A Study of Tidal Influences in the North Water Polynya using Short Time Span Satellite Imagery

The North Water Polynya (NOW) is an area of ocean between Greenland and Ellesmere Island that does not freeze completely during the winter months. The mechanism that maintains the polynya during the Arctic winter and early spring is not precisely known, but the presence of open water is a critical factor in allowing oceanic heat to escape into the atmosphere. The northerly location of the NOW permitted the collection of an Advanced Very High Resolution Radiometer (AVHRR) image every 101 minutes for seven consecutive orbits. The unique, short time span imagery allowed thermal features of the NOW to be mapped over a tidal cycle. The combination of AVHRR imagery, Acoustic Doppler Current Profiler data, and the Composite Arctic Sea Surface Temperature Algorithm show the dynamic nature of the NOW over a tidal cycle. Both the amount and configuration of open water can change dramatically over a 12-hour period in response to tidal fluctuations. The evidence suggests that the amount of open water in the NOW during March and April is related to the velocity of the current, which in turn is influenced by the tidal cycle. The open water caused by the tide-induced movement of ice then allows oceanic heat to escape into the environment. During March and April, the considerable temperature difference between the ocean and the atmosphere at their interface results in a high incidence of ice fog near leads and open water in the NOW. The amount of ice fog observed on the satellite imagery fluctuates with the tidal cycle, suggesting that open water within the NOW is influenced by the tide in the short term.La Polynie des eaux du Nord (NOW) est une zone océanique située entre le Groenland et l’île d’Ellesmere qui ne gèle pas complètement pendant les mois d’hiver. Le mécanisme qui maintient la Polynie ainsi pendant l’hiver et le début du printemps de l’Arctique n’est pas vraiment connu, mais la présence d’eau libre est un facteur critique permettant à la chaleur océanique de s’échapper dans l’atmosphère. L’emplacement nordique de la Polynie des eaux du Nord a permis de recueillir des images par radiomètre perfectionné à très haute résolution (AVHRR) aux 101 minutes pendant sept orbites consécutives. L’imagerie unique obtenue sur une courte durée a permis aux caractéristiques thermales de la Polynie des eaux du Nord d’être mappées sur un cycle des marées. Ensemble, les images captées par AVHRR, les données prélevées au moyen du profileur de courant acoustique à effet Doppler et l’algorithme composite pour les températures de surface de la mer arctique illustrent la nature dynamique de la Polynie des eaux du Nord sur un cycle des marées. La quantité et la configuration de l’eau libre peuvent changer énormément sur une période de 12 heures en raison des fluctuations attribuables aux marées. Les données recueillies laissent croire que la quantité d’eau libre dans la Polynie des eaux du Nord en mars et en avril est influencée par la vélocité du courant qui, à son tour, est influencée par le cycle des marées. Ensuite, l’eau libre découlant du mouvement de la glace provoqué par les marées permet à la chaleur océanique de s’échapper dans l’environnement. En mars et en avril, la différence considérable de température entre l’océan et l’atmosphère à leur interface entraîne une forte incidence de brouillard glacé près des chenaux et des eaux libres de la Polynie des eaux du Nord. La quantité de brouillard glacé observée sur l’imagerie par satellite fluctue en fonction du cycle des marées, ce qui laisse croire que l’eau libre dans la Polynie des eaux du Nord est influencée par la marée à court terme

Precipitation dynamics and chemical properties in tropical mountain forests of Ecuador

International audienceTerrestrial ecosystems in southern Ecuador are strongly affected by interannual climate variations. This holds especially true for the episodic El Niño events, which cause above-normal precipitation in the coastal region of Ecuador and below normal values in the eastern provinces of the Amazon basin (Bendix, 1999). For the transitional zone between these two extremes, which consists mainly of the andean slopes and larger interandean basins the effect on interannual climate variability is not well known. The PREDICT project monitors regional climate in the provinces of Loja and Zamora-Chinchipe (4° S/79° W), where a strong gradients of precipitation are observed. Between the eastern slopes of the Cordillera Real and the dry valley of Catamayo, which are only 70km apart, rain totals drop from over 4000 mm to only 300 mm per year. These two extremes represent the both sides of the Andean mountain chain and are completely covered by the study area, which is 120 km in diameter. Methods used are a combination of point measurements (climate stations) and remote sensing devices (weather radar, satellite imagery), which enable a high-resolution real-time observation of rain distribution and underlying processes. By this, ideal conditions are given to monitor a potential shift of the transition zone between below-average and above-average rainfall situated in this region, if another ENSO-anomaly occurs. Furthermore variability of atmospheric nutrient inputs is analysed within the scope of the project, to assess further impacts on this ecosystem

A new cloud detection algorithm for NOAA AVHRR imagery

1999 IEEE TENCO

Wind Farm Wake: The Horns Rev Photo Case

energie

Vegetation Dynamics in Ecuador

Global forest cover has suffered a dramatic reduction during recent decades, especially in tropical regions, which is mainly due to human activities caused by enhanced population pressures. Nevertheless, forest ecosystems, especially tropical forests, play an important role in the carbon cycle functioning as carbon stocks and sinks, which is why conservation strategies are of utmost importance respective to ongoing global warming. In South America the highest deforestation rates are observed in Ecuador, but an operational surveillance system for continuous forest monitoring, along with the determination of deforestation rates and the estimation of actual carbon socks is still missing. Therefore, the present investigation provides a functional tool based on remote sensing data to monitor forest stands at local, regional and national scales. To evaluate forest cover and deforestation rates at country level satellite data was used, whereas LiDAR data was utilized to accurately estimate the Above Ground Biomass (AGB; carbon stocks) at catchment level. Furthermore, to provide a cost-effective tool for continuous forest monitoring of the most vulnerable parts, an Unmanned Aerial Vehicle (UAV) was deployed and equipped with various sensors (RBG and multispectral camera). The results showed that in Ecuador total forest cover was reduced by about 24% during the last three decades. Moreover, deforestation rates have increased with the beginning of the new century, especially in the Andean Highland and the Amazon Basin, due to enhanced population pressures and the government supported oil and mining industries, besides illegal timber extractions. The AGB stock estimations at catchment level indicated that most of the carbon is stored in natural ecosystems (forest and páramo; AGB ~98%), whereas areas affected by anthropogenic land use changes (mostly pastureland) lost nearly all their storage capacities (AGB ~2%). Furthermore, the LiDAR data permitted the detection of the forest structure, and therefore the identification of the most vulnerable parts. To monitor these areas, it could be shown that UAVs are useful, particularly when equipped with an RGB camera (AGB correlation: R² > 0.9), because multispectral images suffer saturation of the spectral bands over dense natural forest stands, which results in high overestimations. In summary, the developed operational surveillance systems respective to forest cover at different spatial scales can be implemented in Ecuador to promote conservation/ restoration strategies and to reduce the high deforestation rates. This may also mitigate future greenhouse gas emissions and guarantee functional ecosystem services for local and regional populations

SOFOS - A new Satellite-based Operational Fog Observation Scheme

This thesis introduces a new technique for the operational observation of fog from space. The scheme presented uses the Meteosat-8 SEVIRI system for near-real-time detection of low stratus and ground fog areas

User's guide to image processing applications of the NOAA satellite HRPT/AVHRR data. Part 1: Introduction to the satellite system and its applications. Part 2: Processing and analysis of AVHRR imagery

The use of NOAA Advanced Very High Resolution Radar/High Resolution Picture Transmission (AVHRR/HRPT) imagery for earth resource applications is provided for the applications scientist for use within the various Earth science, resource, and agricultural disciplines. A guide to processing NOAA AVHRR data using the hardware and software systems integrated for this NASA project is provided. The processing steps from raw data on computer compatible tapes (1B data format) through usable qualitative and quantitative products for applications are given. The manual is divided into two parts. The first section describes the NOAA satellite system, its sensors, and the theoretical basis for using these data for environmental applications. Part 2 is a hands-on description of how to use a specific image processing system, the International Imaging Systems, Inc. (I2S) Model 75 Array Processor and S575 software, to process these data

Standardized Drought Indices for pre-summer drought assessment in tropical areas

The main climatic indices used for the determination of pre-summer drought severity were developed for temperate zones with very different climatic conditions from those found in the tropical climate zones, particularly with respect to seasonal rainfall variations. The temporal evolution of pre-summer drought leads the authors to compute the indices for each year over a defined period according to the climatic normals of each meteorological station and to consider the months inside the dry episode differently, according to the law of emptying the water reserves. As a function of this, standardized drought indices are proposed for the evaluation of the pre-summer drought in tropical zone. Two new indices were tested: one developed from precipitation and the other also considering temperature. These indices were validated by correlation with Advanced very-high-resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) time series and used to identify the most severe drought conditions in the Yucatan Peninsula. The comparison between the indices and their temporal variations highlighted the importance of temperature in the most critical events and left indications of the impact of global warming on the phenomenon.UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI)UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Ciencias del Mar y Limnología (CIMAR)UCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela de Físic

Automated Detection of Clouds in Satellite Imagery

Many different approaches have been used to automatically detect clouds in satellite imagery. Most approaches are deterministic and provide a binary cloud - no cloud product used in a variety of applications. Some of these applications require the identification of cloudy pixels for cloud parameter retrieval, while others require only an ability to mask out clouds for the retrieval of surface or atmospheric parameters in the absence of clouds. A few approaches estimate a probability of the presence of a cloud at each point in an image. These probabilities allow a user to select cloud information based on the tolerance of the application to uncertainty in the estimate. Many automated cloud detection techniques develop sophisticated tests using a combination of visible and infrared channels to determine the presence of clouds in both day and night imagery. Visible channels are quite effective in detecting clouds during the day, as long as test thresholds properly account for variations in surface features and atmospheric scattering. Cloud detection at night is more challenging, since only courser resolution infrared measurements are available. A few schemes use just two infrared channels for day and night cloud detection. The most influential factor in the success of a particular technique is the determination of the thresholds for each cloud test. The techniques which perform the best usually have thresholds that are varied based on the geographic region, time of year, time of day and solar angle