Joint emulation of Earth System Model temperature-precipitation realizations with internal variability and space-time and cross-variable correlation: fldgen v2.0 software description


Autoři: Abigail Snyder aff001;  Robert Link aff001;  Kalyn Dorheim aff001;  Ben Kravitz aff002;  Ben Bond-Lamberty aff001;  Corinne Hartin aff001
Působiště autorů: Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, United States of America aff001;  Department of Earth and Atmospheric Sciences, Indiana University, Bloomington, IN, United States of America aff002;  Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, United States of America aff003
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: 10.1371/journal.pone.0223542

Souhrn

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.

Klíčová slova:

Climate change – Climate modeling – Covariance – Meteorology – Normal distribution – Precipitation techniques – Statistical data – Earth systems


Zdroje

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Článek vyšel v časopise

PLOS One


2019 Číslo 10

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