as they have been built to answer different questions about risk. Such simulated hazard event sets focus upon a primary damage discriminator, such as wind speed for storm or ground shaking for earthquake, which is subsequently translated into impact on exposure through damage functions describing vulnerability.

A criticism of catastrophe models is that they are not forward looking regarding climate change.<sup>9</sup> Since the consequences of climate change are already present, however, any recent historical record for atmosphericrelated natural hazards comprises a climate change signal, alongside other potential modalities, such as the El Niño–Southern Oscillation (ENSO). Model sensitivity to these climate aspects can be explored in a catastrophe modeling environment and considered as another dimension of uncertainty. In recent years, “climate conditioning” of catastrophe models for differing time horizons and emissions scenarios (such as in Bates [2023]) has received much attention and is an active research frontier, attracting many new entrants to natural hazard risk modeling (see Fielder et al. 2021). Model adjustment can range from a simple shifting of event frequencies in stochastic hazard tables to much fuller incorporation of and alignment with GCM approaches. It must be remembered that there may be considerable uncertainty around future climate patterns (such as rainfall across the Sahel), and it may be challenging to adequately parameterize them without suggesting inappropriate levels of exactitude. Scenario modeling is one typical approach under high uncertainty. Additionally, exposure and vulnerability components of risk (such as urbanization, informal settlements, and flooding) can change much faster than climate trends. Since this work increasingly falls under financial regulation and disclosure regimes (e.g., NGFS 2022), explicit climate modeling for catastrophic risks will see much growth in the near future, with translation of approaches to low-income regions through use of underlying global data sets. This paper’s analysis focuses on past and current weather patterns and does not include an estimation of future changes due to global warming.

# 3. Data on Hazards and Welfare

## 3.1. Hazard data

For the analysis described in this paper, we constructed a database of historical hazard data for all SSA using remotely sensed satellite data and indices that were reputable and publicly available and that had high levels of spatial and historical coverage. The considered hazard variables include rainfall, vegetation cover, evapotranspiration, soil moisture, and the WRSI. Given there is no single definition of drought, these hazard data were used to develop different measures of climatic conditions as a proxy for drought. These measures range from simple ones based on the amount and timing of precipitation during the growing season in a defined area, to more complex composite measures combining precipitation with other information capturing the impact of increased temperatures on water availability and agricultural stress at a location. Appendix B provides more details on all the drought measures considered and the sources of the data.<sup>10</sup> Table 3.1 provides a brief overview of the measures used in the analysis. These measures by and large focus on the first three months of the growing season.

**Table 3.1. Summary of range of hazard measures derived from remotely sensed data**

|**Data type **|**Source**|**Hazard measures**|
|---|---|---|
|Rainfall|CHIRPS global rainfall data set from US<br>Geological Survey (NASA)|Standardized anomaly of cumulative<br>rainfall (based on the first three months of<br>thegrowingseason)|
|Vegetation<br>(greenness)|NDVI product of MODIS vegetation<br>indices|NDVI standardized anomaly (based on the<br>average over the first three months of the<br>growingseason)|
|Evapotranspiration|SPEI generated by the Climatic Research<br>Unit of the Universityof East Anglia|Level of three-month SPEI at the end of the<br>first three months of thegrowingseason|

9 See for example Purdy (2021).

10 A workshop was held at the beginning of the work described in this paper to ensure the right measures were included (in addition to those summarized in appendix B).

9