  We quantify the significance and magnitude of the effect of measurement error
in satellite weather data on modeling agricultural production, agricultural
productivity, and resilience outcomes. In order to provide rigor to our
approach, we combine geospatial weather data from a variety of satellite
sources with the geo-referenced household survey data from four sub-Saharan
African countries that are part of the World Bank Living Standards Measurement
Study - Integrated Surveys on Agriculture (LSMS-ISA) initiative. Our goal is to
provide systematic evidence on which weather metrics have strong predictive
power over a large set of crops and countries and which metrics are only useful
in highly specific settings.
