French Climate and Environment Sciences Laboratory
French Climate and Environment Sciences Laboratory
Dueri S.,IRD Montpellier |
Bopp L.,French Climate and Environment Sciences Laboratory |
Maury O.,IRD Montpellier |
Maury O.,University of Cape Town
Global Change Biology | Year: 2014
Climate-induced changes in the physical, chemical, and biological environment are expected to increasingly stress marine ecosystems, with important consequences for fisheries exploitation. Here, we use the APECOSM-E numerical model (Apex Predator ECOSystem Model - Estimation) to evaluate the future impacts of climate change on the physiology, spatial distribution, and abundance of skipjack tuna, the worldwide most fished species of tropical tuna. The main novelties of our approach lie in the mechanistic link between environmental factors, metabolic rates, and behavioral responses and in the fully three dimensional representation of habitat and population abundance. Physical and biogeochemical fields used to force the model are provided by the last generation of the IPSL-CM5 Earth System Model run from 1990 to 2100 under a 'business-as-usual' scenario (RCP8.5). Our simulations show significant changes in the spatial distribution of skipjack tuna suitable habitat, as well as in their population abundance. The model projects deterioration of skipjack habitat in most tropical waters and an improvement of habitat at higher latitudes. The primary driver of habitat changes is ocean warming, followed by food density changes. Our projections show an increase of global skipjack biomass between 2010 and 2050 followed by a marked decrease between 2050 and 2095. Spawning rates are consistent with population trends, showing that spawning depends primarily on the adult biomass. On the other hand, growth rates display very smooth temporal changes, suggesting that the ability of skipjack to keep high metabolic rates in the changing environment is generally effective. Uncertainties related to our model spatial resolution, to the lack or simplification of key processes and to the climate forcings are discussed. © 2013 John Wiley & Sons Ltd.
Huneeus N.,French Climate and Environment Sciences Laboratory |
Chevallier F.,French Climate and Environment Sciences Laboratory |
Boucher O.,University Pierre and Marie Curie
Atmospheric Chemistry and Physics | Year: 2012
This study estimates the emission fluxes of a range of aerosol species and one aerosol precursor at the global scale. These fluxes are estimated by assimilating daily total and fine mode aerosol optical depth (AOD) at 550 nm from the Moderate Resolution Imaging Spectroradiometer (MODIS) into a global aerosol model of intermediate complexity. Monthly emissions are fitted homogenously for each species over a set of predefined regions. The performance of the assimilation is evaluated by comparing the AOD after assimilation against the MODIS observations and against independent observations. The system is effective in forcing the model towards the observations, for both total and fine mode AOD. Significant improvements for the root mean square error and correlation coefficient against both the assimilated and independent datasets are observed as well as a significant decrease in the mean bias against the assimilated observations. These improvements are larger over land than over ocean. The impact of the assimilation of fine mode AOD over ocean demonstrates potential for further improvement by including fine mode AOD observations over continents. The Angström exponent is also improved in African, European and dusty stations. The estimated emission flux for black carbon is 15 Tg yr -1, 119 Tg yr -1 for particulate organic matter, 17 Pg yr -1 for sea salt, 83 TgS yr -1 for SO 2 and 1383 Tg yr -1 for desert dust. They represent a difference of +45 %, +40 %, +26 %, +13 % and-39 % respectively, with respect to the a priori values. The initial errors attributed to the emission fluxes are reduced for all estimated species. © 2012 Author(s).
Breon F.-M.,French Climate and Environment Sciences Laboratory |
Vermeulen A.,Lille University of Science and Technology |
Descloitres J.,Lille University of Science and Technology
Remote Sensing of Environment | Year: 2011
Because atmospheric aerosols scatter sunlight back to space, reflectance measurements from spaceborne radiometers can be used to estimate the aerosol load and its optical properties. Several aerosol products have been generated in a systematic way, and are available for further studies. In this paper, we evaluate the accuracy of such aerosol products derived from the measurements of POLDER, MODIS, MERIS, SEVIRI and CALIOP, through a statistical comparison with Aerosol Optical Depth (AOD) measurements from the AERONET sunphotometer network. Although this method is commonly used, this study is, to our knowledge, among the most extensive of its type since it compares the performance of the products from 5 different sensors using up to five years of data for each of them at global scale. The choice of these satellite aerosol datasets was based on their availability at the ICARE Data and Service Centre (www.icare.univ-lille1.fr).We distinguish between retrievals over land and ocean and between estimates of total and fine mode AOD. Over the oceans, POLDER and MODIS retrievals are of similar quality, with RMS difference lower than 0.1 and a correlation with AERONET of around 0.9. The POLDER estimates suffer from a small positive bias for clean atmospheres, which weakens its statistics. The other aerosol products are of lesser quality, although the SEVIRI products may be of interest for some applications that require a high temporal resolution. The MERIS product shows a very high bias. Over land, only the MODIS product offers a reliable estimate of the total AOD. On the other hand, the polarization-based retrieval using POLDER data allows a better fine mode estimate than that from MODIS. These results suggest the need for a product combining POLDER and MODIS products over land. The paper also analyses how the statistics change with the spatial and temporal thresholds that are used. Spatio-temporal averaging improves the statistics only slightly, which indicates that random errors are not dominant in the error budget. The paper includes various statistical indicators at global scale, and detailed results at individual ground stations can be obtained on request from the authors. © 2011 Elsevier Inc.
Hauglustaine D.A.,French Climate and Environment Sciences Laboratory |
Balkanski Y.,French Climate and Environment Sciences Laboratory |
Schulz M.,Norwegian Meteorological Institute
Atmospheric Chemistry and Physics | Year: 2014
The ammonia cycle and nitrate particle formation are introduced into the LMDz-INCA (Laboratoire de Météorologie Dynamique, version 4-INteraction with Chemistry and Aerosols, version 3) global model. An important aspect of this new model is that both fine nitrate particle formation in the accumulation mode and coarse nitrate forming on existing dust and sea-salt particles are considered. The model simulates distributions of nitrates and related species in agreement with previous studies and observations. The calculated present-day total nitrate direct radiative forcing since the pre-industrial is-'0.056 W m-2. This forcing corresponds to 18% of the sulfate forcing. Fine particles largely dominate the nitrate forcing, representing close to 90% of this value. The model has been used to investigate the future changes in nitrates and direct radiative forcing of climate based on snapshot simulations for the four representative concentration pathway (RCP) scenarios and for the 2030, 2050, and 2100 time horizons. Due to a decrease in fossil fuel emissions in the future, the concentration of most of the species involved in the nitrate-ammonium-sulfate system drop by 2100 except for ammonia, which originates from agricultural practices and for which emissions significantly increase in the future. Despite the decrease of nitrate surface levels in Europe and North America, the global burden of accumulation mode nitrates increases by up to a factor of 2.6 in 2100. This increase in ammonium nitrate in the future arises despite decreasing NOx emissions due to increased availability of ammonia to form ammonium nitrate. The total aerosol direct forcing decreases from its present-day value of-'0.234 W m-2 to a range of-'0.070 to-'0.130 Wm-2 in 2100 based on the considered scenario. The direct forcing decreases for all aerosols except for nitrates, for which the direct negative forcing increases to a range of-'0.060 to-'0.115 Wm-2 in 2100. Including nitrates in the radiative forcing calculations increases the total direct forcing of aerosols by a factor of 1.3 in 2000, by a factor of 1.7-2.6 in 2030, by 1.9-4.8 in 2050, and by 6.4-8.6 in 2100. These results show that the agricultural emissions of ammonia will play a key role in the future mitigation of climate change, with nitrates becoming the dominant contributor to the anthropogenic aerosol optical depth during the second half of the 21st century and significantly increasing the calculated aerosol direct forcing. This significant increase in the influence that nitrate exerts on climate in the future will at the same time affect regional air quality and nitrogen deposition to the ecosystem.
Valet J.-P.,CNRS Paris Institute of Global Physics |
Valladas H.,French Climate and Environment Sciences Laboratory
Quaternary Science Reviews | Year: 2010
The causes of Neanderthal extinction and the transition with the modern man in Europe and Near East remain largely uncertain. The two main factors currently proposed are the arrival of a modern human competitor and/or the aptitude of the Neanderthals to survive rapidly changing climatic conditions. None of these hypotheses is fully satisfactory because the Neanderthals experienced other large climatic changes and the duration of overlap of the two populations remains largely unknown and even uncertain. No special attention has been given to the geomagnetic excursions of Laschamp and Mono Lake which are synchroneous with the extinction and were the most dramatic events encountered by the Neanderthals over the past 250 thousand years of their existence. During this period the geomagnetic field strength was considerably reduced and the shielding efficiency of the magnetosphere lowered, leaving energetic particles reach latitudes as low as 30°. The enhanced flux of high-energy protons (linked to solar activity) into the atmosphere yielded significant ozone depletion down to latitudes of 40-45°. A direct consequence was an increase of the UV-B radiations at the surface which might have reached at least 15-20% in Europe with significant impacts on health of human populations. We suggest that these conditions, added to some other factors, contributed to the demise of Neanderthal population. © 2010 Elsevier Ltd.
Paillard D.,French Climate and Environment Sciences Laboratory
Comptes Rendus - Geoscience | Year: 2010
The discovery of glacial ages in the 19th century triggered the first scientific questions on the evolution of climate through time, and thus corresponds to the dawn of palaeoclimatology. Since then, scientists have attempted to reconstruct past climatic changes and to understand their physical basis. Two competing theories have been suggested to explain the sequence of glacial-interglacial epochs: either the variations of the Earth orbital elements, or the atmospheric composition in carbon dioxide. If the astronomical theory has been largely confirmed since the last 30 years, a physical modeling of the climatic processes at work is still in its infancy. Besides, the most recent results of palaeoclimatology are clearly demonstrating that, more than never, a synthesis of these two old hypotheses is needed. © 2010 Académie des sciences.
Orr J.C.,French Climate and Environment Sciences Laboratory |
Epitalon J.-M.,French Climate and Environment Sciences Laboratory
Geoscientific Model Development | Year: 2015
Modelers compute ocean carbonate chemistry often based on code from the Ocean Carbon Cycle Model Intercomparison Project (OCMIP), last revised in 2005. Here we offer improved publicly available Fortran 95 routines to model the ocean carbonate system (mocsy 2.0). Both codes take as input dissolved inorganic carbon CT and total alkalinity AT, tracers that are conservative with respect to mixing and changes in temperature and salinity. Both use the same thermodynamic equilibria to compute surface-ocean pCO2 and simulate air-sea CO2 fluxes, but mocsy 2.0 uses a faster and safer algorithm (SolveSAPHE) to solve the alkalinity-pH equation, applicable even under extreme conditions. The OCMIP code computes only surface pCO2, while mocsy computes all other carbonate system variables throughout the water column. It also avoids three common model approximations: that density is constant, that modeled potential temperature is equal to in situ temperature, and that depth is equal to pressure. Errors from these approximations grow with depth, e.g., reaching 3% or more for pCO2, H+, and ωA at 5000 m. The mocsy package uses the equilibrium constants recommended for best practices. It also offers two new options: (1) a recently reassessed total boron concentration BT that is 4% larger and (2) new K1 and K2 formulations designed to include low-salinity waters. Although these options enhance surface pCO2 by up to 7 μatm, individually, they should be avoided until (1) best-practice equations for K1 and K2 are reevaluated with the new BT and (2) formulations of K1 and K2 for low salinities are adjusted to be consistent among pH scales. The common modeling practice of neglecting alkalinity contributions from inorganic P and Si leads to substantial biases that could easily be avoided. With standard options for best practices, mocsy agrees with results from the CO2SYS package within 0.005% for the three inorganic carbon species (concentrations differ by less than 0.01 μmol kg-1). Yet by default, mocsy's deep-water fCO2 and pCO2 are many times larger than those from older packages, because they include pressure corrections for K0 and the fugacity coefficient. © Author(s) 2015.
Carreau J.,Montpellier University |
Vrac M.,French Climate and Environment Sciences Laboratory
Water Resources Research | Year: 2011
We present a new class of stochastic downscaling models, the conditional mixture models (CMMs), which builds on neural network models. CMMs are mixture models whose parameters are functions of predictor variables. These functions are implemented with a one-layer feed-forward neural network. By combining the approximation capabilities of mixtures and neural networks, CMMs can, in principle, represent arbitrary conditional distributions. We evaluate the CMMs at downscaling precipitation data at three stations in the French Mediterranean region. A discrete (Dirac) component is included in the mixture to handle the "no-rain" events. Positive rainfall is modeled with a mixture of continuous densities, which can be either Gaussian, log-normal, or hybrid Pareto (an extension of the generalized Pareto). CMMs are stochastic weather generators in the sense that they provide a model for the conditional density of local variables given large-scale information. In this study, we did not look for the most appropriate set of predictors, and we settled for a decent set as the basis to compare the downscaling models. The set of predictors includes the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalyses sea level pressure fields on a 6 × 6 grid cell region surrounding the stations plus three date variables. We compare the three distribution families of CMMs with a simpler benchmark model, which is more common in the downscaling community. The difference between the benchmark model and CMMs is that positive rainfall is modeled with a single Gamma distribution. The results show that CMM with hybrid Pareto components outperforms both the CMM with Gaussian components and the benchmark model in terms of log-likelihood. However, there is no significant difference with the log-normal CMM. In general, the additional flexibility of mixture models, as opposed to using a single distribution, allows us to better represent the distribution of rainfall, both in the central part and in the upper tail. © 2011 by the American Geophysical Union.
Caley T.,VU University Amsterdam |
Roche D.M.,VU University Amsterdam |
Roche D.M.,French Climate and Environment Sciences Laboratory
Geoscientific Model Development | Year: 2013
Oxygen stable isotopes (δ18O) are among the most useful tools in palaeoclimatology/palaeoceanography. Simulation of oxygen stable isotopes allows testing how the past variability of these isotopes in water can be interpreted. By modelling the proxy directly in the model, the results can also be directly compared with the data. Water isotopes have been implemented in the global three-dimensional model of intermediate complexity LOVECLIM, allowing fully coupled atmosphere-ocean simulations. In this study, we present the validation of the model results for present-day climate against the global database for oxygen stable isotopes in carbonates. The limitation of the model together with the processes operating in the natural environment reveal the complexity of use the continental calcite-δ18O signal of speleothems for a global quantitative data-model comparison exercise. On the contrary, the reconstructed surface ocean calcite-δ18O signal in LOVECLIM does show a very good agreement with the late Holocene database (foraminifers) at the global and regional scales. Our results indicate that temperature and the isotopic composition of the seawater are the main control on the fossil-δ18O signal recorded in foraminifer shells when all species are grouped together. Depth habitat, seasonality and other ecological effects play a more significant role when individual species are considered. We argue that a data-model comparison for surface ocean calcite δ18O in past climates, such as the Last Glacial Maximum (≈ 21 000 yr), could constitute an interesting tool for mapping the potential shifts of the frontal systems and circulation changes throughout time. Similarly, the potential changes in intermediate oceanic circulation systems in the past could be documented by a data (benthic foraminifers)-model comparison exercise whereas future investigations are necessary in order to quantitatively compare the results with data for the deep ocean. © 2013 Author(s).
Roche D.M.,VU University Amsterdam |
Roche D.M.,French Climate and Environment Sciences Laboratory
Geoscientific Model Development | Year: 2013
A new 18O stable water isotope scheme is developed for three components of the iLOVECLIM coupled climate model: atmospheric, oceanic and land surface. The equations required to reproduce the fractionation of stable water isotopes in the simplified atmospheric model ECBilt are developed consistently with the moisture scheme. Simplifications in the processes are made to account for the simplified vertical structure including only one moist layer. Implementation of these equations together with a passive tracer scheme for the ocean and a equilibrium fractionation scheme for the land surface leads to the closure of the (isotopic-) water budget in our climate system. Following the implementation, verification of the existence of usual δ18O to climatic relationships are performed for the Rayleigh distillation, the Dansgaard relationship and the δ18O -salinity relationship. Advantages and caveats of the approach taken are outlined. The isotopic fields simulated are shown to reproduce most expected oxygen-18-climate relationships with the notable exception of the isotopic composition in Antarctica. © Author(s) 2013.