Methods in Agroclimatology: On the Quality of USDA Gridded Crop Condition Layers

High-quality and high-resolution crop condition data continues to be in demand for farmers, agribusiness, government agencies, and agroclimatologists in the United States. This study assessed the quality of the USDA National Agricultural Statistics Service’s (NASS) Gridded Crop Condition data over its historical record (2015–2023) for four major field crops, including corn (Zea mays L.), cotton (Gossypium hirsutum L.), soybeans (Glycine max L.), and wheat (Triticum aestivum L.). When these weekly geospatially referenced, 9 km gridded data are aggregated to county level and further to state level, there are no statistically significant differences between these aggregated crop condition data and the USDA condition data in the Crop Progress and Condition (CPC) report. Further, county-level crop condition ratings are a statistically significant covariate of yield for 80% of corn, 60% of cotton, 65% of soybean, and 80% of wheat-producing counties, respectively. Meteorological and hydrological variables—including accumulated precipitation, maximum and minimum temperatures, surface runoff, evapotranspiration, Palmer Drought indices, and the crop moisture index—also exhibit a medium to strong correlation coefficient with county-level crop conditions. Confirming the quality of these data that are published weekly by the USDA is critical for agricultural stakeholders to make informative, data-driven decisions during the growing season.