Predictability of weather and climate

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.

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.

Abstract:

Disastrous bushfires during the last months of 2019 and January 2020 affected Australia, raising the question to what extent the risk of these fires was exacerbated by anthropogenic climate change. To answer the question for southeastern Australia, where fires were particularly severe, affecting people and ecosystems, we use a physically based index of fire weather, the Fire Weather Index; long-term observations of heat and drought; and 11 large ensembles of state-of-the-art climate models. We find large trends in the Fire Weather Index in the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis (ERA5) since 1979 and a smaller but significant increase by at least 30 % in the models. Therefore, we find that climate change has induced a higher weather-induced risk of such an extreme fire season. This trend is mainly driven by the increase of temperature extremes. In agreement with previous analyses we find that heat extremes have become more likely by at least a factor of 2 due to the long-term warming trend. However, current climate models overestimate variability and tend to underestimate the long-term trend in these extremes, so the true change in the likelihood of extreme heat could be larger, suggesting that the attribution of the increased fire weather risk is a conservative estimate. We do not find an attributable trend in either extreme annual drought or the driest month of the fire season, September–February. The observations, however, show a weak drying trend in the annual mean. For the 2019/20 season more than half of the July–December drought was driven by record excursions of the Indian Ocean Dipole and Southern Annular Mode, factors which are included in the analysis here. The study reveals the complexity of the 2019/20 bushfire event, with some but not all drivers showing an imprint of anthropogenic climate change. Finally, the study concludes with a qualitative review of various vulnerability and exposure factors that each play a role, along with the hazard in increasing or decreasing the overall impact of the bushfires.