Impacts of a change in deep convection scheme on the ARPEGE data assimilation system
Authors: Hubans Antoine , Berre Loïk , Bouteloup Yves , Loo Cécile , Marquet Pascal 
Published: March 2021

&lt;p&gt;&lt;span&gt;I&lt;/span&gt;&lt;span&gt;n the context of Numerical Weather Prediction (NWP), continuous improvement from one &lt;/span&gt;&lt;span&gt;version&lt;/span&gt;&lt;span&gt; to another is made possible by the improvement of individual parts of the models. Thus the evaluation of those parts is crucial. &lt;/span&gt;&lt;span&gt;Within a time step, we see t&lt;/span&gt;&lt;span&gt;he &lt;/span&gt;&lt;span&gt;sequence&lt;/span&gt;&lt;span&gt; of the &lt;/span&gt;&lt;span&gt;resolved &lt;/span&gt;&lt;span&gt;dynamic &lt;/span&gt;&lt;span&gt;part &lt;/span&gt;&lt;span&gt;and physical parametrization&lt;/span&gt;&lt;span&gt;s. &lt;/span&gt;&lt;span&gt;Similarly, w&lt;/span&gt;&lt;span&gt;ithin a data assimilation cycle, &lt;/span&gt;&lt;span&gt;we see&lt;/span&gt;&lt;span&gt; the &lt;/span&gt;&lt;span&gt;sequence &lt;/span&gt;&lt;span&gt;of forecast and analysis. &lt;/span&gt;&lt;span&gt;Th&lt;/span&gt;&lt;span&gt;e&lt;/span&gt;&lt;span&gt;s&lt;/span&gt;&lt;span&gt;e&lt;/span&gt;&lt;span&gt; cyclical behaviours&lt;/span&gt; &lt;span&gt;are responsible for a high coupling between the different parts of &lt;/span&gt;&lt;span&gt;a&lt;/span&gt;&lt;span&gt; NWP system&lt;/span&gt;&lt;span&gt;. &lt;/span&gt;&lt;span&gt;This means that, when &lt;/span&gt;&lt;span&gt;evaluating an individual &lt;/span&gt;&lt;span&gt;physical &lt;/span&gt;&lt;span&gt;parametrization, &lt;/span&gt;&lt;span&gt;a &lt;/span&gt;&lt;span&gt;forecast only &lt;/span&gt;&lt;span&gt;approach &lt;/span&gt;&lt;span&gt;is not &lt;/span&gt;&lt;span&gt;enough&lt;/span&gt; &lt;span&gt;and&lt;/span&gt; &lt;span&gt;simulation&lt;/span&gt;&lt;span&gt;s&lt;/span&gt;&lt;span&gt; of the whole system &lt;/span&gt;&lt;span&gt;with data assimilation &lt;/span&gt;&lt;span&gt;over a long period &lt;/span&gt;&lt;span&gt;are required.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;I&lt;/span&gt;&lt;span&gt;n this work, we focus on the evaluation of the physical parametrization of deep convection in the French model ARPEGE. &lt;/span&gt;&lt;span&gt;We evaluate the direct impact of this parametrization in a forecast only study as well as the &lt;/span&gt;&lt;span&gt;indirect&lt;/span&gt;&lt;span&gt; impact with a 4D-&lt;/span&gt;&lt;span&gt;Var&lt;/span&gt;&lt;span&gt; and the study of the analysis.&lt;/span&gt;&lt;span&gt; We have replace&lt;/span&gt;&lt;span&gt;d&lt;/span&gt;&lt;span&gt; the previous parametrization by the one used in the Integrated Forecast System (IFS) developed &lt;/span&gt;&lt;span&gt;at&lt;/span&gt;&lt;span&gt; the ECMWF. &lt;/span&gt;&lt;span&gt;We seize the opportunity of using an other model parametrization to &lt;/span&gt;&lt;span&gt;rearrange physical tendencies in the same way as in the IFS&lt;/span&gt;&lt;span&gt;. This diagnostic is new for the ARPEGE environment and it leads to an intecomparison &lt;/span&gt;&lt;span&gt;between&lt;/span&gt;&lt;span&gt; the &lt;/span&gt;&lt;span&gt;two model&lt;/span&gt;&lt;span&gt; physic&lt;/span&gt;&lt;span&gt;s&lt;/span&gt;&lt;span&gt;. To evaluate the coupling, we use several &lt;/span&gt;&lt;span&gt;ARP&lt;/span&gt;&lt;span&gt;E&lt;/span&gt;&lt;span&gt;GE &lt;/span&gt;&lt;span&gt;4&lt;/span&gt;&lt;span&gt;D-&lt;/span&gt;&lt;span&gt;Var to compare the change in analysis with an estimate of the analysis error. &lt;/span&gt;&lt;span&gt;Those&lt;/span&gt;&lt;span&gt; studies show a significant impact of the new scheme both in the tendencies and in the analysis.&lt;/span&gt;&lt;/p&gt;