Search Results
Analysing Interlinked Frequency Dynamics of the Urban Acoustic Environment
As sustainable metropolitan regions require more densely built-up areas, a comprehensive understanding of the urban acoustic environment (AE) is needed. However, comprehensive datasets of the urban AE and well-established research methods for the AE are scarce. Datasets of audio recordings tend to be large and require a lot of storage space as well as computationally expensive analyses. Thus, knowledge about the long-term urban AE is limited. In recent years, however, these limitations have been steadily overcome, allowing a more comprehensive analysis of the urban AE. In this respect, the objective of this work is to contribute to a better understanding of the time-frequency domain of the urban AE, analysing automatic audio recordings from nine urban settings over ten months. We compute median power spectra as well as normalised spectrograms for all settings. Additionally, we demonstrate the use of frequency correlation matrices (FCMs) as a novel approach to access large audio datasets. Our results show site-dependent patterns in frequency dynamics. Normalised spectrograms reveal that frequency bins with low power hold relevant information and that the AE changes considerably over a year. We demonstrate that this information can be captured by using FCMs, which also unravel communities of interlinked frequency dynamics for all settings.
Attributing observed permafrost warming in the northern hemisphere to anthropogenic climate change
Permafrost temperatures are increasing globally with the potential of adverse environmental and socio-economic impacts. Nonetheless, the attribution of observed permafrost warming to anthropogenic climate change has relied mostly on qualitative evidence. Here, we compare long permafrost temperature records from 15 boreholes in the northern hemisphere to simulated ground temperatures from Earth system models contributing to CMIP6 using a climate change detection and attribution approach. We show that neither pre-industrial climate variability nor natural drivers of climate change suffice to explain the observed warming in permafrost temperature averaged over all boreholes. However, simulations are consistent with observations if the effects of human emissions on the global climate system are considered. Moreover, our analysis reveals that the effect of anthropogenic climate change on permafrost temperature is detectable at some of the boreholes. Thus, the presented evidence supports the conclusion that anthropogenic climate change is the key driver of northern hemisphere permafrost warming.
Nighttime light data reveal lack of full recovery after hurricanes in Southern US
As the climate warms, many areas of the world are experiencing more frequent and extreme weather events. Hurricanes carry some of the costliest short-term socioeconomic repercussions via economic losses and people displaced. There is, however, little quantitative evidence regarding medium- to long-term effects, nor factors moderating recovery. Here we show that areas affected by hurricanes of category 4 or 5 in the southern US between 2014 and 2020 generally do not demonstrate full recovery in the longer term. Utilizing Visible Infrared Imaging Radiometer Suite nighttime light (NTL) data as a proxy for economic activity and population density, we build a timeline of recovery via NTL radiance levels. We exploit the difference in the eligibility for aid from the Federal Emergency Management Agency (FEMA) to apply a quasi-experimental method to identify changes in NTL radiance attributable to hurricanes. We find that after three years, affected areas demonstrate a reduction in NTL radiance levels of between 2% and 14% compared to the pre-disaster period. Combining these results with machine learning techniques, we are able to investigate those factors that contribute to recovery. We find counties demonstrating smaller reductions in NTL radiance levels in the months following the hurricane are buoyed by the amount of FEMA aid received, but that this aid does not foster a longer-term return to normal radiance levels. Investigating areas receiving FEMA aid at the household and individual level, we find age and employment are more important than other demographic factors in determining hurricane recovery over time. These findings suggest that aid may be more important in motivating short-term recovery for public entities than for individuals but is not sufficient to guarantee complete recovery in the longer term.
Theoretical and paleoclimatic evidence for abrupt transitions in the Earth system
Specific components of the Earth system may abruptly change their state in response to gradual changes in forcing. This possibility has attracted great scientific interest in recent years, and has been recognized as one of the greatest threats associated with anthropogenic climate change. Examples of such components, called tipping elements, include the Atlantic Meridional Overturning Circulation, the polar ice sheets, the Amazon rainforest, as well as the tropical monsoon systems. The mathematical language to describe abrupt climatic transitions is mainly based on the theory of nonlinear dynamical systems and, in particular, on their bifurcations. Applications of this theory to nonautonomous and stochastically forced systems are a very active field of climate research. The empirical evidence that abrupt transitions have indeed occurred in the past stems exclusively from paleoclimate proxy records. In this review, we explain the basic theory needed to describe critical transitions, summarize the proxy evidence for past abrupt climate transitions in different parts of the Earth system, and examine some candidates for future abrupt transitions in response to ongoing anthropogenic forcing. Predicting such transitions remains difficult and is subject to large uncertainties. Substantial improvements in our understanding of the nonlinear mechanisms underlying abrupt transitions of Earth system components are needed. We argue that such an improved understanding requires combining insights from (a) paleoclimatic records; (b) simulations using a hierarchy of models, from conceptual to comprehensive ones; and (c) time series analysis of recent observation-based data that encode the dynamics of the present-day Earth system components that are potentially prone to tipping.
Impacts of climate change on global food trade networks
Countries’ reliance on global food trade networks implies that regionally different climate change impacts on crop yields will be transmitted across borders. This redistribution constitutes a significant challenge for climate adaptation planning and may affect how countries engage in cooperative action. This paper investigates the long-term (2070-2099) potential impacts of climate change on global food trade networks of three key crops: wheat, rice and maize. We propose a simple network model to project how climate change impacts on crop yields may be translated into changes in trade. Combining trade and climate impact data, our analysis proceeds in three steps. First, we use network community detection to analyse how the concentration of global production in present-day trade communities may become disrupted with climate change impacts. Second, we study how countries may change their network position following climate change impacts. Third, we study the total climate-induced change in production plus import within trade communities. Results indicate that the stability of food trade network structures compared to today differs between crops, and that countries’ maize trade is least stable under climate change impacts. Results also project that threats to global food security may depend on production change in a few major global producers, and whether trade communities can balance production and import loss in some vulnerable countries. Overall, our model contributes a baseline analysis of cross-border climate impacts on food trade networks.
Projecting the impact of air pollution on child stunting in India—synergies and trade-offs between climate change mitigation, ambient air quality control, and clean cooking access
Many children in India face the double burden of high exposure to ambient (AAP) and household air pollution, both of which can affect their linear growth. Although climate change mitigation is expected to decrease AAP, climate policies could increase the cost of clean cooking fuels. Here, we develop a static microsimulation model to project the air pollution-related burden of child stunting in India up to 2050 under four scenarios combining climate change mitigation (2 °C target) with national policies for AAP control and subsidised access to clean cooking. We link data from a nationally representative household survey, satellite-based estimates of fine particulate matter (PM2.5), a multi-dimensional demographic projection and PM2.5 and clean cooking access projections from an integrated assessment model. We find that the positive effects on child linear growth from reductions in AAP under the 2 °C Paris Agreement target could be fully offset by the negative effects of climate change mitigation through reduced clean cooking access. Targeted AAP control or subsidised access to clean cooking could shift this trade-off to result in net benefits of 2.8 (95% uncertainty interval [UI]: 1.4, 4.2) or 6.5 (UI: 6.3, 6.9) million cumulative prevented cases of child stunting between 2020–50 compared to business-as-usual. Implementation of integrated climate, air quality, and energy access interventions has a synergistic impact, reducing cumulative number of stunted children by 12.1 (UI: 10.7, 13.7) million compared to business-as-usual, with the largest health benefits experienced by the most disadvantaged children and geographic regions. Findings underscore the importance of complementing climate change mitigation efforts with targeted air quality and energy access policies to concurrently deliver on carbon mitigation, health and air pollution and energy poverty reduction goals in India.
Climate impact emergence and flood peak synchronization projections in the Ganges, Brahmaputra and Meghna basins under CMIP5 and CMIP6 scenarios
The densely populated delta of the three river systems of the Ganges, Brahmaputra and Meghna is highly prone to floods. Potential climate change-related increases in flood intensity are therefore of major societal concern as more than 40 million people live in flood-prone areas in downstream Bangladesh. Here we report on new flood projections using a hydrological model forced by bias-adjusted ensembles of the latest-generation global climate models of CMIP6 (SSP5-8.5/SSP1-2.6) in comparison to CMIP5 (RCP8.5/RCP2.6). Results suggest increases in peak flow magnitude of 36% (16%) on average under SSP5-8.5 (SSP1-2.6), compared to 60% (17%) under RCP8.5 (RCP2.6) by 2070-2099 relative to 1971-2000. Under RCP8.5/SSP5-8.5 (2070-2099), the largest increase in flood risk is projected for the Ganges watershed, where higher flood peaks become the ‘new norm’ as early as mid-2030 implying a relatively short time window for adaptation. In the Brahmaputra and Meghna rivers, the climate impact signal on peak flow emerges after 2070 (CMIP5 and CMIP6 projections). Flood peak synchronization, when annual peak flow occurs simultaneously at (at least) two rivers leading to large flooding events within Bangladesh, show a consistent increase under both projections. While the variability across the ensemble remains high, the increases in flood magnitude are robust in the study basins. Our findings emphasize the need of stringent climate mitigation policies to reduce the climate change impact on peak flows (as presented using SSP1-2.6/RCP2.6) and to subsequently minimize adverse socioeconomic impacts and adaptation costs. Considering Bangladesh’s high overall vulnerability to climate change and its downstream location, synergies between climate change adaptation and mitigation and transboundary cooperation will need to be strengthened to improve overall climate resilience and achieve sustainable development.
Economic losses from hurricanes cannot be nationally offset under unabated warming
Tropical cyclones range among the costliest of all meteorological events worldwide and planetary scale warming provides more energy and moisture to these storms. Modelling the national and global economic repercussions of 2017’s Hurricane Harvey, we find a qualitative change in the global economic response in an increasingly warmer world. While the United States were able to balance regional production failures by the original 2017 hurricane, this option becomes less viable under future warming. In our simulations of over 7000 regional economic sectors with more than 1.8 million supply chain connections, the US are not able to offset the losses by use of national efforts with intensifying hurricanes under unabated warming. At a certain warming level other countries have to step in to supply the necessary goods for production, which gives US economic sectors a competitive disadvantage. In the highly localized mining and quarrying sector—which here also comprises the oil and gas production industry—this disadvantage emerges already with the original Hurricane Harvey and intensifies under warming. Eventually, also other regions reach their limit of what they can offset. While we chose the example of a specific hurricane impacting a specific region, the mechanism is likely applicable to other climate-related events in other regions and other sectors. It is thus likely that the regional economic sectors that are best adapted to climate change gain significant advantage over their competitors under future warming.