthly forecasts, perhaps as a proxy for atmospherically-forced sea surface temperature anomalies. Sea surface temperature anomalies to the west of New Zealand and in the tropical Indian Ocean are also useful, especially for seasonal predictions. Forecast skill is more reliably estimated at the monthly time scale than at the seasonal time scale, as a result of the larger sample size of monthly mean data. While long-term mean levels of skill may be estimated reliably over the whole data set, statistically significant decadal-scale variations are found in the predictability of temperature anomalies. Therefore, even if long-term forecast skill levels are reliably estimated, it may be impossible to predict the short-term skill of operational seasonal climate forecasts. Implications for operational climate predictions in mid-latitudes are discussed. Received July 18, 1997 Revised April 2, 1998     

全球增暖背景下2050年前长江流域气候趋势预估

根据ECHAM5/ MPI-OM模式对长江流域21世纪前半叶气候变化的预估数据,分析了全流域、上游地区和中下游地区未来气候变化趋势。结果表明,长江流域气温将持续升高,尤其7-8月升温趋势明显,年平均温度升高最大幅度为2.60℃;全流域7月降水将增加,8月降水有减少趋势,未来夏季降水更加集中,不仅会增加洪涝灾害的发生机率,也有可能导致旱灾的发生。     

Monthly prediction of air temperature in Australia and New Zealand with machine learning algorithms

Long-term air temperature prediction is of major importance in a large number of applications, including climate-related studies, energy, agricultural, or medical. This paper examines the performance of two Machine Learning algorithms (Support Vector Regression (SVR) and Multi-layer Perceptron (MLP)) in a problem of monthly mean air temperature prediction, from the previous measured values in observational stations of Australia and New Zealand, and climate indices of importance in the region. The performance of the two considered algorithms is discussed in the paper and compared to alternative approaches. The results indicate that the SVR algorithm is able to obtain the best prediction performance among all the algorithms compared in the paper. Moreover, the results obtained have shown that the mean absolute error made by the two algorithms considered is significantly larger for the last 20 years than in the previous decades, in what can be interpreted as a change in the relationship among the prediction variables involved in the training of the algorithms.     

2011—2050年长江流域气候变化预估问题的探讨

利用长江流域1961—2008年观测气象资料,对IPCC 第四次评估报告中12个全球气候模式及所有模式集合平均进行比较验证,结果表明：MIUB_ECHO_G模式对该地区降水模拟能力较强,NCAR_CCSM3模式对温度模拟效果较好。进一步利用MIUB_ECHO_G模式和NCAR_CCSM3模式结果在SRES-A2、-A1B、-B1 3种排放情景下的降水和温度数据,分析2011—2050年3种排放情景下长江流域降水和温度变化特征。结果表明,2011—2050年长江流域降水变化趋势不明显,温度呈增加趋势,增幅在2℃内。     

Changes in Climate Extremes Over the Australian Region and New Zealand During the Twentieth Century

Analyses of high quality data show that there have been some interesting recent changes in the incidence of some climate extremes in the Australian region and New Zealand.     

Investigating Climate Change Impacts and Thresholds: An Application of the CLIMPACTS Integrated Assessment Model for New Zealand Agriculture

The determination of `critical thresholds'is an essential task for informed policydecisions on establishing greenhouse gas emissiontargets. This paper presents a framework fordetermining critical thresholds for New Zealandagriculture, focusing on three agriculturalcrops – kiwifruit, grain maize, andPaspalum dilatatum – as exemplars for the fruitproduction, arable cropping and dairy productionindustries in New Zealand. The approach is based onthe application of a country-scale, integratedassessment model, called CLIMPACTS. The CLIMPACTSsystem contains a climate change scenario generator,climate and land data, and sectoral impact models. Importantly, CLIMPACTS allows time-dependentassessments of climate change and its effects, whichfacilitates the identification and examination of thresholds, which largely relate to spatial changes, over time, in regions of economic importance for these crops. However, whether such thresholds are `critical' for New Zealand cannot currently be addressed by the CLIMPACTS model. The determination of `criticality' requires a fully integrated assessment in which the social, economic, and environmental costs and risks associated with these thresholds are comprehensively evaluated.     

不同代表性浓度路径情景下2045-2050年中国气溶胶分布变化的分析

基于来自于CMIP5中CESM模式的三种RCP情景下的气象场的降尺度模拟,应用区域空气质量模式系统RAMS-CMAQ模拟2045-2050年中国地区气溶胶浓度.三种RCP情景下气象场的降尺度模拟表明,与RCP2.6相比,在RCP4.5和RCP8.5下,华北和华南的近地表温度差减小,风速在华北和华南地区增加,在中部地区下...     

Climate change scenarios of heat waves in Central Europe and their uncertainties

The study examines climate change scenarios of Central European heat waves with a focus on related uncertainties in a large ensemble of regional climate model (RCM) simulations from the EURO-CORDEX and ENSEMBLES projects. Historical runs (1970–1999) driven by global climate models (GCMs) are evaluated against the E-OBS gridded data set in the first step. Although the RCMs are found to reproduce the frequency of heat waves quite well, those RCMs with the coarser grid (25 and 50 km) considerably overestimate the frequency of severe heat waves. This deficiency is improved in higher-resolution (12.5 km) EURO-CORDEX RCMs. In the near future (2020–2049), heat waves are projected to be nearly twice as frequent in comparison to the modelled historical period, and the increase is even larger for severe heat waves. Uncertainty originates mainly from the selection of RCMs and GCMs because the increase is similar for all concentration scenarios. For the late twenty-first century (2070–2099), a substantial increase in heat wave frequencies is projected, the magnitude of which depends mainly upon concentration scenario. Three to four heat waves per summer are projected in this period (compared to less than one in the recent climate), and severe heat waves are likely to become a regular phenomenon. This increment is primarily driven by a positive shift of temperature distribution, but changes in its scale and enhanced temporal autocorrelation of temperature also contribute to the projected increase in heat wave frequencies.     

Climate change mitigation scenarios and policies and measures: the case of Kazakhstan

This article illustrates the main difficulties encountered in the preparation of GHG emission projections and climate change mitigation policies and measures (P&M) for Kazakhstan. Difficulties in representing the system with an economic model have been overcome by representing the energy system with a technical-economic growth model (MARKAL-TIMES) based on the stock of existing plants, transformation processes, and end-use devices. GHG emission scenarios depend mainly on the pace of transition in Kazakhstan from a planned economy to a market economy. Three scenarios are portrayed: an incomplete transition, a fast and successful one, and even more advanced participation in global climate change mitigation, including participation in some emission trading schemes. If the transition to a market economy is completed by 2020, P&M already adopted may reduce emissions of CO₂ from combustion by about 85 MtCO₂ by 2030 – 17% of the emissions in the baseline (WOM) scenario. One-third of these reductions are likely to be obtained from the demand sectors, and two-thirds from the supply sectors. If every tonne of CO₂ not emitted is valued up to US$10 in 2020 and $20 in 2030, additional P&M may further reduce emissions by 110 MtCO₂ by 2030.     

Economic and ecosystem costs and benefits of alternative land use and management scenarios in the Lake Rotorua,New Zealand,catchment

A significant challenge in resource management is addressed: the perceived trade-off between economic growth and ecosystem restoration and conservation. Traditional approaches to management regard restoration as a potential cost to economic productivity. In this study we show that by considering a broader range of economic values, including ecosystem services values, an argument can be made that restoration of lake ecosystems also leads to favourable economic outcomes when commonly disregarded values are considered. Our case study analyses the ecological outcomes of different catchment mitigation and land use scenarios in terms of water quality results in a lake, assessing changes in land use values based on opportunity costs, and ecosystem services values. We show that when considering the value of ecosystem services, intensive agricultural land use is not necessarily the most economically valuable form of land use within a lake catchment. Indeed, a shift towards alternative land uses within a catchment can lead to both ongoing economic benefits and improvements in water quality. In this context, land-use change offers an option for water quality improvement that minimises lake and land mitigation costs, while adding value to catchment land use. An argument is made supporting land use change towards indigenous forest types, which can sustain alternative sources of income such as a range of recreational values, while supporting important ecosystem functions for the region.