Eric Ceschia

Bridging the gap between atmospheric concentrations and local ecosystem measurements.

This paper demonstrates that atmospheric inversions of CO2 are a reliable tool for estimating regional fluxes. We compare results of an inversion over 18 days and a 300 × 300 km2 domain in southwest France against independent measurements of fluxes from aircraft and towers. The inversion used concentration measurements from 2 towers while the independent data included 27 aircraft transects and 5 flux towers. The inversion reduces the mismatch between prior and independent fluxes, improving both spatial and temporal structures. The present mesoscale atmospheric inversion improves by 30% the CO2 fluxes over distances of few hundreds of km around the atmospheric measurement locations

Land management and land-cover change have impacts of similar magnitude on surface temperature

The direct effects of land-cover change on surface climate are increasingly well understood, but fewer studies have investigated the consequences of the trend towards more intensive land management practices. Now, research investigating the biophysical effects of temperate land-management changes reveals a net warming effect of similar magnitude to that driven by changing land cover.

Productivity, Respiration, and Light-Response Parameters of World Grassland and Agroecosystems Derived From Flux-Tower Measurements

Abstract Grasslands and agroecosystems occupy one-third of the terrestrial area, but their contribution to the global carbon cycle remains uncertain. We used a set of 316 site-years of CO2 exchange measurements to quantify gross primary productivity, respiration, and light-response parameters of grasslands, shrublands/savanna, wetlands, and cropland ecosystems worldwide. We analyzed data from 72 global flux-tower sites partitioned into gross photosynthesis and ecosystem respiration with the use of the light-response method (Gilmanov, T. G., D. A. Johnson, and N. Z. Saliendra. 2003. Growing season CO2 fluxes in a sagebrush-steppe ecosystem in Idaho: Bowen ratio/energy balance measurements and modeling. Basic and Applied Ecology 4:167–183) from the RANGEFLUX and WORLDGRASSAGRIFLUX data sets supplemented by 46 sites from the FLUXNET La Thuile data set partitioned with the use of the temperature-response method (Reichstein, M., E. Falge, D. Baldocchi, D. Papale, R. Valentini, M. Aubinet, P. Berbigier, C. Bernhofer, N. Buchmann, M. Falk, T. Gilmanov, A. Granier, T. Grünwald, K. Havránková, D. Janous, A. Knohl, T. Laurela, A. Lohila, D. Loustau, G. Matteucci, T. Meyers, F. Miglietta, J. M. Ourcival, D. Perrin, J. Pumpanen, S. Rambal, E. Rotenberg, M. Sanz, J. Tenhunen, G. Seufert, F. Vaccari, T. Vesala, and D. Yakir. 2005. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Global Change Biology 11:1424–1439). Maximum values of the quantum yield (α  =  75 mmol · mol−1), photosynthetic capacity (Amax  =  3.4 mg CO2 · m−2 · s−1), gross photosynthesis (Pg,max  =  116 g CO2 · m−2 · d−1), and ecological light-use efficiency (εecol  =  59 mmol · mol−1) of managed grasslands and high-production croplands exceeded those of most forest ecosystems, indicating the potential of nonforest ecosystems for uptake of atmospheric CO2. Maximum values of gross primary production (8 600 g CO2 · m−2 · yr−1), total ecosystem respiration (7 900 g CO2 · m−2 · yr−1), and net CO2 exchange (2 400 g CO2 · m−2 · yr−1) were observed for intensively managed grasslands and high-yield crops, and are comparable to or higher than those for forest ecosystems, excluding some tropical forests. On average, 80% of the nonforest sites were apparent sinks for atmospheric CO2, with mean net uptake of 700 g CO2 · m−2 · yr−1 for intensive grasslands and 933 g CO2 · m−2 · d−1 for croplands. However, part of these apparent sinks is accumulated in crops and forage, which are carbon pools that are harvested, transported, and decomposed off site. Therefore, although agricultural fields may be predominantly sinks for atmospheric CO2, this does not imply that they are necessarily increasing their carbon stock.

Evaluation of AMSR-E soil moisture product based on ground measurements over temperate and semi-arid regions

Soil moisture (SM) products provided by remote sensing approaches at continental scale are of great importance for land surface modeling and numerical weather prediction. Before using remotely sensed SM products it is crucial to validate them. This paper presents an evaluation of AMSR-E (Advanced Microwave Scanning Radiometer - Earth Observing System) SM products over two sites. They are located in the south-west of France and in the Sahelian part of Mali in West Africa, in the framework of the SMOSREX (Surface Monitoring Of Soil Reservoir Experiment) and AMMA (African Monsoon Multidisciplinary Analysis) projects respectively. The most representative station of the four stations of each site is used for the comparison of AMSR-E derived and in-situ SM measurements in absolute and normalized values. Results suggest that, although AMSR-E SM product is not able to capture absolute SM values, it provides reliable information on surface SM temporal variability, at seasonal and rainy event scale. It is shown, however, that the use of radiometric products, such as polarization ratio, provides better agreement with ground stations than the derived SM products.

The CarboEurope Regional Experiment Strategy

Quantification of sources and sinks of carbon at global and regional scales requires not only a good description of the land sources and sinks of carbon, but also of the synoptic and mesoscale meteorology. An experiment was performed in Les Landes, southwest France, during May?June 2005, to determine the variability in concentration gradients and fluxes of CO2. The CarboEurope Regional Experiment Strategy (CERES; see also http://carboregional.mediasfrance.org/index) aimed to produce aggregated estimates of the carbon balance of a region that can be meaningfully compared to those obtained from the smallest downscaled information of atmospheric measurements and continental-scale inversions. We deployed several aircraft to concentration sample the CO2 and fluxes over the whole area, while fixed stations observed the fluxes and concentrations at high accuracy. Several (mesoscale) meteorological modeling tools were used to plan the experiment and flight patterns. Results show that at regional scale the relation between profiles and fluxes is not obvious, and is strongly influenced by airmass history and mesoscale flow patterns. In particular, we show from an analysis of data for a single day that taking either the concentration at several locations as representative of local fluxes or taking the flux measurements at those sites as representative of larger regions would lead to incorrect conclusions about the distribution of sources and sinks of carbon. Joint consideration of the synoptic and regional flow, fluxes, and land surface is required for a correct interpretation. This calls for an experimental and modeling strategy that takes into account the large spatial gradients in concentrations and the variability in sources and sinks that arise from different land use types. We briefly describe how such an analysis can be performed and evaluate the usefulness of the data for planning of future networks or longer campaigns with reduced experimental efforts.

An Analytical Model of Evaporation Efficiency for Unsaturated Soil Surfaces with an Arbitrary Thickness

Analytical expressions of evaporative efficiency over bare soil (defined as the ratio of actual to potential soil evaporation) have been limited to soil layers with a fixed depth and/or to specific atmospheric conditions. To fill the gap, a new analytical model is developed for arbitrary soil thicknesses and varying boundary layer conditions. The soil evaporative efficiency is written [0.5 – 0.5 cos(πθL/ θmax)]^P with θL being the water content in the soil layer of thickness L, θmax the soil moisture at saturation and P a function of L and potential soil evaporation. This formulation predicts soil evaporative efficiency in both energy-driven and moisture-driven conditions, which correspond to P 0.5 respectively. For P = 0.5, an equilibrium state is identified when retention forces in the soil compensate the evaporative demand above the soil surface. The approach is applied to in situ measurements of actual evaporation, potential evaporation and soil moisture at five different depths (5, 10, 30 and 60/100 cm) collected in summer at two sites in southwestern France. It is found that (i) soil evaporative efficiency cannot be considered as a function of soil moisture only, since it also depends on potential evaporation, (ii) retention forces in the soil increase in reaction to an increase of potential evaporation and (iii) the model is able to accurately predict soil evaporation process for soil layers with an arbitrary thickness up to 100 cm. This new model representation is expected to facilitate the coupling of land surface models with multi-sensor (multi-sensing-depth) remote sensing data.

A modeling study on mitigation of N2O emissions and NO3 leaching at different agricultural sites across Europe using LandscapeDNDC

The identification of site-specific agricultural management practices in order to maximize yield while minimizing environmental nitrogen losses remains in the center of environmental pollution research. Here, we used the biogeochemical model LandscapeDNDC to explore different agricultural practices with regard to their potential to reduce soil N2O emissions and NO3 leaching while maintaining yields. In a first step, the model was tested against observations of N2O emissions, NO3 leaching, soil micrometeorology as well as crop growth for eight European cropland and grassland sites. Across sites, LandscapeDNDC predicts very well mean N2O emissions (r(2)=0.99) and simulates the magnitude and general temporal dynamics of soil inorganic nitrogen pools. For the assessment of site-specific mitigation potentials of environmental nitrogen losses a Monte Carlo optimization technique considering different agricultural management options (i.e., timing of planting, harvest and fertilization, amount of applied fertilizer as well as residue management) was used. The identified optimized field management practices reduce N2O emissions and NO3 leaching from croplands on average by 21% and 31%, respectively. Likewise, average reductions of 55% for N2O emissions and 16% for NO3 leaching are estimated for grasslands. For mitigating environmental loss - while maintaining yield levels - it was most important to reduce fertilizer application rates by in average 10%. Our analyses indicate that yield scaled N2O emissions and NO3 leaching indicate possible improvements of nitrogen use efficiencies in European farming systems. Moreover, the applied optimization approach can be used also in a prognostic way to predict optimal timings and fertilization options (rates and splitting) upon accurate weather forecasts combined with the knowledge of modeled soil nutrient availability and plant nitrogen demand.

Varying applicability of four different satellite-derived soil moisture products to global gridded crop model evaluation

Abstract Satellite-derived daily surface soil moisture products have been increasingly available, but their applicability to global gridded crop model (GGCM) evaluation is unclear. This study compares four different soil moisture products with the flux tower site observation at 18 cropland sites across the world where either of maize, soybean, rice and wheat is grown. These products include the first and second versions of Climate Change Initiative Soil Moisture (CCISM-1 and CCISM-2) datasets distributed by the European Space Agency and two different AMSR-E (Advanced Microwave Scanning Radiometer–Earth Observing System)-derived soil moisture datasets, separately provided by the Japan Aerospace Exploration Agency (AMSRE-J) and U.S. National Aeronautics and Space Administration (AMSRE-N). The comparison demonstrates varying reliability of these products in representing major characteristics of temporal pattern of cropland soil moisture by product and crop. Possible reasons for the varying reliability include the differences in sensors, algorithms, bands and criteria used when estimating soil moisture. Both the CCISM-1 and CCISM-2 products appear the most reliable for soybean- and wheat-growing area. However, the percentage of valid data of these products is always lower than other products due to relatively strict criteria when merging data derived from multiple sources, although the CCISM-2 product has much more data with valid retrievals than the CCISM-1 product. The reliability of the AMSRE-J product is the highest for maize- and rice-growing areas and comparable to or slightly lower than the CCISM products for soybean- and wheat-growing areas. The AMSRE-N is the least reliable in most location-crop combinations. The reliability of the products for rice-growing area is far lower than that of other upland crops likely due to the extensive use of irrigation and patch distribution of rice paddy in the area examined here. We conclude that the CCISM-1, CCISM-2 and AMSRE-J products are applicable to GGCM evaluation, while the AMSRE-N product is not. However, we encourage users to integrate these products with in situ soil moisture data especially when GGCMs simulations for rice are evaluated.

Eddy covariance measurements over crops

Croplands are managed ecosystems with rapid development over the course of the growing season under nearly optimal growth conditions with respect to nutrient availability (fertilization), water availability (possible irrigation in dry conditions), competition (monocultures where herbicide and fungicides applications keep other competitors off the plot) and plant health (insecticides minimize herbivory by insects).

Spatialization of crop leaf area index and biomass by combining a simple crop model SAFY and high spatial and temporal resolutions remote sensing data

The recent availability of high spatial resolution sensors offers new perspectives for terrestrial applications (agriculture, risks). The aim of this work is to develop a methodology for deriving biophysical variables (Green Leaf Area Index — GLAI, phytomass) from multi-temporal observations at high spatial resolution in order to run a crop model at a regional scale. Accurate predictive crop models require a large set of input parameters, which are not easily available over large area. Spatial upscaling of such models is thus difficult. The use of simple model avoids spatial upscaling issues. This study is focused on SAFY model (Simple Algorithm For Yield estimates) developed by [1]. Key SAFY parameters were calibrated using temporal GLAI profiles, empirically estimated from FORMOSAT-2 time series of images. Most of the SAFY parameters are crop related and have been fixed according to literature. However some parameters are more specific and have been calibrated based on GLAI derived from FORMOSAT-2 observations at a field scale. Two calibration strategies are evaluated as a function of sampling (frequency and temporal distribution) of remote sensing data. Spatial upscaling simulations are assessed based on biomass in-situ measurements taken over maize. Good agreement between modelled and measured phytomass have been found on maize (RMSE =3D 20 g.m−2).