A wavelet transform method to determine monsoon onset and retreat from precipitation time‐series

Journal article

A new method to determine monsoon onset and retreat timings using wavelet transform methodology applied to precipitation time‐series at the pentad scale is described. The principal advantage of this method is its portability, since it can be easily adapted for any region and dataset. The application of the method is illustrated for the North American Monsoon and the Indian Monsoon using four different precipitation datasets and climate model output. The method is shown to be robust across all the datasets and both monsoon regions. The mean onset and retreat dates agree well with previous methods. Spatial distributions of the precipitation and circulation anomalies identified around the onset and retreat dates are also consistent with previous work and illustrate that this method may be used at the grid‐box scale, not just over large area‐averaged regions. The method is also used to characterise the strength and timing of the Midsummer drought in southern Mexico and Central America. A two peak structure is found to be a robust structure in only in 33% of the years, with other years showing only one peak or no signs of a bimodal distribution. The two‐peak structure analysed at the grid‐box scale is shown to be a significant signal in several regions of Central America and southern Mexico. The methodology is also applied to climate model output from the Met Office Hadley Centre UKESM1 and HadGEM3 CMIP6 experiments. The modelled onset and retreat dates agree well with observations in the North American Monsoon but not in the Indian Monsoon. The start and end of the modelled Midsummer drought in southern Mexico and Central America is delayed by one pentad and has a stronger bimodal signal than observed.

Authors: García‐Franco, JL; Osprey, SM; Gray, LJ

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Wiley
• Journal: International Journal of Climatology
• Volume: 41
• Issue: 11
• Pages: 5295-5317
• Publication date: 2021-04-08
• Acceptance date: 2021-04-03
• DOI: 10.1002/joc.7130
• EISSN: 1097-0088
• ISSN: 0899-8418
• Language: English
• Keywords: FFR