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Forests mitigate climate change by storing carbon and reducing emissions via substitution effects of wood products. Additionally, they provide many other important ecosystem services (ESs), but are vulnerable to climate change; therefore, adaptation is necessary. Climate‐smart forestry combines mitigation with adaptation, whilst facilitating the provision of many ESs. This is particularly challenging due to large uncertainties about future climate. Here, we combined ecosystem modeling with robust multi‐criteria optimization to assess how the provision of various ESs (climate change mitigation, timber provision, local cooling, water availability, and biodiversity habitat) can be guaranteed under a broad range of climate futures across Europe. Our optimized portfolios contain 29% unmanaged forests, and implicate a successive conversion of 34% of coniferous to broad‐leaved forests (11% vice versa). Coppices practically vanish from Southern Europe, mainly due to their high water requirement. We find the high shares of unmanaged forests necessary to keep European forests a carbon sink while broad‐leaved and unmanaged forests contribute to local cooling through biogeophysical effects. Unmanaged forests also pose the largest benefit for biodiversity habitat. However, the increased shares of unmanaged and broad‐leaved forests lead to reductions in harvests. This raises the question of how to meet increasing wood demands without transferring ecological impacts elsewhere or enhancing the dependence on more carbon‐intensive industries. Furthermore, the mitigation potential of forests depends on assumptions about the decarbonization of other industries and is consequently crucially dependent on the emission scenario. Our findings highlight that trade‐offs must be assessed when developing concrete strategies for climate‐smart forestry., Plain Language Summary: Forests help mitigate climate change by storing carbon and via avoided emissions when wood products replace more carbon‐intensive materials. At the same time, forests provide many other “ecosystem services (ESs)” to society. For example, they provide timber, habitat for various species, and they cool their surrounding regions. They are, however, also vulnerable to ongoing climate change. Forest management must consider all these aspects, which is particularly challenging considering the uncertainty about future climate. Here, we propose how this may be tackled by computing optimized forest management portfolios for Europe for a broad range of future climate pathways. Our results show that changes to forest composition are necessary. In particular, increased shares of unmanaged and broad‐leaved forests are beneficial for numerous ESs. However, these increased shares also lead to decreases in harvest rates, posing a conflict between wood supply and demand. We further show that the mitigation potential of forests strongly depends on how carbon‐intensive the replaced materials are. Consequently, should these materials become “greener” due to new technologies, the importance of wood products in terms of climate change mitigation decreases. Our study highlights that we cannot optimize every aspect, but that trade‐offs between ESs need to be made., Key Points: Strategies for climate‐smart forestry under a range of climate scenarios always lead to trade‐offs between different ecosystem services (ESs). Higher shares of unmanaged and broad‐leaved forests are beneficial for numerous ESs, but lead to decreased timber provision. The mitigation potential of forests strongly relies on substitution effects which depend on the carbon‐intensity of the alternative products., European Forest Institute (EFI) Networking Fund http://dx.doi.org/10.13039/501100013942, Bayerisches Staatsministerium für Wissenschaft und Kunst, Bayerisches Netzwerk für Klimaforschung (BayKliF) http://dx.doi.org/10.13039/501100004563, Swedish Research Council Formas, German Federal Office for Agriculture and Food (BLE), https://doi.org/10.5281/zenodo.6667489, https://doi.org/10.5281/zenodo.6612953

The Tien Shan and Pamir mountains host over 28,000 glaciers providing essential water resources for increasing water demand in Central Asia. A disequilibrium between glaciers and climate affects meltwater release to Central Asian rivers, challenging the region's water availability. Previous research has neglected temporal variability. We present glacier mass balance estimates based on transient snowline and geodetic surveys with unprecedented spatiotemporal resolution from 1999/00 to 2017/18. Our results reveal spatiotemporal heterogeneity characterized by two mass balance clusters: (a) positive, low variability, and (b) negative, high variability. This translates into variable glacial meltwater release (≈1–16%) of annual river runoff for two watersheds. Our study reveals more complex climate forcing‐runoff responses and importance of glacial meltwater variability for the region than suggested previously., Key Points Annual glacier mass balance for Central Asia (1999/00–2017/18) is derived by combining transient snowlines, geodetic surveys, and modelingStrong spatiotemporal heterogeneity with contrasting patterns of mass gain and loss are foundHot spots of heterogeneous mass balance variability are associated with highly variable glacier melt water runoff

Improved understanding of how our coasts will evolve over a range of time scales (years‐decades) is critical for effective and sustainable management of coastal infrastructure. A robust knowledge of the spatial, directional and temporal variability of the inshore wave climate is required to predict future coastal evolution and hence vulnerability. However, the variability of the inshore directional wave climate has received little attention, and an improved understanding could drive development of skillful seasonal or decadal forecasts of coastal response. We examine inshore wave climate at 63 locations throughout the United Kingdom and Ireland (1980–2017) and show that 73% are directionally bimodal. We find that winter‐averaged expressions of six leading atmospheric indices are strongly correlated (r = 0.60–0.87) with both total and directional winter wave power (peak spectral wave direction) at all studied sites. Regional inshore wave climate classification through hierarchical cluster analysis and stepwise multi‐linear regression of directional wave correlations with atmospheric indices defined four spatially coherent regions. We show that combinations of indices have significant skill in predicting directional wave climates (R 2 = 0.45–0.8; p, Key Points Over 70% of inshore wave climates analyzed throughout the United Kingdom and Ireland were directionally bimodalCombinations of winter atmospheric indices NAO, WEPA, SCAND, and EA are significantly correlated with directional wave climate in all regionsRegression models using multiple winter atmospheric indices enable skillful reconstructions of directional wave climate in all regions

Sea surface temperature (SST) is an essential climate variable, that is directly used in climate monitoring. Although satellite measurements can offer continuous global coverage, obtaining a long‐term homogeneous satellite‐derived SST data set suitable for climate studies based on a single instrument is still a challenge. In this work, we assess a homogeneous SST data set derived from reprocessed Infrared Atmospheric Sounding Interferometer (IASI) level‐1 (L1C) radiance data. The SST is computed using Planck's Law and simple atmospheric corrections. We assess the data set using the ERA5 reanalysis and the EUMETSAT‐released IASI level‐2 SST product. Over the entire period, the reprocessed IASI SST shows a mean global difference with ERA5 close to zero, a mean absolute bias under 0.5°C, with a SD of difference around 0.3°C and a correlation coefficient over 0.99. In addition, the reprocessed data set shows a stable bias and SD, which is an advantage for climate studies. The interannual variability and trends were compared with other SST data sets: ERA5, Hadley Centre's SST (HadISST), and NOAA's Optimal Interpolation SST Analysis (OISSTv2). We found that the reprocessed SST data set is able to capture the patterns of interannual variability well, showing the same areas of high interannual variability (>1.5°C), including over the tropical Pacific in January corresponding to the El Niño Southern Oscillation. Although the period studied is relatively short, we demonstrate that the IASI data set reproduces the same trend patterns found in the other data sets (i.e., cooling trend in the North Atlantic, warming trend over the Mediterranean)., Key Points First IASI algorithm focused on sea surface temperature (SST) suitable for climate studiesThe IASI‐derived SST data set is compared with other available data setsClimate variability and trends are shown and compared to other data sets

TanSat is the 1st Chinese carbon dioxide (CO2) measurement satellite, launched in 2016. In this study, the University of Leicester Full Physics (UoL‐FP) algorithm is implemented for TanSat nadir mode XCO2 retrievals. We develop a spectrum correction method to reduce the retrieval errors by the online fitting of an 8th order Fourier series. The spectrum‐correction model and its a priori parameters are developed by analyzing the solar calibration measurement. This correction provides a significant improvement to the O2 A band retrieval. Accordingly, we extend the previous TanSat single CO2 weak band retrieval to a combined O2 A and CO2 weak band retrieval. A Genetic Algorithm (GA) has been applied to determine the threshold values of post‐screening filters. In total, 18.3% of the retrieved data is identified as high quality compared to the original measurements. The same quality control parameters have been used in a footprint independent multiple linear regression bias correction due to the strong correlation with the XCO2 retrieval error. Twenty sites of the Total Column Carbon Observing Network (TCCON) have been selected to validate our new approach for the TanSat XCO2 retrieval. We show that our new approach produces a significant improvement on the XCO2 retrieval accuracy and precision when compared to TCCON with an average bias and RMSE of −0.08 ppm and 1.47 ppm, respectively. The methods used in this study can help to improve the XCO2 retrieval from TanSat and subsequently the Level‐2 data production, and hence will be applied in the TanSat operational XCO2 processing., Key Points First using O2 A and 1.61 um CO2 band approaching TanSat XCO2 retreivalDevelopment a method on radiometric correction of TanSat L1B data in O2 A and 1.61 um CO2 Validation of new TanSat retrieval against TCCON and recived significant improved results compare to previously retrieval

In climate models, the subgrid‐scale orography (SSO) parameterization imposes a blocked flow drag at low levels that is opposed to the local flow. In IPSL‐CM6A‐LR, an SSO lift force is also applied perpendicular to the local flow to account for the effect of locally blocked air in narrow valleys. Using IPSL‐CM6A‐LR sensitivity experiments, it is found that the tuning of both effects strongly impacts the atmospheric circulation. Increasing the blocking and reducing the lift lead to an equatorward shift of the Northern Hemisphere subtropical jet and a reduction of the midlatitude eddy‐driven jet speed. It also improves the simulated synoptic variability, with a reduced storm‐track intensity and increased blocking frequency over Greenland and Scandinavia. Additionally, it cools the polar lower troposphere in boreal winter. Transformed Eulerian Mean diagnostics also show that the low‐level eddy‐driven subsidence over the polar region is reduced consistent with the simulated cooling. The changes are amplified in coupled experiments when compared to atmosphere‐only experiments, as the low‐troposphere polar cooling is further amplified by the temperature and albedo feedbacks resulting from the Arctic sea ice growth. In IPSL‐CM6A‐LR, this corrects the warm winter bias and the lack of sea ice that were present over the Arctic before adjusting the SSO parameters. Our results, therefore, suggest that the adjustment of SSO parameterization alleviates the Arctic sea ice bias in this case. However, the atmospheric changes induced by the parametrized SSO also impact the ocean, with an equatorward shift of the Northern Hemisphere oceanic gyres and a weaker Atlantic meridional overturning circulation., Key Points The adjustment of the parametrized orography in climate models can alleviate the near‐surface winter biases over the ArcticIncreasing low‐level drag reduces Northern Hemisphere stationary wave amplitudes and shifts the subtropical jet equatorwardIncreasing low‐level drag increases the Arctic sea ice coverage and reduces the Atlantic meridional overturning circulation

A coordinated set of large ensemble atmosphere‐only simulations is used to investigate the impacts of observed Arctic sea ice‐driven variability (SIDV) on the atmospheric circulation during 1979–2014. The experimental protocol permits separating Arctic SIDV from internal variability and variability driven by other forcings including sea surface temperature and greenhouse gases. The geographic pattern of SIDV is consistent across seven participating models, but its magnitude strongly depends on ensemble size. Based on 130 members, winter SIDV is ~0.18 hPa2 for Arctic‐averaged sea level pressure (~1.5% of the total variance), and ~0.35 K2 for surface air temperature (~21%) at interannual and longer timescales. The results suggest that more than 100 (40) members are needed to separate Arctic SIDV from other components for dynamical (thermodynamical) variables, and insufficient ensemble size always leads to overestimation of SIDV. Nevertheless, SIDV is 0.75–1.5 times as large as the variability driven by other forcings over northern Eurasia and Arctic., Key Points Arctic sea ice variations drive ~1.5% of boreal winter Arctic SLP variance during 1979–2014 in coordinated 130‐member AGCM experimentsAn accurate quantification of the impacts of Arctic sea ice‐driven SLP variability requires an ensemble size greater than 100 membersInsufficient ensemble size always leads to an overestimation of the Arctic sea ice‐driven variance within and outside Arctic

Moderate volcanic eruptions are a recurrent source of sulfur dioxide (SO2) in the lower stratosphere. The oxidation of SO2 to sulfuric acid aerosol particles enhance the stratospheric aerosol optical depth with likely impact on the climate. Modelling properly the volcanic aerosol content and its evolution in this region is important for radiative impact issues. In this work, we explore the variability of the tropical Upper Troposphere Lower Stratosphere(UTLS) aerosol content between 2013 and 2019, a period which was particularly impacted by volcanic eruptions. For that purpose, space-borne observations from OMPS (datasets from GES DISC and from University of Saskatchewan) and OSIRIS, together with simulations by the Whole Atmosphere Community Climate Model (WACCM) coupled with the Community Aerosol and Radiation Model for Atmospheres (CARMA), are used. Different model sensitive experiments, particularly for the injection altitude and timing, have been conducted to evaluate how the model captures the aerosol plume in terms of content, optical and microphysical properties, transport and residence time. As an example, the results show that the decay of the Calbuco plume observed by OMPS is well reproduced by the model. This study also benefits from unique datasets in the tropical southern hemisphere from the NDACC Maïdo observatory (Reunion Island, France, 20.5°S, 55.5°E) and providing valuable ground-based observations and balloon sounding opportunities. Together with satellite data, we use ground-based aerosol lidar and in situ optical particle counter observations to assess the model performance. A particular focus is made on recent eruptions. The plume of the Ambae volcano (15°S, 167°E) which erupted in July 2018 is shown to propagate to the northern hemisphere with some influence until summer 2019 in the Asian monsoon region. For the year 2019, we investigate how the Ulawun (5°S, 151°E; ~0.14 Tg of SO2) tropical eruption and the Raikoke mid-latitude eruption (48°N, 153°E; ~1.5Tg of SO2), have influenced the aerosol burden in the tropics.

Soil organic carbon (SOC) is a crucial component of the terrestrial carbon cycle and its turnover time in models is a key source of uncertainty. Studies have highlighted the utility of δ13C measurements for benchmarking SOC turnover in global models. We used 13C as a tracer within a vertically discretized soil module of a land‐surface model, Organising Carbon and Hydrology In Dynamic Ecosystems‐ Soil Organic Matter (ORCHIDEE‐SOM). Our new module represents some of the processes that have been hypothesized to lead to a 13C enrichment with soil depth as follows: 1) the Suess effect and CO2 fertilization, 2) the relative 13C enrichment of roots compared to leaves, and 3) 13C discrimination associated with microbial activity. We tested if the upgraded soil module was able to reproduce the vertical profile of δ13C within the soil column at two temperate sites and the short‐term change in the isotopic signal of soil after a shift in C3/C4 vegetation. We ran the model over Europe to test its performance at larger scale. The model was able to simulate a shift in the isotopic signal due to short‐term changes in vegetation cover from C3 to C4; however, it was not able to reproduce the overall vertical profile in soil δ13C, which arises as a combination of short and long‐term processes. At the European scale, the model ably reproduced soil CO2 fluxes and total SOC stock. These findings stress the importance of the long‐term history of land cover for simulating vertical profiles of δ13C. This new soil module is an emerging tool for the diagnosis and improvement of global SOC models., Key Points Soil 13C was incorporated as a tracer in the land surface model ORCHIDEE‐SOMThe model was able to reproduce short‐term changes such as those observed after a shift in C3/C4 vegetationLong‐term changes in δ13C were more difficult to represent, highlighting the importance of some missing mechanisms

Temporal variations of surface masses, such as the hydrosphere and atmosphere of the Earth, load the surfaces of planetary bodies causing temporal variations in deformation. Surface shear forces and gravitational fields also drive ongoing planetary deformation. Characterizing the spatiotemporal patterns of planetary deformation can constrain allowable models for the interior structure of a planetary body as well as for the distribution of surface and body forces. Pertinent applications include hydrology, glaciology, geodynamics, atmospheric science, and climatology. To address the diversity of emerging applications, we introduce a software suite called LoadDef that provides a collection of modular functions for modeling planetary deformation within a self‐consistent, Python‐based computational framework. Key features of LoadDef include computation of real‐valued potential, load, and shear Love numbers for self‐gravitating and spherically symmetric planetary models; computation of Love‐number partial derivatives with respect to planetary density and elastic structure; computation of displacement, gravity, tilt, and strain load Green's functions; and computation of three‐component surface displacements induced by surface mass loading. At a most basic level, only a planetary‐structure model and a mass‐load model must be supplied as input to LoadDef to utilize all the main features of the software. The end‐to‐end forward‐modeling capabilities for mass‐loading applications lay the foundation for sensitivity studies and geodetic tomography. LoadDef results have been validated with Global Navigation Satellite System observations and verified against independent software and published results. As a case study, we use LoadDef to predict the solid Earth's elastic response to ocean tidal loading across the western United States., Key Points We introduce a software to model elastic planetary deformation driven by gravitational fields, surface mass loading, and shear forcing LoadDef computes real‐valued potential, load, and shear Love numbers, as well as Love‐number partial derivatives for sensitivity studies LoadDef performs end‐to‐end forward modeling of planetary surface displacements generated by surface mass loading

Terrestrial gamma-ray flashes (TGFs), first detected in 1994 by the Burst and Transient Source Experiment (BATSE) instrument aboard the Compton Gamma-Ray Observatory [ Fishman et al., Science, 264, 1313, 1994], are high-energy photon bursts produced in close association with lightning activity in the Earth's atmosphere. Recent analyses of TGF light curves measured by the Gamma-Ray Burst Monitor (GBM) on the Fermi satellite have revealed that 67% of TGF pulses detected are asymmetric with fall time significantly longer than rise time [ Foley et al., JGR, 119, 5931, 2014]. Moreover, using a low-frequency interferometric lightning mapping array, Lyu et al. [GRL, 43, 5516, 2016] have found that most of the initial leader steps and channels were tilted away from the vertical direction, suggesting that such tilted geometry could mislead the interpretation of position-dependent TGF observation from space. The importance of tilted source geometry has been repeatedly emphasized in previous studies, for example, by Hazelton et al. [GRL, 36, L01108, 2009] while investigating the dependence of TGF energy spectra on offset distances, by Fitzpatrick et al. [Phys. Rev. D, 90, 043008, 2014] while studying the temporal and spectral evolution of TGFs, and by Mailyan et al. [JGR, 121, 11346, 2016] while performing spectral analysis on individual TGF events measured by Fermi GBM. Despite the increased emphasis, the tilted TGF geometry has not been investigated in detail in previous studies. In this work, using first-principles Monte Carlo simulations and characteristic TGF sources, we first quantify the increased Compton scattering effects on the temporal and spectral properties of TGFs induced by the tilted source geometry. Modeling results indicate that the source orientation is a critical parameter in TGF analysis and offset distance between the lightning source and satellite location cannot be used as a single parameter characterizing Compton scattering effects. Moreover, we show how the Compton scattering effects can explain the symmetric and asymmetric pulses measured by Fermi GBM and thereby estimate a characteristic timescale for TGF-producing processes.

International audience; Sprites are complex discharges that consist of many plasma filaments named streamers. They are produced high above thunderstorms (40-90 km), usually in association with positive cloud-to-ground lightning. It is known that sprites produce electromagnetic radiation observed typically in the extremely low (ELF) to ultra low (ULF) frequency bands [e.g., Cummer et al., GRL, 25, 1281, 1998]. More recently, sprites have been found to be associated with LF emissions in the range ~50 to 350 kHz [Fullekrug et al., JGR, 115, A00E09, 2010], which emissions have later been proposed to be related to streamer expansion processes [Qin, et al., GRL, 39, L22803, 2012]. In a different context, Ihaddadene and Celestin [JGR, 122, 1000, 2017] have shown that collisions between streamers with opposite polarities would lead to strong electric field variation on the order of a few picoseconds in air at ground-level. It is worth mentioning that collisions between sprite streamers are common. Moreover, use of similarity laws shows that those few picoseconds would turn into a timescale on the order of a fraction of microsecond at 50 km, which hence leads to the interesting possibility of HF-VHF emissions from sprites. These characteristic emissions might in turn carry a signature of given processes in sprite discharges. The future space mission TARANIS funded by CNES will measure electromagnetic emissions associated with Transient Luminous Events, such as sprites, from DC to 30 MHz. Quantifying possible emission processes and identifying corresponding signatures is therefore of prime importance for the preparation of TARANIS. Furthermore, the French radio telescope NenuFAR [Zarka et al., ICATT, 13-18, 2015] is sensitive in the frequency range 10-85 MHz and will attempt observation of sprites as part of one of its Key Programs. Using a streamer fluid model to simulate the collision of streamers in sprites and a simple antenna model, we present an effort on modeling relevant sprite streamer processes generating characteristic electromagnetic radiation in the HF-VHF range and investigate on its possible detection by TARANIS and ground-based instruments.

Terrestrial gamma ray flashes (TGFs) are sub-millisecond bursts of energetic photons produced by the bremsstrahlung from electrons accelerated in the electric fields in thunderstorms. In sufficiently high fields, high-energy electrons can "run away" and create what is known as relativistic runaway electron avalanches (RREAs). TGFs have been routinely observed from space, and occasionally from ground, since their discovery. Some observations have been found to be concurrent with radio emissions detected on ground. Different radio signals have been linked to TGFs, most notably EIPs [e.g., Lyu et al, GRL, 42, 6836-6843, 2015] and slow LF pulses [e.g., Cummer et al., GRL, 38, L14810, 2011]. Moreover, radio signals associated with TGFs may lead to very useful information about TGF production processes [Dwyer and Cummer, JGR, 118, 3769-3790, 2013]. In the present work we study the generation of electromagnetic radiation from TGF sources to constrain the context of TGF-producing electron beams. We use a Monte Carlo model that considers every individual collision of electrons with air molecules [Celestin and Pasko, JGR, 116, A03315, 2011]. This allows us to explicitly quantify the density of low-energy secondary electrons and ions produced during RREAs for various field configurations. We simulate the radio wave propagation using an FDTD model [Marshall et al., JGR, 117, A03316,2012], and compare the results with recent measurements [e.g., Pu et al., GRL, 46, 6990-6997, 2019]. The timescale of the field collapse in the acceleration region and the amplitude of the current moment are of special interest to constrain the geometry of TGF-producing RREAs.

For the first time an evaluation of the whistler rate around the Earth is performed using results from the neural network aboard the microsatellite DEMETER. It is shown that the rate of whistlers with low dispersion calculated all around the Earth as a function of longitude vary between 1 and 6 s-1 during nighttime (22.30 LT) and between 0.5 and 0.7 s-1 during daytime (10.30 LT). The whistler rate is anticorrelated with the F10.7-cm solar flux. A decrease by 25% of the solar flux corresponds to an increase of 62% (26%) of the averaged whistler rate calculated for the entire Earth during nighttime (daytime). Using this averaged whistler rate, the global lightning rate is estimated to be of the order of 123 s-1 (27 s-1) during nighttime (daytime). The main conclusion concerns the precipitation of the electrons in the radiation belt by interaction with the whistlers. It is shown that the decrease of the lightning activity at solar minimum (shown with the help of the Schumann resonances) is largely counterbalanced by the increase of the whistler rates in the upper part of the ionosphere due to the decrease of the ionospheric absorption.

Terrestrial gamma-ray flashes (TGFs) are bursts of high-energy photons originating from the Earth's atmosphere in association with thunderstorm activity [e.g., Briggs et al., JGR, 118, 3805, 2013]. TGFs are believed to be typically produced at altitudes ranging from 10 to 14 km [e.g., Cummer et al., GRL, 41, 8586, 2014]. Relativistic runaway electron avalanches (RREAs) are understood to be the root cause of TGFs but the exact context and configuration of electric fields driving RREAs is currently under debate [e.g., Dwyer et al., Space Sci. Rev., 173, 133, 2012]. In this work, we study the effects of the geomagnetic field combined with the driving electric field on the runaway electron beam geometry. Electron beams naturally follow the direction of the electric field, but the geomagnetic field should cause them to bend. Since the geomagnetic field close to the Earth's surface is known precisely, quantifying the statistical deviation of TGFs in satellite observations gives information on the electric field at the source. We present an analytical method to calculate the relativistic electron beam deviation in arbitrary homogeneous electric and magnetic fields. Moreover, we show that a statistically significant West-East asymmetry consistent with the deviation of RREAs by the geomagnetic field is present in the Fermi-GBM TGF catalog [Roberts et al., JGR, 123, 4381, 2018]. We present the amplitude of the RREA-driving electric field determined using this method on Fermi-GBM data accounting both for tilts of the electric field vector at the TGF source and effects of the atmosphere on photon transport.

International audience; A number of studies have shown how in isolation the atmospheric circulation would balance changes in the top-of-atmosphere energy budget or ocean energy transport, leading to climate impacts such as shifts of the ITCZ or mid-latitude jets. The atmosphere and ocean circulation, and so their respective meridional energy transports, are however tightly coupled through the surface wind forcing of the ocean. We use here the simplest setup for including the effects of the ocean circulation : an aqua-planet with the atmosphere coupled to a 2-layer slab ocean in which the Ekman currents and eddy diffusion can be parameterized. We first show how the interactive ocean strongly damps in the Tropics the atmospheric response to a prescribed inter-hemispheric heat transport. We then apply the same method for a doubling of CO2 : the response of the total meridional energy transport remains weak in the Tropics, but with strong compensation between the atmosphere and ocean components. As a result, the classic circulation response - weaker and broader Hadley cell, poleward jet shift, precipitation changes - is significantly modified.

Organic aerosols (OAs), originating from a wide variety of sources and atmospheric processes, have strong impacts on air quality and climate change. The present PhD thesis aimed to get a better understanding of OA origins using specific organic molecular markers together with their input into source-receptor model such as positive matrix factorization (PMF). This experimental work was based on two field campaigns, conducted in Grenoble (urban site) over the 2013 year and in the Paris region (suburban site of SIRTA, 25 km southwest of Paris) during an intense PM pollution event in March 2015. Following an extended chemical characterization (from 139 to 216 species quantified), the use of key primary and secondary organic molecular markers within the standard filter-based PMF model allowed to deconvolve 9 and 11 PM10 sources (Grenoble and SIRTA, respectively). These included common ones (biomass burning, traffic, dust, sea salt, secondary inorganics and nitrate), as well as uncommon resolved sources such as primary biogenic OA (fungal spores and plant debris), biogenic secondary AO (SOA) (marine, isoprene oxidation) and anthropogenic SOA (polycyclic aromatic hydrocarbons (PAHs) and/or phenolic compounds oxidation). In addition, high time-resolution filter dataset (4h-timebase) available for the Paris region also illustrated a better understanding of the diurnal profiles and the involved chemical processes. These results could be compared to outputs from other measurement techniques (online ACSM (aerosol chemical speciation monitor), offline AMS (aerosol mass spectrometer) analyses), and/or to other data treatment methodologies (EC (elemental carbon) tracer method and SOA tracer method). A good agreement was obtained between all the methods in terms of separation between primary and secondary OA fractions. Nevertheless, and whatever the method used, still about half of the SOA mass was not fully described. Therefore, a novel OA source apportionment approach has finally been developed by combining online (ACSM) and offline (organic molecular markers) measurements and using a time synchronization script. This combined PMF analysis was performed on the unified matrix. It revealed 10 OA factors, including 4 different biomass burning-related chemical profiles. Compared to conventional approaches, this new methodology provided a more comprehensive description of the atmospheric processes related to the different OA sources.; Les aérosols organiques (AO), issus de nombreuses sources et de différents processus atmosphériques, ont un impact significatif sur la qualité de l’air et le changement climatique. L’objectif de ce travail de thèse était d’acquérir une meilleure connaissance de l’origine des AO par l’utilisation de marqueurs organiques moléculaires au sein de modèles source-récepteur de type positive matrix factorization (PMF). Ce travail expérimental était basé sur deux campagnes de prélèvements réalisées à Grenoble (site urbain) au cours de l’année 2013 et dans la région parisienne (site péri-urbain du SIRTA, 25 km au sud-ouest de Paris) lors d’un intense épisode de pollution aux particules (PM) en Mars 2015. Une caractérisation chimique étendue (de 139 à 216 espèces quantifiées) a été réalisée et l’utilisation de marqueurs moléculaires primaires et secondaires clés dans la PMF a permis de déconvoluer de 9 à 11 sources différentes de PM10 (Grenoble et SIRTA, de façon respective) incluant aussi bien des sources classiques (combustion de biomasse, trafic, poussières, sels de mer, nitrate et espèces inorganiques secondaires) que des sources non communément résolues telles que AO biogéniques primaires (spores fongiques et débris de plantes), AO secondaires (AOS) biogéniques (marin, oxydation de l’isoprène) et AOS anthropiques (oxydation des hydrocarbures aromatiques polycycliques (HAP) et/ou des composés phénoliques). En outre, le jeu de données obtenu pour la région parisienne à partir de prélèvements sur des pas de temps courts (4h) a permis d’obtenir une meilleure compréhension des profils diurnes et des processus chimiques impliquées. Ces résultats ont été comparés à ceux issus d’autres techniques de mesures (en temps réel, ACSM (aerosol chemical speciation monitor) et analyse AMS (aerosol mass spectrometer) en différée) et/ou d’autres méthodes de traitement de données (méthodes traceur EC (elemental carbon) et traceur AOS). Un bon accord a été obtenu entre toutes les méthodes en termes de séparation des fractions primaires et secondaires. Cependant, et quelle que soit l’approche utilisée, la moitié de la masse d’AOS n’était toujours pas complètement décrite. Ainsi, une nouvelle approche d’étude des sources de l’AO a été développée en combinant les mesures en temps réel (ACSM) et celles sur filtres (marqueurs moléculaires organiques) et en utilisant un script de synchronisation des données. L’analyse PMF combinée a été réalisée sur la matrice de données unifiée. 10 facteurs AO, incluant 4 profils chimiques différents en lien avec la combustion de biomasse, ont été mis en évidence. Par rapport aux approches conventionnelles, cette nouvelle méthodologie a permis d’obtenir une meilleure compréhension des processus atmosphériques liés aux différentes sources d’AO.

In the framework of the preparation of TARANIS space mission dedicated to the study of transient luminous events (TLEs), a detailed ion-neutral chemistry model has been developed to simulate the impact of blue jet streamers on stratospheric chemistry. It is based on the MIPLASMO model (Microphysical and Photochemical Lagrangian Model of Ozone) widely used over the last 20 years to interpret balloon and satellite measurements associated with stratospheric ozone. It considers the time evolution of 118 species including neutral and ions species, through a set of 1760 reactions. In addition, the neutral chemistry associated with ozone takes classical nitrogen, chlorine and bromine species into account. After model validation, we focus on the streamer representation in the model. We consider two streamer parametrizations, (i) an electric field pulse with constant value as a function of time during the event, (ii) a time-varying realistic electric field, which is the result of an electrodynamic streamer model. Simulations are performed from 20 km to 50 km altitude. Results obtained are analyzed in two different ways: (i) during the first 100 s to identify the major fast mechanism associated with excited species, (ii) during 2 days to evaluate the impact on neutral chemistry (ozone and NOx species). The modelling results indicate that the time evolution of both excited and neutral species volume mixing ratio are very sensitive to the considered streamer parametrization (pulse or realistic streamer) and the differences for two-day simulations are significant. We particularly focus on ozone loss in the mid-, high-stratosphere and ozone production in the low stratosphere as a function of altitude. We find that the impact of streamer parametrization on ozone depends on the altitude.

Organic aerosols (OAs), originating from a wide variety of sources and atmospheric processes, have strong impacts on air quality and climate change. The present PhD thesis aimed to get a better understanding of OA origins using specific organic molecular markers together with their input into source-receptor model such as positive matrix factorization (PMF). This experimental work was based on two field campaigns, conducted in Grenoble (urban site) over the 2013 year and in the Paris region (suburban site of SIRTA, 25 km southwest of Paris) during an intense PM pollution event in March 2015. Following an extended chemical characterization (from 139 to 216 species quantified), the use of key primary and secondary organic molecular markers within the standard filter-based PMF model allowed to deconvolve 9 and 11 PM10 sources (Grenoble and SIRTA, respectively). These included common ones (biomass burning, traffic, dust, sea salt, secondary inorganics and nitrate), as well as uncommon resolved sources such as primary biogenic OA (fungal spores and plant debris), biogenic secondary AO (SOA) (marine, isoprene oxidation) and anthropogenic SOA (polycyclic aromatic hydrocarbons (PAHs) and/or phenolic compounds oxidation). In addition, high time-resolution filter dataset (4h-timebase) available for the Paris region also illustrated a better understanding of the diurnal profiles and the involved chemical processes. These results could be compared to outputs from other measurement techniques (online ACSM (aerosol chemical speciation monitor), offline AMS (aerosol mass spectrometer) analyses), and/or to other data treatment methodologies (EC (elemental carbon) tracer method and SOA tracer method). A good agreement was obtained between all the methods in terms of separation between primary and secondary OA fractions. Nevertheless, and whatever the method used, still about half of the SOA mass was not fully described. Therefore, a novel OA source apportionment approach has finally been developed by combining online (ACSM) and offline (organic molecular markers) measurements and using a time synchronization script. This combined PMF analysis was performed on the unified matrix. It revealed 10 OA factors, including 4 different biomass burning-related chemical profiles. Compared to conventional approaches, this new methodology provided a more comprehensive description of the atmospheric processes related to the different OA sources., Les aérosols organiques (AO), issus de nombreuses sources et de différents processus atmosphériques, ont un impact significatif sur la qualité de l’air et le changement climatique. L’objectif de ce travail de thèse était d’acquérir une meilleure connaissance de l’origine des AO par l’utilisation de marqueurs organiques moléculaires au sein de modèles source-récepteur de type positive matrix factorization (PMF). Ce travail expérimental était basé sur deux campagnes de prélèvements réalisées à Grenoble (site urbain) au cours de l’année 2013 et dans la région parisienne (site péri-urbain du SIRTA, 25 km au sud-ouest de Paris) lors d’un intense épisode de pollution aux particules (PM) en Mars 2015. Une caractérisation chimique étendue (de 139 à 216 espèces quantifiées) a été réalisée et l’utilisation de marqueurs moléculaires primaires et secondaires clés dans la PMF a permis de déconvoluer de 9 à 11 sources différentes de PM10 (Grenoble et SIRTA, de façon respective) incluant aussi bien des sources classiques (combustion de biomasse, trafic, poussières, sels de mer, nitrate et espèces inorganiques secondaires) que des sources non communément résolues telles que AO biogéniques primaires (spores fongiques et débris de plantes), AO secondaires (AOS) biogéniques (marin, oxydation de l’isoprène) et AOS anthropiques (oxydation des hydrocarbures aromatiques polycycliques (HAP) et/ou des composés phénoliques). En outre, le jeu de données obtenu pour la région parisienne à partir de prélèvements sur des pas de temps courts (4h) a permis d’obtenir une meilleure compréhension des profils diurnes et des processus chimiques impliquées. Ces résultats ont été comparés à ceux issus d’autres techniques de mesures (en temps réel, ACSM (aerosol chemical speciation monitor) et analyse AMS (aerosol mass spectrometer) en différée) et/ou d’autres méthodes de traitement de données (méthodes traceur EC (elemental carbon) et traceur AOS). Un bon accord a été obtenu entre toutes les méthodes en termes de séparation des fractions primaires et secondaires. Cependant, et quelle que soit l’approche utilisée, la moitié de la masse d’AOS n’était toujours pas complètement décrite. Ainsi, une nouvelle approche d’étude des sources de l’AO a été développée en combinant les mesures en temps réel (ACSM) et celles sur filtres (marqueurs moléculaires organiques) et en utilisant un script de synchronisation des données. L’analyse PMF combinée a été réalisée sur la matrice de données unifiée. 10 facteurs AO, incluant 4 profils chimiques différents en lien avec la combustion de biomasse, ont été mis en évidence. Par rapport aux approches conventionnelles, cette nouvelle méthodologie a permis d’obtenir une meilleure compréhension des processus atmosphériques liés aux différentes sources d’AO.

Transient Luminous Events (TLEs) are large-scale optical events occurring in the upper-atmosphere from the top of thunderclouds up to the ionosphere. TLEs may have important effects in local, regional, and global scales, and many features of TLEs are not fully understood yet [e.g, Pasko, JGR, 115, A00E35, 2010]. Moreover, meteor events have been suggested to play a role in sprite initiation by producing ionospheric irregularities [e.g, Qin et al., Nat. Commun., 5, 3740, 2014]. The French Fireball Recovery and InterPlanetary Observation Network (FRIPON, https://www.fripon.org/?lang=en), is a national all-sky 30 fps camera network designed to continuously detect meteor events. We seek to make use of this network to observe TLEs over unprecedented space and time scales ( 1000×1000 km with continuous acquisition). To do so, we had to significantly modify FRIPON's triggering software Freeture (https://github.com/fripon/freeture) while leaving the meteor detection capability uncompromised. FRIPON has a great potential in the study of TLEs. Not only could it produce new results about spatial and time distributions of TLEs over a very large area, it could also be used to validate and complement observations from future space missions such as ASIM (ESA) and TARANIS (CNES). In this work, we present an original image processing algorithm that can detect sprites using all-sky cameras while strongly limiting the frequency of false positives and our ongoing work on sprite triangulation using the FRIPON network.

Climate model simulations uniformly show drier and warmer summers in the Eurasian midcontinent during the mid‐Holocene, which is not consistent with paleoenvironmental observations. The simulated climate results from a reduction in the zonal temperature gradient, which weakens westerly flow and reduces moisture flux and precipitation in the midcontinent. As a result, sensible heating is favored over evaporation and latent heating, resulting in substantial surface‐driven atmospheric warming. Thus, the discrepancy with the paleoenvironmental evidence arises initially from a problem in the simulated circulation and is exacerbated by feedback from the land surface. This region is also drier and warmer than indicated by observations in the preindustrial control simulations, and this bias arises in the same way: zonal flow and hence moisture flux into the midcontinent are too weak, and feedback from the land surface results in surface‐driven warming. These analyses suggest the need to improve those aspects of climate models that affect the strength of westerly circulation., Key Points CMIP5/PMIP3 mid‐Holocene simulations in the Eurasian midcontinent are too dry and too warm relative to paleoclimatic observationsThis mismatch is attributed to simulation of weak westerlies and moisture fluxes, amplified by surface‐energy‐balance and surface‐water‐balance feedbackThe mismatch is similar to bias in climate model simulations for the present day

Lightning stepped leaders and laboratory spark discharges in air are known to produce X-rays [e.g., Dwyer et al., Geophys. Res. lett., 32, L20809, 2005; Kochkin et al., J. Phys. D: Appl. Phys., 45, 425202, 2012]. However, the processes behind the production of these X-rays are still not very well understood. During discharges, encounters between streamers of different polarities are very common. For example, during the formation of a new leader step, the negative streamer zone around the tip of a negative leader and the positive streamers initiated from the posiive part of a bidirectional space leader strongly interact. In laboratory experiments, when streamers are approaching a sharp electrode, streamers with the opposite polarity are initiated from the electrode and collide with the former streamers. Recently, the encounter between negative and positive streamers has been proposed as a plausible mechanism for the production of X-rays by spark discharges [Cooray et la., JASTP, 71, 1890, 2009; Kochkin et al., J. Phys. D: Appl. Phys., 45, 425202, 2012], but modeling results have shown later that the increase of the electric field involved in this process, which is above the conventional breakdown threshold field, is accompanied by a strong increase of the electron density. The resulting increase in the conductivity, in turn, causes this electric field to collapse over a few tens of picoseconds, preventing the electrons reaching high energies and producing significant X-ray emissions [e.g., Ihaddadene and Celestin, Geophys. Res. Lett., 45, 5644, 2015]. In this work, we will present simulation results of a new electron acceleration mechanism for producing runaway electron energies above hundred keV. The mechanism couples multiple single streamers and streamer head-on collisions, similar to a laboratory discharge, and is suitable for explaining the high-energy X-rays produced by discharges in air and by lightning stepped leaders.

International audience; To investigate the climate change in the next 30 years over a complex terrain in southwestern Germany, simulations performed with the regional climate model COSMO-CLM at convection-permitting resolution are compared to simulations at 7 km resolution with parameterised convection. An earlier study has shown the main benefits of convection-permitting resolution in the hourly statistics and the diurnal cycle of precipitation intensities. Here, we investigate whether the improved simulation of precipitation in the convection-permitting model is affecting future climate projections in summer. Overall, the future scenario (ECHAM5 with A1B forcing) brings weak changes in mean precipitation, but stronger hourly intensities in the morning and less frequent but more intense daily precipitation. The two model simulations produce similar changes in climate, despite differences in their physical characteristics linked to the formation of convective precipitation. A significant increase in the morning precipitation probably due to large-scale forced convection is found when considering only the most extreme events (above 50 mm/day). In this case, even the diurnal cycles of precipitation and convection-related indices are similar between resolutions, leading to the conclusion that the 7 km model sufficiently resolves the most extreme convective events. In this region and time periods, the 7 km resolution is deemed sufficient for most assessments of near future precipitation change. However, conclusions could be dependent on the characteristics of the region of investigation.

International audience; A major uncertainty in current climate model simulations concerns the evolution of the stratospheric Brewer-Dobson circulation. Models show decreasing mean age, indicating an accelerating circulation, while observations show opposite decadal age variations in the Northern hemisphere. Here, we quantify the effect of the stratospheric volcanic aerosol on mean age variability, using mean age from reanalysis-driven TRACZILLA and CLaMS simulations for the 1989-2010 period, showing decadal variations consistent with observations. Our method is based on a multilinear regression technique using satellite observations of aerosol optical depth including Pinatubo and smaller volcanoes after 2002. We find that the decadal age variations can be primarily attributed to the volcanic signals. In particular the smaller volcanic eruptions after 2002, which are not included in most climate model simulations, cause most of the positive mean age decadal change in the Northern hemisphere after 2002. Consequently, the discrepancy between climate models and observations regarding decadal mean age changes (2002-2010) is likely related to the representation of volcanic stratospheric aerosol in the models.