Improving Climate and Achievement in a Troubled Urban High School through the Talent Development Model.

ERIC Educational Resources Information Center

McPartland, James; Balfanz, Robert; Jordan, Will; Legters, Nettie

1998-01-01

A case study of a large nonselective urban high school in Baltimore (Maryland) describes the design and implementation of a comprehensive package of school reforms, the Talent Development Model with Career Academies. Qualitative and quantitative evidence is provided on significant improvements in school climate, student attendance, promotion…

School Climate of Educational Institutions: Design and Validation of a Diagnostic Scale

ERIC Educational Resources Information Center

Becerra, Sandra

2016-01-01

School climate is recognized as a relevant factor for the improvement of educative processes, favoring the administrative processes and optimum school performance. The present article is the result of a quantitative research model which had the objective of psychometrically designing and validating a scale to diagnose the organizational climate of…

The Relationship between Work Engagement Behavior and Perceived Organizational Support and Organizational Climate

ERIC Educational Resources Information Center

Köse, Akif

2016-01-01

The purpose of this study is to examine the relationship between work engagement and perceived organizational support and organizational climate. The present study, in which quantitative methods have been used, is carried out in the relational screening model. Perceived organizational support scale, organizational climate scale, and work…

The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): Project framework

PubMed Central

Warszawski, Lila; Frieler, Katja; Huber, Veronika; Piontek, Franziska; Serdeczny, Olivia; Schewe, Jacob

2014-01-01

The Inter-Sectoral Impact Model Intercomparison Project offers a framework to compare climate impact projections in different sectors and at different scales. Consistent climate and socio-economic input data provide the basis for a cross-sectoral integration of impact projections. The project is designed to enable quantitative synthesis of climate change impacts at different levels of global warming. This report briefly outlines the objectives and framework of the first, fast-tracked phase of Inter-Sectoral Impact Model Intercomparison Project, based on global impact models, and provides an overview of the participating models, input data, and scenario set-up. PMID:24344316

Check-Up of Planet Earth at the Turn of the Millennium: Anticipated New Phase in Earth Sciences

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Ramanathan, V.

1998-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. In 1999, NASA's Earth Observing AM Satellite (EOS-AM) will repeat Langley's experiment, but for the entire planet, thus pioneering calibrated spectral observations from space. Conceived in response to real environmental problems, EOS-AM, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution of few kilometers on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-AM can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment.

Quantitative approaches in climate change ecology

PubMed Central

Brown, Christopher J; Schoeman, David S; Sydeman, William J; Brander, Keith; Buckley, Lauren B; Burrows, Michael; Duarte, Carlos M; Moore, Pippa J; Pandolfi, John M; Poloczanska, Elvira; Venables, William; Richardson, Anthony J

2011-01-01

Contemporary impacts of anthropogenic climate change on ecosystems are increasingly being recognized. Documenting the extent of these impacts requires quantitative tools for analyses of ecological observations to distinguish climate impacts in noisy data and to understand interactions between climate variability and other drivers of change. To assist the development of reliable statistical approaches, we review the marine climate change literature and provide suggestions for quantitative approaches in climate change ecology. We compiled 267 peer-reviewed articles that examined relationships between climate change and marine ecological variables. Of the articles with time series data (n = 186), 75% used statistics to test for a dependency of ecological variables on climate variables. We identified several common weaknesses in statistical approaches, including marginalizing other important non-climate drivers of change, ignoring temporal and spatial autocorrelation, averaging across spatial patterns and not reporting key metrics. We provide a list of issues that need to be addressed to make inferences more defensible, including the consideration of (i) data limitations and the comparability of data sets; (ii) alternative mechanisms for change; (iii) appropriate response variables; (iv) a suitable model for the process under study; (v) temporal autocorrelation; (vi) spatial autocorrelation and patterns; and (vii) the reporting of rates of change. While the focus of our review was marine studies, these suggestions are equally applicable to terrestrial studies. Consideration of these suggestions will help advance global knowledge of climate impacts and understanding of the processes driving ecological change.

Quantitative Temperature Reconstructions from Holocene and Late Glacial Lake Sediments in the Tropical Andes using Chironomidae (non-biting midges)

NASA Astrophysics Data System (ADS)

Matthews-Bird, F.; Gosling, W. D.; Brooks, S. J.; Montoya, E.; Coe, A. L.

2014-12-01

Chironomidae (non-biting midges) is a family of two-winged aquatic insects of the order Diptera. They are globally distributed and one of the most diverse families within aquatic ecosystems. The insects are stenotopic, and the rapid turnover of species and their ability to colonise quickly favourable habitats means chironomids are extremely sensitive to environmental change, notably temperature. Through the development of quantitative temperature inference models chironomids have become important palaeoecological tools. Proxies capable of generating independent estimates of past climate are crucial to disentangling climate signals and ecosystem response in the palaeoecological record. This project has developed the first modern environmental calibration data set in order to use chironomids from the Tropical Andes as quantitative climate proxies. Using surface sediments from c. 60 lakes from Bolivia, Peru and Ecuador we have developed an inference model capable of reconstructing temperatures, with a prediction error of 1-2°C, from fossil assemblages. Here we present the first Lateglacial and Holocene chironomid-inferred temperature reconstructions from two sites in the tropical Andes. The first record, from a high elevation (4153 m asl) lake in the Bolivian Andes, shows persistently cool temperatures for the past 15 kyr, punctuated by warm episodes in the early Holocene (9-10 kyr BP). The chironomid-inferred Holocene temperature trends from a lake sediment record on the eastern Andean flank of Ecuador (1248 m asl) spanning the last 5 millennia are synchronous with temperature changes in the NGRIP ice core record. The temperature estimates suggest along the eastern flank of the Andes, at lower latitudes (~1°S), climate closely resemble the well-established fluctuations of the Northern Hemisphere for this time period. Late-glacial climate fluctuations across South America are still disputed with some palaeoecological records suggesting evidence for Younger Dryas like events. Estimates from quantitative climate proxies such as chironomids will help constrain these patterns and further our understanding of climate teleconnections on Quaternary timescales.

Photosynthetic Control of Atmospheric Carbonyl Sulfide during the Growing Season

NASA Technical Reports Server (NTRS)

Campbell, J. Elliott; Carmichael, Gregory R.; Chai, T.; Mena-Carrasco, M.; Tang, Y.; Blake, D. R.; Blake, N. J.; Vay, Stephanie A.; Collatz, G. James; Baker, I.;

A Systems Approach to Climate, Water and Diarrhea in Hubli-Dharward, India

NASA Astrophysics Data System (ADS)

Mellor, J. E.; Zimmerman, J.

2014-12-01

Although evidence suggests that climate change will negatively impact water resources and hence diarrheal disease rates in the developing world, there is uncertainty surrounding prior studies. This is due to the complexity of the pathways by which climate impacts diarrhea rates making it difficult to develop interventions. Therefore, our goal was to develop a mechanistic systems approach that incorporates the complex climate, human, engineered and water systems to relate climate change to diarrhea rates under future climate scenarios.To do this, we developed an agent-based model (ABM). Our agents are households and children living in Hubli-Dharward, India. The model was informed with 15 months of weather, water quality, ethnographic and diarrhea incidence data. The model's front end is a stochastic weather simulator incorporating 15 global climate models to simulate rainfall and temperature. The water quality available to agents (residents) on a model "day" is a function of the simulated day's weather and is fully validated with field data. As with the field data, as the ambient temperature increases or it rains, the quality of water available to residents in the model deteriorates. The propensity for an resident to get diarrhea is calculated with an integrated Quantitative Microbial Risk Assessment model with uncertainty simulated with a bootstrap method. Other factors include hand-washing, improved water sources, household water treatment and improved sanitation.The benefits of our approach are as follows: Our mechanistic method allows us to develop scientifically derived adaptation strategies. We can quantitatively link climate scenarios with diarrhea incidence over long time periods. We can explore the complex climate and water system dynamics, rank risk factor importance, examine a broad range of scenarios and identify tipping points. Our approach is modular and expandable such that new datasets can be integrated to study climate impacts on a larger scale. Our results indicate that climate change will have a serious effect on diarrhea incidence in the region. However, adaptation strategies including more reliable water supplies and household water treatment can mitigate these impacts.

Rapid climate change and the rate of adaptation: insight from experimental quantitative genetics.

PubMed

Shaw, Ruth G; Etterson, Julie R

2012-09-01

Evolution proceeds unceasingly in all biological populations. It is clear that climate-driven evolution has molded plants in deep time and within extant populations. However, it is less certain whether adaptive evolution can proceed sufficiently rapidly to maintain the fitness and demographic stability of populations subjected to exceptionally rapid contemporary climate change. Here, we consider this question, drawing on current evidence on the rate of plant range shifts and the potential for an adaptive evolutionary response. We emphasize advances in understanding based on theoretical studies that model interacting evolutionary processes, and we provide an overview of quantitative genetic approaches that can parameterize these models to provide more meaningful predictions of the dynamic interplay between genetics, demography and evolution. We outline further research that can clarify both the adaptive potential of plant populations as climate continues to change and the role played by ongoing adaptation in their persistence. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.

Future climate scenarios and rainfall--runoff modelling in the Upper Gallego catchment (Spain).

PubMed

Bürger, C M; Kolditz, O; Fowler, H J; Blenkinsop, S

2007-08-01

Global climate change may have large impacts on water supplies, drought or flood frequencies and magnitudes in local and regional hydrologic systems. Water authorities therefore rely on computer models for quantitative impact prediction. In this study we present kernel-based learning machine river flow models for the Upper Gallego catchment of the Ebro basin. Different learning machines were calibrated using daily gauge data. The models posed two major challenges: (1) estimation of the rainfall-runoff transfer function from the available time series is complicated by anthropogenic regulation and mountainous terrain and (2) the river flow model is weak when only climate data are used, but additional antecedent flow data seemed to lead to delayed peak flow estimation. These types of models, together with the presented downscaled climate scenarios, can be used for climate change impact assessment in the Gallego, which is important for the future management of the system.

Pollen dispersal slows geographical range shift and accelerates ecological niche shift under climate change

PubMed Central

Aguilée, Robin; Raoul, Gaël; Rousset, François; Ronce, Ophélie

2016-01-01

Species may survive climate change by migrating to track favorable climates and/or adapting to different climates. Several quantitative genetics models predict that species escaping extinction will change their geographical distribution while keeping the same ecological niche. We introduce pollen dispersal in these models, which affects gene flow but not directly colonization. We show that plant populations may escape extinction because of both spatial range and ecological niche shifts. Exact analytical formulas predict that increasing pollen dispersal distance slows the expected spatial range shift and accelerates the ecological niche shift. There is an optimal distance of pollen dispersal, which maximizes the sustainable rate of climate change. These conclusions hold in simulations relaxing several strong assumptions of our analytical model. Our results imply that, for plants with long distance of pollen dispersal, models assuming niche conservatism may not accurately predict their future distribution under climate change. PMID:27621443

Pollen dispersal slows geographical range shift and accelerates ecological niche shift under climate change.

PubMed

Aguilée, Robin; Raoul, Gaël; Rousset, François; Ronce, Ophélie

2016-09-27

Species may survive climate change by migrating to track favorable climates and/or adapting to different climates. Several quantitative genetics models predict that species escaping extinction will change their geographical distribution while keeping the same ecological niche. We introduce pollen dispersal in these models, which affects gene flow but not directly colonization. We show that plant populations may escape extinction because of both spatial range and ecological niche shifts. Exact analytical formulas predict that increasing pollen dispersal distance slows the expected spatial range shift and accelerates the ecological niche shift. There is an optimal distance of pollen dispersal, which maximizes the sustainable rate of climate change. These conclusions hold in simulations relaxing several strong assumptions of our analytical model. Our results imply that, for plants with long distance of pollen dispersal, models assuming niche conservatism may not accurately predict their future distribution under climate change.

Evaluation of mean climate in a chemistry-climate model simulation

NASA Astrophysics Data System (ADS)

Hong, S.; Park, H.; Wie, J.; Park, R.; Lee, S.; Moon, B. K.

2017-12-01

Incorporation of the interactive chemistry is essential for understanding chemistry-climate interactions and feedback processes in climate models. Here we assess a newly developed chemistry-climate model (GRIMs-Chem), which is based on the Global/Regional Integrated Model system (GRIMs) including the aerosol direct effect as well as stratospheric linearized ozone chemistry (LINOZ). We conducted GRIMs-Chem with observed sea surface temperature during the period of 1979-2010, and compared the simulation results with observations and also with CMIP models. To measure the relative performance of our model, we define the quantitative performance metric using the Taylor diagram. This metric allow us to assess overall features in simulating multiple variables. Overall, our model better reproduce the zonal mean spatial pattern of temperature, horizontal wind, vertical motion, and relative humidity relative to other models. However, the model did not produce good simulations at upper troposphere (200 hPa). It is currently unclear which model processes are responsible for this. AcknowledgementsThis research was supported by the Korea Ministry of Environment (MOE) as "Climate Change Correspondence Program."

Projected changes to growth and mortality of Hawaiian corals over the next 100 years.

PubMed

Hoeke, Ron K; Jokiel, Paul L; Buddemeier, Robert W; Brainard, Russell E

2011-03-29

Recent reviews suggest that the warming and acidification of ocean surface waters predicated by most accepted climate projections will lead to mass mortality and declining calcification rates of reef-building corals. This study investigates the use of modeling techniques to quantitatively examine rates of coral cover change due to these effects. Broad-scale probabilities of change in shallow-water scleractinian coral cover in the Hawaiian Archipelago for years 2000-2099 A.D. were calculated assuming a single middle-of-the-road greenhouse gas emissions scenario. These projections were based on ensemble calculations of a growth and mortality model that used sea surface temperature (SST), atmospheric carbon dioxide (CO(2)), observed coral growth (calcification) rates, and observed mortality linked to mass coral bleaching episodes as inputs. SST and CO(2) predictions were derived from the World Climate Research Programme (WCRP) multi-model dataset, statistically downscaled with historical data. The model calculations illustrate a practical approach to systematic evaluation of climate change effects on corals, and also show the effect of uncertainties in current climate predictions and in coral adaptation capabilities on estimated changes in coral cover. Despite these large uncertainties, this analysis quantitatively illustrates that a large decline in coral cover is highly likely in the 21(st) Century, but that there are significant spatial and temporal variances in outcomes, even under a single climate change scenario.

Projected changes to growth and mortality of Hawaiian corals over the next 100 years

USGS Publications Warehouse

Hoeke, R.K.; Jokiel, P.L.; Buddemeier, R.W.; Brainard, R.E.

2011-01-01

Background: Recent reviews suggest that the warming and acidification of ocean surface waters predicated by most accepted climate projections will lead to mass mortality and declining calcification rates of reef-building corals. This study investigates the use of modeling techniques to quantitatively examine rates of coral cover change due to these effects. Methodology/Principal Findings: Broad-scale probabilities of change in shallow-water scleractinian coral cover in the Hawaiian Archipelago for years 2000-2099 A.D. were calculated assuming a single middle-of-the-road greenhouse gas emissions scenario. These projections were based on ensemble calculations of a growth and mortality model that used sea surface temperature (SST), atmospheric carbon dioxide (CO2), observed coral growth (calcification) rates, and observed mortality linked to mass coral bleaching episodes as inputs. SST and CO2 predictions were derived from the World Climate Research Programme (WCRP) multi-model dataset, statistically downscaled with historical data. Conclusions/Significance: The model calculations illustrate a practical approach to systematic evaluation of climate change effects on corals, and also show the effect of uncertainties in current climate predictions and in coral adaptation capabilities on estimated changes in coral cover. Despite these large uncertainties, this analysis quantitatively illustrates that a large decline in coral cover is highly likely in the 21st Century, but that there are significant spatial and temporal variances in outcomes, even under a single climate change scenario.

Warm Mediterranean mid-Holocene summers inferred from fossil midge assemblages

NASA Astrophysics Data System (ADS)

Samartin, Stéphanie; Heiri, Oliver; Joos, Fortunat; Renssen, Hans; Franke, Jörg; Brönnimann, Stefan; Tinner, Willy

2017-02-01

Understanding past climate trends is key for reliable projections of global warming and associated risks and hazards. Uncomfortably large discrepancies between vegetation-based summer temperature reconstructions (mainly based on pollen) and climate model results have been reported for the current interglacial, the Holocene. For the Mediterranean region these reconstructions indicate cooler-than-present mid-Holocene summers, in contrast with expectations based on climate models and long-term changes in summer insolation. We present new quantitative and replicated Holocene summer temperature reconstructions based on fossil chironomid midges from the northern central Mediterranean region. The Holocene thermal maximum is reconstructed 9,000-5,000 years ago and estimated to have been 1-2 °C warmer in mean July temperature than the recent pre-industrial period, consistent with glacier and marine records, and with transient climate model runs. This combined evidence implies that widely used pollen-based summer temperature reconstructions in the Mediterranean area are significantly biased by precipitation or other forcings such as early land use. Our interpretation can resolve the previous discrepancy between climate models and quantitative palaeotemperature records for millennial-scale Holocene summer temperature trends in the Mediterranean region. It also suggests that pollen-based evidence for cool mid-Holocene summers in other semi-arid to arid regions of the Northern Hemisphere may have to be reconsidered, with potential implications for global-scale reconstructions.

Human and climate impact on global riverine water and sediment fluxes - a distributed analysis

NASA Astrophysics Data System (ADS)

Cohen, S.; Kettner, A.; Syvitski, J. P.

2013-05-01

Understanding riverine water and sediment dynamics is an important undertaking for both socially-relevant issues such as agriculture, water security and infrastructure management and for scientific analysis of climate, landscapes, river ecology, oceanography and other disciplines. Providing good quantitative and predictive tools in therefore timely particularly in light of predicted climate and landuse changes. The intensity and dynamics between man-made and climatic factors vary widely across the globe and are therefore hard to predict. Using sophisticated numerical models is therefore warranted. Here we use a distributed global riverine sediment and water discharge model (WBMsed) to simulate human and climate effect on our planet's large rivers.

The Quaternary fossil-pollen record and global change

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

Grimm, E.C.

Fossil pollen provide one of the most valuable records of vegetation and climate change during the recent geological past. Advantages of the fossil-pollen record are that deposits containing fossil pollen are widespread, especially in areas having natural lakes, that fossil pollen occurs in continuous stratigraphic sequences spanning millennia, and that fossil pollen occurs in quantitative assemblages permitting a multivariate approach for reconstructing past vegetation and climates. Because of stratigraphic continuity, fossil pollen records climate cycles on a wide range of scales, from annual to the 100 ka Milankovitch cycles. Receiving particular emphasis recently are decadal to century scale changes, possiblemore » from the sediments of varved lakes, and late Pleistocene events on a 5--10 ka scale possibly correlating with the Heinrich events in the North Atlantic marine record or the Dansgaard-Oeschger events in the Greenland ice-core record. Researchers have long reconstructed vegetation and climate by qualitative interpretation of the fossil-pollen record. Recently quantitative interpretation has developed with the aid of large fossil-pollen databases and sophisticated numerical models. In addition, fossil pollen are important climate proxy data for validating General Circulation Models, which are used for predicting the possible magnitude future climate change. Fossil-pollen data also contribute to an understanding of ecological issues associated with global climate change, including questions of how and how rapidly ecosystems might respond to abrupt climate change.« less

Contribution of physical modelling to climate-driven landslide hazard mapping: an alpine test site

NASA Astrophysics Data System (ADS)

Vandromme, R.; Desramaut, N.; Baills, A.; Hohmann, A.; Grandjean, G.; Sedan, O.; Mallet, J. P.

2012-04-01

The aim of this work is to develop a methodology for integrating climate change scenarios into quantitative hazard assessment and especially their precipitation component. The effects of climate change will be different depending on both the location of the site and the type of landslide considered. Indeed, mass movements can be triggered by different factors. This paper describes a methodology to address this issue and shows an application on an alpine test site. Mechanical approaches represent a solution for quantitative landslide susceptibility and hazard modeling. However, as the quantity and the quality of data are generally very heterogeneous at a regional scale, it is necessary to take into account the uncertainty in the analysis. In this perspective, a new hazard modeling method is developed and integrated in a program named ALICE. This program integrates mechanical stability analysis through a GIS software taking into account data uncertainty. This method proposes a quantitative classification of landslide hazard and offers a useful tool to gain time and efficiency in hazard mapping. However, an expertise approach is still necessary to finalize the maps. Indeed it is the only way to take into account some influent factors in slope stability such as heterogeneity of the geological formations or effects of anthropic interventions. To go further, the alpine test site (Barcelonnette area, France) is being used to integrate climate change scenarios into ALICE program, and especially their precipitation component with the help of a hydrological model (GARDENIA) and the regional climate model REMO (Jacob, 2001). From a DEM, land-cover map, geology, geotechnical data and so forth the program classifies hazard zones depending on geotechnics and different hydrological contexts varying in time. This communication, realized within the framework of Safeland project, is supported by the European Commission under the 7th Framework Programme for Research and Technological Development, Area "Environment", Activity 1.3.3.1 "Prediction of triggering and risk assessment for landslides".

Tropospheric jet response to Antarctic ozone depletion: An update with Chemistry-Climate Model Initiative (CCMI) models

NASA Astrophysics Data System (ADS)

Son, Seok-Woo; Han, Bo-Reum; Garfinkel, Chaim I.; Kim, Seo-Yeon; Park, Rokjin; Abraham, N. Luke; Akiyoshi, Hideharu; Archibald, Alexander T.; Butchart, N.; Chipperfield, Martyn P.; Dameris, Martin; Deushi, Makoto; Dhomse, Sandip S.; Hardiman, Steven C.; Jöckel, Patrick; Kinnison, Douglas; Michou, Martine; Morgenstern, Olaf; O’Connor, Fiona M.; Oman, Luke D.; Plummer, David A.; Pozzer, Andrea; Revell, Laura E.; Rozanov, Eugene; Stenke, Andrea; Stone, Kane; Tilmes, Simone; Yamashita, Yousuke; Zeng, Guang

2018-05-01

The Southern Hemisphere (SH) zonal-mean circulation change in response to Antarctic ozone depletion is re-visited by examining a set of the latest model simulations archived for the Chemistry-Climate Model Initiative (CCMI) project. All models reasonably well reproduce Antarctic ozone depletion in the late 20th century. The related SH-summer circulation changes, such as a poleward intensification of westerly jet and a poleward expansion of the Hadley cell, are also well captured. All experiments exhibit quantitatively the same multi-model mean trend, irrespective of whether the ocean is coupled or prescribed. Results are also quantitatively similar to those derived from the Coupled Model Intercomparison Project phase 5 (CMIP5) high-top model simulations in which the stratospheric ozone is mostly prescribed with monthly- and zonally-averaged values. These results suggest that the ozone-hole-induced SH-summer circulation changes are robust across the models irrespective of the specific chemistry-atmosphere-ocean coupling.

The influence of climatic conditions on the heat balance of the human body

NASA Astrophysics Data System (ADS)

Blażejeczyk, Krzysztof; Krawczyk, Barbara

1991-06-01

The structure of heat exchange between the human body and its surroundings has been studied according to M.I. Budyko's model. Comparative measurements were carried out in the Polish Lakeland (maritime, temperate warm climate), in Central Mongolia (continental, temperate cool climate), and in the Kara Kum desert (dry subtropical climate). The results deal with the summer and early autumn seasons. The calculations indicate that the quantitative apportionment of various forms of heat exchange depend on specific weather conditions, which are typical for the distinguished climatic zones.

On the Hydrologic Adjustment of Climate-Model Projections: The Potential Pitfall of Potential Evapotranspiration

USGS Publications Warehouse

Milly, Paul C.D.; Dunne, Krista A.

2011-01-01

Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement ("downscaling"), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median -11%) caused by the hydrologic model’s apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen–Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors’ findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climate-change impacts on water.

Positive water vapour feedback in climate models confirmed by satellite data

NASA Technical Reports Server (NTRS)

Rind, D.; Lerner, J.; Chiou, E.-W.; Chu, W.; Larsen, J.; Mccormick, M. P.; Mcmaster, L.

1991-01-01

It has recently been suggested that GCMs used to evaluate climate change overestimate the greenhouse effect due to increased concentrations of trace gases in the atmosphere. Here, new satellite-generated water vapor data are used to compare summer and winter moisture values in regions of the middle and upper troposphere that have previously been difficult to observe with confidence. It is found that, as the hemispheres warm, increased convection leads to increased water vapor above 500 mbar in approximate quantitative agreement with results from current climate models. The same conclusion is reached by comparing the tropical western and eastern Pacific regions. Thus, water vapor feedback is not overestimated in models and should amplify the climate response to increased trace-gas concentrations.

A hybrid model to assess the impact of climate variability on streamflow for an ungauged mountainous basin

NASA Astrophysics Data System (ADS)

Wang, Chong; Xu, Jianhua; Chen, Yaning; Bai, Ling; Chen, Zhongsheng

2018-04-01

To quantitatively assess the impact of climate variability on streamflow in an ungauged mountainous basin is a difficult and challenging work. In this study, a hybrid model combing downscaling method based on earth data products, back propagation artificial neural networks (BPANN) and weights connection method was developed to explore an approach for solving this problem. To validate the applicability of the hybrid model, the Kumarik River and Toshkan River, two headwaters of the Aksu River, were employed to assess the impact of climate variability on streamflow by using this hybrid model. The conclusion is that the hybrid model presented a good performance, and the quantitative assessment results for the two headwaters are: (1) the precipitation respectively increased by 48.5 and 41.0 mm in the Kumarik catchment and Toshkan catchment, and the average annual temperature both increased by 0.1 °C in the two catchments during each decade from 1980 to 2012; (2) with the warming and wetting climate, the streamflow respectively increased 1.5 × 108 and 3.3 × 108 m3 per decade in the Kumarik River and the Toshkan River; and (3) the contribution of the temperature and precipitation to the streamflow, which were 64.01 ± 7.34, 35.99 ± 7.34 and 47.72 ± 8.10, 52.26 ± 8.10%, respectively in the Kumarik catchment and Toshkan catchment. Our study introduced a feasible hybrid model for the assessment of the impact of climate variability on streamflow, which can be used in the ungauged mountainous basin of Northwest China.

Extracting climate memory using Fractional Integrated Statistical Model: A new perspective on climate prediction

PubMed Central

Yuan, Naiming; Fu, Zuntao; Liu, Shida

2014-01-01

Long term memory (LTM) in climate variability is studied by means of fractional integral techniques. By using a recently developed model, Fractional Integral Statistical Model (FISM), we in this report proposed a new method, with which one can estimate the long-lasting influences of historical climate states on the present time quantitatively, and further extract the influence as climate memory signals. To show the usability of this method, two examples, the Northern Hemisphere monthly Temperature Anomalies (NHTA) and the Pacific Decadal Oscillation index (PDO), are analyzed in this study. We find the climate memory signals indeed can be extracted and the whole variations can be further decomposed into two parts: the cumulative climate memory (CCM) and the weather-scale excitation (WSE). The stronger LTM is, the larger proportion the climate memory signals will account for in the whole variations. With the climate memory signals extracted, one can at least determine on what basis the considered time series will continue to change. Therefore, this report provides a new perspective on climate prediction. PMID:25300777

Application of stakeholder-based and modelling approaches for supporting robust adaptation decision making under future climatic uncertainty and changing urban-agricultural water demand

NASA Astrophysics Data System (ADS)

Bhave, Ajay; Dessai, Suraje; Conway, Declan; Stainforth, David

2016-04-01

Deep uncertainty in future climate change and socio-economic conditions necessitates the use of assess-risk-of-policy approaches over predict-then-act approaches for adaptation decision making. Robust Decision Making (RDM) approaches embody this principle and help evaluate the ability of adaptation options to satisfy stakeholder preferences under wide-ranging future conditions. This study involves the simultaneous application of two RDM approaches; qualitative and quantitative, in the Cauvery River Basin in Karnataka (population ~23 million), India. The study aims to (a) determine robust water resources adaptation options for the 2030s and 2050s and (b) compare the usefulness of a qualitative stakeholder-driven approach with a quantitative modelling approach. For developing a large set of future scenarios a combination of climate narratives and socio-economic narratives was used. Using structured expert elicitation with a group of climate experts in the Indian Summer Monsoon, climatic narratives were developed. Socio-economic narratives were developed to reflect potential future urban and agricultural water demand. In the qualitative RDM approach, a stakeholder workshop helped elicit key vulnerabilities, water resources adaptation options and performance criteria for evaluating options. During a second workshop, stakeholders discussed and evaluated adaptation options against the performance criteria for a large number of scenarios of climatic and socio-economic change in the basin. In the quantitative RDM approach, a Water Evaluation And Planning (WEAP) model was forced by precipitation and evapotranspiration data, coherent with the climatic narratives, together with water demand data based on socio-economic narratives. We find that compared to business-as-usual conditions options addressing urban water demand satisfy performance criteria across scenarios and provide co-benefits like energy savings and reduction in groundwater depletion, while options reducing agricultural water demand significantly affect downstream water availability. Water demand options demonstrate potential to improve environmental flow conditions and satisfy legal water supply requirements for downstream riparian states. On the other hand, currently planned large scale infrastructural projects demonstrate reduced value in certain scenarios, illustrating the impacts of lock-in effects of large scale infrastructure. From a methodological perspective, we find that while the stakeholder-driven approach revealed robust options in a resource-light manner and helped initiate much needed interaction amongst stakeholders, the modelling approach provides complementary quantitative information. The study reveals robust adaptation options for this important basin and provides a strong methodological basis for carrying out future studies that support adaptation decision making.

Integrating Science and Management to Assess Forest Ecosystem Vulnerability to Climate Change

Treesearch

Leslie A. Brandt; Patricia R. Butler; Stephen D. Handler; Maria K. Janowiak; P. Danielle Shannon; Christopher W. Swanston

2017-01-01

We developed the ecosystem vulnerability assessment approach (EVAA) to help inform potential adaptation actions in response to a changing climate. EVAA combines multiple quantitative models and expert elicitation from scientists and land managers. In each of eight assessment areas, a panel of local experts determined potential vulnerability of forest ecosystems to...

Humor Climate of the Primary Schools

ERIC Educational Resources Information Center

Sahin, Ahmet

2018-01-01

The aim of this study is to determine the opinions primary school administrators and teachers on humor climates in primary schools. The study was modeled as a convergent parallel design, one of the mixed methods. The data gathered from 253 administrator questionnaires, and 651 teacher questionnaires was evaluated for the quantitative part of the…

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

Bartholomew, M. J.

To improve the quantitative description of precipitation processes in climate models, the Atmospheric Radiation Measurement (ARM) Climate Research Facility deployed rain gauges located near disdrometers (DISD and VDIS data streams). This handbook deals specifically with the rain gauges that make the observations for the RAIN data stream. Other precipitation observations are made by the surface meteorology instrument suite (i.e., MET data stream).

Long-term changes in lower tropospheric baseline ozone concentrations: Comparing chemistry-climate models and observations at northern midlatitudes

NASA Astrophysics Data System (ADS)

Parrish, D. D.; Lamarque, J.-F.; Naik, V.; Horowitz, L.; Shindell, D. T.; Staehelin, J.; Derwent, R.; Cooper, O. R.; Tanimoto, H.; Volz-Thomas, A.; Gilge, S.; Scheel, H.-E.; Steinbacher, M.; Fröhlich, M.

2014-05-01

Two recent papers have quantified long-term ozone (O3) changes observed at northern midlatitude sites that are believed to represent baseline (here understood as representative of continental to hemispheric scales) conditions. Three chemistry-climate models (NCAR CAM-chem, GFDL-CM3, and GISS-E2-R) have calculated retrospective tropospheric O3 concentrations as part of the Atmospheric Chemistry and Climate Model Intercomparison Project and Coupled Model Intercomparison Project Phase 5 model intercomparisons. We present an approach for quantitative comparisons of model results with measurements for seasonally averaged O3 concentrations. There is considerable qualitative agreement between the measurements and the models, but there are also substantial and consistent quantitative disagreements. Most notably, models (1) overestimate absolute O3 mixing ratios, on average by 5 to 17 ppbv in the year 2000, (2) capture only 50% of O3 changes observed over the past five to six decades, and little of observed seasonal differences, and (3) capture 25 to 45% of the rate of change of the long-term changes. These disagreements are significant enough to indicate that only limited confidence can be placed on estimates of present-day radiative forcing of tropospheric O3 derived from modeled historic concentration changes and on predicted future O3 concentrations. Evidently our understanding of tropospheric O3, or the incorporation of chemistry and transport processes into current chemical climate models, is incomplete. Modeled O3 trends approximately parallel estimated trends in anthropogenic emissions of NOx, an important O3 precursor, while measured O3 changes increase more rapidly than these emission estimates.

Climate change impacts on tree ranges: model intercomparison facilitates understanding and quantification of uncertainty.

PubMed

Cheaib, Alissar; Badeau, Vincent; Boe, Julien; Chuine, Isabelle; Delire, Christine; Dufrêne, Eric; François, Christophe; Gritti, Emmanuel S; Legay, Myriam; Pagé, Christian; Thuiller, Wilfried; Viovy, Nicolas; Leadley, Paul

2012-06-01

Model-based projections of shifts in tree species range due to climate change are becoming an important decision support tool for forest management. However, poorly evaluated sources of uncertainty require more scrutiny before relying heavily on models for decision-making. We evaluated uncertainty arising from differences in model formulations of tree response to climate change based on a rigorous intercomparison of projections of tree distributions in France. We compared eight models ranging from niche-based to process-based models. On average, models project large range contractions of temperate tree species in lowlands due to climate change. There was substantial disagreement between models for temperate broadleaf deciduous tree species, but differences in the capacity of models to account for rising CO(2) impacts explained much of the disagreement. There was good quantitative agreement among models concerning the range contractions for Scots pine. For the dominant Mediterranean tree species, Holm oak, all models foresee substantial range expansion. © 2012 Blackwell Publishing Ltd/CNRS.

Topex/Poseidon: A United States/France mission. Oceanography from space: The oceans and climate

NASA Technical Reports Server (NTRS)

1992-01-01

The TOPEX/POSEIDON space mission, sponsored by NASA and France's space agency, the Centre National d'Etudes Spatiales (CNES), will give new observations of the Earth from space to gain a quantitative understanding of the role of ocean currents in climate change. Rising atmospheric concentrations of carbon dioxide and other 'greenhouse gases' produced as a result of human activities could generate a global warming, followed by an associated rise in sea level. The satellite will use radar altimetry to measure sea-surface height and will be tracked by three independent systems to yield accurate topographic maps over the dimensions of entire ocean basins. The satellite data, together with the Tropical Ocean and Global Atmosphere (TOGA) program and the World Ocean Circulation Experiment (WOCE) measurements, will be analyzed by an international scientific team. By merging the satellite observations with TOGA and WOCE findings, the scientists will establish the extensive data base needed for the quantitative description and computer modeling of ocean circulation. The ocean models will eventually be coupled with atmospheric models to lay the foundation for predictions of global climate change.

Integrated Research on the Development of Global Climate Risk Management Strategies - Framework and Initial Results of the Research Project ICA-RUS

NASA Astrophysics Data System (ADS)

Emori, Seita; Takahashi, Kiyoshi; Yamagata, Yoshiki; Oki, Taikan; Mori, Shunsuke; Fujigaki, Yuko

2013-04-01

With the aim of proposing strategies of global climate risk management, we have launched a five-year research project called ICA-RUS (Integrated Climate Assessment - Risks, Uncertainties and Society). In this project with the phrase "risk management" in its title, we aspire for a comprehensive assessment of climate change risks, explicit consideration of uncertainties, utilization of best available information, and consideration of every possible conditions and options. We also regard the problem as one of decision-making at the human level, which involves social value judgments and adapts to future changes in circumstances. The ICA-RUS project consists of the following five themes: 1) Synthesis of global climate risk management strategies, 2) Optimization of land, water and ecosystem uses for climate risk management, 3) Identification and analysis of critical climate risks, 4) Evaluation of climate risk management options under technological, social and economic uncertainties and 5) Interactions between scientific and social rationalities in climate risk management (see also: http://www.nies.go.jp/ica-rus/en/). For the integration of quantitative knowledge of climate change risks and responses, we apply a tool named AIM/Impact [Policy], which consists of an energy-economic model, a simplified climate model and impact projection modules. At the same time, in order to make use of qualitative knowledge as well, we hold monthly project meetings for the discussion of risk management strategies and publish annual reports based on the quantitative and qualitative information. To enhance the comprehensiveness of the analyses, we maintain an inventory of risks and risk management options. The inventory is revised iteratively through interactive meetings with stakeholders such as policymakers, government officials and industrial representatives.

New Observationally-Based Metrics for the Analysis of Coupled Climate Model and Earth System Model Simulations of the Southern Ocean

NASA Astrophysics Data System (ADS)

Russell, J. L.

2014-12-01

The exchange of heat and carbon dioxide between the atmosphere and ocean are major controls on Earth's climate under conditions of anthropogenic forcing. The Southern Ocean south of 30°S, occupying just over ¼ of the surface ocean area, accounts for a disproportionate share of the vertical exchange of properties between the deep and surface waters of the ocean and between the surface ocean and the atmosphere; thus this region can be disproportionately influential on the climate system. Despite the crucial role of the Southern Ocean in the climate system, understanding of the particular mechanisms involved remains inadequate, and the model studies underlying many of these results are highly controversial. As part of the overall goal of working toward reducing uncertainties in climate projections, we present an analysis using new data/model metrics based on a unified framework of theory, quantitative datasets, and numerical modeling. These new metrics quantify the mechanisms, processes, and tendencies relevant to the role of the Southern Ocean in climate.

Separating out the influence of climatic trend, fluctuations, and extreme events on crop yield: a case study in Hunan Province, China

NASA Astrophysics Data System (ADS)

Wang, Zhu; Shi, Peijun; Zhang, Zhao; Meng, Yongchang; Luan, Yibo; Wang, Jiwei

2017-09-01

Separating out the influence of climatic trend, fluctuations and extreme events on crop yield is of paramount importance to climate change adaptation, resilience, and mitigation. Previous studies lack systematic and explicit assessment of these three fundamental aspects of climate change on crop yield. This research attempts to separate out the impacts on rice yields of climatic trend (linear trend change related to mean value), fluctuations (variability surpassing the "fluctuation threshold" which defined as one standard deviation (1 SD) of the residual between the original data series and the linear trend value for each climatic variable), and extreme events (identified by absolute criterion for each kind of extreme events related to crop yield). The main idea of the research method was to construct climate scenarios combined with crop system simulation model. Comparable climate scenarios were designed to express the impact of each climate change component and, were input to the crop system model (CERES-Rice), which calculated the related simulated yield gap to quantify the percentage impacts of climatic trend, fluctuations, and extreme events. Six Agro-Meteorological Stations (AMS) in Hunan province were selected to study the quantitatively impact of climatic trend, fluctuations and extreme events involving climatic variables (air temperature, precipitation, and sunshine duration) on early rice yield during 1981-2012. The results showed that extreme events were found to have the greatest impact on early rice yield (-2.59 to -15.89%). Followed by climatic fluctuations with a range of -2.60 to -4.46%, and then the climatic trend (4.91-2.12%). Furthermore, the influence of climatic trend on early rice yield presented "trade-offs" among various climate variables and AMS. Climatic trend and extreme events associated with air temperature showed larger effects on early rice yield than other climatic variables, particularly for high-temperature events (-2.11 to -12.99%). Finally, the methodology use to separate out the influences of the climatic trend, fluctuations, and extreme events on crop yield was proved to be feasible and robust. Designing different climate scenarios and feeding them into a crop system model is a potential way to evaluate the quantitative impact of each climate variable.

On the hydrologic adjustment of climate-model projections: The potential pitfall of potential evapotranspiration

USGS Publications Warehouse

Milly, P.C.D.; Dunne, K.A.

2011-01-01

Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement ("downscaling"), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median 211%) caused by the hydrologic model's apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen-Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors' findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climatechange impacts on water. Copyright ?? 2011, Paper 15-001; 35,952 words, 3 Figures, 0 Animations, 1 Tables.

Check-Up of Planet Earth at the Turn of the Millennium: Contribution of EOS-Terra to a New Phase in Earth Sciences

NASA Technical Reports Server (NTRS)

Kaufman, Yoram

1999-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. In 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution of few kilometers on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical developments that brought to the Terra mission, its objectives and example of application to biomass burning.

Why Is Rainfall Error Analysis Requisite for Data Assimilation and Climate Modeling?

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.

2004-01-01

Given the large temporal and spatial variability of precipitation processes, errors in rainfall observations are difficult to quantify yet crucial to making effective use of rainfall data for improving atmospheric analysis, weather forecasting, and climate modeling. We highlight the need for developing a quantitative understanding of systematic and random errors in precipitation observations by examining explicit examples of how each type of errors can affect forecasts and analyses in global data assimilation. We characterize the error information needed from the precipitation measurement community and how it may be used to improve data usage within the general framework of analysis techniques, as well as accuracy requirements from the perspective of climate modeling and global data assimilation.

Climate Change and Future Pollen Allergy in Europe.

PubMed

Lake, Iain R; Jones, Natalia R; Agnew, Maureen; Goodess, Clare M; Giorgi, Filippo; Hamaoui-Laguel, Lynda; Semenov, Mikhail A; Solomon, Fabien; Storkey, Jonathan; Vautard, Robert; Epstein, Michelle M

2017-03-01

Globally, pollen allergy is a major public health problem, but a fundamental unknown is the likely impact of climate change. To our knowledge, this is the first study to quantify the consequences of climate change upon pollen allergy in humans. We produced quantitative estimates of the potential impact of climate change upon pollen allergy in humans, focusing upon common ragweed ( Ambrosia artemisiifolia ) in Europe. A process-based model estimated the change in ragweed's range under climate change. A second model simulated current and future ragweed pollen levels. These findings were translated into health burdens using a dose-response curve generated from a systematic review and from current and future population data. Models considered two different suites of regional climate/pollen models, two greenhouse gas emissions scenarios [Representative Concentration Pathways (RCPs) 4.5 and 8.5], and three different plant invasion scenarios. Our primary estimates indicated that sensitization to ragweed will more than double in Europe, from 33 to 77 million people, by 2041-2060. According to our projections, sensitization will increase in countries with an existing ragweed problem (e.g., Hungary, the Balkans), but the greatest proportional increases will occur where sensitization is uncommon (e.g., Germany, Poland, France). Higher pollen concentrations and a longer pollen season may also increase the severity of symptoms. Our model projections were driven predominantly by changes in climate (66%) but were also influenced by current trends in the spread of this invasive plant species. Assumptions about the rate at which ragweed spreads throughout Europe had a large influence upon the results. Our quantitative estimates indicate that ragweed pollen allergy will become a common health problem across Europe, expanding into areas where it is currently uncommon. Control of ragweed spread may be an important adaptation strategy in response to climate change. Citation: Lake IR, Jones NR, Agnew M, Goodess CM, Giorgi F, Hamaoui-Laguel L, Semenov MA, Solomon F, Storkey J, Vautard R, Epstein MM. 2017. Climate change and future pollen allergy in Europe. Environ Health Perspect 125:385-391; http://dx.doi.org/10.1289/EHP173.

Revealing, Reducing, and Representing Uncertainties in New Hydrologic Projections for Climate-changed Futures

NASA Astrophysics Data System (ADS)

Arnold, Jeffrey; Clark, Martyn; Gutmann, Ethan; Wood, Andy; Nijssen, Bart; Rasmussen, Roy

2016-04-01

The United States Army Corps of Engineers (USACE) has had primary responsibility for multi-purpose water resource operations on most of the major river systems in the U.S. for more than 200 years. In that time, the USACE projects and programs making up those operations have proved mostly robust against the range of natural climate variability encountered over their operating life spans. However, in some watersheds and for some variables, climate change now is known to be shifting the hydroclimatic baseline around which that natural variability occurs and changing the range of that variability as well. This makes historical stationarity an inappropriate basis for assessing continued project operations under climate-changed futures. That means new hydroclimatic projections are required at multiple scales to inform decisions about specific threats and impacts, and for possible adaptation responses to limit water-resource vulnerabilities and enhance operational resilience. However, projections of possible future hydroclimatologies have myriad complex uncertainties that require explicit guidance for interpreting and using them to inform those decisions about climate vulnerabilities and resilience. Moreover, many of these uncertainties overlap and interact. Recent work, for example, has shown the importance of assessing the uncertainties from multiple sources including: global model structure [Meehl et al., 2005; Knutti and Sedlacek, 2013]; internal climate variability [Deser et al., 2012; Kay et al., 2014]; climate downscaling methods [Gutmann et al., 2012; Mearns et al., 2013]; and hydrologic models [Addor et al., 2014; Vano et al., 2014; Mendoza et al., 2015]. Revealing, reducing, and representing these uncertainties is essential for defining the plausible quantitative climate change narratives required to inform water-resource decision-making. And to be useful, such quantitative narratives, or storylines, of climate change threats and hydrologic impacts must sample from the full range of uncertainties associated with all parts of the simulation chain, from global climate models with simulations of natural climate variability, through regional climate downscaling, and on to modeling of affected hydrologic processes and downstream water resources impacts. This talk will present part of the work underway now both to reveal and reduce some important uncertainties and to develop explicit guidance for future generation of quantitative hydroclimatic storylines. Topics will include: 1- model structural and parameter-set limitations of some methods widely used to quantify climate impacts to hydrologic processes [Gutmann et al., 2014; Newman et al., 2015]; 2- development and evaluation of new, spatially consistent, U.S. national-scale climate downscaling and hydrologic simulation capabilities directly relevant at the multiple scales of water-resource decision-making [Newman et al., 2015; Mizukami et al., 2015; Gutmann et al., 2016]; and 3- development and evaluation of advanced streamflow forecasting methods to reduce and represent integrated uncertainties in a tractable way [Wood et al., 2014; Wood et al., 2015]. A key focus will be areas where climatologic and hydrologic science is currently under-developed to inform decisions - or is perhaps wrongly scaled or misapplied in practice - indicating the need for additional fundamental science and interpretation.

A network-based approach for semi-quantitative knowledge mining and its application to yield variability

NASA Astrophysics Data System (ADS)

Schauberger, Bernhard; Rolinski, Susanne; Müller, Christoph

2016-12-01

Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. A systematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.

Long-Term Changes in Lower Tropospheric Baseline Ozone Concentrations:. [Comparing Chemistry-Climate Models and Observations at Northern Mid-Latitudes

NASA Technical Reports Server (NTRS)

Parrish, D. D.; Lamarque, J.-F.; Naik, V.; Horowitz, L.; Shindell, D. T.; Staehelin, J.; Derwent, R.; Cooper, O. R.; Tanimoto, H.; Volz-Thomas, A.;

What We Talk About When We Talk About Drought: Tree-ring Perspectives on Model-Data Comparisons in Hydroclimate Research

NASA Astrophysics Data System (ADS)

Cook, B.; Anchukaitis, K. J.

2017-12-01

Comparative analyses of paleoclimate reconstructions and climate model simulations can provide valuable insights into past and future climate events. Conducting meaningful and quantitative comparisons, however, can be difficult for a variety of reasons. Here, we use tree-ring based hydroclimate reconstructions to discuss some best practices for paleoclimate-model comparisons, highlighting recent studies that have successfully used this approach. These analyses have improved our understanding of the Medieval-era megadroughts, ocean forcing of large scale drought patterns, and even climate change contributions to future drought risk. Additional work is needed, however, to better reconcile and formalize uncertainties across observed, modeled, and reconstructed variables. In this regard, process based forward models of proxy-systems will likely be a critical tool moving forward.

Environmental determinants of tropical forest and savanna distribution: A quantitative model evaluation and its implication

NASA Astrophysics Data System (ADS)

Zeng, Zhenzhong; Chen, Anping; Piao, Shilong; Rabin, Sam; Shen, Zehao

2014-07-01

The distributions of tropical ecosystems are rapidly being altered by climate change and anthropogenic activities. One possible trend—the loss of tropical forests and replacement by savannas—could result in significant shifts in ecosystem services and biodiversity loss. However, the influence and the relative importance of environmental factors in regulating the distribution of tropical forest and savanna biomes are still poorly understood, which makes it difficult to predict future tropical forest and savanna distributions in the context of climate change. Here we use boosted regression trees to quantitatively evaluate the importance of environmental predictors—mainly climatic, edaphic, and fire factors—for the tropical forest-savanna distribution at a mesoscale across the tropics (between 15°N and 35°S). Our results demonstrate that climate alone can explain most of the distribution of tropical forest and savanna at the scale considered; dry season average precipitation is the single most important determinant across tropical Asia-Australia, Africa, and South America. Given the strong tendency of increased seasonality and decreased dry season precipitation predicted by global climate models, we estimate that about 28% of what is now tropical forest would likely be lost to savanna by the late 21st century under the future scenario considered. This study highlights the importance of climate seasonality and interannual variability in predicting the distribution of tropical forest and savanna, supporting the climate as the primary driver in the savanna biogeography.

Modelling the effects of past and future climate on the risk of bluetongue emergence in Europe

PubMed Central

Guis, Helene; Caminade, Cyril; Calvete, Carlos; Morse, Andrew P.; Tran, Annelise; Baylis, Matthew

2012-01-01

Vector-borne diseases are among those most sensitive to climate because the ecology of vectors and the development rate of pathogens within them are highly dependent on environmental conditions. Bluetongue (BT), a recently emerged arboviral disease of ruminants in Europe, is often cited as an illustration of climate's impact on disease emergence, although no study has yet tested this association. Here, we develop a framework to quantitatively evaluate the effects of climate on BT's emergence in Europe by integrating high-resolution climate observations and model simulations within a mechanistic model of BT transmission risk. We demonstrate that a climate-driven model explains, in both space and time, many aspects of BT's recent emergence and spread, including the 2006 BT outbreak in northwest Europe which occurred in the year of highest projected risk since at least 1960. Furthermore, the model provides mechanistic insight into BT's emergence, suggesting that the drivers of emergence across Europe differ between the South and the North. Driven by simulated future climate from an ensemble of 11 regional climate models, the model projects increase in the future risk of BT emergence across most of Europe with uncertainty in rate but not in trend. The framework described here is adaptable and applicable to other diseases, where the link between climate and disease transmission risk can be quantified, permitting the evaluation of scale and uncertainty in climate change's impact on the future of such diseases. PMID:21697167

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.

Smart climate ensemble exploring approaches: the example of climate impacts on air pollution in Europe.

NASA Astrophysics Data System (ADS)

Lemaire, Vincent; Colette, Augustin; Menut, Laurent

2016-04-01

Because of its sensitivity to weather patterns, climate change will have an impact on air pollution so that, in the future, a climate penalty could jeopardize the expected efficiency of air pollution mitigation measures. A common method to assess the impact of climate on air quality consists in implementing chemistry-transport models forced by climate projections. However, at present, such impact assessment lack multi-model ensemble approaches to address uncertainties because of the substantial computing cost. Therefore, as a preliminary step towards exploring large climate ensembles with air quality models, we developed an ensemble exploration technique in order to point out the climate models that should be investigated in priority. By using a training dataset from a deterministic projection of climate and air quality over Europe, we identified the main meteorological drivers of air quality for 8 regions in Europe and developed statistical models that could be used to estimate future air pollutant concentrations. Applying this statistical model to the whole EuroCordex ensemble of climate projection, we find a climate penalty for six subregions out of eight (Eastern Europe, France, Iberian Peninsula, Mid Europe and Northern Italy). On the contrary, a climate benefit for PM2.5 was identified for three regions (Eastern Europe, Mid Europe and Northern Italy). The uncertainty of this statistical model challenges limits however the confidence we can attribute to associated quantitative projections. This technique allows however selecting a subset of relevant regional climate model members that should be used in priority for future deterministic projections to propose an adequate coverage of uncertainties. We are thereby proposing a smart ensemble exploration strategy that can also be used for other impacts studies beyond air quality.

Multi-objective optimization for evaluation of simulation fidelity for precipitation, cloudiness and insolation in regional climate models

NASA Astrophysics Data System (ADS)

Lee, H.

2016-12-01

Precipitation is one of the most important climate variables that are taken into account in studying regional climate. Nevertheless, how precipitation will respond to a changing climate and even its mean state in the current climate are not well represented in regional climate models (RCMs). Hence, comprehensive and mathematically rigorous methodologies to evaluate precipitation and related variables in multiple RCMs are required. The main objective of the current study is to evaluate the joint variability of climate variables related to model performance in simulating precipitation and condense multiple evaluation metrics into a single summary score. We use multi-objective optimization, a mathematical process that provides a set of optimal tradeoff solutions based on a range of evaluation metrics, to characterize the joint representation of precipitation, cloudiness and insolation in RCMs participating in the North American Regional Climate Change Assessment Program (NARCCAP) and Coordinated Regional Climate Downscaling Experiment-North America (CORDEX-NA). We also leverage ground observations, NASA satellite data and the Regional Climate Model Evaluation System (RCMES). Overall, the quantitative comparison of joint probability density functions between the three variables indicates that performance of each model differs markedly between sub-regions and also shows strong seasonal dependence. Because of the large variability across the models, it is important to evaluate models systematically and make future projections using only models showing relatively good performance. Our results indicate that the optimized multi-model ensemble always shows better performance than the arithmetic ensemble mean and may guide reliable future projections.

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

Bartholomew, Mary Jane

To improve the quantitative description of precipitation processes in climate models, the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility deploys several types of rain gauges (MET, RAIN, and optical rain gauge [ORG] datastreams) as well as disdrometers (DISD and VDIS datastreams) at the Southern Great Plains (SGP) Site. This handbook deals specifically with the independent analog ORG (i.e., the ORG datastream).

Can increasing carbon dioxide cause climate change?

PubMed Central

Lindzen, Richard S.

1997-01-01

The realistic physical functioning of the greenhouse effect is reviewed, and the role of dynamic transport and water vapor is identified. Model errors and uncertainties are quantitatively compared with the forcing due to doubling CO2, and they are shown to be too large for reliable model evaluations of climate sensitivities. The possibility of directly measuring climate sensitivity is reviewed. A direct approach using satellite data to relate changes in globally averaged radiative flux changes at the top of the atmosphere to naturally occurring changes in global mean temperature is described. Indirect approaches to evaluating climate sensitivity involving the response to volcanic eruptions and Eocene climate change are also described. Finally, it is explained how, in principle, a climate that is insensitive to gross radiative forcing as produced by doubling CO2 might still be able to undergo major changes of the sort associated with ice ages and equable climates. PMID:11607742

Merging Methods to Manage Uncertainty: Combining Simulation Modeling and Scenario Planning to Inform Resource Management Under Climate Change

NASA Astrophysics Data System (ADS)

Miller, B. W.; Schuurman, G. W.; Symstad, A.; Fisichelli, N. A.; Frid, L.

2017-12-01

Managing natural resources in this era of anthropogenic climate change is fraught with uncertainties around how ecosystems will respond to management actions and a changing climate. Scenario planning (oftentimes implemented as a qualitative, participatory exercise for exploring multiple possible futures) is a valuable tool for addressing this challenge. However, this approach may face limits in resolving responses of complex systems to altered climate and management conditions, and may not provide the scientific credibility that managers often require to support actions that depart from current practice. Quantitative information on projected climate changes and ecological responses is rapidly growing and evolving, but this information is often not at a scale or in a form that is `actionable' for resource managers. We describe a project that sought to create usable information for resource managers in the northern Great Plains by combining qualitative and quantitative methods. In particular, researchers, resource managers, and climate adaptation specialists co-produced a simulation model in conjunction with scenario planning workshops to inform natural resource management in southwest South Dakota. Scenario planning for a wide range of resources facilitated open-minded thinking about a set of divergent and challenging, yet relevant and plausible, climate scenarios and management alternatives that could be implemented in the simulation. With stakeholder input throughout the process, we built a simulation of key vegetation types, grazing, exotic plants, fire, and the effects of climate and management on rangeland productivity and composition. By simulating multiple land management jurisdictions, climate scenarios, and management alternatives, the model highlighted important tradeoffs between herd sizes and vegetation composition, and between the short- versus long-term costs of invasive species management. It also identified impactful uncertainties related to the effects of fire and grazing on vegetation. Ultimately, this integrative and iterative approach yielded counter-intuitive and surprising findings, and resulted in a more tractable set of possible futures for resource management planning.

Climate-vegetation modelling and fossil plant data suggest low atmospheric CO2 in the late Miocene

NASA Astrophysics Data System (ADS)

Forrest, M.; Eronen, J. T.; Utescher, T.; Knorr, G.; Stepanek, C.; Lohmann, G.; Hickler, T.

2015-12-01

There is an increasing need to understand the pre-Quaternary warm climates, how climate-vegetation interactions functioned in the past, and how we can use this information to understand the present. Here we report vegetation modelling results for the Late Miocene (11-7 Ma) to study the mechanisms of vegetation dynamics and the role of different forcing factors that influence the spatial patterns of vegetation coverage. One of the key uncertainties is the atmospheric concentration of CO2 during past climates. Estimates for the last 20 million years range from 280 to 500 ppm. We simulated Late Miocene vegetation using two plausible CO2 concentrations, 280 ppm CO2 and 450 ppm CO2, with a dynamic global vegetation model (LPJ-GUESS) driven by climate input from a coupled AOGCM (Atmosphere-Ocean General Circulation Model). The simulated vegetation was compared to existing plant fossil data for the whole Northern Hemisphere. For the comparison we developed a novel approach that uses information of the relative dominance of different plant functional types (PFTs) in the palaeobotanical data to provide a quantitative estimate of the agreement between the simulated and reconstructed vegetation. Based on this quantitative assessment we find that pre-industrial CO2 levels are largely consistent with the presence of seasonal temperate forests in Europe (suggested by fossil data) and open vegetation in North America (suggested by multiple lines of evidence). This suggests that during the Late Miocene the CO2 levels have been relatively low, or that other factors that are not included in the models maintained the seasonal temperate forests and open vegetation.

Developing quantitative criteria to evaluate AOGCMs for application to regional climate assessments

NASA Astrophysics Data System (ADS)

Hayhoe, K.; Wake, C.; Bradbury, J.; Degaetano, A.; Hertel, A.

2006-12-01

Climate projections are the foundation for regional assessments of potential climate impacts. However, the soundness of regional assessments depends on the ability of global climate models to reproduce key processes responsible for regional climate trends. Here, we develop a systematic method to compare observed climate with historical atmosphere-ocean general circulation model (AOGCM) simulations, to assess the degree to which AOGCMs are able to reproduce regional circulation patterns. Applying this methodology to the U.S. Northeast (NE), we find that nearly all AOGCMs simulate a reasonable winter NAO pattern and seasonal positions of the Jet Stream and the East Coast Trough. However, not all models capture observed correlations between these circulation patterns and seasonal climate anomalies in the NE. Using only those AOGCMs that meet the criteria in each of these areas, we then develop projections of future climate change in the NE. The primary changes projected to occur over the next century - slightly greater temperature increases in summer than winter, and increases in winter precipitation - are consistent with projected trends in regional climate processes and are relatively independent of model or scale. These suggest confidence in the direction and potential range of the most notable regional climate trends, with the absolute magnitude of change depending on both the sensitivity of the climate system to human forcing as well as on human emissions over coming decades.

Quantifying streamflow change caused by forest disturbance at a large spatial scale: A single watershed study

NASA Astrophysics Data System (ADS)

Wei, Xiaohua; Zhang, Mingfang

2010-12-01

Climatic variability and forest disturbance are commonly recognized as two major drivers influencing streamflow change in large-scale forested watersheds. The greatest challenge in evaluating quantitative hydrological effects of forest disturbance is the removal of climatic effect on hydrology. In this paper, a method was designed to quantify respective contributions of large-scale forest disturbance and climatic variability on streamflow using the Willow River watershed (2860 km2) located in the central part of British Columbia, Canada. Long-term (>50 years) data on hydrology, climate, and timber harvesting history represented by equivalent clear-cutting area (ECA) were available to discern climatic and forestry influences on streamflow by three steps. First, effective precipitation, an integrated climatic index, was generated by subtracting evapotranspiration from precipitation. Second, modified double mass curves were developed by plotting accumulated annual streamflow against annual effective precipitation, which presented a much clearer picture of the cumulative effects of forest disturbance on streamflow following removal of climatic influence. The average annual streamflow changes that were attributed to forest disturbances and climatic variability were then estimated to be +58.7 and -72.4 mm, respectively. The positive (increasing) and negative (decreasing) values in streamflow change indicated opposite change directions, which suggest an offsetting effect between forest disturbance and climatic variability in the study watershed. Finally, a multivariate Autoregressive Integrated Moving Average (ARIMA) model was generated to establish quantitative relationships between accumulated annual streamflow deviation attributed to forest disturbances and annual ECA. The model was then used to project streamflow change under various timber harvesting scenarios. The methodology can be effectively applied to any large-scale single watershed where long-term data (>50 years) are available.

Late Eocene to early Oligocene quantitative paleotemperature record: Evidence from continental halite fluid inclusions

PubMed Central

Zhao, Yan-jun; Zhang, Hua; Liu, Cheng-lin; Liu, Bao-kun; Ma, Li-chun; Wang, Li-cheng

2014-01-01

Climate changes within Cenozoic extreme climate events such as the Paleocene–Eocene Thermal Maximum and the First Oligocene Glacial provide good opportunities to estimate the global climate trends in our present and future life. However, quantitative paleotemperatures data for Cenozoic climatic reconstruction are still lacking, hindering a better understanding of the past and future climate conditions. In this contribution, quantitative paleotemperatures were determined by fluid inclusion homogenization temperature (Th) data from continental halite of the first member of the Shahejie Formation (SF1; probably late Eocene to early Oligocene) in Bohai Bay Basin, North China. The primary textures of the SF1 halite typified by cumulate and chevron halite suggest halite deposited in a shallow saline water and halite Th can serve as an temperature proxy. In total, one-hundred-twenty-one Th data from primary and single-phase aqueous fluid inclusions with different depths were acquired by the cooling nucleation method. The results show that all Th range from 17.7°C to 50.7°C,with the maximum homogenization temperatures (ThMAX) of 50.5°C at the depth of 3028.04 m and 50.7°C at 3188.61 m, respectively. Both the ThMAX presented here are significantly higher than the highest temperature recorded in this region since 1954and agree with global temperature models for the year 2100 predicted by the Intergovernmental Panel on Climate Change. PMID:25047483

Reconstructing Climate Change: The Model-Data Ping-Pong

NASA Astrophysics Data System (ADS)

Stocker, T. F.

2017-12-01

When Cesare Emiliani, the father of paleoceanography, made the first attempts at a quantitative reconstruction of Pleistocene climate change in the early 1950s, climate models were not yet conceived. The understanding of paleoceanographic records was therefore limited, and scientists had to resort to plausibility arguments to interpret their data. With the advent of coupled climate models in the early 1970s, for the first time hypotheses about climate processes and climate change could be tested in a dynamically consistent framework. However, only a model hierarchy can cope with the long time scales and the multi-component physical-biogeochemical Earth System. There are many examples how climate models have inspired the interpretation of paleoclimate data on the one hand, and conversely, how data have questioned long-held concepts and models. In this lecture I critically revisit a few examples of this model-data ping-pong, such as the bipolar seesaw, the mid-Holocene greenhouse gas increase, millennial and rapid CO2 changes reconstructed from polar ice cores, and the interpretation of novel paleoceanographic tracers. These examples also highlight many of the still unsolved questions and provide guidance for future research. The combination of high-resolution paleoceanographic data and modeling has never been more relevant than today. It will be the key for an appropriate risk assessment of impacts on the Earth System that are already underway in the Anthropocene.

Modelling the influence of climate change on the chemical concentrations in the Baltic Sea region with the POPCYCLING-Baltic model.

PubMed

Kong, Deguo; MacLeod, Matthew; Cousins, Ian T

2014-09-01

The effect of projected future changes in temperature, wind speed, precipitation and particulate organic carbon on concentrations of persistent organic chemicals in the Baltic Sea regional environment is evaluated using the POPCYCLING-Baltic multimedia chemical fate model. Steady-state concentrations of hypothetical perfectly persistent chemicals with property combinations that encompass the entire plausible range for non-ionizing organic substances are modelled under two alternative climate change scenarios (IPCC A2 and B2) and compared to a baseline climate scenario. The contributions of individual climate parameters are deduced in model experiments in which only one of the four parameters is changed from the baseline scenario. Of the four selected climate parameters, temperature is the most influential, and wind speed is least. Chemical concentrations in the Baltic region are projected to change by factors of up to 3.0 compared to the baseline climate scenario. For chemicals with property combinations similar to legacy persistent organic pollutants listed by the Stockholm Convention, modelled concentration ratios between two climate change scenarios and the baseline scenario range from factors of 0.5 to 2.0. This study is a first step toward quantitatively assessing climate change-induced changes in the environmental concentrations of persistent organic chemicals in the Baltic Sea region. Copyright © 2014 Elsevier Ltd. All rights reserved.

A synthesis of sedimentary records of Australian environmental change during the last 2000 years

NASA Astrophysics Data System (ADS)

Tyler, J. J.; Karoly, D. J.; Gell, P.; Goodwin, I. D.

2013-12-01

Our understanding of Southern Hemispheric climate variability on multidecadal to multicentennial timescales is limited by a scarcity of quantitative, highly resolved climate records, a problem which is particularly manifest in Australia. To date there are no quantitative, annually resolved records from within continental Australia which extend further back in time than the most recent c. 300 years [Neukom and Gergis, 2012; PAGES 2k Consortium, 2013]. By contrast, a number of marine, lake, peat and speleothem sedimentary records exist, some of which span multiple millennia at sub-decadal resolution. Here we report a database of existing sedimentary records of environmental change in Australia [Freeman et al., 2011], of which 25 have sample resolutions < 100 years/sample and which span > 500 years in duration. The majority of these records are located in southeastern Australia, providing an invaluable resource with which to examine regional scale climate and environmental change. Although most of the records can not be quantitatively related to climate variability, Empirical Orthogonal Functions coupled with Monte Carlo iterative age modelling, demonstrate coherent patterns of environmental and ecological change. This coherency, as well as comparisons with a limited number of quantitative records, suggests that regional hydroclimatic changes were responsible for the observed patterns. Here, we discuss the implications of these findings with respect to Southern Hemisphere climate during the last 2000 years. In addition, we review the progress and potential of ongoing research in the region. References: Freeman, R., I. D. Goodwin, and T. Donovan (2011), Paleoclimate data synthesis and data base for the reconstruction of climate variability and impacts in NSW over the past 2000 years., Climate Futures Technical Report, 1/2011, 50 pages. Neukom, R., and J. Gergis (2012), Southern Hemisphere high-resolution palaeoclimate records of the last 2000 years, Holocene, 22(5), 501-524, doi:10.1177/0959683611427335. PAGES 2k Consortium (2013), Continental-scale temperature variability during the past two millennia, Nature Geoscience, 6, 339-346.

Drought impacts on ecosystem functions of the U.S. National Forests and Grasslands: Part I evaluation of a water and carbon balance model

Treesearch

Shanlei Sun; Ge Sun; Peter Caldwell; Steven G. McNulty; Erika Cohen; Jingfeng Xiao; Yang Zhang

2015-01-01

Understanding and quantitatively evaluating the regional impacts of climate change and variability (e.g., droughts) on forest ecosystem functions (i.e., water yield, evapotranspiration, and productivity) and services (e.g., fresh water supply and carbon sequestration) is of great importance for developing climate change adaptation strategies for National Forests and...

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

Li, Hongyi; Sivapalan, Murugesu; Tian, Fuqiang

Inspired by the Dunne diagram, the climatic and landscape controls on the partitioning of annual runoff into its various components (Hortonian and Dunne overland flow and subsurface stormflow) are assessed quantitatively, from a purely theoretical perspective. A simple distributed hydrologic model has been built sufficient to simulate the effects of different combinations of climate, soil, and topography on the runoff generation processes. The model is driven by a sequence of simple hypothetical precipitation events, for a large combination of climate and landscape properties, and hydrologic responses at the catchment scale are obtained through aggregation of grid-scale responses. It is found,more » first, that the water balance responses, including relative contributions of different runoff generation mechanisms, could be related to a small set of dimensionless similarity parameters. These capture the competition between the wetting, drying, storage, and drainage functions underlying the catchment responses, and in this way, provide a quantitative approximation of the conceptual Dunne diagram. Second, only a subset of all hypothetical catchment/climate combinations is found to be ‘‘behavioral,’’ in terms of falling sufficiently close to the Budyko curve, describing mean annual runoff as a function of climate aridity. Furthermore, these behavioral combinations are mostly consistent with the qualitative picture presented in the Dunne diagram, indicating clearly the commonality between the Budyko curve and the Dunne diagram. These analyses also suggest clear interrelationships amongst the ‘‘behavioral’’ climate, soil, and topography parameter combinations, implying these catchment properties may be constrained to be codependent in order to satisfy the Budyko curve.« less

Functional approach to exploring climatic and landscape controls of runoff generation: 1. Behavioral constraints on runoff volume

NASA Astrophysics Data System (ADS)

Li, Hong-Yi; Sivapalan, Murugesu; Tian, Fuqiang; Harman, Ciaran

2014-12-01

Inspired by the Dunne diagram, the climatic and landscape controls on the partitioning of annual runoff into its various components (Hortonian and Dunne overland flow and subsurface stormflow) are assessed quantitatively, from a purely theoretical perspective. A simple distributed hydrologic model has been built sufficient to simulate the effects of different combinations of climate, soil, and topography on the runoff generation processes. The model is driven by a sequence of simple hypothetical precipitation events, for a large combination of climate and landscape properties, and hydrologic responses at the catchment scale are obtained through aggregation of grid-scale responses. It is found, first, that the water balance responses, including relative contributions of different runoff generation mechanisms, could be related to a small set of dimensionless similarity parameters. These capture the competition between the wetting, drying, storage, and drainage functions underlying the catchment responses, and in this way, provide a quantitative approximation of the conceptual Dunne diagram. Second, only a subset of all hypothetical catchment/climate combinations is found to be "behavioral," in terms of falling sufficiently close to the Budyko curve, describing mean annual runoff as a function of climate aridity. Furthermore, these behavioral combinations are mostly consistent with the qualitative picture presented in the Dunne diagram, indicating clearly the commonality between the Budyko curve and the Dunne diagram. These analyses also suggest clear interrelationships amongst the "behavioral" climate, soil, and topography parameter combinations, implying these catchment properties may be constrained to be codependent in order to satisfy the Budyko curve.

Global Climate Models for the Classroom: The Educational Impact of Student Work with a Key Tool of Climate Scientists

NASA Astrophysics Data System (ADS)

Bush, D. F.; Sieber, R.; Seiler, G.; Chandler, M. A.; Chmura, G. L.

2017-12-01

Efforts to address climate change require public understanding of Earth and climate science. To meet this need, educators require instructional approaches and scientific technologies that overcome cultural barriers to impart conceptual understanding of the work of climate scientists. We compared student inquiry learning with now ubiquitous climate education toy models, data and tools against that which took place using a computational global climate model (GCM) from the National Aeronautics and Space Administration (NASA). Our study at McGill University and John Abbott College in Montreal, QC sheds light on how best to teach the research processes important to Earth and climate scientists studying atmospheric and Earth system processes but ill-understood by those outside the scientific community. We followed a pre/post, control/treatment experimental design that enabled detailed analysis and statistically significant results. Our research found more students succeed at understanding climate change when exposed to actual climate research processes and instruments. Inquiry-based education with a GCM resulted in significantly higher scores pre to post on diagnostic exams (quantitatively) and more complete conceptual understandings (qualitatively). We recognize the difficulty in planning and teaching inquiry with complex technology and we also found evidence that lectures support learning geared toward assessment exams.

Determining the predictors of innovation implementation in healthcare: a quantitative analysis of implementation effectiveness.

PubMed

Jacobs, Sara R; Weiner, Bryan J; Reeve, Bryce B; Hofmann, David A; Christian, Michael; Weinberger, Morris

2015-01-22

The failure rates for implementing complex innovations in healthcare organizations are high. Estimates range from 30% to 90% depending on the scope of the organizational change involved, the definition of failure, and the criteria to judge it. The innovation implementation framework offers a promising approach to examine the organizational factors that determine effective implementation. To date, the utility of this framework in a healthcare setting has been limited to qualitative studies and/or group level analyses. Therefore, the goal of this study was to quantitatively examine this framework among individual participants in the National Cancer Institute's Community Clinical Oncology Program using structural equation modeling. We examined the innovation implementation framework using structural equation modeling (SEM) among 481 physician participants in the National Cancer Institute's Community Clinical Oncology Program (CCOP). The data sources included the CCOP Annual Progress Reports, surveys of CCOP physician participants and administrators, and the American Medical Association Physician Masterfile. Overall the final model fit well. Our results demonstrated that not only did perceptions of implementation climate have a statistically significant direct effect on implementation effectiveness, but physicians' perceptions of implementation climate also mediated the relationship between organizational implementation policies and practices (IPP) and enrollment (p <0.05). In addition, physician factors such as CCOP PI status, age, radiological oncologists, and non-oncologist specialists significantly influenced enrollment as well as CCOP organizational size and structure, which had indirect effects on implementation effectiveness through IPP and implementation climate. Overall, our results quantitatively confirmed the main relationship postulated in the innovation implementation framework between IPP, implementation climate, and implementation effectiveness among individual physicians. This finding is important, as although the model has been discussed within healthcare organizations before, the studies have been predominately qualitative in nature and/or at the organizational level. In addition, our findings have practical applications. Managers looking to increase implementation effectiveness of an innovation should focus on creating an environment that physicians perceive as encouraging implementation. In addition, managers should consider instituting specific organizational IPP aimed at increasing positive perceptions of implementation climate. For example, IPP should include specific expectations, support, and rewards for innovation use.

Responses of leaf traits to climatic gradients: adaptive variation versus compositional shifts

NASA Astrophysics Data System (ADS)

Meng, T.-T.; Wang, H.; Harrison, S. P.; Prentice, I. C.; Ni, J.; Wang, G.

2015-09-01

Dynamic global vegetation models (DGVMs) typically rely on plant functional types (PFTs), which are assigned distinct environmental tolerances and replace one another progressively along environmental gradients. Fixed values of traits are assigned to each PFT; modelled trait variation along gradients is thus driven by PFT replacement. But empirical studies have revealed "universal" scaling relationships (quantitative trait variations with climate that are similar within and between species, PFTs and communities); and continuous, adaptive trait variation has been proposed to replace PFTs as the basis for next-generation DGVMs. Here we analyse quantitative leaf-trait variation on long temperature and moisture gradients in China with a view to understanding the relative importance of PFT replacement vs. continuous adaptive variation within PFTs. Leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC) and nitrogen content of dry matter were measured on all species at 80 sites ranging from temperate to tropical climates and from dense forests to deserts. Chlorophyll fluorescence traits and carbon, phosphorus and potassium contents were measured at 47 sites. Generalized linear models were used to relate log-transformed trait values to growing-season temperature and moisture indices, with or without PFT identity as a predictor, and to test for differences in trait responses among PFTs. Continuous trait variation was found to be ubiquitous. Responses to moisture availability were generally similar within and between PFTs, but biophysical traits (LA, SLA and LDMC) of forbs and grasses responded differently from woody plants. SLA and LDMC responses to temperature were dominated by the prevalence of evergreen PFTs with thick, dense leaves at the warm end of the gradient. Nutrient (N, P and K) responses to climate gradients were generally similar within all PFTs. Area-based nutrients generally declined with moisture; Narea and Karea declined with temperature, but Parea increased with temperature. Although the adaptive nature of many of these trait-climate relationships is understood qualitatively, a key challenge for modelling is to predict them quantitatively. Models must take into account that community-level responses to climatic gradients can be influenced by shifts in PFT composition, such as the replacement of deciduous by evergreen trees, which may run either parallel or counter to trait variation within PFTs. The importance of PFT shifts varies among traits, being important for biophysical traits but less so for physiological and chemical traits. Finally, models should take account of the diversity of trait values that is found in all sites and PFTs, representing the "pool" of variation that is locally available for the natural adaptation of ecosystem function to environmental change.

A Regional Climate Model Evaluation System based on contemporary Satellite and other Observations for Assessing Regional Climate Model Fidelity

NASA Astrophysics Data System (ADS)

Waliser, D. E.; Kim, J.; Mattman, C.; Goodale, C.; Hart, A.; Zimdars, P.; Lean, P.

2011-12-01

Evaluation of climate models against observations is an essential part of assessing the impact of climate variations and change on regionally important sectors and improving climate models. Regional climate models (RCMs) are of a particular concern. RCMs provide fine-scale climate needed by the assessment community via downscaling global climate model projections such as those contributing to the Coupled Model Intercomparison Project (CMIP) that form one aspect of the quantitative basis of the IPCC Assessment Reports. The lack of reliable fine-resolution observational data and formal tools and metrics has represented a challenge in evaluating RCMs. Recent satellite observations are particularly useful as they provide a wealth of information and constraints on many different processes within the climate system. Due to their large volume and the difficulties associated with accessing and using contemporary observations, however, these datasets have been generally underutilized in model evaluation studies. Recognizing this problem, NASA JPL and UCLA have developed the Regional Climate Model Evaluation System (RCMES) to help make satellite observations, in conjunction with in-situ and reanalysis datasets, more readily accessible to the regional modeling community. The system includes a central database (Regional Climate Model Evaluation Database: RCMED) to store multiple datasets in a common format and codes for calculating and plotting statistical metrics to assess model performance (Regional Climate Model Evaluation Tool: RCMET). This allows the time taken to compare model data with satellite observations to be reduced from weeks to days. RCMES is a component of the recent ExArch project, an international effort for facilitating the archive and access of massive amounts data for users using cloud-based infrastructure, in this case as applied to the study of climate and climate change. This presentation will describe RCMES and demonstrate its utility using examples from RCMs applied to the southwest US as well as to Africa based on output from the CORDEX activity. Application of RCMES to the evaluation of multi-RCM hindcast for CORDEX-Africa will be presented in a companion paper in A41.

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

Development and testing of transfer functions for generating quantitative climatic estimates from Australian pollen data

NASA Astrophysics Data System (ADS)

Cook, Ellyn J.; van der Kaars, Sander

2006-10-01

We review attempts to derive quantitative climatic estimates from Australian pollen data, including the climatic envelope, climatic indicator and modern analogue approaches, and outline the need to pursue alternatives for use as input to, or validation of, simulations by models of past, present and future climate patterns. To this end, we have constructed and tested modern pollen-climate transfer functions for mainland southeastern Australia and Tasmania using the existing southeastern Australian pollen database and for northern Australia using a new pollen database we are developing. After testing for statistical significance, 11 parameters were selected for mainland southeastern Australia, seven for Tasmania and six for northern Australia. The functions are based on weighted-averaging partial least squares regression and their predictive ability evaluated against modern observational climate data using leave-one-out cross-validation. Functions for summer, annual and winter rainfall and temperatures are most robust for southeastern Australia, while in Tasmania functions for minimum temperature of the coldest period, mean winter and mean annual temperature are the most reliable. In northern Australia, annual and summer rainfall and annual and summer moisture indexes are the strongest. The validation of all functions means all can be applied to Quaternary pollen records from these three areas with confidence. Copyright

Quantitative Estimation of the Climatic Effects of Carbon Transferred by International Trade.

PubMed

Wei, Ting; Dong, Wenjie; Moore, John; Yan, Qing; Song, Yi; Yang, Zhiyong; Yuan, Wenping; Chou, Jieming; Cui, Xuefeng; Yan, Xiaodong; Wei, Zhigang; Guo, Yan; Yang, Shili; Tian, Di; Lin, Pengfei; Yang, Song; Wen, Zhiping; Lin, Hui; Chen, Min; Feng, Guolin; Jiang, Yundi; Zhu, Xian; Chen, Juan; Wei, Xin; Shi, Wen; Zhang, Zhiguo; Dong, Juan; Li, Yexin; Chen, Deliang

2016-06-22

Carbon transfer via international trade affects the spatial pattern of global carbon emissions by redistributing emissions related to production of goods and services. It has potential impacts on attribution of the responsibility of various countries for climate change and formulation of carbon-reduction policies. However, the effect of carbon transfer on climate change has not been quantified. Here, we present a quantitative estimate of climatic impacts of carbon transfer based on a simple CO2 Impulse Response Function and three Earth System Models. The results suggest that carbon transfer leads to a migration of CO2 by 0.1-3.9 ppm or 3-9% of the rise in the global atmospheric concentrations from developed countries to developing countries during 1990-2005 and potentially reduces the effectiveness of the Kyoto Protocol by up to 5.3%. However, the induced atmospheric CO2 concentration and climate changes (e.g., in temperature, ocean heat content, and sea-ice) are very small and lie within observed interannual variability. Given continuous growth of transferred carbon emissions and their proportion in global total carbon emissions, the climatic effect of traded carbon is likely to become more significant in the future, highlighting the need to consider carbon transfer in future climate negotiations.

Global soil-climate-biome diagram: linking soil properties to climate and biota

NASA Astrophysics Data System (ADS)

Zhao, X.; Yang, Y.; Fang, J.

2017-12-01

As a critical component of the Earth system, soils interact strongly with both climate and biota and provide fundamental ecosystem services that maintain food, climate, and human security. Despite significant progress in digital soil mapping techniques and the rapidly growing quantity of observed soil information, quantitative linkages between soil properties, climate and biota at the global scale remain unclear. By compiling a large global soil database, we mapped seven major soil properties (bulk density [BD]; sand, silt and clay fractions; soil pH; soil organic carbon [SOC] density [SOCD]; and soil total nitrogen [STN] density [STND]) based on machine learning algorithms (regional random forest [RF] model) and quantitatively assessed the linkage between soil properties, climate and biota at the global scale. Our results demonstrated a global soil-climate-biome diagram, which improves our understanding of the strong correspondence between soils, climate and biomes. Soil pH decreased with greater mean annual precipitation (MAP) and lower mean annual temperature (MAT), and the critical MAP for the transition from alkaline to acidic soil pH decreased with decreasing MAT. Specifically, the critical MAP ranged from 400-500 mm when the MAT exceeded 10 °C but could decrease to 50-100 mm when the MAT was approximately 0 °C. SOCD and STND were tightly linked; both increased in accordance with lower MAT and higher MAP across terrestrial biomes. Global stocks of SOC and STN were estimated to be 788 ± 39.4 Pg (1015 g, or billion tons) and 63 ± 3.3 Pg in the upper 30-cm soil layer, respectively, but these values increased to 1654 ± 94.5 Pg and 133 ± 7.8 Pg in the upper 100-cm soil layer, respectively. These results reveal quantitative linkages between soil properties, climate and biota at the global scale, suggesting co-evolution of the soil, climate and biota under conditions of global environmental change.

Quantification of uncertainty in flood risk assessment for flood protection planning: a Bayesian approach

NASA Astrophysics Data System (ADS)

Dittes, Beatrice; Špačková, Olga; Ebrahimian, Negin; Kaiser, Maria; Rieger, Wolfgang; Disse, Markus; Straub, Daniel

2017-04-01

Flood risk estimates are subject to significant uncertainties, e.g. due to limited records of historic flood events, uncertainty in flood modeling, uncertain impact of climate change or uncertainty in the exposure and loss estimates. In traditional design of flood protection systems, these uncertainties are typically just accounted for implicitly, based on engineering judgment. In the AdaptRisk project, we develop a fully quantitative framework for planning of flood protection systems under current and future uncertainties using quantitative pre-posterior Bayesian decision analysis. In this contribution, we focus on the quantification of the uncertainties and study their relative influence on the flood risk estimate and on the planning of flood protection systems. The following uncertainty components are included using a Bayesian approach: 1) inherent and statistical (i.e. limited record length) uncertainty; 2) climate uncertainty that can be learned from an ensemble of GCM-RCM models; 3) estimates of climate uncertainty components not covered in 2), such as bias correction, incomplete ensemble, local specifics not captured by the GCM-RCM models; 4) uncertainty in the inundation modelling; 5) uncertainty in damage estimation. We also investigate how these uncertainties are possibly reduced in the future when new evidence - such as new climate models, observed extreme events, and socio-economic data - becomes available. Finally, we look into how this new evidence influences the risk assessment and effectivity of flood protection systems. We demonstrate our methodology for a pre-alpine catchment in southern Germany: the Mangfall catchment in Bavaria that includes the city of Rosenheim, which suffered significant losses during the 2013 flood event.

Check-Up of Planet Earth at the Turn of the Millennium Anticipated New Phase in Earth Sciences

NASA Technical Reports Server (NTRS)

Kaufman, Yoram

1999-01-01

Langley's remarkable solar and lunar spectra collected from mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. In 1999, NASA's Earth Observing AM Satellite named recently "Terra" (by Ms. Sasha Jones, a 17 year old student in St. Louis, MO) will repeat Langley's experiment, but for the entire planet, thus pioneering calibrated spectral observations from space. Conceived in response to real environmental problems, EOS-AM, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution of few kilometers on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-AM can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In this talk I shall a give a historical perspective for the need for this expensive mission, give examples of the science that we anticipate to achieve using Terra measurements and describe this exciting mission.

Professional Learning: A Fuzzy Logic-Based Modelling Approach

ERIC Educational Resources Information Center

Gravani, M. N.; Hadjileontiadou, S. J.; Nikolaidou, G. N.; Hadjileontiadis, L. J.

2007-01-01

Studies have suggested that professional learning is influenced by two key parameters, i.e., climate and planning, and their associated variables (mutual respect, collaboration, mutual trust, supportiveness, openness). In this paper, we applied analysis of the relationships between the proposed quantitative, fuzzy logic-based model and a series of…

Uncertainty Quantification in Climate Modeling and Projection

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

Qian, Yun; Jackson, Charles; Giorgi, Filippo

The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced (e.g., from the IPCC AR4 to AR5). With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change informationmore » for use in Vulnerability, Impact, and Adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty. The workshop aimed at providing participants, many of them from developing countries, information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer laboratory exercises employing software packages for Bayesian inference, Markov Chain Monte Carlo methods, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progress in quantitatively estimating uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales was also reviewed. The application of Uncertainty Quantification (UQ) concepts to coupled climate system models is still in its infancy. The Coupled Model Intercomparison Project (CMIP) multi-model ensemble currently represents the primary data for assessing reliability and uncertainties of climate change information. An alternative approach is to generate similar ensembles by perturbing parameters within a single-model framework. One of workshop’s objectives was to give participants a deeper understanding of these approaches within a Bayesian statistical framework. However, there remain significant challenges still to be resolved before UQ can be applied in a convincing way to climate models and their projections.« less

Potential effect of climate change on malaria transmission in Africa.

PubMed

Tanser, Frank C; Sharp, Brian; le Sueur, David

2003-11-29

Climate change is likely to affect transmission of vector-borne diseases such as malaria. We quantitatively estimated current malaria exposure and assessed the potential effect of projected climate scenarios on malaria transmission. We produced a spatiotemporally validated (against 3791 parasite surveys) model of Plasmodium falciparum malaria transmission in Africa. Using different climate scenarios from the Hadley Centre global climate model (HAD CM3) climate experiments, we projected the potential effect of climate change on transmission patterns. Our model showed sensitivity and specificity of 63% and 96%, respectively (within 1 month temporal accuracy), when compared with the parasite surveys. We estimate that on average there are 3.1 billion person-months of exposure (445 million people exposed) in Africa per year. The projected scenarios would estimate a 5-7% potential increase (mainly altitudinal) in malaria distribution with surprisingly little increase in the latitudinal extents of the disease by 2100. Of the overall potential increase (although transmission will decrease in some countries) of 16-28% in person-months of exposure (assuming a constant population), a large proportion will be seen in areas of existing transmission. The effect of projected climate change indicates that a prolonged transmission season is as important as geographical expansion in correct assessment of the effect of changes in transmission patterns. Our model constitutes a valid baseline against which climate scenarios can be assessed and interventions planned.

Developing a chironomid training set for western South America (South-Central Chile): potential for quantitative temperature reconstructions

NASA Astrophysics Data System (ADS)

Araneda, A.; Larocque-Tobler, I.; Torrejon, F.; Grosjean, M.; Jana-Pinninghoff, P.; Ortega, C.; Urrutia, R.

2012-12-01

Quantitative climate reconstructions of the last two millennia are a fundamental issue in order to compare the current trends in climate observed nowadays. At global scale most of the climate reconstructions have been developed for the Northern Hemisphere, while for the Southern Hemisphere quantitative reconstructions are very rare and very limited geographically. The recognition of such disparity has generated among other research initiatives the LOTRED-SA Long-Term climate Reconstruction and Dynamics of (southern) South America, a collaborative, high-resolution multi-proxy approach within the framework of the IGBP-PAGES program. In this context our work presents the results of a 50-lakes training set in Central-Southern Chile developed with the aim to generate a basis for quantitative chironomid-inferred temperature reconstructions for this part of the continent. Chironomids (Insecta: Diptera) are aquatic insects that develop a great proportion of their life cycle as larvae in aquatic ecosystems. Several studies, developed mainly in the Northern Hemisphere, have proven their usefulness in reconstructing past climate due to the larvae's relationship to temperature. The training set developed here includes lakes located between 34 and 48 S, covering a broad temperature (as latitudinal) gradient. The surface (0-1 cm) sediment of each lake was sampled and chironomids, organic matter and nutrient were analyzed. Water analyses included the measurement of 10 variables (AirT, WBT, WST, N-tot, P-tot, Fe, Na, pH among others). In order to identify the most important variables explaining the highest variance in the chironomid assemblages, ordinations analyses were performed. A preliminary DCA analysis indicated, according to the length of gradients smaller than 3 STD, that a linear model was more appropriate for further analysis. Hence a RDA analysis was applied to the environmental and species data, indicating that the most important variables to determine chironomid assemblages are water temperature (WST) and organic matter (OM). The statistical performances of the first model evaluated for WST were relatively weak (r2boot = 0.46, RMSEP=0.79) compared with other models. Nevertheless, the results indicate that temperature is still an important predictor of chironomid distribution and that by increasing the number of lakes in the environmental gradient will further increase the predictive performance and contribute to climate reconstruction in the region. Funding for this research is from Fondecyt project No. 11080158 and from de cooperation project CONICYT-SER-01 and CJRP 1001 between Switzerland and Chile. Partial funding of Fondecyt projects 1120765 and 1120807, is also acknowledged.

Resource management and operations in central North Dakota: Climate change scenario planning workshop summary November 12-13, 2015, Bismarck, ND

USGS Publications Warehouse

Fisichelli, Nicholas A.; Schuurman, Gregor; Symstad, Amy J.; Ray, Andrea; Friedman, Jonathan M.; Miller, Brian; Rowland, Erika

2016-01-01

The Scaling Climate Change Adaptation in the Northern Great Plains through Regional Climate Summaries and Local Qualitative-Quantitative Scenario Planning Workshops project synthesizes climate data into 3-5 distinct but plausible climate summaries for the northern Great Plains region; crafts quantitative summaries of these climate futures for two focal areas; and applies these local summaries by developing climate-resource-management scenarios through participatory workshops and, where possible, simulation models. The two focal areas are central North Dakota and southwest South Dakota (Figure 1). The primary objective of this project is to help resource managers and scientists in a focal area use scenario planning to make management and planning decisions based on assessments of critical future uncertainties.This report summarizes project work for public and tribal lands in the central North Dakota focal area, with an emphasis on Knife River Indian Villages National Historic Site. The report explainsscenario planning as an adaptation tool in general, then describes how it was applied to the central North Dakota focal area in three phases. Priority resource management and climate uncertainties were identified in the orientation phase. Local climate summaries for relevant, divergent, and challenging climate scenarios were developed in the second phase. In the final phase, a two-day scenario planning workshop held November 12-13, 2015 in Bismarck, ND, featured scenario development and implications, testing management decisions, and methods for operationalizing scenario planning outcomes.

Resource management and operations in southwest South Dakota: Climate change scenario planning workshop summary January 20-21, 2016, Rapid City, SD

USGS Publications Warehouse

Fisichelli, Nicholas A.; Schuurman, Gregor W.; Symstad, Amy J.; Ray, Andrea; Miller, Brian; Cross, Molly; Rowland, Erika

2016-01-01

The Scaling Climate Change Adaptation in the Northern Great Plains through Regional Climate Summaries and Local Qualitative-Quantitative Scenario Planning Workshops project synthesizes climate data into 3-5 distinct but plausible climate summaries for the northern Great Plains region; crafts quantitative summaries of these climate futures for two focal areas; and applies these local summaries by developing climate-resource-management scenarios through participatory workshops and, where possible, simulation models. The two focal areas are central North Dakota and southwest South Dakota (Figure 1). The primary objective of this project is to help resource managers and scientists in a focal area use scenario planning to make management and planning decisions based on assessments of critical future uncertainties.This report summarizes project work for public and tribal lands in the southwest South Dakota grasslands focal area, with an emphasis on Badlands National Park and Buffalo Gap National Grassland. The report explains scenario planning as an adaptation tool in general, then describes how it was applied to the focal area in three phases. Priority resource management and climate uncertainties were identified in the orientation phase. Local climate summaries for relevant, divergent, and challenging climate scenarios were developed in the second phase. In the final phase, a two-day scenario planning workshop held January 20-21, 2016 in Rapid City, South Dakota, featured scenario development and implications, testing management decisions, and methods for operationalizing scenario planning outcomes.

Tracking Expected Improvements of Decadal Prediction in Climate Services

NASA Astrophysics Data System (ADS)

Suckling, E.; Thompson, E.; Smith, L. A.

2013-12-01

Physics-based simulation models are ultimately expected to provide the best available (decision-relevant) probabilistic climate predictions, as they can capture the dynamics of the Earth System across a range of situations, situations for which observations for the construction of empirical models are scant if not nonexistent. This fact in itself provides neither evidence that predictions from today's Earth Systems Models will outperform today's empirical models, nor a guide to the space and time scales on which today's model predictions are adequate for a given purpose. Empirical (data-based) models are employed to make probability forecasts on decadal timescales. The skill of these forecasts is contrasted with that of state-of-the-art climate models, and the challenges faced by each approach are discussed. The focus is on providing decision-relevant probability forecasts for decision support. An empirical model, known as Dynamic Climatology is shown to be competitive with CMIP5 climate models on decadal scale probability forecasts. Contrasting the skill of simulation models not only with each other but also with empirical models can reveal the space and time scales on which a generation of simulation models exploits their physical basis effectively. It can also quantify their ability to add information in the formation of operational forecasts. Difficulties (i) of information contamination (ii) of the interpretation of probabilistic skill and (iii) of artificial skill complicate each modelling approach, and are discussed. "Physics free" empirical models provide fixed, quantitative benchmarks for the evaluation of ever more complex climate models, that is not available from (inter)comparisons restricted to only complex models. At present, empirical models can also provide a background term for blending in the formation of probability forecasts from ensembles of simulation models. In weather forecasting this role is filled by the climatological distribution, and can significantly enhance the value of longer lead-time weather forecasts to those who use them. It is suggested that the direct comparison of simulation models with empirical models become a regular component of large model forecast intercomparison and evaluation. This would clarify the extent to which a given generation of state-of-the-art simulation models provide information beyond that available from simpler empirical models. It would also clarify current limitations in using simulation forecasting for decision support. No model-based probability forecast is complete without a quantitative estimate if its own irrelevance; this estimate is likely to increase as a function of lead time. A lack of decision-relevant quantitative skill would not bring the science-based foundation of anthropogenic warming into doubt. Similar levels of skill with empirical models does suggest a clear quantification of limits, as a function of lead time, for spatial and temporal scales on which decisions based on such model output are expected to prove maladaptive. Failing to clearly state such weaknesses of a given generation of simulation models, while clearly stating their strength and their foundation, risks the credibility of science in support of policy in the long term.

Statistical surrogate models for prediction of high-consequence climate change.

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

Constantine, Paul; Field, Richard V., Jr.; Boslough, Mark Bruce Elrick

2011-09-01

In safety engineering, performance metrics are defined using probabilistic risk assessments focused on the low-probability, high-consequence tail of the distribution of possible events, as opposed to best estimates based on central tendencies. We frame the climate change problem and its associated risks in a similar manner. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We therefore propose the use of specialized statistical surrogate models (SSMs) for the purpose of exploring the probability law of various climate variables of interest.more » A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field. The SSM can be calibrated to available spatial and temporal data from existing climate databases, e.g., the Program for Climate Model Diagnosis and Intercomparison (PCMDI), or to a collection of outputs from a General Circulation Model (GCM), e.g., the Community Earth System Model (CESM) and its predecessors. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework is developed to provide quantitative measures of confidence, via Bayesian credible intervals, in the use of the proposed approach to assess these risks.« less

Climate Shocks and Migration: An Agent-Based Modeling Approach.

PubMed

Entwisle, Barbara; Williams, Nathalie E; Verdery, Ashton M; Rindfuss, Ronald R; Walsh, Stephen J; Malanson, George P; Mucha, Peter J; Frizzelle, Brian G; McDaniel, Philip M; Yao, Xiaozheng; Heumann, Benjamin W; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree

2016-09-01

This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, 'normal' scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response.

Climate Shocks and Migration: An Agent-Based Modeling Approach

PubMed Central

Entwisle, Barbara; Williams, Nathalie E.; Verdery, Ashton M.; Rindfuss, Ronald R.; Walsh, Stephen J.; Malanson, George P.; Mucha, Peter J.; Frizzelle, Brian G.; McDaniel, Philip M.; Yao, Xiaozheng; Heumann, Benjamin W.; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree

2016-01-01

This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, ‘normal’ scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response. PMID:27594725

[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.

Selecting Populations for Non-Analogous Climate Conditions Using Universal Response Functions: The Case of Douglas-Fir in Central Europe.

PubMed

Chakraborty, Debojyoti; Wang, Tongli; Andre, Konrad; Konnert, Monika; Lexer, Manfred J; Matulla, Christoph; Schueler, Silvio

2015-01-01

Identifying populations within tree species potentially adapted to future climatic conditions is an important requirement for reforestation and assisted migration programmes. Such populations can be identified either by empirical response functions based on correlations of quantitative traits with climate variables or by climate envelope models that compare the climate of seed sources and potential growing areas. In the present study, we analyzed the intraspecific variation in climate growth response of Douglas-fir planted within the non-analogous climate conditions of Central and continental Europe. With data from 50 common garden trials, we developed Universal Response Functions (URF) for tree height and mean basal area and compared the growth performance of the selected best performing populations with that of populations identified through a climate envelope approach. Climate variables of the trial location were found to be stronger predictors of growth performance than climate variables of the population origin. Although the precipitation regime of the population sources varied strongly none of the precipitation related climate variables of population origin was found to be significant within the models. Overall, the URFs explained more than 88% of variation in growth performance. Populations identified by the URF models originate from western Cascades and coastal areas of Washington and Oregon and show significantly higher growth performance than populations identified by the climate envelope approach under both current and climate change scenarios. The URFs predict decreasing growth performance at low and middle elevations of the case study area, but increasing growth performance on high elevation sites. Our analysis suggests that population recommendations based on empirical approaches should be preferred and population selections by climate envelope models without considering climatic constrains of growth performance should be carefully appraised before transferring populations to planting locations with novel or dissimilar climate.

Hydrological and Climatic Significance of Martian Deltas

NASA Astrophysics Data System (ADS)

Di Achille, G.; Vaz, D. A.

2017-10-01

We a) review the geomorphology, sedimentology, and mineralogy of the martian deltas record and b) present the results of a quantitative study of the hydrology and sedimentology of martian deltas using modified version of terrestrial model Sedflux.

Reviewing Bayesian Networks potentials for climate change impacts assessment and management: A multi-risk perspective.

PubMed

Sperotto, Anna; Molina, José-Luis; Torresan, Silvia; Critto, Andrea; Marcomini, Antonio

2017-11-01

The evaluation and management of climate change impacts on natural and human systems required the adoption of a multi-risk perspective in which the effect of multiple stressors, processes and interconnections are simultaneously modelled. Despite Bayesian Networks (BNs) are popular integrated modelling tools to deal with uncertain and complex domains, their application in the context of climate change still represent a limited explored field. The paper, drawing on the review of existing applications in the field of environmental management, discusses the potential and limitation of applying BNs to improve current climate change risk assessment procedures. Main potentials include the advantage to consider multiple stressors and endpoints in the same framework, their flexibility in dealing and communicate with the uncertainty of climate projections and the opportunity to perform scenario analysis. Some limitations (i.e. representation of temporal and spatial dynamics, quantitative validation), however, should be overcome to boost BNs use in climate change impacts assessment and management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Lake Representations in Global Climate Models: An End-User Perspective

NASA Astrophysics Data System (ADS)

Rood, R. B.; Briley, L.; Steiner, A.; Wells, K.

2017-12-01

The weather and climate in the Great Lakes region of the United States and Canada are strongly influenced by the lakes. Within global climate models, lakes are incorporated in many ways. If one is interested in quantitative climate information for the Great Lakes, then it is a first principle requirement that end-users of climate model simulation data, whether scientists or practitioners, need to know if and how lakes are incorporated into models. We pose the basic question, how are lakes represented in CMIP models? Despite significant efforts by the climate community to document and publish basic information about climate models, it is unclear how to answer the question about lake representations? With significant knowledge of the practice of the field, then a reasonable starting point is to use the ES-DOC Comparator (https://compare.es-doc.org/ ). Once at this interface to model information, the end-user is faced with the need for more knowledge about the practice and culture of the discipline. For example, lakes are often categorized as a type of land, a counterintuitive concept. In some models, though, lakes are specified in ocean models. There is little evidence and little confidence that the information obtained through this process is complete or accurate. In fact, it is verifiably not accurate. This experience, then, motivates identifying and finding either human experts or technical documentation for each model. The conclusion from this exercise is that it can take months or longer to provide a defensible answer to if and how lakes are represented in climate models. Our experience with lake finding is that this is not a unique experience. This talk documents our experience and explores barriers we have identified and strategies for reducing those barriers.

Quantitative Modeling of Earth Surface Processes

NASA Astrophysics Data System (ADS)

Pelletier, Jon D.

This textbook describes some of the most effective and straightforward quantitative techniques for modeling Earth surface processes. By emphasizing a core set of equations and solution techniques, the book presents state-of-the-art models currently employed in Earth surface process research, as well as a set of simple but practical research tools. Detailed case studies demonstrate application of the methods to a wide variety of processes including hillslope, fluvial, aeolian, glacial, tectonic, and climatic systems. Exercises at the end of each chapter begin with simple calculations and then progress to more sophisticated problems that require computer programming. All the necessary computer codes are available online at www.cambridge.org/9780521855976. Assuming some knowledge of calculus and basic programming experience, this quantitative textbook is designed for advanced geomorphology courses and as a reference book for professional researchers in Earth and planetary science looking for a quantitative approach to Earth surface processes.

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.

Quantitative Hydraulic Models Of Early Land Plants Provide Insight Into Middle Paleozoic Terrestrial Paleoenvironmental Conditions

NASA Astrophysics Data System (ADS)

Wilson, J. P.; Fischer, W. W.

2010-12-01

Fossil plants provide useful proxies of Earth’s climate because plants are closely connected, through physiology and morphology, to the environments in which they lived. Recent advances in quantitative hydraulic models of plant water transport provide new insight into the history of climate by allowing fossils to speak directly to environmental conditions based on preserved internal anatomy. We report results of a quantitative hydraulic model applied to one of the earliest terrestrial plants preserved in three dimensions, the ~396 million-year-old vascular plant Asteroxylon mackei. This model combines equations describing the rate of fluid flow through plant tissues with detailed observations of plant anatomy; this allows quantitative estimates of two critical aspects of plant function. First and foremost, results from these models quantify the supply of water to evaporative surfaces; second, results describe the ability of plant vascular systems to resist tensile damage from extreme environmental events, such as drought or frost. This approach permits quantitative comparisons of functional aspects of Asteroxylon with other extinct and extant plants, informs the quality of plant-based environmental proxies, and provides concrete data that can be input into climate models. Results indicate that despite their small size, water transport cells in Asteroxylon could supply a large volume of water to the plant's leaves--even greater than cells from some later-evolved seed plants. The smallest Asteroxylon tracheids have conductivities exceeding 0.015 m^2 / MPa * s, whereas Paleozoic conifer tracheids do not reach this threshold until they are three times wider. However, this increase in conductivity came at the cost of little to no adaptations for transport safety, placing the plant’s vegetative organs in jeopardy during drought events. Analysis of the thickness-to-span ratio of Asteroxylon’s tracheids suggests that environmental conditions of reduced relative humidity (<20%) combined with elevated temperatures (>25°C) could cause sufficient cavitation to reduce hydraulic conductivity by 50%. This suggests that the Early Devonian environments that supported the earliest vascular plants were not subject to prolonged midseason droughts, or, alternatively, that the growing season was short. This places minimum constraints on water availability (e.g., groundwater hydration, relative humidity) in locations where Asteroxylon fossils are found; these environments must have had high relative humidities, comparable to tropical riparian environments. Given these constraints, biome-scale paleovegetation models that place early vascular plants distal to water sources can be revised to account for reduced drought tolerance. Paleoclimate proxies that treat early terrestrial plants as functionally interchangeable can incorporate physiological differences in a quantitatively meaningful way. Application of hydraulic models to fossil plants provides an additional perspective on the 475 million-year history of terrestrial photosynthetic environments and has potential to corroborate other plant-based paleoclimate proxies.

Quantitative Assessment of Antarctic Climate Variability and Change

NASA Astrophysics Data System (ADS)

Ordonez, A.; Schneider, D. P.

2013-12-01

The Antarctic climate is both extreme and highly variable, but there are indications it may be changing. As the climate in Antarctica can affect global sea level and ocean circulation, it is important to understand and monitor its behavior. Observational and model data have been used to study climate change in Antarctica and the Southern Ocean, though observational data is sparse and models have difficulty reproducing many observed climate features. For example, a leading hypothesis that ozone depletion has been responsible for sea ice trends is struggling with the inability of ozone-forced models to reproduce the observed sea ice increase. The extent to which this data-model disagreement represents inadequate observations versus model biases is unknown. This research assessed a variety of climate change indicators to present an overview of Antarctic climate that will allow scientists to easily access this data and compare indicators with other observational data and model output. Indicators were obtained from observational and reanalysis data for variables such as temperature, sea ice area, and zonal wind stress. Multiple datasets were used for key variables. Monthly and annual anomaly data from Antarctica and the Southern Ocean as well as tropical indices were plotted as time series on common axes for comparison. Trends and correlations were also computed. Zonal wind, surface temperature, and austral springtime sea ice had strong relationships and were further discussed in terms of how they may relate to climate variability and change in the Antarctic. This analysis will enable hypothesized mechanisms of Antarctic climate change to be critically evaluated.

Benefits of Greenhouse Gas Mitigation on the Supply, Management, and Use of Water Resources in the United States

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

Strzepek, K.; Neumann, Jim; Smith, Joel

Climate change impacts on water resources in the U.S. are likely to be far-reaching and substantial, because the water sector spans many parts of the economy, from supply and demand for agriculture, industry, energy production, transportation and municipal use to damages from natural hazards. This paper provides impact and damage estimates from five water resource-related models in the CIRA frame work, addressing drought risk, flooding damages, water supply and demand, and global water scarcity. The four models differ in the water system assessed, their spatial scale, and the units of assessment, but together they provide a quantitative and descriptive richnessmore » in characterizing water resource sector effects of climate change that no single model can capture. The results also address the sensitivity of these estimates to greenhouse gas emission scenarios, climate sensitivity alternatives, and global climate model selection. While calculating the net impact of climate change on the water sector as a whole may be impractical, because each of the models applied here uses a consistent set of climate scenarios, broad conclusions can be drawn regarding the patterns of change and the benefits of GHG mitigation policies for the water sector. Two key findings emerge: 1) climate mitigation policy substantially reduces the impact of climate change on the water sector across multiple dimensions; and 2) the more managed the water resources system, the more tempered the climate change impacts and the resulting reduction of impacts from climate mitigation policies.« less

Benefits of Greenhouse Gas Mitigation on the Supply, Management, and Use of Water Resources in the United States

DOE PAGES

Strzepek, K.; Neumann, Jim; Smith, Joel; ...

2014-11-29

Climate change impacts on water resources in the U.S. are likely to be far-reaching and substantial, because the water sector spans many parts of the economy, from supply and demand for agriculture, industry, energy production, transportation and municipal use to damages from natural hazards. This paper provides impact and damage estimates from five water resource-related models in the CIRA frame work, addressing drought risk, flooding damages, water supply and demand, and global water scarcity. The four models differ in the water system assessed, their spatial scale, and the units of assessment, but together they provide a quantitative and descriptive richnessmore » in characterizing water resource sector effects of climate change that no single model can capture. The results also address the sensitivity of these estimates to greenhouse gas emission scenarios, climate sensitivity alternatives, and global climate model selection. While calculating the net impact of climate change on the water sector as a whole may be impractical, because each of the models applied here uses a consistent set of climate scenarios, broad conclusions can be drawn regarding the patterns of change and the benefits of GHG mitigation policies for the water sector. Two key findings emerge: 1) climate mitigation policy substantially reduces the impact of climate change on the water sector across multiple dimensions; and 2) the more managed the water resources system, the more tempered the climate change impacts and the resulting reduction of impacts from climate mitigation policies.« less

US forest response to projected climate-related stress: a tolerance perspective.

PubMed

Liénard, Jean; Harrison, John; Strigul, Nikolay

2016-08-01

Although it is widely recognized that climate change will require a major spatial reorganization of forests, our ability to predict exactly how and where forest characteristics and distributions will change has been rather limited. Current efforts to predict future distribution of forested ecosystems as a function of climate include species distribution models (for fine-scale predictions) and potential vegetation climate envelope models (for coarse-grained, large-scale predictions). Here, we develop and apply an intermediate approach wherein we use stand-level tolerances of environmental stressors to understand forest distributions and vulnerabilities to anticipated climate change. In contrast to other existing models, this approach can be applied at a continental scale while maintaining a direct link to ecologically relevant, climate-related stressors. We first demonstrate that shade, drought, and waterlogging tolerances of forest stands are strongly correlated with climate and edaphic conditions in the conterminous United States. This discovery allows the development of a tolerance distribution model (TDM), a novel quantitative tool to assess landscape level impacts of climate change. We then focus on evaluating the implications of the drought TDM. Using an ensemble of 17 climate change models to drive this TDM, we estimate that 18% of US ecosystems are vulnerable to drought-related stress over the coming century. Vulnerable areas include mostly the Midwest United States and Northeast United States, as well as high-elevation areas of the Rocky Mountains. We also infer stress incurred by shifting climate should create an opening for the establishment of forest types not currently seen in the conterminous United States. © 2016 John Wiley & Sons Ltd.

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.

Adapted conservation measures are required to save the Iberian lynx in a changing climate

NASA Astrophysics Data System (ADS)

Fordham, D. A.; Akçakaya, H. R.; Brook, B. W.; Rodríguez, A.; Alves, P. C.; Civantos, E.; Triviño, M.; Watts, M. J.; Araújo, M. B.

2013-10-01

The Iberian lynx (Lynx pardinus) has suffered severe population declines in the twentieth century and is now on the brink of extinction. Climate change could further threaten the survival of the species, but its forecast effects are being neglected in recovery plans. Quantitative estimates of extinction risk under climate change have so far mostly relied on inferences from correlative projections of species' habitat shifts. Here we use ecological niche models coupled to metapopulation simulations with source-sink dynamics to directly investigate the combined effects of climate change, prey availability and management intervention on the persistence of the Iberian lynx. Our approach is unique in that it explicitly models dynamic bi-trophic species interactions in a climate change setting. We show that anticipated climate change will rapidly and severely decrease lynx abundance and probably lead to its extinction in the wild within 50 years, even with strong global efforts to mitigate greenhouse gas emissions. In stark contrast, we also show that a carefully planned reintroduction programme, accounting for the effects of climate change, prey abundance and habitat connectivity, could avert extinction of the lynx this century. Our results demonstrate, for the first time, why considering prey availability, climate change and their interaction in models is important when designing policies to prevent future biodiversity loss.

A Bayesian Approach to Evaluating Consistency between Climate Model Output and Observations

NASA Astrophysics Data System (ADS)

Braverman, A. J.; Cressie, N.; Teixeira, J.

2010-12-01

Like other scientific and engineering problems that involve physical modeling of complex systems, climate models can be evaluated and diagnosed by comparing their output to observations of similar quantities. Though the global remote sensing data record is relatively short by climate research standards, these data offer opportunities to evaluate model predictions in new ways. For example, remote sensing data are spatially and temporally dense enough to provide distributional information that goes beyond simple moments to allow quantification of temporal and spatial dependence structures. In this talk, we propose a new method for exploiting these rich data sets using a Bayesian paradigm. For a collection of climate models, we calculate posterior probabilities its members best represent the physical system each seeks to reproduce. The posterior probability is based on the likelihood that a chosen summary statistic, computed from observations, would be obtained when the model's output is considered as a realization from a stochastic process. By exploring how posterior probabilities change with different statistics, we may paint a more quantitative and complete picture of the strengths and weaknesses of the models relative to the observations. We demonstrate our method using model output from the CMIP archive, and observations from NASA's Atmospheric Infrared Sounder.

A Quantitative Climate-Match Score for Risk-Assessment Screening of Reptile and Amphibian Introductions

NASA Astrophysics Data System (ADS)

van Wilgen, Nicola J.; Roura-Pascual, Núria; Richardson, David M.

2009-09-01

Assessing climatic suitability provides a good preliminary estimate of the invasive potential of a species to inform risk assessment. We examined two approaches for bioclimatic modeling for 67 reptile and amphibian species introduced to California and Florida. First, we modeled the worldwide distribution of the biomes found in the introduced range to highlight similar areas worldwide from which invaders might arise. Second, we modeled potentially suitable environments for species based on climatic factors in their native ranges, using three sources of distribution data. Performance of the three datasets and both approaches were compared for each species. Climate match was positively correlated with species establishment success (maximum predicted suitability in the introduced range was more strongly correlated with establishment success than mean suitability). Data assembled from the Global Amphibian Assessment through NatureServe provided the most accurate models for amphibians, while ecoregion data compiled by the World Wide Fund for Nature yielded models which described reptile climatic suitability better than available point-locality data. We present three methods of assigning a climate-match score for use in risk assessment using both the mean and maximum climatic suitabilities. Managers may choose to use different methods depending on the stringency of the assessment and the available data, facilitating higher resolution and accuracy for herpetofaunal risk assessment. Climate-matching has inherent limitations and other factors pertaining to ecological interactions and life-history traits must also be considered for thorough risk assessment.

Climate versus carbon dioxide controls on biomass burning: a model analysis of the glacial-interglacial contrast

NASA Astrophysics Data System (ADS)

Calvo, M. Martin; Prentice, I. C.; Harrison, S. P.

2014-11-01

Climate controls fire regimes through its influence on the amount and types of fuel present and their dryness. CO2 concentration constrains primary production by limiting photosynthetic activity in plants. However, although fuel accumulation depends on biomass production, and hence on CO2 concentration, the quantitative relationship between atmospheric CO2 concentration and biomass burning is not well understood. Here a fire-enabled dynamic global vegetation model (the Land surface Processes and eXchanges model, LPX) is used to attribute glacial-interglacial changes in biomass burning to an increase in CO2, which would be expected to increase primary production and therefore fuel loads even in the absence of climate change, vs. climate change effects. Four general circulation models provided last glacial maximum (LGM) climate anomalies - that is, differences from the pre-industrial (PI) control climate - from the Palaeoclimate Modelling Intercomparison Project Phase~2, allowing the construction of four scenarios for LGM climate. Modelled carbon fluxes from biomass burning were corrected for the model's observed prediction biases in contemporary regional average values for biomes. With LGM climate and low CO2 (185 ppm) effects included, the modelled global flux at the LGM was in the range of 1.0-1.4 Pg C year-1, about a third less than that modelled for PI time. LGM climate with pre-industrial CO2 (280 ppm) yielded unrealistic results, with global biomass burning fluxes similar to or even greater than in the pre-industrial climate. It is inferred that a substantial part of the increase in biomass burning after the LGM must be attributed to the effect of increasing CO2 concentration on primary production and fuel load. Today, by analogy, both rising CO2 and global warming must be considered as risk factors for increasing biomass burning. Both effects need to be included in models to project future fire risks.

Simulating the Past, Present and Future of the Upper Troposphere and Lower Stratosphere

NASA Astrophysics Data System (ADS)

Gettelman, Andrew; Hegglin, Michaela

2010-05-01

A comprehensive assessment of coupled chemistry climate model (CCM) performance in the upper troposphere and lower stratosphere has been conducted with 18 models. Both qualitative and quantitative comparisons of model representation of UTLS dynamical, radiative and chemical structure have been conducted, using a collection of quantitative grading techniques. The models are able to reproduce the observed climatology of dynamical, radiative and chemical structure in the tropical and extratropical UTLS, despite relatively coarse vertical and horizontal resolution. Diagnostics of the Tropical Tropopause Layer (TTL), Tropopause Inversion Layer (TIL) and Extra-tropical Transition Layer (ExTL) are analyzed. The results provide new insight into the key processes that govern the dynamics and transport in the tropics and extra-tropicsa. The presentation will explain how models are able to reproduce key features of the UTLS, what features they do not reproduce, and why. Model trends over the historical period are also assessed and interannual variability is included in the metrics. Finally, key trends in the UTLS for the future with a given halogen and greenhouse gas scenario are presented, indicating significant changes in tropopause height and temperature, as well as UTLS ozone concentrations in the 21st century due to climate change and ozone recovery.

Projected changes over western Canada using convection-permitting regional climate model and the pseudo-global warming method

NASA Astrophysics Data System (ADS)

Li, Y.; Kurkute, S.; Chen, L.

2017-12-01

Results from the General Circulation Models (GCMs) suggest more frequent and more severe extreme rain events in a climate warmer than the present. However, current GCMs cannot accurately simulate extreme rainfall events of short duration due to their coarse model resolutions and parameterizations. This limitation makes it difficult to provide the detailed quantitative information for the development of regional adaptation and mitigation strategies. Dynamical downscaling using nested Regional Climate Models (RCMs) are able to capture key regional and local climate processes with an affordable computational cost. Recent studies have demonstrated that the downscaling of GCM results with weather-permitting mesoscale models, such as the pseudo-global warming (PGW) technique, could be a viable and economical approach of obtaining valuable climate change information on regional scales. We have conducted a regional climate 4-km Weather Research and Forecast Model (WRF) simulation with one domain covering the whole western Canada, for a historic run (2000-2015) and a 15-year future run to 2100 and beyond with the PGW forcing. The 4-km resolution allows direct use of microphysics and resolves the convection explicitly, thus providing very convincing spatial detail. With this high-resolution simulation, we are able to study the convective mechanisms, specifically the control of convections over the Prairies, the projected changes of rainfall regimes, and the shift of the convective mechanisms in a warming climate, which has never been examined before numerically at such large scale with such high resolution.

Climate Change Research in View of Bibliometrics

PubMed Central

Haunschild, Robin; Bornmann, Lutz; Marx, Werner

2016-01-01

This bibliometric study of a large publication set dealing with research on climate change aims at mapping the relevant literature from a bibliometric perspective and presents a multitude of quantitative data: (1) The growth of the overall publication output as well as (2) of some major subfields, (3) the contributing journals and countries as well as their citation impact, and (4) a title word analysis aiming to illustrate the time evolution and relative importance of specific research topics. The study is based on 222,060 papers (articles and reviews only) published between 1980 and 2014. The total number of papers shows a strong increase with a doubling every 5–6 years. Continental biomass related research is the major subfield, closely followed by climate modeling. Research dealing with adaptation, mitigation, risks, and vulnerability of global warming is comparatively small, but their share of papers increased exponentially since 2005. Research on vulnerability and on adaptation published the largest proportion of very important papers (in terms of citation impact). Climate change research has become an issue also for disciplines beyond the natural sciences. The categories Engineering and Social Sciences show the strongest field-specific relative increase. The Journal of Geophysical Research, the Journal of Climate, the Geophysical Research Letters, and Climatic Change appear at the top positions in terms of the total number of papers published. Research on climate change is quantitatively dominated by the USA, followed by the UK, Germany, and Canada. The citation-based indicators exhibit consistently that the UK has produced the largest proportion of high impact papers compared to the other countries (having published more than 10,000 papers). Also, Switzerland, Denmark and also The Netherlands (with a publication output between around 3,000 and 6,000 papers) perform top—the impact of their contributions is on a high level. The title word analysis shows that the term climate change comes forward with time. Furthermore, the term impact arises and points to research dealing with the various effects of climate change. The discussion of the question of human induced climate change towards a clear fact (for the majority of the scientific community) stimulated research on future pathways for adaptation and mitigation. Finally, the term model and related terms prominently appear independent of time, indicating the high relevance of climate modeling. PMID:27472663

Climate Change Research in View of Bibliometrics.

PubMed

Haunschild, Robin; Bornmann, Lutz; Marx, Werner

2016-01-01

This bibliometric study of a large publication set dealing with research on climate change aims at mapping the relevant literature from a bibliometric perspective and presents a multitude of quantitative data: (1) The growth of the overall publication output as well as (2) of some major subfields, (3) the contributing journals and countries as well as their citation impact, and (4) a title word analysis aiming to illustrate the time evolution and relative importance of specific research topics. The study is based on 222,060 papers (articles and reviews only) published between 1980 and 2014. The total number of papers shows a strong increase with a doubling every 5-6 years. Continental biomass related research is the major subfield, closely followed by climate modeling. Research dealing with adaptation, mitigation, risks, and vulnerability of global warming is comparatively small, but their share of papers increased exponentially since 2005. Research on vulnerability and on adaptation published the largest proportion of very important papers (in terms of citation impact). Climate change research has become an issue also for disciplines beyond the natural sciences. The categories Engineering and Social Sciences show the strongest field-specific relative increase. The Journal of Geophysical Research, the Journal of Climate, the Geophysical Research Letters, and Climatic Change appear at the top positions in terms of the total number of papers published. Research on climate change is quantitatively dominated by the USA, followed by the UK, Germany, and Canada. The citation-based indicators exhibit consistently that the UK has produced the largest proportion of high impact papers compared to the other countries (having published more than 10,000 papers). Also, Switzerland, Denmark and also The Netherlands (with a publication output between around 3,000 and 6,000 papers) perform top-the impact of their contributions is on a high level. The title word analysis shows that the term climate change comes forward with time. Furthermore, the term impact arises and points to research dealing with the various effects of climate change. The discussion of the question of human induced climate change towards a clear fact (for the majority of the scientific community) stimulated research on future pathways for adaptation and mitigation. Finally, the term model and related terms prominently appear independent of time, indicating the high relevance of climate modeling.

An index-based robust decision making framework for watershed management in a changing climate.

PubMed

Kim, Yeonjoo; Chung, Eun-Sung

2014-03-01

This study developed an index-based robust decision making framework for watershed management dealing with water quantity and quality issues in a changing climate. It consists of two parts of management alternative development and analysis. The first part for alternative development consists of six steps: 1) to understand the watershed components and process using HSPF model, 2) to identify the spatial vulnerability ranking using two indices: potential streamflow depletion (PSD) and potential water quality deterioration (PWQD), 3) to quantify the residents' preferences on water management demands and calculate the watershed evaluation index which is the weighted combinations of PSD and PWQD, 4) to set the quantitative targets for water quantity and quality, 5) to develop a list of feasible alternatives and 6) to eliminate the unacceptable alternatives. The second part for alternative analysis has three steps: 7) to analyze all selected alternatives with a hydrologic simulation model considering various climate change scenarios, 8) to quantify the alternative evaluation index including social and hydrologic criteria with utilizing multi-criteria decision analysis methods and 9) to prioritize all options based on a minimax regret strategy for robust decision. This framework considers the uncertainty inherent in climate models and climate change scenarios with utilizing the minimax regret strategy, a decision making strategy under deep uncertainty and thus this procedure derives the robust prioritization based on the multiple utilities of alternatives from various scenarios. In this study, the proposed procedure was applied to the Korean urban watershed, which has suffered from streamflow depletion and water quality deterioration. Our application shows that the framework provides a useful watershed management tool for incorporating quantitative and qualitative information into the evaluation of various policies with regard to water resource planning and management. Copyright © 2013 Elsevier B.V. All rights reserved.

Quantitative Models for the Narragansett Bay Estuary, Rhode Island/Massachusetts, USA

EPA Science Inventory

Multiple drivers, including nutrient loading and climate change, affect the Narragansett Bay ecosystem in Rhode Island/Massachusetts, USA. Managers are interested in understanding the timing and magnitude of these effects, and ecosystem responses to restoration actions. To provid...

Quantitative estimates of Mid- to late Holocene Climate Variability in northeastern Siberia inferred from chironomids in lake sediments

NASA Astrophysics Data System (ADS)

Nazarova, Larisa; Diekmann, Bernhard; Pestrjakova, Ludmila; Herzschuh, Ulrike; Subetto, Dmitry

2010-05-01

Yakutia (Russia, northeastern part of Eurasia) represents one of Earths most extreme climatic settings in the world with deep-reaching frozen ground and a semiarid continental climate with highest seasonal temperature contrasts in the northern hemisphere. The amplitude of temperature variations around the year sometimes exceeds 100oC. There are few examples of quantitative palaeoecological studies in Siberia and these data have to be tested by quantitative studies from other sites in this region, inferred from different proxies and using regional calibration datasets and temperature models that are still lacking. Chironomid midges (Insecta, Diptera, Chironomidae) have been widely used to reconstruct past climate variability in many areas of Western Europe and North America. A chironomid-mean July air temperature inference model has been developed, based on a modern calibration set of 200 lakes sampled along a transect from 110° to 159° E and 61° to73° N in northern Russia. The inference model was applied to sediment cores from 2 lakes in the Central Yakutia in order to reconstruct past July air temperatures. The lacustrine records span mid- to late Holocene. The downcore variability in the chironomid assemblages and the composition of organic matter give evidence of climate-driven and interrelated changes in biological productivity, lacustrine trophic states, and lake-level fluctuations. Three phases of the climate development in Central Yakutia can be derived from the geochemical composition of the lake cores and according to the inferred from chironomid assemblages mean July air ToC. Content of organic matters reached maximal values in the period between 7000-4500 yBP. Sedimentation rate is especially high, numerous molluscs shells are found in sediments. All this along with the reconstructed air temperature confirmed that Mid Holocene optimum in Central Yakutia took place in this period with the maximal temperatures up to 4oC above present day ToC. Strong faunistic changes take place after 4500 yBP. Temperature reconstruction has shown that around 4500 ka BP air temperature went down up to 2oC below modern temperature. These observations confirm end of Holocene climate optimum at this time. The lake status record reveals a long-term trend towards lake-level lowering in the course of climate deterioration after 4.2 cal. ka BP and reduced evaporation as well as progressive sediment infill. This long-term trend is overprinted by short-term fluctuations at centennial time scales with high lake levels and decreased biological productivity during cool climate spells with reduced evaporation, as also observed in modern thermokarst lakes of Central Yakutia.

Solar Effects on Global Climate Due to Cosmic Rays and Solar Energetic Particles

NASA Technical Reports Server (NTRS)

Turco, R. P.; Raeder, J.; DAuria, R.

2005-01-01

Although the work reported here does not directly connect solar variability with global climate change, this research establishes a plausible quantitative causative link between observed solar activity and apparently correlated variations in terrestrial climate parameters. Specifically, we have demonstrated that ion-mediated nucleation of atmospheric particles is a likely, and likely widespread, phenomenon that relates solar variability to changes in the microphysical properties of clouds. To investigate this relationship, we have constructed and applied a new model describing the formation and evolution of ionic clusters under a range of atmospheric conditions throughout the lower atmosphere. The activation of large ionic clusters into cloud nuclei is predicted to be favorable in the upper troposphere and mesosphere, and possibly in the lower stratosphere. The model developed under this grant needs to be extended to include additional cluster families, and should be incorporated into microphysical models to further test the cause-and-effect linkages that may ultimately explain key aspects of the connections between solar variability and climate.

Reassessing Pliocene temperature gradients

NASA Astrophysics Data System (ADS)

Tierney, J. E.

2017-12-01

With CO2 levels similar to present, the Pliocene Warm Period (PWP) is one of our best analogs for climate change in the near future. Temperature proxy data from the PWP describe dramatically reduced zonal and meridional temperature gradients that have proved difficult to reproduce with climate model simulations. Recently, debate has emerged regarding the interpretation of the proxies used to infer Pliocene temperature gradients; these interpretations affect the magnitude of inferred change and the degree of inconsistency with existing climate model simulations of the PWP. Here, I revisit the issue using Bayesian proxy forward modeling and prediction that propagates known uncertainties in the Mg/Ca, UK'37, and TEX86 proxy systems. These new spatiotemporal predictions are quantitatively compared to PWP simulations to assess probabilistic agreement. Results show generally good agreement between existing Pliocene simulations from the PlioMIP ensemble and SST proxy data, suggesting that exotic changes in the ocean-atmosphere are not needed to explain the Pliocene climate state. Rather, the spatial changes in SST during the Pliocene are largely consistent with elevated CO2 forcing.

Simulating climate and stable water isotopes during the Last Interglacial using a coupled climate-isotope model

NASA Astrophysics Data System (ADS)

Gierz, Paul; Werner, Martin; Lohmann, Gerrit

2017-09-01

Understanding the dynamics of warm climate states has gained increasing importance in the face of anthropogenic climate change, and while it is possible to simulate warm interglacial climates, these simulated results cannot be evaluated without the aid of geochemical proxies. One such proxy is δ18O, which allows for inference about both a climate state's hydrology and temperature. We utilize a stable water isotope equipped climate model to simulate three stages during the Last Interglacial (LIG), corresponding to 130, 125, and 120 kyr before present, using forcings for orbital configuration as well as greenhouse gases. We discover heterogeneous responses in the mean δ18O signal to the climate forcing, with large areas of depletion in the LIG δ18O signal over the tropical Atlantic, the Sahel, and the Indian subcontinent, and with enrichment over the Pacific and Arctic Oceans. While we find that the climatology mean relationship between δ18O and temperature remains stable during the LIG, we also discover that this relationship is not spatially consistent. Our results suggest that great care must be taken when comparing δ18O records of different paleoclimate archives with the results of climate models as both the qualitative and quantitative interpretation of δ18O variations as a proxy for past temperature changes may be problematic due to the complexity of the signals.

Assessment of the climate change impacts on fecal coliform contamination in a tidal estuarine system.

PubMed

Liu, Wen-Cheng; Chan, Wen-Ting

2015-12-01

Climate change is one of the key factors affecting the future microbiological water quality in rivers and tidal estuaries. A coupled 3D hydrodynamic and fecal coliform transport model was developed and applied to the Danshuei River estuarine system for predicting the influences of climate change on microbiological water quality. The hydrodynamic and fecal coliform model was validated using observational salinity and fecal coliform distributions. According to the analyses of the statistical error, predictions of the salinity and the fecal coliform concentration from the model simulation quantitatively agreed with the observed data. The validated model was then applied to predict the fecal coliform contamination as a result of climate change, including the change of freshwater discharge and the sea level rise. We found that the reduction of freshwater discharge under climate change scenarios resulted in an increase in the fecal coliform concentration. The sea level rise would decrease fecal coliform distributions because both the water level and the water volume increased. A reduction in freshwater discharge has a negative impact on the fecal coliform concentration, whereas a rising sea level has a positive influence on the fecal coliform contamination. An appropriate strategy for the effective microbiological management in tidal estuaries is required to reveal the persistent trends of climate in the future.

Coupling Processes Between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, Malcolm K. W.; Weisenstein, Debra; Shia, Run-Lie; Sze, N. D.

1998-01-01

The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling tools for this work are the AER 2-dimensional chemistry-transport model, the AER 2-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry. We will continue developing our three-wave model so that we can help NASA determine the strength and weakness of the next generation assessment models.

Coupling Processes Between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, M. K. W.; Weisenstein, Debra; Shia, Run-Lie; Sze, N. D.

1998-01-01

The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling tools for this work are the AER two-dimensional chemistry-transport model, the AER two-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry. We will continue developing our three-wave model so that we can help NASA determine the strength and weakness of the next generation assessment models.

Satellite Contributions to the Quantitative Characterization of Biomass Burning for Climate Modeling

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Kahn, Ralph; Chin, Mian

2012-01-01

Characterization of biomass burning from space has been the subject of an extensive body of literature published over the last few decades. Given the importance of this topic, we review how satellite observations contribute toward improving the representation of biomass burning quantitatively in climate and air-quality modeling and assessment. Satellite observations related to biomass burning may be classified into five broad categories: (i) active fire location and energy release, (ii) burned areas and burn severity, (iii) smoke plume physical disposition, (iv) aerosol distribution and particle properties, and (v) trace gas concentrations. Each of these categories involves multiple parameters used in characterizing specific aspects of the biomass-burning phenomenon. Some of the parameters are merely qualitative, whereas others are quantitative, although all are essential for improving the scientific understanding of the overall distribution (both spatial and temporal) and impacts of biomass burning. Some of the qualitative satellite datasets, such as fire locations, aerosol index, and gas estimates have fairly long-term records. They date back as far as the 1970s, following the launches of the DMSP, Landsat, NOAA, and Nimbus series of earth observation satellites. Although there were additional satellite launches in the 1980s and 1990s, space-based retrieval of quantitative biomass burning data products began in earnest following the launch of Terra in December 1999. Starting in 2000, fire radiative power, aerosol optical thickness and particle properties over land, smoke plume injection height and profile, and essential trace gas concentrations at improved resolutions became available. The 2000s also saw a large list of other new satellite launches, including Aqua, Aura, Envisat, Parasol, and CALIPSO, carrying a host of sophisticated instruments providing high quality measurements of parameters related to biomass burning and other phenomena. These improved data products have enabled significant progress in the study of biomass burning from space. However, appreciable uncertainty remains in many of the measurements that still needs to be addressed. Nevertheless, climate and other atmospheric models are

Servant Leadership and Its Impact on Classroom Climate and Student Achievement

ERIC Educational Resources Information Center

Mulligan, Daniel F.

2016-01-01

The purpose of this quantitative research was to see to what degree a relationship existed between servant leadership, classroom climate, and student achievement in a collegiate environment. This was a quantitative, correlational study. The foundational theories for this research included servant leadership and organizational climate that pertain…

Divergent selection along climatic gradients in a rare central European endemic species, Saxifraga sponhemica

PubMed Central

Walisch, Tania J.; Colling, Guy; Bodenseh, Melanie; Matthies, Diethart

2015-01-01

Background and Aims The effects of habitat fragmentation on quantitative genetic variation in plant populations are still poorly known. Saxifraga sponhemica is a rare endemic of Central Europe with a disjunct distribution, and a stable and specialized habitat of treeless screes and cliffs. This study therefore used S. sponhemica as a model species to compare quantitative and molecular variation in order to explore (1) the relative importance of drift and selection in shaping the distribution of quantitative genetic variation along climatic gradients; (2) the relationship between plant fitness, quantitative genetic variation, molecular genetic variation and population size; and (3) the relationship between the differentiation of a trait among populations and its evolvability. Methods Genetic variation within and among 22 populations from the whole distribution area of S. sponhemica was studied using RAPD (random amplified polymorphic DNA) markers, and climatic variables were obtained for each site. Seeds were collected from each population and germinated, and seedlings were transplanted into a common garden for determination of variation in plant traits. Key Results In contrast to previous results from rare plant species, strong evidence was found for divergent selection. Most population trait means of S. sponhemica were significantly related to climate gradients, indicating adaptation. Quantitative genetic differentiation increased with geographical distance, even when neutral molecular divergence was controlled for, and QST exceeded FST for some traits. The evolvability of traits was negatively correlated with the degree of differentiation among populations (QST), i.e. traits under strong selection showed little genetic variation within populations. The evolutionary potential of a population was not related to its size, the performance of the population or its neutral genetic diversity. However, performance in the common garden was lower for plants from populations with reduced molecular genetic variation, suggesting inbreeding depression due to genetic erosion. Conclusions The findings suggest that studies of molecular and quantitative genetic variation may provide complementary insights important for the conservation of rare species. The strong differentiation of quantitative traits among populations shows that selection can be an important force for structuring variation in evolutionarily important traits even for rare endemic species restricted to very specific habitats. PMID:25862244

Model confirmation in climate economics

PubMed Central

Millner, Antony; McDermott, Thomas K. J.

2016-01-01

Benefit–cost integrated assessment models (BC-IAMs) inform climate policy debates by quantifying the trade-offs between alternative greenhouse gas abatement options. They achieve this by coupling simplified models of the climate system to models of the global economy and the costs and benefits of climate policy. Although these models have provided valuable qualitative insights into the sensitivity of policy trade-offs to different ethical and empirical assumptions, they are increasingly being used to inform the selection of policies in the real world. To the extent that BC-IAMs are used as inputs to policy selection, our confidence in their quantitative outputs must depend on the empirical validity of their modeling assumptions. We have a degree of confidence in climate models both because they have been tested on historical data in hindcasting experiments and because the physical principles they are based on have been empirically confirmed in closely related applications. By contrast, the economic components of BC-IAMs often rely on untestable scenarios, or on structural models that are comparatively untested on relevant time scales. Where possible, an approach to model confirmation similar to that used in climate science could help to build confidence in the economic components of BC-IAMs, or focus attention on which components might need refinement for policy applications. We illustrate the potential benefits of model confirmation exercises by performing a long-run hindcasting experiment with one of the leading BC-IAMs. We show that its model of long-run economic growth—one of its most important economic components—had questionable predictive power over the 20th century. PMID:27432964

High regional climate sensitivity over continental China constrained by glacial-recent changes in temperature and the hydrological cycle.

PubMed

Eagle, Robert A; Risi, Camille; Mitchell, Jonathan L; Eiler, John M; Seibt, Ulrike; Neelin, J David; Li, Gaojun; Tripati, Aradhna K

2013-05-28

The East Asian monsoon is one of Earth's most significant climatic phenomena, and numerous paleoclimate archives have revealed that it exhibits variations on orbital and suborbital time scales. Quantitative constraints on the climate changes associated with these past variations are limited, yet are needed to constrain sensitivity of the region to changes in greenhouse gas levels. Here, we show central China is a region that experienced a much larger temperature change since the Last Glacial Maximum than typically simulated by climate models. We applied clumped isotope thermometry to carbonates from the central Chinese Loess Plateau to reconstruct temperature and water isotope shifts from the Last Glacial Maximum to present. We find a summertime temperature change of 6-7 °C that is reproduced by climate model simulations presented here. Proxy data reveal evidence for a shift to lighter isotopic composition of meteoric waters in glacial times, which is also captured by our model. Analysis of model outputs suggests that glacial cooling over continental China is significantly amplified by the influence of stationary waves, which, in turn, are enhanced by continental ice sheets. These results not only support high regional climate sensitivity in Central China but highlight the fundamental role of planetary-scale atmospheric dynamics in the sensitivity of regional climates to continental glaciation, changing greenhouse gas levels, and insolation.

Congruent climate-related genecological responses from molecular markers and quantitative traits for western white pine (Pinus monticola)

Treesearch

Bryce A. Richardson; Gerald E. Rehfeldt; Mee-Sook Kim

2009-01-01

Analyses of molecular and quantitative genetic data demonstrate the existence of congruent climate-related patterns in western white pine (Pinus monticola). Two independent studies allowed comparisons of amplified fragment length polymorphism (AFLP) markers with quantitative variation in adaptive traits. Principal component analyses...

Water Planning and Climate Change: Actionable Intelligence Yet?

NASA Astrophysics Data System (ADS)

Milly, P.

2008-05-01

Within a rational planning framework, water planners design major water projects by evaluating tradeoffs of costs, benefits, and risks to life and property. The evaluation is based on anticipated future runoff and streamflow. Generally, planners have invoked the stationarity approximation: they have assumed that hydrologic conditions during the planned lifetime of a project will be similar to those observed in the past. Contemporary anthropogenic climate change arguably makes stationarity untenable. In principle, stationarity-based planning under non- stationarity potentially leads to incorrect assessment of tradeoffs, sub-optimal decisions, and excessive financial and environmental costs (e.g., a reservoir that is too big to ever be filled) and/or insufficient benefits (e.g., levees that are too small to hold back the flood waters). As the reigning default assumption for planning, stationarity is an easy target for criticism; provision of a practical alternative is not so easy. The leading alternative, use of quantitative climate-change projections from global climate models in conjunction with water planners' river-basin models, has serious shortcomings of its own. Climate models (1) neglect some terrestrial processes known to influence runoff and streamflow; (2) do not represent precipitation well at the finer resolved time and space scales; (3) do not resolve any processes at the even finer spatial scale of relevance to much of water planning; and (4) disagree among themselves about some changes. Even setting aside the issue of scale mismatch, for which various "downscaling" methods have been proposed, outputs from climate models generally are not directly transferable to river-basin models, and river-basin models commonly use empiricisms whose historical validity might not extrapolate well under climate change. So climate science is informing water management that stationarity is a flawed assumption, but it has not presented a universally and reliably superior alternative. What is to be done? Is climate-change information of sufficient strength to justify making decisions that differ from those that would be optimal under stationarity? I.e., does climate science provide "actionable intelligence" to water planners? A conservative approach to planning in the presence of climate change would begin with stationarity as a base and then superpose, with quantitative estimates of uncertainties, those model-projected changes that appear to be qualitatively robust. The current state of science suggests that the following changes could be considered robust: (1) reduction in the fraction of precipitation falling as snow and earlier seasonal melting of snow, with consequent seasonal redistribution of runoff and streamflow; (2) gradual sea-level rise with heightened risk of encroachment of saline water into coastal surface- and ground-water-supply sources; and (3) global redistribution of precipitation and resultant runoff, with regional focal points ("hot spots") of desiccation and moistening. Even considering the attendant uncertainties, the available information about these changes can significantly affect the cost-benefit-risk tradeoffs of existing and prospective water projects and, therefore, can rationally inform decisions about future courses of action or inaction.

Model Sensitivity to North Atlantic Freshwater Forcing at 8.2 Ka

NASA Technical Reports Server (NTRS)

Morrill, Carrie; Legrande, Allegra Nicole; Renssen, H.; Bakker, P.; Otto-Bliesner, B. L.

2013-01-01

We compared four simulations of the 8.2 ka event to assess climate model sensitivity and skill in responding to North Atlantic freshwater perturbations. All of the simulations used the same freshwater forcing, 2.5 Sv for one year, applied to either the Hudson Bay (northeastern Canada) or Labrador Sea (between Canada's Labrador coast and Greenland). This freshwater pulse induced a decadal-mean slowdown of 10-25%in the Atlantic Meridional Overturning Circulation (AMOC) of the models and caused a large-scale pattern of climate anomalies that matched proxy evidence for cooling in the Northern Hemisphere and a southward shift of the Intertropical Convergence Zone. The multi-model ensemble generated temperature anomalies that were just half as large as those from quantitative proxy reconstructions, however. Also, the duration of AMOC and climate anomalies in three of the simulations was only several decades, significantly shorter than the duration of approx.150 yr in the paleoclimate record. Possible reasons for these discrepancies include incorrect representation of the early Holocene climate and ocean state in the North Atlantic and uncertainties in the freshwater forcing estimates.

The Impact of School Climate on Student Achievement in the Middle Schools of the Commonwealth of Virginia: A Quantitative Analysis of Existing Data

ERIC Educational Resources Information Center

Bergren, David Alexander

2014-01-01

This quantitative study was designed to be an analysis of the relationship between school climate and student achievement through the creation of an index of climate-factors (SES, discipline, attendance, and school size) for which publicly available data existed. The index that was formed served as a proxy measure of climate; it was analyzed…

Probabilistic estimates of drought impacts on agricultural production

NASA Astrophysics Data System (ADS)

Madadgar, Shahrbanou; AghaKouchak, Amir; Farahmand, Alireza; Davis, Steven J.

2017-08-01

Increases in the severity and frequency of drought in a warming climate may negatively impact agricultural production and food security. Unlike previous studies that have estimated agricultural impacts of climate condition using single-crop yield distributions, we develop a multivariate probabilistic model that uses projected climatic conditions (e.g., precipitation amount or soil moisture) throughout a growing season to estimate the probability distribution of crop yields. We demonstrate the model by an analysis of the historical period 1980-2012, including the Millennium Drought in Australia (2001-2009). We find that precipitation and soil moisture deficit in dry growing seasons reduced the average annual yield of the five largest crops in Australia (wheat, broad beans, canola, lupine, and barley) by 25-45% relative to the wet growing seasons. Our model can thus produce region- and crop-specific agricultural sensitivities to climate conditions and variability. Probabilistic estimates of yield may help decision-makers in government and business to quantitatively assess the vulnerability of agriculture to climate variations. We develop a multivariate probabilistic model that uses precipitation to estimate the probability distribution of crop yields. The proposed model shows how the probability distribution of crop yield changes in response to droughts. During Australia's Millennium Drought precipitation and soil moisture deficit reduced the average annual yield of the five largest crops.

Hurricanes and Climate: the U.S. CLIVAR Working Group on Hurricanes

NASA Technical Reports Server (NTRS)

Walsh, Kevin; Camargo, Suzana J.; Vecchi, Gabriel A.; Daloz, Anne Sophie; Elsner, James; Emanuel, Kerry; Horn, Michael; Lim, Young-Kwon; Roberts, Malcolm; Patricola, Christina;

Quantitative Holocene climatic reconstructions for the lower Yangtze region of China

NASA Astrophysics Data System (ADS)

Li, Jianyong; Dodson, John; Yan, Hong; Wang, Weiming; Innes, James B.; Zong, Yongqiang; Zhang, Xiaojian; Xu, Qinghai; Ni, Jian; Lu, Fengyan

2018-02-01

Quantitative proxy-based and high-resolution palaeoclimatic datasets are scarce for the lower reaches of the Yangtze River (LYR) basin. This region is in a transitional vegetation zone which is climatologically sensitive; and as a birthplace for prehistorical civilization in China, it is important to understand how palaeoclimatic dynamics played a role in affecting cultural development in the region. We present a pollen-based and regionally-averaged Holocene climatic twin-dataset for mean total annual precipitation (PANN) and mean annual temperature (TANN) covering the last 10,000 years for the LYR region. This is based on the technique of weighted averaging-partial least squares regression to establish robust calibration models for obtaining reliable climatic inferences. The pollen-based reconstructions generally show an early Holocene climatic optimum with both abundant monsoonal rainfall and warm thermal conditions, and a declining pattern of both PANN and TANN values in the middle to late Holocene. The main driving forces behind the Holocene climatic changes in the LYR area are likely summer solar insolation associated with tropical or subtropical macro-scale climatic circulations such as the Intertropical Convergence Zone (ITCZ), Western Pacific Subtropical High (WPSH), and El Niño/Southern Oscillation (ENSO). Regional multi-proxy comparisons indicate that the Holocene variations in precipitation and temperature for the LYR region display an in-phase relationship with other related proxy records from southern monsoonal China and the Indian monsoon-influenced regions, but are inconsistent with the Holocene moisture or temperature records from northern monsoonal China and the westerly-dominated region in northwestern China. Overall, our comprehensive palaeoclimatic dataset and models may be significant tools for understanding the Holocene Asian monsoonal evolution and for anticipating its future dynamics in eastern Asia.

Failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

2013-08-01

Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

Understanding Climate Uncertainty with an Ocean Focus

NASA Astrophysics Data System (ADS)

Tokmakian, R. T.

2009-12-01

Uncertainty in climate simulations arises from various aspects of the end-to-end process of modeling the Earth’s climate. First, there is uncertainty from the structure of the climate model components (e.g. ocean/ice/atmosphere). Even the most complex models are deficient, not only in the complexity of the processes they represent, but in which processes are included in a particular model. Next, uncertainties arise from the inherent error in the initial and boundary conditions of a simulation. Initial conditions are the state of the weather or climate at the beginning of the simulation and other such things, and typically come from observations. Finally, there is the uncertainty associated with the values of parameters in the model. These parameters may represent physical constants or effects, such as ocean mixing, or non-physical aspects of modeling and computation. The uncertainty in these input parameters propagates through the non-linear model to give uncertainty in the outputs. The models in 2020 will no doubt be better than today’s models, but they will still be imperfect, and development of uncertainty analysis technology is a critical aspect of understanding model realism and prediction capability. Smith [2002] and Cox and Stephenson [2007] discuss the need for methods to quantify the uncertainties within complicated systems so that limitations or weaknesses of the climate model can be understood. In making climate predictions, we need to have available both the most reliable model or simulation and a methods to quantify the reliability of a simulation. If quantitative uncertainty questions of the internal model dynamics are to be answered with complex simulations such as AOGCMs, then the only known path forward is based on model ensembles that characterize behavior with alternative parameter settings [e.g. Rougier, 2007]. The relevance and feasibility of using "Statistical Analysis of Computer Code Output" (SACCO) methods for examining uncertainty in ocean circulation due to parameter specification will be described and early results using the ocean/ice components of the CCSM climate model in a designed experiment framework will be shown. Cox, P. and D. Stephenson, Climate Change: A Changing Climate for Prediction, 2007, Science 317 (5835), 207, DOI: 10.1126/science.1145956. Rougier, J. C., 2007: Probabilistic Inference for Future Climate Using an Ensemble of Climate Model Evaluations, Climatic Change, 81, 247-264. Smith L., 2002, What might we learn from climate forecasts? Proc. Nat’l Academy of Sciences, Vol. 99, suppl. 1, 2487-2492 doi:10.1073/pnas.012580599.

Hemispheric symmetry of the Earth's Energy Balance as a fundamental constraint on the Earth's climate

NASA Astrophysics Data System (ADS)

Stephens, G. L.; Webster, P. J.; OBrien, D. M.

2013-12-01

We currently lack a quantitative understanding of how the Earth's energy balance and the poleward energy transport adjust to different forcings that determine climate change. Currently, there are no constraints that guide this understanding. We will demonstrate that the Earth's energy balance exhibits a remarkable symmetry about the equator, and that this symmetry is a necessary condition of a steady state climate. Our analysis points to clouds as the principal agent that highly regulates this symmetry and sets the steady state. The existence of this thermodynamic steady-state constraint on climate and the symmetry required to sustain it leads to important inferences about the synchronous nature of climate changes between hemispheres, offering for example insights on mechanisms that can sustain global ice ages forced by asymmetric hemispheric solar radiation variations or how climate may respond to increases in greenhouse gas concentration. Further inferences regarding cloud effects on climate can also be deduced without resorting to the complex and intricate processes of cloud formation, whose representation continues to challenge the climate modeling community. The constraint suggests cloud feedbacks must be negative buffering the system against change. We will show that this constraint doesn't exist in the current CMIP5 model experiments and the lack of such a constraint suggests there is insufficient buffering in models in response to external forcings

Selecting Populations for Non-Analogous Climate Conditions Using Universal Response Functions: The Case of Douglas-Fir in Central Europe

PubMed Central

Chakraborty, Debojyoti; Wang, Tongli; Andre, Konrad; Konnert, Monika; Lexer, Manfred J.; Matulla, Christoph; Schueler, Silvio

2015-01-01

Identifying populations within tree species potentially adapted to future climatic conditions is an important requirement for reforestation and assisted migration programmes. Such populations can be identified either by empirical response functions based on correlations of quantitative traits with climate variables or by climate envelope models that compare the climate of seed sources and potential growing areas. In the present study, we analyzed the intraspecific variation in climate growth response of Douglas-fir planted within the non-analogous climate conditions of Central and continental Europe. With data from 50 common garden trials, we developed Universal Response Functions (URF) for tree height and mean basal area and compared the growth performance of the selected best performing populations with that of populations identified through a climate envelope approach. Climate variables of the trial location were found to be stronger predictors of growth performance than climate variables of the population origin. Although the precipitation regime of the population sources varied strongly none of the precipitation related climate variables of population origin was found to be significant within the models. Overall, the URFs explained more than 88% of variation in growth performance. Populations identified by the URF models originate from western Cascades and coastal areas of Washington and Oregon and show significantly higher growth performance than populations identified by the climate envelope approach under both current and climate change scenarios. The URFs predict decreasing growth performance at low and middle elevations of the case study area, but increasing growth performance on high elevation sites. Our analysis suggests that population recommendations based on empirical approaches should be preferred and population selections by climate envelope models without considering climatic constrains of growth performance should be carefully appraised before transferring populations to planting locations with novel or dissimilar climate. PMID:26288363

The National Danish Water Resources Model - using an integrated groundwater - surface water model for decision support and WFD implementation in a changing climate

NASA Astrophysics Data System (ADS)

Lajer Hojberg, Anker; Hinsby, Klaus; Jørgen Henriksen, Hans; Troldborg, Lars

2014-05-01

Integrated and sustainable water resources management and development of river basin management plans according to the Water Framework Directive is getting increasingly complex especially when taking projected climate change into account. Furthermore, uncertainty in future developments and incomplete knowledge of the physical system introduces a high degree of uncertainty in the decision making process. Knowledge based decision making is therefore vital for formulation of robust management plans and to allow assessment of the inherent uncertainties. The Department of Hydrology at the Geological Survey of Denmark and Greenland started in 1996 to develop a mechanistically, transient and spatially distributed groundwater-surface water model - the DK-model - for the assessment of groundwater quantitative status accounting for interactions with surface water and anthropogenic changes, such as extraction strategies and land use, as well as climate change. The model has been subject to continuous update building on hydrogeological knowledge established by the regional water authorities and other national research institutes. With the on-going improvement of the DK-model it is now increasingly applied both by research projects and for decision support e.g. in implementation of the Water Framework Directive or to support other decisions related to protection of water resources (quantitative and chemical status), ecosystems and the built environment. At present, the DK-model constitutes the backbone of a strategic modelling project funded by the Danish Environmental Protection Agency, with the aim of developing a modelling complex that will provide the foundation of the implementation of the Water Framework Directive. Since 2003 the DK-model has been used in more than 25 scientific papers and even more public reports. In the poster and the related review paper we describe the most important applications in both science and policy, where the DK-model has been used either directly or as an important starting point for assessing the impact of climate change on the quantity and quality of groundwater and surface water e.g. in relation to changes in water tables, runoff, nutrient loadings, flooding risks (coastal and hinterland), irrigation demands, sea level rise and seawater intrusion or to assess where geology or climate change create the largest uncertainty for evaluation of the development of water resources quantity and quality.

Urban Heat Islands and Their Mitigation vs. Local Impacts of Climate Change

NASA Astrophysics Data System (ADS)

Taha, H.

2007-12-01

Urban heat islands and their mitigation take on added significance, both negative and positive, when viewed from a climate-change perspective. In negative terms, urban heat islands can act as local exacerbating factors, or magnifying lenses, to the effects of regional and large-scale climate perturbations and change. They can locally impact meteorology, energy/electricity generation and use, thermal environment (comfort and heat waves), emissions of air pollutants, photochemistry, and air quality. In positive terms, on the other hand, mitigation of urban heat islands (via urban surface modifications and control of man-made heat, for example) can potentially have a beneficial effect of mitigating the local negative impacts of climate change. In addition, mitigation of urban heat islands can, in itself, contribute to preventing regional and global climate change, even if modestly, by helping reduce CO2 emissions from power plants and other sources as a result of decreased energy use for cooling (both direct and indirect) and reducing the rates of meteorology-dependent emissions of air pollutants. This presentation will highlight aspects and characteristics of heat islands, their mitigation, their modeling and quantification techniques, and recent advances in meso-urban modeling of California (funded by the California Energy Commission). In particular, the presentation will focus on results from quantitative, modeling-based analyses of the potential benefits of heat island mitigation in 1) reducing point- and area-source emissions of CO2, NOx, and VOC as a result of reduced cooling energy demand and ambient/surface temperatures, 2) reducing evaporative and fugitive hydrocarbon emissions as a result of lowered temperatures, 3) reducing biogenic hydrocarbon emissions from existing vegetative cover, 4) slowing the rates of tropospheric/ground-level ozone formation and/or accumulation in the urban boundary layer, and 5) helping improve air quality. Quantitative estimates of the above will be presented based on recent and earlier meteorological, energy, thermal environmental, emissions, and photochemical modeling studies for California and Texas.

Resolving the Aerosol Piece of the Global Climate Picture

NASA Astrophysics Data System (ADS)

Kahn, R. A.

2017-12-01

Factors affecting our ability to calculate climate forcing and estimate model predictive skill include direct radiative effects of aerosols and their indirect effects on clouds. Several decades of Earth-observing satellite observations have produced a global aerosol column-amount (AOD) record, but an aerosol microphysical property record required for climate and many air quality applications is lacking. Surface-based photometers offer qualitative aerosol-type classification, and several space-based instruments map aerosol air-mass types under favorable conditions. However, aerosol hygroscopicity, mass extinction efficiency (MEE), and quantitative light absorption, must be obtained from in situ measurements. Completing the aerosol piece of the climate picture requires three elements: (1) continuing global AOD and qualitative type mapping from space-based, multi-angle imagers and aerosol vertical distribution from near-source stereo imaging and downwind lidar, (2) systematic, quantitative in situ observations of particle properties unobtainable from space, and (3) continuing transport modeling to connect observations to sources, and extrapolate limited sampling in space and time. At present, the biggest challenges to producing the needed aerosol data record are: filling gaps in particle property observations, maintaining global observing capabilities, and putting the pieces together. Obtaining the PDFs of key particle properties, adequately sampled, is now the leading observational deficiency. One simplifying factor is that, for a given aerosol source and season, aerosol amounts often vary, but particle properties tend to be repeatable. SAM-CAAM (Systematic Aircraft Measurements to Characterize Aerosol Air Masses), a modest aircraft payload deployed frequently could fill this gap, adding value to the entire satellite data record, improving aerosol property assumptions in retrieval algorithms, and providing MEEs to translate between remote-sensing optical constraints and aerosol mass book-kept in climate models [Kahn et al., BAMS 2017]. This will also improve connections between remote-sensing particle types and those defined in models. The third challenge, maintaining global observing capabilities, requires continued community effort and good budgetary fortune.

Quantitative attribution of climate effects on Hurricane Harvey’s extreme rainfall in Texas

NASA Astrophysics Data System (ADS)

Wang, S.-Y. Simon; Zhao, Lin; Yoon, Jin-Ho; Klotzbach, Phil; Gillies, Robert R.

2018-05-01

Hurricane Harvey made landfall in August 2017 as the first land-falling category 4 hurricane to hit the state of Texas since Hurricane Carla in September 1961. While its intensity at landfall was notable, most of the vast devastation in the Houston metropolitan area was due to Harvey stalling near the southeast Texas coast over the next several days. Harvey’s long-duration rainfall event was reminiscent of extreme flooding that occurred in the neighboring state of Louisiana: both of which were caused by a stalled tropical low-pressure system producing four days of intense precipitation. A quantitative attribution analysis of Harvey’s rainfall was conducted using a mesoscale atmospheric model forced by constrained boundary and initial conditions that had their long-term climate trends removed. The removal of the various trends of the boundary and initial conditions minimizes the effects of warming in the air and the ocean surface on Harvey. The 60 member ensemble simulations suggest that post-1980 climate warming could have contributed to the extreme precipitation that fell on southeast Texas during 26–29 August 2017 by approximately 20%, with an interquartile range of 13%–37%. While the attribution outcome could be model dependent, this downscaling approach affords the closest means possible of a case-to-case comparison for event attribution, complementing other statistics-based attribution studies on Harvey. Further analysis of a global climate model tracking Harvey-like stalling systems indicates an increase in storm frequency and intensity over southeast Texas through the mid-21st century.

Climate reconstruction analysis using coexistence likelihood estimation (CRACLE): a method for the estimation of climate using vegetation.

PubMed

Harbert, Robert S; Nixon, Kevin C

2015-08-01

• Plant distributions have long been understood to be correlated with the environmental conditions to which species are adapted. Climate is one of the major components driving species distributions. Therefore, it is expected that the plants coexisting in a community are reflective of the local environment, particularly climate.• Presented here is a method for the estimation of climate from local plant species coexistence data. The method, Climate Reconstruction Analysis using Coexistence Likelihood Estimation (CRACLE), is a likelihood-based method that employs specimen collection data at a global scale for the inference of species climate tolerance. CRACLE calculates the maximum joint likelihood of coexistence given individual species climate tolerance characterization to estimate the expected climate.• Plant distribution data for more than 4000 species were used to show that this method accurately infers expected climate profiles for 165 sites with diverse climatic conditions. Estimates differ from the WorldClim global climate model by less than 1.5°C on average for mean annual temperature and less than ∼250 mm for mean annual precipitation. This is a significant improvement upon other plant-based climate-proxy methods.• CRACLE validates long hypothesized interactions between climate and local associations of plant species. Furthermore, CRACLE successfully estimates climate that is consistent with the widely used WorldClim model and therefore may be applied to the quantitative estimation of paleoclimate in future studies. © 2015 Botanical Society of America, Inc.

Hurricanes and Climate: The U.S. CLIVAR Working Group on Hurricanes

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

Walsh, Kevin J. E.; Camargo, Suzana J.; Vecchi, Gabriel A.

While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and to understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. Climate and Ocean: Variability, Predictability and Change (CLIVAR). This work, combined with results frommore » other model simulations, has strengthened relationships between tropical cyclone formation rates and climate variables such as midtropospheric vertical velocity, with decreased climatological vertical velocities leading to decreased tropical cyclone formation. Systematic differences are shown between experiments in which only sea surface temperature is increased compared with experiments where only atmospheric carbon dioxide is increased. Experiments where only carbon dioxide is increased are more likely to demonstrate a decrease in tropical cyclone numbers, similar to the decreases simulated by many climate models for a future, warmer climate. Experiments where the two effects are combined also show decreases in numbers, but these tend to be less for models that demonstrate a strong tropical cyclone response to increased sea surface temperatures. Lastly, further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.« less

Hurricanes and Climate: The U.S. CLIVAR Working Group on Hurricanes

DOE PAGES

Walsh, Kevin J. E.; Camargo, Suzana J.; Vecchi, Gabriel A.; ...

2015-06-01

While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and to understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. Climate and Ocean: Variability, Predictability and Change (CLIVAR). This work, combined with results frommore » other model simulations, has strengthened relationships between tropical cyclone formation rates and climate variables such as midtropospheric vertical velocity, with decreased climatological vertical velocities leading to decreased tropical cyclone formation. Systematic differences are shown between experiments in which only sea surface temperature is increased compared with experiments where only atmospheric carbon dioxide is increased. Experiments where only carbon dioxide is increased are more likely to demonstrate a decrease in tropical cyclone numbers, similar to the decreases simulated by many climate models for a future, warmer climate. Experiments where the two effects are combined also show decreases in numbers, but these tend to be less for models that demonstrate a strong tropical cyclone response to increased sea surface temperatures. Lastly, further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.« less

Multi-scale Quantitative Precipitation Forecasting Using Nonlinear and Nonstationary Teleconnection Signals and Artificial Neural Network Models

EPA Science Inventory

Global sea surface temperature (SST) anomalies can affect terrestrial precipitation via ocean-atmosphere interaction known as climate teleconnection. Non-stationary and non-linear characteristics of the ocean-atmosphere system make the identification of the teleconnection signals...

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.

Impacts on Water Management and Crop Production of Regional Cropping System Adaptation to Climate Change

NASA Astrophysics Data System (ADS)

Zhong, H.; Sun, L.; Tian, Z.; Liang, Z.; Fischer, G.

2014-12-01

China is one of the most populous and fast developing countries, also faces a great pressure on grain production and food security. Multi-cropping system is widely applied in China to fully utilize agro-climatic resources and increase land productivity. As the heat resource keep improving under climate warming, multi-cropping system will also shifting northward, and benefit crop production. But water shortage in North China Plain will constrain the adoption of new multi-cropping system. Effectiveness of multi-cropping system adaptation to climate change will greatly depend on future hydrological change and agriculture water management. So it is necessary to quantitatively express the water demand of different multi-cropping systems under climate change. In this paper, we proposed an integrated climate-cropping system-crops adaptation framework, and specifically focused on: 1) precipitation and hydrological change under future climate change in China; 2) the best multi-cropping system and correspondent crop rotation sequence, and water demand under future agro-climatic resources; 3) attainable crop production with water constraint; and 4) future water management. In order to obtain climate projection and precipitation distribution, global climate change scenario from HADCAM3 is downscaled with regional climate model (PRECIS), historical climate data (1960-1990) was interpolated from more than 700 meteorological observation stations. The regional Agro-ecological Zone (AEZ) model is applied to simulate the best multi-cropping system and crop rotation sequence under projected climate change scenario. Finally, we use the site process-based DSSAT model to estimate attainable crop production and the water deficiency. Our findings indicate that annual land productivity may increase and China can gain benefit from climate change if multi-cropping system would be adopted. This study provides a macro-scale view of agriculture adaptation, and gives suggestions to national agriculture adaptation strategy decisions.

Evaluation of Projected Agricultural Climate Risk over the Contiguous US

NASA Astrophysics Data System (ADS)

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

2017-12-01

Food demands are rising due to an increasing population with changing food preferences, which places pressure on agricultural production. Additionally, climate extremes have recently highlighted the vulnerability of our agricultural system to climate variability. This study seeks to fill two important gaps in current knowledge: how does the widespread response of irrigated crops differ from rainfed and how can we best account for uncertainty in yield responses. We developed a stochastic approach to evaluate climate risk quantitatively to better understand the historical impacts of climate change and estimate the future impacts it may bring about to agricultural system. Our model consists of Bayesian regression, distribution fitting, and Monte Carlo simulation to simulate rainfed and irrigated crop yields at the US county level. The model was fit using historical data for 1970-2010 and was then applied over different climate regions in the contiguous US using the CMIP5 climate projections. The relative importance of many major growing season climate indices, such as consecutive dry days without rainfall or heavy precipitation, was evaluated to determine what climate indices play a role in affecting future crop yields. The statistical modeling framework also evaluated the impact of irrigation by using county-level irrigated and rainfed yields separately. Furthermore, the projected years with negative yield anomalies were specifically evaluated in terms of magnitude, trend and potential climate drivers. This framework provides estimates of the agricultural climate risk for the 21st century that account for the full uncertainty of climate occurrences, range of crop response, and spatial correlation in climate. The results of this study can contribute to decision making about crop choice and water use in an uncertain future climate.

The transparency, reliability and utility of tropical rainforest land-use and land-cover change models.

PubMed

Rosa, Isabel M D; Ahmed, Sadia E; Ewers, Robert M

2014-06-01

Land-use and land-cover (LULC) change is one of the largest drivers of biodiversity loss and carbon emissions globally. We use the tropical rainforests of the Amazon, the Congo basin and South-East Asia as a case study to investigate spatial predictive models of LULC change. Current predictions differ in their modelling approaches, are highly variable and often poorly validated. We carried out a quantitative review of 48 modelling methodologies, considering model spatio-temporal scales, inputs, calibration and validation methods. In addition, we requested model outputs from each of the models reviewed and carried out a quantitative assessment of model performance for tropical LULC predictions in the Brazilian Amazon. We highlight existing shortfalls in the discipline and uncover three key points that need addressing to improve the transparency, reliability and utility of tropical LULC change models: (1) a lack of openness with regard to describing and making available the model inputs and model code; (2) the difficulties of conducting appropriate model validations; and (3) the difficulty that users of tropical LULC models face in obtaining the model predictions to help inform their own analyses and policy decisions. We further draw comparisons between tropical LULC change models in the tropics and the modelling approaches and paradigms in other disciplines, and suggest that recent changes in the climate change and species distribution modelling communities may provide a pathway that tropical LULC change modellers may emulate to further improve the discipline. Climate change models have exerted considerable influence over public perceptions of climate change and now impact policy decisions at all political levels. We suggest that tropical LULC change models have an equally high potential to influence public opinion and impact the development of land-use policies based on plausible future scenarios, but, to do that reliably may require further improvements in the discipline. © 2014 John Wiley & Sons Ltd.

Strategy to Conduct Quantitative Ecohydrologic Analysis of a UNESCO World Heritage Site: the Peace-Athabasca Delta, Canada

NASA Astrophysics Data System (ADS)

Ward, E. M.; Gorelick, S.; Hadly, E. A.

2016-12-01

The 6000 km2 Peace-Athabasca Delta ("Delta") in northeastern Alberta, Canada, is a Ramsar Convention Wetland and UNESCO World Heritage Site ("in Danger" status pending) where hydropower development and climate change are creating ecological impacts through desiccation and reduction in Delta shoreline habitat. We focus on ecohydrologic changes and mitigation and adaptation options to advance the field of ecohydrology using interdisciplinary technology by combining, for the first time, satellite remote sensing and hydrologic simulation with individual-based population modeling of muskrat (Ondatra zibethicus), a species native to the Delta whose population dynamics are strongly controlled by the hydrology of floodplain lakes. We are building a conceptual and quantitative modeling framework linking climate change, upstream water demand, and hydrologic change in the floodplain to muskrat population dynamics with the objective of exploring the impacts of these stressors on this ecosystem. We explicitly account for cultural and humanistic influences and are committed to effective communication with the regional subsistence community that depends on muskrat for food and income. Our modeling framework can ultimately serve as the basis for improved stewardship and sustainable development upstream of stressed freshwater deltaic, coastal and lake systems worldwide affected by climate change, providing a predictive tool to quantify population changes of animals relevant to regional subsistence food security and commercial trapping.

Pollen-based continental climate reconstructions at 6 and 21 ka: a global synthesis

USGS Publications Warehouse

Bartlein, P.J.; Harrison, S.P.; Brewer, Sandra; Connor, S.; Davis, B.A.S.; Gajewski, K.; Guiot, J.; Harrison-Prentice, T. I.; Henderson, A.; Peyron, O.; Prentice, I.C.; Scholze, M.; Seppa, H.; Shuman, B.; Sugita, S.; Thompson, R.S.; Viau, A.E.; Williams, J.; Wu, H.

2010-01-01

Subfossil pollen and plant macrofossil data derived from 14C-dated sediment profiles can provide quantitative information on glacial and interglacial climates. The data allow climate variables related to growing-season warmth, winter cold, and plant-available moisture to be reconstructed. Continental-scale reconstructions have been made for the mid-Holocene (MH, around 6 ka) and Last Glacial Maximum (LGM, around 21 ka), allowing comparison with palaeoclimate simulations currently being carried out as part of the fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change. The synthesis of the available MH and LGM climate reconstructions and their uncertainties, obtained using modern-analogue, regression and model-inversion techniques, is presented for four temperature variables and two moisture variables. Reconstructions of the same variables based on surface-pollen assemblages are shown to be accurate and unbiased. Reconstructed LGM and MH climate anomaly patterns are coherent, consistent between variables, and robust with respect to the choice of technique. They support a conceptual model of the controls of Late Quaternary climate change whereby the first-order effects of orbital variations and greenhouse forcing on the seasonal cycle of temperature are predictably modified by responses of the atmospheric circulation and surface energy balance.

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.

Measuring the burden of disease due to climate change and developing a forecast model in South Korea.

PubMed

Yoon, S-J; Oh, I-H; Seo, H-Y; Kim, E-J

2014-08-01

Climate change influences human health in various ways, and quantitative assessments of the effect of climate change on health at national level are becoming essential for environmental health management. This study quantified the burden of disease attributable to climate change in Korea using disability-adjusted life years (DALY), and projected how this would change over time. Diseases related to climate change in Korea were selected, and meteorological data for each risk factor of climate change were collected. Mortality was calculated, and a database of incidence and prevalence was established. After measuring the burden of each disease, the total burden of disease related to climate change was assessed by multiplying population-attributable fractions. Finally, an estimation model for the burden of disease was built based on Korean climate data. The total burden of disease related to climate change in Korea was 6.85 DALY/1000 population in 2008. Cerebrovascular diseases induced by heat waves accounted for 72.1% of the total burden of disease (hypertensive disease 1.82 DALY/1000 population, ischaemic heart disease 1.56 DALY/1000 population, cerebrovascular disease 1.56 DALY/1000 population). According to the estimation model, the total burden of disease will be 11.48 DALY/1000 population in 2100, which is twice the total burden of disease in 2008. This study quantified the burden of disease caused by climate change in Korea, and provides valuable information for determining the priorities of environmental health policy in East Asian countries with similar climates. Copyright © 2014 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Coupling Processes Between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, M. K. W.; Weisenstein, Debra; Shia, Run-Li; Sze, N. D.

1997-01-01

This is the first semi-annual report for NAS5-97039 summarizing work performed for January 1997 through June 1997. Work in this project is related to NAS1-20666, also funded by NASA ACMAP. The work funded in this project also benefits from work at AER associated with the AER three-dimensional isentropic transport model funded by NASA AEAP and the AER two-dimensional climate-chemistry model (co-funded by Department of Energy). The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling tools for this work are the AER two-dimensional chemistry-transport model, the AER two-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry.

Future Climate Change in the Baltic Sea Area

NASA Astrophysics Data System (ADS)

Bøssing Christensen, Ole; Kjellström, Erik; Zorita, Eduardo; Sonnenborg, Torben; Meier, Markus; Grinsted, Aslak

2015-04-01

Regional climate models have been used extensively since the first assessment of climate change in the Baltic Sea region published in 2008, not the least for studies of Europe (and including the Baltic Sea catchment area). Therefore, conclusions regarding climate model results have a better foundation than was the case for the first BACC report of 2008. This presentation will report model results regarding future climate. What is the state of understanding about future human-driven climate change? We will cover regional models, statistical downscaling, hydrological modelling, ocean modelling and sea-level change as it is projected for the Baltic Sea region. Collections of regional model simulations from the ENSEMBLES project for example, financed through the European 5th Framework Programme and the World Climate Research Programme Coordinated Regional Climate Downscaling Experiment, have made it possible to obtain an increasingly robust estimation of model uncertainty. While the first Baltic Sea assessment mainly used four simulations from the European 5th Framework Programme PRUDENCE project, an ensemble of 13 transient regional simulations with twice the horizontal resolution reaching the end of the 21st century has been available from the ENSEMBLES project; therefore it has been possible to obtain more quantitative assessments of model uncertainty. The literature about future climate change in the Baltic Sea region is largely built upon the ENSEMBLES project. Also within statistical downscaling, a considerable number of papers have been published, encompassing now the application of non-linear statistical models, projected changes in extremes and correction of climate model biases. The uncertainty of hydrological change has received increasing attention since the previous Baltic Sea assessment. Several studies on the propagation of uncertainties originating in GCMs, RCMs, and emission scenarios are presented. The number of studies on uncertainties related to downscaling and impact models is relatively small, but more are emerging. A large number of coupled climate-environmental scenario simulations for the Baltic Sea have been performed within the BONUS+ projects (ECOSUPPORT, INFLOW, AMBER and Baltic-C (2009-2011)), using various combinations of output from GCMs, RCMs, hydrological models and scenarios for load and emission of nutrients as forcing for Baltic Sea models. Such a large ensemble of scenario simulations for the Baltic Sea has never before been produced and enables for the first time an estimation of uncertainties.

The fate of Amazonian ecosystems over the coming century arising from changes in climate, atmospheric CO2, and land use.

PubMed

Zhang, Ke; de Almeida Castanho, Andrea D; Galbraith, David R; Moghim, Sanaz; Levine, Naomi M; Bras, Rafael L; Coe, Michael T; Costa, Marcos H; Malhi, Yadvinder; Longo, Marcos; Knox, Ryan G; McKnight, Shawna; Wang, Jingfeng; Moorcroft, Paul R

2015-02-20

There is considerable interest in understanding the fate of the Amazon over the coming century in the face of climate change, rising atmospheric CO 2 levels, ongoing land transformation, and changing fire regimes within the region. In this analysis, we explore the fate of Amazonian ecosystems under the combined impact of these four environmental forcings using three terrestrial biosphere models (ED2, IBIS, and JULES) forced by three bias-corrected IPCC AR4 climate projections (PCM1, CCSM3, and HadCM3) under two land-use change scenarios. We assess the relative roles of climate change, CO 2 fertilization, land-use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change are primarily determined by the direction and severity of projected changes in regional precipitation: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%. However, the models predict that CO 2 fertilization will enhance vegetation productivity and alleviate climate-induced increases in plant water stress, and, as a result, sustain high biomass forests, even under the driest climate scenario. Land-use change and climate-driven changes in fire frequency are predicted to cause additional aboveground biomass loss and reductions in forest extent. The relative impact of land use and fire dynamics compared to climate and CO 2 impacts varies considerably, depending on both the climate and land-use scenario, and on the terrestrial biosphere model used, highlighting the importance of improved quantitative understanding of all four factors - climate change, CO 2 fertilization effects, fire, and land use - to the fate of the Amazon over the coming century. © 2015 John Wiley & Sons Ltd.

Climate science and famine early warning

USGS Publications Warehouse

Verdin, James P.; Funk, Chris; Senay, Gabriel B.; Choularton, R.

2005-01-01

Food security assessment in sub-Saharan Africa requires simultaneous consideration of multiple socio-economic and environmental variables. Early identification of populations at risk enables timely and appropriate action. Since large and widely dispersed populations depend on rainfed agriculture and pastoralism, climate monitoring and forecasting are important inputs to food security analysis. Satellite rainfall estimates (RFE) fill in gaps in station observations, and serve as input to drought index maps and crop water balance models. Gridded rainfall time-series give historical context, and provide a basis for quantitative interpretation of seasonal precipitation forecasts. RFE are also used to characterize flood hazards, in both simple indices and stream flow models. In the future, many African countries are likely to see negative impacts on subsistence agriculture due to the effects of global warming. Increased climate variability is forecast, with more frequent extreme events. Ethiopia requires special attention. Already facing a food security emergency, troubling persistent dryness has been observed in some areas, associated with a positive trend in Indian Ocean sea surface temperatures. Increased African capacity for rainfall observation, forecasting, data management and modelling applications is urgently needed. Managing climate change and increased climate variability require these fundamental technical capacities if creative coping strategies are to be devised.

Tropical and Extratropical Cyclone Damages under Climate Change

NASA Astrophysics Data System (ADS)

Ranson, M.; Kousky, C.; Ruth, M.; Jantarasami, L.; Crimmins, A.; Tarquinio, L.

2014-12-01

This paper provides the first quantitative synthesis of the rapidly growing literature on future tropical and extratropical cyclone losses under climate change. We estimate a probability distribution for the predicted impact of changes in global surface air temperatures on future storm damages, using an ensemble of 296 estimates of the temperature-damage relationship from twenty studies. Our analysis produces three main empirical results. First, we find strong but not conclusive support for the hypothesis that climate change will cause damages from tropical cyclones and wind storms to increase, with most models (84 and 92 percent, respectively) predicting higher future storm damages due to climate change. Second, there is substantial variation in projected changes in losses across regions. Potential changes in damages are greatest in the North Atlantic basin, where the multi-model average predicts that a 2.5°C increase in global surface air temperature would cause hurricane damages to increase by 62 percent. The ensemble predictions for Western North Pacific tropical cyclones and European wind storms (extratropical cyclones) are approximately one third of that magnitude. Finally, our analysis shows that existing models of storm damages under climate change generate a wide range of predictions, ranging from moderate decreases to very large increases in losses.

Climate science and famine early warning.

PubMed

Verdin, James; Funk, Chris; Senay, Gabriel; Choularton, Richard

2005-11-29

Food security assessment in sub-Saharan Africa requires simultaneous consideration of multiple socio-economic and environmental variables. Early identification of populations at risk enables timely and appropriate action. Since large and widely dispersed populations depend on rainfed agriculture and pastoralism, climate monitoring and forecasting are important inputs to food security analysis. Satellite rainfall estimates (RFE) fill in gaps in station observations, and serve as input to drought index maps and crop water balance models. Gridded rainfall time-series give historical context, and provide a basis for quantitative interpretation of seasonal precipitation forecasts. RFE are also used to characterize flood hazards, in both simple indices and stream flow models. In the future, many African countries are likely to see negative impacts on subsistence agriculture due to the effects of global warming. Increased climate variability is forecast, with more frequent extreme events. Ethiopia requires special attention. Already facing a food security emergency, troubling persistent dryness has been observed in some areas, associated with a positive trend in Indian Ocean sea surface temperatures. Increased African capacity for rainfall observation, forecasting, data management and modelling applications is urgently needed. Managing climate change and increased climate variability require these fundamental technical capacities if creative coping strategies are to be devised.

Climate science and famine early warning

PubMed Central

Verdin, James; Funk, Chris; Senay, Gabriel; Choularton, Richard

2005-01-01

Food security assessment in sub-Saharan Africa requires simultaneous consideration of multiple socio-economic and environmental variables. Early identification of populations at risk enables timely and appropriate action. Since large and widely dispersed populations depend on rainfed agriculture and pastoralism, climate monitoring and forecasting are important inputs to food security analysis. Satellite rainfall estimates (RFE) fill in gaps in station observations, and serve as input to drought index maps and crop water balance models. Gridded rainfall time-series give historical context, and provide a basis for quantitative interpretation of seasonal precipitation forecasts. RFE are also used to characterize flood hazards, in both simple indices and stream flow models. In the future, many African countries are likely to see negative impacts on subsistence agriculture due to the effects of global warming. Increased climate variability is forecast, with more frequent extreme events. Ethiopia requires special attention. Already facing a food security emergency, troubling persistent dryness has been observed in some areas, associated with a positive trend in Indian Ocean sea surface temperatures. Increased African capacity for rainfall observation, forecasting, data management and modelling applications is urgently needed. Managing climate change and increased climate variability require these fundamental technical capacities if creative coping strategies are to be devised. PMID:16433101

Spatial diffusion of influenza outbreak-related climate factors in Chiang Mai Province, Thailand.

PubMed

Nakapan, Supachai; Tripathi, Nitin Kumar; Tipdecho, Taravudh; Souris, Marc

2012-10-24

Influenza is one of the most important leading causes of respiratory illness in the countries located in the tropical areas of South East Asia and Thailand. In this study the climate factors associated with influenza incidence in Chiang Mai Province, Northern Thailand, were investigated. Identification of factors responsible for influenza outbreaks and the mapping of potential risk areas in Chiang Mai are long overdue. This work examines the association between yearly climate patterns between 2001 and 2008 and influenza outbreaks in the Chiang Mai Province. The climatic factors included the amount of rainfall, percent of rainy days, relative humidity, maximum, minimum temperatures and temperature difference. The study develops a statistical analysis to quantitatively assess the relationship between climate and influenza outbreaks and then evaluate its suitability for predicting influenza outbreaks. A multiple linear regression technique was used to fit the statistical model. The Inverse Distance Weighted (IDW) interpolation and Geographic Information System (GIS) techniques were used in mapping the spatial diffusion of influenza risk zones. The results show that there is a significance correlation between influenza outbreaks and climate factors for the majority of the studied area. A statistical analysis was conducted to assess the validity of the model comparing model outputs and actual outbreaks.

Quantifying climate change impacts on runoff of zoonotic pathogens from land

NASA Astrophysics Data System (ADS)

Sterk, Ankie; de Roda Husman, Ana Maria; Stergiadi, Maria; de Nijs, Ton; Schijven, Jack

2013-04-01

Several studies have shown a correlation between rainfall and waterborne disease outbreaks. One of the mechanisms whereby rainfall may cause outbreaks is through an increase in runoff of animal faeces from fields to surface waters. Faeces originating from wildlife, domestic animals or manure-fertilized fields, is considered an important source of zoonotic pathogens to which people may be exposed by water recreation or drinking-water consumption. Climate changes affect runoff because of increasing winter precipitation and more extreme precipitation events, as well as changes in evaporation. Furthermore, drier summers are leading to longer periods of high soil moisture deficits, increasing the hydrophobicity of soil and consequently changing infiltration capacities. A conceptual model is designed to describe the impacts of climate changes on the terrestrial and aquatic ecosystems, which are both directly and indirectly affecting pathogen loads in the environment and subsequent public health risks. One of the major outcomes was the lack of quantitative data and limited qualitative analyses of impacts of climate changes on pathogen runoff. Quantifying the processes by which micro-organisms are transported from fields to waters is important to be able to estimate such impacts to enable targeted implementation of effective intervention measures. A quantitative model using Mathematica software will be developed to estimate concentrations of pathogens originating from overland flow during runoff events. Different input sources will be included by applying different land-use scenarios, including point source faecal pollution from dairy cows and geese and diffuse source pollution by fertilization. Zoonotic pathogens, i.e. Cryptosporidium and Campylobacter, were selected based on transport properties, faecal loads and disease burden. Transport and survival rates of these pathogens are determined including effects of changes in precipitation but also temperature induced changes on die-off. Moreover, besides climate and surface variables, changes in soil or vegetation and adjustments in agricultural policy are considered. Output of this model can be used to assess how expected climate changes could affect pathogen concentrations in surface waters. The long term aim is to include this information in a larger framework, to quantify the impact of climate change on the infection and eventual disease risks due to exposure to water transmitted pathogens.

Quantitative Models for Ecosystem Assessment in Narragansett Bay: Response to Nutrient Loading and Other Stressors

EPA Science Inventory

Multiple drivers, including nutrient loading and climate change, affect the Narragansett Bay ecosystem. Managers are interested in understanding the timing and magnitude of these effects, as well as ecosystem responses to restoration actions, such as the capacity and potential fo...

An integrated hydrological modeling approach for detection and attribution of climatic and human impacts on coastal water resources

NASA Astrophysics Data System (ADS)

Feng, Dapeng; Zheng, Yi; Mao, Yixin; Zhang, Aijing; Wu, Bin; Li, Jinguo; Tian, Yong; Wu, Xin

2018-02-01

Water resources in coastal areas can be profoundly influenced by both climate change and human activities. These climatic and human impacts are usually intertwined and difficult to isolate. This study developed an integrated model-based approach for detection and attribution of climatic and human impacts and applied this approach to the Luanhe Plain, a typical coastal area in northern China. An integrated surface water-groundwater model was developed for the study area using GSFLOW (coupled groundwater and surface-water flow). Model calibration and validation were performed for background years between 1975 and 2000. The variation in water resources between the 1980s and 1990s was then quantitatively attributed to climate variability, groundwater pumping and changes in upstream inflow. Climate scenarios for future years (2075-2100) were also developed by downscaling the projections in CMIP5. Potential water resource responses to climate change, as well as their uncertainty, were then investigated through integrated modeling. The study results demonstrated the feasibility and value of the integrated modeling-based analysis for water resource management in areas with complex surface water-groundwater interaction. Specific findings for the Luanhe Plain included the following: (1) During the historical period, upstream inflow had the most significant impact on river outflow to the sea, followed by climate variability, whereas groundwater pumping was the least influential. (2) The increase in groundwater pumping had a dominant influence on the decline in groundwater change, followed by climate variability. (3) Synergetic and counteractive effects among different impacting factors, while identified, were not significant, which implied that the interaction among different factors was not very strong in this case. (4) It is highly probable that future climate change will accelerate groundwater depletion in the study area, implying that strict regulations for groundwater pumping are imperative for adaptation.

Satellite Remote Sensing and Mesoscale Modeling of Biomass Burning Aerosols over the Southeast Asian Maritime Continent: Climatic Implications of Smokes on Regional Energy Balance, Cloud Formations and Precipitations

NASA Astrophysics Data System (ADS)

Feng, N.

2015-12-01

The influences of anthropogenic aerosols have been suggested as an important reason for climate changes over Southeast Asia (SE Asia, 10°S~20°N and 90°E~135°E). Accurate observations and modelling of aerosols effects on the weather and climate patterns is crucial for a better understanding and mitigation of anthropogenic climate change. This study uses NASA satellite observations along with online-coupled Weather Research and Forecasting model with Chemistry (WRF-Chem) to evaluate aerosols impacts on climate over SE Asia. We assess the direct and semi-direct radiative effects of smoke particles over this region during September, 2009 when a significant El Niño event caused the highest biomass burning activity during the last 15 years. Quantification efforts are made to assess how changes of radiative and non radiative parameters (sensible and latent heat) due to smoke aerosols would affect regional climate process such as precipitations, clouds and planetary boundary layer process. Comparison of model simulations for the current land cover conditions against surface meteorological observations and satellite observations of precipitations and cloudiness show satisfactory performance of the model over our study area. In order to quantitatively validate the model results, several experiments will be performed to test the aerosols radiative feedback under different radiation schemes and with/without considering aerosol effects explicitly in the model. Relevant ground-based data (e.g. AERONET), along with aerosol vertical profile data from CALIPSO, will also be applied.

Assessing present and future climate changes in Siberia and their regional socioeconomic consequences using a web-based big data geoprocessing platform

NASA Astrophysics Data System (ADS)

Alexeev, V. A.; Gordov, E. P.

2016-12-01

Recently initiated collaborative research project is presented. Its main objective is to develop high spatial and temporal resolution datasets for studying the ongoing and future climate changes in Siberia, caused by global and regional processes in the atmosphere and the ocean. This goal will be achieved by using a set of regional and global climate models for the analysis of the mechanisms of climate change and quantitative assessment of changes in key climate variables, including analysis of extreme weather and climate events and their dynamics, evaluation of the frequency, amplitude and the risks caused by the extreme events in the region. The main practical application of the project is to provide experts, stakeholders and the public with quantitative information about the future climate change in Siberia obtained on the base of a computational web- geoinformation platform. The thematic platform will be developed in order to facilitate processing and analysis of high resolution georeferenced datasets that will be delivered and made available to scientific community, policymakes and other end users as a result of the project. Software packages will be developed to implement calculation of various climatological indicators in order to characterize and diagnose climate change and its dynamics, as well as to archive results in digital form of electronic maps (GIS layers). By achieving these goals the project will provide science based tools necessary for developing mitigation measures for adapting to climate change and reducing negative impact on the population and infrastructure of the region. Financial support of the computational web- geoinformation platform prototype development by the RF Ministry of Education and Science under Agreement 14.613.21.0037 (RFMEFI61315X0037) is acknowledged.

Heat-related mortality in a warming climate: projections for 12 U.S. cities.

PubMed

Petkova, Elisaveta P; Bader, Daniel A; Anderson, G Brooke; Horton, Radley M; Knowlton, Kim; Kinney, Patrick L

2014-10-31

Heat is among the deadliest weather-related phenomena in the United States, and the number of heat-related deaths may increase under a changing climate, particularly in urban areas. Regional adaptation planning is unfortunately often limited by the lack of quantitative information on potential future health responses. This study presents an assessment of the future impacts of climate change on heat-related mortality in 12 cities using 16 global climate models, driven by two scenarios of greenhouse gas emissions. Although the magnitude of the projected heat effects was found to differ across time, cities, climate models and greenhouse pollution emissions scenarios, climate change was projected to result in increases in heat-related fatalities over time throughout the 21st century in all of the 12 cities included in this study. The increase was more substantial under the high emission pathway, highlighting the potential benefits to public health of reducing greenhouse gas emissions. Nearly 200,000 heat-related deaths are projected to occur in the 12 cities by the end of the century due to climate warming, over 22,000 of which could be avoided if we follow a low GHG emission pathway. The presented estimates can be of value to local decision makers and stakeholders interested in developing strategies to reduce these impacts and building climate change resilience.

Multilevel model of safety climate for furniture industries.

PubMed

Rodrigues, Matilde A; Arezes, Pedro M; Leão, Celina P

2015-01-01

Furniture companies can analyze their safety status using quantitative measures. However, the data needed are not always available and the number of accidents is under-reported. Safety climate scales may be an alternative. However, there are no validated Portuguese scales that account for the specific attributes of the furniture sector. The current study aims to develop and validate an instrument that uses a multilevel structure to measure the safety climate of the Portuguese furniture industry. The Safety Climate in Wood Industries (SCWI) model was developed and applied to the safety climate analysis using three different scales: organizational, group and individual. A multilevel exploratory factor analysis was performed to analyze the factorial structure. The studied companies' safety conditions were also analyzed. Different factorial structures were found between and within levels. In general, the results show the presence of a group-level safety climate. The scores of safety climates are directly and positively related to companies' safety conditions; the organizational scale is the one that best reflects the actual safety conditions. The SCWI instrument allows for the identification of different safety climates in groups that comprise the same furniture company and it seems to reflect those groups' safety conditions. The study also demonstrates the need for a multilevel analysis of the studied instrument.

Heat-Related Mortality in a Warming Climate: Projections for 12 U.S. Cities

NASA Technical Reports Server (NTRS)

Petkova, Elisaveta P.; Bader, Daniel A.; Anderson, G. Brooke; Horton, Radley M.; Knowlton, Kim; Kinney, Patrick L.

2014-01-01

Heat is among the deadliest weather-related phenomena in the United States, and the number of heat-related deaths may increase under a changing climate, particularly in urban areas. Regional adaptation planning is unfortunately often limited by the lack of quantitative information on potential future health responses. This study presents an assessment of the future impacts of climate change on heat-related mortality in 12 cities using 16 global climate models, driven by two scenarios of greenhouse gas emissions. Although the magnitude of the projected heat effects was found to differ across time, cities, climate models and greenhouse pollution emissions scenarios, climate change was projected to result in increases in heat-related fatalities over time throughout the 21st century in all of the 12 cities included in this study. The increase was more substantial under the high emission pathway, highlighting the potential benefits to public health of reducing greenhouse gas emissions. Nearly 200,000 heat-related deaths are projected to occur in the 12 cities by the end of the century due to climate warming, over 22,000 of which could be avoided if we follow a low GHG emission pathway. The presented estimates can be of value to local decision makers and stakeholders interested in developing strategies to reduce these impacts and building climate change resilience.

A model-based assessment of the effects of projected climate change on the water resources of Jordan.

PubMed

Wade, A J; Black, E; Brayshaw, D J; El-Bastawesy, M; Holmes, P A C; Butterfield, D; Nuimat, S; Jamjoum, K

2010-11-28

This paper is concerned with the quantification of the likely effect of anthropogenic climate change on the water resources of Jordan by the end of the twenty-first century. Specifically, a suite of hydrological models are used in conjunction with modelled outcomes from a regional climate model, HadRM3, and a weather generator to determine how future flows in the upper River Jordan and in the Wadi Faynan may change. The results indicate that groundwater will play an important role in the water security of the country as irrigation demands increase. Given future projections of reduced winter rainfall and increased near-surface air temperatures, the already low groundwater recharge will decrease further. Interestingly, the modelled discharge at the Wadi Faynan indicates that extreme flood flows will increase in magnitude, despite a decrease in the mean annual rainfall. Simulations projected no increase in flood magnitude in the upper River Jordan. Discussion focuses on the utility of the modelling framework, the problems of making quantitative forecasts and the implications of reduced water availability in Jordan.

Physical and economic consequences of climate change in Europe.

PubMed

Ciscar, Juan-Carlos; Iglesias, Ana; Feyen, Luc; Szabó, László; Van Regemorter, Denise; Amelung, Bas; Nicholls, Robert; Watkiss, Paul; Christensen, Ole B; Dankers, Rutger; Garrote, Luis; Goodess, Clare M; Hunt, Alistair; Moreno, Alvaro; Richards, Julie; Soria, Antonio

2011-02-15

Quantitative estimates of the economic damages of climate change usually are based on aggregate relationships linking average temperature change to loss in gross domestic product (GDP). However, there is a clear need for further detail in the regional and sectoral dimensions of impact assessments to design and prioritize adaptation strategies. New developments in regional climate modeling and physical-impact modeling in Europe allow a better exploration of those dimensions. This article quantifies the potential consequences of climate change in Europe in four market impact categories (agriculture, river floods, coastal areas, and tourism) and one nonmarket impact (human health). The methodology integrates a set of coherent, high-resolution climate change projections and physical models into an economic modeling framework. We find that if the climate of the 2080s were to occur today, the annual loss in household welfare in the European Union (EU) resulting from the four market impacts would range between 0.2-1%. If the welfare loss is assumed to be constant over time, climate change may halve the EU's annual welfare growth. Scenarios with warmer temperatures and a higher rise in sea level result in more severe economic damage. However, the results show that there are large variations across European regions. Southern Europe, the British Isles, and Central Europe North appear most sensitive to climate change. Northern Europe, on the other hand, is the only region with net economic benefits, driven mainly by the positive effects on agriculture. Coastal systems, agriculture, and river flooding are the most important of the four market impacts assessed.

Physical and economic consequences of climate change in Europe

PubMed Central

Ciscar, Juan-Carlos; Iglesias, Ana; Feyen, Luc; Szabó, László; Van Regemorter, Denise; Amelung, Bas; Nicholls, Robert; Watkiss, Paul; Christensen, Ole B.; Dankers, Rutger; Garrote, Luis; Goodess, Clare M.; Hunt, Alistair; Moreno, Alvaro; Richards, Julie; Soria, Antonio

2011-01-01

Quantitative estimates of the economic damages of climate change usually are based on aggregate relationships linking average temperature change to loss in gross domestic product (GDP). However, there is a clear need for further detail in the regional and sectoral dimensions of impact assessments to design and prioritize adaptation strategies. New developments in regional climate modeling and physical-impact modeling in Europe allow a better exploration of those dimensions. This article quantifies the potential consequences of climate change in Europe in four market impact categories (agriculture, river floods, coastal areas, and tourism) and one nonmarket impact (human health). The methodology integrates a set of coherent, high-resolution climate change projections and physical models into an economic modeling framework. We find that if the climate of the 2080s were to occur today, the annual loss in household welfare in the European Union (EU) resulting from the four market impacts would range between 0.2–1%. If the welfare loss is assumed to be constant over time, climate change may halve the EU's annual welfare growth. Scenarios with warmer temperatures and a higher rise in sea level result in more severe economic damage. However, the results show that there are large variations across European regions. Southern Europe, the British Isles, and Central Europe North appear most sensitive to climate change. Northern Europe, on the other hand, is the only region with net economic benefits, driven mainly by the positive effects on agriculture. Coastal systems, agriculture, and river flooding are the most important of the four market impacts assessed. PMID:21282624

Quantitative Analysis of Critical Factors for the Climate Impact of Landfill Mining.

PubMed

Laner, David; Cencic, Oliver; Svensson, Niclas; Krook, Joakim

2016-07-05

Landfill mining has been proposed as an innovative strategy to mitigate environmental risks associated with landfills, to recover secondary raw materials and energy from the deposited waste, and to enable high-valued land uses at the site. The present study quantitatively assesses the importance of specific factors and conditions for the net contribution of landfill mining to global warming using a novel, set-based modeling approach and provides policy recommendations for facilitating the development of projects contributing to global warming mitigation. Building on life-cycle assessment, scenario modeling and sensitivity analysis methods are used to identify critical factors for the climate impact of landfill mining. The net contributions to global warming of the scenarios range from -1550 (saving) to 640 (burden) kg CO2e per Mg of excavated waste. Nearly 90% of the results' total variation can be explained by changes in four factors, namely the landfill gas management in the reference case (i.e., alternative to mining the landfill), the background energy system, the composition of the excavated waste, and the applied waste-to-energy technology. Based on the analyses, circumstances under which landfill mining should be prioritized or not are identified and sensitive parameters for the climate impact assessment of landfill mining are highlighted.

Integrated monitoring and information systems for managing aquatic invasive species in a changing climate.

PubMed

Lee, Henry; Reusser, Deborah A; Olden, Julian D; Smith, Scott S; Graham, Jim; Burkett, Virginia; Dukes, Jeffrey S; Piorkowski, Robert J; McPhedran, John

2008-06-01

Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change.

Integrated monitoring and information systems for managing aquatic invasive species in a changing climate

USGS Publications Warehouse

Lee, Henry; Reusser, Deborah A.; Olden, Julian D.; Smith, Scott S.; Graham, Jim; Burkett, Virginia; Dukes, Jeffrey S.; Piorkowski, Robert J.; Mcphedran, John

2008-01-01

Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change

Time-lag effects of global vegetation responses to climate change.

PubMed

Wu, Donghai; Zhao, Xiang; Liang, Shunlin; Zhou, Tao; Huang, Kaicheng; Tang, Bijian; Zhao, Wenqian

2015-09-01

Climate conditions significantly affect vegetation growth in terrestrial ecosystems. Due to the spatial heterogeneity of ecosystems, the vegetation responses to climate vary considerably with the diverse spatial patterns and the time-lag effects, which are the most important mechanism of climate-vegetation interactive effects. Extensive studies focused on large-scale vegetation-climate interactions use the simultaneous meteorological and vegetation indicators to develop models; however, the time-lag effects are less considered, which tends to increase uncertainty. In this study, we aim to quantitatively determine the time-lag effects of global vegetation responses to different climatic factors using the GIMMS3g NDVI time series and the CRU temperature, precipitation, and solar radiation datasets. First, this study analyzed the time-lag effects of global vegetation responses to different climatic factors. Then, a multiple linear regression model and partial correlation model were established to statistically analyze the roles of different climatic factors on vegetation responses, from which the primary climate-driving factors for different vegetation types were determined. The results showed that (i) both the time-lag effects of the vegetation responses and the major climate-driving factors that significantly affect vegetation growth varied significantly at the global scale, which was related to the diverse vegetation and climate characteristics; (ii) regarding the time-lag effects, the climatic factors explained 64% variation of the global vegetation growth, which was 11% relatively higher than the model ignoring the time-lag effects; (iii) for the area with a significant change trend (for the period 1982-2008) in the global GIMMS3g NDVI (P < 0.05), the primary driving factor was temperature; and (iv) at the regional scale, the variation in vegetation growth was also related to human activities and natural disturbances. Considering the time-lag effects is quite important for better predicting and evaluating the vegetation dynamics under the background of global climate change. © 2015 John Wiley & Sons Ltd.

Model-based scenario planning to inform climate change adaptation in the Northern Great Plains—Final report

USGS Publications Warehouse

Symstad, Amy J.; Miller, Brian W.; Friedman, Jonathan M.; Fisichelli, Nicholas A.; Ray, Andrea J.; Rowland, Erika; Schuurman, Gregor W.

2017-12-18

Public SummaryWe worked with managers in two focal areas to plan for the uncertain future by integrating quantitative climate change scenarios and simulation modeling into scenario planning exercises.In our central North Dakota focal area, centered on Knife River Indian Villages National Historic Site, managers are concerned about how changes in flood severity and growing conditions for native and invasive plants may affect archaeological resources and cultural landscapes associated with the Knife and Missouri Rivers. Climate projections and hydrological modeling based on those projections indicate plausible changes in spring and summer soil moisture ranging from a 7 percent decrease to a 13 percent increase and maximum winter snowpack (important for spring flooding) changes ranging from a 13 percent decrease to a 47 percent increase. Facilitated discussions among managers and scientists exploring the implications of these different climate scenarios for resource management revealed potential conflicts between protecting archeological sites and fostering riparian cottonwood forests. The discussions also indicated the need to prioritize archeological sites for excavation or protection and culturally important plant species for intensive management attention.In our southwestern South Dakota focal area, centered on Badlands National Park, managers are concerned about how changing climate will affect vegetation production, wildlife populations, and erosion of fossils, archeological artifacts, and roads. Climate scenarios explored by managers and scientists in this focal area ranged from a 13 percent decrease to a 33 percent increase in spring precipitation, which is critical to plant growth in the northern Great Plains region, and a slight decrease to a near doubling of intense rain events. Facilitated discussions in this focal area concluded that greater effort should be put into preparing for emergency protection, excavation, and preservation of exposed fossils or artifacts and revealed substantial opportunities for different agencies to learn from each other and cooperate on common management goals. Follow up quantitative simulation modeling of grassland dynamics helped quantify the degree of change expected in vegetation production under the wide range of climate scenarios and suggested that (a) low grazing rates could be adversely affecting vegetation composition in the national park and (b) understanding of the management practices needed to maintain desired vegetation conditions is incomplete.

Estimation of Remote Microclimates from Weather Station Data with Applications to Landscape Architecture.

NASA Astrophysics Data System (ADS)

Brown, Robert Douglas

Several components of a system for quantitative application of climatic statistics to landscape planning and design (CLIMACS) have been developed. One component model (MICROSIM) estimated the microclimate at the top of a remote crop using physically-based models and inputs of weather station data. Temperatures at the top of unstressed, uniform crops on flat terrain within 1600 m of a recording weather station were estimated within 1.0 C 96% of the time for a corn crop and 92% of the time for a soybean crop. Crop top winds were estimated within 0.4 m/s 92% of the time for corn and 100% of the time for soybean. This is of sufficient accuracy for application in landscape planning and design models. A physically-based model (COMFA) was developed for the determination of outdoor human thermal comfort from microclimate inputs. Estimated versus measured comfort levels in a wide range of environments agreed with a correlation coefficient of r = 0.91. Using these components, the CLIMACS concept has been applied to a typical planning example. Microclimate data were generated from weather station information using MICROSIM, then input to COMFA and to a house energy consumption model called HOTCAN to derive quantitative climatic justification for design decisions.

Quantitative Models Describing Past and Current Nutrient Fluxes and Associated Ecosystem Level Responses in the Narragansett Bay Ecosystem

EPA Science Inventory

Multiple drivers, including nutrient loading and climate change, affect the Narragansett Bay ecosystem in Rhode Island/Massachusetts, USA. Managers are interested in understanding the timing and magnitude of these effects, and ecosystem responses to restoration actions. To provid...

Beyond equilibrium climate sensitivity

NASA Astrophysics Data System (ADS)

Knutti, Reto; Rugenstein, Maria A. A.; Hegerl, Gabriele C.

2017-10-01

Equilibrium climate sensitivity characterizes the Earth's long-term global temperature response to increased atmospheric CO2 concentration. It has reached almost iconic status as the single number that describes how severe climate change will be. The consensus on the 'likely' range for climate sensitivity of 1.5 °C to 4.5 °C today is the same as given by Jule Charney in 1979, but now it is based on quantitative evidence from across the climate system and throughout climate history. The quest to constrain climate sensitivity has revealed important insights into the timescales of the climate system response, natural variability and limitations in observations and climate models, but also concerns about the simple concepts underlying climate sensitivity and radiative forcing, which opens avenues to better understand and constrain the climate response to forcing. Estimates of the transient climate response are better constrained by observed warming and are more relevant for predicting warming over the next decades. Newer metrics relating global warming directly to the total emitted CO2 show that in order to keep warming to within 2 °C, future CO2 emissions have to remain strongly limited, irrespective of climate sensitivity being at the high or low end.

Quantitative assessment of Vulnerability of Forest ecosystem to Climate Change in Korea

NASA Astrophysics Data System (ADS)

Byun, J.; Lee, W.; Choi, S.; Oh, S.; Climate Change Model Team

2011-12-01

The purpose of this study was to assess the vulnerability of forest ecosystem to climate change in Korea using outputs of vegetation models(HyTAG and MC1) and socio-ecological indicators. Also it suggested adaptation strategies in forest management through analysis of three vulnerability components: exposure, sensitivity and adaptive capacity. For the model simulation of past years(1971-2000), the climatic data was prepared by the Korea Meteorological Administration(KMA). In addition, for the future simulation, the Fifth-Generation NCAR/Penn State Mesoscale Model(MM5) coupling with atmosphere-ocean circulation model(ECHO-G) provide the future climatic data under the A1B scenarios. HyTAG (Hydrological and Thermal Analogy Groups), korean model of forest distribution on a regional-scale, could show extent of sensitivity and adaptive capacity in connection with changing frequency and changing direction of vegetation. MC1 model could provide variation and direction of NPP(Net Primary Production) and SCS(Soil Carbon Storage). In addition, the sensitivity and adaptation capacity were evaluated for each. Besides indicators from models, many other indicators such as financial affairs and number of officers were included in the vulnerability components. As a result of the vulnerability assessment, south western part and Je-ju island of Korea had relatively high vulnerability. This finding is considered to come from a distinctively adaptative capacity. Using these results, we could propose actions against climate change and develop decision making systems on forest management.

Scenarios Based on Shared Socioeconomic Pathway Assumptions

NASA Astrophysics Data System (ADS)

Edmonds, J.

2013-12-01

A set of new scenarios is being developed by the international scientific community as part of a larger program that was articulated in Moss, et al. (2009), published in Nature. A long series of meetings including climate researchers drawn from the climate modeling, impacts, adaptation and vulnerability (IAV) and integrated assessment modeling (IAM) communities have led to the development of a set of five Shared Socioeconomic Pathways (SSPs), which define the state of human and natural societies at a macro scale over the course of the 21st century without regard to climate mitigation or change. SSPs were designed to explore a range of possible futures consistent with greater or lesser challenges to mitigation and challenges to adaptation. They include a narrative storyline and a set of quantified measures--e.g. demographic and economic profiles--that define the high-level state of society as it evolves over the 21st century under the assumption of no significant climate feedback. SSPs can be used to develop quantitative scenarios of human Earth systems using IAMs. IAMs produce information about greenhouse gas emissions, energy systems, the economy, agriculture and land use. Each set of SSPs will have a different human Earth system realization for each IAM. Five groups from the IAM community have begun to explore the implications of SSP assumptions for emissions, energy, economy, agriculture and land use. We report the quantitative results of initial experiments from those groups. A major goal of the Moss, et al. strategy was to enable the use of CMIP5 climate model ensemble products for IAV research. CMIP5 climate scenarios used four Representative Concentration Pathway (RCP) scenarios, defined in terms of radiative forcing in the year 2100: 2.6, 4.5, 6.0, and 8.5 Wm-2. There is no reason to believe that the SSPs will generate year 2100 levels of radiative forcing that correspond to the four RCP levels, though it is important that at least one SSP produce a scenario with at least 8.5 Wm-2. To address this problem each SSP scenario can be treated as a reference scenario, to which emissions mitigation policies can be applied to create a set of RCP replications. These RCP replications have the underlying SSP socio-economic assumptions in addition to policy assumptions and radiative forcing levels consistent with the CMIP5 products. We report quantitative results of initial experiments from the five participating groups.

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

Modeling the Explicit Chemistry of Anthropogenic and Biogenic Organic Aerosols

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

Madronich, Sasha

2015-12-09

The atmospheric burden of Secondary Organic Aerosols (SOA) remains one of the most important yet uncertain aspects of the radiative forcing of climate. This grant focused on improving our quantitative understanding of SOA formation and evolution, by developing, applying, and improving a highly detailed model of atmospheric organic chemistry, the Generation of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) model. Eleven (11) publications have resulted from this grant.

Limits to global and Australian temperature change this century based on expert judgment of climate sensitivity

NASA Astrophysics Data System (ADS)

Grose, Michael R.; Colman, Robert; Bhend, Jonas; Moise, Aurel F.

2017-05-01

The projected warming of surface air temperature at the global and regional scale by the end of the century is directly related to emissions and Earth's climate sensitivity. Projections are typically produced using an ensemble of climate models such as CMIP5, however the range of climate sensitivity in models doesn't cover the entire range considered plausible by expert judgment. Of particular interest from a risk-management perspective is the lower impact outcome associated with low climate sensitivity and the low-probability, high-impact outcomes associated with the top of the range. Here we scale climate model output to the limits of expert judgment of climate sensitivity to explore these limits. This scaling indicates an expanded range of projected change for each emissions pathway, including a much higher upper bound for both the globe and Australia. We find the possibility of exceeding a warming of 2 °C since pre-industrial is projected under high emissions for every model even scaled to the lowest estimate of sensitivity, and is possible under low emissions under most estimates of sensitivity. Although these are not quantitative projections, the results may be useful to inform thinking about the limits to change until the sensitivity can be more reliably constrained, or this expanded range of possibilities can be explored in a more formal way. When viewing climate projections, accounting for these low-probability but high-impact outcomes in a risk management approach can complement the focus on the likely range of projections. They can also highlight the scale of the potential reduction in range of projections, should tight constraints on climate sensitivity be established by future research.

Mixed-method study of a conceptual model of evidence-based intervention sustainment across multiple public-sector service settings.

PubMed

Aarons, Gregory A; Green, Amy E; Willging, Cathleen E; Ehrhart, Mark G; Roesch, Scott C; Hecht, Debra B; Chaffin, Mark J

2014-12-10

This study examines sustainment of an EBI implemented in 11 United States service systems across two states, and delivered in 87 counties. The aims are to 1) determine the impact of state and county policies and contracting on EBI provision and sustainment; 2) investigate the role of public, private, and academic relationships and collaboration in long-term EBI sustainment; 3) assess organizational and provider factors that affect EBI reach/penetration, fidelity, and organizational sustainment climate; and 4) integrate findings through a collaborative process involving the investigative team, consultants, and system and community-based organization (CBO) stakeholders in order to further develop and refine a conceptual model of sustainment to guide future research and provide a resource for service systems to prepare for sustainment as the ultimate goal of the implementation process. A mixed-method prospective and retrospective design will be used. Semi-structured individual and group interviews will be used to collect information regarding influences on EBI sustainment including policies, attitudes, and practices; organizational factors and external policies affecting model implementation; involvement of or collaboration with other stakeholders; and outer- and inner-contextual supports that facilitate ongoing EBI sustainment. Document review (e.g., legislation, executive orders, regulations, monitoring data, annual reports, agendas and meeting minutes) will be used to examine the roles of state, county, and local policies in EBI sustainment. Quantitative measures will be collected via administrative data and web surveys to assess EBI reach/penetration, staff turnover, EBI model fidelity, organizational culture and climate, work attitudes, implementation leadership, sustainment climate, attitudes toward EBIs, program sustainment, and level of institutionalization. Hierarchical linear modeling will be used for quantitative analyses. Qualitative analyses will be tailored to each of the qualitative methods (e.g., document review, interviews). Qualitative and quantitative approaches will be integrated through an inclusive process that values stakeholder perspectives. The study of sustainment is critical to capitalizing on and benefiting from the time and fiscal investments in EBI implementation. Sustainment is also critical to realizing broad public health impact of EBI implementation. The present study takes a comprehensive mixed-method approach to understanding sustainment and refining a conceptual model of sustainment.

Chemical weathering as a mechanism for the climatic control of bedrock river incision

NASA Astrophysics Data System (ADS)

Murphy, Brendan P.; Johnson, Joel P. L.; Gasparini, Nicole M.; Sklar, Leonard S.

2016-04-01

Feedbacks between climate, erosion and tectonics influence the rates of chemical weathering reactions, which can consume atmospheric CO2 and modulate global climate. However, quantitative predictions for the coupling of these feedbacks are limited because the specific mechanisms by which climate controls erosion are poorly understood. Here we show that climate-dependent chemical weathering controls the erodibility of bedrock-floored rivers across a rainfall gradient on the Big Island of Hawai‘i. Field data demonstrate that the physical strength of bedrock in streambeds varies with the degree of chemical weathering, which increases systematically with local rainfall rate. We find that incorporating the quantified relationships between local rainfall and erodibility into a commonly used river incision model is necessary to predict the rates and patterns of downcutting of these rivers. In contrast to using only precipitation-dependent river discharge to explain the climatic control of bedrock river incision, the mechanism of chemical weathering can explain strong coupling between local climate and river incision.

Coupling Processes between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, M. K. W.; Weisenstein, Debra; Shia, Run-Lie; Sze, N. D.

1998-01-01

This is the third semi-annual report for NAS5-97039, covering January through June 1998. The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling for this work are the AER 2-dimensional chemistry-transport model, the AER 2-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry. We will continue developing our three-wave model so that we can help NASA determine the strengths and weaknesses of the next generation assessment models.

Backscatter modelling and inversion from Cassini/SAR data: Implications for Titan's sand seas properties and climatic conditions

NASA Astrophysics Data System (ADS)

Lucas, A.; Rodriguez, S.; Lemonnier, F.; Paillou, P.; Le Gall, A. A.; Narteau, C.

2015-12-01

Sand seas on Titan may reflect the present and past climatic conditions. Understanding the morphodynamics and physicochemical properties of Titan's dunes is therefore essential for a better comprehension of the climatic and geological history of the largest Saturn's moon. We derived quantitatively surface properties (texture, composition) from the modelling of microwave backscattered signal and Monte Carlo inversion of despeckled Cassini/SAR data over the equatorial sand seas. We show that dunes and inter-dunes have significantly different physical properties. Absorption is more efficient in the dunes compared to the inter-dunes. The inter-dunes are smoother with an higher dielectric constant than the dunes. Considering the composition, the inter-dunes are in between the dunes and the bright inselbergs, suggesting the presence of a shallow layer of sediment in between the dunes. Additionally potential secondary bedforms may have been detected. Implications for dune morphodynamics, sediment inventory and climatic conditions occurring on Titan will be discussed.

Examining bias in pollen-based quantitative climate reconstructions induced by human impact on vegetation in China

NASA Astrophysics Data System (ADS)

Ding, Wei; Xu, Qinghai; Tarasov, Pavel E.

2017-09-01

Human impact is a well-known confounder in pollen-based quantitative climate reconstructions as most terrestrial ecosystems have been artificially affected to varying degrees. In this paper, we use a human-induced pollen dataset (H-set) and a corresponding natural pollen dataset (N-set) to establish pollen-climate calibration sets for temperate eastern China (TEC). The two calibration sets, taking a weighted averaging partial least squares (WA-PLS) approach, are used to reconstruct past climate variables from a fossil record, which is located at the margin of the East Asian summer monsoon in north-central China and covers the late glacial Holocene from 14.7 ka BP (thousands of years before AD 1950). Ordination results suggest that mean annual precipitation (Pann) is the main explanatory variable of both pollen composition and percentage distributions in both datasets. The Pann reconstructions, based on the two calibration sets, demonstrate consistently similar patterns and general trends, suggesting a relatively strong climate impact on the regional vegetation and pollen spectra. However, our results also indicate that the human impact may obscure climate signals derived from fossil pollen assemblages. In a test with modern climate and pollen data, the Pann influence on pollen distribution decreases in the H-set, while the human influence index (HII) rises. Moreover, the relatively strong human impact reduces woody pollen taxa abundances, particularly in the subhumid forested areas. Consequently, this shifts their model-inferred Pann optima to the arid end of the gradient compared to Pann tolerances in the natural dataset and further produces distinct deviations when the total tree pollen percentages are high (i.e. about 40 % for the Gonghai area) in the fossil sequence. In summary, the calibration set with human impact used in our experiment can produce a reliable general pattern of past climate, but the human impact on vegetation affects the pollen-climate relationship and biases the pollen-based climate reconstruction. The extent of human-induced bias may be rather small for the entire late glacial and early Holocene interval when we use a reference set called natural. Nevertheless, this potential bias should be kept in mind when conducting quantitative reconstructions, especially for the recent 2 or 3 millennia.

The Heat is On! Confronting Climate Change in the Classroom

NASA Astrophysics Data System (ADS)

Bowman, R.; Atwood-Blaine, D.

2008-12-01

This paper discusses a professional development workshop for K-12 science teachers entitled "The Heat is On! Confronting Climate Change in the Classroom." This workshop was conducted by the Center for Remote Sensing of Ice Sheets (CReSIS), which has the primary goal to understand and predict the role of polar ice sheets in sea level change. The specific objectives of this summer workshop were two-fold; first, to address the need for advancement in science technology engineering and mathematics (STEM) education and second, to address the need for science teacher training in climate change science. Twenty-eight Kansas teachers completed four pre-workshop assignments online in Moodle and attended a one-week workshop. The workshop included lecture presentations by scientists (both face-to-face and via video-conference) and collaboration between teachers and scientists to create online inquiry-based lessons on the water budget, remote sensing, climate data, and glacial modeling. Follow-up opportunities are communicated via the CReSIS Teachers listserv to maintain and further develop the collegial connections and collaborations established during the workshop. Both qualitative and quantitative evaluation results indicate that this workshop was particularly effective in the following four areas: 1) creating meaningful connections between K-12 teachers and CReSIS scientists; 2) integrating distance-learning technologies to facilitate the social construction of knowledge; 3) increasing teachers' content understanding of climate change and its impacts on the cryosphere and global sea level; and 4) increasing teachers' self-efficacy beliefs about teaching climate science. Evaluation methods included formative content understanding assessments (via "clickers") during each scientist's presentation, a qualitative evaluation survey administered at the end of the workshop, and two quantitative evaluation instruments administered pre- and post- workshop. The first of these quantitative instruments measured teachers' efficacy beliefs about teaching climate science and the outcome expectancy they hold for student achievement. The second, a content test, measured the teachers' content knowledge of climate science and the cryosphere. Our results indicate that the teachers participating in the workshops showed significant increase in personal climate science teaching efficacy, outcome expectancy, and content knowledge of climate science, all at the p < 0.01 level. Interestingly, these results appear to be independent of each other. While one may think that changes in efficacy beliefs are caused by gains in content knowledge, our results show low correlation between these two factors.

First Evaluation of the CCAM Aerosol Simulation over Africa: Implications for Regional Climate Modeling

NASA Astrophysics Data System (ADS)

Horowitz, H.; Garland, R. M.; Thatcher, M. J.; Naidoo, M.; van der Merwe, J.; Landman, W.; Engelbrecht, F.

2015-12-01

An accurate representation of African aerosols in climate models is needed to understand the regional and global radiative forcing and climate impacts of aerosols, at present and under future climate change. However, aerosol simulations in regional climate models for Africa have not been well-tested. Africa contains the largest single source of biomass-burning smoke aerosols and dust globally. Although aerosols are short-lived relative to greenhouse gases, black carbon in particular is estimated to be second only to carbon dioxide in contributing to warming on a global scale. Moreover, Saharan dust is exported great distances over the Atlantic Ocean, affecting nutrient transport to regions like the Amazon rainforest, which can further impact climate. Biomass burning aerosols are also exported from Africa, westward from Angola over the Atlantic Ocean and off the southeastern coast of South Africa to the Indian Ocean. Here, we perform the first extensive quantitative evaluation of the Conformal-Cubic Atmospheric Model (CCAM) aerosol simulation against monitored data, focusing on aerosol optical depth (AOD) observations over Africa. We analyze historical regional simulations for 1999 - 2012 from CCAM consistent with the experimental design of CORDEX at 50 km global horizontal resolution, through the dynamical downscaling of ERA-Interim data reanalysis data, with the CMIP5 emissions inventory (RCP8.5 scenario). CCAM has a prognostic aerosol scheme for organic carbon, black carbon, sulfate, and dust, and non-prognostic sea salt. The CCAM AOD at 550nm was compared to AOD (observed at 440nm, adjusted to 550nm with the Ångström exponent) from long-term AERONET stations across Africa. Sites strongly impacted by dust and biomass burning and with long continuous records were prioritized. In general, the model captures the monthly trends of the AERONET data. This presentation provides a basis for understanding how well aerosol particles are represented over Africa in regional climate modeling and the potential impact on climate predictions, and is the first large scale climate model-measurement verification of aerosols over Africa that we are aware of. CCAM is widely used for regional climate modeling applications, and we also discuss further improvements to the aerosol parameterizations based on our results.

Integrating research tools to support the management of social-ecological systems under climate change

USGS Publications Warehouse

Miller, Brian W.; Morisette, Jeffrey T.

2014-01-01

Developing resource management strategies in the face of climate change is complicated by the considerable uncertainty associated with projections of climate and its impacts and by the complex interactions between social and ecological variables. The broad, interconnected nature of this challenge has resulted in calls for analytical frameworks that integrate research tools and can support natural resource management decision making in the face of uncertainty and complex interactions. We respond to this call by first reviewing three methods that have proven useful for climate change research, but whose application and development have been largely isolated: species distribution modeling, scenario planning, and simulation modeling. Species distribution models provide data-driven estimates of the future distributions of species of interest, but they face several limitations and their output alone is not sufficient to guide complex decisions for how best to manage resources given social and economic considerations along with dynamic and uncertain future conditions. Researchers and managers are increasingly exploring potential futures of social-ecological systems through scenario planning, but this process often lacks quantitative response modeling and validation procedures. Simulation models are well placed to provide added rigor to scenario planning because of their ability to reproduce complex system dynamics, but the scenarios and management options explored in simulations are often not developed by stakeholders, and there is not a clear consensus on how to include climate model outputs. We see these strengths and weaknesses as complementarities and offer an analytical framework for integrating these three tools. We then describe the ways in which this framework can help shift climate change research from useful to usable.

Bayesian Processor of Output for Probabilistic Quantitative Precipitation Forecasting

NASA Astrophysics Data System (ADS)

Krzysztofowicz, R.; Maranzano, C. J.

2006-05-01

The Bayesian Processor of Output (BPO) is a new, theoretically-based technique for probabilistic forecasting of weather variates. It processes output from a numerical weather prediction (NWP) model and optimally fuses it with climatic data in order to quantify uncertainty about a predictand. The BPO is being tested by producing Probabilistic Quantitative Precipitation Forecasts (PQPFs) for a set of climatically diverse stations in the contiguous U.S. For each station, the PQPFs are produced for the same 6-h, 12-h, and 24-h periods up to 84- h ahead for which operational forecasts are produced by the AVN-MOS (Model Output Statistics technique applied to output fields from the Global Spectral Model run under the code name AVN). The inputs into the BPO are estimated as follows. The prior distribution is estimated from a (relatively long) climatic sample of the predictand; this sample is retrieved from the archives of the National Climatic Data Center. The family of the likelihood functions is estimated from a (relatively short) joint sample of the predictor vector and the predictand; this sample is retrieved from the same archive that the Meteorological Development Laboratory of the National Weather Service utilized to develop the AVN-MOS system. This talk gives a tutorial introduction to the principles and procedures behind the BPO, and highlights some results from the testing: a numerical example of the estimation of the BPO, and a comparative verification of the BPO forecasts and the MOS forecasts. It concludes with a list of demonstrated attributes of the BPO (vis- à-vis the MOS): more parsimonious definitions of predictors, more efficient extraction of predictive information, better representation of the distribution function of predictand, and equal or better performance (in terms of calibration and informativeness).

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

Climate Risk Modelling of Balsam Woolly Adelgid Damage Severity in Subalpine Fir Stands of Western North America.

PubMed

Hrinkevich, Kathryn H; Progar, Robert A; Shaw, David C

2016-01-01

The balsam woolly adelgid (Adelges piceae (Ratzeburg) (Homoptera: Adelgidae)) (BWA) is a nonnative, invasive insect that threatens Abies species throughout North America. It is well established in the Pacific Northwest, but continues to move eastward through Idaho and into Montana and potentially threatens subalpine fir to the south in the central and southern Rocky Mountains. We developed a climatic risk model and map that predicts BWA impacts to subalpine fir using a two-step process. Using 30-year monthly climate normals from sites with quantitatively derived BWA damage severity index values, we built a regression model that significantly explained insect damage. The sites were grouped into two distinct damage categories (high damage and mortality versus little or no mortality and low damage) and the model estimates for each group were used to designate distinct value ranges for four climatic risk categories: minimal, low, moderate, and high. We then calculated model estimates for each cell of a 4-kilometer resolution climate raster and mapped the risk categories over the entire range of subalpine fir in the western United States. The spatial variation of risk classes indicates a gradient of climatic susceptibility generally decreasing from the Olympic Peninsula in Washington and the Cascade Range in Oregon and Washington moving eastward, with the exception of some high risk areas in northern Idaho and western Montana. There is also a pattern of decreasing climatic susceptibility from north to south in the Rocky Mountains. Our study provides an initial step for modeling the relationship between climate and BWA damage severity across the range of subalpine fir. We showed that September minimum temperature and a metric calculated as the maximum May temperature divided by total May precipitation were the best climatic predictors of BWA severity. Although winter cold temperatures and summer heat have been shown to influence BWA impacts in other locations, these variables were not as predictive as spring and fall conditions in the Pacific Northwest.

Quantitative and qualitative assessment of the impact of climate change on a combined sewer overflow and its receiving water body.

PubMed

Bi, Eustache Gooré; Monette, Frédéric; Gachon, Philippe; Gaspéri, Johnny; Perrodin, Yves

2015-08-01

Projections from the Canadian Regional Climate Model (CRCM) for the southern part of the province of Québec, Canada, suggest an increase in extreme precipitation events for the 2050 horizon (2041-2070). The main goal of this study consisted in a quantitative and qualitative assessment of the impact of the 20 % increase in rainfall intensity that led, in the summer of 2013, to overflows in the "Rolland-Therrien" combined sewer system in the city of Longueuil, Canada. The PCSWMM 2013 model was used to assess the sensitivity of this overflow under current (2013) and future (2050) climate conditions. The simulated quantitative variables (peak flow, Q(CSO), and volume discharged, VD) served as the basis for deriving ecotoxicological risk indices and event fluxes (EFs) transported to the St. Lawrence (SL) River. Results highlighted 15 to 500% increases in VD and 13 to 148% increases in Q(CSO) by 2050 (compared to 2013), based on eight rainfall events measured from May to October. These results show that (i) the relationships between precipitation and combined sewer overflow variables are not linear and (ii) the design criteria for current hydraulic infrastructure must be revised to account for the impact of climate change (CC) arising from changes in precipitation regimes. EFs discharged into the SL River will be 2.24 times larger in the future than they are now (2013) due to large VDs resulting from CC. This will, in turn, lead to excessive inputs of total suspended solids (TSSs) and tracers for numerous urban pollutants (organic matter and nutrients, metals) into the receiving water body. Ecotoxicological risk indices will increase by more than 100% by 2050 compared to 2013. Given that substantial VDs are at play, and although CC scenarios have many sources of uncertainty, strategies to adapt this drainage network to the effects of CC will have to be developed.

Spatial and Climate Literacy: Connecting Urban and Rural Students

NASA Astrophysics Data System (ADS)

Boger, R. A.; Low, R.; Mandryk, C.; Gorokhovich, Y.

2013-12-01

Through a collaboration between the University of Nebraska-Lincoln (UNL), Brooklyn College, and Lehman College, four independent but linked modules were developed and piloted in courses offered at Brooklyn College and UNL simultaneously. Module content includes climate change science and literacy principles, using geospatial technologies (GIS, GPS and remote sensing) as a vehicle to explore issues associated with global, regional, and local climate change in a concrete, quantitative and visual way using Internet resources available through NASA, NOAA, USGS, and a variety of universities and organizations. The materials take an Earth system approach and incorporate sustainability, resilience, water and watersheds, weather and climate, and food security topics throughout the semester. The research component of the project focuses on understanding the role of spatial literacy and authentic inquiry based experiences in climate change understanding and improving confidence in teaching science. In particular, engaging learners in both climate change science and GIS simultaneously provides opportunities to examine questions about the role that data manipulation, mental representation, and spatial literacy plays in students' abilities to understand the consequences and impacts of climate change. Pre and post surveys were designed to discern relationships between spatial cognitive processes and effective acquisition of climate change science concepts in virtual learning environments as well as alignment of teacher's mental models of nature of science and climate system dynamics to scientific models. The courses will again be offered simultaneously in Spring 2014 at Brooklyn College and UNL. Evaluation research will continue to examine the connections between spatial and climate literacy and teacher's mental models (via qualitative textual analysis using MAXQDA text analysis, and UCINET social network analysis programs) as well as how urban-rural learning interactions may influence climate literacy.

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.

The Potential Impacts of a Scenario of C02-Induced Climatic Change on Ontafio, Canada.

NASA Astrophysics Data System (ADS)

Cohen, S. J.; Allsopp, T. R.

1988-07-01

In 1984, Environment Canada, Ontario Region, with financial and expert support from the Canadian Climate Program, initiated an interdisciplinary pilot study to investigate the potential impact, on Ontario, of a climate scenario which might be anticipated under doubling of atmospheric C02 conditions.There were many uncertainties involved in the climate scenario development and the impacts modeling. Time and resource constraints restricted this study to one climate scenario and to the selection of several available models that could be adapted to these impact studies. The pilot study emphasized the approach and process required to investigate potential regional impacts in an interdisciplinary manner, rather than to produce a forecast of the future.The climate scenario chosen was adapted from experimental model results produced by the Goddard Institute for Space Studies (GISS), coupled with current climate normals. Gridded monthly mean temperatures and precipitation were then used to develop projected biophysical effects. For example, existing physical and/or statistical models were adapted to determine impacts on the Great Lakes net basin supplies, levels and outflows, streamflow subbasin, snowfall and length of snow season.The second phase of the study addressed the impacts of the climate system scenario on natural resources and resource dependent activities. For example, the impacts of projected decreased lake levels and outflows on commercial navigation and hydroelectric generation were assessed. The impacts of the climate scenario on municipal water use, residential beating and cooling energy requirements opportunities and constraints for food production and tourism and recreation were determined quantitatively where models and methodologies were available, otherwise, qualitatively.First order interdependencies of the biophysical effects of the climate scenario and resource dependent activities were evaluated qualitatively in a workshop format culminating in a series of statements on (i) possible preventive, compensatory and substitution strategies and (ii) an assessment of current knowledge gaps and deficiencies, with recommendations for future areas of research.

The CLUVA project: Climate-change scenarios and their impact on urban areas in Africa

NASA Astrophysics Data System (ADS)

Di Ruocco, Angela; Weets, Guy; Gasparini, Paolo; Jørgensen, Gertrud; Lindley, Sarah; Pauleit, Stephan; Vahed, Anwar; Schiano, Pasquale; Kabisch, Sigrun; Vedeld, Trond; Coly, Adrien; Tonye, Emmanuel; Touré, Hamidou; Kombe, Wilbard; Yeshitela, Kumelachew

2013-04-01

CLUVA (CLimate change and Urban Vulnerability in Africa; http://www.cluva.eu/) is a 3 years project, funded by the European Commission in 2010. Its main objective is the estimate of the impacts of climate changes in the next 40 years at urban scale in Africa. The mission of CLUVA is to develop methods and knowledge to assess risks cascading from climate-changes. It downscales IPCC climate projections to evaluate threats to selected African test cities; mainly floods, sea-level rise, droughts, heat waves and desertification. The project evaluates and links: social vulnerability; vulnerability of in-town ecosystems and urban-rural interfaces; vulnerability of urban built environment and lifelines; and related institutional and governance dimensions of adaptation. A multi-scale and multi-disciplinary quantitative, probabilistic, modelling is applied. CLUVA brings together climate experts, risk management experts, urban planners and social scientists with their African counterparts in an integrated research effort focusing on the improvement of the capacity of scientific institutions, local councils and civil society to cope with climate change. The CLUVA approach was set-up in the first year of the project and developed as follows: an ensemble of eight global projections of climate changes is produced for east and west Africa until 2050 considering the new IPCC (International Panel on Climate Changes; http://www.ipcc.ch/) scenarios. These are then downscaled to urban level, where territorial modeling is required to compute hazard effects on the vulnerable physical system (urban ecosystems, informal settlements, lifelines such as transportation and sewer networks) as well as on the social context, in defined time frames, and risk analysis is then employed to assess expected consequences. An investigation of the existing urban planning and governance systems and its interface with climate risks is performed. With the aid of the African partners, the developed approach is currently being applied to selected African case studies: Addis Ababa - Ethiopia; Dar es Salaam - Tanzania, Douala - Cameroun; Ouagadougou - Burkina Faso, St. Louis - Senegal. The poster will illustrate the CLUVA's framework to assess climate-change-related risks at an urban scale in Africa, and will report on the progresses of selected case studies to demonstrate feasibility of a multi-scale and multi-risk quantitative approach for risk management.

Climate change and landscape development in post-closure safety assessment of solid radioactive waste disposal: Results of an initiative of the IAEA.

PubMed

Lindborg, T; Thorne, M; Andersson, E; Becker, J; Brandefelt, J; Cabianca, T; Gunia, M; Ikonen, A T K; Johansson, E; Kangasniemi, V; Kautsky, U; Kirchner, G; Klos, R; Kowe, R; Kontula, A; Kupiainen, P; Lahdenperä, A-M; Lord, N S; Lunt, D J; Näslund, J-O; Nordén, M; Norris, S; Pérez-Sánchez, D; Proverbio, A; Riekki, K; Rübel, A; Sweeck, L; Walke, R; Xu, S; Smith, G; Pröhl, G

2018-03-01

The International Atomic Energy Agency has coordinated an international project addressing climate change and landscape development in post-closure safety assessments of solid radioactive waste disposal. The work has been supported by results of parallel on-going research that has been published in a variety of reports and peer reviewed journal articles. The project is due to be described in detail in a forthcoming IAEA report. Noting the multi-disciplinary nature of post-closure safety assessments, here, an overview of the work is given to provide researchers in the broader fields of radioecology and radiological safety assessment with a review of the work that has been undertaken. It is hoped that such dissemination will support and promote integrated understanding and coherent treatment of climate change and landscape development within an overall assessment process. The key activities undertaken in the project were: identification of the key processes that drive environmental change (mainly those associated with climate and climate change), and description of how a relevant future may develop on a global scale; development of a methodology for characterising environmental change that is valid on a global scale, showing how modelled global changes in climate can be downscaled to provide information that may be needed for characterising environmental change in site-specific assessments, and illustrating different aspects of the methodology in a number of case studies that show the evolution of site characteristics and the implications for the dose assessment models. Overall, the study has shown that quantitative climate and landscape modelling has now developed to the stage that it can be used to define an envelope of climate and landscape change scenarios at specific sites and under specific greenhouse-gas emissions assumptions that is suitable for use in quantitative post-closure performance assessments. These scenarios are not predictions of the future, but are projections based on a well-established understanding of the important processes involved and their impacts on different types of landscape. Such projections support the understanding of, and selection of, plausible ranges of scenarios for use in post-closure safety assessments. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index

NASA Astrophysics Data System (ADS)

Köseoğlu, Denizcan; Belt, Simon T.; Smik, Lukas; Yao, Haoyi; Panieri, Giuliana; Knies, Jochen

2018-02-01

The discovery of IP25 as a qualitative biomarker proxy for Arctic sea ice and subsequent introduction of the so-called PIP25 index for semi-quantitative descriptions of sea ice conditions has significantly advanced our understanding of long-term paleo Arctic sea ice conditions over the past decade. We investigated the potential for classification tree (CT) models to provide a further approach to paleo Arctic sea ice reconstruction through analysis of a suite of highly branched isoprenoid (HBI) biomarkers in ca. 200 surface sediments from the Barents Sea. Four CT models constructed using different HBI assemblages revealed IP25 and an HBI triene as the most appropriate classifiers of sea ice conditions, achieving a >90% cross-validated classification rate. Additionally, lower model performance for locations in the Marginal Ice Zone (MIZ) highlighted difficulties in characterisation of this climatically-sensitive region. CT model classification and semi-quantitative PIP25-derived estimates of spring sea ice concentration (SpSIC) for four downcore records from the region were consistent, although agreement between proxy and satellite/observational records was weaker for a core from the west Svalbard margin, likely due to the highly variable sea ice conditions. The automatic selection of appropriate biomarkers for description of sea ice conditions, quantitative model assessment, and insensitivity to the c-factor used in the calculation of the PIP25 index are key attributes of the CT approach, and we provide an initial comparative assessment between these potentially complementary methods. The CT model should be capable of generating longer-term temporal shifts in sea ice conditions for the climatically sensitive Barents Sea.

Nonlinear Dynamical Modes as a Basis for Short-Term Forecast of Climate Variability

NASA Astrophysics Data System (ADS)

Feigin, A. M.; Mukhin, D.; Gavrilov, A.; Seleznev, A.; Loskutov, E.

2017-12-01

We study abilities of data-driven stochastic models constructed by nonlinear dynamical decomposition of spatially distributed data to quantitative (short-term) forecast of climate characteristics. We compare two data processing techniques: (i) widely used empirical orthogonal function approach, and (ii) nonlinear dynamical modes (NDMs) framework [1,2]. We also make comparison of two kinds of the prognostic models: (i) traditional autoregression (linear) model and (ii) model in the form of random ("stochastic") nonlinear dynamical system [3]. We apply all combinations of the above-mentioned data mining techniques and kinds of models to short-term forecasts of climate indices based on sea surface temperature (SST) data. We use NOAA_ERSST_V4 dataset (monthly SST with space resolution 20 × 20) covering the tropical belt and starting from the year 1960. We demonstrate that NDM-based nonlinear model shows better prediction skill versus EOF-based linear and nonlinear models. Finally we discuss capability of NDM-based nonlinear model for long-term (decadal) prediction of climate variability. [1] D. Mukhin, A. Gavrilov, E. Loskutov , A.Feigin, J.Kurths, 2015: Principal nonlinear dynamical modes of climate variability, Scientific Reports, rep. 5, 15510; doi: 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. [3] Ya. Molkov, D. Mukhin, E. Loskutov, A. Feigin, 2012: Random dynamical models from time series. Phys. Rev. E, Vol. 85, n.3.

Estimating the numerical diapycnal mixing in an eddy-permitting ocean model

NASA Astrophysics Data System (ADS)

Megann, Alex

2018-01-01

Constant-depth (or "z-coordinate") ocean models such as MOM4 and NEMO have become the de facto workhorse in climate applications, having attained a mature stage in their development and are well understood. A generic shortcoming of this model type, however, is a tendency for the advection scheme to produce unphysical numerical diapycnal mixing, which in some cases may exceed the explicitly parameterised mixing based on observed physical processes, and this is likely to have effects on the long-timescale evolution of the simulated climate system. Despite this, few quantitative estimates have been made of the typical magnitude of the effective diapycnal diffusivity due to numerical mixing in these models. GO5.0 is a recent ocean model configuration developed jointly by the UK Met Office and the National Oceanography Centre. It forms the ocean component of the GC2 climate model, and is closely related to the ocean component of the UKESM1 Earth System Model, the UK's contribution to the CMIP6 model intercomparison. GO5.0 uses version 3.4 of the NEMO model, on the ORCA025 global tripolar grid. An approach to quantifying the numerical diapycnal mixing in this model, based on the isopycnal watermass analysis of Lee et al. (2002), is described, and the estimates thereby obtained of the effective diapycnal diffusivity in GO5.0 are compared with the values of the explicit diffusivity used by the model. It is shown that the effective mixing in this model configuration is up to an order of magnitude higher than the explicit mixing in much of the ocean interior, implying that mixing in the model below the mixed layer is largely dominated by numerical mixing. This is likely to have adverse consequences for the representation of heat uptake in climate models intended for decadal climate projections, and in particular is highly relevant to the interpretation of the CMIP6 class of climate models, many of which use constant-depth ocean models at ¼° resolution

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.

Special Interests and the Media: Theory and an Application to Climate Change.

PubMed

Shapiro, Jesse M

2016-12-01

A journalist reports to a voter on an unknown, policy-relevant state. Competing special interests can make claims that contradict the facts but seem credible to the voter. A reputational incentive to avoid taking sides leads the journalist to report special interests' claims to the voter. In equilibrium, the voter can remain uninformed even when the journalist is perfectly informed. Communication is improved if the journalist discloses her partisan leanings. The model provides an account of persistent public ignorance on climate change that is consistent with narrative and quantitative evidence.

A review of multi-risk methodologies for natural hazards: Consequences and challenges for a climate change impact assessment.

PubMed

Gallina, Valentina; Torresan, Silvia; Critto, Andrea; Sperotto, Anna; Glade, Thomas; Marcomini, Antonio

2016-03-01

This paper presents a review of existing multi-risk assessment concepts and tools applied by organisations and projects providing the basis for the development of a multi-risk methodology in a climate change perspective. Relevant initiatives were developed for the assessment of multiple natural hazards (e.g. floods, storm surges, droughts) affecting the same area in a defined timeframe (e.g. year, season, decade). Major research efforts were focused on the identification and aggregation of multiple hazard types (e.g. independent, correlated, cascading hazards) by means of quantitative and semi-quantitative approaches. Moreover, several methodologies aim to assess the vulnerability of multiple targets to specific natural hazards by means of vulnerability functions and indicators at the regional and local scale. The overall results of the review show that multi-risk approaches do not consider the effects of climate change and mostly rely on the analysis of static vulnerability (i.e. no time-dependent vulnerabilities, no changes among exposed elements). A relevant challenge is therefore to develop comprehensive formal approaches for the assessment of different climate-induced hazards and risks, including dynamic exposure and vulnerability. This requires the selection and aggregation of suitable hazard and vulnerability metrics to make a synthesis of information about multiple climate impacts, the spatial analysis and ranking of risks, including their visualization and communication to end-users. To face these issues, climate impact assessors should develop cross-sectorial collaborations among different expertise (e.g. modellers, natural scientists, economists) integrating information on climate change scenarios with sectorial climate impact assessment, towards the development of a comprehensive multi-risk assessment process. Copyright © 2015 Elsevier Ltd. All rights reserved.

Chronic disease and climate change: understanding co-benefits and their policy implications.

PubMed

Capon, Anthony G; Rissel, Chris E

2010-01-01

Chronic disease and climate change are major public policy challenges facing governments around the world. An improved understanding of the relationship between chronic disease and climate change should enable improved policy formulation to support both human health and the health of the planet. Chronic disease and climate change are both unintended consequences of our way of life, and are attributable in part to the ready availability of inexpensive fossil fuel energy. There are co-benefits for health from actions to address climate change. For example, substituting physical activity and a vegetable-rich diet for motor vehicle transport and a meat-rich diet is both good for health and good for the planet. We should encourage ways of living that use less carbon as these can be healthy ways of living, for both individuals and society. Quantitative modelling of co-benefits should inform policy responses.

Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan

PubMed Central

Hsiao, Hsin-I; Jan, Man-Ser; Chi, Hui-Ju

2016-01-01

This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+), ocean temperature (+), ocean salinity of 6 months ago (+), maximum daily rainfall (current (−) and one month ago (−)), and average relative humidity (current and 9 months ago (−)) had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future. PMID:26848675

Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan.

PubMed

Hsiao, Hsin-I; Jan, Man-Ser; Chi, Hui-Ju

2016-02-03

This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+), ocean temperature (+), ocean salinity of 6 months ago (+), maximum daily rainfall (current (-) and one month ago (-)), and average relative humidity (current and 9 months ago (-)) had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future.

The role of clouds and oceans in global greenhouse warming. Final report

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

Hoffert, M.I.

1996-10-01

This research focuses on assessing connections between anthropogenic greenhouse gas emissions and global climatic change. it has been supported since the early 1990s in part by the DOE ``Quantitative Links`` Program (QLP). A three-year effort was originally proposed to the QLP to investigate effects f global cloudiness on global climate and its implications for cloud feedback; and to continue the development and application of climate/ocean models, with emphasis on coupled effects of greenhouse warming and feedbacks by clouds and oceans. It is well-known that cloud and ocean processes are major sources of uncertainty in the ability to predict climatic changemore » from humankind`s greenhouse gas and aerosol emissions. And it has always been the objective to develop timely and useful analytical tools for addressing real world policy issues stemming from anthropogenic climate change.« less

Modeling the influence of a reduced equator-to-pole sea surface temperature gradient on the distribution of water isotopes in the Early/Middle Eocene

NASA Astrophysics Data System (ADS)

Speelman, Eveline N.; Sewall, Jacob O.; Noone, David; Huber, Matthew; von der Heydt, Anna; Damsté, Jaap Sinninghe; Reichart, Gert-Jan

2010-09-01

Proxy-based climate reconstructions suggest the existence of a strongly reduced equator-to-pole temperature gradient during the Azolla interval in the Early/Middle Eocene, compared to modern. Changes in the hydrological cycle, as a consequence of a reduced temperature gradient, are expected to be reflected in the isotopic composition of precipitation (δD, δ 18O). The interpretation of water isotopic records to quantitatively reconstruct past precipitation patterns is, however, hampered by a lack of detailed information on changes in their spatial and temporal distribution. Using the isotope-enabled version of the National Center for Atmospheric Research (NCAR) atmospheric general circulation model, Community Atmosphere Model v.3 (isoCAM3), relationships between water isotopes and past climates can be simulated. Here we examine the influence of an imposed reduced meridional sea surface temperature gradient on the spatial distribution of precipitation and its isotopic composition in an Early/Middle Eocene setting. As a result of the applied forcings, the Eocene simulation predicts the occurrence of less depleted high latitude precipitation, with δD values ranging only between 0 and -140‰ (compared to Present-day 0 to -300‰). Comparison with Early/Middle Eocene-age isotopic proxy data shows that the simulation accurately captures the main features of the spatial distribution of the isotopic composition of Early/Middle Eocene precipitation over land in conjunction with the aspects of the modeled Early/Middle Eocene climate. Hence, the included stable isotope module quantitatively supports the existence of a reduced meridional temperature gradient during this interval.

Pollen-based continental climate reconstructions at 6 and 21 ka: A global synthesis

USGS Publications Warehouse

Bartlein, P.J.; Harrison, S.P.; Brewer, Sandra; Connor, S.; Davis, B.A.S.; Gajewski, K.; Guiot, J.; Harrison-Prentice, T. I.; Henderson, A.; Peyron, O.; Prentice, I.C.; Scholze, M.; Seppa, H.; Shuman, B.; Sugita, S.; Thompson, R.S.; Viau, A.E.; Williams, J.; Wu, H.

2011-01-01

Subfossil pollen and plant macrofossil data derived from 14C-dated sediment profiles can provide quantitative information on glacial and interglacial climates. The data allow climate variables related to growing-season warmth, winter cold, and plant-available moisture to be reconstructed. Continental-scale reconstructions have been made for the mid-Holocene (MH, around 6 ka) and Last Glacial Maximum (LGM, around 21 ka), allowing comparison with palaeoclimate simulations currently being carried out as part of the fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change. The synthesis of the available MH and LGM climate reconstructions and their uncertainties, obtained using modern-analogue, regression and model-inversion techniques, is presented for four temperature variables and two moisture variables. Reconstructions of the same variables based on surface-pollen assemblages are shown to be accurate and unbiased. Reconstructed LGM and MH climate anomaly patterns are coherent, consistent between variables, and robust with respect to the choice of technique. They support a conceptual model of the controls of Late Quaternary climate change whereby the first-order effects of orbital variations and greenhouse forcing on the seasonal cycle of temperature are predictably modified by responses of the atmospheric circulation and surface energy balance. ?? 2010 The Author(s).

Assessment of the Casualty Risk of Multiple Meteorological Hazards in China

PubMed Central

Xu, Wei; Zhuo, Li; Zheng, Jing; Ge, Yi; Gu, Zhihui; Tian, Yugang

2016-01-01

A study of the frequency, intensity, and risk of extreme climatic events or natural hazards is important for assessing the impacts of climate change. Many models have been developed to assess the risk of multiple hazards, however, most of the existing approaches can only model the relative levels of risk. This paper reports the development of a method for the quantitative assessment of the risk of multiple hazards based on information diffusion. This method was used to assess the risks of loss of human lives from 11 types of meteorological hazards in China at the prefectural and provincial levels. Risk curves of multiple hazards were obtained for each province and the risks of 10-year, 20-year, 50-year, and 100-year return periods were mapped. The results show that the provinces (municipalities, autonomous regions) in southeastern China are at higher risk of multiple meteorological hazards as a result of their geographical location and topography. The results of this study can be used as references for the management of meteorological disasters in China. The model can be used to quantitatively calculate the risks of casualty, direct economic losses, building collapse, and agricultural losses for any hazards at different spatial scales. PMID:26901210

Assessment of the Casualty Risk of Multiple Meteorological Hazards in China.

PubMed

Xu, Wei; Zhuo, Li; Zheng, Jing; Ge, Yi; Gu, Zhihui; Tian, Yugang

2016-02-17

A study of the frequency, intensity, and risk of extreme climatic events or natural hazards is important for assessing the impacts of climate change. Many models have been developed to assess the risk of multiple hazards, however, most of the existing approaches can only model the relative levels of risk. This paper reports the development of a method for the quantitative assessment of the risk of multiple hazards based on information diffusion. This method was used to assess the risks of loss of human lives from 11 types of meteorological hazards in China at the prefectural and provincial levels. Risk curves of multiple hazards were obtained for each province and the risks of 10-year, 20-year, 50-year, and 100-year return periods were mapped. The results show that the provinces (municipalities, autonomous regions) in southeastern China are at higher risk of multiple meteorological hazards as a result of their geographical location and topography. The results of this study can be used as references for the management of meteorological disasters in China. The model can be used to quantitatively calculate the risks of casualty, direct economic losses, building collapse, and agricultural losses for any hazards at different spatial scales.

Assessing uncertainties in global cropland futures using a conditional probabilistic modelling framework

NASA Astrophysics Data System (ADS)

Engström, Kerstin; Olin, Stefan; Rounsevell, Mark D. A.; Brogaard, Sara; van Vuuren, Detlef P.; Alexander, Peter; Murray-Rust, Dave; Arneth, Almut

2016-11-01

We present a modelling framework to simulate probabilistic futures of global cropland areas that are conditional on the SSP (shared socio-economic pathway) scenarios. Simulations are based on the Parsimonious Land Use Model (PLUM) linked with the global dynamic vegetation model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) using socio-economic data from the SSPs and climate data from the RCPs (representative concentration pathways). The simulated range of global cropland is 893-2380 Mha in 2100 (± 1 standard deviation), with the main uncertainties arising from differences in the socio-economic conditions prescribed by the SSP scenarios and the assumptions that underpin the translation of qualitative SSP storylines into quantitative model input parameters. Uncertainties in the assumptions for population growth, technological change and cropland degradation were found to be the most important for global cropland, while uncertainty in food consumption had less influence on the results. The uncertainties arising from climate variability and the differences between climate change scenarios do not strongly affect the range of global cropland futures. Some overlap occurred across all of the conditional probabilistic futures, except for those based on SSP3. We conclude that completely different socio-economic and climate change futures, although sharing low to medium population development, can result in very similar cropland areas on the aggregated global scale.

Vegetation Fires in the Coupled Human-Earth System Under Future Environmental and Policy Perspectives

NASA Astrophysics Data System (ADS)

le page, Y.; Morton, D. C.; Hurtt, G. C.

2013-12-01

Fires play a major role in terrestrial ecosystems dynamics and the carbon cycle. Potential changes in fire regimes due to climate change, land use change, or human management could have substantial ecological, climatic and socio-economic impacts, and have recently been emphasized as a source of uncertainty for policy-makers and climate mitigation cost estimates. Anticipating these interactions thus entails interdisciplinary models. Here we describe the development of a new fire modeling framework, which features the essential integration of climatic, vegetation and anthropogenic drivers. The model is an attempt to realistically account for ignition, spread and termination processes, on a 12-hour time step and at 1 degree spatial resolution globally. Because the quantitative influence of fire drivers on these processes are often poorly constrained, the framework includes an optimization procedure whereby key parameters (e.g. influence of moisture on fire spread, probability of cloud-to-ground lightning flashes to actually ignite a fire, human ignition frequency as a function of land use density) are determined to maximize the agreement between modeled and observed burned area over the past decade. The model performs surprisingly well across all biomes, and shows good agreement on non-optimized features, such as seasonality and fire size, which suggests some potential for robust projections. We couple the model to an integrated assessment model and explore the consequences of mitigation policies, land use decisions and climate change on future fire regimes with a focus on the Amazon basin. The coupled model future projections show that business-as-usual land use expansion would increase the frequency of escaped fires in the remaining forest, especially when combined with models projecting a drier climate. Inversely, climate mitigation policies as projected in the IPCC RCP4.5 scenario achieve synergistic benefits, with increased forest extent, less fire ignitions, and higher moisture levels.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.

PubMed

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H; Gambhir, Manoj; Fu, Joshua S; Liu, Yang; Remais, Justin V

2013-09-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis , the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors

PubMed Central

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H.; Gambhir, Manoj; Fu, Joshua S.; Liu, Yang; Remais, Justin V.

2014-01-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate. PMID:24772388

Joint Applications Pilot of the National Climate Predictions and Projections Platform and the North Central Climate Science Center: Delivering climate projections on regional scales to support adaptation planning

NASA Astrophysics Data System (ADS)

Ray, A. J.; Ojima, D. S.; Morisette, J. T.

2012-12-01

The DOI North Central Climate Science Center (NC CSC) and the NOAA/NCAR National Climate Predictions and Projections (NCPP) Platform and have initiated a joint pilot study to collaboratively explore the "best available climate information" to support key land management questions and how to provide this information. NCPP's mission is to support state of the art approaches to develop and deliver comprehensive regional climate information and facilitate its use in decision making and adaptation planning. This presentation will describe the evolving joint pilot as a tangible, real-world demonstration of linkages between climate science, ecosystem science and resource management. Our joint pilot is developing a deliberate, ongoing interaction to prototype how NCPP will work with CSCs to develop and deliver needed climate information products, including translational information to support climate data understanding and use. This pilot also will build capacity in the North Central CSC by working with NCPP to use climate information used as input to ecological modeling. We will discuss lessons to date on developing and delivering needed climate information products based on this strategic partnership. Four projects have been funded to collaborate to incorporate climate information as part of an ecological modeling project, which in turn will address key DOI stakeholder priorities in the region: Riparian Corridors: Projecting climate change effects on cottonwood and willow seed dispersal phenology, flood timing, and seedling recruitment in western riparian forests. Sage Grouse & Habitats: Integrating climate and biological data into land management decision models to assess species and habitat vulnerability Grasslands & Forests: Projecting future effects of land management, natural disturbance, and CO2 on woody encroachment in the Northern Great Plains The value of climate information: Supporting management decisions in the Plains and Prairie Potholes LCC. NCCSC's role in these projects is to provide the connections between climate data and running ecological models, and prototype these for future work. NCPP will develop capacities to provide enhanced climate information at relevant spatial and temporal scales, both for historical climate and projections of future climate, and will work to link expert guidance and understanding of modeling processes and evaluation of modeling with the use of numerical climate data. Translational information thus is a suite of information that aids in translation of numerical climate information into usable knowledge for applications, e.g. ecological response models, hydrologic risk studies. This information includes technical and scientific aspects including, but not limited to: 1) results of objective, quantitative evaluation of climate models & downscaling techniques, 2) guidance on appropriate uses and interpretation, i.e., understanding the advantages and limitations of various downscaling techniques for specific user applications, 3) characterizing and interpreting uncertainty, 4) Descriptions meaningful to applications, e.g. narratives. NCPP believes that translational information is best co-developed between climate scientists and applications scientists, such as the NC-CSC pilot.

North Pacific atmospheric rivers and their influence on western North America at the Last Glacial Maximum

NASA Astrophysics Data System (ADS)

Lora, Juan M.; Mitchell, Jonathan L.; Risi, Camille; Tripati, Aradhna E.

2017-01-01

Southwestern North America was wetter than present during the Last Glacial Maximum. The causes of increased water availability have been recently debated, and quantitative precipitation reconstructions have been underutilized in model-data comparisons. We investigate the climatological response of North Pacific atmospheric rivers to the glacial climate using model simulations and paleoclimate reconstructions. Atmospheric moisture transport due to these features shifted toward the southeast relative to modern. Enhanced southwesterly moisture delivery between Hawaii and California increased precipitation in the southwest while decreasing it in the Pacific Northwest, in agreement with reconstructions. Coupled climate models that are best able to reproduce reconstructed precipitation changes simulate decreases in sea level pressure across the eastern North Pacific and show the strongest southeastward shifts of moisture transport relative to a modern climate. Precipitation increases of ˜1 mm d-1, due largely to atmospheric rivers, are of the right magnitude to account for reconstructed pluvial conditions in parts of southwestern North America during the Last Glacial Maximum.

CO2, the greenhouse effect and global warming: from the pioneering work of Arrhenius and Callendar to today's Earth System Models.

PubMed

Anderson, Thomas R; Hawkins, Ed; Jones, Philip D

2016-09-01

Climate warming during the course of the twenty-first century is projected to be between 1.0 and 3.7°C depending on future greenhouse gas emissions, based on the ensemble-mean results of state-of-the-art Earth System Models (ESMs). Just how reliable are these projections, given the complexity of the climate system? The early history of climate research provides insight into the understanding and science needed to answer this question. We examine the mathematical quantifications of planetary energy budget developed by Svante Arrhenius (1859-1927) and Guy Stewart Callendar (1898-1964) and construct an empirical approximation of the latter, which we show to be successful at retrospectively predicting global warming over the course of the twentieth century. This approximation is then used to calculate warming in response to increasing atmospheric greenhouse gases during the twenty-first century, projecting a temperature increase at the lower bound of results generated by an ensemble of ESMs (as presented in the latest assessment by the Intergovernmental Panel on Climate Change). This result can be interpreted as follows. The climate system is conceptually complex but has at its heart the physical laws of radiative transfer. This basic, or "core" physics is relatively straightforward to compute mathematically, as exemplified by Callendar's calculations, leading to quantitatively robust projections of baseline warming. The ESMs include not only the physical core but also climate feedbacks that introduce uncertainty into the projections in terms of magnitude, but not sign: positive (amplification of warming). As such, the projections of end-of-century global warming by ESMs are fundamentally trustworthy: quantitatively robust baseline warming based on the well-understood physics of radiative transfer, with extra warming due to climate feedbacks. These projections thus provide a compelling case that global climate will continue to undergo significant warming in response to ongoing emissions of CO 2 and other greenhouse gases to the atmosphere. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

2013-01-01

Simulations using IPCC-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We apply support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicts model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures are determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations are the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

Development and Performance of Alternative Electricity Sector Pathways Subject to Multiple Climate and Water Projections

NASA Astrophysics Data System (ADS)

Newmark, R. L.; Vorosmarty, C. J.; Miara, A.; Cohen, S.; Macknick, J.; Sun, Y.; Corsi, F.; Fekete, B. M.; Tidwell, V. C.

2017-12-01

Climate change impacts on air temperatures and water availability have the potential to alter future electricity sector investment decisions as well as the reliability and performance of the power sector. Different electricity sector configurations are more or less vulnerable to climate-induced changes. For example, once-through cooled thermal facilities are the most cost-effective and efficient technologies under cooler and wetter conditions, but can be substantially affected by and vulnerable to warmer and drier conditions. Non-thermal renewable technologies, such as PV and wind, are essentially "drought-proof" but have other integration and reliability challenges. Prior efforts have explored the impacts of climate change on electric sector development for a limited set of climate and electricity scenarios. Here, we provide a comprehensive suite of scenarios that evaluate how different electricity sector pathways could be affected by a range of climate and water resource conditions. We use four representative concentration pathway (RCP) scenarios under five global circulation models (GCM) as climate drivers to a Water Balance Model (WBM), to provide twenty separate future climate-water conditions. These climate-water conditions influence electricity sector development from present day to 2050 as determined using the Regional Energy Deployment Systems (ReEDS) model. Four unique electricity sector pathways will be considered, including business-as-usual, carbon cap, high renewable energy technology costs, and coal reliance scenarios. The combination of climate-water and electricity sector pathway scenarios leads to 80 potential future cases resulting in different national and regional electricity infrastructure configurations. The vulnerability of these configurations in relation to climate change (including in-stream thermal pollution impacts and environmental regulations) is evaluated using the Thermoelectric Power and Thermal Pollution (TP2M) model, providing quantitative estimates of the power sector's ability to meet loads, given changes in air temperature, water temperature, and water availability.

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

The influence of the hydrologic cycle on the extent of sea ice with climatic implications

NASA Technical Reports Server (NTRS)

Dean, Ken; Gosink, Joan

1991-01-01

The role was analyzed of the hydrologic cycle on the distribution of sea ice, and its influence on forcings and fluxes between the marine environment and the atmosphere. River discharge plays a significant role in degrading the sea ice before any melting occurs elsewhere along the coast. The influence is considered of river discharge on the albedo, thermal balance, and distribution of sea ice. Quantitative atmospheric-hydrologic models are being developed to describe these processes in the coastal zone. Input for the models will come from satellite images, hydrologic data, and field observations. The resulting analysis provides a basis for the study of the significance of the hydrologic cycle throughout the Arctic Basin and its influence on the regional climate as a result of possible climatic scenarios. The area offshore from the Mackenzie River delta was selected as the study area.

Coupling Processes Between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, Malcolm K. W.; Weisenstein, Debra; Rodriguez, Jose; Danilin, Michael; Scott, Courtney; Shia, Run-Lie; Eluszkiewicz, Junusz; Sze, Nien-Dak

1999-01-01

This is the final report. The overall objective of this project is to improve the understanding of coupling processes among atmospheric chemistry, aerosol and climate, all important for quantitative assessments of global change. Among our priority are changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The work emphasizes two important aspects: (1) AER's continued participation in preparation of, and providing scientific input for, various scientific reports connected with assessment of stratospheric ozone and climate. These include participation in various model intercomparison exercises as well as preparation of national and international reports. and (2) Continued development of the AER three-wave interactive model to address how the transport circulation will change as ozone and the thermal properties of the atmosphere change, and assess how these new findings will affect our confidence in the ozone assessment results.

Mapping (dis)agreement in hydrologic projections

NASA Astrophysics Data System (ADS)

Melsen, Lieke A.; Addor, Nans; Mizukami, Naoki; Newman, Andrew J.; Torfs, Paul J. J. F.; Clark, Martyn P.; Uijlenhoet, Remko; Teuling, Adriaan J.

2018-03-01

Hydrologic projections are of vital socio-economic importance. However, they are also prone to uncertainty. In order to establish a meaningful range of storylines to support water managers in decision making, we need to reveal the relevant sources of uncertainty. Here, we systematically and extensively investigate uncertainty in hydrologic projections for 605 basins throughout the contiguous US. We show that in the majority of the basins, the sign of change in average annual runoff and discharge timing for the period 2070-2100 compared to 1985-2008 differs among combinations of climate models, hydrologic models, and parameters. Mapping the results revealed that different sources of uncertainty dominate in different regions. Hydrologic model induced uncertainty in the sign of change in mean runoff was related to snow processes and aridity, whereas uncertainty in both mean runoff and discharge timing induced by the climate models was related to disagreement among the models regarding the change in precipitation. Overall, disagreement on the sign of change was more widespread for the mean runoff than for the discharge timing. The results demonstrate the need to define a wide range of quantitative hydrologic storylines, including parameter, hydrologic model, and climate model forcing uncertainty, to support water resource planning.

Systems Approach to Climate, Water, and Diarrhea in Hubli-Dharwad, India.

PubMed

Mellor, Jonathan; Kumpel, Emily; Ercumen, Ayse; Zimmerman, Julie

2016-12-06

Anthropogenic climate change will likely increase diarrhea rates for communities with inadequate water, sanitation, or hygiene facilities including those with intermittent water supplies. Current approaches to study these impacts typically focus on the effect of temperature on all-cause diarrhea while excluding precipitation and diarrhea etiology while not providing actionable adaptation strategies. We develop a partially mechanistic, systems approach to estimate future diarrhea prevalence and design adaptation strategies. The model incorporates downscaled global climate models, water quality data, quantitative microbial risk assessment, and pathogen prevalence in an agent-based modeling framework incorporating precipitation and diarrhea etiology. It is informed using water quality and diarrhea data from Hubli-Dharwad, India-a city with an intermittent piped water supply exhibiting seasonal water quality variability vulnerable to climate change. We predict all-cause diarrhea prevalence to increase by 4.9% (Range: 1.5-9.0%) by 2011-2030, 11.9% (Range: 7.1-18.2%) by 2046-2065, and 18.2% (Range: 9.1-26.2%) by 2080-2099. Rainfall is an important modifying factor. Rotavirus prevalence is estimated to decline by 10.5% with Cryptosporidium and E. coli prevalence increasing by 9.9% and 6.3%, respectively, by 2080-2099 in this setting. These results suggest that ceramic water filters would be recommended as a climate adaptation strategy over chlorination. This work highlights the vulnerability of intermittent water supplies to climate change and the urgent need for improvements.

Effects of land-use and climate on Holocene vegetation composition in northern Europe

NASA Astrophysics Data System (ADS)

Marquer, Laurent; Gaillard, Marie-José; Sugita, Shinya; Poska, Anneli; Trondman, Anna-Kari; Mazier, Florence; Nielsen, Anne Birgitte; Fyfe, Ralph; Jönsson, Anna Maria

2016-04-01

Prior to the advent of agriculture, broad-scale vegetation patterns in Europe were controlled primarily by climate. Early agriculture can be detected in palaeovegetation records, but the relative extent to which past regional vegetation was climatically or anthropogenically-forced is of current scientific interest. Using comparisons of transformed pollen data, climate-model data, dynamic vegetation model simulations and anthropogenic land-cover change data, this study aims to estimate the relative impacts of human activities and climate on the Holocene vegetation composition of northern Europe at a subcontinental scale. The REVEALS model was used for pollen-based quantitative reconstruction of vegetation (RV). Climate variables from ECHAM and the extent of human deforestation from KK10 were used as explanatory variables to evaluate their respective impacts on RV. Indices of vegetation-composition changes based on RV and climate-induced vegetation simulated by the LPJ-GUESS model (LPJG) were used to assess the relative importance of climate and anthropogenic impacts. The results show that climate is the major predictor of Holocene vegetation changes until 5000 years ago. The similarity in rate of change and turnover between RV and LPJG decreases after this time. Changes in RV explained by climate and KK10 vary for the last 2000 years; the similarity in rate of change, turnover, and evenness between RV and LPJG decreases to the present. The main conclusions provide important insights on Neolithic forest clearances that affected regional vegetation from 6700 years ago, although climate (temperature and precipitation) still was a major driver of vegetation change (explains 37% of the variation) at the subcontinental scale. Land use became more important around 5000-4000 years ago, while the influence of climate decreased (explains 28% of the variation). Land-use affects all indices of vegetation compositional change during the last 2000 years; the influence of climate on vegetation, although reduced, remains at 16% until modern time while land-use explains 7%, which underlines that North-European vegetation is still climatically sensitive and, therefore, responds strongly to ongoing climate change.

Drivers of pluvial lake distributions in western North America

NASA Astrophysics Data System (ADS)

Ibarra, D. E.; Oster, J. L.; Winnick, M.; Caves, J. K.; Ritch, A. J.; Chamberlain, C. P.; Maher, K.

2016-12-01

The distribution of large inland lakes in western North America during the Plio-Pleistocene is intimately linked to the regional hydroclimate and moisture delivery dynamics. We investigate the climatological conditions driving terminal basin lakes in western North America during the mid-Pliocene warm period and the latest Pleistocene glacial maximum. Lacustrine deposits and geologic proxies suggest that lakes and wet conditions persisted during both warm and cold periods in the southwest, despite dramatically different global climate, ice sheet configuration and pCO2 levels. We use two complementary methods to quantify the hydroclimate drivers of terminal basin lake levels. First, a quantitative proxy-model comparison is conducted using compilations of geologic proxies and an ensemble of climate models. We utilize archived climate model simulations of the Last Glacial Maximum (21 ka, LGM) and mid-Pliocene (3.3 Ma) produced by the Paleoclimate Modelling Intercomparison Project (PMIP and PlioMIP). Our proxy network is made up of stable isotope records from caves, soils and paleosols, lake deposits and shorelines, glacier chronologies, and packrat middens. Second, we forward model the spatial distribution of lakes in the region using a Budyko framework to constrain the water balance for terminally draining watersheds, and make quantitative comparisons to mapped lacustrine shorelines and outcrops. Cumulatively these two approaches suggest that reduced evaporation and moderate increases in precipitation, relative to modern, drove moderate to large pluvial lakes during the LGM in the Great Basin. In contrast, larger precipitation increases appear to be the primary driver of lake levels during the mid-Pliocene in the southwest, with this spatial difference suggesting a role for El Niño teleconnections. These results demonstrate that during past periods of global change patterns of `dry-gets-drier, wet-gets-wetter' do not hold true for western North America.

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.

Modeling the influence of a reduced equator-to-pole sea surface temperature gradient on the distribution of water isotopes in the Eocene

NASA Astrophysics Data System (ADS)

Speelman, E. N.; Sewall, J. O.; Noone, D. C.; Huber, M.; Sinninghe Damsté, J. S.; Reichart, G.

2009-12-01

Proxy-based climate reconstructions suggest the existence of a strongly reduced equator-to-pole temperature gradient during most of the Early Eocene. With the realization that the Eocene Arctic Ocean was covered with enormous quantities of the free floating freshwater fern Azolla, new questions related to Eocene (global) hydrological cycling facilitating these blooms arose. Changes in hydrological cycling, as a consequence of a reduced temperature gradient, are expected to be most clearly reflected in the isotopic composition (D, 18O) of precipitation. The interpretation of water isotopic records to quantitatively estimate past precipitation patterns is, however, hampered by the lack of detailed information on changes in their spatial and temporal distribution. Using the isotope-enabled global circulation model, Community Atmosphere Model v.3 (isoCAM3), relationships between water isotopes and past climates can be simulated. Here we examine the influence of a reduced meridional sea surface temperature gradient on the spatial distribution of precipitation and its isotopic composition in an Eocene setting. Overall, our combination of Eocene climate forcings, with superimposed TEX86-derived SST estimates and elevated pCO2 concentrations, produces a climate that agrees well with proxy data in locations around the globe. It shows the presence of an intensified hydrological cycle with precipitation exceeding evaporation in the Arctic region. The Eocene model runs with a significantly reduced equator-to-pole temperature gradient in a warmer more humid world predict occurrence of less depleted precipitation, with δD values ranging only between 0 and -140‰ (as opposed to the present-day range of 0 to -300‰). Combining new results obtained from compound specific isotope analyses on terrestrially derived n-alkanes extracted from Eocene sediments, and model calculations, shows that the model not only captures the main features, but reproduces isotopic values quantitatively as well. This combination of modeling outcomes and independent stable isotope records thus confirms independently the validity of the earlier, proxy-based, inferred reduced meridional temperature gradient.

Exploring the Causes of Mid-Holocene Drought in the Rocky Mountains Using Hydrologic Forward Models

NASA Astrophysics Data System (ADS)

Meador, E.; Morrill, C.

2017-12-01

We present a quantitative model-data comparison for mid-Holocene (6 ka) lake levels in the Rocky Mountains, with the goals of assessing the skill coupled climate models and hydrologic forward models in simulating climate change and improving our understanding of the factors causing past changes in water resources. The mid-Holocene climate in this area may in some ways be similar to expected future climate, thus improved understanding of the factors causing past changes in water resources have the potential to aid in the process of water allocation for large areas that share a relatively small water source. This project focuses on Little Windy Hill Pond in the Medicine Bow Forest in the Rocky Mountains in southern Wyoming. We first calibrated the Variable Infiltration Capacity (VIC) catchment hydrologic model and the one-dimensional Hostetler Bartlein lake energy-balance model to modern observations, using U.S. Geological Survey stream discharge data and Snow Telemetry (SNOTEL) data to ensure appropriate selection of model parameters. Once the models were calibrated to modern conditions, we forced them with output from eight mid-Holocene coupled climate model simulations completed as part of the Coupled Model Intercomparison Project, Phase 5. Forcing from nearly all of the CMIP5 models generates intense, short-lived droughts for the mid-Holocene that are more severe than any we modeled for the past six decades. The severity of the mid-Holocene droughts could be sufficient, depending on sediment processes in the lake, to account for low lake levels recorded by loss-on-ignition in sediment cores. Our preliminary analysis of model output indicates that the combined effects of decreased snowmelt runoff and increased summer lake evaporation cause low mid-Holocene lake levels. These factors are also expected to be important in the future under anthropogenic climate change.

Evaluation of CMIP5 Ability to Reproduce 20th Century Regional Trends in Surface Air Temperature and Precipitation over CONUS

NASA Astrophysics Data System (ADS)

Lee, J.; Waliser, D. E.; Lee, H.; Loikith, P. C.; Kunkel, K.

2017-12-01

Monitoring temporal changes in key climate variables, such as surface air temperature and precipitation, is an integral part of the ongoing efforts of the United States National Climate Assessment (NCA). Climate models participating in CMIP5 provide future trends for four different emissions scenarios. In order to have confidence in the future projections of surface air temperature and precipitation, it is crucial to evaluate the ability of CMIP5 models to reproduce observed trends for three different time periods (1895-1939, 1940-1979, and 1980-2005). Towards this goal, trends in surface air temperature and precipitation obtained from the NOAA nClimGrid 5 km gridded station observation-based product are compared during all three time periods to the 206 CMIP5 historical simulations from 48 unique GCMs and their multi-model ensemble (MME) for NCA-defined climate regions during summer (JJA) and winter (DJF). This evaluation quantitatively examines the biases of simulated trends of the spatially averaged temperature and precipitation in the NCA climate regions. The CMIP5 MME reproduces historical surface air temperature trends for JJA for all time period and all regions, except the Northern Great Plains from 1895-1939 and Southeast during 1980-2005. Likewise, for DJF, the MME reproduces historical surface air temperature trends across all time periods over all regions except the Southeast from 1895-1939 and the Midwest during 1940-1979. The Regional Climate Model Evaluation System (RCMES), an analysis tool which supports the NCA by providing access to data and tools for regional climate model validation, facilitates the comparisons between the models and observation. The RCMES Toolkit is designed to assist in the analysis of climate variables and the procedure of the evaluation of climate projection models to support the decision-making processes. This tool is used in conjunction with the above analysis and results will be presented to demonstrate its capability to access observation and model datasets, calculate evaluation metrics, and visualize the results. Several other examples of the RCMES capabilities can be found at https://rcmes.jpl.nasa.gov.

Modeling the potential impacts of climate change on the water table level of selected forested wetlands in the southeastern United States

NASA Astrophysics Data System (ADS)

Zhu, Jie; Sun, Ge; Li, Wenhong; Zhang, Yu; Miao, Guofang; Noormets, Asko; McNulty, Steve G.; King, John S.; Kumar, Mukesh; Wang, Xuan

2017-12-01

The southeastern United States hosts extensive forested wetlands, providing ecosystem services including carbon sequestration, water quality improvement, groundwater recharge, and wildlife habitat. However, these wetland ecosystems are dependent on local climate and hydrology, and are therefore at risk due to climate and land use change. This study develops site-specific empirical hydrologic models for five forested wetlands with different characteristics by analyzing long-term observed meteorological and hydrological data. These wetlands represent typical cypress ponds/swamps, Carolina bays, pine flatwoods, drained pocosins, and natural bottomland hardwood ecosystems. The validated empirical models are then applied at each wetland to predict future water table changes using climate projections from 20 general circulation models (GCMs) participating in Coupled Model Inter-comparison Project 5 (CMIP5) under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios. We show that combined future changes in precipitation and potential evapotranspiration would significantly alter wetland hydrology including groundwater dynamics by the end of the 21st century. Compared to the historical period, all five wetlands are predicted to become drier over time. The mean water table depth is predicted to drop by 4 to 22 cm in response to the decrease in water availability (i.e., precipitation minus potential evapotranspiration) by the year 2100. Among the five examined wetlands, the depressional wetland in hot and humid Florida appears to be most vulnerable to future climate change. This study provides quantitative information on the potential magnitude of wetland hydrological response to future climate change in typical forested wetlands in the southeastern US.

Plant functional diversity affects climate-vegetation interaction

NASA Astrophysics Data System (ADS)

Groner, Vivienne P.; Raddatz, Thomas; Reick, Christian H.; Claussen, Martin

2018-04-01

We present how variations in plant functional diversity affect climate-vegetation interaction towards the end of the African Humid Period (AHP) in coupled land-atmosphere simulations using the Max Planck Institute Earth system model (MPI-ESM). In experiments with AHP boundary conditions, the extent of the green Sahara varies considerably with changes in plant functional diversity. Differences in vegetation cover extent and plant functional type (PFT) composition translate into significantly different land surface parameters, water cycling, and surface energy budgets. These changes have not only regional consequences but considerably alter large-scale atmospheric circulation patterns and the position of the tropical rain belt. Towards the end of the AHP, simulations with the standard PFT set in MPI-ESM depict a gradual decrease of precipitation and vegetation cover over time, while simulations with modified PFT composition show either a sharp decline of both variables or an even slower retreat. Thus, not the quantitative but the qualitative PFT composition determines climate-vegetation interaction and the climate-vegetation system response to external forcing. The sensitivity of simulated system states to changes in PFT composition raises the question how realistically Earth system models can actually represent climate-vegetation interaction, considering the poor representation of plant diversity in the current generation of land surface models.

How to make predictions about future infectious disease risks

PubMed Central

Woolhouse, Mark

2011-01-01

Formal, quantitative approaches are now widely used to make predictions about the likelihood of an infectious disease outbreak, how the disease will spread, and how to control it. Several well-established methodologies are available, including risk factor analysis, risk modelling and dynamic modelling. Even so, predictive modelling is very much the ‘art of the possible’, which tends to drive research effort towards some areas and away from others which may be at least as important. Building on the undoubted success of quantitative modelling of the epidemiology and control of human and animal diseases such as AIDS, influenza, foot-and-mouth disease and BSE, attention needs to be paid to developing a more holistic framework that captures the role of the underlying drivers of disease risks, from demography and behaviour to land use and climate change. At the same time, there is still considerable room for improvement in how quantitative analyses and their outputs are communicated to policy makers and other stakeholders. A starting point would be generally accepted guidelines for ‘good practice’ for the development and the use of predictive models. PMID:21624924

The Data Platform for Climate Research and Action: Introducing Climate Watch

NASA Astrophysics Data System (ADS)

Hennig, R. J.; Ge, M.; Friedrich, J.; Lebling, K.; Carlock, G.; Arcipowska, A.; Mangan, E.; Biru, H.; Tankou, A.; Chaudhury, M.

2017-12-01

The Paris Agreement, adopted through Decision 1/CP.21, brings all nations together to take on ambitious efforts to combat climate change. Open access to climate data supporting climate research, advancing knowledge, and informing decision making is key to encourage and strengthen efforts of stakeholders at all levels to address and respond to effects of climate change. Climate Watch is a robust online data platform developed in response to the urgent needs of knowledge and tools to empower climate research and action, including those of researchers, policy makers, the private sector, civil society, and all other non-state actors. Building on the rapid growing technology of open data and information sharing, Climate Watch is equipped with extensive amount of climate data, informative visualizations, concise yet efficient user interface, and connection to resources users need to gather insightful information on national and global progress towards delivering on the objective of the Convention and the Paris Agreement. Climate Watch brings together hundreds of quantitative and qualitative indicators for easy explore, visualize, compare, download at global, national, and sectoral levels: Greenhouse gas (GHG) emissions for more than 190 countries over the1850-2014 time period, covering all seven Kyoto Gases following IPCC source/sink categories; Structured information on over 150 NDCs facilitating the clarity, understanding and transparency of countries' contributions to address climate change; Over 6500 identified linkages between climate actions in NDCs across the 169 targets of the sustainable development goals (SDG); Over 200 indicators describing low carbon pathways from models and scenarios by integrated assessment models (IAMs) and national sources; and Data on vulnerability and risk, policies, finance, and many more. Climate Watch platform is developed as part of the broader efforts within the World Resources Institute, the NDC Partnership, and in collaboration with GIZ, UNFCCC, World Bank, and Climate Analytics.

An empirical test of the relative and combined effects of land-cover and climate change on local colonization and extinction.

PubMed

Yalcin, Semra; Leroux, Shawn James

2018-04-14

Land-cover and climate change are two main drivers of changes in species ranges. Yet, the majority of studies investigating the impacts of global change on biodiversity focus on one global change driver and usually use simulations to project biodiversity responses to future conditions. We conduct an empirical test of the relative and combined effects of land-cover and climate change on species occurrence changes. Specifically, we examine whether observed local colonization and extinctions of North American birds between 1981-1985 and 2001-2005 are correlated with land-cover and climate change and whether bird life history and ecological traits explain interspecific variation in observed occurrence changes. We fit logistic regression models to test the impact of physical land-cover change, changes in net primary productivity, winter precipitation, mean summer temperature, and mean winter temperature on the probability of Ontario breeding bird local colonization and extinction. Models with climate change, land-cover change, and the combination of these two drivers were the top ranked models of local colonization for 30%, 27%, and 29% of species, respectively. Conversely, models with climate change, land-cover change, and the combination of these two drivers were the top ranked models of local extinction for 61%, 7%, and 9% of species, respectively. The quantitative impacts of land-cover and climate change variables also vary among bird species. We then fit linear regression models to test whether the variation in regional colonization and extinction rate could be explained by mean body mass, migratory strategy, and habitat preference of birds. Overall, species traits were weakly correlated with heterogeneity in species occurrence changes. We provide empirical evidence showing that land-cover change, climate change, and the combination of multiple global change drivers can differentially explain observed species local colonization and extinction. © 2018 John Wiley & Sons Ltd.

Modelling climate change impacts on tourism demand: A comparative study from Sardinia (Italy) and Cap Bon (Tunisia).

PubMed

Köberl, Judith; Prettenthaler, Franz; Bird, David Neil

2016-02-01

Tourism represents an important source of income and employment in many Mediterranean regions, including the island of Sardinia (Italy) and the Cap Bon peninsula (Tunisia). Climate change may however impact tourism in both regions, for example, by altering the regions' climatic suitability for common tourism types or affecting water availability. This paper assesses the potential impacts of climate change on tourism in the case study regions of Sardinia and Cap Bon. Direct impacts are studied in a quantitative way by applying a range of climate scenario data on the empirically estimated relationship between climatic conditions and tourism demand, using two different approaches. Results indicate a potential for climate-induced tourism revenue gains especially in the shoulder seasons during spring and autumn, but also a threat of climate-induced revenue losses in the summer months due to increased heat stress. Annual direct net impacts are nevertheless suggested to be (slightly) positive in both case study regions. Significant climate-induced reductions in total available water may however somewhat counteract the positive direct impacts of climate change by putting additional water costs on the tourism industry. Copyright © 2015 Elsevier B.V. All rights reserved.

Fallacies and fantasies: the theoretical underpinnings of the Coexistence Approach for palaeoclimate reconstruction

NASA Astrophysics Data System (ADS)

Grimm, Guido W.; Potts, Alastair J.

2016-03-01

The Coexistence Approach has been used to infer palaeoclimates for many Eurasian fossil plant assemblages. However, the theory that underpins the method has never been examined in detail. Here we discuss acknowledged and implicit assumptions and assess the statistical nature and pseudo-logic of the method. We also compare the Coexistence Approach theory with the active field of species distribution modelling. We argue that the assumptions will inevitably be violated to some degree and that the method lacks any substantive means to identify or quantify these violations. The absence of a statistical framework makes the method highly vulnerable to the vagaries of statistical outliers and exotic elements. In addition, we find numerous logical inconsistencies, such as how climate shifts are quantified (the use of a "centre value" of a coexistence interval) and the ability to reconstruct "extinct" climates from modern plant distributions. Given the problems that have surfaced in species distribution modelling, accurate and precise quantitative reconstructions of palaeoclimates (or even climate shifts) using the nearest-living-relative principle and rectilinear niches (the basis of the method) will not be possible. The Coexistence Approach can be summarised as an exercise that shoehorns a plant fossil assemblage into coexistence and then assumes that this must be the climate. Given the theoretical issues and methodological issues highlighted elsewhere, we suggest that the method be discontinued and that all past reconstructions be disregarded and revisited using less fallacious methods. We outline six steps for (further) validation of available and future taxon-based methods and advocate developing (semi-quantitative) methods that prioritise robustness over precision.

Potential impacts of agricultural drought on crop yield variability under a changing climate in Texas

NASA Astrophysics Data System (ADS)

Lee, K.; Leng, G.; Huang, M.; Sheffield, J.; Zhao, G.; Gao, H.

2017-12-01

Texas has the largest farm area in the U.S, and its revenue from crop production ranks third overall. With the changing climate, hydrological extremes such as droughts are becoming more frequent and intensified, causing significant yield reduction in rainfed agricultural systems. The objective of this study is to investigate the potential impacts of agricultural drought on crop yields (corn, sorghum, and wheat) under a changing climate in Texas. The Variable Infiltration Capacity (VIC) model, which is calibrated and validated over 10 major Texas river basins during the historical period, is employed in this study.The model is forced by a set of statistically downscaled climate projections from Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensembles at a spatial resolution of 1/8°. The CMIP5 projections contain four Representative Concentration Pathways (RCP) that represent different greenhouse gas concentration (4.5 and 8.5 w/m2 are selected in this study). To carry out the analysis, VIC simulations from 1950 to 2099 are first analyzed to investigate how the frequency and severity of agricultural droughts will be altered in Texas (under a changing climate). Second, future crop yields are projected using a statistical crop model. Third, the effects of agricultural drought on crop yields are quantitatively analyzed. The results are expected to contribute to future water resources planning, with a goal of mitigating the negative impacts of future droughts on agricultural production in Texas.

Understanding the dust cycle at high latitudes: integrating models and observations

NASA Astrophysics Data System (ADS)

Albani, S.; Mahowald, N. M.; Maggi, V.; Delmonte, B.; Winckler, G.; Potenza, M. A. C.; Baccolo, G.; Balkanski, Y.

2017-12-01

Changing climate conditions affect dust emissions and the global dust cycle, which in turn affects climate and biogeochemistry. Paleodust archives from land, ocean, and ice sheets preserve the history of dust deposition for a range of spatial scales from close to the major hemispheric sources to remote sinks such as the polar ice sheets. In each hemisphere common features on the glacial-interglacial time scale mark the baseline evolution of the dust cycle, and inspired the hypothesis that increased dust deposition to ocean stimulated the glacial biological pump contributing to the reduction of atmospheric carbon dioxide levels. On the other hand finer geographical and temporal scales features are superposed to these glacial-interglacial trends, providing the chance of a more sophisticated understanding of the dust cycle, for instance allowing distinctions in terms of source availability or transport patterns as recorded by different records. As such paleodust archives can prove invaluable sources of information, especially when characterized by a quantitative estimation of the mass accumulation rates, and interpreted in connection with climate models. We review our past work and present ongoing research showing how climate models can help in the interpretation of paleodust records, as well as the potential of the same observations for constraining the representation of the global dust cycle embedded in Earth System Models, both in terms of magnitude and physical parameters related to particle sizes and optical properties. Finally we show the impacts on climate, based on this kind of observationally constrained model simulations.

Enhancing Students' Scientific and Quantitative Literacies through an Inquiry-Based Learning Project on Climate Change

ERIC Educational Resources Information Center

McCright, Aaron M.

2012-01-01

Promoting sustainability and dealing with complex environmental problems like climate change demand a citizenry with considerable scientific and quantitative literacy. In particular, students in the STEM disciplines of (biophysical) science, technology, engineering, and mathematics need to develop interdisciplinary skills that help them understand…

Knowledge discovery and nonlinear modeling can complement climate model simulations for predictive insights about climate extremes and their impacts

NASA Astrophysics Data System (ADS)

Ganguly, A. R.; Steinbach, M.; Kumar, V.

2009-12-01

The IPCC AR4 not only provided conclusive evidence about anticipated global warming at century scales, but also indicated with a high level of certainty that the warming is caused by anthropogenic emissions. However, an outstanding knowledge-gap is to develop credible projections of climate extremes and their impacts. Climate extremes are defined in this context as extreme weather and hydrological events, as well as changes in regional hydro-meteorological patterns, especially at decadal scales. While temperature extremes from climate models have relatively better skills, hydrological variables and their extremes have significant shortcomings. Credible projections about tropical storms, sea level rise, coastal storm surge, land glacier melts, and landslides remain elusive. The next generation of climate models is expected to have higher precision. However, their ability to provide more accurate projections of climate extremes remains to be tested. Projections of observed trends into the future may not be reliable in non-stationary environments like climate change, even though functional relationships derived from physics may hold. On the other hand, assessments of climate change impacts which are useful for stakeholders and policy makers depend critically on regional and decadal scale projections of climate extremes. Thus, climate impacts scientists often need to develop qualitative inferences about the not so-well predicted climate extremes based on insights from observations (e.g., increased hurricane intensity) or conceptual understanding (e.g., relation of wildfires to regional warming or drying and hurricanes to SST). However, neither conceptual understanding nor observed trends may be reliable when extrapolating in a non-stationary environment. These urgent societal priorities offer fertile grounds for nonlinear modeling and knowledge discovery approaches. Thus, qualitative inferences on climate extremes and impacts may be transformed into quantitative predictive insights based on a combination of hypothesis-guided data analysis and relatively hypothesis-free but data-guided discovery processes. The analysis and discovery approaches need to be cognizant of climate data characteristics like nonlinear processes, low-frequency variability, long-range spatial dependence and long-memory temporal processes; the value of physically-motivated conceptual understanding and functional associations; as well as possible thresholds and tipping points in the impacted natural, engineered or human systems. Case studies focusing on new methodologies as well as novel climate insights are discussed with a focus on stakeholder requirements.

Java Climate Model: a tool for interaction between science, policy and citizens, to avoid dangerous anthropogenic interference in the climate system

NASA Astrophysics Data System (ADS)

Matthews, B.

2003-04-01

To reach an effective global agreement to help avoid "dangerous anthropogenic interference in the climate system" (UNFCCC article 2) we must balance many complex interacting issues, and also inspire the active engagement of citizens around the world. So we have to transfer understanding back from computers and experts, into the ultimate "integrated assessment model" which remains the global network of human heads. The Java Climate Model (JCM) tries to help provide a quantitative framework for this global dialogue, by enabling anybody to explore many mitigation policy options and scientific uncertainties simply by adjusting parameter controls with a mouse in a web browser. The instant response on linked plots helps to demonstrate cause and effect, and the sensitivity to various assumptions, risk and value judgements. JCM implements the same simple models and formulae as used by IPCC for the TAR projections, in efficient modular structure, including carbon cycle and atmospheric chemistry, radiative forcing, changes in temperature and sealevel, including some feedbacks. As well as explore the SRES scenarios, the user can create a wide variety of inverse scenarios for stabilising CO2, forcing, or temperature. People ask how local emissions which they can control, may influence the vast global natural and human systems, and change local climate impacts which affect them directly. JCM includes regional emissions and socioeconomic data, and scaled climate impact maps. However to complete this loop in a fast interactive model is a challenge! For transparency and accessibility, pop-up information is provided in ten languages, and documentation ranges from key cross-cutting questions, to them details of the model formulae, including all source code.

Empirical radio propagation model for DTV applied to non-homogeneous paths and different climates using machine learning techniques.

PubMed

Gomes, Igor Ruiz; Gomes, Cristiane Ruiz; Gomes, Herminio Simões; Cavalcante, Gervásio Protásio Dos Santos

2018-01-01

The establishment and improvement of transmission systems rely on models that take into account, (among other factors), the geographical features of the region, as these can lead to signal degradation. This is particularly important in Brazil, where there is a great diversity of scenery and climates. This article proposes an outdoor empirical radio propagation model for Ultra High Frequency (UHF) band, that estimates received power values that can be applied to non-homogeneous paths and different climates, this last being of an innovative character for the UHF band. Different artificial intelligence techniques were chosen on a theoretical and computational basis and made it possible to introduce, organize and describe quantitative and qualitative data quickly and efficiently, and thus determine the received power in a wide range of settings and climates. The proposed model was applied to a city in the Amazon region with heterogeneous paths, wooded urban areas and fractions of freshwater among other factors. Measurement campaigns were conducted to obtain data signals from two digital TV stations in the metropolitan area of the city of Belém, in the State of Pará, to design, compare and validate the model. The results are consistent since the model shows a clear difference between the two seasons of the studied year and small RMS errors in all the cases studied.

Empirical radio propagation model for DTV applied to non-homogeneous paths and different climates using machine learning techniques

PubMed Central

Gomes, Herminio Simões; Cavalcante, Gervásio Protásio dos Santos

2018-01-01

The establishment and improvement of transmission systems rely on models that take into account, (among other factors), the geographical features of the region, as these can lead to signal degradation. This is particularly important in Brazil, where there is a great diversity of scenery and climates. This article proposes an outdoor empirical radio propagation model for Ultra High Frequency (UHF) band, that estimates received power values that can be applied to non-homogeneous paths and different climates, this last being of an innovative character for the UHF band. Different artificial intelligence techniques were chosen on a theoretical and computational basis and made it possible to introduce, organize and describe quantitative and qualitative data quickly and efficiently, and thus determine the received power in a wide range of settings and climates. The proposed model was applied to a city in the Amazon region with heterogeneous paths, wooded urban areas and fractions of freshwater among other factors. Measurement campaigns were conducted to obtain data signals from two digital TV stations in the metropolitan area of the city of Belém, in the State of Pará, to design, compare and validate the model. The results are consistent since the model shows a clear difference between the two seasons of the studied year and small RMS errors in all the cases studied. PMID:29596503

The epistemological status of general circulation models

NASA Astrophysics Data System (ADS)

Loehle, Craig

2018-03-01

Forecasts of both likely anthropogenic effects on climate and consequent effects on nature and society are based on large, complex software tools called general circulation models (GCMs). Forecasts generated by GCMs have been used extensively in policy decisions related to climate change. However, the relation between underlying physical theories and results produced by GCMs is unclear. In the case of GCMs, many discretizations and approximations are made, and simulating Earth system processes is far from simple and currently leads to some results with unknown energy balance implications. Statistical testing of GCM forecasts for degree of agreement with data would facilitate assessment of fitness for use. If model results need to be put on an anomaly basis due to model bias, then both visual and quantitative measures of model fit depend strongly on the reference period used for normalization, making testing problematic. Epistemology is here applied to problems of statistical inference during testing, the relationship between the underlying physics and the models, the epistemic meaning of ensemble statistics, problems of spatial and temporal scale, the existence or not of an unforced null for climate fluctuations, the meaning of existing uncertainty estimates, and other issues. Rigorous reasoning entails carefully quantifying levels of uncertainty.

The Earth Observing System Terra Mission

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Einaudi, Franco (Technical Monitor)

2000-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. After the launch in Dec. 16 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution better than 1 km on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical perspective of the Terra mission and the key new elements of the mission. We expect to have first images that demonstrate the most innovative capability from EOS Terra 5 instruments: MODIS - 1.37 micron cirrus cloud channel; 250m daily coverage for clouds and vegetation change; 7 solar channels for land and aerosol studies; new fire channels; Chlorophyll fluorescence; MISR - first 9 multi angle views of clouds and vegetation; MOPITT - first global CO maps and C114 maps; ASTER - Thermal channels for geological studies with 15-90 m resolution.

The Earth Observing System Terra Mission

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.

2000-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. After the launch in Dec. 16 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution smaller than 1 km on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical perspective of the Terra mission and the key new elements of the mission. We expect to have some first images that demonstrate the most innovative capability from EOS Terra: MODIS - 1.37 microns cirrus channel; 250 m daily cover for clouds and vegetation change; 7 solar channels for land and aerosol; new fire channels; Chlorophyll fluorescence; MISR - 9 multi angle views of clouds and vegetation; MOPITT - Global CO maps and CH4 maps; ASTER - Thermal channels for geological studies with 15-90 m resolution.

Modeling agricultural commodity prices and volatility in response to anticipated climate change

NASA Astrophysics Data System (ADS)

Lobell, D. B.; Tran, N.; Welch, J.; Roberts, M.; Schlenker, W.

2012-12-01

Food prices have shown a positive trend in the past decade, with episodes of rapid increases in 2008 and 2011. These increases pose a threat to food security in many regions of the world, where the poor are generally net consumers of food, and are also thought to increase risks of social and political unrest. The role of global warming in these price reversals have been debated, but little quantitative work has been done. A particular challenge in modeling these effects is that they require understanding links between climate and food supply, as well as between food supply and prices. Here we combine the anticipated effects of climate change on yield levels and volatility with an empirical competitive storage model to examine how expected climate change might affect prices and social welfare in the international food commodity market. We show that price level and volatility do increase over time in response to decreasing yield, and increasing yield variability. Land supply and storage demand both increase, but production and consumption continue to fall leading to a decrease in consumer surplus, and a corresponding though smaller increase in producer surplus.

Large rainfall changes consistently projected over substantial areas of tropical land

NASA Astrophysics Data System (ADS)

Chadwick, Robin; Good, Peter; Martin, Gill; Rowell, David P.

2016-02-01

Many tropical countries are exceptionally vulnerable to changes in rainfall patterns, with floods or droughts often severely affecting human life and health, food and water supplies, ecosystems and infrastructure. There is widespread disagreement among climate model projections of how and where rainfall will change over tropical land at the regional scales relevant to impacts, with different models predicting the position of current tropical wet and dry regions to shift in different ways. Here we show that despite uncertainty in the location of future rainfall shifts, climate models consistently project that large rainfall changes will occur for a considerable proportion of tropical land over the twenty-first century. The area of semi-arid land affected by large changes under a higher emissions scenario is likely to be greater than during even the most extreme regional wet or dry periods of the twentieth century, such as the Sahel drought of the late 1960s to 1990s. Substantial changes are projected to occur by mid-century--earlier than previously expected--and to intensify in line with global temperature rise. Therefore, current climate projections contain quantitative, decision-relevant information on future regional rainfall changes, particularly with regard to climate change mitigation policy.

Performance evaluation of a non-hydrostatic regional climate model over the Mediterranean/Black Sea area and climate projections for the XXI century

NASA Astrophysics Data System (ADS)

Mercogliano, Paola; Bucchignani, Edoardo; Montesarchio, Myriam; Zollo, Alessandra Lucia

2013-04-01

In the framework of the Work Package 4 (Developing integrated tools for environmental assessment) of PERSEUS Project, high resolution climate simulations have been performed, with the aim of furthering knowledge in the field of climate variability at regional scale, its causes and impacts. CMCC is a no profit centre whose aims are the promotion, research coordination and scientific activities in the field of climate changes. In this work, we show results of numerical simulation performed over a very wide area (13W-46E; 29-56N) at spatial resolution of 14 km, which includes the Mediterranean and Black Seas, using the regional climate model COSMO-CLM. It is a non-hydrostatic model for the simulation of atmospheric processes, developed by the DWD-Germany for weather forecast services; successively, the model has been updated by the CLM-Community, in order to develop climatic applications. It is the only documented numerical model system in Europe designed for spatial resolutions down to 1 km with a range of applicability encompassing operational numerical weather prediction, regional climate modelling the dispersion of trace gases and aerosol and idealised studies and applicable in all regions of the world for a wide range of available climate simulations from global climate and NWP models. Different reasons justify the development of a regional model: the first is the increasing number of works in literature asserting that regional models have also the features to provide more detailed description of the climate extremes, that are often more important then their mean values for natural and human systems. The second one is that high resolution modelling shows adequate features to provide information for impact assessment studies. At CMCC, regional climate modelling is a part of an integrated simulation system and it has been used in different European and African projects to provide qualitative and quantitative evaluation of the hydrogeological and public health risks. A simulation covering the period 1971-2000 and driven by ERA40 reanalysis has been performed, in order to assess the capability of the model to reproduce the present climate, with "perfect boundary conditions". A comparison, in terms of 2-metre temperature and precipitation, with EOBS dataset will be shown and discussed, in order to analyze the capabilities in simulating the main features of the observed climate over a wide area, at high spatial resolution. Then, a comparison between the results of COSMO-CLM driven by the global model CMCC-MED (whose atmospheric component is ECHAM5) and by ERA40 will be provided for a characterization of the errors induced by the global model. Finally, climate projections on the examined area for the XXI century, considering the RCP4.5 emission scenario for the future, will be provided. In this work a special emphasis will be issued to the analysis of the capability to reproduce not only the average climate trend but also extremes of the present and future climate, in terms of temperature, precipitation and wind.

Assessment of temperature and precipitation over Mediterranean Area and Black Sea with non hydrostatic high resolution regional climate model

NASA Astrophysics Data System (ADS)

Mercogliano, P.; Montesarchio, M.; Zollo, A.; Bucchignani, E.

2012-12-01

In the framework of the Italian GEMINA Project (program of expansion and development of the Euro-Mediterranean Center for Climate Change (CMCC), high resolution climate simulations have been performed, with the aim of furthering knowledge in the field of climate variability at regional scale, its causes and impacts. CMCC is a no profit centre whose aims are the promotion, research coordination and scientific activities in the field of climate changes. In this work, we show results of numerical simulation performed over a very wide area (13W-46E; 29-56N) at spatial resolution of 14 km, which includes all the Mediterranean Sea, using the regional climate model COSMO-CLM. It is a non-hydrostatic model for the simulation of atmospheric processes, developed by the DWD-Germany for weather forecast services; successively, the model has been updated by the CLM-Community, in order to develop climatic applications. It is the only documented numerical model system in Europe designed for spatial resolutions down to 1 km with a range of applicability encompassing operational numerical weather prediction, regional climate modelling the dispersion of trace gases and aerosol and idealised studies and applicable in all regions of the world for a wide range of available climate simulations from global climate and NWP models. Different reasons justify the development of a regional model: the first is the increasing number of works in literature asserting that regional models have also the features to provide more detailed description of the climate extremes, that are often more important then their mean values for natural and human systems. The second one is that high resolution modelling shows adequate features to provide information for impact assessment studies. At CMCC, regional climate modelling is a part of an integrated simulation system and it has been used in different European and African projects to provide qualitative and quantitative evaluation of the hydrogeological and public health risks. A simulation covering the period 1971-2000 and driven by ERA40 reanalysis has been performed, in order to assess the capability of the model to reproduce the present climate, with "perfect boundary conditions". A comparison, in terms of 2-metre temperature and precipitation, with EOBS dataset will be shown and discussed, in order to analyze the capabilities in simulating the main features of the observed climate over a wide area, at high spatial resolution. Then, a comparison between the results of COSMO-CLM driven by the global model CMCC-MED (whose atmospheric component is ECHAM5) and by ERA40 will be provided for a characterization of the errors induced by the global model. Finally, climate projections on the examined area for the XXI century, considering the RCP4.5 emission scenario for the future, will be provided. In this work a special emphasis will be issued to the analysis of the capability to reproduce not only the average climate patterns but also extremes of the present and future climate, in terms of temperature, precipitation and wind.

Quantifying climatic variability in monsoonal northern China over the last 2200 years and its role in driving Chinese dynastic changes

NASA Astrophysics Data System (ADS)

Li, Jianyong; Dodson, John; Yan, Hong; Zhang, David D.; Zhang, Xiaojian; Xu, Qinghai; Lee, Harry F.; Pei, Qing; Cheng, Bo; Li, Chunhai; Ni, Jian; Sun, Aizhi; Lu, Fengyan; Zong, Yongqiang

2017-03-01

Our understanding on the spatial-temporal patterns of climatic variability over the last few millennia in the East Asian monsoon-dominated northern China (NC), and its role at a macro-scale in affecting the prosperity and depression of Chinese dynasties is limited. Quantitative high-resolution, regionally-synthesized palaeoclimatic reconstructions as well as simulations, and numerical analyses of their relationships with various fine-scale, numerical agro-ecological, social-economic, and geo-political historical records during the period of China's history, are presented here for NC. We utilize pollen data together with climate modeling to reconstruct and simulate decadal- to centennial-scale variations in precipitation or temperature for NC during the last 2200 years (-200-2000 AD). We find an overall cyclic-pattern (wet/warm or dry/cold) in the precipitation and temperature anomalies on centennial- to millennial-scale that can be likely considered as a representative for the entire NC by comparison with other related climatic records. We suggest that solar activity may play a key role in driving the climatic fluctuations in NC during the last 22 centuries, with its quasi ∼100, 50, 23, or 22-year periodicity clearly identified in our climatic reconstructions. We employ variation partitioning and redundancy analysis to quantify the independent effects of climatic factors on accounting for the total variation of 17 fine-grained numerical Chinese historical records. We quantitatively illustrate that precipitation (67.4%) may have been more important than temperature (32.5%) in causing the overall agro-ecological and macro-geopolitical shifts in imperial China with NC as the central ruling region and an agricultural heartland over the last 2200 years.

The effects of climate change on the demand for municipal water for residential landscaping in Southern Nevada

NASA Astrophysics Data System (ADS)

Tchigriaeva, E.; Lott, C.; Rollins, K.

2013-12-01

We analyze urban residential water demand for Southern Nevada as a part of the Nevada Infrastructure for Climate Change Science, Education, and Outreach project. The Nevada Climate Change project is a statewide interdisciplinary program which has launched joint research, education, and outreach on the effects of regional climate change on ecosystem services in Nevada with a particular focus on water resources. We estimate a random effect multiple regression model of urban residential water demand in order to better understand how residential water use is impacted by weather conditions and landscape characteristics and ultimately to inform predictions of urban water demand. The project develops a methodology of unification for several datasets from various sources including the Las Vegas Valley Water District (LVVWD), the Southern Nevada Water Authority (SNWA), Clark County Assessor, and the National Climatic Data Center (NCDC) resulting in a sample of 3,671,983 observations for 62,237 households with uninterrupted water use history for Las Vegas urban residents for the period from February 2007 to December 2011. The presented results (i) are significantly robust and in accordance with the economics theories, (ii) support basic empirical knowledge of weather and surface influence on water outdoor consumption, (iii) suggest quantitative measurements for predicting future water use due to climate/temperature changes as well as landscape redesign practices, and (iv) provide quantitative evaluation of the effectiveness of the existing water conservation programs by the Southern Nevada Water Authority (SNWA). The further study of conservation programs and analysis of interactions between surfaces and weather using the developed approach looks promising.

Species-free species distribution models describe macroecological properties of protected area networks.

PubMed

Robinson, Jason L; Fordyce, James A

2017-01-01

Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or "footprint") of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or have narrow geographic distributions, and are thus prone to future shifts away from the climatic conditions in these parks in current climates. In other cases, some parks are broadly similar to large geographic regions surrounding the park or have climatic envelopes that may persist into near-term climate change. Larger parks predict larger climatic envelopes, in current conditions, but on average the predicted area of climate envelopes are smaller in our single future conditions scenario. Individual units in a protected area network may vary in the potential for climate adaptation, and adaptive management strategies for the network should account for the landscape contexts of the geodiversity or climate diversity within individual units. Conservation strategies, including maintaining connectivity, assessing the feasibility of assisted migration and other landscape restoration or enhancements can be optimized using analysis methods to assess the spatial properties of protected area networks in biogeographic and macroecological contexts.

Modelled vs. reconstructed past fire dynamics - how can we compare?

NASA Astrophysics Data System (ADS)

Brücher, Tim; Brovkin, Victor; Kloster, Silvia; Marlon, Jennifer R.; Power, Mitch J.

2015-04-01

Fire is an important process that affects climate through changes in CO2 emissions, albedo, and aerosols (Ward et al. 2012). Fire-history reconstructions from charcoal accumulations in sediment indicate that biomass burning has increased since the Last Glacial Maximum (Power et al. 2008; Marlon et al. 2013). Recent comparisons with transient climate model output suggest that this increase in global ?re activity is linked primarily to variations in temperature and secondarily to variations in precipitation (Daniau et al. 2012). In this study, we discuss the best way to compare global ?re model output with charcoal records. Fire models generate quantitative output for burned area and fire-related emissions of CO2, whereas charcoal data indicate relative changes in biomass burning for specific regions and time periods only. However, models can be used to relate trends in charcoal data to trends in quantitative changes in burned area or fire carbon emissions. Charcoal records are often reported as Z-scores (Power et al. 2008). Since Z-scores are non-linear power transformations of charcoal influxes, we must evaluate if, for example, a two-fold increase in the standardized charcoal reconstruction corresponds to a 2- or 200-fold increase in the area burned. In our study we apply the Z-score metric to the model output. This allows us to test how well the model can quantitatively reproduce the charcoal-based reconstructions and how Z-score metrics affect the statistics of model output. The Global Charcoal Database (GCD version 2.5; www.gpwg.org/gpwgdb.html) is used to determine regional and global paleofire trends from 218 sedimentary charcoal records covering part or all of the last 8 ka BP. To retrieve regional and global composites of changes in fire activity over the Holocene the time series of Z-scores are linearly averaged to achieve regional composites. A coupled climate-carbon cycle model, CLIMBA (Brücher et al. 2014), is used for this study. It consists of the CLIMBER-2 Earth system model of intermediate complexity and the JSBACH land component of the Max Planck Institute Earth System Model. The fire algorithm in JSBACH assumes a constant annual lightning cycle as the sole fire ignition mechanism (Arora and Boer 2005). To eliminate data processing differences as a source for potential discrepancies, the processing of both reconstructed and modeled data, including e.g. normalisation with respect to a given base period and aggregation of time series was done in exactly the same way. Here, we compare the aggregated time series on a hemispheric and regional scale.

Biogenic organic emissions, air quality and climate

NASA Astrophysics Data System (ADS)

Guenther, A. B.

2015-12-01

Living organisms produce copious amounts of a diverse array of metabolites including many volatile organic compounds that are released into the atmosphere. These compounds participate in numerous chemical reactions that influence the atmospheric abundance of important air pollutants and short-lived climate forcers including organic aerosol, ozone and methane. The production and release of these organics are strongly influenced by environmental conditions including air pollution, temperature, solar radiation, and water availability and they are highly sensitive to stress and extreme events. As a result, releases of biogenic organics to the atmosphere have an impact on, and are sensitive to, air quality and climate leading to potential feedback couplings. Their role in linking air quality and climate is conceptually clear but an accurate quantitative representation is needed for predictive models. Progress towards this goal will be presented including numerical model development and assessments of the predictive capability of the Model of Emission of Gases and Aerosols from Nature (MEGAN). Recent studies of processes controlling the magnitude and variations in biogenic organic emissions will be described and observations of their impact on atmospheric composition will be shown. Recent advances and priorities for future research will be discussed including laboratory process studies, long-term measurements, multi-scale regional studies, global satellite observations, and the development of a next generation model for simulating land-atmosphere chemical exchange.

Adapting to rates versus amounts of climate change: a case of adaptation to sea-level rise

NASA Astrophysics Data System (ADS)

Shayegh, Soheil; Moreno-Cruz, Juan; Caldeira, Ken

2016-10-01

Adaptation is the process of adjusting to climate change in order to moderate harm or exploit beneficial opportunities associated with it. Most adaptation strategies are designed to adjust to a new climate state. However, despite our best efforts to curtail greenhouse gas emissions, climate is likely to continue changing far into the future. Here, we show how considering rates of change affects the projected optimal adaptation strategy. We ground our discussion with an example of optimal investment in the face of continued sea-level rise, presenting a quantitative model that illustrates the interplay among physical and economic factors governing coastal development decisions such as rate of sea-level rise, land slope, discount rate, and depreciation rate. This model shows that the determination of optimal investment strategies depends on taking into account future rates of sea-level rise, as well as social and political constraints. This general approach also applies to the development of improved strategies to adapt to ongoing trends in temperature, precipitation, and other climate variables. Adaptation to some amount of change instead of adaptation to ongoing rates of change may produce inaccurate estimates of damages to the social systems and their ability to respond to external pressures.

A Decision Analysis Tool for Climate Impacts, Adaptations, and Vulnerabilities

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

Omitaomu, Olufemi A; Parish, Esther S; Nugent, Philip J

Climate change related extreme events (such as flooding, storms, and drought) are already impacting millions of people globally at a cost of billions of dollars annually. Hence, there are urgent needs for urban areas to develop adaptation strategies that will alleviate the impacts of these extreme events. However, lack of appropriate decision support tools that match local applications is limiting local planning efforts. In this paper, we present a quantitative analysis and optimization system with customized decision support modules built on geographic information system (GIS) platform to bridge this gap. This platform is called Urban Climate Adaptation Tool (Urban-CAT). Formore » all Urban-CAT models, we divide a city into a grid with tens of thousands of cells; then compute a list of metrics for each cell from the GIS data. These metrics are used as independent variables to predict climate impacts, compute vulnerability score, and evaluate adaptation options. Overall, the Urban-CAT system has three layers: data layer (that contains spatial data, socio-economic and environmental data, and analytic data), middle layer (that handles data processing, model management, and GIS operation), and application layer (that provides climate impacts forecast, adaptation optimization, and site evaluation). The Urban-CAT platform can guide city and county governments in identifying and planning for effective climate change adaptation strategies.« less

Exploring climate change vulnerability across sectors and scenarios using indicators of impacts and coping capacity.

PubMed

Dunford, R; Harrison, P A; Jäger, J; Rounsevell, M D A; Tinch, R

Addressing climate change vulnerability requires an understanding of both the level of climate impacts and the capacity of the exposed population to cope. This study developed a methodology for allowing users to explore vulnerability to changes in ecosystem services as a result of climatic and socio-economic changes. It focuses on the vulnerability of Europe across multiple sectors by combining the outputs of a regional integrated assessment (IA) model, the CLIMSAVE IA Platform, with maps of coping capacity based on the five capitals approach. The presented methodology enables stakeholder-derived socio-economic futures to be represented within a quantitative integrated modelling framework in a way that changes spatially and temporally with the socio-economic storyline. Vulnerability was mapped for six key ecosystem services in 40 combined climate and socio-economic scenarios. The analysis shows that, whilst the north and west of Europe are generally better placed to cope with climate impacts than the south and east, coping could be improved in all areas. Furthermore, whilst the lack of coping capacity in dystopian scenarios often leads to greater vulnerability, there are complex interactions between sectors that lead to patterns of vulnerability that vary spatially, with scenario and by sector even within the more utopian futures.

Epidemics in Ming and Qing China: Impacts of changes of climate and economic well-being.

PubMed

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

2015-07-01

We investigated the mechanism of epidemics with the impacts of climate change and socio-economic fluctuations in the Ming and Qing Dynasties in China (AD 1368-1901). Using long-term and high-quality datasets, this study is the first quantitative research that verifies the 'climate change → economy → epidemics' mechanism in historical China by statistical methods that include correlation analysis, Granger causality analysis, ARX, and Poisson-ARX modeling. The analysis provides the evidences that climate change could only fundamentally lead to the epidemics spread and occurrence, but the depressed economic well-being is the direct trigger of epidemics spread and occurrence at the national and long term scale in historical China. Moreover, statistical modeling shows that economic well-being is more important than population pressure in the mechanism of epidemics. However, population pressure remains a key element in determining the social vulnerability of the epidemics occurrence under climate change. Notably, the findings not only support adaptation theories but also enhance our confidence to address climatic shocks if economic buffering capacity can be promoted steadily. The findings can be a basis for scientists and policymakers in addressing global and regional environmental changes. Copyright © 2015 Elsevier Ltd. All rights reserved.

A new space-time characterization of Northern Hemisphere drought in model simulations of the past and future as compared to the paleoclimate record

NASA Astrophysics Data System (ADS)

Coats, S.; Smerdon, J. E.; Stevenson, S.; Fasullo, J.; Otto-Bliesner, B. L.

2017-12-01

The observational record, which provides only limited sampling of past climate variability, has made it difficult to quantitatively analyze the complex spatio-temporal character of drought. To provide a more complete characterization of drought, machine learning based methods that identify drought in three-dimensional space-time are applied to climate model simulations of the last millennium and future, as well as tree-ring based reconstructions of hydroclimate over the Northern Hemisphere extratropics. A focus is given to the most persistent and severe droughts of the past 1000 years. Analyzing reconstructions and simulations in this context allows for a validation of the spatio-temporal character of persistent and severe drought in climate model simulations. Furthermore, the long records provided by the reconstructions and simulations, allows for sufficient sampling to constrain projected changes to the spatio-temporal character of these features using the reconstructions. Along these lines, climate models suggest that there will be large increases in the persistence and severity of droughts over the coming century, but little change in their spatial extent. These models, however, exhibit biases in the spatio-temporal character of persistent and severe drought over parts of the Northern Hemisphere, which may undermine their usefulness for future projections. Despite these limitations, and in contrast to previous claims, there are no systematic changes in the character of persistent and severe droughts in simulations of the historical interval. This suggests that climate models are not systematically overestimating the hydroclimate response to anthropogenic forcing over this period, with critical implications for confidence in hydroclimate projections.

The challenge of identifying greenhouse gas-induced climatic change

NASA Technical Reports Server (NTRS)

Maccracken, Michael C.

1992-01-01

Meeting the challenge of identifying greenhouse gas-induced climatic change involves three steps. First, observations of critical variables must be assembled, evaluated, and analyzed to determine that there has been a statistically significant change. Second, reliable theoretical (model) calculations must be conducted to provide a definitive set of changes for which to search. Third, a quantitative and statistically significant association must be made between the projected and observed changes to exclude the possibility that the changes are due to natural variability or other factors. This paper provides a qualitative overview of scientific progress in successfully fulfilling these three steps.

Land use allocation model considering climate change impact

NASA Astrophysics Data System (ADS)

Lee, D. K.; Yoon, E. J.; Song, Y. I.

2017-12-01

In Korea, climate change adaptation plans are being developed for each administrative district based on impact assessments constructed in various fields. This climate change impact assessments are superimposed on the actual space, which causes problems in land use allocation because the spatial distribution of individual impacts may be different each other. This implies that trade-offs between climate change impacts can occur depending on the composition of land use. Moreover, the actual space is complexly intertwined with various factors such as required area, legal regulations, and socioeconomic values, so land use allocation in consideration of climate change can be very difficult problem to solve (Liu et al. 2012; Porta et al. 2013).Optimization techniques can generate a sufficiently good alternatives for land use allocation at the strategic level if only the fitness function of relationship between impact and land use composition are derived. It has also been noted that land use optimization model is more effective than the scenario-based prediction model in achieving the objectives for problem solving (Zhang et al. 2014). Therefore in this study, we developed a quantitative tool, MOGA (Multi Objective Genetic Algorithm), which can generate a comprehensive land use allocations considering various climate change impacts, and apply it to the Gangwon-do in Korea. Genetic Algorithms (GAs) are the most popular optimization technique to address multi-objective in land use allocation. Also, it allows for immediate feedback to stake holders because it can run a number of experiments with different parameter values. And it is expected that land use decision makers and planners can formulate a detailed spatial plan or perform additional analysis based on the result of optimization model. Acknowledgments: This work was supported by the Korea Ministry of Environment (MOE) as "Climate Change Correspondence Program (Project number: 2014001310006)"

Early Mars Climate Revisited With a Global Probability Map of Martian Valley Network Origin and Distribution

NASA Astrophysics Data System (ADS)

Grau Galofre, A.; Jellinek, M.; Osinski, G. R.

2016-12-01

Valley networks are among the most arresting features on the surface of Mars. Their provocative morphologic resemblance to river valleys on Earth has lead many scientists to argue for Martian river valleys in a "warm and wet" climate scenario, with conditions similar to the terrestrial mid-to-low latitudes. However, this warm scenario is difficult to reconcile with climate models for an Early Mars receiving radiation from a fainter young Sun. Moreover, recent models suggest a colder scenario, with conditions more similar to present day Greenland or Antarctica. Here we use three independent characterization schemes to show quantitative evidence for fluvial, glacial, groundwater sapping and subglacial meltwater channels to build the first global probability map of Martian valley networks. We distinguish a SW-NE corridor of fluvial drainage networks spanning latitudes from 30ºS to 30ºN. We identify additional widespread patterns related to glaciation, subglacial drainage and channels incised by groundwater springs. This global characterization of Martian valleys has profound implications for the average climate of early Mars as well as its variability in space and time.

Water management in the Roman world

NASA Astrophysics Data System (ADS)

Dermody, Brian J.; van Beek, Rens L. P. H.; Meeks, Elijah; Klein Goldewijk, Kees; Bierkens, Marc F. P.; Scheidel, Walter; Wassen, Martin J.; van der Velde, Ype; Dekker, Stefan C.

2014-05-01

Climate variability can have extreme impacts on societies in regions that are water-limited for agriculture. A society's ability to manage its water resources in such environments is critical to its long-term viability. Water management can involve improving agricultural yields through in-situ irrigation or redistributing water resources through trade in food. Here, we explore how such water management strategies affected the resilience of the Roman Empire to climate variability in the water-limited region of the Mediterranean. Using the large-scale hydrological model PCR-GLOBWB and estimates of landcover based on the Historical Database of the Global Environment (HYDE) we generate potential agricultural yield maps under variable climate. HYDE maps of population density in conjunction with potential yield estimates are used to develop maps of agricultural surplus and deficit. The surplus and deficit regions are abstracted to nodes on a water redistribution network based on the Stanford Geospatial Network Model of the Roman World (ORBIS). This demand-driven, water redistribution network allows us to quantitatively explore how water management strategies such as irrigation and food trade improved the resilience of the Roman Empire to climate variability.

Model-based evidence for persistent species zonation shifts in the southern Rocky Mountains under a warming climate

NASA Astrophysics Data System (ADS)

Foster, A.; Shuman, J. K.; Shugart, H. H., Jr.; Dwire, K. A.; Fornwalt, P.; Sibold, J.; Negrón, J. F.

2016-12-01

Forests in the Rocky Mountains are a crucial part of the North American carbon budget, but increases in disturbances such as insect outbreaks and fire, in conjunction with climate change, threaten their vitality. Mean annual temperatures in the western United States have increased by 2°C since 1950 and the higher elevations are warming faster than the rest of the landscape. It is predicted that this warming trend will continue, and that by the end of this century, nearly 50% of the western US landscape will have climate profiles with no current analog within that region. Individual tree-based modeling allows various climate change scenarios and their effects on forest dynamics to be tested. We use an updated individual-based gap model, the University of Virginia Forest Model Enhanced (UVAFME) at a subalpine site in the southern Rocky Mountains. UVAFME has been quantitatively and qualitatively validated in the southern Rocky Mountains, and results show that UVAFME-output on size structure, biomass, and species composition compares reasonably to inventory data and descriptions of vegetation zonation and successional dynamics for the region. We perform a climate sensitivity test in which temperature is first increased linearly by 2°C over 100 years, stabilized for 200 years, cooled back to present climate values over 100 years, and again stabilized for 200 years. This test is conducted to determine what effect elevated temperatures may have on vegetation zonation, and how persistent the changes may be if the climate is brought back to its current state. Results show that elevated temperatures within the southern Rocky Mountains may lead to decreases in biomass and changes in species composition as species migrate upslope. These changes are also likely to be fairly persistent for at least one- to two-hundred years. The results from this study suggest that UVAFME and other individual-based gap models can be used to inform forest management and climate mitigation strategies for this vitally important region.

Intercomparison of different uncertainty sources in hydrological climate change projections for an alpine catchment (upper Clutha River, New Zealand)

NASA Astrophysics Data System (ADS)

Jobst, Andreas M.; Kingston, Daniel G.; Cullen, Nicolas J.; Schmid, Josef

2018-06-01

As climate change is projected to alter both temperature and precipitation, snow-controlled mid-latitude catchments are expected to experience substantial shifts in their seasonal regime, which will have direct implications for water management. In order to provide authoritative projections of climate change impacts, the uncertainty inherent to all components of the modelling chain needs to be accounted for. This study assesses the uncertainty in potential impacts of climate change on the hydro-climate of a headwater sub-catchment of New Zealand's largest catchment (the Clutha River) using a fully distributed hydrological model (WaSiM) and unique ensemble encompassing different uncertainty sources: general circulation model (GCM), emission scenario, bias correction and snow model. The inclusion of snow models is particularly important, given that (1) they are a rarely considered aspect of uncertainty in hydrological modelling studies, and (2) snow has a considerable influence on seasonal patterns of river flow in alpine catchments such as the Clutha. Projected changes in river flow for the 2050s and 2090s encompass substantial increases in streamflow from May to October, and a decline between December and March. The dominant drivers are changes in the seasonal distribution of precipitation (for the 2090s +29 to +84 % in winter) and substantial decreases in the seasonal snow storage due to temperature increase. A quantitative comparison of uncertainty identified GCM structure as the dominant contributor in the seasonal streamflow signal (44-57 %) followed by emission scenario (16-49 %), bias correction (4-22 %) and snow model (3-10 %). While these findings suggest that the role of the snow model is comparatively small, its contribution to the overall uncertainty was still found to be noticeable for winter and summer.

Koppen bioclimatic evaluation of CMIP historical climate simulations

DOE PAGES

Phillips, Thomas J.; Bonfils, Celine J. W.

2015-06-05

Köppen bioclimatic classification relates generic vegetation types to characteristics of the interactive annual-cycles of continental temperature (T) and precipitation (P). In addition to predicting possible bioclimatic consequences of past or prospective climate change, a Köppen scheme can be used to pinpoint biases in model simulations of historical T and P. In this study a Köppen evaluation of Coupled Model Intercomparison Project (CMIP) simulations of historical climate is conducted for the period 1980–1999. Evaluation of an example CMIP5 model illustrates how errors in simulating Köppen vegetation types (relative to those derived from observational reference data) can be deconstructed and related tomore » model-specific temperature and precipitation biases. Measures of CMIP model skill in simulating the reference Köppen vegetation types are also developed, allowing the bioclimatic performance of a CMIP5 simulation of T and P to be compared quantitatively with its CMIP3 antecedent. Although certain bioclimatic discrepancies persist across model generations, the CMIP5 models collectively display an improved rendering of historical T and P relative to their CMIP3 counterparts. Additionally, the Köppen-based performance metrics are found to be quite insensitive to alternative choices of observational reference data or to differences in model horizontal resolution.« less

Validation and Refinement of a Lunar Irradiance Model for Suomi NPP VIIRS Day-Night Band Quantitative Nighttime Applications

NASA Astrophysics Data System (ADS)

Miller, S. D.; Combs, C.; Wagner, S.; Viticchiè, B.; Walther, A.; Solbrig, J.

2014-12-01

The VIIRS Day-Night Band provides the first calibrated observations of nocturnal low-light visible/near-infrared (~500-900 nm response, 710 nm central wavelength) radiances, including reflected moonlight down to values of 3 × 10-5 W·m-2·sr-1. These novel measurements afford the first opportunity to attempt nighttime retrievals of optical depth for optically thick clouds when moonlight is available, thereby advancing our ability to observe the diurnal cycle of such structures as marine stratocumuli which are thought to play an important role in determining climate and climate feedbacks. In order to leverage the Day-Night Band measurements in this capacity, we must first convert the upwelling top-of-atmosphere radiances to equivalent values of reflectance. Doing so requires a detailed knowledge of the down-welling top-of-atmosphere lunar spectral irradiance which, unlike sunlight, varies significantly over the course of the ~29.5 day lunar cycle. This research summarizes the ongoing development, validation, and refinement of a lunar irradiance model designed to convert Day-Night Band radiances to equivalent lunar reflectance. Comparisons between daytime and nighttime Day-Night Band reflectance for vicarious calibration targets offering radiometric stability (e.g., White Sands, Salar de Uyuni, Dome-C, and snow fields) confirms the model's performance to within an expected ~10% uncertainty. An observed lunar-phase-dependent trend associated with the model's assumption of a disk-averaged albedo was addressed via analysis of a version of the model adapted for comparison against Meteosat Second Generation SEVIRI lunar measurements. The analysis resulted in a phase-dependent 6th order polynomial correction to the model and expected model uncertainty improvements to within ~5%. Examples of lunar reflectance imagery for operational applications and the provisional quantitative application of Day-Night Band lunar reflectance to nighttime cloud optical property retrievals, bearing relevance to the diurnally resolved global climate data record, are shown.

Analysis on the adaptive countermeasures to ecological management under changing environment in the Tarim River Basin, China

NASA Astrophysics Data System (ADS)

Yang, Fan; Xue, Lianqing; Zhang, Luochen; Chen, Xinfang; Chi, Yixia

2017-12-01

This article aims to explore the adaptive utilization strategies of flow regime versus traditional practices in the context of climate change and human activities in the arid area. The study presents quantitative analysis of climatic and anthropogenic factors to streamflow alteration in the Tarim River Basin (TRB) using the Budyko method and adaptive utilization strategies to eco-hydrological regime by comparing the applicability between autoregressive moving average model (ARMA) model and combined regression model. Our results suggest that human activities played a dominant role in streamflow deduction in the mainstream with contribution of 120.7%~190.1%. While in the headstreams, climatic variables were the primary determinant of streamflow by 56.5~152.6% of the increase. The comparison revealed that combined regression model performed better than ARMA model with the qualified rate of 80.49~90.24%. Based on the forecasts of streamflow for different purposes, the adaptive utilization scheme of water flow is established from the perspective of time and space. Our study presents an effective water resources scheduling scheme for the ecological environment and provides references for ecological protection and water allocation in the arid area.

Quantitative use of Palaeo-Proxy Data in Global Circulation Models

NASA Astrophysics Data System (ADS)

Collins, M.

2003-04-01

It is arguably one of the ultimate aims of palaeo-modelling science to somehow "get the palaeo-proxy data into the model" i.e. to constrain the climate of the model the trajectory of the real climate recorded in the palaeo data. The traditional way of interfacing data with models is to use data assimilation. This presents a number of problems in the palaeo context as the data are more often representative of seasonal to annual or decadal climate and models have time steps of order minutes, hence the model increments are likely to be vanishingly small. Also, variational data assimilation schemes would require the adjoint of the coupled ocean-atmosphere model and the adjoint of the functions which translate model variables such as temperature and precipitation into the palaeo-proxies, both of which are hard to determine because of the high degree of non-linearity in the system and the wide range of space and time scales. An alternative is to add forward models of proxies to the model and run "many years" of simulation until an analog state is found which matches the palaeo data for each season, year, decade etc. Clearly "many years" might range from a few thousand years to almost infinity and depends on the number of degrees of freedom in the climate system and on the error characteristics of the palaeo data. The length of simulation required is probably beyond the supercomputer capacity of a single institution and hence an alternative is to use idle capacity of home and business personal computers - the climateprediction.net project.

Modeling aquifer behaviour under climate change and high consumption: Case study of the Sfax region, southeast Tunisia

NASA Astrophysics Data System (ADS)

Boughariou, Emna; Allouche, Nabila; Jmal, Ikram; Mokadem, Naziha; Ayed, Bachaer; Hajji, Soumaya; Khanfir, Hafedh; Bouri, Salem

2018-05-01

The water resources are exhausted by the increasing demand related to the population growth. They are also affected by climate circumstances, especially in arid and semi-arid regions. These areas are already undergoing noticeable shortages and low annual precipitation rate. This paper presents a numerical model of the Sfax shallow aquifer system that was developed by coupling the geographical information system tool ArcGIS 9.3 and ground water modeling system GMS6.5's interface, ground water flow modeling MODFLOW 2000. Being in coastal city and having an arid climate with high consumption rates, this aquifer is undergoing a hydraulic stress situation. Therefore, the groundwater piezometric variations were calibrated for the period 2003-2013 and simulated based on two scenarios; first the constant and growing consumption and second the rainfall forecast as a result of climate change scenario released by the Tunisian Ministry of Agriculture and Water Resources and the German International Cooperation Agency "GIZ" using HadCM3 as a general circulation model. The piezometric simulations globally forecast a decrease that is about 0.5 m in 2020 and 1 m in 2050 locally the decrease is more pronounced in "Chaffar" and "Djbeniana" regions and that is more evident for the increasing consumption scenario. The two scenarios announce a quantitative degradation of the groundwater by the year 2050 with an alarming marine intrusion in "Djbeniana" region.

Local indicators of climate change: The potential contribution of local knowledge to climate research

PubMed Central

Reyes-García, Victoria; Fernández-Llamazares, Álvaro; Guèze, Maximilien; Garcés, Ariadna; Mallo, Miguel; Vila-Gómez, Margarita; Vilaseca, Marina

2016-01-01

Local knowledge has been proposed as a place-based tool to ground-truth climate models and to narrow their geographic sensitivity. To assess the potential role of local knowledge in our quest to understand better climate change and its impacts, we first need to critically review the strengths and weaknesses of local knowledge of climate change and the potential complementarity with scientific knowledge. With this aim, we conducted a systematic, quantitative meta-analysis of published peer-reviewed documents reporting local indicators of climate change (including both local observations of climate change and observed impacts on the biophysical and the social systems). Overall, primary data on the topic are not abundant, the methodological development is incipient, and the geographical extent is unbalanced. On the 98 case studies documented, we recorded the mention of 746 local indicators of climate change, mostly corresponding to local observations of climate change (40%), but also to observed impacts on the physical (23%), the biological (19%), and the socioeconomic (18%) systems. Our results suggest that, even if local observations of climate change are the most frequently reported type of change, the rich and fine-grained knowledge in relation to impacts on biophysical systems could provide more original contributions to our understanding of climate change at local scale. PMID:27642368

Maximum warming occurs about one decade after carbon dioxide emission

NASA Astrophysics Data System (ADS)

Ricke, K.; Caldeira, K.

2014-12-01

There has been a long tradition of estimating the amount of climate change that would result from various carbon dioxide emission or concentration scenarios but there has been relatively little quantitative analysis of how long it takes to feel the consequences of an individual carbon dioxide emission. Using conjoined results of recent carbon-cycle and physical-climate model intercomparison projects, we find the median time between an emission and maximum warming is 10.1 years, with a 90% probability range of 6.6 to 30.7 years. We evaluate uncertainties in timing and amount of warming, partitioning them into three contributing factors: carbon cycle, climate sensitivity and ocean thermal inertia. To characterize the carbon cycle uncertainty associated with the global temperature response to a carbon dioxide emission today, we use fits to the time series of carbon dioxide concentrations from a CO2-impulse response function model intercomparison project's 15 ensemble members (1). To characterize both the uncertainty in climate sensitivity and in the thermal inertia of the climate system, we use fits to the time series of global temperature change from the Coupled Model Intercomparison Project phase 5 (CMIP5; 2) abrupt4xco2 experiment's 20 ensemble's members separating the effects of each uncertainty factors using one of two simple physical models for each CMIP5 climate model. This yields 6,000 possible combinations of these three factors using a standard convolution integral approach. Our results indicate that benefits of avoided climate damage from avoided CO2 emissions will be manifested within the lifetimes of people who acted to avoid that emission. While the relevant time lags imposed by the climate system are substantially shorter than a human lifetime, they are substantially longer than the typical political election cycle, making the delay and its associated uncertainties both economically and politically significant. References: 1. Joos F et al. (2013) Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis. Atmos Chem Phys 13:2793-2825. 2. Taylor KE, Stouffer RJ, Meehl GA (2011) An Overview of CMIP5 and the Experiment Design. Bull Am Meteorol Soc 93:485-498.

Water isotope systematics: Improving our palaeoclimate interpretations

USGS Publications Warehouse

Jones, M. D.; Dee, S.; Anderson, L.; Baker, A.; Bowen, G.; Noone, D.

2016-01-01

The stable isotopes of oxygen and hydrogen, measured in a variety of archives, are widely used proxies in Quaternary Science. Understanding the processes that control δ18O change have long been a focus of research (e.g. Shackleton and Opdyke, 1973; Talbot, 1990 ; Leng, 2006). Both the dynamics of water isotope cycling and the appropriate interpretation of geological water-isotope proxy time series remain subjects of active research and debate. It is clear that achieving a complete understanding of the isotope systematics for any given archive type, and ideally each individual archive, is vital if these palaeo-data are to be used to their full potential, including comparison with climate model experiments of the past. Combining information from modern monitoring and process studies, climate models, and proxy data is crucial for improving our statistical constraints on reconstructions of past climate variability.As climate models increasingly incorporate stable water isotope physics, this common language should aid quantitative comparisons between proxy data and climate model output. Water-isotope palaeoclimate data provide crucial metrics for validating GCMs, whereas GCMs provide a tool for exploring the climate variability dominating signals in the proxy data. Several of the studies in this set of papers highlight how collaborations between palaeoclimate experimentalists and modelers may serve to expand the usefulness of palaeoclimate data for climate prediction in future work.This collection of papers follows the session on Water Isotope Systematics held at the 2013 AGU Fall Meeting in San Francisco. Papers in that session, the breadth of which are represented here, discussed such issues as; understanding sub-GNIP scale (Global Network for Isotopes in Precipitation, (IAEA/WMO, 2006)) variability in isotopes in precipitation from different regions, detailed examination of the transfer of isotope signals from precipitation to geological archives, and the implications of advances in understanding in these areas for the interpretation of palaeo records and proxy data – climate model comparison.Here, we briefly review these areas of research, and discuss challenges for the water isotope community in improving our ability to partition climate vs. auxiliary signals in palaeoclimate data.

The American Climate Prospectus: a risk-centered analysis of the economic impacts of climate change

NASA Astrophysics Data System (ADS)

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

2014-12-01

The American Climate Prospectus (ACP), the analysis underlying the Risky Business project, quantitatively assessed the climate risks posed to the United States' economy in six sectors - crop yields, energy demand, coastal property, crime, labor productivity, and mortality [1]. The ACP is unique in its characterization of the full probability distribution of economic impacts of climate change throughout the 21st century, making it an extremely useful basis for risk assessments. Three key innovations allow for this characterization. First, climate projections from CMIP5 models are scaled to a temperature probability distribution derived from a coarser climate model (MAGICC). This allows a more accurate representation of the whole distribution of future climates (in particular the tails) than a simple ensemble average. These are downscaled both temporally and spatially. Second, a set of local sea level rise and tropical cyclone projections are used in conjunction with the most detailed dataset of coastal property in the US in order to capture the risks of rising seas and storm surge. Third, we base many of our sectors on empirically-derived responses to temperature and precipitation. Each of these dose-response functions is resampled many times to populate a statistical distribution. Combining these with uncertainty in emissions scenario, climate model, and weather, we create the full probability distribution of climate impacts from county up to national levels, as well as model the effects upon the economy as a whole. Results are presented as likelihood ranges, as well as changes to return intervals of extreme events. The ACP analysis allows us to compare between sectors to understand the magnitude of required policy responses, and also to identify risks through time. Many sectors displaying large impacts at the end of the century, like those of mortality, have smaller changes in the near-term, due to non-linearities in the response functions. Other sectors, like coastal damages, have monotonically increasing costs throughout the 21st century. Taken together, the results from the ACP presents a unique and novel view of the short-, medium-, and long-term economic risks of climate change in the US. References: [1] T. Houser et al (2014), American Climate Prospectus, www.climateprospectus.org.

Diverse Responses of Global Vegetation to Climate Changes: Spatial Patterns and Time-lag Effects

NASA Astrophysics Data System (ADS)

Wu, D.; Zhao, X.; Zhou, T.; Huang, K.; Xu, W.

2014-12-01

Global climate changes have enormous influences on vegetation growth, meanwhile, response of vegetation to climate express space diversity and time-lag effects, which account for spatial-temporal disparities of climate change and spatial heterogeneity of ecosystem. Revelation of this phenomenon will help us further understanding the impact of climate change on vegetation. Assessment and forecast of global environmental change can be also improved under further climate change. Here we present space diversity and time-lag effects patterns of global vegetation respond to three climate factors (temperature, precipitation and solar radiation) based on quantitative analysis of satellite data (NDVI) and Climate data (Climate Research Unit). We assessed the time-lag effects of global vegetation to main climate factors based on the great correlation fitness between NDVI and the three climate factors respectively among 0-12 months' temporal lags. On this basis, integrated response model of NDVI and the three climate factors was built to analyze contribution of different climate factors to vegetation growth with multiple regression model and partial correlation model. In the result, different vegetation types have distinct temporal lags to the three climate factors. For the precipitation, temporal lags of grasslands are the shortest while the evergreen broad-leaf forests are the longest, which means that grasslands are more sensitive to precipitation than evergreen broad-leaf forests. Analysis of different climate factors' contribution to vegetation reveal that vegetation are dominated by temperature in the high northern latitudes; they are mainly restricted by precipitation in arid and semi-arid areas (Australia, Western America); in humid areas of low and intermediate latitudes (Amazon, Eastern America), vegetation are mainly influenced by solar radiation. Our results reveal the time-lag effects and major driving factors of global vegetation growth and explain the spatiotemporal variations of global vegetation in last 30 years. Significantly, it is as well as in forecasting and assessing the influences of future climate change on the vegetation dynamics. This work was supported by the High Technology Research and Development Program of China (Grant NO.2013AA122801).

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.

Impact of Climate Variability and Landscape Patterns on Water Budget and Nutrient Loads in a Peri-urban Watershed: A Coupled Analysis Using Process-based Hydrological Model and Landscape Indices.

PubMed

Li, Chongwei; Zhang, Yajuan; Kharel, Gehendra; Zou, Chris B

2018-06-01

Nutrient discharge into peri-urban streams and reservoirs constitutes a significant pressure on environmental management, but quantitative assessment of non-point source pollution under climate variability in fast changing peri-urban watersheds is challenging. Soil and Water Assessment Tool (SWAT) was used to simulate water budget and nutrient loads for landscape patterns representing a 30-year progression of urbanization in a peri-urban watershed near Tianjin metropolis, China. A suite of landscape pattern indices was related to nitrogen (N) and phosphorous (P) loads under dry and wet climate using CANOCO redundancy analysis. The calibrated SWAT model was adequate to simulate runoff and nutrient loads for this peri-urban watershed, with Nash-Sutcliffe coefficient (NSE) and coefficient of determination (R 2 ) > 0.70 and percentage bias (PBIAS) between -7 and +18 for calibration and validation periods. With the progression of urbanization, forest remained the main "sink" landscape while cultivated and urban lands remained the main "source" landscapes with the role of orchard and grassland being uncertain and changing with time. Compared to 1984, the landscape use pattern in 2013 increased nutrient discharge by 10%. Nutrient loads modelled under wet climate were 3-4 times higher than that under dry climate for the same landscape pattern. Results indicate that climate change could impose a far greater impact on runoff and nutrient discharge in a peri-urban watershed than landscape pattern change.

Climatic and anthropogenic changes in Western Switzerland: Impacts on water stress.

PubMed

Milano, Marianne; Reynard, Emmanuel; Köplin, Nina; Weingartner, Rolf

2015-12-01

Recent observed hydro-climatic changes in mountainous areas are of concern as they may directly affect capacity to fulfill water needs. The canton of Vaud in Western Switzerland is an example of such a region as it has experienced water shortage episodes during the past decade. Based on an integrated modeling framework, this study explores how hydro-climatic conditions and water needs could evolve in mountain environments and assesses their potential impacts on water stress by the 2060 horizon. Flows were simulated based on a daily semi-distributed hydrological model. Future changes were derived from Swiss climate scenarios based on two regional climate models. Regarding water needs, the authorities of the canton of Vaud provided a population growth scenario while irrigation and livestock trends followed a business-as-usual scenario. Currently, the canton of Vaud experiences moderate water stress from June to August, except in its Alpine area where no stress is noted. In the 2060 horizon, water needs could exceed 80% of the rivers' available resources in low- to mid-altitude environments in mid-summer. This arises from the combination of drier and warmer climate that leads to longer and more severe low flows, and increasing urban (+40%) and irrigation (+25%) water needs. Highlighting regional differences supports the development of sustainable development pathways to reduce water tensions. Based on a quantitative assessment, this study also calls for broader impact studies including water quality issues. Copyright © 2015 Elsevier B.V. All rights reserved.

Impact of Climate Variability and Landscape Patterns on Water Budget and Nutrient Loads in a Peri-urban Watershed: A Coupled Analysis Using Process-based Hydrological Model and Landscape Indices

NASA Astrophysics Data System (ADS)

Li, Chongwei; Zhang, Yajuan; Kharel, Gehendra; Zou, Chris B.

2018-06-01

Nutrient discharge into peri-urban streams and reservoirs constitutes a significant pressure on environmental management, but quantitative assessment of non-point source pollution under climate variability in fast changing peri-urban watersheds is challenging. Soil and Water Assessment Tool (SWAT) was used to simulate water budget and nutrient loads for landscape patterns representing a 30-year progression of urbanization in a peri-urban watershed near Tianjin metropolis, China. A suite of landscape pattern indices was related to nitrogen (N) and phosphorous (P) loads under dry and wet climate using CANOCO redundancy analysis. The calibrated SWAT model was adequate to simulate runoff and nutrient loads for this peri-urban watershed, with Nash-Sutcliffe coefficient (NSE) and coefficient of determination ( R 2) > 0.70 and percentage bias (PBIAS) between -7 and +18 for calibration and validation periods. With the progression of urbanization, forest remained the main "sink" landscape while cultivated and urban lands remained the main "source" landscapes with the role of orchard and grassland being uncertain and changing with time. Compared to 1984, the landscape use pattern in 2013 increased nutrient discharge by 10%. Nutrient loads modelled under wet climate were 3-4 times higher than that under dry climate for the same landscape pattern. Results indicate that climate change could impose a far greater impact on runoff and nutrient discharge in a peri-urban watershed than landscape pattern change.

Geologic and climatic controls on the radon emanation coefficient

USGS Publications Warehouse

Schumann, R.R.; Gundersen, L.C.S.; ,

1997-01-01

Geologic, pedologic, and climatic factors, including radium content, grain size, siting of radon parents within soil grains or on grain coatings, and soil moisture conditions, determine a soil's emanating power and radon transport characteristics. Data from field studies indicate that soils derived from similar parent rocks in different regions have significantly different emanation coefficients due to the effects of climate on these soil characteristics. An important tool for measuring radon source strength (i.e., radium content) is ground-based and aerial gamma radioactivity measurements. Regional correlations between soil radium content, determined by gamma spectrometry, and soil-gas or indoor radon concentrations can be traced to the influence of climatic and geologic factors on intrinsic permeability and radon emanation coefficients. Data on soil radium content, permeability, and moisture content, when combined with data on emanation coefficients, can form a framework for development of quantitative predictive models for radon generation in rocks and soils.

Sensitivity of regional forest carbon budgets to continuous and stochastic climate change pressures

NASA Astrophysics Data System (ADS)

Sulman, B. N.; Desai, A. R.; Scheller, R. M.

2010-12-01

Climate change is expected to impact forest-atmosphere carbon budgets through three processes: 1. Increased disturbance rates, including fires, mortality due to pest outbreaks, and severe storms 2. Changes in patterns of inter-annual variability, related to increased incidence of severe droughts and defoliating insect outbreaks 3. Continuous changes in forest productivity and respiration, related to increases in mean temperature, growing season length, and CO2 fertilization While the importance of these climate change effects in future regional carbon budgets has been established, quantitative characterization of the relative sensitivity of forested landscapes to these different types of pressures is needed. We present a model- and- data-based approach to understanding the sensitivity of forested landscapes to climate change pressures. Eddy-covariance and biometric measurements from forests in the northern United States were used to constrain two forest landscape models. The first, LandNEP, uses a prescribed functional form for the evolution of net ecosystem productivity (NEP) over the age of a forested grid cell, which is reset following a disturbance event. This model was used for investigating the basic statistical properties of a simple landscape’s responses to climate change pressures. The second model, LANDIS-II, includes different tree species and models forest biomass accumulation and succession, allowing us to investigate the effects of more complex forest processes such as species change and carbon pool accumulation on landscape responses to climate change effects. We tested the sensitivity of forested landscapes to these three types of climate change pressures by applying ensemble perturbations of random disturbance rates, distribution functions of inter-annual variability, and maximum potential carbon uptake rates, in the two models. We find that landscape-scale net carbon exchange responds linearly to continuous changes in potential carbon uptake and inter-annual variability, while responses to stochastic changes are non-linear and become more important at shorter mean disturbance intervals. These results provide insight on how to better parameterize coupled carbon-climate models to more realistically simulate feedbacks between forests and the atmosphere.

Past and future trends of hydroclimatic intensity over the Indian monsoon region

NASA Astrophysics Data System (ADS)

Mohan, T. S.; Rajeevan, M.

2017-01-01

The hydroclimatic intensity index (HY-INT) is a single index that quantitatively combines measures of precipitation intensity and dry spell length, thus providing an integrated response of the hydrological cycle to global warming. The HY-INT index is a product of the precipitation intensity (PINT, intensity during wet days) and dry spell length (DSL). Using the observed gridded rainfall data sets of 1951-2010 period, the changes in HY-INT, PINT, and DSL over the Indian monsoon region have been examined in addition to changes in maximum consecutive dry days (MCD). We have also considered 10 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models for examining the changes in these indices during the present-day and future climate change scenarios. For climate change projections, the Representative Concentration Pathway (RCP) 4.5 scenario was considered. The analysis of observational data during the period 1951-2010 suggested an increase in DSL and MCD over most of central India. Further, statistically significant (95% level) increase in HY-INT is also noted during the period of 1951-2010, which is mainly caused due to significant increase in precipitation intensity. The CMIP5 model projections of future climate also suggest a statistically significant increase in HY-INT over the Indian region. Out of the 10 models considered, seven models suggest a consistent increase in HY-INT during the period of 2010-2100 under the RCP4.5 scenario. However, the projected increase in HY-INT is mainly due to increase in the precipitation intensity, while dry spell length (DSL) showed little changes in the future climate.

Impact of climate change on water resources status: A case study for Crete Island, Greece

NASA Astrophysics Data System (ADS)

Koutroulis, Aristeidis G.; Tsanis, Ioannis K.; Daliakopoulos, Ioannis N.; Jacob, Daniela

2013-02-01

SummaryAn assessment of the impact of global climate change on the water resources status of the island of Crete, for a range of 24 different scenarios of projected hydro-climatological regime is presented. Three "state of the art" Global Climate Models (GCMs) and an ensemble of Regional Climate Models (RCMs) under emission scenarios B1, A2 and A1B provide future precipitation (P) and temperature (T) estimates that are bias adjusted against observations. The ensemble of RCMs for the A1B scenario project a higher P reduction compared to GCMs projections under A2 and B1 scenarios. Among GCMs model results, the ECHAM model projects a higher P reduction compared to IPSL and CNCM. Water availability for the whole island at basin scale until 2100 is estimated using the SAC-SMA rainfall-runoff model And a set of demand and infrastructure scenarios are adopted to simulate potential water use. While predicted reduction of water availability under the B1 emission scenario can be handled with water demand stabilized at present values and full implementation of planned infrastructure, other scenarios require additional measures and a robust signal of water insufficiency is projected. Despite inherent uncertainties, the quantitative impact of the projected changes on water availability indicates that climate change plays an important role to water use and management in controlling future water status in a Mediterranean island like Crete. The results of the study reinforce the necessity to improve and update local water management planning and adaptation strategies in order to attain future water security.

Future air pollution in the Shared Socio-economic Pathways

DOE PAGES

Rao, Shilpa; Klimont, Zbigniew; Smith, Steven J.; ...

2016-07-15

Emissions of air pollutants such as sulfur and nitrogen oxides and particulates have significant health impacts as well as effects on natural and anthropogenic ecosystems. These same emissions also can change atmospheric chemistry and the planetary energy balance, thereby impacting global and regional climate. Long-term scenarios for air pollutant emissions are needed as inputs to global climate and chemistry models, and for analysis linking air pollutant impacts across sectors. In this paper we present methodology and results for air pollutant emissions in Shared Socioeconomic Pathways (SSP) scenarios. We first present a set of three air pollution narratives that describe high,more » central, and low pollution control ambitions over the 21 st century. These narratives are then translated into quantitative guidance for use in integrated assessment models. We provide an overview of pollutant emission trajectories under the SSP scenarios. Pollutant emissions in these scenarios cover a wider range than the scenarios used in previous international climate model comparisons. Furthermore, the SSP scenarios provide the opportunity to access a more comprehensive range of future global and regional air quality outcomes.« less

Future air pollution in the Shared Socio-economic Pathways

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

Rao, Shilpa; Klimont, Zbigniew; Smith, Steven J.

Emissions of air pollutants such as sulfur and nitrogen oxides and particulates have significant health impacts as well as effects on natural and anthropogenic ecosystems. These same emissions also can change atmospheric chemistry and the planetary energy balance, thereby impacting global and regional climate. Long-term scenarios for air pollutant emissions are needed as inputs to global climate and chemistry models, and for analysis linking air pollutant impacts across sectors. In this paper we present methodology and results for air pollutant emissions in Shared Socioeconomic Pathways (SSP) scenarios. We first present a set of three air pollution narratives that describe high,more » central, and low pollution control ambitions over the 21 st century. These narratives are then translated into quantitative guidance for use in integrated assessment models. We provide an overview of pollutant emission trajectories under the SSP scenarios. Pollutant emissions in these scenarios cover a wider range than the scenarios used in previous international climate model comparisons. Furthermore, the SSP scenarios provide the opportunity to access a more comprehensive range of future global and regional air quality outcomes.« less

A modern pollen-climate dataset from the Darjeeling area, eastern Himalaya: Assessing its potential for past climate reconstruction

NASA Astrophysics Data System (ADS)

Ghosh, Ruby; Bruch, Angela A.; Portmann, Felix; Bera, Subir; Paruya, Dipak Kumar; Morthekai, P.; Ali, Sheikh Nawaz

2017-10-01

Relying on the ability of pollen assemblages to differentiate among elevationally stratified vegetation zones, we assess the potential of a modern pollen-climate dataset from the Darjeeling area, eastern Himalaya, in past climate reconstructions. The dataset includes 73 surface samples from 25 sites collected from a c. 130-3600 m a.s.l. elevation gradient along a horizontal distance of c. 150 km and 124 terrestrial pollen taxa, which are analysed with respect to various climatic and environmental variables such as mean annual temperature (MAT), mean annual precipitation (MAP), mean temperature of coldest quarter (MTCQ), mean temperature of warmest quarter (MTWQ), mean precipitation of driest quarter (MPDQ), mean precipitation of wettest quarter (MPWQ), AET (actual evapotranspiration) and MI (moisture index). To check the reliability of the modern pollen-climate relationships different ordination methods are employed and subsequently tested with Huisman-Olff-Fresco (HOF) models. A series of pollen-climate parameter transfer functions using weighted-averaging regression and calibration partial least squares (WA-PLS) models are developed to reconstruct past climate changes from modern pollen data, and have been cross-validated. Results indicate that three of the environmental variables i.e., MTCQ, MPDQ and MI have strong potential for past climate reconstruction based on the available surface pollen dataset. The potential of the present modern pollen-climate relationship for regional quantitative paleoclimate reconstruction is further tested on a Late Quaternary fossil pollen profile from the Darjeeling foothill region with previously reconstructed and quantified climate. The good agreement with existing data allows for new insights in the hydroclimatic conditions during the Last glacial maxima (LGM) with (winter) temperature being the dominant controlling factor for glacial changes during the LGM in the eastern Himalaya.

Amsterdamøya: a key site for the post-glacial of Svalbard

NASA Astrophysics Data System (ADS)

Bakke, Jostein; Balascio, Nicholas; van der Bilt, Willem; D`Andrea, William; Bradley, Raymond; Gjerde, Marthe; Hormes, Anne; Olafsdottir, Sædis; Røthe, Torgeir; Vasskog, Kristian; De Wet, Greg; Werner, Johannes

2016-04-01

No other place on Earth is changing as fast as the Arctic in terms of climate. On average this region is warming twice as fast as the global average with a seasonal bias towards winter. A major retreat in sea ice extent accompanied by an even more massive thinning represents one of the most robust trends in the Arctic. This trend is anticipated to continue in the decades to come and, according to some models, will leave the Arctic Ocean open during summer some time between 2050-2100. Unabated reduction in the spring-snow cover represents another significant trend. The current warming is also expressed in the massive melting of the Greenland ice sheet as well as local glaciers and ice caps in the Arctic, which causes increased freshwater influx to the Arctic Ocean and adjacent seas. Climate modeling and scenarios are improving and becoming of growing importance, but without a firmer understanding of natural climate variability over longer timescale it is still hard to evaluate and best read the output from these models. In the SHIFTS project we have done an unparalleled effort to overcome this quandary, providing necessary empirical data on past climate which is critical for assessing past changes in atmospheric circulation patterns controlling Arctic hydroclimate. Our study site is located at the northwestern corner of Svalbard on the Island of Amsterdamøya, a site sensitive to changes in both oceanic and atmospheric forcing, at tail of the westward moving branch of the North Atlantic current. Here we have cored several lakes with the goal of providing quantitative data on temperature, hydrology and winter precipitation for the Holocene. Our approach has been to combine reconstruction of glaciers with lipid biomarkers and hydrogen isotopes with the goal of unravel the underlying signature of past climate in the Arctic. Chronological control is secured by radiocarbon dates on macrofossils combined with measurement of paleomagnetic secular variations. Here we synthesis the individual time series providing quantitative data on winter precipitation and summer temperature of the past.

Reliability of regional climate simulations

NASA Astrophysics Data System (ADS)

Ahrens, W.; Block, A.; Böhm, U.; Hauffe, D.; Keuler, K.; Kücken, M.; Nocke, Th.

2003-04-01

Quantification of uncertainty becomes more and more a key issue for assessing the trustability of future climate scenarios. In addition to the mean conditions, climate impact modelers focus in particular on extremes. Before generating such scenarios using e.g. dynamic regional climate models, a careful validation of present-day simulations should be performed to determine the range of errors for the quantities of interest under recent conditions as a raw estimate of their uncertainty in the future. Often, multiple aspects shall be covered together, and the required simulation accuracy depends on the user's demand. In our approach, a massive parallel regional climate model shall be used on the one hand to generate "long-term" high-resolution climate scenarios for several decades, and on the other hand to provide very high-resolution ensemble simulations of future dry spells or heavy rainfall events. To diagnosis the model's performance for present-day simulations, we have recently developed and tested a first version of a validation and visualization chain for this model. It is, however, applicable in a much more general sense and could be used as a common test bed for any regional climate model aiming at this type of simulations. Depending on the user's interest, integrated quality measures can be derived for near-surface parameters using multivariate techniques and multidimensional distance measures in a first step. At this point, advanced visualization techniques have been developed and included to allow for visual data mining and to qualitatively identify dominating aspects and regularities. Univariate techniques that are especially designed to assess climatic aspects in terms of statistical properties can then be used to quantitatively diagnose the error contributions of the individual used parameters. Finally, a comprehensive in-depth diagnosis tool allows to investigate, why the model produces the obtained near-surface results to answer the question if the model performs well from the modeler's point of view. Examples will be presented for results obtained using this approach for assessing the risk of potential total agricultural yield loss under drought conditions in Northeast Brazil and for evaluating simulation results for a 10-year period for Europe. To support multi-run simulations and result evaluation, the model will be embedded into an already existing simulation environment that provides further postprocessing tools for sensitivity studies, behavioral analysis and Monte-Carlo simulations, but also for ensemble scenario analysis in one of the next steps.

Predicting Factors of Perceived Organizational Support by Full-Time and Part-Time Community College Faculty as Relates to Student Retention Rates

ERIC Educational Resources Information Center

Nichols, Sarah K.

2012-01-01

Student retention is socially, politically, and financially important to educational institutions. This quantitative study explored the gap in research regarding the relationship between employment of part-time in lieu of full-time faculty and student retention. The campus climate exchange model (CCEM), served as the conceptual framework in this…

Coupling Processes Between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, Malcolm; Weisenstein, Debra; Rodriquez, Jose; Danilin, Michael; Scott, Courtney; Shia, Run-Lie; Eluszkiewicz, Janusz; Sze, Nien-Dak; Stewart, Richard W. (Technical Monitor)

1999-01-01

This is the final report for NAS5-97039 for work performed between December 1996 and November 1999. The overall objective of this project is to improve the understanding of coupling processes among atmospheric chemistry, aerosol and climate, all important for quantitative assessments of global change. Among our priority are changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The work emphasizes two important aspects: (1) AER's continued participation in preparation of, and providing scientific input for, various scientific reports connected with assessment of stratospheric ozone and climate. These include participation in various model intercomparison exercises as well as preparation of national and international reports. (2) Continued development of the AER three-wave interactive model to address how the transport circulation will change as ozone and the thermal properties of the atmosphere change, and assess how these new findings will affect our confidence in the ozone assessment results.

On determining the point of no return in climate change

NASA Astrophysics Data System (ADS)

van Zalinge, Brenda C.; Feng, Qing Yi; Aengenheyster, Matthias; Dijkstra, Henk A.

2017-08-01

Earth's global mean surface temperature has increased by about 1.0 °C over the period 1880-2015. One of the main causes is thought to be the increase in atmospheric greenhouse gases. If greenhouse gas emissions are not substantially decreased, several studies indicate that there will be a dangerous anthropogenic interference with climate by the end of this century. However, there is no good quantitative measure to determine when it is too late to start reducing greenhouse gas emissions in order to avoid such dangerous interference. In this study, we develop a method for determining a so-called point of no return for several greenhouse gas emission scenarios. The method is based on a combination of aspects of stochastic viability theory and linear response theory; the latter is used to estimate the probability density function of the global mean surface temperature. The innovative element in this approach is the applicability to high-dimensional climate models as demonstrated by the results obtained with the PlaSim model.

Estimating Irrigation Water Requirements using MODIS Vegetation Indices and Inverse Biophysical Modeling

NASA Technical Reports Server (NTRS)

Imhoff, Marc L.; Bounoua, Lahouari; Harriss, Robert; Harriss, Robert; Wells, Gordon; Glantz, Michael; Dukhovny, Victor A.; Orlovsky, Leah

2007-01-01

An inverse process approach using satellite-driven (MODIS) biophysical modeling was used to quantitatively assess water resource demand in semi-arid and arid agricultural lands by comparing the carbon and water flux modeled under both equilibrium (in balance with prevailing climate) and non-equilibrium (irrigated) conditions. Since satellite observations of irrigated areas show higher leaf area indices (LAI) than is supportable by local precipitation, we postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. For an observation year we used MODIS vegetation indices, local climate data, and the SiB2 photosynthesis-conductance model to examine the relationship between climate and the water stress function for a given grid-cell and observed leaf area. To estimate the minimum amount of supplemental water required for an observed cell, we added enough precipitation to the prevailing climatology at each time step to minimize the water stress function and bring the soil to field capacity. The experiment was conducted on irrigated lands on the U.S. Mexico border and Central Asia and compared to estimates of irrigation water used.

The Sensitivity of the North American Monsoon to Deglacial Climate Change in Proxies and Models

NASA Astrophysics Data System (ADS)

Bhattacharya, T.; Tierney, J. E.

2017-12-01

The North American Monsoon (NAM), which brings summer rainfall to the arid US Southwest and northwestern Mexico, remains one of the least understood monsoon systems. Model simulations produce divergent NAM responses to future anthropogenic warming, and many paleoclimatic records from the NAM region are more sensitive to winter rainfall than the summertime circulation. As a result, we have an incomplete understanding of NAM sensitivity to past and future global climate change. Our work seeks to improve understanding of NAM dynamics using new proxy records and model simulations. We have developed quantitative reconstructions of NAM strength since the LGM ( 21 ka BP) using leaf wax biomarkers (e.g. dD of n-acids) from marine sediment cores in the Gulf of California. We contrast these proxy records with idealized GCM simulations (i.e. CESM1.2) to diagnose the mechanisms behind NAM responses to LGM boundary conditions and abrupt deglacial climate events. Our results suggest that ice-sheet induced changes in atmospheric circulation acted in concert with local changes in Gulf of California SSTs to modulate the late glacial NAM. This work has important implications for our understanding of NAM dynamics, its relationship with other monsoon systems, and its sensitivity to past and future global climate change.

Critical Watersheds: Climate Change, Tipping Points, and Energy-Water Impacts

NASA Astrophysics Data System (ADS)

Middleton, R. S.; Brown, M.; Coon, E.; Linn, R.; McDowell, N. G.; Painter, S. L.; Xu, C.

2014-12-01

Climate change, extreme climate events, and climate-induced disturbances will have a substantial and detrimental impact on terrestrial ecosystems. How ecosystems respond to these impacts will, in turn, have a significant effect on the quantity, quality, and timing of water supply for energy security, agriculture, industry, and municipal use. As a community, we lack sufficient quantitative and mechanistic understanding of the complex interplay between climate extremes (e.g., drought, floods), ecosystem dynamics (e.g., vegetation succession), and disruptive events (e.g., wildfire) to assess ecosystem vulnerabilities and to design mitigation strategies that minimize or prevent catastrophic ecosystem impacts. Through a combination of experimental and observational science and modeling, we are developing a unique multi-physics ecohydrologic framework for understanding and quantifying feedbacks between novel climate and extremes, surface and subsurface hydrology, ecosystem dynamics, and disruptive events in critical watersheds. The simulation capability integrates and advances coupled surface-subsurface hydrology from the Advanced Terrestrial Simulator (ATS), dynamic vegetation succession from the Ecosystem Demography (ED) model, and QUICFIRE, a novel wildfire behavior model developed from the FIRETEC platform. These advances are expected to make extensive contributions to the literature and to earth system modeling. The framework is designed to predict, quantify, and mitigate the impacts of climate change on vulnerable watersheds, with a focus on the US Mountain West and the energy-water nexus. This emerging capability is used to identify tipping points in watershed ecosystems, quantify impacts on downstream users, and formally evaluate mitigation efforts including forest (e.g., thinning, prescribed burns) and watershed (e.g., slope stabilization). The framework is being trained, validated, and demonstrated using field observations and remote data collections in the Valles Caldera National Preserve, including pre- and post-wildfire and infestation observations. Ultimately, the framework will be applied to the upper Colorado River basin. Here, we present an overview of the framework development strategy and latest field and modeling results.

Climate Change Education: Quantitatively Assessing the Impact of a Botanical Garden as an Informal Learning Environment

ERIC Educational Resources Information Center

Sellmann, Daniela; Bogner, Franz X.

2013-01-01

Although informal learning environments have been studied extensively, ours is one of the first studies to quantitatively assess the impact of learning in botanical gardens on students' cognitive achievement. We observed a group of 10th graders participating in a one-day educational intervention on climate change implemented in a botanical garden.…

Broad-scale climate influences on spring-spawning herring (Clupea harengus, L.) recruitment in the Western Baltic Sea.

PubMed

Gröger, Joachim P; Hinrichsen, Hans-Harald; Polte, Patrick

2014-01-01

Climate forcing in complex ecosystems can have profound implications for ecosystem sustainability and may thus challenge a precautionary ecosystem management. Climatic influences documented to affect various ecological functions on a global scale, may themselves be observed on quantitative or qualitative scales including regime shifts in complex marine ecosystems. This study investigates the potential climatic impact on the reproduction success of spring-spawning herring (Clupea harengus) in the Western Baltic Sea (WBSS herring). To test for climate effects on reproduction success, the regionally determined and scientifically well-documented spawning grounds of WBSS herring represent an ideal model system. Climate effects on herring reproduction were investigated using two global indices of atmospheric variability and sea surface temperature, represented by the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO), respectively, and the Baltic Sea Index (BSI) which is a regional-scale atmospheric index for the Baltic Sea. Moreover, we combined a traditional approach with modern time series analysis based on a recruitment model connecting parental population components with reproduction success. Generalized transfer functions (ARIMAX models) allowed evaluating the dynamic nature of exogenous climate processes interacting with the endogenous recruitment process. Using different model selection criteria our results reveal that in contrast to NAO and AMO, the BSI shows a significant positive but delayed signal on the annual dynamics of herring recruitment. The westward influence of the Siberian high is considered strongly suppressing the influence of the NAO in this area leading to a higher explanatory power of the BSI reflecting the atmospheric pressure regime on a North-South transect between Oslo, Norway and Szczecin, Poland. We suggest incorporating climate-induced effects into stock and risk assessments and management strategies as part of the EU ecosystem approach to support sustainable herring fisheries in the Western Baltic Sea.

Broad-Scale Climate Influences on Spring-Spawning Herring (Clupea harengus, L.) Recruitment in the Western Baltic Sea

PubMed Central

Gröger, Joachim P.; Hinrichsen, Hans-Harald; Polte, Patrick

2014-01-01

Climate forcing in complex ecosystems can have profound implications for ecosystem sustainability and may thus challenge a precautionary ecosystem management. Climatic influences documented to affect various ecological functions on a global scale, may themselves be observed on quantitative or qualitative scales including regime shifts in complex marine ecosystems. This study investigates the potential climatic impact on the reproduction success of spring-spawning herring (Clupea harengus) in the Western Baltic Sea (WBSS herring). To test for climate effects on reproduction success, the regionally determined and scientifically well-documented spawning grounds of WBSS herring represent an ideal model system. Climate effects on herring reproduction were investigated using two global indices of atmospheric variability and sea surface temperature, represented by the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO), respectively, and the Baltic Sea Index (BSI) which is a regional-scale atmospheric index for the Baltic Sea. Moreover, we combined a traditional approach with modern time series analysis based on a recruitment model connecting parental population components with reproduction success. Generalized transfer functions (ARIMAX models) allowed evaluating the dynamic nature of exogenous climate processes interacting with the endogenous recruitment process. Using different model selection criteria our results reveal that in contrast to NAO and AMO, the BSI shows a significant positive but delayed signal on the annual dynamics of herring recruitment. The westward influence of the Siberian high is considered strongly suppressing the influence of the NAO in this area leading to a higher explanatory power of the BSI reflecting the atmospheric pressure regime on a North-South transect between Oslo, Norway and Szczecin, Poland. We suggest incorporating climate-induced effects into stock and risk assessments and management strategies as part of the EU ecosystem approach to support sustainable herring fisheries in the Western Baltic Sea. PMID:24586279

Cultural and climatic changes shape the evolutionary history of the Uralic languages.

PubMed

Honkola, T; Vesakoski, O; Korhonen, K; Lehtinen, J; Syrjänen, K; Wahlberg, N

2013-06-01

Quantitative phylogenetic methods have been used to study the evolutionary relationships and divergence times of biological species, and recently, these have also been applied to linguistic data to elucidate the evolutionary history of language families. In biology, the factors driving macroevolutionary processes are assumed to be either mainly biotic (the Red Queen model) or mainly abiotic (the Court Jester model) or a combination of both. The applicability of these models is assumed to depend on the temporal and spatial scale observed as biotic factors act on species divergence faster and in smaller spatial scale than the abiotic factors. Here, we used the Uralic language family to investigate whether both 'biotic' interactions (i.e. cultural interactions) and abiotic changes (i.e. climatic fluctuations) are also connected to language diversification. We estimated the times of divergence using Bayesian phylogenetics with a relaxed-clock method and related our results to climatic, historical and archaeological information. Our timing results paralleled the previous linguistic studies but suggested a later divergence of Finno-Ugric, Finnic and Saami languages. Some of the divergences co-occurred with climatic fluctuation and some with cultural interaction and migrations of populations. Thus, we suggest that both 'biotic' and abiotic factors contribute either directly or indirectly to the diversification of languages and that both models can be applied when studying language evolution. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

Methodology for qualitative uncertainty assessment of climate impact indicators

NASA Astrophysics Data System (ADS)

Otto, Juliane; Keup-Thiel, Elke; Rechid, Diana; Hänsler, Andreas; Pfeifer, Susanne; Roth, Ellinor; Jacob, Daniela

2016-04-01

The FP7 project "Climate Information Portal for Copernicus" (CLIPC) is developing an integrated platform of climate data services to provide a single point of access for authoritative scientific information on climate change and climate change impacts. In this project, the Climate Service Center Germany (GERICS) has been in charge of the development of a methodology on how to assess the uncertainties related to climate impact indicators. Existing climate data portals mainly treat the uncertainties in two ways: Either they provide generic guidance and/or express with statistical measures the quantifiable fraction of the uncertainty. However, none of the climate data portals give the users a qualitative guidance how confident they can be in the validity of the displayed data. The need for such guidance was identified in CLIPC user consultations. Therefore, we aim to provide an uncertainty assessment that provides the users with climate impact indicator-specific guidance on the degree to which they can trust the outcome. We will present an approach that provides information on the importance of different sources of uncertainties associated with a specific climate impact indicator and how these sources affect the overall 'degree of confidence' of this respective indicator. To meet users requirements in the effective communication of uncertainties, their feedback has been involved during the development process of the methodology. Assessing and visualising the quantitative component of uncertainty is part of the qualitative guidance. As visual analysis method, we apply the Climate Signal Maps (Pfeifer et al. 2015), which highlight only those areas with robust climate change signals. Here, robustness is defined as a combination of model agreement and the significance of the individual model projections. Reference Pfeifer, S., Bülow, K., Gobiet, A., Hänsler, A., Mudelsee, M., Otto, J., Rechid, D., Teichmann, C. and Jacob, D.: Robustness of Ensemble Climate Projections Analyzed with Climate Signal Maps: Seasonal and Extreme Precipitation for Germany, Atmosphere (Basel)., 6(5), 677-698, doi:10.3390/atmos6050677, 2015.

Estimating the Numerical Diapycnal Mixing in the GO5.0 Ocean Model

NASA Astrophysics Data System (ADS)

Megann, A.; Nurser, G.

2014-12-01

Constant-depth (or "z-coordinate") ocean models such as MOM4 and NEMO have become the de facto workhorse in climate applications, and have attained a mature stage in their development and are well understood. A generic shortcoming of this model type, however, is a tendency for the advection scheme to produce unphysical numerical diapycnal mixing, which in some cases may exceed the explicitly parameterised mixing based on observed physical processes, and this is likely to have effects on the long-timescale evolution of the simulated climate system. Despite this, few quantitative estimations have been made of the magnitude of the effective diapycnal diffusivity due to numerical mixing in these models. GO5.0 is the latest ocean model configuration developed jointly by the UK Met Office and the National Oceanography Centre (Megann et al, 2014), and forms part of the GC1 and GC2 climate models. It uses version 3.4 of the NEMO model, on the ORCA025 ¼° global tripolar grid. We describe various approaches to quantifying the numerical diapycnal mixing in this model, and present results from analysis of the GO5.0 model based on the isopycnal watermass analysis of Lee et al (2002) that indicate that numerical mixing does indeed form a significant component of the watermass transformation in the ocean interior.

Deaf college students' attitudes toward racial/ethnic diversity, campus climate, and role models.

PubMed

Parasnis, Ila; Samar, Vincent J; Fischer, Susan D

2005-01-01

Deaf college students' attitudes toward a variety of issues related to racial/ethnic diversity were surveyed by contacting all racial/ethnic minority deaf students and a random sample of Caucasian deaf students attending the National Technical Institute for the Deaf (NTID), Rochester Institute of Technology; 38% completed the survey. Although racial/ethnic groups similarly perceived NTID's commitment and efforts related to diversity, they differed significantly on some items related to campus climate and role models. Furthermore, the racial/ethnic minority groups differed from each other in their perceptions of campus comfort level, racial conflict, friendship patterns, and availability of role models. Educational satisfaction was positively correlated with campus comfort level; both correlated negatively with perception of discrimination and racial conflict. Qualitative data analyses supported quantitative data analyses and provided rich detail that facilitated interpretation of deaf students' experiences related to racial/ethnic diversity.

Sensitivity of the Eocene climate to CO2 and orbital variability

NASA Astrophysics Data System (ADS)

Keery, John S.; Holden, Philip B.; Edwards, Neil R.

2018-02-01

The early Eocene, from about 56 Ma, with high atmospheric CO2 levels, offers an analogue for the response of the Earth's climate system to anthropogenic fossil fuel burning. In this study, we present an ensemble of 50 Earth system model runs with an early Eocene palaeogeography and variation in the forcing values of atmospheric CO2 and the Earth's orbital parameters. Relationships between simple summary metrics of model outputs and the forcing parameters are identified by linear modelling, providing estimates of the relative magnitudes of the effects of atmospheric CO2 and each of the orbital parameters on important climatic features, including tropical-polar temperature difference, ocean-land temperature contrast, Asian, African and South (S.) American monsoon rains, and climate sensitivity. Our results indicate that although CO2 exerts a dominant control on most of the climatic features examined in this study, the orbital parameters also strongly influence important components of the ocean-atmosphere system in a greenhouse Earth. In our ensemble, atmospheric CO2 spans the range 280-3000 ppm, and this variation accounts for over 90 % of the effects on mean air temperature, southern winter high-latitude ocean-land temperature contrast and northern winter tropical-polar temperature difference. However, the variation of precession accounts for over 80 % of the influence of the forcing parameters on the Asian and African monsoon rainfall, and obliquity variation accounts for over 65 % of the effects on winter ocean-land temperature contrast in high northern latitudes and northern summer tropical-polar temperature difference. Our results indicate a bimodal climate sensitivity, with values of 4.36 and 2.54 °C, dependent on low or high states of atmospheric CO2 concentration, respectively, with a threshold at approximately 1000 ppm in this model, and due to a saturated vegetation-albedo feedback. Our method gives a quantitative ranking of the influence of each of the forcing parameters on key climatic model outputs, with additional spatial information from singular value decomposition providing insights into likely physical mechanisms. The results demonstrate the importance of orbital variation as an agent of change in climates of the past, and we demonstrate that emulators derived from our modelling output can be used as rapid and efficient surrogates of the full complexity model to provide estimates of climate conditions from any set of forcing parameters.

Changes in river water temperature between 1980 and 2012 in Yongan watershed, eastern China: Magnitude, drivers and models

NASA Astrophysics Data System (ADS)

Chen, Dingjiang; Hu, Minpeng; Guo, Yi; Dahlgren, Randy A.

2016-02-01

Climate warming is expected to have major impacts on river water quality, water column/hyporheic zone biogeochemistry and aquatic ecosystems. A quantitative understanding of spatio-temporal air (Ta) and water (Tw) temperature dynamics is required to guide river management and to facilitate adaptations to climate change. This study determined the magnitude, drivers and models for increasing Tw in three river segments of the Yongan watershed in eastern China. Over the 1980-2012 period, Tw in the watershed increased by 0.029-0.046 °C yr-1 due to a ∼0.050 °C yr-1 increase of Ta and changes in local human activities (e.g., increasing developed land and population density and decreasing forest area). A standardized multiple regression model was developed for predicting annual Tw (R2 = 0.88-0.91) and identifying/partitioning the impact of the principal drivers on increasing Tw:Ta (76 ± 1%), local human activities (14 ± 2%), and water discharge (10 ± 1%). After normalizing water discharge, climate warming and local human activities were estimated to contribute 81-95% and 5-19% of the observed rising Tw, respectively. Models forecast a 0.32-1.76 °C increase in Tw by 2050 compared with the 2000-2012 baseline condition based on four future scenarios. Heterogeneity of warming rates existed across seasons and river segments, with the lower flow river and dry season demonstrating a more pronounced response to climate warming and human activities. Rising Tw due to changes in climate, local human activities and hydrology has a considerable potential to aggravate river water quality degradation and coastal water eutrophication in summer. Thus it should be carefully considered in developing watershed management strategies in response to climate change.

Capturing subregional variability in regional-scale climate change vulnerability assessments of natural resources.

PubMed

Buotte, Polly C; Peterson, David L; McKelvey, Kevin S; Hicke, Jeffrey A

2016-03-15

Natural resource vulnerability to climate change can depend on the climatology and ecological conditions at a particular site. Here we present a conceptual framework for incorporating spatial variability in natural resource vulnerability to climate change in a regional-scale assessment. The framework was implemented in the first regional-scale vulnerability assessment conducted by the US Forest Service. During this assessment, five subregional workshops were held to capture variability in vulnerability and to develop adaptation tactics. At each workshop, participants answered a questionnaire to: 1) identify species, resources, or other information missing from the regional assessment, and 2) describe subregional vulnerability to climate change. Workshop participants divided into six resource groups; here we focus on wildlife resources. Participants identified information missing from the regional assessment and multiple instances of subregional variability in climate change vulnerability. We provide recommendations for improving the process of capturing subregional variability in a regional vulnerability assessment. We propose a revised conceptual framework structured around pathways of climate influence, each with separate rankings for exposure, sensitivity, and adaptive capacity. These revisions allow for a quantitative ranking of species, pathways, exposure, sensitivity, and adaptive capacity across subregions. Rankings can be used to direct the development and implementation of future regional research and monitoring programs. The revised conceptual framework is equally applicable as a stand-alone model for assessing climate change vulnerability and as a nested model within a regional assessment for capturing subregional variability in vulnerability. Copyright © 2015 Elsevier Ltd. All rights reserved.

Statistical Surrogate Models for Estimating Probability of High-Consequence Climate Change

NASA Astrophysics Data System (ADS)

Field, R.; Constantine, P.; Boslough, M.

2011-12-01

We have posed the climate change problem in a framework similar to that used in safety engineering, by acknowledging that probabilistic risk assessments focused on low-probability, high-consequence climate events are perhaps more appropriate than studies focused simply on best estimates. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We have developed specialized statistical surrogate models (SSMs) that can be used to make predictions about the tails of the associated probability distributions. A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field, that is, a random variable for every fixed location in the atmosphere at all times. The SSM can be calibrated to available spatial and temporal data from existing climate databases, or to a collection of outputs from general circulation models. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework was also developed to provide quantitative measures of confidence, via Bayesian credible intervals, to assess these risks. To illustrate the use of the SSM, we considered two collections of NCAR CCSM 3.0 output data. The first collection corresponds to average December surface temperature for years 1990-1999 based on a collection of 8 different model runs obtained from the Program for Climate Model Diagnosis and Intercomparison (PCMDI). We calibrated the surrogate model to the available model data and make various point predictions. We also analyzed average precipitation rate in June, July, and August over a 54-year period assuming a cyclic Y2K ocean model. We applied the calibrated surrogate model to study the probability that the precipitation rate falls below certain thresholds and utilized the Bayesian approach to quantify our confidence in these predictions. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under Contract DE-AC04-94AL85000.

The Ocean Colour Climate Change Initiative: III. A Round-Robin Comparison on In-Water Bio-Optical Algorithms

NASA Technical Reports Server (NTRS)

Brewin, Robert J.W.; Sathyendranath, Shubha; Muller, Dagmar; Brockmann, Carsten; Deschamps, Pierre-Yves; Devred, Emmanuel; Doerffer, Roland; Fomferra, Norman; Franz, Bryan; Grant, Mike;

Uncertainties in assessing climate change impacts on the hydrology of Mediterranean basins

NASA Astrophysics Data System (ADS)

Ludwig, Ralf

2013-04-01

There is substantial evidence in historical and recent observations that the Mediterranean and neighboring regions are especially vulnerable to the impacts of climate change. Numerous climate projections, stemming from ensembles of global and regional climate models, agree on severe changes in the climate forcing which are likely to exacerbate subsequent ecological, economic and social impacts. Many of these causal connections are closely linked to the general expectation that water availability will decline in the already water-stressed basins of Africa, the Mediterranean region and the Near East, even though considerable regional variances must be expected. Consequently, climate change impacts on water resources are raising concerns regarding their possible management and security implications. Decreasing access to water resources and other related factors could be a cause or a 'multiplier' of tensions within and between countries. Whether security threats arise from climate impacts or options for cooperation evolve does not depend only on the severity of the impacts themselves, but on social, economic, and institutional vulnerabilities or resilience as well as factors that influence local, national and international relations. However, an assessment of vulnerability and risks hinges on natural, socio-economic, and political conditions and responses, all of which are uncertain. Multidisciplinary research is needed to tackle the multi-facet complexity of climate change impacts on water resources in the Mediterranean and neighboring countries. This is particularly true in a region of overall data scarcity and poor data management and exchange structures. The current potential to develop appropriate regional adaptation measures towards climate change impacts suffers heavily from large uncertainties. These spread along a long chain of components, starting from the definition of emission scenarios to global and regional climate modeling to impact models and a subsequent variety of management options and adaptation strategies. Therefore, the 4-year FP7-project CLIMB (Climate induced changes on the hydrology of Mediterranean basins, GA: 244151) includes a major focus on the assessment and quantification of uncertainties. First, CLIMB employs a rigorous climate change model analysis, auditing the Global and Regional Climate Model data available through the ENSEMBLES and PRUDENCE initiatives. The audits lead to select the best regional performers as compared to observed values during the climatic reference period (1971- 2000). Specific bias correction and downscaling procedures are applied to provide the driving inputs and meet the demands of the subsequent impact models, transferring a future climate signal (2041-2070) into hydrological quantities at the catchment or landscape scale. However, very limited quantitative knowledge is as yet available about the role of hydrological model complexity for climate change impact assessment, where predictive power becomes more and more important and raises the demand for process-based and spatially explicit model types. Thus, CLIMB uses hydrological model ensembles to analyze the performance of existing models and works to identify the appropriate level of model complexity, and thus to determine the data specifications required to provide robust results in a climate change context. The presentation focuses on the CLIMB multi-level strategy to uncertainty assessment and highlights latest findings in some of the seven CLIMB case studies. In particular, the presentation will demonstrate the current constraints of hydro-meteorological data availability and processing and searches for solutions that can eventually be provided by integrating hydro-meteorology and ICT research communities.

Evaluation of Land Suitability and Potential Production of Gambir Uncaria gambir Roxb. L) at Salido Saribulan, Pesisir Selatan Regency

NASA Astrophysics Data System (ADS)

Yuni, Juniarti

2017-04-01

Gambir (Uncaria gambir Roxb. L) is a specific commodity of export in West Sumatra. Area of Gambir tree increases about 8 % per year in West Sumatera and until 1998 its production increased about 17% per year. However, in 1999 its area does not parallel with its production. In the last five years, the volume of export increases about 82.81%, while its value of export reaches US 2.5/kg. Therefore, this commodity has a strategic value for city's earnings. One of predicted causes is the use of unappropriated land. The aim of this research is to measure levels of land suitability in the buffer zone. TNKS (The National Park Kerinci-Seblat) in order to get the area, which is suitable for growing commodity of Gambir tree. To evaluate land suitability, quantitative model from FAO is used by combining environmental data, climate and condition of land (physical and chemical characteristic of the land). Estimation of Radiation Thermal Production Potential (RPP). Every data is measured (rating) individually and included in several mathematical formulas. After that, potential production of a land based on climate (Climate Production Potential) = CPP) is obtained quantitatively. By changing certain variant of this model program, it can predict the result of the plant in another area. By entering the real data of a land plant production, this model can predict the real plant production of land (Land Production Potential= LPP). Salido Saribulan area is included in class of land suitability S3f which is suitable for growing Gambir tree with a limitation factor of nutrient retention. Potential of actual gambir production at Salido Saribulan is 5 ton/ha, which is higher than actual gambir production.

A quantitative evaluation of ethylene production in the recombinant cyanobacterium Synechocystis sp. PCC 6803 harboring the ethylene-forming enzyme by membrane inlet mass spectrometry.

PubMed

Zavřel, Tomáš; Knoop, Henning; Steuer, Ralf; Jones, Patrik R; Červený, Jan; Trtílek, Martin

2016-02-01

The prediction of the world's future energy consumption and global climate change makes it desirable to identify new technologies to replace or augment fossil fuels by environmentally sustainable alternatives. One appealing sustainable energy concept is harvesting solar energy via photosynthesis coupled to conversion of CO2 into chemical feedstock and fuel. In this work, the production of ethylene, the most widely used petrochemical produced exclusively from fossil fuels, in the model cyanobacterium Synechocystis sp. PCC 6803 is studied. A novel instrumentation setup for quantitative monitoring of ethylene production using a combination of flat-panel photobioreactor coupled to a membrane-inlet mass spectrometer is introduced. Carbon partitioning is estimated using a quantitative model of cyanobacterial metabolism. The results show that ethylene is produced under a wide range of light intensities with an optimum at modest irradiances. The results allow production conditions to be optimized in a highly controlled setup. Copyright © 2015 Elsevier Ltd. All rights reserved.

Unraveling past impacts of climate change and land management on historic peatland development using proxy-based reconstruction, monitoring data and process modeling.

PubMed

Heinemeyer, Andreas; Swindles, Graeme T

2018-05-08

Peatlands represent globally significant soil carbon stores that have been accumulating for millennia under water-logged conditions. However, deepening water-table depths (WTD) from climate change or human-induced drainage could stimulate decomposition resulting in peatlands turning from carbon sinks to carbon sources. Contemporary WTD ranges of testate amoebae (TA) are commonly used to predict past WTD in peatlands using quantitative transfer function models. Here we present, for the first time, a study comparing TA-based WTD reconstructions to instrumentally monitored WTD and hydrological model predictions using the MILLENNIA peatland model to examine past peatland responses to climate change and land management. Although there was very good agreement between monitored and modeled WTD, TA-reconstructed water table was consistently deeper. Predictions from a larger European TA transfer function data set were wetter, but the overall directional fit to observed WTD was better for a TA transfer function based on data from northern England. We applied a regression-based offset correction to the reconstructed WTD for the validation period (1931-2010). We then predicted WTD using available climate records as MILLENNIA model input and compared the offset-corrected TA reconstruction to MILLENNIA WTD predictions over an extended period (1750-1931) with available climate reconstructions. Although the comparison revealed striking similarities in predicted overall WTD patterns, particularly for a recent drier period (1965-1995), there were clear periods when TA-based WTD predictions underestimated (i.e. drier during 1830-1930) and overestimated (i.e. wetter during 1760-1830) past WTD compared to MILLENNIA model predictions. Importantly, simulated grouse moor management scenarios may explain the drier TA WTD predictions, resulting in considerable model predicted carbon losses and reduced methane emissions, mainly due to drainage. This study demonstrates the value of a site-specific and combined data-model validation step toward using TA-derived moisture conditions to understand past climate-driven peatland development and carbon budgets alongside modeling likely management impacts. © 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

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.

Climate change, humans, and the extinction of the woolly mammoth.

PubMed

Nogués-Bravo, David; Rodríguez, Jesús; Hortal, Joaquín; Batra, Persaram; Araújo, Miguel B

2008-04-01

Woolly mammoths inhabited Eurasia and North America from late Middle Pleistocene (300 ky BP [300,000 years before present]), surviving through different climatic cycles until they vanished in the Holocene (3.6 ky BP). The debate about why the Late Quaternary extinctions occurred has centred upon environmental and human-induced effects, or a combination of both. However, testing these two hypotheses-climatic and anthropogenic-has been hampered by the difficulty of generating quantitative estimates of the relationship between the contraction of the mammoth's geographical range and each of the two hypotheses. We combined climate envelope models and a population model with explicit treatment of woolly mammoth-human interactions to measure the extent to which a combination of climate changes and increased human pressures might have led to the extinction of the species in Eurasia. Climate conditions for woolly mammoths were measured across different time periods: 126 ky BP, 42 ky BP, 30 ky BP, 21 ky BP, and 6 ky BP. We show that suitable climate conditions for the mammoth reduced drastically between the Late Pleistocene and the Holocene, and 90% of its geographical range disappeared between 42 ky BP and 6 ky BP, with the remaining suitable areas in the mid-Holocene being mainly restricted to Arctic Siberia, which is where the latest records of woolly mammoths in continental Asia have been found. Results of the population models also show that the collapse of the climatic niche of the mammoth caused a significant drop in their population size, making woolly mammoths more vulnerable to the increasing hunting pressure from human populations. The coincidence of the disappearance of climatically suitable areas for woolly mammoths and the increase in anthropogenic impacts in the Holocene, the coup de grâce, likely set the place and time for the extinction of the woolly mammoth.

Terrestrial Feedbacks Incorporated in Global Vegetation Models through Observed Trait-Environment Responses

NASA Astrophysics Data System (ADS)

Bodegom, P. V.

2015-12-01

Most global vegetation models used to evaluate climate change impacts rely on plant functional types to describe vegetation responses to environmental stresses. In a traditional set-up in which vegetation characteristics are considered constant within a vegetation type, the possibility to implement and infer feedback mechanisms are limited as feedback mechanisms will likely involve a changing expression of community trait values. Based on community assembly concepts, we implemented functional trait-environment relationships into a global dynamic vegetation model to quantitatively assess this feature. For the current climate, a different global vegetation distribution was calculated with and without the inclusion of trait variation, emphasizing the importance of feedbacks -in interaction with competitive processes- for the prevailing global patterns. These trait-environmental responses do, however, not necessarily imply adaptive responses of vegetation to changing conditions and may locally lead to a faster turnover in vegetation upon climate change. Indeed, when running climate projections, simulations with trait variation did not yield a more stable or resilient vegetation than those without. Through the different feedback expressions, global and regional carbon and water fluxes were -however- strongly altered. At a global scale, model projections suggest an increased productivity and hence an increased carbon sink in the next decades to come, when including trait variation. However, by the end of the century, a reduced carbon sink is projected. This effect is due to a downregulation of photosynthesis rates, particularly in the tropical regions, even when accounting for CO2-fertilization effects. Altogether, the various global model simulations suggest the critical importance of including vegetation functional responses to changing environmental conditions to grasp terrestrial feedback mechanisms at global scales in the light of climate change.

Assessing Extratropical Influence on Tropical Climatology and Variability with Regional Coupled Data Assimilation

NASA Astrophysics Data System (ADS)

Lu, F.; Liu, Z.; Liu, Y.; Zhang, S.; Jacob, R. L.

2017-12-01

The Regional Coupled Data Assimilation (RCDA) method is introduced as a tool to study coupled climate dynamics and teleconnections. The RCDA method is built on an ensemble-based coupled data assimilation (CDA) system in a coupled general circulation model (CGCM). The RCDA method limits the data assimilation to the desired model components (e.g. atmosphere) and regions (e.g. the extratropics), and studies the ensemble-mean model response (e.g. tropical response to "observed" extratropical atmospheric variability). When applied to the extratropical influence on tropical climate, the RCDA method has shown some unique advantages, namely the combination of a fully coupled model, real-world observations and an ensemble approach. Tropical variability (e.g. El Niño-Southern Oscillation or ENSO) and climatology (e.g. asymmetric Inter-Tropical Convergence Zone or ITCZ) were initially thought to be determined mostly by local forcing and ocean-atmosphere interaction in the tropics. Since late 20th century, numerous studies have showed that extratropical forcing could affect, or even largely determine some aspects of the tropical climate. Due to the coupled nature of the climate system, however, the challenge of determining and further quantifying the causality of extratropical forcing on the tropical climate remains. Using the RCDA method, we have demonstrated significant control of extratropical atmospheric forcing on ENSO variability in a CGCM, both with model-generated and real-world observation datasets. The RCDA method has also shown robust extratropical impact on the tropical double-ITCZ bias in a CGCM. The RCDA method has provided the first systematic and quantitative assessment of extratropical influence on tropical climatology and variability by incorporating real world observations in a CGCM.

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…

Topographic, latitudinal and climatic distribution of Pinus coulteri: geographic range limits are not at the edge of the climate envelope

USGS Publications Warehouse

Chardon, Nathalie I.; Cornwell, William K.; Flint, Lorraine E.; Flint, Alan L.; Ackerly, David D.

2015-01-01

With changing climate, many species are projected to move poleward or to higher elevations to track suitable climates. The prediction that species will move poleward assumes that geographically marginal populations are at the edge of the species' climatic range. We studied Pinus coulteri from the center to the northern (poleward) edge of its range, and examined three scenarios regarding the relationship between the geographic and climatic margins of a species' range. We used herbarium and iNaturalist.org records to identify P. coulteri sites, generated a species distribution model based on temperature, precipitation, climatic water deficit, and actual evapotranspiration, and projected suitability under future climate scenarios. In fourteen populations from the central to northern portions of the range, we conducted field studies and recorded elevation, slope and aspect (to estimate solar insolation) to examine relationships between local and regional distributions. We found that northern populations of P. coulteri do not occupy the cold or wet edge of the species' climatic range; mid-latitude, high elevation populations occupy the cold margin. Aspect and insolation of P. coulteri populations changed significantly across latitudes and elevations. Unexpectedly, northern, low-elevation stands occupy north-facing aspects and receive low insolation, while central, high-elevation stands grow on more south-facing aspects that receive higher insolation. Modeled future climate suitability is projected to be highest in the central, high elevation portion of the species range, and in low-lying coastal regions under some scenarios, with declining suitability in northern areas under most future scenarios. For P. coulteri, the lack of high elevation habitat combined with a major dispersal barrier may limit northward movement in response to a warming climate. Our analyses demonstrate the importance of distinguishing geographically vs. climatically marginal populations, and the importance of quantitative analysis of the realized climate space to understand species range limits.

Morphological Inheritance in Sandy Coastline Morphologies Subject to Long-Term Changes in Wave Climate: Surprising Insights from a Coastline Evolution Model

NASA Astrophysics Data System (ADS)

Murray, A. B.; Thomas, C.; Hurst, M. D.; Barkwith, A.; Ashton, A. D.; Ellis, M. A.

2014-12-01

Recent numerical modelling demonstrates that when sandy coastlines are affected predominantly by waves approaching from "high" angles (> ~45° between the coastline and wave crests at the offshore limit of shore-parallel contours), large-scale (kms to 100 kms) morphodynamic instabilities and finite-amplitude interactions can lead to the emergence of striking coastline features, including sand waves, capes and spits. The type of feature that emerges depends on the wave climate, defined as the angular distribution of wave influences on alongshore sediment transport. Under a constant wave climate, coastline morphology reaches a dynamical steady state; the cross-shore/alongshore aspect ratio and the general appearance of the features remains constant. In previous modelling involving wave-climate change, as well as comparisons between observed coastline morphologies and wave climates, it has been implicitly assumed that the morphology adjusts in a quasi-equilibrium fashion, so that at any time the coastline shape reflects the current forcing. However, here we present new model results showing pronounced path dependence in coastline morphodynamics. In experiments with a period of constant wave climate followed by a period of transition to a new wave climate and then a run-on phase, the features that exist during the run-on phase can be qualitatively and quantitatively different from those that would develop initially under the final wave climate. Although the features inherited from the past wave-climate history may in some case be true alternate stable states, in other cases the inherited features gradually decay toward the morphology that would be expected given the final wave climate. A suite of such experiments allows us to characterize how the e-folding timescale of this decay depends on 1) the initial wave climate, 2) the path through wave-climate space, and 3) the rate of transition. When the initial features are flying spits with cross-shore amplitudes of 6 - 8 km, e-folding times can be on the order of millennia or longer. These results could provide a new perspective when interpreting current and past coastline features. In addition, the complex paleo-coastline structure that develops in the coastal hinterlands in these experiments could be relevant to the structures observed in some coastal environments.

Quantifying the Climate Impacts of Land Use Change (Invited)

NASA Astrophysics Data System (ADS)

Anderson-Teixeira, K. J.; Snyder, P. K.; Twine, T. E.

2010-12-01

Climate change mitigation efforts that involve land use decisions call for comprehensive quantification of the climate services of terrestrial ecosystems. This is particularly imperative for analyses of the climate impact of bioenergy production, as land use change is often the single most important factor in determining bioenergy’s sustainability. However, current metrics of the climate services of terrestrial ecosystems used for policy applications—including biofuels life cycle analyses—account only for biogeochemical climate services (greenhouse gas regulation), ignoring biophysical climate regulation services (regulation of water and energy balances). Policies thereby run the risk of failing to advance the best climate solutions. Here, we present a quantitative metric that combines biogeochemical and biophysical climate services of terrestrial ecosystems, the ‘climate regulation value’ (CRV), which characterizes the climate benefit of maintaining an ecosystem over a multiple-year time frame. Using a combination of data synthesis and modeling, we calculate the CRV for a variety of natural and managed ecosystem types within the western hemisphere. Biogeochemical climate services are generally positive in unmanaged ecosystems (clearing the ecosystem has a warming effect), and may be positive or negative (clearing the ecosystem has a cooling effect) for managed ecosystems. Biophysical climate services may be either positive (e.g., tropical forests) or negative (e.g., high latitude forests). When averaged on a global scale, biogeochemical services usually outweigh biophysical services; however, biophysical climate services are not negligible. This implies that effective analysis of the climate impacts of bioenergy production must consider the integrated effects of biogeochemical and biophysical ecosystem climate services.

Olive cultivars adaptability in Southern Italy in present and future climate

NASA Astrophysics Data System (ADS)

Riccardi, M.; Alfieri, S.; Bonfante, A.; Basile, A.; Di Tommasi, P.; Menenti, M.; De Lorenzi, F.

2012-04-01

The intra-specific biodiversity of agricultural crops is very significant and likely to provide the single major opportunity to cope with the effects of the changing climate on agricultural ecosystems. Assessment of adaptive capacity must rely on quantitative descriptions of plant responses to environmental factors (e.g. soil water availability, temperature). Moreover climate scenario needs to be downscaled to the spatial scale relevant to crop and farm management. Distributed models of crop response to environmental forcing might be used for this purpose, but severely constrained by the very scarce knowledge on variety-specific values of model parameters, thus limiting the potential exploitation of intra-specific biodiversity towards adaptation. We have developed an approach towards this objective that relies on two complementary elements: a)a distributed model of the soil plant atmosphere system to downscale climate scenarios to landscape units, where generic model parameters for each species are used; b)a data base on climatic requirements of as many varieties as feasible for each species relevant to the agricultural production system of a given region. By means of this approach, the adaptability of some olive cultivars was evaluated in a composite (hills and plains) area of Southern Italy (Valle Telesina, Campania Region, about 20.000 ha). The yearly average temperature is 22.5 °C and rainfall ranges between 600 and 900 mm. Two different climate scenarios were considered: current climate (1961-1990) and future climate (2021-2050). Future climate scenarios at low spatial resolution were generated with general circulation models (AOGCM) and down-scaled by means of a statistical model (Tomozeiu et al., 2007). The climate was represented by daily observations of minimum, maximum temperature and precipitation on a regular grid with a spatial resolution of 35 km; 50 realizations were used for future climate. The soil water regime of 45 soil units was described for the two climate scenarios by using an hydrological distributed model (SWAP). For 11 olive cultivars, the yield response function to soil water regime was determined through the re-analysis of experimental data (unpublished or derived from scientific literature). According to these responses, cultivar-specific threshold values of soil water (or evapotranspiration) deficit were defined. The soil water regime calculated by the distributed model was compared with the threshold values to identify cultivars compatible with present and expected climates. The operation is repeated for a set of realizations of each climate scenario. This analysis is performed in a distributed manner, i.e. using the time series for each model grid to assess possible variations in the extent and spatial distribution of cultivated area of olive cultivars. In the study area future climate scenarios predict an increase of monthly minimum and maximum air temperature of about 2°C during the summer (June, July and August) and a reduction of rainfall in autumn. Spatial pattern of cultivars distribution, according their threshold values and soil water regime, was determined in the present and future climate scenarios, thus assessing variations in cultivars adaptability to future climate with respect to the present. Key words: climate change, biodiversity, water availability, yield response. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008).

Effects of global changes on the climatic niche of the tick Ixodes ricinus inferred by species distribution modelling.

PubMed

Porretta, Daniele; Mastrantonio, Valentina; Amendolia, Sara; Gaiarsa, Stefano; Epis, Sara; Genchi, Claudio; Bandi, Claudio; Otranto, Domenico; Urbanelli, Sandra

2013-09-19

Global climate change can seriously impact on the epidemiological dynamics of vector-borne diseases. In this study we investigated how future climatic changes could affect the climatic niche of Ixodes ricinus (Acari, Ixodida), among the most important vectors of pathogens of medical and veterinary concern in Europe. Species Distribution Modelling (SDM) was used to reconstruct the climatic niche of I. ricinus, and to project it into the future conditions for 2050 and 2080, under two scenarios: a continuous human demographic growth and a severe increase of gas emissions (scenario A2), and a scenario that proposes lower human demographic growth than A2, and a more sustainable gas emissions (scenario B2). Models were reconstructed using the algorithm of "maximum entropy", as implemented in the software Maxent 3.3.3e; 4,544 occurrence points and 15 bioclimatic variables were used. In both scenarios an increase of climatic niche of about two times greater than the current area was predicted as well as a higher climatic suitability under the scenario B2 than A2. Such an increase occurred both in a latitudinal and longitudinal way, including northern Eurasian regions (e.g. Sweden and Russia), that were previously unsuitable for the species. Our models are congruent with the predictions of range expansion already observed in I. ricinus at a regional scale and provide a qualitative and quantitative assessment of the future climatically suitable areas for I. ricinus at a continental scale. Although the use of SDM at a higher resolution should be integrated by a more refined analysis of further abiotic and biotic data, the results presented here suggest that under future climatic scenarios most of the current distribution area of I. ricinus could remain suitable and significantly increase at a continental geographic scale. Therefore disease outbreaks of pathogens transmitted by this tick species could emerge in previous non-endemic geographic areas. Further studies will implement and refine present data toward a better understanding of the risk represented by I. ricinus to human health.

The PMIP4 contribution to CMIP6 - Part 2: Two interglacials, scientific objective and experimental design for Holocene and Last Interglacial simulations

NASA Astrophysics Data System (ADS)

Otto-Bliesner, Bette L.; Braconnot, Pascale; Harrison, Sandy P.; Lunt, Daniel J.; Abe-Ouchi, Ayako; Albani, Samuel; Bartlein, Patrick J.; Capron, Emilie; Carlson, Anders E.; Dutton, Andrea; Fischer, Hubertus; Goelzer, Heiko; Govin, Aline; Haywood, Alan; Joos, Fortunat; LeGrande, Allegra N.; Lipscomb, William H.; Lohmann, Gerrit; Mahowald, Natalie; Nehrbass-Ahles, Christoph; Pausata, Francesco S. R.; Peterschmitt, Jean-Yves; Phipps, Steven J.; Renssen, Hans; Zhang, Qiong

2017-11-01

Two interglacial epochs are included in the suite of Paleoclimate Modeling Intercomparison Project (PMIP4) simulations in the Coupled Model Intercomparison Project (CMIP6). The experimental protocols for simulations of the mid-Holocene (midHolocene, 6000 years before present) and the Last Interglacial (lig127k, 127 000 years before present) are described here. These equilibrium simulations are designed to examine the impact of changes in orbital forcing at times when atmospheric greenhouse gas levels were similar to those of the preindustrial period and the continental configurations were almost identical to modern ones. These simulations test our understanding of the interplay between radiative forcing and atmospheric circulation, and the connections among large-scale and regional climate changes giving rise to phenomena such as land-sea contrast and high-latitude amplification in temperature changes, and responses of the monsoons, as compared to today. They also provide an opportunity, through carefully designed additional sensitivity experiments, to quantify the strength of atmosphere, ocean, cryosphere, and land-surface feedbacks. Sensitivity experiments are proposed to investigate the role of freshwater forcing in triggering abrupt climate changes within interglacial epochs. These feedback experiments naturally lead to a focus on climate evolution during interglacial periods, which will be examined through transient experiments. Analyses of the sensitivity simulations will also focus on interactions between extratropical and tropical circulation, and the relationship between changes in mean climate state and climate variability on annual to multi-decadal timescales. The comparative abundance of paleoenvironmental data and of quantitative climate reconstructions for the Holocene and Last Interglacial make these two epochs ideal candidates for systematic evaluation of model performance, and such comparisons will shed new light on the importance of external feedbacks (e.g., vegetation, dust) and the ability of state-of-the-art models to simulate climate changes realistically.

Estimating effects of tidal power projects and climate change on threatened and endangered marine species and their food web.

PubMed

Busch, D Shallin; Greene, Correigh M; Good, Thomas P

2013-12-01

Marine hydrokinetic power projects will operate as marine environments change in response to increased atmospheric carbon dioxide concentrations. We considered how tidal power development and stressors resulting from climate change may affect Puget Sound species listed under the U.S. Endangered Species Act (ESA) and their food web. We used risk tables to assess the singular and combined effects of tidal power development and climate change. Tidal power development and climate change posed risks to ESA-listed species, and risk increased with incorporation of the effects of these stressors on predators and prey of ESA-listed species. In contrast, results of a model of strikes on ESA-listed species from turbine blades suggested that few ESA-listed species are likely to be killed by a commercial-scale tidal turbine array. We applied scenarios to a food web model of Puget Sound to explore the effects of tidal power and climate change on ESA-listed species using more quantitative analytical techniques. To simulate development of tidal power, we applied results of the blade strike model. To simulate environmental changes over the next 50 years, we applied scenarios of change in primary production, plankton community structure, dissolved oxygen, ocean acidification, and freshwater flooding events. No effects of tidal power development on ESA-listed species were detected from the food web model output, but the effects of climate change on them and other members of the food web were large. Our analyses exemplify how natural resource managers might assess environmental effects of marine technologies in ways that explicitly incorporate climate change and consider multiple ESA-listed species in the context of their ecological community. Estimación de los Efectos de Proyectos de Energía de las Mareas y el Cambio Climático sobre Especies Marinas Amenazadas y en Peligro y su Red Alimentaria. © 2013 Society for Conservation Biology No claim to original US government works.

Impact of climate change on river discharge in the Teteriv River basin (Ukraine)

NASA Astrophysics Data System (ADS)

Didovets, Iulii; Lobanova, Anastasia; Krysanova, Valentina; Snizhko, Sergiy; Bronstert, Axel

2016-04-01

The problem of water resources availability in the climate change context arises now in many countries. Ukraine is characterized by a relatively low availability of water resources compared to other countries. It is the 111th among 152 countries by the amount of domestic water resources available per capita. To ensure socio-economic development of the region and to adapt to climate change, a comprehensive assessment of potential changes in qualitative and quantitative characteristics of water resources in the region is needed. The focus of our study is the Teteriv River basin located in northern Ukraine within three administrative districts covering the area of 15,300 km2. The Teteriv is the right largest tributary of the Dnipro River, which is the fourth longest river in Europe. The water resources in the region are intensively used in industry, communal infrastructure, and agriculture. This is evidenced by a large number of dams and industrial objects which have been constructed from the early 20th century. For success of the study, it was necessary to apply a comprehensive hydrological model, tested in similar natural conditions. Therefore, an eco-hydrological model SWIM with the daily time step was applied, as this model was used previously for climate impact assessment in many similar river basins on the European territory. The model was set up, calibrated and validated for the gauge Ivankiv located close to the outlet of the Teteriv River. The Nash-Sutcliffe efficiency coefficient for the calibration period is 0.79 (0.86), and percent bias is 4,9% (-3.6%) with the daily (monthly) time step. The future climate scenarios were selected from the IMPRESSIONS (Impacts and Risks from High-End Scenarios: Strategies for Innovative Solutions, www.impressions-project.eu) project, which developed 7 climate scenarios under RCP4.5 and RCP8.5 based on GCMs and downscaled using RCMs. The results of climate impact assessment for the Teteriv River basin will be presented.

Impact of Emissions and Long-Range Transport on Multi-Decadal Aerosol Trends: Implications for Air Quality and Climate

NASA Technical Reports Server (NTRS)

Chin, Mian

2012-01-01

We present a global model analysis of the impact of long-range transport and anthropogenic emissions on the aerosol trends in the major pollution regions in the northern hemisphere and in the Arctic in the past three decades. We will use the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model to analyze the multi-spatial and temporal scale data, including observations from Terra, Aqua, and CALIPSO satellites and from the long-term surface monitoring stations. We will analyze the source attribution (SA) and source-receptor (SR) relationships in North America, Europe, East Asia, South Asia, and the Arctic at the surface and free troposphere and establish the quantitative linkages between emissions from different source regions. We will discuss the implications for regional air quality and climate change.

A Framework for Prioritizing NOAA's Climate Data Portfolio to Improve Relevance and Value

NASA Astrophysics Data System (ADS)

Privette, J. L.; Hutchins, C.; McPherson, T.; Wunder, D.

2016-12-01

NOAA's National Centers for Environmental Information (NCEI) is the largest civilian environmental data archive in the world. NCEI operationally provides hundreds of long term homogeneous climate data records and assessments that describe Earth's atmosphere, oceans and land surface. For decades, these data have underpinned leading climate research and modeling efforts and provided key insights into weather and climate changes. Recently, NCEI has increased support for economic and societal sectors beyond climate research by emphasizing use-inspired product development and services. Accordingly, NCEI has begun comprehensively assessing customer needs and user applications. In parallel, NCEI is analyzing and adjusting its full product portfolio to best address those needs and applications. In this presentation, we will describe NCEI's new approaches to capturing needs, performing use analytics, and molding a more responsive portfolio. We will summarize the findings of a quantitative relevance- and cost-scoring analysis that suggests the relative effectiveness of NCEI science and service investments. Finally, we will describe NCEI's effort to review, document and validate customer-driven product requirements. Results will help guide future prioritization of measurements, research and development, and product services.

A multi-disciplinary approach for the integrated assessment of water alterations under climate change

NASA Astrophysics Data System (ADS)

Sperotto, Anna; Torresan, Silvia; Molina, Jose Luis; Pulido Velazquez, Manuel; Critto, Andrea; Marcomini, Antonio

2017-04-01

Understanding the co-evolution and interrelations between natural and human pressures on water systems is required to ensure a sustainable management of resources under uncertain climate change conditions. To pursue multi-disciplinary research is therefore necessary to consider the multiplicity of stressors affecting water resources, take into account alternative perspectives (i.e. social, economic and environmental objective and priorities) and deal with uncertainty which characterize climate change scenarios. However, approaches commonly adopted in water quality assessment are predominantly mono-disciplinary, single-stressors oriented and apply concepts and models specific of different academic disciplines (e.g. physics, hydrology, ecology, sociology, economy) which, in fact, seldom shed their conceptual blinders failing to provide truly integrated results. In this context, the paper discusses the benefits and limits of adopting a multi-disciplinary approach where different knowledge domains collaborate and quantitative and qualitative information, coming from multiple conceptual and model-based research, are integrated in a harmonic manner. Specifically, Bayesian Networks are used as meta-modelling tool for structuring and combining the probabilistic information available in existing hydrological models, climate change and land use projections, historical observations and expert opinion. The developed network allows to perform a stochastic multi-risk assessment considering the interlacing between climate (i.e. irregularities in water regime) and land use changes (i.e. agriculture, urbanization) and their cascading impacts on water quality parameters (i.e. nutrients loadings). Main objective of the model is the development of multi-risk scenarios to assess and communicate the probability of not meeting a "Good chemical water status" over future timeframe taking into account projected climatic and not climatic conditions. The outcomes are finally used to identify tradeoffs between different water uses and perspectives, thus promoting the implementation of best practices for adaptation and management with ancillary co-benefits and cross-sectoral implications (i.e. tourism, fishing, biodiversity). Some preliminary results, describing the application of the model in the Dese-Zero river estuary, one of the main tributaries of the Venice Lagoon in Italy, will be here presented and discussed.

A quantitative assessment of the contributions of climatic indicators to changes in nutrients and oxygen levels in a shallow reservoir in China

NASA Astrophysics Data System (ADS)

Zhang, Chen; Zhang, Wenna; Liu, Hanan; Gao, Xueping; Huang, Yixuan

2017-06-01

Climate change has an indirect effect on water quality in freshwater ecosystems, but it is difficult to assess the contribution of climate change to the complex system. This study explored to what extent climatic indicators (air temperature, wind speed, and rainfall) influence nutrients and oxygen levels in a shallow reservoir, Yuqiao Reservoir, China. The study comprises three parts—describing the temporal trends of climatic indicators and water quality parameters during the period 1992-2011, analyzing the potential impacts of climate on water quality, and finally developing a quantitative assessment to evaluate how climatic factors govern nutrient levels in the reservoir. Our analyses showed that the reservoir experienced substantial cold periods (1992-2001) followed by a warm period (2002-2011). The results showed that increasing air temperature in spring, autumn, and winter and increasing annual wind speed decrease total phosphorus (TP) concentration in the reservoir in spring, summer, and winter. According to the quantitative assessment, the increase in air temperature in spring and winter had a larger contribution to the decrease in TP concentration (47.2 and 64.1%), compared with the influence from decreased wind speed and rainfall. The field data suggest that nutrients decline due to enhanced uptake by macrophytes in years when spring was warmer and the macrophytes started to grow earlier in the season. The increasing wind speed and air temperature in spring also significantly contribute to the increase in dissolved oxygen concentration. This study helps managers to foresee how potential future climate change might influence water quality in similar lake ecosystems.

Middle Holocene humidity increase in Florida: climate or sea-level?

NASA Astrophysics Data System (ADS)

Donders, Timme H.

2014-11-01

Florida climate in highly sensitive to both high and low latitude climate perturbations due to its latitudinal position surrounded by water masses that transport heat northward. A well-studied aspect is that middle Holocene conditions became significantly wetter in Florida, initiating widespread peat accumulation in the Everglades. This environmental change has been attributed to various climate forcings, such as migration of the Intertropical Convergence Zone (ITCZ), increases in tropical storm intensity, position of the Bermuda High, intensification of the El Niño Southern Oscillation (ENSO), and post glacial sea level rise (SLR). Discerning between these forcings is only possible with quantitative reconstructions from a transect of sites that are affected differentially. Application of a transfer function on a north-to-south gradient of pollen records from Florida lakes here shows that the pattern of increasing precipitation during the middle Holocene cannot be explained by SLR, but that ENSO intensification is an important contributing factor. Seasonal-resolved proxy records with improved age models are urgently needed to further solve these issues.

Quasi-periodic climatic changes on Mars and earth

NASA Technical Reports Server (NTRS)

Cutts, J. A.; Pollack, J. B.; Toon, O. B.; Howard, A. D.

1981-01-01

Evidence of climatic changes on Mars and the earth due to geologic and astronomical variations is discussed. Finely striped ice-free bands in the Martian polar caps have been taken to indicate that long term variations in the orbit and axial tilt of Mars have precipitated these features at the rate of a mm/yr. Photogrammetric and photometric methods have contributed to measurements of the composition and depth of the Martian caps (14-46 m), and observations of higher solar energy absorption in the northern ice cap implies greater dust deposition in that region than on the south cap; however, the transport mechanisms are not well understood. Comparisons of earth and Martian climatic variations data are made, noting a lack of information on the age intervals of marine and nonmarine sediments on the earth. The possibilities of using quantitative data other than layer thickness to constrain climate models are discussed, and the slope or albedo of layers, or the spacing of polar undulations are suggested.

1,500 year quantitative reconstruction of winter precipitation in the Pacific Northwest

PubMed Central

Steinman, Byron A.; Abbott, Mark B.; Mann, Michael E.; Stansell, Nathan D.; Finney, Bruce P.

2012-01-01

Multiple paleoclimate proxies are required for robust assessment of past hydroclimatic conditions. Currently, estimates of drought variability over the past several thousand years are based largely on tree-ring records. We produced a 1,500-y record of winter precipitation in the Pacific Northwest using a physical model-based analysis of lake sediment oxygen isotope data. Our results indicate that during the Medieval Climate Anomaly (MCA) (900–1300 AD) the Pacific Northwest experienced exceptional wetness in winter and that during the Little Ice Age (LIA) (1450–1850 AD) conditions were drier, contrasting with hydroclimatic anomalies in the desert Southwest and consistent with climate dynamics related to the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). These findings are somewhat discordant with drought records from tree rings, suggesting that differences in seasonal sensitivity between the two proxies allow a more compete understanding of the climate system and likely explain disparities in inferred climate trends over centennial timescales. PMID:22753510

An improved ENSO simulation by representing chlorophyll-induced climate feedback in the NCAR Community Earth System Model.

PubMed

Kang, Xianbiao; Zhang, Rong-Hua; Gao, Chuan; Zhu, Jieshun

2017-12-07

The El Niño-Southern oscillation (ENSO) simulated in the Community Earth System Model of the National Center for Atmospheric Research (NCAR CESM) is much stronger than in reality. Here, satellite data are used to derive a statistical relationship between interannual variations in oceanic chlorophyll (CHL) and sea surface temperature (SST), which is then incorporated into the CESM to represent oceanic chlorophyll -induced climate feedback in the tropical Pacific. Numerical runs with and without the feedback (referred to as feedback and non-feedback runs) are performed and compared with each other. The ENSO amplitude simulated in the feedback run is more accurate than that in the non-feedback run; quantitatively, the Niño3 SST index is reduced by 35% when the feedback is included. The underlying processes are analyzed and the results show that interannual CHL anomalies exert a systematic modulating effect on the solar radiation penetrating into the subsurface layers, which induces differential heating in the upper ocean that affects vertical mixing and thus SST. The statistical modeling approach proposed in this work offers an effective and economical way for improving climate simulations.

Improving ecophysiological simulation models to predict the impact of elevated atmospheric CO2 concentration on crop productivity

PubMed Central

Yin, Xinyou

2013-01-01

Background Process-based ecophysiological crop models are pivotal in assessing responses of crop productivity and designing strategies of adaptation to climate change. Most existing crop models generally over-estimate the effect of elevated atmospheric [CO2], despite decades of experimental research on crop growth response to [CO2]. Analysis A review of the literature indicates that the quantitative relationships for a number of traits, once expressed as a function of internal plant nitrogen status, are altered little by the elevated [CO2]. A model incorporating these nitrogen-based functional relationships and mechanisms simulated photosynthetic acclimation to elevated [CO2], thereby reducing the chance of over-estimating crop response to [CO2]. Robust crop models to have small parameterization requirements and yet generate phenotypic plasticity under changing environmental conditions need to capture the carbon–nitrogen interactions during crop growth. Conclusions The performance of the improved models depends little on the type of the experimental facilities used to obtain data for parameterization, and allows accurate projections of the impact of elevated [CO2] and other climatic variables on crop productivity. PMID:23388883

Spatiotemporal variation of the association between climate dynamics and HFRS outbreaks in Eastern China during 2005-2016 and its geographic determinants

PubMed Central

Wu, Jiaping; Cazelles, Bernard; Qian, Quan; Mu, Di; Wang, Yong; Yin, Wenwu; Zhang, Wenyi

2018-01-01

Background Hemorrhagic fever with renal syndrome (HFRS) is a rodent-associated zoonosis caused by hantavirus. The HFRS was initially detected in northeast China in 1931, and since 1955 it has been detected in many regions of the country. Global climate dynamics influences HFRS spread in a complex nonlinear way. The quantitative assessment of the spatiotemporal variation of the “HFRS infections-global climate dynamics” association at a large geographical scale and during a long time period is still lacking. Methods and findings This work is the first study of a recently completed dataset of monthly HFRS cases in Eastern China during the period 2005–2016. A methodological synthesis that involves a time-frequency technique, a composite space-time model, hotspot analysis, and machine learning is implemented in the study of (a) the association between HFRS incidence spread and climate dynamics and (b) the geographic factors impacting this association over Eastern China during the period 2005–2016. The results showed that by assimilating core and city-specific knowledge bases the synthesis was able to depict quantitatively the space-time variation of periodic climate-HFRS associations at a large geographic scale and to assess numerically the strength of this association in the area and period of interest. It was found that the HFRS infections in Eastern China has a strong association with global climate dynamics, in particular, the 12, 18 and 36 mos periods were detected as the three main synchronous periods of climate dynamics and HFRS distribution. For the 36 mos period (which is the period with the strongest association), the space-time correlation pattern of the association strength indicated strong temporal but rather weak spatial dependencies. The generated space-time maps of association strength and association hotspots provided a clear picture of the geographic variation of the association strength that often-exhibited cluster characteristics (e.g., the south part of the study area displays a strong climate-HFRS association with non-point effects, whereas the middle-north part displays a weak climate-HFRS association). Another finding of this work is the upward climate-HFRS coherency trend for the past few years (2013–2015) indicating that the climate impacts on HFRS were becoming increasingly sensitive with time. Lastly, another finding of this work is that geographic factors affect the climate-HFRS association in an interrelated manner through local climate or by means of HFRS infections. In particular, location (latitude, distance to coastline and longitude), grassland and woodland are the geographic factors exerting the most noticeable effects on the climate-HFRS association (e.g., low latitude has a strong effect, whereas distance to coastline has a wave-like effect). Conclusions The proposed synthetic quantitative approach revealed important aspects of the spatiotemporal variation of the climate-HFRS association in Eastern China during a long time period, and identified the geographic factors having a major impact on this association. Both findings could improve public health policy in an HFRS-torn country like China. Furthermore, the synthetic approach developed in this work can be used to map the space-time variation of different climate-disease associations in other parts of China and the World. PMID:29874263

Assisted migration of forest populations for adapting trees to climate change

Treesearch

Cuauhtémoc Sáenz-Romero; Roberto A. Lindig-Cisneros; Dennis G. Joyce; Jean Beaulieu; J. Bradley St. Clair; Barry C. Jaquish

2016-01-01

We present evidence that climatic change is an ongoing process and that forest tree populations are genetically differentiated for quantitative traits because of adaptation to specific habitats. We discuss in detail indications that the shift of suitable climatic habitat for forest tree species and populations, as a result of rapid climatic change, is likely to cause...

Chapter 14: The impacts of climate change on forestry

Treesearch

Linda A. Joyce

2007-01-01

The quantitative analysis of the impact of future climate change on forests and forestry began in the 1980s, motivated by research in the atmospheric sciences and concerns about the potential impacts of climate change on forest ecosystems. These analyses suggested that forest ecosystems would be seriously impacted by climate change, with consequent impacts on the...

Educators and the Quality of Their Work Environment: An Analysis of the Organisational Climate in Primary Schools

ERIC Educational Resources Information Center

Vos, D.; van der Westhuizen, Philip C.; Mentz, P. J.; Ellis, S. M.

2012-01-01

The prevalent organisational climate in primary schools in the North West Province was determined in order to formulate management strategies to increase the organisational climate. For this purpose, a quantitative research method, founded in post-positivistic points of departure, was applied. In the process, the Organizational Climate Description…

Predicting the responses of forest distribution and aboveground biomass to climate change under RCP scenarios in southern China.

PubMed

Dai, Erfu; Wu, Zhuo; Ge, Quansheng; Xi, Weimin; Wang, Xiaofan

2016-11-01

In the past three decades, our global climate has been experiencing unprecedented warming. This warming has and will continue to significantly influence the structure and function of forest ecosystems. While studies have been conducted to explore the possible responses of forest landscapes to future climate change, the representative concentration pathways (RCPs) scenarios under the framework of the Coupled Model Intercomparison Project Phase 5 (CMIP5) have not been widely used in quantitative modeling research of forest landscapes. We used LANDIS-II, a forest dynamic landscape model, coupled with a forest ecosystem process model (PnET-II), to simulate spatial interactions and ecological succession processes under RCP scenarios, RCP2.6, RCP4.5 and RCP8.5, respectively. We also modeled a control scenario of extrapolating current climate conditions to examine changes in distribution and aboveground biomass (AGB) among five different forest types for the period of 2010-2100 in Taihe County in southern China, where subtropical coniferous plantations dominate. The results of the simulation show that climate change will significantly influence forest distribution and AGB. (i) Evergreen broad-leaved forests will expand into Chinese fir and Chinese weeping cypress forests. The area percentages of evergreen broad-leaved forests under RCP2.6, RCP4.5, RCP8.5 and the control scenarios account for 18.25%, 18.71%, 18.85% and 17.46% of total forest area, respectively. (ii) The total AGB under RCP4.5 will reach its highest level by the year 2100. Compared with the control scenarios, the total AGB under RCP2.6, RCP4.5 and RCP8.5 increases by 24.1%, 64.2% and 29.8%, respectively. (iii) The forest total AGB increases rapidly at first and then decreases slowly on the temporal dimension. (iv) Even though the fluctuation patterns of total AGB will remain consistent under various future climatic scenarios, there will be certain responsive differences among various forest types. © 2016 John Wiley & Sons Ltd.

Tandem transmission/reflection mode XRD instrument including XRF for in situ measurement of Martian rocks and soils

NASA Astrophysics Data System (ADS)

Delhez, Robert; Van der Gaast, S. J.; Wielders, Arno; de Boer, J. L.; Helmholdt, R. B.; van Mechelen, J.; Reiss, C.; Woning, L.; Schenk, H.

2003-02-01

The mineralogy of the surface material of Mars is the key to disclose its present and past life and climates. Clay mineral species, carbonates, and ice (water and CO2) are and/or contain their witnesses. X-ray powder diffraction (XRPD) is the most powerful analytical method to identify and quantitatively characterize minerals in complex mixtures. This paper discusses the development of a working model of an instrument consisting of a reflection mode diffractometer and a transmission mode CCD-XRPD instrument, combined with an XRF module. The CCD-XRD/XRF instrument is analogous to the instrument for Mars missions developed by Sarrazin et al. (1998). This part of the tandem instrument enables "quick and dirty" analysis of powdered (!) matter to monitor semi-quantitatively the presence of clay minerals as a group, carbonates, and ices and yields semi-quantitative chemical information from X-ray fluorescence (XRF). The reflection mode instrument (i) enables in-situ measurements of rocks and soils and quantitative information on the compounds identified, (ii) has a high resolution and reveals large spacings for accurate identification, in particular of clay mineral species, and (iii) the shape of the line profiles observed reveals the kind and approximate amounts of lattice imperfections present. It will be shown that the information obtained with the reflection mode diffractometer is crucial for finding signs of life and changes in the climate on Mars. Obviously this instrument can also be used for other extra-terrestrial research.

Quantitative Metrics for Provenance in the Global Change Information System

NASA Astrophysics Data System (ADS)

Sherman, R. A.; Tipton, K.; Elamparuthy, A.

2017-12-01

The Global Change Information System (GCIS) is an open-source web-based resource to provide traceable provenance for government climate information, particularly the National Climate Assessment and other climate science reports from the U.S. Global Change Research Program. Since 2014, GCIS has been adding and updating information and linking records to make the system as complete as possible for the key reports. Our total count of records has grown to well over 20,000, but until recently there hasn't been an easy way to measure how well all those records were serving the mission of providing provenance. The GCIS team has recently established quantitative measures of whether each record has sufficient metadata and linkages to be useful for users of our featured climate reports. We will describe our metrics and show how they can be used to guide future development of GCIS and aid users of government climate data.

Combining Multidisciplinary Science, Quantitative Reasoning and Social Context to Teach Global Sustainability and Prepare Students for 21st Grand Challenges

NASA Astrophysics Data System (ADS)

Myers, J. D.

2011-12-01

The Earth's seven billion humans are consuming a growing proportion of the world's ecosystem products and services. Human activity has also wrought changes that rival the scale of many natural geologic processes, e.g. erosion, transport and deposition, leading to recognition of a new geological epoch, the Anthropocene. Because of these impacts, several natural systems have been pushed beyond the planetary boundaries that made the Holocene favorable for the expansion of humanity. Given these human-induced stresses on natural systems, global citizens will face an increasing number of grand challenges. Unfortunately, traditional discipline-based introductory science courses do little to prepare students for these complex, scientifically-based and technologically-centered challenges. With NSF funding, an introductory, integrated science course stressing quantitative reasoning and social context has been created at UW. The course (GEOL1600: Global Sustainability: Managing the Earth's Resources) is a lower division course designed around the energy-water-climate (EWC) nexus and integrating biology, chemistry, Earth science and physics. It melds lectures, lecture activities, reading questionnaires and labs to create a learning environment that examines the EWT nexus from a global through regional context. The focus on the EWC nexus, while important socially and intended to motivate students, also provides a coherent framework for identifying which disciplinary scientific principles and concepts to include in the course: photosynthesis and deep time (fossil fuels), biogeochemical cycles (climate), chemical reactions (combustion), electromagnetic radiation (solar power), nuclear physics (nuclear power), phase changes and diagrams (water and climate), etc. Lecture activities are used to give students the practice they need to make quantitative skills routine and automatic. Laboratory exercises on energy (coal, petroleum, nuclear power), water (in Bangladesh), energy production and water (shale gas hydrofracing and oil sand production) and climate (scientific modeling, carbon emission management) address EWC issues in international, national and regional contexts while reflecting the news headlines of the day.

Hydro-geomorphological characterization and classification of Chilean river networks using horizontal, vertical and climatological properties

NASA Astrophysics Data System (ADS)

Pereira, A. A.; Gironas, J. A.; Passalacqua, P.; Mejia, A.; Niemann, J. D.

2017-12-01

Previous work has shown that lithological, tectonic and climatic processes have a major influence in shaping the geomorphology of river networks. Accordingly, quantitative classification methods have been developed to identify and characterize network types (dendritic, parallel, pinnate, rectangular and trellis) based solely on the self-affinity of their planform properties, computed from available Digital Elevation Model (DEM) data. In contrast, this research aim is to include both horizontal and vertical properties to evaluate a quantitative classification method for river networks. We include vertical properties to consider the unique surficial conditions (e.g., large and steep height drops, volcanic activity, and complexity of stream networks) of the Andes Mountains. Furthermore, the goal of the research is also to explain the implications and possible relations between the hydro-geomorphological properties and climatic conditions. The classification method is applied to 42 basins in the southern Andes in Chile, ranging in size from 208 Km2 to 8,000 Km2. The planform metrics include the incremental drainage area, stream course irregularity and junction angles, while the vertical metrics include the hypsometric curve and the slope-area relationship. We introduce new network structures (Brush, Funnel and Low Sinuosity Rectangular), possibly unique to the Andes, that can be quantitatively differentiated from previous networks identified in other geographic regions. Then, this research evaluates the effect that excluding different Strahler order streams has on the horizontal properties and therefore in the classification. We found that climatic conditions are not only linked to horizontal parameters, but also to vertical ones, finding significant correlation between climatic variables (average near-surface temperature and rainfall) and vertical measures (parameters associated with the hypsometric curve and slope-area relation). The proposed classification shows differences among basins previously classified as the same type, which are not noticeable in their horizontal properties and helps reduce misclassifications within the old clusters. Additional hydro-geomorphological metrics are to be considered in the classification method to improve the effectiveness of it.

Effects of adjusting cropping systems on utilization efficiency of climatic resources in Northeast China under future climate scenarios

NASA Astrophysics Data System (ADS)

Guo, Jianping; Zhao, Junfang; Xu, Yanhong; Chu, Zheng; Mu, Jia; Zhao, Qian

Quantitatively evaluating the effects of adjusting cropping systems on the utilization efficiency of climatic resources under climate change is an important task for assessing food security in China. To understand these effects, we used daily climate variables obtained from the regional climate model RegCM3 from 1981 to 2100 under the A1B scenario and crop observations from 53 agro-meteorological experimental stations from 1981 to 2010 in Northeast China. Three one-grade zones of cropping systems were divided by heat, water, topography and crop-type, including the semi-arid areas of the northeast and northwest (III), the one crop area of warm-cool plants in semi-humid plain or hilly regions of the northeast (IV), and the two crop area in irrigated farmland in the Huanghuaihai Plain (VI). An agro-ecological zone model was used to calculate climatic potential productivities. The effects of adjusting cropping systems on climate resource utilization in Northeast China under the A1B scenario were assessed. The results indicated that from 1981 to 2100 in the III, IV and VI areas, the planting boundaries of different cropping systems in Northeast China obviously shifted toward the north and the east based on comprehensively considering the heat and precipitation resources. However, due to high temperature stress, the climatic potential productivity of spring maize was reduced in the future. Therefore, adjusting the cropping system is an effective way to improve the climatic potential productivity and climate resource utilization. Replacing the one crop in one year model (spring maize) by the two crops in one year model (winter wheat and summer maize) significantly increased the total climatic potential productivity and average utilization efficiencies. During the periods of 2011-2040, 2041-2070 and 2071-2100, the average total climatic potential productivities of winter wheat and summer maize increased by 9.36%, 11.88% and 12.13% compared to that of spring maize, respectively. Additionally, compared with spring maize, the average utilization efficiencies of thermal resources of winter wheat and summer maize dramatically increased by 9.2%, 12.1% and 12.0%, respectively. The increases in the average utilization efficiencies of precipitation resources of winter wheat and summer maize were 1.78 kg hm-2 mm-1, 2.07 kg hm-2 mm-1 and 1.92 kg hm-2 mm-1 during 2011-2040, 2041-2070 and 2071-2100, respectively. Our findings highlight that adjusting cropping systems can dominantly contribute to utilization efficiency increases of agricultural climatic resources in Northeast China in the future.

Evaluating the effects of terrestrial ecosystems, climate and carbon dioxide on weathering over geological time: a global-scale process-based approach.

PubMed

Taylor, Lyla L; Banwart, Steve A; Valdes, Paul J; Leake, Jonathan R; Beerling, David J

2012-02-19

Global weathering of calcium and magnesium silicate rocks provides the long-term sink for atmospheric carbon dioxide (CO(2)) on a timescale of millions of years by causing precipitation of calcium carbonates on the seafloor. Catchment-scale field studies consistently indicate that vegetation increases silicate rock weathering, but incorporating the effects of trees and fungal symbionts into geochemical carbon cycle models has relied upon simple empirical scaling functions. Here, we describe the development and application of a process-based approach to deriving quantitative estimates of weathering by plant roots, associated symbiotic mycorrhizal fungi and climate. Our approach accounts for the influence of terrestrial primary productivity via nutrient uptake on soil chemistry and mineral weathering, driven by simulations using a dynamic global vegetation model coupled to an ocean-atmosphere general circulation model of the Earth's climate. The strategy is successfully validated against observations of weathering in watersheds around the world, indicating that it may have some utility when extrapolated into the past. When applied to a suite of six global simulations from 215 to 50 Ma, we find significantly larger effects over the past 220 Myr relative to the present day. Vegetation and mycorrhizal fungi enhanced climate-driven weathering by a factor of up to 2. Overall, we demonstrate a more realistic process-based treatment of plant fungal-geosphere interactions at the global scale, which constitutes a first step towards developing 'next-generation' geochemical models.

Evaluating the effects of terrestrial ecosystems, climate and carbon dioxide on weathering over geological time: a global-scale process-based approach

PubMed Central

Taylor, Lyla L.; Banwart, Steve A.; Valdes, Paul J.; Leake, Jonathan R.; Beerling, David J.

2012-01-01

Global weathering of calcium and magnesium silicate rocks provides the long-term sink for atmospheric carbon dioxide (CO2) on a timescale of millions of years by causing precipitation of calcium carbonates on the seafloor. Catchment-scale field studies consistently indicate that vegetation increases silicate rock weathering, but incorporating the effects of trees and fungal symbionts into geochemical carbon cycle models has relied upon simple empirical scaling functions. Here, we describe the development and application of a process-based approach to deriving quantitative estimates of weathering by plant roots, associated symbiotic mycorrhizal fungi and climate. Our approach accounts for the influence of terrestrial primary productivity via nutrient uptake on soil chemistry and mineral weathering, driven by simulations using a dynamic global vegetation model coupled to an ocean–atmosphere general circulation model of the Earth's climate. The strategy is successfully validated against observations of weathering in watersheds around the world, indicating that it may have some utility when extrapolated into the past. When applied to a suite of six global simulations from 215 to 50 Ma, we find significantly larger effects over the past 220 Myr relative to the present day. Vegetation and mycorrhizal fungi enhanced climate-driven weathering by a factor of up to 2. Overall, we demonstrate a more realistic process-based treatment of plant fungal–geosphere interactions at the global scale, which constitutes a first step towards developing ‘next-generation’ geochemical models. PMID:22232768

Advancements in the use of speleothems as climate archives

NASA Astrophysics Data System (ADS)

Wong, Corinne I.; Breecker, Daniel O.

2015-11-01

Speleothems have become a cornerstone of the approach to better understanding Earth's climatic teleconnections due to their precise absolute chronologies, their continuous or semicontinuous deposition and their global terrestrial distribution. We review the last decade of speleothem-related research, building off a similar review by McDermott (2004), in three themes - i) investigation of global teleconnections using speleothem-based climate reconstructions, ii) refinement of climate interpretations from speleothem proxies through cave monitoring, and iii) novel, technical methods of speleothem-based climate reconstructions. Speleothem records have enabled critical insight into the response of global hydroclimate to large climate changes. This includes the relevant forcings and sequence of climatic responses involved in glacial terminations and recognition of a global monsoon response to climate changes on orbital and millennial time scales. We review advancements in understanding of the processes that control speleothem δ13C values and introduce the idea of a direct atmospheric pCO2 influence. We discuss progress in understanding kinetic isotope fractionation, which, with further advances, may help quantify paleoclimate changes despite non-equilibrium formation of speleothems. This feeds into the potential of proxy system modeling to consider climatic, hydrological and biogeochemical processes with the objective of quantitatively interpreting speleothem proxies. Finally, we provide an overview of emerging speleothem proxies and novel approaches using existing proxies. Most recently, technical advancements made in the measurement of fluid inclusions are now yielding reliable determinations of paleotemperatures.

The nexus between climate change, ecosystem services and human health: Towards a conceptual framework.

PubMed

Chiabai, Aline; Quiroga, Sonia; Martinez-Juarez, Pablo; Higgins, Sahran; Taylor, Tim

2018-09-01

This paper addresses the impact that changes in natural ecosystems can have on health and wellbeing focusing on the potential co-benefits that green spaces could provide when introduced as climate change adaptation measures. Ignoring such benefits could lead to sub-optimal planning and decision-making. A conceptual framework, building on the ecosystem-enriched Driver, Pressure, State, Exposure, Effect, Action model (eDPSEEA), is presented to aid in clarifying the relational structure between green spaces and human health, taking climate change as the key driver. The study has the double intention of (i) summarising the literature with a special emphasis on the ecosystem and health perspectives, as well as the main theories behind these impacts, and (ii) modelling these findings into a framework that allows for multidisciplinary approaches to the underlying relations between human health and green spaces. The paper shows that while the literature based on the ecosystem perspective presents a well-documented association between climate, health and green spaces, the literature using a health-based perspective presents mixed evidence in some cases. The role of contextual factors and the exposure mechanism are rarely addressed. The proposed framework could serve as a multidisciplinary knowledge platform for multi-perspecitve analysis and discussion among experts and stakeholders, as well as to support the operationalization of quantitative assessment and modelling exercises. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Impacts of Non-Stationarity in Climate on Flood Intensity-Duration-Frequency: Case Studies in Mountainous Areas with Snowmelt

NASA Astrophysics Data System (ADS)

Hou, Z.; Ren, H.; Sun, N.; Leung, L. R.; Liu, Y.; Coleman, A. M.; Skaggs, R.; Wigmosta, M. S.

2017-12-01

Hydrologic engineering design usually involves intensity-duration-frequency (IDF) analysis for calculating runoff from a design storm of specified precipitation frequency and duration using event-based hydrologic rainfall-runoff models. Traditionally, the procedure assumes climate stationarity and neglects snowmelt-driven runoff contribution to floods. In this study, we used high resolution climate simulations to provide inputs to the physics-based Distributed Hydrology Soil and Vegetation Model (DHSVM) to determine the spatially distributed precipitation and snowmelt available for runoff. Climate model outputs were extracted around different mountainous field sites in Colorado and California. IDF curves were generated at each numerical grid of DHSVM based on the simulated precipitation, temperature, and available water for runoff. Quantitative evaluation of trending and stationarity tests were conducted to identify (quasi-)stationary time periods for reliable IDF analysis. The impact of stationarity was evaluated by comparing the derived IDF attributes with respect to time windows of different length and level of stationarity. Spatial mapping of event return-period was performed for various design storms, and spatial mapping of event intensity was performed for given duration and return periods. IDF characteristics were systematically compared (historical vs RCP4.5 vs RCP8.5) using annual maximum series vs partial duration series data with the goal of providing reliable IDF analyses to support hydrologic engineering design.

Climate Impacts of Fire-Induced Land-Surface Changes

NASA Astrophysics Data System (ADS)

Liu, Y.; Hao, X.; Qu, J. J.

2017-12-01

One of the consequences of wildfires is the changes in land-surface properties such as removal of vegetation. This will change local and regional climate through modifying the land-air heat and water fluxes. This study investigates mechanism by developing and a parameterization of fire-induced land-surface property changes and applying it to modeling of the climate impacts of large wildfires in the United States. Satellite remote sensing was used to quantitatively evaluate the land-surface changes from large fires provided from the Monitoring Trends in Burning Severity (MTBS) dataset. It was found that the changes in land-surface properties induced by fires are very complex, depending on vegetation type and coverage, climate type, season and time after fires. The changes in LAI are remarkable only if the actual values meet a threshold. Large albedo changes occur in winter for fires in cool climate regions. The signs are opposite between the first post-fire year and the following years. Summer day-time temperature increases after fires, while nigh-time temperature changes in various patterns. The changes are larger in forested lands than shrub / grassland lands. In the parameterization scheme, the detected post-fire changes are decomposed into trends using natural exponential functions and fluctuations of periodic variations with the amplitudes also determined by natural exponential functions. The final algorithm is a combination of the trends, periods, and amplitude functions. This scheme is used with Earth system models to simulate the local and regional climate effects of wildfires.

Climate Change and Conservation Planning in California: The San Francisco Bay Area Upland Habitat Goals Approach

NASA Astrophysics Data System (ADS)

Branciforte, R.; Weiss, S. B.; Schaefer, N.

2008-12-01

Climate change threatens California's vast and unique biodiversity. The Bay Area Upland Habitat Goals is a comprehensive regional biodiversity assessment of the 9 counties surrounding San Francisco Bay, and is designing conservation land networks that will serve to protect, manage, and restore that biodiversity. Conservation goals for vegetation, rare plants, mammals, birds, fish, amphibians, reptiles, and invertebrates are set, and those goals are met using the optimization algorithm MARXAN. Climate change issues are being considered in the assessment and network design in several ways. The high spatial variability at mesoclimatic and topoclimatic scales in California creates high local biodiversity, and provides some degree of local resiliency to macroclimatic change. Mesoclimatic variability from 800 m scale PRISM climatic norms is used to assess "mesoclimate spaces" in distinct mountain ranges, so that high mesoclimatic variability, especially local extremes that likely support range limits of species and potential climatic refugia, can be captured in the network. Quantitative measures of network resiliency to climate change include the spatial range of key temperature and precipitation variables within planning units. Topoclimatic variability provides a finer-grained spatial patterning. Downscaling to the topoclimatic scale (10-50 m scale) includes modeling solar radiation across DEMs for predicting maximum temperature differentials, and topographic position indices for modeling minimum temperature differentials. PRISM data are also used to differentiate grasslands into distinct warm and cool types. The overall conservation strategy includes local and regional connectivity so that range shifts can be accommodated.

Response of the Indian Creek alluvial fan, Nevada, to glacial-interglacial climate change

NASA Astrophysics Data System (ADS)

D'Arcy, Mitch; Roda-Boluda, Duna; Whittaker, Alexander; Brooke, Sam

2017-04-01

Alluvial fans have been shown to record signals of glacial-interglacial climate changes. Specifically, it has been suggested that their down-system grain size fining patterns may record changes in sediment flux. However, very few field studies have tested this because they require (i) robust fan chronologies, (ii) constraints on basin subsidence and 3D fan geometry, and (iii) a suitable model for inverting grain size fining for sediment flux. Here, we present a case study from the fluvially-dominated Indian Creek fan system in Fish Lake Valley, Nevada, which satisfies these criteria. We measure grain size fining patterns on a surface dating to the mid-glacial period ˜71 kyr ago, and a surface dating to the Holocene, which between them represent an overall warming (˜3 ˚ C) and drying (˜30%) of the regional climate. We use constraints on basin subsidence and a self-similar model of grain size fining to reconstruct sediment fluxes to the alluvial fan during the time periods captured by the two surfaces. Our results indicate a decline in sediment flux of ˜38% between the deposition of the ˜71 kyr and Holocene surfaces, implying significant sensitivity to climatic forcing over time periods of >10 kyr. This could represent a decrease in catchment erosion rates and/or a decrease in sediment export as the climate dried. Our results offer quantitative new constraints on how simple landscapes react to known glacial-interglacial climate shifts.

Geography and Similarity of Regional Cuisines in China

PubMed Central

Zhu, Yu-Xiao; Huang, Junming; Zhang, Zi-Ke; Zhang, Qian-Ming; Zhou, Tao; Ahn, Yong-Yeol

2013-01-01

Food occupies a central position in every culture and it is therefore of great interest to understand the evolution of food culture. The advent of the World Wide Web and online recipe repositories have begun to provide unprecedented opportunities for data-driven, quantitative study of food culture. Here we harness an online database documenting recipes from various Chinese regional cuisines and investigate the similarity of regional cuisines in terms of geography and climate. We find that geographical proximity, rather than climate proximity, is a crucial factor that determines the similarity of regional cuisines. We develop a model of regional cuisine evolution that provides helpful clues for understanding the evolution of cuisines and cultures. PMID:24260166

Geography and similarity of regional cuisines in China.

PubMed

Zhu, Yu-Xiao; Huang, Junming; Zhang, Zi-Ke; Zhang, Qian-Ming; Zhou, Tao; Ahn, Yong-Yeol

2013-01-01

Food occupies a central position in every culture and it is therefore of great interest to understand the evolution of food culture. The advent of the World Wide Web and online recipe repositories have begun to provide unprecedented opportunities for data-driven, quantitative study of food culture. Here we harness an online database documenting recipes from various Chinese regional cuisines and investigate the similarity of regional cuisines in terms of geography and climate. We find that geographical proximity, rather than climate proximity, is a crucial factor that determines the similarity of regional cuisines. We develop a model of regional cuisine evolution that provides helpful clues for understanding the evolution of cuisines and cultures.

Sensitivity of global terrestrial ecosystems to climate variability.

PubMed

Seddon, Alistair W R; Macias-Fauria, Marc; Long, Peter R; Benz, David; Willis, Kathy J

2016-03-10

The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems--be they natural or with a strong anthropogenic signature--to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

Sensitivity of global terrestrial ecosystems to climate variability

NASA Astrophysics Data System (ADS)

Seddon, Alistair W. R.; Macias-Fauria, Marc; Long, Peter R.; Benz, David; Willis, Kathy J.

2016-03-01

The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems—be they natural or with a strong anthropogenic signature—to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

Impacts of climate variability and change on crop yield in sub-Sahara Africa

NASA Astrophysics Data System (ADS)

Pan, S.; Zhang, J.; Yang, J.; Chen, G.; Xu, R.; Zhang, B.; Lou, Y.

2017-12-01

Much concern has been raised about the impacts of climate change and climate extremes on Africa's food security. The impact of climate change on Africa's agriculture is likely to be severe compared to other continents due to high rain-fed agricultural dependence, and limited ability to mitigate and adapt to climate change. In recent decades, warming in Africa is more pronounced and faster than the global average and this trend is likely to continue in the future. However, quantitative assessment on impacts of climate extremes and climate change on crop yield has not been well investigated yet. By using an improved agricultural module of the Dynamic Land Ecosystem Model (DLEM-AG2) driven by spatially-explicit information on land use, climate and other environmental changes, we have assessed impacts of historical climate variability and future climate change on food crop yield across the sub-Sahara Africa during1980-2016 and the rest of the 21st century (2017-2099). Our simulated results indicate that African crop yield in the past three decades shows an increasing trend primarily due to cropland expansion. However, crop yield shows substantially spatial and temporal variation due to inter-annual and inter-decadal climate variability and spatial heterogeneity of environmental drivers. Droughts have largely reduced crop yield in the most vulnerable regions of Sub-Sahara Africa. Future projections with DLEM-AG2 show that food crop production in Sub-Sahara Africa would be favored with limiting end-of-century warming to below 1.50 C.

A quantitative evaluation of the public response to climate engineering

NASA Astrophysics Data System (ADS)

Wright, Malcolm J.; Teagle, Damon A. H.; Feetham, Pamela M.

2014-02-01

Atmospheric greenhouse gas concentrations continue to increase, with CO2 passing 400 parts per million in May 2013. To avoid severe climate change and the attendant economic and social dislocation, existing energy efficiency and emissions control initiatives may need support from some form of climate engineering. As climate engineering will be controversial, there is a pressing need to inform the public and understand their concerns before policy decisions are taken. So far, engagement has been exploratory, small-scale or technique-specific. We depart from past research to draw on the associative methods used by corporations to evaluate brands. A systematic, quantitative and comparative approach for evaluating public reaction to climate engineering is developed. Its application reveals that the overall public evaluation of climate engineering is negative. Where there are positive associations they favour carbon dioxide removal (CDR) over solar radiation management (SRM) techniques. Therefore, as SRM techniques become more widely known they are more likely to elicit negative reactions. Two climate engineering techniques, enhanced weathering and cloud brightening, have indistinct concept images and so are less likely to draw public attention than other CDR or SRM techniques.

Future U.S. ozone projections dependence on regional emissions, climate change, long-range transport and differences in modeling design

NASA Astrophysics Data System (ADS)

He, Hao; Liang, Xin-Zhong; Lei, Hang; Wuebbles, Donald J.

2016-03-01

A consistent modeling framework with nested global and regional chemical transport models (CTMs) is used to separate and quantitatively assess the relative contributions to projections of future U.S. ozone pollution from the effects of emissions changes, climate change, long-range transport (LRT) of pollutants, and differences in modeling design. After incorporating dynamic lateral boundary conditions (LBCs) from a global CTM, a regional CTM's representation of present-day U.S. ozone pollution is notably improved, especially relative to results from the regional CTM with fixed LBCs or from the global CTM alone. This nested system of global and regional CTMs projects substantial surface ozone trends for the 2050's: 6-10 ppb decreases under the 'clean' A1B scenario and ∼15 ppb increases under the 'dirty' A1Fi scenario. Among the total trends of future ozone, regional emissions changes dominate, contributing negative 25-60% in A1B and positive 30-45% in A1Fi. Comparatively, climate change contributes positive 10-30%, while LRT effects through changing chemical LBCs account for positive 15-20% in both scenarios, suggesting introducing dynamic LBCs could influence projections of the U.S. future ozone pollution with a magnitude comparable to effects of climate change alone. The contribution to future ozone projections due to differences in modeling design, including model formulations, emissions treatments, and other factors between the global and the nested regional CTMs, is regionally dependent, ranging from negative 20% to positive 25%. It is shown that the model discrepancies for present-day simulations between global and regional CTMs can propagate into future U.S. ozone projections systematically but nonlinearly, especially in California and the Southeast. Therefore in addition to representations of emissions change and climate change, accurate treatment of LBCs for the regional CTM is essential for projecting the future U.S. ozone pollution.

Probabilistic seasonal Forecasts to deterministic Farm Leve Decisions: Innovative Approach

NASA Astrophysics Data System (ADS)

Mwangi, M. W.

2015-12-01

Climate change and vulnerability are major challenges in ensuring household food security. Climate information services have the potential to cushion rural households from extreme climate risks. However, most the probabilistic nature of climate information products is not easily understood by majority of smallholder farmers. Despite the probabilistic nature, climate information have proved to be a valuable climate risk adaptation strategy at the farm level. This calls for innovative ways to help farmers understand and apply climate information services to inform their farm level decisions. The study endeavored to co-design and test appropriate innovation systems for climate information services uptake and scale up necessary for achieving climate risk development. In addition it also determined the conditions necessary to support the effective performance of the proposed innovation system. Data and information sources included systematic literature review, secondary sources, government statistics, focused group discussions, household surveys and semi-structured interviews. Data wasanalyzed using both quantitative and qualitative data analysis techniques. Quantitative data was analyzed using the Statistical Package for Social Sciences (SPSS) software. Qualitative data was analyzed using qualitative techniques, which involved establishing the categories and themes, relationships/patterns and conclusions in line with the study objectives. Sustainable livelihood, reduced household poverty and climate change resilience were the impact that resulted from the study.

Energy & Climate: Getting Quantitative

NASA Astrophysics Data System (ADS)

Wolfson, Richard

2011-11-01

A noted environmentalist claims that buying an SUV instead of a regular car is energetically equivalent to leaving your refrigerator door open for seven years. A fossil-fuel apologist argues that solar energy is a pie-in-the-sky dream promulgated by na"ive environmentalists, because there's nowhere near enough solar energy to meet humankind's energy demand. A group advocating shutdown of the Vermont Yankee nuclear plant claims that 70% of its electrical energy is lost in transmission lines. Around the world, thousands agitate for climate action, under the numerical banner ``350.'' Neither the environmentalist, the fossil-fuel apologist, the antinuclear activists, nor most of those marching under the ``350'' banner can back up their assertions with quantitative arguments. Yet questions about energy and its environmental impacts almost always require quantitative answers. Physics can help! This poster gives some cogent examples, based on the newly published 2^nd edition of the author's textbook Energy, Environment, and Climate.

Co-production of science for regional integrated assessment and management of climate change impacts: The case study of Aspen, CO

NASA Astrophysics Data System (ADS)

Arnott, J. C.; Katzenberger, J.

2015-12-01

The impacts of global climate change to regional scales are complex and cut across sectorial and jurisdictional boundaries, and therefore, a unique enterprise of collaboration between scientists, resource managers, and other stakeholders for development of adequate response strategies is required. Such collaboration has been exhibited between stakeholders, researchers, and a boundary organization—the Aspen Global Change Institute—since 2005 in assessing impacts and crafting policies in response with regard to climate change impacts in the mountain watershed surrounding Aspen, CO. A series of structured stakeholder interviews and town hall sessions, impact assessment reports, and intensive collaboration between various information providers and user groups has set the stage for development of both mitigation of and adaptation to climate change impacts. The most recent example of this has included the use of global scale climate model output to inform the development of resiliency strategies in response to extreme precipitation projections. The use of this kind of resource has been considered in a variety of decision-making contexts and has included the development of region- and decision-relevant qualitative scenarios that make use of quantitative model-based information. Results from this line of work that include feedback from actual users', a boundary organization, and researchers' perspectives will be reported along with examples of policy and implementation results.

Climate Change Threatens Coexistence within Communities of Mediterranean Forested Wetlands

PubMed Central

Di Paola, Arianna; Valentini, Riccardo; Paparella, Francesco

2012-01-01

The Mediterranean region is one of the hot spots of climate change. This study aims at understanding what are the conditions sustaining tree diversity in Mediterranean wet forests under future scenarios of altered hydrological regimes. The core of the work is a quantitative, dynamic model describing the coexistence of different Mediterranean tree species, typical of arid or semi-arid wetlands. Two kind of species, i.e. Hygrophilous (drought sensitive, flood resistant) and Non-hygrophilous (drought resistant, flood sensitive), are broadly defined according to the distinct adaptive strategies of trees against water stress of summer drought and winter flooding. We argue that at intermediate levels of water supply the dual role of water (resource and stress) results in the coexistence of the two kind of species. A bifurcation analysis allows us to assess the effects of climate change on the coexistence of the two species in order to highlight the impacts of predicted climate scenarios on tree diversity. Specifically, the model has been applied to Mediterranean coastal swamp forests of Central Italy located at Castelporziano Estate and Circeo National Park. Our results show that there are distinct rainfall thresholds beyond which stable coexistence becomes impossible. Regional climatic projections show that the lower rainfall threshold may be approached or crossed during the XXI century, calling for an urgent adaptation and mitigation response to prevent biodiversity losses. PMID:23077484

Modeling Reef Island Morphodynamics in Profile and Plan View

NASA Astrophysics Data System (ADS)

Ashton, A. D.; Ortiz, A. C.; Lorenzo-Trueba, J.

2016-12-01

Reef islands are carbonate detrital landforms perched atop shallow reef flats of atolls and barrier reef systems. Often comprising the only subaerial, inhabitable land of many island chains and island nations, these low-lying, geomorphically active landforms face considerable hazards from climate change. While there hazards include wave overtopping and groundwater salinization, sea-level rise and wave climate change will affect sediment transport and shoreline dynamics, including the possibility for wholesale reorganization of the islands themselves. Here we present a simplified morphodynamic model that can spatially quantify the potential impacts of climate change on reef islands. Using parameterizations of sediment transport pathways and feedbacks from previously presented XBeach modeling results, we investigate how sea-level rise, change in storminess, and different carbonate production rates can affect the profile evolution of reef islands, including feedbacks with the shallow reef flat that bounds the islands offshore (and lagoonward). Model results demonstrate that during rising sea levels, the reef flat can serve as a sediment trap, starving reef islands of detrital sediment that could otherwise fortify the shore against sea-level-rise-driven erosion. On the other hand, if reef flats are currently shallow (likely due to geologic inheritance or biologic cementation processes) such that sea-level rise does not result in sediment accumulation on the flat, reef island shorelines may be more resilient to rising seas. We extend the model in plan view to examine how long-term (decadal) changes in wave approach direction could affect reef island shoreline orientation. We compare model results to historical and geologic change for different case studies on the Marshall Islands. This simplified modeling approach, focusing on boundary dynamics and mass fluxes, provides a quantitative tool to predict the response of reef island environments to climate change.

Modeling Insights into Deuterium Excess as an Indicator of Water Vapor Source Conditions

NASA Technical Reports Server (NTRS)

Lewis, Sophie C.; Legrande, Allegra Nicole; Kelley, Maxwell; Schmidt, Gavin A.

2013-01-01

Deuterium excess (d) is interpreted in conventional paleoclimate reconstructions as a tracer of oceanic source region conditions, such as temperature, where precipitation originates. Previous studies have adopted co-isotopic approaches to estimate past changes in both site and oceanic source temperatures for ice core sites using empirical relationships derived from conceptual distillation models, particularly Mixed Cloud Isotopic Models (MCIMs). However, the relationship between d and oceanic surface conditions remains unclear in past contexts. We investigate this climate-isotope relationship for sites in Greenland and Antarctica using multiple simulations of the water isotope-enabled Goddard Institute for Space Studies (GISS) ModelE-R general circulation model and apply a novel suite of model vapor source distribution (VSD) tracers to assess d as a proxy for source temperature variability under a range of climatic conditions. Simulated average source temperatures determined by the VSDs are compared to synthetic source temperature estimates calculated using MCIM equations linking d to source region conditions. We show that although deuterium excess is generally a faithful tracer of source temperatures as estimated by the MCIM approach, large discrepancies in the isotope-climate relationship occur around Greenland during the Last Glacial Maximum simulation, when precipitation seasonality and moisture source regions were notably different from present. This identified sensitivity in d as a source temperature proxy suggests that quantitative climate reconstructions from deuterium excess should be treated with caution for some sites when boundary conditions are significantly different from the present day. Also, the exclusion of the influence of humidity and other evaporative source changes in MCIM regressions may be a limitation of quantifying source temperature fluctuations from deuterium excess in some instances.

Sensitivity of Sahelian Precipitation to Desert Dust under ENSO variability: a regional modeling study

NASA Astrophysics Data System (ADS)

Jordan, A.; Zaitchik, B. F.; Gnanadesikan, A.

2016-12-01

Mineral dust is estimated to comprise over half the total global aerosol burden, with a majority coming from the Sahara and Sahel region. Bounded by the Sahara Desert to the north and the Sahelian Savannah to the south, the Sahel experiences high interannual rainfall variability and a short rainy season during the boreal summer months. Observation-based data for the past three decades indicates a reduced dust emission trend, together with an increase in greening and surface roughness within the Sahel. Climate models used to study regional precipitation changes due to Saharan dust yield varied results, both in sign convention and magnitude. Inconsistency of model estimates drives future climate projections for the region that are highly varied and uncertain. We use the NASA-Unified Weather Research and Forecasting (NU-WRF) model to quantify the interaction and feedback between desert dust aerosol and Sahelian precipitation. Using nested domains at fine spatial resolution we resolve changes to mesoscale atmospheric circulation patterns due to dust, for representative phases of El Niño-Southern Oscillation (ENSO). The NU-WRF regional earth system model offers both advanced land surface data and resolvable detail of the mechanisms of the impact of Saharan dust. Results are compared to our previous work assessed over the Western Sahel using the Geophysical Fluid Dynamics Laboratory (GFDL) CM2Mc global climate model, and to other previous regional climate model studies. This prompts further research to help explain the dust-precipitation relationship and recent North African dust emission trends. This presentation will offer a quantitative analysis of differences in radiation budget, energy and moisture fluxes, and atmospheric dynamics due to desert dust aerosol over the Sahel.

How do Changes in Hydro-Climate Conditions Alter the Risk of Infection With Fasciolosis?

NASA Astrophysics Data System (ADS)

Beltrame, L.; Dunne, T.; Rose, H.; Walker, J.; Morgan, E.; Vickerman, P.; Wagener, T.

2017-12-01

Fasciolosis is a widespread parasitic disease of livestock and is emerging as a major zoonosis. Since the parasite and its intermediate host live and develop in the environment, risk of infection is directly affected by climatic-environmental conditions. Changes in disease prevalence, seasonality and distribution have been reported in recent years and attributed to altered temperature and rainfall patterns, raising concerns about the effects of climate change in the future. Therefore, it is urgent to understand how changes in climate-environmental drivers may alter the dynamics of disease risk in a quantitative way, to guide parasite control strategies and interventions in the coming decades. In a previous work, we developed and tested a novel mechanistic hydro-epidemiological model for Fasciolosis, which explicitly represents the parasite life-cycle in connection with key environmental processes, allowing to capture the impact of previously unseen conditions. In this study, we use the new mechanistic model to assess the sensitivity of infection rates to changes in climate-environmental factors. This is challenging as processes underlying disease transmission are complex and interacting, and may have contrasting effects on the parasite life-cycle stages. To this end, we set up a sensitivity analysis framework to investigate in a structured way which factors play a key role in controlling the magnitude, timing and spread of infection, and how the sensitivity of disease risk varies in time and space. Moreover, we define synthetic scenarios to explore the space of possible variability of the hydro-climate drivers and investigate conditions that lead to critical levels of infection. The study shows how the new model combined with the sensitivity analysis framework can support decision-making, providing useful information for disease management.

Long-Term Field Data and Climate-Habitat Models Show That Orangutan Persistence Depends on Effective Forest Management and Greenhouse Gas Mitigation

PubMed Central

Gregory, Stephen D.; Brook, Barry W.; Goossens, Benoît; Ancrenaz, Marc; Alfred, Raymond; Ambu, Laurentius N.; Fordham, Damien A.

2012-01-01

Background Southeast Asian deforestation rates are among the world’s highest and threaten to drive many forest-dependent species to extinction. Climate change is expected to interact with deforestation to amplify this risk. Here we examine whether regional incentives for sustainable forest management will be effective in improving threatened mammal conservation, in isolation and when combined with global climate change mitigation. Methodology/Principal Findings Using a long time-series of orangutan nest counts for Sabah (2000–10), Malaysian Borneo, we evaluated the effect of sustainable forest management and climate change scenarios, and their interaction, on orangutan spatial abundance patterns. By linking dynamic land-cover and downscaled global climate model projections, we determine the relative influence of these factors on orangutan spatial abundance and use the resulting statistical models to identify habitat crucial for their long-term conservation. We show that land-cover change the degradation of primary forest had the greatest influence on orangutan population size. Anticipated climate change was predicted to cause reductions in abundance in currently occupied populations due to decreased habitat suitability, but also to promote population growth in western Sabah by increasing the suitability of presently unoccupied regions. Conclusions/Significance We find strong quantitative support for the Sabah government’s proposal to implement sustainable forest management in all its forest reserves during the current decade; failure to do so could result in a 40 to 80 per cent regional decline in orangutan abundance by 2100. The Sabah orangutan is just one (albeit iconic) example of a forest-dependent species that stands to benefit from sustainable forest management, which promotes conservation of existing forests. PMID:22970145

Long-term field data and climate-habitat models show that orangutan persistence depends on effective forest management and greenhouse gas mitigation.

PubMed

Gregory, Stephen D; Brook, Barry W; Goossens, Benoît; Ancrenaz, Marc; Alfred, Raymond; Ambu, Laurentius N; Fordham, Damien A

2012-01-01

Southeast Asian deforestation rates are among the world's highest and threaten to drive many forest-dependent species to extinction. Climate change is expected to interact with deforestation to amplify this risk. Here we examine whether regional incentives for sustainable forest management will be effective in improving threatened mammal conservation, in isolation and when combined with global climate change mitigation. Using a long time-series of orangutan nest counts for Sabah (2000-10), Malaysian Borneo, we evaluated the effect of sustainable forest management and climate change scenarios, and their interaction, on orangutan spatial abundance patterns. By linking dynamic land-cover and downscaled global climate model projections, we determine the relative influence of these factors on orangutan spatial abundance and use the resulting statistical models to identify habitat crucial for their long-term conservation. We show that land-cover change the degradation of primary forest had the greatest influence on orangutan population size. Anticipated climate change was predicted to cause reductions in abundance in currently occupied populations due to decreased habitat suitability, but also to promote population growth in western Sabah by increasing the suitability of presently unoccupied regions. We find strong quantitative support for the Sabah government's proposal to implement sustainable forest management in all its forest reserves during the current decade; failure to do so could result in a 40 to 80 per cent regional decline in orangutan abundance by 2100. The Sabah orangutan is just one (albeit iconic) example of a forest-dependent species that stands to benefit from sustainable forest management, which promotes conservation of existing forests.

Climate change impacts on natural toxins in food production systems, exemplified by deoxynivalenol in wheat and diarrhetic shellfish toxins.

PubMed

van der Fels-Klerx, H J; Olesen, J E; Naustvoll, L-J; Friocourt, Y; Mengelers, M J B; Christensen, J H

2012-01-01

Climate change is expected to affect food and feed safety, including the occurrence of natural toxins in primary crop and seafood production; however, to date, quantitative estimates are scarce. This study aimed to estimate the impact of climate change effects on mycotoxin contamination of cereal grains cultivated in the terrestrial area of north west Europe, and on the frequency of harmful algal blooms and contamination of shellfish with marine biotoxins in the North Sea coastal zone. The study focused on contamination of wheat with deoxynivalenol, and on abundance of Dinophysis spp. and the possible relationship with diarrhetic shellfish toxins. The study used currently available data and models. Global and regional climate models were combined with models of crop phenology, mycotoxin prediction models, hydrodynamic models and ecological models, with the output of one model being used as input for the other. In addition, statistical data analyses using existing national datasets from the study area were performed to obtain information on the relationships between Dinophysis spp. cell counts and contamination of shellfish with diarrhetic shellfish toxins as well as on frequency of cereal cropping. In this paper, a summary of the study is presented, and overall conclusions and recommendations are given. Climate change projections for the years 2031-2050 were used as the starting point of the analyses relative to a preceding 20-year baseline period from which the climate change signal was calculated. Results showed that, in general, climate change effects lead to advanced flowering and harvest of wheat, and increased risk of contamination of wheat with deoxynivalenol. Blooms of dinoflagellates were estimated to occur more often. If the group of Dinophysis spp. behaves similarly to other flagellates in the future then frequency of harmful algal blooms of Dinophysis spp. may also increase, but consequences for contamination of shellfish with diarrhetic shellfish toxins are uncertain. Climate change will also have indirect effects on toxin contamination, which may be equally important. For example, the frequency of cropping of wheat and maize in north Europe was projected to increase under climate change, which will also increase the risk of contamination of the grains with deoxynivalenol. Risk managers are encouraged to consider the entire range of the predictions of climate change effects on food safety hazards, rather than median or average values only. Furthermore, it is recommended to closely monitor levels of mycotoxins and marine biotoxins in the future, in particular related to risky situations associated with favourable climatic conditions for toxin producing organisms. In particular, it is important to pay attention to the continuity of collecting the right data, and the availability and accessibility of databases. On a European level, it is important to stress the need for harmonisation of terminology and data collection.

Impacts of climate change on the microbial safety of pre-harvest leafy green vegetables as indicated by Escherichia coli O157 and Salmonella spp.

PubMed

Liu, Cheng; Hofstra, Nynke; Franz, Eelco

2013-05-15

The likelihood of leafy green vegetable (LGV) contamination and the associated pathogen growth and survival are strongly related to climatic conditions. Particularly temperature increase and precipitation pattern changes have a close relationship not only with the fate and transport of enteric bacteria, but also with their growth and survival. Using all relevant literature, this study reviews and synthesises major impacts of climate change (temperature increases and precipitation pattern changes) on contamination sources (manure, soil, surface water, sewage and wildlife) and pathways of foodborne pathogens (focussing on Escherichia coli O157 and Salmonella spp.) on pre-harvested LGVs. Whether climate change increases their prevalence depends not only on the resulting local balance of the positive and negative impacts but also on the selected regional climate change scenarios. However, the contamination risks are likely to increase. This review shows the need for quantitative modelling approaches with scenario analyses and additional laboratory experiments. This study gives an extensive overview of the impacts of climate change on the contamination of pre-harvested LGVs and shows that climate change should not be ignored in food safety management and research. Copyright © 2013 Elsevier B.V. All rights reserved.

An isoline separating relatively warm from relatively cool wintertime forest surface temperatures for the southeastern United States

NASA Astrophysics Data System (ADS)

Wickham, J.; Wade, T. G.; Riitters, K. H.

2014-09-01

Forest-oriented climate mitigation policies promote forestation as a means to increase uptake of atmospheric carbon to counteract global warming. Some have pointed out that a carbon-centric forest policy may be overstated because it discounts biophysical aspects of the influence of forests on climate. In extra-tropical regions, many climate models have shown that forests tend to be warmer than grasslands and croplands because forest albedos tend to be lower than non-forest albedos. A lower forest albedo results in higher absorption of solar radiation and increased sensible warming that is not offset by the cooling effects of carbon uptake in extra-tropical regions. However, comparison of forest warming potential in the context of climate models is based on a coarse classification system of tropical, temperate, and boreal. There is considerable variation in climate within the broad latitudinal zonation of tropical, temperate, and boreal, and the relationship between biophysical (albedo) and biogeochemical (carbon uptake) mechanisms may not be constant within these broad zones. We compared wintertime forest and non-forest surface temperatures for the southeastern United States and found that forest surface temperatures shifted from being warmer than non-forest surface temperatures north of approximately 36°N to cooler south of 36°N. Our results suggest that the biophysical aspects of forests' influence on climate reinforce the biogeochemical aspects of forests' influence on climate south of 36°N. South of 36°N, both biophysical and biogeochemical properties of forests appear to support forestation as a climate mitigation policy. We also provide some quantitative evidence that evergreen forests tend to have cooler wintertime surface temperatures than deciduous forests that may be attributable to greater evapotranspiration rates.

Warm climates of the past—a lesson for the future?

PubMed Central

Lunt, D. J.; Elderfield, H.; Pancost, R.; Ridgwell, A.; Foster, G. L.; Haywood, A.; Kiehl, J.; Sagoo, N.; Shields, C.; Stone, E. J.; Valdes, P.

2013-01-01

This Discussion Meeting Issue of the Philosophical Transactions A had its genesis in a Discussion Meeting of the Royal Society which took place on 10–11 October 2011. The Discussion Meeting, entitled ‘Warm climates of the past: a lesson for the future?’, brought together 16 eminent international speakers from the field of palaeoclimate, and was attended by over 280 scientists and members of the public. Many of the speakers have contributed to the papers compiled in this Discussion Meeting Issue. The papers summarize the talks at the meeting, and present further or related work. This Discussion Meeting Issue asks to what extent information gleaned from the study of past climates can aid our understanding of future climate change. Climate change is currently an issue at the forefront of environmental science, and also has important sociological and political implications. Most future predictions are carried out by complex numerical models; however, these models cannot be rigorously tested for scenarios outside of the modern, without making use of past climate data. Furthermore, past climate data can inform our understanding of how the Earth system operates, and can provide important contextual information related to environmental change. All past time periods can be useful in this context; here, we focus on past climates that were warmer than the modern climate, as these are likely to be the most similar to the future. This introductory paper is not meant as a comprehensive overview of all work in this field. Instead, it gives an introduction to the important issues therein, using the papers in this Discussion Meeting Issue, and other works from all the Discussion Meeting speakers, as exemplars of the various ways in which past climates can inform projections of future climate. Furthermore, we present new work that uses a palaeo constraint to quantitatively inform projections of future equilibrium ice sheet change. PMID:24043873

Warm climates of the past--a lesson for the future?

PubMed

Lunt, D J; Elderfield, H; Pancost, R; Ridgwell, A; Foster, G L; Haywood, A; Kiehl, J; Sagoo, N; Shields, C; Stone, E J; Valdes, P

2013-10-28

This Discussion Meeting Issue of the Philosophical Transactions A had its genesis in a Discussion Meeting of the Royal Society which took place on 10-11 October 2011. The Discussion Meeting, entitled 'Warm climates of the past: a lesson for the future?', brought together 16 eminent international speakers from the field of palaeoclimate, and was attended by over 280 scientists and members of the public. Many of the speakers have contributed to the papers compiled in this Discussion Meeting Issue. The papers summarize the talks at the meeting, and present further or related work. This Discussion Meeting Issue asks to what extent information gleaned from the study of past climates can aid our understanding of future climate change. Climate change is currently an issue at the forefront of environmental science, and also has important sociological and political implications. Most future predictions are carried out by complex numerical models; however, these models cannot be rigorously tested for scenarios outside of the modern, without making use of past climate data. Furthermore, past climate data can inform our understanding of how the Earth system operates, and can provide important contextual information related to environmental change. All past time periods can be useful in this context; here, we focus on past climates that were warmer than the modern climate, as these are likely to be the most similar to the future. This introductory paper is not meant as a comprehensive overview of all work in this field. Instead, it gives an introduction to the important issues therein, using the papers in this Discussion Meeting Issue, and other works from all the Discussion Meeting speakers, as exemplars of the various ways in which past climates can inform projections of future climate. Furthermore, we present new work that uses a palaeo constraint to quantitatively inform projections of future equilibrium ice sheet change.

Regional climates in the GISS general circulation model: Surface air temperature

NASA Technical Reports Server (NTRS)

Hewitson, Bruce

1994-01-01

One of the more viable research techniques into global climate change for the purpose of understanding the consequent environmental impacts is based on the use of general circulation models (GCMs). However, GCMs are currently unable to reliably predict the regional climate change resulting from global warming, and it is at the regional scale that predictions are required for understanding human and environmental responses. Regional climates in the extratropics are in large part governed by the synoptic-scale circulation and the feasibility of using this interscale relationship is explored to provide a way of moving to grid cell and sub-grid cell scales in the model. The relationships between the daily circulation systems and surface air temperature for points across the continental United States are first developed in a quantitative form using a multivariate index based on principal components analysis (PCA) of the surface circulation. These relationships are then validated by predicting daily temperature using observed circulation and comparing the predicted values with the observed temperatures. The relationships predict surface temperature accurately over the major portion of the country in winter, and for half the country in summer. These relationships are then applied to the surface synoptic circulation of the Goddard Institute for Space Studies (GISS) GCM control run, and a set of surface grid cell temperatures are generated. These temperatures, based on the larger-scale validated circulation, may now be used with greater confidence at the regional scale. The generated temperatures are compared to those of the model and show that the model has regional errors of up to 10 C in individual grid cells.

Direct Measurements of the Convective Recycling of the Upper Troposphere

NASA Technical Reports Server (NTRS)

Bertram, Timothy H.; Perring, Anne E.; Wooldridge, Paul J.; Crounse, John D.; Kwan, Alan J.; Wennberg, Paul O.; Scheuer, Eric; Dibb, Jack; Avery, Melody; Sachse, Glen;

Climate Intervention as an Optimization Problem

NASA Astrophysics Data System (ADS)

Caldeira, Ken; Ban-Weiss, George A.

2010-05-01

Typically, climate models simulations of intentional intervention in the climate system have taken the approach of imposing a change (eg, in solar flux, aerosol concentrations, aerosol emissions) and then predicting how that imposed change might affect Earth's climate or chemistry. Computations proceed from cause to effect. However, humans often proceed from "What do I want?" to "How do I get it?" One approach to thinking about intentional intervention in the climate system ("geoengineering") is to ask "What kind of climate do we want?" and then ask "What pattern of radiative forcing would come closest to achieving that desired climate state?" This involves defining climate goals and a cost function that measures how closely those goals are attained. (An important next step is to ask "How would we go about producing these desired patterns of radiative forcing?" However, this question is beyond the scope of our present study.) We performed a variety of climate simulations in NCAR's CAM3.1 atmospheric general circulation model with a slab ocean model and thermodynamic sea ice model. We then evaluated, for a specific set of climate forcing basis functions (ie, aerosol concentration distributions), the extent to which the climate response to a linear combination of those basis functions was similar to a linear combination of the climate response to each basis function taken individually. We then developed several cost functions (eg, relative to the 1xCO2 climate, minimize rms difference in zonal and annual mean land temperature, minimize rms difference in zonal and annual mean runoff, minimize rms difference in a combination of these temperature and runoff indices) and then predicted optimal combinations of our basis functions that would minimize these cost functions. Lastly, we produced forward simulations of the predicted optimal radiative forcing patterns and compared these with our expected results. Obviously, our climate model is much simpler than reality and predictions from individual models do not provide a sound basis for action; nevertheless, our model results indicate that the general approach outlined here can lead to patterns of radiative forcing that make the zonal annual mean climate of a high CO2 world markedly more similar to that of a low CO2 world simultaneously for both temperature and hydrological indices, where degree of similarity is measured using our explicit cost functions. We restricted ourselves to zonally uniform aerosol concentrations distributions that can be defined in terms of a positive-definite quadratic equation on the sine of latitude. Under this constraint, applying an aerosol distribution in a 2xCO2 climate that minimized a combination of rms difference in zonal and annual mean land temperature and runoff relative to the 1xCO2 climate, the rms difference in zonal and annual mean temperatures was reduced by ~90% and the rms difference in zonal and annual mean runoff was reduced by ~80%. This indicates that there may be potential for stratospheric aerosols to diminish simultaneously both temperature and hydrological cycle changes caused by excess CO2 in the atmosphere. Clearly, our model does not include many factors (eg, socio-political consequences, chemical consequences, ocean circulation changes, aerosol transport and microphysics) so we do not argue strongly for our specific climate model results, however, we do argue strongly in favor of our methodological approach. The proposed approach is general, in the sense that cost functions can be developed that represent different valuations. While the choice of appropriate cost functions is inherently a value judgment, evaluating those functions for a specific climate simulation is a quantitative exercise. Thus, the use of explicit cost functions in evaluating model results for climate intervention scenarios is a clear way of separating value judgments from purely scientific and technical issues.

Selection of a Representative Subset of Global Climate Models that Captures the Profile of Regional Changes for Integrated Climate Impacts Assessment

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Mcdermid, Sonali P.

2017-01-01

We present the Representative Temperature and Precipitation (T&P) GCM Subsetting Approach developed within the Agricultural Model Intercomparison and Improvement Project (AgMIP) to select a practical subset of global climate models (GCMs) for regional integrated assessment of climate impacts when resource limitations do not permit the full ensemble of GCMs to be evaluated given the need to also focus on impacts sector and economics models. Subsetting inherently leads to a loss of information but can free up resources to explore important uncertainties in the integrated assessment that would otherwise be prohibitive. The Representative T&P GCM Subsetting Approach identifies five individual GCMs that capture a profile of the full ensemble of temperature and precipitation change within the growing season while maintaining information about the probability that basic classes of climate changes (relatively cool/wet, cool/dry, middle, hot/wet, and hot/dry) are projected in the full GCM ensemble. We demonstrate the selection methodology for maize impacts in Ames, Iowa, and discuss limitations and situations when additional information may be required to select representative GCMs. We then classify 29 GCMs over all land areas to identify regions and seasons with characteristic diagonal skewness related to surface moisture as well as extreme skewness connected to snow-albedo feedbacks and GCM uncertainty. Finally, we employ this basic approach to recognize that GCM projections demonstrate coherence across space, time, and greenhouse gas concentration pathway. The Representative T&P GCM Subsetting Approach provides a quantitative basis for the determination of useful GCM subsets, provides a practical and coherent approach where previous assessments selected solely on availability of scenarios, and may be extended for application to a range of scales and sectoral impacts.

Quantifying alluvial fan sensitivity to climate in Death Valley, California, from field observations and numerical models

NASA Astrophysics Data System (ADS)

Brooke, Sam; Whittaker, Alexander; Armitage, John; D'Arcy, Mitch; Watkins, Stephen

2017-04-01

A quantitative understanding of landscape sensitivity to climate change remains a key challenge in the Earth Sciences. The stream-flow deposits of coupled catchment-fan systems offer one way to decode past changes in external boundary conditions as they comprise simple, closed systems that can be represented effectively by numerical models. Here we combine the collection and analysis of grain size data on well-dated alluvial fan surfaces in Death Valley, USA, with numerical modelling to address the extent to which sediment routing systems record high-frequency, high-magnitude climate change. We compile a new database of Holocene and Late-Pleistocene grain size trends from 11 alluvial fans in Death Valley, capturing high-resolution grain size data ranging from the Recent to 100 kyr in age. We hypothesise the observed changes in average surface grain size and fining rate over time are a record of landscape response to glacial-interglacial climatic forcing. With this data we are in a unique position to test the predictions of landscape evolution models and evaluate the extent to which climate change has influenced the volume and calibre of sediment deposited on alluvial fans. To gain insight into our field data and study area, we employ an appropriately-scaled catchment-fan model that calculates an eroded volumetric sediment budget to be deposited in a subsiding basin according to mass balance where grain size trends are predicted by a self-similarity fining model. We use the model to compare predicted trends in alluvial fan stratigraphy as a function of boundary condition change for a range of model parameters and input grain size distributions. Subsequently, we perturb our model with a plausible glacial-interglacial magnitude precipitation change to estimate the requisite sediment flux needed to generate observed field grain size trends in Death Valley. Modelled fluxes are then compared with independent measurements of sediment supply over time. Our results constitute one of the first attempts to combine the detailed collection of alluvial fan grain size data in time and space with coupled catchment-fan models, affording us the means to evaluate how well field and model data can be reconciled for simple sediment routing systems.

[Emotional climate and internal communication in a clinical management unit compared with two traditional hospital services].

PubMed

Alonso, E; Rubio, A; March, J C; Danet, A

2011-01-01

The aim of this study is to compare the emotional climate, quality of communication and performance indicators in a clinical management unit and two traditional hospital services. Quantitative study. questionnaire of 94 questions. 83 health professionals (63 responders) from the clinical management unit of breast pathology and the hospital services of medical oncology and radiation oncology. descriptive statistics, comparison of means, correlation and linear regression models. The clinical management unit reaches higher values compared with the hospital services about: performance indicators, emotional climate, internal communication and evaluation of the leadership. An important gap between existing and desired sources, channels, media and subjects of communication appear, in both clinical management unit and traditional services. The clinical management organization promotes better internal communication and interpersonal relations, leading to improved performance indicators. Copyright © 2011 SECA. Published by Elsevier Espana. All rights reserved.

Biodestruction of strongly swelling polymer hydrogels and its effect on the water retention capacity of soils

NASA Astrophysics Data System (ADS)

Smagin, A. V.; Sadovnikova, N. B.; Smagina, M. V.

2014-06-01

The biodestruction of strongly swelling polymer hydrogels (water adsorbing soil conditioners of the new generation) has been studied at the quantitative level using original mathematical models. In laboratory experiments, a relationship between the hydrogel degradation rate and the temperature has been obtained, and the effect of the biodestruction on the water retention curve of soil compositions with hydrogels (used as an index of their water retention capacity) has been assessed. From the automatic monitoring data of the temperature regime of soils, the potential biodestruction of hydrogels has been predicted for different climatic conditions. The loss of hydrogels during three months of the vegetation period because of destruction can exceed 30% of their initial content in irrigated agriculture under arid climatic conditions and more than 10% under humid climatic conditions. Thus, the biodestruction of hydrogels is one of the most important factors decreasing their efficiency under actual soil conditions.

Gravity Waves Generated by Convection: A New Idealized Model Tool and Direct Validation with Satellite Observations

NASA Astrophysics Data System (ADS)

Alexander, M. Joan; Stephan, Claudia

2015-04-01

In climate models, gravity waves remain too poorly resolved to be directly modelled. Instead, simplified parameterizations are used to include gravity wave effects on model winds. A few climate models link some of the parameterized waves to convective sources, providing a mechanism for feedback between changes in convection and gravity wave-driven changes in circulation in the tropics and above high-latitude storms. These convective wave parameterizations are based on limited case studies with cloud-resolving models, but they are poorly constrained by observational validation, and tuning parameters have large uncertainties. Our new work distills results from complex, full-physics cloud-resolving model studies to essential variables for gravity wave generation. We use the Weather Research Forecast (WRF) model to study relationships between precipitation, latent heating/cooling and other cloud properties to the spectrum of gravity wave momentum flux above midlatitude storm systems. Results show the gravity wave spectrum is surprisingly insensitive to the representation of microphysics in WRF. This is good news for use of these models for gravity wave parameterization development since microphysical properties are a key uncertainty. We further use the full-physics cloud-resolving model as a tool to directly link observed precipitation variability to gravity wave generation. We show that waves in an idealized model forced with radar-observed precipitation can quantitatively reproduce instantaneous satellite-observed features of the gravity wave field above storms, which is a powerful validation of our understanding of waves generated by convection. The idealized model directly links observations of surface precipitation to observed waves in the stratosphere, and the simplicity of the model permits deep/large-area domains for studies of wave-mean flow interactions. This unique validated model tool permits quantitative studies of gravity wave driving of regional circulation and provides a new method for future development of realistic convective gravity wave parameterizations.

Sensitivity of the Tropical Atmospheric Energy Balance to ENSO-Related SST Changes: Comparison of Climate Model Simulations to Observed Responses

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Fitzjarrald, Dan; Marshall, Susan; Oglesby, Robert; Roads, John; Arnold, James E. (Technical Monitor)

2001-01-01

This paper focuses on how fresh water and radiative fluxes over the tropical oceans change during ENSO warm and cold events and how these changes affect the tropical energy balance. At present, ENSO remains the most prominent known mode of natural variability at interannual time scales. While this natural perturbation to climate is quite distinct from possible anthropogenic changes in climate, adjustments in the tropical water and energy budgets during ENSO may give insight into feedback processes involving water vapor and cloud feedbacks. Although great advances have been made in understanding this phenomenon and realizing prediction skill over the past decade, our ability to document the coupled water and energy changes observationally and to represent them in climate models seems far from settled (Soden, 2000 J Climate). In a companion paper we have presented observational analyses, based principally on space-based measurements which document systematic changes in rainfall, evaporation, and surface and top-of-atmosphere (TOA) radiative fluxes. Here we analyze several contemporary climate models run with observed SSTs over recent decades and compare SST-induced changes in radiation, precipitation, evaporation, and energy transport to observational results. Among these are the NASA / NCAR Finite Volume Model, the NCAR Community Climate Model, the NCEP Global Spectral Model, and the NASA NSIPP Model. Key disagreements between model and observational results noted in the recent literature are shown to be due predominantly to observational shortcomings. A reexamination of the Langley 8-Year Surface Radiation Budget data reveals errors in the SST surface longwave emission due to biased SSTs. Subsequent correction allows use of this data set along with ERBE TOA fluxes to infer net atmospheric radiative heating. Further analysis of recent rainfall algorithms provides new estimates for precipitation variability in line with interannual evaporation changes inferred from the da Silva, Young, Levitus COADS analysis. The overall results from our analysis suggest an increase (decrease) of the hydrologic cycle during ENSO warm (cold) events at the rate of about 5 W/sq m per K of SST change. Model results agree reasonably well with this estimate of sensitivity. This rate is slightly less than that which would be expected for constant relative humidity over the tropical oceans. There remain, however, significant quantitative uncertainties in cloud forcing changes in the models as compared to observations. These differences are examined in relationship to model convection and cloud parameterizations Analysis of the possible sampling and measurement errors compared to systematic model errors is also presented.

Risk assessments of regional climate change over Europe: generation of probabilistic ensemble and uncertainty assessment for EURO-CODEX

NASA Astrophysics Data System (ADS)

Yuan, J.; Kopp, R. E.

2017-12-01

Quantitative risk analysis of regional climate change is crucial for risk management and impact assessment of climate change. Two major challenges to assessing the risks of climate change are: CMIP5 model runs, which drive EURO-CODEX downscaling runs, do not cover the full range of uncertainty of future projections; Climate models may underestimate the probability of tail risks (i.e. extreme events). To overcome the difficulties, this study offers a viable avenue, where a set of probabilistic climate ensemble is generated using the Surrogate/Model Mixed Ensemble (SMME) method. The probabilistic ensembles for temperature and precipitation are used to assess the range of uncertainty covered by five bias-corrected simulations from the high-resolution (0.11º) EURO-CODEX database, which are selected by the PESETA (The Projection of Economic impacts of climate change in Sectors of the European Union based on bottom-up Analysis) III project. Results show that the distribution of SMME ensemble is notably wider than both distribution of raw ensemble of GCMs and the spread of the five EURO-CORDEX in RCP8.5. Tail risks are well presented by the SMME ensemble. Both SMME ensemble and EURO-CORDEX projections are aggregated to administrative level, and are integrated into impact functions of PESETA III to assess climate risks in Europe. To further evaluate the uncertainties introduced by the downscaling process, we compare the 5 runs from EURO-CORDEX with runs from the corresponding GCMs. Time series of regional mean, spatial patterns, and climate indices are examined for the future climate (2080-2099) deviating from the present climate (1981-2010). The downscaling processes do not appear to be trend-preserving, e.g. the increase in regional mean temperature from EURO-CORDEX is slower than that from the corresponding GCM. The spatial pattern comparison reveals that the differences between each pair of GCM and EURO-CORDEX are small in winter. In summer, the temperatures of EURO-CORDEX are generally lower than those of GCMs, while the drying trends in precipitation of EURO-CORDEX are smaller than those of GCMs. Climate indices are significantly affected by bias-correction and downscaling process. Our study provides valuable information for selecting climate indices in different regions over Europe.

Formation of Valley Networks in a Cold and Icy Early Mars Climate: Predictions for Erosion Rates and Channel Morphology

NASA Astrophysics Data System (ADS)

Cassanelli, J.

2017-12-01

Mars is host to a diverse array of valley networks, systems of linear-to-sinuous depressions which are widely distributed across the surface and which exhibit branching patterns similar to the dendritic drainage patterns of terrestrial fluvial systems. Characteristics of the valley networks are indicative of an origin by fluvial activity, providing among the most compelling evidence for the past presence of flowing liquid water on the surface of Mars. Stratigraphic and crater age dating techniques suggest that the formation of the valley networks occurred predominantly during the early geologic history of Mars ( 3.7 Ga). However, whether the valley networks formed predominantly by rainfall in a relatively warm and wet early Mars climate, or by snowmelt and episodic rainfall in an ambient cold and icy climate, remains disputed. Understanding the formative environment of the valley networks will help distinguish between these warm and cold end-member early Mars climate models. Here we test a conceptual model for channel incision and evolution under cold and icy conditions with a substrate characterized by the presence of an ice-free dry active layer and subjacent ice-cemented regolith, similar to that found in the Antarctic McMurdo Dry Valleys. We implement numerical thermal models, quantitative erosion and transport estimates, and morphometric analyses in order to outline predictions for (1) the precise nature and structure of the substrate, (2) fluvial erosion/incision rates, and (3) channel morphology. Model predictions are compared against morphologic and morphometric observational data to evaluate consistency with the assumed cold climate scenario. In the cold climate scenario, the substrate is predicted to be characterized by a kilometers-thick globally-continuous cryosphere below a 50-100 meter thick desiccated ice-free zone. Initial results suggest that, with the predicted substrate structure, fluvial channel erosion and morphology in a cold early Mars climate exposed to episodic high temperatures will not differ significantly from that in a warm climate. The fundamentally different hydrologic conditions are likely to influence other aspects of valley network morphology and morphometry including: drainage density, drainage pattern, and stream orders.

Regional climate modulates the canopy mosaic of favourable and risky microclimates for insects.

PubMed

Pincebourde, Sylvain; Sinoquet, Herve; Combes, Didier; Casas, Jerome

2007-05-01

1. One major gap in our ability to predict the impacts of climate change is a quantitative analysis of temperatures experienced by organisms under natural conditions. We developed a framework to describe and quantify the impacts of local climate on the mosaic of microclimates and physiological states of insects within tree canopies. This approach was applied to a leaf mining moth feeding on apple leaf tissues. 2. Canopy geometry was explicitly considered by mapping the 3D position and orientation of more than 26 000 leaves in an apple tree. Four published models for canopy radiation interception, energy budget of leaves and mines, body temperature and developmental rate of the leaf miner were integrated. Model predictions were compared with actual microclimate temperatures. The biophysical model accurately predicted temperature within mines at different positions within the tree crown. 3. Field temperature measurements indicated that leaf and mine temperature patterns differ according to the regional climatic conditions (cloudy or sunny) and depending on their location within the canopy. Mines in the sun can be warmer than those in the shade by several degrees and the heterogeneity of mine temperature was incremented by 120%, compared with that of leaf temperature. 4. The integrated model was used to explore the impact of both warm and exceptionally hot climatic conditions recorded during a heat wave on the microclimate heterogeneity at canopy scale. During warm conditions, larvae in sunlight-exposed mines experienced nearly optimal growth conditions compared with those within shaded mines. The developmental rate was increased by almost 50% in the sunny microhabitat compared with the shaded location. Larvae, however, experienced optimal temperatures for their development inside shaded mines during extreme climatic conditions, whereas larvae in exposed mines were overheating, leading to major risks of mortality. 5. Tree canopies act as both magnifiers and reducers of the climatic regime experienced in open air outside canopies. Favourable and risky spots within the canopy do change as a function of the climatic conditions at the regional scale. The shifting nature of the mosaic of suitable and risky habitats may explain the observed uniform distribution of leaf miners within tree canopies.

Optical properties of volcanic ash: improving remote sensing observations.

NASA Astrophysics Data System (ADS)

Whelley, Patrick; Colarco, Peter; Aquila, Valentina; Krotkov, Nickolay; Bleacher, Jake; Garry, Brent; Young, Kelsey; Rocha Lima, Adriana; Martins, Vanderlei; Carn, Simon

2016-04-01

Many times each year explosive volcanic eruptions loft ash into the atmosphere. Global travel and trade rely on aircraft vulnerable to encounters with airborne ash. Volcanic ash advisory centers (VAACs) rely on dispersion forecasts and satellite data to issue timely warnings. To improve ash forecasts model developers and satellite data providers need realistic information about volcanic ash microphysical and optical properties. In anticipation of future large eruptions we can study smaller events to improve our remote sensing and modeling skills so when the next Pinatubo 1991 or larger eruption occurs, ash can confidently be tracked in a quantitative way. At distances >100km from their sources, drifting ash plumes, often above meteorological clouds, are not easily detected from conventional remote sensing platforms, save deriving their quantitative characteristics, such as mass density. Quantitative interpretation of these observations depends on a priori knowledge of the spectral optical properties of the ash in UV (>0.3μm) and TIR wavelengths (>10μm). Incorrect assumptions about the optical properties result in large errors in inferred column mass loading and size distribution, which misguide operational ash forecasts. Similarly, simulating ash properties in global climate models also requires some knowledge of optical properties to improve aerosol speciation.

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.

Climate change on the Colorado River: a method to search for robust management strategies

NASA Astrophysics Data System (ADS)

Keefe, R.; Fischbach, J. R.

2010-12-01

The Colorado River is a principal source of water for the seven Basin States, providing approximately 16.5 maf per year to users in the southwestern United States and Mexico. Though the dynamics of the river ensure Upper Basin users a reliable supply of water, the three Lower Basin states (California, Nevada, and Arizona) are in danger of delivery interruptions as Upper Basin demand increases and climate change threatens to reduce future streamflows. In light of the recent drought and uncertain effects of climate change on Colorado River flows, we evaluate the performance of a suite of policies modeled after the shortage sharing agreement adopted in December 2007 by the Department of the Interior. We build on the current literature by using a simplified model of the Lower Colorado River to consider future streamflow scenarios given climate change uncertainty. We also generate different scenarios of parametric consumptive use growth in the Upper Basin and evaluate alternate management strategies in light of these uncertainties. Uncertainty associated with climate change is represented with a multi-model ensemble from the literature, using a nearest neighbor perturbation to increase the size of the ensemble. We use Robust Decision Making to compare near-term or long-term management strategies across an ensemble of plausible future scenarios with the goal of identifying one or more approaches that are robust to alternate assumptions about the future. This method entails using search algorithms to quantitatively identify vulnerabilities that may threaten a given strategy (including the current operating policy) and characterize key tradeoffs between strategies under different scenarios.

Climate vulnerability of drinking water supplies

NASA Astrophysics Data System (ADS)

Selmeczi, Pál; Homolya, Emese; Rotárné Szalkai, Ágnes

2016-04-01

Extreme weather conditions in Hungary led to difficulties in drinking water management on diverse occasions in the past. Due to reduced water resources and the coexisting high demand for drinking water in dry summer periods the availability of a number of water supplies became insufficient therefore causing limitations in water access. In some other cases, as a result of floods and flash floods over karstic areas evolving in consequence of excessive precipitation, several water supplies had to be excluded in order to avoid the risk of infections. More frequent occurrence of extreme weather conditions and further possible changes in the future induce the necessity for an analysis of the vulnerability of drinking water resources to climate change. Since 95% of the total drinking water supply in Hungary originates from subsurface layers, significance of groundwater resources is outstanding. The aim of our work carried out in the frames of the NAGiS (National Adaptation Geo-information System) project was to build up a methodology for the study and determination of the vulnerability of drinking water supplies to climate. The task covered analyses of climatic parameters influencing drinking water supplies principally and hydrogeological characteristics of the geological media that significantly determines vulnerability. Effects on drinking water resources and their reduction or exclusion may imply societal and economic consequences therefore we extended the analyses to the investigation of possibilities concerning the adaptation capacity to changed conditions. We applied the CIVAS (Climate Impact and Vulnerability Assessment Scheme) model developed in the frames of the international climate research project CLAVIER (Climate Change and Variability: Impact on Central and Eastern Europe) to characterize climate vulnerability of drinking water supplies. The CIVAS model, being based on the combined evaluation of exposure, sensitivity and adaptability, provides a unified methodical scheme to quantitative climatic impact assessment. We investigate the effects of climate change in the integrated context of exposure, sensitivity, impact, adaptive capacity and vulnerability, thus apart from the expected environmental changes societal and economic processes are also taken into account. Climate vulnerability has been determined on the basis of the distribution and categorisation of the chosen indicators. Further effects, independent of climate change and caused by anthropogenic activity, result in similar phenomena. It is often difficult to differentiate between natural and anthropogenic effects that occur simultaneously therefore in the analyses of vulnerability anthropogenic activity is needed to be taken into account. We determined climate vulnerability using data of two different climate models and for two separate future time periods. Results on the basis of both climate model projections suggest that a considerable number of regions in the area under investigation appear to be vulnerable to climate change to a certain extent and vulnerability intensifies to the end of the 21th century.

Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index

NASA Technical Reports Server (NTRS)

Zhang, Ping; Anderson, Bruce; Tan, Bin; Barlow, Mathew; Myneni, Ranga

2011-01-01

A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.

Development of Nested Socioeconomic Storylines for Climate Change IAV Applications (Invited)

NASA Astrophysics Data System (ADS)

Preston, B. L.; Absar, M.

2013-12-01

Socioeconomic scenarios are important for understanding future societal consequences of climate and weather. The global shared socioeconomic pathways (SSPs) represent a new opportunity for coordinated development and application of such scenarios to improve the representation of alternative societal development pathways within climate change consequence analysis. However, capitalizing on this opportunity necessitates bridging the scale disparity between the global SSPs and the regional/local context for which many impact, adaptation and vulnerability (IAV) studies are conducted. To this end, we adopted the Factor, Actor, and Sector methodology to develop a set of qualitative national and sub-national socioeconomic storylines for the United States and U.S. Southeast using the global SSPs as boundary conditions. In particular, our study sought to develop storylines to explore alternative socioeconomic futures for the U.S. Southeast and their implications for adaptive capacity of the region's energy, water, and agricultural sectors. These storylines subsequently serve as the foundation for a range of downstream IAV applications. These include qualitative vulnerability analysis to explore interactions between energy, water, and agriculture in a changing climate; as well as quantitative impact assessment where regional storylines are used to establish modeling parameters within a biophysical crop model. Such methods and applications illustrate potentially useful opportunities for routinizing the use of SSP-based storylines in IAV studies.

Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) Final Campaign Report

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

Wood, R.

2016-01-01

The extensive coverage of low clouds over the subtropical eastern oceans greatly impacts the current climate. In addition, the response of low clouds to changes in atmospheric greenhouse gases and aerosols is a major source of uncertainty, which thwarts accurate prediction of future climate change. Low clouds are poorly simulated in climate models, partly due to inadequate long-term simultaneous observations of their macrophysical and microphysical structure, radiative effects, and associated aerosol distribution in regions where their impact is greatest. The thickness and extent of subtropical low clouds is dependent on tight couplings between surface fluxes of heat and moisture, radiativemore » cooling, boundary layer turbulence, and precipitation (much of which evaporates before reaching the ocean surface and is closely connected to the abundance of cloud condensation nuclei). These couplings have been documented as a result of past field programs and model studies. However, extensive research is still required to achieve a quantitative understanding sufficient for developing parameterizations, which adequately predict aerosol indirect effects and low cloud response to climate perturbations. This is especially true of the interactions between clouds, aerosol, and precipitation. These processes take place in an ever-changing synoptic environment that can confound interpretation of short time period observations.« less

Limited potential for adaptation to climate change in a broadly distributed marine crustacean.

PubMed

Kelly, Morgan W; Sanford, Eric; Grosberg, Richard K

2012-01-22

The extent to which acclimation and genetic adaptation might buffer natural populations against climate change is largely unknown. Most models predicting biological responses to environmental change assume that species' climatic envelopes are homogeneous both in space and time. Although recent discussions have questioned this assumption, few empirical studies have characterized intraspecific patterns of genetic variation in traits directly related to environmental tolerance limits. We test the extent of such variation in the broadly distributed tidepool copepod Tigriopus californicus using laboratory rearing and selection experiments to quantify thermal tolerance and scope for adaptation in eight populations spanning more than 17° of latitude. Tigriopus californicus exhibit striking local adaptation to temperature, with less than 1 per cent of the total quantitative variance for thermal tolerance partitioned within populations. Moreover, heat-tolerant phenotypes observed in low-latitude populations cannot be achieved in high-latitude populations, either through acclimation or 10 generations of strong selection. Finally, in four populations there was no increase in thermal tolerance between generations 5 and 10 of selection, suggesting that standing variation had already been depleted. Thus, plasticity and adaptation appear to have limited capacity to buffer these isolated populations against further increases in temperature. Our results suggest that models assuming a uniform climatic envelope may greatly underestimate extinction risk in species with strong local adaptation.

Climate change may restrict dryland forest regeneration in the 21st century

USGS Publications Warehouse

Petrie, M.D.; Bradford, John B.; Hubbard, R.M.; Lauenroth, W.K.; Andrews, Caitlin; Schlaepfer, D.R.

2017-01-01

The persistence and geographic expansion of dryland forests in the 21st century will be influenced by how climate change supports the demographic processes associated with tree regeneration. Yet, the way that climate change may alter regeneration is unclear. We developed a quantitative framework that estimates forest regeneration potential (RP) as a function of key environmental conditions for ponderosa pine, a key dryland forest species. We integrated meteorological data and climate projections for 47 ponderosa pine forest sites across the western United States, and evaluated RP using an ecosystem water balance model. Our primary goal was to contrast conditions supporting regeneration among historical, mid-21st century and late-21st century time frames. Future climatic conditions supported 50% higher RP in 2020–2059 relative to 1910–2014. As temperatures increased more substantially in 2060–2099, seedling survival decreased, RP declined by 50%, and the frequency of years with very low RP increased from 25% to 58%. Thus, climate change may initially support higher RP and increase the likelihood of successful regeneration events, yet will ultimately reduce average RP and the frequency of years with moderate climate support of regeneration. Our results suggest that climate change alone may begin to restrict the persistence and expansion of dryland forests by limiting seedling survival in the late 21st century.

Climate change may restrict dryland forest regeneration in the 21st century.

PubMed

Petrie, M D; Bradford, J B; Hubbard, R M; Lauenroth, W K; Andrews, C M; Schlaepfer, D R

2017-06-01

The persistence and geographic expansion of dryland forests in the 21st century will be influenced by how climate change supports the demographic processes associated with tree regeneration. Yet, the way that climate change may alter regeneration is unclear. We developed a quantitative framework that estimates forest regeneration potential (RP) as a function of key environmental conditions for ponderosa pine, a key dryland forest species. We integrated meteorological data and climate projections for 47 ponderosa pine forest sites across the western United States, and evaluated RP using an ecosystem water balance model. Our primary goal was to contrast conditions supporting regeneration among historical, mid-21st century and late-21st century time frames. Future climatic conditions supported 50% higher RP in 2020-2059 relative to 1910-2014. As temperatures increased more substantially in 2060-2099, seedling survival decreased, RP declined by 50%, and the frequency of years with very low RP increased from 25% to 58%. Thus, climate change may initially support higher RP and increase the likelihood of successful regeneration events, yet will ultimately reduce average RP and the frequency of years with moderate climate support of regeneration. Our results suggest that climate change alone may begin to restrict the persistence and expansion of dryland forests by limiting seedling survival in the late 21st century. © 2017 by the Ecological Society of America.

Life history and spatial traits predict extinction risk due to climate change

NASA Astrophysics Data System (ADS)

Pearson, Richard G.; Stanton, Jessica C.; Shoemaker, Kevin T.; Aiello-Lammens, Matthew E.; Ersts, Peter J.; Horning, Ned; Fordham, Damien A.; Raxworthy, Christopher J.; Ryu, Hae Yeong; McNees, Jason; Akçakaya, H. Reşit

2014-03-01

There is an urgent need to develop effective vulnerability assessments for evaluating the conservation status of species in a changing climate. Several new assessment approaches have been proposed for evaluating the vulnerability of species to climate change based on the expectation that established assessments such as the IUCN Red List need revising or superseding in light of the threat that climate change brings. However, although previous studies have identified ecological and life history attributes that characterize declining species or those listed as threatened, no study so far has undertaken a quantitative analysis of the attributes that cause species to be at high risk of extinction specifically due to climate change. We developed a simulation approach based on generic life history types to show here that extinction risk due to climate change can be predicted using a mixture of spatial and demographic variables that can be measured in the present day without the need for complex forecasting models. Most of the variables we found to be important for predicting extinction risk, including occupied area and population size, are already used in species conservation assessments, indicating that present systems may be better able to identify species vulnerable to climate change than previously thought. Therefore, although climate change brings many new conservation challenges, we find that it may not be fundamentally different from other threats in terms of assessing extinction risks.

Ecohydrologic process modeling of mountain block groundwater recharge.

PubMed

Magruder, Ian A; Woessner, William W; Running, Steve W

2009-01-01

Regional mountain block recharge (MBR) is a key component of alluvial basin aquifer systems typical of the western United States. Yet neither water scientists nor resource managers have a commonly available and reasonably invoked quantitative method to constrain MBR rates. Recent advances in landscape-scale ecohydrologic process modeling offer the possibility that meteorological data and land surface physical and vegetative conditions can be used to generate estimates of MBR. A water balance was generated for a temperate 24,600-ha mountain watershed, elevation 1565 to 3207 m, using the ecosystem process model Biome-BGC (BioGeochemical Cycles) (Running and Hunt 1993). Input data included remotely sensed landscape information and climate data generated with the Mountain Climate Simulator (MT-CLIM) (Running et al. 1987). Estimated mean annual MBR flux into the crystalline bedrock terrain is 99,000 m(3) /d, or approximately 19% of annual precipitation for the 2003 water year. Controls on MBR predictions include evapotranspiration (radiation limited in wet years and moisture limited in dry years), soil properties, vegetative ecotones (significant at lower elevations), and snowmelt (dominant recharge process). The ecohydrologic model is also used to investigate how climatic and vegetative controls influence recharge dynamics within three elevation zones. The ecohydrologic model proves useful for investigating controls on recharge to mountain blocks as a function of climate and vegetation. Future efforts will need to investigate the uncertainty in the modeled water balance by incorporating an advanced understanding of mountain recharge processes, an ability to simulate those processes at varying scales, and independent approaches to calibrating MBR estimates. Copyright © 2009 The Author(s). Journal compilation © 2009 National Ground Water Association.

Hydrology and density feedbacks control the ecology of intermediate hosts of schistosomiasis across habitats in seasonal climates

PubMed Central

Perez-Saez, Javier; Mande, Theophile; Ceperley, Natalie; Bertuzzo, Enrico; Mari, Lorenzo; Rinaldo, Andrea

2016-01-01

We report about field and theoretical studies on the ecology of the aquatic snails (Bulinus spp. and Biomphalaria pfeifferi) that serve as obligate intermediate hosts in the complex life cycle of the parasites causing human schistosomiasis. Snail abundance fosters disease transmission, and thus the dynamics of snail populations are critically important for schistosomiasis modeling and control. Here, we single out hydrological drivers and density dependence (or lack of it) of ecological growth rates of local snail populations by contrasting novel ecological and environmental data with various models of host demography. Specifically, we study various natural and man-made habitats across Burkina Faso’s highly seasonal climatic zones. Demographic models are ranked through formal model comparison and structural risk minimization. The latter allows us to evaluate the suitability of population models while clarifying the relevant covariates that explain empirical observations of snail abundance under the actual climatic forcings experienced by the various field sites. Our results link quantitatively hydrological drivers to distinct population dynamics through specific density feedbacks, and show that statistical methods based on model averaging provide reliable snail abundance projections. The consistency of our ranking results suggests the use of ad hoc models of snail demography depending on habitat type (e.g., natural vs. man-made) and hydrological characteristics (e.g., ephemeral vs. permanent). Implications for risk mapping and space-time allocation of control measures in schistosomiasis-endemic contexts are discussed. PMID:27162339

Hydrology and density feedbacks control the ecology of intermediate hosts of schistosomiasis across habitats in seasonal climates.

PubMed

Perez-Saez, Javier; Mande, Theophile; Ceperley, Natalie; Bertuzzo, Enrico; Mari, Lorenzo; Gatto, Marino; Rinaldo, Andrea

2016-06-07

We report about field and theoretical studies on the ecology of the aquatic snails (Bulinus spp. and Biomphalaria pfeifferi) that serve as obligate intermediate hosts in the complex life cycle of the parasites causing human schistosomiasis. Snail abundance fosters disease transmission, and thus the dynamics of snail populations are critically important for schistosomiasis modeling and control. Here, we single out hydrological drivers and density dependence (or lack of it) of ecological growth rates of local snail populations by contrasting novel ecological and environmental data with various models of host demography. Specifically, we study various natural and man-made habitats across Burkina Faso's highly seasonal climatic zones. Demographic models are ranked through formal model comparison and structural risk minimization. The latter allows us to evaluate the suitability of population models while clarifying the relevant covariates that explain empirical observations of snail abundance under the actual climatic forcings experienced by the various field sites. Our results link quantitatively hydrological drivers to distinct population dynamics through specific density feedbacks, and show that statistical methods based on model averaging provide reliable snail abundance projections. The consistency of our ranking results suggests the use of ad hoc models of snail demography depending on habitat type (e.g., natural vs. man-made) and hydrological characteristics (e.g., ephemeral vs. permanent). Implications for risk mapping and space-time allocation of control measures in schistosomiasis-endemic contexts are discussed.

Career Paths for Geosciences Students (Invited)

NASA Astrophysics Data System (ADS)

Bowers, T. S.; Flewelling, S. A.

2013-12-01

Current and future drivers of hiring in the geosciences include climate, environment, energy, georisk and litigation areas. Although climate is closely linked to the atmospheric sciences, hiring needs in the geosciences exist as well, in understanding potential impacts of climate change on coastal erosion and water resources. Where and how to consider carbon sequestration as a climate mitigation policy will also require geosciences expertise. The environmental sciences have long been a source of geosciences hiring, and have ongoing needs in the areas of investigation of contamination, and in fluid and chemical transport. The recent expansion of the energy sector in the U.S. is providing opportunities for the geosciences in oil and gas production, hydraulic fracturing, and in geothermal development. In georisk, expertise in earthquake and volcanic hazard prediction are increasingly important, particularly in population centers. Induced seismicity is a relatively new area of georisk that will also require geosciences skills. The skills needed in the future geosciences workforce are increasingly interdisciplinary, and include those that are both observational and quantitative. Field observations and their interpretation must be focused forward as well as backwards and include the ability to recognize change as it occurs. Areas of demand for quantitative skills include hydrological, geophysical, and geochemical modeling, math and statistics, with specialties such as rock mechanics becoming an increasingly important area. Characteristics that students should have to become successful employees in these sectors include strong communication skills, both oral and written, the ability to know when to stop "studying" and identify next steps, and the ability to turn research areas into solutions to problems.

The role of organic soil layer on the fate of Siberian larch forest and near-surface permafrost under changing climate: A simulation study

NASA Astrophysics Data System (ADS)

SATO, H.; Iwahana, G.; Ohta, T.

2013-12-01

Siberian larch forest is the largest coniferous forest region in the world. In this vast region, larch often forms nearly pure stands, regenerated by recurrent fire. This region is characterized by a short and dry growing season; the annual mean precipitation for Yakutsk was only about 240 mm. To maintain forest ecosystem under such small precipitation, underlying permafrost and seasonal soil freezing-thawing-cycle have been supposed to play important roles; (1) frozen ground inhibits percolation of soil water into deep soil layers, and (2) excess soil water at the end of growing season can be carried over until the next growing season as ice, and larch trees can use the melt water. As a proof for this explanation, geographical distribution of Siberian larch region highly coincides with continuous and discontinuous permafrost zone. Recent observations and simulation studies suggests that existences of larch forest and permafrost in subsurface layer are co-dependent; permafrost maintains the larch forest by enhancing water use efficiency of trees, while larch forest maintains permafrost by inhibiting solar radiation and preventing heat exchanges between soil and atmosphere. Owing to such complexity and absence of enough ecosystem data available, current-generation Earth System Models significantly diverse in their prediction of structure and key ecosystem functions in Siberian larch forest under changing climate. Such uncertainty should in turn expand uncertainty over predictions of climate, because Siberian larch forest should have major role in the global carbon balance with its huge area and vast potential carbon pool within the biomass and soil, and changes in boreal forest albedo can have a considerable effect on Northern Hemisphere climate. In this study, we developed an integrated ecosystem model, which treats interactions between plant-dynamics and freeze-thaw cycles. This integrated model contains a dynamic global vegetation model SEIB-DGVM, which simulates plant and carbon dynamics. It also contains a one-dimensional land surface model NOAH 2.7.1, which simulates soil moisture (both liquid and frozen), soil temperature, snowpack depth and density, canopy water content, and the energy and water fluxes. This integrated model quantitatively reconstructs post-fire development of forest structure (i.e. LAI and biomass) and organic soil layer, which dampens heat exchanges between soil and atmosphere. With the post-fire development of LAI and the soil organic layer, the integrated model also quantitatively reconstructs changes in seasonal maximum of active layer depth. The integrated model is then driven by the IPCC A1B scenario of rising atmospheric CO2, and by climate changes during the twenty-first century resulting from the change in CO2. This simulation suggests that forecasted global warming would causes decay of Siberian larch ecosystem, but such responses could be delayed by "memory effect" of the soil organic layer for hundreds of years.

Coupled hydrogeological and geomechanical modelling for the analysis of large slope instabilities.

NASA Astrophysics Data System (ADS)

Laloui, Lyesse; Ferrari, Alessio; Bonnard, Christophe

2010-05-01

Slowly-moving landslides (average velocity between 2 and 10 cm/year) are quite frequent in mountainous or hilly areas and they may display occasional crises, generally due to exceptional climatic conditions. The hazard related to these events cannot be analysed in terms of probability analysis, as the number of recorded past events is generally very small and climate changes could significantly modify the environmental setting. Quantitative relationships relating climatic condition fluctuations and sliding area velocity must then be pursued by taking into account the most relevant physical processes involved in the landslide behaviours. Conventional stability analyses are unable to deal with such questions because they do not allow the velocity fields to be determined. With regard to the behaviour of large slope instabilities, a methodology is presented which aims to describe the behaviour of slow-moving landslides by means of a coupled hydrogeological and geomechanical modelling framework. As it is well known, the evolution of the pore water pressure within the landslide body is often recognized as the main cause for the occurrence of displacement accelerations. In this sense the interaction among the hydrological and the mechanical responses must be considered to analyse the landslide behaviour, with the aim of quantitatively relating pore water pressure variations and movements. For a given case study, pore water pressure evolutions in space and time are obtained from a duly calibrated finite element hydrogeological model, which can take into account the role of several key factors such as infiltration, preferential flows and vegetation. Computed groundwater pressures resulting from the hydrogeological simulations are introduced as nodal forces in a finite element geomechanical model in order to calculate stress evolutions and displacements. The use of advanced constitutive models based on the generalised effective stress concept allows taking into account specific behavioural features such as the effects of the changes in the degree of saturation, associated to the fluctuation of the groundwater level. The geomechanical model is calibrated comparing computed and measured displacements in relevant points of the slope. When appropriate, the outcomes from the geomechanical model can be used in an iterative way to update the hydrogeological model settings. In this way it is possible to simulate the evolution of critical factors (such as permeability or retention properties of the involved materials) associated to the cumulated displacements. Once calibrated, the coupled models can be used to assess the landslide behaviour under different scenarios, including modified climatic conditions and the implementation of mitigation measures. Applications to relevant case studies are presented in order to demonstrate the adequacy and the usefulness of the proposed modelling framework.

Quantifying sediment dynamics on alluvial fans, Iglesia basin, south Central Argentine Andes

NASA Astrophysics Data System (ADS)

Harries, Rebekah; Kirstein, Linda; Whittaker, Alex; Attal, Mikael; Peralta, Silvio

2017-04-01

Qualitative interpretations of environmental change drawn from alluvial fan stratigraphy typically tie the deposition of greater volumes of coarser sediment to wetter climatic periods. For example, step changes in sediment flux and discharge associated with glacial-interglacial cycles are often linked to the progradation and back stepping of a fan's toe (Harvey et al, 2002). Indeed, more recent quantitative stratigraphic models demonstrate changes in the volume and calibre of sediment fluxed from an uplifted catchment can produce predictable shifts in the rate at which fluvial deposits fine downstream (Duller et al. 2010, Armitage et al. 2011). These interpretations, however, make three important assumptions: 1) the volume and calibre of the sediment transferred from an eroding mountain belt to a depositional basin is directly related to climate through some value of time-averaged discharge or catchment wetness; 2) lateral sources of sediment, such as tributaries, do not significantly influence the pattern of deposition in a basin and, similarly, 3) the reworking of older fan surfaces is minimal and does not impact the depositional pattern of younger deposits. Here we demonstrate each of these assumptions underestimates the importance of variance in transportable grain sizes in influencing the local and basin-wide deposited grain size trends. Using the Iglesia basin in the Argentine south Central Andes as a natural laboratory, we compare three large, adjacent, alluvial fan systems whose catchments experience the same background tectonic and climatic forcing. We find regional climate forcing is not expressed uniformly in the downstream grain size fining rates of their modern systems. Furthermore, we observe the variance in transportable grain sizes supplied from each primary catchment and the variance of material introduced by tributaries and fan surfaces downstream can act as first order controls on the rate of downstream fining. We also raise the importance of considering factors such as climate storminess and degree of glacial cover in having a dominant control on the variance of sediment released. These findings have significant implications for our ability to invert the fluvial stratigraphy for climatically driven changes in discharge and highlight a need to quantify the impact of sediment dynamics on modern systems so that we may better understand the limitations in applying quantitative models to ancient stratigraphy.

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

NASA Astrophysics Data System (ADS)

Urrego-Blanco, Jorge R.; Urban, Nathan M.; Hunke, Elizabeth C.; Turner, Adrian K.; Jeffery, Nicole

2016-04-01

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. It is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.

Impacts of Climate Change On The Occurrence of Extreme Events: The Mice Project

NASA Astrophysics Data System (ADS)

Palutikof, J. P.; Mice Team

It is widely accepted that climate change due to global warming will have substan- tial impacts on the natural environment, and on human activities. Furthermore, it is increasingly recognized that changes in the severity and frequency of extreme events, such as windstorm and flood, are likely to be more important than changes in the average climate. The EU-funded project MICE (Modelling the Impacts of Climate Extremes) commenced in January 2002. It seeks to identify the likely changes in the occurrence of extremes of rainfall, temperature and windstorm due to global warm- ing, using information from climate models as a basis, and to study the impacts of these changes in selected European environments. The objectives are: a) to evaluate, by comparison with gridded and station observations, the ability of climate models to successfully reproduce the occurrence of extremes at the required spatial and temporal scales. b) to analyse model output with respect to future changes in the occurrence of extremes. Statistical analyses will determine changes in (i) the return periods of ex- tremes, (ii) the joint probability of extremes (combinations of damaging events such as windstorm followed by heavy rain), (iii) the sequential behaviour of extremes (whether events are well-separated or clustered) and (iv) the spatial patterns of extreme event occurrence across Europe. The range of uncertainty in model predictions will be ex- plored by analysing changes in model experiments with different spatial resolutions and forcing scenarios. c) to determine the impacts of the predicted changes in extremes occurrence on selected activity sectors: agriculture (Mediterranean drought), commer- cial forestry and natural forest ecosystems (windstorm and flood in northern Europe, fire in the Mediterranean), energy use (temperature extremes), tourism (heat stress and Mediterranean beach holidays, changes in the snow pack and winter sports ) and civil protection/insurance (windstorm and flood). Impacts will be evaluated through a combination of techniques ranging from quantitative analyses through to expert judge- ment. Throughout the project, a continuing dialogue with stakeholders and end-users will be maintained.

A Bibliometric Analysis of Climate Engineering Research

NASA Astrophysics Data System (ADS)

Belter, C. W.; Seidel, D. J.

2013-12-01

The past five years have seen a dramatic increase in the number of media and scientific publications on the topic of climate engineering, or geoengineering, and some scientists are increasingly calling for more research on climate engineering as a possible supplement to climate change mitigation and adaptation strategies. In this context, understanding the current state of climate engineering research can help inform policy discussions and guide future research directions. Bibliometric analysis - the quantitative analysis of publications - is particularly applicable to fields with large bodies of literature that are difficult to summarize by traditional review methods. The multidisciplinary nature of the published literature on climate engineering makes it an ideal candidate for bibliometric analysis. Publications on climate engineering are found to be relatively recent (more than half of all articles during 1988-2011 were published since 2008), include a higher than average percentage of non-research articles (30% compared with 8-15% in related scientific disciplines), and be predominately produced by countries located in the Northern Hemisphere and speaking English. The majority of this literature focuses on land-based methods of carbon sequestration, ocean iron fertilization, and solar radiation management and is produced with little collaboration among research groups. This study provides a summary of existing publications on climate engineering, a perspective on the scientific underpinnings of the global dialogue on climate engineering, and a baseline for quantitatively monitoring the development of climate engineering research in the future.

Wetland Ecohydrology: stochastic description of water level fluctuations across the soil surface

NASA Astrophysics Data System (ADS)

Tamea, S.; Muneepeerakul, R.; Laio, F.; Ridolfi, L.; Rodriguez-Iturbe, I.

2009-12-01

Wetlands provide a suite of social and ecological critical functions such as being habitats of disease-carrying vectors, providing buffer zones against hurricanes, controlling sediment transport, filtering nutrients and contaminants, and a repository of great biological diversity. More recently, wetlands have also been recognized as crucial for carbon storage in the context of global climate change. Despite such importance, quantitative approaches to many aspects of wetlands are far from adequate. Therefore, improving our quantitative understanding of wetlands is necessary to our ability to maintain, manage, and restore these invaluable environments. In wetlands, hydrologic factors and ecosystem processes interplay and generate unique characteristics and a delicate balance between biotic and abiotic elements. The main hydrologic driver of wetland ecosystems is the position of the water level that, being above or below ground, determines the submergence or exposure of soil. When the water level is above the soil surface, soil saturation and lack of oxygen causes hypoxia, anaerobic functioning of microorganisms and anoxic stress in plants, that might lead to the death of non-adapted organisms. When the water level lies below the soil surface, the ecosystem becomes groundwater-dependent, and pedological and physiological aspects play their role in the soil water balance. We propose here a quantitative description of wetland ecohydrology, through a stochastic process-based water balance, driven by a marked compound Poisson noise representing rainfall events. The model includes processes such as rainfall infiltration, evapotranspiration, capillary rise, and the contribution of external water bodies, which are quantified in a simple yet realistic way. The semi-analytical steady-state probability distributions of water level spanning across the soil surface are validated with data from the Everglades (Florida, USA). The model and its results allow for a quantitative analysis of the long term behavior of biotic and abiotic factors which depend on the position of the water level and enable the assessment of impacts of climate changes on the wetland ecosystem.

Differences in Assessments of Organizational School Climate between Teachers and Adminsitrators

ERIC Educational Resources Information Center

Duff, Brandy Kinlaw

2013-01-01

The purpose of this quantitative study was to examine the organizational school climate perceptions of teachers and principals and to ascertain the extent to which their perceptions differed. This causal comparative study used the Organizational Climate Description Questionnaire for Elementary Schools (OCDQ-RE) as the survey instrument for data…

EMISSION REDUCTIONS AIMED AT IMPROVING AIR QUALITY: UNINTENDED CLIMATIC CONSEQUENCES AND THE EFFECT OF CLIMATE CHANGE ON THEIR SUCCESS

EPA Science Inventory

This work will provide improved understanding of the role of climate change, both in the recent past and future, on the success of pollutant control strategies, allowing for better planning and accountability of emission reductions. This work will also provide a quantitative a...

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...

Attribution of maize yield increase in China to climate change and technological advancement between 1980 and 2010

NASA Astrophysics Data System (ADS)

Guo, Jianping; Zhao, Junfang; Wu, Dingrong; Mu, Jia; Xu, Yanhong

2014-12-01

Crop yields are affected by climate change and technological advancement. Objectively and quantitatively evaluating the attribution of crop yield change to climate change and technological advancement will ensure sustainable development of agriculture under climate change. In this study, daily climate variables obtained from 553 meteorological stations in China for the period 1961-2010, detailed observations of maize from 653 agricultural meteorological stations for the period 1981-2010, and results using an Agro-Ecological Zones (AEZ) model, are used to explore the attribution of maize (Zea mays L.) yield change to climate change and technological advancement. In the AEZ model, the climatic potential productivity is examined through three step-by-step levels: photosynthetic potential productivity, photosynthetic thermal potential productivity, and climatic potential productivity. The relative impacts of different climate variables on climatic potential productivity of maize from 1961 to 2010 in China are then evaluated. Combined with the observations of maize, the contributions of climate change and technological advancement to maize yield from 1981 to 2010 in China are separated. The results show that, from 1961 to 2010, climate change had a significant adverse impact on the climatic potential productivity of maize in China. Decreased radiation and increased temperature were the main factors leading to the decrease of climatic potential productivity. However, changes in precipitation had only a small effect. The maize yields of the 14 main planting provinces in China increased obviously over the past 30 years, which was opposite to the decreasing trends of climatic potential productivity. This suggests that technological advancement has offset the negative effects of climate change on maize yield. Technological advancement contributed to maize yield increases by 99.6%-141.6%, while climate change contribution was from -41.4% to 0.4%. In particular, the actual maize yields in Shandong, Henan, Jilin, and Inner Mongolia increased by 98.4, 90.4, 98.7, and 121.5 kg hm-2 yr-1 over the past 30 years, respectively. Correspondingly, the maize yields affected by technological advancement increased by 113.7, 97.9, 111.5, and 124.8 kg hm-2 yr-1, respectively. On the contrary, maize yields reduced markedly under climate change, with an average reduction of -9.0 kg hm-2 yr-1. Our findings highlight that agronomic technological advancement has contributed dominantly to maize yield increases in China in the past three decades.

Arctic cities and climate change: climate-induced changes in stability of Russian urban infrastructure built on permafrost

NASA Astrophysics Data System (ADS)

Shiklomanov, Nikolay; Streletskiy, Dmitry; Swales, Timothy

2014-05-01

Planned socio-economic development during the Soviet period promoted migration into the Arctic and work force consolidation in urbanized settlements to support mineral resources extraction and transportation industries. These policies have resulted in very high level of urbanization in the Soviet Arctic. Despite the mass migration from the northern regions during the 1990s following the collapse of the Soviet Union and the diminishing government support, the Russian Arctic population remains predominantly urban. In five Russian Administrative regions underlined by permafrost and bordering the Arctic Ocean 66 to 82% (depending on region) of the total population is living in Soviet-era urban communities. The political, economic and demographic changes in the Russian Arctic over the last 20 years are further complicated by climate change which is greatly amplified in the Arctic region. One of the most significant impacts of climate change on arctic urban landscapes is the warming and degradation of permafrost which negatively affects the structural integrity of infrastructure. The majority of structures in the Russian Arctic are built according to the passive principle, which promotes equilibrium between the permafrost thermal regime and infrastructure foundations. This presentation is focused on quantitative assessment of potential changes in stability of Russian urban infrastructure built on permafrost in response to ongoing and future climatic changes using permafrost - geotechnical model forced by GCM-projected climate. To address the uncertainties in GCM projections we have utilized results from 6 models participated in most recent IPCC model inter-comparison project. The analysis was conducted for entire extent of Russian permafrost-affected area and on several representative urban communities. Our results demonstrate that significant observed reduction in urban infrastructure stability throughout the Russian Arctic can be attributed to climatic changes and that projected future climatic changes will further negatively affect communities on permafrost. However, the uncertainties in magnitude and spatial and temporal patterns of projected climate change produced by individual GCMs translate to substantial variability of the future state of infrastructure built on permafrost.

Remote sensing of ecosystem vulnerability: Assessing climate-vegetation-livestock interactions in Mongolia

NASA Astrophysics Data System (ADS)

Kang, S.; Hong, S. Y.

2015-12-01

Stock breeding is a major economic sector of Mongolia, supporting unique cultural and social identity. In spite of its long history, contemporary pastoralism increases interventions on climate-vegetation interactions substantially, which results in negative feedbacks to livestock sector. This presentation draws an attention how natural processes of climate and vegetation interact with livestock dynamics. Massive loss of livestock and wildlife animal during winter seasons (dzud) is an endemic climatic disaster in the Central Asia grasslands but the mechanisms are not well understood yet. Recent national-wide sever Dzud occurred during 2009-2010 winter in Mongolia. The dzud mechanisms were investigated by developing a schematic mechanism model on climate-vegetation-livestock interactions and applying it for quantitative statistical analysis. Various remote sensing products were integrated to prepare the status and process variables of the schematic model, including daily temperature, precipitation, evapotranspiration, and primary production and biomass for a period from 2003 to 2010. At a lower level of administration (i.e., 'soum' generally larger than 1000 km2), stepwise multiple regression analysis was conducted to find significant factors of inter-annual livestock change. As results, linear regression models were successfully produced at 70% of soums. Summer and winter variables appeared equally important in controlling livestock dynamics. The primary factor of each soum showed certain regional patterns incident well with climate severity and foraging resource availability (e.g. temperature in north, dryness in south, and NDVI in middle). Regional pattern of herbaceous biodiversity depends on both climate and disturbance (i.e. fire and grazing) gradients but the livestock grazing effect appeared localized normally within 1.5 km from livestock shelter or wells. At a local-scale (i.e. family level smaller than 100 km2), species composition seems to provide useful indicator of grazing pressure, while climate and fire disturbance determined regional pattern of vegetation biodiversity. The results provide a useful premise to devise a satellite-based assessment tool for foraging resource availability and biological regime shift by grazing and climate change in future study.

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.

[Impact of changes in land use and climate on the runoff in Liuxihe Watershed based on SWAT model].

PubMed

Yuan, Yu-zhi; Zhang, Zheng-dong; Meng, Jin-hua

2015-04-01

SWAT model, an extensively used distributed hydrological model, was used to quantitatively analyze the influences of changes in land use and climate on the runoff at watershed scale. Liuxihe Watershed' s SWAT model was established and three scenarios were set. The calibration and validation at three hydrological stations of Wenquan, Taipingchang and Nangang showed that the three factors of Wenquan station just only reached the standard in validated period, and the other two stations had relative error (RE) < 15%, correlation coefficient (R2) > 0.8 and Nash-Sutcliffe efficiency valve (Ens) > 0.75, suggesting that SWAT model was appropriate for simulating runoff response to land use change and climate variability in Liuxihe watershed. According to the integrated scenario simulation, the annual runoff increased by 11.23 m3 x s(-1) from 2001 to 2010 compared with the baseline period from 1991 to 2000, among which, the land use change caused an annual runoff reduction of 0.62 m3 x s(-1), whereas climate variability caused an annual runoff increase of 11.85 m3 x s(-1). Apparently, the impact of climate variability was stronger than that of land use change. On the other hand, the scenario simulation of extreme land use showed that compared with the land use in 2000, the annual runoff of the farmland scenario and the grassland scenario increased by 2.7% and 0.5% respectively, while that of the forest land scenario were reduced by 0.7%, which suggested that forest land had an ability of diversion closure. Furthermore, the scenario simulation of climatic variability indicated that the change of river runoff correlated positively with precipitation change (increase of 11.6% in annual runoff with increase of 10% in annual precipitation) , but negatively with air temperature change (reduction of 0.8% in annual runoff with increase of 1 degrees C in annual mean air temperature), which showed that the impact of precipitation variability was stronger than that of air temperature change. Therefore, in face of climate variability, we need to pay attention to strong rainfall forecasts, optimization of land use structure and spatial distribution, which could reduce the negative hydrological effects (such as floods) induced by climate change.

Spatial relationship between climatic diversity and biodiversity conservation value.

PubMed

Wang, Junjun; Wu, Ruidong; He, Daming; Yang, Feiling; Hu, Peijun; Lin, Shiwei; Wu, Wei; Diao, Yixin; Guo, Yang

2018-06-04

Capturing the full range of climatic diversity in a reserve network is expected to improve the resilience of biodiversity to climate change. Therefore, a study on systematic conservation planning for climatic diversity that explicitly or implicitly hypothesizes that regions with higher climatic diversity will support greater biodiversity is needed. However, little is known about the extent and generality of this hypothesis. This study utilized the case of Yunnan, southwest China, to quantitatively classify climatic units and modeled 4 climatic diversity indicators, including the variety of climatic units (VCU), rarity of climatic units (RCU), endemism of climatic units (ECU) and a composite index of climatic units (CICD). We used 5 reliable priority conservation area (PCA) schemes to represent the areas with high biodiversity conservation value. We then investigated the spatial relationships between the 4 climatic diversity indicators and the 5 PCA schemes and assessed the representation of climatic diversity within the existing nature reserves. The CICD exhibited the best performance for indicating high conservation value areas, followed by the ECU and RCU. However, contrary to conventional knowledge, VCU did not show a positive association with biodiversity conservation value. The rarer or more endemic climatic units tended to have higher reserve coverage than the more common units. However, only 28 units covering 10.5% of the land in Yunnan had more than 17% of their areas protected. In addition to climatic factors, topography and human disturbances also significantly affected the relationship between climatic diversity and biodiversity conservation value. This analysis suggests that climatic diversity can be an effective surrogate for establishing a more robust reserve network under climate change in Yunnan. Our study improves the understanding of the relationship between climatic diversity and biodiversity and helps build an evidence-based foundation for systematic conservation planning that targets climatic diversity in response to climate change. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Southeast Atmosphere Studies: learning from model-observation syntheses

NASA Astrophysics Data System (ADS)

Mao, Jingqiu; Carlton, Annmarie; Cohen, Ronald C.; Brune, William H.; Brown, Steven S.; Wolfe, Glenn M.; Jimenez, Jose L.; Pye, Havala O. T.; Ng, Nga Lee; Xu, Lu; McNeill, V. Faye; Tsigaridis, Kostas; McDonald, Brian C.; Warneke, Carsten; Guenther, Alex; Alvarado, Matthew J.; de Gouw, Joost; Mickley, Loretta J.; Leibensperger, Eric M.; Mathur, Rohit; Nolte, Christopher G.; Portmann, Robert W.; Unger, Nadine; Tosca, Mika; Horowitz, Larry W.

2018-02-01

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales.This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.

Southeast Atmosphere Studies: learning from model-observation syntheses

PubMed Central

Mao, Jingqiu; Carlton, Annmarie; Cohen, Ronald C.; Brune, William H.; Brown, Steven S.; Wolfe, Glenn M.; Jimenez, Jose L.; Pye, Havala O. T.; Ng, Nga Lee; Xu, Lu; McNeill, V. Faye; Tsigaridis, Kostas; McDonald, Brian C.; Warneke, Carsten; Guenther, Alex; Alvarado, Matthew J.; de Gouw, Joost; Mickley, Loretta J.; Leibensperger, Eric M.; Mathur, Rohit; Nolte, Christopher G.; Portmann, Robert W.; Unger, Nadine; Tosca, Mika; Horowitz, Larry W.

2018-01-01

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales. This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.

Southeast Atmosphere Studies: Learning from Model-Observation Syntheses

NASA Technical Reports Server (NTRS)

Mao, Jingqiu; Carlton, Annmarie; Cohen, Ronald C.; Brune, William H.; Brown, Steven S.; Wolfe, Glenn M.; Jimenez, Jose L.; Pye, Havala O. T.; Ng, Nga Lee; Xu, Lu;

Setting up a model intercomparison project for the last deglaciation

NASA Astrophysics Data System (ADS)

Ivanovic, R. F.; Gregoire, L. J.; Valdes, P. J.; Roche, D. M.; Kageyama, M.

2014-12-01

The last deglaciation (~ 21-9 ka) presents a series of opportunities to study the underlying mechanisms of abrupt climate changes and long-term trends in the Earth System. Most of the forcings are relatively well constrained and geological archives record responses over a range of timescales. Despite this, large uncertainties remain over the feedback loops that culminated in the collapse of the great Northern Hemisphere ice sheets, and a consensus has yet to be reached on the chains of events that led to rapid surface warming and cooling during this period.Climate models are powerful tools for quantitatively assessing these outstanding issues through their ability to temporally resolve cause and effect, as well as break down the contributions from different forcings. This is well demonstrated by pioneering work; for example by Liu et al. (2009), Roche et al. (2011), Gregoire et al. (2012) and Menviel et al. (2011). However, such work is not without challenges; model-geological data mismatches remain unsolved and it is difficult to compare results from different models with unique experiment designs. Therefore, we have established a multidisciplinary Paleoclimate Model Intercomparison Project working group to coordinate transient climate model simulations and geological archive compilations of the last deglaciation. Here, we present the plans and progress of the working group in its first phase of activity; the investigation of Heinrich Stadial 1 and the lead into the Bolling warming event. We describe the set-up of the core deglacial experiment, explain our approach for dealing with uncertain climate forcings and outline our solutions to challenges posed by this research. By defining a common experiment design, we have built a framework to include models of different speeds, complexities and resolution, maximising the reward of this varied approach. One of the next challenges is to compile transient proxy records and develop a methodology for dealing with uncertainty and error in model-geological data comparisons. Through this global and interdisciplinary initiative, we combine multi-proxy records with a suite of different modelling techniques to test hypotheses for abrupt climate changes and reconstruct the chain of events that deglaciated the Earth 21-9 ka.

Water-Food Nexus on Lancang-Mekong River Basin

NASA Astrophysics Data System (ADS)

Do, P.; Tian, F.; Hu, H.

2017-12-01

Water-Food-Energy nexus on Lancang-Mekong river basin In the Lancang-Mekong river basin, the connexions between climate and the water-food-energy nexus are strong. One of them can be reflected by the hydropower energy and irrigation sectors, impacted since these last years by intense droughts and increasing salinity. The purpose of this study is to understand quantitatively how the current hydropower impact on the streamflow and the irrigated crops will be influenced by the climate change for the next 30 years. A hydropower-crop model is computed to reproduce hydropower generation and revenue, revenue from crop and crop area in 2050. The outcomes will be used for water management in the region and strengthen the cooperation mechanisms between Mekong riparian countries.

Complex climatic and CO2 controls on net primary productivity of temperate dryland ecosystems over central Asia during 1980-2014

NASA Astrophysics Data System (ADS)

Zhang, Chi; Ren, Wei

2017-09-01

Central Asia covers a large land area of 5 × 106 km2 and has unique temperate dryland ecosystems, with over 80% of the world's temperate deserts, which has been experiencing dramatic warming and drought in the recent decades. How the temperate dryland responds to complex climate change, however, is still far from clear. This study quantitatively investigates terrestrial net primary productivity (NPP) in responses to temperature, precipitation, and atmospheric CO2 during 1980-2014, by using the Arid Ecosystem Model, which can realistically predict ecosystems' responses to changes in climate and atmospheric CO2 according to model evaluation against 28 field experiments/observations. The simulation results show that unlike other middle-/high-latitude regions, NPP in central Asia declined by 10% (0.12 × 1015 g C) since the 1980s in response to a warmer and drier climate. The dryland's response to warming was weak, while its cropland was sensitive to the CO2 fertilization effect (CFE). However, the CFE was inhibited by the long-term drought from 1998 to 2008 and the positive effect of warming on photosynthesis was largely offset by the enhanced water deficit. The complex interactive effects among climate drivers, unique responses from diverse ecosystem types, and intensive and heterogeneous climatic changes led to highly complex NPP changing patterns in central Asia, of which 69% was dominated by precipitation variation and 20% and 9% was dominated by CO2 and temperature, respectively. The Turgay Plateau in northern Kazakhstan and southern Xinjiang in China are hot spots of NPP degradation in response to climate change during the past three decades and in the future.

Climate change will restrict ponderosa pine forest regeneration in the 21st century in absence of disturbance

NASA Astrophysics Data System (ADS)

Petrie, M. D.; Bradford, J. B.; Hubbard, R. M.; Lauenroth, W. K.; Andrews, C.

2016-12-01

The persistence of ponderosa pine forests and the ability for these forests to colonize new habitats in the 21st century will be influenced by how climate change supports ponderosa pine regeneration through the demographic processes of seed production, germination and survival. Yet, the way that climate change may support or restrict the frequency of successful regeneration is unclear. We developed a quantitative, criteria-based framework to estimate ponderosa pine regeneration potential (RP: a metric from 0-1) in response to climate forcings and environmental conditions. We used the SOILWAT ecosystem water balance model to simulate drivers of air and soil temperature, evaporation and soil moisture availability for 47 ponderosa pine sites across the western United States, using meteorological data from 1910-2014, and projections from nine General Circulation Models and the RCP 8.5 emissions scenario for 2020-2099. Climate change simulations increased the success of early developmental stages of seed production and germination, and supported 49.7% higher RP in 2020-2059 compared to averages from 1910-2014. As temperatures increased in 2060-2099, survival scores decreased, and RP was reduced by 50.3% compared to 1910-2014. Although the frequency of years with high RP did not change in 2060-2099 (12% of years), the frequency of years with very low RP increased from 25% to 58% of years. Thus, climate change will initially support higher RP and more favorable years in 2020-2059, yet will reduce average RP and the frequency of years with moderate regeneration support in 2060-2099. Forest regeneration is complex and not fully-understood, but our results suggest it is likely that climate change alone will instigate restrictions to the persistence and expansion of ponderosa pine in the 21st century.

The relative role of climate change and human activities in the desertification process in Yulin region of northwest China.

PubMed

Wang, Tao; Sun, Jian-Guo; Han, Hui; Yan, Chang-Zhen

2012-12-01

To overcome the shortcoming of existing studies, this paper put forward a statistical vegetation-climate relationship model with integrated temporal and spatial characteristics. Based on this model, we quantitatively discriminated on the grid scale the relative role of climate change and human activities in the desertification dynamics from 1986 to 2000 in Yulin region. Yulin region's desertification development occurred mainly in the southern hilly and gully area and its reverse in the northwest sand and marsh area. This spatial pattern was especially evident and has never changed thoroughly. From the first time section (1986-1990) to the second (1991-1995), the desertification was developing as a whole, and either in the desertification development district or in the reverse district human activities' role was always occupying an overwhelmingly dominant position (they were 98.7% and 101.4%, respectively), the role of climate change was extremely slight. From the second time section (1991-1995) to the third (1996-2000), the desertification process was reaching a state of stability, in the desertification development district the role of climate change was nearly equivalent to that of human activities (they were 46.2% and 53.8% separately), and yet in the desertification reverse district, the role of human activities came up to 119.0%, the role of climate change amounted to -19.0%. In addition, the relative role of climate change and human activities possessed great spatial heterogeneity. The above conclusion rather coincides with the qualitative analysis in many literatures, which indicates that this method has certain rationality and can be utilized as a reference for the monitoring and studying of desertification in other areas.

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

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

Urrego-Blanco, Jorge Rolando; Urban, Nathan Mark; Hunke, Elizabeth Clare

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual modelmore » parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

DOE PAGES

Urrego-Blanco, Jorge Rolando; Urban, Nathan Mark; Hunke, Elizabeth Clare; ...

2016-04-01

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual modelmore » parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less

Understanding the varied response of the extratropical storm tracks to climate change

PubMed Central

O’Gorman, Paul A.

2010-01-01

Transient eddies in the extratropical storm tracks are a primary mechanism for the transport of momentum, energy, and water in the atmosphere, and as such are a major component of the climate system. Changes in the extratropical storm tracks under global warming would impact these transports, the ocean circulation and carbon cycle, and society through changing weather patterns. I show that the southern storm track intensifies in the multimodel mean of simulations of 21st century climate change, and that the seasonal cycle of storm-track intensity increases in amplitude in both hemispheres. I use observations of the present-day seasonal cycle to confirm the relationship between storm-track intensity and the mean available potential energy of the atmosphere, and show how this quantitative relationship can be used to account for much of the varied response in storm-track intensity to global warming, including substantially different responses in simulations with different climate models. The results suggest that storm-track intensity is not related in a simple way to global-mean surface temperature, so that, for example, a stronger southern storm track in response to present-day global warming does not imply it was also stronger in hothouse climates of the past. PMID:20974916

Understanding the varied response of the extratropical storm tracks to climate change.

PubMed

O'Gorman, Paul A

2010-11-09

Transient eddies in the extratropical storm tracks are a primary mechanism for the transport of momentum, energy, and water in the atmosphere, and as such are a major component of the climate system. Changes in the extratropical storm tracks under global warming would impact these transports, the ocean circulation and carbon cycle, and society through changing weather patterns. I show that the southern storm track intensifies in the multimodel mean of simulations of 21st century climate change, and that the seasonal cycle of storm-track intensity increases in amplitude in both hemispheres. I use observations of the present-day seasonal cycle to confirm the relationship between storm-track intensity and the mean available potential energy of the atmosphere, and show how this quantitative relationship can be used to account for much of the varied response in storm-track intensity to global warming, including substantially different responses in simulations with different climate models. The results suggest that storm-track intensity is not related in a simple way to global-mean surface temperature, so that, for example, a stronger southern storm track in response to present-day global warming does not imply it was also stronger in hothouse climates of the past.

Drought Tolerance during Reproductive Development is Important for Increasing wheat yield Potential under Climate change in Europe.

PubMed

Senapati, Nimai; Stratonovitch, Pierre; Paul, Matthew J; Semenov, Mikhail A

2018-06-12

Drought stress during reproductive development could drastically reduce grain number and wheat yield, but quantitative evaluation of such effect is unknown under climate change. The objectives of this study were to a) evaluate potential yield benefits of drought tolerance during reproductive development for wheat ideotypes under climate change in Europe, and b) identify potential cultivar parameters for improvement. We used the Sirius wheat model to optimise drought tolerant (DT) and drought sensitive (DS) wheat ideotypes under future 2050 climate scenario at 13 contrasting sites, representing major wheat growing regions in Europe. Averaged over the sites, DT ideotypes achieved 13.4% greater yield compared to DS, with the double yield stability for DT. However, the performances of the ideotypes were site dependent. Mean yield of DT was 28-37% greater compared to DS in southern Europe. In contrast, no yield difference (≤ 1%) between ideotypes was found in north-western Europe. An intermediate yield benefit of 10-23% was found due to drought tolerance in central and eastern Europe. We conclude that tolerance to drought stress during reproductive development is important for high yield potentials and greater yield stability of wheat under climate change in Europe.

What Has Caused Desertification in China?

PubMed

Feng, Qi; Ma, Hua; Jiang, Xuemei; Wang, Xin; Cao, Shixiong

2015-11-03

Desertification is the result of complex interactions among various factors, including climate change and human activities. However, previous research generally focused on either meteorological factors associated with climate change or human factors associated with human activities, and lacked quantitative assessments of their interaction combined with long-term monitoring. Thus, the roles of climate change and human factors in desertification remain uncertain. To understand the factors that determine whether mitigation programs can contribute to desertification control and vegetation cover improvements in desertified areas of China, and the complex interactions that affect their success, we used a pooled regression model based on panel data to calculate the relative roles of climate change and human activities on the desertified area and on vegetation cover (using the normalized-difference vegetation index, NDVI, which decreases with increasing desertification) from 1983 to 2012. We found similar effect magnitudes for socioeconomic and environmental factors for NDVI but different results for desertification: socioeconomic factors were the dominant factor that affected desertification, accounting for 79.3% of the effects. Climate change accounted for 46.6 and 20.6% of the effects on NDVI and desertification, respectively. Therefore, desertification control programs must account for the integrated effects of both socioeconomic and natural factors.

What Has Caused Desertification in China?

PubMed Central

Feng, Qi; Ma, Hua; Jiang, Xuemei; Wang, Xin; Cao, Shixiong

2015-01-01

Desertification is the result of complex interactions among various factors, including climate change and human activities. However, previous research generally focused on either meteorological factors associated with climate change or human factors associated with human activities, and lacked quantitative assessments of their interaction combined with long-term monitoring. Thus, the roles of climate change and human factors in desertification remain uncertain. To understand the factors that determine whether mitigation programs can contribute to desertification control and vegetation cover improvements in desertified areas of China, and the complex interactions that affect their success, we used a pooled regression model based on panel data to calculate the relative roles of climate change and human activities on the desertified area and on vegetation cover (using the normalized-difference vegetation index, NDVI, which decreases with increasing desertification) from 1983 to 2012. We found similar effect magnitudes for socioeconomic and environmental factors for NDVI but different results for desertification: socioeconomic factors were the dominant factor that affected desertification, accounting for 79.3% of the effects. Climate change accounted for 46.6 and 20.6% of the effects on NDVI and desertification, respectively. Therefore, desertification control programs must account for the integrated effects of both socioeconomic and natural factors. PMID:26525278

Application of solar max ACRIM data to analyze solar-driven climatic variability on Earth

NASA Technical Reports Server (NTRS)

Hoffert, M. I.

1986-01-01

Terrestrial climatic effects associated with solar variability have been proposed for at least a century, but could not be assessed quantitatively owing to observational uncertainities in solar flux variations. Measurements from 1980 to 1984 by the Active Cavity Radiometer Irradiance Monitor (ACRIM), capable of resolving fluctuations above the sensible atmosphere less than 0.1% of the solar constant, permit direct albeit preliminary assessments of solar forcing effects on global temperatures during this period. The global temperature response to ACRIM-measured fluctuations was computed from 1980 to 1985 using the NYU transient climate model including thermal inertia effects of the world ocean; and compared the results with observations of recent temperature trends. Monthly mean ACRIM-driven global surface temperature fluctuations computed with the climate model are an order of magnitude smaller, of order 0.01 C. In constrast, global mean surface temperature observations indicate an approx. 0.1 C increase during this period. Solar variability is therefore likely to have been a minor factor in global climate change during this period compared with variations in atmospheric albedo, greenhouse gases and internal self-inducedoscillations. It was not possible to extend the applicability of the measured flux variations to longer periods since a possible correlation of luminosity with solar annual activity is not supported by statistical analysis. The continuous monitoring of solar flux by satellite-based instruments over timescales of 20 years or more comparable to timescales for thermal relaxation of the oceans and of the solar cycle itself is needed to resolve the question of long-term solar variation effects on climate.

Virtual water management in the Roman world

NASA Astrophysics Data System (ADS)

Dermody, B.; Van Beek, L. P.; Meeks, E.; Klein Goldewijk, K.; Bierkens, M. F.; Scheidel, W.; Wassen, M. J.; Van der Velde, Y.; Dekker, S. C.

2013-12-01

Climate change can have extreme societal impacts particularly in regions that are water-limited for agriculture. A society's ability to manage its water resources in such environments is critical to its long-term viability. Water management can involve improving agricultural yields through in-situ irrigation or the redistribution of virtual water resources through trade in food. Here, we explore how such water management strategies improve societal resilience by examining virtual water management during the Roman Empire in the water-limited region of the Mediterranean. Climate was prescribed based on previously published reconstructions which show that during the Roman Empire when the Central Mediterranean was wetter, the West and Southeastern Mediterranean became drier and vice-versa. Evidence indicates that these shifts in the climatic seesaw may have occurred relatively rapidly. Using the Global hydrological model PCR GLOBWB and estimates of landcover based on the HYDE dataset we generate potential agricultural yield maps under two extremes of this climatic seesaw. HYDE estimates of population in conjunction with potential yield estimates are used to identify regions of Mediterranean with a yield surplus or deficit. The surplus and deficit regions form nodes on a virtual water redistribution network with transport costs taken from the Stanford Geospatial Network Model of the Roman World (ORBIS). Our demand-driven, virtual water redistribution network allows us to quantitatively explore the importance of water management strategies such as irrigation and food trade for the Romans. By examining virtual water transport cost anomalies between climate scenarios our analysis highlights regions of the Mediterranean that were most vulnerable to climate change during the Roman Period.

A model for evaluating stream temperature response to climate change in Wisconsin

USGS Publications Warehouse

Stewart, Jana S.; Westenbroek, Stephen M.; Mitro, Matthew G.; Lyons, John D.; Kammel, Leah E.; Buchwald, Cheryl A.

2015-01-01

Integrating the SWB Model with the ANN Model provided a mechanism by which downscaled global or regional climate model results could be used to estimate the potential effects of climate change on future stream temperature on a daily time step. To address future climate scenarios, statistically downscaled air temperature and precipitation projections from 10 GCMs and 2 time periods were used with the SWB-ANNv1 Model to project future stream temperature. Projections of future stream temperatures at mid- (2046–65) and late- (2081–2100) 21st century showed the July mean water temperature increasing for all stream segments with about 80 percent of stream kilometers increasing by 1 to 2 degrees Celsius (°C) by mid-century and about 99 percent increasing by 1 to 3 °C by late-century. Projected changes in stream temperatures also affected changes in thermal classes with a loss in the total amount of cold-water, cold-transition, and warm-transition thermal habitat and a gain in warm-water and very warm thermal habitat for both mid- and late-21st century time periods. The greatest losses occurred for cold-water streams and the greatest gains for warm-water streams, with a contraction of cold-water streams in the Driftless Area of western and southern Wisconsin and an expansion of warm-water streams across northern Wisconsin. Results of this study suggest that such changes will affect the composition of fish assemblages, with a loss of suitable habitat for cold-water fishes and gain in suitable habitat for warm-water fishes. In the end, these projected changes in thermal habitat attributable to climate may result in a net loss of fisheries, because many warm-water species may be unable to colonize habitats formerly occupied by cold-water species because of other habitat limitations (e.g., stream size, gradient). Although projected stream temperatures may vary greatly, depending on the emissions scenario and models used, the results presented in this report represent one possibility. The relative change in stream temperature can provide useful information for planning for potential climate impacts to aquatic ecosystems. Model results can be used to help identify vulnerabilities of streams to climate change, guide stream surveys and thermal classifications, prioritize the allocation of scarce financial resources, identify approaches to climate adaptation to best protect and enhance resiliency in stream thermal habitat, and provide information to make quantitative assessments of statewide stream resources.

Evaluation of MuSyQ land surface albedo based on LAnd surface Parameters VAlidation System (LAPVAS)

NASA Astrophysics Data System (ADS)

Dou, B.; Wen, J.; Xinwen, L.; Zhiming, F.; Wu, S.; Zhang, Y.

2016-12-01

satellite derived Land surface albedo is an essential climate variable which controls the earth energy budget and it can be used in applications such as climate change, hydrology, and numerical weather prediction. However, the accuracy and uncertainty of surface albedo products should be evaluated with a reliable reference truth data prior to applications. A new comprehensive and systemic project of china, called the Remote Sensing Application Network (CRSAN), has been launched recent years. Two subjects of this project is developing a Multi-source data Synergized Quantitative Remote Sensin g Production System ( MuSyQ ) and a Web-based validation system named LAnd surface remote sensing Product VAlidation System (LAPVAS) , which aims to generate a quantitative remote sensing product for ecosystem and environmental monitoring and validate them with a reference validation data and a standard validation system, respectively. Land surface BRDF/albedo is one of product datasets of MuSyQ which has a pentad period with 1km spatial resolution and is derived by Multi-sensor Combined BRDF Inversion ( MCBI ) Model. In this MuSyQ albedo evaluation, a multi-validation strategy is implemented by LAPVAS, including directly and multi-scale validation with field measured albedo and cross validation with MODIS albedo product with different land cover. The results reveal that MuSyQ albedo data with a 5-day temporal resolution is in higher sensibility and accuracy during land cover change period, e.g. snowing. But results without regard to snow or changed land cover, MuSyQ albedo generally is in similar accuracy with MODIS albedo and meet the climate modeling requirement of an absolute accuracy of 0.05.

Survival of Norway spruce remains higher in mixed stands under a dryer and warmer climate.

PubMed

Neuner, Susanne; Albrecht, Axel; Cullmann, Dominik; Engels, Friedrich; Griess, Verena C; Hahn, W Andreas; Hanewinkel, Marc; Härtl, Fabian; Kölling, Christian; Staupendahl, Kai; Knoke, Thomas

2015-02-01

Shifts in tree species distributions caused by climatic change are expected to cause severe losses in the economic value of European forestland. However, this projection disregards potential adaptation options such as tree species conversion, shorter production periods, or establishment of mixed species forests. The effect of tree species mixture has, as yet, not been quantitatively investigated for its potential to mitigate future increases in production risks. For the first time, we use survival time analysis to assess the effects of climate, species mixture and soil condition on survival probabilities for Norway spruce and European beech. Accelerated Failure Time (AFT) models based on an extensive dataset of almost 65,000 trees from the European Forest Damage Survey (FDS)--part of the European-wide Level I monitoring network--predicted a 24% decrease in survival probability for Norway spruce in pure stands at age 120 when unfavorable changes in climate conditions were assumed. Increasing species admixture greatly reduced the negative effects of unfavorable climate conditions, resulting in a decline in survival probabilities of only 7%. We conclude that future studies of forest management under climate change as well as forest policy measures need to take this, as yet unconsidered, strongly advantageous effect of tree species mixture into account. © 2014 John Wiley & Sons Ltd.

Declines in low-elevation subalpine tree populations outpace growth in high-elevation populations with warming

DOE PAGES

Conlisk, Erin; Castanha, Cristina; Germino, Matthew J.; ...

2017-02-08

Species distribution shifts in response to climate change require that recruitment increase beyond current range boundaries. For trees with long life spans, the importance of climate-sensitive seedling establishment to the pace of range shifts has not been demonstrated quantitatively. Using spatially explicit, stochastic population models combined with data from long-term forest surveys, we explored whether the climate-sensitivity of recruitment observed in climate manipulation experiments was sufficient to alter populations and elevation ranges of two widely distributed, high-elevation North American conifers. Empirically observed, warming-driven declines in recruitment led to rapid modelled population declines at the low-elevation, ‘warm edge’ of subalpine forestmore » and slow emergence of populations beyond the high-elevation, ‘cool edge’. Because population declines in the forest occurred much faster than population emergence in the alpine, we observed range contraction for both species. For Engelmann spruce, this contraction was permanent over the modelled time horizon, even in the presence of increased moisture. For limber pine, lower sensitivity to warming may facilitate persistence at low elevations – especially in the presence of increased moisture – and rapid establishment above tree line, and, ultimately, expansion into the alpine. Synthesis. Assuming 21st century warming and no additional moisture, population dynamics in high-elevation forests led to transient range contractions for limber pine and potentially permanent range contractions for Engelmann spruce. Thus, limitations to seedling recruitment with warming can constrain the pace of subalpine tree range shifts.« less

Declines in low-elevation subalpine tree populations outpace growth in high-elevation populations with warming

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

Conlisk, Erin; Castanha, Cristina; Germino, Matthew J.

Species distribution shifts in response to climate change require that recruitment increase beyond current range boundaries. For trees with long life spans, the importance of climate-sensitive seedling establishment to the pace of range shifts has not been demonstrated quantitatively. Using spatially explicit, stochastic population models combined with data from long-term forest surveys, we explored whether the climate-sensitivity of recruitment observed in climate manipulation experiments was sufficient to alter populations and elevation ranges of two widely distributed, high-elevation North American conifers. Empirically observed, warming-driven declines in recruitment led to rapid modelled population declines at the low-elevation, ‘warm edge’ of subalpine forestmore » and slow emergence of populations beyond the high-elevation, ‘cool edge’. Because population declines in the forest occurred much faster than population emergence in the alpine, we observed range contraction for both species. For Engelmann spruce, this contraction was permanent over the modelled time horizon, even in the presence of increased moisture. For limber pine, lower sensitivity to warming may facilitate persistence at low elevations – especially in the presence of increased moisture – and rapid establishment above tree line, and, ultimately, expansion into the alpine. Synthesis. Assuming 21st century warming and no additional moisture, population dynamics in high-elevation forests led to transient range contractions for limber pine and potentially permanent range contractions for Engelmann spruce. Thus, limitations to seedling recruitment with warming can constrain the pace of subalpine tree range shifts.« less

Impacts of extreme heat and drought on crop yields in China: an assessment by using the DLEM-AG2 model

NASA Astrophysics Data System (ADS)

Zhang, J.; Yang, J.; Pan, S.; Tian, H.

2016-12-01

China is not only one of the major agricultural production countries with the largest population in the world, but it is also the most susceptible to climate change and extreme events. Much concern has been raised about how extreme climate has affected crop yield, which is crucial for China's food supply security. However, the quantitative assessment of extreme heat and drought impacts on crop yield in China has rarely been investigated. By using the Dynamic Land Ecosystem Model (DLEM-AG2), a highly integrated process-based ecosystem model with crop-specific simulation, here we quantified spatial and temporal patterns of extreme climatic heat and drought stress and their impacts on the yields of major food crops (rice, wheat, maize, and soybean) across China during 1981-2015, and further investigated the underlying mechanisms. Simulated results showed that extreme heat and drought stress significantly reduced national cereal production and increased the yield gaps between potential yield and rain-fed yield. The drought stress was the primary factor to reduce crop yields in the semi-arid and arid regions, and extreme heat stress slightly aggravated the yield loss. The yield gap between potential yield and rain-fed yield was larger at locations with lower precipitation. Our results suggest that a large exploitable yield gap in response to extreme climatic heat-drought stress offers an opportunity to increase productivity in China by optimizing agronomic practices, such as irrigation, fertilizer use, sowing density, and sowing date.

Declines in low-elevation subalpine tree populations outpace growth in high-elevation populations with warming

USGS Publications Warehouse

Conlisk, Erin; Castanha, Cristina; Germino, Matthew J.; Veblen, Thomas T; Smith, Jeremy M.; Kueppers, Lara M.

2017-01-01

Species distribution shifts in response to climate change require that recruitment increase beyond current range boundaries. For trees with long life spans, the importance of climate-sensitive seedling establishment to the pace of range shifts has not been demonstrated quantitatively.Using spatially explicit, stochastic population models combined with data from long-term forest surveys, we explored whether the climate-sensitivity of recruitment observed in climate manipulation experiments was sufficient to alter populations and elevation ranges of two widely distributed, high-elevation North American conifers.Empirically observed, warming-driven declines in recruitment led to rapid modelled population declines at the low-elevation, ‘warm edge’ of subalpine forest and slow emergence of populations beyond the high-elevation, ‘cool edge’. Because population declines in the forest occurred much faster than population emergence in the alpine, we observed range contraction for both species. For Engelmann spruce, this contraction was permanent over the modelled time horizon, even in the presence of increased moisture. For limber pine, lower sensitivity to warming may facilitate persistence at low elevations – especially in the presence of increased moisture – and rapid establishment above tree line, and, ultimately, expansion into the alpine.Synthesis. Assuming 21st century warming and no additional moisture, population dynamics in high-elevation forests led to transient range contractions for limber pine and potentially permanent range contractions for Engelmann spruce. Thus, limitations to seedling recruitment with warming can constrain the pace of subalpine tree range shifts.

Test Driven Development of a Parameterized Ice Sheet Component

NASA Astrophysics Data System (ADS)

Clune, T.

2011-12-01

Test driven development (TDD) is a software development methodology that offers many advantages over traditional approaches including reduced development and maintenance costs, improved reliability, and superior design quality. Although TDD is widely accepted in many software communities, the suitability to scientific software is largely undemonstrated and warrants a degree of skepticism. Indeed, numerical algorithms pose several challenges to unit testing in general, and TDD in particular. Among these challenges are the need to have simple, non-redundant closed-form expressions to compare against the results obtained from the implementation as well as realistic error estimates. The necessity for serial and parallel performance raises additional concerns for many scientific applicaitons. In previous work I demonstrated that TDD performed well for the development of a relatively simple numerical model that simulates the growth of snowflakes, but the results were anecdotal and of limited relevance to far more complex software components typical of climate models. This investigation has now been extended by successfully applying TDD to the implementation of a substantial portion of a new parameterized ice sheet component within a full climate model. After a brief introduction to TDD, I will present techniques that address some of the obstacles encountered with numerical algorithms. I will conclude with some quantitative and qualitative comparisons against climate components developed in a more traditional manner.

Reducing the Uncertainties in Direct Aerosol Radiative Forcing

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2011-01-01

Airborne particles, which include desert and soil dust, wildfire smoke, sea salt, volcanic ash, black carbon, natural and anthropogenic sulfate, nitrate, and organic aerosol, affect Earth's climate, in part by reflecting and absorbing sunlight. This paper reviews current status, and evaluates future prospects for reducing the uncertainty aerosols contribute to the energy budget of Earth, which at present represents a leading factor limiting the quality of climate predictions. Information from satellites is critical for this work, because they provide frequent, global coverage of the diverse and variable atmospheric aerosol load. Both aerosol amount and type must be determined. Satellites are very close to measuring aerosol amount at the level-of-accuracy needed, but aerosol type, especially how bright the airborne particles are, cannot be constrained adequately by current techniques. However, satellite instruments can map out aerosol air mass type, which is a qualitative classification rather than a quantitative measurement, and targeted suborbital measurements can provide the required particle property detail. So combining satellite and suborbital measurements, and then using this combination to constrain climate models, will produce a major advance in climate prediction.

Elevation-induced climate change as a dominant factor causing the late Miocene C(4) plant expansion in the Himalayan foreland.

PubMed

Wu, Haibin; Guo, Zhengtang; Guiot, Joël; Hatté, Christine; Peng, Changhui; Yu, Yanyan; Ge, Junyi; Li, Qin; Sun, Aizhi; Zhao, Deai

2014-05-01

During the late Miocene, a dramatic global expansion of C4 plant distribution occurred with broad spatial and temporal variations. Although the event is well documented, whether subsequent expansions were caused by a decreased atmospheric CO2 concentration or climate change is a contentious issue. In this study, we used an improved inverse vegetation modeling approach that accounts for the physiological responses of C3 and C4 plants to quantitatively reconstruct the paleoclimate in the Siwalik of Nepal based on pollen and carbon isotope data. We also studied the sensitivity of the C3 and C4 plants to changes in the climate and the atmospheric CO2 concentration. We suggest that the expansion of the C4 plant distribution during the late Miocene may have been primarily triggered by regional aridification and temperature increases. The expansion was unlikely caused by reduced CO2 levels alone. Our findings suggest that this abrupt ecological shift mainly resulted from climate changes related to the decreased elevation of the Himalayan foreland. © 2013 John Wiley & Sons Ltd.

Lumped parameter, isotopic model simulations of closed-basin lake response to drought in the Pacific Northwest and implications for lake sediment oxygen isotope records.

NASA Astrophysics Data System (ADS)

Steinman, B. A.; Rosenmeier, M.; Abbott, M.

2008-12-01

The economy of the Pacific Northwest relies heavily on water resources from the drought-prone Columbia River and its tributaries, as well as the many lakes and reservoirs of the region. Proper management of these water resources requires a thorough understanding of local drought histories that extends well beyond the instrumental record of the twentieth century, a time frame too short to capture the full range of drought variability in the Pacific Northwest. Here we present a lumped parameter, mass-balance model that provides insight into the influence of hydroclimatological changes on two small, closed-basin systems located in north- central Washington. Steady state model simulations of lake water oxygen isotope ratios using modern climate and catchment parameter datasets demonstrate a strong sensitivity to both the amount and timing of precipitation, and to changes in summertime relative humidity, particularly at annual and decadal time scales. Model tests also suggest that basin hypsography can have a significant impact on lake water oxygen isotope variations, largely through surface area to volume and consequent evaporative flux to volume ratio changes in response to drought and pluvial sequences. Additional simulations using input parameters derived from both on-site and National Climatic Data Center historical climate datasets accurately approximate three years of continuous lake observations (seasonal water sampling and continuous lake level monitoring) and twentieth century oxygen isotope ratios in sediment core authigenic carbonate recovered from the lakes. Results from these model simulations suggest that small, closed-basin lakes in north-central Washington are highly sensitive to changes in the drought-related climate variables, and that long (8000 year), high resolution records of quantitative changes in precipitation and evaporation are obtainable from sediment cores recovered from water bodies of the Pacific Northwest.

Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model

NASA Technical Reports Server (NTRS)

Yang, Runhua; Cohn, Stephen E.; daSilva, Arlindo; Joiner, Joanna; Houser, Paul R.

1997-01-01

The Earth's land surface, including its biomass, is an integral part of the Earth's weather and climate system. Land surface heterogeneity, such as the type and amount of vegetative covering., has a profound effect on local weather variability and therefore on regional variations of the global climate. Surface conditions affect local weather and climate through a number of mechanisms. First, they determine the re-distribution of the net radiative energy received at the surface, through the atmosphere, from the sun. A certain fraction of this energy increases the surface ground temperature, another warms the near-surface atmosphere, and the rest evaporates surface water, which in turn creates clouds and causes precipitation. Second, they determine how much rainfall and snowmelt can be stored in the soil and how much instead runs off into waterways. Finally, surface conditions influence the near-surface concentration and distribution of greenhouse gases such as carbon dioxide. The processes through which these mechanisms interact with the atmosphere can be modeled mathematically, to within some degree of uncertainty, on the basis of underlying physical principles. Such a land surface model provides predictive capability for surface variables including ground temperature, surface humidity, and soil moisture and temperature. This information is important for agriculture and industry, as well as for addressing fundamental scientific questions concerning global and local climate change. In this study we apply a methodology known as tangent linear modeling to help us understand more deeply, the behavior of the Mosaic land surface model, a model that has been developed over the past several years at NASA/GSFC. This methodology allows us to examine, directly and quantitatively, the dependence of prediction errors in land surface variables upon different vegetation conditions. The work also highlights the importance of accurate soil moisture information. Although surface variables are predicted imperfectly due to inherent uncertainties in the modeling process, our study suggests how satellite observations can be combined with the model, through land surface data assimilation, to improve their prediction.

Nitrogen gas emissions and nitrate leaching dynamics under different tillage practices based on data synthesis and process-based modeling

NASA Astrophysics Data System (ADS)

Huang, Y.; Ren, W.; Tao, B.; Zhu, X.

2017-12-01

Nitrogen losses from the agroecosystems have been of great concern to global changes due to the effects on global warming and water pollution in the form of nitrogen gas emissions (e.g., N2O) and mineral nitrogen leaching (e.g., NO3-), respectively. Conservation tillage, particularly no-tillage (NT), may enhance soil carbon sequestration, soil aggregation and moisture; therefore it has the potential of promoting N2O emissions and reducing NO3- leaching, comparing with conventional tillage (CT). However, associated processes are significantly affected by various factors, such as soil properties, climate, and crop types. How tillage management practices affect nitrogen transformations and fluxes is still far from clear, with inconsistent even opposite results from previous studies. To fill this knowledge gap, we quantitatively investigated gaseous and leaching nitrogen losses from NT and CT agroecosystems based on data synthesis and an improved process-based agroecosystem model. Our preliminary results suggest that NT management is more efficient in reducing NO3- leaching, and meanwhile it simultaneously increases N2O emissions by approximately 10% compared with CT. The effects of NT on N2O emissions and NO3- leaching are highly influenced by the placement of nitrogen fertilizer and are more pronounced in humid climate conditions. The effect of crop types is a less dominant factor in determining N2O and NO3- losses. Both our data synthesis and process-based modeling suggest that the enhanced carbon sequestration capacity from NT could be largely compromised by relevant NT-induced increases in N2O emissions. This study provides the comprehensive quantitative assessment of NT on the nitrogen emissions and leaching in agroecosystems. It provides scientific information for identifying proper management practices for ensuring food security and minimizing the adverse environmental impacts. The results also underscore the importance of suitable nitrogen management in the NT agroecosystems for climate adaptation and mitigation.

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.

Quantitative metrics for assessing predicted climate change pressure on North American tree species

Treesearch

Kevin M. Potter; William W. Hargrove

2013-01-01

Changing climate may pose a threat to forest tree species, forcing three potential population-level responses: toleration/adaptation, movement to suitable environmental conditions, or local extirpation. Assessments that prioritize and classify tree species for management and conservation activities in the face of climate change will need to incorporate estimates of the...

Climate change may restrict dryland forest regeneration in the 21st century

Treesearch

M. D. Petrie; J. B. Bradford; R. M. Hubbard; W. K. Lauenroth; C. M. Andrews; D. R. Schlaepfer

2017-01-01

The persistence and geographic expansion of dryland forests in the 21st century will be influenced by how climate change supports the demographic processes associated with tree regeneration. Yet, the way that climate change may alter regeneration is unclear. We developed a quantitative framework that estimates forest regeneration potential (RP) as a function of key...

The Effectiveness of the Geospatial Curriculum Approach on Urban Middle-Level Students' Climate Change Understandings

ERIC Educational Resources Information Center

Bodzin, Alec M.; Fu, Qiong

2014-01-01

Climate change science is a challenging topic for student learning. This quantitative study examined the effectiveness of a geospatial curriculum approach to promote climate change science understandings in an urban school district with eighth-grade students and investigated whether teacher- and student-level factors accounted for students'…

Using a dynamic vegetation model for future projections of crop yields: application to Belgium in the framework of the VOTES and MASC projects

NASA Astrophysics Data System (ADS)

Jacquemin, Ingrid; Henrot, Alexandra-Jane; Fontaine, Corentin M.; Dendoncker, Nicolas; Beckers, Veronique; Debusscher, Bos; Tychon, Bernard; Hambuckers, Alain; François, Louis

2016-04-01

Dynamic vegetation models (DVM) were initially designed to describe the dynamics of natural ecosystems as a function of climate and soil, to study the role of the vegetation in the carbon cycle. These models are now directly coupled with climate models in order to evaluate feedbacks between vegetation and climate. But DVM characteristics allow numerous other applications, leading to amelioration of some of their modules (e.g., evaluating sensitivity of the hydrological module to land surface changes) and developments (e.g., coupling with other models like agent-based models), to be used in ecosystem management and land use planning studies. It is in this dynamic context about DVMs that we have adapted the CARAIB (CARbon Assimilation In the Biosphere) model. One of the main improvements is the implementation of a crop module, allowing the assessment of climate change impacts on crop yields. We try to validate this module at different scales: - from the plot level, with the use of eddy-covariance data from agricultural sites in the FLUXNET network, such as Lonzée (Belgium) or other Western European sites (Grignon, Dijkgraaf,…), - to the country level, for which we compare the crop yield calculated by CARAIB to the crop yield statistics for Belgium and for different agricultural regions of the country. Another challenge for the CARAIB DVM was to deal with the landscape dynamics, which is not directly possible due to the lack of consideration of anthropogenic factors in the system. In the framework of the VOTES and the MASC projects, CARAIB is coupled with an agent-based model (ABM), representing the societal component of the system. This coupled module allows the use of climate and socio-economic scenarios, particularly interesting for studies which aim at ensuring a sustainable approach. This module has particularly been exploited in the VOTES project, where the objective was to provide a social, biophysical and economic assessment of the ecosystem services in four municipalities under urban pressure in the center of Belgium. The biophysical valuation was carried out with the coupled module, allowing a quantitative evaluation of key ecosystem services as a function of three climatic and socio-economic scenarios.

Influence of late Quaternary climate change on present patterns of genetic variation in valley oak, Quercus lobata Née.

PubMed

Gugger, Paul F; Ikegami, Makihiko; Sork, Victoria L

2013-07-01

Phylogeography and ecological niche models (ENMs) suggest that late Quaternary glacial cycles have played a prominent role in shaping present population genetic structure and diversity, but have not applied quantitative methods to dissect the relative contribution of past and present climate vs. other forces. We integrate multilocus phylogeography, climate-based ENMs and multivariate statistical approaches to infer the effects of late Quaternary climate change on contemporary genetic variation of valley oak (Quercus lobata Née). ENMs indicated that valley oak maintained a stable distribution with local migration from the last interglacial period (~120 ka) to the Last Glacial Maximum (~21 ka, LGM) to the present compared with large-scale range shifts for an eastern North American white oak (Quercus alba L.). Coast Range and Sierra Nevada foothill populations diverged in the late Pleistocene before the LGM [104 ka (28-1622)] and have occupied somewhat distinct climate niches, according to ENMs and coalescent analyses of divergence time. In accordance with neutral expectations for stable populations, nuclear microsatellite diversity positively correlated with niche stability from the LGM to present. Most strikingly, nuclear and chloroplast microsatellite variation significantly correlated with LGM climate, even after controlling for associations with geographic location and present climate using partial redundancy analyses. Variance partitioning showed that LGM climate uniquely explains a similar proportion of genetic variance as present climate (16% vs. 11-18%), and together, past and present climate explains more than geography (19%). Climate can influence local expansion-contraction dynamics, flowering phenology and thus gene flow, and/or impose selective pressures. These results highlight the lingering effect of past climate on genetic variation in species with stable distributions. © 2013 John Wiley & Sons Ltd.

Projections of water resources availability in Crete for the 21st century under the global change perspective

NASA Astrophysics Data System (ADS)

Koutroulis, A. G.; Tsanis, I. K.; Jacob, D.

2012-04-01

A robust signal of a warmer and drier climate over the western Mediterranean region is projected from the majority of climate models. This effect appears more pronounced during warm periods, when the seasonal decrease of precipitation can exceed control climatology by 25-30%. The rapid development of Crete in the last 30 years has exerted strong pressures on the natural resources of the region. Urbanization and growth of agriculture, tourism and industry had strong impact on the water resources of island by substantially increasing water demand. The objective of this study is to analyze and assess the impact of global change on the water resources status for the island of Crete for a range of 24 different scenarios of projected hydro-climatological regime, demand and supply potential. Water resources application issues analyzed and facilitated within this study, focusing on a refinement of the future water demands of the island, and comparing with "state of the art" global climate model (GCM) results and an ensemble of regional climate models (RCMs) under three different emission scenarios, to estimate water resources availability, during the 21st century. A robust signal of water scarcity is projected for all the combinations of emission (A2, A1B and B1), demand and infrastructure scenarios. Despite the uncertainty of the assessments, the quantitative impact of the projected changes on water availability indicates that climate change plays an equally important role to water use and management in controlling future water status in a Mediterranean island like the island of Crete. The outcome of this analysis will assist in short and long-term strategic water resources planning by prioritizing water related infrastructure development.

An integrated risk and vulnerability assessment framework for climate change and malaria transmission in East Africa.

PubMed

Onyango, Esther Achieng; Sahin, Oz; Awiti, Alex; Chu, Cordia; Mackey, Brendan

2016-11-11

Malaria is one of the key research concerns in climate change-health relationships. Numerous risk assessments and modelling studies provide evidence that the transmission range of malaria will expand with rising temperatures, adversely impacting on vulnerable communities in the East African highlands. While there exist multiple lines of evidence for the influence of climate change on malaria transmission, there is insufficient understanding of the complex and interdependent factors that determine the risk and vulnerability of human populations at the community level. Moreover, existing studies have had limited focus on the nature of the impacts on vulnerable communities or how well they are prepared to cope. In order to address these gaps, a systems approach was used to present an integrated risk and vulnerability assessment framework for studies of community level risk and vulnerability to malaria due to climate change. Drawing upon published literature on existing frameworks, a systems approach was applied to characterize the factors influencing the interactions between climate change and malaria transmission. This involved structural analysis to determine influential, relay, dependent and autonomous variables in order to construct a detailed causal loop conceptual model that illustrates the relationships among key variables. An integrated assessment framework that considers indicators of both biophysical and social vulnerability was proposed based on the conceptual model. A major conclusion was that this integrated assessment framework can be implemented using Bayesian Belief Networks, and applied at a community level using both quantitative and qualitative methods with stakeholder engagement. The approach enables a robust assessment of community level risk and vulnerability to malaria, along with contextually relevant and targeted adaptation strategies for dealing with malaria transmission that incorporate both scientific and community perspectives.

Impact of Climate Change on Irrigation and Hydropower Potential: A Case of Upper Blue Nile Basin

NASA Astrophysics Data System (ADS)

Abdella, E. J.; Gosain, A. K.; Khosa, R.

2017-12-01

Due to the growing pressure in water resource and climate change there is great uncertainty in the availability of water for existing as well as proposed irrigation and hydropower projects in the Upper Blue Nile basin (longitude 34oE and 39oE and latitude 7oN and 12oN). This study quantitatively assessed the impact of climate change on the hydrological regime of the basin which intern affect water availability for different use including hydropower and irrigation. Ensemble of four bias corrected regional climate models (RCM) of CORDEX Africa domain and two scenarios (RCP 4.5 and RCP 8.5) were used to determine climate projections for future (2021-2050) period. The outputs from the climate models used to drive the calibrated Soil and Water Assessment Tool (SWAT) hydrologic model to simulate future runoff. The simulated discharge were used as input to a Water Evaluation and Planning (WEAP) water allocation model to determine the implication in hydropower and irrigation potential of the basin. The WEAP model was setup to simulate three scenarios which includes Current, Medium-term (by 2025) and Long-term (by 2050) Development scenario. The projected mean annual temperature of the basin are warmer than the baseline (1982 - 2005) average in the range of 1 to 1.4oC. Projected mean annual precipitation varies across the basin in the range of - 3% to 7%, much of the expected increase is in the highland region of the basin. The water use simulation indicate that the current annual average irrigation water demand in the basin is 1.29Bm3y-1 with 100% coverage. By 2025 and 2050, with the development of new schemes and changing climate, water demand for irrigation is estimated to increase by 2.5 Bm3y-1 and 3.4 Bm3y-1 with 99 % and 96% coverage respectively. Simulation for domestic water demand coverage for all scenarios shows that there will be 100% coverage for the two major cities in the basin. The hydropower generation simulation indicate that 98% of hydroelectricity potential could be produced if all planed dams are constructed. The results in this study demonstrate the general idea of future water availability for different purpose in the basin, but uncertainties still exist in the projected future climate and simulated runoff. Optimal operation of existing and proposed reservoirs is also crucial in the context of climate change.

Major modes of short-term climate variability in the newly developed NUIST Earth System Model (NESM)

NASA Astrophysics Data System (ADS)

Cao, Jian; Wang, Bin; Xiang, Baoqiang; Li, Juan; Wu, Tianjie; Fu, Xiouhua; Wu, Liguang; Min, Jinzhong

2015-05-01

A coupled earth system model (ESM) has been developed at the Nanjing University of Information Science and Technology (NUIST) by using version 5.3 of the European Centre Hamburg Model (ECHAM), version 3.4 of the Nucleus for European Modelling of the Ocean (NEMO), and version 4.1 of the Los Alamos sea ice model (CICE). The model is referred to as NUIST ESM1 (NESM1). Comprehensive and quantitative metrics are used to assess the model's major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model's assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring-fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific (CP)-ENSO and eastern Pacific (EP)-ENSO; however, the equatorial SST variability, biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden-Julian Oscillation (MJO), and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version (T159) demonstrates improved simulation with respect to the climatology, interannual variance, monsoon-ENSO lead-lag correlation, spatial structures of the leading mode of the Asian-Australian monsoon rainfall variability, and the eastward propagation of the MJO.

Genetic and physiological bases for phenological responses to current and predicted climates

PubMed Central

Wilczek, A. M.; Burghardt, L. T.; Cobb, A. R.; Cooper, M. D.; Welch, S. M.; Schmitt, J.

2010-01-01

We are now reaching the stage at which specific genetic factors with known physiological effects can be tied directly and quantitatively to variation in phenology. With such a mechanistic understanding, scientists can better predict phenological responses to novel seasonal climates. Using the widespread model species Arabidopsis thaliana, we explore how variation in different genetic pathways can be linked to phenology and life-history variation across geographical regions and seasons. We show that the expression of phenological traits including flowering depends critically on the growth season, and we outline an integrated life-history approach to phenology in which the timing of later life-history events can be contingent on the environmental cues regulating earlier life stages. As flowering time in many plants is determined by the integration of multiple environmentally sensitive gene pathways, the novel combinations of important seasonal cues in projected future climates will alter how phenology responds to variation in the flowering time gene network with important consequences for plant life history. We discuss how phenology models in other systems—both natural and agricultural—could employ a similar framework to explore the potential contribution of genetic variation to the physiological integration of cues determining phenology. PMID:20819808

Climate change impact on infection risks during bathing downstream of sewage emissions from CSOs or WWTPs.

PubMed

Sterk, Ankie; de Man, Heleen; Schijven, Jack F; de Nijs, Ton; de Roda Husman, Ana Maria

2016-11-15

Climate change is expected to influence infection risks while bathing downstream of sewage emissions from combined sewage overflows (CSOs) or waste water treatment plants (WWTPs) due to changes in pathogen influx, rising temperatures and changing flow rates of the receiving waters. In this study, climate change impacts on the surface water concentrations of Campylobacter, Cryptosporidium and norovirus originating from sewage were modelled. Quantitative microbial risk assessment (QMRA) was used to assess changes in risks of infection. In general, infection risks downstream of WWTPs are higher than downstream CSOs. Even though model outputs show an increase in CSO influxes, in combination with changes in pathogen survival, dilution within the sewage system and bathing behaviour, the effects on the infection risks are limited. However, a decrease in dilution capacity of surface waters could have significant impact on the infection risks of relatively stable pathogens like Cryptosporidium and norovirus. Overall, average risks are found to be higher downstream WWTPs compared to CSOs. Especially with regard to decreased flow rates, adaptation measures on treatment at WWTPs may be more beneficial for human health than decreasing CSO events. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

U.S. Eastern Continental Shelf Carbon Cycling (USECoS): Modeling, Data Assimilation, and Analysis

NASA Technical Reports Server (NTRS)

Mannino, Antonio

2008-01-01

Although the oceans play a major role in the uptake of fossil fuel CO2 from the atmosphere, there is much debate about the contribution from continental shelves, since many key shelf fluxes are not yet well quantified: the exchange of carbon across the land-ocean and shelf-slope interfaces, air-sea exchange of CO2, burial, and biological processes including productivity. Our goal is to quantify these carbon fluxes along the eastern U.S. coast using models quantitatively verified by comparison to observations, and to establish a framework for predicting how these fluxes may be modified as a result of climate and land use change. Our research questions build on those addressed with previous NASA funding for the USECoS (U.S. Eastern Continental Shelf Carbon Cycling) project. We have developed a coupled biogeochemical ocean circulation model configured for this study region and have extensively evaluated this model with both in situ and remotely-sensed data. Results indicate that to further reduce uncertainties in the shelf component of the global carbon cycle, future efforts must be directed towards 1) increasing the resolution of the physical model via nesting and 2) making refinements to the biogeochemical model and quantitatively evaluating these via the assimilation of biogeochemical data (in situ and remotely-sensed). These model improvements are essential for better understanding and reducing estimates of uncertainties in current and future carbon transformations and cycling in continental shelf systems. Our approach and science questions are particularly germane to the carbon cycle science goals of the NASA Earth Science Research Program as well as the U.S. Climate Change Research Program and the North American Carbon Program. Our interdisciplinary research team consists of scientists who have expertise in the physics and biogeochemistry of the U.S. eastern continental shelf, remote-sensing data analysis and data assimilative numerical models.

Evaluation of the Earth System CoG Infrastructure in Supporting a Model Intercomparison Project

NASA Astrophysics Data System (ADS)

Wallis, J. C.; Rood, R. B.; Murphy, S.; Cinquini, L.; DeLuca, C.

2013-12-01

Earth System CoG is a web-based collaboration environment that combines data services with metadata and project management services. The environment is particularly suited to support software development and model intercomparison projects. CoG was recently used to support the National Climate Predictions and Projections Platform (NCPP) Quantitative Evaluation of Downscaling (QED-2013) workshop. QED-2013 was a workshop with a community approach for the objective, quantitative evaluation of techniques to downscale climate model predictions and projections. This paper will present a brief introduction to CoG, QED-2013, and findings from an ethnographic evaluation of how CoG supported QED-2013. The QED-2013 workshop focused on real-world application problems drawn from several sectors, and contributed to the informed use of downscaled data. This workshop is a part of a larger effort by NCPP and partner organizations to develop a standardized evaluation framework for local and regional climate information. The main goals of QED-2013 were to a) coordinate efforts for quantitative evaluation, b) develop software infrastructure, c) develop a repository of information, d) develop translational and guidance information, e) identify and engage key user communities, and f) promote collaboration and interoperability. CoG was a key player in QED-2013 support. NCPP was an early adopter of the CoG platform, providing valuable recommendations for overall development plus specific workshop-related requirements. New CoG features developed for QED-2013 included: the ability to publish images and associated metadata contained within XML files to its associated data node combine both artifacts into an integrated display. The ability to modify data search facets into scientifically relevant groups and display dynamic lists of workshop participants and their interests was also added to the interface. During the workshop, the QED-2013 project page on CoG provided meeting logistics, meeting materials, shared spaces and resources, and data services. The evaluation of CoG tools was focused on the usability of products rather than metrics, such as number of independent hits to a web site. We wanted to know how well CoG tools supported the workshop participants and their tasks. For instance, what workshop tasks could be performed within the CoG environment? Were these tasks performed there or with alternative tools? And do participants plan to use the tools after the workshop for other projects? Ultimately, we wanted to know if CoG contributed to NCPP's need for a flexible and extensible evaluation platform, and did it support the integration of dispersed resources, quantitative evaluation of climate projections, and the generation and management of interpretive information. Evaluation of the workshop and activity occurred during, at the end of, and after the workshop. During the workshop, an ethnographer observed and participated in the workshop, and collected short, semi-structured interviews with a subset of the participants. At the end of the workshop, an exit survey was administered to all the participants. After the workshop, a variety of methods were used to capture the impact of the workshop.

Quantitative summer and winter temperature reconstructions from pollen and chironomid data in the Baltic-Belarus area

NASA Astrophysics Data System (ADS)

Veski, Siim; Seppä, Heikki; Stančikaitė, Migle; Zernitskaya, Valentina; Reitalu, Triin; Gryguc, Gražyna; Heinsalu, Atko; Stivrins, Normunds; Amon, Leeli; Vassiljev, Jüri; Heiri, Oliver

2015-04-01

Quantitative reconstructions based on fossil pollen and chironomids are widely used and useful for long-term climate variability estimations. The Lateglacial and early Holocene period (15-8 ka BP) in the Baltic-Belarus (BB) area between 60°-51° N was characterized by sudden shifts in climate due to various climate forcings affecting the climate of the northern hemisphere and North Atlantic, including the proximity of receding ice sheets. Climate variations in BB during the LG were eminent as the southern part of the region was ice free during the Last Glacial Maximum over 19 ka BP, whereas northern Estonia became ice free no sooner than 13 ka BP. New pollen based reconstructions of summer (May-to-August) and winter (December-to-February) temperatures between 15-8 ka BP along a S-N transect in the BB area display trends in temporal and spatial changes in climate variability. These results are completed by two chironomid-based July mean temperature reconstructions (Heiri et al. 2014). The magnitude of change compared with modern temperatures was more prominent in the northern part of BB area than in the southern part. The 4 °C winter and 2 °C summer warming at the start of GI-1 was delayed in the BB area and Lateglacial maximum temperatures were reached at ca 13.6 ka BP, being 4 °C colder than the modern mean. The Younger Dryas cooling in the area was 5 °C colder than present as inferred by all proxies (Veski et al. in press). In addition, our analyses show an early Holocene divergence in winter temperature trends with modern values reaching 1 ka earlier (10 ka BP) in southern BB compared to the northern part of the region (9 ka BP). Heiri, O., Brooks, S.J., Renssen, H., Bedford, A., Hazekamp, M., Ilyashuk, B., Jeffers, E.S., Lang, B., Kirilova, E., Kuiper, S., Millet, L., Samartin, S., Toth, M., Verbruggen, F., Watson, J.E., van Asch, N., Lammertsma, E., Amon, L., Birks, H.H., Birks, J.B., Mortensen, M.F., Hoek, W.Z., Magyari, E., Muñoz Sobrino, C., Seppä, H., Tinner, W., Tonkov, S., Veski, S., Lotter, A.F., 2014. Validation of climate model-inferred regional temperature change for late-glacial Europe. Nature Communications 5:4914, doi: 10.1038/ncomms5914 Veski, S., Seppä, H., Stančikaitė, M., Zernitskaya, V., Reitalu, T., Gryguc, G., Heinsalu, A., Stivrins, N., Amon, L., Vassiljev, J., Heiri, O. (in press). Quantitative summer and winter temperature reconstructions from pollen and chironomid data between 15 and 8 ka BP in the Baltic-Belarus area. Quaternary International. doi: 10.1016/j.quaint.2014.10.059

Quantifying the effect of trend, fluctuation, and extreme event of climate change on ecosystem productivity.

PubMed

Liu, Yupeng; Yu, Deyong; Su, Yun; Hao, Ruifang

2014-12-01

Climate change comprises three fractions of trend, fluctuation, and extreme event. Assessing the effect of climate change on terrestrial ecosystem requires an understanding of the action mechanism of these fractions, respectively. This study examined 11 years of remotely sensed-derived net primary productivity (NPP) to identify the impacts of the trend and fluctuation of climate change as well as extremely low temperatures caused by a freezing disaster on ecosystem productivity in Hunan province, China. The partial least squares regression model was used to evaluate the contributions of temperature, precipitation, and photosynthetically active radiation (PAR) to NPP variation. A climatic signal decomposition and contribution assessment model was proposed to decompose climate factors into trend and fluctuation components. Then, we quantitatively evaluated the contributions of each component of climatic factors to NPP variation. The results indicated that the total contribution of the temperature, precipitation, and PAR to NPP variation from 2001 to 2011 in Hunan province is 85 %, and individual contributions of the temperature, precipitation, and PAR to NPP variation are 44 % (including 34 % trend contribution and 10 % fluctuation contribution), 5 % (including 4 % trend contribution and 1 % fluctuation contribution), and 36 % (including 30 % trend contribution and 6 % fluctuation contribution), respectively. The contributions of temperature fluctuation-driven NPP were higher in the north and lower in the south, and the contributions of precipitation trend-driven NPP and PAR fluctuation-driven NPP are higher in the west and lower in the east. As an instance of occasionally triggered disturbance in 2008, extremely low temperatures and a freezing disaster produced an abrupt decrease of NPP in forest and grass ecosystems. These results prove that the climatic trend change brought about great impacts on ecosystem productivity and that climatic fluctuations and extreme events can also alter the ecosystem succession process, even resulting in an alternative trajectory. All of these findings could improve our understanding of the impacts of climate change on the provision of ecosystem functions and services and can also provide a basis for policy makers to apply adaptive measures to overcome the unfavorable influence of climate change.

Incorporating human activities into an earth system model of the Northeastern United States: socio-hydrology at the regional scale

NASA Astrophysics Data System (ADS)

Rosenzweig, B.; Vorosmarty, C. J.; Miara, A.; Stewart, R.; Wollheim, W. M.; Lu, X.; Kicklighter, D. W.; Ehsani, N.; Shikhmacheva, K.; Yang, P.

2013-12-01

The Northeastern United States is one of the most urbanized regions of the world and its 70 million residents will be challenged by climate change as well as competing demands for land and water through the remainder of the 21st Century. The strategic management decisions made in the next few years will have major impacts on the region's future water resources, but planners have had limited quantitative information to support their decision-making. We have developed a Northeast Regional Earth System Model (NE-RESM), which allows for the testing of future scenarios of climate change, land use change and infrastructure management to better understand their implications for the region's water resources and ecosystem services. Human features of the water cycle - including thermoelectric power plants, wastewater treatment plants interbasin transfers and changes in impervious cover with different patterns of urban development - are explicitly represented in our modeling. We are currently engaged in a novel, participatory scenario design process with regional stakeholders to ensure the policy relevancy of our modeling experiments. The NE-RESM hydrologic modeling domain. Figure by Stanley Glidden and Rob Stewart

Influence of wind speed averaging on estimates of dimethylsulfide emission fluxes

DOE PAGES

Chapman, E. G.; Shaw, W. J.; Easter, R. C.; ...

2002-12-03

The effect of various wind-speed-averaging periods on calculated DMS emission fluxes is quantitatively assessed. Here, a global climate model and an emission flux module were run in stand-alone mode for a full year. Twenty-minute instantaneous surface wind speeds and related variables generated by the climate model were archived, and corresponding 1-hour-, 6-hour-, daily-, and monthly-averaged quantities calculated. These various time-averaged, model-derived quantities were used as inputs in the emission flux module, and DMS emissions were calculated using two expressions for the mass transfer velocity commonly used in atmospheric models. Results indicate that the time period selected for averaging wind speedsmore » can affect the magnitude of calculated DMS emission fluxes. A number of individual marine cells within the global grid show DMS emissions fluxes that are 10-60% higher when emissions are calculated using 20-minute instantaneous model time step winds rather than monthly-averaged wind speeds, and at some locations the differences exceed 200%. Many of these cells are located in the southern hemisphere where anthropogenic sulfur emissions are low and changes in oceanic DMS emissions may significantly affect calculated aerosol concentrations and aerosol radiative forcing.« less

Satellite Sensed Skin Sea Surface Temperature

NASA Technical Reports Server (NTRS)

Donlon, Craig

1997-01-01

Quantitative predictions of spatial and temporal changes the global climate rely heavily on the use of computer models. Unfortunately, such models cannot provide the basis for climate prediction because key physical processes are inadequately treated. Consequently, fine tuning procedures are often used to optimize the fit between model output and observational data and the validation of climate models using observations is essential if model based predictions of climate change are to be treated with any degree of confidence. Satellite Sea Surface Temperature (SST) observations provide high spatial and temporal resolution data which is extremely well suited to the initialization, definition of boundary conditions and, validation of climate models. In the case of coupled ocean-atmosphere models, the SST (or more correctly the 'Skin' SST (SSST)) is a fundamental diagnostic variable to consider in the validation process. Daily global SST maps derived from satellite sensors also provide adequate data for the detection of global patterns of change which, unlike any other SST data set, repeatedly extend into the southern hemisphere extra-tropical regions. Such data are essential to the success of the spatial 'fingerprint' technique, which seeks to establish a north-south asymmetry where warming is suppressed in the high latitude Southern Ocean. Some estimates suggest that there is a greater than 80% chance of directly detecting significant change (97.5 % confidence level) after 10-12 years of consistent global observations of mean sea surface temperature. However, these latter statements should be qualified with the assumption that a negligible drift in the observing system exists and that biases between individual instruments required to derive a long term data set are small. Given that current estimates for the magnitude of global warming of 0.015 K yr(sup -1) - 0.025 K yr(sup -1), satellite SST data sets need to be both accurate and stable if such a warming trend is to be confidently detected. Some of these activities are focussed to develop and deploy instrumentation suitable for the collection of precise in situ measurements of the SSST which can be used to improve the accuracy of satellite measurements, while others develop techniques to generate improved global analyses of sea surface temperature using historical data.

Deglacial temperature history of West Antarctica

PubMed Central

Clow, Gary D.; Steig, Eric J.; Buizert, Christo; Fudge, T. J.; Koutnik, Michelle; Waddington, Edwin D.; Alley, Richard B.

2016-01-01

The most recent glacial to interglacial transition constitutes a remarkable natural experiment for learning how Earth’s climate responds to various forcings, including a rise in atmospheric CO2. This transition has left a direct thermal remnant in the polar ice sheets, where the exceptional purity and continual accumulation of ice permit analyses not possible in other settings. For Antarctica, the deglacial warming has previously been constrained only by the water isotopic composition in ice cores, without an absolute thermometric assessment of the isotopes’ sensitivity to temperature. To overcome this limitation, we measured temperatures in a deep borehole and analyzed them together with ice-core data to reconstruct the surface temperature history of West Antarctica. The deglacial warming was 11.3±1.8∘C, approximately two to three times the global average, in agreement with theoretical expectations for Antarctic amplification of planetary temperature changes. Consistent with evidence from glacier retreat in Southern Hemisphere mountain ranges, the Antarctic warming was mostly completed by 15 kyBP, several millennia earlier than in the Northern Hemisphere. These results constrain the role of variable oceanic heat transport between hemispheres during deglaciation and quantitatively bound the direct influence of global climate forcings on Antarctic temperature. Although climate models perform well on average in this context, some recent syntheses of deglacial climate history have underestimated Antarctic warming and the models with lowest sensitivity can be discounted. PMID:27911783

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.

Deglacial temperature history of West Antarctica.

PubMed

Cuffey, Kurt M; Clow, Gary D; Steig, Eric J; Buizert, Christo; Fudge, T J; Koutnik, Michelle; Waddington, Edwin D; Alley, Richard B; Severinghaus, Jeffrey P

2016-12-13

The most recent glacial to interglacial transition constitutes a remarkable natural experiment for learning how Earth's climate responds to various forcings, including a rise in atmospheric CO 2 This transition has left a direct thermal remnant in the polar ice sheets, where the exceptional purity and continual accumulation of ice permit analyses not possible in other settings. For Antarctica, the deglacial warming has previously been constrained only by the water isotopic composition in ice cores, without an absolute thermometric assessment of the isotopes' sensitivity to temperature. To overcome this limitation, we measured temperatures in a deep borehole and analyzed them together with ice-core data to reconstruct the surface temperature history of West Antarctica. The deglacial warming was [Formula: see text]C, approximately two to three times the global average, in agreement with theoretical expectations for Antarctic amplification of planetary temperature changes. Consistent with evidence from glacier retreat in Southern Hemisphere mountain ranges, the Antarctic warming was mostly completed by 15 kyBP, several millennia earlier than in the Northern Hemisphere. These results constrain the role of variable oceanic heat transport between hemispheres during deglaciation and quantitatively bound the direct influence of global climate forcings on Antarctic temperature. Although climate models perform well on average in this context, some recent syntheses of deglacial climate history have underestimated Antarctic warming and the models with lowest sensitivity can be discounted.

Bridging the divide: a model-data approach to Polar and Alpine microbiology.

PubMed

Bradley, James A; Anesio, Alexandre M; Arndt, Sandra

2016-03-01

Advances in microbial ecology in the cryosphere continue to be driven by empirical approaches including field sampling and laboratory-based analyses. Although mathematical models are commonly used to investigate the physical dynamics of Polar and Alpine regions, they are rarely applied in microbial studies. Yet integrating modelling approaches with ongoing observational and laboratory-based work is ideally suited to Polar and Alpine microbial ecosystems given their harsh environmental and biogeochemical characteristics, simple trophic structures, distinct seasonality, often difficult accessibility, geographical expansiveness and susceptibility to accelerated climate changes. In this opinion paper, we explain how mathematical modelling ideally complements field and laboratory-based analyses. We thus argue that mathematical modelling is a powerful tool for the investigation of these extreme environments and that fully integrated, interdisciplinary model-data approaches could help the Polar and Alpine microbiology community address some of the great research challenges of the 21st century (e.g. assessing global significance and response to climate change). However, a better integration of field and laboratory work with model design and calibration/validation, as well as a stronger focus on quantitative information is required to advance models that can be used to make predictions and upscale processes and fluxes beyond what can be captured by observations alone. © FEMS 2016.

State-and-transition models: Conceptual versus simulation perspectives, usefulness and breadth of use, and land management applications

USGS Publications Warehouse

Provencher, Louis; Frid, Leonardo; Czembor, Christina; Morisette, Jeffrey T.

2016-01-01

State-and-Transition Simulation Modeling (STSM) is a quantitative analysis method that can consolidate a wide array of resource management issues under a “what-if” scenario exercise. STSM can be seen as an ensemble of models, such as climate models, ecological models, and economic models that incorporate human dimensions and management options. This chapter presents STSM as a tool to help synthesize information on social–ecological systems and to investigate some of the management issues associated with exotic annual Bromus species, which have been described elsewhere in this book. Definitions, terminology, and perspectives on conceptual and computer-simulated stochastic state-and-transition models are given first, followed by a brief review of past STSM studies relevant to the management of Bromus species. A detailed case study illustrates the usefulness of STSM for land management. As a whole, this chapter is intended to demonstrate how STSM can help both managers and scientists: (a) determine efficient resource allocation for monitoring nonnative grasses; (b) evaluate sources of uncertainty in model simulation results involving expert opinion, and their consequences for management decisions; and (c) provide insight into the consequences of predicted local climate change effects on ecological systems invaded by exotic annual Bromus species.

Bridging the divide: a model-data approach to Polar and Alpine microbiology

PubMed Central

Bradley, James A.; Anesio, Alexandre M.; Arndt, Sandra

2016-01-01

Advances in microbial ecology in the cryosphere continue to be driven by empirical approaches including field sampling and laboratory-based analyses. Although mathematical models are commonly used to investigate the physical dynamics of Polar and Alpine regions, they are rarely applied in microbial studies. Yet integrating modelling approaches with ongoing observational and laboratory-based work is ideally suited to Polar and Alpine microbial ecosystems given their harsh environmental and biogeochemical characteristics, simple trophic structures, distinct seasonality, often difficult accessibility, geographical expansiveness and susceptibility to accelerated climate changes. In this opinion paper, we explain how mathematical modelling ideally complements field and laboratory-based analyses. We thus argue that mathematical modelling is a powerful tool for the investigation of these extreme environments and that fully integrated, interdisciplinary model-data approaches could help the Polar and Alpine microbiology community address some of the great research challenges of the 21st century (e.g. assessing global significance and response to climate change). However, a better integration of field and laboratory work with model design and calibration/validation, as well as a stronger focus on quantitative information is required to advance models that can be used to make predictions and upscale processes and fluxes beyond what can be captured by observations alone. PMID:26832206

Coupling Processes between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, Malcolm K. W.; Weisenstein, Debra K.; Shia, Run-Lie; Scott, Courtney J.; Sze, Nien Dak

1998-01-01

This is the fourth semi-annual report for NAS5-97039, covering the time period July through December 1998. The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling tools for this work are the Atmospheric and Environmental Research (AER) two-dimensional chemistry-transport model, the AER two-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry. For this six month period, we report on a modeling study of new rate constant which modify the NOx/NOy ratio in the lower stratosphere; sensitivity to changes in stratospheric water vapor in the future atmosphere; a study of N2O and CH4 observations which has allowed us to adjust diffusion in the 2-D CTM in order to obtain appropriate polar vortex isolation; a study of SF6 and age of air with comparisons of models and measurements; and a report on the Models and Measurements II effort.

Missing rings in Pinus halepensis – the missing link to relate the tree-ring record to extreme climatic events

Treesearch

Klemen Novak; Martin de Luis; Miguel A. Saz; Luis A. Longares; Roberto Serrano-Notivoli; Josep Raventos; Katarina Cufar; Jozica Gricar; Alfredo Di Filippo; Gianluca Piovesan; Cyrille B.K. Rathgeber; Andreas Papadopoulos; Kevin T. Smith

2016-01-01

Climate predictions for the Mediterranean Basin include increased temperatures, decreased precipitation, and increased frequency of extreme climatic events (ECE). These conditions are associated with decreased tree growth and increased vulnerability to pests and diseases. The anatomy of tree rings responds to these environmental conditions. Quantitatively, the width of...

The Impact of School Climate on the Achievement of Elementary School Students Who Are Economically Disadvantaged a Quantitative Study

ERIC Educational Resources Information Center

Smallwood, Gina W.

2014-01-01

The purpose of this research was to explore the impact of school climate on the achievement of third and fourth grade students who are economically disadvantaged in Mathematics and Reading/Language Arts. Students' perception of school climate was studied using the "Tripod Survey" variables of a caring, captivating, and academically…

Phenotypic plasticity and adaptive evolution contribute to advancing flowering phenology in response to climate change.

PubMed

Anderson, Jill T; Inouye, David W; McKinney, Amy M; Colautti, Robert I; Mitchell-Olds, Tom

2012-09-22

Anthropogenic climate change has already altered the timing of major life-history transitions, such as the initiation of reproduction. Both phenotypic plasticity and adaptive evolution can underlie rapid phenological shifts in response to climate change, but their relative contributions are poorly understood. Here, we combine a continuous 38 year field survey with quantitative genetic field experiments to assess adaptation in the context of climate change. We focused on Boechera stricta (Brassicaeae), a mustard native to the US Rocky Mountains. Flowering phenology advanced significantly from 1973 to 2011, and was strongly associated with warmer temperatures and earlier snowmelt dates. Strong directional selection favoured earlier flowering in contemporary environments (2010-2011). Climate change could drive this directional selection, and promote even earlier flowering as temperatures continue to increase. Our quantitative genetic analyses predict a response to selection of 0.2 to 0.5 days acceleration in flowering per generation, which could account for more than 20 per cent of the phenological change observed in the long-term dataset. However, the strength of directional selection and the predicted evolutionary response are likely much greater now than even 30 years ago because of rapidly changing climatic conditions. We predict that adaptation will likely be necessary for long-term in situ persistence in the context of climate change.

Pollen-climate relationships in time (9 ka, 6 ka, 0 ka) and space (upland vs. lowland) in eastern continental Asia

NASA Astrophysics Data System (ADS)

Tian, Fang; Cao, Xianyong; Dallmeyer, Anne; Zhao, Yan; Ni, Jian; Herzschuh, Ulrike

2017-01-01

Temporal and spatial stability of the vegetation-climate relationship is a basic ecological assumption for pollen-based quantitative inferences of past climate change and for predicting future vegetation. We explore this assumption for the Holocene in eastern continental Asia (China, Mongolia). Boosted regression trees (BRT) between fossil pollen taxa percentages (Abies, Artemisia, Betula, Chenopodiaceae, Cyperaceae, Ephedra, Picea, Pinus, Poaceae and Quercus) and climate model outputs of mean annual precipitation (Pann) and mean temperature of the warmest month (Mtwa) for 9 and 6 ka (ka = thousand years before present) were set up and results compared to those obtained from relating modern pollen to modern climate. Overall, our results reveal only slight temporal differences in the pollen-climate relationships. Our analyses suggest that the importance of Pann compared with Mtwa for taxa distribution is higher today than it was at 6 ka and 9 ka. In particular, the relevance of Pann for Picea and Pinus increases and has become the main determinant. This change in the climate-tree pollen relationship parallels a widespread tree pollen decrease in north-central China and the eastern Tibetan Plateau. We assume that this is at least partly related to vegetation-climate disequilibrium originating from human impact. Increased atmospheric CO2 concentration may have permitted the expansion of moisture-loving herb taxa (Cyperaceae and Poaceae) during the late Holocene into arid/semi-arid areas. We furthermore find that the pollen-climate relationship between north-central China and the eastern Tibetan Plateau is generally similar, but that regional differences are larger than temporal differences. In summary, vegetation-climate relationships in China are generally stable in space and time, and pollen-based climate reconstructions can be applied to the Holocene. Regional differences imply the calibration-set should be restricted spatially.

Projected effects of Climate-change-induced flow alterations on stream macroinvertebrate abundances.

PubMed

Kakouei, Karan; Kiesel, Jens; Domisch, Sami; Irving, Katie S; Jähnig, Sonja C; Kail, Jochem

2018-03-01

Global change has the potential to affect river flow conditions which are fundamental determinants of physical habitats. Predictions of the effects of flow alterations on aquatic biota have mostly been assessed based on species ecological traits (e.g., current preferences), which are difficult to link to quantitative discharge data. Alternatively, we used empirically derived predictive relationships for species' response to flow to assess the effect of flow alterations due to climate change in two contrasting central European river catchments. Predictive relationships were set up for 294 individual species based on (1) abundance data from 223 sampling sites in the Kinzig lower-mountainous catchment and 67 sites in the Treene lowland catchment, and (2) flow conditions at these sites described by five flow metrics quantifying the duration, frequency, magnitude, timing and rate of flow events using present-day gauging data. Species' abundances were predicted for three periods: (1) baseline (1998-2017), (2) horizon 2050 (2046-2065) and (3) horizon 2090 (2080-2099) based on these empirical relationships and using high-resolution modeled discharge data for the present and future climate conditions. We compared the differences in predicted abundances among periods for individual species at each site, where the percent change served as a proxy to assess the potential species responses to flow alterations. Climate change was predicted to most strongly affect the low-flow conditions, leading to decreased abundances of species up to -42%. Finally combining the response of all species over all metrics indicated increasing overall species assemblage responses in 98% of the studied river reaches in both projected horizons and were significantly larger in the lower-mountainous Kinzig compared to the lowland Treene catchment. Such quantitative analyses of freshwater taxa responses to flow alterations provide valuable tools for predicting potential climate-change impacts on species abundances and can be applied to any stressor, species, or region.

Enhancing the Quantitative Representation of Socioeconomic Conditions in the Shared Socio-economic Pathways (SSPs) using the International Futures Model

NASA Astrophysics Data System (ADS)

Rothman, D. S.; Siraj, A.; Hughes, B.

2013-12-01

The international research community is currently in the process of developing new scenarios for climate change research. One component of these scenarios are the Shared Socio-economic Pathways (SSPs), which describe a set of possible future socioeconomic conditions. These are presented in narrative storylines with associated quantitative drivers. The core quantitative drivers include total population, average GDP per capita, educational attainment, and urbanization at the global, regional, and national levels. At the same time there have been calls, particularly by the IAV community, for the SSPs to include additional quantitative information on other key social factors, such as income inequality, governance, health, and access to key infrastructures, which are discussed in the narratives. The International Futures system (IFs), based at the Pardee Center at the University of Denver, is able to provide forecasts of many of these indicators. IFs cannot use the SSP drivers as exogenous inputs, but we are able to create development pathways that closely reproduce the core quantitative drivers defined by the different SSPs, as well as incorporating assumptions on other key driving factors described in the qualitative narratives. In this paper, we present forecasts for additional quantitative indicators based upon the implementation of the SSP development pathways in IFs. These results will be of value to many researchers.

Passive-solar homes for Texas

NASA Astrophysics Data System (ADS)

Garrison, M. L.

1982-06-01

Acceptance of passive solar technologies has been slow within the conventional building trades in Texas because it is a common misconception that solar is expensive, and data on local applications is severely limited or nonexistent. It is the purpose of this solar development to move passive solar design into the mainstream of public acceptance by helping to overcome and eliminate these barriers. Specifically, the goal is to develop a set of regional climatic building standards to help guide the conventional building trade toward the utilization of soft energy systems which will reduce overall consumption at a price and convenience most Texans can afford. To meet this objective, eight sample passive design structures are presented. These designs represent state of the art regional applications of passive solar space conditioning. The methodology used in the passive solar design process included: analysis of regional climatic data; analysis of historical regional building prototypes; determination of regional climatic design priorities and assets; prototypical design models for the discretionary housing market; quantitative thermal analysis of prototypical designs; and construction drawings of building prototypes.

The Tropical Rainfall Measuring Mission: An Overview

NASA Technical Reports Server (NTRS)

Kummerow. Christian; Hong, Ye

1999-01-01

The importance of quantitative knowledge of tropical rainfall, its associated latent heating and variability is summarized in the context of the global hydrologic cycle. Much of the tropics is covered by oceans. What land exists, is covered largely by rainforests that are only thinly populated. The only way to adequately measure the global tropical rainfall for climate and general circulation models is from space. To address these issues, the TRMM satellite was launched in Nov. 1997. It has been operating successfully ever since.