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Since weather, as a phenomenon of the medium, is an experience of light, to see in the light is to see in the weather.
Passive acoustic-based weather systems are a promising solution to provide long-term in situ weather data with fine time and spatial resolutions.
This work illustrates how environmental noise may be relevant when investigating small strain signals, showing the importance of having data from weather stations and water level sensors colocated with GPS stations.
In addition, initial tests show that this method is capable of reproducing experimental noise measurements within 3 dB accuracy.
Much of climate variability may be explained by the presence of white noise due to synoptic weather disturbances whose impact on climate at longer timescales is due to the integrating effect of the ocean’s ability to store and release heat.
This temporal summation reduces the noise related to smaller-scale weather variability but also implicitly emphasizes the peak of the climatological seasonal cycle of rainfall.
Results show that STEP algorithm can effectively improve quality of polarimetric weather data in the presence of ground clutter and noise.
Many of these are noticeably significant above the confidence level for 'weather' or other (fire regime, ecosystem change) noise and thus should be further investigated in order to adapt to their impacts.
The results indicate that the North Atlantic tripole pattern is forced primarily by the local weather noise surface heat flux.
Journal ArticleDOI
28 Nov 2017-Chaos
27 Citations
Understanding the possible relationships between the SST-forced signal and the weather noise is critically important in climate predictability.

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What specific impacts of climate change in localized areas are expected to be the focus of future climate reporting?
4 answers
Future climate reporting is anticipated to focus on specific impacts in localized areas, such as changes in mean temperature thresholds leading to more disruption days in cities like Chicago and Shenzhen. Additionally, regional media coverage in vulnerable coastal cities like Santos, Selsey, and Broward County is expected to highlight local climate governance developments, with attention on issues like beaches, shoreline neighborhoods, real estate development in low-lying areas, and natural reserves. Furthermore, efforts to support local climate reporting through workshops have shown increased self-efficacy among journalists, although the frequency of climate change reporting may not have significantly risen due to external factors like the impact of COVID-19 on the news industry. This comprehensive approach will enable a more nuanced understanding of climate change impacts at the local level for better preparedness and adaptation strategies.
How does the severity of droughts affect the export of beef cattle in Australia?
5 answers
The severity of droughts significantly impacts the export of beef cattle in Australia. Research indicates that droughts have a positive and statistically significant effect on short-term and long-term debts, equity for dairy farms, and short-term debt for sheep and beef farms, affecting the capital structure of farms. Additionally, droughts have been found to increase non-performing loans (NPLs) in dairy farming, although no significant impact was observed in sheep/beef farming. Furthermore, projections suggest a tenfold increase in the area subject to extreme droughts by the end of the century, particularly affecting the southern and western regions of Australia, which could lead to a significant increase in drought risk and severity, impacting beef cattle exports.
How hybrid models are adding value to forecasting?
5 answers
Hybrid models in forecasting, combining machine learning with physics-based models, offer significant value by enhancing prediction accuracy across various domains. These models leverage the strengths of both approaches, mitigating biases in dynamical outputs, learning from extensive datasets, and merging predictability sources with different time horizons. They improve forecasting skill for diverse variables like rainfall, temperature, streamflow, floods, and more, crucial for water resource management, pandemic predictions, and stock market forecasting. By integrating different models and techniques, hybrid approaches excel in providing more accurate and reliable forecasts, addressing challenges such as nonlinear system modeling, volatility considerations, and early epidemic detection. Overall, hybrid models stand out for their ability to optimize predictions by combining the best of machine learning and physics-based modeling techniques.
How does atmospheric circulation affect air temperature?
5 answers
Atmospheric circulation significantly influences air temperature by impacting temperature trends on various temporal scales. Studies show that while circulation trends have a minor effect on annual mean temperature trends in most regions, they play a more substantial role in seasonal and monthly temperature variations. Atmospheric circulation patterns, such as the Hadley cell and transient eddy heating, contribute to temperature changes in different hemispheres and seasons. In Europe and northern Asia, large-scale weather patterns and circulation classifications explain observed temperature variability, with distinct seasonality and spatial patterns affecting winter warming trends. Additionally, in Bulgaria, circulation indices indicate a significant positive trend in air temperatures, with varying impacts of west–east and south–north air mass transport on temperature changes throughout the year.
Is the world warming?
4 answers
Yes, the world is warming. NASA scientists have observed that the average global temperature has risen by approximately 0.8°Celsius (1.4°Fahrenheit) since 1880, with two-thirds of this increase occurring since 1975. Additionally, recent reports have settled debates over atmospheric warming trends in the past 35 years, confirming the reality of global warming. Despite some regions showing cooling trends, there is significant spatial variability in temperature changes across the World Ocean, with both warming and cooling trends observed in different areas over 20-year periods since 1950. Greenhouse models predict even more warming than is currently evident, suggesting that for climate change to align with projections, the modest warming trends of the 1980s need to accelerate into the next millennium.
How does mcclellan oscillator affects stock returns?
5 answers
The McClellan Oscillator, although not explicitly mentioned in the provided contexts, can be understood in the context of stock market oscillators like the Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI), and Stochastic Oscillator (KDJ). These oscillators are used to predict short-term stock changes by analyzing stock indices like the New York Stock Exchange. The combination of these oscillators can provide a relatively higher possibility of predicting short-term stock movements, regardless of market periods. Additionally, the study of volatility-of-volatility in stock markets suggests a trade-off between returns and volatility-of-volatility, impacting average annual returns significantly. Therefore, incorporating the insights from these contexts, the McClellan Oscillator, as a part of technical analysis tools, may indirectly influence stock returns by aiding in short-term prediction and risk assessment.
Temperature rising trend in Bangladesh?
5 answers
The temperature rising trend in Bangladesh is evident from various studies. Analysis of historical data from 1981 to 2019 shows an increasing trend in mean maximum and minimum temperatures, with rates of 0.19-0.26°C and 0.15-0.18°C per decade respectively. Another study covering 1989-2019 also confirms rising maximum temperatures, especially in the Southeastern region of Bangladesh. Furthermore, a study spanning 1980-2017 indicates a faster increase in daily maximum temperatures compared to daily minimum temperatures, with significant warming trends observed mainly since the 2000s. Additionally, a study focusing on Dhaka city reveals a consistent upward trend in average annual temperatures over the last few decades. These findings collectively highlight the consistent and concerning trend of rising temperatures in Bangladesh.
Is the climate getting hotter or colder?
5 answers
The climate is generally getting hotter, as indicated by NASA and NOAA reports confirming ongoing global warming trends. However, it is essential to note that within this overall warming trend, there can be periods of no trend or even cooling in surface air temperatures over shorter timescales, as observed in the last 34 years and in climate model simulations. This variability can lead to temporary fluctuations in temperature despite the long-term warming trajectory. Climate change models, despite uncertainties, provide confidence in predicting future climate trends, emphasizing the importance of understanding the complexities of climate dynamics and the need for continued efforts to mitigate the impacts of global environmental changes.
How can heavy flooding be solve?
4 answers
Heavy oil flooding issues can be addressed through various methods such as employing novel viscosity reducers to alter flow behavior, developing ultralow interfacial tension solutions to reduce capillary pressure and mobilize heavy oil, and utilizing chemical flooding agents to enhance heavy oil recovery by forming stable emulsions. Additionally, implementing mathematical models coupled with permeability and thermal fields can aid in simulating steam flooding processes effectively. Furthermore, a novel coupling approach with hydrological rainfall-runoff models can help predict and manage flooding events resulting from convective heavy precipitation in urban areas. By integrating these approaches, heavy oil flooding challenges can be mitigated, leading to improved recovery and management strategies in heavy oil reservoirs.
How is an observational study performed on the impact of urban regions on precipitation?
5 answers
An observational study on the impact of urban regions on precipitation involves analyzing how different urban forms influence the spatial distribution and intensity of rainfall. By utilizing data from radar, rain gauges, and climate simulation models, researchers assess precipitation variations based on wind directions, urban sprawl, altitude gradient, and surface roughness across multiple cities over several years. The study aims to unravel the intricate interactions between thermodynamic and aerodynamic processes in urban atmospheres, synoptic conditions, and urban form characteristics to determine the spatial variability of precipitation patterns. Results indicate that urbanization factors like impervious surfaces, urban heat island effects, and increased water vapor play significant roles in enhancing extreme precipitation events in urban areas. Additionally, findings suggest that urban areas intensify rainfall, conserve spatial structures, and influence storm trajectories, potentially acting as barriers to storm movements.
Why SVM show outperformance over the neural network model in the field of climate research?
5 answers
Support Vector Machine (SVM) demonstrates superior performance over neural network models in climate research due to its effectiveness in predicting extreme climatic conditions. SVM models have shown higher accuracy in forecasting global land-ocean temperatures compared to multilayer perceptron neural networks (MLPNN). Additionally, SVM based on Radial Basis Kernel has been found to outperform other SVM types in predicting different climatic phases. On the other hand, neural networks, while successful in various applications, are limited by their black-box nature, hindering trustworthiness in climate science. The explainable artificial intelligence (XAI) field aims to address this limitation by providing insights into the underlying physical mechanisms of neural network predictions, enhancing their reliability in climate research.