Updates to the radiometric calibration of the Atmospheric Infrared Sounder (AIRS)Pagano, Thomas S.; Manning, Evan M.; Broberg, Steven E.; Aumann, Hartmut; Wilson, Robert C.; Overoye, Ken
doi: 10.1117/12.2676416pmid: N/A
The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua spacecraft measures the upwelling radiance of the atmosphere from 3.7 to 15.4 μm. The AIRS radiometric calibration coefficients convert the counts measured from the instrument’s A/D converters (Level 1A) to SI traceable radiance units (Level 1B). The calibration equations are based on how the instrument operates and follow a simple second order relationship between counts and radiance. Terms are included to account for nonlinearity of the detectors, emissivity and temperature knowledge of the on-board calibrator (OBC) blackbody and radiometric offset due to coupling of the polarization of the scan mirror with the spectrometer. Radiometric coefficients have not been updated since launch and are used in the operational Version 5 available at the GES/DISC. A new set of coefficients, Version 7 (V7), were produced in 2018 but never released. This paper presents the coefficients for Version 8 (V8) with only a few changes from V7 relating to the additional time used in the training of the trend of the polarization coefficients. We then compare new coefficients, V8, with the latest operational version of the AIRS radiometric calibration coefficients Version 5 (V5) and the prior V7. The Version 8 coefficients utilize more of the pre-flight test data and show lower residuals to the tests than V5. V8 also removes a trend in the polarization seen in Module 5 and is expected to have more accurate nonlinearity than prior versions.
Using Dome Concordia to characterize the long-term stability of VIIRS thermal emissive bandsAngal, Amit; Xiong, Xiaoxiong; Shrestha, Ashish; Wu, Aisheng
doi: 10.1117/12.2676768pmid: N/A
The Visible Infrared Imaging Radiometer Suite (VIIRS) instruments aboard the Suomi NPP and NOAA-20 spacecraft have successfully provided Earth image products since 2011 and 2017, respectively. Maintaining accurate radiometric calibration and calibration consistency between the two sensors is a necessity for the continued quality of long-term data records. In this work, the use of frequent VIIRS measurements of brightness temperature over the area surrounding Dome Concordia (Dome C), Antarctica (75.1 S, 123.4E) to track the long-term stability of its thermal emissive bands (TEB) is presented. The extremely dry, cold, and rarefied atmosphere of the site makes it ideal to track and detect longterm changes in the TEB responses via analysis of near-nadir and off-nadir VIIRS overpasses in reference to the surface temperature measurements provided by an automated weather station (AWS). Multi-year Dome C measurements have been used to assess the stability of the VIIRS response-versus-scan-angle (RVS) of the half-angle-mirror (HAM), derived from prelaunch characterization, and detector differences at multiple scan angles. Also, included in this work is the RVS stability assessments using the Dome C overpasses. The methodology developed via this work will also be applied to the recently launched VIIRS instrument onboard the NOAA-21 satellite (previously JPSS-2) in the future.
An update on the MODIS thermal emissive bands on-orbit performancePerez Diaz, Carlos; Chang, Tiejun; Lin, Hanzhi; Wu, Aisheng; Sarid, Gal; Xiong, Xiaoxiong
doi: 10.1117/12.2677456pmid: N/A
The MODIS instrument onboard the Terra and Aqua satellites provides key measurements of various environmental parameters such as the land, ocean, and atmosphere. After over two decades of successful operations, both sensors experienced anomalies in the year 2022. In March, the Aqua spacecraft and, subsequently, the MODIS instrument entered a safe mode, and Terra MODIS experienced a Command Processor and Format Processor (CP/FP) reset. Separately, the Terra constellation exit maneuver (CEM) was performed in October, which included the transition of the MODIS instrument into a safe configuration as well. While MODIS has 16 infrared channels referred to as the thermal emissive bands (TEB), only the longwave infrared bands (27-30) were significantly impacted due to an increase in electronic crosstalk contamination after the Aqua MODIS sensor entered into safe mode. Crosstalk corrections have been applied to these bands to maintain the Level 1B product quality. Although to a lesser extent, the same MODIS bands were affected due to a slight increase in electronic crosstalk contamination after the Terra CEM was completed. Lastly, the Terra MODIS CP/FP reset had an effect on the digital output that transferred onto its photovoltaic bands due to their calibration algorithm. This paper presents the impacts of these events on the instruments’ TEB performance, and the subsequent changes made to their respective calibration algorithms.
The comparison of ARIMA and LSTM in forecasting of long-term surface movements derived from PSINSARYagmur, Nur; Musaoglu, Nebiye
doi: 10.1117/12.2677482pmid: N/A
In recent years, airports, serving as vital transportation hubs, have faced the challenge of limited available land in megacities. As a result, airport construction on reclaimed areas has become a common solution. However, over time, these areas are exposed to soil behaviors like settlement and uplift, leading to surface movements. Detecting and monitoring these movements consistently is crucial to prevent potential disasters. Interferometric Synthetic Aperture Radar (InSAR) has emerged as a powerful tool for monitoring surface movements with high temporal and spatial resolution based on satellite properties, unlike traditional point-based methods. In particular, time series InSAR methods, such as Persistent Scatterer Interferometry (PSI), have been developed to monitor surface movements over a period of time. However, in addition to observing past surface movements, forecasting future movements is also of great importance. In this context, various forecasting methods have been explored, among which Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) have gained significant popularity due to their successful performance. In a recent study, these two methods were applied to forecast surface movements at Istanbul Airport, utilizing time series data obtained from the freely available Sentinel-1 SAR images. The performance of the ARIMA and LSTM models was evaluated using well-established metrics including root mean square error (RMSE) and mean absolute error (MAE). Both ARIMA and LSTM are suitable for forecasting surface movements, but LSTM exhibited a marginally better fit to the data compared to the ARIMA model.
Cloud thermodynamic phase retrievals with a low-cost, division-of-focal-plane polarization cameraVenkatesulu, Erica; Shaw, Joseph A.
doi: 10.1117/12.2677564pmid: N/A
Cloud thermodynamic phase is an important parameter in climate models and cloud remote sensing because it controls whether a cloud tends to have a net heating or cooling effect and it must be known to retrieve other cloud parameters. Passive remote sensing of cloud thermodynamic phase using shortwave infrared radiance ratios is a well-known technique, and adding polarization sensitivity to the radiance ratio method can increase accuracy. Ground-based passive polarimetric remote sensing of cloud phase has also been performed in visible and near infrared wavelengths. Prior work has relied on highly sensitive, expensive polarimeters to detect the small change in polarization state between ice and liquid clouds. We explored the use of a low-cost, commercial division-of-focal-plane polarization imager for cloud thermodynamic phase retrievals. We calibrated and deployed a monochrome polarization imager, with both a moderate field-of-view lens and a fisheye lens. The imagers were deployed alongside a verified dual-polarization lidar that provided a truth measurement at the zenith. In this paper, we discuss the relationship between the Stokes S1 parameter measured by the low-cost polarization imager with both lenses and the cloud thermodynamic phase retrieved by a dual-polarization lidar.
Improving IPATS channel-to-channel registration assessmentTan, Bin; Reth, Alan D.; Criscione, Joseph C.; Dellomo, John J.
doi: 10.1117/12.2676847pmid: N/A
The Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) is a primary tool for assessing INR performance of GOES-R series ABI images. IPATS assesses five INR metrics: navigation, channel-to-channel registration (CCR), frame-to-frame registration, within-frame registration, and swath-to-swath registration. It was discovered that CCR assessment results between Visible-Near-Infrared (VNIR) channels and Infrared (IR) channels exhibits an annual oscillation in the north-south (NS) direction and a diurnal oscillation in the east-west (EW) direction, with an amplitude of approximately 5 μrad and 2.5 μrad, respectively. However, differences of navigation assessment results between VNIR and IR channels do not exhibit the annual or diurnal oscillations observed in CCR results. This indicates that the observed oscillations are due to measurement errors. The characteristics of the oscillations imply that cloud shadows are a possible cause of these measurement errors. In this study, several methods are explored to minimize the impact of cloud shadows on VNIR to IR CCR assessments: a) assessment at landmark locations only; b) using navigation assessment results to filter CCR assessments; c) using the ABI clear-sky-ratio product as a cloud mask; and d) smaller CCR assessment windows. In this paper, each method and a combination of several methods are evaluated based on assessment accuracy and the number of successful assessments. The selected approach is then used to reprocess GOES-16 ABI CCR data to show reductions in the annual and diurnal measurement error oscillations.
Comparison of ABI INR using the operational and GRATDAT-generated L1B imagesGuo, Song
doi: 10.1117/12.2679430pmid: N/A
The Advanced Baseline Imager (ABI) sensor, which is on board the new generation of NOAA’s Geostationary Observational Environmental Satellites (GOES) R-series or GOES-R platforms, is of critical importance in weather forecasting and other environmental monitoring. The NOAA GOES-R Calibration Working Group (CWG) has developed an Image Navigation and Registration (INR) monitoring system CENRAIS (CWG Extended Navigation and Registration Analysis and Improvement System). The GOES-R ABI Trending and Data Analysis Toolkit (GRATDAT) is a software tool suite for supporting the GOES-R Advanced Baseline Imager (ABI) radiometric and geometric operations. It has the capacity to process the GOES-R ABI L0 data up to the L1B data through full sets of radiometric and geometric processing the same as the GOES-R ground operational processing of the data. Therefore, GRATDAT has the potential to be used as a toolkit in calibration and validation group work investigating the cause of the geometric calibration or correction anomaly. This paper focuses on the comparison of GOES-R Geometric or INR monitoring using both the GRATDAT generated and GOES-R ground processing generated L1b data and runs both pairs of the same time images through CENRAIS to evaluate and assess the accuracy of the GRATDAT Geometric or INR processing by comparing with the CENRAIS results of the two. The goal of this work is to make sure GRATDAT is accurate enough to be used as a toolkit to assistant in tracing the cause of any anomaly. In GRATDAT processing of GOES-R data from Level 0 to Level 1B, we can adjust any look up table (LUT) values to check the impacts of the parameters or thresholds used in the L0 to L1B processing, which gives us more power to detect both the geometric and radiometric anomaly and assess the impacts of any parameter and threshold value changes in the processing. Preliminary results of 2-hour FD and CONUS image comparison show the CENRAIS results from both Full Disk (FD) and CONUS image pairs are comparable and matching well from the pairs of CENRAIS runs. The Image Navigation Residuals (NAV), Frame-to-Frame Registration (FFR), Channel-to-Channel Registration (CCR) results from the comparison of two sets of images will be presented. One full day of the two sets of images will be processed through CENRAIS for a robust and convincing comparison.
20 years of atmospheric infrared sounder (AIRS) data: status, climate trends, and future data continuityAumann, Hartmut; Broberg, Steven; Manning, Evan; Pagano, Thomas; Wilson, Robert C.
doi: 10.1117/12.2677646pmid: N/A
The exit of EOS Aqua from the A-train in early 2023 marks the end of 20 years of Atmospheric Infrared Sounder (AIRS) data from the 1:30 PM ascending node orbit. The AIRS 20-year data record shows impressive accuracy and stability. Trends in the radiometry relative to accepted stable geophysical references are at the -3 to +6 mK/yr level, likely caused by unaccounted for changes in the lower troposphere and increasing sensor aging effects. Previously unknown trends are seen in the distribution of clouds. The planned continuation of the AIRS data record with potentially 20 years of multiple Cross-track Infrared Sounder (CrIS) instruments may be used to confirm these trends. The overlap of three years of AIRS, SNPP-CrIS and JPSS1-CrIS shows radiometric agreement under cloud free ocean conditions at the 50 mK level. However, there are large day/night, land/ocean and cloud dependent differences between AIRS and CrIS data, which, even if explained by known footprint size differences, will complicate the climate change interpretation of trends from potentially 40 years of concatenated data.
Preliminary assessment of the NOAA-21 VIIRS on-orbit reflective solar band calibration and performanceChoi, Taeyoung; Blonski, Slawomir; Shao, Xi; Wang, Wenhui
doi: 10.1117/12.2677921pmid: N/A
On November 10, 2022, the NOAA-21 (also known as Joint Polar Satellite System (JPSS)-2) Visible Infrared Imaging Radiometer Suite (VIIRS) was successfully launched and operated on-orbit. The NOAA-21 VIIRS is the third VIIRS instrument in the series, following S-NPP and NOAA-20, providing 22 spectral bands that cover a spectral range from 0. 402 m to 12.5 m. From the intensive Post Launch Tests (PLTs), the NOAA-21 VIIRS Sensor Data Record (SDR) achieved beta maturity status on Feb. 23, 2023 and is expected to achieve provisional and validated maturity in the next few months, ensuring the performance requirements are met and data are of high quality with on-orbit calibration. The accuracy of the current NOAA-21 VIIRS Reflective Solar Band (RSB) calibration was limited by in the Solar Diffuser (SD) degradation estimates, which proportionally affect the accuracy of the on-orbit RSB calibration. To achieve the beta maturity status, the SD degradation was omitted from the initial radiometric response analyses, and calculated solar calibration scaling coefficients (F-factors) were extrapolated to the start of the on-orbit operations that marked the onset of the SD degradation. To mitigate the unexpected SD reflectance variability, a series of yaw maneuvers will be performed as a part of the PLTs during the Intensive Calibration and Validation (ICV) phase. In addition to the yaw points, on-orbit Solar Diffuser Stability Monitor data sets will fill the intermediate angles between the yaw angles. The updated estimates of the SD degradation (H-factors) will be applied in the SD F-factor calculations. Finally, the improved SD F-factors will be compared and validated with vicarious calibration results, such as lunar F-factors. This paper will evaluate the impacts of SD-based calibration updates for NOAA-21 RSBs through assessing the radiometric biases of NOAA-21 VIIRS RSBs relative to NOAA-20 ensuring the radiometric accuracy of the NOAA-21 SDR products.