Models; Emergent_constraints; Impacts; Climate Change; Projections; Uncertainty; Temperature; Precipitation
Touma Danielle, Stevenson Samantha, Lehner Flavio, Coats Sloan (2021), Human-driven greenhouse gas and aerosol emissions cause distinct regional impacts on extreme fire weather, in Nature Communications
, 12(1), 212-212.
Ciavarella Andrew, Cotterill Daniel, Stott Peter, Kew Sarah, Philip Sjoukje, van Oldenborgh Geert Jan, Skålevåg Amalie, Lorenz Philip, Robin Yoann, Otto Friederike, Hauser Mathias, Seneviratne Sonia I., Lehner Flavio, Zolina Olga (2021), Prolonged Siberian heat of 2020 almost impossible without human influence, in Climatic Change
, 166(1-2), 9-9.
van Oldenborgh Geert Jan, Krikken Folmer, Lewis Sophie, Leach Nicholas J., Lehner Flavio, Saunders Kate R., van Weele Michiel, Haustein Karsten, Li Sihan, Wallom David, Sparrow Sarah, Arrighi Julie, Singh Roop K., van Aalst Maarten K., Philip Sjoukje Y., Vautard Robert, Otto Friederike E. L. (2021), Attribution of the Australian bushfire risk to anthropogenic climate change, in Natural Hazards and Earth System Sciences
, 21(3), 941-960.
Bonan David B., Lehner Flavio, Holland Marika M. (2021), Partitioning uncertainty in projections of Arctic sea ice, in Environmental Research Letters
Brunner Lukas, Pendergrass Angeline G., Lehner Flavio, Merrifield Anna L., Lorenz Ruth, Knutti Reto (2020), Reduced global warming from CMIP6 projections when weighting models by performance and independence, in Earth System Dynamics
, 11(4), 995-1012.
Mankin Justin S., Lehner Flavio, Coats Sloan, McKinnon Karen A. (2020), The Value of Initial Condition Large Ensembles to Robust Adaptation Decision‐Making, in Earth's Future
, 8(10), e2012EF001.
Papalexiou Simon Michael, Rajulapati Chandra Rupa, Clark Martyn P., Lehner Flavio (2020), Robustness of CMIP6 Historical Global Mean Temperature Simulations: Trends, Long‐Term Persistence, Autocorrelation, and Distributional Shape, in Earth's Future
, 8(10), e2020EF001.
Tokarska Katarzyna B, Arora Vivek K, Gillett Nathan P, Lehner Flavio, Rogelj Joeri, Schleussner Carl-Friedrich, Séférian Roland, Knutti Reto (2020), Uncertainty in carbon budget estimates due to internal climate variability, in Environmental Research Letters
, 15(10), 104064-104064.
Lehner Flavio, Deser Clara, Maher Nicola, Marotzke Jochem, Fischer Erich M., Brunner Lukas, Knutti Reto, Hawkins Ed (2020), Partitioning climate projection uncertainty with multiple large ensembles and CMIP5/6, in Earth System Dynamics
, 11(2), 491-508.
Maher Nicola, Lehner Flavio, Marotzke Jochem (2020), Quantifying the role of internal variability in the temperature we expect to observe in the coming decades, in Environmental Research Letters
, 15(5), 054014-054014.
Tokarska Katarzyna B., Stolpe Martin B., Sippel Sebastian, Fischer Erich M., Smith Christopher J., Lehner Flavio, Knutti Reto (2020), Past warming trend constrains future warming in CMIP6 models, in Science Advances
, 6(12), eaaz9549-eaaz9549.
KrikkenFolmer, LehnerFlavio, HausteinKarsten, DrobyshevIgor, van OldenborghGeert Jan, Attribution of the role of climate change in the forest fires in Sweden 2018, in Natural Hazards and Earth System Sciences
SimpsonIsla, McKinnonKaren, DavenportFrances, TingleyMartin, LehnerFlavio, Al FahadAbdullah, ChenDi, Emergent constraints on the large scale atmospheric circulation and regional hydroclimate: do they still work in CMIP6 and how much can they actually constrain the future?, in Journal of Climate
Future projections of regional climate change are still very uncertain. This is particularly true for the mid-term projection period (2030s-2050s), where initial condition predictability is lost and emissions scenarios have yet to drive divergence of climate trajectories. In current ensembles of coupled climate models ~50% of the model projection uncertainty for mid-latitude land warming for this period is related to internal variability and regional feedbacks, rather than to transient climate response or the choice of emissions scenario; the contribution from internal variability is even larger for precipitation. In order to inform stakeholders on climate impact risks associated with this crucial planning horizon, an improved understanding of these sources of uncertainty is needed. This proposal combines new methodologies and innovative model simulations with the ultimate goal of reducing uncertainties in regional temperature and precipitation projections. We will investigate current and upcoming multi-model ensembles, as well as idealized model experiments with the following objectives: (i) quantifying sources of spread in mid-term projections of temperature and precipitation over mid-latitude land areas, (ii) removing the contribution of atmospheric circulation variability to this spread and identifying thermodynamic drivers of the remaining projection uncertainty, and (iii) observationally constraining the remaining uncertainty, thereby focusing on land surface-atmosphere interactions driven by soil moisture and surface fluxes, the influence of model biases in sea surface temperature variability on projected hydroclimate changes, and the link between precipitation changes and the magnitude of projected land-sea warming contrast. This project will result in an improved understanding of the origin of inter-model spread in climate change projections and improved estimates of regional anthropogenic climate change, and therefore a more reliable quantification of risk associated with changes in mean climate as well as its variability.