Relevant bibliographies by topics / Climate change model

Academic literature on the topic 'Climate change model'

Author: Grafiati

Published: 18 May 2024

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Journal articles on the topic "Climate change model"

Hanf, Franziska, Janina Körper, Thomas Spangehl, and Ulrich Cubasch. "Shifts of climate zones in multi-model climate change experiments using the Köppen climate classification." Meteorologische Zeitschrift 21, no. 2 (April 1, 2012): 111–23. http://dx.doi.org/10.1127/0941-2948/2012/0344.

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A Shinde Waman, Sneha. "Replicable Model for Climate Proofing and Reducing Vulnerabilities due to Climate Change in different Agro Climatic Zones of Maharashtra." International Journal of Science and Research (IJSR) 13, no. 4 (April 5, 2024): 1373–76. http://dx.doi.org/10.21275/sr24416172526.

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Elía, Ramón Côté. "Climate and climate change sensitivity to model configuration in the Canadian RCM over North America." Meteorologische Zeitschrift 19, no. 4 (August 1, 2010): 325–39. http://dx.doi.org/10.1127/0941-2948/2010/0469.

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Fan, Fangxing, Raymond S. Bradley, and Michael A. Rawlins. "Climate change in the northeastern US: regional climate model validation and climate change projections." Climate Dynamics 43, no. 1-2 (June 1, 2014): 145–61. http://dx.doi.org/10.1007/s00382-014-2198-1.

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Nobre, Paulo, Leo S. P. Siqueira, Roberto A. F. de Almeida, Marta Malagutti, Emanuel Giarolla, Guilherme P. Castelão, Marcus J. Bottino, et al. "Climate Simulation and Change in the Brazilian Climate Model." Journal of Climate 26, no. 17 (August 23, 2013): 6716–32. http://dx.doi.org/10.1175/jcli-d-12-00580.1.

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Abstract The response of the global climate system to atmospheric CO2 concentration increase in time is scrutinized employing the Brazilian Earth System Model Ocean–Atmosphere version 2.3 (BESM-OA2.3). Through the achievement of over 2000 yr of coupled model integrations in ensemble mode, it is shown that the model simulates the signal of recent changes of global climate trends, depicting a steady atmospheric and oceanic temperature increase and corresponding marine ice retreat. The model simulations encompass the time period from 1960 to 2105, following the phase 5 of the Coupled Model Intercomparison Project (CMIP5) protocol. Notwithstanding the accurate reproduction of large-scale ocean–atmosphere coupled phenomena, like the ENSO phenomena over the equatorial Pacific and the interhemispheric gradient mode over the tropical Atlantic, the BESM-OA2.3 coupled model shows systematic errors on sea surface temperature and precipitation that resemble those of other global coupled climate models. Yet, the simulations demonstrate the model’s potential to contribute to the international efforts on global climate change research, sparking interest in global climate change research within the Brazilian climate modeling community, constituting a building block of the Brazilian Framework for Global Climate Change Research.

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Karmalkar, Ambarish V., Raymond S. Bradley, and Henry F. Diaz. "Climate change in Central America and Mexico: regional climate model validation and climate change projections." Climate Dynamics 37, no. 3-4 (May 29, 2011): 605–29. http://dx.doi.org/10.1007/s00382-011-1099-9.

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van Eck, Christel W., Bob C. Mulder, and Sander van der Linden. "Climate Change Risk Perceptions of Audiences in the Climate Change Blogosphere." Sustainability 12, no. 19 (September 27, 2020): 7990. http://dx.doi.org/10.3390/su12197990.

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The Climate Change Risk Perception Model (CCRPM, Van der Linden, 2015) has been used to characterize public risk perceptions; however, little is known about the model’s explanatory power in other (online) contexts. In this study, we extend the model and investigate the risk perceptions of a unique audience: The polarized climate change blogosphere. In total, our model explained 84% of the variance in risk perceptions by integrating socio-demographic characteristics, cognitive factors, experiential processes, socio-cultural influences, and an additional dimension: Trust in scientists and blogs. Although trust and the scientific consensus are useful additions to the model, affect remains the most important predictor of climate change risk perceptions. Surprisingly, the relative importance of social norms and value orientations is minimal. Implications for risk and science communication are discussed.

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M, Navaneetha Krishnan, Ranjith R, and Lavanya B. "Climate Change Prediction Using ARIMA Model." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 621–25. http://dx.doi.org/10.22214/ijraset.2022.43777.

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Abstract: It is a challenging task to forecast weather data accurately. The temperature change has important implications for business and economic activity. Effective management of global climate change impacts will depend upon accurate and costeffective forecasts. This paper univariate statistic techniques to model the properties of a world mean temperature dataset to develop a parsimonious forecasting model for managerial decision-making over the short-term horizon and the ARIMAbased prognostication tool has been developed by implementing the ARIMA algorithm in python. Although the model is estimated on global temperature data, the methodology could even be applied to temperature data at more localized levels. The statistical techniques include seasonal and non-seasonal unit root testing with and without structural breaks as well as ARIMA and SARIMA modelling. This paper helps us to predict the air temperature, which is the main problem of global warming. Prediction of the likely impact of climate change on monthly mean maximum and minimum temperature in Tamilnadu. Time-series techniques to develop a parsimonious model of global mean temperature change that can be used to forecast over the short-term horizon (5- 10) years. Keywords: Global warming, Forecasting, temperature

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Scaife, Adam, Chris Folland, and John Mitchell. "A model approach to climate change." Physics World 20, no. 2 (February 2007): 20–25. http://dx.doi.org/10.1088/2058-7058/20/2/29.

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Khokhlov, V., E. Serga, and L. Neodstrelova. "Objective selection of model run from regional climate models ensemble." Ukrainian hydrometeorological journal, no. 28 (December 14, 2021): 29–36. http://dx.doi.org/10.31481/uhmj.28.2021.03.

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In this paper, a method was developed in relation to the north-western coast of the Black Sea in order to determine the optimal model run from regional climate models ensemble. As a result of climate change, which has been observed since the late 1980s in Ukraine, various natural objects changes have been also transformed. The study of such changes in the future is possible only by using runs of global or regional climate models. Moreover, the step of the spatial grid in the climate model must be comparative with the spatial size of a natural object under study. In the north-western coast of the Black Sea, climate change is characterized by increasing aridity of climate and a corresponding decrease in freshwater inflows into coastal lagoons from their catchments, making ecosystems of these lagoons sensitive and vulnerable to climate change. Using numerical models in order to study climate change impact on these natural objects requires input hydrometeorological information in the spatial grid points, the distance between which should correspond to the horizontal size of lagoons, i.e. several kilometers. In this paper, data from the scenarios RCP4.5 and RCP8.5 of the ensemble from 14 model runs with different regional climatic models of the CORDEX project were used to simulate the future changes of the temperature and precipitation regime. For each grid point and scenario, a single simulation was selected from the ensemble, which best reproduces the intra-annual changes of temperature, precipitation, and evaporation compared to the ensemble means. Despite the sufficiently large distance between the estuaries, the method allowed the selection of a single optimal model run, which shows the significant differences in spring and summer precipitation as well as year-around evaporation in the southern and northern parts of the northwestern coast of the region. This run well reproduces the relationship between temperature, precipitation, and evaporation in the southern and northern parts of the northwestern coast of the Black Sea.

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Dissertations / Theses on the topic "Climate change model"

Ogutu, Benjamin Keroboto Za'Ngoti. "Energy balance mathematical model on climate change." Thesis, Paris 6, 2015. http://www.theses.fr/2015PA066224/document.

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Dans cet étude, un modèle de complexité réduite des interactions et rétroactions du système couplé climat-économie-biosphère est construit avec le minimum de variables et d'équations nécessaires. Le Coupled Climate-Economy-Biosphere (CoCEB) est un modèle d’évaluation intégrée (IAM pour Integrated assessment model) du changement globale. Alors que beaucoup IAM traitent les coûts de réduction des émissions (abattement) simplement comme une perte non productive de revenu, cet étude considère également les activités d’abattement comme un investissement dans l'efficacité énergétique globale de l'économie et dans la diminution de l’ « intensité carbone » du système énergétique. L’étude montre que ces efforts aident à l’abattement du changement climatique et ont un effet positif sur l’économie. La plupart des IAM actuels se concentrent principalement sur le secteur énergétique pour les mesures d’abattement, et ne tiennent compte des émissions provenant de l'utilisation des terres que comme un forçage exogène. Le CoCEB a donc été étendu en ajoutant une équation pour la biomasse ses échanges de carbone. Cela permet d’étudier les aspects économiques de la séquestration de carbone du au contrôle du déboisement dans les forêts, et aussi à l’application généralisée des technologies de capture et stockage du carbone (CCS). L’étude confirme que ces mesures réduisent l’impact du changement climatique sur la croissance économique, mais ces résultats restent très dépendants des grandes incertitudes sur le cout des CCS et du contrôle de la deforestation. Ce modèle est un cadre formel qui représente de façon simple les différents éléments du système couplé et leurs interactions, il rassemble les différentes estimations des coûts afférents aux mesures de mitigation et permet de les comparer de façon cohérente
The goal of this study is to build a global reduced-complexity model of coupled climate-economy-biosphere interactions, which uses the minimum number of variables and equations needed to capture the fundamental mechanisms involved and can thus help clarify the role of the different mechanisms and parameters. The Coupled Climate-Economy-Biosphere (CoCEB) model takes an integrated assessment approach to simulating global change. While many integrated assessment models treat abatement costs merely as an unproductive loss of income, the study considered abatement activities also as an investment in overall energy efficiency of the economy and decrease of overall carbon intensity of the energy system. The study shows that these efforts help to abate climate change and lead to positive effects in economic growth. Due to the fact that integrated assessment models in the literature mainly focus on mitigation in the energy sector and consider emissions from land-use as exogenous, the global climate-economy-biosphere (CoCEB) model was extended by adding a biomass equation and the related exchanges of CO2 and used to investigate the relationship between the effects of using carbon capture and storage (CCS) and deforestation control, and the economy growth rate. These measures are found to reduce the impacts of climate change and positively affect the economy growth. These results remain nevertheless sensitive to the formulation of CCS costs while those for deforestation control were less sensitive. The model developed brings together and summarizes information from diverse estimates of climate change mitigation measures and their associated costs, and allows comparing them in a coherent way

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Zhou, Jian. "Integrating geospatial web 2.0 and global climate model for communicating climate change." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=114508.

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This study investigates the use of Geospatial Web 2.0 and Global Climate Models for climate change communication. The aim of this research has been to integrate the data, models, and tools of climate science with Geoweb to advance climate change communication. Several Geoweb applications have been developed to demonstrate the solutions for this integration and to fulfil two research objectives: (1) develop a method to employ Geoweb technologies for communicating climate change, (2) improve the accessibility of Global Climate Model by providing tools to engage people in the practice of climate science as well as the fundamental procedures involved in global climate modeling. My research method is to extend Geoweb functionality to existing climate science tools, with the goal of easing the interface and increasing the interactivity of those tools to elaborate the scientific process of climate modeling. Geoweb has the power to manipulate climate change datasets from diverse sources for creating interactive climate change visualization. This power can be further enhanced if we integrate Geoweb with scientific climate data analysis and visualization systems. Nonetheless, Geoweb technologies that provide 2D visualization are more stable, faster, and popularly used than the 3D visualization. It is more robust to use Geoweb for climate model output. Instead, employing Geoweb for other aspects of global climate model requires close cooperation between climate modeling scientists and Geoweb technology experts due to its complexity. It is crucial to balance an easy-to-use user interface and the complexity of information transferred. Following this study, it is hoped that much more efforts from global climate modeling groups and Geoweb science researchers can be drawn together to facilitate climate change communication.
Cette étude porte sur l'utilisation de Géospatiales Web 2.0 et Modèle Climatique Global pour le communication du changement climatique. Le but de cette recherche a été d'intégrer les données, les modèles et les outils de la science du climat avec Geoweb pour faire progresser la communication du changement climatique. Plusieurs applications de GeoWeb ont été développés pour démontrer les solutions de cette intégration et de remplir deux objectifs de recherche: (1) développer une méthode d' utiliser les technologies GeoWeb pour communiquer du changement climatique, (2) améliorer l'accessibilité de Modèle Climatique Global en fournissant des outils pour engager personnes dans la pratique de la science du climat, ainsi que les procédures fondamentales liées à la modélisation du climat mondial. Ma méthode de recherche est d'étendre les fonctionnalités de Geoweb à des outils existants des sciences du climat, dans le but d'alléger l'interface et en augmentant l'interactivité de ces outils pour élaborer le processus scientifique de la modélisation du climat. Geoweb a le pouvoir de manipuler des ensembles de données du changement climatique provenant de diverses sources pour créer une visualisation interactive du changement climatique. Ce pouvoir peut être encore améliorée si l'on intègre Geoweb avec analyse scientifique des données climatiques et des systèmes de visualisation. Néanmoins, les technologies GeoWeb qui fournissent une visualisation 2D sont plus stables, plus rapide et couramment utilisée que la visualisation 3D. Il est plus robuste à utiliser Geoweb pour la sortie des modèles climatiques. Au lieu de cela, en utilisant Geoweb pour d'autres aspects du modèle climatique global nécessite des coopérations étroites entre les scientifiques de modélisation du climat et des experts en technologie de GeoWeb en raison de sa complexité. Il est essentiel d'équilibrer un outil facile à utiliser l'interface utilisateur et la complexité des informations transférées. Suite à cette étude, il est à espérer que beaucoup plus d'efforts de groupes mondiaux de modélisation du climat et des chercheurs en sciences GeoWeb peuvent être réunis pour faciliter la communication pour le changement climatique.

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Wi, Sungwook. "Impact of Climate Change on Hydroclimatic Variables." Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/265344.

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The conventional approach to the frequency analysis of extreme rainfall is complicated by non-stationarity resulting from climate change. In this study significant trends in extreme rainfall are detected using statistical trend tests (Mann-Kendall test and t-test) for all over the Korean Peninsula. The violation of the stationarity for 1 hour annual maximum series is detected for large part of the area especially for southwestern and northeastern regions. For stations showing non-stationarity, the non-stationary generalized extreme value (GEV) distribution model with a location parameter in the form of linear function of time makes significant improvement in modeling rainfall extremes when compared to the stationary GEV model. The Bartlett-Lewis rainfall model is used to generate annual maximum series for the purpose of generating the Intensity-Duration-Frequency (IDF) curve. Using 100 sets of 50 year synthetic annual maxima, it is found that the observed annual rainfall maximum series are reasonably represented by the model. The observed data is perturbed by change factors to incorporate the climate change scenario from the WRF (Weather Research and Forecasting) regional climate model into IDF estimates. The IDF curves for the future period 2040-2079 show highest estimates for all return periods and rainfall durations. The future IDF estimates show significant difference from the IDF estimates of the historical period (1968-2000). Overall, IDF curves show an increasing tendency over time. A historical and future climate simulation is evaluated over the Colorado River Basin using a 111-year simulation (1969-2079) of the WRF climate change scenario. We find the future projections show statistically significant increases in temperature with larger increases in the northern part of the basin. There are statistically insignificant increases in precipitation, while snowfall shows a statistically significant decrease throughout the period in all but the highest elevations and latitudes. The strongest decrease in snowfall is seen at high elevations in the southern part of the basin and low elevations in the northern part of the basin.

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Alberth, Stephan Eric. "Valuing technical change information in an integrated assessment model of climate change." Thesis, University of Cambridge, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.613302.

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Otto, Vincent M., Andreas Loeschel, and John M. Reilly. "Directed Technical Change and Climate Policy." MIT Joint Program on the Science and Policy of Global Change, 2006. http://hdl.handle.net/1721.1/32541.

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This paper studies the cost effectiveness of climate policy if there are technology externalities. For this purpose, we develop a forward-looking CGE model that captures empirical links between CO2 emissions associated with energy use, directed technical change and the economy. We find the cost-effective climate policy to include a combination of R&D subsidies and CO2 emission constraints, although R&D subsidies raise the shadow value of the CO2 constraint (i.e. CO2 price) because of a strong rebound effect from stimulating innovation. Furthermore, we find that CO2 constraints differentiated toward CO2-intensive sectors are more cost effective than constraints that generate uniform CO2 prices among sectors. Differentiated CO2 prices, through technical change and concomitant technology externalities, encourage growth in the non-CO2 intensive sectors and discourage growth in CO2-intensive sectors. Thus, it is cost effective to let the latter bear relatively more of the abatement burden. This result is robust to whether emission constraints, R&D subsidies or combinations of both are used to reduce CO2 emissions.
Abstract in HTML and technical report in PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/).

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Gars, Johan. "Essays on the Macroeconomics of Climate Change." Doctoral thesis, Stockholms universitet, Nationalekonomiska institutionen, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-74555.

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This thesis consists of three essays on macroeconomic aspects of climate change. Technological Trends and the Intertemporal Incentives For Fossil-Fuel Use analyzes how (the expectations about) the future developments of different kinds of technology affect the intertemporal incentives for fossil-fuel use. I find that improvements in the future state of technologies for alternative-energy generation, energy efficiency and total factor productivity all increase fossil-fuel use before the change takes place. The effect of changes in the efficiency of non-energy inputs is the reverse, while the effect of changes in fossil-fuel based energy technology is ambiguous. These conclusions are robust to a number of variations of the assumptions made. The Role of the Nature of Damages considers to what extent the choice of modeling climate impacts as affecting productivity, utility or the depreciation of capital affects the behavior of integrated assessment models. I carry out my analysis in two different ways. Firstly, under some simplifying assumptions, I derive a simple formula for the optimal tax on fossil-fuel use that adds up the three different types of climate effects. Secondly, I use a two-period model with exogenous climate to analyze how the allocation of fossil-fuel use over time is affected by the effects of climate change. I find that this is sensitive to the assumptions made. Indirect Effects of Climate Change investigates how direct effects of climate change in some countries have indirect effects on other countries going through changing world market prices of goods and financial instruments. When calculating the total effects of climate change, these indirect effects must also be taken into account. I first derive these indirect effects in a many-country model. Reaching agreements about reductions in the emissions of greenhouse gases is made difficult by the negative correlation there seems to be between emissions of greenhouse gases and the vulnerability to climate change. I argue, based on a stylized two country example, that trade in goods will tend to make the countries' interests more aligned while trade in financial instruments will tend to make the countries' interests less aligned.

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Betts, Richard Arthur. "Modelling the influence of the vegetated land surface on climate and climate change." Thesis, University of Reading, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.312335.

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Conradie, Willem Stefaan. "Conceptualising and quantifying the nonlinear, chaotic climate: implications for climate model experimental design." Master's thesis, University of Cape Town, 2015. http://hdl.handle.net/11427/16527.

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Includes bibliographical references
Uncertainty in climate system initial conditions (ICs) is known to limit the predictability of future atmospheric states. On weather time scales (i.e. hours to days), the separation between two atmospheric model trajectories, initially "indistinguishable" (compared to unavoidable uncertainties) from one another, diverges exponentially-on-average over time, so that the "memory" of model ICs is eventually lost. In other words, there is a theoretical limit in the lead time for skilful weather forecasts. However, the influence of perturbations to climate system model ICs - particularly in more slowly evolving climate system components (e.g., the oceans and ice sheets) - on the evolution of model "climates" on longer time scales is less well understood. Hence, in order to better understand the role of IC uncertainty in climate predictability, particularly in the context of climate change, it is necessary to develop approaches for investigating and quantifying - at various spatial and temporal scales - the nature of the influence of ICs on the evolution of climate system trajectories. To this end, this study explores different conceptualisations and competing definitions of climate and the climate system, focussing on the role of ICs. The influence of ICs on climate quantifications, using probability distributions, is subsequently investigated in a climate model experiments using a low-resolution version of the Community Climate System Model version 4 (CCSM4). The model experiment consists of 11 different 50-member ensemble simulations with constant forcing, and three 50-member ensemble simulations under a climate change scenario with transient forcing. By analysing the output at global and regional scales, at least three distinct levels of IC influence are detected: (a) microscopic influence; (b) interannual-scale influence; and (c) intercentennial-scale influence. Distinct patterns of interannual-scale IC influence appear to be attributable to aperiodic and quasi-periodic variability in the model. It is found that, over some spatial domains, significant (p < 0.01) differences in atmospheric variable "climatologies", taken from 60-year distributions of model trajectories, occur due to IC differences of a similar order to round-off error. In addition, climate distributions constructed using different approaches are found to differ significantly. There is some evidence that ensemble distributions of multidecadal temperature response to transient forcing conditions can be influenced by ICs. The implications for quantifying and conceptualising climate are considered in the context of the experimental results. It is concluded that IC ensemble experiments can play a valuable role in better understanding climate variability and change, as well as allowing for superior quantification of model climates.

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Yettella, Vineel. "The Role of Internal Variability in Climate Change Projections within an Initial Condition Climate Model Ensemble." Thesis, University of Colorado at Boulder, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=10981737.

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Unforced internal variability abounds in the climate system and often confounds the identification of climate change due to external forcings. Given that greenhouse gas concentrations are projected to increase for the foreseeable future, separating forced climate change from internal variability is a key concern with important implications. Here, we leverage a 40-member ensemble, the Community Earth System Model Large Ensemble (CESM-LE) to investigate the influence of internal variability on the detection of forced changes in two climate phenomena. First, using cyclone identification and compositing techniques within the CESM-LE, we investigate precipitation changes in extratropical cyclones under greenhouse gas forcing and the effect of internal variability on the detection of these changes. We find that the ensemble projects increased cyclone precipitation under twenty-first century business-as-usual greenhouse gas forcing and this response exceeds internal variability in both near- and far- futures. Further, we find that these changes are almost entirely driven by increases in cyclone moisture. Next, we explore the role of internal variability in projections of the annual cycle of surface temperature over Northern Hemisphere land. Internal variability strongly confounds forced changes in the annual cycle over many regions of the Northern Hemisphere. Changes over Europe, North Africa and Siberia, however, are large and easily detectable and further, are remarkably robust across model ensembles from the Coupled Model Intercomparison Project Phase 5 (CMIP5) archive. Using a simple energy balance model, we find that changes in the annual cycle over the three regions are mostly driven by changes in surface heat fluxes.

The thesis also presents a novel ensemble-based framework for diagnosing forced changes in regional climate variability. Changes in climate variability are commonly assessed in terms of changes in the variances of climate variables. The covariance response has received much less attention, despite the existence of large-scale modes of variability that induce covariations in climate variables over a wide range of spatial scales. Addressing this, the framework facilitiates a unified assessment of forced changes in the regional variances and covariances of climate variables.

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Clark, Logan N. "Southern Hemisphere Pressure Relationships during the 20th Century - Implications for Climate Reconstructions and Model Evaluation." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1586778291377432.

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Books on the topic "Climate change model"

Agoramoorthy, Govindasamy. Sadguru model of rural development mitigates climate change in India's drylands. New Delhi: Daya Publishing House, a division of Astral International Pvt. Ltd., 2015.

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Wendy, Howe, Henderson-Sellers A, and Model Evaluation Consortium for Climate Assessment., eds. Assessing climate change: Results from the Model Evaluation Consortium for Climate Assessment. Amsterdam: Gordon and Breach Science Publishers, 1997.

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Ann-Maree, Hansen, ed. Climate change atlas: Greenhouse simulations from the Model Evaluation Consortium for Climate Assessment. Dordrecht: Kluwer Academic Publishers, 1995.

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Shrestha, Arun Bhakta. Climate change in the eastern Himalayas: Observed trends and model projections. Kathmandu: International Centre for Integrated Mountain Development, 2010.

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Sensitivity of a global climate model to the urban land unit. Middletown, Delaware: Legates Consulting Llc, 2013.

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Nozawa, Tōru. Climate change simulations with a coupled ocean-atmosphere GCM called the model for interdisciplinary research on climate: MIROC. Tsukuba, Japan: Center for Global Environmental Research, National Institute for Environmental Studies, 2007.

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Hulme, Mike. Observational data sets, climate model validation and climate change detection: Final report to the Department of the Environment, April 1995 to March 1997. Norwich: Climatic Research Unit, University of East Anglia, 1997.

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Grotch, Stanley L. An intercomparison of general circulation model predictions of regional climate change: Presented at the International Conference on "Modelling of Global Climate Change and Variability," Hamburg, Federal Republic of Germany, September 1989. [Springfield, Va: Available from National Technical Information Service, 1990.

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Nuttal, Pat, ed. Climate, ticks and disease. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789249637.0000.

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Abstract This book is a collection of 77 expert opinions arranged in three sections. Section 1 on "Climate" sets the scene, including predictions of future climate change, how climate change affects ecosystems, and how to model projections of the spatial distribution of ticks and tick-borne infections under different climate change scenarios. Section 2 on "Ticks" focuses on ticks (although tick-borne pathogens creep in) and whether or not changes in climate affect the tick biosphere, from physiology to ecology. Section 3 on "Disease" focuses on the tick-host-pathogen biosphere, ranging from the triangle of tick-host-pathogen molecular interactions to disease ecology in various regions and ecosystems of the world. Each of these three sections ends with a synopsis that aims to give a brief overview of all the expert opinions within the section. The book concludes with Section 4 (Final Synopsis and Future Predictions). This synopsis attempts to summarize evidence provided by the experts of tangible impacts of climate change on ticks and tick-borne infections. In constructing their expert opinions, contributors give their views on what the future might hold. The final synopsis provides a snapshot of their expert thoughts on the future.

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Jay, Hannah Lee, Conservation International, and California Energy Commission. Public Interest Energy Research., eds. BioMove: Creation of a complex and dynamic model for assessing the impacts of climate change on California vegetation : PIER final project report. [Sacramento, Calif: California Energy Commission, 2008.

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Book chapters on the topic "Climate change model"

Bahman, Zohuri, and Mossavar-Rahmani Farhang. "Climate Change." In A Model to Forecast Future Paradigms, 281–317. Includes bibliographical references and index. | Contents: Volume 1. Introduction to knowledge is power in four dimensions: Apple Academic Press, 2019. http://dx.doi.org/10.1201/9781003000662-7.

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De Larminat, Philippe. "Formulating an Energy Balance Model." In Climate Change, 41–53. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781119053989.ch4.

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Brewer, Thomas. "Climate Model Projections and Potential Action Paths." In Climate Change, 199–222. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-42906-4_12.

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Ganopolski, Andrey, and Reinhard Calov. "Simulation of Glacial Cycles with an Earth System Model." In Climate Change, 49–55. Vienna: Springer Vienna, 2012. http://dx.doi.org/10.1007/978-3-7091-0973-1_3.

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Ye, Duzheng. "Sensitivity of Climate Model to Hydrology." In Understanding Climate Change, 101–8. Washington, D. C.: American Geophysical Union, 2013. http://dx.doi.org/10.1029/gm052p0101.

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Estrada, Mario Arturo Ruiz, Ibrahim Ndoma, and Donghyun Park. "The Application of the Macroeconomics Analysis of Climate Changes Model (MACC-Model) in China: Floods." In Climate Change Management, 33–48. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14938-7_3.

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Helmke, Hannah, Hans-Peter Hafner, Fabian Gebert, and Ari Pankiewicz. "Provision of Climate Services—The XDC Model." In Climate Change Management, 223–49. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36875-3_12.

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Moernaut, Renée, Jelle Mast, and Luc Pauwels. "Framing Climate Change: A Multi-level Model." In Climate Change Management, 215–71. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69838-0_14.

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Roche, Didier M., Hans Renssen, and Didier Paillard. "A Spatial View on Temperature Change and Variability During the Last Deglaciation: A Model Analysis." In Climate Change, 79–91. Vienna: Springer Vienna, 2012. http://dx.doi.org/10.1007/978-3-7091-0973-1_6.

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Schlesinger, Michael E. "Quantitative Analysis of Feedbacks in Climate Model Simulations." In Understanding Climate Change, 177–87. Washington, D. C.: American Geophysical Union, 2013. http://dx.doi.org/10.1029/gm052p0177.

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Conference papers on the topic "Climate change model"

Arenson, Lukas, David Sego, and Greg Newman. "The use of a convective heat flow model in road designs for Northern regions." In 2006 IEEE EIC Climate Change Conference. IEEE, 2006. http://dx.doi.org/10.1109/eicccc.2006.277276.

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Holtanová, Eva, and Tomáš Halenka. "Climate change scenarios." In První konference PERUN. Český hydrometeorologický ústav, 2023. http://dx.doi.org/10.59984/978-80-7653-063-8.03.

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Climate change scenarios represent plausible alternative future climate states that can occur under certain assumptions about the evolution of anthropogenic climate forcings, in particular emissions and concentrations of greenhouse gases and aerosols, but also changes in land use. Possible pathways used to be presented in the form of emission scenarios, but today more broadly defined 'socio-economic pathways' (SSPs) are available. Climate change scenarios are a tool for finding the limits of possible future developments. Estimates of future climate can be made in different ways. Nowadays they are mostly based on the outputs of global climate models, with possible application of downscaling approach. The model outputs then need to be subjected to some form of post-processing before further application in order to reduce the impact of known model errors. The extent of uncertainty associated with the resulting data should also be assessed. In particular, the procedures used in the PERUN project will be presented, but also other options, including recent approaches such as storylines and global warming levels will be mentioned.

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"The AgMIP Global Gridded Model Intercomparison." In ASABE 1st Climate Change Symposium: Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152124282.

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Croce, Pietro, Paolo Formichi, and Filippo Landi. "A BAYESIAN HIERARCHICAL MODEL FOR CLIMATIC LOADS UNDER CLIMATE CHANGE." In 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering. Athens: Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece, 2019. http://dx.doi.org/10.7712/120219.6342.18579.

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"New model for capturing heterogeneity of fertilizer-induced N2O emission factors." In ASABE 1st Climate Change Symposium: Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152144930.

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"Exploring Water Management Options with COWA: A Coupled Human-Climate-Water Model." In ASABE 1st Climate Change Symposium: Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152144305.

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"A computational fluid dynamics model of methane and ammonia emissions from tie-stall dairy barns." In ASABE 1st Climate Change Symposium: Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152124152.

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Miller, Sara, Terrance Quinn, and James Ianelli. "Estimation of Age-Specific Migration in an Age-Structured Model." In Resiliency of Gadid Stocks to Fishing and Climate Change. Alaska Sea Grant College Program, 2008. http://dx.doi.org/10.4027/rgsfcc.2008.09.

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"Application of the CERES-Maize Model for Climate Change Impact Assessment in Rainfed Corn Production in Isabela, Philippines." In ASABE 1st Climate Change Symposium: Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152088440.

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Nissan, Hannah, Jim Clarke, Shirley Oliveira, and Ralf Toumi. "Adapting to Climate Change: A Regional Climate Model Study of the Caucasus." In International Conference on Health, Safety and Environment in Oil and Gas Exploration and Production. Society of Petroleum Engineers, 2012. http://dx.doi.org/10.2118/157430-ms.

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Reports on the topic "Climate change model"

Dewart, Jean Marie. Conceptual Model of Climate Change Impacts at LANL. Office of Scientific and Technical Information (OSTI), May 2016. http://dx.doi.org/10.2172/1253547.

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Kocarev, Ljupco. An Interactive Multi-Model for Consensus on Climate Change. Office of Scientific and Technical Information (OSTI), July 2014. http://dx.doi.org/10.2172/1136784.

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Gillingham, Kenneth, William Nordhaus, David Anthoff, Geoffrey Blanford, Valentina Bosetti, Peter Christensen, Haewon McJeon, John Reilly, and Paul Sztorc. Modeling Uncertainty in Climate Change: A Multi-Model Comparison. Cambridge, MA: National Bureau of Economic Research, October 2015. http://dx.doi.org/10.3386/w21637.

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Auffhammer, Maximilian, Solomon Hsiang, Wolfram Schlenker, and Adam Sobel. Using Weather Data and Climate Model Output in Economic Analyses of Climate Change. Cambridge, MA: National Bureau of Economic Research, May 2013. http://dx.doi.org/10.3386/w19087.

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Policy Institute, International Food. Projections from IFPRI's IMPACT model: Climate change and food systems. Washington, DC: International Food Policy Research Institute, 2022. http://dx.doi.org/10.2499/9780896294257_14.

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Kukla, G., and J. Gavin. Global climate change model natural climate variation: Paleoclimate data base, probabilities and astronomic predictors. Office of Scientific and Technical Information (OSTI), May 1994. http://dx.doi.org/10.2172/145219.

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Russell, H. A. J., and S. K. Frey. Canada One Water: integrated groundwater-surface-water-climate modelling for climate change adaptation. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/329092.

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Canada 1 Water is a 3-year governmental multi-department-private-sector-academic collaboration to model the groundwater-surface-water of Canada coupled with historic climate and climate scenario input. To address this challenge continental Canada has been allocated to one of 6 large watershed basins of approximately two million km2. The model domains are based on natural watershed boundaries and include approximately 1 million km2 of the United States. In year one (2020-2021) data assembly and validation of some 20 datasets (layers) is the focus of work along with conceptual model development. To support analysis of the entire water balance the modelling framework consists of three distinct components and modelling software. Land Surface modelling with the Community Land Model will support information needed for both the regional climate modelling using the Weather Research & Forecasting model (WRF), and input to HydroGeoSphere for groundwater-surface-water modelling. The inclusion of the transboundary watersheds will provide a first time assessment of water resources in this critical international domain. Modelling is also being integrated with Remote Sensing datasets, notably the Gravity Recovery and Climate Experiment (GRACE). GRACE supports regional scale watershed analysis of total water flux. GRACE along with terrestrial time-series data will serve provide validation datasets for model results to ensure that the final project outputs are representative and reliable. The project has an active engagement and collaborative effort underway to try and maximize the long-term benefit of the framework. Much of the supporting model datasets will be published under open access licence to support broad usage and integration.

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Edmonds, J. A., M. A. Wise, and C. N. MacCracken. ADVANCED ENERGY TECHNOLOGIES AND CLIMATE CHANGE: AN ANALYSIS USING THE GLOBAL CHANGE ASSESSMENT MODEL (GCAM). Office of Scientific and Technical Information (OSTI), May 1994. http://dx.doi.org/10.2172/1127203.

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Cooter, Ellen J., Brian K. Eder, Sharon K. LeDuc, and Lawrence Truppi. General Circulation Model Output for Forest Climate Change Research and Applications. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station, 1993. http://dx.doi.org/10.2737/se-gtr-085.

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