Skip to main content
ARS Home » Research » Publications at this Location » Publication #108753
Title: ERROR ANALYSIS OF SOIL TEMPERATURE SIMULATIONS USING MEASURED AND ESTIMATEDHOURLY WEATHER DATA WITH 2DSOIL

Author
item Timlin, Dennis
item Pachepsky, Yakov
item Acock, Basil
item SIMUNEK, JIRKA - UNIVERSITY OF CA
item Flerchinger, Gerald
item WHISLER, FRANK - MISSISSIPPI STATE UNIVER

Submitted to: Agriculture Ecosystems and the Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/1/2001
Publication Date: 2/2/2002
Citation: N/A

Interpretive Summary: Many crop simulation models use one hour time steps for atmospheric, soil, and plant processes but often meteorological data are only available as daily summaries. Methods are available to downscale meteorological data (solar radiation, air temperature, wind speed) from daily summary data to hourly data. The objective of this study was to investigate how errors in estimation of hourly values of solar radiation and air temperature affect errors in simulation of soil temperature. Measured soil temperature data and hourly weather data were available from two sites, one in Washington, the other in Mississippi. The model used was 2DSOIL. The errors in estimated values of air temperature and solar radiation were small. However, there was more error in the estimation of solar radiation because cloud cover is difficult to predict. The model, 2DSOIL, predicted soil temperatures accurately using measured hourly air temperatures and radiation. Use of estimated hourly air temperature and radiation will, generally result in under-predictions of soil temperature by 2 to 3 deg C and increase error by 2 - 3 deg C. Also peak, daily high temperatures may be underestimated. The results of this research will help users of simulation models evaluate theimpact of using less detailed weather data in their models.

Technical Abstract: Many crop simulation models use one hour time steps for atmospheric, soil and plant processes but often meteorological data are only available as daily summaries. Methods are available to downscale meteorological data (solar radiation, air temperature, wind speed) from daily summary data to hourly data. The objective of this study was to investigate how errors in estimation of hourly values of solar radiation and air temperature affect errors in simulation of soil temperature. Measured soil temperature data and hourly weather data were available from two sites, one in Washington, the other in Mississippi. The model used was 2DSOIL. The standard deviations of the estimated values were about 2 deg C for air temperature and 85 W m-2 for solar radiation. The mean difference in simulated and measured soil temperatures for all depths at both sites was less than 1 deg C and standard deviations were about 1 to 3 deg C, indicating low bias. The range of errors were highest in the surface soils and were highest at the Washington site when the soil was wetted after rainfall; differences could be as high as 19 deg C at midday. The ranges of error were similar at both sites. Relative to simulated soil temperatures using measured hourly data, simulated soil temperatures using estimated data were, on average, over all depths 2 deg C lower and standard deviations ranged from 2 to 3 deg C. The errors were similar over all depths. Use of estimated hourly air temperature and radiation will, generally result in under-predictions of soil temperature by 2 to 3 deg C and slightly increased error. Also peak, daily high temperatures may be underestimated.