seasonal rainfall, (2) number of days without rain, (3) mean seasonal temperature, and (4) growing degree days (GDD). These four variables are indicative of a number of different ways to measure precipitation and temperature (volume/degree v. count). We spend what may be more space than is typical in an economics paper discussing the descriptive statistics around these measures, but this is essential for understanding the way in which each EO product differs in its measurement of rainfall and temperature. In summarizing the descriptive statistics, we highlight a trends or stylized facts about differences in measurement (a) between EO products within a country and (b) within an EO product between countries.

Figure 4 presents the distribution of total rainfall (measured in mm) during the growing season, by country and EO product.<sup>9</sup> Not surprisingly, there are substantial differences in the distribution of rainfall across countries. Ethiopia and Uganda average around 650mm of rainfall a season while Malawi, Nigeria, and Tanzania average around 900mm of rainfall a season. By contrast, Niger averages only around 350mm of rainfall in a season. These level differences in the quantity of precipitation in a country are clearly due to geographic characteristics. When we consider all countries together, some general trends emerge with respect to EO sources. A first trend (T1) is that ERA5 tends to have long tails, indicating this reanalysis data product reports dramatically more rainfall than other EO source.<sup>10</sup> For example, in Ethiopia and Tanzania, ERA5 reports some households receiving 6,000-7,000mm of rainfall in a season - six to seven meters - while no other EO product reports even half that amount. A second trend (T2) is that CPC tends to measure less rainfall relative to other EO products. For example, in Ethiopia and Malawi, CPC reports only half as much rainfall as the other products.

However, there are important exceptions to these trends. In Ethiopia, Malawi, and Uganda, both T1 and T2 hold but in Niger, neither holds. In fact, nearly the opposite is seen: ERA5 measures lower rainfall, with a distribution below those of all other EO products. CPC’s distribution is nearly identical to the distribution of the non-ERA5 products. Next, in Nigeria, T2 holds (CPC reports less rainfall than the other products) but T1 does not hold. The largest volume of rainfall reported by ERA5 and is almost the exact same amount as reported by CHIRPS, MERRA-2, and TAMSAT. Finally, in Tanzania, T1 holds (ERA5 reports values more than double any other product) but T2 does not. Here CHIRPS and TAMSAT report less rainfall than the other products and both report zero rainfall for some households, something that does not happen for any other products in any country but Niger. The differences in rainfall reported by each EO product are likely due to a combination of the country’s geography (topography, hydrology) and the method each product uses to convert EO signals to estimates of the volume of precipitation.

Figure 5 further explores these differences by estimating the mean number of days without rain

> 9We discuss our calculation of growing season in the Appendix Section 6.

> 10These long tails are shown by Hennermann and Berrisford (2020). A few times per year, the rainfall can be extremely large in small areas, in an event known as a “rain bomb”. This can create the long tails we observe on the high rainfall end.

12