On-orbit calibration and characterization of GOES-17 ABI IR bands under dynamic thermal condition

Wang, Zhipeng; Wu, Xiangqian; Yu, Fangfang; Fulbright, Jon P.; Kline, Elizabeth; Yoo, Hyelim; Schmit, Timothy J.; Gunshor, Mathew M.; Coakley, Monica M.; Black, Mason; Lindsey, Daniel T.; Qian, Haifeng; Shao, Xi; Iacovazzi, R.

doi:10.1117/1.jrs.14.034527

Cited by 9 publications

(4 citation statements)

References 18 publications

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“…Both ABIs have the same design except that there was malfunction of loop heat pipe (LHP) on GOES-17 ABI after it was launched. [8][9][10] The LHP transfers heat from the ABI electronics to the radiator and could not operate at its designed capacity on GOES-17 ABI. 8,9 This caused difficulty in maintaining at the intended temperature for some of the ABI IR channel detectors during parts of night, leading to partial loss of ABI imagery.…”

Section: Comparison Of Goes-16 and Goes-17abi Ch07 Stray Lightmentioning

confidence: 99%

Characterization and monitoring of GOES-16 ABI stray light and comparison with Himawari-8 AHI and GOES-17 ABI

Shao

et al. 2021

J. Appl. Rem. Sens.

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The Advanced Baseline Imager (ABI) aboard Geostationary Operational Environmental Satellite (GOES)-16 and-17 satellites represent the next-generation geostationary multispectral imaging instrument. Since GOES-16 ABI imagery data became available, stray light was observed in ABI visible, near-infrared (VNIR), and 3.9 μm, i.e., CH07, channels. A stray-light characterization scheme was developed to quantitatively monitor stray-light variation in ABI imagery. The stray-light analysis is focused on ABI CH07, whose nighttime radiometric performance being impacted by stray light is of main concern. It is found that the stray light in the ABI imagery occurs over ∼3 months around spring and fall equinox each year. The maximum stray light of GOES-16 ABI CH07 is ∼0.65 K at 300 K scene in zone of normal performance (ZONP), i.e., region with relative solar angle >7.5 deg, which is within the radiometric requirement of 1 K. The analysis of Himawari-8 Advanced Himawari Imager (AHI) CH07 data indicates that its maximum stray light is ∼3.35 K at 300 K scene in ZONP, much higher than that of GOES-16. This confirms the effectiveness of reducing the major stray-light leaking path in ABI as a result of lessons learned from Himawari-8 AHI. The magnitude of GOES-17 ABI CH07 stray light is shown to be ∼0.45 K in ZONP, slightly lower than GOES-16. The analysis of AHI 3.9 and 6.2 μm channel stray-light radiance ratio is shown to match the ratio of solar irradiance spectrum, which suggests that the stray-light issue is due to direct leakage of solar radiation through the instrument. Further characterization and monitoring of GOES-16 ABI VNIR channel stray light also help understand the solar origin of ABI stray light. This paper also investigated cases of strong atmospheric refraction-induced stray-light contamination onto ABI detectors during solar eclipse seasons and presents scheme to reduce such potentially harmful contamination. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Section: Comparison Of Goes-16 and Goes-17abi Ch07 Stray Lightmentioning

confidence: 99%

Characterization and monitoring of GOES-16 ABI stray light and comparison with Himawari-8 AHI and GOES-17 ABI

Shao

et al. 2021

J. Appl. Rem. Sens.

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“…These satellites achieve RC precision of 0.1-0.5K by observing a carried blackbody, a lake or an ocean, etc. [16][17][18][19][20] Some other infrared sensors, such as ATSR [21], ETM+ [22], VISR [23], and MODIS [24], achieve higher precision by further averaging the calibration results over a relatively long period. Additionally, some standard stars, such as Vega and Sirius, have also been utilized for infrared RC for some space-based sensors [25].…”

Section: Introductionmentioning

confidence: 99%

Towards Artificial Intelligence Based Radiometric Calibration for In-orbit Remote Sensing Satellites

Chen,

Wu,

Hui

et al. 2024

Preprint

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Radiometric Calibration (RC) is a key step in high-precision aerospace infrared remote sensing. Currently, source-based RC is the most prevailing methodologies, where a radiometric source such as blackbody with known radiation energy is observed by the sensor and the corresponding output digital number is recorded. However, the methodology is limited by several constraints, e.g., space and weight requirement for in-orbit blackbodies, and lack of uniformity and ideal properties of blackbodies. This paper presents a new artificial intelligence based RC that directly generates RC coefficients given the state of the sensor parameters. First, we derive the relationship between the RC coefficients and the physical parameters and environmental parameters of the sensor. Next, we steadily collect a large quantity of remote sensing data using our in-orbit satellites since 2018 and correspondingly train a neural network to fit such function for the generation of RC coefficients. Finally, our extensive experiments show that the proposed method achieves high-accuracy RC comparable with state-of-the-art methods that use in-orbit blackbody. To the best of our knowledge, we are the first to demonstrate an artificial-intelligence-based RC method for satellites without observation to blackbodies during in-orbit remote sensing. We anticipate that the new approach could promote the accuracy and uniformity of global infrared remote sensing data, thereby promoting the ability to discern natural laws and understand longterm environmental or celestial trends. Besides, it can substantially save the cost for carrying and observing in-orbit blackbodies.

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“…The satellites are positioned over the equator at 75.2 • W (GOES-16) and 137.2 • W (GOES-17). Although our analysis centered on the 2020 megafires in western Oregon and southwest Washington (closer to GOES-17) we relied on GOES-16, which is optimized for the eastern US, thereby accepting decreased spatial resolution near the edge of the field of view (~4 km) owing to concerns over the technical accuracy of GOES-17 [17].…”

mentioning

confidence: 99%

It’s about Time: A Method for Estimating Wildfire Arrival and Weather Conditions at Field-Sampled Locations

Klock,

Busby,

Fried

2023

Fire

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Weather conditions at the time of wildfire front arrival strongly influence fire behavior and effects, yet few methods exist for estimating weather conditions more spatio-temporally resolved than coarse-grain (e.g., 4 km) daily averages. When a fire front advances rapidly and weather conditions are heterogeneous over space and time, greater spatio-temporal precision is required to accurately link fire weather to observed fire effects. To identify the influence of fire weather on fire effects observed across a sample of existing forest inventory plots during a wind-driven megafire event in the US Pacific Northwest, we explored and compared three methods for estimating time of fire arrival and the wind speed at that arrival time for each plot location. Two methods were based on widely used, remotely sensed active fire data products with dissimilar spatial and temporal resolutions. The third and preferred method, Modeled-Weather Interpolated Perimeters (MoWIP), is a new approach that leveraged fine-grained (1.3 km, hourly) wind speed and direction from modeled fire weather to guide interpolation of aerial infrared-detected (IR) operational perimeters, subdividing the time intervals defined by sequential IR perimeters into quartile intervals to enhance temporal resolution of predicted fire arrival times. Our description of these fire arrival “time stamp” methods and discussion of their utility and shortcomings should prove useful to fire scientists, ecologists, land managers, and future analyses seeking to link estimated fire weather and observed fire effects.

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On-orbit calibration and characterization of GOES-17 ABI IR bands under dynamic thermal condition

Cited by 9 publications

References 18 publications

Characterization and monitoring of GOES-16 ABI stray light and comparison with Himawari-8 AHI and GOES-17 ABI

Characterization and monitoring of GOES-16 ABI stray light and comparison with Himawari-8 AHI and GOES-17 ABI

Towards Artificial Intelligence Based Radiometric Calibration for In-orbit Remote Sensing Satellites

It’s about Time: A Method for Estimating Wildfire Arrival and Weather Conditions at Field-Sampled Locations

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