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Gif-sur-Yvette, France

Lauerwald R.,Free University of Colombia | Lauerwald R.,Institute Pierre Simon Laplace | Lauerwald R.,University of Hamburg | Laruelle G.G.,Free University of Colombia | And 4 more authors.
Global Biogeochemical Cycles | Year: 2015

CO2 evasion from rivers (FCO2) is an important component of the global carbon budget. Here we present the first global maps of CO2 partial pressures (pCO2) in rivers of stream orders 3 and higher and the resulting FCO2 at 0.5° resolution constructed with a statistical model. A geographic information system based approach is used to derive a pCO2 prediction function trained on data from 1182 sampling locations. While data from Asia and Africa are scarce and the training data set is dominated by sampling locations from the Americas, Europe, and Australia, the sampling locations cover the full spectrum from high to low latitudes. The predictors of pCO2 are net primary production, population density, and slope gradient within the river catchment as well as mean air temperature at the sampling location (r2 = 0.47). The predicted pCO2 map was then combined with spatially explicit estimates of stream surface area Ariver and gas exchange velocity k calculated from published empirical equations and data sets to derive the FCO2 map. Using Monte Carlo simulations, we assessed the uncertainties of our estimates. At the global scale, we estimate an average river pCO2 of 2400 (2019-2826) μatm and a FCO2 of 650 (483-846) Tg C yr-1 (5th and 95th percentiles of confidence interval). Our global CO2 evasion is substantially lower than the recent estimate of 1800 Tg C yr-1 although the training set of pCO2 is very similar in both studies, mainly due to lower tropical pCO2 estimates in the present study. Our maps reveal strong latitudinal gradients in pCO2, Ariver, and FCO2. The zone between 10°N and 10°S contributes about half of the global CO2 evasion. Collection of pCO2 data in this zone, in particular, for African and Southeast Asian rivers is a high priority to reduce uncertainty on FCO2. ©2015. American Geophysical Union. All Rights Reserved. Source


Berg A.,LOCEAN IPSL | De Noblet-Ducoudre N.,LSCE IPSL | Sultan B.,LOCEAN IPSL | Lengaigne M.,LOCEAN IPSL | Guimberteau M.,LOCEAN IPSL
Agricultural and Forest Meteorology | Year: 2013

Climate change impacts on agriculture could arguably be most critical for developing countries in tropical regions: their populations rely importantly on agriculture and climate-dependant resources, poverty limits their capacity to anticipate and adapt to climate change, and population increase already poses a serious challenge to food security in those regions. Current projections of climate change impacts on tropical crop yields, even though on average negative, remain largely uncertain: there is need for more consistent, large-scale, quantitative assessments.In this study we use a newly developed agro-DGVM (Dynamical Global Vegetation Model including an explicit representation of croplands) driven by projections from several climate models and two SRES scenarios to evaluate climate change impacts on potential C4 crop productivity over Africa and India from 1960 to 2100. We specifically separate the effect of increasing atmospheric CO2 levels. We perform transient simulations directly forced by climate model outputs: to preserve consistency in the analysis despite regional biases in climate models, we analyze yield change on a bioclimatic basis (using the Köppen classification) rather than on a geographical basis. We find that the potential productivity of one of the most important staple crops in those regions, millet, will overall decrease, on average over all models and scenarios, by -6% (individual model projections ranging from -29% to +11%). The bioclimatic analysis allows us to highlight the main climate drivers of these changes. The main impact is a moderate but robust temperature-driven yield decrease over Equatorial and Temperate Köppen zones; larger but much more inconsistent yield changes occur in Arid Köppen zones, reflecting the uncertainty in precipitation projections from climate models. The uncertainty in aggregated impacts reflects the uncertainty over these areas, underlining the need to narrow the uncertainty in precipitation projections over dry areas if more reliable agricultural impact assessments over tropical regions are to be provided. Our results are also consistent with the limited magnitude of the impact of increased atmospheric CO2 levels on C4 crop yields described in the literature. While such climatic impacts further increase the challenge of achieving future food security in developing countries in the Tropics, most of these impacts can arguably be mitigated through adaptation measures and improved agricultural practices. © 2011 Elsevier B.V. Source


Lehodey P.,MEMMS Marine Ecosystems Modelling and Monitoring by Satellites | Senina I.,MEMMS Marine Ecosystems Modelling and Monitoring by Satellites | Sibert J.,University of Hawaii at Manoa | Bopp L.,LSCE IPSL | And 3 more authors.
Progress in Oceanography | Year: 2010

An improved version of the spatial ecosystem and population dynamics model SEAPODYM was used to investigate the potential impacts of global warming on tuna populations. The model included an enhanced definition of habitat indices, movements, and accessibility of tuna predators to different vertically migrant and non-migrant micronekton functional groups. The simulations covered the Pacific basin (model domain) at a 2°×2° geographic resolution. The structure of the model allows an evaluation from multiple data sources, and parameterization can be optimized by adjoint techniques and maximum likelihood using fishing data. A first such optimized parameterization was obtained for bigeye tuna (Thunnus obesus) in the Pacific Ocean using historical catch data for the last 50years and a hindcast from a coupled physical-biogeochemical model driven by the NCEP atmospheric reanalysis. The parameterization provided very plausible biological parameter values and a good fit to fishing data from the different fisheries, both within and outside the time period used for optimization. We then employed this model to forecast the future of bigeye tuna populations in the Pacific Ocean. The simulation was driven by the physical-biogeochemical fields predicted from a global marine biogeochemistry - climate simulation. This global simulation was performed with the IPSL climate model version 4 (IPSL-CM4) coupled to the oceanic biogeochemical model PISCES and forced by atmospheric CO2, from historical records over 1860-2000, and under the SRES A2 IPCC scenario for the 21st century (i.e. atmospheric CO2 concentration reaching 850ppm in the year 2100). Potential future changes in distribution and abundance under the IPCC scenario are presented but without taking into account any fishing effort. The simulation showed an improvement in bigeye tuna spawning habitat both in subtropical latitudes and in the eastern tropical Pacific (ETP) where the surface temperature becomes optimal for bigeye tuna spawning. The adult feeding habitat also improved in the ETP due to the increase of dissolved oxygen concentration in the sub-surface allowing adults to access deeper forage. Conversely, in the Western Central Pacific the temperature becomes too warm for bigeye tuna spawning. The decrease in spawning is compensated by an increase of larvae biomass in subtropical regions. However, natural mortality of older stages increased due to lower habitat values (too warm surface temperatures, decreasing oxygen concentration in the sub-surface and less food). This increased mortality and the displacement of surviving fish to the eastern region led to stable then declining adult biomass at the end of the century. © 2010 Elsevier Ltd. Source


Swingedouw D.,LSCE IPSL | Mignot J.,LOCEAN IPSL | Labetoulle S.,LOCEAN IPSL | Guilyardi E.,LOCEAN IPSL | And 2 more authors.
Climate Dynamics | Year: 2013

The mechanisms involved in Atlantic meridional overturning circulation (AMOC) decadal variability and predictability over the last 50 years are analysed in the IPSL-CM5A-LR model using historical and initialised simulations. The initialisation procedure only uses nudging towards sea surface temperature anomalies with a physically based restoring coefficient. When compared to two independent AMOC reconstructions, both the historical and nudged ensemble simulations exhibit skill at reproducing AMOC variations from 1977 onwards, and in particular two maxima occurring respectively around 1978 and 1997. We argue that one source of skill is related to the large Mount Agung volcanic eruption starting in 1963, which reset an internal 20-year variability cycle in the North Atlantic in the model. This cycle involves the East Greenland Current intensity, and advection of active tracers along the subpolar gyre, which leads to an AMOC maximum around 15 years after the Mount Agung eruption. The 1997 maximum occurs approximately 20 years after the former one. The nudged simulations better reproduce this second maximum than the historical simulations. This is due to the initialisation of a cooling of the convection sites in the 1980s under the effect of a persistent North Atlantic oscillation (NAO) positive phase, a feature not captured in the historical simulations. Hence we argue that the 20-year cycle excited by the 1963 Mount Agung eruption together with the NAO forcing both contributed to the 1990s AMOC maximum. These results support the existence of a 20-year cycle in the North Atlantic in the observations. Hindcasts following the CMIP5 protocol are launched from a nudged simulation every 5 years for the 1960-2005 period. They exhibit significant correlation skill score as compared to an independent reconstruction of the AMOC from 4-year lead-time average. This encouraging result is accompanied by increased correlation skills in reproducing the observed 2-m air temperature in the bordering regions of the North Atlantic as compared to non-initialized simulations. To a lesser extent, predicted precipitation tends to correlate with the nudged simulation in the tropical Atlantic. We argue that this skill is due to the initialisation and predictability of the AMOC in the present prediction system. The mechanisms evidenced here support the idea of volcanic eruptions as a pacemaker for internal variability of the AMOC. Together with the existence of a 20-year cycle in the North Atlantic they propose a novel and complementary explanation for the AMOC variations over the last 50 years. © 2012 Springer-Verlag. Source


Le Hegarat-Mascle S.,University Paris - Sud | Ottle C.,LSCE IPSL
International Journal of Remote Sensing | Year: 2013

Surface features such as furrows are here detected using high spatial resolution images such as those provided by IKONOS (pixel size 1 m × 1 m in panchromatic mode) and WorldView-1 instruments (pixel size 0.5 m × 0.5 m), through a new detection methodology based on image analysis. This methodology includes four different steps. First, segmentation of the whole image is performed in order to label each agricultural field individually. Then, for each field, mathematical morphological processes are applied (erosion followed by functional geodesic reconstruction) in order to enhance the image contrast. Then, an automatic thresholding process is applied to construct a binary image of the furrows or other features in the field. In order to reduce the noise due to the overlap between the classes of furrow and background, the a priori information that furrows are straight lines exhibiting regular patterns is introduced. The Hough transform is applied to detect straight lines (represented in polar coordinates) and furrow directions as accumulations on the angle axis in the Hough space. The proposed method was applied on a WorldView-1 image acquired over the Lokna catchment within the Plava watershed in Russia (around 180 km2) and validated against ground truth observations. © 2013 Copyright Taylor and Francis Group, LLC. Source

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