The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

TitleThe Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model
Publication TypeJournal Article
Year of Publication2018
JournalJournal of Advances in Modeling Earth Systems
Volume10
Date Published02/2018
Abstract

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. About 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology).The relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.

URLhttp://dx.doi.org/10.1002/2017ms000962
DOI10.1002/2017ms000962
Funding Program: 
Journal: Journal of Advances in Modeling Earth Systems
Volume: 10

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. About 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology).The relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.

DOI: 10.1002/2017ms000962
Year of Publication: 2018
Citation: "The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model." Journal of Advances in Modeling Earth Systems. 2018;10.