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handbook/_build/html/_sources/chapters/01-climate-toolkit-for-beginners/data-sources.md

@@ -29,7 +29,7 @@ These models don't predict specific events at particular times or locations, but
 
 Even if the computing power has increased, it is however impossible to compute the climate state of every possible points on the planet. What the models do is to compute the climate state of regularly spaced points, creating *de facto* a grid with each point at the center of its cell. The value is considered to be an average of the grid cell.
 
-When dealing with climate data, we have to consider that climate is related not only to the Earth surface (that we have already seen how it can be represented through a system of coordinates), but also to atmospheric conditions. So we have to add a third dimension to our system, named ‘height’ or ‘pressure’ and also divided into cells.
+When dealing with climate data, we have to consider that climate is related not only to the Earth surface (that we have already seen how it can be represented through [a system of coordinates](https://ecmwfcode4earth.github.io/tales-of-drought/chapters/01-climate-toolkit-for-beginners/coordinate-system.html)), but also to atmospheric conditions. So we have to add a third dimension to our system, named ‘height’ or ‘pressure’ and also divided into cells.
 
 However, climate evolves over time, so we must consider it as a fourth dimension.
 
@@ -49,14 +49,24 @@ ERA5 is the latest climate reanalysis produced by ECMWF. It is available from 19
 <p class="credits">Three stages of reanalysis - <a href="https://climate.copernicus.eu/copernicus-regional-reanalysis-europe-cerra" target="_blank">Copernicus Climate Change Service</a></p>
 
 
- # TODO: add information about drought data.
+ ## The drought dataset
+The dataset we'll be using is [**ERA5-DROUGHT**](https://cds.climate.copernicus.eu/cdsapp#!/dataset/dderived-drought-historical?tab=overview), which is derived from the ERA5 reanalysis provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). This dataset includes two primary standardized drought indicators:
+
+- The Standardized Precipitation Index (SPI)
+- The Standardized Precipitation-Evapotranspiration Index (SPEI)
+
+The [next chapter](https://ecmwfcode4earth.github.io/tales-of-drought/chapters/02-drought-focus/indices.html) takes an in-depth look at these two indices.
+
 
 ```{tip} 
 If you are interested to learn more about climate data sources, you can watch the three ECMWF's course:
 - [Data Resources - Observations](https://learning.ecmwf.int/course/view.php?id=64)
 - [Data Resources - Reanalyses](https://learning.ecmwf.int/course/view.php?id=63)
 - [Data Resources - Climate Models](https://learning.ecmwf.int/course/view.php?id=62)
 
+Read this slides:
+- [Data Resources - Climate Models](https://climate.copernicus.eu/sites/default/files/2021-12/10-c3s-uls-data-resources-climate-models.pdf)
+
 Or you can visit the webpages:
 - [Observation components of the Global Observing System](https://community.wmo.int/en/observation-components-global-observing-system) of the World Meteorological Organization (WMO).
 - [Basics of Global Climate Models](https://www.climatehubs.usda.gov/hubs/northwest/topic/basics-global-climate-models) of the USDA Climate Hubs

handbook/_build/html/_sources/chapters/02-drought-focus/index.md

@@ -23,5 +23,7 @@ In urban areas, water shortages can disrupt industries, compromise sanitation, a
 </div>
 
 ```{tip} 
-You can learn more about drought's impacts in the "[Atlas of Mortality and Economic Losses from Weather and Climate Extremes (1970-2012)](https://wmo.int/about-us/world-meteorological-day/wmd-2020/drought)" by the World Meteorological Organization (WMO).
+You can learn more about drought's impacts in these two reports:
+- "[Atlas of Mortality and Economic Losses from Weather and Climate Extremes (1970-2012)](https://wmo.int/about-us/world-meteorological-day/wmd-2020/drought)" by the World Meteorological Organization (WMO).
+- "[Global Drought Snapshot 2023](https://www.unccd.int/sites/default/files/2023-12/Global%20drought%20snapshot%202023.pdf)" by the United Nations Convention to Combat Desertification (UNCCD). On page 12, you can find the list of countries declaring drought emergencies in 2022-2023.
 ```

handbook/_build/html/_sources/chapters/02-drought-focus/indices.md

@@ -22,7 +22,8 @@ For our analysis we will focus on two indices: **SPI** and **SPEI**.
 
 The **Standardized Precipitation Index** (**SPI**) is an index used to measure drought intensity. It works by comparing the amount of rainfall in a specific period to the historical average for that same period. This helps determine how much more, or less, it has rained compared to usual conditions. 
 
-This global **SPI** is calculated using data from the era5-dataset. This **SPI** can examine rainfall over various timescales, including 1, 3, 6, 12, 24, 36 and 48 months, allowing for a detailed analysis of short-term fluctuations and long-term trends in precipitation.
+This global **SPI** is calculated using data from the era5-dataset. This **SPI** can examine rainfall over various timescales (accumulation windows), including 1, 3, 6, 12, 24, 36 and 48 months, allowing for a detailed analysis of short-term fluctuations and long-term trends in precipitation. The appropriate choice of time scale depends on the specific drought impact: values for 1 and 3 months are useful for the basic drought monitoring, 6 months or less are suitable for assessing agricultural impacts, and 12 months or longer are relevant for monitoring hydrological impacts.
+
 
 
 ```{tip} 
@@ -33,25 +34,32 @@ If you're interested in learning more about the **SPI** index, you can download
 ## SPEI index
 
 
-The **Standardized Precipitation Evapotranspiration Index** (**SPEI**) is a widely used meteorological index for measuring drought conditions. The **SPEI** quantifies the deficit of water on the land's surface over various time periods, typically spanning months. It is designed to take into account both precipitation and potential PET in determining drought.
+The **Standardized Precipitation Evapotranspiration Index** (**SPEI**) is a widely used meteorological index for measuring drought conditions. The **SPEI** quantifies the deficit of water on the land's surface over various time periods, typically spanning months. It is designed to take into account both precipitation and potential evapotranspiration (PET) in determining drought.
 
 In simpler terms, the **SPEI** scores indicate how wet or dry a period is compared to normal conditions, using standard-deviation from the mean: negative values indicate drier than usual periods while positive values correspond to wetter than usual periods. The magnitude of the SPEI is an indicator of the severity of event.  
-**SPEI** values ranging from -1 to 1 are generally viewed as normal. 
 
 
+The **SPEI** is typically computed over a range of time windows from 1 over 3 and 6 to 12 months or more (24, 36, 48 months). Similar to the SPI index, the chosen time window helps identify and monitor conditions associated with various drought impacts.
+
+**SPI** and **SPEI** values are in units of standard deviation from the standardised mean. The magnitude of these indices indicates the severity of drought events: values between -1 and 1 are generally considered normal, while values outside this range indicate either drier-than-usual or wetter-than-usual conditions.
+
+**SPI** and **SPEI** values ranging from -1 to 1 are generally viewed as normal. 
+
 Here's what the scores typically represent:
 
-- SPEI > 2.0: extremely wet  
-- 1.5 < SPEI <= 2.0: severely wet  
-- 1.0 < SPEI <= 1.5: moderately wet  
-- 0 < SPEI <= 1.0: near-normal / mildly wet  
-- –1.0 < SPEI <= 0: near-normal / mildly dry  
-- –1.5 < SPEI <= –1.0: moderately dry  
-- –2.0 < SPEI <= –1.5: severely dry  
-- SPEI < –2.0: extremely dry
+- SPI/SPEI > 2.0: extremely wet  
+- 1.5 < SPI/SPEI <= 2.0: severely wet  
+- 1.0 < SPI/SPEI <= 1.5: moderately wet  
+- 0 < SPI/SPEI <= 1.0: near-normal / mildly wet  
+- –1.0 < SPI/SPEI <= 0: near-normal / mildly dry  
+- –1.5 < SPI/SPEI <= –1.0: moderately dry  
+- –2.0 < SPI/SPEI <= –1.5: severely dry  
+- SPI/SPEI < –2.0: extremely dry
 
+There are significant differences in the sensitivity of SPI and SPEI values at different time scales: the smaller the time scale, the more the wet and dry changes.
 
-The **SPEI** is typically computed over a range of time windows from 1 over 3 and 6 to 12 months or more. The time window considered is indicative of the potential impact of meteorological drought, which is often the primary driver of drought.
+Being standardized indices makes them unitless measures, which facilitates comparative analysis across diverse time series
+datasets.
 
 
 ```{tip}