Having shown that, on average G4, has a good simulation of the northward progression of the rains throughout the monsoon season (Fig. 1), and that there is some predictability of interannual variations in onset timing, we now explore the mechanisms that control onset. The mean properties of WAM onset in G4 and reanalyses are explored in Sect. 4.1. Onset variability and the source of forecast skill, as found in the previous section, are investigated in Sect. 4.2. Throughout this section we will use the rainfall-based onset indicator (1) (Sect. 2.3) to quantify onset.
We have seen in Sect. 3.2 (Fig. 1) that WAM onset simulated by G4 compares favourably to observations: the rainfall maxima move north from the Gulf of Guinea coast to the Sahel in early July, similar as the observations although G4 is wetter over the Sahel in July than the observations. As noted before, in the ERAI and MERRA reanalyses the rainfall maxima do not penetrate far enough north into the Sahel, i.e. north of 10N (Fig. 1), or do so later than observed. The aim is to understand what causes the mean evolution of G4 and reanalyses rainfall to be different at the time of onset in early July, as evident from Fig. 1.
For G4 we use 1 May hindcasts for years 1992–2005 which have additional diagnostic output. For ERAI and MERRA we use the full range of available years (1979–2010) to obtain the best possible estimate of the atmosphere’s mean state. For the period 1992–2005 average onset dates are very similar in all datasets: 2 July (G4), 29 June (MERRA), 3 July (ERAI), 28 June (GPCP) and we will analyse differences averaged between 15–29 June and 30 June–14 July, i.e. the 15 days before and after the nominal mean onset date.
Average MSLP, rainfall and horizontal moisture transport at 925 hPa from G4 in the second half of June are shown in the top panel of Fig. 7 (mean fields for ERAI and MERRA are qualitatively similar and not shown here). The Saharan heat low is well established with cyclonic low-level winds advecting maritime air into the western and central Sahel. Flow from the Gulf of Guinea towards the Sudan region appears to be driven by the pressure difference between the tropical Atlantic and the Red Sea. To determine the changes that occur in these variables around the mean onset date we calculate the composite difference of the average over 30 June–15 July minus the average over 15–29 June. In G4 (middle panel of Fig. 7) the Saharan heat low deepens by 2 hPa in early July on the Atlantic side of its centre. The high pressure over the Gulf of Guinea increases by 1 hPa, following the seasonal cooling of local SST at this time (see also Thorncroft et al. 2011). These anomalous pressure gradients induce increased moist flow into the continent near the Gulf of Guinea coast and Senegal/Mauretania with moisture convergence (shown by the white ‘+’ signs) in the central Sahel (between 10E–10W and 10–15N). This eastward flow establishing around the onset is reminiscent of the regional model study by Sijikumar et al. (2006). This region also has increased ascent (indicated by ‘o’) and increased rainfall. This is associated with increased low level convergence from the west and south which provides a source of latent heating in this region (not shown here, but its zonal mean may be seen in Fig. 9). A noticeable feature of the MSLP anomalies in G4 in early July is their largely zonal orientation between 15–20N.
In ERAI (Fig. 7 lower panel) the Saharan heat low also deepens by 2 hPa but pressure changes in the Sahel and central Sahara are weaker than in G4. As a result the pressure anomaly in ERAI in early July is less zonal and dominated by the cyclonic feature in the western Sahara. Pressure increase over the Gulf of Guinea is smaller than in G4, about 0.5 hPa. As a result of these different pressure changes moisture transport anomalies at 925 hPa do not penetrate into the central Sahel but instead are diverted northward to the western Sahara. Near the Gulf of Guinea coast the change in moisture transport is orientated more zonally than in G4 and mostly non-divergent. There is no extra ascent between 10E–10W and 10–15N as in G4 and more extensive descent of dry air from aloft over Mali and Mauretania. Rainfall changes in ERAI in early July are limited to the ocean and the eastern Sahel with a gap over the central Sahel. We note that G4 and ERAI are in broad agreement about changes over the eastern Sahel/central Sudan.
Verification of these changes in G4 requires observations made for long enough and with sufficient temporal resolution to reliably estimate 15-day changes. We use HadISD, a dataset of quality-controlled sub-daily WMO station reports (Dunn et al. 2012). Note that many of these data will have been assimilated in ERAI and this should be kept in mind when comparing ERAI and HadISD. We use HadISD to estimate average MSLP changes between early July and late June 1979–2010, Fig. 8 (see Appendix 2 for details of the calculation). Local minima of negative pressure change are seen over Morocco and Egypt, positive pressure change is seen south of the Sahara with perhaps a local maximum around 12N. The available observations show that model and ERAI reanalyses get the large scale pattern right: positive in the south, negative in the northwest (compare Figs. 7 and 8). The changes in the Sahel in ERAI are perhaps somewhat weaker than in the station data; those in GloSea4 in the northern Sahara (Algeria and Libya) are too strongly negative. Unfortunately there is little data coverage in HadISD between 15 and 25N, i.e. in the northern Sahel and southern Sahara. This means that we cannot determine if the pressure pattern of G4 or ERAI in this region is more realistic. If this gap in coverage of station data in HadISD is representative of the station data assimilated in ERAI then it suggests that, on average, over the course of the reanalysis period ERAI is perhaps not strongly constrained by station observations in the region between 15 and 25N.
We extend this analysis of the near-surface changes to that of changes aloft, in a meridional/vertical plane. We do this for specific humidity, zonal, meridional and vertical pressure velocity at pressure levels between 1,000 and 400 hPa, and supplement this with precipitation, MSLP, surface skin temperature, sensible heat (‘SH’) and latent heat (‘LH’) flux and total cloud cover changes. We calculate zonal means between 10E and 10W and calculate composite differences in these variables before and after onset. (Figs. 9, 10, see captions for legend).
In G4 the northward shift in rainfall is clearly visible, centered around 10N. This shift is accompanied by a drying south of 10N (5N at higher levels) and a moistening north of 10N across most of the troposphere. There is also an increase in cloud cover north of 10N. We see an increase in low-level northward flow between 5 and 25N. Cooler SSTs mean there is reduced latent heat (‘LH’) flux and anomalous descent over the ocean, which is consistent with the drying of the atmosphere south of 5N. Over land we see an increase in surface LH flux around 15N that is collocated with anomalous rising across most of the troposphere (cf. ‘o’ in Fig. 7). At the latitudes where LH flux increases (12–18N) sensible heat (‘SH’) flux is reduced. To the north we see an increase in SH flux. Hagos and Zhang (2010) calculated the divergent circulation response of the WAM to SH and LH fluxes, with the circulation driven by SH flux instrumental in advancing the monsoon circulation inland. It is beyond the scope of this paper to repeat their analysis for G4. However, we note a similar colocation as Hagos and Zhang (2010) of LH changes and deep overturning changes (increase around 15N, decrease south of 10N) and, to a lesser extent, of SH increase and shallow overturning (north of 20N). We note that the African Easterly Jet weakens near 10N, as observed by Sultan and Janicot (2003) in the NCEP reanalyses. For most variables we lack the independent observations to verify these changes in G4, except for precipitation. Comparing zonal mean precipitation in G4 and GPCP (green line in bottom panel of Fig. 9) suggests that G4 gets the right pattern of rainfall change but overestimates its amplitude. A possible interpretation is that in G4 the processes controlling onset are working in the right way but are overly active.
The ERAI (Fig. 10) and MERRA (Fig. 19, Appendix 4) reanalyses show essentially the same response as G4 south of 5N (i.e. over the ocean and the coast), but differ substantially from G4 over land. Moistening of the troposphere over land is weaker and does not extend much above 800 hPa. Instead we see drying between 500 and 700 hPa and increased southward flow of dry air from the Sahara (stronger and reaching further south than in G4). Between 10 and 15N there is downward flow of dry air in the reanalyses (see also ‘V’ in Fig. 7), whereas G4 has upward motion here. Changes in the boundary layer (e.g. MSLP and latent heat flux) and the enhanced monsoon inflow at 925 hPa are smaller than in G4. Like G4, the reanalyses overestimate rainfall changes over the ocean and just north from the coast (0–10N) compared to GPCP.
Summarising, the key difference between G4 and the reanalyses is the presence of dry air over the Sahel across most of the middle and lower troposphere. The reanalyses have weaker low-level inflow of moist air from the ocean than G4 and a stronger flow aloft of dry air from the Sahara. This implies that the reanalyses have a smaller increase in moisture supply to the lower and middle troposphere and less increased upward motion or convection over the Sahel, consistent with the dry rainfall bias in the Sahel north of 10N. G4 and reanalyses do generate a reduction in rainfall over the coastal region, as seen in GPCP, and this is one of the two components of onset indicator (1). It explains why onset dates from the reanalyses have some correlation with GPCP-based onset in spite of their shortcomings in reproducing rainfall changes over the Sahel.
Seasonal forecast skill in the atmosphere arises from the interaction between the atmosphere and more slowly evolving (i.e. more predictable) components of the climate system, e.g. sea surface temperature (SST). In this section we will therefore investigate the relation between SST and the rainfall-based onset indicator (1) (Sect. 2.3)
Teleconnection with SST
To see how June SST anomalies affect timing of the onset we calculate a regression between these variables (units °C/day). We do this for observations (HadISST SST (Rayner et al. 2003) and GPCP-derived onset dates); G4 hindcasts (initialised on 1 May) and ERAI and MERRA reanalyses, Fig. 11. Positive teleconnections show where warm SST delays the onset and cold SST hastens onset (opposite for areas of negative teleconnections). The observed teleconnection pattern (top left panel) shows that warm SSTs in the Gulf of Guinea (‘GoG’) and S tropical Atlantic delay onset. There is a significant signal in the Pacific (mainly in W Pacific and off equator, i.e. outside the Niño 3 and 4 regions). G4 captures the pattern in the S Atlantic but it is too weak, i.e. effect of warm SST anomalies in delaying the onset is too small compared to observations. The model does not capture the contribution from SST outside the equatorial Atlantic. The reanalyses have teleconnections similar to the observed in the equatorial Atlantic, but over the Pacific both differ substantially from the observed pattern. Teleconnections in the six ENSEMBLES hindcasts are shown in the Appendix 3, Fig. 18. Most ENSEMBLES models capture the teleconnection in the Atlantic but differ in the simulated strength. Like the reanalyses, none of these models accurately reproduce the observed pattern over both the Pacific and Indian Ocean.
To confirm the robustness of the observed teleconnection pattern of Fig. 11 we also calculated it using different observational SST datasets: Reynolds OIv2 (Reynolds et al. 2002) and HadSST3 (Kennedy et al. 2011). June SST teleconnections using these SST observations are very similar to that for HadISST (not shown). Pattern correlation with the HadISST-derived pattern is strong: 0.82 for Reynolds and 0.70 for HadSST3. None of the teleconnection patterns change much if they are calculated over the G4 extended hindcast period 1989–2009 (not shown). Therefore we believe that the observed teleconnection pattern in Fig. 11 is a robust feature. On its own, however, a statistical relation between SST and monsoon onset date does not necessarily mean that SST affects the timing of the onset directly. For example both could be driven by some other process, or the statistical relation could just be picking up random fluctuations in the climate system that happen to co-incide but have no physical connection. However, we found additional support for a direct physical link in two ways.
Firstly, we found that the more accurately a model reproduces the observed teleconnection pattern, the better its hindcast skill is of monsoon onset: Fig. 12 shows the anomaly correlation of onset in hindcasts and observed onset (vertical axis) against pattern correlation between simulated and observed teleconnection (horizontal axis) for models and reanalyses. Better hindcast skill is found in models with better pattern correlation. This suggests that the observed teleconnection pattern is not merely noise but indicates a pathway for SST to affect timing of the monsoon onset. This forcing pathway forms a source of potential skill in models, provided they can reproduce this teleconnection. The Meteo France and CMCC-INGV are best at capturing this teleconnection pattern and have the best anomaly correlation with observed onset. This is perhaps surprising, given that these models have the largest mean biases in Sahelian rainfall of the ensemble (Fig. 17). It suggests that processes controlling the mean rainfall amount over the Sahel and those that control variability of timing of onset are not the same.
Establishing how Atlantic SST anomalies can affect onset date provides a second argument for the importance of the teleconnection of Fig. 11. We will investigate this in the following section. Previous studies have highlighted the possibility of remote influences on the African monsoon at intra-seasonal timescales: model experiments by Lavender and Matthews (2009) have suggested that SSTs in the Pacific warm pool can affect convection in West Africa through the MJO. Flaounas et al. (2011) describe how westward propagating Rossby waves, triggered by onset of the Indian monsoon, can inhibit convection over West Africa. We will focus on the role of Atlantic SST, the nearest ocean basin. All models and reanalyses capture its teleconnection to some extent, whereas many struggle to reproduce the observed SST teleconnection over the combined other basins (i.e. the tropical Pacific as well as Indian oceans).
Monsoon response to Atlantic SST
In this section we investigate what processes give rise to a late monsoon onset and how they are linked to SST.
Footnote 1 We compare processes in G4 and in MERRA and ERAI re-analyses. As seen in the previous section, G4 has problems with onset being too unresponsive to Atlantic SST. Reanalyses also have problems with monsoon onset, e.g. their failure to reproduce the observed shift of the rainfall maximum to north of 10N during JAS (Fig. 1). Neither G4 nor reanalyses should therefore be thought of as completely representative of the real atmosphere and their comparison should be viewed as a sensitivity study of the processes that can cause late onset.
For G4 we use the same hindcast (1992–2005) as in Sect. 3.2. For the reanalyses we use the maximum range of available years (1979–2010) to obtain the best possible estimate of the processes. Building on our analysis of the mean onset (Sect. 3.2, Fig. 7) we start by looking at low-level changes first and subsequently analyze the latitude-height cross sections. In Fig. 13 we show regressions of all variables onto onset date, in order to quantify how they change when onset is late.
In G4 (Fig. 13 top row) warm SST in late June in the Gulf of Guinea (‘GoG’) causes a local reduction of MSLP and consequently a reduction in the north-south pressure gradient between the ocean and the land (see the mean state in Fig. 7, top panel). Furthermore, there is a shift in the center of the Saharan heat low to the north-east (cf. Fig. 7 top panel). Over the GoG the pressure change drives anomalous low-level moisture transport towards the coast (strongest from the ocean side) which sees an increase in rainfall. The changes in the Saharan heat low cause a weakening of the westerly moisture transport between 10 and 20N from the Atlantic and cause a reduction of rainfall over the Sahel. In the first half of July the pressure anomaly over the GoG has largely subsided (although, interestingly, the warm SST anomaly is still present there). In the Sahel the warm surface air temperature anomaly has increased and there is a large negative pressure anomaly here. The now increased pressure difference between the GoG and the Sahel reinstates the northward moisture transport to the Sahel from the GoG. Westerly moisture transport from the Atlantic between 10 and 15N is still weakened. The rainfall anomalies in early July reflect this, with reduced deficit in the east but sustained deficit in the west. In the second half of July (not shown) most anomalies over land have disappeared.
In ERAI (Fig. 13 bottom row) in late June there is a warm SST anomaly in the GoG associated with a late onset, but no sign of related MSLP change here. Instead, we note a large positive pressure anomaly over the central and eastern Sahara (Algeria, Libya and Egypt), with signs of a cold anomaly at the surface. This reduces the north-south pressure difference between the land and the ocean, reducing the low-level moisture transport from the GoG into the central Sahel. The increased low-level moisture convergence near the GoG causes increased rainfall there. In the Sahel there is little change in rainfall, apart from a region over Niger. In early July the pressure anomaly over the Sahara has disappeared. There are still rainfall anomalies over the coast and eastern Sahel/Sudan region but the regression of onset date onto SST shows a weakened signal over the GoG.
To verify these relations in observations we again use the HadISD station data and the GPCP-derived onset date. Regressions from the station data onto the onset date are shown in Fig. 14 (details in Appendix 2). It confirms the presence of negative MSLP and warm air temperature anomalies in the Sahel and near the GoG coast in both periods, similar to G4 but with a smaller amplitude. As before, there are insufficient observations in the southern Sahara (15–25N). In the northern Sahara the observations in late June show no significant MSLP signal like ERAI does. The observations do show a positive MSLP anomaly north of 30N in early July by which time the MSLP anomaly has disappeared in the ERAI reanalyses.
We use the same variables as for the mean onset in Sect. 3.2 and calculate zonal means of these fields between 10E and 10W for latitudes 10S–30N. The zonal mean fields were then time-averaged over two 15-day periods before and after average GPCP monsoon onset: 15 June–29 June and 30 June–14 July. Finally, we regressed the zonally and temporally averaged fields against the respective model/reanalysis monsoon onset dates, to determine the linear change ‘per day of late onset’ for each data set (Fig. 15).
In G4, warm SST in the second half of June causes a strong upward LH flux or evaporation over the ocean, and deep upward motion, with low-level meridional convergence: northward flow south of 5N, southward flow between 5 and 10N where it opposes ‘normal’ monsoon inflow. There is an increase in precipitation around the Gulf of Guinea (‘GoG’) coast (5N) and a reduction in the Sahel (north of 10N). The low-level flow is consistent with anomalous gradients in MSLP (purple line). Over the land area north of 10N there is anomalous poleward flow above 700 hPa and a strengthening of the AEJ. In the area of anomalous ascent over the ocean specific humidity increases, whereas over land around 15N there is drying, strongest between 925 and 800 hPa. Consistent with the drier air, rainfall and total cloud cover are reduced around 15N. A warm skin temperature anomaly appears at 15N, accompanied by increased surface SH flux and decreased LH flux. In the first half of July the warm anomaly over land near 15N amplifies, as do the SH and LH flux changes. MSLP over land deepens further, with a local minimum near 15N. At this latitude increased ascent develops with increased northward and eastward low-level flow towards 15N. The anomalous circulation is again reminiscent of that described by Hagos and Zhang (2010): near LH flux anomalies there is deep ascent and low-level convergence that acts to delay northward progression of the monsoon; near SH maxima there is shallow ascent (up to about 700 hPa) whose low-level convergence promotes the inland penetration of the monsoon flow.
In the ERAI reanalyses we see in the second half of June a similar behaviour as G4: a warm SST, with anomalous ascent/moistening and increase in precipitation near the GoG coast, and a southward low-level flow between 5 and 20N. Differences are the amount of moistening over the ocean, which is smaller than G4 and the drying over land, which is stronger than G4. Also, the anomalous flow over the Sahel above 700 hPa is southward, bringing dry air from the Sahara, whereas it is northward in G4, i.e. coming from the ocean. During the first half of July ERAI also has an amplification of the warming at 15N, SH flux and low pressure anomaly at 15N, but not as strong as G4. The main differences with G4 in this period is that ERAI does not bring in more humid air around 10N in the lower troposphere and that the southward flow anomaly between 5–10N and 1,000–850 hPa persists to the first half of July. It is not until the second half of July that a small increase is seen in the low-level northward flow near 15N (not shown).
In MERRA the changes over the ocean in the second half of June are similar to G4 and ERAI (Fig. 20). Over land the flow aloft is southward (like in ERAI), but the drying over land is not as large as ERAI and more like G4. In the first half of July anomalous northward flow develops around 10N (between 925–850 hPa), like in G4.
In summary: Reanalyses and G4 all show that warm SSTs in the equatorial Atlantic in late June cause anomalous evaporation, and anomalous ascent near the GoG coast. The ascent is fed by low-level southward flow between 5 and 10N that opposes the monsoon inflow. This causes a drying of the lower troposphere and reduction of rainfall over the Sahel. There is less consensus about what happens next, in the first half of July. All models show a warming of the land in the Sahel. In G4 this causes a strong increase of SH flux and a local drop in MSLP near 15N that acts to accelerate the monsoon inflow. This is followed by the arrival of more humid air over the Sahel in late July. In ERAI and MERRA the response of the land surface is smaller than G4. A small increase of the monsoon inflow into the Sahel is seen in MERRA (early July) and ERAI (late July), but otherwise there is little sign of any anomalies in the reanalyses from mid-July onwards.
The scarcity of model-independent observations in this region over long enough periods makes it difficult to assess how realistic model and reanalyses are in simulating processes associated with variability of onset. However, we can compare the simulated changes in precipitation with those in GPCP observations (green lines in Fig. 15). The good agreement between observations and models (as well as between G4/reanalyses) near the coast in the second half of June suggests that we can have confidence in this part of the response to warm SST. Over land the surface response is quantitatively different in model/reanalyses, and we are therefore less confident about this part of the response associated with late onset. One interpretation of these results is that over land G4 is too active, whereas the reanalyses are too inactive.