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Delegates are invited to meet and discuss with the poster presenters in this topic directly after the session 'Remote sensing: From toys to tools?' taking place on Wednesday, 12 March 2014 at 14:15-15:45. The meet-the-authors will take place in the poster area.

Rebecca Barthelmie Indiana University, United States of America
Co-authors:

(1) Indiana University, Bloomington, United States of America (2) DTU, Roskilde, Denmark (3) Danish Techjnical University, Roskilde, Denmark

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Abstract

Satellite and ground based observations integrated into a wind atlas for the Great Lakes

Introduction

According to the US Environmental Protection Agency, the Great Lakes are the largest surface freshwater system and the Basin has a population of 33 million. The Great Lakes are potential locations for large offshore wind farms because of their expected wind resource, because they are close to large load centers and some areas have moderate water depths. However, offshore wind resources over the Great Lakes are difficult to quantify accurately due the spatial sparseness of offshore observations, the formation of ice during winter months, and the temporal and spatial variability of satellite imagery available for wind field retrieval.

Approach

This study combines measured wind data from coastal land stations, buoys, and SAR-derived wind fields to estimate the wind resource of the Great Lakes through the generation of wind atlases. The study aims to capture the long-term variability of the wind resource using long-term coastal and buoy data sets but to combine this with the spatial coverage from satellite wind retrieval. The technique is based on the wind atlas methodology for satellite-derived wind speeds that has been used successfully in other regions. The results are presented in the Wind Atlas format.

Main body of abstract

A major challenge is to provide both spatial and temporal variability of the wind resource for the Great Lakes. The data cover the period 2003-2012. Each data set has both advantages and disadvantages e.g. the datasets at 61 coastal sites are for relatively low heights and represent coastal conditions. The 21 buoy data sets are not available during the ice season. The satellite derived wind speeds provide excellent spatial coverage in some, but not all, regions and are temporally limited and sometimes sparse. By combining the data sets with the WAsP model, a Wind Atlas for the Great Lakes is being produced that can address some of the data gaps and quantify the wind resource.
Because the Great Lakes system is a high-latitude fresh water system it is subject to extensive winter ice cover. Aside from the technical challenges for wind energy development, it also represents a challenge for resource assessment. The wind atlas approach will be applied to quantify the wind resource during the ice season based on the existing data sets. The success of the technique partly depends on how robust the relationships are between the coastal/buoys site wind speeds and those derived from the satellite platforms.


Conclusion

Previous studies of the Great Lakes wind resource have mainly been based on modeling due to the difficulties of quantify the resource from remote and ground-based data sets that are temporally and/or spatially limited. We will present our approach to combine datasets based on the Wind Atlas methodology and compare this with previous resource studies. We are developing a method to extrapolate the wind resource in time and space to cover the ice season and this work will also be presented.


Learning objectives
Understand the advantages and limitations of wind resources derived from ground-based and remote sensing platforms and how these can be integrated in terms of quantifying temporal and spatial wind speeds and presented as a Wind Atlas