Abstract
The National Agricultural Statistics Service (NASS) uses regression models to forecast yield for crops such as corn, soybeans and winter wheat. Analyses were conducted on the use of precipitation data in these regression models (McCormick and Birkett 1992, and McCormick 1993). Precipitation data are obtained from two sources. The National Climatic Data Center (NCDC) supplies historic precipitation data used for developing regression model parameters. The Climate Analysis Center (CAC) supplies current year precipitation data that are used as regression model input. CAC weather station density is sparse across the U.S. in many major agricultural areas compared to NCDC weather station density. As a result, significant differences exist between NCDC and CAC regional precipitation terms for corn and winter wheat. This paper evaluates the effect on forecast accuracy when only CAC data are used versus NCDC data for model development. Results indicate that regional corn, soybean and winter wheat models based on CAC data are just as accurate as NCDC based models.
Keywords
Precipitation data, regression models, forecast accuracy.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
McCormick, M. Denice
(1993).
"THE EFFECT OF WEATHER STATION DENSITY ON CROP YIELD FORECASTS,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1380
THE EFFECT OF WEATHER STATION DENSITY ON CROP YIELD FORECASTS
The National Agricultural Statistics Service (NASS) uses regression models to forecast yield for crops such as corn, soybeans and winter wheat. Analyses were conducted on the use of precipitation data in these regression models (McCormick and Birkett 1992, and McCormick 1993). Precipitation data are obtained from two sources. The National Climatic Data Center (NCDC) supplies historic precipitation data used for developing regression model parameters. The Climate Analysis Center (CAC) supplies current year precipitation data that are used as regression model input. CAC weather station density is sparse across the U.S. in many major agricultural areas compared to NCDC weather station density. As a result, significant differences exist between NCDC and CAC regional precipitation terms for corn and winter wheat. This paper evaluates the effect on forecast accuracy when only CAC data are used versus NCDC data for model development. Results indicate that regional corn, soybean and winter wheat models based on CAC data are just as accurate as NCDC based models.
