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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.

The last few years have seen an explosion of interest in extreme event attribution, the science of estimating the influence of human activities or other factors on the probability and other characteristics of an observed extreme weather or climate event. This is driven by public interest, but also has practical applications in decision-making after the event and for raising awareness of current and future climate change impacts. The World Weather Attribution (WWA) collaboration has over the last 5 years developed a methodology to answer these questions in a scientifically rigorous way in the immediate wake of the event when the information is most in demand. This methodology has been developed in the practice of investigating the role of climate change in two dozen extreme events world-wide. In this paper, we highlight the lessons learned through this experience. The methodology itself is documented in a more extensive companion paper. It covers all steps in the attribution process: the event choice and definition, collecting and assessing observations and estimating probability and trends from these, climate model evaluation, estimating modelled hazard trends and their significance, synthesis of the attribution of the hazard, assessment of trends in vulnerability and exposure, and communication. Here, we discuss how each of these steps entails choices that may affect the results, the common problems that can occur and how robust conclusions can (or cannot) be derived from the analysis. Some of these developments also apply to other attribution methodologies and indeed to other problems in climate science.

During August 25-30, 2017, Hurricane Harvey stalled over Texas and caused extreme precipitation, particularly over Houston and the surrounding area on August 26-28. This resulted in extensive flooding with over 80 fatalities and large economic costs. It was an extremely rare event: the return period of the highest observed three-day precipitation amount, 1043.4 mm 3dy−1 at Baytown, is more than 9000 years (97.5% one-sided confidence interval) and return periods exceeded 1000 yr (750 mm 3dy−1) over a large area in the current climate. Observations since 1880 over the region show a clear positive trend in the intensity of extreme precipitation of between 12% and 22%, roughly two times the increase of the moisture holding capacity of the atmosphere expected for 1 °C warming according to the Clausius-Clapeyron (CC) relation. This would indicate that the moisture flux was increased by both the moisture content and stronger winds or updrafts driven by the heat of condensation of the moisture. We also analysed extreme rainfall in the Houston area in three ensembles of 25 km resolution models. The first also shows 2 × CC scaling, the second 1 × CC scaling and the third did not have a realistic representation of extreme rainfall on the Gulf Coast. Extrapolating these results to the 2017 event, we conclude that global warming made the precipitation about 15% (8%-19%) more intense, or equivalently made such an event three (1.5-5) times more likely. This analysis makes clear that extreme rainfall events along the Gulf Coast are on the rise. And while fortifying Houston to fully withstand the impact of an event as extreme as Hurricane Harvey may not be economically feasible, it is critical that information regarding the increasing risk of extreme rainfall events in general should be part of the discussion about future improvements to Houston's flood protection system.

In July 2021 extreme rainfall across Western Europe caused severe flooding and substantial impacts, including over 200 fatalities and extensive infrastructure damage within Germany and the Benelux countries. After the event, a hydrological assessment and a probabilistic event attribution analysis of rainfall data were initiated and complemented by discussing the vulnerability and exposure context. The global mean surface temperature (GMST) served as a covariate in a generalised extreme value distribution fitted to observational and model data, exploiting the dependence on GMST to estimate how anthropogenic climate change affects the likelihood and severity of extreme events. Rainfall accumulations in Ahr/Erft and the Belgian Meuse catchment vastly exceeded previous observed records. In regions of that limited size the robust estimation of return values and the detection and attribution of rainfall trends are challenging. However, for the larger Western European region it was found that, under current climate conditions, on average one rainfall event of this magnitude can be expected every 400 years at any given location. Consequently, within the entire region, events of similar magnitude are expected to occur more frequently than once in 400 years. Anthropogenic climate change has already increased the intensity of the maximum 1-day rainfall event in the summer season by 3–19 %. The likelihood of such an event to occur today compared to a 1.2 ∘C cooler climate has increased by a factor of 1.2–9. Models indicate that intensity and frequency of such events will further increase with future global warming. While attribution of small-scale events remains challenging, this study shows that there is a robust increase in the likelihood and severity of rainfall events such as the ones causing extreme impacts in July 2021 when considering a larger region.

Extreme weather and climate events associated with El Niño and La Niña cause massive societal impacts. Therefore, observations and forecasts are used around the world to prepare for such events. However, global warming has caused warm El Niño events to seem bigger than they are, while cold La Niña events seem smaller, in the commonly used Niño3.4 index (sea surface temperature (SST) anomalies over 5 ∘ S–5 ∘ N, 120–170 ∘ W). We propose a simple and elegant adjustment, defining a relative Niño3.4 index as the difference between the original SST anomaly and the anomaly over all tropical oceans (20 ∘ S–20 ∘ N). This relative index describes the onset of convection better, is not contaminated by global warming and can be monitored and forecast in real-time. We show that the relative Niño3.4 index is better in line with effects on rainfall and would be more useful for preparedness for El Niño and La Niña in a changing climate and for El Niño—Southern Oscillation research.

A stationary low pressure system and elevated levels of precipitable water provided a nearly continuous source of precipitation over Louisiana, United States (US), starting around 10 August 2016. Precipitation was heaviest in the region broadly encompassing the city of Baton Rouge, with a 3-day maximum found at a station in Livingston, LA (east of Baton Rouge), from 12 to 14 August 2016 (648.3 mm, 25.5 inches). The intense precipitation was followed by inland flash flooding and river flooding and in subsequent days produced additional backwater flooding. On 16 August, Louisiana officials reported that 30 000 people had been rescued, nearly 10 600 people had slept in shelters on the night of 14 August and at least 60 600 homes had been impacted to varying degrees. As of 17 August, the floods were reported to have killed at least 13 people. As the disaster was unfolding, the Red Cross called the flooding the worst natural disaster in the US since Super Storm Sandy made landfall in New Jersey on 24 October 2012. Before the floodwaters had receded, the media began questioning whether this extreme event was caused by anthropogenic climate change. To provide the necessary analysis to understand the potential role of anthropogenic climate change, a rapid attribution analysis was launched in real time using the best readily available observational data and high-resolution global climate model simulations. The objective of this study is to show the possibility of performing rapid attribution studies when both observational and model data and analysis methods are readily available upon the start. It is the authors' aspiration that the results be used to guide further studies of the devastating precipitation and flooding event. Here, we present a first estimate of how anthropogenic climate change has affected the likelihood of a comparable extreme precipitation event in the central US Gulf Coast. While the flooding event of interest triggering this study occurred in south Louisiana, for the purposes of our analysis, we have defined an extreme precipitation event by taking the spatial maximum of annual 3-day inland maximum precipitation over the region of 29–31° N, 85–95° W, which we refer to as the central US Gulf Coast. Using observational data, we find that the observed local return time of the 12–14 August precipitation event in 2016 is about 550 years (95 % confidence interval (CI): 450–1450). The probability for an event like this to happen anywhere in the region is presently 1 in 30 years (CI 11–110). We estimate that these probabilities and the intensity of extreme precipitation events of this return time have increased since 1900. A central US Gulf Coast extreme precipitation event has effectively become more likely in 2016 than it was in 1900. The global climate models tell a similar story; in the most accurate analyses, the regional probability of 3-day extreme precipitation increases by more than a factor of 1.4 due to anthropogenic climate change. The magnitude of the shift in probabilities is greater in the 25 km (higher-resolution) climate model than in the 50 km model. The evidence for a relation to El Niño half a year earlier is equivocal, with some analyses showing a positive connection and others none.

In the period 2015-2017, the Western Cape region has suffered from three consecutive years of below average rainfall-leading to a prolonged drought and acute water shortages, most prominently in the city of Cape Town. After testing that the precipitation deficit is the primary driver behind the reduced surface water availability, we undertake a multi-method attribution analysis for the meteorological drought, defined in terms of a deficit in the 3 years running mean precipitation averaged over the Western Cape area. The exact estimate of the return time of the event is sensitive to the number of stations whose data is incorporated in the analysis but the rarity of the event is unquestionable, with a return time of more than a hundred years. Synthesising the results from five different large model ensembles as well as observed data gives a significant increase by a factor of three (95% confidence interval 1.5-6) of such a drought to occur because of anthropogenic climate change. All the model results further suggest that this trend will continue with future global warming. These results are in line with physical understanding of the effect of climate change at these latitudes and highlights that measures to improve Cape Town's resilience to future droughts are an adaptation priority.

The agricultural sector of any country plays a pivotal role in its economy. Irrigation and the provision of appropriate nutrient levels in soil are essential for optimizing plant growth and enhancing crop productivity. To support the increasing need for food due to the growing population worldwide, synthetic fertilizers have been widely used in the agricultural sector. These fertilizers could readily dissolve in the irrigation water or soil moisture, causing excessive release of the nutrients that plants cannot uptake from the root zone. The excess nutrients in the soil further harm the environment via surface run‐off, leaching, and volatilization. Thus, materials with high water absorption and retention capacity, and precise control over the prolonged fertilizer release offer a potential solution to address these issues. To meet these requirements, the development of slow‐release fertilizer hydrogels (SRFHs) represents a promising approach. SRFHs serve as natural agrochemicals to enhance crop growth and yield through controlled and self‐sustained delivery of water and nutrients. This review provides a comprehensive study on the recent advancements in SRFHs, including their preparation methods, properties, slow‐release behavior, and applications in smart agriculture. The response of soil microbial diversity to slow‐release fertilizers is briefly discussed, and the future potential of SRFHs is highlighted herein. Superabsorbent hydrogels can be used for slow‐release of N‐, P‐, K‐fertilizers into the soil, enhancing soil moisture and plant growth. These hydrogels thus help in improving crop productivity through sustained nutrient release, aligning with smart agriculture. The present Review highlights recent advancements in slow‐release fertilizer hydrogels, including their preparation methods, properties, slow‐release behavior, impact on soil microbial diversity and soil health, and applications in smart agriculture.

Over the last few years, methods have been developed to answer questions on the effect of global warming on recent extreme events. Many “event attribution” studies have now been performed, a sizeable fraction even within a few weeks of the event, to increase the usefulness of the results. In doing these analyses, it has become apparent that the attribution itself is only one step of an extended process that leads from the observation of an extreme event to a successfully communicated attribution statement. In this paper we detail the protocol that was developed by the World Weather Attribution group over the course of the last 4 years and about two dozen rapid and slow attribution studies covering warm, cold, wet, dry, and stormy extremes. It starts from the choice of which events to analyse and proceeds with the event definition, observational analysis, model evaluation, multi-model multi-method attribution, hazard synthesis, vulnerability and exposure analysis and ends with the communication procedures. This article documents this protocol. It is hoped that our protocol will be useful in designing future event attribution studies and as a starting point of a protocol for an operational attribution service.

Chitosan is a deacetylated chitin which is found naturally, particularly in fungal cell walls and crustacean shells. Chitosan is biocompatible and fully biodegradable and is extensively analyzed for antimicrobial property. Chitosan has also been explored as a drug carrier due to its biocompatible properties. Some studies have demonstrated that use of chitosan to coat nanoparticles made of other materials would help in reducing their impact on the body and also increase their bioavailability. The molecular weight of chitosan and the degree of deacetylation can be modified to derive different physicomechanical properties. Chitosan exhibits potent antifungal activity against several fungal strains including Rhizopus oryzae, Aspergillus niger and Alternaria alternata. Various factors such as molecular weight, dose and functional groups attached to the chitosan have been shown to modulate the antifungal activity of chitosan. Chitosan is known to exert antifungal activity without the need for any chemical modification, however, new derivatives of chitosan can be created to target specific microbial pathogens. The development of novel and ecofriendly methods of chitosan nanoparticles (CSNPs) preparation is in progress for developing chitosan as an efficient antimicrobial agent and in drug delivery system. This review is to focus on recent application of CSNPs as antibacterial and antifungal agent and to highlight the effectiveness of employing chitosan with silver and other metal nanoparticles.