# MODIS Retrieval of Aerosol Optical Depth over Turboid Coastal Water
## 4 Results  
Figure 5 shows the example of CW applied to an Aqua-observed scene (10 December 2015) over the Bay of Bengal. According to the standard DT retrieval (MYD04), AOD reaches 1.6 in the center of the granule and decreases gradually southward. MYD04 does not provide retrievals over the coastal water at north part of the Bay of Bengal (Figure 5c). This non-retrieval region is in cloud-free conditions (Figure 5a), so AOD was not retrieved due to turbid water or underlying sea-floor. Figure 5b shows non-retrievals are in 36.4% of this cloud-free, coastal area (within 5 km of coastline or with water depth less than 50 m). Figure 4: (**a**) is monthly mean 0.55 μm AOD and fine mode fraction (FMF) from MOD04 (Terra) in December, 2015. (**b**) is average absolute AOD difference as a function a distance with respect to reference points (black solid circles in (**a**)). (**c**) is monthly mean 0.55 μm AOD and fine mode fraction (FMF) from MOD04 (Terra) in December, 2015. (**d**) is similar to (**b**), but for FMF. Figure 5: (**a**) Aqua MODIS true color image on 10 December 2015. (**b**) Blue and red represents coastal water where MYD AOD retrievals are available (blue) and unavailable (red), respectively in clear sky condition. (**c**) MYD04 0.55 μm DT/DB merged AOD retrievals. (**d**) is similar to (**c**), but the coastal water gaps where MYD04 AOD retrievals are not available in clear sky condition (red box) are filled by AOD retrievals from CW algorithm. AERONET AOD measurement overlaps on (**c**,**d**). The CW algorithm enhances DT-ocean, by retrieving AOD over those turbid water conditions (Figure 5d). These \"new\" retrievals are consistent, in that there appears to be smooth transition in retrieved AOD (e.g., land \(\rightarrow\) CW \(\rightarrow\) ocean). In addition, the new CW AOD retrievals compare well with corresponding values observed by AERONET (overlaid as filled circles in Figure 5c,d). To validate, we follow the standard protocol, in that AERONET measurements within \(\pm\)30 min of the MODIS overpass time are averaged and compared against MODIS retrievals averaged within a 25-km radius circular region centered over the AERONET site. This means that there are three situations: MxD04 retrievals only, CW retrievals only, and cases where both are available within the 25-km of the AERONET site. AOD (at 0.55 \(\upmu\)m) retrievals from MxD04 product and CW algorithm are evaluated against AERONET data (as shown in Figure 6). We use a Venn diagram in Figure 6 to represent how MODIS AOD retrievals (MxD04 and/or CW) and AERONET observations are collocated. Figure 6a is a scatter plot of MxD04 retrievals versus AERONET measurements in the cases that have retrievals only from MxD04, and these cases can be divided into two categories: (a) all cloud-free pixels within 25-km radius proximity of AERONET site are retrieved through MODIS operational algorithm or (b) only part of cloud-free pixels are retrieved through MODIS DT algorithm, but the AOD of the rest of the cloud-free pixels cannot be retrieved with the CW algorithm because these pixels are over turbid water and no open-ocean pixel is close enough (i.e., within 100 km) to provide aerosol single scattering property for CW algorithm. Figure 6b is a scatter plot of CW retrievals versus AERONET measurements in the cases where all cloud-free pixels within 25-km radius proximity of AERONET site cannot be retrieved through MODIS DT algorithm but some or all of these cloud-free pixels can be retrieved through CW algorithm. Comparison of Figure 6a,b shows that normalized mean bias (NMB, \(NMB=\sum_{i=1}^{N}\left(\left(\tau_{i}^{MODIS}-\tau_{i}^{AERONET}\right)/ \tau_{i}^{AERONET}\right)/N\)) and root mean square error (RMSE) of CW algorithm (12.0% and 0.141) are smaller than that of MxD04 (15.9% and 0.213).