A Simple Band Ratio Library (BRL) Algorithm for Retrieval of Hourly Aerosol Optical Depth Using FY-4A AGRI Geostationary Satellite Data

نویسندگان

چکیده

The Advanced Geostationary Radiation Imager (AGRI) is one of the primary payloads aboard FY-4A geostationary meteorological satellite, which can provide high-frequency, wide coverage, and multiple spectral channel observations for China surrounding areas. There are currently few studies on aerosol optical depth (AOD) inversion from AGRI data. Based data, a new land AOD retrieval algorithm called band ratio library (BRL) was proposed in this study. monthly average surface reflectance established after obtaining relationship MODIS combined dataset. In order to calculate hourly AOD, look-up tables (LUT) various models were constructed using 6SV model. We quantitatively compared produced data with AERONET ground validate BRL algorithm. AGRI-retrieved good agreement measured by AERONET, has correlation coefficient R 0.84, linear regression function AODAGRI = 0.80 ∗ AODAERONET − 0.004, root-mean-square error (RMSE) 0.16, approximately 60% results fall within uncertain range ±(0.2 × + 0.05). A cross-comparison made product provided NASA. comparison verification show accuracy estimation

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

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

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 atmos...

متن کامل

Aerosol Optical Depth Spatial and Temporal Variability Using Satellite Data Over Indian Major Cities

Introduction: The study’s main aim is to investigate the long-term variation of Aerosol Optical Depth (AOD). It also aims to show the relationship between meteorological parameters. This study evaluates long-term (2010 to 2021) special and temporal changes over major Indian regions using satellite-based data from NASA’s Terra Satellite. Materials and Methods: This study was carried out during ...

متن کامل

Hourly Global Radiation Prediction from Geostationary Satellite Data

The possibility to generate 2-D predictions of solar radiation one hour ahead and over a large geographic area is the focus of this study. In that view, hourly satellite maps of irradiations extracted from the Heliosat-3 have been used as training data and inputs of artificial neural networks (ANN) and as inputs for apersistence model. These models were computed for each point of the map, allow...

متن کامل

A Modified Aerosol Free Vegetation Index Algorithm for Aerosol Optical Depth Retrieval Using GOSAT TANSO-CAI Data

In this paper, we introduced a new algorithm for retrieving aerosol optical depth (AOD) over land, from the Cloud and Aerosol Imager (CAI), which is one of the instruments on the Greenhouse Gases Observing Satellite (GOSAT) for detecting and correcting cloud and aerosol interference. We used the GOSAT and AErosol RObotic NETwork (AERONET) collocated data from different regions over the globe to...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Remote Sensing

سال: 2022

ISSN: ['2315-4632', '2315-4675']

DOI: https://doi.org/10.3390/rs14194861