1Earth and Environmental Systems Institute, Pennsylvania State University, University Park, PA 16802, USA
2Institute for Marine and Atmospheric Research Utrecht, Utrecht University, The Netherlands
3Department of Geosciences, Pennsylvania State University, University Park, PA 16802, USA
4Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA 15289, USA
anow at: Rijkswaterstaat, Ministry of Infrastructure and Environment, The Netherlands
bnow at: Research Square, Durham, NC 27701, USA
cnow at: Royal Netherlands Institute for Sea Research (NIOZ), Department of Estuarine & Delta Systems (EDS), Yerseke,The Netherlands
*These authors contributed equally to this work.
Received: 12 Dec 2016 – Accepted: 11 Jan 2017 – Published: 12 Jan 2017
Abstract. Simple models can play pivotal roles in the quantification and framing of uncertainties surrounding climate change and sea-level rise. They are computationally efficient, transparent, and easier to reproduce. These qualities make simple models useful for uncertainty quantification and risk characterization. Simple model codes are increasingly distributed as open source, as well as actively shared and guided. Alas, computer codes used in the geosciences can often be hard to access, run, modify (e.g., with regards to assumptions and model components), and review. Here, we introduce a simple model framework for projections of global mean temperatures as well as regional sea levels and coastal flood risk (BRICK: Building blocks for Relevant Ice and Climate Knowledge). The BRICK model framework is written in R and Fortran and aims to help mitigate these issues, while maintaining a high degree of computational efficiency. We demonstrate the flexibility of this framework through simple model intercomparison experiments. Furthermore, we demonstrate that BRICK is suitable for risk assessment applications by using a didactic example in local flood risk management.
Wong, T. E., Bakker, A., Ruckert, K., Applegate, P., Slangen, A., and Keller, K.: BRICK v0.1, a simple, accessible, and transparent model framework for climate and regional sea-level projections, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-303, in review, 2017.
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Latest update: 21 Jan 2017