Satellite Microwave Remote Sensing Instrument Performance Estimate Using Monte Carlo Simulation
Keywords
AV-H; GMF; Ocean wind vector; Precipitation Radar; TMI; wind direction retrieval
Abstract
In this paper, we describe a Monte Carlo technique to simulate the active and passive remote sensor observations (normalized ocean radar backscatter, σ° and brightness temperatures, Tb) and to estimate the resulting wind direction retrieval accuracy. A critical part of the simulation was to calculate the satellite/sensor geometry for each point along the orbital ground track. For this, we used the System Tool Kit (STK) orbital analysis software to determine the antenna pointing geometry and instantaneous-field-of-view (IFOV) locations (latitude, longitude, EIA, and azimuth) versus orbit position. Next, these simulated sensor IFOV's were spatially gridded into 0.25°xO.25° boxes and collocated with numerical weather model 'nature-run' outputs, to obtain the desired geophysical parameters, namely wind speed and wind direction. Using existing radar and radiometer geophysical model functions (GMF), which relate ocean σ° and Tb with wind speed, relative wind direction, and earth incidence angle, the radar backscatter measurements and radiometer brightness temperatures (AV-H) were simulated, with realistic values of Gaussian noise added. Finally, a maximum likelihood estimation (MLE) procedure was applied to retrieve the wind directions, which were compared to the nature run WD, and the error statistical results are presented.
Publication Date
10-1-2018
Publication Title
Conference Proceedings - IEEE SOUTHEASTCON
Volume
2018-April
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/SECON.2018.8479041
Copyright Status
Unknown
Socpus ID
85056176998 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85056176998
STARS Citation
Hossan, Alamgir; Jacobi, Maria; and Jones, W. Linwood, "Satellite Microwave Remote Sensing Instrument Performance Estimate Using Monte Carlo Simulation" (2018). Scopus Export 2015-2019. 7647.
https://stars.library.ucf.edu/scopus2015/7647