David J. Lamich

Assessing the Effects of Data Selection with the DAO Physical-Space Statistical Analysis System*

Conventional optimal interpolation (OI) analysis systems solve the standard statistical analysis equations approximately, by invoking a local approximation and a data selection procedure. Although solution of the analysis equations is essentially exact in the recent generation of global spectral variational analysis systems, these new systems also include substantial changes in error covariance modeling, making it difficult to discern whether improvements in analysis and forecast quality are due to exact, global solution of the analysis equations, or to changes in error covariance modeling. The formulation and implementation of a new type of global analysis system at the Data Assimilation Office, termed the Physical-space Statistical Analysis System (PSAS), is described in this article. Since this system operates directly in physical space, it is capable of employing error covariance models identical to those of the predecessor OI system, as well as more advanced models. To focus strictly on the effect of global versus local solution of the analysis equations, a comparison between PSAS and OI analyses is carried out with both systems using identical error covariance models and identical data. Spectral decomposition of the analysis increments reveals that, relative to the PSAS increments, the OI increments have too little power at large horizontal scales and excessive power at small horizontal scales. The OI increments also display an unrealistically large ratio of divergence to vorticity. Dynamical imbalances in the OI-analyzed state can therefore be attributed in part to the approximate local method of solution, and are not entirely due to the simple geostrophic constraint built into the forecast error covariance model. Root-mean-square observation minus 6-h forecast errors in the zonal wind component are substantially smaller for the PSAS system than for the OI system.

The use of assimilated stratospheric data in constituent transport calculations

Abstract Analysis of atmospheric data by assimilation of height and wind measurements into a general circulation model is routine in tropospheric analysis and numerical weather prediction. A stratospheric assimilation system has been developed at NASA/Goddard Space Flight Center. This unique system generates wind data that is consistent with the geopotential height (and temperature) field and the primitive equations in the general circulation model. These wind fields should offer a significant improvement over the geostrophic analysis normally used in the stratosphere. This paper reports the first known calculations to use data from an assimilation to calculate constituent transport in the stratosphere. Nitric acid (NHO3) during the LIMS period is studied. While there are still significant discrepancies between the calculated and observed HNO3, there are some remarkable successes. Particularly, the high-latitude time variance of the HNO3 is accurately captured. These studies suggest that data from an assi...

Parallel Computing at the NASA Data Assimilation Office (DAO)

The goal of atmospheric data assimilation is to produce accurate gridded datasets of fields by assimilating a range of observations along with physically consistent model forecasts. The NASA Data Assimilation Office (DAO) is currently upgrading its end-to-end data assimilation system (GEOS DAS) to support NASAs Mission To Planet Earth (MTPE) Enterprise. This effort is also part of a NASA HPCC Earth and Space Sciences (ESS) Grand Challenge PI project. Future Core computing, using a modular Fortran 90 design and distributed memory (MPI) software, will be carried out at Ames Research Center. The algorithmic and performance issues involved in the Core system are the main subjects of this presentation.

The minor stratospheric warming of January 1989 - Results from STRATAN, a stratospheric-tropospheric data assimilation system

Abstract Using a stratospheric-tropospheric data assimilation system, referred to as STRATAN, a minor sudden stratospheric warming that occurred in January 1989 is investigated. The event had a maximum influence on the stratospheric circulation near 2 hPa. The zonal mean circulation reversed briefly in the polar region as the temperature increased 34 K in 3 days. The cause of the warming is shown to be the rapid development and subsequent movement of a warm anomaly, which initially developed in the midlatitudes. The development of the warm anomaly is caused by adiabatic descent, and the dissipation by radiative cooling. A brief comparison with the NMC analysis and temperature sounding data is also presented.