Global Space-based Inter-Calibration System Research Articles

Characterization of the East—West Spatial Uniformity for GOES-16/17 ABI Bands Using the Moon

The Advanced Baseline Imager (ABI) is the primary instrument onboard the NOAA Geostationary Operational Environmental Satellite-R Series (GOES-R) satellites, providing continuous weather imagery over the vast area in the Western Hemisphere. It is imperative to ensure consistent calibration accuracy within the instrument’s field of regard (FOR). This paper characterized the spatial uniformity in the east–west (EW) direction for the six ABI visible and near-infrared (VNIR) bands of the first two GOES-R satellites, GOES-16 (G16) and GOES-17 (G17), using a special collection of lunar chasing images during their post-launch testing and post-launch product testing (PLT/PLPT) periods. The EW response versus scan-angle (RVS) is examined with the normalized lunar irradiance ratios at varying scan angles combined from multiple lunar-chasing events. The impacts of straylight from the Earth were found in some of the B01–B03 lunar images. The straylight, including those scattered into the spacelook scenes near the polar regions and those leaked into space near the Moon, can cause RVS variation up to 1% for B01 and to a lesser magnitude for the other two bands. Straylight correction algorithms are applied for the accurate ABI lunar image irradiance calculation. After the corrections, the RVS variation is reduced to less than 0.3% for all the VNIR bands of both G16/17 in full-disk (FD) images. Results of this study also confirm that the Global Space-based Inter-Calibration System (GSICS) Implementation of the ROLO (GIRO) model has high relative accuracy for the ABI VNIR bands when the lunar images are collected within a relatively short time. The method described in this paper can be applied to validate the EW spatial uniformity for imagers on other geostationary satellites, including the recently launched GOES-18 and the future GOES-U satellites.

High-resolution outgoing long wave radiation data (2014–2020) of INSAT-3D Imager and its comparison with Clouds and Earth’s Radiant Energy System (CERES) data

As a proxy of convection INSAT-3D satellite-derived product Outgoing Long Wave Radiation (OLR) data is available in both high temporal and spatial ranges over 40°N–40°S & 35°E–135°E. Daily gridded data set of 7 years of data (2014–2020) has been generated at 10 km × 10 km resolution and the same is compared with Clouds and Earth’s Radiant Energy System (CERES) instrument data taken from CERES as reference. Almost all the INSAT-3D data set generated is Global Space-based Inter-Calibration System (GSICS) corrected. The spatiotemporal consistency of the data set was statistically analyzed and found to be reasonably good agreement having a bias of ∼±5–6 W/m2 over above said domain.This inter-comparison is essential to get confidence in the data sets and release it further in the public domain for any scientific study. Again, this data set will be very useful in diagnosing the variations of convection at different scales (daily, weekly, monthly, annual, seasonal, intra-seasonal, etc.) & an important repository of Daily Climate Data Records (DCDR) for future studies. The specified domain of the present study is affected throughout the year with variable (weak, moderate, intense, or severe) spatiotemporal Inter-Tropical Convergence Zone (ITCZ) convection streams due to different types of weather activities (winter, pre-monsoon, monsoon, and post-monsoon) throughout the year. To visualize the importance of this high-resolution OLR data set a case study of Cyclone Amphan and Vayu is presented. The extremely severe intense convection (OLR departure −112 W/m2 with INSAT-3D new data set whereas −104 W/m2 in CERES data) was observed in both the data sets on 18th May-2020 at 13.7–16°N & 86.2–86.8°E during the super cyclonic stage of Amphan. A similar type of variation in the OLR has been noticed for Vayu Cyclone (OLR departure −94 W/m2 with INSAT-3D new data set whereas −86 W/m2 in CERES data). This information is very useful in impact-based forecasting and further future actions for disaster managers/decision-makers. The localized convective features during cyclone activity over the Indian Ocean region both in the Arabian Sea and the Bay of Bengal are well captured with this new data set and the difference in OLR of INSAT -3D and CERES -9 W/m2 and -12 W/m2 respectively.

Introduction of the Advanced Meteorological Imager of Geo-Kompsat-2a: In-Orbit Tests and Performance Validation

Geo-Kompsat-2A (Geostationary-Korean Multi-Purpose SATtellite-2A, GK2A), a new generation of Korean geostationary meteorological satellite, carry state-of-the-art optical sensors with significantly higher radiometric, spectral, and spatial resolution than the Communication, Ocean, and Meteorological Satellite (COMS) previously available in the geostationary orbit. The new Advanced Meteorological Imager (AMI) on GK2A has 16 observation channels, and its spatial resolution is 0.5 or 1 km for visible channels and 2 km for near-infrared and infrared channels. These advantages, when combined with shortened revisit times (around 10 min for full disk and 2 min for sectored regions), provide new levels of capacity for the identification and tracking of rapidly changing weather phenomena and for the derivation of quantitative products. These improvements will bring about unprecedented levels of performance in nowcasting services and short-range weather forecasting systems. Imagery from the satellites is distributed and disseminated to users via multiple paths, including internet services and satellite broadcasting services. In post-launch performance validation, infrared channel calibration is accurate to within 0.2 K with no significant diurnal variation using an approach developed under the Global Space-based Inter-Calibration System framework. Visible and near infrared channels showed unexpected seasonal variations of approximately 5 to 10% using the ray matching method and lunar calibration. Image navigation was accurate to within requirements, 42 µrad (1.5 km), and channel-to-channel registration was also validated. This paper describes the features of the GK2A AMI, GK2A ground segment, and data distribution. Early performance results of AMI during the commissioning period are presented to demonstrate the capabilities and applications of the sensor.

S-NPP VIIRS Day Night Band On-Board Solar Diffuser Calibration Validation Using the Scheduled Lunar Collections

Similar to the Reflective Solar Band (RSB) calibration, Suomi-National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) on-board calibration of Day Night Band (DNB) is based on the Solar Diffuser (SD) observations in the Low Gain State (LGS). DNB has a broad spectral response covering a wavelength range roughly from 500 nm to 900 nm with a large dynamic range from three different gain states called High Gain State (HGS), Mid Gain State (MGS), and LGS. The calibration of MGS and HGS is also dependent on the LGS gain estimation with the gain ratios for each gain state. Over the lifetime of S-NPP VIIRS operations, the LGS gains have been derived from the on-board SD observations since its launch in October 2011. In this study, the lifetime LGS gains are validated by the lunar calibration coefficients (defined as F-factors) using a lunar irradiance model called Global Space-based Inter-Calibration System (GSICS) Implementation of RObotic Lunar Observatory (ROLO) (GIRO). Using the moon as an independent on-orbit calibration source, the S-NPP VIIRS DNB on-board SD based radiometric calibration is validated by the lunar F-factors within two percent of the lunar F-factors in terms of the standard deviation in the long-term trends over nine years of the S-NPP VIIRS operation.

Evaluation of GSICS Correction for COMS/MI Visible Channel Using S-NPP/VIIRS

The Global Space-based Inter-Calibration System (GSICS) is an international partnership sponsored by World Meteorological Organization (WMO) to continue and improve climate monitoring and to ensure consistent accuracy between observation data from meteorological satellites operating around the world. The objective for GSICS is to inter-calibration from pairs of satellites observations, which includes direct comparison of collocated Geostationary Earth Orbit (GEO)-Low Earth Orbit (LEO) observations. One of the GSICS intercalibration methods, the Ray-matching technique, is a surrogate approach that uses matched, co-angled and colocated pixels to transfer the calibration from a well calibrated satellite sensor to another sensor. In Korea, the first GEO satellite, Communication Ocean and Meteorological Satellite (COMS), is used to participate in the GSICS program. The National Meteorological Satellite Center (NMSC), which operated COMS/MI, calculated the Radiative Transfer Model (RTM)-based GSICS coefficient coefficients. The L1P reproduced through GSICS correction coefficient showed lower RMSE and Bias than L1B without GSICS correction coefficient applied. The calculation cycles of the GSICS correction coefficients for COMS/MI visible channel are provided annual and diurnal (2, 5, 10, 14-day), but long-term evaluation according to these cycles was not performed. The purpose of this paper is to perform evaluation depending on the annual/diurnal cycles of COMS/MI GSICS correction coefficients based on the ray-matching technique using Suomi-NPP/Visible Infrared Imaging Radiometer Suite (VIIRS) data as reference data. As a result of evaluation, the diurnal cycle had a higher coincidence rate with the reference data than the annual cycle, and the 14-day diurnal cycle was the most suitable for use as the GSICS correction coefficient.

Extending the Global Space-Based Inter-Calibration System (GSICS) to Tie Satellite Radiances to an Absolute Scale

The Global Space-based Inter-Calibration System (GSICS) routinely monitors the calibration of various channels of Earth-observing satellite instruments and generates GSICS Corrections, which are functions that can be applied to tie them to reference instruments. For the infrared channels of geostationary imagers GSICS algorithms are based on comparisons of collocated observations with hyperspectral reference instruments; whereas Pseudo Invariant Calibration Targets are currently used to compare the counterpart channels in the reflected solar band to multispectral reference sensors. This paper discusses how GSICS products derived from both approaches can be tied to an absolute scale using specialized satellite reference instruments with SI-traceable calibration on orbit. This would provide resilience against gaps between reference instruments and drifts in their calibration outside their overlap period and allow construction of robust and harmonized data records from multiple satellite sources to build Fundamental Climate Data Records, as well as more uniform environmental retrievals in both space and time, thus improving inter-operability.

Development of a Methodology to Generate In-Orbit Electrooptical Module Temperature-Based Calibration Coefficients for INSAT-3D/3DR Infrared Imager Channels

It has been observed that the lab-based calibration coefficients of a satellite instrument differ in the actual in-orbit operation due to different environmental conditions. The lab-based coefficients are measured when all the components of the satellite instrument are in thermal equilibrium, while during in-orbit operations, there may be significant variations in temperature between various components as well as the diurnal temperature gradients of subsystems, especially in the geostationary platform due to midnight sunray intrusion. This article proposes a new technique to measure the in-orbit calibration coefficients using the collocated matchup data at different electrooptical module temperatures of the INSAT-3D/3DR imager counts and hyperspectral sounder radiances such as Advanced InfraRed Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) that are considered as the reference instruments. The radiances generated by new calibration coefficients show less bias and standard deviations for all infrared (IR) channels of INSAT-3D and INSAT-3DR when compared with the convolved radiances generated from the AIRS and IASI radiances using the procedure established by the Global Space-based Intercalibration System (GSICS).

Intercalibration of FY-3C MWRI Against GMI Using the Ocean Microwave Radiative Transfer Model

This work addresses the intercalibration of the Microwave Radiation Imager (MWRI) on the Chinese second-generation polar-orbiting meteorological satellite Fengyun 3C (FY-3C) against the Microwave Imager (GMI) on the Global Precipitation Measurement (GPM) Core Observatory , in which a modified Double Difference (DD) method is developed and the Brightness Temperatures (TBs) in FY-3C MWRI and GMI channels are simulated using the ocean microwave Radiative Transfer Model (RTM) fed with the fifth generation of European Centre for Medium-range Weather Forecast (ECMWF) atmospheric reanalysis (ERA5) data. With the modified DD method, the intercalibration of FY-3C MWRI in 2017 are obtained. The results show that the MWRI observations are underestimated, especially for the low frequency channels. The calibration biases (mean of DDs) in FY-3C MWRI channels are temperature dependent, and decrease with the frequency increment. The in-orbit calibration of the MWRI descending (MWRID) data is 1~2 K worse than that of the MWRI ascending (MWRIA) data. At the TBs of standard scene defined by the Global Space-based Inter-Calibration System (GSICS), the calibration errors (mean of DDs ± standard deviation at the mean) of MWRIA data in January 2017 are −6.7±0.4 K, −8.3±0.8 K, −3.0±0.7 K, −1.9±1.0 K, −2.5±1.1 K, −3.9±0.8 K, −2.1±1.5 K, −1.5±1.0 K and −0.4±2.3 K in the 10V/H, 18V/H, 23V, 36V/H and 89V/H channels, respectively, while the calibration errors of MWRID data in January 2017 are −7.6±0.8 K, −9.1±1.2 K, −4.4±0.8 K, −2.9±1.3 K, −3.6±1.2 K, −5.1±0.8 K, −2.6±1.4 K, −2.5±1.1 K and −1.2±2.5 K in the nine channels, respectively. Although calibration biases exist, the in-orbit calibration of FY-3C MWRI is generally stable in 2017. The results of the modified DD method are consistent with that of the DD method. The modified DD method is promising to be applied to the intercalibration with both target and reference radiometers on polar-orbiting satellites.

Radiometric Model and Inter-Comparison Results of the SGLI-VNR On-Board Calibration

The Second Generation Global Imager (SGLI) on Global Change Observation Mission–Climate (GCOM-C) satellite empowers surface and atmospheric measurements related to the carbon cycle and radiation budget, with two radiometers of Visible and Near Infrared Radiometer (SGLI-VNR) and Infrared Scanning Radiometer (SGLI-IRS) that perform a wide-band (380 nm–12 µm) optical observation not only with as wide as a 1150–1400 km field of view (FOV), but also with as high as 0.25–0.5 km resolution. Additionally, polarization and along-track slant view observations are quite characteristic of SGLI. It is important to calibrate radiometers to provide the sensor data records for more than 28 standard products and 23 research products including clouds, aerosols, ocean color, vegetation, snow and ice, and other applications. In this paper, the radiometric model and the first results of on-board calibrations on the SGLI-VNR, which include weekly solar and light-emitting diode (LED) calibration and monthly lunar calibration, will be described. Each calibration data was obtained with corrections, where beta angle correction and avoidance of reflection from multilayer insulation (MLI) were applied for solar calibration; LED temperature correction was performed for LED calibration; and the GIRO (GSICS (Global Space-based Inter-Calibration System) Implementation of the ROLO (RObotic Lunar Observatory) model) model was used for lunar calibration. Results show that the inter-comparison of the relative degradation amount between these three calibrations agreed to within 1% or less.

Recalibration of over 35 Years of Infrared and Water Vapor Channel Radiances of the JMA Geostationary Satellites

Infrared sounding measurements of the Infrared Atmospheric Sounding Interferometer (IASI), Atmospheric Infrared Sounder (AIRS), and High-resolution Infrared Radiation Sounder/2 (HIRS/2) instruments are used to recalibrate infrared (IR; ~11 µm) channels and water vapor (WV; ~6 µm) channels of the Visible and Infrared Spin Scan Radiometer (VISSR), Japanese Advanced Meteorological Imager (JAMI), and IMAGER instruments onboard the historical geostationary satellites of the Japan Meteorological Agency (JMA). The recalibration was performed using a common recalibration method developed by European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), which can be applied to the historical geostationary satellites to produce Fundamental Climate Data Records (FCDR). Pseudo geostationary imager radiances were computed from the infrared sounding measurements and regressed against the radiances from the geostationary satellites. Recalibration factors were computed from these pseudo imager radiance pairs. This paper presents and evaluates the result of recalibration of longtime-series of IR (1978–2016) and WV (1995–2016) measurements from JMA’s historical geostationary satellites. For the IR data of the earlier satellites (Geostationary Metrological Satellite (GMS) to GMS-4) significant seasonal variations in radiometric biases were observed. This suggests that the sensors on GMS to GMS-4 were strongly affected by seasonal variations in solar illumination. The amplitudes of these seasonal variations range from 3 K for the earlier satellites to <0.4 K for the recent satellites (GMS-5, Geostationary Operational Environmental Satellite-9 (GOES-9), Multi-functional Transport Satellite-1R (MTSAT-1R) and MTSAT-2). For the WV data of GOES-9, MTSAT-1R and MTSAT-2, no seasonal variations in radiometric biases were observed. However, for GMS-5, the amplitude of seasonal variation in bias was about 0.5 K. Overall, the magnitude of the biases for GMS-5, MTSAT-1R and MTSAT-2 were smaller than 0.3 K. Finally, our analysis confirms the existence of errors due to atmospheric absorption contamination in the operational Spectral Response Function (SRF) of the WV channel of GMS-5. The method used in this study is based on the principles developed within Global Space-based Inter-calibration System (GSICS). Moreover, presented results contribute to the Inter-calibration of imager observations from time-series of geostationary satellites (IOGEO) project under the umbrella of the World Meteorological Organization (WMO) initiative Sustained and Coordinated Processing of Environmental Satellite data for Climate Monitoring (SCOPE-CM).

Cross-Track Infrared Sounder Spectral Gap Filling Toward Improving Intercalibration Uncertainties

The cross-track infrared sounder (CrIS) is a hyper-spectral infrared sounder with 2211 (full-spectral resolution) channels over three wavelength ranges. Due to its excellent calibration and high spectral resolution, CrlS radiances are also used as an infrared reference to check calibration accuracy of other narrow- or broadband instruments. However, there are spectral gaps between the CrlS bands, which impact the accuracy of intercomparison between CrlS and other instruments. To fill up the spectral gaps, this paper develops a new method to predict the CrlS gap channels. A training data set was first built based on the spectra selected from different seasons to represent different atmospheric and surface conditions. The principal component regression method is then developed to derive the prediction coefficients between the CrlS measured and the gap channel spectra. The prediction accuracies are around 0.005 K ± 0.18 mK, 0.06 K ± 0.45 mK, and 0.05 K ± 0.71 mK for the long-, middle-, and short-wave gap channels, respectively. It should note that the predicted channels are intended to be only used in the intercomparison purposes instead of providing exact information of these gap channels. When comparing the CrlS gap radiances with atmospheric infrared sounder and infrared atmospheric sounding interferometer, consistent results are observed between CrIS and other sounders. The further intercomparison results with visible infrared imaging radiometer suite and advanced baseline imager suggest that the predicted gap radiances are good enough for the intercalibration purposes and this method can be confidently applied in global space-based intercalibration system community.

On-orbit radiometric calibration of Suomi NPP VIIRS reflective solar bands using the Moon and solar diffuser.

Radiometric calibration of the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (VIIRS) reflective solar bands relies mainly on the onboard solar diffuser (SD) observations. The SD reflectance degrades over time due to the exposure to solar ultraviolet radiation. The uncertainties embedded in characterizing the SD bidirectional reflectance distribution function (BRDF) directly affect the accuracy of sensor radiometric calibration coefficients, such as F-factors, which are proxies of detector gain. The Moon-based radiometric calibration provides an independent way of validating and correcting the SD-based calibration. This study focuses on the comparison of the long-term SD F-factors with lunar F-factors by using two independent lunar irradiance models, i.e., Miller and Turner (MT) model and the Global Space-based Inter-Calibration System Implementation of ROLO (GIRO) model. To monitor the long-term detector response changes, the lunar F-factor differences are matched to the SD F-factors by applying the best fit scaling factors. Overall, the two lunar F-factors agree well, within 2% of one sigma standard deviation in the reflective solar bands compared to the SD F-factors. The lifetime standard deviations of difference between the GIRO-based lunar and SD F-factors show better long-term match than that of MT-based lunar F-factors. The GIRO-based lunar F-factors show increasing differences over time in comparison with the SD F-factors especially for bands M1 to M4, which indicates the underestimation of the VIIRS detector degradation by SD F-factors for these bands. Using standard SD calibration method and the GIRO-based lunar model, long-term difference between the lunar and SD F-factors shows there are 1.6%, 1.3%, 1.0%, and 0.9% increases in lunar F-factor trend for bands M1 to M4 at the end of year 2015. To mitigate these time-dependent biases, NOAA Ocean Color (OC) group and NASA VIIRS characterization support team (VCST) developed lunar correction methods and applied them to their specific products. However, the amounts of band-dependent lunar corrections are not consistent between these two teams, especially in the short-wavelength bands from M1 to M4, depending on the versions of lunar models and SD F-factor calculation algorithms. Using the standard SD F-factor algorithm and the multi-agency endorsed GIRO model, we derived lunar correction factors based on the quadratic fits between the SD and lunar F-factors. The differences with the NOAA OC group and NASA VCST team are compared and described in this study.

Potential of INSAT-3D sounder-derived total precipitable water product for weather forecast

Abstract. The objectives of the INSAT-3D satellite are to enhance the meteorological observations and to monitor the Earth's surface for weather forecasting and disaster warning. One of the weather-monitoring capabilities of the INSAT-3D sounder is the estimation of water vapour in the atmosphere. The amount of water vapour present in the atmospheric column is derived as the total precipitable water (TPW) product from the infrared radiances measured by the INSAT-3D sounder. The present study is based on TPW derived from INSAT-3D sounder, radiosonde (RS) observations and the corresponding National Oceanic and Atmospheric Administration (NOAA) satellite. To assess retrieval performances of INSAT-3D sounder-derived TPW, RS TPW observations are considered for the validation from May to September 2016 from 34 stations belonging to the India Meteorological Department (IMD). The analysis is performed on daily, monthly, and subdivisional bases over the Indian region. The comparison of INSAT-3D TPW with RS TPW on daily and monthly bases shows that the root mean square error (RMSE) and correlation coefficients (CC) are ∼8 mm and 0.8, respectively. However, on subdivisional and overall scales, the RMSE found to be in the range of 1 to 2 mm and CC was around 0.9 in comparison with RS and NOAA. The spatial distribution of INSAT-3D TPW with actual rainfall observation is also investigated. In general, INSAT-3D TPW corresponds well with rainfall observation; however, it has found that heavy rainfall events occur in the presence of high TPW values. In addition, the cases of thunderstorm events were assessed using TPW from INSAT-3D and network of Global Navigation Satellite System (GNSS) receiver. This shows the good agreement between TPW from INSAT-3D and GNSS during the mesoscale activity. The improvement in the estimation of TPW is carried out by applying the GSICS calibration corrections (Global Space-based Inter-Calibration System) to the radiances from infrared (IR) channels of the sounder, which is used by IMDPS (INSAT Meteorological Data Processing System). The current TPW from INSAT-3D satellite can be utilized operationally for weather monitoring and forecast purposes. It can also offer substantial opportunities for improvement in nowcasting studies.

COMS Visible Channel Calibration Using Moon Observation Data

COMS (Communication, Ocean, and Meteorological Satellite) has been in operation since April 2011. The COMS MI (Meteorological Imager) has one visible and four infrared channels. Through the use of the GSICS (Global Space-based Inter-Calibration System), the KMA (Korea Meteorological Administration) has monitored the radiometric performance of the COMS visible channel through its own calibration system and the use of four different earth targets: ocean, desert, water cloud, and DCC (Deep Convective Cloud). To use the invariant target of the Moon, the KMA adopted GIRO (GSICS Implementation of the ROLO (Robotic Lunar Observatory) model), which was released by EUMETSAT. In this study, a total of 146 lunar observation data (Level 1A) with various phase angles obtained between April 2011 and December 2017 are analyzed. A degradation rate of approximately −1.52 ± 0.10% per year occurred using the GIRO method, which was a degradation of approximately 12% over the eight years (from 2011 to 2018) during COMS MI’s operational period. The lunar calibration result was in good agreement with results provided by other calibration methods such as the DCC using the RTM (Radiative Transfer Model), which was approximately −1.43 ± 0.13% per year. Selection of on-Moon pixels provided an uncertainty of approximately 0.01% per year, while that related to the phase angle (Sun-Moon-Satellite) was approximately 0.06% per year.

Improved Spatial Collocation and Parallax Correction Approaches for Calibration Accuracy Validation of Thermal Emissive Band on Geostationary Platform

Calibration accuracy validation (CAV) can usually be realized by intercalibration between different satellites. Under the framework of Global Space-Based Intercalibration System (GSICS), two modifications, improved spatial collocation with variable weighting (VW) and parallax correction (PC) approaches, to enhance the CAV performance are proposed. Distinguished from the uniform weighting method recommended by GSICS, the proposed VW one establishes a novel way of overlapping identification and overlapping area computation that is widely suitable for measurements from both the same and different platforms. Simulations indicate that the uncertainty of the VW method behaves better for the collocated targets far away from satellite’s nadir with a certain geolocation error, and is superior to 0.6 K for most overlapping situations when the geolocation error is less than 0.5 pixels. Case application shows that the VW method can significantly alleviate the uncertainty of assessed biases in brightness temperature (BT) by around 0.1–0.3 K for target nonuniformity larger than 2.5%, where the optimal bias estimation can be implemented with its uncertainty as little as possible. Besides the uncertainty improvement, the PC approach has the capability to reduce the bias of CAV by around 0.2–0.3 K, especially for BT range lower than 220 K with a limited number of paired samples. Long-term results show that the monthly biases of FY-2E and FY-2G satellites were superior to 1.5 and 1.0 K, respectively, where the mean monthly absolute biases of FY-2G IR1-IR3 bands were 0.4, 0.6, and 0.5 K, respectively. The proposed VW and PC methods are recommended for GSICS utilization and will further benefit to a more comprehensive community.

Improvements in the On-Orbit Response Versus Scan Angle Characterization of the Aqua MODIS Reflective Solar Bands

The Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) has been chosen by the Global Space-based Inter-Calibration System operational community as the reference sensor in cross-sensor calibration. A number of geostationary orbit and low-earth orbit sensors use the 0.64- $\mu \text{m}$ band from Aqua MODIS as a calibration reference. After over 15 years on-orbit, the performance characteristics of the MODIS instrument have changed, with effects evident at short wavelengths. MODIS employs a reflectance-based calibration using the solar diffuser measurements with the monthly lunar observations facilitating a response versus scan angle characterization on-orbit. As the instrument continues to operate beyond its design lifetime of 6 years, the on-board calibrators alone are insufficient to accurately characterize the instrument’s response at all scan angles. This results in a long-term reflectance drift, particularly observed in the 0.64- and 0.85- $\mu \text{m}$ bands, while observing the temporally invariant desert sites. Long-term reflectance drifts of up to 2% and 3% are observed at the beginning of scan for the 0.64- and 0.85- $\mu \text{m}$ bands, respectively. An approach using earth-view response to supplement the on-board calibrator measurements has been shown to overcome these inadequacies and is now implemented for the 0.64-, 0.85-, 0.46-, and 0.55- $\mu \text{m}$ land bands of Aqua MODIS. This paper presents the details related to the algorithm implementation and an independent evaluation using the Dome Concordia site and deep-convective clouds. This approach has been reviewed, tested, and approved by the MODIS science team and has been implemented in the forward production of the MODIS L1B Collection 6 starting July 9, 2016. This enhanced approach has also been adopted in the MODIS L1B Collection 6.1 reprocess for the entire mission to facilitate an improved quality of downstream science products. The results with the enhanced approach reduce the reflectance drifts to within 0.5% for most cases.

Multi-Instrument Inter-Calibration (MIIC) System

In order to have confidence in the long-term records of atmospheric and surface properties derived from satellite measurements it is important to know the stability and accuracy of the actual radiance or reflectance measurements. Climate quality measurements require accurate calibration of space-borne instruments. Inter-calibration is the process that ties the calibration of a target instrument to a more accurate, preferably SI-traceable, reference instrument by matching measurements in time, space, wavelength, and view angles. A major challenge for any inter-calibration study is to find and acquire matched samples from within the large data volumes distributed across Earth science data centers. Typically less than 0.1% of the instrument data are required for inter-calibration analysis. Software tools and networking middleware are necessary for intelligent selection and retrieval of matched samples from multiple instruments on separate spacecraft. This paper discusses the Multi-Instrument Inter-Calibration (MIIC) system, a web-based software framework used by the Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder mission to simplify the data management mechanics of inter-calibration. MIIC provides three main services: (1) inter-calibration event prediction; (2) data acquisition; and (3) data analysis. The combination of event prediction and powerful server-side functions reduces the data volume required for inter-calibration studies by several orders of magnitude, dramatically reducing network bandwidth and disk storage needs. MIIC provides generic retrospective analysis services capable of sifting through large data volumes of existing instrument data. The MIIC tiered design deployed at large institutional data centers can help international organizations, such as Global Space Based Inter-Calibration System (GSICS), more efficiently acquire matched data from multiple data centers. In this paper we describe the MIIC architecture and services.

Inter-comparison of the infrared channels of the meteorological imager onboard COMS and hyperspectral IASI data

The successful launch and commissioning of the first geostationary meteorological satellite of Korea has the potential to enhance earth observation capability over the Asia Pacific region. Although the specifications of the payload, the meteorological imager (MI), have been verified during both ground and in-orbit tests, there is the possibility of variation and/or degradation of data quality due to many different reasons, such as the accumulation of contaminants, the aging of instrument components, and unexpected external disturbance. Thus, for better utilization of MI data, it is imperative to continuously monitor and maintain the data quality. As a part of such activity, this study presents an inter-calibration, based on the Global Space-based Inter-Calibration System (GSICS), between the MI data and the high quality hyperspectral data from the Infrared Atmospheric Sounding Interferometer (IASI) of the Metop-A satellite. Both sets of data, acquired for three years from April 2011 to March 2014, are processed to prepare the matchup dataset, which is spatially collocated, temporally concurrent, angularly coincident, and spectrally comparable. The results show that the MI data are stable within the specifications and show no significant degradation during the study period. However, the water vapor channel shows a rather large bias value of −0.77 K, with a root-mean-square difference (RMSD) of around 1.1 K, which is thought to be due to the shift in the spectral response function. The shortwave channel shows a maximum RMSD of around 1.39 K, mainly due to the coarse digitization at the lower temperature. The inter-comparison results are re-checked through a sensitivity analysis with different sets of threshold values used for the matchup dataset. Based on this, we confirm that the overall quality of the MI data meets the user requirements and maintains the expected performance, although the water vapor channel requires further investigation.

Effects of GSICS correction on estimation of sea surface temperature using COMS data

A main objective of the Global Space-Based Inter-Calibration System (GSICS) is to ensure consistent accuracy of thermal infrared (IR) channels of satellite measurements. In this article, IR channels observed by the Communication, Ocean, and Meteorological Satellite (COMS) were corrected using observations by the Infrared Atmospheric Sounding Interferometer (IASI) on board Meteorological Operation (MetOp) satellites as a reference. We then produced sea surface temperature (SST) products using GSICS-corrected COMS/Meteorological Imager (MI) IR data and evaluated the accuracies of the SST data by comparing with buoy data. Our results showed that SST produced from GSICS-corrected IR data was more accurate than that from original IR data, with a difference of 0.01–0.2ºC. Differences in SST between the original and GSICS-corrected IR showed a linear proportional relationship around IR2 (12.0 μm) during the day and IR1 (10.8 μm) at night. In the IR1 analysis, accuracies of daytime SST were improved significantly when the GSICS correction was applied to COMS IR data; also, the mean and median values of SST discrepancies (between the original and GSICS-corrected IR) according to changes in brightness temperature difference (BTD) were close to 0ºC. We found that the accuracies of SST estimation from satellite IR bands were greatly improved by applying the GSICS correction.

Sensitivity analysis of satellite-retrieved SST using IR data from COMS/MI

Abstract : Sea Surface Temperature (SST) is the temperature close to the ocean’s surface and affects theEarth’s atmosphere as an important parameter for the climate circulation and change. The SST from satellitestill has biases from the error in specifying retrieval coefficients from either forward modeling or instrumentalbiases. So in this paper, we performed sensitivity analysis using input parameter of the SST to notice that theSST is most affected among the input parameter. We used Infrared (IR) data from the Communication, Ocean,and Meteorological Satellite (COMS)/Meteorological Imager (MI) from April 2011 to March 2012. We alsoused the Global Space-based Inter-Calibration System (GSICS) correction to quality of the IR data from COMS.SST was calculated by substituting the input parameters; IR data with or without the GSICS correction. Theresults of this sensitivity analysis, the SST was sensitive from -0.0403 to 0.2743 K when the IR data werechanged by the GSICS corrections. Key Words :