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Journal articles on the topic '190501 Climate change models'

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Published: 10 December 2022

Last updated: 29 January 2023

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1

Pitman, A. J., and R. J. Stouffer. "Abrupt change in climate and climate models." Hydrology and Earth System Sciences Discussions 3, no. 4 (July 19, 2006): 1745–71. http://dx.doi.org/10.5194/hessd-3-1745-2006.

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Abstract. First, we review the evidence that abrupt climate changes have occurred in the past and then demonstrate that climate models have developing capacity to simulate many of these changes. In particular, the processes by which changes in the ocean circulation drive abrupt changes appear to be captured by climate models to a degree that is encouraging. The evidence that past changes in the ocean have driven abrupt change in terrestrial systems is also convincing, but these processes are only just beginning to be included in climate models. Second, we explore the likelihood that climate models can capture those abrupt changes in climate that may occur in the future due to the enhanced greenhouse effect. We note that existing evidence indicates that a major collapse of the thermohaline circulate seems unlikely in the 21st century, although very recent evidence suggests that a weakening may already be underway. We have confidence that current climate models can capture a weakening, but a collapse of the thermohaline circulation in the 21st century is not projected by climate models. Worrying evidence of instability in terrestrial carbon, from observations and modelling studies, is beginning to accumulate. Current climate models used by the Intergovernmental Panel on Climate Change for the 4th Assessment Report do not include these terrestrial carbon processes. We therefore can not make statements with any confidence regarding these changes. At present, the scale of the terrestrial carbon feedback is believed to be small enough that it does not significantly affect projections of warming during the first half of the 21st century. However, the uncertainties in how biological systems will respond to warming are sufficiently large to undermine confidence in this belief and point us to areas requiring significant additional work.

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2

Pitman, A. J., and R. J. Stouffer. "Abrupt change in climate and climate models." Hydrology and Earth System Sciences 10, no. 6 (November 28, 2006): 903–12. http://dx.doi.org/10.5194/hess-10-903-2006.

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Abstract. First, we review the evidence that abrupt climate changes have occurred in the past and then demonstrate that climate models have developing capacity to simulate many of these changes. In particular, the processes by which changes in the ocean circulation drive abrupt changes appear to be captured by climate models to a degree that is encouraging. The evidence that past changes in the ocean have driven abrupt change in terrestrial systems is also convincing, but these processes are only just beginning to be included in climate models. Second, we explore the likelihood that climate models can capture those abrupt changes in climate that may occur in the future due to the enhanced greenhouse effect. We note that existing evidence indicates that a major collapse of the thermohaline circulation seems unlikely in the 21st century, although very recent evidence suggests that a weakening may already be underway. We have confidence that current climate models can capture a weakening, but a collapse in the 21st century of the thermohaline circulation is not projected by climate models. Worrying evidence of instability in terrestrial carbon, from observations and modelling studies, is beginning to accumulate. Current climate models used by the Intergovernmental Panel on Climate Change for the 4th Assessment Report do not include these terrestrial carbon processes. We therefore can not make statements with any confidence regarding these changes. At present, the scale of the terrestrial carbon feedback is believed to be small enough that it does not significantly affect projections of warming during the first half of the 21st century. However, the uncertainties in how biological systems will respond to warming are sufficiently large to undermine confidence in this belief and point us to areas requiring significant additional work.

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3

Dooge, J. C. I. "Hydrologic models and climate change." Journal of Geophysical Research 97, no. D3 (1992): 2677. http://dx.doi.org/10.1029/91jd02156.

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4

Anonymous. "Numerical models of climate change." Eos, Transactions American Geophysical Union 69, no. 45 (1988): 1556. http://dx.doi.org/10.1029/88eo01181.

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5

Schär, Christoph, Christoph Frei, Daniel Lüthi, and Huw C. Davies. "Surrogate climate-change scenarios for regional climate models." Geophysical Research Letters 23, no. 6 (March 15, 1996): 669–72. http://dx.doi.org/10.1029/96gl00265.

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6

Ewert, F., J. R. Porter, M. D. A. Rounsevell;, S. P. Long, E. A. Ainsworth, A. D. B. Leakey, D. R. Ort, J. Nosberger, and D. Schimel. "Crop Models, CO2, and Climate Change." Science 315, no. 5811 (January 26, 2007): 459c—460c. http://dx.doi.org/10.1126/science.315.5811.459c.

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7

Dowlatabadi, Hadi. "Integrated assessment models of climate change." Energy Policy 23, no. 4-5 (April 1995): 289–96. http://dx.doi.org/10.1016/0301-4215(95)90155-z.

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8

Herrando-Pérez, Salvador. "Climate change heats matrix population models." Journal of Animal Ecology 82, no. 6 (October 24, 2013): 1117–19. http://dx.doi.org/10.1111/1365-2656.12146.

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9

Araujo, Miguel B., Richard G. Pearson, Wilfried Thuiller, and Markus Erhard. "Validation of species-climate impact models under climate change." Global Change Biology 11, no. 9 (September 2005): 1504–13. http://dx.doi.org/10.1111/j.1365-2486.2005.01000.x.

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10

Bush, Drew, Renee Sieber, Mark A. Chandler, and Linda E. Sohl. "Teaching anthropogenic global climate change (AGCC) using climate models." Journal of Geography in Higher Education 43, no. 4 (September 9, 2019): 527–43. http://dx.doi.org/10.1080/03098265.2019.1661370.

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11

Pierce, D. W., T. P. Barnett, B. D. Santer, and P. J. Gleckler. "Selecting global climate models for regional climate change studies." Proceedings of the National Academy of Sciences 106, no. 21 (May 13, 2009): 8441–46. http://dx.doi.org/10.1073/pnas.0900094106.

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12

Huntingford, Chris, John Gash, and Anna Maria Giacomello. "Climate change and hydrology: next steps for climate models." Hydrological Processes 20, no. 9 (2006): 2085–87. http://dx.doi.org/10.1002/hyp.6208.

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13

García-Rodeja Gayoso, Isabel, and Glauce L. De Oliveira. "Climate change and the change of models of students’thinking." Enseñanza de las Ciencias. Revista de investigación y experiencias didácticas 30, no. 3 (November 15, 2012): 195. http://dx.doi.org/10.5565/rev/ec/v30n3.695.

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14

Forest, Chris E., Myles R. Allen, Peter H. Stone, and Andrei P. Sokolov. "Constraining uncertainties in climate models using climate change detection techniques." Geophysical Research Letters 27, no. 4 (February 15, 2000): 569–72. http://dx.doi.org/10.1029/1999gl010859.

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15

Belda, Michal, Petr Skalák, Aleš Farda, Tomáš Halenka, Michel Déqué, Gabriella Csima, Judit Bartholy, et al. "CECILIA Regional Climate Simulations for Future Climate: Analysis of Climate Change Signal." Advances in Meteorology 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/354727.

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Regional climate models (RCMs) are important tools used for downscaling climate simulations from global scale models. In project CECILIA, two RCMs were used to provide climate change information for regions of Central and Eastern Europe. Models RegCM and ALADIN-Climate were employed in downscaling global simulations from ECHAM5 and ARPEGE-CLIMAT under IPCC A1B emission scenario in periods 2021–2050 and 2071–2100. Climate change signal present in these simulations is consistent with respective driving data, showing similar large-scale features: warming between 0 and 3°C in the first period and 2 and 5°C in the second period with the least warming in northwestern part of the domain increasing in the southeastern direction and small precipitation changes within range of +1 to −1 mm/day. Regional features are amplified by the RCMs, more so in case of the ALADIN family of models.

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16

von Storch, Hans, and Dennis Bray. "Models, manifestation and attribution of climate change." Meteorology Hydrology and Water Management 5, no. 1 (January 18, 2017): 47–52. http://dx.doi.org/10.26491/mhwm/67388.

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17

Mudur, G. "Climate Change: Monsoon Shrinks With Aerosol Models." Science 270, no. 5244 (December 22, 1995): 1922. http://dx.doi.org/10.1126/science.270.5244.1922.

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18

Worrell, Ernst. "Economic Models of Climate Change: A Critique." Resources, Conservation and Recycling 42, no. 4 (November 2004): 389–90. http://dx.doi.org/10.1016/j.resconrec.2004.03.001.

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19

Parson, Edward A., and and Karen Fisher-Vanden. "INTEGRATED ASSESSMENT MODELS OF GLOBAL CLIMATE CHANGE." Annual Review of Energy and the Environment 22, no. 1 (November 1997): 589–628. http://dx.doi.org/10.1146/annurev.energy.22.1.589.

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20

Janssen, Marco A. "Sequential optimization of integrated climate change models." Mathematics and Computers in Simulation 54, no. 6 (January 2001): 477–89. http://dx.doi.org/10.1016/s0378-4754(00)00278-0.

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21

Forgó, Ferenc, János Fülöp, and Mária Prill. "Game theoretic models for climate change negotiations." European Journal of Operational Research 160, no. 1 (January 2005): 252–67. http://dx.doi.org/10.1016/j.ejor.2003.06.025.

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22

Read, Peter L. "A Sea Change in Exoplanet Climate Models?" Astrobiology 14, no. 8 (August 2014): 627–28. http://dx.doi.org/10.1089/ast.2014.1404.

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23

Stott, Peter A., and Chris E. Forest. "Ensemble climate predictions using climate models and observational constraints." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 365, no. 1857 (June 14, 2007): 2029–52. http://dx.doi.org/10.1098/rsta.2007.2075.

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Two different approaches are described for constraining climate predictions based on observations of past climate change. The first uses large ensembles of simulations from computationally efficient models and the second uses small ensembles from state-of-the-art coupled ocean–atmosphere general circulation models. Each approach is described and the advantages of each are discussed. When compared, the two approaches are shown to give consistent ranges for future temperature changes. The consistency of these results, when obtained using independent techniques, demonstrates that past observed climate changes provide robust constraints on probable future climate changes. Such probabilistic predictions are useful for communities seeking to adapt to future change as well as providing important information for devising strategies for mitigating climate change.

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24

Semenov, MA, J. Wolf, LG Evans, H. Eckersten, and A. Iglesias. "Comparison of wheat simulation models under climate change. II. Application of climate change scenarios." Climate Research 7 (1996): 271–81. http://dx.doi.org/10.3354/cr007271.

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25

Hammerle, R. H., J. W. Shiller, and M. J. Schwarz. "Global Climate Change." Journal of Engineering for Gas Turbines and Power 113, no. 3 (July 1, 1991): 448–55. http://dx.doi.org/10.1115/1.2906251.

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This paper reviews the validity of the greenhouse warming theory, its possible impact on the automotive industry, and what could be done. Currently there is very limited evidence that man’s activity has caused global warming. Mathematical models of the earth’s heat balance predict warming and associated climate changes, but their predictions have not been validated. Concern over possible warming has led to several evaluations of feasible CO2 control measures. Although cars and trucks contribute only a small fraction of the CO2 buildup, the automotive industry may be expected to reduce its share of the atmospheric CO2 loading if controls become necessary. Methods to reduce automotive CO2 emissions, including alternative fuels such as methanol, natural gas, and electricity, are discussed. Also, control of the other greenhouse gases, which may currently contribute about 45 percent of the greenhouse warming, is considered.

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26

Dasgupta, Partha. "Pricing climate change." Politics, Philosophy & Economics 13, no. 4 (August 13, 2014): 394–416. http://dx.doi.org/10.1177/1470594x14541521.

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In developing the basis on which climate change should be priced, I do five things. First, I review the ethical foundations for valuing future consumption relative to present consumption (i.e. social discount rates). Second, I report that the criterion for both assessing and prescribing economic policies should not be an economy's GDP, but an inclusive measure of an economy's wealth adjusted for the distribution of wealth. Third, I apply the resulting analysis to the problem of pricing carbon concentration in the atmosphere. I give prominence to future uncertainties. Fourth, I show that the existing models of human behaviour on the basis of which these questions have been analysed by economists have serious deficiencies, in as much as the idea of personhood embodied in them has been built on the psychology of confirmed egotists. Fifth, I sketch the motivations of a social being and show how the altered specification of the human person affects the social price of climate change.

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27

Beckage, Brian, Louis J. Gross, Katherine Lacasse, Eric Carr, Sara S. Metcalf, Jonathan M. Winter, Peter D. Howe, et al. "Linking models of human behaviour and climate alters projected climate change." Nature Climate Change 8, no. 1 (January 2018): 79–84. http://dx.doi.org/10.1038/s41558-017-0031-7.

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28

Chen, Jie, François P. Brissette, Philippe Lucas-Picher, and Daniel Caya. "Impacts of weighting climate models for hydro-meteorological climate change studies." Journal of Hydrology 549 (June 2017): 534–46. http://dx.doi.org/10.1016/j.jhydrol.2017.04.025.

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29

Guereña, Arantxa, Margarita Ruiz-Ramos, Carlos H. Díaz-Ambrona, José R. Conde, and M. Inés Mínguez. "Assessment of Climate Change and Agriculture in Spain Using Climate Models." Agronomy Journal 93, no. 1 (January 2001): 237–49. http://dx.doi.org/10.2134/agronj2001.931237x.

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30

Oo, Han Thi, Win Win Zin, and Cho Cho Thin Kyi. "Assessment of Future Climate Change Projections Using Multiple Global Climate Models." Civil Engineering Journal 5, no. 10 (October 7, 2019): 2152–66. http://dx.doi.org/10.28991/cej-2019-03091401.

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Nowadays, the hydrological cycle which alters river discharge and water availability is affected by climate change. Therefore, the understanding of climate change is curial for the security of hydrologic conditions of river basins. The main purpose of this study is to assess the projections of future climate across the Upper Ayeyarwady river basin for its sustainable development and management of water sector for this area. Global Ten climate Models available from CMIP5 represented by the IPCC for its fifth Assessment Report were bias corrected using linear scaling method to generate the model error. Among the GCMs, a suitable climate model for each station is selected based on the results of performance indicators (R2 and RMSE). Future climate data are projected based on the selected suitable climate models by using future climate scenarios: RCP2.6, RCP4.5, and RCP8.5. According to this study, future projection indicates to increase in precipitation amounts in the rainy and winter season and diminishes in summer season under all future scenarios. Based on the seasonal temperature changes analysis for all stations, the future temperature are predicted to steadily increase with higher rates during summer than the other two seasons and it can also be concluded that the monthly minimum temperature rise is a bit larger than the maximum temperature rise in all seasons.

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31

Soares, Pedro M. M., Rita M. Cardoso, João Jacinto Ferreira, and Pedro M. A. Miranda. "Climate change and the Portuguese precipitation: ENSEMBLES regional climate models results." Climate Dynamics 45, no. 7-8 (December 10, 2014): 1771–87. http://dx.doi.org/10.1007/s00382-014-2432-x.

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32

Mitchell, C. D. "CLIMATE CHANGE: A 1994 SCIENCE SUMMARY." APPEA Journal 34, no. 2 (1994): 104. http://dx.doi.org/10.1071/aj93090.

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New observations of the chemical composition of the atmosphere are reshaping scientific understanding of the global sources and sinks of the greenhouse gases. Current trends in the atmospheric concentrations of some of these gases are reviewed, with reference to new work emerging from Antarctic ice cores.Accompanying an understanding of the composition of the atmosphere, is the need to understand the processes which drive the global climate system, including interactions between the atmosphere and oceans. Studies of climatic processes therefore form the scientific underpinning for the development of numerical models that describe the response of the global climate system to observed changes in the composition of the atmosphere.Success or failure in efforts to improve model simulations can be assessed using a variety of objective statistical tests. Examples of such tests show demonstrable progress in the ability of global climate models to simulate the present day climate realistically.Since confidence in the regional details of climate predictions from climate models is low, considerable effort is being devoted to developing models capable of providing improved regional estimates of climate change and in practice a variety of models not limited to the global-scale models are used in this work. In the meantime, several approaches to assessing the potential impacts of climate change are possible. These are discussed with special reference to tropical cyclones and east coast lows.Throughout this review emphasis is placed on recent Australian contributions to the field, most notably work conducted within CSIRO.

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33

DE, U. S. "Climate change impact : Regional scenario." MAUSAM 52, no. 1 (December 29, 2021): 201–12. http://dx.doi.org/10.54302/mausam.v52i1.1688.

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Climate change and global warming are going to be the major issues for the 21st century. Their impacts on agriculture, water availability and other natural resources are of serious concern. The paper briefly summarizes the existing information on global warming, past climatic anomalies and occurrence of extreme events vis-a-vis their impact on south Asia in general and Indian in particular. Use of GCM models in conjunction with crop simulation models for impact assessment in agriculture are briefly touched upon. The impact on hydrosphere in terms of water availability and on the forests in India are also discussed. A major shift in our policy makers paradigm is needed to make development sustainable in the face of climate change, global warming and sea level rise.

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34

PALTSEV, SERGEY, and PANTELIS CAPROS. "COST CONCEPTS FOR CLIMATE CHANGE MITIGATION." Climate Change Economics 04, supp01 (November 2013): 1340003. http://dx.doi.org/10.1142/s2010007813400034.

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Major cost concepts used for evaluation of carbon policy are considered, including change in GDP, change in consumption, change in welfare, energy system cost, and area under marginal abatement cost (MAC) curve. The issues associated with the use of these concepts are discussed. We use the results from the models that participated in the European Energy Modeling Forum (EMF28) study to illustrate the cost concepts. There is substantial variability in the estimates of costs between the models, with some models showing substantial costs and some models reporting benefits from mitigation in some scenarios. Because impacts of a policy are evaluated as changes from a reference scenario, it is important to define a reference scenario. MAC cost measures tend to exclude existing distortions in the economy, while existing energy taxes and subsidies are substantial in many countries. We discuss that carbon prices are inadequate measures of the policy costs. We conclude that changes in macroeconomic consumption or welfare are the most appropriate measures of policy costs.

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35

Wolf, J. "Comparison of two potato simulation models under climate change. II. Application of climate change scenarios." Climate Research 21 (2002): 187–98. http://dx.doi.org/10.3354/cr021187.

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36

Wang, Bin, Michela Biasutti, Michael P. Byrne, Christopher Castro, Chih-Pei Chang, Kerry Cook, Rong Fu, et al. "Monsoons Climate Change Assessment." Bulletin of the American Meteorological Society 102, no. 1 (January 2021): E1—E19. http://dx.doi.org/10.1175/bams-d-19-0335.1.

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AbstractMonsoon rainfall has profound economic and societal impacts for more than two-thirds of the global population. Here we provide a review on past monsoon changes and their primary drivers, the projected future changes, and key physical processes, and discuss challenges of the present and future modeling and outlooks. Continued global warming and urbanization over the past century has already caused a significant rise in the intensity and frequency of extreme rainfall events in all monsoon regions (high confidence). Observed changes in the mean monsoon rainfall vary by region with significant decadal variations. Northern Hemisphere land monsoon rainfall as a whole declined from 1950 to 1980 and rebounded after the 1980s, due to the competing influences of internal climate variability and radiative forcing from greenhouse gases and aerosol forcing (high confidence); however, it remains a challenge to quantify their relative contributions. The CMIP6 models simulate better global monsoon intensity and precipitation over CMIP5 models, but common biases and large intermodal spreads persist. Nevertheless, there is high confidence that the frequency and intensity of monsoon extreme rainfall events will increase, alongside an increasing risk of drought over some regions. Also, land monsoon rainfall will increase in South Asia and East Asia (high confidence) and northern Africa (medium confidence), decrease in North America, and be unchanged in the Southern Hemisphere. Over the Asian–Australian monsoon region, the rainfall variability is projected to increase on daily to decadal scales. The rainy season will likely be lengthened in the Northern Hemisphere due to late retreat (especially over East Asia), but shortened in the Southern Hemisphere due to delayed onset.

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37

Plattner, G. K., R. Knutti, F. Joos, T. F. Stocker, W. von Bloh, V. Brovkin, D. Cameron, et al. "Long-Term Climate Commitments Projected with Climate–Carbon Cycle Models." Journal of Climate 21, no. 12 (June 15, 2008): 2721–51. http://dx.doi.org/10.1175/2007jcli1905.1.

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Abstract Eight earth system models of intermediate complexity (EMICs) are used to project climate change commitments for the recent Intergovernmental Panel on Climate Change’s (IPCC’s) Fourth Assessment Report (AR4). Simulations are run until the year 3000 a.d. and extend substantially farther into the future than conceptually similar simulations with atmosphere–ocean general circulation models (AOGCMs) coupled to carbon cycle models. In this paper the following are investigated: 1) the climate change commitment in response to stabilized greenhouse gases and stabilized total radiative forcing, 2) the climate change commitment in response to earlier CO2 emissions, and 3) emission trajectories for profiles leading to the stabilization of atmospheric CO2 and their uncertainties due to carbon cycle processes. Results over the twenty-first century compare reasonably well with results from AOGCMs, and the suite of EMICs proves well suited to complement more complex models. Substantial climate change commitments for sea level rise and global mean surface temperature increase after a stabilization of atmospheric greenhouse gases and radiative forcing in the year 2100 are identified. The additional warming by the year 3000 is 0.6–1.6 K for the low-CO2 IPCC Special Report on Emissions Scenarios (SRES) B1 scenario and 1.3–2.2 K for the high-CO2 SRES A2 scenario. Correspondingly, the post-2100 thermal expansion commitment is 0.3–1.1 m for SRES B1 and 0.5–2.2 m for SRES A2. Sea level continues to rise due to thermal expansion for several centuries after CO2 stabilization. In contrast, surface temperature changes slow down after a century. The meridional overturning circulation is weakened in all EMICs, but recovers to nearly initial values in all but one of the models after centuries for the scenarios considered. Emissions during the twenty-first century continue to impact atmospheric CO2 and climate even at year 3000. All models find that most of the anthropogenic carbon emissions are eventually taken up by the ocean (49%–62%) in year 3000, and that a substantial fraction (15%–28%) is still airborne even 900 yr after carbon emissions have ceased. Future stabilization of atmospheric CO2 and climate change requires a substantial reduction of CO2 emissions below present levels in all EMICs. This reduction needs to be substantially larger if carbon cycle–climate feedbacks are accounted for or if terrestrial CO2 fertilization is not operating. Large differences among EMICs are identified in both the response to increasing atmospheric CO2 and the response to climate change. This highlights the need for improved representations of carbon cycle processes in these models apart from the sensitivity to climate change. Sensitivity simulations with one single EMIC indicate that both carbon cycle and climate sensitivity related uncertainties on projected allowable emissions are substantial.

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38

Ledig, F. Thomas. "Climate Change and Conservation." Acta Silvatica et Lignaria Hungarica 8, no. 1 (December 1, 2012): 57–74. http://dx.doi.org/10.2478/v10303-012-0005-4.

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Abstract - Conserving forest genetic resources and, indeed, preventing species extinctions will be complicated by the expected changes in climate projected for the next century and beyond. This paper uses case examples from rare spruces (Picea sp.) from North America to discuss the interplay of conservation, genetics, and climate change. New models show how climate change will affect these spruces, making it necessary to relocate them if they are to survive, a tool known as assisted migration or, preferably, assisted colonization. The paper concludes with some speculation on the broader implications of climate change, and the relevance of conservation to preserving the necessary ecological services provided by forests.

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39

Bosu, Himel, Towhida Rashid, Abdul Mannan, and Javed Meandad. "Climate Change Analysis for Bangladesh Using CMIP5 Models." Dhaka University Journal of Earth and Environmental Sciences 9, no. 1 (July 15, 2021): 1–12. http://dx.doi.org/10.3329/dujees.v9i1.54856.

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Using the Coupled Model Inter-comparison Project phase 5 (CMIP5) global climate modeling predictions, the study analyzes the distribution of rainfall and temperature in Bangladesh in recent years (1981–2005) and in three future periods (2025–2049, 2050–2074 and 2075–2099) considering RCP 4.5 and RCP 8.5 scenarios. In the historical period, all three CMIP5 models (MPI-ESM-LR, MPI-ESM-MR and NorESM1-M) mostly underestimated the observed mean rainfall data collected from Bangladesh Meteorological Department (BMD), but for temperature the result is found almost similar between models and observation. The CMIP5 models simulation reveal biases in monthly mean rainfall and temperature over Bangladesh in the past, so bias-correction is performed for future data. Quantile mapping bias-correction reduces significant amount of biases from the projection data of rainfall and temperature. By the end of the twenty-first century, the multi-model ensemble annual mean rainfall averaged over Bangladesh is projected to change between -2% to 9% and -3% to 15% under RCP 4.5 and RCP 8.5, respectively. The changes in spatial patterns of annual rainfall indicate a decrease in rainfall over a major portion in the west and the northwestern and an increase in the southeast, east, and the northeastern part of the country. The multi-model ensemble projection reveals a continuous increase in the annual mean temperature and shows a larger increase over the northwestern part and west-central part of Bangladesh. By the end of the twenty-first century, the annual mean temperature over Bangladesh is projected to increase by 1.9 (0.9-2.8) °C and 4 (2.8-4.6) °C under the RCP 4.5 and RCP 8.5 scenarios respectively, relative to the reference climate (1981-2005). The Dhaka University Journal of Earth and Environmental Sciences, Vol. 9(1), 2020, P 1-12

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40

Blanchard, Élodie Vieille. "The origins of integrated models of climate change." Atoms for Peace: an International Journal 3, no. 3 (2012): 238. http://dx.doi.org/10.1504/afp.2012.046739.

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41

Spash, Clive L. "Human‐induced climate change: The limits of models." Environmental Politics 5, no. 2 (June 1996): 376–80. http://dx.doi.org/10.1080/09644019608414276.

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42

Revesz, Richard L., Peter H. Howard, Kenneth Arrow, Lawrence H. Goulder, Robert E. Kopp, Michael A. Livermore, Michael Oppenheimer, and Thomas Sterner. "Global warming: Improve economic models of climate change." Nature 508, no. 7495 (April 2014): 173–75. http://dx.doi.org/10.1038/508173a.

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43

Graham, L. Phil, Stefan Hagemann, Simon Jaun, and Martin Beniston. "On interpreting hydrological change from regional climate models." Climatic Change 81, S1 (March 23, 2007): 97–122. http://dx.doi.org/10.1007/s10584-006-9217-0.

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44

Ackerman, Frank, Stephen J. DeCanio, Richard B. Howarth, and Kristen Sheeran. "Limitations of integrated assessment models of climate change." Climatic Change 95, no. 3-4 (April 2, 2009): 297–315. http://dx.doi.org/10.1007/s10584-009-9570-x.

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Schwanitz, Valeria Jana. "Evaluating integrated assessment models of global climate change." Environmental Modelling & Software 50 (December 2013): 120–31. http://dx.doi.org/10.1016/j.envsoft.2013.09.005.

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Schimmelpfennig, David. "Uncertainty in economic models of climate-change impacts." Climatic Change 33, no. 2 (June 1996): 213–34. http://dx.doi.org/10.1007/bf00140247.

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Rose, Adam. "Multisector economic models for analyzing global climate change." Global and Planetary Change 11, no. 4 (April 1996): 201–21. http://dx.doi.org/10.1016/0921-8181(95)00053-4.

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Holland, M. M., and C. M. Bitz. "Polar amplification of climate change in coupled models." Climate Dynamics 21, no. 3-4 (September 1, 2003): 221–32. http://dx.doi.org/10.1007/s00382-003-0332-6.

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Kaiser, Harry M. "Climate Change and Agriculture." Northeastern Journal of Agricultural and Resource Economics 20, no. 2 (October 1991): 151–63. http://dx.doi.org/10.1017/s0899367x0000297x.

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Abstract:

Without a doubt, climate change will be one of the most important environmental topics of the 1990s and will be high on the research agendas of many scientific disciplines in years ahead. While not yet universally accepted, it is now widely believed that anthropogenic emissions of carbon dioxide and other “greenhouse” gases have the potential to substantially warm climates worldwide. Although there is no consensus on the timing and magnitude of global warming, current climate models predict an average increase of 2.8°C to 5.2°C in the earth's temperature over the next century (Karl, Diaz, and Barnett). Changes in regional temperature and precipitation will likely accompany the global warming, but there is even less scientific agreement on the magnitude of these changes.

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Garrido, A., D. Rey, M. Ruiz-Ramos, and MI Mínguez. "Climate change and crop adaptation in Spain: consistency of regional climate models." Climate Research 49, no. 3 (November 9, 2011): 211–27. http://dx.doi.org/10.3354/cr01029.

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