scholarly journals Removing Solar Radiative Effect from the VIIRS M12 Band at 3.7 μm for Daytime Sea Surface Temperature Retrievals

2014 ◽  
Vol 31 (11) ◽  
pp. 2522-2529
Author(s):  
Quanhua Liu ◽  
Alexander Ignatov ◽  
Fuzhong Weng ◽  
XingMing Liang
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Atmospheric Aerosols ◽  
Infrared Imaging ◽  
Research Work ◽  
Sea Surface ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Infrared Band ◽  
Cloud Mask

AbstractOperational sea surface temperature (SST) retrieval algorithms are stratified into nighttime and daytime. The nighttime algorithm uses two split-window Visible Infrared Imaging Radiometer Suite (VIIRS) bands—M15 and M16, centered at ~11 and ~12 m, respectively—and a shortwave infrared band—M12, centered at ~3.7 m. The M12 is most transparent and critical for accurate SST retrievals. However, it is not used during the daytime because of contamination by solar radiation, which is reflected by the ocean surface and scattered by atmospheric aerosols. As a result, daytime VIIRS SST and cloud mask products and applications are degraded and inconsistent with their nighttime counterparts. This study proposes a method to remove the solar contamination from the VIIRS M12 based on theoretical radiative transfer model analyses. The method uses either of the two VIIRS shortwave bands, centered at 1.6 m (M10) or 2.25 m (M11), to correct for the effect of solar reflectance in M12. Subsequently, the corrected daytime brightness temperature in M12 can be used as input into nighttime cloud mask and SST algorithms. Preliminary comparisons with the European Centre for Medium-Range Weather Forecasts (ECMWF) SST analysis suggest that the daytime SST products can be improved and potentially reconciled with the nighttime SST product. However, more substantial case studies and assessments using different SST products are required before the transition of this research work into operational products.

scholarly journals Improving Satellite-Derived Sea Surface Temperature Accuracies Using Water Vapor Profile Data

2011 ◽  
Vol 28 (1) ◽  
pp. 85-93 ◽  
Author(s):  
Ian J. Barton
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Satellite Data ◽  
Sea Surface ◽  
Radiative Transfer Model ◽  
Clear Correlation ◽  
Transfer Model ◽  
The Difference

Abstract Analyses based on atmospheric infrared radiative transfer simulations and collocated ship and satellite data are used to investigate whether knowledge of vertical atmospheric water vapor distributions can improve the accuracy of sea surface temperature (SST) estimates from satellite data. Initially, a simulated set of satellite brightness temperatures generated by a radiative transfer model with a large maritime radiosonde database was obtained. Simple linear SST algorithms are derived from this dataset, and these are then reapplied to the data to give simulated SST estimates and errors. The concept of water vapor weights is introduced in which a weight is a measure of the layer contribution to the difference between the surface temperature and that measured by the satellite. The weight of each atmospheric layer is defined as the layer water vapor amount multiplied by the difference between the SST and the midlayer temperature. Satellite-derived SST errors are then plotted against the difference in the sum of weights above an altitude of 2.5 km and that below. For the simple two-channel (with typical wavelengths of 11 and 12 μm) analysis, a clear correlation between the weights differences and the SST errors is found. A second group of analyses using ship-released radiosondes and satellite data also show a correlation between the SST errors and the weights differences. The analyses suggest that, for an SST derived using a simple two-channel algorithm, the accuracy may be improved if account is taken of the vertical distribution of water vapor above the ocean surface. For SST estimates derived using algorithms that include data from a 3.7-μm channel, there is no such correlation found.

scholarly journals Effect of Out-of-Band Response in NOAA-16 AVHRR Channel 3b on Top-of-Atmosphere Radiances Calculated with the Community Radiative Transfer Model

2009 ◽  
Vol 26 (9) ◽  
pp. 1968-1972 ◽  
Author(s):  
Quanhua Liu ◽  
Xingming Liang ◽  
Yong Han ◽  
Paul van Delst ◽  
Yong Chen ◽  
...  
Keyword(s):  
High Resolution ◽  
Radiative Transfer ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Surface Wind ◽  
Sea Surface ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Absorption Bands ◽  
Clear Sky

Abstract The Community Radiative Transfer Model (CRTM) developed at the Joint Center for Satellite Data Assimilation (JCSDA) is used in conjunction with a daily sea surface temperature (SST) and the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) atmospheric data and surface wind to calculate clear-sky top-of-atmosphere (TOA) brightness temperatures (BTs) in three Advanced Very High Resolution Radiometer (AVHRR) thermal infrared channels over global oceans. CRTM calculations are routinely performed by the sea surface temperature team for four AVHRR instruments on board the National Oceanic and Atmospheric Administration (NOAA) satellites NOAA-16, NOAA-17, and NOAA-18 and the Meteorological Operation (MetOp) satellite MetOp-A, and they are compared with clear-sky TOA BTs produced by the operational AVHRR Clear-Sky Processor for Oceans (ACSPO). It was observed that the model minus observation (M−O) bias in the NOAA-16 AVHRR channel 3b (Ch3b) centered at 3.7 μm experienced a discontinuity of ∼0.3 K when a new CRTM version 1.1 (v.1.1) was implemented in ACSPO processing in September 2008. No anomalies occurred in any other AVHRR channel or for any other platform. This study shows that this discontinuity is caused by the out-of-band response in NOAA-16 AVHRR Ch3b and by using a single layer to the NCEP GFS temperature profiles above 10 hPa for the alpha version of CRTM. The problem has been solved in CRTM v.1.1, which uses one of the six standard atmospheres to fill in the missing data above the top pressure level in the input NCEP GFS data. It is found that, because of the out-of-band response, the NOAA-16 AVHRR Ch3b has sensitivity to atmospheric temperature at high altitudes. This analysis also helped to resolve another anomaly in the absorption bands of the High Resolution Infrared Radiation Sounder (HIRS) sensor, whose radiances and Jacobians were affected to a much greater extent by this CRTM inconsistency.

scholarly journals Estimating Infrared Radiometric Satellite Sea Surface Temperature Retrieval Cold Biases in the Tropics due to Unscreened Optically Thin Cirrus Clouds

2017 ◽  
Vol 34 (2) ◽  
pp. 355-373 ◽  
Author(s):  
Jared W. Marquis ◽  
Alec S. Bogdanoff ◽  
James R. Campbell ◽  
James A. Cummings ◽  
Douglas L. Westphal ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Radiative Transfer Model ◽  
Orthogonal Polarization ◽  
Cold Bias ◽  
Transfer Model ◽  
Single Observation ◽  
Cloud Optical Depth ◽  
Level 2

AbstractPassive longwave infrared radiometric satellite–based retrievals of sea surface temperature (SST) at instrument nadir are investigated for cold bias caused by unscreened optically thin cirrus (OTC) clouds [cloud optical depth (COD) ≤ 0.3]. Level 2 nonlinear SST (NLSST) retrievals over tropical oceans (30°S–30°N) from Moderate Resolution Imaging Spectroradiometer (MODIS) radiances collected aboard the NASA Aqua satellite (Aqua-MODIS) are collocated with cloud profiles from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. OTC clouds are present in approximately 25% of tropical quality-assured (QA) Aqua-MODIS Level 2 data, representing over 99% of all contaminating cirrus found. Cold-biased NLSST (MODIS, AVHRR, and VIIRS) and triple-window (AVHRR and VIIRS only) SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical 1.5-km-thick OTC cloud placed incrementally from 10.0 to 18.0 km above mean sea level for cloud optical depths between 0.0 and 0.3. Corresponding cold bias estimates for each sensor are estimated using relative Aqua-MODIS cloud contamination frequencies as a function of cloud-top height and COD (assuming they are consistent across each platform) integrated within each corresponding modeled cold bias matrix. NLSST relative OTC cold biases, for any single observation, range from 0.33° to 0.55°C for the three sensors, with an absolute (bulk mean) bias between 0.09° and 0.14°C. Triple-window retrievals are more resilient, ranging from 0.08° to 0.14°C relative and from 0.02° to 0.04°C absolute. Cold biases are constant across the Pacific and Indian Oceans. Absolute bias is lower over the Atlantic but relative bias is higher, indicating that this issue persists globally.

scholarly journals Comparison of SLSTR Thermal Emissive Bands Clear-Sky Measurements with Those of Geostationary Imagers

2020 ◽  
Vol 12 (20) ◽  
pp. 3279
Author(s):  
Bingkun Luo ◽  
Peter J. Minnett
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Azimuth Angle ◽  
Sea Surface ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Clear Sky ◽  
Brightness Temperatures ◽  
Infrared Imager ◽  
Earth Observation Satellite

The Sentinel-3 series satellites belong to the European Earth Observation satellite missions for supporting oceanography, land, and atmospheric studies. The Sea and Land Surface Temperature Radiometer (SLSTR) onboard the Sentinel-3 satellites was designed to provide a significant improvement in remote sensing of skin sea surface temperature (SSTskin). The successful application of SLSTR-derived SSTskin fields depends on their accuracies. Based on sensor-dependent radiative transfer model simulations, geostationary Geostationary Operational Environmental Satellite (GOES-16) Advanced Baseline Imagers (ABI) and Meteosat Second Generation (MSG-4) Spinning Enhanced Visible and Infrared Imager (SEVIRI) brightness temperatures (BT) have been transformed to SLSTR equivalents to permit comparisons at the pixel level in three ocean regions. The results show the averaged BT differences are on the order of 0.1 K and the existence of small biases between them are likely due to the uncertainties in cloud masking, satellite view angle, solar azimuth angle, and reflected solar light. This study demonstrates the feasibility of combining SSTskin retrievals from SLSTR with those of ABI and SEVIRI.

scholarly journals Automatic Detection of Optical Signatures within and around Floating Tonga-Fiji Pumice Rafts Using MODIS, VIIRS, and OLCI Satellite Sensors

2021 ◽  
Vol 13 (3) ◽  
pp. 501
Author(s):  
Andra Whiteside ◽  
Cécile Dupouy ◽  
Awnesh Singh ◽  
Robert Frouin ◽  
Christophe Menkes ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Land Surface ◽  
Pacific Islands ◽  
Infrared Imaging ◽  
Far East ◽  
Automatic Detection ◽  
Sea Surface ◽  
Chlorophyll A Concentration

An underwater volcanic eruption off the Vava’u island group in Tonga on 7 August 2019 resulted in the creation of floating pumice on the ocean’s surface extending over an area of 150 km2. The pumice’s far-reaching effects from its origin in the Tonga region to Fiji and the methods of automatic detection using satellite imagery are described, making it possible to track the westward drift of the pumice raft over 43 days. Level 2 Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), Sentinel-3 Ocean and Land Color Instrument (OLCI), and Sentinel-3 Sea and Land Surface Temperature Radiometer (SLSTR) imagery of sea surface temperature, chlorophyll-a concentration, quasi-surface (i.e., Rayleigh-corrected) reflectance, and remote sensing reflectance were used to distinguish consolidated and fragmented rafts as well as discolored and mesotrophic waters. The rafts were detected by a 1 to 3.5 °C enhancement in the MODIS-derived “sea surface temperature” due to the emissivity difference of the raft material. Large plumes of discolored waters, characterized by higher satellite reflectance/backscattering of particles in the blue than surrounding waters (and corresponding to either submersed pumice or associated white minerals), were associated with the rafts. The discolored waters had relatively lower chlorophyll-a concentration, but this was artificial, resulting from the higher blue/red reflectance ratio caused by the reflective pumice particles. Mesotrophic waters were scarce in the region of the pumice rafts, presumably due to the absence of phytoplanktonic response to a silicium-rich pumice environment in these tropical oligotrophic environments. As beach accumulations around Pacific islands surrounded by coral shoals are a recurrent phenomenon that finds its origin far east in the ocean along the Tongan trench, monitoring the events from space, as demonstrated for the 7 August 2019 eruption, might help mitigate their potential economic impacts.

Assimilation of Low-Peaking Satellite Observations Using the Coupled Interface Framework

2020 ◽  
Vol 148 (2) ◽  
pp. 637-654
Author(s):  
Sergey Frolov ◽  
William Campbell ◽  
Benjamin Ruston ◽  
Craig H. Bishop ◽  
David Kuhl ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Circulation Model ◽  
Satellite Observations ◽  
Sea Surface ◽  
Transfer Model ◽  
Western Boundary ◽  
Diurnal Variability ◽  
Near Surface ◽  
The Impact

Abstract Coupled data assimilation (DA) provides a consistent framework for assimilating satellite observations that are sensitive to several components of the Earth system. In this paper, we focus on low-peaking infrared satellite channels that are sensitive to the lower atmosphere and Earth surface temperature (EST) over both ocean and land. Our atmospheric hybrid-4DVAR system [the Navy Global Environmental Model (NAVGEM)] is extended to include the following: 1) variability in the sea surface temperature (both diurnal variability and climatological perturbations to the ensemble members), 2) the coupled Jacobians of the radiative transfer model for the infrared sensors, and 3) the coupled covariances between the EST and the atmosphere. Our coupling approach is found to improve forecast accuracy and to provide corrections to the EST that are in balance with the atmospheric analysis. The largest impact of the coupling is found on near-surface atmospheric temperature and humidity in the tropics, but the impact extends all the way to the stratosphere. The role of each coupling element on the performance of the global atmospheric circulation model is investigated. Inclusion of variability in the sea surface temperature has the strongest positive impact on the forecast quality. Additional inclusion of the coupled Jacobian and ensemble-based coupled covariances led to further improvements in scores and to modification of the corrections to the ocean boundary layer. Coupled DA had significant impact on latent and sensible heat fluxes over land, locations of western boundary currents, and along the ice edge.

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

2020 ◽  
Vol 12 (20) ◽  
pp. 3369 ◽  
Author(s):  
Peter J. Minnett ◽  
Katherine A. Kilpatrick ◽  
Guillermo P. Podestá ◽  
Robert H. Evans ◽  
Malgorzata D. Szczodrak ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Infrared Imaging ◽  
Sea Surface ◽  
Climate Data ◽  
Physical Processes ◽  
Radiometric Measurements ◽  
The Future ◽  
Accuracy And Stability

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.

scholarly journals Aerosol Induced Changes in Sea Surface Temperature Over the Bay of Bengal Due to COVID-19 Lockdown

2021 ◽  
Vol 8 ◽  
Author(s):  
T. S. Sarin ◽  
V. Vinoj ◽  
D. Swain ◽  
K. Landu ◽  
E. Suhas
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Atmospheric Aerosols ◽  
Bay Of Bengal ◽  
Anthropogenic Activities ◽  
Sea Surface ◽  
Emissions Reduction ◽  
Induced Changes

The role of COVID-19 pandemic lockdown in improving air quality was reported extensively for land regions globally. However, limited studies have explored these over oceanic areas close to high anthropogenic activities and emissions. The Bay of Bengal (BoB) basin is one such region adjacent to the highly populated South Asian region. We find that Aerosol Optical Depth (AOD) over the BoB declined by as much as 0.1 or 30% during the peak lockdown of April 2020 compared to long-term climatology during 2003–2019. Simultaneously, the sea surface temperature (SST) rose by 0.5–1.5°C over the central and north-western parts of the BoB with an average increase of 0.83°C. We show that up to 30% of this observed warming is attributable to reduced atmospheric aerosols. The study highlights the importance of anthropogenic emissions reduction due to COVID lockdown on short-term changes to SST over ocean basins with implications to regional weather.

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