Development of an open-source regional data assimilation system in PEcAn v. 1.7.2: application to carbon cycle reanalysis across the contiguous US using SIPNET

Dokoohaki, Hamze; Morrison, Bailey D.; Raiho, Ann; Serbin, Shawn P.; Zarada, Katie; Dramko, Luke; Dietze, Michael

doi:https://doi.org/10.5194/gmd-15-3233-2022

Articles | Volume 15, issue 8

https://doi.org/10.5194/gmd-15-3233-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-15-3233-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 8

Development and technical paper

|

20 Apr 2022

Development and technical paper |

| 20 Apr 2022

Development of an open-source regional data assimilation system in PEcAn v. 1.7.2: application to carbon cycle reanalysis across the contiguous US using SIPNET

Hamze Dokoohaki, Bailey D. Morrison, Ann Raiho, Shawn P. Serbin, Katie Zarada, Luke Dramko, and Michael Dietze

Model code and software

The Predictive Ecosystem Analyzer (PEcAn) is an integrated ecological bioinformatics toolbox. David LeBauer, Michael Dietze, Hamze Dokoohaki, Rob Kooper, Alexey Shiklomanov, Betsy Cowdery, Istem Fer, Anthony Gardella, Ben Bond-Lamberty, Shawn P. Serbin, Ann Raiho, Anne Thomas, Chris Black, James Simkins, Ankur Desai, Joshua Mantooth, Aman Kumar, Liam Burke, Afshin Pourmokhtarian, Christy Rollinson, Shubham Agarwal, Brady Hardiman, Martin De Kauwe, Eugene, Tess McCabe, Katie Ragosta, Tony Cohen, zhangwenx, Tony Viskari, Yan Zhao, and Jing Xia https://doi.org/10.5281/zenodo.5557914

NASA_CMS_SDA S. Serbin, H. Dokoohaki, B. Morrison, A. Andrews, and M. Dietze https://osf.io/efcv5/?view_only= f2eeea87a6504abbae81164efd2b481c

Short summary

We present a new terrestrial carbon cycle data assimilation system, built on the PEcAn model–data eco-informatics system, and its application for the development of a proof-of-concept carbon reanalysis product that harmonizes carbon pools (leaf, wood, soil) and fluxes (GPP, Ra, Rh, NEE) across the contiguous United States from 1986–2019. Here, we build on a decade of work on uncertainty propagation to generate the most complete and robust uncertainty accounting available to date.