Multi-Instrument Calibration Method Based on a Multiwavelength Ocean Surface Model

2010 ◽  
Vol 7 (1) ◽  
pp. 195-199 ◽  
Author(s):  
Damien Josset ◽  
Jacques Pelon ◽  
Yongxiang Hu
2018 ◽  
Vol 217 ◽  
pp. 52-60 ◽  
Author(s):  
Guosheng Zhang ◽  
William Perrie ◽  
Biao Zhang ◽  
Shahid Khurshid ◽  
Kerri Warner

2013 ◽  
Vol 13 (7) ◽  
pp. 17585-17642
Author(s):  
W. Sun ◽  
C. Lukashin

Abstract. Reflected solar radiance from the Earth–atmosphere system is polarized. Radiance measurements can be affected by the reflected light's state of polarization if the radiometric sensor is sensitive to the polarization of observed light. To enable the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission for inter-calibration of the polarization-sensitive imagers, such as the MODIS, the polarization state of the reflected solar light must be known with sufficient accuracy. For this purpose, the polarized solar radiation from the ocean–atmosphere system is studied with an adding-doubling radiative transfer model (ADRTM). The Cox-and-Munk ocean wave slope distribution model is used in calculation of the reflection matrix of a wind-ruffled ocean surface. An empirical foam spectral reflectance model and an empirical spectral reflectance model for water volume below the surface are integrated in the ocean surface model. Solar reflectance from the ADRTM is compared with that from the discrete-ordinate radiative transfer (DISORT) model. Sensitivity studies for reflected solar radiation are conducted for various ocean-surface and atmospheric conditions for the stratification of polarization distribution models (PDMs), which are to be used in the inter-calibration of the polarization-sensitive imager measurements with the CLARREO data. This modeling provides a reliable approach for making the spectral CLARREO PDMs over the broad solar spectra, which cannot be achieved by empirical PDMs based on the analysis of the data from polarimetric sensors.


2017 ◽  
Author(s):  
Chong Shi ◽  
Teruyuki Nakajima

Abstract. Retrieval of aerosol optical properties and water leaving radiance over ocean is changeling since the latter mostly accounts for ~10% of satellite observed signal and can be easily contaminated by the atmospheric scattering. Such an effort would be more difficulty in turbid coastal waters due to the existence of optically complex oceanic substances or high aerosol loading. In an effort to solve such problems, we present an optimization approach for the simultaneous determination of aerosol optical thickness (AOT) and normalized water leaving radiance (nLw) from multi-spectral measurements. In this algorithm, a coupled atmosphere-ocean radiative transfer model combined with a comprehensive bio-optical oceanic module is used to jointly simulate the satellite observed reflectance at the top of atmosphere and water leaving radiance just above the ocean surface. Then a full-physical nonlinear optimization method is adopted to retrieve AOT and nLw in one step. The algorithm is validated using Aerosol Robotic Network Ocean Color (AERONET-OC) products selected from eight OC sites distributed over different waters, consisting of observation cases covered both in and out of sun glint from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. Results show a good consistency between retrieved and in situ measurements in each site. It is demonstrated that more accurate AOT are determined based on the simultaneous retrieval method, particularly in shorter wavelengths and sun glint conditions, where the averaged percentage difference (APD) of retrieved AOT generally reduce by approximate 10 % in visible bands compared with those derived from the standard atmospheric correction (AC) scheme. It is caused that all the spectral measurements can be used jointly to increase the information content in the inversion of AOT and the wind speed is also simultaneously retrieved to compensate the specular reflectance error estimated from the rough ocean surface model. For the retrieval of nLw, over atmospheric correction can be avoided to have a significant improvement for the inversion of nLw at 412 nm. Furthermore, generally better estimates of band ratios of nLw(443)/nLw(554) and nLw(488)/nLw(554), which are employed in the inversion of chlorophyll a concentration (Chl), are obtained using simultaneous retrieval approach with less root mean square errors and relative differences than those derived from the standard AC approach in comparison to the AERONET-OC products, as a result that the APD value of retrieved Chl decreases by about 5 %. On the other hand, the standard AC scheme yields a more accurate retrieval of nLw at 488 nm, prompting a further optimization of oceanic bio-optical module of current model.


2013 ◽  
Vol 13 (20) ◽  
pp. 10303-10324 ◽  
Author(s):  
W. Sun ◽  
C. Lukashin

Abstract. Reflected solar radiance from the Earth–atmosphere system is polarized. Radiance measurements can be affected by light's state of polarization if the radiometric sensor has polarization dependence. To enable the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission for inter-calibration of the imagers with polarization dependence, such as the MODIS, the polarization state of the light must be known with sufficient accuracy. For this purpose, the polarized solar radiation from the ocean–atmosphere system is studied with an adding-doubling radiative transfer model (ADRTM). The Cox–Munk ocean wave slope distribution model is used in calculation of the reflection matrix of a wind-ruffled ocean surface. An empirical foam spectral reflectance model and an empirical spectral reflectance model for water volume below the surface are integrated in the ocean-surface model. Solar reflectance from the ADRTM is compared with that from the discrete-ordinate radiative transfer (DISORT) model. Sensitivity studies are conducted for various ocean-surface and atmospheric conditions for the stratification of polarization distribution models (PDMs), which are to be used in the inter-calibration of the polarization-sensitive imager measurements with the CLARREO data. This report presents the first accurate approach for making the spectral PDMs over broad solar spectra, which cannot be achieved by empirical PDMs based on the data from polarimetric sensors.


2019 ◽  
Vol 67 (1) ◽  
pp. 70-81 ◽  
Author(s):  
Philippe Riboust ◽  
Guillaume Thirel ◽  
Nicolas Le Moine ◽  
Pierre Ribstein

Abstract Conceptual degree-day snow models are often calibrated using runoff observations. This makes the snow models dependent on the rainfall-runoff model they are coupled with. Numerous studies have shown that using Snow Cover Area (SCA) remote sensing observation from MODIS satellites helps to better constrain parameters. The objective of this study was to calibrate the CemaNeige degree-day snow model with SCA and runoff observations. In order to calibrate the snow model with SCA observations, the original CemaNeige SCA formulation was revisited to take into account the hysteresis that exists between SCA and the snow water equivalent (SWE) during the accumulation and melt phases. Several parametrizations of the hysteresis between SWE and SCA were taken from land surface model literature. We showed that they improve the performances of SCA simulation without degrading the river runoff simulation. With this improvement, a new calibration method of the snow model was developed using jointly SCA and runoff observations. Further analysis showed that the CemaNeige calibrated parameter sets are more robust for simulating independent periods than parameter sets obtained from discharge calibration only. Calibrating the snow model using only SCA data gave mixed results, with similar performances as using median parameters from all watersheds calibration.


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