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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.)
Figure 1: 24-hour maximum wind gust (m/s) on 5 December based on ECMWF operational IFS forecasts at 00 UTC on 3 and 5 December (left and middle, respectively; with white contours for the mean sea level pressure in hPa on 12 UTC on 5 December) 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).
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 in hPa at 12 UTC on 5 December) and observations (right).
Model experiments
Several experiments have been conducted with OpenIFS for both cases with the aim and to the forecast quality. The details of experiments are summarized in Table 1.1 Dec 2015; 2 Dec 2015;
3 Dec 2015; 4 Dec 2015; 5 Dec 2015
3 Dec 2015; 4 Dec 2015
3 Dec 2015; 4 Dec 2015
3 Dec 2015; 4 Dec 2015
!! 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:
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Size File name
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To run OpenIFS, the files highlighted in green in the box above are needed, i.e., the initial conditions for the atmospheric model (files with ICM) and the namelist (namelistfc). The namelist controls the necessary settings (e.g., time step, experiment ID) as well as the post-processing. The most important namelist elements are listed below with their explanation:
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In the evaluation, we would like to investigate the following variables:
- 2-meter temperature: its GRIB code number is 167;
- precipitation: it is composed from large-scale and convective precipitation with code numbers 142 and 143, respectively;
- mean sea level pressure: its code number is 151;
- 10-meter wind gust: its code number is 49;
- temperature at 850 hPa level: its code number is 130;
- relative humidity at 700 hPa level: its code number is 157;
- geopotential at 500 hPa level: its code number is 129;
u and v wind components at 250 and 100 hPa.
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<p>The listed variables have to be included in the namelist among the post-processing variables (see the code numbers and levels highlighted with <b>bold</b> characters in the box above). Instead of the wind components at given pressure level, the direct model output contains vorticity and divergence (with code number 138 and 155; see the highlight in <b><font color=red>red</font></b> above). To obtain the horizontal wind components, an external post-processing is needed, which calculates <i>u</i> and <i>v</i> from the vorticity and divergence (see later). More information about the namelist settings and GRIB field codes can be found in the <b><a href="https://software.ecmwf.int/wiki/display/OIFS/How-to+articles" target="_blank">how-to articles</a></b>: <a href="https://software.ecmwf.int/wiki/display/OIFS/How+to+control+OpenIFS+output" target="_blank">How to control OpenIFS output</a>.</p> |
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<p><b><font color=red>!!</font></b> To run the model, the paths of the input data and the namelist have to be set in the job. ..... <a href="https://software.ecmwf.int/wiki/display/OIFS/5.6+Acceptance+testing+OpenIFS+after+installation" target="_blank">Acceptance testing OpenIFS after installation</a>.</p> |
Preparation of data for visualization
After the job run is completed, the outputs are split into 2 files (located in the working directory): ICMGG for the gridpoint fields and ICMSH for the spectral ones. The two files should include all the necessary variables set in the namelist. However, before visualisation of the results, some steps are still needed.
Post-processing of model outputs
The Metview macros prepared for visualisation of experiment results desire the meteorological variables in GRIB files separated by variables and day with the following names:
t2_${day}.gribfor 2-meter temperature,p_${day}.gribfor precipitation,mslp_${day}.gribfor mean sea level pressure,gust_${day}.gribfor 10-meter wind gust,t850_${day}.gribfor temperature at 850 hPa,q700_${day}.gribfor relative humidity at 700 hPa,z500_${day}.gribfor geopotential at 500 hPa,u250_${day}.gribfor horizontal wind components at 250 hPa,u100_${day}.gribfor horizontal wind components at 100 hPa,
where day is the given date in format of yyyymmdd (e.g., 20151203). All the files should contain data for 8 timesteps per day (i.e., in every 3 hours).
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Please note the lowercase letters in the filenames. |
The 2-meter temperature, the precipitation, the mean sea level pressure and the wind gust are expected in gridpoint representation, so will be taken from the ICMGG files. To prepare the needed input files for the Metview macros, the next operations are needed on the raw ICMGG outputs:
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where expID is the 4-digit experiment ID and step is the post-processing step (every 3 hours). For precipitation, both the convective and large-scale precipitation components have to be in the same file:
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The pressure level data are required in spectral representation, so they will be taken from ICMSH files. To prepare the needed input files for the Metview macros, the next operations are needed on the raw ICMSH outputs:
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For wind, the files should include the <i>u</i> and <i>v</i> wind components. To obtain wind components from the vorticity and divergence, we will use the <font style="font-family:monospace;">dv2uvl</font> command of CDO (Climate Data Operators) software (more information about the possibilities in CDO can be found in the <b><a href="https://software.ecmwf.int/wiki/display/OIFS/How-to+articles" target="_blank">how-to articles</a></b>: <a href="https://software.ecmwf.int/wiki/display/OIFS/How+to+convert+GRIB+to+netCDF" target="_blank">How to convert GRIB to netCDF</a>): |
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The size of the resulted files varies by the spatial resolution and the representation of the data. For instance, the file size at T255L91 resolution is 10 MB and 8 MB per variables for gridpoint and spectral fields, respectively, whereas these values increases to 35 MB and 26 MB at T639L137, to 233 MB and 179 MB at T1279L137.
Preparation of reference data
As reference data, we will apply ECMWF re-analyses. Both ERA-Interim and ERA5 datasets are available for the users and can be downloaded from the ECMWF MARS (Meteorological Archival and Retrieval System) system. Re-analyses are created by optimal combination of available observational information and short-range numerical predictions using data assimilation techniques and provide the most comprehensive description of the past and current states of the 3-dimensional atmosphere or the Earth system.ERA-Interim dataset (Berrisford et al., 2011) was prepared on 79 km horizontal resolution with 60 vertical levels starting from 1979. Analysis fields were constructed in every 6 hours using variety of observations (conventional measurements, remote sensing data, air craft measurements etc.), the 4D-Var data assimilation technique and the IFS model version which was operational in 2009 (cycle 31r2). The forecasts initialized from the analysis produced 3 hourly outputs up to 24 hours.
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<p><b>ERA5</b> (<a href="#hersbach">Hersbach and Dee</a>, 2016) is being constructed on higher, 32 km horizontal resolution with 137 vertical levels from 1950. Analysis fields are is being prepared hourly with inclusion of newly reprocessed observational data, using the 4D-Var data assimilation technique and the IFS cycle 42r1 model version. ERA5 forecasts initialized from the hourly analyses produce hourly outputs up to 18 hours and give an estimation of forecast uncertainty. There is an important difference between ERA-Interim and ERA5 in handling of the accumulated parameters: in ERA5 the accumulation is calculated from the previous post-processing step (i.e., along one hour), while in ERA-Interim it is from the beginning of the forecast – this feature will have relevance in evaluation of the precipitation amount and wind gust. (More information about the characteristics of ERA-Interim and ERA5 can be found in the <b><a href="https://software.ecmwf.int/wiki/display/CKB/Copernicus+Knowledge+Base" target="_blank">Copernicus Knowledge Base</a></b>: <a href="https://software.ecmwf.int/wiki/pages/viewpage.action?pageId=74764925" target="_blank">What are the changes from ERA-Interim to ERA5?</a>)</p> |
The Metview macros prepared for visualisation of re-analysis data desire the meteorological variables in GRIB files separated by variables for a time period with the following names:
${dataset}_t2_${period}.grib${dataset}_${period}.grib${dataset}_${period}.grib${dataset}_${period}.grib${dataset}_${period}.grib${dataset}_${period}.grib${dataset}_${period}.grib${dataset}_${period}.grib${dataset}_${period}.grib
where datasetei for ERA-Interim and ea for ERA5; period is the investigated time period in format of yyyymmdd-yyyymmdd (e.g., 20151201-20151206 for Desmond).
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Please note again the lowercase letters in the filenames. Furthermore, the re-analysis data should not be split by day, because data for the whole period will be handled together by the Metview macros. |
The 2-meter temperature, the precipitation, the mean sea level pressure and the wind gust are expected in gridpoint representation, while the pressure level data are required in spectral representation. Total precipitation and wind gust as accumulated parameters derive from forecasts, all the other variables are real analyses. Consequently, the daily quantities for precipitation and wind gust are composed of 8 and 24 timesteps from ERA-Interim and ERA5, respectively, the other variables have 4 and 8 timesteps (recall that output frequency of the forecast experiment is 3 hours). Besides the two (large-scale and convective) precipitation components, total precipitation is also available for direct retrieve both in ERA-Interim and ERA5, with GRIB code 228.
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<p>
To download the necessary data from MARS, the following steps have to be accomplished:
<ol>
<li>To have access to the ECMWF public datasets, you will need to have an account on ECMWF web site: <a href="https://apps.ecmwf.int/registration/" target="_blank">https://apps.ecmwf.int/registration/</a>.
<li>To retrieve data from MARS, you will need to download and install an ECMWF key. This page shows that step by step: <a href="https://software.ecmwf.int/wiki/display/WEBAPI/Access+ECMWF+Public+Datasets" target="_blank">Access ECMWF Public Datasets</a>.
<li>Having your key, you can run the <a href="https://software.ecmwf.int/stash/projects/OIFS/repos/oifs40r1/browse/casestudies/mars/scr_download_re-analysis?at=evaluation" target="_blank"><font style="font-family:monospace;">scr_download_re-analysis</font></a> shell script available in the <a href="https://software.ecmwf.int/stash/projects/OIFS/repos/oifs40r1/browse" target="_blank">OpenIFS repository (for cycle 40r1)</a> and using <font style="font-family:monospace;">getmars</font> for retrieve.
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The re-analysis source (i.e., ERA-Interim or ERA5), the surface and pressure level variables to be retrieved, the period of the data and the output directory have to/can be specified for the scr_download_re-analysis script. Calling it with -h option, it gives a detailed help with some examples at the end (or calling it without any option, it also gives short instructions to its configuration):
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digs@laerad 995: ./scr_download_re-analysis -h
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This script downloads surface and pressure level ERA-Interim or ERA5 re-analysis data for a given time range from MARS.
Usage:
-c[class],-s[surface_variables],-p[plevel_variables],-f[firstdate],-l[lastdate],-o[output_directory]
-h/-help
Examples:
./scr_download_re-analysis -cei -s"t2 p mslp gust" -p"t850 q700 z500 u250 u100" -f20151203 -l20151205 -o"../reference"
./scr_download_re-analysis -cea -sall -p"t850 q700 z500 u250 u100" -f20151203 -l20151205 -o"/home/rd/digs/metview/paper_OIFS/input/reference"
./scr_download_re-analysis -ce5 -s" " -p"t850" -f20151203 -o"/home/rd/digs/metview/paper_OIFS/input/reference"
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Please take into account that the script is able to retrieve only the variables listed above. For further parameters the program has to be modified manually. Furthermore, please note the |
Metview macros
- where they are, how to set them up .. etc
Catalogue
References
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<p><a name="hersbach"></a>Hersbach, H., Dee, D.P., 2016: <a href="https://www.ecmwf.int/en/newsletter/147/news/era5-reanalysis-production" target="_blank">ERA5 reanalysis is in production.</a> <em>ECMWF Newsletter 147,</em> p. 7.</p> |