Merge pull request #1035 from PCMDI/docs_update_lee1043

Docs update
PCMDI · Jan 30, 2024 · 0a3529b · 0a3529b
2 parents 4cce53c + 909c05b
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diff --git a/docs/metrics.rst b/docs/metrics.rst
@@ -12,11 +12,11 @@ A suite of demo scripts and interactive Jupyter notebooks are provided with `thi
  :maxdepth: 1
 
  metrics_mean-clim
- subdaily-precipitation
- metrics_mov
  metrics_enso
+ metrics_mov
  metrics_mjo
  metrics_monsoon
  metrics_ext
  metrics_precip-variability
- metrics_precip-distribution
+ metrics_precip-distribution
+ metrics_subdaily-precipitation
diff --git a/docs/metrics_enso.rst b/docs/metrics_enso.rst
@@ -20,7 +20,7 @@ Demo
 * `PMP demo Jupyter notebook`_
 
 Results
-=========
+=======
 * `Interactive graphics for PMP-calculated ENSO Metrics`_
 * `Description for included metrics`_
 * `Description for the results`_

diff --git a/docs/metrics_mean-clim.rst b/docs/metrics_mean-clim.rst
@@ -22,6 +22,11 @@ Each of these steps is included in the
 along with a series of examples that demonstrate the options. 
 These steps are also summarized below.
 
+Demo
+====
+* `PMP demo Jupyter notebook1a`_ (Compute climatologies)
+* `PMP demo Jupyter notebook1b`_ (Run mean climate driver)
+
 
 Observational climatologies
 ###########################
@@ -102,3 +107,6 @@ In addition to the minimum set of parameters noted above, the following **additi
 * **save_test_clims** Select to save (or not) interpolated climatologies including masking
 * **case_id** Save JSON and netCDF files into a subdirectory so that results from multiple tests can be readily organized
 
+.. _PMP demo Jupyter notebook1a: https://github.com/PCMDI/pcmdi_metrics/blob/main/doc/jupyter/Demo/Demo_1a_compute_climatologies.ipynb
+.. _PMP demo Jupyter notebook1b: https://github.com/PCMDI/pcmdi_metrics/blob/main/doc/jupyter/Demo/Demo_1b_mean_climate.ipynb
+
diff --git a/docs/metrics_monsoon.rst b/docs/metrics_monsoon.rst
@@ -11,9 +11,13 @@ The PMP currently can be used to produce baseline metrics on the overall evoluti
 
 These evolution results are based on the work of Sperber and Annamalai (2014). Climatological pentads of precipitation in observations and CMIP5 for six monsoon-related domains (AIR: All-India Rainfall, AUS: Australian Monsoon, GoG: Gulf of Guinea, NAM: North American Monsoon, SAM: South American Monsoon, and Sahel). In the Northern Hemisphere the 73 climatological pentads run from January-December, while in the Southern Hemisphere the climatological pentads run from July-June. For each domain the precipitation is accumulated at each subsequent pentad and then divided by the total precipitation to give the fractional accumulation of precipitation as a function of pentad. Except for GoG, onset (decay) of monsoon occurs for a fractional accumulation of 0.2 (0.8). Between these fractional accumulations the accumulation of precipitation is nearly linear as the monsoon season progresses.
 
-
+Demo
+====
+* `PMP demo Jupyter notebook`_
 
 References
 ==========
+* Sperber, K.R. and Annamalai, H., 2014. The use of fractional accumulated precipitation for the evaluation of the annual cycle of monsoons. Climate Dynamics, 43, 3219-3244, doi:10.1007/s00382-014-2099-3
+
+.. _PMP demo Jupyter notebook: https://github.com/PCMDI/pcmdi_metrics/blob/main/doc/jupyter/Demo/Demo_2b_monsoon_sperber.ipynb
 
-Sperber, K.R. and Annamalai, H., 2014. The use of fractional accumulated precipitation for the evaluation of the annual cycle of monsoons. Climate Dynamics, 43, 3219-3244, doi:10.1007/s00382-014-2099-3
diff --git a/docs/metrics_precip-distribution.rst b/docs/metrics_precip-distribution.rst
@@ -13,7 +13,7 @@ Demo
 In preparation
 
 Example parameter files
-======================
+=======================
 A set of example parameter files for models and observations can be viewed at `this link`_.
 
 Required data sets 

diff --git a/docs/metrics_precip-variability.rst b/docs/metrics_precip-variability.rst
@@ -13,7 +13,7 @@ Demo
 * `PMP demo Jupyter notebook`_
 
 Example parameter files
-======================
+=======================
 A set of example parameter files for models and observations can be viewed at `this link`_.
 
 Required data sets 

diff --git a/docs/subdaily-precipitation.rst → docs/metrics_subdaily-precipitation.rst b/docs/subdaily-precipitation.rst → docs/metrics_subdaily-precipitation.rst
@@ -11,14 +11,17 @@ The PMP can be used to compare observed and simulated sub-daily precipitation, i
 
 Analysis of higher frequency data often includes multiple stages of processing. `The flow diagram of the PMP's sub-daily precipitation <https://github.com/PCMDI/pcmdi_metrics/blob/master/doc/Diurnal%20Cycle%20Diagram.pdf>`_ shows that is the case here. Each of the steps highlighted in the flow diagram are included in `the diurnal cycle and intermittency Jupyter notebook demo <https://github.com/PCMDI/pcmdi_metrics/blob/master/doc/jupyter/Demo/Demo_3_diurnal_cycle.ipynb>`_. 
 
+Demo
+====
+* `PMP demo Jupyter notebook`_
 
 References
 ==========
+* Covey, C, PJ Gleckler, C Doutriaux, DN Williams, A Dai, J Fasullo, K Trenberth, and A Berg. 2016. ”Metrics for the diurnal cycle of precipitation: Toward routine benchmarks for climate models.” Journal of Climate 29(12): 4461–4471, https://doi.org/10.1175/JCLI-D-15-0664.1
+* Covey, C, C Doutriaux, PJ Gleckler, KE Taylor, KE Trenberth, and Y Zhang. 2018. “High-frequency intermittency in observed and model-simulated precipitation.” Geophysical Research Letters 45(22): 12514–12522, https://doi.org/10.1029/2018GL078926
+* Dai, A. 2006. “Precipitation characteristics coupled climate models.” Journal of Climate 19(18): 4605–4630, https://doi.org/10.1175/JCLI3884.1
+* Trenberth, KE, Y Zhang, and M Gehne. 2017. ”Intermittency in precipitation: Duration, frequency, intensity, and amounts using hourly data.” Journal of Hydrometeorology 18(5): 1393–1412, https://doi.org/10.1175/JHM-D-16-0263.1
 
-Covey, C, PJ Gleckler, C Doutriaux, DN Williams, A Dai, J Fasullo, K Trenberth, and A Berg. 2016. ”Metrics for the diurnal cycle of precipitation: Toward routine benchmarks for climate models.” Journal of Climate 29(12): 4461–4471, https://doi.org/10.1175/JCLI-D-15-0664.1
 
-Covey, C, C Doutriaux, PJ Gleckler, KE Taylor, KE Trenberth, and Y Zhang. 2018. “High-frequency intermittency in observed and model-simulated precipitation.” Geophysical Research Letters 45(22): 12514–12522, https://doi.org/10.1029/2018GL078926
 
-Dai, A. 2006. “Precipitation characteristics coupled climate models.” Journal of Climate 19(18): 4605–4630, https://doi.org/10.1175/JCLI3884.1
-
-Trenberth, KE, Y Zhang, and M Gehne. 2017. ”Intermittency in precipitation: Duration, frequency, intensity, and amounts using hourly data.” Journal of Hydrometeorology 18(5): 1393–1412, https://doi.org/10.1175/JHM-D-16-0263.1
+.. _PMP demo Jupyter notebook: https://github.com/PCMDI/pcmdi_metrics/blob/main/doc/jupyter/Demo/Demo_3_diurnal_cycle.ipynb