![]() ![]() ![]() The locations of the AQS monitoring sites are also utilized to stratify comparisons by the degree of urbanization. For both species the overpredictions are most pronounced in the summer. The annual root mean square errors (RMSEs) are 15.4 ppbv for ozone and 13.4 ppbv for NO2. It is found that both ozone and NO2 are overestimated over the contiguous US (CONUS), with annual biases of +5.6 and +5.1 ppbv, respectively. ![]() In this work, quality-controlled and-assured Air Quality System (AQS) ozone and nitrogen dioxide (NO2) observations are used to evaluate the experimental predictions in 2010. Routine evaluation using near-real-time AIRNow ozone measurements through 2011 showed better performance of the operational ozone predictions. The National Air Quality Forecast Capability (NAQFC) project provides the US with operational and experimental real-time ozone predictions using two different versions of the three-dimensional Community Multi-scale Air Quality (CMAQ) modeling system. The Australian monsoon, which is dominant during the DJF period, causes warmer-than-average SST conditions in the northern part of Indonesia, particularly the northern part of the ITF. This cooling period intensifies during the JJA period and subsides in the SON period. Specifically, the SST conditions in the ITF region and southeast Indian Ocean cool from the MAM period. The results of this study generally show that geostrophic currents move to the east, and SST tends to be warmer during the Asian monsoon period than during the Australian monsoon period, which has a cooler SST (with geostrophic currents moving to the northwest). The results of the SST data verification show a 0.85☌ RMSE and 0.6☌ MAE they are significantly correlated at 0.82 with a 95% confidence level. Observational conductivity–temperature–depth (CTD) data obtained in December 2019 were used to identify statistical errors in the Copernicus Marine Service SST data. SST and geostrophic current data obtained from Copernicus Marine Service and surface wind speed and direction data from the European Center for Medium-Range Weather Forecasts (ECMWF) from March 2019 to February 2020 were statistically and descriptively analyzed. This study aims to determine the effect of these monsoons on the SSTs in the southeast Indian Ocean and the Indonesian throughflow (ITF) region. The differences in conditions occurring during these monsoon phenomena can affect sea surface temperatures (SSTs). Indonesia is influenced by two types of monsoons, namely, the Asian and Australian monsoons. ![]()
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