Bispectral and brightness temperature difference analysis of 1991 FIRE cirrus IFO satellite data

1993 ◽  
Author(s):  
Eric O. Schmidt ◽  
Robert F. Arduini ◽  
Bruce A. Wielicki ◽  
Bryan A. Baum
Keyword(s):  
Brightness Temperature ◽  
Temperature Difference ◽  
Satellite Data ◽  
Difference Analysis

scholarly journals DECISION TREE CLOUD DETECTION ALGORITHM BASED ON FY-4A SATELLITE DATA

2019 ◽  
Vol XLII-3/W9 ◽  
pp. 219-226
Author(s):  
Z. F. Yu ◽  
W. H. Ai ◽  
Z. H. Tan ◽  
W. Yan
Keyword(s):  
Decision Tree ◽  
Brightness Temperature ◽  
Temperature Difference ◽  
Satellite Data ◽  
Detection Algorithm ◽  
Processing Technology ◽  
Cloud Detection ◽  
Detection Model ◽  
Meteorological Satellite

Abstract. In order to study the on-board processing technology of meteorological satellites, a decision tree cloud detection algorithm is proposed by taking FY-4A satellite data as an example. According to the channel setting of the Advanced Geosynchronous Radiation Imager (AGRI) on FY-4A satellite, the 0.65 μm, 1.375 μm, 3.75 μm, and 10.7 μm bands are selected as the cloud detection channels, and the reflectance, brightness temperature or bright temperature difference of the four channels are used as the cloud detection indicators, the thresholds of the four cloud detection indicators are obtained through statistics. On this basis, the decision tree cloud detection model is constructed and validated using FY-4A satellite data. The results show that the algorithm is simple, convenient and efficient, and the overall effect of cloud detection is good. It is an effective way for meteorological satellite cloud detection on-board processing technology.

scholarly journals The detectability of sea-ice leads in satellite data as a function of atmospheric conditions and measurement scale

1993 ◽  
Vol 17 ◽  
pp. 227-232 ◽  
Author(s):  
J. Key ◽  
R. Stone ◽  
J. Maslanik ◽  
E. Ellefsen
Keyword(s):  
Sea Ice ◽  
Brightness Temperature ◽  
Satellite Data ◽  
The Arctic ◽  
Transfer Model ◽  
Atmospheric Effects ◽  
Ice Crystal ◽  
Model Calculations ◽  
Ice Leads ◽  
The Impact

The release of heat from sea-ice leads is an important component of the heat budget in the Arctic, but the impact of leads on regional scale climate is difficult to assess without information on their distribution in both space and time. Remote sensing of leads using satellite data, specifically AVHRR thermal and Landsat visible imagery, is examined with respect to one lead parameter: lead width. Atmospheric effects are illustrated through the concept of thermal contrast transmittance, where the brightness temperature contrast between leads of various ice thicknesses and the surrounding multi-year ice is simulated using a radiative transfer model. Calculations are made as a function of aerosol, ice crystal precipitation, and cirrus cloud optical depths. For example, at ice crystal optical depths of more than about 1.5 under mean January conditions in the central Arctic, the brightness temperature differences between 2 m and 5 cm thick ice are similar to the ice temperature variability so that there would be insufficient contrast to distinguish a lead from the surrounding ice. The geometrical aspects of the sensor are also simulated by degrading Landsat data so that the effect of sensor field-of-view on retrieved lead width statistics can be assessed. Large leads tend to “grow” with increased pixel size while small leads disappear. Changes in lead width and orientation distributions can readily be seen.

Comparison of Ground-Based Radar and Geosynchronous Satellite Climatologies of Warm-Season Precipitation over the United States

2008 ◽  
Vol 47 (12) ◽  
pp. 3264-3270 ◽  
Author(s):  
John D. Tuttle ◽  
Richard E. Carbone ◽  
Phillip A. Arkin
Keyword(s):  
United States ◽  
Brightness Temperature ◽  
Satellite Data ◽  
Warm Season ◽  
Propagation Speed ◽  
Radar Data ◽  
The United States ◽  
Temperature Threshold ◽  
Brightness Temperatures ◽  
The Difference

Abstract Studies in the past several years have documented the climatology of warm-season precipitation-episode statistics (propagation speed, span, and duration) over the United States using a national composited radar dataset. These climatological studies have recently been extended to other continents, including Asia, Africa, and Australia. However, continental regions outside the United States have insufficient radar coverage, and the newer studies have had to rely on geostationary satellite data at infrared (IR) frequencies as a proxy for rainfall. It is well known that the use of IR brightness temperatures to infer rainfall is subject to large errors. In this study, the statistics of warm-season precipitation episodes derived from radar and satellite IR measurements over the United States are compared and biases introduced by the satellite data are evaluated. It is found that the satellite span and duration statistics are highly dependent upon the brightness temperature threshold used but with the appropriate choices of thresholds can be brought into good agreement with those based upon radar data. The propagation-speed statistics of satellite events are on average ∼4 m s−1 faster than radar events and are relatively insensitive to the brightness temperature threshold. A simple correction procedure based upon the difference between the steering winds for the precipitation core and the winds at the level of maximum anvil outflow is developed.

scholarly journals Microwave signatures of ice hydrometeors from ground-based observations above Summit, Greenland

2015 ◽  
Vol 15 (23) ◽  
pp. 34497-34532
Author(s):  
C. Pettersen ◽  
R. Bennartz ◽  
M. S. Kulie ◽  
A. J. Merrelli ◽  
M. D. Shupe ◽  
...  
Keyword(s):  
Brightness Temperature ◽  
Temperature Difference ◽  
Liquid Water ◽  
High Frequency ◽  
Passive Microwave ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Cloud Radar ◽  
Brightness Temperatures ◽  
High Frequency Microwave

Abstract. Multi-instrument, ground-based measurements provide unique and comprehensive datasets of the atmosphere for a specific location over long periods of time and resulting data compliments past and existing global satellite observations. This paper explores the effect of ice hydrometeors on ground-based, high frequency passive microwave measurements and attempts to isolate an ice signature for summer seasons at Summit, Greenland from 2010–2013. Data from a combination of passive microwave, cloud radar, radiosonde, and ceilometer were examined to isolate the ice signature at microwave wavelengths. By limiting the study to a cloud liquid water path of 40 g m−2 or less, the cloud radar can identify cases where the precipitation was dominated by ice. These cases were examined using liquid water and gas microwave absorption models, and brightness temperatures were calculated for the high frequency microwave channels: 90, 150, and 225 GHz. By comparing the measured brightness temperatures from the microwave radiometers and the calculated brightness temperature using only gas and liquid contributions, any residual brightness temperature difference is due to emission and scattering of microwave radiation from the ice hydrometeors in the column. The ice signature in the 90, 150, and 225 GHz channels for the Summit Station summer months was isolated. This measured ice signature was then compared to an equivalent brightness temperature difference calculated with a radiative transfer model including microwave single scattering properties for several ice habits. Initial model results compare well against the four years of summer season isolated ice signature in the high-frequency microwave channels.

scholarly journals The detectability of sea-ice leads in satellite data as a function of atmospheric conditions and measurement scale

1993 ◽  
Vol 17 ◽  
pp. 227-232 ◽  
Author(s):  
J. Key ◽  
R. Stone ◽  
J. Maslanik ◽  
E. Ellefsen
Keyword(s):  
Sea Ice ◽  
Brightness Temperature ◽  
Satellite Data ◽  
The Arctic ◽  
Transfer Model ◽  
Atmospheric Effects ◽  
Ice Crystal ◽  
Model Calculations ◽  
Ice Leads ◽  
The Impact

The release of heat from sea-ice leads is an important component of the heat budget in the Arctic, but the impact of leads on regional scale climate is difficult to assess without information on their distribution in both space and time. Remote sensing of leads using satellite data, specifically AVHRR thermal and Landsat visible imagery, is examined with respect to one lead parameter: lead width. Atmospheric effects are illustrated through the concept of thermal contrast transmittance, where the brightness temperature contrast between leads of various ice thicknesses and the surrounding multi-year ice is simulated using a radiative transfer model. Calculations are made as a function of aerosol, ice crystal precipitation, and cirrus cloud optical depths. For example, at ice crystal optical depths of more than about 1.5 under mean January conditions in the central Arctic, the brightness temperature differences between 2 m and 5 cm thick ice are similar to the ice temperature variability so that there would be insufficient contrast to distinguish a lead from the surrounding ice. The geometrical aspects of the sensor are also simulated by degrading Landsat data so that the effect of sensor field-of-view on retrieved lead width statistics can be assessed. Large leads tend to “grow” with increased pixel size while small leads disappear. Changes in lead width and orientation distributions can readily be seen.

Temperature Difference Analysis and Control Methods in Precision Finishing of Large-Aperture Optical Component

2014 ◽  
Vol 41 (11) ◽  
pp. 1116001
Author(s):  
焦翔 Jiao Xiang ◽  
朱健强 Zhu Jianqiang ◽  
樊全堂 Fan Quantang ◽  
李养帅 Li Yangshuai
Keyword(s):  
Temperature Difference ◽  
Optical Component ◽  
Control Methods ◽  
Difference Analysis ◽  
Large Aperture ◽  
And Control ◽  
Precision Finishing

Application of nighttime fog detection method using MSG8 SEVIRI in an arid environment

2020 ◽  
Author(s):  
Michael Weston ◽  
Marouane Temimi
Keyword(s):  
Brightness Temperature ◽  
United Arab Emirates ◽  
Temperature Difference ◽  
Land Surface ◽  
Visual Inspection ◽  
Detection Method ◽  
Arid Environment ◽  
Desert Region ◽  
Channel Ratio ◽  
Low Cloud

<p class="western"><span>The detection of fog and low cloud (FLC) from satellite data remains challenging despite advances in methodologies and technology. Current methods make use of one or a combination of channel differencing from satellite instruments, surface observations, model data or artificial intelligence. An alternative to the brightness temperature difference method was developed for the GOES-R advanced baseline imager (ABI) which makes use of a channel ratio instead of a channel difference. We apply this method, the so called pseudo emissivity of the 3.9 µm channel, to SEVIRI MSG8 data over the United Arab Emirates, a desert region of the Arabian Peninsula. Low cloud is removed using temperature difference between ERA5 land surface temperature and 10.8 µm channel brightness temperature. Visual inspection of the final fog only mask shows that this method works well over this region. Verification at three sites where METAR data is available returned POD (FAR) of 0.77 (0.27), 0.50 (0.65) and 0.83 (0.26) respectively. Application of this method can be further developed to represent seasonal fog distribution and frequency across the United Arab Emirates.</span></p>

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