Update CI pages

Author: matamadio

docs/_toc.yml

@@ -19,7 +19,7 @@ parts:
         - file: docs/global-exposure
         - file: docs/global-vulnerability
         - file: docs/disaster-data
-        - file: docs/climate-data
+        - file: docs/climate-indices
         - file: docs/rdl
         - file: docs/external-data
   - caption: Disaster Risk Analytics

docs/climate-data.md

@@ -1,36 +1,9 @@
 # Climate indices
 
-The climate component offers an overview of climate indices related to hydro-meteorological hazards based on the most updated information (**CMIP6**).
-The related tool provides aggregated statistics at boundary level (country or subnational level) for a selection of:
- 1) climate-related hazards
- 2) country
- 3) time periods
+The climate component offers an overview of climate indices related to hydro-meteorological hazards based on the most updated climate modelling (**CMIP6**).
+The [Climate Indices tools](run_ci) allow to compute climate indices for the desired sub-national boundary level.
 
- The data can be aggregated:
- - across time (20 years windows) for representation of spatial distribution at sub-national level (**Map output**)
-   ```
-   ADM1_mean(Ensemble_p50(Period_mean(anomaly/hist_SD)))
-   ```
-   ```{figure} images/ci_adm.png
-   ---
-   align: center
-   ---
-   Example of mean standardardised anomaly (ensemble median) plotted for one climate index over Pakistan, period 2040-2060, 3 SSP scenarios - mean for subnational unit.
-   ```
- - across space (country boundaries) for time-series representation (**Chart output**)
-   ```
-   Ensemble_p10(ADM0_mean(anomaly/hist_SD))
-   Ensemble_p50(ADM0_mean(anomaly/hist_SD))
-   Ensemble_p90(ADM0_mean(anomaly/hist_SD))
-   ```
-    ```{figure} images/ci_tseries.png
-   ---
-   align: center
-   ---
-   Example of mean standardardised anomaly (ensemble median) plotted for one climate index over Pakistan, time-series up to 2100,  3 SSP scenarios - mean at country level.
-   ```
-
-The table summarises the relevant climate indices and related time scale. 
+The table summarises relationship between climate indices and hazard trends. 
 
 |   Name   |                  Description                  |  Time-scale  |
 |:--------:|:---------------------------------------------:|:------------:|
@@ -44,10 +17,9 @@ The table summarises the relevant climate indices and related time scale.
 | Heat     | WBGT or UTCI [°C] - bias adjusted             |     Daily    |
 | tmean    | Mean surface temperature [°C]                 |    Monthly   |
 
-## Input data
-The climate indices are primarily sourced from the [**WB Cimate Change Knowledge Portal**](https://climateknowledgeportal.worldbank.org). Additional indice such as drought indices are obtained from external sources.
-
-### Sources of CMIP6 data
+## Data sources
+The climate indices are primarily sourced from the [**WB Cimate Change Knowledge Portal**](https://climateknowledgeportal.worldbank.org).
+Additional indices could also be obtained from external sources.
 
 | **Name** | **Developer** | **Description** | **Data format** |
 | --- |:---:|---|---|
@@ -56,20 +28,10 @@ The climate indices are primarily sourced from the [**WB Cimate Change Knowledge
 | [IPCC atlas](https://interactive-atlas.ipcc.ch/regional-information) | IPCC | Selection of climate variables for a range of periods and scenario | Table, geodata, maps, charts |
 | [Global Drought Indices](https://data.ceda.ac.uk/badc/hydro-jules/data/Global_drought_indices) | CEDA | Global high-resolution drought datasets from 1981-2022 | Geodata |       
 
-### Dimensions:
+## Dimensions:
    - **SSP:** socio-climatic scenarios SSP1/RCP2.6, SSP2/RCP4.5, SSP3/RCP7.0, SSP5/RCP8
    - **Models ensemble range:** percentiles p10, p50, p90
    - **Period:** {Historical (1981-2015)}, [Near term (2020-2039), Medium term (2040-2059), Long term (2060-2079), End of century (2080-2099)]
    - **Time scale:** Annual (R10mm, CWD, slr, SPEI); Monthly (Rxday, R99p, tmean); Daily (Heat) 
    - **Value statistic:** {P10, P50, P90, SD}, [P10, P50, P90] 
 
-### Script setup [WIP]
-
-
-### Processing
-- Runs over one selected country and for a specific set of indices depending on selected hazard
-- Consider four SSP-RCP scenarios (SSP1-2.6; SSP2-4.5; SSP3-7.0; SSP5-8.5)
-- Consider four 20-years periods (near term, medium term, long term, end of century)
-- Calculate median, 10th percentile (p10) and 90th percentile (p90) of standardised anomaly across models in the ensemble ([more details](https://climateinformation.org/confidence-and-robustness/how-to-interpret-agreement-ensemble-value-range/))
-- Plot maps and timeseries
-- Exported results as multi-tab excel (table) and multi-layer geopackage (vector)

docs/climate-indices.md

@@ -1,3 +1,4 @@
+(run_ci)=
 # Climate Indices Analytics
 
 Choose from a selection of climate indices to analyze temperature extremes, precipitation patterns, heat stress indicators, and drought metrics.