Introduction This page describes two studies of different convective cases; one over N. America associated with formation of severe tornadoes, the other over central Africa. Both cases are studied starting the forecast from the same date/time (initial conditions). The N.America case has strong large scale forcing whereas the central African case is driven by the diurnal cycle. US Tornado convection case (Arkansas) On the 27 April 7pm local time (00UTC 28 April), tornadoes hit towns north and west of Little Rock, Arkansas killing approx 17 people.  (http://edition.cnn.com/2014/04/28/us/severe-weather/index.html?hpt=hp_c2). On the evening on the 28 April fatal tornadoes occurred over Mississippi (http://www.bbc.co.uk/news/world-us-canada-27199071). More information can also be found on the ECMWF Severe Event Catalogue 201404 - Convection - Arkansas U.S. African diurnal deep convection (Central Africa) To be done.

Initial conditions

To be done.

Key questions to address with the control forecast

TODO: Add maps.

Case study: N.America deep convection

On 27 April 2014 7pm local time (00UTC 28 April), tornadoes hit towns north and west of Little Rock, Arkansas.

Case study: African deep convection

TODO: note area of interest (show WV image?)

Sensitivity experiments

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.

Not all of the suggested experiments are applicable to both cases, indicated in brackets.

• What's the impact of the different 'lead times' on the forecast of the convection (i.e. starting from different dates)? (N.America only)
• What's the impact of resolution on the forecast of the convection? (both)
• Does reducing the model timestep improve or worsen the forecast? (both)

• Turn off deep convection (both)

  Do this by editing fort.4, find the namelist block NAMCUMF and add a line: LMFPEN=false,            ! disable deep convection

• Impact of the improved diurnal cycle of convection. (Africa only)
  In this sensitivity experiment, look at the timing of convective and precipitation events by changing how the model parametrizes the diurnal cycle.

  OpenIFS has 3 options for the controlling the diurnal cycle. To change between them: - Edit the fort.4 file - Find the namelist NAMCUMF and change the parameter RCAPDCYCL accordingly: RCAPDCYCL = 2 (default) activates the diurnal cycle using sub-cloud CAPE, RCAPDCYCL = 1 diurnal cycle using surface sensible heat flux, RCAPDCYCL = 0 reverts the code to a setting before the diurnal cycle for convection was implemented.

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

  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)

• Impact of the convective time scale adjustment (both)
  An optimization factor in the parametrization is used for tuning the diurnal cycle. This can be altered by changing a value in the model namelist.

  To change the timescale: - Edit the fort.4 file - Find the namelist  NAMCUMF, parameter RTAUA. - The default value is RTAUA=1. - Run two sensitivity experiments with values of RTAUA = 0.33 and 3. The ratio between the actual cloud base mass flux and the unit (initial) cloud base mass flux: \frac{M_{base}}{M^*_{base}} = \frac{PCAPE - PCAPE_{bl}}{\tau} Look at the amplitude of precipitation.

• Sensitivity to entrainment rate (both)

  To change the entrainment rate: - Edit the fort.4 file - Find the namelist block NAMCUMF, parameter ENTRORG - The default value is ENTRORG= 1.75E-3 ENTRORG= 5.8E-4 reduced by factor 3 (mostly shallow convection regime) ENTRORG= 5.25E-3 multiplied by factor 3 (mostly deep convection regime) Look at the cloud top height, precipitation and eventually changes in temperature and moisture fields with respect to the reference. Note also this is having less impact with the diurnal cycle activated.

Additional questions

• How important is the correct diurnal cycle of precipitation and radiation for 2m temperature and dewpoint forecast?

Further reading

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 are pleased to acknowledge the input from Peter Bechtold, Filip Vana, Sandor Kertesz in preparing the material for the OpenIFS user workshop in Stockholm 2014, from which the material on this page is derived.

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