A 9‐year summary of radar characteristics of mesocyclonic storms and of deep convection in southern Québec
Abstract Nine summers of reflectivity and Doppler data, (1993–2001), archived by the Marshall Radar Observatory of McGill University have been processed for the purpose of identifying the location, strength and frequency of occurrence of severe weather events associated with convective activity. A mesocyclone detection and tracking algorithm has identified 329 features with a lifetime of at least 10 minutes. The distribution of their duration, path length, diameter, depth, rotational velocity and shear are provided, as well as their hourly and monthly frequency. Their geographical distribution reveals an increased relative probability of occurrence over the western area of the McGill radar coverage as well as to the north, near Mirabel, and a reduced probability of occurrence near the metropolitan area of Montréal. The analysis of deep convection has been performed in terms of upper level Vertically Integrated Liquid water content maps (UVIL) where the vertical integration of reflectivity begins at a height of 5 km. UVIL maps are preferred among other types of reflectivity‐based radar products because they are the least affected by radar artefacts such as bright band, ground echoes, anomalous propagation and beam blocking. An inherent bias, present in the standard generation of UVIL maps, and due to an oxygen attenuation overcorrection and to the vertical profile of reflectivity of thunderstorms as sampled by a broadening beamwidth, has been identified and corrected. The geographical distribution of UVIL measurements in terms of the time that a UVIL threshold of 10 and 15 kg m−2 is exceeded has been obtained for both the individual years and for the entire 9‐year period. Areas of preferred convection have been identified in the latter, particularly along the flatlands of the St. Lawrence River Basin. A relative minimum is quite noticeable along a broad corridor running north and south of the radar over heavily forested mountainous regions. This combination results in a non‐negligible correlation of the order of ‐0.2 between the height of the topography (m) and deep convection. Curves revealing the relative severity of the nine years in terms of a continuous UVIL threshold have also been derived. The years 1994, 1998 and 1999 emerged as the most active years while 1996 and 2000 were clearly very quiet.
Radar Network–Based Detection of Mesocyclones at the German Weather Service
The radar network of the German Weather Service [Deutscher Wetterdienst (DWD)] provides 3D Doppler data in high spatial and temporal resolution, supporting the identiﬁcation and tracking of dynamic small-scale weather phenomena. The software framework Polarimetric Radar Algorithms (POLARA) has been developed at DWD to better exploit the capabilities of the existing remote sensing data. The data processing and quality assurance implemented in POLARA include a dual-PRF dealiasing algorithm with error correction. Azimuthal shear information is derived and processed in the mesocyclone detection algorithm (MCD). Low- and midlevel azimuthal shear and track products are available as composite (multiradar) products. Azimuthal shear may be considered as a proxy for rotation. The MCD results and azimuthal shear products are part of the severe weather detection algorithms of DWD and are provided to the forecaster on the NinJo meteorological workstation system. The forecaster analyzes potentially severe cells by combining near-storm environment data with the MCD product as well as with the instantaneous azimuthal shear products(mid-and lowlevel)andtheirtracks.Theseproductsand tracksareusedto diagnose threatpotential by means of azimuthal shear intensity and track longevity. Feedback from forecasters has shown the utility of the algorithms to analyze and diagnose severe convective cells in Germany and in adjacent Europe. In this paper, the abovementioned algorithms and products are presented in detail and case studies illustrating us- ability and performance are shown. velocity errors in high shear regions. This is an essential prerequisite for the mesocyclone detection and azimuthal shear algorithms. The quality-controlled radar elevation scan data are henceforth called base data . These base data are storedatthecentralofﬁceoftheDWDinalong-termarchive system (Deutscher Wetterdienst 2016b). The radar base data and the derived products are visualized in the radar and Storm Cell Identiﬁcation and Tracking (SCIT) layers (Joe et al. 2005) of the NinJo workstation (Koppert et al. 2004).
The Role of Information Retrieval in the Diagnostic/Decision making Process within the Medical Appointment: A Review of the Literature
ABSTRACT Information retrieval/memory recall by patients/carers within the medical appointment is reported to be of paramount importance to the diagnostic/decision-making process within the medical appointment and hence to the outcome of the medical encounter itself. The rationale behind this paper (second in a series of papers) is to delve into the current literature to ascertain the pervasiveness of long-term information retrieval/memory recall concepts within this intricate environment, including the disease states in which patient information retrieval/memory recall research has been conducted, affording an analysis of research activities in order to identify the gaps in knowledge that currently exist. A rigorous systematic process detected 49 papers that clearly consider information retrieval/memory recall events within the medical appointment. Content analysis was conducted using a Concept-Centric Matrix in conjunction with open-coding techniques, giving rise to the detection of 227 concepts, which were subsequently assembled into 63 categories. Our analysis reveals the prevalence of long-term information retrieval/memory recall concepts, and the disease states that have conducted patient information retrieval/memory recall research (within the medical appointment) reported in writings over the past 43 years. Additionally, we have advanced our conceptual model of memory recall/information retrieval within the elicitation phase of the medical appointment, which we first presented in an earlier paper . The current paper is of significance as it facilitates an augmented understanding of information retrieval/memory recall (and the importance of same to the diagnostic/decision-making process and to patient outcomes, within the medical appointment. Furthermore, the exploration serves to highlight a number of IS research opportunities.