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A3: ID.10532 Atmospheric Dynamics from LIDAR
Wind Field Retrieve Model For An Airborne Wind Lidar
1Ocean University of China, People's Republic of China; 2Shandong University of Science and Technology, College of Geomatics; 3Key Laboratory of Surveying and Mapping Technology on Island and Reef, State Bureau of Surveying and Mapping, China; 4Ludong University, School of Physics and Optoelectronic Engineering; 5The First Institute of Oceanography, State Oceanic Administration;
In this paper, we established a nonlinear model for an airborne wind lidar （1550nm fiber laser coherent wind lidar）and completed the L-M (Levenberg-Marquardt) algorithm for to solve this nonlinear model. We tested the algorithm with the modeled data. The retrieved velocity and the true velocity fit well, the correlation coefficient is about0.98. After the simulation test, we use the model and the L-M algorithm to process the wind lidar experiment data; compare the retrieve results with the radiosonde wind profile. The consistence of them is very well, especially at the altitude between 2km-3km. We may speculate that when the atmosphere flows not so dramatically, the lidar and the radiosonde measurements are synchronous strictly; it is possible to retrieve horizontal wind speeds and directions consistently with the radiosonde using our wind lidar model and L-M algorithm.
The L-M algorithm is a widely used optimization algorithm. It is an iterative technique that locates the minimum of a function expressed as the sum of squares of nonlinear functions. It has become a standard technique for nonlinear least-squares problems and can be thought of as a combination of steepest descent and the Gauss-Newton method. The L-M algorithm finds the minimization value of the merit function by iteration. At each step of the iteration, it will update the parameters. The iteration will stop when the merit function is minimized.
We compared horizontal wind speeds and directions of the wind lidar with the radiosonde results. Fig.1 is compare results.
In Fig.1, for the wind speeds, we can find that the wind lidar results distributed well around the radiosonde results; for the wind directions, at a height above 2km, the lidar and the radiosonde agreed well, but at height range of 1km-2km, consistency of the two results are not so good. Reasons for this inconsistency maybe that, first, the lidar and the radiosonde measurements are not synchronous strictly. Second, the atmosphere in the layer between 1km-2km maybe not so stable during the time when the radiosonde is measuring. Third, in the layer between 1km-2km, the wind speeds are very low, the directions calculation using these small value may induce large direction errors. Of course, this model can be also available for incoherent wind lidar.
Pre-Launch Validation Activities with the Airborne Demonstrator for the ESA ADM – Aeolus Wind-Lidar Mission
DLR Deutsches Zentrum fuer Luft- und Raumfahrt, Germany;
Vertical wind profiles on a global scale are the priority need to improve the quality of numerical weather prediction (NWP). The spaceborne wind lidar ALADIN shall deliver such profiles within the ESA Earth Explorer Atmospheric Dynamics Mission (ADM) Aeolus to be orbited in 2017. At DLR (German Aerospace Center) the ALADIN Airborne Demonstrator (A2D), was developed focusing on a high degree of commonality in laser source and Doppler lidar receiver design and operating at the ultraviolet wavelength of 355 nm as the satellite. In operation since 2005 A2D has performed in support of the Aeolus mission by validating retrieval algorithms as well as the instrument concept and operation procedures. Following a series of ground and airborne campaigns with the A2D, in May 2015 a joint ESA - DLR - NASA airborne campaign based in Island, for the first time deployed four Doppler wind lidars plus dropsondes on two aircrafts focusing on calibration-validation procedures for the Aeolus mission. On-board the NASA DC-8 the coherent 2-µm wind lidar DAWN and the 355 nm direct-detection Doppler lidar TWiLiTE measured 3D wind profiles supported by a dropsonde unit additionally providing temperature, pressure, humidity and wind profiles. One objective of this WindVal campaign was to compare co-located NASA wind measurements with measurements from A2D and a second coherent 2 µm lidar, both onboard the DLR Falcon. Another first and extraordinary advantage of the formation was performing calibrations of the A2D over the Greenland sea-ice in nadir looking geometry where the Falcon flies circles while the DC-8 provides co-located wind and temperature measurements for the area. An overview of the WindVal campaign will be presented together with first results from the on-going data analysis.
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Conference: 2016 Dragon 3 Final Results Symposium
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