Month: May 2024

Combining Spatial Downscaling Techniques and Diurnal Temperature Cycle Modelling to Estimate Diurnal Patterns of Land Surface Temperature at Field Scale

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Abstract

Land surface Temperature (LST) at high spatial resolution and at sub-daily scale is highly useful for monitoring evaporative stress in plants, heatwave events, and droughts. Spatial downscaling methods are often used to improve the spatial resolution of LST and Diurnal Temperature Cycle (DTC) models are available to estimate the diurnal variation in LST using limited multi-temporal satellite observations. In this paper, we propose a simple approach to estimate DTC at field scale combining spatial downscaling and DTC modelling. For downscaling the LST from medium-resolution sensors, we have compared three spatial downscaling techniques: Principal Component Regression based disaggregation, DisTrad disaggregation model and a Spatio Temporal Integrated Temperature Fusion Model (STITFM). The PCR-based disaggregation technique uses multiple fine-resolution auxiliary datasets such as vegetation indices, radar backscattering coefficient, etc. The downscaled LSTs from PCR and DisTrad were compared with the original fine-resolution LST from ECOSTRESS and Landsat. The spatially downscaled LST observations from all the three models were then used in the GOT01‑ts DTC model to estimate the corresponding diurnal temperature cycle at fine resolution. The DTC estimated from the downscaled LSTs from all the three methods were compared with in situ DTC obtained from ground observations over four sites. The PCR technique using multiple indices captured the spatial and diurnal patterns of LST across four different sites, yielding a combined Root Mean Square Error (RMSE) of 2.48 K and 0.95 coefficient of determination (R2). The proposed approach can be potentially used to model the diurnal variability of land surface fluxes over different landscapes with finer spatial resolution.

Evaluation of the performance of CMIP6 models in simulating precipitation over Morocco

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Abstract

Morocco is encountering record daily maximum temperatures, severe rainfall deficits, intense thunderstorms, droughts, and powerful wind gusts, causing significant harm to people and property. Therefore, it is crucial to understand the course of these occurrences and to determine to what extent the global climate models (GCMs) used to project climate can replicate rainfall before they can be used in downscaling or impact assessment studies. GCMs are essential tools for climate studies, but selecting the best-performing ones remains challenging. This study aims to assess the extent to which certain climate models from the Coupled Model Intercomparison Project’s 6th phase (CMIP6) reproduce the spatial and temporal variability of precipitation across Morocco between 1981 and 2014. Total monthly precipitation from the Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) were used as observational references. We used six robust statistical metrics on monthly and annual scales, including relative bias, correlation coefficient, root means square error, relative error, Taylor diagram, and Kling–Gupta efficiency. The outcomes demonstrated that the ability of GCMs to simulate precipitation varied over space and time. The spatio-temporal properties of precipitation were well reproduced by all GCMs, with correlation values ranging from 0.78 to 0.87. The research also revealed that only a few models accurately captured the spatial patterns of the detected trends. According to the KGE metric, the GCM INM_CM5_0 is ranked first among the models with the highest KGE value (0.45), followed by GCM FGOALS_f3_L with a value of around 0.41. The study results can be applied to climate projections using CMIP6 under different IPCC scenarios.

Quantum circuit synthesis with diffusion models

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Abstract

Quantum computing has recently emerged as a transformative technology. Yet, its promised advantages rely on efficiently translating quantum operations into viable physical realizations. Here we use generative machine learning models, specifically denoising diffusion models (DMs), to facilitate this transformation. Leveraging text conditioning, we steer the model to produce desired quantum operations within gate-based quantum circuits. Notably, DMs allow to sidestep during training the exponential overhead inherent in the classical simulation of quantum dynamics—a consistent bottleneck in preceding machine learning techniques. We demonstrate the model’s capabilities across two tasks: entanglement generation and unitary compilation. The model excels at generating new circuits and supports typical DM extensions such as masking and editing to, for instance, align the circuit generation to the constraints of the targeted quantum device. Given their flexibility and generalization abilities, we envision DMs as pivotal in quantum circuit synthesis, both enhancing practical applications and providing insights into theoretical quantum computation.

University lecturers’ lived experiences of teaching critical thinking in Australian university: a hermeneutic phenomenological research

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Abstract

The study explores insights into the phenomenon of Australian lecturers’ lived experiences of teaching standalone critical thinking units within associate degree courses at one university in Victoria, Melbourne, Australia. The study makes an original contribution by focusing upon the experiences of teaching staff in Australian universities in relation to teaching critical thinking, particularly from a Heideggerian hermeneutic phenomenological and Gadamerian hermeneutic theoretical and conceptual framework. At present, there are no unified methods, frameworks, or models of teaching critical thinking in Australian higher education. This problem for lecturers is an important aspect of a university education that is not well understood. This is a global educational issue and is a matter of teaching and learning concern worldwide in tertiary education (e.g. United States of America, New Zealand, Canada, and the UK). Although, several studies have been conducted on teaching critical thinking from the perspective of university lecturers. There is limited research that focus on teaching staff in Australian universities’ experience with teaching critical thinking that has used Heidegger’s hermeneutic phenomenology and Gadamer’s hermeneutic circle, interpretive approach in gathering data. Using interviews, data is conducted with three first-year undergraduate Australian university Ph.D. lecturers. During the analysis of the empirical data, three themes were significant in revealing the key findings: (a) Dwelling; (b) Sorge, and (c) Concern. The comprehensive understanding of the results was that the challenges university lecturers faced in developing students to thinking critically provided new pedagogical curriculum insights for the teaching and learning of a standalone critical thinking unit within the associate degree course.

Assessment of the Effect of Land Use and Climate Change on Natural Resources and Agriculture in the Subarnarekha Basin, India, Using the SWAT

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Abstract

In the present study, the Soil and Water Assessment Tool was applied to determine the impacts of changing Land Use and Land Cover (LULC), Geophysical Fluid Dynamics Laboratory – Earth System Model Version 2, and Representative Concentration Pathways (RCP) 8.5 climate scenario on the monthly streamflow in the Subarnarekha basin of India. The results showed increased flow due to a reduction in agricultural area, a rise in built-up area, and a reduction in water bodies due to LULC change. In addition, lower annual precipitation and increased projected temperature were observed under RCP8.5. Although annual precipitation is decreasing, some components of the water balance are slightly increasing. From 2013 to 2020, surface flow increased by 98.85 mm and water yield decreased by 13.33 mm. However, in the climate change scenario, surface flow increased by 142.85 mm. Water yield decreased by 21.88 mm, lateral flow slightly decreased by 7.06 mm, and a further significant decrease 68.37% was noted in groundwater flow. The downward trend in groundwater flow is a serious concern, and therefore, more surface water storage structures must be planned to increase groundwater recharge and capture the increased surface flow. The model performance was statistically tested for NSE (Nash–Sutcliffe efficiency), R2, and PBIAS (percent bias). During the calibration period and validation stages, NSE, R2, and PBIAS were found to be 0.72, 0.83, and − 15.20%, and 0.85, 0.82, and − 27%, respectively, with the 2013 LULC map. The decreased monthly water availability and declining trend of winter rainfall need to be taken care of while planning the cropping pattern of the basin.

Assessment of dynamical downscaling performance over cordex east Asia using MPAS-A global variable resolution model: climatology, seasonal cycle, and extreme events

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Abstract

A 29-year variable resolution climate simulation is conducted from January 1988 to December 2016 using the Model for Prediction Across Scale-Atmosphere (MPAS-A), with prescribed sea surface temperatures obtained from ERA-Interim reanalysis. The global variable resolution configuration employs a mesh refinement of 92–25 km centered over East Asia. Model validations against combined observed datasets highlight that MPAS-A demonstrated advantages over three selected Regional Climate Models (RCMs) in terms of the spatial distribution of precipitation and spatial variability of the near-surface air temperature but struggled with accurately depicting temporal precipitation patterns. MPAS-A’s anomalies in mid-latitude circulation and wave activity fluxes explained the weaker cold air activities during winter in eastern China and the northward shift of the Meiyu rain belt. Common issues with reference RCMs exist in MPAS-A, such as excessive zonal moisture transport over the ocean and unrealistic interannual variability over the northwest Pacific Ocean. The wet biases over the ocean are associated with systematically higher Convective Available Potential Energy (CAPE) for MPAS-A. However, the extreme rainfall indices such as R95pTOT and R99pTOT are not completely dominated by these wet biases and still exhibit reasonable results. This finding underscores the robustness and potential of the variable resolution (VR) approach in obtaining regional information within a single model framework.

“Laws Could Always Be Revoked”: Sociopolitical Uncertainty in the Transition to Marriage Equality

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Abstract

Introduction

Shifting sociopolitical landscapes may create doubts, questions, or concerns for individuals, especially those who hold a disenfranchised identity or are in marginalized relationships (Meyer in Psychology of Sexualities Review 7:81–90, 2016). As a result of political and societal opposition following the Supreme Court Obergefell v. Hodges (2015) decision, for example, legal and social uncertainties may lead to distress for same-sex couples.

Methods

Guided by the Contextual Relational Uncertainty (CRU) model (Monk & Ogolsky in Journal of Family Theory & Review, 11(2):243–261, 2019), we test the association between sociopolitical uncertainties (i.e., uncertainty about legal recognition, social acceptance, and norms or scripts) and relational uncertainty (i.e., self, partner, and relationship uncertainty) among people in same-sex (n = 180) and different-sex (n = 180) relationships 1 year after the Obergefell ruling.

Results

We found that most sources of sociopolitical uncertainty were positively associated with the sources of relational uncertainty. Using thematic analysis, we also analyzed responses to open-ended questions about concerns and experiences related to the Obergefell v. Hodges decision. We identified primary themes including increased (a) social certainty and (b) relational security, but also increased uncertainty related to (c) the breadth and permanence of legal recognition, (d) family norms and roles, and (e) potential backlash.

Conclusions

Overall, these findings provide more evidence of the positive and negative consequences of precarious societal transitions on the lives of individuals, particularly people in marginalized relationships.

Policy Implications

Policymakers and court system officials should be conscious of the full import of legislation. Even when producing legislation that is perceived to benefit a population, policies and educational resources should be considered that further support these communities across the transition.