LEADER 04297nam 2201129z- 450 001 9910346674903321 005 20231214133601.0 010 $a3-03897-943-0 035 $a(CKB)4920000000094918 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/58171 035 $a(EXLCZ)994920000000094918 100 $a20202102d2019 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRemote Sensing of Atmospheric Conditions for Wind Energy Applications 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 215 $a1 electronic resource (290 p.) 311 $a3-03897-942-2 330 $aThis Special Issue ?Atmospheric Conditions for Wind Energy Applications? hosts papers on aspects of remote sensing for atmospheric conditions for wind energy applications. 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 is 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.. 610 $acomplex flow 610 $aFloating Lidar System (FLS) 610 $amesoscale 610 $awind energy resources 610 $avariational analysis 610 $awind turbine 610 $awind sensing 610 $awind energy 610 $awind gusts 610 $awake 610 $awind structure 610 $acomplex terrain 610 $aglobal ocean 610 $aremote sensing forecasting 610 $adetached eddy simulation 610 $afive-minute ahead wind power forecasting 610 $atropical cyclones 610 $afetch effect 610 $aaerosol 610 $avertical Light Detection and Ranging 610 $arange gate length 610 $aresource assessment 610 $afield experiments 610 $aremote sensing 610 $aoptical flow 610 $aturbulence 610 $aatmospheric boundary layer 610 $aDoppler Wind Lidar 610 $aoffshore 610 $aempirical equation 610 $aLidar 610 $aWindSAT 610 $acoastal wind measurement 610 $aoffshore wind speed forecasting 610 $aDoppler wind lidar 610 $aDoppler 610 $awind 610 $awind lidar 610 $across-correlation 610 $aQuikSCAT 610 $awind resource assessment 610 $adetecting and tracking 610 $asingle-particle 610 $agust prediction 610 $aNWP model 610 $avelocity-azimuth-display algorithm 610 $alidar-assisted control (LAC) 610 $aDoppler lidar 610 $amotion estimation 610 $apower performance testing 610 $alidar 610 $alarge-eddy simulations 610 $awind farm 610 $acoherent Doppler lidar 610 $awake modeling 610 $aprobabilistic forecasting 610 $acontrol 610 $aNeoWins 610 $awind turbine controls 610 $aimpact prediction 610 $awind turbine wake 610 $aHazaki Oceanographical Research Station 610 $aVAD 610 $avirtual lidar 610 $aDoppler radar 610 $aIEA Wind Task 32 610 $aASCAT 610 $awind atlas 610 $aturbulence intensity 700 $aHasager$b Charlotte$4auth$01305936 702 $aSjöholm$b Mikael$4auth 906 $aBOOK 912 $a9910346674903321 996 $aRemote Sensing of Atmospheric Conditions for Wind Energy Applications$93028038 997 $aUNINA