Nadine Gobron

Recent decline in the global land evapotranspiration trend due to limited moisture supply

More than half of the solar energy absorbed by land surfaces is currently used to evaporate water. Climate change is expected to intensify the hydrological cycle and to alter evapotranspiration, with implications for ecosystem services and feedback to regional and global climate. Evapotranspiration changes may already be under way, but direct observational constraints are lacking at the global scale. Until such evidence is available, changes in the water cycle on land—a key diagnostic criterion of the effects of climate change and variability—remain uncertain. Here we provide a data-driven estimate of global land evapotranspiration from 1982 to 2008, compiled using a global monitoring network, meteorological and remote-sensing observations, and a machine-learning algorithm. In addition, we have assessed evapotranspiration variations over the same time period using an ensemble of process-based land-surface models. Our results suggest that global annual evapotranspiration increased on average by 7.1 ± 1.0 millimetres per year per decade from 1982 to 1997. After that, coincident with the last major El Niño event in 1998, the global evapotranspiration increase seems to have ceased until 2008. This change was driven primarily by moisture limitation in the Southern Hemisphere, particularly Africa and Australia. In these regions, microwave satellite observations indicate that soil moisture decreased from 1998 to 2008. Hence, increasing soil-moisture limitations on evapotranspiration largely explain the recent decline of the global land-evapotranspiration trend. Whether the changing behaviour of evapotranspiration is representative of natural climate variability or reflects a more permanent reorganization of the land water cycle is a key question for earth system science.

Global patterns of land‐atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations

We upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE). We trained MTE to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use. We applied the trained MTEs to generate global flux fields at a 0.5 degrees x 0.5 degrees spatial resolution and a monthly temporal resolution from 1982 to 2008. Cross-validation analyses revealed good performance of MTE in predicting among-site flux variability with modeling efficiencies (MEf) between 0.64 and 0.84, except for NEE (MEf = 0.32). Performance was also good for predicting seasonal patterns (MEf between 0.84 and 0.89, except for NEE (0.64)). By comparison, predictions of monthly anomalies were not as strong (MEf between 0.29 and 0.52). Improved accounting of disturbance and lagged environmental effects, along with improved characterization of errors in the training data set, would contribute most to further reducing uncertainties. Our global estimates of LE (158 +/- 7 J x 10(18) yr(-1)), H (164 +/- 15 J x 10(18) yr(-1)), and GPP (119 +/- 6 Pg C yr(-1)) were similar to independent estimates. Our global TER estimate (96 +/- 6 Pg C yr(-1)) was likely underestimated by 5-10%. Hot spot regions of interannual variability in carbon fluxes occurred in semiarid to semihumid regions and were controlled by moisture supply. Overall, GPP was more important to interannual variability in NEE than TER. Our empirically derived fluxes may be used for calibration and evaluation of land surface process models and for exploratory and diagnostic assessments of the biosphere.

Influence of spring and autumn phenological transitions on forest ecosystem productivity

We use eddy covariance measurements of net ecosystem productivity (NEP) from 21 FLUXNET sites (153 site-years of data) to investigate relationships between phenology and productivity (in terms of both NEP and gross ecosystem photosynthesis, GEP) in temperate and boreal forests. Results are used to evaluate the plausibility of four different conceptual models. Phenological indicators were derived from the eddy covariance time series, and from remote sensing and models. We examine spatial patterns (across sites) and temporal patterns (across years); an important conclusion is that it is likely that neither of these accurately represents how productivity will respond to future phenological shifts resulting from ongoing climate change. In spring and autumn, increased GEP resulting from an ‘extra’ day tends to be offset by concurrent, but smaller, increases in ecosystem respiration, and thus the effect on NEP is still positive. Spring productivity anomalies appear to have carry-over effects that translate to productivity anomalies in the following autumn, but it is not clear that these result directly from phenological anomalies. Finally, the productivity of evergreen needleleaf forests is less sensitive to phenology than is productivity of deciduous broadleaf forests. This has implications for how climate change may drive shifts in competition within mixed-species stands.

Designing a spectral index to estimate vegetation water content from remote sensing data: Part 1: Theoretical approach

This paper describes the methodology used to create a spectral index to retrieve vegetation water content from remotely sensed data in the solar spectrum domain. A global sensitivity analysis (GSA) using radiative transfer models is used to understand and quantify vegetation water content effects on the signal measured at three levels: leaf, canopy, and atmosphere. An index is then created that optimises retrieval of vegetation water content (in terms of water quantity per unit area at canopy level) and minimises perturbing effects of geophysical and atmospheric effects. The new index, optimised for the new SPOT-VEGETATION sensor, is presented as an example. Limitations and robustness of the index are also discussed.

Estimation of vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from atmosphere‐corrected MISR data

The multiangle imaging spectroradiometer (MISR) instrument is designed to provide global imagery at nine discrete viewing angles and four visible/near-infrared spectral bands. This paper describes an algorithm for the retrieval of leaf area index (LAI) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR) from atmospherically corrected MISR data. The proposed algorithm is designed to utilize all the information provided by this instrument, using a two-step process. The first step involves a comparison of the retrieved spectral hemispherically integrated reflectances with those determined from the model which depend on biome type, canopy structure, and soil/understory reflectances. The biome/canopy/soil/understory models that pass this comparison test are subject to the second step, which is a comparison of their directional reflectances at the MISR angles to the retrieved spectral directional reflectances. This procedure, however, can produce multiple acceptable solutions. The measure theory is used to specify the most probable values of LAI and FPAR using the set of all acceptable solutions. Optimization of the retrieval technique for efficient global processing is discussed. This paper is the second of a two-part set describing a synergistic algorithm for producing global LAI and FPAR fields from canopy reflectance data provided by the MODIS (moderate resolution imaging spectroradiometer) and MISR instruments.

A semidiscrete model for the scattering of light by vegetation

An advanced bidirectional reflectance factor model is developed to account for the architectural effects exhibited by homogeneous vegetation canopies for the first orders of light scattering. The characterization of the canopy allows the simulation of the relevant scattering processes as a function of the number, size, and orientation of the leaves, as well as the total height of the canopy. A turbid medium approach is used to represent the contribution to the total reflectance due to the light scattering at orders higher than 1. This model therefore incorporates two previously separate approaches to the problem of describing light scattering in plant canopies and enhances existing models relying on parameterized formulae to account for the hot spot effect in the extinction coefficient. Simulation results using this model compare quite favorably with those produced with a Monte Carlo ray-tracing model for a variety of vegetation cases. The semidiscrete model is also inverted against a well-documented data set of bidirectional reflectance factors taken over a soybean canopy. It is shown that the inversion of the model against a small subset of these measurements leads to reasonable values for the retrieved canopy parameters. These values are used in a direct mode to simulate the bidirectional reflectance factors for solar and viewing conditions significantly different from those available in the subset of soybean data and compared with the full set of actual measurements.

Evaluation of fraction of absorbed photosynthetically active radiation products for different canopy radiation transfer regimes: Methodology and results using Joint Research Center products derived from SeaWiFS against ground-based estimations

[1] This paper discusses the quality and the accuracy of the Joint Research Center (JRC) fraction of absorbed photosynthetically active radiation (FAPAR) products generated from an analysis of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data. The FAPAR value acts as an indicator of the presence and state of the vegetation and it can be estimated from remote sensing measurements using a physically based approach. The quality of the SeaWiFS FAPAR products assessed in this paper capitalizes on the availability of a 6-year FAPAR time series over the full globe. This evaluation exercise is performed in two phases involving, first, an analysis of the verisimilitude of the FAPAR products under documented environmental conditions and, second, a direct comparison of the FAPAR values with ground-based estimations where and when the latter are available. This second phase is conducted following a careful analysis of problems arising for performing such a comparison. This results in the grouping of available field information into broad categories representing different radiative transfer regimes. This strategy greatly helps the interpretation of the results since it recognizes the various levels of difficulty and sources of uncertainty associated with the radiative sampling of different types of vegetation canopies.

Advanced vegetation indices optimized for up-coming sensors: Design, performance, and applications

This paper describes the implementation of a physical and mathematical approach to designing advanced vegetation indices optimized for future sensors operating in the solar domain such as the medium resolution imaging spectrometer (MERIS), the global imager (GLI), and the VEGETATION instrument, and proposes an initial evaluation of such indices. These optimized indices address sensor-specific issues such as dependencies with respect to the actual spectral response of the sensor as well as the natural sensitivity of remote sensing measurements to illumination and observing geometry, to atmospheric absorption and scattering effects, and to soil color or brightness changes. The derivation of vegetation index formulae optimized to estimate the same vegetation property fraction of absorbed photosynthetically active radiation (FAPAR) from data generated by different sensors allows the comparison of their relative performances compared with existing vegetation indices, both from a theoretical and experimental point of view and permits the creation of global products, as well as the constitution of long time series from multiple sensors.

Radiation transfer model intercomparison (RAMI) exercise

The community involved in modeling radiation transfer over terrestrial surfaces designed and implemented the first phase of a radiation transfer model intercomparison (RAMI) exercise. This paper discusses the rationale and motivation for this endeavor, presents the intercomparison protocol as well as the evaluation procedures, and describes the principal results. Participants were asked to simulate the transfer of radiation for a variety of precisely defined terrestrial environments and illumination conditions. These were abstractions of typical terrestrial systems and included both homogeneous and heterogeneous scenes. The differences between the results generated by eight different models, including both one-dimensional and three-dimensional approaches, were then documented and analyzed. RAMI proposed a protocol to quantitatively assess the consequences of the model discrepancies with respect to application, such as those motivating the development of physically based inversion procedures. This first phase of model intercomparison has already proved useful in assessing the ability of the modeling community to generate similar radiation fields despite the large panoply of models that were tested. A detailed analysis of the results also permitted to identify apparent “outliers” and their main deficiencies. Future undertakings in this intercomparison framework must be oriented toward an expansion of RAMI into other and more complex geophysical systems as well as the focusing on actual inverse problems.

Uniqueness of multiangular measurements. I. An indicator of subpixel surface heterogeneity from MISR

The recent availability of quasi-simultaneous multispectral and multidirectional measurements from space, as provided by the Multi-angle Imaging SpectroRadiometer (MISR) on board the Terra platform, offers new and unique opportunities to document the anisotropy of land surfaces at critical solar wavelengths. This paper presents simple physical principles supporting the interpretation of the anisotropy of spectral radiances exiting terrestrial surfaces in terms of a signature of surface heterogeneity. The shape of the anisotropy function is represented with two model parameter values which may be mapped and interpreted in their own right. The value of one of these parameters also permits identifying geophysical conditions where the surface heterogeneity becomes significant and where three-dimensional (3D) radiation transfer effects have to be explicitly accounted for. This paper documents these findings on the basis of results from a number of 3D radiation transfer model simulations. The latter are used to perform an extensive sensitivity study which includes issues related to the scale of investigation. A preliminary validation of these results, conducted with a dataset collected by the AirMISR instrument over the Konza prairie, is also discussed.