All‐sky microwave humidity sounder assimilation in the Korean Integrated Model forecast system

Abstract

The Korean Integrated Model (KIM) and hybrid data assimilation system were extended to assimilate all‐sky radiance from microwave satellite sensors. Initially, a radiative transfer model for the TIROS Operational Vertical Sounder (TOVS), called RTTOV‐SCATT (version 11.3), was implemented to assimilate the Microwave Humidity Sounder (MHS) 183 GHz channels over the ocean. Cloud and precipitation parameters are not directly assimilated into our system, but temperature and humidity profiles are improved in the all‐sky assimilation. In the cycled analysis and forecast experiments, an assimilation of the MHS in a cloudy region shows globally substantial benefits: the coverage of the MHS radiance data is increased by 23–28% in the all‐sky assimilation. It is demonstrated that RTTOV‐SCATT well describes the brightness temperature (TB) on selected cloudy pixels over the Tropics and the Southern Hemisphere, with potential for linking the TB innovation to the increment for the hydrometeor variable. As a result, a reduction of 1.11% in the specific humidity root‐mean‐square error occurs in the 6‐hr forecast field as compared to the European Centre for Medium‐Range Weather Forecasts (ECMWF)'s Integrated Forecasting System (IFS) analysis. Even though the all‐sky MHS assimilation's impact on the Northern Hemisphere midlatitudes is not remarkable, it nonetheless produces an improved humidity analysis increment for a heavy rainfall case over East Asia.

Assimilating Sentinel‐3 All‐Sky PWV Retrievals to Improve the WRF Forecasting Performance Over the South China

“…In our study, the retrieved water vapor data (i.e., PWV) are assimilated. Second, the water vapor radiance data used in most previous work are from IR or microwave channels (S. Lee et al, 2020;Y. Li et al, 2021;Xian et al, 2019).…”

“…To introduce valuable external information over the cloudy regions, all‐sky microwave radiance data have been routinely assimilated by several operational centers, such as the European Centre for Medium‐range Weather Forecasts (Bauer et al., 2010; Geer et al., 2014) and the National Centers for Environmental Prediction (NCEP) (Zhu et al., 2014). Many recent studies have assimilated all‐sky microwave water vapor radiance to improve NWP performance for different weather conditions (Lawrence et al., 2018; S. Lee et al., 2020; Y. Li et al., 2021; Xian et al., 2019). These studies generally showed that assimilation of all‐sky microwave water vapor radiance can generate better forecasting results, for example, higher rainfall forecast skill scores, better humidity forecasting fields, and more accurate forecast of tropical cyclone intensity and trajectory track.…”

“…To introduce valuable external information over the cloudy regions, all-sky microwave radiance data have been routinely assimilated by several operational centers, such as the European Centre for Medium-range Weather Forecasts (Bauer et al, 2010;Geer et al, 2014) and the National Centers for Environmental Prediction (NCEP) (Zhu et al, 2014). Many recent studies have assimilated all-sky microwave water vapor radiance to improve NWP performance for different weather conditions (Lawrence et al, 2018;S. Lee et al, 2020;Y.…”

All‐sky infrared radiance assimilation of a geostationary satellite in the Japan Meteorological Agency's global system

“…Finally, the development and operational implementation of ASR assimilation are involved with close comparison of ASR observations and simulation, helping to understand and improve the physical processes of forecast models. Similar benefits have already been proved in microwave (MW) ASR assimilation that are more developed and already implemented in operational centers (Zhu et al ., 2016; Kazumori and Kadowaki, 2017; Geer et al ., 2017a; Migliorini and Candy, 2019; Lee et al ., 2020).…”

The Potential Value of Combining Assimilation of Water Vapor Radiances and Cloud Liquid/Ice Water Path From ABI on Analyses and Forecasts for Hurricane Irma (2017)

“…Beyond the typical difficulties shared by the direct assimilation of radiances, such as large uncertainties and biases in the Radiative Transfer Model for cloud absorption and scattering (Li et al., 2016; Okamoto, 2017), the inconsistency between the simulated hydrometeors and observations (Barlakas et al., 2021), and high nonlinearity for the cloudy radiance (Errico et al., 2007), direct assimilation of cloud‐affected IR, near‐IR, and VIS radiances suffers from the significant challenge of the high sensitivity of Jacobian to clouds (Li et al., 2016; Vidot et al., 2015). In addition, most of the channels currently used for IR imager all‐sky assimilation are water vapor channels, making the thermodynamic information updated but not the cloud due to the lack of direct observations (e.g., Candy & Migliorini, 2021; Geer et al., 2019; Lee et al., 2020; Shahabadi & Buehner, 2021; Xian et al., 2019; Zhang et al., 2016).…”