Quantification of parallax errors in sky simulator domes for clear sky conditions

2002 ◽  
Vol 34 (4) ◽  
pp. 313-327 ◽  
Author(s):  
J Mardaljevic

Scale model illuminance measurements in sky simulator domes are inherently subject to parallax errors. The magnitude of these errors under a number of Commission Internationale de l’É clairage (CIE) clear sky configurations is quantified using computer simulation techniques. In practical operation of a sky simulator dome, a second parallax error in the normalization measurements for horizontal illuminance is likely to compound the parallax error in the other illuminance measurements. This additional parallax error is accounted for in the simulations. The concept of a parallax-bounded volume is introduced. This is the volume of the dome which, on the basis of parallax alone, must contain a scale model if it is not to be subject to errors in the measurement of illuminance beyond a given tolerance. The findings indicate that, on the basis of a credible design goal for the sky simulator dome, high accuracy illuminance predictions (610%) are practically unattainable.

2017 ◽  
Author(s):  
Pauline Martinet ◽  
Domenico Cimini ◽  
Francesco De Angelis ◽  
Guylaine Canut ◽  
Vinciane Unger ◽  
...  

Abstract. A RPG-HATPRO ground-based microwave radiometer (MWR) was operated in a deep Alpine valley during the Passy-2015 field campaign. This experiment aims at investigating how stable boundary layers during wintertime conditions drive the accumulation of pollutants. In order to understand the atmospheric processes in the valley, MWR continuously provide vertical profiles of temperature and humidity at a high time frequency, providing valuable information to follow the evolution of the boundary layer. A one-dimensional variational (1DVAR) retrieval technique has been implemented during the field campaign to optimally combine MWR and 1 h forecasts from the French convective scale model AROME. Retrievals were compared to radiosonde data launched at least every 3 hours during two intensive observation periods (IOP). An analysis of the AROME forecast errors during the IOPs has shown a large underestimation of the surface cooling during the strongest stable episode. MWR brightness temperatures were monitored against simulations from the radiative transfer model ARTS2 (Atmospheric Radiative Transfer Simulator) and radiosonde launched during the field campaign. Large errorswere observed for most transparent channels (i.e., 51–52 GHz) affected by absorption model and calibration uncertainties while a good agreement was found for opaque channels (i.e., 54–58 GHz). Based on this monitoring, a bias correction of raw brightness temperature measurements was applied before the 1DVAR retrievals. 1DVAR retrievals were found to significantly improve the AROME forecasts up to 3 km but mainly below 1 km and to outperform usual statistical regressions above 1 km. With the present implementation, a root-mean-square-error (RMSE) of 1 K through all the atmospheric profile was obtained with values within 0.5 K below 500 m in clear-sky conditions. The use of lower elevation angles (up to 5°) in the MWR scanning and the bias correction were found to improve the retrievals below 1000 m. MWR retrievals were found to catch very well deep nearsurface temperature inversions. Larger errors were observed in cloudy conditions due to difficulty of ground-based MWR to resolve high level inversions that are still challenging. Finally, 1DVAR retrievals were optimized for the analysis of the IOPs by using radiosondes as backgrounds in the 1DVAR algorithm instead of the AROME forecasts. A significant improvement of the retrievals in cloudy conditions and below 1000 m in clear-sky was observed. From this study, we can conclude that MWR are expected to bring valuable information into NWP models up to 3 km altitude both in clear-sky and cloudy-sky conditions with the maximum improvement found around 500 m. With an accuracy between 0.5 and 1 K in RMSE, our study has also proved MWR to be capable of resolving deep near-surface temperature inversions observed in complex terrain during highly stable boundary layer conditions.


2010 ◽  
Vol 3 (4) ◽  
pp. 839-851 ◽  
Author(s):  
O. P. Hasekamp

Abstract. An important new challenge in the field of multi-angle photo-polarimetric satellite remote sensing is the retrieval of aerosol properties under cloudy conditions. In this paper the possibility has been explored to perform a simultaneous retrieval of aerosol and cloud properties for partly cloudy scenes and for fully cloudy scenes where the aerosol layer is located above the cloud, using multi-angle photo-polarimetric measurements. Also, for clear sky conditions a review is given of the capabilities of multi-angle photo-polarimetric measurements in comparison with other measurement types. It is shown that already for clear sky conditions polarization measurements are highly important for the retrieval of aerosol optical and microphysical properties over land surfaces with unknown reflection properties. Furthermore, it is shown that multi-angle photo-polarimetric measurements have the capability to distinguish between aerosols and clouds, and thus facilitate a simultaneous retrieval of aerosol and cloud properties. High accuracy (0.002–0.004) of the polarimetric measurements plays an essential role here.


2010 ◽  
Vol 3 (2) ◽  
pp. 1229-1262 ◽  
Author(s):  
O. P. Hasekamp

Abstract. An important new challenge in the field of multi-angle photopolarimetric satellite remote sensing is the retrieval of aerosol properties under cloudy conditions. In this paper the possibility has been explored to perform a simultaneous retrieval of aerosol and cloud properties for partly cloudy scenes and for fully cloudy scenes where the aerosol layer is located above the cloud, using multi-angle photo-polarimetric measurements. Also, for clear sky conditions a review is given of the capabilities of multi-angle photo-polarimetric measurements in comparison with other measurement types. It is shown that already for clear sky conditions polarization measurements are highly important for the retrieval of aerosol optical and microphysical properties over land surfaces with unknown reflection properties. Furthermore, it is shown that multi-angle photo-polarimetric measurements have the capability to distinguish between aerosols and clouds, and thus facilitate a simultaneous retrieval of aerosol and cloud properties. High accuracy (0.002–0.004) of the polarimetric measurements plays an essential role here.


2017 ◽  
Vol 10 (9) ◽  
pp. 3385-3402 ◽  
Author(s):  
Pauline Martinet ◽  
Domenico Cimini ◽  
Francesco De Angelis ◽  
Guylaine Canut ◽  
Vinciane Unger ◽  
...  

Abstract. A RPG-HATPRO ground-based microwave radiometer (MWR) was operated in a deep Alpine valley during the Passy-2015 field campaign. This experiment aims to investigate how stable boundary layers during wintertime conditions drive the accumulation of pollutants. In order to understand the atmospheric processes in the valley, MWRs continuously provide vertical profiles of temperature and humidity at a high time frequency, providing valuable information to follow the evolution of the boundary layer. A one-dimensional variational (1DVAR) retrieval technique has been implemented during the field campaign to optimally combine an MWR and 1 h forecasts from the French convective scale model AROME. Retrievals were compared to radiosonde data launched at least every 3 h during two intensive observation periods (IOPs). An analysis of the AROME forecast errors during the IOPs has shown a large underestimation of the surface cooling during the strongest stable episode. MWR brightness temperatures were monitored against simulations from the radiative transfer model ARTS2 (Atmospheric Radiative Transfer Simulator) and radiosonde launched during the field campaign. Large errors were observed for most transparent channels (i.e., 51–52 GHz) affected by absorption model and calibration uncertainties while a good agreement was found for opaque channels (i.e., 54–58 GHz). Based on this monitoring, a bias correction of raw brightness temperature measurements was applied before the 1DVAR retrievals. 1DVAR retrievals were found to significantly improve the AROME forecasts up to 3 km but mainly below 1 km and to outperform usual statistical regressions above 1 km. With the present implementation, a root-mean-square error (RMSE) of 1 K through all the atmospheric profile was obtained with values within 0.5 K below 500 m in clear-sky conditions. The use of lower elevation angles (up to 5°) in the MWR scanning and the bias correction were found to improve the retrievals below 1000 m. MWR retrievals were found to catch deep near-surface temperature inversions very well. Larger errors were observed in cloudy conditions due to the difficulty of ground-based MWRs to resolve high level inversions that are still challenging. Finally, 1DVAR retrievals were optimized for the analysis of the IOPs by using radiosondes as backgrounds in the 1DVAR algorithm instead of the AROME forecasts. A significant improvement of the retrievals in cloudy conditions and below 1000 m in clear-sky conditions was observed. From this study, we can conclude that MWRs are expected to bring valuable information into numerical weather prediction models up to 3 km in altitude both in clear-sky and cloudy-sky conditions with the maximum improvement found around 500 m. With an accuracy between 0.5 and 1 K in RMSE, our study has also proven that MWRs are capable of resolving deep near-surface temperature inversions observed in complex terrain during highly stable boundary layer conditions.


Author(s):  
D.J. Benefiel ◽  
R.S. Weinstein

Intramembrane particles (IMP or MAP) are components of most biomembranes. They are visualized by freeze-fracture electron microscopy, and they probably represent replicas of integral membrane proteins. The presence of MAP in biomembranes has been extensively investigated but their detailed ultrastructure has been largely ignored. In this study, we have attempted to lay groundwork for a systematic evaluation of MAP ultrastructure. Using mathematical modeling methods, we have simulated the electron optical appearances of idealized globular proteins as they might be expected to appear in replicas under defined conditions. By comparing these images with the apearances of MAPs in replicas, we have attempted to evaluate dimensional and shape distortions that may be introduced by the freeze-fracture technique and further to deduce the actual shapes of integral membrane proteins from their freezefracture images.


2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.


2021 ◽  
Vol 12 (3) ◽  
pp. 46-47
Author(s):  
Nikita Saxena

Space-borne satellite radiometers measure Sea Surface Temperature (SST), which is pivotal to studies of air-sea interactions and ocean features. Under clear sky conditions, high resolution measurements are obtainable. But under cloudy conditions, data analysis is constrained to the available low resolution measurements. We assess the efficiency of Deep Learning (DL) architectures, particularly Convolutional Neural Networks (CNN) to downscale oceanographic data from low spatial resolution (SR) to high SR. With a focus on SST Fields of Bay of Bengal, this study proves that Very Deep Super Resolution CNN can successfully reconstruct SST observations from 15 km SR to 5km SR, and 5km SR to 1km SR. This outcome calls attention to the significance of DL models explicitly trained for the reconstruction of high SR SST fields by using low SR data. Inference on DL models can act as a substitute to the existing computationally expensive downscaling technique: Dynamical Downsampling. The complete code is available on this Github Repository.


1985 ◽  
Vol 107 (4) ◽  
pp. 267-269 ◽  
Author(s):  
S. Z. Wu ◽  
D. N. Wormley ◽  
D. Rowell ◽  
P. Griffith

An evaluation of systems for control of fossil fuel power plant boiler and stack implosions has been performed using computer simulation techniques described in a companion paper. The simulations have shown that forced and induced draft fan control systems and induced draft fan bypass systems reduce the furnace pressure excursions significantly following a main fuel trip. The limitations of these systems are associated with actuator range and response time and stack pressure excursions during control actions. Preliminary study suggests that an alternative control solution may be achieved by discharging steam into the furnace after a fuel trip.


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