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1/8˚ resolution MOM6-COBALT daily physical and biogeochemical diagnostics for 2008

The files in this dataset contain daily mean chlorophyll (µg/kg), pH, nitrate (mol/kg), dissolved oxygen (mol/kg), potential temperature (˚C) and salinity model outputs for 2008 for the region between 20-55˚N, 135-111˚W. Data was extracted from a global grid run with coupled ocean-ice model configured using the Modular Ocean Model 6 (MOM6, <a href="https://github.com/NOAA-GFDL/MOM6">https://github.com/NOAA-GFDL/MOM6</a> ) and Sea Ice Simulator (SIS2) developed at the NOAA Geophysical Fluid Dynamics Laboratory (Adcroft et al., 2019). The horizontal resolution of the grid is 1/8˚, which is considered eddying and no eddy parameterization was included. Vertically, the model uses 75 hybrid vertical-sigma2 layer coordinates that is remapped onto 35 World Ocean Atlas/Coupled Model Intercomparison Project standard depth levels. The atmospheric forcing was derived from the Japanese 55-year Reanalysis version 1.5 (JRA55 1.5, <a href="https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55">https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55</a>). The model is driven by river freshwater runoff from a monthly climatology derived from Dai and Trenberth (2002) and Dai et al. (2009), which can be assessed at <a href="https://rda.ucar.edu/datasets/ds551.0/">https://rda.ucar.edu/datasets/ds551.0/</a>. A remapping scheme was used to add freshwater into the appropriate coastal grid cells near the river mouths. The biogeochemical model used was the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALTv2, Stock et al., 2020), which uses 33 tracers for representation of coupled elemental cycles of carbon, nitrogen, phosphorus, iron, silicon, alkalinity, oxygen and lithogenic matter and associated plankton food web dynamics. More details about the model setup are described in Liu et al. (2019) and Liu et al. (2021). This work was part of a PMEL-led project "A Pilot BGC Argo Float Array in the California Current Large Marine Ecosystem" funded by NOAA Research.   References:   Adcroft, A., Anderson, W., Blanton, C., Bushuk, M., Dufour, C.O., Dunne, J.P., Griffies, S.M. et al. (2019). The GFDL Global Ocean and Sea Ice Model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth System, doi: 10.1029/2019MS001726   Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, 2009: Changes in continental freshwater discharge from 1948-2004. J. Climate, 22, 2773-2791   Dai, A., and K. E. Trenberth, 2002: Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687   Liu, X., Dunne, J.P., Stock, C. A., Harrison, M.J., Adcroft, A., Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 22, 13910-13919. Doi:10.1029/2019GL085097   Liu, X., Stock, C.A., Dunne, J.P., Lee, M., Shevliakova, E., Malyshev, S., Milly, P.C.D (2021). Simulated Global Coastal Ecosystem Responses to a Half-Century Increase in River Nitrogen Loads.   Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., et al. (2020). Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO2. Journal of Advances in Modeling Earth Systems, 12, e2019MS002043. https://doi.org/10.1029/2019MS002043

1/8˚ resolution MOM6-COBALT daily physical and biogeochemical diagnostics for 2010

The files in this dataset contain daily mean chlorophyll (µg/kg), pH, nitrate (mol/kg), dissolved oxygen (mol/kg), potential temperature (˚C) and salinity model outputs for 2010 for the region between 20-55˚N, 135-111˚W. Data was extracted from a global grid run with coupled ocean-ice model configured using the Modular Ocean Model 6 (MOM6, <a href="https://github.com/NOAA-GFDL/MOM6">https://github.com/NOAA-GFDL/MOM6</a> ) and Sea Ice Simulator (SIS2) developed at the NOAA Geophysical Fluid Dynamics Laboratory (Adcroft et al., 2019). The horizontal resolution of the grid is 1/8˚, which is considered eddying and no eddy parameterization was included. Vertically, the model uses 75 hybrid vertical-sigma2 layer coordinates that is remapped onto 35 World Ocean Atlas/Coupled Model Intercomparison Project standard depth levels. The atmospheric forcing was derived from the Japanese 55-year Reanalysis version 1.5 (JRA55 1.5, <a href="https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55">https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55</a>). The model is driven by river freshwater runoff from a monthly climatology derived from Dai and Trenberth (2002) and Dai et al. (2009), which can be assessed at <a href="https://rda.ucar.edu/datasets/ds551.0/">https://rda.ucar.edu/datasets/ds551.0/</a>. A remapping scheme was used to add freshwater into the appropriate coastal grid cells near the river mouths. The biogeochemical model used was the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALTv2, Stock et al., 2020), which uses 33 tracers for representation of coupled elemental cycles of carbon, nitrogen, phosphorus, iron, silicon, alkalinity, oxygen and lithogenic matter and associated plankton food web dynamics. More details about the model setup are described in Liu et al. (2019) and Liu et al. (2021). This work was part of a PMEL-led project "A Pilot BGC Argo Float Array in the California Current Large Marine Ecosystem" funded by NOAA Research.   References:   Adcroft, A., Anderson, W., Blanton, C., Bushuk, M., Dufour, C.O., Dunne, J.P., Griffies, S.M. et al. (2019). The GFDL Global Ocean and Sea Ice Model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth System, doi: 10.1029/2019MS001726   Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, 2009: Changes in continental freshwater discharge from 1948-2004. J. Climate, 22, 2773-2791   Dai, A., and K. E. Trenberth, 2002: Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687   Liu, X., Dunne, J.P., Stock, C. A., Harrison, M.J., Adcroft, A., Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 22, 13910-13919. Doi:10.1029/2019GL085097   Liu, X., Stock, C.A., Dunne, J.P., Lee, M., Shevliakova, E., Malyshev, S., Milly, P.C.D (2021). Simulated Global Coastal Ecosystem Responses to a Half-Century Increase in River Nitrogen Loads.   Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., et al. (2020). Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO2. Journal of Advances in Modeling Earth Systems, 12, e2019MS002043. https://doi.org/10.1029/2019MS002043

1/8˚ resolution MOM6-COBALT daily physical and biogeochemical diagnostics for 2009

The files in this dataset contain daily mean chlorophyll (µg/kg), pH, nitrate (mol/kg), dissolved oxygen (mol/kg), potential temperature (˚C) and salinity model outputs for 2009 for the region between 20-55˚N, 135-111˚W. Data was extracted from a global grid run with coupled ocean-ice model configured using the Modular Ocean Model 6 (MOM6, <a href="https://github.com/NOAA-GFDL/MOM6">https://github.com/NOAA-GFDL/MOM6</a> ) and Sea Ice Simulator (SIS2) developed at the NOAA Geophysical Fluid Dynamics Laboratory (Adcroft et al., 2019). The horizontal resolution of the grid is 1/8˚, which is considered eddying and no eddy parameterization was included. Vertically, the model uses 75 hybrid vertical-sigma2 layer coordinates that is remapped onto 35 World Ocean Atlas/Coupled Model Intercomparison Project standard depth levels. The atmospheric forcing was derived from the Japanese 55-year Reanalysis version 1.5 (JRA55 1.5, <a href="https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55">https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55</a>). The model is driven by river freshwater runoff from a monthly climatology derived from Dai and Trenberth (2002) and Dai et al. (2009), which can be assessed at <a href="https://rda.ucar.edu/datasets/ds551.0/">https://rda.ucar.edu/datasets/ds551.0/</a>. A remapping scheme was used to add freshwater into the appropriate coastal grid cells near the river mouths. The biogeochemical model used was the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALTv2, Stock et al., 2020), which uses 33 tracers for representation of coupled elemental cycles of carbon, nitrogen, phosphorus, iron, silicon, alkalinity, oxygen and lithogenic matter and associated plankton food web dynamics. More details about the model setup are described in Liu et al. (2019) and Liu et al. (2021). This work was part of a PMEL-led project "A Pilot BGC Argo Float Array in the California Current Large Marine Ecosystem" funded by NOAA Research.   References:   Adcroft, A., Anderson, W., Blanton, C., Bushuk, M., Dufour, C.O., Dunne, J.P., Griffies, S.M. et al. (2019). The GFDL Global Ocean and Sea Ice Model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth System, doi: 10.1029/2019MS001726   Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, 2009: Changes in continental freshwater discharge from 1948-2004. J. Climate, 22, 2773-2791   Dai, A., and K. E. Trenberth, 2002: Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687   Liu, X., Dunne, J.P., Stock, C. A., Harrison, M.J., Adcroft, A., Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 22, 13910-13919. Doi:10.1029/2019GL085097   Liu, X., Stock, C.A., Dunne, J.P., Lee, M., Shevliakova, E., Malyshev, S., Milly, P.C.D (2021). Simulated Global Coastal Ecosystem Responses to a Half-Century Increase in River Nitrogen Loads.   Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., et al. (2020). Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO2. Journal of Advances in Modeling Earth Systems, 12, e2019MS002043. https://doi.org/10.1029/2019MS002043

1/8˚ resolution MOM6-COBALT daily physical and biogeochemical diagnostics for 2011

The files in this dataset contain daily mean chlorophyll (µg/kg), pH, nitrate (mol/kg), dissolved oxygen (mol/kg), potential temperature (˚C) and salinity model outputs for 2011 for the region between 20-55˚N, 135-111˚W. Data was extracted from a global grid run with coupled ocean-ice model configured using the Modular Ocean Model 6 (MOM6, <a href="https://github.com/NOAA-GFDL/MOM6">https://github.com/NOAA-GFDL/MOM6</a> ) and Sea Ice Simulator (SIS2) developed at the NOAA Geophysical Fluid Dynamics Laboratory (Adcroft et al., 2019). The horizontal resolution of the grid is 1/8˚, which is considered eddying and no eddy parameterization was included. Vertically, the model uses 75 hybrid vertical-sigma2 layer coordinates that is remapped onto 35 World Ocean Atlas/Coupled Model Intercomparison Project standard depth levels. The atmospheric forcing was derived from the Japanese 55-year Reanalysis version 1.5 (JRA55 1.5, <a href="https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55">https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55</a>). The model is driven by river freshwater runoff from a monthly climatology derived from Dai and Trenberth (2002) and Dai et al. (2009), which can be assessed at <a href="https://rda.ucar.edu/datasets/ds551.0/">https://rda.ucar.edu/datasets/ds551.0/</a>. A remapping scheme was used to add freshwater into the appropriate coastal grid cells near the river mouths. The biogeochemical model used was the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALTv2, Stock et al., 2020), which uses 33 tracers for representation of coupled elemental cycles of carbon, nitrogen, phosphorus, iron, silicon, alkalinity, oxygen and lithogenic matter and associated plankton food web dynamics. More details about the model setup are described in Liu et al. (2019) and Liu et al. (2021). This work was part of a PMEL-led project "A Pilot BGC Argo Float Array in the California Current Large Marine Ecosystem" funded by NOAA Research.   References:   Adcroft, A., Anderson, W., Blanton, C., Bushuk, M., Dufour, C.O., Dunne, J.P., Griffies, S.M. et al. (2019). The GFDL Global Ocean and Sea Ice Model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth System, doi: 10.1029/2019MS001726   Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, 2009: Changes in continental freshwater discharge from 1948-2004. J. Climate, 22, 2773-2791   Dai, A., and K. E. Trenberth, 2002: Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687   Liu, X., Dunne, J.P., Stock, C. A., Harrison, M.J., Adcroft, A., Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 22, 13910-13919. Doi:10.1029/2019GL085097   Liu, X., Stock, C.A., Dunne, J.P., Lee, M., Shevliakova, E., Malyshev, S., Milly, P.C.D (2021). Simulated Global Coastal Ecosystem Responses to a Half-Century Increase in River Nitrogen Loads.   Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., et al. (2020). Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO2. Journal of Advances in Modeling Earth Systems, 12, e2019MS002043. https://doi.org/10.1029/2019MS002043

1/8˚ resolution MOM6-COBALT daily physical and biogeochemical diagnostics for 2012

The files in this dataset contain daily mean chlorophyll (µg/kg), pH, nitrate (mol/kg), dissolved oxygen (mol/kg), potential temperature (˚C) and salinity model outputs for 2012 for the region between 20-55˚N, 135-111˚W. Data was extracted from a global grid run with coupled ocean-ice model configured using the Modular Ocean Model 6 (MOM6, <a href="https://github.com/NOAA-GFDL/MOM6">https://github.com/NOAA-GFDL/MOM6</a> ) and Sea Ice Simulator (SIS2) developed at the NOAA Geophysical Fluid Dynamics Laboratory (Adcroft et al., 2019). The horizontal resolution of the grid is 1/8˚, which is considered eddying and no eddy parameterization was included. Vertically, the model uses 75 hybrid vertical-sigma2 layer coordinates that is remapped onto 35 World Ocean Atlas/Coupled Model Intercomparison Project standard depth levels. The atmospheric forcing was derived from the Japanese 55-year Reanalysis version 1.5 (JRA55 1.5, <a href="https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55">https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55</a>). The model is driven by river freshwater runoff from a monthly climatology derived from Dai and Trenberth (2002) and Dai et al. (2009), which can be assessed at <a href="https://rda.ucar.edu/datasets/ds551.0/">https://rda.ucar.edu/datasets/ds551.0/</a>. A remapping scheme was used to add freshwater into the appropriate coastal grid cells near the river mouths. The biogeochemical model used was the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALTv2, Stock et al., 2020), which uses 33 tracers for representation of coupled elemental cycles of carbon, nitrogen, phosphorus, iron, silicon, alkalinity, oxygen and lithogenic matter and associated plankton food web dynamics. More details about the model setup are described in Liu et al. (2019) and Liu et al. (2021). This work was part of a PMEL-led project "A Pilot BGC Argo Float Array in the California Current Large Marine Ecosystem" funded by NOAA Research.   References:   Adcroft, A., Anderson, W., Blanton, C., Bushuk, M., Dufour, C.O., Dunne, J.P., Griffies, S.M. et al. (2019). The GFDL Global Ocean and Sea Ice Model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth System, doi: 10.1029/2019MS001726   Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, 2009: Changes in continental freshwater discharge from 1948-2004. J. Climate, 22, 2773-2791   Dai, A., and K. E. Trenberth, 2002: Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687   Liu, X., Dunne, J.P., Stock, C. A., Harrison, M.J., Adcroft, A., Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 22, 13910-13919. Doi:10.1029/2019GL085097   Liu, X., Stock, C.A., Dunne, J.P., Lee, M., Shevliakova, E., Malyshev, S., Milly, P.C.D (2021). Simulated Global Coastal Ecosystem Responses to a Half-Century Increase in River Nitrogen Loads.   Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., et al. (2020). Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO2. Journal of Advances in Modeling Earth Systems, 12, e2019MS002043. https://doi.org/10.1029/2019MS002043

1/8˚ resolution MOM6-COBALT daily physical and biogeochemical diagnostics for 2013

The files in this dataset contain daily mean chlorophyll (µg/kg), pH, nitrate (mol/kg), dissolved oxygen (mol/kg), potential temperature (˚C) and salinity model outputs for 2013 for the region between 20-55˚N, 135-111˚W. Data was extracted from a global grid run with coupled ocean-ice model configured using the Modular Ocean Model 6 (MOM6, <a href="https://github.com/NOAA-GFDL/MOM6">https://github.com/NOAA-GFDL/MOM6</a> ) and Sea Ice Simulator (SIS2) developed at the NOAA Geophysical Fluid Dynamics Laboratory (Adcroft et al., 2019). The horizontal resolution of the grid is 1/8˚, which is considered eddying and no eddy parameterization was included. Vertically, the model uses 75 hybrid vertical-sigma2 layer coordinates that is remapped onto 35 World Ocean Atlas/Coupled Model Intercomparison Project standard depth levels. The atmospheric forcing was derived from the Japanese 55-year Reanalysis version 1.5 (JRA55 1.5, <a href="https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55">https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55</a>). The model is driven by river freshwater runoff from a monthly climatology derived from Dai and Trenberth (2002) and Dai et al. (2009), which can be assessed at <a href="https://rda.ucar.edu/datasets/ds551.0/">https://rda.ucar.edu/datasets/ds551.0/</a>. A remapping scheme was used to add freshwater into the appropriate coastal grid cells near the river mouths. The biogeochemical model used was the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALTv2, Stock et al., 2020), which uses 33 tracers for representation of coupled elemental cycles of carbon, nitrogen, phosphorus, iron, silicon, alkalinity, oxygen and lithogenic matter and associated plankton food web dynamics. More details about the model setup are described in Liu et al. (2019) and Liu et al. (2021). This work was part of a PMEL-led project "A Pilot BGC Argo Float Array in the California Current Large Marine Ecosystem" funded by NOAA Research.   References:   Adcroft, A., Anderson, W., Blanton, C., Bushuk, M., Dufour, C.O., Dunne, J.P., Griffies, S.M. et al. (2019). The GFDL Global Ocean and Sea Ice Model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth System, doi: 10.1029/2019MS001726   Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, 2009: Changes in continental freshwater discharge from 1948-2004. J. Climate, 22, 2773-2791   Dai, A., and K. E. Trenberth, 2002: Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687   Liu, X., Dunne, J.P., Stock, C. A., Harrison, M.J., Adcroft, A., Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 22, 13910-13919. Doi:10.1029/2019GL085097   Liu, X., Stock, C.A., Dunne, J.P., Lee, M., Shevliakova, E., Malyshev, S., Milly, P.C.D (2021). Simulated Global Coastal Ecosystem Responses to a Half-Century Increase in River Nitrogen Loads.   Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., et al. (2020). Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO2. Journal of Advances in Modeling Earth Systems, 12, e2019MS002043. https://doi.org/10.1029/2019MS002043

1/8˚ resolution MOM6-COBALT daily physical and biogeochemical diagnostics for 2016

The files in this dataset contain daily mean chlorophyll (µg/kg), pH, nitrate (mol/kg), dissolved oxygen (mol/kg), potential temperature (˚C) and salinity model outputs for 2016 for the region between 20-55˚N, 135-111˚W. Data was extracted from a global grid run with coupled ocean-ice model configured using the Modular Ocean Model 6 (MOM6, <a href="https://github.com/NOAA-GFDL/MOM6">https://github.com/NOAA-GFDL/MOM6</a> ) and Sea Ice Simulator (SIS2) developed at the NOAA Geophysical Fluid Dynamics Laboratory (Adcroft et al., 2019). The horizontal resolution of the grid is 1/8˚, which is considered eddying and no eddy parameterization was included. Vertically, the model uses 75 hybrid vertical-sigma2 layer coordinates that is remapped onto 35 World Ocean Atlas/Coupled Model Intercomparison Project standard depth levels. The atmospheric forcing was derived from the Japanese 55-year Reanalysis version 1.5 (JRA55 1.5, <a href="https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55">https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55</a>). The model is driven by river freshwater runoff from a monthly climatology derived from Dai and Trenberth (2002) and Dai et al. (2009), which can be assessed at <a href="https://rda.ucar.edu/datasets/ds551.0/">https://rda.ucar.edu/datasets/ds551.0/</a>. A remapping scheme was used to add freshwater into the appropriate coastal grid cells near the river mouths. The biogeochemical model used was the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALTv2, Stock et al., 2020), which uses 33 tracers for representation of coupled elemental cycles of carbon, nitrogen, phosphorus, iron, silicon, alkalinity, oxygen and lithogenic matter and associated plankton food web dynamics. More details about the model setup are described in Liu et al. (2019) and Liu et al. (2021). This work was part of a PMEL-led project "A Pilot BGC Argo Float Array in the California Current Large Marine Ecosystem" funded by NOAA Research.   References:   Adcroft, A., Anderson, W., Blanton, C., Bushuk, M., Dufour, C.O., Dunne, J.P., Griffies, S.M. et al. (2019). The GFDL Global Ocean and Sea Ice Model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth System, doi: 10.1029/2019MS001726   Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, 2009: Changes in continental freshwater discharge from 1948-2004. J. Climate, 22, 2773-2791   Dai, A., and K. E. Trenberth, 2002: Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687   Liu, X., Dunne, J.P., Stock, C. A., Harrison, M.J., Adcroft, A., Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 22, 13910-13919. Doi:10.1029/2019GL085097   Liu, X., Stock, C.A., Dunne, J.P., Lee, M., Shevliakova, E., Malyshev, S., Milly, P.C.D (2021). Simulated Global Coastal Ecosystem Responses to a Half-Century Increase in River Nitrogen Loads.   Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., et al. (2020). Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO2. Journal of Advances in Modeling Earth Systems, 12, e2019MS002043. https://doi.org/10.1029/2019MS002043

1/8˚ resolution MOM6-COBALT daily physical and biogeochemical diagnostics for 2015

The files in this dataset contain daily mean chlorophyll (µg/kg), pH, nitrate (mol/kg), dissolved oxygen (mol/kg), potential temperature (˚C) and salinity model outputs for 2015 for the region between 20-55˚N, 135-111˚W. Data was extracted from a global grid run with coupled ocean-ice model configured using the Modular Ocean Model 6 (MOM6, <a href="https://github.com/NOAA-GFDL/MOM6">https://github.com/NOAA-GFDL/MOM6</a> ) and Sea Ice Simulator (SIS2) developed at the NOAA Geophysical Fluid Dynamics Laboratory (Adcroft et al., 2019). The horizontal resolution of the grid is 1/8˚, which is considered eddying and no eddy parameterization was included. Vertically, the model uses 75 hybrid vertical-sigma2 layer coordinates that is remapped onto 35 World Ocean Atlas/Coupled Model Intercomparison Project standard depth levels. The atmospheric forcing was derived from the Japanese 55-year Reanalysis version 1.5 (JRA55 1.5, <a href="https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55">https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55</a>). The model is driven by river freshwater runoff from a monthly climatology derived from Dai and Trenberth (2002) and Dai et al. (2009), which can be assessed at <a href="https://rda.ucar.edu/datasets/ds551.0/">https://rda.ucar.edu/datasets/ds551.0/</a>. A remapping scheme was used to add freshwater into the appropriate coastal grid cells near the river mouths. The biogeochemical model used was the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALTv2, Stock et al., 2020), which uses 33 tracers for representation of coupled elemental cycles of carbon, nitrogen, phosphorus, iron, silicon, alkalinity, oxygen and lithogenic matter and associated plankton food web dynamics. More details about the model setup are described in Liu et al. (2019) and Liu et al. (2021). This work was part of a PMEL-led project "A Pilot BGC Argo Float Array in the California Current Large Marine Ecosystem" funded by NOAA Research.   References:   Adcroft, A., Anderson, W., Blanton, C., Bushuk, M., Dufour, C.O., Dunne, J.P., Griffies, S.M. et al. (2019). The GFDL Global Ocean and Sea Ice Model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth System, doi: 10.1029/2019MS001726   Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, 2009: Changes in continental freshwater discharge from 1948-2004. J. Climate, 22, 2773-2791   Dai, A., and K. E. Trenberth, 2002: Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687   Liu, X., Dunne, J.P., Stock, C. A., Harrison, M.J., Adcroft, A., Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 22, 13910-13919. Doi:10.1029/2019GL085097   Liu, X., Stock, C.A., Dunne, J.P., Lee, M., Shevliakova, E., Malyshev, S., Milly, P.C.D (2021). Simulated Global Coastal Ecosystem Responses to a Half-Century Increase in River Nitrogen Loads.   Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., et al. (2020). Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO2. Journal of Advances in Modeling Earth Systems, 12, e2019MS002043. https://doi.org/10.1029/2019MS002043

1/8˚ resolution MOM6-COBALT daily physical and biogeochemical diagnostics for 2018

The files in this dataset contain daily mean chlorophyll (µg/kg), pH, nitrate (mol/kg), dissolved oxygen (mol/kg), potential temperature (˚C) and salinity model outputs for 2018 for the region between 20-55˚N, 135-111˚W. Data was extracted from a global grid run with coupled ocean-ice model configured using the Modular Ocean Model 6 (MOM6, <a href="https://github.com/NOAA-GFDL/MOM6">https://github.com/NOAA-GFDL/MOM6</a> ) and Sea Ice Simulator (SIS2) developed at the NOAA Geophysical Fluid Dynamics Laboratory (Adcroft et al., 2019). The horizontal resolution of the grid is 1/8˚, which is considered eddying and no eddy parameterization was included. Vertically, the model uses 75 hybrid vertical-sigma2 layer coordinates that is remapped onto 35 World Ocean Atlas/Coupled Model Intercomparison Project standard depth levels. The atmospheric forcing was derived from the Japanese 55-year Reanalysis version 1.5 (JRA55 1.5, <a href="https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55">https://jra.kishou.go.jp/JRA-55/index_en.html#jra-55</a>). The model is driven by river freshwater runoff from a monthly climatology derived from Dai and Trenberth (2002) and Dai et al. (2009), which can be assessed at <a href="https://rda.ucar.edu/datasets/ds551.0/">https://rda.ucar.edu/datasets/ds551.0/</a>. A remapping scheme was used to add freshwater into the appropriate coastal grid cells near the river mouths. The biogeochemical model used was the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALTv2, Stock et al., 2020), which uses 33 tracers for representation of coupled elemental cycles of carbon, nitrogen, phosphorus, iron, silicon, alkalinity, oxygen and lithogenic matter and associated plankton food web dynamics. More details about the model setup are described in Liu et al. (2019) and Liu et al. (2021). This work was part of a PMEL-led project "A Pilot BGC Argo Float Array in the California Current Large Marine Ecosystem" funded by NOAA Research.   References:   Adcroft, A., Anderson, W., Blanton, C., Bushuk, M., Dufour, C.O., Dunne, J.P., Griffies, S.M. et al. (2019). The GFDL Global Ocean and Sea Ice Model OM4.0: Model description and simulation features. Journal of Advances in Modeling Earth System, doi: 10.1029/2019MS001726   Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, 2009: Changes in continental freshwater discharge from 1948-2004. J. Climate, 22, 2773-2791   Dai, A., and K. E. Trenberth, 2002: Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687   Liu, X., Dunne, J.P., Stock, C. A., Harrison, M.J., Adcroft, A., Resplandy, L. (2019). Simulating Water Residence Time in the Coastal Ocean: A Global Perspective. Geophysical Research Letters, 46, 22, 13910-13919. Doi:10.1029/2019GL085097   Liu, X., Stock, C.A., Dunne, J.P., Lee, M., Shevliakova, E., Malyshev, S., Milly, P.C.D (2021). Simulated Global Coastal Ecosystem Responses to a Half-Century Increase in River Nitrogen Loads.   Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., et al. (2020). Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO2. Journal of Advances in Modeling Earth Systems, 12, e2019MS002043. https://doi.org/10.1029/2019MS002043

Stellar chromospheric activity spectral database of solar-type stars based on the LAMOST Low-Resolution Spectroscopic Survey(disused)

A stellar chromospheric activity spectral database of solar-type stars is constructed based on the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Low-Resolution Spectroscopic Survey (LRS). The database contains 1,330,654 high-quality LRS spectra of solar-type stars with Teff ranging from 4800 K to 6800 K. We measure the mean fluxes at line cores of the Ca II H&K lines using a 1 Å rectangular bandpass as well as a 1.09 Å full width at half maximum (FWHM) triangular bandpass, and the mean fluxes of two 20 Å pseudo-continuum bands on the two sides of the lines. Three chromospheric activity indexes, Srec using the rectangular bandpass, and Stri and SMWL using the triangular bandpass, are evaluated based on the measured fluxes. The uncertainties of all the obtained parameters are estimated. We also produce spectrum diagrams of Ca II H&K lines for all the spectra in the database. This database with more than one million high-quality LAMOST LRS spectra and basal chromospheric activity parameters can be further used for investigating activity characteristics of solar-type stars and solar-stellar connection.   The entity of the database is composed of (1) a catalog of spectral sample and activity parameters, and (2) a library of spectrum diagrams. (1) Catalog of Spectral Sample and Activity Parameters CaIIHK_Sindex_LAMOST_DR7_LRS.csv (2) Library of Spectrum Diagrams spectrum_diagrams_000-049.zip  (46 subfolders) spectrum_diagrams_050-099.zip  (40 subfolders) spectrum_diagrams_100-149.zip  (47 subfolders) spectrum_diagrams_150-199.zip  (49 subfolders) spectrum_diagrams_200-249.zip  (47 subfolders) spectrum_diagrams_250-299.zip  (45 subfolders) spectrum_diagrams_300-349.zip  (41 subfolders) spectrum_diagrams_350-399.zip  (39 subfolders) spectrum_diagrams_400-449.zip  (45 subfolders) spectrum_diagrams_450-499.zip  (35 subfolders) spectrum_diagrams_500-549.zip  (27 subfolders) spectrum_diagrams_550-599.zip  (38 subfolders) spectrum_diagrams_600-649.zip  (32 subfolders) spectrum_diagrams_650-699.zip  (26 subfolders) spectrum_diagrams_700-749.zip  (28 subfolders)

Stellar chromospheric activity spectral database of solar-type stars based on the LAMOST Low-Resolution Spectroscopic Survey (disused)

A stellar chromospheric activity spectral database of solar-type stars is constructed based on the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Low-Resolution Spectroscopic Survey (LRS). The database contains 1,330,654 high-quality LRS spectra of solar-type stars with effective temperature ranging from 4800 K to 6800 K. We measure the mean fluxes at line cores of the Ca II H&K lines using a 1 Å rectangular bandpass as well as a 1.09 Å full width at half maximum (FWHM) triangular bandpass, and the mean fluxes of two 20 Å pseudo-continuum bands on the two sides of the lines. Three chromospheric activity indexes, Srec based on the 1 Å rectangular bandpass, and Stri and SMWL based on the 1.09 Å FWHM triangular bandpass, are evaluated from the measured fluxes. The uncertainties of all the obtained parameters are estimated. We also produce spectrum diagrams of Ca II H&K lines for all the spectra in the database. This database with more than one million high-quality LAMOST LRS spectra and basal chromospheric activity parameters can be further used for investigating activity characteristics of solar-type stars and solar-stellar connection.   The entity of the database is composed of (1) a catalog of spectral sample and activity parameters, and (2) a library of spectrum diagrams. (1) Catalog of Spectral Sample and Activity Parameters CaIIHK_Sindex_LAMOST_DR7_LRS.csv (2) Library of Spectrum Diagrams spectrum_diagrams_000-049.zip  (46 subfolders) spectrum_diagrams_050-099.zip  (40 subfolders) spectrum_diagrams_100-149.zip  (47 subfolders) spectrum_diagrams_150-199.zip  (49 subfolders) spectrum_diagrams_200-249.zip  (47 subfolders) spectrum_diagrams_250-299.zip  (45 subfolders) spectrum_diagrams_300-349.zip  (41 subfolders) spectrum_diagrams_350-399.zip  (39 subfolders) spectrum_diagrams_400-449.zip  (45 subfolders) spectrum_diagrams_450-499.zip  (35 subfolders) spectrum_diagrams_500-549.zip  (27 subfolders) spectrum_diagrams_550-599.zip  (38 subfolders) spectrum_diagrams_600-649.zip  (32 subfolders) spectrum_diagrams_650-699.zip  (26 subfolders) spectrum_diagrams_700-749.zip  (28 subfolders)

Stellar chromospheric activity spectral database of solar-type stars based on the LAMOST Low-Resolution Spectroscopic Survey(disused)

A stellar chromospheric activity spectral database of solar-type stars is constructed based on the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Low-Resolution Spectroscopic Survey (LRS). The database contains 1,330,654 high-quality LRS spectra of solar-type stars with effective temperature ranging from 4800 K to 6800 K. We measure the mean fluxes at line cores of the Ca II H&K lines using a 1 Å rectangular bandpass as well as a 1.09 Å full width at half maximum (FWHM) triangular bandpass, and the mean fluxes of two 20 Å pseudo-continuum bands on the two sides of the lines. Three chromospheric activity indexes, Srec based on the 1 Å rectangular bandpass, and Stri and SMWL based on the 1.09 Å FWHM triangular bandpass, are evaluated from the measured fluxes. The uncertainties of all the obtained parameters are estimated. We also produce spectrum diagrams of Ca II H&K lines for all the spectra in the database. This database with more than one million high-quality LAMOST LRS spectra and basal chromospheric activity parameters can be further used for investigating activity characteristics of solar-type stars and solar-stellar connection.   The entity of the database is composed of (1) a catalog of spectral sample and activity parameters, and (2) a library of spectrum diagrams. (1) Catalog of Spectral Sample and Activity Parameters CaIIHK_Sindex_LAMOST_DR7_LRS.csv (2) Library of Spectrum Diagrams spectrum_diagrams_000-049.zip  (46 subfolders) spectrum_diagrams_050-099.zip  (40 subfolders) spectrum_diagrams_100-149.zip  (47 subfolders) spectrum_diagrams_150-199.zip  (49 subfolders) spectrum_diagrams_200-249.zip  (47 subfolders) spectrum_diagrams_250-299.zip  (45 subfolders) spectrum_diagrams_300-349.zip  (41 subfolders) spectrum_diagrams_350-399.zip  (39 subfolders) spectrum_diagrams_400-449.zip  (45 subfolders) spectrum_diagrams_450-499.zip  (35 subfolders) spectrum_diagrams_500-549.zip  (27 subfolders) spectrum_diagrams_550-599.zip  (38 subfolders) spectrum_diagrams_600-649.zip  (32 subfolders) spectrum_diagrams_650-699.zip  (26 subfolders) spectrum_diagrams_700-749.zip  (28 subfolders)

Project files provided as supporting information to the manuscript "Information-theoretical measures identify accurate low-resolution representations of protein configurational space"

The dataset contains the following compressed folder: -Notebooks.zip: This folder contains:   -python_script:         -RESREL.py: script performing the clusterization and computing the relevance resolution curves         -random_curves.py: script generating the random value and computing the corresponding RES-REV curves_s         -Cluster_distance_matrix.py: script returning the distance among clusters for a given partition.   -python_notebook:         -Exploratory_analysis.ipynb:  Analysis performed on the 12-protein_dataset         -DMAPS_ANTI.ipynb: Diffusion Map for the Antibody         -DMAPS_COV_1ake.ipynb: Diffusion Map + Inter-Intra state decomposition of covariance for 1ake Packages required for the usage of these python scripts/notebooks:   -numpy   -pandas   -matplotlib   -seaborn   -multiprocessing   -scipy   ======== RAW DATA ======== The raw data produced and employed in this study are available on a Google Drive folder at the following address: https://drive.google.com/drive/folders/1PasAUCgpR5-gdzUVEdyusgZIayQN0Le9 In this folder, together with the compressed Notebooks.zip folder, one can fin the compressed folder Data.zip, within which the following data are present: -12-protein_dataset:     -md.mdp: the .mdp file used in the MD simulations     -PROTEIN_PDB_CODE:         -Hk_{sel}.npy & Hs_{sel}.npy: the Rel & Res curves, sel=[all, CA, CB]         -RMSD_{sel}.npy: the RMSD matrix, sel=[all, CA, CB]         -npt.gro:protein+water+ions structure @TEO the equilibration (NVT+NPT)         -MSR_df.csv: a dataset containing the following columns                   'area' : area behind the Relevance-Resolution curve;                   'selection': the atomic selection (['all', 'CA', 'CB']) used to compute the RMSD matrix used for the clusterization (and consequently the Relevance-Resolution curves)                   'method': the linkage measure used in the clustering procedure, an integer in [0,6];                   'method_name': the linkage measure used in the clustering procedure, a string in ['average','ward','complete','single','centroid','median','weighted'];                   'rmsd_mean': the mean value of the rmsd vector along the trajectory computed wrt the first frame;                   'rmsd_var': the variance of the rmsd vector along the trajectory computed wrt the first frame;                   'rgy_mean': the mean value of the radius of gyration  along the trajectory;                   'rgy_var': the variance of the radius of gyration  along the trajectory;                   'rmsf_mean': the mean value of the rmsf;                   'rmsf_var': the variance of the rmsf;                   'RMSD_M_mean': the mean value of the RMSD matrix.                   'RMSD_M_var': the variance of the RMSD matrix.   -Random:     -curves.npy= 100K Relevance-Resolution Random curves for M=40001     -curves_s.npy= 100K Relevance-Resolution Random curves for M=15000   -validation_dataset:     -antibody:         -Hk_CB.npy & Hs_CB.npy: the Rel & Res curves         -RMSD_CB.npy: the RMSD matrix         -DIFF_{M}.npy: the eigenvalue/vector of the 10-D diffusion space         -Label_{method}.npy: the label vector for n_clusters     -1ake:         -Hk_{sel}.npy & Hs_{sel}.npy: the Rel & Res curves         -RMSD_{sel}.npy: the RMSD matrix         -DIFF_{M}.npy: the eigenvalue/vector of the 10-D diffusion space         -Label_{method}.npy: the label vector for n_clusters         -intra_{m}.npy: the intra-cluster covariance matrix         -inter_cov_{m}.npy: the inter-cluster correlation matrix   NOTE ===== The matrices of the cluster distances for adenylate kinase and antibody have been computed through the script Cluster_distance_matrix.py. These matrices have not been included in the dataset because of their large size; the raw data are however available upon request.

opencc-zeroMay 2022View details →

dryad36/100

Application of inverse theory for high spatial resolution reconstructions of thermospheric vector wind fields from Doppler shifts measured by a ground-based network of all-sky Fabry-Perot interferometers

Several types of all-sky viewing Fabry-Perot Interferometers (FPI) have been developed since the 1990s for ground-based remote sensing of thermospheric winds. The Scanning Doppler Imager (SDI) is one such instrument, which provides temporally simultaneous line-of-sight observations from hundreds of independent look directions per instrument exposure. A geographically distributed network of such instruments increases spatial coverage and, at many locations, also provides overlapping observations along multiple independent lines-of-sight. Together, these characteristics significantly increase the density and fidelity that is possible for reconstructed thermospheric vector wind fields, compared to a traditional narrow-field FPI, but at the cost of complexity and difficulty. Presently, we describe an application of inverse theory to reconstruct three-component vector thermospheric neutral wind fields using data from multiple SDI instruments. The salient features of the method used here are the ability to reconstruct three-component winds on a dense grid that is sampled regularly in latitude, longitude, and time, without assuming any a-priori underlying structure of the winds. This requires solving an inverse problem that does not in general yield a unique solution unless additional constraints are enforced. We describe this step, also known also as regularization, along with the strategy used to maximize the spatial resolution of the derived wind fields by automatically determining the minimum level of regularization that can produce stable inversions. We present example results obtained from applying this technique to one night of data from a network of SDIs in Alaska, and discuss the implications of these results for current understanding of thermospheric dynamics.

dryad36/100

Crowd-sourced SfM: Best practices for high resolution monitoring of coastal cliffs and bluffs

Digital oblique photos of an approximately 2.0 km alongshore reach of seaward-facing coastal bluff faces on the Strait of Juan de Fuca, Washington State, were collected at least quarterly between 2016 and 2022. In total over 3900 photos were collected over 38 separate surveys. The photos were collected to support digital surface reconstructions using Structure-from-Motion (SfM) photogrammetry, and specifically to assess the quality of surfaces generated with photos collected using relatively simple techniques that could be accessible to community science programs. A secondary goal was to use the photos, and the digital surfaces generated with them, to evaluate patterns and rates of erosion on the bluff face.

opencc-zeroMay 2022View details →

Dataset for "Quantifying the physical impact of bottom trawling based on high-resolution bathymetric data"

Bathymetric point cloud data and ship log data used for the article "Quantifying the physical impact of bottom trawling based on high-resolution bathymetric data" by Mischa Schönke, David Clemens and Peter Feldens (<a href="https://doi.org/10.3390/rs14122782">https://doi.org/10.3390/rs14122782</a>)

Auxiliary Euro-Calliope datasets: Spatial data to represent a European energy system model at several spatial resolutions

Main output generated with the <a href="https://github.com/brynpickering/possibility-for-electricity-autarky/tree/custom-regions">custom-region possibility-for-electricity-autarky</a> workflow. This output provides similar data to <a href="https://doi.org/10.5281/zenodo.3246302">https://doi.org/10.5281/zenodo.3246302</a> (technically eligible land area for renewables and other spatially disaggregated energy system data), but with two key differences: <ol> <li>The spatial extent has been expanded to include Iceland.</li> <li>Two new spatial resolutions have been added: `ehighways` and `ehighways_disaggregated`.</li> </ol> `ehighways` defines 98 regions based on the result of work undertaken in the European Commission Seventh Framework Programme project e-HIGHWAY 2050 [1]. The regions cover 35 European countries; 19 are described at a national resolution and the rest at a subnational resolution. Those at a subnational resolution are aggregated from NUTS3-2006 statistical units. `ehighways_disaggregated` provides the data at the resolution of statistical units in Europe, which is then aggregated to produce the data at the `ehighways` resolution. The mapping from statistical units to ehighways regions is defined in `./ehighways/statistical_units_to_ehighways_regions.csv`. `./ehighways/units.png` shows a map of the resulting 98 `ehighways` regions. The region colours are used to help differentiate regions and have no other meaning. This dataset is used as an input to the <a href="https://github.com/calliope-project/sector-coupled-euro-calliope">Sector-Coupled Euro-Calliope workflow</a>. [1] Anderski, T., Surmann, Y., Stemmer, S., Grisey, N., Momot, E., Leger, A.-C., Betraoui, B., and van Roy, P. (2014). European cluster model of the Pan-European transmission grid (e-HIGHWAY 2050)

opencc-by-4.0Mar 2021View details →

LS-500: Global 500m-resolution Cropland Suitability

LS-500 is a global cropland suitability dataset at the highest-ever resolution of 500 m (18 arcsec) developed from a brand-new cropland extent data. The data incorporated the topographical effects on the cropland growth by using recently developed digital elevation model. Cropland suitability with the distinction of irrigation, i.e. the suitability of crop cultivation in a natural condition was also estimated and archived in the dataset. Please refer to the following published paper for the detailed description and the methodology. Ishikawa Y., & Yamazaki D. Global high-resolution estimation of cropland suitability and its comparative analysis to actual cropland distribution, Hydrological Research Letters, 15(2), 9-15. 2021. https://doi.org/10.3178/hrl.15.9

opencc-by-4.0Jun 2022View details →

CryoGridLite: Model output of pan-Arctic simulations at 1° resolution from 1700 to 2020

CryoGridLite is a lightweight version of the more complex and process-rich CryoGrid Community model (<a href="https://gmd.copernicus.org/preprints/gmd-2022-127/">Westermann et al. 2022</a>). This archive contains the following output datasets which were produced by the model. <code>./SETUP.zip</code> The parameters varied in the ensemble simulations. <code>./RESULTS.zip</code> The output variables. An overview of the output variables is provided below and in the README.md file of the archived code. The model code can be found here: <a href="https://zenodo.org/record/6619537">10.5281/zenodo.6619537</a> Input data required for pan-Arctic simulations can be found here: <a href="https://zenodo.org/record/6619212">10.5281/zenodo.6619212</a> <table> <thead> <tr> <th>Variable</th> <th>Coordinates</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td>H_lat_sum</td> <td>(tile, time, longitude, latitude)</td> <td>Total latent heat content in the entire ground column (550m) [J/m²]</td> </tr> <tr> <td>H_sen_sum</td> <td>(tile, time, longitude, latitude)</td> <td>Total sensible heat content in the entire ground column (550m) [J/m²]</td> </tr> <tr> <td>H_tot_sum</td> <td>(tile, time, longitude, latitude)</td> <td>Total heat content in the entire ground column (550m) [J/m²]</td> </tr> <tr> <td>H_lat_50m</td> <td>(tile, time, longitude, latitude)</td> <td>Total latent heat content in the uppermost 50m of the ground column [J/m²]</td> </tr> <tr> <td>H_sen_50m</td> <td>(tile, time, longitude, latitude)</td> <td>Total sensible heat content in the uppermost 50m of the ground column [J/m²]</td> </tr> <tr> <td>H_tot_50m</td> <td>(tile, time, longitude, latitude)</td> <td>Total heat content in the uppermost 50m of the ground column [J/m²]</td> </tr> <tr> <td>ThawedGround_10m</td> <td>(tile, time, longitude, latitude)</td> <td>Maximum vertically integrated depth of thawed ground (T>0°C) in the uppermost 10m of the ground column [m]</td> </tr> <tr> <td>T_av_all</td> <td>(tile, time, longitude, latitude, depth)</td> <td>Mean annual ground temperature [°C]</td> </tr> <tr> <td>T_min_all</td> <td>(tile, time, longitude, latitude, depth)</td> <td>Minimum annual ground temperature [°C]</td> </tr> <tr> <td>T_max_all</td> <td>(tile, time, longitude, latitude, depth)</td> <td>Maximum annual ground temperature [°C]</td> </tr> <tr> <td>LandArea</td> <td>(latitude, longitude)</td> <td>Total area covered by land within the model grid cell [km²]</td> </tr> </tbody> </table>