Plant Migrations Impact on Potential Vegetation and Carbon Redistribution in Northern North America from Climate Change

Forests have a prominent role in carbon storage and sequestration. Anthropogenic forcing has the potential to accelerate climate change and alter the distribution of forests. How forests redistribute spatially and temporally in response to climate change can alter their carbon sequestration potential. The driving question for this research was: How does plant migration from climate change impact vegetation distribution and carbon sequestration potential over continental scales? Large-scale simulation of the equilibrium response of vegetation and carbon from future climate change has shown relatively modest net gains in sequestration potential, but studies of the transient response has been limited to the sub-continent or landscape scale. The transient response depends on fine scale processes such as competition, disturbance, landscape characteristics, dispersal, and other factors, which makes it computational prohibitive at large domain sizes. To address this, this research used an advanced mechanistic model (Ecosystem Demography Model, ED) that is individually based, but pseudo-spatial, that reduces computational intensity while maintaining the fine scale processes that drive the transient response. First, the model was validated against remote sensing data for current plant functional type distribution in northern North America with a current climatology, and then a future climatology was used to predict the potential equilibrium redistribution of vegetation and carbon from future climate change. Next, to enable transient calculations, a method was developed to simulate the spatially explicit process of dispersal in pseudo-spatial modeling frameworks. Finally, the new dispersal sub-model was implemented in the mechanistic ecosystem model, and a model experimental design was designed and completed to estimate the transient response of vegetation and carbon to climate change. The potential equilibrium forest response to future climate change was found to be large, with large gross changes in distribution of plant functional types and comparatively smaller changes in net carbon sequestration potential for the region. However, the transient response was found to be on the order of centuries, and to depend strongly on disturbance rates and dispersal distances. Future work should explore the impact of species-specific disturbance and dispersal rates, landscape fragmentation, and other processes that influence migration rates and have been simulated at the sub-continent scale, but now at continental scales, and explore a range of alternative future climate scenarios as they continue to be developed.

Status of current research on the implication of climate change on built environment

The cycling interaction between climate change and building performance is of dynamic nature and both are essentially the cause and the effect of each other. On one hand, buildings contribute significantly to the global warming process. On the other hand, climate change is also expected to impact on many aspects of building performance. In this paper, the status of current research on the implication of climate change on built environment is reviewed. It is found that although the present research has covered broad areas of research, they are generally only limited to the qualitative analyses. It is also highlighted that although it is widely realized that reducing greenhouse gas emissions from the building sector is very important, the adoption of complementary adaptation strategy to prepare the building for a range of climate change scenarios is also necessary. Due to the lack of holistic approach to generate future hourly weather data, various approaches have been used to generate different key weather variables. This ad hoc situation has seriously hindered the application of building simulation technique to the climate change impact study, in particular, to provide quantitative information for policy and design development.

Reservoir performance under uncertainty in hydrologic impacts of climate change

Relatively few studies have addressed water management and adaptation measures in the face of changing water balances due to climate change. The current work studies climate change impact on a multipurpose reservoir performance and derives adaptive policies for possible futurescenarios. The method developed in this work is illustrated with a case study of Hirakud reservoir on the Mahanadi river in Orissa, India,which is a multipurpose reservoir serving flood control, irrigation and power generation. Climate change effects on annual hydropower generation and four performance indices (reliability with respect to three reservoir functions, viz. hydropower, irrigation and flood control, resiliency, vulnerability and deficit ratio with respect to hydropower) are studied. Outputs from three general circulation models (GCMs) for three scenarios each are downscaled to monsoon streamflow in the Mahanadi river for two future time slices, 2045-65 and 2075-95. Increased irrigation demands, rule curves dictated by increased need for flood storage and downscaled projections of streamflow from the ensemble of GCMs and scenarios are used for projecting future hydrologic scenarios. It is seen that hydropower generation and reliability with respect to hydropower and irrigation are likely to show a decrease in future in most scenarios, whereas the deficit ratio and vulnerability are likely to increase as a result of climate change if the standard operating policy (SOP) using current rule curves for flood protection is employed. An optimal monthly operating policy is then derived using stochastic dynamic programming (SDP) as an adaptive policy for mitigating impacts of climate change on reservoir operation. The objective of this policy is to maximize reliabilities with respect to multiple reservoir functions of hydropower, irrigation and flood control. In variations to this adaptive policy, increasingly more weightage is given to the purpose of maximizing reliability with respect to hydropower for two extreme scenarios. It is seen that by marginally sacrificing reliability with respect to irrigation and flood control, hydropower reliability and generation can be increased for future scenarios. This suggests that reservoir rules for flood control may have to be revised in basins where climate change projects an increasing probability of droughts. However, it is also seen that power generation is unable to be restored to current levels, due in part to the large projected increases in irrigation demand. This suggests that future water balance deficits may limit the success of adaptive policy options. (C) 2010 Elsevier Ltd. All rights reserved.

Hydrologic drought prediction under climate change: Uncertainty modeling with Dempster-Shafer and Bayesian approaches

Representation and quantification of uncertainty in climate change impact studies are a difficult task. Several sources of uncertainty arise in studies of hydrologic impacts of climate change, such as those due to choice of general circulation models (GCMs), scenarios and downscaling methods. Recently, much work has focused on uncertainty quantification and modeling in regional climate change impacts. In this paper, an uncertainty modeling framework is evaluated, which uses a generalized uncertainty measure to combine GCM, scenario and downscaling uncertainties. The Dempster-Shafer (D-S) evidence theory is used for representing and combining uncertainty from various sources. A significant advantage of the D-S framework over the traditional probabilistic approach is that it allows for the allocation of a probability mass to sets or intervals, and can hence handle both aleatory or stochastic uncertainty, and epistemic or subjective uncertainty. This paper shows how the D-S theory can be used to represent beliefs in some hypotheses such as hydrologic drought or wet conditions, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The D-S approach has been used in this work for information synthesis using various evidence combination rules having different conflict modeling approaches. A case study is presented for hydrologic drought prediction using downscaled streamflow in the Mahanadi River at Hirakud in Orissa, India. Projections of n most likely monsoon streamflow sequences are obtained from a conditional random field (CRF) downscaling model, using an ensemble of three GCMs for three scenarios, which are converted to monsoon standardized streamflow index (SSFI-4) series. This range is used to specify the basic probability assignment (bpa) for a Dempster-Shafer structure, which represents uncertainty associated with each of the SSFI-4 classifications. These uncertainties are then combined across GCMs and scenarios using various evidence combination rules given by the D-S theory. A Bayesian approach is also presented for this case study, which models the uncertainty in projected frequencies of SSFI-4 classifications by deriving a posterior distribution for the frequency of each classification, using an ensemble of GCMs and scenarios. Results from the D-S and Bayesian approaches are compared, and relative merits of each approach are discussed. Both approaches show an increasing probability of extreme, severe and moderate droughts and decreasing probability of normal and wet conditions in Orissa as a result of climate change. (C) 2010 Elsevier Ltd. All rights reserved.

Modeling the vulnerability of an urban groundwater system due to the combined impacts of climate change and management scenarios

Climate change impact on a groundwater-dependent small urban town has been investigated in the semiarid hard rock aquifer in southern India. A distributed groundwater model was used to simulate the groundwater levels in the study region for the projected future rainfall (2012-32) obtained from a general circulation model (GCM) to estimate the impacts of climate change and management practices on groundwater system. Management practices were based on the human-induced changes on the urban infrastructure such as reduced recharge from the lakes, reduced recharge from water and wastewater utility due to an operational and functioning underground drainage system, and additional water extracted by the water utility for domestic purposes. An assessment of impacts on the groundwater levels was carried out by calibrating a groundwater model using comprehensive data gathered during the period 2008-11 and then simulating the future groundwater level changes using rainfall from six GCMs Institute of Numerical Mathematics Coupled Model, version 3.0 (INM-CM. 3.0); L'Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL-CM4); Model for Interdisciplinary Research on Climate, version 3.2 (MIROC3.2); ECHAM and the global Hamburg Ocean Primitive Equation (ECHO-G); Hadley Centre Coupled Model, version 3 (HadCM3); and Hadley Centre Global Environment Model, version 1 (HadGEM1)] that were found to show good correlation to the historical rainfall in the study area. The model results for the present condition indicate that the annual average discharge (sum of pumping and natural groundwater outflow) was marginally or moderately higher at various locations than the recharge and further the recharge is aided from the recharge from the lakes. Model simulations showed that groundwater levels were vulnerable to the GCM rainfall and a scenario of moderate reduction in recharge from lakes. Hence, it is important to sustain the induced recharge from lakes by ensuring that sufficient runoff water flows to these lakes.

Climate change scenarios of surface solar radiation in data sparse regions: a case study in Malaprabha River Basin, India

A variety of methods are available to estimate future solar radiation (SR) scenarios at spatial scales that are appropriate for local climate change impact assessment. However, there are no clear guidelines available in the literature to decide which methodologies are most suitable for different applications. Three methodologies to guide the estimation of SR are discussed in this study, namely: Case 1: SR is measured, Case 2: SR is measured but sparse and Case 3: SR is not measured. In Case 1, future SR scenarios are derived using several downscaling methodologies that transfer the simulated large-scale information of global climate models to a local scale ( measurements). In Case 2, the SR was first estimated at the local scale for a longer time period using sparse measured records, and then future scenarios were derived using several downscaling methodologies. In Case 3: the SR was first estimated at a regional scale for a longer time period using complete or sparse measured records of SR from which SR at the local scale was estimated. Finally, the future scenarios were derived using several downscaling methodologies. The lack of observed SR data, especially in developing countries, has hindered various climate change impact studies. Hence, this was further elaborated by applying the Case 3 methodology to a semi-arid Malaprabha reservoir catchment in southern India. A support vector machine was used in downscaling SR. Future monthly scenarios of SR were estimated from simulations of third-generation Canadian General Circulation Model (CGCM3) for various SRES emission scenarios (A1B, A2, B1, and COMMIT). Results indicated a projected decrease of 0.4 to 12.2 W m(-2) yr(-1) in SR during the period 2001-2100 across the 4 scenarios. SR was calculated using the modified Hargreaves method. The decreasing trends for the future were in agreement with the simulations of SR from the CGCM3 model directly obtained for the 4 scenarios.

Climate change adaptation through coastal and use management: The context of environmental justice

Despite an increasing literary focus on climate change adaptation, the facilitation of this adaptation is occurring on a limited basis (Adger et al. 2007) .This limited basis is not necessarily due to inability; rather, a lack of comprehensive cost estimates of all options specifically hinders adaptation in vulnerable communities (Adger et al. 2007). Specifically the estimated cost of the climate change impact of sea-level rise is continually increasing due to both increasing rates and the resulting multiplicative impact of coastal erosion (Karl et al., 2009, Zhang et al., 2004) Based on the 2007 Intergovernmental Panel on Climate Change report, minority groups and small island nations have been identified within these vulnerable communities. Therefore the development of adaptation policies requires the engagement of these communities. State examples of sea-level rise adaptation through land use planning mechanisms such as land acquisition programs (New Jersey) and the establishment of rolling easements (Texas) are evidence that although obscured, adaptation opportunities are being acted upon (Easterling et al., 2004, Adger et al.2007). (PDF contains 4 pages)

Modeling the Links between Biodiversity, Ecosystem Services and Human Wellbeing in the Context of Climate Change: Results from an Econometric Analysis on the European Forest Ecosystems

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The role of adaptive thermal comfort in the prediction of the thermal performance of a modern mixed-mode office building in the UK under climate change

Climate change is becoming a serious issue for the construction industry, since the time scales at which climate change takes place can be expected to show a true impact on the thermal performance of buildings and HVAC systems. In predicting this future building performance by means of building simulation, the underlying assumptions regarding thermal comfort conditions and the related heating, ventilating and air conditioning (HVAC) control set points become important. This article studies the thermal performance of a reference office building with mixedmode ventilation in the UK, using static and adaptive thermal approaches, for a series of time horizons (2020, 2050 and 2080). Results demonstrate the importance of the implementation of adaptive thermal comfort models, and underpin the case for its use in climate change impact studies. Adaptive thermal comfort can also be used by building designers to make buildings more resilient towards change. © 2010 International Building Performance Simulation Association (IBPSA).

Impacts of climate change on non-native species

Anthropogenic changes to climate and extreme weather events have already led to the introduction of non-native species (NNS) to the North Atlantic. Regional climate models predict that there will be a continuation of the current trend of warming throughout the 21st century providing enhanced opportunities for NNS at each stage of the invasion process. Increasing evidence is now available to show that climate change has led to the northwards range expansion of a number of NNS in the UK and Ireland, such as the Asian club tunicate Styela clava and the Pacific oyster Crassostrea gigas. Providing definitive evidence though of the direct linkage between climate change and the spread of the majority of NNS is extremely challenging, due to other confounding factors, such as anthropogenic activity. Localised patterns of water movement and food supply may also be complicating the overall pattern of northwards range expansion, by preventing the expansion of some NNS, such as the slipper limpet Crepidula fornicata and the Chilean oyster Ostrea chilensis, from a particular region. A greater understanding of the other aspects of climate change and increased atmospheric CO2, such as increased rainfall, heat waves, frequency of storm events, and ocean acidification may aid in increasing the confidence that scientists have in predicting the long term influence of climate change on the introduction, spread and establishment of NNS.

Integrated modelling of climate change impacts on water resources and quality in a lowland catchment: River Kennet, UK

An integrated approach to climate change impact assessment is explored by linking established models of regional climate (SDSM), water resources (CATCHMOD) and water quality (INCA) within a single framework. A case study of the River Kennet illustrates how the system can be used to investigate aspects of climate change uncertainty, deployable water resources, and water quality dynamics in upper and lower reaches of the drainage network. The results confirm the large uncertainty in climate change scenarios and freshwater impacts due to the choice of general circulation model (GCM). This uncertainty is shown to be greatest during summer months as evidenced by large variations between GCM-derived projections of future tow river flows, deployable yield from groundwater, severity of nutrient flushing episodes, and Long-term trends in surface water quality. Other impacts arising from agricultural land-use reform or delivery of EU Water Framework Directive objectives under climate change could be evaluated using the same framework. (c) 2006 Elsevier B.V. All rights reserved.

Adapting to climate change impacts on water resources in England - an assessment of draft Water Resources Management Plans

Climate change is expected to produce reductions in water availability in England, potentially necessitating adaptive action by the water industry to maintain supplies. As part of Ofwat's fifth Periodic Review (PR09), water companies recently released their draft Water Resources Management Plans, setting out how each company intends to maintain the balance between the supply and demand for water over the next 25 years, following Environment Agency guidelines. This paper reviews these plans to determine company estimates of the impact of climate change on water supply relative to other resource pressures. The approaches adopted for incorporating the impact in the plans and the proposed management solutions are also identified. Climate change impacts for individual resource zones range from no reductions in deployable output to greater than 50% over the planning period. The estimated national aggregated loss of deployable output under a “core” climate scenario is ~520 Ml/d (3% of deployable output) by 2034/35, the equivalent of the supply of one entire water company (South West Water). Climate change is the largest single driver of change in water supplies over the planning period. Over half of the climate change impact is concentrated in southern England. In extreme cases, climate change uncertainty is of the same magnitude as the change under the core scenario (up to a loss of ~475 Ml/d). 44 of the 68 resource zones with available data are estimated to have a climate change impact. In 35 of these climate change has the greatest impact although in 10 zones sustainability reductions have a greater impact. Of the overall change in downward pressure on the supply-demand balance over the planning period, ~56% is accounted for by increased demand (620 Ml/d) and supply side climate change accounts for ~37% (407 Ml/d). Climate change impacts have a cumulative impact in concert with other changing supply side reducing components increasing the national pressure on the supply-demand balance. Whilst the magnitude of climate change appears to justify its explicit consideration, it is rare that adaptation options are planned solely in response to climate change but as a suite of options to provide a resilient supply to a range of pressures (including significant demand side pressures). Supply-side measures still tend to be considered by water companies to be more reliable than demand-side measures.

Uncertainty in simulating wheat yields under climate change

Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1, 3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

Climate change projections and selected impacts for Vietnam

In September 2013, the 5th Assessment Report (5AR) of the International Panel on Climate Change (IPCC) has been released. Taking the 5AR cli-mate change scenarios into account, the World Bank published an earli-er report on climate change and its impacts on selected hot spot re-gions, including Southeast Asia. Currently, dynamical and statistical-dynamical downscaling efforts are underway to obtain higher resolution and more robust regional climate change projections for tropical South-east Asia, including Vietnam. Such initiatives are formalized under the World Meteorological Organization (WMO) Coordinated Regional Dynamic Downscaling Experiment (CORDEX) East Asia and Southeast Asia and also take place in climate change impact projects such as the joint Vietnam-ese-German project “Environmental and Water Protection Technologies of Coastal Zones in Vietnam (EWATEC-COAST)”. In this contribution, the lat-est assessments for changes in temperature, precipitation, sea level, and tropical cyclones (TCs) under the 5AR Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5 are reviewed. Special emphasis is put on changes in extreme events like heat waves and/or heavy precipita-tion. A regional focus is Vietnam south of 16°N. A continued increase in mean near surface temperature is projected, reaching up to 5°C at the end of this century in northern Vietnam un-der the high greenhouse-gas forcing scenario RCP8.5. Overall, project-ed changes in annual precipitation are small, but there is a tendency of more rainfall in the boreal winter dry season. Unprecedented heat waves and an increase in extreme precipitation events are projected by both global and regional climate models. Globally, TCs are projected to decrease in number, but an increase in intensity of peak winds and rain-fall in the inner core region is estimated. Though an assessment of changes in land-falling frequency in Vietnam is uncertain due to difficul-ties in assessing changes in TC tracks, some work indicates a reduction in the number of land-falling TCs in Vietnam. Sea level may rise by 75-100 cm until the end of the century with the Vietnamese coastline experienc-ing 10-15% higher rise than on global average. Given the large rice and aquaculture production in the Mekong and Red River Deltas, that are both prone to TC-related storm surges and flooding, this poses a challenge to foodsecurity and protection of coastal population and assets.