A Model of the Feedbacks Between Agricultural Ecosystems and Weather and Climate Evaluated At the Field Scale with Remotely Sensed Observations of Soil Moisture.

Models of crop growth in response to weather and climate have been used for several years to predict yield. More recently, models which account for the feedbacks between agricultural ecosystems and weather and climate have been developed. These models not only grow crops in response to weather, but allow variables such as the land surface albedo and exchange of moisture and heat between the land and the atmosphere to change to be in concert with current crop conditions. These new models will allow future regional and global weather and climate models to predict how large-scale changes in the management and composition of agricultural ecosystems may affect weather and climate, and how a changing climate may effect agricultural ecosystems. These predictions will be used to make decisions regarding the effect of future agricultural ecosystems on environmental quality, the possible large-scale production of biofuels on weather and climate, and how future climates may affect the productivity of certain land areas. New tools are becoming available to evaluate the performance of models that account for the feedbacks between agricultural ecosystems and weather and climate. For example, the recently-launched Soil Moisture and Ocean Salinity (European Space Agency) satellite mission is the first to employ passive microwave remote sensing to obtain measurements of both near-surface soil moisture and the amount of vegetation present at a spatial scale compatible with weather and climate models. There is a need to evaluate these models at the spatial scale at which these new satellite data will be available. Past evaluations have relied on the use of point measurements. There is a mismatch in the support (the area integrated by each sample) between these point samples and satellite measurements. The support of current satellite measurements is tens of kilometers and the spatial variability within this footprint is large. With our current understanding of the scaling of point measurements, it is difficult to evaluate model performance at the satellite scale at present. We will evaluate the performance of the Agro-IBIS model, one of a handful of models which simulate the feedbacks between agricultural ecosystems and weather and climate, on the field scale with point-scale measurements and observations of soil moisture from a new type of remote sensing instrument that simulates the type of data available from a satellite but at a scale at which the spatial variability in field properties can be accounted for. This new remote sensing instrument uses cosmic rays to sense the 10-20 cm soil moisture of an area approximately 700 m in diameter. One of the first of these cosmic-ray sensors has been installed at a heavily-instrumented outdoor laboratory managed by our research group. We will compare the observations of soil moisture produced by this cosmic-ray instrument with in-situ point measurements and the predictions of the Agro-IBIS model.