scholarly journals Improved SIFTER v2 algorithm for long-term GOME-2A satellite retrievals of fluorescence with a correction for instrument degradation

2020 ◽  
Vol 13 (8) ◽  
pp. 4295-4315
Author(s):  
Erik van Schaik ◽  
Maurits L. Kooreman ◽  
Piet Stammes ◽  
L. Gijsbert Tilstra ◽  
Olaf N. E. Tuinder ◽  
...  
Keyword(s):  
Near Infrared ◽  
Photosynthetic Activity ◽  
Gross Primary Production ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
Oxygen Absorption ◽  
Spectral Window ◽  
Data Product ◽  
Uncertainty Estimates ◽  
Water Vapour Absorption

Abstract. Solar-induced fluorescence (SIF) data from satellites are increasingly used as a proxy for photosynthetic activity by vegetation and as a constraint on gross primary production. Here we report on improvements in the algorithm to retrieve mid-morning (09:30 LT) SIF estimates on the global scale from the GOME-2 sensor on the MetOp-A satellite (GOME-2A) for the period 2007–2019. Our new SIFTER (Sun-Induced Fluorescence of Terrestrial Ecosystems Retrieval) v2 algorithm improves over a previous version by using a narrower spectral window that avoids strong oxygen absorption and being less sensitive to water vapour absorption, by constructing stable reference spectra from a 6-year period (2007–2012) of atmospheric spectra over the Sahara and by applying a latitude-dependent zero-level adjustment that accounts for biases in the data product. We generated stable, good-quality SIF retrievals between January 2007 and June 2013, when GOME-2A degradation in the near infrared was still limited. After the narrowing of the GOME-2A swath in July 2013, we characterised the throughput degradation of the level-1 data in order to derive reflectance corrections and apply these for the SIF retrievals between July 2013 and December 2018. SIFTER v2 data compare well with the independent NASA v2.8 data product. Especially in the evergreen tropics, SIFTER v2 no longer shows the underestimates against other satellite products that were seen in SIFTER v1. The new data product includes uncertainty estimates for individual observations and is best used for mostly clear-sky scenes and when spectral residuals remain below a certain spectral autocorrelation threshold. Our results support the use of SIFTER v2 data being used as an independent constraint on photosynthetic activity on regional to global scales.

scholarly journals Improved SIFTER v2 algorithm for long-term GOME-2A satellite retrievals of fluorescence with a correction for instrument degradation

2020 ◽  
Author(s):  
Erik van Schaik ◽  
Maurits L. Kooreman ◽  
Piet Stammes ◽  
L. Gijsbert Tilstra ◽  
Olaf N. E. Tuinder ◽  
...  
Keyword(s):  
Near Infrared ◽  
Photosynthetic Activity ◽  
Gross Primary Production ◽  
Global Scale ◽  
Retrieval Algorithm ◽  
Oxygen Absorption ◽  
Spectral Window ◽  
Data Product ◽  
Uncertainty Estimates ◽  
Water Vapour Absorption

Abstract. Solar-induced fluorescence (SIF) data from satellites are increasingly used as a proxy for photosynthetic activity by vegetation, and as a constraint on gross primary production. Here we develop an improved retrieval algorithm to retrieve mid-morning (09:30 hrs local time) SIF estimates on the global scale from GOME-2 sensor on the Metop-A satellite (GOME-2A) for the period 2007–2019. Our new SIFTER v2 algorithm improves over a previous version by using a narrower spectral window that avoids strong oxygen absorption and is less sensitive to water vapour absorption, by constructing stable reference spectra from a 6-year period (2007–2012) of atmospheric spectra over the Sahara, and by applying a latitude-dependent zero-level adjustment that accounts for biases in the data product. We generated stable, good-quality SIF retrievals between January 2007 and June 2013, when GOME-2A degradation in the near infrared was still limited. After the narrowing of the GOME-2A swath in July 2013, we characterized the throughput degradation of the level-1 data in order to derive reflectance corrections and apply these for the SIF retrievals between July 2013 and December 2018. SIFTER v2 data compares well with the independent NASA v2.8 data product. Especially in the evergreen tropics, SIFTER v2 no longer shows the underestimates against other satellite products that were seen in SIFTER v1. The new data product includes uncertainty estimates for individual observations, and is best used for mostly clear-sky scenes, and when spectral residuals remain below a certain spectral autocorrelation threshold. Our results support the use of SIFTER v2 data to be used as an independent constraint on photosynthetic activity on regional to global scales.

scholarly journals Twelve years of SIFTER Sun-Induced Fluorescence retrievals from GOME-2 as an independent constraint on photosynthesis across continents and biomes

2020 ◽  
Author(s):  
Maurits L. Kooreman ◽  
K. Folkert Boersma ◽  
Erik van Schaik ◽  
Anteneh G. Mengistu ◽  
Olaf N. E. Tuinder ◽  
...  
Keyword(s):  
Photosynthetic Activity ◽  
Gross Primary Production ◽  
Global Scale ◽  
Retrieval Algorithm ◽  
Oxygen Absorption ◽  
Water Vapor Absorption ◽  
Zonal Distribution ◽  
Spectral Window ◽  
Tropical Regions ◽  
Uncertainty Estimates

<p>Solar-Induced Fluorescence (SIF) data from satellites are increasingly used as a proxy for photosynthetic activity by vegetation, and as a constraint on gross primary production. The Royal Netherlands Meteorological Institute has developed an improved retrieval algorithm called SIFTER, to retrieve mid-morning (09:30 hrs local time) SIF estimates on the global scale from GOME-2 sensors on the Metop satellite series. The product is developed within the ACSAF network of EUMETSAT and a beta version is publicly available on www.temis.nl. The SIFTER algorithm improves over a previous version by using a narrower spectral window that avoids strong oxygen absorption and is less sensitive to water vapor absorption, by constructing stable reference spectra from a 6-year period (2007-2012) of atmospheric spectra over the Sahara, and by applying a latitude-dependent zero-level adjustment that accounts for biases in the product data. With SIFTER, we generate stable, good-quality SIF retrievals also in tropical regions that are known to suffer from high noise in other SIF products. Uncertainty estimates are included for individual observations, and the product is best used for mostly clear-sky scenes, and when spectral residuals remain below a certain threshold. The strength of SIFTER in the tropical regions was exploited to quantify the 2015/2016 drought in the Amazon, related to El Niño. We found that SIF was strongly suppressed over areas with anomalously high temperatures and decreased levels of soil moisture. SIF went below its climatological range starting from the end of the 2015 dry season and returned to normal levels by February 2016. A validation study is performed to assess the SIFTER quality against independent SIF and GPP products from other platforms, including SIF from OCO-2 and GOSAT, modeled GPP from MPI-BGC and eddy covariance derived, in-situ GPP measurements. SIFTER shows strong correlations (0.70 – 0.94) in the zonal distribution for each continent and in capturing seasonal patterns of SIF and GPP over different regions across the globe (0.62-0.99) when comparing to OCO-2 SIF and GPP from MPI-BGC. At ecosystem level, SIFTER was evaluated against OCO-2 SIF and EC GPP for five flux tower sites with varying biomes and geolocations. Regions with a homogeneous vegetation distribution show a higher correlation than heterogeneous regions. Overall, the results support the use of SIFTER data to be used as an independent constraint on photosynthetic activity on global and regional scales.</p>

Inferring non-steady-state terrestrial vegetation carbon turnover times from multi-decadal space-borne observations on global scale

2020 ◽  
Author(s):  
Naixin Fan ◽  
Simon Besnard ◽  
Maurizio Santoro ◽  
Oliver Cartus ◽  
Nuno Carvalhais
Keyword(s):  
Climate Change ◽  
Steady State ◽  
Carbon Fixation ◽  
Carbon Sink ◽  
Gross Primary Production ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
Turnover Time ◽  
Terrestrial Vegetation ◽  
Time Step

<p>The global biomass is determined by the vegetation turnover times (τ) and carbon fixation through photosynthesis. Vegetation turnover time is a central parameter that not only partially determines the terrestrial carbon sink but also the response of terrestrial vegetation to the future changes in climate. However, the change of magnitude, spatial patterns and uncertainties in τ as well as the sensitivity of these processes to climate change is not well understood due to lack of observations on global scale. In this study, we explore a new dataset of annual above-ground biomass (AGB) change from 1993 to 2018 from spaceborne scatterometer observations. Using the long-term, spatial-explicit global dynamic dataset, we investigated how τ change over almost three decades including the uncertainties. Previous estimations of τ under steady-state assumption can now be challenged acknowledging that terrestrial ecosystems are, for the most of cases, not in balance. In this study, we explore this new dataset to derive global maps of τ in non-steady-state for different periods of time. We used a non-steady-state carbon model in which the change of AGB is a function of Gross Primary Production (GPP) and τ (ΔAGB = α*GPP-AGB/ τ). The parameter α represents the percentage of incorporation of carbon from GPP to biomass. By exploring the AGB change in 5 to 10 years of time step, we were able to infer τ and α from the observations of AGB and GPP change by solving the linear equation. We show how τ changes after potential disturbances in the early 2000s in comparison to the previous decade. We also show the spatial distributions of α from the change of AGB. By accessing the change in biomass, τ and α as well as their associated uncertainties, we provide a comprehensive diagnostic on the vegetation dynamics and the potential response of biomass to disturbance and to climate change.   </p><p></p><p></p><p></p><p></p><p></p><p></p>

scholarly journals Extreme events in gross primary production: a characterization across continents

2014 ◽  
Vol 11 (1) ◽  
pp. 1869-1907 ◽  
Author(s):  
J. Zscheischler ◽  
M. D. Mahecha ◽  
S. Harmeling ◽  
A. Rammig ◽  
E. Tomelleri ◽  
...  
Keyword(s):  
South America ◽  
Primary Production ◽  
Extreme Events ◽  
Gross Primary Production ◽  
Climate Extremes ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
Early Summer ◽  
Seasonal Effects ◽  
Data Sets

Abstract. Climate extremes can affect the functioning of terrestrial ecosystems, for instance via a reduction of the photosynthetic capacity or alterations of respiratory processes. Yet the dominant regional and seasonal effects of hydrometeorological extremes are still not well documented. Here we quantify and characterize the role of large spatiotemporal extreme events in gross primary production (GPP) as triggers of continental anomalies. We also investigate seasonal dynamics of extreme impacts on continental GPP anomalies. We find that the 50 largest positive (increase in uptake) and negative extremes (decrease in uptake) on each continent can explain most of the continental variation in GPP, which is in line with previous results obtained at the global scale. We show that negative extremes are larger than positive ones and demonstrate that this asymmetry is particularly strong in South America and Europe. Most extremes in GPP start in early summer. Our analysis indicates that the overall impacts and the spatial extents of GPP extremes are power law distributed with exponents that vary little across continents. Moreover, we show that on all continents and for all data sets the spatial extents play a more important role than durations or maximal GPP anomaly when it comes to the overall impact of GPP extremes. An analysis of possible causes implies that across continents most extremes in GPP can best be explained by water scarcity rather than by extreme temperatures. However, for Europe, South America and Oceania we identify also fire as an important driver. Our findings are consistent with remote sensing products. An independent validation against a literature survey on specific extreme events supports our results to a large extent.

scholarly journals Extreme events in gross primary production: a characterization across continents

2014 ◽  
Vol 11 (11) ◽  
pp. 2909-2924 ◽  
Author(s):  
J. Zscheischler ◽  
M. Reichstein ◽  
S. Harmeling ◽  
A. Rammig ◽  
E. Tomelleri ◽  
...  
Keyword(s):  
South America ◽  
Primary Production ◽  
Extreme Events ◽  
Gross Primary Production ◽  
Climate Extremes ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
Seasonal Effects ◽  
Carbon Uptake ◽  
Uptake Rates

Abstract. Climate extremes can affect the functioning of terrestrial ecosystems, for instance via a reduction of the photosynthetic capacity or alterations of respiratory processes. Yet the dominant regional and seasonal effects of hydrometeorological extremes are still not well documented and in the focus of this paper. Specifically, we quantify and characterize the role of large spatiotemporal extreme events in gross primary production (GPP) as triggers of continental anomalies. We also investigate seasonal dynamics of extreme impacts on continental GPP anomalies. We find that the 50 largest positive extremes (i.e., statistically unusual increases in carbon uptake rates) and negative extremes (i.e., statistically unusual decreases in carbon uptake rates) on each continent can explain most of the continental variation in GPP, which is in line with previous results obtained at the global scale. We show that negative extremes are larger than positive ones and demonstrate that this asymmetry is particularly strong in South America and Europe. Our analysis indicates that the overall impacts and the spatial extents of GPP extremes are power-law distributed with exponents that vary little across continents. Moreover, we show that on all continents and for all data sets the spatial extents play a more important role for the overall impact of GPP extremes compared to the durations or maximal GPP. An analysis of possible causes across continents indicates that most negative extremes in GPP can be attributed clearly to water scarcity, whereas extreme temperatures play a secondary role. However, for Europe, South America and Oceania we also identify fire as an important driver. Our findings are consistent with remote sensing products. An independent validation against a literature survey on specific extreme events supports our results to a large extent.

scholarly journals Remote sensing of near-infrared chlorophyll fluorescence from space in scattering atmospheres: implications for its retrieval and interferences with atmospheric CO<sub>2</sub> retrievals

2012 ◽  
Vol 5 (8) ◽  
pp. 2081-2094 ◽  
Author(s):  
C. Frankenberg ◽  
C. O'Dell ◽  
L. Guanter ◽  
J. McDuffie
Keyword(s):  
Chlorophyll Fluorescence ◽  
Greenhouse Gas ◽  
Near Infrared ◽  
Global Scale ◽  
Oxygen Absorption ◽  
Random Errors ◽  
Solar Absorption ◽  
Systematic Biases ◽  
Gas Space ◽  
Absorption Features

Abstract. With the advent of dedicated greenhouse gas space-borne spectrometers sporting high resolution spectra in the O2 A-band spectral region (755–774 nm), the retrieval of chlorophyll fluorescence has become feasible on a global scale. If unaccounted for, however, fluorescence can indirectly perturb the greenhouse gas retrievals as it perturbs the oxygen absorption features. As atmospheric CO2 measurements are used to invert net fluxes at the land–atmosphere interface, a bias caused by fluorescence can be crucial as it will spatially correlate with the fluxes to be inverted. Avoiding a bias and retrieving fluorescence accurately will provide additional constraints on both the net and gross fluxes in the global carbon cycle. We show that chlorophyll fluorescence, if neglected, systematically interferes with full-physics multi-band XCO2 retrievals using the O2 A-band. Systematic biases in XCO2 can amount to +1 ppm if fluorescence constitutes 1% to the continuum level radiance. We show that this bias can be largely eliminated by simultaneously fitting fluorescence in a full-physics based retrieval. If fluorescence is the primary target, a dedicated but very simple retrieval based purely on Fraunhofer lines is shown to be more accurate and very robust even in the presence of large scattering optical depths. We find that about 80% of the surface fluorescence is retained at the top-of-atmosphere, even for cloud optical thicknesses around 2–5. We further show that small instrument modifications to future O2 A-band spectrometer spectral ranges can result in largely reduced random errors in chlorophyll fluorescence, paving the way towards a more dedicated instrument exploiting solar absorption features only.

scholarly journals Vegetation modulates the impact of climate extremes on gross primary production

2020 ◽  
Author(s):  
Milan Flach ◽  
Alexander Brenning ◽  
Fabian Gans ◽  
Markus Reichstein ◽  
Sebastian Sippel ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Primary Production ◽  
Gross Primary Production ◽  
Climate Extremes ◽  
Co2 Flux ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
The One ◽  
The Impact ◽  
Heat Events

Abstract. Drought and heat events affect the uptake and sequestration of carbon in terrestrial ecosystems. Factors such as the duration, timing and intensity of extreme events influence the magnitude of impacts on ecosystem processes such as gross primary production (GPP), i.e. the ecosystem uptake of CO2. Preceding soil moisture depletion may exacerbate these impacts. However, some vegetation types may be more resilient to climate extremes than others. This effect is insufficiently understood at the global scale and is the focus of this study. Using a global upscaled product of GPP that scales up in-situ land CO2 flux observations with global satellite remote sensing, we study the impact of climate extremes at the global scale. We find that GPP in grasslands and agricultural areas is generally reduced during heat and drought events. However, we also find that forests, if considered globally, appear not in general to be particularly sensitive to droughts and heat events that occurred during the analyzed period or even show increased GPP values during these events. On the one hand, this is in many cases plausible, e.g. when no negative preconditioning has occurred. On the other hand, however, this may also reflect a lack of sensitivity in current remote sensing derived GPP products to the effects of droughts and heatwaves. The overall picture calls for a differentiated consideration of different land cover types in the assessments of risks of climate extremes for ecosystem functioning.

scholarly journals Vegetation modulates the impact of climate extremes on gross primary production

2021 ◽  
Vol 18 (1) ◽  
pp. 39-53
Author(s):  
Milan Flach ◽  
Alexander Brenning ◽  
Fabian Gans ◽  
Markus Reichstein ◽  
Sebastian Sippel ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Primary Production ◽  
Gross Primary Production ◽  
Climate Extremes ◽  
Co2 Flux ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
The One ◽  
The Impact ◽  
Heat Events

Abstract. Drought and heat events affect the uptake and sequestration of carbon in terrestrial ecosystems. Factors such as the duration, timing, and intensity of extreme events influence the magnitude of impacts on ecosystem processes such as gross primary production (GPP), i.e., the ecosystem uptake of CO2. Preceding soil moisture depletion may exacerbate these impacts. However, some vegetation types may be more resilient to climate extremes than others. This effect is insufficiently understood at the global scale and is the focus of this study. Using a global upscaled product of GPP that scales up in situ land CO2 flux observations with global satellite remote sensing, we study the impact of climate extremes at the global scale. We find that GPP in grasslands and agricultural areas is generally reduced during heat and drought events. However, we also find that forests, if considered globally, appear in general to not be particularly sensitive to droughts and heat events that occurred during the analyzed period or even show increased GPP values during these events. On the one hand, normal-to-increased GPP values are in many cases plausible, e.g., when conditions prior to the event have been particularly positive. On the other hand, however, normal-to-increased GPP values in forests may also reflect a lack of sensitivity in current remote-sensing-derived GPP products to the effects of droughts and heatwaves. The overall picture calls for a differentiated consideration of different land cover types in the assessments of risks of climate extremes for ecosystem functioning.

scholarly journals Tipping the ENSO into a permanent El Niño can trigger state transitions in global terrestrial ecosystems

2019 ◽  
Author(s):  
Mateo Duque-Villegas ◽  
Juan F. Salazar ◽  
Angela M. Rendón
Keyword(s):  
Primary Production ◽  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
Gross Primary Production ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
State Transitions

Abstract. Some large-scale components of the Earth's climate system have been identified as policy-relevant tipping elements, meaning that anthropogenic forcing and perturbations may push them across a tipping point threshold, with potential global scale impact on ecosystems and concomitant environmental and social phenomena. A pronounced change in the amplitude and/or frequency of the El Niño-Southern Oscillation (ENSO) is among such tipping elements. Here we use the Planet Simulator (PlaSim), an Earth system model of intermediate complexity, to investigate the potential impact on global climate and terrestrial ecosystems of shifting the current dynamics of the ENSO into a permanent El Niño. When forced with sea surface temperature (SST) derived from observations, the PlaSim model yields a realistic representation of large-scale climatological patterns, including realistic estimates of the global energy and water balances, and gross primary production. In a permanent El Niño state, we found significant differences in the global distribution of water and energy fluxes, and associated impacts on gross primary production, indicating that vegetation productivity decreases in the tropics whereas it increases in temperate and boreal regions. We identify regions in which these El Niño-induced changes are consistent with potential state transitions in global terrestrial ecosystems, including potential dieback of the Amazon rainforest, southward expansion of the Sahel, and further aridification of Australia.

scholarly journals Potential of the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor for the monitoring of terrestrial chlorophyll fluorescence

2015 ◽  
Vol 8 (3) ◽  
pp. 1337-1352 ◽  
Author(s):  
L. Guanter ◽  
I. Aben ◽  
P. Tol ◽  
J. M. Krijger ◽  
A. Hollstein ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Canopy Structure ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
Pixel Size ◽  
Satellite Mission ◽  
Spectral Window ◽  
Monitoring Instrument ◽  
Vegetation Parameters ◽  
Spatio Temporal

Abstract. Global monitoring of sun-induced chlorophyll fluorescence (SIF) is improving our knowledge about the photosynthetic functioning of terrestrial ecosystems. The feasibility of SIF retrievals from spaceborne atmospheric spectrometers has been demonstrated by a number of studies in the last years. In this work, we investigate the potential of the upcoming TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite mission for SIF retrieval. TROPOMI will sample the 675–775 nm spectral window with a spectral resolution of 0.5 nm and a pixel size of 7 km × 7 km. We use an extensive set of simulated TROPOMI data in order to assess the uncertainty of single SIF retrievals and subsequent spatio-temporal composites. Our results illustrate the enormous improvement in SIF monitoring achievable with TROPOMI with respect to comparable spectrometers currently in-flight, such as the Global Ozone Monitoring Experiment-2 (GOME-2) instrument. We find that TROPOMI can reduce global uncertainties in SIF mapping by more than a factor of 2 with respect to GOME-2, which comes together with an approximately 5-fold improvement in spatial sampling. Finally, we discuss the potential of TROPOMI to map other important vegetation parameters at a global scale with moderate spatial resolution and short revisit time. Those include leaf photosynthetic pigments and proxies for canopy structure, which will complement SIF retrievals for a self-contained description of vegetation condition and functioning.

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