Extreme dry and wet spells face changes in their duration and timing

Dry spells are sequences of days without precipitation. They can have negative implications for societies, including water security and agriculture. For example, changes in their duration and within-year timing can pose a threat to food production and wildfire risk. Conversely, wet spells are sequences of days with precipitation above a certain threshold, and changes in their duration and within-year timing can impact agriculture, flooding or the prevalence of water-related vector-borne diseases. Here we assess changes in the duration and within-year timing of extreme dry and wet spells over 60 years (1958-2017) using a consistent global land surface precipitation dataset of 5093 rain gauge locations. The dataset allowed for detailed spatial analyses of the United States, Europe and Australia. While many locations exhibit statistically significant changes in the duration of extreme dry and wet spells, the changes in the within-year timing are less often significant. Our results show consistencies with observations and projections from state-of-the-art climate and water resources research. In addition, we provide new insights regarding trends in the timing of extreme dry and wet spells, an aspect being equally important for possible future implications of extremes in a changing climate, which has not yet received the same level of attention and is characterized by larger uncertainty

Effect Of Different Hydrological Model Structures On The Assimilation Of Distributed Uncertain Observations

The reliable evaluation of the flood forecasting is a crucial problem for assessing flood risk and consequent damages. Different hydrological models (distributed, semi-distributed or lumped) have been proposed in order to deal with this issue. The choice of the proper model structure has been investigated by many authors and it is one of the main sources of uncertainty for a correct evaluation of the outflow hydrograph. In addition, the recent increasing of data availability makes possible to update hydrological models as response of real-time observations. For these reasons, the aim of this work it is to evaluate the effect of different structure of a semi-distributed hydrological model in the assimilation of distributed uncertain discharge observations. The study was applied to the Bacchiglione catchment, located in Italy. The first methodological step was to divide the basin in different sub-basins according to topographic characteristics. Secondly, two different structures of the semi-distributed hydrological model were implemented in order to estimate the outflow hydrograph. Then, synthetic observations of uncertain value of discharge were generated, as a function of the observed and simulated value of flow at the basin outlet, and assimilated in the semi-distributed models using a Kalman Filter. Finally, different spatial patterns of sensors location were assumed to update the model state as response of the uncertain discharge observations. The results of this work pointed out that, overall, the assimilation of uncertain observations can improve the hydrologic model performance. In particular, it was found that the model structure is an important factor, of difficult characterization, since can induce different forecasts in terms of outflow discharge. This study is partly supported by the FP7 EU Project WeSenseIt

Assimilation Of Heterogeneous Uncertain Data, Having Different Observational Errors, In Hydrological Models

Accurate real-time forecasting of river water level is an important issue that has to be addressed in order to prevent and mitigate water-related risk. To this end, data assimilation methods have been used to improve the forecasts ability of water model merging observations coming from stations and model simulations. As a consequence of the increasing availability of dynamic and cheap sensors, having variable life-span, space and temporal coverage, the citizens are becoming an active part in information capturing, evaluation and communication. On the other hand, it is difficult to assess the uncertain related to the observation coming from such sensors. The main objective of this work is to evaluate the influence of the observational error in the proposed assimilation methodologies used to update the hydrological model as response of dynamic observations of water discharge. We tested the developed approaches on a test study area - the Brue catchment, located in the South West of England, UK. Two different filtering approaches, Ensemble Kalman filter and Particle filter, were applied to the semi-distributed hydrological model. Discharge observations were synthetically generated as a function of the observed and simulated value of flow at the basin outlet. Different types of observational error were introduced assuming diverse sets of probability distributions, first and second order moments. The results of this work show how the assimilation of dynamic observations, in time and space, can improve the hydrologic model performance with a better forecast of flood events. It was found that the choice of the appropriate observational error, of difficult characterization, and type of filtering approach affects the model accuracy. This study is partly supported by the FP7 EU Project WeSenseIt

Speculative Political Ecologies: (re)imagining urban futures of climate extremes

What role can a speculative political ecology play in (re)imaging urban futures of climate extremes? In recent years, narratives of dystopian futures of climate extremes have proliferated in geosciences, and across the media and creative arts. These anxiety-fueled narratives often generate a sense of resignation and unavoidability, which contributes to foreclosing the possibility of radically different political projects. In this article, we argue that these narratives conceal the coproduction of nature and society and treat nature as the problem, thereby locking futures into dystopic configurations. Political ecology scholarship can contribute to generate a politics of possibility by reconceptualizing the relations that constitute urban futures under climate extremes as socionatural. This, we argue, calls for a more experimental political ecology and new forms of theorizing. To this aim, we develop a speculative political ecological approach grounded on a numerical model that examines the potential of transformative change in the aftermath of extreme flood events in a capitalist city. Analytically, this opens a unique possibility of exploring urban futures beyond current trajectories, and how these alternative futures might transform vulnerability and inequality across urban spaces. From a policy perspective, we lay the foundations for a new generation of models that apprehend the role of power and agency in shaping uneven urban futures of climate extremes

Linking bacterial and eukaryotic microbiota to litter chemistry: Combining next generation sequencing with 13 C CPMAS NMR spectroscopy

Microbial succession over decomposing litter is controlled by biotic interactions, dispersal limitation, grazing pressure, and substrate chemical changes. Recent evidence suggests that the changes in litter chemistry and microbiome during decomposition are interdependent. However, most previous studies separately addressed the microbial successional dynamics or the molecular changes of decomposing litter. Here, we combined litter chemical characterization by 13 C NMR spectroscopy with next generation sequencing to compare leaf litter chemistry and microbiome dynamics using 30 litter types, either fresh or decomposed for 30 and 180 days. We observed a decrease of cellulose and C/N ratio during decomposition, while lignin content and lignin/N ratio showed the opposite pattern. 13 C NMR revealed significant chemical changes as microbial decomposition was proceeding, with a decrease in O-alkyl C and an increase in alkyl C and methoxyl C relative abundances. Overall, bacterial and eukaryotic taxonomical richness increased with litter age. Among Bacteria, Proteobacteria dominated all undecomposed litters but this group was progressively replaced by members of Actinobacteria, Bacteroidetes, and Firmicutes. Nitrogen-fixing genera such as Beijerinckia and Rhizobium occurred both in undecomposed as well as in aged litters. Among Eukarya, fungi belonging to the Ascomycota phylum were dominant in undecomposed litter with the typical phyllospheric genus Aureobasidium. In aged litters, phyllospheric species were replaced by zygomycetes and other ascomycetous and basidiomycetous fungi. Our analysis of decomposing litter highlighted an unprecedented, widespread occurrence of protists belonging to the Amebozoa and Cercozoa. Correlation network analysis showed that microbial communities are non-randomly structured, showing strikingly distinct composition in relation to litter chemistry. Our data demonstrate that the importance of litter chemistry in shaping microbial community structure increased during the decomposition process, being of little importance for freshly fallen leaves

Concurrent wet and dry hydrological extremes at the global scale

Abstract. Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions characterising the former is, therefore, of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global co-occurrence. We define these using the monthly self-calibrated Palmer Drought Severity Index based on the Penman-Monteith model (sc_PDSI_pm) covering the period 1950–2014, at 2.5° horizontal resolution. We find that the land areas affected by extreme wet, dry and wet-dry events (i.e. geographically remote, yet temporally co-occurring wet or dry extremes) all display increasing trends with time, of which changes in dry and wet-dry episodes are significant (p-value 2, with documented high-impact flooding and drought episodes spanning diverse regions. To further elucidate the interplay of wet and dry extremes at a grid-point scale, we introduce two new metrics: the wet-dry (WD) ratio and the extreme transition (ET) time interval. The WD-ratio measures the relative occurrence of extreme wet or dry events, whereas ET quantifies the average separation time of hydrological extremes with opposite signs. The WD-ratio shows that the incidence of extreme wet episodes dominates over dry episodes in the USA, northern and southern south America, northern Europe, north Africa, western China and most of Australia. Conversely, extreme dry events are more prominent in most of the remaining regions. The median ET for wet to dry is ~ 27 months, while the dry to wet median ET is 21 months. We also evaluate correlations between wet-dry hydrological extremes and leading modes of large-scale variability, namely the: El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and American Multi-decadal Oscillation (AMO). We find that ENSO and PDO have a similar influence globally, with the former significantly impacting (p-value <<0.01) a larger area compared to the latter, whereas the AMO shows an almost inverse pattern, and significantly impacts a larger overall area. Our analysis brings new insights on hydrological multi-hazards and are of direct relevance to governments and organisations with globally distributed interests, such as (re)insurance companies. Specifically, the multi-hazard maps may be used to evaluate worst-case disaster scenarios considering the potential co-occurrence of wet and dry hydrological extremes

Protocol for evaluating quality and safety for the public through home care nursing in Italy: a multicentre cross-sectional descriptive observational study (AIDOMUS-IT)

introduction: considering the increasing complexity of care and workload for home care nurses due to the ageing of the population, it is crucial to describe the work environment and the community care setting. the aim of this study protocol is to map the characteristics and identify gaps of home care in the community to design future interventions aimed at ensuring quality and safety. methods and analysis: this is a national cross-sectional descriptive observational study using the survey method. nurses from all participating community care centres will be recruited through convenience sampling by the coordinators of each centre, who will act as facilitators for this study. all community care recipients and their informal carers during the study period will be invited to complete a survey.to map the characteristics and identify gaps of home care in the community, three sources of data will be collected: (1) organisational characteristics, professional satisfaction, intention to leave and burn-out; (2) experience of care recipients and their informal carers and (3) improper access to the emergency department, readmission to hospital, comorbidities, services offered and users' level of autonomy, and main and secondary diagnoses.considering the total italian nursing population of approximately 450 000 registered nurses, a sample size of 1% of this population, equal to approximately 4600 nurses, was hypothesised.This study started in July 2022 and is planned to end in december 2023.data will be analysed using descriptive and inferential statistics. ethics and dissemination: this study protocol was approved by the liguria regional ethics committee in november 2022. informed consent will be obtained from participants and confidentiality will be ensured. data collected for this study will be kept anonymised in a protected database.the results of the study will be disseminated mainly through conferences, publications and meetings with government representatives