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

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.

Download Full-text

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

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-7-12545-2014 ◽

2014 ◽

Vol 7 (12) ◽

pp. 12545-12588 ◽

Cited By ~ 4

Author(s):

L. Guanter ◽

I. Aben ◽

P. Tol ◽

J. M. Krijger ◽

A. Hollstein ◽

...

Keyword(s):

Chlorophyll Fluorescence ◽

Canopy Structure ◽

Terrestrial Ecosystems ◽

Pixel Size ◽

Satellite Mission ◽

Spectral Window ◽

Monitoring Instrument ◽

Vegetation Parameters ◽

Ozone Monitoring ◽

Spatio Temporal

Abstract. Global monitoring of sun-induced chlorophyll fluorescence (SIF) can improve 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 2 with respect to GOME-2, which comes together with an about 5-fold improvement in spatial sampling. Finally, we discuss the potential of TROPOMI to accurately map other important vegetation parameters, such as leaf photosynthetic pigments and proxies for canopy structure, which will complement SIF retrievals for a self-contained description of vegetation condition and functioning.

Download Full-text

Sun-Induced chlorophyll Fluorescence full spectrum retrieval and analysis of long-term time series

10.5194/egusphere-egu2020-21306 ◽

2020 ◽

Author(s):

Ilaria Cesana ◽

Sergio Cogliati ◽

Marco Celesti ◽

Tommaso Julitta ◽

Roberto Colombo

Keyword(s):

Chlorophyll Fluorescence ◽

Chlorophyll Content ◽

Canopy Structure ◽

Fluorescence Emission ◽

Simulated Data ◽

Terrestrial Ecosystems ◽

Retrieval Algorithm ◽

Satellite Mission ◽

Biophysical Parameters ◽

Full Spectrum

Remote sensing of Sun-Induced chlorophyll Fluorescence (SIF) represents a growing and promising area of research in support of the upcoming ESA&#8217;s FLEX (FLuorescence EXplorer) satellite mission. For this reason, the link between SIF and photosynthetic activity has been widely explored in the recent years, as tool to characterize and monitoring terrestrial ecosystems functioning.&#160;The SIF detection is challenging because this faint signal (which represents only few percent of the total radiance) is over imposed on the light reflected from the Earth&#8217;s surface. Decoupling these two contributions is not trivial and dedicated algorithms are needed. For this reason, a novel SIF retrieval algorithm, named SpecFit, has been developed in order to retrieve the entire SIF spectrum in the entire wavelength interval in which chlorophyll fluorescence emission occurs (670-768 nm). This novel approach is able to disentangle SIF and reflectance contributions from the total radiance spectrum emerging from the top of canopy. Nevertheless, the further interpretation of the SIF spectrum in relation to plant photosynthesis is complicated by the fact that the SIF signal is strongly influenced by several biophysical parameters, such as canopy structure and chlorophyll content that affect the leaves/canopy radiation transfer and therefore the overall remote sensed signal.&#160;The proposed work aims to verify first the SpecFit algorithm robustness on both simulated and field data and, second to investigate the potential of novel fluorescence indexes defined from the SIF full spectrum.&#160; &#160;&#160;The algorithm accuracy has been tested on a set of simulated data, obtained by coupling MODTRAN (atmosphere) and SCOPE (canopy) radiative transfer models. Scatterplots between forward simulations and retrieved SIF showed R2 close to 0.98 considering all the evaluated metrics, namely: maximum of the peaks in the red and far-red and SIF spectrum integral.The temporal series acquired during the ESA&#8217;s ATMOFlex and FLEXSense campaigns organised in an agricultural area in Braccagni (Tuscany, Italy) were, instead, used to test the algorithm on experimental measures acquired with FLOX spectrometers, from February to August on different crops (forage, alfalfa and corn). For the first time, SIF spectra observed on different vegetation species at different growing stages are presented in this work and their consistency with SIF values estimated by the more consolidated and widely used Spectral Fitting retrieval Method (SFM) are presented. The relationship found shows a linear regression slopes close to 1, intercepts approximately equal to 0 and R2 higher than 0.92 are all evidences of the SpecFit accuracy. &#160;&#160;The final step consists in analysing the temporal evolution of novel fluorescence indexes derived from the SIF spectrum. Specifically, SpecFit SIF evaluated at 760 nm and 687 nm and normalized by the retrieved spectrum integral (SIFSpecFit/SIFINT) were compared to the index SIF760/SIF687, the latter is a proxy of the chlorophyll content. SIF760/SIF687 and SIF760/SIFINT increase linearly during the growing season due to re-absorption processes that affect both the indexes. Conversely, an inverse relationship is found between SIF760/SIF687and SIF687/SIFINT because the contribute in the visible red wavelengths to the integral become weaker at increasing biomass content.&#160;

Download Full-text

The spatio-temporal evolution of groundwater dependent precipitation

10.5194/egusphere-egu21-15579 ◽

2021 ◽

Author(s):

Cristina Passet ◽

Lan Wang-Erlandsson ◽

Yoshihide Wada ◽

Agnes Pranindita ◽

Agatha De Boer

Keyword(s):

Temporal Evolution ◽

Groundwater Resources ◽

Terrestrial Ecosystems ◽

Global Scale ◽

Groundwater Abstraction ◽

Groundwater Availability ◽

Basin Scale ◽

The Usa ◽

Spatio Temporal ◽

Selection Of

<div>A substantial portion of groundwater abstracted from aquifers is used for irrigation and evaporated to the atmosphere, potentially contributing towards downwind precipitation. While the fate of evaporation fluxes from land have been analysed, the atmospheric pathways of evaporation originating from groundwater have not yet been globally quantified. This study analysed the geographical distribution, the seasonality and the magnitude of groundwater-dependent precipitation (Pgw)&#160;at a global scale and for a selection of countries and river basins. The Eulerian moisture tracking WAM-2layers model was used to process meteorological and groundwater abstraction input data from 1980 to 2010. &#160;Results show considerable contributions of groundwater to precipitation downwind of the most heavily irrigated areas, leading to net groundwater losses over these areas. Globally, 40% of the Pgw&#160;precipitates directly in the oceans, and do not contribute to biomass production in terrestrial ecosystems. Some of the countries with the highest rates of groundwater abstraction (India, the USA, Pakistan and Iran), receive low volumes of Pgw&#160;and are net losers of groundwater resources. The countries with the highest net gain of groundwater are China, Canada and Russia. At river basin scale, the Indus, Ganges and Mississippi basins are net losers of groundwater to downwind Pgw, while the Yangtze, Tarim and Brahmaputra basins receive more Pgw&#160;than their groundwater withdrawals. The share of precipitation that originates from groundwater varies considerably with seasons, and can be especially high when low local precipitation levels occur in combination with high upwind groundwater abstraction. Furthermore, precipitation dependence on&#160;groundwater (&#961;gw), has steadily increased between 1980 to 2010 in all studied areas and globally. Our study suggests that the countries and basins with a high and increasing dependency on &#961;gw&#160;to support their precipitation can be vulnerable to groundwater availability upwind.</div>

Download Full-text

Wide discrepancies in the magnitude and direction of modeled solar-induced chlorophyll fluorescence in response to light conditions

Biogeosciences ◽

10.5194/bg-17-3733-2020 ◽

2020 ◽

Vol 17 (13) ◽

pp. 3733-3755 ◽

Cited By ~ 2

Author(s):

Nicholas C. Parazoo ◽

Troy Magney ◽

Alex Norton ◽

Brett Raczka ◽

Cédric Bacour ◽

...

Keyword(s):

Chlorophyll Fluorescence ◽

Canopy Structure ◽

Fluorescence Emission ◽

Light Response ◽

Global Scale ◽

Primary Objective ◽

Mechanistic Modeling ◽

Quantum Yields ◽

Fluorescence Quantum Yields ◽

Community Land Model

Abstract. Recent successes in passive remote sensing of far-red solar-induced chlorophyll fluorescence (SIF) have spurred the development and integration of canopy-level fluorescence models in global terrestrial biosphere models (TBMs) for climate and carbon cycle research. The interaction of fluorescence with photochemistry at the leaf and canopy scales provides opportunities to diagnose and constrain model simulations of photosynthesis and related processes, through direct comparison to and assimilation of tower, airborne, and satellite data. TBMs describe key processes related to the absorption of sunlight, leaf-level fluorescence emission, scattering, and reabsorption throughout the canopy. Here, we analyze simulations from an ensemble of process-based TBM–SIF models (SiB3 – Simple Biosphere Model, SiB4, CLM4.5 – Community Land Model, CLM5.0, BETHY – Biosphere Energy Transfer Hydrology, ORCHIDEE – Organizing Carbon and Hydrology In Dynamic Ecosystems, and BEPS – Boreal Ecosystems Productivity Simulator) and the SCOPE (Soil Canopy Observation Photosynthesis Energy) canopy radiation and vegetation model at a subalpine evergreen needleleaf forest near Niwot Ridge, Colorado. These models are forced with local meteorology and analyzed against tower-based continuous far-red SIF and gross-primary-productivity-partitioned (GPP) eddy covariance data at diurnal and synoptic scales during the growing season (July–August 2017). Our primary objective is to summarize the site-level state of the art in TBM–SIF modeling over a relatively short time period (summer) when light, canopy structure, and pigments are similar, setting the stage for regional- to global-scale analyses. We find that these models are generally well constrained in simulating photosynthetic yield but show strongly divergent patterns in the simulation of absorbed photosynthetic active radiation (PAR), absolute GPP and fluorescence, quantum yields, and light response at the leaf and canopy scales. This study highlights the need for mechanistic modeling of nonphotochemical quenching in stressed and unstressed environments and improved the representation of light absorption (APAR), distribution of light across sunlit and shaded leaves, and radiative transfer from the leaf to the canopy scale.

Download Full-text

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

Atmospheric Measurement Techniques ◽

10.5194/amt-13-4295-2020 ◽

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.

Download Full-text

A near-global, high resolution land surface parameter dataset for the variable infiltration capacity model

Scientific Data ◽

10.1038/s41597-021-00999-4 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Jacob R. Schaperow ◽

Dongyue Li ◽

Steven A. Margulis ◽

Dennis P. Lettenmaier

Keyword(s):

Land Surface ◽

Global Scale ◽

Radiation Budget ◽

Soil Parameters ◽

Variable Infiltration Capacity ◽

Infiltration Capacity ◽

Vic Model ◽

Spatial Coverage ◽

Land Surface Parameter ◽

Vegetation Parameters

AbstractHydrologic models predict the spatial and temporal distribution of water and energy at the land surface. Currently, parameter availability limits global-scale hydrologic modelling to very coarse resolution, hindering researchers from resolving fine-scale variability. With the aim of addressing this problem, we present a set of globally consistent soil and vegetation parameters for the Variable Infiltration Capacity (VIC) model at 1/16° resolution (approximately 6 km at the equator), with spatial coverage from 60°S to 85°N. Soil parameters derived from interpolated soil profiles and vegetation parameters estimated from space-based MODIS measurements have been compiled into input files for both the Classic and Image drivers of the VIC model, version 5. Geographical subsetting codes are provided, as well. Our dataset provides all necessary land surface parameters to run the VIC model at regional to global scale. We evaluate VICGlobal’s ability to simulate the water balance in the Upper Colorado River basin and 12 smaller basins in the CONUS, and their ability to simulate the radiation budget at six SURFRAD stations in the CONUS.

Download Full-text

Plant ecophysiological processes in spectral profiles: perspective from a deciduous broadleaf forest

Journal of Plant Research ◽

10.1007/s10265-021-01302-7 ◽

2021 ◽

Author(s):

Hibiki M. Noda ◽

Hiroyuki Muraoka ◽

Kenlo Nishida Nasahara

Keyword(s):

Remote Sensing ◽

Optical Properties ◽

Spectral Reflectance ◽

Canopy Structure ◽

Terrestrial Ecosystems ◽

Optical Remote Sensing ◽

Canopy Reflectance ◽

Broadleaf Forest ◽

Leaf Optical Properties ◽

Deciduous Broadleaf Forest

AbstractThe need for progress in satellite remote sensing of terrestrial ecosystems is intensifying under climate change. Further progress in Earth observations of photosynthetic activity and primary production from local to global scales is fundamental to the analysis of the current status and changes in the photosynthetic productivity of terrestrial ecosystems. In this paper, we review plant ecophysiological processes affecting optical properties of the forest canopy which can be measured with optical remote sensing by Earth-observation satellites. Spectral reflectance measured by optical remote sensing is utilized to estimate the temporal and spatial variations in the canopy structure and primary productivity. Optical information reflects the physical characteristics of the targeted vegetation; to use this information efficiently, mechanistic understanding of the basic consequences of plant ecophysiological and optical properties is essential over broad scales, from single leaf to canopy and landscape. In theory, canopy spectral reflectance is regulated by leaf optical properties (reflectance and transmittance spectra) and canopy structure (geometrical distributions of leaf area and angle). In a deciduous broadleaf forest, our measurements and modeling analysis of leaf-level characteristics showed that seasonal changes in chlorophyll content and mesophyll structure of deciduous tree species lead to a seasonal change in leaf optical properties. The canopy reflectance spectrum of the deciduous forest also changes with season. In particular, canopy reflectance in the green region showed a unique pattern in the early growing season: green reflectance increased rapidly after leaf emergence and decreased rapidly after canopy closure. Our model simulation showed that the seasonal change in the leaf optical properties and leaf area index caused this pattern. Based on this understanding we discuss how we can gain ecophysiological information from satellite images at the landscape level. Finally, we discuss the challenges and opportunities of ecophysiological remote sensing by satellites.

Download Full-text

Retrieving Sun-Induced Chlorophyll Fluorescence from Hyperspectral Data with TanSat Satellite

Sensors ◽

10.3390/s21144886 ◽

2021 ◽

Vol 21 (14) ◽

pp. 4886

Author(s):

Shilei Li ◽

Maofang Gao ◽

Zhao-Liang Li

Keyword(s):

Chlorophyll Fluorescence ◽

Fluorescence Spectrum ◽

Singular Vector ◽

Low Frequency ◽

Information Criterion ◽

Hyperspectral Data ◽

High Spectral Resolution ◽

Remotely Sensed Data ◽

Spectral Window ◽

Vector Decomposition

A series of algorithms for satellite retrievals of sun-induced chlorophyll fluorescence (SIF) have been developed and applied to different sensors. However, research on SIF retrieval using hyperspectral data is performed in narrow spectral windows, assuming that SIF remains constant. In this paper, based on the singular vector decomposition (SVD) technique, we present an approach for retrieving SIF, which can be applied to remotely sensed data with ultra-high spectral resolution and in a broad spectral window without assuming that the SIF remains constant. The idea is to combine the first singular vector, the pivotal information of the non-fluorescence spectrum, with the low-frequency contribution of the atmosphere, plus a linear combination of the remaining singular vectors to express the non-fluorescence spectrum. Subject to instrument settings, the retrieval was performed within a spectral window of approximately 7 nm that contained only Fraunhofer lines. In our retrieval, hyperspectral data of the O2-A band from the first Chinese carbon dioxide observation satellite (TanSat) was used. The Bayesian Information Criterion (BIC) was introduced to self-adaptively determine the number of free parameters and reduce retrieval noise. SIF retrievals were compared with TanSat SIF and OCO-2 SIF. The results showed good consistency and rationality. A sensitivity analysis was also conducted to verify the performance of this approach. To summarize, the approach would provide more possibilities for retrieving SIF from hyperspectral data.

Download Full-text

Reduced resilience of terrestrial ecosystems locally is not reflected on a global scale

Communications Earth & Environment ◽

10.1038/s43247-021-00163-1 ◽

2021 ◽

Vol 2 (1) ◽

Author(s):

Yuhao Feng ◽

Haojie Su ◽

Zhiyao Tang ◽

Shaopeng Wang ◽

Xia Zhao ◽

...

Keyword(s):

Climate Change ◽

Global Climate Change ◽

Vegetation Index ◽

Global Climate ◽

Terrestrial Ecosystem ◽

Terrestrial Ecosystems ◽

Global Scale ◽

Ecological Resilience ◽

Terrestrial Vegetation ◽

Ecosystem Resilience

AbstractGlobal climate change likely alters the structure and function of vegetation and the stability of terrestrial ecosystems. It is therefore important to assess the factors controlling ecosystem resilience from local to global scales. Here we assess terrestrial vegetation resilience over the past 35 years using early warning indicators calculated from normalized difference vegetation index data. On a local scale we find that climate change reduced the resilience of ecosystems in 64.5% of the global terrestrial vegetated area. Temperature had a greater influence on vegetation resilience than precipitation, while climate mean state had a greater influence than climate variability. However, there is no evidence for decreased ecological resilience on larger scales. Instead, climate warming increased spatial asynchrony of vegetation which buffered the global-scale impacts on resilience. We suggest that the response of terrestrial ecosystem resilience to global climate change is scale-dependent and influenced by spatial asynchrony on the global scale.

Download Full-text

Temporal Variation of Chlorophyll-a Concentrations in Highly Dynamic Waters from Unattended Sensors and Remote Sensing Observations

Sensors ◽

10.3390/s18082699 ◽

2018 ◽

Vol 18 (8) ◽

pp. 2699 ◽

Cited By ~ 2

Author(s):

Jian Li ◽

Liqiao Tian ◽

Qingjun Song ◽

Zhaohua Sun ◽

Hongjing Yu ◽

...

Keyword(s):

Remote Sensing ◽

Water Quality ◽

Chlorophyll Fluorescence ◽

Chlorophyll A ◽

Temporal Variations ◽

Lake Area ◽

Short Term ◽

Chl A ◽

Spatio Temporal

Monitoring of water quality changes in highly dynamic inland lakes is frequently impeded by insufficient spatial and temporal coverage, for both field surveys and remote sensing methods. To track short-term variations of chlorophyll fluorescence and chlorophyll-a concentrations in Poyang Lake, the largest freshwater lake in China, high-frequency, in-situ, measurements were collected from two fixed stations. The K-mean clustering method was also applied to identify clusters with similar spatio-temporal variations, using remote sensing Chl-a data products from the MERIS satellite, taken from 2003 to 2012. Four lake area classes were obtained with distinct spatio-temporal patterns, two of which were selected for in situ measurement. Distinct daily periodic variations were observed, with peaks at approximately 3:00 PM and troughs at night or early morning. Short-term variations of chlorophyll fluorescence and Chl-a levels were revealed, with a maximum intra-diurnal ratio of 5.1 and inter-diurnal ratio of 7.4, respectively. Using geostatistical analysis, the temporal range of chlorophyll fluorescence and corresponding Chl-a variations was determined to be 9.6 h, which indicates that there is a temporal discrepancy between Chl-a variations and the sampling frequency of current satellite missions. An analysis of the optimal sampling strategies demonstrated that the influence of the sampling time on the mean Chl-a concentrations observed was higher than 25%, and the uncertainty of any single Terra/MODIS or Aqua/MODIS observation was approximately 15%. Therefore, sampling twice a day is essential to resolve Chl-a variations with a bias level of 10% or less. The results highlight short-term variations of critical water quality parameters in freshwater, and they help identify specific design requirements for geostationary earth observation missions, so that they can better address the challenges of monitoring complex coastal and inland environments around the world.

Download Full-text