1. © Crown copyright Met Office Deep moist convection as a governor of the West African Monsoon 1 UK Met Office, 2 University of Leeds, 3 National Centre for Atmospheric Science, Reading C. E. Birch 1 and J. H. Marsham 2 D. J. Parker 1, D. Copsey 2, N. Dixon 2, L. Garcia-Carreras 2, D. Copsey 2, P. Knippertz 1, G. Lister 3

2. © Crown copyright Met Office 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 Large biases even in reanalysis products (e.g. Meynadier et al., 2010) 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. 2.How do these biases in the circulation affect the components of the water budget? 3.Can we say something useful about reality?

3. Cascade simulations Multi-day continental-scale convection-permitting simulations © Crown copyright Met Office 12 km explicit versus 12 km 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 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 12 km 40 km 1.5 km 4 km

4. Mean rainfall © Crown copyright Met Office Parameterised gives rain too early in the day Explicit gives timing close to observations, but over-predicts the 18Z maximum Rainfall (mm hr -1 ) Time of day Rainfall (mm hr -1 ) Birch et al. (2013)

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

6. © Crown copyright Met Office Differences in mean state: 12km runs θ and GPH: Explicit-Parameterised 21Z Latitude (°) Pressure (hPa) θ More rain in 12km exp = greater convective heating (64 Wm -2 ) 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

7. © Crown copyright Met Office Differences in mean state: 12km runs

8. © Crown copyright Met Office 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. © Crown copyright Met Office Water budget analysis Parker et al. 2005 Low pressure High pressure

10. © Crown copyright Met Office Water budget analysis 40km param NWP Climate 12km param 12km exp 4km exp v*q (m s -1 kg kg -1 ) Mean diurnal cycle v*q at Niamey (14°N) Time of day Time Latitude Time Latitude Moisture flux (v*q) at 400 m above ground level Time of day v*q (m s -1 kg kg -1 ) Mean diurnal cycle v*q at 6°N

11. © Crown copyright Met Office Water budget analysis Different wind patterns transport different amounts of water northwards

12. © Crown copyright Met Office Water budget analysis Observations 12km param 12km explicit Day Cum sum (mm s -1 ) Dries atmos Precipitable water vapour tendency Moisture flux convergence Moisture flux convergence (monsoon) Evaporation Precipitation *-1 Evap-precip Evap Precip Evap Precip Evap Precip Evap-precip dries surface. MFD small and dries atmosphere MFC replaces atmospheric water. Evap-precip wets surface (as it should) Cum sum (mm s -1 )

13. © Crown copyright Met Office 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 (Birch et al, in prep): The convection and its timing weaken the Sahel-Sahara winds and moisture transport Generate a more realistic simulated water cycle Biases in the parameterised models are similar to those found in reanalysis products by Meynadier et al. (2010) 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  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

14. Thank you © Crown copyright Met Office