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- Author or Editor: Claude E. Duchon x
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Abstract
A series of nomograms is presented showing the longwave radiation temperature correction for various thermocouple wire diameters, different values of emitted and absorbed radiation, and for wind speeds from zero to 10 m sec−1. The temperature correction is computed from the steady-state balance between radiative and convective heat transfers and is to be added to the measured temperature. The radiation field is based upon previous measurements made under clear nighttime skies and the free and forced convection correlation formulae are adopted from wind tunnel experiments.
Abstract
A series of nomograms is presented showing the longwave radiation temperature correction for various thermocouple wire diameters, different values of emitted and absorbed radiation, and for wind speeds from zero to 10 m sec−1. The temperature correction is computed from the steady-state balance between radiative and convective heat transfers and is to be added to the measured temperature. The radiation field is based upon previous measurements made under clear nighttime skies and the free and forced convection correlation formulae are adopted from wind tunnel experiments.
Abstract
A method is developed to predict corn yield during the growing season using a plant process model (CERES-Maize), current weather data and climatological data. The procedure is to place the current year's daily weather (temperature and precipitation) into the model up to the time the yield prediction is to be made and sequences of historical data (one sequence per year) after that time until the end of the growing season to produce yield estimates. The mean of the distribution of yield estimates is taken as the prediction. The variance associated with a prediction is relatively constant until the time of tassel initiation and then decreases toward zero as the season progresses. As a consequence, perfect weather forecasts reach their peak value between the beginning of car growth and the beginning of grain fill.
The change in the predicted yield in response to weather as the growing season progresses is discussed for 1983 and 1976 at Peoria, Illinois. Results are given of an attempt to incorporate 30-day Climate Analytic Center outlooks into the predictive scheme.
Abstract
A method is developed to predict corn yield during the growing season using a plant process model (CERES-Maize), current weather data and climatological data. The procedure is to place the current year's daily weather (temperature and precipitation) into the model up to the time the yield prediction is to be made and sequences of historical data (one sequence per year) after that time until the end of the growing season to produce yield estimates. The mean of the distribution of yield estimates is taken as the prediction. The variance associated with a prediction is relatively constant until the time of tassel initiation and then decreases toward zero as the season progresses. As a consequence, perfect weather forecasts reach their peak value between the beginning of car growth and the beginning of grain fill.
The change in the predicted yield in response to weather as the growing season progresses is discussed for 1983 and 1976 at Peoria, Illinois. Results are given of an attempt to incorporate 30-day Climate Analytic Center outlooks into the predictive scheme.
Abstract
A Fourier method of filtering digital data called Lanczos filtering is described. Its principal feature is the use of “sigma factors” which significantly reduce the amplitude of the Gibbs oscillation. A pair of graphs is developed that can be used to determine filter response quality given the number of weights and the value of the cutoff frequency, the only two inputs required by the method. Examples of response functions in one and two dimensions are given and comparisons are made with response functions from other filters. The simplicity of calculating the weights and the adequate response make Lanczos filtering an attractive filtering method.
Abstract
A Fourier method of filtering digital data called Lanczos filtering is described. Its principal feature is the use of “sigma factors” which significantly reduce the amplitude of the Gibbs oscillation. A pair of graphs is developed that can be used to determine filter response quality given the number of weights and the value of the cutoff frequency, the only two inputs required by the method. Examples of response functions in one and two dimensions are given and comparisons are made with response functions from other filters. The simplicity of calculating the weights and the adequate response make Lanczos filtering an attractive filtering method.
Abstract
The steady-state radiation temperature correction for a spherical temperature sensor, defined as the difference between the observed sensor temperature and the true air temperature, is computed for clear nighttime conditions in terms of five meteorological and physical parameters: sphere diameter, wind speed, observed sensor temperature, total incident radiation, and the absorptivities and emissivity of the sphere. The range of values encompassed by these parameters are, respectively, 0.001 to 0.1 cm, 0 to 400 cm set−1, 270 to 300K, 0.009 to 0.020 cal sec−1 cm−2, and 0 to 1.
The infrared radiation incident on a sphere in the boundary layer of the atmosphere is related matic- matically to the radiation observed by a flat plate type of radiometer. The derived relationship is based on previous measurements of the spatial distribution of the intensity of infrared sky radiation.
Numerically, the radiation temperature correction is determined by using a sequence of three graphs in-corporating the various parameters. The correction, to be added to the observed sensor temperature, varies from less than 0.01K to 3K.
Abstract
The steady-state radiation temperature correction for a spherical temperature sensor, defined as the difference between the observed sensor temperature and the true air temperature, is computed for clear nighttime conditions in terms of five meteorological and physical parameters: sphere diameter, wind speed, observed sensor temperature, total incident radiation, and the absorptivities and emissivity of the sphere. The range of values encompassed by these parameters are, respectively, 0.001 to 0.1 cm, 0 to 400 cm set−1, 270 to 300K, 0.009 to 0.020 cal sec−1 cm−2, and 0 to 1.
The infrared radiation incident on a sphere in the boundary layer of the atmosphere is related matic- matically to the radiation observed by a flat plate type of radiometer. The derived relationship is based on previous measurements of the spatial distribution of the intensity of infrared sky radiation.
Numerically, the radiation temperature correction is determined by using a sequence of three graphs in-corporating the various parameters. The correction, to be added to the observed sensor temperature, varies from less than 0.01K to 3K.
Abstract
A method is presented for obtaining empirical confidence limits for variance spectra. It can be applied whenever the distribution of spectral variances is unknown but the stochastic model of the data is known or proposed.
For computer-generated white noise the results show that the normalized raw spectral variances do not vary as the theoretical model, χ2 10/10, predicts due to the appearance of expected negative line variances. Thus, the lower a priori and a posteriori confidence limits are less than their theoretical counterparts. The empirical confidence limits for normalized hanned spectral variances agree with those from the theoretical model, χ2 27/27.
Abstract
A method is presented for obtaining empirical confidence limits for variance spectra. It can be applied whenever the distribution of spectral variances is unknown but the stochastic model of the data is known or proposed.
For computer-generated white noise the results show that the normalized raw spectral variances do not vary as the theoretical model, χ2 10/10, predicts due to the appearance of expected negative line variances. Thus, the lower a priori and a posteriori confidence limits are less than their theoretical counterparts. The empirical confidence limits for normalized hanned spectral variances agree with those from the theoretical model, χ2 27/27.
Observations at the San Juan, Puerto Rico international airport show that the annual mean temperature has increased by about 2.1°C (3.8°F) from 1956 to 1983. The chief contributors to the increase are an increase in daily minimum temperature from 1956 to about 1970 and an increase in daily maximum temperature from about 1970 to 1983. In addition, there is evidence for veering of the wind direction so that overland trajectories are more frequent. No comparable temperature change has been measured at a cooperative station 8 km to the southwest in the city of San Juan nor at other stations in Puerto Rico, thus ruling out a synoptic-scale phenomenon. It is hypothesized that as the airport expanded in size and the vegetation diminished, a mini heat island evolved. The heat island combined with the development of adjacent residential and commercial areas and a changing wind direction account for the observed annual mean temperature increase.
Observations at the San Juan, Puerto Rico international airport show that the annual mean temperature has increased by about 2.1°C (3.8°F) from 1956 to 1983. The chief contributors to the increase are an increase in daily minimum temperature from 1956 to about 1970 and an increase in daily maximum temperature from about 1970 to 1983. In addition, there is evidence for veering of the wind direction so that overland trajectories are more frequent. No comparable temperature change has been measured at a cooperative station 8 km to the southwest in the city of San Juan nor at other stations in Puerto Rico, thus ruling out a synoptic-scale phenomenon. It is hypothesized that as the airport expanded in size and the vegetation diminished, a mini heat island evolved. The heat island combined with the development of adjacent residential and commercial areas and a changing wind direction account for the observed annual mean temperature increase.
Abstract
Accurate measurements of net radiation are basic to all studies of the surface energy budget. In preparation for an energy budget experiment significant differences were found between direct and component measurement of net radiation, which prompted this investigation of their cause. The instruments involved were an all-black single-dome Fritschen-type net pyrradiometer, two Eppley model 8–48 pyranometers, and an Eppley model PIR pyrgeometer. Each had recently been calibrated. The accuracy of the component instruments was considered first. Comparisons of about one hour on each of three nights between the pyrgeometer and five empirical formulas showed that the average departure over all formulas from the pyrgeometer average was −1%. Other comparisons between the pyrgeometer and an infrared thermometer viewing the surface yielded similar results. Alternate shading and unshading of the pyrgeometer looking upward during daytime resulted in a formula that was used to correct the downward longwave radiation under clear skies. The correction is dependent on wind speed, in contrast to a recent paper showing negligible dependence, but is in accord with earlier findings. Based on the manufacturer's specifications, the pyranometer calibrations were considered to be within 2% of the World Radiation Reference.
Thus a series of experiments was carried out using what were believed to be reasonably accurate component measurements of net radiation and measurements from the net pyrradiometer. The results showed that the sensitivity of the latter was less in the longwave band than in the shortwave band in agreement with findings of others. Speculating on possible further dependence of sensitivity to the upward and downward streams of radiation, a method was developed to determine the magnitude of the individual net pyrmdiometer components. A reflective double-shell hemispherical cup was affixed to the upward or downward face of the net pyrradiometer such that linear regression could be applied to simultaneous measurements from the net pyrradiometer, pyranometer, pyrgeometer, and the inner cup temperature, assumed to he at air temperature, to estimate the individual components. Although a substantial difference in shartwave sensitivity was computed using this method, the result was not definitive because of the limited number and the narrow range of longwave observations. Nevertheless, the method can be employed in the field to verify uniform sensitivity of a net pyrradiometer's sensing surfaces to shortwave and longwave radiation. The method may have particular application to Fritschen-type net pyrradiometers of recently improved design after extended field use.
Abstract
Accurate measurements of net radiation are basic to all studies of the surface energy budget. In preparation for an energy budget experiment significant differences were found between direct and component measurement of net radiation, which prompted this investigation of their cause. The instruments involved were an all-black single-dome Fritschen-type net pyrradiometer, two Eppley model 8–48 pyranometers, and an Eppley model PIR pyrgeometer. Each had recently been calibrated. The accuracy of the component instruments was considered first. Comparisons of about one hour on each of three nights between the pyrgeometer and five empirical formulas showed that the average departure over all formulas from the pyrgeometer average was −1%. Other comparisons between the pyrgeometer and an infrared thermometer viewing the surface yielded similar results. Alternate shading and unshading of the pyrgeometer looking upward during daytime resulted in a formula that was used to correct the downward longwave radiation under clear skies. The correction is dependent on wind speed, in contrast to a recent paper showing negligible dependence, but is in accord with earlier findings. Based on the manufacturer's specifications, the pyranometer calibrations were considered to be within 2% of the World Radiation Reference.
Thus a series of experiments was carried out using what were believed to be reasonably accurate component measurements of net radiation and measurements from the net pyrradiometer. The results showed that the sensitivity of the latter was less in the longwave band than in the shortwave band in agreement with findings of others. Speculating on possible further dependence of sensitivity to the upward and downward streams of radiation, a method was developed to determine the magnitude of the individual net pyrmdiometer components. A reflective double-shell hemispherical cup was affixed to the upward or downward face of the net pyrradiometer such that linear regression could be applied to simultaneous measurements from the net pyrradiometer, pyranometer, pyrgeometer, and the inner cup temperature, assumed to he at air temperature, to estimate the individual components. Although a substantial difference in shartwave sensitivity was computed using this method, the result was not definitive because of the limited number and the narrow range of longwave observations. Nevertheless, the method can be employed in the field to verify uniform sensitivity of a net pyrradiometer's sensing surfaces to shortwave and longwave radiation. The method may have particular application to Fritschen-type net pyrradiometers of recently improved design after extended field use.
Abstract
No abstract available.
Abstract
No abstract available.
Abstract
A cross-spectral analysis method is developed to estimate the noise variance spectra of three or more independent measurement systems observing the same input. The noise is modeled using a first-order autoregressive process. Estimates of the two process parameters are used to determine confidence limits for system noise that can be placed on the observed data.
The method has been applied to dew-point data collected in aircraft intercomparison flights and a research flight in the National Hail Research Experiment. The six dew-point systems used were manufactured by the same company and operate by electrically cooling a metal mirror until a film of water vapor or frost is optically detected on the mirrored surface. The ratio of the signal to noise variance was found to vary between about 10:1 and 100:1 at the origin and decrease to zero between about 0.15 and 0.3 Hz, both properties dependent on atmospheric conditions and the structure of system noise. Since the data were collected once per second, appropriate filtering and decimation could be performed for archiving purposes with a 50% space savings and small loss of “information.” Ninety-five percent confidence limits on the filtered observed data with a cutoff at 0.2 Hz vary from ±0.5 to ±0.1°C, with the latter figure most representative of those computed.
Abstract
A cross-spectral analysis method is developed to estimate the noise variance spectra of three or more independent measurement systems observing the same input. The noise is modeled using a first-order autoregressive process. Estimates of the two process parameters are used to determine confidence limits for system noise that can be placed on the observed data.
The method has been applied to dew-point data collected in aircraft intercomparison flights and a research flight in the National Hail Research Experiment. The six dew-point systems used were manufactured by the same company and operate by electrically cooling a metal mirror until a film of water vapor or frost is optically detected on the mirrored surface. The ratio of the signal to noise variance was found to vary between about 10:1 and 100:1 at the origin and decrease to zero between about 0.15 and 0.3 Hz, both properties dependent on atmospheric conditions and the structure of system noise. Since the data were collected once per second, appropriate filtering and decimation could be performed for archiving purposes with a 50% space savings and small loss of “information.” Ninety-five percent confidence limits on the filtered observed data with a cutoff at 0.2 Hz vary from ±0.5 to ±0.1°C, with the latter figure most representative of those computed.
Abstract
An improved parameterization is presented for estimating effective atmospheric emissivity for use in calculating downwelling longwave radiation based on temperature, humidity, pressure, and solar radiation observations. The first improvement is the incorporation of an annual sinusoidal variation in effective clear-sky atmospheric emissivity, based on typical climatological variations in near-surface vapor pressure. The second is the continuous estimation of fractional cloudiness by taking the ratio of observed solar radiation to a modeled clear-sky solar radiation. Previous methods employed observer-estimated fractional cloudiness. Data from the Atmospheric Radiation Measurement (ARM) program were used to develop these improvements. The estimation of cloudiness was then used to modify the effective clear-sky atmospheric emissivity in order to calculate 30-min averages of downwelling longwave radiation. Monthly mean bias errors (mbe’s) of −9 to +4 W m−2 and root-mean-square errors (rmse’s) of 11–22 W m−2 were calculated based on ARM data over a 1-yr period. These mbe’s were smaller overall than any of the six previous methods tested, while the rmse’s were similar to the best previous methods. The improved parameterization was then tested on FIFE data from the summer of 1987. Although the monthly mbe’s were larger, the rmse’s were smaller.
It is also shown that data from upper-air soundings can be used to calculate the effective atmospheric emissivity rather than specifying the aforementioned sinusoidal variation. Using ARM upper-air soundings, this method resulted in larger mbe’s, −7 to +11 W m−2, especially during the summer months, and similar rmse’s. The success of the method suggests that it has application at any observing site within reasonable proximity of an upper-air sounding, while removing the empiricism used to specify the annual sinusoidal variation in emissivity.
Abstract
An improved parameterization is presented for estimating effective atmospheric emissivity for use in calculating downwelling longwave radiation based on temperature, humidity, pressure, and solar radiation observations. The first improvement is the incorporation of an annual sinusoidal variation in effective clear-sky atmospheric emissivity, based on typical climatological variations in near-surface vapor pressure. The second is the continuous estimation of fractional cloudiness by taking the ratio of observed solar radiation to a modeled clear-sky solar radiation. Previous methods employed observer-estimated fractional cloudiness. Data from the Atmospheric Radiation Measurement (ARM) program were used to develop these improvements. The estimation of cloudiness was then used to modify the effective clear-sky atmospheric emissivity in order to calculate 30-min averages of downwelling longwave radiation. Monthly mean bias errors (mbe’s) of −9 to +4 W m−2 and root-mean-square errors (rmse’s) of 11–22 W m−2 were calculated based on ARM data over a 1-yr period. These mbe’s were smaller overall than any of the six previous methods tested, while the rmse’s were similar to the best previous methods. The improved parameterization was then tested on FIFE data from the summer of 1987. Although the monthly mbe’s were larger, the rmse’s were smaller.
It is also shown that data from upper-air soundings can be used to calculate the effective atmospheric emissivity rather than specifying the aforementioned sinusoidal variation. Using ARM upper-air soundings, this method resulted in larger mbe’s, −7 to +11 W m−2, especially during the summer months, and similar rmse’s. The success of the method suggests that it has application at any observing site within reasonable proximity of an upper-air sounding, while removing the empiricism used to specify the annual sinusoidal variation in emissivity.
