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J. A. Warburton and L. G. Young

Abstract

Thermal neutron activation methods have been applied to the determination of silver content in samples of hail, rain and snow. Hail and rain samples were collected in South Dakota in regions where AgI cloud seeding was being conducted; the snow was collected in the eastern Sierra Nevada in an area where no such seeding was being conducted. No silver was detected in the snow samples analyzed, indicating concentrations on the average less than 2.5 × 10−11 gm ml−1. Eighty percent of the hail and rain samples analyzed contained measurable quantities of silver up to 70 times the minimum detectable amount. Some of these latter samples were collected in nominally unseeded areas, and although the chemical form in which the silver entered the precipitation is unknown—thereby casting doubt on its consequence—the observations raise important questions which deserve answers, particularly as they may affect statistical evaluations of weather modification experiments.

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J. A. Warburton and L. G. Young

Abstract

Laboratory techniques have been developed for concentrating and isolating silver from aqueous samples. When these concentrated samples are activated in a thermal neutron flux of 4 × 1012n cm−2 sec−1, quantitative measurements down to 10−9 gm masses of silver can be made. When 1-liter samples of water are used, the lower limit of detection of silver in the sample is about 3 × 10−12 gm cm−3 concentration. Typical Ag concentrations being observed in snow collected in the western United States range from this lower limit to 10−8 gm cm−3, the majority being between 10−9 and 10−11. The lower limit does not therefore appear to be a serious factor in silver determinations in snow collected at ground stations. The system described is a non-destructive one, the accuracy of measurement using γ-ray spectrometry being 1, 2, 10 and 80% for masses of silver 10−6, 10−7, 10−8 and 10−9 gm, respectively. By using a 24-sec half-life radioisotope for the Ag determination, the cost of activation and turn-around time on samples is kept to a minimum. Data analysis is computerized and rapid.

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J. A. Warburton, L. G. Young, and R. H. Stone

Abstract

Trace chemical analysis techniques have been used in a series of cloud-seeding experiments in the central Sierra Nevada with the ultimate purpose of distinguishing whether the submicron-sized aerosol particles used for seeding are removed by nucleation or by scavenging in snowfall. The research programs used submicron-sized seeding aerosols with different nucleating characteristics. When winter storms were seeded with silver iodide in the Lake Tahoe and Lake Almanor watersheds, positive correlations were observed between silver concentrations and precipitation amounts in both catchment areas.This is considered to be evidence that the AgI aerosols are not being removed in the snowfall entirely by scavenging processes. When two separate aerosols of silver iodide and indium sesquioxide were released simultaneously from the same ground locations during winter snowstorms in the Lake Almanor watershed, it was found that considerably more of the ice-nucleating aerosol particles (AgI) were removed by the snowfall than the non-ice-nucleating ones (In203). Under the experimental conditions employed, scavenging alone of the two aerosols would lead to a chemical ratio of Ag:In in the snowfall of 0.83:l. Ratios as high as 17.2:l were observed, the mean ratio being 4: I. These results are considered to be evidence of the removal of substantial numbers of the AgI aerosol particles through direct nucleation of ice crystals.

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T. C. McCandless, G. S. Young, S. E. Haupt, and L. M. Hinkelman

Abstract

This paper describes the development and testing of a cloud-regime-dependent short-range solar irradiance forecasting system for predictions of 15-min-average clearness index (global horizontal irradiance). This regime-dependent artificial neural network (RD-ANN) system classifies cloud regimes with a k-means algorithm on the basis of a combination of surface weather observations, irradiance observations, and GOES-East satellite data. The ANNs are then trained on each cloud regime to predict the clearness index. This RD-ANN system improves over the mean absolute error of the baseline clearness-index persistence predictions by 1.0%, 21.0%, 26.4%, and 27.4% at the 15-, 60-, 120-, and 180-min forecast lead times, respectively. In addition, a version of this method configured to predict the irradiance variability predicts irradiance variability more accurately than does a smart persistence technique.

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Jose Henrique G. M. Alves, Michael L. Banner, and Ian R. Young

Abstract

The time-honored topic of fully developed wind seas pioneered by Pierson and Moskowitz is revisited to review the asymptotic evolution limits of integral spectral parameters used by the modeling community in the validation of wind-wave models. Discrepancies are investigated between benchmark asymptotic limits obtained by scaling integral spectral parameters using alternative wind speeds. Using state-of-the-art wind and wave modeling technology, uncertainties in the Pierson–Moskowitz limits due to inhomogeneities in the wind fields and contamination of the original data by crossing seas and swells are also investigated. The resulting reanalyzed database is used to investigate the optimal scaling wind parameter and to refine the levels of the full-development asymptotes of nondimensional integral wave spectral parameters used by the wind-wave modeling community. The results are also discussed in relation to recent advances in quantifying wave-breaking probability of wind seas. The results show that the parameterization of integral spectral parameters and the scaling of nondimensional asymptotes as a function of U 10 yields relations consistent with similarity theory. On the other hand, expressing integral spectral parameters and scaling nondimensional asymptotes as a function of u∗ or alternative proposed scaling wind speeds yields relations that do not conform to similarity requirements as convincingly. The reanalyzed spectra are used to investigate parameter values and shapes of analytical functions representing fully developed spectra. These results support an analytical form with a spectral tail proportional to f −4.

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C. M. R. Platt, S. A. Young, R. T. Austin, G. R. Patterson, D. L. Mitchell, and S. D. Miller

Abstract

This paper presents further results on the optical properties of tropical and equatorial cirrus using the light detecting and ranging (lidar) radiometer (LIRAD) method. The results were obtained from observations in the Maritime Continent Thunderstorm Experiment (MCTEX). Values were obtained of cirrus cloud backscatter coefficient, infrared (IR) emittance, optical depth and absorption coefficient, cloud height and depth, and backscatter-to-extinction ratio. The values agree well with previous results obtained on equatorial cirrus in the Pilot Radiation Observation Experiment (PROBE) and extend those results to lower temperatures. Observations made of lidar linear depolarization ratio show similar trends to those observed in PROBE, extending those results to lower temperatures.

Regressions of cloud IR emittance and absorption coefficients are performed as a preliminary tropical dataset for both cloud-resolving and climate models. These regressions are compared with previous regressions on midlatitude and tropical synoptic cirrus clouds. The IR absorption coefficients in tropical and equatorial cirrus appear to be larger than in midlatitude cirrus for temperatures less than −40°C, with the difference increasing toward low temperatures. Thus, a significantly different relationship may be appropriate for tropical cirrus compared to midlatitude cirrus clouds.

Effective diameters of small particles in the colder tropical clouds are also measured using the ratio of visible extinction to infrared absorption. A new treatment of multiple scattering is used to correct the ratios. Effective diameters range from 6 to 9.3 μm at the colder temperatures.

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A. Protat, S. A. Young, S. A. McFarlane, T. L’Ecuyer, G. G. Mace, J. M. Comstock, C. N. Long, E. Berry, and J. Delanoë

Abstract

The objective of this paper is to investigate whether estimates of the cloud frequency of occurrence and associated cloud radiative forcing as derived from ground-based and satellite active remote sensing and radiative transfer calculations can be reconciled over a well-instrumented active remote sensing site located in Darwin, Australia, despite the very different viewing geometry and instrument characteristics. It is found that the ground-based radar–lidar combination at Darwin does not detect most of the cirrus clouds above 10 km (because of limited lidar detection capability and signal obscuration by low-level clouds) and that the CloudSat radar–Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) combination underreports the hydrometeor frequency of occurrence below 2-km height because of instrument limitations at these heights. The radiative impact associated with these differences in cloud frequency of occurrence is large on the surface downwelling shortwave fluxes (ground and satellite) and the top-of-atmosphere upwelling shortwave and longwave fluxes (ground). Good agreement is found for other radiative fluxes. Large differences in radiative heating rate as derived from ground and satellite radar–lidar instruments and radiative transfer calculations are also found above 10 km (up to 0.35 K day−1 for the shortwave and 0.8 K day−1 for the longwave). Given that the ground-based and satellite estimates of cloud frequency of occurrence and radiative impact cannot be fully reconciled over Darwin, caution should be exercised when evaluating the representation of clouds and cloud–radiation interactions in large-scale models, and limitations of each set of instrumentation should be considered when interpreting model–observation differences.

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David R. Doelling, Norman G. Loeb, Dennis F. Keyes, Michele L. Nordeen, Daniel Morstad, Cathy Nguyen, Bruce A. Wielicki, David F. Young, and Moguo Sun

Abstract

The Clouds and the Earth’s Radiant Energy System (CERES) instruments on board the Terra and Aqua spacecraft continue to provide an unprecedented global climate record of the earth’s top-of-atmosphere (TOA) energy budget since March 2000. A critical step in determining accurate daily averaged flux involves estimating the flux between CERES Terra or Aqua overpass times. CERES employs the CERES-only (CO) and the CERES geostationary (CG) temporal interpolation methods. The CO method assumes that the cloud properties at the time of the CERES observation remain constant and that it only accounts for changes in albedo with solar zenith angle and diurnal land heating, by assuming a shape for unresolved changes in the diurnal cycle. The CG method enhances the CERES data by explicitly accounting for changes in cloud and radiation between CERES observation times using 3-hourly imager data from five geostationary (GEO) satellites. To maintain calibration traceability, GEO radiances are calibrated against Moderate Resolution Imaging Spectroradiometer (MODIS) and the derived GEO fluxes are normalized to the CERES measurements. While the regional (1° latitude × 1° longitude) monthly-mean difference between the CG and CO methods can exceed 25 W m−2 over marine stratus and land convection, these regional biases nearly cancel in the global mean. The regional monthly CG shortwave (SW) and longwave (LW) flux uncertainty is reduced by 20%, whereas the daily uncertainty is reduced by 50% and 20%, respectively, over the CO method, based on comparisons with 15-min Geostationary Earth Radiation Budget (GERB) data.

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D.L. Westphal, S. Kinne, P. Pilewskie, J.M. Alvarez, P. Minnis, D.F. Young, S.G. Benjamin, W.L. Eberhard, R.A. Kropfli, S.Y. Matrosov, J.B. Snider, T.A. Uttal, A.J. Heymsfield, G.G. Mace, S.H. Melfi, D.O'C. Starr, and J.J. Soden

Abstract

Observations from a wide variety of instruments and platforms are used to validate many different aspects of a three-dimensional mesoscale simulation of the dynamics, cloud microphysics, and radiative transfer of a cirrus cloud system observed on 26 November 1991 during the second cirrus field program of the First International Satellite Cloud Climatology Program (ISCCP) Regional Experiment (FIRE-II) located in southeastern Kansas. The simulation was made with a mesoscale dynamical model utilizing a simplified bulk water cloud scheme and a spectral model of radiative transfer. Expressions for cirrus optical properties for solar and infrared wavelength intervals as functions of ice water content and effective particle radius are modified for the midlatitude cirrus observed during FIRE-II and are shown to compare favorably with explicit size-resolving calculations of the optical properties. Rawinsonde, Raman lidar, and satellite data are evaluated and combined to produce a time–height cross section of humidity at the central FIRE-II site for model verification. Due to the wide spacing of rawinsondes and their infrequent release, important moisture features go undetected and are absent in the conventional analyses. The upper-tropospheric humidities used for the initial conditions were generally less than 50% of those inferred from satellite data, yet over the course of a 24-h simulation the model produced a distribution that closely resembles the large-scale features of the satellite analysis. The simulated distribution and concentration of ice compares favorably with data from radar, lidar, satellite, and aircraft. Direct comparison is made between the radiative transfer simulation and data from broadband and spectral sensors and inferred quantities such as cloud albedo, optical depth, and top-of-the-atmosphere 11-µm brightness temperature, and the 6.7-µm brightness temperature. Comparison is also made with theoretical heating rates calculated using the rawinsonde data and measured ice water size distributions near the central site. For this case study, and perhaps for most other mesoscale applications, the differences between the observed and simulated radiative quantities are due more to errors in the prediction of ice water content, than to errors in the optical properties or the radiative transfer solution technique.

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M. E. Cope, G. D. Hess, S. Lee, K. Tory, M. Azzi, J. Carras, W. Lilley, P. C. Manins, P. Nelson, L. Ng, K. Puri, N. Wong, S. Walsh, and M. Young

Abstract

The Australian Air Quality Forecasting System (AAQFS) is the culmination of a 3-yr project to develop a numerical primitive equation system for generating high-resolution (1–5 km) short-term (24–36 h) forecasts for the Australian coastal cities of Melbourne and Sydney. Forecasts are generated 2 times per day for a range of primary and secondary air pollutants, including ozone, nitrogen dioxide, carbon monoxide, sulfur dioxide, and particles that are less than 10 μm in diameter (PM10). A preliminary assessment of system performance has been undertaken using forecasts generated over a 3-month demonstration period. For the priority pollutant ozone it was found that AAQFS achieved a coefficient of determination of 0.65 and 0.57 for forecasts of peak daily 1-h concentration in Melbourne and Sydney, respectively. The probability of detection and false-alarm rate were 0.71 and 0.55, respectively, for a 60-ppb forecast threshold in Melbourne. A similar level of skill was achieved for Sydney. System performance is also promising for the primary gaseous pollutants. Further development is required before the system can be used to forecast PM10 confidently, with a systematic overprediction of 24-h PM10 concentration occurring during the winter months.

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