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Overview

OpenIFS users can check their model installation with a short acceptance test on T21 resolution. The meteorological evaluation framework makes it possible also to assess the meteorological performance of OpenIFS based on two sets of case studies.

We chose two weather events which had been predicted originally with different skill. Several model experiments were carried out

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Introduction

Meteorological evaluation of the OpenIFS outputs is demonstrated here on case studies. Two weather events have been chosen in order to show the model's capabilities on the one hand, and on the other hand, to provide reference cases for the users (to compare the results of their installed model version with the ones run at the ECMWF or to inter-compare the results of different model versions). Important aspects at selection of the cases were their geographical scope and their physical background, i.e., those storm events were preferred which had severe impact over Europe and were governed by large-scale dynamical forcings. Cases both with weak and good operational forecast skill were considered.

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Case studies

Storm Xaver

On the 5 December 2013 a large and violent cyclonic storm hit the North Sea region and several adjacent countries. Problems were caused both by the high wind speeds and the related storm surge. The surge reached 6 metres in Hamburg for example and was the highest along the England east-coast for 60 years. In the aftermaths of the cyclone a blizzard hit Sweden. The storm system was named Xaver by Berlin's Free University; other names assigned elsewhere include Bodil, Sven and St. Nicholas (Hewson et al., 2014). T he cyclone developed around 00 UTC on 4 December northeast of Newfoundland and it was situated between converging northerly and southerly airstreams. Due to the westerly wind jet accelerated by the convergence, the cyclone moved to northeast and east, deepening explosively. It had an intense meso-vortex hanging back to west, which enhanced the strong wind (see Figure 1). The cyclone was presented in the operational forecasts 8-9 days before the event and the forecasts indicated the very strong wind gust 3-4 days in advance. (Although some strength overestimation over Germany as well as timing error in surface pressure were concluded.)

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Figure 1: 24-hour maximum wind gust (m/s) on 5 December with mean sea level pressure (white contours; hPa) on 12 UTC on 5 December from the operational forecasts at 00 UTC on 3 (left) and 5 December (middle) and from the observations (right).

Storm Desmond

Storm Desmond caused severe flooding, travel disruption and a power outage across northern England, parts of Scotland and Ireland on 5 December 2015. Cumbria in northwestern part of England is one of the worst affected regions with more than 200 mm of rain in 24 hours recorded in that area. Storm Desmond broke the United Kingdom's 24-hour rainfall record, with 341.4 mm of rain falling in Honister Pass, Cumbria. On Saturday, 5 December, UK Met office issued a red warning of heavy rain for Cumbria. The cyclone also led to flooding in southern Norway.

Orographical enhancement of precipitation played a major role in the event and the operational model of the ECMWF picked well the highest rainfall amounts over the orographical barriers. However, the forecast underestimated the peak values of about 100 mm in 24 hours in Cumbria and overestimated the precipitation amount in lee of the hills (Figure 2).

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Figure 2: 24-hour precipitation amount (mm) between 6 UTC on 5 December and 6 UTC on 6 December, based on ECMWF operational IFS forecast at 00 UTC on 5 December (left, with cyan contours for the mean sea level pressure at 12 UTC on 5 December) and observations (right).

Model experiments

Several experiments have been conducted with OpenIFS for both cases with the aim

to test the effect of starting date

and

, forecast length, initial condition as well as spatial resolution

to

on the forecast quality. The

details of experiments are summarized in Table 1. Anchortable1table1Table 1: Settings of the experiments achieved for Storm Xaver and Storm Desmond.Experiment IDInitial conditionResolutionStarting dateTime stepOutput frequency
Xaver
1.ERA-InterimT255L911 Dec 20132700 s3h2.ERA_InterimT639L137900 s3h3.ERA5T255L912700 s3h4.ERA5T639L137900 s3hline
Desmond
1.grygERA-InterimT255L91

1 Dec 2015; 2 Dec 2015;
3 Dec 2015; 4 Dec 2015; 5 Dec 2015

2700 s3h2.gs22ERA-InterimT639L137

3 Dec 2015; 4 Dec 2015  

900 s3h3.gs23ERA-InterimT1279L1373 Dec 2015; 4 Dec 2015600 s3h4.gs0cERA5T255L91

3 Dec 2015; 4 Dec 2015

2700 s3h5.gs04ERA5T639L137

3 Dec 2015; 4 Dec 2015

900 s3h

!! The input data and the namelists needed to run the experiments can be downloaded from the ECMWF FTP server: download.ecmwf.int/openifs/evalution. !!

The files are packed in .tgz files and structured into directories named after the case studies (i.e., Xaver_201312, Desmond_201512) and subdirectories indicating the main experiment characteristics (e.g., T255L91_ERA5). The archive files were prepared by starting dates (e.g., gs0c_2015120300.tgz). Typical content of a .tgz file is as follows:

SizeFile nameDescription

0
0
4750
3983964
26563
3161

3161
9763008
7311120
36695160

106044120
54997789
13000184
26709432

26709416
64560
7943760
64560
2349600

2015120300/
2015120300/ecmwf/
2015120300/ecmwf/namelistfc
2015120300/ecmwf/NODE.001_01.model.1
2015120300/ecmwf/ifs.stat.model.1
2015120300/ecmwf/wam_namelist
2015120300/ecmwf/wam_namelist_coupled_000
2015120300/ICMCLgs0cINIT
2015120300/ICMGGgs0cINIT
2015120300/ICMSHgs0cINIT
2015120300/ICMGGgs0cINIUA
2015120300/wam_grid_tables
2015120300/wam_subgrid_0
2015120300/wam_subgrid_1
2015120300/wam_subgrid_2
2015120300/cdwavein
2015120300/specwavein
2015120300/uwavein
2015120300/sfcwindin

: directory for a given starting date
: subdirectory containing the namelists and some outputs
: namelist with detailed experiment setup
: output file in text format including all the important information about the model run
: namelist of the wave model
: namelist of the wave model
: input file containing surface and soil information (albedo, soil temperature etc.)
: input file containing gridpoint surface initial data
: input file containing initial data for the prognostic variables in spectral representation
: input file containing initial data for the prognostic variables in gridpoint representation Panel
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            0 2015120300/                               : directory for a given starting date
            0 2015120300/ecmwf/                         : subdirectory containing the namelists and some outputs
         4750 2015120300/ecmwf/namelistfc               : namelist with detailed experiment setup
      3983964 2015120300/ecmwf/NODE.001_01.model.1      : output file in text format including all the important information about the model run
        26563 2015120300/ecmwf/ifs.stat.model.1
         3161 2015120300/ecmwf/wam_namelist             : namelist of the wave model
         3161 2015120300/ecmwf/wam_namelist_coupled_000 : namelist of the wave model
      9763008 2015120300/ICMCLgs0cINIT                  : input file containing surface and soil information (albedo, soil temperature etc.)
      7311120 2015120300/ICMGGgs0cINIT                  : input file containing gridpoint surface initial data
     36695160 2015120300/ICMSHgs0cINIT                  : input file containing initial data for the prognostic variables in spectral representation

model outputs are visualized and evaluated using Metview.

After introduction of the two cases, this section guides the user step by step through running the selected experiments, post-processing the model outputs, downloading the reference data and visualising the model outputs with Metview. A catalogue from the prepared figures is also included. The input data and the namelists needed for the model runs, the scripts for the MARS retrieves of the re-analyses, the Metview macros for visualization and the output figures are available for download on the ECMWF download server.


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    106044120 2015120300/ICMGGgs0cINIUA                 : input file containing initial data for the prognostic variables in gridpoint representation
     54997789 2015120300/wam_grid_tables
     13000184 2015120300/wam_subgrid_0
     267094322015120300/wam_subgrid_1
     26709416 2015120300/wam_subgrid_2
        64560 2015120300/cdwavein
      7943760 2015120300/specwavein
        64560 2015120300/uwavein
      2349600 2015120300/sfcwindin
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	        0	2015120300/									: directory for a given starting date
	        0 	2015120300/ecmwf/ 							: subdirectory containing the namelists and some outputs
      4750 	<strong>2015120300/ecmwf/namelistfc 				: namelist with detailed experiment setup</strong>
 	  3983964	2015120300/ecmwf/NODE.001_01.model.1		: output file in text format including all the important information about the model run
	    26563	2015120300/ecmwf/ifs.stat.model.1
	     3161	2015120300/ecmwf/wam_namelist				: namelist of the wave model
	     3161	2015120300/ecmwf/wam_namelist_coupled_000	: namelist of the wave model
	  9763008	2015120300/ICMCLgs0cINIT					: input file containing surface and soil information (albedo, soil temperature etc.)
	  7311120	2015120300/ICMGGgs0cINIT					: input file containing gridpoint surface initial data
	 36695160	2015120300/ICMSHgs0cINIT					: input file containing initial data for the prognostic variables in spectral representation
	106044120	2015120300/ICMGGgs0cINIUA					: input file containing initial data for the prognostic variables in gridpoint representation 
	 54997789	2015120300/wam_grid_tables
	 13000184	2015120300/wam_subgrid_0
	 26709432	2015120300/wam_subgrid_1
	 26709416	2015120300/wam_subgrid_2
	    64560	2015120300/cdwavein
	  7943760	2015120300/specwavein
	    64560	2015120300/uwavein
	  2349600	2015120300/sfcwindin

       

    

Post-processing

- how to prepare data for plotting

Metview macros

- where they are, how to set them up .. etc

Catalogue

References

Hewson, T. , Magnusson, L. , Breivik, O. , Prates, F ., Tsonevsky, I. , de Vries, H.J.W. , 2014: Windstorms in northwest Europe in late 2013. ECMWF Newsletter 139, 22–28. [PDF]

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