Editorial for the special issue "remote sensing of atmospheric conditions forwind energy applications"

Research output: Contribution to journalEditorial – Annual report year: 2019Researchpeer-review

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Editorial for the special issue "remote sensing of atmospheric conditions forwind energy applications". / Hasager, Charlotte Bay; Sjöholm, Mikael.

In: Remote Sensing, Vol. 11, No. 7, 781, 2019.

Research output: Contribution to journalEditorial – Annual report year: 2019Researchpeer-review

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@article{e622ed10520e4c509a60c370d08c3c47,
title = "Editorial for the special issue {"}remote sensing of atmospheric conditions forwind energy applications{"}",
abstract = "This Special Issue hosts papers on aspects of remote sensing for atmospheric conditions for wind energy applications. The wind lidar technology is presented from a theoretical view on the coherent focused Doppler lidar principles. Furthermore, wind lidar for applied use for wind turbine control, wind farm wake, and gust characterizations are presented, as well as methods to reduce uncertainty when using lidar in complex terrain. Wind lidar observations are used to validate numerical model results. Wind Doppler lidar mounted on aircraft used for observing winds in hurricane conditions and Doppler radar on the ground used for very short-term wind forecasting are presented. For the offshore environment, floating lidar data processing is presented as well as an experiment with wind-profiling lidar on a ferry for model validation. Assessments of wind resources in the coastal zone using wind-profiling lidar and global wind maps using satellite data are presented.",
keywords = "Aerosol, Complex terrain, Control, Doppler wind lidar, Offshore, Wake, Wind energy, Wind farm, Wind turbine",
author = "Hasager, {Charlotte Bay} and Mikael Sj{\"o}holm",
year = "2019",
doi = "10.3390/rs11070781",
language = "English",
volume = "11",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "M D P I AG",
number = "7",

}

RIS

TY - JOUR

T1 - Editorial for the special issue "remote sensing of atmospheric conditions forwind energy applications"

AU - Hasager, Charlotte Bay

AU - Sjöholm, Mikael

PY - 2019

Y1 - 2019

N2 - This Special Issue hosts papers on aspects of remote sensing for atmospheric conditions for wind energy applications. The wind lidar technology is presented from a theoretical view on the coherent focused Doppler lidar principles. Furthermore, wind lidar for applied use for wind turbine control, wind farm wake, and gust characterizations are presented, as well as methods to reduce uncertainty when using lidar in complex terrain. Wind lidar observations are used to validate numerical model results. Wind Doppler lidar mounted on aircraft used for observing winds in hurricane conditions and Doppler radar on the ground used for very short-term wind forecasting are presented. For the offshore environment, floating lidar data processing is presented as well as an experiment with wind-profiling lidar on a ferry for model validation. Assessments of wind resources in the coastal zone using wind-profiling lidar and global wind maps using satellite data are presented.

AB - This Special Issue hosts papers on aspects of remote sensing for atmospheric conditions for wind energy applications. The wind lidar technology is presented from a theoretical view on the coherent focused Doppler lidar principles. Furthermore, wind lidar for applied use for wind turbine control, wind farm wake, and gust characterizations are presented, as well as methods to reduce uncertainty when using lidar in complex terrain. Wind lidar observations are used to validate numerical model results. Wind Doppler lidar mounted on aircraft used for observing winds in hurricane conditions and Doppler radar on the ground used for very short-term wind forecasting are presented. For the offshore environment, floating lidar data processing is presented as well as an experiment with wind-profiling lidar on a ferry for model validation. Assessments of wind resources in the coastal zone using wind-profiling lidar and global wind maps using satellite data are presented.

KW - Aerosol

KW - Complex terrain

KW - Control

KW - Doppler wind lidar

KW - Offshore

KW - Wake

KW - Wind energy

KW - Wind farm

KW - Wind turbine

U2 - 10.3390/rs11070781

DO - 10.3390/rs11070781

M3 - Editorial

VL - 11

JO - Remote Sensing

JF - Remote Sensing

SN - 2072-4292

IS - 7

M1 - 781

ER -