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Greenhouse Gas Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Bowling Green, Kentucky

    Alternative N fertilizers that produce low greenhouse gas (GHG) emissions from soil are needed to reduce the impacts of agricultural practices on global warming potential (GWP). We quantified and compared growing season fluxes of N2O, CH4, and CO2resulting from applications of different N fertilizer sources, urea (U), urea-ammonium nitrate (UAN), ammonium nitrate (NH4 NO3), poultry litter, and commercially available, enhanced-efficiency N fertilizers.

    SGP97 GCIP/NESOB-97 Surface: Hourly Precipitation Composite

    NAL Geospatial Catalog
      This precipitation composite is composed of data from several sources (i.e., National Weather Service (NWS) Cooperative Observers, National Centers for Environmental Prediction (NCEP), and the daily precipitation data extracted from the NESOB 1997 Hourly Precipitation Composite).

      SGP97 GCIP/NESOB-97 Surface: Daily Precipitation Composite

      NAL Geospatial Catalog
        This precipitation composite is composed of data from several sources (i.e., National Weather Service (NWS) Cooperative Observers, National Centers for Environmental Prediction (NCEP), and the daily precipitation data extracted from the NESOB 1997 Hourly Precipitation Composite).

        International Climate Benchmarks and Input Parameters for a Stochastic Weather Generator, CLIGEN

          This dataset represents CLIGEN input parameters for locations in 68 countries. CLIGEN is a point-scale stochastic weather generator that produces long-term weather simulations with daily output. The input parameters are essentially monthly climate statistics that also serve as climate benchmarks. Three unique input parameter sets are differentiated by having been produced from 30-year, 20-year and 10-year minimum record lengths.

          GOSSYM

            GOSSYM is a dynamic, process-level simulation model of cotton growth and yield. GOSSYM essentially is a materials balance model which keeps track of carbon and nitrogen in the plant and water and nitrogen in the soil root zone. GOSSYM predicts the response of the field crop to variations in the environment and to cultural inputs. Specifically, the model responds to weather inputs of daily total solar radiation, maximum and minimum air temperatures, daily total wind run, and rainfall and/or irrigation amount. The model also responds to cultural inputs such as preplant and withinseason applications of nitrogen fertilizer, row spacing and within row plant density as they affect total plant population, and cultivation practices.

            Virtual Grower 3

              Initially designed to help greenhouse growers determine heating costs and do simple simulations to figure out where heat savings could be achieved, it has slowly added features so that now, Virtual Grower can help not only identify those savings through different greenhouse designs, but predict crop growth, assist in scheduling, make real-time predictions of energy use, and see the impact of supplemental lighting on plant growth and development. In other words, the software can be a safety net and allow users to experiment with "what if" scenarios in a risk-free setting.