Engineering topics

Wargan, K.

Publications and source records attributed to Wargan, K..

22 records · Page 2

NASA NTRS2003

Comparison of Flow-Dependent and Static Error Correlation Models in the DAO Ozone Data Assimilation System

In a data assimilation system the forecast error covariance matrix governs the way in which the data information is spread throughout the model grid. Implementation of a correct method of assigning covariances is expected to have an impact on the analysis results. The simplest models assume that correlations are constant in time and isotropic or nearly isotropic. In such models the analysis depends on the dynamics only through assumed error standard deviations. In applications to atmospheric tracer data assimilation this may lead to inaccuracies, especially in regions with strong wind shears or high gradient of potential vorticity, as well as in areas where no data are available. In order to overcome this problem we have developed a flow-dependent covariance model that is based on short term evolution of error correlations. The presentation compares performance of a static and a flow-dependent model applied to a global three- dimensional ozone data assimilation system developed at NASA s Data Assimilation Office. We will present some results of validation against WMO balloon-borne sondes and the Polar Ozone and Aerosol Measurement (POAM) III instrument. Experiments show that allowing forecast error correlations to evolve with the flow results in positive impact on assimilated ozone within the regions where data were not assimilated, particularly at high latitudes in both hemispheres and in the troposphere. We will also discuss statistical characteristics of both models; in particular we will argue that including evolution of error correlations leads to stronger internal consistency of a data assimilation ,

Wargan, K.↗

NASA NTRS2003

Impact of Flow-Dependent Error Correlations and Tropospheric Chemistry on Assimilated Ozone

The presentation compares different versions of a global three-dimensional ozone data assimilation system developed at NASA's Data Assimilation Office. The Solar Backscatter Ultraviolet/2 (SBUV/2) total and partial ozone column retrievals are the sole data assimilated in all of the experiments presented. We study the impact of changing the forecast error covariance model from a version assuming static correlations with a one that captures a short-term Lagrangian evolution of those correlations. This is further combined with a study of the impact of neglecting the tropospheric ozone production, loss and dry deposition rates, which are obtained from the Harvard GEOS-CHEM model. We compare statistical characteristics of the assimilated data and the results of validation against independent observations, obtained from WMO balloon-borne sondes and the Polar Ozone and Aerosol Measurement (POAM) III instrument. Experiments show that allowing forecast error correlations to evolve with the flow results in positive impact on assimilated ozone within the regions where data were not assimilated, particularly at high latitudes in both hemispheres. On the other hand, the main sensitivity to tropospheric chemistry is in the Tropics and sub-Tropics. The best agreement between the assimilated ozone and the in-situ sonde data is in the experiment using both flow-dependent error covariances and tropospheric chemistry.

Wargan, K.↗

NASA NTRS2003

Monitoring and Assimilation of MIPAS and SCIAMACHY Ozone Data

Preliminary results are presented from experiments that integrate ozone observations from two ENVISAT-borne instruments with the ozone data assimilation system developed at NASA's Data Assimilation Office (DAO). The data used are ozone total column provided by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) and stratospheric profiles from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument. The DAO's existing system sequentially assimilates the Solar Backscatter Ultraviolet/2 total and partial ozone column data. Incorporation of SCIAMACHY and MIPAS data is done in two stages. First, the observations are monitored. The monitoring consists of computing the differences between Envisat observations and the ozone system forecast, i.e. observed-minus-forecast (O-F) residuals. The O-F residuals are then analyzed using simple statistical methods to examine the spatial distribution of differences, which are large for SCIAMACHY near the terminator. In the second stage, the MIPAS data will be actively assimilated along with the SBW/2 observations; any preliminary results of note will be discussed.

Wargan, K.↗

NASA NTRS2003

Assimilation of Satellite Ozone Observations

This talk will discuss assimilation of ozone data from satellite-borne instruments. Satellite observations of ozone total columns and profiles have been measured by a series of Total Ozone Mapping Spectrometer (TOMS), Solar Backscatter Ultraviolet (SBUV) instruments, and more recently by the Global Ozone Monitoring Experiment. Additional profile data are provided by instruments on NASA's Upper Atmosphere Research Satellite and by occultation instruments on other platforms. Instruments on Envisat' and future EOS Aura satellite will supply even more comprehensive data about the ozone distribution. Satellite data contain a wealth of information, but they do not provide synoptic global maps of ozone fields. These maps can be obtained through assimilation of satellite data into global chemistry and transport models. In the ozone system at NASA's Data Assimilation Office (DAO) any combination of TOMS, SBUV, and Microwave Limb sounder (MLS) data can be assimilated. We found that the addition of MLS to SBUV and TOMS data in the system helps to constrain the ozone distribution, especially in the polar night region and in the tropics. The assimilated ozone distribution in the troposphere and lower stratosphere is sensitive also to finer changes in the SBUV and TOMS data selection and to changes in error covariance models. All results are established by comparisons of assimilated ozone with independent profiles from ozone sondes and occultation instruments.

Stajner, I.↗