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Climate change will impact the value and optimal adoption of residential rooftop solar


Rooftop solar adoption is critical for residential decarbonization and hinges on its value to households. Climate change will probably affect the value of rooftop solar through impacts on rooftop solar generation and cooling demand, but no studies have quantified this effect. In this study, we quantified household-level effects of climate change on rooftop solar value and techno-economically optimal capacity by integrating empirical demand data for over 2,000 US households across 17 cities, household-level simulation and optimization models, and downscaled weather data for historic and future climates. We found that climate change will increase the value of rooftop solar to households by up to 19% and increase techno-economically optimal household capacity by up to 25% by the end of the century under a Representative Concentration Pathway 4.5 scenario. This increased value is robust across cities, households, future warming scenarios and retail tariff structures. Researchers, installers and policymakers should capture this increasing value to maximize household and system value of rooftop solar.

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Fig. 1: Climate change-induced residential cooling and solar potential change.
Fig. 2: Average change in the ratio of VOS per watt across households by city under the RCP-4.5-Hotter scenario.
Fig. 3: Climate change effects on household-level techno-economically optimal RSPV capacity and VOS.
Fig. 4: Household VOS increases due to capacity effect versus direct climate effect.
Fig. 5: Average household VOS and techno-economically optimal capacity increases under different climate scenarios.

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Data availability

The individual hourly cooling behaviour data can be obtained from Ecobee upon request38. The future TGW climate data are from the US Department of Energy Office of Scientific and Technical Information39 and are publicly available. Other data sources are provided in Methods and Supplementary Information. The household-level VOS and optimal solar capacity data are available via Figshare at (ref. 64).

Code availability

The codes (python scripts) are available via Figshare at (ref. 64), including model codes (HHAC model, solar potential mapping and VOS optimization) and figure production codes (Figs. 15).


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This work was supported by the National Natural Science Foundation of China (grant nos. 72025401, 72243007 and 72140003), the National Key Research and Development Program of China (Grant Nos. 2022YFC3702902, 2022YFC3702900 and 2023YFE0204600), the Carbon Neutrality and Energy System Transformation (CNEST) Project and the Ordos-Tsinghua Innovative & Collaborative Research Program in Carbon Neutrality. M.T.C. thanks the U.S. National Science Foundation under grant no. 2142421 for funding. We thank P. Wildstein for building modelling and grid tariff analysis and R. Jain for building simulations.

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Authors and Affiliations



M.S. developed the research concept, designed and performed the analysis, collected data, wrote the code and drafted the paper. M.T.C contributed to the development of the concept, reviewed the codes and revised the narrative structure and language of the paper. X.L. contributed to the draft paper and its revision.

Corresponding authors

Correspondence to Xi Lu or Michael T. Craig.

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Nature Climate Change thanks Amarasinghage T. D. Perera, Zhili Wang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Methods 1–7, Results 1–8, Figs. 1–43 and Tables 1–4.

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Shi, M., Lu, X. & Craig, M.T. Climate change will impact the value and optimal adoption of residential rooftop solar. Nat. Clim. Chang. 14, 482–489 (2024).

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