Evaluation on penetration rate of cloud for incoming solar radiation using geostationary satellite data

2012 ◽  
Vol 48 (2) ◽  
pp. 115-123 ◽  
Author(s):  
Jong-Min Yeom ◽  
Kyung-Soo Han ◽  
Jae-Jin Kim
Keyword(s):  
Solar Radiation ◽  
Satellite Data ◽  
Penetration Rate ◽  
Geostationary Satellite ◽  
Incoming Solar Radiation

scholarly journals Geolocation Correction for Geostationary Satellite Observations by a Phase-Only Correlation Method Using a Visible Channel

2020 ◽  
Vol 12 (15) ◽  
pp. 2472
Author(s):  
Hideaki Takenaka ◽  
Taiyou Sakashita ◽  
Atsushi Higuchi ◽  
Teruyuki Nakajima
Keyword(s):  
Solar Radiation ◽  
Satellite Data ◽  
Ground Truth ◽  
Satellite Observation ◽  
Geostationary Satellite ◽  
Satellite Observations ◽  
Physical Analysis ◽  
Observation Data ◽  
Time Analysis ◽  
Real Time Analysis

This study describes a high-speed correction method for geolocation information of geostationary satellite data for accurate physical analysis. Geostationary satellite observations with high temporal resolution provide instantaneous analysis and prompt reports. We have previously reported the quasi real-time analysis of solar radiation at the surface and top of the atmosphere using geostationary satellite data. Estimating atmospheric parameters and surface albedo requires accurate geolocation information to estimate the solar radiation accurately. The physical analysis algorithm for Earth observations is verified by the ground truth. In particular, downward solar radiation at the surface is validated by pyranometers installed at ground observation sites. The ground truth requires that the satellite observation data pixels be accurately linked to the location of the observation equipment on the ground. Thus, inaccurate geolocation information disrupts verification and causes complex problems. It is difficult to determine whether error in the validation of physical quantities arises from the estimation algorithm, satellite sensor calibration, or a geolocation problem. Geolocation error hinders the development of accurate analysis algorithms; therefore, accurate observational information with geolocation information based on latitude and longitude is crucial in atmosphere and land target analysis. This method provides the basic data underlying physical analysis, parallax correction, etc. Because the processing speed is important in geolocation correction, we used the phase-only correlation (POC) method, which is fast and maintains the accuracy of geolocation information in geostationary satellite observation data. Furthermore, two-dimensional fast Fourier transform allowed the accurate correction of multiple target points, which improved the overall accuracy. The reference dataset was created using NASA’s Shuttle Radar Topography Mission 1-s mesh data. We used HIMAWARI-8/Advanced HIMAWARI Imager data to demonstrate our method, with 22,709 target points for every 10-min observation and 5826 points for every 2.5 min observation. Despite the presence of disturbances, the POC method maintained its accuracy. Column offset and line offset statistics showed stability and characteristic error trends in the raw HIMAWARI standard data. Our method was sufficiently fast to apply to quasi real-time analysis of solar radiation every 10 and 2.5 min. Although HIMAWARI-8 is used as an example here, our method is applicable to all geostationary satellites. The corrected HIMAWARI 16 channel gridded dataset is available from the open database of the Center for Environmental Remote Sensing (CEReS), Chiba University, Japan. The total download count was 50,352,443 on 8 July 2020. Our method has already been applied to NASA GeoNEX geostationary satellite products.

scholarly journals An Algorithm for the Retrieval of Aerosol Optical Depth from Geostationary Satellite Data in Thailand

1970 ◽  
Vol 8 (3) ◽  
pp. 32-41
Author(s):  
Itsara Masiri ◽  
Serm Janjai ◽  
Treenuch Jantarach
Keyword(s):  
Solar Radiation ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Satellite Data ◽  
Reasonable Agreement ◽  
Surface Albedo ◽  
Computer Code ◽  
Geostationary Satellite ◽  
Digital Data ◽  
Main Input

An algorithm was developed to estimate aerosol optical depth (AOD) from geostationary satellite data. The 6S radiative transfer computer code was employed to generate a look-up table (LUT) which incorporates several combinations of satellite-derived variables including earthatmospheric reflectivity, atmospheric reflectivity and surface albedo. The parameterization of the satellite-derived atmospheric reflectivity accounted for the scattering of solar radiation by clouds, absorption of solar radiation by water vapour, ozone and gases and solar radiation depletion by aerosols. The digital data of the MTSAT-1R satellite were used as the main input of the algorithm. For the validation, the values of AOD derived from this algorithm were compared with those obtained from four sites of Aerosol Robotic Network (AERONET) in Thailand, and a reasonable agreement was found. DOI: http://dx.doi.org/10.3126/jie.v8i3.5929 JIE 2011; 8(3): 32-41

DOWNWARD SOLAR RADIATION FROM GEOSTATIONARY SATELLITE DATA A first global view

Weather ◽  
1989 ◽  
Vol 44 (7) ◽  
pp. 311-314 ◽  
Author(s):  
E. Raschke ◽  
M. Rieland
Keyword(s):  
Solar Radiation ◽  
Satellite Data ◽  
Geostationary Satellite ◽  
Global View

scholarly journals Approximating annual mean incoming solar radiation

2021 ◽  
Vol 500 (1) ◽  
pp. 125129
Author(s):  
Alice Nadeau ◽  
Richard McGehee
Keyword(s):  
Solar Radiation ◽  
Incoming Solar Radiation

Solar irradiance estimation from geostationary satellite data: II. Physical models

Solar Energy ◽  
1993 ◽  
Vol 51 (6) ◽  
pp. 457-465 ◽  
Author(s):  
M. Noia ◽  
C.F. Ratto ◽  
R. Festa
Keyword(s):  
Satellite Data ◽  
Solar Irradiance ◽  
Geostationary Satellite ◽  
Physical Models
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