Climate Analytics Lab

Improving climate projections with machine learning

Journal Articles

* = (co-)supervised

2024

  • Niu, R., Wu, D., Kim, K., Ma, Y.-A., Watson-Parris, D., and Yu, R.: Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling, Accepted at ICML 2024, arXiv
  • *Bouabid, S., Sejdinovic, D., and Watson-Parris, D. FaIRGP: A Bayesian Energy Balance Model for Surface Temperatures Emulation. Accepted in Journal of Advances in Modeling Earth Systems: 10.22541/essoar.169008319.96252512/v1
  • Jordan, G., Haywood, J., Malavelle, F., Chen, Y., Peace, A., Duncan, E., Partridge, D. G., Kim, P., Watson-Parris, D., Takemura, T., Neubauer, D., Myhre, G., Skeie, R., and Laakso, A.: How well are aerosol-cloud interactions represented in climate models? Part 1: Understanding the sulphate aerosol production from the 2014–15 Holuhraun eruption. Atmos. Chem. Phys., 24, 1939–1960, 10.5194/acp-24-1939-2024
  • Fiedler, S., Naik, V., O’Connor, F.M., Smith, C. J., Pincus, R., Griffiths, P., Kramer, R., 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., Myhre, G., and Forster P.M. Interactions between atmospheric composition and climate change - Progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP. Geosci. Model Dev., 17, 2387–2417, 10.5194/gmd-17-2387-2024
  • *Bouabid, S., Watson-Parris, D., Stefanovic, S., Nenes, A., Sejdinovic, D. AODisaggregation: toward global aerosol vertical profiles. Accepted at Environmental Data Science

2023

  • *Manshausen, P., Watson-Parris, D., Christensen, M. W., Jalkanen, J.-P., and Stier, P. Rapid saturation of cloud water adjustments to shipping emissions. Atmospheric Chemistry and Physics (Highlight Letter) 23, 10.5194/egusphere-2023-813
  • Regayre, L. A., Deaconu, L., Grosvenor, D. P., Sexton, D., Symonds, C. C., Langton, T., Watson-Paris, D., Mulcahy, J. P., Pringle, K. J., Richardson, M. G., Johnson, J. S., Rostron, J., Gordon, H., Lister, G., Stier, P., and Carslaw, K. S. Identifying climate model structural inconsistencies allows for tight constraint of aerosol radiative forcing. Atmospheric Chemistry and Physics, 23: 10.5194/acp-23-8749-2023
  • Yik, W., Silva, S.J., Geiss, A., Watson-Parris, D. Exploring Randomly Wired Neural Networks for Climate Model Emulation. Artificial Intelligence for the Earth Systems: 10.1175/AIES-D-22-0088.1
  • *Manshausen, P., Watson-Parris, D., Wagner, L., Maier, P., Muller, S. J., Ramminger, G., and Stier, P.: Pollution tracker: Finding industrial sources of aerosol emission in satellite imagery. Environmental Data Science, 2: 10.1017/eds.2023.20
  • *Williams, A., Watson-Parris, D., Dagan, G., Stier, P. Dependence of fast changes in global and local precipitation on the geographical location of absorbing aerosol. Journal of Climate: 10.1175/JCLI-D-23-0022.1
  • *Harder, P., Watson-Parris, D., Stier, P., Strassel, D., Gauger, N.R., Keuper, J. Physics-Informed Learning of Aerosol Microphysics. Environ. Data Sci. 1: 10.1017/eds.2022.22

2022

  • Watson-Parris, D. & Smith, C. J. Large uncertainty in future warming due to aerosol forcing. Nature Climate Change 12 (12): 10.1038/s41558-022-01516-0

  • Watson-Parris, D., Christensen, M., Laurenson, A., Clewley, D., Gryspeerdt, E., Stier, P. “Shipping regulations lead to large reduction in cloud perturbations”. PNAS 119 (41) e2206885119: https://doi.org/10.1073/pnas.2206885119

    Highlight: “Air pollution cools climate more than expected – this makes cutting carbon emissions more urgent.” The Conversation

  • *Manshausen, P., Watson-Parris, D., Christensen, M., Jalkenen, J.P., Stier, P. “Invisible Ship Tracks Show Strong Cloud Sensitivity to Aerosol”. Nature 610, 101–106: https://doi.org/10.1038/s41586-022-05122-0

    Briefing: “Finding the invisible traces of shipping in marine clouds” Nature

  • Watson-Parris, D., Rao, Y., Olivié, D., Seland, Ø., … “ClimateBench v1.0: A benchmark for data-driven climate projections”. Journal of Advances in Modeling Earth Systems 14, e2021MS002954: https://doi.org/10.1029/2021MS002954
  • Che, H., Stier, P., Watson-Parris, D., Gordon, H., Deaconu, L. “Source attribution of cloud condensation nuclei and their impact on stratocumulus clouds and radiation in the south-eastern Atlantic”. Atmospheric Chemistry and Physics 22, 10789–10807: https://doi.org/10.5194/acp-22-10789-2022
  • *Williams, A., Stier, P., Dagan. G., Watson-Parris, D. “Strong control of effective radiative forcing by the spatial pattern of absorbing aerosol”. Nature Climate Change: https://doi.org/10.1038/s41558-022-01415-4
  • Salzmann, M., …, Watson-Parris, D., …, Tegen, I. “The global atmosphere-aerosol model ICON-A-HAM2.3”. Journal of Advances in Modeling Earth Systems 14, e2021MS002699: https://doi.org/10.1029/2021MS002699
  • Whaley, C. H., Mahmood, R., Salzen, K., Winter, B., Eckhardt, S., …, Watson-Parris, D., Weiss-Gibbons, T. “Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study”. Atmospheric Chemistry and Physics: https://doi.org/10.5194/acp-22-5775-2022
  • Christensen, M., Gettelman, A., …, Watson-Parris, D., … “Opportunistic Experiments to Constrain Aerosol Effective Radiative Forcing”. Atmospheric Chemistry and Physics, 22: https://doi.org/10.5194/acp-22-641-2022

2021

  • Watson-Parris, D., Williams, A., Deaconu, L., Stier, P. “Model calibration using ESEm v1.1.0 – an open, scalable Earth System Emulator”. Geoscientific Model Development, 14: https://doi.org/10.5194/gmd-14-7659-2021
  • Christensen, M., Gettelman, A., …, Watson-Parris, D., … “Opportunistic Experiments to Constrain Aerosol Effective Radiative Forcing”. Atmospheric Chemistry and Physics, 22: https://doi.org/10.5194/acp-22-641-2022

  • Kasim, M. F., Watson-Parris, D., Deaconu, L. , Topp-Mugglestone, J. , Hatfield, P., Froula, D. H., Gregori, G., Jarvis, M. , Korenaga, J., Viezzer, E. & Vinko S. M. “Building high accuracy emulators for scientific simulations with deep neural architecture search”. Machine Learning: Science and Technology, 3: https://doi.org/10.1088/2632-2153/ac3ffa

    Highlight: “From models of galaxies to atoms, simple AI shortcuts speed up simulations by billions of times.” Science 10.1126/science.abb2769

  • Sand, M., Samset, B. H., Myhre, G., …, and Watson-Parris, D. “Aerosol absorption in global models from AeroCom Phase III”. Atmospheric Chemistry and Physics, 21: https://doi.org/10.5194/acp-21-15929-2021
  • Zhang, S., Stier, P., Watson-Parris, D. “On the Contribution of Fast and Slow Responses to Precipitation Changes Caused by Aerosol Perturbations”. Atmospheric Chemistry and Physics, 21: https://doi.org/10.5194/acp-21-10179-2021
  • Langton, T., Stier, P., Watson-Parris, D., Mulcahy, J. “Decomposing Indirect Aerosol Forcing by Global Cloud Regimes”. Geophysical Research Letters, 48: http://dx.doi.org/10.1029/2021GL093833
  • Watson-Parris, D. “Machine learning for climate and weather are worlds apart”. Phil. Trans. R. Soc. A 379: http://doi.org/10.1098/rsta.2020.0098
  • Dagan, G., Stier, P. & Watson-Parris, D. “An energetic view on the geographical dependence of the fast aerosol radiative effects on precipitation”. JGR: Atmospheres, 126: https://doi.org/10.1029/2020JD033045
  • Watson-Parris, D., Sutherland, S. A., Christensen, M. W. & Stier, P. “A large-scale analysis of pockets of open cells and their radiative impact”. Geophysical Research Letters, 48: https://doi.org/10.1029/2020GL092213

2020

  • Gettelman, A., Lamboll, R. D., Bardeen, C., Forster, P., Watson-Parris, D. “Climate Impacts of COVID-19 Induced Emission Changes”. Geophysical Research Letters, 48: https://doi.org/10.1029/2020GL091805

    Highlight: COVID-19 lockdowns temporarily raised global temperatures https://bit.ly/3p20zc8

  • Brown, H, Liu, X., …, Watson-Paris, D., …, Chand, D. “Biomass burning aerosols in most climate models are too absorbing”. Nature Communications: https://doi.org/10.1038/s41467-020-20482-9
  • Dagan, G., Stier, P. & Watson-Parris, D. “Aerosol forcing masks and delays the formation of the North-Atlantic warming hole by three decades”. Geophysical Research Letters, 47: https://doi.org/10.1029/2020GL090778
  • Haywood, J. M., Abel, S., … Watson-Parris, D., … Zuidema, P. “Overview: The CLoud-Aerosol-Radiation Interaction and Forcing: Year-2017 (CLARIFY-2017) measurement campaign”. Atmos. Chem. Phys.: https://acp.copernicus.org/preprints/acp-2020-729/
  • Che, H., Stier, P., Gordon, H., Watson-Parris, D. & Deaconu, L. “The significant role of biomass burning aerosols in clouds and radiation in the South-eastern Atlantic Ocean”, Atmos. Chem. Phys..: https://doi.org/10.5194/acp-2020-532
  • McCoy, I. L., McCoy, D. T., Wood, R., Regayre, L., Watson- Parris, D., Grosvenor, D. P., Mulcahy, J., Hu, Y., Bender, F. A. M., Field, P. R., Carslaw, K., Gordon, H. “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. F., Watson-Parris, D. & Olivie, D. “Assessing California wintertime precipitation responses to various climate drivers”. Journal of Geophysical Research: Atmospheres, 125: https://doi.org/10.1029/2019JD031736
  • Watson-Parris, D., Bellouin, N., Deaconu, L., Schutgens, N., Yoshioka, M., Regayre, L. A., Pringle, K. J., Johnson, J. S., Carslaw, K. S. & Stier, P. “Constraining uncertainty in aerosol direct forcing”. Geophysical Research Letters, 47: https://doi.org/10.1029/2020GL087141
  • Wood, T., Maycock, A. C., Forster, P. M., Richardson T. B., …. Watson-Parris, D. “The Southern hemisphere midlatitude circulation response to rapid adjustments and sea surface temperature driven feedbacks” Journal of Climate 1-53: https://doi.org/10.1175/JCLI-D-19-1015.1

2019

  • Richardson, T. B., Forster, P. M., Smith, C. J., Maycock, A. C., Wood, T., Andrews, T., Boucher, ..., Mülmenstädt, J., Myhre, G., Olivié, D., Portmann, R. W., Samset, B. H., … Watson-Parris, D. “Efficacy of Climate Forcings in PDRMIP Models”. Journal of Geophysical Research: Atmospheres, 124, 12824– 12844: https://doi.org/10.1029/2019JD030581

    Editors’ Highlight: “How Does Climate Respond to Different Forcings?” https://eos.org/editor-highlights/how-does-climate-respond-to-different-forcings

  • Hodnebrog, O., Myhre, G., Samset, B. H., Alterskjær, K., Andrews, T., Boucher, O., Faluvegi, G., Fläschner, D., M Forster, P., …, Watson-Parris, D. “Water vapour adjustments and responses differ between climate drivers”. Atmospheric Chemistry and Physics, 19(20): https://doi.org/10.5194/acp-19-12887-2019
  • Tegen, I., Neubauer, D., Ferrachat, S., Drian, C. S.-L., Bey, I., Schutgens, N., Stier, P., Watson-Parris, D., Stanelle, T., ..., Heinold, B., & Lohmann, U. “The global aerosol-climate model ECHAM6.3–HAM2.3 Part 1: Aerosol evaluation”. Geoscientific Model Development, 12(4): https://doi.org/10.5194/gmd-12-3609-2019
  • Watson-Parris, D., Schutgens, N., Reddington, C., Pringle, K. J., Liu, D., Allan, J. D., Coe, H., Carslaw, K. S., & Stier, P. “In situ constraints on the vertical distribution of global aerosol”. Atmospheric Chemistry and Physics, 19(18): https://doi.org/10.5194/acp-19-11765-2019
  • Dagan, G., Stier, P., & Watson-Parris, D. “Contrasting Response of Precipitation to Aerosol Perturbation in the Tropics and Extratropics Explained by Energy Budget Considerations”. Geophysical Research Letters, 46(13): https://doi.org/10.1029/2019GL083479
  • Dagan, G., Stier, P., & Watson-Parris, D. “Analysis of the Atmospheric Water Budget for Elucidating the Spatial Scale of Precipitation Changes Under Climate Change”. Geophysical Research Letters, 46(17–18): https://doi.org/10.1029/2019GL084173

  • Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson‐Parris, D., …, Stevens, B. “Bounding global aerosol radiative forcing of climate change”. Reviews of Geophysics, 2019RG000660: https://doi.org/10.1029/2019RG000660

    Editors’ Highlight: “Effects of Particles on Climate Remain Unsettled” https://eos.org/editor-highlights/effects-of-particles-on-climate-remain-unsettled

  • Heikenfeld, M., Marinescu, P. J., Christensen, M., Watson-Parris, D., Senf, F., Van Den Heever, S. C., & Stier, P. (2019). “Tobac 1.2: Towards a flexible framework for tracking and analysis of clouds in diverse datasets”. Geoscientific Model Development, 12(11): https://doi.org/10.5194/gmd-12-4551-2019
  • Fanourgakis, G. S., Kanakidou, M., Nenes, A., Bauer, S. E., Bergman, T., Carslaw, K. S., Grini, A., Hamilton, D. S., Johnson, J. S., Karydis, V. A., Kirkeväg, A., …, Watson-Parris, D., …, Yu, F. “Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation”. Atmospheric Chemistry and Physics, 19(13): https://doi.org/10.5194/acp-19-8591-2019

2018

  • Myhre, G., Kramer, R. J., Smith, C. J., Hodnebrog, Ø., Forster, P., Soden, B. J., Samset, B. H., Stjern, C. W., Andrews, T., Boucher, O., Faluvegi, G., Fläschner, D., Kasoar, M., Kirkevåg, A., Lamarque, J.-F., Olivié, D., … Watson-Parris, D. “Quantifying the Importance of Rapid Adjustments for Global Precipitation Changes”. Geophysical Research Letters, 45(20): https://doi.org/10.1029/2018GL079474
  • Watson-Parris, D., Schutgens, N., Winker, D., Burton, S. P., Ferrare, R. A., & Stier, P. “On the Limits of CALIOP for Constraining Modeled Free Tropospheric Aerosol”. Geophysical Research Letters, 45(17): https://doi.org/10.1029/2018GL078195
  • Smith, C. J., Kramer, R. J., Myhre, G., Forster, P. M., Soden, B. J., Andrews, T., Boucher, O., Faluvegi, G., Fläschner, D., Hodnebrog, Ø., Kasoar, M., Kharin, V., Kirkevåg, A., Lamarque, J.-F., Mülmenstädt, J., Olivié, D., Richardson, T., Samset, D., … Watson-Parris, D. “Understanding Rapid Adjustments to Diverse Forcing Agents”. Geophysical Research Letters, 45(21): https://doi.org/10.1029/2018GL079826
  • Lund, M. T., Samset, B. H., Skeie, R. B., Watson-Parris, D., Katich, J. M., Schwarz, J. P., & Weinzierl, B. “Short Black Carbon lifetime inferred from a global set of aircraft observations”. Npj Climate and Atmospheric Science, 1(1), 31: https://doi.org/10.1038/s41612-018-0040-x

2016

  • Watson-Parris, D., Schutgens, N., Cook, N., Kipling, Z., Kershaw, P., Gryspeerdt, E., Lawrence, B., & Stier, P. “Community Intercomparison Suite (CIS) v1.4.0: A tool for intercomparing models and observations”. Geoscientific Model Development, 9(9): https://doi.org/10.5194/gmd-9-3093-2016

2013

  • Badcock, T. J., Hammersley, S., Watson-Parris, D., Dawson, P., ..., McAleese, C., Oliver, R. A., & Humphreys, C. J. (2013). “Carrier density dependent localization and consequences for efficiency droop in InGaN/GaN quantum well structures”. Japanese Journal of Applied Physics, 52(8 PART 2): https://iopscience.iop.org/article/10.7567/JJAP.52.08JK10

2012

  • Hammersley, S., Watson-Parris, D., Dawson, P, ..., McAleese, C., Oliver, R. A., & Humphreys, C. J. (2012). “The consequences of high injected carrier densities on carrier localization and efficiency droop in InGaN/GaN quantum well structures”. Journal of Applied Physics, 111(8): https://doi.org/10.1063/1.3703062

2011

  • Watson-Parris, D., Godfrey, M. J., Dawson, P., Oliver, R. A., Galtrey, M. J., Kappers, M. J., & Humphreys, C. J. (2011). “Carrier localization mechanisms in InxGa1-xN/GaN quantum wells”. Physical Review B, 83(11): https://doi.org/10.1103/PhysRevB.83.115321
  • Hammersley, S., Badcock, T. J., Watson-Parris, D., Godfrey, M. J., Dawson, P., Kappers, M. J., & Humphreys, C. J. (2011). “Study of efficiency droop and carrier localisation in an InGaN/GaN quantum well structure”. Physica Status Solidi (C), 8, 2194-2196: https://doi.org/10.1002/pssc.201001001

2010

  • Watson-Parris, D., Godfrey, M. J., Oliver, R. A., Dawson, P., Galtrey, M. J., Kappers, M. J., & Humphreys, C. J. (2010). “Energy landscape and carrier wave-functions in InGaN/GaN quantum wells”. Physica Status Solidi (C), 7, 2255–2258: https://doi.org/10.1002/pssc.200983516

    Highlight: Chosen for the cover page of special issue

Conference Papers

2022

  • Tazi, K., Salas-Porras, E. D., Braude, A., Okoh, D., Lamb, K. D., Watson-Parris, D., Harder, P., Meinert, N. “Pyrocast: A Machine Learning Pipeline to Forecast Pyrocumulonimbus (PyroCb) clouds” Climate Change AI workshop at NeurIPS 2022: https://arxiv.org/abs/2211.13052
  • Salas-Porras, E. D., Tazi, K., Braude, A., Okoh, D., Lamb, K. D., Watson-Parris, D., Harder, P., Meinert, N. “Identifying causes of Pyrocumulonimbus (PyroCb)” Causal Machine Learning for Real-World Impact Workshop at NeurIPS 2022: https://arxiv.org/abs/2211.08883

2021

  • Jesson, A., Manshausen, P., Douglas, A., Watson-Parris, D., Gal, Y., Stier, P. “Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific” Climate Change AI workshop at NeurIPS 2021: https://arxiv.org/abs/2110.15084
  • Harder, P., Watson-Parris, D., Strassel, D., Gauger, N., Stier, P., Keuper, J. “Emulating Aerosol Microphysics with Machine Learning” Tackling Climate Change with Machine Learning Workshop at ICML 2021: https://arxiv.org/abs/2109.10593
  • Schroeder de Witt, C., Tong, C., Zantedeschi, V., Martini D., Kalaitzis, A., Chantry, M., Watson-Parris, D., Bilinski, P. “RainBench: Towards Data-Driven Global Precipitation Forecasting from Satellite Imagery” Thirty-Fifth AAAI Conference on Artificial Intelligence: https://ojs.aaai.org/index.php/AAAI/article/view/17749

2020

  • Tong, C., Schroeder de Witt, C. A., Zantedeschi, V., Martini, D., Kalaitzis, A., Chantry, M ., Watson-Parris, D., Bilinski, P. “RainBench: Enabling Data-Driven Precipitation Forecasting on a Global Scale” Tackling Climate Change with Machine Learning workship at NeurIPS 2020

    Highlight: Spotlight talk

  • Zantedeschi, V., Martini, D., Tong, C., Schroeder de Witt, C. A., Bilinski, P., Kalaitzis, A., Chantry, M ., Watson-Parris, D. “Towards Data-Driven Physics-Informed Global Precipitation Forecasting From Satellite Imagery” AI for Earth Sciences workshop at NeurIPS 2020: https://ai4earthscience.github.io/neurips-2020-workshop/papers/ai4earth_neurips_2020_20.pdf

    Highlight: Spotlight talk

  • Harder, P., Jones, W., Lguensat, R., Bouabid, S., Fulton, J., Quesada-Chacón, D., Marcolongo, A., Stefanović, S., Rao, Y., Manshausen, P. & Watson-Parris, D. “NightVision: Generating Nighttime Satellite Imagery from Infra-Red Observations” Tackling Climate Change with Machine Learning workship at NeurIPS 2020: https://arxiv.org/abs/2011.07017

2019

  • Zantedeschi, V., Falasca, F., Douglas, A., Strange, R., Kusner, M. J., Watson-Parris, D. “Cumulo: A Dataset for Learning Cloud Classes” Climate Change AI workshop at NeurIPS 2019, Vancouver, Canada: https://arxiv.org/abs/1911.04227

    Highlight: Chosen for ‘best paper’ award

  • Watson-Parris, D., Sutherland, S., Christensen, M., Caterini, A., Sejdinovic, D., Stier, P. “Detecting anthropogenic cloud perturbations with deep learning” Climate Change: How Can AI Help? workshop at ICML 2019, Long Beach, California: https://arxiv.org/abs/1911.13061

    Highlight: Chosen for ‘best paper’ award

Book Contributions

  • Allan, J. and Watson-Parris, D. “Measurements of Ambient Aerosol Properties” in Aerosols and Climate, by Ken Carslaw. Elsevier (in press)
  • Contributed to “Modelling of short-lived climate forcers” in AMAP 2021 Assessment: Arctic climate, air quality, and health impacts from short-lived climate forcers (in press)