scholarly journals Forecasting seeing for the Maunakea Observatories

2020 ◽  
Vol 496 (4) ◽  
pp. 4734-4748
Author(s):  
Ryan Lyman ◽  
Tiziana Cherubini ◽  
Steven Businger
Keyword(s):  
Adaptive Optics ◽  
Atmospheric Stability ◽  
Weather Conditions ◽  
Image Resolution ◽  
Image Motion ◽  
Optical Turbulence ◽  
Observational Measures ◽  
Weather Model ◽  
Operational Forecasting

ABSTRACT Optical turbulence greatly impacts the range and quality of astronomical observations. Advanced knowledge of the expected atmospheric optical turbulence provides important guidance that helps astronomers decide which instrument to schedule and enables them to optimize the adaptive optics technology that improves image resolution. Along with forecasts of weather conditions, prediction of the optical observing quality on the Maunakea summit has been a goal for the Maunakea Weather Center (MKWC) since its inception more than 20 yr ago. Forecasting optical turbulence, and its derivative, ‘seeing’, has proven to be quite challenging because optical turbulence is too small and complex to directly capture with a regional weather model. Fortunately, the permanent installation of a Differential Image Motion Monitor (DIMM) and Multi-Aperture Scintillation Sensor (MASS) at the summit of Maunakea has made seeing observations available during the last decade, providing valuable feedback to the MKWC. This paper summarizes the experience at MKWC in anticipating optical turbulence for the summit of Maunakea accrued through years of daily operational forecasting, and continuous comparison between MKWC official forecasts, model guidance, and observational measures of seeing. Access to a decade seeing observations has allowed quantification the factors that impact seeing, including wind shear, atmospheric stability patterns, and optical turbulence, and to document the seasonal and intra-seasonal variations in seeing. Consequently, the combination of experience gained, and custom model guidance has led to more accurate seeing forecasts (rms errors averaging <0.25 arcsec since 2012) for the Maunakea astronomical observatories.

Daytime optical turbulence profiling with a profiler of the differential solar limb

2020 ◽  
Vol 499 (2) ◽  
pp. 1909-1917
Author(s):  
Tengfei Song ◽  
Zhanchuan Cai ◽  
Yu Liu ◽  
Mingyu Zhao ◽  
Yuliang Fang ◽  
...  
Keyword(s):  
Atmospheric Turbulence ◽  
Adaptive Optics ◽  
Solar Limb ◽  
Coefficient Matrix ◽  
Image Motion ◽  
Index Structure ◽  
Test Results ◽  
Optical Turbulence ◽  
Optical Telescopes ◽  
Turbulence Parameters

ABSTRACT Atmospheric turbulence reduces the image quality and resolution of ground-based optical telescopes. Future large solar telescopes (e.g. the CGST, China Giant Solar Telescope) should be equipped with adaptive optics (AO) systems. The design of AO systems is associated with atmospheric optical turbulence parameters, especially the profile of the refractive index structure $C_{n}^{2}(h)$. With the solar differential image motion monitor (S-DIMM) and the profiler of the moon limb (PML), a simplified version of a PML, termed a profiler of the differential solar limb (PDSL), was built in order to determine the daytime $C_{n}^{2}(h)$ and other atmospheric turbulence parameters. A PDSL with differential solar limb fluctuations was used to determine the turbulence profiling, and the extended solar limb extends the range of separation angles for a higher resolution of the height profile. The PDSL structure and its performance are described. In addition, numerical simulations were conducted to verify the effectiveness of the method. As revealed from the simulation results, the layered integral coefficient matrix is capable of solving the discretization error and enhancing the inversion accuracy of the turbulence contour. The first test results at Mt Wumingshan (a candidate site for the CGST) are presented.

scholarly journals Limitations imposed by optical turbulence profile structure and evolution on tomographic reconstruction for the ELT

2020 ◽  
Vol 494 (2) ◽  
pp. 2773-2784 ◽  
Author(s):  
O J D Farley ◽  
J Osborn ◽  
T Morris ◽  
T Fusco ◽  
B Neichel ◽  
...  
Keyword(s):  
Adaptive Optics ◽  
Tomographic Reconstruction ◽  
Large Data ◽  
Atmospheric Conditions ◽  
Optical Turbulence ◽  
Statistical Nature ◽  
Number Of Layers ◽  
Wide Range ◽  
The Impact

ABSTRACT The performance of tomographic adaptive optics (AO) systems is intrinsically linked to the vertical profile of optical turbulence. First, a sufficient number of discrete turbulent layers must be reconstructed to model the true continuous turbulence profile. Secondly over the course of an observation, the profile as seen by the telescope changes and the tomographic reconstructor must be updated. These changes can be due to the unpredictable evolution of turbulent layers on meteorological time-scales as short as minutes. Here, we investigate the effect of changing atmospheric conditions on the quality of tomographic reconstruction by coupling fast analytical AO simulation to a large data base of 10 691 high-resolution turbulence profiles measured over two years by the Stereo-SCIDAR instrument at ESO Paranal, Chile. This work represents the first investigation of these effects with a large, statistically significant sample of turbulence profiles. The statistical nature of the study allows us to assess not only the degradation and variability in tomographic error with a set of system parameters (e.g. number of layers and temporal update period), but also the required parameters to meet some error threshold. In the most challenging conditions where the profile is rapidly changing, these parameters must be far more tightly constrained in order to meet this threshold. By providing estimates of these constraints for a wide range of system geometries as well as the impact of different temporal optimization strategies we may assist the designers of tomographic AO for the extremely large telescope to dimension their systems.

Water quality of Tampa Bay, Florida : wet-weather conditions, October 1971

1975 ◽  
Author(s):  
Carl R. Goodwin ◽  
Joseph S. Rosenshein ◽  
D.M. Michaelis
Keyword(s):  
Water Quality ◽  
Weather Conditions ◽  
Tampa Bay ◽  
Wet Weather

Robust Environmental Sensing Using UAVs

2021 ◽  
Vol 2 (4) ◽  
pp. 1-20
Author(s):  
Ahmed Boubrima ◽  
Edward W. Knightly
Keyword(s):  
Air Pollution ◽  
Gas Sensors ◽  
High Performance ◽  
Weather Conditions ◽  
Ambient Air ◽  
Mission Planning ◽  
Pollution Monitoring ◽  
Compound Pollution ◽  
Planning Algorithm

In this article, we first investigate the quality of aerial air pollution measurements and characterize the main error sources of drone-mounted gas sensors. To that end, we build ASTRO+, an aerial-ground pollution monitoring platform, and use it to collect a comprehensive dataset of both aerial and reference air pollution measurements. We show that the dynamic airflow caused by drones affects temperature and humidity levels of the ambient air, which then affect the measurement quality of gas sensors. Then, in the second part of this article, we leverage the effects of weather conditions on pollution measurements’ quality in order to design an unmanned aerial vehicle mission planning algorithm that adapts the trajectory of the drones while taking into account the quality of aerial measurements. We evaluate our mission planning approach based on a Volatile Organic Compound pollution dataset and show a high-performance improvement that is maintained even when pollution dynamics are high.

scholarly journals Economic Analysis of a Transport Company in the Aspect of Car Vehicle Operation

2021 ◽  
Vol 13 (1) ◽  
pp. 427
Author(s):  
Magdalena Rykała ◽  
Łukasz Rykała
Keyword(s):  
Weather Conditions ◽  
Neural Model ◽  
Motor Vehicles ◽  
Bulk Materials ◽  
The Sustainable Development ◽  
Average Temperature ◽  
Transport Services ◽  
Vehicle Operation ◽  
The Impact

The article describes the issues of transport of bulk materials. The knowledge of this process has a key impact on the rational planning of transport tasks. It is necessary to have knowledge about the transport services market and the competition that exists in it. In order to achieve a competitive advantage on the market, enterprises should analyze data on the implementation of transport tasks on an ongoing basis. It is also important that the costs incurred from the conducted activity are minimized, while increasing the quality of services and taking into account the sustainable development of the enterprise. The study analyzes data from a few selected motor vehicles in the period of 3 years of operation, coming from an enterprise specializing in the transport of bulk materials. Moreover, a global sensitivity analysis was performed based on a neural model describing the impact of the analyzed factors on the company’s profit. The results show that the most important factors influencing the company’s profit are the fuel consumption of individual vehicles, the driver (driving style) and the month (average temperature, weather conditions).

scholarly journals 1178 J, 527 nm near diffraction limited laser based on a complete closed-loop adaptive optics controlled off-axis multi-pass amplification laser system

2021 ◽  
Vol 9 ◽  
Author(s):  
Deen Wang ◽  
Xin Zhang ◽  
Wanjun Dai ◽  
Ying Yang ◽  
Xuewei Deng ◽  
...  
Keyword(s):  
Laser Beam ◽  
Adaptive Optics ◽  
Closed Loop ◽  
Focal Spot ◽  
Beam Quality ◽  
Laser System ◽  
Diffraction Limit ◽  
Kdp Crystal ◽  
Main Amplifier

Abstract A 1178 J near diffraction limited 527 nm laser is realized in a complete closed-loop adaptive optics (AO) controlled off-axis multi-pass amplification laser system. Generated from a fiber laser and amplified by the pre-amplifier and the main amplifier, a 1053 nm laser beam with the energy of 1900 J is obtained and converted into a 527 nm laser beam by a KDP crystal with 62% conversion efficiency, 1178 J and beam quality of 7.93 times the diffraction limit (DL). By using a complete closed-loop AO configuration, the static and dynamic wavefront distortions of the laser system are measured and compensated. After correction, the diameter of the circle enclosing 80% energy is improved remarkably from 7.93DL to 1.29DL. The focal spot is highly concentrated and the 1178 J, 527 nm near diffraction limited laser is achieved.

scholarly journals Modeling of Yield Losses Caused by Potato Late Blight on Eight Cultivars with Different Levels of Resistance to Phytophthora infestans

Plant Disease ◽  
2012 ◽  
Vol 96 (7) ◽  
pp. 935-942 ◽  
Author(s):  
Toky Rakotonindraina ◽  
Jean-Éric Chauvin ◽  
Roland Pellé ◽  
Robert Faivre ◽  
Catherine Chatot ◽  
...  
Keyword(s):  
Late Blight ◽  
Phytophthora Infestans ◽  
Relative Yield ◽  
Weather Conditions ◽  
Potato Late Blight ◽  
Yield Losses ◽  
Predictive Quality ◽  
Wide Range ◽  
Cultivar Susceptibility

The Shtienberg model for predicting yield loss caused by Phytophthora infestans in potato was developed and parameterized in the 1990s in North America. The predictive quality of this model was evaluated in France for a wide range of epidemics under different soil and weather conditions and on cultivars different than those used to estimate its parameters. A field experiment was carried out in 2006, 2007, 2008, and 2009 in Brittany, western France to assess late blight severity and yield losses. The dynamics of late blight were monitored on eight cultivars with varying types and levels of resistance. The model correctly predicted relative yield losses (efficiency = 0.80, root mean square error of prediction = 13.25%, and bias = –0.36%) as a function of weather and the observed disease dynamics for a wide range of late blight epidemics. In addition to the evaluation of the predictive quality of the model, this article provides a dataset that describes the development of various late blight epidemics on potato as a function of weather conditions, fungicide regimes, and cultivar susceptibility. Following this evaluation, the Shtienberg model can be used with confidence in research and development programs to better manage potato late blight in France.

scholarly journals A Review of Detection and Removal of Raindrops in Automotive Vision Systems

2021 ◽  
Vol 7 (3) ◽  
pp. 52
Author(s):  
Yazan Hamzeh ◽  
Samir A. Rawashdeh
Keyword(s):  
Detrimental Effect ◽  
Weather Conditions ◽  
Traffic Sign ◽  
Survey Paper ◽  
Sign Recognition ◽  
Adverse Weather Conditions ◽  
Wide Range ◽  
Adverse Weather ◽  
Protective Cover

Research on the effect of adverse weather conditions on the performance of vision-based algorithms for automotive tasks has had significant interest. It is generally accepted that adverse weather conditions reduce the quality of captured images and have a detrimental effect on the performance of algorithms that rely on these images. Rain is a common and significant source of image quality degradation. Adherent rain on a vehicle’s windshield in the camera’s field of view causes distortion that affects a wide range of essential automotive perception tasks, such as object recognition, traffic sign recognition, localization, mapping, and other advanced driver assist systems (ADAS) and self-driving features. As rain is a common occurrence and as these systems are safety-critical, algorithm reliability in the presence of rain and potential countermeasures must be well understood. This survey paper describes the main techniques for detecting and removing adherent raindrops from images that accumulate on the protective cover of cameras.

Projected changes in pyroconvective conditions in the Iberian Peninsula at the end of the 21st century

2021 ◽  
Author(s):  
Martín Senande-Rivera ◽  
Gonzalo Miguez-Macho
Keyword(s):  
Iberian Peninsula ◽  
21St Century ◽  
Surface Wind ◽  
Atmospheric Stability ◽  
Weather Conditions ◽  
Fire Season ◽  
Fire Plume ◽  
Near Surface ◽  
Wildfire Spread ◽  
Projected Changes

<p>Extreme wildfire events associated with strong pyroconvection have gained the attention of the scientific community and the society in recent years. Strong convection in the fire plume can influence fire behaviour, as downdrafts can cause abrupt variations in surface wind direction and speed that can result in bursts of unexpected fire propagation. Climate change is expected to increase the length of the fire season and the extreme wildfire potential, so the risk of pyroconvection occurence might be also altered. Here, we analyse atmospheric stability and near-surface fire weather conditions in the Iberian Peninsula at the end of the 21st century to assess the projected changes in pyroconvective risk during favourable weather conditions for wildfire spread.  </p>

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