Steven J. Meyer

Estimating potential evapotranspiration: the effect of random and systematic errors

Random and systematic errors, inherent in meteorological measurements, affect the values of variables used to estimate potential evapotranspiration (ETp). A simulation approach was used to study the effect of the magnitude of those errors on daily ETp estimates over the course of a growing season. Previous attempts to quantify the effect of errors in those variables have been conducted using only 24 h of data. In this study, daily ETp was calculated with the Penman method using data collected at four locations in Nebraska during the 1985 growing season. These ETp values were compared to estimates made after introducing random and systematic errors to the input data. Errors in ETp estimates were progressively larger for errors introduced into the wind run, temperature, humidity, and radiation data leading to the conclusion that accuracy and calibration of humidity and radiation sensors is more critical than wind run and temperature in the Central High Plains of the U.S.

Nonfederal Automated Weather Stations and Networks in the United States and Canada: A Preliminary Survey*

Abstract Not all weather data are collected by federal agencies. Fueled by the need for more specific meteorological data in real or near-real time, the number of automated weather stations (AWSS) and AWS networks has expanded to the state and private sector over the past decade. This study employed a survey to determine the spatial extent and disposition of these nonfederal AWSs and AWS networks in the United States and Canada, the type of measurements taken, the operating procedures (i.e., maintenance and data-retrieval techniques), and the uses of the data (e.g., research, public service, agency needs). The rapid growth and expansion in the number of AWSs and networks can be viewed as a positive step toward expanding data available for meteorological research and service. As AWS networks continue to grow and expand in the United States and Canada, it is recommended that an AWS climatic database be established. With proper logistical coordination and the cooperation of network operators, development of ...

Genetically Engineered Plants, Endangered Species, and Risk: A Temporal and Spatial Exposure Assessment for Karner Blue Butterfly Larvae and Bt Maize Pollen

Genetically engineered maize (Zea mays) containing insecticidal endotoxin proteins from Bacillus thuringiensis (Bt) delta-endotoxin proteins has been adopted widely in the Midwestern United States. The proteins are toxic to several lepidopteran species and because a variety of maize tissues, including pollen, may express the endotoxins, the probability of exposure to nontarget species, including endangered species, needs to be understood. The objective of this study was to assess the potential temporal and spatial exposure of endangered Karner blue butterfly larvae (Lycaeides melissa samuelis) to Bt maize pollen in Wisconsin using probabilistic exposure techniques and geographic information systems analysis. Based on degree-day modeling of butterfly phenology and maize pollen shed, there is some potential for temporal exposure of larvae to maize pollen. However, in the majority of years and locations, maize pollen shed most likely will occur after the majority of larval feeding on wild lupine (Lupinus perennis). The spatial analysis indicates that some Karner blue butterfly populations occur in close proximity to maize fields, but in the vast majority of cases the butterflys host plant and maize fields are separated by more than 500 m. A small number of potential or existing Karner blue butterfly sites are located near maize fields, including sites in two of the four counties where temporal overlap is most likely. The exposure assessment indicates that these two counties should receive the highest priority to determine if Karner blue butterfly larvae are actually at risk and then, if needed, to reduce or prevent exposure.

Nonfederal Automated Weather Stations and Networks in the United States in the United States and Canada: A Preliminary Survey

Abstract Not all weather data are collected by federal agencies. Fueled by the need for more specific meteorological data in real or near-real time, the number of automated weather stations (AWSS) and AWS networks has expanded to the state and private sector over the past decade. This study employed a survey to determine the spatial extent and disposition of these nonfederal AWSs and AWS networks in the United States and Canada, the type of measurements taken, the operating procedures (i.e., maintenance and data-retrieval techniques), and the uses of the data (e.g., research, public service, agency needs). The rapid growth and expansion in the number of AWSs and networks can be viewed as a positive step toward expanding data available for meteorological research and service. As AWS networks continue to grow and expand in the United States and Canada, it is recommended that an AWS climatic database be established. With proper logistical coordination and the cooperation of network operators, development of ...

The relationship of climatic indices and variables to corn (maize) yields: a principal components analysis☆

Abstract The multivariate statistical technique of principal components analysis was used to evaluate the relationship of climatic indices and variables to corn ( Zea mays L.) yields in the Great Plains and Midwest of the United States. Results demonstrated that during years in which precipitation was consistently above or below normal throughout the growing season, the Palmer Drought Severity Index (PDSI) and the Crop Moisture Index (CMI) related well to actual yield. However, during years in which there was an occurrence of dry or wet spells lasting for several weeks (particularly during pollination), the magnitude of the PDSI and the CMI did not adequately reflect the impact of that dry or wet period on the crop. The results of this analysis demonstrate that principal components analysis is a powerful statistical tool for evaluating the relationship between crop yield and climatic variables and the associated regional patterns for these relationships.

Predicting movement of stalk borer (Lepidoptera: Noctuidae) larvae in corn

Abstract The stalk borer [Papaipema nebris (Guenee)], is a sporadic, yet serious pest of corn, (Zea mays L.), in the midwestern USA, particularly where corn fields are adjacent to grassy areas, such as roadside ditches, grass waterways, and terraces. An important management strategy is to apply an insecticide when the larvae move from the initial grass or broadleaf hosts to corn hosts. After the larvae bore into corn stalks, they are much more difficult to manage. Therefore, predicting the movement of larvae from weed hosts to corn hosts is crucial. This study was conducted to determine probable dates for stalk borer larval movement using climatic data from 67 locations across portions of South Dakota, Nebraska, Kansas, Minnesota, Iowa, Missouri, Wisconsin, Illinois, Michigan, and Indiana. We also examined the difference in probable dates of larval movement using the entire climate data record (60–90 yr) as opposed to using the 30-yr climatic normal record (1961–1990). The minimum number of degree-days (780 Celsius degree-days 4.4 °C base temperature) in which larvae move from initial weed hosts to corn, were accumulated for each year in the climate record beginning 1 March and correlated with calendar dates. The mean date of larval movement in the in the states examined spans approximately 3 weeks, from 2 June in the southern portions to 23 June in the northern portions. Standard deviations about the mean date of larval movement were 5, 6, and 7 days in the southern, central, and northern portions, respectively. There was little difference between predicted dates using long-term climatic data compared to those using 30-yr climatic normal data.

Improving Projected Potential Evapotranspiration Estimates Using National Weather Service Forecasts

Abstract In a recent survey conducted by the University of Nebrasks Center for Agricultural Meteorology and Climatology of Agricultural Network (AGNET) users, the results of potential evapotranspiration (ETp) projections (calculated using the Blaney-Criddle approach, which employs “normal” climatic data to project ETp, estimates up to three days into the future) were labeled “unrealistic”. To improve these projection National Weather Service (NWS) forecast variables were used as input into the Blancy-Criddle and Penman equations. ETp, projections calculated according to the Penman equation, with data measured by automated weather stations as input, were assumed to represent the “best” attainable. ETp projections calculated using NWS forecasted values were compared with the “best” projections for the summer of 1985. Increased accuracy in ETp, projections due to increased accuracy in the individual forecasted input variables was evaluated. Overall, daily ETp, projections made with the Blancy-Criddle equati...