Merge branch 'main' into mean_clim_upgrade_lee1043_20240812

README.md

@@ -40,7 +40,8 @@ The package expects model data to be [CF-compliant](http://cfconventions.org/).
 Documentation
 -------------
 
-**Getting Started**
+### Getting Started
+
 
 * Installation requirements and instructions are available on the [Install](http://pcmdi.github.io/pcmdi_metrics/install.html) page
 
@@ -51,7 +52,7 @@ Documentation
 * [View Demo](https://github.com/PCMDI/pcmdi_metrics/blob/main/doc/jupyter/Demo/README.md)
 
 
-**References**
+### References
 
 Latest: 
 
@@ -275,6 +276,22 @@ Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/d
 
 This project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification.
 
+## Disclaimer
+This document was prepared as an account of work sponsored by an
+agency of the United States government. Neither the United States government
+nor Lawrence Livermore National Security, LLC, nor any of their employees
+makes any warranty, expressed or implied, or assumes any legal liability or
+responsibility for the accuracy, completeness, or usefulness of any
+information, apparatus, product, or process disclosed, or represents that its
+use would not infringe privately owned rights. Reference herein to any specific
+commercial product, process, or service by trade name, trademark, manufacturer,
+or otherwise does not necessarily constitute or imply its endorsement,
+recommendation, or favoring by the United States government or Lawrence
+Livermore National Security, LLC. The views and opinions of authors expressed
+herein do not necessarily state or reflect those of the United States
+government or Lawrence Livermore National Security, LLC, and shall not be used
+for advertising or product endorsement purposes.
+
 
 
 

doc/jupyter/Demo/Demo_0_download_data.ipynb

@@ -130,7 +130,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "pmp_devel_20241106_xcdat0.7.3",
+   "display_name": "pmp_devel_20241202",
    "language": "python",
    "name": "python3"
   },

doc/jupyter/Demo/Demo_1a_compute_climatologies.ipynb

@@ -13,6 +13,14 @@
    "id": "de63a73f",
    "metadata": {},
    "source": [
+    "This notebook introduces PCDMI mean climate driver.\n",
+    "\n",
+    "**Reference**\n",
+    "\n",
+    "* Gleckler, P. J., Taylor, K. E., and Doutriaux, C.: Performance metrics for climate models, J. Geophys. Res., 113, D06104, https://doi.org/10.1029/2007jd008972, 2008. \n",
+    "\n",
+    "* Lee, J., Gleckler, P. J., Ahn, M.-S., Ordonez, A., Ullrich, P. A., Sperber, K. R., Taylor, K. E., Planton, Y. Y., Guilyardi, E., Durack, P., Bonfils, C., Zelinka, M. D., Chao, L.-W., Dong, B., Doutriaux, C., Zhang, C., Vo, T., Boutte, J., Wehner, M. F., Pendergrass, A. G., Kim, D., Xue, Z., Wittenberg, A. T., and Krasting, J.: Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3, Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, 2024.\n",
+    "\n",
     "Model output and observations must be converted into annual climatologies for use with the mean climate driver. This has already been done for the observations provided by PCMDI. PMP provides a script for generating these input climatologies from other data. For more information about using the script, see [the documentation](https://github.com/PCMDI/pcmdi_metrics/tree/main/sample_setups/pcmdi_parameter_files/mean_climate/make_clims). The basic use is shown here:   \n",
     "```\n",
     "python pcmdi_compute_climatologies.py \\  \n",

doc/jupyter/Demo/Demo_1b_mean_climate.ipynb

@@ -2563,7 +2563,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### Land/sea masks  \n",
+    "### Land/sea masks  \n",
     "Land/Sea masking is required for some regions (e.g. \"land\"). This is controlled by variables `sftlf_filename_template` and `generate_sftlf`. The metrics package expects the land/sea mask files to be located with the model data under a fixed field variable ('fx') with a file name that follows the pattern in `sftlf_filename_template`. The example data does not come with a land/sea mask, so we set `generate_sftlf` to `True` in the basic parameter file to have the PMP generate a land/sea mask where 0 represents ocean and 100 represents land."
    ]
   },

doc/jupyter/Demo/Demo_6_ENSO.ipynb

@@ -13,9 +13,13 @@
    "id": "161973d0",
    "metadata": {},
    "source": [
-    "This notebook provides an overview of running the [ENSO Metrics package](https://github.com/CLIVAR-PRP/ENSO_metrics) through the PMP. More information can be found in the [README]( ). Example parameter files are located in the [PMP sample setups]( ). \n",
+    "This notebook provides an overview of running the [ENSO Metrics package](https://github.com/CLIVAR-PRP/ENSO_metrics) through the PMP.\n",
     "\n",
-    "**Reference**: Planton, Y., E. Guilyardi, A. T. Wittenberg, J. Lee, P. J. Gleckler, T. Bayr, S. McGregor, M. J. McPhaden, S. Power, R. Roehrig, A. Voldoire, 2020: Evaluating El Niño in climate models with the CLIVAR 2020 ENSO metrics package. Bulletin of the American Meteorological Society. [doi: 10.1175/BAMS-D-19-0337.1](https://doi.org/10.1175/BAMS-D-19-0337.1)\n",
+    "**Reference**\n",
+    "\n",
+    "* Planton, Y., E. Guilyardi, A. T. Wittenberg, J. Lee, P. J. Gleckler, T. Bayr, S. McGregor, M. J. McPhaden, S. Power, R. Roehrig, A. Voldoire, 2020: Evaluating El Niño in climate models with the CLIVAR 2020 ENSO metrics package. Bulletin of the American Meteorological Society. [doi: 10.1175/BAMS-D-19-0337.1](https://doi.org/10.1175/BAMS-D-19-0337.1)\n",
+    "\n",
+    "* Lee, J., P. J. Gleckler, M.-S. Ahn, A. Ordonez, P. Ullrich, K. R. Sperber, K. E. Taylor, Y. Y. Planton, E. Guilyardi, P. Durack, C. Bonfils, M. D. Zelinka, L.-W. Chao, B. Dong, C. Doutriaux, C. Zhang, T. Vo, J. Boutte, M. F. Wehner, A. G. Pendergrass, D. Kim, Z. Xue, A. T. Wittenberg, and J. Krasting, 2024: Systematic and Objective Evaluation of Earth System Models: PCMDI Metrics Package (PMP) version 3. Geoscientific Model Development, 17, 3919–3948, [doi: 10.5194/gmd-17-3919-2024](https://doi.org/10.5194/gmd-17-3919-2024)\n",
     "\n",
     "Description for individual metrics can be found at https://github.com/CLIVAR-PRP/ENSO_metrics/wiki."
    ]