scholarly journals Synergistic use of Imager Window observations for Cloud Clearing of Sounder Observation for INSAT-3D

2014 ◽  
Vol XL-8 ◽  
pp. 315-320 ◽  
Author(s):  
J. Satapathy ◽  
P. K. Thapliyal ◽  
M. V. Shukla ◽  
C. M. Kishtawal
Keyword(s):  
Statistical Analysis ◽  
High Resolution ◽  
Spatial Resolution ◽  
Atmospheric Temperature ◽  
Indian Region ◽  
Supplementary Information ◽  
Atmospheric Conditions ◽  
Clear Sky ◽  
Fractional Cloud ◽  
Cloud Mask

The retrieval of atmospheric temperature and water vapor profiles from infrared Sounder are severely limited by the presence of cloud. Therefore, retrieval from infrared sounding observations is performed only over clear-sky atmospheric conditions. The probability of finding a clear-sky pixel at spatial resolution of 10 km is found to be very small globally. This study presents a quantitative analysis of the clear-sky probability that is carried out for different months over the Indian region for INSAT-3D Sounder. The probability of a clear-sky is found to be ~7 % for the field of view of 10 km corresponding to the INSAT-3D Sounder. This statistical analysis is established using MODIS cloud mask having 95 % confidence level at 1 km resolution spread in the region between 50E&ndash;110E and 30S&ndash;30N. This necessitates cloud clearing to remove the effect of partial clouds in the Sounder FOV to provide a clear-sky equivalent sounding retrieval. <br><br> Various methods were explored to derive the cloud-cleared radiances using supplementary information such as high resolution infrared or microwave observations. This study presents an effort to use the existing traditional method to derive optimal cloudcleared radiances for INSAT-3D Sounder, by estimating the fractional cloud cover using collocated high resolution INSAT-3D Imager window channel observation. The final Sounder cloud-cleared radiances have been validated with the operational AIRS L2 cloud-cleared radiance products. <br><br> Nevertheless, the statistical analysis of clear-sky probability over Indian region also provides a significant insight towards the dependency of spatial resolution and the considerable field-of-regard (FOR) in obtaining the clear-sky area in the satellite observations. This, in a way, necessitates the cloud-clearing for coarser resolution sensors and at the same time, states the benefits of using very high resolution sensors. It has been observed that FOV of 1km and by choosing a reasonably good FOR can eliminate the cloudy-sky hindrances by increasing the probability of clear-sky from 5 % to 50 %.

scholarly journals A robust threshold-based cloud mask for the HRV channel of MSG SEVIRI

2013 ◽  
Vol 6 (2) ◽  
pp. 2829-2855
Author(s):  
S. Bley ◽  
H. Deneke
Keyword(s):  
High Resolution ◽  
Cloud Fraction ◽  
Small Scale ◽  
Cloud Detection ◽  
Low Resolution ◽  
Test Dataset ◽  
Clear Sky ◽  
Cloud Mask ◽  
Spectral Channels ◽  
Selection Of

Abstract. A robust threshold-based cloud mask for the high-resolution visible (HRV) channel (1 × 1 km2) of the METEOSAT SEVIRI instrument is introduced and evaluated. It is based on operational EUMETSAT cloud mask for the low resolution channels of SEVIRI (3 × 3 km2), which is used for the selection of suitable thresholds to ensure consistency with its results. The aim of using the HRV channel is to resolve small-scale cloud structures which cannot be detected by the low resolution channels. We find that it is of advantage to apply thresholds relative to clear-sky reflectance composites, and to adapt the threshold regionally. Furthermore, the accuracy of the different spectral channels for thresholding and the suitability of the HRV channel are investigated for cloud detection. The case studies show different situations to demonstrate the behaviour for various surface and cloud conditions. Overall, between 4 and 24% of cloudy low-resolution SEVIRI pixels are found to contain broken clouds in our test dataset depending on considered region. Most of these broken pixels are classified as cloudy by EUMETSAT's cloud mask, which will likely result in an overestimate if the mask is used as estimate of cloud fraction.

scholarly journals SPHERE/ZIMPOL high resolution polarimetric imager

2018 ◽  
Vol 619 ◽  
pp. A9 ◽  
Author(s):  
H. M. Schmid ◽  
A. Bazzon ◽  
R. Roelfsema ◽  
D. Mouillet ◽  
J. Milli ◽  
...  
Keyword(s):  
High Resolution ◽  
Adaptive Optics ◽  
Spatial Resolution ◽  
Focal Plane ◽  
Surface Brightness ◽  
Absolute Calibration ◽  
Wind Effect ◽  
High Contrast ◽  
Atmospheric Conditions ◽  
Very High

Context. The SPHERE “planet finder” is an extreme adaptive optics (AO) instrument for high resolution and high contrast observations at the Very Large Telescope (VLT). We describe the Zurich Imaging Polarimeter (ZIMPOL), the visual focal plane subsystem of SPHERE, which pushes the limits of current AO systems to shorter wavelengths, higher spatial resolution, and much improved polarimetric performance. Aims. We present a detailed characterization of SPHERE/ZIMPOL which should be useful for an optimal planning of observations and for improving the data reduction and calibration. We aim to provide new benchmarks for the performance of high contrast instruments, in particular for polarimetric differential imaging. Methods. We have analyzed SPHERE/ZIMPOL point spread functions (PSFs) and measure the normalized peak surface brightness, the encircled energy, and the full width half maximum (FWHM) for different wavelengths, atmospheric conditions, star brightness, and instrument modes. Coronagraphic images are described and the peak flux attenuation and the off-axis flux transmission are determined. Simultaneous images of the coronagraphic focal plane and the pupil plane are analyzed and the suppression of the diffraction rings by the pupil stop is investigated. We compared the performance at small separation for different coronagraphs with tests for the binary α Hyi with a separation of 92 mas and a contrast of Δm ≈ 6m. For the polarimetric mode we made the instrument calibrations using zero polarization and high polarization standard stars and here we give a recipe for the absolute calibration of polarimetric data. The data show small (< 1 mas) but disturbing differential polarimetric beam shifts, which can be explained as Goos-Hähnchen shifts from the inclined mirrors, and we discuss how to correct this effect. The polarimetric sensitivity is investigated with non-coronagraphic and deep, coronagraphic observations of the dust scattering around the symbiotic Mira variable R Aqr. Results. SPHERE/ZIMPOL reaches routinely an angular resolution (FWHM) of 22−28 mas, and a normalized peak surface brightness of SB0 − mstar ≈ −6.5m arcsec−2 for the V-, R- and I-band. The AO performance is worse for mediocre ≳1.0″ seeing conditions, faint stars mR ≳ 9m, or in the presence of the “low wind” effect (telescope seeing). The coronagraphs are effective in attenuating the PSF peak by factors of > 100, and the suppression of the diffracted light improves the contrast performance by a factor of approximately two in the separation range 0.06″−0.20″. The polarimetric sensitivity is Δp < 0.01% and the polarization zero point can be calibrated to better than Δp ≈ 0.1%. The contrast limits for differential polarimetric imaging for the 400 s I-band data of R Aqr at a separation of ρ = 0.86″ are for the surface brightness contrast SBpol( ρ)−mstar ≈ 8m arcsec−2 and for the point source contrast mpol( ρ)−mstar ≈ 15m and much lower limits are achievable with deeper observations. Conclusions. SPHERE/ZIMPOL achieves imaging performances in the visual range with unprecedented characteristics, in particular very high spatial resolution and very high polarimetric contrast. This instrument opens up many new research opportunities for the detailed investigation of circumstellar dust, in scattered and therefore polarized light, for the investigation of faint companions, and for the mapping of circumstellar Hα emission.

scholarly journals SPARC: New Cloud, Snow, and Cloud Shadow Detection Scheme for Historical 1-km AVHHR Data over Canada

2007 ◽  
Vol 24 (3) ◽  
pp. 322-343 ◽  
Author(s):  
Konstantin V. Khlopenkov ◽  
Alexander P. Trishchenko
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Supervised Classification ◽  
Image Data ◽  
Local Area ◽  
The United States ◽  
Temperature Fields ◽  
Polar Regions ◽  
Detection Scheme ◽  
Clear Sky

Abstract The identification of clear-sky and cloudy pixels is a key step in the processing of satellite observations. This is equally important for surface and cloud–atmosphere applications. In this paper, the Separation of Pixels Using Aggregated Rating over Canada (SPARC) algorithm is presented, a new method of pixel identification for image data from the Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA satellites. The SPARC algorithm separates image pixels into clear-sky and cloudy categories based on a specially designed rating scheme. A mask depicting snow/ice and cloud shadows is also generated. The SPARC algorithm has been designed to work year-round (day and night) over the temperate and polar regions of North America, for current and historical AVHRR/NOAA High-Resolution Picture Transmission (HRPT) and Local Area Coverage (LAC) data with original 1-km spatial resolution. The algorithm was tested and applied to data from the AVHRR sensors flown on board NOAA-6 to NOAA-18. The method was employed in generating historical clear-sky composites for the 1982–2005 period at daily, 10-day, and monthly time scales at 1-km resolution for an area of 5700 km × 4800 km centered over Canada. This region also covers the northern part of the United States, including Alaska, as well as Greenland and the surrounding oceans. The SPARC algorithm is designed to produce an aggregated rating that accumulates the results of several tests. The magnitude of the rating serves as an indicator of the probability for a pixel to belong to the clear-sky, partly cloudy, or overcast categories. The individual tests employ the spectral properties of five AVHRR channels, as well as surface skin temperature maps from the North American Regional Reanalysis (NARR) dataset. These temperature fields are available at 32 km × 32 km spatial resolution and at 3-h time intervals. Combining all test results into one final rating for each pixel is beneficial for the generation of multiscene clear-sky composites. The selection of the best pixel to be used in the final clear-sky product is based on the magnitude of the rating. This provides much-improved results relative to other approaches or “yes/no” decision methods. The SPARC method has been compared to the results of supervised classification for a number of AVHRR scenes representing various seasons (snow-free summer, winter with snow/ice coverage, and transition seasons). The results show an overall agreement between the automated (SPARC) and the supervised classification at the level of 80% to 91%.

scholarly journals Quality assessment of heterogeneous surface radiation network data

2012 ◽  
Vol 8 (1) ◽  
pp. 93-97 ◽  
Author(s):  
R. Becker ◽  
K. Behrens
Keyword(s):  
Quality Assessment ◽  
Sunshine Duration ◽  
Surface Radiation ◽  
Quality Data ◽  
Atmospheric Conditions ◽  
Remotely Sensed Data ◽  
Clear Sky ◽  
Assessment Approach ◽  
Sensor Degradation ◽  
Cloud Mask

Abstract. The DWD national radiation measurement network comprises 82 automatic sites, 29 manned sites with shaded and unshaded pyranometer and the BSRN station at Lindenberg. The quality assessment routinely applied takes into account the basic astronomical and empirical considerations as well as some interdependencies like total to diffuse flux relation and cross checking with sunshine duration. A more advanced quality assessment approach attempts to routinely utilise timeseries of clear sky radiative transfer simulations for every site. For that purpose a link to cloud coverage obtained from Meteosat second generation geostationary satellite data, highly resolved in time and space, was established. There is a predefined calibration cycle of 30 month for automatic stations. Data analysis on this timescale allows for the detection of sensor degradation, wrong calibration or configuration and other possible local disturbances. Furthermore using satellite cloud mask enables the identification of larger clear sky regions characterized by similar atmospheric conditions. Thus, in a regionalization step correction or recalibration of moderate quality data to a higher level can be considered. The paper provides an overview of DWD surface radiation network and the current activities to improve automatic quality assessment using remotely sensed data and clear sky modeling for the upgrading of radiation data.

scholarly journals A threshold-based cloud mask for the high-resolution visible channel of Meteosat Second Generation SEVIRI

2013 ◽  
Vol 6 (10) ◽  
pp. 2713-2723 ◽  
Author(s):  
S. Bley ◽  
H. Deneke
Keyword(s):  
High Resolution ◽  
Small Scale ◽  
Cloud Detection ◽  
Low Resolution ◽  
Data Set ◽  
Clear Sky ◽  
Infrared Imager ◽  
Cloud Optical Thickness ◽  
Cloud Mask ◽  
Spectral Channels

Abstract. A threshold-based cloud mask for the high-resolution visible (HRV) channel (1 × 1 km2) of the Meteosat SEVIRI (Spinning Enhanced Visible and Infrared Imager) instrument is introduced and evaluated. It is based on operational EUMETSAT cloud mask for the low-resolution channels of SEVIRI (3 × 3 km2), which is used for the selection of suitable thresholds to ensure consistency with its results. The aim of using the HRV channel is to resolve small-scale cloud structures that cannot be detected by the low-resolution channels. We find that it is of advantage to apply thresholds relative to clear-sky reflectance composites, and to adapt the threshold regionally. Furthermore, the accuracy of the different spectral channels for thresholding and the suitability of the HRV channel are investigated for cloud detection. The case studies show different situations to demonstrate the behavior for various surface and cloud conditions. Overall, between 4 and 24% of cloudy low-resolution SEVIRI pixels are found to contain broken clouds in our test data set depending on considered region. Most of these broken pixels are classified as cloudy by EUMETSAT's cloud mask, which will likely result in an overestimate if the mask is used as an estimate of cloud fraction. The HRV cloud mask aims for small-scale convective sub-pixel clouds that are missed by the EUMETSAT cloud mask. The major limit of the HRV cloud mask is the minimum cloud optical thickness (COT) that can be detected. This threshold COT was found to be about 0.8 over ocean and 2 over land and is highly related to the albedo of the underlying surface.

scholarly journals Probabilistic approach to cloud and snow detection on Advanced Very High Resolution Radiometer (AVHRR) imagery

2014 ◽  
Vol 7 (3) ◽  
pp. 799-822 ◽  
Author(s):  
J. P. Musial ◽  
F. Hüsler ◽  
M. Sütterlin ◽  
C. Neuhaus ◽  
S. Wunderle
Keyword(s):  
High Resolution ◽  
Probabilistic Approach ◽  
Threshold Value ◽  
Single Step ◽  
Common Input ◽  
Clear Sky ◽  
Probability Estimates ◽  
Wide Range ◽  
Cloud Mask ◽  
Very High

Abstract. Derivation of probability estimates complementary to geophysical data sets has gained special attention over the last years. Information about a confidence level of provided physical quantities is required to construct an error budget of higher-level products and to correctly interpret final results of a particular analysis. Regarding the generation of products based on satellite data a common input consists of a cloud mask which allows discrimination between surface and cloud signals. Further the surface information is divided between snow and snow-free components. At any step of this discrimination process a misclassification in a cloud/snow mask propagates to higher-level products and may alter their usability. Within this scope a novel probabilistic cloud mask (PCM) algorithm suited for the 1 km × 1 km Advanced Very High Resolution Radiometer (AVHRR) data is proposed which provides three types of probability estimates between: cloudy/clear-sky, cloudy/snow and clear-sky/snow conditions. As opposed to the majority of available techniques which are usually based on the decision-tree approach in the PCM algorithm all spectral, angular and ancillary information is used in a single step to retrieve probability estimates from the precomputed look-up tables (LUTs). Moreover, the issue of derivation of a single threshold value for a spectral test was overcome by the concept of multidimensional information space which is divided into small bins by an extensive set of intervals. The discrimination between snow and ice clouds and detection of broken, thin clouds was enhanced by means of the invariant coordinate system (ICS) transformation. The study area covers a wide range of environmental conditions spanning from Iceland through central Europe to northern parts of Africa which exhibit diverse difficulties for cloud/snow masking algorithms. The retrieved PCM cloud classification was compared to the Polar Platform System (PPS) version 2012 and Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 cloud masks, SYNOP (surface synoptic observations) weather reports, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical feature mask version 3 and to MODIS collection 5 snow mask. The outcomes of conducted analyses proved fine detection skills of the PCM method with results comparable to or better than the reference PPS algorithm.

scholarly journals An Improvement in Forecasting Rapid Intensification of Typhoon Sinlaku (2008) Using Clear-Sky Full Spatial Resolution Advanced IR Soundings

2010 ◽  
Vol 49 (4) ◽  
pp. 821-827 ◽  
Author(s):  
Hui Liu ◽  
Jun Li
Keyword(s):  
Water Vapor ◽  
Tropical Cyclone ◽  
Spatial Resolution ◽  
Atmospheric Temperature ◽  
Track Forecast ◽  
Rapid Intensification ◽  
Atmospheric Infrared Sounder ◽  
Clear Sky ◽  
Typhoon Track ◽  
High Vertical Resolution

Abstract Hyperspectral infrared (IR) sounders, such as the Atmospheric Infrared Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI), provide unprecedented global atmospheric temperature and moisture soundings with high vertical resolution and accuracy. In this paper, the authors investigate whether advanced IR soundings of water vapor and temperature observations can improve the analysis of a tropical cyclone vortex and the forecast of rapid intensification of a tropical cyclone. Both the IR water vapor and temperature soundings significantly improve the typhoon vortex in the analysis and the forecast of the rapid intensification of Typhoon Sinlaku (2008). The typhoon track forecast is also substantially improved when the full spatial resolution AIRS soundings are assimilated. This study demonstrates the potential important application of high spatial and hyperspectral IR soundings in forecasting tropical cyclones.

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

Recent Progress In High-Resolution Shadowing For Biological Transmission Electron Microscopy

1990 ◽  
Vol 48 (1) ◽  
pp. 510-511 ◽  
Author(s):  
Heinz Gross ◽  
Katarina Krusche ◽  
Peter Tittmann
Keyword(s):  
Heavy Metal ◽  
High Resolution ◽  
Freeze Drying ◽  
Atmospheric Conditions ◽  
Vacuum Equipment ◽  
Transmission Electron ◽  
Gas Atmosphere ◽  
Gas Molecules ◽  
Residual Gas ◽  
Backing Layer

Freeze-drying followed by heavy metal shadowing is a long established and straight forward approach to routinely study the structure of dehydrated macromolecules. Very thin specimens such as isolated membranes or single macromolecules are directly adsorbed on C-coated grids. After rapid freezing the grids are transferred into a suitable vacuum equipment for freeze-drying and heavy metal shadowing.To improve the resolution power of shadowing films we introduced shadowing at very low specimen temperature (−250°C). To routinely do that without the danger of contamination we developed in collaboration with Balzers an UHV (p≤10-9 mbar) machine (BAF500K, Fig.2). It should be mentioned here that at −250°C the specimen surface acts as effective cryopump for practically all impinging residual gas molecules from the residual gas atmosphere.Common high resolution shadowing films (Pt/C, Ta/W) have to be protected from alterations due to air contact by a relatively thick C-backing layer, when transferred via atmospheric conditions into the TEM. Such an additional C-coat contributes disturbingly to the contrast at high resolution.

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