Academic literature on the topic 'Model Seasonal Cycle'

Abstract A simple model of ENSO is developed to examine the effects of the seasonally varying background state of the equatorial Pacific on the seasonal synchronization of ENSO event peaks. The model is based on the stochastically forced recharge oscillator, extended to include periodic variations of the two main model parameters, which represent ENSO’s growth rate and angular frequency. Idealized experiments show that the seasonal cycle of the growth rate parameter sets the seasonal cycle of ENSO variance; the inclusion of the time dependence of the angular frequency parameter has a negligible effect. Event peaks occur toward the end of the season with the most unstable growth rate. Realistic values of the parameters are estimated from a linearized upper-ocean heat budget with output from a high-resolution general circulation model hindcast. Analysis of the hindcast output suggests that the damping by the mean flow field dominates the seasonal cycle of ENSO’s growth rate and, thereby, seasonal ENSO variance. The combination of advective, Ekman pumping, and thermocline feedbacks plays a secondary role and acts to enhance the seasonal cycle of the ENSO growth rate.

Abstract This work explores the maintenance of the stratospheric structure in a primitive equation model that is forced by a Newtonian cooling with a prescribed radiative equilibrium temperature field. Models such as this are well suited to analyze and address questions regarding the nature of wave propagation and troposphere–stratosphere interactions. The focus lies on the lower to midstratosphere and the mean annual cycle, with its large interhemispheric variations in the radiative background state and forcing, is taken as a benchmark to be simulated with reasonable verisimilitude. A reasonably realistic basic stratospheric temperature structure is a necessary first step in understanding stratospheric dynamics. It is first shown that using a realistic radiative background temperature field based on radiative transfer calculations substantially improves the basic structure of the model stratosphere compared to previously used setups. Then, the physical processes that are needed to maintain the seasonal cycle of temperature in the lower stratosphere are explored. It is found that an improved stratosphere and seasonally varying topographically forced stationary waves are, in themselves, insufficient to produce a seasonal cycle of sufficient amplitude in the tropics, even if the topographic forcing is large. Upwelling associated with baroclinic wave activity is an important influence on the tropical lower stratosphere and the seasonal variation of tropospheric baroclinic activity contributes significantly to the seasonal cycle of the lower tropical stratosphere. Given a reasonably realistic basic stratospheric structure and a seasonal cycle in both stationary wave activity and tropospheric baroclinic instability, it is possible to obtain a seasonal cycle in the lower stratosphere of amplitude comparable to the observations.

This paper investigates the degree of comovements in quarterly Italian time series of sectoral output. A recently developed multivariate technique for the empirical analysis of long-run, cyclical and seasonal comovements is used in the context of a multisectoral real-business-cycle model augmented with persistent seasonal shocks in productivity. Our empirical results emphasize the role of input–output relations in the propagation mechanism and indicate that sectoral outputs have a relatively low number of common stochastic trends, in conflict with the hypothesis of independent productivity shocks. In contrast, stochastic seasonals seem to move idiosyncratically. Furthermore, our findings suggest that the theoretical model should be extended to allow for deterministic seasonal shifts in preferences.

Water vapor and ozone are powerful radiative constituents in the tropical lower stratosphere, impacting the local heating budget and nonlocally forcing the troposphere below. Their near-tropopause seasonal cycle structures imply associated “radiative seasonal cycles” in heating rates that could affect the amplitude and phase of the local temperature seasonal cycle. Overlying stratospheric seasonal cycles of water vapor and ozone could also play a role in the lower stratosphere and upper troposphere heat budgets through nonlocal propagation of radiation. Previous studies suggest that the tropical lower stratospheric ozone seasonal cycle radiatively amplifies the local temperature seasonal cycle by up to 35%, while water vapor is thought to have a damping effect an order of magnitude smaller. This study uses Aura Microwave Limb Sounder observations and an offline radiative transfer model to examine ozone, water vapor, and temperature seasonal cycles and their radiative linkages in the lower stratosphere and upper troposphere. Radiative sensitivities to ozone and water vapor vertical structures are explicitly calculated, which has not been previously done in a seasonal cycle context. Results show that the water vapor radiative seasonal cycle in the lower stratosphere is not sensitive to the overlying water vapor structure. In contrast, about one-third of ozone’s radiative seasonal cycle amplitude at 85 hPa is associated with longwave emission above 85 hPa. Ozone’s radiative effects are not spatially homogenous: for example, the Northern Hemisphere tropics have a seasonal cycle of radiative temperature adjustments with an amplitude 0.8 K larger than the Southern Hemisphere tropics.

Abstract The role of extratropical waves in the tropical upwelling branch of the Brewer–Dobson circulation is investigated in an idealized model of the stratosphere and troposphere. To simulate different stratospheric seasonal cycles of planetary waves in the two hemispheres, seasonally varying radiative heating is imposed only in the stratosphere, and surface topographic forcing is prescribed only in the Northern Hemisphere (NH). A zonally symmetric version of the same model is used to diagnose the effects of different wavenumbers and different regions of the total forcing on tropical stratospheric upwelling. The simple configuration can simulate a reasonable seasonal cycle of the tropical upwelling in the lower stratosphere with a stronger amplitude in January (NH midwinter) than in July (NH midsummer), as in the observations. It is shown that the seasonal cycle of stratospheric planetary waves and tropical upwelling responds nonlinearly to the strength of the tropospheric forcing, with a midwinter maximum under strong NH-like tropospheric forcing and double peaks in the fall and spring under weak Southern Hemisphere (SH)-like forcing. The planetary wave component of the total forcing can approximately reproduce the seasonal cycle of tropical stratospheric upwelling in the zonally symmetric model. The zonally symmetric model further demonstrates that the planetary wave forcing in the winter tropical and subtropical stratosphere contributes most to the seasonal cycle of tropical stratospheric upwelling, rather than the high-latitude wave forcing. This suggests that the planetary wave forcing, prescribed mostly in the extratropics in the model, has to propagate equatorward into the subtropical latitudes to induce sufficient tropical upwelling. Another interesting finding is that the planetary waves in the summer lower stratosphere can drive a shallow residual circulation rising in the subtropics and subsiding in the extratropics.

Economists typically use seasonally adjusted data in which the assumption is imposed that seasonality is uncorrelated with trend and cycle. The importance of this assumption has been highlighted by the Great Recession. The paper examines an unobserved components model that permits nonzero correlations between seasonal and nonseasonal shocks. Identification conditions for estimation of the parameters are discussed from the perspectives of both analytical and simulation results. Applications to UK household consumption expenditures and US employment reject the zero correlation restrictions and also show that the correlation assumptions imposed have important implications about the evolution of the trend and cycle in the post-Great Recession period.

Abstract One of the key characteristics of El Niño–Southern Oscillation (ENSO) is its synchronization to the annual cycle, which manifests in the tendency of ENSO events to peak during boreal winter. Current theory offers two possible mechanisms to account the for ENSO synchronization: frequency locking of ENSO to periodic forcing by the annual cycle, or the effect of the seasonally varying background state of the equatorial Pacific on ENSO’s coupled stability. Using a parametric recharge oscillator (PRO) model of ENSO, the authors test which of these scenarios provides a better explanation of the observed ENSO synchronization. Analytical solutions of the PRO model show that the annual modulation of the growth rate parameter results directly in ENSO’s seasonal variance, amplitude modulation, and 2:1 phase synchronization to the annual cycle. The solutions are shown to be applicable to the long-term behavior of the damped model excited by stochastic noise, which produces synchronization characteristics that agree with the observations and can account for the variety of ENSO synchronization behavior in state-of-the-art coupled general circulation models. The model also predicts spectral peaks at “combination tones” between ENSO and the annual cycle that exist in the observations and many coupled models. In contrast, the nonlinear frequency entrainment scenario predicts the existence of a spectral peak at the biennial frequency corresponding to the observed 2:1 phase synchronization. Such a peak does not exist in the observed ENSO spectrum. Hence, it can be concluded that the seasonal modulation of the coupled stability is responsible for the synchronization of ENSO events to the annual cycle.

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. The Southern Ocean forms an important component of the Earth system as a major sink of CO2 and heat. Recent studies based on the Coupled Model Intercomparison Project version 5 (CMIP5) Earth system models (ESMs) show that CMIP5 models disagree on the phasing of the seasonal cycle of the CO2 flux (FCO2) and compare poorly with available observation products for the Southern Ocean. Because the seasonal cycle is the dominant mode of CO2 variability in the Southern Ocean, its simulation is a rigorous test for models and their long-term projections. Here we examine the competing roles of temperature and dissolved inorganic carbon (DIC) as drivers of the seasonal cycle of pCO2 in the Southern Ocean to explain the mechanistic basis for the seasonal biases in CMIP5 models. We find that despite significant differences in the spatial characteristics of the mean annual fluxes, the intra-model homogeneity in the seasonal cycle of FCO2 is greater than observational products. FCO2 biases in CMIP5 models can be grouped into two main categories, i.e., group-SST and group-DIC. Group-SST models show an exaggeration of the seasonal rates of change of sea surface temperature (SST) in autumn and spring during the cooling and warming peaks. These higher-than-observed rates of change of SST tip the control of the seasonal cycle of pCO2 and FCO2 towards SST and result in a divergence between the observed and modeled seasonal cycles, particularly in the Sub-Antarctic Zone. While almost all analyzed models (9 out of 10) show these SST-driven biases, 3 out of 10 (namely NorESM1-ME, HadGEM-ES and MPI-ESM, collectively the group-DIC models) compensate for the solubility bias because of their overly exaggerated primary production, such that biologically driven DIC changes mainly regulate the seasonal cycle of FCO2.

The seasonal cycle of snow and sea ice is a fundamental feature of the Arctic climate system. In the Northern Hemisphere, about 55 million km2 of sea ice and snow undergo complete melt and freeze processes every year. Because snow and sea ice are much brighter (higher albedo) than the underlying surface, their presence reduces absorption of incoming solar energy at high latitudes. Therefore, changes of the sea-ice and snow cover have a large impact on the Arctic climate and possibly at lower latitudes. One of the most important determining factors of the seasonal snow and sea-ice cover is the timing of the seasonal melt-freeze transitions. Hence, in order to better understand Arctic climate variability, it is key to continuously monitor these transitions. This thesis presents an algorithm for obtaining melt-freeze transitions using scatterometers over both the land and sea-ice domains. These satellite-borne instruments emit radiation at microwave wavelengths and measure the returned signal. Several scatterometers are employed: QuikSCAT (1999–2009), ASCAT (2009–present), and OSCAT (2009–present). QuikSCAT and OSCAT operate at Ku-band (λ=2.2 cm) and ASCAT at C-band (λ=5.7 cm), resulting in slightly different surface interactions. This thesis discusses these dissimilarities over the Arctic sea-ice domain, and juxtaposes the time series of seasonal melt-freeze transitions from the three scatterometers and compares them with other, independent datasets. The interactions of snow and sea ice with other components of the Arctic climate system are complex. Models are commonly employed to disentangle these interactions. But this hinges upon robust and well-formulated models, reached by perpetual testing against observations. This thesis also presents an evaluation of how well eleven state-of-the-art global climate models reproduce the Arctic sea-ice cover and the summer length—given by the melt-freeze transitions—using surface observations of air temperature.

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: In press. Paper 4: Submitted.

Includes bibliographical references
A 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.

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This 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.

Cette thèse étudie les cycles économiques provinciaux chinois durant la période 1989-2009. Dans un premier temps, Nous utilisons une variété de techniques afin d'examiner la nature et le degré de comouvement entre les cycles de croissance provinciaux chinois. Nous détectons différentes propriétés des cycles de croissance provinciaux. En utilisant une méthodologie de classification basée sur un modèle, nous constatons que les provinces peuvent être classées parmi cinq classes en fonction des mesures standards des caractéristiques cycliques. Bien que la majorité des provinces a connu la récession qui a eu lieu autour de la crise asiatique, la nation dans son ensemble a connu une phase d'expansion. En outre, toutes les provinces, ont connu la récession liée à la crise financière internationale qui a eu lieu en 2007/2008 à l'exception du Jiangsu et Tianjin. Toutes les provinces côtières, sauf Hainan, sont significativement synchronisées avec le cycle national. En outre, nous constatons que les quatre principales récessions nationales sont bien diffusées dans tout le pays. Ensuite, nous analysons la co-cyclicité entre les provinces dans chacune des six régions définies par Groenewold et al. (2008). Nous nous basons sur la décomposition tendance-cycle en utilisant le modèle à composantes inobservables univarié et multivarié. Nous trouvons que La majorité des cycles provinciaux reflètent des chocs de la demande plutôt que des chocs de l'offre. En examinant si des cycles communs existent au sein de chaque région, nous pouvons formuler des conclusions sur la pertinence de la définition de ces régions
This 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

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

This study investigates the upper ocean circulation along the west Australian coast, based on recent observations (WOCE ICM6, 1994/96) and numerical output from the 1/6 degree Parallel Ocean Program model (POP11B 1993/97). Particularly, we identify the source regions of the Leeuwin Current, quantify its mean and seasonal variability in terms of volume, heat and salt transports, and examine its heat balance (cooling mechanism). This also leads to further understanding of the regional circulation associated with the Leeuwin Undercurrent, the Eastern Gyral Current and the southeast Indian Subtropical Gyre. The tropical and subtropical sources of the Leeuwin Current are understood from an online numerical particle tracking. Some of the new findings are the Tropical Indian Ocean source of the Leeuwin Current (in addition to the Indonesian Throughflow/Pacific); the Eastern Gyral Current as a recirculation of the South Equatorial Current; the subtropical source of the Leeuwin Current fed by relatively narrow subsurface-intensified eastward jets in the Subtropical Gyre, which are also a major source for the Subtropical Water (salinity maximum) as observed in the Leeuwin Undercurrent along the ICM6 section at 22 degrees S. The ICM6 current meter array reveals a rich vertical current structure near North West Cape (22 degrees S). The coastal part of the Leeuwin Current has dominant synoptic variability and occasionally contains large spikes in its transport time series arising from the passage of tropical cyclones. On the mean, it is weaker and shallower compared to further downstream, and it only transports Tropical Water, of a variable content. The Leeuwin Undercurrent carries Subtropical Water, South Indian Central Water and Antarctic Intermediate Water equatorward between 150/250 to 500/750 m. There is a poleward flow just below the undercurrent which advects a mixed Intermediate Water, partially associated with outflows from the Red Sea and Persian Gulf. Narrow bottom-intensified currents are also observed. The 5-year mean model Leeuwin Current is a year-round poleward flow between 22 degrees S and 34 degrees S. It progressively deepens, from 150 to 300 m depth. Latitudinal variations in its volume transport are a response to lateral inflows/outflows. It has double the transport at 34 degrees S (-2.2 Sv) compared to at 22 degrees S (-1.2 Sv). These model estimates, however, may underestimate the transport of the Leeuwin Current by 50%. Along its path, the current becomes cooler (6 degrees C), saltier (0.6 psu) and denser (2 kg m -3). At seasonal scales, a stronger poleward flow in May-June advects the warmest and freshest waters along the west Australian coast. This advection is apparently spun up by the arrival of a poleward Kelvin wave in April, and reinforced by a minimum in the equatorward wind stress during July. In the model heat balance, the Leeuwin Current is significantly cooled by the eddy heat flux divergence (4 degrees C out of 6 degrees C), associated with mechanisms operating at submonthly time scales. However, exactly which mechanisms it is not yet clear. Air-sea fluxes only account for ~30% of the cooling and seasonal rectification is negligible. The eddy heat divergence, originating over a narrow region along the outer edge of the Leeuwin Current, is responsible for a considerable warming of a vast area of the adjacent ocean interior, which is then associated with strong heat losses to the atmosphere. The model westward eddy heat flux estimates are considerably larger than those associated with long lived warm core eddies detaching from the Leeuwin Current and moving offshore. This suggests that these mesoscale features are not the main mechanism responsible for the cooling of the Leeuwin Current. We suspect instead that short lived warm core eddies might play an important role.

Both physical circulation and biogeochemical characteristics are unique in the Southern Ocean (SO) region, and are fundamentally different from those of the northern hemisphere. Moreover, according to previous research, the oceanic response to the trend of the Southern Annual Mode (SAM) has profound impacts on the future oceanic uptake of carbon dioxide in the SO. In other words, the climate and circulation of the SO are strongly coupled to the overlying atmospheric variability. However, while we have understanding on the SO physical circulation and have the ability to predict the future changes of the SO climate and physical processes, the link between the SO physical processes, the air-sea carbon flux, and correlated climate variability remains unknown. Even though scientists have been studying the spatial and temporal variability of the SO carbon flux and the associated biogeochemical processes, the spatial patterns and the magnitudes of the air-sea carbon flux do not agree between models and observations. Therefore, in this study, we utilized a modified version of a general circulation model (GCM) to performed realistic simulations of the SO carbon on seasonal to interannual timescales, and focused on the crucial physical and biogeochemical processes that control the carbon flux. The spatial pattern and the seasonal cycle of the air-sea carbon dioxide flux is calculated, and is broadly consistent with the climatological observations. The variability of air-sea carbon flux is mainly controlled by the gas exchange rate and the partial pressure of carbon dioxide, which is in turn controlled by the compensating changes in temperature and dissolved inorganic carbon. We investigated the seasonal variability of dissolved inorganic carbon based on different regional processes. Furthermore, we also investigated the dynamical adjustment of the surface carbon flux in response to the different gas exchange parameterizations, and conclude that parameterization has little impact on spatially integrated carbon flux. Our simulation well captured the SO carbon cycle variability on seasonal to interannual timescales, and we will improve our model by employ a better scheme of nutrient cycle, and consider more nutrients as well as ecological processes in our future study.

Seventeen Earth system models (ESMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were evaluated, focusing on the seasonal sensitivities of net biome production (NBP), net primary production (NPP), and heterotrophic respiration (Rh) to interannual variations in temperature and precipitation during 1982-2005 and their changes over the twenty-first century. Temperature sensitivity of NPP in ESMs was generally consistent across northern high-latitude biomes but significantly more negative for tropical and subtropical biomes relative to satellite-derived estimates. The temperature sensitivity of NBP in both inversion-based and ESM estimates was generally consistent in March-May (MAM) and September-November (SON) for tropical forests, semiarid ecosystems, and boreal forests. By contrast, for inversion-based NBP estimates, temperature sensitivity of NBP was nonsignificant for June-August (JJA) for all biomes except boreal forest; whereas, for ESM NBP estimates, the temperature sensitivity for JJA was significantly negative for all biomes except shrublands and subarctic ecosystems. Both satellite-derivedNPP and inversion-based NBP are often decoupled from precipitation, whereas ESM NPP and NBP estimates are generally positively correlated with precipitation, suggesting that ESMs are oversensitive to precipitation. Over the twenty-first century, changes in temperature sensitivities of NPP, Rh, and NBP are consistent across all RCPs but stronger under more intensive scenarios. The temperature sensitivity of NBP was found to decrease in tropics and subtropics and increase in northern high latitudes in MAM due to an increased temperature sensitivity of NPP. Across all biomes, projected temperature sensitivity of NPP decreased in JJA and SON. Projected precipitation sensitivity of NBP did not change across biomes, except over grasslands in MAM.

Land ecosystems absorb about a quarter of all human emissions of carbon (C) by fossil fuel burning and land use change. This percentage varies greatly within years due to the land ecosystem response to climate variability and disturbance. Significant uncertainties remain in our knowledge of the magnitude and spatio-temporal changes in the land C sinks. The aims of my thesis are 1) to evaluate the capacity of different dynamic global vegetation models (DGVMs) to reproduce the fluxes and stocks of the land C cycle and 2) to analyse the drivers of change in the land C over the last two decades (1990-2009). In the first part of this thesis I evaluated the DGVM results over two regions: the Northern Hemisphere (NH) and the Tropics. Over the NH DGVMs tend to simulate longer growing seasons and a greater positive leaf area index trend in response to warming than that observed from satellite data. For the tropical region we found a high spatial correlation between the DGVMs and the observations for C stocks and fluxes, but the models produced higher C stocks over the non-forested areas. In the second part I studied the processes controlling the regional land C cycle. The findings can be summarized as: (1) the land CO2 sink has increased over the study period, through increases in tropical and southern regions with negligible change in northern regions; (2) globally and in most regions, the land sinks are not increasing as fast as the growth rate of excess atmospheric CO2 and (3) changes in water availability, particularly over the dry season, played a fundamental role in determining regional trends in NPP. My work seeks to improve our understanding of the relationship between the C cycle and its drivers, however considerable research is needed to understand the role of additional processes such as land use change, nitrogen deposition, to mention just a few.

Thesis (M.S.)--University of Wisconsin--Madison, 1987.
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Lifeline for about one-sixth of the world’s population in the subcontinent, the Indian summer monsoon (ISM) is an integral part of the annual cycle of the winds (reversal of winds with seasons), coupled with a strong annual cycle of precipitation (wet summer and dry winter). For over a century, high socioeconomic impacts of ISM rainfall (ISMR) in the region have driven scientists to attempt to predict the year-to-year variations of ISM rainfall. A remarkably stable phenomenon, making its appearance every year without fail, the ISM climate exhibits a rather small year-to-year variation (the standard deviation of the seasonal mean being 10% of the long-term mean), but it has proven to be an extremely challenging system to predict. Even the most skillful, sophisticated models are barely useful with skill significantly below the potential limit on predictability. Understanding what drives the mean ISM climate and its variability on different timescales is, therefore, critical to advancing skills in predicting the monsoon. A conceptual ISM model helps explain what maintains not only the mean ISM but also its variability on interannual and longer timescales.The annual ISM precipitation cycle can be described as a manifestation of the seasonal migration of the intertropical convergence zone (ITCZ) or the zonally oriented cloud (rain) band characterized by a sudden “onset.” The other important feature of ISM is the deep overturning meridional (regional Hadley circulation) that is associated with it, driven primarily by the latent heat release associated with the ISM (ITCZ) precipitation. The dynamics of the monsoon climate, therefore, is an extension of the dynamics of the ITCZ. The classical land–sea surface temperature gradient model of ISM may explain the seasonal reversal of the surface winds, but it fails to explain the onset and the deep vertical structure of the ISM circulation. While the surface temperature over land cools after the onset, reversing the north–south surface temperature gradient and making it inadequate to sustain the monsoon after onset, it is the tropospheric temperature gradient that becomes positive at the time of onset and remains strongly positive thereafter, maintaining the monsoon. The change in sign of the tropospheric temperature (TT) gradient is dynamically responsible for a symmetric instability, leading to the onset and subsequent northward progression of the ITCZ. The unified ISM model in terms of the TT gradient provides a platform to understand the drivers of ISM variability by identifying processes that affect TT in the north and the south and influence the gradient.The predictability of the seasonal mean ISM is limited by interactions of the annual cycle and higher frequency monsoon variability within the season. The monsoon intraseasonal oscillation (MISO) has a seminal role in influencing the seasonal mean and its interannual variability. While ISM climate on long timescales (e.g., multimillennium) largely follows the solar forcing, on shorter timescales the ISM variability is governed by the internal dynamics arising from ocean–atmosphere–land interactions, regional as well as remote, together with teleconnections with other climate modes. Also important is the role of anthropogenic forcing, such as the greenhouse gases and aerosols versus the natural multidecadal variability in the context of the recent six-decade long decreasing trend of ISM rainfall.

Discovered at the very end of the 20th century, the Indian Ocean Dipole (IOD) is a mode of natural climate variability that arises out of coupled ocean–atmosphere interaction in the Indian Ocean. It is associated with some of the largest changes of ocean–atmosphere state over the equatorial Indian Ocean on interannual time scales. IOD variability is prominent during the boreal summer and fall seasons, with its maximum intensity developing at the end of the boreal-fall season. Between the peaks of its negative and positive phases, IOD manifests a markedly zonal see-saw in anomalous sea surface temperature (SST) and rainfall—leading, in its positive phase, to a pronounced cooling of the eastern equatorial Indian Ocean, and a moderate warming of the western and central equatorial Indian Ocean; this is accompanied by deficit rainfall over the eastern Indian Ocean and surplus rainfall over the western Indian Ocean. Changes in midtropospheric heating accompanying the rainfall anomalies drive wind anomalies that anomalously lift the thermocline in the equatorial eastern Indian Ocean and anomalously deepen them in the central Indian Ocean. The thermocline anomalies further modulate coastal and open-ocean upwelling, thereby influencing biological productivity and fish catches across the Indian Ocean. The hydrometeorological anomalies that accompany IOD exacerbate forest fires in Indonesia and Australia and bring floods and infectious diseases to equatorial East Africa. The coupled ocean–atmosphere instability that is responsible for generating and sustaining IOD develops on a mean state that is strongly modulated by the seasonal cycle of the Austral-Asian monsoon; this setting gives the IOD its unique character and dynamics, including a strong phase-lock to the seasonal cycle. While IOD operates independently of the El Niño and Southern Oscillation (ENSO), the proximity between the Indian and Pacific Oceans, and the existence of oceanic and atmospheric pathways, facilitate mutual interactions between these tropical climate modes.

Wildland fires are a common global disturbance and many of these fires burn through mixtures of living and dead vegetation. Live fuels are unique because they regulate biomass and water content actively through processes such as photosynthesis or transpiration. The main goal of these processes is to maintain the growth and maintenance demands of the plants while minimising water loss. Historically, live fuel dynamics were assumed to be only driven by evaporative or drying processes and little attention was paid to the interplay between carbon and water dynamics. Here we present a mechanistic model of live fuel moisture (LFM) which is a critical component of live fuel flammability. The model decouples LFM into metrics that are easy to measure such as particle density, surface-area-to-volume ratio, leaf mass area and relative water content. Each metric serves as a proxy for important components of the seasonal water and carbon cycle or to capture inter-species variations in physical properties.We evaluate this model using field measurements of physical and chemical characteristics for a Douglas Fir (Pseudotsuga menziesii), a common intermountain US tree species that commonly burns in crown fires. This simple, mechanistic model was effective at characterising the seasonal variations in LFM across both new and old foliage as a simple function of foliar density and relative water content (r2=0.984,p < 0.05) . Finally, we show how this decoupled model can be used to more appropriately parameterize a 3-dimensional computational fluid dynamics based fire behaviour model to represent an appropriate live fuel moisture as the combined effects of biomass and moisture variations on canopy flammability.

This chapter describes a study designed to evaluate the spectrum of the residence time of the water at different depths of a deep lake, and to examine the mechanisms governing the seasonal cycle of thermal stratification and destratification, with the ultimate aim of assessing the actual exchange time of the lake water. The study was performed on Lake Maggiore (depth 370m) using a multidimensional mathematical model and computer codes for the heat and mass transfer in very large natural water bodies. A 3D Eulerian time-dependent CFD (Computational Fluid Dynamics) code was applied under real conditions, taking into account the effects of the monthly mean values of the mass flow rates and temperatures of all the tributaries, mass flow rate of the Ticino effluent and meteorological, hydrological, and limnological parameters available from the rich data-base of the CNR-ISE (Pallanza). The velocity distributions from these simulations were used to compute the paths of a large number of massless markers with different initial positions and evaluate their residence times in the lake.

Abstract This chapter analyses a version of simple models of competition for a single resource between two species with different seasonal variation in their resource capture rates. This scenario had been shown to promote coexistence in earlier studies. The chapter shows that, for different parameters, the ability of species to coexist often decreases with greater differences in their season resource uptake patterns. In addition, a given pair species often has alternative outcomes, which may be two different coexistence outcomes, two exclusion outcomes, or coexistence and exclusion. This is related to the fact that a single consumer may also have several alternative attractors, due to interaction of the inherent consumer–resource cycle and the seasonality in capture rate. Most of the models assume a single resource type with logistic growth, but the qualitative results can also be found in systems with abiotic resource growth and systems with multiple resources. Longer period lengths for the cycle in capture rates favours coexistence over exclusion outcomes, and coexistence of multiple species at long period lengths is possible. Coexistence of seasonal and aseasonal species on a single resource can occur, and the same mechanism operates in systems with type II functional responses. The results have several general messages about seasonal systems: (1) increasing similarity can make coexistence more or less likely; (2) invasion ability often does not imply persistence in cases with multiple attractors, which includes many seasonal systems; (3) differences in seasonal responses often produce qualitatively different outcomes than do other types of resource segregation.

<em>Abstract.</em>—Size-selective mortality is a dominant variable regulating the dynamics of salmon populations. Body size, growth rate, and energy state during one life stage influence survival during that and subsequent life stages. Therefore, simultaneously examining allometric processes, foraging, and thermal constraints on growth within and among life stages can provide a powerful analytical framework for identifying critical periods and sizes during the life cycle of salmon, and for understanding the processes that contribute to the specific ecological bottlenecks confronting different species or stocks of salmon. A bioenergetics model was used to simulate generalized growth responses to a factorial combination of body size, daily feeding rate, and prey energy density over a continuous range of temperatures (0–24oC). The results of these simulations indicated that: 1) smaller salmon benefit from higher potential scope for growth or activity than larger salmon, based on the different allometric relationships for maximum consumption, metabolism, and waste; 2) optimal temperatures for growth decline with increasing body size; 3) optimal temperatures for growth also decline as daily rations decline; 4) thermal tolerances (temperature thresholds beyond which weight loss will occur) also shift to cooler temperatures for larger salmon and when ration sizes decline; 5) increasing the composite energy density of the diet can increase both optimal growth temperature, and thermal tolerance, especially at larger body sizes; 6) after spawners enter freshwater, the amount of energy and days available to migrate, and successfully spawn at a given upstream location was very sensitive to ambient river temperature, and the swimming speed required to reach the spawning grounds. When placed in the context of climate variability, seasonal shifts in temperature, and food availability, these simulations suggest that growth will be more frequently limited by feeding rate (prey availability) and prey quality than by temperature, especially for smaller, younger life stages. Larger salmon should be more sensitive to temperature change, but reductions in optimal growth temperature and thermal tolerance would be magnified for all life stages, if either feeding rate or prey quality were to be reduced. Given intense size-selective mortality during one or more early life stages, this simulation framework could be adopted to identify the key factors limiting growth to critical sizes during critical periods in the life cycle of specific salmon stocks.

Wildfire activity in recent years not only have large total area burned but also large, single-day fire spread events that pose challenges to ecological systems and human communities. Our objective was to better understand the relationships between extreme single-day fire spread events, annual area burned, and fire-season climate, and predict changes under future warming. We employ a satellite-derived dataset of daily fire spread events in the western USA and gridded climate data over this region to assess relationships between extreme single-day fire spread events, annual area burned, and fire-season maximum temperature, climate moisture deficit, and vapor pressure deficit over a time period of 2002-2020. We then develop models to predict fire activity under a 2°C warming scenario. Extreme single-day fire spread events >1100 ha (the top 16%) accounted for 70% of the cumulative area burned over the period of analysis. Annual area burned was correlated with number and mean size of spread events, and those largest of these large fire spread events. In 2020, wildfires burned over 4 million ha in the US and we identified 441 extreme events in 2020 alone that together burned 2.2 million ha across our study area. In contrast, the average extreme events between 2002 and 2019 was 168 per year that burned 0.5 million ha. Fire season climate variables correlate strongly with the annual number of extreme events and area burned. Our models predict that the annual number of extreme fire spread events more than doubles under a 2°C warming scenario, with an attendant doubling in area burned. Exceptional fire seasons like 2020 will likely be more common, and wildfire activity under future extremes will likely exceed anything witnessed yet. Safeguarding human communities and supporting resilient ecosystems may require new lines of scientific inquiry, novel land management approaches, and accelerated climate mitigation efforts.

In seasonal frozen soil area, the engineering problems caused by the excessive moisture content of the subgrade soil are widespread. In view of this phenomenon, author proposes to employ a new type of research and development of the seepage drainage geogrid (SDG) to cool and drain the soil. Through indoor model test, after two freeze-thaw cycles, the experimental comparison of the size and laying method of various SDG was carried out. The test result shows that the model with a natural grit layer has the most drainage effect. While, the model contains two layers of interconnected grilles has the best cooling effect. The indoor model test is simulated by accurate numerical simulation. The simulation results are compared with the indoor test results. The fitting results of the two results are very high, which provides theoretical support and data guarantee for the application of seepage drainage grille to strengthen the roadbed in the cold road.

Gainesville Regional Utilities (GRU) is a fully vertically-integrated utility with electric power generation, transmission, and distribution system owned by the City of Gainesville, FL. We have two primary generating plant sites: Deerhaven with two conventional coal-fired steam units (DH1 and DH2) and John R. Kelly (JCC1) combined-cycle Unit 1. Kelly Station (the focus of this study) is located in southeast Gainesville near the downtown business district. It has one - 120 MW combined-cycle unit (JCC1) in 1 × 1 configuration, consisting of: one GE Frame 7E combustion turbine (dual fuel), one Applied Thermal Systems two pressure HRSG, one 50-year old Westinghouse steam turbine unit with cooling tower, fuel storage, pumping equipment, transmission, and distribution equipment. In 2013, GRU with a seasonal peak load of approximately 500 MWs was to start receiving the output of a new 100 MW bio-fuel plant under a purchase power agreement. It was apparent that the operation of the GRU units would drastically change. It was predicted by GRU that DH2 a 255 MW coal unit would move to a cycling duty unit and the Kelly combined-cycle unit would be relegated to “peaking” operation. To better understand and predict future operational impacts, GRU contracted with Intertek AIM (APTECH) to conduct a Cost of Cycling study. This paper is our presentation of the results of the study and the changes that were indicated by the cycling analysis to manage the GRU system at the lowest cost and to incorporate the new modes of cycling operation. The expected modes of operation based on the results of the study were reversed to use the lowest cost unit for frequent cycling of JCC1 and changed the previously base loaded coal unit DH2 into a seasonal unit with long seasonal shut downs. This paper further shows the actions implemented by GRU at Kelly station to improve the cycling response and reduce the damage impact of each cycle by managing the startup ramp rates of the limiting equipment. The plant had limited budget for capital improvements and focused principally on managing the cost by modifying the startup procedures using real time operating data. Our conclusion was that by following the report recommendations, a new “Start Model” produced repeatable and acceptable results that minimized possible damage to the unit while meeting the need to use the renewable energy and support the customer by providing power at the lowest cost. The paper will demonstrate the improvement areas, the actual changes, and the results of those changes to the cycling data and the savings due to reduced damage.

Rankine cycle power plants efficiency varies across the seasons due to changes in ambient air and cooling water temperatures. The size of this variation is influenced by the unit design. Test data collected on units to develop economic dispatch (input output) models produces an “as found” result. This result includes current imposed season influence and mechanical condition of the unit. With additional steps, these models can be adjusted to account for and quantify the seasonal efficiency changes. This paper will review the various methods used to account for these changes and evaluate the pros and cons of each method.

A new perspective of dynamic LCA (life cycle assessment) is proposed with the predictive usage mining for sustainability (PUMS) algorithm. By defining usage patterns as trend, seasonality, and level from a time series of usage information, predictive LCA can be conducted in a real time horizon. Large-scale sensor data of product operation is analyzed in order to mine usage patterns and build a usage model for LCA. The PUMS algorithm consists of handling missing and abnormal values, seasonal period analysis, segmentation analysis, time series analysis, and predictive LCA. A newly developed segmentation algorithm can distinguish low activity periods and help to capture patterns more clearly. Furthermore, a predictive LCA method is formulated using a time series usage model. Finally, generated data is used to do predictive LCA of agricultural machinery as a case study.

A Photovoltaic (PV) module consists of layers of different materials constrained together through an encapsulant polymer. During operation, it experiences mechanical and thermal loads due to seasonal and temperature variations, which cause breakage of interconnects owing to fatigue and laminate warpage. This is due to the fact that there is a coefficient of thermal expansion (CTE) mismatch because of the presence of unlike materials within the laminate. Therefore, thermo-mechanical stresses are induced in the module. Glass, being the thickest of all in the module, plays a significant role in the stressing of components. The lifetime of today’s PV module is expected to be 25 years and this period corresponds to the guarantee of the manufacturer. Its high reliability will help it to reach grid parity. But the problem is that it is not convenient to wait and assess its durability. Qualification standards such as ASTM E1171-09 are useful in predicting a module’s failure. In this work, material of each component of the PV module is characterized and then the implementation of material models is discussed. A Finite-Element (FE) model of 36 cell PV module is developed using 2D layered shell elements in ANSYS. A single temperature cycle of ASTM E1171-09 is simulated after lamination procedure and 24 hour storage at constant temperature. The FE model is validated by simulating an experimental procedure in the literature by determining change of cell gap during the temperature cycle. Finally, parametric studies are performed with respect to lamination thickness.

Abstract Excess gas produced in reservoirs has traditionally been flared into the atmosphere as it is a byproduct of oil and gas recovery operations. Large volumes of gas are still flared in areas where there is a lack of infrastructure to collect and transport the gas. Gas injection into reservoirs has been shown to increase hydrocarbon production and is a method of Enhanced Oil Recovery (EOR). The proposed method for EOR would be to capture the gas that would otherwise be flared and re-inject it into the reservoir. This would further reduce overall gas flaring and increase production simultaneously. Re-injections sites are carefully chosen to ensure the gas injection yields the best production and is also economically viable. As the world increases the amount of variable renewable energy sources, solutions developed in the traditional energy industry can provide stability to the power grid and reduce the prices for consumers. In Texas, there is a large contribution to total energy production coming from both wind and solar, which have both daily and seasonal variability. A secondary objective is utilizing the potentially flared gas to generate electricity during the high-demand months of summer and winter. Since one of the main reasons for flaring gas is the lack of infrastructure to transport the gas, the ability to use the gas to generate electricity on-site has the potential to be an invaluable asset. Generators are built and connected to the already-in-place electrical grid, bypassing the need to build new pipelines to transport the gas. This solution provides for seasonal storage for associated gas and enhanced oil recovery at the same time. A model of an unconventional reservoir found in West Texas was built to study the feasibility of this project. Using reservoir simulation software, a single horizontal well with 50 fractures along the horizontal was placed in the reservoir model. The model has a porosity of 3.7% and a permeability of 7 nD in the horizontal direction and 0.7 nD in the vertical. The fractures have a half-length of 200 ft and a fracture zone permeability of 300 mD. The fluid properties and historical production were taken from a PVT report and production data provided. The model was then history-matched to get an accurate forecast. Three cases were tested with this model. The base case consisted of 30 years of normal depletion with no injection (Fig. 1) The second case consisted of cyclic injection for 30 years (Fig. 2). Fig. 3a and Fig. 3b show the reservoir pressure in relation to gas injection. In the third case, the injection after depletion consisted of 15 years of normal depletion and 15 years of cyclic injection. The injection cycle consisted of 3 months of production, 2 months of injection, and 1 month of soaking for both the second and third case. Naturally, this cycle would allow for excess electricity generation to meet the demand peaks in summer and winter. The base case produced a total of 205 MSTB, the second case produced 266 MSTB, and the third case produced 260 MSTB. The second case recovered the most oil with an average incremental of 12.9 barrels per 1 Mscf of gas injected.

Continuing efforts to increase the efficiency of utility-scale electricity generation has resulted in considerable interest in Brayton cycles operating with supercritical carbon dioxide (S-CO2). One of the advantages of S-CO2 Brayton cycles, compared to the more traditional steam Rankine cycle, is that equal or greater thermal efficiencies can be realized using significantly smaller turbomachinery. Another advantage is that heat rejection is not limited by the saturation temperature of the working fluid, facilitating dry cooling of the cycle (i.e., the use of ambient air as the sole heat rejection medium). While dry cooling is especially advantageous for power generation in arid climates, the reduction in water consumption at any location is of growing interest due to likely tighter environmental regulations being enacted in the future. Daily and seasonal weather variations coupled with electric load variations means the plant will operate away from its design point the majority of the year. Models capable of predicting the off-design and part-load performance of S-CO2 power cycles are necessary for evaluating cycle configurations and turbomachinery designs. This paper presents a flexible modeling methodology capable of predicting the steady state performance of various S-CO2 cycle configurations for both design and off-design ambient conditions, including part-load plant operation. The models assume supercritical CO2 as the working fluid for both a simple recuperated Brayton cycle and a more complex recompression Brayton cycle.

In the sugar mill in Tanegashima which is an isolated island in Japan, raw sugar production process produces raw sugar and bagasse simultaneously. Raw bagasse is not storable because of its perishability due to high moisture content. Actually, the bagasse boiler burns more bagasse than that is required for the sugar mill. Hence, the temperature of flue gas increases and a massive amount of unused heat at around 200 °C is exhausted during sugar mill operation period. On the other hand, many other factories in this island burn imported oil at package boilers to generate process steam up to 120 °C all year around. To resolve this spatial and seasonal mismatch, we employed thermochemical energy storage and transport system using zeolite steam adsorption and regeneration cycle. We introduced a basic design of heat release device which is called “Zeolite boiler”, that is a moving bed with indirect heat exchanger. Adsorbed steam is assumed to be generated by a package boiler. A small zeolite boiler with 20 kg/h of zeolite was designed by using a developed quasi-2D simulation code that numerically solves mass and heat conservation equations of the counter-flow reactor model. As the result of single injection from the top of chamber, the zeolite boiler could generate 4.95 kg/h of dry saturated steam at 0.2 MPa when 4.0 kg/h of steam was injected from the package boiler. Multi injection process was considered to improve the heat recovery rate. By injecting 3.0 kg/h and 1.0 kg/h of steam separately from the top and the middle of the chamber, 5.9 kg/h of steam was generated and heat recovery rate was increased by 13 points.

Numerous socio-economic activities depend on the seasonal rainfall and groundwater recharge cycle across the Central American Isthmus. Population growth and unregulated land use changes resulted in extensive surface water pollution and a large dependency on groundwater resources. This chapter uses stable isotope variations in rainfall, surface water, and groundwater of Costa Rica, Nicaragua, El Salvador, and Honduras to develop a regionalized rainfall isoscape, isotopic lapse rates, spatial-temporal isotopic variations, and air mass back trajectories determining potential mean recharge elevations, moisture circulation patterns, and surface water-groundwater interactions. Intra-seasonal rainfall modes resulted in two isotopically depleted incursions (W-shaped isotopic pattern) during the wet season and two enriched pulses during the Mid-Summer Drought and the months of the strongest trade winds. Notable isotopic sub-cloud fractionation and near-surface secondary evaporation were identified as common denominators within the Central American Dry Corridor. Groundwater and surface water isotope ratios depicted the strong orographic separation into the Caribbean and Pacific domains, mainly induced by the governing moisture transport from the Caribbean Sea, complex rainfall producing systems across the N-S mountain range, and the subsequent mixing with local evapotranspiration, and, to a lesser degree, the eastern Pacific Ocean fluxes. Groundwater recharge was characterized by a) depleted recharge in highland areas (72.3%), b) rapid recharge via preferential flow paths (13.1%), and enriched recharge due to near-surface secondary fractionation (14.6%). Median recharge elevation ranged from 1,104 to 1,979 m a.s.l. These results are intended to enhance forest conservation practices, inform water protection regulations, and facilitate water security and sustainability planning in the Central American Isthmus.

Organic Rankine cycles (ORC) are efficient technologies for waste heat recovery (WHR) at low to mid temperatures. For the design of ORC power cycles, several thermodynamic parameters should be considered. A challenge related to small scale (<50 kW) ORC cycles is to define the optimal process given frequent variability in a heat source. Many relevant applications require robust ORC systems to perform under varying heat source loads. This is an area where the body of knowledge must be further developed.In this work, the design of small-scale ORC cycles with varying heat source conditions is addressed by means of system modelling, simulation, and optimization. A framework is presented that consists of multi-scale optimization for the design of small-scale ORC systems considering seasonal and hourly heat source variations. The framework is developed as a flexible tool allowing to include fit-for-purpose models of key elements of the cycle, such as expander and heat exchanger, to suitably simulate off-design performance.The optimization framework has been tested on a case study representing a woodchips-fired micro-cogeneration unit via ORC. The case study is representative of an existing unit operating at the Czech Technical University (CTU) in Prague. The results indicate that the tool delivers an ORC design that has a 5 % larger accumulated power production with the hourly variation of the heat source during one year than the original ORC solely optimized at the design heat source condition. The optimal ORC system also shows a 33 % smaller nominal capacity and size of heat exchangers than the ORC at the reference design, indicating a potential reduction in the capital cost.

Abstract The heating seasonal performance factor (HSPF) of an air-source heat pump is degraded by the defrost cycle. Electric resistance heat was added to the refrigerant through the use of a 750-watt immersion heater inserted at the base of the suction-line accumulator and by heating the accumulator shell via a 900-watt electric band heater attached to the outside of the accumulator. The electric resistance heat and its hot metal surface was used as an active enhancement technique to increase the rate of refrigerant boiling during the initial few minutes of the reverse-cycle defrost. The unit was fully instrumented and equipped with two possible expansion devices: a short-tube orifice and a thermal expansion valve (TXV), for cooling / defrost mode operation and a TXV for the heating mode. Tests were run in psychrometric rooms that maintained outdoor conditions at 1.7°C dry bulb and 80% relative humidity and indoor conditions at 21.1°C dry bulb. Overall performance characteristics of particular interest were integrated COP, cycle time, defrost cycle time, along with other instantaneous comparisons of power, refrigerant flow rate, temperatures and pressures. Tests with a 1.8 mm diameter orifice defrost mode expansion device and the immersion heater enhancement showed the best system improvement. This test had a 3.1% increase in integrated cyclic COP and a 11% reduction of the defrost cycle time. The reduced cycle time came primarily as a result of a 1.0 minute reduction (31%) of the outdoor coil post-melt (draining) time.

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.

In soil solarization, moist soil is covered with a transparent plastic film, resulting in passive solar heating which inactivates soil-borne pathogen/weed propagules. Although solarization is an effective alternative to soil fumigation and chemical pesticide application, it is not widely used due to its long duration, which coincides with the growing season of some crops, thereby causing a loss of income. The basis of this project was that solarization of amended soil would be utilized more widely if growers could adopt the practice without losing production. In this research we examined three factors expected to contribute to greater utilization of solarization: 1) investigation of techniques that increase soil temperature, thereby reducing the time required for solarization; 2) development and validation of predictive soil heating models to enable informed decisions regarding soil and solarization management that accommodate the crop production cycle, and 3) elucidation of the contributions of microbial activity and microbial community structure to soil heating during solarization. Laboratory studies and a field trial were performed to determine heat generation in soil amended with compost during solarization. Respiration was measured in amended soil samples prior to and following solarization as a function of soil depth. Additionally, phytotoxicity was estimated through measurement of germination and early growth of lettuce seedlings in greenhouse assays, and samples were subjected to 16S ribosomal RNA gene sequencing to characterize microbial communities. Amendment of soil with 10% (g/g) compost containing 16.9 mg CO2/g dry weight organic carbon resulted in soil temperatures that were 2oC to 4oC higher than soil alone. Approximately 85% of total organic carbon within the amended soil was exhausted during 22 days of solarization. There was no significant difference in residual respiration with soil depth down to 17.4 cm. Although freshly amended soil proved highly inhibitory to lettuce seed germination and seedling growth, phytotoxicity was not detected in solarized amended soil after 22 days of field solarization. The sequencing data obtained from field samples revealed similar microbial species richness and evenness in both solarized amended and non-amended soil. However, amendment led to enrichment of a community different from that of non-amended soil after solarization. Moreover, community structure varied by soil depth in solarized soil. Coupled with temperature data from soil during solarization, community data highlighted how thermal gradients in soil influence community structure and indicated microorganisms that may contribute to increased soil heating during solarization. Reliable predictive tools are necessary to characterize the solarization process and to minimize the opportunity cost incurred by farmers due to growing season abbreviation, however, current models do not accurately predict temperatures for soils with internal heat generation associated with the microbial breakdown of the soil amendment. To address the need for a more robust model, a first-order source term was developed to model the internal heat source during amended soil solarization. This source term was then incorporated into an existing “soil only” model and validated against data collected from amended soil field trials. The expanded model outperformed both the existing stable-soil model and a constant source term model, predicting daily peak temperatures to within 0.1°C during the critical first week of solarization. Overall the results suggest that amendment of soil with compost prior to solarization may be of value in agricultural soil disinfestations operations, however additional work is needed to determine the effects of soil type and organic matter source on efficacy. Furthermore, models can be developed to predict soil temperature during solarization, however, additional work is needed to couple heat transfer models with pathogen and weed inactivation models to better estimate solarization duration necessary for disinfestation.

Annual plants have developed a range of different mechanisms to avoid flowering (exposure of reproductive organs to the environment) under adverse environmental conditions. Seasonal environmental events such as gradual changes in day length and temperature affect the timing of transition to flowering in many annual and perennial plants. Research in Arabidopsis and additional species suggest that some environmental signals converge on transcriptional regulation of common floral integrators such as FLOWERING LOCUS T (FT). Here we studied environmental induction of flowering in the model legume Medicago truncatula. Similarly to Arabidopsis, the transition to flowering in M. truncatula is hastened by long photoperiods and long periods of vernalization (4°C for 2-3 weeks). Ecotypes collected in Israel retain a vernalization response even though winter temperatures are way above 4°C. Here we show that this species is also highly responsive (flowers earlier) to mild ambient temperatures up to 19°C simulating winter conditions in its natural habitat. Physiological experiments allowed us to time the transition to flowering due to low temperatures, and to compare it to vernalization. We have made use of natural variation, and induced mutants to identify key genes involved in this process, and we provide here data suggesting that an FT gene in M.truncatula is transcriptionally regulated by different environmental cues. Flowering time was found to be correlated with MtFTA and MtFTB expression levels. Mutation in the MtFTA gene showed a late flowering phenotype, while over-expressing MtFTA in Arabidopsis complemented the ft- phenotype. We found that combination of 4°C and 12°C resulted in a synergistic increase in MtFTB expression, while combining 4°C and long photoperiods caused a synergistic increase in MtFTA expression. These results suggest that the two vernalization temperatures work through distinct mechanisms. The early flowering kalil mutant expressed higher levels of MtFTA and not MtFTB suggesting that the KALIL protein represses MtFTA specifically. The desert ecotype Sde Boker flowers earlier in response to short treatments of 8-12oc vernalization and expresses higher levels of MtFTA. This suggests a possible mechanism this desert ecotype developed to flower as fast as possible and finish its growth cycle before the dry period. MtFTA and FT expression are induced by common environmental cues in each species, and expression is repressed under short days. Replacing FT with the MtFTA gene (including regulatory elements) caused high MtFTA expression and early flowering under short days suggesting that the mechanism used to repress flowering under short days has diversified between the two species.The circadian regulated gene, GIGANTEA (GI) encodes a unique protein in Arabidopsis that is involved in flowering mechanism. In this research we characterized how the expression of the M.truncatula GI ortholog is regulated by light and temperature in comparison to its regulation in Arabidopsis. In Arabidopsis GI was found to be involved in temperature compensation to the clock. In addition, GI was found to be involved in mediating the effect of temperature on flowering time. We tested the influence of cold temperature on the MtGI gene in M.truncatula and found correlation between MtGI levels and extended periods of 12°C treatment. MtGI elevation that was found mostly after plants were removed from the cold influence preceded the induction of MtFT expression. This data suggests that MtGI might be involved in 12°C cold perception with respect to flowering in M.truncatula. GI seems to integrate diverse environmental inputs and translates them to the proper physiological and developmental outputs, acting through several different pathways. These research enabled to correlate between temperature and circadian clock in M.truncatula and achieved a better understanding of the flowering mechanism of this species.

There is a need for more and higher quality data on pedestrian demand patterns for a number of applications in planning, transportation engineering, public health, and other areas. It is particularly desirable to better characterize the influence of daily, weekly, and annual variations; the impact of weather and special events; and the effects of changes in pedestrian phasing. This paper proposes and demonstrates a methodology for quantifying the relative demand for pedestrian service at a signalized intersection by using the percent of signal cycles per hour in which the pedestrian phase was actuated. Although this performance measure does not by itself provide a pedestrian count, it can be used as a surrogate to characterize how pedestrian volumes vary due to operating conditions. More importantly, since this technique does not require new sensors, the data can be collected at thousands of intersections across the nation where pedestrian push buttons are in use. This paper documents findings from over a year of data collection at a signalized intersection on a college campus. The effects of daily/weekly/annual variations, special events, weather (temperature and precipitation), seasonal changes in activity patterns, and changes in pedestrian signal phasing are documented. A Tobit model is used to account for the influences of these variables and understand how they co-influence pedestrian activity. The implementation of an exclusive pedestrian phase is associated with a 9% increase in pedestrian phase utilization at the intersection. This change is associated with a decrease in user cost relative to performing midblock crossings. The modeled impact of snowfall events adds further insight by showing that as the user cost of making midblock crossings increases, pedestrian activity at the intersection increases.