Month: August 2024

Impact of Convective and Land Surface Parameterization Schemes on the Simulation of Surface Temperature and Precipitation Using RegCM4.7 During Summer Period Over the DPR Korea

Latest Results

Abstract

This paper has investigated the impact of convective parameterization schemes (CPS) and land surface models (LSM) on the simulation of summer climate over the Democratic People’s Republic of Korea (DPR Korea) using the regional climate model (RegCM 4.7). The sensitivity experiments with two LSMs [Biosphere Atmosphere Transfer Scheme (BATS) and Community Land Model (CLM 3.5)] and four CPSs (Grell, Emanuel, Grell over land and Emanuel over ocean (GL_EO), Emanuel over land and Grell over ocean (EL_GO)) at 30 km horizontal resolution are carried out in summer (from June to August) for 10 years (2001–2010) for this purpose. The simulation results are compared with the available observation data provided from the State Hydro-Meteorological Administration of the DPR Korea (SHMAK). The results show that summer mean circulation patterns (SMCP) and summer averaged surface temperature (SAST) is well captured for most of the simulations, but summer rainfall is not well represented by RegCM 4.7. The performance of the CLM3.5 scheme is better in all the simulations than the BATS scheme. Among the CPSs, the EL_GO scheme shows the smallest biases in the simulation of SAST and summer rainfall. The simulations using EL_GO with CLM3.5 shows the best performance in simulating the SAST and summer rainfall over the study region among the considered CPSs and LSMs. These results will be helpful to improve the prediction of climate change over the DPR Korea.

Monthly electricity consumption data at 1 km × 1 km grid for 280 cities in China from 2012 to 2019

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Abstract

High spatio-temporal resolution estimates of electricity consumption are essential for formulating effective energy transition strategies. However, the data availability is limited by complex spatio-temporal heterogeneity and insufficient multi-source feature fusion. To address these issues, this study introduces an innovative downscaling method that combines multi-source data with machine learning and spatial interpolation techniques. The method’s accuracy showed significant improvements, with determination coefficients (R2) increasing by 30.1% and 33.4% over the baseline model in two evaluation datasets. With this advanced model, we estimated monthly electricity consumption across 1 km x 1 km grid for 280 Chinese cities from 2012 to 2019. Our dataset is highly consistent with officially released electricity consumption of different industries (Pearson correlation coefficients within 0.83 - 0.91). Moreover, our data can reflect the electricity consumption patterns of different urban land uses compared to other datasets. This study bridges a significant gap in fine-grained electricity consumption data, providing a robust foundation for the development of sustainable energy policies.

The Effects of Moral Intensity and Moral Disengagement on Rule Violations: Occupational Safety in UK-based Construction Work During the COVID-19 Pandemic

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Abstract

We take an ethics theory perspective to examine rule violations and workarounds in the UK construction industry in the context of the COVID-19 pandemic. The UK construction sector remained largely operational during lockdowns in the UK, providing an opportunity to explore the ways in which construction workers made ethical decisions in situ, related to health and safety at work, and COVID-19 rules. We conducted 22 semi-structured interviews with participants from 11 organisations (3 major construction companies and 8 subcontractors) during November 2021 to January 2022. Our qualitative analysis focused on coding responses based on the use of moral disengagement tactics, and the dimensions of moral intensity (magnitude of consequences, social consensus, probability of effect, temporal immediacy, proximity and, concentration of effect). We found instances of ethical dilemmas, including conflicts between compliance with organisational health and safety rules, and following COVID-19 rules. Our analysis showed that rule violations were often justified based on moral disengagement tactics, particularly cognitive reconstrual, obscuring personal agency, disregarding consequences and vilification of the victims. Furthermore, moral intensity played a significant role in making ethical decisions about violating rules. Moral intensity was most influential (across dimensions) for moral disengagement based on cognitive reconstrual (e.g., justifications for choosing to follow one set of rules over another). Social context was highly influential in workers’ ethical decisions, including organisational and group social norms, but wider societal attitudes towards the COVID-19 pandemic, also played a significant role. We discuss the implications for business ethics theory, policy and practice, including recommendations for businesses and policymakers.

Exposing State Repression: Digital Discursive Contention by Chinese Protestors

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Abstract

One of the major issues in international development is how disadvantaged populations mobilize in response to state repression. Whether in the Black Lives Movement or in the 2011 Arab Spring, digital exposures of police abuse have spurred social movements when people took to social media to expose it. Yet, in authoritarian regimes, citizens cannot easily initiate or participate in social movements. In such cases, how do victims of police violence express their dissatisfaction? This study examines this question in contemporary China, where repression of protesters is well documented. Based on a dataset of microblogs—Chinese tweets—documenting 74,415 protest events in the early Xi administration (2013–2016), this study analyzes how ordinary protestors, including migrant workers, peasants, and the urban poor, expose police abuse in social media. A close reading of microblogs documenting 150 randomly sampled events finds that Chinese protestors adopt three distinct narrative types: citizenship, solidarity, and confrontational. An accompanying quantitative analysis of the wider dataset further finds that ordinary protestors frequently expose police abuse online and that mentions of police abuse are closely associated with the above three narratives. Overall, this study contributes to understanding how abused protestors discursively contest authorities in the world’s most powerful authoritarian regime.

Academic freedom and the signifying gap: Thoughts on diaspora, displacement, and Israel-Palestine

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Abstract

The essay interrogates the history and contemporary plight of academic freedom in the current context of heightened political pressures amidst polarizing, moralizing ideological commitments and suppressions of free inquiry, debate, dissent, and truth seeking. It argues that such semiotic collapses reflect a vanishing signifying gap, which has unconscious determinants linked with the erasures of the feminine, and which produces a stifling insistence on sameness at the expense of difference. By examining the surveillances of speech in the context of Israel-Palestine, and particularly post October 7, the essays argues that Palestine , as the site of radical rupture of the signifying chain, occupies a space where freedom of association and speech halt. This crisis also functions as a zero point to law, a semiotic and structural role occupied by the feminine and its cryptic yet spatializing signifier, the vaginal. When enabled, this signifying gap opens an onto-ethical space between the real of ancestral, disavowed trauma and the symbolic discursive realm, revealing unsettling truths, social tensions, and liberatory desires. Its relevance to the semiotic confinements and censorial campaigns haunting the academy (and general culture) but also haunting the holy contested land, occupied territories, and contiguous/noncontiguous borders of Israel-Palestine is not accidental; perhaps this void is so primal as to be barely a metaphor for the sacred dimensions between possession and dispossession essential to political, semiotic, and spiritual liberation/enfranchisement. The wave of encampments and protests across US campuses, unsettling and agitating as they necessarily must be, underscore the primacy of the gap, of a symbolic and real space, in fostering a mutually constitutive relationship between academic freedom and emancipatory politics.

Is the Effect of Educational Attainments on Trust in Scientists Underestimated?

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Abstract

This research aims to assess and quantify the impact of educational attainments on trust in scientists during the COVID-19 pandemic. The study utilizes instrumental variables (IV) and conventional ordinary least squares regression (OLS) approaches that are applied to micro-data from a multinational survey in 26 nations. The IV approach is used to address endogeneity that is caused by reverse causality, omitted variables, and measurement error. The results of IV models suggest that a unit increase in educational attainments leads to an increase in trust in scientists by a factor of 0.20 to 0.28. In comparison, the results of the conventional OLS suggest that a unit increase in educational attainments leads to an increase in trust in scientists by a factor of 0.09 to 0.16. The results suggest that ignoring endogeneity leads to a considerable underestimation of education’s effect on trust in scientists. At the same time, the results indicate that educational training is a key tool to promote science by increasing trust in scientists. Such a conclusion is especially important given that the results are based on the survey conducted during the COVID-19 pandemic, a period characterized by unprecedented public health and economic crises, political backslash, and an “infodemic” of disinformation and misinformation.

Dominant role of grazing and snow cover variability on vegetation shifts in the drylands of Kazakhstan

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Abstract

Decomposing the responses of ecosystem structure and function in drylands to changes in human-environmental forcing is a pressing challenge. Though trend detection studies are extensive, these studies often fail to attribute them to potential spatiotemporal drivers. Most attribution studies use a single empirical model or a causal graph that cannot be generalized or extrapolated to larger scales or account for spatial changes and multiple independent processes. Here, we proposed and tested a multi-stage, multi-model framework that detects vegetation trends and attributes them to ten independent social-environmental system (SES) drivers in Kazakhstan (KZ). The time series segmented residual trend analysis showed that 45.71% of KZ experienced vegetation degradation, with land use change as the predominant contributor (22.54%; 0.54 million km2), followed by climate change and climate variability. Pixel-wise fitted Granger Causality and random forest models revealed that sheep & goat density and snow cover had dominant negative and positive impacts on vegetation in degraded areas, respectively. Overall, we attribute vegetation changes to SES driver impacts for 19.81% of KZ (out of 2.39 million km2). The identified vegetation degradation hotspots from this study will help identify locations where restoration projects could have a greater impact and achieve land degradation neutrality in KZ.

Effects of landcover fine-scale patterns on neighborhood-level winter and summer nocturnal and diurnal air temperatures

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Abstract

Context

There is a gap of knowledge on the effects of fine resolution landcover patterns on the distribution of air temperatures within neighborhoods, as well as on how these effects may differ depending on temporal (i.e., summer and winter, diurnal and nocturnal), and spatial (i.e. extent) scales.

Objectives

(1) Evaluate the effects of compositional and configurational fine-scale landcover patterns on the spatial distribution of air temperatures within neighborhoods. (2) Determine differences between winter and summer seasons and diurnal and nocturnal periods. (3) Evaluate if these effects relate to the spatial extent used for the analysis.

Methods

Relationships between four landscape metrics and air temperature within four contrasting neighborhoods located in Santiago. Landcover was classified in six classes (built up, barren, grass, evergreen, deciduous, woody) from 1.5m resolution satellite images and temperature acquired from dataloggers located within neighborhoods. Linear mixed models were used for testing the relationships at six spatial extents.

Results

Landcover composition and configuration influence temperatures within neighborhoods, but these effects can greatly differ depending on the season, time of the day and extent of analysis. Grass and evergreen trees show the highest effects on neighborhood´s temperatures among the six landcover classes. Grass reduces summer temperatures at smaller extents but may increase temperatures at larger extents. Evergreen trees play a major role during the winter season increasing coldest nocturnal temperatures at all the analyzed extents. These vegetation effects appear to be mostly associated with the average and largest size of their respective patches.

Conclusions

Fine-scale landcover patterns play a role in regulating temperatures within neighborhoods, but these effects depend on the season, time of the day and spatial extent. Researchers and decision makers must be aware that results obtained at a given scale cannot be directly translated to another scales.

From physical climate storylines to environmental risk scenarios for adaptation in the Pilcomayo Basin, central South America

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Abstract

Communicating climate change projections to diverse stakeholders and addressing their concerns is crucial for fostering effective climate adaptation. This paper explores the use of storyline projections as an intermediate technology that bridges the gap between climate science and local knowledge in the Pilcomayo basin. Through fieldwork and interviews with different stakeholders, key environmental concerns influenced by climate change were identified. Traditional approaches to produce regional climate information based on projections often lack relevance to local communities and fail to address their concerns explicitly. By means of storylines approach to evaluate climate projections and by differentiating between upper and middle-lower basin regions and focusing on dry (winter) and rainy (summer) seasons, three qualitatively different storylines of plausible precipitation and temperature changes were identified and related to the main potential risks. By integrating these climate results with local knowledge, a summary of the social and environmental impacts related to each storyline was produced, resulting in three narrated plausible scenarios for future environmental change. The analysis revealed that climate change significantly influences existing issues and activities in the region. Projected trends indicate a shift towards warmer and drier conditions, with uncertainties mainly surrounding summer rainfall, which impacts the probability of increased flooding and river course changes, two of the most concerning issues in the region. These findings serve as a foundation for problem-specific investigations and contribute to informed decision-making for regional climate adaptation. Finally, we highlight the importance of considering local concerns when developing climate change projections and adaptation strategies.