On What Scale Can We Predict the Agronomic Onset of the West African Monsoon?

Rory G J Fitzpatrick,Peter Knippertz,Caroline L Bain,Douglas J Parker,John H Marsham

doi:10.1175/mwr-d-15-0274.1

Rory G J Fitzpatrick, Peter Knippertz + Show 3 more

Open Access

https://doi.org/10.1175/mwr-d-15-0274.1

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Abstract

Abstract Accurate prediction of the commencement of local rainfall over West Africa can provide vital information for local stakeholders and regional planners. However, in comparison with analysis of the regional onset of the West African monsoon, the spatial variability of the local monsoon onset has not been extensively explored. One of the main reasons behind the lack of local onset forecast analysis is the spatial noisiness of local rainfall. A new method that evaluates the spatial scale at which local onsets are coherent across West Africa is presented. This new method can be thought of as analogous to a regional signal against local noise analysis of onset. This method highlights regions where local onsets exhibit a quantifiable degree of spatial consistency (denoted local onset regions or LORs). It is found that local onsets exhibit a useful amount of spatial agreement, with LORs apparent across the entire studied domain; this is in contrast to previously found results. Identifying local onset regions and understanding their variability can provide important insight into the spatial limit of monsoon predictability. While local onset regions can be found over West Africa, their size is much smaller than the scale found for seasonal rainfall homogeneity. A potential use of local onset regions is presented that shows the link between the annual intertropical front progression and local agronomic onset.

Highlights

Accurate forecasting of the West African monsoon (WAM) is a topic of great importance for local stakeholders and the wider forecasting community
Over West Africa there is research into how seasonal precipitation totals or the annual shift of the maximum precipitation belt are affected by many drivers
These include but are by no means limited to sea surface temperatures (e.g., Caniaux et al 2011; Rowell 2013), the Saharan heat low (Lavaysse et al 2009) and associated modulation in forcing by midlatitude Rossby waves (Roehrig et al 2011), the phase and intensity of the Madden–Julian oscillation (Maloney and Shaman 2008; Lavender and Matthews 2009), dry-air intrusions from the Mediterranean tied to the Rossby wave response of the Indian monsoon onset (Flaounas et al 2012a,b), or African easterly waves (Berry and Thorncroft 2005; Bain et al 2014), among other examples

Summary

Introduction

Accurate forecasting of the West African monsoon (WAM) is a topic of great importance for local stakeholders and the wider forecasting community. Over West Africa there is research into how seasonal precipitation totals or the annual shift of the maximum precipitation belt are affected by many drivers These include but are by no means limited to sea surface temperatures (e.g., Caniaux et al 2011; Rowell 2013), the Saharan heat low (Lavaysse et al 2009) and associated modulation in forcing by midlatitude Rossby waves (Roehrig et al 2011), the phase and intensity of the Madden–Julian oscillation (Maloney and Shaman 2008; Lavender and Matthews 2009), dry-air intrusions from the Mediterranean tied to the Rossby wave response of the Indian monsoon onset (Flaounas et al 2012a,b), or African easterly waves (Berry and Thorncroft 2005; Bain et al 2014), among other examples.

Data and definitions used

Method for identifying local onset regions

Correlation between local onset regions and the intertropical front

Findings

Summary