This work represents an analysis of the spatial and temporal variability of nitrate deposition and preservation recorded in multiple ice core and snow pit records from the Greenland ice sheet. The primary objective of this research was to develop improved estimates of variability in the preserved ice core record of nitrate to aid in the interpretation of paleoatmospheric concentrations of reactive nitrogen compounds. Three separate works are presented, each focusing on a unique component of variability. The first is a study related to the direct preservation of nitrate over a single year. The second and third topics are related to analysis of ice core records collected during NASA's Program for Arctic Regional Climate Assessment (PARCA) which was initiated in 1993 and continued through 2002.The first study of preservation demonstrated that nitrate, despite possible post-depositional cycling and alteration, was well preserved throughout the year, such that the total flux measured in a snow pit taken to represent the previous year, was representative of snow surface concentrations during the past year. The small difference in preserved concentrations from observed surface snow concentrations gives evidence of only 7% post-depositional loss at this site (mean annual accumulation ~23 g cm-2 yr-1). Results from these studies indicate that at this site accumulation is the most significant process affecting preservation of nitrate in the firn.In the second study, the temporal variability of preserved nitrate was evaluated through time series analysis and correlation studies with available paleoclimate proxy records. Six Greenland ice cores covering the period 1794-1995 show correlated co-variability of nitrate concentration for periods greater than ten years and a ~60% increase in average concentration during the last 75 years. The changes in concentration yield ~30% higher nitrate flux (2.5 to 3.2 g m-2 a-1) and ~11% greater variability during 1895-1994 period versus the prior 100 years. Nitrate trends in the cores during the last 100 years are also correlated with global nitrate emissions, with an average r-value of 0.93 for the six cores.The last study focused on spatial variability of nitrate, and the relation of deposition to components of the earth system including temperature and accumulation. The objective of the study was to assess the contribution of spatial (latitude, longitude, and elevation) and climate (accumulation and temperature) components to the preserved record. Furthermore, the study evaluated the influence of anthropogenic activities on the spatial distribution of nitrate of the Greenland ice sheet. Large scale spatial variability exists as a result of accumulation gradients, with concentration 5% greater in the northern plateau, yet flux over the northern plateau is 30% lower than the dry snow zone as a whole. While spatially, flux appears to be more dependent on accumulation, preservation of flux shows increasing dependence on concentration with increasing accumulation. The relationship between concentration and accumulation is non-linear, showing less dependence in the low accumulation regions versus high accumulation regions. Accumulation alone is insufficient to account for the observed variability in nitrate flux in the low accumulation regions, and evidence supports an additional component to a transfer function model for nitrate that includes photochemistry, temperature, and possibly sublimation. In high accumulation regions, evidence points to a dilution effect, with concentration decreases resulting from increased accumulation. Flux estimates over the ice sheet are compared with a GEOS-CHEM model estimate of reactive nitrogen vertical fluxes showing the model captures a significant component of the variability in the southern portion of the ice sheet, but under-represents the flux and variability in the northern half of the ice sheet by a factor of 4.

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The remarkable salinity difference between the upper Pacific and Atlantic Oceans is often explained through net export of water vapour across Central America. To investigate this mechanism a study of salinity signals in the Equatorial Pacific Ocean current system was made looking at responses to fresh water input from two sources (local versus remote - Atlantic Ocean) as well as a combination of the two. Statistical analyses (Empirical Orthogonal Functions, Single Value Decomposition and Wavelet analysis) were used to split the main sources of the atmospheric freshwater input into local and remote contributions and to quantify both contributions. The remote source was assumed to have been transported over Central America from the Atlantic Ocean as an atmospheric freshwater flux, whereas the local source originated in the Pacific Ocean itself. The analysis suggests that 74% of the total variance in precipitation over the tropical eastern Pacific is due to water vapour transport from the Atlantic. It also demonstrates strong influence of ENSO events, with maximum correlation at a two months time lag. During La Ni�a periods the precipitation variance is more closely related to water vapour transport across Central America (the remote source), while during El Ni�o periods it is more closely related to the water vapour transport by Southerly winds along the west coast of South America (the local source). The current and temperature fields provided by the Modular Ocean Model (version 2) were used to study the changes in the salinity field when freshwater was added to or removed from the model. ECMWF ERA-40 data taken from the ECMWF data server was used to determine the atmospheric flux of freshwater at the ocean surface, in the form of evaporation minus precipitation (E-P). The Mixed Layer Depth (MLD) computed from temperature and salinity fields determines to what depth the salinity's dilution/concentration takes place for every grid point. Each MLD was calculated from the results of the previous time step, and the water column was considered well mixed from the surface to this depth. The statistical relationships were used to reconstruct the precipitation over the tropical eastern Pacific. A numerical ocean model, which uses currents and temperature from a global ocean model and is forced by precipitation, was used to study the ocean's response to either the remote or the local source acting in isolation. Through time lag correlation analysis of the sea surface salinity anomalies produced by the variation in the reconstructed precipitation fields, it is found that the anomaly signals of salinity propagate westward along the Equator at a rate of approximately 0.25 m.s-1 (6.1 degrees per month).

Une meilleure connaissance du cycle biogéochimique du méthane est un élémentfondamental dans la compréhension du changement climatique actuel. La modélisationinverse est une des méthodes permettant d’estimer les sources et puits de méthaneen combinant l’information venant d’observations atmosphériques, d’une connaissancea priori des flux de méthane, et d’un modèle de chimie-transport. Cependant, leserreurs liées à la modélisation du transport atmosphérique sont apparues comme unelimitation de plus en plus dominante de cette méthode suite à l’augmentation dunombre et de la diversité des observations.Après avoir montré que l’impact des erreurs de transport sur les inversions des flux deméthane pouvait être important, j’ai cherché à améliorer les capacités de la versionoffline de LMDz, modèle de transport utilisé pour simuler le transport atmosphériquedans le système inverse du LSCE. Pour cela, j’ai intégré des développements récents(paramétrisation de la convection profonde, de la diffusion verticale et du mélangenon-local dans la couche limite) et raffiné la résolution horizontale et verticale.En exploitant les différentes versions disponibles de LMDz, neuf inversions atmosphériquesont été réalisées, estimant les sources et puits de méthane entre 2006 et 2012.Deux périodes de fortes émissions ont été mises en évidence : en 2007 et en 2010,qui ont principalement été attribuées à des anomalies dans les régions tropicales et enChine, où des événements climatiques majeurs ont été observés (Amérique du Sud etAsie du Sud-Est) et où le développement économique se poursuit à un rythme soutenu(Chine), même si les émissions de certains inventaires sont surestimées. / A better knowledge of the methane biogeochemical cycle is fundamental for a betterunderstanding of climate change. Inverse modelling is one powerful tool to derivemethane sources and sinks by optimally combining information from atmospheric observations of methane mixing ratios, from process-based models and inventories ofmethane emissions and sinks, and from a chemistry-transport model used to link emissionsto atmospheric mixing ratios. However, uncertainties related to the modelling ofatmospheric transport are becoming a serious limitation for inverse modelling due tothe increasing number and type of observations.After showing that the impact of transport errors on current atmospheric inversionscould be significant, I tried to improve the representation of atmospheric transport inthe inverse system used at LSCE. Thus, I have tested new physical parameterizations(deep convection, vertical diffusion and non-local transport within the boundary layer)in the LMDz model and adapted it to finer horizontal and vertical resolutions. Thesedevelopments were integrated into the inverse system.Nine inversions have been performed using the different versions of LMDz in order toestimate methane emissions over the period 2006-2012. Two years of strong methaneemissions have been highlighted in 2007 and in 2010. These anomalies have beenmainly attributed to anomalies in the Tropics and in China, where major climate eventshave been observed (Tropical South America and South East Asia) and where economicdevelopment is carrying on with a fast pace (China), even if emissions magnitude andtrend reported in inventories are found to be overestimated.

Les émissions anthropiques et naturelles de méthane en Sibérie contribuent de manièrenotable, mais mal quantifiée au budget mondial de méthane (3–11% des émissions mondiales).Au Sud de la région, les émissions anthropiques sont liées aux grands centres urbains.Au Nord, l’extraction de gaz et de pétrole en Sibérie occidentale induit d’importantessources anthropiques ponctuelles. Ces régions sont aussi couvertes de vastes zones humidesnaturelles émettant du méthane durant l’été (typiquement de mai à septembre). Nous utilisonsdes inversions atmosphériques régionales à la méso-échelle pour mieux comprendreles contributions de chaque processus dans le budget sibérien. Les inversions souffrent desincertitudes dans les observations, dans la simulation du transport et dans l’amplitude et ladistribution des émissions. Pour prendre en compte ces incertitudes, je développe une nouvelleméthode d’inversion basée sur une marginalisation des statistiques d’erreurs. Je testecette méthode et documente sa robustesse sur un cas test. Je l’applique ensuite à la Sibérie.À l’aide de mesures de concentrations atmosphériques de méthane collectées par des sitesd’observation de surface en Sibérie, j’estime le budget régional de méthane sibérien à 5–28 TgCH4.a−1 (1–5% des émissions mondiales), soit une réduction de 50% des incertitudespar rapport aux précédentes études dans la région. Grâce à cette méthode, je suis de plus enmesure de détecter des structures d’émissions par zones de quelques milliers de km2 et leurvariabilité à une résolution de 2–4 semaines. / Anthopogenic and natural methane emissions in Siberia significantly contribute to theglobal methane budget, but the magnitude of these emissions is uncertain (3–11% of globalemissions). To the South, anthropogenic emissions are related to big urban centres. To theNorth, oil and gas extraction in West Siberia is responsible for conspicuous point sources.These regions are also covered by large natural wetlands emitting methane during the snowfreeseason, roughly from May to September. Regional atmospheric inversions at a meso-scaleprovide a mean for improving our knowledge on all emission process. But inversions sufferfrom the uncertainties in the assimilated observations, in the atmospheric transport modeland in the emission magnitude and distribution. I developp a new inversion method based onerror statistic marginalization in order to account for these uncertainties. I test this methodon case study and explore its robustness. I then apply it to Siberia. Using measurements ofmethane atmospheric concentrations gathered at Siberian surface observation sites, I founda regional methane budget in Siberia of 5–28 TgCH4.a−1 (1–5% of global emissions). Thisimplies a reduction of 50% in the uncertainties on the regional budget. With the new method,I also can detect emission patterns at a resolution of a few thousands km2 and emissionvariability at a resolution of 2–4 weeks.

Per- and polyfluoroalkyl substances (PFAS) are a group of highly fluorinated compounds which comprises of more than 4700 substances. A smaller number of those substances is rou-tinely measured, usually the short (C4-C7) and long chain PFAS (>C7). Detection of PFAS in different water matrices including wet precipitation have been done previously in a limited number of studies, including ultra-short chain compounds (C1-C3). Ultra-short chain com-pounds have however not been investigated to a larger extent. In this study, twelve rainwater samples from Råö have been analysed, each representing a composite sample of one month. Long (C8-C18), short as well as ultra-short chain PFAS have been included in the analysis. Long and short chain compounds were analysed with ultra-performance liquid chromatography tan-dem mass spectrometer (UPLC-MS/MS) and ultra-short chain compounds with ultra-perfor-mance convergence chromatography tandem spectrometer (UPCC-MS/MS). Long and short-chain PFAS had a total detectable concentration of 5.1-110 ng/L. A seasonal trend was also studied, which showed a significant difference when performing a Kruskal Wallis test in meas-ured total mean long and short chain PFAS concentration. Dunnet´s test indicated a significant difference between all the seasons. Highest concentrations were measured during summer and lowest during winter. Ultra-short chain compounds analysed by UPCC MS/MS had a total concentration between 16-410 ng/L. No significant difference in total ultra-short PFAS mean concentration could be seen between different seasons using a Kruskal Wallis test. The total PFAS concentration in the rain samples ranged from 28 to 540 ng/L, where ultra-short chain PFAS contributed to 58-92 % of the total concentration. Which makes them an important group to include in future measurements of PFAS in water samples and especially in rainwater sam-ples.

The isotopic composition of water in the atmosphere is influenced by how the water evaporated, how it was transported, and how it formed in the cloud before falling. Because these processes are temperature dependent, the isotopic ratios stored in glacial ice and other proxy sources have been used as an indicator of pre-instrumental climate. There is uncertainty, however, as to whether isotopic ratios should be interpreted as a proxy of local temperature, or as a broader indicator of changes in how the vapor was transported. To better understand these processes, the NASA GISS general circulation model (GCM) was used to examine two different types of controls on the isotopic composition of moisture. The first control was the large-scale circulation of the atmosphere. Over Europe, it was found that δ18O is strongly controlled by a Northern Annular Mode-like pattern, detected in both the GCM and for Europe’s high-quality precipitation δ18O data. Over the southwest Yukon, it was found that higher δ18O was associated with moisture transport from the south, which led to a re-interpretation of the large mid-19th century δ18O shift seen in the ice cores from Mt. Logan. The second type of control was microphysical, relating to the way precipitation interacts with vapor after it has formed. Using a GCM sensitivity experiment, the effects of ‘post-condensation exchange’ were found to depend primarily on the proportion between the amount of upstream precipitation that fell as rain and the amount that fell as snow, and at low latitudes, on the strength of atmospheric moisture recycling. This led to a partitioning of the well-observed correlation between temperature and precipitation δ18O into its initial and post-condensation components, and a GCM-based interpretation of satellite measurements of the isotopic composition of water vapor in the troposphere.

The isotopic composition of water in the atmosphere is influenced by how the water evaporated, how it was transported, and how it formed in the cloud before falling. Because these processes are temperature dependent, the isotopic ratios stored in glacial ice and other proxy sources have been used as an indicator of pre-instrumental climate. There is uncertainty, however, as to whether isotopic ratios should be interpreted as a proxy of local temperature, or as a broader indicator of changes in how the vapor was transported. To better understand these processes, the NASA GISS general circulation model (GCM) was used to examine two different types of controls on the isotopic composition of moisture. The first control was the large-scale circulation of the atmosphere. Over Europe, it was found that δ18O is strongly controlled by a Northern Annular Mode-like pattern, detected in both the GCM and for Europe’s high-quality precipitation δ18O data. Over the southwest Yukon, it was found that higher δ18O was associated with moisture transport from the south, which led to a re-interpretation of the large mid-19th century δ18O shift seen in the ice cores from Mt. Logan. The second type of control was microphysical, relating to the way precipitation interacts with vapor after it has formed. Using a GCM sensitivity experiment, the effects of ‘post-condensation exchange’ were found to depend primarily on the proportion between the amount of upstream precipitation that fell as rain and the amount that fell as snow, and at low latitudes, on the strength of atmospheric moisture recycling. This led to a partitioning of the well-observed correlation between temperature and precipitation δ18O into its initial and post-condensation components, and a GCM-based interpretation of satellite measurements of the isotopic composition of water vapor in the troposphere.

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