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Initial conditions
To be done.
Run the control forecast
The first step is to run the control forecast. Both cases can be studied with a single forecast.
See below for tasks and key questions to address for the control forecast before moving on to the sensitivity experiments.
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.
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Case study: African deep convection
TODO: note area of interest (show WV image?)
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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.
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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)
Expand Do this by editing
fort.4
, find the namelist blockNAMCUMF
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.Expand title How to change the representation of diurnal convection (click here to expand...) Info 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 parameterRCAPDCYCL
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)
Expand title How to change the code (click here to expand…) Edit the source code to increase the auto conversion rate by 20%
File: ifs/phys_ec/sucldp.F90, change:
Code Block line 123: RKCONV=1._JPRB/6000._JPRB ! 1/autoconversion time scale (s)
to:
Code Block 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.Expand title How to change the time scale (click here to expand...) 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:
Mathdisplay \frac{M_{base}}{M^*_{base}} = \frac{PCAPE - PCAPE_{bl}}{\tau}
Look at the amplitude of precipitation.
Sensitivity to entrainment rate (both)
Expand 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
- 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
- ECMWF training course lecture notes on : Introduction to Moist Processes (PDF), Convection lecture 1 (PDF), Convection lecture 2 (PDF), Convection lecture 3 (PDF)
- 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.
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