Academic literature on the topic 'Atmospheric cycle'

Abstract The seasonal cycle of the heating of the atmosphere is divided into a component due to direct solar absorption in the atmosphere and a component due to the flux of energy from the surface to the atmosphere via latent, sensible, and radiative heat fluxes. Both observations and coupled climate models are analyzed. The vast majority of the seasonal heating of the northern extratropics (78% in the observations and 67% in the model average) is due to atmospheric shortwave absorption. In the southern extratropics, the seasonal heating of the atmosphere is entirely due to atmospheric shortwave absorption in both the observations and the models, and the surface heat flux opposes the seasonal heating of the atmosphere. The seasonal cycle of atmospheric temperature is surface amplified in the northern extratropics and nearly barotropic in the Southern Hemisphere; in both cases, the vertical profile of temperature reflects the source of the seasonal heating. In the northern extratropics, the seasonal cycle of atmospheric heating over land differs markedly from that over the ocean. Over the land, the surface energy fluxes complement the driving absorbed shortwave flux; over the ocean, they oppose the absorbed shortwave flux. This gives rise to large seasonal differences in the temperature of the atmosphere over land and ocean. Downgradient temperature advection by the mean westerly winds damps the seasonal cycle of heating of the atmosphere over the land and amplifies it over the ocean. The seasonal cycle in the zonal energy transport is 4.1 PW. Finally, the authors examine the change in the seasonal cycle of atmospheric heating in 11 models from phase 3 of the Coupled Model Intercomparison Project (CMIP3) due to a doubling of atmospheric carbon dioxide from preindustrial concentrations. The seasonal heating of the troposphere is everywhere enhanced by increased shortwave absorption by water vapor; it is reduced where sea ice has been replaced by ocean, which increases the effective heat storage reservoir of the climate system and thereby reduces the seasonal magnitude of energy fluxes between the surface and the atmosphere. As a result, the seasonal amplitude of temperature increases in the upper troposphere (where atmospheric shortwave absorption increases) and decreases at the surface (where the ice melts).

Abstract. Air pollution is substantially modulated by meteorological conditions, and especially their diurnal variations may play a key role in air quality evolution. However, the behaviors of temperature diurnal cycles along with the associated atmospheric condition and their effects on air quality in China remain poorly understood. Here, for the first time, we examine the diurnal cycles of day-to-day temperature change and reveal their impacts on winter air quality forecasting in mountain-basin areas. Three different diurnal cycles of the preceding day-to-day temperature change are identified and exhibit notably distinct effects on the day-to-day changes in atmospheric-dispersion conditions and air quality. The diurnal cycle with increasing temperature obviously enhances the atmospheric stability in the lower troposphere and suppresses the development of the planetary boundary layer, thus deteriorating the air quality on the following day. By contrast, the diurnal cycle with decreasing temperature in the morning is accompanied by a worse dispersion condition with more stable atmosphere stratification and weaker surface wind speed, thereby substantially worsening the air quality. Conversely, the diurnal cycle with decreasing temperature in the afternoon seems to improve air quality on the following day by enhancing the atmospheric-dispersion conditions on the following day. The findings reported here are critical to improve the understanding of air pollution in mountain-basin areas and exhibit promising potential for air quality forecasting.

Abstract. The seasonal changes in the globally averaged atmospheric carbon-dioxide concentrations reflect an important aspect of the global carbon cycle: the gas exchange between the atmosphere and terrestrial biosphere. The data on the globally averaged atmospheric carbon-dioxide concentrations, which are reported by Earth System Research Laboratory of the US National Oceanic & Atmospheric Administration (NOAA/ESRL), could be used to demonstrate the adequacy of the global carbon-cycle models. However, it was recently found that the observed amplitude of seasonal variations in the atmospheric carbon-dioxide concentrations is higher than simulated. In this paper, the factors that affect the amplitude of seasonal variations are explored using a carbon-cycle model of reduced complexity. The model runs show that the low amplitude of the simulated seasonal variations may result from underestimated effect of substrate limitation on the seasonal pattern of heterotrophic respiration and from an underestimated magnitude of the annual gross primary production (GPP) in the terrestrial ecosystems located to the north of 25° N.

Abstract. The methane (CH4) cycle is a key component of the Earth system that links planetary climate, biological metabolism, and the global biogeochemical cycles of carbon, oxygen, sulfur, and hydrogen. However, currently lacking is a numerical model capable of simulating a diversity of environments in the ocean, where CH4 can be produced and destroyed, and with the flexibility to be able to explore not only relatively recent perturbations to Earth's CH4 cycle but also to probe CH4 cycling and associated climate impacts under the very low-O2 conditions characteristic of most of Earth's history and likely widespread on other Earth-like planets. Here, we present a refinement and expansion of the ocean–atmosphere CH4 cycle in the intermediate-complexity Earth system model cGENIE, including parameterized atmospheric O2–O3–CH4 photochemistry and schemes for microbial methanogenesis, aerobic methanotrophy, and anaerobic oxidation of methane (AOM). We describe the model framework, compare model parameterizations against modern observations, and illustrate the flexibility of the model through a series of example simulations. Though we make no attempt to rigorously tune default model parameters, we find that simulated atmospheric CH4 levels and marine dissolved CH4 distributions are generally in good agreement with empirical constraints for the modern and recent Earth. Finally, we illustrate the model's utility in understanding the time-dependent behavior of the CH4 cycle resulting from transient carbon injection into the atmosphere, and we present model ensembles that examine the effects of atmospheric pO2, oceanic dissolved SO42-, and the thermodynamics of microbial metabolism on steady-state atmospheric CH4 abundance. Future model developments will address the sources and sinks of CH4 associated with the terrestrial biosphere and marine CH4 gas hydrates, both of which will be essential for comprehensive treatment of Earth's CH4 cycle during geologically recent time periods.

Abstract The nonlinearities that cause El Niño events to deviate more from the mean state than La Niña events are still not completely understood. This paper investigates the contribution of one candidate mechanism: ENSO nonlinearities originating from the atmosphere. The initially linear intermediate complexity model of the equatorial Pacific Ocean, in which all couplings were fitted to observations, describes the ENSO cycle reasonably well. In this linear model, extra terms are systematically introduced in the atmospheric component: the nonlinear response of mean wind stress to SST anomalies, the skewness of the driving noise term in the atmosphere, and the relation of this noise term to the background SST or the ENSO phase. The nonlinear response of mean wind stress to SST in the ENSO region is found to be the dominant term influencing the ENSO cycle. However, this influence is only visible when noise fields are used that are fitted to observed patterns of prescribed standard deviation and spatial decorrelation. Standard deviation and skewness of noise do have a dependence on the ENSO phase, but this has a relatively small influence on the ENSO cycle in this model. With these additional nonlinearities in the representation of the atmosphere, a step forward has been made toward building a realistic reduced complexity model for ENSO.

Abstract. The trajectories of soil carbon in our changing climate are of the utmost importance as soil is a substantial carbon reservoir with a large potential to impact the atmospheric carbon dioxide (CO2) burden. Atmospheric CO2 observations integrate all processes affecting carbon exchange between the surface and the atmosphere and therefore are suitable for carbon cycle model evaluation. In this study, we present a framework for how to use atmospheric CO2 observations to evaluate two distinct soil carbon models (CBALANCE, CBA, and Yasso, YAS) that are implemented in a global land surface model (JSBACH). We transported the biospheric carbon fluxes obtained by JSBACH using the atmospheric transport model TM5 to obtain atmospheric CO2. We then compared these results with surface observations from Global Atmosphere Watch stations, as well as with column XCO2 retrievals from GOSAT (Greenhouse Gases Observing Satellite). The seasonal cycles of atmospheric CO2 estimated by the two different soil models differed. The estimates from the CBALANCE soil model were more in line with the surface observations at low latitudes (0–45∘ N) with only a 1 % bias in the seasonal cycle amplitude, whereas Yasso underestimated the seasonal cycle amplitude in this region by 32 %. Yasso, on the other hand, gave more realistic seasonal cycle amplitudes of CO2 at northern boreal sites (north of 45∘ N) with an underestimation of 15 % compared to a 30 % overestimation by CBALANCE. Generally, the estimates from CBALANCE were more successful in capturing the seasonal patterns and seasonal cycle amplitudes of atmospheric CO2 even though it overestimated soil carbon stocks by 225 % (compared to an underestimation of 36 % by Yasso), and its estimations of the global distribution of soil carbon stocks were unrealistic. The reasons for these differences in the results are related to the different environmental drivers and their functional dependencies on the two soil carbon models. In the tropics, heterotrophic respiration in the Yasso model increased earlier in the season since it is driven by precipitation instead of soil moisture, as in CBALANCE. In temperate and boreal regions, the role of temperature is more dominant. There, heterotrophic respiration from the Yasso model had a larger seasonal amplitude, which is driven by air temperature, compared to CBALANCE, which is driven by soil temperature. The results underline the importance of using sub-annual data in the development of soil carbon models when they are used at shorter than annual timescales.

Abstract A coupled climate and carbon (CO2) cycle model is used to investigate the global climate and carbon cycle changes out to the year 2300 that would occur if CO2 emissions from all the currently estimated fossil fuel resources were released to the atmosphere. By the year 2300, the global climate warms by about 8 K and atmospheric CO2 reaches 1423 ppmv. The warming is higher than anticipated because the sensitivity to radiative forcing increases as the simulation progresses. In this simulation, the rate of emissions peaks at over 30 Pg C yr−1 early in the twenty-second century. Even at the year 2300, nearly 50% of cumulative emissions remain in the atmosphere. Both soils and living biomass are net carbon sinks throughout the simulation. Despite having relatively low climate sensitivity and strong carbon uptake by the land biosphere, these model projections suggest severe long-term consequences for global climate if all the fossil fuel carbon is ultimately released into the atmosphere.

In this paper, the earlier results, which were obtained with the climate model developed at the A.M. Obu khov Institute of Atmospheric Physics, Russian Academy of Sciences (IAP RAS CM) and related to the impact of the atmospheric sulphur dioxide on terrestrial carbon cycle, are elucidated. Because of the unavailability of the global data for near surface SO2 concentration, it was reconstructed by using statistical model which was fitted employing the output of the atmospheric chemistry-transport model RAMS-CMAQ. The obtained results are in general agreement with those reported earlier. In particular, the most significant SO2 impact on terrestrial carbon cycle is simulated for south-east North America and for Europe. However, such impact for south-east Asia is markedly weaker in comparison to that reported earlier, which is related to excessive moisture content in the atmosphere of this region.

Thesis (Ph. D.)--University of California, San Diego, 2007.
Title from first page of PDF file (viewed July 10, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 146-154).

Dans un contexte de changement climatique, la connaissance des climats passés permet de mieux cerner l'évolution future du climat. Les isotopes stables de l'eau constituent un excellent proxy paléo-climatique. Les propriétés physiques des isotopes lourds de l'eau (H182 O; HDO) induisent des fractionnements isotopiques, qui dépendent de la température et du taux de distillation. Sous réserve d'une inversion bien conditionnée du signal isotopique, on peut reconstruire les variations passées du climat à partir d'archives isotopiques. Les carottes de glace andines constituent un enregistrement unique de la variabilité du climat tropical. En revanche, la complexité de la circulation atmosphérique rend plus ardue l'interprétation de leur signal isotopique. En conséquence, nous avons développé au cours de cette thèse un module traitant du fractionnement des isotopes stables de l'eau au sein du modèle de circulation régionale REMO pour application au cas de l'Amérique du Sud. Le manuscrit retrace les principales étapes de la thèse. Il s'agit de la mise en perspective du travail de thèse dans la problématique du changement climatique ; la description du modèle de circulation régionale REMOiso et de son module traitant des isotopes de l'eau ; la validation initiale de REMOiso sur l'Europe ; l'étude des variations saisonnières des précipitations, de la circulation atmosphérique régionale et du signal isotopique en Amérique du Sud ; de l'enregistrement par les isotopes stables de l'eau de la mousson sud-américaine
Climate change has recently become a major concerning among scientists and the general public. A better knowledge of past climates helps forecasting the future evolution of climate. Stable water isotopes stand as an outstanding paleo-climate proxy. Physical properties of heavy stable water isotopes (H182 O; HDO) cause fractionation processes related to temperature and degree of distillation. If the isotopic signal is correctly inverted, past climate change can be inferred from isotopic archives. Andean ice-cores offer a unique records of tropical climate and its variability through time. However, the interpretation of the isotopic signal is difficult because of complex atmospheric dynamic over South America. For this purpose, we developed a module handling the stable water isotope fractionation processes within the regional circulation model REMO and applied it to South America. The manuscript outlines the major milestones of the present PhD. We first introduce the research topic in the wider scope of climate change; the description of the stable water isotope enabled regional circulation model REMOiso; an initial validation of REMOiso over Europe; an investigation of the seasonal variations of precipitation, atmospheric circulation and isotopic signal over South America; and at last the recording of the south American monsoon system (SAMS) by stable water isotope diagnostics

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 1992.
Title as it appears in the M.I.T. Graduate List, Feb. 1992: Diurnal cycle of deep cloud cover in tropics.
Includes bibliographical references (leaf 53).
by Sewon Park.
M.S.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 1999.
Includes bibliographical references (p. [84]-[87]).
In this thesis, I designed and implemented a simple atmosphere-ocean coupled carbon cycle model which can be used as a tool to uncover the mechanisms of the interaction between the dynamics of the atmosphere-ocean system and the oceanic reservoir of CO 2 on the 101 to 103 years time scale. The atmosphere-ocean coupled model is originally developed by Marotzke (20,21), and the biogeochemical model is developed by Follows(personal communication). The atmosphere-ocean-carbon model makes the atmosphere-ocean dynamics and the carbon cycle fully interactive, and results in two stationary states characterized by two distinct patterns of the thermohaline circulation. The temperature driven, high latitudes sinking mode showed significantly lower atmospheric pCO2 than the salinity-driven, low latitudes sinking mode. The atmosphere-ocean dynamics dominates the system behavior of the model. The carbon cycle weakly feedbacks on the atmosphere-ocean system through the radiation balance. The model reveals two feedback mechanisms, the global warming feedback and the thermohaline pCO 2 feedback. The thermohaline pCO2 feedback has three sub-components, which are the biological pump feedback, the outgassing feedback and the DIC exporting feedback. The numerical experiments estimate the relative importance among them. The system becomes less stable when all the feedback mechanism is introduced. The model could be used to understand some basic mechanism of the situations similar to the anthropogenic global warming. The stability analysis is applied to evaluate the model runs. The current rate of 7 GTC yr - 1 can induce the spontaneous shutdown of thermohaline circulation after 550 years of constant emission. The stability of the thermohaline circulation rapidly decreases even before the system stops the thermohaline circulation. The model parameterized surface alkalinity as a simple function of sea surface salinity or as a constant, rather than solving the alkalinity cycle explicitly. The system is sensitive to the parameterization, in which different assumptions on alkalinity lead to different results both analytically and numerically.
by Takamitsu Ito.
S.M.

ENGLISH:

The natural nitrogen cycle has been and is significantly perturbed by anthropogenic emissions of reactive nitrogen (Nr) compounds into the atmosphere, resulting from our production of energy and food. In the last century global ammonia (NH3) emissions have doubled and represent nowadays more than half of total the Nr emissions. NH3 is also the principal atmospheric base in the atmosphere and rapidly forms aerosols by reaction with acids. It is therefore a species of high relevance for the Earth's environment, climate and human health (Chapter 1). As a short-lived species, NH3 is highly variable in time and space, and while ground based measurements are possible, they are sparse and their spatial coverage is largely heterogeneous. Consequently, global spatial and temporal patterns of NH3 emissions are poorly understood and account for the largest uncertainties in the nitrogen cycle. The aim of this work is to assess distributions and saptiotemporal variability of NH3 using satellite measurements to improve our understanding of its contribution to the global nitrogen cycle and its related effects.

Recently, satellite instruments have demonstrated their abilities to measure NH3 and to supplement the sparse surface measuring network by providing global total columns daily. The Infrared Atmospheric Sounding Interferometer (IASI), on board MetOp platforms, is measuring NH3 at a high spatiotemporal resolution. IASI circles the Earth in a polar Sun-synchronous orbit, covering the globe twice a day with a circular pixel size of 12km diameter at nadir and with overpass times at 9:30 and 21:30 (local solar time when crossing the equator). An improved retrieval scheme based on the calculation of Hyperspectral Range Index (HRI) is detailed in Chapter 2 and compared with previous retrieval methods. This approach fully exploits the hyperspectral nature of IASI by using a broader spectral range (800-1200 cm-1) where NH3 is optically active. It allows retrieving total columns from IASI spectra globally and twice a day without large computational resources and with an improved detection limit. More specifically the retrieval procedure involves two steps: the calculation of a dimensionless spectral index (HRI) and the conversion of this index into NH3 total columns using look-up tables (LUTs) built from forward radiative transfer simulations under various atmospheric conditions. The retrieval also includes an error characterization of the retrieved column, which is of utmost importance for further analysis and comparisons. Global distributions using five years of data (1 November 2007 to 31 October 2012) from IASI/MetOp-A are presented and analyzed separately for the morning and evening overpasses. The advantage of the HRI-based retrieval scheme over other methods, in particular to identify smaller emission sources and transport patterns over the oceans is shown. The benefit of the high spatial sampling and resolution of IASI is highlighted with the regional distribution over China and the first four-year time series are briefly discussed.

We evaluate four years (1 January 2008 to 31 December 2011) of IASI-NH3 columns from the morning observations and of LOTOS-EUROS model simulations over Europe and Western Russia. We describe the methodology applied to account for the variable retrieval sensitivity of IASI measurements in Chapter 3. The four year mean distributions highlight three main agricultural hotspots in Europe: The Po Valley, the continental part of Northwestern Europe, and the Ebro Valley. A general good agreement between IASI and LOTOS-EUROS is shown, not only over source regions but also over remote areas and over seas when transport is observed. The yearly analyses reveal that, on average, the measured NH3 columns are higher than the modeled ones. Large discrepancies are observed over industrial areas in Eastern Europe and Russia pointing to underestimated if not missing emissions in the underlying inventories. For the three hotspots areas, we show that the seasonality between IASI and LOTOS-EUROS matches when the sensitivity of the satellite measurements is taken into account. The best agreement is found in the Netherlands, both in magnitude and timing, most likely as the fixed emission timing pattern was determined from experimental data sets from this country. Moreover, comparisons of the daily time series indicate that although the dynamic of the model is in reasonable agreement with the measurements, the model may suffer from a possible misrepresentation of emission timing and magnitude. Overall, the distinct temporal patterns observed for the three sites underline the need for improved timing of emissions. Finally, the study of the Russian fires event of 2010 shows that NH3 modeled plumes are not enough dispersed, which is confirmed with a comparison using in situ measurements.

Chapter 4 describes the comparisons of IASI-NH3 measurements with several independent ground-based and airborne data sets. Even though the in situ data are sparse, we show that the yearly distributions are broadly consistent. For the monthly analyzes we use ground-based measurements in Europe, China and Africa. Overall, IASI-derived concentrations are in fair agreement but are also characterized by less variability. Statistically significant correlations are found for several sites, but low slopes and high intercepts are calculated in all cases. At least three reasons can explain this: (1) the lack of representativity of the point surface measurement for the large IASI pixel, (2) the use of a single profile shape in the retrieval scheme over land, which does therefore not account for a varying boundary layer height, (3) the impact of the averaging procedure applied to satellite measurements to obtain a consistent quantity to compare with the in situ monthly data. The use of hourly surface measurements and of airborne data sets allows assessing IASI individual observations. Much higher correlation coefficients are found in particular when comparing IASI-derived volume mixing ratio with vertically resolved measurements performed from the NOAA WP-3D airplane during CalNex campaign in 2010. The results demonstrate the need, for validation of the satellite columns, of measurements performed at various altitudes and covering a large part of the satellite footprint.

The six-year of IASI observations available at the end of this thesis are used to analyze regional time series for the first time (Chapter 5). More precisely, we use the IASI measurements over that period (1 January 2008 to 31 December 2013) to identify seasonal patterns and inter-annual variability at subcontinental scale. This is achieved by looking at global composite seasonal means and monthly time series over 12 regions around the world (Europe, Eastern Russia and Northern Asia, Australia, Mexico, South America, 2 sub-regions for Northern America and South Asia, 3 sub-regions for Africa), considering separately but simultaneously measurements from IASI morning and evening overpasses. The seasonal cycle is inferred for the majority of these regions. The relations between the NH3 atmospheric abundance and emission processes is emphasized at smaller regional scale by extracting at high spatial resolution the global climatology of the month of maxima columns. In some region, the predominance of a single source appears clearly (e.g. agriculture in Europe and North America, fires in central South Africa and South America), while in others a composite of source processes on small scale is demonstrated (e.g. Northern Central Africa and Southwestern Asia).

Chapter 6 presents the achievements of this thesis, as well as ongoing activities and future perspectives.

FRANCAIS:

Le cycle naturel de l'azote est fortement perturbé suite aux émissions atmosphériques de composés azotés réactifs (Nr) résultant de nos besoins accrus en énergie et en nourriture. Les émissions d'ammoniac (NH3) ont doublé au cours du siècle dernier, représentant aujourd'hui plus de la moitié des émissions totales de Nr. De plus, le NH3 étant le principal composé basique de notre atmosphère, il réagit rapidement avec les composés acides pour former des aérosols. C'est dès lors un constituant prépondérant pour l'environnement, le climat et la santé publique. Les problématiques environnementales y étant liées sont décrites au Chapitre 1. En tant que gaz en trace le NH3 se caractérise par une importante variabilité spatiale et temporelle. Bien que des mesures in situ soient possibles, elles sont souvent rares et couvrent le globe de façon hétérogène. Il en résulte un manque de connaissance sur l'évolution temporelle et la variabilité spatiale des émissions, ainsi que de leurs amplitudes, qui représentent les plus grandes incertitudes pour le cycle de l'azote (également décrites au Chapitre 1).

Récemment, les sondeurs spatiaux opérant dans l'infrarouge ont démontré leurs capacités à mesurer le NH3 et par là à compléter le réseau d'observations de surface. Particulièrement, l'Interféromètre Atmosphérique de Sondage Infrarouge (IASI), à bord de la plateforme MetOp, mesure le NH3 à une relativement haute résolution spatiotemporelle. Il couvre le globe deux fois par jour, grâce à son orbite polaire et son balayage autour du nadir, avec un temps de passage à 9h30 et à 21h30 (temps solaire local quand il croise l'équateur). Une nouvelle méthode de restitution des concentrations basée sur le calcul d'un index hyperspectral sans dimension (HRI) est détaillée et comparée aux méthodes précédentes au Chapitre 2. Cette méthode permet d'exploiter de manière plus approfondie le caractère hyperspectral de IASI en se basant sur une bande spectrale plus étendue (800-1200 cm-1) au sein de laquelle le NH3 est optiquement actif. Nous décrivons comment restituer ces concentrations deux fois par jour sans nécessiter de grandes ressources informatiques et avec un meilleur seuil de détection. Plus spécifiquement, la procédure de restitution des concentrations consiste en deux étapes: le HRI est calculé dans un premier temps pour chaque spectre puis est ensuite converti en une colonne totale de NH3 à l'aide de tables de conversions. Ces tables ont été construites sur base de simulations de transfert radiatif effectuées pour différentes conditions atmosphériques. Le processus de restitution des concentrations comprend également le calcul d'une erreur sur la colonne mesurée. Des distributions globales moyennées sur cinq ans (du 1 novembre 2007 au 31 Octobre 2012) sont présentées et analysées séparément pour le passage diurne et nocturne de IASI. L'avantage de ce nouvel algorithme par rapport aux autres méthodes, permettant l'identification de sources plus faibles de NH3 ainsi que du transport depuis les sources terrestres au-dessus des océans, est démontré. Le bénéfice de la haute couverture spatiale et temporelle de IASI est mis en exergue par une description régionale au-dessus de la Chine ainsi que par l'analyse de premières séries temporelles hémisphériques sur quatre ans.

Au Chapitre 3, nous évaluons quatre ans (du 1 janvier 2008 au 31 décembre 2011) de mesures matinales de IASI ainsi que de simulations du modèle LOTOS-EUROS, effectuées au-dessus de l'Europe et de l'ouest de la Russie. Nous décrivons une méthodologie pour prendre en compte, dans la comparaison avec le modèle, la sensibilité variable de l'instrument IASI pour le NH3. Les comparaisons montrent alors une bonne concordance générale entre les mesures et les simulations. Les distributions pointent trois régions sources: la vallée du Pô, le nord-ouest de l'Europe continentale et la vallée de l'Ebre. L'analyse des distributions annuelles montre qu'en moyenne, les colonnes de NH3 mesurées sont plus élevées que celles simulées, à part pour quelques cas spécifiques. Des différences importantes ont été identifiées au-dessus de zones industrielles en Europe de l'est et en Russie, ce qui tend à incriminer une sub-estimation voire une absence de ces sources dans les inventaires d'émissions utilisés en entrée du modèle. Nous avons également montré que la saisonnalité est bien reproduite une fois la sensibilité des mesures satellites prise en compte. La meilleure concordance entre le modèle et IASI est observée pour les Pays-Bas, ce qui est certainement dû au fait que le profil temporel des émissions utilisé pour les simulations LOTOS-EUROS est basé sur des études expérimentales réalisées dans ce pays. L'étude des séries temporelles journalières indique que la dynamique du modèle est raisonnablement en accord avec les mesures mais pointe néanmoins une possible mauvaise représentation du profil temporel ainsi que de l'ampleur des émissions. Finalement, l'étude des importants feux ayant eu cours en Russie à l'été 2010 a montré que les panaches modélisés sont moins étendus que ceux observés, ce qui a été confirmé grâce à une comparaison avec des mesures sols.

Le chapitre 4 est dédié à la confrontation des mesures IASI avec différents jeux de données indépendants acquis depuis le sol et par avion. Les distributions globales annuelles sont concordantes, bien que la couverture spatiale des mesures sols soit limitée. Des mesures effectuées à la surface en Europe, en Chine et en Afrique sont utilisées pour les comparaisons mensuelles. Ces dernières révèlent une bonne concordance générale, bien que les mesures satellites montrent une plus faible amplitude de variations de concentrations. Des corrélations statistiquement significatives ont été calculées pour de nombreux sites, mais les régressions linéaires sont caractérisées par des pentes faibles et des ordonnées à l'origine élevées dans tous les cas. Au minimum, trois raisons contribuent à expliquer cela: (1) le manque de représentativité des mesures ponctuelles pour l'étendue des pixels IASI, (2) l'utilisation d'une seule forme de profil vertical pour la restitution des concentrations, qui ne prend dès lors pas en compte la hauteur de la couche limite, (3) l'impact de la procédure utilisée pour moyenner les observations satellites afin d'obtenir des quantités comparables aux mesures sols mensuelles. La prise en compte de mesures en surface effectuées à plus haute résolution temporelle ainsi que de mesures faites depuis un avion permet d'évaluer les observations IASI individuelles. Les coefficients de corrélation calculés sont bien plus élevés, en particulier pour la comparaison avec les mesures effectuées depuis l'avion NOAA WP-3D pendant la campagne CalNex en 2010. Ces résultats démontrent la nécessité de ce type d'observations, effectuées à différentes altitudes et couvrant une plus grande surface du pixel, pour valider les colonnes IASI-NH3.

Les six ans de données IASI disponibles à la fin de cette thèse sont utilisées pour tracer les premières séries temporelles sub-continentales (Chapitre 5). Plus spécifiquement, nous explorons les mesures IASI durant cette période (du 1 janvier 2008 jusqu'au 31 décembre 2013) pour identifier des structures saisonnières ainsi que la variabilité inter-annuelle à l'échelle sous-continentale. Pour arriver à cela, des moyennes saisonnières composites ont été produites ainsi que des séries temporelles mensuelles au-dessus de 12 régions du globe (Europe, est de la Russie et nord de l'Asie, Australie, Mexique, Amérique du Sud, 2 sous-régions en Amérique du nord et en Asie du sud et 3 sous-régions en Afrique), considérant séparément mais simultanément les mesures matinales et nocturnes de IASI. Le cycle saisonnier est raisonnablement bien décrit pour la plupart des régions. La relation entre la quantité de NH3 atmosphérique et ses sources d'émission est mise en exergue à l'échelle plus régionale par l'extraction à haute résolution spatiale d'une climatologie des mois de colonnes maximales. Dans certaines régions, la prédominance d'un processus source apparait clairement (par exemple l'agriculture en Europe et en Amérique du nord, les feux en Afrique du Sud et en Amérique du Sud), alors que, pour d'autres, la diversité des sources d'émissions est démontrée (par exemple pour le nord de l'Afrique centrale et l'Asie du sud-ouest).

Le Chapitre 6 reprend brièvement les principaux aboutissements de cette thèse et présente les différentes recherches en cours et les perspectives associées.

Doctorat en Sciences agronomiques et ingénierie biologique
info:eu-repo/semantics/nonPublished

Ocean Alkalinization deliberately modifies the chemistry of the surface ocean to enhance the uptake of atmospheric CO2. Here we quantify, using idealized Earth system model (ESM) simulations, changes in carbon cycle feedbacks and in the seasonal cycle of the surface ocean carbonate system due to ocean alkalinization. We find that both, carbon-concentration and carbon climate feedback, are enhanced due to the increased sensitivity of the carbonate system to changes in atmospheric CO2 and changes in temperature. While the temperature effect, which decreases ocean carbon uptake, remains small in our model, the carbon concentration feedback enhances the uptake of carbon due to alkalinization by more than 20%. The seasonal cycle of air-sea CO2 fluxes is strongly enhanced due to an increased buffer capacity in an alkalinized ocean. This is independent of the seasonal cycle of pCO2, which is only slightly enhanced. The most significant change in the seasonality of the surface ocean carbonate system is an increased seasonal cycle of the aragonite saturation state, which has the potential to adversely affect ecosystem health.

The Global Coupled model version 4 (GC4) is an upgraded configuration of the MetUM system, building upon its predecessor, GC3.0/3.1. It incorporates various improvements and changes in the atmospheric and land components (Global Atmosphere 8 and Global Land 9 - GA8GL9) while keeping the ocean component (Global Ocean 6 - GO6) unchanged, except for minor bug fixes. The GC4 model introduces several enhancements, such as the drag package for land surface and hydrology, improvements in radiation and large-scale precipitation parametrisations, advancements in the boundary layer and convection representation (including the prognostic-based convective entrainment rate - ProgEnt), and updates in aerosol properties. Additionally, the inclusion of a multi-grid solver in the dynamics module aims to improve model stability and reduce computational costs. Key improvements in GC4 include better representation of the diurnal cycle of convection over land, reduced Southern Ocean warm bias, increased rainfall over India during the JJA season, improved distribution of precipitation, enhanced representation of low-medium clouds over Northern Europe, and positive impacts of atmosphere-ocean coupling on NWP scores. However, challenges and areas for further improvement persist, including excessive global precipitation, warm biases over coastal regions of East Asia, wet biases over East Asia, weak cloud forcing over certain regions, hydrological cycle discrepancies, biases in gross primary productivity, persistent Southern Ocean biases, enhanced warming and weakened trade winds in the equatorial east Pacific, excessive surface warming in the North Atlantic, weakening of monsoon low-pressure systems and tropical cyclones, drying over Africa, and excessive thick cloud biases in mid-latitudes. The next version of GC (GC5) will attempt to address some of these biases in the next development and assessment cycle with inputs from relevant evaluation groups and partners.

Snow is a critical component of the global hydrologic cycle and is a key input to river and stream flow forecasts. In 2016, the National Oceanic and Atmospheric Administration launched the National Water Model (NWM) to provide a high-fidelity numerical forecast of streamflow integrated with the broader atmospheric prediction modeling framework. The NWM is coupled to the atmospheric model using the Noah-MP land surface modeling framework. While snow in Noah-MP has been consistently evaluated in the western United States, less attention has been paid to understanding and optimizing its performance in the Northeast US (NEUS). The newly installed New York State Mesonet (NYSM), a network of high-quality surface meteorological stations distributed across New York State, provides a unique opportunity to evaluate Noah-MP performance in the NEUS. In this report, we document the methodology used to perform single-column simulations using meteorological inputs from the NYSM and compare the point evaluations against baseline NWM performance. We further discuss how enhanced surface energy balance measurements at a selection of NYSM sites can be used to evaluate specific components of Noah-MP and present initial results.