Sea Surface Temperature Retrieval from MODIS Radiances Using Truncated Total Least Squares with Multiple Channels and Parameters

Abstract

Global sea-surface temperatures (SST) from MODIS measured brightness temperatures generated using the regression methods, have been available to users for more than a decade, and are used extensively for a wide range of atmospheric and oceanic studies. However, as evidenced by a number of studies, there are indications that the retrieval quality and cloud detection are somewhat sub-optimal. To improve the performance of both of these aspects, we endorse a new physical deterministic algorithm, based on truncated total least squares (TTLS), using multiple channels and parameters, in conjunction with a hybrid cloud detection scheme using a radiative transfer model atop a functional spectral difference method. The TTLS method is a new addition that improves the information content of the retrieval compared to our previous work using modified total least squares (MTLS), which is feasible because more measurements are available, allowing a larger retrieval vector. A systematic study is conducted to ascertain the appropriate channel selection for SST retrieval from the 16 thermal infrared channels available from the MODIS instrument. Additionally, since atmospheric aerosol is a well-known source of degraded quality of SST retrieval, we include aerosol profiles from numerical weather prediction in the forward simulation and include the total column density of all aerosols in the retrieval vector of our deterministic inverse method. We used a slightly modified version of our earlier reported cloud detection algorithm, namely CEM (cloud and error mask), for this study. Time series analysis of more than a million match-ups shows that our new algorithm (TTLS+CEM) can reduce RMSE by~50% while increasing data coverage by~50% compared to the operationally available MODIS SST.

A transformative approach to enhance the parameter information from microwave and infrared remote sensing measurements

“…RTLS, MTLS, TTLS) have been successfully tested in several case studies (e.g. Koner & Drummond, 2008a;Koner & Harris, 2016a;Koner et al, 2015) using real remote sensing measurements and implemented in near-real-time operations at NOAA (Koner et al, 2015;Koner, Harris, & Maturi, 2016). These results are discussed and contrasted against SI methods for both balloon-based hyperspectral data and satellite-based imagers' measurements.…”

“…The cumulative RMSE values of different SST retrievals are plotted on the y-axis. A cloud-free subset is made using an experimental filter (Koner & Harris, 2016a;. The LS (Equation 2) result is used for comparison since the condition number of the Jacobian for this problem is ~5 (very low) and the noise amplification during inversion is not excessive (cf.…”

“…An algorithm in the form of TTLS (Koner & Harris, 2016a) has been developed using an inverse model of six measurements and three retrieved parameters including total column of all aerosols due to the availability of numerous channels in the thermal IR of Moderate Resolution Imaging Spectroradiometer (MODIS). The sensitivity of physics-based algorithms can be easily compared by their analytically calculated information content.…”

“…To demonstrate this deficiency, the SST retrieval map of a particular granule from MODIS-AQUA (October 30, 2019) for a dynamic oceanographic area of the California coast using two different approaches is shown in Figure 5. The two approaches are the Physical Deterministic SST retrieval suite (PDSST) (Koner & Harris, 2016a) and prevalent regression-based SST retrieval, downloaded from the Physical Oceanography Distributed Active Archive Center (PO. DAAC) website.…”

A comparison between the 2010 and 2016 El-Ninō induced coral bleaching in the Indonesian waters

“…The advantages of satellite-derived SST are vast in coverage at high resolution compared to any other form of conventional collected SST data [39]. Among the satellite derived SST products, MODIS has been providing high quality global SST for over a decade (~15 years) from a single sensor [39,40] and used for a wide variety of studies in the field of earth's climate system, weather forecasting, and oceanographic research, e.g., ocean circulation modelling and the complexity of ocean surface currents, large scale SST anomalies that indicated climate perturbations such as El-Niño events, upwelling regions, ocean biology, including coral reefs and algae blooms [39][40][41][42] and many other wide-range topics. Therefore, in this study, we used monthly SST data from 2002 to 2017 (15 years) derived by Thermal infrared (TIR) sensor of MODIS (Moderate Resolution Imaging Spectroradio-meter) at 11 μm bands of Aqua satellite with a ground resolution of 4 km by 4 km intensively.…”