Impact of Observation Density of Next-Generation GeoHIS on Global Numerical Model Performance: A KIM-OSSE Study
Abstract
The geostationary hyperspectral infrared sounder (GeoHIS) provides atmospheric variables at high spatiotemporal resolution. Consequently, GeoHIS can provide valuable information for improving real-time forecasting and enhancing the performance of numerical weather prediction (NWP). GeoHIS provides higher temporal resolution than that of a polar-orbiting platform, observing the same region 2~3 times daily. Therefore, we assess the forecast impact of a next-generation GeoHIS on a numerical model according to observation density using KIM-OSSE (Korean Integrated Model–Observing System Simulation Experiment) in this study. Simulated observations are generated from the nature run dataset (ECO 1280) provided by Cooperative Institute for Research in the Atmosphere at Colorado State University (CIRA/CSU). These simulated observations are then assimilated into KIM, after which KIM generates forecast fields. Using this framework, we evaluated the impact of GeoHIS on a global numerical model. The results showed noticeable improvements in geopotential height, particularly in the mid- and upper troposphere, while wind, temperature, and humidity remain largely unchanged in EXP-1 and EXP-2. An analysis of the sensitivity to GeoHIS temporal resolution, by comparing hourly data and 3-hourly data, revealed that higher temporal resolution leads to greater forecast improvements.