NDLI: Investigation of a Complex Nocturnal Flow in Owens Valley, California Using Coherent Doppler Lidar

Content Provider	Springer Nature Link
Author	Choukulkar, Aditya Calhoun, Ronald Billings, Brian Doyle, James
Copyright Year	2012
Abstract	A study of an interesting meteorological episode over the Owens Valley, California, USA during the Terrain-Induced Rotor EXperiment was conducted using a recently adapted statistical interpolation method to retrieve wind-velocity vectors from Doppler lidar data. This vector retrieval method has been adapted from radar data assimilation techniques. Results show that the method allows better preservation of local variations in the flow field than other techniques. In addition, a high resolution Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®) run is used to understand the large-scale flow within the valley and compared with lidar retrievals. Observations from 1030 UTC to 1230 UTC (0230 local time to 0430 local time) on March 27, 2006 are presented. Lidar observations show complex and uncharacteristic flows such as sudden bursts of westerly cross-valley wind mixing with the dominant up-valley wind. Model results from COAMPS and other in-situ instrumentation are used to corroborate and complement these observations. The optimal interpolation technique for Doppler lidar data vector retrieval appears well suited for scenarios with complex spatial variations in the flow field.
Starting Page	359
Ending Page	378
Page Count	20
File Format	PDF
ISSN	00068314
Journal	Boundary-Layer Meteorology
Volume Number	144
Issue Number	3
e-ISSN	15731472
Language	English
Publisher	Springer Netherlands
Publisher Date	2012-05-22
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) Lidar Mountain meteorology Optimal interpolation Owens Valley Terrain-Induced Rotor Experiment (T-REX) Vector retrieval Meteorology/Climatology Atmospheric Protection/Air Quality Control/Air Pollution
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science

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