Merge pull request #16 from JGCRI/dev

Dev

DESCRIPTION

@@ -47,4 +47,4 @@ Remotes:
 Config/testthat/edition: 3
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.2.1
+RoxygenNote: 7.2.3

paper/paper.bib

@@ -1,96 +1,109 @@
 @article{khan2021impacts,
-  title={Impacts of long-term temperature change and variability on electricity investments},
-  author={Khan, Zarrar and Iyer, Gokul and Patel, Pralit and Kim, Son and Hejazi, Mohamad and Burleyson, Casey and Wise, Marshall},
-  journal={Nature communications},
-  volume={12},
-  number={1},
-  pages={1643},
-  year={2021},
-  publisher={Nature Publishing Group UK London},
-  doi={10.1038/s41467-021-21785-1},
-  url={https://doi.org/10.1038/s41467-021-21785-1}
+  title = {Impacts of long-term temperature change and variability on electricity investments},
+  volume = {12},
+  ISSN = {2041-1723},
+  url = {http://dx.doi.org/10.1038/s41467-021-21785-1},
+  DOI = {10.1038/s41467-021-21785-1},
+  number = {1},
+  journal = {Nature Communications},
+  publisher = {Springer Science and Business Media LLC},
+  author = {Khan,  Zarrar and Iyer,  Gokul and Patel,  Pralit and Kim,  Son and Hejazi,  Mohamad and Burleyson,  Casey and Wise,  Marshall},
+  year = {2021},
+  month = mar
 }
 
 @article{ciscar2014integrated,
-  title={Integrated assessment of climate impacts and adaptation in the energy sector},
-  author={Ciscar, Juan-Carlos and Dowling, Paul},
-  journal={Energy Economics},
-  volume={46},
-  pages={531--538},
-  year={2014},
-  publisher={Elsevier},
-  doi={10.1016/j.eneco.2014.07.003},
-  url={https://doi.org/10.1016/j.eneco.2014.07.003}
+  title = {Integrated assessment of climate impacts and adaptation in the energy sector},
+  volume = {46},
+  ISSN = {0140-9883},
+  url = {http://dx.doi.org/10.1016/j.eneco.2014.07.003},
+  DOI = {10.1016/j.eneco.2014.07.003},
+  journal = {Energy Economics},
+  publisher = {Elsevier BV},
+  author = {Ciscar,  Juan-Carlos and Dowling,  Paul},
+  year = {2014},
+  month = nov,
+  pages = {531–538}
 }
 
 @article{wise2019representing,
-  title={Representing power sector detail and flexibility in a multi-sector model},
-  author={Wise, Marshall and Patel, Pralit and Khan, Zarrar and Kim, Son H and Hejazi, Mohamad and Iyer, Gokul},
-  journal={Energy Strategy Reviews},
-  volume={26},
-  pages={100411},
-  year={2019},
-  publisher={Elsevier},
-  doi={10.1016/j.esr.2019.100411},
-  url={https://doi.org/10.1016/j.esr.2019.100411}
+  title = {Representing power sector detail and flexibility in a multi-sector model},
+  volume = {26},
+  ISSN = {2211-467X},
+  url = {http://dx.doi.org/10.1016/j.esr.2019.100411},
+  DOI = {10.1016/j.esr.2019.100411},
+  journal = {Energy Strategy Reviews},
+  publisher = {Elsevier BV},
+  author = {Wise,  Marshall and Patel,  Pralit and Khan,  Zarrar and Kim,  Son H. and Hejazi,  Mohamad and Iyer,  Gokul},
+  year = {2019},
+  month = nov,
+  pages = {100411}
 }
 
 @article{binsted2022electrified,
-  title={An electrified road to climate goals},
-  author={Binsted, Matthew},
-  journal={Nature Energy},
-  volume={7},
-  number={1},
-  pages={9--10},
-  year={2022},
-  publisher={Nature Publishing Group UK London},
-  doi={10.1038/s41560-021-00974-8},
-  url={https://doi.org/10.1038/s41560-021-00974-8}
+  title = {An electrified road to climate goals},
+  volume = {7},
+  ISSN = {2058-7546},
+  url = {http://dx.doi.org/10.1038/s41560-021-00974-8},
+  DOI = {10.1038/s41560-021-00974-8},
+  number = {1},
+  journal = {Nature Energy},
+  publisher = {Springer Science and Business Media LLC},
+  author = {Binsted,  Matthew},
+  year = {2022},
+  month = jan,
+  pages = {9–10}
 }
 
 @techreport{jones2022im3,
   title={IM3/HyperFACETS Thermodynamic Global Warming (TGW) Simulation Datasets},
-  author={Jones, Andrew D and Rastogi, Deeksha and Vahmani, Pouya and Stansfield, Alyssa and Reed, Kevin and Ullrich, Paul and Rice, Jennie S},
+  author={Jones,  Andrew D. and Rastogi,  Deeksha and Vahmani,  Pouya and Stansfield,  Alyssa and Reed,  Kevin and Thurber,  Travis and Ullrich,  Paul and Rice,  Jennie S.},
   year={2022},
-  institution={MultiSector Dynamics-Living, Intuitive, Value-adding, Environment},
+  publisher={MultiSector Dynamics-Living, Intuitive, Value-adding, Environment},
   doi={10.57931/1885756},
   url={https://doi.org/10.57931/1885756}
 }
 
 @article{calvin2019gcam,
-  title={GCAM v5. 1: representing the linkages between energy, water, land, climate, and economic systems},
-  author={Calvin, Katherine and Patel, Pralit and Clarke, Leon and Asrar, Ghassem and Bond-Lamberty, Ben and Cui, Ryna Yiyun and Di Vittorio, Alan and Dorheim, Kalyn and Edmonds, Jae and Hartin, Corinne and others},
-  journal={Geoscientific Model Development (Online)},
-  volume={12},
-  number={PNNL-SA-137098},
-  year={2019},
-  publisher={Lawrence Berkeley National Lab.(LBNL), Berkeley, CA (United States); Pacific~…},
-  DOI={10.5194/gmd-12-677-2019}
+  title = {GCAM v5.1: representing the linkages between energy,  water,  land,  climate,  and economic systems},
+  volume = {12},
+  ISSN = {1991-9603},
+  url = {http://dx.doi.org/10.5194/gmd-12-677-2019},
+  DOI = {10.5194/gmd-12-677-2019},
+  number = {2},
+  journal = {Geoscientific Model Development},
+  publisher = {Copernicus GmbH},
+  author = {Calvin,  Katherine and Patel,  Pralit and Clarke,  Leon and Asrar,  Ghassem and Bond-Lamberty,  Ben and Cui,  Ryna Yiyun and Di Vittorio,  Alan and Dorheim,  Kalyn and Edmonds,  Jae and Hartin,  Corinne and Hejazi,  Mohamad and Horowitz,  Russell and Iyer,  Gokul and Kyle,  Page and Kim,  Sonny and Link,  Robert and McJeon,  Haewon and Smith,  Steven J. and Snyder,  Abigail and Waldhoff,  Stephanie and Wise,  Marshall},
+  year = {2019},
+  month = feb,
+  pages = {677–698}
 }
 
-@Article{binsted2022gcam-usa,
-AUTHOR = {Binsted, M. and Iyer, G. and Patel, P. and Graham, N. T. and Ou, Y. and Khan, Z. and Kholod, N. and Narayan, K. and Hejazi, M. and Kim, S. and Calvin, K. and Wise, M.},
-TITLE = {GCAM-USA v5.3\_water\_dispatch: integrated modeling of subnational US energy, water, and land systems within a global framework},
-JOURNAL = {Geoscientific Model Development},
-VOLUME = {15},
-YEAR = {2022},
-NUMBER = {6},
-PAGES = {2533--2559},
-URL = {https://gmd.copernicus.org/articles/15/2533/2022/},
-DOI = {10.5194/gmd-15-2533-2022}
+@article{binsted2022gcam-usa,
+  title = {GCAM-USA v5.3_water_dispatch: integrated modeling of subnational US energy,  water,  and land systems within a global framework},
+  volume = {15},
+  ISSN = {1991-9603},
+  url = {http://dx.doi.org/10.5194/gmd-15-2533-2022},
+  DOI = {10.5194/gmd-15-2533-2022},
+  number = {6},
+  journal = {Geoscientific Model Development},
+  publisher = {Copernicus GmbH},
+  author = {Binsted,  Matthew and Iyer,  Gokul and Patel,  Pralit and Graham,  Neal T. and Ou,  Yang and Khan,  Zarrar and Kholod,  Nazar and Narayan,  Kanishka and Hejazi,  Mohamad and Kim,  Son and Calvin,  Katherine and Wise,  Marshall},
+  year = {2022},
+  month = mar,
+  pages = {2533–2559}
 }
 
-
 @article{iturbide2019,
-title = {The R-based climate4R open framework for reproducible climate data access and post-processing},
-journal = {Environmental Modelling & Software},
-volume = {111},
-pages = {42-54},
-year = {2019},
-issn = {1364-8152},
-doi = {https://doi.org/10.1016/j.envsoft.2018.09.009},
-url = {https://www.sciencedirect.com/science/article/pii/S1364815218303049},
-author = {M. Iturbide and J. Bedia and S. Herrera and J. Baño-Medina and J. Fernández and M.D. Frías and R. Manzanas and D. San-Martín and E. Cimadevilla and A.S. Cofiño and J.M. Gutiérrez},
-keywords = {Open science, Climate indices, CMIP5, Downscaling, Climatic change, NetCDF-java},
-abstract = {Climate-driven sectoral applications commonly require different types of climate data (e.g. observations, reanalysis, climate change projections) from different providers. Data access, harmonization and post-processing (e.g. bias correction) are time-consuming error-prone tasks requiring different specialized software tools at each stage of the data workflow, thus hindering reproducibility. Here we introduce climate4R, an R-based climate services oriented framework tailored to the needs of the vulnerability and impact assessment community that integrates in the same computing environment harmonized data access, post-processing, visualization and a provenance metadata model for traceability and reproducibility of results. climate4R allows accessing local and remote (OPeNDAP) data sources, such as the Santander User Data Gateway (UDG), a THREDDS-based service including a wide catalogue of popular datasets (e.g. ERA-Interim, CORDEX, etc.). This provides a unique comprehensive open framework for end-to-end sectoral reproducible applications. All the packages, data and documentation for reproducing the experiments in this paper are available from http://www.meteo.unican.es/climate4R.}
+  title = {The R-based climate4R open framework for reproducible climate data access and post-processing},
+  volume = {111},
+  ISSN = {1364-8152},
+  url = {http://dx.doi.org/10.1016/j.envsoft.2018.09.009},
+  DOI = {10.1016/j.envsoft.2018.09.009},
+  journal = {Environmental Modelling & Software},
+  publisher = {Elsevier BV},
+  author = {Iturbide,  M. and Bedia,  J. and Herrera,  S. and Baño-Medina,  J. and Fernández,  J. and Frías,  M.D. and Manzanas,  R. and San-Martín,  D. and Cimadevilla,  E. and Cofiño,  A.S. and Gutiérrez,  J.M.},
+  year = {2019},
+  month = jan,
+  pages = {42–54}
 }

paper/paper.md

@@ -35,7 +35,7 @@ bibliography: paper.bib
 
 # Statement of Field
 
-Heating and cooling degree days are commonly used as meteorological indices in the energy system to measure the temperature deviations from the reference temperature over time. These indices are widely calculated at point scale rather than spatial scale. With the increasing availability of spatially distributed climate data, few tools are developed to access and post-process the raw climate data format into tabular format, such as `Climate4R` [@iturbide2019].However, there are rarely well-documented and open-source tools that streamline the calculation of population-weighted HDD and CDD at user-defined spatiotemporal resolutions or electricity dispatch sectors defined in GCAM, directly using gridded climate and population data. `helios` is developed to integrate these workflows and standardize the output for easy usage within and beyond GCAM applications.
+Heating and cooling degree days are commonly used as meteorological indices in the energy system to measure the temperature deviations from the reference temperature over time. These indices are widely calculated at point scale rather than spatial scale. With the increasing availability of spatially distributed climate data, few tools are developed to access and post-process the raw climate data format into tabular format, such as `Climate4R` [@iturbide2019]. However, there are rarely well-documented and open-source tools that streamline the calculation of population-weighted HDD and CDD at user-defined spatiotemporal resolutions or electricity dispatch sectors defined in GCAM, directly using gridded climate and population data. `helios` is developed to integrate these workflows and standardize the output for easy usage within and beyond GCAM applications.
 
 # Design and Functionality