While extreme weather and climate events have been studied for several decades, analysis of compound events has only begun in recent years. In this burgeoning field there are still many open questions around the optimal methodology and analysis tools for analysis. After consultation with state emergency services in Tasmania, Australia, we examined which compound events have the largest impacts on their organizations. Through this consultation process we found that many of the severe flooding events in the state do not coincide with the highest rainfall days. Flooding on intense rainfall days is well understood, but flooding can also occur on days where the rainfall is not particularly extreme, especially if catchments are already saturated. Using the Australian Gridded Climate Data and six dynamically downscaled, Representative Concentration Pathway 8.5, bias adjusted Coupled Model Intercomparison Project 5 models we developed a method to quantify such compounding events to examine how they are changing from 1961 to 2100. We optimized a pre‐existing technique to estimate the antecedent conditions in catchments, combined with daily rainfall. We found that during 1961–2017, the number of compound rainfall events has been decreasing in the four Tasmanian catchments we studied, although the trend was statistically significant in only one case. The intensity of compound rainfall events was found to have increased significantly in some areas. Many future projections place Tasmania at the boundary of a drying trend to the west and wetting trend to the east and the position of this boundary varies between models leading to contrasting projected changes for parts of Tasmania. However, there is projected to be a decline in rainfall to 2100 associated with the southward shift in the storm‐track. Compound rainfall events are projected to decline throughout Tasmania, except in the south which will remain stable to 2100. The intensities are projected to increase in the south and decrease in the west, related to the changing thermodynamics and dynamics of rainfall drivers in the region in a warmer climate.

For the first time1 Australia's wine sector now has national, fine-scaled climate information, tailored to describe the climate indices most relevant to growing winegrapes across Australia informed by the most up-to-date climate science.

Sudden stratospheric warmings (SSWs) have been linked with anomalously cold temperatures at the surface in the middle to high latitudes of the Northern Hemisphere as climatological westerly winds in the stratosphere tend to weaken and turn easterly. However, previous studies have largely relied on reanalyses and model simulations to infer the role of SSWs on surface climate and SSW relationships with extremes have not been fully analyzed. Here, we use observed daily gridded temperature and precipitation data over Europe to comprehensively examine the response of climate extremes to the occurrence of SSWs. We show that for much of Scandinavia, winters with SSWs are on average at least 1 °C cooler, but the coldest day and night of winter is on average at least 2 °C colder than in non‐SSW winters. Anomalously high pressure over Scandinavia reduces precipitation on the northern Atlantic coast but increases overall rainfall and the number of wet days in southern Europe. In the 60 days after SSWs, cold extremes are more intense over Scandinavia with anomalously high pressure and drier conditions prevailing. Over southern Europe there is a tendency toward lower pressure, increased precipitation and more wet days. The surface response in cold temperature extremes over northwest Europe to the 2018 SSW was stronger than observed for any SSW during 1979–2016. Our analysis shows that SSWs have an effect not only on mean climate but also extremes over much of Europe. Only with carefully designed analyses are the relationships between SSWs and climate means and extremes detectable above synoptic‐scale variability.

Winds are one of the major meteorological contributors to deaths, damage and insured losses in Australia. A 'freak storm' hit the state of South Australia on 28 September 2016, causing state-wide blackouts and leaving 1.7 million people without power. In the first part of this two-part study, we analyse this event and find that it was indeed extreme, deepening more explosively than all but two Adelaide-affecting extratropical cyclones over the past 37 years and exhibiting the lowest central pressure. This generated hurricane force winds, with the central South Australia site of Neptune Island recording a gust of over 120kmh(-1). We show that this storm potentially contained a sting jet. Such jets are well known as a cause of major damage across Europe, and this is the first study which investigates whether a sting jet can be produced over Australia. The main deepening of the system occurred over the Great Australian Bight, so if a sting jet did form and make it to the surface, it was not the cause of the state-wide damage. However, the cyclone did contain numerous extreme gust-producing mesoscale features, as explored in part II of this paper (Earl and Simmons, 2018).

Fire regimes across the globe have great spatial and temporal variability, and these are influence by many factors including anthropogenic management, climate, and vegetation types. Here we utilize the satellite-based active fire product, from Moderate Resolution Imaging Spectroradiometer (MODIS) sensors, to statistically analyze variability and trends in fire activity from the global to regional scales. We split up the regions by economic development, region/geographical land use, clusters of fire-abundant areas, or by religious/cultural influence. Weekly cycle tests are conducted to highlight and quantify part of the anthropogenic influence on fire regime across the world. We find that there is a strong statistically significant decline in 2001-2016 active fires globally linked to an increase in net primary productivity observed in northern Africa, along with global agricultural expansion and intensification, which generally reduces fire activity. There are high levels of variability, however. The large-scale regions exhibit either little change or decreasing in fire activity except for strong increasing trends in India and China, where rapid population increase is occurring, leading to agricultural intensification and increased crop residue burning. Variability in Canada has been linked to a warming global climate leading to a longer growing season and higher fuel loads. Areas with a strong weekly cycle give a good indication of where fire management is being applied most extensively, for example, the United States, where few areas retain a natural fire regime.

An extreme extratropical cyclone (ETC) struck South Australia on 28 September 2016, causing state‐wide blackouts and damage. In the second part of this two‐part study, we examine the extreme surface wind producing mechanisms within the ETC. ETCs have been extensively studied in the Northern Hemisphere (particularly in western Europe), highlighting the gust‐producing mesoscale features within. Before now, no Southern Hemisphere ETC has been examined in this way. There were a number of extreme gust‐producing features within the ETC, comparable to those observed in storms over western Europe. One such feature was a convective line, which caused many of the most extreme gusts and knocked out the state power grid. However, dry slot convection also contributed to the extremes, and this feature rarely causes extreme gusts in ETCs over the UK. Thus, further analysis is warranted to examine whether this is a common extreme‐gust‐producing ETC feature over Southern Australia. The strongest winds recorded throughout the event occurred on 29 September, and these were associated with the cold conveyor belt which spiralled around the low‐pressure centre.

Numerous studies have addressed the mesoscale features within extratropical cyclones (ETCs) that are responsible for the most destructive winds, though few have utilized surface observation data, and most are based on case studies. By using a 39-station UK surface observation network, coupled with in-depth analysis of the causes of extreme gusts during the period 2008-2014, we show that larger-scale features (warm and cold conveyer belts) are most commonly associated with the top 1% of UK gusts but smaller-scale features generate the most extreme winds. The cold conveyor belt is far more destructive when joining the momentum of the ETC, rather than earlier in its trajectory, ahead of the approaching warm front. Sting jets and convective lines account for two thirds of severe surface gusts in the UK.

Throughout the world fire regimes are determined by climate, vegetation, and anthropogenic factors, and they have great spatial and temporal variability. The availability of high‐quality satellite data has revolutionized fire monitoring, allowing for a more consistent and comprehensive evaluation of temporal and spatial patterns. Here we utilize a satellite based “active fire” (AF) product to statistically analyze 2001–2015 variability and trends in Australian fire activity and link this to precipitation and large‐scale atmospheric structures (namely, the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD)) known to have potential for predicting fire activity in different regions. It is found that Australian fire activity is decreasing (during summer (December–February)) or stable, with high temporal and spatial variability. Eastern New South Wales (NSW) has the strongest decreasing trend (to the 1% confidence level), especially during the winter (JJA) season. Other significantly decreasing areas are Victoria/NSW, Tasmania, and South‐east Queensland. These decreasing fire regions are relatively highly populated, so we suggest that the declining trends are due to improved fire management, reducing the size and duration of bush fires. Almost half of all Australian AFs occur during spring (September–November). We show that there is considerable potential throughout Australia for a skillful forecast for future season fire activity based on current and previous precipitation activity, ENSO phase, and to a lesser degree, the IOD phase. This is highly variable, depending on location, e.g., the IOD phase is for more indicative of fire activity in southwest Western Australia than for Queensland.

Regular diurnal and weekly cycles (WCs) in temperature provide valuable insights into the consequences of anthropogenic activity on the urban environment. Different locations experience a range of identified WCs and have very different structures. Two important sources of urban heat are those associated with the effect of large urban structures on the radiation budget and energy storage and those from the heat generated as a consequence of anthropogenic activity. The former forcing will remain relatively constant, but a WC will appear in the latter. WCs for specific times of day and the urban heat island (UHI) have not been analysed heretofore. We use three-hourly surface (2 m) temperature data to analyse the WCs of seven major Australian cities at different times of day and to determine to what extent one of our major city’s (Melbourne) UHI exhibits a WC. We show that the WC of temperature in major cities differs according to the time of day and that the UHI intensity of Melbourne is affected on a WC. This provides crucial information that can contribute toward the push for healthier urban environments in the face of a more extreme climate.

One approach to quantifying anthropogenic influences on the environment and the consequences of those is to examine weekly cycles (WCs). No long-term natural process occurs on a WC so any such signal can be considered anthropogenic. There is much ongoing scientific debate as to whether regional-scale WCs exist above the statistical noise level, with most significant studies claiming that anthropogenic aerosols and their interaction with solar radiation and clouds (direct/indirect effect) is the controlling factor. A major source of anthropogenic aerosol, underrepresented in the literature, is active fire (AF) from anthropogenic burning for land clearance/management. WCs in AF have not been analyzed heretofore, and these can provide a mechanism for observed regional-scale WCs in several meteorological variables. We show that WCs in AFs are highly pronounced for many parts of the world, strongly influenced by the working week and particularly the day(s) of rest, associated with religious practices.

ABSTRACTDeep moist convection (DMC) requires three ingredients: instability, moisture and lift. One measure that incorporates two of these, instability and moisture, is convective available potential energy (CAPE). A 10‐year climatology of CAPE over Great Britain is presented covering the period 1 June 2002–31 May 2012, based on a 9‐km grid spacing implementation of the Weather Research and Forecasting (WRF) model, with two‐way interactive nesting. Appropriate tests are carried out to verify model reliability by comparing simulated and observed CAPE. CAPE is found to be highly variable both spatially and temporally, the highest values being produced during Spanish plume events. A strong relationship is confirmed between surface temperature and CAPE magnitude, the highest CAPE across Great Britain during this period locally exceeding 3000 J kg−1. In an average year, 15 days produce CAPE in excess of 500 J kg−1 somewhere in Great Britain, 4 days > 1000 J kg−1 and 1 day > 1500 J kg−1. Three main CAPE seasons are identified: ‘land dominated CAPE’ between April and September, ‘sea dominated CAPE’ between September and January and ‘low CAPE’ from January to April. The southern North Sea witnesses significant CAPE all year round because of a combination of favourable synoptic situations, including warm air plumes in spring/summer and cold air incursions over warmer seas in winter. CAPE is not a direct predictor of thunderstorm incidence, due in part to the confounding effect of convective inhibition (CIN). However, at the annual scale, when comparing against an existing days of thunder climatology, we observe a close correspondence with >500 J kg−1 CAPE frequency.

The climate of the northeast Atlantic region comprises substantial decadal variability in storminess. It also exhibits strong inter-and intra-annual variability in extreme high and low wind speed episodes. Here the authors quantify and discuss causes of the variability seen in the U.K. wind climate over the recent period 1980-2010. Variations in U.K. hourly mean (HM) wind speeds, in daily maximum gust speeds and in associated wind direction measurements, made at standard 10-m height and recorded across a network of 40 stations, are considered. The Weibull distribution is shown to generally provide a good fit to the hourly wind data, albeit with the shape parameter k spatially varying from 1.4 to 2.1, highlighting that the commonly assumed k = 2 Rayleigh distribution is not universal. It is found that the 10th and 50th percentile HM wind speeds have declined significantly over this specific period, while still incorporating a peak in the early 1990s. The authors' analyses place the particularly "low wind" year of 2010 into longer-term context and their findings are compared with other recent international studies. Wind variability is also quantified and discussed in terms of variations in the exceedance of key wind speed thresholds of relevance to the insurance and wind energy industries. Associated interannual variability in energy density and potential wind power output of the order of +/- 20% around the mean is revealed. While 40% of network average winds are in the southwest quadrant, 51% of energy in the wind is associated with this sector. The findings are discussed in the context of current existing challenges to improve predictability in the Euro-Atlantic sector over all time scales.

The UK has one of the most variable wind climates; NW Europe as a whole is a challenging region for forecast- and climate-modelling alike. In Europe, strong winds within extra-tropical cyclones (ETCs) remain on average the most economically significant weather peril when averaged over multiple years, so an understanding how ETCs cause extreme surface winds and how these extremes vary over time is crucial. An assessment of the 1980-2010 UK wind regime is presented based on a unique 40-station network of 10m hourly mean windspeed and daily maximum gustspeed (DMGS) surface station measurements. The regime is assessed, in the context of longer- and larger-scale wind variability, in terms of temporal trends, seasonality, spatial variation, distribution and extremes. Annual mean windspeed ranged from 4.4 to 5.4 ms-1 (a 22% difference) with 2010 recording the lowest annual network mean windspeed over the period, attracting the attention of the insurance and wind energy sectors, both highly exposed to windspeed variations. A short subjective climatology (2008-2010) is developed of the ETCs and their sub-storm features which are associated with the strongest DMGSs. The little studied UK Quasi-linear convective systems (QLCSs) and pseudo-QLCSs are found to account for 22% of the top 1% of DMGSs, with the better known Sting Jet accounting for at most 5%. This same climatology of 2008-10 ETCs then forms the basis of performance assessments of global forecast ensemble systems. At T+48, an ensemble consisting of just the ECMWF and Canadian EPS members (total-70) is found to capture the same set of extreme events as an ensemble consisting of nine global centres (157-239) highlighting the value of using model physics perturbations at this range. A prominent ETC, Emma, then forms the basis of a high-resolution model sensitivity analysis using the Weather Research and Forecasting model. Surface wind simulations display greater sensitivity to different cloud microphysics schemes and to horizontal resolution than to vertical resolution, the former highlighting the importance of diabatic processes within extreme European ETCs.

11 12 The climate of the north-east Atlantic region comprises substantial decadal variability in 13 storminess. It also exhibits strong interand intra-annual variability in extreme high and 14 low windspeed episodes. Here we quantify and discuss causes of the variability seen in 15 the UK wind climate over the recent period 1980-2010. We consider variations in UK 16 hourly windspeeds, in daily maximum gust speeds and in associated wind direction 17 measurements, made at standard 10m height, recorded across a network of 40 stations. 18 The Weibull distribution is shown to generally provide a good fit to the hourly wind data, 19 albeit with shape parameter, k, spatially varying from 1.4-2.1, highlighting that the 20 commonly assumed k=2 Rayleigh distribution is not universal. We find that the 10 th and 21 50 th percentile HM windspeeds have declined significantly over this specific period, 22 whilst still incorporating a peak in the early 1990s. Our analyses place the particularly 23 „low wind‟ year of 2010 into longer term context and our findings are compared with 24 other recent international studies. Wind variability is also quantified and discussed in 25 terms of variations in the exceedence of key windspeed thresholds of relevance to the 26 insurance and wind energy industries. Associated inter-annual variability in energy 27 density and potential wind power output of the order of ±20% around the mean is 28 revealed. While 40% of network average winds are in the SW quadrant, 51% of energy in 29 the wind is associated with this sector. Our findings are discussed in the context of 30 current existing challenges to improve predictability in the Euro-Atlantic sector over all 31 timescales. 32