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Understanding the mesoscale spatial and temporal variability of precipitation (of the order of 1 to 100 km, and of minutes to hours, respectively) is essential for larger-scale studies, especially in highly heterogeneous areas, such as coastal regions, mountains and urban areas. The adequate capturing of the precipitation patterns in both diagnostic and prognostic terms remains an open challenge. On the one hand, commonly used ground measuring devices, such as rain gauges, disdrometers and other point instruments, exhibit an ineffective sampling for the whole range of scales and areas covered with precipitation. On the other hand, weather radars provide a much greater spatial and temporal resolution which, however, must be exploited with care in rain rate estimations, due to complicated and non-unique transfer functions used in the processing procedures. This study aims at bridging, to at least some extent, this scale gap and to demonstrate the role of fine-scale precipitation estimates derived from weather radar data, and to illustrate their impacts on larger scale weather patterns. The focus is on the precipitable water content and its changes during a Mediterranean cyclone evolution. In this paper, the first results with the regional radar signal processing chain that provides the radar data assimilation (RDA) in the Harmonie convection permitting numerical model are described. The numerical experiments exhibit effective simulation of the precipitable water at different stages of the frontal depression which affected Cyprus in the Eastern Mediterranean, during 31 December 2018–2 January 2019. In particular, it was found that the major volume of precipitable water was related to the cyclone frontal zone (which is in turn related to heavier precipitation), followed by a weaker field of precipitable water behind the frontal zone (and weaker precipitation). During the whole severe weather period, the precipitable water minimum was maintained over the island's central mountain range, reflecting the importance of interactions and feedbacks between the air flow and orography. The radar data assimilation influences the results of the simulations, depending on the particular area and cyclone stage. The largest innovations due to RDA occur with the approach of the cyclone's frontal zone. Enhancement of precipitable water due to RDA is observed over most of the whole area, but this is more pronounced in weaker precipitation locations. The impact is associated with a shift of the precipitable water maximum towards higher values in the precipitable water distribution, which is accompanied by enlarged sizes of areas with greater precipitable water. During the cyclone's mature stage and at the rear zone, the integrated RDA impact over the whole domain is almost negligible but takes the form of mesoscale cells of opposite signs; at this stage, radar measurements yield an alteration of both the positions and rates of spatial precipitable water fields, which result in intermittent mesoscale changes. • Radar data assimilation in the Harmonie numerical model is performed. • Radar data from two weather radars in Cyprus are assimilated into the model. • The focus is on simulated precipitable water and its changes. • Simulations with an eastern Mediterranean depression are reported. • The assimilation renders considerable influence on the results of the simulations. [ABSTRACT FROM AUTHOR]

Weather radars are suitable for short-range forecasting and nowcasting activities. They have the capability to monitor precipitation, resolving very local scales, with good spatial and temporal details, with a widespread scanning range. The Cyprus Department of Meteorology operates two X-band weather radars which, however, have not been employed in a numerical weather prediction (NWP) system, until now. This process requires a design of multi-domain expertise, mixed-signal modelling and effective paths to implementation. This work describes the first results with the regional radar signal processing chain that provides the final reflectivity data assimilation (DA) in the Harmonie convection permitting numerical model. The DA technique includes one-dimensional (1-D) retrieval, followed by a three-dimensional variational (1D+3DVar) assimilation of volume of radar reflectivity data. The pre-processing approach additionally creates a regular cube grid in which a horizontal size of meshes coincides with the horizontal model resolution. This minimizes the representative error associated with the discrepancy between resolutions of informational sources. The pre-processing and assimilation of radar reflectivity has a positive impact on the convective system dynamics through controlling the intensity and location of the updraft due to maintaining the sizes and shapes of precipitation patterns in the model similar to those in the measurements. The DA performance is assessed for case studies characterized by different precipitation regimes. Results are satisfactory, especially during intense precipitation, particularly regarding its spatial and temporal characterization. [ABSTRACT FROM AUTHOR]