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. The N.America case has strong large scale forcing whereas the central African case is driven by the diurnal cycle.
Both cases are studied starting the forecast from the same date/time (initial conditions).
In these case studies, you will carry out a control forecast, followed by any number of suggested sensitivities experiments.
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).
This case study will look at the role of convection and the large scale in these events.
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)
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.Increase the precipitation auto conversion rate - what impact does this have? (both)
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.Sensitivity to entrainment rate (both)
Additional questions
- How important is the correct diurnal cycle of precipitation and radiation for 2m temperature and dewpoint forecast?
Further reading
- P. Bechtold et al, 2014Representing Equilibrium and Nonequilibrium Convection in Large-Scale Models. J. Atmos. Sci., 71, 734–753. http://journals.ametsoc.org/doi/abs/10.1175/JAS-D-13-0163.1
- See section on convection in description of Atmospheric Physics: http://www.ecmwf.int/en/research/modelling-and-prediction/atmospheric-physics
- More information about the N.American tornadoes can be found on the ECMWF Severe Event Catalogue - 201404 - Convection - Arkansas U.S
- IFS documentation, Part IV, Physical Processes - Chapter 6: convection (PDF).
- ECMWF Newsletter, summer 2014, number 140. Article on OpenIFS user workshop 2014 (Stockholm), page 2 (PDF)
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 grateful to: Peter Bechtold, Filip Vana, Sandor Kertesz in preparing the material for the OpenIFS user workshop in Stockholm 2014, from which most of the material on this page is derived. We also thank the forecast department for their material on the ECMWF Severe Event Catalogue that was used in preparing these cases.