update descriptions

Author: jtmims

diagnostics/mar/SST_bias_NOAA_OISSTv2/SST_bias_NOAA_OISSTv2.html

@@ -1,25 +1,16 @@
-<title>MDTF example-multicase diagnostic</title>
+<title>Sea Surface Temperature Bias - NOAA OISSTv2</title>
 <img src="../mdtf_diag_banner.png">
-<h3>Multi-Case Example Diagnostic: zonal-average near-surface temperature anomaly</h3>
+<h3>MAR Diagnostic notebook: Sea Surface Temperature Bias - NOAA OISSTv2</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.
+    This notebook plots the SST bias of a model simulation vs. climataology derived from NOAA OISSTv2    
+    Authors: Xinru Li and John Krasting
 </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)
+        <TH align=left>SST bias
 </TABLE>
 <!-- update the name of the template to [your_pod_name]_ipynb.html -->
 <TH align=center><A href=SST_bias_NOAA_OISSTv2_ipynb.html>notebook</A>

diagnostics/mar/SST_bias_NOAA_OISSTv2/SST_bias_NOAA_OISSTv2.ipynb

@@ -252,7 +252,7 @@
    "metadata": {},
    "source": [
     "ds = momgrid.Gridset(filelist, force_symmetric=True, return_corners=True)\n",
-    "model_type = ds.model\n",
+    "model_type = tos_subset.df['source_id'][0] #this will need to be worked through with MAR team\n",
     "ds = ds.data.sel(time=slice(f\"{str(start).zfill(4)}-01-01\",f\"{str(end).zfill(4)}-12-31\"))"
    ],
    "outputs": [],
@@ -289,7 +289,7 @@
    "id": "3f322d2e-1c88-479f-86c7-5910d71cf3f9",
    "metadata": {},
    "source": [
-    "model_type = 'om5'\n",
+    "\n",
     "if \"om4\" in model_type:\n",
     "    dsobs = xr.open_dataset(\"/archive/John.Krasting/NOAA_OISST_v2_annual_mean_1993-2017_OM4.nc\", use_cftime=True)\n",
     "elif \"om5\" in model_type:\n",

diagnostics/mar/SST_bias_NOAA_OISSTv2/settings.jsonc

@@ -1,10 +1,10 @@
 {
   "settings" : {
     "driver" : "SST_bias_NOAA_OISSTv2.ipynb",
-    "long_name" : "Example diagnostic",
+    "long_name" : "Sea Surface Temperature Bias - NOAA OISSTv2",
     "convention": "gfdl",
     "mar": true,
-    "description" : "Example diagnostic",
+    "description" : "This notebook plots the SST bias of a model simulation vs. climataology derived from NOAA OISSTv2",
     "runtime_requirements": {
         "python3": ["matplotlib", "xarray", "netCDF4"]
     }