The INDC counter, aggregation of national contributrions and 2°C trajectories

Rapport du groupe interdisciplinaire sur les contributions nationalesConsidering that limiting global warming to below 2°C implies a CO2 budget not to be exceeded and near-zero emissions by 21OO (IPCC), we can assess global 2030 greenhouse gas emissions implied by INDCs in comparison to long-term trajectories. Ahead of the COP21, we estimate that submitted INDCs would bring global greenhouse gas emissions in the range of 55 to 64 GtC02eq in 2030.Under this assumption,global emissions in 2030 are thus higher than the level of 51GtC0 2eq for the year 2012. However, this is not in contradiction with a peaking of global emissions that can only be expected after 2020, given in particular the projected dynamics of emissions in China and other developing countries.The published INDCs represent a significant step towards trajectories compatible with the 2°C goal,but remain insufficient to join trajectories presenting a reasonable probability of success.ln order to increase the chance of meeting the 2°C objective, the ambition of the short-term contributions needs to be strengthened in future negotiations.ln order to sustain a high pace in emissions reductions after 2030,structural measures are also needed, which, in order to have a rapi impact, should be prepared as early as possible. Continued efforts are needed to accelerate the development of low carbon solutions on the one hand,and demonstrate the feasibility of negative emissions on the other hand

Etude de la structure de l'atmosphere a des fins meteorologiques a partir du sondage satellitaire : application a des cas specifiques et au calcul des flux radiatifs infrarouge

SIGLECNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Comment on Rayleigh-scattering calculations for the terrestrial atmosphere

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A comparison of cloud droplet radii measured from space

International audienceCloud droplet effective radius (CDR) can be estimated from the spectral signature of cloud reflectance. The technique has been applied to measurements of the Advanced Very High Resolution Radiometer instrument and more recently to the Moderate Resolution Imaging Spectroradiometer (MODIS). Another technique relies on the directional signature of the polarized reflectance and has been applied to observations from Polarization and Directionality of the Earth's Reflectances (POLDER) onboard Advanced Earth Observation Satellite (ADEOS). Although the latter technique requires very specific conditions, we argue that, when applicable, it is very accurate. A large fraction of successful POLDER estimates are derived from measurements over stratocumulus cloud fields. During portions of 2003, POLDER and MODIS acquired near coincident observations. The data can then be used for an evaluation of the two CDR products. The two datasets are highly correlated over the oceans albeit with a MODIS high bias of about 2 μm. The correlation breaks down when POLDER retrieves small droplets (less than 7 μm), which occurs over most land surfaces as well as polluted oceanic areas. We discuss the possible causes for biases and errors. Although differences in the two CDR estimates are expected because of the differences in the spatial scale and vertical weighting function, we did not find a fully satisfactory explanation for the bias and lack of correlation over land surfaces. It seems, however, that the spatial variability as seen by MODIS is larger than that deduced from POLDER measurements, in particular over land surfaces

Global distribution of cloud droplet effective radius from POLDER polarization measurements

International audiencePolarization measurements from the spaceborne POLDER instrument are used to estimate the droplet effective radius of liquid-phase clouds. Eight months of measurements have been processed. Seasonal averages have been generated and are discussed here. The measurements confirm that, on average, droplets are 2 to 3 gm smaller over land than over the oceans. The smaller droplets are found over highly polluted regions and in areas affected by smoke from biomass burning activity. The influence of land masses is apparent downwind of the continents. Largest droplets are found in remote tropical oceans, away from major aerosol sources. A large zonal gradient is also apparent in the southern oceans, with very small droplets close to the Antarctic continent

Variability of biome reflectance directional signatures as seen by POLDER

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Wind power potential and intermittency issues in the context of climate change

International audienceWind power is developing rapidly because of its potential to provide renewable electricity and the largereduction in installation costs during the past decade. However, the high temporal variability of the wind powersource is an obstacle to a high penetration in the electricity mix as it makes difficult to balance electricity supplyand demand. There is therefore a need to quantify the variability of wind power and also to analyze how thisvariability decreases through spatial aggregation. In the context of climate change, it is also necessary to analyzehow the wind power potential and its variability may change in the future. One difficulty for such objective is thelarge biases in the modeled winds, and the difficulty to derive a reliable power curve. In this paper, we proposean Empirical Parametric Power Curve Function (EPPCF) model to calibrate a power curve function for a realisticestimate of wind power from weather and climate model data at the regional or national scale. We use this modelto analyze the wind power potential, with France as an example, considering the future wind turbine evolution,both onshore and offshore, with a focus on the production intermittency and the impact of spatial decorrelations. We also analyze the impact of climate change.We show that the biases in the modeled wind vary from region to region, and must be corrected for a validevaluation of the wind power potential. For onshore wind, we quantify the potential increase of the load factorlinked to the wind turbine evolution (from a current 23% to 30% under optimistic hypothesis). For offshore, ourestimate of the load factor is smaller for the French coast than is currently observed for installed wind farms thatare further north (around 35% versus 39%). However, the estimates vary significantly with the atmosphericmodel used, with a large spatial gradient with the distance from the coast. The improvement potential appearssmaller than over land. The temporal variability of wind power is large, with variations of 100% of the averagewithin 3–10 h at the regional scale and 14 h at the national scale. A better spatial distribution of the wind farmscould further reduce the temporal variability by around 20% at the national scale, although it would remain highwith respect to that of the demand. The impact of climate change on the wind power resource is insignificant(from +2.7% to − 8.4% for national annual mean load factor) and even its direction varies among models

Spaceborne estimate of atmospheric CO2_2 column by use of the differential absorption method: error analysis

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Spaceborne remote sensing of greenhouse gas concentrations

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Comment

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