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Major drivers of East African Monsoon variability and improved prediction for Onset dates
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Monsoon rain and its year-to-year variability have a profound influence on Africa’s socio-economic structure by heavily impacting agricultural and energy sectors.  The current study focuses on major drivers of the east African Monsoon during October-November-December (OND) which is a common onset window for various rainfall patterns, unimodal or bimodal. Major drivers of monsoon rain in the East African sector, covering Tanzania, Malawi, Kenya and Somalia could be different in early or extended boreal winter, due to the relative positioning of the Intertropical convergence zone and its seasonal migration -hence the location and season is the focus here.Two drivers viz. Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO) both separately  indicate very strong positive connections with monsoon(OND) rain. Not only is a strong significant correlation present in OND season with zero seasonal lag, but the signal is also present even a season ahead (before four months too).  This is also confirmed using various data sources, detrending the data, using regression technique and covering even earlier as well as later periods.  To further strengthen results, a compositing technique is applied that can additionally identify strong signals when different combinations of ENSO and IOD phases act as confounding factors. Results of precipitation anomaly suggest that when IOD and ENSO are both on the same phase in July-August-September (JAS), a significant OND rainfall anomaly is noticed around the east African sector: a deficit (excess) of monsoon rain when both drivers are in the negative (positive) phase. Walker circulation seems to play a major part in transporting signals, via reversing its ascending or descending branch over the regions, when IOD and ENSO are in the same phase. These results can be used for prediction purposes and interestingly, that criterion of IOD and ENSO being of same phase in JAS was again matched in 2022 (both negative) and hence it was possible to deliver early warnings for a deficit in the rain, a season ahead.Methods to compute the Monsoon Onset as determined by meteorological services such as the Tanzania Meteorological Authority rely on various thresholds (these can vary according to the country). To overcome some of the biases with such methods, other definitions of ‘Onset’ take into account cumulative rainfall amount: these have also been tested. Late (early) Onsets dominate years when ENSO and IOD are both in their negative (positive) phases during the JAS season. The cumulative rainfall and Onset days are correlated such that early Onsets are usually associated with more seasonal rainfall and vice versa. Uncertainty in cumulative rain as well as the Onset date of the OND Monsoon is reduced to a large degree when years are categorised based on ENSO and IOD phases of the previous season. Such results have implications for future planning in optimizing agricultural and energy outputs, mitigating severe consequences and losses, alongside taking advantage of favourable weather scenarios. It will impact the livelihoods of millions of Africans. 
Title: Major drivers of East African Monsoon variability and improved prediction for Onset dates
Description:
Monsoon rain and its year-to-year variability have a profound influence on Africa’s socio-economic structure by heavily impacting agricultural and energy sectors.
  The current study focuses on major drivers of the east African Monsoon during October-November-December (OND) which is a common onset window for various rainfall patterns, unimodal or bimodal.
Major drivers of monsoon rain in the East African sector, covering Tanzania, Malawi, Kenya and Somalia could be different in early or extended boreal winter, due to the relative positioning of the Intertropical convergence zone and its seasonal migration -hence the location and season is the focus here.
Two drivers viz.
Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO) both separately  indicate very strong positive connections with monsoon(OND) rain.
Not only is a strong significant correlation present in OND season with zero seasonal lag, but the signal is also present even a season ahead (before four months too).
 This is also confirmed using various data sources, detrending the data, using regression technique and covering even earlier as well as later periods.
 To further strengthen results, a compositing technique is applied that can additionally identify strong signals when different combinations of ENSO and IOD phases act as confounding factors.
Results of precipitation anomaly suggest that when IOD and ENSO are both on the same phase in July-August-September (JAS), a significant OND rainfall anomaly is noticed around the east African sector: a deficit (excess) of monsoon rain when both drivers are in the negative (positive) phase.
Walker circulation seems to play a major part in transporting signals, via reversing its ascending or descending branch over the regions, when IOD and ENSO are in the same phase.
These results can be used for prediction purposes and interestingly, that criterion of IOD and ENSO being of same phase in JAS was again matched in 2022 (both negative) and hence it was possible to deliver early warnings for a deficit in the rain, a season ahead.
Methods to compute the Monsoon Onset as determined by meteorological services such as the Tanzania Meteorological Authority rely on various thresholds (these can vary according to the country).
To overcome some of the biases with such methods, other definitions of ‘Onset’ take into account cumulative rainfall amount: these have also been tested.
Late (early) Onsets dominate years when ENSO and IOD are both in their negative (positive) phases during the JAS season.
The cumulative rainfall and Onset days are correlated such that early Onsets are usually associated with more seasonal rainfall and vice versa.
Uncertainty in cumulative rain as well as the Onset date of the OND Monsoon is reduced to a large degree when years are categorised based on ENSO and IOD phases of the previous season.
Such results have implications for future planning in optimizing agricultural and energy outputs, mitigating severe consequences and losses, alongside taking advantage of favourable weather scenarios.
It will impact the livelihoods of millions of Africans.
 .
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