added reference to IPCC_2023

src/docs/JOSS/paper.bib

@@ -98,62 +98,11 @@ @article{BUI:2021114111
 abstract = {Many subsurface engineering applications involve tight-coupling between fluid flow, solid deformation, fracturing, and similar processes. To better understand the complex interplay of different governing equations, and therefore design efficient and safe operations, numerical simulations are widely used. Given the relatively long time-scales of interest, fully-implicit time-stepping schemes are often necessary to avoid time-step stability restrictions. A major computational bottleneck for these methods, however, is the linear solver. These systems are extremely large and ill-conditioned. Because of the wide range of processes and couplings that may be involved – e.g. formation and propagation of fractures, deformation of the solid porous medium, viscous flow of one or more fluids in the pores and fractures, complicated well sources and sinks, etc. – it is difficult to develop general-purpose but scalable linear solver frameworks. This challenge is further aggravated by the range of different discretization schemes that may be adopted, which have a direct impact on the linear system structure. To address this obstacle, we describe a flexible strategy based on multigrid reduction (MGR) that can produce purely algebraic preconditioners for a wide spectrum of relevant physics and discretizations. We demonstrate that MGR, guided by physics and theory in block preconditioning, can tackle several distinct and challenging problems, notably: a hybrid discretization of single-phase flow, compositional multiphase flow with complex wells, and hydraulic fracturing simulations. Extension to other systems can be handled quite naturally. We demonstrate the efficiency and scalability of the resulting solvers through numerical examples of difficult, field-scale problems.}
 }
 
-@article{Pearson:2017,
-  	url = {http://adsabs.harvard.edu/abs/2017arXiv170304627P},
-  	Archiveprefix = {arXiv},
-  	Author = {{Pearson}, S. and {Price-Whelan}, A.~M. and {Johnston}, K.~V.},
-  	Eprint = {1703.04627},
-  	Journal = {ArXiv e-prints},
-  	Keywords = {Astrophysics - Astrophysics of Galaxies},
-  	Month = mar,
-  	Title = {{Gaps in Globular Cluster Streams: Pal 5 and the Galactic Bar}},
-  	Year = 2017
-}
-
-@book{Binney:2008,
-  	url = {http://adsabs.harvard.edu/abs/2008gady.book.....B},
-  	Author = {{Binney}, J. and {Tremaine}, S.},
-  	Booktitle = {Galactic Dynamics: Second Edition, by James Binney and Scott Tremaine.~ISBN 978-0-691-13026-2 (HB).~Published by Princeton University Press, Princeton, NJ USA, 2008.},
-  	Publisher = {Princeton University Press},
-  	Title = {{Galactic Dynamics: Second Edition}},
-  	Year = 2008
-}
-
-@article{gaia,
-    author = {{Gaia Collaboration}},
-    title = "{The Gaia mission}",
-    journal = {Astronomy and Astrophysics},
-    archivePrefix = "arXiv",
-    eprint = {1609.04153},
-    primaryClass = "astro-ph.IM",
-    keywords = {space vehicles: instruments, Galaxy: structure, astrometry, parallaxes, proper motions, telescopes},
-    year = 2016,
-    month = nov,
-    volume = 595,
-    doi = {10.1051/0004-6361/201629272},
-    url = {http://adsabs.harvard.edu/abs/2016A%26A...595A...1G},
-}
 
-@article{astropy,
-    author = {{Astropy Collaboration}},
-    title = "{Astropy: A community Python package for astronomy}",
-    journal = {Astronomy and Astrophysics},
-    archivePrefix = "arXiv",
-    eprint = {1307.6212},
-    primaryClass = "astro-ph.IM",
-    keywords = {methods: data analysis, methods: miscellaneous, virtual observatory tools},
-    year = 2013,
-    month = oct,
-    volume = 558,
-    doi = {10.1051/0004-6361/201322068},
-    url = {http://adsabs.harvard.edu/abs/2013A%26A...558A..33A}
-}
 
-@misc{fidgit,
-  author = {A. M. Smith and K. Thaney and M. Hahnel},
-  title = {Fidgit: An ungodly union of GitHub and Figshare},
-  year = {2020},
-  publisher = {GitHub},
-  journal = {GitHub repository},
-  url = {https://github.com/arfon/fidgit}
+@book{ IPCC_2023, 
+place={Cambridge}, 
+title={Climate Change 2022 - Mitigation of Climate Change: Working Group III Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change}, 
+publisher={Cambridge University Press}, 
+year={2023}
 }

src/docs/JOSS/paper.md

@@ -105,7 +105,7 @@ Note that the version of GEOS described here should be considered a separate wor
 
 The increasing threat of climate change has resulted in an increased focus on mitigating carbon emissions into the atmosphere.
 Carbon Capture and Storage (CCS) of CO2 in subsurface reservoirs and saline aquifers is an important technology required to meet global climate goals. 
-Given the 2050 net-zero GHG goals, CO2 storage capacities required to offset emissions is orders of magnitude greater than current levels.(reference needed)
+Given the 2050 net-zero GHG goals, CO2 storage capacities required to offset emissions is orders of magnitude greater than current levels [@IPCC_2023].
 One factor in the evaluation of CO2 storage sites are the containment risks associated with the injection of liquefied CO2 in the subsurface.
 The primary goal of GEOS is to provide the global community with an open-source tool that is capable of simulating the complex coupled physics that occurs when liquefied CO2 is injected into a subsurface reservoir. 
 Thus, GEOS is freely available and focused on the simulation of reservoir integrity through various failure mechanisms such as caprock failure, fault leakage, and wellbore failure.
@@ -142,7 +142,7 @@ As an example of a field case where GEOS has been applied, we present a simulati
 Figure \ref{RW_final}a illustrates the computational mesh and Figure \ref{RW_final}b shows results after 25 years of injection.
 Simulations such as these play a critical role in predicting the performance of potential CO2 storage sites.
 
-![Real world CO2 storage site: (a) discrete mesh, transparency is used for the overburden region to reveal the complex faulted structure of the storage reservoir; (b) results of a compositional flow simulation after 25 years of CO2 injection. The CO2 plume is shown in white near the bottom of the well. Colors in the reservoir layer indicate changes in fluid pressure, and the colors in the overburden indicate vertical displacement resulting from the injection. Note that color scales have been removed intentionally.\label{RW_results}](RW_final.pdf){ width=1oo% }
+![Real world CO2 storage site: (a) discrete mesh, transparency is used for the overburden region to reveal the complex faulted structure of the storage reservoir; (b) results of a compositional flow simulation after 25 years of CO2 injection. The CO2 plume is shown in white near the bottom of the well. Colors in the reservoir layer indicate changes in fluid pressure, and the colors in the overburden indicate vertical displacement resulting from the injection. Note that color scales have been removed intentionally.\label{RW_results}](RW_final.pdf){ width=100% }
 
 
 As an example of the weak scalability of GEOS on exascale systems, we present two weak scaling studies on a simple wellbore geometry using the exascale Frontier supercomputer located at Oak Ridge National Laboratory (ORNL).