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Статті в журналах з теми "Model Seasonal Cycle"
Stein, Karl, Niklas Schneider, Axel Timmermann, and Fei-Fei Jin. "Seasonal Synchronization of ENSO Events in a Linear Stochastic Model*." Journal of Climate 23, no. 21 (November 1, 2010): 5629–43. http://dx.doi.org/10.1175/2010jcli3292.1.
Повний текст джерелаJucker, M., S. Fueglistaler, and G. K. Vallis. "Maintenance of the Stratospheric Structure in an Idealized General Circulation Model." Journal of the Atmospheric Sciences 70, no. 11 (October 31, 2013): 3341–58. http://dx.doi.org/10.1175/jas-d-12-0305.1.
Повний текст джерелаCubadda, Gianluca, Giovanni Savio, and Roberto Zelli. "SEASONALITY, PRODUCTIVITY SHOCKS, AND SECTORAL COMOVEMENTS IN A REAL BUSINESS CYCLE MODEL FOR ITALY." Macroeconomic Dynamics 6, no. 3 (June 2002): 337–56. http://dx.doi.org/10.1017/s1365100500000316.
Повний текст джерелаGilford, Daniel M., and Susan Solomon. "Radiative Effects of Stratospheric Seasonal Cycles in the Tropical Upper Troposphere and Lower Stratosphere." Journal of Climate 30, no. 8 (April 2017): 2769–83. http://dx.doi.org/10.1175/jcli-d-16-0633.1.
Повний текст джерелаGiese, Benjamin S., and James A. Carton. "The Seasonal Cycle in Coupled Ocean-Atmosphere Model." Journal of Climate 7, no. 8 (August 1994): 1208–17. http://dx.doi.org/10.1175/1520-0442(1994)007<1208:tscico>2.0.co;2.
Повний текст джерелаChen, Gang, and Lantao Sun. "Mechanisms of the Tropical Upwelling Branch of the Brewer–Dobson Circulation: The Role of Extratropical Waves." Journal of the Atmospheric Sciences 68, no. 12 (December 1, 2011): 2878–92. http://dx.doi.org/10.1175/jas-d-11-044.1.
Повний текст джерелаHindrayanto, Irma, Jan P. A. M. Jacobs, Denise R. Osborn, and Jing Tian. "TREND–CYCLE–SEASONAL INTERACTIONS: IDENTIFICATION AND ESTIMATION." Macroeconomic Dynamics 23, no. 8 (February 6, 2018): 3163–88. http://dx.doi.org/10.1017/s1365100517001092.
Повний текст джерелаStein, Karl, Axel Timmermann, Niklas Schneider, Fei-Fei Jin, and Malte F. Stuecker. "ENSO Seasonal Synchronization Theory." Journal of Climate 27, no. 14 (July 10, 2014): 5285–310. http://dx.doi.org/10.1175/jcli-d-13-00525.1.
Повний текст джерелаThum, Tea, Julia E. M. S. Nabel, Aki Tsuruta, Tuula Aalto, Edward J. Dlugokencky, Jari Liski, Ingrid T. Luijkx, et al. "Evaluating two soil carbon models within the global land surface model JSBACH using surface and spaceborne observations of atmospheric CO<sub>2</sub>." Biogeosciences 17, no. 22 (November 23, 2020): 5721–43. http://dx.doi.org/10.5194/bg-17-5721-2020.
Повний текст джерелаMongwe, N. Precious, Marcello Vichi, and Pedro M. S. Monteiro. "The seasonal cycle of <i>p</i>CO<sub>2</sub> and CO<sub>2</sub> fluxes in the Southern Ocean: diagnosing anomalies in CMIP5 Earth system models." Biogeosciences 15, no. 9 (May 15, 2018): 2851–72. http://dx.doi.org/10.5194/bg-15-2851-2018.
Повний текст джерелаДисертації з теми "Model Seasonal Cycle"
Mortin, Jonas. "On the Arctic Seasonal Cycle." Doctoral thesis, Stockholms universitet, Meteorologiska institutionen (MISU), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-100008.
Повний текст джерелаAt the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: In press. Paper 4: Submitted.
Mongwe, Ndunisani Precious. "The seasonal cycle of CO₂ fluxes in the Southern Ocean: a model spatial scale sensitivity analysis." Master's thesis, University of Cape Town, 2014. http://hdl.handle.net/11427/29014.
Повний текст джерелаA recent study by Lenton et al., 2013, compared the mean seasonal cycle of air-sea CO₂ flux in the Southern Ocean(SO) over 1990 – 2009 period using five ocean biogeochemical models(BGMs) and atmospheric and ocean inversion models with monthly mean observations for the year 2000. This was done using a set of geographic boundaries to defined sub-domains of the SO consistent with the Regional Carbon Cycle and Assessment and Processes (RECCAP) protocol. Lenton et al., 2013 found that the seasonal cycle anomaly of the five BGMs better resolved observations of the air-sea CO₂ flux seasonal cycle in the SAZ, but was generally out phase with observations in the polar zone. In this study two setups of the ocean biogeochemical model NEMO PISCES was used to investigate the characteristics of the air-sea CO₂ flux seasonal cycle in the Southern Ocean in the period 1993- 2006. The study focused on two aspects i.e. (i) the sensitivity of air-sea CO₂ flux seasonal cycle to model resolution: comparing the ORCA2-LIM-PISCES (2° x 2° cos Ø) and PERIANT05 (NEMO-PISCES) (0.5° x 0.5° cos Ø) model configurations relative to climatological mean observations for the year 2000 (Takahashi et al., 2009) , and (ii) the sensitivity of air-sea CO₂ flux seasonal cycle to zonal boundary definition: comparing the air-sea CO₂ flux seasonal cycle and annual fluxes for three different boundaries i.e. Lenton 2013 RECCAP boundaries (44°S – 58°S and south of 58°S), geographic boundaries (40°S -50°S and south of 50°S) and dynamic boundaries (Sub-Antarctic Zone and Antarctic Zone, defined using climatological frontal positions). The seasonal cycle of the air-sea CO₂ flux in ORCA2 was found to be out of phase and overestimated the CO₂ flux compared to observations in almost all the sub-regions considered. The use of dynamic boundaries was found not to improve resolving observations seasonal cycle of air-sea CO₂ flux in both ORCA2 and PERIANT05. Boundary definition was found to affect the magnitude of ORCA2 annual air-sea CO₂ fluxes surface area based, where sub-regions of larger surface area gave larger annual CO₂ uptake and vice versa. This was mainly because ORCA2 air-sea CO₂ fluxes were found to show a general CO₂ in-gassing bias and spatially uniform in most parts of the SO and hence integration over a larger surface area gave larger annual fluxes. On the contrary PERIANT05 air-sea CO₂ fluxes spatial variability was not uniform in most parts of the SO however influenced by regional processes and hence annual fluxes were found not surface area based. The poor spatial representation and seasonal cycle sensitivity of ORCA2 air-sea CO₂ fluxes was found to be primarily due to lack or weak winter CO₂ entrainment and biological CO₂ draw down during the summer season. PERIANT05 on the contrary showed the effect of winter CO₂ entrainment, however maintains lack of or weak biological CO₂ draw down in the seasonal cycle. PERIANT05 was also found to show major weakness in the spatial representation of air-sea CO₂ fluxes north of the polar front with relative to T09 observations.
Gordon, Lawrence Joseph. "Analysis of a simulation of the seasonal cycle in the tropical Pacific Ocean in an eddy-resolving global ocean model." Thesis, Monterey, California. Naval Postgraduate School, 1992. http://hdl.handle.net/10945/23537.
Повний текст джерелаThis paper examines the multi-level, primitive equation, global ocean circulation model of Semtner and Chervin for its ability to simulate the seasonal cycle in the tropical Pacific Ocean. The result of a 20-year integration of this model using annual mean wind forcing was reported in Semtner and Chervin (1988). This was the first global eddyresolving ocean calculation and it showed many realistic features of ocean circulation. The phase of the simulation analyzed in this report incorporates seasonally varying wind forcing from the Hellerman and Rosenstein (1983) global data set. These wind stress values were defined on a grid with 2° spacing which have been interpolated to the onehalf degree grid points of the Semtner and Chervin model. There is no interannual variability in the wind fields of this data set. The results presented here are from the fourth year of a 10-year seasonal cycle run.
Gatfaoui, Jamel. "Modeling Chinese provincial business cycles." Thesis, Aix-Marseille, 2012. http://www.theses.fr/2012AIXM1110.
Повний текст джерелаThis thesis deals with the Chinese provincial growth cycles over the period 1989-2009. First, we use a variety of techniques to examine the nature and degree of comovement among Chinese provincial growth cycles. We detect different properties of the provincial growth cycles. Using a model-based clustering methodology, we find that provinces can be classified among five major clusters as a function of standard measures of cyclical characteristics. Although the majority of provinces experienced the recession that occurred around the Asian crisis, the nation as whole experienced an expansionary phase. Moreover, all the provinces experienced the recession related to the subprime crisis that occurred in 2007/2008 except Jiangsu and Tianjing. However, All coastal provinces except Hainan are significantly synchronized with the national cycle. Furthermore, we find that the main four national recessions are well diffused across the country. Then, we analyse the co-cyclicality between provinces in each of the six regions defined by Groenewold et al. (2008). We rely on trend-cycle decomposition by using both univariate and multivariate unobserved component model. The majority of provincial cycles reflect demand rather than supply-side shocks. By examining the commonality of provincial growth cycles within each region, we ask whether the definition of these regions is supported by statistical analysis. We find mixed results. Finally, we use a Markov switching model that allow for the identification of business/seasonal cycle interaction
Van, Damme Martin. "Assessment of global atmospheric ammonia using IASI infrared satellite observations." Doctoral thesis, Universite Libre de Bruxelles, 2015. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209085.
Повний текст джерелаThe 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
Domingues, Catia Motta, and Catia Domingues@csiro au. "Kinematics and Heat Budget of the Leeuwin Current." Flinders University. SOCPES, 2006. http://catalogue.flinders.edu.au./local/adt/public/adt-SFU20060612.211358.
Повний текст джерелаHsu, Wei-Ching. "The variability and seasonal cycle of the Southern Ocean carbon flux." Thesis, Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/49079.
Повний текст джерелаLiu, Yongwen, Shilong Piao, Xu Lian, Philippe Ciais, and W. Kolby Smith. "Seasonal Responses of Terrestrial Carbon Cycle to Climate Variations in CMIP5 Models: Evaluation and Projection." AMER METEOROLOGICAL SOC, 2017. http://hdl.handle.net/10150/625331.
Повний текст джерелаMurray-Tortarolo, Guillermo Nicolas. "Recent trends in the land carbon cycle." Thesis, University of Exeter, 2015. http://hdl.handle.net/10871/18661.
Повний текст джерелаPyeatt, John Samuel. "The seasonal cycle of planetary-scale divergent circulations a comparison of observed fields and model simulations /." 1987. http://catalog.hathitrust.org/api/volumes/oclc/16461301.html.
Повний текст джерелаTypescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 93-97).
Книги з теми "Model Seasonal Cycle"
Gordon, Lawrence Joseph. Analysis of a simulation of the seasonal cycle in the tropical Pacific Ocean in an eddy-resolving global ocean model. Monterey, Calif: Naval Postgraduate School, 1992.
Знайти повний текст джерелаBarsky, Robert B. The seasonal cycle and the business cycle. Cambridge, MA: National Bureau of Economic Research, 1988.
Знайти повний текст джерелаCecchetti, Stephen G. International cycles. Cambridge, MA: National Bureau of Economic Research, 1995.
Знайти повний текст джерелаMiron, Jeffrey A. What have macroeconomists learned about business cycles from the study of seasonal cycles? Cambridge, MA: National Bureau of Economic Research, 1995.
Знайти повний текст джерелаKrane, Spencer D. The cyclical sensitivity of seasonality in US employment. Basle, Switzerland: Bank for International Settlements, Monetary and Economic Dept., 1999.
Знайти повний текст джерелаLumsdaine, Robin L. Identifying the common component in international economic fluctuations. Cambridge, MA: National Bureau of Economic Research, 1997.
Знайти повний текст джерелаCecchetti, Stephen G. Do firms smooth the seasonal in production in a boom?: Theory and evidence. Cambridge, MA: National Bureau of Economic Research, 1995.
Знайти повний текст джерелаGoswami, B. N., and Soumi Chakravorty. Dynamics of the Indian Summer Monsoon Climate. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.613.
Повний текст джерелаHameed, Saji N. The Indian Ocean Dipole. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.619.
Повний текст джерелаLumsdaine, Robin L., and Eswar Prasad. Identifying the Common Component in International Economic Fluctuations: A New Approach. International Monetary Fund, 1999.
Знайти повний текст джерелаЧастини книг з теми "Model Seasonal Cycle"
Bee Dagum, Estela, and Silvia Bianconcini. "Seasonal Adjustment Based on ARIMA Model Decomposition: TRAMO-SEATS." In Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation, 115–45. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31822-6_5.
Повний текст джерелаFung, Inez Y. "Analysis of the Seasonal and Geographical Patterns of Atmospheric CO2 Distributions with a Three-Dimensional Tracer Model." In The Changing Carbon Cycle, 459–73. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1915-4_22.
Повний текст джерелаHeimann, Martin, Charles D. Keeling, and Compton J. Tucker. "A three dimensional model of atmospheric CO2transport based on observed winds: 3. Seasonal cycle and synoptic time scale variations." In Aspects of Climate Variability in the Pacific and the Western Americas, 277–303. Washington, D. C.: American Geophysical Union, 2013. http://dx.doi.org/10.1029/gm055p0277.
Повний текст джерелаBee Dagum, Estela, and Silvia Bianconcini. "Seasonal Adjustment Based on Structural Time Series Models." In Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation, 147–64. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31822-6_6.
Повний текст джерелаJolly, W. Matt, and Elliott T. Conrad. "A mechanistic live fuel moisture model." In Advances in Forest Fire Research 2022, 32–35. Imprensa da Universidade de Coimbra, 2022. http://dx.doi.org/10.14195/978-989-26-2298-9_3.
Повний текст джерелаCastellano, Leonardo, Nicoletta Sala, Angelo Rolla, and Walter Ambrosetti. "The Residence Time of the Water in Lake MAGGIORE. Through an Eulerian-Lagrangian Approach." In Complexity Science, Living Systems, and Reflexing Interfaces, 218–34. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2077-3.ch011.
Повний текст джерелаAbrams, Peter A. "Competition in seasonal environments." In Competition Theory in Ecology, 171–208. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780192895523.003.0008.
Повний текст джерела"Pacific Salmon: Ecology and Management of Western Alaska’s Populations." In Pacific Salmon: Ecology and Management of Western Alaska’s Populations, edited by David A. Beauchamp. American Fisheries Society, 2009. http://dx.doi.org/10.47886/9781934874110.ch5.
Повний текст джерелаSilva, Pedro, Miguel Carmo, João Rio, and Ilda Novo. "Evolution of the annual cycle of Burned Area in Portugal from 1980 to 2018: Implications for fire season management." In Advances in Forest Fire Research 2022, 1095–100. Imprensa da Universidade de Coimbra, 2022. http://dx.doi.org/10.14195/978-989-26-2298-9_165.
Повний текст джерелаWang, Fang. "Numerical Simulation Analysis of Hydrothermal Change of Subgrade by Seepage Drainage Geogrid Under the Effect of Asphalt Mixture Freeze-Thaw Action." In Advances in Transdisciplinary Engineering. IOS Press, 2021. http://dx.doi.org/10.3233/atde210146.
Повний текст джерелаТези доповідей конференцій з теми "Model Seasonal Cycle"
Hilleman, Douglas, John M. Lindsay, and Tim Hinson. "Gainesville Regional Utilities Kelly Plant Asset Management With Cycling Operation." In ASME 2015 Power Conference collocated with the ASME 2015 9th International Conference on Energy Sustainability, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/power2015-49148.
Повний текст джерелаMilton, J. W. "A Review of Seasonal Dispatch Modeling Methods." In ASME 2005 Power Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/pwr2005-50087.
Повний текст джерелаMa, Jungmok, and Harrison M. Kim. "Predictive Usage Mining for Sustainability of Complex Systems Design." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34755.
Повний текст джерелаHasan, Osama, A. F. M. Arif, and M. U. Siddiqui. "Finite Element Modeling and Analysis of Photovoltaic Modules." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-89429.
Повний текст джерелаGracian, Luis Alberto, Ivan Miguel Arguello, and Iskander Rasimovich Diyashev. "Gas-Flaring Solution Enhances Oil Recovery and Electric Power Reliability." In SPE Western Regional Meeting. SPE, 2023. http://dx.doi.org/10.2118/213002-ms.
Повний текст джерелаDyreby, John J., Sanford A. Klein, Gregory F. Nellis, and Douglas T. Reindl. "Modeling Off-Design and Part-Load Performance of Supercritical Carbon Dioxide Power Cycles." In ASME Turbo Expo 2013: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/gt2013-95824.
Повний текст джерелаFujii, Shoma, Yuichiro Kanematsu, Yasunori Kikuchi, and Takao Nakagaki. "Effect of Multi Injection Process on “Zeolite Boiler” in Thermochemical Energy Storage and Transport System of Unused Heat From Bagasse Boiler." In ASME 2017 11th International Conference on Energy Sustainability collocated with the ASME 2017 Power Conference Joint With ICOPE-17, the ASME 2017 15th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2017 Nuclear Forum. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/es2017-3253.
Повний текст джерелаSánchez-Murillo, Ricardo. "Tracer hydrology of the data-scarce and heterogeneous Central American Isthmus." In I Congreso Internacional de Ciencias Exactas y Naturales. Universidad Nacional, 2019. http://dx.doi.org/10.15359/cicen.1.36.
Повний текст джерелаKim, Donghoi, Rubén M. Montañés, Luca Riboldi, Lars O. Nord, Jan Spale, and Vaclav Novotny. "Design optimization of small-scale ORC cycles for fluctuating heat source." In 63rd International Conference of Scandinavian Simulation Society, SIMS 2022, Trondheim, Norway, September 20-21, 2022. Linköping University Electronic Press, 2022. http://dx.doi.org/10.3384/ecp192029.
Повний текст джерелаNutter, Darin W., and Dennis L. O’Neal. "Shortening the Defrost Cycle Time With Active Enhancement Within the Suction-Line Accumulator of an Air-Source Heat Pump." In ASME 1996 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/imece1996-0261.
Повний текст джерелаЗвіти організацій з теми "Model Seasonal Cycle"
Miron, Jeffrey. Seasonal Fluctuations and the Life Cycle-Permanent Income Model of Consumption. Cambridge, MA: National Bureau of Economic Research, February 1986. http://dx.doi.org/10.3386/w1845.
Повний текст джерелаSchwinger, Jörg. Report on modifications of ocean carbon cycle feedbacks under ocean alkalinization. OceanNETs, June 2022. http://dx.doi.org/10.3289/oceannets_d4.2.
Повний текст джерелаVanderGheynst, Jean, Michael Raviv, Jim Stapleton, and Dror Minz. Effect of Combined Solarization and in Solum Compost Decomposition on Soil Health. United States Department of Agriculture, October 2013. http://dx.doi.org/10.32747/2013.7594388.bard.
Повний текст джерелаSamach, Alon, Douglas Cook, and Jaime Kigel. Molecular mechanisms of plant reproductive adaptation to aridity gradients. United States Department of Agriculture, January 2008. http://dx.doi.org/10.32747/2008.7696513.bard.
Повний текст джерелаDay, Christopher M., Hiromal Premachandra, and Darcy M. Bullock. Characterizing the Impacts of Phasing, Environment, and Temporal Factors on Pedestrian Demand at Traffic Signals. Purdue University, 2011. http://dx.doi.org/10.5703/1288284317352.
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