Spin-up time from switching the microphysics scheme in the assimilation cycle and impacts on the precipitation forecast quality

Sven Ulbrich,Kobra Khosravianghadikolaei,Michael Hoff,Christian Welzbacher,Roland Potthast,Christoph Schraff,Ulrich Blahak,Liselotte Bach,Alberto De Lozar,Klaus Stephan

doi:10.5194/ems2021-379

Abstract

&lt;p&gt;The SINFONY project at Deutscher Wetterdienst (DWD) aims to produce seamless precipitation forecast products from minutes up to 12 hours, with particular focus on convective events. While the near future predictions are typically from nowcasting procedures using radar data, the numerical weather prediction (NWP) aims at longer time scales. The lead-time in the latest available forecast is usually too long for merging both the nowcasting and NWP output to produce reliable seamless predictions.&lt;/p&gt;&lt;p&gt;At DWD, the current forecasts are produced by the short range numerical weather prediction (SRNWP) &lt;span&gt;making use of a&lt;/span&gt; continuous assimilation cycle with relatively long cutoff times and using 1-moment microphysics. In order to reduce the differences in the precipitation to the &lt;span&gt;nowcasting &lt;/span&gt;on the NWP side, we use two different approaches. First, we reduce the lead-time from the model start by running 1-hourly forecasts based on an assimilation cycle with shorter data cutoff. Secondly, we use new observational systems in the assimilation cycle, such as radar or satellite data to capture and represent strong convective activity. This procedure is called Rapid Update Cycle (RUC). As an additional measure, we introduce a 2-Moment microphysics scheme into the numerical model, resulting in a better representation of the radar reflectivities. In order to keep the model state similar to that of the SRNWP, the RUC is a time limited assimilation cycle starting from forecasts of the SRNWP at pre-defined times.&lt;/p&gt;&lt;p&gt;The introduction of the 2-Moment scheme leads to a spin-up affecting both the assimilation cycle and the short forecasts. The resulting effects are analysed by comparison with the corresponding assimilation cycle using the 1-Moment scheme. As a complementary approach for the analysis, the routine cycle is run with the 2-Moment scheme. The forecast quality is used as a measure to compare the results with respect to precipitation and additional observed parameters. It is shown in how far the resulting improvements are related to the assimilation and momentum scheme, or to the higher frequency of forecasts.&lt;/p&gt;

Highlights

OSA1.3 : Meteorological observations from GNSS and other space-based geodetic observing techniques OSA1.7: The Weather Research and Forecasting Model (WRF): development, research and applications
OSA3.5: MEDiterranean Services Chain based On climate PrEdictions (MEDSCOPE)
UP2.1 : Cities and urban areas in the earth- OSA3.1: Climate monitoring: data rescue, atmosphere system management, quality and homogenization 14:00-15:30

Summary

Introduction

OSA1.3 : Meteorological observations from GNSS and other space-based geodetic observing techniques OSA1.7: The Weather Research and Forecasting Model (WRF): development, research and applications. EMS Annual Meeting Virtual | 3 - 10 September 2021 Strategic Lecture on Europe and droughts: Hydrometeorological processes, forecasting and preparedness Serving society – furthering science – developing applications: Meet our awardees ES2.1 - continued until 11:45 from 11:45: ES2.3: Communication of science ES2.2: Dealing with Uncertainties

Results

Conclusion