Crop models have many current and potential uses for answering questions in research, crop management, and policy. Models can assist in synthesis of research understanding about the interactions of genetics, physiology, and the environment, integration across disciplines, and organization of data. They can assist in preseason and in‐season management decisions on cultural practices, fertilization, irrigation, and pesticide use. Crop models can assist policy makers by predicting soil erosion, leaching of agrichemicals, effects of climatic change, and large‐area yield forecasts. Cautions and limitations in model uses are suggested, because appropriate use for a particular purpose depends on whether the model complexity is appropriate to the question being asked and whether the model has been tested in diverse environments. There is a need for both complex and simple models. In some cases, simple models are not appropriate because they are not programmed to address a particular phenomenon. In other cases, complex models are not appropriate because they may require inputs that are not practical to obtain in a field situation. Modelers need to be forthright in model description and promotion. For example, what does a given model respond to? What are the limitations of the model? What factors does the model not address? What are the limitations of inputs to run the models? Examples are given of model use to evaluate genetic improvement in photosynthesis and seed‐filling duration, yield response to planting date and row spacing, and effects of change in seasonal temperature. We believe that use of crop growth models will play an increasingly important role in research understanding, crop management, and policy questions.

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Rising CO2 and potential global warming will cause changes in evapotranspiration (ET). Our research objective was to determine the impact of CO2 and air temperature on canopy ET, water use efficiency (WUE), foliage temperature, and canopy resistance (Rc) of soybean [Glycine max (L.) Merr.]. Plants were grown in sunlit, controlled‐environment chambers at cyclic maximum/minimum air temperatures from 28/18°C to 44/34°C and CO2 of 350 or 700 μmol mol−1 Maximum ET rate in the early afternoon at 35 d after planting ranged from 7.5 mol m−2 s−1 at 28/18°C to 19.0 mol m−2 s−1 at 44/34°C. Daily ET during the middle of the season ranged from 260 mol H2O m−2 d−1 (4.7 mm d−1) at 28/18°C to 660 mol H2O m−2 d−1 (11.9 mm d−1) at 44/34°C. Mean daily ET was linearly related to mean air temperature (Tair) as: [Mean daily ET = 21.4 × Tair − 306, r2 = 0.99 (mol H2O m−2 d−1), or mean daily ET = 0.385 × Tair − 5.5 (mm d−1)]. Doubled CO2 caused a 9% decrease in ET at 28/18°C, but CO2 had little effect at 40/30°C or 44/34°C. Whole‐day WUE declined linearly with air temperature, with a slope of −0.150 [(μmol CO2 mmol−1 H2O) °C−1]. Changes in ET and WUE were governed by changes in foliage temperature and Rc. In conclusion, increases in temperature anticipated by climate change could more than offset decreases of ET that would be caused by increases in CO2

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Daily weather data commonly used in simulation models of agricultural or ecological systems are sometimes incomplete, frequently contain errors, and are often in an inconvenient format. The WeatherMan is a user‐oriented software package designed to assist in preparing daily weather data for use with simulation models. The software can import or export daily weather files with any column format (including the Decision Support System for Agrotechnology Transfer ver. 2.1 and ver. 3.0 files) and convert the data to desirable units. Data are checked and flagged for possible errors on import. Several techniques are available for filling in missing values and erroneous data on export. WeatherMan also contains two methods (WGEN and SIMMETEO) for stochastically generating sequences of daily weather data. Both methods can be parameterized from the daily data and the second method uses monthly means from any secondary data source. Summary statistics of raw and generated data can be graphed or presented in tables.