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Ariel Cohen

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Ariel Cohen and Eliahu Doron

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Four cases of mountain lee waves in the Middle East are discussed. The wavelengths as observed on satellite pictures are compared with calculations of wavelengths based on several different assumptions. Results show that the theory most applicable in the region is the one assuming an exponential increase in the wind speed with height. However, the best agreement with the measured wavelengths is achieved by the simple “parcel method,” although the assumptions inherent in this method are not realized in practice. Practically, this result could be applied to deduce the mean wind speed in the layer, as suggested by Fritz, or alternatively, with the help of the mean wind, to deduce the mean static stability in the layer.

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Jehuda Neumann and Ariel Cohen

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The effect of the introduction of one or two layers of particulate matter on the heating by direct solar radiation of the earth surface-atmosphere system is calculated for a cloudless sky. It is found for a fairly wide range of absorption and backscatter coefficients of the particles with respect to.direct solar radiation that when we have but one particle layer, either near the surface or in the lower stratosphere, the combined system is cooled; the atmosphere is heated (for a finite absorption) but this heating is offset by the greater cooling of the surface. Thus, our conclusions are different in some respects from those advanced by Charlson and Pilat and, to a lesser extent, from those inferred by McCormick and Ludwig.

If we have two layers of particles, one near the surface and the other in the lower stratosphere, and if we assume that both layers have the same optical characteristics with regard to solar radiation, then the earth surface-atmosphere system may actually gain heat provided that the absorption coefficient of the particle layers is fairly large with respect to the backscatter coefficient.

We estimate from the equations of the model that the layer of particles injected into the lower stratosphere by the 1963 Mt. Agung eruption absorbed and backscattered a total of about 6% of the solar radiation reaching the lower stratosphere.

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Ariel Cohen and Michael Graber

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The laser-radar system, consisting of a ruby laser as the emitter, has been used to map the aerosol layer centered at 20 km. Scattering measurements were made in two polarizations. Changes as a function of time in the number density were detected by use of an analysis method which requires no assumption on the air density profile.

The number density variations were observed from an analysis of the depolarization of the backscattered fight.

The results were compared to those obtained in different sites over the whole globe and the heights of the maximum concentration vs latitude are presented.

Regular measurements of the stratospheric aerosol profile are being carried out in order to detect future concentration variations due to volcanic eruptions or other possible dust sources. The profile describes the altitude dependence of the aerosol concentrations between 7.5–22.5 km, by use of a multi-channel scaler.

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Moshe Kleiman, Smadar Egert, and Ariel Cohen

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An algorithm for the determination of the number density profiles of a specific aerosol as a function of time and space is developed and discussed. The algorithm is applicable to atmospheric conditions in which a varying density particulate background contributes to the lidar backscatter a significant or even a major part of the total amount of the mattered light. The method is based on a priori knowledge of the dependence of the background aerosol mass backscatering coefficients on the varying lidar parameters (wavelength, polarization, scattering angle). The sensitivity of the method is also discussed. The theoretical approach is expanded to cases where the aerosol is mixed in two or more different backgrounds.

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John A. Hart and Ariel E. Cohen

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This study introduces a system that objectively assesses severe thunderstorm nowcast probabilities based on hourly mesoscale data across the contiguous United States during the period from 2006 to 2014. Previous studies have evaluated the diagnostic utility of parameters in characterizing severe thunderstorm environments. In contrast, the present study merges cloud-to-ground lightning flash data with both severe thunderstorm report and Storm Prediction Center Mesoscale Analysis system data to create lightning-conditioned prognostic probabilities for numerous parameters, thus incorporating null-severe cases. The resulting dataset and corresponding probabilities are called the Statistical Severe Convective Risk Assessment Model (SSCRAM), which incorporates a sample size of over 3.8 million 40-km grid boxes. A subset of five parameters of SSCRAM is investigated in the present study. This system shows that severe storm probabilities do not vary strongly across the range of values for buoyancy parameters compared to vertical shear parameters. The significant tornado parameter [where “significant” refers to tornadoes producing (Fujita scale) F2/(enhanced Fujita scale) EF2 damage] exhibits considerable skill at identifying downstream tornado events, with higher conditional probabilities of occurrence at larger values, similar to effective storm-relative helicity, both findings being consistent with previous studies. Meanwhile, lifting condensation level heights are associated with conditional probabilities that vary little within an optimal range of values for tornado occurrence, yielding less skill in quantifying tornado potential using this parameter compared to effective storm-relative helicity. The systematic assessment of probabilities using convective environmental information could have applications in present-day operational forecasting duties and the upcoming warn-on-forecast initiatives.

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John A. Hart and Ariel E. Cohen

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This study is an application of the Statistical Severe Convective Risk Assessment Model (SSCRAM), which objectively assesses conditional severe thunderstorm probabilities based on archived hourly mesoscale data across the United States collected from 2006 to 2014. In the present study, SSCRAM is used to assess the utility of severe thunderstorm parameters commonly employed by forecasters in anticipating thunderstorms that produce significant tornadoes (i.e., causing F2/EF2 or greater damage) from June through October. The utility during June–October is compared to that during other months. Previous studies have identified some aspects of the summertime challenge in severe storm forecasting, and this study provides an in-depth quantification of the within-year variability of severe storms predictability. Conditional probabilities of significant tornadoes downstream of lightning occurrence using common parameter values, such as the effective-layer significant tornado parameter, convective available potential energy, and vertical shear, are found to substantially decrease during the months of June–October compared to other months. Furthermore, conditional probabilities of significant tornadoes during June–October associated with these parameters are nearly invariable regardless of value, highlighting the challenge of using objective environmental data to attempt to forecast significant tornadoes from June through October.

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Ariel Cohen, Jehuda Neumann, and William Low

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The previously adopted values of the depolarization factor of clear atmospheric air are checked with the values obtained by lidar facilities, and with those obtained in laboratory measurements, using scattering of a He-Ne gas laser. These values and the importance of the depolarization factor in lidar measurements are discussed.

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Ram Hashmonay, Ariel Cohen, and Uri Dayan

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The temporal variation of the atmospheric boundary layer (ABL) over Jerusalem is accurately measured by means of a lidar system. The findings are explained and discussed based on the specific synoptic situation of typical summer days in the Middle East. The different behavior of the ABL near the seashore and inland is stressed. The measurement technique is also used to detect the entrainment zone and its development over Jerusalem.

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Daphne S. LaDue and Ariel E. Cohen

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Professional meteorologists gain a great deal of knowledge through formal education, but two factors require ongoing learning throughout a career: professionals must apply their learning to the specific subdiscipline they practice, and the knowledge and technology they rely on becomes outdated over time. It is thus inherent in professional practice that much of the learning is more or less self-directed. While these principles apply to any aspect of meteorology, this paper applies concepts to weather and climate forecasting, for which a range of resources, from many to few, for learning exist. No matter what the subdiscipline, the responsibility for identifying and pursuing opportunities for professional, lifelong learning falls to the members of the subdiscipline. Thus, it is critical that meteorologists periodically assess their ongoing learning needs and develop the ability to reflectively practice. The construct of self-directed learning and how it has been implemented in similar professions provide visions for how individual meteorologists can pursue—and how the profession can facilitate—the ongoing, self-directed learning efforts of meteorologists.

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