Abstract

Earth System Models (ESMs) are excellent tools for quantifying many aspects of future climate dynamics but are too computationally expensive to produce large collections of scenarios for downstream users of ESM data. In particular, many researchers focused on the impacts of climate change require large collections of ESM runs to rigorously study the impacts to both human and natural systems of low-frequency high-importance events, such as multi-year droughts. Climate model emulators provide an effective mechanism for filling this gap, reproducing many aspects of ESMs rapidly but with lower precision. The fldgen v1.0 R package quickly generates thousands of realizations of gridded temperature fields by randomizing the residuals of pattern scaling temperature output from any single ESM, retaining the spatial and temporal variance and covariance structures of the input data at a low computational cost. The fldgen v2.0 R package described here extends this capability to produce joint realizations of multiple variables, with a focus on temperature and precipitation in an open source software package available for community use (https://github.com/jgcri/fldgen). This substantially improves the fldgen package by removing the requirement that the ESM variables be normally distributed, and will enable researchers to quickly generate covarying temperature and precipitation data that are synthetic but faithful to the characteristics of the original ESM.

Highlights

  • Two important topics to researchers in earth sciences, future climate dynamics, and joint human-Earth system modeling are the effects of extreme events and uncertainty in climate

  • Fldgen v2.0 provides a tool for climate change impacts modelers to rigorously analyze the impacts of extreme events that previously could not be fully evaluated due to limited Earth System Models (ESMs) realizations and region-to-region teleconnections that are not explicitly known globally, such as multi-year droughts across different regions

  • With the mathematical construction described in the previous section and summarized in Fig 3, when the full workflow depicted in Fig 1 is completed, the algorithm can be run on any input ESM residuals, provided their distribution in each grid cell is continuous and invertible

Read more

Summary

RESEARCH ARTICLE

Joint emulation of Earth System Model temperature-precipitation realizations with internal variability and space-time and crossvariable correlation: fldgen v2.0 software description a1111111111 a1111111111 a1111111111 a1111111111 a1111111111. Abigail SnyderID1☯*, Robert LinkID1☯, Kalyn DorheimID1‡, Ben Kravitz2,3‡, Ben BondLamberty, Corinne Hartin

OPEN ACCESS
Introduction
Conclusions
Utility and limitations
Training the emulator from ESM data
Description of inputs
Structure of a trained emulator
Generating new realizations
Availability Quality control
Programming language
Software location
Author Contributions
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call