Evaluation of Sentinel-3A and Sentinel-3B ocean land colour instrument green instantaneous fraction of absorbed photosynthetically active radiation

Gobron, Nadine; Morgan, Olivier; Adams, Jennifer; Brown, Luke A.; Cappucci, Fabrizio; Dash, Jadunandan; Lanconelli, Christian; Marioni, Mirko; Robustelli, Monica

doi:10.1016/j.rse.2021.112850

Cited by 14 publications

(7 citation statements)

References 37 publications

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“…The native resolution is approximately 300 m, referred to as Full Resolution (FR). A Reduced Resolution (RR) processing mode provides Level-1B data at sampling rates decreased by a factor of four in both spatial dimensions resulting in a resolution of approximately 1.2 km [53]. The main objective of the Sentinel-3 mission is to measure sea surface topography, sea and land surface temperature, and ocean and land surface color with high accuracy and reliability to support ocean forecasting systems, environmental monitoring, and climate monitoring.…”

Section: Remote Sensing Measurementsmentioning

confidence: 99%

Blue Color Indices as a Reference for Remote Sensing of Black Sea Water

et al. 2023

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In this paper, we propose to analyze the values of the “blue” color index for further use in additional atmospheric correction of Level 2 remote sensing reflectance data for the waters of the Black Sea. Regardless of seasonal phenomena, atmospheric conditions, and the type of water, the average color index in the short-wave region, according to in situ measurements CI(412/443), varies from 0.77 to 0.83. The most frequently observed value is 0.8. In turn, the values of the “blue” color index CI(412/443) according to the satellite data of MODIS Aqua/Terra, VIIRS SNPP, and OLCI Sentinel 3A scanners showed a large scatter in values based on the standard deviation of the sample. The paper proposes to introduce the value of the minimum allowable threshold CI(412/443) > 0.59 based on the small variance found from in situ measurements, as well as on the basis of a theoretical estimate of the possible values of the index CI(412/443) when varying the backscattering exponent and the exponent for the absorption approximation. The quality check of the remote sensing data showed that, according to this selection criterion, 15% of data are physically incorrect for MODIS Aqua, 30% for MODIS Terra, 20% for Sentinel 3A, and 26% for VIIRS SNPP. In the course of the work, it was shown that the MODIS Aqua satellite provides the most high-quality and reliable information about the optical characteristics of the Black Sea.

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Section: Remote Sensing Measurementsmentioning

confidence: 99%

Blue Color Indices as a Reference for Remote Sensing of Black Sea Water

et al. 2023

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“…Historically, the differences observed have been fully attributed to the satellite products, assuming in situ measurements as the true value. However, the true value is unknown and in situ uncertainties have to be also accounted for (Gobron et al., 2022; Immler et al., 2010), especially due to the progressive improvement of remote sensing. Moreover, the mismatch between in situ and satellite measurements introduces a systematic difference in the comparison that, if not corrected, adds a third component into the uncertainty budget that could be the dominant one (Virtanen et al., 2018).…”

Section: Introductionmentioning

confidence: 99%

Impact of the Spatio‐Temporal Mismatch Between Satellite and In Situ Measurements on Validations of Surface Solar Radiation

Urraca,

Lanconelli,

Gobron

2024

JGR Atmospheres

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Satellite and in situ sensors do not observe exactly the same measurand. This introduces a mismatch between both types of measurements in the spatial or temporal. The mismatch differences can be the dominant component in their comparison, so they have to be removed for an adequate validation of satellite products. With this aim, we propose a methodology to characterize the mismatch between satellite and in situ measurements of surface solar radiation, evaluating the impact of the mismatch on validations. The Surface Solar Radiation Data Set—Heliosat (SARAH‐2) and the Baseline Surface Radiation Network are used to characterize the spatial and temporal mismatch, respectively. The mismatch differences in both domains are driven by cloud variability. At least 5 years are needed to characterize the mismatch, which is not constant throughout the year due to seasonal and diurnal cloud cover patterns. Increasing the mismatch can artificially improve the validation metrics under some circumstances, but the mismatch must be always minimized for a correct product assessment. Finally, we test two types of up‐scaling methods based on SARAH‐2 in the validation of degree‐scale products. The fully data‐driven correction removes all the mismatch effects (systematic and random) but fully propagates SARAH‐2 uncertainty to the corrections. The model‐based correction only removes the systematic mismatch difference, but it can correct measurements not covered by the high‐resolution data set and depends less SARAH‐2 uncertainty.

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“…Understanding the effects of fractions of light on plant growth can also lead to the development of more sustainable [24] and efficient farming practices, such as vertical farming [25] and hydroponics, which require less land [26] and water [27] than traditional agriculture [28]. By identifying the optimal growing conditions and adapting agricultural practices accordingly, farmers can better prepare for the challenges posed by climate change.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Interactive Influences of Climate Change and Urban Development on the Fraction of Absorbed Photosynthetically Active Radiation

Nwokolo,

Meyer,

Ahia

2024

Atmosphere

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This study aimed to utilize hybrid physics-based models that allow for a comprehensive evaluation of how solar–meteorological variables influence the fraction of absorbed photosynthetically active radiation (FAPAR). By integrating both physical and statistical approaches, these models provided a novel perspective on understanding the complex relationship between solar radiation and FAPAR dynamics. The integration of URE and CLC in studying ecosystem efficiency in the nations of China and India is crucial, owing to their interdependent nature. To achieve this, the coupled model intercomparison project phase 6 (CMIP6) was utilized, which involved interpolating data from the most recent five GCMs from the six-phase CMIP6. By integrating advanced modeling techniques with observational data, this innovative approach enabled a holistic assessment of the intricate connections between urban development, climate dynamics, and the productivity of surrounding ecosystems in these regions. The reported decline in FAPAR productivity in China and India highlights the growing concern over the impact of climate change on the health and resilience of vegetation. China experienced negative changes of −1.425, −0.414, and −0.018, while India reported negative changes of −2.463, 2.199, and 2.915 under different scenarios. Interestingly, despite these variations, both countries observed similar tidal variations in their seasonal bases, suggesting a consistent pattern in the fluctuations of vegetation productivity throughout the year. The authors of this study collected and analyzed extensive data on CLC and URE in order to investigate their impact on FAPAR fluctuations in China and India. The higher impact of URE compared to CLC in terms of effective contributions suggests that URE plays a crucial role in shaping the atmospheric physics of both China, accounting for 45.26%, and India, registering 33.95%. Conversely, the effects of CLC and PAR residual factor (PRF) were more pronounced in India compared to China, with impacts of 8.21% and 53.03% compared to 4.21% and 46.70%, respectively.

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Evaluation of Sentinel-3A and Sentinel-3B ocean land colour instrument green instantaneous fraction of absorbed photosynthetically active radiation

Cited by 14 publications

References 37 publications

Blue Color Indices as a Reference for Remote Sensing of Black Sea Water

Blue Color Indices as a Reference for Remote Sensing of Black Sea Water

Impact of the Spatio‐Temporal Mismatch Between Satellite and In Situ Measurements on Validations of Surface Solar Radiation

Exploring the Interactive Influences of Climate Change and Urban Development on the Fraction of Absorbed Photosynthetically Active Radiation

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