Machine-learning (ML) methods have shown great potential for weather downscaling. These data-driven approaches provide a more efficient alternative for producing high-resolution weather datasets and forecasts compared to physics-based numerical simulations. Neural operators, which learn solution operators for a family of partial differential equations, have shown great success in scientific ML applications involving physics-driven datasets. Neural operators are grid-resolution-invariant and are often evaluated on higher grid resolutions than they are trained on, i.e., zero-shot super-resolution. Given their promising zero-shot super-resolution performance on dynamical systems emulation, we present a critical investigation of their zero-shot weather downscaling capabilities, which is when models are tasked with producing high-resolution outputs using higher upsampling factors than are seen during training. To this end, we create two realistic downscaling experiments with challenging upsampling factors (e.g., 8x and 15x) across data from different simulations: the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) and the Wind Integration National Dataset Toolkit. While neural operator-based downscaling models perform better than interpolation and a simple convolutional baseline, we show the surprising performance of an approach that combines a powerful transformer-based model with parameter-free interpolation at zero-shot weather downscaling. We find that this Swin-Transformer-based approach mostly outperforms models with neural operator layers in terms of average error metrics, whereas an Enhanced Super-Resolution Generative Adversarial Network-based approach is better than most models in terms of capturing the physics of the ground truth data. We suggest their use in future work as strong baselines.

While China's energy system is still largely a “black” system depending on fossil fuel inputs, the electric power system is greening at the margins. We demonstrate, using 2014 data on additions to China's electric power system, that the system is greening– with powerful implications for the future of the country's energy profile. We utilize three lines of argument: first, utilizing data for electric energy generated, where we show that China actually generated less energy from thermal sources in 2014 than in 2013, while increasing generation from water, wind and solar; second, examining capacity additions, we show that new capacity in water, wind and solar (WWS) exceeded new capacity for thermal; and third, in terms of investment. We argue that such data rebut claims made that China is getting blacker while its greening efforts remain small and insubstantial, or that China will become dependent on nuclear power rather than hydro, wind and solar as it cleans its energy system.

In many large shallow lakes across the globe, the surface wind field drives the hydrodynamic process directly through the momentum and energy exchange at the air–water interface. Numerous field measurements, experiments and modeling show that wind-driven hydrodynamic disturbances have profound impacts on the structure and function of lake ecosystems. In this article, we review the response of the shallow lake to the wind-driven wave and flow field, which may accelerate the sediment resuspension and nutrient cycling and, in turn, affect the concentrations of nutrients and dissolved oxygen. Furthermore, the life activities of bacterioplankton, plankton and fish in the aquatic ecosystem are closely related to these water-quality factors. Although we have a developed understanding of the physical processes and biogeochemical cycles of lakes by process-based modeling, the most basic wind-driven hydrodynamic process in some lake models is imprecise. Comprehensive results of physical parameterization, including the wind stress and wind drag coefficient, with their mathematical expressions for depicting the wind-driven force in the hydrodynamic model of lakes are synthesized. Some of these expressions are empirically determined without considering the dynamic environment, and expressions based on physical mechanisms have been widely recognized. Additionally, the adaptation standard of wind-driven force parameterizations to inland lake models under light winds is provided. This article highlights the importance of heterogeneous wind field variability and suggests future studies on the wind fields in extreme climates, which could also cause damage to deep lake ecosystems and the biodiversity effects of wind wave turbulence.

The study of the icebergs and their movements is one of many applications of scatterometer data in the study of the ecosystems of polar regions. SCATSAT-1 is the Indian Space Research Organisation’s (ISRO’s) Ku-band (13.515625 GHz) scatterometer. Using enhanced resolution Gamma0H (horizontally polarised incidence angle normalised backscattering coefficient) data of SCATSAT-1, we observed the movement of iceberg D28 and its interaction with wind, ocean currents and sea ice for one and a half years of its journey (JD 269, 2019 to JD 051, 2021). The data sets used are as follows: (1) SCATSAT-1 level-4 Gamma0H; (2) OSCAR (Ocean Surface Current Analysis Real-time) third-degree resolution ocean surface currents; (3) hourly wind speed data of ERA5; 4) NSIDC (National Snow and Ice Data Center) sea ice concentration data; and (5) NSIDC Polar Path-finder Daily EASE-Grid Sea Ice Motion Vectors, Version-3. For this study, we divide the continent into five different regions/sectors. It is found that the trajectory of the iceberg is influenced by the resultant of the wind and ocean current, at different scales in these regions. Moreover, sea ice motion can also change the course of iceberg. From the on-screen digitisation of the iceberg, the average area of the iceberg is found to be approximately 1509.82 km2 with approximate dimensions of 27 km × 55.5 km. We conclude that spatial and temporal behaviours of the iceberg can be ascertained from the scatterometer data.

Sustainable energy economics in Latin America has become relevant due to the region’s dependence on the oil market and the disruption caused by the COVID-19 pandemic. A systematic review of the ten major economies in the region based on gross domestic product is conducted. We primarily analyze production performance of hydro, wind, and solar energies, in terms of total gigawatt hours produced, current participation levels in energy matrices, and total installed capacity. Current and future trends and legal frameworks for each technology and country are discussed. Our analyses indicate that Latin America and the Caribbean can potentially increase the usage of renewable energy sources given a plethora of natural resources, favorable geographical and climatic conditions, and existing large-scale hydro installations to counteract the inconsistency of wind and solar projects. Therefore, governments in the region must overhaul sustainable policies to increase awareness and reduce energy dependence on foreign powers.

Due to the exceptional complexity of the propulsion system (sails), square-riggers form a special group of sailing vessels. In modern pleasure and sport sailing, simple Bermuda (triangular) sailing rigging prevails, which is widely discussed in the literature, both in terms of theory and numerous experiments. The literature on the theory on square-riggers is, in turn, limited mainly to the description of good sailing practice developed over the centuries. Its important element was maximising vessel speed, but this discussion has not been documented by scientific research. This paper presents the significant parameters influencing the speed of a square-rigged sailing vessel and selects those which are the most important from the point of view of its maximisation. The paper also proposes methods and measurement systems which optimise selected parameters affecting the achievement of higher speeds. The paper describes the types of speeds of typical sailing vessels, provides a historical synthesis of sailing ships with respect to their speed, and presents a selection and description of the parameters affecting the speed of modern square-rigged vessels. The paper ends with a proposed method and measurement system for experimental research aiming at rigging optimisation in a square-rigged sailing vessel from the point of view of maximising its speed.

As no internationally agreed-upon method for determining safe speed values currently exists, collecting vast amounts of information on conventional ship behaviour could be used to train autonomous ship intelligence in determining safe speeds in different conditions. This requires speed data collected from conventional ships to resemble what can be described as safe speeds. To test this, the Automatic Identification System (AIS) and environmental data – namely visibility, mean wind speed and significant wave height – were collected and merged for two study areas in Norway in the period between 27 March 2014 and 1 January 2021. Regression analyses based on 47,490 unique vessel transits were conducted and supplemented by two graphical methods for revealing relationships between variables. Contrary to the contemporary understanding of safe speed, reduced visibility did not lead to significantly reduced transit speeds. Wind and waves caused a reduction in speed in the open ocean, but not in coastal waters. Transit speeds were lower in coastal waters than in the open ocean.

China's west has long been framed as an undeveloped frontier, set apart by poverty and a resource-based economy. Since the 2000s, however, utility-scale renewable energy infrastructure has expanded rapidly in western China, promising local economic benefits tied to national low-carbon transition. This paper contends that these benefits have been precarious and unevenly distributed. I argue that utility-scale renewable energy has remade western China as a “low-carbon frontier,” a resource-rich region that generates low-carbon value for the national green economy. I highlight three features of low-carbon frontiers: they are constructed as spaces of exploitable low-carbon resources, creating an investment boom; they are enclosed through new land arrangements and infrastructure construction, rapidly and with little coordination; and they are reliant on external markets and policy decisions, entrenching dependency. These conditions make it difficult for frontier regions to capture sustained economic development benefits from the boom in the absence of persistent central state supports. I analyse these features by comparing two sets of technologies with similar, but ultimately diverging, trajectories: small and large hydropower in China's south-west, and solar and wind in the north-west.