Planck-Weighted Transmittance and Correction of Solar Reflection for Broadband Infrared Satellite Channels

2012 ◽  
Vol 29 (3) ◽  
pp. 382-396 ◽  
Author(s):  
Yong Chen ◽  
Fuzhong Weng ◽  
Yong Han ◽  
Quanhua Liu
Keyword(s):  
Surface Temperature ◽  
Optical Thickness ◽  
Near Infrared ◽  
Spectral Response ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Atmospheric Layer ◽  
Explanatory Variables ◽  
Brightness Temperatures ◽  
Satellite Channels

Abstract The line-by-line radiative transfer model (LBLRTM) is used to derive the channel transmittances. The channel transmittance from a level to the top of the atmosphere can be approximated by three methods: Planck-weighted transmittance 1 (PW1), Planck-weighted transmittance 2 (PW2), and non-Planck-weighted transmittance (ORD). The PW1 method accounts for a radiance variation across the instrument’s spectral response function (SRF) and the Planck function is calculated with atmospheric layer temperature, whereas the PW2 method accounts for the variation based on the temperatures at the interface between atmospheric layers. For channels with broad SRFs, the brightness temperatures (BTs) derived from the ORD are less accurate than these from either PW1 or PW2. Furthermore, the BTs from PW1 are more accurate than these from PW2, and the BT differences between PW1 and PW2 increase with atmospheric optical thickness. When the band correction is larger than 1, the PW1 method should be used to account for the Planck radiance variation across the instrument’s SRF. When considering the solar contribution in daytime, the correction of the solar reflection has been made for near-infrared broadband channels (~3.7 μm) when using PW1 transmittance. The solar transmittance is predicted by using explanatory variables, such as PW1 transmittance, the secant of zenith angle, and the surface temperature. With this correction, the errors can be significantly reduced.

scholarly journals MISR Calibration and Implications for Low-Light-Level Aerosol Retrieval over Dark Water

2005 ◽  
Vol 62 (4) ◽  
pp. 1032-1052 ◽  
Author(s):  
Ralph Kahn ◽  
Wen-Hao Li ◽  
John V. Martonchik ◽  
Carol J. Bruegge ◽  
David J. Diner ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Near Infrared ◽  
Light Level ◽  
Single Scattering ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Radiometric Calibration ◽  
Low Light ◽  
Vicarious Calibration

Abstract Studying aerosols over ocean is one goal of the Multiangle Imaging Spectroradiometer (MISR) and other spaceborne imaging systems. But top-of-atmosphere equivalent reflectance typically falls in the range of 0.03 to 0.12 at midvisible wavelengths and can be below 0.01 in the near-infrared, when an optically thin aerosol layer is viewed over a dark ocean surface. Special attention must be given to radiometric calibration if aerosol optical thickness, and any information about particle microphysical properties, are to be reliably retrieved from such observations. MISR low-light-level vicarious calibration is performed in the vicinity of remote islands hosting Aerosol Robotic Network (AERONET) sun- and sky-scanning radiometers, under low aerosol loading, low wind speed, relatively cloud free conditions. MISR equivalent reflectance is compared with values calculated from a radiative transfer model constrained by coincident, AERONET-retrieved aerosol spectral optical thickness, size distribution, and single scattering albedo, along with in situ wind measurements. Where the nadir view is not in sun glint, MISR equivalent reflectance is also compared with Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance. The authors push the limits of the vicarious calibration method’s accuracy, aiming to assess absolute, camera-to-camera, and band-to-band radiometry. Patterns repeated over many well-constrained cases lend confidence to the results, at a few percent accuracy, as do additional vicarious calibration tests performed with multiplatform observations taken during the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) campaign. Conclusions are strongest in the red and green bands, but are too uncertain to accept for the near-infrared. MISR nadir-view and MODIS low-light-level absolute reflectances differ by about 4% in the blue and green bands, with MISR reporting higher values. In the red, MISR agrees with MODIS band 14 to better than 2%, whereas MODIS band 1 is significantly lower. Compared to the AERONET-constrained model, the MISR aft-viewing cameras report reflectances too high by several percent in the blue, green, and possibly the red. Better agreement is found in the nadir- and the forward-viewing cameras, especially in the blue and green. When implemented on a trial basis, calibration adjustments indicated by this work remove 40% of a 0.05 bias in retrieved midvisible aerosol optical depth over dark water scenes, produced by the early postlaunch MISR algorithm. A band-to-band correction has already been made to the MISR products, and the remaining calibration adjustments, totaling no more than a few percent, are planned.

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.

Characterization of Bias of Advanced Himawari Imager Infrared Observations from NWP Background Simulations Using CRTM and RTTOV

2016 ◽  
Vol 33 (12) ◽  
pp. 2553-2567 ◽  
Author(s):  
X. Zou ◽  
X. Zhuge ◽  
F. Weng
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Land Surface ◽  
Near Infrared ◽  
Weather Prediction ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Brightness Temperatures ◽  
Emissivity Model ◽  
New Generation

AbstractStarting in 2014, the new generation of Japanese geostationary meteorological satellites carries an Advanced Himawari Imager (AHI) to provide the observations of visible, near infrared, and infrared with much improved spatial and temporal resolutions. For applications of the AHI measurements in numerical weather prediction (NWP) data assimilation systems, the biases of the AHI brightness temperatures at channels 7–16 from the model simulations are first characterized and evaluated using both the Community Radiative Transfer Model (CRTM) and the Radiative Transfer for the TIROS Operational Vertical Sounder (RTTOV). It is found that AHI biases under a clear-sky atmosphere are independent of satellite zenith angle except for channel 7. The biases of three water vapor channels increase with scene brightness temperatures and are nearly constant except at high brightness temperatures for the remaining infrared channels. The AHI biases at all the infrared channels are less than 0.6 and 1.2 K over ocean and land, respectively. The differences in biases between RTTOV and CRTM with the land surface emissivity model used in RTTOV are small except for the upper-tropospheric water vapor channels 8 and 9 and the low-tropospheric carbon dioxide channel 16. Since the inputs used for simulations are the same for CRTM and RTTOV, the differential biases at the water vapor channels may be associated with subtle differences in forward models.

scholarly journals Use of Infrared Satellite Observations for the Surface Temperature Retrieval over Land in a NWP Context

2019 ◽  
Vol 11 (20) ◽  
pp. 2371 ◽  
Author(s):  
Mohamed Zied Sassi ◽  
Nadia Fourrié ◽  
Vincent Guidard ◽  
Camille Birman
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Weather Prediction ◽  
Satellite Observations ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Infrared Sensors ◽  
Diurnal Cycles ◽  
Brightness Temperatures ◽  
Different Seasons

In Numerical Weather Prediction (NWP), an accurate description of surface temperature is needed to assimilate satellite observations. These observations produced by infrared and microwave sensors, help retrieving good quality land surface temperature (LST) by using surface sensitive channels and emissivity atlases. This work is a preparatory step in order to assimilate LSTs in Météo-France NWP models surface analysis. We focus on IASI and SEVIRI sensors. The first part of this work aims at comparing the SEVIRI retrieved LST to local observations from two stations included in the meso-scale AROME-France domain over four periods from different seasons. Diurnal cycles of local LST and SEVIRI LST show a good agreement especially for the summer period. Averaged biases show seasonal variability and are smaller during Winter and Autumn with less than 1 K values for both stations. The second part of the study deals with the comparison of LST values retrieved from different infrared sensors in AROME-France model. First results show encouraging agreement between both LSTs. A comparison during Autumn period for clear sky conditions reveals an almost null bias and a standard deviation of about 1.6 K. More detailed comparisons were performed over contrasted seasons with a special attention to diurnal cycles for both sensors. A better agreement is noticed during nighttime. The last step of this inter-comparison was to study the simulation of SEVIRI and IASI brightness temperatures by using a fast radiative transfer model. Thus, several simulations have been run covering various dates from different seasons by daytime and nighttime using SEVIRI LSTs, IASI LSTs and AROME-France model LSTs. Simulated brightness temperatures were then compared to observations. As expected, the best simulations are the ones using the LST retrieved from the sensor for which simulations are performed. However, the LST retrieved from another sensor provides better simulations than the predicted LST from the model especially during nighttime. For IASI simulations, SEVIRI LSTs increase RMSE by 0.2 K to 0.9 K compared to IASI LSTs for nighttime case and by around 1.5 K for daytime.

scholarly journals Using IASI to simulate the total spectrum of outgoing long-wave radiances

2015 ◽  
Vol 15 (12) ◽  
pp. 6561-6575 ◽  
Author(s):  
E. C. Turner ◽  
H.-T. Lee ◽  
S. F. B. Tett
Keyword(s):  
High Resolution ◽  
Near Infrared ◽  
Spectral Response ◽  
Wave Spectrum ◽  
Radiant Energy ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
High Resolution Spectrum ◽  
Night Time ◽  
Long Wave

Abstract. A new method of deriving high-resolution top-of-atmosphere spectral radiances in 10 181 bands, over the whole outgoing long-wave spectrum of the Earth, is presented. Correlations between different channels measured by the Infrared Atmospheric Sounding Interfermeter (IASI) on the MetOp-A (Meteorological Operation) satellite and unobserved wavenumbers are used to estimate far infrared (FIR) radiances at 0.5 cm−1 intervals between 25.25 and 644.75 cm−1 (the FIR), and additionally between 2760 and 3000 cm−1 (the NIR – near infrared). Radiances simulated by the line-by-line radiative transfer model (LBLRTM) are used to construct the prediction model. The spectrum is validated by comparing the Integrated Nadir Long-wave Radiance (INLR) product spanning the whole 25.25–3000 cm−1 range with the corresponding broadband measurements from the Clouds and the Earth's Radiant Energy System (CERES) instrument on the Terra and Aqua satellites at points of simultaneous nadir overpass. There is a mean difference of 0.3 W m−2 sr−1 (0.5% relative difference). This is well within the uncertainties associated with the measurements made by either instrument. However, there is a noticeable contrast when the bias is separated into night-time and daytime scenes with the latter being significantly larger, possibly due to errors in the CERES Ed3 Spectral Response Functions (SRF) correction method. In the absence of an operational spaceborne instrument that isolates the FIR, this product provides a useful proxy for such measurements within the limits of the regression model it is based on, which is shown to have very low root mean squared errors. The new high-resolution spectrum is presented for global mean clear and all skies where the FIR is shown to contribute 44 and 47% to the total INLR, respectively. In terms of the spectral cloud effect (Cloud Integrated Nadir Long-wave Radiance – CINLR), the FIR contributes 19% and in some subtropical instances appears to be negative; results that would go unobserved with a traditional broadband analysis.

scholarly journals Remote sensing of aerosol properties from multi-wavelength and multi-pixel information over the ocean

2018 ◽  
Author(s):  
Chong Shi ◽  
Makiko Hashimoto ◽  
Teruyuki Nakajima
Keyword(s):  
Remote Sensing ◽  
Spatial Variation ◽  
Optical Thickness ◽  
Measurement Errors ◽  
Near Infrared ◽  
Aerosol Optical Thickness ◽  
Dust Particles ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Satellite Measurements

Abstract. In this study, we investigate the feasibility of multi-pixel scheme in the inversion of aerosol optical thickness (AOT) for multi-spectral satellite instruments over the ocean. Different from the traditional satellite aerosol retrievals conducted pixel by pixel independently, we derive the aerosol optical thickness of multiple pixels simultaneously by adding smoothness constraint on the spatial variation of aerosols and oceanic substances, which helps the satellite retrieval with higher consistency from pixel to pixel. Simulations are performed for two representative oceanic circumstances – open and coastal waters, as well as the land-ocean interface region. We retrieve the AOT for fine, sea spray, and dust particles simultaneously using synthetic spectral measurements from the Greenhouse Gases Observing Satellite/Thermal and Near Infrared Sensor for Carbon Observations-Cloud and Aerosol Imager (GOSAT/TANSO-CAI) with four wavelengths coving from the ultraviolet to shortwave infrared bands. The forward radiation calculation is performed by a coupled atmosphere-ocean radiative transfer model combined with a three-component bio-optical oceanic module, where the chlorophyll a concentration, sediment and colored dissolved organic matter are considered. Results show that accuracies of the derived AOT and spectral remote-sensing reflectance are both improved by applying smoothness constraints on the spatial variation of aerosol and oceanic substances in homogeneous or inhomogeneous surface conditions. The multi-pixel scheme can be effective to compensate the retrieval biases induced by measurement errors and improve the retrieval sensitivity, particularly for the fine aerosol over the coastal water. We then apply the algorithm to derive AOTs using real satellite measurements. Results indicate that the multi-pixel method helps to polish the irregular retrieved results of the satellite imagery and shows promising potentiality to correct the overestimation of aerosols over high turbid waters, by benefiting from the coincident retrieval of neighboring pixels. A comparison of retrieved AOTs from satellite measurements with those from the Aerosol Robotic Network (AERONET) also indicates that retrievals conducted by the multi-pixel scheme are more consistent with the AERONET observations.

scholarly journals Mineralogical and chemical properties inversed from 21-lunar-day VNIS observations taken during the Chang’E-4 mission

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qinghong Zeng ◽  
Shengbo Chen ◽  
Yuanzhi Zhang ◽  
Yongling Mu ◽  
Rui Dai ◽  
...  
Keyword(s):  
Impact Crater ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Chemical Properties ◽  
Landing Site ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Chemical Compositions ◽  
Impact Melt ◽  
And Chemical Properties

AbstractWe report on the mineralogical and chemical properties of materials investigated by the lunar rover Yutu-2, which landed on the Von Kármán crater in the pre-Nectarian South Pole–Aitken (SPA) basin. Yutu-2 carried several scientific payloads, including the Visible and Near-infrared Imaging Spectrometer (VNIS), which is used for mineral identification, offering insights into lunar evolution. We used 86 valid VNIS data for 21 lunar days, with mineral abundance obtained using the Hapke radiative transfer model and sparse unmixing algorithm and chemical compositions empirically estimated. The mineralogical properties of the materials at the Chang’E-4 (CE-4) site referred to as norite/gabbro, based on findings of mineral abundance, indicate that they may be SPA impact melt components excavated by a surrounding impact crater. We find that CE-4 materials are dominated by plagioclase and pyroxene and feature little olivine, with 50 of 86 observations showing higher LCP than HCP in pyroxene. In view of the effects of space weathering, olivine content may be underestimated, with FeO and TiO2 content estimated using the maturity-corrected method. Estimates of chemical content are 7.42–18.82 wt% FeO and 1.48–2.1 wt% TiO2, with a low-medium Mg number (Mg # ~ 55). Olivine-rich materials are not present at the CE-4 landing site, based on the low-medium Mg #. Multi-origin materials at the CE-4 landing site were analyzed with regard to concentrations of FeO and TiO2 content, supporting our conclusion that the materials at CE-4 do not have a single source but rather are likely a mixture of SPA impact melt components excavated by surrounding impact crater and volcanic product ejecta.

scholarly journals A Satellite-Based Assessment of Upper-Tropospheric Water Vapor Measurements during AFWEX

2009 ◽  
Vol 48 (11) ◽  
pp. 2284-2294 ◽  
Author(s):  
Eui-Seok Chung ◽  
Brian J. Soden
Keyword(s):  
Water Vapor ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Raman Lidar ◽  
Test Bed ◽  
Upper Troposphere ◽  
Brightness Temperatures ◽  
Radiation Test ◽  
Humidity Measurements ◽  
Atmospheric Radiation Measurement

Abstract Consistency of upper-tropospheric water vapor measurements from a variety of state-of-the-art instruments was assessed using collocated Geostationary Operational Environmental Satellite-8 (GOES-8) 6.7-μm brightness temperatures as a common benchmark during the Atmospheric Radiation Measurement Program (ARM) First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Water Vapor Experiment (AFWEX). To avoid uncertainties associated with the inversion of satellite-measured radiances into water vapor quantity, profiles of temperature and humidity observed from in situ, ground-based, and airborne instruments are inserted into a radiative transfer model to simulate the brightness temperature that the GOES-8 would have observed under those conditions (i.e., profile-to-radiance approach). Comparisons showed that Vaisala RS80-H radiosondes and Meteolabor Snow White chilled-mirror dewpoint hygrometers are systemically drier in the upper troposphere by ∼30%–40% relative to the GOES-8 measured upper-tropospheric humidity (UTH). By contrast, two ground-based Raman lidars (Cloud and Radiation Test Bed Raman lidar and scanning Raman lidar) and one airborne differential absorption lidar agree to within 10% of the GOES-8 measured UTH. These results indicate that upper-tropospheric water vapor can be monitored by these lidars and well-calibrated, stable geostationary satellites with an uncertainty of less than 10%, and that correction procedures are required to rectify the inherent deficiencies of humidity measurements in the upper troposphere from these radiosondes.

Consistent retrieval of cloud/aerosol single scattering properties and surface reflectance

2021 ◽  
Author(s):  
Marta Luffarelli ◽  
Yves Govaerts
Keyword(s):  
Radiative Transfer ◽  
Optical Thickness ◽  
Solution Space ◽  
Single Scattering ◽  
Aerosol Optical Thickness ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Surface Reflectance ◽  
Earth System ◽  
System Components

<p>The CISAR (Combined Inversion of Surface and AeRosols) algorithm is exploited in the framework of the ESA Aerosol Climate Change Initiatiave (CCI) project, aiming at providing a set of atmospheric (cloud and aerosol) and surface reflectance products derived from S3A/SLSTR observations using the same radiative transfer physics and assumptions. CISAR is an advance algorithm developed by Rayference originally designed for the retrieval of aerosol single scattering properties and surface reflectance from both geostationary and polar orbiting satellite observations.  It is based on the inversion of a fast radiative transfer model (FASTRE). The retrieval mechanism allows a continuous variation of the aerosol and cloud single scattering properties in the solution space.</p><p> </p><p>Traditionally, different approaches are exploited to retrieve the different Earth system components, which could lead to inconsistent data sets. The simultaneous retrieval of different atmospheric and surface variables over any type of surface (including bright surfaces and water bodies) with the same forward model and inversion scheme ensures the consistency among the retrieved Earth system components. Additionally, pixels located in the transition zone between pure clouds and pure aerosols are often discarded from both cloud and aerosol algorithms. This “twilight zone” can cover up to 30% of the globe. A consistent retrieval of both cloud and aerosol single scattering properties with the same algorithm could help filling this gap.</p><p> </p><p>The CISAR algorithm aims at overcoming the need of an external cloud mask, discriminating internally between aerosol and cloud properties. This approach helps reducing the overestimation of aerosol optical thickness in cloud contaminated pixels. The surface reflectance product is delivered both for cloud-free and cloudy observations.  </p><p> </p><p>Global maps obtained from the processing of S3A/SLSTR observations will be shown. The SLSTR/CISAR products over events such as, for instance, the Australian fire in the last months of 2019, will be discussed in terms of aerosol optical thickness, aerosol-cloud discrimination and fine/coarse mode fraction.</p>

scholarly journals Comparison of measured brightness temperatures from SMOS with modelled ones from ORCHIDEE and H-TESSEL over the Iberian Peninsula

2015 ◽  
Vol 12 (12) ◽  
pp. 13019-13067
Author(s):  
A. Barella-Ortiz ◽  
J. Polcher ◽  
P. de Rosnay ◽  
M. Piles ◽  
E. Gelati
Keyword(s):  
Soil Moisture ◽  
Radiative Transfer ◽  
Iberian Peninsula ◽  
Land Surface ◽  
Function Analysis ◽  
Microwave Emission ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Brightness Temperatures

Abstract. L-Band radiometry is considered to be one of the most suitable techniques to estimate surface soil moisture by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm. The work exposed compares brightness temperatures measured by the Soil Moisture and Ocean Salinity (SMOS) mission to two different sets of modelled ones, over the Iberian Peninsula from 2010 to 2012. The latter were estimated using a radiative transfer model and state variables from two land surface models: (i) ORganising Carbon and Hydrology In Dynamic EcosystEms (ORCHIDEE) and (ii) Hydrology – Tiled ECMWF Scheme for Surface Exchanges over Land (H-TESSEL). The radiative transfer model used is the Community Microwave Emission Model (CMEM). A good agreement in the temporal evolution of measured and modelled brightness temperatures is observed. However, their spatial structures are not consistent between them. An Empirical Orthogonal Function analysis of the brightness temperature's error identifies a dominant structure over the South-West of the Iberian Peninsula which evolves during the year and is maximum in Fall and Winter. Hypotheses concerning forcing induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for it at the moment. Further hypotheses are proposed at the end of the paper.

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