Spatio-Temporal Variations of Aerosol Optical Depth over Areas Around Beijing in Recent 14 Years

2014 ◽  
Vol 997 ◽  
pp. 843-846 ◽  
Author(s):  
Hao Liu ◽  
Xin Ming Tang ◽  
Wei Cao ◽  
Zhi Ying Xie ◽  
Jing Han Lei ◽  
...  

Based on the monthly data of MODIS Level 3, the spatio-temporal variabilities of Aerosol Optical Depth (AOD) over areas around Beijing have been analyzed from March 2000 to December 2013. The results presented that: (1) In the past 14 years , the annual mean AODs vary between 0.428 and 0.550; The recent 14 years can be divided into two stages, the first stage is 2000-2007, which shows an increasing trend with an increase rate of 1.349%, while the second stage is 2008-2013, which shows an decreasing trend with a decrease rate of 1.483%; Summer has the maximum AOD, but shows a decreasing trend, while winter has the minimum AOD, but shows an increasing trend. (2) AODs over the south are higher than the north, high AODs are mainly distributed along the southwest of Hebei and southwest of Shandong with an AOD of 0.72, while low AODs are mainly distributed along the north of Hebei and the north of Shanxi with an AOD of 0.23; The spatial distribution of AOD varies with the seasons, AODs are high in spring, and are maximized in summer, then show a significant decrease from summer to autumn, while are minimized in winter.

2019 ◽  
Vol 248 ◽  
pp. 526-535 ◽  
Author(s):  
Qianqian Yang ◽  
Qiangqiang Yuan ◽  
Linwei Yue ◽  
Tongwen Li ◽  
Huanfeng Shen ◽  
...  

2020 ◽  
Vol 12 (14) ◽  
pp. 2256
Author(s):  
Sang Seo Park ◽  
Sang-Woo Kim ◽  
Chang-Keun Song ◽  
Jong-Uk Park ◽  
Kang-Ho Bae

In this study, the spatio-temporal variability of aerosol optical depth (AOD), total column ozone (TCO), and total column NO2 (TCN) was identified over East Asia using long-term datasets from ground-based and satellite observations. Based on the statistical results, optimized spatio-temporal ranges for the validation study were determined with respect to the target materials. To determine both spatial and temporal ranges for the validation study, we confirmed that the observed datasets can be statistically considered as the same quantity within the ranges. Based on the thresholds of R2>0.95 (temporal) and R>0.95 (spatial), the basic ranges for spatial and temporal scales for AOD validation was within 30 km and 30 min, respectively. Furthermore, the spatial scales for AOD validation showed seasonal variation, which expanded the range to 40 km in summer and autumn. Because of the seasonal change of latitudinal gradient of the TCO, the seasonal variation of the north-south range is a considerable point. For the TCO validation, the north-south range is varied from 0.87° in spring to 1.05° in summer. The spatio-temporal range for TCN validation was 20 min (temporal) and 20–50 km (spatial). However, the nearest value of satellite data was used in the validation because the spatio-temporal variation of TCN is large in summer and autumn. Estimation of the spatio-temporal variability for respective pollutants may contribute to improving the validation of satellite products.


2021 ◽  
Vol 13 (4) ◽  
pp. 622
Author(s):  
Wan-Ru Huang ◽  
Pin-Yi Liu ◽  
Ya-Hui Chang ◽  
Cheng-An Lee

This study assesses the performance of satellite precipitation products (SPPs) from the latest version, V06B, Integrated Multi-satellitE Retrievals for Global Precipitation Mission (IMERG) Level-3 (including early, late, and final runs), in depicting the characteristics of typhoon season (July to October) rainfall over Taiwan within the period of 2000–2018. The early and late runs are near-real-time SPPs, while final run is post-real-time SPP adjusted by monthly rain gauge data. The latency of early, late, and final runs is approximately 4 h, 14 h, and 3.5 months, respectively, after the observation. Analyses focus on the seasonal mean, daily variation, and interannual variation of typhoon-related (TC) and non-typhoon-related (non-TC) rainfall. Using local rain-gauge observations as a reference for evaluation, our results show that all IMERG products capture the spatio-temporal variations of TC rainfall better than those of non-TC rainfall. Among SPPs, the final run performs better than the late run, which is slightly better than the early run for most of the features assessed for both TC and non-TC rainfall. Despite these differences, all IMERG products outperform the frequently used Tropical Rainfall Measuring Mission 3B42 v7 (TRMM7) for the illustration of the spatio-temporal characteristics of TC rainfall in Taiwan. In contrast, for the non-TC rainfall, the final run performs notably better relative to TRMM7, while the early and late runs showed only slight improvement. These findings highlight the advantages and disadvantages of using IMERG products for studying or monitoring typhoon season rainfall in Taiwan.


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