Claude E. Duchon

Lanczos Filtering in One and Two Dimensions

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.

An Improved Parameterization for Estimating Effective Atmospheric Emissivity for Use in Calculating Daytime Downwelling Longwave Radiation

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 11–2...

Comparative rainfall observations from pit and aboveground rain gauges with and without wind shields

A study of rain gauge observations was initiated in 1995 to assess the magnitude of undercatch due to wind and the effect of reducing undercatch using an Alter-type wind shield. The observation site was near the Norman, Oklahoma, airport with good exposure in all directions. The experimental setup comprised three tipping-bucket rain gauges, three weighing-bucket rain gauges, and anemometers at 1 and 2 m. For each type of gauge, one was placed in a pit with its orifice at ground level, and the other two were placed above ground, one with an Alter shield and one without. One-minute rainfall accumulations and wind speed averages were obtained from 101 rainfall events over 30 months. The results show that for typical rainfall events, the undercatch of the unshielded tipping-bucket rain gauges was 4% relative to the tipping-bucket pit gauge. The comparable figure for the unshielded weighing-bucket gauge was 5%. Both Alter-shielded gauges showed less than a 1% reduction in undercatch relative to the unshielded gauges for typical rainfall events. We discuss the sources of errors that can be expected in similar rain gauge measurements when the gauges are properly maintained.

Estimating Cloud Type from Pyranometer Observations

In this paper the authors evaluate an inexpensive and automatable method to estimate cloud type at a given location during daylight hours using the time series of irradiance from a pyranometer. The motivation for this investigation is to provide ground-based estimates of cloud type at locations where there are no human observations of sky condition. A pyranometer naturally measures the effect of intervening clouds along the solar beam path to the sensor. Because a daily time series of irradiance is nonstationary, it is appropriately scaled to yield a stationary time series. From the latter, the standard deviation and ratio of observed irradiance to clear-sky irradiance derived from a 21-min moving window are related to one of the following cloud types or conditions: cirrus, cumulus, cirrus and cumulus, stratus, precipitation or fog, no clouds, and other clouds. Comparisons with human observations at the Department of Energy Atmospheric Radiation Measurement Calibration and Radiation Testbed site in northern Oklahoma show that the pyranometer method and human observations are in agreement about 45% of the time. Many of the differences can be attributed to two factors: 1) the pyranometer method is weighted toward clouds crossing the sun’s path, while the human observer can view clouds over the entire sky, and 2) the presence of aerosols causes the pyranometer to overestimate the occurrence of cirrus and cirrus plus cumulus. When attenuation of the solar beam by aerosols is negligible or can be accounted for, the pyranometer method should be especially useful for cloud-type assessment where no other sky observations are available.

Corn Yield Prediction Using Climatology

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 years 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 ear 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. 21 references, 14 figures, 1 table.

Assessment of Rainfall Estimates Using a Standard Z-R Relationship and the Probability Matching Method Applied to Composite Radar Data in Central Florida

Abstract Precipitation estimates from radar systems are a crucial component of many hydrometeorological applications, from dash flood forecasting to regional water budget studies. For analyses on large spatial scales and long timescales, it is frequently necessary to use composite reflectivities from a network of radar systems. Such composite products are useful for regional or national studies, but introduce a set of difficulties not encountered when using single radars. For instance, each contributing radar has its own calibration and scanning characteristics, but radar identification may not be retained in the compositing procedure. As a result, range effects on signal return cannot be taken into account. This paper assesses the accuracy with which composite radar imagery can be used to estimate precipitation in the convective environment of Florida during the summer of 1991. Results using Z = 300 R1.4. (WSR-88D default Z-R relationship) are compared with those obtained using the probability matching m...

An example of using Landsat and GOES data in a water budget model

Landsat and GOES satellite data are used in analyzing monthly water budgets on a 538-km2 watershed in central Oklahoma for 1984–1985. The budget components examined are water yield, percolation loss, evapotranspiration and change in soil water content. The hydrologic model employed is SWRRB (Simulator for Water Resources in Rural Basins) developed by the Agricultural Research Service of the U.S. Department of Agriculture. Landsat imagery is used to subdivide the basin into land covers for model application. The land cover subareas are more homogeneous than subbasins with mixed vegetation and their use allows tracking of the unique contribution of each type of cover to the water budget. Daily insolation is determined from GOES imagery. A comparison of budget components based on pyranometer insolation versus unbiased GOES estimates shows a maximum difference less than 4% and 5 mm for any component of the annual and monthly budgets, respectively. Satellite-derived temperatures are simulated by adding systematic and random errors to observed temperatures. A temperature bias of a few degrees greatly changes the growing season and monthly budgets of winter wheat.

Effect of Ship Heating on Dry-Bulb Temperature Measurements in GATE

Abstract The effect of ship heating on dry-bulb temperature measurements made during GATE is investigated. It is found that measurements taken on a bow boom are less affected than those taken on the ships bridge. It is also seen that the ship heating effect must be accounted for before meaningful estimates of the error content of dry-bulb temperature measurement systems can be determined.

Effect of the number of soil layers on a modeled surface water budget

A sensitivity analysis was performed to determine the effects of systematically increasing the number of soil layers in a land surface-atmosphere model on the components of the modeled water budget. The study was done for a forested location in central Oklahoma for a 65-day period in spring 1996 using the model called Simulator for Hydrology and Energy Exchange at the Land Surface (SHEELS). SHEELS is based on the Biosphere-Atmosphere Transfer Scheme (BATS), except that the subsurface hydrology was substantially changed to improve representation of the soil moisture profile. The soil profile was divided into zones of thickness 0.05 m (upper), 1.25 m (root), and 1.20 m (bottom). The two principal conclusions are that (1) the water budget is very sensitive to the number of layers in the soil profile under wet conditions and (2) the water budget is much more sensitive to the number of layers in the profile than to the range of 2 orders of magnitude in saturated hydraulic conductivity considered in this study. A result of the latter conclusion is that larger errors in modeled water fluxes can occur from using an insufficient number of soil layers than from using an incorrect value of saturated hydraulic conductivity.

Long-Range Transport of Air Pollution: A Case Study, August 1970

Abstract An air pollution episode during August 1970 over the central United States is examined. By use of surface visibilities and an 850-mb wind trajectory analysis, we observed the pollution to advance as much as 700 mi from the central midwest (source region) into the upper midwest and Great Plains (impact area). A large, nearly stationary high-pressure system over the source region allowed the pollution to accumulate beneath a mid-level subsidence inversion located generally near 700 mb. Southeasterly flow around the backside of the High and the northeasterly flow around a weak Low to the south advected the pollution into the impact area. At times, surface visibilities in parts of the impact area were restricted by haze to as little as 4 mi. Although particulate count data were meager, several stations recorded their highest particulate count of the year during the episode.