Quantitative precipitation forecast with radar data assimilation in the HARMONIE model
Journal Title: Вісник Одеського державного екологічного університету - Year 2017, Vol 22, Issue 22
Abstract
The further development of the data assimilation system in the operational numerical convective-permitted HARMONIE model is presented. Radar measurements of reflectivity are included in the observational model. In the focus of the study is the following: firstly, the general contribution of radar data assimilation into quantitative forecasts of precipitation; secondly, comparison of the results of numerical experiments obtained with the use of various pre-processing methods of reflectivity in a measurement tracking system. Two methods of pre-processing, such as “simple thinning” and “superobservation” are applied for reducing the amount of input data. Comparison of test numerical experiments with radar data versus reference one, in which the radar measurements are not included in the data assimilation module, is performed, The results show that accounting reflective characteristics of the atmosphere at the model initial conditions allows to increase the accuracy of microphysical processes simulations due to correction of the moisture content in the middle troposphere. For a severe precipitation event, the test experiments provide estimates of 10 mm / 12 hours higher in comparing to the control one. Vertical profiles of moisture content show that the major changes occur in the layer between 850 and 600 hPa. In the precipitation core, rain rate increases roughly at a value of 5-7 mm / h. Correction of moisture content in the middle troposphere leads to increasing quantitative precipitation estimates at the surface and approaching them to retrospective analysis values. However, the results of numerical experiments are sensitive to the choice of a pre-processing approach and internal parameters. Optimization of this choice by accounting for the resolution of the model grid and spatial features of the atmospheric flow will be performed at the next stage of the study.
Authors and Affiliations
S. V. Ivanov, I. G. Ruban, Yu. O. Palamarchuk
Keywords
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