cmi_soybean_weather_data {BioCro}

Champaign, IL weather data for Soybean-BioCro

Description

Champaign, IL weather data specified at hourly intervals in the CST time zone for the years 2002, 2004, 2005, and 2006. The data includes typical inputs required for BioCro simulations, with the addition of day_length, which is specifically required for soybean simulations. Although this quantity can be calculated by modules during the course of a simulation, it is included in this weather data to speed up the simulations. The time range is restricted to the SoyFACE growing season that was used for each year.

This weather data is included in the BioCro package so users can reproduce the calculations of Matthews et al. (2022) [doi:10.1093/insilicoplants/diab032] and for exploratory purposes; it is likely that most BioCro studies will require different data sets, and no attempt is made here to be exhaustive.

Usage

soybean_weather

Format

A list of 4 named elements, where each element is a data frame corresponding to one year of weather data and the name of each element is a year, for example '2004'. Each data frame has 2952 - 3384 observations (representing hourly time points) of 14 variables:

• year: the year

• doy: the day of year

• hour: the hour

• time_zone_offset: the time zone offset relative to UTC (hr)

• precip: preciptation rate (mm / hr)

• rh: the ambient relative humidity (dimensionless)

• dw_solar: downwelling global solar radiation (J / m^2 / s)

• up_solar: upwelling global solar radiation (J / m^2 / s)

• netsolar: net global solar radiation (downwelling - upwelling) (J / m^2 /s)

• solar: the incoming photosynthetically active photon flux density (PPFD) measured on a ground area basis including direct and diffuse sunlight light just outside the crop canopy (micromol / m^2 / s)

• temp: the ambient air temperature (degrees Celsius)

• windspeed: the wind speed in the ambient air just outside the canopy (m / s)

• zen: the solar zenith angle (degrees)

• day_length: the length of the daily photoperiod (hours)

Source

Weather data were obtained from the public SURFRAD and WARM databases and processed according to the method described in Matthews et al. (2022) [doi:10.1093/insilicoplants/diab032]. See that paper for a full description of the data processing.

In brief, the columns in the data frames were determined from SURFRAD and WARM variables as follows:

• precip: from the precip variable in the WARM data set

• rh: from the rh variable in the SURFRAD data set

• dw_solar: from the dw_solar variable in the SURFRAD data set

• up_solar: from the uw_solar variable in the SURFRAD data set

• netsolar: from the netsolar variable in the SURFRAD data set

• solar: from the par variable in the SURFRAD data set; when these values are not available, the netsolar and up_solar variables are used to make an estimate; when these values are also not available, the dw_solar variable is used to make an estimate

• temp: from the temp variable in the SURFRAD data set

• windspeed: from the windspd variable in the SURFRAD data set

• zen: from the zen variable in the SURFRAD data set

• day_length: calculated from solar using an oscillator-based circadian clock

The WARM data set includes daily values. Hourly values for precipitation are derived from daily totals by assuming a constant rate of precipitation throughout the day.

The SURFRAD data set includes values at 1 or 3 minute intervals. Hourly values are determined by averaging over hourly intervals, where the value at hour h is the average over that hour. Some values are missing; any missing entries are filled by interpolating between neighboring hours.

To create this data frame, hourly values for all columns except day_length are extracted from the WARM and SURFRAD data. Then, BioCro is used to run the circadian clock model that determines photoperiod length. (See this page for additional information about the clock model: soybean_clock.) The result from this calculation is then appended to the weather data frame as a new column.

The time_zone_offset is set to a constant value of -6 since this data is specified in the CST time zone (i.e., UTC-6). Since the value of this quantity does not change, it could in principle be considered a parameter rather than a driver; however, it is included with the weather data for convenience.

To reduce size the in the BioCro repository, the raw data is rounded to three significant digits. This can be done with the following code: soybean_weather <- lapply(raw_soybean_weather, function(wd) { for (cn in colnames(wd)) { wd[[cn]] <- signif(wd[[cn]], digits = 3) }; wd })