Blar i NORCE vitenarkiv på forfatter "Knutti, Reto"

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    • Climate Scenarios for Switzerland CH2018 – Approach and Implications 

      Fischer, Andreas M.; Strassmann, Kuno M.; Croci-Maspoli, Mischa; Hama, Michiko; Knutti, Reto; Kotlarski, Sven; Schär, Christoph; Schnadt Poberaj, Christina; Ban, Nikolina; Bavay, Mathias; Beyerle, Urs; Bresch, David N.; Brönnimann, Stefan; Burlando, P.; Casanueva, Ana; Fatichi, Simone; Feigenwinter, Iris; Fischer, Erich M.; Hirschi, Martin; Liniger, Mark A.; Marty, Christoph; Medhaug, Iselin; Peleg, Nadav; Pickl, M.; Raible, Christoph C.; Rajczak, Jan; Rössler, O.; Scherrer, Simon C.; Schwierz, Cornelia; Seneviratne, Sonia I.; Skelton, Maurice; Sørland, Silje Lund; Spirig, Curdin; Tschurr, F.; Zeder, Joel; Zubler, Elias M. (Peer reviewed; Journal article, 2022)
      To make sound decisions in the face of climate change, government agencies, policymakers and private stakeholders require suitable climate information on local to regional scales. In Switzerland, the development of climate ...

    • ESD Reviews: Climate feedbacks in the Earth system and prospects for their evaluation 

      Heinze, Christoph; Eyring, Veronika; Friedlingstein, Pierre; Jones, Colin; Balkanski, Yves; Collins, William; Fichefet, Thierry; Gao, Shuang; Hall, Alex; Ivanova, Detelina; Knorr, Wolfgang; Knutti, Reto; Löw, Alexander; Ponater, Michael; Schultz, Martin G.; Schulz, Michael; Siebesma, Pier; Teixeira, Joao; Tselioudis, George; Vancoppenolle, Martin (Peer reviewed; Journal article, 2019)
      Earth system models (ESMs) are key tools for providing climate projections under different scenarios of human-induced forcing. ESMs include a large number of additional processes and feedbacks such as biogeochemical cycles ...

    • Learning from weather and climate science to prepare for a future pandemic 

      Schemm, Sebastian; Grund, Dana; Knutti, Reto; Wernli, Heini; Ackermann, Martin; Evensen, Geir (Peer reviewed; Journal article, 2023)
      Established pandemic models have yielded mixed results to track and forecast the SARS-CoV-2 pandemic. To prepare for future outbreaks, the disease-modeling community can improve their modeling capabilities by learning from ...