Are the Cloud-Top Heights Retrieved From GOES-16/ABI and GOES-17/ABI Consistent?
- 15 July 2024
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Geoscience and Remote Sensing
- Vol. 62 (01962892) , 1-9
Abstract
The United States geostationary operational environmental satellites GOES-16 and GOES-17 provide cloud-top height (CTH) data. A fusion model combining their CTH is vital for global high-resolution weather forecasting and climate analysis. However, ensuring a high degree of consistency between CTH from GOES-16 and GOES-17 is essential for building an effective CTH fusion model. In this paper, a consistency analysis was conducted on the CTH in regions where GOES-16/ABI and GOES-17/ABI observations overlap. Results show that the CTH of GOES-16 and GOES-17 exhibits a small mean error (ME) and high correlation, but between 9:30 and 15:00 (UTC), the ME, standard deviation (Std), and root mean square error (RMSE) are significantly larger than those during other periods, with the maximum values occurring between approximately 12:00 and 14:00. The difference in Satellite viewing zenith angle (ΔVZA) at the same observation pixel had an impact on the CTH consistency. The larger ΔVZA is, the larger ME, Std, and RMSE are; The increase in ME of between the two CTH from 9:30 to 15:00 was related to the difference in radiance of the 12.3μm and 13.3μm channel, while the increase in Std was related to the difference in radiance of the 13.3μm. It is due to anomalies in the channel radiance observations caused by the degradation of the imager's performance by solar radiation exposure during this period. The fusion of GOES-16 and GOES-17 CTH data needs to take into consideration the differences in VZA and the data quality control between 9:30 and 15:00.Keywords
Funding Information
- National Natural Science Foundation of China (41575020)
This publication has 37 references indexed in Scilit:
- Diurnal time representation of MODIS, VIIRS, MISR, and AHI over Asia and OceaniaRemote Sensing of Environment, 2023
- Retrieval of total and fine mode aerosol optical depth by an improved MODIS Dark Target algorithmEnvironment International, 2022
- Cloud identification and property retrieval from Himawari-8 infrared measurements via a deep neural networkRemote Sensing of Environment, 2022
- The incidence and magnitude of the hot-spot bidirectional reflectance distribution function (BRDF) signature in GOES-16 Advanced Baseline Imager (ABI) 10 and 15 minute reflectance over north AmericaRemote Sensing of Environment, 2021
- Cloudy-sky land surface temperature from VIIRS and MODIS satellite data using a surface energy balance-based methodRemote Sensing of Environment, 2021
- GOES-16 ABI solar reflective channel validation for earth science applicationRemote Sensing of Environment, 2020
- ABI Cloud Products from the GOES-R Series2020
- Evaluation of Cloud Top Height Retrievals from China’s Next-Generation Geostationary Meteorological Satellite FY-4AJournal of Meteorological Research, 2019
- Radiative effect differences between multi-layered and single-layer clouds derived from CERES, CALIPSO, and CloudSat dataJournal of Quantitative Spectroscopy and Radiative Transfer, 2011
- Comparison of cloud-top height retrievals from ground-based 35 GHz MMCR and GMS-5 satellite observations at ARM TWP Manus siteAtmospheric Research, 2004