1. Institute for Climate and Atmospheric Science SCHOOL OF EARTH AND ENVIRONMENT Deep moist convection as a governor of the West African Monsoon C. E. Birch 1, D. J. Parker 1, A. O'Leary 1, C. M. Taylor 2, P. Harris 2, J. H. Marsham 3, G. Lister 4 N. Dixon 1, L. Garcia-Carreras 1, D. J. Parker 1, D. Copsey 2, P. Knippertz 1, G. Lister 3, C. L. Bain 2 Cathryn E. Birch 1 and J. H. Marsham 1 1 University of Leeds, 2 UK Met Office, 3 NCAS, University of Reading

2. Introduction 26 th Aug 2010, MSG Dundee receiving station Millions of people rely on the West African Monsoon rains, especially for agriculture Mesoscale convective systems provide most of the Sahel’s rainfall - precursor for Atlantic hurricanes Need to predict on both climate and NWP scales Use the Cascade simulations to: 1.Link model biases in the location and diurnal cycle of convection to biases in the large-scale circulation of the monsoon system (Marsham et al. (2013), GRL) 2.How do these biases in the circulation affect the components of the water budget (Birch et al. (2013), in prep.)? 3.Can we say something useful about reality?

3. 12 km 40 km 1.5 km 4 km Cascade simulations Multi-day continental-scale convection-permitting simulations 12km explicit versus 12km parameterised allows us to isolate the role of the representation of convection from grid-spacing. 12km explicit is coarse, but can give reasonable squall-lines (Weismann et al., 1996). Met Office Unified Model 40 days: 25 th July - 3rd Sept 2006 Explicit convection: 1.5km, 4km and 12km Parameterised convection: 12 km and 40 km NWP analyses Climate run (GA3.0), 10 year atmosphere-only simulation

4. Mean rainfall Mean diurnal cycle Parameterised gives rain too early in the day Explicit gives timing close to observations, but over-predicts the 18Z maximum Explicit models have more rain in Sahel Rainfall (mm hr -1 ) Time of day Latitude (°) Rainfall (mm hr -1 )

5. Differences in mean state: 12km runs Net surface radiation: Explicit-Parameterised Less day-time cloud in explicit gives greater solar heating (mean=14 Wm -2 ) Marsham et al. 2013

6. θ and GPH: Explicit-Parameterised 21Z Differences in mean state: 12km runs Latitude Pressure (hPa) θ More rain in 12km exp = great convective heating Boundary layer is warmer in 12km exp due to greater SW dn (i.e. fewer clouds) during the day Near-surface pressure is lower in 12km exp due to heating L More rain in explicit run over the Sahel gives greater convective heating (mean = 5.2mm/day vs. 2.8 mm/day ~ 64 Wm -2 )

7. Differences in mean state: 12km runs

8. Time evolution of differences Difference evolves within 24 hours as a result of the different representation of deep convection Increased pressure gradient = increased winds Marsham et al. 2013

9. Parker et al. 2005 Low pressure Water budget analysis High pressure

10. Moisture flux (v*q) at 400m 40km param NWP Climate 12km param 12km exp 4km exp Time of day v*q (m s -1 kg kg -1 ) Mean diurnal cycle v*q at Niamey (14°N) Time of day v*q (m s -1 kg kg -1 ) Mean diurnal cycle v*q at 6°N

11. Differences in mean state: 12km runs Different wind patterns transport different amounts of water northwards

12. Mean ET minus rainfall ALMIP-TRMM 40km param Climate 12km param 12km exp 4km exp Surface drying Surface wetting

13. Water budget components Observations 12km param 12km explicit Day Cum sum (mm s -1 ) Dries atmos Wets atmos PWVt MFD *-1 MFD monsoon *-1 Evap Ppt *-1 ET-ppt Evap Precip Evap Precip Evap Precip Evap-precip dries surface. MFD small and dries atmosphere MFD replaces atmospheric water. Evap-precip wets surface (as it should).

14. Conclusions Cascade shows a fundamentally different monsoon in the explicit runs (Marsham et al., 2013, GRL), caused by: Increased precipitation further north Convection being later in the diurnal cycle Better representation of cold pools This changes the diurnal cycle of the entire monsoon flow: Weakens the Sahel-Sahara winds and moisture transport Generates a more realistic simulated water cycle Convection acts as a “governor” to the WAM, it is self-regulating: The monsoon flow allows the moist convection to exist The convection inhibits the monsoon flow Improved parameterisations of deep convection (location, timing & structures) will improve predictions of the entire WAM and its water cycle.  Increased precipitation further north  Convection being later in the diurnal cycle  Explicit representation of cold pools The convection creates relatively low pressure in the Sahel, which weakens the Sahel- Sahara winds As the WAM moves northwards it is self-regulated by the convection itself by reducing its ability to move further north Convection acts as a “governor” to the WAM: The monsoon flow allows the moist convection to exist The convection inhibits the monsoon flow Seamless approach allows us to attribute errors in climate and NWP models to specific physical processes and also tells us something about the monsoon system in reality

15. Thank you C.E.Birch@leeds.ac.uk

16. Mean rainfall North-south rainfall distribution is difference in 40km param and 12km param Due to difference in CAPE closure: 40km = RH based, 12km = vertical velocity based 40km param triggers convection further north and has increased rainfall rates 40km param still suffers from biases associated with the diurnal cycle 40km param 12km param

17. Compute water budget terms for Cascade runs How do biases in the large-scale flow affect the water budget – does this feedback onto the large-scale flow? ET P MFD PW Water budget analysis Precipitable water (PW) tendency - Moisture flux divergence (MFD) = Evapo- transpiration (ET) - Ppt (P)

18. Mean evapotranspiration Latitude Evapotranspiration (mm s -1 )

19. Water budget components Obs – upper box 12km param – upper box12km exp – upper box Day Cum sum (mm s -1 ) PWVt MFD *-1 MFD monsoon *-1 Evap Ppt *-1 ET-ppt Dries atmos Wets atmos

20. Water budget components Obs – lower box 12km param – lower box12km exp – lower box Day Cum sum (mm s -1 ) Dries atmos Wets atmos PWVt MFD *-1 MFD monsoon *-1 Evap Ppt *-1 ET-ppt

21. Conclusions Predicting the WAM is a major challenge on all time scales The Cascade runs have different representations of the monsoon, caused by: - Increased precipitation further north in the explicit runs - Convection being later in the diurnal cycle in the explicit runs Differences are consistent with NWP and climate errors Improved parameterisations of deep convection (location, timing & structures) will improve predictions of the entire WAM system Same analysis, LBC’s, land surface Only difference is the convection scheme Within 24 hours the models diverge – has to be due to the differences in convection schemes Feedback on rainfall

22. Conclusions The explicit models suggest that in reality: The convection creates relatively low pressure in the Sahel, which weakens the Sahel-Sahara winds As the WAM moves northwards it is self-regulated by the convection itself by reducing its ability to move further north Convection acts as a “governor” to the WAM: The monsoon flow allows the moist convection to exist The convection inhibits the monsoon flow Seamless approach allows us to attribute errors in climate and NWP models to specific physical processes and also tells us something about the monsoon system in reality

23. Differences in mean state: 12km runs Net surface radiation: Explicit-Parameterised Less day-time cloud in explicit gives greater solar heating (mean=14 Wm -2 ) Lowers pressure over the Sahel, weakening the Sahel-Sahara pressure gradient Marsham et al. 2013 Z925: Explicit-Parameterised

24. Marsham et al. 2013 Differences in mean state: 12km runs Sahel - Sahara geopotential difference (m) Evidence for difference in pressure gradients in the observations Pressure gradients affect the meridional winds

25. Time evolution of differences v*q difference Exp-Param v*q greater in 12km explicit v*q greater in 12km param