[M-GI29] Data assimilation: A fundamental approach in geosciences

[MGI29-02] EFSO at different geographical locations verified with observing-system experiments

★Invited Papers

*Akira Yamazaki¹, Takemasa Miyoshi^2,1, Jun Inoue⁴, Takeshi Enomoto^3,1, Nobumasa Komori¹ (1.Application Laboratory, Japan Agency for Marine-Earth Science and Technology, 2.RIKEN, 3.Kyoto University, 4.National Institute of Polar Research)

An EFSO (ensemble forecast sensitivity to observations) diagnosis has been implemented in an atmospheric general circulation model (AFES) and an ensemble Kalman filter (LETKF) data assimilation system to estimate the impacts of specific observations from the quasi-operational global observing system on weekly short-range forecasts. Observing system experiments (OSEs) are commonly used for evaluating the impact of observations on data assimilation systems. In previous work, we have conducted many OSEs using in-house developed data assimilation system known as the AFES-LETKF data assimilation system. So far, there studies have focused on the remote influences of small subsets of observations obtained during field campaigns. However, conducting OSEs during a campaign is not very practical because they are too expensive in computational resources and time, as additional data assimilation and forecast cycles must be performed to evaluate specific observations. Alternatively, the EFSO technique allows to diagnose, without conducting OSEs, the impacts of all observations by quantifying the extent to which each observation improves or degrades subsequent forecasts typically within short ranges. Our purpose is to understand how well EFSO can estimate actual observation impacts obtained by OSEs of individual observations and their downstream influence during short-to-medium range forecasts. Initially, we interpreted physically "observation impact" which is estimated by EFSO or an OSE. In the next, it was examined whether EFSO reasonably approximates the impacts of a subset of observations from specific geographical locations for 6-hour forecasts, and how long the 6-hour observation impacts can be retained during the 7-day forecast period. The reference for these forecasts was obtained from 12 data denial experiments in each of which a subset of three radiosonde observations launched from a geographical location was excluded. The 12 locations were selected from three latitudinal bands comprising (i) four Arctic regions, (ii) four midlatitude regions in the Northern Hemisphere, and (iii) four tropical regions during the Northern Hemisphere winter of 2015/16. The estimated winter-averaged EFSO-derived observation impacts well corresponded to the 6-hour observation impacts obtained by the data denials and EFSO could reasonably estimate the observation impacts by the data denials on short-range (6-hour to 2-day) forecasts. Furthermore, during the medium-range (4-day to 7-day) forecasts, it was found that the Arctic observations tend to seed the broadest impacts and their short-range observation impacts could be projected to beneficial impacts in Arctic and midlatitude North American areas. The midlatitude area located just downstream of dynamical propagation from the Arctic toward the midlatitudes.