Phenology of stomoxyinae in a Kenyan forest

Publication Type

Journal Article

Journal Name

Journal of Advances in Modeling Earth Systems

Name of Author

Thorsten Mauritsen, Max Planck Institute for Meteorology
Jürgen Bader, Max Planck Institute for Meteorology
Tobias Becker, Max Planck Institute for Meteorology
Jörg Behrens, Duetsches Klimarechenzentrum GmbH
Matthias Bittner, Max Planck Institute for Meteorology
Renate Brokopf, Max Planck Institute for Meteorology
Victor Brovkin, Max Planck Institute for Meteorology
Martin Claussen, Max Planck Institute for Meteorology
Traute Crueger, Max Planck Institute for Meteorology
Monika Esch, Max Planck Institute for Meteorology
Irina Fast, Duetsches Klimarechenzentrum GmbH
Stephanie Fiedler, Stockholms universitet
Dagmar Fläschner, Max Planck Institute for Meteorology
Veronika Gayler, Max Planck Institute for Meteorology
Marco Giorgetta, Max Planck Institute for Meteorology
Daniel S. Goll, Laboratoire des Sciences du Climat et de l'Environnement
Helmuth Haak, Max Planck Institute for Meteorology
Stefan Hagemann, Max Planck Institute for Meteorology
Christopher Hedemann, Max Planck Institute for Meteorology
Cathy Hohenegger, Max Planck Institute for Meteorology
Tatiana Ilyina, Max Planck Institute for Meteorology
Thomas Jahns, Duetsches Klimarechenzentrum GmbH
Diego Jimenéz-de-la-Cuesta, Max Planck Institute for Meteorology
Johann Jungclaus, Max Planck Institute for Meteorology
Thomas Kleinen, Max Planck Institute for Meteorology
Silvia Kloster, Max Planck Institute for Meteorology
Daniela Kracher, Max Planck Institute for Meteorology
Stefan Kinne, Max Planck Institute for Meteorology

Publication Date

4-1-2019

Abstract

A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI-ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low-level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO2 over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO2 forcing, which nonetheless can be represented by a simple two-layer model.

Keywords

climate sensitivity, coupled climate model, model development

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