Introduction of the GSI into the NCEP Global Data Assimilation System

Abstract

At the National Centers for Environmental Prediction (NCEP), a new three-dimensional variational data assimilation (3DVAR) analysis system was implemented into the operational Global Data Assimilation System (GDAS) on 1 May 2007. The new analysis system, the Gridpoint Statistical Interpolation (GSI), replaced the Spectral Statistical Interpolation (SSI) 3DVAR system, which had been operational since 1991. The GSI was developed at the Environmental Modeling Center at NCEP as part of an effort to create a more unified, robust, and efficient analysis scheme. The key aspect of the GSI is that it formulates the analysis in model grid space, which allows for more flexibility in the application of the background error covariances and makes it straightforward for a single analysis system to be used across a broad range of applications, including both global and regional modeling systems and domains.Due to the constraints of working with an operational system, the final GDAS package included many changes other than just a simple replacing of the SSI with the new GSI. The new GDAS package contained an upgrade to the Global Forecast System model, including a new vertical coordinate, as well as new features in the GSI that were never developed for the SSI. Some of these new features included changes to the observation selection, quality control, minimization algorithm, dynamic balance constraint, and assimilation of new observation types. The evaluation of the new system relative to the SSI-based system was performed for nearly an entire year of analyses and forecasts. The objective and subjective evaluations showed that the new package exhibited superior forecast performance relative to the old SSI-based system. The new system has been shown to improve forecast skill in the tropics and substantially reduce the short-term forecast error in the extratropics. This implementation has laid the groundwork for future scientific advancements in data assimilation at NCEP.

Advanced infrared sounder subpixel cloud detection with imagers and its impact on radiance assimilation in NWP

“…It was developed by the National Centers for Environmental Prediction (NCEP) as a next-generation analysis system based on the operational Spectral Statistical Interpolation analysis system. DTC transitioned the operational GSI system into a community system that is widely used in the research environment [Kleist et al, 2009;Ma et al, 2011]. The system is capable of assimilating various kinds of observations: from surface to upper air to radar to satellite observations.…”

Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models

“…The Gridpoint Statistical Interpolation (GSI) system (Kleist et al, 2009), which uses a 3D-Var approach, is applied here to perform data assimilation experiments using satellite data to improve the initial aerosol state for the WRF-Chem (Grell et al, 2005) model when utilizing the MOSAIC aerosol model (Zaveri et al, 2008). We present two case studies, which correspond to the use of AOD (Saide et al, 2013) and cloud number droplet satellite retrievals (N d ) (Saide et al, 2012a).…”

Linear and non-linear response to parameter variations in a mesoscale model

“…In GEFS, an ensemble transform rescales perturbations every 6 h, and recentres them on NCEP's operational deterministic analysis given by the NCEP Gridpoint Statistical Interpolation [GSI; Kleist et al (2009)] 3-D variational data assimilation scheme. A new set of perturbations are computed every 6 h, and each is rescaled according to the analysis error variance as specified in the GSI.…”