scholarly journals Remote Sensing and GIS Application Analysis of Active Fire, Aerosol Optical Thickness and Estimated PM10 In The North of Thailand and Chiang Rai Province

2012 ◽  
Vol 1 ◽  
pp. 304-308 ◽  
Author(s):  
Nion Sirimongkonlertkul ◽  
Vivarad Phonekeo
Keyword(s):  
Remote Sensing ◽  
Optical Thickness ◽  
Remote Sensing And Gis ◽  
Aerosol Optical Thickness ◽  
Gis Application ◽  
The North ◽  
Active Fire ◽  
Application Analysis

scholarly journals Estimating a relationship between aerosol optical thickness and surface wind speed over the ocean

2006 ◽  
Vol 6 (6) ◽  
pp. 11621-11651 ◽  
Author(s):  
P. Glantz ◽  
D. E. Nilsson ◽  
W. von Hoyningen-Huene
Keyword(s):  
Wind Speed ◽  
Optical Thickness ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Sea Salt ◽  
Aerosol Optical Thickness ◽  
Marine Aerosols ◽  
Hygroscopic Growth ◽  
The North ◽  
The North Pacific

Abstract. Retrieved aerosol optical thickness (AOT) based on data obtained by the Sea viewing Wide Field Sensor (SeaWiFS) is combined with surface wind speed, obtained at the European Centre for Medium-Range Weather Forecasts (ECMWFs), over the North Pacific for September 2001. In this study a cloud screening approach is introduced in an attempt to exclude pixels partly or fully covered by clouds. The relatively broad swath width for which the nadir looking SeaWiFS instrument scanned over the North Pacific means that the AOT can be estimated according to relatively large range of wind speeds for each of the scenes analyzed. The sensitivity in AOT due to sea salt and hygroscopic growth of the marine aerosols has also been investigated. The validation of the results is based on previous parameterization in combination with the environmental quantities wind speed, RH and boundary layer height (BLH), estimated at the ECMWF. In this study a factor of 2 higher mean AOT is obtained for a wind speed up to about 13 m s−1 for September 2001 over remote ocean areas. Furthermore, a factor of 2 higher AOT is more or less supported by the validation of the results. Approximately, 50% of the enhancement seems to be due to hygroscopic growth of the marine aerosols and the remaining part due to increase in the sea salt particle mass concentrations, caused by a wind driven water vapor and sea salt flux, respectively. Reasonable agreement occurs also between satellites retrieved aerosol optical thickness and AOT observed at several AERONET (Aerosol Robotic NETwork) ground-based remote sensing stations. Finally, possible reasons why relatively large standard deviations occur around the mean values of AOT estimated for a single scene are discussed.

scholarly journals A geostatistical data fusion technique for merging remote sensing and ground-based observations of aerosol optical thickness

2010 ◽  
Vol 115 (D20) ◽  
Author(s):  
Abhishek Chatterjee ◽  
Anna M. Michalak ◽  
Ralph A. Kahn ◽  
Susan R. Paradise ◽  
Amy J. Braverman ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Fusion ◽  
Optical Thickness ◽  
Aerosol Optical Thickness ◽  
Fusion Technique

scholarly journals New Statistical Model for Variability of Aerosol Optical Thickness: Theory and Application to MODIS Data over Ocean*

2016 ◽  
Vol 73 (2) ◽  
pp. 821-837 ◽  
Author(s):  
Mikhail D. Alexandrov ◽  
Igor V. Geogdzhayev ◽  
Kostas Tsigaridis ◽  
Alexander Marshak ◽  
Robert Levy ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Optical Thickness ◽  
Large Scale ◽  
Climate Models ◽  
Marine Boundary Layer ◽  
Structure Functions ◽  
Aerosol Optical Thickness ◽  
Small Scale ◽  
Scale Invariant ◽  
Modis Data

Abstract A novel model for the variability in aerosol optical thickness (AOT) is presented. This model is based on the consideration of AOT fields as realizations of a stochastic process that is the exponent of an underlying Gaussian process with a specific autocorrelation function. In this approach, AOT fields have lognormal PDFs and structure functions with the correct asymptotic behavior at large scales. The latter is an advantage compared with fractal (scale invariant) approaches. The simple analytical form of the structure function in the proposed model facilitates its use for the parameterization of AOT statistics derived from remote sensing data. The new approach is illustrated using a 1-yr-long global MODIS AOT dataset (over ocean) with 10-km resolution. It was used to compute AOT statistics for sample cells forming a grid with 5° spacing. The observed shapes of the structure functions indicated that, in a large number of cases, the AOT variability is split into two regimes that exhibit different patterns of behavior: small-scale stationary processes and trends reflecting variations at larger scales. The small-scale patterns are suggested to be generated by local aerosols within the marine boundary layer, while the large-scale trends are indicative of elevated aerosols transported from remote continental sources. This assumption is evaluated by comparison of the geographical distributions of these patterns derived from MODIS data with those obtained from the GISS GCM. This study shows considerable potential to enhance comparisons between remote sensing datasets and climate models beyond regional mean AOTs.

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