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Solar Calc: Estimating Hourly Incoming Solar Radiation from Limited Meteorological Data
Entry ID: USDA_ARS_SolarCalc
Abstract: Two major properties which determine weed seed germination are soil temperature
and moisture content. Incident radiation is the primary variable controlling
energy input to the soil system and thereby influences both moisture and
temperature profiles. However, a majority of agricultural field sites lack
proper instrumentation to measure solar radiation directly. To overcome this
shortcoming, an ... empirical model was developed to estimate total incident solar
radiation (beam and diffuse) with hourly time steps.
Input parameters for the model are latitude, longitude, and elevation of the
field site, along with daily precipitation (mm) with daily minimum and maximum
air temperatures (degrees C). The file format for this weather data file is a
comma spaced value file (CSV) with the following format:
DOY, MIN, MAX, PREC
Where DOY is day of year, MIN is the minimum air temperature, MAX is the
maximum air temperature, and PREC is the total daily rainfall. Each day has a
separate line in the file. Field validation of this model was conducted at a
total of 18 sites, where sufficient meteorological data were available for
validation, allowing a total of 42 individual yearly comparisons.
The model performed well, with an average Pearson correlation of 0.92, d-index
of 0.95, modeling efficiency of 0.80, root mean square error of 111 W m-2, and
a mean absolute error of 56 W m-2. These results compare favorably to other
developed empirical solar radiation models, but with the advantage of
predicting hourly solar radiation for the entire year based on limited climatic
data and no site-specific calibration requirement. This solar radiation
prediction tool can be integrated into dormancy, germination and growth models
to improve microclimate-based simulation of development of weeds and other
[Summary provided by the USDA.]
ISO Topic Category
Quality The USDA-ARS makes no warranties as to the merchantability or fitness of
SolarCalc 1.0 for any particular purpose, or any other warranties expressed or
implied. Since some portions of SolarCalc 1.0 have been validated with only
limited data sets, it should not be used to make operational management
decisions. The USDA-ARS is not liable for any damages resulting from the use or
misuse of SolarCalc 1.0, its output and its accompanying documentation.
Access Constraints Users must complete a registration form in order to download software.
Use Constraints SolarCalc was written in Java, and therefore can run on multiple platforms
(e.g. Windows, Mac, Unix).
Creation and Review Dates