A wavelet transform method to determine monsoon onset and retreat from precipitation time‐series
Abstract:
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.Origins of multi-decadal variability in sudden stratospheric warmings
Abstract:
Sudden stratospheric warmings (SSWs) are major disruptions of the Northern Hemisphere (NH) stratospheric polar vortex and occur on average approximately six times per decade in observation-based records. However, within these records, intervals of significantly higher and lower SSW rates are observed, suggesting the possibility of low-frequency variations in event occurrence. A better understanding of factors that influence this decadal variability may help to improve predictability of NH midlatitude surface climate, through stratosphere–troposphere coupling. In this work, multi-decadal variability of SSW events is examined in a 1000-year pre-industrial simulation of a coupled global climate model. Using a wavelet spectral decomposition method, we show that hiatus events (intervals of a decade or more with no SSWs) and consecutive SSW events (extended intervals with at least one SSW in each year) vary on multi-decadal timescales of periods between 60 and 90 years. Signals on these timescales are present for approximately 450 years of the simulation. We investigate the possible source of these long-term signals and find that the direct impact of variability in tropical sea surface temperatures, as well as the associated Aleutian Low, can account for only a small portion of the SSW variability. Instead, the major influence on long-term SSW variability is associated with long-term variability in amplitude of the stratospheric quasi-biennial oscillation (QBO). The QBO influence is consistent with the well-known Holton–Tan relationship, with SSW hiatus intervals associated with extended periods of particularly strong, deep QBO westerly phases. The results support recent studies that have highlighted the role of vertical coherence in the QBO when considering coupling between the QBO, the polar vortex and tropospheric circulation.Tracing North Atlantic Oscillation Forecast Errors to Stratospheric Origins, with a new analysis of the 2021 winter
Abstract:
The North Atlantic Oscillation (NAO) is the main driver of weather variability in parts of Eurasia, Greenland, North America, and North Africa on a range of time scales. Successful extended-range NAO predictions would equate to improved predictions of precipitation and temperature in these regions. It has become clear that the NAO is influenced by the stratosphere, but because this downward coupling is not fully reproduced by all forecast models the potential for improved NAO forecasts has not been fully realized. Here, an analysis of 21 winters of subseasonal forecast data from the European Centre for Medium-Range Weather Forecasts monthly forecasting system is presented. By dividing the forecasts into clusters according to their errors in North Atlantic Ocean sea level pressure 15-30 days into the forecasts, we identify relationships between these errors and the state of the stratospheric polar vortex when the forecasts were initialized. A key finding is that the model overestimates the persistence of both the negative NAO response following a weak polar vortex and the positive NAO response following a strong polar vortex. A case in point is the sudden stratospheric warming in early 2019, which was followed by five consecutive weeks of an overestimation of the negative NAO regime. A consequence on the ground was temperature predictions for northern Europe that were too cold. In this talk, we include a new analysis of the temperature prediction performance following the January 2021 sudden stratospheric warming. Another important finding is that the model appears to misrepresent the gradual downward impact of stratospheric vortex anomalies. This result suggests that an improved representation and prediction of stratosphere-troposphere coupling in models might yield substantial benefits for extended-range weather forecasting in the Northern Hemisphere midlatitudes.