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Model evaluation and hindcasting: An experiment with an integrated assessment model

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  • Chaturvedi, Vaibhav
  • Kim, Sonny
  • Smith, Steven J.
  • Clarke, Leon
  • Yuyu, Zhou
  • Kyle, Page
  • Patel, Pralit

Abstract

Integrated assessment models have been extensively used to examine long term energy and greenhouse emissions trajectories, but these models have rarely been examined with respect to their ability to capture historical dynamics. We evaluate the USA buildings component of the Global Change Assessment Model by calibrating the model for 1990 and running forward to 2095. Results for 1995, 2000, 2005 and 2010 are compared to historical estimates at the level of fuel, service, and US states. We highlight that the creation of a historical evaluation dataset is one of the foremost challenges in the evaluation process. This model set-up matches the reported growth of residential floorspace but slightly overestimates heating service demand and underestimates the growth in miscellaneous plug loads. While cooling service appears to be underestimated in 2005, we find little evidence for a systematic bias for other years. The apparently rapid growth of some demands in the commercial sector was also not captured. While these differences carry through into future projections, the overall character of these projections is not changed. These results highlight the difficulty of determining the relationship between energy service demand, which is an unobserved variable, and its drivers when there is limited historical data.

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  • Chaturvedi, Vaibhav & Kim, Sonny & Smith, Steven J. & Clarke, Leon & Yuyu, Zhou & Kyle, Page & Patel, Pralit, 2013. "Model evaluation and hindcasting: An experiment with an integrated assessment model," Energy, Elsevier, vol. 61(C), pages 479-490.
  • Handle: RePEc:eee:energy:v:61:y:2013:i:c:p:479-490
    DOI: 10.1016/j.energy.2013.08.061
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    3. Leibowicz, Benjamin D. & Lanham, Christopher M. & Brozynski, Max T. & Vázquez-Canteli, José R. & Castejón, Nicolás Castillo & Nagy, Zoltan, 2018. "Optimal decarbonization pathways for urban residential building energy services," Applied Energy, Elsevier, vol. 230(C), pages 1311-1325.
    4. Seungho Jeon & Minyoung Roh & Jaeick Oh & Suduk Kim, 2020. "Development of an Integrated Assessment Model at Provincial Level: GCAM-Korea," Energies, MDPI, vol. 13(10), pages 1-15, May.
    5. Nikas, A. & Gambhir, A. & Trutnevyte, E. & Koasidis, K. & Lund, H. & Thellufsen, J.Z. & Mayer, D. & Zachmann, G. & Miguel, L.J. & Ferreras-Alonso, N. & Sognnaes, I. & Peters, G.P. & Colombo, E. & Howe, 2021. "Perspective of comprehensive and comprehensible multi-model energy and climate science in Europe," Energy, Elsevier, vol. 215(PA).
    6. Charlie Wilson & Céline Guivarch & Elmar Kriegler & Bas Ruijven & Detlef P. Vuuren & Volker Krey & Valeria Jana Schwanitz & Erica L. Thompson, 2021. "Evaluating process-based integrated assessment models of climate change mitigation," Climatic Change, Springer, vol. 166(1), pages 1-22, May.
    7. Li, Wenliang & Zhou, Yuyu & Cetin, Kristen & Eom, Jiyong & Wang, Yu & Chen, Gang & Zhang, Xuesong, 2017. "Modeling urban building energy use: A review of modeling approaches and procedures," Energy, Elsevier, vol. 141(C), pages 2445-2457.
    8. Zhao, Xin & Calvin, Katherine V. & Wise, Marshall A. & Iyer, Gokul, 2021. "The role of global agricultural market integration in multiregional economic modeling: Using hindcast experiments to validate an Armington model," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 1-17.

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