climate change methods: Topics by Science.gov

Sample records for climate change methods

Accounting for multiple climate components when estimating climate change exposure and velocity

USGS Publications Warehouse

Nadeau, Christopher P.; Fuller, Angela K.

2015-01-01

The effect of anthropogenic climate change on organisms will likely be related to climate change exposure and velocity at local and regional scales. However, common methods to estimate climate change exposure and velocity ignore important components of climate that are known to affect the ecology and evolution of organisms.We develop a novel index of climate change (climate overlap) that simultaneously estimates changes in the means, variation and correlation between multiple weather variables. Specifically, we estimate the overlap between multivariate normal probability distributions representing historical and current or projected future climates. We provide methods for estimating the statistical significance of climate overlap values and methods to estimate velocity using climate overlap.We show that climates have changed significantly across 80% of the continental United States in the last 32 years and that much of this change is due to changes in the variation and correlation between weather variables (two statistics that are rarely incorporated into climate change studies). We also show that projected future temperatures are predicted to be locally novel (<1·5% overlap) across most of the global land surface and that exposure is likely to be highest in areas with low historical climate variation. Last, we show that accounting for changes in the variation and correlation between multiple weather variables can dramatically affect velocity estimates; mean velocity estimates in the continental United States were between 3·1 and 19·0 km yr−1when estimated using climate overlap compared to 1·4 km yr−1 when estimated using traditional methods.Our results suggest that accounting for changes in the means, variation and correlation between multiple weather variables can dramatically affect estimates of climate change exposure and velocity. These climate components are known to affect the ecology and evolution of organisms, but are ignored by most measures of climate change. We conclude with a set of future directions and recommend future work to determine which measures of climate change exposure and velocity are most related to biological responses to climate change.
Detection and Attribution of Anthropogenic Climate Change Impacts

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia; Neofotis, Peter

2013-01-01

Human-influenced climate change is an observed phenomenon affecting physical and biological systems across the globe. The majority of observed impacts are related to temperature changes and are located in the northern high- and midlatitudes. However, new evidence is emerging that demonstrates that impacts are related to precipitation changes as well as temperature, and that climate change is impacting systems and sectors beyond the Northern Hemisphere. In this paper, we highlight some of this new evidence-focusing on regions and sectors that the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) noted as under-represented-in the context of observed climate change impacts, direct and indirect drivers of change (including carbon dioxide itself), and methods of detection. We also present methods and studies attributing observed impacts to anthropogenic forcing. We argue that the expansion of methods of detection (in terms of a broader array of climate variables and data sources, inclusion of the major modes of climate variability, and incorporation of other drivers of change) is key to discerning the climate sensitivities of sectors and systems in regions where the impacts of climate change currently remain elusive. Attributing such changes to human forcing of the climate system, where possible, is important for development of effective mitigation and adaptation. Current challenges in documenting adaptation and the role of indigenous knowledge in detection and attribution are described.
Incorporating climate change projections into riparian restoration planning and design

USGS Publications Warehouse

Perry, Laura G.; Reynolds, Lindsay V.; Beechie, Timothy J.; Collins, Mathias J.; Shafroth, Patrick B.

2015-01-01

Climate change and associated changes in streamflow may alter riparian habitats substantially in coming decades. Riparian restoration provides opportunities to respond proactively to projected climate change effects, increase riparian ecosystem resilience to climate change, and simultaneously address effects of both climate change and other human disturbances. However, climate change may alter which restoration methods are most effective and which restoration goals can be achieved. Incorporating climate change into riparian restoration planning and design is critical to long-term restoration of desired community composition and ecosystem services. In this review, we discuss and provide examples of how climate change might be incorporated into restoration planning at the key stages of assessing the project context, establishing restoration goals and design criteria, evaluating design alternatives, and monitoring restoration outcomes. Restoration planners have access to numerous tools to predict future climate, streamflow, and riparian ecology at restoration sites. Planners can use those predictions to assess which species or ecosystem services will be most vulnerable under future conditions, and which sites will be most suitable for restoration. To accommodate future climate and streamflow change, planners may need to adjust methods for planting, invasive species control, channel and floodplain reconstruction, and water management. Given the considerable uncertainty in future climate and streamflow projections, riparian ecological responses, and effects on restoration outcomes, planners will need to consider multiple potential future scenarios, implement a variety of restoration methods, design projects with flexibility to adjust to future conditions, and plan to respond adaptively to unexpected change.
Selection of climate change scenario data for impact modelling.

PubMed

Sloth Madsen, M; Maule, C Fox; MacKellar, N; Olesen, J E; Christensen, J Hesselbjerg

2012-01-01

Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented in this paper, applied to relative humidity, but it could be adopted to other variables if needed.
Transferability of optimally-selected climate models in the quantification of climate change impacts on hydrology

NASA Astrophysics Data System (ADS)

Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe

2016-11-01

Given the ever increasing number of climate change simulations being carried out, it has become impractical to use all of them to cover the uncertainty of climate change impacts. Various methods have been proposed to optimally select subsets of a large ensemble of climate simulations for impact studies. However, the behaviour of optimally-selected subsets of climate simulations for climate change impacts is unknown, since the transfer process from climate projections to the impact study world is usually highly non-linear. Consequently, this study investigates the transferability of optimally-selected subsets of climate simulations in the case of hydrological impacts. Two different methods were used for the optimal selection of subsets of climate scenarios, and both were found to be capable of adequately representing the spread of selected climate model variables contained in the original large ensemble. However, in both cases, the optimal subsets had limited transferability to hydrological impacts. To capture a similar variability in the impact model world, many more simulations have to be used than those that are needed to simply cover variability from the climate model variables' perspective. Overall, both optimal subset selection methods were better than random selection when small subsets were selected from a large ensemble for impact studies. However, as the number of selected simulations increased, random selection often performed better than the two optimal methods. To ensure adequate uncertainty coverage, the results of this study imply that selecting as many climate change simulations as possible is the best avenue. Where this was not possible, the two optimal methods were found to perform adequately.
"Intelligent Ensemble" Projections of Precipitation and Surface Radiation in Support of Agricultural Climate Change Adaptation

NASA Technical Reports Server (NTRS)

Taylor, Patrick C.; Baker, Noel C.

2015-01-01

Earth's climate is changing and will continue to change into the foreseeable future. Expected changes in the climatological distribution of precipitation, surface temperature, and surface solar radiation will significantly impact agriculture. Adaptation strategies are, therefore, required to reduce the agricultural impacts of climate change. Climate change projections of precipitation, surface temperature, and surface solar radiation distributions are necessary input for adaption planning studies. These projections are conventionally constructed from an ensemble of climate model simulations (e.g., the Coupled Model Intercomparison Project 5 (CMIP5)) as an equal weighted average, one model one vote. Each climate model, however, represents the array of climate-relevant physical processes with varying degrees of fidelity influencing the projection of individual climate variables differently. Presented here is a new approach, termed the "Intelligent Ensemble, that constructs climate variable projections by weighting each model according to its ability to represent key physical processes, e.g., precipitation probability distribution. This approach provides added value over the equal weighted average method. Physical process metrics applied in the "Intelligent Ensemble" method are created using a combination of NASA and NOAA satellite and surface-based cloud, radiation, temperature, and precipitation data sets. The "Intelligent Ensemble" method is applied to the RCP4.5 and RCP8.5 anthropogenic climate forcing simulations within the CMIP5 archive to develop a set of climate change scenarios for precipitation, temperature, and surface solar radiation in each USDA Farm Resource Region for use in climate change adaptation studies.
Assessment of composite index methods for agricultural vulnerability to climate change.

PubMed

Wiréhn, Lotten; Danielsson, Åsa; Neset, Tina-Simone S

2015-06-01

A common way of quantifying and communicating climate vulnerability is to calculate composite indices from indicators, visualizing these as maps. Inherent methodological uncertainties in vulnerability assessments, however, require greater attention. This study examines Swedish agricultural vulnerability to climate change, the aim being to review various indicator approaches for assessing agricultural vulnerability to climate change and to evaluate differences in climate vulnerability depending on the weighting and summarizing methods. The reviewed methods are evaluated by being tested at the municipal level. Three weighting and summarizing methods, representative of climate vulnerability indices in general, are analysed. The results indicate that 34 of 36 method combinations differ significantly from each other. We argue that representing agricultural vulnerability in a single composite index might be insufficient to guide climate adaptation. We emphasize the need for further research into how to measure and visualize agricultural vulnerability and into how to communicate uncertainties in both data and methods. Copyright © 2015 Elsevier Ltd. All rights reserved.
Assessing the Assessment Methods: Climate Change and Hydrologic Impacts

NASA Astrophysics Data System (ADS)

Brekke, L. D.; Clark, M. P.; Gutmann, E. D.; Mizukami, N.; Mendoza, P. A.; Rasmussen, R.; Ikeda, K.; Pruitt, T.; Arnold, J. R.; Rajagopalan, B.

2014-12-01

The Bureau of Reclamation, the U.S. Army Corps of Engineers, and other water management agencies have an interest in developing reliable, science-based methods for incorporating climate change information into longer-term water resources planning. Such assessments must quantify projections of future climate and hydrology, typically relying on some form of spatial downscaling and bias correction to produce watershed-scale weather information that subsequently drives hydrology and other water resource management analyses (e.g., water demands, water quality, and environmental habitat). Water agencies continue to face challenging method decisions in these endeavors: (1) which downscaling method should be applied and at what resolution; (2) what observational dataset should be used to drive downscaling and hydrologic analysis; (3) what hydrologic model(s) should be used and how should these models be configured and calibrated? There is a critical need to understand the ramification of these method decisions, as they affect the signal and uncertainties produced by climate change assessments and, thus, adaptation planning. This presentation summarizes results from a three-year effort to identify strengths and weaknesses of widely applied methods for downscaling climate projections and assessing hydrologic conditions. Methods were evaluated from two perspectives: historical fidelity, and tendency to modulate a global climate model's climate change signal. On downscaling, four methods were applied at multiple resolutions: statistically using Bias Correction Spatial Disaggregation, Bias Correction Constructed Analogs, and Asynchronous Regression; dynamically using the Weather Research and Forecasting model. Downscaling results were then used to drive hydrologic analyses over the contiguous U.S. using multiple models (VIC, CLM, PRMS), with added focus placed on case study basins within the Colorado Headwaters. The presentation will identify which types of climate changes are expressed robustly across methods versus those that are sensitive to method choice; which method choices seem relatively more important; and where strategic investments in research and development can substantially improve guidance on climate change provided to water managers.
Rapid climate change did not cause population collapse at the end of the European Bronze Age

PubMed Central

Armit, Ian; Swindles, Graeme T.; Becker, Katharina; Plunkett, Gill; Blaauw, Maarten

2014-01-01

The impact of rapid climate change on contemporary human populations is of global concern. To contextualize our understanding of human responses to rapid climate change it is necessary to examine the archeological record during past climate transitions. One episode of abrupt climate change has been correlated with societal collapse at the end of the northwestern European Bronze Age. We apply new methods to interrogate archeological and paleoclimate data for this transition in Ireland at a higher level of precision than has previously been possible. We analyze archeological 14C dates to demonstrate dramatic population collapse and present high-precision proxy climate data, analyzed through Bayesian methods, to provide evidence for a rapid climatic transition at ca. 750 calibrated years B.C. Our results demonstrate that this climatic downturn did not initiate population collapse and highlight the nondeterministic nature of human responses to past climate change. PMID:25404290
Rapid climate change did not cause population collapse at the end of the European Bronze Age.

PubMed

Armit, Ian; Swindles, Graeme T; Becker, Katharina; Plunkett, Gill; Blaauw, Maarten

2014-12-02

The impact of rapid climate change on contemporary human populations is of global concern. To contextualize our understanding of human responses to rapid climate change it is necessary to examine the archeological record during past climate transitions. One episode of abrupt climate change has been correlated with societal collapse at the end of the northwestern European Bronze Age. We apply new methods to interrogate archeological and paleoclimate data for this transition in Ireland at a higher level of precision than has previously been possible. We analyze archeological (14)C dates to demonstrate dramatic population collapse and present high-precision proxy climate data, analyzed through Bayesian methods, to provide evidence for a rapid climatic transition at ca. 750 calibrated years B.C. Our results demonstrate that this climatic downturn did not initiate population collapse and highlight the nondeterministic nature of human responses to past climate change.
Projecting climate change impacts on hydrology: the potential role of daily GCM output

NASA Astrophysics Data System (ADS)

Maurer, E. P.; Hidalgo, H. G.; Das, T.; Dettinger, M. D.; Cayan, D.

2008-12-01

A primary challenge facing resource managers in accommodating climate change is determining the range and uncertainty in regional and local climate projections. This is especially important for assessing changes in extreme events, which will drive many of the more severe impacts of a changed climate. Since global climate models (GCMs) produce output at a spatial scale incompatible with local impact assessment, different techniques have evolved to downscale GCM output so locally important climate features are expressed in the projections. We compared skill and hydrologic projections using two statistical downscaling methods and a distributed hydrology model. The downscaling methods are the constructed analogues (CA) and the bias correction and spatial downscaling (BCSD). CA uses daily GCM output, and can thus capture GCM projections for changing extreme event occurrence, while BCSD uses monthly output and statistically generates historical daily sequences. We evaluate the hydrologic impacts projected using downscaled climate (from the NCEP/NCAR reanalysis as a surrogate GCM) for the late 20th century with both methods, comparing skill in projecting soil moisture, snow pack, and streamflow at key locations in the Western United States. We include an assessment of a new method for correcting for GCM biases in a hybrid method combining the most important characteristics of both methods.
Climate Change Impacts and Adaptation on Southwestern DoD Facilities

DTIC Science & Technology

2017-03-03

integrating climate change risks into decision priorities. 15. SUBJECT TERMS adaptation, baseline sensitivity, climate change, climate exposure...four bases we found that integrating climate change risks into the current decision matrix, by linking projected risks to current or past impacts...data and decision tools and methods. Bases have some capacity to integrate climate-related information, but they have limited resources to undertake
Deducing Climatic Elasticity to Assess Projected Climate Change Impacts on Streamflow Change across China

NASA Astrophysics Data System (ADS)

Liu, Jianyu; Zhang, Qiang; Zhang, Yongqiang; Chen, Xi; Li, Jianfeng; Aryal, Santosh K.

2017-10-01

Climatic elasticity has been widely applied to assess streamflow responses to climate changes. To fully assess impacts of climate under global warming on streamflow and reduce the error and uncertainty from various control variables, we develop a four-parameter (precipitation, catchment characteristics n, and maximum and minimum temperatures) climatic elasticity method named PnT, based on the widely used Budyko framework and simplified Makkink equation. We use this method to carry out the first comprehensive evaluation of the streamflow response to potential climate change for 372 widely spread catchments in China. The PnT climatic elasticity was first evaluated for a period 1980-2000, and then used to evaluate streamflow change response to climate change based on 12 global climate models under Representative Concentration Pathway 2.6 (RCP2.6) and RCP 8.5 emission scenarios. The results show that (1) the PnT climatic elasticity method is reliable; (2) projected increasing streamflow takes place in more than 60% of the selected catchments, with mean increments of 9% and 15.4% under RCP2.6 and RCP8.5 respectively; and (3) uncertainties in the projected streamflow are considerable in several regions, such as the Pearl River and Yellow River, with more than 40% of the selected catchments showing inconsistent change directions. Our results can help Chinese policy makers to manage and plan water resources more effectively, and the PnT climatic elasticity should be applied to other parts of the world.
Approaches to predicting potential impacts of climate change on forest disease: An example with Armillaria root disease

Treesearch

Ned B. Klopfenstein; Mee-Sook Kim; John W. Hanna; Bryce A. Richardson; John E. Lundquist

2011-01-01

Climate change will likely have dramatic impacts on forest health because many forest trees could become maladapted to climate. Furthermore, climate change will have additional impacts on forest health through changes in the distribution and severity of forest disease. Methods are needed to predict the influence of climate change on forest disease so that appropriate...
Climate Change Impacts and Vulnerability Assessment in Industrial Complexes

NASA Astrophysics Data System (ADS)

Lee, H. J.; Lee, D. K.

2016-12-01

Climate change has recently caused frequent natural disasters, such as floods, droughts, and heat waves. Such disasters have also increased industrial damages. We must establish climate change adaptation policies to reduce the industrial damages. It is important to make accurate vulnerability assessment to establish climate change adaptation policies. Thus, this study aims at establishing a new index to assess vulnerability level in industrial complexes. Most vulnerability indices have been developed with subjective approaches, such as the Delphi survey and the Analytic Hierarchy Process(AHP). The subjective approaches rely on the knowledge of a few experts, which provokes the lack of the reliability of the indices. To alleviate the problem, we have designed a vulnerability index incorporating objective approaches. We have investigated 42 industrial complex sites in Republic of Korea (ROK). To calculate weights of variables, we used entropy method as an objective method integrating the Delphi survey as a subjective method. Finally, we found our method integrating both subjective method and objective method could generate result. The integration of the entropy method enables us to assess the vulnerability objectively. Our method will be useful to establish climate change adaptation policies by reducing the uncertainties of the methods based on the subjective approaches.
Relating Climate Change Risks to Water Supply Planning Assumptions: Recent Applications by the U.S. Bureau of Reclamation (Invited)

NASA Astrophysics Data System (ADS)

Brekke, L. D.

2009-12-01

Presentation highlights recent methods carried by Reclamation to incorporate climate change and variability information into water supply assumptions for longer-term planning. Presentation also highlights limitations of these methods, and possible method adjustments that might be made to address these limitations. Reclamation was established more than one hundred years ago with a mission centered on the construction of irrigation and hydropower projects in the Western United States. Reclamation’s mission has evolved since its creation to include other activities, including municipal and industrial water supply projects, ecosystem restoration, and the protection and management of water supplies. Reclamation continues to explore ways to better address mission objectives, often considering proposals to develop new infrastructure and/or modify long-term criteria for operations. Such studies typically feature operations analysis to disclose benefits and effects of a given proposal, which are sensitive to assumptions made about future water supplies, water demands, and operating constraints. Development of these assumptions requires consideration to more fundamental future drivers such as land use, demographics, and climate. On the matter of establishing planning assumptions for water supplies under climate change, Reclamation has applied several methods. This presentation highlights two activities where the first focuses on potential changes in hydroclimate frequencies and the second focuses on potential changes in hydroclimate period-statistics. The first activity took place in the Colorado River Basin where there was interest in the interarrival possibilities of drought and surplus events of varying severity relevant to proposals on new criteria for handling lower basin shortages. The second activity occurred in California’s Central Valley where stakeholders were interested in how projected climate change possibilities translated into changes in hydrologic and water supply statistics relevant to a long-term federal Endangered Species Act consultation. Projected climate change possibilities were characterized by surveying a large ensemble of climate projections for change in period climate-statistics and then selecting a small set of projections featuring a bracketing set of period-changes relative to the those from the complete ensemble. Although both methods served the needs of their respective planning activities, each has limited applicability for other planning activities. First, each method addresses only one climate change aspect and not the other. Some planning activities may need to consider potential changes in both period-statistics and frequencies. Second, neither method addresses CMIP3 projected changes in climate variability. The first method bases frequency possibilities on historical information while the second method only surveys CMIP3 projections for change in period-mean and then superimposes those changes on historical variability. Third, artifacts of CMIP3 design lead to interpretation challenges when implementing the second method (e.g., inconsistent projection initialization, model-dependent expressions of multi-decadal variability). Presentation summarizes these issues and also potential method adjustments to address them when defining planning assumptions for water supplies.
Beyond Reduction: Climate Change Adaptation Planning for Universities and Colleges

ERIC Educational Resources Information Center

Owen, Rochelle; Fisher, Erica; McKenzie, Kyle

2013-01-01

Purpose: The purpose of this paper is to outline a unique six-step process for the inclusion of climate change adaption goals and strategies in a University Climate Change Plan. Design/methodology/approach: A mixed-method approach was used to gather data on campus climate change vulnerabilities and adaption strategies. A literature review…
Assessing Elementary Science Methods Students' Understanding about Global Climate Change

ERIC Educational Resources Information Center

Lambert, Julie L.; Lindgren, Joan; Bleicher, Robert

2012-01-01

Global climate change, referred to as climate change in this paper, has become an important planetary issue, and given that K-12 students have numerous alternative conceptions or lack of prior knowledge, it is critical that teachers have an understanding of the fundamental science underlying climate change. Teachers need to understand the natural…
Climate Change Impacts at Department of Defense Installations

DTIC Science & Technology

2017-06-16

locations. The ease of use of this method and its flexibility have led to a wide variety of applications for assessing impacts of climate change 4...versions of these statistical methods to provide the basis for regional climate assessments for various states, regions, and government agencies...averaging (REA) method proposed by Giorgi and Mearns (2002). This method assigns reliability classifications for the multi-model ensemble simulation by
VALUE - Validating and Integrating Downscaling Methods for Climate Change Research

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Benestad, Rasmus; Kotlarski, Sven; Huth, Radan; Hertig, Elke; Wibig, Joanna; Gutierrez, Jose

2013-04-01

Our understanding of global climate change is mainly based on General Circulation Models (GCMs) with a relatively coarse resolution. Since climate change impacts are mainly experienced on regional scales, high-resolution climate change scenarios need to be derived from GCM simulations by downscaling. Several projects have been carried out over the last years to validate the performance of statistical and dynamical downscaling, yet several aspects have not been systematically addressed: variability on sub-daily, decadal and longer time-scales, extreme events, spatial variability and inter-variable relationships. Different downscaling approaches such as dynamical downscaling, statistical downscaling and bias correction approaches have not been systematically compared. Furthermore, collaboration between different communities, in particular regional climate modellers, statistical downscalers and statisticians has been limited. To address these gaps, the EU Cooperation in Science and Technology (COST) action VALUE (www.value-cost.eu) has been brought into life. VALUE is a research network with participants from currently 23 European countries running from 2012 to 2015. Its main aim is to systematically validate and develop downscaling methods for climate change research in order to improve regional climate change scenarios for use in climate impact studies. Inspired by the co-design idea of the international research initiative "future earth", stakeholders of climate change information have been involved in the definition of research questions to be addressed and are actively participating in the network. The key idea of VALUE is to identify the relevant weather and climate characteristics required as input for a wide range of impact models and to define an open framework to systematically validate these characteristics. Based on a range of benchmark data sets, in principle every downscaling method can be validated and compared with competing methods. The results of this exercise will directly provide end users with important information about the uncertainty of regional climate scenarios, and will furthermore provide the basis for further developing downscaling methods. This presentation will provide background information on VALUE and discuss the identified characteristics and the validation framework.

Advancing Research Methods to Detect Impact of Climate Change on Health in Grand'Anse, Haiti

NASA Astrophysics Data System (ADS)

Barnhart, S.; Coq, R. N.; Frederic, R.; DeRiel, E.; Camara, H.; Barnhart, K. R.

2013-12-01

Haiti is considered particularly vulnerable to the effects of climate change, but directly linking climate change to health effects is limited by the lack of robust data and the multiple determinants of health. Worsening storms and rising temperatures in this rugged country with high poverty is likely to adversely affect economic activity, population growth and other determinants of health. For the past two years, the Univ. of Washington has supported the public hospital in the department of Grand'Anse. Grand'Anse, a relatively contained region in SW Haiti with an area of 11,912 km2, is predominantly rural with a population of 350,000 and is bounded to the south by peaks up to 2,347 m. Grand'Anse would serve as an excellent site to assess the interface between climate change and health. The Demographic and Health Survey (DHS) shows health status is low relative to other countries. Estimates of climate change for Jeremie, the largest city in Grand'Anse, predict the mean monthly temperature will increase from 26.1 to 27.3 oC while mean monthly rainfall will decrease from 80.5 to 73.5 mm over the next 60 years. The potential impact of these changes ranges from threatening food security to greater mortality. Use of available secondary data such as indicators of climate change and DHS health status are not likely to offer sufficient resolution to detect positive or negative impacts of climate change on health. How might a mixed methods approach incorporating secondary data and quantitative and qualitative survey data on climate, economic activity, health and determinants of health address the hypothesis: Climate change does not adversely affect health? For example, in Haiti most women deliver at home. Maternal mortality is high at 350 deaths/100,000 deliveries. This compares to deliveries in facilities where the median rate is less than 100/100,000. Thus, maternal mortality is closely linked to access to health care in this rugged mountainous country. Climate change might result in worsening tropical storms that impede access due to the poor condition of footpaths and thus adversely affect maternal mortality. Additional factors such as deforestation and associated accelerated rainwater runoff may further worsen conditions. The linkage between maternal mortality and climate change will not be detected unless more robust methods are used. We propose using a mixed methods approach that combines use of secondary climate and health data (e.g. Landsat, stream flow, precipitation) with a stratified spatial sampling strategy across this complex land mass coupled with direct observation and qualitative methods using key informant interviews to probe for root causes of changes in health outcomes such as weather, deforestation, food and economic security. This mixed methods approach can be used for cross-sectional, retrospective and longitudinal studies linking the impact of climatological factors and important determinants of health such as economic activity. We propose that the impact of climate change on health will be best studied by mixed method approaches and that reliance on secondary data alone risks missing important associations between changes in climate and health.
Study of phase clustering method for analyzing large volumes of meteorological observation data

NASA Astrophysics Data System (ADS)

Volkov, Yu. V.; Krutikov, V. A.; Botygin, I. A.; Sherstnev, V. S.; Sherstneva, A. I.

2017-11-01

The article describes an iterative parallel phase grouping algorithm for temperature field classification. The algorithm is based on modified method of structure forming by using analytic signal. The developed method allows to solve tasks of climate classification as well as climatic zoning for any time or spatial scale. When used to surface temperature measurement series, the developed algorithm allows to find climatic structures with correlated changes of temperature field, to make conclusion on climate uniformity in a given area and to overview climate changes over time by analyzing offset in type groups. The information on climate type groups specific for selected geographical areas is expanded by genetic scheme of class distribution depending on change in mutual correlation level between ground temperature monthly average.
A hydrologic drying bias in water-resource impact analyses of anthropogenic climate change

USGS Publications Warehouse

Milly, Paul; Dunne, Krista A.

2017-01-01

For water-resource planning, sensitivity of freshwater availability to anthropogenic climate change (ACC) often is analyzed with “offline” hydrologic models that use precipitation and potential evapotranspiration (Ep) as inputs. Because Ep is not a climate-model output, an intermediary model of Ep must be introduced to connect the climate model to the hydrologic model. Several Ep methods are used. The suitability of each can be assessed by noting a credible Ep method for offline analyses should be able to reproduce climate models’ ACC-driven changes in actual evapotranspiration in regions and seasons of negligible water stress (Ew). We quantified this ability for seven commonly used Ep methods and for a simple proportionality with available energy (“energy-only” method). With the exception of the energy-only method, all methods tend to overestimate substantially the increase in Ep associated with ACC. In an offline hydrologic model, the Ep-change biases produce excessive increases in actual evapotranspiration (E), whether the system experiences water stress or not, and thence strong negative biases in runoff change, as compared to hydrologic fluxes in the driving climate models. The runoff biases are comparable in magnitude to the ACC-induced runoff changes themselves. These results suggest future hydrologic drying (wetting) trends likely are being systematically and substantially overestimated (underestimated) in many water-resource impact analyses.
Developing and applying uncertain global climate change projections for regional water management planning

NASA Astrophysics Data System (ADS)

Groves, David G.; Yates, David; Tebaldi, Claudia

2008-12-01

Climate change may impact water resources management conditions in difficult-to-predict ways. A key challenge for water managers is how to incorporate highly uncertain information about potential climate change from global models into local- and regional-scale water management models and tools to support local planning. This paper presents a new method for developing large ensembles of local daily weather that reflect a wide range of plausible future climate change scenarios while preserving many statistical properties of local historical weather patterns. This method is demonstrated by evaluating the possible impact of climate change on the Inland Empire Utilities Agency service area in southern California. The analysis shows that climate change could impact the region, increasing outdoor water demand by up to 10% by 2040, decreasing local water supply by up to 40% by 2040, and decreasing sustainable groundwater yields by up to 15% by 2040. The range of plausible climate projections suggests the need for the region to augment its long-range water management plans to reduce its vulnerability to climate change.
Climatic Change--Past, Present & Future

ERIC Educational Resources Information Center

Lindholm, Roy C.

1976-01-01

Presented is a review of studies investigating factors affecting climatic changes in the Earth's atmosphere--past, present, and future. Dating methods, particularly the Oxygen 18/16 method, are discussed. (SL)
Assessing species vulnerability to climate change

NASA Astrophysics Data System (ADS)

Pacifici, Michela; Foden, Wendy B.; Visconti, Piero; Watson, James E. M.; Butchart, Stuart H. M.; Kovacs, Kit M.; Scheffers, Brett R.; Hole, David G.; Martin, Tara G.; Akçakaya, H. Resit; Corlett, Richard T.; Huntley, Brian; Bickford, David; Carr, Jamie A.; Hoffmann, Ary A.; Midgley, Guy F.; Pearce-Kelly, Paul; Pearson, Richard G.; Williams, Stephen E.; Willis, Stephen G.; Young, Bruce; Rondinini, Carlo

2015-03-01

The effects of climate change on biodiversity are increasingly well documented, and many methods have been developed to assess species' vulnerability to climatic changes, both ongoing and projected in the coming decades. To minimize global biodiversity losses, conservationists need to identify those species that are likely to be most vulnerable to the impacts of climate change. In this Review, we summarize different currencies used for assessing species' climate change vulnerability. We describe three main approaches used to derive these currencies (correlative, mechanistic and trait-based), and their associated data requirements, spatial and temporal scales of application and modelling methods. We identify strengths and weaknesses of the approaches and highlight the sources of uncertainty inherent in each method that limit projection reliability. Finally, we provide guidance for conservation practitioners in selecting the most appropriate approach(es) for their planning needs and highlight priority areas for further assessments.
A new economic assessment index for the impact of climate change on grain yield

NASA Astrophysics Data System (ADS)

Dong, Wenjie; Chou, Jieming; Feng, Guolin

2007-03-01

The impact of climate change on agriculture has received wide attention by the scientific community. This paper studies how to assess the grain yield impact of climate change, according to the climate change over a long time period in the future as predicted by a climate system model. The application of the concept of a traditional “yield impact of meteorological factor (YIMF)” or “yield impact of weather factor” to the grain yield assessment of a decadal or even a longer timescale would be suffocated at the outset because the YIMF is for studying the phenomenon on an interannual timescale, and it is difficult to distinguish between the trend caused by climate change and the one resulting from changes in non-climatic factors. Therefore, the concept of the yield impact of climatic change (YICC), which is defined as the difference in the per unit area yields (PUAY) of a grain crop under a changing and an envisaged invariant climate conditions, is presented in this paper to assess the impact of global climate change on grain yields. The climatic factor has been introduced into the renowned economic Cobb-Douglas model, yielding a quantitative assessment method of YICC using real data. The method has been tested using the historical data of Northeast China, and the results show that it has an encouraging application outlook.
Exploring adaptations to climate change with stakeholders: A participatory method to design grassland-based farming systems.

PubMed

Sautier, Marion; Piquet, Mathilde; Duru, Michel; Martin-Clouaire, Roger

2017-05-15

Research is expected to produce knowledge, methods and tools to enhance stakeholders' adaptive capacity by helping them to anticipate and cope with the effects of climate change at their own level. Farmers face substantial challenges from climate change, from changes in the average temperatures and the precipitation regime to an increased variability of weather conditions and the frequency of extreme events. Such changes can have dramatic consequences for many types of agricultural production systems such as grassland-based livestock systems for which climate change influences the seasonality and productivity of fodder production. We present a participatory design method called FARMORE (FARM-Oriented REdesign) that allows farmers to design and evaluate adaptations of livestock systems to future climatic conditions. It explicitly considers three climate features in the design and evaluation processes: climate change, climate variability and the limited predictability of weather. FARMORE consists of a sequence of three workshops for which a pre-existing game-like platform was adapted. Various year-round forage production and animal feeding requirements must be assembled by participants with a computerized support system. In workshop 1, farmers aim to produce a configuration that satisfies an average future weather scenario. They refine or revise the previous configuration by considering a sample of the between-year variability of weather in workshop 2. In workshop 3, they explicitly take the limited predictability of weather into account. We present the practical aspects of the method based on four case studies involving twelve farmers from Aveyron (France), and illustrate it through an in-depth description of one of these case studies with three dairy farmers. The case studies shows and discusses how workshop sequencing (1) supports a design process that progressively accommodates complexity of real management contexts by enlarging considerations of climate change to climate variability and low weather predictability, and (2) increases the credibility and salience of the design method. Further enhancements of the method are outlined, especially the selection of pertinent weather scenarios. Copyright © 2017 Elsevier Ltd. All rights reserved.
Rural health service managers' perspectives on preparing rural health services for climate change.

PubMed

Purcell, Rachael; McGirr, Joe

2018-02-01

To determine health service managers' (HSMs) recommendations on strengthening the health service response to climate change. Self-administered survey in paper or electronic format. Rural south-west of New South Wales. Health service managers working in rural remote metropolitan areas 3-7. Proportion of respondents identifying preferred strategies for preparation of rural health services for climate change. There were 43 participants (53% response rate). Most respondents agreed that there is scepticism regarding climate change among health professionals (70%, n = 30) and community members (72%, n = 31). Over 90% thought that climate change would impact the health of rural populations in the future with regard to heat-related illnesses, mental health, skin cancer and water security. Health professionals and government were identified as having key leadership roles on climate change and health in rural communities. Over 90% of the respondents believed that staff and community in local health districts (LHDs) should be educated about the health impacts of climate change. Public health education facilitated by State or Federal Government was the preferred method of educating community members, and education facilitated by the LHD was the preferred method for educating health professionals. Health service managers hold important health leadership roles within rural communities and their health services. The study highlights the scepticism towards climate change among health professionals and community members in rural Australia. It identifies the important role of rural health services in education and advocacy on the health impacts of climate change and identifies recommended methods of public health education for community members and health professionals. © 2017 National Rural Health Alliance Inc.
Understandings of Climate Change Articulated by Swedish Secondary School Students

ERIC Educational Resources Information Center

Holmqvist Olander, Mona; Olander, Clas

2017-01-01

This study investigated beliefs about climate change among Swedish secondary school students at the end of their K-12 education. An embedded mixed method approach was used to analyse 51 secondary school students' written responses to two questions: (1) What implies climate change? (2) What affects climate? A quantitative analysis of the responses…
Climate Cases: Learning about Student Conceptualizations of Global Climate Change

ERIC Educational Resources Information Center

Tierney, Benjamin P.

2013-01-01

The complex topic of global climate change continues to be a challenging yet important topic among science educators and researchers. This mixed methods study adds to the growing research by investigating student conceptions of climate change from a system theory perspective (Von Bertalanffy, 1968) by asking the question, "How do differences…
Climate-induced change of environmentally defined floristic domains: A conservation based vulnerability framework

Treesearch

Debbie Jewitt; Barend F.N. Erasmus; Peter S. Goodman; Timothy G. O' Connor; William W. Hargrove; Damian M. Maddalena; Ed. T.F. Witkowski

2015-01-01

Global climate change is having marked influences on species distributions, phenology and ecosystem composition and raises questions as to the effectiveness of current conservation strategies. Conservation planning has only recently begun to adequately account for dynamic threats such as climate change. We propose a method to incorporate climate-dynamic environmental...
A method to encapsulate model structural uncertainty in ensemble projections of future climate: EPIC v1.0

NASA Astrophysics Data System (ADS)

Lewis, Jared; Bodeker, Greg E.; Kremser, Stefanie; Tait, Andrew

2017-12-01

A method, based on climate pattern scaling, has been developed to expand a small number of projections of fields of a selected climate variable (X) into an ensemble that encapsulates a wide range of indicative model structural uncertainties. The method described in this paper is referred to as the Ensemble Projections Incorporating Climate model uncertainty (EPIC) method. Each ensemble member is constructed by adding contributions from (1) a climatology derived from observations that represents the time-invariant part of the signal; (2) a contribution from forced changes in X, where those changes can be statistically related to changes in global mean surface temperature (Tglobal); and (3) a contribution from unforced variability that is generated by a stochastic weather generator. The patterns of unforced variability are also allowed to respond to changes in Tglobal. The statistical relationships between changes in X (and its patterns of variability) and Tglobal are obtained in a training phase. Then, in an implementation phase, 190 simulations of Tglobal are generated using a simple climate model tuned to emulate 19 different global climate models (GCMs) and 10 different carbon cycle models. Using the generated Tglobal time series and the correlation between the forced changes in X and Tglobal, obtained in the training phase, the forced change in the X field can be generated many times using Monte Carlo analysis. A stochastic weather generator is used to generate realistic representations of weather which include spatial coherence. Because GCMs and regional climate models (RCMs) are less likely to correctly represent unforced variability compared to observations, the stochastic weather generator takes as input measures of variability derived from observations, but also responds to forced changes in climate in a way that is consistent with the RCM projections. This approach to generating a large ensemble of projections is many orders of magnitude more computationally efficient than running multiple GCM or RCM simulations. Such a large ensemble of projections permits a description of a probability density function (PDF) of future climate states rather than a small number of individual story lines within that PDF, which may not be representative of the PDF as a whole; the EPIC method largely corrects for such potential sampling biases. The method is useful for providing projections of changes in climate to users wishing to investigate the impacts and implications of climate change in a probabilistic way. A web-based tool, using the EPIC method to provide probabilistic projections of changes in daily maximum and minimum temperatures for New Zealand, has been developed and is described in this paper.
A quantitative method for risk assessment of agriculture due to climate change

NASA Astrophysics Data System (ADS)

Dong, Zhiqiang; Pan, Zhihua; An, Pingli; Zhang, Jingting; Zhang, Jun; Pan, Yuying; Huang, Lei; Zhao, Hui; Han, Guolin; Wu, Dong; Wang, Jialin; Fan, Dongliang; Gao, Lin; Pan, Xuebiao

2018-01-01

Climate change has greatly affected agriculture. Agriculture is facing increasing risks as its sensitivity and vulnerability to climate change. Scientific assessment of climate change-induced agricultural risks could help to actively deal with climate change and ensure food security. However, quantitative assessment of risk is a difficult issue. Here, based on the IPCC assessment reports, a quantitative method for risk assessment of agriculture due to climate change is proposed. Risk is described as the product of the degree of loss and its probability of occurrence. The degree of loss can be expressed by the yield change amplitude. The probability of occurrence can be calculated by the new concept of climate change effect-accumulated frequency (CCEAF). Specific steps of this assessment method are suggested. This method is determined feasible and practical by using the spring wheat in Wuchuan County of Inner Mongolia as a test example. The results show that the fluctuation of spring wheat yield increased with the warming and drying climatic trend in Wuchuan County. The maximum yield decrease and its probability were 3.5 and 64.6%, respectively, for the temperature maximum increase 88.3%, and its risk was 2.2%. The maximum yield decrease and its probability were 14.1 and 56.1%, respectively, for the precipitation maximum decrease 35.2%, and its risk was 7.9%. For the comprehensive impacts of temperature and precipitation, the maximum yield decrease and its probability were 17.6 and 53.4%, respectively, and its risk increased to 9.4%. If we do not adopt appropriate adaptation strategies, the degree of loss from the negative impacts of multiclimatic factors and its probability of occurrence will both increase accordingly, and the risk will also grow obviously.
Office of Land and Emergency Management (OLEM) Climate Change Adaptation Training

EPA Pesticide Factsheets

This training discusses climate vulnerabilities and methods for incorporating adaptation measures into OLEM programs. This training is meant to follow completion of EPA's Introductory Climate Change Training.
Climate Change Discourse in Mass Media: Application of Computer-Assisted Content Analysis

ERIC Educational Resources Information Center

Kirilenko, Andrei P.; Stepchenkova, Svetlana O.

2012-01-01

Content analysis of mass media publications has become a major scientific method used to analyze public discourse on climate change. We propose a computer-assisted content analysis method to extract prevalent themes and analyze discourse changes over an extended period in an objective and quantifiable manner. The method includes the following: (1)…
Assessment of the Effect of Climate Change on Grain Yields in China

NASA Astrophysics Data System (ADS)

Chou, J.

2006-12-01

The paper elaborates the social background and research background; makes clear what the key scientific issues need to be resolved and where the difficulties are. In the research area of parasailing the grain yield change caused by climate change, massive works have been done both in the domestic and in the foreign. It is our upcoming work to evaluate how our countrywide climate change information provided by this pattern influence our economic and social development; and how to make related policies and countermeasures. the main idea in this paper is that the grain yield change is by no means the linear composition of social economy function effect and the climatic change function effect. This paper identifies the economic evaluation object, proposes one new concept - climate change output. The grain yields change affected by the social factors and the climatic change working together. Climate change influences the grain yields by the non ¨C linear function from both climate change and social factor changes, not only by climate change itself. Therefore, in my paper, the appraisal object is defined as: The social factors change based on actual social changing situations; under the two kinds of climate change situation, the invariable climate change situation and variable climate change situation; the difference of grain yield outputs is called " climate change output ", In order to solve this problem, we propose a method to analyze and imitate on the historical materials. Giving the condition that the climate is invariable, the social economic factor changes cause the grain yield change. However, this grain yield change is a tentative quantity index, not an actual quantity number. So we use the existing historical materials to exam the climate change output, based on the characteristic that social factor changes greater in year than in age, but the climate factor changes greater in age than in year. The paper proposes and establishes one economy - climate model (C-D-C model) to appraise the grain yield change caused by the climatic change. Also the preliminary test on this model has been done. In selection of the appraisal methods, we take the C-D production function model, which has been proved more mature in the economic research, as our fundamental model. Then, we introduce climate index (arid index) to the C-D model to develop one new model. This new model utilizes the climatic change factor in the economical model to appraise how the climatic change influence the grain yield change. The new way of appraise should have the better application prospect. The economy - climate model (The C-D-C model) has been applied on the eight Chinese regions that we divide; it has been proved satisfactory in its feasibility, rationality and the application prospect. So we can provide the theoretical fundamentals for policy-making under the more complex and uncertain climate change. Therefore, we open a new possible channel for the global climate change research moving toward the actual social, economic life.
A method for physically based model analysis of conjunctive use in response to potential climate changes

USGS Publications Warehouse

Hanson, R.T.; Flint, L.E.; Flint, A.L.; Dettinger, M.D.; Faunt, C.C.; Cayan, D.; Schmid, W.

2012-01-01

Potential climate change effects on aspects of conjunctive management of water resources can be evaluated by linking climate models with fully integrated groundwater-surface water models. The objective of this study is to develop a modeling system that links global climate models with regional hydrologic models, using the California Central Valley as a case study. The new method is a supply and demand modeling framework that can be used to simulate and analyze potential climate change and conjunctive use. Supply-constrained and demand-driven linkages in the water system in the Central Valley are represented with the linked climate models, precipitation-runoff models, agricultural and native vegetation water use, and hydrologic flow models to demonstrate the feasibility of this method. Simulated precipitation and temperature were used from the GFDL-A2 climate change scenario through the 21st century to drive a regional water balance mountain hydrologic watershed model (MHWM) for the surrounding watersheds in combination with a regional integrated hydrologic model of the Central Valley (CVHM). Application of this method demonstrates the potential transition from predominantly surface water to groundwater supply for agriculture with secondary effects that may limit this transition of conjunctive use. The particular scenario considered includes intermittent climatic droughts in the first half of the 21st century followed by severe persistent droughts in the second half of the 21st century. These climatic droughts do not yield a valley-wide operational drought but do cause reduced surface water deliveries and increased groundwater abstractions that may cause additional land subsidence, reduced water for riparian habitat, or changes in flows at the Sacramento-San Joaquin River Delta. The method developed here can be used to explore conjunctive use adaptation options and hydrologic risk assessments in regional hydrologic systems throughout the world.
Model uncertainties do not affect observed patterns of species richness in the Amazon.

PubMed

Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo; Loyola, Rafael

2017-01-01

Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale-patterns of species richness and species vulnerability to climate change-are affected by the inputs used to model and project species distribution. We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of variation, choosing the appropriate statistics according to the study objective is also essential for estimating the impacts of climate change on species distribution. Yet from a conservation perspective, we show that Amazon endemic fauna is potentially vulnerable to climate change, due to expected reductions on suitable climate area. Climate-driven faunal movements are predicted towards the Andes mountains, which might work as climate refugia for migrating species.
Climate change and dengue: a critical and systematic review of quantitative modelling approaches

PubMed Central

2014-01-01

Background Many studies have found associations between climatic conditions and dengue transmission. However, there is a debate about the future impacts of climate change on dengue transmission. This paper reviewed epidemiological evidence on the relationship between climate and dengue with a focus on quantitative methods for assessing the potential impacts of climate change on global dengue transmission. Methods A literature search was conducted in October 2012, using the electronic databases PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search focused on peer-reviewed journal articles published in English from January 1991 through October 2012. Results Sixteen studies met the inclusion criteria and most studies showed that the transmission of dengue is highly sensitive to climatic conditions, especially temperature, rainfall and relative humidity. Studies on the potential impacts of climate change on dengue indicate increased climatic suitability for transmission and an expansion of the geographic regions at risk during this century. A variety of quantitative modelling approaches were used in the studies. Several key methodological issues and current knowledge gaps were identified through this review. Conclusions It is important to assemble spatio-temporal patterns of dengue transmission compatible with long-term data on climate and other socio-ecological changes and this would advance projections of dengue risks associated with climate change. PMID:24669859

Model uncertainties do not affect observed patterns of species richness in the Amazon

PubMed Central

Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo

2017-01-01

Background Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale—patterns of species richness and species vulnerability to climate change—are affected by the inputs used to model and project species distribution. Methods We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. Results The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. Conclusions From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of variation, choosing the appropriate statistics according to the study objective is also essential for estimating the impacts of climate change on species distribution. Yet from a conservation perspective, we show that Amazon endemic fauna is potentially vulnerable to climate change, due to expected reductions on suitable climate area. Climate-driven faunal movements are predicted towards the Andes mountains, which might work as climate refugia for migrating species. PMID:29023503
Directed International Technological Change and Climate Policy: New Methods for Identifying Robust Policies Under Conditions of Deep Uncertainty

NASA Astrophysics Data System (ADS)

Molina-Perez, Edmundo

It is widely recognized that international environmental technological change is key to reduce the rapidly rising greenhouse gas emissions of emerging nations. In 2010, the United Nations Framework Convention on Climate Change (UNFCCC) Conference of the Parties (COP) agreed to the creation of the Green Climate Fund (GCF). This new multilateral organization has been created with the collective contributions of COP members, and has been tasked with directing over USD 100 billion per year towards investments that can enhance the development and diffusion of clean energy technologies in both advanced and emerging nations (Helm and Pichler, 2015). The landmark agreement arrived at the COP 21 has reaffirmed the key role that the GCF plays in enabling climate mitigation as it is now necessary to align large scale climate financing efforts with the long-term goals agreed at Paris 2015. This study argues that because of the incomplete understanding of the mechanics of international technological change, the multiplicity of policy options and ultimately the presence of climate and technological change deep uncertainty, climate financing institutions such as the GCF, require new analytical methods for designing long-term robust investment plans. Motivated by these challenges, this dissertation shows that the application of new analytical methods, such as Robust Decision Making (RDM) and Exploratory Modeling (Lempert, Popper and Bankes, 2003) to the study of international technological change and climate policy provides useful insights that can be used for designing a robust architecture of international technological cooperation for climate change mitigation. For this study I developed an exploratory dynamic integrated assessment model (EDIAM) which is used as the scenario generator in a large computational experiment. The scope of the experimental design considers an ample set of climate and technological scenarios. These scenarios combine five sources of uncertainty: climate change, elasticity of substitution between renewable and fossil energy and three different sources of technological uncertainty (i.e. R&D returns, innovation propensity and technological transferability). The performance of eight different GCF and non-GCF based policy regimes is evaluated in light of various end-of-century climate policy targets. Then I combine traditional scenario discovery data mining methods (Bryant and Lempert, 2010) with high dimensional stacking methods (Suzuki, Stem and Manzocchi, 2015; Taylor et al., 2006; LeBlanc, Ward and Wittels, 1990) to quantitatively characterize the conditions under which it is possible to stabilize greenhouse gas emissions and keep temperature rise below 2°C before the end of the century. Finally, I describe a method by which it is possible to combine the results of scenario discovery with high-dimensional stacking to construct a dynamic architecture of low cost technological cooperation. This dynamic architecture consists of adaptive pathways (Kwakkel, Haasnoot and Walker, 2014; Haasnoot et al., 2013) which begin with carbon taxation across both regions as a critical near term action. Then in subsequent phases different forms of cooperation are triggered depending on the unfolding climate and technological conditions. I show that there is no single policy regime that dominates over the entire uncertainty space. Instead I find that it is possible to combine these different architectures into a dynamic framework for technological cooperation across regions that can be adapted to unfolding climate and technological conditions which can lead to a greater rate of success and to lower costs in meeting the end-of-century climate change objectives agreed at the 2015 Paris Conference of the Parties. Keywords: international technological change, emerging nations, climate change, technological uncertainties, Green Climate Fund.
Upgrades to the REA method for producing probabilistic climate change projections

NASA Astrophysics Data System (ADS)

Xu, Ying; Gao, Xuejie; Giorgi, Filippo

2010-05-01

We present an augmented version of the Reliability Ensemble Averaging (REA) method designed to generate probabilistic climate change information from ensembles of climate model simulations. Compared to the original version, the augmented one includes consideration of multiple variables and statistics in the calculation of the performance-based weights. In addition, the model convergence criterion previously employed is removed. The method is applied to the calculation of changes in mean and variability for temperature and precipitation over different sub-regions of East Asia based on the recently completed CMIP3 multi-model ensemble. Comparison of the new and old REA methods, along with the simple averaging procedure, and the use of different combinations of performance metrics shows that at fine sub-regional scales the choice of weighting is relevant. This is mostly because the models show a substantial spread in performance for the simulation of precipitation statistics, a result that supports the use of model weighting as a useful option to account for wide ranges of quality of models. The REA method, and in particular the upgraded one, provides a simple and flexible framework for assessing the uncertainty related to the aggregation of results from ensembles of models in order to produce climate change information at the regional scale. KEY WORDS: REA method, Climate change, CMIP3
Argumentation as a Strategy for Increasing Preservice Teachers' Understanding of Climate Change, a Key Global Socioscientific Issue

ERIC Educational Resources Information Center

Lambert, Julie L.; Bleicher, Robert E.

2017-01-01

Findings of this study suggest that scientific argumentation can play an effective role in addressing complex socioscientific issues (i.e. global climate change). This research examined changes in preservice teachers' knowledge and perceptions about climate change in an innovative undergraduate-level elementary science methods course. The…
Using Four Downscaling Techniques to Characterize Uncertainty in Updating Intensity-Duration-Frequency Curves Under Climate Change

NASA Astrophysics Data System (ADS)

Cook, L. M.; Samaras, C.; McGinnis, S. A.

2017-12-01

Intensity-duration-frequency (IDF) curves are a common input to urban drainage design, and are used to represent extreme rainfall in a region. As rainfall patterns shift into a non-stationary regime as a result of climate change, these curves will need to be updated with future projections of extreme precipitation. Many regions have begun to update these curves to reflect the trends from downscaled climate models; however, few studies have compared the methods for doing so, as well as the uncertainty that results from the selection of the native grid scale and temporal resolution of the climate model. This study examines the variability in updated IDF curves for Pittsburgh using four different methods for adjusting gridded regional climate model (RCM) outputs into station scale precipitation extremes: (1) a simple change factor applied to observed return levels, (2) a naïve adjustment of stationary and non-stationary Generalized Extreme Value (GEV) distribution parameters, (3) a transfer function of the GEV parameters from the annual maximum series, and (4) kernel density distribution mapping bias correction of the RCM time series. Return level estimates (rainfall intensities) and confidence intervals from these methods for the 1-hour to 48-hour duration are tested for sensitivity to the underlying spatial and temporal resolution of the climate ensemble from the NA-CORDEX project, as well as, the future time period for updating. The first goal is to determine if uncertainty is highest for: (i) the downscaling method, (ii) the climate model resolution, (iii) the climate model simulation, (iv) the GEV parameters, or (v) the future time period examined. Initial results of the 6-hour, 10-year return level adjusted with the simple change factor method using four climate model simulations of two different spatial resolutions show that uncertainty is highest in the estimation of the GEV parameters. The second goal is to determine if complex downscaling methods and high-resolution climate models are necessary for updating, or if simpler methods and lower resolution climate models will suffice. The final results can be used to inform the most appropriate method and climate model resolutions to use for updating IDF curves for urban drainage design.
A Study of Teacher Candidates' Experiences Investigating Global Climate Change Within an Elementary Science Methods Course

NASA Astrophysics Data System (ADS)

Hestness, Emily; Randy McGinnis, J.; Riedinger, Kelly; Marbach-Ad, Gili

2011-06-01

We investigated the inclusion of a curricular module on global climate change in an Elementary Science Methods course. Using complementary research methods, we analyzed findings from 63 teacher candidates' drawings, questionnaires, and journal entries collected throughout their participation in the module. We highlighted three focal cases to illustrate the diversity of participants' experiences. Findings suggest potential positive impacts on teacher candidates' content understanding related to global climate change, confidence to teach, and awareness of resources to support their future science instruction. Recommendations for science teacher education underscore the importance of providing opportunities for teacher candidates to increase their relevant content understanding, helping teacher candidates become familiar with appropriate curricular resources, and engaging in ongoing conversation and evaluation of developing views and understandings related to global climate change.
A New Time-varying Concept of Risk in a Changing Climate.

PubMed

Sarhadi, Ali; Ausín, María Concepción; Wiper, Michael P

2016-10-20

In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.
Achieving Climate Change Absolute Accuracy in Orbit

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A.; Young, D. F.; Mlynczak, M. G.; Thome, K. J; Leroy, S.; Corliss, J.; Anderson, J. G.; Ao, C. O.; Bantges, R.; Best, F.;

2013-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREO's inherently high absolute accuracy will be verified and traceable on orbit to Système Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earth's thermal infrared spectrum (5-50 micron), the spectrum of solar radiation reflected by the Earth and its atmosphere (320-2300 nm), and radio occultation refractivity from which accurate temperature profiles are derived. The mission has the ability to provide new spectral fingerprints of climate change, as well as to provide the first orbiting radiometer with accuracy sufficient to serve as the reference transfer standard for other space sensors, in essence serving as a "NIST [National Institute of Standards and Technology] in orbit." CLARREO will greatly improve the accuracy and relevance of a wide range of space-borne instruments for decadal climate change. Finally, CLARREO has developed new metrics and methods for determining the accuracy requirements of climate observations for a wide range of climate variables and uncertainty sources. These methods should be useful for improving our understanding of observing requirements for most climate change observations.

Can changes in the distributions of resident birds in China over the past 50 years be attributed to climate change?

PubMed Central

Wu, Jianguo; Zhang, Guobin

2015-01-01

The distributions of bird species have changed over the past 50 years in China. To evaluate whether the changes can be attributed to the changing climate, we analyzed the distributions of 20 subspecies of resident birds in relation to climate change. Long-term records of bird distributions, gray relational analysis, fuzzy-set classification techniques, and attribution methods were used. Among the 20 subspecies of resident birds, the northern limits of over half of the subspecies have shifted northward since the 1960s, and most changes have been related to the thermal index. Driven by climate change over the past 50 years, the suitable range and latitude or longitude of the distribution centers of certain birds have exhibited increased fluctuations. The northern boundaries of over half of the subspecies have shifted northward compared with those in the 1960s. The consistency between the observed and predicted changes in the range limits was quite high for some subspecies. The changes in the northern boundaries or the latitudes of the centers of distribution of nearly half of the subspecies can be attributed to climate change. The results suggest that climate change has affected the distributions of particular birds. The method used to attribute changes in bird distributions to climate change may also be effective for other animals. PMID:26078858
Can changes in the distributions of resident birds in China over the past 50 years be attributed to climate change?

PubMed

Wu, Jianguo; Zhang, Guobin

2015-06-01

The distributions of bird species have changed over the past 50 years in China. To evaluate whether the changes can be attributed to the changing climate, we analyzed the distributions of 20 subspecies of resident birds in relation to climate change. Long-term records of bird distributions, gray relational analysis, fuzzy-set classification techniques, and attribution methods were used. Among the 20 subspecies of resident birds, the northern limits of over half of the subspecies have shifted northward since the 1960s, and most changes have been related to the thermal index. Driven by climate change over the past 50 years, the suitable range and latitude or longitude of the distribution centers of certain birds have exhibited increased fluctuations. The northern boundaries of over half of the subspecies have shifted northward compared with those in the 1960s. The consistency between the observed and predicted changes in the range limits was quite high for some subspecies. The changes in the northern boundaries or the latitudes of the centers of distribution of nearly half of the subspecies can be attributed to climate change. The results suggest that climate change has affected the distributions of particular birds. The method used to attribute changes in bird distributions to climate change may also be effective for other animals.
Evaluating the impact of climate change on landslide occurrence, hazard, and risk: from global to regional scale.

NASA Astrophysics Data System (ADS)

Gariano, Stefano Luigi; Guzzetti, Fausto

2017-04-01

According to the fifth report of the Intergovernmental Panel on Climate Change, "warming of the climate system is unequivocal". The influence of climate changes on slope stability and landslides is also undisputable. Nevertheless, the quantitative evaluation of the impact of global warming, and the related changes in climate, on landslides remains a complex question to be solved. The evidence that climate and landslides act at only partially overlapping spatial and temporal scales complicates the evaluation. Different research fields, including e.g., climatology, physics, hydrology, geology, hydrogeology, geotechnics, soil science, environmental science, and social science, must be considered. Climatic, environmental, demographic, and economic changes are strictly correlated, with complex feedbacks, to landslide occurrence and variation. Thus, a holistic, multidisciplinary approach is necessary. We reviewed the literature on landslide-climate studies, and found a bias in their geographical distribution, with several studies centered in Europe and North America, and large parts of the world not investigated. We examined advantages and drawbacks of the approaches adopted to evaluate the effects of climate variations on landslides, including prospective modelling and retrospective methods that use landslide and climate records, and paleo-environmental information. We found that the results of landslide-climate studies depend more on the emission scenarios, the global circulation models, the regional climate models, and the methods to downscale the climate variables, than on the description of the variables controlling slope processes. Using ensembles of projections based on a range of emissions scenarios would reduce (or at least quantify) the uncertainties in the obtained results. We performed a preliminary global assessment of the future landslide impact, presenting a global distribution of the projected impact of climate change on landslide activity and abundance. Where global warming is expected to increase, the frequency and intensity of severe rainfall events, a primary trigger of shallow, rapid-moving landslides that cause many landslide fatalities, an increase in the number of people exposed to landslide risk is to be expected. Furthermore, we defined a group of objective and reproducible methods for the quantitative evaluation of the past and future (expected) variations in landslide occurrence and distribution, and in the impact and risk to the population, as a result of changes in climatic and environmental factors (particularly, land use changes), at regional scale. The methods were tested in a southern Italian region, but they can easily applied in other physiographic and climatic regions, where adequate information is available.
Comparative risk assessment of the burden of disease from climate change.

PubMed

Campbell-Lendrum, Diarmid; Woodruff, Rosalie

2006-12-01

The World Health Organization has developed standardized comparative risk assessment methods for estimating aggregate disease burdens attributable to different risk factors. These have been applied to existing and new models for a range of climate-sensitive diseases in order to estimate the effect of global climate change on current disease burdens and likely proportional changes in the future. The comparative risk assessment approach has been used to assess the health consequences of climate change worldwide, to inform decisions on mitigating greenhouse gas emissions, and in a regional assessment of the Oceania region in the Pacific Ocean to provide more location-specific information relevant to local mitigation and adaptation decisions. The approach places climate change within the same criteria for epidemiologic assessment as other health risks and accounts for the size of the burden of climate-sensitive diseases rather than just proportional change, which highlights the importance of small proportional changes in diseases such as diarrhea and malnutrition that cause a large burden. These exercises help clarify important knowledge gaps such as a relatively poor understanding of the role of nonclimatic factors (socioeconomic and other) that may modify future climatic influences and a lack of empiric evidence and methods for quantifying more complex climate-health relationships, which consequently are often excluded from consideration. These exercises highlight the need for risk assessment frameworks that make the best use of traditional epidemiologic methods and that also fully consider the specific characteristics of climate change. These include the longterm and uncertain nature of the exposure and the effects on multiple physical and biotic systems that have the potential for diverse and widespread effects, including high-impact events.
Climate change vulnerability for species-Assessing the assessments.

PubMed

Wheatley, Christopher J; Beale, Colin M; Bradbury, Richard B; Pearce-Higgins, James W; Critchlow, Rob; Thomas, Chris D

2017-09-01

Climate change vulnerability assessments are commonly used to identify species at risk from global climate change, but the wide range of methodologies available makes it difficult for end users, such as conservation practitioners or policymakers, to decide which method to use as a basis for decision-making. In this study, we evaluate whether different assessments consistently assign species to the same risk categories and whether any of the existing methodologies perform well at identifying climate-threatened species. We compare the outputs of 12 climate change vulnerability assessment methodologies, using both real and simulated species, and validate the methods using historic data for British birds and butterflies (i.e. using historical data to assign risks and more recent data for validation). Our results show that the different vulnerability assessment methods are not consistent with one another; different risk categories are assigned for both the real and simulated sets of species. Validation of the different vulnerability assessments suggests that methods incorporating historic trend data into the assessment perform best at predicting distribution trends in subsequent time periods. This study demonstrates that climate change vulnerability assessments should not be used interchangeably due to the poor overall agreement between methods when considering the same species. The results of our validation provide more support for the use of trend-based rather than purely trait-based approaches, although further validation will be required as data become available. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
Knowledge and perceptions about the health impact of climate change among health sciences students in Ethiopia: a cross-sectional study

PubMed Central

2014-01-01

Background Climate change affects human health in various ways. Health planners and policy makers are increasingly addressing potential health impacts of climate change. Ethiopia is vulnerable to these impacts. Assessing students’ knowledge, understanding and perception about the health impact of climate change may promote educational endeavors to increase awareness of health impacts linked to climate change and to facilitate interventions. Methods A cross-sectional study using a questionnaire was carried out among the health science students at Haramaya University. Quantitative methods were used to analyze the results. Result Over three quarters of the students were aware of health consequences of climate change, with slightly higher rates in females than males and a range from 60.7% (pharmacy students) to 100% (environmental health and post-graduate public health students). Electronic mass media was reportedly the major source of information but almost all (87.7%) students stated that their knowledge was insufficient to fully understand the public health impacts of climate change. Students who knew about climate change were more likely to perceive it as a serious health threat than those who were unaware of these impacts [OR: 17.8, 95% CI: 8.8-32.1] and also considered their departments to be concerned about climate change (OR: 7.3, 95% CI: 2.8-18.8), a perception that was also significantly more common among students who obtained their information from the electronic mass media and schools (p < 0.05). Using electronic mass media was also significantly associated with knowledge about the health impacts of climate change. Conclusion Health sciences students at Haramaya University may benefit from a more comprehensive curriculum on climate change and its impacts on health. PMID:24916631
The effects of climate downscaling technique and observational data set on modeled ecological responses

Treesearch

Afshin Pourmokhtarian; Charles T. Driscoll; John L. Campbell; Katharine Hayhoe; Anne M. K. Stoner

2016-01-01

Assessments of future climate change impacts on ecosystems typically rely on multiple climate model projections, but often utilize only one downscaling approach trained on one set of observations. Here, we explore the extent to which modeled biogeochemical responses to changing climate are affected by the selection of the climate downscaling method and training...
Statistical downscaling of daily precipitation over Llobregat river basin in Catalonia (Spain) using three downscaling methods.

NASA Astrophysics Data System (ADS)

Ballinas, R.; Versini, P.-A.; Sempere, D.; Escaler, I.

2009-09-01

Any long-term change in the patterns of average weather in a global or regional scale is called climate change. It may cause a progressive increase of atmospheric temperature and consequently may change the amount, frequency and intensity of precipitation. All these changes of meteorological parameters may modify the water cycle: run-off, infiltration, aquifer recharge, etc. Recent studies in Catalonia foresee changes in hydrological systems caused by climate change. This will lead to alterations in the hydrological cycle that could impact in land use, in the regimen of water extractions, in the hydrological characteristics of the territory and reduced groundwater recharge. Besides, can expect a loss of flow in rivers. In addition to possible increases in the frequency of extreme rainfall, being necessary to modify the design of infrastructure. Because this, it work focuses on studying the impacts of climate change in one of the most important basins in Catalonia, the Llobregat River Basin. The basin is the hub of the province of Barcelona. It is a highly populated and urbanized catchment, where water resources are used for different purposes, as drinking water production, agricultural irrigation, industry and hydro-electrical energy production. In consequence, many companies and communities depend on these resources. To study the impact of climate change in the Llobregat basin, storms (frequency, intensity) mainly, we will need regional climate change information. A regional climate is determined by interactions at large, regional and local scales. The general circulation models (GCMs) are run at too coarse resolution to permit accurate description of these regional and local interactions. So far, they have been unable to provide consistent estimates of climate change on a local scale. Several regionalization techniques have been developed to bridge the gap between the large-scale information provided by GCMs and fine spatial scales required for regional and environmental impact studies. Downscaling methods to assess the effect of large-scale circulations on local parameters have. Statistical downscaling methods are based on the view that regional climate can be conditioned by two factors: large-scale climatic state and regional/local features. Local climate information is derived by first developing a statistical model which relates large-scale variables or "predictors" for which GCMs are trustable to regional or local surface "predictands" for which models are less skilful. The main advantage of these methods is that they are computationally inexpensive, and can be applied to outputs from different GCM experiments. Three statistical downscaling methods are applied: Analogue method, Delta Change and Direct Forcing. These methods have been used to determine daily precipitation projections at rain gauge location to study the intensity, frequency and variability of storms in a context of climate change in the Llobregat River Basin in Catalonia, Spain. This work is part of the European project "Water Change" (included in the LIFE + Environment Policy and Governance program). It deals with Medium and long term water resources modelling as a tool for planning and global change adaptation. Two stakeholders involved in the project provided the historical time series: Catalan Water Agency (ACA) and the State Meteorological Agency (AEMET).
Challenges and Opportunities for Integrating Social Science Perspectives into Climate and Global Change Assessments

NASA Astrophysics Data System (ADS)

Larson, E. K.; Li, J.; Zycherman, A.

2017-12-01

Integration of social science into climate and global change assessments is fundamental for improving understanding of the drivers, impacts and vulnerability of climate change, and the social, cultural and behavioral challenges related to climate change responses. This requires disciplinary and interdisciplinary knowledge as well as integrational and translational tools for linking this knowledge with the natural and physical sciences. The USGCRP's Social Science Coordinating Committee (SSCC) is tasked with this challenge and is working to integrate relevant social, economic and behavioral knowledge into processes like sustained assessments. This presentation will discuss outcomes from a recent SSCC workshop, "Social Science Perspectives on Climate Change" and their applications to sustained assessments. The workshop brought academic social scientists from four disciplines - anthropology, sociology, geography and archaeology - together with federal scientists and program managers to discuss three major research areas relevant to the USGCRP and climate assessments: (1) innovative tools, methods, and analyses to clarify the interactions of human and natural systems under climate change, (2) understanding of factors contributing to differences in social vulnerability between and within communities under climate change, and (3) social science perspectives on drivers of global climate change. These disciplines, collectively, emphasize the need to consider socio-cultural, political, economic, geographic, and historic factors, and their dynamic interactions, to understand climate change drivers, social vulnerability, and mitigation and adaptation responses. They also highlight the importance of mixed quantitative and qualitative methods to explain impacts, vulnerability, and responses at different time and spatial scales. This presentation will focus on major contributions of the social sciences to climate and global change research. We will discuss future directions for sustained assessments that integrate and reflect the social science understanding of the complex relationships between social and natural worlds in a changing climate, and factors that impact effective mitigation and adaptation strategies that address risks and vulnerabilities of climate change.
Climate change

USGS Publications Warehouse

Cronin, Thomas M.

2016-01-01

Climate change (including climate variability) refers to regional or global changes in mean climate state or in patterns of climate variability over decades to millions of years often identified using statistical methods and sometimes referred to as changes in long-term weather conditions (IPCC, 2012). Climate is influenced by changes in continent-ocean configurations due to plate tectonic processes, variations in Earth’s orbit, axial tilt and precession, atmospheric greenhouse gas (GHG) concentrations, solar variability, volcanism, internal variability resulting from interactions between the atmosphere, oceans and ice (glaciers, small ice caps, ice sheets, and sea ice), and anthropogenic activities such as greenhouse gas emissions and land use and their effects on carbon cycling.
Quantitative analysis of the effect of climate change and human activities on runoff in the Liujiang River Basin

NASA Astrophysics Data System (ADS)

LI, X.

2017-12-01

Abstract: As human basic and strategic natural resources, Water resources have received an unprecedented challenge under the impacts of global climate change. Analyzing the variation characteristics of runoff and the effect of climate change and human activities on runoff could provide the basis for the reasonable utilization and management of water resources. Taking the Liujiang River Basin as the research object, the discharge data of hydrological station and meteorological data at 24 meteorological stations in the Guangxi Province as the basis, the variation characteristics of runoff and precipitation in the Liujiang River Basin was analyzed, and the quantitatively effect of climate change and human activities on runoff was proposed. The results showed that runoff and precipitation in the Liujiang River Basin had an increasing trend from 1964 to 2006. Using the method of accumulative anomaly and the orderly cluster method, the runoff series was divided into base period and change period. BP - ANN model and sensitivity coefficient method were used for quantifying the influences of climate change and human activities on runoff. We found that the most important factor which caused an increase trend of discharges in the Liujiang River Basin was precipitation. Human activities were also important factors which influenced the intra-annual distribution of runoff. Precipitation had a more sensitive influence to runoff variation than potential evaporation in the Liujiang River Basin. Key words: Liujiang River Basin, climate change, human activities, BP-ANN, sensitivity coefficient method
Plastic and evolutionary responses to climate change in fish

PubMed Central

Crozier, Lisa G; Hutchings, Jeffrey A

2014-01-01

The physical and ecological ‘fingerprints’ of anthropogenic climate change over the past century are now well documented in many environments and taxa. We reviewed the evidence for phenotypic responses to recent climate change in fish. Changes in the timing of migration and reproduction, age at maturity, age at juvenile migration, growth, survival and fecundity were associated primarily with changes in temperature. Although these traits can evolve rapidly, only two studies attributed phenotypic changes formally to evolutionary mechanisms. The correlation-based methods most frequently employed point largely to ‘fine-grained’ population responses to environmental variability (i.e. rapid phenotypic changes relative to generation time), consistent with plastic mechanisms. Ultimately, many species will likely adapt to long-term warming trends overlaid on natural climate oscillations. Considering the strong plasticity in all traits studied, we recommend development and expanded use of methods capable of detecting evolutionary change, such as the long term study of selection coefficients and temporal shifts in reaction norms, and increased attention to forecasting adaptive change in response to the synergistic interactions of the multiple selection pressures likely to be associated with climate change. PMID:24454549

Plastic and evolutionary responses to climate change in fish.

PubMed

Crozier, Lisa G; Hutchings, Jeffrey A

2014-01-01

The physical and ecological 'fingerprints' of anthropogenic climate change over the past century are now well documented in many environments and taxa. We reviewed the evidence for phenotypic responses to recent climate change in fish. Changes in the timing of migration and reproduction, age at maturity, age at juvenile migration, growth, survival and fecundity were associated primarily with changes in temperature. Although these traits can evolve rapidly, only two studies attributed phenotypic changes formally to evolutionary mechanisms. The correlation-based methods most frequently employed point largely to 'fine-grained' population responses to environmental variability (i.e. rapid phenotypic changes relative to generation time), consistent with plastic mechanisms. Ultimately, many species will likely adapt to long-term warming trends overlaid on natural climate oscillations. Considering the strong plasticity in all traits studied, we recommend development and expanded use of methods capable of detecting evolutionary change, such as the long term study of selection coefficients and temporal shifts in reaction norms, and increased attention to forecasting adaptive change in response to the synergistic interactions of the multiple selection pressures likely to be associated with climate change.
Assessment of bias correction under transient climate change

NASA Astrophysics Data System (ADS)

Van Schaeybroeck, Bert; Vannitsem, Stéphane

2015-04-01

Calibration of climate simulations is necessary since large systematic discrepancies are generally found between the model climate and the observed climate. Recent studies have cast doubt upon the common assumption of the bias being stationary when the climate changes. This led to the development of new methods, mostly based on linear sensitivity of the biases as a function of time or forcing (Kharin et al. 2012). However, recent studies uncovered more fundamental problems using both low-order systems (Vannitsem 2011) and climate models, showing that the biases may display complicated non-linear variations under climate change. This last analysis focused on biases derived from the equilibrium climate sensitivity, thereby ignoring the effect of the transient climate sensitivity. Based on the linear response theory, a general method of bias correction is therefore proposed that can be applied on any climate forcing scenario. The validity of the method is addressed using twin experiments with a climate model of intermediate complexity LOVECLIM (Goosse et al., 2010). We evaluate to what extent the bias change is sensitive to the structure (frequency) of the applied forcing (here greenhouse gases) and whether the linear response theory is valid for global and/or local variables. To answer these question we perform large-ensemble simulations using different 300-year scenarios of forced carbon-dioxide concentrations. Reality and simulations are assumed to differ by a model error emulated as a parametric error in the wind drag or in the radiative scheme. References [1] H. Goosse et al., 2010: Description of the Earth system model of intermediate complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603-633. [2] S. Vannitsem, 2011: Bias correction and post-processing under climate change, Nonlin. Processes Geophys., 18, 911-924. [3] V.V. Kharin, G. J. Boer, W. J. Merryfield, J. F. Scinocca, and W.-S. Lee, 2012: Statistical adjustment of decadal predictions in a changing climate, Geophys. Res. Lett., 39, L19705.
Patterns and biases in climate change research on amphibians and reptiles: a systematic review.

PubMed

Winter, Maiken; Fiedler, Wolfgang; Hochachka, Wesley M; Koehncke, Arnulf; Meiri, Shai; De la Riva, Ignacio

2016-09-01

Climate change probably has severe impacts on animal populations, but demonstrating a causal link can be difficult because of potential influences by additional factors. Assessing global impacts of climate change effects may also be hampered by narrow taxonomic and geographical research foci. We review studies on the effects of climate change on populations of amphibians and reptiles to assess climate change effects and potential biases associated with the body of work that has been conducted within the last decade. We use data from 104 studies regarding the effect of climate on 313 species, from 464 species-study combinations. Climate change effects were reported in 65% of studies. Climate change was identified as causing population declines or range restrictions in half of the cases. The probability of identifying an effect of climate change varied among regions, taxa and research methods. Climatic effects were equally prevalent in studies exclusively investigating climate factors (more than 50% of studies) and in studies including additional factors, thus bolstering confidence in the results of studies exclusively examining effects of climate change. Our analyses reveal biases with respect to geography, taxonomy and research question, making global conclusions impossible. Additional research should focus on under-represented regions, taxa and questions. Conservation and climate policy should consider the documented harm climate change causes reptiles and amphibians.
Climate change and human health: what are the research trends? A scoping review protocol

PubMed Central

Herlihy, Niamh; Bar-Hen, Avner; Verner, Glenn; Fischer, Helen; Sauerborn, Rainer; Depoux, Anneliese; Flahault, Antoine; Schütte, Stefanie

2016-01-01

Introduction For 28 years, the Intergovernmental Panel on Climate Change (IPCC) has been assessing the potential risks associated with anthropogenic climate change. Although interest in climate change and health is growing, the implications arising from their interaction remain understudied. Generating a greater understanding of the health impacts of climate change could be key step in inciting some of the changes necessary to decelerate global warming. A long-term and broad overview of the existing scientific literature in the field of climate change and health is currently missing in order to ensure that all priority areas are being adequately addressed. In this paper we outline our methods to conduct a scoping review of the published peer-reviewed literature on climate change and health between 1990 and 2015. Methods and analysis A detailed search strategy will be used to search the PubMed and Web of Science databases. Specific inclusion and exclusion criteria will be applied in order to capture the most relevant literature in the time frame chosen. Data will be extracted, categorised and coded to allow for statistical analysis of the results. Ethics and dissemination No ethical approval was required for this study. A searchable database of climate change and health publications will be developed and a manuscript will be complied for publication and dissemination of the findings. We anticipate that this study will allow us to map the trends observed in publications over the 25-year time period in climate change and health research. It will also identify the research areas with the highest volume of publications as well as highlight the research trends in climate change and health. PMID:28011805
Assessing the response of runoff to climate change and human activities for a typical basin in the Northern Taihang Mountain, China

NASA Astrophysics Data System (ADS)

Wang, Jinfeng; Gao, Yanchuan; Wang, Sheng

2018-04-01

Climate change and human activities are the two main factors on runoff change. Quantifying the contribution of climate change and human activities on runoff change is important for water resources planning and management. In this study, the variation trend and abrupt change point of hydro-meteorological factors during 1960-2012 were detected by using the Mann-Kendall test and Pettitt change-point statistics. Then the runoff was simulated by SWAT model. The contribution of climate change and human activities on runoff change was calculated based on the SWAT model and the elasticity coefficient method. The results showed that in contrast to the increasing trend for annual temperature, the significant decreasing trends were detected for annual runoff and precipitation, with an abrupt change point in 1982. The simulated results of SWAT had good consistency with observed ones, and the values of R2 and E_{NS} all exceeded 0.75. The two methods used for assessing the contribution of climate change and human activities on runoff reduction yielded consistent results. The contribution of climate change (precipitation reduction and temperature rise) was {˜ }37.5%, while the contribution of human activities (the increase of economic forest and built-up land, hydrologic projects) was {˜ }62.5%.
Managing hardwood-softwood mixtures for future forests in eastern North America: assessing suitability to projected climate change

Treesearch

John M. Kabrick; Kenneth L. Clark; Anthony W. D' Amato; Daniel C. Dey; Laura S. Kenefic; Christel C. Kern; Benjamin O. Knapp; David A. MacLean; Patricia Raymond; Justin D. Waskiewicz

2017-01-01

Despite growing interest in management strategies for climate change adaptation, there are few methods for assessing the ability of stands to endure or adapt to projected future climates. We developed a means for assigning climate "Compatibility" and "Adaptability" scores to stands for assessing the suitability of tree species for projected climate...
Development of incremental dynamical downscaling and analysis system for regional scale climate change projections

NASA Astrophysics Data System (ADS)

Wakazuki, Yasutaka; Hara, Masayuki; Fujita, Mikiko; Ma, Xieyao; Kimura, Fujio

2013-04-01

Regional scale climate change projections play an important role in assessments of influences of global warming and include statistical (SD) and dynamical downscaling (DD) approaches. One of DD methods is developed basing on the pseudo-global-warming (PGW) method developed by Kimura and Kitoh (2007) in this study. In general, DD uses regional climate model (RCM) with lateral boundary data. In PGW method, the climatological mean difference estimated by GCMs are added to the objective analysis data (ANAL), and the data are used as the lateral boundary data in the future climate simulations. The ANAL is also used as the lateral boundary conditions of the present climate simulation. One of merits of the PGW method is that influences of biases of GCMs in RCM simulations are reduced. However, the PGW method does not treat climate changes in relative humidity, year-to-year variation, and short-term disturbances. The developing new downscaling method is named as the incremental dynamical downscaling and analysis system (InDDAS). The InDDAS treat climate changes in relative humidity and year-to-year variations. On the other hand, uncertainties of climate change projections estimated by many GCMs are large and are not negligible. Thus, stochastic regional scale climate change projections are expected for assessments of influences of global warming. Many RCM runs must be performed to make stochastic information. However, the computational costs are huge because grid size of RCM runs should be small to resolve heavy rainfall phenomena. Therefore, the number of runs to make stochastic information must be reduced. In InDDAS, climatological differences added to ANAL become statistically pre-analyzed information. The climatological differences of many GCMs are divided into mean climatological difference (MD) and departures from MD. The departures are analyzed by principal component analysis, and positive and negative perturbations (positive and negative standard deviations multiplied by departure patterns (eigenvectors)) with multi modes are added to MD. Consequently, the most likely future states are calculated with climatological difference of MD. For example, future states in cases that temperature increase is large and small are calculated with MD plus positive and negative perturbations of the first mode.
Climate Benchmark Missions: CLARREO

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A.; Young, David F.

2010-01-01

CLARREO (Climate Absolute Radiance and Refractivity Observatory) is one of the four Tier 1 missions recommended by the recent NRC decadal survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to rigorously observe climate change on decade time scales and to use decadal change observations as the most critical method to determine the accuracy of climate change projections such as those used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). A rigorously known accuracy of both decadal change observations as well as climate projections is critical in order to enable sound policy decisions. The CLARREO mission accomplishes this critical objective through highly accurate and SI traceable decadal change observations sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. The same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. The CLARREO breakthrough in decadal climate change observations is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. These accuracy levels are determined both by the projected decadal changes as well as by the background natural variability that such signals must be detected against. The accuracy for decadal change traceability to SI standards includes uncertainties of calibration, sampling, and analysis methods. Unlike most other missions, all of the CLARREO requirements are judged not by instantaneous accuracy, but instead by accuracy in large time/space scale average decadal changes. Given the focus on decadal climate change, the NRC Decadal Survey concluded that the single most critical issue for decadal change observations was their lack of accuracy and low confidence in observing the small but critical climate change signals. CLARREO is the recommended attack on this challenge, and builds on the last decade of climate observation advances in the Earth Observing System as well as metrological advances at NIST (National Institute of Standards and Technology) and other standards laboratories.
Investigating the Climate Change Beliefs, Knowledge, Behaviors, and Cultural Worldviews of Rural Middle School Students and Their Families during an Out-of-School Intervention: A Mixed-Methods Study

ERIC Educational Resources Information Center

Gutierrez, Kristie Susan

2016-01-01

In a recent nationwide survey, 63% of American adults believe that there is global warming, yet 52% received a "grade" of "F" on climate change knowledge and beliefs. Climate change is a politically-charged topic in the 21st century. Even for those who support the 97% of scientists who assert that climate change is occurring,…
Climate Change Education in Earth System Science

NASA Astrophysics Data System (ADS)

Hänsel, Stephanie; Matschullat, Jörg

2013-04-01

The course "Atmospheric Research - Climate Change" is offered to master Earth System Science students within the specialisation "Climate and Environment" at the Technical University Bergakademie Freiberg. This module takes a comprehensive approach to climate sciences, reaching from the natural sciences background of climate change via the social components of the issue to the statistical analysis of changes in climate parameters. The course aims at qualifying the students to structure the physical and chemical basics of the climate system including relevant feedbacks. The students can evaluate relevant drivers of climate variability and change on various temporal and spatial scales and can transform knowledge from climate history to the present and the future. Special focus is given to the assessment of uncertainties related to climate observations and projections as well as the specific challenges of extreme weather and climate events. At the end of the course the students are able to critically reflect and evaluate climate change related results of scientific studies and related issues in media. The course is divided into two parts - "Climate Change" and "Climate Data Analysis" and encompasses two lectures, one seminar and one exercise. The weekly "Climate change" lecture transmits the physical and chemical background for climate variation and change. (Pre)historical, observed and projected climate changes and their effects on various sectors are being introduced and discussed regarding their implications for society, economics, ecology and politics. The related seminar presents and discusses the multiple reasons for controversy in climate change issues, based on various texts. Students train the presentation of scientific content and the discussion of climate change aspects. The biweekly lecture on "Climate data analysis" introduces the most relevant statistical tools and methods in climate science. Starting with checking data quality via tools of exploratory data analysis the approaches on climate time series, trend analysis and extreme events analysis are explained. Tools to describe relations within the data sets and significance tests further corroborate this. Within the weekly exercises that have to be prepared at home, the students work with self-selected climate data sets and apply the learned methods. The presentation and discussion of intermediate results by the students is as much part of the exercises as the illustration of possible methodological procedures by the teacher using exemplary data sets. The total time expenditure of the course is 270 hours with 90 attendance hours. The remainder consists of individual studies, e.g., preparation of discussions and presentations, statistical data analysis, and scientific writing. Different forms of examination are applied including written or oral examination, scientific report, presentation and portfolio work.
Climate change streamflow scenarios designed for critical period water resources planning studies

NASA Astrophysics Data System (ADS)

Hamlet, A. F.; Snover, A. K.; Lettenmaier, D. P.

2003-04-01

Long-range water planning in the United States is usually conducted by individual water management agencies using a critical period planning exercise based on a particular period of the observed streamflow record and a suite of internally-developed simulation tools representing the water system. In the context of planning for climate change, such an approach is flawed in that it assumes that the future climate will be like the historic record. Although more sophisticated planning methods will probably be required as time goes on, a short term strategy for incorporating climate uncertainty into long-range water planning as soon as possible is to create alternate inputs to existing planning methods that account for climate uncertainty as it affects both supply and demand. We describe a straight-forward technique for constructing streamflow scenarios based on the historic record that include the broad-based effects of changed regional climate simulated by several global climate models (GCMs). The streamflow scenarios are based on hydrologic simulations driven by historic climate data perturbed according to regional climate signals from four GCMs using the simple "delta" method. Further data processing then removes systematic hydrologic model bias using a quantile-based bias correction scheme, and lastly, the effects of random errors in the raw hydrologic simulations are removed. These techniques produce streamflow scenarios that are consistent in time and space with the historic streamflow record while incorporating fundamental changes in temperature and precipitation from the GCM scenarios. Planning model simulations based on these climate change streamflow scenarios can therefore be compared directly to planning model simulations based on the historic record of streamflows to help planners understand the potential impacts of climate uncertainty. The methods are currently being tested and refined in two large-scale planning exercises currently being conducted in the Pacific Northwest (PNW) region of the US, and the resulting streamflow scenarios will be made freely available on the internet for a large number of sites in the PNW to help defray the costs of including climate change information in other studies.
Climate Change in the Preservice Teacher's Mind

ERIC Educational Resources Information Center

Lambert, Julie L.; Bleicher, Robert E.

2013-01-01

Given the recent media attention on the public's shift in opinion toward being more skeptical about climate change, 154 preservice teachers' participated in an intervention in an elementary science methods course. Findings indicated that students developed a deeper level of concern about climate change. Their perceptions on the evidence…
A climate-change scenario for the Columbia River Basin.

Treesearch

Sue A. Ferguson

1997-01-01

This work describes the method used to generate a climate-change scenario for the Columbia River basin. The scenario considers climate patterns that may change if the atmospheric concentration of carbon dioxide (C02), or its greenhouse gas equivalent, were to double over pre-Industrial Revolution values. Given the current rate of increase in...
The importance of assessing climate change vulnerability to address species conservation

Treesearch

Karen E. Bagne; Megan M. Friggens; Sharon J. Coe; Deborah M. Finch

2014-01-01

Species conservation often prioritizes attention on a small subset of "special status" species at high risk of extinction, but actions based on current lists of special status species may not effectively moderate biodiversity loss if climate change alters threats. Assessments of climate change vulnerability may provide a method to enhance identification of...
Data driven approaches vs. qualitative approaches in climate change impact and vulnerability assessment.

NASA Astrophysics Data System (ADS)

Zebisch, Marc; Schneiderbauer, Stefan; Petitta, Marcello

2015-04-01

In the last decade the scope of climate change science has broadened significantly. 15 years ago the focus was mainly on understanding climate change, providing climate change scenarios and giving ideas about potential climate change impacts. Today, adaptation to climate change has become an increasingly important field of politics and one role of science is to inform and consult this process. Therefore, climate change science is not anymore focusing on data driven approaches only (such as climate or climate impact models) but is progressively applying and relying on qualitative approaches including opinion and expertise acquired through interactive processes with local stakeholders and decision maker. Furthermore, climate change science is facing the challenge of normative questions, such us 'how important is a decrease of yield in a developed country where agriculture only represents 3% of the GDP and the supply with agricultural products is strongly linked to global markets and less depending on local production?'. In this talk we will present examples from various applied research and consultancy projects on climate change vulnerabilities including data driven methods (e.g. remote sensing and modelling) to semi-quantitative and qualitative assessment approaches. Furthermore, we will discuss bottlenecks, pitfalls and opportunities in transferring climate change science to policy and decision maker oriented climate services.
Climate and Management Controls on Forest Growth and Forest Carbon Balance in the Western United States

NASA Astrophysics Data System (ADS)

Kelsey, Katharine Cashman

Climate change is resulting in a number of rapid changes in forests worldwide. Forests comprise a critical component of the global carbon cycle, and therefore climate-induced changes in forest carbon balance have the potential to create a feedback within the global carbon cycle and affect future trajectories of climate change. In order to further understanding of climate-driven changes in forest carbon balance, I (1) develop a method to improve spatial estimates forest carbon stocks, (2) investigate the effect of climate change and forest management actions on forest recovery and carbon balance following disturbance, and (3) explore the relationship between climate and forest growth, and identify climate-driven trends in forest growth through time, within San Juan National Forest in southwest Colorado, USA. I find that forest carbon estimates based on texture analysis from LandsatTM imagery improve regional forest carbon maps, and this method is particularly useful for estimating carbon stocks in forested regions affected by disturbance. Forest recovery from disturbance is also a critical component of future forest carbon stocks, and my results indicate that both climate and forest management actions have important implications for forest recovery and carbon dynamics following disturbance. Specifically, forest treatments that use woody biomass removed from the forest for electricity production can reduce carbon emissions to the atmosphere, but climate driven changes in fire severity and forest recovery can have the opposite effect on forest carbon stocks. In addition to the effects of disturbance and recovery on forest condition, I also find that climate change is decreasing rates of forest growth in some species, likely in response to warming summer temperatures. These growth declines could result in changes of vegetation composition, or in extreme cases, a shift in vegetation type that would alter forest carbon storage. This work provides insight into both current and future changes in forest carbon balance as a consequence of climate change and forest management in the western US.
Creating Effective Dialogue Around Climate Change

NASA Astrophysics Data System (ADS)

Kiehl, J. T.

2015-12-01

Communicating climate change to people from diverse sectors of society has proven to be difficult in the United States. It is widely recognized that difficulties arise from a number of sources, including: basic science understanding, the psychologically affect laden content surrounding climate change, and the diversity of value systems that exist in our society. I explore ways of working with the affect that arises around climate change and describe specific methods to work with the resistance often encountered when communicating this important issue. The techniques I describe are rooted in psychology and group process and provide means for creating more effective narratives to break through the barriers to communicating climate change science. Examples are given from personal experiences in presenting climate change to diverse groups.
Tree growth and climate in the Pacific Northwest, North America: a broad-scale analysis of changing growth environments

Treesearch

Whitney L. Albright; David L. Peterson

2013-01-01

Climate change in the 21st century will affect tree growth in the Pacific Northwest region of North America, although complex climateâgrowth relationships make it difficult to identify how radial growth will respond across different species distributions. We used a novel method to examine potential growth responses to climate change at a broad geographical scale with a...
Climate change and vector-borne diseases of public health significance.

PubMed

Ogden, Nicholas H

2017-10-16

There has been much debate as to whether or not climate change will have, or has had, any significant effect on risk from vector-borne diseases. The debate on the former has focused on the degree to which occurrence and levels of risk of vector-borne diseases are determined by climate-dependent or independent factors, while the debate on the latter has focused on whether changes in disease incidence are due to climate at all, and/or are attributable to recent climate change. Here I review possible effects of climate change on vector-borne diseases, methods used to predict these effects and the evidence to date of changes in vector-borne disease risks that can be attributed to recent climate change. Predictions have both over- and underestimated the effects of climate change. Mostly under-estimations of effects are due to a focus only on direct effects of climate on disease ecology while more distal effects on society's capacity to control and prevent vector-borne disease are ignored. There is increasing evidence for possible impacts of recent climate change on some vector-borne diseases but for the most part, observed data series are too short (or non-existent), and impacts of climate-independent factors too great, to confidently attribute changing risk to climate change. © Crown copyright 2017.
VALUE - A Framework to Validate Downscaling Approaches for Climate Change Studies

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Gutiérrez, José M.; Kotlarski, Sven; Chandler, Richard E.; Hertig, Elke; Wibig, Joanna; Huth, Radan; Wilke, Renate A. I.

2015-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. VALUE aims to foster collaboration and knowledge exchange between climatologists, impact modellers, statisticians, and stakeholders to establish an interdisciplinary downscaling community. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. Here, we present the key ingredients of this framework. VALUE's main approach to validation is user-focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur: what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Do methods fail in representing regional climate change? How is the overall representation of regional climate, including errors inherited from global climate models? The framework will be the basis for a comprehensive community-open downscaling intercomparison study, but is intended also to provide general guidance for other validation studies.

VALUE: A framework to validate downscaling approaches for climate change studies

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Gutiérrez, José M.; Kotlarski, Sven; Chandler, Richard E.; Hertig, Elke; Wibig, Joanna; Huth, Radan; Wilcke, Renate A. I.

2015-01-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. VALUE aims to foster collaboration and knowledge exchange between climatologists, impact modellers, statisticians, and stakeholders to establish an interdisciplinary downscaling community. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. In this paper, we present the key ingredients of this framework. VALUE's main approach to validation is user- focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur: what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Do methods fail in representing regional climate change? How is the overall representation of regional climate, including errors inherited from global climate models? The framework will be the basis for a comprehensive community-open downscaling intercomparison study, but is intended also to provide general guidance for other validation studies.
Development of hi-resolution regional climate scenarios in Japan by statistical downscaling

NASA Astrophysics Data System (ADS)

Dairaku, K.

2016-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. To meet with the needs of stakeholders such as local governments, a Japan national project, Social Implementation Program on Climate Change Adaptation Technology (SI-CAT), launched in December 2015. It develops reliable technologies for near-term climate change predictions. Multi-model ensemble regional climate scenarios with 1km horizontal grid-spacing over Japan are developed by using CMIP5 GCMs and a statistical downscaling method to support various municipal adaptation measures appropriate for possible regional climate changes. A statistical downscaling method, Bias Correction Spatial Disaggregation (BCSD), is employed to develop regional climate scenarios based on CMIP5 RCP8.5 five GCMs (MIROC5, MRI-CGCM3, GFDL-CM3, CSIRO-Mk3-6-0, HadGEM2-ES) for the periods of historical climate (1970-2005) and near future climate (2020-2055). Downscaled variables are monthly/daily precipitation and temperature. File format is NetCDF4 (conforming to CF1.6, HDF5 compression). Developed regional climate scenarios will be expanded to meet with needs of stakeholders and interface applications to access and download the data are under developing. Statistical downscaling method is not necessary to well represent locally forced nonlinear phenomena, extreme events such as heavy rain, heavy snow, etc. To complement the statistical method, dynamical downscaling approach is also combined and applied to some specific regions which have needs of stakeholders. The added values of statistical/dynamical downscaling methods compared with parent GCMs are investigated.
Understanding the impacts of climate change and human activities on streamflow: a case study of the Soan River basin, Pakistan

NASA Astrophysics Data System (ADS)

Shahid, Muhammad; Cong, Zhentao; Zhang, Danwu

2017-09-01

Climate change and land use change are the two main factors that can alter the catchment hydrological process. The objective of this study is to evaluate the relative contribution of climate change and land use change to runoff change of the Soan River basin. The Mann-Kendal and the Pettit tests are used to find out the trends and change point in hydroclimatic variables during the period 1983-2012. Two different approaches including the abcd hydrological model and the Budyko framework are then used to quantify the impact of climate change and land use change on streamflow. The results from both methods are consistent and show that annual runoff has significantly decreased with a change point around 1997. The decrease in precipitation and increases in potential evapotranspiration contribute 68% of the detected change while the rest of the detected change is due to land use change. The land use change acquired from Landsat shows that during post-change period, the agriculture has increased in the Soan basin, which is in line with the positive contribution of land use change to runoff decrease. This study concludes that aforementioned methods performed well in quantifying the relative contribution of land use change and climate change to runoff change.
Economic Evidence on the Health Impacts of Climate Change in Europe

PubMed Central

Hutton, Guy; Menne, Bettina

2014-01-01

BACKGROUND In responding to the health impacts of climate change, economic evidence and tools inform decision makers of the efficiency of alternative health policies and interventions. In a time when sweeping budget cuts are affecting all tiers of government, economic evidence on health protection from climate change spending enables comparison with other public spending. METHODS The review included 53 countries of the World Health Organization (WHO) European Region. Literature was obtained using a Medline and Internet search of key terms in published reports and peer-reviewed literature, and from institutions working on health and climate change. Articles were included if they provided economic estimation of the health impacts of climate change or adaptation measures to protect health from climate change in the WHO European Region. Economic studies are classified under health impact cost, health adaptation cost, and health economic evaluation (comparing both costs and impacts). RESULTS A total of 40 relevant studies from Europe were identified, covering the health damage or adaptation costs related to the health effects of climate change and response measures to climate-sensitive diseases. No economic evaluation studies were identified of response measures specific to the impacts of climate change. Existing studies vary in terms of the economic outcomes measured and the methods for evaluation of health benefits. The lack of robust health impact data underlying economic studies significantly affects the availability and precision of economic studies. CONCLUSIONS Economic evidence in European countries on the costs of and response to climate-sensitive diseases is extremely limited and fragmented. Further studies are urgently needed that examine health impacts and the costs and efficiency of alternative responses to climate-sensitive health conditions, in particular extreme weather events (other than heat) and potential emerging diseases and other conditions threatening Europe. PMID:25452694
Probabilistic projections of 21st century climate change over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, E.; Sokolov, A. P.; Schlosser, C. A.; Scott, J. R.; Gao, X.

2013-12-01

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an earth system model of intermediate complexity, with a two-dimensional zonal-mean atmosphere, to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three dimensional atmospheric model; and a statistical downscaling, where a pattern scaling algorithm uses climate-change patterns from 17 climate models. This framework allows for key sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections; climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate); natural variability; and structural uncertainty. Results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also nd that dierent initial conditions lead to dierences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider all sources of uncertainty when modeling climate impacts over Northern Eurasia.
Probabilistic projections of 21st century climate change over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, Erwan; Sokolov, Andrei; Schlosser, Adam; Scott, Jeffery; Gao, Xiang

2013-12-01

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional zonal-mean atmosphere to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three-dimensional atmospheric model, and a statistical downscaling, where a pattern scaling algorithm uses climate change patterns from 17 climate models. This framework allows for four major sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections, climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate), natural variability, and structural uncertainty. The results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also find that different initial conditions lead to differences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider these sources of uncertainty when modeling climate impacts over Northern Eurasia.
Uncertainties Associated with Quantifying Climate Change Impacts on Human Health: A Case Study for Diarrhea

PubMed Central

Kolstad, Erik W.; Johansson, Kjell Arne

2011-01-01

Background Climate change is expected to have large impacts on health at low latitudes where droughts and malnutrition, diarrhea, and malaria are projected to increase. Objectives The main objective of this study was to indicate a method to assess a range of plausible health impacts of climate change while handling uncertainties in a unambiguous manner. We illustrate this method by quantifying the impacts of projected regional warming on diarrhea in this century. Methods We combined a range of linear regression coefficients to compute projections of future climate change-induced increases in diarrhea using the results from five empirical studies and a 19-member climate model ensemble for which future greenhouse gas emissions were prescribed. Six geographical regions were analyzed. Results The model ensemble projected temperature increases of up to 4°C over land in the tropics and subtropics by the end of this century. The associated mean projected increases of relative risk of diarrhea in the six study regions were 8–11% (with SDs of 3–5%) by 2010–2039 and 22–29% (SDs of 9–12%) by 2070–2099. Conclusions Even our most conservative estimates indicate substantial impacts from climate change on the incidence of diarrhea. Nevertheless, our main conclusion is that large uncertainties are associated with future projections of diarrhea and climate change. We believe that these uncertainties can be attributed primarily to the sparsity of empirical climate–health data. Our results therefore highlight the need for empirical data in the cross section between climate and human health. PMID:20929684
A data centred method to estimate and map changes in the full distribution of daily surface temperature

NASA Astrophysics Data System (ADS)

Chapman, Sandra; Stainforth, David; Watkins, Nicholas

2016-04-01

Characterizing how our climate is changing includes local information which can inform adaptation planning decisions. This requires quantifying the geographical patterns in changes at specific quantiles or thresholds in distributions of variables such as daily surface temperature. Here we focus on these local changes and on a model independent method to transform daily observations into patterns of local climate change. Our method [1] is a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of how fast different quantiles of the distributions are changing. This involves both determining which quantiles and geographical locations show the greatest change but also, those at which any change is highly uncertain. For temperature, changes in the distribution itself can yield robust results [2]. We demonstrate how the fundamental timescales of anthropogenic climate change limit the identification of societally relevant aspects of changes. We show that it is nevertheless possible to extract, solely from observations, some confident quantified assessments of change at certain thresholds and locations [3]. We demonstrate this approach using E-OBS gridded data [4] timeseries of local daily surface temperature from specific locations across Europe over the last 60 years. [1] Chapman, S. C., D. A. Stainforth, N. W. Watkins, On estimating long term local climate trends, Phil. Trans. Royal Soc., A,371 20120287 (2013) [2] Stainforth, D. A. S. C. Chapman, N. W. Watkins, Mapping climate change in European temperature distributions, ERL 8, 034031 (2013) [3] Chapman, S. C., Stainforth, D. A., Watkins, N. W. Limits to the quantification of local climate change, ERL 10, 094018 (2015) [4] Haylock M. R. et al ., A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119, (2008)
Full annual cycle climate change vulnerability assessment for migratory birds

USGS Publications Warehouse

Culp, Leah A.; Cohen, Emily B.; Scarpignato, Amy L.; Thogmartin, Wayne E.; Marra, Peter P.

2017-01-01

Climate change is a serious challenge faced by all plant and animal species. Climate change vulnerability assessments (CCVAs) are one method to assess risk and are increasingly used as a tool to inform management plans. Migratory animals move across regions and continents during their annual cycles where they are exposed to diverse climatic conditions. Climate change during any period and in any region of the annual cycle could influence survival, reproduction, or the cues used to optimize timing of migration. Therefore, CCVAs for migratory animals best estimate risk when they include climate exposure during the entire annual cycle. We developed a CCVA incorporating the full annual cycle and applied this method to 46 species of migratory birds breeding in the Upper Midwest and Great Lakes (UMGL) region of the United States. Our methodology included background risk, climate change exposure × climate sensitivity, adaptive capacity to climate change, and indirect effects of climate change. We compiled information about migratory connectivity between breeding and stationary non-breeding areas using literature searches and U.S. Geological Survey banding and re-encounter data. Climate change exposure (temperature and moisture) was assessed using UMGL breeding season climate and winter climate from non-breeding regions for each species. Where possible, we focused on non-breeding regions known to be linked through migratory connectivity. We ranked 10 species as highly vulnerable to climate change and two as having low vulnerability. The remaining 34 species were ranked as moderately vulnerable. In general, including non-breeding data provided more robust results that were highly individualistic by species. Two species were found to be highly vulnerable throughout their annual cycle. Projected drying will have the greatest effect during the non-breeding season for species overwintering in Mexico and the Caribbean. Projected temperature increases will have the greatest effect during the breeding season in UMGL as well as during the non-breeding season for species overwintering in South America. We provide a model for adaptive management of migratory animals in the face of projected climate change, including identification of priority species, research needs, and regions within non-breeding ranges for potential conservation partnerships.
Climate change effects on extreme flows of water supply area in Istanbul: utility of regional climate models and downscaling method.

PubMed

Kara, Fatih; Yucel, Ismail

2015-09-01

This study investigates the climate change impact on the changes of mean and extreme flows under current and future climate conditions in the Omerli Basin of Istanbul, Turkey. The 15 regional climate model output from the EU-ENSEMBLES project and a downscaling method based on local implications from geophysical variables were used for the comparative analyses. Automated calibration algorithm is used to optimize the parameters of Hydrologiska Byråns Vattenbalansavdel-ning (HBV) model for the study catchment using observed daily temperature and precipitation. The calibrated HBV model was implemented to simulate daily flows using precipitation and temperature data from climate models with and without downscaling method for reference (1960-1990) and scenario (2071-2100) periods. Flood indices were derived from daily flows, and their changes throughout the four seasons and year were evaluated by comparing their values derived from simulations corresponding to the current and future climate. All climate models strongly underestimate precipitation while downscaling improves their underestimation feature particularly for extreme events. Depending on precipitation input from climate models with and without downscaling the HBV also significantly underestimates daily mean and extreme flows through all seasons. However, this underestimation feature is importantly improved for all seasons especially for spring and winter through the use of downscaled inputs. Changes in extreme flows from reference to future increased for the winter and spring and decreased for the fall and summer seasons. These changes were more significant with downscaling inputs. With respect to current time, higher flow magnitudes for given return periods will be experienced in the future and hence, in the planning of the Omerli reservoir, the effective storage and water use should be sustained.
Patterns and biases in climate change research on amphibians and reptiles: a systematic review

PubMed Central

2016-01-01

Climate change probably has severe impacts on animal populations, but demonstrating a causal link can be difficult because of potential influences by additional factors. Assessing global impacts of climate change effects may also be hampered by narrow taxonomic and geographical research foci. We review studies on the effects of climate change on populations of amphibians and reptiles to assess climate change effects and potential biases associated with the body of work that has been conducted within the last decade. We use data from 104 studies regarding the effect of climate on 313 species, from 464 species–study combinations. Climate change effects were reported in 65% of studies. Climate change was identified as causing population declines or range restrictions in half of the cases. The probability of identifying an effect of climate change varied among regions, taxa and research methods. Climatic effects were equally prevalent in studies exclusively investigating climate factors (more than 50% of studies) and in studies including additional factors, thus bolstering confidence in the results of studies exclusively examining effects of climate change. Our analyses reveal biases with respect to geography, taxonomy and research question, making global conclusions impossible. Additional research should focus on under-represented regions, taxa and questions. Conservation and climate policy should consider the documented harm climate change causes reptiles and amphibians. PMID:27703684
The effects of climate downscaling technique and observational data set on modeled ecological responses.

PubMed

Pourmokhtarian, Afshin; Driscoll, Charles T; Campbell, John L; Hayhoe, Katharine; Stoner, Anne M K

2016-07-01

Assessments of future climate change impacts on ecosystems typically rely on multiple climate model projections, but often utilize only one downscaling approach trained on one set of observations. Here, we explore the extent to which modeled biogeochemical responses to changing climate are affected by the selection of the climate downscaling method and training observations used at the montane landscape of the Hubbard Brook Experimental Forest, New Hampshire, USA. We evaluated three downscaling methods: the delta method (or the change factor method), monthly quantile mapping (Bias Correction-Spatial Disaggregation, or BCSD), and daily quantile regression (Asynchronous Regional Regression Model, or ARRM). Additionally, we trained outputs from four atmosphere-ocean general circulation models (AOGCMs) (CCSM3, HadCM3, PCM, and GFDL-CM2.1) driven by higher (A1fi) and lower (B1) future emissions scenarios on two sets of observations (1/8º resolution grid vs. individual weather station) to generate the high-resolution climate input for the forest biogeochemical model PnET-BGC (eight ensembles of six runs).The choice of downscaling approach and spatial resolution of the observations used to train the downscaling model impacted modeled soil moisture and streamflow, which in turn affected forest growth, net N mineralization, net soil nitrification, and stream chemistry. All three downscaling methods were highly sensitive to the observations used, resulting in projections that were significantly different between station-based and grid-based observations. The choice of downscaling method also slightly affected the results, however not as much as the choice of observations. Using spatially smoothed gridded observations and/or methods that do not resolve sub-monthly shifts in the distribution of temperature and/or precipitation can produce biased results in model applications run at greater temporal and/or spatial resolutions. These results underscore the importance of carefully considering field observations used for training, as well as the downscaling method used to generate climate change projections, for smaller-scale modeling studies. Different sources of variability including selection of AOGCM, emissions scenario, downscaling technique, and data used for training downscaling models, result in a wide range of projected forest ecosystem responses to future climate change. © 2016 by the Ecological Society of America.
Teaching Climate Change Science in Senior Secondary School: Issues, Barriers and Opportunities

ERIC Educational Resources Information Center

Bunten, Rod; Dawson, Vaille

2014-01-01

This paper argues that, despite its difficulties, climate change can (and perhaps needs to) be taught rigorously to students by enquiry rather than through transmission and that such a method will enable students to make judgments on other issues of scientific controversy. It examines the issues and barriers to the teaching of climate change,…
Review and recommendations for climate change vulnerability assessment approaches with examples from the Southwest

Treesearch

M. Friggens; K. Bagne; D. Finch; D. Falk; J. Triepke; A. Lynch

2013-01-01

Climate change creates new challenges for resource managers and decision-makers with broad and often complex effects that make it difficult to accurately predict and design management actions to minimize undesirable impacts. We review pertinent information regarding methods and approaches used to conduct climate change vulnerability assessments to reveal assumptions...
Re-Examining the Relationship between Tillage Regime and Global Climate Change

ERIC Educational Resources Information Center

Hammons, Sarah K.

2009-01-01

It is known that anthropogenic greenhouse gas emissions are a major contributor to global climate change and that reducing our emissions will stem its acceleration (Baker et al., 2007). Aside from emission reductions, another method for stemming global climate change is to reduce the levels of greenhouse gases already in the atmosphere by storing…
Pacific Islands Regional Climate Assessment: Building a Framework to Track Physical and Social Indicators of Climate Change Across Pacific Islands

NASA Astrophysics Data System (ADS)

Grecni, Z. N.; Keener, V. W.

2016-12-01

Assessments inform regional and local climate change governance and provide the critical scientific basis for U.S. climate policy. Despite the centrality of scientific information to public discourse and decision making, comprehensive assessments of climate change drivers, impacts, and the vulnerability of human and ecological systems at regional or local scales are often conducted on an ad hoc basis. Methods for sustained assessment and communication of scientific information are diverse and nascent. The Pacific Islands Regional Climate Assessment (PIRCA) is a collaborative effort to assess climate change indicators, impacts, and adaptive capacity of the Hawaiian archipelago and the US-Affiliated Pacific Islands (USAPI). In 2012, PIRCA released the first comprehensive report summarizing the state of scientific knowledge about climate change in the region as a technical input to the U.S. National Climate Assessment. A multi-method evaluation of PIRCA outputs and delivery revealed that the vast majority of key stakeholders view the report as extremely credible and use it as a resource. The current study will present PIRCA's approach to establishing physical and social indicators to track on an ongoing basis, starting with the Republic of the Marshall Islands as an initial location of focus for providing a cross-sectoral indicators framework. Identifying and tracking useful indicators is aimed at sustaining the process of knowledge coproduction with decision makers who seek to better understand the climate variability and change and its impacts on Pacific Island communities.
Effect of historical land-use and climate change on tree-climate relationships in the upper Midwestern United States.

PubMed

Goring, Simon J; Williams, John W

2017-04-01

Contemporary forest inventory data are widely used to understand environmental controls on tree species distributions and to construct models to project forest responses to climate change, but the stability and representativeness of contemporary tree-climate relationships are poorly understood. We show that tree-climate relationships for 15 tree genera in the upper Midwestern US have significantly altered over the last two centuries due to historical land-use and climate change. Realised niches have shifted towards higher minimum temperatures and higher rainfall. A new attribution method implicates both historical climate change and land-use in these shifts, with the relative importance varying among genera and climate variables. Most climate/land-use interactions are compounding, in which historical land-use reinforces shifts in species-climate relationships toward wetter distributions, or confounding, in which land-use complicates shifts towards warmer distributions. Compounding interactions imply that contemporary-based models of species distributions may underestimate species resilience to climate change. © 2017 John Wiley & Sons Ltd/CNRS.
An Observationally-Centred Method to Quantify the Changing Shape of Local Temperature Distributions

NASA Astrophysics Data System (ADS)

Chapman, S. C.; Stainforth, D. A.; Watkins, N. W.

2014-12-01

For climate sensitive decisions and adaptation planning, guidance on how local climate is changing is needed at the specific thresholds relevant to particular impacts or policy endeavours. This requires the quantification of how the distributions of variables, such as daily temperature, are changing at specific quantiles. These temperature distributions are non-normal and vary both geographically and in time. We present a method[1,2] for analysing local climatic time series data to assess which quantiles of the local climatic distribution show the greatest and most robust changes. We have demonstrated this approach using the E-OBS gridded dataset[3] which consists of time series of local daily temperature across Europe over the last 60 years. Our method extracts the changing cumulative distribution function over time and uses a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. The change in temperature can be tracked at a temperature threshold, at a likelihood, or at a given return time, independently for each geographical location. Geographical correlations are thus an output of our method and reflect both climatic properties (local and synoptic), and spatial correlations inherent in the observation methodology. We find as an output many regionally consistent patterns of response of potential value in adaptation planning. For instance, in a band from Northern France to Denmark the hottest days in the summer temperature distribution have seen changes of at least 2°C over a 43 year period; over four times the global mean change over the same period. We discuss methods to quantify the robustness of these observed sensitivities and their statistical likelihood. This approach also quantifies the level of detail at which one might wish to see agreement between climate models and observations if such models are to be used directly as tools to assess climate change impacts at local scales. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, Phil. Trans. R. Soc. A, 371 20120287. [2] D A Stainforth, S C Chapman, N W Watkins, 2013, Environ. Res. Lett. 8, 034031 [3] Haylock, M.R. et al., 2008, J. Geophys. Res (Atmospheres), 113, D20119
Developing the evidence base for mainstreaming adaptation of stormwater systems to climate change.

PubMed

Gersonius, B; Nasruddin, F; Ashley, R; Jeuken, A; Pathirana, A; Zevenbergen, C

2012-12-15

In a context of high uncertainty about hydro-climatic variables, the development of updated methods for climate impact and adaptation assessment is as important, if not more important than the provision of improved climate change data. In this paper, we introduce a hybrid method to facilitate mainstreaming adaptation of stormwater systems to climate change: i.e., the Mainstreaming method. The Mainstreaming method starts with an analysis of adaptation tipping points (ATPs), which is effect-based. These are points of reference where the magnitude of climate change is such that acceptable technical, environmental, societal or economic standards may be compromised. It extends the ATP analysis to include aspects from a bottom-up approach. The extension concerns the analysis of adaptation opportunities in the stormwater system. The results from both analyses are then used in combination to identify and exploit Adaptation Mainstreaming Moments (AMMs). Use of this method will enhance the understanding of the adaptive potential of stormwater systems. We have applied the proposed hybrid method to the management of flood risk for an urban stormwater system in Dordrecht (the Netherlands). The main finding of this case study is that the application of the Mainstreaming method helps to increase the no-/low-regret character of adaptation for several reasons: it focuses the attention on the most urgent effects of climate change; it is expected to lead to potential cost reductions, since adaptation options can be integrated into infrastructure and building design at an early stage instead of being applied separately; it will lead to the development of area-specific responses, which could not have been developed on a higher scale level; it makes it possible to take account of local values and sensibilities, which contributes to increased public and political support for the adaptive strategies. Copyright © 2012 Elsevier Ltd. All rights reserved.
[Climate change risk of nature reserve and its assessment: A case study of Dalinuoer National Nature Reserve in Inner Mongolia Autonomous Region].

PubMed

Zhao, Wei; Shen, Wei Shou; Liu, Hai Yue

2016-12-01

According to the theoretical framework of addressing climate change based on risk mana-gement and the challenge to nature reserve management under climate change, climate change risk of nature reserve was analyzed and defined. Focus on birds and water habitat, grassland habitat, forest habitat, wetland habitat in Dalinuoer Nature Reserve, risk assessment method of nature reserve under climate change was formulated, climate change risks to Dalinuoer Nature Reserve and its habitats were assessed and predicted. The results showed that, during the period from 1997 to 2010, there was significant volatility in dynamic changes of climate change risks to Dalinuoer Nature Reserve and waterbody, grassland, forest, wetland in the region, Dalinuoer Nature Reserve and its habitats were in status of risk in 1999, 2001, 2005 and 2008, wetland habitat was also in status of risk in 2002 and 2004. Under scenario A, B and C, climate change risks to Dalinuoer Nature Reserve and waterbody, grassland, forest, wetland in the region would be more serious in 2020 and 2030, compared with the 2010 level. Climate change risks to different habitats were different significantly, with most serious climate change risk to wetland habitat due to its sensitivity to climate change and rich bird resources. The effect of climate change on nature reserve and related risk would be aggravated by excess utilization of water resource and grassland resource. As climate change risks had appeared in Dalinuoer Nature Reserve, risk management associated with climate change could greatly help to maintain and enhance biodiversity protection function of nature reserves.

Impacts of climate change on rainfall extremes and urban drainage systems: a review.

PubMed

Arnbjerg-Nielsen, K; Willems, P; Olsson, J; Beecham, S; Pathirana, A; Bülow Gregersen, I; Madsen, H; Nguyen, V-T-V

2013-01-01

A review is made of current methods for assessing future changes in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic-induced climate change. The review concludes that in spite of significant advances there are still many limitations in our understanding of how to describe precipitation patterns in a changing climate in order to design and operate urban drainage infrastructure. Climate change may well be the driver that ensures that changes in urban drainage paradigms are identified and suitable solutions implemented. Design and optimization of urban drainage infrastructure considering climate change impacts and co-optimizing these with other objectives will become ever more important to keep our cities habitable into the future.
Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

DOE PAGES

Calvin, Kate; Fisher-Vanden, Karen

2017-10-27

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparisonmore » between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between - 12% and + 15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.« less
Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

NASA Astrophysics Data System (ADS)

Calvin, Kate; Fisher-Vanden, Karen

2017-11-01

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparison between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between -12% and +15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.
Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

DOE Office of Scientific and Technical Information (OSTI.GOV)

Calvin, Kate; Fisher-Vanden, Karen

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparisonmore » between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between - 12% and + 15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.« less
Woody plants and the prediction of climate-change impacts on bird diversity.

PubMed

Kissling, W D; Field, R; Korntheuer, H; Heyder, U; Böhning-Gaese, K

2010-07-12

Current methods of assessing climate-induced shifts of species distributions rarely account for species interactions and usually ignore potential differences in response times of interacting taxa to climate change. Here, we used species-richness data from 1005 breeding bird and 1417 woody plant species in Kenya and employed model-averaged coefficients from regression models and median climatic forecasts assembled across 15 climate-change scenarios to predict bird species richness under climate change. Forecasts assuming an instantaneous response of woody plants and birds to climate change suggested increases in future bird species richness across most of Kenya whereas forecasts assuming strongly lagged woody plant responses to climate change indicated a reversed trend, i.e. reduced bird species richness. Uncertainties in predictions of future bird species richness were geographically structured, mainly owing to uncertainties in projected precipitation changes. We conclude that assessments of future species responses to climate change are very sensitive to current uncertainties in regional climate-change projections, and to the inclusion or not of time-lagged interacting taxa. We expect even stronger effects for more specialized plant-animal associations. Given the slow response time of woody plant distributions to climate change, current estimates of future biodiversity of many animal taxa may be both biased and too optimistic.
'Changing climate, changing health, changing stories' profile: using an EcoHealth approach to explore impacts of climate change on inuit health.

PubMed

Harper, S L; Edge, V L; Cunsolo Willox, A

2012-03-01

Global climate change and its impact on public health exemplify the challenge of managing complexity and uncertainty in health research. The Canadian North is currently experiencing dramatic shifts in climate, resulting in environmental changes which impact Inuit livelihoods, cultural practices, and health. For researchers investigating potential climate change impacts on Inuit health, it has become clear that comprehensive and meaningful research outcomes depend on taking a systemic and transdisciplinary approach that engages local citizens in project design, data collection, and analysis. While it is increasingly recognised that using approaches that embrace complexity is a necessity in public health, mobilizing such approaches from theory into practice can be challenging. In 2009, the Rigolet Inuit Community Government in Rigolet, Nunatsiavut, Canada partnered with a transdisciplinary team of researchers, health practitioners, and community storytelling facilitators to create the Changing Climate, Changing Health, Changing Stories project, aimed at developing a multi-media participatory, community-run methodological strategy to gather locally appropriate and meaningful data to explore climate-health relationships. The goal of this profile paper is to describe how an EcoHealth approach guided by principles of transdisciplinarity, community participation, and social equity was used to plan and implement this climate-health research project. An overview of the project, including project development, research methods, project outcomes to date, and challenges encountered, is presented. Though introduced in this one case study, the processes, methods, and lessons learned are broadly applicable to researchers and communities interested in implementing EcoHealth approaches in community-based research.
Climate Trends and Farmers' Perceptions of Climate Change in Zambia.

PubMed

Mulenga, Brian P; Wineman, Ayala; Sitko, Nicholas J

2017-02-01

A number of studies use meteorological records to analyze climate trends and assess the impact of climate change on agricultural yields. While these provide quantitative evidence on climate trends and the likely effects thereof, they incorporate limited qualitative analysis of farmers' perceptions of climate change and/or variability. The present study builds on the quantitative methods used elsewhere to analyze climate trends, and in addition compares local narratives of climate change with evidence found in meteorological records in Zambia. Farmers offer remarkably consistent reports of a rainy season that is growing shorter and less predictable. For some climate parameters-notably, rising average temperature-there is a clear overlap between farmers' observations and patterns found in the meteorological records. However, the data do not support the perception that the rainy season used to begin earlier, and we generally do not detect a reported increase in the frequency of dry spells. Several explanations for these discrepancies are offered. Further, we provide policy recommendations to help farmers adapt to climate change/variability, as well as suggestions to shape future climate change policies, programs, and research in developing countries.
A New High Resolution Climate Dataset for Climate Change Impacts Assessments in New England

NASA Astrophysics Data System (ADS)

Komurcu, M.; Huber, M.

2016-12-01

Assessing regional impacts of climate change (such as changes in extreme events, land surface hydrology, water resources, energy, ecosystems and economy) requires much higher resolution climate variables than those available from global model projections. While it is possible to run global models in higher resolution, the high computational cost associated with these simulations prevent their use in such manner. To alleviate this problem, dynamical downscaling offers a method to deliver higher resolution climate variables. As part of an NSF EPSCoR funded interdisciplinary effort to assess climate change impacts on New Hampshire ecosystems, hydrology and economy (the New Hampshire Ecosystems and Society project), we create a unique high-resolution climate dataset for New England. We dynamically downscale global model projections under a high impact emissions scenario using the Weather Research and Forecasting model (WRF) with three nested grids of 27, 9 and 3 km horizontal resolution with the highest resolution innermost grid focusing over New England. We prefer dynamical downscaling over other methods such as statistical downscaling because it employs physical equations to progressively simulate climate variables as atmospheric processes interact with surface processes, emissions, radiation, clouds, precipitation and other model components, hence eliminates fix relationships between variables. In addition to simulating mean changes in regional climate, dynamical downscaling also allows for the simulation of climate extremes that significantly alter climate change impacts. We simulate three time slices: 2006-2015, 2040-2060 and 2080-2100. This new high-resolution climate dataset (with more than 200 variables saved in hourly (six hourly) intervals for the highest resolution domain (outer two domains)) along with model input and restart files used in our WRF simulations will be publicly available for use to the broader scientific community to support in-depth climate change impacts assessments for New England. We present results focusing on future changes in New England extreme events.
Focus on Agriculture and Forestry Benefits of Reducing Climate Change Impacts

EPA Science Inventory

The objective of this focus issue is to present the methods and results of modeling exercises that estimate the impacts of climate change on agriculture and forestry under a consistent set of climate projections that represent futures with and without global-scale GHG mitigation....
Conflict in a changing climate

NASA Astrophysics Data System (ADS)

Carleton, T.; Hsiang, S. M.; Burke, M.

2016-05-01

A growing body of research illuminates the role that changes in climate have had on violent conflict and social instability in the recent past. Across a diversity of contexts, high temperatures and irregular rainfall have been causally linked to a range of conflict outcomes. These findings can be paired with climate model output to generate projections of the impact future climate change may have on conflicts such as crime and civil war. However, there are large degrees of uncertainty in such projections, arising from (i) the statistical uncertainty involved in regression analysis, (ii) divergent climate model predictions, and (iii) the unknown ability of human societies to adapt to future climate change. In this article, we review the empirical evidence of the climate-conflict relationship, provide insight into the likely extent and feasibility of adaptation to climate change as it pertains to human conflict, and discuss new methods that can be used to provide projections that capture these three sources of uncertainty.
Hydrological modeling as an evaluation tool of EURO-CORDEX climate projections and bias correction methods

NASA Astrophysics Data System (ADS)

Hakala, Kirsti; Addor, Nans; Seibert, Jan

2017-04-01

Streamflow stemming from Switzerland's mountainous landscape will be influenced by climate change, which will pose significant challenges to the water management and policy sector. In climate change impact research, the determination of future streamflow is impeded by different sources of uncertainty, which propagate through the model chain. In this research, we explicitly considered the following sources of uncertainty: (1) climate models, (2) downscaling of the climate projections to the catchment scale, (3) bias correction method and (4) parameterization of the hydrological model. We utilize climate projections at the 0.11 degree 12.5 km resolution from the EURO-CORDEX project, which are the most recent climate projections for the European domain. EURO-CORDEX is comprised of regional climate model (RCM) simulations, which have been downscaled from global climate models (GCMs) from the CMIP5 archive, using both dynamical and statistical techniques. Uncertainties are explored by applying a modeling chain involving 14 GCM-RCMs to ten Swiss catchments. We utilize the rainfall-runoff model HBV Light, which has been widely used in operational hydrological forecasting. The Lindström measure, a combination of model efficiency and volume error, was used as an objective function to calibrate HBV Light. Ten best sets of parameters are then achieved by calibrating using the genetic algorithm and Powell optimization (GAP) method. The GAP optimization method is based on the evolution of parameter sets, which works by selecting and recombining high performing parameter sets with each other. Once HBV is calibrated, we then perform a quantitative comparison of the influence of biases inherited from climate model simulations to the biases stemming from the hydrological model. The evaluation is conducted over two time periods: i) 1980-2009 to characterize the simulation realism under the current climate and ii) 2070-2099 to identify the magnitude of the projected change of streamflow under the climate scenarios RCP4.5 and RCP8.5. We utilize two techniques for correcting biases in the climate model output: quantile mapping and a new method, frequency bias correction. The FBC method matches the frequencies between observed and GCM-RCM data. In this way, it can be used to correct for all time scales, which is a known limitation of quantile mapping. A novel approach for the evaluation of the climate simulations and bias correction methods was then applied. Streamflow can be thought of as the "great integrator" of uncertainties. The ability, or the lack thereof, to correctly simulate streamflow is a way to assess the realism of the bias-corrected climate simulations. Long-term monthly mean as well as high and low flow metrics are used to evaluate the realism of the simulations under current climate and to gauge the impacts of climate change on streamflow. Preliminary results show that under present climate, calibration of the hydrological model comprises of a much smaller band of uncertainty in the modeling chain as compared to the bias correction of the GCM-RCMs. Therefore, for future time periods, we expect the bias correction of climate model data to have a greater influence on projected changes in streamflow than the calibration of the hydrological model.
Future fire probability modeling with climate change data and physical chemistry

Treesearch

Richard P. Guyette; Frank R. Thompson; Jodi Whittier; Michael C. Stambaugh; Daniel C. Dey

2014-01-01

Climate has a primary influence on the occurrence and rate of combustion in ecosystems with carbon-based fuels such as forests and grasslands. Society will be confronted with the effects of climate change on fire in future forests. There are, however, few quantitative appraisals of how climate will affect wildland fire in the United States. We demonstrated a method for...
Attributing runoff changes to climate variability and human activities: uncertainty analysis using four monthly water balance models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Shuai; Xiong, Lihua; Li, Hong-Yi

2015-05-26

Hydrological simulations to delineate the impacts of climate variability and human activities are subjected to uncertainties related to both parameter and structure of the hydrological models. To analyze the impact of these uncertainties on the model performance and to yield more reliable simulation results, a global calibration and multimodel combination method that integrates the Shuffled Complex Evolution Metropolis (SCEM) and Bayesian Model Averaging (BMA) of four monthly water balance models was proposed. The method was applied to the Weihe River Basin (WRB), the largest tributary of the Yellow River, to determine the contribution of climate variability and human activities tomore » runoff changes. The change point, which was used to determine the baseline period (1956-1990) and human-impacted period (1991-2009), was derived using both cumulative curve and Pettitt’s test. Results show that the combination method from SCEM provides more skillful deterministic predictions than the best calibrated individual model, resulting in the smallest uncertainty interval of runoff changes attributed to climate variability and human activities. This combination methodology provides a practical and flexible tool for attribution of runoff changes to climate variability and human activities by hydrological models.« less
Effects of climate change on water requirements and phenological period of major crops in Heihe River basin, China - Based on the accumulated temperature threshold method

NASA Astrophysics Data System (ADS)

Han, Dongmei; Xu, Xinyi; Yan, Denghua

2016-04-01

In recent years, global climate change has significantly caused a serious crisis of water resources throughout the world. However, mainly through variations in temperature, climate change will affect water requirements of crop. It is obvious that the rise of temperature affects growing period and phenological period of crop directly, then changes the water demand quota of crop. Methods including accumulated temperature threshold and climatic tendency rate were adopted, which made up for the weakness of phenological observations, to reveal the response of crop phenological change during the growing period. Then using Penman-Menteith model and crop coefficients from the United Nations Food& Agriculture Organization (FAO), the paper firstly explored crop water requirements in different growth periods, and further forecasted quantitatively crop water requirements in Heihe River Basin, China under different climate change scenarios. Results indicate that: (i) The results of crop phenological change established in the method of accumulated temperature threshold were in agreement with measured results, and (ii) there were many differences in impacts of climate warming on water requirement of different crops. The growth periods of wheat and corn had tendency of shortening as well as the length of growth periods. (ii)Results of crop water requirements under different climate change scenarios showed: when temperature increased by 1°C, the start time of wheat growth period changed, 2 days earlier than before, and the length of total growth period shortened 2 days. Wheat water requirements increased by 1.4mm. However, corn water requirements decreased by almost 0.9mm due to the increasing temperature of 1°C. And the start time of corn growth period become 3 days ahead, and the length of total growth period shortened 4 days. Therefore, the contradiction between water supply and water demands are more obvious under the future climate warming in Heihe River Basin, China.
Incorporating climate change into ecosystem service assessments and decisions: a review.

PubMed

Runting, Rebecca K; Bryan, Brett A; Dee, Laura E; Maseyk, Fleur J F; Mandle, Lisa; Hamel, Perrine; Wilson, Kerrie A; Yetka, Kathleen; Possingham, Hugh P; Rhodes, Jonathan R

2017-01-01

Climate change is having a significant impact on ecosystem services and is likely to become increasingly important as this phenomenon intensifies. Future impacts can be difficult to assess as they often involve long timescales, dynamic systems with high uncertainties, and are typically confounded by other drivers of change. Despite a growing literature on climate change impacts on ecosystem services, no quantitative syntheses exist. Hence, we lack an overarching understanding of the impacts of climate change, how they are being assessed, and the extent to which other drivers, uncertainties, and decision making are incorporated. To address this, we systematically reviewed the peer-reviewed literature that assesses climate change impacts on ecosystem services at subglobal scales. We found that the impact of climate change on most types of services was predominantly negative (59% negative, 24% mixed, 4% neutral, 13% positive), but varied across services, drivers, and assessment methods. Although uncertainty was usually incorporated, there were substantial gaps in the sources of uncertainty included, along with the methods used to incorporate them. We found that relatively few studies integrated decision making, and even fewer studies aimed to identify solutions that were robust to uncertainty. For management or policy to ensure the delivery of ecosystem services, integrated approaches that incorporate multiple drivers of change and account for multiple sources of uncertainty are needed. This is undoubtedly a challenging task, but ignoring these complexities can result in misleading assessments of the impacts of climate change, suboptimal management outcomes, and the inefficient allocation of resources for climate adaptation. © 2016 John Wiley & Sons Ltd.
Linking Indigenous Knowledge and Observed Climate Change Studies

NASA Technical Reports Server (NTRS)

Alexander, Chief Clarence; Bynum, Nora; Johnson, Liz; King, Ursula; Mustonen, Tero; Neofotis, Peter; Oettle, Noel; Rosenzweig, Cynthia; Sakakibara, Chie; Shadrin, Chief Vyacheslav;

2010-01-01

We present indigenous knowledge narratives and explore their connections to documented temperature and other climate changes and observed climate change impact studies. We then propose a framework for enhancing integration of these indigenous narratives of observed climate change with global assessments. Our aim is to contribute to the thoughtful and respectful integration of indigenous knowledge with scientific data and analysis, so that this rich body of knowledge can inform science, and so that indigenous and traditional peoples can use the tools and methods of science for the benefit of their communities if they choose to do so. Enhancing ways of understanding such connections are critical as the Intergovernmental Panel on Climate Change Fifth Assessment process gets underway.

Uncertainties associated with quantifying climate change impacts on human health: a case study for diarrhea.

PubMed

Kolstad, Erik W; Johansson, Kjell Arne

2011-03-01

Climate change is expected to have large impacts on health at low latitudes where droughts and malnutrition, diarrhea, and malaria are projected to increase. The main objective of this study was to indicate a method to assess a range of plausible health impacts of climate change while handling uncertainties in a unambiguous manner. We illustrate this method by quantifying the impacts of projected regional warming on diarrhea in this century. We combined a range of linear regression coefficients to compute projections of future climate change-induced increases in diarrhea using the results from five empirical studies and a 19-member climate model ensemble for which future greenhouse gas emissions were prescribed. Six geographical regions were analyzed. The model ensemble projected temperature increases of up to 4°C over land in the tropics and subtropics by the end of this century. The associated mean projected increases of relative risk of diarrhea in the six study regions were 8-11% (with SDs of 3-5%) by 2010-2039 and 22-29% (SDs of 9-12%) by 2070-2099. Even our most conservative estimates indicate substantial impacts from climate change on the incidence of diarrhea. Nevertheless, our main conclusion is that large uncertainties are associated with future projections of diarrhea and climate change. We believe that these uncertainties can be attributed primarily to the sparsity of empirical climate-health data. Our results therefore highlight the need for empirical data in the cross section between climate and human health.
Investigating the Capacity of Hydrological Models to Project Impacts of Climate Change in the Context of Water Allocation

NASA Astrophysics Data System (ADS)

Velez, Carlos; Maroy, Edith; Rocabado, Ivan; Pereira, Fernando

2017-04-01

To analyse the impacts of climate changes, hydrological models are used to project the hydrology responds under future conditions that normally differ from those for which they were calibrated. The challenge is to assess the validity of the projected effects when there is not data to validate it. A framework for testing the ability of models to project climate change was proposed by Refsgaard et al., (2014). The authors recommend the use of the differential-split sample test (DSST) in order to build confidence in the model projections. The method follow three steps: 1. A small number of sub-periods are selected according to one climate characteristics, 2. The calibration - validation test is applied on these periods, 3. The validation performances are compered to evaluate whether they vary significantly when climatic characteristics differ between calibration and validation. DSST rely on the existing records of climate and hydrological variables; and performances are estimated based on indicators of error between observed and simulated variables. Other authors suggest that, since climate models are not able to reproduce single events but rather statistical properties describing the climate, this should be reflected when testing hydrological models. Thus, performance criteria such as RMSE should be replaced by for instance flow duration curves or other distribution functions. Using this type of performance criteria, Van Steenbergen and Willems, (2012) proposed a method to test the validity of hydrological models in a climate changing context. The method is based on the evaluation of peak flow increases due to different levels of rainfall increases. In contrast to DSST, this method use the projected climate variability and it is especially useful to compare different modelling tools. In the framework of a water allocation project for the region of Flanders (Belgium) we calibrated three hydrological models: NAM, PDM and VHM; for 67 gauged sub-catchments with approx. 40 years of records. This paper investigates the capacity of the three hydrological models to project the impacts of climate change scenarios. It is proposed a general testing framework which combine the use of the existing information through an adapted form of DSST with the approach proposed by Van Steenbergen and Willems, (2012) adapted to assess statistical properties of flows useful in the context of water allocation. To assess the model we use robustness criteria based on a Log Nash-Sutcliffe, BIAS on cummulative volumes and relative changes based on Q50/Q90 estimated from the duration curve. The three conceptual rainfall-runoff models yielded different results per sub-catchments. A relation was found between robustness criteria and changes in mean rainfall and changes in mean potential evapotranspiration. Biases are greatly affected by changes in precipitation, especially when the climate scenarios involve changes in precipitation volume beyond the range used for calibration. Using the combine approach we were able to classify the modelling tools per sub-catchments and create an ensemble of best models to project the impacts of climate variability for the catchments of 10 main rivers in Flanders. Thus, managers could understand better the usability of the modelling tools and the credibility of its outputs for water allocation applications. References Refsgaard, J.C., Madsen, H., Andréassian, V., Arnbjerg-Nielsen, K., Davidson, T.A., Drews, M., Hamilton, D.P., Jeppesen, E., Kjellström, E., Olesen, J.E., Sonnenborg, T.O., Trolle, D., Willems, P., Christensen, J.H., 2014. A framework for testing the ability of models to project climate change and its impacts. Clim. Change. Van Steenbergen, N., Willems, P., 2012. Method for testing the accuracy of rainfall - runoff models in predicting peak flow changes due to rainfall changes , in a climate changing context. J. Hydrol. 415, 425-434.
Incorporating Student Activities into Climate Change Education

NASA Astrophysics Data System (ADS)

Steele, H.; Kelly, K.; Klein, D.; Cadavid, A. C.

2013-12-01

Under a NASA grant, Mathematical and Geospatial Pathways to Climate Change Education, students at California State University, Northridge integrated Geographic Information Systems (GIS), remote sensing, satellite data technologies, and climate modelling into the study of global climate change under a Pathway for studying the Mathematics of Climate Change (PMCC). The PMCC, which is an interdisciplinary option within the BS in Applied Mathematical Sciences, consists of courses offered by the departments of Mathematics, Physics, and Geography and is designed to prepare students for careers and Ph.D. programs in technical fields relevant to global climate change. Under this option students are exposed to the science, mathematics, and applications of climate change science through a variety of methods including hands-on experience with computer modeling and image processing software. In the Geography component of the program, ESRI's ArcGIS and ERDAS Imagine mapping, spatial analysis and image processing software were used to explore NASA satellite data to examine the earth's atmosphere, hydrosphere and biosphere in areas that are affected by climate change or affect climate. These technology tools were incorporated into climate change and remote sensing courses to enhance students' knowledge and understanding of climate change through hands-on application of image processing techniques to NASA data. Several sets of exercises were developed with specific learning objectives in mind. These were (1) to increase student understanding of climate change and climate change processes; (2) to develop student skills in understanding, downloading and processing satellite data; (3) to teach remote sensing technology and GIS through applications to climate change; (4) to expose students to climate data and methods they can apply to solve real world problems and incorporate in future research projects. In the Math and Physics components of the course, students learned about atmospheric circulation with applications of the Lorenz model, explored the land-sea breeze problem with the Dynamics and Thermodynamics Circulation Model (DTDM), and developed simple radiative transfer models. Class projects explored the effects of varying the content of CO2 and CH4 in the atmosphere, as well as the properties of paleoclimates in atmospheric simulations using EdGCM. Initial assessment of student knowledge, attitudes, and behaviors associated with these activities, particularly about climate change, was measured. Pre- and post-course surveys provided student perspectives about the courses and their learning about remote sensing and climate change concepts. Student performance on the tutorials and course projects evaluated students' ability to learn and apply their knowledge about climate change and skills with remote sensing to assigned problems or proposed projects of their choice. Survey and performance data illustrated that the exercises were successful in meeting their intended learning objectives as well as opportunities for further refinement and expansion.
An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change

PubMed Central

Casajus, Nicolas; Périé, Catherine; Logan, Travis; Lambert, Marie-Claude; de Blois, Sylvie; Berteaux, Dominique

2016-01-01

An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one. PMID:27015274

An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change.

PubMed

Casajus, Nicolas; Périé, Catherine; Logan, Travis; Lambert, Marie-Claude; de Blois, Sylvie; Berteaux, Dominique

2016-01-01

An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one.
The savory method can not green deserts or reverse climate change

USDA-ARS?s Scientific Manuscript database

Mr. Allan Savory addressed one of the major environmental challenges of our time – rapidly increasing atmospheric CO2 concentrations and climate warming - in a video presentation entitled, "How to green the world's deserts and reverse climate change" that was presented at the 2013 TED (Technology, E...
Climate change and natural disasters – integrating science and practice to protect health

PubMed Central

Sauerborn, Rainer; Ebi, Kristie

2012-01-01

Background Hydro-meteorological disasters are the focus of this paper. The authors examine, to which extent climate change increases their frequency and intensity. Methods Review of IPCC-projections of climate-change related extreme weather events and related literature on health effects. Results Projections show that climate change is likely to increase the frequency, intensity, duration, and spatial distribution of a range of extreme weather events over coming decades. Conclusions There is a need for strengthened collaboration between climate scientists, the health researchers and policy-makers as well as the disaster community to jointly develop adaptation strategies to protect human. PMID:23273248
Vulnerability Assessment of Natural Disasters for Small and Mid-Sized Streams due to Climate Change and Stream Improvement

NASA Astrophysics Data System (ADS)

Choi, D.; Jun, H. D.; Kim, S.

2012-04-01

Vulnerability assessment plays an important role in drawing up climate change adaptation plans. Although there are some studies on broad vulnerability assessment in Korea, there have been very few studies to develop and apply locally focused and specific sector-oriented climate change vulnerability indicators. Especially, there has seldom been any study to investigate the effect of an adaptation project on assessing the vulnerability status to climate change for fundamental local governments. In order to relieve adverse effects of climate change, Korean government has performed the project of the Major Four Rivers (Han, Geum, Nakdong and Yeongsan river) Restoration since 2008. It is expected that water level in main stream of 4 rivers will be dropped through this project, but flood effect will be mainly occurred in small and mid-sized streams which flows in main stream. Hence, we examined how much the project of the major four rivers restoration relieves natural disasters. Conceptual framework of vulnerability-resilience index to climate change for the Korean fundamental local governments is defined as a function of climate exposure, sensitivity, and adaptive capacity. Then, statistical data on scores of proxy variables assumed to comprise climate change vulnerability for local governments are collected. Proxy variables and estimated temporary weights of them are selected by surveying a panel of experts using Delphi method, and final weights are determined by modified Entropy method. Developed vulnerability-resilience index was applied to Korean fundamental local governments and it is calculated under each scenario as follows. (1) Before the major four rivers restoration, (2) 100 years after represented climate change condition without the major four rivers restoration, (3) After the major four rivers restoration without representing climate change (this means present climate condition) and (4) After the major four rivers restoration and 100 years after represented climate change condition. In the results of calculated vulnerability-resilience index of each scenario, it can be noticed that vulnerability of watersheds which are located near main stream of four rivers is alleviated, but because of climate change, vulnerability is getting high in most watersheds. Also, considering future climate change and river restoration, vulnerability of several watersheds is relieved by river restoration. Acknowledges This work was funded by the National Emergency Management Agency (NEMA) in Korea Program under Grant NEMA-10-NH-04.
Mapping the changing pattern of local climate as an observed distribution

NASA Astrophysics Data System (ADS)

Chapman, Sandra; Stainforth, David; Watkins, Nicholas

2013-04-01

It is at local scales that the impacts of climate change will be felt directly and at which adaptation planning decisions must be made. This requires quantifying the geographical patterns in trends at specific quantiles in distributions of variables such as daily temperature or precipitation. Here we focus on these local changes and on the way observational data can be analysed to inform us about the pattern of local climate change. We present a method[1] for analysing local climatic timeseries data to assess which quantiles of the local climatic distribution show the greatest and most robust trends. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily temperature from specific locations across Europe over the last 60 years. Our method extracts the changing cumulative distribution function over time and uses a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of the sensitivity of different quantiles of the distributions to changing climate. Geographical location and temperature are treated as independent variables, we thus obtain as outputs the pattern of variation in sensitivity with temperature (or occurrence likelihood), and with geographical location. We find as an output many regionally consistent patterns of response of potential value in adaptation planning. We discuss methods to quantify and map the robustness of these observed sensitivities and their statistical likelihood. This also quantifies the level of detail needed from climate models if they are to be used as tools to assess climate change impact. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, in press [2] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119, doi:10.1029/2008JD10201
Future change in seasonal march of snow water equivalent due to global climate change

NASA Astrophysics Data System (ADS)

Hara, M.; Kawase, H.; Ma, X.; Wakazuki, Y.; Fujita, M.; Kimura, F.

2012-04-01

Western side of Honshu Island in Japan is one of the heaviest snowfall areas in the world, although the location is relatively lower latitude than other heavy snowfall areas. Snowfall is one of major source for agriculture, industrial, and house-use in Japan. The change in seasonal march of snow water equivalent, e.g., snowmelt season and amount will strongly influence to social-economic activities (ex. Ma et al., 2011). We performed the four numerical experiments including present and future climate simulations and much-snow and less-snow cases using a regional climate model. Pseudo-Global-Warming (PGW) method (Kimura and Kitoh, 2008) is applied for the future climate simulations. NCEP/NCAR reanalysis is used for initial and boundary conditions in present climate simulation and PGW method. MIROC 3.2 medres 2070s output under IPCC SRES A2 scenario and 1990s output under 20c3m scenario used for PGW method. In much-snow cases, Maximum total snow water equivalent over Japan, which is mostly observed in early February, is 49 G ton in the present simulation, the one decreased 26 G ton in the future simulation. The decreasing rate of snow water equivalent due to climate change was 49%. Main cause of the decrease of the total snow water equivalent is strongly affected by the air temperature rise due to global climate change. The difference in present and future precipitation amount is little.
Environmental water demand assessment under climate change conditions.

PubMed

Sarzaeim, Parisa; Bozorg-Haddad, Omid; Fallah-Mehdipour, Elahe; Loáiciga, Hugo A

2017-07-01

Measures taken to cope with the possible effects of climate change on water resources management are key for the successful adaptation to such change. This work assesses the environmental water demand of the Karkheh river in the reach comprising Karkheh dam to the Hoor-al-Azim wetland, Iran, under climate change during the period 2010-2059. The assessment of the environmental demand applies (1) representative concentration pathways (RCPs) and (2) downscaling methods. The first phase of this work projects temperature and rainfall in the period 2010-2059 under three RCPs and with two downscaling methods. Thus, six climatic scenarios are generated. The results showed that temperature and rainfall average would increase in the range of 1.7-5.2 and 1.9-9.2%, respectively. Subsequently, flows corresponding to the six different climatic scenarios are simulated with the unit hydrographs and component flows from rainfall, evaporation, and stream flow data (IHACRES) rainfall-runoff model and are input to the Karkheh reservoir. The simulation results indicated increases of 0.9-7.7% in the average flow under the six simulation scenarios during the period of analysis. The second phase of this paper's methodology determines the monthly minimum environmental water demands of the Karkheh river associated with the six simulation scenarios using a hydrological method. The determined environmental demands are compared with historical ones. The results show that the temporal variation of monthly environmental demand would change under climate change conditions. Furthermore, some climatic scenarios project environmental water demand larger than and some of them project less than the baseline one.
Teaching About Climate Change in Medical Education: An Opportunity

PubMed Central

Maxwell, Janie; Blashki, Grant

2016-01-01

Climate change threatens many of the gains in development and health over the last century. However, it could also be a catalyst for a necessary societal transformation to a sustainable and healthy future. Doctors have a crucial role in climate change mitigation and health system adaptation to prepare for emergent health threats and a carbon-constrained future. This paper argues that climate change should be integrated into medical education for three reasons: first, to prepare students for clinical practice in a climate-changing world; secondly, to promote public health and eco-health literacy; and finally, to deepen existing learning and strengthen graduate attributes. This paper builds on existing literature and the authors’ experience to outline potential learning objectives, teaching methods and assessment tasks. In the wake of recent progress at the United Nations climate change conference, COP-21, it is hoped that this paper will assist universities to integrate teaching about climate change into medical education. Significance for public health There is a strong case for teaching about climate change in medical education. Anthropogenic climate change is accepted by scientists, governments and health authorities internationally. Given the dire implications for human health, climate change is of fundamental relevance to future doctors. Integrating climate change into medical education offers an opportunity for future doctors to develop skills and insights essential for clinical practice and a public health role in a climate-changing world. This echoes a broader call for improved public health literacy among medical graduates. This paper provides medical schools with a rationale and an outline for teaching on climate change. PMID:27190980
Teaching About Climate Change in Medical Education: An Opportunity.

PubMed

Maxwell, Janie; Blashki, Grant

2016-04-26

Climate change threatens many of the gains in development and health over the last century. However, it could also be a catalyst for a necessary societal transformation to a sustainable and healthy future. Doctors have a crucial role in climate change mitigation and health system adaptation to prepare for emergent health threats and a carbon-constrained future. This paper argues that climate change should be integrated into medical education for three reasons: first, to prepare students for clinical practice in a climate-changing world; secondly, to promote public health and eco-health literacy; and finally, to deepen existing learning and strengthen graduate attributes. This paper builds on existing literature and the authors' experience to outline potential learning objectives, teaching methods and assessment tasks. In the wake of recent progress at the United Nations climate change conference, COP-21, it is hoped that this paper will assist universities to integrate teaching about climate change into medical education. Significance for public healthThere is a strong case for teaching about climate change in medical education. Anthropogenic climate change is accepted by scientists, governments and health authorities internationally. Given the dire implications for human health, climate change is of fundamental relevance to future doctors. Integrating climate change into medical education offers an opportunity for future doctors to develop skills and insights essential for clinical practice and a public health role in a climate-changing world. This echoes a broader call for improved public health literacy among medical graduates. This paper provides medical schools with a rationale and an outline for teaching on climate change.
Climate Change and Macro-Economic Cycles in Pre-Industrial Europe

PubMed Central

Pei, Qing; Zhang, David D.; Lee, Harry F.; Li, Guodong

2014-01-01

Climate change has been proven to be the ultimate cause of social crisis in pre-industrial Europe at a large scale. However, detailed analyses on climate change and macro-economic cycles in the pre-industrial era remain lacking, especially within different temporal scales. Therefore, fine-grained, paleo-climate, and economic data were employed with statistical methods to quantitatively assess the relations between climate change and agrarian economy in Europe during AD 1500 to 1800. In the study, the Butterworth filter was adopted to filter the data series into a long-term trend (low-frequency) and short-term fluctuations (high-frequency). Granger Causality Analysis was conducted to scrutinize the associations between climate change and macro-economic cycle at different frequency bands. Based on quantitative results, climate change can only show significant effects on the macro-economic cycle within the long-term. In terms of the short-term effects, society can relieve the influences from climate variations by social adaptation methods and self-adjustment mechanism. On a large spatial scale, temperature holds higher importance for the European agrarian economy than precipitation. By examining the supply-demand mechanism in the grain market, population during the study period acted as the producer in the long term, whereas as the consumer in the short term. These findings merely reflect the general interactions between climate change and macro-economic cycles at the large spatial region with a long-term study period. The findings neither illustrate individual incidents that can temporarily distort the agrarian economy nor explain some specific cases. In the study, the scale thinking in the analysis is raised as an essential methodological issue for the first time to interpret the associations between climatic impact and macro-economy in the past agrarian society within different temporal scales. PMID:24516601
Climate change and macro-economic cycles in pre-industrial europe.

PubMed

Pei, Qing; Zhang, David D; Lee, Harry F; Li, Guodong

2014-01-01

Climate change has been proven to be the ultimate cause of social crisis in pre-industrial Europe at a large scale. However, detailed analyses on climate change and macro-economic cycles in the pre-industrial era remain lacking, especially within different temporal scales. Therefore, fine-grained, paleo-climate, and economic data were employed with statistical methods to quantitatively assess the relations between climate change and agrarian economy in Europe during AD 1500 to 1800. In the study, the Butterworth filter was adopted to filter the data series into a long-term trend (low-frequency) and short-term fluctuations (high-frequency). Granger Causality Analysis was conducted to scrutinize the associations between climate change and macro-economic cycle at different frequency bands. Based on quantitative results, climate change can only show significant effects on the macro-economic cycle within the long-term. In terms of the short-term effects, society can relieve the influences from climate variations by social adaptation methods and self-adjustment mechanism. On a large spatial scale, temperature holds higher importance for the European agrarian economy than precipitation. By examining the supply-demand mechanism in the grain market, population during the study period acted as the producer in the long term, whereas as the consumer in the short term. These findings merely reflect the general interactions between climate change and macro-economic cycles at the large spatial region with a long-term study period. The findings neither illustrate individual incidents that can temporarily distort the agrarian economy nor explain some specific cases. In the study, the scale thinking in the analysis is raised as an essential methodological issue for the first time to interpret the associations between climatic impact and macro-economy in the past agrarian society within different temporal scales.
Projection of future runoff change using climate elasticity method derived from Budyko framework in major basins across China

NASA Astrophysics Data System (ADS)

Xing, Wanqiu; Wang, Weiguang; Zou, Shan; Deng, Chao

2018-03-01

This study established a climate elasticity method based on Budyko hypothesis and enhanced it by selecting the most effective Budyko-type formula to strengthen the runoff change prediction reliability. The spatiotemporal variations in hydrologic variables (i.e., runoff, precipitation and potential evaporation) during historical period were revealed first and the climate elasticities of runoff were investigated. The proposed climate elasticity method was also applied to project the spatiotemporal variations in future runoff and its key influencing factors in 35 watersheds across China. Wherein, the future climate series were retrieved by consulting the historical series, informed by four global climate models (GCMs) under representative concentration pathways from phase five of the Coupled Model Intercomparison Project. Wang-Tang equation was selected as the optimal Budyko-type equation for its best ability in reproducing the runoff change (with a coefficient of determination and mean absolute error of 0.998 and 1.36 mm, respectively). Observed runoff presents significant decreasing trends in the northern and increasing trends in the southern regions of China, and generally its change is identified to be more sensitive to climatic variables in Hai River Basin and lower Yellow River Basin. Compared to the runoff during the reference period, positive change rates in the north and negative change rates in the south of China in the mid-21st century can be practically generalized from the majority of GCMs projections. This maybe resulted from the increasing precipitation, especially in parts of northern basins. Meanwhile, GCMs project a consistently upward trend in potential evaporation although significant decreasing trends occur in the majority of catchments for the historical period. The results indicate that climate change will possibly bring some changes to the water resources over China in the mid-21st century and some countermeasures of water resources planning and management should be taken.
A method for screening climate change-sensitive infectious diseases.

PubMed

Wang, Yunjing; Rao, Yuhan; Wu, Xiaoxu; Zhao, Hainan; Chen, Jin

2015-01-14

Climate change is a significant and emerging threat to human health, especially where infectious diseases are involved. Because of the complex interactions between climate variables and infectious disease components (i.e., pathogen, host and transmission environment), systematically and quantitatively screening for infectious diseases that are sensitive to climate change is still a challenge. To address this challenge, we propose a new statistical indicator, Relative Sensitivity, to identify the difference between the sensitivity of the infectious disease to climate variables for two different climate statuses (i.e., historical climate and present climate) in non-exposure and exposure groups. The case study in Anhui Province, China has demonstrated the effectiveness of this Relative Sensitivity indicator. The application results indicate significant sensitivity of many epidemic infectious diseases to climate change in the form of changing climatic variables, such as temperature, precipitation and absolute humidity. As novel evidence, this research shows that absolute humidity has a critical influence on many observed infectious diseases in Anhui Province, including dysentery, hand, foot and mouth disease, hepatitis A, hemorrhagic fever, typhoid fever, malaria, meningitis, influenza and schistosomiasis. Moreover, some infectious diseases are more sensitive to climate change in rural areas than in urban areas. This insight provides guidance for future health inputs that consider spatial variability in response to climate change.
A Method for Screening Climate Change-Sensitive Infectious Diseases

PubMed Central

Wang, Yunjing; Rao, Yuhan; Wu, Xiaoxu; Zhao, Hainan; Chen, Jin

2015-01-01

Climate change is a significant and emerging threat to human health, especially where infectious diseases are involved. Because of the complex interactions between climate variables and infectious disease components (i.e., pathogen, host and transmission environment), systematically and quantitatively screening for infectious diseases that are sensitive to climate change is still a challenge. To address this challenge, we propose a new statistical indicator, Relative Sensitivity, to identify the difference between the sensitivity of the infectious disease to climate variables for two different climate statuses (i.e., historical climate and present climate) in non-exposure and exposure groups. The case study in Anhui Province, China has demonstrated the effectiveness of this Relative Sensitivity indicator. The application results indicate significant sensitivity of many epidemic infectious diseases to climate change in the form of changing climatic variables, such as temperature, precipitation and absolute humidity. As novel evidence, this research shows that absolute humidity has a critical influence on many observed infectious diseases in Anhui Province, including dysentery, hand, foot and mouth disease, hepatitis A, hemorrhagic fever, typhoid fever, malaria, meningitis, influenza and schistosomiasis. Moreover, some infectious diseases are more sensitive to climate change in rural areas than in urban areas. This insight provides guidance for future health inputs that consider spatial variability in response to climate change. PMID:25594780
Evidence of climate change impact on stream low flow from the tropical mountain rainforest watershed in Hainan Island, China

Treesearch

Z. Zhou; Y. Ouyang; Z. Qiu; G. Zhou; M. Lin; Y. Li

2017-01-01

Stream low flow estimates are central to assessing climate change impact, water resource management, and ecosystem restoration. This study investigated the impacts of climate change upon stream low flows from a rainforest watershed in Jianfengling (JFL) Mountain, Hainan Island, China, using the low flow selection method as well as the frequency and probability analysis...
Which early works are cited most frequently in climate change research literature? A bibliometric approach based on Reference Publication Year Spectroscopy.

PubMed

Marx, Werner; Haunschild, Robin; Thor, Andreas; Bornmann, Lutz

2017-01-01

This bibliometric analysis focuses on the general history of climate change research and, more specifically, on the discovery of the greenhouse effect. First, the Reference Publication Year Spectroscopy (RPYS) is applied to a large publication set on climate change of 222,060 papers published between 1980 and 2014. The references cited therein were extracted and analyzed with regard to publications, which are cited most frequently. Second, a new method for establishing a more subject-specific publication set for applying RPYS (based on the co-citations of a marker reference) is proposed (RPYS-CO). The RPYS of the climate change literature focuses on the history of climate change research in total. We identified 35 highly-cited publications across all disciplines, which include fundamental early scientific works of the nineteenth century (with a weak connection to climate change) and some cornerstones of science with a stronger connection to climate change. By using the Arrhenius (Philos Mag J Sci Ser 5(41):237-276, 1896) paper as a RPYS-CO marker paper, we selected only publications specifically discussing the discovery of the greenhouse effect and the role of carbon dioxide. Using different RPYS approaches in this study, we were able to identify the complete range of works of the celebrated icons as well as many less known works relevant for the history of climate change research. The analyses confirmed the potential of the RPYS method for historical studies: Seminal papers are detected on the basis of the references cited by the overall community without any further assumptions.
Impacts of future climate change on river discharge based on hydrological inference: A case study of the Grand River Watershed in Ontario, Canada.

PubMed

Li, Zhong; Huang, Guohe; Wang, Xiuquan; Han, Jingcheng; Fan, Yurui

2016-04-01

Over the recent years, climate change impacts have been increasingly studied at the watershed scale. However, the impact assessment is strongly dependent upon the performance of the climatic and hydrological models. This study developed a two-step method to assess climate change impacts on water resources based on the Providing Regional Climates for Impacts Studies (PRECIS) modeling system and a Hydrological Inference Model (HIM). PRECIS runs provided future temperature and precipitation projections for the watershed under the Intergovernmental Panel on Climate Change SRES A2 and B2 emission scenarios. The HIM based on stepwise cluster analysis is developed to imitate the complex nonlinear relationships between climate input variables and targeted hydrological variables. Its robust mathematical structure and flexibility in predictor selection makes it a desirable tool for fully utilizing various climate modeling outputs. Although PRECIS and HIM cannot fully cover the uncertainties in hydro-climate modeling, they could provide efficient decision support for investigating the impacts of climate change on water resources. The proposed method is applied to the Grand River Watershed in Ontario, Canada. The model performance is demonstrated with comparison to observation data from the watershed during the period 1972-2006. Future river discharge intervals that accommodate uncertainties in hydro-climatic modeling are presented and future river discharge variations are analyzed. The results indicate that even though the total annual precipitation would not change significantly in the future, the inter-annual distribution is very likely to be altered. The water availability is expected to increase in Winter while it is very likely to decrease in Summer over the Grand River Watershed, and adaptation strategies would be necessary. Copyright © 2016 Elsevier B.V. All rights reserved.
Using Probabilistic Methods in Water Scarcity Assessments: A First Step Towards a Water Scarcity Risk Assessment Framework

NASA Technical Reports Server (NTRS)

Veldkamp, Ted; Wada, Yoshihide; Aerts, Jeroen; Ward, Phillip

2016-01-01

Water scarcity -driven by climate change, climate variability, and socioeconomic developments- is recognized as one of the most important global risks, both in terms of likelihood and impact. Whilst a wide range of studies have assessed the role of long term climate change and socioeconomic trends on global water scarcity, the impact of variability is less well understood. Moreover, the interactions between different forcing mechanisms, and their combined effect on changes in water scarcity conditions, are often neglected. Therefore, we provide a first step towards a framework for global water scarcity risk assessments, applying probabilistic methods to estimate water scarcity risks for different return periods under current and future conditions while using multiple climate and socioeconomic scenarios.
Minority Pre-service Teachers' and Faculty Training on Climate Change Education in Delaware State University

NASA Astrophysics Data System (ADS)

Ozbay, G.; Fox-Lykens, R.; Veron, D. E.; Rogers, M.; Merrill, J.; Harcourt, P.; Mead, H.

2015-12-01

Delaware State University is working toward infusing undergraduate education with climate change science and enhancing the climate change learning content of pre-service teacher preparation programs as part of the MADE-CLEAR project (www.madeclear.org). Faculty development workshops have been conducted to prepare and educate a cadre of faculty from different disciplines in global climate science literacy. Following the workshops, the faculty participants have integrated climate literacy tenets into their existing curriculum. Follow up meetings have helped the faculty members to use specific content in their curriculum such as greenhouse gases, atmospheric CO2, sea level rise, etc. Additional training provided to the faculty participants in pedagogical methods of climate change instruction to identify common misconceptions and barriers to student understanding. Some pre-service teachers were engaged in summer internships and learned how to become messenger of climate change science by the state parks staff during the summer. Workshops were offered to other pre-service teachers to teach them specific climate change topics with enhanced hands-on laboratory activities. The participants were provided examples of lesson plans and guided to develop their own lesson plans and present them. Various pedagogical methods have been explored for teaching climate change content to the participants. The pre-service teachers found the climate content very challenging and confusing. Training activities were modified to focus on targeted topics and modeling of pedagogical techniques for the faculty and pre-service teachers. Program evaluation confirms that the workshop participant show improved understanding of the workshop materials by the participants if they were introduced few climate topics. Learning how to use hands-on learning tools and preparing lesson plans are two of the challenges successfully implemented by the pre-service teachers. Our next activity includes pre-service teachers to use their lesson plans to teach the climate change content in the middle school science classes. This will mutually help the middle school science teachers' to learn and use the materials provided by the pre-service teachers and also pre-service teachers' to improve their teaching skills on climate change content.
Investigating the Climate Change Beliefs, Knowledge, Behaviors, and Cultural Worldviews of Rural Middle School Students and their Families During An Out-of-School Intervention: A Mixed-Methods Study

NASA Astrophysics Data System (ADS)

Gutierrez, Kristie Susan

In a recent nationwide survey, 63% of American adults believe that there is global warming, yet 52% received a 'grade' of 'F' on climate change knowledge and beliefs. Climate change is a politically-charged topic in the 21st century. Even for those who support the 97% of scientists who assert that climate change is occurring, many are still uncertain about the role that humans play in this complex process. This mixed-methods study examined the climate change beliefs, content knowledge, worldviews, and behaviors of rural middle school students and their families in four rural, high poverty school districts in the Southeastern United States (US). The students, who ranged from 5-8th grades, were part of an after school STEM Career Club program that met for two hours, six times per semester. STEM Club students (N = 243) and selected students' families (n = 15) interacted with climate change activities and materials in the student clubs and in an at-home intervention. Quantitative pre- and post-intervention surveys were used to measure any changes in climate change content knowledge and beliefs as well as participants' worldviews. Qualitative audio data gathered from at-home intervention activities with students and their family members, as well as during family dyad interviews, was coded using the Determinants of Behavior framework that reflected climate change awareness, during and post-intervention. This embedded mixed-methods design with climate change education was designed to reflect place-based examples in these rural, southeastern US communities, and to empower families to see the relevance of this global issue, consider their role, learn more about climate science, and take actions locally. Initially, a large percentage of students believed that global warming is occurring (69.5%) and is occurring at least in some part due to human influence (69.3%). Students had learned significantly more total climate change knowledge, post-intervention. Analyses of variance (ANOVA) found a significant main effect for gender; males improved significantly more than females on the content knowledge test. Significant gains in content knowledge could be traced to engagement in specific club activities. The vast majority (73.3%) of students held egalitarian worldviews, while students were almost equivalent on the individualism (48.8%) /communitarian (47.7%) worldview scale. Student worldviews correlated to responses on the affective items of the survey, but did not predict students' climate change content knowledge. Findings from this study suggest that significant gains in climate change content knowledge can be attained through short-term out-of-school interventions, but not climate change beliefs. For rural, low income families, knowledge talk was most common (26.6%), followed by discussion of behaviors (11.5%), and talk regarding the seriousness of the problem (10.6%). Seventy-two percent of the participants (n = 18; 9 students, 9 adults) were coded as individualistic egalitarian. Changes in climate change content knowledge from pre- to post-intervention were greatest in the students and parents who were highly engaged in the at-home family intervention, indicating that parents and students can benefit from climate change interventions in their own homes.

Engaging Key Stakeholders in Climate Change: A Community-Based Project for Youth-Led Participatory Climate Action

NASA Astrophysics Data System (ADS)

Trott, Carlie D.

Few studies have examined how youth think about, and take action on climate change and far fewer have sought to facilitate their engagement using participatory methods. This dissertation evaluated the impacts of Science, Camera, Action! (SCA), a novel after-school program that combined climate change education with participatory action through photovoice. The specific aims of this study were to: (1) Evaluate the impacts of SCA on youth participants' climate change knowledge, attitudes, and behaviors; (2) Examine how SCA participation served to empower youth agency; and (3) Explore SCA's influence on youths' science engagement. Participants were 55 youths (ages 10 to 12) across three Boys and Girls Club sites in Northern Colorado. SCA's Science component used interactive activities to demonstrate the interrelationships between Earth's changing climate, ecosystems, and sustainable actions within communities. Photovoice, SCA's Camera component, was used to explore youths' climate change perspectives and to identify opportunities for their active engagement. Finally, SCA's Action component aimed to cultivate youth potential as agents of change in their families and communities through the development and implementation of youth-led action projects. Action projects included local policy advocacy, a tree-planting campaign, a photo gallery opening, development of a website, and the establishment of a Boys and Girls Club community garden. To evaluate SCA impacts, a combination of survey and focus group methods were used. Following the program, youth demonstrated increased knowledge of the scientific and social dimensions of the causes and consequences of climate change, as well as its solutions through human action. Though participants expressed a mix of positive (e.g., hope) and negative (e.g., sadness) emotions about climate change, they left the program with an increased sense of respect for nature, an enhanced sense of environmental responsibility, and a greater sense of urgency towards the need for climate change action. Further, participants reported increased engagement in personal pro-environmental behaviors, an enhanced sense of agency in the context of climate change, and provided strong evidence of their role as agents of change in family and community contexts. Through SCA, participants gained a deeper appreciation for science (e.g., in school, careers, and society) and reported increased interest, participation, confidence, and performance in school science. Findings contribute to the vast and growing psychology literature on climate change perceptions and action, and from the understudied perspective of youth. Through a combination of innovative methods and interactive projects, the youth in this study gained a number of psychosocial and educational benefits, while tangibly contributing to the sustainable transformation of their families and communities. Findings of this dissertation have implications for educational programs, youth organizing, and interventions aimed to strengthen youths' active engagement with critical social and scientific issues that impact their lives.
Polar Bears or People?: How Framing Can Provide a Useful Analytic Tool to Understand & Improve Climate Change Communication in Classrooms

NASA Astrophysics Data System (ADS)

Busch, K. C.

2014-12-01

Not only will young adults bear the brunt of climate change's effects, they are also the ones who will be required to take action - to mitigate and to adapt. The Next Generation Science Standards include climate change, ensuring the topic will be covered in U.S. science classrooms in the near future. Additionally, school is a primary source of information about climate change for young adults. The larger question, though, is how can the teaching of climate change be done in such a way as to ascribe agency - a willingness to act - to students? Framing - as both a theory and an analytic method - has been used to understand how language in the media can affect the audience's intention to act. Frames function as a two-way filter, affecting both the message sent and the message received. This study adapted both the theory and the analytic methods of framing, applying them to teachers in the classroom to answer the research question: How do teachers frame climate change in the classroom? To answer this question, twenty-five lessons from seven teachers were analyzed using semiotic discourse analysis methods. It was found that the teachers' frames overlapped to form two distinct discourses: a Science Discourse and a Social Discourse. The Science Discourse, which was dominant, can be summarized as: Climate change is a current scientific problem that will have profound global effects on the Earth's physical systems. The Social Discourse, used much less often, can be summarized as: Climate change is a future social issue because it will have negative impacts at the local level on people. While it may not be surprising that the Science Discourse was most often heard in these science classrooms, it is possibly problematic if it were the only discourse used. The research literature on framing indicates that the frames found in the Science Discourse - global scale, scientific statistics and facts, and impact on the Earth's systems - are not likely to inspire action-taking. This study indicates that framing may be a useful theory for investigating how climate change is taught and learned in classrooms. In addition, suggestions are made for how to develop effective professional development for teachers to improve their communication of climate change.
Quantifying the relative contribution of climate and human impacts on streamflow at seasonal scale

NASA Astrophysics Data System (ADS)

Xin, Z.; Zhang, L.; Li, Y.; Zhang, C.

2017-12-01

Both climate change and human activities have induced changes to hydrology. The quantification of their impacts on streamflow is a challenge, especially at the seasonal scale due to seasonality of climate and human impacts, i.e., water use for irrigation and water storage and release due to reservoir operation. In this study, the decomposition method based on the Budyko hypothesis is extended to the seasonal scale and is used to quantify the climate and human impacts on annual and seasonal streamflow changes. The results are further compared and verified with those simulated by the hydrological method of abcd model. Data are split into two periods (1953-1974 and 1975-2005) to quantify the change. Three seasons, including wet, dry and irrigation seasons are defined by introducing the monthly aridity index. In general, results showed a satisfactory agreement between the Budyko decomposition method and abcd model. Both climate change and human activities were found to induce a decrease in streamflow at the annual scale, with 67% of the change contributed by human activities. At the seasonal scale, the human-induced contribution to the reduced stream flow was 64% and 73% for dry and wet seasons, respectively; whereas in the irrigation season, the impact of human activities on reducing the streamflow was more pronounced (180%) since the climate contributes to increased streamflow. In addition, the quantification results were analyzed for each month in the wet season to reveal the effects of intense precipitation and reservoir operation rules during flood season.
Using multiple climate projections for assessing hydrological response to climate change in the Thukela River Basin, South Africa

NASA Astrophysics Data System (ADS)

Graham, L. Phil; Andersson, Lotta; Horan, Mark; Kunz, Richard; Lumsden, Trevor; Schulze, Roland; Warburton, Michele; Wilk, Julie; Yang, Wei

This study used climate change projections from different regional approaches to assess hydrological effects on the Thukela River Basin in KwaZulu-Natal, South Africa. Projecting impacts of future climate change onto hydrological systems can be undertaken in different ways and a variety of effects can be expected. Although simulation results from global climate models (GCMs) are typically used to project future climate, different outcomes from these projections may be obtained depending on the GCMs themselves and how they are applied, including different ways of downscaling from global to regional scales. Projections of climate change from different downscaling methods, different global climate models and different future emissions scenarios were used as input to simulations in a hydrological model to assess climate change impacts on hydrology. A total of 10 hydrological change simulations were made, resulting in a matrix of hydrological response results. This matrix included results from dynamically downscaled climate change projections from the same regional climate model (RCM) using an ensemble of three GCMs and three global emissions scenarios, and from statistically downscaled projections using results from five GCMs with the same emissions scenario. Although the matrix of results does not provide complete and consistent coverage of potential uncertainties from the different methods, some robust results were identified. In some regards, the results were in agreement and consistent for the different simulations. For others, particularly rainfall, the simulations showed divergence. For example, all of the statistically downscaled simulations showed an annual increase in precipitation and corresponding increase in river runoff, while the RCM downscaled simulations showed both increases and decreases in runoff. According to the two projections that best represent runoff for the observed climate, increased runoff would generally be expected for this basin in the future. Dealing with such variability in results is not atypical for assessing climate change impacts in Africa and practitioners are faced with how to interpret them. This work highlights the need for additional, well-coordinated regional climate downscaling for the region to further define the range of uncertainties involved.
A Review on Climate Change in Weather Stations of Guilan Province Using Mann-Kendal Methodand GIS

NASA Astrophysics Data System (ADS)

Behzadi, Jalal

2016-07-01

Climate has always been changing during the life time of the earth, and has appeared in the form of ice age, hurricanes, severe and sudden temperature changes, precipitation and other climatic elements, and has dramatically influenced the environment, and in some cases has caused severe changes and even destructions. Some of the most important aspects of climate changes can be found in precipitation types of different regions in the world and especially Guilan, which is influenced by drastic land conversions and greenhouse gases. Also, agriculture division, industrial activities and unnecessary land conversions are thought to have a huge influence on climate change. Climate change is a result of abnormalcies of metorologyl parameters. Generally, the element of precipitation is somehow included in most theories about climate change. The present study aims to reveal precipitation abnormalcies in Guilan which lead to climate change, and possible deviations of precipitation parameter based on annual, seasonal and monthly series have been evaluated. The Mann-Kendal test has been used to reveal likely deviations leading to climate change. The trend of precipitation changes in long-term has been identifiedusing this method. Also, the beginning and end of these changes have been studied in five stations as representatives of all the thirteen weather stations. Then,the areas which have experienced climate change have been identified using the GIS software along with the severity of the changes with an emphasis on drought. These results can be used in planning and identifying the effects of these changes on the environment. Keywords: Climate Change, Guilan, Mann-Kendal, GIS
Dominant climatic factors driving annual runoff changes at the catchment scale across China

NASA Astrophysics Data System (ADS)

Huang, Zhongwei; Yang, Hanbo; Yang, Dawen

2016-07-01

With global climate changes intensifying, the hydrological response to climate changes has attracted more attention. It is beneficial not only for hydrology and ecology but also for water resource planning and management to understand the impact of climate change on runoff. In addition, there are large spatial variations in climate type and geographic characteristics across China. To gain a better understanding of the spatial variation of the response of runoff to changes in climatic factors and to detect the dominant climatic factors driving changes in annual runoff, we chose the climate elasticity method proposed by Yang and Yang (2011). It is shown that, in most catchments of China, increasing air temperature and relative humidity have negative impacts on runoff, while declining net radiation and wind speed have positive impacts on runoff, which slow the overall decline in runoff. The dominant climatic factors driving annual runoff are precipitation in most parts of China, net radiation mainly in some catchments of southern China, air temperature and wind speed mainly in some catchments in northern China.
Statistical bias correction method applied on CMIP5 datasets over the Indian region during the summer monsoon season for climate change applications

NASA Astrophysics Data System (ADS)

Prasanna, V.

2018-01-01

This study makes use of temperature and precipitation from CMIP5 climate model output for climate change application studies over the Indian region during the summer monsoon season (JJAS). Bias correction of temperature and precipitation from CMIP5 GCM simulation results with respect to observation is discussed in detail. The non-linear statistical bias correction is a suitable bias correction method for climate change data because it is simple and does not add up artificial uncertainties to the impact assessment of climate change scenarios for climate change application studies (agricultural production changes) in the future. The simple statistical bias correction uses observational constraints on the GCM baseline, and the projected results are scaled with respect to the changing magnitude in future scenarios, varying from one model to the other. Two types of bias correction techniques are shown here: (1) a simple bias correction using a percentile-based quantile-mapping algorithm and (2) a simple but improved bias correction method, a cumulative distribution function (CDF; Weibull distribution function)-based quantile-mapping algorithm. This study shows that the percentile-based quantile mapping method gives results similar to the CDF (Weibull)-based quantile mapping method, and both the methods are comparable. The bias correction is applied on temperature and precipitation variables for present climate and future projected data to make use of it in a simple statistical model to understand the future changes in crop production over the Indian region during the summer monsoon season. In total, 12 CMIP5 models are used for Historical (1901-2005), RCP4.5 (2005-2100), and RCP8.5 (2005-2100) scenarios. The climate index from each CMIP5 model and the observed agricultural yield index over the Indian region are used in a regression model to project the changes in the agricultural yield over India from RCP4.5 and RCP8.5 scenarios. The results revealed a better convergence of model projections in the bias corrected data compared to the uncorrected data. The study can be extended to localized regional domains aimed at understanding the changes in the agricultural productivity in the future with an agro-economy or a simple statistical model. The statistical model indicated that the total food grain yield is going to increase over the Indian region in the future, the increase in the total food grain yield is approximately 50 kg/ ha for the RCP4.5 scenario from 2001 until the end of 2100, and the increase in the total food grain yield is approximately 90 kg/ha for the RCP8.5 scenario from 2001 until the end of 2100. There are many studies using bias correction techniques, but this study applies the bias correction technique to future climate scenario data from CMIP5 models and applied it to crop statistics to find future crop yield changes over the Indian region.
Applying a simple water-energy balance framework to predict the climate sensitivity of streamflow over the continental United States

NASA Astrophysics Data System (ADS)

Renner, M.; Bernhofer, C.

2011-12-01

The prediction of climate effects on terrestrial ecosystems and water resources is one of the major research questions in hydrology. Conceptual water-energy balance models can be used to gain a first order estimate of how long-term average streamflow is changing with a change in water and energy supply. A common framework for investigation of this question is based on the Budyko hypothesis, which links hydrological response to aridity. Recently, Renner et al. (2011) introduced the CCUW hypothesis, which is based on the assumption that the total efficiency of the catchment ecosystem to use the available water and energy for actual evapotranspiration remains constant even under climate changes. Here, we confront the climate sensitivity approaches (including several versions of Budyko's approach and the CCUW) with data of more than 400 basins distributed over the continental United States. We first map an estimate of the sensitivity of streamflow to changes in precipitation using long-term average data of the period 1949-2003. This provides a hydro-climatic status of the respective basins as well as their expected proportional effect on changes in climate. Next, by splitting the data in two periods, we (i) analyse the long-term average changes in hydro-climatolgy, we (ii) use the different climate sensitivity methods to predict the change in streamflow given the observed changes in water and energy supply and (iii) we apply a quantitative approach to separate the impacts of changes in the long-term average climate from basin characteristics change on streamflow. This allows us to evaluate the observed changes in streamflow as well as to evaluate the impact of basin changes on the validity of climate sensitivity approaches. The apparent increase of streamflow in the majority of basins in the US is dominated by a climate trend towards increased humidity. It is further evident that impacts of changes in basin characteristics appear in parallel with climate changes. There are coherent spatial patterns with basins of increasing catchment efficiency being dominant in the western and central parts of the US. A hot spot of decreasing efficiency is found within the US Midwest. The impact of basin changes on the prediction is large and can be twice as the observed change signal. However, we find that both, the CCUW hypothesis and the approaches using the Budyko hypothesis, show minimal deviations between observed and predicted changes in streamflow for basins where a dominance of climatic changes and low influences of basin changes have been found. Thus, climate sensitivity methods can be regarded as valid tools if we expect climate changes only and neglect any direct anthropogenic influences.
Experiment, monitoring, and gradient methods used to infer climate change effects on plant communities yield consistent patterns

Treesearch

Sarah C. Elmendorf; Gregory H.R. Henry; Robert D. Hollisterd; Anna Maria Fosaa; William A. Gould; Luise Hermanutz; Annika Hofgaard; Ingibjorg I. Jonsdottir; Janet C. Jorgenson; Esther Levesque; Borgbor Magnusson; Ulf Molau; Isla H. Myers-Smith; Steven F. Oberbauer; Christian Rixen; Craig E. Tweedie; Marilyn Walkers

2015-01-01

Inference about future climate change impacts typically relies on one of three approaches: manipulative experiments, historical comparisons (broadly defined to include monitoring the response to ambient climate fluctuations using repeat sampling of plots, dendroecology, and paleoecology techniques), and space-for-time substitutions derived from sampling along...
A Review of Quantitative Methods for Evaluating Impacts of Climate Change on Urban Water Infrastructure

EPA Science Inventory

It is widely accepted that global climate change will impact the regional and local climate and alter some aspects of the hydrologic cycle, which in turn can affect the performance of the urban water supply, wastewater and storm water infrastructur4e. How the urban water infrastr...
Combining analytical frameworks to assess livelihood vulnerability to climate change and analyse adaptation options.

PubMed

Reed, M S; Podesta, G; Fazey, I; Geeson, N; Hessel, R; Hubacek, K; Letson, D; Nainggolan, D; Prell, C; Rickenbach, M G; Ritsema, C; Schwilch, G; Stringer, L C; Thomas, A D

2013-10-01

Experts working on behalf of international development organisations need better tools to assist land managers in developing countries maintain their livelihoods, as climate change puts pressure on the ecosystem services that they depend upon. However, current understanding of livelihood vulnerability to climate change is based on a fractured and disparate set of theories and methods. This review therefore combines theoretical insights from sustainable livelihoods analysis with other analytical frameworks (including the ecosystem services framework, diffusion theory, social learning, adaptive management and transitions management) to assess the vulnerability of rural livelihoods to climate change. This integrated analytical framework helps diagnose vulnerability to climate change, whilst identifying and comparing adaptation options that could reduce vulnerability, following four broad steps: i) determine likely level of exposure to climate change, and how climate change might interact with existing stresses and other future drivers of change; ii) determine the sensitivity of stocks of capital assets and flows of ecosystem services to climate change; iii) identify factors influencing decisions to develop and/or adopt different adaptation strategies, based on innovation or the use/substitution of existing assets; and iv) identify and evaluate potential trade-offs between adaptation options. The paper concludes by identifying interdisciplinary research needs for assessing the vulnerability of livelihoods to climate change.
Combining analytical frameworks to assess livelihood vulnerability to climate change and analyse adaptation options☆

PubMed Central

Reed, M.S.; Podesta, G.; Fazey, I.; Geeson, N.; Hessel, R.; Hubacek, K.; Letson, D.; Nainggolan, D.; Prell, C.; Rickenbach, M.G.; Ritsema, C.; Schwilch, G.; Stringer, L.C.; Thomas, A.D.

2013-01-01

Experts working on behalf of international development organisations need better tools to assist land managers in developing countries maintain their livelihoods, as climate change puts pressure on the ecosystem services that they depend upon. However, current understanding of livelihood vulnerability to climate change is based on a fractured and disparate set of theories and methods. This review therefore combines theoretical insights from sustainable livelihoods analysis with other analytical frameworks (including the ecosystem services framework, diffusion theory, social learning, adaptive management and transitions management) to assess the vulnerability of rural livelihoods to climate change. This integrated analytical framework helps diagnose vulnerability to climate change, whilst identifying and comparing adaptation options that could reduce vulnerability, following four broad steps: i) determine likely level of exposure to climate change, and how climate change might interact with existing stresses and other future drivers of change; ii) determine the sensitivity of stocks of capital assets and flows of ecosystem services to climate change; iii) identify factors influencing decisions to develop and/or adopt different adaptation strategies, based on innovation or the use/substitution of existing assets; and iv) identify and evaluate potential trade-offs between adaptation options. The paper concludes by identifying interdisciplinary research needs for assessing the vulnerability of livelihoods to climate change. PMID:25844020
Impacts of climate change and human activities on runoff in Weihe Basin based on Budyko hypothesis

NASA Astrophysics Data System (ADS)

Wu, H. S.; Liu, D. F.; Chang, J. X.; Zhang, H. X.; Huang, Q.

2017-08-01

The Weihe River Basin (WRB) is the largest tributary of the Yellow River and plays an irreplaceable role in the Shaanxi-Gansu-Ningxia area. In recent years, owing to the human activities and climate change, the runoff of the WRB has reduced, wherefore, it is necessary to analyze the impact on runoff quantitatively. By using the data of Huaxian and Zhuangtou stations, we can respectively calculate the changes in runoff for climate change and human activities via Budyko hypothesis. The trend of runoff, precipitation, temperature, potential evapotranspiration and the break points are examined by Mann-Kendall test (M-K method), cumulative anomaly method and ordered cluster analysis. The results show that the break points of runoff series in WRB are 1970 and 1989, so that the runoff series can be divided into the baseline period and the changed period. Based on the data of potential evapotranspiration and Budyko formula, the contribution rates of climate change and human activities to runoff are 41% and 59% in 1970-1989. From 1990 to 2010, the contribution rates of climate change and human activities are 37% and 63%, respectively.
Developing an approach to effectively use super ensemble experiments for the projection of hydrological extremes under climate change

NASA Astrophysics Data System (ADS)

Watanabe, S.; Kim, H.; Utsumi, N.

2017-12-01

This study aims to develop a new approach which projects hydrology under climate change using super ensemble experiments. The use of multiple ensemble is essential for the estimation of extreme, which is a major issue in the impact assessment of climate change. Hence, the super ensemble experiments are recently conducted by some research programs. While it is necessary to use multiple ensemble, the multiple calculations of hydrological simulation for each output of ensemble simulations needs considerable calculation costs. To effectively use the super ensemble experiments, we adopt a strategy to use runoff projected by climate models directly. The general approach of hydrological projection is to conduct hydrological model simulations which include land-surface and river routing process using atmospheric boundary conditions projected by climate models as inputs. This study, on the other hand, simulates only river routing model using runoff projected by climate models. In general, the climate model output is systematically biased so that a preprocessing which corrects such bias is necessary for impact assessments. Various bias correction methods have been proposed, but, to the best of our knowledge, no method has proposed for variables other than surface meteorology. Here, we newly propose a method for utilizing the projected future runoff directly. The developed method estimates and corrects the bias based on the pseudo-observation which is a result of retrospective offline simulation. We show an application of this approach to the super ensemble experiments conducted under the program of Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI). More than 400 ensemble experiments from multiple climate models are available. The results of the validation using historical simulations by HAPPI indicates that the output of this approach can effectively reproduce retrospective runoff variability. Likewise, the bias of runoff from super ensemble climate projections is corrected, and the impact of climate change on hydrologic extremes is assessed in a cost-efficient way.
Impacts of climate change on current methodologies for flood risk analysis: Watershed-scale analyses using the Soil and Water Assessment Tool (SWAT)

NASA Astrophysics Data System (ADS)

Spellman, P.; Griffis, V. W.; LaFond, K.

2013-12-01

A changing climate brings about new challenges for flood risk analysis and water resources planning and management. Current methods for estimating flood risk in the US involve fitting the Pearson Type III (P3) probability distribution to the logarithms of the annual maximum flood (AMF) series using the method of moments. These methods are employed under the premise of stationarity, which assumes that the fitted distribution is time invariant and variables affecting stream flow such as climate do not fluctuate. However, climate change would bring about shifts in meteorological forcings which can alter the summary statistics (mean, variance, skew) of flood series used for P3 parameter estimation, resulting in erroneous flood risk projections. To ascertain the degree to which future risk may be misrepresented by current techniques, we use climate scenarios generated from global climate models (GCMs) as input to a hydrological model to explore how relative changes to current climate affect flood response for watersheds in the northeastern United States. The watersheds were calibrated and run on a daily time step using the continuous, semi-distributed, process based Soil and Water Assessment Tool (SWAT). Nash Sutcliffe Efficiency (NSE), RMSE to Standard Deviation ratio (RSR) and Percent Bias (PBIAS) were all used to assess model performance. Eight climate scenarios were chosen from GCM output based on relative precipitation and temperature changes from the current climate of the watershed and then further bias-corrected. Four of the scenarios were selected to represent warm-wet, warm-dry, cool-wet and cool-dry future climates, and the other four were chosen to represent more extreme, albeit possible, changes in precipitation and temperature. We quantify changes in response by comparing the differences in total mass balance and summary statistics of the logarithms of the AMF series from historical baseline values. We then compare forecasts of flood quantiles from fitting a P3 distribution to the logs of historical AMF data to that of generated AMF series.
A data centred method to estimate and map how the local distribution of daily precipitation is changing

NASA Astrophysics Data System (ADS)

Chapman, Sandra; Stainforth, David; Watkins, Nick

2014-05-01

Estimates of how our climate is changing are needed locally in order to inform adaptation planning decisions. This requires quantifying the geographical patterns in changes at specific quantiles in distributions of variables such as daily temperature or precipitation. Here we focus on these local changes and on a method to transform daily observations of precipitation into patterns of local climate change. We develop a method[1] for analysing local climatic timeseries to assess which quantiles of the local climatic distribution show the greatest and most robust changes, to specifically address the challenges presented by daily precipitation data. We extract from the data quantities that characterize the changes in time of the likelihood of daily precipitation above a threshold and of the relative amount of precipitation in those days. Our method is a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of how fast different quantiles of precipitation distributions are changing. This involves both determining which quantiles and geographical locations show the greatest change but also, those at which any change is highly uncertain. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily precipitation from specific locations across Europe over the last 60 years. We treat geographical location and precipitation as independent variables and thus obtain as outputs the pattern of change at a given threshold of precipitation and with geographical location. This is model- independent, thus providing data of direct value in model calibration and assessment. Our results show regionally consistent patterns of systematic increase in precipitation on the wettest days, and of drying across all days which is of potential value in adaptation planning. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, 371 20120287; D. A. Stainforth, 2013, S. C. Chapman, N. W. Watkins, Mapping climate change in European temperature distributions, Environ. Res. Lett. 8, 034031 [2] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119
Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed

EPA Pesticide Factsheets

Changes in climate and land cover are among the principal variables affecting watershed hydrology.This paper uses a cell-based model to examine the hydrologic impacts of climate and land-cover changes in thesemi-arid Lower Virgin River (LVR) watershed located upstream of Lake Mead, Nevada, USA. The cell-basedmodel is developed by considering direct runoff based on the Soil Conservation Service - Curve Number (SCSCN)method and surplus runoff based on the Thornthwaite water balance theory. After calibration and validation,the model is used to predict LVR discharge under future climate and land-cover changes. The hydrologicsimulation results reveal climate change as the dominant factor and land-cover change as a secondary factor inregulating future river discharge. The combined effects of climate and land-cover changes will slightly increaseriver discharge in summer but substantially decrease discharge in winter. This impact on water resources deservesattention in climate change adaptation planning.This dataset is associated with the following publication:Chen, H., S. Tong, H. Yang, and J. Yang. Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed. Hydrological Sciences Journal. IAHS LIMITED, Oxford, UK, 60(10): 1739-1758, (2015).
Assessing response of sediment load variation to climate change and human activities with six different approaches.

PubMed

Zhao, Guangju; Mu, Xingmin; Jiao, Juying; Gao, Peng; Sun, Wenyi; Li, Erhui; Wei, Yanhong; Huang, Jiacong

2018-05-23

Understanding the relative contributions of climate change and human activities to variations in sediment load is of great importance for regional soil, and river basin management. Considerable studies have investigated spatial-temporal variation of sediment load within the Loess Plateau; however, contradictory findings exist among methods used. This study systematically reviewed six quantitative methods: simple linear regression, double mass curve, sediment identity factor analysis, dam-sedimentation based method, the Sediment Delivery Distributed (SEDD) model, and the Soil Water Assessment Tool (SWAT) model. The calculation procedures and merits for each method were systematically explained. A case study in the Huangfuchuan watershed on the northern Loess Plateau has been undertaken. The results showed that sediment load had been reduced by 70.5% during the changing period from 1990 to 2012 compared to that of the baseline period from 1955 to 1989. Human activities accounted for an average of 93.6 ± 4.1% of the total decline in sediment load, whereas climate change contributed 6.4 ± 4.1%. Five methods produced similar estimates, but the linear regression yielded relatively different results. The results of this study provide a good reference for assessing the effects of climate change and human activities on sediment load variation by using different methods. Copyright © 2018. Published by Elsevier B.V.
Refugia Research Coalition: A regional-scale approach for connecting refugia science to natural and cultural resource management

EPA Science Inventory

Background / question / methods Warmer air and water temperatures, changing precipitation patterns, and altered fire regimes associated with climate change threaten many important natural and cultural resources. Climate change refugia are areas relatively buffered from contempora...
Mixed methods approach to understanding farmer and agricultural advisor perceptions of climate change and adaptation in Vermont, United States

Treesearch

Rachel E. Schattman; V. Ernesto Méndez; Scott C. Merrill; Asim Zia

2018-01-01

The relationships among farmers' belief in climate change, perceptions of climate-related risk, and use of climate adaptation practices is a growing topic of interest in U.S. scholarship. The northeast region is not well represented in the literature, although it is highly agricultural and will likely face climaterelated risks that differ from those faced in other...

The Relative Impact of Climate Change on the Extinction Risk of Tree Species in the Montane Tropical Andes.

PubMed

Tejedor Garavito, Natalia; Newton, Adrian C; Golicher, Duncan; Oldfield, Sara

2015-01-01

There are widespread concerns that anthropogenic climate change will become a major cause of global biodiversity loss. However, the potential impact of climate change on the extinction risk of species remains poorly understood, particularly in comparison to other current threats. The objective of this research was to examine the relative impact of climate change on extinction risk of upper montane tree species in the tropical Andes, an area of high biodiversity value that is particularly vulnerable to climate change impacts. The extinction risk of 129 tree species endemic to the region was evaluated according to the IUCN Red List criteria, both with and without the potential impacts of climate change. Evaluations were supported by development of species distribution models, using three methods (generalized additive models, recursive partitioning, and support vector machines), all of which produced similarly high AUC values when averaged across all species evaluated (0.82, 0.86, and 0.88, respectively). Inclusion of climate change increased the risk of extinction of 18-20% of the tree species evaluated, depending on the climate scenario. The relative impact of climate change was further illustrated by calculating the Red List Index, an indicator that shows changes in the overall extinction risk of sets of species over time. A 15% decline in the Red List Index was obtained when climate change was included in this evaluation. While these results suggest that climate change represents a significant threat to tree species in the tropical Andes, they contradict previous suggestions that climate change will become the most important cause of biodiversity loss in coming decades. Conservation strategies should therefore focus on addressing the multiple threatening processes currently affecting biodiversity, rather than focusing primarily on potential climate change impacts.
Vulnerability of European freshwater catchments to climate change.

PubMed

Markovic, Danijela; Carrizo, Savrina F; Kärcher, Oskar; Walz, Ariane; David, Jonathan N W

2017-09-01

Climate change is expected to exacerbate the current threats to freshwater ecosystems, yet multifaceted studies on the potential impacts of climate change on freshwater biodiversity at scales that inform management planning are lacking. The aim of this study was to fill this void through the development of a novel framework for assessing climate change vulnerability tailored to freshwater ecosystems. The three dimensions of climate change vulnerability are as follows: (i) exposure to climate change, (ii) sensitivity to altered environmental conditions and (iii) resilience potential. Our vulnerability framework includes 1685 freshwater species of plants, fishes, molluscs, odonates, amphibians, crayfish and turtles alongside key features within and between catchments, such as topography and connectivity. Several methodologies were used to combine these dimensions across a variety of future climate change models and scenarios. The resulting indices were overlaid to assess the vulnerability of European freshwater ecosystems at the catchment scale (18 783 catchments). The Balkan Lakes Ohrid and Prespa and Mediterranean islands emerge as most vulnerable to climate change. For the 2030s, we showed a consensus among the applied methods whereby up to 573 lake and river catchments are highly vulnerable to climate change. The anthropogenic disruption of hydrological habitat connectivity by dams is the major factor reducing climate change resilience. A gap analysis demonstrated that the current European protected area network covers <25% of the most vulnerable catchments. Practical steps need to be taken to ensure the persistence of freshwater biodiversity under climate change. Priority should be placed on enhancing stakeholder cooperation at the major basin scale towards preventing further degradation of freshwater ecosystems and maintaining connectivity among catchments. The catchments identified as most vulnerable to climate change provide preliminary targets for development of climate change conservation management and mitigation strategies. © 2017 John Wiley & Sons Ltd.
The Relative Impact of Climate Change on the Extinction Risk of Tree Species in the Montane Tropical Andes

PubMed Central

Tejedor Garavito, Natalia; Newton, Adrian C.; Golicher, Duncan; Oldfield, Sara

2015-01-01

There are widespread concerns that anthropogenic climate change will become a major cause of global biodiversity loss. However, the potential impact of climate change on the extinction risk of species remains poorly understood, particularly in comparison to other current threats. The objective of this research was to examine the relative impact of climate change on extinction risk of upper montane tree species in the tropical Andes, an area of high biodiversity value that is particularly vulnerable to climate change impacts. The extinction risk of 129 tree species endemic to the region was evaluated according to the IUCN Red List criteria, both with and without the potential impacts of climate change. Evaluations were supported by development of species distribution models, using three methods (generalized additive models, recursive partitioning, and support vector machines), all of which produced similarly high AUC values when averaged across all species evaluated (0.82, 0.86, and 0.88, respectively). Inclusion of climate change increased the risk of extinction of 18–20% of the tree species evaluated, depending on the climate scenario. The relative impact of climate change was further illustrated by calculating the Red List Index, an indicator that shows changes in the overall extinction risk of sets of species over time. A 15% decline in the Red List Index was obtained when climate change was included in this evaluation. While these results suggest that climate change represents a significant threat to tree species in the tropical Andes, they contradict previous suggestions that climate change will become the most important cause of biodiversity loss in coming decades. Conservation strategies should therefore focus on addressing the multiple threatening processes currently affecting biodiversity, rather than focusing primarily on potential climate change impacts. PMID:26177097
Assessment of hi-resolution multi-ensemble statistical downscaling regional climate scenarios over Japan

NASA Astrophysics Data System (ADS)

Dairaku, K.

2017-12-01

The Asia-Pacific regions are increasingly threatened by large scale natural disasters. Growing concerns that loss and damages of natural disasters are projected to further exacerbate by climate change and socio-economic change. Climate information and services for risk assessments are of great concern. Fundamental regional climate information is indispensable for understanding changing climate and making decisions on when and how to act. To meet with the needs of stakeholders such as National/local governments, spatio-temporal comprehensive and consistent information is necessary and useful for decision making. Multi-model ensemble regional climate scenarios with 1km horizontal grid-spacing over Japan are developed by using CMIP5 37 GCMs (RCP8.5) and a statistical downscaling (Bias Corrected Spatial Disaggregation (BCSD)) to investigate uncertainty of projected change associated with structural differences of the GCMs for the periods of historical climate (1950-2005) and near future climate (2026-2050). Statistical downscaling regional climate scenarios show good performance for annual and seasonal averages for precipitation and temperature. The regional climate scenarios show systematic underestimate of extreme events such as hot days of over 35 Celsius and annual maximum daily precipitation because of the interpolation processes in the BCSD method. Each model projected different responses in near future climate because of structural differences. The most of CMIP5 37 models show qualitatively consistent increase of average and extreme temperature and precipitation. The added values of statistical/dynamical downscaling methods are also investigated for locally forced nonlinear phenomena, extreme events.
Awakening the Scientist Inside: Global Climate Change and the Nature of Science in an Elementary Science Methods Course

ERIC Educational Resources Information Center

Matkins, Juanita Jo; Bell, Randy L.

2007-01-01

This investigation assessed the impact of situating explicit nature of science (NOS) instruction within the issues surrounding global climate change and global warming (GCC/GW). Participants in the study were 15 preservice elementary teachers enrolled in a science methods course. The instructional intervention included explicit NOS instruction…
Environmental Adult Education for Mitigating the Impacts of Climate Change on Crop Production and Fish Farming in Rivers State of Nigeria

ERIC Educational Resources Information Center

Eheazu, Caroline L.; Ezeala, Joy I.

2017-01-01

The threats of climate change to human society and natural ecosystems have become a devastating environmental problem for crop production and fish farming in Nigeria. This is partly because farmers and fisher folk are known to adopt age-old methods that do not counter current global warming and climate change effects. The purpose of this study was…
Climate analogues suggest limited potential for intensification of production on current croplands under climate change

PubMed Central

Pugh, T.A.M.; Müller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-01-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand. PMID:27646707
Climate Analogues Suggest Limited Potential for Intensification of Production on Current Croplands Under Climate Change

NASA Technical Reports Server (NTRS)

Pugh, T. A. M.; Mueller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-01-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.
Climate analogues suggest limited potential for intensification of production on current croplands under climate change

NASA Astrophysics Data System (ADS)

Pugh, T. A. M.; Müller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-09-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.
Assessment of climate impacts on the karst-related carbon sink in SW China using MPD and GIS

NASA Astrophysics Data System (ADS)

Zeng, Sibo; Jiang, Yongjun; Liu, Zaihua

2016-09-01

Riverine carbon fluxes of some catchments in the world have significantly changed due to contemporary climate change and human activities. As a large region with an extensive karstic area of nearly 7.5 × 105 km2, Southwest (SW) China has experienced dramatic climate changes during recent decades. Although some studies have investigated the karst-related carbon sink in some parts of this region, the importance of climate impacts have not been assessed. This research examined the impacts of recent climate change on the karst-related carbon sink in the SW China for the period 1970-2013, using a modified maximal potential dissolution (MPD) method and GIS. We first analyzed the major determinants of carbonate dissolution at a spatial scale, calculated the total karst-related carbon sink (TCS) and carbon sink fluxes (CSFs) in the SW China karst region with different types of carbonate rocks, and then compared with other methods, and analyzed the causes of CSFs variations under the changed climate conditions. The results show that the TCS in SW China experienced a dramatic change with regional climate, and there was a trend with TCS decreasing by about 19% from 1970s to 2010s. This decrease occurred mostly in Guizhou and Yunnan provinces, which experienced larger decreases in runoff depth in the past 40 years (190 mm and 90 mm, respectively) due to increased air temperature (0.33 °C and 1.04 °C, respectively) and decreased precipitation (156 mm and 106 mm, respectively). The mean value of CSFs in SW China, calculated by the modified MPD method, was approximately 9.36 t C km- 2 a- 1. In addition, there were large differences in CSFs among the provinces, attributed to differences in regional climate and to carbonate lithologies. These spatiotemporal changes depended mainly on hydrological variations (i.e., discharge or runoff depth). This work, thus, suggests that the karst-related carbon sink could respond to future climate change quickly, and needs to be considered in the modern global carbon cycle model.
Climate Reconstructions of the Younger Dryas: An ELA Model Investigating Variability in ELA Depressions, Temperature, and Precipitation Changes for the Graubϋnden Alps

NASA Astrophysics Data System (ADS)

Keeler, D. G.; Rupper, S.; Schaefer, J. M.; Finkel, R. C.

2015-12-01

The high sensitivity of mountain glaciers to even small perturbations in climate, combined with a near global distribution, make alpine glaciers an important target for terrestrial paleoclimate reconstructions. The geomorphic remnant of past glaciers can yield important insights into past climate, particularly in regions where other methods of reconstruction are not possible. The quantitative conversion of these changes in geomorphology to a climate signal, however, presents a significant challenge. A particular need exists for a versatile climate reconstruction method applicable to diverse glacierized regions around the globe. Because the glacier equilibrium line altitude (ELA) provides a more explicit comparison of climate than properties such as glacier length or area, ELA methods lend themselves well to such a need, and allow for a more direct investigation of the primary drivers of mountain glaciations during specific events. Here, we present an ELA model for quantifying changes in climate based on changes in glacier extent, while accounting for differences in glacier width, glacier shape, bed topography, ice thickness, and glacier length. The model furthermore provides bounds on the ΔELA using Monte Carlo simulations. These methods are validated using published mass balances and ELA measurements from 4 modern glaciers in the European Alps. We then use this ELA model, combined with a surface mass and energy balance model, to estimate the changes in temperature/precipitation between the Younger Dryas (constrained by 10Be surface exposure ages) and the present day for three glacier systems in the Graubϋnden Alps. Our results indicate an ELA depression in this area of 257 m ±45 m during the Younger Dryas (YD) relative to today. This corresponds to a 1.3 °C ±0.36 °C decrease in temperature or a 156% ±30% increase in precipitation relative to today. These results indicate the likelihood of a predominantly temperature-driven change rather than a strong dependence on precipitation. We apply these same methods to additional areas around the globe to obtain preliminary, self-consistent estimates of temperature/precipitation for multiple regions. These methods and results enhance our understanding of the global and regional patterns in the climate system during the YD.
Assessment of Climate Change Impacts on Agricultural Water Demands and Crop Yields in California's Central Valley

NASA Astrophysics Data System (ADS)

Tansey, M. K.; Flores-Lopez, F.; Young, C. A.; Huntington, J. L.

2012-12-01

Long term planning for the management of California's water resources requires assessment of the effects of future climate changes on both water supply and demand. Considerable progress has been made on the evaluation of the effects of future climate changes on water supplies but less information is available with regard to water demands. Uncertainty in future climate projections increases the difficulty of assessing climate impacts and evaluating long range adaptation strategies. Compounding the uncertainty in the future climate projections is the fact that most readily available downscaled climate projections lack sufficient meteorological information to compute evapotranspiration (ET) by the widely accepted ASCE Penman-Monteith (PM) method. This study addresses potential changes in future Central Valley water demands and crop yields by examining the effects of climate change on soil evaporation, plant transpiration, growth and yield for major types of crops grown in the Central Valley of California. Five representative climate scenarios based on 112 bias corrected spatially downscaled CMIP 3 GCM climate simulations were developed using the hybrid delta ensemble method to span a wide range future climate uncertainty. Analysis of historical California Irrigation Management Information System meteorological data was combined with several meteorological estimation methods to compute future solar radiation, wind speed and dew point temperatures corresponding to the GCM projected temperatures and precipitation. Future atmospheric CO2 concentrations corresponding to the 5 representative climate projections were developed based on weighting IPCC SRES emissions scenarios. The Land, Atmosphere, and Water Simulator (LAWS) model was used to compute ET and yield changes in the early, middle and late 21st century for 24 representative agricultural crops grown in the Sacramento, San Joaquin and Tulare Lake basins. Study results indicate that changes in ET and yield vary between crops due to plant specific sensitivities to temperature, solar radiation and the vapor pressure deficits. Shifts in the growth period to earlier in the year, shortened growth period for annual crops as well as extended fall growth can also exert important influences. Projected increases in CO2 concentrations in the late 21st century exert very significant influences on ET and yield for many crops. To characterize potential impacts and the range of uncertainty, changes in total agricultural water demands and yields were computed assuming that current crop types and acreages in 21 Central Valley regional planning areas remained constant throughout the 21st century for each of the 5 representative future climate scenarios.
Precipitation Indices as a Tool for Climate-Resilient Development in the Peruvian Andes

NASA Astrophysics Data System (ADS)

Chisolm, R. E.; McKinney, D. C.

2016-12-01

The local people living in the mountains of the Ancash Department in Peru have noticed changes in their water supply as climate change has altered precipitation patterns. They are seeking adaptation solutions to help guarantee the reliability of their water supply, but there has been very little analysis of historical data to evaluate and justify these adaptation solutions. In addition, Peru's Ministry of Economy and Finance now requires that climate change be part of the vulnerability assessment for all public investment project proposals, but there are currently no tools or methods of data analysis for including climate change in vulnerability assessments. Compounding the difficulties of considering climate change in the sustainability of development projects is the scarcity of climate data in the region and the difficulty of accessing existing data. To counteract this problem, the Peruvian government recommends using local people's perceptions of change as a proxy for gauged climate data. This work focuses on precipitation data analysis in the mountains of Ancash, Peru. The objectives of this analysis were to determine the accuracy of the local population's perceptions of climate change and to investigate how changes in precipitation patterns might impact public investment projects. The precipitation data analysis was compared to a local study of perceptions of change to determine whether or not these perceptions might be used in lieu of gauged climate data. It appears that people's perceptions of precipitation trends do not accurately reflect the trends observed in the gauged data. The methods of analysis were designed so that the results may be useful for public investment projects with a particular emphasis on agricultural projects. The data were analyzed for trends, seasonal patterns and variability. Dry spells were examined, and the results indicate that droughts during the rainy season have become more frequent and of longer duration. This could have significant impact on agricultural projects. It is likely that the current practice of relying exclusively on wet season rainfall to meet crop water requirements may not be sustainable in the future. Further analysis of climate data is needed to generate a regional climatic characterization that can be used for climate-resilient development projects.
Methods of teaching the physics of climate change in undergraduate physics courses

NASA Astrophysics Data System (ADS)

Sadler, Michael

2015-04-01

Although anthropogenic climate change is generally accepted in the scientific community, there is considerable skepticism among the general population and, therefore, in undergraduate students of all majors. Students are often asked by their peers, family members, and others, whether they ``believe'' climate change is occurring and what should be done about it (if anything). I will present my experiences and recommendations for teaching the physics of climate change to both physics and non-science majors. For non-science majors, the basic approach is to try to develop an appreciation for the scientific method (particularly peer-reviewed research) in a course on energy and the environment. For physics majors, the pertinent material is normally covered in their undergraduate courses in modern physics and thermodynamics. Nevertheless, it helps to review the basics, e.g. introductory quantum mechanics (discrete energy levels of atomic systems), molecular spectroscopy, and blackbody radiation. I have done this in a separate elective topics course, titled ``Physics of Climate Change,'' to help the students see how their knowledge gives them insight into a topic that is very volatile (socially and politically).
Characterizing the Sensitivity of Groundwater Storage to Climate variation in the Indus Basin

NASA Astrophysics Data System (ADS)

Huang, L.; Sabo, J. L.

2017-12-01

Indus Basin represents an extensive groundwater aquifer facing the challenge of effective management of limited water resources. Groundwater storage is one of the most important variables of water balance, yet its sensitivity to climate change has rarely been explored. To better estimate present and future groundwater storage and its sensitivity to climate change in the Indus Basin, we analyzed groundwater recharge/discharge and their historical evolution in this basin. Several methods are applied to specify the aquifer system including: water level change and storativity estimates, gravity estimates (GRACE), flow model (MODFLOW), water budget analysis and extrapolation. In addition, all of the socioeconomic and engineering aspects are represented in the hydrological system through the change of temporal and spatial distributions of recharge and discharge (e.g., land use, crop structure, water allocation, etc.). Our results demonstrate that the direct impacts of climate change will result in unevenly distributed but increasing groundwater storage in the short term through groundwater recharge. In contrast, long term groundwater storage will decrease as a result of combined indirect and direct impacts of climate change (e.g. recharge/discharge and human activities). The sensitivity of groundwater storage to climate variation is characterized by topography, aquifer specifics and land use. Furthermore, by comparing possible outcomes of different human interventions scenarios, our study reveals human activities play an important role in affecting the sensitivity of groundwater storage to climate variation. Over all, this study presents the feasibility and value of using integrated hydrological methods to support sustainable water resource management under climate change.
Tracing the flow: Climate change actor-networks in Oklahoma secondary science education

NASA Astrophysics Data System (ADS)

Colston, Nicole Marie

This dissertation reports research about the translation of climate change in science education. Public controversies about climate change education raises questions about the lived experiences of teachers in Oklahoma and the role of science education in increasing public understanding. A mixed methods research design included rhetorical analysis of climate change denial media, key informant interviews with science education stakeholders, and a survey questionnaire of secondary science teachers. Final analysis was further informed by archival research and supplemented by participant observation in state-wide meetings and science teacher workshops. The results are organized into three distinct manuscripts intended for publication across the fields of communication, science education, and climate science. As a whole the dissertation answers the research question, how does manufactured scientific controversy about climate change present specific challenges and characterize negotiations in secondary science education in Oklahoma? Taken together, the findings suggest that manufactured controversy about climate change introduces a logic of non-problematicity, challenges science education policy making, and undermines scientific consensus about global warming.
Downscaling U.S. public opinion about climate change and the 'Six Americas' to states, cities, and counties

NASA Astrophysics Data System (ADS)

Marlon, J. R.; Howe, P. D.; Leiserowitz, A.

2013-12-01

For climate change communication to be most effective, messages should be targeted to the characteristics of local audiences. In the U.S., 'Six Americas' have been identified among the public based on their response to the climate change issue. The distribution of these different 'publics' varies between states and communities, yet data about public opinion at the sub-national scale remains scarce. In this presentation, we describe a methodology to statistically downscale results from national-level surveys about the Six Americas, climate literacy, and other aspects of public opinion to smaller areas, including states, metropolitan areas, and counties. The method utilizes multilevel regression with poststratification (MRP) to model public opinion at various scales using a large national-level survey dataset. We present state and county-level estimates of two key beliefs about climate change: belief that climate change is happening, and belief in the scientific consensus about climate change. We further present estimates of how the Six Americas vary across the U.S.
An Evaluation of Methods for Assessing Vulnerability of Army Installations toImpacts of Climate Change on Listed and At-Risk Species

DTIC Science & Technology

2017-07-01

ER D C/ CE RL T R- 17 -2 5 Army Environmental Quality Technology An Evaluation of Methods for Assessing Vulnerability of Army...Evaluation of Methods for Assessing Vulnerability of Army Installations to Impacts of Climate Change on Listed and At-Risk Species Matthew G. Hohmann...their suitability for informing BRAC-related evaluations. Three recently developed methods for assessing the vulnerability of Army installations to
Streamflow Bias Correction for Climate Change Impact Studies: Harmless Correction or Wrecking Ball?

NASA Astrophysics Data System (ADS)

Nijssen, B.; Chegwidden, O.

2017-12-01

Projections of the hydrologic impacts of climate change rely on a modeling chain that includes estimates of future greenhouse gas emissions, global climate models, and hydrologic models. The resulting streamflow time series are used in turn as input to impact studies. While these flows can sometimes be used directly in these impact studies, many applications require additional post-processing to remove model errors. Water resources models and regulation studies are a prime example of this type of application. These models rely on specific flows and reservoir levels to trigger reservoir releases and diversions and do not function well if the unregulated streamflow inputs are significantly biased in time and/or amount. This post-processing step is typically referred to as bias-correction, even though this step corrects not just the mean but the entire distribution of flows. Various quantile-mapping approaches have been developed that adjust the modeled flows to match a reference distribution for some historic period. Simulations of future flows are then post-processed using this same mapping to remove hydrologic model errors. These streamflow bias-correction methods have received far less scrutiny than the downscaling and bias-correction methods that are used for climate model output, mostly because they are less widely used. However, some of these methods introduce large artifacts in the resulting flow series, in some cases severely distorting the climate change signal that is present in future flows. In this presentation, we discuss our experience with streamflow bias-correction methods as part of a climate change impact study in the Columbia River basin in the Pacific Northwest region of the United States. To support this discussion, we present a novel way to assess whether a streamflow bias-correction method is merely a harmless correction or is more akin to taking a wrecking ball to the climate change signal.
Vulnerability of eco-environmental health to climate change: the views of government stakeholders and other specialists in Queensland, Australia

PubMed Central

2010-01-01

Background There is overwhelming scientific evidence that human activities have changed and will continue to change the climate of the Earth. Eco-environmental health, which refers to the interdependencies between ecological systems and population health and well-being, is likely to be significantly influenced by climate change. The aim of this study was to examine perceptions from government stakeholders and other relevant specialists about the threat of climate change, their capacity to deal with it, and how to develop and implement a framework for assessing vulnerability of eco-environmental health to climate change. Methods Two focus groups were conducted in Brisbane, Australia with representatives from relevant government agencies, non-governmental organisations, and the industry sector (n = 15) involved in the discussions. The participants were specialists on climate change and public health from governmental agencies, industry, and non-governmental organisations in South-East Queensland. Results The specialists perceived climate change to be a threat to eco-environmental health and had substantial knowledge about possible implications and impacts. A range of different methods for assessing vulnerability were suggested by the participants and the complexity of assessment when dealing with multiple hazards was acknowledged. Identified factors influencing vulnerability were perceived to be of a social, physical and/or economic nature. They included population growth, the ageing population with associated declines in general health and changes in the vulnerability of particular geographical areas due to for example, increased coastal development, and financial stress. Education, inter-sectoral collaboration, emergency management (e.g. development of early warning systems), and social networks were all emphasised as a basis for adapting to climate change. To develop a framework, different approaches were discussed for assessing eco-environmental health vulnerability, including literature reviews to examine the components of vulnerability such as natural hazard risk and exposure and to investigate already existing frameworks for assessing vulnerability. Conclusion The study has addressed some important questions in regard to government stakeholders and other specialists' views on the threat of climate change and its potential impacts on eco-environmental health. These findings may have implications in climate change and public health decision-making. PMID:20663227

Climate-smart management of biodiversity

USGS Publications Warehouse

Nadeau, Christopher P.; Fuller, Angela K.; Rosenblatt, Daniel L.

2015-01-01

Determining where biodiversity is likely to be most vulnerable to climate change and methods to reduce that vulnerability are necessary first steps to incorporate climate change into biodiversity management plans. Here, we use a spatial climate change vulnerability assessment to (1) map the potential vulnerability of terrestrial biodiversity to climate change in the northeastern United States and (2) provide guidance on how and where management actions for biodiversity could provide long-term benefits under climate change (i.e., climate-smart management considerations). Our model suggests that biodiversity will be most vulnerable in Delaware, Maryland, and the District of Columbia due to the combination of high climate change velocity, high landscape resistance, and high topoclimate homogeneity. Biodiversity is predicted to be least vulnerable in Vermont, Maine, and New Hampshire because large portions of these states have low landscape resistance, low climate change velocity, and low topoclimate homogeneity. Our spatial climate-smart management considerations suggest that: (1) high topoclimate diversity could moderate the effects of climate change across 50% of the region; (2) decreasing local landscape resistance in conjunction with other management actions could increase the benefit of those actions across 17% of the region; and (3) management actions across 24% of the region could provide long-term benefits by promoting short-term population persistence that provides a source population capable of moving in the future. The guidance and framework we provide here should allow conservation organizations to incorporate our climate-smart management considerations into management plans without drastically changing their approach to biodiversity conservation.
Reconstructing Student Conceptions of Climate Change; An Inquiry Approach

NASA Astrophysics Data System (ADS)

McClelland, J. Collin

No other environmental issue today has as much potential to alter life on Earth as does global climate change. Scientific evidence continues to grow; indicating that climate change is occurring now, and that change is a result of human activities (National Research Council [NRC], 2010). The need for climate literacy in society has become increasingly urgent. Unfortunately, understanding the concepts necessary for climate literacy remains a challenge for most individuals. A growing research base has identified a number of common misconceptions people have about climate literacy concepts (Leiserowitz, Smith, & Marlon 2011; Shepardson, Niyogi, Choi, & Charusombat, 2009). However, few have explored this understanding in high school students. This sequential mixed methods study explored the changing conceptions of global climate change in 90 sophomore biology students through the course of their participation in an eight-week inquiry-based global climate change unit. The study also explored changes in students' attitudes over the course of the study unit, contemplating possible relationships between students' conceptual understanding of and attitudes toward global climate change. Phase I of the mixed methods study included quantitative analysis of pre-post content knowledge and attitude assessment data. Content knowledge gains were statistically significant and over 25% of students in the study shifted from an expressed belief of denial or uncertainty about global warming to one of belief in it. Phase II used an inductive approach to explore student attitudes and conceptions. Conceptually, very few students grew to a scientifically accurate understanding of the greenhouse effect or the relationship between global warming and climate change. However, they generally made progress in their conceptual understanding by adding more specific detail to explain their understanding. Phase III employed a case study approach with eight purposefully selected student cases, identifying five common conceptual and five common attitudebased themes. Findings suggest similar misconceptions revealed in prior research also occurred in this study group. Some examples include; connecting global warming to the hole in the ozone layer, and falsely linking unrelated environmental issues like littering to climate change. Data about students' conceptual understanding of energy may also have implications for education research curriculum development. Similar to Driver & While no statistical relationship between students' attitudes about global climate change and overall conceptual understanding emerged, some data suggested that climate change skeptics may perceive the concept of evidence differently than non-skeptics. One-way ANOVA data comparing skeptics with other students on evidence-based assessment items was significant. This study offers insights to teachers of potential barriers students face when trying to conceptualize global climate change concepts. More importantly it reinforces the idea that students generally find value in learning about global climate change in the classroom.
Climate change vulnerability of native and alien freshwater fishes of California: a systematic assessment approach.

PubMed

Moyle, Peter B; Kiernan, Joseph D; Crain, Patrick K; Quiñones, Rebecca M

2013-01-01

Freshwater fishes are highly vulnerable to human-caused climate change. Because quantitative data on status and trends are unavailable for most fish species, a systematic assessment approach that incorporates expert knowledge was developed to determine status and future vulnerability to climate change of freshwater fishes in California, USA. The method uses expert knowledge, supported by literature reviews of status and biology of the fishes, to score ten metrics for both (1) current status of each species (baseline vulnerability to extinction) and (2) likely future impacts of climate change (vulnerability to extinction). Baseline and climate change vulnerability scores were derived for 121 native and 43 alien fish species. The two scores were highly correlated and were concordant among different scorers. Native species had both greater baseline and greater climate change vulnerability than did alien species. Fifty percent of California's native fish fauna was assessed as having critical or high baseline vulnerability to extinction whereas all alien species were classified as being less or least vulnerable. For vulnerability to climate change, 82% of native species were classified as highly vulnerable, compared with only 19% for aliens. Predicted climate change effects on freshwater environments will dramatically change the fish fauna of California. Most native fishes will suffer population declines and become more restricted in their distributions; some will likely be driven to extinction. Fishes requiring cold water (<22°C) are particularly likely to go extinct. In contrast, most alien fishes will thrive, with some species increasing in abundance and range. However, a few alien species will likewise be negatively affected through loss of aquatic habitats during severe droughts and physiologically stressful conditions present in most waterways during summer. Our method has high utility for predicting vulnerability to climate change of diverse fish species. It should be useful for setting conservation priorities in many different regions.
Climate Change Vulnerability of Native and Alien Freshwater Fishes of California: A Systematic Assessment Approach

PubMed Central

Moyle, Peter B.; Kiernan, Joseph D.; Crain, Patrick K.; Quiñones, Rebecca M.

2013-01-01

Freshwater fishes are highly vulnerable to human-caused climate change. Because quantitative data on status and trends are unavailable for most fish species, a systematic assessment approach that incorporates expert knowledge was developed to determine status and future vulnerability to climate change of freshwater fishes in California, USA. The method uses expert knowledge, supported by literature reviews of status and biology of the fishes, to score ten metrics for both (1) current status of each species (baseline vulnerability to extinction) and (2) likely future impacts of climate change (vulnerability to extinction). Baseline and climate change vulnerability scores were derived for 121 native and 43 alien fish species. The two scores were highly correlated and were concordant among different scorers. Native species had both greater baseline and greater climate change vulnerability than did alien species. Fifty percent of California’s native fish fauna was assessed as having critical or high baseline vulnerability to extinction whereas all alien species were classified as being less or least vulnerable. For vulnerability to climate change, 82% of native species were classified as highly vulnerable, compared with only 19% for aliens. Predicted climate change effects on freshwater environments will dramatically change the fish fauna of California. Most native fishes will suffer population declines and become more restricted in their distributions; some will likely be driven to extinction. Fishes requiring cold water (<22°C) are particularly likely to go extinct. In contrast, most alien fishes will thrive, with some species increasing in abundance and range. However, a few alien species will likewise be negatively affected through loss of aquatic habitats during severe droughts and physiologically stressful conditions present in most waterways during summer. Our method has high utility for predicting vulnerability to climate change of diverse fish species. It should be useful for setting conservation priorities in many different regions. PMID:23717503
Farmers' perceptions of and adaptation strategies to climate change and their determinants; the case of Punjab province, Pakistan

NASA Astrophysics Data System (ADS)

Abid, M.; Scheffran, J.; Schneider, U. A.; Ashfaq, M.

2014-10-01

Climate change is a global environmental threat to all economic sectors, particularly the agricultural sector. Pakistan is one of the negatively affected countries from climate change due to its high exposure to extreme events and low adaptive capacity. In Pakistan, farmers are the primary stakeholders in agriculture and are more at risk due to climate vulnerability. Based on farm household data of 450 households collected from three districts in three agro-ecological zones in Punjab province of Pakistan, this study examined how farmers perceive climate change and how they adapt their farming in response to perceived changes in climate. The results demonstrate that awareness to climate change persists in the area, and farm households make adjustments to adapt their agriculture in response to climatic change. Overall 58% of the farm households adapted their farming to climate change. Changing crop varieties, changing planting dates, plantation of trees and changing fertilizer were the main adaptation methods implemented by farm households in the study area. Results from the binary logistic model revealed that education, farm experience, household size, land area, tenancy status, ownership of tube-well, access to market information, information on weather forecasting and extension all influence the farmers' choice of adaptation measures. Results also indicate that adaptation to climate change is constrained by several factors such as lack of information; lack of money; resource constraint and shortage of irrigation water in the study area. Findings of the study suggest the need of greater investment in farmer education and improved institutional setup for climate change adaptation to improve farmers' wellbeing.
Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality.

PubMed

Gosling, Simon N; Hondula, David M; Bunker, Aditi; Ibarreta, Dolores; Liu, Junguo; Zhang, Xinxin; Sauerborn, Rainer

2017-08-16

Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to "adaptation uncertainty" (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios. This study had three aims: a ) Compare the range in projected impacts that arises from using different adaptation modeling methods; b ) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c ) recommend modeling method(s) to use in future impact assessments. We estimated impacts for 2070-2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty. The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty. Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634.
Bioethics and Public Health Collaborate to Reveal Impacts of Climate Change on Caribbean Life

NASA Astrophysics Data System (ADS)

Macpherson, C.; Akpinar-Elci, M.

2011-12-01

Interdisciplinary dialog and collaboration aimed at protecting health against climate change is impeded by the small number of scientists and health professionals skilled in interdisciplinary work, and by the view held by many that "climate change won't affect me personally". These challenges may be surmounted by discussions about the lived experience of climate change and how this threatens things we value. Dialog between bioethics and public health generated an innovative collaboration using the focus group method. The main limitation of focus groups is the small number of participants however the data obtained is generalizable to wider groups and is used regularly in business to enhance marketing strategies. Caribbean academicians from varied disciplines discussed how climate change affects them and life in the Caribbean. Caribbean states are particularly vulnerable to climate change because their large coastal areas are directly exposed to rising sea levels and their development relies heavily on foreign aid. The Caribbean comprises about half of the 39 members of the Association of Small Island States (AOSIS), and small island states comprise about 5% of global population [1]. Participants described socioeconomic and environmental changes in the Caribbean that they attribute to climate change. These include extreme weather, unusual rain and drought, drying rivers, beach erosion, declining fish catches, and others. The session exposed impacts on individuals, businesses, agriculture, and disaster preparedness. This data helps to reframe climate change as a personal reality rather than a vague future concern. It is relevant to the design, implementation, and sustainability of climate policies in the Caribbean and perhaps other small island states. The method and interdisciplinary approach can be used in other settings to elicit dialog about experiences and values across sectors, and to inform policies. Those who have experienced extreme weather are more concerned about climate change than others [2] and no expertise is needed to discuss such experiences or related values. These are accessible concepts in all disciplines and across socioeconomic levels. Research to further identify and describe values challenged by climate change is needed and can be communicated across disciplines and to the public. The resultant dialog will facilitate interdisciplinary collaboration, public and political debate, and possibly generate behavior change. References 1. Alliance of Small Island States (AOSIS). Accessed July 6, 2011. http://aosis.info/members-and-observers/ 2. Spence A., Poortinga W., Butler C., Pidgeon N.F. Perceptions of climate change and willingness to save energy related to flood experience. Nature Climate Change. March 2011. Accessed July 6, 2011. http://www.nature.com/nclimate/journal/vaop/ncurrent/full/nclimate1059.html
Application of scenario-neutral methods to quantify impacts of climate change on water resources in East Africa

NASA Astrophysics Data System (ADS)

Ascott, M.; Macdonald, D.; Lapworth, D.; Tindimugaya, C.

2017-12-01

Quantification of the impact of climate change on water resources is essential for future resource planning. Unfortunately, climate change impact studies in African regions are often hindered by the extent in variability in future rainfall predictions, which also diverge from current drying trends. To overcome this limitation, "scenario-neutral" methods have been developed which stress a hydrological system using a wide range of climate futures to build a "climate response surface". We developed a hydrological model and scenario-neutral framework to quantify climate change impacts on river flows in the Katonga catchment, Uganda. Using the lumped catchment model GR4J, an acceptable calibration to historic daily flows (1966 - 2010, NSE = 0.69) was achieved. Using a delta change approach, we then systematically changed rainfall and PET inputs to develop response surfaces for key metrics, developed with Ugandan water resources planners (e.g. Q5, Q95). Scenarios from the CMIP5 models for 2030s and 2050s were then overlain on the response surface. The CMIP5 scenarios show consistent increases in temperature but large variability in rainfall increases, which results in substantial variability in increases in river flows. The developed response surface covers a wide range of climate futures beyond the CMIP5 projections, and can help water resources planners understand the sensitivity of water resource systems to future changes. When future climate scenarios are available, these can be directly overlain on the response surface without the need to re-run the hydrological model. Further work will consider using scenario-neutral approaches in more complex, semi-distributed models (e.g. SWAT), and will consider land use and socioeconomic change.
Advances in risk assessment for climate change adaptation policy.

PubMed

Adger, W Neil; Brown, Iain; Surminski, Swenja

2018-06-13

Climate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of large-scale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts.This article is part of the theme issue 'Advances in risk assessment for climate change adaptation policy'. © 2018 The Author(s).
Advances in risk assessment for climate change adaptation policy

NASA Astrophysics Data System (ADS)

Adger, W. Neil; Brown, Iain; Surminski, Swenja

2018-06-01

Climate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of large-scale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts. This article is part of the theme issue `Advances in risk assessment for climate change adaptation policy'.
Advances in risk assessment for climate change adaptation policy

PubMed Central

Adger, W. Neil; Brown, Iain; Surminski, Swenja

2018-01-01

Climate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of large-scale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts. This article is part of the theme issue ‘Advances in risk assessment for climate change adaptation policy’. PMID:29712800
Climate Change, Human Health, and Biomedical Research: Analysis of the National Institutes of Health Research Portfolio

PubMed Central

Balbus, John M.; Christian, Carole; Haque, Ehsanul; Howe, Sally E.; Newton, Sheila A.; Reid, Britt C.; Roberts, Luci; Wilhelm, Erin; Rosenthal, Joshua P.

2013-01-01

Background: According to a wide variety of analyses and projections, the potential effects of global climate change on human health are large and diverse. The U.S. National Institutes of Health (NIH), through its basic, clinical, and population research portfolio of grants, has been increasing efforts to understand how the complex interrelationships among humans, ecosystems, climate, climate variability, and climate change affect domestic and global health. Objectives: In this commentary we present a systematic review and categorization of the fiscal year (FY) 2008 NIH climate and health research portfolio. Methods: A list of candidate climate and health projects funded from FY 2008 budget appropriations were identified and characterized based on their relevance to climate change and health and based on climate pathway, health impact, study type, and objective. Results: This analysis identified seven FY 2008 projects focused on climate change, 85 climate-related projects, and 706 projects that focused on disease areas associated with climate change but did not study those associations. Of the nearly 53,000 awards that NIH made in 2008, approximately 0.17% focused on or were related to climate. Conclusions: Given the nature and scale of the potential effects of climate change on human health and the degree of uncertainty that we have about these effects, we think that it is helpful for the NIH to engage in open discussions with science and policy communities about government-wide needs and opportunities in climate and health, and about how NIH’s strengths in human health research can contribute to understanding the health implications of global climate change. This internal review has been used to inform more recent initiatives by the NIH in climate and health. PMID:23552460
Climate change and the economics of biomass energy feedstocks in semi-arid agricultural landscapes: A spatially explicit real options analysis.

PubMed

Regan, Courtney M; Connor, Jeffery D; Raja Segaran, Ramesh; Meyer, Wayne S; Bryan, Brett A; Ostendorf, Bertram

2017-05-01

The economics of establishing perennial species as renewable energy feedstocks has been widely investigated as a climate change adapted diversification option for landholders, primarily using net present value (NPV) analysis. NPV does not account for key uncertainties likely to influence relevant landholder decision making. While real options analysis (ROA) is an alternative method that accounts for the uncertainty over future conditions and the large upfront irreversible investment involved in establishing perennials, there have been limited applications of ROA to evaluating land use change decision economics and even fewer applications considering climate change risks. Further, while the influence of spatially varying climate risk on biomass conversion economic has been widely evaluated using NPV methods, effects of spatial variability and climate on land use change have been scarcely assessed with ROA. In this study we applied a simulation-based ROA model to evaluate a landholder's decision to convert land from agriculture to biomass. This spatially explicit model considers price and yield risks under baseline climate and two climate change scenarios over a geographically diverse farming region. We found that underlying variability in primary productivity across the study area had a substantial effect on conversion thresholds required to trigger land use change when compared to results from NPV analysis. Areas traditionally thought of as being quite similar in average productive capacity can display large differences in response to the inclusion of production and price risks. The effects of climate change, broadly reduced returns required for land use change to biomass in low and medium rainfall zones and increased them in higher rainfall areas. Additionally, the risks posed by climate change can further exacerbate the tendency for NPV methods to underestimate true conversion thresholds. Our results show that even under severe drying and warming where crop yield variability is more affected than perennial biomass plantings, comparatively little of the study area is economically viable for conversion to biomass under $200/DM t, and it is not until prices exceed $200/DM t that significant areas become profitable for biomass plantings. We conclude that for biomass to become a valuable diversification option the synchronisation of products and services derived from biomass and the development of markets is vital. Copyright © 2017 Elsevier Ltd. All rights reserved.
A framework for evaluating statistical downscaling performance under changing climatic conditions (Invited)

NASA Astrophysics Data System (ADS)

Dixon, K. W.; Balaji, V.; Lanzante, J.; Radhakrishnan, A.; Hayhoe, K.; Stoner, A. K.; Gaitan, C. F.

2013-12-01

Statistical downscaling (SD) methods may be viewed as generating a value-added product - a refinement of global climate model (GCM) output designed to add finer scale detail and to address GCM shortcomings via a process that gleans information from a combination of observations and GCM-simulated climate change responses. Making use of observational data sets and GCM simulations representing the same historical period, cross-validation techniques allow one to assess how well an SD method meets this goal. However, lacking observations of future, the extent to which a particular SD method's skill might degrade when applied to future climate projections cannot be assessed in the same manner. Here we illustrate and describe extensions to a 'perfect model' experimental design that seeks to quantify aspects of SD method performance both for a historical period (1979-2008) and for late 21st century climate projections. Examples highlighting cases in which downscaling performance deteriorates in future climate projections will be discussed. Also, results will be presented showing how synthetic datasets having known statistical properties may be used to further isolate factors responsible for degradations in SD method skill under changing climatic conditions. We will describe a set of input files used to conduct these analyses that are being made available to researchers who wish to utilize this experimental framework to evaluate SD methods they have developed. The gridded data sets cover a region centered on the contiguous 48 United States with a grid spacing of approximately 25km, have daily time resolution (e.g., maximum and minimum near-surface temperature and precipitation), and represent a total of 120 years of model simulations. This effort is consistent with the 2013 National Climate Predictions and Projections Platform Quantitative Evaluation of Downscaling Workshop goal of supporting a community approach to promote the informed use of downscaled climate projections.
Data-model synthesis of grassland carbon metabolism. Quantifying direct, indirect & interactive effects of warming & elevated CO 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pendall, Elise; Ogle, Kiona; Parton, William

2016-02-29

This research project improved understanding of how climate change (elevated atmospheric CO 2, warming and altered precipitation) can affect grassland ecosystem productivity and nutrient availability. Our advanced experimental and modeling methods allowed us to test 21 specific hypotheses. We found that ecosystem changes over years of exposure to climate change can shift the plant communities and potentially make them more resilient to future climate changes. These changes in plant communities may be related to increased growth of belowground roots and enhanced nutrient uptake by some species. We also found that climate change can increase the spread of invasive and noxiousmore » weeds. These findings are important for land managers to make adaptive planning decisions for domestic livestock production in response to climate variability in semi-arid grasslands.« less
Changes in the geographical distribution of plant species and climatic variables on the West Cornwall peninsula (South West UK).

PubMed

Kosanic, Aleksandra; Anderson, Karen; Harrison, Stephan; Turkington, Thea; Bennie, Jonathan

2018-01-01

Recent climate change has had a major impact on biodiversity and has altered the geographical distribution of vascular plant species. This trend is visible globally; however, more local and regional scale research is needed to improve understanding of the patterns of change and to develop appropriate conservation strategies that can minimise cultural, health, and economic losses at finer scales. Here we describe a method to manually geo-reference botanical records from a historical herbarium to track changes in the geographical distributions of plant species in West Cornwall (South West England) using both historical (pre-1900) and contemporary (post-1900) distribution records. We also assess the use of Ellenberg and climate indicator values as markers of responses to climate and environmental change. Using these techniques we detect a loss in 19 plant species, with 6 species losing more than 50% of their previous range. Statistical analysis showed that Ellenberg (light, moisture, nitrogen) and climate indicator values (mean January temperature, mean July temperature and mean precipitation) could be used as environmental change indicators. Significantly higher percentages of area lost were detected in species with lower January temperatures, July temperatures, light, and nitrogen values, as well as higher annual precipitation and moisture values. This study highlights the importance of historical records in examining the changes in plant species' geographical distributions. We present a method for manual geo-referencing of such records, and demonstrate how using Ellenberg and climate indicator values as environmental and climate change indicators can contribute towards directing appropriate conservation strategies.
Changes in the geographical distribution of plant species and climatic variables on the West Cornwall peninsula (South West UK)

PubMed Central

Kosanic, Aleksandra; Anderson, Karen; Harrison, Stephan; Turkington, Thea; Bennie, Jonathan

2018-01-01

Recent climate change has had a major impact on biodiversity and has altered the geographical distribution of vascular plant species. This trend is visible globally; however, more local and regional scale research is needed to improve understanding of the patterns of change and to develop appropriate conservation strategies that can minimise cultural, health, and economic losses at finer scales. Here we describe a method to manually geo-reference botanical records from a historical herbarium to track changes in the geographical distributions of plant species in West Cornwall (South West England) using both historical (pre-1900) and contemporary (post-1900) distribution records. We also assess the use of Ellenberg and climate indicator values as markers of responses to climate and environmental change. Using these techniques we detect a loss in 19 plant species, with 6 species losing more than 50% of their previous range. Statistical analysis showed that Ellenberg (light, moisture, nitrogen) and climate indicator values (mean January temperature, mean July temperature and mean precipitation) could be used as environmental change indicators. Significantly higher percentages of area lost were detected in species with lower January temperatures, July temperatures, light, and nitrogen values, as well as higher annual precipitation and moisture values. This study highlights the importance of historical records in examining the changes in plant species’ geographical distributions. We present a method for manual geo-referencing of such records, and demonstrate how using Ellenberg and climate indicator values as environmental and climate change indicators can contribute towards directing appropriate conservation strategies. PMID:29401494
Spatially explicit integrated modeling and economic valuation of climate driven land use change and its indirect effects.

PubMed

Bateman, Ian; Agarwala, Matthew; Binner, Amy; Coombes, Emma; Day, Brett; Ferrini, Silvia; Fezzi, Carlo; Hutchins, Michael; Lovett, Andrew; Posen, Paulette

2016-10-01

We present an integrated model of the direct consequences of climate change on land use, and the indirect effects of induced land use change upon the natural environment. The model predicts climate-driven shifts in the profitability of alternative uses of agricultural land. Both the direct impact of climate change and the induced shift in land use patterns will cause secondary effects on the water environment, for which agriculture is the major source of diffuse pollution. We model the impact of changes in such pollution on riverine ecosystems showing that these will be spatially heterogeneous. Moreover, we consider further knock-on effects upon the recreational benefits derived from water environments, which we assess using revealed preference methods. This analysis permits a multi-layered examination of the economic consequences of climate change, assessing the sequence of impacts from climate change through farm gross margins, land use, water quality and recreation, both at the individual and catchment scale. Copyright © 2016 Elsevier Ltd. All rights reserved.
Individual contributions of climate and vegetation change to soil moisture trends across multiple spatial scales.

PubMed

Feng, Huihui

2016-09-07

Climate and vegetation change are two dominating factors for soil moisture trend. However, their individual contributions remain unknown due to their complex interaction. Here, I separated their contributions through a trajectory-based method across the global, regional and local scales. Our results demonstrated that climate change accounted for 98.78% and 114.64% of the global drying and wetting trend. Vegetation change exhibited a relatively weak influence (contributing 1.22% and -14.64% of the global drying and wetting) because it occurred in a limited area on land. Regionally, the impact of vegetation change cannot be neglected, which contributed -40.21% of the soil moisture change in the wetting zone. Locally, the contributions strongly correlated to the local environmental characteristics. Vegetation negatively affected soil moisture trends in the dry and sparsely vegetated regions and positively in the wet and densely vegetated regions. I conclude that individual contributions of climate and vegetation change vary at the global, regional and local scales. Climate change dominates the soil moisture trends, while vegetation change acts as a regulator to drying or wetting the soil under the changing climate.
Diagnosis of Middle Atmosphere Climate Sensitivity by the Climate Feedback Response Analysis Method

NASA Technical Reports Server (NTRS)

Zhu, Xun; Yee, Jeng-Hwa; Cai, Ming; Swartz, William H.; Coy, Lawrence; Aquila, Valentina; Talaat, Elsayed R.

2014-01-01

We present a new method to diagnose the middle atmosphere climate sensitivity by extending the Climate Feedback-Response Analysis Method (CFRAM) for the coupled atmosphere-surface system to the middle atmosphere. The Middle atmosphere CFRAM (MCFRAM) is built on the atmospheric energy equation per unit mass with radiative heating and cooling rates as its major thermal energy sources. MCFRAM preserves the CFRAM unique feature of an additive property for which the sum of all partial temperature changes due to variations in external forcing and feedback processes equals the observed temperature change. In addition, MCFRAM establishes a physical relationship of radiative damping between the energy perturbations associated with various feedback processes and temperature perturbations associated with thermal responses. MCFRAM is applied to both measurements and model output fields to diagnose the middle atmosphere climate sensitivity. It is found that the largest component of the middle atmosphere temperature response to the 11-year solar cycle (solar maximum vs. solar minimum) is directly from the partial temperature change due to the variation of the input solar flux. Increasing CO2 always cools the middle atmosphere with time whereas partial temperature change due to O3 variation could be either positive or negative. The partial temperature changes due to different feedbacks show distinctly different spatial patterns. The thermally driven globally averaged partial temperature change due to all radiative processes is approximately equal to the observed temperature change, ranging from 0.5 K near 70 km from the near solar maximum to the solar minimum.

Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality

PubMed Central

Hondula, David M.; Bunker, Aditi; Ibarreta, Dolores; Liu, Junguo; Zhang, Xinxin; Sauerborn, Rainer

2017-01-01

Background: Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to “adaptation uncertainty” (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios. Objectives: This study had three aims: a) Compare the range in projected impacts that arises from using different adaptation modeling methods; b) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c) recommend modeling method(s) to use in future impact assessments. Methods: We estimated impacts for 2070–2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty. Results: The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty. Conclusions: Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634 PMID:28885979
Climate change effects on human health in a gender perspective: some trends in Arctic research

PubMed Central

Natalia, Kukarenko

2011-01-01

Background Climate change and environmental pollution have become pressing concerns for the peoples in the Arctic region. Some researchers link climate change, transformations of living conditions and human health. A number of studies have also provided data on differentiating effects of climate change on women's and men's well-being and health. Objective To show how the issues of climate and environment change, human health and gender are addressed in current research in the Arctic. The main purpose of this article is not to give a full review but to draw attention to the gaps in knowledge and challenges in the Arctic research trends on climate change, human health and gender. Methods A broad literature search was undertaken using a variety of sources from natural, medical, social science and humanities. The focus was on the keywords. Results Despite the evidence provided by many researchers on differentiating effects of climate change on well-being and health of women and men, gender perspective remains of marginal interest in climate change, environmental and health studies. At the same time, social sciences and humanities, and gender studies in particular, show little interest towards climate change impacts on human health in the Arctic. As a result, we still observe the division of labour between disciplines, the disciplinary-bound pictures of human development in the Arctic and terminology confusion. Conclusion Efforts to bring in a gender perspective in the Arctic research will be successful only when different disciplines would work together. Multidisciplinary research is a way to challenge academic/disciplinary homogeneity and their boundaries, to take advantage of the diversity of approaches and methods in production of new integrated knowledge. Cooperation and dialogue across disciplines will help to develop adequate indicators for monitoring human health and elaborating efficient policies and strategies to the benefit of both women and men in the Arctic. PMID:21949499
Climate change impacts on global rainfed agricultural land availability

NASA Astrophysics Data System (ADS)

Zhang, X.; Cai, X.

2010-12-01

Global rainfed agricultural land availability can be subject to significant changes in both magnitude and spatial distribution due to climate change. We assess the possible changes using current and projected climate data from thirteen general circulation models (GCMs) under two emission scenarios, A1B & B1, together with global databases on land, including soil properties and slope. Two ensemble methods with the set of GCMs, Simple Average Method (SAM) and Root Mean Square Error Ensemble Method (RMSEMM), are employed to abate uncertainty involved in global GCM projections for assembling regional climate. Fuzzy logic, which handles land classification in an approximate yet efficient way, is adopted to estimate the land suitability through empirically determined membership functions and fuzzy rules chosen through a learning process based on remote sensed crop land products. Land suitability under five scenarios, which include the present-climate baseline scenario and four projected scenarios, A1B-SAM, A1B-RMSEMM, B1-SAM, and B1-RMSEMM, are assessed for both global and seven important agricultural regions in the world, Africa, China, India, Europe (excluding Russia), Russia, South America, and U.S. It is found that countries at the high latitudes of north hemisphere are more likely to benefit from climate change with respect to agricultural land availability; while countries at mid- and low latitudes may suffer different levels of loss of potential arable land. Expansions of the gross potential arable land are likely to occur in regions at the north high latitudes, including Russia, North China and U.S., while land shrinking can be expected in South America, Africa, India and Europe. Although the greatest potential for agricultural expansion lies in Africa and South America, with current cultivated land accounting for 20% and 13% respectively of the net potential arable land, negative effects from climate change may decline the potential. In summary, climate change is likely to alter the global distribution of potential rainfed arable land and further influence agricultural production and related socio-economic aspects around the end of this century. Global suitable rainfed agricultural land (can be used for regular crops) changes between A1B-SAM scenario based on 2070-2099 averaged climate data and baseline scenario simulated using 1961-1990 averaged climate data
Household preferences for reducing greenhouse gas emissions in four European high-income countries: Does health information matter? A mixed-methods study protocol.

PubMed

Herrmann, Alina; Fischer, Helen; Amelung, Dorothee; Litvine, Dorian; Aall, Carlo; Andersson, Camilla; Baltruszewicz, Marta; Barbier, Carine; Bruyère, Sébastien; Bénévise, Françoise; Dubois, Ghislain; Louis, Valérie R; Nilsson, Maria; Richardsen Moberg, Karen; Sköld, Bore; Sauerborn, Rainer

2017-08-01

It is now universally acknowledged that climate change constitutes a major threat to human health. At the same time, some of the measures to reduce greenhouse gas emissions, so-called climate change mitigation measures, have significant health co-benefits (e.g., walking or cycling more; eating less meat). The goal of limiting global warming to 1,5° Celsius set by the Conference of the Parties to the United Nations Framework Convention on Climate Change in Paris in 2015 can only be reached if all stakeholders, including households, take actions to mitigate climate change. Results on whether framing mitigation measures in terms of their health co-benefits increases the likelihood of their implementation are inconsistent. The present study protocol describes the transdisciplinary project HOPE (HOuseholds' Preferences for reducing greenhouse gas emissions in four European high-income countries) that investigates the role of health co-benefits in households' decision making on climate change mitigation measures in urban households in France, Germany, Norway and Sweden. HOPE employs a mixed-methods approach combining status-quo carbon footprint assessments, simulations of the reduction of households' carbon footprints, and qualitative in-depth interviews with a subgroup of households. Furthermore, a policy analysis of current household oriented climate policies is conducted. In the simulation of the reduction of households' carbon footprints, half of the households are provided with information on health co-benefits of climate change mitigation measures, the other half is not. Households' willingness to implement the measures is assessed and compared in between-group analyses of variance. This is one of the first comprehensive mixed-methods approaches to investigate which mitigation measures households are most willing to implement in order to reach the 1,5° target set by the Paris Agreement, and whether health co-benefits can serve as a motivator for households to implement these measures. The comparison of the empirical data with current climate policies will provide knowledge for tailoring effective climate change mitigation and health policies.
climwin: An R Toolbox for Climate Window Analysis.

PubMed

Bailey, Liam D; van de Pol, Martijn

2016-01-01

When studying the impacts of climate change, there is a tendency to select climate data from a small set of arbitrary time periods or climate windows (e.g., spring temperature). However, these arbitrary windows may not encompass the strongest periods of climatic sensitivity and may lead to erroneous biological interpretations. Therefore, there is a need to consider a wider range of climate windows to better predict the impacts of future climate change. We introduce the R package climwin that provides a number of methods to test the effect of different climate windows on a chosen response variable and compare these windows to identify potential climate signals. climwin extracts the relevant data for each possible climate window and uses this data to fit a statistical model, the structure of which is chosen by the user. Models are then compared using an information criteria approach. This allows users to determine how well each window explains variation in the response variable and compare model support between windows. climwin also contains methods to detect type I and II errors, which are often a problem with this type of exploratory analysis. This article presents the statistical framework and technical details behind the climwin package and demonstrates the applicability of the method with a number of worked examples.
Risky Business and the American Climate Prospectus: Economic Risks of Climate Change in the United States"

NASA Astrophysics Data System (ADS)

Gordon, K.; Houser, T.; Kopp, R. E., III; Hsiang, S. M.; Larsen, K.; Jina, A.; Delgado, M.; Muir-Wood, R.; Rasmussen, D.; Rising, J.; Mastrandrea, M.; Wilson, P. S.

2014-12-01

The United States faces a range of economic risks from global climate change - from increased flooding and storm damage, to climate-driven changes in crop yields and labor productivity, to heat-related strains on energy and public health systems. The Risky Business Project commissioned a groundbreaking new analysis of these and other climate risks by region of the country and sector of the economy. The American Climate Prospectus (ACP) links state-of-the-art climate models with econometric research of human responses to climate variability and cutting edge private sector risk assessment tools, the ACP offers decision-makers a data driven assessment of the specific risks they face. We describe the challenge, methods, findings, and policy implications of the national risk analysis, with particular focus on methodological innovations and novel insights.
Trends in Reports on Climate Change in 2009-2011 in the Korean Press Based on Daily Newspapers' Ownership Structure

PubMed Central

Lee, Jihye; Kim, Hyunsook; Hong, Youngtak; Lee, Weonyoung

2013-01-01

Objectives The mass media play a crucial role in risk communication regarding climate change. The aim of this study was to investigate the trend in journalistic reports on climate change in the daily newspapers of Korea. Methods We selected 9 daily newspapers in Korea, which according to the ABC Association, represented 77% of newspaper circulation, out of a total of 44 Korean daily newspapers. The collected articles were from 2009 to 2011. All of the articles were sorted into the following 8 categories: greenhouse gas, climate change conventions, sea level rise, Intergovernmental Panel on Climate Change synthesis reports, expected damage and effect, use of fossil fuels, global warming, and mitigation or adaptation. A chi-squared test was done on the articles, which were counted and classified into cause, effect, and measurement of climate change according to the newspaper's majority or minority ownership structure. Results From the 9 selected newspapers, the number of articles on climate change by month was greatest in December 2009. Generally, the articles vague about climate change (lack of precise data, negative or skeptical tone, and improper use of terminology) were much more common than the articles presenting accurate knowledge. A statistical difference was found based on ownership structure: the majority-owned newspapers addressed the cause of climate change, while the minority-owned newspapers referred more to climate change measurement. Conclusions Our investigation revealed that generally Korean daily newspapers did not deliver accurate information about climate change. The coverage of the newspapers showed significant differences according to the ownership structure. PMID:23573375
Incremental dynamical downscaling for probabilistic analysis based on multiple GCM projections

NASA Astrophysics Data System (ADS)

Wakazuki, Y.

2015-12-01

A dynamical downscaling method for probabilistic regional scale climate change projections was developed to cover an uncertainty of multiple general circulation model (GCM) climate simulations. The climatological increments (future minus present climate states) estimated by GCM simulation results were statistically analyzed using the singular vector decomposition. Both positive and negative perturbations from the ensemble mean with the magnitudes of their standard deviations were extracted and were added to the ensemble mean of the climatological increments. The analyzed multiple modal increments were utilized to create multiple modal lateral boundary conditions for the future climate regional climate model (RCM) simulations by adding to an objective analysis data. This data handling is regarded to be an advanced method of the pseudo-global-warming (PGW) method previously developed by Kimura and Kitoh (2007). The incremental handling for GCM simulations realized approximated probabilistic climate change projections with the smaller number of RCM simulations. Three values of a climatological variable simulated by RCMs for a mode were used to estimate the response to the perturbation of the mode. For the probabilistic analysis, climatological variables of RCMs were assumed to show linear response to the multiple modal perturbations, although the non-linearity was seen for local scale rainfall. Probability of temperature was able to be estimated within two modes perturbation simulations, where the number of RCM simulations for the future climate is five. On the other hand, local scale rainfalls needed four modes simulations, where the number of the RCM simulations is nine. The probabilistic method is expected to be used for regional scale climate change impact assessment in the future.
Where the Rubber Hits the Road: The Politics and Science of Climate Change in Congress

NASA Astrophysics Data System (ADS)

Koppes, M.

2004-12-01

Scientific understanding of the magnitude and rate of global and regional climate change is being actively communicated to Capitol Hill, however this information is being framed within the political debate that has brought climate change policy in the U.S. to a practical standstill. Efforts by scientists to communicate to Congress advances in the understanding of climate change have been obscured by policy-makers, lobbyists and some scientists themselves, into two polarized camps: those that who claim that current climate change is insignificant and/or of non-anthropogenic origin, and those who predict irreversible climate change in the near future and advocate a precautionary approach to anthropogenic contributions. As a science policy advisor to a Member of Congress active in the climate policy debate over the past year, I have observed firsthand most of the scientific information on climate change presented to Congress being partitioned into these camps. The political debate surrounding climate change policy has centered on the policymakers' understanding of scientific uncertainty. Communication by researchers of the definition of risk and uncertainty in climate science, in the language and framework of the legislative debate, is of utmost importance in order for policymakers to effectively understand and utilize science in the decision-making process. A comparison with the recent white paper on climate change policy developed by the UK Science and Technology council and currently adopted by UK policymakers demonstrates the importance of a general public understanding of the existing magnitude of climate change, uncertainties in the rate of future climate variability and its associated economic and social costs. Communication of research results on climate change has been most effective in the policy debate when framed within the context of economic or security risks in the short term. Other effective methods include communicating local and regional climate scenarios and associated probabilities to individual policy-makers, as is currently being utilized to promote sponsorship of the Climate Stewardship Act in Congress.
A comparison of methods to estimate future sub-daily design rainfall

NASA Astrophysics Data System (ADS)

Li, J.; Johnson, F.; Evans, J.; Sharma, A.

2017-12-01

Warmer temperatures are expected to increase extreme short-duration rainfall due to the increased moisture-holding capacity of the atmosphere. While attention has been paid to the impacts of climate change on future design rainfalls at daily or longer time scales, the potential changes in short duration design rainfalls have been often overlooked due to the limited availability of sub-daily projections and observations. This study uses a high-resolution regional climate model (RCM) to predict the changes in sub-daily design rainfalls for the Greater Sydney region in Australia. Sixteen methods for predicting changes to sub-daily future extremes are assessed based on different options for bias correction, disaggregation and frequency analysis. A Monte Carlo cross-validation procedure is employed to evaluate the skill of each method in estimating the design rainfall for the current climate. It is found that bias correction significantly improves the accuracy of the design rainfall estimated for the current climate. For 1 h events, bias correcting the hourly annual maximum rainfall simulated by the RCM produces design rainfall closest to observations, whereas for multi-hour events, disaggregating the daily rainfall total is recommended. This suggests that the RCM fails to simulate the observed multi-duration rainfall persistence, which is a common issue for most climate models. Despite the significant differences in the estimated design rainfalls between different methods, all methods lead to an increase in design rainfalls across the majority of the study region.
Climate change science education across schools, campuses, and centers: strategies and successes

NASA Astrophysics Data System (ADS)

Merrill, J.; Harcourt, P.; Rogers, M.; Buttram, J.; Petrone, C.; Veron, D. E.; Sezen-Barrie, A.; Stylinski, C.; Ozbay, G.

2016-02-01

With established partnerships in higher education, K-12, and informal science education communities across Delaware and Maryland, the NSF-funded MADE CLEAR project (Maryland Delaware Climate Change Education, Assessment, and Research) has instituted a suite of professional development strategies to bring climate change science into science education methods courses, K-12 classrooms, university lecture halls, and public park facilities. MADE CLEAR partners have provided consistent climate literacy topics (mechanisms, human contributions, local and global impacts, mitigation and adaptation) while meeting the unique needs of each professional community. In-person topical lectures, hands-on work with classroom materials, seed funding for development of new education kits, and on-line live and recorded sessions are some of the tools employed by the team to meet those needs and build enduring capacity for climate change science education. The scope of expertise of the MADE CLEAR team, with climate scientists, educators, learning scientists, and managers has provided not only PD tailored for each education audience, but has also created, fostered, and strengthened relationships across those audiences for long-term sustainability of the newly-built capacity. Specific examples include new climate change programs planned for implementation across Delaware State Parks that will be consistent with middle school curriculum; integration of climate change topics into science methods classes for pre-service teachers at four universities; and active K-12 and informal science education teams working to cooperatively develop lessons that apply informal science education techniques and formal education pedagogy. Evaluations by participants highlight the utility of personal connections, access to experts, mentoring and models for developing implementation plans.
Response of spatial vegetation distribution in China to climate changes since the Last Glacial Maximum (LGM)

PubMed Central

Wang, Siyang; Xu, Xiaoting; Shrestha, Nawal; Zimmermann, Niklaus E.; Tang, Zhiyao; Wang, Zhiheng

2017-01-01

Analyzing how climate change affects vegetation distribution is one of the central issues of global change ecology as this has important implications for the carbon budget of terrestrial vegetation. Mapping vegetation distribution under historical climate scenarios is essential for understanding the response of vegetation distribution to future climatic changes. The reconstructions of palaeovegetation based on pollen data provide a useful method to understand the relationship between climate and vegetation distribution. However, this method is limited in time and space. Here, using species distribution model (SDM) approaches, we explored the climatic determinants of contemporary vegetation distribution and reconstructed the distribution of Chinese vegetation during the Last Glacial Maximum (LGM, 18,000 14C yr BP) and Middle-Holocene (MH, 6000 14C yr BP). The dynamics of vegetation distribution since the LGM reconstructed by SDMs were largely consistent with those based on pollen data, suggesting that the SDM approach is a useful tool for studying historical vegetation dynamics and its response to climate change across time and space. Comparison between the modeled contemporary potential natural vegetation distribution and the observed contemporary distribution suggests that temperate deciduous forests, subtropical evergreen broadleaf forests, temperate deciduous shrublands and temperate steppe have low range fillings and are strongly influenced by human activities. In general, the Tibetan Plateau, North and Northeast China, and the areas near the 30°N in Central and Southeast China appeared to have experienced the highest turnover in vegetation due to climate change from the LGM to the present. PMID:28426780
The Promise and Limitations of Using Analogies to Improve Decision-Relevant Understanding of Climate Change.

PubMed

Raimi, Kaitlin T; Stern, Paul C; Maki, Alexander

2017-01-01

To make informed choices about how to address climate change, members of the public must develop ways to consider established facts of climate science and the uncertainties about its future trajectories, in addition to the risks attendant to various responses, including non-response, to climate change. One method suggested for educating the public about these issues is the use of simple mental models, or analogies comparing climate change to familiar domains such as medical decision making, disaster preparedness, or courtroom trials. Two studies were conducted using online participants in the U.S.A. to test the use of analogies to highlight seven key decision-relevant elements of climate change, including uncertainties about when and where serious damage may occur, its unprecedented and progressive nature, and tradeoffs in limiting climate change. An internal meta-analysis was then conducted to estimate overall effect sizes across the two studies. Analogies were not found to inform knowledge about climate literacy facts. However, results suggested that people found the medical analogy helpful and that it led people-especially political conservatives-to better recognize several decision-relevant attributes of climate change. These effects were weak, perhaps reflecting a well-documented and overwhelming effect of political ideology on climate change communication and education efforts in the U.S.A. The potential of analogies and similar education tools to improve understanding and communication in a polarized political environment are discussed.
An analytical approach to separate climate and human contributions to basin streamflow variability

NASA Astrophysics Data System (ADS)

Li, Changbin; Wang, Liuming; Wanrui, Wang; Qi, Jiaguo; Linshan, Yang; Zhang, Yuan; Lei, Wu; Cui, Xia; Wang, Peng

2018-04-01

Climate variability and anthropogenic regulations are two interwoven factors in the ecohydrologic system across large basins. Understanding the roles that these two factors play under various hydrologic conditions is of great significance for basin hydrology and sustainable water utilization. In this study, we present an analytical approach based on coupling water balance method and Budyko hypothesis to derive effectiveness coefficients (ECs) of climate change, as a way to disentangle contributions of it and human activities to the variability of river discharges under different hydro-transitional situations. The climate dominated streamflow change (ΔQc) by EC approach was compared with those deduced by the elasticity method and sensitivity index. The results suggest that the EC approach is valid and applicable for hydrologic study at large basin scale. Analyses of various scenarios revealed that contributions of climate change and human activities to river discharge variation differed among the regions of the study area. Over the past several decades, climate change dominated hydro-transitions from dry to wet, while human activities played key roles in the reduction of streamflow during wet to dry periods. Remarkable decline of discharge in upstream was mainly due to human interventions, although climate contributed more to runoff increasing during dry periods in the semi-arid downstream. Induced effectiveness on streamflow changes indicated a contribution ratio of 49% for climate and 51% for human activities at the basin scale from 1956 to 2015. The mathematic derivation based simple approach, together with the case example of temporal segmentation and spatial zoning, could help people understand variation of river discharge with more details at a large basin scale under the background of climate change and human regulations.
Potential Impacts of Future Climate Change on Regional Air Quality and Public Health over China

NASA Astrophysics Data System (ADS)

Hong, C.; Zhang, Q.; Zhang, Y.; He, K.

2017-12-01

Future climate change would affect public health through changing air quality. Climate extremes and poor weather conditions are likely to occur at a higher frequency in China under a changing climate, but the air pollution-related health impacts due to future climate change remain unclear. Here the potential impacts of future climate change on regional air quality and public health over China is projected using a coupling of climate, air quality and epidemiological models. We present the first assessment of China's future air quality in a changing climate under the Representative Concentration Pathway 4.5 (RCP4.5) scenario using the dynamical downscaling technique. In RCP4.5 scenario, we estimate that climate change from 2006-2010 to 2046-2050 is likely to adversely affect air quality covering more than 86% of population and 55% of land area in China, causing an average increase of 3% in O3 and PM2.5 concentrations, which are found to be associated with the warmer climate and the more stable atmosphere. Our estimate of air pollution-related mortality due to climate change in 2050 is 26,000 people per year in China. Of which, the PM2.5-related mortality is 18,700 people per year, and the O3-related mortality is 7,300 people per year. The climate-induced air pollution and health impacts vary spatially. The climate impacts are even more pronounced on the urban areas where is densely populated and polluted. 90% of the health loss is concentrated in 20% of land areas in China. We use a simple statistical analysis method to quantify the contributions of climate extremes and find more intense climate extremes play an important role in climate-induced air pollution-related health impacts. Our results indicate that global climate change will likely alter the level of pollutant management required to meet future air quality targets as well as the efforts to protect public health in China.
Public Health Nurses’ Knowledge and Attitudes Regarding Climate Change

PubMed Central

Chaudry, Rosemary V.; Mac Crawford, John

2011-01-01

Background: Climate change affects human health, and health departments are urged to act to reduce the severity of these impacts. Yet little is known about the perspective of public health nurses—the largest component of the public health workforce—regarding their roles in addressing health impacts of climate change. Objectives: We determined the knowledge and attitudes of public health nurses concerning climate change and the role of public health nursing in divisions of health departments in addressing health-related impacts of climate change. Differences by demographic subgroups were explored. Methods: An online survey was distributed to nursing directors of U.S. health departments (n = 786) with Internet staff directories. Results: Respondents (n = 176) were primarily female, white public health nursing administrators with ≥ 5 years of experience. Approximately equal percentages of respondents self-identified as having moderate, conservative, and liberal political views. Most agreed that the earth has experienced climate change and that climate change is somewhat controllable. Respondents identified an average of 5 of the 12 listed health-related impacts of climate change, but the modal response was zero impact. Public health nursing was perceived as having responsibility to address health-related impacts of climate change but lacking the ability to address these impacts. Conclusions: Public health nurses view the environment as under threat and see a role for nursing divisions in addressing health effects of climate change. However, they recognize the limited resources and personnel available to devote to this endeavor. PMID:22128069
Preparing for Climate Change: A Perspective from Local Public Health Officers in California

PubMed Central

Bedsworth, Louise

2009-01-01

Background The most recent scientific findings show that even with significant emission reductions, some amount of climate change is likely inevitable. The magnitude of the climate changes will depend on future emissions and climate sensitivity. These changes will have local impacts, and a significant share of coping with these changes will fall on local governmental agencies. Public health is no exception, because local public health agencies are crucial providers of disease prevention, health care, and emergency preparedness services. Methods This article presents the results of a survey of California’s local pubic health officers conducted between August and October 2007. The survey gauged health officers’ concerns about the public health impacts of climate change, programs in place that could help to mitigate these health effects, and information and resource needs for better coping with a changing climate. Results The results of this survey show that most public health officers feel that climate change poses a serious threat to public health but that they do not feel well equipped in terms of either resources or information to cope with that threat. Nonetheless, public health agencies currently implement a number of programs that will help these agencies handle some of the challenges posed by a changing climate. Conclusions Overall, the results suggest that local public health agencies in California are likely in a better position than they perceive to address the threats associated with climate change but that there is a larger role for them to play in climate policy. PMID:19440502
Climate change vulnerability to agrarian ecosystem of small Island: evidence from Sagar Island, India

NASA Astrophysics Data System (ADS)

Mandal, S.; Satpati, L. N.; Choudhury, B. U.; Sadhu, S.

2018-04-01

The present study assessed climate change vulnerability in agricultural sector of low-lying Sagar Island of Bay of Bengal. Vulnerability indices were estimated using spatially aggregated biophysical and socio-economic parameters by applying principal component analysis and equal weight method. The similarities and differences of outputs of these two methods were analysed across the island. From the integration of outputs and based on the severity of vulnerability, explicit vulnerable zones were demarcated spatially. Results revealed that life subsistence agriculture in 11.8% geographical area (2829 ha) of the island along the western coast falls under very high vulnerable zone (VHVZ VI of 84-99%) to climate change. Comparatively higher values of exposure (0.53 ± 0.26) and sensitivity (0.78 ± 0.14) subindices affirmed that the VHV zone is highly exposed to climate stressor with very low adaptive capacity (ADI= 0.24 ± 0.16) to combat vulnerability to climate change. Hence, food security for a population of >22 thousands comprising >3.7 thousand agrarian households are highly exposed to climate change. Another 17% area comprising 17.5% population covering 20% villages in north-western and eastern parts of the island also falls under high vulnerable (VI= 61%-77%) zone. Findings revealed large spatial heterogeneity in the degree of vulnerability across the island and thus, demands devising area specific planning (adaptation and mitigation strategies) to address the climate change impact implications both at macro and micro levels.
Farmers' perceptions of and adaptation strategies to climate change and their determinants: the case of Punjab province, Pakistan

NASA Astrophysics Data System (ADS)

Abid, M.; Scheffran, J.; Schneider, U. A.; Ashfaq, M.

2015-05-01

Climate change is a global environmental threat to all economic sectors, particularly the agricultural sector. Pakistan is one of the countries negatively affected by climate change due to its high exposure to extreme events and low adaptive capacity. In Pakistan, farmers are the primary stakeholders in agriculture and are more at risk due to climate vulnerability. Based on farm household data from 450 households collected from three districts in three agroecological zones in the Punjab province of Pakistan, this study examines how farmers perceive climate change and how they adapt their farming in response to perceived changes in climate. The results demonstrate that awareness of climate change is widespread throughout the area, and farm households make adjustments to adapt their agriculture in response to climatic change. Overall 58% of the farm households adapted their farming to climate change. Changing crop varieties, changing planting dates, planting of shade trees and changing fertilizers were the main adaptation methods implemented by farm households in the study area. The results from the binary logistic model reveal that education, farm experience, household size, land area, tenancy status, ownership of a tube well, access to market information, information on weather forecasting and agricultural extension services all influence farmers' choices of adaptation measures. The results also indicate that adaptation to climate change is constrained by several factors such as lack of information, lack of money, resource constraints and shortage of irrigation water in the study area. Findings of the study suggest the need for greater investment in farmer education and improved institutional setup for climate change adaptation to improve farmers' wellbeing.
Wintertime urban heat island modified by global climate change over Japan

NASA Astrophysics Data System (ADS)

Hara, M.

2015-12-01

Urban thermal environment change, especially, surface air temperature (SAT) rise in metropolitan areas, is one of the major recent issues in urban areas. The urban thermal environmental change affects not only human health such as heat stroke, but also increasing infectious disease due to spreading out virus vectors habitat and increase of industry and house energy consumption. The SAT rise is mostly caused by global climate change and urban heat island (hereafter UHI) by urbanization. The population in Tokyo metropolitan area is over 30 millions and the Tokyo metropolitan area is one of the biggest megacities in the world. The temperature rise due to urbanization seems comparable to the global climate change in the major megacities. It is important to project how the urbanization and the global climate change affect to the future change of urban thermal environment to plan the adaptation and mitigation policy. To predict future SAT change in urban scale, we should estimate future UHI modified by the global climate change. This study investigates change in UHI intensity (UHII) of major metropolitan areas in Japan by effects of the global climate change. We performed a series of climate simulations. Present climate simulations with and without urban process are conducted for ten seasons using a high-resolution numerical climate model, the Weather Research and Forecasting (WRF) model. Future climate projections with and without urban process are also conducted. The future projections are performed using the pseudo global warming method, assuming 2050s' initial and boundary conditions estimated by a GCM under the RCP scenario. Simulation results indicated that UHII would be enhanced more than 30% in Tokyo during the night due to the global climate change. The enhancement of urban heat island is mostly caused by change of lower atmospheric stability.

Climate driven crop planting date in the ACME Land Model (ALM): Impacts on productivity and yield

NASA Astrophysics Data System (ADS)

Drewniak, B.

2017-12-01

Climate is one of the key drivers of crop suitability and productivity in a region. The influence of climate and weather on the growing season determine the amount of time crops spend in each growth phase, which in turn impacts productivity and, more importantly, yields. Planting date can have a strong influence on yields with earlier planting generally resulting in higher yields, a sensitivity that is also present in some crop models. Furthermore, planting date is already changing and may continue, especially if longer growing seasons caused by future climate change drive early (or late) planting decisions. Crop models need an accurate method to predict plant date to allow these models to: 1) capture changes in crop management to adapt to climate change, 2) accurately model the timing of crop phenology, and 3) improve crop simulated influences on carbon, nutrient, energy, and water cycles. Previous studies have used climate as a predictor for planting date. Climate as a plant date predictor has more advantages than fixed plant dates. For example, crop expansion and other changes in land use (e.g., due to changing temperature conditions), can be accommodated without additional model inputs. As such, a new methodology to implement a predictive planting date based on climate inputs is added to the Accelerated Climate Model for Energy (ACME) Land Model (ALM). The model considers two main sources of climate data important for planting: precipitation and temperature. This method expands the current temperature threshold planting trigger and improves the estimated plant date in ALM. Furthermore, the precipitation metric for planting, which synchronizes the crop growing season with the wettest months, allows tropical crops to be introduced to the model. This presentation will demonstrate how the improved model enhances the ability of ALM to capture planting date compared with observations. More importantly, the impact of changing the planting date and introducing tropical crops will be explored. Those impacts include discussions on productivity, yield, and influences on carbon and energy fluxes.
INTRODUCTION: Focus on Climate Engineering: Intentional Intervention in the Climate System

NASA Astrophysics Data System (ADS)

2009-12-01

Geoengineering techniques for countering climate change have been receiving much press recently as a `Plan B' if a global deal to tackle climate change is not agreed at the COP15 negotiations in Copenhagen this December. However, the field is controversial as the methods may have unforeseen consequences, potentially making temperatures rise in some regions or reducing rainfall, and many aspects remain under-researched. This focus issue of Environmental Research Letters is a collection of research articles, invited by David Keith, University of Calgary, and Ken Caldeira, Carnegie Institution, that present and evaluate different methods for engineering the Earth's climate. Not only do the letters in this issue highlight various methods of climate engineering but they also detail the arguments for and against climate engineering as a concept. Further reading Focus on Geoengineering at http://environmentalresearchweb.org/cws/subject/tag=geoengineering IOP Conference Series: Earth and Environmental Science is an open-access proceedings service available at www.iop.org/EJ/journal/ees Focus on Climate Engineering: Intentional Intervention in the Climate System Contents Modification of cirrus clouds to reduce global warming David L Mitchell and William Finnegan Climate engineering and the risk of rapid climate change Andrew Ross and H Damon Matthews Researching geoengineering: should not or could not? Martin Bunzl Of mongooses and mitigation: ecological analogues to geoengineering H Damon Matthews and Sarah E Turner Toward ethical norms and institutions for climate engineering research David R Morrow, Robert E Kopp and Michael Oppenheimer On the possible use of geoengineering to moderate specific climate change impacts Michael C MacCracken The impact of geoengineering aerosols on stratospheric temperature and ozone P Heckendorn, D Weisenstein, S Fueglistaler, B P Luo, E Rozanov, M Schraner, L W Thomason and T Peter The fate of the Greenland Ice Sheet in a geoengineered, high CO2 world Peter J Irvine, Daniel J Lunt, Emma J Stone and Andy Ridgwell Assessing the benefits of crop albedo bio-geoengineering Joy S Singarayer, Andy Ridgwell and Peter Irvine Can we control El Niño? Douglas G MacMynowski Geoengineering by cloud seeding: influence on sea ice and climate system Philip J Rasch, John Latham and Chih-Chieh (Jack) Chen
Variance analysis of forecasted streamflow maxima in a wet temperate climate

NASA Astrophysics Data System (ADS)

Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.

2018-05-01

Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.
Pacific-Australia Climate Change Science and Adaptation Planning program: supporting climate science and enhancing climate services in Pacific Island Countries

NASA Astrophysics Data System (ADS)

Kuleshov, Yuriy; Jones, David; Hendon, Harry; Charles, Andrew; Shelton, Kay; de Wit, Roald; Cottrill, Andrew; Nakaegawa, Toshiyuki; Atalifo, Terry; Prakash, Bipendra; Seuseu, Sunny; Kaniaha, Salesa

2013-04-01

Over the past few years, significant progress in developing climate science for the Pacific has been achieved through a number of research projects undertaken under the Australian government International Climate Change Adaptation Initiative (ICCAI). Climate change has major impact on Pacific Island Countries and advancement in understanding past, present and futures climate in the region is vital for island nation to develop adaptation strategies to their rapidly changing environment. This new science is now supporting new services for a wide range of stakeholders in the Pacific through the National Meteorological Agencies of the region. Seasonal climate prediction is particularly important for planning in agriculture, tourism and other weather-sensitive industries, with operational services provided by all National Meteorological Services in the region. The interaction between climate variability and climate change, for example during droughts or very warm seasons, means that much of the early impacts of climate change are being felt through seasonal variability. A means to reduce these impacts is to improve forecasts to support decision making. Historically, seasonal climate prediction has been developed based on statistical past relationship. Statistical methods relate meteorological variables (e.g. temperature and rainfall) to indices which describe large-scale environment (e.g. ENSO indices) using historical data. However, with observed climate change, statistical approaches based on historical data are getting less accurate and less reliable. Recognising the value of seasonal forecasts, we have used outputs of a dynamical model POAMA (Predictive Ocean Atmosphere Model for Australia), to develop web-based information tools (http://poama.bom.gov.au/experimental/pasap/index.shtml) which are now used by climate services in 15 partner countries in the Pacific for preparing seasonal climate outlooks. Initial comparison conducted during 2012 has shown that the predictive skill of POAMA is consistently higher than skill of statistical-based method. Presently, under the Pacific-Australia Climate Change Science and Adaptation Planning (PACCSAP) program, we are developing dynamical model-based seasonal climate prediction for climate extremes. Of particular concern are tropical cyclones which are the most destructive weather systems that impact on coastal areas of Australia and Pacific Island Countries. To analyse historical cyclone data, we developed a consolidate archive for the Southern Hemisphere and North-Western Pacific (http://www.bom.gov.au/cyclone/history/tracks/). Using dynamical climate models (POAMA and Japan Meteorological Agency's model), we work on improving accuracy of seasonal forecasts of tropical cyclone activity for the regions of Western Pacific. Improved seasonal climate prediction based on dynamical models will further enhance climate services in Australia and Pacific Island Countries.
Downscaling Global Emissions and Its Implications Derived from Climate Model Experiments

PubMed Central

Abe, Manabu; Kinoshita, Tsuguki; Hasegawa, Tomoko; Kawase, Hiroaki; Kushida, Kazuhide; Masui, Toshihiko; Oka, Kazutaka; Shiogama, Hideo; Takahashi, Kiyoshi; Tatebe, Hiroaki; Yoshikawa, Minoru

2017-01-01

In climate change research, future scenarios of greenhouse gas and air pollutant emissions generated by integrated assessment models (IAMs) are used in climate models (CMs) and earth system models to analyze future interactions and feedback between human activities and climate. However, the spatial resolutions of IAMs and CMs differ. IAMs usually disaggregate the world into 10–30 aggregated regions, whereas CMs require a grid-based spatial resolution. Therefore, downscaling emissions data from IAMs into a finer scale is necessary to input the emissions into CMs. In this study, we examined whether differences in downscaling methods significantly affect climate variables such as temperature and precipitation. We tested two downscaling methods using the same regionally aggregated sulfur emissions scenario obtained from the Asian-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model. The downscaled emissions were fed into the Model for Interdisciplinary Research on Climate (MIROC). One of the methods assumed a strong convergence of national emissions intensity (e.g., emissions per gross domestic product), while the other was based on inertia (i.e., the base-year remained unchanged). The emissions intensities in the downscaled spatial emissions generated from the two methods markedly differed, whereas the emissions densities (emissions per area) were similar. We investigated whether the climate change projections of temperature and precipitation would significantly differ between the two methods by applying a field significance test, and found little evidence of a significant difference between the two methods. Moreover, there was no clear evidence of a difference between the climate simulations based on these two downscaling methods. PMID:28076446
Climate Change, Foodborne Pathogens and Illness in Higher-Income Countries.

PubMed

Lake, I R; Barker, G C

2018-03-01

We present a review of the likely consequences of climate change for foodborne pathogens and associated human illness in higher-income countries. The relationships between climate and food are complex and hence the impacts of climate change uncertain. This makes it difficult to know which foodborne pathogens will be most affected, what the specific effects will be, and on what timescales changes might occur. Hence, a focus upon current capacity and adaptation potential against foodborne pathogens is essential. We highlight a number of developments that may enhance preparedness for climate change. These include the following: Adoption of novel surveillance methods, such as syndromic methods, to speed up detection and increase the fidelity of intervention in foodborne outbreaks Genotype-based approaches to surveillance of food pathogens to enhance spatiotemporal resolution in tracing and tracking of illness Ever increasing integration of plant, animal and human surveillance systems, One Health, to maximise potential for identifying threats Increased commitment to cross-border (global) information initiatives (including big data) Improved clarity regarding the governance of complex societal issues such as the conflict between food safety and food waste Strong user-centric (social) communications strategies to engage diverse stakeholder groups The impact of climate change upon foodborne pathogens and associated illness is uncertain. This emphasises the need to enhance current capacity and adaptation potential against foodborne illness. A range of developments are explored in this paper to enhance preparedness.
The effects of land use change and precipitation change on direct runoff in Wei River watershed, China.

PubMed

Dong, Leihua; Xiong, Lihua; Lall, Upmanu; Wang, Jiwu

2015-01-01

The principles and degrees to which land use change and climate change affect direct runoff generation are distinctive. In this paper, based on the MODIS data of land use in 1992 and 2003, the impacts of land use and climate change are explored using the Soil Conservation Service Curve Number (SCS-CN) method under two defined scenarios. In the first scenario, the precipitation is assumed to be constant, and thus the consequence of land use change could be evaluated. In the second scenario, the condition of land use is assumed to be constant, so the influence only induced by climate change could be assessed. Combining the conclusions of two scenarios, the effects of land use and climate change on direct runoff volume can be separated. At last, it is concluded: for the study basin, the land use types which have the greatest effect on direct runoff generation are agricultural land and water body. For the big sub basins, the effect of land use change is generally larger than that of climate change; for middle and small sub basins, most of them suffer more from land use change than from climate change.
Satellite passive microwave detection of surface water inundation changes over the pan-Arctic from AMSR

NASA Astrophysics Data System (ADS)

Du, J.; Kimball, J. S.; Jones, L. A.; Watts, J. D.

2016-12-01

Climate is one of the key drivers of crop suitability and productivity in a region. The influence of climate and weather on the growing season determine the amount of time crops spend in each growth phase, which in turn impacts productivity and, more importantly, yields. Planting date can have a strong influence on yields with earlier planting generally resulting in higher yields, a sensitivity that is also present in some crop models. Furthermore, planting date is already changing and may continue, especially if longer growing seasons caused by future climate change drive early (or late) planting decisions. Crop models need an accurate method to predict plant date to allow these models to: 1) capture changes in crop management to adapt to climate change, 2) accurately model the timing of crop phenology, and 3) improve crop simulated influences on carbon, nutrient, energy, and water cycles. Previous studies have used climate as a predictor for planting date. Climate as a plant date predictor has more advantages than fixed plant dates. For example, crop expansion and other changes in land use (e.g., due to changing temperature conditions), can be accommodated without additional model inputs. As such, a new methodology to implement a predictive planting date based on climate inputs is added to the Accelerated Climate Model for Energy (ACME) Land Model (ALM). The model considers two main sources of climate data important for planting: precipitation and temperature. This method expands the current temperature threshold planting trigger and improves the estimated plant date in ALM. Furthermore, the precipitation metric for planting, which synchronizes the crop growing season with the wettest months, allows tropical crops to be introduced to the model. This presentation will demonstrate how the improved model enhances the ability of ALM to capture planting date compared with observations. More importantly, the impact of changing the planting date and introducing tropical crops will be explored. Those impacts include discussions on productivity, yield, and influences on carbon and energy fluxes.
Sensitivity of the projected hydroclimatic environment of the Delaware River basin to formulation of potential evapotranspiration

USGS Publications Warehouse

Williamson, Tanja N.; Nystrom, Elizabeth A.; Milly, Paul C.D.

2016-01-01

The Delaware River Basin (DRB) encompasses approximately 0.4 % of the area of the United States (U.S.), but supplies water to 5 % of the population. We studied three forested tributaries to quantify the potential climate-driven change in hydrologic budget for two 25-year time periods centered on 2030 and 2060, focusing on sensitivity to the method of estimating potential evapotranspiration (PET) change. Hydrology was simulated using the Water Availability Tool for Environmental Resources (Williamson et al. 2015). Climate-change scenarios for four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCMs) and two Representative Concentration Pathways (RCPs) were used to derive monthly change factors for temperature (T), precipitation (PPT), and PET according to the energy-based method of Priestley and Taylor (1972). Hydrologic simulations indicate a general increase in annual (especially winter) streamflow (Q) as early as 2030 across the DRB, with a larger increase by 2060. This increase in Q is the result of (1) higher winter PPT, which outweighs an annual actual evapotranspiration (AET) increase and (2) (for winter) a major shift away from storage of PPT as snow pack. However, when PET change is evaluated instead using the simpler T-based method of Hamon (1963), the increases in Q are small or even negative. In fact, the change of Q depends as much on PET method as on time period or RCP. This large sensitivity and associated uncertainty underscore the importance of exercising caution in the selection of a PET method for use in climate-change analyses.
Contributions of climate change to the boundary shifts in the farming-pastoral ecotone in northern China since 1970

NASA Astrophysics Data System (ADS)

Shi, W.; Liu, Y.; Shi, X.

2017-12-01

Critical transitions of farming-pastoral ecotone (FPE) boundaries can be affected by climate change and human activities, yet current studies have not adequately analyzed the spatially explicit contributions of climate change to FPE boundary shifts, particularly those in different regions and periods. In this study, we present a series of analyses at the point (gravity center analysis), line (boundary shifts detected using two methods) and area (spatial analysis) levels to quantify climate contributions at the 1 km scale in each ecological functional region during three study periods from the 1970s to the 2000s using climate and land use data. Both gravity center analysis and boundary shift detection reveal similar spatial patterns, with more extensive boundary shifts in the northeastern and southeastern parts of the FPE in northern China, especially during the 1970s-1980s and 1990s-2000s. Climate contributions in the X- and Y-coordinate directions and in the directions of transects along boundaries show that significant differences in climate contributions to FPE boundary shifts exist in different ecological regions during the three periods. Additionally, the results in different directions exhibit good agreement in most of the ecological functional regions during most of the periods. However, the contribution values in the directions of transects along the boundaries (with 1-17%) were always smaller than those in the X-and Y-coordinate directions (4-56%), which suggests that the analysis in the transect directions is more stable and reasonable. Thus, this approach provides an alternative method for detecting the climate contributions to boundary shifts associated with land use changes. Spatial analysis of the relationship between climate change and land use change in the context of FPE boundary shifts in northern China provides further evidence and explanation of the driving forces of climate change. Our findings suggest that an improved understanding of the quantitative contributions of climate change to the formation and transition of the FPE in northern China is essential for addressing current and future adaptation and mitigation measures and regional land use management.
Developing convolutional neural networks for measuring climate change opinions from social media data

NASA Astrophysics Data System (ADS)

Mao, H.; Bhaduri, B. L.

2016-12-01

Understanding public opinions on climate change is important for policy making. Public opinion, however, is typically measured with national surveys, which are often too expensive and thus being updated at a low frequency. Twitter has become a major platform for people to express their opinions on social and political issues. Our work attempts to understand if Twitter data can provide complimentary insights about climate change perceptions. Since the nature of social media is real-time, this data source can especially help us understand how public opinion changes over time in response to climate events and hazards, which though is very difficult to be captured by manual surveys. We use the Twitter Streaming API to collect tweets that contain keywords, "climate change" or "#climatechange". Traditional machine-learning based opinion mining algorithms require a significant amount of labeled data. Data labeling is notoriously time consuming. To address this problem, we use hashtags (a significant feature used to mark topics of tweets) to annotate tweets automatically. For example, hashtags, #climatedenial and #climatescam, are negative opinion labels, while #actonclimate and #climateaction are positive. Following this method, we can obtain a large amount of training data without human labor. This labeled dataset is used to train a deep convolutional neural network that classifies tweets into positive (i.e. believe in climate change) and negative (i.e. do not believe). Based on the positive/negative tweets obtained, we will further analyze risk perceptions and opinions towards policy support. In addition, we analyze twitter user profiles to understand the demographics of proponents and opponents of climate change. Deep learning techniques, especially convolutional deep neural networks, have achieved much success in computer vision. In this work, we propose a convolutional neural network architecture for understanding opinions within text. This method is compared with lexicon-based opinion analysis approaches. Results and the advantages/limitations of this method are to be discussed.
Choosing and using climate change scenarios for ecological-impact assessments and conservation decisions

USGS Publications Warehouse

Amy K. Snover,; Nathan J. Mantua,; Littell, Jeremy; Michael A. Alexander,; Michelle M. McClure,; Janet Nye,

2013-01-01

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment.
Influence of climate change on the flowering of temperate fruit trees

NASA Astrophysics Data System (ADS)

Perez-Lopez, D.; Ruiz-Ramos, M.; Sánchez-Sánchez, E.; Centeno, A.; Prieto-Egido, I.; Lopez-de-la-Franca, N.

2012-04-01

It is well known that winter chilling is necessary for the flowering of temperate trees. The chilling requirement is a criterion for choosing a species or variety at a given location. Also chemistry products can be used for reducing the chilling-hours needs but make our production more expensive. This study first analysed the observed values of chilling hours for some representative agricultural locations in Spain for the last three decades and their projected changes under climate change scenarios. Usually the chilling is measured and calculated as chilling-hours, and different methods have been used to calculate them (e.g. Richarson et al., 1974 among others) according to the species considered. For our objective North Carolina method (Shaltout and Unrath, 1983) was applied for apples, Utah method (Richardson et al. 1974) for peach and grapevine and the approach used by De Melo-Abreu et al. (2004) for olive trees. The influence of climate change in temperate trees was studied by calculating projections of chilling-hours with climate data from Regional Climate Models (RCMs) at high resolution (25 km) from the European Project ENSEMBLES (http://www.ensembles-eu.org/). These projections will allow for analysing the modelled variations of chill-hours between 2nd half of 20C and 1st half of 21C at the study locations.
Population response to climate change: linear vs. non-linear modeling approaches.

PubMed

Ellis, Alicia M; Post, Eric

2004-03-31

Research on the ecological consequences of global climate change has elicited a growing interest in the use of time series analysis to investigate population dynamics in a changing climate. Here, we compare linear and non-linear models describing the contribution of climate to the density fluctuations of the population of wolves on Isle Royale, Michigan from 1959 to 1999. The non-linear self excitatory threshold autoregressive (SETAR) model revealed that, due to differences in the strength and nature of density dependence, relatively small and large populations may be differentially affected by future changes in climate. Both linear and non-linear models predict a decrease in the population of wolves with predicted changes in climate. Because specific predictions differed between linear and non-linear models, our study highlights the importance of using non-linear methods that allow the detection of non-linearity in the strength and nature of density dependence. Failure to adopt a non-linear approach to modelling population response to climate change, either exclusively or in addition to linear approaches, may compromise efforts to quantify ecological consequences of future warming.
78 FR 24287 - Call for Expert Reviewers to the U.S. Government Review of the 2013 Revised Supplementary Methods...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-24

... socio-economic information for understanding the scientific basis of climate change, potential impacts... submissions by Parties to the U.N. Framework Convention on Climate Change (UNFCCC). These reports are... SUMMARY: The United States Global Change Research Program, in cooperation with the Department of State...
Testing a Weather Generator for Downscaling Climate Change Projections over Switzerland

NASA Astrophysics Data System (ADS)

Keller, Denise E.; Fischer, Andreas M.; Liniger, Mark A.; Appenzeller, Christof; Knutti, Reto

2016-04-01

Climate information provided by global or regional climate models (RCMs) are often too coarse and prone to substantial biases, making it impossible to directly use daily time-series of the RCMs for local assessments and in climate impact models. Hence, statistical downscaling becomes necessary. For the Swiss National Climate Change Initiative (CH2011), a delta-change approach was used to provide daily climate projections at the local scale. This data have the main limitations that changes in variability, extremes and in the temporal structure, such as changes in the wet day frequency, are not reproduced. The latter is a considerable downside of the delta-change approach for many impact applications. In this regard, stochastic weather generators (WGs) are an appealing technique that allow the simulation of multiple realizations of synthetic weather sequences consistent with the locally observed weather statistics and its future changes. Here, we analyse a Richardson-type weather generator (WG) as an alternative method to downscale daily precipitation, minimum and maximum temperature. The WG is calibrated for 26 Swiss stations and the reference period 1980-2009. It is perturbed with change factors derived from 12 RCMs (ENSEMBLES) to represent the climate of 2070-2099 assuming the SRES A1B emission scenario. The WG can be run in multi-site mode, making it especially attractive for impact-modelers that rely on a realistic spatial structure in downscaled time-series. The results from the WG are benchmarked against the original delta-change approach that applies mean additive or multiplicative adjustments to the observations. According to both downscaling methods, the results reveal area-wide mean temperature increases and a precipitation decrease in summer, consistent with earlier studies. For the summer drying, the WG indicates primarily a decrease in wet-day frequency and correspondingly an increase in mean dry spell length by around 18% - 40% at low-elevation stations. By construction, these potential changes cannot be represented by a delta-change approach. In winter, both methods project a shortening of the frost period (-30 to -60 days) and a decrease of snow days (-20% to -100%). The WG demonstrates though, that almost present-day conditions in snow-days could still occur in the future. As expected, both methods have difficulties in representing extremes. If users focus on changes in temporal sequences and need a large number of future realizations that are spatially consistent, it is recommended to use data from a WG instead of a delta-change approach.
Dependence of future mortality changes on global CO2 concentrations: A review.

PubMed

Lee, Jae Young; Choi, Hayoung; Kim, Ho

2018-05-01

The heterogeneity among previous studies of future mortality projections due to climate change has often hindered comparisons and syntheses of resulting impacts. To address this challenge, the present study introduced a novel method to normalize the results from projection studies according to different baseline and projection periods and climate scenarios, thereby facilitating comparison and synthesis. This study reviewed the 15 previous studies involving projected climate change-related mortality under Representative Concentration Pathways. To synthesize their results, we first reviewed the important study design elements that affected the reported results in previous studies. Then, we normalized the reported results by CO 2 concentration in order to eliminate the effects of the baseline period, projection period, and climate scenario choices. For twenty-five locations worldwide, the normalized percentage changes in temperature-attributable mortality per 100 ppm increase in global CO 2 concentrations ranged between 41.9% and 330%, whereas those of total mortality ranged between 0.3% and 4.8%. The normalization methods presented in this work will guide future studies to provide their results in a normalized format and facilitate research synthesis to reinforce our understanding on the risk of climate change. Copyright © 2018 Elsevier Ltd. All rights reserved.
Revision and application of the LINKAGES model to simulate forest growth in central hardwood landscapes in response to climate change

Treesearch

William D. Dijak; Brice B. Hanberry; Jacob S. Fraser; Hong S. He; Wen J. Wang; Frank R. Thompson

2017-01-01

Context. Global climate change impacts forest growth and methods of modeling those impacts at the landscape scale are needed to forecast future forest species composition change and abundance. Changes in forest landscapes will affect ecosystem processes and services such as succession and disturbance, wildlife habitat, and production of forest...
Statistical methods for change-point detection in surface temperature records

NASA Astrophysics Data System (ADS)

Pintar, A. L.; Possolo, A.; Zhang, N. F.

2013-09-01

We describe several statistical methods to detect possible change-points in a time series of values of surface temperature measured at a meteorological station, and to assess the statistical significance of such changes, taking into account the natural variability of the measured values, and the autocorrelations between them. These methods serve to determine whether the record may suffer from biases unrelated to the climate signal, hence whether there may be a need for adjustments as considered by M. J. Menne and C. N. Williams (2009) "Homogenization of Temperature Series via Pairwise Comparisons", Journal of Climate 22 (7), 1700-1717. We also review methods to characterize patterns of seasonality (seasonal decomposition using monthly medians or robust local regression), and explain the role they play in the imputation of missing values, and in enabling robust decompositions of the measured values into a seasonal component, a possible climate signal, and a station-specific remainder. The methods for change-point detection that we describe include statistical process control, wavelet multi-resolution analysis, adaptive weights smoothing, and a Bayesian procedure, all of which are applicable to single station records.
Projecting future precipitation and temperature at sites with diverse climate through multiple statistical downscaling schemes

NASA Astrophysics Data System (ADS)

Vallam, P.; Qin, X. S.

2017-10-01

Anthropogenic-driven climate change would affect the global ecosystem and is becoming a world-wide concern. Numerous studies have been undertaken to determine the future trends of meteorological variables at different scales. Despite these studies, there remains significant uncertainty in the prediction of future climates. To examine the uncertainty arising from using different schemes to downscale the meteorological variables for the future horizons, projections from different statistical downscaling schemes were examined. These schemes included statistical downscaling method (SDSM), change factor incorporated with LARS-WG, and bias corrected disaggregation (BCD) method. Global circulation models (GCMs) based on CMIP3 (HadCM3) and CMIP5 (CanESM2) were utilized to perturb the changes in the future climate. Five study sites (i.e., Alice Springs, Edmonton, Frankfurt, Miami, and Singapore) with diverse climatic conditions were chosen for examining the spatial variability of applying various statistical downscaling schemes. The study results indicated that the regions experiencing heavy precipitation intensities were most likely to demonstrate the divergence between the predictions from various statistical downscaling methods. Also, the variance computed in projecting the weather extremes indicated the uncertainty derived from selection of downscaling tools and climate models. This study could help gain an improved understanding about the features of different downscaling approaches and the overall downscaling uncertainty.

Uncertainty in projected point precipitation extremes for hydrological impact analysis of climate change

NASA Astrophysics Data System (ADS)

Van Uytven, Els; Willems, Patrick

2017-04-01

Current trends in the hydro-meteorological variables indicate the potential impact of climate change on hydrological extremes. Therefore, they trigger an increased importance climate adaptation strategies in water management. The impact of climate change on hydro-meteorological and hydrological extremes is, however, highly uncertain. This is due to uncertainties introduced by the climate models, the internal variability inherent to the climate system, the greenhouse gas scenarios and the statistical downscaling methods. In view of the need to define sustainable climate adaptation strategies, there is a need to assess these uncertainties. This is commonly done by means of ensemble approaches. Because more and more climate models and statistical downscaling methods become available, there is a need to facilitate the climate impact and uncertainty analysis. A Climate Perturbation Tool has been developed for that purpose, which combines a set of statistical downscaling methods including weather typing, weather generator, transfer function and advanced perturbation based approaches. By use of an interactive interface, climate impact modelers can apply these statistical downscaling methods in a semi-automatic way to an ensemble of climate model runs. The tool is applicable to any region, but has been demonstrated so far to cases in Belgium, Suriname, Vietnam and Bangladesh. Time series representing future local-scale precipitation, temperature and potential evapotranspiration (PET) conditions were obtained, starting from time series of historical observations. Uncertainties on the future meteorological conditions are represented in two different ways: through an ensemble of time series, and a reduced set of synthetic scenarios. The both aim to span the full uncertainty range as assessed from the ensemble of climate model runs and downscaling methods. For Belgium, for instance, use was made of 100-year time series of 10-minutes precipitation observations and daily temperature and PET observations at Uccle and a large ensemble of 160 global climate model runs (CMIP5). They cover all four representative concentration pathway based greenhouse gas scenarios. While evaluating the downscaled meteorological series, particular attention was given to the performance of extreme value metrics (e.g. for precipitation, by means of intensity-duration-frequency statistics). Moreover, the total uncertainty was decomposed in the fractional uncertainties for each of the uncertainty sources considered. Research assessing the additional uncertainty due to parameter and structural uncertainties of the hydrological impact model is ongoing.
Scenario-based stakeholder engagement: incorporating stakeholders preferences into coastal planning for climate change.

PubMed

Tompkins, Emma L; Few, Roger; Brown, Katrina

2008-09-01

Climate change poses many challenges for ecosystem and resource management. In particular, coastal planners are struggling to find ways to prepare for the potential impacts of future climate change while dealing with immediate pressures. Decisions on how to respond to future risks are complicated by the long time horizons and the uncertainty associated with the distribution of impacts. Existing coastal zone management approaches in the UK either do not adequately incorporate changing stakeholder preferences, or effectively ensure that stakeholders are aware of the trade-offs inherent in any coastal management decision. Using a novel method, scenario-based stakeholder engagement, which brings together stakeholder analysis, climate change management scenarios and deliberative techniques, the necessary trade-offs associated with long term coastal planning are explored. The method is applied to two case studies of coastal planning in Christchurch Bay on the south coast of England and the Orkney Islands off the north coast of Scotland. A range of conflicting preferences exist on the ideal governance structure to manage the coast under different climate change scenarios. In addition, the results show that public understanding of the trade-offs that have to be made is critical in gaining some degree of public support for long term coastal decision-making. We conclude that scenario-based stakeholder engagement is a useful tool to facilitate coastal management planning that takes into account the complexities and challenges of climate change, and could be used in conjunction with existing approaches such as the Shoreline Management Planning process.
Compounding Impacts of Human-Induced Water Stress and Climate Change on Water Availability

NASA Technical Reports Server (NTRS)

Mehran, Ali; AghaKouchak, Amir; Nakhjiri, Navid; Stewardson, Michael J.; Peel, Murray C.; Phillips, Thomas J.; Wada, Yoshihide; Ravalico, Jakin K.

2017-01-01

The terrestrial phase of the water cycle can be seriously impacted by water management and human water use behavior (e.g., reservoir operation, and irrigation withdrawals). Here we outline a method for assessing water availability in a changing climate, while explicitly considering anthropogenic water demand scenarios and water supply infrastructure designed to cope with climatic extremes. The framework brings a top-down and bottom-up approach to provide localized water assessment based on local water supply infrastructure and projected water demands. When our framework is applied to southeastern Australia we find that, for some combinations of climatic change and water demand, the region could experience water stress similar or worse than the epic Millennium Drought. We show considering only the influence of future climate on water supply, and neglecting future changes in water demand and water storage augmentation might lead to opposing perspectives on future water availability. While human water use can significantly exacerbate climate change impacts on water availability, if managed well, it allows societies to react and adapt to a changing climate. The methodology we present offers a unique avenue for linking climatic and hydrologic processes to water resource supply and demand management and other human interactions.
Compounding Impacts of Human-Induced Water Stress and Climate Change on Water Availability.

PubMed

Mehran, Ali; AghaKouchak, Amir; Nakhjiri, Navid; Stewardson, Michael J; Peel, Murray C; Phillips, Thomas J; Wada, Yoshihide; Ravalico, Jakin K

2017-07-24

The terrestrial phase of the water cycle can be seriously impacted by water management and human water use behavior (e.g., reservoir operation, and irrigation withdrawals). Here we outline a method for assessing water availability in a changing climate, while explicitly considering anthropogenic water demand scenarios and water supply infrastructure designed to cope with climatic extremes. The framework brings a top-down and bottom-up approach to provide localized water assessment based on local water supply infrastructure and projected water demands. When our framework is applied to southeastern Australia we find that, for some combinations of climatic change and water demand, the region could experience water stress similar or worse than the epic Millennium Drought. We show considering only the influence of future climate on water supply, and neglecting future changes in water demand and water storage augmentation might lead to opposing perspectives on future water availability. While human water use can significantly exacerbate climate change impacts on water availability, if managed well, it allows societies to react and adapt to a changing climate. The methodology we present offers a unique avenue for linking climatic and hydrologic processes to water resource supply and demand management and other human interactions.
Multi-criteria evaluation of CMIP5 GCMs for climate change impact analysis

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Rana, Arun; Moradkhani, Hamid; Sharma, Ashish

2017-04-01

Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area.
Impacts of weighting climate models for hydro-meteorological climate change studies

NASA Astrophysics Data System (ADS)

Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe; Caya, Daniel

2017-06-01

Weighting climate models is controversial in climate change impact studies using an ensemble of climate simulations from different climate models. In climate science, there is a general consensus that all climate models should be considered as having equal performance or in other words that all projections are equiprobable. On the other hand, in the impacts and adaptation community, many believe that climate models should be weighted based on their ability to better represent various metrics over a reference period. The debate appears to be partly philosophical in nature as few studies have investigated the impact of using weights in projecting future climate changes. The present study focuses on the impact of assigning weights to climate models for hydrological climate change studies. Five methods are used to determine weights on an ensemble of 28 global climate models (GCMs) adapted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. Using a hydrological model, streamflows are computed over a reference (1961-1990) and future (2061-2090) periods, with and without post-processing climate model outputs. The impacts of using different weighting schemes for GCM simulations are then analyzed in terms of ensemble mean and uncertainty. The results show that weighting GCMs has a limited impact on both projected future climate in term of precipitation and temperature changes and hydrology in terms of nine different streamflow criteria. These results apply to both raw and post-processed GCM model outputs, thus supporting the view that climate models should be considered equiprobable.
Competition alters tree growth responses to climate at individual and stand scales

Treesearch

Kevin R. Ford; Ian K. Breckheimer; Jerry F. Franklin; James A. Freund; Steve J. Kroiss; Andrew J. Larson; Elinore J. Theobald; Janneke HilleRisLambers

2017-01-01

Understanding how climate affects tree growth is essential for assessing climate change impacts on forests but can be confounded by effects of competition, which strongly influences tree responses to climate. We characterized the joint influences of tree size, competition, and climate on diameter growth using hierarchical Bayesian methods applied to permanent sample...
How well are the climate indices related to the GRACE-observed total water storage changes in China?

NASA Astrophysics Data System (ADS)

Devaraju, B.; Vishwakarma, B.; Sneeuw, N. J.

2017-12-01

The fresh water availability over land masses is changing rapidly under the influence of climate change and human intervention. In order to manage our water resources and plan for a better future, we need to demarcate the role of climate change. The total water storage change in a region can be obtained from the GRACE satellite mission. On the other hand, many climate change indicators, for example ENSO, are derived from sea surface temperature. In this contribution we investigate the relationship between the total water storage change over China with the climate indices using statistical time-series decomposition techniques, such as Seasonal and Trend decomposition using Loess (STL), Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA). The anomalies in climate variables, such as sea surface temperature, are responsible for anomalous precipitation and thus an anomalous total water storage change over land. Therefore, it is imperative that we use a GRACE product that can capture anomalous water storage changes with unprecedented accuracy. Since filtering decreases the sensitivity of GRACE products substantially, we use the data-driven method of deviation for recovering the signal lost due to filtering. To this end, we are able to obtain the spatial fingerprint of individual climate index on total water storage change observed over China.
Projected wetland densities under climate change: Habitat loss but little geographic shift in conservation strategy

USGS Publications Warehouse

Sofaer, Helen R.; Skagen, Susan K.; Barsugli, Joseph J.; Rashford, Benjamin S.; Reese, Gordon C.; Hoeting, Jennifer A.; Wood, Andrew W.; Noon, Barry R.

2016-01-01

Climate change poses major challenges for conservation and management because it alters the area, quality, and spatial distribution of habitat for natural populations. To assess species’ vulnerability to climate change and target ongoing conservation investments, researchers and managers often consider the effects of projected changes in climate and land use on future habitat availability and quality and the uncertainty associated with these projections. Here, we draw on tools from hydrology and climate science to project the impact of climate change on the density of wetlands in the Prairie Pothole Region of the USA, a critical area for breeding waterfowl and other wetland-dependent species. We evaluate the potential for a trade-off in the value of conservation investments under current and future climatic conditions and consider the joint effects of climate and land use. We use an integrated set of hydrological and climatological projections that provide physically based measures of water balance under historical and projected future climatic conditions. In addition, we use historical projections derived from ten general circulation models (GCMs) as a baseline from which to assess climate change impacts, rather than historical climate data. This method isolates the impact of greenhouse gas emissions and ensures that modeling errors are incorporated into the baseline rather than attributed to climate change. Our work shows that, on average, densities of wetlands (here defined as wetland basins holding water) are projected to decline across the U.S. Prairie Pothole Region, but that GCMs differ in both the magnitude and the direction of projected impacts. However, we found little evidence for a shift in the locations expected to provide the highest wetland densities under current vs. projected climatic conditions. This result was robust to the inclusion of projected changes in land use under climate change. We suggest that targeting conservation towards wetland complexes containing both small and relatively large wetland basins, which is an ongoing conservation strategy, may also act to hedge against uncertainty in the effects of climate change.
Growth-climate relationships across topographic gradients in the northern Great Lakes

Treesearch

S.F. Dymond; A.W. D' Amato; Randy Kolka; P.V. Bolstad; Stephen Sebestyen; J.B. Bradford

2016-01-01

Climatic conditions exert important control over the growth, productivity, and distribution of forests, and characterizing these relationships is essential for understanding how forest ecosystems will respond to climate change. We used dendrochronological methods to develop climateâgrowth relationships for two dominant species, Populus tremuloides...
A survey of urban climate change experiments in 100 cities

PubMed Central

Castán Broto, Vanesa; Bulkeley, Harriet

2013-01-01

Cities are key sites where climate change is being addressed. Previous research has largely overlooked the multiplicity of climate change responses emerging outside formal contexts of decision-making and led by actors other than municipal governments. Moreover, existing research has largely focused on case studies of climate change mitigation in developed economies. The objective of this paper is to uncover the heterogeneous mix of actors, settings, governance arrangements and technologies involved in the governance of climate change in cities in different parts of the world. The paper focuses on urban climate change governance as a process of experimentation. Climate change experiments are presented here as interventions to try out new ideas and methods in the context of future uncertainties. They serve to understand how interventions work in practice, in new contexts where they are thought of as innovative. To study experimentation, the paper presents evidence from the analysis of a database of 627 urban climate change experiments in a sample of 100 global cities. The analysis suggests that, since 2005, experimentation is a feature of urban responses to climate change across different world regions and multiple sectors. Although experimentation does not appear to be related to particular kinds of urban economic and social conditions, some of its core features are visible. For example, experimentation tends to focus on energy. Also, both social and technical forms of experimentation are visible, but technical experimentation is more common in urban infrastructure systems. While municipal governments have a critical role in climate change experimentation, they often act alongside other actors and in a variety of forms of partnership. These findings point at experimentation as a key tool to open up new political spaces for governing climate change in the city. PMID:23805029
Knowledge and perceptions about the health impact of climate change among health sciences students in Ethiopia: a cross-sectional study.

PubMed

Nigatu, Andualem S; Asamoah, Benedict O; Kloos, Helmut

2014-06-11

Climate change affects human health in various ways. Health planners and policy makers are increasingly addressing potential health impacts of climate change. Ethiopia is vulnerable to these impacts. Assessing students' knowledge, understanding and perception about the health impact of climate change may promote educational endeavors to increase awareness of health impacts linked to climate change and to facilitate interventions. A cross-sectional study using a questionnaire was carried out among the health science students at Haramaya University. Quantitative methods were used to analyze the results. Over three quarters of the students were aware of health consequences of climate change, with slightly higher rates in females than males and a range from 60.7% (pharmacy students) to 100% (environmental health and post-graduate public health students). Electronic mass media was reportedly the major source of information but almost all (87.7%) students stated that their knowledge was insufficient to fully understand the public health impacts of climate change. Students who knew about climate change were more likely to perceive it as a serious health threat than those who were unaware of these impacts [OR: 17.8, 95% CI: 8.8-32.1] and also considered their departments to be concerned about climate change (OR: 7.3, 95% CI: 2.8-18.8), a perception that was also significantly more common among students who obtained their information from the electronic mass media and schools (p < 0.05). Using electronic mass media was also significantly associated with knowledge about the health impacts of climate change. Health sciences students at Haramaya University may benefit from a more comprehensive curriculum on climate change and its impacts on health.
Variation in Estimated Ozone-Related Health Impacts of Climate Change due to Modeling Choices and Assumptions

PubMed Central

Post, Ellen S.; Grambsch, Anne; Weaver, Chris; Morefield, Philip; Leung, Lai-Yung; Nolte, Christopher G.; Adams, Peter; Liang, Xin-Zhong; Zhu, Jin-Hong; Mahoney, Hardee

2012-01-01

Background: Future climate change may cause air quality degradation via climate-induced changes in meteorology, atmospheric chemistry, and emissions into the air. Few studies have explicitly modeled the potential relationships between climate change, air quality, and human health, and fewer still have investigated the sensitivity of estimates to the underlying modeling choices. Objectives: Our goal was to assess the sensitivity of estimated ozone-related human health impacts of climate change to key modeling choices. Methods: Our analysis included seven modeling systems in which a climate change model is linked to an air quality model, five population projections, and multiple concentration–response functions. Using the U.S. Environmental Protection Agency’s (EPA’s) Environmental Benefits Mapping and Analysis Program (BenMAP), we estimated future ozone (O3)-related health effects in the United States attributable to simulated climate change between the years 2000 and approximately 2050, given each combination of modeling choices. Health effects and concentration–response functions were chosen to match those used in the U.S. EPA’s 2008 Regulatory Impact Analysis of the National Ambient Air Quality Standards for O3. Results: Different combinations of methodological choices produced a range of estimates of national O3-related mortality from roughly 600 deaths avoided as a result of climate change to 2,500 deaths attributable to climate change (although the large majority produced increases in mortality). The choice of the climate change and the air quality model reflected the greatest source of uncertainty, with the other modeling choices having lesser but still substantial effects. Conclusions: Our results highlight the need to use an ensemble approach, instead of relying on any one set of modeling choices, to assess the potential risks associated with O3-related human health effects resulting from climate change. PMID:22796531
[Climate suitability for tea growing in Zhejiang Province].

PubMed

Jin, Zhi-Feng; Ye, Jian-Gang; Yang, Zai-Qiang; Sun, Rui; Hu, Bo; Li, Ren-Zhong

2014-04-01

It is important to quantitatively assess the climate suitability of tea and its response to climate change. Based on meteorological indices of tea growth and daily meteorological data from 1971 to 2010 in Zhejiang Province, three climate suitability models for single climate factors, including temperature, precipitation and sunshine, were established at a 10-day scale by using the fuzzy mathematics method, and a comprehensive climate suitability model was established with the geometric average method. The results indicated that the climate suitability was high in the tea growth season in Zhejiang Province, and the three kinds of climate suitability were all higher than 0.6. As for the single factor climate suitability, temperature suitability was the highest and sunshine suitability was the lowest. There were obvious inter-annual variations of tea climate suitability, with a decline trend in the 1970s, less variation in the 1980s, and an obvious incline trend after the 1990s. The change tendency of climate suitability for spring tea was similar with that of annual climate suitability, lower in the 1980s, higher in the 1970s and after the 1990s. However, the variation amplitude of the climate suitability for spring tea was larger. The climate suitability for summer tea and autumn tea showed a decline trend from 1971 to 2010.
Projections and downscaling of 21st century temperatures, precipitation, radiative fluxes and winds for the southwestern US, with focus on the Lake Tahoe basin

USGS Publications Warehouse

Dettinger, Michael D.

2013-01-01

Recent projections of global climate changes in response to increasing greenhouse-gas concentrations in the atmosphere include warming in the Southwestern US and, especially, in the vicinity of Lake Tahoe of from about +3°C to +6°C by end of century and changes in precipitation on the order of 5-10 % increases or (more commonly) decreases, depending on the climate model considered. Along with these basic changes, other climate variables like solar insolation, downwelling (longwave) radiant heat, and winds may change. Together these climate changes may result in changes in the hydrology of the Tahoe basin and potential changes in lake overturning and ecological regimes. Current climate projections, however, are generally spatially too coarse (with grid cells separated by 1 to 2° latitude and longitude) for direct use in assessments of the vulnerabilities of the much smaller Tahoe basin. Thus, daily temperatures, precipitation, winds, and downward radiation fluxes from selected global projections have been downscaled by a statistical method called the constructed-analogues method onto 10 to 12 km grids over the Southwest and especially over Lake Tahoe. Precipitation, solar insolation and winds over the Tahoe basin change only moderately (and with indeterminate signs) in the downscaled projections, whereas temperatures and downward longwave fluxes increase along with imposed increases in global greenhouse-gas concentrations.
Detecting and Attributing Health Burdens to Climate Change.

PubMed

Ebi, Kristie L; Ogden, Nicholas H; Semenza, Jan C; Woodward, Alistair

2017-08-07

Detection and attribution of health impacts caused by climate change uses formal methods to determine a ) whether the occurrence of adverse health outcomes has changed, and b ) the extent to which that change could be attributed to climate change. There have been limited efforts to undertake detection and attribution analyses in health. Our goal was to show a range of approaches for conducting detection and attribution analyses. Case studies for heatwaves, Lyme disease in Canada, and Vibrio emergence in northern Europe highlight evidence that climate change is adversely affecting human health. Changes in rates and geographic distribution of adverse health outcomes were detected, and, in each instance, a proportion of the observed changes could, in our judgment, be attributed to changes in weather patterns associated with climate change. The results of detection and attribution studies can inform evidence-based risk management to reduce current, and plan for future, changes in health risks associated with climate change. Gaining a better understanding of the size, timing, and distribution of the climate change burden of disease and injury requires reliable long-term data sets, more knowledge about the factors that confound and modify the effects of climate on health, and refinement of analytic techniques for detection and attribution. At the same time, significant advances are possible in the absence of complete data and statistical certainty: there is a place for well-informed judgments, based on understanding of underlying processes and matching of patterns of health, climate, and other determinants of human well-being. https://doi.org/10.1289/EHP1509.
Detecting and Attributing the Effects of Climate Change on the Distributions of Snake Species Over the Past 50 Years.

PubMed

Wu, Jianguo

2016-01-01

It is unclear whether the distributions of snakes have changed in association with climate change over the past years. We detected the distribution changes of snakes over the past 50 years and determined whether the changes could be attributed to recent climate change in China. Long-term records of the distribution of nine snake species in China, grey relationship analysis, fuzzy sets classification techniques, the consistency index, and attributed methods were used. Over the past 50 years, the distributions of snake species have changed in multiple directions, primarily shifting northwards, and most of the changes were related to the thermal index. Driven by climatic factors over the past 50 years, the distribution boundary and distribution centers of some species changed with the fluctuations. The observed and predicted changes in distribution were highly consistent for some snake species. The changes in the northern limits of distributions of nearly half of the species, as well as the southern and eastern limits, and the distribution centers of some snake species can be attributed to climate change.
The distributions of Chinese yak breeds in response to climate change over the past 50 years.

PubMed

Wu, Jianguo

2016-07-01

The effects of prior climate change on yak breed distributions are uncertain. Here, we measured changes in the distributions of 12 yak breeds over the past 50 years in China and examined whether the changes could be attributed to climate change. Long-term records of yak breed distribution, grey relational analysis, fuzzy sets classification techniques and attribution methods were used. Over the past 50 years, the distributions of several yak breeds have changed in multiple directions, mainly shifting northward or westward, and most of these changes are related to the thermal index. Driven by climate change over the past years, the suitable range and the distribution centers of certain yak breeds have changed with fluctuation and have mainly shifted northward, eastward or southward. The consistency of observed versus predicted changes in distribution boundaries or distribution centers is higher for certain yak breeds. Changes in the eastern distribution boundary of two yak breeds over the past 50 years can be attributed to climate change. © 2015 Japanese Society of Animal Science.
A community based approach to improving resilience of forests and water resources: A local and regional climate adaptation methodology

Treesearch

Toby Thaler; Gwen Griffith; Nancy Gilliam

2014-01-01

Forest-based ecosystem services are at risk from human-caused stressors, including climate change. Improving governance and management of forests to reduce impacts and increase community resilience to all stressors is the objective of forest-related climate change adaptation. The Model Forest Policy Program (MFPP) has applied one method designed to meet this objective...
Probabilistic Climate Scenario Information for Risk Assessment

NASA Astrophysics Data System (ADS)

Dairaku, K.; Ueno, G.; Takayabu, I.

2014-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. In order to develop probabilistic regional climate information that represents the uncertainty in climate scenario experiments in Japan, we compared the physics ensemble experiments using the 60km global atmospheric model of the Meteorological Research Institute (MRI-AGCM) with multi-model ensemble experiments with global atmospheric-ocean coupled models (CMIP3) of SRES A1b scenario experiments. The MRI-AGCM shows relatively good skills particularly in tropics for temperature and geopotential height. Variability in surface air temperature of physical ensemble experiments with MRI-AGCM was within the range of one standard deviation of the CMIP3 model in the Asia region. On the other hand, the variability of precipitation was relatively well represented compared with the variation of the CMIP3 models. Models which show the similar reproducibility in the present climate shows different future climate change. We couldn't find clear relationships between present climate and future climate change in temperature and precipitation. We develop a new method to produce probabilistic information of climate change scenarios by weighting model ensemble experiments based on a regression model (Krishnamurti et al., Science, 1999). The method can be easily applicable to other regions and other physical quantities, and also to downscale to finer-scale dependent on availability of observation dataset. The prototype of probabilistic information in Japan represents the quantified structural uncertainties of multi-model ensemble experiments of climate change scenarios. Acknowledgments: This study was supported by the SOUSEI Program, funded by Ministry of Education, Culture, Sports, Science and Technology, Government of Japan.

An observationally centred method to quantify local climate change as a distribution

NASA Astrophysics Data System (ADS)

Stainforth, David; Chapman, Sandra; Watkins, Nicholas

2013-04-01

For planning and adaptation, guidance on trends in local climate is needed at the specific thresholds relevant to particular impact or policy endeavours. This requires quantifying trends at specific quantiles in distributions of variables such as daily temperature or precipitation. These non-normal distributions vary both geographically and in time. The trends in the relevant quantiles may not simply follow the trend in the distribution mean. We present a method[1] for analysing local climatic timeseries data to assess which quantiles of the local climatic distribution show the greatest and most robust trends. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily temperature from specific locations across Europe over the last 60 years. Our method extracts the changing cumulative distribution function over time and uses a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of the sensitivity of different quantiles of the distributions to changing climate. Geographical location and temperature are treated as independent variables, we thus obtain as outputs how the trend or sensitivity varies with temperature (or occurrence likelihood), and with geographical location. These sensitivities are found to be geographically varying across Europe; as one would expect given the different influences on local climate between, say, Western Scotland and central Italy. We find as an output many regionally consistent patterns of response of potential value in adaptation planning. We discuss methods to quantify the robustness of these observed sensitivities and their statistical likelihood. This also quantifies the level of detail needed from climate models if they are to be used as tools to assess climate change impact. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, in press [2] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119, doi:10.1029/2008JD10201
The Effects of Climate Model Similarity on Local, Risk-Based Adaptation Planning

NASA Astrophysics Data System (ADS)

Steinschneider, S.; Brown, C. M.

2014-12-01

The climate science community has recently proposed techniques to develop probabilistic projections of climate change from ensemble climate model output. These methods provide a means to incorporate the formal concept of risk, i.e., the product of impact and probability, into long-term planning assessments for local systems under climate change. However, approaches for pdf development often assume that different climate models provide independent information for the estimation of probabilities, despite model similarities that stem from a common genealogy. Here we utilize an ensemble of projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to develop probabilistic climate information, with and without an accounting of inter-model correlations, and use it to estimate climate-related risks to a local water utility in Colorado, U.S. We show that the tail risk of extreme climate changes in both mean precipitation and temperature is underestimated if model correlations are ignored. When coupled with impact models of the hydrology and infrastructure of the water utility, the underestimation of extreme climate changes substantially alters the quantification of risk for water supply shortages by mid-century. We argue that progress in climate change adaptation for local systems requires the recognition that there is less information in multi-model climate ensembles than previously thought. Importantly, adaptation decisions cannot be limited to the spread in one generation of climate models.
Considering Students' Out-of-School Lives and Values in Designing Learning Environments for Climate Change

NASA Astrophysics Data System (ADS)

Walsh, E.; Tsurusaki, B.

2012-12-01

What are the implications of social controversy for the teaching and learning of climate change science? How do the political dimensions of this controversy affect learners' attitudes towards and reasoning about climate change and climate science? Case studies from a pilot enactment of an ecological impacts of climate change curriculum explore these questions by describing how five high school students' understandings of climate change science developed at the intersection of political and scientific values, attitudes, and ways of knowing. Case studies combine qualitative, ethnographic methods including interviews and classroom video observations with quantitative pre/post-assessments of student conceptual understandings and weekly surveys of student engagement. Data indicate that students had initial perceptions of climate change informed by the media and their families—both supporting and rejecting the scientific consensus—that influenced how they engaged with the scientific evidence. While students who were initially antagonistic to anthropogenic climate change did develop conceptual understandings of the scientific evidence for human-influences on climate change, this work was challenging and at times frustrating for them. These case studies demonstrate the wide range of initial attitudes and understandings that students bring to the study of climate change. They also demonstrate that it is possible to make significant shifts in students' understandings of climate change science, even in students who were initially resistant to the idea of anthropogenic climate change. Finally, multiple case studies discuss ways that the learning that occurred in the classroom crossed out of the classroom into the students' homes and family talk. This work highlights how learners' pathways are shaped not only by their developing understanding of the scientific evidence but also by the political and social influences that learners navigate across the contexts of their lives. It underscores the need to understand and support students as they interact with climate change across the contexts of their lives.
Review of Climate Change and Health in Ethiopia: Status and Gap Analysis

PubMed Central

Simane, Belay; Beyene, Hunachew; Deressa, Wakgari; Kumie, Abera; Berhane, Kiros; Samet, Jonathan

2017-01-01

Background This review assessed Ethiopia’s existing situation on issues related to the environment, climate change and health, and identifies gaps and needs that can be addressed through research, training, and capacity building. Methods The research was conducted through a comprehensive review of available secondary data and interviewing key informants in various national organizations involved in climate change adaptation and mitigation activities. Results Climate change-related health problems, such as mortality and morbidity due to floods and heat waves, vector-borne diseases, water-borne diseases, meningitis, and air pollution-related respiratory diseases are increasing in Ethiopia. Sensitive systems such as agriculture, health, and water have been affected, and the effects of climate change will continue to magnify without the right adaptation and mitigation measures. Currently, research on climate change and health is not adequately developed in Ethiopia. Research and other activities appear to be fragmented and uncoordinated. As a result, very few spatially detailed and methodologically consistent studies have been made to assess the impact of climate in the country. There has often been a lack of sufficient collaboration among organizations on the planning and execution of climate change and health activities, and the lack of trained professionals who can perform climate change and health-related research activities at various levels. Conclusion Firstly, there is a lack of organized structure in the various organizations. Secondly, there is inadequate level of inter-sectoral collaboration and poor coordination and communication among different stakeholders. Thirdly, there are no reliable policy guidelines and programs among organizations, agencies and offices that target climate change and health. Fourth, the existing policies fail to consider the gender and community-related dimensions of climate change. Fifth, the monitoring and evaluation efforts exerted on climate change and health activities are not strong enough to address the climate change and health issues in the country. PMID:28867919
The species velocity of trees in Alaska

NASA Astrophysics Data System (ADS)

Morrison, B. D.; Napier, J.; de Lafontaine, G.; Heath, K.; Li, B.; Hu, F.; Greenberg, J. A.

2017-12-01

Anthropogenic climate change has motivated interest in the paleo record to enhance our knowledge about past vegetation responses to climate change and help understand potential responses in the future. Additionally, polar regions currently experience the most rapid rates of climate change globally, prompting concern over changes in the ecological composition of high latitude ecosystems. Recent analyses have attempted to construct methods to estimate a species' ability to track climate change by computing climate velocity; a measure of the rate of climate displacement across a landscape which may indicate the speed an organism must migrate to keep pace with climate change. However, a challenge to using climate velocity in understanding range shifts is a lack of species-specificity in the velocity calculations: climate velocity does not actually use any species data in its analysis. To solve the shortcomings of climate velocity in estimating species displacement rates, we computed the "species velocity" of white spruce, green and grey alder populations across the state of Alaska from the Last Glacial Maximum (LGM) to today. Species velocity represents the rate and direction a species is required to migrate to keep pace with a changing climate following the LGM. We used a species distribution model to determine past and present white spruce and alder distributions using statistically downscaled climate data at 60m. Species velocity was then derived from the change in species distribution per year by the change in distribution over Alaska (km/yr). High velocities indicate locations where the species environmental envelope is changing drastically and must disperse rapidly to survive climate change. As a result, high velocity regions are more vulnerable to distribution shifts and higher risk of local extinction. Conversely, low species velocities indicate locations where the local climate envelope is shifting relatively slowly, reducing the stress to disperse quickly with minimal loss of optimal habitat. Our results suggest that these species do not exclusively redistribute to higher latitudes and elevations in a warming climate, suggesting that 1) microtopography plays a significant role in the distribution of a species and 2) many species may not be tracking temperature change, but other climate restrictions.
The Promise and Limitations of Using Analogies to Improve Decision-Relevant Understanding of Climate Change

PubMed Central

Stern, Paul C.; Maki, Alexander

2017-01-01

To make informed choices about how to address climate change, members of the public must develop ways to consider established facts of climate science and the uncertainties about its future trajectories, in addition to the risks attendant to various responses, including non-response, to climate change. One method suggested for educating the public about these issues is the use of simple mental models, or analogies comparing climate change to familiar domains such as medical decision making, disaster preparedness, or courtroom trials. Two studies were conducted using online participants in the U.S.A. to test the use of analogies to highlight seven key decision-relevant elements of climate change, including uncertainties about when and where serious damage may occur, its unprecedented and progressive nature, and tradeoffs in limiting climate change. An internal meta-analysis was then conducted to estimate overall effect sizes across the two studies. Analogies were not found to inform knowledge about climate literacy facts. However, results suggested that people found the medical analogy helpful and that it led people—especially political conservatives—to better recognize several decision-relevant attributes of climate change. These effects were weak, perhaps reflecting a well-documented and overwhelming effect of political ideology on climate change communication and education efforts in the U.S.A. The potential of analogies and similar education tools to improve understanding and communication in a polarized political environment are discussed. PMID:28135337
An Investigation of Secondary Students' Mental Models of Climate Change and the Greenhouse Effect

NASA Astrophysics Data System (ADS)

Varela, Begoña; Sesto, Vanessa; García-Rodeja, Isabel

2018-03-01

There are several studies dealing with students' conceptions on climate change, but most of them refer to understanding before instruction. In contrast, this study investigates students' conceptions and describes the levels of sophistication of their mental models on climate change and the greenhouse effect. The participants were 40 secondary students (grade 7) in Spain. As a method of data collection, a questionnaire was designed with open-ended questions focusing on the mechanism, causes, and actions that could be useful in reducing climate change. Students completed the same questionnaire before and after instruction. The students' conceptions and mental models were identified by an inductive and iterative analysis of the participants' explanations. With regard to the students' conceptions, the results show that they usually link climate change to an increase in temperature, and they tend to mention, even after instruction, generic actions to mitigate climate change, such as not polluting. With regard to the students' mental models, the results show an evolution of models with little consistency and coherence, such as the models on level 1, towards higher levels of sophistication. The paper concludes with educational implications proposed for solving learning difficulties regarding the greenhouse effect and climate change.
Health Care Facilities Resilient to Climate Change Impacts

PubMed Central

Paterson, Jaclyn; Berry, Peter; Ebi, Kristie; Varangu, Linda

2014-01-01

Climate change will increase the frequency and magnitude of extreme weather events and create risks that will impact health care facilities. Health care facilities will need to assess climate change risks and adopt adaptive management strategies to be resilient, but guidance tools are lacking. In this study, a toolkit was developed for health care facility officials to assess the resiliency of their facility to climate change impacts. A mixed methods approach was used to develop climate change resiliency indicators to inform the development of the toolkit. The toolkit consists of a checklist for officials who work in areas of emergency management, facilities management and health care services and supply chain management, a facilitator’s guide for administering the checklist, and a resource guidebook to inform adaptation. Six health care facilities representing three provinces in Canada piloted the checklist. Senior level officials with expertise in the aforementioned areas were invited to review the checklist, provide feedback during qualitative interviews and review the final toolkit at a stakeholder workshop. The toolkit helps health care facility officials identify gaps in climate change preparedness, direct allocation of adaptation resources and inform strategic planning to increase resiliency to climate change. PMID:25522050
Climate change and consequences in the Arctic: perception of climate change by the Nenets people of Vaigach Island

PubMed Central

Davydov, Alexander N.; Mikhailova, Galina V.

2011-01-01

Background Arctic climate change is already having a significant impact on the environment, economic activity, and public health. For the northern peoples, traditions and cultural identity are closely related to the natural environment so any change will have consequences for society in several ways. Methods A questionnaire was given to the population on the Vaigach island, the Nenets who rely to a large degree on hunting, fishing and reindeer herding for survival. Semi-structured interviews were also conducted about perception of climate change. Results Climate change is observed and has already had an impact on daily life according to more than 50% of the respondents. The winter season is now colder and longer and the summer season colder and shorter. A decrease in standard of living was noticeable but few were planning to leave. Conclusion Climate change has been noticed in the region and it has a negative impact on the standard of living for the Nenets. However, as of yet they do not want to leave as cultural identity is important for their overall well-being. PMID:22091216
Adapting to Uncertainty: Comparing Methodological Approaches to Climate Adaptation and Mitigation Policy

NASA Astrophysics Data System (ADS)

Huda, J.; Kauneckis, D. L.

2013-12-01

Climate change adaptation represents a number of unique policy-making challenges. Foremost among these is dealing with the range of future climate impacts to a wide scope of inter-related natural systems, their interaction with social and economic systems, and uncertainty resulting from the variety of downscaled climate model scenarios and climate science projections. These cascades of uncertainty have led to a number of new approaches as well as a reexamination of traditional methods for evaluating risk and uncertainty in policy-making. Policy makers are required to make decisions and formulate policy irrespective of the level of uncertainty involved and while a debate continues regarding the level of scientific certainty required in order to make a decision, incremental change in the climate policy continues at multiple governance levels. This project conducts a comparative analysis of the range of methodological approaches that are evolving to address uncertainty in climate change policy. It defines 'methodologies' to include a variety of quantitative and qualitative approaches involving both top-down and bottom-up policy processes that attempt to enable policymakers to synthesize climate information into the policy process. The analysis examines methodological approaches to decision-making in climate policy based on criteria such as sources of policy choice information, sectors to which the methodology has been applied, sources from which climate projections were derived, quantitative and qualitative methods used to deal with uncertainty, and the benefits and limitations of each. A typology is developed to better categorize the variety of approaches and methods, examine the scope of policy activities they are best suited for, and highlight areas for future research and development.
Projecting Climate Change Impacts on Wildfire Probabilities

NASA Astrophysics Data System (ADS)

Westerling, A. L.; Bryant, B. P.; Preisler, H.

2008-12-01

We present preliminary results of the 2008 Climate Change Impact Assessment for wildfire in California, part of the second biennial science report to the California Climate Action Team organized via the California Climate Change Center by the California Energy Commission's Public Interest Energy Research Program pursuant to Executive Order S-03-05 of Governor Schwarzenegger. In order to support decision making by the State pertaining to mitigation of and adaptation to climate change and its impacts, we model wildfire occurrence monthly from 1950 to 2100 under a range of climate scenarios from the Intergovernmental Panel on Climate Change. We use six climate change models (GFDL CM2.1, NCAR PCM1, CNRM CM3, MPI ECHAM5, MIROC3.2 med, NCAR CCSM3) under two emissions scenarios--A2 (C02 850ppm max atmospheric concentration) and B1(CO2 550ppm max concentration). Climate model output has been downscaled to a 1/8 degree (~12 km) grid using two alternative methods: a Bias Correction and Spatial Donwscaling (BCSD) and a Constructed Analogues (CA) downscaling. Hydrologic variables have been simulated from temperature, precipitation, wind and radiation forcing data using the Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model. We model wildfire as a function of temperature, moisture deficit, and land surface characteristics using nonlinear logistic regression techniques. Previous work on wildfire climatology and seasonal forecasting has demonstrated that these variables account for much of the inter-annual and seasonal variation in wildfire. The results of this study are monthly gridded probabilities of wildfire occurrence by fire size class, and estimates of the number of structures potentially affected by fires. In this presentation we will explore the range of modeled outcomes for wildfire in California, considering the effects of emissions scenarios, climate model sensitivities, downscaling methods, hydrologic simulations, statistical model specifications for california wildfire, and their intersection with a range of development scenarios for California.
Predicting the relatiave vulnerability of near-coastal species to climate change using a rule-based ecoinformatics approach

EPA Science Inventory

Background/Questions/Methods Near-coastal species are threatened by multiple climate change drivers, including temperature increases, ocean acidification, and sea level rise. To identify vulnerable habitats, geographic regions, and species, we developed a sequential, rule-based...
Climate Change Education on Public Health Consequences and Impacts to the Human System - An Interdisciplinary Approach to Promoting Climate Literacy

NASA Astrophysics Data System (ADS)

Matiella Novak, M.; Paxton, L. J.

2012-12-01

In this talk we will discuss our approach to translating an abstract, difficult to internalize idea ("climate change") into knowledge that speaks to people directly in terms of their own lives. Recent research suggests that communicating climate change in the context of public health impacts, and even national security risks, is a more effective method of reaching communities that are currently disengaged or nonresponsive to climate change science than the approaches currently being used. Understanding that these new perspectives might reach a broader audience, the Global Assimilation of Information for Action (GAIA) project has proposed implementing a suite of education activities that focus on the public health consequences that will arise and/or becoming exacerbated by climate change. Reaching the disparate communities that must be brought together to create a workable approach is challenging. GAIA has developed a novel framework for sharing information and developing communities of interest that cross boundaries in what is otherwise a highly disciplinary approach to climate change studies. Members of the GAIA community include climate change, environmental and public health experts, as well as relevant stakeholders, policy makers and decision makers. By leveraging the existing expertise within the GAIA community, an opportunity exists to present climate change education (CCE) in a way that emphasizes how climate change will affect public health, and utilizes an approach that has been shown to engage a broader and more diverse audience. Focusing CCE on public health effects is a new and potentially transformative method since it makes the results more tangible and less "random". When CCE is focused on what will happen to the Earth's climate and associated meteorological hazards one might be tempted to view this as something that can be coped with thus enabling the individualist entrepreneur point of view. Weather disasters always seem to happen to someone else - someone not like you. On the other hand, public health impacts are felt by millions and lead to very high costs and those impacts are something with which most people have direct experiences. We will discuss, for example, how climate change can be framed as a cost/benefit problem by looking at the long term costs of increase in disease and illness such as the startling trends in childhood asthma. Changes in water availability, and water and air quality, will result from a warming climate, with measureable consequences for public health: disease spread, food and water security, respiratory health, etc. By integrating this information with education efforts, society, educators and decision makers will have a better understanding of how climate change affects the human system, and what decisions can be made at the individual and community levels to mitigate and adapt to climate change. We will show how this can be achieved.
Limits to health adaptation in a changing climate

NASA Astrophysics Data System (ADS)

Ebi, K. L.

2015-12-01

Introduction: Because the health risks of climate variability and change are not new, it has been assumed that health systems have the capacity, experience, and tools to effectively adapt to changing burdens of climate-sensitive health outcomes with additional climate change. However, as illustrated in the Ebola crisis, health systems in many low-income countries have insufficient capacity to manage current health burdens. These countries also are those most vulnerable to climate change, including changes in food and water safety and security, increases in extreme weather and climate events, and increases in the geographic range, incidence, and seasonality of a variety of infectious diseases. The extent to which they might be able to keep pace with projected risks depends on assumptions of the sustainability of development pathways. At the same time, the magnitude and pattern of climate change will depend on greenhouse gas emission pathways. Methods: Review of the success of health adaptation projects and expert judgment assessment of the degree to which adaptation efforts will be able to keep pace with projected changes in climate variability and change. Results: Health adaptation can reduce the current and projected burdens of climate-sensitive health outcomes over the short term in many countries, but the extent to which it could do so past mid-century will depend on emission and development pathways. Under high emission scenarios, climate change will be rapid and extensive, leading to fundamental shifts in the burden of climate-sensitive health outcomes that will challenging for many countries to manage. Sustainable development pathways could delay but not eliminate associated health burdens. Conclusions: To prepare for and cope with the Anthropocene, health systems need additional adaptation policies and measures to develop more robust health systems, and need to advocate for rapid and significant reductions in greenhouse gas emissions.
A comparative review of multi-risk modelling methodologies for climate change adaptation in mountain regions

NASA Astrophysics Data System (ADS)

Terzi, Stefano; Torresan, Silvia; Schneiderbauer, Stefan

2017-04-01

Keywords: Climate change, mountain regions, multi-risk assessment, climate change adaptation. Climate change has already led to a wide range of impacts on the environment, the economy and society. Adaptation actions are needed to cope with the impacts that have already occurred (e.g. storms, glaciers melting, floods, droughts) and to prepare for future scenarios of climate change. Mountain environment is particularly vulnerable to the climate changes due to its exposure to recent climate warming (e.g. water regime changes, thawing of permafrost) and due to the high degree of specialization of both natural and human systems (e.g. alpine species, valley population density, tourism-based economy). As a consequence, the mountain local governments are encouraged to undertake territorial governance policies to climate change, considering multi-risks and opportunities for the mountain economy and identifying the best portfolio of adaptation strategies. This study aims to provide a literature review of available qualitative and quantitative tools, methodological guidelines and best practices to conduct multi-risk assessments in the mountain environment within the context of climate change. We analyzed multi-risk modelling and assessment methods applied in alpine regions (e.g. event trees, Bayesian Networks, Agent Based Models) in order to identify key concepts (exposure, resilience, vulnerability, risk, adaptive capacity), climatic drivers, cause-effect relationships and socio-ecological systems to be integrated in a comprehensive framework. The main outcomes of the review, including a comparison of existing techniques based on different criteria (e.g. scale of analysis, targeted questions, level of complexity) and a snapshot of the developed multi-risk framework for climate change adaptation will be here presented and discussed.
Developing Climate Change Literacy With the Humanities: A Narrative Approach

NASA Astrophysics Data System (ADS)

Siperstein, S.

2015-12-01

Teaching the science and policy of climate change is necessary but insufficient for helping students to develop a robust climate literacy. Climate change educators must also teach students how to evaluate historical trends, to unpack the assumptions in shared cultural narratives, to grapple with ethical dilemmas, and more generally to traverse the turbulence of feeling that is a hallmark of living in a time of global climate chaos. In short, climate literacy must include the skills and strategies of the humanities, and specifically literary and cultural studies. After providing an overview of how literary and cultural studies scholars from around the world are developing innovative pedagogical methods for addressing climate change (drawing on the presenter's experience editing the forthcoming volume Teaching Climate Change in the Humanities), the presentation will then report on a specific Literary Genres course taught at the University of Oregon. The course, offered to undergraduate non-majors who entered the class with little or no knowledge of climate change, constituted a case study of action research into the transdisciplinary teaching of climate change. The presentation will thus draw on quantitative course assessments, student coursework, and the instructor's own experiences in arguing that three key narratives underpin the work we do as multidisciplinary climate change educators: narratives of observation, narratives of speculation, and narratives of conversion. That is, we guide students through the processes of witnessing climate change, imagining more just and sustainable futures, and by so doing, transforming themselves and their communities. In the particular Literary Genres course under consideration, students used the tools of literary and cultural studies first to analyze existing versions of these narratives and then to compose their own versions of these narratives based on their local communities and ecologies. In the context of multidisciplinary climate change education, one of the most important roles of the humanities is to empower students by giving them the critical and creative tools to tell their own climate stories.
Determining the contributions of urbanisation and climate change to NPP variations over the last decade in the Yangtze River Delta, China.

PubMed

Wu, Shaohua; Zhou, Shenglu; Chen, Dongxiang; Wei, Zongqiang; Dai, Liang; Li, Xingong

2014-02-15

Terrestrial net primary production (NPP) is an important measure of global change, and identifying the relative contributions of urbanisation and climate change to NPP is important for understanding the impact of human and natural influences on terrestrial systems and the carbon cycle. The objective of this study was to reveal how urbanisation and climate drive changes in NPP. Satellite-based estimates of NPP collected over a 12-year period (1999-2010) were analysed to identify NPP variations in the Yangtze River Delta. Temporal and spatial analysis methods were used to identify the relationships among NPP, nighttime light urbanisation index values, and climatic factors from pixel to regional scales. The NPP of the entire Yangtze River Delta decreased slightly at a rate of -0.5 g C m(-2)a(-1) from 1999 to 2010, but this change was not significant. However, in the urban region, NPP decreased significantly (p<0.05) at a rate of -4.7 g C m(-2)a(-1) due to urbanisation processes. A spatially explicit method was proposed to partition the relative contributions of urbanisation and climate change to NPP variation. The results revealed that the urbanisation factor is the main driving force for NPP change in high-speed urbanisation areas, and the factor accounted for 47% of the variations. However, in the forest and farm regions, the NPP variation was mainly controlled by climate change and residual factors. Copyright © 2013 Elsevier B.V. All rights reserved.
Are human activities induced runoff change overestimated?

NASA Astrophysics Data System (ADS)

Zhang, Danwu; Cong, Zhentao

2017-04-01

In the context of climate change, not only does the amount of annual precipitation and potential evapotranspiration alter, but also do the seasonal characteristics of climate, such as intra-annual distribution of water and energy. Yet, the runoff change induced by the change in seasonality of climatic forces is seldom evaluated, which is usually thought as the results of human activity, leading to contaminative runoff change attribution results. The past 50-year climatology seasonality was investigated by analyzing the daily meteorological records of 743 national weather stations across the China. Obvious spatial pattern of climatology seasonality emerged in China. The trend analysis indicated that there is decrease in precipitation seasonality, leaving other seasonal characteristics, such as peak time of climate forcing unchanged. With the aid of stochastic soil moisture model, water-energy balance models which take the effects of climate seasonality into consideration are developed. Efforts are made to achieve a better understanding of mean annual runoff change due to the climate change. As a representative of hydrologic responses, the contributions of variations in climate, especially in precipitation seasonality, and land use to runoff change of 282 catchments in China were evaluated. The results showed that the decline of precipitation seasonality has a significant influence on runoff change in the Yellow River, Haihe River and Liaohe River. Meanwhile, it also indicated that the contribution of land use change to runoff change is overestimated by the common runoff change attribution methods.
Multi-site precipitation downscaling using a stochastic weather generator

NASA Astrophysics Data System (ADS)

Chen, Jie; Chen, Hua; Guo, Shenglian

2018-03-01

Statistical downscaling is an efficient way to solve the spatiotemporal mismatch between climate model outputs and the data requirements of hydrological models. However, the most commonly-used downscaling method only produces climate change scenarios for a specific site or watershed average, which is unable to drive distributed hydrological models to study the spatial variability of climate change impacts. By coupling a single-site downscaling method and a multi-site weather generator, this study proposes a multi-site downscaling approach for hydrological climate change impact studies. Multi-site downscaling is done in two stages. The first stage involves spatially downscaling climate model-simulated monthly precipitation from grid scale to a specific site using a quantile mapping method, and the second stage involves the temporal disaggregating of monthly precipitation to daily values by adjusting the parameters of a multi-site weather generator. The inter-station correlation is specifically considered using a distribution-free approach along with an iterative algorithm. The performance of the downscaling approach is illustrated using a 10-station watershed as an example. The precipitation time series derived from the National Centers for Environment Prediction (NCEP) reanalysis dataset is used as the climate model simulation. The precipitation time series of each station is divided into 30 odd years for calibration and 29 even years for validation. Several metrics, including the frequencies of wet and dry spells and statistics of the daily, monthly and annual precipitation are used as criteria to evaluate the multi-site downscaling approach. The results show that the frequencies of wet and dry spells are well reproduced for all stations. In addition, the multi-site downscaling approach performs well with respect to reproducing precipitation statistics, especially at monthly and annual timescales. The remaining biases mainly result from the non-stationarity of NCEP precipitation. Overall, the proposed approach is efficient for generating multi-site climate change scenarios that can be used to investigate the spatial variability of climate change impacts on hydrology.
Advantages and applicability of commonly used homogenisation methods for climate data

NASA Astrophysics Data System (ADS)

Ribeiro, Sara; Caineta, Júlio; Henriques, Roberto; Soares, Amílcar; Costa, Ana Cristina

2014-05-01

Homogenisation of climate data is a very relevant subject since these data are required as an input in a wide range of studies, such as atmospheric modelling, weather forecasting, climate change monitoring, or hydrological and environmental projects. Often, climate data series include non-natural irregularities which have to be detected and removed prior to their use, otherwise it would generate biased and erroneous results. Relocation of weather stations or changes in the measuring instruments are amongst the most relevant causes for these inhomogeneities. Depending on the climate variable, its temporal resolution and spatial continuity, homogenisation methods can be more or less effective. For example, due to its natural variability, precipitation is identified as a very challenging variable to be homogenised. During the last two decades, numerous methods have been proposed to homogenise climate data. In order to compare, evaluate and develop those methods, the European project COST Action ES0601, Advances in homogenisation methods of climate series: an integrated approach (HOME), was released in 2008. Existing homogenisation methods were improved based on the benchmark exercise issued by this project. A recent approach based on Direct Sequential Simulation (DSS), not yet evaluated by the benchmark exercise, is also presented as an innovative methodology for homogenising climate data series. DSS already proved to be a successful geostatistical method in environmental and hydrological studies, and it provides promising results for the homogenisation of climate data. Since DSS is a geostatistical stochastic approach, it accounts for the joint spatial and temporal dependence between observations, as well as the relative importance of stations both in terms of distance and correlation. This work presents a chronological review of the most commonly used homogenisation methods for climate data and available software packages. A short description and classification is provided for each method. Their advantages and applicability are discussed based on literature review and on the results of the HOME project. Acknowledgements: The authors gratefully acknowledge the financial support of "Fundação para a Ciência e Tecnologia" (FCT), Portugal, through the research project PTDC/GEO-MET/4026/2012 ("GSIMCLI - Geostatistical simulation with local distributions for the homogenization and interpolation of climate data").

Sustained Large-Scale Collective Climate Action Supported by Effective Climate Change Education Practice

NASA Astrophysics Data System (ADS)

Niepold, F., III; Crim, H.; Fiorile, G.; Eldadah, S.

2017-12-01

Since 2012, the Climate and Energy Literacy community have realized that as cities, nations and the international community seek solutions to global climate change over the coming decades, a more comprehensive, interdisciplinary approach to climate literacy—one that includes economic and social considerations—will play a vital role in knowledgeable planning, decision-making, and governance. City, county and state leaders are now leading the American response to a changing climate by incubating social innovation to prevail in the face of unprecedented change. Cities are beginning to realize the importance of critical investments to support the policies and strategies that will foster the climate literacy necessary for citizens to understand the urgency of climate actions and to succeed in a resilient post-carbon economy and develop the related workforce. Over decade of federal and non-profit Climate Change Education effective methods have been developed that can support municipality's significant educational capabilities for the purpose of strengthening and scaling city, state, business, and education actions designed to sustain and effectively address this significant social change. Looking to foster the effective and innovative strategies that will enable their communities several networks have collaborated to identify recommendations for effective education and communication practices when working with different types of audiences. U.S. National Science Foundation funded Climate Change Education Partnership (CCEP) Alliance, the National Wildlife Federation, NOAA Climate Program Office, Tri-Agency Climate Change Education Collaborative and the Climate Literacy and Energy Awareness Network (CLEAN) are working to develop a new web portal that will highlight "effective" practices that includes the acquisition and use of climate change knowledge to inform decision-making. The purpose of the web portal is to transfer effective practice to support communities to be empowered to address the challenges of a new climate reality and ensure that all people are capable of taking an active role in shaping a sustainable future.
Engaging communities and climate change futures with Multi-Scale, Iterative Scenario Building (MISB) in the western United States

Treesearch

Daniel Murphy; Carina Wyborn; Laurie Yung; Daniel R. Williams; Cory Cleveland; Lisa Eby; Solomon Dobrowski; Erin Towler

2016-01-01

Current projections of future climate change foretell potentially transformative ecological changes that threaten communities globally. Using two case studies from the United States Intermountain West, this article highlights the ways in which a better articulation between theory and methods in research design can generate proactive applied tools that enable...
Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models.

PubMed

Keith, David A; Akçakaya, H Resit; Thuiller, Wilfried; Midgley, Guy F; Pearson, Richard G; Phillips, Steven J; Regan, Helen M; Araújo, Miguel B; Rebelo, Tony G

2008-10-23

Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.
Climate change impacts on rainfall extremes and urban drainage: state-of-the-art review

NASA Astrophysics Data System (ADS)

Willems, Patrick; Olsson, Jonas; Arnbjerg-Nielsen, Karsten; Beecham, Simon; Pathirana, Assela; Bülow Gregersen, Ida; Madsen, Henrik; Nguyen, Van-Thanh-Van

2013-04-01

Under the umbrella of the IWA/IAHR Joint Committee on Urban Drainage, the International Working Group on Urban Rainfall (IGUR) has reviewed existing methodologies for the analysis of long-term historical and future trends in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic climate change. Current practises have several limitations and pitfalls, which are important to be considered by trend or climate change impact modellers and users of trend/impact results. The review considers the following aspects: Analysis of long-term historical trends due to anthropogenic climate change: influence of data limitation, instrumental or environmental changes, interannual variations and longer term climate oscillations on trend testing results. Analysis of long-term future trends due to anthropogenic climate change: by complementing empirical historical data with the results from physically-based climate models, dynamic downscaling to the urban scale by means of Limited Area Models (LAMs) including explicitly small-scale cloud processes; validation of RCM/GCM results for local conditions accounting for natural variability, limited length of the available time series, difference in spatial scales, and influence of climate oscillations; statistical downscaling methods combined with bias correction; uncertainties associated with the climate forcing scenarios, the climate models, the initial states and the statistical downscaling step; uncertainties in the impact models (e.g. runoff peak flows, flood or surcharge frequencies, and CSO frequencies and volumes), including the impacts of more extreme conditions than considered during impact model calibration and validation. Implications for urban drainage infrastructure design and management: upgrading of the urban drainage system as part of a program of routine and scheduled replacement and renewal of aging infrastructure; how to account for the uncertainties; flexible and sustainable solutions; adaptive approach that provides inherent flexibility and reversibility and avoids closing off options; importance of active learning. References: Willems, P., Olsson, J., Arnbjerg-Nielsen, K., Beecham, S., Pathirana, A., Bülow Gregersen, I., Madsen, H., Nguyen, V-T-V. (2012). Impacts of climate change on rainfall extremes and urban drainage. IWA Publishing, 252 p., Paperback Print ISBN 9781780401256; Ebook ISBN 9781780401263 Willems, P., Arnbjerg-Nielsen, K., Olsson, J., Nguyen, V.T.V. (2012), 'Climate change impact assessment on urban rainfall extremes and urban drainage: methods and shortcomings', Atmospheric Research, 103, 106-118
Merger of three modeling approaches to assess potential effects of climate change on trees in the eastern United States

Treesearch

Louis R. Iverson; Anantha M. Prasad; Stephen N. Matthews; Matthew P. Peters

2010-01-01

Climate change will likely cause impacts that are species specific and significant; modeling is critical to better understand potential changes in suitable habitat. We use empirical, abundance-based habitat models utilizing decision tree-based ensemble methods to explore potential changes of 134 tree species habitats in the eastern United States (http://www.nrs.fs.fed....
The Effectiveness of a Geospatial Technologies-Integrated Curriculum to Promote Climate Literacy

NASA Astrophysics Data System (ADS)

Anastasio, D. J.; Bodzin, A. M.; Peffer, T.; Sahagian, D. L.; Cirucci, L.

2011-12-01

This study examined the effectiveness of a geospatial technologies - integrated climate change curriculum (http://www.ei.lehigh.edu/eli/cc/) to promote climate literacy in an urban school district. Five 8th grade Earth and Space Science classes in an urban middle school (Bethlehem, Pennsylvania) consisting of three different ability level tracks participated in the study. Data gathering methods included pre/posttest assessments, daily classroom observations, daily teacher meetings, and examination of student produced artifacts. Data was gathered using a climate change literacy assessment instrument designed to measure students' climate change content knowledge. The items included distractors that address misunderstandings and knowledge deficits about climate change from the existing literature. Paired-sample t-test analyses were conducted to compare the pre- and post-test assessment results. The results of these analyses were used to compare overall gains as well as ability level track groups. Overall results regarding the use of the climate change curriculum showed significant improvement in urban middle school students' understanding of climate change concepts. Effect sizes were large (ES>0.8) and significant (p<0.001) for the entire assessment and for each ability level subgroup. Findings from classroom observations, assessments embedded in the curriculum, and the examination of all student artifacts revealed that the use of geospatial technologies enable middle school students to improve their knowledge of climate change and improve their spatial thinking and reasoning skills.
A method for modeling the effects of climate and land use changes on erosion and sustainability of soil in a Mediterranean watershed (Languedoc, France).

PubMed

Paroissien, Jean-Baptiste; Darboux, Frédéric; Couturier, Alain; Devillers, Benoît; Mouillot, Florent; Raclot, Damien; Le Bissonnais, Yves

2015-03-01

Global climate and land use changes could strongly affect soil erosion and the capability of soils to sustain agriculture and in turn impact regional or global food security. The objective of our study was to develop a method to assess soil sustainability to erosion under changes in land use and climate. The method was applied in a typical mixed Mediterranean landscape in a wine-growing watershed (75 km(2)) within the Languedoc region (La Peyne, France) for two periods: a first period with the current climate and land use and a second period with the climate and land use scenarios at the end of the twenty-first century. The Intergovernmental Panel on Climate Change A1B future rainfall scenarios from the Météo France General circulation model was coupled with four contrasting land use change scenarios that were designed using a spatially-explicit land use change model. Mean annual erosion rate was estimated with an expert-based soil erosion model. Soil life expectancy was assessed using soil depth. Soil erosion rate and soil life expectancy were combined into a sustainability index. The median simulated soil erosion rate for the current period was 3.5 t/ha/year and the soil life expectancy was 273 years, showing a low sustainability of soils. For the future period with the same land use distribution, the median simulated soil erosion rate was 4.2 t/ha/year and the soil life expectancy was 249 years. The results show that soil erosion rate and soil life expectancy are more sensitive to changes in land use than to changes in precipitation. Among the scenarios tested, institution of a mandatory grass cover in vineyards seems to be an efficient means of significantly improving soil sustainability, both in terms of decreased soil erosion rates and increased soil life expectancies. Copyright © 2014 Elsevier Ltd. All rights reserved.
Local adaptation and the evolution of species' ranges under climate change.

PubMed

Atkins, K E; Travis, J M J

2010-10-07

The potential impact of climate change on biodiversity is well documented. A well developed range of statistical methods currently exists that projects the possible future habitat of a species directly from the current climate and a species distribution. However, studies incorporating ecological and evolutionary processes remain limited. Here, we focus on the potential role that local adaptation to climate may play in driving the range dynamics of sessile organisms. Incorporating environmental adaptation into a stochastic simulation yields several new insights. Counter-intuitively, our simulation results suggest that species with broader ranges are not necessarily more robust to climate change. Instead, species with broader ranges can be more susceptible to extinction as locally adapted genotypes are often blocked from range shifting by the presence of cooler adapted genotypes that persist even when their optimum climate has left them behind. Interestingly, our results also suggest that it will not always be the cold-adapted phenotypes that drive polewards range expansion. Instead, range shifts may be driven by phenotypes conferring adaptation to conditions prevalent towards the centre of a species' equilibrium distribution. This may have important consequences for the conservation method termed predictive provenancing. These initial results highlight the potential importance of local adaptation in determining how species will respond to climate change and we argue that this is an area requiring urgent theoretical and empirical attention. 2010 Elsevier Ltd. All rights reserved.
EVALUATING SHORT-TERM CLIMATE VARIABILITY IN THE LATE HOLOCENE OF THE NORTHERN GREAT PLAINS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joseph H. Hartman

1999-09-01

This literature study investigated methods and areas to deduce climate change and climate patterns, looking for short-term cycle phenomena and the means to interpret them. Many groups are actively engaged in intensive climate-related research. Ongoing research might be (overly) simplified into three categories: (1) historic data on weather that can be used for trend analysis and modeling; (2) detailed geological, biological (subfossil), and analytical (geochemical, radiocarbon, etc.) studies covering the last 10,000 years (about since last glaciation); and (3) geological, paleontological, and analytical (geochemical, radiometric, etc.) studies over millions of years. Of importance is our ultimate ability to join thesemore » various lines of inquiry into an effective means of interpretation. At this point, the process of integration is fraught with methodological troubles and misconceptions about what each group can contribute. This project has met its goals to the extent that it provided an opportunity to study resource materials and consider options for future effort toward the goal of understanding the natural climate variation that has shaped our current civilization. A further outcome of this project is a proposed methodology based on ''climate sections'' that provides spatial and temporal correlation within a region. The method would integrate cultural and climate data to establish the climate history of a region with increasing accuracy with progressive study and scientific advancement (e. g., better integration of regional and global models). The goal of this project is to better understand natural climatic variations in the recent past (last 5000 years). The information generated by this work is intended to provide better context within which to examine global climate change. The ongoing project will help to establish a basis upon which to interpret late Holocene short-term climate variability as evidenced in various studies in the northern Great Plains, northern hemisphere, and elsewhere. Finally these data can be integrated into a history of climate change and predictive climate models. This is not a small undertaking. The goals of researchers and the methods used vary considerably. The primary task of this project was literature research to (1) evaluate existing methodologies used in geologic climate change studies and evidence for short-term cycles produced by these methodologies and (2) evaluate late Holocene climate patterns and their interpretations.« less
ECOSYSTEM IMPACTS OF GEOENGINEERING: A Review for Developing a Science Plan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Russell, Lynn M; Jackson, Robert B; Norby, Richard J

2012-01-01

Geoengineering methods are intended to reduce the magnitude of climate change, which is already having demonstrable effects on ecosystem structure and functioning. Two different types of activities have been proposed: solar radiation management (SRM), or sunlight reflection methods, which involves reflecting a small percentage of solar light back into space to offset the warming due to greenhouse gases, and carbon dioxide removal (CDR), which includes a range of engineered and biological processes to remove carbon dioxide (CO2) from the atmosphere. This report evaluates some of the possible impacts of CDR and SRM on the physical climate and their subsequent influencemore » on ecosystems, which include the risks and uncertainties associated with new kinds of purposeful perturbations to the Earth. Therefore, the question considered in this review is whether CDR and SRM methods would exacerbate or alleviate the deleterious impacts on ecosystems associated with climate changes that might occur in the foreseeable future.Geoengineering methods are intended to reduce the magnitude of climate change, which is already having demonstrable effects on ecosystem structure and functioning. Two different types of activities have been proposed: solar radiation management (SRM), or sunlight reflection methods, which involves reflecting a small percentage of solar light back into space to offset the warming due to greenhouse gases, and carbon dioxide removal (CDR), which includes a range of engineered and biological processes to remove carbon dioxide (CO2) from the atmosphere. This report evaluates some of the possible impacts of CDR and SRM on the physical climate and their subsequent influence on ecosystems, which include the risks and uncertainties associated with new kinds of purposeful perturbations to the Earth. Therefore, the question considered in this review is whether CDR and SRM methods would exacerbate or alleviate the deleterious impacts on ecosystems associated with climate changes that might occur in the foreseeable future.« less
The potential for behavioral thermoregulation to buffer "cold-blooded" animals against climate warming.

PubMed

Kearney, Michael; Shine, Richard; Porter, Warren P

2009-03-10

Increasing concern about the impacts of global warming on biodiversity has stimulated extensive discussion, but methods to translate broad-scale shifts in climate into direct impacts on living animals remain simplistic. A key missing element from models of climatic change impacts on animals is the buffering influence of behavioral thermoregulation. Here, we show how behavioral and mass/energy balance models can be combined with spatial data on climate, topography, and vegetation to predict impacts of increased air temperature on thermoregulating ectotherms such as reptiles and insects (a large portion of global biodiversity). We show that for most "cold-blooded" terrestrial animals, the primary thermal challenge is not to attain high body temperatures (although this is important in temperate environments) but to stay cool (particularly in tropical and desert areas, where ectotherm biodiversity is greatest). The impact of climate warming on thermoregulating ectotherms will depend critically on how changes in vegetation cover alter the availability of shade as well as the animals' capacities to alter their seasonal timing of activity and reproduction. Warmer environments also may increase maintenance energy costs while simultaneously constraining activity time, putting pressure on mass and energy budgets. Energy- and mass-balance models provide a general method to integrate the complexity of these direct interactions between organisms and climate into spatial predictions of the impact of climate change on biodiversity. This methodology allows quantitative organism- and habitat-specific assessments of climate change impacts.
The potential for behavioral thermoregulation to buffer “cold-blooded” animals against climate warming

PubMed Central

Kearney, Michael; Shine, Richard; Porter, Warren P.

2009-01-01

Increasing concern about the impacts of global warming on biodiversity has stimulated extensive discussion, but methods to translate broad-scale shifts in climate into direct impacts on living animals remain simplistic. A key missing element from models of climatic change impacts on animals is the buffering influence of behavioral thermoregulation. Here, we show how behavioral and mass/energy balance models can be combined with spatial data on climate, topography, and vegetation to predict impacts of increased air temperature on thermoregulating ectotherms such as reptiles and insects (a large portion of global biodiversity). We show that for most “cold-blooded” terrestrial animals, the primary thermal challenge is not to attain high body temperatures (although this is important in temperate environments) but to stay cool (particularly in tropical and desert areas, where ectotherm biodiversity is greatest). The impact of climate warming on thermoregulating ectotherms will depend critically on how changes in vegetation cover alter the availability of shade as well as the animals' capacities to alter their seasonal timing of activity and reproduction. Warmer environments also may increase maintenance energy costs while simultaneously constraining activity time, putting pressure on mass and energy budgets. Energy- and mass-balance models provide a general method to integrate the complexity of these direct interactions between organisms and climate into spatial predictions of the impact of climate change on biodiversity. This methodology allows quantitative organism- and habitat-specific assessments of climate change impacts. PMID:19234117
Comprehensive methods for earlier detection and monitoring of forest decline

Treesearch

Jennifer Pontius; Richard Hallett

2014-01-01

Forested ecosystems are threatened by invasive pests, pathogens, and unusual climatic events brought about by climate change. Earlier detection of incipient forest health problems and a quantitatively rigorous assessment method is increasingly important. Here, we describe a method that is adaptable across tree species and stress agents and practical for use in the...
Quantification of increased flood risk due to global climate change for urban river management planning.

PubMed

Morita, M

2011-01-01

Global climate change is expected to affect future rainfall patterns. These changes should be taken into account when assessing future flooding risks. This study presents a method for quantifying the increase in flood risk caused by global climate change for use in urban flood risk management. Flood risk in this context is defined as the product of flood damage potential and the probability of its occurrence. The study uses a geographic information system-based flood damage prediction model to calculate the flood damage caused by design storms with different return periods. Estimation of the monetary damages these storms produce and their return periods are precursors to flood risk calculations. The design storms are developed from modified intensity-duration-frequency relationships generated by simulations of global climate change scenarios (e.g. CGCM2A2). The risk assessment method is applied to the Kanda River basin in Tokyo, Japan. The assessment provides insights not only into the flood risk cost increase due to global warming, and the impact that increase may have on flood control infrastructure planning.
Climate change and human health: what are the research trends? A scoping review protocol.

PubMed

Herlihy, Niamh; Bar-Hen, Avner; Verner, Glenn; Fischer, Helen; Sauerborn, Rainer; Depoux, Anneliese; Flahault, Antoine; Schütte, Stefanie

2016-12-23

For 28 years, the Intergovernmental Panel on Climate Change (IPCC) has been assessing the potential risks associated with anthropogenic climate change. Although interest in climate change and health is growing, the implications arising from their interaction remain understudied. Generating a greater understanding of the health impacts of climate change could be key step in inciting some of the changes necessary to decelerate global warming. A long-term and broad overview of the existing scientific literature in the field of climate change and health is currently missing in order to ensure that all priority areas are being adequately addressed. In this paper we outline our methods to conduct a scoping review of the published peer-reviewed literature on climate change and health between 1990 and 2015. A detailed search strategy will be used to search the PubMed and Web of Science databases. Specific inclusion and exclusion criteria will be applied in order to capture the most relevant literature in the time frame chosen. Data will be extracted, categorised and coded to allow for statistical analysis of the results. No ethical approval was required for this study. A searchable database of climate change and health publications will be developed and a manuscript will be complied for publication and dissemination of the findings. We anticipate that this study will allow us to map the trends observed in publications over the 25-year time period in climate change and health research. It will also identify the research areas with the highest volume of publications as well as highlight the research trends in climate change and health. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Future respiratory hospital admissions from wildfire smoke under climate change in the Western US

NASA Astrophysics Data System (ADS)

Coco Liu, Jia; Mickley, Loretta J.; Sulprizio, Melissa P.; Yue, Xu; Peng, Roger D.; Dominici, Francesca; Bell, Michelle L.

2016-12-01

Background. Wildfires are anticipated to be more frequent and intense under climate change. As a result, wildfires may emit more air pollutants that can harm health in communities in the future. The health impacts of wildfire smoke under climate change are largely unknown. Methods. We linked projections of future levels of fine particulate matter (PM2.5) specifically from wildfire smoke under the A1B climate change scenario using the GEOS-Chem model for 2046-2051, present-day estimates of hospital admission impacts from wildfire smoke, and future population projections to estimate the change in respiratory hospital admissions for persons ≥65 years by county (n = 561) from wildfire PM2.5 under climate change in the Western US. Results. The increase in intense wildfire smoke days from climate change would result in an estimated 178 (95% confidence interval: 6.2, 361) additional respiratory hospital admissions in the Western US, accounting for estimated future increase in the elderly population. Climate change is estimated to impose an additional 4990 high-pollution smoke days. Central Colorado, Washington and southern California are estimated to experience the highest percentage increase in respiratory admissions from wildfire smoke under climate change. Conclusion. Although the increase in number of respiratory admissions from wildfire smoke seems modest, these results provide important scientific evidence of an often-ignored aspect of wildfire impact, and information on their anticipated spatial distribution. Wildfires can cause serious social burdens such as property damage and suppression cost, but can also raise health problems. The results provide information that can be incorporated into development of environmental and health policies in response to climate change. Climate change adaptation policies could incorporate scientific evidence on health risks from natural disasters such as wildfires.
Adapting to climate change

Treesearch

Constance I. Millar; Christopher W. Swanston; David L. Peterson

2014-01-01

Federal agencies have led the development of adaptation principles and tools in forest ecosystems over the past decade. Successful adaptation efforts generally require organizations to: (1) develop science-management partnerships, (2) provide education on climate change science, (3) provide a toolkit of methods and processes for vulnerability assessment and adaptation...
Increase in quantity and quality of suitable areas for invasive species as climate changes.

PubMed

Bertelsmeier, Cleo; Luque, Gloria M; Courchamp, Franck

2013-12-01

As climatically suitable range projections become increasingly used to assess distributions of species, we recommend systematic assessments of the quality of habitat in addition to the classical binary classification of habitat. We devised a method to assess occurrence probability, captured by a climatic suitability index, through which we could determine variations in the quality of potential habitat. This relative risk assessment circumvents the use of an arbitrary suitability threshold. We illustrated our method with 2 case studies on invasive ant species. We estimated invasion potential of the destroyer ant (Monomorium destructor) and the European fire ant (Myrmica rubra) on a global scale currently and by 2080 with climate change. We found that 21.1% of the world's landmass currently has a suitable climate for the destroyer ant and 16% has a suitable climate for European fire ant. Our climatic suitability index showed that both ant species would benefit from climate change, but in different ways. The size of the potential distribution increased by 35.8% for the destroyer ant. Meanwhile, the total area of potential distribution remained the same for the European fire ant (>0.05%), but the level of climatic suitability within this range increased greatly and led to an improvement in habitat quality (i.e., of invasive species' establishment likelihood). Either through quantity or quality of suitable areas, both invasive ant species are likely to increase the extent of their invasion in the future, following global climate change. Our results show that species may increase their range if either more areas become suitable or if the available areas present improved suitability. Studies in which an arbitrary suitability threshold was used may overlook changes in area quality within climatically suitable areas and as a result reach incorrect predictions. Incremento de la Cantidad y Calidad de Áreas Idóneas para Especies Invasoras a Medida que Cambia el Clima. © 2013 Society for Conservation Biology.
The $10 trillion value of better information about the transient climate response.

PubMed

Hope, Chris

2015-11-13

How much is better information about climate change worth? Here, I use PAGE09, a probabilistic integrated assessment model, to find the optimal paths of CO(2) emissions over time and to calculate the value of better information about one aspect of climate change, the transient climate response (TCR). Approximately halving the uncertainty range for TCR has a net present value of about $10.3 trillion (year 2005 US$) if accomplished in time for emissions to be adjusted in 2020, falling to $9.7 trillion if accomplished by 2030. Probabilistic integrated assessment modelling is the only method we have for making estimates like these for the value of better information about the science and impacts of climate change. © 2015 The Author(s).
Global Climate Change Pilot Course Project

NASA Astrophysics Data System (ADS)

Schuenemann, K. C.; Wagner, R.

2011-12-01

In fall 2011 a pilot course on "Global Climate Change" is being offered, which has been proposed to educate urban, diverse, undergraduate students about climate change at the introductory level. The course has been approved to fulfill two general college requirements, a natural sciences requirement that focuses on the scientific method, as well as a global diversity requirement. This course presents the science behind global climate change from an Earth systems and atmospheric science perspective. These concepts then provide the basis to explore the effect of global warming on regions throughout the world. Climate change has been taught as a sub-topic in other courses in the past solely using scientific concepts, with little success in altering the climate change misconceptions of the students. This pilot course will see if new, innovative projects described below can make more of an impact on the students' views of climate change. Results of the successes or failures of these projects will be reported, as well as results of a pre- and post-course questionnaire on climate change given to students taking the course. Students in the class will pair off and choose a global region or country that they will research, write papers on, and then represent in four class discussions spaced throughout the semester. The first report will include details on the current climate of their region and how the climate shapes that region's society and culture. The second report will discuss how that region is contributing to climate change and/or sequestering greenhouse gases. Thirdly, students will discuss observed and predicted changes in that region's climate and what impact it has had, and could have, on their society. Lastly, students will report on what role their region has played in mitigating climate change, any policies their region may have implemented, and how their region can or cannot adapt to future climate changes. They will also try to get a feel for the region's attitude towards climate change science, policy, and the stances taken by other regions on climate change. The professor will provide a model of integrative research using the U.S. as a focus, and on discussion days, prompt a sort of United Nations discussion on each of these topics with the intention of having the students look at climate change from a different point of view that contrasts their current U.S.-centric view, as well as realize the interdependence of regions particularly in regards to climate change.

Reconciling Scale Mismatch in Water Governance, Hydro-climatic Processes and Infrastructure Systems of Water Supply in Las Vegas

NASA Astrophysics Data System (ADS)

Garcia, M. E.; Alarcon, T.; Portney, K.; Islam, S.

2013-12-01

Water resource systems are a classic example of a common pool resource due to the high cost of exclusion and the subtractability of the resource; for common pool resources, the performance of governance systems primarily depends on how well matched the institutional arrangements and rules are to the biophysical conditions and social norms. Changes in water governance, hydro-climatic processes and infrastructure systems occur on disparate temporal and spatial scales. A key challenge is the gap between current climate change model resolution, and the spatial and temporal scale of urban water supply decisions. This gap will lead to inappropriate management policies if not mediated through a carefully crafted decision making process. Traditional decision support and planning methods (DSPM) such as classical decision analysis are not equipped to deal with a non-static climate. While emerging methods such as decision scaling, robust decision making and real options are designed to deal with a changing climate, governance systems have evolved under the assumption of a static climate and it is not clear if these methods are well suited to the existing governance regime. In our study, these questions are contextualized by examining an urban water utility that has made significant changes in policy to adapt to changing conditions: the Southern Nevada Water Authority (SNWA) which serves metropolitan Las Vegas. Like most desert cities, Las Vegas exists because of water; the artesian springs of the Las Vegas Valley once provided an ample water supply for Native Americans, ranchers and later a small railroad city. However, population growth has increased demands far beyond local supplies. The area now depends on the Colorado River for the majority of its water supply. Natural climate variability with periodic droughts has further challenged water providers; projected climate changes and further population growth will exacerbate these challenges. Las Vegas is selected as a case study due to the combined challenges of population growth and climate change, common in the arid west, and due its cooperative institutional response to these challenges, unprecedented in the arid west. To begin to disentangle this question we have analyzed the institutional arrangements and rules which govern water decision making in the Las Vegas Valley and evaluated the existing DSPM used by the SNWA and partner utilities. Presented here are the preliminary results from an ongoing project.
Sensitivity of Alpine Snow and Streamflow Regimes to Climate Changes

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Marks, D. G.; Bernhardt, M.

2014-12-01

Understanding the sensitivity of hydrological processes to climate change in alpine areas with snow dominated regimes is of paramount importance as alpine basins show both high runoff efficiency associated with the melt of the seasonal snowpack and great sensitivity of snow processes to temperature change. In this study, meteorological data measured in a selection of alpine headwaters basins including Reynolds Mountain East, Idaho, USA, Wolf Creek, Yukon in Canada, and Zugspitze Mountain, Germany with climates ranging from arctic to continental temperate were used to study the snow and streamflow sensitivity to climate change. All research sites have detailed multi-decadal meteorological and snow measurements. The Cold Regions Hydrological Modelling platform (CRHM) was used to create a model representing a typical alpine headwater basin discretized into hydrological response units with physically based representations of snow redistribution by wind, complex terrain snowmelt energetics and runoff processes in alpine tundra. The sensitivity of snow hydrology to climate change was investigated by changing air temperature and precipitation using weather generating methods based on the change factors obtained from different climate model projections for future and current periods. The basin mean and spatial variability of peak snow water equivalent, sublimation loss, duration of snow season, snowmelt rates, streamflow peak, and basin discharge were assessed under varying climate scenarios and the most sensitive hydrological mechanisms to the changes in the different alpine climates were detected. The results show that snow hydrology in colder alpine climates is more resilient to warming than that in warmer climates, but that compensatory factors to warming such as reduced blowing snow sublimation loss and reduced melt rate should also be assessed when considering climate change impacts on alpine hydrology.
Climate change impacts and adaptive strategies: lessons from the grapevine.

PubMed

Mosedale, Jonathan R; Abernethy, Kirsten E; Smart, Richard E; Wilson, Robert J; Maclean, Ilya M D

2016-11-01

The cultivation of grapevines for winemaking, known as viticulture, is widely cited as a climate-sensitive agricultural system that has been used as an indicator of both historic and contemporary climate change. Numerous studies have questioned the viability of major viticulture regions under future climate projections. We review the methods used to study the impacts of climate change on viticulture in the light of what is known about the effects of climate and weather on the yields and quality of vineyard harvests. Many potential impacts of climate change on viticulture, particularly those associated with a change in climate variability or seasonal weather patterns, are rarely captured. Key biophysical characteristics of viticulture are often unaccounted for, including the variability of grapevine phenology and the exploitation of microclimatic niches that permit successful cultivation under suboptimal macroclimatic conditions. We consider how these same biophysical characteristics permit a variety of strategies by which viticulture can adapt to changing climatic conditions. The ability to realize these strategies, however, is affected by uneven exposure to risks across the winemaking sector, and the evolving capacity for decision-making within and across organizational boundaries. The role grape provenance plays in shaping perceptions of wine value and quality illustrates how conflicts of interest influence decisions about adaptive strategies within the industry. We conclude by considering what lessons can be taken from viticulture for studies of climate change impacts and the capacity for adaptation in other agricultural and natural systems. © 2016 John Wiley & Sons Ltd.
Climate change adaptation in Tanjung Mas – Semarang: a comparison between male- and female-headed households

NASA Astrophysics Data System (ADS)

Handayani, W.; Ananda, M. R.; Esariti, L.; Anggraeni, M.

2018-03-01

Mainly due to its complexity, the effort to mainstream gender in addressing climate change issues has been far from the satisfying result. However, there is an urgent call to accommodate gender lens issues and to become more gender sensitive in an attempt to have an effective intervention in responding climate change impact. To enrich the reports on gender and climate change adaptation in city-based case, this paper aims to elaborate climate change adaptation in Tanjung Mas – Semarang city focusing on the gender perspective analysis in male- and female-headed households. The quantitative descriptive method is applied to carry out the analyses, including adaptive strategy and gender role analyses. The research result indicates there are not any significant differences in the climate change adaptation strategies applied in male- and female-headed households. This shows that women in the female-headed households, with their double burden, performed well in managing their roles. Therefore, in particular perspective, it may not be relevant to state that woman and female-headed households are likely to be more vulnerable compared with their counterparts.
Mapping human dimensions of climate change research in the Canadian Arctic.

PubMed

Ford, James D; Bolton, Kenyon; Shirley, Jamal; Pearce, Tristan; Tremblay, Martin; Westlake, Michael

2012-12-01

This study maps current understanding and research trends on the human dimensions of climate change (HDCC) in the eastern and central Canadian Arctic. Developing a systematic literature review methodology, 117 peer reviewed articles are identified and examined using quantitative and qualitative methods. The research highlights the rapid expansion of HDCC studies over the last decade. Early scholarship was dominated by work documenting Inuit observations of climate change, with research employing vulnerability concepts and terminology now common. Adaptation studies which seek to identify and evaluate opportunities to reduce vulnerability to climate change and take advantage of new opportunities remain in their infancy. Over the last 5 years there has been an increase social science-led research, with many studies employing key principles of community-based research. We currently have baseline understanding of climate change impacts, adaptation, and vulnerability in the region, but key gaps are evident. Future research needs to target significant geographic disparities in understanding, consider risks and opportunities posed by climate change outside of the subsistence hunting sector, complement case study research with regional analyses, and focus on identifying and characterizing sustainable and feasible adaptation interventions.
Biologically Based Methods for Pest Management in Agriculture under Changing Climates: Challenges and Future Directions.

PubMed

Chidawanyika, Frank; Mudavanhu, Pride; Nyamukondiwa, Casper

2012-11-09

The current changes in global climatic regimes present a significant societal challenge, affecting in all likelihood insect physiology, biochemistry, biogeography and population dynamics. With the increasing resistance of many insect pest species to chemical insecticides and an increasing organic food market, pest control strategies are slowly shifting towards more sustainable, ecologically sound and economically viable options. Biologically based pest management strategies present such opportunities through predation or parasitism of pests and plant direct or indirect defense mechanisms that can all be important components of sustainable integrated pest management programs. Inevitably, the efficacy of biological control systems is highly dependent on natural enemy-prey interactions, which will likely be modified by changing climates. Therefore, knowledge of how insect pests and their natural enemies respond to climate variation is of fundamental importance in understanding biological insect pest management under global climate change. Here, we discuss biological control, its challenges under climate change scenarios and how increased global temperatures will require adaptive management strategies to cope with changing status of insects and their natural enemies.
Studying Weather and Climate Extremes in a Non-stationary Framework

NASA Astrophysics Data System (ADS)

Wu, Z.

2010-12-01

The study of weather and climate extremes often uses the theory of extreme values. Such a detection method has a major problem: to obtain the probability distribution of extremes, one has to implicitly assume the Earth’s climate is stationary over a long period within which the climatology is defined. While such detection makes some sense in a purely statistical view of stationary processes, it can lead to misleading statistical properties of weather and climate extremes caused by long term climate variability and change, and may also cause enormous difficulty in attributing and predicting these extremes. To alleviate this problem, here we report a novel non-stationary framework for studying weather and climate extremes in a non-stationary framework. In this new framework, the weather and climate extremes will be defined as timescale-dependent quantities derived from the anomalies with respect to non-stationary climatologies of different timescales. With this non-stationary framework, the non-stationary and nonlinear nature of climate system will be taken into account; and the attribution and the prediction of weather and climate extremes can then be separated into 1) the change of the statistical properties of the weather and climate extremes themselves and 2) the background climate variability and change. The new non-stationary framework will use the ensemble empirical mode decomposition (EEMD) method, which is a recent major improvement of the Hilbert-Huang Transform for time-frequency analysis. Using this tool, we will adaptively decompose various weather and climate data from observation and climate models in terms of the components of the various natural timescales contained in the data. With such decompositions, the non-stationary statistical properties (both spatial and temporal) of weather and climate anomalies and of their corresponding climatologies will be analyzed and documented.
Conservation and adaptation to climate change.

PubMed

Brooke, Cassandra

2008-12-01

The need to adapt to climate change has become increasingly apparent, and many believe the practice of biodiversity conservation will need to alter to face this challenge. Conservation organizations are eager to determine how they should adapt their practices to climate change. This involves asking the fundamental question of what adaptation to climate change means. Most studies on climate change and conservation, if they consider adaptation at all, assume it is equivalent to the ability of species to adapt naturally to climate change as stated in Article 2 of the United Nations Framework Convention on Climate Change. Adaptation, however, can refer to an array of activities that range from natural adaptation, at one end of the spectrum, to sustainability science in coupled human and natural systems at the other. Most conservation organizations deal with complex systems in which adaptation to climate change involves making decisions on priorities for biodiversity conservation in the face of dynamic risks and involving the public in these decisions. Discursive methods such as analytic deliberation are useful for integrating scientific knowledge with public perceptions and values, particularly when large uncertainties and risks are involved. The use of scenarios in conservation planning is a useful way to build shared understanding at the science-policy interface. Similarly, boundary organizations-organizations or institutions that bridge different scales or mediate the relationship between science and policy-could prove useful for managing the transdisciplinary nature of adaptation to climate change, providing communication and brokerage services and helping to build adaptive capacity. The fact that some nongovernmental organizations (NGOs) are active across the areas of science, policy, and practice makes them well placed to fulfill this role in integrated assessments of biodiversity conservation and adaptation to climate change.
Vulnerability Assessments and Resilience Planning at Federal Sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moss, Richard H.; Blohm, Andrew; Delgado, Alison

2016-02-01

U.S. government agencies are now directed to assess the vulnerability of their operations and facilities to climate change and to develop adaptation plans to increase their resilience. Specific guidance on methods is still evolving based on the many different available frameworks. This technical paper synthesizes lessons and insights from a series of research case studies conducted by the investigators at facilities of the U.S. Departments of Energy and Defense. The paper provides a framework of steps for climate vulnerability assessments at Federal facilities and elaborates on three sets of methods required for assessments, regardless of the detailed framework used. Inmore » a concluding section, the paper suggests a roadmap to further develop methods to support agencies in preparing for climate change.« less
Compounding Impacts of Human-Induced Water Stress and Climate Change on Water Availability

DOE PAGES

Mehran, Ali; AghaKouchak, Amir; Nakhjiri, Navid; ...

2017-07-24

The terrestrial phase of the water cycle can be seriously impacted by water management and human water use behavior (e.g., reservoir operation, and irrigation withdrawals). Here we outline a method for assessing water availability in a changing climate, while explicitly considering anthropogenic water demand scenarios and water supply infrastructure designed to cope with climatic extremes. The framework brings a top-down and bottom-up approach to provide localized water assessment based on local water supply infrastructure and projected water demands. When our framework is applied to southeastern Australia we find that, for some combinations of climatic change and water demand, the regionmore » could experience water stress similar or worse than the epic Millennium Drought. We show considering only the influence of future climate on water supply, and neglecting future changes in water demand and water storage augmentation might lead to opposing perspectives on future water availability. While human water use can significantly exacerbate climate change impacts on water availability, if managed well, it allows societies to react and adapt to a changing climate. The methodology we present offers a unique avenue for linking climatic and hydrologic processes to water resource supply and demand management and other human interactions.« less
Compounding Impacts of Human-Induced Water Stress and Climate Change on Water Availability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mehran, Ali; AghaKouchak, Amir; Nakhjiri, Navid

The terrestrial phase of the water cycle can be seriously impacted by water management and human water use behavior (e.g., reservoir operation, and irrigation withdrawals). Here we outline a method for assessing water availability in a changing climate, while explicitly considering anthropogenic water demand scenarios and water supply infrastructure designed to cope with climatic extremes. The framework brings a top-down and bottom-up approach to provide localized water assessment based on local water supply infrastructure and projected water demands. When our framework is applied to southeastern Australia we find that, for some combinations of climatic change and water demand, the regionmore » could experience water stress similar or worse than the epic Millennium Drought. We show considering only the influence of future climate on water supply, and neglecting future changes in water demand and water storage augmentation might lead to opposing perspectives on future water availability. While human water use can significantly exacerbate climate change impacts on water availability, if managed well, it allows societies to react and adapt to a changing climate. The methodology we present offers a unique avenue for linking climatic and hydrologic processes to water resource supply and demand management and other human interactions.« less
Integrating bioclimate with population models to improve forecasts of species extinctions under climate change.

PubMed

Brook, Barry W; Akçakaya, H Resit; Keith, David A; Mace, Georgina M; Pearson, Richard G; Araújo, Miguel B

2009-12-23

Climate change is already affecting species worldwide, yet existing methods of risk assessment have not considered interactions between demography and climate and their simultaneous effect on habitat distribution and population viability. To address this issue, an international workshop was held at the University of Adelaide in Australia, 25-29 May 2009, bringing leading species distribution and population modellers together with plant ecologists. Building on two previous workshops in the UK and Spain, the participants aimed to develop methodological standards and case studies for integrating bioclimatic and metapopulation models, to provide more realistic forecasts of population change, habitat fragmentation and extinction risk under climate change. The discussions and case studies focused on several challenges, including spatial and temporal scale contingencies, choice of predictive climate, land use, soil type and topographic variables, procedures for ensemble forecasting of both global climate and bioclimate models and developing demographic structures that are realistic and species-specific and yet allow generalizations of traits that make species vulnerable to climate change. The goal is to provide general guidelines for assessing the Red-List status of large numbers of species potentially at risk, owing to the interactions of climate change with other threats such as habitat destruction, overexploitation and invasive species.
An experimental detrending approach to attributing change of pan evaporation in comparison with the traditional partial differential method

NASA Astrophysics Data System (ADS)

Wang, Tingting; Sun, Fubao; Xia, Jun; Liu, Wenbin; Sang, Yanfang

2017-04-01

In predicting how droughts and hydrological cycles would change in a warming climate, change of atmospheric evaporative demand measured by pan evaporation (Epan) is one crucial element to be understood. Over the last decade, the derived partial differential (PD) form of the PenPan equation is a prevailing attribution approach to attributing changes to Epan worldwide. However, the independency among climatic variables required by the PD approach cannot be met using long term observations. Here we designed a series of numerical experiments to attribute changes of Epan over China by detrending each climatic variable, i.e., an experimental detrending approach, to address the inter-correlation among climate variables, and made comparison with the traditional PD method. The results show that the detrending approach is superior not only to a complicate system with multi-variables and mixing algorithm like aerodynamic component (Ep,A) and Epan, but also to a simple case like radiative component (Ep,R), when compared with traditional PD method. The major reason for this is the strong and significant inter-correlation of input meteorological forcing. Very similar and fine attributing results have been achieved based on detrending approach and PD method after eliminating the inter-correlation of input through a randomize approach. The contribution of Rh and Ta in net radiation and thus Ep,R, which has been overlooked based on the PD method but successfully detected by detrending approach, provides some explanation to the comparing results. We adopted the control run from the detrending approach and applied it to made adjustment of PD method. Much improvement has been made and thus proven this adjustment an effective way in attributing changes to Epan. Hence, the detrending approach and the adjusted PD method are well recommended in attributing changes in hydrological models to better understand and predict water and energy cycle.
The future demographic niche of a declining grassland bird fails to shift poleward in response to climate change

USGS Publications Warehouse

McCauley, Lisa A.; Ribic, Christine; Pomara, Lars Y.; Zuckerberg, Benjamin

2017-01-01

ContextTemperate grasslands and their dependent species are exposed to high variability in weather and climate due to the lack of natural buffers such as forests. Grassland birds are particularly vulnerable to this variability, yet have failed to shift poleward in response to recent climate change like other bird species in North America. However, there have been few studies examining the effect of weather on grassland bird demography and consequent influence of climate change on population persistence and distributional shifts.ObjectivesThe goal of this study was to estimate the vulnerability of Henslow’s Sparrow (Ammodramus henslowii), an obligate grassland bird that has been declining throughout much of its range, to past and future climatic variability.MethodsWe conducted a demographic meta-analysis from published studies and quantified the relationship between nest success rates and variability in breeding season climate. We projected the climate-demography relationships spatially, throughout the breeding range, and temporally, from 1981 to 2050. These projections were used to evaluate population dynamics by implementing a spatially explicit population model.ResultsWe uncovered a climate-demography linkage for Henslow’s Sparrow with summer precipitation, and to a lesser degree, temperature positively affecting nest success. We found that future climatic conditions—primarily changes in precipitation—will likely contribute to reduced population persistence and a southwestward range contraction.ConclusionsFuture distributional shifts in response to climate change may not always be poleward and assessing projected changes in precipitation is critical for grassland bird conservation and climate change adaptation.
Forest Health Monitoring and Forest Inventory Analysis programs monitor climate change effects in forest ecosystems

Treesearch

Kenneth W. Stolte

2001-01-01

The Forest Health Monitoring (FHM) and Forest Inventory and Analyses (FIA) programs are integrated bilogical monitoring systems that use nationally standardized methods to evaluate and report on the health and sustainability of forest ecosystems in the United States. Many of the anticipated changes in forest ecosystems from climate change were also issues addressed in...
Can we use the past as a lens to the future? Using historic events to predict regional grassland and shrubland responses to multi-year drought or wet periods under climate change

USDA-ARS?s Scientific Manuscript database

Background/Question/Methods Ecologists are being challenged to predict ecosystem responses under changing climatic conditions. Water availability is the primary driver of ecosystem processes in temperate grasslands and shrublands, but uncertainty in the magnitude and direction of change in precipita...
How would the ocean carbon cycle be affected by radiation management geoengineering?

NASA Astrophysics Data System (ADS)

Lauvset, Siv K.; Tjiputra, Jerry; Muri, Helene; Grini, Alf

2017-04-01

Human emissions of carbon dioxide to the atmosphere is unequivocally causing global warming and climate change (IPCC, 2013). At the 21st United Nations Framework Convention on climate Change (UNFCCC) Conference of the Parties it was agreed to limit the increase in global average temperature to 2˚C above pre-industrial levels. We have used the Norwegian Earth System Model (NorESM1-ME) and applied radiation management (RM) methods in order to bring the future radiative forcing change in the RCP8.5 CO2 emission scenario in line with that of the RCP4.5 CO2 emission scenario. Three different RM methods, with varying effects on atmospheric physics, were used in these experiments: stratospheric aerosol injection (SAI); marine sky brightening (MSB); and cirrus cloud thinning (CCT). Here we will present how the different methods affect the ocean carbon cycle, which is a well-known and important feedback on climate change. In particular, we focus on changes to the ocean primary production, which are known to be spatially and temporally complex. We show that while the global mean temperature when applying RM is similar to that in the RCP4.5 scenario, no RM method produce similar ocean primary production as in the RCP4.5 scenario. Our simulations indicate that when it comes to the ocean primary productivity there will be regional winners and losers. The different RM methods also produce spatially very different results, partly linked to how the different RM methods affect clouds. The results of this work does nothing to diminish the complexity of climate impacts on primary production, but rather highlights that any change in ocean primary production is driven by a combination of several parameters, which all change in different ways. The experiments highlight the, at present, uncertain changes to ocean productivity in the future and highlights the caution necessary before additional human perturbations to the Earth system is attempted.
Using Scenario Development to Encourage Tourism Business Resilience in the Great Lakes

NASA Astrophysics Data System (ADS)

Chin, N.; Day, J.; Sydnor, S.; Cherkauer, K. A.

2015-12-01

Tourism is an economic sector anticipated to be greatly affected by climate change, but the potential impacts of climate change on tourism have rarely been examined in detail in existing research. Past research has shown, however, that the small and medium businesses that dominate the tourism sector could be greatly impacted by climate change. We have presented global climate and hydrologic model research results to pre-selected coastal tourism business owners in the Great Lakes region to determine the best methods for delivering user-friendly future climate scenarios, given that existing research suggests that climate change adaptive behaviors and resilience increase with information (message) clarity. Model output analyses completed for this work have focused on temperature, precipitation, and extreme weather events due to their economic impact on tourism activities. We have also experimented with the development and use of infographics because of their ability to present information quickly and clearly. Initial findings of this work will be presented as well as lessons learned from stakeholder interactions. Two main results include that (1) extreme weather events may have more meaning to tourism business owners than general trends in climate and (2) long-term planning for climate is extremely difficult for tourism business owners because they operate on a much shorter planning timeline than those generally used for climate change analyses.
ECOSYSTEM IMPACTS OF GEOENGINEERING: A Review for Developing a Science Plan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Russell, Lynn M.; Rasch, Philip J.; Mace, Georgina

2012-06-01

Geoengineering methods are intended to reduce the magnitude of climate change. Climate change in some regions is already having demonstrable effects on ecosystem structure and functioning. Two different types of geoengineering activities have been proposed: carbon dioxide removal (CDR), which includes a range of engineered and biological processes to remove carbon dioxide (CO2) from the atmosphere, and solar radiation management (SRM, or sunlight reflection methods), whereby a small percentage of sunlight is reflected back into space to offset warming from greenhouse gases. In this review, we evaluate some of the possible impacts of CDR and SRM on the physical climatemore » and their subsequent influence on ecosystems, including the risks and uncertainties associated with new kinds of purposeful perturbations to Earth. Specifically, we find evidence that, if implemented successfully, some CDR methods and continue use of some SRM methods) could alleviate some of the deleterious ecosystem impacts associated with climate changes that might occur in the foreseeable future.« less
Perception, attitude and behavior in relation to climate change: A survey among CDC health professionals in Shanxi province, China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Junni, E-mail: junxinni@163.com; Hansen, Alana, E-mail: alana.hansen@adelaide.edu.au; Zhang, Ying, E-mail: ying.zhang@sydney.edu.au

Background: A better understanding of public perceptions, attitude and behavior in relation to climate change will provide an important foundation for government's policy-making, service provider's guideline development and the engagement of local communities. The purpose of this study was to assess the perception towards climate change, behavior change, mitigation and adaptation measures issued by the central government among the health professionals in the Centres for Disease Control and Prevention (CDC) in China. Methods: In 2013, a cross-sectional questionnaire survey was undertaken among 314 CDC health professionals in various levels of CDC in Shanxi Province, China. Descriptive analyses were performed. Results:more » More than two thirds of the respondents believed that climate change has happened at both global and local levels, and climate change would lead to adverse impacts to human beings. Most respondents (74.8%) indicated the emission of greenhouse gases was the cause of climate change, however there was a lack of knowledge about greenhouse gases and their sources. Media was the main source from which respondents obtained the information about climate change. A majority of respondents showed that they were willing to change behavior, but their actions were limited. In terms of mitigation and adaptation measures issued by the Chinese Government, respondents' perception showed inconsistency between strategies and relevant actions. Moreover, although the majority of respondents believed some strategies and measures were extremely important to address climate change, they were still concerned about economic development, energy security, and local environmental protection. Conclusion: There are gaps between perceptions and actions towards climate change among these health professionals. Further efforts need to be made to raise the awareness of climate change among health professionals, and to promote relevant actions to address climate change in the context of the proposed policies with local sustainable development. - Highlights: • Global climate change has significant impacts on human wellbeing and health. • Health professionals play a significant role in improving the health of local citizens in China. • Perceptions of CDC staff on climate change are useful for policy making. • There are gaps between perceptions and actions among these health professionals in China. • Further efforts need to raise awareness of climate change and promote relevant actions.« less

Bias-correction of CORDEX-MENA projections using the Distribution Based Scaling method

NASA Astrophysics Data System (ADS)

Bosshard, Thomas; Yang, Wei; Sjökvist, Elin; Arheimer, Berit; Graham, L. Phil

2014-05-01

Within the Regional Initiative for the Assessment of the Impact of Climate Change on Water Resources and Socio-Economic Vulnerability in the Arab Region (RICCAR) lead by UN ESCWA, CORDEX RCM projections for the Middle East Northern Africa (MENA) domain are used to drive hydrological impacts models. Bias-correction of newly available CORDEX-MENA projections is a central part of this project. In this study, the distribution based scaling (DBS) method has been applied to 6 regional climate model projections driven by 2 RCP emission scenarios. The DBS method uses a quantile mapping approach and features a conditional temperature correction dependent on the wet/dry state in the climate model data. The CORDEX-MENA domain is particularly challenging for bias-correction as it spans very diverse climates showing pronounced dry and wet seasons. Results show that the regional climate models simulate too low temperatures and often have a displaced rainfall band compared to WATCH ERA-Interim forcing data in the reference period 1979-2008. DBS is able to correct the temperature biases as well as some aspects of the precipitation biases. Special focus is given to the analysis of the influence of the dry-frequency bias (i.e. climate models simulating too few rain days) on the bias-corrected projections and on the modification of the climate change signal by the DBS method.
Evaluation of Historical and Projected Agricultural Climate Risk Over the Continental US

NASA Astrophysics Data System (ADS)

Zhu, X.; Troy, T. J.; Devineni, N.

2016-12-01

Food demands are rising due to an increasing population with changing food preferences, which places pressure on agricultural systems. In addition, in the past decade climate extremes have highlighted the vulnerability of our agricultural production to climate variability. Quantitative analyses in the climate-agriculture research field have been performed in many studies. However, climate risk still remains difficult to evaluate at large scales yet shows great potential of help us better understand historical climate change impacts and evaluate the future risk given climate projections. In this study, we developed a framework to evaluate climate risk quantitatively by applying statistical methods such as Bayesian regression, distribution fitting, and Monte Carlo simulation. We applied the framework over different climate regions in the continental US both historically and for modeled climate projections. The relative importance of any major growing season climate index, such as maximum dry period or heavy precipitation, was evaluated to determine what climate indices play a role in affecting crop yields. The statistical modeling framework was applied using county yields, with irrigated and rainfed yields separated to evaluate the different risk. This framework provides estimates of the climate risk facing agricultural production in the near-term that account for the full uncertainty of climate occurrences, range of crop response, and spatial correlation in climate. In particular, the method provides robust estimates of importance of irrigation in mitigating agricultural climate risk. The results of this study can contribute to decision making about crop choice and water use in an uncertain climate.
An adaptation strategy of sandland peasants in Yogyakarta toward climate change

NASA Astrophysics Data System (ADS)

Rusdiyana, E.; Suminah

2018-03-01

This study aims to explore and describe the adaptation strategies of sandland peasants toward climate change. Qualitative research method was employed and the data were collected through observation. In addition, the recording of the data, interview and the validity of data were determined by triangulation of sources. The results of the research showed that the adaptation strategies of sandland peasants toward climate change were; (1) the adjustment of crop varieties, (2) the utilization of productive crops as wind breaking, and (3) the irrigation system using “sumur panthek”.
Climate Connections in Virginia: Your Actions Matter

NASA Astrophysics Data System (ADS)

Hoffman, J. S.; Maurakis, E. G.

2016-12-01

Our project objectives are to educate the general public about the science of climate change on global and local scales, highlight current and potential future impacts of climate change on Virginia and its communities, define community climate resiliency and why it is important, illustrate how individuals can contribute to the resiliency of their own community by taking personal steps to be prepared for weather events and health threats related to climate change, and, foster a conversion of climate change awareness and understanding into personal action to increase readiness and resiliency in homes, schools, and communities. The communication methods used to convey climate change and resiliency information are: development of new programming for the museum's NOAA Science on a Sphere® and digital Dome theater, production of a statewide digital media series (24 audio and 12 video content pieces/year), engagement with social media platforms, a public lecture series, facilitation of resiliency-themed programming (Art Lab, Challenge Lab, EcoLab), establishment of extreme event readiness challenge workshops, and enacting community preparedness and resiliency checklist and certification programs. A front-end evaluation was conducted to survey general audience understanding of the difference between climate and weather, climate change impacts, and resilience. We seek here to share some initial content and reflection based on the first few months of this project. Funded by NOAA Award NA15SEC0080009 and the Virginia Environmental Endowment.
Applying a framework for landscape planning under climate change for the conservation of biodiversity in the Finnish boreal forest.

PubMed

Mazziotta, Adriano; Triviño, Maria; Tikkanen, Olli-Pekka; Kouki, Jari; Strandman, Harri; Mönkkönen, Mikko

2015-02-01

Conservation strategies are often established without consideration of the impact of climate change. However, this impact is expected to threaten species and ecosystem persistence and to have dramatic effects towards the end of the 21st century. Landscape suitability for species under climate change is determined by several interacting factors including dispersal and human land use. Designing effective conservation strategies at regional scales to improve landscape suitability requires measuring the vulnerabilities of specific regions to climate change and determining their conservation capacities. Although methods for defining vulnerability categories are available, methods for doing this in a systematic, cost-effective way have not been identified. Here, we use an ecosystem model to define the potential resilience of the Finnish forest landscape by relating its current conservation capacity to its vulnerability to climate change. In applying this framework, we take into account the responses to climate change of a broad range of red-listed species with different niche requirements. This framework allowed us to identify four categories in which representation in the landscape varies among three IPCC emission scenarios (B1, low; A1B, intermediate; A2, high emissions): (i) susceptible (B1 = 24.7%, A1B = 26.4%, A2 = 26.2%), the most intact forest landscapes vulnerable to climate change, requiring management for heterogeneity and resilience; (ii) resilient (B1 = 2.2%, A1B = 0.5%, A2 = 0.6%), intact areas with low vulnerability that represent potential climate refugia and require conservation capacity maintenance; (iii) resistant (B1 = 6.7%, A1B = 0.8%, A2 = 1.1%), landscapes with low current conservation capacity and low vulnerability that are suitable for restoration projects; (iv) sensitive (B1 = 66.4%, A1B = 72.3%, A2 = 72.0%), low conservation capacity landscapes that are vulnerable and for which alternative conservation measures are required depending on the intensity of climate change. Our results indicate that the Finnish landscape is likely to be dominated by a very high proportion of sensitive and susceptible forest patches, thereby increasing uncertainty for landscape managers in the choice of conservation strategies. © 2014 John Wiley & Sons Ltd.
Climate Change and Water Security in South Africa; Assessing Conflict and Coping Strategies in KwaZulu-Natal

NASA Astrophysics Data System (ADS)

Hosea, P. O.

2017-12-01

The focus on the security implication of climate change was intensified after the 2007 United Nations Security Council debate on climate change as a threat multiplier. In the light of this, Africa is identified as the continent highly vulnerable to climate change impacts due to its high dependence on climate sensitive economy, high poverty prevalence rate, weak institutional coping capacity as well as poor social infrastructure. In the past decades, the peculiarity of South Africa vis-à-vis climate change vulnerability, especially water scarcity, has become an issue of political and economic concern. The country is water stressed due to its arid and semi-arid conditions. In light of this, the Council for Scientific and Industrial Research (CSIR) (2010) assert that while global temperature increased by 0.80C over the last century, the surface temperature around the Southern Africa region increased by 2.00C over the same period. This connotes that climate change and its impact is inevitable for the region. This will further exacerbate the already stress water resources within South Africa. Owing to Cilliers (2009) and the Council on Foreign Relations (2016) argument that most conflict in Africa are largely driven by resource competition which are masqueraded as issues based on politics, religion or ethnicity, this study investigates the propensity of conflict dynamics in relation to climate change and water security. Using eco-violence theory as a theoretical framework and on the premises of human security, the study assess the security implications triggered by the impact of climate change on water security of rural communities in uMkhanyakude District Municipality, KwaZulu-Natal, South Africa. It focused on the extent to which this might trigger conflict as a coping mechanism among rural dwellers to water insecurity in order to inform policy options. Data for the were sourced using a mixed method paradigm where 385 survey questionnaire were distributed using simple random sampling method, 28 in-depth interview using specific sampling as well as 8 focus group discussion. The data generated were analyzed using descriptive statistic with SPSS, as well as thematic content analysis for the quantitative and qualitative data respectively.
A dynamic, climate-driven model of Rift Valley fever.

PubMed

Leedale, Joseph; Jones, Anne E; Caminade, Cyril; Morse, Andrew P

2016-03-31

Outbreaks of Rift Valley fever (RVF) in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF) model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.
Economic evidence on the health impacts of climate change in europe.

PubMed

Hutton, Guy; Menne, Bettina

2014-01-01

In responding to the health impacts of climate change, economic evidence and tools inform decision makers of the efficiency of alternative health policies and interventions. In a time when sweeping budget cuts are affecting all tiers of government, economic evidence on health protection from climate change spending enables comparison with other public spending. The review included 53 countries of the World Health Organization (WHO) European Region. Literature was obtained using a Medline and Internet search of key terms in published reports and peer-reviewed literature, and from institutions working on health and climate change. Articles were included if they provided economic estimation of the health impacts of climate change or adaptation measures to protect health from climate change in the WHO European Region. Economic studies are classified under health impact cost, health adaptation cost, and health economic evaluation (comparing both costs and impacts). A total of 40 relevant studies from Europe were identified, covering the health damage or adaptation costs related to the health effects of climate change and response measures to climate-sensitive diseases. No economic evaluation studies were identified of response measures specific to the impacts of climate change. Existing studies vary in terms of the economic outcomes measured and the methods for evaluation of health benefits. The lack of robust health impact data underlying economic studies significantly affects the availability and precision of economic studies. Economic evidence in European countries on the costs of and response to climate-sensitive diseases is extremely limited and fragmented. Further studies are urgently needed that examine health impacts and the costs and efficiency of alternative responses to climate-sensitive health conditions, in particular extreme weather events (other than heat) and potential emerging diseases and other conditions threatening Europe.
Projected wetland densities under climate change: habitat loss but little geographic shift in conservation strategy.

PubMed

Sofaer, Helen R; Skagen, Susan K; Barsugli, Joseph J; Rashford, Benjamin S; Reese, Gordon C; Hoeting, Jennifer A; Wood, Andrew W; Noon, Barry R

2016-09-01

Climate change poses major challenges for conservation and management because it alters the area, quality, and spatial distribution of habitat for natural populations. To assess species' vulnerability to climate change and target ongoing conservation investments, researchers and managers often consider the effects of projected changes in climate and land use on future habitat availability and quality and the uncertainty associated with these projections. Here, we draw on tools from hydrology and climate science to project the impact of climate change on the density of wetlands in the Prairie Pothole Region of the USA, a critical area for breeding waterfowl and other wetland-dependent species. We evaluate the potential for a trade-off in the value of conservation investments under current and future climatic conditions and consider the joint effects of climate and land use. We use an integrated set of hydrological and climatological projections that provide physically based measures of water balance under historical and projected future climatic conditions. In addition, we use historical projections derived from ten general circulation models (GCMs) as a baseline from which to assess climate change impacts, rather than historical climate data. This method isolates the impact of greenhouse gas emissions and ensures that modeling errors are incorporated into the baseline rather than attributed to climate change. Our work shows that, on average, densities of wetlands (here defined as wetland basins holding water) are projected to decline across the U.S. Prairie Pothole Region, but that GCMs differ in both the magnitude and the direction of projected impacts. However, we found little evidence for a shift in the locations expected to provide the highest wetland densities under current vs. projected climatic conditions. This result was robust to the inclusion of projected changes in land use under climate change. We suggest that targeting conservation towards wetland complexes containing both small and relatively large wetland basins, which is an ongoing conservation strategy, may also act to hedge against uncertainty in the effects of climate change. © 2016 by the Ecological Society of America.
Reservoir adaptive operating rules based on both of historical streamflow and future projections

NASA Astrophysics Data System (ADS)

Zhang, Wei; Liu, Pan; Wang, Hao; Chen, Jie; Lei, Xiaohui; Feng, Maoyuan

2017-10-01

Climate change is affecting hydrological variables and consequently is impacting water resources management. Historical strategies are no longer applicable under climate change. Therefore, adaptive management, especially adaptive operating rules for reservoirs, has been developed to mitigate the possible adverse effects of climate change. However, to date, adaptive operating rules are generally based on future projections involving uncertainties under climate change, yet ignoring historical information. To address this, we propose an approach for deriving adaptive operating rules considering both historical information and future projections, namely historical and future operating rules (HAFOR). A robustness index was developed by comparing benefits from HAFOR with benefits from conventional operating rules (COR). For both historical and future streamflow series, maximizations of both average benefits and the robustness index were employed as objectives, and four trade-offs were implemented to solve the multi-objective problem. Based on the integrated objective, the simulation-based optimization method was used to optimize the parameters of HAFOR. Using the Dongwushi Reservoir in China as a case study, HAFOR was demonstrated to be an effective and robust method for developing adaptive operating rules under the uncertain changing environment. Compared with historical or projected future operating rules (HOR or FPOR), HAFOR can reduce the uncertainty and increase the robustness for future projections, especially regarding results of reservoir releases and volumes. HAFOR, therefore, facilitates adaptive management in the context that climate change is difficult to predict accurately.
2700 years of Mediterranean environmental change in central Italy: a synthesis of sedimentary and cultural records to interpret past impacts of climate on society

NASA Astrophysics Data System (ADS)

Mensing, Scott A.; Tunno, Irene; Sagnotti, Leonardo; Florindo, Fabio; Noble, Paula; Archer, Claire; Zimmerman, Susan; Pavón-Carrasco, Francisco Javier; Cifani, Gabriele; Passigli, Susanna; Piovesan, Gianluca

2015-05-01

Abrupt climate change in the past is thought to have disrupted societies by accelerating environmental degradation, potentially leading to cultural collapse. Linking climate change directly to societal disruption is challenging because socioeconomic factors also play a large role, with climate being secondary or sometimes inconsequential. Combining paleolimnologic, historical, and archaeological methods provides for a more secure basis for interpreting the past impacts of climate on society. We present pollen, non-pollen palynomorph, geochemical, paleomagnetic and sedimentary data from a high-resolution 2700 yr lake sediment core from central Italy and compare these data with local historical documents and archeological surveys to reconstruct a record of environmental change in relation to socioeconomic history and climatic fluctuations. Here we document cases in which environmental change is strongly linked to changes in local land management practices in the absence of clear climatic change, as well as examples when climate change appears to have been a strong catalyst that resulted in significant environmental change that impacted local communities. During the Imperial Roman period, despite a long period of stable, mild climate, and a large urban population in nearby Rome, our site shows only limited evidence for environmental degradation. Warm and mild climate during the Medieval Warm period, on the other hand, led to widespread deforestation and erosion. The ability of the Romans to utilize imported resources through an extensive trade network may have allowed for preservation of the environment near the Roman capital, whereas during medieval time, the need to rely on local resources led to environmental degradation. Cool wet climate during the Little Ice Age led to a breakdown in local land use practices, widespread land abandonment and rapid reforestation. Our results present a high-resolution regional case study that explores the effect of climate change on society for an under-documented region of Europe.
A review of downscaling procedures - a contribution to the research on climate change impacts at city scale

NASA Astrophysics Data System (ADS)

Smid, Marek; Costa, Ana; Pebesma, Edzer; Granell, Carlos; Bhattacharya, Devanjan

2016-04-01

Human kind is currently predominantly urban based, and the majority of ever continuing population growth will take place in urban agglomerations. Urban systems are not only major drivers of climate change, but also the impact hot spots. Furthermore, climate change impacts are commonly managed at city scale. Therefore, assessing climate change impacts on urban systems is a very relevant subject of research. Climate and its impacts on all levels (local, meso and global scale) and also the inter-scale dependencies of those processes should be a subject to detail analysis. While global and regional projections of future climate are currently available, local-scale information is lacking. Hence, statistical downscaling methodologies represent a potentially efficient way to help to close this gap. In general, the methodological reviews of downscaling procedures cover the various methods according to their application (e.g. downscaling for the hydrological modelling). Some of the most recent and comprehensive studies, such as the ESSEM COST Action ES1102 (VALUE), use the concept of Perfect Prog and MOS. Other examples of classification schemes of downscaling techniques consider three main categories: linear methods, weather classifications and weather generators. Downscaling and climate modelling represent a multidisciplinary field, where researchers from various backgrounds intersect their efforts, resulting in specific terminology, which may be somewhat confusing. For instance, the Polynomial Regression (also called the Surface Trend Analysis) is a statistical technique. In the context of the spatial interpolation procedures, it is commonly classified as a deterministic technique, and kriging approaches are classified as stochastic. Furthermore, the terms "statistical" and "stochastic" (frequently used as names of sub-classes in downscaling methodological reviews) are not always considered as synonymous, even though both terms could be seen as identical since they are referring to methods handling input modelling factors as variables with certain probability distributions. In addition, the recent development is going towards multi-step methodologies containing deterministic and stochastic components. This evolution leads to the introduction of new terms like hybrid or semi-stochastic approaches, which makes the efforts to systematically classifying downscaling methods to the previously defined categories even more challenging. This work presents a review of statistical downscaling procedures, which classifies the methods in two steps. In the first step, we describe several techniques that produce a single climatic surface based on observations. The methods are classified into two categories using an approximation to the broadest consensual statistical terms: linear and non-linear methods. The second step covers techniques that use simulations to generate alternative surfaces, which correspond to different realizations of the same processes. Those simulations are essential because there is a limited number of real observational data, and such procedures are crucial for modelling extremes. This work emphasises the link between statistical downscaling methods and the research of climate change impacts at city scale.
A multi-layered governance framework for incorporating social science insights into adapting to the health impacts of climate change.

PubMed

Bowen, Kathryn J; Ebi, Kristie; Friel, Sharon; McMichael, Anthony J

2013-09-10

Addressing climate change and its associated effects is a multi-dimensional and ongoing challenge. This includes recognizing that climate change will affect the health and wellbeing of all populations over short and longer terms, albeit in varied ways and intensities. That recognition has drawn attention to the need to take adaptive actions to lessen adverse impacts over the next few decades from unavoidable climate change, particularly in developing country settings. A range of sectors is responsible for appropriate adaptive policies and measures to address the health risks of climate change, including health services, water and sanitation, trade, agriculture, disaster management, and development. To broaden the framing of governance and decision-making processes by using innovative methods and assessments to illustrate the multi-sectoral nature of health-related adaptation to climate change. This is a shift from sector-specific to multi-level systems encompassing sectors and actors, across temporal and spatial scales. A review and synthesis of the current knowledge in the areas of health and climate change adaptation governance and decision-making processes. A novel framework is presented that incorporates social science insights into the formulation and implementation of adaptation activities and policies to lessen the health risks posed by climate change. Clarification of the roles that different sectors, organizations, and individuals occupy in relation to the development of health-related adaptation strategies will facilitate the inclusion of health and wellbeing within multi-sector adaptation policies, thereby strengthening the overall set of responses to minimize the adverse health effects of climate change.
Defining Canadian Perspectives on Climate Change Science and Solutions

NASA Astrophysics Data System (ADS)

Rieger, C.; Byrne, J. M.

2014-12-01

Despite the overwhelming scientific evidence of potentially disastrous change in global climate, little is being accomplished in climate mitigation or adaptation in Canada. The energy sector in Canada is still primarily oil and gas, with huge tax breaks to the industry in spite of well known harmful regional and global impacts of fossil fuel pollution. One of the largest concerns for the climate science community is the variable and often complacent attitude many Canadians share on the issue of climate change. The objective herein is twofold: (1) a survey tool will be used to assess the views and opinions of Canadians on climate change science and solutions; (2) develop better communication methods for industry, government and NGOs to share the science and solutions with the public. The study results will inform the Canadian public, policy makers and industry of practical, effective changes needed to address climate change challenges. A survey of Canadians' perspectives is an important step in policy changing research. The climate research and application community must know the most effective ways to communicate the science and solutions with a public that is often resistant to change. The AGU presentation will feature the results of the survey, while continued work into 2015 will be towards advancing communication. This study is both timely and crucial for science communicators in understanding how Canadians view climate change, considering, for example, devastatingly extreme weather being experienced of late and its effect on the economy. The results will assist in recognizing how to encourage Canadians to work towards a more sustainable and resilient energy sector in Canada and abroad.
A multi-layered governance framework for incorporating social science insights into adapting to the health impacts of climate change

PubMed Central

Bowen, Kathryn J.; Ebi, Kristie; Friel, Sharon; McMichael, Anthony J.

2013-01-01

Background Addressing climate change and its associated effects is a multi-dimensional and ongoing challenge. This includes recognizing that climate change will affect the health and wellbeing of all populations over short and longer terms, albeit in varied ways and intensities. That recognition has drawn attention to the need to take adaptive actions to lessen adverse impacts over the next few decades from unavoidable climate change, particularly in developing country settings. A range of sectors is responsible for appropriate adaptive policies and measures to address the health risks of climate change, including health services, water and sanitation, trade, agriculture, disaster management, and development. Objectives To broaden the framing of governance and decision-making processes by using innovative methods and assessments to illustrate the multi-sectoral nature of health-related adaptation to climate change. This is a shift from sector-specific to multi-level systems encompassing sectors and actors, across temporal and spatial scales. Design A review and synthesis of the current knowledge in the areas of health and climate change adaptation governance and decision-making processes. Results A novel framework is presented that incorporates social science insights into the formulation and implementation of adaptation activities and policies to lessen the health risks posed by climate change. Conclusion Clarification of the roles that different sectors, organizations, and individuals occupy in relation to the development of health-related adaptation strategies will facilitate the inclusion of health and wellbeing within multi-sector adaptation policies, thereby strengthening the overall set of responses to minimize the adverse health effects of climate change. PMID:24028938
Climate change and disturbance interactions: Workshop on climate change and disturbance interactions in western North America, Tucson, Ariz., 12-15 February 2007

USGS Publications Warehouse

McKenzie, Don; Allen, Craig D.

2007-01-01

Warming temperatures across western North America, coupled with increased drought, are expected to exacerbate disturbance regimes, particularly wildfires, insect outbreaks, and invasions of exotic species. Many ecologists and resource managers expect ecosystems to change more rapidly from disturbance effects than from the effects of a changing climate by itself. A particular challenge is to understand the interactions among disturbance regimes; for example, how will massive outbreaks of bark beetles, which kill drought-stressed trees by feeding on cambial tissues, increase the potential for large severe wildfires in a warming climate?Researchers in climatology, ecosystem science, fire and insect ecology, and landscape modeling from across western North America convened in Tucson, Ariz., for a 2 and a half day intensive workshop to identify new research directions in climate change and disturbance ecology. Four work groups focused on different aspects of the response of disturbance regimes to climate change: (1) extreme events and climatic variability (2) the effects of changing disturbance regimes on ecosystems, (3) disturbance interactions and cumulative effects, and (4) developing new landscape disturbance models. The workshop was structured with the analytic hierarchy process, a decision support method for achieving consensus from diverse groups of experts without sacrificing individual contributions.
Projecting Future Heat-Related Mortality under Climate Change Scenarios: A Systematic Review

PubMed Central

Barnett, Adrian Gerard; Wang, Xiaoming; Vaneckova, Pavla; FitzGerald, Gerard; Tong, Shilu

2011-01-01

Background: Heat-related mortality is a matter of great public health concern, especially in the light of climate change. Although many studies have found associations between high temperatures and mortality, more research is needed to project the future impacts of climate change on heat-related mortality. Objectives: We conducted a systematic review of research and methods for projecting future heat-related mortality under climate change scenarios. Data sources and extraction: A literature search was conducted in August 2010, using the electronic databases PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 through July 2010. Data synthesis: Fourteen studies fulfilled the inclusion criteria. Most projections showed that climate change would result in a substantial increase in heat-related mortality. Projecting heat-related mortality requires understanding historical temperature–mortality relationships and considering the future changes in climate, population, and acclimatization. Further research is needed to provide a stronger theoretical framework for projections, including a better understanding of socioeconomic development, adaptation strategies, land-use patterns, air pollution, and mortality displacement. Conclusions: Scenario-based projection research will meaningfully contribute to assessing and managing the potential impacts of climate change on heat-related mortality. PMID:21816703
Homogenising time series: Beliefs, dogmas and facts

NASA Astrophysics Data System (ADS)

Domonkos, P.

2010-09-01

For obtaining reliable information about climate change and climate variability the use of high quality data series is essentially important, and one basic tool of quality improvements is the statistical homogenisation of observed time series. In the recent decades large number of homogenisation methods has been developed, but the real effects of their application on time series are still not known entirely. The ongoing COST HOME project (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As part of the COST activity, a benchmark dataset was built whose characteristics approach well the characteristics of real networks of observed time series. This dataset offers much better opportunity than ever to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. The author believes that several old theoretical rules have to be re-evaluated. Some examples of the hot questions, a) Statistically detected change-points can be accepted only with the confirmation of metadata information? b) Do semi-hierarchic algorithms for detecting multiple change-points in time series function effectively in practise? c) Is it good to limit the spatial comparison of candidate series with up to five other series in the neighbourhood? Empirical results - those from the COST benchmark, and other experiments too - show that real observed time series usually include several inhomogeneities of different sizes. Small inhomogeneities seem like part of the climatic variability, thus the pure application of classic theory that change-points of observed time series can be found and corrected one-by-one is impossible. However, after homogenisation the linear trends, seasonal changes and long-term fluctuations of time series are usually much closer to the reality, than in raw time series. The developers and users of homogenisation methods have to bear in mind that the eventual purpose of homogenisation is not to find change-points, but to have the observed time series with statistical properties those characterise well the climate change and climate variability.
Choosing and using climate-change scenarios for ecological-impact assessments and conservation decisions.

PubMed

Snover, Amy K; Mantua, Nathan J; Littell, Jeremy S; Alexander, Michael A; McClure, Michelle M; Nye, Janet

2013-12-01

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment. Selección y Uso de Escenarios de Cambio Climático para Estudios de Impacto Ecológico y Decisiones de Conservación. © 2013 Society for Conservation Biology.
AgMIP: New Results from Sub-Saharan Africa and South Asia Regional Integrated Assessments

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2014-12-01

AgMIP conducted the first set of comprehensive regional integrated assessments of climate change impacts on smallholder farmers in Sub-Saharan Africa and South Asia led by researchers from the regions themselves. The project developed new methods integrating climate, crop, livestock and economic models to conduct climate change impact assessments that characterize impacts on smallholder groups. AgMIP projections of climate change impacts on agriculture are more realistic than previous assessments because they take agricultural development into account. Using the best available data and models, the assessments directly evaluated yield, income, and poverty outcomes including the effects of adaptation packages and development pathways. Results show that even with agricultural development, climate change generally will exert negative pressure on yields of smallholder farmers in Sub-Saharan Africa and South Asia. Without adaptation, climate change leads to increased poverty in some locations in Sub-Saharan Africa and South Asia compared to a future in which climate change does not occur. Adaptation can significantly improve smallholder farmer responses to climate change. AgMIP expert teams identified improved varieties, sowing practices, fertilizer application, and irrigation applications as prioritized adaptation strategies. These targeted adaptation packages were able to overcome a portion of detrimental impacts but could not compensate completely in many locations. Even in cases where average impact is near zero, vulnerability (i.e., those at risk of loss) can be substantial even when mean impacts are positive.

New methods in hydrologic modeling and decision support for culvert flood risk under climate change

NASA Astrophysics Data System (ADS)

Rosner, A.; Letcher, B. H.; Vogel, R. M.; Rees, P. S.

2015-12-01

Assessing culvert flood vulnerability under climate change poses an unusual combination of challenges. We seek a robust method of planning for an uncertain future, and therefore must consider a wide range of plausible future conditions. Culverts in our case study area, northwestern Massachusetts, USA, are predominantly found in small, ungaged basins. The need to predict flows both at numerous sites and under numerous plausible climate conditions requires a statistical model with low data and computational requirements. We present a statistical streamflow model that is driven by precipitation and temperature, allowing us to predict flows without reliance on reference gages of observed flows. The hydrological analysis is used to determine each culvert's risk of failure under current conditions. We also explore the hydrological response to a range of plausible future climate conditions. These results are used to determine the tolerance of each culvert to future increases in precipitation. In a decision support context, current flood risk as well as tolerance to potential climate changes are used to provide a robust assessment and prioritization for culvert replacements.
Evaluation of climatic changes in South-Asia

NASA Astrophysics Data System (ADS)

Kjellstrom, Erik; Rana, Arun; Grigory, Nikulin; Renate, Wilcke; Hansson, Ulf; Kolax, Michael

2016-04-01

Literature has sufficient evidences of climate change impact all over the world and its impact on various sectors. In light of new advancements made in climate modeling, availability of several climate downscaling approaches, the more robust bias correction methods with varying complexities and strengths, in the present study we performed a systematic evaluation of climate change impact over South-Asia region. We have used different Regional Climate Models (RCMs) (from CORDEX domain), (Global Climate Models GCMs) and gridded observations for the study area to evaluate the models in historical/control period (1980-2010) and changes in future period (2010-2099). Firstly, GCMs and RCMs are evaluated against the Gridded observational datasets in the area using precipitation and temperature as indicative variables. Observational dataset are also evaluated against the reliable set of observational dataset, as pointed in literature. Bias, Correlation, and changes (among other statistical measures) are calculated for the entire region and both the variables. Eventually, the region was sub-divided into various smaller domains based on homogenous precipitation zones to evaluate the average changes over time period. Spatial and temporal changes for the region are then finally calculated to evaluate the future changes in the region. Future changes are calculated for 2 Representative Concentration Pathways (RCPs), the middle emission (RCP4.5) and high emission (RCP8.5) and for both climatic variables, precipitation and temperature. Lastly, Evaluation of Extremes is performed based on precipitation and temperature based indices for whole region in future dataset. Results have indicated that the whole study region is under extreme stress in future climate scenarios for both climatic variables i.e. precipitation and temperature. Precipitation variability is dependent on the location in the area leading to droughts and floods in various regions in future. Temperature is hinting towards a constant increase throughout the region regardless of location.
Assessing Potential Future Carbon Dynamics with Climate Change and Fire Management in a Mountainous Landscape on the Olympic Peninsula, Washington, USA

NASA Astrophysics Data System (ADS)

Kennedy, R. S.

2010-12-01

Forests of the mountainous landscapes of the maritime Pacific Northwestern USA may have high carbon sequestration potential via their high productivity and moderate to infrequent fire regimes. With climate change, there may be shifts in incidence and severity of fire, especially in the drier areas of the region, via changes to forest productivity and hydrology, and consequent effects to C sequestration and forest structure. To explore this issue, I assessed potential effects of fire management (little fire suppression/wildland fire management/highly effective fire suppression) under two climate change scenarios on future C sequestration dynamics (amounts and spatial pattern) in Olympic National Park, WA, over a 500-year simulation period. I used the simulation platform FireBGCv2, which contains a mechanistic, individual tree succession model, a spatially explicit climate-based biophysical model that uses daily weather data, and a spatially explicit fire model incorporating ignition, spread, and effects on ecosystem components. C sequestration patterns varied over time and spatial and temporal patterns differed somewhat depending on the climate change scenario applied and the fire management methods employed. Under the more extreme climate change scenario with little fire suppression, fires were most frequent and severe and C sequestration decreased. General trends were similar under the more moderate climate change scenario, as compared to current climate, but spatial patterns differed. Both climate change scenarios under highly effective fire suppression showed about 50% of starting total C after the initial transition phase, whereas with 10% fire suppression both scenarios exhibited about 10% of starting amounts. Areas of the landscape that served as refugia for older forest under increasing frequency of high severity fire were also hotspots for C sequestration in a landscape experiencing increasing frequency of disturbance with climate change.
A Sustainable Early Warning System for Climate Change Impacts on Water Quality Management

NASA Astrophysics Data System (ADS)

Lee, T.; Tung, C.; Chung, N.

2007-12-01

In this era of rapid social and technological change leading to interesting life complexity and environmental displacement, both positive and negative effects among ecosystems call for a balance in which there are impacts by climate changes. Early warning systems for climate change impacts are necessary in order to allow society as a whole to properly and usefully assimilate the masses of new information and knowledge. Therefore, our research addresses to build up a sustainable early warning mechanism. The main goal is to mitigate the cumulative impacts on the environment of climate change and enhance adaptive capacities. An effective early warning system has been proven for protection. However, there is a problem that estimate future climate changes would be faced with high uncertainty. In general, take estimations for climate change impacts would use the data from General Circulation Models and take the analysis as the Intergovernmental Panel on Climate Change declared. We follow the course of the method for analyzing climate change impacts and attempt to accomplish the sustainable early warning system for water quality management. Climate changes impact not only on individual situation but on short-term variation and long-term gradually changes. This kind characteristic should adopt the suitable warning system for long-term formulation and short- term operation. To continue the on-going research of the long-term early warning system for climate change impacts on water quality management, the short-term early warning system is established by using local observation data for reappraising the warning issue. The combination of long-term and short-term system can provide more circumstantial details. In Taiwan, a number of studies have revealed that climate change impacts on water quality, especially in arid period, the concentration of biological oxygen demand may turn into worse. Rapid population growth would also inflict injury on its assimilative capacity to degenerate. To concern about those items, the sustainable early warning system is established and the initiative fall into the following categories: considering the implications for policies, applying adaptive strategies and informing the new climate changes. By setting up the framework of early warning system expectantly can defend stream area from impacts damaging and in sure the sustainable development.
A Framework for Addressing Skeptics' Claims Using Evidence-Based Argumentation: Lessons Learned from Educational Research

NASA Astrophysics Data System (ADS)

Lambert, J. L.; Bleicher, R. E.; Edwards, A.; Henderson, A.

2012-12-01

In science education, climate change is an issue that is especially useful for teaching concepts spanning several fields of science, as well the nature and practices of science. In response, we are developing a NASA-funded curriculum, titled Climate Science Investigations (CSI): South Florida, that teaches high school and first-year undergraduate level students how to analyze and use scientific data answer questions about climate change. To create an effective curriculum, we integrated lessons learned from our educational research conducted within our elementary science methods courses (Lambert, Lindgren, & Bleicher, 2012). For the past few years, we have been integrating climate science in our courses as a way to teach standards across several science disciplines and assessing our preservice teachers' gains in knowledge over the semesters. More recently, given the media attention and reports on the public's shift in opinion toward being more skeptical (Kellstedt, Zahran, & Vedlitz, 2008; Washington & Cook, 2011), we have assessed our students' perceptions about climate change and implemented strategies to help students use evidence-based scientific argumentation to address common claims of climate skeptics. In our elementary science methods courses, we framed climate change as a crosscutting theme, as well as a core idea, in the Next Generation Science Standards. We proposed that the issue and science of climate change would help preservice teachers not only become more interested in the topic, but also be more prepared to teach core science concepts spanning several disciplines (physical, life, and earth sciences). We also thought that highlighting the "practice of scientific inquiry" by teaching students to develop evidence-based arguments would help the preservice teachers become more analytical and able to differentiate scientific evidence from opinions, which could ultimately influence their perceptions on climate change. Lessons learned from our preservice teachers' conceptions and perceptions about climate change, as well as the difficulties in engaging in evidence-based argumentation, have informed and enhanced the framework for development of the CSI: South Florida curriculum. The modules are sequenced according to the proposed learning progression. First, students are introduced to the nature of science and Earth's energy balance. Students then investigate the temporal and spatial temperature data to answer the question of whether Earth is warming. Students also compare natural and anthropogenic causes of climate change, investigate the various observed and projected consequences of climate change in the fourth module, and examine ways to mitigate the effects of and adapt to climate change. Finally, students learn how to refute skeptics' claims by providing counter evidence and reasoning of why the skeptics' claim is not the appropriate explanation. This paper describes our conceptual framework for teaching students how to address the skeptics' claims using the content learned in the CSI: South Florida curriculum and evidence-based argumentation.
How Teachers' Beliefs About Climate Change Influence Their Instruction and Resulting Student Outcomes

NASA Astrophysics Data System (ADS)

Nation, M.; Feldman, A.; Smith, G.

2017-12-01

The purpose of the study was to understand the relationship between teachers' beliefs and understandings of climate change and their instructional practices to determine if and how they impact student outcomes. Limited research has been done in the area of teacher beliefs on climate change, their instruction, and resulting student outcomes. This study contributes to the greater understanding of teachers' beliefs and impact on climate change curriculum implementation. The study utilized a mixed methods approach to data collection and analysis. Data were collected in the form of classroom observations, surveys, and interviews from teachers and students participating in the study over a four-month period. Qualitative and quantitative findings were analyzed through thematic coding and descriptive analysis and compared in an effort to triangulate findings. The results of the study suggest teachers and students believe climate change is occurring and humans are largely to blame. Personal beliefs are important when teaching controversial topics, such as climate change, but participants maintained neutrality within their instruction of the topic, as not to appear biased or influence students' decisions about climate change, and avoid political controversy in the classroom. Overall, the study found teachers' level of understandings and beliefs about climate change had little impact on their instruction and resulting student outcomes. Based on the findings, simply adding climate change to the existing science curriculum is not sufficient for teachers or students. Teachers need to be better prepared about effective pedagogical practices of the content in order to effectively teach a climate-centered curriculum. The barriers that exist for the inclusion of teachers' personal beliefs need to be removed in order for teachers to assert their own personal beliefs about climate change within their classroom instruction. Administrators and stakeholders need to support science teachers' beliefs about climate change, and uphold the efforts of the scientific community, regardless of political hierarchy. Students are loosing an opportunity for insight into educated, knowledgeable mentors, and are by-in-large left to the opinions of climate change that overwhelm news media, which may not be as trustworthy.
Modeling and dynamic monitoring of ecosystem performance in the Yukon River Basin

USGS Publications Warehouse

Wylie, Bruce K.; Zhang, L.; Ji, Lei; Tieszen, Larry L.; Bliss, N.B.

2008-01-01

Central Alaska is ecologically sensitive and experiencing stress in response to marked regional warming. Resource managers would benefit from an improved ability to monitor ecosystem processes in response to climate change, fire, insect damage, and management policies and to predict responses to future climate scenarios. We have developed a method for analyzing ecosystem performance as represented by the growing season integral of normalized difference vegetation index (NDVI), which is a measure of greenness that can be interpreted in terms of plant growth or photosynthetic activity (gross primary productivity). The approach illustrates the status and trends of ecosystem changes and separates the influences of climate and local site conditions from the influences of disturbances and land management.We emphasize the ability to quantify ecosystem processes, not simply changes in land cover, across the entire period of the remote sensing archive (Wylie and others, 2008). The method builds upon remotely sensed measures of vegetation greenness for each growing season. By itself, however, a time series of greenness often reflects annual climate variations in temperature and precipitation. Our method seeks to remove the influence of climate so that changes in underlying ecological conditions are identified and quantified. We define an "expected ecosystem performance" to represent the greenness response expected in a particular year given the climate of that year. We distinguish "performance anomalies" as cases where the ecosystem response is significantly different from the expected ecosystem performance. Maps of the performance anomalies (fig. 1) and trends in the anomalies give valuable information on the ecosystems for land managers and policy makers at a resolution of 1 km to 250 m.
An Ill Wind? Climate Change, Migration, and Health

PubMed Central

Barnett, Jon

2012-01-01

Background: Climate change is projected to cause substantial increases in population movement in coming decades. Previous research has considered the likely causal influences and magnitude of such movements and the risks to national and international security. There has been little research on the consequences of climate-related migration and the health of people who move. Objectives: In this review, we explore the role that health impacts of climate change may play in population movements and then examine the health implications of three types of movements likely to be induced by climate change: forcible displacement by climate impacts, resettlement schemes, and migration as an adaptive response. Methods: This risk assessment draws on research into the health of refugees, migrants, and people in resettlement schemes as analogs of the likely health consequences of climate-related migration. Some account is taken of the possible modulation of those health risks by climate change. Discussion: Climate-change–related migration is likely to result in adverse health outcomes, both for displaced and for host populations, particularly in situations of forced migration. However, where migration and other mobility are used as adaptive strategies, health risks are likely to be minimized, and in some cases there will be health gains. Conclusions: Purposeful and timely policy interventions can facilitate the mobility of people, enhance well-being, and maximize social and economic development in both places of origin and places of destination. Nevertheless, the anticipated occurrence of substantial relocation of groups and communities will underscore the fundamental seriousness of human-induced climate change. PMID:22266739
Climate Change and Older Americans: State of the Science

PubMed Central

Hurley, Bradford J.; Schultz, Peter A.; Jaglom, Wendy S.; Krishnan, Nisha; Harris, Melinda

2012-01-01

Background: Older adults make up 13% of the U.S. population, but are projected to account for 20% by 2040. Coinciding with this demographic shift, the rate of climate change is accelerating, bringing rising temperatures; increased risk of floods, droughts, and wildfires; stronger tropical storms and hurricanes; rising sea levels; and other climate-related hazards. Older Americans are expected to be located in places that may be relatively more affected by climate change, including coastal zones and large metropolitan areas. Objective: The objective of this review is to assess the vulnerability of older Americans to climate change and to identify opportunities for adaptation. Methods: We performed an extensive literature survey and summarized key findings related to demographics; climate stressors relevant to older adults; factors contributing to exposure, sensitivity, and adaptive capacity; and adaptation strategies. Discussion: A range of physiological and socioeconomic factors make older adults especially sensitive to and/or at risk for exposure to heat waves and other extreme weather events (e.g., hurricanes, floods, droughts), poor air quality, and infectious diseases. Climate change may increase the frequency or severity of these events. Conclusions: Older Americans are likely to be especially vulnerable to stressors associated with climate change. Although a growing body of evidence reports the adverse effects of heat on the health of older adults, research gaps remain for other climate-related risks. We need additional study of the vulnerability of older adults and the interplay of vulnerability, resilience, and adaptive responses to projected climate stressors. PMID:23033457
Climate Change In Indonesia (Case Study : Medan, Palembang, Semarang)

NASA Astrophysics Data System (ADS)

Suryadi, Yadi; Sugianto, Denny Nugroho; Hadiyanto

2018-02-01

Indonesia's maritime continent is one of the most vulnerable regions regarding to climate change impacts. One of the vulnerable areas affected are the urban areas, because they are home to almost half of Indonesia's population where they live and earn a living, so that environmental management efforts need to be done. To support such efforts, climate change analysis is required. The analysis was carried out in several big cities in Indonesia. The method used in the research was trend analysis of temperature, rainfall, shifts in rainfall patterns, and extreme climatic trend. The data of rainfall and temperature were obtained from Meteorology and Geophysics Agency (BMKG). The result shows that the air temperature and rainfall have a positive trend, except in Semarang City which having a negative rainfall trend. The result also shows heavy rainfall trends. These indicate that climate is changing in these three cities.
Climate Change and Its Impact on the Yield of Major Food Crops: Evidence from Pakistan

PubMed Central

Ali, Sajjad; Liu, Ying; Ishaq, Muhammad; Shah, Tariq; Abdullah; Ilyas, Aasir; Din, Izhar Ud

2017-01-01

Pakistan is vulnerable to climate change, and extreme climatic conditions are threatening food security. This study examines the effects of climate change (e.g., maximum temperature, minimum temperature, rainfall, relative humidity, and the sunshine) on the major crops of Pakistan (e.g., wheat, rice, maize, and sugarcane). The methods of feasible generalized least square (FGLS) and heteroscedasticity and autocorrelation (HAC) consistent standard error were employed using time series data for the period 1989 to 2015. The results of the study reveal that maximum temperature adversely affects wheat production, while the effect of minimum temperature is positive and significant for all crops. Rainfall effect towards the yield of a selected crop is negative, except for wheat. To cope with and mitigate the adverse effects of climate change, there is a need for the development of heat- and drought-resistant high-yielding varieties to ensure food security in the country. PMID:28538704
Anthropology is missing: on the World Development Report 2010: Development and Climate Change.

PubMed

Trostle, James

2010-07-01

When the World Bank publishes a report on climate change, the world takes notice. What are its diagnoses and treatments, and how present is anthropology in this analysis? The 2010 World Development Report on climate change provides few new diagnostic tools and no clear Bank policy revisions. It often fails to harmonize neoliberal development rhetoric with new climate-change imperatives. It nods to the importance of social context and risk perception yet refers primarily to behavioral economics and psychological constructs. Although anthropologists are documenting the local effects and human responses to larger-scale, climate-driven processes, our work is absent in the report. To play a role at global scale we would do well to learn more about concepts like nonlinearity and emergence, systems analysis, modeling, and disease dynamics. Our adroitness in developing metaphors and methods for crossing scale will make our efforts more visible and applicable.
Climate Change and Its Impact on the Yield of Major Food Crops: Evidence from Pakistan.

PubMed

Ali, Sajjad; Liu, Ying; Ishaq, Muhammad; Shah, Tariq; Abdullah; Ilyas, Aasir; Din, Izhar Ud

2017-05-24

Pakistan is vulnerable to climate change, and extreme climatic conditions are threatening food security. This study examines the effects of climate change (e.g., maximum temperature, minimum temperature, rainfall, relative humidity, and the sunshine) on the major crops of Pakistan (e.g., wheat, rice, maize, and sugarcane). The methods of feasible generalized least square (FGLS) and heteroscedasticity and autocorrelation (HAC) consistent standard error were employed using time series data for the period 1989 to 2015. The results of the study reveal that maximum temperature adversely affects wheat production, while the effect of minimum temperature is positive and significant for all crops. Rainfall effect towards the yield of a selected crop is negative, except for wheat. To cope with and mitigate the adverse effects of climate change, there is a need for the development of heat- and drought-resistant high-yielding varieties to ensure food security in the country.
A Global Framework for Monitoring Phenological Responses to Climate Change

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, Michael A; Hoffman, Forrest M; Hargrove, William Walter

2005-01-01

Remote sensing of vegetation phenology is an important method with which to monitor terrestrial responses to climate change, but most approaches include signals from multiple forcings, such as mixed phenological signals from multiple biomes, urbanization, political changes, shifts in agricultural practices, and disturbances. Consequently, it is difficult to extract a clear signal from the usually assumed forcing: climate change. Here, using global 8 km 1982 to 1999 Normalized Difference Vegetation Index (NDVI) data and an eight-element monthly climatology, we identified pixels whose wavelet power spectrum was consistently dominated by annual cycles and then created phenologically and climatically self-similar clusters, whichmore » we term phenoregions. We then ranked and screened each phenoregion as a function of landcover homogeneity and consistency, evidence of human impacts, and political diversity. Remaining phenoregions represented areas with a minimized probability of non-climatic forcings and form elemental units for long-term phenological monitoring.« less
A probabilistic method for streamflow projection and associated uncertainty analysis in a data sparse alpine region

NASA Astrophysics Data System (ADS)

Ren, Weiwei; Yang, Tao; Shi, Pengfei; Xu, Chong-yu; Zhang, Ke; Zhou, Xudong; Shao, Quanxi; Ciais, Philippe

2018-06-01

Climate change imposes profound influence on regional hydrological cycle and water security in many alpine regions worldwide. Investigating regional climate impacts using watershed scale hydrological models requires a large number of input data such as topography, meteorological and hydrological data. However, data scarcity in alpine regions seriously restricts evaluation of climate change impacts on water cycle using conventional approaches based on global or regional climate models, statistical downscaling methods and hydrological models. Therefore, this study is dedicated to development of a probabilistic model to replace the conventional approaches for streamflow projection. The probabilistic model was built upon an advanced Bayesian Neural Network (BNN) approach directly fed by the large-scale climate predictor variables and tested in a typical data sparse alpine region, the Kaidu River basin in Central Asia. Results show that BNN model performs better than the general methods across a number of statistical measures. The BNN method with flexible model structures by active indicator functions, which reduce the dependence on the initial specification for the input variables and the number of hidden units, can work well in a data limited region. Moreover, it can provide more reliable streamflow projections with a robust generalization ability. Forced by the latest bias-corrected GCM scenarios, streamflow projections for the 21st century under three RCP emission pathways were constructed and analyzed. Briefly, the proposed probabilistic projection approach could improve runoff predictive ability over conventional methods and provide better support to water resources planning and management under data limited conditions as well as enable a facilitated climate change impact analysis on runoff and water resources in alpine regions worldwide.
Addressing Value and Belief Systems on Climate Literacy in the Southeastern United States

NASA Astrophysics Data System (ADS)

McNeal, K. S.

2012-12-01

The southeast (SEUS; AL, AR, GA, FL, KY, LA, NC, SC, TN, E. TX) faces the greatest impacts as a result of climate change of any region in the U.S. which presents considerable and costly adaptation challenges. Paradoxically, people in the SEUS hold attitudes and perceptions that are more dismissive of climate change than those of any other region. An additional mismatch exists between the manner in which climate science is generally communicated and the underlying core values and beliefs held by a large segment of people in the SEUS. As a result, people frequently misinterpret and/or distrust information sources, inhibiting efforts to productively discuss and consider climate change and related impacts on human and environmental systems, and possible solutions and outcomes. The Climate Literacy Partnership in the Southeast (CLiPSE) project includes an extensive network of partners throughout the SEUS from faith, agriculture, culturally diverse, leisure, and K-20 educator communities that aim to address this educational need through a shared vision. CLiPSE has conducted a Climate Stewardship Survey (CSS) to determine the knowledge and perceptions of individuals in and beyond the CLiPSE network. The descriptive results of the CSS indicate that religion, predominantly Protestantism, plays a minor role in climate knowledge and perceptions. Likewise, political affiliation plays a minimal role in climate knowledge and perceptions between religions. However, when Protestants were broken out by political affiliation, statistically significant differences (t(30)=2.44, p=0.02) in knowledge related to the causes of climate change exist. Those Protestants affiliated with the Democratic Party (n=206) tended to maintain a statistically significant stronger knowledge of the causes of global climate change than their Republican counterparts. When SEUS educator (n=277) group was only considered, similar trends were evidenced, indicating that strongly held beliefs potentially influence classroom climate instruction. In order to assist this educator group, CLiPSE has aligned a sub-set of the Climate and Energy Awareness Network (CLEAN) education resources to 11 SEUS state standards in order to better enable educators to implement climate topics in their classrooms. As a potential method to address the unique belief systems in the SEUS, CLiPSE has determined that the best way to engage individuals in the SEUS on the topic of climate change is to invite them into an honest dialogue surrounding climate. To facilitate these conversations effectively, CLiPSE utilizes a dialogical community model that values diversity, encourages respect for one another, recognizes and articulates viewpoints, and prioritizes understanding over resolution. CLiPSE emphasizes people's values and beliefs as they relate to climate change information. Results from pilot studies indicate that this is a promising method to bring together diverse individuals on the climate change topic and initiate the conversation about this very important issue that can often be considered "taboo" in the SEUS.
Detecting hydrological changes through conceptual model

NASA Astrophysics Data System (ADS)

Viola, Francesco; Caracciolo, Domenico; Pumo, Dario; Francipane, Antonio; Valerio Noto, Leonardo

2015-04-01

Natural changes and human modifications in hydrological systems coevolve and interact in a coupled and interlinked way. If, on one hand, climatic changes are stochastic, non-steady, and affect the hydrological systems, on the other hand, human-induced changes due to over-exploitation of soils and water resources modifies the natural landscape, water fluxes and its partitioning. Indeed, the traditional assumption of static systems in hydrological analysis, which has been adopted for long time, fails whenever transient climatic conditions and/or land use changes occur. Time series analysis is a way to explore environmental changes together with societal changes; unfortunately, the not distinguishability between causes restrict the scope of this method. In order to overcome this limitation, it is possible to couple time series analysis with an opportune hydrological model, such as a conceptual hydrological model, which offers a schematization of complex dynamics acting within a basin. Assuming that model parameters represent morphological basin characteristics and that calibration is a way to detect hydrological signature at a specific moment, it is possible to argue that calibrating the model over different time windows could be a method for detecting potential hydrological changes. In order to test the capabilities of a conceptual model in detecting hydrological changes, this work presents different "in silico" experiments. A synthetic-basin is forced with an ensemble of possible future scenarios generated with a stochastic weather generator able to simulate steady and non-steady climatic conditions. The experiments refer to Mediterranean climate, which is characterized by marked seasonality, and consider the outcomes of the IPCC 5th report for describing climate evolution in the next century. In particular, in order to generate future climate change scenarios, a stochastic downscaling in space and time is carried out using realizations of an ensemble of General Circulation Models (GCMs) for the future scenarios 2046-2065 and 2081-2100. Land use changes (i.e., changes in the fraction of impervious area due to increasing urbanization) are explicitly simulated, while the reference hydrological responses are assessed by the spatially distributed, process-based hydrological model tRIBS, the TIN-based Real-time Integrated Basin Simulator. Several scenarios have been created, describing hypothetical centuries with steady conditions, climate change conditions, land use change conditions and finally complex conditions involving both transient climatic modifications and gradual land use changes. A conceptual lumped model, the EHSM (EcoHydrological Streamflow Model) is calibrated for the above mentioned scenarios with regard to different time-windows. The calibrated parameters show high sensitivity to anthropic variations in land use and/or climatic variability. Land use changes are clearly visible from parameters evolution especially when steady climatic conditions are considered. When the increase in urbanization is coupled with rainfall reduction the ability to detect human interventions through the analysis of conceptual model parameters is weakened.
Projecting the potential evapotranspiration by coupling different formulations and input data reliabilities: The possible uncertainty source for climate change impacts on hydrological regime

NASA Astrophysics Data System (ADS)

Wang, Weiguang; Li, Changni; Xing, Wanqiu; Fu, Jianyu

2017-12-01

Representing atmospheric evaporating capability for a hypothetical reference surface, potential evapotranspiration (PET) determines the upper limit of actual evapotranspiration and is an important input to hydrological models. Due that present climate models do not give direct estimates of PET when simulating the hydrological response to future climate change, the PET must be estimated first and is subject to the uncertainty on account of many existing formulae and different input data reliabilities. Using four different PET estimation approaches, i.e., the more physically Penman (PN) equation with less reliable input variables, more empirical radiation-based Priestley-Taylor (PT) equation with relatively dependable downscaled data, the most simply temperature-based Hamon (HM) equation with the most reliable downscaled variable, and downscaling PET directly by the statistical downscaling model, this paper investigated the differences of runoff projection caused by the alternative PET methods by a well calibrated abcd monthly hydrological model. Three catchments, i.e., the Luanhe River Basin, the Source Region of the Yellow River and the Ganjiang River Basin, representing a large climatic diversity were chosen as examples to illustrate this issue. The results indicated that although similar monthly patterns of PET over the period 2021-2050 for each catchment were provided by the four methods, the magnitudes of PET were still slightly different, especially for spring and summer months in the Luanhe River Basin and the Source Region of the Yellow River with relatively dry climate feature. The apparent discrepancy in magnitude of change in future runoff and even the diverse change direction for summer months in the Luanhe River Basin and spring months in the Source Region of the Yellow River indicated that the PET method related uncertainty occurred, especially in the Luanhe River Basin and the Source Region of the Yellow River with smaller aridity index. Moreover, the possible reason of discrepancies in uncertainty between three catchments was quantitatively discussed by the contribution analysis based on climatic elasticity method. This study can provide beneficial reference to comprehensively understand the impacts of climate change on hydrological regime and thus improve the regional strategy for future water resource management.
Attributing Climate Conditions for Stable Malaria Transmission to Human Activity in sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Sheldrake, L.; Mitchell, D.; Allen, M. R.

2015-12-01

Temperature and precipitation limit areas of stable malaria transmission, but the effects of climate change on the disease remain controversial. Previously, studies have not separated the influence of anthropogenic climate change and natural variability, despite being an essential step in the attribution of climate change impacts. Ensembles of 2900 simulations of regional climate in sub-Saharan Africa for the year 2013, one representing realistic conditions and the other how climate might have been in the absence of human influence, were used to force a P.falciparium climate suitability model developed by the Mapping Malaria Risk in Africa project. Strongest signals were detected in areas of unstable transmission, indicating their heightened sensitivity to climatic factors. Evidently, impacts of human-induced climate change were unevenly distributed: the probability of conditions being suitable for stable malaria transmission were substantially reduced (increased) in the Sahel (Greater Horn of Africa (GHOA), particularly in the Ethiopian and Kenyan highlands). The length of the transmission season was correspondingly shortened in the Sahel and extended in the GHOA, by 1 to 2 months, including in Kericho (Kenya), where the role of climate change in driving recent malaria occurrence is hotly contested. Human-induced warming was primarily responsible for positive anomalies in the GHOA, while reduced rainfall caused negative anomalies in the Sahel. The latter was associated with anthropogenic impacts on the West African Monsoon, but uncertainty in the RCM's ability to reproduce precipitation trends in the region weakens confidence in the result. That said, outputs correspond well with broad-scale changes in observed endemicity, implying a potentially important contribution of anthropogenic climate change to the malaria burden during the past century. Results support the health-framing of climate risk and help indicate hotspots of climate vulnerability, providing information to direct control interventions and investment, and allude to climate injustices. Extending methods, such as by using multiple climate and malaria models and investigating trends over longer timescales, would make results more generally applicable and improve their policy relevance.
Targeting climate diversity in conservation planning to build resilience to climate change

USGS Publications Warehouse

Heller, Nicole E.; Kreitler, Jason R.; Ackerly, David; Weiss, Stuart; Recinos, Amanda; Branciforte, Ryan; Flint, Lorraine E.; Flint, Alan L.; Micheli, Elisabeth

2015-01-01

Climate change is raising challenging concerns for systematic conservation planning. Are methods based on the current spatial patterns of biodiversity effective given long-term climate change? Some conservation scientists argue that planning should focus on protecting the abiotic diversity in the landscape, which drives patterns of biological diversity, rather than focusing on the distribution of focal species, which shift in response to climate change. Climate is one important abiotic driver of biodiversity patterns, as different climates host different biological communities and genetic pools. We propose conservation networks that capture the full range of climatic diversity in a region will improve the resilience of biotic communities to climate change compared to networks that do not. In this study we used historical and future hydro-climate projections from the high resolution Basin Characterization Model to explore the utility of directly targeting climatic diversity in planning. Using the spatial planning tool, Marxan, we designed conservation networks to capture the diversity of climate types, at the regional and sub-regional scale, and compared them to networks we designed to capture the diversity of vegetation types. By focusing on the Conservation Lands Network (CLN) of the San Francisco Bay Area as a real-world case study, we compared the potential resilience of networks by examining two factors: the range of climate space captured, and climatic stability to 18 future climates, reflecting different emission scenarios and global climate models. We found that the climate-based network planned at the sub-regional scale captured a greater range of climate space and showed higher climatic stability than the vegetation and regional based-networks. At the same time, differences among network scenarios are small relative to the variance in climate stability across global climate models. Across different projected futures, topographically heterogeneous areas consistently show greater climate stability than homogenous areas. The analysis suggests that utilizing high-resolution climate and hydrological data in conservation planning improves the likely resilience of biodiversity to climate change. We used these analyses to suggest new conservation priorities for the San Francisco Bay Area.

Studying Climate Response to Forcing by the Nonlinear Dynamical Mode Decomposition

NASA Astrophysics Data System (ADS)

Mukhin, Dmitry; Gavrilov, Andrey; Loskutov, Evgeny; Feigin, Alexander

2017-04-01

An analysis of global climate response to external forcing, both anthropogenic (mainly, CO2 and aerosol) and natural (solar and volcanic), is needed for adequate predictions of global climate change. Being complex dynamical system, the climate reacts to external perturbations exciting feedbacks (both positive and negative) making the response non-trivial and poorly predictable. Thus an extraction of internal modes of climate system, investigation of their interaction with external forcings and further modeling and forecast of their dynamics, are all the problems providing the success of climate modeling. In the report the new method for principal mode extraction from climate data is presented. The method is based on the Nonlinear Dynamical Mode (NDM) expansion [1,2], but takes into account a number of external forcings applied to the system. Each NDM is represented by hidden time series governing the observed variability, which, together with external forcing time series, are mapped onto data space. While forcing time series are considered to be known, the hidden unknown signals underlying the internal climate dynamics are extracted from observed data by the suggested method. In particular, it gives us an opportunity to study the evolution of principal system's mode structure in changing external conditions and separate the internal climate variability from trends forced by external perturbations. Furthermore, the modes so obtained can be extrapolated beyond the observational time series, and long-term prognosis of modes' structure including characteristics of interconnections and responses to external perturbations, can be carried out. In this work the method is used for reconstructing and studying the principal modes of climate variability on inter-annual and decadal time scales accounting the external forcings such as anthropogenic emissions, variations of the solar activity and volcanic activity. The structure of the obtained modes as well as their response to external factors, e.g. forecast their change in 21 century under different CO2 emission scenarios, are discussed. [1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510 [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101. http://doi.org/10.1063/1.4968852
Research agenda for integrated landscape modeling

Treesearch

Samuel A. Cushman; Donald McKenzie; David L. Peterson; Jeremy Littell; Kevin S. McKelvey

2007-01-01

Reliable predictions of how changing climate and disturbance regimes will affect forest ecosystems are crucial for effective forest management. Current fire and climate research in forest ecosystem and community ecology offers data and methods that can inform such predictions. However, research in these fields occurs at different scales, with disparate goals, methods,...
Test Plan for a Calibration Demonstration System for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

NASA Technical Reports Server (NTRS)

Thome, Kurtis; McCorkel, Joel; Hair, Jason; McAndrew, Brendan; Daw, Adrian; Jennings, Donald; Rabin, Douglas

2012-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe high-accuracy, long-term climate change trends and to use decadal change observations as the most critical method to determine the accuracy of climate change. One of the major objectives of CLARREO is to advance the accuracy of SI traceable absolute calibration at infrared and reflected solar wavelengths. This advance is required to reach the on-orbit absolute accuracy required to allow climate change observations to survive data gaps while remaining sufficiently accurate to observe climate change to within the uncertainty of the limit of natural variability. While these capabilities exist at NIST in the laboratory, there is a need to demonstrate that it can move successfully from NIST to NASA and/or instrument vendor capabilities for future spaceborne instruments. The current work describes the test plan for the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. The goal of the CDS is to allow the testing and evaluation of calibration approaches , alternate design and/or implementation approaches and components for the CLARREO mission. SOLARIS also provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The end result of efforts with the SOLARIS CDS will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections. The CLARREO mission addresses the need to observe high-accuracy, long-term climate change trends and advance the accuracy of SI traceable absolute calibration. The current work describes the test plan for the SOLARIS which is the calibration demonstration system for the reflected solar portion of CLARREO. SOLARIS provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The end result will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections.
Public interest in climate change over the past decade and the effects of the ‘climategate’ media event

NASA Astrophysics Data System (ADS)

Anderegg, William R. L.; Goldsmith, Gregory R.

2014-05-01

Despite overwhelming scientific consensus concerning anthropogenic climate change, many in the non-expert public perceive climate change as debated and contentious. There is concern that two recent high-profile media events—the hacking of the University of East Anglia emails and the Himalayan glacier melt rate presented in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change—may have altered public opinion of climate change. While survey data is valuable for tracking public perception and opinion over time, including in response to climate-related media events, emerging methods that facilitate rapid assessment of spatial and temporal patterns in public interest and opinion could be exceptionally valuable for understanding and responding to these events’ effects. We use a novel, freely-available dataset of worldwide web search term volumes to assess temporal patterns of interest in climate change over the past ten years, with a particular focus on looking at indicators of climate change skepticism around the high-profile media events. We find that both around the world and in the US, the public searches for the issue as ‘global warming,’ rather than ‘climate change,’ and that search volumes have been declining since a 2007 peak. We observe high, but transient spikes of search terms indicating skepticism around the two media events, but find no evidence of effects lasting more than a few months. Our results indicate that while such media events are visible in the short-term, they have little effect on salience of skeptical climate search terms on longer time-scales.
The AgMIP Coordinated Climate-Crop Modeling Project (C3MP): Methods and Protocols

NASA Technical Reports Server (NTRS)

Shukla, Sonali P.; Ruane, Alexander Clark

2014-01-01

Climate change is expected to alter a multitude of factors important to agricultural systems, including pests, diseases, weeds, extreme climate events, water resources, soil degradation, and socio-economic pressures. Changes to carbon dioxide concentration ([CO2]), temperature, and water (CTW) will be the primary drivers of change in crop growth and agricultural systems. Therefore, establishing the CTW-change sensitivity of crop yields is an urgent research need and warrants diverse methods of investigation. Crop models provide a biophysical, process-based tool to investigate crop responses across varying environmental conditions and farm management techniques, and have been applied in climate impact assessment by using a variety of methods (White et al., 2011, and references therein). However, there is a significant amount of divergence between various crop models' responses to CTW changes (Rotter et al., 2011). While the application of a site-based crop model is relatively simple, the coordination of such agricultural impact assessments on larger scales requires consistent and timely contributions from a large number of crop modelers, each time a new global climate model (GCM) scenario or downscaling technique is created. A coordinated, global effort to rapidly examine CTW sensitivity across multiple crops, crop models, and sites is needed to aid model development and enhance the assessment of climate impacts (Deser et al., 2012). To fulfill this need, the Coordinated Climate-Crop Modeling Project (C3MP) (Ruane et al., 2014) was initiated within the Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013). The submitted results from C3MP Phase 1 (February 15, 2013-December 31, 2013) are currently being analyzed. This chapter serves to present and update the C3MP protocols, discuss the initial participation and general findings, comment on needed adjustments, and describe continued and future development. AgMIP aims to improve substantially the climate, crop, and economic simulation tools that are used to characterize the agricultural sector, to assess future world food security under changing climate conditions, and to enhance adaptation capacity both globally and regionally. To understand better and improve the modeled crop responses, AgMIP has conducted detailed crop model intercomparisons at closely observed field sites for wheat (Asseng et al., 2013), rice (Li et al., in review), maize (Bassu et al., 2014), and sugarcane (Singels et al., 2013). A coordinated modeling exercise was one of the original motivations for AgMIP, and C3MP provides rapid estimation of crop responses to CO2, water, and temperature (CTW) changes, adding dimension and insight into the crop model intercomparisons, while facilitating interactions within the global community of modelers. C3MP also contributes a fast-track, multi-model climate sensitivity assessment for the AgMIP climate and crop modeling teams on Research Track 2 (Fig. 1), which seeks to understand the impact of projected climatic changes on crop production and food security (Rosenzweig et al., 2013; Ruane et al., 2014).
Exploring the response of net primary productivity variations to urban expansion and climate change: a scenario analysis for Guangdong Province in China.

PubMed

Pei, Fengsong; Li, Xia; Liu, Xiaoping; Lao, Chunhua; Xia, Gengrui

2015-03-01

Urban land development alters landscapes and carbon cycle, especially net primary productivity (NPP). Despite projections that NPP is often reduced by urbanization, little is known about NPP changes under future urban expansion and climate change conditions. In this paper, terrestrial NPP was calculated by using Biome-BGC model. However, this model does not explicitly address urban lands. Hence, we proposed a method of NPP-fraction to detect future urban NPP, assuming that the ratio of real NPP to potential NPP for urban cells remains constant for decades. Furthermore, NPP dynamics were explored by integrating the Biome-BGC and the cellular automata (CA), a widely used method for modeling urban growth. Consequently, urban expansion, climate change and their associated effects on the NPP were analyzed for the period of 2010-2039 using Guangdong Province in China as a case study. In addition, four scenarios were designed to reflect future conditions, namely baseline, climate change, urban expansion and comprehensive scenarios. Our analyses indicate that vegetation NPP in urban cells may increase (17.63 gC m(-2) year(-1)-23.35 gC m(-2) year(-1)) in the climate change scenario. However, future urban expansion may cause some NPP losses of 241.61 gC m(-2) year(-1), decupling the NPP increase of the climate change factor. Taking into account both climate change and urban expansion, vegetation NPP in urban area may decrease, minimally at a rate of 228.54 gC m(-2) year(-1) to 231.74 gC m(-2) year(-1). Nevertheless, they may account for an overall NPP increase of 0.78 TgC year(-1) to 1.28 TgC year(-1) in the whole province. All these show that the provincial NPP increase from climate change may offset the NPP decrease from urban expansion. Despite these results, it is of great significance to regulate reasonable expansion of urban lands to maintain carbon balance. Copyright © 2014 Elsevier Ltd. All rights reserved.
Responding to Climate Change at the Poles: Findings from the National Research Council's Reports on Climate Intervention

NASA Astrophysics Data System (ADS)

Russell, L. M.; McNutt, M. K.; Abdalati, W.; Caldeira, K.; Doney, S. C.; Falkowski, P. G.; Fetter, S.; Fleming, J. R.; Hamburg, S.; Morgan, G.; Penner, J.; Pierrehumbert, R.; Rasch, P. J.; Snow, J. T.; Wilcox, J.

2015-12-01

Earlier this year the National Research Council of the US National Academy of Sciences released a pair of reports on two strategies of climate intervention in order to reduce the risks of negative impacts from climate change. The first of the pair of reports discusses the opportunities and challenges in carbon capture and long-term, safe sequestration. The second report discusses several approaches to reflecting sunlight to cool Earth, including the risks, time scales, costs, and socio-economic, and political considerations. The primary conclusion from these pair of reports is that mitigation and adaptation are still our best choices in terms of cost and low risk for reducing harmful effects from climate change: there is no "silver bullet." Given that the polar regions of the planet are the most sensitive to climate change, the reports also touched on the potential for regional climate intervention. The majority of the methods that are currently under discussion and for which there is a body of peer-reviewed research would have global impacts, with but few exceptions.
Scale-dependent complementarity of climatic velocity and environmental diversity for identifying priority areas for conservation under climate change.

PubMed

Carroll, Carlos; Roberts, David R; Michalak, Julia L; Lawler, Joshua J; Nielsen, Scott E; Stralberg, Diana; Hamann, Andreas; Mcrae, Brad H; Wang, Tongli

2017-11-01

As most regions of the earth transition to altered climatic conditions, new methods are needed to identify refugia and other areas whose conservation would facilitate persistence of biodiversity under climate change. We compared several common approaches to conservation planning focused on climate resilience over a broad range of ecological settings across North America and evaluated how commonalities in the priority areas identified by different methods varied with regional context and spatial scale. Our results indicate that priority areas based on different environmental diversity metrics differed substantially from each other and from priorities based on spatiotemporal metrics such as climatic velocity. Refugia identified by diversity or velocity metrics were not strongly associated with the current protected area system, suggesting the need for additional conservation measures including protection of refugia. Despite the inherent uncertainties in predicting future climate, we found that variation among climatic velocities derived from different general circulation models and emissions pathways was less than the variation among the suite of environmental diversity metrics. To address uncertainty created by this variation, planners can combine priorities identified by alternative metrics at a single resolution and downweight areas of high variation between metrics. Alternately, coarse-resolution velocity metrics can be combined with fine-resolution diversity metrics in order to leverage the respective strengths of the two groups of metrics as tools for identification of potential macro- and microrefugia that in combination maximize both transient and long-term resilience to climate change. Planners should compare and integrate approaches that span a range of model complexity and spatial scale to match the range of ecological and physical processes influencing persistence of biodiversity and identify a conservation network resilient to threats operating at multiple scales. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
A method to identify drivers of societal change likely to affect natural assets in the future, illustrated with Australia's native biodiversity.

PubMed

Pepper, D A; Lada, Hania; Thomson, James R; Bakar, K Shuvo; Lake, P S; Mac Nally, Ralph

2017-03-01

Human society has a profound adverse effect on natural assets as human populations increase and as global climate changes. We need to envisage different futures that encompass plausible human responses to threats and change, and become more mindful of their likely impacts on natural assets. We describe a method for developing a set of future scenarios for a natural asset at national scale under ongoing human population growth and climate change. The method involves expansive consideration of potential drivers of societal change, a reduction of these to form a small set of key drivers to which contrasting settings are assigned, which we use to develop a set of different scenarios. We use Australia's native biodiversity as the focus to illustrate the method. Copyright © 2016 Elsevier B.V. All rights reserved.
Climate Hazard Assessment for Stakeholder Adaptation Planning in New York City

NASA Technical Reports Server (NTRS)

Horton, Radley M.; Gornitz, Vivien; Bader, Daniel A.; Ruane, Alex C.; Goldberg, Richard; Rosenzweig, Cynthia

2011-01-01

This paper describes a time-sensitive approach to climate change projections, developed as part of New York City's climate change adaptation process, that has provided decision support to stakeholders from 40 agencies, regional planning associations, and private companies. The approach optimizes production of projections given constraints faced by decision makers as they incorporate climate change into long-term planning and policy. New York City stakeholders, who are well-versed in risk management, helped pre-select the climate variables most likely to impact urban infrastructure, and requested a projection range rather than a single 'most likely' outcome. The climate projections approach is transferable to other regions and consistent with broader efforts to provide climate services, including impact, vulnerability, and adaptation information. The approach uses 16 Global Climate Models (GCMs) and three emissions scenarios to calculate monthly change factors based on 30-year average future time slices relative to a 30- year model baseline. Projecting these model mean changes onto observed station data for New York City yields dramatic changes in the frequency of extreme events such as coastal flooding and dangerous heat events. Based on these methods, the current 1-in-10 year coastal flood is projected to occur more than once every 3 years by the end of the century, and heat events are projected to approximately triple in frequency. These frequency changes are of sufficient magnitude to merit consideration in long-term adaptation planning, even though the precise changes in extreme event frequency are highly uncertain
Putting Climate Change on the Map: A Translation from Time to Space

NASA Astrophysics Data System (ADS)

Marzeion, B.; Bethke, I.; Drange, H.

2009-04-01

By increasing the concentrations of atmospheric greenhouses gases, man is changing the physical geography of planet Earth. This message is often given to the public in form of rather abstract numbers, such as changes in the annual mean surface temperature. Therefore, one of the difficulties to overcome when educating the public about climate change is to translate these abstract numbers into everyday experiences - a task that is not easy given the statistical and thereby abstract definition of the term 'climate' itself. However, climate does not only vary with time, but also with space, and people generally have a better idea of what it would be like to live in another place, than to experience an annual mean temperature rise of e.g. 3 K. We used the model calculations from the fourth assessment report of the Intergovernmental Panel on Climate Change to translate the projected temperature change into a change of location: Each point on a geographical map is shifted to the closest location that in the year 2000 has the annual mean temperature that the point is projected to have at some time in the future. With this method, it is possible to create a new kind of accessible and visually appealing illustration of climate change, answering the question: Where do I have to go today to experience tomorrow's climate? Similarly, it is possible to answer a related question: Where would I have to move if I want to continue living in today's climate?
Countering Climate Confusion in the Classroom: New Methods and Initiatives

NASA Astrophysics Data System (ADS)

McCaffrey, M.; Berbeco, M.; Reid, A. H.

2014-12-01

Politicians and ideologues blocking climate education through legislative manipulation. Free marketeers promoting the teaching of doubt and controversy to head off regulation. Education standards and curricula that skim over, omit, or misrepresent the causes, effects, risks and possible responses to climate change. Teachers who unknowingly foster confusion by presenting "both sides" of a phony scientific controversy. All of these contribute to dramatic differences in the quality and quantity of climate education received by U.S. students. Most U.S. adults and teens fail basic quizzes on energy and climate basics, in large part, because climate science has never been fully accepted as a vital component of a 21st-century science education. Often skipped or skimmed over, human contributions to climate change are sometimes taught as controversy or through debate, perpetuating a climate of confusion in many classrooms. This paper will review recent history of opposition to climate science education, and explore initial findings from a new survey of science teachers on whether, where and how climate change is being taught. It will highlight emerging effective pedagogical practices identified in McCaffrey's Climate Smart & Energy Wise, including the role of new initiatives such as the Next Generation Science Standards and Green Schools, and detail efforts of the Science League of America in countering denial and doubt so that educators can teach consistently and confidently about climate change.
Climate Risk and Vulnerability in the Caribbean and Gulf of Mexico Region: Interactions with Spatial Population and Land Cover Change

NASA Astrophysics Data System (ADS)

Chen, R. S.; Levy, M.; Baptista, S.; Adamo, S.

2010-12-01

Vulnerability to climate variability and change will depend on dynamic interactions between different aspects of climate, land-use change, and socioeconomic trends. Measurements and projections of these changes are difficult at the local scale but necessary for effective planning. New data sources and methods make it possible to assess land-use and socioeconomic changes that may affect future patterns of climate vulnerability. In this paper we report on new time series data sets that reveal trends in the spatial patterns of climate vulnerability in the Caribbean/Gulf of Mexico Region. Specifically, we examine spatial time series data for human population over the period 1990-2000, time series data on land use and land cover over 2000-2009, and infant mortality rates as a proxy for poverty for 2000-2008. We compare the spatial trends for these measures to the distribution of climate-related natural disaster risk hotspots (cyclones, floods, landslides, and droughts) in terms of frequency, mortality, and economic losses. We use these data to identify areas where climate vulnerability appears to be increasing and where it may be decreasing. Regions where trends and patterns are especially worrisome include coastal areas of Guatemala and Honduras.
Dynamic response of airborne infections to climate change: predictions for varicella

NASA Astrophysics Data System (ADS)

Baker, R.; Mahmud, A. S.; Metcalf, C. J. E.

2017-12-01

Characterizing how climate change will alter the burden of infectious diseases has clear applications for public health policy. Despite our uniquely detailed understanding of the transmission process for directly transmitted infections, the impact of climate variables on these infections remains understudied. We develop a novel methodology for estimating the causal relationship between climate and directly transmitted infections, which combines an epidemiological model of disease transmission with panel regression techniques. Our method allows us to move beyond correlational approaches to studying the link between climate and infectious diseases. Further, we can generate semi-mechanistic projections of incidence across climate scenarios. We illustrate our approach using 30 years of reported cases of varicella, a common airborne childhood infection, across 32 states in Mexico. We find significantly increased varicella transmission in drier conditions. We use this to map potential changes in the magnitude and variability of varicella incidence in Mexico as a result of projected changes in future climate conditions. Our results indicate that the predicted decrease in humidity in Mexico towards the end of the century will increase incidence of varicella, all else equal, and that these changes in incidence will be non-uniform across the year.
Climate change as a migration driver from rural and urban Mexico

NASA Astrophysics Data System (ADS)

Nawrotzki, Raphael J.; Hunter, Lori M.; Runfola, Daniel M.; Riosmena, Fernando

2015-11-01

Studies investigating migration as a response to climate variability have largely focused on rural locations to the exclusion of urban areas. This lack of urban focus is unfortunate given the sheer numbers of urban residents and continuing high levels of urbanization. To begin filling this empirical gap, this study investigates climate change impacts on US-bound migration from rural and urban Mexico, 1986-1999. We employ geostatistical interpolation methods to construct two climate change indices, capturing warm and wet spell duration, based on daily temperature and precipitation readings for 214 weather stations across Mexico. In combination with detailed migration histories obtained from the Mexican Migration Project, we model the influence of climate change on household-level migration from 68 rural and 49 urban municipalities. Results from multilevel event-history models reveal that a temperature warming and excessive precipitation significantly increased international migration during the study period. However, climate change impacts on international migration is only observed for rural areas. Interactions reveal a causal pathway in which temperature (but not precipitation) influences migration patterns through employment in the agricultural sector. As such, climate-related international migration may decline with continued urbanization and the resulting reductions in direct dependence of households on rural agriculture.
Climate Change as Migration Driver from Rural and Urban Mexico.

PubMed

Nawrotzki, Raphael J; Hunter, Lori M; Runfola, Daniel M; Riosmena, Fernando

2015-11-01

Studies investigating migration as a response to climate variability have largely focused on rural locations to the exclusion of urban areas. This lack of urban focus is unfortunate given the sheer numbers of urban residents and continuing high levels of urbanization. To begin filling this empirical gap, this study investigates climate change impacts on U.S.-bound migration from rural and urban Mexico, 1986-1999. We employ geostatistical interpolation methods to construct two climate change indices, capturing warm and wet spell duration, based on daily temperature and precipitation readings for 214 weather stations across Mexico. In combination with detailed migration histories obtained from the Mexican Migration Project, we model the influence of climate change on household-level migration from 68 rural and 49 urban municipalities. Results from multilevel event-history models reveal that a temperature warming and excessive precipitation significantly increased international migration during the study period. However, climate change impacts on international migration is only observed for rural areas. Interactions reveal a causal pathway in which temperature (but not precipitation) influences migration patterns through employment in the agricultural sector. As such, climate-related international migration may decline with continued urbanization and the resulting reductions in direct dependence of households on rural agriculture.
Deliberation as Communication Instruction: A Study of a Climate Change Deliberation in an Introductory Biology Course

ERIC Educational Resources Information Center

Drury, Sara A. Mehltretter

2015-01-01

The author argues that deliberation is an innovative method for teaching communication skills, particularly group communication, in the undergraduate science, technology, engineering, and math (STEM) curriculum. A case study using a deliberation activity on global climate change in an introductory biology course demonstrates how deliberative…
Developing a model for effects of climate change on human health and health-environment interactions: Heat stress in Austin, Texas

EPA Science Inventory

Background/Question/Methods In December, 2010, a consortium of EPA, Centers for Disease Control, and state and local health officials convened in Austin, Texas for a “participatory modeling workshop” on climate change effects on human health and health-environment interactions. ...
A method for estimating vulnerability of Douglas-fir growth to climate change in the Northwestern U.S.

Treesearch

J.S. Littell; D.L. Peterson

2005-01-01

Borrowing from landscape ecology, atmospheric science, and integrated assessment, we aim to understand the complex interactions that determine productivity in montane forests and utilize such relationships to forecast montane forest vulnerability under global climate change. Specifically, we identify relationships for precipitation and temperature that govern the...
Remediating Misconception on Climate Change among Secondary School Students in Malaysia

ERIC Educational Resources Information Center

Karpudewan, Mageswary; Roth, Wolff-Michael; Chandrakesan, Kasturi

2015-01-01

Existing studies report on secondary school students' misconceptions related to climate change; they also report on the methods of teaching as reinforcing misconceptions. This quasi-experimental study was designed to test the null hypothesis that a curriculum based on constructivist principles does not lead to greater understanding and fewer…

Maintaining forest diversity in a changing climate: A geophysical approach

Treesearch

Mark Anderson; Nels Johnson; Scott Bearer

2014-01-01

Forest conservationists need a method to conserve the maximum amount of biological diversity while allowing species and communities to rearrange in response to a continually changing climate. Here, we develop such an approach for northeastern North America. First we characterize and categorize forest blocks based on their geology, landforms, and elevation zones. Next,...
Developing a model for effects of climate change on human health and health-environment interactions: Heat stress in Austin, Texas presentation

EPA Science Inventory

Background/Question/Methods In December, 2010, a consortium of EPA, Centers for Disease Control, and state and local health officials convened in Austin, Texas for a “participatory modeling workshop” on climate change effects on human health and health-environment int...
The Urban Climate Change Research Network (UCCRN) Second Assessment Report on Climate Change and Cities (ARC3-2), and the UCCRN Hubs

NASA Astrophysics Data System (ADS)

Rosenzweig, C.; Ali Ibrahim, S.

2015-12-01

The objective of this session is to foster a dialogue between experts working on global-scale, climate change and cities assessments in order to simultaneously present state-of-the-art knowledge on how cities are responding to climate change and to define emerging opportunities and challenges to the effective placement of this knowledge in the hands of local stakeholders and decision-makers. We will present the UCCRN and the Second UCCRN Assessment Report on Climate Change and Cities (ARC3-2), the second in an ongoing series of global, interdisciplinary, cross-regional, science-based assessments to address climate risks, adaptation, mitigation, and policy mechanisms relevant to cities. This is an especially important time to examine these issues. Cities continue to act as world leaders in climate action. Several major climate change assessment efforts are in full swing, at a crucial stage where significant opportunities for the co-production of knowledge between researchers and stakeholders exist. The IPCC AR5 Working Group II and III Reports have placed unprecedented attention on cities and urbanization and their connection to the issue of climate change. Concurrently several major, explicitly city-focused efforts have emerged from the Urban Climate Change Research Network (UCCRN), ICLEI, the Durban Adaptation Charter (DAC), C40, Future Earth, and the Urbanization and Global Environmental Change (UGEC) Project, among others. The underlying rationale for the discussion will be to identify methods and approaches to further foster the development and dissemination of new climate change knowledge and information that will be useful for cities, especially in small and medium-sized cities and in the developing country context where the demand is particularly acute. Participants will leave this session with: · The latest scientific data and state-of-the-knowledge on how cities are responding to climate change · Emerging opportunities and challenges to the effective placement of this knowledge in the hands of local stakeholders and decision-makers and for urban resilience and adaptation action · How practitioner-scientist interactions can work best · Synergies between the IPCC, ARC3, and other climate and cities assessments
Development of the virtual research environment for analysis, evaluation and prediction of global climate change impacts on the regional environment

NASA Astrophysics Data System (ADS)

Okladnikov, Igor; Gordov, Evgeny; Titov, Alexander; Fazliev, Alexander

2017-04-01

Description and the first results of the Russian Science Foundation project "Virtual computational information environment for analysis, evaluation and prediction of the impacts of global climate change on the environment and climate of a selected region" is presented. The project is aimed at development of an Internet-accessible computation and information environment providing unskilled in numerical modelling and software design specialists, decision-makers and stakeholders with reliable and easy-used tools for in-depth statistical analysis of climatic characteristics, and instruments for detailed analysis, assessment and prediction of impacts of global climate change on the environment and climate of the targeted region. In the framework of the project, approaches of "cloud" processing and analysis of large geospatial datasets will be developed on the technical platform of the Russian leading institution involved in research of climate change and its consequences. Anticipated results will create a pathway for development and deployment of thematic international virtual research laboratory focused on interdisciplinary environmental studies. VRE under development will comprise best features and functionality of earlier developed information and computing system CLIMATE (http://climate.scert.ru/), which is widely used in Northern Eurasia environment studies. The Project includes several major directions of research listed below. 1. Preparation of geo-referenced data sets, describing the dynamics of the current and possible future climate and environmental changes in detail. 2. Improvement of methods of analysis of climate change. 3. Enhancing the functionality of the VRE prototype in order to create a convenient and reliable tool for the study of regional social, economic and political consequences of climate change. 4. Using the output of the first three tasks, compilation of the VRE prototype, its validation, preparation of applicable detailed description of climate change in Western Siberia, and dissemination of the Project results. Results of the first stage of the Project implementation are presented. This work is supported by the Russian Science Foundation grant No16-19-10257.
Impacts of land cover changes on climate trends in Jiangxi province China.

PubMed

Wang, Qi; Riemann, Dirk; Vogt, Steffen; Glaser, Rüdiger

2014-07-01

Land-use/land-cover (LULC) change is an important climatic force, and is also affected by climate change. In the present study, we aimed to assess the regional scale impact of LULC on climate change using Jiangxi Province, China, as a case study. To obtain reliable climate trends, we applied the standard normal homogeneity test (SNHT) to surface air temperature and precipitation data for the period 1951-1999. We also compared the temperature trends computed from Global Historical Climatology Network (GHCN) datasets and from our analysis. To examine the regional impacts of land surface types on surface air temperature and precipitation change integrating regional topography, we used the observation minus reanalysis (OMR) method. Precipitation series were found to be homogeneous. Comparison of GHCN and our analysis on adjusted temperatures indicated that the resulting climate trends varied slightly from dataset to dataset. OMR trends associated with surface vegetation types revealed a strong surface warming response to land barrenness and weak warming response to land greenness. A total of 81.1% of the surface warming over vegetation index areas (0-0.2) was attributed to surface vegetation type change and regional topography. The contribution of surface vegetation type change decreases as land cover greenness increases. The OMR precipitation trend has a weak dependence on surface vegetation type change. We suggest that LULC integrating regional topography should be considered as a force in regional climate modeling.
Simulation of growth of Adirondack conifers in relation to global climate change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pan, Y.; Raynal, D.J.

1993-06-01

Several conifer species grown in plantations in the southeastern Adirondack mountains of New York were chosen to model tree growth. In the models, annual xylem growth was decomposed into several components that reflect various intrinsic or extrinsic factors. Growth signals indicative of climatic effects were used to construct response functions using both multivariate analysis and Kalman filter methods. Two models were used to simulate tree growth response to future CO[sub 2]-induced climate change projected by GCMs. The comparable results of both models indicate that different conifer species have individualistic growth responses to future climatic change. The response behaviors of treesmore » are affected greatly by local stand conditions. The results suggest possible changes in future growth and distributions of naturally occurring conifers in this region.« less
To frame is to explain: a deductive frame-analysis of Dutch and French climate change coverage during the annual UN Conferences of the Parties.

PubMed

Dirikx, Astrid; Gelders, Dave

2010-11-01

This study examines the way Dutch and French newspapers frame climate change during the annual United Nations Conferences of the Parties. The methods used in previous studies on the framing of climate change do not allow for general cross-national comparisons. We conduct a quantitative deductive framing analysis on 257 quality Dutch and French newspaper articles between 2001 and 2007. Both countries' newspapers seem to frame climate change through mainly the same lens. The majority of the articles make reference to the consequences of the (non-)pursuit of a certain course of action and of possible losses and gains (consequences frame). Additionally, many articles mention the need for urgent actions, refer to possible solutions and suggest that governments are responsible for and/or capable of alleviating climate change problems (responsibility frame). Finally, the conflict frame was found to be used less often than the aforementioned frames, but more regularly than the human interest frame.
Climate change and climate variability: personal motivation for adaptation and mitigation

PubMed Central

2011-01-01

Background Global climate change impacts on human and natural systems are predicted to be severe, far reaching, and to affect the most physically and economically vulnerable disproportionately. Society can respond to these threats through two strategies: mitigation and adaptation. Industry, commerce, and government play indispensable roles in these actions but so do individuals, if they are receptive to behavior change. We explored whether the health frame can be used as a context to motivate behavioral reductions of greenhouse gas emissions and adaptation measures. Methods In 2008, we conducted a cross-sectional survey in the United States using random digit dialing. Personal relevance of climate change from health threats was explored with the Health Belief Model (HBM) as a conceptual frame and analyzed through logistic regressions and path analysis. Results Of 771 individuals surveyed, 81% (n = 622) acknowledged that climate change was occurring, and were aware of the associated ecologic and human health risks. Respondents reported reduced energy consumption if they believed climate change could affect their way of life (perceived susceptibility), Odds Ratio (OR) = 2.4 (95% Confidence Interval (CI): 1.4 - 4.0), endanger their life (perceived severity), OR = 1.9 (95% CI: 1.1 - 3.1), or saw serious barriers to protecting themselves from climate change, OR = 2.1 (95% CI: 1.2 - 3.5). Perceived susceptibility had the strongest effect on reduced energy consumption, either directly or indirectly via perceived severity. Those that reported having the necessary information to prepare for climate change impacts were more likely to have an emergency kit OR = 2.1 (95% CI: 1.4 - 3.1) or plan, OR = 2.2 (95% CI: 1.5 -3.2) for their household, but also saw serious barriers to protecting themselves from climate change or climate variability, either by having an emergency kit OR = 1.6 (95% CI: 1.1 - 2.4) or an emergency plan OR = 1.5 (95%CI: 1.0 - 2.2). Conclusions Motivation for voluntary mitigation is mostly dependent on perceived susceptibility to threats and severity of climate change or climate variability impacts, whereas adaptation is largely dependent on the availability of information relevant to climate change. Thus, the climate change discourse could be framed from a health perspective to motivate behaviour change. PMID:21600004
Tailored scenarios for streamflow climate change impacts based on the perturbation of precipitation and evapotranspiration

NASA Astrophysics Data System (ADS)

Ntegeka, Victor; Willems, Patrick; Baguis, Pierre; Roulin, Emmanuel

2015-04-01

It is advisable to account for a wide range of uncertainty by including the maximum possible number of climate models and scenarios for future impacts. As this is not always feasible, impact assessments are inevitably performed with a limited set of scenarios. The development of tailored scenarios is a challenge that needs more attention as the number of available climate change simulations grows. Whether these scenarios are representative enough for climate change impacts is a question that needs addressing. This study presents a methodology of constructing tailored scenarios for assessing runoff flows including extreme conditions (peak flows) from an ensemble of future climate change signals of precipitation and potential evapotranspiration (ETo) derived from the climate model simulations. The aim of the tailoring process is to formulate scenarios that can optimally represent the uncertainty spectrum of climate scenarios. These tailored scenarios have the advantage of being few in number as well as having a clear description of the seasonal variation of the climate signals, hence allowing easy interpretation of the implications of future changes. The tailoring process requires an analysis of the hydrological impacts from the likely future change signals from all available climate model simulations in a simplified (computationally less expensive) impact model. Historical precipitation and ETo time series are perturbed with the climate change signals based on a quantile perturbation technique that accounts for the changes in extremes. For precipitation, the change in wetday frequency is taken into account using a markov-chain approach. Resulting hydrological impacts from the perturbed time series are then subdivided into high, mean and low hydrological impacts using a quantile change analysis. From this classification, the corresponding precipitation and ETo change factors are back-tracked on a seasonal basis to determine precipitation-ETo covariation. The established precipitation-ETo covariations are used to inform the scenario construction process. Additionally, the back-tracking of extreme flows from driving scenarios allows for a diagnosis of the physical responses to climate change scenarios. The method is demonstrated through the application of scenarios from 10 Regional Climate Models,21 Global Climate Models and selected catchments in central Belgium. Reference Ntegeka, V., Baguis, P., Roulin, E., & Willems, P. (2014). Developing tailored climate change scenarios for hydrological impact assessments. Journal of Hydrology, 508, 307-321.
Misleading prioritizations from modelling range shifts under climate change

USGS Publications Warehouse

Sofaer, Helen R.; Jarnevich, Catherine S.; Flather, Curtis H.

2018-01-01

AimConservation planning requires the prioritization of a subset of taxa and geographical locations to focus monitoring and management efforts. Integration of the threats and opportunities posed by climate change often relies on predictions from species distribution models, particularly for assessments of vulnerability or invasion risk for multiple taxa. We evaluated whether species distribution models could reliably rank changes in species range size under climate and land use change.LocationConterminous U.S.A.Time period1977–2014.Major taxa studiedPasserine birds.MethodsWe estimated ensembles of species distribution models based on historical North American Breeding Bird Survey occurrences for 190 songbirds, and generated predictions to recent years given c. 35 years of observed land use and climate change. We evaluated model predictions using standard metrics of discrimination performance and a more detailed assessment of the ability of models to rank species vulnerability to climate change based on predicted range loss, range gain, and overall change in range size.ResultsSpecies distribution models yielded unreliable and misleading assessments of relative vulnerability to climate and land use change. Models could not accurately predict range expansion or contraction, and therefore failed to anticipate patterns of range change among species. These failures occurred despite excellent overall discrimination ability and transferability to the validation time period, which reflected strong performance at the majority of locations that were either always or never occupied by each species.Main conclusionsModels failed for the questions and at the locations of greatest interest to conservation and management. This highlights potential pitfalls of multi-taxa impact assessments under global change; in our case, models provided misleading rankings of the most impacted species, and spatial information about range changes was not credible. As modelling methods and frameworks continue to be refined, performance assessments and validation efforts should focus on the measures of risk and vulnerability useful for decision-making.
Quantifying the Value of Downscaled Climate Model Information for Adaptation Decisions: When is Downscaling a Smart Decision?

NASA Astrophysics Data System (ADS)

Terando, A. J.; Wootten, A.; Eaton, M. J.; Runge, M. C.; Littell, J. S.; Bryan, A. M.; Carter, S. L.

2015-12-01

Two types of decisions face society with respect to anthropogenic climate change: (1) whether to enact a global greenhouse gas abatement policy, and (2) how to adapt to the local consequences of current and future climatic changes. The practice of downscaling global climate models (GCMs) is often used to address (2) because GCMs do not resolve key features that will mediate global climate change at the local scale. In response, the development of downscaling techniques and models has accelerated to aid decision makers seeking adaptation guidance. However, quantifiable estimates of the value of information are difficult to obtain, particularly in decision contexts characterized by deep uncertainty and low system-controllability. Here we demonstrate a method to quantify the additional value that decision makers could expect if research investments are directed towards developing new downscaled climate projections. As a proof of concept we focus on a real-world management problem: whether to undertake assisted migration for an endangered tropical avian species. We also take advantage of recently published multivariate methods that account for three vexing issues in climate impacts modeling: maximizing climate model quality information, accounting for model dependence in ensembles of opportunity, and deriving probabilistic projections. We expand on these global methods by including regional (Caribbean Basin) and local (Puerto Rico) domains. In the local domain, we test whether a high resolution (2km) dynamically downscaled GCM reduces the multivariate error estimate compared to the original coarse-scale GCM. Initial tests show little difference between the downscaled and original GCM multivariate error. When propagated through to a species population model, the Value of Information analysis indicates that the expected utility that would accrue to the manager (and species) if this downscaling were completed may not justify the cost compared to alternative actions.
Climate Projection Data base for Roads - CliPDaR: Design a guideline for a transnational database of downscaled climate projection data for road impact models - within the Conference's of European Directors of Roads (CEDR) TRANSNATIONAL ROAD RESEARCH PROG

NASA Astrophysics Data System (ADS)

Matulla, Christoph; Namyslo, Joachim; Fuchs, Tobias; Türk, Konrad

2013-04-01

The European road sector is vulnerable to extreme weather phenomena, which can cause large socio-economic losses. Almost every year there occur several weather triggered events (like heavy precipitation, floods, landslides, high winds, snow and ice, heat or cold waves, etc.), that disrupt transportation, knock out power lines, cut off populated regions from the outside and so on. So, in order to avoid imbalances in the supply of vital goods to people as well as to prevent negative impacts on health and life of people travelling by car it is essential to know present and future threats to roads. Climate change might increase future threats to roads. CliPDaR focuses on parts of the European road network and contributes, based on the current body of knowledge, to the establishment of guidelines helping to decide which methods and scenarios to apply for the estimation of future climate change based challenges in the field of road maintenance. Based on regional scale climate change projections specific road-impact models are applied in order to support protection measures. In recent years, it has been recognised that it is essential to assess the uncertainty and reliability of given climate projections by using ensemble approaches and downscaling methods. A huge amount of scientific work has been done to evaluate these approaches with regard to reliability and usefulness for investigations on possible impacts of climate changes. CliPDaR is going to collect the existing approaches and methodologies in European countries, discuss their differences and - in close cooperation with the road owners - develops a common line on future applications of climate projection data to road impact models. As such, the project will focus on reviewing and assessing existing regional climate change projections regarding transnational highway transport needs. The final project report will include recommendations how the findings of CliPDaR may support the decision processes of European national road administrations regarding possible future climate change impacts. First project results are presented at the conference.
75 FR 54403 - U.S. National Climate Assessment Objectives, Proposed Topics, and Next Steps

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-07

..., methods and design, tools for assessing climate change and impacts, dealing with uncertainty, sources of..., coordination with other Federal climate-related programs, design of documents and tailored communications with... methodological perspectives related to selecting model and downscaling outputs and approaches for their use in...
Projections of suitable habitat for rare species under global warming scenarios

Treesearch

F. Thomas Ledig; Gerald E. Rehfeldt; Cuauhtemoc Saenz-Romero; Flores-Lopez Celestino

2010-01-01

Premise of the study: Modeling the contemporary and future climate niche for rare plants is a major hurdle in conservation, yet such projections are necessary to prevent extinctions that may result from climate change. Methods: We used recently developed spline climatic models and modifi ed Random Forests...
Hampton Roads climate impact quantification initiative : baseline assessment of the transportation assets & overview of economic analyses useful in quantifying impacts

DOT National Transportation Integrated Search

2016-09-13

The Hampton Roads Climate Impact Quantification Initiative (HRCIQI) is a multi-part study sponsored by the U.S. Department of Transportation (DOT) Climate Change Center with the goals that include developing a cost tool that provides methods for volu...
Community-based Participatory Process – Climate Change and Health Adaptation Program for Northern First Nations and Inuit in Canada

PubMed Central

Peace, Diane McClymont; Myers, Erin

2012-01-01

Objectives Health Canada's Program for Climate Change and Health Adaptation in Northern First Nation and Inuit Communities is unique among Canadian federal programs in that it enables community-based participatory research by northern communities. Study design The program was designed to build capacity by funding communities to conduct their own research in cooperation with Aboriginal associations, academics, and governments; that way, communities could develop health-related adaptation plans and communication materials that would help in adaptation decision-making at the community, regional, national and circumpolar levels with respect to human health and a changing environment. Methods Community visits and workshops were held to familiarize northerners with the impacts of climate change on their health, as well as methods to develop research proposals and budgets to meet program requirements. Results Since the launch of the Climate Change and Health Adaptation Program in 2008, Health Canada has funded 36 community projects across Canada's North that focus on relevant health issues caused by climate change. In addition, the program supported capacity-building workshops for northerners, as well as a Pan-Arctic Results Workshop to bring communities together to showcase the results of their research. Results include: numerous films and photo-voice products that engage youth and elders and are available on the web; community-based ice monitoring, surveillance and communication networks; and information products on land, water and ice safety, drinking water, food security and safety, and traditional medicine. Conclusions Through these efforts, communities have increased their knowledge and understanding of the health effects related to climate change and have begun to develop local adaptation strategies. PMID:22584509
Climate Change, Hydrology and Landscapes of America's Heartland: A Coupled Natural-Human System

NASA Astrophysics Data System (ADS)

Lant, C.; Misgna, G.; Secchi, S.; Schoof, J. T.

2012-12-01

This paper will present a methodological overview of an NSF-funded project under the Coupled Natural and Human System program. Climate change, coupled with variations and changes in economic and policy environments and agricultural techniques, will alter the landscape of the U.S. Midwest. Assessing the effects of these changes on watersheds, and thus on water quantity, water quality, and agricultural production, entails modeling a coupled natural-human system capable of answering research questions such as: (1) How will the climate of the U.S. Midwest change through the remainder of the 21st Century? (2) How will climate change, together with changing markets and policies, affect land use patterns at various scales, from the U.S. Midwest, to agricultural regions, to watersheds, to farms and fields? (3) Under what policies and prices does landscape change induced by climate change generate a positive or a negative feedback through changes in carbon storage, evapotranspiration, and albedo? (4) Will climate change expand or diminish the agricultural production and ecosystem service generation capacities of specific watersheds? Such research can facilitate early adaptation and make a timely contribution to the successful integration of agricultural, environmental, and trade policy. Rural landscapes behave as a system through a number of feedback mechanisms: climatic, agro-technology, market, and policy. Methods, including agent-based modeling, SWAT modeling, map algebra using logistic regression, and genetic algorithms for analyzing each of these feedback mechanisms will be described. Selected early results that link sub-system models and incorporate critical feedbacks will also be presented.igure 1. Overall Modeling framework for Climate Change, Hydrology and Landscapes of America's Heartland.
Two-Sides of the Same Coin: Communicating Climate Change Science to Water Utilities and Stakeholders in Florida and Hawai'i

NASA Astrophysics Data System (ADS)

Keener, V. W.; Staal, L.

2011-12-01

The NOAA-funded Regional Integrated Sciences and Assessment (RISA) programs act as boundary organizations that both conduct and translate academic climate research in the physical and social sciences for a variety of stakeholder applications, including for local and state governments, natural resource managers, non-climate scientists, and community members. For the past six years, I have worked with two RISAs-one in the southeast United States, and recently in the Pacific region. In confronting the most immediate impacts of climate change, Florida and Hawai'i are both currently dealing with saltwater intrusion effects on infrastructure and water supply, sea level rise impacts on vulnerable coastlines, and expect the problems to worsen in the future. Both RISAs have focused on water resource sustainability as a topic of interest, and held workshops on climate variability and change impacts for water utilities and a wider range of relevant stakeholders. Methods that have been used to communicate climate science, projected impacts, and risk have included: working groups/collaborative learning, scientific presentations and presentations of relevant case studies, beach management planning, in-depth interviews, and educational radio spots. Despite the similarities in the types of issues being confronted, stakeholders in each location have responded with differing levels of acceptance, which has resulted in the usage of different methods of communication of the same types of climate science information. This talk will focus on the success of a variety of different methods in communicating similar information on comparable risks to different audiences.
Climate and tourism in the Black Forest during the warm season.

PubMed

Endler, Christina; Matzarakis, Andreas

2011-03-01

Climate, climate change and tourism all interact. Part of the public discussion about climate change focusses on the tourism sector, with direct and indirect impacts being of equally high relevance. Climate and tourism are closely linked. Thus, climate is a very decisive factor in choices both of destination and of type of journey (active holidays, wellness, and city tours) in the tourism sector. However, whether choices about destinations or types of trip will alter with climate change is difficult to predict. Future climates can be simulated and projected, and the tendencies of climate parameters can be estimated using global and regional climate models. In this paper, the focus is on climate change in the mountainous regions of southwest Germany - the Black Forest. The Black Forest is one of the low mountain ranges where both winter and summer tourism are vulnerable to climate change due to its southern location; the strongest climatic changes are expected in areas covering the south and southwest of Germany. Moreover, as the choice of destination is highly dependent on good weather, a climatic assessment for tourism is essential. Thus, the aim of this study was to estimate climatic changes in mountainous regions during summer, especially for tourism and recreation. The assessment method was based on human-biometeorology as well as tourism-climatologic approaches. Regional climate simulations based on the regional climate model REMO were used for tourism-related climatic analyses. Emission scenarios A1B and B1 were considered for the time period 2021 to 2050, compared to the 30-year base period of 1971-2000, particularly for the warm period of the year, defined here as the months of March-November. In this study, we quantified the frequency, but not the means, of climate parameters. The study results show that global and regional warming is reflected in an increase in annual mean air temperature, especially in autumn. Changes in the spring show a slight negative trend, which is in line with the trend of a decrease in physiologically equivalent temperature as well as in thermal comfort conditions. Due to the rising air temperature, heat stress as well as sultry conditions are projected to become more frequent, affecting human health and recreation, especially at lower lying altitudes. The tops of the mountains and higher elevated areas still have the advantage of offering comfortable climatic conditions.
Climate change increases the probability of heavy rains in Northern England/Southern Scotland like those of storm Desmond—a real-time event attribution revisited

NASA Astrophysics Data System (ADS)

Otto, Friederike E. L.; van der Wiel, Karin; van Oldenborgh, Geert Jan; Philip, Sjoukje; Kew, Sarah F.; Uhe, Peter; Cullen, Heidi

2018-02-01

On 4-6 December 2015, storm Desmond caused very heavy rainfall in Northern England and Southern Scotland which led to widespread flooding. A week after the event we provided an initial assessment of the influence of anthropogenic climate change on the likelihood of one-day precipitation events averaged over an area encompassing Northern England and Southern Scotland using data and methods available immediately after the event occurred. The analysis was based on three independent methods of extreme event attribution: historical observed trends, coupled climate model simulations and a large ensemble of regional model simulations. All three methods agreed that the effect of climate change was positive, making precipitation events like this about 40% more likely, with a provisional 2.5%-97.5% confidence interval of 5%-80%. Here we revisit the assessment using more station data, an additional monthly event definition, a second global climate model and regional model simulations of winter 2015/16. The overall result of the analysis is similar to the real-time analysis with a best estimate of a 59% increase in event frequency, but a larger confidence interval that does include no change. It is important to highlight that the observational data in the additional monthly analysis does not only represent the rainfall associated with storm Desmond but also that of storms Eve and Frank occurring towards the end of the month.

The Impact of Climate Projection Method on the Analysis of Climate Change in Semi-arid Basins

NASA Astrophysics Data System (ADS)

Halper, E.; Shamir, E.

2016-12-01

In small basins with arid climates, rainfall characteristics are highly variable and stream flow is tightly coupled with the nuances of rainfall events (e.g. hourly precipitation patterns Climate change assessments in these basins typically employ CMIP5 projections downscaled with Bias Corrected Statistical Downscaling and Bias Correction/Constructed Analogs (BCSD-BCCA) methods, but these products have drawbacks. Specifically, BCSD-BCCA these projections do not explicitly account for localized physical precipitation mechanisms (e.g. monsoon and snowfall) that are essential to many hydrological systems in the U. S. Southwest. An investigation of the impact of different types of precipitation projections for two kinds of hydrologic studies is being conducted under the U.S. Bureau of Reclamation's Science and Technology Grant Program. An innovative modeling framework consisting of a weather generator of likely hourly precipitation scenarios, coupled with rainfall-runoff, river routing and groundwater models, has been developed in the Nogales, Arizona area. This framework can simulate the impact of future climate on municipal water operations. This framework allows the rigorous comparison of the BCSD-BCCA methods with alternative approaches including rainfall output from dynamical downscaled Regional Climate Models (RCM), a stochastic rainfall generator forced by either Global Climate Models (GCM) or RCM, and projections using historical records conditioned on either GCM or RCM. The results will provide guide for the use of climate change projections into hydrologic studies of semi-arid areas. The project extends this comparison to analyses of flood control. Large flows on the Bill Williams River are a concern for the operation of dams along the Lower Colorado River. After adapting the weather generator for this region, we will evaluate the model performance for rainfall and stream flow, with emphasis on statistical features important to the specific needs of flood management. The end product of the research is to develop a test to guide selection of a precipitation projection method (including downscaling procedure) for a given region and objective.
The Role of Health in Climate Litigation

PubMed Central

Simmens, Samuel J.; Glicksman, Robert; Paddock, LeRoy; Kim, Daniel; Whited, Brittany

2018-01-01

Objectives. To examine how the courts, which play a critical role in shaping public policy, consider public health in climate change and coal-fired power plant lawsuits. Methods. We coded US local, state, and federal court decisions relating to climate change and coal-fired power plants from 1990 to 2016 (n = 873) and qualitatively investigated 139 cases in which litigants raised issues concerning the health impacts of climate change. We also conducted 78 interviews with key litigants, advocates, industry representatives, advising scientists, and legal experts. Results. Health has been a critical consideration in key climate lawsuits, but in a minority of cases. Litigants have presented health arguments most frequently and effectively in terms of airborne exposures. Health impacts have typically been used to gain standing and argue that the evidence for government actions is insufficient. Conclusions. The courts represent a pivotal branch of government in shaping climate policy. Increasing inclusion of health concerns in emergent areas of litigation could help drive more effective climate policymaking. PMID:29698089
Climate change impact on groundwater levels in the Guarani Aquifer outcrop zone

NASA Astrophysics Data System (ADS)

Melo, D. D.; Wendland, E.

2013-12-01

The unsustainable use of groundwater in many countries might cause water availability restrictions in the future. Such issue is likely to worsen due to predicted climate changes for the incoming decades. As numerous studies suggest, aquifers recharge rates will be affected as a result of climate change. The Guarani Aquifer System (GAS) is one of the most important transboundary aquifer in the world, providing drinkable water for millions of people in four South American countries (Brazil, Argentina, Uruguay and Paraguay). Considering the GAS relevance and how its recharge rates might be altered by climatic conditions anomalies, the objective of this work is to assess possible climate changes impacts on groundwater levels in this aquifer outcrop zone. Global Climate Models' (GCM) outputs were used as inputs in a transient flux groundwater model created using the software SPA (Simulation of Process in Aquifers), enabling groundwater table fluctuation to be evaluated under distinct climatic scenarios. Six monitoring wells, located in a representative basin (Ribeirão da Onça basin) inside a GAS outcrop zone (ROB), provided water table measurements between 2004 and 2011 to calibrate the groundwater model. Using observed climatic data, a water budget method was applied to estimate recharge in different types of land uses. Statistically downscaled future climate scenarios were used as inputs for that same recharge model, which provided data for running SPA under those scenarios. The results show that most of the GCMs used here predict temperature arises over 275,15 K and major monthly rainfall mean changes to take place in the dry season. During wet seasons, those means might experience around 50% decrease. The transient model results indicate that water table variations, derived from around 70% of the climate scenarios, would vary below those measured between 2004 and 2011. Among the thirteen GCMs considered in this work, only four of them predicted more extreme climate scenarios. In some regions of the study area and under these extreme conditions, groundwater surface would decline more than 10 m. Although more optimistic scenarios resulted in an increase of groundwater levels in more than half of ROB, these would cause up to 5 m water table decline. The results reinforce the need for a permanent hydrogeological monitoring, mainly in the GAS recharge areas, along with the development of other climate change impacts assessment works using different downscaling and recharge estimates methods.
Changes of reference evapotranspiration in the Haihe River Basin: Present observations and future projection from climatic variables through multi-model ensemble

NASA Astrophysics Data System (ADS)

Xing, Wanqiu; Wang, Weiguang; Shao, Quanxi; Peng, Shizhang; Yu, Zhongbo; Yong, Bin; Taylor, John

2014-04-01

As the most excellent indicator for hydrological cycle and a central link to water-balance calculations, the reference evapotranspiration (ET0) is of increasing importance in assessing the potential impacts of climate change on hydrology and water resources systems since the climate change has been becoming more pronounced. In this study, we conduct an investigation on the spatial and temporal changes in ET0 of the Haihe River Basin in present and future stages. The ET0 in the past five decades (1961-2010) are calculated by the Penman-Monteith method with historical climatic variables in 40 sites while the ET0 estimation for the future period of 2011-2099 is based on the related climatic variables projected by Coupled General Circulation Model (CGCM) multimodel ensemble projections in Phase 3 of the Coupled Model Intercomparison Project (CMIP3) using the Bayesian Model Average (BMA) approach. Results can be summarized for the present and future as follows. (1) No coherent spatial patterns in ET0 changes are seen in the whole basin. Half of the stations distributed mainly in the eastern and southeastern plain regions present significant negative trends, while only 3 stations in the western mountainous and plateau basin show significant positive trends. Radiation is mainly responsible for the ET0 change in the southern and eastern basin, whereas relative humidity and wind speed are the leading factors in the eastern coastal and north parts. (2) BMA ensemble method is competent to produce lower bias in comparison with other common methods in this basin. Future spatiotemporal ET0 pattern analysis by means of the BMA method based on the ensembles of four CGCMs suggested that although the spatial patterns under three scenarios are different in the forthcoming two decades, generally increasing trends can be found in the 21st century, which is mainly attributed to the significant increasing temperature. In addition, the implication of future ET0 change in agriculture and local water resources is discussed as an extension of this work. The results can provide beneficial reference and comprehensive information to understand the impact of climate change on the future water balance and improve the regional strategy for water resource and eco-environment management in the Haihe River Basin.
Mainstreaming Climate Change: Recent and Ongoing Efforts to Understand, Improve, and Expand Consideration of Climate Change in Federal Water Resources Planning

NASA Astrophysics Data System (ADS)

Ferguson, I. M.; McGuire, M.; Broman, D.; Gangopadhyay, S.

2017-12-01

The Bureau of Reclamation is a Federal agency tasked with developing and managing water supply and hydropower projects in the Western U.S. Climate and hydrologic variability and change significantly impact management actions and outcomes across Reclamation's programs and initiatives, including water resource planning and operations, infrastructure design and maintenance, hydropower generation, and ecosystem restoration, among others. Planning, design, and implementation of these programs therefore requires consideration of future climate and hydrologic conditions will impact program objectives. Over the past decade, Reclamation and other Federal agencies have adopted new guidelines, directives, and mandates that require consideration of climate change in water resources planning and decision making. Meanwhile, the scientific community has developed a large number of climate projections, along with an array of models, methods, and tools to facilitate consideration of climate projections in planning and decision making. However, water resources engineers, planners, and decision makers continue to face challenges regarding how best to use the available data and tools to support major decisions, including decisions regarding infrastructure investments and long-term operating criteria. This presentation will discuss recent and ongoing research towards understanding, improving, and expanding consideration of climate projections and related uncertainties in Federal water resources planning and decision making. These research efforts address a variety of challenges, including: How to choose between available climate projection datasets and related methods, models, and tools—many of which are considered experimental or research tools? How to select an appropriate decision framework when design or operating alternatives may differ between climate scenarios? How to effectively communicate results of a climate impacts analysis to decision makers? And, how to improve robustness and resilience of water resources systems in the face of significant uncertainty? Discussion will focus on the intersection between technical challenges and decision making paradigms and the need for improved scientist-decision maker engagement through the lens of this Federal water management agency.
Disentangling the effects of climate variability and functional change on ecosystem carbon dynamics using semi-empirical modelling

NASA Astrophysics Data System (ADS)

Wu, J.; van der Linden, L.; Lasslop, G.; Carvalhais, N.; Pilegaard, K.; Beier, C.; Ibrom, A.

2012-04-01

The ecosystem carbon balance is affected by both external climatic forcing (e.g. solar radiation, air temperature and humidity) and internal dynamics in the ecosystem functional properties (e.g. canopy structure, leaf photosynthetic capacity and carbohydrate reserve). In order to understand to what extent and at which temporal scale, climatic variability and functional changes regulated the interannual variation (IAV) in the net ecosystem exchange of CO2 (NEE), data-driven analysis and semi-empirical modelling (Lasslop et al. 2010) were performed based on a 13 year NEE record in a temperate deciduous forest (Pilegaard et al 2011, Wu et al. 2012). We found that the sensitivity of carbon fluxes to climatic variability was significantly higher at shorter than at longer time scales and changed seasonally. This implied that the changing distribution of climate anomalies during the vegetation period could have stronger impacts on future ecosystem carbon balances than changes in average climate. At the annual time scale, approximately 80% of the interannual variability in NEE was attributed to the variation in the model parameters, indicating the observed IAV in the carbon dynamics at the investigated site was dominated by changes in ecosystem functioning. In general this study showed the need for understanding the mechanisms of ecosystem functional change. The method can be applied at other sites to explore ecosystem behavior across different plant functional types and climate gradients. Incorporating ecosystem functional change into process based models will reduce the uncertainties in long-term predictions of ecosystem carbon balances in global climate change projections. Acknowledgements. This work was supported by the EU FP7 project CARBO-Extreme, the DTU Climate Centre and the Danish national project ECOCLIM (Danish Council for Strategic Research).
A Model for Collaborative Learning in Undergraduate Climate Change Courses

NASA Astrophysics Data System (ADS)

Teranes, J. L.

2008-12-01

Like several colleges and universities across the nation, the University of California, San Diego, has introduced climate change topics into many existing and new undergraduate courses. I have administered a program in this area at UCSD and have also developed and taught a new lower-division UCSD course entitled "Climate Change and Society", a general education course for non-majors. This class covers the basics of climate change, such as the science that explains it, the causes of climate change, climate change impacts, and mitigation strategies. The teaching methods for this course stress interdisciplinary approaches. I find that inquiry-based and collaborative modes of learning are particularly effective when applied to science-based climate, environmental and sustainability topics. Undergraduate education is often dominated by a competitive and individualistic approach to learning. In this approach, individual success is frequently perceived as contingent on others being less successful. Such a model is at odds with commonly stated goals of teaching climate change and sustainability, which are to equip students to contribute to the debate on global environmental change and societal adaptation strategies; and to help students become better informed citizens and decision makers. I present classroom-tested strategies for developing collaborative forms of learning in climate change and environmental courses, including team projects, group presentations and group assessment exercises. I show how critical thinking skills and long-term retention of information can benefit in the collaborative mode of learning. I find that a collaborative learning model is especially appropriate to general education courses in which the enrolled student body represents a wide diversity of majors, class level and expertise. I also connect collaborative coursework in interdisciplinary environmental topics directly to applications in the field, where so much "real-world" achievement in research, education, government and business is effectively accomplished in collaborative teams.
The Agriculture Model Intercomparison and Improvement Project (AgMIP) (Invited)

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2010-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation exercise for historical model intercomparison and future climate change conditions with participation of multiple crop and world agricultural trade modeling groups around the world. The goals of AgMIP are to improve substantially the characterization of risk of hunger and world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Historical period results will spur model improvement and interaction among major modeling groups, while future period results will lead directly to tests of adaptation and mitigation strategies across a range of scales. AgMIP will consist of a multi-scale impact assessment utilizing the latest methods for climate and agricultural scenario generation. Scenarios and modeling protocols will be distributed on the web, and multi-model results will be collated and analyzed to ensure the widest possible coverage of agricultural crops and regions. AgMIP will place regional changes in agricultural production in a global context that reflects new trading opportunities, imbalances, and shortages in world markets resulting from climate change and other driving forces for food supply. Such projections are essential inputs from the Vulnerability, Impacts, and Adaptation (VIA) research community to the Intergovernmental Panel on Climate Change Fifth Assessment (AR5), now underway, and the UN Framework Convention on Climate Change. They will set the context for local-scale vulnerability and adaptation studies, supply test scenarios for national-scale development of trade policy instruments, provide critical information on changing supply and demand for water resources, and elucidate interactive effects of climate change and land use change. AgMIP will not only provide crucially-needed new global estimates of how climate change will affect food supply and hunger in the agricultural regions of the world, but it will also build the capabilities of developing countries to estimate how climate change will affect their supply and demand for food.
The impacts of land use, radiative forcing, and biological changes on regional climate in Japan

NASA Astrophysics Data System (ADS)

Dairaku, K.; Pielke, R. A., Sr.

2013-12-01

Because regional responses of surface hydrological and biogeochemical changes are particularly complex, it is necessary to develop assessment tools for regional scale adaptation to climate. We developed a dynamical downscaling method using the regional climate model (NIED-RAMS) over Japan. The NIED-RAMS model includes a plant model that considers biological processes, the General Energy and Mass Transfer Model (GEMTM) which adds spatial resolution to accurately assess critical interactions within the regional climate system for vulnerability assessments to climate change. We digitalized a potential vegetation map that formerly existed only on paper into Geographic Information System data. It quantified information on the reduction of green spaces and the expansion of urban and agricultural areas in Japan. We conducted regional climate sensitivity experiments of land use and land cover (LULC) change, radiative forcing, and biological effects by using the NIED-RAMS with horizontal grid spacing of 20 km. We investigated regional climate responses in Japan for three experimental scenarios: 1. land use and land cover is changed from current to potential vegetation; 2. radiative forcing is changed from 1 x CO2 to 2 x CO2; and 3. biological CO2 partial pressures in plants are doubled. The experiments show good accuracy in reproducing the surface air temperature and precipitation. The experiments indicate the distinct change of hydrological cycles in various aspects due to anthropogenic LULC change, radiative forcing, and biological effects. The relative impacts of those changes are discussed and compared. Acknowledgments This study was conducted as part of the research subject "Vulnerability and Adaptation to Climate Change in Water Hazard Assessed Using Regional Climate Scenarios in the Tokyo Region' (National Research Institute for Earth Science and Disaster Prevention; PI: Koji Dairaku) of Research Program on Climate Change Adaptation (RECCA), and was supported by the SOUSEI Program, funded by Ministry of Education, Culture, Sports, Science and Technology, Government of Japan.
Adapting to the Changing Climate: An Assessment of Local Health Department Preparations for Climate Change-Related Health Threats, 2008-2012

PubMed Central

Roser-Renouf, Connie; Maibach, Edward W.; Li, Jennifer

2016-01-01

Background Climate change poses a major public health threat. A survey of U.S. local health department directors in 2008 found widespread recognition of the threat, but limited adaptive capacity, due to perceived lack of expertise and other resources. Methods We assessed changes between 2008 and 2012 in local public health departments' preparedness for the public health threats of climate change, in light of increasing national polarization on the issue, and widespread funding cutbacks for public health. A geographically representative online survey of directors of local public health departments was conducted in 2011–2012 (N = 174; response rate = 50%), and compared to the 2008 telephone survey results (N = 133; response rate = 61%). Results Significant polarization had occurred: more respondents in 2012 were certain that the threat of local climate change impacts does/does not exist, and fewer were unsure. Roughly 10% said it is not a threat, compared to 1% in 2008. Adaptation capacity decreased in several areas: perceived departmental expertise in climate change risk assessment; departmental prioritization of adaptation; and the number of adaptation-related programs and services departments provided. In 2008, directors' perceptions of local impacts predicted the number of adaptation-related programs and services their departments offered, but in 2012, funding predicted programming and directors' impact perceptions did not. This suggests that budgets were constraining directors' ability to respond to local climate change-related health threats. Results also suggest that departmental expertise may mitigate funding constraints. Strategies for overcoming these obstacles to local public health departments' preparations for climate change are discussed. PMID:26991658
Risk Assessment in Relation to the Effect of Climate Change on Water Shortage in the Taichung Area

NASA Astrophysics Data System (ADS)

Hsiao, J.; Chang, L.; Ho, C.; Niu, M.

2010-12-01

Rapid economic development has stimulated a worldwide greenhouse effect and induced global climate change. Global climate change has increased the range of variation in the quantity of regional river flows between wet and dry seasons, which effects the management of regional water resources. Consequently, the influence of climate change has become an important issue in the management of regional water resources. In this study, the Monte Carlo simulation method was applied to risk analysis of shortage of water supply in the Taichung area. This study proposed a simulation model that integrated three models: weather generator model, surface runoff model, and water distribution model. The proposed model was used to evaluate the efficiency of the current water supply system and the potential effectiveness of two additional plans for water supply: the “artificial lakes” plan and the “cross-basin water transport” plan. A first-order Markov Chain method and two probability distribution models, exponential distribution and normal distribution, were used in the weather generator model. In the surface runoff model, researchers selected the Generalized Watershed Loading Function model (GWLF) to simulate the relationship between quantity of rainfall and basin outflow. A system dynamics model (SD) was applied to the water distribution model. Results of the simulation indicated that climate change could increase the annual quantity of river flow in the Dachia River and Daan River basins. However, climate change could also increase the difference in the quantity of river flow between wet and dry seasons. Simulation results showed that in current system case or in the additional plan cases, shortage status of water for both public and agricultural uses with conditions of climate change will be mostly worse than that without conditions of climate change except for the shortage status for the public use in the current system case. With or without considering the effect of climate change, the additional plans, especially the “cross-basin water transport” plan, for water supply could significantly increase the supply of water for public use. The proposed simulation model and results of analysis in this study could provide valuable reference for decision-makers in regards to risk analysis of regional water supply.
Can metric-based approaches really improve multi-model climate projections? A perfect model framework applied to summer temperature change in France.

NASA Astrophysics Data System (ADS)

Boé, Julien; Terray, Laurent

2014-05-01

Ensemble approaches for climate change projections have become ubiquitous. Because of large model-to-model variations and, generally, lack of rationale for the choice of a particular climate model against others, it is widely accepted that future climate change and its impacts should not be estimated based on a single climate model. Generally, as a default approach, the multi-model ensemble mean (MMEM) is considered to provide the best estimate of climate change signals. The MMEM approach is based on the implicit hypothesis that all the models provide equally credible projections of future climate change. This hypothesis is unlikely to be true and ideally one would want to give more weight to more realistic models. A major issue with this alternative approach lies in the assessment of the relative credibility of future climate projections from different climate models, as they can only be evaluated against present-day observations: which present-day metric(s) should be used to decide which models are "good" and which models are "bad" in the future climate? Once a supposedly informative metric has been found, other issues arise. What is the best statistical method to combine multiple models results taking into account their relative credibility measured by a given metric? How to be sure in the end that the metric-based estimate of future climate change is not in fact less realistic than the MMEM? It is impossible to provide strict answers to those questions in the climate change context. Yet, in this presentation, we propose a methodological approach based on a perfect model framework that could bring some useful elements of answer to the questions previously mentioned. The basic idea is to take a random climate model in the ensemble and treat it as if it were the truth (results of this model, in both past and future climate, are called "synthetic observations"). Then, all the other members from the multi-model ensemble are used to derive thanks to a metric-based approach a posterior estimate of climate change, based on the synthetic observation of the metric. Finally, it is possible to compare the posterior estimate to the synthetic observation of future climate change to evaluate the skill of the method. The main objective of this presentation is to describe and apply this perfect model framework to test different methodological issues associated with non-uniform model weighting and similar metric-based approaches. The methodology presented is general, but will be applied to the specific case of summer temperature change in France, for which previous works have suggested potentially useful metrics associated with soil-atmosphere and cloud-temperature interactions. The relative performances of different simple statistical approaches to combine multiple model results based on metrics will be tested. The impact of ensemble size, observational errors, internal variability, and model similarity will be characterized. The potential improvements associated with metric-based approaches compared to the MMEM is terms of errors and uncertainties will be quantified.
Evaluation of the impacts of climate change on disease vectors through ecological niche modelling.

PubMed

Carvalho, B M; Rangel, E F; Vale, M M

2017-08-01

Vector-borne diseases are exceptionally sensitive to climate change. Predicting vector occurrence in specific regions is a challenge that disease control programs must meet in order to plan and execute control interventions and climate change adaptation measures. Recently, an increasing number of scientific articles have applied ecological niche modelling (ENM) to study medically important insects and ticks. With a myriad of available methods, it is challenging to interpret their results. Here we review the future projections of disease vectors produced by ENM, and assess their trends and limitations. Tropical regions are currently occupied by many vector species; but future projections indicate poleward expansions of suitable climates for their occurrence and, therefore, entomological surveillance must be continuously done in areas projected to become suitable. The most commonly applied methods were the maximum entropy algorithm, generalized linear models, the genetic algorithm for rule set prediction, and discriminant analysis. Lack of consideration of the full-known current distribution of the target species on models with future projections has led to questionable predictions. We conclude that there is no ideal 'gold standard' method to model vector distributions; researchers are encouraged to test different methods for the same data. Such practice is becoming common in the field of ENM, but still lags behind in studies of disease vectors.
Prototype development of user specific climate services

NASA Astrophysics Data System (ADS)

Jacob, Daniela

2017-04-01

Systematic consultations in the last years with representatives from sectors particularly affected by climate change have helped the Climate Service Center Germany (GERICS) to identify the most pressing needs of stakeholders from public and private sectors. Besides the development of innovative climate service products and methods, areas are also identified, for which intensive research activities have to be initiated. An example is the demand of decision makers for high-resolution climate change information needed at regional to local levels for their activities towards climate change adaptation. For questions concerning adaptation to climate change, no standard solutions can be provided. Different from mitigation measures, adaptation measures must be framed in accordance with the specific circumstances prevailing in the local situation. Here, individual solutions, which satisfy the individual requirements and needs, are necessary. They have to be developed in close co-operation with the customers and users. For example, the implications of climate change on strategic and operative decisions, e.g. in enterprises and urban planning, are becoming increasingly important. Therefore, high-quality consultancy for businesses and public administration is needed, in order to support decision makers in identifying associated risks and opportunities. For the development of prototype products, GERICS has framed a general methodological approach, including the idea generation, the iterative development, and the prototype testing in co-development with the user. High process transparency and high product quality are prerequisite for the success of a product. The co-development process ensures the best possible communication of user tailored climate change information for different target groups.
Private land manager capacity to conserve threatened communities under climate change.

PubMed

Raymond, C M; Lechner, A M; Lockwood, M; Carter, O; Harris, R M B; Gilfedder, L

2015-08-15

Major global changes in vegetation community distributions and ecosystem processes are expected as a result of climate change. In agricultural regions with a predominance of private land, biodiversity outcomes will depend on the adaptive capacity of individual land managers, as well as their willingness to engage with conservation programs and actions. Understanding adaptive capacity of landholders is critical for assessing future prospects for biodiversity conservation in privately owned agricultural landscapes globally, given projected climate change. This paper is the first to develop and apply a set of statistical methods (correlation and bionomial regression analyses) for combining social data on land manager adaptive capacity and factors associated with conservation program participation with biophysical data describing the current and projected-future distribution of climate suitable for vegetation communities. We apply these methods to the Tasmanian Midlands region of Tasmania, Australia and discuss the implications of the modelled results on conservation program strategy design in other contexts. We find that the integrated results can be used by environmental management organisations to design community engagement programs, and to tailor their messages to land managers with different capacity types and information behaviours. We encourage environmental agencies to target high capacity land managers by diffusing climate change and grassland management information through well respected conservation NGOs and farm system groups, and engage low capacity land managers via formalized mentoring programs. Copyright © 2015 Elsevier Ltd. All rights reserved.
Building an ensemble of climate scenarios for decision-making in hydrology: benefits, pitfalls and uncertainties

NASA Astrophysics Data System (ADS)

Braun, Marco; Chaumont, Diane

2013-04-01

Using climate model output to explore climate change impacts on hydrology requires several considerations, choices and methods in the post treatment of the datasets. In the effort of producing a comprehensive data base of climate change scenarios for over 300 watersheds in the Canadian province of Québec, a selection of state of the art procedures were applied to an ensemble comprising 87 climate simulations. The climate data ensemble is based on global climate simulations from the Coupled Model Intercomparison Project - Phase 3 (CMIP3) and regional climate simulations from the North American Regional Climate Change Assessment Program (NARCCAP) and operational simulations produced at Ouranos. Information on the response of hydrological systems to changing climate conditions can be derived by linking climate simulations with hydrological models. However, the direct use of raw climate model output variables as drivers for hydrological models is limited by issues such as spatial resolution and the calibration of hydro models with observations. Methods for downscaling and bias correcting the data are required to achieve seamless integration of climate simulations with hydro models. The effects on the results of four different approaches to data post processing were explored and compared. We present the lessons learned from building the largest data base yet for multiple stakeholders in the hydro power and water management sector in Québec putting an emphasis on the benefits and pitfalls in choosing simulations, extracting the data, performing bias corrections and documenting the results. A discussion of the sources and significance of uncertainties in the data will also be included. The climatological data base was subsequently used by the state owned hydro power company Hydro-Québec and the Centre d'expertise hydrique du Québec (CEHQ), the provincial water authority, to simulate future stream flows and analyse the impacts on hydrological indicators. While this submission focuses on the production of climatic scenarios for application in hydrology, the submission « The (cQ)2 project: assessing watershed scale hydrological changes for the province of Québec at the 2050 horizon, a collaborative framework » by Catherine Guay describes how Hydro-Québec and CEHQ put the data into use.
"Climate Matters Documoments": Enabling Regionally-Specific Climate Awareness

NASA Astrophysics Data System (ADS)

Keener, V. W.; Finucane, M.

2012-12-01

The Pacific Regional Integrated Sciences & Assessments (RISA) is a multidisciplinary program that enhances the ability of Pacific Island communities to understand, plan for, and adapt to climate-induced change. Using both social and physical science research methods, the Pacific RISA engages a network of regional decision-makers and stakeholders to help solve climate-related issues. Pacific RISA has a broad audience of local and regional decision-makers (i.e. natural resource managers, community planners, state and federal government agencies) and stakeholders (i.e. farmers and ranchers, fishermen, community and native islander groups). The RISA program engages with this audience through a mixed-method approach of two-way communication, including one-on-one interviews, workshops, consensus discussions and public presentations that allow us to tailor our efforts to the needs of specific stakeholders. A recent Pacific RISA project was the creation and production of four short, educational "documoment" videos that explore the different ways in which climate change in Hawaii affects stakeholders from different sectors. The documoments, generally titled "Climate Matters", start with a quote about why climate matters to each stakeholder: a rancher, a coastal hotel owner, the manager of a landfill, and the local branch of the National Weather Service. The narratives then have each stakeholder discussing how climate impacts their professional and personal lives, and describing the types of climate change they have experienced in the islands. Each video ends with a technical fact about how different climate variables in Hawaii (sea level, precipitation, ENSO) have actually changed within the last century of observational data. Freely available on www.PacificRISA.org, the Documoments have been viewed over 350 times, and have inspired similar video projects and received positive attention from different audiences of stakeholders and scientists. In other assessment work the Pacific RISA has done, we found that many stakeholders who regularly make climate sensitive decisions do not always realize it. By viewing videos like the Climate Matters Documoments, it may help a wide variety of community stakeholders and natural resource decision makers realize the myriad ways in which climate change affects their communities and jobs. In addition, when viewed outside of the Pacific Islands region, the different stories told in the Documoments help foster a greater understanding of the unique climate-related issues faced within the Hawaiian Islands.
Differentiating climate- and human-induced drivers of grassland degradation in the Liao River Basin, China.

PubMed

He, Chunyang; Tian, Jie; Gao, Bin; Zhao, Yuanyuan

2015-01-01

Quantitatively distinguishing grassland degradation due to climatic variations from that due to human activities is of great significance to effectively governing degraded grassland and realizing sustainable utilization. The objective of this study was to differentiate these two types of drivers in the Liao River Basin during 1999-2009 using the residual trend (RESTREND) method and to evaluate the applicability of the method in semiarid and semihumid regions. The relationship between the normalized difference vegetation index (NDVI) and each climatic factor was first determined. Then, the primary driver of grassland degradation was identified by calculating the change trend of the normalized residuals between the observed and the predicted NDVI assuming that climate change was the only driver. We found that the RESTREND method can be used to quantitatively and effectively differentiate climate and human drivers of grassland degradation. We also found that the grassland degradation in the Liao River Basin was driven by both natural processes and human activities. The driving factors of grassland degradation varied greatly across the study area, which included regions having different precipitation and altitude. The degradation in the Horqin Sandy Land, with lower altitude, was driven mainly by human activities, whereas that in the Kungl Prairie, with higher altitude and lower precipitation, was caused primarily by climate change. Therefore, the drivers of degradation and local conditions should be considered in an appropriate strategy for grassland management to promote the sustainability of grasslands in the Liao River Basin.
A Vulnerability Assessment of Fish and Invertebrates to Climate Change on the Northeast U.S. Continental Shelf.

PubMed

Hare, Jonathan A; Morrison, Wendy E; Nelson, Mark W; Stachura, Megan M; Teeters, Eric J; Griffis, Roger B; Alexander, Michael A; Scott, James D; Alade, Larry; Bell, Richard J; Chute, Antonie S; Curti, Kiersten L; Curtis, Tobey H; Kircheis, Daniel; Kocik, John F; Lucey, Sean M; McCandless, Camilla T; Milke, Lisa M; Richardson, David E; Robillard, Eric; Walsh, Harvey J; McManus, M Conor; Marancik, Katrin E; Griswold, Carolyn A

2016-01-01

Climate change and decadal variability are impacting marine fish and invertebrate species worldwide and these impacts will continue for the foreseeable future. Quantitative approaches have been developed to examine climate impacts on productivity, abundance, and distribution of various marine fish and invertebrate species. However, it is difficult to apply these approaches to large numbers of species owing to the lack of mechanistic understanding sufficient for quantitative analyses, as well as the lack of scientific infrastructure to support these more detailed studies. Vulnerability assessments provide a framework for evaluating climate impacts over a broad range of species with existing information. These methods combine the exposure of a species to a stressor (climate change and decadal variability) and the sensitivity of species to the stressor. These two components are then combined to estimate an overall vulnerability. Quantitative data are used when available, but qualitative information and expert opinion are used when quantitative data is lacking. Here we conduct a climate vulnerability assessment on 82 fish and invertebrate species in the Northeast U.S. Shelf including exploited, forage, and protected species. We define climate vulnerability as the extent to which abundance or productivity of a species in the region could be impacted by climate change and decadal variability. We find that the overall climate vulnerability is high to very high for approximately half the species assessed; diadromous and benthic invertebrate species exhibit the greatest vulnerability. In addition, the majority of species included in the assessment have a high potential for a change in distribution in response to projected changes in climate. Negative effects of climate change are expected for approximately half of the species assessed, but some species are expected to be positively affected (e.g., increase in productivity or move into the region). These results will inform research and management activities related to understanding and adapting marine fisheries management and conservation to climate change and decadal variability.
A Vulnerability Assessment of Fish and Invertebrates to Climate Change on the Northeast U.S. Continental Shelf

PubMed Central

Hare, Jonathan A.; Morrison, Wendy E.; Nelson, Mark W.; Stachura, Megan M.; Teeters, Eric J.; Griffis, Roger B.; Alexander, Michael A.; Scott, James D.; Alade, Larry; Bell, Richard J.; Chute, Antonie S.; Curti, Kiersten L.; Curtis, Tobey H.; Kircheis, Daniel; Kocik, John F.; Lucey, Sean M.; McCandless, Camilla T.; Milke, Lisa M.; Richardson, David E.; Robillard, Eric; Walsh, Harvey J.; McManus, M. Conor; Marancik, Katrin E.; Griswold, Carolyn A.

2016-01-01

Climate change and decadal variability are impacting marine fish and invertebrate species worldwide and these impacts will continue for the foreseeable future. Quantitative approaches have been developed to examine climate impacts on productivity, abundance, and distribution of various marine fish and invertebrate species. However, it is difficult to apply these approaches to large numbers of species owing to the lack of mechanistic understanding sufficient for quantitative analyses, as well as the lack of scientific infrastructure to support these more detailed studies. Vulnerability assessments provide a framework for evaluating climate impacts over a broad range of species with existing information. These methods combine the exposure of a species to a stressor (climate change and decadal variability) and the sensitivity of species to the stressor. These two components are then combined to estimate an overall vulnerability. Quantitative data are used when available, but qualitative information and expert opinion are used when quantitative data is lacking. Here we conduct a climate vulnerability assessment on 82 fish and invertebrate species in the Northeast U.S. Shelf including exploited, forage, and protected species. We define climate vulnerability as the extent to which abundance or productivity of a species in the region could be impacted by climate change and decadal variability. We find that the overall climate vulnerability is high to very high for approximately half the species assessed; diadromous and benthic invertebrate species exhibit the greatest vulnerability. In addition, the majority of species included in the assessment have a high potential for a change in distribution in response to projected changes in climate. Negative effects of climate change are expected for approximately half of the species assessed, but some species are expected to be positively affected (e.g., increase in productivity or move into the region). These results will inform research and management activities related to understanding and adapting marine fisheries management and conservation to climate change and decadal variability. PMID:26839967

Validation of catchment models for predicting land-use and climate change impacts. 1. Method

NASA Astrophysics Data System (ADS)

Ewen, J.; Parkin, G.

1996-02-01

Computer simulation models are increasingly being proposed as tools capable of giving water resource managers accurate predictions of the impact of changes in land-use and climate. Previous validation testing of catchment models is reviewed, and it is concluded that the methods used do not clearly test a model's fitness for such a purpose. A new generally applicable method is proposed. This involves the direct testing of fitness for purpose, uses established scientific techniques, and may be implemented within a quality assured programme of work. The new method is applied in Part 2 of this study (Parkin et al., J. Hydrol., 175:595-613, 1996).
The use of climate information to estimate future mortality from high ambient temperature: A systematic literature review

PubMed Central

Arbuthnott, Katherine; Kovats, Sari; Hajat, Shakoor; Falloon, Pete

2017-01-01

Background and objectives Heat related mortality is of great concern for public health, and estimates of future mortality under a warming climate are important for planning of resources and possible adaptation measures. Papers providing projections of future heat-related mortality were critically reviewed with a focus on the use of climate model data. Some best practice guidelines are proposed for future research. Methods The electronic databases Web of Science and PubMed/Medline were searched for papers containing a quantitative estimate of future heat-related mortality. The search was limited to papers published in English in peer-reviewed journals up to the end of March 2017. Reference lists of relevant papers and the citing literature were also examined. The wide range of locations studied and climate data used prevented a meta-analysis. Results A total of 608 articles were identified after removal of duplicate entries, of which 63 were found to contain a quantitative estimate of future mortality from hot days or heat waves. A wide range of mortality models and climate model data have been used to estimate future mortality. Temperatures in the climate simulations used in these studies were projected to increase. Consequently, all the papers indicated that mortality from high temperatures would increase under a warming climate. The spread in projections of future climate by models adds substantial uncertainty to estimates of future heat-related mortality. However, many studies either did not consider this source of uncertainty, or only used results from a small number of climate models. Other studies showed that uncertainty from changes in populations and demographics, and the methods for adaptation to warmer temperatures were at least as important as climate model uncertainty. Some inconsistencies in the use of climate data (for example, using global mean temperature changes instead of changes for specific locations) and interpretation of the effects on mortality were apparent. Some factors which have not been considered when estimating future mortality are summarised. Conclusions Most studies have used climate data generated using scenarios with medium and high emissions of greenhouse gases. More estimates of future mortality using climate information from the mitigation scenario RCP2.6 are needed, as this scenario is the only one under which the Paris Agreement to limit global warming to 2°C or less could be realised. Many of the methods used to combine modelled data with local climate observations are simplistic. Quantile-based methods might offer an improved approach, especially for temperatures at the ends of the distributions. The modelling of adaptation to warmer temperatures in mortality models is generally arbitrary and simplistic, and more research is needed to better quantify adaptation. Only a small number of studies included possible changes in population and demographics in their estimates of future mortality, meaning many estimates of mortality could be biased low. Uncertainty originating from establishing a mortality baseline, climate projections, adaptation and population changes is important and should be considered when estimating future mortality. PMID:28686743
Multi-model approach to assess the impact of climate change on runoff

NASA Astrophysics Data System (ADS)

Dams, J.; Nossent, J.; Senbeta, T. B.; Willems, P.; Batelaan, O.

2015-10-01

The assessment of climate change impacts on hydrology is subject to uncertainties related to the climate change scenarios, stochastic uncertainties of the hydrological model and structural uncertainties of the hydrological model. This paper focuses on the contribution of structural uncertainty of hydrological models to the overall uncertainty of the climate change impact assessment. To quantify the structural uncertainty of hydrological models, four physically based hydrological models (SWAT, PRMS and a semi- and fully distributed version of the WetSpa model) are set up for a catchment in Belgium. Each model is calibrated using four different objective functions. Three climate change scenarios with a high, mean and low hydrological impact are statistically perturbed from a large ensemble of climate change scenarios and are used to force the hydrological models. This methodology allows assessing and comparing the uncertainty introduced by the climate change scenarios with the uncertainty introduced by the hydrological model structure. Results show that the hydrological model structure introduces a large uncertainty on both the average monthly discharge and the extreme peak and low flow predictions under the climate change scenarios. For the low impact climate change scenario, the uncertainty range of the mean monthly runoff is comparable to the range of these runoff values in the reference period. However, for the mean and high impact scenarios, this range is significantly larger. The uncertainty introduced by the climate change scenarios is larger than the uncertainty due to the hydrological model structure for the low and mean hydrological impact scenarios, but the reverse is true for the high impact climate change scenario. The mean and high impact scenarios project increasing peak discharges, while the low impact scenario projects increasing peak discharges only for peak events with return periods larger than 1.6 years. All models suggest for all scenarios a decrease of the lowest flows, except for the SWAT model with the mean hydrological impact climate change scenario. The results of this study indicate that besides the uncertainty introduced by the climate change scenarios also the hydrological model structure uncertainty should be taken into account in the assessment of climate change impacts on hydrology. To make it more straightforward and transparent to include model structural uncertainty in hydrological impact studies, there is a need for hydrological modelling tools that allow flexible structures and methods to validate model structures in their ability to assess impacts under unobserved future climatic conditions.
Time-varying Concurrent Risk of Extreme Droughts and Heatwaves in California

NASA Astrophysics Data System (ADS)

Sarhadi, A.; Diffenbaugh, N. S.; Ausin, M. C.

2016-12-01

Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena such as droughts and heatwaves. The concurrent of these nature-changing climatic extremes may result in intensifying undesirable consequences in terms of human health and destructive effects in water resources. The present study assesses the risk of concurrent extreme droughts and heatwaves under dynamic nonstationary conditions arising from climate change in California. For doing so, a generalized fully Bayesian time-varying multivariate risk framework is proposed evolving through time under dynamic human-induced environment. In this methodology, an extreme, Bayesian, dynamic copula (Gumbel) is developed to model the time-varying dependence structure between the two different climate extremes. The time-varying extreme marginals are previously modeled using a Generalized Extreme Value (GEV) distribution. Bayesian Markov Chain Monte Carlo (MCMC) inference is integrated to estimate parameters of the nonstationary marginals and copula using a Gibbs sampling method. Modelled marginals and copula are then used to develop a fully Bayesian, time-varying joint return period concept for the estimation of concurrent risk. Here we argue that climate change has increased the chance of concurrent droughts and heatwaves over decades in California. It is also demonstrated that a time-varying multivariate perspective should be incorporated to assess realistic concurrent risk of the extremes for water resources planning and management in a changing climate in this area. The proposed generalized methodology can be applied for other stochastic nature-changing compound climate extremes that are under the influence of climate change.
Vulnerability and adaptation to climate-related fire impacts in rural and urban interior Alaska

USGS Publications Warehouse

Trainor, Sarah F.; Calef, Monika; Natcher, David; Chapin, F. Stuart; McGuire, A. David; Huntington, Orville; Duffy, Paul A.; Rupp, T. Scott; DeWilde, La'Ona; Kwart, Mary; Fresco, Nancy; Lovecraft, Amy Lauren

2009-01-01

This paper explores whether fundamental differences exist between urban and rural vulnerability to climate-induced changes in the fire regime of interior Alaska. We further examine how communities and fire managers have responded to these changes and what additional adaptations could be put in place. We engage a variety of social science methods, including demographic analysis, semi-structured interviews, surveys, workshops and observations of public meetings. This work is part of an interdisciplinary study of feedback and interactions between climate, vegetation, fire and human components of the Boreal forest social–ecological system of interior Alaska. We have learned that although urban and rural communities in interior Alaska face similar increased exposure to wildfire as a result of climate change, important differences exist in their sensitivity to these biophysical, climate-induced changes. In particular, reliance on wild foods, delayed suppression response, financial resources and institutional connections vary between urban and rural communities. These differences depend largely on social, economic and institutional factors, and are not necessarily related to biophysical climate impacts per se. Fire management and suppression action motivated by political, economic or other pressures can serve as unintentional or indirect adaptation to climate change. However, this indirect response alone may not sufficiently reduce vulnerability to a changing fire regime. More deliberate and strategic responses may be required, given the magnitude of the expected climate change and the likelihood of an intensification of the fire regime in interior Alaska.
The Use of Statistical Downscaling to Project Regional Climate Changes as they Relate to Future Energy Production

NASA Astrophysics Data System (ADS)

Werth, D. W.; O'Steen, L.; Chen, K.; Altinakar, M. S.; Garrett, A.; Aleman, S.; Ramalingam, V.

2010-12-01

Global climate change has the potential for profound impacts on society, and poses significant challenges to government and industry in the areas of energy security and sustainability. Given that the ability to exploit energy resources often depends on the climate, the possibility of climate change means we cannot simply assume that the untapped potential of today will still exist in the future. Predictions of future climate are generally based on global climate models (GCMs) which, due to computational limitations, are run at spatial resolutions of hundreds of kilometers. While the results from these models can predict climatic trends averaged over large spatial and temporal scales, their ability to describe the effects of atmospheric phenomena that affect weather on regional to local scales is inadequate. We propose the use of several optimized statistical downscaling techniques that can infer climate change at the local scale from coarse resolution GCM predictions, and apply the results to assess future sustainability for two sources of energy production dependent on adequate water resources: nuclear power (through the dissipation of waste heat from cooling towers, ponds, etc.) and hydroelectric power. All methods will be trained with 20th century data, and applied to data from the years 2040-2049 to get the local-scale changes. Models of cooling tower operation and hydropower potential will then use the downscaled data to predict the possible changes in energy production, and the implications of climate change on plant siting, design, and contribution to the future energy grid can then be examined.
Climate change impact on growing degree day accumulation values

NASA Astrophysics Data System (ADS)

Bekere, Liga; Sile, Tija; Bethers, Uldis; Sennikovs, Juris

2015-04-01

A well-known and often used method to assess and forecast plant growth cycle is the growing degree day (GDD) method with different formulas used for accumulation calculations. With this method the only factor that affects plant development is temperature. So with climate change and therefore also change in temperature the typical times of plant blooming or harvest can be expected to change. The goal of this study is to assess this change in the Northern Europe region. As an example strawberry bloom and harvest times are used. As the first part of this study it was required to define the current GDD amounts required for strawberry bloom and harvest. It was done using temperature data from the Danish Meteorological Institute's (DMI) NWP model HIRLAM for the years 2010-2012 and general strawberry growth observations in Latvia. This way we acquired an example amount of GDD required for strawberry blooming and harvest. To assess change in the plant growth cycle we used regional climate models (RCM) - Euro-CORDEX. RCM temperature data for both past and future periods was analyzed and bias correction was carried out. Then the GDD calculation methodology was applied on corrected temperature data and results showing change in strawberry growth cycle - bloom and harvest times - in Northern Europe were visualized.
Sensitivity of worst-case strom surge considering influence of climate change

NASA Astrophysics Data System (ADS)

Takayabu, Izuru; Hibino, Kenshi; Sasaki, Hidetaka; Shiogama, Hideo; Mori, Nobuhito; Shibutani, Yoko; Takemi, Tetsuya

2016-04-01

There are two standpoints when assessing risk caused by climate change. One is how to prevent disaster. For this purpose, we get probabilistic information of meteorological elements, from enough number of ensemble simulations. Another one is to consider disaster mitigation. For this purpose, we have to use very high resolution sophisticated model to represent a worst case event in detail. If we could use enough computer resources to drive many ensemble runs with very high resolution model, we can handle these all themes in one time. However resources are unfortunately limited in most cases, and we have to select the resolution or the number of simulations if we design the experiment. Applying PGWD (Pseudo Global Warming Downscaling) method is one solution to analyze a worst case event in detail. Here we introduce an example to find climate change influence on the worst case storm-surge, by applying PGWD to a super typhoon Haiyan (Takayabu et al, 2015). 1 km grid WRF model could represent both the intensity and structure of a super typhoon. By adopting PGWD method, we can only estimate the influence of climate change on the development process of the Typhoon. Instead, the changes in genesis could not be estimated. Finally, we drove SU-WAT model (which includes shallow water equation model) to get the signal of storm surge height. The result indicates that the height of the storm surge increased up to 20% owing to these 150 years climate change.
Applying network theory to prioritize multispecies habitat networks that are robust to climate and land-use change.

PubMed

Albert, Cécile H; Rayfield, Bronwyn; Dumitru, Maria; Gonzalez, Andrew

2017-12-01

Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land-use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we developed a method to integrate uncertainty in climate and land-use change projections with the latest developments in network-connectivity research and spatial, multipurpose conservation prioritization. We used land-use change simulations to explore robustness of species' habitat networks to alternative development scenarios. We applied our method to 14 vertebrate focal species of periurban Montreal, Canada. Accounting for connectivity in spatial prioritization strongly modified conservation priorities and the modified priorities were robust to uncertain climate change. Setting conservation priorities based on habitat quality and connectivity maintained a large proportion of the region's connectivity, despite anticipated habitat loss due to climate and land-use change. The application of connectivity criteria alongside habitat-quality criteria for protected-area design was efficient with respect to the amount of area that needs protection and did not necessarily amplify trade-offs among conservation criteria. Our approach and results are being applied in and around Montreal and are well suited to the design of ecological networks and green infrastructure for the conservation of biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low. © 2017 Society for Conservation Biology.
Responses to salinity in invasive cordgrass hybrids and their parental species (Spartina) in a scenario of sea level rise and climate change

USDA-ARS?s Scientific Manuscript database

Background/Question/Methods: Salinity is one of the main abiotic factors in salt marshes. Studies rooted to analyzed salinity tolerance of halophytes may help to relate their physiological tolerances with distribution limits in the field. Climate change-induced sea level rise and higher temperatures...
Teaching Anthropogenic Climate Change through Interdisciplinary Collaboration: Helping Students Think Critically about Science and Ethics in Dialogue

ERIC Educational Resources Information Center

Todd, Claire; O'Brien, Kevin J.

2016-01-01

Anthropogenic climate change is a complicated issue involving scientific data and analyses as well as political, economic, and ethical issues. In order to capture this complexity, we developed an interdisciplinary student and faculty collaboration by (1) offering introductory lectures on scientific and ethical methods to two classes, (2) assigning…
Case Study 3: Species vulnerability assessment for the Middle Rio Grande, New Mexico

Treesearch

Deborah M. Finch; Megan Friggens; Karen Bagne

2011-01-01

This case study describes a method for scoring terrestrial species that have potential to be vulnerable to climate change. The assessment tool seeks to synthesize complex information related to projected climate changes into a predictive tool for species conservation. The tool was designed to aid managers in prioritizing species management actions in response to...
Determining suitable locations for seed transfer under climate change: a global quantitative method

Treesearch

Kevin M. Potter; William W. Hargrove

2012-01-01

Changing climate conditions will complicate efforts to match seed sources with the environments to which they are best adapted. Tree species distributions may have to shift to match new environmental conditions, potentially requiring the establishment of some species entirely outside of their current distributions to thrive. Even within the portions of tree species...
Climate Change Communication by a Research Institute: Experiences, Successes, and Challenges from a North European Perspective

ERIC Educational Resources Information Center

Lyytimäki, Jari; Nygrén, Nina A.; Ala-Ketola, Ulla; Pellinen, Sirpa; Ruohomäki, Virpi; Inkinen, Aino

2013-01-01

Communicating about climate change is challenging not only because of the multidisciplinary and complex nature of the issue itself and multiple policy options related to mitigation and adaptation, but also because of the plenitude of potential communication methods coupled with limited resources for communication. This article explores climate…
Evaluations of alternative methods for monitoring and estimating responses of salmon productivity in the North Pacific to future climatic change and other processes: A simulation study

EPA Science Inventory

Estimation of the relative influence of climate change, compared to other human activities, on dynamics of Pacific salmon (Oncorhynchus spp.) populations can help management agencies take appropriate management actions. We used empirically based simulation modelling of 48 sockeye...
Assessment of winter wheat loss risk impacted by climate change from 1982 to 2011

NASA Astrophysics Data System (ADS)

Du, Xin

2017-04-01

The world's farmers will face increasing pressure to grow more food on less land in succeeding few decades, because it seems that the continuous population growth and agricultural products turning to biofuels would extend several decades into the future. Therefore, the increased demand for food supply worldwide calls for improved accuracy of crop productivity estimation and assessment of grain production loss risk. Extensive studies have been launched to evaluate the impacts of climate change on crop production based on various crop models drove with global or regional climate model (GCM/RCM) output. However, assessment of climate change impacts on agriculture productivity is plagued with uncertainties of the future climate change scenarios and complexity of crop model. Therefore, given uncertain climate conditions and a lack of model parameters, these methods are strictly limited in application. In this study, an empirical assessment approach for crop loss risk impacted by water stress has been established and used to evaluate the risk of winter wheat loss in China, United States, Germany, France and United Kingdom. The average value of winter wheat loss risk impacted by water stress for the three countries of Europe is about -931kg/ha, which is obviously higher in contrast with that in China (-570kg/ha) and in United States (-367kg/ha). Our study has important implications for further application of operational assessment of crop loss risk at a country or region scale. Future studies should focus on using higher spatial resolution remote sensing data, combining actual evapo-transpiration to estimate water stress, improving the method for downscaling of statistic crop yield data, and establishing much more rational and elaborate zoning method.
Investigating Downscaling Methods and Evaluating Climate Models for Use in Estimating Regional Water Resources in Mountainous Regions under Changing Climatic Conditions

NASA Technical Reports Server (NTRS)

Frei, Allan; Nolin, Anne W.; Serreze, Mark C.; Armstrong, Richard L.; McGinnis, David L.; Robinson, David A.

2004-01-01

The purpose of this three-year study is to develop and evaluate techniques to estimate the range of potential hydrological impacts of climate change in mountainous areas. Three main objectives are set out in the proposal. (1) To develop and evaluate transfer functions to link tropospheric circulation to regional snowfall. (2) To evaluate a suite of General Circulation Models (GCMs) for use in estimating synoptic scale circulation and the resultant regional snowfall. And (3) to estimate the range of potential hydrological impacts of changing climate in the two case study areas: the Upper Colorado River basin, and the Catskill Mountains of southeastern New York State. Both regions provide water to large populations.
Vulnerability of Thai rice production to simultaneous climate and socioeconomic changes: a double exposure analysis

NASA Astrophysics Data System (ADS)

Sangpenchan, R.

2011-12-01

This research explores the vulnerability of Thai rice production to simultaneous exposure by climate and socioeconomic change -- so-called "double exposure." Both processes influence Thailand's rice production system, but the vulnerabilities associated with their interactions are unknown. To understand this double exposure, I adopts a mixed-method, qualitative-quantitative analytical approach consisting of three phases of analysis involving a Vulnerability Scoping Diagram, a Principal Component Analysis, and the EPIC crop model using proxy datasets collected from secondary data sources at provincial scales.The first and second phases identify key variables representing each of the three dimensions of vulnerability -- exposure, sensitivity, and adaptive capacity indicating that the greatest vulnerability in the rice production system occurs in households and areas with high exposure to climate change, high sensitivity to climate and socioeconomic stress, and low adaptive capacity. In the third phase, the EPIC crop model simulates rice yields associated with future climate change projected by CSIRO and MIROC climate models. Climate change-only scenarios project the decrease in yields by 10% from the current productivity during 2016-2025 and 30% during 2045-2054. Scenarios applying both climate change and improved technology and management practices show that a 50% increase in rice production is possible, but requires strong collaboration between sectors to advance agricultural research and technology and requires strong adaptive capacity in the rice production system characterized by well-developed social capital, social networks, financial capacity, and infrastructure and household mobility at the local scale. The vulnerability assessment and climate and crop adaptation simulations used here provide useful information to decision makers developing vulnerability reduction plans in the face of concurrent climate and socioeconomic change.
Quantitative assessment of the impacts of climate change and human activities on runoff change in a typical karst watershed, SW China.

PubMed

Wu, Luhua; Wang, Shijie; Bai, Xiaoyong; Luo, Weijun; Tian, Yichao; Zeng, Cheng; Luo, Guangjie; He, Shiyan

2017-12-01

The Yinjiang River watershed is a typical karst watershed in Southwest China. The present study explored runoff change and its responses to different driving factors in the Yinjiang River watershed over the period of 1984 to 2015. The methods of cumulative anomaly, continuous wavelet analysis, Mann-Kendall rank correlation trend test, and Hurst exponent were applied to analyze the impacts of climate change and human activities on runoff change. The contributions of climate change and human activities to runoff change were quantitatively assessed using the comparative method of the slope changing ratio of cumulative quantity (SCRCQ). The following results were obtained: (1) From 1984 to 2015, runoff and precipitation exhibited no-significant increasing trend, whereas evaporation exhibited significant decreasing trend. (2) In the future, runoff, precipitation, and evaporation will exhibit weak anti-persistent feature with different persistent times. This feature indicated that in their persistent times, runoff and precipitation will continuously decline, whereas evaporation will continuously increase. (3) Runoff and precipitation were well-synchronized with abrupt change features and stage characteristics, and exhibited consistent multi-timescale characteristics that were different from that of evaporation. (4) The contribution of precipitation to runoff change was 50%-60% and was considered high and stable. The contribution of evaporation to runoff change was 10%-90% and was variable with a positive or negative effects. The contribution of human activities to runoff change was 20%-60% and exerted a low positive or negative effect. (5) Climatic factors highly contributed to runoff change. By contrast, the contribution of human activities to runoff change was low. The contribution of climatic factors to runoff change was highly variable because of differences among base periods. In conclusion, this paper provides a basic theoretical understanding of the main factors that contribute to runoff change in a karst watershed. Copyright © 2017 Elsevier B.V. All rights reserved.
Redefining thermal regimes to design reserves for coral reefs in the face of climate change.

PubMed

Chollett, Iliana; Enríquez, Susana; Mumby, Peter J

2014-01-01

Reef managers cannot fight global warming through mitigation at local scale, but they can use information on thermal patterns to plan for reserve networks that maximize the probability of persistence of their reef system. Here we assess previous methods for the design of reserves for climate change and present a new approach to prioritize areas for conservation that leverages the most desirable properties of previous approaches. The new method moves the science of reserve design for climate change a step forwards by: (1) recognizing the role of seasonal acclimation in increasing the limits of environmental tolerance of corals and ameliorating the bleaching response; (2) using the best proxy for acclimatization currently available; (3) including information from several bleaching events, which frequency is likely to increase in the future; (4) assessing relevant variability at country scales, where most management plans are carried out. We demonstrate the method in Honduras, where a reassessment of the marine spatial plan is in progress.

Redefining Thermal Regimes to Design Reserves for Coral Reefs in the Face of Climate Change

PubMed Central

Chollett, Iliana; Enríquez, Susana; Mumby, Peter J.

2014-01-01

Reef managers cannot fight global warming through mitigation at local scale, but they can use information on thermal patterns to plan for reserve networks that maximize the probability of persistence of their reef system. Here we assess previous methods for the design of reserves for climate change and present a new approach to prioritize areas for conservation that leverages the most desirable properties of previous approaches. The new method moves the science of reserve design for climate change a step forwards by: (1) recognizing the role of seasonal acclimation in increasing the limits of environmental tolerance of corals and ameliorating the bleaching response; (2) using the best proxy for acclimatization currently available; (3) including information from several bleaching events, which frequency is likely to increase in the future; (4) assessing relevant variability at country scales, where most management plans are carried out. We demonstrate the method in Honduras, where a reassessment of the marine spatial plan is in progress. PMID:25333380
Changes in Landscape Greenness and Climatic Factors over ...

EPA Pesticide Factsheets

Monitoring and quantifying changes in vegetation cover over large areas using remote sensing can be achieved using the Normalized Difference Vegetation Index (NDVI), an indicator of greenness. However, distinguishing gradual shifts in NDVI (e.g. climate change) versus direct and rapid changes (e.g., fire, land development) is challenging as changes can be confounded by time-dependent patterns, and variation associated with climatic factors. In the present study we leveraged a method, that we previously developed for a pilot study, to address these confounding factors by evaluating NDVI change using autoregression techniques that compare results from univariate (NDVI vs. time) and multivariate analyses (NDVI vs. time and climatic factors) for ~7,660,636 1-km2 pixels comprising the 48 contiguous states of the USA, over a 25-year period (1989−2013). NDVI changed significantly for 48% of the nation over the 25-year in the univariate analyses where most significant trends (85%) indicated an increase in greenness over time. By including climatic factors in the multivariate analyses of NDVI over time, the detection of significant NDVI trends increased to 53% (an increase of 5%). Comparisons of univariate and multivariate analyses for each pixel showed that less than 4% of the pixels had a significant NDVI trend attributable to gradual climatic changes while the remainder of pixels with a significant NDVI trend indicated that changes were due to direct factors. Whi
Health impact assessment of global climate change: expanding on comparative risk assessment approaches for policy making.

PubMed

Patz, Jonathan; Campbell-Lendrum, Diarmid; Gibbs, Holly; Woodruff, Rosalie

2008-01-01

Climate change is projected to have adverse impacts on public health. Cobenefits may be possible from more upstream mitigation of greenhouse gases causing climate change. To help measure such cobenefits alongside averted disease-specific risks, a health impact assessment (HIA) framework can more comprehensively serve as a decision support tool. HIA also considers health equity, clearly part of the climate change problem. New choices for energy must be made carefully considering such effects as additional pressure on the world's forests through large-scale expansion of soybean and oil palm plantations, leading to forest clearing, biodiversity loss and disease emergence, expulsion of subsistence farmers, and potential increases in food prices and emissions of carbon dioxide to the atmosphere. Investigators must consider the full range of policy options, supported by more comprehensive, flexible, and transparent assessment methods.
Estimating the economic impact of climate change on cardiovascular diseases--evidence from Taiwan.

PubMed

Liao, Shu-Yi; Tseng, Wei-Chun; Chen, Pin-Yu; Chen, Chi-Chung; Wu, Wei-Min

2010-12-01

The main purpose of this study was to investigate how climate change affects blood vessel-related heart disease and hypertension and to estimate the associated economic damage. In this paper, both the panel data model and the contingent valuation method (CVM) approaches are applied. The empirical results indicate that the number of death from cardiovascular diseases would be increased by 0.226% as the variation in temperature increases by 1%. More importantly, the number of death from cardiovascular diseases would be increased by 1.2% to 4.1% under alternative IPCC climate change scenarios. The results from the CVM approach show that each person would be willing to pay US$51 to US$97 per year in order to avoid the increase in the mortality rate of cardiovascular diseases caused by climate change.
Estimating the Economic Impact of Climate Change on Cardiovascular Diseases—Evidence from Taiwan

PubMed Central

Liao, Shu-Yi; Tseng, Wei-Chun; Chen, Pin-Yu; Chen, Chi-Chung; Wu, Wei-Min

2010-01-01

The main purpose of this study was to investigate how climate change affects blood vessel-related heart disease and hypertension and to estimate the associated economic damage. In this paper, both the panel data model and the contingent valuation method (CVM) approaches are applied. The empirical results indicate that the number of death from cardiovascular diseases would be increased by 0.226% as the variation in temperature increases by 1%. More importantly, the number of death from cardiovascular diseases would be increased by 1.2% to 4.1% under alternative IPCC climate change scenarios. The results from the CVM approach show that each person would be willing to pay US$51 to US$97 per year in order to avoid the increase in the mortality rate of cardiovascular diseases caused by climate change. PMID:21318006
Mapping Climate Change Vulnerabilities to Infectious Diseases in Europe

PubMed Central

Suk, Jonathan E.; Estevez, Virginia; Ebi, Kristie L.; Lindgren, Elisabet

2011-01-01

Background: The incidence, outbreak frequency, and distribution of many infectious diseases are generally expected to change as a consequence of climate change, yet there is limited regional information available to guide decision making. Objective: We surveyed government officials designated as Competent Bodies for Scientific Advice concerning infectious diseases to examine the degree to which they are concerned about potential effects of climate change on infectious diseases, as well as their perceptions of institutional capacities in their respective countries. Methods: In 2007 and 2009/2010, national infectious disease experts from 30 European Economic Area countries were surveyed about recent and projected infectious disease patterns in relation to climate change in their countries and the national capacity to cope with them. Results: A large majority of respondents agreed that climate change would affect vector-borne (86% of country representatives), food-borne (70%), water-borne (68%), and rodent-borne (68%) diseases in their countries. In addition, most indicated that institutional improvements are needed for ongoing surveillance programs (83%), collaboration with the veterinary sector (69%), management of animal disease outbreaks (66%), national monitoring and control of climate-sensitive infectious diseases (64%), health services during an infectious disease outbreak (61%), and diagnostic support during an epidemic (54%). Conclusions: Expert responses were generally consistent with the peer-reviewed literature regarding the relationship between climate change and vector- and water-borne diseases, but were less so for food-borne diseases. Shortcomings in institutional capacity to manage climate change vulnerability, identified in this assessment, should be addressed in impact, vulnerability, and adaptation assessments. PMID:22113877
Using Impact-Relevant Sensitivities to Efficiently Evaluate and Select Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Vano, J. A.; Kim, J. B.; Rupp, D. E.; Mote, P.

2014-12-01

We outline an efficient approach to help researchers and natural resource managers more effectively use global climate model information in their long-term planning. The approach provides an estimate of the magnitude of change of a particular impact (e.g., summertime streamflow) from a large ensemble of climate change projections prior to detailed analysis. These estimates provide both qualitative information as an end unto itself (e.g., the distribution of future changes between emissions scenarios for the specific impact) and a judicious, defensible evaluation structure that can be used to qualitatively select a sub-set of climate models for further analysis. More specifically, the evaluation identifies global climate model scenarios that both (1) span the range of possible futures for the variable/s most important to the impact under investigation, and (2) come from global climate models that adequately simulate historical climate, providing plausible results for the future climate in the region of interest. To identify how an ecosystem process responds to projected future changes, we methodically sample, using a simple sensitivity analysis, how an impact variable (e.g., streamflow magnitude, vegetation carbon) responds locally to projected regional temperature and precipitation changes. We demonstrate our technique over the Pacific Northwest, focusing on two types of impacts each in three distinct geographic settings: (a) changes in streamflow magnitudes in critical seasons for water management in the Willamette, Yakima, and Upper Columbia River basins; and (b) changes in annual vegetation carbon in the Oregon and Washington Coast Ranges, Western Cascades, and Columbia Basin ecoregions.
Mapping vulnerability to climate change and its repercussions on human health in Pakistan

PubMed Central

2012-01-01

Background Pakistan is highly vulnerable to climate change due to its geographic location, high dependence on agriculture and water resources, low adaptive capacity of its people, and weak system of emergency preparedness. This paper is the first ever attempt to rank the agro-ecological zones in Pakistan according to their vulnerability to climate change and to identify the potential health repercussions of each manifestation of climate change in the context of Pakistan. Methods A climate change vulnerability index is constructed as an un-weighted average of three sub-indices measuring (a) the ecological exposure of each region to climate change, (b) sensitivity of the population to climate change and (c) the adaptive capacity of the population inhabiting a particular region. The regions are ranked according to the value of this index and its components. Since health is one of the most important dimensions of human wellbeing, this paper also identifies the potential health repercussions of each manifestations of climate change and links it with the key manifestations of climate change in the context of Pakistan. Results The results indicate that Balochistan is the most vulnerable region with high sensitivity and low adaptive capacity followed by low-intensity Punjab (mostly consisting of South Punjab) and Cotton/Wheat Sindh. The health risks that each of these regions face depend upon the type of threat that they face from climate change. Greater incidence of flooding, which may occur due to climate variability, poses the risk of diarrhoea and gastroenteritis; skin and eye Infections; acute respiratory infections; and malaria. Exposure to drought poses the potential health risks in the form of food insecurity and malnutrition; anaemia; night blindness; and scurvy. Increases in temperature pose health risks of heat stroke; malaria; dengue; respiratory diseases; and cardiovascular diseases. Conclusion The study concludes that geographical zones that are more exposed to climate change in ecological and geographic terms- such as Balochistan, Low-Intensity Punjab, and Cotton-Wheat Sindh -also happen to be the most deprived regions in Pakistan in terms of socio-economic indicators, suggesting that the government needs to direct its efforts to the socio-economic uplift of these lagging regions to reduce their vulnerability to the adverse effects of climate change. PMID:22938568
Curve number method response to historical climate variability and trends

USDA-ARS?s Scientific Manuscript database

With the dependence on the curve number (CN) model by the engineering community, the question arises as to whether changes in climate may affect the performance of the CN algorithm which impacts estimates of runoff. A study was conducted to determine the effects of “climate period” (period of unifor...
Use of NARCCAP Model Projections to Develop a Future Typical Meteorological Year and Estimate the Impact of a Changing Climate on Building Energy Consumption

NASA Astrophysics Data System (ADS)

Patton, S. L.; Takle, E. S.; Passe, U.; Kalvelage, K.

2013-12-01

Current simulations of building energy consumption use weather input files based on the past thirty years of climate observations. These 20th century climate conditions may be inadequate when designing buildings meant to function well into the 21st century. An alternative is using model projections of climate change to estimate future risk to the built environment. In this study, model-projected changes in climate were combined with existing typical meteorological year data to create future typical meteorological year data. These data were then formatted for use in EnergyPlus simulation software to evaluate their potential impact on commercial building energy consumption. The modeled climate data were taken from the North American Regional Climate Change Assessment Program (NARCCAP). NARCCAP uses results of global climate models to drive regional climate models, also known as dynamical downscaling. This downscaling gives higher resolution results over specific locations, and the multiple global/regional climate model combinations provide a unique opportunity to quantify the uncertainty of climate change projections and their impacts. Our results show a projected decrease in heating energy consumption and a projected increase in cooling energy consumption for nine locations across the United States for all model combinations. Warmer locations may expect a decrease in heating load of around 30% to 45% and an increase in cooling load of around 25% to 35%. Colder locations may expect a decrease in heating load of around 15% to 25% and an increase in cooling load of around 40% to 70%. The change in net energy consumption is determined by the balance between the magnitudes of heating change and cooling change. Net energy consumption is projected to increase by an average of 5% for lower-latitude locations and decrease by an average of 5% for higher-latitude locations. With these projected annual and seasonal changes presenting strong evidence for the unsuitable nature of current building practices holding up under future climate change, we recommend using our methods and results to make modifications and adaptations to existing buildings and to aid in the design of future buildings.
The climate of the Taimyr Peninsula in the Holocene and a Forecast of Climatic Changes in the Arctic

NASA Astrophysics Data System (ADS)

Ukraintseva, V.

2009-04-01

Based on the data of the spore-pollen and radiocarbon methods during our research of a peat bog in the south-eastern part of the Taimyr Peninsula we discovered for the first time the natural dynamics of the climate for this region during the period of the last 10 500 years [2, 3] and made a long-term forecast of climatic changes both for the Taimyr Peninsula and for other Arctic regions. By the quantitative characteristics of the climate and their dynamics in time, reconstructed for the basin of the Fomich River (71 ° 42 ' North, 108 ° 03 ' East) and for the Taimyr Peninsula on the whole, we have established two climatic types: tundra (10500 ±140 years BP- 7040 ± 60 years BP) and forest (5720± 60 years BP - 500 ± 60 years BP to the present time). In the first half of the Holocene the climate there was rather stable; only 7530 years ago a sharp cooling took place; the second half of the Holocene, beginning with 5720 years ago, is characterized by alternating fluctuations in the climate [3]. Taking only the palaeoclimatic reconstructions as a basis, we can talk about a trend of climatic changes in the future. However comparing the Sun activity` forecast, expressed in Wolf units (Max W), made by V.N. Kupetsky [1], with the climatic characteristics, which we have reconstructed, we could then make a more precise forecast of climatic changes for the Taimyr Peninsula and the Russian part of the Arctic (Table). The above forecast lets us make the following basically important conclusions: (1) the climate`s warming, which is currently being observed on the Earth (the 23rd cycle of the Sun`s activity) will last till 2011; (2) during the following two cycles (24th and 25th) the Sun`s activity will decrease to 100-110 Wolf units, which will cause a cooling of the climate on the Earth; (3) in the following, the 26th cycle, the Sun`s activity will increase up to 130 Wolf units, which will cause a warming of the climate; (4) in the 27th cycle (2037-2048) the Sun`s activity will decrease to 100 Wolf units, causing a cooling on the Earth again. Thus, the forecast of climatic changes in the Arctic, which we have worked up and based on the Sun-Earth connections, is an objective natural reality. The climate fluctuations in the Arctic, which we have identified for the last 12-10 thousand years, will continue in the forthcoming 50-100 years. Consequently, only the synthesis of solar-telescopic, palaeoclimatic and modern meteorological data allows making a valid long-term global forecast of climatic changes and of the Earth`s landscape in the future. Regional and local forecasts developed on the basis of a global forecast will be then of the primary value. Since the solar-telescopic data are alpha and omega for forecast constructions, their publication in the open press is an absolute necessity. This would enable scientists to make realistic forecasts of climatic changes for specific districts and regions of the Earth in the future. The contemporary scientific knowledge level does not show us any other way yet. Bibliography: 1. Kupetsky, V.N. Landscapes of freezing seas. Dissertation for the Degree of Doctor of Geographical Science. Saint-Petersburg State University, 1998 ( Russian). 2. Ukraintseva, V.V. Use of the index of similarity for the assessment of fossil spore-pollen spectra // Modern Problems of Paleofloristics, Paleophytogeography and Phytostratigraphy. Transaction of the International Paleobotanical Conference. Moscow, May 17-18, 2005. Vol.1. - Moscow: GEOS, 2005. P. 314 - 318. 3. Ukraintseva, V.V. On the new method of reconstruction of climates of the past on the basis of the spore-pollen analysis method data// SOCIETY. ENVIRONMENT. DEVELOPMENT. 2008. No.3. P.142-154 (Russian). 4. Ukraintseva V.V., Pospelov I.N. Reconstruction of Climates of the Past and a Forecast: a New Method in Principal// The Holocene, 2008 (in press).
Uncertainty in Driftless Area Cold-Water Fishery Decision Making and a Framework for Stakeholder-Based Science

NASA Astrophysics Data System (ADS)

Schuster, Z.

2015-12-01

The paradigm of stakeholder-based science is becoming more popular as organizations such as the U.S. Department of the Interior Climate Science Centers adopt it as a way of providing practicable climate change information to practitioners. One of the key issues stakeholders face in adopting climate change information into their decision processes is how uncertainty is addressed and communicated. In this study, we conducted a series of semi-structured interviews with managers and scientists working on stream habitat restoration of cold-water fisheries in the Driftless Area of Wisconsin that were focused on how they interpret and manage uncertainty and what types of information they need to make better decisions. One of the important lessons we learned from the interviews is that if researchers are going to provide useful climate change information to stakeholders, they need to understand where and how decisions are made and what adaptation measures are actually available in a given decision arena. This method of incorporating social science methods into climate science production can provide a framework for researchers from the Climate Science Centers and others who are interested in pursuing stakeholder-based science. By indentifying a specific ecological system and conducting interviews with actors who work on that system, researchers will be able to gain a better understanding of how their climate change science can fit into existing or shape new decision processes. We also interpreted lessons learned from our interviews via existing literature in areas such as stakeholder-based modeling and the decision sciences to provide guidance specific to the stakeholder-based science process.
Potential climate engineering effectiveness and side effects during a high carbon dioxide-emission scenario

PubMed Central

Keller, David P.; Feng, Ellias Y.; Oschlies, Andreas

2014-01-01

The realization that mitigation efforts to reduce carbon dioxide emissions have, until now, been relatively ineffective has led to an increasing interest in climate engineering as a possible means of preventing the potentially catastrophic consequences of climate change. While many studies have addressed the potential effectiveness of individual methods there have been few attempts to compare them. Here we use an Earth system model to compare the effectiveness and side effects of afforestation, artificial ocean upwelling, ocean iron fertilization, ocean alkalinization and solar radiation management during a high carbon dioxide-emission scenario. We find that even when applied continuously and at scales as large as currently deemed possible, all methods are, individually, either relatively ineffective with limited (<8%) warming reductions, or they have potentially severe side effects and cannot be stopped without causing rapid climate change. Our simulations suggest that the potential for these types of climate engineering to make up for failed mitigation may be very limited. PMID:24569320
Are We Telling Decision-makers the Wrong Things - and with Too Much Confidence?

NASA Astrophysics Data System (ADS)

Arnold, J.; Nowak, K. C.; Vano, J. A.; Newman, A. J.; Mizukami, N.; Mendoza, P. A.; Nijssen, B.; Wood, A.; Gutmann, E. D.; Clark, M. P.; Rasmussen, R.

2016-12-01

Water-resource management relies on decision-making over a wide range of space-time scales, nearly none of which maps cleanly onto the scales of current hydroclimatic scenarios of anthropogenic change. Myriad choices are made during vulnerability and impact assessments to quantify the changed-climate sensitivities of models used in that decision-making, including choices of hydrologic models, parameters, and parameterizations; their input forcings determined with various climate downscaling approaches; selected GCMs and output variables to be downscaled; and the forcing emissions scenarios, to name a few. Choosing alternative methods for producing gridded meteorological fields, for examples, can produce very different effects on the projected hydrologic outcomes they drive, with uncertainties across those methods revealed to be as large or larger than the climate change signal itself in some cases. Additionally, many popular climate downscaling methods simply rescale GCM precipitation, producing hydroclimatic projections with too much drizzle, incorrect representations of extreme events, and improper spatial scaling of variables crucial to water-resource vulnerability assessments and, importantly, the decisions they seek to inform. Real-world water-resource vulnerability and impacts assessments can be highly time-sensitive and resource limited, though, so they typically do not confront or even fully represent uncertainties associated with all choices. That deficiency results in assessments built on only partially revealed uncertainties which can misrepresent significant sensitivities and impacts in the final assessments of climate threats and hydrologic vulnerabilities. This talk will describe recent work by the U.S. Army Corps of Engineers, Bureau of Reclamation, University of Washington, and National Center for Atmospheric Research to develop and test methods to characterize more fully the uncertainties in the modeling chain for real-world uses. Examples will illustrate new implementations for communicating that fuller characterization in the ways most useful to inform water-resource management across multiple space-time scales under climate-changed futures.
Attribution of changes in precipitation patterns in African rainforests

NASA Astrophysics Data System (ADS)

Otto, F. E.; Jones, R. G.; Halladay, K.; Allen, M. R.

2013-12-01

The effects of projected future global and regional climate change on the water cycle and thus on global water security are amongst the most economically and politically important challenges that society faces in the 21st century. The provision of secure access to water resources and the protection of communities from water-related risks have emerged as top priorities amongst policymakers within the public and private sectors alike. Investment decisions on water infrastructure rely heavily on quantitative assessments of risks and uncertainties associated with future changes in water-related threats. Especially with the introduction of loss and damages on the agenda of the UNFCCC additionally the attribution of such changes to anthropogenic climate change and other external climate drivers is crucial. Probabilistic event attribution (PEA) provides a method of evaluating the extent to which human-induced climate change is affecting localised weather events and impacts of such events that relies on good observations as well as climate modelling. The overall approach is to simulate both, the statistics of observed weather, and the statistics of the weather that would have occurred had specific external drivers of climate change been absent. The majority of studies applying PEA have focused on quantifying attributable risk, with changes in risk depending on an assumption of 'all other things being equal', including natural drivers of climate change and vulnerability. Most previous attribution studies have focused on European extreme weather events, but the most vulnerable regions to climate change are in Asia and Africa. One of the most complex hydrological systems is the tropical rainforest, with the rainforests in tropical Africa being some of the most under-researched regions in the world. Research in the Amazonian rainforest suggests potential vulnerability to climate change. We will present results from using the large ensemble of atmosphere-only general circulation model (AGCM) simulations within the weather@home project, and analysing statistics of precipitation in the dry season of the Congo Basin rainforests. Because observed data sets in that region are of very poor quality we show how validation methods not only relying on such data have been used to investigate the applicability of PEA analysis from large model ensembles to this tropical region. Additionally we will present results for the same region but generated with a very large ensemble of regional climate simulations which allows analysing the importance of a realistic simulation of small scale precipitation processes for attribution studies in a tropical climate. We highlight that PEA analysis has the potential to provide valuable scientific evidence of recent or anticipated climatological changes in the water cycle, especially in regions with sparse observational data and unclear projections of future changes. However, the strong influence of SST tele-connection patterns on tropical precipitation provides more challenges in the set-up of attribution studies than studies on mid-latitude rainfall.
Mulit Criteria - Application on Climate Change Adaptation and Biofuel Cultivation on Contaminated Land

NASA Astrophysics Data System (ADS)

Andersson-Sköld, Yvonne; Suer, Pascal; Bergman, Ramona; Helgesson, Helena

2010-05-01

A decision support tool/method has been developed to systematically include sustainability at an early stage in planning issues. Sustainability was subdivided into human health, environmental impacts, resources, and social and economic impacts. Health, environmental and resources impacts were based on the Swedish environmental objectives, life cycle assessment (LCA) impact categories, and contaminated soil guidelines. The resulting impact indicators were climate change - global warming potential, large scale and local air quality, water and soil quality, landscape, energy, materials, wellbeing/welfare, direct financial costs, social economic aspects, and flexi-bility. The method offers an iterative discussion framework that is systematic, condensed and yet a simplistic way of describing consequences of climate change and related adaptation measures including economic, social and environmental aspects. Application of the tool to biofuel cultivation on contaminated soil indicated that traditional soil remediation may have higher social and economical benefits but be less suitable from a health, environment, and resources perspective. The tool has further been applied in municipalities on climate change impacts and adaptation measures. Re-sults from the application in tree municipalities will be presented: Gothenburg City, Lidköping and Arvika. In Gothenburg and Lidköping the major impact of climate change is increase in sea water level (North Sea and Lake Vänern respectively) combined with extreme weather conditions. According to regional climate change scenarios Arvika is located in one of the worst affected areas in Sweden with respect to increase of intensive rainfall and extreme flows. The adaptation measures investigated at the three locations include doing nothing, different constructions and planning. The results are based on previous risk identification investigations, flood and land slide maps and interviews with civil servants in the three municipalities.
Climate Change and Public Health Surveillance: Toward a Comprehensive Strategy

PubMed Central

Moulton, Anthony Drummond; Schramm, Paul John

2017-01-01

Context Climate change poses a host of serious threats to human health that robust public health surveillance systems can help address. It is unknown, however, whether existing surveillance systems in the United States have adequate capacity to serve that role, nor what actions may be needed to develop adequate capacity. Objective Our goals were to review efforts to assess and strengthen the capacity of public health surveillance systems to support health-related adaptation to climate change in the United States and to determine whether additional efforts are warranted. Methods Building on frameworks issued by the Intergovernmental Panel on Climate Change and the Centers for Disease Control and Prevention, we specified 4 core components of public health surveillance capacity relevant to climate change health threats. Using standard methods, we next identified and analyzed multiple assessments of the existing, relevant capacity of public health surveillance systems as well as attempts to improve that capacity. We also received information from selected national public health associations. Findings Multiple federal, state, and local public health agencies, professional associations, and researchers have made valuable, initial efforts to assess and strengthen surveillance capacity. These efforts, however, have been made by entities working independently and without the benefit of a shared conceptual framework or strategy. Their principal focus has been on identifying suitable indicators and data sources largely to the exclusion of other core components of surveillance capacity. Conclusions A more comprehensive and strategic approach is needed to build the public health surveillance capacity required to protect the health of Americans in a world of rapidly evolving climate change. Public health practitioners and policy makers at all levels can use the findings and issues reviewed in this article as they lead design and execution of a coordinated, multisector strategic plan to create and sustain that capacity. PMID:28169865
Climate change-related temperature impacts on warm season heat mortality: a proof-of-concept methodology using BenMAP.

PubMed

Voorhees, A Scott; Fann, Neal; Fulcher, Charles; Dolwick, Patrick; Hubbell, Bryan; Bierwagen, Britta; Morefield, Philip

2011-02-15

Climate change is anticipated to raise overall temperatures and is likely to increase heat-related human health morbidity and mortality risks. The objective of this work was to develop a proof-of-concept approach for estimating excess heat-related premature deaths in the continental United States resulting from potential changes in future temperature using the BenMAP model. In this approach we adapt the methods and tools that the US Environmental Protection Agency uses to assess air pollution health impacts by incorporating temperature modeling and heat mortality health impact functions. This new method demonstrates the ability to apply the existing temperature-health literature to quantify prospective changes in climate-sensitive heat-related mortality. We compared estimates of future temperature with and without climate change and applied heat-mortality health functions to estimate relative changes in heat-related premature mortality. Using the A1B emissions scenario, we applied the GISS-II global circulation model downscaled to 36-km using MM5 and formatted using the Meteorology-Chemistry Interface Processor. For averaged temperatures derived from the 5 years 2048-2052 relative to 1999-2003 we estimated for the warm season May-September a national U.S. estimate of annual incidence of heat-related mortality to be 3700-3800 from all causes, 3500 from cardiovascular disease, and 21 000-27 000 from nonaccidental death, applying various health impact functions. Our estimates of mortality, produced to validate the application of a new methodology, suggest the importance of quantifying heat impacts in economic assessments of climate change.
Arctic indigenous peoples as representations and representatives of climate change.

PubMed

Martello, Marybeth Long

2008-06-01

Recent scientific findings, as presented in the Arctic Climate Impact Assessment (ACIA), indicate that climate change in the Arctic is happening now, at a faster rate than elsewhere in the world, and with major implications for peoples of the Arctic (especially indigenous peoples) and the rest of the planet. This paper examines scientific and political representations of Arctic indigenous peoples that have been central to the production and articulation of these claims. ACIA employs novel forms and strategies of representation that reflect changing conceptual models and practices of global change science and depict indigenous peoples as expert, exotic, and at-risk. These portrayals emerge alongside the growing political activism of Arctic indigenous peoples who present themselves as representatives or embodiments of climate change itself as they advocate for climate change mitigation policies. These mutually constitutive forms of representation suggest that scientific ways of seeing the global environment shape and are shaped by the public image and voice of global citizens. Likewise, the authority, credibility, and visibility of Arctic indigenous activists derive, in part, from their status as at-risk experts, a status buttressed by new scientific frameworks and methods that recognize and rely on the local experiences and knowledges of indigenous peoples. Analyses of these relationships linking scientific and political representations of Arctic climate change build upon science and technology studies (STS) scholarship on visualization, challenge conventional notions of globalization, and raise questions about power and accountability in global climate change research.
Winter Precipitation Forecast in the European and Mediterranean Regions Using Cluster Analysis

NASA Astrophysics Data System (ADS)

Totz, Sonja; Tziperman, Eli; Coumou, Dim; Pfeiffer, Karl; Cohen, Judah

2017-12-01

The European climate is changing under global warming, and especially the Mediterranean region has been identified as a hot spot for climate change with climate models projecting a reduction in winter rainfall and a very pronounced increase in summertime heat waves. These trends are already detectable over the historic period. Hence, it is beneficial to forecast seasonal droughts well in advance so that water managers and stakeholders can prepare to mitigate deleterious impacts. We developed a new cluster-based empirical forecast method to predict precipitation anomalies in winter. This algorithm considers not only the strength but also the pattern of the precursors. We compare our algorithm with dynamic forecast models and a canonical correlation analysis-based prediction method demonstrating that our prediction method performs better in terms of time and pattern correlation in the Mediterranean and European regions.

Correlated k-distribution method for radiative transfer in climate models: Application to effect of cirrus clouds on climate

NASA Technical Reports Server (NTRS)

Lacis, A. A.; Wang, W. C.; Hansen, J. E.

1979-01-01

A radiative transfer method appropriate for use in simple climate models and three dimensional global climate models was developed. It is fully interactive with climate changes, such as in the temperature-pressure profile, cloud distribution, and atmospheric composition, and it is accurate throughout the troposphere and stratosphere. The vertical inhomogeneity of the atmosphere is accounted for by assuming a correlation of gaseous k-distributions of different pressures and temperatures. Line-by-line calculations are made to demonstrate that The method is remarkably accurate. The method is then used in a one-dimensional radiative-convective climate model to study the effect of cirrus clouds on surface temperature. It is shown that an increase in cirrus cloud cover can cause a significant warming of the troposphere and the Earth's surface, by the mechanism of an enhanced green-house effect. The dependence of this phenomenon on cloud optical thickness, altitude, and latitude is investigated.
Robust Engineering Designs for Infrastructure Adaptation to a Changing Climate

NASA Astrophysics Data System (ADS)

Samaras, C.; Cook, L.

2015-12-01

Infrastructure systems are expected to be functional, durable and safe over long service lives - 50 to over 100 years. Observations and models of climate science show that greenhouse gas emissions resulting from human activities have changed climate, weather and extreme events. Projections of future changes (albeit with uncertainties caused by inadequacies of current climate/weather models) can be made based on scenarios for future emissions, but actual future emissions are themselves uncertain. Most current engineering standards and practices for infrastructure assume that the probabilities of future extreme climate and weather events will match those of the past. Climate science shows that this assumption is invalid, but is unable, at present, to define these probabilities over the service lives of existing and new infrastructure systems. Engineering designs, plans, and institutions and regulations will need to be adaptable for a range of future conditions (conditions of climate, weather and extreme events, as well as changing societal demands for infrastructure services). For their current and future projects, engineers should: Involve all stakeholders (owners, financers, insurance, regulators, affected public, climate/weather scientists, etc.) in key decisions; Use low regret, adaptive strategies, such as robust decision making and the observational method, comply with relevant standards and regulations, and exceed their requirements where appropriate; Publish design studies and performance/failure investigations to extend the body of knowledge for advancement of practice. The engineering community should conduct observational and modeling research with climate/weather/social scientists and the concerned communities and account rationally for climate change in revised engineering standards and codes. This presentation presents initial research on decisionmaking under uncertainty for climate resilient infrastructure design.
Applying simple water-energy balance frameworks to predict the climate sensitivity of streamflow over the continental United States

NASA Astrophysics Data System (ADS)

Renner, M.; Bernhofer, C.

2012-08-01

The prediction of climate effects on terrestrial ecosystems and water resources is one of the major research questions in hydrology. Conceptual water-energy balance models can be used to gain a first order estimate of how long-term average streamflow is changing with a change in water and energy supply. A common framework for investigation of this question is based on the Budyko hypothesis, which links hydrological response to aridity. Recently, Renner et al. (2012) introduced the climate change impact hypothesis (CCUW), which is based on the assumption that the total efficiency of the catchment ecosystem to use the available water and energy for actual evapotranspiration remains constant even under climate changes. Here, we confront the climate sensitivity approaches (the Budyko approach of Roderick and Farquhar, 2011, and the CCUW) with data of more than 400 basins distributed over the continental United States. We first estimate the sensitivity of streamflow to changes in precipitation using long-term average data of the period 1949 to 2003. This provides a hydro-climatic status of the respective basins as well as their expected proportional effect to changes in climate. Next, we test the ability of both approaches to predict climate impacts on streamflow by splitting the data into two periods. We (i) analyse the long-term average changes in hydro-climatology and (ii) derive a statistical classification of potential climate and basin change impacts based on the significance of observed changes in runoff, precipitation and potential evapotranspiration. Then we (iii) use the different climate sensitivity methods to predict the change in streamflow given the observed changes in water and energy supply and (iv) evaluate the predictions by (v) using the statistical classification scheme and (vi) a conceptual approach to separate the impacts of changes in climate from basin characteristics change on streamflow. This allows us to evaluate the observed changes in streamflow as well as to assess the impact of basin changes on the validity of climate sensitivity approaches. The apparent increase of streamflow of the majority of basins in the US is dominated by an increase in precipitation. It is further evident that impacts of changes in basin characteristics appear simultaneously with climate changes. There are coherent spatial patterns with catchments where basin changes compensate for climatic changes being dominant in the western and central parts of the US. A hot spot of basin changes leading to excessive runoff is found within the US Midwest. The impact of basin changes on the prediction is large and can be twice as much as the observed change signal. Although the CCUW and the Budyko approach yield similar predictions for most basins, the data of water-limited basins support the Budyko framework rather than the CCUW approach, which is known to be invalid under limiting climatic conditions.
Effects of climate change on plant population growth rate and community composition change.

PubMed

Chang, Xiao-Yu; Chen, Bao-Ming; Liu, Gang; Zhou, Ting; Jia, Xiao-Rong; Peng, Shao-Lin

2015-01-01

The impacts of climate change on forest community composition are still not well known. Although directional trends in climate change and community composition change were reported in recent years, further quantitative analyses are urgently needed. Previous studies focused on measuring population growth rates in a single time period, neglecting the development of the populations. Here we aimed to compose a method for calculating the community composition change, and to testify the impacts of climate change on community composition change within a relatively short period (several decades) based on long-term monitoring data from two plots-Dinghushan Biosphere Reserve, China (DBR) and Barro Colorado Island, Panama (BCI)-that are located in tropical and subtropical regions. We proposed a relatively more concise index, Slnλ, which refers to an overall population growth rate based on the dominant species in a community. The results indicated that the population growth rate of a majority of populations has decreased over the past few decades. This decrease was mainly caused by population development. The increasing temperature had a positive effect on population growth rates and community change rates. Our results promote understanding and explaining variations in population growth rates and community composition rates, and are helpful to predict population dynamics and population responses to climate change.
Fine- and coarse-filter conservation strategies in a time of climate change.

PubMed

Tingley, Morgan W; Darling, Emily S; Wilcove, David S

2014-08-01

As species adapt to a changing climate, so too must humans adapt to a new conservation landscape. Classical frameworks have distinguished between fine- and coarse-filter conservation strategies, focusing on conserving either the species or the landscapes, respectively, that together define extant biodiversity. Adapting this framework for climate change, conservationists are using fine-filter strategies to assess species vulnerability and prioritize the most vulnerable species for conservation actions. Coarse-filter strategies seek to conserve either key sites as determined by natural elements unaffected by climate change, or sites with low climate velocity that are expected to be refugia for climate-displaced species. Novel approaches combine coarse- and fine-scale approaches--for example, prioritizing species within pretargeted landscapes--and accommodate the difficult reality of multiple interacting stressors. By taking a diversified approach to conservation actions and decisions, conservationists can hedge against uncertainty, take advantage of new methods and information, and tailor actions to the unique needs and limitations of places, thereby ensuring that the biodiversity show will go on. © 2014 New York Academy of Sciences.
Detection of greenhouse-gas-induced climatic change. Progress report, 1 December 1991--30 June 1994

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wigley, T.M.L.; Jones, P.D.

1994-07-01

In addition to changes due to variations in greenhouse gas concentrations, the global climate system exhibits a high degree of internally-generated and externally-forced natural variability. To detect the enhanced greenhouse effect, its signal must be isolated from the ``noise`` of this natural climatic variability. A high quality, spatially extensive data base is required to define the noise and its spatial characteristics. To facilitate this, available land and marine data bases will be updated and expanded. The data will be analyzed to determine the potential effects on climate of greenhouse gas concentration changes and other factors. Analyses will be guided bymore » a variety of models, from simple energy balance climate models to ocean General Circulation Models. Appendices A--G contain the following seven papers: (A) Recent global warmth moderated by the effects of the Mount Pinatubo eruption; (B) Recent warming in global temperature series; (C) Correlation methods in fingerprint detection studies; (D) Balancing the carbon budget. Implications for projections of future carbon dioxide concentration changes; (E) A simple model for estimating methane concentration and lifetime variations; (F) Implications for climate and sea level of revised IPCC emissions scenarios; and (G) Sulfate aerosol and climatic change.« less
Climate change and human infectious diseases: A synthesis of research findings from global and spatio-temporal perspectives.

PubMed

Liang, Lu; Gong, Peng

2017-06-01

The life cycles and transmission of most infectious agents are inextricably linked with climate. In spite of a growing level of interest and progress in determining climate change effects on infectious disease, the debate on the potential health outcomes remains polarizing, which is partly attributable to the varying effects of climate change, different types of pathogen-host systems, and spatio-temporal scales. We summarize the published evidence and show that over the past few decades, the reported negative or uncertain responses of infectious diseases to climate change has been growing. A feature of the research tendency is the focus on temperature and insect-borne diseases at the local and decadal scale. Geographically, regions experiencing higher temperature anomalies have been given more research attention; unfortunately, the Earth's most vulnerable regions to climate variability and extreme events have been less studied. From local to global scales, agreements on the response of infectious diseases to climate change tend to converge. So far, an abundance of findings have been based on statistical methods, with the number of mechanistic studies slowly growing. Research gaps and trends identified in this study should be addressed in the future. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Climate Change as Migration Driver from Rural and Urban Mexico

PubMed Central

Hunter, Lori M.; Runfola, Daniel M.; Riosmena, Fernando

2015-01-01

Studies investigating migration as a response to climate variability have largely focused on rural locations to the exclusion of urban areas. This lack of urban focus is unfortunate given the sheer numbers of urban residents and continuing high levels of urbanization. To begin filling this empirical gap, this study investigates climate change impacts on U.S.-bound migration from rural and urban Mexico, 1986–1999. We employ geostatistical interpolation methods to construct two climate change indices, capturing warm and wet spell duration, based on daily temperature and precipitation readings for 214 weather stations across Mexico. In combination with detailed migration histories obtained from the Mexican Migration Project, we model the influence of climate change on household-level migration from 68 rural and 49 urban municipalities. Results from multilevel event-history models reveal that a temperature warming and excessive precipitation significantly increased international migration during the study period. However, climate change impacts on international migration is only observed for rural areas. Interactions reveal a causal pathway in which temperature (but not precipitation) influences migration patterns through employment in the agricultural sector. As such, climate-related international migration may decline with continued urbanization and the resulting reductions in direct dependence of households on rural agriculture. PMID:26692890
Quantifying the consequences of changing hydroclimatic extremes on protection levels for the Rhine

NASA Astrophysics Data System (ADS)

Sperna Weiland, Frederiek; Hegnauer, Mark; Buiteveld, Hendrik; Lammersen, Rita; van den Boogaard, Henk; Beersma, Jules

2017-04-01

The Dutch method for quantifying the magnitude and frequency of occurrence of discharge extremes in the Rhine basin and the potential influence of climate change hereon are presented. In the Netherlands flood protection design requires estimates of discharge extremes for return periods of 1000 up to 100,000 years. Observed discharge records are too short to derive such extreme return discharges, therefore extreme value assessment is based on very long synthetic discharge time-series generated with the Generator of Rainfall And Discharge Extremes (GRADE). The GRADE instrument consists of (1) a stochastic weather generator based on time series resampling of historical f rainfall and temperature and (2) a hydrological model optimized following the GLUE methodology and (3) a hydrodynamic model to simulate the propagation of flood waves based on the generated hydrological time-series. To assess the potential influence of climate change, the four KNMI'14 climate scenarios are applied. These four scenarios represent a large part of the uncertainty provided by the GCMs used for the IPCC 5th assessment report (the CMIP5 GCM simulations under different climate forcings) and are for this purpose tailored to the Rhine and Meuse river basins. To derive the probability distributions of extreme discharges under climate change the historical synthetic rainfall and temperature series simulated with the weather generator are transformed to the future following the KNMI'14 scenarios. For this transformation the Advanced Delta Change method, which allows that the changes in the extremes differ from those in the means, is used. Subsequently the hydrological model is forced with the historical and future (i.e. transformed) synthetic time-series after which the propagation of the flood waves is simulated with the hydrodynamic model to obtain the extreme discharge statistics both for current and future climate conditions. The study shows that both for 2050 and 2085 increases in discharge extremes for the river Rhine at Lobith are projected by all four KNMI'14 climate scenarios. This poses increased requirements for flood protection design in order to prepare for changing climate conditions.
Using Risk Assessment and Habitat Suitability Models to Prioritise Invasive Species for Management in a Changing Climate.

PubMed

Chai, Shauna-Lee; Zhang, Jian; Nixon, Amy; Nielsen, Scott

2016-01-01

Accounting for climate change in invasive species risk assessments improves our understanding of potential future impacts and enhances our preparedness for the arrival of new non-native species. We combined traditional risk assessment for invasive species with habitat suitability modeling to assess risk to biodiversity based on climate change. We demonstrate our method by assessing the risk for 15 potentially new invasive plant species to Alberta, Canada, an area where climate change is expected to facilitate the poleward expansion of invasive species ranges. Of the 15 species assessed, the three terrestrial invasive plant species that could pose the greatest threat to Alberta's biodiversity are giant knotweed (Fallopia sachalinensis), tamarisk (Tamarix chinensis), and alkali swainsonpea (Sphaerophysa salsula). We characterise giant knotweed as 'extremely invasive', with 21 times the suitable habitat between baseline and future projected climate. Tamarisk is 'extremely invasive' with a 64% increase in suitable habitat, and alkali swainsonpea is 'highly invasive' with a 21% increase in suitable habitat. Our methodology can be used to predict and prioritise potentially new invasive species for their impact on biodiversity in the context of climate change.
Using Risk Assessment and Habitat Suitability Models to Prioritise Invasive Species for Management in a Changing Climate

PubMed Central

Chai, Shauna-Lee; Zhang, Jian; Nixon, Amy; Nielsen, Scott

2016-01-01

Accounting for climate change in invasive species risk assessments improves our understanding of potential future impacts and enhances our preparedness for the arrival of new non-native species. We combined traditional risk assessment for invasive species with habitat suitability modeling to assess risk to biodiversity based on climate change. We demonstrate our method by assessing the risk for 15 potentially new invasive plant species to Alberta, Canada, an area where climate change is expected to facilitate the poleward expansion of invasive species ranges. Of the 15 species assessed, the three terrestrial invasive plant species that could pose the greatest threat to Alberta’s biodiversity are giant knotweed (Fallopia sachalinensis), tamarisk (Tamarix chinensis), and alkali swainsonpea (Sphaerophysa salsula). We characterise giant knotweed as ‘extremely invasive’, with 21 times the suitable habitat between baseline and future projected climate. Tamarisk is ‘extremely invasive’ with a 64% increase in suitable habitat, and alkali swainsonpea is ‘highly invasive’ with a 21% increase in suitable habitat. Our methodology can be used to predict and prioritise potentially new invasive species for their impact on biodiversity in the context of climate change. PMID:27768758
Nonlinear regional warming with increasing CO2 concentrations

NASA Astrophysics Data System (ADS)

Good, Peter; Lowe, Jason A.; Andrews, Timothy; Wiltshire, Andrew; Chadwick, Robin; Ridley, Jeff K.; Menary, Matthew B.; Bouttes, Nathaelle; Dufresne, Jean Louis; Gregory, Jonathan M.; Schaller, Nathalie; Shiogama, Hideo

2015-02-01

When considering adaptation measures and global climate mitigation goals, stakeholders need regional-scale climate projections, including the range of plausible warming rates. To assist these stakeholders, it is important to understand whether some locations may see disproportionately high or low warming from additional forcing above targets such as 2 K (ref. ). There is a need to narrow uncertainty in this nonlinear warming, which requires understanding how climate changes as forcings increase from medium to high levels. However, quantifying and understanding regional nonlinear processes is challenging. Here we show that regional-scale warming can be strongly superlinear to successive CO2 doublings, using five different climate models. Ensemble-mean warming is superlinear over most land locations. Further, the inter-model spread tends to be amplified at higher forcing levels, as nonlinearities grow--especially when considering changes per kelvin of global warming. Regional nonlinearities in surface warming arise from nonlinearities in global-mean radiative balance, the Atlantic meridional overturning circulation, surface snow/ice cover and evapotranspiration. For robust adaptation and mitigation advice, therefore, potentially avoidable climate change (the difference between business-as-usual and mitigation scenarios) and unavoidable climate change (change under strong mitigation scenarios) may need different analysis methods.
Studying plant–pollinator interactions in a changing climate: A review of approaches1

PubMed Central

Byers, Diane L.

2017-01-01

Plant–pollinator interactions are potentially at risk due to climate change. Because of the spatial and temporal variation associated with the effects of climate change and the responses of both actors, research to assess this interaction requires creative approaches. This review focuses on assessments of plants’ and pollinators’ altered phenology in response to environmental changes, as phenology is one of the key responses. I reviewed research methods with the goal of presenting the wide diversity of available techniques for addressing changes in these interactions. Approaches ranged from use of historical specimens to multisite experimental community studies; while differing in depth of historical information and community interactions, all contribute to assessment of phenology changes. Particularly insightful were those studies that directly assessed the environmental changes across spatial and temporal scales and the responses of plants and pollinators at these scales. Longer-term studies across environmental gradients, potentially with reciprocal transplants, enable an assessment of climate impacts at both scales. While changes in phenology are well studied, the impacts of phenology changes are not. Future research should include approaches to address this gap. PMID:28690933
Development of Distributed Research Center for analysis of regional climatic and environmental changes

NASA Astrophysics Data System (ADS)

Gordov, E.; Shiklomanov, A.; Okladnikov, I.; Prusevich, A.; Titov, A.

2016-11-01

We present an approach and first results of a collaborative project being carried out by a joint team of researchers from the Institute of Monitoring of Climatic and Ecological Systems, Russia and Earth Systems Research Center UNH, USA. Its main objective is development of a hardware and software platform prototype of a Distributed Research Center (DRC) for monitoring and projecting of regional climatic and environmental changes in the Northern extratropical areas. The DRC should provide the specialists working in climate related sciences and decision-makers with accurate and detailed climatic characteristics for the selected area and reliable and affordable tools for their in-depth statistical analysis and studies of the effects of climate change. Within the framework of the project, new approaches to cloud processing and analysis of large geospatial datasets (big geospatial data) inherent to climate change studies are developed and deployed on technical platforms of both institutions. We discuss here the state of the art in this domain, describe web based information-computational systems developed by the partners, justify the methods chosen to reach the project goal, and briefly list the results obtained so far.
Focus on climate projections for adaptation strategies

NASA Astrophysics Data System (ADS)

Feijt, Arnout; Appenzeller, Christof; Siegmund, Peter; von Storch, Hans

2016-01-01

Most papers in this focus issue on ‘climate and climate impact projections for adaptation strategies’ are solicited by the guest editorial team and originate from a cluster of projects that were initiated 5 years ago. These projects aimed to provide climate change and climate change adaptation information for a wide range of societal areas for the lower parts of the deltas of the Rhine and Meuse rivers, and particularly for the Netherlands. The papers give an overview of our experiences, methods, approaches, results and surprises in the process to developing scientifically underpinned climate products and services for various clients. Although the literature on interactions between society and climate science has grown over the past decade both with respect to policy-science framing in post-normal science (Storch et al 2011 J. Environ. Law Policy 1 1-15, van der Sluijs 2012 Nature and Culture 7 174-195), user-science framing (Berkhout et al 2014 Regional Environ. Change 14 879-93) and joint knowledge production (Hegger et al 2014 Regional Environ. Change 14 1049-62), there is still a lot to gain. With this focus issue we want to contribute to best practices in this quickly moving field between science and society.
Biodiversity of Terrestrial Vegetation during Past Warm Periods

NASA Astrophysics Data System (ADS)

Davies-Barnard, T.; Valdes, P. J.; Ridgwell, A.

2016-12-01

Previous modelling studies of vegetation have generally used a small number of plant functional types to understand how the terrestrial biosphere responds to climate changes. Whilst being useful for understanding first order climate feedbacks, this climate-envelope approach makes a lot of assumptions about past vegetation being very similar to modern. A trait-based method has the advantage for paleo modelling in that there are substantially less assumptions made. In a novel use of the trait-based dynamic vegetation model JeDi, forced with output from climate model HadCM3, we explore past biodiversity and vegetation carbon changes. We use JeDi to model an optimal 2000 combinations of fifteen different traits to enable assessment of the overall level of biodiversity as well as individual growth strategies. We assess the vegetation shifts and biodiversity changes in past greenhouse periods to better understand the impact on the terrestrial biosphere. This work provides original insights into the response of vegetation and terrestrial carbon to climate and hydrological changes in high carbon dioxide climates over time, including during the Late Permian and Cretaceous. We evaluate how the location of biodiversity hotspots and species richness in past greenhouse climates is different to the present day.
Local farmers' perceptions of climate change and local adaptive strategies: a case study from the Middle Yarlung Zangbo River Valley, Tibet, China.

PubMed

Li, Chunyan; Tang, Ya; Luo, Han; Di, Baofeng; Zhang, Liyun

2013-10-01

Climate change affects the productivity of agricultural ecosystems. Farmers cope with climate change based on their perceptions of changing climate patterns. Using a case study from the Middle Yarlung Zangbo River Valley, we present a new research framework that uses questionnaire and interview methods to compare local farmers' perceptions of climate change with the adaptive farming strategies they adopt. Most farmers in the valley believed that temperatures had increased in the last 30 years but did not note any changes in precipitation. Most farmers also reported sowing and harvesting hulless barley 10-15 days earlier than they were 20 years ago. In addition, farmers observed that plants were flowering and river ice was melting earlier in the season, but they did not perceive changes in plant germination, herbaceous vegetation growth, or other spring seasonal events. Most farmers noticed an extended fall season signified by delays in the freezing of rivers and an extended growing season for grassland vegetation. The study results showed that agricultural practices in the study area are still traditional; that is, local farmers' perceptions of climate change and their strategies to mitigate its impacts were based on indigenous knowledge and their own experiences. Adaptive strategies included adjusting planting and harvesting dates, changing crop species, and improving irrigation infrastructure. However, the farmers' decisions could not be fully attributed to their concerns about climate change. Local farming systems exhibit high adaptability to climate variability. Additionally, off-farm income has reduced the dependence of the farmers on agriculture, and an agricultural subsidy from the Chinese Central Government has mitigated the farmers' vulnerability. Nevertheless, it remains necessary for local farmers to build a system of adaptive climate change strategies that combines traditional experience and indigenous knowledge with scientific research and government polices as key factors.
Local Farmers' Perceptions of Climate Change and Local Adaptive Strategies: A Case Study from the Middle Yarlung Zangbo River Valley, Tibet, China

NASA Astrophysics Data System (ADS)

Li, Chunyan; Tang, Ya; Luo, Han; Di, Baofeng; Zhang, Liyun

2013-10-01

Climate change affects the productivity of agricultural ecosystems. Farmers cope with climate change based on their perceptions of changing climate patterns. Using a case study from the Middle Yarlung Zangbo River Valley, we present a new research framework that uses questionnaire and interview methods to compare local farmers' perceptions of climate change with the adaptive farming strategies they adopt. Most farmers in the valley believed that temperatures had increased in the last 30 years but did not note any changes in precipitation. Most farmers also reported sowing and harvesting hulless barley 10-15 days earlier than they were 20 years ago. In addition, farmers observed that plants were flowering and river ice was melting earlier in the season, but they did not perceive changes in plant germination, herbaceous vegetation growth, or other spring seasonal events. Most farmers noticed an extended fall season signified by delays in the freezing of rivers and an extended growing season for grassland vegetation. The study results showed that agricultural practices in the study area are still traditional; that is, local farmers' perceptions of climate change and their strategies to mitigate its impacts were based on indigenous knowledge and their own experiences. Adaptive strategies included adjusting planting and harvesting dates, changing crop species, and improving irrigation infrastructure. However, the farmers' decisions could not be fully attributed to their concerns about climate change. Local farming systems exhibit high adaptability to climate variability. Additionally, off-farm income has reduced the dependence of the farmers on agriculture, and an agricultural subsidy from the Chinese Central Government has mitigated the farmers' vulnerability. Nevertheless, it remains necessary for local farmers to build a system of adaptive climate change strategies that combines traditional experience and indigenous knowledge with scientific research and government polices as key factors.
Climate change adaptation options in rainfed upland cropping systems in the wet tropics: A case study of smallholder farms in North-West Cambodia.

PubMed

Touch, Van; Martin, Robert John; Scott, Jeannette Fiona; Cowie, Annette; Liu, De Li

2016-11-01

While climate change is confirmed to have serious impacts on agricultural production in many regions worldwide, researchers have proposed various measures that farmers can apply to cope with and adapt to those changes. However, it is often the case that not every adaptation measure would be practical and adoptable in a specific region. Farmers may have their own ways of managing and adapting to climate change that need to be taken into account when considering interventions. This study aimed to engage with farmers to: (1) better understand small-holder knowledge, attitudes and practices in relation to perceived or expected climate change; and (2) document cropping practices, climate change perceptions, constraints to crop production, and coping and adaptation options with existing climate variability and expected climate change. This study was conducted in 2015 in Sala Krau village near Pailin (12°52'N, 102°45'E) and Samlout (12°39'N, 102°36'E) of North-West Cambodia. The methods used were a combination of focus group discussions and one-on-one interviews where 132 farming households were randomly selected. We found that farmers were conscious of changes in climate over recent years, and had a good understanding of likely future changes. While farmers are aware of some practices that can be modified to minimize risk and cope with anticipated changes, they are reluctant to apply them. Furthermore; there are no government agricultural extension services provided at the village level and farmers have relied on each other and other actors in the value chain network for information to support their decision-making. There is a lack of knowledge of the principles of conservation agriculture that urgently require agricultural extension services in the region to build farmer ability to better cope and adapt to climate change. Copyright © 2016 Elsevier Ltd. All rights reserved.
The potential of exceptional climate change education on individual lifetime carbon emissions

NASA Astrophysics Data System (ADS)

Cordero, E.; Centeno, D.; Todd, A. M.

2016-12-01

Strategies to mitigate climate change often center on clean technologies such as electric vehicles and solar panels, while the mitigation potential of a quality educational experience is rarely discussed. We investigate the role of education on individual carbon emissions using case studies from an intensive one-year university general education course focused on climate science and solutions. Results from this analysis demonstrate that students who completed the university course had significantly lower carbon emissions compared to a control group. If such an educational experience could be expanded throughout the United States, we estimate that education could be as valuable a climate change mitigation method as improving the fuel efficiency of automobiles. Relatedly, we also report on a new approach to apply real-time cloud based data to track the environmental impact of students during their participation in educational climate change programs. Such a tool would help illustrate the potential of education as a viable carbon mitigation strategy.

Twitter Analytics: Are the U.S. Coastal Regions Prepared for Climate Change in 2017?

NASA Astrophysics Data System (ADS)

Singleton, S. L.; Kumar, S.

2017-12-01

According to the U.S. National Climate Assessment, the Southeast Coast and Gulf Coast of the United States are particularly susceptible to sea level rise, heat waves, hurricanes and less accessibility to clean water due to climate change. This is because of the extreme variation of topography in these two regions. Preparation for climate change consequences can only occur with conversation, which is a method of bringing awareness to the issue. Over the past decade, social media has taken over the spectrum of information exchange in the United States. Social Network Analysis (SNA) is a field that is emerging with the growth in popularity of social media. SNA is the practice of analyzing trends in volume and opinion of a population of social media users. Twitter, one popular social media platform, is one of the largest microblogging sites in the world, and it provides an abundance of data related to the trending topics such as climate change. Twitter analytics is a type of SNA performed on data from the tweets of Twitter users. In this work, Twitter analytics is performed on the data generated from the Twitter users in the United States, who were talking about climate change, global warming and/or CO2, over the course of one year (July 2016 - June 2017). Specifically, a regional comparative analysis on the coastal U.S. regions was conducted to recognize which region(s) is/are falling behind on the conversation about climate change. Sentiment analysis was also performed to understand the trends in opinion about climate change that vary over time. Experimental results determined that the southeast coast of the United States is deficient in their discussion about climate change compared to the other coastal regions. Igniting the conversation about this issue in these regions will mitigate the disasters due to climate change by increasing awareness in the people of these regions so they can properly prepare.
Evolutionary potential of upper thermal tolerance: biogeographic patterns and expectations under climate change.

PubMed

Diamond, Sarah E

2017-02-01

How will organisms respond to climate change? The rapid changes in global climate are expected to impose strong directional selection on fitness-related traits. A major open question then is the potential for adaptive evolutionary change under these shifting climates. At the most basic level, evolutionary change requires the presence of heritable variation and natural selection. Because organismal tolerances of high temperature place an upper bound on responding to temperature change, there has been a surge of research effort on the evolutionary potential of upper thermal tolerance traits. Here, I review the available evidence on heritable variation in upper thermal tolerance traits, adopting a biogeographic perspective to understand how heritability of tolerance varies across space. Specifically, I use meta-analytical models to explore the relationship between upper thermal tolerance heritability and environmental variability in temperature. I also explore how variation in the methods used to obtain these thermal tolerance heritabilities influences the estimation of heritable variation in tolerance. I conclude by discussing the implications of a positive relationship between thermal tolerance heritability and environmental variability in temperature and how this might influence responses to future changes in climate. © 2016 New York Academy of Sciences.
Notable shifting in the responses of vegetation activity to climate change in China

NASA Astrophysics Data System (ADS)

Chen, Aifang; He, Bin; Wang, Honglin; Huang, Ling; Zhu, Yunhua; Lv, Aifeng

The weakening relationship between inter-annual temperature variability and vegetation activity in the Northern Hemisphere over the last three decades has been reported by a recent study. However, how and to what extent vegetation activity responds to climate change in China is still unclear. We applied the Pearson correlation and partial correlation methods with a moving 15-y window to the GIMMS NDVI dataset from NOAA/AVHRR and observed climate data to examine the variation in the relationships between vegetation activity and climate variables. Results showed that there was an expanding negative response of vegetation growth to climate warming and a positive role of precipitation. The change patterns between NDVI and climate variables over vegetation types during the past three decades pointed an expending negative correlation between NDVI and temperature and a positive role of precipitation over most of the vegetation types (meadow, grassland, shrub, desert, cropland, and forest). Specifically, correlation between NDVI and temperature (PNDVI-T) have shifted from positive to negative in most of the station of temperature-limited areas with evergreen broadleaf forests, whereas precipitation-limited temperate grassland and desert were characterized by a positive PNDVI-P. This study contributes to ongoing investigations of the effects of climate change on vegetation activity. It is also of great importance for designing forest management strategies to cope with climate change.
The use of climate information to estimate future mortality from high ambient temperature: A systematic literature review.

PubMed

Sanderson, Michael; Arbuthnott, Katherine; Kovats, Sari; Hajat, Shakoor; Falloon, Pete

2017-01-01

Heat related mortality is of great concern for public health, and estimates of future mortality under a warming climate are important for planning of resources and possible adaptation measures. Papers providing projections of future heat-related mortality were critically reviewed with a focus on the use of climate model data. Some best practice guidelines are proposed for future research. The electronic databases Web of Science and PubMed/Medline were searched for papers containing a quantitative estimate of future heat-related mortality. The search was limited to papers published in English in peer-reviewed journals up to the end of March 2017. Reference lists of relevant papers and the citing literature were also examined. The wide range of locations studied and climate data used prevented a meta-analysis. A total of 608 articles were identified after removal of duplicate entries, of which 63 were found to contain a quantitative estimate of future mortality from hot days or heat waves. A wide range of mortality models and climate model data have been used to estimate future mortality. Temperatures in the climate simulations used in these studies were projected to increase. Consequently, all the papers indicated that mortality from high temperatures would increase under a warming climate. The spread in projections of future climate by models adds substantial uncertainty to estimates of future heat-related mortality. However, many studies either did not consider this source of uncertainty, or only used results from a small number of climate models. Other studies showed that uncertainty from changes in populations and demographics, and the methods for adaptation to warmer temperatures were at least as important as climate model uncertainty. Some inconsistencies in the use of climate data (for example, using global mean temperature changes instead of changes for specific locations) and interpretation of the effects on mortality were apparent. Some factors which have not been considered when estimating future mortality are summarised. Most studies have used climate data generated using scenarios with medium and high emissions of greenhouse gases. More estimates of future mortality using climate information from the mitigation scenario RCP2.6 are needed, as this scenario is the only one under which the Paris Agreement to limit global warming to 2°C or less could be realised. Many of the methods used to combine modelled data with local climate observations are simplistic. Quantile-based methods might offer an improved approach, especially for temperatures at the ends of the distributions. The modelling of adaptation to warmer temperatures in mortality models is generally arbitrary and simplistic, and more research is needed to better quantify adaptation. Only a small number of studies included possible changes in population and demographics in their estimates of future mortality, meaning many estimates of mortality could be biased low. Uncertainty originating from establishing a mortality baseline, climate projections, adaptation and population changes is important and should be considered when estimating future mortality.
Surface mass balance model evaluation from satellite and airborne lidar mapping

NASA Astrophysics Data System (ADS)

Sutterley, T. C.; Velicogna, I.; Fettweis, X.; van den Broeke, M. R.

2016-12-01

We present estimates of Greenland Ice Sheet (GrIS) surface elevation change from a novel combination of satellite and airborne laser altimetry measurements. Our method combines measurements from the Airborne Topographic Mapper (ATM), the Land, Vegetation and Ice Sensor (LVIS) and ICESat-1 to generate elevation change rates at high spatial resolution. This method allows to extend the records of each instrument, increases the overall spatial coverage compared to a single instrument, and produces high-quality, coherent maps of surface elevation change. In addition by combining the lidar datasets, we are able to investigate seasonal and interannual surface elevation change for years where Spring and Fall Operation IceBridge campaigns are available. We validate our method by comparing with the standard NSIDC elevation change product calculated using overlapping Level-1B ATM data. We use the altimetry-derived mass changes to evaluate the uncertainty in surface mass balance, particularly in the runoff component, from two Regional Climate Models (RCM's), the Regional Atmospheric Climate Model (RACMO) and the Modéle Atmosphérique Régional (MAR), and one Global Climate Model (GCM), MERRA2/GEOS-5. We investigate locations with low ice sheet surface velocities that are within the estimated ablation zones of each regional climate model. We find that the surface mass balance outputs from RACMO and MAR show good correspondence with mass changes derived from surface elevation changes over long periods. At two sites in Northeast Greenland (NEGIS), the MAR model has better correspondence with the altimetry estimate. We find that the differences at these locations are primarily due to the characterization of meltwater refreeze within the ice sheet.
Climate Change Impact Assessment of Food- and Waterborne Diseases.

PubMed

Semenza, Jan C; Herbst, Susanne; Rechenburg, Andrea; Suk, Jonathan E; Höser, Christoph; Schreiber, Christiane; Kistemann, Thomas

2012-04-01

The PubMed and ScienceDirect bibliographic databases were searched for the period of 1998-2009 to evaluate the impact of climatic and environmental determinants on food- and waterborne diseases. The authors assessed 1,642 short and concise sentences (key facts), which were extracted from 722 relevant articles and stored in a climate change knowledge base. Key facts pertaining to temperature, precipitation, water, and food for 6 selected pathogens were scrutinized, evaluated, and compiled according to exposure pathways. These key facts (corresponding to approximately 50,000 words) were mapped to 275 terminology terms identified in the literature, which generated 6,341 connections. These relationships were plotted on semantic network maps to examine the interconnections between variables. The risk of campylobacteriosis is associated with mean weekly temperatures, although this link is shown more strongly in the literature relating to salmonellosis. Irregular and severe rain events are associated with Cryptosporidium sp. outbreaks, while noncholera Vibrio sp. displays increased growth rates in coastal waters during hot summers. In contrast, for Norovirus and Listeria sp. the association with climatic variables was relatively weak, but much stronger for food determinants. Electronic data mining to assess the impact of climate change on food- and waterborne diseases assured a methodical appraisal of the field. This climate change knowledge base can support national climate change vulnerability, impact, and adaptation assessments and facilitate the management of future threats from infectious diseases. In the light of diminishing resources for public health this approach can help balance different climate change adaptation options.
Climate Change Impact Assessment of Food- and Waterborne Diseases

PubMed Central

Semenza, Jan C.; Herbst, Susanne; Rechenburg, Andrea; Suk, Jonathan E.; Höser, Christoph; Schreiber, Christiane; Kistemann, Thomas

2011-01-01

The PubMed and ScienceDirect bibliographic databases were searched for the period of 1998–2009 to evaluate the impact of climatic and environmental determinants on food- and waterborne diseases. The authors assessed 1,642 short and concise sentences (key facts), which were extracted from 722 relevant articles and stored in a climate change knowledge base. Key facts pertaining to temperature, precipitation, water, and food for 6 selected pathogens were scrutinized, evaluated, and compiled according to exposure pathways. These key facts (corresponding to approximately 50,000 words) were mapped to 275 terminology terms identified in the literature, which generated 6,341 connections. These relationships were plotted on semantic network maps to examine the interconnections between variables. The risk of campylobacteriosis is associated with mean weekly temperatures, although this link is shown more strongly in the literature relating to salmonellosis. Irregular and severe rain events are associated with Cryptosporidium sp. outbreaks, while noncholera Vibrio sp. displays increased growth rates in coastal waters during hot summers. In contrast, for Norovirus and Listeria sp. the association with climatic variables was relatively weak, but much stronger for food determinants. Electronic data mining to assess the impact of climate change on food- and waterborne diseases assured a methodical appraisal of the field. This climate change knowledge base can support national climate change vulnerability, impact, and adaptation assessments and facilitate the management of future threats from infectious diseases. In the light of diminishing resources for public health this approach can help balance different climate change adaptation options. PMID:24808720
Climate Change and Food Security: Health Impacts in Developed Countries

PubMed Central

Hooper, Lee; Abdelhamid, Asmaa; Bentham, Graham; Boxall, Alistair B.A.; Draper, Alizon; Fairweather-Tait, Susan; Hulme, Mike; Hunter, Paul R.; Nichols, Gordon; Waldron, Keith W.

2012-01-01

Background: Anthropogenic climate change will affect global food production, with uncertain consequences for human health in developed countries. Objectives: We investigated the potential impact of climate change on food security (nutrition and food safety) and the implications for human health in developed countries. Methods: Expert input and structured literature searches were conducted and synthesized to produce overall assessments of the likely impacts of climate change on global food production and recommendations for future research and policy changes. Results: Increasing food prices may lower the nutritional quality of dietary intakes, exacerbate obesity, and amplify health inequalities. Altered conditions for food production may result in emerging pathogens, new crop and livestock species, and altered use of pesticides and veterinary medicines, and affect the main transfer mechanisms through which contaminants move from the environment into food. All these have implications for food safety and the nutritional content of food. Climate change mitigation may increase consumption of foods whose production reduces greenhouse gas emissions. Impacts may include reduced red meat consumption (with positive effects on saturated fat, but negative impacts on zinc and iron intake) and reduced winter fruit and vegetable consumption. Developed countries have complex structures in place that may be used to adapt to the food safety consequences of climate change, although their effectiveness will vary between countries, and the ability to respond to nutritional challenges is less certain. Conclusions: Climate change will have notable impacts upon nutrition and food safety in developed countries, but further research is necessary to accurately quantify these impacts. Uncertainty about future impacts, coupled with evidence that climate change may lead to more variable food quality, emphasizes the need to maintain and strengthen existing structures and policies to regulate food production, monitor food quality and safety, and respond to nutritional and safety issues that arise. PMID:23124134
Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections.

PubMed

Junk, J; Ulber, B; Vidal, S; Eickermann, M

2015-11-01

Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.
Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections

NASA Astrophysics Data System (ADS)

Junk, J.; Ulber, B.; Vidal, S.; Eickermann, M.

2015-11-01

Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.
Ecoclimatic indicators to study crop suitability in present and future climatic conditionsTIC CONDITIONS

NASA Astrophysics Data System (ADS)

Caubel, Julie; Garcia de Cortazar Atauri, Inaki; Huard, Frédéric; Launay, Marie; Ripoche, Dominique; Gouache, David; Bancal, Marie-Odile; Graux, Anne-Isabelle; De Noblet, Nathalie

2013-04-01

Climate change is expected to affect both regional and global food production through changes in overall agroclimatic conditions. It is therefore necessary to develop simple tools of crop suitability diagnosis in a given area so that stakeholders can envisage land use adaptations under climate change conditions. The most common way to investigate potential impacts of climate on the evolution of agrosystems is to make use of an array of agroclimatic indicators, which provide synthetic information derived from climatic variables and calculated within fixed periods (i.e. January first - 31th July). However, the information obtained during these periods does not enable to take account of the plant response to climate. In this work, we present some results of the research program ORACLE (Opportunities and Risks of Agrosystems & forests in response to CLimate, socio-economic and policy changEs in France (and Europe). We proposed a suite of relevant ecoclimatic indicators, based on temperature and rainfall, in order to evaluate crop suitability for both present and new climatic conditions. Ecoclimatic indicators are agroclimatic indicators (e.g., grain heat stress) calculated during specific phenological phases so as to take account of the plant response to climate (e.g., the grain filling period, flowering- harvest). These indicators are linked with the ecophysiological processes they characterize (for e.g., the grain filling). To represent this methodology, we studied the suitability of winter wheat in future climatic conditions through three distinct French sites, Toulouse, Dijon and Versailles. Indicators have been calculated using climatic data from 1950 to 2100 simulated by the global climate model ARPEGE forced by a greenhouse effect corresponding to the SRES A1B scenario. The Quantile-Quantile downscaling method was applied to obtain data for the three locations. Phenological stages (emergence, ear 1 cm, flowering, beginning of grain filling and harvest) have been simulated by the STICS, CERES and PANORAMIX crop models with the same input climatic data. Results showed that phenological stages tend to be reached earlier in the future. Significant differences were noted between indicators calculated for invariable calendar periods and indicators calculated during phenological phases. Therefore, ecoclimatic indicators are relevant to provide accurate information about crop suitability in the context of climate change. Whereas most of the indicators do not indicate any significant changes in the future, plant mortality due to frost risks from emergence to ear 1 cm tends to decrease and water supply tends to be more limiting in the future. These indicators do not replace models but represent additional tools for understanding and spatializing some results obtained by models. Their use can provide a spatial distribution of crops according to their suitability in present or future climatic conditions and enable us to minimize the risk of crop failure. It would be interesting to consider the response uncertainties according to the uncertainties we have in future climatic predictions by using different greenhouse emission scenarios and downscaling methods.
Ecoclimatic indicators to study crop suitability in present and future climatic conditions

NASA Astrophysics Data System (ADS)

Caubel, Julie; Garcia de Cortazar Atauri, Inaki; Huard, Frédéric; Launay, Marie; Ripoche, Dominique; Gouache, David; Bancal, Marie-Odile; Graux, Anne-Isabelle; De Noblet, Nathalie

2013-04-01

Climate change is expected to affect both regional and global food production through changes in overall agroclimatic conditions. It is therefore necessary to develop simple tools of crop suitability diagnosis in a given area so that stakeholders can envisage land use adaptations under climate change conditions. The most common way to investigate potential impacts of climate on the evolution of agrosystems is to make use of an array of agroclimatic indicators, which provide synthetic information derived from climatic variables and calculated within fixed periods (i.e. January first - 31th July). However, the information obtained during these periods does not enable to take account of the plant response to climate. In this work, we present some results of the research program ORACLE (Opportunities and Risks of Agrosystems & forests in response to CLimate, socio-economic and policy changEs in France (and Europe). We proposed a suite of relevant ecoclimatic indicators, based on temperature and rainfall, in order to evaluate crop suitability for both present and new climatic conditions. Ecoclimatic indicators are agroclimatic indicators (e.g., grain heat stress) calculated during specific phenological phases so as to take account of the plant response to climate (e.g., the grain filling period, flowering- harvest). These indicators are linked with the ecophysiological processes they characterize (for e.g., the grain filling). To represent this methodology, we studied the suitability of winter wheat in future climatic conditions through three distinct French sites, Toulouse, Dijon and Versailles. Indicators have been calculated using climatic data from 1950 to 2100 simulated by the global climate model ARPEGE forced by a greenhouse effect corresponding to the SRES A1B scenario. The Quantile-Quantile downscaling method was applied to obtain data for the three locations. Phenological stages (emergence, ear 1 cm, flowering, beginning of grain filling and harvest) have been simulated by the STICS, CERES and PANORAMIX crop models with the same input climatic data. Results showed that phenological stages tend to be reached earlier in the future. Significant differences were noted between indicators calculated for invariable calendar periods and indicators calculated during phenological phases. Therefore, ecoclimatic indicators are relevant to provide accurate information about crop suitability in the context of climate change. Whereas most of the indicators do not indicate any significant changes in the future, plant mortality due to frost risks from emergence to ear 1 cm tends to decrease and water supply tends to be more limiting in the future. These indicators do not replace models but represent additional tools for understanding and spatializing some results obtained by models. Their use can provide a spatial distribution of crops according to their suitability in present or future climatic conditions and enable us to minimize the risk of crop failure. It would be interesting to consider the response uncertainties according to the uncertainties we have in future climatic predictions by using different greenhouse emission scenarios and downscaling methods.
Finding "Models" in Clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leung, Ruby

2017-05-01

Internationally recognized Climate Scientist Ruby Leung is a cloud gazer. But rather than looking for shapes, Ruby’s life’s calling is to develop regional atmospheric models to better predict and understand the effects of global climate change at scales relevant to humans and the environment. Ruby’s accomplishments include developing novel methods for modeling mountain clouds and precipitation in climate models, and improving understanding of hydroclimate variability and change. She also has led efforts to develop regional climate modeling capabilities in the Weather Research and Forecasting model that is widely adopted by scientists worldwide. Ruby is part of a team of PNNLmore » researchers studying the impacts of global warming.« less
Estimating farmers' willingness to pay for climate change adaptation: the case of the Malaysian agricultural sector.

PubMed

Masud, Muhammad Mehedi; Junsheng, Ha; Akhtar, Rulia; Al-Amin, Abul Quasem; Kari, Fatimah Binti

2015-02-01

This paper estimates Malaysian farmers' willingness to pay (WTP) for a planned adaptation programme for addressing climate issues in the Malaysian agricultural sector. We used the contingent valuation method (CVM) for a monetary valuation of farmers' preferences for a planned adaptation programme by ascertaining the value attached to address climatic issues in the Malaysian agricultural sector. Structured questionnaires were distributed among the sampled farmers. The study found that 74 % of respondents were willing to pay for a planned adaptation programme and that several socioeconomic and motivation factors have greater influence on their WTP. This paper clearly specifies the steps needed for all institutional bodies to better address issues in climate change. The outcomes of this paper will support policy makers to better design an efficient adaptation framework for adapting to the adverse impacts of climate change.
Climate change influences on marine infectious diseases: implications for management and society

USGS Publications Warehouse

Burge, Colleen A.; Eakin, C. Mark; Friedman, Carolyn S.; Froelich, Brett; Hershberger, Paul K.; Hofmann, Eileen E.; Petes, Laura E.; Prager, Katherine C.; Weil, Ernesto; Willis, Bette L.; Ford, Susan E.; Harvell, C. Drew

2014-01-01

Infectious diseases are common in marine environments, but the effects of a changing climate on marine pathogens are not well understood. Here, we focus on reviewing current knowledge about how the climate drives hostpathogen interactions and infectious disease outbreaks. Climate-related impacts on marine diseases are being documented in corals, shellfish, finfish, and humans; these impacts are less clearly linked to other organisms. Oceans and people are inextricably linked, and marine diseases can both directly and indirectly affect human health, livelihoods, and well-being. We recommend an adaptive management approach to better increase the resilience of ocean systems vulnerable to marine diseases in a changing climate. Land-based management methods of quarantining, culling, and vaccinating are not successful in the ocean; therefore, forecasting conditions that lead to outbreaks and designing tools/approaches to influence these conditions may be the best way to manage marine disease.
The use of EuroCordex in marine climate projections

NASA Astrophysics Data System (ADS)

Tinker, Jonathan; Palmer, Matthew; Lowe, Jason; Howard, Tom

2017-04-01

The Northwest European Shelf seas (NWS, including the North Sea, Irish Sea and Celtic Sea) are of economic, environmental and cultural importance to a number of European countries. However, their representation by global climate models (GCMs) is very crude, due to their inability to represent the complex geometry and the absence of tides. Therefore, there is a need to employ dynamical downscaling methods when considering the potential impacts of climate change on the European (and other) shelf seas. Using a shelf seas model to dynamically downscale of the ocean component of the GCM is a well established method. While taking open ocean lateral boundary conditions from the GCM ocean is acceptable, using surface flux forcings from the GCM atmosphere is often problematic. The CORDEX project provides an important dataset of high spatial and temporal resolution atmospheric forcings, derived from 'parent' CMIP5 GCM simulations. We drive the NEMO shelf seas model with data from CMIP5 models and EURO-CORDEX Regional Climate Model (RCM) data to produce a set of NWS climate projections. We require relatively high temporal resolution output, and run-off (for the river forcings), and so are limited to a subset of the available EURO-CORDEX RCMs. From these we select two CMIP5 GCMs with the same RCM with two emissions scenarios to give a minimum estimate of GCM model structural and emission scenario uncertainty. Other experiments allow an initial estimate of the uncertainty associated with the model structure of both the shelf seas and the RCM. Our analysis is focused on the uncertainty associated with the mean change in a number of physical marine impacts and the drivers of coastal variability and change, including sea level and the propagation of open ocean signals onto the shelf. Our work is part of the UK Climate Projections (UKCP18) and will inform the following UK Climate Change Risk Assessments, required as part of the Climate Change Act.
Climate change and wetland loss impacts on a Western river's water quality

NASA Astrophysics Data System (ADS)

Records, R. M.; Arabi, M.; Fassnacht, S. R.; Duffy, W. G.; Ahmadi, M.; Hegewisch, K. C.

2014-05-01

An understanding of potential stream water quality conditions under future climate is critical for the sustainability of ecosystems and protection of human health. Changes in wetland water balance under projected climate could alter wetland extent or cause wetland loss. This study assessed the potential climate-induced changes to in-stream sediment and nutrients loads in the historically snow melt-dominated Sprague River, Oregon, Western United States. Additionally, potential water quality impacts of combined changes in wetland water balance and wetland area under future climatic conditions were evaluated. The study utilized the Soil and Water Assessment Tool (SWAT) forced with statistical downscaling of general circulation model (GCM) data from the Coupled Model Intercomparison Project 5 (CMIP5) using the Multivariate Adaptive Constructed Analogs (MACA) method. Our findings suggest that in the Sprague River (1) mid-21st century nutrient and sediment loads could increase significantly during the high flow season under warmer-wetter climate projections, or could change only nominally in a warmer and somewhat drier future; (2) although water quality conditions under some future climate scenarios and no wetland loss may be similar to the past, the combined impact of climate change and wetland losses on nutrient loads could be large; (3) increases in stream total phosphorus (TP) concentration with wetland loss under future climate scenarios would be greatest at high-magnitude, low-probability flows; and (4) loss of riparian wetlands in both headwaters and lowlands could increase outlet TP loads to a similar degree, but this could be due to distinctly different mechanisms in different parts of the watershed.
Tree-species range shifts in a changing climate: detecting, modeling, assisting

Treesearch

Louis R. Iverson; Donald McKenzie

2013-01-01

In these times of rapidly changing climate, the science of detecting and modeling shifts in the ranges of tree species is advancing of necessity. We briefly review the current state of the science on several fronts. First, we review current and historical evidence for shifting ranges and migration. Next, we review two broad categories of methods, focused on the spatial...
Preliminary Steps Towards Integrating Climate and Land Use (ICLUS): the Development of Land-Use Scenarios Consistent with Climate Change Emissions Storylines (2008, External Review Draft)

EPA Science Inventory

This report was prepared by the Global Change Research Program (GCRP) in the National Center for Environmental Assessment (NCEA) of the Office of Research and Development (ORD) at the U.S. Environmental Protection Agency (EPA). This draft report is a description of the methods u...
Re-evaluating occupational heat stress in a changing climate.

PubMed

Spector, June T; Sheffield, Perry E

2014-10-01

The potential consequences of occupational heat stress in a changing climate on workers, workplaces, and global economies are substantial. Occupational heat stress risk is projected to become particularly high in middle- and low-income tropical and subtropical regions, where optimal controls may not be readily available. This commentary presents occupational heat stress in the context of climate change, reviews its impacts, and reflects on implications for heat stress assessment and control. Future efforts should address limitations of existing heat stress assessment methods and generate economical, practical, and universal approaches that can incorporate data of varying levels of detail, depending on resources. Validation of these methods should be performed in a wider variety of environments, and data should be collected and analyzed centrally for both local and large-scale hazard assessments and to guide heat stress adaptation planning. Heat stress standards should take into account variability in worker acclimatization, other vulnerabilities, and workplace resources. The effectiveness of controls that are feasible and acceptable should be evaluated. Exposure scientists are needed, in collaboration with experts in other areas, to effectively prevent and control occupational heat stress in a changing climate. © The Author 2014. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

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