Standard Meteorological Measurements

Instruments that measure weather variables have been invented and tested since the time of Leonardo de Vinci. The earliest instruments were crude by today’s standards and required manual observation and notation of the weather variable of interest. In recent years, the miniaturization of circuits–sensors and the use of electronic processors have made it possible to collect ever-increasing numbers of observations on scales not previously considered. In many agricultural applications, the primary portion of the atmosphere that is of interest is the lower planetary boundary layer, or that layer affected by the earth’s surface. Accurate measurement of weather variables in the lower planetary boundary layer requires an understanding of the interactions among the atmosphere, plant communities, and soils. Temperature and pressure are often measured because of their role in air movement and energy exchange between the earth’s surface and the atmosphere. Temperature is perhaps of greater interest in agricultural applications because it is a driving variable that determines the rate of growth and development of an organism, and thus determines what species can grow in a region. Wind speed and direction are measured because of their role in convective energy exchange and the movement of spores, pollen, odors, and chemicals as they drift in the atmosphere. Precipitation amount, intensity, frequency, and form are important in determining the availability of water for crops and play an important role in soil erosion by water and in water quality issues. Solar radiation and relative humidity are additional weather variables, important to agriculture, that are often measured by appropriate sensors at automated weather stations. These variables will be discussed by Klassen and Bugbee (2005, this volume) and Campbell and Diak (2005, this volume)

Standard Meteorological Measurements

Instruments that measure weather variables have been invented and tested since the time of Leonardo de Vinci. The earliest instruments were crude by today’s standards and required manual observation and notation of the weather variable of interest. In recent years, the miniaturization of circuits–sensors and the use of electronic processors have made it possible to collect ever-increasing numbers of observations on scales not previously considered. In many agricultural applications, the primary portion of the atmosphere that is of interest is the lower planetary boundary layer, or that layer affected by the earth’s surface. Accurate measurement of weather variables in the lower planetary boundary layer requires an understanding of the interactions among the atmosphere, plant communities, and soils. Temperature and pressure are often measured because of their role in air movement and energy exchange between the earth’s surface and the atmosphere. Temperature is perhaps of greater interest in agricultural applications because it is a driving variable that determines the rate of growth and development of an organism, and thus determines what species can grow in a region. Wind speed and direction are measured because of their role in convective energy exchange and the movement of spores, pollen, odors, and chemicals as they drift in the atmosphere. Precipitation amount, intensity, frequency, and form are important in determining the availability of water for crops and play an important role in soil erosion by water and in water quality issues. Solar radiation and relative humidity are additional weather variables, important to agriculture, that are often measured by appropriate sensors at automated weather stations. These variables will be discussed by Klassen and Bugbee (2005, this volume) and Campbell and Diak (2005, this volume)

Southern great plains 1997 hydrological experiment: vegetation sampling and data documentation

"Prepared for the United States Department of Agriculture, Agricultural Research Service"--Cover

ESTIMATING CORN YIELD RESPONSE MODELS TO PREDICT IMPACTS OF CLIMATE CHANGE

Projections of the impacts of climate change on agriculture require flexible and accurate yield response models. Typically, estimated yield response models have used fixed calendar intervals to measure weather variables and omitted observations on solar radiation, an essential determinant of crop yield. A corn yield response model for Illinois crop reporting districts is estimated using field data. Weather variables are time to crop growth stages to allow use of the model if climate change shifts dates of the crop growing season. Solar radiation is included. Results show this model is superior to conventionally specified models in explaining yield variation in Illinois corn.Crop Production/Industries,

Midwestern Climate Center soils atlas and database

Includes bibliographical references (p. 36)

Remote sensing of corn and soybean canopy productivity: data collection and documentation

"Prepared for the U.S. Department of Agriculture"--Cover."August 2001.

Operation of rain gage and ground-water monitoring networks for the Imperial Valley Water Authority: year seven, September 1998-August 1999

"August 2000.""Prepared for the Imperial Valley Water Authority."Duplicate of http://hdl.handle.net/2142/54955</a

Identification of factors that aid carbon sequestration in Illinois agricultural systems

"Final report to Illinois Council on Food and Agricultural Research (C-FAR) on contract IDACF 02E 145 WS.""March 2003.""Contract report 2003-02.""Steven E. Hollinger, Principal investigator.

Weather-caused unexpected record high corn yields

ABSTRACT Average corn yields in a four-county area of 6,422 km 2 in Illinois exceeded 11945 kg/ha in 2003, setting new statewide records and more than 945 kg/ha above previous high yields in this area. During the growing season, crop experts noted that the July weather was ideal but also predicted that the hot, dry August conditions would reduce average corn yields to 9431 kg/ha, which was 2514 kg/ha below the actual harvested yields. Examination of the weather conditions and plant stages during 2003 revealed that several factors led to the record yields. Factors that collectively caused rapid vegetative growth, maintained high plant density, and created extensive ear-filling were: rapid corn emergence after extensive early planting in April, deep rooting during a dry 3-week period in May, and frequent sunny skies in May-July coupled with timely rains, normal temperatures, few hot days, and adequate soil moisture. Moisture needs during the hot, dry August were met with high moisture levels in moderate to deep soils which eliminated potential crop stress. Comparison of the 2003 growing-season weather with that of 1994, when prior but lower yield records were set, revealed that the high frequency of clear skies and very few hot days were key to the higher yields in 2003. Sunny days from April through August 2003 were nearly double the monthly averages and greatly aided plant development, ear filling, and kernel weight. The number of days with maximum temperatures &gt;32 o C was only 56% of the average number, thereby minimizing heat stress. Because most crop experts did not detect the unusual combination of 2003 good weather factors, they predicted lower yields than occurred and were greatly surprised at the record yield outcome

Real-time web-based dissemination of Illinois soil temperature

"Prepared for the Illinois Department of Agriculture"--Cover