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Cristian Muñoz and David M. Schultz

Abstract

A study of 500-hPa cutoff lows in central Chile during 1979–2017 was conducted to contrast cutoff lows associated with the lowest quartile of daily precipitation amounts (LOW25) with cutoff lows associated with the highest quartile (HIGH25). To understand the differences between low- and high-precipitation cutoff lows, daily precipitation records, radiosonde observations, and reanalyses were used to analyze the three ingredients necessary for deep moist convection (instability, lift, and moisture) at the eastern and equatorial edge of these lows. Instability was generally small, if any, and showed no major differences between LOW25 and HIGH25 events. Synoptic-scale ascent associated with Q-vector convergence also showed little difference between LOW25 and HIGH25 events. In contrast, the moisture distribution around LOW25 and HIGH25 cutoff lows was different, with a moisture plume that was more defined and more intense equatorward of HIGH25 cutoff lows as compared with LOW25 cutoff lows where the moisture plume occurred poleward of the cutoff low. The presence of the moisture plume equatorward of HIGH25 cutoff lows may have contributed to the shorter persistence of HIGH25 events by providing a source for latent-heat release when the moisture plume reached the windward side of the Andes. Indeed, whereas 48% of LOW25 cutoff lows persisted for longer than 72 h, only 25% of HIGH25 cutoff lows did, despite both systems occurring mostly during the rainy season (May–September). The occurrence of an equatorial moisture plume on the eastern and equatorial edge of cutoff lows is fairly common during high-impact precipitation events, and this mechanism could help to explain high-impact precipitation where the occurrence of cutoff lows and moisture plumes is frequent.

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David M. Schultz, Robert M. Rauber, and Kenneth F. Heideman
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Jay W. Hanna, David M. Schultz, and Antonio R. Irving

Abstract

To explore the role of cloud microphysics in a large dataset of precipitating clouds, a 6-month dataset of satellite-derived cloud-top brightness temperatures from the longwave infrared band (channel 4) on the Geostationary Operational Environmental Satellite (GOES) is constructed over precipitation-reporting surface observation stations, producing 144 738 observations of snow, rain, freezing rain, and sleet. The distributions of cloud-top brightness temperatures were constructed for each precipitation type, as well as light, moderate, and heavy snow and rain. The light-snow distribution has a maximum at −16°C, whereas the moderate- and heavy-snow distributions have a bimodal distribution with a primary maximum around −16° to −23°C and a secondary maximum at −35° to −45°C. The light, moderate, and heavy rain, as well as the freezing rain and sleet, distributions are also bimodal with roughly the same temperature maxima, although the colder mode dominates when compared with the snow distributions. The colder of the bimodal peaks trends to lower temperatures with increasing rainfall intensity: −45°C for light rain, −47°C for moderate rain, and −50°C for heavy rain. Like the distributions for snow, the colder peak increases in amplitude relative to the warmer peak at heavier rainfall intensities. The steep slope in the snow distribution for cloud-tops warmer than −15°C is likely due to the combined effects of above-freezing cloud-top temperatures not producing snow, the activation of ice nuclei, the maximum growth rate for ice crystals at temperatures near −15°C, and ice multiplication processes from −3° to −8°C. In contrast, the rain distributions have a gentle slope toward higher cloud-top brightness temperatures (−5° to 0°C), likely due to the warm-rain process. Last, satellite-derived cloud-top brightness temperatures are compared with coincident radiosonde-derived cloud-top temperatures. Although most differences between these two are small, some are as large as ±60°C. The cause of these differences remains unclear, and several hypotheses are offered.

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David M. Schultz, Timothy M. DelSole, Robert M. Rauber, and Walter A. Robinson
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Noora Eresmaa, Jari Härkönen, Sylvain M. Joffre, David M. Schultz, Ari Karppinen, and Jaakko Kukkonen

Abstract

A new three-step idealized-profile method to estimate the mixing height from vertical profiles of ceilometer backscattering coefficient is developed to address the weaknesses found with such estimates that are based on the one-step idealized-profile method. This three-step idealized-profile method fits the backscattering coefficient profile of ceilometer measurements into an idealized scaled vertical profile of three error functions, thus having the potential to determine three aerosol layers (one for the surface layer, one for the mixing height, and one for the artificial layer caused by the weakened signal). This three-step idealized-profile method is tested with ceilometer and radiosounding data collected during the Helsinki Testbed campaign (2 January 2006–13 March 2007). Excluding cases with low aerosol concentration in the boundary layer, cases with clouds present, and cases with precipitation present, the resulting dataset consists of 97 simultaneous backscattering coefficient profiles and radiosoundings. The three-step method is compared with the one-step method and other commonly employed algorithms. A strong correlation (correlation coefficient r = 0.91) between the mixing heights as determined by the three-step method using ceilometer data and those determined from radiosoundings is an improvement over the same correlation using the one-step method (r = 0.28), as well as the other algorithms.

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