Dew point temperature (Td) is a precise measure of atmospheric moisture. A significant number of models for studying crop--climate interactions and earth processes require daily Td as an input. However, limited availability of Td data is a major barrier for applications of these models. In this paper, we present a daily Td estimation method for the northern Great Plains (NGP). The daily Td estimation method presented here requires daily maximum, minimum, and mean temperature data. Data from six sites in the NGP were used for the study. These sites record hourly Td data from relative humidity. Length of the time series is 14 yr (1986-1999). Four different regression-based approaches were adopted and applied to all sites. Eventually, the best method was adopted based on its performance. The model evaluation statistics show that the selected model performs satisfactorily for these six sites. For example, root mean square error (RMSE), mean absolute error (MAE), and d index (ranges between 0 and 1, where 1 indicates no model error) values for North Platte, NE, application are 3.23, 2.55, and 0.97, respectively. The selected method was further applied to five additional locations in the NGP, and again it performed satisfactorily. For example, RMSE, MAE, and d index values for McCook, NE, application are 2.6, 2.0, and 0.98, respectively. From the model evaluation, we conclude that the model performed satisfactorily and will be quite useful in estimating Td.
ASJC Scopus subject areas
- Agronomy and Crop Science