Skip to content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

SolarCalc 1.0

Metadata Updated: November 10, 2020

Solar Calc: Estimating Hourly Incoming Solar Radiation from Limited Meteorological Data 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 plants. Disclaimer: 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. SolarCalc 1.0 was written in Java, and therefore can run on multiple platforms (e.g. Windows, Mac, Unix).

Access & Use Information

Public: This dataset is intended for public access and use. License: Creative Commons CCZero

Downloads & Resources


Metadata Created Date November 10, 2020
Metadata Updated Date November 10, 2020

Metadata Source

Harvested from USDA JSON

Additional Metadata

Resource Type Dataset
Metadata Created Date November 10, 2020
Metadata Updated Date November 10, 2020
Publisher Agricultural Research Service
Identifier edc733e5-98af-41b8-88e5-c644c50ce047
Data Last Modified 2020-02-07
Public Access Level public
Bureau Code 005:18
Metadata Context
Schema Version
Catalog Describedby
Harvest Object Id 6bf6994e-65a6-465b-b3a9-4eb9d219c81e
Harvest Source Id d3fafa34-0cb9-48f1-ab1d-5b5fdc783806
Harvest Source Title USDA JSON
Program Code 005:040
Source Datajson Identifier True
Source Hash 98b9990e4d29c6148eb3fe96d2c1f2f46baa665e
Source Schema Version 1.1

Didn't find what you're looking for? Suggest a dataset here.

An official website of the General Services Administration.

Looking for U.S. government information and services?