Comparison of AMSR-2 wind speed and sea surface temperature with moored buoy observations over the Northern Indian Ocean

BNK Reddy, R Venkatesan, KK Osuri, S Mathew… - Journal of Earth System …, 2018 - Springer
Journal of Earth System Science, 2018Springer
Abstract The Northern Indian Ocean (NIO) is unique due to seasonal reversal of wind
patterns, the formation of vortices and eddies which make satellite observations arduous.
The veracity of sea surface wind (SSW) and sea surface temperature (SST) products of sun-
synchronous AMSR-2 satellite are compared with high-temporal moored buoy observations
over the NIO. The two year-long (2013–2014) comparisons reveal that the root-mean-square-
error (RMSE) of AMSR-2 SST and SSW is< 0.4^ ∘ C< 0.4∘ C and< 1.5 ms^-1< 1.5 ms-1 …
Abstract
The Northern Indian Ocean (NIO) is unique due to seasonal reversal of wind patterns, the formation of vortices and eddies which make satellite observations arduous. The veracity of sea surface wind (SSW) and sea surface temperature (SST) products of sun-synchronous AMSR-2 satellite are compared with high-temporal moored buoy observations over the NIO. The two year-long (2013–2014) comparisons reveal that the root-mean-square-error (RMSE) of AMSR-2 SST and SSW is and , respectively, which are within the error range prescribed for the AMSR-2 satellite (, . The SST–wind relation is analyzed using data both from the buoy and satellite. As a result, the low-SST is associated with low-wind condition (positive slope) in the northern part of the Bay of Bengal (BoB), while low SST values are associated with high wind conditions (negative slope) over the southern BoB. Moreover, the AMSR-2 displayed larger slope for SST–wind relation and could be mainly due to overestimation of SST and underestimation of wind as compared to the buoy. The AMSR-2 SSW exhibited higher error during post-monsoon followed by monsoon season and could be attributed to the high wind conditions associated with intense oceanic vortices. The study suggests that the AMSR-2 products are reliable and can be used in tropical air–sea interactions, meso-scale features, and weather and climate studies.
Springer
以上显示的是最相近的搜索结果。 查看全部搜索结果