The FIFE Historic Monthly Meteorology Data Data Set is one of the historical data sets used for the FIFE project. This data set provides monthly precipitation values from January 1858 to December 1989 for Manhattan, Kansas adjacent to the FIFE study area. Daily weather observations of precipitation were made according to the procedures outlined by the National Weather Service by Kansas State University. The daily precipitation data were then summed to produce monthly precipitation.

A shapefile of annual average wind resource potential for Kansas, United States at a 50 meter height. This data set has been validated by NREL and wind energy meteorological consultants. Note: This data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. The wind power resource estimates were produced by AWS TrueWind using their MesoMap system and historical weather data under contract to Wind Powering America/NREL. This map has been validated with available surface data by NREL and wind energy meteorological consultants. For updated gridded long-term average wind data please see the "Global Wind Atlas" resource below. For more information on NREL's wind resource data development, see the "Wind Integration National Dataset (WIND) Toolkit" and the "WIND Toolkit Long-Term Ensemble Dataset" resources.

Environmental characterization for defining the target population of environments (TPE) is critical to improve the efficiency of breeding programs in crops, such as sorghum (Sorghum bicolor L.). The aim of this study was to characterize the spatial and temporal variation for a TPE for sorghum within the United States. APSIM-sorghum, included in the Agricultural Production Systems sIMulator software platform, was used to quantify water-deficit and heat patterns for 15 sites in the sorghum belt. Historical weather data (∼35 years) was used to identify water (WSP) and heat (HSP) stress patterns to develop water–heat clusters. Four WSPs were identified with large differences in the timing of onset, intensity, and duration of the stress. In the western region of Kansas, Oklahoma, and Texas, the most frequent WSP (∼35%) was stress during grain filling with late recovery. For northeast Kansas, WSP frequencies were more evenly distributed, suggesting large temporal variation. Three HSPs were defined, with the low HSP being most frequent (∼68%). Field data from Kansas State University sorghum hybrid yield performance trials (2006–2013 period, 6 hybrids, 10 sites, 46 site × year combinations) were classified into the previously defined WSP and HSP clusters. As the intensity of the environmental stress increased, there was a clear reduction on grain yield. Both simulated and observed yield data showed similar yield trends when the level of heat or water stressed increased. Field yield data clearly separated contrasting clusters for both water and heat patterns (with vs. without stress). Thus, the patterns were regrouped into four categories, which account for the observed genotype by environment interaction (GxE) and can be applied in a breeding program. A better definition of TPE to improve predictability of GxE could accelerate genetic gains and help bridge the gap between breeders, agronomists, and farmers.