Satellite Derived Surface Wetness and Temperature
Products and Crop Yields Prediction in Real Time

Alan Basist, Joel Sivillo, Craig Tillman

Weather Predict Consulting

Abstract
The most important factors influencing yield variations at a given location are heat and moisture. To understand those changes, the presenters have developed a technique to identify surface wetness and temperature from the Special Sensor Microwave Imager (SSMI), a passive microwave instrument that flies on a suite of operational satellite platforms. Weather Predict Consulting (WPC)’s proprietary software accurately identifies these parameters under nearly all sky conditions, allowing continuous coverage and monitoring of surface wetness and temperature. Moreover, it has been confirmed that the wetness product is an excellent measure of upper level soil moisture in most locations. The 22-year mean climatology at both weekly and monthly time scales and the corresponding anomalies are calculated from the SSMI data from 1988 to present. These anomalies serve as the foundation of our tools to monitor growing conditions in near real time. Several statistical crop yield models have been developed to use the SSMI surface wetness and temperatures as predictors. The models are uniquely calibrated on yields for specific crop–region combinations. These yield predictions have demonstrated value by identifying quantitative yield variations during the reproductive and early filling stages of crop development. As such, the SSMI based forecast results frequently lead the USDA final assessment of yields in many areas around the world. We will present product examples and findings at the conference.

Keywords: Agriculture, yields, monitoring, satellite, surface wetness, land surface temperatures