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Over the past 30 years, numerous large-scale photometric astronomical surveys have been conducted, including SDSS, Pan-STARRS, Gaia,2MASS, WISE, and others. These surveys provide extensive photometric measurements that can be used to infer…
Forecasting meteorological variables is challenging due to the complexity of their processes, requiring advanced models for accuracy. Accurate precipitation forecasts are vital for society. Reliable predictions help communities mitigate…
A data-driven model (DDM) suitable for regional weather forecasting applications is presented. The model extends the Artificial Intelligence Forecasting System by introducing a stretched-grid architecture that dedicates higher resolution…
Image degradation impedes our ability to extract information from astronomical observations. One factor contributing to this degradation is ``dome seeing", the reduction in image quality due to variations in the index of refraction within…
Optical turbulence, driven by fluctuations of the atmospheric refractive index, poses a significant challenge to ground-based optical systems, as it distorts the propagation of light. This degradation affects both astronomical observations…
Accurate and timely regional weather prediction is vital for sectors dependent on weather-related decisions. Traditional prediction methods, based on atmospheric equations, often struggle with coarse temporal resolutions and inaccuracies.…
We report results of a two-year campaign of measurements, during arctic winter darkness, of optical turbulence in the atmospheric boundary-layer above the Polar Environment Atmospheric Laboratory in northern Ellesmere Island (latitude +80…
Arctic warming threatens over 100 billion in permafrost-dependent infrastructure across Northern territories, yet existing risk assessment frameworks lack spatiotemporal validation, uncertainty quantification, and operational…
Weather station data is a valuable resource for climate prediction, however, its reliability can be limited in remote locations. To compound the issue, making local predictions often relies on sensor data that may not be accessible for a…
Thermal management in the hyper-scale cloud data centers is a critical problem. Increased host temperature creates hotspots which significantly increases cooling cost and affects reliability. Accurate prediction of host temperature is…
We present summer site testing results based on DIMM data obtained at Dome C, Antarctica. These data have been collected on the bright star Canopus during two 3-months summer campaigns in 2003-2004 and 2004-2005. We performed continuous…
We installed two sets of Astronomical Site Monitoring System(ASMS) at Lijiang Observatory(GMG), for the running of the 2.4-meter Lijiang optical telescope(LJT) and the 1.6-meter Multi-channel Photometric Survey Telescope (Mephisto). The…
Post-processing typically takes the outputs of a Numerical Weather Prediction (NWP) model and applies linear statistical techniques to produce improve localized forecasts, by including additional observations, or determining systematic…
Dome A, Antarctica has been thought to be one of the best astronomical sites on the earth since decades ago. From it was first visited by astronomers in 2008, dozens of facilities for astronomical observation and site testing were deployed.…
Machine Learning algorithms are good tools for both classification and prediction purposes. These algorithms can further be used for scientific discoveries from the enormous data being collected in our era. We present ways of discovering…
Forecast of optical turbulence and atmospheric parameters relevant for ground-based astronomy is becoming an important goal for telescope planning and AO instruments optimization in several major telescope. Such detailed and accurate…
Current global warming is causing significant changes in snowfall in polar regions, directly impacting the mass balance of the ice caps. The only water supply in Antarctica, precipitation, is poorly estimated from surface measurements. The…
Collecting time series data spatially distributed in many locations is often important for analyzing climate change and its impacts on ecosystems. However, comprehensive spatial data collection is not always feasible, requiring us to…
Climate system models (CSMs), through integrating cross-sphere interactions among the atmosphere, ocean, land, and cryosphere, have emerged as pivotal tools for deciphering climate dynamics and improving forecasting capabilities. Recent…
Real-time high-resolution wind predictions are beneficial for various applications including safe manned and unmanned aviation. Current weather models require too much compute and lack the necessary predictive capabilities as they are valid…