Merge branch 'NOAA-GFDL:main' into container

data/fieldlist_GFDL.jsonc

@@ -20,15 +20,15 @@
       "standard_name": "latitude",
       "units": "degrees_north"
     },
-    "yh": {
+    "xq": {
       "axis": "Y",
-      "standard_name": "h_point_nominal_longitude",
+      "standard_name": "q_point_nominal_latitude",
       "long_name": "h point nominal latitude",
       "units": "degrees_north"
     },
-    "xq": {
+    "xh": {
       "axis": "X",
-      "standard_name": "x_point_nominal_latitude",
+      "standard_name": "h_point_nominal_latitude",
       "long_name": "x point nominal latitude",
       "units": "degrees_north"
     },
@@ -96,8 +96,8 @@
     }
   },
   "variables" : {
-    "$ref": "./gfdl-cmor-tables/gfdl_to_cmip6_vars.json",
-    "$ref": "./gfdl-cmor-tables/gfdl_to_cmip5_vars.json",
+    //"$ref": "./gfdl-cmor-tables/gfdl_to_cmip6_vars.json",
+    //"$ref": "./gfdl-cmor-tables/gfdl_to_cmip5_vars.json",
 
     "areacello": {
       "standard_name": "cell_area",

diagnostics/SM_ET_coupling/settings.jsonc

@@ -8,7 +8,6 @@
   "settings" : {
     "driver" : "SM_ET_coupling.py",
     "long_name" : "Coupling between Soil Moisture and EvapoTranspiration",
-    "realm" : ["atmos", "land"],
     "convention" : "cmip",
     "description" : "Coupling of Soil Moisture with Evapotranspiration",
     "runtime_requirements": {

diagnostics/example_notebook/doc/example_notebook.rst

@@ -0,0 +1,53 @@
+Multi-Case Example Diagnostic Documentation
+===========================================
+
+Last update: Apr 2024
+
+This POD illustrates how multiple cases (experiments) can be analyzed together. The
+muliple cases are specified to the MDTF Framework where they are initialized and
+preprocessed independently.
+
+.. note::
+  This POD assumes familiarity with the single-case example diagnostic
+
+Version & Contact info
+----------------------
+
+- Version/revision information: version 1.1 (Oct 2022)
+- Model Development Task Force Framework Team
+
+Open source copyright agreement
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+The MDTF framework is distributed under the LGPLv3 license (see LICENSE.txt).
+Unless you've distributed your script elsewhere, you don't need to change this.
+
+Functionality
+-------------
+The framework generates yaml file called *case_info.yml* with environment variables
+for the file paths and variable information for each case. The **example_multicase** POD reads the yaml file
+information into a dictionary, and loops through the dictionary to read near-surface air temperature (TAS) data
+for each case. The POD time averages the data and calculates the anomaly relative to the global mean.
+The anomalies are zonally-averaged and the results from all cases are shown on a single plot.
+
+Required programming language and libraries
+-------------------------------------------
+
+* Python >= 3.12
+* xarray
+* numpy
+* matplotlib
+* yaml
+* sys
+
+Required model output variables
+-------------------------------
+
+* tas - Surface (2-m) air temperature (CF: air_temperature)
+
+References
+----------
+
+1. E. D. Maloney et al. (2019): Process-Oriented Evaluation of Climate and
+Weather Forecasting Models. *BAMS*, **100** (9), 1665–1686,
+`doi:10.1175/BAMS-D-18-0042.1 <https://doi.org/10.1175/BAMS-D-18-0042.1>`__.

diagnostics/example_notebook/example_notebook.html

@@ -0,0 +1,31 @@
+<title>MDTF example-multicase diagnostic</title>
+<img src="../mdtf_diag_banner.png">
+<h3>Multi-Case Example Diagnostic: zonal-average near-surface temperature anomaly</h3>
+<p>
+    This POD illustrates how multiple cases (experiments) can be analyzed together.
+    The MDTF-diagnostics framework initializes and processes each case, writes the environment variables for the cases
+    to a yaml file (case_info.yml), and exports an ESM Intake catalog with information about the post-processed
+    data for each ease to the working directory (WORK_DIR). The example_multicase POD driver script reads
+    environment information from case_info.yml into a dictionary that it references to read data from the
+    post-processed files in the data catalog.
+</p>
+<p>
+    The example_multicase POD reads near-surface air temperature (TAS) from netcdf output files for multiple cases.
+    The POD time averages the TAS data and calculates the anomaly relative to the global mean.
+    The anomalies are zonally-averaged and the results from all cases are shown on a single plot.
+</p>
+<TABLE>
+    <TR>
+        <TH align=left style="color:navy;">Time averages
+        <TH align=left>Model Results
+    <TR>
+        <TH align=left>Zonal-mean near-surface temperature anomalies (K)
+</TABLE>
+<!--
+  If the POD generates one figure per case, use the following format in your python script file paths:
+  <TH align=center><A href=model/example_model_plot_{{CASENAME}}.png>{{CASENAME}}</A>
+  The framework output manager will automatically append a link to each file
+-->
+<TH align=center><A href=model/example_multicase_plot.png>plot</A>
+<!-- update the name of the template to [your_pod_name]_ipynb.html -->
+<TH align=center><A href=example_notebook_ipynb.html>notebook</A>