Exploring the Potential of Satellite Solar-Induced Fluorescence to Constrain Global Transpiration Estimates

The opening and closing of plant stomata regulates the global water, carbon and energy cycles. Biophysical feedbacks on climate are highly dependent on transpiration, which is mediated by vegetation phenology and plant responses to stress conditions. Here, we explore the potential of satellite observations of solar-induced chlorophyll fluorescence (SIF)normalized by photosynthetically-active radiation (PAR)to diagnose the ratio of transpiration to potential evaporation (transpiration efficiency', ). This potential is validated at 25 eddy-covariance sites from seven biomes worldwide. The skill of the state-of-the-art land surface models (LSMs) from the eartH2Observe project to estimate is also contrasted against eddy-covariance data. Despite its relatively coarse (0.5 degrees) resolution, SIF/PAR estimates, based on data from the Global Ozone Monitoring Experiment 2 (GOME-2) and the Clouds and Earth's Radiant Energy System (CERES), correlate to the in situ significantly (average inter-site correlation of 0.59), with higher correlations during growing seasons (0.64) compared to decaying periods (0.53). In addition, the skill to diagnose the variability of in situ demonstrated by all LSMs is on average lower, indicating the potential of SIF data to constrain the formulations of transpiration in global models via, e.g., data assimilation. Overall, SIF/PAR estimates successfully capture the effect of phenological changes and environmental stress on natural ecosystem transpiration, adequately reflecting the timing of this variability without complex parameterizations.

[1]  Anny Cazenave,et al.  Global Evaluation of the ISBA-TRIP Continental Hydrological System. Part II: Uncertainties in River Routing Simulation Related to Flow Velocity and Groundwater Storage , 2010 .

[2]  A. Dolman,et al.  Fifty years since Monteith's 1965 seminal paper: the emergence of global ecohydrology , 2014 .

[3]  Dean Vickers,et al.  Five years of carbon fluxes and inherent water-use efficiency at two semi-arid pine forests with different disturbance histories , 2012 .

[4]  B. Barkstrom,et al.  Clouds and the Earth's Radiant Energy System (CERES): An Earth Observing System Experiment , 1996 .

[5]  S. Kanae,et al.  A physically based description of floodplain inundation dynamics in a global river routing model , 2011 .

[6]  P. Ciais,et al.  The carbon balance of Africa: synthesis of recent research studies , 2011, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[7]  J. Landgraf,et al.  Global Retrievals of Solar‐Induced Chlorophyll Fluorescence With TROPOMI: First Results and Intersensor Comparison to OCO‐2 , 2018, Geophysical research letters.

[8]  A. Porcar-Castell,et al.  Dynamic response of plant chlorophyll fluorescence to light, water and nutrient availability. , 2015, Functional plant biology : FPB.

[9]  Bertrand Decharme,et al.  Reconciling soil thermal and hydrological lower boundary conditions in land surface models , 2013 .

[10]  Filipe Aires,et al.  Water, Energy, and Carbon with Artificial Neural Networks (WECANN): A statistically-based estimate of global surface turbulent fluxes using solar-induced fluorescence , 2016 .

[11]  I. C. Prentice,et al.  A dynamic global vegetation model for studies of the coupled atmosphere‐biosphere system , 2005 .

[12]  Serge Rambal,et al.  The growth respiration component in eddy CO2 flux from a Quercus ilex mediterranean forest , 2004 .

[13]  Markus Reichstein,et al.  Improving canopy processes in the Community Land Model version 4 (CLM4) using global flux fields empirically inferred from FLUXNET data , 2011 .

[14]  Martina Flörke,et al.  Domestic and industrial water uses of the past 60 years as a mirror of socio-economic development: A global simulation study , 2013 .

[15]  N. McDowell,et al.  Pragmatic hydraulic theory predicts stomatal responses to climatic water deficits. , 2016, The New phytologist.

[16]  Paul D. Colaizzi,et al.  Two-source energy balance model estimates of evapotranspiration using component and composite surface temperatures☆ , 2012 .

[17]  Edwin W. Pak,et al.  An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data , 2005 .

[18]  Jaap Schellekens,et al.  MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data , 2016 .

[19]  Göran Lindström,et al.  Priestley-Taylor evapotranspiration in HBV-simulations , 1997 .

[20]  K. Moffett,et al.  Remote Sens , 2015 .

[21]  Alfredo Huete,et al.  Dry-season greening of Amazon forests , 2016, Nature.

[22]  S. Seneviratne,et al.  Climate extremes and the carbon cycle , 2013, Nature.

[23]  A. Frank,et al.  Productivity, Respiration, and Light-Response Parameters of World Grassland and Agroecosystems Derived From Flux-Tower Measurements , 2010 .

[24]  Jan Polcher,et al.  Sensitivity of the West African hydrological cycle in ORCHIDEE to infiltration processes , 2008 .

[25]  E. Middleton,et al.  First observations of global and seasonal terrestrial chlorophyll fluorescence from space , 2010 .

[26]  C. Frankenberg,et al.  Simulations of chlorophyll fluorescence incorporated into the Community Land Model version 4 , 2015, Global change biology.

[27]  K. Pearson VII. Note on regression and inheritance in the case of two parents , 1895, Proceedings of the Royal Society of London.

[28]  Xiaoliang Lu,et al.  Potential of solar-induced chlorophyll fluorescence to estimate transpiration in a temperate forest , 2018 .

[29]  Pierre Gentine,et al.  Land–atmospheric feedbacks during droughts and heatwaves: state of the science and current challenges , 2018, Annals of the New York Academy of Sciences.

[30]  A. Goldstein,et al.  What the towers don't see at night: nocturnal sap flow in trees and shrubs at two AmeriFlux sites in California. , 2007, Tree physiology.

[31]  David P. Billesbach,et al.  Spatiotemporal Variations in Growing Season Exchanges of CO2, H2O, and Sensible Heat in Agricultural Fields of the Southern Great Plains , 2007 .

[32]  J. Canadell,et al.  Greening of the Earth and its drivers , 2016 .

[33]  Matthew F. McCabe,et al.  Partitioning of evapotranspiration in remote sensing-based models , 2018, Agricultural and Forest Meteorology.

[34]  G. Collatz,et al.  Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer , 1991 .

[35]  Bofu Yu,et al.  Partitioning evapotranspiration based on the concept of underlying water use efficiency , 2016 .

[36]  Pierre Goovaerts,et al.  Fine-resolution mapping of soil organic carbon based on multivariate secondary data , 2006 .

[37]  Hans Peter Schmid,et al.  Measurements of CO2 and energy fluxes over a mixed hardwood forest in the mid-western United States , 2000 .

[38]  Richard G. Allen,et al.  Evapotranspiration between satellite overpasses: methodology and case study in agricultural dominant semi‐arid areas , 2016 .

[39]  Maurizio Mencuccini,et al.  Predicting stomatal responses to the environment from the optimization of photosynthetic gain and hydraulic cost. , 2017, Plant, cell & environment.

[40]  Philip Lewis,et al.  Retrieval and global assessment of terrestrial chlorophyll fluorescence from GOSAT space measurements , 2012 .

[41]  Marko Scholze,et al.  Assimilating solar-induced chlorophyll fluorescence into the terrestrial biosphere model BETHY-SCOPE v1.0: Model description and information content , 2017 .

[42]  P. Tregoning,et al.  A global water cycle reanalysis (2003-2012) merging satellite gravimetry and altimetry observations with a hydrological multi-model ensemble , 2013 .

[43]  A. Bondeau,et al.  Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model , 2009 .

[44]  T. Holmes,et al.  Global land-surface evaporation estimated from satellite-based observations , 2010 .

[45]  J. Vose,et al.  Drought limitations to leaf-level gas exchange: results from a model linking stomatal optimization and cohesion-tension theory. , 2016, Plant, cell & environment.

[46]  M. S. Moran,et al.  Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence , 2014, Proceedings of the National Academy of Sciences.

[47]  R. Scott Using watershed water balance to evaluate the accuracy of eddy covariance evaporation measurements for three semiarid ecosystems , 2010 .

[48]  François Tardieu,et al.  Variability among species of stomatal control under fluctuating soil water status and evaporative demand: modelling isohydric and anisohydric behaviours , 1998 .

[49]  Matthew F. McCabe,et al.  The GEWEX LandFlux project: evaluation of model evaporation using tower-based and globally gridded forcing data , 2015 .

[50]  Filipe Aires,et al.  Water, Energy, and Carbon with Artificial Neural Networks (WECANN): A statistically-based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence. , 2017, Biogeosciences.

[51]  Matthew F. McCabe,et al.  The WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation data sets , 2015 .

[52]  Marie Combe,et al.  Plant water-stress parameterization determines the strength of land-atmosphere coupling , 2016 .

[53]  Anne Verhoef,et al.  Modeling plant transpiration under limited soil water: Comparison of different plant and soil hydraulic parameterizations and preliminary implications for their use in land surface models , 2014 .

[54]  Ge Sun,et al.  Drought during canopy development has lasting effect on annual carbon balance in a deciduous temperate forest. , 2008, The New phytologist.

[55]  Dara Entekhabi,et al.  Partitioning Evapotranspiration Over the Continental United States Using Weather Station Data , 2018, Geophysical Research Letters.

[56]  N. Baker Chlorophyll fluorescence: a probe of photosynthesis in vivo. , 2008, Annual review of plant biology.

[57]  C. Frankenberg,et al.  OCO-2 advances photosynthesis observation from space via solar-induced chlorophyll fluorescence , 2017, Science.

[58]  L. Guanter,et al.  The seasonal cycle of satellite chlorophyll fluorescence observations and its relationship to vegetation phenology and ecosystem atmosphere carbon exchange , 2014 .

[59]  I. E. Woodrow,et al.  A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions , 1987 .

[60]  L. Guanter,et al.  Modeling canopy conductance and transpiration from solar-induced chlorophyll fluorescence , 2019, Agricultural and Forest Meteorology.

[61]  C. Frankenberg,et al.  New global observations of the terrestrial carbon cycle from GOSAT: Patterns of plant fluorescence with gross primary productivity , 2011, Geophysical Research Letters.

[62]  P. Milly,et al.  Potential evapotranspiration and continental drying , 2016 .

[63]  L. Guanter,et al.  Assessing the potential of sun-induced fluorescence and the canopy scattering coefficient to track large-scale vegetation dynamics in Amazon forests , 2016 .

[64]  P. Jarvis The Interpretation of the Variations in Leaf Water Potential and Stomatal Conductance Found in Canopies in the Field , 1976 .

[65]  D. Medvigy,et al.  Hydrological niche separation explains seasonal and inter-annual variations of vegetation dynamics in seasonally dry tropical forests , 2015 .

[66]  Y. Xue,et al.  Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis , 2012 .

[67]  S. J. Birks,et al.  Terrestrial water fluxes dominated by transpiration , 2013, Nature.

[68]  A. Huete,et al.  Amazon rainforests green‐up with sunlight in dry season , 2006 .

[69]  Joshua B. Fisher,et al.  Global nutrient limitation in terrestrial vegetation , 2012 .

[70]  Jing M. Chen,et al.  Angular normalization of GOME‐2 Sun‐induced chlorophyll fluorescence observation as a better proxy of vegetation productivity , 2017 .

[71]  J. Joiner,et al.  Retrieval of sun-induced chlorophyll fluorescence from space , 2014 .

[72]  Wouter H. Maes,et al.  Potential evaporation at eddy-covariance sites across the globe , 2018, Hydrology and Earth System Sciences.

[73]  Matthew O. Jones,et al.  Sunlight mediated seasonality in canopy structure and photosynthetic activity of Amazonian rainforests , 2015 .

[74]  David Medvigy,et al.  Diversity in plant hydraulic traits explains seasonal and inter-annual variations of vegetation dynamics in seasonally dry tropical forests. , 2016, The New phytologist.

[75]  George Papageorgiou,et al.  6 – Chlorophyll Fluorescence: An Intrinsic Probe of Photosynthesis , 1975 .

[76]  D. Baldocchi,et al.  Inter-annual variability in carbon dioxide exchange of an oak/grass savanna and open grassland in California , 2007 .

[77]  Russell L. Scott,et al.  The carbon balance pivot point of southwestern U.S. semiarid ecosystems: Insights from the 21st century drought , 2015 .

[78]  M. G. De Kauwe,et al.  Do land surface models need to include di ff erential plant species responses to drought ? Examining model predictions across a latitudinal gradient in Europe , 2015 .

[79]  Nicholas C. Parazoo,et al.  Global Analysis of Bioclimatic Controls on Ecosystem Productivity Using Satellite Observations of Solar-Induced Chlorophyll Fluorescence , 2017, Remote. Sens..

[80]  Petra Döll,et al.  Global-scale analysis of river flow alterations due to water withdrawals and reservoirs , 2009 .

[81]  Josep Peñuelas,et al.  Phenology Feedbacks on Climate Change , 2009, Science.

[82]  J. C. Hargreaves,et al.  Interactive comment on “ The Joint UK Land Environment Simulator ( JULES ) , Model description – Part 2 : Carbon fluxes and vegetation ” , 2011 .

[83]  Marc Aubinet,et al.  Annual net ecosystem carbon exchange by a sugar beet crop , 2006 .

[84]  G. Bonan Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests , 2008, Science.

[85]  Kathy Steppe,et al.  Solar-induced fluorescence: the best alternative to monitor global transpiration? , 2018 .

[86]  Peter G. Fairweather,et al.  CSIRO : water for a healthy country national research flagship , 2008 .

[87]  M. Susan Moran,et al.  Carbon dioxide exchange in a semidesert grassland through drought‐induced vegetation change , 2010 .

[88]  M. Rossini,et al.  Airborne based spectroscopy of red and far-red sun-induced chlorophyll fluorescence: Implications for improved estimates of gross primary productivity , 2016 .

[89]  Diego G. Miralles,et al.  Revisiting the contribution of transpiration to global terrestrial evapotranspiration , 2017 .

[90]  Paolo De Angelis,et al.  Reconciling the optimal and empirical approaches to modelling stomatal conductance , 2011 .

[91]  Niko E. C. Verhoest,et al.  Vegetation anomalies caused by antecedent precipitation in most of the world , 2017 .

[92]  Vincent Rivalland,et al.  Modelling forest transpiration and CO2 fluxes—response to soil moisture stress , 2004 .

[93]  N. Verhoest,et al.  GLEAM v3: satellite-based land evaporation and root-zone soil moisture , 2016 .

[94]  Neill Prohaska,et al.  Leaf flush drives dry season green-up of the Central Amazon , 2016 .

[95]  Zong-Liang Yang,et al.  Technical description of version 4.5 of the Community Land Model (CLM) , 2013 .

[96]  B. Hurk,et al.  A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System , 2009 .

[97]  Per Ambus,et al.  Field measurements of atmosphere-biosphere interactions in a Danish beech forest , 2003 .

[98]  J. Norman,et al.  Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature , 1995 .

[99]  W. Dorigo,et al.  A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset , 2016 .

[100]  C. Frankenberg,et al.  Linking chlorophyll a fluorescence to photosynthesis for remote sensing applications: mechanisms and challenges. , 2014, Journal of experimental botany.

[101]  C. Frankenberg,et al.  Application of satellite solar-induced chlorophyll fluorescence to understanding large-scale variations in vegetation phenology and function over northern high latitude forests , 2017 .

[102]  Reinder Ronda,et al.  Representation of the canopy conductance in modeling the surface energy budget for low vegetation , 2001 .

[103]  Martha C. Anderson,et al.  The future of evapotranspiration: Global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources , 2017 .

[104]  I. C. Prentice,et al.  Optimal stomatal behaviour around the world , 2015 .

[105]  Yi Lin,et al.  Monitoring and Assessing the 2012 Drought in the Great Plains: Analyzing Satellite-Retrieved Solar-Induced Chlorophyll Fluorescence, Drought Indices, and Gross Primary Production , 2016, Remote. Sens..

[106]  Atul K. Jain,et al.  Global Carbon Budget 2016 , 2016 .

[107]  E. Schulze,et al.  Relationships among Maximum Stomatal Conductance, Ecosystem Surface Conductance, Carbon Assimilation Rate, and Plant Nitrogen Nutrition: A Global Ecology Scaling Exercise , 1994 .