Role of sea-surface wind and transport on enhanced aerosol optical depth observed over the Arabian Sea

2012 ◽  
Vol 33 (16) ◽  
pp. 5105-5118 ◽  
Author(s):  
P. Sivaprasad ◽  
C. A. Babu
2012 ◽  
Vol 5 (4) ◽  
pp. 5205-5243 ◽  
Author(s):  
J. C. Anderson ◽  
J. Wang ◽  
J. Zeng ◽  
M. Petrenko ◽  
G. G. Leptoukh ◽  
...  

Abstract. Coastal regions around the globe are a major source for anthropogenic aerosols in the atmosphere, but the underlying surface characteristics are not favorable for the Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms designed for retrieval of aerosols over dark land or open-ocean surfaces. Using data collected from 62 coastal stations worldwide from the Aerosol Robotic Network (AERONET) from ~ 2002–2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard Aqua satellite. It is found that coastal AODs (at 550 nm) characterized respectively by the MODIS Dark Land (hereafter Land) surface algorithm, the Open-Ocean (hereafter Ocean) algorithm, and AERONET all exhibit a log-normal distribution. After filtering by quality flags, the MODIS AODs respectively retrieved from the Land and Ocean algorithms are highly correlated with AERONET (with R2 &amp;approx; 0.8), but only the Land algorithm AODs fall within the expected error envelope greater than 66% of the time. Furthermore, the MODIS AODs from the Land algorithm, Ocean algorithm, and combined Land_and_Ocean product show statistically significant discrepancies from their respective counterparts from AERONET in terms of mean, probability density function, and cumulative density function, which suggest a need for future improvement in retrieval algorithms. Without filtering with quality flag, the MODIS Land_and_Ocean AOD dataset can be degraded by 30–50% in terms of mean bias. Overall, the MODIS Ocean algorithm overestimates the AERONET coastal AOD by 0.021 for AOD < 0.25 and underestimates it by 0.029 for AOD > 0.25. This dichotomy is shown to be related to the ocean surface wind speed and cloud contamination effects on the satellite aerosol retrieval. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) reveals that wind speeds over the global coastal region (with a mean and median value of 2.94 m s−1 and 2.66 m s−1, respectively) are often slower than 6 m s−1 assumed in the MODIS Ocean algorithm. As a result of high correlation (R2 > 0.98) between the bias in binned MODIS AOD and the corresponding binned wind speed over the coastal sea surface, an empirical scheme for correcting the bias of AOD retrieved from the MODIS Ocean algorithm is formulated and is shown to be effective over the majority of the coastal AERONET stations, and hence can be used in future analysis of AOD trend and MODIS AOD data assimilation.


2012 ◽  
Vol 50 (7) ◽  
pp. 2901-2909 ◽  
Author(s):  
Alexis A. Mouche ◽  
Fabrice Collard ◽  
Bertrand Chapron ◽  
Knut-Frode Dagestad ◽  
Gilles Guitton ◽  
...  

2019 ◽  
Vol 11 (9) ◽  
pp. 1112
Author(s):  
Guoqing Han ◽  
Changming Dong ◽  
Junde Li ◽  
Jingsong Yang ◽  
Qingyue Wang ◽  
...  

Based on both satellite remote sensing sea surface temperature (SST) data and numerical model results, SST warming differences in the Mozambique Channel (MC) west of the Madagascar Island (MI) were found with respect to the SST east of the MI along the same latitude. The mean SST west of the MI is up to about 3.0 °C warmer than that east of the MI. The SST differences exist all year round and the maximum value appears in October. The area of the highest SST is located in the northern part of the MC. Potential factors causing the SST anomalies could be sea surface wind, heat flux and oceanic flow advection. The presence of the MI results in weakening wind in the MC and in turn causes weakening of the mixing in the upper oceans, thus the surface mixed layer depth becomes shallower. There is more precipitation on the east of the MI than that inside the MC because of the orographic effects. Different precipitation patterns and types of clouds result in different solar radiant heat fluxes across both sides of the MI. Warm water advected from the equatorial area also contribute to the SST warm anomalies.


2004 ◽  
Vol 1 (6) ◽  
pp. 137-143 ◽  
Author(s):  
Alexey Nekrasov ◽  
Jacco J.M. de Wit ◽  
Peter Hoogeboom

2002 ◽  
Vol 124 (3) ◽  
pp. 169-172 ◽  
Author(s):  
Dag Myrhaug ◽  
Olav H. Slaattelid

The paper considers the effects of sea roughness and atmospheric stability on the sea surface wind stress over waves, which are in local equilibrium with the wind, by using the logarithmic boundary layer profile including a stability function, as well as adopting some commonly used sea surface roughness formulations. The engineering relevance of the results is also discussed.


2011 ◽  
Vol 29 (2) ◽  
pp. 393-399
Author(s):  
T. I. Tarkhova ◽  
M. S. Permyakov ◽  
E. Yu. Potalova ◽  
V. I. Semykin

Abstract. Sea surface wind perturbations over sea surface temperature (SST) cold anomalies over the Kashevarov Bank (KB) of the Okhotsk Sea are analyzed using satellite (AMSR-E and QuikSCAT) data during the summer-autumn period of 2006–2009. It is shown, that frequency of cases of wind speed decreasing over a cold spot in August–September reaches up to 67%. In the cold spot center SST cold anomalies reached 10.5 °C and wind speed lowered down to ~7 m s−1 relative its value on the periphery. The wind difference between a periphery and a centre of the cold spot is proportional to SST difference with the correlations 0.5 for daily satellite passes data, 0.66 for 3-day mean data and 0.9 for monthly ones. For all types of data the coefficient of proportionality consists of ~0.3 m s−1 on 1 °C.


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