Project Objectives

NextGEMS is designed to address three specific objectives:

Objective 1 (O1)
to develop two SR-ESMs for applications (i) by demonstrating their capacity to more realistically rep- resent the coupled (land-ocean-atmosphere) climate system, also through an ability to better lever- age observations; (ii) by performing the first global multi-decadal (30 y) SR-ESM based climate projections, testing for out-of-sample climate trajectories, i.e., surprises, and thereby giving a new perspective on uncertainty; and (iii) by expanding their scope to begin more physically coupling ‘Earth-system’ processes, including the carbon cycle and the atmospheric aerosol.

Objective 2 (O2)
to use SR-ESMs to test emerging and long-standing hypotheses underpinning our understanding of climate change: (i) that convective organization contributes importantly to Earth’s energy budget and the strength of cloud feedbacks; (ii) that a more explicit representation of cloud-aerosol interactions mutes aerosol-radiative forcing; (iii) that 2 km to 200 km scale atmospheric and oceanic circulations are of leading order importance for air-sea fluxes in the tropics, thereby influencing not only the mean tropical and mid-latitude climate, but also its variability, including extremes; (iv) that storm-scale variability in weather systems and of the land surface strongly influence extra-tropical climate and extremes, for instance by conditioning circulation regimes, like blocking; (v) that capturing landscape variability globally greatly improves the realism with which regional climate can be simulated; and (vi) that storm-scale variability through its impact on hydrological extremes affects the carbon budget, with associated implications for the global carbon (emissions) stock-take.

Objective 3 (O3)
to build new, more integrated, communities of ESM users by: (i) exploiting the necessity of developing SR-ESMs around a centralized infrastructure to create development and analysis paradigms that can more directly involve a broader and more distributed scientific community; and (ii) by exploiting the affinity between what people experience and what SR-ESMs simulate (i.e., events, in addition to statistics) to more directly involve non-scientific users in model development, thereby fostering Knowledge Coproduction.

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