Lothar storm

Introduction

The Lothar storm that swept across Europe during 24-27 December 1999 is provided as a sample case study to use with OpenIFS. This storm was one of several severe storms to hit Europe in December 1999 and Lothar affected northern France, Switzerland and Germany (for more details see: Wernli et al., 2002, QJRMS;  Ulbrich et al., 2001, Weather, 56, 70-80).

The storms were characterized by record-breaking windspeed observations and rapid development across Europe. There was also a band of extremely high baroclinity near the cyclone track over the N. Atlantic and partly into Europe associated with Lothar.

The ECMWF forecasting system of the time did not accurately capture the storm's intensity though the strong jet stream was predicted some 9 days earlier. The storm initiated from a small disturbance in the Atlantic. More recently, Wedi et al, 2012, ECMWF Newsletter, have shown that very high resolution (T7999; ~2.5km) is necessary to accurately model the high wind speeds observed, particularly over the mountainous regions of Europe.

A number of initial conditions are provided along with suggested exercises. Feedback on this case study (and others) is welcomed.



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Initial conditions

Note:  The initial conditions data for the case studies described here are available for OpenIFS 40r1. Please contact OpenIFS Support if you require initial experiment data for more recent model version. 

Case study initial conditions for the Lothar storm are provided on the OpenIFS ftp site. The ftp site is password protected, only licensed institutes may be provided with the ftp password. Please contact: openifs-support@ecmwf.int.

The Lothar depression developed initially on 24th December off the North American east coast at 35N.

The initial conditions are available at a range of different resolutions and start dates for a 10 day forecast. The experiment ids are created at ECMWF and used for identifying the model forecasts on the ECMWF archive system (for those with access).

Note that ERA-Interim has a resolution of T255 and the operational resolution at that time was T319. Initial data has been spectrally interpolated to the model resolutions.

The ERA-Interim analysis is an improvement over the original analysis which did not have as many observations. The scientific content of the IFS operational model at that time was significantly different to the more modern OpenIFS. A rough proxy for  how the forecast at the time performed would be to run OpenIFS at T255, the resolution of the initial data.

As OpenIFS is a spectral model, the 'T' number refers to the triangular truncation in spectral space. Equivalent grid resolutions are:
T159 ~ 125km resolution, T255 ~ 80km, T511 ~ 40km, T799 ~ 25km, T1279 ~ 16km.

The number of vertical levels is given after the letter 'L' e.g. L62 means 62 vertical levels.

Please note that higher resolutions progressively require more processors and computer memory to run.

Single start dates
ResolutionExpt idStart dateAnalysisFilenameFile size
T159L60fqar1999/12/24/12zERA-InterimT159_1999122412_fqar.tgz22Mb
T255L60fqak1999/12/24/12zERA-InterimT255_1999122412_fqak.tgz54Mb
T511L60fqaj1999/12/24/12zERA-InterimT511_1999122412_fqaj.tgz205Mb
T1023L60fs2y1999/12/24/12zERA-InterimT1023_1999122412_fs2y.tgz780Mb
T1279L60fqaf1999/12/24/12zERA-InterimT1279_1999122412_fqaf.tgz1.2Gb

To unpack files with .tgz, either use:

tar zxf T159_1999122412_fqar.tgz

or if your tar command does not support compression:

mv T159_1999122412_fqar.tgz T159_1999122412_fqar.tar.gz
gunzip T159_1999122412_fqar.tar.gz
tar xf T159_1999122412_fqar.tar

Multiple start dates
ResolutionExp idStart datesAnalysisFilenameFile size
T255g8oz1999/12, 14th-25th, 12zERA-InterimT255_199912_14-25_g8oz.tar.bz2660Mb
T511g8su1999/12, 14th-25th, 12zERA-InterimT511_199912_14-25_g8su.tar.bz22.3Gb
T1279g8t31999/12, 14th-25th, 12zERA-InterimT1279_199912_14-19_g8t3.tar.bz2
T1279_199912_20-25_g8t3.tar.bz2		6Gb

These files use the 'bzip2' command rather than 'gzip', to achieve a better compression.

Uncompressing may take a long time depending on your system.

To uncompress:

bzip2 -d T255_199912_14-25_g8oz.tar.bz2
tar xf T255_199912_14-25_g8oz.tar


Download instructions

Example using T159
% mkdir -p runs/lothar/t159
% cd runs
% ftp ftp.ecmwf.int
ftp> cd case_studies/lothar_storm
ftp> binary
ftp> get 1999122412_T159_fqar.tgz
ftp> quit
% tar zxf 1999122412_T159_fqar.tgz
% ls
1999122412_T159.tgz  ICMCLfqarINIT  ICMGGfqarINIT  ICMGGfqarINIUA  ICMSHfqarINIT  ecmwf
% ls ecmwf
NODE.001_01  namelistfc

The 'ecmwf' directory contains the files produced at ECMWF when this experiment was run:

  • namelistfc : copy this file to 'fort.4' to run the experiment (modify as required)
  • NODE.001_01 : this is the model output file as run at ECMWF. If your run fails, it may be useful to compare with this file.

Suggested sensitivity experiments

As ERA-Interim is an improved analysis, forecasts from these starting initial conditions will not reproduce the operational forecast of the storm as it was in 1999. Because of changes to the forecasting system, this is impossible to reproduce with OpenIFS. A proxy is to run the model at the same resolution as the ERA-Interim data (T255) as this is close to the resolution of the operational model of the time. 

The IFS is highly tuned to give the best forecast over a range of initial conditions. However, it is instructive to try some sensitivity experiments to understand the role of various physical and dynamical processes.

  • What's the impact of the different 'lead times' on the forecast of the storm (i.e. starting from different dates)?

  • What's the impact of resolution on the forecast of the storm: both for it's development and impact over areas worse hit in Europe?

  • Does reducing the model timestep improve or worsen the forecast?

  • Reduce the gravity wave drag - how does this affect the forecast in the upper and lower levels?

     Edit the source code to half the gravity wave drag coefficient

    File: ifs/phys_ec/sugwd.F90, change:

    Line 108: !  Revised gwd parameter values
Line 109: GKDRAG =0.15_JPRB

    to:

    Line 108: !  Revised gwd parameter values
Line 109: GKDRAG = 0.075_JPRB   !  half GWD coefficient: 0.15_JPRB

  • Increase the precipitation auto conversion rate - what impact does this have?

    Edit the source code to increase the auto conversion rate by 20%

    File: ifs/phys_ec/sucldp.F90, change:

    line 123: RKCONV=1._JPRB/6000._JPRB   ! 1/autoconversion time scale (s)

    to:

    line 123: ! RKCONV=1._JPRB/6000._JPRB   ! 1/autoconversion time scale (s)
line 124: RKCONV=1.2_JPRB/6000._JPRB    ! default scaled by 20%: 1/autoconversion time scale (s)

  • Change the surface transfer coefficient in the turbulence scheme

    Reduce the coefficient by 20%.

    Alter surf/module/surfexcdriver_ctl_mod.F90 from :

    line 671:  DO JL=KIDIA,KFDIA
line 672:    IF (JTILE == IFRMAX(JL)) THEN 
line 673:      PKHLEV(JL)=ZKHLEV(JL)
line 674:    ENDIF
line 675:  ENDDO

    to:

    line 671:  DO JL=KIDIA,KFDIA
line 672:    IF (JTILE == IFRMAX(JL)) THEN 
line 673:      PKHLEV(JL)=ZKHLEV(JL)
line 674:    ENDIF
line 675:    !  reduce surface transfer coeff by 20% in turbulence scheme
line 676:    ZCFMTI(JL,JTILE)=0.8_JPRB*ZCFMTI(JL,JTILE)
line 677:  ENDDO

  • Reduce the asymptotic mixing length scale (K) - how does this affect surface & near-surface fields?

    For this change, two files need to be edited:

    ifs/phys_ec/suvdf.F90
     line 53: RLAM   = 75.0_jprb  !! 150._JPRB: reduce to 75m

    and:

    ifs/phys_ec/vdfexcu.F90
     ZKLEN     = 75.0_jprb  !! 150.0_JPRB     ! asymptotic K length scale troposphere - Reduce to 75m
  • For these last 4 cases where the model's parametrizations have been altered, which make the biggest difference and why? Does any of the changes improve the forecast in any way?

  • If you were providing forecasts for wind and precipitation to the general public based on these experiments, what could you say with certainty and what is less certain? How would this change over different countries?


Further reading

Wernli et al., 2002, QJRMS

Ulbrich et al., 2001, Weather, 56, 70-80

Wikipedia article:

Cyclone Lothar and Martin, Wikipedia article, retrieved 17/12/14.

This article in a recent ECMWF Newsletter has a description of student projects at the University of Stockholm using the Lothar storm case study.

A. Hannachi, J. Kjellsson, M. Tjernström, G. Carver, 2012, Teaching with the OpenIFS at Stockholm University, ECMWF Newsletter No. 134, Winter 2012/13.

Comments

The forecasting system at ECMWF makes use of "ensembles" of forecasts to account for errors in the initial state. In reality, the forecast depends on the initial state in a much more complex way than just the model resolution or starting date.  At ECMWF many initial states are created for the same starting time by use of "singular vectors" and "ensemble data assimilation" techniques which change the vertical structure of the initial perturbations.

As further reading and an extension of this case study, research how these methods work.

Acknowledgements

We gratefully acknowledge: Dr Anton Beljaars (ECMWF) for suggestions and code changes for the parametrization changes in the list of sensitivity experiments; Prof Erland Kallen for reviewing & comments on the text.