|
|
基于葵花8号资料的风云四号A星海表温度产品交叉验证
|
Abstract:
风云四号A星是我国新一代静止轨道气象卫星的试验卫星，评估其海表温度产品的精度对海洋相关领域的研究和应用具有重要意义。以葵花8号海表温度产品为基准对2019年8月的风云四号A星海表温度产品进行了精度评价。研究结果表明：风云四号A星海表温度产品与葵花8号海表温度产品的时空分布比较一致，两者之间的平均偏差为0.23 K，平均绝对偏差和均方根误差分别为0.68 K和0.85 K。风云四号A星海表温度产品具有较高的精度，可以服务于气候监测和天气预报等研究领域。
Fengyun-4A (FY-4A) is the first satellite of China’s new generation geostationary meteorological sat-ellites, assessing the accuracy of the FY-4A sea surface temperature (SST) product is of great significance to the research and application in related fields of the ocean. In this paper, we evaluate the accuracy of the FY-4A SST product in August 2019 using the Himawari-8 SST product as a bench-mark. The results show that the retrieved FY-4A SST product has a comparable accuracy with the Himawari-8 SST product, with a bias, mean absolute error and root mean squared error of 0.23 K, 0.68 K and 0.85 K, respectively. FY-4A SST product with the high accuracy can be used in the research fields of climate monitoring and weather forecasting.
Fengyun-4A (FY-4A) is the first satellite of China’s new generation geostationary meteorological satellites, assessing the accuracy of the FY-4A sea surface temperature (SST) product is of great significance to the research and application in related fields of the ocean. In this paper, we evaluate the accuracy of the FY-4A SST product in August 2019 using the Himawari-8 SST product as a benchmark. The results show that the retrieved FY-4A SST product has a comparable accuracy with the Himawari-8 SST product, with a bias, mean absolute error and root mean squared error of 0.23 K, 0.68 K and 0.85 K, respectively. FY-4A SST product with the high accuracy can be used in the research fields of climate monitoring and weather forecasting.
| [1] | 何全军, 曹静, 陈翔, 张月维. 基于非线性算法的FY-3A/VIRR SST反演[J]. 气象, 2013, 39(1): 74-79. |
| [2] | Banzon, V., Smith, T.M., Chin, T.M., Liu, C. and Hankins, W. (2016) A Long-Term Record of Blended Satellite and in Situ Sea-Surface Temperature for Climate Monitoring, Modeling and Environmental Studies. Earth Sys-tem Science Data, 8, 165-176. https://doi.org/10.5194/essd-8-165-2016 |
| [3] | 郑贵洲, 熊良超, 廖艳雯, 王红平. 利用MODIS数据反演南海南部海表温度及时空变化分析[J]. 遥感技术与应用, 2020, 35(1): 132-140. |
| [4] | Walton, C.C., Pichel, W.G., Sapper, J.F. and May, D.A. (1998) The Development and Operational Ap-plication of Nonlinear Algorithms for the Measurement of Sea Surface Temperatures with the NOAA Polar-Orbiting En-vironmental Satellites. Journal of Geophysical Research: Oceans, 103, 27999-28012. https://doi.org/10.1029/98JC02370 |
| [5] | 杨航, 王素娟, 刘铭坤, 管磊. FY-3C/VIRR西北太平洋区域海表温度精度评估[J]. 中国海洋大学学报(自然科学版), 2020, 50(12): 151-159. https://doi.org/10.16441/j.cnki.hdxb.20180419 |
| [6] | 奚萌. 基于最优插值算法的红外和微波遥感海表温度数据融合[D]: [硕士学位论文]. 北京: 国家海洋环境预报研究中心, 2011. |
| [7] | 何锡玉, 蔡夕方, 朱亚平, 张雷. 我国风云极轨气象卫星及应用进展[J]. 气象科技进展, 2021, 11(1): 34-39. |
| [8] | 门聪. 海洋一号B卫星海洋水色扫描仪(HY-1B/COCTS)海表温度反演与印证[D]: [硕士学位论文]. 青岛: 中国海洋大学, 2013. |
| [9] | Kilpatrick, K.A., et al. (2015) A Decade of Sea Surface Temperature from MODIS. Remote Sensing of Environment, 165, 27-41. https://doi.org/10.1016/j.rse.2015.04.023 |
| [10] | 耿晓雯, 闵锦忠, 杨春, 王元兵, 许冬梅. FY-4A AGRI辐射率资料偏差特征分析及订正试验[J]. 大气科学, 2020, 44(4): 679-694. |
| [11] | 崔鹏, 王素娟, 陆风, 肖萌. FY-4A/AGRI海表温度产品和质量检验[J]. 应用气象学报, 2023, 34(3): 257-269. |
| [12] | 王素娟, 陆风, 张鹏, 张晓虎, 崔鹏, 王维和. FY2海面温度产品质量检验方法与误差分析[J]. 气象, 2013, 39(10): 1331-1336. |
| [13] | 王素娟, 崔鹏, 张鹏, 冉茂农, 陆风, 王维和. FY-3B/VIRR海表温度算法改进及精度评估[J]. 应用气象学报, 2014, 25(6): 701-710. |
| [14] | Tu, Q. and Hao, Z. (2020) Validation of Sea Surface Temperature Derived from Himawari-8 by JAXA. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 448-459.
https://doi.org/10.1109/JSTARS.2019.2963773 |
| [15] | Kurihara, Y., Murakami, H. and Kachi, M. (2016) Sea Sur-face Temperature from the New Japanese Geostationary Meteorological Himawari-8 Satellite. Geophysical Research Let-ters, 43, 1234-1240. (In English)
https://doi.org/10.1002/2015GL067159 |
| [16] | Duan, S.-B., et al. (2019) Validation of Collection 6 MODIS Land Surface Temperature Product Using in Situ Measurements. Remote Sensing of Environment, 225, 16-29. https://doi.org/10.1016/j.rse.2019.02.020 |
| [17] | Yang, M., Guan, L., Beggs, H., Morgan, N., Kurihara, Y. and Ka-chi, M. (2020) Comparison of Himawari-8 AHI SST with Shipboard Skin SST Measurements in the Australian Region. Remote Sensing, 12, 1237.
https://doi.org/10.3390/rs12081237 |
| [18] | Luo, B., Minnett, P.J. and Nalli, N.R. (2021) Infrared Satellite-Derived Sea Surface Skin Temperature Sensitivity to Aerosol Vertical Distribution—Field Data Analysis and Model Simulations. Remote Sensing of Environment, 252, Article ID: 112151. https://doi.org/10.1016/j.rse.2020.112151 |
| [19] | Xi, X., Ignatov, A. and Zhou, X. (2019) Exploring MERRA-2 Global Meteorological and Aerosol Reanalyses for Improved SST Retrieval. Remote Sensing of Environment, 223, 1-7. https://doi.org/10.1016/j.rse.2019.01.011 |
| [20] | Woo, H.-J., Park, K.-A., Li, X. and Lee, E.-Y. (2018) Sea Surface Temperature Retrieval from the First Korean Geostationary Satellite COMS Data: Validation and Error Assessment. Remote Sensing, 10, Article No. 1916.
https://doi.org/10.3390/rs10121916 |
