Emissivity and reflection model for calculating unpolarized isotropic water surface-leaving radiance in the infrared. I: Theoretical development and calculations

IASI-Derived Sea Surface Temperature Data Set for Climate Studies

Sea surface temperature (SST) is an essential climate variable, that is directly used in climate monitoring. Although satellite measurements can offer continuous global coverage, obtaining a long-term homogeneous satellite-derived SST data set suitable for climate studies based on a single instrument is still a challenge. In this work, we assess a homogeneous SST data set derived from reprocessed Infrared Atmospheric Sounding Interferometer (IASI) level-1 (L1C) radiance data. The SST is computed using Planck's Law and simple atmospheric corrections. We assess the data set using the ERA5 reanalysis and the EUMETSAT-released IASI level-2 SST product. Over the entire period, the reprocessed IASI SST shows a mean global difference with ERA5 close to zero, a mean absolute bias under 0.5°C, with a SD of difference around 0.3°C and a correlation coefficient over 0.99. In addition, the reprocessed data set shows a stable bias and SD, which is an advantage for climate studies. The interannual variability and trends were compared with other SST data sets: ERA5, Hadley Centre's SST (HadISST), and NOAA's Optimal Interpolation SST Analysis (OISSTv2). We found that the reprocessed SST data set is able to capture the patterns of interannual variability well, showing the same areas of high interannual variability (>1.5°C), including over the tropical Pacific in January corresponding to the El Niño Southern Oscillation. Although the period studied is relatively short, we demonstrate that the IASI data set reproduces the same trend patterns found in the other data sets (i.e., cooling trend in the North Atlantic, warming trend over the Mediterranean).

Skin Sea-Surface Temperature from VIIRS on Suomi-NPP—NASA Continuity Retrievals

Retrievals of skin Sea-Surface Temperature (SSTskin) from the measurements of the Visible Infrared Imaging Radiometer Suite on the Suomi-National Polar-orbiting Partnership satellite are presented and discussed. The algorithms used to derive the SSTskin from the radiometric measurements are given in detail. A number of approaches to assess the accuracy and stability of the Visible Infrared Imaging Radiometer Suite (VIIRS) SSTskin retrievals are reported, and factors including latitude and season, and physical processes in the atmosphere and at the surface are discussed. We conclude that the Suomi National Polar-orbiting Partnership (S-NPP) VIIRS is capable of matching and improving upon the accuracies of SSTskin from the MODISs on Terra and Aqua, and that the VIIRS SSTskin fields have the potential to contribute to the extension of the satellite-derived Climate Data Records of SST into the future.

Combining Fractional Cover Images with One-Class Classifiers Enables Near Real-Time Monitoring of Fallows in the Northern Grains Region of Australia

Fallows are widespread in dryland cropping systems. However, timely information about their spatial extent and location remains scarce. To overcome this lack of information, we propose to classify fractional cover data from Sentinel-2 with biased support vector machines. Fractional cover images describe the land surface in intuitive, biophysical terms, which reduces the spectral variability within the fallow class. Biased support vector machines are a type of one-class classifiers that require labelled data for the class of interest and unlabelled data for the other classes. They allow us to extrapolate in-situ observations collected during flowering to the rest of the growing season to generate large training data sets, thereby reducing the data collection requirements. We tested this approach to monitor fallows in the northern grains region of Australia and showed that the seasonal fallow extent can be mapped with >92% accuracy both during the summer and winter seasons. The summer fallow extent can be accurately mapped as early as mid-December (1–4 months before harvest). The winter fallow extent can be accurately mapped from mid-August (2–4 months before harvest). Our method also detected emergence dates successfully, indicating the near real-time accuracy of our method. We estimated that the extent of fallow fields across the northern grains region of Australia ranged between 50% in winter 2017 and 85% in winter 2019. Our method is scalable, sensor independent and economical to run. As such, it lays the foundations for reconstructing and monitoring the cropping dynamics in Australia.

A Monte Carlo Emissivity Model for Wind-Roughened Sea Surface

Sea surface emissivity (SSE) is a key variable in the estimation of sea surface temperature and the sea surface radiation budget. A physical base SSE model with adequate accuracy and acceptable computational efficiency is highly desired. This paper develops a Monte Carlo ray-tracing model to compute the SSE of a wind-roughened sea surface. The adoption of a two-dimensional continuous surface model and averaging the two polarization components in advance before ray-tracing gives the model acceptable computational efficiency. The developed model can output the contributions of direct emission and the reflected component to the effective emissivity. The contribution of the reflected component to the effective emissivity reaches 0.035 at an 80° emission angle for a wind speed larger than 10 m/s. The emissivity spectra and channel emissivities collected from two field campaigns and one set of outdoor measurements are used to validate the developed model. Statistical results indicate that the absolute value of bias or difference is less than 0.5% when the view angle is less than 65°, which means the retrieval accuracy of sea surface temperature (SST) is guaranteed from the view of SSE. When the view angle increases, the accuracy of the developed model degraded, especially at the view angle of 85°. Without considering this view angle, the absolute value of bias or difference is less than 0.016, and the root mean square difference (RMSD) is less than 0.018.

Polarized infrared reflectivity of one-dimensional Gaussian sea surfaces with surface reflections

Sea surface infrared reflectivity is an important parameter in maritime remote sensing. Usually, single reflection by the sea surface is considered. However, a loss of energy is then reported for large zenith observation angles (θ>50°) with a peak of about 4% for θ≈80°, because of the neglect of the multiple surface reflections. This paper presents calculations for the polarized infrared reflectivity of one-dimensional sea surfaces (2D problems) with two surface reflections, by introducing a bistatic illumination function with two reflections. The results show good agreement with the ones obtained by a Monte Carlo ray-tracing method. It is also shown that the energy conservation criterion is better satisfied after considering two surface reflections.

MATISSE-v2.0 infrared sea images: sensitivity analysis and experimental validation using MIRAMER campaign measurements in solar glint configurations

The validation of the multiresolution model of sea radiance in the infrared, developed at Onera, is investigated by comparison with measurements obtained during the MIRAMER campaign that took place in May 2008 in the Mediterranean Sea. The sea radiance model and optical properties are expressed and the experimental setup of the campaign is briefly presented. We focus on solar glint measurements collected on the 22nd of May at 5 h 59 m 50 s in the mid-wave IR (3.93-4.14 μm) band and the long-wave IR (8.19-8.96 μm) band onboard the research vessel (R/V) Atalante at a grazing observational angle. A sensitivity analysis of glitter radiance on atmospheric and aerosol profiles, as well as sea temperature and wind speed in the vicinity of the measured contextual parameters, is presented. Modeled and measured images are compared and results are delved into further by comparisons of histograms, averaged vertical and horizontal profiles. Errors in the 3.93-4.14 μm band are under those potentially due to calibration, whereas discrepancies are noticed in the 8.19-8.96 μm band, where the deepest analysis has to be performed.

Multiresolution infrared optical properties for Gaussian sea surfaces: theoretical validation in the one-dimensional case

The validation of the multiresolution model of sea surface infrared optical properties developed at ONERA is investigated in the one-dimensional case by comparison with a reference model, using a submillimeter discretization of the surface. Having expressed the optical properties, we detail the characteristics of each model. A set of numerical tests is made for various wind speeds, resolutions, and realizations of the sea surface. The tests show a good agreement between the results except for grazing angles, where the impact of multiple reflections and the effects of adjacent rough surfaces on shadow have to be investigated.