Global GOSAT, OCO-2 and OCO-3 Solar Induced Chlorophyll Fluorescence Datasets

Abstract. The retrieval of solar induced chlorophyll fluorescence (SIF) from space is a relatively new advance in Earth observation science, having only become feasible within the last decade. Interest in SIF data has grown exponentially, and the retrieval of SIF and the provision of SIF data products has become an important and formal component of spaceborne Earth observation missions. Here, we describe the global Level 2 SIF Lite data products for the Greenhouse Gases Observing Satellite (GOSAT), the Orbiting Carbon Observatory-2 (OCO-2), and OCO-3 platforms, which are provided for each platform in daily netCDF files. We also outline the methods used to retrieve SIF and estimate uncertainty, describe all the data fields, and provide users the background information necessary for the proper use and interpretation of the data, such as considerations of retrieval noise, sun-sensor geometry, the indirect relationship between SIF and photosynthesis, and differences among the three platforms and their respective data products. OCO-2 and OCO-3 have the highest spatial resolution spaceborne SIF retrievals to date, and the target and snapshot area mode observation modes of OCO-2 and OCO-3 are unique. These modes provide hundreds to thousands of SIF retrievals at biologically diverse global target sites during a single overpass, and provide an opportunity to better inform our understanding of canopy-scale vegetation SIF emission across biomes.

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On the impact of canopy model complexity on simulated carbon, water, and solar-induced chlorophyll fluorescence fluxes

10.5194/bg-2021-214 ◽

2021 ◽

Author(s):

Yujie Wang ◽

Christian Frankenberg

Keyword(s):

Chlorophyll Fluorescence ◽

Land Surface ◽

Climate Modeling ◽

Global Scale ◽

Model Complexity ◽

Transfer Scheme ◽

Sun Sensor ◽

Sensor Geometry ◽

The Impact ◽

Canopy Model

Abstract. Lack of direct carbon, water, and energy flux observations at global scales makes it difficult to calibrate land surface models (LSMs). The increasing number of remote sensing based products provide an alternative way to verify or constrain land models given its global coverage and satisfactory spatial and temporal resolutions. However, these products and LSMs often differ in their assumptions and model setups, for example, the canopy model complexity. The disagreements hamper the fusion of global scale datasets with LSMs. To evaluate how much the canopy complexity affects predicted canopy fluxes, we simulated and compared the carbon, water, and solar-induced chlorophyll fluorescence (SIF) fluxes using five different canopy complexity setups from a one-layered big-leaf canopy to a multi-layered canopy with leaf angular distributions. We modeled the canopy fluxes using a recently developed Land model by the Climate Modeling Alliance. Our model results suggested that (1) when using the same model inputs, model predicted carbon, water, and SIF fluxes were all higher for simpler canopy setups; (2) when accounting for vertical photosynthetic capacity heterogeneity, differences among canopy complexity levels increased compared to the scenario of a uniform canopy; (3) SIF fluxes modeled with different canopy complexity levels changed with sun-sensor geometry. Given the different modeled canopy fluxes with different canopy complexities, we recommend (1) not misusing parameters inverted with different canopy complexities or assumptions to avoid biases in model outputs, and (2) using complex canopy model with angular distribution and hyperspectral radiation transfer scheme when linking land processes to remotely sensed spectra.

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On the impact of canopy model complexity on simulated carbon, water, and solar-induced chlorophyll fluorescence fluxes

Biogeosciences ◽

10.5194/bg-19-29-2022 ◽

2022 ◽

Vol 19 (1) ◽

pp. 29-45

Author(s):

Yujie Wang ◽

Christian Frankenberg

Keyword(s):

Chlorophyll Fluorescence ◽

Land Surface ◽

Climate Modeling ◽

Global Scale ◽

Model Complexity ◽

Transfer Scheme ◽

Sun Sensor ◽

Sensor Geometry ◽

The Impact ◽

Canopy Model

Abstract. Lack of direct carbon, water, and energy flux observations at global scales makes it difficult to calibrate land surface models (LSMs). The increasing number of remote-sensing-based products provide an alternative way to verify or constrain land models given their global coverage and satisfactory spatial and temporal resolutions. However, these products and LSMs often differ in their assumptions and model setups, for example, the canopy model complexity. The disagreements hamper the fusion of global-scale datasets with LSMs. To evaluate how much the canopy complexity affects predicted canopy fluxes, we simulated and compared the carbon, water, and solar-induced chlorophyll fluorescence (SIF) fluxes using five different canopy complexity setups from a one-layered canopy to a multi-layered canopy with leaf angular distributions. We modeled the canopy fluxes using the recently developed land model by the Climate Modeling Alliance, CliMA Land. Our model results suggested that (1) when using the same model inputs, model-predicted carbon, water, and SIF fluxes were all higher for simpler canopy setups; (2) when accounting for vertical photosynthetic capacity heterogeneity, differences between canopy complexity levels increased compared to the scenario of a uniform canopy; and (3) SIF fluxes modeled with different canopy complexity levels changed with sun-sensor geometry. Given the different modeled canopy fluxes with different canopy complexities, we recommend (1) not misusing parameters inverted with different canopy complexities or assumptions to avoid biases in model outputs and (2) using a complex canopy model with angular distribution and a hyperspectral radiation transfer scheme when linking land processes to remotely sensed spectra.

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TROPOMI reveals dry-season increase of solar-induced chlorophyll fluorescence in the Amazon forest

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1908157116 ◽

2019 ◽

Vol 116 (44) ◽

pp. 22393-22398 ◽

Cited By ~ 4

Author(s):

Russell Doughty ◽

Philipp Köhler ◽

Christian Frankenberg ◽

Troy S. Magney ◽

Xiangming Xiao ◽

...

Keyword(s):

Chlorophyll Fluorescence ◽

Forest Canopy ◽

Dry Season ◽

Amazon Forest ◽

Wet Season ◽

Carbon Cycles ◽

Sun Sensor ◽

Sensor Geometry ◽

Earth Observation Satellites

Photosynthesis of the Amazon rainforest plays an important role in the regional and global carbon cycles, but, despite considerable in situ and space-based observations, it has been intensely debated whether there is a dry-season increase in greenness and photosynthesis of the moist tropical Amazonian forests. Solar-induced chlorophyll fluorescence (SIF), which is emitted by chlorophyll, has a strong positive linear relationship with photosynthesis at the canopy scale. Recent advancements have allowed us to observe SIF globally with Earth observation satellites. Here we show that forest SIF did not decrease in the early dry season and increased substantially in the late dry season and early part of wet season, using SIF data from the Tropospheric Monitoring Instrument (TROPOMI), which has unprecedented spatial resolution and near-daily global coverage. Using in situ CO2 eddy flux data, we also show that cloud cover rarely affects photosynthesis at TROPOMI’s midday overpass, a time when the forest canopy is most often light-saturated. The observed dry-season increases of forest SIF are not strongly affected by sun-sensor geometry, which was attributed as creating a pseudo dry-season green-up in the surface reflectance data. Our results provide strong evidence that greenness, SIF, and photosynthesis of the tropical Amazonian forest increase during the dry season.

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Minimum aerosol layer detection sensitivities and their subsequent impacts on aerosol optical thickness retrievals in CALIPSO level 2 data products

Atmospheric Measurement Techniques ◽

10.5194/amt-11-499-2018 ◽

2018 ◽

Vol 11 (1) ◽

pp. 499-514 ◽

Cited By ~ 22

Author(s):

Travis D. Toth ◽

James R. Campbell ◽

Jeffrey S. Reid ◽

Jason L. Tackett ◽

Mark A. Vaughan ◽

...

Keyword(s):

Optical Thickness ◽

Aerosol Optical Thickness ◽

Orthogonal Polarization ◽

Aerosol Layer ◽

Aerosol Extinction ◽

Noise Floor ◽

Data Products ◽

Moderate Resolution Imaging Spectroradiometer ◽

Level 2 ◽

Global Mean

Abstract. Due to instrument sensitivities and algorithm detection limits, level 2 (L2) Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) 532 nm aerosol extinction profile retrievals are often populated with retrieval fill values (RFVs), which indicate the absence of detectable levels of aerosol within the profile. In this study, using 4 years (2007–2008 and 2010–2011) of CALIOP version 3 L2 aerosol data, the occurrence frequency of daytime CALIOP profiles containing all RFVs (all-RFV profiles) is studied. In the CALIOP data products, the aerosol optical thickness (AOT) of any all-RFV profile is reported as being zero, which may introduce a bias in CALIOP-based AOT climatologies. For this study, we derive revised estimates of AOT for all-RFV profiles using collocated Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target (DT) and, where available, AErosol RObotic NEtwork (AERONET) data. Globally, all-RFV profiles comprise roughly 71 % of all daytime CALIOP L2 aerosol profiles (i.e., including completely attenuated profiles), accounting for nearly half (45 %) of all daytime cloud-free L2 aerosol profiles. The mean collocated MODIS DT (AERONET) 550 nm AOT is found to be near 0.06 (0.08) for CALIOP all-RFV profiles. We further estimate a global mean aerosol extinction profile, a so-called “noise floor”, for CALIOP all-RFV profiles. The global mean CALIOP AOT is then recomputed by replacing RFV values with the derived noise-floor values for both all-RFV and non-all-RFV profiles. This process yields an improvement in the agreement of CALIOP and MODIS over-ocean AOT.

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Version 4 CALIPSO IIR ice and liquid water cloud microphysical properties, Part I: the retrieval algorithms

10.5194/amt-2020-387 ◽

2020 ◽

Author(s):

Anne Garnier ◽

Jacques Pelon ◽

Nicolas Pascal ◽

Mark A. Vaughan ◽

Philippe Dubuisson ◽

...

Keyword(s):

Liquid Water ◽

Cloud Base ◽

Transfer Model ◽

Effective Diameter ◽

Ice Clouds ◽

Clear Sky ◽

Brightness Temperatures ◽

Microphysical Properties ◽

Data Products ◽

Level 2

Abstract. Following the release of the Version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version 4 (V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter and ice or liquid water path estimates. Dedicated retrievals for water clouds were added in V4, taking advantage of the high sensitivity of the IIR retrieval technique to small particle sizes. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results will be presented in a companion (Part II) paper. To reduce biases at very small emissivities that were made evident in V3, the radiative transfer model used to compute clear sky brightness temperatures over oceans has been updated and tuned for the simulations using MERRA-2 data to match IIR observations in clear sky conditions. Furthermore, the clear-sky mask has been refined compared to V3 by taking advantage of additional information now available in the V4 CALIOP 5-km layer products used as an input to the IIR algorithm. After sea surface emissivity adjustments, observed and computed brightness temperatures differ by less than ± 0.2 K at night for the three IIR channels centered at 08.65, 10.6, and 12.05 µm, and inter-channel biases are reduced from several tens of Kelvin in V3 to less than 0.1 K in V4. We have also aimed at improving retrievals in ice clouds having large optical depths by refining the determination of the radiative temperature needed for emissivity computation. The initial V3 estimate, namely the cloud centroid temperature derived from CALIOP, is corrected using a parameterized function of temperature difference between cloud base and top altitudes, cloud absorption optical depth, and the CALIOP multiple scattering correction factor. As shown in Part II, this improvement reduces the low biases at large optical depths that were seen in V3, and increases the number of retrievals in dense ice clouds. As in V3, the IIR microphysical retrievals use the concept of microphysical indices applied to the pairs of IIR channels at 12.05 μm and 10.6 μm and at 12.05 μm and 08.65 μm. The V4 algorithm uses ice look-up tables (LUTs) built using two ice crystal models from the recent TAMUice 2016 database, namely the single hexagonal column model and the 8-element column aggregate model, from which bulk properties are synthesized using a gamma size distribution. Four sets of effective diameters derived from a second approach are also reported in V4. Here, the LUTs are analytical functions relating microphysical index applied to IIR channels 12.05 µm and 10.6 µm and effective diameter as derived from in situ measurements at tropical and mid-latitudes during the TC4 and SPARTICUS field experiments.

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Laser Remote Sensing from ISS: CATS Cloud and Aerosol Level 2 Data Products (Heritage Edition)

EPJ Web of Conferences ◽

10.1051/epjconf/201611904012 ◽

2016 ◽

Vol 119 ◽

pp. 04012 ◽

Cited By ~ 1

Author(s):

Sharon Rodier ◽

Steve Palm ◽

Mark Vaughan ◽

John Yorks ◽

Matt McGill ◽

...

Keyword(s):

Remote Sensing ◽

Data Products ◽

Level 2 ◽

Laser Remote Sensing

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Extinction and optical depth retrievals for CALIPSO's Version 4 data release

Atmospheric Measurement Techniques ◽

10.5194/amt-11-5701-2018 ◽

2018 ◽

Vol 11 (10) ◽

pp. 5701-5727 ◽

Cited By ~ 39

Author(s):

Stuart A. Young ◽

Mark A. Vaughan ◽

Anne Garnier ◽

Jason L. Tackett ◽

James D. Lambeth ◽

...

Keyword(s):

Optical Depth ◽

Satellite Observations ◽

Orthogonal Polarization ◽

Ice Clouds ◽

Extinction Coefficients ◽

Retrieval Algorithms ◽

Data Release ◽

Data Products ◽

Lidar Ratio ◽

Level 2

Abstract. The Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud–Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) satellite has been making near-global height-resolved measurements of cloud and aerosol layers since mid-June 2006. Version 4.10 (V4) of the CALIOP data products, released in November 2016, introduces extensive upgrades to the algorithms used to retrieve the spatial and optical properties of these layers, and thus there are both obvious and subtle differences between V4 and previous data releases. This paper describes the improvements made to the extinction retrieval algorithms and illustrates the impacts of these changes on the extinction and optical depth estimates reported in the CALIPSO lidar level 2 data products. The lidar ratios for both aerosols and ice clouds are generally higher than in previous data releases, resulting in generally higher extinction coefficients and optical depths in V4. A newly implemented algorithm for retrieving extinction coefficients in opaque layers is described and its impact examined. Precise lidar ratio estimates are also retrieved in these opaque layers. For semi-transparent cirrus clouds, comparisons between CALIOP V4 optical depths and the optical depths reported by MODIS collection 6 show substantial improvements relative to earlier comparisons between CALIOP version 3 and MODIS collection 5.

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Comparisons of Chlorophyll Fluorescence and Physiological Characteristics of Wheat Seedlings Influenced by Iso-Osmotic Stresses from Polyethylene Glycol and Sodium Chloride

Agronomy ◽

10.3390/agronomy10030325 ◽

2020 ◽

Vol 10 (3) ◽

pp. 325

Author(s):

Chiu-Yueh Lan ◽

Kuan-Hung Lin ◽

Chun-Liang Chen ◽

Wen-Dar Huang ◽

Chang-Chang Chen

Keyword(s):

Chlorophyll Fluorescence ◽

Polyethylene Glycol ◽

Sodium Chloride ◽

Energy Dissipation ◽

Quantum Yield ◽

Photochemical Quenching ◽

Effective Quantum Yield ◽

Wheat Seedlings ◽

Level 3 ◽

Level 2

Wheat (Triticum aestivum) cultivar Taichung SEL.2 (TCS2) is a salt-tolerance variety, but the mechanism involved remains unclear. This study aims to distinguish between the non-ionic osmotic and salt-mediated physiological effects on TCS2. Osmotic agents polyethylene glycol (PEG) and sodium chloride (NaCl) were applied at three iso-osmotic levels, level 1 containing 24% (w/v) PEG and 200 mM NaCl, level 2 containing 26.5% (w/v) PEG and 250 mM NaCl), and level 3 containing 29% (w/v) PEG and 300 mM NaCl, respectively. According to the investigation of chlorophyll fluorescence in the better NaCl-treated seedlings, maximal quantum yield of photosystem II (PSII) (Fv/Fm) and significant higher effective quantum yield of PSII (ΦPSII) at level 3 were observed. Meanwhile, the non-photochemical quenching of PSII (NPQ) and the quantum yield of regulated energy dissipation of PSII [Y(NPQ)] were significantly higher in the NaCl-treated seedlings, and the quantum yield of non-regulated energy dissipation of PSII [Y(NO)] in the NaCl-treated seedlings was lower than the PEG-treated ones at level 2 and level 3. Furthermore, the less extensive degradation of photosynthetic pigments, the better ascorbate peroxidase (APX) activity and the less accumulation of malondialdehyde (MDA) were also observed in NaCl-treated seedlings. In the morphological traits, shoot elongation in NaCl-treated seedlings was also preserved. These results suggest that TCS2 is more resistant to NaCl-induced osmotic stress than to the PEG-induced stress. This study contributes to plant breeder interest in drought- and/or salt-tolerant wheat varieties.

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Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Remote Sensing ◽

10.3390/rs12101634 ◽

2020 ◽

Vol 12 (10) ◽

pp. 1634 ◽

Cited By ~ 1

Author(s):

Raha Hakimdavar ◽

Alfred Hubbard ◽

Frederick Policelli ◽

Amy Pickens ◽

Matthew Hansen ◽

...

Keyword(s):

Sustainable Development ◽

Surface Water ◽

Spatial Resolution ◽

The Philippines ◽

Earth Observation ◽

Landsat 8 ◽

Sustainable Development Goal ◽

Development Goal ◽

Data Products ◽

Over Time

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6 reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped over time for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1 reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

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NGIC: turning concepts into reality

10.5194/egusphere-egu2020-7627 ◽

2020 ◽

Author(s):

Nikolay Miloshev ◽

Petya Trifonova ◽

Ivan Georgiev ◽

Tania Marinova ◽

Nikolay Dobrev ◽

...

Keyword(s):

Conceptual Model ◽

Information And Communication Technologies ◽

Earth Observation ◽

Data Resource ◽

Road Map ◽

Data Products ◽

Information And Communication ◽

Development Goals ◽

Governmental Institutions ◽

Anthropogenic Risks

The National Geo-Information Center (NGIC) is a distributed research infrastructure funded by the National road map for scientific infrastructure (2017-2023) of Bulgaria. It operates in a variety of disciplines such as geophysics, geology, seismology, geodesy, oceanology, climatology, soil science, etc. providing data products and services. Created as a partnership between four institutes working in the field of Earth observation: the National Institute of Geophysics, Geodesy and Geography (NIGGG), the National Institute of Meteorology and Hydrology (NIMH), the Institute of Oceanology (IO), the Geological Institute (GI), and two institutes competent in ICT: the Institute of Mathematics and Informatics (IMI) and the Institute of Information and Communication Technologies (IICT), NGIC consortium serve as primary community of data collectors for national geoscience research. Besides the science, NGIC aims to support decision makers during the process of prevention and protection of the population from natural and anthropogenic risks and disasters.Individual NGIC partners originated independently and differ from one another in management and disciplinary scope. Thus, the conceptual model of the NGIC system architecture is based on a federated model structure in which the partners retain their independence and contribute to the development of the common infrastructure through the data and research they carry out. The basic conceptual model of architecture uses both service and microservice concepts and may be altered according to the specifics of the organization environment and development goals of the NGIC information system. It consists of three layers: &#8220;Sources&#8221; layer containing the providers of Data, Data products, Services and Soft-ware (DDSS), &#8220;Interoperability&#8221;- regulating the access, automation of discovery and selection of DDSS and data collection from the sources, and &#8220;Integration&#8221; layer which produces integrated data products.The diversity of NGIC&#8217;s data, data products, and services is a major strength and of high value to its users like governmental institutions and agencies, research organizations and universities, private sector enterprises, media and the public. NGIC will pursue collaboration with initiatives, projects and research infrastructures for Earth observation to enhance access to an integrated global data resource.

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