scholarly journals Evaluation of Multiangle Imaging Spectroradiometer cloud motion vectors using NOAA radar wind profiler data

2009 ◽  
Vol 114 (D21) ◽  
Author(s):  
Laura M. Hinkelman ◽  
Roger T. Marchand ◽  
Thomas P. Ackerman
Keyword(s):  
Wind Profiler ◽  
Motion Vectors ◽  
Cloud Motion ◽  
Profiler Data ◽  
Multiangle Imaging ◽  
Multiangle Imaging Spectroradiometer

scholarly journals A novel approach for the extraction of cloud motion vectors using airglow imager measurements

2015 ◽  
Vol 8 (9) ◽  
pp. 3893-3901 ◽  
Author(s):  
S. Satheesh Kumar ◽  
T. Narayana Rao ◽  
A. Taori
Keyword(s):  
Meridional Wind ◽  
Noise Removal ◽  
Search Window ◽  
Motion Vectors ◽  
Good Correspondence ◽  
Cloud Motion ◽  
Cloud Height ◽  
Novel Approach ◽  
Wind Velocities ◽  
Cloud Tracking

Abstract. The paper explores the possibility of implementing an advanced photogrammetric technique, generally employed for satellite measurements, on airglow imager, a ground-based remote sensing instrument primarily used for upper atmospheric studies, measurements of clouds for the extraction of cloud motion vectors (CMVs). The major steps involved in the algorithm remain the same, including image processing for better visualization of target elements and noise removal, identification of target cloud, setting a proper search window for target cloud tracking, estimation of cloud height, and employing 2-D cross-correlation to estimate the CMVs. Nevertheless, the implementation strategy at each step differs from that of satellite, mainly to suit airglow imager measurements. For instance, climatology of horizontal winds at the measured site has been used to fix the search window for target cloud tracking. The cloud height is estimated very accurately, as required by the algorithm, using simultaneous collocated lidar measurements. High-resolution, both in space and time (4 min), cloud imageries are employed to minimize the errors in retrieved CMVs. The derived winds are evaluated against MST radar-derived winds by considering it as a reference. A very good correspondence is seen between these two wind measurements, both showing similar wind variation. The agreement is also found to be good in both the zonal and meridional wind velocities with RMSEs < 2.4 m s−1. Finally, the strengths and limitations of the algorithm are discussed, with possible solutions, wherever required.

Multiangle Imaging Spectroradiometer: optical characterization of the calibration panels

1997 ◽  
Vol 36 (27) ◽  
pp. 7016 ◽  
Author(s):  
Brendan T. McGuckin ◽  
David A. Haner ◽  
Robert T. Menzies
Keyword(s):  
Optical Characterization ◽  
Multiangle Imaging ◽  
Multiangle Imaging Spectroradiometer

scholarly journals Prediction of Solar Power Using Near-Real Time Satellite Data

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5865
Author(s):  
Abhnil Amtesh Prasad ◽  
Merlinde Kay
Keyword(s):  
Real Time ◽  
Satellite Data ◽  
Solar Power ◽  
Short Term ◽  
Motion Vectors ◽  
Clear Sky ◽  
Cloud Motion ◽  
Visible Images ◽  
Grid Operators ◽  
Short Term Prediction

Solar energy production is affected by the attenuation of incoming irradiance from underlying clouds. Often, improvements in the short-term predictability of irradiance using satellite irradiance models can assist grid operators in managing intermittent solar-generated electricity. In this paper, we develop and test a satellite irradiance model with short-term prediction capabilities using cloud motion vectors. Near-real time visible images from Himawari-8 satellite are used to derive cloud motion vectors using optical flow estimation techniques. The cloud motion vectors are used for the advection of pixels at future time horizons for predictions of irradiance at the surface. Firstly, the pixels are converted to cloud index using the historical satellite data accounting for clear, cloudy and cloud shadow pixels. Secondly, the cloud index is mapped to the clear sky index using a historical fitting function from the respective sites. Thirdly, the predicated all-sky irradiance is derived by scaling the clear sky irradiance with a clear sky index. Finally, a power conversion model trained at each site converts irradiance to power. The prediction of solar power tested at four sites in Australia using a one-month benchmark period with 5 min ahead prediction showed that errors were less than 10% at almost 34–60% of predicted times, decreasing to 18–26% of times under live predictions, but it outperformed persistence by >50% of the days with errors <10% for all sites. Results show that increased latency in satellite images and errors resulting from the conversion of cloud index to irradiance and power can significantly affect the forecasts.

An evaluation of two automated quality control methods designed for use with hourly wind profiler data

1994 ◽  
Vol 12 (8) ◽  
pp. 711-724 ◽  
Author(s):  
P. A. Miller ◽  
M. F. Barth ◽  
D. W. van de Kamp ◽  
T. W. Schlatter ◽  
B. L. Weber ◽  
...  
Keyword(s):  
Quality Control ◽  
Statistical Evaluation ◽  
Wind Profiler ◽  
Control Methods ◽  
Operational Environment ◽  
Central United States ◽  
National Networks ◽  
Automated Quality Control ◽  
Profiler Data

Abstract. The National Oceanic and Atmospheric Administration (NOAA) has completed the installation of a 30-site demonstration network of wind-profiling radars in the central United States. The network is being used to demonstrate and assess the utility of wind profiler technology in a quasi-operational environment, and to help define operational requirements for possible future national networks. This paper describes two automated quality control methods designed to remove erroneous winds from the hourly network data. Case study examples and statistical evaluation of the performance of each method are also presented.

Sign in / Sign up

Export Citation Format

Share Document