Merge pull request #16 from datapartnership/drought-dec24

Update analysis up to Dec 2024 using CHIRPS v3

docs/drought-eo.md

@@ -15,26 +15,26 @@ The Standardized Precipitation Index ([SPI](https://library.wmo.int/doc_num.php?
 The SPI calculation is based on the long-term precipitation record for a particular location and long-term period (longer than 30 years is desirable). The calculation method consists of a transformation of one frequency distribution (e.g., gamma) to another frequency distribution (normal, or Gaussian). The first step to calculate SPI is to adequately choose a particular probability distribution (e.g., gamma distribution, incomplete beta distribution (McKee et al. 1993, 1995), and Pearson III distribution (Guttman 1998, 1999) that reliably fits the long-term precipitation time series and conducts fitting to that distribution.   
 
 Gamma distribution has been widely used, as the gamma distribution has been understood as the reliable fit to the precipitation distribution. The fitting can be achieved through the maximum likelihood estimation of the gamma distribution parameters. The percentile value from this probability distribution is then transformed to the corresponding value in the new probability distribution. As a result, the probability that the rainfall is less than or equal to any rainfall amount will be the same as the probability that the new variate is less than or equal to the corresponding value of that rainfall amount. The normal distribution is usually used for this another transformation so that the mean and standard deviation of the SPI for a certain station and long-term period is zero and one, respectively (Edwards and McKee 1997).   
-  
+
 ### Interpretation
 
 The SPI maps can be interpreted at various time scales. This in turn indicates that the SPI is useful in both short-term and long-term applications. These time scales reflect the impact of drought on the availability of the different water resources. For instance, soil moisture conditions respond to precipitation anomalies on a relatively short scale. Groundwater, streamflow, and reservoir storage reflect the longer-term precipitation anomalies.
 
 The threshold and the symbology for the SPI can follow below color codes and image.  
 
-| Class  | Threshold  | Hex  | RGB  |
-|---|---|---|---|
-| Exceptionally Dry  | -2.00 and below  | `#760005` ![#760005](https://via.placeholder.com/15/760005/000000?text=+)  | rgb(118, 0, 5)  |
-| Extremely Dry  | -2.00 to -1.50  | `#ec0013` ![#ec0013](https://via.placeholder.com/15/ec0013/000000?text=+)  | rgb(236, 0, 19)  |
-| Severely Dry  | -1.50 to -1.20  | `#ffa938` ![#ffa938](https://via.placeholder.com/15/ffa938/000000?text=+)  | rgb(255, 169, 56)  |
-| Moderately Dry  | -1.20 to -0.70  | `#fdd28a` ![#fdd28a](https://via.placeholder.com/15/fdd28a/000000?text=+)  | rgb(253, 210, 138)  |
-| Abnormally Dry  | -0.70 to -0.50  | `#fefe53` ![#fefe53](https://via.placeholder.com/15/fefe53/000000?text=+)  | rgb(254, 254, 83)  |
-| Near Normal  | -0.50 to +0.50  | `#ffffff` ![#ffffff](https://via.placeholder.com/15/ffffff/000000?text=+)  | rgb(255, 255, 255)  |
-| Abnormally Moist  | +0.50 to +0.70  | `#a2fd6e` ![#a2fd6e](https://via.placeholder.com/15/a2fd6e/000000?text=+)  | rgb(162, 253, 110)  |
-| Moderately Moist  | +0.70 to +1.20  | `#00b44a` ![#00b44a](https://via.placeholder.com/15/00b44a/000000?text=+)  | rgb(0, 180, 74)  |
-| Very Moist  | +1.20 to +1.50  | `#008180` ![#008180](https://via.placeholder.com/15/008180/000000?text=+)  | rgb(0, 129, 128)  |
-| Extremely Moist  | +1.50 to +2.00  | `#2a23eb` ![#2a23eb](https://via.placeholder.com/15/2a23eb/000000?text=+)  | rgb(42, 35, 235)  |
-| Exceptionally Moist  | +2.00 and above  | `#a21fec` ![#a21fec](https://via.placeholder.com/15/a21fec/000000?text=+)  | rgb(162, 31, 236)  |
+| Class  | Threshold  | Color  |  Hex  | RGB  |
+|---|---|---|---|---|
+| Exceptionally Dry  | -2.00 and below  | <span style="background-color: #760005; padding: 0 10px;">&nbsp;&nbsp;&nbsp;</span> | `#760005` | rgb(118, 0, 5)  |
+| Extremely Dry  | -2.00 to -1.50  | <span style="background-color: #ec0013; padding: 0 10px;">&nbsp;&nbsp;&nbsp;</span> | `#ec0013` | rgb(236, 0, 19)  |
+| Severely Dry  | -1.50 to -1.20  | <span style="background-color: #ffa938; padding: 0 10px;">&nbsp;&nbsp;&nbsp;</span> | `#ffa938`  | rgb(255, 169, 56)  |
+| Moderately Dry  | -1.20 to -0.70  | <span style="background-color: #fdd28a; padding: 0 10px;">&nbsp;&nbsp;&nbsp;</span> | `#fdd28a` | rgb(253, 210, 138)  |
+| Abnormally Dry  | -0.70 to -0.50  | <span style="background-color: #fefe53; padding: 0 10px;">&nbsp;&nbsp;&nbsp;</span> | `#fefe53` | rgb(254, 254, 83)  |
+| Near Normal  | -0.50 to +0.50  | <span style="background-color: #bfbfbf; padding: 0 10px;">&nbsp;&nbsp;&nbsp;</span> | `#bfbfbf`  | rgb(191, 191, 191)  |
+| Abnormally Moist  | +0.50 to +0.70  | <span style="background-color: #a2fd6e; padding: 0 10px;">&nbsp;&nbsp;&nbsp;</span> | `#a2fd6e` | rgb(162, 253, 110)  |
+| Moderately Moist  | +0.70 to +1.20  | <span style="background-color: #00b44a; padding: 0 10px;">&nbsp;&nbsp;&nbsp;</span> | `#00b44a` | rgb(0, 180, 74)  |
+| Very Moist  | +1.20 to +1.50  | <span style="background-color: #008180; padding: 0 10px;">&nbsp;&nbsp;&nbsp;</span> | `#008180` | rgb(0, 129, 128)  |
+| Extremely Moist  | +1.50 to +2.00  | <span style="background-color: #2a23eb; padding: 0 10px;">&nbsp;&nbsp;&nbsp;</span> | `#2a23eb` | rgb(42, 35, 235)  |
+| Exceptionally Moist  | +2.00 and above  | <span style="background-color: #a21fec; padding: 0 10px;">&nbsp;&nbsp;&nbsp;</span> | `#a21fec` | rgb(162, 31, 236)  |
 
 ### Strengths and Limitations
 
@@ -49,61 +49,73 @@ The threshold and the symbology for the SPI can follow below color codes and ima
 
 Below is the SPI example for different time scale and how to interpret the value, following the guideline from the US [National Drought Mitigation Center](https://drought.unl.edu/Monitoring/SPI/MapInterpretation.aspx)
 
-* SPI 1-month
+* **SPI 1-month**
 
 	Reflects relatively short term conditions. Its application can be related closely with short term soil moisture and crop stress. Interpretation of the 1-month SPI may be misleading unless climatology is understood. In regions where rainfall is normally low during a month, large negative or positive SPIs may result even though the departure from the mean is relatively small. 
 
-	![SPI1](./images/spi01.png)
+	![SPI1](./images/others/spi01.png)
 
-* 3 month
+* **SPI 3-month**
 
 	Provides a comparison of the precipitation over a specific 3 month period with the precipitation totals from the same 3 month period for all the years included in the historical record. Reflects short and medium term moisture conditions and provides a seasonal estimation of precipitation.
 
-	![SPI3](./images/spi03.png)
+	![SPI3](./images/others/spi03.png)
 
-* 6 month
+* **SPI 6-month**
 
 	Compares the precipitation for that period with the same 6 month period over the historical record. A 6 month SPI can be very effective in showing the precipitation over distinct seasons and may be associated with anomalous streamflow and reservoir levels.
 
-	![SPI6](./images/spi06.png)
+	![SPI6](./images/others/spi06.png)
 
-* 9 month
+* **SPI 9-month**
 
 	Provides an indication of precipitation patterns over a medium time scale. SPI values below 1.5 for these time scales are usually a good indication that significant impacts are occurring in agriculture and may be showing up in other sectors as well.
 
-	![SPI9](./images/spi09.png)
+	![SPI9](./images/others/spi09.png)
 
-* 12 month
+* **SPI 12-month**
 
 	Reflects long term precipitation patterns. Longer SPIs tend toward zero unless a specific trend is taking place. SPIs of these time scales are probably tied to streamflow, reservoir levels, and even groundwater levels at the longer time scales. In some locations of the country, the 12 month SPI is most closely related with the Palmer Index, and the two indices should reflect similar conditions.
 
-	![SPI12](./images/spi12.png)
+	![SPI12](./images/others/spi12.png)
+
+Below is the latest SPI - 3, 6 and 12 month condition based on CHIRPS version 3.0 as of December 2024.
 
-Below is the latest SPI-12 condition based on CHIRPS as of May 2023.
+::::{tab-set}
+:::{tab-item} SPI-3
+![SPI3-202412](./images/maps/mar_cli_chirps_spi03_20241201.png)
+:::
 
-![SPI12-202305](./images/maps/mar_cli_chirps_spi12_20230501.png)
+:::{tab-item} SPI-6
+![SPI6-202412](./images/maps/mar_cli_chirps_spi06_20241201.png)
+:::
+
+:::{tab-item} SPI-12
+![SPI12-202412](./images/maps/mar_cli_chirps_spi12_20241201.png)
+:::
+::::
 
 In addition to geographical maps, time series charts offer a compelling visualization tool that vividly captures the evolution of drought conditions. These charts, with their month-by-month and year-by-year granularity, effectively illustrate the changing dynamics of drought. Furthermore, they provide insightful details on the percentage of regions affected over time, painting a comprehensive picture of how droughts impact different areas periodically. 
 
 * National
 
-	![SPI6-timeseries-adm0](./images/chart_spi06/chirps_spi06_ma000000.png)
+	![SPI6-timeseries-adm0](./images/charts/spi06/spi_6_month_Morocco.png)
 
-* Admin1
+* Admin1, example: SPI-6 for Beni Mellal Khenifra
 
-	![SPI6-timeseries-adm1](./images/chart_spi06/chirps_spi06_ma001000.png)
+	![SPI6-timeseries-adm1](./images/charts/spi06/spi_6_month_Morocco_BeniMellalKhenifra.png)
 
-* Admin2
+* Admin2, example: SPI-6 for Provinced Azilal, Beni Mellal Khenifra
 
-	![SPI6-timeseries-adm2](./images/chart_spi06/chirps_spi06_ma001001.png)
+	![SPI6-timeseries-adm2](./images/charts/spi06/spi_6_month_Morocco_BeniMellalKhenifra_ProvincedAzilal.png)
 
 Other chart for different time scale from National, Admin1 and Admin2 level are available in folder
 
-* [SPI 3-month](https://github.com/datapartnership/morocco-economic-monitor/tree/main/docs/images/chart_spi03)
+* [SPI 3-month](https://github.com/datapartnership/morocco-economic-monitor/tree/main/docs/images/charts/spi03)
 
-* [SPI 6-month](https://github.com/datapartnership/morocco-economic-monitor/tree/main/docs/images/chart_spi06)
+* [SPI 6-month](https://github.com/datapartnership/morocco-economic-monitor/tree/main/docs/images/charts/spi06)
 
-* [SPI 12-month](https://github.com/datapartnership/morocco-economic-monitor/tree/main/docs/images/chart_spi12)
+* [SPI 12-month](https://github.com/datapartnership/morocco-economic-monitor/tree/main/docs/images/charts/spi12)
 
 
 ## SPI-based drought characteristics
@@ -114,7 +126,7 @@ Numerous indices for measuring drought, including SPI, SPEI, PDSI, among others,
 
 The run theory was initially introduced by Yevjevich in [1967](https://www.engr.colostate.edu/ce/facultystaff/yevjevich/papers/HydrologyPapers_n23_1967.pdf) and has since been used to identify drought characteristics. The paper from Le, et al in [2019](https://doi.org/10.1002/joc.6164) provide better explanation about it: duration, severity, intensity, and interarrival.
 
-![RunTheory](./images/runtheory.png)
+![RunTheory](./images/others/runtheory.png)
 
 Illustration of drought events and characteristics based on run theory (adapted from Yevjevich, 1967). 
 
@@ -124,7 +136,23 @@ Illustration of drought events and characteristics based on run theory (adapted
 * Magnitude M: the absolute cumulative SPEI value during drought events. Unitless
 * Severity S: the number came from magnitude divided by duration to get level of severity. Unitless
 
+::::{tab-set}
+:::{tab-item} Drought Characteristics
+![DR](./images/maps/mar_cli_spi_drought_characteristics_chirps.png)
+:::
+
+:::{tab-item} SPI-3
+![SPI3-DR](./images/maps/mar_cli_spi03_drought_characteristics_chirps.png)
+:::
+
+:::{tab-item} SPI-6
+![SPI6-DR](./images/maps/mar_cli_spi06_drought_characteristics_chirps.png)
+:::
+
+:::{tab-item} SPI-12
 ![SPI12-DR](./images/maps/mar_cli_spi12_drought_characteristics_chirps.png)
+:::
+::::
 
 :::{note}
 Currently we are still not sure on Inter-arrival time usefulness, even though we are confident with the algorithm and calculation for this following above paper. 

docs/drought-howto-characteristics.md

@@ -199,7 +199,7 @@ print('Completed!')
 
 Above script will also generate a chart on the Maximum Drought Magnitude Over Time
 
-![DM](./images/drought-magnitude-overtime.png)
+![DM](./images/others/drought-magnitude-overtime.png)
 
 ## Drought Duration
 
@@ -278,7 +278,7 @@ print('Completed!')
 
 Above script will also generate a chart on the Maximum Drought Duration Over Time
 
-![DD](./images/drought-duration-overtime.png)
+![DD](./images/others/drought-duration-overtime.png)
 
 ## Drought Severity
 
@@ -353,7 +353,7 @@ print('Completed!')
 
 Above script will also generate a chart on the Mean Drought Severity Over Time
 
-![DS](./images/drought-severity-overtime.png)
+![DS](./images/others/drought-severity-overtime.png)
 
 ## SPI Classification
 

docs/drought-howto-spianalysis.md

@@ -276,21 +276,21 @@ As explain in Step 1.1. Input requirement above, we need to check the variable a
 
 	:::{note}
     **Notes on re-ordering process (Case by case)**
-    
+  
     After re-ordering the variables, sometimes user experience `lat` or `lon` dimension becomes `UNLIMITED` which is wrong. The `time` dimension should be the `UNLIMITED` dimension.
-    
+  
     Fortunately you can do this to fix the `lat` or `lon` dimension who becomes `UNLIMITED` using `ncks` command below:
-    
+  
     ``` bash
     ncks --fix_rec_dmn lat mar_cli_chirps_monthly_1981_2023_temp1.nc -o mar_cli_chirps_monthly_1981_2023_temp2.nc
     ```
-    
+  
     And to make `UNLIMITED` the `time` dimension again using `ncks` command below:
-    
+  
     ``` bash
     ncks --mk_rec_dmn time mar_cli_chirps_monthly_1981_2023_temp2.nc -o mar_cli_chirps_monthly_1981_2023_llt.nc
     ```
-    
+  
     If you don't come accross the problem, `lat` or `lon` dimension becomes `UNLIMITED`, then skip above process and go directly to step below.
 	:::
 
@@ -350,7 +350,7 @@ Let visualize the result using [Panoply](https://www.giss.nasa.gov/tools/panoply
 	- Grid tab: Zoom in the map through menu-editor Plot > Zoom - Plot In few times until Morocco appear proportionally, then Change value on Center on Lon `-10.0` Lat `32.0`, then  Set grid spacing `2.0` and Labels on every grid lines.
 	- Overlays tab: Change `Overlay 1` to `MWDB_Coasts_Countries_1.cnob`
 
-	![Panoply](./images/panoply.png)
+	![Panoply](./images/others/panoply.png)
 
 
 ## 5. Convert the result to GeoTIFF