9129767 Y3BW4YZW 1 apa 50 date desc year Watson-Parris, D. 18 https://dwatsonparris.scrippsprofiles.ucsd.edu/wp-content/plugins/zotpress/
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Watson‐Parris, D. (2025). Integrating Top‐Down Energetic Constraints With Bottom‐Up Process‐Based Constraints for More Accurate Projections of Future Warming. Geophysical Research Letters, 52(8), e2024GL114269. https://doi.org/10.1029/2024GL114269
Watson-Parris, D., Wilcox, L. J., Stjern, C. W., Allen, R. J., Persad, G., Bollasina, M. A., Ekman, A. M. L., Iles, C. E., Joshi, M., Lund, M. T., McCoy, D., Westervelt, D. M., Williams, A. I. L., & Samset, B. H. (2025). Surface temperature effects of recent reductions in shipping SO2 emissions are within internal variability. Atmospheric Chemistry and Physics, 25(8), 4443–4454. https://doi.org/10.5194/acp-25-4443-2025
Baño-Medina, J., Sengupta, A., Doyle, J. D., Reynolds, C. A., Watson-Parris, D., & Monache, L. D. (2025). Are AI weather models learning atmospheric physics? A sensitivity analysis of cyclone Xynthia. Npj Climate and Atmospheric Science, 8(1), 92. https://doi.org/10.1038/s41612-025-00949-6
Nowack, P., & Watson-Parris, D. (2025). Opinion: Why all emergent constraints are wrong but some are useful – a machine learning perspective. Atmospheric Chemistry and Physics, 25(4), 2365–2384. https://doi.org/10.5194/acp-25-2365-2025
Petrenko, M., Kahn, R., Chin, M., Bauer, S. E., Bergman, T., Bian, H., Curci, G., Johnson, B., Kaiser, J. W., Kipling, Z., Kokkola, H., Liu, X., Mezuman, K., Mielonen, T., Myhre, G., Pan, X., Protonotariou, A., Remy, S., Skeie, R. B., … Zhang, K. (2025). Biomass burning emission analysis based on MODIS aerosol optical depth and AeroCom multi-model simulations: implications for model constraints and emission inventories. Atmospheric Chemistry and Physics, 25(3), 1545–1567. https://doi.org/10.5194/acp-25-1545-2025
Russo, M. R., Bartholomew, S. L., Hassell, D., Mason, A. M., Neininger, E., Perman, A. J., Sproson, D. A. J., Watson-Parris, D., & Abraham, N. L. (2025). Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator). Geoscientific Model Development, 18(1), 181–191. https://doi.org/10.5194/gmd-18-181-2025
Myhre, G., Samset, B. H., Stjern, C. W., Hodnebrog, Ø., Kramer, R., Smith, C., Andrews, T., Boucher, O., Faluvegi, G., Forster, P. M., Iversen, T., Kirkevåg, A., Olivié, D., Shindell, D., Stier, P., & Watson-Parris, D. (2025). The warming effect of black carbon must be reassessed in light of observational constraints. Cell Reports Sustainability, 2(9), 100428. https://doi.org/10.1016/j.crsus.2025.100428
Lütjens, B., Ferrari, R., Watson‐Parris, D., & Selin, N. E. (2025). The Impact of Internal Variability on Benchmarking Deep Learning Climate Emulators. Journal of Advances in Modeling Earth Systems, 17(8), e2024MS004619. https://doi.org/10.1029/2024MS004619
Baño‐Medina, J., Sengupta, A., Watson‐Parris, D., Hu, W., & Delle Monache, L. (2025). Toward Calibrated Ensembles of Neural Weather Model Forecasts. Journal of Advances in Modeling Earth Systems, 17(4), e2024MS004734. https://doi.org/10.1029/2024MS004734
Toll, V., Rahu, J., Keernik, H., Trofimov, H., Voormansik, T., Manshausen, P., Hung, E., Michelson, D., Christensen, M. W., Post, P., Junninen, H., Murray, B. J., Lohmann, U., Watson-Parris, D., Stier, P., Donaldson, N., Storelvmo, T., Kulmala, M., & Bellouin, N. (2024). Glaciation of liquid clouds, snowfall, and reduced cloud cover at industrial aerosol hot spots. Science, 386(6723), 756–762. https://doi.org/10.1126/science.adl0303
Eidhammer, T., Gettelman, A., Thayer-Calder, K., Watson-Parris, D., Elsaesser, G., Morrison, H., Van Lier-Walqui, M., Song, C., & McCoy, D. (2024). An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6. Geoscientific Model Development, 17(21), 7835–7853. https://doi.org/10.5194/gmd-17-7835-2024
Song, C., McCoy, D. T., Eidhammer, T., Gettelman, A., McCoy, I. L., Watson‐Parris, D., Wall, C. J., Elsaesser, G., & Wood, R. (2024). Buffering of Aerosol‐Cloud Adjustments by Coupling Between Radiative Susceptibility and Precipitation Efficiency. Geophysical Research Letters, 51(11), e2024GL108663. https://doi.org/10.1029/2024GL108663
Fiedler, S., Naik, V., O’Connor, F. M., Smith, C. J., Griffiths, P., Kramer, R. J., Takemura, T., Allen, R. J., Im, U., Kasoar, M., Modak, A., Turnock, S., Voulgarakis, A., Watson-Parris, D., Westervelt, D. M., Wilcox, L. J., Zhao, A., Collins, W. J., Schulz, M., … Forster, P. M. (2024). Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP. Geoscientific Model Development, 17(6), 2387–2417. https://doi.org/10.5194/gmd-17-2387-2024
Jordan, G., Malavelle, F., Chen, Y., Peace, A., Duncan, E., Partridge, D. G., Kim, P., Watson-Parris, D., Takemura, T., Neubauer, D., Myhre, G., Skeie, R., Laakso, A., & Haywood, J. (2024). How well are aerosol–cloud interactions represented in climate models? – Part 1: Understanding the sulfate aerosol production from the 2014–15 Holuhraun eruption. Atmospheric Chemistry and Physics, 24(3), 1939–1960. https://doi.org/10.5194/acp-24-1939-2024
Bouabid, S., Sejdinovic, D., & Watson‐Parris, D. (2024). FaIRGP: A Bayesian Energy Balance Model for Surface Temperatures Emulation. Journal of Advances in Modeling Earth Systems, 16(6), e2023MS003926. https://doi.org/10.1029/2023MS003926
Bouabid, S., Watson-Parris, D., Stefanović, S., Nenes, A., & Sejdinovic, D. (2024). Aerosol optical depth disaggregation: toward global aerosol vertical profiles. Environmental Data Science, 3, e16. https://doi.org/10.1017/eds.2024.15
Manshausen, P., Watson-Parris, D., Christensen, M. W., Jalkanen, J.-P., & Stier, P. (2023). Rapid saturation of cloud water adjustments to shipping emissions. Atmospheric Chemistry and Physics, 23(19), 12545–12555. https://doi.org/10.5194/acp-23-12545-2023
Williams, A. I. L., Watson-Parris, D., Dagan, G., & Stier, P. (2023). Dependence of Fast Changes in Global and Local Precipitation on the Geographical Location of Absorbing Aerosol. Journal of Climate, 36(18), 6163–6176. https://doi.org/10.1175/JCLI-D-23-0022.1
Regayre, L. A., Deaconu, L., Grosvenor, D. P., Sexton, D. M. H., Symonds, C., Langton, T., Watson-Paris, D., Mulcahy, J. P., Pringle, K. J., Richardson, M., Johnson, J. S., Rostron, J. W., Gordon, H., Lister, G., Stier, P., & Carslaw, K. S. (2023). Identifying climate model structural inconsistencies allows for tight constraint of aerosol radiative forcing. Atmospheric Chemistry and Physics, 23(15), 8749–8768. https://doi.org/10.5194/acp-23-8749-2023
Manshausen, P., Watson-Parris, D., Wagner, L., Maier, P., Muller, S. J., Ramminger, G., & Stier, P. (2023). Pollution tracker: Finding industrial sources of aerosol emission in satellite imagery. Environmental Data Science, 2, e21. https://doi.org/10.1017/eds.2023.20
Regayre, L. A., Deaconu, L., Grosvenor, D. P., Sexton, D., Symonds, C. C., Langton, T., Watson-Parris, D., Mulcahy, J. P., Pringle, K. J., Richardson, M., Johnson, J. S., Rostron, J., Gordon, H., Lister, G., Stier, P., & Carslaw, K. S. (2022). Identifying climate model structural inconsistencies allows for tight constraint of aerosol radiative forcing [Preprint]. https://doi.org/10.5194/egusphere-2022-1330
Watson-Parris, D., Christensen, M. W., Laurenson, A., Clewley, D., Gryspeerdt, E., & Stier, P. (2022). Shipping regulations lead to large reduction in cloud perturbations. Proceedings of the National Academy of Sciences, 119(41), e2206885119. https://doi.org/10.1073/pnas.2206885119
Manshausen, P., Watson-Parris, D., Christensen, M. W., Jalkanen, J.-P., & Stier, P. (2022). Invisible ship tracks show large cloud sensitivity to aerosol. Nature, 610(7930), 101–106. https://doi.org/10.1038/s41586-022-05122-0
Che, H., Stier, P., Watson-Parris, D., Gordon, H., & Deaconu, L. (2022). Source attribution of cloud condensation nuclei and their impact on stratocumulus clouds and radiation in the south-eastern Atlantic. Atmospheric Chemistry and Physics, 22(16), 10789–10807. https://doi.org/10.5194/acp-22-10789-2022
Whaley, C. H., Mahmood, R., von Salzen, K., Winter, B., Eckhardt, S., Arnold, S., Beagley, S., Becagli, S., Chien, R.-Y., Christensen, J., Damani, S. M., Dong, X., Eleftheriadis, K., Evangeliou, N., Faluvegi, G., Flanner, M., Fu, J. S., Gauss, M., Giardi, F., … Weiss-Gibbons, T. (2022). Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study. Atmospheric Chemistry and Physics, 22(9), 5775–5828. https://doi.org/10.5194/acp-22-5775-2022
Kasim, M. F., Watson-Parris, D., Deaconu, L., Oliver, S., Hatfield, P., Froula, D. H., Gregori, G., Jarvis, M., Khatiwala, S., Korenaga, J., Topp-Mugglestone, J., Viezzer, E., & Vinko, S. M. (2022). Building high accuracy emulators for scientific simulations with deep neural architecture search. Machine Learning: Science and Technology, 3(1), 015013. https://doi.org/10.1088/2632-2153/ac3ffa
Christensen, M. W., Gettelman, A., Cermak, J., Dagan, G., Diamond, M., Douglas, A., Feingold, G., Glassmeier, F., Goren, T., Grosvenor, D. P., Gryspeerdt, E., Kahn, R., Li, Z., Ma, P.-L., Malavelle, F., McCoy, I. L., McCoy, D. T., McFarquhar, G., Mülmenstädt, J., … Yuan, T. (2022). Opportunistic experiments to constrain aerosol effective radiative forcing. Atmospheric Chemistry and Physics, 22(1), 641–674. https://doi.org/10.5194/acp-22-641-2022
Watson-Parris, D., & Smith, C. J. (2022). Large uncertainty in future warming due to aerosol forcing. Nature Climate Change, 12(12), 1111–1113. https://doi.org/10.1038/s41558-022-01516-0
Watson-Parris, D., Rao, Y., Olivié, D., Seland, Ø., Nowack, P., Camps‐Valls, G., Stier, P., Bouabid, S., Dewey, M., Fons, E., Gonzalez, J., Harder, P., Jeggle, K., Lenhardt, J., Manshausen, P., Novitasari, M., Ricard, L., & Roesch, C. (2022). ClimateBench v1.0: A Benchmark for Data‐Driven Climate Projections. Journal of Advances in Modeling Earth Systems, 14(10). https://doi.org/10.1029/2021MS002954
Williams, A. I. L., Stier, P., Dagan, G., & Watson-Parris, D. (2022). Strong control of effective radiative forcing by the spatial pattern of absorbing aerosol. Nature Climate Change, 12(8), 735–742. https://doi.org/10.1038/s41558-022-01415-4
Salzmann, M., Ferrachat, S., Tully, C., Münch, S., Watson-Parris, D., Neubauer, D., Siegenthaler‐Le Drian, C., Rast, S., Heinold, B., Crueger, T., Brokopf, R., Mülmenstädt, J., Quaas, J., Wan, H., Zhang, K., Lohmann, U., Stier, P., & Tegen, I. (2022). The Global Atmosphere‐Aerosol Model ICON‐A‐HAM2.3–Initial Model Evaluation and Effects of Radiation Balance Tuning on Aerosol Optical Thickness. Journal of Advances in Modeling Earth Systems, 14(4). https://doi.org/10.1029/2021MS002699
Watson-Parris, D., Williams, A., Deaconu, L., & Stier, P. (2021). Model calibration using ESEm v1.1.0 – an open, scalable Earth system emulator. Geoscientific Model Development, 14(12), 7659–7672. https://doi.org/10.5194/gmd-14-7659-2021
Sand, M., Samset, B. H., Myhre, G., Gliß, J., Bauer, S. E., Bian, H., Chin, M., Checa-Garcia, R., Ginoux, P., Kipling, Z., Kirkevåg, A., Kokkola, H., Le Sager, P., Lund, M. T., Matsui, H., van Noije, T., Olivié, D. J. L., Remy, S., Schulz, M., … Watson-Parris, D. (2021). Aerosol absorption in global models from AeroCom phase III. Atmospheric Chemistry and Physics, 21(20), 15929–15947. https://doi.org/10.5194/acp-21-15929-2021
Langton, T., Stier, P., Watson-Parris, D., & Mulcahy, J. P. (2021). Decomposing Effective Radiative Forcing Due to Aerosol Cloud Interactions by Global Cloud Regimes. Geophysical Research Letters, 48(18). https://doi.org/10.1029/2021GL093833
Zhang, S., Stier, P., & Watson-Parris, D. (2021). On the contribution of fast and slow responses to precipitation changes caused by aerosol perturbations. Atmospheric Chemistry and Physics, 21(13), 10179–10197. https://doi.org/10.5194/acp-21-10179-2021
Dagan, G., Stier, P., & Watson-Parris, D. (2021). An Energetic View on the Geographical Dependence of the Fast Aerosol Radiative Effects on Precipitation. Journal of Geophysical Research: Atmospheres, 126(9). https://doi.org/10.1029/2020JD033045
Watson-Parris, D. (2021). Machine learning for weather and climate are worlds apart. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 379(2194), 20200098. https://doi.org/10.1098/rsta.2020.0098
Watson-Parris, D., Sutherland, S. A., Christensen, M. W., Eastman, R., & Stier, P. (2021). A Large‐Scale Analysis of Pockets of Open Cells and Their Radiative Impact. Geophysical Research Letters, 48(6). https://doi.org/10.1029/2020GL092213
Gettelman, A., Lamboll, R., Bardeen, C. G., Forster, P. M., & Watson-Parris, D. (2021). Climate Impacts of COVID‐19 Induced Emission Changes. Geophysical Research Letters, 48(3). https://doi.org/10.1029/2020GL091805
Haywood, J. M., Abel, S. J., Barrett, P. A., Bellouin, N., Blyth, A., Bower, K. N., Brooks, M., Carslaw, K., Che, H., Coe, H., Cotterell, M. I., Crawford, I., Cui, Z., Davies, N., Dingley, B., Field, P., Formenti, P., Gordon, H., de Graaf, M., … Zuidema, P. (2021). The CLoud–Aerosol–Radiation Interaction and Forcing: Year 2017 (CLARIFY-2017) measurement campaign. Atmospheric Chemistry and Physics, 21(2), 1049–1084. https://doi.org/10.5194/acp-21-1049-2021
Brown, H., Liu, X., Pokhrel, R., Murphy, S., Lu, Z., Saleh, R., Mielonen, T., Kokkola, H., Bergman, T., Myhre, G., Skeie, R. B., Watson-Parris, D., Stier, P., Johnson, B., Bellouin, N., Schulz, M., Vakkari, V., Beukes, J. P., van Zyl, P. G., … Chand, D. (2021). Biomass burning aerosols in most climate models are too absorbing. Nature Communications, 12(1), 277. https://doi.org/10.1038/s41467-020-20482-9
Dagan, G., Stier, P., & Watson-Parris, D. (2020). Aerosol Forcing Masks and Delays the Formation of the North Atlantic Warming Hole by Three Decades. Geophysical Research Letters, 47(22). https://doi.org/10.1029/2020GL090778
Wood, T., Maycock, A. C., Forster, P. M., Richardson, T. B., Andrews, T., Boucher, O., Myhre, G., Samset, B. H., Kirkevåg, A., Lamarque, J.-F., Mülmenstädt, J., Olivié, D., Takemura, T., & Watson-Parris, D. (2020). The Southern Hemisphere Midlatitude Circulation Response to Rapid Adjustments and Sea Surface Temperature Driven Feedbacks. Journal of Climate, 33(22), 9673–9690. https://doi.org/10.1175/JCLI-D-19-1015.1
McCoy, I. L., McCoy, D. T., Wood, R., Regayre, L., Watson-Parris, D., Grosvenor, D. P., Mulcahy, J. P., Hu, Y., Bender, F. A.-M., Field, P. R., Carslaw, K. S., & Gordon, H. (2020). The hemispheric contrast in cloud microphysical properties constrains aerosol forcing. Proceedings of the National Academy of Sciences, 117(32), 18998–19006. https://doi.org/10.1073/pnas.1922502117
Allen, R. J., Lamarque, J., Watson-Parris, D., & Olivié, D. (2020). Assessing California Wintertime Precipitation Responses to Various Climate Drivers. Journal of Geophysical Research: Atmospheres, 125(12). https://doi.org/10.1029/2019JD031736
Che, H., Stier, P., Gordon, H., Watson-Parris, D., & Deaconu, L. (2020). The significant role of biomass burning aerosols in clouds andradiation in the South-eastern Atlantic Ocean [Preprint]. Clouds and Precipitation/Atmospheric Modelling/Troposphere/Physics (physical properties and processes). https://doi.org/10.5194/acp-2020-532