An ensemble Kalman filter data assimilation system for the whole neutral atmosphere

Abstract

Abstract. A data assimilation system with a four-dimensional local ensemble transform Kalman filter (4D-LETKF) is developed to make a new analysis data for the atmosphere up to the lower thermosphere using the Japanese Atmospherics General Circulation model for Upper Atmosphere Research. The time period from 10 January 2017 to 20 February 2017, when an international radar network observation campaign was performed, is focused on. The model resolution is T42L124 which can resolve phenomena at synoptic and larger scales. A conventional observation dataset provided by National Centers for Environmental Prediction, PREPBUFR, and satellite temperature data from the Aura Microwave Limb Sounder (MLS) for the stratosphere and mesosphere are assimilated. First, the performance of the forecast model is improved by modifying the vertical profile of the horizontal diffusion coefficient and modifying the source intensity in the non-orographic gravity wave parameterization, by comparing it with radar wind observations in the mesosphere. Second, the MLS observational bias is estimated as a function of the month and latitude and removed before the data assimilation. Third, data assimilation parameters, such as the degree of gross error check, localization length, inflation factor, and assimilation window are optimized based on a series of sensitivity tests. The effect of increasing the ensemble member size is also examined. The obtained global data are evaluated by comparison with the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) reanalysis data covering pressure levels up to 0.1 hPa and by the radar mesospheric observations which are not assimilated.

Formation of a Mesospheric Inversion Layer and the Subsequent Elevated Stratopause Associated With the Major Stratospheric Sudden Warming in 2018/19

“…Thus, it is considered that the model used in this study could also reproduce a major part of GWs in the middle atmosphere, but over a wider horizontal wavelength range than the KANTO model. Koshin et al (2020) recently developed a four-dimensional local ensemble transform Kalman filter (4D-LET-KF) assimilation system in a medium-resolution (T42L124, a latitudinal interval of 2.8125°) version of the JAGUAR, which called Japanese Atmospheric GCM for Upper Atmosphere Research-Data Assimilation System; JAGUAR-DAS. They assimilated the PrepBUFR observational data set provided by the National Centers for Environmental Prediction (NCEP), including temperature, wind, humidity, and surface pressure from radiosondes, aircrafts, wind profilers, and satellites, and satellite temperature data from the Aura Microwave Limb Sounder (MLS).…”

Intercomparison of middle atmospheric meteorological analyses for the Northern Hemisphere winter 2009–2010

“…It is cooperatively developed by the Japan Agency for Marine-Earth Science and Technology (JAM-STEC), the Kyushu University, and the University of Tokyo based on the Model for Interdisciplinary Research on Cli-mate (MIROC) and the Kyushu-GCM (general circulation model; Watanabe and Miyahara, 2009). A full set of physical parameterizations necessary to simulate altitudes from the surface to ∼ 150 km is included, as described in Koshin et al (2020). The JAGUAR model generates short-term forecasts that are used as background fields for the data assimilation system (JAGUAR-DAS), which employs a four-dimensional local ensemble transform Kalman filter (4D-LETKF) developed by Miyoshi and Yamane (2007).…”

“…As the uppermost layers are taken as a sponge layer, only data below ∼ 105 km altitude are usable for dynamical analysis. Following Koshin et al (2020), the JAGUAR-DAS output used in the present study assimilates the standard National Centers for Environmental Prediction (NCEP) PREPBUFR dataset for the troposphere and lower stratosphere. For the stratosphere, mesosphere, and lower thermosphere, JAGUAR-DAS assimilates bias-corrected MLS temperature retrievals from 100 to 0.002 hPa (∼ 16 to 90 km altitude).…”

“…To address the emerging need for accurate global atmospheric analyses throughout the entire middle atmosphere, high-altitude data assimilation and modeling systems (e.g., Pedatella et al, 2014b;McCormack et al, 2017;Koshin et al, 2020) have been developed recently to provide observation-based constraints of middle atmospheric meteorological variability for whole atmosphere models (Sassi et al, 2018;McDonald et al, 2018;Pedatella et al, 2019). These systems produce global meteorological analyses by incorporating both standard operational meteorological observations near the surface and satellite-based observations of the middle atmosphere from dedicated NASA research missions such as Aura (Schoeberl et al, 2006) and TIMED (Thermosphere-Ionosphere-Mesosphere Energetics and Dynamics; Yee et al, 1999).…”

“…This paper presents the first intercomparison of four analyses extending into the middle atmosphere: the highaltitude version of the Navy Global Environmental Model (NAVGEM-HA; Eckermann et al, 2018), the Whole At-mosphere Community Climate Model with thermosphereionosphere eXtension using the Data Assimilation Research Testbed (WACCMX+DART; Pedatella et al, 2018), the Japanese Atmospheric General circulation model for Upper Atmosphere Research with Data Assimilation System (JAGUAR-DAS; Koshin et al, 2020;, and MERRA-2. Each of these systems assimilates middle atmosphere data to varying degrees, with top output levels ranging from 80 to ∼ 500 km altitude.…”