Mental preparation for climate adaptation: The role of cognition and culture in enhancing adaptive capacity of water management in Kiribati

In many Least Developed Countries (LDCs) and Small Island Developing States (SIDS), such as in Kiribati, formal national adaptation programmes are currently being operationalised or are in the pipeline. A key focus is on motivating householders to adapt in anticipation of climate change through pilot community projects. In this paper, we argue that the water sector must pay equal attention to how communities cognitively perceive the process of adaptation if interventions are to be effective. Adopting a cognitive model to gain such insights we conclude that individual's belief in their own abilities to manage water stress play a crucial role in driving intentions to adapt and therefore greater attention needs to be placed on understanding the underling drivers shaping such beliefs.     

Impact of a Saturation-Dependent Dissipation Source Function on Operational Hindcasts of Wind-Waves in the Australian Region

The impact of a modified parametric form of the dissipation source function S ds on the skill of an operational spectral wind-wave model is investigated. Numerical experiments are made with a version of the WAM model presently used operationally by the Australian Bureau of Meteorology to produce sea-state forecasts within the Australian region. Performances of wave hindcasts obtained using several alternative forms of this newly proposed dissipation source function are compared to those produced with forms of S ds commonly used operationally. A new ad hoc technique to compare modelled and observed wave spectra is introduced to assess the quality of calculated one-dimensional frequency spectra.

Our results indicate that wave model performance in terms of integral spectral parameters, such as the significant wave height H s , may benefit from improved parameterisations of the dissipation source term S ds . On the other hand, we also found that model performance was relatively poor in terms of predictions of the one-dimensional frequency spectrum, regardless of the chosen form of S ds . These results suggest that further refinements of the dissipation source term are strongly dependent on improved parametrisations of the nonlinear interactions source term S nl .     

Validation of the Canadian land surface scheme (class) for a subarctic open woodland

Abstract

This study reports on testing of the peatland version of the Canadian Land Surface Scheme (CLASS) for simulating the energy balance of subarctic open woodland terrain. Model results are compared against several years of measured data from a site near Churchill, Manitoba. In contrast to most forest environments, the floor of the open forest plays a large role in total ecosystem energy exchange. This behaviour presents a significant challenge for land surface models like CLASS and their simplified treatment of vegetation canopies.

Simulations of summer energy balance for seven years encompassing a wide range of meteorological conditions produced consistent results. Root mean square errors for sensible and latent heat fluxes fell between 11 and 28 W m^?2. CLASS consistently underestimated slightly the daily latent heat flux and overestimated the sensible heat flux, average mean bias errors being ‐7.6 and 9.1 W m^?2, respectively. The soil heat flux was less well represented. In general, CLASS was able to capture the diurnal and seasonal behaviour of the measured fluxes under a range of conditions with reasonable accuracy.

In a full year simulation, CLASS reproduced the annual variations in energy balance with some discrepancies associated with snow accumulation and ablation periods. The model performance was sensitive to both snow density and specification of the surface cover. Recommendations for improving the model for subarctic woodlands and terrain types with similar features are discussed.     

Current state and trends in Canadian Arctic marine ecosystems: I. Primary production

During the International Polar Year (IPY), large international research programs provided a unique opportunity for assessing the current state and trends in major components of arctic marine ecosystems at an exceptionally wide spatio-temporal scale: sampling covered most regions of the Canadian Arctic (IPY-Canada??s Three Oceans project), and the coastal and offshore areas of the southeastern Beaufort Sea were monitored over almost a full year (IPY-Circumpolar Flaw Lead project). The general goal of these projects was to improve our understanding of how the response of arctic marine ecosystems to climate warming will alter the productivity and structure of the food web and the ecosystem services it provides to Northerners. The present paper summarizes and discusses six key findings related to primary production (PP), which determines the amount of food available to consumers. (1) Offshore, the warming and freshening of the surface layer is leading to the displacement of large nanophytoplankton species by small picophytoplankton cells, with potentially profound bottom-up effects within the marine food web. (2) In coastal areas, PP increases as favourable winds and the deeper seaward retreat of ice promote upwelling. (3) Multiple upwelling events repeatedly provide food to herbivores throughout the growth season. (4) A substantial amount of pelagic PP occurs under thinning ice and cannot be detected by orbiting sensors. (5) Early PP in the spring does not imply a trophic mismatch with key herbivores. (6) The epipelagic ecosystem is very efficient at retaining carbon in surface waters and preventing its sedimentation to the benthos. While enhanced PP could result in increased fish and marine mammal harvests for Northerners, it will most likely be insufficient for sustainable large-scale commercial fisheries in the Canadian Arctic.     

Geochemical study of submicron particulate matter(PM1)in a metropolitan area

Air pollution has become a major problem in urban areas due to increasing industrialization and urbanization.In this study ambient concentrations of PM1 and metal concentrations as well as source contributions were identified and quantified by using Positive Matrix Factorization(PMF)in receptor modeling in the Metropolitan Area of Porto Alegre,Brazil.The PM1 samples were collected on PTFE filters from December 2012 to December 2014 in two sampling sites.Major ion and trace element concentrations were assessed.The average concentrations were 12.8 and 15.2μg/m³ for Canoas and Sapucaia do Sul sites,respectively.Major ion contributions of PM1 were secondary pollutants such as sulfate and nitrate.Trace elements,especially Cu,Pb,Zn,Cd,and Ni also made important contributions which are directly associated with anthropogenic contributions.Our results show significantly higher levels in winter than in summer.Most of the PM1 and the analyzed PM species and elements originated from anthropogenic sources,especially road traffic,combustion processes and industrial activities,which are grouped in 7 major contributing sources.A back-trajectory analysis showed that the long-range transport of pollutants was not relevant in relation to the contribution to PM1 and metal concentrations.This work highlights the importance of urban planning to reduce human health exposure to traffic and industrial emissions,combined with awareness-raising actions for citizens concerning the impact of indoor sources.     

Towards sustainable groundwater use: setting long-term goals, backcasting, and managing adaptively

The sustainability of crucial earth resources, such as groundwater, is a critical issue. We consider groundwater sustainability a value-driven process of intra- and intergenerational equity that balances the environment, society, and economy. Synthesizing hydrogeological science and current sustainability concepts, we emphasize three sustainability approaches: setting multigenerational sustainability goals, backcasting, and managing adaptively. As most aquifer problems are long-term problems, we propose that multigenerational goals (50 to 100 years) for water quantity and quality that acknowledge the connections between groundwater, surface water, and ecosystems be set for many aquifers. The goals should be set by a watershed- or aquifer-based community in an inclusive and participatory manner. Policies for shorter time horizons should be developed by backcasting, and measures implemented through adaptive management to achieve the long-term goals. Two case histories illustrate the importance and complexity of a multigenerational perspective and adaptive management. These approaches could transform aquifer depletion and contamination to more sustainable groundwater use, providing groundwater for current and future generations while protecting ecological integrity and resilience.     

Accuracy of a pre-trained sentiment analysis (SA) classification model on tweets related to emergency response and early recovery assessment: the case of 2019 Albanian earthquake

Traditionally, earthquake impact assessments have been made via fieldwork by non-governmental organisations (NGO's) sponsored data collection; however, this approach is time-consuming, expensive and often limited. Recently, social media (SM) has become a valuable tool for quickly collecting large amounts of first-hand data after a disaster and shows great potential for decision-making. Nevertheless, extracting meaningful information from SM is an ongoing area of research. This paper tests the accuracy of the pre-trained sentiment analysis (SA) model developed by the no-code machine learning platform MonkeyLearn using the text data related to the emergency response and early recovery phase of the three major earthquakes that struck Albania on the 26th November 2019. These events caused 51 deaths, 3000 injuries and extensive damage. We obtained 695 tweets with the hashtags: #Albania #AlbanianEarthquake, and #albanianearthquake from the 26th November 2019 to the 3rd February 2020. We used these data to test the accuracy of the pre-trained SA classification model developed by MonkeyLearn to identify polarity in text data. This test explores the feasibility to automate the classification process to extract meaningful information from text data from SM in real-time in the future. We tested the no-code machine learning platform's performance using a confusion matrix. We obtained an overall accuracy (ACC) of 63% and a misclassification rate of 37%. We conclude that the ACC of the unsupervised classification is sufficient for a preliminary assessment, but further research is needed to determine if the accuracy is improved by customising the training model of the machine learning platform.

     

Late Pleistocene–Holocene environmental and climatic history of a freshwater paramo ecosystem in the northern Andes

This study presents the first multi-proxy palaeoenvironmental and palaeoclimatic history for northern South America based on the palaeolimnological reconstruction of a pond located in a dry paramo at 3570 masl. During the Last Glacial Maximum (LGM), the study area was under glacial conditions, then during global events Heinrich Stadial 1 (HS1), Bølling–Allerød (BA), and the Younger Dryas (YD), the pond expanded, accumulation rates and proxies for erosion reached the highest values, indicative of humid conditions, with maxima in humidity during the BA and YD. Dry conditions and pond desiccation occurred in the Greenlandian–Northgrippian and by 6010 cal a bp the area was transformed into the mire of today. Comparisons with records from other sites in South America indicate that changes in humidity are most likely controlled by the Intertropical Convergence Zone, mainly during the glacial and postglacial, and by changes in the Pacific Ocean, more pronounced after the YD.