Overview of Intercalibration of Satellite Instruments

Intercalibration of satellite instruments is critical for detection and quantification of changes in the Earth’s environment, weather forecasting, understanding climate processes, and monitoring climate and land cover change. These applications use data from many satellites; for the data to be interoperable, the instruments must be cross-calibrated. To meet the stringent needs of such applications, instruments must provide reliable, accurate, and consistent measurements over time. Robust techniques are required to ensure that observations from different instruments can be normalized to a common scale that the community agrees on. The long-term reliability of this process needs to be sustained in accordance with established reference standards and best practices. Furthermore, establishing physical meaning to the information through robust Système International d’unités traceable calibration and validation (Cal/Val) is essential to fully understand the parameters under observation. The processes of calibration, correction, stabilitymonitoring, and quality assurance need to be underpinned and evidenced by comparison with “peer instruments” and, ideally, highly calibrated in-orbit reference instruments. Intercalibration between instruments is a central pillar of the Cal/Val strategies of many national and international satellite remote sensing organizations. Intercalibration techniques as outlined in this paper not only provide a practical means of identifying and correcting relative biases in radiometric calibration between instruments but also enable potential data gaps between measurement records in a critical time series to be bridged. Use of a robust set of internationally agreed upon and coordinated intercalibration techniques will lead to significant improvement in the consistency between satellite instruments and facilitate accurate monitoring of the Earth’s climate at uncertainty levels needed to detect and attribute the mechanisms of change. This paper summarizes the state-of-the-art of postlaunch radiometric calibration of remote sensing satellite instruments through intercalibration

Overview of Intercalibration of Satellite Instruments

Intercalibration of satellite instruments is critical for detection and quantification of changes in the Earth’s environment, weather forecasting, understanding climate processes, and monitoring climate and land cover change. These applications use data from many satellites; for the data to be interoperable, the instruments must be cross-calibrated. To meet the stringent needs of such applications, instruments must provide reliable, accurate, and consistent measurements over time. Robust techniques are required to ensure that observations from different instruments can be normalized to a common scale that the community agrees on. The long-term reliability of this process needs to be sustained in accordance with established reference standards and best practices. Furthermore, establishing physical meaning to the information through robust Système International d’unités traceable calibration and validation (Cal/Val) is essential to fully understand the parameters under observation. The processes of calibration, correction, stabilitymonitoring, and quality assurance need to be underpinned and evidenced by comparison with “peer instruments” and, ideally, highly calibrated in-orbit reference instruments. Intercalibration between instruments is a central pillar of the Cal/Val strategies of many national and international satellite remote sensing organizations. Intercalibration techniques as outlined in this paper not only provide a practical means of identifying and correcting relative biases in radiometric calibration between instruments but also enable potential data gaps between measurement records in a critical time series to be bridged. Use of a robust set of internationally agreed upon and coordinated intercalibration techniques will lead to significant improvement in the consistency between satellite instruments and facilitate accurate monitoring of the Earth’s climate at uncertainty levels needed to detect and attribute the mechanisms of change. This paper summarizes the state-of-the-art of postlaunch radiometric calibration of remote sensing satellite instruments through intercalibration

GEO-LEO Reflective Band Inter-Comparison with BRDF and Atmospheric Scattering Corrections

The inter-comparison of the reflective solar bands (RSB) between the instruments onboard a geostationary orbit satellite and a low Earth orbit satellite is very helpful in assessing their calibration consistency. Himawari-8 was launched 7 October 2014 and GOES-R was launched on 19 November 2016. Unlike previous GOES instruments, the Advanced Himawari Imager (AHI) on Himawari-8 and the Advanced Baseline Imager (ABI) on GOES-R have onboard calibrators for the RSB. Independent assessment of calibration is nonetheless important to enhance their product quality. MODIS (Moderate Resolution Imaging Spectroradiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) can provide good references for sensor calibration. In this work, the inter-comparison between AHI and VIIRS is performed over a pseudo-invariant target. The use of stable and uniform calibration sites provides comparison with accurate adjustment for band spectral difference, reduction of impact from pixel mismatching, and consistency of BRDF (Bidirectional Reflectance Distribution Function) and atmospheric correction. The site used is the Strzelecki Desert in Australia. Due to the difference in solar and view angles, two corrections must be applied in order to compare the measurements. The first is the atmospheric scattering correction applied to the top of atmosphere reflectance measurements. The second correction is applied to correct the BRDF effect. The atmospheric correction is performed using a vector version of the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) model and the BRDF correction is performed using a semi-empirical model. Our results show that AHI band 1 (0.47 microns) has a good agreement with VIIRS band M3 within 0.15 percent. AHI band 5 (1.61 microns) shows the largest difference (5.09 percent) with VIIRS band M10, while AHI band 5 shows the least difference (1.87 percent) in comparison with VIIRS band I3. The methods developed in this work can also be directly applied to assess GOES-16/ABI (Geostationary Operational Environment Satellite16 / Advanced Baseline Imager) calibration consistency, a topic we will address in the future

Aqua and Terra MODIS RSB Calibration Comparison Using BRDF Modeled Reflectance

The inter-comparison of MODIS reflective solar bands onboard Aqua and Terra is very important for assessment of each instrument's calibration. One of the limitations is the lack of simultaneous nadir overpasses. Their measurements over a selected Earth view target have significant differences in solar and view angles, which magnify the effects of atmospheric scattering and Bidirectional Reflectance Distribution Function (BRDF). In this work, an intercomparison technique is formulated after correction for site's BRDF and atmospheric effects. The reflectance measurements over Libya desert sites 1, 2, and 4 from both the Aqua and Terra MODIS are regressed to a BRDF model with an adjustable coefficient accounting for calibration difference. The ratio between Aqua and Terra reflectance measurements are derived for bands 1 to 9 and the results from different sites show good agreement. For year 2003, the ratios are in the range of 0.985 to1.010 for band 1 to 9. Band 3 shows the lowest ratio 0.985 and band 1 shows the highest ratio 1.010. For the year 2014, the ratio ranges from approximately 0.983 for bands 2 and 1.012 for band 8. The BRDF corrected reflectance for the two instruments are also derived for every year from 2003 to 2014 for stability assessment. Bands 1 and 2 show greater than 1 differences between the two instruments. Aqua bands 1 and 2 show downward trends while Terra bands 1 and 2 show upward trends. Bands 8 and 9 of both Aqua and Terra show large variations of reflectance measurement over time

Workshop on Strategies for Calibration and Validation of Global Change Measurements

The Committee on Environment and Natural Resources (CENR) Task Force on Observations and Data Management hosted a Global Change Calibration/Validation Workshop on May 10-12, 1995, in Arlington, Virginia. This Workshop was convened by Robert Schiffer of NASA Headquarters in Washington, D.C., for the CENR Secretariat with a view toward assessing and documenting lessons learned in the calibration and validation of large-scale, long-term data sets in land, ocean, and atmospheric research programs. The National Aeronautics and Space Administration (NASA)/Goddard Space Flight Center (GSFC) hosted the meeting on behalf of the Committee on Earth Observation Satellites (CEOS)/Working Group on Calibration/walidation, the Global Change Observing System (GCOS), and the U. S. CENR. A meeting of experts from the international scientific community was brought together to develop recommendations for calibration and validation of global change data sets taken from instrument series and across generations of instruments and technologies. Forty-nine scientists from nine countries participated. The U. S., Canada, United Kingdom, France, Germany, Japan, Switzerland, Russia, and Kenya were represented

Stratospheric ozone climatology and variability from ground-based and satellite observations over Irene, South Africa (25.5°S; 28.1°E)

M. Sc. University of KwaZulu-Natal, Durban 2014.The climatological characteristic of ozone over Irene (25.˚S, 28.1˚E) was assessed in this thesis using ground-based satellite observations. The aim of this was to examine the variability of both total and vertical ozone distribution over Irene. Ground based instruments were selected since they provide accurate measurement of ozone while satellite measurements were used for this study because they provide a wider coverage. Satellite data from Total Ozone Mapping Spectrometer (TOMS) from November 1978 to May 1993, Global Ozone Monitoring Experiment-1 (GOME-1) from August 1995 to June 2003, Earth Probe Total Ozone Monitoring Spectrometer (EP-TOMS) from January 1997 to December 2005, Microwave Limb Sounder (October 2004 to April 2013), Ozone Monitoring Interferometer (OMI) from October 2004 to December 2013, Global Ozone Monitoring Experiment-2 (GOME-2) from January 2007 to December 2013, and Infrared Atmospheric Sounding Interferometer (IASI) from June 2008 to December 2011 and ground-based measurements from Dobson Instrument (August 1989 to December 2011) as well as Ozonesondes (November 1978 to Decemeber 2007) were used. The seven satellites and two ground based instruments used for this study were selected as they provide long term ozone monitoring data. The above satellites measurements were collected when they overpass over Irene. The height profiles of ozone concentration obtained from ozonesondes and satellite (MLS) are in good in good agreement from 15 km and above. Maximum ozone concentration was found in the height region of 23 km to 27 km. Above this height, ozone concentration reduced with increasing height. The monthly variation of ozone concentration from ozonesondes and MLS showed maximum concentration during spring and minimum concentration during autumn. Maximum ozone concentration from ozonesonde corresponds to 4.5x10¹² molecules/cm³ while that from MLS satellite was ~ 4.1x10¹² molecules/cm³ during spring. A difference in the range of 4x10¹¹molecules/cm³ and 0.8x10¹² molecules/cm³ was obtained for all seasons except during winter when the difference was in the range of 0.6x10¹² molecules/cm³ and 0.9x10¹² molecules/cm³. Satellite measurements used to determine column ozone replicated spring maximum and autumn minimum. TOMS variation displayed higher value of total column ozone of about 7 DU when compared with other satellites but had good agreement with Dobson instrument. Combined satellite measurement of ozone was within 3 DU with Dobson mesurement. Satellite comparison with Dobson improved when both GOME measurements were not used to within 1 DU while GOME comparison with Dobson was within 5 DU. EPTOMS and GOME-1 showed gradual increase in column ozone between 1995 and 2005 by ~2 DU which has increased to ~7 DU in the last decade as measured by OMI, GOME-2 and IASI satellites. Ozone variability over South Africa was consistent with the seasonal variability of spring maximum and autumn minimum. The lower part of South Africa had more total ozone compared to the central part and lower part of South Africa attributed to maritime activities taking place in the region as well as the impact of wind from ozone rich regions in the high latitudes to mid-latitude regions. The north eastern part of South Africa had ~5 DU more than other northern part. This is atributed to the impact of biomass burning in the surrounding regions. This study has shown that there was ozone loss between 1978 and 1991 in Irene but there has been gradual recovery of ozone by ~ 7 DU per decade