Le phytoplancton joue un rôle important dans le cycle océanique du carbone. Les capteurs spatiaux de « couleur de l'océan » permettent, depuis plus de vingt ans, un suivi quasi-quotidien de la concentration en phytoplancton dans les eaux de surface du globe. Ces données sont utilisées pour quantifier la « pompe biologique marine » de carbone. Cependant, l'efficacité de cette « pompe biologique » varie fortement en fonction du groupe de phytoplancton présent dans les eaux de surface. Distinguer les principaux groupes depuis l'espace était donc un enjeu majeur des études de la couleur de l'océan au début de ma thèse.<br />Durant ma thèse, j'ai utilisé une approche empirique visant à mettre en évidence des relations entre les mesures spectrales effectuées par le capteur spatial SeaWiFS et la présence de groupes dominants de phytoplancton identifiés à l'aide d'inventaires pigmentaires collectés lors des campagnes GeP&CO (10/1999 - 07/2002) entre la France et la Nouvelle-Calédonie. J'ai montré que quatre grands groupes de phytoplancton peuvent être identifiés de façon fiable (Haptophytes, Prochlorococcus, Cyanobacterie et Diatomées) et que trois groupes supplémentaires sont probablement détectables (Trichodesmiums, Phaeocystis, Coccolithophoridés). J'ai appliqué cette classification, appelée PHYSAT, à l'ensemble des données journalières du capteur SeaWIFS de 1997 à 2004. Les résultats obtenus apportent, pour la première fois, une information sur la distribution spatio-temporelle des principaux groupes de phytoplancton à l'échelle du globe.

Thesis (Ph.D.)--University of Delaware, 2009. / Principal faculty advisor: Daniel J. Leathers, Dept. of Geography. Includes bibliographical references.

Thesis (doctoral)--Universidad de Zaragoza, 1982. / Includes bibliographical references (p. 247-249).

Models of tephra fallout are used to assess volcanic hazards in advance of eruptions and in near-real-time. Current models often approximate the wind field using simplistic assumptions of the atmosphere that cannot account for typical variations in wind velocity that occur in time and three-dimensional space. Here, a widely used mesoscale atmospheric model is used to improve forecasts of the location of the major axis of dispersion for erupting plumes. The Pennsylvania State University-National Center for Atmospheric Research fifth-generation Mesoscale Model (MM5) specializes in atmospheric prediction for regions on the order of ten to hundreds of kilometers on a side. MM5 generates realistic wind fields based on the laws of conservation of mass, energy, and momentum, along with land surface data and atmospheric forecasts and observations.

Coral-based climate reconstructions typically have not used multiple cores from a region to capture and replicate a climate signal largely because of concerns focused on coral conservation, analytical expense, and time constraints. Coral Sr/Ca reproducibility through the 20th century was investigated using three intra-colony and three inter-colony coral records, from the reefs offshore of Amédée Island, New Caledonia. Different sampling resolutions were examined in coral Sr/Ca (fortnightly and monthly) and delta 18O (fortnightly, monthly, and seasonally) as well as similar scale subsampling of the daily in situ SST record. The mean coral Sr/Ca, delta 18O, and daily SST values do not change as a function of sampling resolution. The coral Sr/Ca signal is highly reproducible; the average absolute offset between coeval Sr/Ca determinations between any two coral Sr/Ca time series is 0.036 mmol/mol (approximately 0.65°C), which is less than twice the analytical precision of the coral Sr/Ca measurements. The stack average of the monthly coral Sr/Ca variations and monthly anomalies are significantly correlated with monthly in situ SST (r equals -0.95, -0.56, respectively) for the period 1967 to 1992 and monthly 1-degree gridded SST data product (r equals -0.95, -0.53, respectively) for the period 1900 to 1999. The coral Sr/Ca-SST reconstruction exhibits decadal-scale fluctuations that exceed those observed in the gridded SST time series, which may reflect true differences between the SST at a shallow reef site and those averaged over a 1-degree grid box or they may reflect inadequacies in the methodology used to create the gridded SST product when few observations are available. A warming trend of approximately 0.6°C is observed in the coral Sr/Ca-SST record. Monthly coral Sr/Ca records and seasonally resolved coral delta 18O record from this site share variance in the latter half of the 20th century, but not in the early 20th century, suggestive of a change in seawater delta 18O.

This dissertation examines the role of climate science in ensuring environmental stability. It traces the career of the climatologist Charles Warren Thornthwaite, beginning with his work as a population geographer for the Social Science Research Council in the early 1930s and ending in the early 1960s with his work as an independent consultant for the military, agribusiness firms, and international organizations. I argue that Thornthwaite's approach to environmental stability began as an effort to create "holistic" stability, one characterized by a relative continuity of the relationships of people to the land they inhabited, and evolved into approach that favored "mechanistic" stability, one characterized by the interaction and exchange discrete environmental factors--energy, water, crops, etc. / History of Science

No description available.

Atmospheric rivers (ARs) are important contributors to cool season precipitation in the Southwestern US, and in some cases can lead to extreme hydrometeorological events in the region. We performed a climatological analysis and identified two predominant types of ARs that affect the central mountainous region in Arizona: Type 1 ARs originate in the tropics near Hawaii (central Pacific) and enhance their moisture in the midlatitudes, with maximum moisture transport over the ocean at low-levels of the troposphere. On the other hand, moisture in Type 2 ARs has a more direct tropical origin and meridional orientation with maximum moisture transfer at mid-levels. We then analyze future projections of Southwest ARs in a suite of global and regional climate models used in the North American Regional Climate Change Assessment Program (NARCCAP), to evaluate projected future changes in the frequency and intensity of ARs under warmer global climate conditions. We find a consistent and clear intensification of the water vapor transport associated with the ARs that impinge upon Arizona and adjacent regions, however, the response of AR-related precipitation intensity to increased moisture flux and column-integrated water vapor is weak and no robust variations are projected either by the global or the regional NARCCAP models. To evaluate the effect of horizontal resolution and improve our physical understanding of these results, we numerically simulated a historical AR event using the Weather Research and Forecasting (WRF) model at a 3-km resolution. We then performed a pseudo-global warming experiment by modifying the lateral and lower boundary conditions to reflect possible changes in future ARs (as projected by the ensemble of global model simulations used for NARCCAP). Interestingly we find that despite higher specific humidity, some regions still receive less rainfall in the warming climate experiments - partially due to changes in thermodynamics, but primarily due to AR dynamics. Therefore, we conclude from this analysis that overall future increase in atmospheric temperature and water content as projected by global climate models will not necessarily translate into generalized heavier AR-related precipitation in the Southwestern US.

Recent climate changes show that the historical record is not an appropriate analog for future climate conditions. This understanding calls into question management decisions that assume climate stationarity and consequently the demand for climate information has increased in order to help frame climate risk more accurately. However, deficits in knowledge about climate impacts and weak connections between existing information and resource managers are two barriers to effective incorporation of climate information in resource management, development, risk management, and other climate-sensitive decisions. In research presented here, I showcase results that address knowledge gaps in the impact of climate on glacial resources in Bolivia, South America. I present a mixing model analysis using isotopic and anion tracers to estimate that glacial meltwater contributed about 50% of the water to streams and reservoirs in La Paz region of Bolivia during the 2011 wet and 2012 dry seasons. To assess how future warming may impact water supplies, I develop a temperature-driven empirical model to estimated changes in a future glacial area. Surface temperature changes were extracted from a multi-model ensemble of global climate models produced for the latest Intergovernmental Panel on Climate Change (IPCC) fifth assessment report and for two greenhouse gas emission scenarios. In both scenarios, declines in glacial area are substantial. For many small glaciers, temperatures at the toe of each glacier rise above the glacier's maximum elevation by 2050 suggesting that water resources will be substantially impacted with continued warming. While these results address a knowledge gap, the extent to which they inform resource management is unknown because the research was conducted without an explicit connection to resource management. Information produced in this fashion is generally acknowledged as being less immediately useful for decision-making because of access and comprehension barriers. These challenges may be mollified, however, with information management strategies. Therefore, I present results from an experiment to see if translating and contextualizing existing climate-related information - information produced similarly to the glacier results highlighted above - help facilitate its use. During a drought afflicted period in Arizona and New Mexico, a monthly synthesis of climate impacts information was disseminated to more than 1400 people. Survey responses from 117 people who consulted the information indicated that the majority of them made at least one drought-related decision and the information in the synthesis at least moderately influenced the majority of those decisions. In addition, more than 90% of the survey respondents indicated that the synthesis improved their understanding of climate and drought; it also helped the majority of them better prepare for drought. The results demonstrate that routine interpretation and synthesis of existing climate information can help enhance access to and understanding of climate information.

The aim of the research undertaken in this dissertation was to use medium-range to seasonal precipitation forecasts for hydrologic applications for catchments in the core North American Monsoon (NAM) region. To this end, it was necessary to develop a better understanding of the physical and statistical relationships between runoff processes and the temporal statistics of rainfall. To achieve this goal, development of statistically downscaled estimates of warm season precipitation over the core region of the North American Monsoon Experiment (NAME) were developed. Currently, NAM precipitation is poorly predicted on local and regional scales by Global Circulation Models (GCMs). The downscaling technique used here, the K-Nearest Neighbor (KNN) model, combines information from retrospective GCM forecasts with simultaneous historical observations to infer statistical relationships between the low-resolution GCM fields and the locally-observed precipitation records. The stochastic nature of monsoon rainfall presents significant challenges for downscaling efforts and, therefore, necessitate a regionalization and an ensemble or probabilistic-based approach to quantitative precipitation forecasting. It was found that regionalization of the precipitation climatology prior to downscaling using KNN offered significant advantages in terms of improved skill scores.Selected output variables from retrospective ensemble runs of the National Centers for Environmental Predictions medium-range forecast (MRF) model were fed into the KNN downscaling model. The quality of the downscaled precipitation forecasts was evaluated in terms of a standard suite of ensemble verification metrics. This study represents the first time the KNN model has been successfully applied within a warm season convective climate regime and shown to produce skillful and reliable ensemble forecasts of daily precipitation out to a lead time of four to six days, depending on the forecast month.Knowledge of the behavior of the regional hydrologic systems in NAM was transferred into a modeling framework aimed at improving intra-seasonal hydrologic predictions. To this end, a robust lumped-parameter computational model of intermediate conceptual complexity was calibrated and applied to generate streamflow in three unregulated test basins in the core region of the NAM. The modeled response to different time-accumulated KNN-generated precipitation forcing was investigated. Although the model had some difficulty in accurately simulating hydrologic fluxes on the basis of Hortonian runoff principles only, the preliminary results achieved from this study are encouraging. The primary and most novel finding from this study is an improved predictability of the NAM system using state-of-the-art ensemble forecasting systems. Additionally, this research significantly enhanced the utility of the MRF ensemble forecasts and made them reliable for regional hydrologic applications. Finally, monthly streamflow simulations (from an ensemble-based approach) have been demonstrated. Estimated ensemble forecasts provide quantitative estimates of uncertainty associated with our model forecasts.