Weather variables obtained from NASA's Prediction of Worldwide Energy Resource (https://power.larc.nasa.gov/) for the 591 environments in the historical series analyzed by Krause et al. (2022).
A data frame in messy format with 504 observations on the following 5 variables:
locations, 63 levels (observed locations in the historical series)
day of the year
calendar date in the format YYYY/MM/DD
days from average planting date
daily average temperature at 2 meters
daily maximum temperature at 2 meters
daily minimum average temperature at 2 meters
wind speed at 2 meters
relative humidity at 2 meters
dew point at 2 meters
downward thermal infrared (longwave) radiative flux
insolation incident on a horizontal surface
duration of sunshine in hours
the deficit of vapor pressure
the slope of saturation vapor pressure curve
deficit of evapotranspiration
effect of temperature on radiation use efficiency
daily temperature range at 2 meters
photothermal time (GDD \times daylight in hours)
photothermal ratio (GDD / daylight in hours)
Comprehensive R Archive Network (CRAN) policy limits R package size to 5 Mb. In order to give the users new opportunities of data analysis, we provide weather data for all combinations of locations (63) and years (31), resulting in information for 1,953 environments. If an environment was not observed in a given year, weather data was retrieved with the average planting and maturity data based on the empirical data for that location. This data set can be downloaded here.
Krause, M. D., Dias, K. O. G., Singh, A. K., and Beavis. W. D. (2022). Using large soybean historical data to study genotype by environment variation and identify mega-environments with the integration of genetic and non-genetic factors. bioRxiv, doi: 10.1101/2022.04.11.487885
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